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Table of Contents 

APPENDIX A – MAJOR LEGAL AUTHORITIES ..................................................................................................... 1091

APPENDIX B – MANAGEMENT OBJECTIVES AND DIRECTION ............................................................................ 1097

APPENDIX C – VEGETATION MODELING ........................................................................................................... 1163

APPENDIX D – MODELING LARGE STOCHASTIC WILDFIRES AND FIRE SEVERITY WITHIN THE RANGE OF THE 

NORTHERN SPOTTED OWL ............................................................................................................................... 1229

APPENDIX E – AIR QUALITY .............................................................................................................................. 1245

APPENDIX F – AREAS OF CRITICAL ENVIRONMENTAL CONCERN ...................................................................... 1249

APPENDIX G – CLIMATE CHANGE ..................................................................................................................... 1295

APPENDIX H – FIRE AND FUELS ........................................................................................................................ 1305

APPENDIX I – FISHERIES ................................................................................................................................... 1333

APPENDIX J – BEST MANAGEMENT PRACTICES ................................................................................................ 1345

APPENDIX K – LANDS AND REALTY .................................................................................................................. 1389

APPENDIX L – LIVESTOCK GRAZING .................................................................................................................. 1435

APPENDIX M – ENERGY AND MINERALS .......................................................................................................... 1447

APPENDIX N – RARE PLANTS AND FUNGI ......................................................................................................... 1463

APPENDIX O – RECREATION ............................................................................................................................. 1489

APPENDIX P – SOCIOECONOMICS .................................................................................................................... 1505

APPENDIX Q – PUBLIC MOTORIZED ACCESS DESIGNATION GUIDELINES .......................................................... 1589

APPENDIX R – TRIBAL ...................................................................................................................................... 1613

APPENDIX S – OTHER WILDLIFE ........................................................................................................................ 1651

APPENDIX T – NORTHERN SPOTTED OWL ........................................................................................................ 1737

APPENDIX U – WILD AND SCENIC RIVER SUITABILITY REPORT SUMMARY ....................................................... 1793

APPENDIX V – MONITORING PLAN FOR THE PROPOSED RMPS ........................................................................ 1807

APPENDIX W – RESPONSES TO COMMENTS ..................................................................................................... 1833

APPENDIX X – GUIDANCE FOR USE OF THE COMPLETED RMPS ........................................................................ 1997
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Table of Figures 

FIGURE C-1. CVS PRIMARY SAMPLE UNIT DESIGN ..................................................................................................1167

FIGURE C-2. CVS PLOT LOCATIONS AND FOI UNITS ................................................................................................1168

FIGURE C-3. GRADIENT OF SILVICULTURAL SYSTEMS AND REGENERATION HARVEST METHODS .........................1184

FIGURE C-4. STAND STRUCTURAL TYPES PRODUCED BY VARIOUS SILVICULTURAL SYSTEMS ................................1184

FIGURE C-5. CLEARCUT STAND IMMEDIATELY POST-HARVEST ...............................................................................1187

FIGURE C-6. VARIABLE RETENTION (REGENERATION) HARVEST-IDEALIZED RETENTION PATTERNS ......................1188

FIGURE C-7. UNEVEN-AGED MANAGEMENT/SELECTION HARVEST – IDEALIZED HARVEST PATTERNS ..................1189

FIGURE C-8. NON-DECLINING EVEN-FLOW (TOP) AND NON-DECLINING DISCOUNTED FLOW (BOTTOM) .............1220

FIGURE D-1. ANALYSIS AREA FOR MODELING AND ANALYSIS OF POTENTIAL EFFECTS ON NORTHERN SPOTTED OWL 

HABITAT AND POPULATIONS FROM LARGE WILDFIRES (LEFT), AND BLM-ADMINISTERED LANDS WITHIN THE 

ANALYSIS AREA BY DISTRICT (RIGHT) ..............................................................................................................1231

FIGURE D-2. ANNUAL AND DECADAL NUMBERS OF LARGE WILDFIRES (≥ 1,000 ACRES) IN THE ANALYSIS AREA 

(1970–2013) ....................................................................................................................................................1233

FIGURE D-3. COMPARISON OF THREE DECADES OF OBSERVED LARGE WILDFIRE HISTORY FROM MONITORING 

TRENDS IN BURN SEVERITY FIRE OCCURRENCE DATA (LEFT) WITH THE FIRST THREE DECADES OF RANDOMLY 

GENERATED FIRE LOCATIONS (RIGHT) ............................................................................................................1234

FIGURE D-4. HISTORICAL (1970–2013) WILDFIRE DISTRIBUTION BY FIRE SIZE WITHIN THE RANGE OF THE 

NORTHERN SPOTTED OWL .............................................................................................................................1235

FIGURE D-5. COMPARISON OF ANNUAL PROPORTION OF AREA BURNED BY MAPPED FIRE SEVERITY FROM MTBS 

DATA FROM 1986 TO 2011 WITH MODELED SEVERITY BASED ON A THREE QUANTILE CLASSIFICATION OF THE 

FIRESEV MAP FOR THE FIVE DECADAL MODELS .............................................................................................1237

FIGURE D-6. TRENDS IN AREA BURNED BY FIRE SEVERITY CLASS ...........................................................................1238

FIGURE D-7. COMPARISON OF ACTUAL AREA BURNED (BLACK SHADING) BY LARGE WILDFIRES FROM 1970 TO 2013 

(LEFT) WITH MODELED LARGE WILDFIRES OVER 5 DECADES (RIGHT) ...........................................................1239

FIGURE D-8. COMPARISON OF A LARGE WILDFIRE SUITABILITY MODEL BASED ON THE CURRENT CLIMATE NORMAL 

(LEFT) WITH SAME MODEL BASED ON PROJECTED CLIMATE NORMAL CHANGES IN TEMPERATURE AND 

PRECIPITATION BY 2060 (RIGHT) (FROM YANG ET AL. IN PREP.) ....................................................................1241

FIGURE H-1. ANALYSIS AREA WITHIN THE STATE OF OREGON ...............................................................................1305

FIGURE H-2. BLM-ADMINISTERED LANDS WITHIN THE ANALYSIS AREA ................................................................. 1306

FIGURE H-3. LANDSCAPE UNITS ..............................................................................................................................1313

FIGURE H-4. EXAMPLE LANDSCAPE UNIT (STRATA) DEPARTURE SUMMARY CALCULATION ..................................1314

FIGURE H-5. BLM SUCCESSIONAL/STRUCTURAL STAGE (S-CLASS) DATA FOR BLM-ADMINISTERED LANDS IN THE 

ANALYSIS AREA ...............................................................................................................................................1315

FIGURE H-6. GRADIENT NEAREST NEIGHBOR (GNN) S-CLASS DATA FOR THE ANALYSIS AREA ..............................1316

FIGURE H-7. BLM AND GNN S-CLASS DATA COMBINED ..........................................................................................1317

FIGURE H-8. STAND-LEVEL FIRE RESISTANCE CATEGORIES IN THE HARVEST LAND BASE IN THE DRY FOREST IN THE 

KLAMATH FALLS FIELD OFFICE FOR THE CURRENT CONDITION IN 50 YEARS .................................................1323

FIGURE H-9. STAND-LEVEL FIRE RESISTANCE CATEGORIES IN THE HARVEST LAND BASE IN THE DRY FOREST ON THE 

MEDFORD DISTRICT FOR THE CURRENT CONDITION IN 50 YEARS ................................................................. 1324

FIGURE H-10. STAND-LEVEL FIRE RESISTANCE CATEGORIES IN THE HARVEST LAND BASE IN THE DRY FOREST ON 

THE ROSEBURG DISTRICT IN 50 YEARS ...........................................................................................................1325

FIGURE H-11. STAND-LEVEL FIRE HAZARD FOR ALL BLM-ADMINISTERED LANDS ON THE COOS BAY DISTRICT 

WITHIN THE WDA IN 2063..............................................................................................................................1326

FIGURE H-12. STAND-LEVEL FIRE HAZARD FOR ALL BLM-ADMINISTERED LANDS ON THE EUGENE DISTRICT WITHIN 

THE WDA IN 2063 ...........................................................................................................................................1326

FIGURE H-13. STAND-LEVEL FIRE HAZARD FOR ALL BLM-ADMINISTERED LANDS ON THE KLAMATH FALLS FIELD 

OFFICE WITHIN THE WDA IN 2063 ..................................................................................................................1327

FIGURE H-14. STAND-LEVEL FIRE HAZARD FOR ALL BLM-ADMINISTERED LANDS ON THE MEDFORD DISTRICT 

WITHIN THE WDA IN 2063..............................................................................................................................1327

FIGURE H-15. STAND-LEVEL FIRE HAZARD FOR ALL BLM-ADMINISTERED LANDS ON THE ROSEBURG DISTRICT 

WITHIN THE WDA IN 2063..............................................................................................................................1328
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FIGURE H-16. STAND-LEVEL FIRE HAZARD FOR ALL BLM-ADMINISTERED LANDS ON THE SALEM DISTRICT WITHIN 

THE WDA IN 2063 ...........................................................................................................................................1328

FIGURE H-17. STAND-LEVEL FIRE HAZARD IN THE LATE-SUCCESSIONAL RESERVE IN THE DRY FOREST IN THE 

COASTAL/NORTH IN 50 YEARS ........................................................................................................................1329

FIGURE H-18. STAND-LEVEL FIRE HAZARD IN THE LATE-SUCCESSIONAL RESERVE IN THE DRY FOREST IN THE 

INTERIOR/SOUTH IN 50 YEARS........................................................................................................................1330

FIGURE I-1. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF UPPER WILLAMETTE RIVER STEELHEAD ....1334

FIGURE I-2. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF LOWER COLUMBIA RIVER CHINOOK SALMON

........................................................................................................................................................................1335

FIGURE I-3. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF LOWER COLUMBIA RIVER CHUM SALMON

........................................................................................................................................................................1336

FIGURE I-4. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF LOWER COLUMBIA RIVER COHO SALMON

........................................................................................................................................................................1337

FIGURE I-5. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF LOWER COLUMBIA RIVER STEELHEAD ......1338

FIGURE I-6. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF OREGON COAST COHO SALMON ..............1339

FIGURE I-7. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF SOUTHERN OREGON NORTHERN CALIFORNIA 

COHO SALMON ...............................................................................................................................................1340

FIGURE I-8. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF UPPER WILLAMETTE RIVER SPRING CHINOOK 

SALMON ..........................................................................................................................................................1341

FIGURE I-9. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF BULL TROUT IN THE MCKENZIE BASIN ......1342

FIGURE I-10. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF LOST RIVER SUCKER ................................1343

FIGURE I-11. CRITICAL HABITAT DESIGNATION AND DISTRIBUTION OF SHORTNOSE SUCKER ...............................1344

FIGURE N-1. SPECIAL STATUS SPECIES ‘HOT SPOTS’ WITHIN THE DECISION AREA .................................................1463

FIGURE O-1. COOS BAY DISTRICT RECREATION MANAGEMENT AREA LOCATIONS ................................................1498

FIGURE O-2. EUGENE DISTRICT RECREATION MANAGEMENT AREA LOCATIONS ...................................................1499

FIGURE O-3. KLAMATH FALLS FIELD OFFICE RECREATION MANAGEMENT AREA LOCATIONS ...............................1500

FIGURE O-4. MEDFORD DISTRICT RECREATION MANAGEMENT AREA LOCATIONS ...............................................1501

FIGURE O-5. ROSEBURG DISTRICT RECREATION MANAGEMENT AREA LOCATIONS ..............................................1502

FIGURE O-6. SALEM DISTRICT RECREATION MANAGEMENT AREA LOCATIONS .....................................................1503

FIGURE T-1. FLOWCHART OF THE BLM MAXENT MODELING SEQUENCE ...............................................................1741

FIGURE T-2. DISTRIBUTION OF HEXAGONS RELATIVE HABITAT SUITABILITY SCORES AMONG VARIOUS BINS FROM 

2006 GNN MAXENT MODELS DEVELOPED BY THE U.S. FISH AND WILDLIFE SERVICE AND THE U.S. FOREST 

SERVICE ...........................................................................................................................................................1742

FIGURE T-3. BIVARIATE SCATTERPLOTS FOR SELECT 2006 GNN VARIABLES FOR THE THREE WESTERN OREGON 

MODELING REGIONS (LEFT) AND 2013 WOODSTOCK VARIABLES FOR THE DECISION AREA (RIGHT) ...........1746

FIGURE T-4. NO TIMBER HARVEST: DISTRIBUTION OF RELATIVE HABITAT SUITABILITY BY DECADE FOR MODEL 8, 

ON THE DECISION AREA (A AND C), AND ON BLM-ADMINISTERED LANDS IN THE OREGON AND CALIFORNIA 

CASCADES MODELING REGION (B) .................................................................................................................1748

FIGURE T-5. NO TIMBER HARVEST: DISTRIBUTIONS OF RELATIVE HABITAT SUITABILITY BY DECADE FOR MODEL 8 

(TOP) AND MODEL 9 (BOTTOM) ON THE DECISION AREA ..............................................................................1750

FIGURE T-6. NO TIMBER HARVEST: DISTRIBUTION OF RELATIVE HABITAT SUITABILITY BY DECADE FOR MODEL 8 

(TOP) AND MODEL 9 (BOTTOM), ON THE DECISION AREA .............................................................................1751

FIGURE T-7. NO TIMBER HARVEST: DISTRIBUTIONS OF RELATIVE HABITAT SUITABILITY BY DECADE FOR MODEL 9 

(TOP) AND MODEL 10 (BOTTOM) ON THE DECISION AREA ............................................................................1753

FIGURE T-8. NO TIMBER HARVEST: DISTRIBUTIONS OF RELATIVE HABITAT SUITABILITY BY DECADE FOR MODEL 8 

(TOP) AND MODEL 11 (BOTTOM) ON THE DECISION AREA ............................................................................1755

FIGURE T-9. NO TIMBER HARVEST: DISTRIBUTIONS OF RELATIVE HABITAT SUITABILITY BY DECADE FOR MODEL 9 

(TOP) AND MODEL 12 (BOTTOM) ON THE DECISION AREA ............................................................................1756

FIGURE T-10. NO TIMBER HARVEST: DISTRIBUTION OF RELATIVE HABITAT SUITABILITY BY DECADE FOR MODEL 9 

(TOP) AND MODEL 12 (BOTTOM) ON THE DECISION AREA ............................................................................1757

FIGURE T-11. COMPARISONS OF THE DISTRIBUTION OF RELATIVE HABITAT SUITABILITY AT THE HEXAGON SCALE, 

ON BLM-ADMINISTERED LANDS (LEFT COLUMN), AND ALL LANDS (RIGHT COLUMN), IN THE OREGON AND 
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CALIFORNIA KLAMATH, OREGON COAST RANGE AND THE OREGON AND CALIFORNIA CASCADES MODELING 

REGIONS (DESCRIBED BY DAVIS ET AL. 2011) ................................................................................................. 1760

FIGURE T-12. SPATIAL DISTRIBUTION OF RELATIVE HABITAT SUITABILITY FOR THE U.S. FISH AND WILDLIFE SERVICE 

2012 GNN MAXENT MODEL (LEFT) AND THE BLM 2013 WOODSTOCK MODEL 13 (RIGHT)...........................1761

FIGURE T-13. RANGEWIDE DISTRIBUTION OF RELATIVE HABITAT SUITABILITY VALUES AMONG TRAINING 

NORTHERN SPOTTED OWL SITES FOR THE U.S. FISH AND WILDLIFE SERVICE 1996 GNN MAXENT MODEL AND 

BLM’S 1996 GNN MODEL 13...........................................................................................................................1763

FIGURE T-14. RANGEWIDE DISTRIBUTION OF RELATIVE HABITAT SUITABILITY VALUES AMONG TEST NORTHERN 

SPOTTED OWL SITES FOR THE U.S. FISH AND WILDLIFE SERVICE 1996 GNN MAXENT MODEL AND BLM’S 1996 

GNN MODEL 13 ...............................................................................................................................................1763

FIGURE T-15. DISTRIBUTION OF RELATIVE HABITAT SUITABILITY VALUES AMONG TRAINING NORTHERN SPOTTED 

OWL SITES ON THE DECISION AREA FOR THE U.S. FISH AND WILDLIFE SERVICE 2012 GNN MAXENT MODEL 

AND BLM’S 2013 WOODSTOCK MODEL 13 ....................................................................................................1765

FIGURE T-16. DISTRIBUTION OF RELATIVE HABITAT SUITABILITY VALUES AMONG TEST NORTHERN SPOTTED OWL 

SITES ON THE DECISION AREA FOR THE U.S. FISH AND WILDLIFE SERVICE 2012 GNN MAXENT MODEL AND 

BLM’S 2013 WOODSTOCK MODEL 13 .............................................................................................................1765

FIGURE T-17. COMPARISON OF THE MEAN OF ESTIMATES OF TERRITORIAL NORTHERN SPOTTED OWLS ON EIGHT 

DEMOGRAPHIC STUDY AREAS ESTIMATED IN THE FIELD (EMPIRICAL ESTIMATES, N = MEAN OF THREE 

HIGHEST YEARS BETWEEN 1996 AND 2006) AND ESTIMATED USING THE BLM NORTHERN SPOTTED OWL 

HEXSIM MODEL (MEAN FROM 20 REPLICATES OF HEXSIM AT TIME-STEP 59) ..............................................1785

FIGURE T-18. HYPOTHETICAL BARRED OWL CONTROL AREAS IN THE UNITED STATES’ PORTION OF THE NORTHERN 

SPOTTED OWL’S RANGE..................................................................................................................................1790

Table of Tables 

TABLE B-1. EASTSIDE MANAGEMENT AREA – RIPARIAN RESERVE DISTANCES BY WATER FEATURE .....................1104

TABLE B-2. SNAG CREATION LEVELS WITHIN THE HARVEST LAND BASE ................................................................1107

TABLE B-3. SNAG CREATION LEVELS WITHIN THE LATE-SUCCESSIONAL RESERVE AND RIPARIAN RESERVE ..........1115

TABLE B-4. DOWN WOODY MATERIAL RETENTION LEVELS WHEN IMPLEMENTING FUELS REDUCTION OR 

PRESCRIBED FIRE TREATMENTS WITHIN THE LATE-SUCCESSIONAL RESERVE AND RIPARIAN RESERVE ........1115

TABLE B-5. RIPARIAN RESERVE DISTANCE BY WATER FEATURE..............................................................................1119

TABLE B-6. ZONE-SPECIFIC MANAGEMENT DIRECTION FOR STREAMS IN CLASS I SUBWATERSHEDS....................1119

TABLE B-7. ZONE-SPECIFIC MANAGEMENT DIRECTION FOR STREAMS IN CLASS II SUBWATERSHEDS...................1121

TABLE B-8. ZONE-SPECIFIC MANAGEMENT DIRECTION FOR STREAMS IN CLASS III SUBWATERSHEDS .................1122

TABLE B-9. RIPARIAN RESERVE DISTANCE BY WATER FEATURE..............................................................................1125

TABLE B-10. ZONE-SPECIFIC MANAGEMENT DIRECTION FOR STREAMS IN CLASS I SUBWATERSHEDS..................1125

TABLE B-11. ZONE-SPECIFIC MANAGEMENT DIRECTION FOR STREAMS IN CLASS II SUBWATERSHEDS.................1127

TABLE B-12. ZONE-SPECIFIC MANAGEMENT DIRECTION FOR STREAMS IN CLASS III SUBWATERSHEDS................1128

TABLE B-13. CULTURAL USE ALLOCATIONS WITH DESIRED OUTCOMES AND MANAGEMENT ACTIONS ...............1132

TABLE B-14. ALLOTMENTS UNAVAILABLE FOR LIVESTOCK GRAZING, COOS BAY DISTRICT ....................................1138

TABLE B-15. ALLOTMENTS UNAVAILABLE FOR LIVESTOCK GRAZING, KLAMATH FALLS FIELD OFFICE ...................1140

TABLE B-16. EXCLOSURES OR OTHER AREAS PREVIOUSLY CLOSED TO LIVESTOCK GRAZING, KLAMATH FALLS FIELD 

OFFICE .............................................................................................................................................................1140

TABLE B-17. ALLOTMENTS UNAVAILABLE FOR LIVESTOCK GRAZING, MEDFORD DISTRICT ...................................1142

TABLE C-1. MODELING GROUPS USED TO DEVELOP STRATA. .................................................................................1169

TABLE C-2. EXISTING STAND CONDITION CODING ..................................................................................................1170

TABLE C-3. BLM WESTERN OREGON ACREAGE BY AGE CLASS DISTRIBUTION AND SUSTAINED YIELD UNIT AS OF 

JANUARY 1, 2013 ............................................................................................................................................1173

TABLE C-4. BLM WESTERN OREGON ACREAGE BY AGE CLASS DISTRIBUTION AND SUSTAINED YIELD UNIT AFTER 

2013 LARGE FIRE DATA ADJUSTMENT ............................................................................................................1173

TABLE C-5. PERCENTAGE OF SITE PRODUCTIVITY CLASSES WITHIN EACH SUSTAINED-YIELD UNIT .......................1174

TABLE C-6. STRATA REPRESENTATION WITH CVS SUBPLOTS ..................................................................................1175
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TABLE C-7. RESULTS FROM NET INVENTORY COMPARISON (MMBF VOLUME) ......................................................1176

TABLE C-8. EXAMPLE OF ONE FOI UNIT SUBDIVIDED INTO FOUR UNIQUE AREAS .................................................1177

TABLE C-9. GIS DATA THEMES USED IN THE ANALYSIS FOR THE PROPOSED RMP .................................................1178

TABLE C-10. MOIST VS. DRY FORESTED ACRES BY DISTRICT ...................................................................................1181

TABLE C-11. MOIST/DRY POTENTIAL VEGETATION TYPE CATEGORIZATION BY DISTRICT ......................................1181

TABLE C-12. SILVICULTURAL SYSTEMS/HARVEST METHOD BY LAND USE ALLOCATION ........................................1185

TABLE C-13. SILVICULTURAL SYSTEMS SELECTED MODELING ASSUMPTIONS* ......................................................1186

TABLE C-14. UNEVEN-AGED MANAGEMENT MODELING STRATEGIES BY LAND USE ALLOCATION ........................1196

TABLE C-15. TIMBER YIELD DEDUCTIONS DUE TO DEFECT AND BREAKAGE BY HARVEST STAND AGE ...................1197

TABLE C-16. TIMBER YIELD DEDUCTIONS DUE TO SOIL COMPACTION ...................................................................1198

TABLE C-17. TIMBER YIELD DEDUCTIONS DUE TO SNAG RETENTION BY LAND USE ALLOCATION .........................1199

TABLE C-18. TIMBER YIELD DEDUCTIONS DUE TO DOWN WOODY MATERIAL RETENTION BY THE PROPOSED RMP 

AND ALTERNATIVES AND LAND USE ALLOCATION .........................................................................................1200

TABLE C-19. TIMBER YIELD DEDUCTIONS FROM FOREGONE HARVEST VOLUME DUE TO GREEN TREE RETENTION BY 

LAND USE ALLOCATION ..................................................................................................................................1202

TABLE C-20. MINIMUM HARVEST AGE BY SITE PRODUCTIVITY CLASS FOR THE NO ACTION ALTERNATIVE ...........1209

TABLE C-21. RESERVE HARVESTING CONSTRAINTS FOR ALTERNATIVE A ...............................................................1211

TABLE C-22. MINIMUM HARVEST AGE CONSTRAINTS BY 10-YEAR WOODSTOCK PERIOD FOR LOW INTENSITY 

TIMBER AREA AND MODERATE INTENSITY TIMBER AREA ..............................................................................1213

TABLE C-23. MODELED HARVEST AND CONTRIBUTION TO ASQ .............................................................................1217

TABLE C-24. WOODSTOCK MODELING OUTPUT VARIABLES ...................................................................................1221

TABLE D-1. PARAMETERS USED TO ASSIGN RANDOM POINTS A WILDFIRE SIZE BY BUFFERING THE POINT LOCATION

........................................................................................................................................................................1236

TABLE E-1. FUELS CHARACTERISTIC CLASSIFICATION SYSTEM FUELBEDS USED IN EACH ANALYSIS GROUP TO 

ESTIMATE PARTICULATE EMISSIONS FROM WILDFIRE ...................................................................................1246

TABLE E-2. ACRES, FUEL MOISTURES, AND TARGETED CONSUMPTION RATES FOR LIVE WOODY FUELS IN EACH 

SEVERITY CLASS FOR PAST WILDFIRES ............................................................................................................1247

TABLE F-1. AREAS OF CRITICAL ENVIRONMENTAL CONCERN DESIGNATIONS BY ALTERNATIVE AND THE PROPOSED 

RMP ................................................................................................................................................................. 1251

TABLE F-2. MANAGEMENT DIRECTION FOR AREAS OF CRITICAL ENVIRONMENTAL CONCERN .............................1256

TABLE F-3. SPECIFIC RELEVANT AND IMPORTANT VALUES .....................................................................................1268

TABLE G-1. FUELS CHARACTERISTIC CLASSIFICATION SYSTEM FUELBEDS USED IN EACH ANALYSIS GROUP TO 

ESTIMATE GREENHOUSE GAS EMISSIONS FROM WILDFIRE ...........................................................................1302

TABLE G-2. ACRES, FUEL MOISTURES, AND TARGETED CONSUMPTION RATES FOR LIVE WOODY FUELS IN EACH 

SEVERITY CLASS FOR PAST WILDFIRES ............................................................................................................1303

TABLE H-1. ILAP PVTS IN THE ANALYSIS AREA TO LANDFIRE BPS MODEL CROSSWALK .........................................1307

TABLE H-2. BLM-ADMINISTERED LANDS BY S-CLASS IN TERMS OF SPECIES COMPOSITION, STAND STRUCTURE, AND 

STAND AGE FOR EACH BIOPHYSICAL SETTING ................................................................................................1309

TABLE H-3. NON-BLM-ADMINISTERED LANDS BY S-CLASS IN TERMS OF SPECIES COMPOSITION, STAND STRUCTURE, 

AND STAND AGE FOR EACH BIOPHYSICAL SETTING .......................................................................................1310

TABLE H-4. REFERENCE CONDITION RANGE BY POTENTIAL VEGETATION TYPE (PVT)/BIOPHYSICAL SETTING (BPS)

........................................................................................................................................................................1312

TABLE H-5. ACRES OF CURRENT CONDITION FORESTED AND NON-FORESTED BLM-ADMINISTERED LANDS WITHIN 

THE PLANNING AREA ......................................................................................................................................1319

TABLE H-6. BLM-DEFINED STRUCTURAL STAGES AND SUBDIVISIONS, RELATIVE STAND-LEVEL RESISTANCE TO 

REPLACEMENT FIRE RATINGS, AND ASSUMPTIONS REGARDING OVERALL FUEL PROFILE CONTINUITY, AND 

VERTICAL AND HORIZONTAL FUEL CONTINUITY .............................................................................................1321

TABLE H-7. BLM-DEFINED STRUCTURAL STAGES AND SUBDIVISIONS, RELATIVE STAND-LEVEL FIRE HAZARD 

RATINGS AND ASSUMPTIONS REGARDING SURFACE FUEL LOADING, CANOPY BASE HEIGHT, AND CANOPY 

FUEL BULK DENSITY (CONTINUITY) AS THE BASIS FOR THE HAZARD RATING ................................................1322

TABLE I-1. BUREAU SENSITIVE AND BUREAU STRATEGIC FISH SPECIES WITHIN THE DECISION AREA. .................. 1333

TABLE J-1. BEST MANAGEMENT PRACTICES FOR ROADS AND LANDINGS ..............................................................1348

TABLE J-2. BEST MANAGEMENT PRACTICES FOR TIMBER HARVEST ACTIVITIES.....................................................1362
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TABLE J-3. SOIL COVER BASED ON EROSION HAZARD RATINGS .............................................................................1365

TABLE J-4. BEST MANAGEMENT PRACTICES FOR PLANTING, PRE-COMMERCIAL THINNING, AND FERTILIZATION

........................................................................................................................................................................1366

TABLE J-5. BEST MANAGEMENT PRACTICES FOR FIRE AND FUEL MANAGEMENT .................................................1366

TABLE J-6. WATER BAR SPACING BY GRADIENT AND EROSION CLASS ....................................................................1371

TABLE J-7. BEST MANAGEMENT PRACTICES FOR SURFACE SOURCE WATER FOR DRINKING WATER PROTECTION

........................................................................................................................................................................1371

TABLE J-8. BEST MANAGEMENT PRACTICES FOR RECREATION MANAGEMENT .....................................................1373

TABLE J-9. BEST MANAGEMENT PRACTICES FOR LIVESTOCK GRAZING ..................................................................1376

TABLE J-10. BEST MANAGEMENT PRACTICES FOR MINERALS (SALABLE) ...............................................................1378

TABLE J-11. BEST MANAGEMENT PRACTICES FOR SPILL PREVENTION AND ABATEMENT .....................................1379

TABLE J-12. BEST MANAGEMENT PRACTICES FOR RESTORATION ACTIVITIES ........................................................1382

TABLE J-13. TIMBER PRODUCTION CAPABILITY CLASSIFICATION SOIL CATEGORIES OF CONCERN ........................1384

TABLE J-14. BEST MANAGEMENT PRACTICES SPECIFIC TO THE DRY FOREST (REFER TO TABLE J-13 FOR CATEGORY 

TYPE) ...............................................................................................................................................................1385

TABLE K-1. WITHDRAWAL TABLES LEGEND.............................................................................................................1391

TABLE K-2. WITHDRAWALS IN THE COOS BAY DISTRICT .........................................................................................1392

TABLE K-3. WITHDRAWALS IN THE EUGENE DISTRICT ............................................................................................1399

TABLE K-4. WITHDRAWALS IN THE KLAMATH FALLS FIELD OFFICE ........................................................................1403

TABLE K-5. WITHDRAWALS IN THE MEDFORD DISTRICT .........................................................................................1407

TABLE K-6. WITHDRAWALS IN THE ROSEBURG DISTRICT ........................................................................................1417

TABLE K-7. WITHDRAWALS IN THE SALEM DISTRICT ..............................................................................................1421

TABLE K-8. LAND TENURE ZONE 3 LANDS IN THE COOS BAY DISTRICT ...................................................................1425

TABLE K-9. LAND TENURE ZONE 3 LANDS IN THE EUGENE DISTRICT ......................................................................1425

TABLE K-10. LAND TENURE ZONE 3 LANDS IN THE KLAMATH FALLS FIELD OFFICE ................................................1426

TABLE K-11. LAND TENURE ZONE 3 LANDS IN THE MEDFORD DISTRICT ................................................................1427

TABLE K-12. LAND TENURE ZONE 3 LANDS IN THE ROSEBURG DISTRICT ...............................................................1428

TABLE K-13. LAND TENURE ZONE 3 LANDS IN THE SALEM DISTRICT ......................................................................1429

TABLE K-14. COMMUNICATION SITES IN THE COOS BAY DISTRICT ........................................................................1432

TABLE K-15. COMMUNICATION SITES IN THE EUGENE DISTRICT............................................................................1432

TABLE K-16. COMMUNICATION SITES IN THE KLAMATH FALLS FIELD OFFICE ........................................................1433

TABLE K-17. COMMUNICATION SITES IN THE MEDFORD DISTRICT ........................................................................1433

TABLE K-18. COMMUNICATION SITES IN THE ROSEBURG DISTRICT .......................................................................1433

TABLE K-19. COMMUNICATION SITES IN THE SALEM DISTRICT ..............................................................................1434

TABLE L-1. AVAILABLE KLAMATH FALLS FIELD OFFICE GRAZING ALLOTMENTS ......................................................1436

TABLE L-2. AVAILABLE MEDFORD DISTRICT GRAZING ALLOTMENTS ......................................................................1443

TABLE M-1. SALABLE MINERAL DEVELOPMENT 10-YEAR SCENARIO FOR NEW OR EXPANDED QUARRY 

DEVELOPMENT ...............................................................................................................................................1447

TABLE M-2. LOCATABLE MINERAL DEVELOPMENT 10-YEAR SCENARIO NOTICES ..................................................1447

TABLE M-3. LOCATABLE MINERAL DEVELOPMENT 10-YEAR SCENARIO PLANS OF OPERATION ............................1448

TABLE M-4. RANKING OF DISTRICT-DESIGNATED RESERVE – LANDS MANAGED FOR THEIR WILDERNESS 

CHARACTERISTICS LANDS THAT THE BLM WOULD RECOMMENDED FOR WITHDRAWAL FROM LOCATABLE 

MINERAL ENTRY ..............................................................................................................................................1452

TABLE M-5. RANKING OF ELIGIBLE WILD AND SCENIC RIVER SEGMENTS THAT THE BLM WOULD RECOMMEND FOR 

WITHDRAWAL FROM LOCATABLE MINERAL ENTRY .......................................................................................1453

TABLE M-6. RANKING OF AREAS OF ENVIRONMENTAL CONCERN THAT THE BLM WOULD RECOMMEND FOR 

WITHDRAWAL FROM LOCATABLE MINERAL ENTRY .......................................................................................1454

TABLE M-7. RANKING OF SPECIAL RECREATIONAL MANAGEMENT AREAS THAT THE BLM WOULD RECOMMEND 

FOR WITHDRAWAL FROM LOCATABLE MINERAL ENTRY ................................................................................1457

TABLE N-1. EXISTING CONSERVATION STRATEGY AND AGREEMENTS FOR BUREAU SPECIAL STATUS PLANT SPECIES

........................................................................................................................................................................1464

TABLE N-2. BLM SENSITIVE PLANTS AND FUNGI WITHIN THE PLANNING AREA (BLM OREGON/WASHINGTON STATE 

DIRECTOR’S SENSITIVE SPECIES LIST, JULY 2015)............................................................................................1465
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TABLE N-3. SURVEY AND MANAGE SPECIES IN THE NO ACTION ALTERNATIVE ......................................................1481

TABLE O-1. RECREATION MANAGEMENT AREAS WITHIN THE DECISION AREA BY ALTERNATIVE AND THE PROPOSED 

RMP ................................................................................................................................................................. 1489

TABLE P-1. PRICE DATA AND HARVEST VOLUME DATA, 2012 ................................................................................1507

TABLE P-2. SUMMARY STATISTICS ..........................................................................................................................1510

TABLE P-3. TOBIT MODEL OF DAILY TIME SPENT ON OUTDOOR RECREATION FOR WESTERN U.S. STATES IN THE 

YEARS 2007–2013, COEFFICIENTS AND STANDARD ERRORS ..........................................................................1512

TABLE P-4. ELASTICITY OF DEMAND FOR SHIFT IN LAND FROM NON-RECREATIONAL TO RECREATIONAL 

MANAGEMENT ...............................................................................................................................................1513

TABLE P-5. RECREATION VISITATION ESTIMATES FOR THE PROPOSED RMP AND ALTERNATIVES BY 

IMPLEMENTATION SCENARIO.........................................................................................................................1514

TABLE P-6. EMPLOYMENT BY INDUSTRY BY DISTRICT MODEL AREA, 2012 (JOBS) .................................................1517

TABLE P-7. EARNINGS BY INDUSTRY BY DISTRICT MODEL AREA, 2012 (MILLIONS OF 2012 DOLLARS) ..................1518

TABLE P-8. EMPLOYMENT CONTRIBUTION OF BLM PROGRAMS TO DISTRICT MODEL AREAS BY INDUSTRY, 2012 

(JOBS) ..............................................................................................................................................................1519

TABLE P-9. EARNINGS CONTRIBUTION OF BLM PROGRAMS TO DISTRICT MODEL AREAS BY INDUSTRY, 2012 

(MILLIONS OF 2012 DOLLARS) ........................................................................................................................1520

TABLE P-10. EMPLOYMENT AND EARNINGS IN THE COOS BAY DISTRICT MODEL AREA FOR THE PROPOSED RMP 

AND ALTERNATIVES ........................................................................................................................................1521

TABLE P-11. EMPLOYMENT AND EARNINGS IN THE EUGENE DISTRICT MODEL AREA FOR THE PROPOSED RMP AND 

ALTERNATIVES ................................................................................................................................................1522

TABLE P-12. EMPLOYMENT AND EARNINGS IN THE KLAMATH FALLS FIELD OFFICE MODEL AREA FOR THE 

PROPOSED RMP AND ALTERNATIVES .............................................................................................................1523

TABLE P-13. EMPLOYMENT AND EARNINGS IN THE MEDFORD DISTRICT MODEL AREA FOR THE PROPOSED RMP 

AND ALTERNATIVES ........................................................................................................................................1524

TABLE P-14. EMPLOYMENT AND EARNINGS IN THE ROSEBURG DISTRICT MODEL AREA FOR THE PROPOSED RMP 

AND ALTERNATIVES ........................................................................................................................................1525

TABLE P-15. EMPLOYMENT AND EARNINGS IN THE SALEM-OTHER DISTRICT MODEL AREA* FOR THE PROPOSED 

RMP AND ALTERNATIVES ................................................................................................................................1526

TABLE P-16. EMPLOYMENT AND EARNINGS IN THE SALEM-PORTLAND MSA DISTRICT MODEL AREA* FOR THE 

PROPOSED RMP AND ALTERNATIVES .............................................................................................................1527

TABLE P-17. STRATIFIED RANDOM SAMPLE OF COMMUNITIES BY POPULATION (SELECTED CITIES HIGHLIGHTED)

........................................................................................................................................................................1529

TABLE P-18. COMMUNITY CAPACITY/RESILIENCY BASELINE INPUTS ...................................................................... 1530

TABLE P-19. SELECTED SOCIOECONOMIC CHARACTERISTICS FOR SELECTED CITIES IN WESTERN OREGON ..........1531

TABLE P-20. SELECTED SOCIOECONOMIC CHARACTERISTICS: FEDERALLY RECOGNIZED TRIBES WITH LAND IN THE 

PLANNING AREA, 2009 AND 2012 (1) .............................................................................................................1539

TABLE P-21. CITY OF COQUILLE INTERVIEW ............................................................................................................1546

TABLE P-22. CITY OF GOLD BEACH INTERVIEW .......................................................................................................1549

TABLE P-23. CITY OF DRAIN INTERVIEW ..................................................................................................................1551

TABLE P-24. CITY OF FLORENCE INTERVIEW ...........................................................................................................1554

TABLE P-25. CITY OF GRANTS PASS INTERVIEW ......................................................................................................1556

TABLE P-26. CITY OF KLAMATH FALLS INTERVIEW ..................................................................................................1559

TABLE P-27. JUNCTION CITY INTERVIEW .................................................................................................................1561

TABLE P-28. LINCOLN CITY INTERVIEW ...................................................................................................................1563

TABLE P-29. CITY OF MOLALLA INTERVIEW ............................................................................................................1565

TABLE P-30. CITY OF ROGUE RIVER INTERVIEW ......................................................................................................1567

TABLE P-31. CITY OF ST. HELENS INTERVIEW. .........................................................................................................1569

TABLE P-32. CITY OF SUBLIMITY INTERVIEW ...........................................................................................................1571

TABLE P-33. CITY OF WINSTON INTERVIEW ............................................................................................................1573

TABLE P-34. CONFEDERATED TRIBES OF THE GRAND RONDE COMMUNITY OF OREGON INTERVIEW ..................1576

TABLE P-35. COQUILLE INDIAN TRIBE INTERVIEW ..................................................................................................1578

TABLE P-36. MINORITY POPULATIONS MEETING ENVIRONMENTAL JUSTICE CRITERIA .........................................1581
viii | P a g e

TABLE P-37. LOW-INCOME POPULATIONS MEETING ENVIRONMENTAL JUSTICE CRITERIA ...................................1584

TABLE Q-1. CURRENT PUBLIC MOTORIZED ACCESS DESIGNATIONS WITHIN THE DECISION AREA ........................1590

TABLE Q-2. PUBLIC MOTORIZED ACCESS DESIGNATIONS IN THE DECISION AREA .................................................1590

TABLE Q-3. COOS BAY DISTRICT PUBLIC MOTORIZED ACCESS DESIGNATIONS ......................................................1591

TABLE Q-4. EUGENE DISTRICT PUBLIC MOTORIZED ACCESS DESIGNATIONS BY ALTERNATIVE AND THE PROPOSED 

RMP ................................................................................................................................................................. 1594

TABLE Q-5. KLAMATH FALLS FIELD OFFICE PUBLIC MOTORIZED ACCESS DESIGNATIONS BY ALTERNATIVE AND THE 

PROPOSED RMP ..............................................................................................................................................1596

TABLE Q-6. MEDFORD DISTRICT PUBLIC MOTORIZED ACCESS DESIGNATIONS BY ALTERNATIVE AND THE PROPOSED 

RMP ................................................................................................................................................................. 1598

TABLE Q-7. ROSEBURG DISTRICT PUBLIC MOTORIZED ACCESS DESIGNATIONS BY ALTERNATIVE AND THE 

PROPOSED RMP ..............................................................................................................................................1600

TABLE Q-8. SALEM DISTRICT PUBLIC MOTORIZED ACCESS DESIGNATIONS BY ALTERNATIVE AND THE PROPOSED 

RMP ................................................................................................................................................................. 1602

TABLE Q-9. CURRENT AUTHORIZED MOTORIZED AND NON-MOTORIZED TRAILS WITHIN THE DECISION AREA ...1609

TABLE R-1. ALPHABETICAL LISTING OF TRIBAL LISTENING SESSIONS*....................................................................1631

TABLE R-2. LISTENING SESSION AGENDA AND FORMAT .........................................................................................1632

TABLE R-3. PLANTS OF CULTURAL SIGNIFICANCE TO THE KLAMATH TRIBES ..........................................................1641

TABLE R-4. COMMON CULTURAL PLANTS OF IMPORTANCE TO TRIBES IN WESTERN OREGON ............................1644

TABLE S-1. BALD EAGLE NESTING HABITAT DEVELOPMENT IN THE DECISION AREA .............................................1651

TABLE S-2. BALD EAGLE NESTING HABITAT DEVELOPMENT IN THE PLANNING AREA ............................................1651

TABLE S-3. GOLDEN EAGLE NESTING HABITAT DEVELOPMENT IN THE DECISION AREA ........................................1652

TABLE S-4. GOLDEN EAGLE NESTING HABITAT DEVELOPMENT IN THE PLANNING AREA .......................................1652

TABLE S-5. EARLY SUCCESSIONAL FOREST HABITAT DEVELOPMENT IN THE DECISION AREA ................................1653

TABLE S-6. EARLY SUCCESSIONAL FOREST HABITAT DEVELOPMENT IN THE PLANNING AREA ..............................1653

TABLE S-7. STAND ESTABLISHMENT FOREST HABITAT DEVELOPMENT IN THE DECISION AREA ............................1653

TABLE S-8. STAND ESTABLISHMENT FOREST HABITAT DEVELOPMENT IN THE PLANNING AREA ...........................1654

TABLE S-9. YOUNG FOREST HABITAT DEVELOPMENT IN THE DECISION AREA .......................................................1654

TABLE S-10. YOUNG FOREST HABITAT DEVELOPMENT IN THE PLANNING AREA ...................................................1654

TABLE S-11. MATURE FOREST HABITAT DEVELOPMENT IN THE DECISION AREA ...................................................1655

TABLE S-12. MATURE FOREST HABITAT DEVELOPMENT IN THE PLANNING AREA .................................................1655

TABLE S-13. STRUCTURALLY-COMPLEX FOREST HABITAT DEVELOPMENT IN THE DECISION AREA .......................1655

TABLE S-14. STRUCTURALLY-COMPLEX FOREST HABITAT DEVELOPMENT IN THE PLANNING AREA ......................1656

TABLE S-15. EARLY SUCCESSIONAL, STAND ESTABLISHMENT, AND YOUNG STANDS WITH STRUCTURAL LEGACIES 

(1.1, 2.1, 3.1, 3.3) IN THE DECISION AREA ......................................................................................................1656

TABLE S-16. MATURE AND STRUCTURALLY-COMPLEX STANDS WITH STRUCTURAL LEGACIES (4.2, 5.1, 5.2, 5.3) IN 

THE DECISION AREA ........................................................................................................................................1656

TABLE S-17. SNAG DENSITY (TREES PER ACRE) IN THE DECISION AREA BY STRUCTURAL GROUP ..........................1658

TABLE S-18. SNAG DENSITY (TREES PER ACRE) IN THE DECISION AREA BY STRUCTURAL STAGE ...........................1658

TABLE S-19. SNAG DENSITY (TREES PER ACRE) IN THE NORTHERN DISTRICTS (COOS BAY, EUGENE, AND SALEM) BY 

STRUCTURAL GROUP ......................................................................................................................................1659

TABLE S-20. SNAG DENSITY (TREES PER ACRE) IN THE NORTHERN DISTRICTS (COOS BAY, EUGENE, AND SALEM) BY 

STRUCTURAL STAGE ........................................................................................................................................1659

TABLE S-21. SNAG DENSITY (TREES PER ACRE) IN THE SOUTHERN DISTRICTS (KLAMATH FALLS, MEDFORD, AND 

ROSEBURG) BY STRUCTURAL GROUP .............................................................................................................1660

TABLE S-22. SNAG DENSITY (TREES PER ACRE) IN THE SOUTHERN DISTRICTS (KLAMATH FALLS, MEDFORD, AND 

ROSEBURG) BY STRUCTURAL STAGE ...............................................................................................................1660

TABLE S-23. DOWN WOODY MATERIAL COVER IN THE DECISION AREA BY STRUCTURAL GROUP ........................1661

TABLE S-24. DOWN WOODY MATERIAL COVER IN THE DECISION AREA BY STRUCTURAL STAGE ..........................1661

TABLE S-25. DOWN WOODY MATERIAL COVER IN THE NORTHERN DISTRICTS (COOS BAY, EUGENE, AND SALEM) BY 

STRUCTURAL GROUP ......................................................................................................................................1661

TABLE S-26. DOWN WOODY MATERIAL COVER IN THE NORTHERN DISTRICTS (COOS BAY, EUGENE, AND SALEM) BY 

STRUCTURAL STAGE ........................................................................................................................................1662
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TABLE S-27. DOWN WOODY MATERIAL COVER IN THE SOUTHERN DISTRICTS (KLAMATH FALLS, MEDFORD, AND 

ROSEBURG) BY STRUCTURAL GROUP .............................................................................................................1662

TABLE S-28. DOWN WOODY MATERIAL COVER IN THE SOUTHERN DISTRICTS (KLAMATH FALLS, MEDFORD, AND 

ROSEBURG) BY STRUCTURAL STAGE ...............................................................................................................1663

TABLE S-29. SNAG AND DOWN WOODY MATERIAL TARGET LEVELS WITHIN THE HARVEST LAND BASE ..............1664

TABLE S-30. SNAG AND DOWN WOODY MATERIAL TARGET LEVELS WITHIN THE LATE-SUCCESSIONAL RESERVE AND 

RIPARIAN RESERVE ..........................................................................................................................................1664

TABLE S-31. SNAG AND DOWN WOODY MATERIAL DEFICITS (-) OR SURPLUS (+) WITHIN THE HARVEST LAND BASE

........................................................................................................................................................................1665

TABLE S-32. SNAG AND DOWN WOODY MATERIAL DEFICITS (-) OR SURPLUS (+) WITHIN THE LATE-SUCCESSIONAL 

RESERVE AND RIPARIAN RESERVE .................................................................................................................. 1665

TABLE S-33. HABITAT DEVELOPMENT FOR BUREAU SENSITIVE WILDLIFE SPECIES DOCUMENTED OR SUSPECTED TO 

OCCUR IN THE DECISION AREA .......................................................................................................................1667

TABLE S-34. HABITAT DEVELOPMENT FOR BUREAU STRATEGIC WILDLIFE SPECIES DOCUMENTED OR SUSPECTED TO 

OCCUR IN THE DECISION AREA .......................................................................................................................1676

TABLE S-35. SURVEY AND MANAGE WILDLIFE SPECIES: HABITAT DEVELOPMENT .................................................1682

TABLE S-36. SURVEY AND MANAGE WILDLIFE SPECIES: LAND USE ALLOCATIONS OF KNOWN SITES IN THE DECISION 

AREA ................................................................................................................................................................1689

TABLE S-37. HABITAT DEVELOPMENT FOR LANDBIRD FOCAL SPECIES ...................................................................1691

TABLE S-38. HIGH-QUALITY FORAGE HABITAT DEVELOPMENT FOR THE COLUMBIAN WHITE-TAILED DEER WITHIN 

THE RANGE OF THE LOWER COLUMBIA RIVER POPULATION IN THE DECISION AREA ...................................1698

TABLE S-39. HIGH-QUALITY FORAGE HABITAT DEVELOPMENT FOR THE COLUMBIAN WHITE-TAILED DEER WITHIN 

THE RANGE OF THE LOWER COLUMBIA RIVER POPULATION IN THE PLANNING AREA ................................. 1698

TABLE S-40. HIGH-QUALITY FORAGE HABITAT DEVELOPMENT IN CONIFER FOREST FOR THE COLUMBIAN WHITETAILED DEER WITHIN THE RANGE OF THE DOUGLAS COUNTY POPULATION IN THE DECISION AREA...........1699

TABLE S-41. HIGH-QUALITY FORAGE HABITAT DEVELOPMENT IN CONIFER FOREST FOR THE COLUMBIAN WHITETAILED DEER WITHIN THE RANGE OF THE DOUGLAS COUNTY POPULATION IN THE PLANNING AREA.........1699

TABLE S-42. HIGH-QUALITY FORAGE HABITAT DEVELOPMENT FOR DEER AND ELK IN THE DECISION AREA .........1700

TABLE S-43. HIGH-QUALITY FORAGE HABITAT DEVELOPMENT FOR DEER AND ELK IN THE PLANNING AREA .......1700

TABLE S-44. TOTAL FISHER HABITAT (DENNING, RESTING, FORAGING COMBINED) IN THE DECISION AREA ........1701

TABLE S-45. FISHER DENNING HABITAT IN THE DECISION AREA ............................................................................1701

TABLE S-46. FISHER RESTING HABITAT IN THE DECISION AREA ..............................................................................1701

TABLE S-47. FISHER FORAGING HABITAT IN THE DECISION AREA ...........................................................................1702

TABLE S-48. TOTAL FISHER HABITAT (DENNING, RESTING, FORAGING COMBINED) IN THE PLANNING AREA .......1702

TABLE S-49. FISHER DENNING HABITAT IN THE PLANNING AREA ...........................................................................1702

TABLE S-50. FISHER RESTING HABITAT IN THE PLANNING AREA ............................................................................1703

TABLE S-51. FISHER FORAGING HABITAT IN THE PLANNING AREA .........................................................................1703

TABLE S-52. LAND USE ALLOCATIONS OF FISHER HABITAT UNDER THE NO ACTION ALTERNATIVE ON BLMADMINISTERED LANDS ....................................................................................................................................1704

TABLE S-53. LAND USE ALLOCATIONS OF FISHER HABITAT UNDER ALTERNATIVE A ON BLM-ADMINISTERED LANDS

........................................................................................................................................................................1705

TABLE S-54. LAND USE ALLOCATIONS OF FISHER HABITAT UNDER ALTERNATIVE B ON BLM-ADMINISTERED LANDS

........................................................................................................................................................................1706

TABLE S-55. LAND USE ALLOCATIONS OF FISHER HABITAT UNDER ALTERNATIVE C ON BLM-ADMINISTERED LANDS

........................................................................................................................................................................1707

TABLE S-56. LAND USE ALLOCATIONS OF FISHER HABITAT UNDER ALTERNATIVE D ON BLM-ADMINISTERED LANDS

........................................................................................................................................................................1708

TABLE S-57. LAND USE ALLOCATIONS OF FISHER HABITAT UNDER THE PROPOSED RMP ON BLM-ADMINISTERED 

LANDS .............................................................................................................................................................1709

TABLE S-58. FISHER HABITAT HARVESTED BY THE END OF EACH DECADE UNDER THE NO ACTION ALTERNATIVE 

OVER 50 YEARS (2013–2063) ..........................................................................................................................1710

TABLE S-59. FISHER HABITAT HARVESTED BY THE END OF EACH DECADE UNDER ALTERNATIVE A OVER 50 YEARS 

(2013–2063). ...................................................................................................................................................1710
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TABLE S-60. FISHER HABITAT HARVESTED BY THE END OF EACH DECADE UNDER ALTERNATIVE B OVER 50 YEARS 

(2013–2063) ....................................................................................................................................................1710

TABLE S-61. FISHER HABITAT HARVESTED BY THE END OF EACH DECADE UNDER ALTERNATIVE C OVER 50 YEARS 

(2013–2063) ....................................................................................................................................................1710

TABLE S-62. FISHER HABITAT HARVESTED BY THE END OF EACH DECADE UNDER ALTERNATIVE D OVER 50 YEARS 

(2013–2063) ....................................................................................................................................................1711

TABLE S-63. FISHER HABITAT HARVESTED BY THE END OF EACH DECADE UNDER THE PROPOSED RMP OVER 50 

YEARS (2013–2063) .........................................................................................................................................1711

TABLE S-64. FISHER POPULATION IN THE PLANNING AREA UNDER THE NO ACTION ALTERNATIVE ......................1711

TABLE S-65. FISHER POPULATION IN THE PLANNING AREA UNDER ALTERNATIVE A .............................................1712

TABLE S-66. FISHER POPULATION IN THE PLANNING AREA UNDER ALTERNATIVE B .............................................1712

TABLE S-67. FISHER POPULATION IN THE PLANNING AREA UNDER ALTERNATIVE C .............................................1712

TABLE S-68. FISHER POPULATION IN THE PLANNING AREA UNDER ALTERNATIVE D .............................................1712

TABLE S-69. FISHER POPULATION IN THE PLANNING AREA UNDER THE PROPOSED RMP .....................................1713

TABLE S-70. FISHER POPULATION FORECAST IN THE PLANNING AREA UNDER THE NO TIMBER HARVEST REFERENCE 

ANALYSIS .........................................................................................................................................................1713

TABLE S-71. WOLF POPULATION, CONTROL, AND DEPREDATION IN OREGON ......................................................1714

TABLE S-72. WOLF POPULATION, CONTROL, AND DEPREDATION IN THE NORTHERN ROCKY MOUNTAIN 

POPULATION ...................................................................................................................................................1714

TABLE S-73. MARBLED MURRELET NESTING HABITAT DEVELOPMENT IN THE DECISION AREA .............................1715

TABLE S-74. MARBLED MURRELET HIGH-QUALITY NESTING HABITAT DEVELOPMENT IN THE DECISION AREA ....1715

TABLE S-75. MARBLED MURRELET NESTING HABITAT DEVELOPMENT IN THE PLANNING AREA ...........................1715

TABLE S-76. MARBLED MURRELET HIGH-QUALITY NESTING HABITAT DEVELOPMENT IN THE PLANNING AREA ..1716

TABLE S-77. LAND USE ALLOCATIONS OF MARBLED MURRELET NESTING HABITAT UNDER THE NO ACTION 

ALTERNATIVE ON BLM-ADMINISTERED LANDS ..............................................................................................1716

TABLE S-78. LAND USE ALLOCATIONS OF HIGH-QUALITY MARBLED MURRELET NESTING HABITAT UNDER THE NO 

ACTION ALTERNATIVE ON BLM-ADMINISTERED LANDS .................................................................................1716

TABLE S-79. LAND USE ALLOCATIONS OF MARBLED MURRELET NESTING HABITAT UNDER ALTERNATIVE A ON BLMADMINISTERED LANDS ....................................................................................................................................1717

TABLE S-80. LAND USE ALLOCATIONS OF HIGH-QUALITY MARBLED MURRELET NESTING HABITAT UNDER 

ALTERNATIVE A ON BLM-ADMINISTERED LANDS ...........................................................................................1717

TABLE S-81. LAND USE ALLOCATIONS OF MARBLED MURRELET NESTING HABITAT UNDER ALTERNATIVE B ON BLMADMINISTERED LANDS ....................................................................................................................................1717

TABLE S-82. LAND USE ALLOCATIONS OF HIGH-QUALITY MARBLED MURRELET NESTING HABITAT UNDER 

ALTERNATIVE B ON BLM-ADMINISTERED LANDS ...........................................................................................1718

TABLE S-83. LAND USE ALLOCATIONS OF MARBLED MURRELET NESTING HABITAT UNDER ALTERNATIVE C ON BLMADMINISTERED LANDS ....................................................................................................................................1718

TABLE S-84. LAND USE ALLOCATIONS OF HIGH-QUALITY MARBLED MURRELET NESTING HABITAT UNDER 

ALTERNATIVE C ON BLM-ADMINISTERED LANDS ...........................................................................................1718

TABLE S-85. LAND USE ALLOCATIONS OF MARBLED MURRELET NESTING HABITAT UNDER ALTERNATIVE D ON BLMADMINISTERED LANDS ....................................................................................................................................1719

TABLE S-86. LAND USE ALLOCATIONS OF HIGH-QUALITY MARBLED MURRELET NESTING HABITAT UNDER 

ALTERNATIVE D ON BLM-ADMINISTERED LANDS ...........................................................................................1719

TABLE S-87. LAND USE ALLOCATIONS OF MARBLED MURRELET NESTING HABITAT UNDER THE PROPOSED RMP ON 

BLM-ADMINISTERED LANDS ...........................................................................................................................1720

TABLE S-88. LAND USE ALLOCATIONS OF HIGH-QUALITY MARBLED MURRELET NESTING HABITAT UNDER THE 

PROPOSED RMP ON BLM-ADMINISTERED LANDS ..........................................................................................1720

TABLE S-89. INTERPRETATION OF THE KAPPA STATISTIC ........................................................................................1720

TABLE S-90. CROSS-TABULATION OF STRUCTURAL STAGES USED IN THE PROPOSED RMP/FINAL EIS COMPARED 

WITH HABITAT CLASSES FROM FALXA AND RAPHAEL (2015) .........................................................................1722

TABLE S-91. CROSS-TABULATION OF MARBLED MURRELET HABITAT CLASS (FROM RACHAEL ET AL. 2015) HIGHQUALITY VS. NON-HIGH QUALITY NESTING HABITAT .....................................................................................1723
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TABLE S-92. CROSS-TABULATION OF MARBLED MURRELET HABITAT CLASS (FROM RAPHAEL ET AL. 2015) HIGHQUALITY NESTING HABITAT, LOW-QUALITY NESTING HABITAT, AND NON-HABITAT ....................................1723

TABLE S-93. CROSS-TABULATION OF MARBLED MURRELET HABITAT CLASS (FROM RAPHAEL ET AL. 2015) NESTING 

HABITAT VS. NON-HABITAT ............................................................................................................................1724

TABLE S-94. MARBLED MURRELET NESTING HABITAT DEVELOPMENT IN DESIGNATED CRITICAL HABITAT IN THE 

DECISION AREA ...............................................................................................................................................1725

TABLE S-95. MARBLED MURRELET HIGH-QUALITY NESTING HABITAT DEVELOPMENT IN DESIGNATED CRITICAL 

HABITAT IN THE DECISION AREA ....................................................................................................................1725

TABLE S-96. MARBLED MURRELET HIGH-QUALITY NESTING HABITAT DEVELOPMENT IN DESIGNATED CRITICAL 

HABITAT IN THE PLANNING AREA ................................................................................................................... 1725

TABLE S-97. LAND USE ALLOCATIONS OF DESIGNATED MARBLED MURRELET CRITICAL HABITAT ........................1726

TABLE S-98. LAND USE ALLOCATIONS OF DESIGNATED MARBLED MURRELET CRITICAL HABITAT WITHIN ZONE 1

........................................................................................................................................................................1726

TABLE S-99. LAND USE ALLOCATIONS OF DESIGNATED MARBLED MURRELET CRITICAL HABITAT WITHIN ZONE 2

........................................................................................................................................................................1726

TABLE S-100. KNOWN MARBLED MURRELET SITES AND PAST SURVEY EFFORT IN THE PLANNING AREA .............1727

TABLE S-101. DECADAL FORECAST (2013–2063) OF MARBLED MURRELET OCCUPIED SITES DISCOVERED OR LOST 

UNDER THE NO ACTION ALTERNATIVE ...........................................................................................................1727

TABLE S-102. DECADAL FORECAST (2013–2063) OF MARBLED MURRELET OCCUPIED SITES DISCOVERED OR LOST 

UNDER ALTERNATIVE A...................................................................................................................................1728

TABLE S-103. DECADAL FORECAST (2013–2063) OF MARBLED MURRELET OCCUPIED SITES DISCOVERED OR LOST 

UNDER ALTERNATIVE B ...................................................................................................................................1728

TABLE S-104. DECADAL FORECAST (2013–2063) OF MARBLED MURRELET OCCUPIED SITES DISCOVERED OR LOST 

UNDER ALTERNATIVE C ...................................................................................................................................1729

TABLE S-105. DECADAL FORECAST (2013–2063) OF MARBLED MURRELET OCCUPIED SITES DISCOVERED OR LOST 

UNDER ALTERNATIVE D ..................................................................................................................................1729

TABLE S-106. DECADAL FORECAST (2013–2063) OF MARBLED MURRELET OCCUPIED SITES DISCOVERED OR LOST 

UNDER THE PROPOSED RMP ..........................................................................................................................1730

TABLE S-107. DECADAL FORECAST (2013–2063) OF MARBLED MURRELET OCCUPIED SITES EXPECTED UNDER THE 

NO HARVEST REFERENCE ANALYSIS................................................................................................................1730

TABLE S-108. NORTH OREGON COAST DPS OF THE RED TREE VOLE HABITAT DEVELOPMENT IN THE DECISION AREA

........................................................................................................................................................................1730

TABLE S-109. NORTH OREGON COAST DPS OF THE RED TREE VOLE HABITAT DEVELOPMENT IN THE PLANNING 

AREA ................................................................................................................................................................1731

TABLE S-110. NORTH OREGON COAST DPS OF THE RED TREE VOLE HABITAT IN THE HARVEST LAND BASE .........1731

TABLE S-111. RE-CLASSIFICATION OF NON-FOREST HABITATS FROM GNN ............................................................1732

TABLE S-112. NON-FOREST HABITAT WITHIN THE DECISION AND PLANNING AREAS ............................................1734

TABLE S-113. CROSS-WALK OF GNN STRUCCOND TO WOODSTOCK STRUCTURAL STAGES ...................................1735

TABLE S-114. ASSUMPTIONS FOR DEVELOPMENT OF STRUCTURAL STAGES ON NON-BLM-ADMINISTERED LANDS

........................................................................................................................................................................1736

TABLE T-1. MODEL 13 VARIABLES AND PERCENT CONTRIBUTIONS BY MODELING REGION..................................1758

TABLE T-2. METRICS, CALCULATED FROM DATA DEVELOPED BY DAVIS ET AL. (2011), USED TO FORECAST DECADAL 

(1996–2006) LOSSES OF NORTHERN SPOTTED OWL DISPERSAL AND NESTING-ROOSTING HABITAT FROM 

TIMBER HARVEST ON LANDS OTHER THAN BLM-ADMINISTERED LANDS IN THE PLANNING AREA ...............1768

TABLE T-3. CHANGES, CALCULATED FROM DATA DEVELOPED BY DAVIS ET AL. (2011), IN RELATIVE HABITAT 

SUITABILITY VALUES FROM TIMBER HARVESTS OCCURRING IN NORTHERN SPOTTED OWL HABITAT BETWEEN 

1996 AND 2006 BY PHYSIOGRAPHIC PROVINCE AND NORTHWEST FOREST PLAN LAND USE ALLOCATION ..1770

TABLE T-4. A COMPARISON OF THE ESTIMATED ACRES OF NORTHERN SPOTTED OWL NESTING-ROOSTING HABITAT 

ON FEDERAL LANDS AS CALCULATED BY THE U.S. FOREST SERVICE AND THE BLM .......................................1772

TABLE T-5. A COMPARISON OF THE ESTIMATED ACRES OF NORTHERN SPOTTED OWL DISPERSAL HABITAT ON ALL 

LANDS IN WESTERN OREGON AS CALCULATED BY THE U.S. FOREST SERVICE AND BY THE BLM ...................1774
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TABLE T-6. A COMPARISON OF DECADAL RATES OF CHANGE IN RELATIVE HABITAT SUITABILITY VALUE ON NONFEDERAL LANDS FROM LARGE WILDFIRES, TIMBER HARVEST AND FOREST INGROWTH, BY STRENGTH-OFSELECTION CATEGORY AND PHYSIOGRAPHIC PROVINCE, USING FOUR METHODS DESCRIBED IN THE TEXT 1779

TABLE T-7. BARRED OWL ENCOUNTER RATES USED BY THE BLM FOR THE DRAFT RMP/EIS AND PROPOSED 

RMP/FINAL EIS ................................................................................................................................................1787

TABLE U-1. ALL ELIGIBLE WILD AND SCENIC RIVER SEGMENTS WITHIN THE DECISION AREA ................................1794

TABLE U-2. ELIGIBLE RIVERS WITHIN THE DECISION AREA THAT THE BLM IDENTIFIED AS MEETING SUITABILITY 

CRITERIA ..........................................................................................................................................................1796

TABLE U-3. LITTLE NORTH SANTIAM RIVER STUDY SEGMENT ................................................................................1797

TABLE U-4. NORTH FORK SILETZ RIVER STUDY SEGMENT .......................................................................................1797

TABLE U-5. ROGUE RIVER STUDY SEGMENT ...........................................................................................................1797

TABLE U-6. SANDY RIVER STUDY SEGMENT ............................................................................................................1798

TABLE U-7. TABLE ROCK FORK MOLALLA RIVER STUDY SEGMENT .........................................................................1798

TABLE U-8. WEST FORK ILLINOIS RIVER STUDY SEGMENT ......................................................................................1798

TABLE V-1. EXAMPLE OF TABLE 1–FUNCTIONING CONDITION STATUS FROM USDI TR-1737-9 (1993) .................1813

TABLE V-2. DECADE 1 MODELED ACRES BY TREATMENT TYPE BY HARVEST LAND BASE SUB-ALLOCATION ..........1825

TABLE V-3. DECADE 2 MODELED ACRES BY TREATMENT TYPE BY HARVEST LAND BASE SUB-ALLOCATION ..........1826

TABLE V-4. MARBLED MURRELET SURVEY REPORTING ..........................................................................................1829

TABLE V-5. MARBLED MURRELET OCCUPIED SITE ..................................................................................................1829

TABLE V-6. MARBLED MURRELET NESTING HABITAT MODIFIED OR REMOVED WITHOUT SURVEYS ....................1829

TABLE V-7. SURVEY REPORTING FOR THE NORTH OREGON COAST DPS OF THE RED TREE VOLE ..........................1830

TABLE W-1. COMPARISON OF NORTHWEST FOREST PLAN AQUATIC CONSERVATION STRATEGY OBJECTIVES AND 

THE PROPOSED RMP .......................................................................................................................................1842

Table of Maps 

MAP F-1. AREAS OF CRITICAL ENVIRONMENTAL CONCERN WITHIN THE PLANNING AREA ...................................1250

MAP R-1. TRIBAL LANDS OF THE CONFEDERATED TRIBES OF THE COOS, LOWER UMPQUA, AND SIUSLAW INDIANS

........................................................................................................................................................................1616

MAP R-2. TRIBAL LANDS OF THE CONFEDERATED TRIBES OF GRANDE RONDE .....................................................1618

MAP R-3. TRIBAL LANDS OF THE CONFEDERATED TRIBES OF SILETZ INDIANS .......................................................1622

MAP R-4. ANCESTRAL HOMELANDS AND AREAS OF SPECIAL INTEREST TO THE COQUILLE INDIAN TRIBE ............1625

MAP R-5. TRIBAL LANDS OF THE COW CREEK BAND OF UMPQUA TRIBE OF INDIANS ...........................................1627

MAP R-6. TRIBAL LANDS OF THE KLAMATH TRIBES ................................................................................................1630

MAP U-1. LITTLE NORTH SANTIAM RIVER STUDY SEGMENT ..................................................................................1799

MAP U-2. NORTH FORK SILETZ RIVER STUDY SEGMENT .........................................................................................1800

MAP U-3. ROGUE RIVER STUDY SEGMENT ..............................................................................................................1801

MAP U-4. SANDY RIVER STUDY SEGMENT ..............................................................................................................1802

MAP U-5. TABLE ROCK FORK – MOLALLA RIVER STUDY SEGMENT .........................................................................1803

MAP U-6. WEST FORK ILLINOIS RIVER STUDY SEGMENT ........................................................................................1804
1489 | P a g e

Appendix O – Recreation 

Table O-1. Recreation Management Areas within the decision area by alternative and the Proposed RMP 

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

Coos Bay

1 Bastendorff Beach SRMA 39 39 39 39 39

2 Blue Ridge Trail System ERMA - 1,405 1,405 1,405 1,405

3 Coos Head SRMA - - 11 11 60

4 Dean Creek Elk Viewing Area SRMA 14 14 14 1,146 1,146

5 Doerner Fir Trail ERMA - 17 17 17 17

6 Edson Creek Campground SRMA 46 45 45 45 45

7 Euphoria Ridge Trail ERMA - - - 473 -

342 East Fork Illinois Trails* ERMA - - - - 1,440

8 Fawn Creek Campground SRMA 3 3 3 3 3

9 Floras Lake ERMA - 50 50 50 50

10 Hinsdale Garden SRMA 11 11 11 11 11

11 Hunter Creek Trail System ERMA - 1,408 198 198 198

12 Loon Lake Recreation Area SRMA 77 76 76 76 76

13 Lost Lake SRMA - 14 - - -

14 North Spit Beach and Ponds Unit ERMA - - 336 336 -

15 North Spit Boat Ramp SRMA 5 5 5 5 5

16 North Spit Trail System ERMA - 1,317 1,317 - 1,505

17 Park Creek Campground SRMA 4 4 4 4 4

18 Rocky Peak Trail ERMA - 1,948 1,948 1,948 1,948

19 Sixes River Campground SRMA 27 27 27 27 27

20 Smith River Corridor ERMA - - 9,505 9,505 9,505

21 Smith River Falls Campground SRMA 4 4 4 4 4

22 Storm Ranch SRMA 235 236 236 236 236

23 Vincent Creek Campground SMRA 4 4 4 4 4

24 Wasson Creek ERMA - - - 5,813 5,811

343 West Laverne Park Campground SRMA 24 24 24 24 24

Eugene

25 Barlow Creek Trail and Trailhead ERMA - - - 100 -

26 Calapooya Divide Backcountry 

Byway ERMA - - 270 270 225

27 Carpenter Bypass Mountain Bike 

Trail ERMA - 1,160 1,160 1,160 1,160

28 Carpenter Bypass Staging Area SRMA 1 1 1 1 1

29 Cascade View OHV Complex SRMA 6 6 6 6 6

30 Clay Creek Recreation Site SRMA 10 10 10 10 10

31 Clay Creek Trail ERMA - 14 14 14 14

32 Coburg Hiking Trail System ERMA - - 2,019 2,019 1,940

33 Coburg Hills Backcountry Byway ERMA - - 79 79 79

34 Crooked Creek OHV Staging Site SRMA 1 1 1 1 1

35 Culp Creek Expansion Site SRMA - - - <1 -

36 Culp Creek Trailhead SRMA 1 <1 <1 <1 <1

37 Dorena Dam Trail Access Site SRMA 3 1 1 1 1

38 Eagles Rest Hiking/Biking Trail ERMA - 3 3 3 3

39 Esmond Lake Trailhead and Trail ERMA - - - 158 -

40 Hult Equestrian Staging Area SRMA - 1 1 1 1

41 Hult Reservoir Non-motorized Trail ERMA - 213 213 213 213
1490 | P a g e

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

42 Hult Reservoir Recreation Area SRMA 21 21 21 21 21

43 Lost Creek Backcountry Byway ERMA - - 145 145 145

44 Lost Creek Trails ERMA - 20 20 20 20

45 Low Pass OHV Emphasis Area ERMA - - 511 511 -

46 Lower Lake Creek Falls SRMA 2 2 2 2 2

47 Martin Rapids Overlook SRMA 3 3 3 3 3

48 McGowan Creek Environmental 

Education Area Trail ERMA - 80 80 80 91

49 McGowan Creek Environmental 

Education Area SRMA 1 1 1 1 1

50 McKenzie River Campground SRMA - - 146 146 146

51 McKenzie River Dispersed 

Recreation Corridor ERMA - - 276 276 276

52 McKercher Park SRMA 2 <1 <1 <1 <1

53 Mosby Creek Trailhead SRMA 10 10 10 10 10

54 North Bowl Campground ERMA - - 83 83 83

55 Rennie Boat Landing SRMA 1 1 1 1 1

56 Row River Trail ERMA - 67 67 67 67

57 Row River Trail Expansion ERMA - - 3 3 32

58 Sharps Creek Expansion Site ERMA - - - 5 -

59 Sharps Creek Recreation Site SRMA 3 3 3 3 3

60 Shotgun Creek Backcountry Byway ERMA - - 169 169 169

61 Shotgun Creek Recreation Site SRMA 16 16 16 16 16

62 Shotgun Non-Motorized Trail 

System ERMA - 64 64 64 64

63 Shotgun OHV Trail System ERMA - 5,755 5,753 5,753 5,753

64 Silver Creek Boat and McKenzie 

River Watchable Wildlife Site SRMA 2 1 1 1 1

65 Siuslaw Bend Campground ERMA - - - 483 -

66 Siuslaw River SRMA - - - 8,403 -

67 Smith Creek SRMA 3 1 1 1 1

68 Taylor Landing Recreation Site SRMA 3 3 3 3 3

69 Tyrrell Seed Orchard Interpretive 

Trail ERMA - 8 8 8 8

70 Upper Lake Creek ERMA - 13,021 13,021 13,021 12,486

71 Whitewater Day Use Area SRMA 8 6 6 6 6

72 Whittaker Creek Recreation Area SRMA 2 2 2 2 2

73 Whittaker Creek Trail ERMA - 13 13 13 13

74 Willamalane Non-Motorized Trails ERMA - - - 1,057 1,057

75 Willamette River Greenway SRMA 4 4 4 4 4

76 Wolf Creek Environmental 

Education Site and Trail ERMA - - - 549 -

Klamath Falls

77 Barnes Valley Boat Ramp ERMA 8 8 8 8 -

78 Bryant Mountain ERMA - - 9,086 9,094 9.094

79 Frog Camp SRMA 7 7 7 7 -

80 Gerber ERMA - 41,332 41,332 39,917 39,908

81 Gerber Recreation Area SRMA 473 272 272 272 272

82 Hogback Mountain SRMA - 2,284 2,284 - 2,284

83 KFRA ERMA - - - 140,576 -

84 Klamath River Campground SRMA 38 26 26 26 24

85 Klamath River WSR ERMA - 2,663 2,663 2,663 2,634
1491 | P a g e

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

86 Lower Klamath Hills

B=E, 

C,D=S, 

PRMP=E

- 1,596 1,596 1,596 1,596

87 Miller Creek Camp SRMA 2 2 2 2 2

88 North Bryant Mountain SRMA - - 5 - -

89 Pacific Crest Trail Corridor SRMA 7 7 7 7 659

90 Potholes Camp SRMA 8 8 8 8 8

91 South Bryant Mountain SRMA - - 3 - -

92 Spring Island River Access SRMA 6 2 2 2 2

93 Stan H Spring SRMA 6 2 2 - 2

94 Stukel Mountain

C=E, 

D=S, 

PRMP=

E

- - 9,622 9,622 9,622

95 Surveyor Campground SRMA 28 28 28 28 27

96 Surveyor Mountain ERMA - 18,033 18,033 - 17,377

97 Swan Lake Rim ERMA - - 9,106 9,106 9,106

98 Topsy Recreation Site SRMA 14 14 14 14 14

99 Willow Valley Reservoir Boat 

Ramp SRMA 12 12 12 12 12

100 Wood River Wetland A,C,D=S, 

B=E 1 3,174 3,174 3,174 -

Medford

101 Anderson-Little Apple ERMA - - 7,483 7,483 7,482

102 Anderson Addition ERMA - - 10,076 10,076 10,076

103 Armstrong Gulch Trailhead SRMA 1 1 1 1 -

104 Baker Cypress Trail ERMA - 3 3 3 3

105 Bald-Wagon ERMA - - 3,124 - 3,124

344 Beacon Hill* ERMA - - - - 4,617

106 Beacon Hill Trail ERMA - 12 12 12 12

107 Bear Gulch Trailhead SRMA <1 <1 <1 <1 -

108 Bell Forest ERMA - - 3,800 - 3,800

109 Bolt Mountain Trail ERMA - 10 392 392 392

110 Buck-Berry Rock ERMA - - 6,504 6,504 6,504

111 Buck Prairie II XC Ski Trailhead SRMA 1 1 1 1 -

112 Buck Prairie II XC Ski Trails SRMA - 967 - - -

113 Buck Prairie Toilet SRMA <1 <1 <1 <1 -

114 Buck Prairie XC Ski Trails SRMA - 967 - - -

115 Buck Prairie/Hyatt ERMA - - 11,845 16,817 9,927

116 Buckhorn Mountain ERMA - - 8,284 8,284 8,206

117 Bunny Meadows

A=S, 

B,C,D=E, 

PRMP=E

8 8 8 8 8

118 Burma Pond Campground and 

Trailhead SRMA 2 2 2 2 9

119 Burma Pond Trail ERMA - 4 4 4 -

120 Cathedral Hills Trail System

B=E, 

C,D=S, 

PRMP=S

- 545 546 546 546

121 Chicken Foot SRMA <1 - - - -

122 China Gulch SRMA <1 - - - -

123 Cow Creek Backcountry Byway ERMA - 88 - - 41

124 Coyote Creek OHV Area ERMA - - - 14,569 -
1492 | P a g e

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

125 Deer Creek Education/Interpretive 

Area SRMA - - 41 41 41

126 Deming Gulch Equestrian Trailhead SRMA 1 1 - - -

127 Deming Gulch Trailhead SRMA <1 <1 - - -

128 East Applegate Ridge Trail ERMA - - 44 44 44

129 East Fork Illinois Trails C=E, 

D=S - - 1,441 1,441 -

130 Eight Dollar Accessible Boardwalk 

Trailhead SRMA <1 - - - -

131 Eight Dollar Mountain ERMA - - 2,095 2,134 2,134

132 Eight Dollar Mountain Boardwalk 

Trail ERMA - 1 - - -

133 Eight Dollar Mountain Interpretive 

Site ERMA - - - 39 -

134 Eight Dollar Mountain Parking Area SRMA <1 <1 - - -

135 Elderberry Flat Campground SRMA 23 23 23 23 23

136 Enchanted-Timber ERMA - - - 13,774 -

137 Enchanted Forest and Felton Trails ERMA - 36 37 37 38

138 Enchanted Forest Trailhead SRMA 2 2 - - -

139 Enchanted Well ERMA - - - 8,641 -

140 Espy Trailhead SRMA 1 1 - - -

141 Evans Creek Hang Gliding Launch 

Site ERMA - - - 26 -

142 Galice Hellgate Backcountry Byway ERMA - 258 258 258 258

143 Gold Nugget Waysides SRMA 11 11 49 49 49

144 Grants Pass Peak Non-motorized 

Trails ERMA - - 11,927 11,834 11,923

145 Grave Creek to Marial Backcountry 

Byway ERMA - 348 348 348 348

146 Grayback Mountain Trail ERMA - 76 76 76 77

147 Grayback Mountain Trailhead SRMA <1 <1 <1 <1 -

148 Green Springs Mtn. Loop Trailhead SRMA <1 <1 - - -

149 Green Top Mountain ERMA - - - 5,316 5,316

150 Grizzly Peak SRMA - - - 3,593 -

151 Grizzly Peak Trail SRMA - - 2,954 - 2,951

152 Grizzly Peak Trailhead SRMA 1 506 - - -

153 Hidden Creek Trail ERMA - 7 7 7 7

154 Hidden Creek Trailhead SRMA <1 - - - -

155 Hyatt Lake Campground SRMA 37 149 149 149 52

156 Hyatt Watchable Wildlife Site SRMA - 2 2 2 -

157 Illinois Forks Park ERMA - - 79 79 77

158 Isabella SRMA <1 - - - -

159 Jack Ash Trail and Connector Trail ERMA - - 203 203 203

160 Jackson Creek ERMA - - 507 - 507

161 Jacksonville Woodlands Trailhead SRMA 1 1 - - -

162 Jacksonville Woodlands Trails ERMA - 105 103 103 103

163 Jeffrey Pine Loop Trail ERMA - 4 - - -

164 Kane Creek SRMA <1 - - - -

165 Kenney Meadows Recreation Site SRMA 20 20 20 20 20

166 Kerby ERMA - - 654 654 654

167 Kerby Peak Trail ERMA - 36 36 36 36
1493 | P a g e

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

168 Kerby Peak Trailhead SRMA <1 <1 <1 <1 -

169 King Mountain Trail SRMA - 5 5 5 6

170 King Mountain Trailhead SRMA 1 1 1 1 -

171 Lake Selmac Trails

B=E, 

C,D=S, 

PRMP=

S

- 440 443 443 443

172 Layton Ditch Trail ERMA - 43 -

173 Layton Ditch Trailhead SRMA <1 - - - -

174 Left Right Center Foots ERMA - - 7,657 7,657 7,651

175 Little Applegate Trailhead SRMA 1 1 - - -

176 Lodgepole SRMA <1 <1 <1 <1 <1

177 Logan Cut ERMA - - 527 527 526

178 London Peak Trail ERMA - 14 14 14 15

179 Lower Table Rock Trailhead SRMA 2 - - - -

180 Medco Railroad Trail ERMA - - - 106 106

181 Mount Bolivar Trailhead SRMA <1 <1 <1 <1 <1

182 Mountain of the Rogue SRMA - - 5,069 5,069 5,069

183 Mungers Butte ERMA - - 11,873 11,873 11,873

184 Northwest Hills ERMA - - 480 2,620 2,341

185 Nugget Falls ERMA - 5 - - -

186 Pacific Crest Trail 1 and 2 SRMA 1,094 955 951 951 6,161

187 Pacific Crest Trailhead at Little 

Hyatt Lake SRMA <1 - - - -

188 Provolt Seed Orchard SRMA - - 295 295 294

189 Quartz Creek OHV Area SRMA - - 8,344 8,344 8,344

190 Rainie Falls Overlook SRMA 1 1 <1 <1 -

191 Rattlesnake ERMA - 21 56 56 56

192 Rock Creek Trails ERMA - - 6,793 6,793 5,706

193 Rockydale ERMA - - 186 186 186

194 Rogue Greenway ERMA - - 370 370 370

195 Rogue Timber ERMA - - 7,906 - 7,902

196 Rogue Wild and Scenic River SRMA 15,949 11,409 11,409 11,409 11,395

197 Rough and Ready Trail ERMA - 2 2 2 2

198 Roundtop Mountain SRMA - - 13,168 13,168 13,168

199 Section 29 ERMA - - 203 203 202

200 Silver Creek ERMA - - 57 57 57

201 Skull Creek Campground SRMA 8 7 7 7 7

202 Skycrest Trailhead SRMA <1 <1 - - -

203 Sterling Mine Ditch Trail SRMA - 1,322 1,279 1,279 1,280

204 Table Mountain Snow Play Area SRMA 9 9 9 9 9

205 Table Rock Trailheads SRMA - 4 - - -

206 Table Rock Trails ERMA - 52 - - -

207 Table Rocks SRMA - - 1,329 1,329 1,282

208 Thompson-Cantrall ERMA - - 23,317 23,317 23,317

209 Timber Mountain Recreation Area ERMA - 10,160 - - -

210 Tucker Flat Campground SRMA 9 8 8 8 12

211 Tunnel Ridge Trailhead SRMA 1 1 - - -

212 Upper Table Rock Trailhead SRMA 2 - - - -

213 Wagner Creek Trail ERMA - 2 2 2 2
1494 | P a g e

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

214 Wagner Creek Trailhead SRMA <1 <1 - - -

215 Wellington Mine Trail ERMA - - 44 44 45

216 West Applegate Ridge Trail ERMA - - - 210 -

217 West Fork Evans Creek ERMA - - 3,042 3,042 3,042

218 Whiskey Creek Overlook SRMA <1 <1 <1 <1 <1

219 Wild Rogue Canyon ERMA - - - 50,451 50,451

220 Wildcat Campground and Horse 

Camp SRMA - 47 47 47 -

221 Williams Creek Wayside SRMA 1 1 - - -

222 Wolf Gap Trailhead SRMA 1 1 - - -

223 Woodrat ERMA - - 3,876 3,876 3,876

224 Woodrat Mtn. Gliding Sites SRMA 7 7 - - 7

Roseburg

225 Baker Park SRMA 12 12 12 12 -

226 Bohemia Trail ERMA - - - 16 -

227 Boomer Hill OHV ERMA - - 4,635 4,635 -

345 Calapooya Divide Backcountry 

Byway*

ERMA - - - - 44

228 Cavitt Creek Falls Recreation Site SRMA 16 16 16 16 16

229 China Ditch ERMA - 62 62 62 61

230 Cow Creek Backcountry Byway ERMA - - 88 88 88

231 Cow Creek Backcountry Byway 

Kiosk SRMA 1 1 1 1 1

232 Cow Creek Recreation Gold 

Panning Area SRMA 4 4 4 4 4

233 E-Mile Day-Use Area SRMA 5 5 5 5 5

234 Eagleview Group Campground SRMA 12 12 12 12 12

235 Emerald Trail B=E, 

C,D=S - 17 17 17 -

236 Hill Creek Trail B=E, 

CD=S - 2 2 2 -

237 Hill Creek Wayside SRMA 1 1 1 1 -

238 Honeycombs ERMA - - - 63 4

239 Hubbard Creek OHV ERMA - - 11,587 11,587 11,583

240 Island Creek Day-Use Area SRMA 1 1 28 28 28

241 Lone Pine Group Campground SRMA 9 9 9 9 -

242 Lone Rock Drift Boat Launch SRMA 2 <1 <1 <1 1

243 Millpond/Lone Pine Recreation Site SRMA - - 23 23 52

244 Millpond Recreation Site SRMA 21 21 - - -

245 Narrows ERMA - - 16 16 16

246 North Bank-West Entrance SRMA 1 1 1 1 2

247 North Bank-Comstock Day Use 

Area SRMA 2 2 2 2 2

248 North Bank Habitat Management 

Area ERMA - 6,586 6,586 6,586 6,523

249 North Umpqua Trail-Swiftwater B=E, 

C,D=S - 65 65 65 -

250 North Umpqua Trail-Tioga B=E, 

C,D=S - 33 33 33 -

251 North Umpqua Wild Scenic River 

Corridor SRMA - - 2,058 2,058 2,058

252 Olalla Creek OHV ERMA - - 4,752 4,752 -
1495 | P a g e

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

253 Osprey Boat Ramp SRMA 2 3 3 3 3

254 Red Top Pond ERMA - 11 11 11 12

255 Rock Creek Recreation Site SRMA 19 19 21 21 22

256 Rock Creek Trail ERMA - - - 14 -

257 Sawmill Trail B=E, 

C,D=S - 20 20 20 -

258 Scaredman Recreation Site SRMA 10 10 10 10 10

259 Smith River Corridor-Roseburg ERMA - - 140 140 140

260 South Fork Deer Creek OHV ERMA - - 1,402 1,402 -

261 South Umpqua ERMA - - - 4 -

262 Stick Beach B=E, 

C,D=S - 1 1 1 -

263 Susan Creek Day Use Area SRMA 2 2 2 2 -

264 Susan Creek Falls Trail B=E, 

C,D=S - 8 8 8 -

265 Susan Creek Falls Trailhead SRMA 1 1 1 1 -

266 Susan Creek Recreation Site SRMA 25 25 25 25 -

267 Swiftwater Day-Use Area SRMA 4 4 4 4 4

268 Swiftwater Trailhead SRMA 2 2 2 2 -

269 Tinhat Pond ERMA - - - 5 -

270 Tyee Recreation Area SRMA 14 14 14 14 14

271 Upper Susan Creek Falls Trail ERMA - - - 1,318 53

272 White Rock OHV Area ERMA - - 9,846 9,846 -

273 Wolf Creek Falls Trail

B=E, 

D,

PRMP=

S, 

- 14 - 14 16

274 Wolf Creek Falls Trailhead SRMA 2 2 - 2 -

275 Wolf Creek Falls Trailhead and 

Trail SRMA - - 16 - -

Salem

276 Alder Glen SRMA 5 - - - -

277 Alder Glen Campground SRMA - 4 4 4 -

278 Alsea Falls Hiking Trails ERMA - 272 272 272 -

279 Alsea Falls Recreation Site SRMA 36 31 31 31 -

280 Alsea Falls Shared Use Trail System SRMA - 1,510 2,923 2,923 -

346 Alsea Falls* SRMA - - - - 3,226

281 Aquila Vista SRMA 178 178 178 178 178

282 Baty Butte Trail ERMA - 551 - - 551

283 Canyon Creek SRMA 13 13 13 13 13

284 Cedar Grove SRMA 5 5 5 5 5

285 Crabtree Valley ERMA - - 914 914 584

286 Crazy Cougar ERMA - - 1,444 1,444 1,312

287 Crooked Finger ERMA - - - 451 451

288 Crown Zellerbach Trail (CZ 

Mainline) ERMA - - 23 23 23

289 Dogwood SRMA 6 6 6 6 6

290 Dovre SRMA 4 4 4 4 -

291 Eagle Creek Trail ERMA - 160 160 160 160

292 Elk Bend SRMA 4 4 4 4 -

293 Elkhorn Creek WSR ERMA - - - 1,103 1,103

294 Elkhorn Valley Campground SRMA 78 78 78 78 78

295 Fan Creek SRMA 3 3 3 3 -

296 Fishermen’s Bend Recreation Site SRMA 183 184 184 184 184
1496 | P a g e

District/

Field 

Office

Location

No. on 

Figures 

O-1 to 

O-6

RMA Name RMA 

Type

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

297 Green Peter Peninsula ERMA - - 1,557 2,056 2,055

298 High Peak-Grindstone ERMA - - - 976 -

299 Highland ERMA - - - 844 844

300 Ivors Wayside SRMA 2 2 2 2 2

301 Kilchis Glider Launch Site ERMA - - 38 38 -

302 Little North Fork Wilson ERMA - - 1,160 1,160 -

303 Marmot Recreation Site SRMA - 26 92 92 92

304 Marmot Trail System ERMA - - 576 - 530

305 Mary’s Peak ERMA - - - 3,774 3,759

306 Mill Creek SRMA 6 6 469 6 -

307 Mill Creek-Gooseneck ERMA - - 7,416 7,878 7,300

347 Mill Creek Recreation Site* SRMA - - - - 469

308 Missouri Bend SRMA 3 3 3 3 3

348 Mountaindale* ERMA - - - - 199

309 Table Rock Fork – Molalla River ERMA - 5,907 13,997 19,906 19,353

310 Monument Peak Trail System ERMA - 909 909 909 909

311 Nasty Rock Trail ERMA - 135 135 135 135

349 Nestucca River* SRMA - - - - 134

312 Nestucca Backcountry Byway ERMA - 323 322 322 204

313 North Fork Eagle Creek 

Campground SRMA - - - 68 68

314 North Fork Santiam County Park SRMA 12 12 12 12 12

315 Old Miner’s Meadow SRMA 3 3 - 3 3

316 Oxbow Regional Park SRMA 265 260 260 260 260

317 Pacific City ERMA - - 79 79 63

318 Quartzville Backcountry Byway ERMA - 34 34 34 34

319 Quartzville Creek and Yellowstone 

Trail ERMA - - 2,731 2,727 2,727

320 Quartzville Creek Corridor ERMA - 2,060 - - -

322 Salmonberry Rail to Trail ERMA - - 14 14 14

321 Sandy-Salmon WSR Corridor ERMA - 785 - - -

323 Sandy-Salmon River Corridor ERMA - - 1,824 2,400 1,870

324 Sandy Ridge Trail System SRMA - 1,260 2,239 3,802 3,802

325 Sandy Ridge Trailhead SRMA 29 29 52 52 52

326 Scaponia Park SRMA 8 8 8 8 8

327 Shellburg Trail System ERMA - - 283 283 283

328 Sheridan Peak Overlook SRMA 4 3 3 3 3

329 Silver Falls State Park SRMA 237 237 237 237 237

330 Snow Peak/Neal Creek ERMA - - - 6,763 6,757

331 South Fork Alsea Backcountry 

Byway ERMA - 88 88 88 88

332 South Fork Clackamas Waterfalls ERMA - - - 1,116 1,116

333 Table Rock Wilderness-Pechuck 

Lookout ERMA - 6,171 6,171 6,171 6,171

350 Tillamook Ridge-Little North Fork 

Wilson*

ERMA - - - - 5,745

334 Three Bears-Hardy Creek SRMA 14 14 14 14 14

335 Upper Nestucca OHV Trail System ERMA - 6,713 6,494 10,663 7,633

336 Wildcat Creek ERMA - - - 2,444 -

337 Wildcat Creek Trail System SRMA - - 2,444 - 2,444

338 Wildwood Recreation Site SRMA 311 553 553 553 553

339 Wilhoit Springs ERMA - - - 571 561

340 Yaquina Head ONA SRMA 91 91 91 91 91

341 Yellowbottom SRMA 13 13 13 13 13
1497 | P a g e

* Denotes Recreation Management Areas (RMAs) in the Proposed Resource Management Plan (PRMP) with different names and 

spatial extents then RMAs identified in the action alternatives. The Proposed RMP combined several RMAs or split RMAs where 

necessary to logically manage recreation opportunities and protect similar recreation setting characteristics when compared to 

RMA boundaries in the action alternatives. 
1498 | Page

Figure O-1. Coos Bay District Recreation Management Area locations 
1499 | Page

Figure O-2. Eugene District Recreation Management Area locations 
1500 | Page

Figure O-3. Klamath Falls Field Office Recreation Management Area locations 
1501 | Page

Figure O-4. Medford District Recreation Management Area locations 
1502 | Page

Figure O-5. Roseburg District Recreation Management Area locations 
1503 | Page

Figure O-6. Salem District Recreation Management Area locations 

More information on RMA Frameworks is located on the BLM web site at 

http://www.blm.gov/or/plans/rmpswesternoregon/feis.php. 

At this location is a description of each Recreation Management Area using the RMA Frameworks. 

Each RMA description includes the recreation values, types of visitors, the outcome objectives, the 

Recreation Setting Characteristics, and the applicable management actions and allowable use 

restrictions. 

1503 | Page

Figure O-6. Salem District Recreation Management Area locations 

More information on RMA Frameworks is located on the BLM web site at 

http://www.blm.gov/or/plans/rmpswesternoregon/feis.php. 

At this location is a description of each Recreation Management Area using the RMA Frameworks. 

Each RMA description includes the recreation values, types of visitors, the outcome objectives, the 

Recreation Setting Characteristics, and the applicable management actions and allowable use 

restrictions. 
1504 | P a g e

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1505 | P a g e

Appendix P – Socioeconomics 

The socioeconomic analysis and this appendix were prepared for the BLM by a team of specialists at 

Environmental Resources Management (ERM) and subcontractors, under the project management of 

Clive Graham, ERM, and the direction of Stewart Allen of the interdisciplinary team. 

Issue 1 

How would the alternatives affect the supply, demand, and value of goods and services derived from 

BLM-administered lands?

Western Oregon Timber Market Model 

The BLM modeled timber markets34 in western Oregon using stumpage supply and demand functions that 

incorporate existing information, linear functions, and the economic constructs of supply, derived 

demand, and market arbitrage. In this analysis, the BLM described the stumpage market using linear 

equations for demand (Qd) and supply (Qs):

Qd = a1 − a2 ∗ P (1) 

Qs = b1 + b2 ∗ P (2) 

The parameters a1, a2 , b1, and b2 can be estimated from the observed market price, quantity, estimates of 

the stumpage supply, and demand elasticities. Key is the relation for estimating elasticity (∈) as: 

∈ =

∆Q

∆P

 ×

p

q

 (3) 

Equation 3 can be rewritten to solve for the slope of equations 1 and 2 (a2, b2) as:

slope = ∈ × q

p

 (4) 

The intercept terms of equations 1 and 2 (a1, b1) can be solved as: 

intercept = q

slope ×p

 (5) 

The development of the supply and demand relations each involve additional steps described in the 

following paragraphs. Once the equations are parameterized, they can be solved as simultaneous 

equations for market equilibrium (where qs = qd and ps = pd). In this analysis, the BLM assumed that 

market arbitrage following changes in BLM timber harvest would lead to new market equilibrium prices 

and private harvest levels. 

Stumpage Supply 

The supply curve is constructed as a composite of the behavior of different groups of timberland owners. 

In this case, it represents the timber harvest behavior of five different timberland owners/agencies: private 

 

34 Timber markets are regional in nature defined by available species and mix of manufacturing facilities. 

Traditionally, western Oregon is considered part of the larger Douglas-fir region, or the Pacific Northwest, 

Westside. For a more detailed discussion, see Haynes (2008). 
1506 | P a g e

entities, State agencies, the U.S. Forest Service, the BLM, and other public entities. Of these five owner 

groups, only the private timberland owners are known to be responsive to different price levels. The BLM 

assumed in this analysis that the four public owner groups set harvest levels through various planning 

processes that are generally unresponsive to price levels. In the context of equation 2, this means that the 

slope coefficient is based solely on the elasticity of private timberland owners. Public owners contribute 

only to the intercept term; the q in equation 5 includes both public and private timber harvest. 

Stumpage Demand 

In the case of saw timber, the largest product markets are for solid wood products like lumber and panel 

products.35 In this case, the BLM derived stumpage demand function from product demand. In 

agricultural literature,36 factor and product markets are linked through a concept called the “elasticity of 

price transmission” (∂), defined as

∂ = ∆Pp 

∆Ps ×

P

s

Pp (6) 

where P

p

is product price, and P

s

is the stumpage price. The elasticity of price transmission is calculated 

in two steps. First, a marketing margin can be estimated as: 

P

s = c1 + c2 × P

p

 (7) 

Second, using the results from equation 7, ∂ is calculated as:

∂ = 1

c2 

× 

P

s

Pp

 (8) 

The elasticity of price transmission is necessary to estimate the elasticity of demand for stumpage, 

consistent with product markets as shown in equation 9. 

∈s = ∈p × ∂ (9) 

With ∈s, equation 4 can estimate the slope of the stumpage demand function, and equation 5 can estimate 

the slope coefficient. 

Parameterizing the Model 

In this analysis, the BLM estimated the model using data for 2012 (Table P-1). Price data (Dollars/Mbf) 

and harvest volume data (MMbf) are in long log scale and were collected from the 2012 Production, 

Prices, Employment and Trade report (Zhou 2013). 

 

35 See the discussion in Adams and Haynes (1980). Also, see Adams and Haynes (2007). 

36 See George and King (1971) for a summary of derived demand as it is used here. 
1507 | P a g e

Table P-1. Price data and harvest volume data, 2012 

Ownership Harvest Volume

(MMbf)

Price

(Dollars/Mbf) Weights Weighted Price

Private 2,664.2 - - -

State 234.4 $301.55 0.362 $109.28

U.S. Forest Service 268.1 $94.65 0.414 $39.23

BLM 144.3 $146.41 0.223 $28.74

Other Public 43.2 - - -

Total/Average 3,354.2 $180.87 1.000 177.26

In this analysis, the BLM estimated ∂ as 0.83837 and, from the literature, used values for ∈ of 0.277 for 

private timber supply and 0.68538 for softwood lumber and panels. Using this information, the BLM 

developed the following supply and demand functions: 

qs = 2,615.84 + 4.1655 P

qd = 5,279.59 – 10.8619 P 

The solution of these two equations is the equilibrium price and quantity observed in 2012. 

 

37 The BLM estimated this by estimating the market margin (Equation 7) using lumber price data (Table P-1) and 

BLM stumpage price (Table 96) from Zhou (2013), 1986–2011. The elasticity of price transmission was computed 

using equation 8. 

38 Both elasticity estimates are weighted averages taken from Table 3.4 and 3.3 in Adams and Haynes (2007). 
1508 | P a g e

Outdoor Recreation Demand Elasticity Calculation 

Purpose and Background 

This section describes the approach to calculating demand elasticity, or responsiveness, to changes in the 

quantity of BLM-administered outdoor recreation areas. Its purpose is to calculate demand elasticity to 

estimate how outdoor recreation participation would change under the Proposed RMP and each 

alternative. The results of this analysis provide district-specific estimates for changes in visitation by 

alternative, which can then be used to estimate the economic value and market impacts associated with 

visits. ECONorthwest, as a subcontractor to ERM, prepared this analysis for the BLM. 

Because there does not exist a traditional market establishing prices and supply for most outdoor 

recreation, economists typically base their value estimates on visitation and time-use information (see, for 

example, Hoteling 1947, McConnell and Strand 1981, Amoako-Tuffour and Martínez-Espiñeira 2012). 

These methods of valuation often work well when coupled with site visitation and individual socioeconomic data but are often insufficient when considering locations that are not currently managed for 

recreational purposes. A central issue with valuing recreation due to proposed site changes is to 

understand the interplay of recreation demand and land supply. For instance, Siikamäki (2011) utilized 

the American Time Use Survey (ATUS) data to value the effect of increases in the supply of State park 

lands on recreational time use. Results of his model suggest that the addition of approximately 2 million 

acres of State park lands between 1975 and 2007 contributed to about 600 million hours of nature 

recreation and $3.85 billion in annual recreational value. 

ECONorthwest has developed a model of the effect of recreational land supply on demand for outdoor 

recreational time use in the western continental United States. Importantly, this model distinguishes 

between changes in the supply of protected land managed for recreational uses versus other nonrecreational land uses (e.g., forestry, biodiversity, and mineral extraction). The data used for this model 

include recreational time use from the 2007–2013 ATUS, to characterize utilization of recreational 

resources, and the U.S. Geological Survey Protected Area Database, to define the local supply of 

recreation. Based upon these sources of data, the model predicts the effect of changes in the supply of 

recreational lands on time spent recreating. 

Data 

The U.S. Bureau of Labor Statistics funds ATUS, and the U.S. Census Bureau collects the data. ATUS 

provides detailed descriptions of daily time use for survey respondents. ATUS provides a representative 

snapshot of the annual national time budget for Americans 15 years of age or older during a particular 

year. ATUS respondents are drawn from a sub-sample of individuals exiting the Current Population 

Survey, used to estimate national employment statistics. Time use categories include activities such as 

eating, sleeping, working, and driving.39 In addition, these data provide estimates of the total time the 

respondent spends engaging in outdoor recreation. The time use categories used to represent outdoor 

recreation include: 

 Biking 

 Rock Climbing 

 Hunting 

 Fishing 

 Golfing 

 Hiking 

 Running/Walking 

 Snow Skiing 

 

39 For a full list of ATUS time use designations see U.S. Bureau of Labor Statistics (2013). 
1509 | P a g e

 Team Sports 

The sum of the total minutes allocated to these activities is representative of the budget for outdoor 

recreation for a particular ATUS survey respondent. These estimates are nationally representative using 

sample weights provided by the U.S. Census Bureau. These weights take into account the day of the week 

of the interview and the total share of the US population that that the individual represents. 

The sample considered for this analysis consists of ATUS respondents from the years 2007–2013 located 

in western U.S. states.40 Due to privacy concerns, ATUS does not provide detailed locational information 

for survey respondents. However, linking this survey with data previously collected from the Current 

Population Survey can be used to identify the state and core based statistical area (CBSA) the individual 

is located in, which are the spatial units used for this analysis. Hence, this analysis excludes individuals 

located outside of a CBSA, which as of 2010, represents approximately 6.3 percent of the U.S. population 

(U.S. Census Bureau 2010). Overall, there are 33,069 respondents from 78 CBSAs located across the 

western U.S. Approximately 6 percent of respondents were from the Oregon. 

For this analysis, the BLM represented the total supply of government-managed recreational lands using 

the Protected Area Database—a GIS-based database of land use in the United States, including Federal, 

State, and local government land holdings. These data also distinguish between land management 

designations and based upon this information, we determine the total quantity of recreational and nonrecreational lands managed by Federal and State/local agencies, respectively, for each CBSA in the 

western United States. As examples, recreational lands would include National, State and local parks, 

whereas, non-recreation lands include lands managed for timber production, mining, or habitat 

management. 

The dependent variable for this analysis is the total minutes spent per person per day engaging in outdoor 

recreation, summarized in Table P-2. Explanatory variables include individual controls for gender, age, 

number of children living at home, race, educational attainment, income, employment, as well as the 

population of the CBSA and population of the State per year. The analysis also controlled for the day of 

the week, the month, and if the interview day was on a holiday. Regional fixed effects are included to 

account for fixed differences in recreational behavior among states.41 The supply of parkland is 

represented as the density of parks, measured as the acres of parkland per acre. Alternative models were 

also run using the total acres of parks and density of parks per acre per person, with no improvement over 

results reported here. Table P-2 provides summary statistics for included explanatory variables. 

 

40 This includes the following states Arizona, California, Colorado, Idaho, Kansas, Montana, Nebraska, New 

Mexico, North Dakota, Nevada, Oklahoma, South Dakota Texas, Utah, Washington, and Wyoming. 

41 In this analysis, the BLM divides the Western states into three regions: 1) Arizona, Colorado, New Mexico, 

Kansas, Nebraska, Oklahoma, Utah, and Texas 2) California and Nevada, 3) Idaho, Oregon, Montana, North 

Dakota, South Dakota, Washington, and Wyoming. 
1510 | P a g e

Table P-2. Summary statistics

Variable Mean Standard 

Deviation Minimum Maximum

Female 0.552 0.497 - 1

Age 44.834 17.442 15 85

Number of Children at Home 0.978 1.216 - 10

Race

Black 0.081 0.273 - 1

Hispanic 0.286 0.452 - 1

Asian 0.058 0.233 - 1

Other 0.029 0.168 - 1

Education

High School 0.208 0.406 - 1

Some College 0.286 0.452 - 1

Bachelors 0.206 0.404 - 1

Professional Degree 0.111 0.315 - 1

Income

$15k – $30k 0.156 0.363 - 1

$30k – $50k 0.195 0.396 - 1

$50k – $75k 0.175 0.380 - 1

$75k – $100k 0.118 0.323 - 1

$100k – $150k 0.111 0.314 - 1

Over $150k 0.099 0.299 - 1

Missing 0.065 0.247 - 1

Employment

Unemployed 0.043 0.203 - 1

Not in Labor Force 0.344 0.475 - 1

Population

CBSA Population (in 100s of Thousands) 36.915 38.361 0.976 130.648

State Population (in 100s of Thousands) 211.772 143.192 9.348 384.314

CBSA Park Density (Acres in Parks  Gross Acres)

Federal Recreation 7.855 8.236 - 43.723

Federal Non-recreation 17.369 20.779 - 83.552

State Recreation 2.046 2.647 - 11.942

State Non-recreation 5.424 5.902 - 29.294

Econometric Model 

Individuals in this analysis include both those who spend at least part of their day recreating outdoors (17 

percent of observations) and others who spent no time on recreation during the interview day. Thus, to 

account for censoring of the dependent variable, the econometric model is a Tobit model of the number of 

minutes spent on outdoor recreation per day with left hand censoring at zero. In addition, the model is 

weighted using provided ATUS survey weights for consistent and representative results for the average 

American in the sample. Let Y be the daily minutes spent on outdoor recreation for individual i in CBSA 

j, and equation 1 represents the econometric model for this analysis. 

(1) Yij = β1 ∙ FRj + β2 ∙ FNRj + β3 ∙ LRj + β4 ∙ LNRj + XijA + Ri + Ɛij
1511 | P a g e

Equation 1 predicts the total budget for outdoor recreation as a function of the supply of protected lands in 

the vicinity of the individual, along with other individual attributes. The variables FRj, FNRj

, LRj and 

LNRj represent the density of protected lands managed for Federal recreation, Federal non-recreation, 

local recreation, and local non-recreation at the CBSA level, respectively. Xij is a vector of other 

individual and community attributes (e.g., income, education, race, population) and Α is a vector of 

coefficients for these attributes. Ri is a vector of regional fixed effects and Ɛij is a normally distributed 

error term, clustered by CBSA to account for correlation in recreational patterns among individuals 

located in the same metropolitan area. 

Importantly, for individuals with non-zero time allocated to recreation reported in the ATUS data, the 

analysis cannot determine the precise location where recreation took place. Hence, while some of the 

budgeted recreation time may occur on Federal and local recreation sites, some time may also be spent at 

other locations or outside the local CBSA. However, the purpose of the model is to determine the general 

effect of increases in supply of recreational on recreational demand, rather than a precise accounting of 

locations and times where recreation occurred. 

The coefficients β1 – β4 give the marginal effect of an increase in the density of parklands on the budget 

of time spent on outdoor recreation. For the purpose of this analysis, the BLM assumed that an increase in 

the supply of recreational lands, be they managed by Federal or local agencies, would have a positive 

effect on time spent recreating. The effect of non-recreational lands is ambiguous. Because these lands 

would not be managed explicitly for recreation, recreational opportunities may be limited in these areas. 

By comparing the marginal effect of an increase in recreational lands and a parallel decrease in nonrecreational lands, it is possible to estimate the effect of a shift in lands management from nonrecreational to recreational uses. 

Results 

Table P-3 presents coefficients and standard errors for results of the Tobit model of daily recreational 

time use for western states during the years 2007–2013. Where statistically significant, coefficients 

reported in Table 2 generally conform to expectation. On average, males, retired individuals and those 

with fewer children living at home tend to spend more time on outdoor recreation. Age has a non-linear 

effect on recreation. For younger individuals, increases in age tend to decrease time spent recreating; 

whereas, older individuals spend more time on recreation as they age. This result is consistent with the 

hypothesis that respondents generally have less time to devote to recreation as they enter the work force 

and raise a family but gradually have more time to spend on recreation as they retire and children leave 

the house. In addition, respondents with greater income (above $50,000 a year) and a bachelors or postbachelor’s degree tend to spend more time recreating. Individuals located in more populated states also 

tend to report more spending more time on outdoor recreation. This result may be due to more populated 

states having larger budgets to spend on maintaining and establishing recreation areas, thus encouraging 

recreation though higher quality opportunities. 
1512 | P a g e

Table P-3. Tobit model of daily time spent on outdoor recreation for western U.S. states in the years 

2007–2013, coefficients and standard errors 

Variable Coefficient Standard Error

Female -36.36*** 3.11

Age -4.44*** 0.67

Age^2 0.04*** 0.01

Number of Children at Home -9.97*** 3.08

Number of Children at Home ^2 -0.05 0.63

Race

Black -7.23 8.17

Hispanic -0.02 5.33

Asian -0.89 6.63

Other 20.19* 10.70

Education

High School -20.29*** 5.53

Some College -7.99 6.50

Bachelors 25.18*** 6.76

Professional Degree 43.20*** 7.49

Income

$15k – $30k -2.01 8.06

$30k – $50k 9.27 7.31

$50k – $75k 18.97*** 6.52

$75k – $100k 28.16*** 8.08

$100k – $150k 44.80*** 9.40

Over $150k 45.88*** 8.39

Missing 26.42*** 8.96

Employment

Unemployed 6.01 10.61

Not in Labor Force 32.27*** 3.91

Population

CBSA Population (in 100s of Thousands) 0.01 0.03

State Population (in 100s of Thousands) 0.07*** 0.02

CBSA Park Density (Acres in Parks  Gross Acres)

Federal Recreation 0.70*** 0.20

Federal Non-recreation 0.14 0.12

State Recreation 2.15** 0.96

State Non-recreation 1.30*** 0.33

Fixed Effects

Region Yes

Holiday Yes

Day of Week Yes

Month Yes

Year Yes

Sample 33,069

Core Based Statistical Areas (CBSAs) 78

* Significant at the 10 percent level 

** Significant at the 5 percent level 

*** Significant at the 1 percent level 
1513 | P a g e

The effect of increases in protected land on recreation varies depending upon location, ownership and the 

recreational management type. Increases in CBSA-level recreational lands managed by Federal and local 

agencies have a positive and statistically significant effect on recreational time allocation. For instance, a 

one percent increase in Federal and local recreational lands increases time spent recreating by an average 

of 0.98 and 0.90 minutes per day, respectively. By contrast, Federal non-recreational lands have a 

statistically insignificant and near zero effect on outdoor recreation, and local non-recreational lands have 

a statistically significant and positive effect on time spent recreating. These results suggest that while 

Federal non-recreational lands tend to be unappealing for recreational users, local non-recreational lands 

may offer more opportunities for recreation, even if not explicitly designed for these purposes. 

Elasticity of Demand to Recreational Land Supply 

These results facilitate an analysis of the potential effect that transitioning lands from non-recreational 

management to recreational management would have spent on time engaged in outdoor recreation. In 

particular, this analysis estimated the elasticity of demand for time spent on recreation with respect to the 

supply of recreation opportunities in terms of acreage of land managed for recreation. Next, the analysis 

estimated the elasticity of demand with respect to the supply of recreation opportunities on land not 

managed for recreation. The analysis then combined these two estimates, such that a one percent increase 

in the supply of recreation on lands managed for recreation is balanced by a commensurate decrease in 

the supply of recreation on lands not managed for recreation. 

In this analysis, acreage of land managed for recreation serves as a proxy for outdoor recreation 

opportunities. While a comprehensive, spatially explicit dataset of all recreation opportunities is not 

available, the Protected Areas Database does provide a relatively comprehensive dataset for all recreation 

area by ownership/administration. Similarly, the specific recreation opportunities associated with new 

RMAs under the Proposed RMP and alternatives are not defined, and the acreage serves as a proxy for the 

specific recreation opportunities that the BLM would implement over time. This analysis utilizes 

elasticity estimates derived from acreage-based relationships, and applies the elasticity estimates to 

acreage-based changes. 

An elasticity represents the ratio of percent change in demand associated with a percent change in a 

particular explanatory variable. In this case, by estimating an elasticity of demand for a change in 

recreational land supply, this analysis provides a calculation of elasticity that can be applied to changes in 

outdoor recreation area on BLM-administered lands to estimate corresponding changes in visitation. This 

particular elasticity approach is the appropriate method, because it implicitly accounts for several factors 

including current demand levels, current supply levels, and proportionate relationships between supply 

and demand that capture scarcity of outdoor recreation opportunities by context. 

Table P-4 summarizes the elasticity of demand for an increase in CBSA-level recreation for both 

federally and locally protected lands in Oregon. These results suggest that a 10 percent increase in Federal 

and local land managed for recreation would result in an increase in recreational time demand by 

approximately 1.7 percent and 0.08 percent, respectively. 

Table P-4. Elasticity of demand for shift in land from non-recreational to recreational management

Oregon

Land Conversion Marginal Effect Standard Error

Federal 0.1770*** 0.0597

State 0.0083 0.0113

* Significant at the 10 percent level 

** Significant at the 5 percent level 

*** Significant at the 1 percent level
1514 | P a g e

ATUS data do not include sufficient sample sizes to limit outdoor recreation to only the most common 

activities on BLM-administered lands. While including a broader range of activities such as team sports 

provides sufficient sample size to calculate statistically significant elasticities, it also likely leads to lower 

elasticity values than otherwise. This is because changes in Federal outdoor recreation areas are unlikely 

to influence strongly the amount of time respondents to the survey spend on team sports. Because of this 

data limitation, actual investments by the BLM in increasing the quantity and quality of outdoor 

recreation facilities would likely generate greater demand response for those targeted activities than these 

elasticity values predict. 

Elasticity Application to the Proposed RMP and Alternatives 

To apply these elasticity estimates to changes in total acreage in Recreation Management Areas (RMAs) 

in the decision area under the Proposed RMP and alternatives, this analysis applied the elasticity to 

current measures of RMA acreage by district and current outdoor recreation visitation by district. The 

results are projected changes in visitation by district and activity type for the Proposed RMP and each 

alternative. Table P-5 shows the number of visits over time (including long-term participation 

projections), by district, alternative and implementation scenario. Total visits in 2012 were 5.3 million, as 

shown for the No Action alternative. Under the Proposed RMP, applying the elasticity corresponding to 

the proposed change in total RMA acreage, and taking into consideration long term and socioeconomic 

projections, visits would reach 11.9 million in 2062. 

Table P-5. Recreation visitation estimates for the Proposed RMP and alternatives by implementation 

scenario 

Alternative/

Proposed RMP Phasing Geography Year

2012 2020 2030 2040 2050 2060 2062

No Action N/A

Totals 5,300,902 5,753,782 6,356,367 6,907,409 7,440,363 7,998,835 8,106,746

Coos Bay 594,958 645,788 713,420 775,268 835,085 897,766 909,878

Eugene 937,639 1,017,746 1,124,333 1,221,803 1,316,073 1,414,857 1,433,945

Klamath Falls 125,260 135,962 150,201 163,222 175,815 189,012 191,562

Medford 1,144,697 1,242,494 1,372,618 1,491,612 1,606,700 1,727,299 1,750,602

Roseburg 982,089 1,065,993 1,177,633 1,279,724 1,378,463 1,481,930 1,501,923

Salem 1,516,259 1,645,800 1,818,162 1,975,781 2,128,226 2,287,970 2,318,837

Alt. A

20 years

Totals 5,300,902 5,426,063 5,498,638 5,861,327 6,313,569 6,787,464 6,879,033

Coos Bay 594,958 605,178 608,573 647,733 697,710 750,080 760,199

Eugene 937,639 948,389 947,091 1,006,640 1,084,309 1,165,697 1,181,424

Klamath Falls 125,260 126,737 126,614 134,586 144,970 155,851 157,954

Medford 1,144,697 1,210,845 1,275,074 1,369,209 1,474,853 1,585,555 1,606,946

Roseburg 982,089 994,950 995,577 1,058,596 1,140,275 1,225,863 1,242,401

Salem 1,516,259 1,539,964 1,545,710 1,644,562 1,771,452 1,904,416 1,930,109

50 years

Totals 5,300,902 5,639,043 6,056,062 6,374,680 6,626,153 6,845,459 6,879,033

Coos Bay 594,958 630,979 675,301 708,617 734,494 756,857 760,199

Eugene 937,639 991,705 1,058,079 1,107,162 1,144,659 1,176,752 1,181,424

Klamath Falls 125,260 132,503 141,397 147,980 153,014 157,325 157,954

Medford 1,144,697 1,237,450 1,352,889 1,446,681 1,524,975 1,595,343 1,606,946

Roseburg 982,089 1,039,526 1,110,085 1,162,518 1,202,774 1,237,330 1,242,401

Salem 1,516,259 1,606,878 1,718,313 1,801,723 1,866,236 1,921,851 1,930,109

Alt. B N/A

Totals 5,300,902 5,753,782 6,356,367 6,907,409 7,440,363 7,998,835 8,106,746

Coos Bay 594,958 645,788 713,420 775,268 835,085 897,766 909,878

Eugene 937,639 1,017,746 1,124,333 1,221,803 1,316,073 1,414,857 1,433,945

Klamath Falls 125,260 135,962 150,201 163,222 175,815 189,012 191,562

Medford 1,144,697 1,242,494 1,372,618 1,491,612 1,606,700 1,727,299 1,750,602

Roseburg 982,089 1,065,993 1,177,633 1,279,724 1,378,463 1,481,930 1,501,923

Salem 1,516,259 1,645,800 1,818,162 1,975,781 2,128,226 2,287,970 2,318,837

Alt. C. 20 years

Totals 5,300,902 6,670,021 8,754,406 9,832,047 10,590,657 11,385,589 11,539,191

Coos Bay 594,958 694,162 857,352 953,891 1,027,490 1,104,613 1,119,515

Eugene 937,639 1,005,720 1,148,235 1,260,814 1,358,094 1,460,033 1,479,730

Klamath Falls 125,260 137,003 159,481 175,708 189,265 203,471 206,216

Medford 1,144,697 1,659,789 2,394,991 2,726,066 2,936,401 3,156,807 3,199,395

Roseburg 982,089 1,445,897 2,105,094 2,398,949 2,584,045 2,778,003 2,815,480

Salem 1,516,259 1,727,449 2,089,251 2,316,619 2,495,362 2,682,664 2,718,855

50 years Totals 5,300,902 6,074,572 7,195,959 8,396,812 9,716,733 11,223,446 11,539,191
1515 | P a g e

Coos Bay 594,958 654,696 747,372 848,538 961,437 1,092,090 1,119,515

Eugene 937,639 987,872 1,080,146 1,185,103 1,305,912 1,449,495 1,479,730

Klamath Falls 125,260 133,288 147,228 162,884 180,736 201,787 206,216

Medford 1,144,697 1,420,945 1,796,812 2,191,572 2,618,609 3,098,924 3,199,395

Roseburg 982,089 1,229,984 1,565,794 1,917,985 2,298,523 2,726,062 2,815,480

Salem 1,516,259 1,647,788 1,858,606 2,090,731 2,351,515 2,655,087 2,718,855

Alt. D

20 years

Totals 5,300,902 7,102,064 9,885,177 11,211,130 12,076,146 12,982,579 13,157,726

Coos Bay 594,958 732,915 960,774 1,080,183 1,163,527 1,250,861 1,267,736

Eugene 937,639 1,036,792 1,240,215 1,374,220 1,480,251 1,591,358 1,612,827

Klamath Falls 125,260 153,883 201,301 226,248 243,704 261,997 265,531

Medford 1,144,697 1,897,088 2,976,501 3,429,336 3,693,933 3,971,199 4,024,774

Roseburg 982,089 1,448,437 2,138,673 2,445,101 2,633,758 2,831,447 2,869,646

Salem 1,516,259 1,832,948 2,367,712 2,656,041 2,860,973 3,075,717 3,117,211

50 years

Totals 5,300,902 6,225,837 7,591,859 9,099,124 10,790,132 12,743,978 13,157,726

Coos Bay 594,958 667,016 781,807 911,452 1,058,969 1,231,215 1,267,736

Eugene 937,639 992,707 1,102,640 1,234,147 1,388,751 1,573,537 1,612,827

Klamath Falls 125,260 140,222 164,137 191,172 221,952 257,907 265,531

Medford 1,144,697 1,524,192 2,037,286 2,586,529 3,191,024 3,879,290 4,024,774

Roseburg 982,089 1,219,060 1,551,747 1,912,663 2,313,305 2,772,503 2,869,646

Salem 1,516,259 1,682,640 1,954,243 2,263,161 2,616,130 3,029,526 3,117,211

PRMP

20 years

Totals 5,300,902 6,775,898 9,031,513 10,170,006 10,954,692 11,776,949 11,935,831

Coos Bay 594,958 754,662 1,000,206 1,125,351 1,212,180 1,303,166 1,320,747

Eugene 937,639 1,002,908 1,146,872 1,260,052 1,357,274 1,459,151 1,478,836

Klamath Falls 125,260 135,939 157,727 173,730 187,135 201,181 203,895

Medford 1,144,697 1,833,536 2,803,352 3,216,161 3,464,310 3,724,340 3,774,585

Roseburg 982,089 1,199,706 1,545,055 1,730,891 1,864,441 2,004,385 2,031,426

Salem 1,516,259 1,849,147 2,378,301 2,663,821 2,869,353 3,084,726 3,126,341

50 years

Totals 5,300,902 6,111,641 7,292,978 8,568,921 9,979,781 11,596,069 11,935,831

Coos Bay 594,958 683,049 812,091 951,694 1,106,246 1,283,485 1,320,747

Eugene 937,639 983,849 1,074,076 1,179,125 1,301,521 1,447,903 1,478,836

Klamath Falls 125,260 132,407 145,650 160,893 178,517 199,471 203,895

Medford 1,144,697 1,503,758 1,983,613 2,487,515 3,032,892 3,646,008 3,774,585

Roseburg 982,089 1,104,643 1,289,731 1,491,803 1,717,017 1,976,776 2,031,426

Salem 1,516,259 1,703,935 1,987,817 2,297,890 2,643,588 3,042,427 3,126,341
1516 | P a g e

Issue 2 

How would the alternatives affect economic activity in the planning area derived from BLM-administered 

lands?
1517 | P a g e

Table P-6. Employment by industry by district model area, 2012 (jobs) 

Industry (Sector)

District Model Area Name and Counties

Planning

Area

Totals

Oregon

Totals

Coos

Bay Eugene KlamathFalls Medford Roseburg SalemOther

SalemPortland

MSA

Coos,

Curry Lane Klamath Jackson,Josephine Douglas

Benton,

Clatsop,

Lincoln,

Linn,

Marion,

Polk,

Tillamook

Clackamas,

Columbia,

Multnomah,

Washington,

Yamhill

Agriculture 3,237 5,462 2,511 5,479 3,330 23,169 19,389 62,577 90,083

Mining 58 104 46 141 117 1,641 2,686 4,793 5,066

Utilities 95 135 118 342 172 573 2,326 3,760 4,759

Construction 2,089 8,085 1,505 8,154 2,203 17,348 53,287 92,671 105,523

Manufacturing 3,781 12,422 2,132 9,029 4,820 25,976 104,812 162,973 181,427

Wholesale Trade 569 6,201 848 3,659 766 7,196 54,798 74,037 80,548

Retail Trade 4,629 24,783 4,288 20,422 4,845 37,659 108,402 205,027 231,382

Transportation and

Warehousing 1,012 2,885 1,251 4,802 1,724 11,998 32,363 56,036 62,888

Information 297 4,209 206 2,612 330 3,114 24,267 35,034 38,482

Finance and Insurance 935 6,041 996 5,722 1,851 9,432 59,627 84,604 92,582

Real Estate and Leasing 525 9,080 492 4,165 1,928 10,394 68,062 94,646 104,672

Professional Services 1,465 10,986 1,159 8,046 1,649 17,638 88,560 129,504 143,216

Management of Companies 341 1,884 624 1,703 434 2,380 22,639 30,005 30,783

Administrative and Waste

Services 2,246 10,172 1,587 7,786 2,668 16,440 66,660 107,560 117,952

Education Services 361 3,598 391 2,048 509 7,108 36,728 50,742 53,762

Health and Social Services 4,605 25,433 3,670 21,741 5,276 46,972 121,260 228,956 257,275

Arts, Entertainment, and

Recreation Services 902 3,825 858 5,014 626 8,245 25,709 45,178 51,711

Accommodation and Food

Services 3,548 13,739 2,319 11,155 3,038 27,496 80,764 142,059 160,824

Other Personal Services 2,295 11,722 2,237 9,162 2,966 19,309 58,908 106,599 119,825

Governments 7,286 25,283 4,643 14,346 7,275 65,321 116,243 240,396 288,801

Totals 40,276 186,049 31,881 145,525 46,527 359,408 1,147,490 1,957,157 2,221,563

Sources: MIG, Inc. (2013); Oregon Forest Resources Institute (2012) (forest products industries within greater Agriculture and Manufacturing throughout planning area) 
1518 | P a g e

Table P-7. Earnings by industry by district model area, 2012 (millions of 2012 dollars) 

Industry (Sector)

District Model Area Name and Counties

Planning

Area

Totals

Oregon

Totals

Coos

Bay Eugene KlamathFalls Medford Roseburg SalemOther

SalemPortland

MSA

Coos,

Curry Lane Klamath Jackson,Josephine Douglas

Benton,

Clatsop,

Lincoln,

Linn,

Marion,

Polk,

Tillamook

Clackamas,

Columbia,

Multnomah,

Washington,

Yamhill

Agriculture $117.3 $152.5 $89.2 $139.6 $85.4 $822.9 $753.0 $2,160.0 $2,750.4

Mining $3.8 $6.2 $2.5 $5.2 $3.6 $37.0 $70.6 $129.1 $140.7

Utilities $12.6 $15.3 $16.6 $51.2 $21.8 $76.6 $435.8 $629.8 $766.7

Construction $73.6 $443.2 $52.8 $432.9 $89.2 $839.7 $3,756.2 $5,687.7 $6,253.7

Manufacturing $148.6 $802.8 $122.4 $493.2 $261.0 $1,621.9 $9,827.7 $13,277.7 $14,212.3

Wholesale Trade $30.6 $368.1 $38.7 $190.5 $32.3 $483.9 $5,434.7 $6,578.9 $6,920.3

Retail Trade $144.2 $726.6 $108.4 $633.7 $145.0 $1,103.7 $3,713.7 $6,575.1 $7,374.1

Transportation and

Warehousing $51.7 $163.1 $51.9 $209.7 $84.6 $584.9 $1,722.7 $2,868.5 $3,243.2

Information $13.7 $243.5 $8.9 $117.3 $17.0 $182.5 $2,011.3 $2,594.1 $2,769.1

Finance and Insurance $42.2 $323.0 $33.3 $222.8 $59.1 $432.4 $3,866.1 $4,978.8 $5,264.0

Real Estate and Leasing $17.1 $127.2 $14.6 $101.4 $23.5 $285.3 $1,118.3 $1,687.4 $1,910.4

Professional Services $54.1 $459.8 $36.5 $253.0 $80.6 $779.7 $6,486.0 $8,149.7 $8,741.6

Management of Companies $22.2 $160.1 $44.1 $126.6 $30.6 $166.9 $2,488.9 $3,039.4 $3,086.4

Administrative and Waste

Services $52.8 $318.6 $43.4 $200.7 $75.9 $462.7 $2,489.2 $3,643.3 $4,004.7

Education Services $4.5 $73.4 $4.6 $34.5 $7.0 $160.8 $1,057.4 $1,342.4 $1,390.8

Health and Social Services $175.4 $1,343.0 $170.0 $1,083.3 $265.3 $2,382.9 $7,184.5 $12,604.4 $14,006.6

Arts, Entertainment, and

Recreation Services $10.6 $47.6 $8.9 $63.6 $9.2 $96.6 $592.8 $829.3 $920.4

Accommodation and Food

Services $73.1 $295.0 $45.0 $234.9 $62.1 $581.3 $2,022.5 $3,313.9 $3,703.4

Other Personal Services $66.5 $349.6 $55.1 $267.4 $78.7 $576.4 $2,564.4 $3,958.3 $4,380.6

Governments $393.1 $1,315.2 $251.1 $742.6 $357.7 $3,433.6 $7,471.2 $13,964.4 $16,573.0

Totals $1,507.7 $7,733.7 $1,198.0 $5,604.1 $1,789.7 $15,111.7 $65,067.0 $98,012.0 $108,412.3

Sources: MIG, Inc. (2013); Oregon Forest Resources Institute (2012) (forest products industries within greater Agriculture and Manufacturing throughout planning area) 
1519 | P a g e

Table P-8. Employment contribution of BLM programs to district model areas by industry, 2012 (jobs) 

Industry (Sector)

District Model Area Name and Counties

Planning

Area

Totals

Coos Bay Eugene Klamath

Falls Medford Roseburg Salem-Other Salem-PortlandMSA

Coos,

Curry Lane Klamath Jackson,Josephine Douglas

Benton,

Clatsop,

Lincoln, Linn,

Marion, Polk,

Tillamook

Clackamas,

Columbia,

Multnomah,

Washington,

Yamhill

Agriculture 420 272 73 265 272 255 230 1,788

Mining 31 6 - 16 16 12 10 92

Utilities 1 - - 2 1 1 2 7

Construction 6 6 1 9 8 4 8 42

Manufacturing 132 113 7 70 141 76 88 626

Wholesale Trade 19 25 4 31 27 10 36 153

Retail Trade 17 25 5 33 27 13 34 153

Transportation and

Warehousing 87 141 20 135 126 58 150 717

Information 14 10 1 16 9 9 17 75

Finance and Insurance 6 9 2 18 8 5 22 70

Real Estate and Leasing 8 25 3 21 19 11 28 113

Professional Services 18 52 4 52 23 30 33 213

Management of Companies 11 14 1 12 8 9 17 72

Administrative and Waste

Services 17 27 3 32 25 12 35 151

Education Services 13 18 2 14 12 14 19 92

Health and Social Services 21 46 8 62 33 27 37 234

Arts, Entertainment, and

Recreation Services 72 87 12 81 92 38 115 498

Accommodation and Food

Services 135 225 29 165 201 72 340 1,167

Other Personal Services 27 34 5 35 26 21 28 177

Governments 195 227 63 429 287 214 48 1,464

Totals 1,249 1,363 245 1,496 1,362 891 1,297 7,904

Note: Totals may not add due to rounding. 
1520 | P a g e

Table P-9. Earnings contribution of BLM programs to district model areas by industry, 2012 (millions of 2012 dollars) 

Industry(Sector)

District Model Area Name and Counties

Planning

Area

Totals

Coos Bay Eugene Klamath

Falls Medford Roseburg Salem-Other Salem-PortlandMSA

Coos,

Curry Lane Klamath Jackson,Josephine Douglas

Benton,

Clatsop,

Lincoln, Linn,

Marion, Polk,

Tillamook

Clackamas,

Columbia,

Multnomah,

Washington,

Yamhill

Agriculture $20.4 $12.7 $1.6 $10.1 $13.1 $12.6 $12.2 $82.6

Mining $1.0 $0.2 $0.0 $0.5 $0.2 $0.5 $0.3 $2.7

Utilities $0.1 $0.0 $0.0 $0.2 $0.1 $0.1 $0.2 $0.8

Construction $0.3 $0.4 $0.1 $0.5 $0.4 $0.2 $0.7 $2.6

Manufacturing $7.1 $6.6 $0.4 $3.7 $7.6 $4.6 $5.3 $35.2

Wholesale Trade $1.1 $1.5 $0.2 $1.7 $1.2 $0.7 $3.3 $9.7

Retail Trade $0.8 $1.2 $0.2 $1.3 $1.0 $0.7 $2.1 $7.2

Transportation and

Warehousing $2.5 $4.2 $0.6 $4.1 $3.5 $1.7 $4.8 $21.4

Information $0.6 $0.5 $0.1 $0.7 $0.4 $0.4 $1.1 $3.8

Finance and Insurance $0.3 $0.5 $0.1 $0.7 $0.3 $0.3 $1.4 $3.6

Real Estate and Leasing $0.3 $0.5 $0.1 $0.5 $0.3 $0.3 $0.8 $2.7

Professional Services $1.4 $1.5 $0.3 $2.4 $1.1 $1.3 $2.0 $10.1

Management of Companies $0.5 $0.7 $0.1 $0.6 $0.4 $0.4 $1.5 $4.0

Administrative and Waste

Services $0.5 $1.0 $0.1 $0.9 $0.8 $0.4 $1.6 $5.2

Education Services $0.3 $0.5 $0.0 $0.3 $0.3 $0.3 $0.6 $2.4

Health and Social Services $0.8 $2.4 $0.4 $3.0 $1.6 $1.3 $2.1 $11.6

Arts, Entertainment, & 

Recreation Services $1.6 $2.6 $0.3 $2.0 $2.5 $1.3 $3.6 $14.0

Accommodation & Food

Services $2.8 $4.8 $0.6 $3.4 $4.1 $1.5 $9.1 $26.3

Other Personal Services $0.6 $1.0 $0.1 $1.0 $0.7 $0.5 $1.1 $5.1

Governments $13.9 $18.0 $4.2 $28.3 $19.2 $16.8 $4.0 $104.4

Totals $56.8 $60.7 $9.4 $66.0 $58.9 $45.9 $57.8 $355.3

Note: Totals may not add due to rounding. 
1521 | P a g e

Table P-10. Employment and earnings in the Coos Bay District model area for the Proposed RMP and alternatives 

Program/Industry

Employment (Jobs) Earnings (Millions of 2012 Constant Dollars)

2012 2018 2012 2018

CurrentModifiedNo

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP CurrentModified

No

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP

BLM Program

Recreation 276 294 289 294 297 301 307 $7.0 $7.5 $7.3 $7.5 $7.5 $7.6 $7.8

Grazing - - - - - - - - - - - - - -

Timber 710 688 443 450 958 229 277 $33.3 $32.4 $20.8 $21.2 $45.1 $10.8 $13.0

Minerals - - - - - - - - - - - - - -

Agency

Expenditures 192 164 120 149 236 90 115 $13.1 $11.2 $8.2 $10.2 $16.0 $6.1 $3.3

Federal Payments

to Counties* 20 51 31 40 73 20 28 $1.0 $2.5 $1.5 $2.0 $3.6 $1.0 $1.4

Payments to

Coos 13 32 20 25 47 13 18 $0.6 $1.6 $1.0 $1.2 $2.3 $0.6 $0.9

Payments to

Curry 7 18 11 14 26 7 10 $0.4 $0.9 $0.6 $0.7 $1.3 $0.4 $0.5

Totals 1,198 1,196 883 933 1,564 641 726 $54.4 $53.6 $37.9 $40.8 $72.4 $25.6 $25.5

Timber-Related Industries

Forestry, Logging,

& Support

Activities

232 204 145 143 284 75 93 $13.6 $11.9 $8.5 $8.4 $16.6 $4.4 $5.4

Wood Products

Manufacturing 131 147 83 88 205 43 50 $7.3 $8.2 $4.6 $4.9 $11.4 $2.4 $2.8

Paper

Manufacturing 0 0 0 0 0 0 0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

Totals 363 351 228 231 489 118 143 $20.8 $20.1 $13.1 $13.2 $28.0 $6.8 $8.2

Recreation-Related Industries

Arts,

Entertainment, & 

Recreation

Services

71 73 64 65 83 59 61 $1.6 $1.6 $1.2 $1.3 $2.2 $1.3 $1.4

Accommodation

& Food Services 133 140 134 138 148 135 139 $2.7 $2.9 $2.4 $2.8 $3.6 $3.8 $4.0

Totals 204 214 198 203 231 194 200 $4.4 $4.5 $3.6 $4.2 $5.8 $5.1 $5.4

* Federal payments include only those that would be paid under the O&C formula. Current has been modified as if O&C payments had been made in lieu of SRS payments. 

Note: Totals may not add due to rounding. 
1522 | P a g e

Table P-11. Employment and earnings in the Eugene District model area for the Proposed RMP and alternatives 

Program/Industry

Employment (Jobs) Earnings (Millions of 2012 Constant Dollars)

2012 2018 2012 2018

CurrentModifiedNo

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP CurrentModified

No

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP

BLM Program

Recreation 527 561 551 561 548 549 546 $16.2 $17.2 $16.9 $17.2 $16.8 $16.9 $16.8

Grazing - - - - - - - - - - - - - -

Timber 480 1,156 884 1,164 2,022 664 1,008 $23.2 $56.0 $42.8 $56.4 $97.9 $32.2 $49.0

Minerals 3 3 3 3 3 3 3 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2

Agency

Expenditures 259 435 284 331 485 279 367 $15.2 $25.5 $16.7 $19.5 $28.5 $16.4 $8.1

Federal Payments

to Lane County* 28 71 43 55 102 28 39 $1.9 $4.9 $3.0 $3.8 $7.1 $2.0 $2.7

Totals 1,297 2,226 1,764 2,115 3,160 1,524 1,963 $56.7 $103.8 $79.5 $97.0 $150.4 $67.6 $76.7

Timber-Related Industries

Forestry, Logging,

& Support

Activities

118 260 199 251 453 154 230 $6.8 $15.1 $11.5 $14.6 $26.3 $8.9 $13.3

Wood Products

Manufacturing 81 205 155 216 362 111 166 $4.5 $11.3 $8.5 $11.9 $20.0 $6.1 $9.1

Paper

Manufacturing 13 38 30 38 65 23 38 $1.2 $3.5 $2.7 $3.5 $6.0 $2.1 $3.5

Totals 212 503 383 505 881 288 433 $12.5 $29.9 $22.8 $30.0 $52.3 $17.2 $25.9

Recreation-Related Industries

Arts,

Entertainment, & 

Recreation

Services

87 123 108 122 161 98 113 $2.6 $4.3 $3.4 $4.3 $6.5 $3.3 $4.0

Accommodation

& Food Services 222 250 236 244 254 233 235 $4.8 $5.3 $4.3 $5.2 $5.6 $5.7 $5.3

Totals 309 373 344 367 415 331 347 $7.4 $9.7 $7.7 $9.6 $12.1 $9.0 $9.3

* Federal payments include only those that would be paid under the O&C formula. Current has been modified as if O&C payments had been made in lieu of SRS payments. 

Note: Totals may not add due to rounding. 
1523 | P a g e

Table P-12. Employment and earnings in the Klamath Falls Field Office model area for the Proposed RMP and alternatives 

Program/Industry

Employment (Jobs) Earnings (Millions of 2012 Constant Dollars)

2012 2018 2012 2018

CurrentModifiedNo

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP CurrentModified

No

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP

BLM Program

Recreation 60 64 63 64 63 65 62 $1.60 $1.7 $1.7 $1.7 $1.7 $1.7 $1.6

Grazing 55 55 55 55 55 - 55 0.8 $0.8 $0.8 $0.8 $0.8 - $0.8

Timber 40 75 25 62 74 49 56 $1.90 $3.5 $1.2 $2.9 $3.5 $2.3 $2.6

Minerals - - - - - - - - - - - - - -

Agency

Expenditures 71 78 75 87 97 78 89 $4.20 $4.6 $4.4 $5.1 $5.7 $4.6 $2.1

Federal Payments

to Klamath

County*

4 11 7 9 17 5 6 $0.20 $0.6 $0.4 $0.5 $0.8 $0.2 $0.3

Totals 231 283 224 277 305 197 268 $8.70 $11.1 $8.3 $10.9 $12.5 $8.9 $7.5

Timber-Related Industries

Forestry, Logging,

& Support

Activities

15 23 10 20 24 17 19 $0.90 $1.3 $0.6 $1.2 $1.4 $1.0 $1.1

Wood Products

Manufacturing 6 16 4 12 14 8 10 $0.30 $0.9 $0.2 $0.7 $0.8 $0.5 $0.6

Paper

Manufacturing - - - - - - - - - - - - - -

Totals 21 39 13 32 38 26 29 $1.20 $2.2 $0.7 $1.9 $2.2 $1.5 $1.7

Recreation-Related Industries

Arts,

Entertainment, & 

Recreation

Services

12 14 12 14 14 13 13 $0.30 $0.3 $0.2 $0.3 $0.4 $0.4 $0.3

Accommodation

& Food Services 28 31 30 31 31 30 30 $0.60 $0.6 $0.5 $0.6 $0.7 $0.8 $0.6

Totals 40 45 41 45 45 43 42 $0.80 $0.9 $0.7 $0.9 $1.0 $1.1 $0.9

* Federal payments include only those that would be paid under the O&C formula. Current has been modified as if O&C payments had been made in lieu of SRS payments. 

Note: Totals may not add due to rounding. 
1524 | P a g e

Table P-13. Employment and earnings in the Medford District model area for the Proposed RMP and alternatives 

Program/Industry

Employment (Jobs) Earnings (Millions of 2012 Constant Dollars)

2012 2018 2012 2018

CurrentModifiedNo

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP CurrentModified

No

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP

BLM Program

Recreation 425 453 452 453 502 531 525 $12.20 $12.9 $12.9 $12.9 $14.4 $15.2 $15.0

Grazing 40 40 40 40 40 - 40 0.6 $0.6 $0.6 $0.6 $0.6 - $0.6

Timber 340 1,384 598 931 998 471 739 $15.80 $64.6 $27.9 $43.5 $46.6 $22.0 $34.5

Minerals 1 1 1 1 1 1 1 <$0.0 <$0.0 <$0.0 <$0.0 <$0.0 <$0.0 <$0.0

Agency

Expenditures 454 641 560 641 686 514 682 $27.20 $38.4 $33.6 $38.4 $41.1 $30.8 $17.8

Federal Payments

to Counties* 66 170 103 133 246 68 93 $2.90 $7.4 $4.5 $5.8 $10.7 $3.0 $4.1

Payments to

Jackson 44 114 69 89 165 46 63 $1.60 $4.1 $2.5 $3.2 $5.9 $1.6 $2.2

Payments to

Josephine 22 56 34 44 81 22 31 $1.30 $3.3 $2.0 $2.6 $4.8 $1.3 $1.8

Totals 1,326 2,688 1,753 2,199 2,473 1,586 2,081 $58.60 $124.0 $79.5 $101.3 $113.4 $71.0 $71.9

Timber-Related Industries

Forestry, Logging,

& Support

Activities

80 271 122 186 204 96 164 $4.60 $15.9 $7.1 $10.9 $11.9 $5.6 $9.6

Wood Products

Manufacturing 59 289 121 192 202 96 139 $3.30 $16.0 $6.7 $10.6 $11.2 $5.3 $7.7

Paper

Manufacturing - - - - - - - - - - - - - -

Totals 139 560 243 377 406 191 303 $7.90 $31.9 $13.8 $21.5 $23.1 $10.9 $17.3

Recreation-Related Industries

Arts,

Entertainment, &

Recreation

Services

80 132 96 112 123 101 112 $2.00 $4.4 $2.5 $3.4 $4.5 $3.9 $4.3

Accommodation

& Food Services 159 187 175 183 205 196 199 $3.30 $3.8 $3.4 $3.8 $6.3 $7.4 $7.0

Totals 239 320 272 295 328 297 311 $5.30 $8.2 $5.9 $7.1 $10.9 $11.3 $11.3

* Federal payments include only those that would be paid under the O&C formula. Current has been modified as if O&C payments had been made in lieu of SRS payments. 

Note: Totals may not add due to rounding. 
1525 | P a g e

Table P-14. Employment and earnings in the Roseburg District model area for the Proposed RMP and alternatives 

Program/Industry

Employment (Jobs) Earnings (Millions of 2012 Constant Dollars)

2012 2018 2012 2018

CurrentModifiedNo

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP CurrentModified

No

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP

BLM Program

Recreation 507 540 530 540 603 599 554 $13.6 $14.5 $14.2 $14.5 $16.2 $16.1 $14.9

Grazing - - - - - - - - - - - - - -

Timber 488 770 323 455 879 267 397 $23.5 $37.0 $15.5 $21.9 $42.2 $12.8 $19.1

Minerals 2 2 2 2 2 2 2 $0.1 $0.1 $0.1 $0.1 $0.1 $0.1 $0.0

Agency

Expenditures 176 229 165 214 334 141 232 $12.0 $15.7 $11.3 $14.7 $22.8 $9.6 $5.7

Federal Payments

to Douglas

County*

51 131 79 103 190 53 72 $2.6 $6.7 $4.0 $5.2 $9.7 $2.7 $3.7

Totals 1,225 1,672 1,100 1,314 2,008 1,062 1,257 $51.8 $74.0 $45.2 $56.4 $91.1 $41.4 $43.3

Timber-Related Industries

Forestry, Logging,

& Support

Activities

147 208 87 135 236 78 124 $8.6 $12.1 $5.0 $7.8 $13.7 $4.5 $7.2

Wood Products

Manufacturing 133 235 99 128 269 76 107 $7.4 $13.1 $5.5 $7.1 $15.0 $4.2 $5.9

Paper

Manufacturing - - - - - - - - - - - - - -

Totals 280 442 185 263 505 154 231 $16.0 $25.1 $10.5 $15.0 $28.7 $8.8 $13.1

Recreation-Related Industries

Arts,

Entertainment, & 

Recreation

Services

92 107 89 96 121 97 95 $2.5 $3.2 $2.0 $2.6 $4.9 $3.8 $3.1

Accommodation

& Food Services 197 214 205 212 243 228 214 $4.0 $4.3 $3.5 $4.3 $8.0 $7.9 $5.7

Totals 289 321 294 307 364 325 309 $6.5 $7.5 $5.6 $6.9 $12.9 $11.7 $8.7

* Federal payments include only those that would be paid under the O&C formula. Current has been modified as if O&C payments had been made in lieu of SRS payments. 

Note: Totals may not add due to rounding. 
1526 | P a g e

Table P-15. Employment and earnings in the Salem-Other district model area*for the Proposed RMP and alternatives 

Program/Industry

Employment (Jobs) Earnings (Millions of 2012 Constant Dollars)

2012 2018 2012 2018

CurrentModifiedNo

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP CurrentModified

No

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP

BLM Program

Recreation 133 141 139 141 141 143 145 $3.8 $4.0 $4.0 $4.0 $4.0 $4.1 $4.1

Grazing - - - - - - - - - - - - - -

Timber 432 353 459 503 630 425 483 $21.3 $17.5 $22.7 $24.9 $31.2 $21.1 $24.0

Minerals - - - - - - - - - - - - - -

Agency

Expenditures 271 314 254 255 415 182 247 $17.4 $20.2 $16.3 $16.4 $26.7 $11.7 $15.9

Federal Payments

to Counties† 15 37 23 29 54 15 21 $0.9 $2.4 $1.5 $1.9 $3.5 $1.0 $1.3

Totals 851 845 874 928 1,240 765 896 $43.5 $44.1 $44.5 $47.2 $65.4 $37.8 $45.4

Timber-Related Industries

Forestry, Logging,

& Support

Activities

125 101 132 146 182 120 137 $7.4 $5.9 $7.8 $8.6 $10.7 $7.1 $8.0

Wood Products

Manufacturing 56 38 52 58 71 46 49 $3.1 $2.1 $2.9 $3.2 $3.9 $2.6 $2.7

Paper

Manufacturing 15 17 20 21 28 20 25 $1.3 $1.5 $1.9 $2.0 $2.6 $1.8 $2.3

Totals 196 156 204 225 280 187 211 $11.8 $9.6 $12.5 $13.8 $17.2 $11.5 $13.1

Recreation-Related Industries

Arts,

Entertainment, & 

Recreation

Services

38 36 40 42 49 38 41 $1.3 $1.2 $1.4 $1.5 $1.9 $1.4 $1.6

Accommodation

& Food Services 71 77 73 75 84 72 76 $1.5 $1.6 $1.3 $1.6 $2.0 $1.9 $2.0

Totals 109 113 113 117 133 110 117 $2.8 $2.8 $2.7 $3.1 $3.8 $3.4 $3.6

* Includes Benton, Clatsop, Lincoln, Linn, Marion, Polk, and Tillamook Counties 

† Federal payments include only those that would be paid under the O&C formula. Current has been modified as if O&C payments had been made in lieu of SRS payments. 

Note: Totals may not add due to rounding. 
1527 | P a g e

Table P-16. Employment and earnings in the Salem-Portland MSA district model area*for the Proposed RMP and alternatives 

Program/Industry

Employment (Jobs) Earnings (Millions of 2012 Constant Dollars)

2012 2018 2012 2018

CurrentModifiedNo

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP CurrentModified

No

Action

Alt.

A

Alt.

B

Alt.

C

Alt.

D

PRMP

BLM Program

Recreation 854 909 893 909 909 923 932 $32.8 $34.9 $34.3 $34.9 $34.8 $35.4 $35.8

Grazing - - - - - - - - - - - - - -

Timber 407 295 396 422 532 372 406 $22.8 $16.6 $22.3 $23.7 $29.9 $20.9 $22.9

Minerals - - - - - - - - - - - - - -

Agency

Expenditures - - - - - - - - - - - - - -

Federal Payments

to Counties† 14 37 22 29 54 15 20 $1.0 $2.5 $1.5 $1.9 $3.6 $1.0 $1.4

Totals 1,275 1,241 1,312 1,360 1,494 1,309 1,358 $56.5 $53.9 $58.0 $60.5 $68.3 $57.3 $60.0

Timber-Related Industries

Forestry, Logging,

& Support

Activities

78 62 81 90 112 74 84 $4.4 $3.6 $4.6 $5.1 $6.4 $4.2 $4.8

Wood Products

Manufacturing 51 30 43 45 56 40 40 $2.8 $1.7 $2.4 $2.5 $3.1 $2.2 $2.2

Paper

Manufacturing 13 11 15 15 20 14 16 $1.2 $1.0 $1.3 $1.4 $1.8 $1.3 $1.5

Totals 142 104 139 150 188 129 141 $8.5 $6.2 $8.3 $9.0 $11.3 $7.8 $8.5

Recreation-Related Industries

Arts,

Entertainment, & 

Recreation

Services

115 118 119 122 127 122 124 $3.6 $3.5 $3.3 $3.8 $4.6 $4.7 $4.8

Accommodation

& Food Services 339 361 355 361 363 366 370 $9.1 $9.7 $8.1 $9.7 $11.4 $13.0 $13.0

Totals 454 478 474 484 490 488 494 $12.7 $13.2 $11.3 $13.5 $15.9 $17.7 $17.8

* Includes Clackamas, Columbia, Multnomah, Washington, and Yamhill Counties 

† Federal payments include only those that would be paid under the O&C formula. Current has been modified as if O&C payments had been made in lieu of SRS payments. 

Note: Totals may not add due to rounding. 
1528 | P a g e

Issue 5 

How would the RMP alternatives affect the capacity and resiliency of different types of communities in 

the planning area?

Census Places Random Selection 
1529 | P a g e

Census Places Random Selection for Community Capacity and Resiliency 

May 29, 2014 

Table P-17. Stratified random sample of communities by population (selected cities highlighted) 

Coos Bay 47,218 Roseburg 661,130 Salem

Powers 689 Sutherlin 7,810 Hubbard 3,173

Port Orford 1,133 Roseburg 21,181 Mount Angel 3,286

Lakeside 1,699 Salem 661,130 Toledo 3,465

Gold Beach 2,253 Johnson City 566 Harrisburg 3,567

Myrtle Point 2,514 Manzanita 598 Aumsville 3,584

Bandon 3,066 Monroe 617 Lafayette 3,742

Coquille 3,866 Gaston 637 Wood Village 3,878

Brookings 6,336 Yachats 690 Philomath 4,584

North Bend 9,695 Maywood Park 752 Tillamook 4,935

Coos Bay 15,967 Garibaldi 779 Warrenton 4,989

Eugene 39,724 Scio 838 Sheridan 6,127

Coburg 1,035 Adair Village 840 Seaside 6,477

Lowell 1,045 Halsey 904 Scappoose 6,592

Dunes City 1,303 Aurora 918 Stayton 7,644

Oakridge 3,205 Falls City 947 Lincoln City 7,930

Veneta 4,561 Donald 979 Molalla 8,108

Creswell 5,031 Yamhill 1,024 Independence 8,590

Junction City 5,392 Lyons 1,161 Fairview 8,920

Florence 8,466 Tangent 1,164 Sweet Home 8,925

Cottage Grove 9,686 Siletz 1,212 Silverton 9,222

Lakeview 23,223 Bay City 1,286 Astoria 9,477

Chiloquin 734 Rockaway Beach 1,312 Monmouth 9,534

Malin 805 Millersburg 1,329 Sandy 9,570

Merrill 844 Durham 1,351 Newport 9,989

Klamath Falls 20,840 Depoe Bay 1,398 Damascus 10,539

Medford 101,776 Gearhart 1,462 Gladstone 11,497

Gold Hill 1,220 Amity 1,614 Cornelius 11,869

Cave Junction 1,883 Brownsville 1,668 St. Helens 12,883

Rogue River 2,131 Cannon Beach 1,690 Happy Valley 13,903

Jacksonville 2,785 Clatskanie 1,737 Dallas 14,583

Shady Cove 2,904 Banks 1,777 Lebanon 15,518

Phoenix 4,538 Turner 1,854 Canby 15,829

Talent 6,066 Mill 1,855 Troutdale 15,962

Eagle Point 8,469 Rainier 1,895 Sherwood 18,194

Central Point 17,169 Columbia City 1,946 Wilsonville 19,509

Ashland 20,078 North Plains 1,947 Milwaukie 20,291

Grants Pass 34,533 Carlton 2,007 Forest Grove 21,083

Roseburg 49,031 Willamina 2,025 Newberg 22,068

Glendale 874 Waldport 2,033 Woodburn 24,080

Oakland 927 Vernonia 2,151 West Linn 25,109

Yoncalla 1,047 Gervais 2,464 Tualatin 26,054

Drain 1,151 Dayton 2,534 Oregon City 31,859

Riddle 1,185 Sublimity 2,681 McMinnville 32,187

Canyonville 1,884 Estacada 2,695 Keizer 36,478

Myrtle Creek 3,439 Jefferson 3,098 Lake Oswego 36,619

Reedsport 4,154 King City 3,111

Winston 5,379 Dundee 3,162 Grand Total 922,102
1530 | P a g e

Community Capacity/Resiliency Baseline 

Table P-18. Community capacity/resiliency baseline inputs 

Data Set What Does This Tell Us? Community Base Data Availability

County Sub County

Population 2010, 2012 Size, generally

= more community capacity Y Y

Population change 2000 to 

2010/2012

Growing pop, generally

= more capacity Y Y

Employment/Unemployment, 

2012

High employment/low 

unemployment, generally

= more capacity

Y Y

Employment volatility 

(diversity) current at place empt 

by industry (possibly including 

change over time)

More employment, employment 

access = more capacity

More diversity in disconnected 

industries (not all in one sector) 

= more resiliency

Y Y

Household income 2010 or 

most recent from American 

Community Survey (number of 

households)

Median household income or 

share in plus 3–5 $ income 

brackets (e.g., $20–34, 35–50)

Higher incomes, generally

= more capacity, more 

resiliency.

Y Y

Poverty rate Lower poverty = more capacity Y Y

Education (% population with 

High School certificate; with a 

4 year degree)

Higher = more capacity, more 

resiliency. Y Y

Community Health

Population with health 

insurance (available from 

census)

Healthy Communities have 

more capacity, more resiliency Y Y

Community wealth:

Assessable tax base?

(needs to be expressed in 

relative terms (e.g., per capita))

More wealth = more capacity, 

more resiliency Y If available

Recreation indicator?

Recreation demand/scarcity? 

(per Rec. Planning Criteria)

Lower scarcity = more capacity Y - Specifics to 

be determined If available
1531 | P a g e

Selected Socioeconomic Characteristics 

Table P-19. Selected socioeconomic characteristics for selected cities in western Oregon 

Characteristic Oregon Coquille Drain Florence

Number % Number % Number % Number %

Population

Total Population, 2012 3,836,628 3,874 1,142 8,412

Population, 2000 3,421,399 4,184 1,012 7,263

Population Change 2000–

2012 415,229 12% -310 -8% 130 13% 1,149 16%

Age Distribution (2012)

Population 19 years and under 967,636 25% 756 20% 296 26% 1,036 12%

Population 20–64 years 2,328,465 61% 2,312 60% 594 52% 4,293 51%

Population 65 years and older 540,527 14% 806 21% 252 22% 3,083 37%

Totals 3,836,628 100% 3,874 100% 1,142 100% 8,412 100%

Median age (years) 38.4 47.4 42.2 57.6

Race

White alone, 2012 3,272,707 85% 3,460 89% 1,084 95% 7,820 93%

Minority 563,921 15% 414 11% 58 5% 592 7%

Housing

Total housing units 1,673,593 N/A 1,953 50% 433 38% 5,207 62%

Occupied housing units 1,512,718 100% 1,592 82% 418 97% 4,438 85%

Vacant housing units 160,875 11% 361 18% 15 4% 769 15%

Owner-occupied 945,824 63% 1,104 57% 253 61% 2,766 62%

Renter-occupied 566,894 37% 488 25% 165 39% 1,672 38%

Median housing unit value ($) 246,100 154,100 133,100 201,200

Median gross rent ($) 854 478 151 1,606

Employment

Workers 16 years and over 3,072,774 80% 3,281 85% 921 81% 7,600 90%

In labor force 1,957,085 67% 1,794 46% 501 44% 3,244 39%

Unemployed 210,379 7% 71 2% 115 10% 258 3%

Occupation

Civilian employed population

16 years and over

1,743,524 57% 1,723 44% 386 34% 2,967 35%

Management, business,

science and arts occupations

627,719 36% 399 23% 62 16% 653 22%

Service occupations 315,529 18% 474 28% 82 21% 689 23%

Sales and office occupations 426,554 25% 409 24% 96 25% 637 21%

Natural resources,

construction, and

maintenance occupations

164,625 9% 343 20% 38 10% 347 12%

Production,

transportation, and

material moving 

occupations

209,097 12% 98 6% 108 28% 641 22%

Jobs in a 5-mile Radius of

the Community by Sector

2,086 559 3,651

Accommodation and Food

Services

145,131 9% 81 4% 33 6% 1,008 28%

Administration and Support,

Waste Management and 

Remediation

84,402 5% 50 2% 20 4% 141 4%

Agriculture, Forestry, Fishing

and Hunting

40,859 3% 182 9% 16 3% 86 2%

Arts, Entertainment, and

Recreation

26,407 2% 4 0% 2 0% 89 2%

Construction 71,050 4% 85 4% 46 8% 142 4%

Educational Services 158,758 10% 115 6% 124 22% 171 5%

Finance and Insurance 57,164 4% 87 4% 10 2% 103 3%
1532 | P a g e

Characteristic Oregon Coquille Drain Florence

Number % Number % Number % Number %

Health Care and Social

Assistance

230,433 14% 254 12% 8 1% 702 19%

Information 33,677 2% 12 1% 0 0% 110 3%

Management of Companies

and Enterprises

32,692 2% 64 3% 13 2% 21 1%

Manufacturing 167,695 10% 378 18% 139 25% 39 1%

Mining, Quarrying, and Oil

and Gas Extraction

1,596 0% 1 0% 8 1% 0 0%

Other Services (excluding

Public Administration)

60,136 4% 81 4% 13 2% 154 4%

Professional, Scientific, and

Technical Services

77,910 5% 27 1% 2 0% 70 2%

Public Administration 91,242 6% 480 23% 29 5% 93 3%

Real Estate and Rental and

Leasing

25,259 2% 5 0% 0 0% 102 3%

Retail Trade 181,165 11% 125 6% 61 11% 525 14%

Transportation and

Warehousing

52,036 3% 45 2% 31 6% 43 1%

Utilities 8,692 1% 9 0% 4 1% 27 1%

Wholesale Trade 74,290 5% 1 0% 0 0% 25 1%

Jobs Distribution

Variability Compared to

Oregon (3)

608% 267% 130%

Jobs by Earnings

$1,250 per month or less 395,867 24% 458 22% 163 29% 1,240 34%

$1,251 – $3,333 per month 621,915 38% 865 41% 257 46% 1,675 46%

More than $3,333 per month 602,812 37% 763 37% 139 25% 736 20%

Income

Median household income ($) 50,036 47,714 36,964 35,000

Persons below poverty level 584,059 15% 185 5% 97 8% 995 12%

Health Insurance Coverage

Civilian noninstitutionalized

population

3,796,881 99% 3,704 96% 1,142 100% 8,377 100%

With health insurance coverage 3,191,034 84% 3,240 84% 911 80% 6,996 83%

No health insurance coverage 605,847 16% 464 12% 231 20% 1,381 16%

Education (highest level obtained)

High School certificate 635,670 17% 2,371 61% 466 41% 3,541 42%

4 year degree 760,816 20% 682 18% 0 0% 0 0%

Assessed Value of Property

Total assessed value for tax

year 2013–14 ($)

202,372,480 52,373,224 837,548,331

Assessed Value Per Capita

(dollars)

52,239 45,861 99,566

Recreation

Outdoor recreation land in the

county where the community

is located (acres per 1,000

population)

8,605 5,012 16,069 5,098
1533 | P a g e

Characteristic Gold Beach Grants Pass Junction City Klamath Falls

# % # % # % # %

Population

Total Population, 2012 2,563 34,454 5,445 20,943

Population, 2000 1,897 23,003 4,721 19,462

Population Change 2000–

2012 666 35% 11,451 50% 724 15% 1,481 8%

Age Distribution (2012)

Population 19 years and under 664 26% 8,918 26% 1,551 28% 5,425 26%

Population 20–64 years 1,401 55% 18,533 54% 3,110 57% 12,989 62%

Population 65 years and older 498 19% 7,003 20% 784 14% 2,529 12%

Totals 2,563 100% 34,454 100% 5,445 100% 20,943 100%

Median age (years) 41.1 40 36.3 35

Race

White alone, 2012 2,334 91% 32,246 94% 5,032 92% 17,985 86%

Minority 229 9% 2,178 6% 413 8% 2,958 14%

Housing

Total housing units 1,327 52% 15,760 46% 2,250 41% 10,190 49%

Occupied housing units 1,029 78% 14,545 92% 2,049 91% 9,054 89%

Vacant housing units 298 22% 1,215 8% 201 9% 1,136 11%

Owner-occupied 674 66% 7,308 50% 990 48% 4,280 47%

Renter-occupied 355 34% 7,237 50% 1,059 52% 4,774 53%

Median housing unit value ($) 220,100 196,900 179,400 148,600

Median gross rent ($) 336 6,959 984 4,551

Employment

Workers 16 years and over 2,103 82% 27,321 79% 4,188 77% 16,844 80%

In labor force 1,195 47% 14,892 55% 2,747 50% 10,539 50%

Unemployed 123 5% 1,771 6% 386 7% 1,354 6%

Occupation

Civilian employed population 

16 years and over 1,072 42% 13,092 38% 2,361 43% 9,118 44%

Management, business, 

science and arts occupations 284 26% 3,138 24% 443 19% 2,836 31%

Service occupations 257 24% 3,273 25% 461 20% 2,213 24%

Sales and office occupations 304 28% 3,687 28% 565 24% 2,002 22%

Natural resources, 

construction, and maintenance 

occupations

134 13% 1,108 8% 498 21% 937 10%

Production, transportation, 

and material moving 

occupations

93 9% 1,886 14% 394 17% 1,130 12%

Jobs in a 5-mile Radius of 

the Community by Sector 1,394 17,216 12,205 18,710

Accommodation and Food 

Services 229 16% 2,012 12% 690 6% 1,644 9%

Administration and Support, 

Waste Management and 

Remediation

6 0% 778 5% 413 3% 1,143 6%

Agriculture, Forestry, Fishing 

and Hunting 37 3% 45 0% 488 4% 377 2%

Arts, Entertainment, and 

Recreation 4 0% 165 1% 86 1% 284 2%

Construction 49 4% 390 2% 641 5% 669 4%

Educational Services 93 7% 848 5% 1,218 10% 2,172 12%

Finance and Insurance 25 2% 690 4% 149 1% 561 3%

Health Care and Social 

Assistance 154 11% 3,977 23% 912 7% 3,455 18%

Information 42 3% 292 2% 27 0% 195 1%

Management of Companies 

and Enterprises 0 0% 77 0% 44 0% 506 3%
1534 | P a g e

Characteristic Gold Beach Grants Pass Junction City Klamath Falls

# % # % # % # %

Manufacturing 103 7% 1,358 8% 3,053 25% 1,497 8%

Mining, Quarrying, and Oil 

and Gas Extraction 0 0% 0 0% 13 0% 1 0%

Other Services (excluding 

Public Administration) 38 3% 726 4% 448 4% 660 4%

Professional, Scientific, and 

Technical Services 60 4% 473 3% 251 2% 563 3%

Public Administration 295 21% 982 6% 202 2% 1,262 7%

Real Estate and Rental and 

Leasing 15 1% 243 1% 175 1% 201 1%

Retail Trade 188 13% 2,978 17% 2,055 17% 2,506 13%

Transportation and 

Warehousing 35 3% 228 1% 397 3% 355 2%

Utilities 17 1% 76 0% 42 0% 143 1%

Wholesale Trade 4 0% 878 5% 901 7% 516 3%

Jobs Distribution Variability 

Compared to Oregon (3) 183% 96% 123% 117%

Jobs by Earnings

$1,250 per month or less 467 34% 5,043 29% 2,911 24% 5,292 28%

$1,251 – $3,333 per month 565 41% 8,087 47% 5,538 45% 8,219 44%

More than $3,333 per month 362 26% 4,086 24% 3,756 31% 5,199 28%

Income

Median household income 

(dollars) 50,958 32,991 35,067 31,971

Persons below poverty level 370 14% 7,132 21% 1,239 23% 5,131 24%

Health Insurance Coverage

Civilian non-institutionalized 

population 2,516 98% 33,614 98% 5,342 98% 20,538 98%

With health insurance coverage 1,865 73% 28,272 84% 4,320 79% 16,245 78%

No health insurance coverage 651 25% 5,342 16% 1,022 19% 4,338 21%

Education (highest level obtained)

High School certificate 1,176 46% 30,251 88% 1,770 33% 5,634 27%

4 year degree 90 4% 4,617 13% 87 2% 1,173 6%

Assessed Value of Property

Total assessed value for tax 

year 2013–14 ($) 226,856,877 2,624,936,968 355,651,839 1,264,904,779

Assessed Value Per Capita ($) 88,512 76,187 65,317 60,397

Recreation

Outdoor recreation land in the 

county where the community 

is located (acres per thousand 

population)

31,208 8,612 5,098 34,321
1535 | P a g e

Characteristic Lincoln City Molalla Rogue River St. Helens City

# % # % # % # %

Population

Total Population, 2012 7,926 8,039 2,265 12,807

Population, 2000 7,437 5,647 1,847 10,019

Population Change 2000–

2012 489 6% 2,392 42% 418 23% 2,788 22%

Age Distribution (2012)

Population 19 years and under 1,729 21.8% 2,598 32% 500 22% 3,737 29%

Population 20–64 years 4,575 57.7% 4,654 58% 1,158 51% 8,043 63%

Population 65 years and older 1,622 20.5% 787 10% 607 27% 1,027 8%

Totals 7,926 100% 8,039 100% 2,265 100% 12,807 100%

Median age (years) 44.6 32 45.6 33.3

Race

White alone, 2012 6,931 87.4% 7,520 94% 2,103 93% 11,512 89.9

Minority 995 13% 519 6% 162 7% 1,295 10%

Housing

Total housing units 5,720 5,720 3,010 37% 1,132 50% 5,123 40%

Occupied housing units 3,932 69% 2,966 99% 997 88% 4,725 92%

Vacant housing units 1,788 31% 44 1% 135 12% 398 8%

Owner-occupied 1,929 49% 2,077 70% 567 57% 3,007 59%

Renter-occupied 2,003 51% 889 30% 430 43% 1,718 34%

Median housing unit value ($) 233,700 204,600 177,900 186,000

Median gross rent ($) 717 889 420 1,701

Employment

Workers 16 years and over 6,500 82% 5,813 72% 1,838 81% 9,842 77%

In labor force 3,963 61% 4,006 69% 877 39% 6,742 53%

Unemployed 505 8% 444 8% 100 4% 1,202 9%

Occupation

Civilian employed population 

16 years and over 3,458 44% 3,562 44% 777 34% 5,540 43%

Management, business, 

science and arts occupations 649 19% 683 19% 195 25% 1,371 25%

Service occupations 1,091 32% 696 20% 146 19% 852 15%

Sales and office occupations 1,268 37% 819 23% 236 30% 1,669 30%

Natural resources, 

construction, and maintenance 

occupations

253 7% 650 18% 102 13% 829 15%

Production, transportation, 

and material moving 

occupations

197 6% 714 20% 98 13% 819 15%

Jobs in a Five Mile Radius 

of the Community by Sector 5,709 3,804 1,304 3,729

Accommodation and Food 

Services 1,721 30% 266 7% 104 8% 358 10%

Administration and Support, 

Waste Management and 

Remediation

240 4% 54 1% 58 4% 151 4%

Agriculture, Forestry, Fishing 

and Hunting 12 0% 710 19% 62 5% 52 1%

Arts, Entertainment, and 

Recreation 661 12% 66 2% 19 1% 47 1%

Construction 226 4% 260 7% 117 9% 85 2%

Educational Services 159 3% 427 11% 202 15% 479 13%

Finance and Insurance 48 1% 36 1% 19 1% 126 3%

Health Care and Social 

Assistance 674 12% 253 7% 141 11% 705 19%

Information 53 1% 47 1% 32 2% 28 1%

Management of Companies 

and Enterprises 1 0% 5 0% 0 0% 23 1%
1536 | P a g e

Characteristic Lincoln City Molalla Rogue River St. Helens City

# % # % # % # %

Manufacturing 47 1% 680 18% 198 15% 512 14%

Mining, Quarrying, and Oil 

and Gas Extraction 0 0% 16 0% 19 1% 0 0%

Other Services (excluding 

Public Administration) 168 3% 203 5% 52 4% 176 5%

Professional, Scientific, and 

Technical Services 66 1% 51 1% 49 4% 93 2%

Public Administration 244 4% 102 3% 40 3% 417 11%

Real Estate and Rental and 

Leasing 233 4% 24 1% 20 2% 58 2%

Retail Trade 1,030 18% 385 10% 132 10% 345 9%

Transportation and 

Warehousing 46 1% 121 3% 25 2% 45 1%

Utilities 23 0% 0 0% 0 0% 0 0%

Wholesale Trade 57 1% 98 3% 15 1% 29 1%

Jobs Distribution Variability 

Compared to Oregon (3) 217% 157% 49% 81%

Jobs by Earnings

$1,250 per month or less 2,147 38% 1,170 31% 465 36% 799 21%

$1,251 – $3,333 per month 2,575 45% 1,653 43% 523 40% 2,079 56%

More than $3,333 per month 987 17% 981 26% 316 24% 851 23%

Income

Median household income ($) 29,686 52,926 32,426 53,151

Persons below poverty level 1,616 20% 868 11% 398 18% 2,267 18%

Health Insurance Coverage

Civilian non-institutionalized 

population 7,886 99% 7,992 99% 2,265 100% 12,621 99%

With health insurance coverage 6,299 80% 6,664 83% 1,884 83% 10,706 84%

No health insurance coverage 1,587 20% 1,328 17% 381 17% 1,915 15%

Education (highest level obtained)

High School certificate 1,745 22% 6,930 86% 695 31% 2,420 19%

4 year degree 1,119 14% 780 10% 0 0% 1,288 10%

Assessed Value of Property

Total assessed value for tax 

year 2013–14 ($) 1,521,308,480 490,884,897 135,999,651 815,441,324

Assessed Value Per Capita ($) 191,939 61,063 60,044 63,672

Recreation

Outdoor recreation land in the 

county where the community 

is located (acres per 1,000 

population)

4,906 1,682 4,416 565
1537 | P a g e

Characteristic Sublimity Winston # % #

%

Population

Total Population, 2012 2,683 5,352

Population, 2000 2,148 4,613

Population Change 2000–2012 535 25% 739 16%

Age Distribution (2012)

Population 19 years and under 495 18% 1,674 31%

Population 20–64 years 1,346 50% 3,012 56%

Population 65 years and older 842 31% 666 12%

Totals 2,683 100% 5,352 100%

Median age (years) 51 31.9

Race

White alone, 2012 2,623 98% 4,980 93%

Minority 60 2% 372 7%

Housing

Total housing units 1,134 42% 1,927 36%

Occupied housing units 1,085 96% 1,809 94%

Vacant housing units 49 4% 118 6%

Owner-occupied 731 67% 1,074 59%

Renter-occupied 354 33% 735 41%

Median housing unit value ($) 247,300 154,400

Median gross rent ($) 347 723

Employment

Workers 16 years and over 2,292 85% 3,961 74%

In labor force 1,089 48% 2,208 41%

Unemployed 61 3% 388 7%

Occupation

Civilian employed population 16 years and 

over

1,016 38% 1,820 34%

Management, business, science and arts 

occupations 370 36% 335 18%

Service occupations 156 15% 337 19%

Sales and office occupations 276 27% 680 37%

Natural resources, construction, and 

maintenance occupations 115 11% 183 10%

Production, transportation, and material 

moving occupations 99 10% 285 16%

Jobs in a Five Mile Radius of the 

Community by Sector 17,216 4,032

Accommodation and Food Services 2,012 12% 264 7%

Administration & Support, Waste 

Management and Remediation 778 5% 72 2%

Agriculture, Forestry, Fishing and Hunting 45 0% 136 3%

Arts, Entertainment, and Recreation 165 1% 45 1%

Construction 390 2% 252 6%

Educational Services 848 5% 293 7%

Finance and Insurance 690 4% 35 1%

Health Care and Social Assistance 3,977 23% 196 5%

Information 292 2%6 0%

Management of Companies and Enterprises 77 0% 319 8%

Manufacturing 1,358 8% 1,325 33%

Mining, Quarrying, and Oil and Gas 

Extraction

0 0% 17 0%

Other Services (excluding Public 

Administration) 726 4% 106 3%

Professional, Scientific, and Technical 

Services 473 3% 42 1%

Public Administration 982 6% 48 1%

Real Estate and Rental and Leasing 243 1% 30 1%
1538 | P a g e

Characteristic Sublimity Winston

# % # %

Retail Trade 2,978 17% 316 8%

Transportation and Warehousing 228 1% 301 7%

Utilities 76 0% 89 2%

Wholesale Trade 878 5% 140 3%

Jobs Distribution Variability Compared 

to Oregon (3) 96% 174%

Jobs by Earnings

$1,250 per month or less 5,043 29% 846 21%

$1,251 – $3,333 per month 8,087 47% 1,542 38%

More than $3,333 per month 4,086 24% 1,644 41%

Income

Median household income ($) 58,708 31,627

Persons below poverty level 150 6% 1,584 30%

Health Insurance Coverage

Civilian non-institutionalized population 2,432 91% 5,345 100%

With health insurance coverage 2,229 92% 4,589 86%

No health insurance coverage 203 8% 756 14%

Education (highest level obtained)

High School certificate 2,519 94% 1,295 24%

4 year degree 816 30% 417 8%

Assessed Value of Property

Total assessed value for tax year 2013–14 ($) 187,046,485 223,555,844

Assessed Value Per Capita ($) 69,715 41,771

Recreation

Outdoor recreation land in the county where 

the community is located (acres per 1,000 

population)

828 16,069

Sources:

Assessed Property Value derived from individual County Assessors Offices Summary of Assessment and Tax Rolls. 

Oregon Parks and Recreation Department. 2011. Oregon Statewide Outdoor Recreation Resource/Facility Bulletin Final Report. 

A Component of the 2013–2017 Oregon Statewide Comprehensive Outdoor Recreation Plan. 

http://www.oregon.gov/oprd/PLANS/docs/scorp/2013-2018_SCORP/2013-2017-SCORP_App_B.pdf. 

U.S. Census Bureau; American Community Survey, 2012 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; generated by Joan Huston; using American FactFinder; http://factfinder2.census.gov; (May 2014). 

U.S. Census Bureau; American Community Survey, 2009 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; generated by Joan Huston; using American FactFinder; http://factfinder2.census.gov; (May 2014). 

U.S. Census Bureau; Census 2000, Summary File 1, Table DP05; generated by Joan Huston; using American FactFinder; 

http://factfinder2.census.gov; (May 2014). 

U.S. Census Bureau. 2013. OnTheMap Application. Longitudinal-Employer Household Dynamics Program. 

http://onthemap.ces.census.gov/; generated by Clive Graham July 3, 2014. 

Notes:

(1) All data are for 2012 with the exception of the Coquille Indian Tribe and Cow Creek Band of Umpqua Tribe of Indians. For 

these two tribes the most recent available data in all categories are the from 2009 five-year estimates. 

(2) The population that is 16 years or older and available to work. 

(3) A measure of difference in the distribution of jobs by sector in the 5-mile radius compared to the distribution of jobs for the 

State. A higher number means a larger difference in distribution. 

The American Community Survey data is derived from a sample of American households that contains a greater level of detailed 

socioeconomic data than the decennial census. Where available, we used American Community Survey data from 2012, which is 

informed by data collected over the prior 5 years and extrapolated for each community (for two tribes, data was only available 

from 2009). Since the American Community Survey uses data derived from a sample of the population, and is not a true count of 

the population like the decennial census, margins of error are associated with the extrapolated data. These margins of error vary 

across the geography sampled; however, smaller populations generally experience larger margins of error when compared to 

more populated geographies. 
1539 | P a g e

Table P-20. Selected socioeconomic characteristics: federally recognized Tribes with land in the planning 

area, 2009 and 2012 (1) 

Characteristic Oregon

Confederated 

Tribes of Coos, 

Lower Umpqua, 

and Siuslaw 

Indians

Confederated 

Tribes of the 

Grand Ronde

Confederated 

Tribes of the 

Siletz Indians

Number % Number % Number % Number %

Population

Population, 2012, 2009 (1) 3,836,628 24 473 476

Population, 2000 3,421,399 25 55 308

Population Change 415,229 12% -1 -4% 418 760% 168 55%

Age Distribution

Population 19 years and under 967,636 25% 4 17% 164 35% 193 41%

Population 20–64 years 2,328,465 61% 13 54% 278 59% 243 51%

Population 65 years and older 540,527 14% 7 29% 31 7% 40 8%

Median age (years) 38 62 28 29

Race

White alone 3,272,707 85% 12 50% 92 19% 56 12%

Minority (Non-white) population 563,921 15% 12 50% 381 81% 420 88%

Housing

Total housing units 1,673,593 15 193 173

Occupied housing units 1,512,718 90% 15 100% 185 96% 160 93%

Owner-occupied 945,824 57% 3 20% 13 7% 88 55%

Renter-occupied 566,894 34% 12 80% 172 93% 72 45%

Vacant housing units 160,875 10% 0 0% 8 4% 13 8%

Median value owner-occupied units ($) 246,100 91,700 79,100

Median gross rent ($) 854 450 833 458

Employment

Population in the labor force (2) 1,953,903 67% 2 10% 176 56% 224 71%

Unemployed 210,379 7% 18 90% 139 44% 40 13%

Occupation

Civilian employed population 16 years 

and over 1,743,524 57% 0 0% 37 12% 184 58%

Management, business, science and 

arts occupations 627,719 36% 0 0% 47 35% 55 30%

Service occupations 315,529 18% 0 0% 58 43% 44 24%

Sales and office occupations 426,554 25% 0 0% 25 19% 45 25%

Natural resources, construction, and 

maintenance occupations 164,625 9% 0 0% 2 2% 29 16%

Production, transportation, and material 

moving occupations 209,097 12% 0 0% 2 2% 11 6%

Jobs in a 5-mile Radius of the 

Community by Sector 18,273 100% 2,168 100% 6,642 100%

Accommodation & Food Services 145,131 9% 2,727 15% 1,331 61% 1,489 22%

Administration & Support, Waste 

Management and Remediation 84,402 5% 1,347 7% 21 1% 245 4%

Agriculture, Forestry, Fishing and 

Hunting 40,859 3% 509 3% 107 5% 163 2%

Arts, Entertainment, and Recreation 26,407 2% 214 1% - 0% 679 10%

Construction 71,050 4% 609 3% 10 0% 266 4%

Educational Services 158,758 10% 1,195 7% 50 2% 280 4%

Finance and Insurance 57,164 4% 415 2% 8 0% 58 1%

Health Care and Social Assistance 230,433 14% 4,169 23% 26 1% 715 11%

Information 33,677 2% 331 2% 2 0% 46 1%

Management of Companies and 

Enterprises 32,692 2% 184 1% - 0% 1 0%

Manufacturing 167,695 10% 612 3% 77 4% 419 6%

Mining, Quarrying, and Oil and Gas 1,596 0% 27 0% - 0% 4 0%
1540 | P a g e

Characteristic Oregon

Confederated 

Tribes of Coos, 

Lower Umpqua, 

and Siuslaw 

Indians

Confederated 

Tribes of the 

Grand Ronde

Confederated 

Tribes of the 

Siletz Indians

Number % Number % Number % Number %

Extraction

Other Services (excluding Public 

Administration) 60,136 4% 598 3% 17 1% 190 3%

Professional, Scientific, and Technical 

Services 77,910 5% 427 2% 7 0% 81 1%

Public Administration 91,242 6% 1,062 6% 370 17% 536 8%

Real Estate and Rental and Leasing 25,259 2% 291 2% 3 0% 160 2%

Retail Trade 181,165 11% 2,439 13% 86 4% 1,035 16%

Transportation and Warehousing 52,036 3% 686 4% 35 2% 200 3%

Utilities 8,692 1% 137 1% 13 1% 13 0%

Wholesale Trade 74,290 5% 294 2% 5 0% 62 1%

Jobs Distribution Concentration 

Compared to Oregon (3) 51% 554% 99%

Jobs by Earnings

$1,250 per month or less 395,867 24% 5,611 31% 245 11% 2,272 34%

$1,251 – $3,333 per month 621,915 38% 8,030 44% 1,121 52% 2,728 41%

More than $3,333 per month 602,812 37% 4,632 25% 802 37% 1,642 25%

Income

Median household income ($) 50,036 15,938 24,861 39,000

Persons below poverty level 584,059 15% 6 25% 130 28% 81 18%

Health Insurance Coverage

With health insurance coverage 3,191,034 84% 22 92% 379 80% 335 70%

No health insurance coverage 605,847 16% 2 8% 94 20% 141 30%

Education (highest level obtained)

High School certificate 635,670 17% 7 29% 157 33% 97 20%

4 year degree 760,816 20% 0 0% 18 4% 25 5%

Recreation

Outdoor recreation land in the county 

where the community is located (acres 

per 1,000 population)

8,605 5,012 18,487 4,906
1541 | P a g e

Characteristic

Confederated 

Tribes of Warm 

Springs 

Reservation of 

Oregon

Coquille Indian 

Tribe

Cow Creek Band 

of Umpqua Tribe 

of Indians

Klamath Tribes

# % # % # % # %

Population

Population, 2012, 2009 (1) 3,960 297 21 17

Population, 2000 3,314 258 22 9

Population Change 646 19% 39 15% -1 -5% 8 89%

Age Distribution

Population 19 years and under 1,473 37% 103 35% 3 14% 0 0%

Population 20–64 years 2,235 56% 156 53% 12 57% 7 41%

Population 65 years and older 252 6% 38 13% 6 29% 10 59%

Median age (years) 27 30 62 70

Race

White alone 303 8% 131 44% 21 100% 6 35%

Minority (Non-white) population 3,657 92% 166 56% 0 0% 11 65%

Housing

Total housing units 1,157 112 9 14

Occupied housing units 1,037 90% 102 91% 9 100% 14 100%

Owner-occupied 650 63% 52 16% 7 78% 4 29%

Renter-occupied 387 37% 50 49% 2 22% 10 71%

Vacant housing units 120 10% 10 9% 0 0% 0 0%

Median value owner-occupied units ($) 103,200 152,800 387,500 275,000

Median gross rent ($) 673 483 N/A 371

Employment

Population in the labor force (2) 1,748 64% 108 51% 7 33% 5 29%

Unemployed 474 17% 14 7% 0 0% 1 6%

Occupation

Civilian employed population 16 years 

and over 1,274 47% 94 44% 7 33% 4 24%

Management, business, science and 

arts occupations 267 21% 24 23% 0 0% 2 50%

Service occupations 433 34% 30 28% 5 71% 0 0%

Sales and office occupations 287 23% 22 24% 2 29% 0 0%

Natural resources, construction, and 

maintenance occupations 86 7% 1 20% 0 0% 0 0%

Production, transportation, and material 

moving occupations 201 16% 14 15% 0 0% 2 50%

Jobs in a 5-mile Radius of the 

Community by Sector 2,250 100% 17,768 100% 27,040 100% 17,418 100%

Accommodation & Food Services 331 15% 2,661 15% 2,682 10% 1,516 9%

Administration & Support, Waste 

Management and Remediation 29 1% 1,240 7% 1,377 5% 1,076 6%

Agriculture, Forestry, Fishing &

Hunting 189 8% 601 3% 899 3% 222 1%

Arts, Entertainment, & Recreation 6 0% 136 1% 222 1% 383 2%

Construction 51 2% 627 4% 954 4% 550 3%

Information 4 0% 221 1% 299 1% 193 1%

Educational Services 102 5% 1,205 7% 1,930 7% 1,447 8%

Finance and Insurance 22 1% 375 2% 760 3% 557 3%

Health Care and Social Assistance 43 2% 3,891 22% 5,051 19% 3,414 20%

Information 4 0% 221 1% 299 1% 193 1%

Management of Companies and 

Enterprises - 0% 164 1% 532 2% 499 3%

Manufacturing 273 12% 940 5% 3,106 11% 1,419 8%

Mining, Quarrying, and Oil and Gas 

Extraction 1 0% 44 0% 91 0% 1 0%
1542 | P a g e

Characteristic

Confederated 

Tribes of Warm 

Springs 

Reservation of 

Oregon

Coquille Indian 

Tribe

Cow Creek Band 

of Umpqua Tribe 

of Indians

Klamath Tribes

# % # % # % # %

Other Services (excluding Public 

Administration) 11 0% 538 3% 874 3% 620 4%

Professional, Scientific, and Technical 

Services 31 1% 414 2% 658 2% 552 3%

Public Administration 890 40% 1,067 6% 2,558 9% 1,404 8%

Real Estate and Rental and Leasing - 0% 218 1% 339 1% 189 1%

Retail Trade 39 2% 2,343 13% 3,120 12% 2,523 14%

Transportation and Warehousing 13 1% 696 4% 887 3% 313 2%

Utilities 101 4% 83 0% 198 1% 112 1%

Wholesale Trade 114 5% 304 2% 503 2% 428 2%

Jobs Distribution Concentration 

Compared to Oregon (3) 267% 55% 39% 117%

Jobs by Earnings

$1,250 per month or less 407 18% 5,351 30% 7,077 26% 4,903 28%

$1,251 – $3,333 per month 1,199 53% 7,779 44% 11,693 43% 7,835 45%

More than $3,333 per month 644 29% 4,638 26% 8,270 31% 4,680 27%

Income

Median household income ($) 47,526 39,346 22,250 6,944

Persons below poverty level 1,069 28% 67 23% 0 0% 9 53%

Health Insurance Coverage

With health insurance coverage 2,535 65% N/A N/A N/A N/A 14 82%

No health insurance coverage 1,369 35% N/A N/A N/A N/A 3 18%

Education (highest level obtained)

High School certificate 664 17% 69 23% 7 33% 0 0%

4 year degree 193 5% 15 5% 2 10% 9 53%

Recreation

Outdoor recreation land in the county 

where the community is located (acres 

per 1,000 population)

1,682 5,012 16,069 34,321

Notes:

(1) All data are for 2012 with the exception of the Coquille Indian Tribe and Cow Creek Band of Umpqua Tribe of Indians. For 

these two tribes the most recent available data in all categories are the from 2009 five-year estimates. 

(2) The population that is 16 years or older and available to work. 

(3) A measure of difference in the distribution of jobs by sector in the 5-mile radius compared to the distribution of jobs for the 

State. A higher number means a larger difference in distribution. 

Sources:

Oregon Parks and Recreation Department. 2011. Oregon Statewide Outdoor Recreation Resource/Facility Bulletin Final Report. 

A Component of the 2013-2017 Oregon Statewide Comprehensive Outdoor Recreation Plan. 

http://www.oregon.gov/oprd/PLANS/docs/scorp/2013-2018_SCORP/2013-2017-SCORP_App_B.pdf. 

U.S. Census Bureau; American Community Survey, 2012 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; generated by Joan Huston; using American FactFinder; http://factfinder2.census.gov; (May 2014). 

U.S. Census Bureau; American Community Survey, 2009 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; generated by Joan Huston; using American FactFinder; http://factfinder2.census.gov; (May 2014). 

U.S. Census Bureau; Census 2000, Summary File 1, Table DP05; generated by Joan Huston; using American FactFinder; 

http://factfinder2.census.gov; (May 2014). 

U.S. Census Bureau. 2013. OnTheMap Application. Longitudinal-Employer Household Dynamics Program. 

http://onthemap.ces.census.gov/; generated by Clive Graham July 3, 2014. 

The American Community Survey data is derived from a sample of American households that contains a 

greater level of detailed socioeconomic data than the decennial census. Where available, we used 

American Community Survey data from 2012, which is informed by data collected over the prior 5 years 

and extrapolated for each community (for two tribes, data was only available from 2009). Since the 
1543 | P a g e

American Community Survey uses data derived from a sample of the population, and is not a true count 

of the population like the decennial census, margins of error are associated with the extrapolated data. 

These margins of error vary across the geography sampled; however, smaller populations generally 

experience larger margins of error when compared to more populated geographies. 

Community Profiles 

The BLM developed brief, introductory geographic and economic profiles of the selected communities to 

have some familiarity with the communities prior to the interviews. For the tribes, the section contains 

profiles only for those that opted to participate in the interviews.

Coquille 

Coquille is the county seat of Coos County, and is located on Oregon Route 42 along the Coquille River 

approximately 20 miles downstream from the Pacific Ocean. Deriving its name from the Coquille Indian 

Tribe, the city’s primary economic driver is the timber industry. Other economic activities include 

healthcare and tourism.

Area: 2.80 square miles. 2012 population: 3,874. http://cityofcoquille.org/

Drain 

Drain is in Douglas County, approximately 20 miles south of Eugene on Oregon Routes 99 and 38 at a 

pass in the coast range created by Pass Creek, a tributary of the Umpqua River. Drain is named after town 

founder and politician Charles J. Drain. The North Douglas School District is one of the major employers 

in the city, which is home to both the combined elementary/middle school and the high school. 

Area: 0.61 square miles. 2012 population: 1,142. http://www.drainoregon.org/ 

Florence 

Florence is located in Lane County on the Oregon coast at the mouth of the Siuslaw River roughly due 

east of Eugene, is located along U.S. Highway 101. The Siuslaw Tribe of Native Americans formerly 

inhabited the Florence area. The city’s traditional economy was based on timber and fishing, but both 

have declined, and the city now focuses on tourism. The Confederated Tribes of Coos, Lower Umpqua 

and Siuslaw Indians own the Three Rivers Casino located just east of the city. 

Area: 5.87 square miles. 2012 population: 8,412. http://www.ci.florence.or.us/ 

Gold Beach 

Gold Beach is the county seat of Curry County and is located on the Oregon coast approximately 50 miles 

north of the California border. The community was originally named Ellensburg in the 1850s, but later 

took the name Gold Beach after a beach near the mouth of the Rogue River where placer mines extracted 

gold. Gold Beach is a center for fishing, ocean charters, and outdoor recreation. The primary industries in 

the city are tourism and government. 

Area: 2.76 square miles. Population 2012: 2,563. http://www.goldbeachoregon.gov/

Grants Pass 

Grants Pass is the county seat of Josephine County and is located on Interstate 5, northwest of Medford. 

Incorporated in 1887, the city was named in honor of General Ulysses S. Grant. Attractions include the

Rogue River and the nearby Oregon Caves National Monument. Once a timber-based community, the 

economy is currently a mix of light manufacturing, secondary wood products, retail trade, tourism, 

recreation, and service-based industries.

Area: 11.03 square miles. Population 2012: 34,454. https://www.grantspassoregon.gov/ 
1544 | P a g e

Klamath Falls 

Klamath Falls is the county seat of Klamath County, and is located on the southeast shore of the Upper 

Klamath Lake, about 25 miles north of California. Founded in 1867 under the name Linkville, the city 

was renamed Klamath Falls in 1893. Logging was Klamath Falls’ first major industry, while tourism and 

recreation have become current economic mainstays. The nearby Lava Beds National Monument and 

Crater Lake National Park are common tourist destinations. 

Area: 20.66 square miles. Population 2012: 20,943. http://ci.klamath-falls.or.us/

Junction City 

Junction City is located in Lane County on U.S. Route 99 west of the Willamette River, approximately 15 

miles northwest of Eugene. Agricultural land surrounds the city, which has a strong manufacturing base 

including historic ties with the recreational vehicle industry. Incorporated in 1872, Junction City is also a 

gateway to Oregon wine country. 

Area: 2.36 square miles. 2012 population: 5,445. http://www.junctioncityoregon.gov/

Lincoln City 

Lincoln City is located in Lane County on the Oregon coast approximately 60 miles from Salem and 90 

miles from Portland. Lincoln City incorporated in 1965, uniting the cities of Delake, Oceanlake and Taft, 

and the unincorporated communities of Cutler City and Nelscott. It is a beach and resort community; 

tourism is the city’s primary industry. Lincoln City is also home to the Chinook Winds Casino operated 

by the Confederated Tribes of the Siletz. 

Area: 5.68 square miles. Population 2012: 7,926. http://www.lincolncity.org/

Molalla 

Molalla is located in Clackamas County, 30 miles southeast of Portland. The city was named after the

Molalla River, which in turn was named for the Molalla, a Native American tribe that inhabited the area. 

Descendants of the Molalla tribe are members of the Confederated Tribes of Grand Ronde. Historically, 

lumber production was the community’s biggest industry. In recent years, the city has diversified its 

economic base with manufacturing, commercial, tourism, and recreation, with Molalla as the gateway to 

the Molalla River Recreation Corridor. 

Area: 2.26 square miles. Population 2012: 8,039. http://www.cityofmolalla.com/

Rogue River 

Rogue River is located in the western edge of Jackson County along U.S. Route 5. Formerly known as 

Woodville the settlement changed to Rogue River. During the 1830s and 1840s, the area had become a 

stopover for trappers and traders traveling from Fort Vancouver on the Columbia River south to 

California along the Siskiyou Trail. Today’s Interstate 5 traces the route of that trail. Rogue River was 

closely tied to the timber industry but is now seeing a shift to service and retail jobs.

Area: 0.97 square miles. Population 2012: 2,265. http://cityofrogueriver.org/

St. Helens 

St. Helens is the county seat of Columbia County and is located about 30 miles north of Portland along the 

Oregon-Washington border. Bounded by the Columbia River to the east, St. Helens is named for its view

of Mount St. Helens in Washington, approximately 40 miles away. The city has a strong focus on business

development, especially in its Downtown Historic District and through its Main Street Program. St. 

Helens also offers a variety of tourism and recreation activities along the Columbia River. 

Area: 5.51 square miles. Population 2012: 12,807. http://www.ci.st-helens.or.us/
1545 | P a g e

Sublimity 

Sublimity is located in Marion County, about 15 miles east of Salem on a plateau on the western foothills 

of the Oregon Cascades. The town incorporated in 1903. Sublimity was a center for the timber industry 

through the 1980s, but is now a bedroom community for Salem. 

Area: 0.93 square miles. Population 2012: 2,683. http://www.cityofsublimity.org/

Winston

Winston is located in Douglas County less than 10 miles south of Roseburg along the South Umpqua 

River. Although separated by the river, Winston is often regarded as part of a single entity with nearby 

Dillard and Willis Creek. Winston experienced significant growth when lumber mills began to open 

towards the middle of the twentieth century, and it remains timber-dependent today. 

Area: 2.65 square miles. Population 2012: 5,352. http://www.winstoncity.org/

Confederated Tribes of the Grand Ronde Community of Oregon 

The Confederated Tribes of the Grand Ronde’s reservation and other owned lands cover approximately 

10,700 acres in Yamhill and Polk Counties. The population on these lands is approximately 470 (2012 

Census), but tribal membership across Western Oregon is 5,000–6,000.

The Tribes’ vision is to be a tribal community providing responsible stewardship of human and natural 

resources http://www.grandronde.org/ikanum/index.html (June 27, 2014). The Tribes’ sources of income 

include the Spirit Mountain Casino, timber sales from tribal lands, and tourism. The Grand Ronde is 

involved in community building functions such as housing, education, and health care. 

http://www.grandronde.org/. 

Coquille Indian Tribe of Coos County, Oregon 

The Coquille Indian Tribe’s reservation and its tribal service area covers approximately 15,600 square 

miles of Coos, Curry, Douglas, and Lane counties, with its main tribal campus in Southeastern Coos 

County. 

The Tribe is the second largest employer in Coos County, Oregon, with successful business ventures in 

forestry, arts and exhibits, gaming and hospitality, assisted living and memory care, high-speed 

telecommunications, and renewable energy. The Tribe also operates the Mill Resort & Casino in Coos 

Bay and manages the Coquille Forest, comprised of 14 separate parcels of formerly BLM-administered 

timberlands in eastern Coos County, totaling 5,410 acres. http://www.coquilletribe.org/.

Environmental Resources Management (ERM) sent letters to the Tribal Work Group of the Cooperating 

Agencies Advisory Group, as well as to city officials of selected cities in the planning area. The BLM 

included copies of these letters in the Draft RMP/EIS (pp. 1329–1331), and they are hereby incorporated 

by reference. 
1546 | P a g e

Interview Summaries 

This appendix contains summaries of the interviews that the BLM conducted with communities in the 

planning area.

Please note that, while the interviewees participated as representatives of their city or Tribe, they spoke as 

individuals and not formally on behalf of the city elected officials or of the Tribal leaderships.

City of Coquille 

Date: July 16, 2014 

Participants:

Ben Marchant, City Manager; Coquille 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-21. City of Coquille interview 

Question Discussion/ Response

How do you view your 

community’s ‘capacity,’

that is your community’s

ability to face changes,

respond to external and 

internal stresses, create,

and take advantage of 

opportunities, and meet its 

needs?

Coquille is challenged because its capacity is bound up with the economy of

southwestern Oregon, which has been in malaise since the mid-1980s. Ben 

has been City Manager for two years and was hired in part to increase the

city’s capacity by, for example, diversifying the economy and attracting

families with children to move to the city. His sense of the history is that the

city’s economic heyday was in the early1980s; there were three mills, car

dealers, large retail stores. Now there is only one mill and many of the stores

are gone – in that sense the city is depressed. For a while, the city was under

development moratorium, but has since expanded its sewer treatment plant.

The capacity data are somewhat inconsistent. The city lost population 

(approximately 8%) between 2000 and 2012. The population is older and 

there has been a decline in the 18 and under age cohort. Coquille had the

third lowest assessed value per capita among the 13 cities surveyed. On the

other hand, Ben said the tax base was healthy and household incomes are

relatively high such that the city does not meet the criteria for State

Community Development Block Grant funding because the city is above the

50% low- to moderate-income threshold for eligibility.

Ben feels that the growing elderly and retiree population require expensive

services from the city and that this has affected the schools budget (he

commented that the physics program had been cut).

The city’s remaining mill is a major employer (between 1/3 to 1/2 of all jobs

in the city). The other major employment sectors are government (Coquille

is the county seat) and institutional—employment at the area’s hospital.

Although Coquille is 10 miles off U.S. 101 (the coast highway), it does

attract visitors. The city offers a variety of options including summer

festivals, theatre, and antiquing.
1547 | P a g e

Question Discussion/ Response

How do you view your 

community’s ‘resiliency,’

that is your community’s

ability to adapt to change 

over time?

Ben feels that Coquille has a great sense of community with very strong

volunteer programs and ability to raise funds for charity. This undercurrent

of community is a testament to the city’s capacity to weather economic

challenges and work together to find solutions to problems.

As timber production has declined, the community is somewhat divided 

between those who see the potential for a timber-based economy to come

back, and others who think that timber is not coming back and that the city

needs to adapt to the “new normal.” The latter group sees some hope in the

proposed Jordan Cove Energy Project in Coos Bay to export liquefied 

natural gas.

Ben feels that Oregon’s citizen-driven tax cap initiatives (Measure 5 and 

Measure 50) limit government revenues and, as a result cities’ capacity to 

provide services. For example, Ben said that important services like the

ambulance program were operating in the red. Coquille needs to become less

dependent on property tax revenues. Ben said that Curry County was in the

worst financial condition, with Coos, Josephine, and Douglas close behind.

The city’s one timber mill is sustained by logging on private land. The City

of Coquille owns approximately 800 acres of forestland on two parcels in

separate locations east and west of the city. The city plans a timber sale on

part of this land.

All cities in Coos County are members of watershed associations to sustain 

and improve water quality. The associations focus on habitat restoration, 

preventing silt and runoff, and best practices around the watershed.

Ben sees a sociopolitical divide between rural and urban areas in Western 

Oregon; the urban areas progressing economically and the rural areas much 

less. This could impact the resiliency of cities like Coquille in the future.

How do the ways the

BLM manages its

resources affect your

community (its capacity 

and resiliency)?

Ben said that the BLM’s management has a great effect on the community. 

Coquille, like many cities in Western Oregon, sees restoring the O&C lands

to local management or to be managed for the benefit of local communities

as a major issue, because they see the effects of millions of dollars of

potential income that are lost every year. Local management would benefit

communities by helping to offset the property tax revenue caps.

Have changes in the

BLM’s resource

management over time

affected your community? 

In what ways?

Ben said he had seen harvest studies from the 1930s that would have allowed 

for 10% of the forest to be harvested at a sustainable rate. In his view, the

steep decline in harvest since the 1990s has resulted in forests that are

overgrown, begging questions about how to manage this enormous resource.

Are there changes in the

ways that the BLM

manages its resources that

would increase your

community’s capacity and 

resiliency?

Ben feels that there has been a transition within the BLM from a pragmatic

management approach to a more “idealistic” (let the forest be) mindset. He

sees this as flawed and somewhat inconsistent, for example, managed hunts

for some species and protections for others.

Ben said that if the BLM opened up more timberland for harvest it would 

have positive direct and spillover effects on the local economy.
1548 | P a g e

Question Discussion/ Response

BLM has very few trails and campgrounds near Coquille – Ben felt there are

more in the eastern part of the planning area. Ben feels that Coquille

residents would benefit from the availability of more access into the forest. It

could also be another attractor for tourists. The Coquille River provides

opportunities for recreational fishing.
1549 | P a g e

City of Gold Beach

Date: July 10, 2014 

Participants:

Jodi Fritts-Matthey, City Administrator; City of Gold Beach

Will Newdall, Public Works Superintendent; City of Gold Beach

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-22. City of Gold Beach interview 

Question Discussion/Response

How do you view your 

community’s ‘capacity,’

that is your community’s 

ability to face changes, 

respond to external and 

internal stresses, create, 

and take advantage of 

opportunities, and meet its 

needs?

Gold Beach is a small city with limited capacity. Its population is 

approximately 2,500 and it is located in Curry County, which has the 

smallest population among Western Oregon counties – 22,300. Gold Beach 

is the County seat, which provides some stability but, overall, there are only 

approximately 1,400 jobs in a 5-mile radius of the city. According to the 

Census, the city added approximately 660 people between 2000 and 2012.

Jodi Fritts (Jodi) stated that Gold Beach used to be totally timber dependent. 

In the mid-1980s, the city experienced a major economic setback when its 

only timber mill burned down and was not rebuilt. The mill had provided 

jobs for many residents, and its loss left a significant “economic hole that 

has not been filled.” There are no longer means to process timber in Gold 

Beach, and the closest mill is in Brookings, OR, roughly 30 miles away.

Jodi said that during the recession of the mid to late 2000s, the public sector 

took a huge employment hit in the city and in the County, especially 

considering their relatively low populations. She said that Gold Beach “lost 

hundreds of Federal, State, local and school district jobs.” These job losses 

have resulted in a severely stressed level of economic capacity. The Census 

data state an unemployment rate of 5% for the city, but Jodi believes this is 

low. Data from the Bureau of Labor Statistics (June 2013–May 2014) 

indicate Curry County’s unemployment rate is between 10.0 and 11.9%, 

putting the County’s rate above the State’s (7%).

Currently, the city’s major economic drivers are tourism and government. 

Tourism is based on the beaches, hiking, horseback riding, and boating and 

rafting.
1550 | P a g e

Question Discussion/Response

How do you view your 

community’s ‘resiliency,’

that is your community’s 

ability to adapt to change 

over time?

Gold Beach has struggled to adapt from its former timber-reliant economy. 

Jodi says that the city’s basket essentially had only one egg (the timber egg) 

and that tourism jobs have not been equivalent replacements. She added that 

the city has not recovered from the job losses during the recession; to her, it 

was, and remains a “depression.” (Jodi cited the Grapes of Wrath in 

describing the recession’s impacts).

Jodi states that the city is trying to grow its tourism economy. But, it is not 

easy for a small, relatively isolated place with limited options and 

opportunities. Growing tourism has been a “tough sell” among some 

residents who hold on to the possibility of a return to a better economy 

through logging.

In short, the city’s resiliency is extremely low.

How do the ways the 

BLM manages its 

resources affect your 

community (its capacity 

and resiliency)?

The BLM only owns a small portion of land in the upper portion of Gold 

Beach at the Rogue River National Recreation Trail. As such, the BLM’s 

management has no effects on the city. The U.S. Forest Service has much 

larger land holdings, approximately 70% of the land; but, to Jodi’s 

knowledge, there have been no timber sales in recent years from U.S. Forest 

Service land.

Some city residents look back fondly at the older timber-dependent 

economy. But, in Jodi’s view, any effort by the BLM to contribute to the 

city’s capacity is 30 years late.

The BLM has some land near Cape Blanco State Park (Cape Blanco 

lighthouse), which is managed by the Oregon Parks and Recreation 

Department, but this is some 30 miles north of Gold Beach.

Have changes in the 

BLM’s resource 

management over time 

affected your community? 

In what ways?

Any small role the BLM had when the city’s mill was operating has now 

gone.

The city is responsible for providing nearly all services within the city. The 

city does not benefit directly from timber payments to counties. The only 

services the county provides in the city are the jail and maintaining county 

roads in the city (approximately 15% of the roads). The jail is important 

because if it exceeds capacity inmates are released into Gold Beach.

Are there changes in the 

ways that the BLM 

manages its resources that 

would increase your 

community’s capacity and 

resiliency?

If BLM’s management could result in increased payments to Curry County 

then pressure on the County’s budget would decrease and make it more 

likely that county services in the city are maintained.
1551 | P a g e

City of Drain

Date: July 25, 2014 

Participants:

Suzanne Anderson, Mayor; City of Drain 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Mayor Anderson provided written responses to the questions. These are provided verbatim, followed by 

input from the personal interview. 

Table P-23. City of Drain interview 

Question Discussion/Response

How do you view your 

community’s ‘capacity,’

that is your community’s

ability to face changes,

respond to external and 

internal stresses, create,

and take advantage of 

opportunities, and meet its 

needs?

Written response

In times of sustainable economic growth, our community has the ability to

take advantage of opportunities to create new jobs, businesses and focus on

increasing the overall health and prosperity of our community. Also, we can

focus on infrastructure improvements, including streets and utilities (electric, 

water, sewer & communications).

Interview

Mayor Anderson (Suzanne) said she had lived in Douglas County all her life. 

She said that unemployment in Drain was around 40% versus the 10% figure

cited in the data from the Census. She said the logging population had fallen 

drastically, due to lack of demand and mechanization of the logging

industry.

Drain is down to only one working mill, Emerald Forest Products, which

trucks veneer in to be dried, and then ships the dried veneer back to other

plants to make plywood. Drain’s population is not growing and enrollment at

the city’s combined elementary/middle school and high school has declined

from about 500 to 345. Nevertheless, the school district remains one of the 

largest employers.

How do you view your 

community’s ‘resiliency,’

that is your community’s

ability to adapt to change

over time?

Written response

DIFFICULT! Significant changes (governmental policies, recession, etc.)

resulting in job loss and less income flows significantly affects our ability to 

maintain community stability. When these changes occur the overall socioeconomic health of our community declines and it is very difficult to adapt

to changes without corresponding changes in governmental policies that

create opportunities for socio-economic growth.

Interview

It is difficult for a small city to actively “adapt.” The city did however have a

recent success— as much by chance as by effort. Malcolm Drilling, a

specialty-drilling contractor in the deep foundation industry, purchased 
1552 | P a g e

Question Discussion/Response

Drain’s former North Douglas Wood Products facility in 2013, and is now

one of the city’s major employers.

Local colleges are gearing more programs to help former loggers find the

assistance they need to start new careers, though the older generation loggers

are finding it difficult to transfer their skills into new trades or professions.

Mayor Anderson has seen the city of Drain struggle as mills closed and 

Douglas County lost funding from timber receipts. The city is unable to

fund a police force and therefore contracts with the County’s deputies to fill

this need. The countywide library system has also suffered, and lacks

funding to upgrade computers and other services. Other services the county

provides that affect the city are the jail, health and social services, and

juvenile services.

How do the ways the

BLM manages its

resources affect your

community (its capacity 

and resiliency)?

Written response

It has a direct effect on our community. BLM’s statutory authority for 

managing resources on O&C and Coos Bay Wagon Road (CBWR) lands is 

the O&C Act of 1937. This law dedicates the O&C and CBWR lands to 

permanent timber production through long-term sustained forestry to help 

support local communities and O&C county governments with revenues 

from the sale of timber and by supplying timber to local industries for the 

purpose of creating jobs and income. BLM’s management direction must, 

therefore, give the highest priority to achieving those results. Planning 

decisions for the management of these lands must be designed to: (1) create 

jobs and income flow within the O&C Counties; (2) create opportunities for 

growth in the timber and related industries; (3) provide a sustainable source 

of revenues to O&C Counties based on the principles of sustained yield 

timber production; (4) increased tax revenue to the State of Oregon; and (5) 

contribute to the stability of communities in Western Oregon.

Fifty percent of the receipts from the sale of timber from the O&C lands are 

distributed to the 18 O&C Counties in which the lands are located. That 

50% is distributed to the Counties according to their proportion of the total 

assessed value of the lands and timber that existed in each of the Counties in 

1915. These percentages range from 0.36% to 25.05% for the 18 Counties. It 

does not matter in which Counties the timber is harvested. All Counties get 

their assigned percentages of whatever receipts are available each year. In 

Douglas County, we receive about 25%.

The receipts are available to O&C Counties without restriction to be used 

for essential services, including especially public safety programs such as 

sheriff’s patrols and corrections, as well as health and social services, 

libraries and programs for juveniles and seniors. These services have both a 

direct and indirect effect on residents of my community.

Interview

Suzanne said that historically Douglas County has been one of the highest 

recipients of payments to counties, making it more dependent and more 
1553 | P a g e

Question Discussion/Response

vulnerable.

Suzanne said the city did not benefit from the BLM’s recreational resources.

Have changes in the

BLM’s resource

management over time

affected your community? 

In what ways?

Are there changes in the

ways that the BLM

manages its resources that

would increase your

community’s capacity and 

resiliency?

Major changes in forest policies occurred in 1995 and continue today that 

significantly reduced BLM’s ability to manage the O&C and CBWR lands 

for permanent timber production through sustained yield forestry. 

Significant negative socio-economic impacts have occurred in the form of 

job loss and increased unemployment; reduced income flow; business 

closure and/or reduction in operations; and reduced County and community 

services. In addition, significant increases have occurred in crime activities, 

mental health and drug addiction issues, and other social impacts that have 

affected the quality of life for residents living within communities.

The healthy functioning of O&C County governments and communities they 

serve depends in substantial part on the BLM’s compliance with the O&C 

Act. Changes in the way BLM manages O&C forests to comply with its 

mandatory O&C statutory authority must be addressed in a land use 

planning revision for O&C and CBWR lands. Simply stated, BLM plan 

revisions must significantly identify the availability of more forestlands for 

timber production that can be sold, cut and removed on a sustained yield 

basis. This in turn will create sustainable economic growth in communities 

by taking advantage of opportunities to create more jobs and increase 

income flows; develop new businesses and revive old ones, and increase the 

overall health and prosperity of communities. If, on the other hand, BLM 

chooses to maintain the status quo or further reduce the availability of 

timber that can be sold and harvested on a sustained yield basis, 

communities will continue to decline from a socio-economic perspective. 

Without major changes in the way BLM manages these lands, some O&C 

Counties will become incapable of providing essential County services and, 

therefore, cause communities residing within the O&C Counties to continue

to suffer and decline, which we have already recently experienced.

Interview

Drain currently only has logging rights on private lands, and the Mayor feels

that the area could significantly benefit from gaining access to logging on 

Federal lands. There have been clashes between cities and

environmentalists, making it difficult for the cities to move forward in a way

that could be mutually beneficial. Cities are required to agree to numerous

environmental regulations, which the Mayor feels that Drain goes above and 

beyond these regulations and is still experiencing push back from 

environmentalist groups.

The Mayor points out that the BLM should have a leadership role in these

timber disputes and considers all possibilities and outcomes.
1554 | P a g e

City of Florence 

Date: July 31, 2014 

Participants:

Larry Patterson, City Manager Pro Tem; City of Florence 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-24. City of Florence interview 

Question Discussion/Response

How do you view your 

community’s ‘capacity,’

that is your community’s 

ability to face changes, 

respond to external and 

internal stresses, create, 

and take advantage of 

opportunities, and meet its 

needs?

Larry Patterson (Larry) moved to the State of Oregon in 1986 and served in 

city administration in Bend and Oregon City, retiring in 2010. Larry 

recently joined the City of Florence as an interim City Manager.

Florence is a coastal resort town with a large elderly population. 

Recreational tourism is important to the City, with the coast, golf, fishing, 

and a casino as major draws.

Larry sees Florence’s capacity being challenged, as the city experiences a 

weak overall economy and more and more costs forced upon it because of 

declining intergovernmental fund transfers. The City had about a 16% 

population increase between 2000 and 2012. The city’s 65 years and older 

population (37%) is more than triple the share for the state of Oregon. Larry 

sees this high retiree population as posing some limits to contributing to the 

city’s capacity—indeed the city’s median household income is $35,000, at 

the lower end of the cities that were interviewed. Larry pointed out retirees 

with higher incomes (like in Bend, OR) have a greater positive fiscal impact 

for a city.

The city’s hospital and ambulance services are important to the large elderly 

population, and in tandem with these services is the higher demand for 

public transportation. The city ambulance service is provided by a private 

company, and supplemented with first responder service from the fire 

department.

The Three Rivers Casino, owned and operated by the Siuslaw tribe of 

Native Americans, is located just east of the city. Larry feels that spillover 

spending in the city by casino guests is small though he thinks there are 

opportunities for stronger, mutually beneficial connections between the city 

and the casino. For example, he thinks both could benefit from more hotel 

rooms.

How do you view your 

community’s ‘resiliency,’

that is your community’s 

ability to adapt to change 

over time?

The city’s traditional economy was based on timber and fishing. Both have 

declined. Florence had an icehouse but it was moved down the coast to 

Coos Bay (to a more direct location), and the city lost the jobs and 

associated business activity.

The city has sought to adapt to changing circumstances by focusing on 

tourism but tourism does not provide the stability of the traditional 

industries. Tourism in Florence is very seasonal and though tourism 
1555 | P a g e

Question Discussion/Response

provides a continuum of jobs, many are lower paying jobs.

Florence’s main draw is its location on the Oregon Coast, but it has limited 

accessibility. It is on the Oregon Coast Highway (US Highway 101) but is 

not close to I-5. Larry feels that the city needs a vision and plan to grow its 

tourism industry. The city needs more hotel capacity and development of 

the “shoulder” seasons (extending the visitor season later into the Fall and 

Winter when the weather from time to time can be very pleasant).

Florence has far less resiliency compared to larger cities; larger cities can 

recover more quickly from adversity.

There is a budget proposal for a local gas tax increase in Florence in an 

effort to increase revenue for street improvements. Larry feels that, like all 

money measures, passage of such a measure will always be a challenge. A 

five-year moratorium imposed by the State legislature was recently lifted, 

meaning local governments are now able to seek voter approval for such gas 

tax increases.

How do the ways the 

BLM manages its 

resources affect your 

community (its capacity 

and resiliency)?

Larry sees the direct day-to-day impact from the BLM as small. He did 

point out that the BLM administers property with sand dunes on the north 

side of town. The BLM’s lack of maintenance has meant that the city has 

had to take responsibility for removing sand. Sand removal affects roads 

and also affects local business such as Fred Meyer and the Sandpines Golf 

Links.

In the bigger picture he thinks that the BLM’s management affects the 

counties, and, in turn, the cities. As timber receipts have declined, jobs have 

been lost and discretionary funds for cities, streets, social services watershed 

enhancements along with other services have been cut.

Larry sees the cost of fighting forest fires are a significant issue for Western 

Oregon. The costs are huge (one fire he cited cost $70 million) impacting 

State budgets and subsequently impacting Counties and cities as resources 

are directed away from other priorities. These cuts affect the entire State and 

therefore affect cities like Florence.

Have changes in the 

BLM’s resource 

management over

time affected your 

community? In what 

ways?

Are there changes in the 

ways that the BLM 

manages its resources that 

would increase your 

community’s capacity and 

resiliency?

Larry does not have answers to how to manage the forest. However, he feels 

strongly that a healthy forest industry is needed. The healthier the forest is 

the greater its ability to bring about positive economic effects on 

communities. An increase in the timber yield would benefit the local 

communities like Florence as well as the counties.
1556 | P a g e

City of Grants Pass 

Date: July 30, 2014 

Participants:

Simon Hare, County Commissioner; Josephine County 

Aaron Cubic, City Administrator: City of Grants Pass 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-25. City of Grants Pass interview 

Question Discussion/Response

How do you view

your community’s

‘capacity,’ that is

your community’s

ability to face

changes, respond to 

external and internal

stresses, create, and

take advantage of 

opportunities, and 

meet its needs?

Aaron Cubic (Aaron) has been with the city for two years having previously 

served in Roseburg. Commissioner Hare (Simon) is a south Oregon native. He 

lived elsewhere for around 10 years, including a stint with the Federal

government in Washington DC. He returned to Oregon and been a Josephine 

County Commissioner since 2011.

Aaron said that Grants Pass overall is doing relatively well based on several 

measures of capacity (such as population growth, employment diversity, per 

capita assessed property value). The city ranks high for livability. The city had a 

50% population increase between 2000 and 2012. However, the poverty rate in 

2012 was 21%.

Aaron said the city has been striving to retain existing businesses and maintain a 

viable workforce, as it has navigated a shift from a timber and natural resourcebased economy to a more diversified economy. He said that tourism and 

healthcare were important sectors of the local economy. The government sector 

is also important since Grants Pass is the county seat. Aaron praised the 

community college for doing a great job of matching people with the skills they 

need to find work, especially former timber employees.

Simon added that he feels the city is at a “tipping” point with respect to 

responding to the impacts and effects of the management of forest resources. As 

an example he recounted that the last sawmill in Josephine County (Rough and 

Ready) had to close in 2012 for lack of inventory. It had been in the county for 

92 years and had provided 85 jobs, historically as high as 225. Fortunately, it is 

expected to reopen with approximately 70 jobs in the near future. State funds 

have helped the mill with retooling.

Recreation is important to the city and the county. The Rogue River is a 

particularly important resource.
1557 | P a g e

Question Discussion/Response

How do you view

your community’s

‘resiliency,’ that is

your community’s

ability to adapt to

change over time?

Grants Pass benefits from its relative size and capacity, but the city is highly 

dependent on the county. Simon said the city and county were “tied at the hip.”

Aaron feels that as the rural area has struggled economically due to the decline 

in the timber industry, the city has felt these effects both directly in strain on 

city services (public safety and social services) and indirectly due to reduced 

county funding.

As the county struggles to fund programs, the effects are felt by the city which 

lacks the resources to make up shortfalls. Ballot measures that would increase 

tax levies had majority support in the city, but failed overall due to insufficient 

support in the rural areas.

Josephine County administers services that are important to the city including 

juvenile services, the jail, the court system and district attorneys, and public 

health. Aaron says the city has been hit harder than other areas with the 

reduction of Secure Rural Schools (SRS) funding because of the decline in 

county resources that are now passed down from the county.

How do the ways the

BLM manages its

resources affect your

community (its

capacity and 

resiliency)?

Aaron and Simon said that the ways the BLM manages its timber resources 

directly affect the city. The BLM administers approximately 300,000 acres land 

in Josephine County, close to 30% of the county land area. This includes one of 

the largest contiguous O&C land areas in Western Oregon along the Rogue 

River in the northwest part of the County.

If more Federal land were opened up for logging the timber industry would 

benefit and result in more timber-related jobs with direct beneficial impacts to 

the city, especially to former timber workers who are struggling to transition to 

new employment.

Simon said that when there was more logging on Federal lands Josephine 

county was receiving $10 to $12 million annually in shared timber receipts, 

whereas payments under the SRS are currently approximately $5 million. Of 

these monies, a good deal is spent on roads. Simon said the county spent $1.5 

million helping to maintain roads needed to access Federal lands.

Fire is a huge concern for Grants Pass. Large fires in 2013 (such as the 54,000-

acre Douglas Complex and Big Windy) effectively shut down the city causing 

economic losses, heat, human health effects, and negative reputational impacts. 

Reportedly, the Rogue River rafting companies lost $100,000 per day when 

they were unable to operate. Simon estimated that 25% of the fires in Oregon 

are in the BLM’s Medford District.

Have changes in the

BLM’s resource

management over 

time affected your

community? In what

ways?

Are there changes in

the ways that the

Simon acknowledges that there are no simple answers to the forestland 

management questions. He served on Governor Kitzhaber’s O&C lands task 

force and has some familiarity with the issues. He thinks that the management is 

unbalanced; 300% of the Northwest Forest Plan’s conservation goals were 

being achieved, but only 8% of the timber industry’s goals. He is looking to the 

new round of RMP’s for more balance.

In Simon’s view, if plans are written solely from the perspective of ecology,

they will not be effective; ecological set-asides with no management will lead to 
1558 | P a g e

Question Discussion/Response

BLM manages its 

resources that would

increase your

community’s capacity 

and resiliency?

more fires. He is interested in water quality, but not just for its own sake; the 

Rogue River, for example, supports a $15 million economy based on fishing 

(salmon, steelhead) and other recreation (Josephine County Parks Dept. Study).

Simon reiterated his feeling that Grants Pass/Josephine County are at a tipping 

point with respect to their resiliency. Absent change, the communities’ inability 

to deliver services will create a failed situation that will affect their reputation 

and send them into an economic spiral they will have great difficulty recovering 

from. The county’s tax rate (58 cents per $1,000 of assessed value) is the lowest 

in the State of Oregon. O&C Payments as proportion of the county budget is 

13% (only in Douglas County is the share higher). Simon acknowledged that 

the property tax rate is low but added that this low number should not be taken 

out of context because other taxes and fees make up the total tax burden.

There is strong community support for putting more forestland back into 

production and for clearing the dead/dying timber. Simon serves on the 

Interagency Salvage Committee. What, he asks, are they going to do with the 

75,000 acres that burnt in the fire? He finds it very frustrating that a new plan 

has to be prepared after each fire. There should be an overall plan that is 

mutually agreed upon under which actions can be taken without unnecessary

“reinventing the wheel.”

Simon feels that in the past when there were more people (including loggers) in 

the forest and the roads were more actively managed, these people in a sense 

were the first responders and were able to provide faster response times to 

emergencies. Now he sees fires escalating more rapidly as first responders are 

faced with overgrowth and blocked access roads.
1559 | P a g e

City of Klamath Falls 

Date: July 23, 2014 

Participants:

Nathan Cherpeski, City Manager; City of Klamath Falls 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-26. City of Klamath Falls interview 

Question Discussion/Response

How do you view your 

community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and internal 

stresses, create, and 

take advantage of 

opportunities, and 

meet its needs?

Nathan feels that Klamath Falls is challenged in terms of capacity. Traditionally 

the city was a natural resource-heavy, resource dependent community, with lots 

of lumber mills. Workers were able to get decent, well-paying jobs without 

having, necessarily, a high level of education. With the decline in the timber 

industry, much of the supporting timber infrastructure has disappeared and the 

city has struggled.

Today the census data indicate the challenges: poverty rate of 24% (compared 

to 15% for Oregon); high number of lower paying jobs, relatively low rate of 

homeownership (42%), only 8% of jobs in manufacturing, unemployment rate 

of 10–12% (Bureau of Labor Statistics Klamath county data for June 2013–May 

2014). Nathan cites as factors the loss of resource-based jobs and an influx of 

lower income retirees. While the population of the city is approximately 21,000, 

the area population is around 40,000.

The city is surrounded by forest and recreation land. The city is the closest 

community to Crater Lake National Park, making it a destination. Klamath 

County has the highest per capita amount of outdoor recreation land (34,300 

acres) compared to the other counties in the capacity/resiliency assessment. 

Tourism is important to the economy, but jobs in the tourism sector do not pay 

as well as those in manufacturing.

The city’s interior location off the interstate highway grid makes it hard to 

attract new industries. The city’s largest job sectors are Health Care and Social 

Assistance, Education, and Retail. Oregon Institute of Technology, the only 

public institute of technology in the Northwest U.S., is a strong city asset.

How do you view your 

community’s

‘resiliency,’ that is 

your community’s 

ability to adapt to 

change over time?

Nathan says that the city is still a timber town at heart – the wild west. Opinions 

vary; some residents look back fondly at the older timber-dependent economy 

and yearn for a return. Others see the need to forge a new path.

Nathan points out that the city is seeking to adapt from its former timber-reliant 

economy to a more diversified economy, but the challenges make this difficult. 

In that sense, the city has not turned around. He feels that some of the city’s 

adaptation efforts have been stymied by an environmental interests/interest 

groups who are not from the area and do not have to live with the consequences 

of failed economic initiatives. Nathan gave as an example, a private developers 

interests/efforts to develop a ski resort (following the example of Bend) – which 

failed due to red tape and environmental concerns.
1560 | P a g e

Question Discussion/Response

Nathan questions whether the city is being given the tools (or conversely is 

being denied the tools) to be resilient and allow it to adapt.

The types of jobs that are interested in coming to the city are lower paying jobs 

such as call centers. Nathan spoke about the significant loss that the community 

felt about the Jeld-Wen’s decision to move its corporate, global headquarters 

from Klamath Falls to Charlotte, North Carolina. Jen-Weld, windows and doors 

manufacturer, was Oregon’s largest private company. As a result, 

manufacturing jobs remained while corporate executive jobs were lost.

As another example, Nathan cited Collins, a wood products company, where 

employment at its Klamath plant was once as high as 1,200 but has fallen to 

300.

Industry consolidations have left the city with old mill redevelopment sites.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

While Nathan did not single out the BLM, he felt that its decisions are part of a 

larger decision-making environment that has resulted in the city’s loss of 

capacity. The rules and regulations, which are formulated in metropolitan areas, 

have hurt and continue to hurt small rural cities.

The overall result is pressure on the city’s resources and strain on the social 

safety network.

The BLM and the U.S. Forest Service manage some of the access roads around 

Klamath Falls that connect residents and tourists with forestlands and natural 

areas. There is strong support among residents for more access to public lands 

(off-road vehicles) to allow the public to use the resources.

BLM’s management of other resources such as minerals have a minimal effect 

on Klamath Falls.

Have changes in the 

BLM’s

resource management 

over time affected 

your community? In 

what ways?

Are there changes in 

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

Nathan believes the supply should be increased – allowing a “reasonable”

amount of logging. His view is that as the timber harvest continues to decline, 

trees tend to be smaller and grow closer together, dying in the forest as opposed 

to being harvested. This results in unhealthy forest land which is prime tinder 

for forest fires, which the area experiences on an annual basis. Nathan cited the

Moccasin Hill Fire as a recentJuly 2014) example.

Nathan sees the importance for the BLM to manage the city’s public lands for 

more than only recreation and to provide more resource products.

These changes would positively impact Klamath Falls and increase its capacity 

and resiliency
1561 | P a g e

City of Junction City 

Date: August 14, 2014 

Participants:

Jason Knope, Public Works Director; City of Junction City

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-27. Junction City interview 

Question Discussion/Response

How do you view your 

community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and internal 

stresses, create, and 

take advantage of 

opportunities, and 

meet its needs?

Jason Knope (Jason) is a lifelong Oregonian. He thinks that Junction city’s 

capacity is fairly high which he attributes in part to strong community 

engagement that has broadened the city’s ability to meet its needs and face 

change.

Junction City is located approximately 15 miles northwest of Eugene and is 

surrounded by agricultural land in the Willamette River valley. The city benefits 

from its proximity to both rural and urban environments and opportunities. The 

city had a 15% population increase between 2000 and 2012.

The city has a strong manufacturing economic sector comprising approximately 

3,000 jobs, 25% of the jobs in a five mile radius (the largest in number of any of 

the cities in the sample— and Jason thinks the number may be closer to 35%). 

Historically this was due in part to the city housing the Country Coach 

Recreational Vehicle manufacturing plant. At its height, the company had 

between 500 and 600 employees. It went bankrupt in November 2009, but has 

recently reopened under the same name, though now with approximately 100 

employees focusing on refurbishing and modernizing RV interiors.

Jason said that the economy in Junction City is fairly diverse, though it has little 

today in the way of timber-related industries. He estimates that about 5% of the 

city’s workforce is directly related to the timber industry, or indirectly in a 

support capacity.

Jason added that some of the city’s labor force work in Eugene. There is a small 

tourism and visitation economic component, Junction City being in Oregon 

wine country—the city is gateway to the Long Tom agri-tourism trail.

How do you view your 

community’s 

‘resiliency,’ that is 

your community’s 

ability to adapt to 

change over time?

The city’s traditional economy was based on timber and farming, but as noted 

above is now quite diverse. Jason feels the city has done a good job in 

diversifying after the decline of the timber industry. He attributes this in part to 

geography and locational opportunities (the city is located on Oregon Route 99 

truck route) but also, in his opinion, to unusually strong community engagement 

and involvement that has led to development of a strong community vision. For 

example, Jason points out that the city currently has three different committees 

dealing with community development, looking at the potential ripple effects of 

different community development options in different locations in relation to 

the vision for the city’s future. These committees engage in “what ifs” – helping 

the city decide its investment and development policy.
1562 | P a g e

Question Discussion/Response

Agriculture in the area has also changed. Agriculture has always been an 

integral part of Junction City’s economic landscape, but Jason explains that 

there has been a shift from the traditional grass, hay and seed crops to organic 

crops; wheat and barley, and to biofuels. He estimates this sector now makes up 

between 40% and 50% of agricultural production.

Jason believes the city learnt lessons through its experience with Country 

Coach, primarily to push to broaden its horizons. It expanded its Urban Growth 

Boundary, examined its fees and rates schedules to ensure the city was 

attractive to development, invested in infrastructure, engaged the community, 

explored development scenarios, and looked for opportunities to diversify. This 

included a prison, which did not move forward, and a new psychiatric hospital, 

part of the Oregon State Hospital system, which is scheduled to open in 2015.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

Jason feels the direct day-to-day impact from the BLM on Junction City is 

relatively small. The city has moved on compared to 10–15 years ago when it 

was more timber-dependent.

He thinks there are two or three lumber mills outside town, inside the Urban 

Growth Boundary - Seneca Sawmill, Lane Forest Products, and Weyerhaeuser -

and perhaps one mill in town, a processing packing business that relocated from 

Eugene. However, as noted above, overall employment in timber industries is 

small.

In the bigger picture, he thinks that the BLM’s management affects the counties, 

and, in turn, the cities. Specifically, as timber receipts have declined, 

discretionary funds have been cut. Jason explains that until 2008 Junction City 

was receiving between $60,000 and $65,000 a year in timber receipts funds 

from Lane County for the city’s street fund. This was the second largest source 

of funding after gas tax receipts (approximately $300,000). The city no longer 

receives these monies, which is regrettable as the city was using them for 

pedestrian-related projects.

Have changes in the 

BLM’s resource 

management over time 

affected your 

community? In what 

ways?

Are there changes in 

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

Jason believes that an increase in timber production would have a positive effect 

on Junction City. Over time, the timber-related industries have shrunk to some 

degree, though he notes that they have not gone away entirely. More timber 

opportunities would certainly provide the community with more options and he 

sees a more reliable timber resource as a benefit to the area overall.
1563 | P a g e

City of Lincoln City 

Date: July 11, 2014 

Participants:

David Hawker, City Manager; Lincoln City

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-28. Lincoln City interview 

Question Discussion/Response

How do you view your 

community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and internal 

stresses, create, and 

take advantage of 

opportunities, and 

meet its needs?

Lincoln City has an interesting capacity mix. The assessed value of property in 

the city is high but residents’ incomes are low. This is due to the nature of the 

city as a vacation and second home destination on the Oregon Coast. Roughly, a 

third of the housing stock in the city is second homes, owned mostly by 

residents of Portland and Salem. It is the premiere beach town destination 

within driving distance of these larger municipalities.

Lincoln City serves a variety of residential and visitor markets. The city has a 

large number of short-term rental units (hotel, motel vacation rental dwellings); 

about 4,000. This helps make it a fairly inexpensive place to visit. A variety of 

well-priced long-term rentals are also available. With its low cost of living, it 

also attracts retirees. This variety provides a high flux of visitors and seasonal 

residents over the course of the year, and the city accommodates and benefits 

from this variety.

The city is home to a retail outlets mall and the Chinook Winds Casino,

operated by the Confederated Tribes of the Siletz.

Low resident incomes are due to the concentration of employment in retail, 

accommodation, and food service jobs. This includes seasonal employment.

David feels that Lincoln City has high capacity because its economic diversity 

makes is less sensitive to economic ups and downs. Low resident income is a 

concern but is offset to some degree by the property tax base and visitor 

spending.

How do you view your 

community’s 

‘resiliency,’ that is 

your community’s 

ability to adapt to 

change over time?

Resiliency was to some extent thrust on the city. During the 1960s, partially as a 

result of the Clean Water Act, three cities and three unincorporated areas 

became incorporated as the City of Lincoln City. This created rational, 

consolidated boundaries for efficient delivery of city services.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

The BLM has very little direct effect on the city. Approximately 60% of 

Lincoln City’s watershed is in Federal ownership, but the BLM owns very little 

compared to the USFS. Water quality could be a major concern, but the decline 

in logging since the 1990s on all Federal lands has meant that potentially 

impactful logging practices have not occurred.

Have changes in the 

BLM’s resource 

Recreation is a major component of Federal land management in the area. What 

drives tourism in Lincoln City is the beach but, increasingly, opportunities to 
1564 | P a g e

Question Discussion/Response

management over time 

affected your 

community? In what 

ways?

Are there changes in 

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

experience the spectacular landscape and natural areas by hiking, trails, and 

scenic viewing, hunting and fishing. For example, the U.S. Forest Service 

maintains the Cascade Head National Scenic Research Area in the Siuslaw 

National Forest, which has congressional legislative limits for activities. While 

logging on private lands occurs, David was not aware of Federal timber sales.

Whatever the BLM can do to maintain and increase access to this landscape for 

recreation would benefit Lincoln City. David speculated that if land swaps 

between the BLM and the USFS could be affected, this could provide 

opportunities for better management.

The city does not benefit directly from timber payments to counties. David 

thought that payments to Lincoln County were earmarked for social services, so 

increases in payments could have an indirect beneficial effect on city residents.
1565 | P a g e

City of Molalla

The City of Molalla was unavailable for an interview. However, Molalla City Manager, Dan Huff, 

provided written responses to the questions. These are provided verbatim below, followed by some 

additional observations by ERM.

Table P-29. City of Molalla interview 

Question Discussion/ Response

How do you view your 

community’s 

‘capacity,’ that is your 

community's ability to 

face changes, respond 

to external and internal 

stresses, create, and 

take advantage of 

opportunities, and 

meet its needs?

Dan Huff written response

Today, Molalla is in a fairly strong position to react to change and respond to 

opportunities. Molalla never really grew up when the mills closed in the 1980s 

due to a large influx of residents that were commuting to Portland and Salem 

area employment. Because of that change, the city did not have to face that 

changing economy until the late 2007–2012. Today our capacity and 

infrastructure is managed for growth and expansion, capitalizing on the 

recreation and agriculture in the region.

Additional observations

The city benefits from its proximity to both Portland and Salem, which are 

about 30 and 40 miles away, respectively.

Molalla has experienced a significant population increase (42%) between 2000 

and 2012. At just over 8,000 residents, the city has a relatively low percentage 

of its population below the poverty level (11%) compared to the State 

percentage (15%).

Molalla is the gateway to the Molalla River Recreation Corridor, attracting 

visitors year-round for sightseeing, fishing, hunting, water sports, camping, 

mountain biking, and horseback riding.

How do you view your 

community’s 

‘resiliency,’ that is 

your community’s 

ability to adapt to 

change over time?

Written response

Molalla is a tough town and people choose to live here today. The economic 

and fiscal storms have not changed the longtime resident’s belief in their 

community as a great place to live or come home to. Molalla has adapted and 

accepted that part of its role is as a commuter city but with a vibrant past that is 

connected to timber.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity

and resiliency)?

Written response

BLM’s management of resources in the Molalla River corridor have not 

impacted the recreation component of this area recently. We do have some 

timber related jobs but there is not much timber-related activity in town today. 

Four in-town mills have closed since the mid-eighties and periphery businesses 

like saw shops, and equipment dealers go with the mills. There are two mills 

north of town, and the former in-town mills are redevelopment sites today. The 

old sites are now being looked at for redevelopment - one redevelopment area at 

the south end of town is now a bark and chip mobile unit.

Have changes in the 

BLM’s resource 

Written response
1566 | P a g e

Question Discussion/ Response

management over time 

affected your 

community? In what 

ways?

Are there changes in 

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

Resource management has removed the historic job market from the area. 

However, Molalla continues to pursue other opportunities as a bedroom 

community to Salem and Portland. Because the farm or mill to market 

transportation corridors are not as high volume with trucks highway 

maintenance dollars have decreased in the area over the years at the State level.

At this point probably not. Other than promotion of recreation, I am not sure 

how resource management would greatly impact the community today.
1567 | P a g e

City of Rogue River 

Date: July 22, 2014 

Participants:

Pam VanArsdale, Mayor; City of Rogue River

Mark Reagles, City Administrator: City of Rogue River 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-30. City of Rogue River interview 

Question Discussion/Response

How do you view your 

community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and internal 

stresses, create, and 

take advantage of 

opportunities, and 

meet its needs?

Mark has been with city for 20 years. He is a 4th generation Oregonian. Both he 

and his father worked in the timber industry and lost their jobs (Roseburg 

Lumber). He said that the City of Rogue River’s capacity is closely tied to the 

timber industry. As the fortunes of the timber industry have ebbed and flowed, 

so have the city’s fortunes – wreaking havoc with its economy and capacity.

Before the 1970s, Rogue River had more than one mill. The city’s one 

remaining mill (owned by Medford Corp) burned to the ground in 1990. It was 

rebuilt then sold, and resold, closing for long periods during transitions. The 

mill, located by I-5, is now owned by Murphy Plywood. It employs 

approximately 150 people – and is the largest employer, and taxpayer in the 

city. Murphy plans to add another shift, which could increase the number of 

jobs to about 250. Mark pointed out that timber-related employment is more 

widespread including truck drivers, loggers, construction workers, and 

machinists. The Rogue River School District is the second largest employer.

The city lost over 400 residents (18%) between 2000 and 2012 and has an 18% 

poverty rate. Mark said that the city has seen an increase in retirement-aged 

residents and a decline in the school-aged population, to the point where one of 

the city’s four schools had to close. In the late 1980s and 1990s retirees were 

coming from California; people interested in enjoying Oregon’s great quality of 

life.

Mayor VanArsdale (Pam) said that the city has seen a shift to service and retail 

jobs, but these jobs tend to be low wage compared to the higher, familysupporting wage jobs in the timber industry.

Recreational tourism is a small portion of the city’s economy. While the Rogue 

River is well known for rafting, that activity takes place upstream of the city. In 

2009, the Savage Rapids (irrigation) Dam between Grants Pass and Rogue 

River was removed. While this benefitted fishes and fishing in the Rogue River, 

the city lost the lake behind the dam, which was used for boating. The city 

considered it a loss –the city gets little economic benefit from fishing.

How do you view your 

community’s 

‘resiliency,’ that is 

your community’s 

ability to adapt to 

Rogue River has struggled to adapt from a timber-reliant economy to a more 

diversified economy. The lack of diversity makes the city less resilient. Mark 

pointed out that because the city is small the ebbs and flows in timber-related 

employment have major direct and ripple impacts on the community. Rogue 

River cannot compete with the larger cities.
1568 | P a g e

Question Discussion/Response

change over time?

For example, he noted that during the 2007–2009 recession, the mill’s assessed 

value fell from $13 million to $3 million—with severe effects on city tax 

revenues.

The city’s loss of population is an indication of the city’s resiliency challenges.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

Mark feels that the way the BLM manages its timber resources directly affects 

the City. If more Federal land were opened up for logging the timber industry 

would benefit and result in more timber-related jobs with direct beneficial 

impacts to the City. With a stronger timber industry, more stable jobs could be 

offered and more people would set up roots in the community. This would result 

in more school-aged children being added to the school system, creating the 

need for hiring more education jobs.

In places where the BLM has cut roads into the forestlands and properly 

managed these roads, it is easier for emergency vehicles to access particularly in 

the case of a forest fire.

The BLM management of recreation resources has limited effects on the City. 

However, Mark did note that the BLM is working with a local group to open up 

an area for mountain biking approximately two miles from the City on the 

Rogue River Greenway, a 30-mile partially complete greenway between the 

Cities of Grants Pass and Central Point.

Have changes in the 

BLM’s resource 

management over time 

affected your 

community? In what 

ways?

Are there changes in 

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

In Mark’s and the Mayor’s view, the BLM should actively “manage” its lands 

and “use” the resource. Enough land has been preserved and timber should be 

cut which would have multiple benefits: economic (as described above); help 

manage the risk of fire, and, as a side benefit open up areas for hunting – for 

food and for recreation. Mark said he is a hunter and hunts on private and public 

land – he finds the hunting is better on private lands that are managed.

Mayor VanArsdale felt that the forestland can be managed to meet both the 

environmental interests and economic interests, which will make for a more 

well-rounded economy.

Mark feels that the BLM should allow more timber sales and boost the supply. 

He thinks the decline of timber is a supply issue – not an issue of jobs moving 

overseas.
1569 | P a g e

City of St. Helens

Date: August 26, 2014 

Participants:

John Walsh, City Administrator; City of St. Helens 

Susan Conn, City Councilor; City of St. Helens 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-31. City of St. Helens interview. 

Question Discussion/ Response

How do you view 

your community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and 

internal stresses, 

create, and take 

advantage of 

opportunities, and 

meet its needs?

John Walsh has served as City Administrator for St. Helens since 2012. Susan 

Conn has served as a City Councilor since 2012, and is a long-time resident. 

John had previously worked in Coos County and is familiar with timber issues.

John noted that the city’s capacity numbers look good with high population 

growth, a high working-age population cohort, and high median household 

income. However, he said that the numbers don’t tell the whole story.

John and Susan said that historically the city was a mill town and had several 

mills but the city has experienced a steady drop-off in timber-related 

employment in recent decades culminating in the closure of a Boise Paper plant 

in 2012; the plant had been winding down over time, but all told, the job losses 

totaled approximately 900. John said this was a devastating social blow for the 

city. The one remaining mill is the Cascade Tissue plant, which has 

approximately 60 jobs—a huge change for the city.

John described St. Helens as a healthy, middle-class town, but essentially a 

bedroom community for Portland and Hillsboro, both approximately 30 miles 

away. Hillsboro is the location of one of Intel’s product development and 

manufacturing campuses, and is the largest private employer in the State. John 

estimated that about three-quarters of St. Helens’ residents commute out of the 

city to work. John and Susan said that while the city is fortunate to have this 

proximity to jobs, the jobs are not “in the city” and the result has been a loss of 

social cohesion. As examples, John cited the decline in participation in 

charitable organizations and social clubs such as the Kiwanis. Susan noted that 

three bookstores, including her own, had closed.

St. Helens is the county seat of Columbia County and public administration is 

one of the larger job sectors (11%).

St. Helens owns a 2,500-acre tree farm which it harvests for sale; no old growth.

How do you view 

your community’s 

‘resiliency,’ that is 

your community’s 

ability to adapt to 

change over time?

John noted that change has been thrust on the city. The mills had provided 

commercial tax base and had supported the public utilities. With the mills’ 

decline and the city’s loss of income and inability to raise revenue due to tax 

caps, the city has had to enact double-digit rate utility increases over the past 

five years and has reduced its workforce by 30%. He noted that the tax rate, 

$1.90 per $1,000, is unchanged since 1995. As a result, revenues only increase if 
1570 | P a g e

Question Discussion/ Response

the assessed value goes up, but this too is capped.

John said that the State has been doing a good job of retraining the workforce as 

fewer Oregonians are employed in the timber industry. Susan said that older 

generations have been especially affected by changes in the economic landscape 

in St. Helens.

John said that the city is fortunate in that residents have alternative job options 

in Portland and Hillsboro. He thought that total employment was back to prerecession levels, but not the same jobs.

The city is working to adapt to the new economic environment. John said that 

the large mills were located along the Columbia River waterfront, which limited 

public access to this area. The city is working with Boise in order to acquire 

those properties and transition to new uses. The planning effort includes design 

collaborations between the city, Portland State University, and the American 

Institute of Architects.

However, both he and Susan acknowledged that lack of a bridge over the 

Columbia river to I-5 is a major impediment to the city’s economic 

development.

John felt that generally cities had more resiliency compared to counties because 

the counties were tasked with more services and the cities had more options to 

raise revenues.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

There is relatively little BLM land near St. Helens, compared to many of the 

other cities in the sample, but the city is affected by the way the BLM manages 

its resources in that the county has cut services. Susan noted that the county got 

close to closing the jail in the city.

John said that the city had never received pass-through Federal timber funds 

from Columbia County, and so had not relied on such funds.

Have changes in the 

BLM’s resource 

management over 

time affected your 

community? In what 

ways?

Are there changes in 

the ways that the 

BLM manages its 

resources that would 

increase your 

community’s capacity 

and resiliency?

John sees a sustainable timber harvest as the key to increasing community 

capacity and resiliency. He did not think the entire decline of the timber industry 

was attributable to the BLM; there were many other factors to consider. He 

noted that St. Helens had not been affected by the forest fires that had affected 

other parts of the State.
1571 | P a g e

City of Sublimity 

Date: July 28, 2014 

Participants:

Sam Brentano, County Commissioner; Marion County Board of Commissioners, former Mayor of 

Sublimity 

Hitesh Parekh, Management Analyst; Marion County 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-32. City of Sublimity interview 

Question Discussion/Response

How do you view your 

community’s

‘capacity,’ that is your

community’s ability to 

face changes, respond

to external and internal

stresses, create, and

take advantage of 

opportunities, and 

meet its needs?

Commissioner Brentano (Sam) is a former Mayor of Sublimity (1983–1993) and 

understands its unique needs and challenges. He recalls that Sublimity was

formerly an almost entirely agricultural- and timber-based economy, which has

shifted dramatically in recent decades as all the mills in Marion County have 

closed. He recalled that in the 1970s and 1980s there were mills in many of the

nearby towns and many mill owners lived in Sublimity; at that time, he said, the

city had a high per capita income.

Today he described Sublimity as a healthy, middle-class town – but essentially a

bedroom community for Salem. There is little or no involvement by the city’s

residents in forest-related industries, whereas these used to be a key source of

economic vitality.

In spite of high household incomes (Sublimity’s was the highest among the

cities interviewed) its tax base is too low to cover many necessary services. The

city contracts with Marion County for public safety (Sheriff), and relies on the

county for many services including public safety, courts, and solid waste. The 

county spends 80% of its general fund on these services.

The city depends on the county for so many services that as the county’s ability

to provide services is strained, the city’s capacity is reduced.

How do you view your 

community’s

‘resiliency,’ that is

your community’s

ability to adapt to

change over time?

The city has changed over time as described above. Sam said that Marion 

County, by having less BLM acreage, is not as dependent as other O&C

Counties on timber.

The county payments (Secure Rural Schools and PILT) help, but they currently

total $5 to $6 million a year and make up a small share of the county budget.

How do the ways the

BLM manages its

resources affect your

community (its

capacity and 

resiliency)?

Sam said that the BLM owns approximately 20,000 acres of land in Marion 

County while the U.S. Forest Service owns 200,000 acres making the BLM’s

impact on the county lower than in other counties.

Sam’s concern is with the way the BLM (and other agencies) manages the

timber resources. In his view, it should be treated like a crop and managed to 

help communities. This is not how the timberlands are currently being managed, 

and as a result, they contribute little to the community’s capacity. In some 

respects, lack of management is a drain on resources. For example, the county

has to spend timber dollars to pay for Sheriff’s deputies to patrol around the
1572 | P a g e

Question Discussion/Response

forest. Sam thought there was more Federal patrol oversight in the past.

Sam also believes that the mismanagement contributes to the number and extent

of forest fires.

The BLM has some small recreation areas near Sublimity, which are used by

residents, namely the Elkhorn Valley Recreation Site (Little North Santiam

Recreation Area, Yellowbottom Recreation Site, and Fishermen’s Bend). These

are small and contribute little to overall community capacity.

Have changes in the

BLM’s resource

management over time

affected your

community? In what

ways?

Are there changes in

the ways that the BLM

manages its resources

that would increase 

your community’s

capacity and 

resiliency?

In Sam’s view, the key to increasing community capacity and resiliency is a

sustainable timber harvest. The lack of timber harvest has hurt communities by

reducing income and leaving a resource that is simply waiting to burn – this is

bad policy.

The market is there for Oregon. Canada stepped in and took market share as the

U.S. stopped producing.
1573 | P a g e

City of Winston

Date: August 25, 2014 

Participants:

Sharon Harrison, Mayor; City of Winston 

Ken Harrison, former U.S. Forest Service employee

Kevin Miller, Superintendent; Winston-Dillard School District 

David M. Van Dermark, City Manager; City of Winston 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Kristina Higgins, Intern; ERM 

Table P-33. City of Winston interview 

Question Discussion/Response

How do you view your 

community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and internal 

stresses, create, and 

take advantage of 

opportunities, and 

meet its needs?

Both Mr. (Ken) and Mayor (Sharon) Harrison are long-time residents of 

Winston, having owned and operated the Harrison Hardware store for over 20 

years prior to its sale in 2013. Ken is also a former timber industry employee; he 

worked for the U.S. Forest Service as well as private timber companies that 

worked with the BLM and the U.S. Forest Service.

The city’s population increased by 16% between 2000 and 2012 (from 4,613 to 

5,352), but Winston’s poverty rate in 2012 was 30%, twice the rate for the State 

as a whole.

Kevin said that Winston struggles with economic resources and is “living close 

to the bone.” The city is becoming a retirement community. While retirees help 

the city fiscally to some degree—paying property taxes, for example—they 

don’t tend to spend much and as a result do not contribute to the local economy 

as much as the family-wage jobs that used to be more prevalent. Kevin pointed 

out that the nearest major medical center is in Roseburg (roughly 10 miles 

north) where there is a VA hospital. Winston residents may spend their dollars 

in Roseburg when attending medical appointments.

David says that the city is open to development and is very business-friendly. It 

has capacity for growth and is ready to grow.

The Cow Creek Band of Umpqua Tribe of Indians owns land near Winston in 

the city’s growth area, but it has little impact on the city’s capacity. The Tribe 

raises alfalfa and beef cattle. The Tribe owns a casino in Canyonville 

approximately 25 miles south of Winston along Interstate 5.
1574 | P a g e

Question Discussion/Response

How do you view your 

community’s 

‘resiliency,’ that is 

your community’s 

ability to adapt to 

change over time?

Sharon says that Winston was and remains a timber-dependent community. 

Roseburg Forest Products, which is in Dillard about 3 miles south of Winston, 

employs 1,200–1,500 people at several mills. (This accounts for the high 

number of jobs in the manufacturing sector in a 5-mile radius around the City in 

the Census data). There were many layoffs there in 2008 but employment has 

almost recovered. Kevin added that mechanization has affected employment. A 

shift that used to require 100 people now needs only 30.

The city has struggled to adapt to a changing economy and demographics. 

Kevin said that in 1980s the school district had some 2,000 children; today there 

are approximately 1,400. There is a sense that the job growth is in Portland. The 

Winston community today is very mobile and people move to the jobs.

The community has also lost truck farms. New businesses such as wineries have 

opened but the wages, relatively speaking, are lower. Sharon feels the overall 

income in Winston has been reduced.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

Ken said that the BLM’s management practices affect the community greatly. 

He said that recent policy is marked by lack of management. The only tree 

cutting is thinning which leaves the old growth trees that can’t be touched due 

to the Endangered Species Act. Winston and the surrounding Douglas County 

have a huge forestland base – which is a renewable resource, unlike minerals, 

which are a one-time extraction. However, unlike 20 years ago when the BLM 

was more actively managing these lands and timber harvests were putting 

dollars into the county budgets, today the city does not get the benefits it used 

to.

David points out that in the past the cities were given pass-through funds from 

Secure Rural Schools to help manage their road maintenance. Winston received 

$100,000 annually (a quarter of its $400,000/year road budget) until these funds 

were stopped in 2010. The lack of O&C funds has resulted in raised costs to the 

city, such as IT, jail beds, and radio communication.

He does not blame the BLM; rather he puts the blame on environmental 

interests who file frequent lawsuits against the BLM. Kevin noted a recent 

lawsuit regarding the Elliott State Forest. The forest is part of the Common 

School Fund Lands to be managed for the benefit of the schools under the 

Oregon Constitution. A portion of the forestland, under the instruction of the 

State Land Board, is slated to be sold to a private entity, though environmental 

groups have claimed that this sale should not be allowed to take place. The 

Winston-Dillard School District has filed an amicus brief in support of the sale, 

as this will result in a harvest and sales benefits for schools.

Kevin said that the BLM is decommissioning roads – creating a more natural 

environment but limiting access to the forest. This is a serious problem with 

respect to access for first responders in the event of a forest fire, preventing 

access for emergency vehicles. In addition, this reduces forest access from a 

recreation standpoint.

Kevin did wish to point to an alternative education program; a collaboration 

with the BLM that teaches children about working in the forests and on stream 
1575 | P a g e

Question Discussion/Response

restoration. He sees this as a very beneficial program.

Have changes in the 

BLM’s resource 

management over time 

affected your 

community? In what 

ways?

Are there changes in 

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

David feels that if the BLM should get back to timber harvest and land 

management in the manner in which it did in the past. This would provide 

revenues and reduce the incidence of large forest fires and other problems. In 

his view, the BLM is not in compliance with the O&C Act - requiring that the 

lands be managed to contribute to the economic stability of local communities 

and industries.

He feels that there is worldwide market demand for timber products, as well as 

a need to harvest the timber in an efficient and economically viable way. 

Oregon produces Douglas-fir, a great tree for framing houses. As Oregon scaled 

down its harvest, Canada has been increasing its timber exports and sends logs 

to the U.S. to be milled.
1576 | P a g e

Confederated Tribes of the Grand Ronde Community of Oregon 

Date: July 8, 2014 

Participants:

Heather Ulrich, District Archaeologist; Bureau of Land Management 

Michael Wilson, Natural Resources Department Manager; Confederated Tribes of the Grand Ronde 

Community of Oregon 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Table P-34. Confederated Tribes of the Grand Ronde Community of Oregon interview 

Question Discussion/ Response

How do you view your 

community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and internal 

stresses, create and 

take advantage of 

opportunities, and 

meet its needs?

The word “community” needs to be understood broadly. It needs to consider the 

greater membership of the Grand Ronde tribes, not just those living on the 

reservation or in the tribally owned lands in the (unincorporated) town of Grand 

Ronde. The tribes have 5,000–6,000 members spread out over the lands that 

were ceded to the U.S. including, for example, in the BLM’s Roseburg and 

Medford districts. Mike said he would look for membership data to supplement 

the census data that is specific to tribally owned lands.

The Grand Ronde’s capacity has increased over time, for example, since the 

Northwest Forest Plan, but the Community still faces challenges in serving its 

members and meeting its mission. There are more jobs today than back then but 

this is not attributable to the BLM.

Funding for tribal functions comes from a variety of sources. Mike estimated 

the income from timber sales at approximately $2 to $3 million a year. The 

Tribes get the majority of their funds from the casino. The Tribe does not levy a 

property tax. Mike said he would look into measures of community 

income/wealth that might be comparable to, for example, the tax base of a city 

or county, in order to help the BLM understand the Tribes’ financial capacity.

The Grand Ronde has taken on community building functions such as housing, 

education, and health care. The State passed legislation allowing tribes to create 

their own police departments. Grand Ronde has a police department in the town 

of Grand Ronde (unincorporated), and has developed its own fire station. The 

members living in this area wanted to make sure they had these services (where 

county services were lacking).

The Tribes have established a “Spirit Mountain Community Fund” to support 

members and projects throughout the Tribes’ geographical areas of interest. The 

fund is supported by revenues from the casino. It has helped fund, for example, 

a charter school and an environmental project on the Willamette River.

How do you view

your community’s

‘resiliency,’ that is

your community’s

ability to adapt to

change over time?

The Tribes have shown their resiliency in the way they have diversified their 

economy; the Spirit Mountain Casino, for example, being a major economic 

driver. The diversification has helped the Tribe’s resilience.

During the recession, there was a significant drop in casino revenues.
1577 | P a g e

Question Discussion/ Response

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

Members have an interest in gathering plants when needed on BLM land, 

hunting, and access to places of spiritual significance. Mike felt the BLM has 

done a good job in meeting those needs and interests.

The way the BLM manages its timber resources affects the community. Many 

tribal members live in timber-dependent communities. The Grand Ronde sells 

timber from its reservation. The Tribes understand the need for mills, loggers, 

and competition. The BLM can play a role in maintaining the industry.

A healthy industry is important to support the services that are important to 

tribal members such schools, police, fire, and roads.

As Mike talks to people in the timber industry, the importance of having a 

predictable supply of raw material is very important. In addition, if the mills are 

too far away the logs lack value; competition is important.

Mike said he would send the forest management plan (10-year plan) for the 

Grand Ronde’s forest.

Mike did not see a direct correlation between the BLM’s resource management 

and the casino revenues that are driven by broader economic trends.

There are management issues on the micro level. For example, there is about a 

mile of boundary sharing on the eastern side of the Grand Ronde reservation, 

where the tribes share a road with the BLM.

Have changes in the 

BLM’s resource 

management over time 

affected your 

community? In what 

ways?

Are there changes in 

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

The lack of predictability in the timber market and sales has affected tribal 

members in that timber supports the broader economy. If the broader economy 

is doing well then the Tribes will benefit too.

The ways BLM manages cultural resources and natural resources/habitat affects 

the community. The BLM could work with the Tribes to find the right balance 

in protecting these resources, and provide more resource-based jobs to help 

industry.

With respect to hunting, there is disappointment over declining opportunities to 

hunt deer and elk - fewer openings and meadows due to lack of active 

management, so the hunting areas for those species have declined. But Mike 

thought this was more of a U.S. Forest Service issue than a BLM issue.
1578 | P a g e

Coquille Indian Tribe 

Date: July 14, 2014 

Participants: 

Brenda Meade, Tribal Chairperson, Coquille Indian Tribe 

George Smith, Executive Director, Coquille Indian Tribe 

Mark Johnston, Deputy Executive Director, Coquille Indian Tribe 

Clive Graham, Principal; ERM 

Jill Bellenger, Associate Consultant; ERM 

Heather Ulrich, District Archaeologist; Bureau of Land Management 

Table P-35. Coquille Indian Tribe interview 

Question Discussion/Response

How do you view your 

community’s 

‘capacity,’ that is your 

community’s ability to 

face changes, respond 

to external and internal 

stresses, create, and 

take advantage of 

opportunities, and 

meet its needs?

George gave a little background recent history about the Coquille Indian Tribe. 

The Coquille Indian Tribe was terminated in 1954, but the United States 

reinstituted Federal recognition to the Tribe and restored its full sovereignty 

rights in 1989. Tribal membership is now approximately 1,000 across five 

counties in southwest Oregon. The 297 number in the Census data only reflects 

the population on the approximately 6,500 acres in the Census Bureau’s 

boundary maps – mostly in the North Bend/Coos Bay area.

The 1954 termination “cut loose” the membership resulting in more assimilation 

into local communities compared to reservations such as Warm Springs. This 

means that the socioeconomic state of the Tribe is closely bound up with local 

communities; the counties and cities, such as Coos Bay and North Bend. For 

example, Coquille children attend community schools so when these schools are 

affected by cutbacks, tribal children and families are equally affected.

Southwestern Oregon was historically heavily dependent on timber and fishing. 

Coos Bay was an export center for the Oregon coast. Since the 1990s, there has 

been an 80% reduction in timber sales. As a result, Coos County and the Coos 

Bay area became economically stressed. The recession that began in 2007 was 

one more blow and the area has not recovered.

Brenda added that the Tribe is currently facing the strain of responding to 

increasing needs of the tribal membership; increased population and healthcare 

costs. Census data indicate a tribal poverty rate of 23% compared to 15% for the 

State as a whole.

The Coquille Indian Tribe is the second largest employer in Coos County, 

making it a vital part of the wider economic landscape.

In summary, the Tribe has internal capacity and resources but is located in a 

region of Oregon with macro level economic challenges that strain the Tribe’s 

capacity to meet its needs.

How do you view your 

community’s 

‘resiliency,’ that is 

your community’s 

The Tribe has shown its resiliency by its survival, resurgence, and recent 

population growth. The Tribe has adapted and continues to adapt to economic 

realities. The Mill Resort and Casino in Coos Bay is an important source of 

income for the Tribe, but revenues were significantly affected by the recession, 
1579 | P a g e

Question Discussion/Response

ability to adapt to 

change over time?

and only now are they beginning to climb back to pre-recession numbers. 

Overall, economic recovery in southwest Oregon has been much slower than in 

the metropolitan parts of the State.

The Tribe is engaged in economic development initiatives through the Coquille 

Economic Development Corporation. These include business ventures in 

forestry, arts and exhibits, gaming and hospitality, assisted living and memory 

care, high-speed telecommunications (Optical Rural Community Access 

Communications) and renewable energy.

Because tribal and tribal members’ fortunes are closely tied to the local 

communities, resiliency is also affected by the communities’ lack of resiliency. 

For example, Brenda pointed out that in attempting to address budget 

constraints, the Coos Bay School District went to a 4-day school week during 

the 2013–14 school year. This type of action affects tribal members’ lives.

How do the ways the 

BLM manages its 

resources affect your 

community (its 

capacity and 

resiliency)?

The timber industry is a major driver for Coos County and so that the way BLM 

manages its resources has a great effect on the community.

The Tribe owns the Coquille Forest, comprised of 14 separate parcels of former 

BLM timberlands in eastern Coos County, totaling approximately 5,410 acres. 

The Tribe is legally mandated to manage the forest consistent with BLM’s 

management practices. This places a financial management burden on the Tribe. 

Bureau of Indian Affairs funding covers some the need, but the Tribe has to 

supplement. The Tribe believes that the BLM’s practices are not all in the 

Tribe’s economic interests. For example, George said that BLM’s practices 

follow guidelines in the Northwest Forest Plan but that these guidelines go 

beyond the requirements of the Endangered Species Act and NEPA. As a result, 

the forests are becoming overgrown and are not being given the opportunity to 

regenerate.

The Tribe is proud of its management practices. The Coquille Forest is Forest 

Stewardship Council (FSC) certified.

The Tribe is very concerned about habitat, water resources, and water quality –

such as for salmon runs. George said that Tribal monitoring has been held up as 

a national model.

Mark said that BLM’s management of recreation resources had little effect on 

the Tribe. He did note BLM’s role in helping manage the local Dunes National 

Recreation Area at the mouth of the Umpqua River that attracted visitors and 

some spinoff visitation to tribal facilities near Coos Bay.

Have changes in the 

BLM’s resource 

management over time 

affected your 

community? In what 

ways?

Are there changes in 

Brenda feels that the Federal lands have not been managed well; very few jobs 

are generated. George added that the biggest change in resource management 

has been the decrease in the timber harvest. Practices have changed from 

allowing sales, Survey and Manage, then to only allowing thinning – all 

triggering lawsuits.

George feels that BLM’s forest management is driven more by risk aversion to 

lawsuits than by its obligations to manage for sustained yield. As noted above, 

he believes this has led the BLM to go over and above its obligations under the 
1580 | P a g e

Question Discussion/Response

the ways that the BLM 

manages its resources 

that would increase 

your community’s 

capacity and 

resiliency?

ESA and NEPA. A more balanced, science driven approach would increase the 

Allowable Sale Quantity (ASQ) which would result in higher timber sales and a 

stronger local economy; which would help the Tribe. The timber capacity is 

there; the forest is very productive.

Most of the Coquille land is in a trust from the Federal government, and the 

Tribe has been constrained by economic stress from litigations in the timber 

industry and increasing restrictions and requirements incurred by the BLM and 

other agencies related to how the Tribe is required to manage its timber. The 

way the BLM has been writing its management plans goes above and beyond, 

as George points out, what is required for endangered species protection and 

NEPA regulations.

The Tribe supports Federal legislation that would decouple management of the 

Coquille Forest from BLM management.

Brenda added that the Tribe is very concerned about fire; she believes that 

BLM’s management has been “cookie cutter” easy to administer but having 

negative consequences such as allowing the buildup of material that is fuel for 

fire.

Tribal lands are open to the public. The Tribe would like to work with the BLM 

to allow it to erect fences and gates to protect access to certain areas.
1581 | P a g e

Issue 6 

Would the alternatives result in environmental justice impacts (disproportionally high and adverse effects 

on minority, low-income, or Tribal populations or communities)?

Minority Populations Meeting Environmental Justice 

Criteria 

Table P-36. Minority populations meeting environmental justice criteria 

Geography Total 

Population

All Minorities Hispanic

Number Percent Number Percent

Oregon 3,836,628 563,921 15% 449,888 12%

Benton County

Summit CDP 66 33 50% 0 0%

Clackamas County

Barlow City 302 24 8% 87 29%

Canby City 15,770 1,264 8% 3,735 24%

Happy Valley City 14,050 3,900 28% 697 5%

Johnson City 657 50 8% 244 37%

Coos County

Glasgow CDP 1,057 232 22% 14 1%

Powers City 890 179 20% 83 9%

Jackson County

White City CDP 7,392 1,027 14% 2,301 31%

Josephine County

Merlin CDP 1,484 353 24% 65 4%

Selma CDP 579 56 10% 117 20%

Klamath County

Bonanza Town 418 51 12% 76 18%

Chiloquin City 766 603 79% 44 6%

Malin City 712 156 22% 555 78%

Merrill City 805 110 14% 416 52%

Lincoln County

Lincoln Beach CDP 1,982 482 24% 358 18%

Siletz City 1,400 441 32% 42 3%

Linn County

Crabtree CDP 308 49 16% 66 21%

Waterloo Town 320 35 11% 73 23%

West Scio CDP 163 40 25% 21 13%

Marion County 315,391 61,715 20% 76,429 24%

Brooks CDP 665 173 26% 88 13%

Four Corners CDP 16,472 4,555 28% 6,360 39%

Gervais City 2,475 754 30% 1,700 69%

Hayesville CDP 18,224 6,383 35% 6,891 38%

Hubbard City 3,154 920 29% 1,221 39%

Keizer City 36,402 4,673 13% 7,015 19%

Labish Village CDP 195 113 58% 128 66%

Mount Angel City 3,347 603 18% 953 28%

Salem City (1) 154,835 28,403 18% 30,565 20%
1582 | P a g e

Geography Total 

Population

All Minorities Hispanic

Number Percent Number Percent

St. Paul City 310 31 10% 73 24%

Stayton City 7,637 1,234 16% 1,535 20%

Woodburn City 23,879 9,067 38% 13,444 56%

Multnomah County 737,110 158,601 22% 79,791 11%

Fairview City 8,884 1,807 20% 1,268 14%

Gresham City 105,612 20,891 20% 21,074 20%

Maywood Park City 1,008 226 22% 4 0%

Portland City 585,888 131,729 22% 54,420 9%

Wood Village City 3,870 644 17% 1,160 30%

Polk County

Independence City 8,535 1,724 20% 3,271 38%

Tillamook County

Bayside Gardens CDP 804 156 19% 0 0%

Washington County 531,818 122,803 23% 83,085 16%

Aloha CDP 50,710 15,057 30% 10,664 21%

Beaverton City 90,254 25,072 28% 14,310 16%

Bethany CDP 20,505 7,914 39% 960 5%

Bull Mountain CDP 8,990 1,847 21% 224 2%

Cedar Hills CDP 9,273 1,919 21% 1,205 13%

Cedar Mill CDP (1) 15,118 2,919 19% 529 3%

Cornelius City 11,867 4,039 34% 5,916 50%

Forest Grove City 21,245 3,609 17% 5,338 25%

Hillsboro City 91,998 26,243 29% 22,885 25%

Oak Hills CDP 11,005 3,065 28% 418 4%

Rockcreek CDP 9,488 1,888 20% 572 6%

Tualatin City (1) 26,106 3,814 15% 4,852 19%

Yamhill County

Dayton City 2,537 820 32% 1,021 40%

Grand Ronde CDP (1) 1,451 677 47% 115 8%

Lafayette City 3,709 445 12% 904 24%

McMinnville City 32,092 5,672 18% 6,324 20%

Sheridan City 6,086 966 16% 974 16%

Tribes

Coos, Lower Umpqua, and 

Siuslaw Reservation and OffReservation Trust Land, OR24 12 50% 0 0%

Coquille Reservation and OffReservation Trust Land, OR (2) 297 166 56% 15 5%

Grand Ronde Community and 

Off-Reservation Trust Land, OR 473 381 81% 7 1%

Klamath Reservation, OR 17 11 65% 0 0%

Siletz Reservation and OffReservation Trust Land, OR 476 420 88% 19 4%

Warm Springs Reservation and 

Off-Reservation Trust Land, OR 3,960 3,657 92% 372 9%

Notes: Geographies meeting the 50 percent criterion shown in gray with black border; Geographies meeting the meaningfully 

greater criterion shown in gray 
1583 | P a g e

(1) Where a city or Census Designated Place (CDP) spans more than one county, the BLM assigned it to the county with largest 

share of population. 

(2) Shows 2009 American Community Survey 5-Year Data since 2012 data not available 

Sources: 

U.S. Census Bureau; American Community Survey, 2012 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; American FactFinder; http://factfinder2.census.gov; (July 2014). 

U.S. Census Bureau; American Community Survey, 2011 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; American FactFinder; http://factfinder2.census.gov; (July 2014). 

U.S. Census Bureau; American Community Survey, 2010 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; American FactFinder; http://factfinder2.census.gov; (July 2014). 

U.S. Census Bureau; American Community Survey, 2010 Census Restricting Data, Table DP05; American FactFinder; 

http://factfinder2.census.gov; (July 2014). 

U.S. Census Bureau; American Community Survey, 2009 American Community Survey 5-Year Estimates, Tables DP03, DP04, 

DP05, S1901 and S1701; American FactFinder; http://factfinder2.census.gov; (July 2014). 

Low-income Populations Meeting Environmental Justice 

Criteria 
1584 | P a g e

Table P-37. Low-income populations meeting environmental justice criteria 

Geography Type Total 

Population

Poverty Population

(Shaded Cells are ≥ 25% of 

State Percentage)

Total 

Households

Median 

Household 

Income

Low-Income Households

(Shaded Cells are ≥ 25% 

of State Percentage)

Number Percent Number Percent

Oregon 3,836,628 584,059 15% 1,512,718 $50,036 366,078 24%

Benton County County 85,501 17,418 20% 33,502 $48,635 9,716 29%

Alpine CDP CDP 114 37 32% 45 $19,750 24 53%

Alsea CDP CDP 126 22 17% 52 $33,654 20 39%

Corvallis City City 54,341 14,355 26% 21,391 $37,793 7,765 36%

Monroe City City 635 73 11% 243 $36,328 78 32%

Clackamas County County 377,206 36,265 10% 145,004 $63,951 24,506 17%

Estacada City City 377,206 674 25% 1,071 $39,844 380 36%

Government Camp CDP CDP 131 4 3% 64 $250,000 29 45%

Johnson City City 657 176 27% 295 $33,456 120 41%

Clatsop County County 37,068 5,725 15% 15,757 $44,330 4,286 27%

Astoria City City 9,510 1,896 20% 4,171 $40,603 1,360 33%

Cannon Beach City City 1,373 344 25% 650 $39,559 222 34%

Warrenton City City 4,991 811 16% 2,047 $35,325 643 31%

Westport CDP CDP 483 56 12% 227 $26,435 98 43%

Columbia County County 49,317 6,797 14% 19,060 $55,358 4,289 23%

Clatskanie City City 1,788 391 22% 723 $35,875 257 36%

Deer Island CDP CDP 269 57 21% 140 $48,182 53 38%

Prescott City City 34 5 15% 19 $23,750 12 63%

Coos County County 62,937 10,661 17% 26,567 $37,853 8,581 32%

Bandon City City 3,053 443 15% 1,684 $34,279 635 38%

Barview CDP CDP 1,832 803 44% 752 $20,133 456 61%

Bunker Hill CDP CDP 1,892 396 21% 573 $21,305 319 56%

Coos Bay City City 15,938 2,899 18% 6,659 $38,820 2,224 33%

Lakeside City City 1,444 230 16% 675 $36,779 213 32%

Myrtle Point City City 2,496 635 25% 1,007 $29,702 391 39%

Powers City City 890 192 22% 313 $28,750 146 47%

Curry County County 22,344 3,048 14% 10,320 $38,401 3,488 34%

Gold Beach City City 2,563 370 14% 1,029 $50,958 330 32%

Harbor CDP CDP 2,098 384 18% 1,251 $26,629 589 47%

Langlois CDP CDP 218 76 35% 92 $33,906 28 31%

Nesika Beach CDP CDP 352 40 11% 200 $26,813 71 36%

Port Orford City City 1,198 328 27% 568 $30,667 238 42%

Douglas County County 107,391 18,777 17% 43,678 $40,096 12,667 29%

Gardiner CDP CDP 94 25 27% 45 $85,625 9 20%

Glendale City City 854 243 28% 323 $34,226 111 34%

Glide CDP CDP 1,867 466 25% 698 $49,940 161 23%

Lookingglass CDP CPD 1,227 371 30% 424 $41,802 126 30%
1585 | P a g e

Geography Type Total 

Population

Poverty Population

(Shaded Cells are ≥ 25% of 

State Percentage)

Total 

Households

Median 

Household 

Income

Low-Income Households

(Shaded Cells are ≥ 25% 

of State Percentage)

Number Percent Number Percent

Melrose CDP CDP 743 62 8% 323 $50,938 98 30%

Myrtle Creek City City 3,446 805 23% 1,388 $37,650 557 40%

Reedsport City City 4,165 903 22% 1,864 $28,293 805 43%

Riddle City City 921 209 23% 409 $39,034 140 34%

Roseburg City City 21,542 3,892 18% 9,454 $39,621 3,101 33%

Roseburg North CDP CDP 6,493 1,462 23% 2,700 $30,951 948 35%

Tri-City CDP CDP 3,866 829 21% 1,317 $43,220 302 23%

Winchester Bay CDP CDP 243 19 8% 104 $55,652 46 44%

Winston City City 5,352 1,584 30% 1,809 $31,627 662 37%

Yoncalla City City 1,145 310 27% 486 $32,813 189 39%

Jackson County County 203,613 33,346 16% 83,370 $43,664 23,093 28%

Butte Falls Town Town 516 129 25% 179 $39,267 50 28%

Foots Creek CDP CDP 861 105 12% 392 $37,917 153 39%

Gold Hill City City 1,087 208 19% 470 $37,375 146 31%

Phoenix City City 4,550 765 17% 2,126 $31,267 746 35%

Shady Cove City City 2,893 502 17% 1,348 $35,695 506 38%

Talent City City 6,086 1,156 19% 2,797 $32,961 1,108 40%

Trail CDP CDP 203 26 13% 124 $28,125 44 36%

White City CDP CDP 7,392 1,584 21% 2,338 $42,163 592 25%

Wimer CDP CDP 708 149 21% 313 $18,375 173 55%

Josephine County County 82,636 16,301 20% 34,373 $36,699 11,446 33%

Cave Function City City 1,817 613 34% 740 $22,016 433 59%

Fruitdale CDP CDP 900 229 25% 348 $39,231 120 35%

Grants Pass City City 34,454 6,962 20% 14,545 $32,991 5,353 37%

Kerby CDP CDP 397 219 55% 189 $18,250 145 77% O’Brien CDP CDP 143 38 27% 106 $25,987 38 36%

Selma CDP CDP 579 300 52% 214 $23,438 117 55%

Takilma CDP CDP 175 11 6% 99 $13,264 74 75%

Williams CDP CDP 1,195 372 31% 492 $37,264 143 29%

Klamath County County 66,350 12,143 18% 27,747 $41,066 8,740 32%

Bonanza Town Town 418 90 22% 149 $35,179 51 34%

Chiloquin City City 766 259 34% 281 $34,141 90 32%

Klamath Falls City City 20,943 5,131 24% 9,054 $31,971 3,685 41%

Malin City City 712 205 29% 207 $33,594 86 42%

Merrill City City 805 116 14% 294 $37,500 99 34%

Lane County County 351,794 64,705 18% 145,474 $42,628 42,478 29%

Cottage Grove City City 9,671 1,833 19% 3,876 $35,158 1,430 37%

Eugene City City 156,222 34,671 22% 65,907 $41,525 20,958 32%

Florence City City 8,412 995 12% 4,438 $35,000 1,611 36%
1586 | P a g e

Geography Type Total 

Population

Poverty Population

(Shaded Cells are ≥ 25% of 

State Percentage)

Total 

Households

Median 

Household 

Income

Low-Income Households

(Shaded Cells are ≥ 25% 

of State Percentage)

Number Percent Number Percent

Junction City City 5,445 1,239 23% 2,049 $35,067 770 38%

Oakridge City City 3,211 667 21% 1,514 $41,284 527 35%

Springfield City City 59,347 12,143 20% 23,972 $38,315 7,455 31%

Lincoln County County 45,992 7,262 16% 21,039 $41,996 6,480 31%

Lincoln City City 7,926 1,616 20% 3,932 $29,686 1,687 43%

Newport City City 9,989 1,815 18% 4,455 $47,270 1,417 32%

Siletz City City 1,400 310 22% 495 $37,188 159 32%

Waldport City City 1,818 263 14% 924 $35,889 398 43%

Linn County County 116,871 19,237 16% 44,566 $47,129 11,364 26%

Cascadia CDP CDP 20 15 75% 17 $6,417 15 88%

Crabtree CDP CDP 308 33 11% 151 $72,526 50 33%

Halsey City City 1,015 206 20% 295 $50,804 47 16%

Lacomb CDP CDP 345 40 12% 129 $51,193 43 33%

Mill City (1) City 1,625 393 24% 569 $40,313 177 31%

Shedd CDP CDP 607 236 39% 183 $61,599 17 9%

Sweet Home City City 8,938 1,930 22% 3,645 $36,205 1,185 33%

Waterloo Town Town 320 78 24% 88 $48,750 24 27%

West Scio CDP CDP 163 52 32% 111 $16,845 61 55%

Marion County County 315,391 55,223 18% 113,227 $46,654 27,514 24%

Brooks CDP CDP 665 160 24% 175 $11,161 95 54%

Four Corners CDP CDP 16,472 3,754 23% 5,467 $45,372 1,438 26%

Gates City City 675 161 24% 271 $39,750 91 34%

Gervais City City 2,475 685 28% 629 $45,063 140 22%

Hayesville CDP CDP 18,224 4,671 26% 6,437 $39,587 1,944 30%

Labish Village CDP CDP 195 44 23% 70 $34,015 15 21%

Mehama CDP CDP 238 56 24% 86 $56,406 22 26%

Woodburn City City 23,879 5,362 22% 7,517 $41,818 2,195 29%

Multnomah County County 737,110 123,434 17% 303,654 $51,582 74,699 25%

Wood Village City City 3,870 1,211 31% 1,281 $42,917 369 29%

Polk County County 75,448 10,788 14% 27,973 $52,365 6,658 24%

Falls City City 1,089 251 23% 383 $36,083 148 39%

Independence City City 8,535 2,244 26% 2,848 $40,719 946 33%

Monmouth City City 9,549 2,167 23% 3,358 $29,697 1,461 44%

Tillamook County County 25,254 4,197 17% 10,843 $41,869 3,123 29%

Bayside Gardens CDP CDP 804 182 23% 365 $37,566 110 30%

Beaver CDP CDP 1896 3% 84 $45,750 39 46%

Cape Meares CDP CDP 74 21 28% 45 $85,417 21 47%

Cloverdale CDP CDP 337 124 37% 106 $41,429 11 10%

Garibaldi City City 736 150 20% 353 $38,750 118 33%
1587 | P a g e

Geography Type Total 

Population

Poverty Population

(Shaded Cells are ≥ 25% of 

State Percentage)

Total 

Households

Median 

Household 

Income

Low-Income Households

(Shaded Cells are ≥ 25% 

of State Percentage)

Number Percent Number Percent

Idaville CDP CDP 395 79 20% 153 $23,444 107 70%

Neahkahnie CDP CDP 115 41 36% 79 $9,659 41 52%

Neskowin CDP CDP 91 1 1% 61 $32,566 30 49%

Pacific City CDP CDP 1,078 250 23% 408 $31,348 106 26%

Rockaway Beach City City 1,082 154 14% 555 $36,318 190 34%

Tillamook City City 4,934 1,473 30% 2,100 $31,832 848 40%

Wheeler City City 280 25 9% 139 $30,893 44 32%

Washington County County 531,818 57,466 11% 200,160 $64,375 31,825 16%

King City City 3,138 293 9% 1,967 $36,446 661 34%

Yamhill County County 99,119 13,068 13% 33,920 $53,950 7,089 21%

Amity City City 1,636 302 18% 557 $48,750 174 31%

Fort Hill CDP (1) CDP 110 17 15% 97 $21,514 84 87%

Grand Ronde CDP (1) CDP 1,451 257 18% 573 $35,240 225 39%

Willamina City (1) City 1,685 319 19% 633 $34,844 201 32%

Tribes

Coos, Lower Umpqua, and Siuslaw 

Reservation and Off-Reservation Trust 

Land, OR

Tribe 24 6 25% 15 $15,938 10 67%

Coquille Reservation and Off-Reservation 

Trust Land, OR (2) Tribe 297 67 23% 102 $28,750 49 48%

Cow Creek Reservation, OR (2) Tribe 21 - 0% 9 $22,250 5 56%

Grand Ronde Community and OffReservation Trust Land, OR Tribe 473 130 27% 185 $24,861 95 51%

Klamath Reservation, OR Tribe 17 9 53% 14 $6,944 12 86%

Warm Springs Reservation and OffReservation Trust Land, OR Tribe 3,960 1,069 27% 1037 $47,526 209 20%

Notes: 

(1) Where a city or Census Designated Place (CDP) spans more than one county, the BLM assigned it to the county with largest share of population. 

(2) Shows 2009 American Community Survey 5-Year data since 2012 data not available. 

Sources: 

U.S. Census Bureau; American Community Survey, 2012 American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, S1901 and S1701; American FactFinder; 

http://factfinder2.census.gov; (July 2014). 

U.S. Census Bureau; American Community Survey, 2011 American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, S1901 and S1701; American FactFinder; 

http://factfinder2.census.gov; (July 2014). 

U.S. Census Bureau; American Community Survey, 2009 American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, S1901 and S1701; American FactFinder; 

http://factfinder2.census.gov; (July 2014). 

U.S. Census Bureau; American Community Survey, Profile of Selected Economic Characteristics: 2000 Census 2000 Summary File 3 (SF 3), Table DP-3; American FactFinder; 

http://factfinder2.census.gov; (Sept 2014). 
1588 | P a g e

References 

Adams, D. M., and R. W. Haynes. 1980. The 1980 softwood timber assessment market model: structure, projections, and policy 

simulations. Forest Science 26(3): a0001–z0001. 

Adams, D. M., and R. W. Haynes. 2007. Resource and market projections for forest policy development: twenty-five years of 

experience with the USRPA Timber Assessment. Vol. 14. Springer Science & Business Media. 589 pp. 

Amoako-Tuffour, J., and R. Martínez-Espiñeira. 2012. Leisure and the net opportunity cost of travel time in recreation demand 

analysis: an application to Gros Morne National Park. Journal of Applied Economics, 15(1), 25–49.

http://dx.doi.org/10.1016/S1514-0326(12)60002-6. 

Bureau of Labor Statistics .2015. American Time Use Survey. http://www.bls.gov/tus/. 

George, P. S., and G. A. King. 1971. Consumer demand for food commodities in the United States with projections for 1980. 

Giannini Foundation Monograph Number 26. http://giannini.ucop.edu/Monographs/26_George_King.pdf. 

Haynes, R. W. 2008. Emergent lessons from a century of experience with Pacific Northwest timber markets. General Technical 

Report PNW-GTR-747. USDA Forest Service, Pacific Northwest Research Station, Portland, OR. 45 pp. 

https://www.researchgate.net/profile/Richard_Haynes7/publication/237416217_Emergent_Lessons_From_a_Century_of_Ex

perience_With_Pacific_Northwest_Timber_Markets/links/561becd808ae044edbb38b12.pdf. 

Hotelling, H. 1947. Letter to National Park Service in An Economic Study of the Monetary Evaluation of Recreation in the 

Nationa1 Parks (U.S. Department of the Interior, National Park Service and Recreational Planning Division, 1949).

Krumenauer, G., and B. Turner. 2014. Employment projections by industry and occupations 2012–2022, Oregon and regional 

summary. Oregon Employment Department, April 2014. 

https://www.qualityinfo.org/documents/10182/92203/Oregon+Employment+Projections+2012-2022?version=1.0 (accessed 

November 21, 2014). 

McConnell, K. E., and I. Strand. 1981. Measuring the cost of time in recreation demand analysis: an application to sport fishing. 

American Journal of Agricultural Economics, 63(1), 153–156. http://www.jstor.org/stable/1239822. 

MIG, Inc. 2013. IMPLAN version 3 software and Oregon state package data set. Huntersville, NC. 

http://implan.com/.OregonForestResourcesInstitute, 2012. 

Oregon Forest Resources Institute (OFRI). 2012. The 2012 Forest Report: An economic assessment of Oregon’s forest and wood 

products manufacturing sector. Portland, OR. Data support provided by Dr. Dan Green of Economic Analysis Systems. 

Moscow, ID. 

Oregon Parks and Recreation Department (OPRD). 2011. Oregon Statewide Outdoor Recreation Resource/Facility Bulletin Final 

Report. A component of the 2013–2017 Oregon Statewide Comprehensive Outdoor Recreation Plan. 

Siikamäki, J. 2011. Contributions of the U.S. State park system to nature recreation. Proceedings of the National Academy of 

Sciences, 108(34), 14031–14036. http://www.pnas.org/content/108/34/14031.full.pdf. 

U.S. Bureau of Labor Statistics. 2013. American time use survey—Multi-year activity lexicon 2003–2013. 11 pp. 

http://www.bls.gov/tus/lexiconnoex0313.pdf. 

U.S. Census Bureau. 2000. Census2000, Summary File 1, Table DP05; generated by Joan Huston; using American FactFinder; 

http://factfinder2.census.gov; (May 2014). 

---. 2000. American Community Survey, Profile of Selected Economic Characteristics: 2000 Census 2000 Summary File 3 (SF3), 

Table DP-3; American FactFinder. http://factfinder2.census.gov; (Sept 2014). 

---. 2009. American Community Survey, 2009 American Community Survey 5-YearEstimates,Tables DP03,DP04, 

DP05,S1901and S1701; generated by Joan Huston; using American FactFinder. http://factfinder2.census.gov; (May2014). 

---. 2009. American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, S1901 and S1701; American FactFinder; 

http://factfinder2.census.gov; (July 2014). 

---. 2010. 2010 Census: State Population Profile Maps. http://www.census.gov/2010census/. 

---. 2010. American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, S1901 and S1701; American FactFinder; 

http://factfinder2.census.gov; (July 2014). 

---. 2010. American Community Survey, 2010 Census Restricting Data, Table DP05; American FactFinder. 

http://factfinder2.census.gov; (July 2014). 

---. 2011. American Community Survey, 2011 American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, 

S1901and S1701;American FactFinder. http://factfinder2.census.gov; (July 2014). 

---. 2012. American Community Survey, 2012 American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, 

S1901 and S1701; generated by Joan Huston; using American FactFinder. http://factfinder2.census.gov; (May2014). 

---. 2012. American Community Survey, 2012 American Community Survey 5-Year Estimates, Tables DP03, DP04, DP05, 

S1901 and S1701; American FactFinder. http://factfinder2.census.gov; (July 2014). 

---. 2013. On The Map Application. Longitudinal-Employer Household Dynamics Program. http://onthemap.ces.census.gov/;

generated by Clive Graham July 3, 2014. 

U.S. Geological Service. 2015. Protected Areas Data Portal. http://gapanalysis.usgs.gov/padus/. 

Zhou, X. 2013. Production, prices, employment, and trade in Northwest forest industries, all quarters 2012. Resource Bulletin 

PNW-RB-265. USDA FS, Pacific Northwest Research Station. Portland, OR. 163 pp. 

http://www.fs.fed.us/pnw/pubs/pnw_rb265.pdf.
1589 | P a g e

Appendix Q – Public Motorized Access 

Designation Guidelines 

This section provides guidelines for public motorized access designations that the BLM would implement 

following adoption of the RMP until the BLM completes implementation-level travel management 

planning. The BLM has developed these interim guidelines at the district level, for designations that 

contain travel management opportunities (i.e., Class I, II, III, and IV motorized, mechanized, pedestrian, 

and equestrian travel). 

Consistent with current BLM policy (USDI BLM 2011), the BLM is deferring implementation-level 

travel management planning during this RMP revision process. This appendix outlines the decisionmaking process that would be used to develop the initial transportation network, would provide the basis 

for future management decisions, and would set guidelines for making transportation network 

adjustments through the life of the RMP. 

The BLM has developed these management guidelines consistent with BLM Manual H-8342 – Travel and 

Transportation Handbook (USDI BLM 2012). This handbook provides specific guidance for preparing, 

amending, revising, maintaining, implementing, monitoring, and evaluating BLM land use and travel 

management plans. 

Designation for Public Motorized Access 

All Federal lands are required to have designations for public motorized access (as defined in 43 CFR 

8340.0–5 (a)). These designations must be determined in resource management plans and classified as 

open, limited, or closed to public motorized travel activities. The BLM bases these designations on 

protecting natural and cultural resources and public safety, limiting visitor conflicts, and providing 

diverse recreational opportunities. Criteria for open, limited, and closed are designations are established in 

43 CFR 8340.0–5 (f, g, h). The designations for public motorized access are defined as: 

 Open– Areas where the BLM does not limit public motorized travel activities since there are no 

issues regarding resources, visitor conflicts, or public safety to warrant limiting cross-country 

travel 

 Limited– Areas where the BLM has restricted public motorized travel activities in order to meet 

recreational and resource management objectives42

 Closed– Areas that the BLM has closed to all public motorized vehicle activities to protect 

resources, ensure visitor safety, or reduce visitor conflicts 

Table Q-1 displays the current public motorized access designations within the decision area.

 

42 Restrictions may include the number or types of vehicles, the time or season of use, permitted or licensed use 

only, or limiting use to existing or designated roads and trails. 
1590 | P a g e

Table Q-1. Current public motorized access designations within the decision area 

Travel Management 

Area Designation 

(1995 RMP)

Coos Bay

(Acres)

Eugene

(Acres)

Klamath 

Falls

(Acres)

Medford

(Acres)

Roseburg

(Acres)

Salem

(Acres)

Totals

(Acres)

Open 562 59 29,495 133,043 43 156,460 319,661

Limited 321,185 308,169 179,413 644,283 419,357 216,539 2,088,946

Closed 3,486 3,461 3,874 32,466 3,277 16,975 63,539

Totals 325,233 311,689 212,781 809,792 422,677 392,159 2,472,147

Table Q-2 displays the acres of public motorized access designations by alternative and the Proposed 

RMP. 

Table Q-2. Public motorized access designations in the decision area 

Trails and Travel 

Management

No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

Open 319,661 - - - - -

Limited 2,088,946 2,345,575 2,325,663 2,296,313 2,320,987 2,322,820

Closed 63,539 128,757 148,551 178,001 153,305 156,036

The designations for public motorized access do not apply to non-motorized uses (e.g., hiking, biking, 

equestrian), though areas can be designated for non-motorized transportation systems in the land use 

planning process.43 In the designations for public motorized access, the BLM would consider the needs 

for a variety of road and trail systems tailored to a variety of users including non-motorized recreational 

uses. These designations would be refined through implementation-level travel management planning. 

Management of Areas Designated for Public Motorized 

Access 

The BLM will make final route designations within the decision area in comprehensive, interdisciplinary 

Travel and Transportation Management Plans, which are scheduled to be completed within five years 

after the completion of the western Oregon RMPs. Until implementation-level Travel Management 

Planning is complete, routes and trails would be managed in accordance with their designation of closed

or limited to existing routes for public motorized travel activities, as described for each district. 

 

43 To restrict non-motorized travel to specific routes, the BLM must develop supplemental rules through a Federal 

Register process, consistent with 43 CFR 8365.1–6 Supplementary Rules. 
1591 | P a g e

Coos Bay District Public Motorized Access Designations 

Table Q-3. Coos Bay District public motorized access designations 

Designation No Action

(Acres)

Alt. A

(Acres)

Alt. B

(Acres)

Alt. C

(Acres)

Alt. D

(Acres)

PRMP

(Acres)

Open 562 - - - - -

Limited to 

Existing Routes 321,185 318,500 319,565 319,565 318,469 316,423

Limited to 

Designated Routes - - 1,401 1,401 1,401 4,072

Closed 3,486 5,191 2,724 2,724 3,821 3,741

Description: Includes all BLM-administered lands within the Coos Bay District. See additional 

guidelines for the Blue Ridge OHV Travel Management Area.

Limited Area Management Guidelines: 

 The BLM will manage limited areas in accordance with all applicable Federal and State 

motorized vehicle regulations.

 The BLM will limit motorized vehicle use to administrative, commercial, and passenger vehicle 

traffic where not specifically signed or gated.

 Until road and trail designations are complete, all public motorized travel activities would be 

limited in the interim to the existing road and trail network unless closed or restricted under a 

previous planning effort or due to special circumstances as defined below: 

o The BLM may close or limit routes under seasonal or administrative restrictions. These 

restrictions may include, but are not limited to, fire danger, wet conditions, special 

requirements for wildlife species, protection of cultural resources, or for public safety. 

 Vehicles may pull off roads or trails to park or allow others to pass, up to 25 feet from the 

centerline of the road or up to 15 feet from the centerline of a trail. 

 Limitations apply to all Class I (all-terrain vehicles), Class II (four-wheel drive vehicles), and 

Class III (motorcycles) public motorized vehicles and to all activity types (e.g., recreational and 

commercial) unless authorized by the BLM for administrative purposes. 

Closed Area Management Guidelines: All motorized vehicles are prohibited from entering closed areas 

unless authorized by the BLM for administrative purposes

Process for ongoing public collaboration and outreach: 

 The principal venue for public collaboration is through public outreach and scoping during future 

implementation-level travel management planning efforts, special projects, and local partnership. 

 The BLM would send press releases as needed informing the public of motorized travel 

opportunities and restrictions. The BLM would post signs where appropriate. 

 Upon completion of the implementation-level transportation management plan, maps and 

brochures will be available to the public at the Coos Bay District office illustrating designations, 

describing specific restrictions, and defining opportunities. 

Process for selecting a final road and trail network: The BLM has completed route designations for 

the New River ACEC and the Blue Ridge OHV Travel Management Area. The BLM would accomplish 

final route designations for the rest of the district though comprehensive and interdisciplinary 
1592 | P a g e

implementation-level travel and transportation management planning scheduled to be completed no later 

than 5 years after completion of the RMP revision.

The BLM’s geo-database would provide information for identifying roads and trails for both motorized 

and non-motorized activities. The BLM would continue to conduct on-the-ground inventories if roads and 

trails cannot be identified using remote-sensing techniques. The BLM would evaluate proposed 

designations through public scoping and a NEPA analysis. The BLM would consider changes to the 

designated system during the implementation-level travel management planning process. 

Road and trail construction and maintenance standards: The BLM will construct and maintain roads 

and trails in accordance with the standards in BLM Manual H-9114-1 – Trails (USDI BLM 1987) and 

other professional sources. 

Blue Ridge OHV Travel Management Area 

The BLM completed route designations within the Blue Ridge OHV Travel Management Area through 

the Blue Ridge Multiple Use Trail System environmental assessment (EA OR-125-98-18). The BLM 

would continue to manage the Blue Ridge OHV Travel Management Area in the Coos Bay District as a 

Recreation Management Area with an off-highway vehicle focus. The following management guidelines 

apply to the Blue Ridge OHV Travel Management Area on the Coos Bay District: 

Acres: 1,609

OHV Designation: Limited to designated roads and trails

Niche: Offers a multiple-use, single-track trail riding experience for hikers, equestrians, mountain bikers, 

and motorcycle riders.

Management Guidelines: 

 The single-track trail system is available to Class III (motorcycles) vehicles with Oregon allterrain vehicle permits and all non-motorized modes of travel. 

 Motorized, mechanized, and equestrian use is prohibited between December and April to prevent 

excessive damage to the trail tread when soil moisture conditions are high. Motorized use on the 

trail system may be restricted during summer months due to fire hazard conditions. 

Process for ongoing public collaboration/outreach: The principal venue for public collaboration on the 

trail system is through local partnership relationships. A printed trail map is available to the public at the 

Coos Bay District office and on the Coos Regional Trail Partnership webpage. The trail system is marked 

on the ground with regulatory and directional signage.

Process for selecting a final road and trail network: The BLM completed route designations through 

the Blue Ridge Multiple Use Trail System environmental assessment (EA OR-125-98-18). The BLM 

would use adaptive management to adjust the system for commercial timber production demands, user 

needs and resource protection. The BLM would accomplish these modifications in collaboration with trail 

partners and users and through changes to the Blue Ridge Trail system plan and an environmental 

assessment. 

Road and trail construction and maintenance standards: The BLM would construct and maintain 

roads and trails in accordance with the design features identified in the environmental assessment, 

standards in BLM Manual H-9114-1 – Trails (USDI BLM 1987), and other professional sources. Trail 
1593 | P a g e

maintenance would be a priority within this Travel Management Area to ensure a quality riding 

experience for trail users and to conserve natural resource values.
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Eugene District Public Motorized Access Designations 

Table Q-4. Eugene District public motorized access designations by alternative and the Proposed RMP 

Designation No Action

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

Open 59 - - - - -

Limited to 

Existing Routes 308,169 289,796 283,963 281,750 279,757 307,503

Limited to 

Designated Routes - - 5,728 5,727 5,727 -

Closed 3,461 20,601 20,707 22,921 24,915 3,561

Description: Includes all BLM-administered lands within the Eugene District. See additional guidelines 

for the Shotgun Creek OHV Travel Management Area.

Limited Area Management Guidelines: 

 The BLM will manage limited areas in accordance with all applicable Federal and State motorized 

vehicle regulations.

 The BLM will limit motorized vehicle use to administrative, commercial, and passenger vehicle 

traffic where not specifically signed or gated.

 Until road and trail designations are complete, all public motorized travel activities would be 

limited to the existing road and trail network unless closed or restricted under a previous planning 

effort or due to special circumstances as defined below: 

o The BLM may close or limit routes under seasonal or administrative restrictions. These 

restrictions may include, but are not limited to, fire danger, wet conditions, special 

requirements for wildlife species, protection of cultural resources, or for public safety. 

 Vehicles may pull off roads or trails to park or allow others to pass, up to 25 feet from the 

centerline of the road or up to 15 feet from the centerline of a trail. 

 Limitations apply to all Class I (all-terrain vehicles), Class II (four-wheel drive vehicles), and Class 

III (motorcycles) public motorized vehicles and to all activity types (e.g., recreational and 

commercial) unless authorized by the BLM for administrative purposes. 

Closed Area Management Guidelines: All motorized vehicles are prohibited from entering closed areas 

unless authorized by the BLM for administrative purposes

Process for ongoing public collaboration/outreach: 

 The principal venue for public collaboration is through public outreach and scoping during future 

implementation level travel management planning efforts, special projects, and local partnership. 

 The BLM would send press releases as needed informing the public of motorized travel 

opportunities and restrictions. The BLM would post signs where appropriate. 

 Upon completion of the implementation-level transportation management plan, maps and 

brochures shall be available to the public at the main office illustrating designations, describing 

specific restrictions, and defining opportunities. 

Process for selecting a final road and trail network: The BLM has completed route designations for 

the Upper Lake Creek Special Recreation Management Area and the Shotgun Creek OHV Travel 

Management Area. The BLM would accomplish final route designations for the rest of the district 

through comprehensive, interdisciplinary implementation-level travel and transportation planning, which 

is scheduled to be completed no later than 5 years after completion of the RMP revision.
1595 | P a g e

BLM’s geo-database would provide information for identifying roads and trails for both motorized and 

non-motorized activities. The BLM would continue to conduct on-the-ground inventories if roads and 

trails cannot be identified using remote-sensing techniques. The BLM would evaluate proposed 

designations through public scoping and a NEPA analysis. The BLM would consider changes to the 

designated system during the transportation management planning process. 

Road and trail construction and maintenance standards: The BLM will construct and maintain roads 

and trails in accordance with the standards in BLM Manual H-9114-1 – Trails (USDI BLM 1987) and 

other professional sources.

Shotgun Creek OHV Travel Management Area 

Acres: 5,755

OHV Designation: Limited to existing roads and trails

Niche: Offers a multiple-use trail riding experience for motorcycle riders, all-terrain vehicle riders, and 

four-wheel drive enthusiasts.

Management Guidelines: 

 The trail system is available to Class I (all-terrain vehicles), Class II (four-wheel drive vehicles), 

and Class III (motorcycles) motorized vehicles with Oregon all-terrain vehicle permits. 

 The BLM will sign and map routes open to OHV use. 

 Routes available for OHV use may change periodically due to timber harvest activity or trail 

rehabilitation. 

Process for ongoing public collaboration/outreach: The principal venue for public collaboration on the 

trail system is through local partnership relationships. A trail map is available to the public at the Eugene 

District Office and is updated as trail routes change. The trail system is marked on the ground with 

regulatory and directional signs. 

Process for selecting a final road and trail network: The BLM completed route designations through 

two Shotgun OHV Trail System environmental assessments (EA OR 090-00-04 and EA OR 090-06-04). 

The BLM would consider changes to the transportation system during the route designation planning 

process. The BLM will accomplish these modifications in collaboration with trail partners and users. 

Road and trail construction and maintenance standards: Trail maintenance will be a priority within 

this OHV area to ensure quality riding experiences for trail users and to conserve natural resource values. 
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Klamath Falls Field Office Public Motorized Access Designations 

Table Q-5. Klamath Falls Field Office public motorized access designations by alternative and the 

Proposed RMP 

Designation No Action Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

Open 29,495 - - - - -

Limited to 

Existing Routes 132,191 213,266 209,559 200,501 202,759 200,312

Limited to 

Designated Routes 47,222 - - - - 2

Closed 3,874 494 4,201 13,260 11,001 13,771

Description: Includes all BLM-administered lands within the Klamath Falls Field Office. 

Limited Area Management Guidelines: 

 The BLM will manage limited areas in accordance with all applicable Federal and State 

motorized vehicle regulations.

 The BLM would limit motor vehicle use to administrative, commercial, and passenger vehicle 

traffic where not specifically signed or gated. 

 Until road and trail designations are complete, all public motorized travel activities will be 

limited in the interim to the existing road and trail network unless closed or restricted under a 

previous planning effort or due to special circumstances as defined below: 

o The BLM may close or limit routes under seasonal or administrative restrictions. These 

restrictions may include, but are not limited to, fire danger, wet conditions, special 

requirements for wildlife species, protection of cultural resources, or for public safety. 

 Vehicles may pull off roads or trails to park or allow others to pass, up to 25 feet from the 

centerline of the road or up to 15 feet from the centerline of a trail. 

 Limitations apply to all Class I (all-terrain vehicles), Class II (four-wheel drive vehicles), and 

Class III (motorcycles) public motorized vehicles and to all activity types (e.g., recreational and 

commercial) unless authorized by the BLM for administrative purposes. 

Seasonal restrictions: 

 The Eastside seasonal OHV closure is in effect from November 1 to April 15 and applies to all 

BLM-administered lands within deer winter range cooperative wildlife areas, including the 

majority of Stukel and Bryant Mountain and portions of the Gerber Block as mapped. 

 The Pokegama wildlife area seasonal OHV closure is in effect from November 20 to April 1. 

 For designated snowmobile trails, wheeled vehicles are prohibited once grooming of trails begins 

for winter season. 

 he OHV use may be limited in other areas on a seasonal basis due to special conditions such as 

temporary fire restrictions, special wildlife requirements, etc. 

Closed Area Management Guidelines: All motorized vehicles are prohibited from entering closed areas 

unless authorized by the BLM for administrative purposes

Process for ongoing public collaboration/outreach: 

 The principal venue for public collaboration is through public outreach and scoping during future 

implementation-level travel management planning efforts, special projects, and local partnerships. 
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 The BLM would send press releases as needed informing the public of OHV opportunities and 

restrictions. The BLM would post signs where appropriate. 

 Upon completion of the transportation management plan, maps and brochures shall be available 

to the public at the main office illustrating designations, describing specific restrictions, and 

defining opportunities. 

 The BLM would continue to participate with other land managers in the cooperative management 

of the Pokegama wildlife area and deer winter range areas. 

Process for selecting a final road and trail network: The BLM will accomplish final route designations 

for the rest of the district in a comprehensive, interdisciplinary travel and transportation management 

plan, which is scheduled to be completed no later than 5 years after completion of the RMP revision.

The BLM’s geo-database would provide information for identifying roads and trails for both motorized 

and non-motorized activities. The BLM would continue to conduct on-the-ground inventories if roads and 

trails cannot be identified using remote-sensing techniques. The BLM will evaluate proposed designations 

through public scoping and a NEPA analysis. The BLM will consider changes to the designated system 

during the transportation management planning process. 

Road and trail construction and maintenance standards: The BLM would construct and maintain 

roads and trails in accordance with the standards in BLM Manual H-9114-1 – Trails (USDI BLM 1987) 

and other professional sources. 
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Medford District Public Motorized Access Designations 

Table Q-6. Medford District public motorized access designations by alternative and the Proposed RMP 

Designation No Action

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

Open 133,043 - - - - -

Limited to 

Existing Routes 26,514 715,439 730,596 734,121 769,047 695,115

Limited to 

Designated Routes 617,769 - - - - -

Closed 32,466 89,889 74,719 71,195 36,246 111,517

Description: Includes all BLM-administered lands within the Medford District.

Limited to Existing Area Management Guidelines: 

 The BLM will manage limited areas in accordance with all applicable Federal and State 

motorized vehicle regulations.

 Paved roads are limited to licensed, street-legal vehicles only. 

 Road Maintenance Level 1 and 2 routes44 are open to Class I (all-terrain vehicles), Class II (fourwheel drive vehicles), and Class III (motorcycles) vehicles. Trails less than 50 inches in width are 

restricted to all-terrain vehicles and motorcycles. 

 Roads on private property that do not have a secured public right-of-way are not necessarily open 

to public or recreational vehicle traffic, even if they are a “continuation” of the BLM road system 

or a road shown on the preliminary maps. 

 Until road and trail designations are complete, all motorized vehicles will be limited in the 

interim to the existing road and trail network unless closed or restricted under a previous planning 

effort or due to special circumstances: 

o The BLM may close or limit routes under seasonal or administrative restrictions. These 

restrictions may include, but are not limited to, fire danger, wet conditions, special 

requirements for wildlife species, to protect cultural resources, or for public safety. 

 In the Butte Falls Resource Area, the Jackson Access and Cooperative Travel Management Area 

closure (32,822 acres) is in effect from mid-October through April 30. Only those roads shown in 

green on Oregon Department of Fish and Wildlife maps or posted with green reflectors are open 

to motorized vehicles during the period of the restriction. 

 Vehicles may pull off roads or trails to park or allow others to pass, up to 25 feet from the 

centerline of the road or up to 15 feet from the centerline of a trail. 

 Limitations apply to all Class I (all-terrain vehicles), Class II (four-wheel drive vehicles), and 

Class III (motorcycles) public motorized vehicles and to all activity types (e.g., recreational and 

commercial) unless authorized by the BLM for administrative purposes. 

 Non-motorized travel (e.g., horseback riding, hiking, and mountain biking) is allowed on all 

access routes. 

 

44 Level 1 – This level is assigned to roads where minimum maintenance is required to protect adjacent lands and resource 

values. Emphasis is given to maintaining drainage and runoff patterns as needed to protect adjacent lands. Grading, brushing, or 

slide removal is not performed unless roadbed drainage is being adversely affected, causing erosion. Closure and traffic 

restrictive devices are maintained as needed. 

Level 2 – This level is assigned to roads that are passable by high clearance vehicles. Drainage structures are to be inspected 

within a 3-year period and maintained as needed. Grading is conducted as necessary to correct drainage problems. Brushing is 

conducted as needed to allow access. These are typically low standard, low volume; single lane, natural and aggregate surfaced, 

and are functionally classified as a resource road.
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Closed Area Management Guidelines: All motorized vehicles are prohibited from entering closed areas 

unless authorized by the BLM for administrative purposes 

Process for ongoing public collaboration/outreach: 

 The principal venue for public collaboration is through public outreach and scoping during future 

implementation-level travel management planning efforts, special projects, and local partnership. 

 The BLM would send press releases as needed informing the public of motorized travel 

opportunities and restrictions. The BLM would post signs where appropriate. 

 Upon completion of the transportation management plan, maps and brochures shall be available 

to the public at the main office illustrating designations, describing specific restrictions, and 

defining opportunities. 

Process for selecting a final road and trail network: The BLM would accomplish final route 

designations for the rest of the district through comprehensive and interdisciplinary implementation-level 

travel and transportation management planning scheduled to be completed no later than 5 years after 

completion of the RMP revision.

The BLM’s geo-database would provide information for identifying roads and trails for both motorized 

and non-motorized activities. The BLM has been and would continue to conduct on-the-ground 

inventories if roads and trails cannot be identified using remote-sensing techniques. The BLM would 

evaluate proposed designations through public scoping and a NEPA analysis. The BLM would consider 

changes to the designated system during the transportation management planning process. 

Road and trail construction and maintenance standards: The BLM would construct and maintain 

roads and trails in accordance with the standards in BLM Manual H-9114-1 – Trails (USDI BLM 1987) 

and other professional sources. 
1600 | P a g e

Roseburg District Public Motorized Access Designations 

Table Q-7. Roseburg District public motorized access designations by alternative and the Proposed RMP 

Designation No Action

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

Open 43 - - - - -

Limited to 

Existing Routes 412,626 418,978 412,196 400,259 398,863 413,420

Limited to 

Designated Routes 6,731 - - - - -

Closed 3,277 3,808 10,591 22,528 23,924 10,220

Description: Includes all BLM-administered lands within the Roseburg District.

Limited Area Management Guidelines: 

 The BLM will manage limited areas in accordance with all applicable Federal and State 

motorized vehicle regulations.

 The BLM will limit motorized vehicle use to administrative, commercial, and passenger vehicle 

traffic where not specifically signed or gated. 

 Until road and trail designations are complete, all public motorized travel activities will be 

limited in the interim to the existing road and trail network unless closed or restricted under a 

previous planning effort or due to special circumstances as defined below. 

o The BLM may close or limit routes under seasonal or administrative restrictions. These 

restrictions may include, but are not limited to, fire danger, wet conditions, special 

requirements for wildlife species, protection of cultural resources, or for public safety. 

 Vehicles may pull off roads or trails to park or allow others to pass, up to 25 feet from the 

centerline of the road or up to 15 feet from the centerline of a trail. 

 Limitations apply to all Class I (all-terrain vehicles), Class II (four-wheel drive vehicles), and 

Class III (motorcycles) public motorized vehicles and to all activity types (e.g., recreational and 

commercial) unless authorized by the BLM for administrative purposes. 

Closed Area Management Guidelines: All motorized vehicles are prohibited from entering closed areas 

unless authorized by the BLM for administrative purposes

Process for ongoing public collaboration/outreach:

 The principal venue for public collaboration is through public outreach and scoping during future 

implementation-level travel management planning efforts, special projects, and local partnership. 

 The BLM would send press releases as needed informing the public of motorized travel 

opportunities and restrictions. The BLM would post signs where appropriate. 

 Upon completion of the implementation-level transportation management plan, maps and 

brochures shall be available to the public at the Roseburg District office illustrating designations, 

describing specific restrictions, and defining opportunities. 

Process for selecting a final road and trail network: The BLM would accomplish final route 

designations for the rest of the district through a comprehensive and interdisciplinary implementationlevel travel and transportation management plan, which is scheduled to be completed no later than 5 years 

after completion of the RMP revision.
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The BLM’s geo-database would provide information for identifying roads and trails for both motorized 

and non-motorized activities. The BLM would continue to conduct on-the-ground inventories if roads and 

trails cannot be identified using remote-sensing techniques. The BLM will evaluate proposed designations 

through public scoping and a NEPA analysis. The BLM would consider changes to the designated system 

during the implementation-level transportation planning. 

Road and trail construction and maintenance standards: The BLM would construct and maintain 

roads and trails in accordance with the standards in BLM Manual H-9114-1 – Trails (USDI BLM 1987) 

and other professional sources. 
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Salem District Public Motorized Access Designations 

Table Q-8. Salem District public motorized access designations by alternative and the Proposed RMP 

Designation No Action

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

Open 156,460 - - - - -

Limited to 

Existing Routes 48,771 389,595 361,780 346,806 340,067 378,497

Limited to 

Designated Routes 167,768 - 6,684 6,185 10,626 7,434

Closed 16,975 8,774 29,881 45,374 47,672 13,226

Description: Includes all BLM-administered lands within the Salem District. See additional guidelines 

for the Upper Nestucca OHV Area.

Limited to Existing Area Management Guidelines: 

 The BLM will manage limited areas in accordance with all applicable Federal and State motorized 

vehicle regulations.

 The BLM would limit motorized vehicle use to administrative, commercial, and passenger vehicle 

traffic where not specifically signed or gated. 

 Until road and trail designations are complete, all public motorized travel activities would be limited 

in the interim to the existing road and trail network unless closed or restricted under a previous 

planning effort or due to special circumstances: 

o The BLM may close or limit routes under seasonal or administrative restrictions. These 

restrictions may include, but are not limited to, fire danger, wet conditions, special 

requirements for wildlife species, protection of cultural resources, or for public safety. 

 Vehicles may pull off roads or trails to park or allow others to pass, up to 25 feet from the centerline 

of the road or up to 15 feet from the centerline of a trail. 

 Limitations apply to all Class I (all-terrain vehicles), Class II (four-wheel drive vehicles), and Class 

III (motorcycles) public motorized vehicles and to all activity types (e.g., recreational and 

commercial) unless authorized by the BLM for administrative purposes. 

Closed Area Management Guidelines: All motorized vehicles are prohibited from entering closed areas 

unless authorized by the BLM for administrative purposes

Process for ongoing public collaboration/outreach: 

 The principal venue for public collaboration is through public outreach and scoping during future 

implementation-level travel management planning efforts, special projects, and local partnership.

 The BLM would send press releases as needed informing the public of motorized travel 

opportunities and restrictions. The BLM would post signs where appropriate.

 Upon completion of the implementation-level management plan, maps and brochures shall be 

available to the public at the main office illustrating designations, and describing specific 

restrictions.

Process for selecting a final road and trail network: Route designations have been completed for the 

Upper Nestucca Travel Management Area. The BLM would accomplish final route designations for the 

rest of the district through a comprehensive and interdisciplinary implementation-level travel and 
1603 | P a g e

transportation management plan scheduled to be completed no later than 5 years after completion of the 

RMP revision.

The BLM’s geo-database would provide information for identifying roads and trails for both motorized 

and non-motorized activities. The BLM has been and would continue to conduct on-the-ground 

inventories if roads and trails cannot be identified using remote-sensing techniques. The BLM would 

evaluate proposed designations through public scoping and a NEPA analysis. The BLM would consider 

changes to the existing system during implementation-level travel planning. 

Road and trail construction and maintenance standards: The BLM would construct and maintain 

roads and trails in accordance with the standards in BLM Manual H-9114-1 – Trails (USDI BLM 1987) 

and other professional sources. 

Upper Nestucca OHV Travel Management Area 

Acres: 9,579 

Designation: Limited to existing roads and trails 

Niche: Located 20 miles northwest of McMinnville, Oregon, this area provides Class I (all-terrain 

vehicles), and Class III (motorcycles) OHV riding experience along a designated road and trail network. 

Management Guidelines:

 Designated trails and maintained roadways are limited to Class I and Class III motor vehicle use 

within the boundaries of the OHV area. 

 All Class I and Class III vehicles must be equipped with approved spark arresters, an Oregon allterrain vehicles sticker for the appropriate vehicle class, and must meet posted noise requirements. 

 Class II vehicle use is only authorized on Road Maintenance Level 3 and Level 4 roadways45.

 The BLM may restrict motorized use on the trail system during summer months due to fire hazard 

conditions. 

 The BLM may be permanently or temporarily close areas or trails for administrative use, extreme 

wet conditions, construction and reconstruction requirements, or other environmental concerns. 

Process for ongoing public collaboration/outreach: The principal venue for public collaboration on the 

trail system is through local partnership with the Applegate Rough Riders Motorcycle Club. Trail maps 

are available to the public at the Salem District Office and Tillamook Field Office. The trail system is 

marked on the ground with regulatory and directional signage.

Process for selecting a final road and trail network: The BLM has completed route designations 

 

45 Level 3 – This level is assigned to roads where management objectives require the road to be open seasonally or year-round 

for commercial, recreational, or administrative access. Typically, these roads are natural or aggregate surfaced, but may include 

low use bituminous surfaced road. These roads have a defined cross section with drainage structures (e.g., rolling dips, culverts, 

or ditches). These roads may be negotiated by passenger cars traveling at prudent speeds. User comfort and convenience are not 

considered a high priority. Drainage structures are to be inspected at least annually and maintained as needed. Grading is 

conducted to provide a reasonable level of riding comfort at prudent speeds for the road conditions. Brushing is conducted as 

needed to improve sight distance. 

Level 4 – This level is assigned to roads where management objectives require the road to be open all year (except may be closed 

or have limited access due to snow conditions) and which connect major administrative features (recreational sites, local road 

systems, administrative sites, etc.) to County, State, or Federal roads. Typically, these roads are single or double lane, aggregate, 

or bituminous surface, with a higher volume of commercial and recreational traffic than administrative traffic.
1604 | P a g e

through the Upper Nestucca Motorcycle Trail System Environmental Assessment (EA OR 086-97-05). 

The BLM will use adaptive management to adjust the system for timber management, user needs, and 

resource protection.

Road and trail construction and maintenance standards: The BLM will construct and maintain roads 

and trails in accordance with the design features identified in the Monitoring and Maintenance Plan for 

the Upper Nestucca OHV Trail System. Trail maintenance will be a priority within this OHV area to 

ensure a quality riding experience for trail users and to conserve natural resource values.

Implementation-Level Travel Management Planning 

Implementation-level TMP is the process of establishing a final travel and transportation network that 

includes route-specific designations within the broader land use planning level designations for public 

motorized access. In accordance with current BLM policy, the delineation of the BLM’s final travel and 

transportation network is being deferred. The BLM would complete this process in the planning area 

within 5 years of completion of this RMP revision. 

As part of this process, the BLM may additionally delineate Travel Management Areas to address 

particular concerns and prescribe specific management actions for a defined geographic area. The BLM 

typically identifies Travel Management Areas where travel and transportation management (either 

motorized or non-motorized) requires particular focus or increased intensity of management. While 

designations for public motorized access are a mandatory land use plan allocations, Travel Management 

Areas are an optional planning tool to frame transportation issues and help delineate travel networks that 

address specific uses and resource concerns. Dividing an area into Travel Management Areas can allow 

for higher priority areas to go through the implementation-level travel management process first, 

deferring areas with lower resource or user conflict concerns for later travel planning efforts. Travel 

Management Areas also provide the opportunity to establish a link between Recreation and 

Transportation Management Areas. To help ensure that that travel decisions support program-specific 

management objectives, the BLM may identify Travel Management Area boundaries that correspond with 

the Recreation Management Areas defined for various outcomes. 

Travel Management Land Use Planning 

While delineation of Travel Management Areas is optional, designation of all lands public motorized 

access is a required to occur when conducting land use planning. The BLM will base all designations for 

public motorized access on the protection of resources, the promotion of safety for all users, and the 

minimization of conflicts among various users of BLM-administered lands. Additionally, areas and trails 

for all types of travel must support the goals, objectives, and management actions contained in the 

resource management plan, and applicable laws and policies. The BLM has designated all lands within 

the decision area as open, limited, or closed for the management of public motorized vehicle areas and 

trails under the alternatives and the Proposed RMP in accordance with the following criteria (43 CFR 

8342.1): 

a) Areas and trails shall be located to minimize damage to soil, watershed, vegetation, air, or other 

resources of the public lands, and to prevent impairment of wilderness suitability. 

b) Areas and trails shall be located to minimize harassment of wildlife or significant disruption of 

wildlife habitats. Special attention will be given to protect endangered or threatened species and 

their habitats. 

c) Areas and trails shall be located to minimize conflicts between off-road vehicle use and other 

existing or proposed recreational uses of the same or neighboring public lands, and to ensure the 

compatibility of such uses with existing conditions in populated areas, taking into account noise 

and other factors. 
1605 | P a g e

d) Areas and trails shall not be located in officially designated wilderness areas or primitive areas. 

Areas and trails shall be located in natural areas only if the authorized officer determines that offroad vehicle use in such locations will not adversely affect their natural, esthetic, scenic, or other 

values for which such areas are established. 

Travel designations in the action alternatives and the Proposed RMP include limited and closed. Lands 

designated as open areas only occur under the No Action alternative. 

Limited designations restrict travel in specified areas and/or on designated routes, roads, vehicle ways, or 

trails. This designation is used where public travel use must be restricted to meet specific resource 

management objectives. Examples of limitations include number or type of conveyance; time or season of 

use; permitted or licensed use only; use limited to existing roads and trails; use limited to designated 

roads and trail; or other limitations if restrictions are necessary to meet resource management objectives, 

including certain competitive or intensive use areas that have special limitations (see 43 CFR 8340.0–5). 

There are three distinct uses of the limited designation in the RMPs for Western Oregon. The three types 

of limited designations are: 

 Travel limited to existing roads and trails; areas where public travel is restricted to existing roads 

and trails. This designation is an interim designation until route-specific planning can occur. At 

the point at which travel planning occurs, motorized travel in the area would be refined to identify 

appropriate areas, seasons, or types of conveyance for which to limit public travel uses. 

 Travel limited to designated roads and trails; areas where specific types of public travel (e.g., 

motorized, mechanized, pedestrian) are restricted to designated roads and trails. Areas with this 

designation are identified where implementation-level travel management planning has occurred 

prior to this plan revision. 

 Travel limited to designated roads and trails and limited seasonally; in these areas, specific types 

of public travel (e.g., motorized, mechanized, pedestrian) are restricted to seasonal use periods 

and to designated roads and trails. Areas with this designation are identified where 

implementation-level travel management planning has occurred prior to this plan revision. 

Closed designations identify areas where public motorized vehicle travel is prohibited. Access by means 

other than motorized vehicle, such as mechanized or non-motorized use is permitted. Areas are designated 

closed if closure to all public motorized vehicular use is necessary to protect resources, promote visitor 

safety, or reduce use conflicts (see 43 CFR 8340.0–5). 

Future Implementation Planning Guidance 

The designations defined above require an additional level of effort and planning prior to implementation. 

Implementation-level decisions generally constitute the BLM’s final approval allowing on-the-ground 

actions to proceed. These types of decisions require site-specific planning and environmental (e.g., 

NEPA) analysis. The implementation-level travel management planning will be conducted using an 

interdisciplinary team approach to address all resource uses, including administrative, recreation, 

commercial and associated modes of travel (motorized, mechanized and non-motorized types). 

The designation of the individual roads, primitive roads and trails are addressed as an implementationlevel plan tiered from the RMP. Travel and transportation decisions can be developed as a stand-alone 

Travel Management Plan (TMP) or incorporated into activity management plans, such as those for 

recreation or energy. A TMP is the document that describes the decisions related to the selection and 

management of the transportation network. Route-specific decisions in a TMP support the RMP goals, 

objectives, and management actions, and the designation criteria in 43 CFR 8342.1. Individual route 
1606 | P a g e

designations would occur during subsequent implementation-level travel management planning efforts. 

Upon the completion of implementation level travel management plans OHV management areas 

designated as limited to existing roads and trails would transition to limited to designated roads and trails 

as identified through the implementation level travel management analysis. 

In western Oregon, district staff would complete implementation-level travel planning and would 

delineate route-specific decisions to support RMP goals, objectives, and management direction, and the 

designation criteria in 43 CFR 8342.1. In addition, districts would consider the following criteria: 

 The BLM would consider public land roads or trails determined to cause considerable adverse 

effects or to continue a nuisance or threat to public safety for relocation or closure and 

rehabilitation after appropriate coordination with applicable agencies and partners. 

 Routes that are duplicative, parallel, or redundant would be considered for closure. Eliminate 

parallel roads travelling to the same destination when the destination can be accessed from the 

same direction and topography and user experience. 

 All routes would undergo a route evaluation to determine its purpose and need and the potential 

resource and/or user conflicts from motorized travel. Where resource and/or user conflicts 

outweigh the purpose and need for the route, the route would be considered for closure or 

considered for relocation outside of sensitive habitat. 

 Routes that do not have a purpose and need would be considered for closure. 

 Consider limiting over snow vehicles (OSV) designed for use over snow and that run on tracks 

and/or skis, while in use over snow to designated routes or consider seasonal closures on routes in 

sensitive areas. 

 Routes not required for public access or recreation with a current administrative/agency purpose 

or need would be evaluated for administrative access only. 

 Consider prioritizing restoration of routes not designated in a Travel Management Plan. 

 Consider using seed mixes or transplant techniques that would maintain or enhance habitat when 

rehabilitating linear disturbances. 

 Temporary closures would be considered in accordance with 43 CFR 8364 (Closures and 

Restrictions); 43 CFR 8351 (Designated National Areas); 43 CFR 6302 (Use of Wilderness 

Areas, Prohibited Acts, and Penalties); 43 CFR 8341 (Conditions of Use). 

 Temporary closure or restriction orders under these authorities are enacted at the discretion of the 

authorized officer to resolve management conflicts and protect persons, property, and public 

lands and resources. Where an authorized officer determines that off-highway vehicles are 

causing or would cause considerable adverse effects upon soil, vegetation, wildlife, wildlife 

habitat, cultural resources, historical resources, threatened or endangered species, wilderness 

suitability, other authorized uses, or other resources, the affected areas shall be immediately 

closed to the type(s) of vehicle causing the adverse effect until the adverse effects are eliminated 

and measures implemented to prevent recurrence. (43 CFR 8341.2) A closure or restriction order 

shall be considered only after other management strategies and alternatives have been explored. 

The duration of temporary closure or restriction orders shall be limited to 24 months or less; 

however, certain situations may require longer closures and/or iterative temporary closures. This 

may include closure of routes or areas. 

When developing implementation-level Travel Management Plans, the BLM would consider the 

following when determining the compatibility of different types of public travel opportunities: 

 Other resource values and uses 

 Primary travelers 

 Emerging uses such as growing recreational-use types 

 Setting characteristics that are to be maintained, including recreation setting characteristics and 

VRM settings 
1607 | P a g e

 Primary means of travel allowed to accomplish the objectives and to maintain the setting 

characteristics 

 Social conflicts between different travel types 

 Social conflicts between public land visitors and adjacent property owners 

 Number and types of access points 

 Existing right-of-ways (ROWs) and future ROW requests 

 Existing geographic identify and public knowledge of the area 

 Identifiable boundaries of the Travel Management Area based on topography, major roads, or 

other easily discernible elements 

Implementation-level travel management planning would be completed within 5 years of completion of 

these RMP revisions. Districts would be responsible for identifying timelines to complete travel planning 

efforts. These timelines would identify areas in order of priority for completion, and would be updated 

regularly in all relevant planning areas to accelerate the accomplishment of data collection, route 

evaluation and selection, and on the ground implementation efforts including signing, monitoring and 

rehabilitation. Prioritization of areas for completion of implementation-level travel management planning 

would follow the criteria included in this appendix. 

The implementation-level travel management planning process includes development of a public outreach 

strategy. Consultation with interested user groups, Federal, State, county and local agencies, local 

landowners, and other parties would be done in a manner that provides an opportunity for the public to 

express itself and have its views given consideration. A public outreach strategy to engage fully all 

interested stakeholders would be incorporated into future travel management plans. 

A complete TMP includes or addresses—

 Criteria to select or reject specific transportation linear features in the final travel management 

network; to add new roads, primitive roads or trails; and to specify limitations. The criteria must 

include those identified in 43 CFR 8342.1 

 A map of roads, primitive roads, and trails for all travel modes and uses, including motorized, 

non-motorized, and mechanized travel 

 Definitions and additional limitations for specific roads, primitive roads, and trails 

 Guidelines for managing and maintaining the travel management system. This includes, at a 

minimum, the development of route-specific roads, primitive roads, and trail management 

objectives, a sign plan, and education/public information plan, an enforcement plan, and a process 

requiring the application of engineering best management practices; and 

 Indicators to guide plan maintenance, amendments, or revisions related to the travel management 

network. 

 Needed easements and rights-of-way (ROW) (to be issued to the Bureau of Land Management 

[BLM] or others) to maintain the existing road, primitive road, and trail network providing public 

land access 

 Provisions for new route construction or adaptation or relocation of existing routes 

 A plan for decommissioning and rehabilitating closed or unauthorized routes 

 A monitoring plan 

 Classification of all roads, primitive roads, and trails, designated for travel in a TMP, as assets in 

the Facility Asset Management System. All roads, primitive roads, and trails will also be 

identified as such in the Ground Transportation Linear Feature geospatial database. 
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Existing Motorized and Non-Motorized Trails 

The BLM is currently working on an inventory of all user-created motorized and non-motorized routes 

within the decision area. The BLM will use this inventory as a baseline to guide future route designations 

through implementation-level travel management planning within the areas that are designated limited to 

existing routes. 

Recreation routes (authorized and unauthorized) have been created in response to demand for trail-based 

recreation. Table Q-9 displays the current authorized trails within the decision area. As demand for trailbased recreation (especially OHV riding) increased, the number of routes increased. The routes developed 

for administrative and resource uses provide primary access routes throughout most of the decision area. 

These primary access routes were created for administrative and resource uses, not for recreation. As a 

result, the routes are not always providing the recreation experience users are looking for. Over time, 

recreation use extended, connected, or pioneered new routes from the administrative and resource use 

routes. This pattern of route development has resulted in high route densities where the administrative and 

resource use routes provided access for recreation use. 
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Table Q-9. Current authorized motorized and non-motorized trails within the decision area 

District/Field Office Recreation Trail Miles

Coos Bay

Blue Ridge 10.0

Doerner Fir 0.5

Euphoria Ridge OHV Trail System 4.0

Floras Lake 1.0

Four Mile Creek 0.3

Loon Lake Waterfall 0.5

Lost Lake 1.0

New River/Storm Ranch 2.0

New River Water Trails 5.0

New Fork Hunter Creek 2.0

North Spit Trail System 9.0

Subtotal 35.3

Eugene

Clay Creek Trail 0.6

Eagles Rest Trail 0.2

Lake Creek Falls Trail 0.2

Row River Trail 13.5

Shotgun Creek Non-Motorized Trails 6.2

Shotgun Creek OHV Trail System 23.2

Tyrrell Forest Succession Trail 1.0

Whittaker Creek Trail 1.0

Subtotal 45.9

Klamath Falls

Gerber-Miller Creek Potholes Trail 13.0

Keno Spencer Snowmobile Trail 6.0

Pacific Crest National Scenic Trail 1.0

Pederson Snowmobile Trail 5.0

Surveyor Peak Snowmobile Trail 3.0

Wood River Wetland Trail 1.0

Subtotal 29.0

Medford

Armstrong Gulch Trail 1.0

Baker Cypress < 1.0

Beacon Hill 1.0

Bolt Mountain 3.0

Buck Prairie Cross Country Trails 17.0

Cathedral Hills Trail System 11.0

Eight Dollar Mountain Boardwalk/Trail 0.3

Enchanted Mountain/Felton 5.0

Grayback Mountain Trails 6.5

Grizzly Peak 5.0

Hidden Creek 1.0

Jacksonville Woodlands 2.5

Jeffrey Pine Loop 1.0

Kelsey Peak 3.0

Kerby Peak 4.0
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District/Field Office Recreation Trail Miles

King Mountain 1.0

Lake Selmac 3.0

Layton Ditch 2.0

London Peak Accessible 0.3

Lower London Peak 2.0

Lower Table Rock 2.0

Mountain of the Rogue Trail System 8.0

Mule Creek 3.0

Pacific Crest National Scenic Trail 22.4

Rainie Falls 2.0

Rogue River National Recreation Trail 23.0

Rough and Ready 0.5

Sterling Mine Ditch Trail 21.0

Tunnel Ridge 1.0

Upper Table Rock 2.0

Wagner Creek 0.5

Wolf Gap 4.0

Subtotal 159.5

Roseburg

China Ditch Trail 0.4

Emerald Trail 1.3

Miner-Wolf Creek WW Trail 0.2

North Bank Ranch Trail System 8.0

North Umpqua Trail 12.3

Sawmill Trail 12.3

Susan Creek Trails 2.0

Susan Creek Falls Trails 1.0

Wolf Creek Falls Trails 1.2

Subtotal 38.7

Salem

Alsea Falls Trail System 8.0

Baty Butte-Silver King Trail 3.4

Boulder Ridge Trail 0.2

Eagle Creek Trail 0.5

McIntyre Ridge Trail 0.5

Molalla River Trail System 24.6

Nasty Rock Trail 1.0

Sandy Ridge Trail System 15.4

Table Rock Wilderness Trails 20.4

Upper Nestucca OHV Trail System 25.0

Valley of the Giants Trail 0.8

Subtotal 99.8

Grand Total 395.1

The BLM still requires additional data and information on site-specific travel routes to be able to 

complete implementation-level travel management planning across the entire planning area. Route 
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identification and comprehensive route inventories have been and are continuing to be collected to have 

this complete information available to complete all implementation-level travel management planning 

within 5 years after the completion of these RMP revisions.

Criteria to Prioritize Implementation Level Travel Planning 

The BLM would prioritize implementation-level travel management planning by reviewing lands within 

each district at the scale of areas designated for public motorized access or Travel Management Areas. 

The BLM would prioritize the order for completion of implementation-level travel management planning 

by prioritizing those areas meeting most of the following criteria first: 

 Areas where damage to soil watershed, vegetation, air, or other resources of the public lands, and 

to prevent impairment of wilderness suitability is occurring 

 Areas where harassment to wildlife or substantial disruption to wildlife habitats are occurring; 

Prioritize areas where harassment to threatened and endangered species and their habitats are 

occurring 

 Areas where conflicts between motorized and non-motorized recreational uses are occurring 

 Areas where route, type of use, or season of use designations are necessary to support 

management objectives or management direction for the RMP-designated land use allocations 

 Areas that have secured legal public access 

 Areas also identified as Special Recreation Management Areas where a strong linear asset 

component is identified (e.g., mountain biking, hiking, equestrian, OHV) 

 Areas with completed route inventories 

Areas not meeting any of these criteria would be scheduled to be completed last, but not more than 5 

years after completion of these RMP revisions. Where multiple areas meet an equal number of criteria for 

prioritization listed above, BLM districts would apply local knowledge of public concerns, interests, or 

controversies to prioritize areas to respond to local stakeholders and interested publics. 

Plan Maintenance and Changes to Route Designations 

The RMP would include indicators that would guide plan maintenance, amendments, or revisions related 

to designations for public motorized access or the approved road and trail systems within limited to 

existing areas. Future conditions may require the designation or construction of new routes or closure of 

routes to better address resources and resource use conflicts. The BLM would be able to modify actual 

route designations within the limited category through implementation-level travel management planning 

without necessitating an RMP amendment, although compliance with NEPA would still be required. 

The BLM would accomplish implementation-level travel management planning through plan 

maintenance. The BLM would collaborate with affected and interested parties in evaluating changes to 

the existing and designated road and trail network in limited area designations and changes to the broader 

Recreation Management Area designations that emphasize motorized OHV recreation. In conducting such 

evaluations, the BLM would consider the following: 

 Routes suitable for various categories of OHVs and opportunities for shared trail use 

 Needs for parking, trailheads, informational and directional signs, mapping and route profiles, 

and development of brochures or other materials for public dissemination 

 Opportunities to tie into existing or planned route networks 

 Measures needed to meet other resource objectives in the RMP 
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References 

USDI BLM. 1987. BLM Manual Handbook H-9114-1 – Trails. Available at BLM district offices. 

---. 2012. BLM Manual Handbook H-8342-1 – Travel and Transportation Management. 146 pp. 

http://www.blm.gov/pgdata/etc/medialib/blm/ca/pdf/cdd/west_mojave_plan_updates.Par.33567.File.dat/Travel%20and%20

Transportation%20Management%20Handbook.pdf.
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Appendix R – Tribal

Biographies and Maps 

The BLM compiled data and text from five of the seven Tribes with Tribal lands and varying interests 

within the planning area, or portions of it. Each Tribe wrote and submitted their individual Tribal 

biography. The BLM did not alter or edit the text in any way. The BLM created the maps using data 

provided by each of the Tribes in order to show those lands of interest to each Tribe. The maps and 

biographies do not reflect a BLM endorsement of tribally stated territories or histories. In addition, the 

nomenclature used on each map came from the Tribes as well. The BLM has included these biographies 

and maps as context for the Tribal Interests section as well as to allow the Tribes to state who they are and 

how they define their interest in the lands administered by the BLM in western Oregon. It also provides 

managers and others who implement this RMP with valuable information about the history and interests 

of Tribes within the planning area. All seven tribes listed below are federally recognized Tribes and 

interact with the BLM as sovereign Nations. 

 The Confederated Tribes of Coos, Lower Umpqua, and Siuslaw Indians 

 The Confederated Tribes of the Grand Ronde Community of Oregon 

 The Confederated Tribes of Siletz Indians 

 The Confederated Tribes of the Warm Springs Indian Reservation 

o (The BLM did not receive documents from the Confederated Tribes of the Warm 

Springs.) 

 The Coquille Indian Tribe 

 The Cow Creek Band of Umpqua Tribe of Indians 

 The Klamath Tribes 

The Confederated Tribes of the Coos, Lower Umpqua, and 

Siuslaw Indians 

We, the Coos, Lower Umpqua, and Siuslaw, are coastal people. We still live on lands that once were 

managed by our ancestors. We have always strived to live in balance with the land and waters, using their 

gracious bounties and sustaining them for future generations. We have always held sacred the land and 

the resources that rely on that land, water, and air. We have always lived using what the Creator has 

provided. We have endured many hardships to our land, people and culture over the last 150 years. 

Thousands of our ancestors lost their lives to relocation, sickness, and moral. Over the last century we 

have worked to sustain our people and culture by protecting the environment, natural resources and trying 

to find ways to balance our traditions and philosophy with the dynamic and developing viewpoints 

communities that share our coasts and lands. 

A Historical Record 

In 1855, members of the Coos, Lower Umpqua, and Siuslaw Tribes, along with members of the other 

coastal Oregon tribes, signed a treaty with the United States of America. This treaty would have ceded 

lands west of the summit of the Coast Range. This treaty was introduced in the United States Senate and 

read once, but whether through negligence or whether due to concerns arising from what is commonly 

known as the Rogue River War, it was never read a second time nor ratified by the Senate. Despite the 

lack of ratification, the Coos and Lower Umpqua Tribes were held captive beginning in 1856, the Coos 

were confined on the sand spit known as Ki:we’et (now commonly known as Sitka Dock) just south of 

Empire, the Lower Umpqua moved to Fort Umpqua on the north spit of the Umpqua River, then at the 
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Alsea Sub-Agency of the Coast Reservation and the Siuslaw were confined within the Coast Reservation, 

the boundary of which included most of the western portion of their Ancestral Territory. 

In 1871, the federal Appropriations Act ended treaty making between the federal government and tribes. 

The relationship between sovereigns was continued by the United States through “agreements,” statutes, 

and Executive Orders in lieu of treaties. The passage of this act ended the prospects of the Tribes’ treaty 

being ratified. 

In 1875, the Alsea Sub-Agency of the Coast Reservation was opened to Euro-American settlement. This 

occurred against the will and heartfelt testimony of the Coos and Lower Umpqua confined at the subagency. These Tribal Members were ordered to relocate to the remaining portion of the Coast Reservation 

centered around the Siletz Agency. Most if not all of the Coos and Lower Umpqua refused and relocated 

around the remnant Siuslaw population centered around the traditional village of Qa’ich (now commonly 

known as the area around the Hatch Tract, the site of the Confederated Tribes Three Rivers Casino and 

Hotel); centered around the area of Gardner and the confluence of the Smith and Umpqua Rivers, or 

centered around South Slough and other areas around Coos Bay. 

In 1887, the General Allotment (Dawes) Act authorized allotments to Indian People. Most of these passed 

out of Indian tenure due to financial hardship, lack of familiarity of the applicable land tenure laws and 

regulations, and/or due to scheming by non-Indian land investors. Some allotments remain in Tribal 

Member ownership in fee status or have been sold to the Confederated Tribes government. 

In 1917, the Coos, Lower Umpqua and Siuslaw Indians, in reflection of millennia of shared cultural and 

political ties, and in response to sixty years of common adversity, formally confederated to form the 

Confederated Tribes of the Coos, Lower Umpqua and Siuslaw Indians. The primary purpose of this 

confederation was to pursue land claims. Since according to United States Law in order to take lands a 

ratified treaty agreement had to take place and there was no such ratified treaty. 

In 1929, the United States government waived its sovereign immunity (45 Stat.1256, as amended by 47 

Stat. 307) and allowed the Confederated Tribes to sue the federal government in the United States Court 

of Claims for settlement of land claims. Testimony from several Tribal Members and members of the 

broader community was taken over the next several years. In 1935, the testimony of George Bundy 

Wasson (of Coos and Coquille descent) in the Court of Claims described the boundary of Ancestral 

Territory as extending from Fivemile Point (Coos County) north to Tenmile Creek (Lane County) thence 

east to the crest of the Coast Range, including the Coos, Umpqua (to the head of tide), Smith, and Siuslaw 

Watersheds. (This description has been carried forward and appears on the enrollment cards of members 

of the Confederated Tribes and was adopted in Tribal Council Resolution No. 90-010.) In 1938, the 

United States Court of Claims ruled against the Confederated Tribes, describing Indian testimony as 

hearsay and self-interested. Later in1938 the United States Supreme Court refused to hear Confederated 

Tribes appeal of this Court of Claims ruling. In 1947, the Confederated Tribes filed claim to the 

reorganized Indian Claims Commission, which in 1952 rejected the Confederated Tribes claim, ruling 

that the matter was res judicata, or a case already decided by the Court of Claims. 

Following World War II, the United States government pursued the goal of Indian assimilation into the 

“melting pot” and promoted the termination of federal recognition of several tribes. In 1951, the 

Confederated Tribes of the Coos, Lower Umpqua and Siuslaw Indians refused to endorse termination of 

federal recognition. In 1954, Public Law 588 terminated federal recognition of forty-three bands and 

tribes in Oregon effective 13 August 1956, including, without consent, the Confederated Tribes of the 

Coos, Lower Umpqua and Siuslaw Indians. 
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In 1956, the Confederated Tribes of the Coos, Lower Umpqua and Siuslaw Indians petitioned the United 

Nations for membership “to the end that truth and justice may be raised up and accorded their proper 

place.” The petition was ignored.

The period of termination was a dismal time. Tribal Members continued to know who they were, 

continued to remember their Ancestors, continued to honor their Elders, continued to meet among 

themselves as a Tribe, continued to raise their children to be Coos, Lower Umpqua, and Siuslaw, and 

continued to fight for their rights. Despite the dismissal of their Tribal identity by the United States 

government, the Confederated Tribes of the Coos, Lower Umpqua and Siuslaw Indians maintained 

continuous government of, by, and for the Tribes, and exercised the rights and fulfilled the responsibilities 

of any government to its People. 

From 1954 through 1984, the Confederated Tribes expended three decades of human energy, money, and 

political capital working to have federal recognition restored. Through the sacrifices of many who lived to 

see the day, and through the sacrifices of many others who did not, federal recognition was restored to the 

Confederated Tribes of the Coos, Lower Umpqua and Siuslaw Indians through the enactment of Public 

Law 98-481which was signed into law on 17 October 1984. 

Future Directions 

We of the Coos, Lower Umpqua, and Siuslaw have lived here since time immemorial. Our culture and 

stories are reminders to show our appreciation for all that we have. We have always taken only what we 

need, and we have always given back. For hundreds of generations we lived in balance with nature. We 

bring back the bones of the first caught Salmon to the ocean to show respect to the Salmon. It is our way 

of celebrating and communicating our appreciation to the Salmon, in recognition of their sacrifice. It is 

also a time to refrain from fishing and give reprieve to the first Salmon as they run upriver. We consider 

ourselves responsible for the survival and health of the fish, forest, waters and all the resources of our 

lands. 

We understand that People are part of the Natural World. We understand that for us to live other parts of 

creation must give us their lives. We understand that our lives depend on the lives of others. We must take 

care of them, as they take care of us. We all must take care of each other. For ten thousand years, for five 

hundred generations, we have returned our Ancestors to the earth. Our Ancestors’ bones are all around us 

– in the earth, in the trees, in the water, in the air. We feel the spirits of our Ancestors accompanying us 

every day as the Tribe continues on. 

Over 150 years ago, we signed a treaty would have exchanged our land for some promises. That treaty 

was never ratified; we were removed from our lands and the promises were not kept. Where once millions 

of salmon returned to our streams, today only thousands return. 

BLM-managed lands are culturally significant to the Tribes. Tribal cultural resources include 

archaeological sites and traditional cultural properties; living cultural resources such as cedar and salmon; 

and spiritually-significant sites including certain promontories and viewsheds. These cultural resources 

contribute to the health of tribal cultures and the persistence of tribal identities. 

Today, we are Tribal members and we are neighbors. Today we sit around the same table. Today we face 

the same issues, and today we work together and create common solutions. We are proud to be members 

of the communities in our Ancestral Watersheds. We greatly respect the accomplishments of our 

partnerships, and we look forward to the continued healing that our partnerships can achieve. 
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INSERT MAP HERE

Map R-1. Tribal Lands of the Confederated Tribes of the Coos, Lower Umpqua, and Siuslaw Indians 
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The Confederated Tribes of the Grand Ronde Community of 

Oregon 

More than 30 Tribes and Bands were relocated to the Grand Ronde Reservation from western Oregon, 

southwestern Washington, and northern California and removed to the Reservation after signing seven 

treaties from 1853-1855. These include the Rogue River, Umpqua, Chasta, Kalapuya, Chinookan, Molalla 

and Tillamook Indians who had lived in their traditional homelands since time immemorial. Prior to 

removal they lived off the land – fish, game and plant foods were plentiful, and they traded with other 

Tribes and later, with non-Indians. 

The Grand Ronde Reservation was begun by treaty arrangements in 1854 and 1855 and firmly established 

by Executive Order on June 30th, 1857. The original reservation contained more than 60,000 acres and 

was located on the eastern side of the coast range on the headwaters’ of the South Yamhill River, about 

60 miles southwest of Portland and about 25 miles from the ocean. 

In 1887, the General Allotment Act became law. Under the law, 270 allotments totaling more than 33,000 

acres were made to the Tribal members of the reservation. These allotments came with the understanding 

that they would pass from federal trust status into private ownership after 25 years. The purpose of the 

Act was to encourage Tribal people to become farmers and eliminate common ownership of land, 

traditional activities and practices. In 1901 U.S. Inspector James McLaughlin declared 25,791 acres of the 

reservation “surplus” and the U.S. sold it for $1.10 per acre to non-tribal businesses and citizens. 

In 1936 under the Indian Reorganization Act (also known as the Howard-Wheeler Act), the Tribe was 

able to purchase 536.99 acres to provide homes and land for tribal people. The attempt at recovery of land 

was halted on August 13th, 1954, when the Congress passed Public Law 588, the Western Oregon 

Termination Act, which terminated the Tribe’s federal recognition and abolished the treaties that had been 

negotiated in good faith. This act of legislation was aggressively pursued by then Secretary of Interior 

James Douglas McKay. McKay was Oregon’s 25th Governor prior to accepting the position of Secretary 

of Interior. McKay oversaw the implementation of the Western Oregon Termination Act, which went into 

effect on August 13, 1956. For nearly 30 years, the members of the Tribe were landless with the 

exception of the Tribal cemetery and without the Tribe to provide a focal point of community. Irreparable 

damage was done to the Tribal community’s health, education, languages and cultures. In the early 1970s 

efforts began to reverse the Termination Act and to reestablish the Tribe. Tribal leaders worked together 

with no financial backing, only a cemetery, and their desire for the Tribe to restore its federal recognition. 

On November 22nd, 1983, Public Law 98-165, also known as the Grand Ronde Restoration Act, was 

signed into law. After a great deal of negotiations with the local community, local landowners, as well as 

state and federal agencies, the Tribe developed a Reservation Plan. Following this on September 9th, 

1988, Public Law 100-425, also known as the Grand Ronde Reservation Act, was passed, restoring 9,811 

acres of the original reservation. On October 4, 1994, Public law 103-435, added 240 acres to the 

Reservation to compensate the Tribe for a surveying error that was never corrected prior. Today the 

10,052-acre reservation lies just north of the community of Grand Ronde. With Restoration of the Tribal 

government and the re-establishment of the Reservation, the Tribe has focused on rebuilding Tribal 

programs, developing Tribal services and servicing the greater community. The Tribe has provided a 

viable community that contributes to the local economy and provides for the achievement of the Tribal 

members. 
1618 | Page

INSERT MAP HERE

Map R-2. Tribal Lands of the Confederated Tribes of Grande Ronde 
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The Confederated Tribes of Siletz Indians 

The Confederated Tribes of Siletz Indians (CTSI) consists of the many Tribes and Bands who were 

removed to or came to reside on the Siletz/Coast Reservation beginning in 1856 or after. Almost 

exclusively, ancestral Tribal residents resided there by Aboriginal Right and/or Treaty Right (it being 

their designated permanent home under treaty stipulations/approved federal policy). 

Prior to Treaties being signed, the Reservation being established, and the U.S policy that all Western 

Oregon Indians were to confederate and live within its borders, Siletz ancestral peoples maintained about 

20 million acres of ancestral territories, approximately 19 million of those acres were the area of Oregon 

west of the summit of the Cascades. As treaties were signed, our people generally ceded large territories 

to the U.S., while maintaining certain rights. Those rights included: (1) the right to a permanent 

reservation (and adequate land, water, fish wildlife and other resources for the CTSI to sustain itself into 

the future); (2) payment for cession of aboriginal title to those vast territories; and (3) right to a temporary 

reservation or ability to stay within the ceded area until the President of the U.S. selected the permanent 

reservation. 

November 9, 1855, President Pierce signed an Executive Order establishing our permanent reservation at 

about 1.1 million acres. It included approximately 1/3 of what is now the State of Oregon’s coastline. 

Removal of our ancestors to the new reservation began soon after. An encampment was established just 

off the eastern border of the reservation as a staging area for bringing tribes to the reservation. Just after 

most of the tribes had moved from the encampment/staging area to the Siletz Reservation, President 

Buchanan saw fit to re-designate the temporary encampment as the Grand Ronde Reservation. All Tribes 

and individuals who came to reside within the Siletz Reservation became members of the Confederated 

Tribes of Siletz. Those who remained at the encampment became members of the Confederated Tribes of 

Grand Ronde. All Western Oregon Indians were considered to belong to one or the other of the 

confederations. There were individuals, and small family groups who had stayed off-reservation, or 

returned from one or other of the reservation to live in old homelands. 

Many hardships were endured, including starvation, neglect, abuse, forced labor, and violent assaults and 

punishments, sometimes resulting in deaths. Tribes were still being brought onto our Reservation from 

temporary encampments at Fort Umpqua and other places into the early 1860s. At about this time, the 

Coos, Lower Umpqua people who had not previously resided within the reservation were brought to a 

new Sub-Agency of our reservation established at Yachats, referred to as the Alsea Sub-Agency or 

Yachats Sub-Agency. 

Quickly the brutal implementation of federal policy turned our Reservation’s atmosphere into one of a 

harsh prison camp, rather than the Tribal Homeland that had been promised. That perception of our 

population suffering to bend to the will and whims of the U.S. and shifting policy decisions led U.S. 

Administrative and Legislative officials to take actions which grabbed large portions of our permanent 

reservation through illegal means – which did not take into account our peoples’ treaty rights, or their 

own legal responsibilities/lack of authority. 

In 1865, about 200,000 acres of our permanent reservation, around Yaquina Bay were taken by order 

signed by President Johnson. That action left our remaining reservation lands in two detached parcels. In 

1875, another 700,000 acres were ripped from our possession through an Act of Congress. Our people 

were forced to move, instead of being informed that they had to give informed consent in order for the 

Act to legally take effect. 

From 1875-1892 our remaining reservation consisted of about 225,000 acres. In 1892 the General 

Allotment Act took effect both on reservation and for our off-reservation families. Five hundred fifty-one 
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(551) Siletz Reservation Allotments of approximately 80 acres each were assigned to the tribal members 

then present, and before some families could even return to claim an allotment, the allotment rolls were 

closed and the remaining reservation lands declared “surplus.” Our Tribe was forced to agree to cede 

those lands for 74 cents an acre, or they “could be taken just like the 1865 and 1875 reductions – without 

compensation”. Promises that future tribal members could apply for and receive allotments from the open 

and unclaimed areas of the ceded areas remain unfulfilled. 

Quickly, U.S. law and policy began to restrict our ability to hang onto even our allotments. By 1912, over 

half of the Siletz Allotments were non-Indian owned. All of these actions, from treaties, removal, 

reservation reductions, to loss of family allotments were experienced as a constant onslaught, and 

continued as U.S. Court of Claims and Indian Claims Commission cases were brought forward by our 

people. The U.S. Courts generally denied or minimized the U.S.’s responsibilities to our pay for lands 

ceded to the U.S., or maintain the reservation boundaries that had been set according to treaty stipulations. 

A combination of individuals who were of Coos, Lower Umpqua and Siuslaw descent brought suit for 

taking of aboriginal title without a title. Many enrolled Siletz members participated in the suit, but the 

effort was initiated by off-reservation families not enrolled, so the Court found in part that the group did 

not have standing to bring the suit – because the Confederated Tribes of Siletz, the legal successors in 

interest to those ancestral tribes, had not brought the action. Our Tillamook, Yaquina, Alsea, Tututni, 

Chetco and Coquille people brought suit through the Confederated Tribes of Siletz Indians, and seemed to 

be on the verge of a major victory, when the U.S. appealed that claims case to the U.S. Supreme Court. 

The Supreme Court decided that descendants of those tribes were only entitled to value at the time of 

taking, no interest accrued, because the U.S had failed to ratify their own treaty. A mere pittance was 

recovered for all of the generations of suffering since removal from those lands. 

Simultaneous with land claims actions proceeding, was Siletz and Grand Ronde being targeted for the 

U.S. Policy of terminating tribal governments in the 1950s. The Western Oregon Termination Act was 

passed in 1954, and named the Confederated Tribes of Siletz Indians and Confederated Tribes of Grand 

Ronde, but no other Tribal governments were really recognized at that time. To ensure that no individuals 

living off-reservation, separate from Siletz or Grand Ronde, or that constituent groups who were members 

of those confederations could step forward later, and claim that they had survived the intended 

termination by not being named in the act – Congress named every western Oregon aboriginal group who 

had ever been named in a federal document, to be sure no chance of any tribal groups asserting status in 

Western Oregon would be possible. In 1956, the Western Oregon Termination Act took full effect. 

Termination was meant to be the final blow to the CTSI and its members. The judgment funds from 

claims decisions were even held-up as insurance that no concerted resistance to the implementation of 

Termination would arise. About 1970, Siletz Indians began calling meetings and asking our people to 

come together and support an effort to get Congress to address our situation. Many of our people were 

living in poverty. Sub-standard housing was too common, healthcare and education access was low. In 

1973, the Menominee Tribe of Wisconsin successfully petitioned Congress to reverse their Termination 

Act. The CTSI began working toward the same goal, but as the first landless tribe to regain federal 

recognition after being terminated. In November 1977, Congress passed, and President Jimmy Carter 

signed into law The Siletz Restoration Act. The Restoration Act called for an initial Reservation Plan to 

be submitted to Congress for consideration. The Siletz Tribe was advised to submit a modest request for 

return of lands, which could alter be expanded. The 1980, Siletz Reservation Act included about 3,660 

acres of small scattered BLM administered parcels, primarily east of the town of Siletz. Today the CTSI 

owns about 15,000 acres, mostly timberlands added to our holdings after 1980, through purchase, 

donation, wildlife mitigation agreements, etc. Those lands are held in a variety of status’ (Reservation, 

non-Reservation Trust, and fee) and managed for a combination of resource use/protection/enhancement 

values and revenue generation for member services. 
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Many places of intense historical, cultural and spiritual significance to our Confederated Tribes of Siletz 

Indians are now owned/managed by the BLM. Among these are ancestral villages such as Umpqua Eden, 

prayer places, treaty signing, and temporary Reservation sites such as Table Rocks in the Rogue Valley, 

battle sites such as Hungry Hill, numerous plant and other resource gathering places tended by our 

ancestors, both within and outside of our 1855 Siletz Reservation boundaries, including Yaquina Head 

Outstanding Natural Area. Because our people do not hold title or control of these places currently does 

not release us from our obligations to maintain our connections to them and recognize them for their 

importance to all generations in the past, present and future.
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Map R-3. Tribal Lands of the Confederated Tribes of Siletz Indians 
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The Coquille Indian Tribe 

The Coquille Indian Tribe is a people that have always shared a strong connection with the land. This 

relationship is evident in the tribe’s name which comes from the Native name for a lamprey eel, or 

“Scoquel,” of which the river it abounded in took its name as well, and was later shortened to, “Coquell.” 

Thus, “Coquille”, pronounced, Ko-kwel, derived from a Chinook jargon word, became the name of a 

place and a people. 

Coquille ancestors lived at South Slough on lower Coos Bay, in all the watersheds of the Coquille River 

system from the ocean to its headwaters, and along the coast as far as Cape Blanco and Port Orford. They 

spoke three distinct local languages; Miluk, Hanis, and Athapaskan, intermixed with Chinook jargon, the 

trade language for Northwest Native Americans. Along the coast, estuary shorelines and sheltered coastal 

bays offered food of all sorts, and canoe travel was easy. In the interior, streams and rivers full of fish and 

valleys where deer and elk wintered, determined where villages were located. Seasonal places in the 

uplands and interior valleys away from the estuaries and coast were often hunting and food gathering 

areas used by many different Native groups. Typically, when Coquille and other groups gathered for 

berry and nut harvesting, root digging, or at hunting and fishing sites, it was also a time of celebration, 

and for renewing old relationships and making new ones. These places were returned to year after year. 

Today, annual events like the Mid-Winter Gathering, Restoration Day Celebration, and Solstice Dances 

all respond to those ancient Coquille practices. 

The Coquille people’s Ancestral Homelands encompassed more than one million acres, all of it ceded to 

the U.S. government in treaties signed by, “Coquille chiefs and head-men,” first in 1851 and again in 

1855. Those treaties were never ratified by the U.S. Senate, thus reservation lands and other 

considerations promised in the treaties never materialized, so the Coquille people and the generations that 

followed were denied permanent Tribal homelands. 

On June 28, 1989, Congress passed public Law 101-42, which re-established the Coquilles as a federally 

recognized Indian Tribe. The Coquille Restoration Act restored the Tribe’s eligibility to participate in 

federal Indian programs and to receive funding to provide health, education, housing assistance, and 

pursue economic development for its members. The Act also reaffirmed the Tribe as a sovereign 

government, and validated the Tribe’s authority to manage and administer political and legal jurisdiction 

over its lands and resources, its businesses, and its Tribal community members. Today, the Tribe, made 

up of over a thousand members, provides services to tribal members throughout the world and especially 

concentrated within the five-county service area of Coos, Curry, Douglas, Lane, and Jackson counties in 

Oregon. 

The Coquille Forest was created by enactment of P.L. 104-208, Division B, and Title V on September 30 

1996. This Public Law, passed by the U.S. Congress and signed by President Clinton, restored 5,410 

acres (5,397 according to GIS) of ancestral homelands to the Coquille Indian Tribe and designated the 

restored lands as the Coquille Forest. 

The Coquille Forest Act allows the Coquille Tribe an opportunity to reaffirm Tribal stewardship over a 

small portion of its ancestral homelands, and to reestablish many of the Tribal cultural traditions that were 

once practiced on these landscapes. 

The purpose for creation of the Coquille Forest was described by Senator Hatfield in his statement before 

the U.S. Senate concerning Amendment No. 5150 to the Oregon Resources Conservation Act of 1996 [S. 

1662]: "It is intended to establish a Coquille Forest for the Coquille Tribe that will mesh into the broader 

forest management of Coos County. Within this context, the Coquille Forest is to provide a basis for 
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restoring the Tribe’s culture as well as providing economic benefits [Congressional Record- Senate, pg. 

S9656, August 2, 1996]. 

The respect the Coquille people have always had for their Ancestral Homelands, much of which is now 

administered by the Bureau of Land Management, is carried on in legacy through the practices of the 

Coquille Indian Tribe today. Annual trips are still made to harvest traditional foods, gather grasses for 

weaving baskets and enjoy celebrations on the land their ancestors had stewardship over for thousands of 

years. The land is, and always will be, an integral part of their identity and heritage as a people. 
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Map R-4. Ancestral Homelands and Areas of Special Interest to the Coquille Indian Tribe 
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The Cow Creek Band of Umpqua Tribe of Indians 

The Cow Creek Band of Umpqua Tribe of Indians, located in Douglas County, Oregon, signed a treaty 

with the United States of America on September 19, 1853, which was one of the first treaty’s from the 

Pacific Northwest to be ratified by the Senate on April 12, 1854. By that agreement, the Cow Creeks 

became a landless tribe, ceding more than 800 square miles of the Umpqua watershed in Southwestern 

Oregon to the United States. Unfortunately, the Treaty was ignored by the Federal Government for nearly 

a century until the Termination Act in 1956 which terminated federal relations with the Cow Creeks, 

along with 60 other tribes and bands in western Oregon. 

The Cow Creeks received no prior notification of the Termination Act, and because of that were able to 

obtain presidential action in 1980 to take a land claims case to the U.S. Court of Claims. On December 

29, 1982, nearly 125 years after the Treaty was signed, P.L. 97-391 was passed by Congress and the Tribe 

regained federal recognition. 

With federal recognition, the tribe was able to negotiate federal contracts with the Bureau of Indian 

Affairs and the Indian Health Service to administer such programs as Housing, Education, and others 

related to health for the enrolled membership of the Tribe within the tribal service area. 

Current enrollment for the Tribe is over 1600 members. Nearly one half of all tribal members reside in the 

tribe’s seven county service area consisting of Coos, Deschutes, Douglas, Jackson, Josephine, Klamath 

and Lane Counties. These counties were determined by the Bureau of Indian Affairs and Indian Health 

Service as required by the CFR to define “on or near the reservation” for the tribe.

In 1985 the Tribe purchased 29 acres in Canyonville, Oregon which was eventually taken into “trust” by 

the federal government and became the Tribal Reservation. This property is only 6 miles from where the 

Treaty was signed in 1853. 

The tribe has maintained strong cultural ties to the area. The traditional Cow Creek Pow-wow is held 

annually at South Umpqua Falls, an area that has tremendous importance to the tribe’s culture and 

tradition. 

Another area of great historical, cultural, and traditional use is an area known as the Huckleberry Patch on 

the Rogue-Umpqua Divide. This area was a traditional use area for the tribe and has great historic 

importance. 

The Tribe has remained steadfast in the realization of tribal economic self-sufficiency. After years of 

planning and financial packaging, the Tribe opened the Cow Creek Bingo Center on April 30, 1992. 

Through careful management of tribal assets, the tribe was able to initiate a series of expansions that 

resulted in the Seven Feather Hotel and Casino Resort. 

With proceeds from the resort, the tribe has developed an aggressive economic development program that 

includes land acquisition and business diversification and development. 
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Map R-5. Tribal Lands of the Cow Creek Band of Umpqua Tribe of Indians 
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The Klamath Tribes 

naanok ?ans naat sat’waY

a naat ciiwapk diceew’a “We help each other; We will live good”

We are the Klamath Tribes, the Klamaths, the Modocs and the Yahooskin. We have lived here (Map R6), in the Klamath Basin of Oregon, from time beyond memory. Our legends and oral history tell about 

when the world and the animals were created, when the animals and gmok’am’c – the Creator – sat 

together and discussed the creation of man. If stability defines success, our presence here has been, and 

always will be, essential to the economic well-being of our homeland and those who abide here. 

Time Immemorial 

In the old times we believed everything we needed to live was provided for us by our Creator in this rich 

land east of the Cascades. We still believe this. We saw success as a reward for virtuous striving and 

likewise as an assignment of spiritual favor, thus, “Work hard so that people will respect you”, was the 

counsel of our elders. For thousands upon countless thousands of years we survived by our 

industriousness. When the months of long winter nights were upon us, we survived on our prudent 

reserves from the abundant seasons. Toward the end of March, when supplies dwindled, large fish runs 

surged up the Williamson, Sprague, and Lost River. At the place on the Sprague River where gmok’am’c 

first instituted the tradition, we still celebrate the Return of c’waam Ceremony.

The six tribes of the Klamaths were bound together by ties of loyalty and Family, they lived along the 

Klamath Marsh, on the banks of Agency Lake, near the mouth of the Lower Williamson River, on Pelican 

Bay, beside the Link River, and in the uplands of the Sprague River Valley. The Modoc’s lands included 

the Lower Lost River, around Clear Lake, and the territory that extended south as far as the mountains 

beyond Goose Lake. The Yahooskin Bands occupied the area east of the Yamsay Mountain, south of 

Lakeview, and north of Fort Rock. Everything we needed was contained within these lands. 

The Nineteenth Century 

In 1826 Peter Skeen Ogden, a fur trapper from the Hudson’s Bay Company, was the first white man to 

leave his footprints on our lands. One hundred and seventy five years later those footprints have 

multiplied into the thousands, each leaving their marks on the lands and the Klamath Tribes. The 

newcomers came first as explorers, then as missionaries, settlers and ranchers. After decades of hostilities 

with the invaders, the Klamath Tribes ceded more than 23 million acres of land in 1864 and we entered 

the reservation era. We did, however, retain rights to hunt, fish and gather in safety on the lands reserved 

for us “in perpetuity” — forever. Treaty 1864 

From the first, Klamath Tribal members demonstrated an eagerness to turn new economic opportunities to 

our advantage. Under the reservation program, cattle ranching was promoted. In the pre-reservation days 

horses were considered an important form of wealth and the ownership of cattle was easily accepted. 

Tribal members took up ranching, and were successful at it. Today the cattle industry still remains an 

important economic asset for many of us. The quest for economic self-sufficiency was pursued 

energetically and with determination by Tribal members. Many, both men and women, took advantage of 

the vocational training offered at the Agency and soon held a wide variety of skilled jobs at the Agency, 

at the Fort Klamath military post, and in the town of Linkville. Due to the widespread trade networks 

established by the Tribes long before the settlers arrived, another economic enterprise that turned out to 

be extremely successful during the reservation period was freighting, in August of 1889, there were 20 

Tribal teams working year-round to supply the private and commercial needs of the rapidly growing 
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county. A Klamath Tribal Agency – sponsored sawmill was completed in 1870 for the purpose of 

constructing the Agency. 

The Twentieth Century 

By 1873, Tribal members were selling lumber to Fort Klamath and many other private parties, and by 

1896 the sale to parties outside of the reservation was estimated at a quarter of a million board feet. With 

the arrival of the railroad in 1911, reservation timber became extremely valuable. The economy of 

Klamath County was sustained by it for decades. By the 1950’s the Klamath Tribes were one of the 

wealthiest Tribes in the United States. We owned and judiciously managed for long term yield, the largest 

remaining stand of Ponderosa pine in the west. We were entirely self-sufficient. We were the only tribes 

in the United States that paid for all the federal, state and private services used by our members. 

In 1954, the Klamath Tribes were terminated from federal recognition as a tribe by an act of congress. 

During the process of termination the elected Tribal representatives consistently opposed termination. 

There was, in addition, a report from the Bureau of Indian Affairs (BIA) which concluded that the 

Klamath Tribes were NOT ready for termination and recommended against it. Despite this consistent 

official opposition from the Tribes and the BIA, congress adopted the Klamath Termination Act (P. L 

587). Not only did we see the end of federal recognition and supplemental human services, but tragically 

our reservation land base of approximately 1.8 million acres was taken by condemnation and the 

Klamaths were terminated as a Tribe. This single act of Congress had devastating effects on the Klamath 

Tribes and several other tribes across the country. 

The Tribes’ Position on Termination

In 1974 the Federal Court ruled that we had retained our Treaty Rights to hunt, fish and gather, and to be 

consulted in land management decisions when those decisions affected our Treaty Rights. 

In 1986, we were successful in regaining Restoration of Federal Recognition for our Tribes. Although our 

land base was not returned to us, we were directed to compose a plan to regain economic self-sufficiency. 

Our Economic Self-sufficiency Plan reflects the Klamath Tribes’ continued commitment to playing a 

pivotal role in the local economy. 

During the Economic Self-sufficiency Plan (ESSP) development process, the Planning Department and 

other committees reviewed hundreds of ideas and concept combinations that would help attain our muchdesired goal of long term economic self-sufficiency. After a lengthy analysis process the recommendation 

was made and accepted by the Tribal Council and the General Council, that the Tribes construct a casino. 

With our usual energy and determination the Tribes efforts became reality.
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Map R-6. Tribal Lands of the Klamath Tribes 
1631 | P a g e

Tribal Listening Sessions 

Overview 

As part of the outreach process for the RMP, the BLM reached out to all nine federally recognized Tribes 

located within or holding interests within the planning area, inviting them to participate in listening 

sessions. These invitations initiated coordination and communication with the Tribes in this RMP 

planning process. Several Tribes also have representatives in the Cooperating Agency Advisory Group 

(CAAG), which has been and will continue to collaborate with the BLM throughout the duration of the 

planning process. In addition to these efforts and formal government-to-government consultation, the 

BLM will continue to be available for meetings throughout the planning process with interested and 

affected Tribes. 

BLM managers and RMP team members conducted listening sessions with five Tribes at local Tribal 

Headquarters (Table R-1). Cogan Owens Cogan facilitated four of the five meetings with assistance from 

DS Consulting; BLM staff facilitated one meeting. Their notes, combined with BLM staff notes, comprise 

the content of this summary. 

Table R-1. Alphabetical listing of Tribal listening sessions* 

Tribe Date

The Confederated Tribes of Grand Ronde Community of Oregon† May 22, 2013

The Confederated Tribes of Siletz Indians†June 7, 2013

The Coquille Indian Tribe† May 14, 2013

The Cow Creek Band of Umpqua Tribe of Indians† December 18, 2013

The Klamath Tribes†July 15, 2013

* The Confederated Tribes of Coos, Lower Umpqua, and Siuslaw Indians, Confederated Tribes of Warm Springs, Karuk Tribe, 

and Quartz Valley Indian Community elected not to have listening sessions. 

† Denotes the Tribal representative serves as a member of the CAAG. In addition to these Tribes, the Confederated Tribes of 

Coos, Lower Umpqua, and Siuslaw Indians also serve on the CAAG. 

These listening sessions initiated efforts to ensure that Tribes were involved early in the RMP process and 

that the BLM understands Tribal interests. The listening sessions—

 Provided Tribal Councils and staff with an update on the planning process and external 

initiatives; 

 Sought input on Tribal issues and concerns and what analytical questions need to be addressed in 

developing Planning Criteria; 

 Identified how Tribes can provide input during future phases of the planning process; and 

 Sought input on the level and mechanisms for participation desired by each Tribe. 

The BLM had not publically released the Purpose and Need at the time the first three listening sessions 

were held. These notes reflect only the listening sessions, and not subsequent discussions that the BLM 

held with the Tribes who expressed interest in follow up discussions on the Purpose and Need. These 

follow up sessions with the Tribes occurred through conversations with Tribal representatives through the 

CAAG.

At each listening session, materials presented included—

 Maps of BLM-administered lands in western Oregon (e.g., planning area and administrative land 

designations) 

 Draft analytical questions developed with input from the CAAG’s Tribal Work Group 

 A fact sheet on the process and timeline 
1632 | P a g e

Listening sessions ranged from 1.5 to 3 hours in length and covered several common discussion items 

(Table R-2).

Table R-2. Listening session agenda and format 

Meeting Agenda Items Participants

Introductions and Background District Manager and Tribal 

Council

Update on Planning Process and Schedule State Office staff

Questions/Discussion Tribal Council and staff

Listening Session

 What are the areas of Tribal interest?

 What are Tribal values and concerns to address in the RMP?

 What are analytical questions that BLM should address?

Facilitator

Summary/Closing District Manager

To help frame the discussion of Planning Criteria for Tribal interests, Heather Ulrich, RMP Tribal 

Liaison, provided a preliminary list of issues and concerns that generally addressed how BLMadministered land management actions would affect the following: 

 Tribal plant collection, management, and use 

 Tribal resource collection of obsidian and other non-biological resources 

 Tribal fishing and hunting resources and practices 

 Tribal access to areas of interest including areas of plant collection, fishing, hunting, sacred sites, 

or places of traditional religious and cultural importance 

 Sacred sites and places of traditional religious and cultural importance 

 Neighboring Tribally managed lands 

Because of these listening sessions, the BLM expanded and refined this initial list to address the diverse 

number topics and resources of interest to Tribes more accurately. The Planning Criteria contains a 

section on Tribal Interests that outlines the refined list of analytical questions as gathered from Tribal 

outreach. 

Tribal Listening Session Highlights

The following section summarizes the participants and highlights of each of the listening sessions. 

Confederated Tribes of Grand Ronde 

May 22, 2013 

Tribal Headquarters, Grand Ronde, Oregon 

Tribal council participants: Toby McClary, Secretary; Jon George, Council Member; June Sherer, 

Council Member; Kathleen Tom, Council Member; Chris Mercier, Council Member 

Tribal staff participants: David Harrelson, Cultural Protection Manager; Eirik Thorsgard, Tribal Historic 

Preservation Officer; Michael Karnosh, Ceded Lands Program Manager; Michael Wilson, Natural 

Resources Director 

BLM attendees: Kim Titus, Salem District Manager; Ginnie Grilley, Eugene District Manager; Heather 

Ulrich, RMP Tribal Liaison; Mark Brown, RMP Project Manager; Trish Hogervorst, Salem District 

Public Affairs Officer 
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Facilitator: Jim Owens, Cogan Owens Cogan 

General comments and highlights of main Tribal interest topics 

 The Grand Ronde has just signed (2013) a Natural Resources Management Plan that they feel 

may serve as a model for other Tribes. Their timber land is managed for sustained yield. In 

writing their Natural Resources Management Plan, the Tribe met with environmental groups to 

educate them on the plan. The Tribe is very proud of the fact that environmental groups had 

previously predicted the Grand Ronde timber would be gone in 20 years; at 30 years, there is still 

plenty of timber on Tribal lands due to good management. 

 The Tribe asked about gated BLM roads. Could tribes get passes through gated areas to access 

cultural sites? Could BLM let the Tribe know the conditions of the roads? Tribal members could 

serve as eyes/ears for the BLM on BLM-administered lands during their Tribal gathering of 

cedar, huckleberries, etc. Tribal access and public access are not the same. The Tribe expressed a 

need for Tribal access to BLM-administered lands for religious reasons. 

 Private companies are harvesting and punching in roads interrupting fish passage and providing 

no maintenance on the roads for many years. The Tribe is concerned about this happening on 

BLM-administered lands. 

 There is a lot of available timber and our communities and counties are in need; consider 

increased timber production based upon sustainable management principles. 

 Can the BLM add language at the plan level that establishes Tribes as partners for cultural 

resource work such as surveys? 

 Develop a partnership for managing plants of interest, including “take” and the preparation for 

harvest and harvest methods. 

 Could the Grand Ronde be included in all Tribal consultations since all lands on the BLM map 

are Ceded lands with treaty rights? 

 The Tribe is contracting with National Park Service (NPS) and National Oceanic and 

Atmospheric Administration (NOAA) to conduct traditional cultural landscape studies on 

indigenous landscapes. Could the BLM hire Tribes to work on this on BLM-administered land? 

 There are concerns regarding management of BLM-administered lands bordering the eastside of 

Grand Ronde lands. 

 Could BLM meet regularly with Tribes on new rules coming down and create a memorandum of 

understanding on annual meeting to discuss mutual issues/projects? The Tribe would like to 

finish Tribal memorandum of understanding as cooperating agency on the planning process. 

 Interested in discussion of Purpose and Need at a future date. 

 The Tribe offered a tour of Grand Ronde lands to see work (i.e., fish passage projects) they are 

doing in natural resources. The Tribe has opened 60+ miles of streams for fish passage. 

Planning considerations 

 Restoration and long-term maintenance of fish passage. Old roads left unmaintained block fish 

passage. 

 Indigenous landscapes and landscape level analysis. 

 Quantifying non-commercial items is not the way to approach it. Cannot compare value of timber 

products versus non-commercial timber products (e.g., items for making baskets and other Tribal 

cultural needs). 

 How BLM manages collection of special forest products to prevent degradation. 

 Tribe would like to provide information to the BLM on restoration efforts (e.g., hazelnut sticks 

for basketry). The Tribe would like to see more lands managed for Tribal cultural resources.
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Confederated Tribes of Siletz Indians 

June 7, 2013 

Tribal Headquarters, Siletz, Oregon 

Tribal Council participants: Delores Pigsley, Chairman; Lillie Butler, Council Member; Loraine Butler, 

Council Member; Reggie Butler, Sr. , Council Member; Robert Kentta, Council Member 

Tribal staff participants: Mike Kennedy, Natural Resources Manager 

BLM attendees: Kim Titus, Salem District Manager; Ginnie Grilley, Eugene District Manager; Mark 

Brown, RMP Project Manager; Heather Ulrich RMP Tribal Liaison; Richard Hatfield, Mary’s Peak 

Resource Area Field Manager 

Facilitator: Jim Owens, Cogan Owens Cogan 

General comments and highlights of main Tribal interest topics 

 How does the RMP fit into the Wyden Plan? 

 The Tribe expressed concern for air, water, and climate change. 

 The Tribe expressed concern for timber receipts and Secure Rural Schools. 

 The Tribe stated it would like a memorandum of understanding for collecting basketry materials. 

 Tribe has past and ongoing interest in public domain lands in Lincoln County. 

 Look into Tribes’ “right of first refusal” for excess Federal lands within original reservation 

boundaries that are designated for disposal. 

o Can Tribes provide input to what lands the BLM can put in Land Tenure Zone 3 (suitable for 

disposal)? 

 First level of interest in BLM-administered lands are those within the original reservation 

boundary. Some interests include: 

o Hazel management 

o Hunting access 

o Spruce root collection 

 The Tribe expressed concern regarding destruction and looting of archaeological sites and 

artifacts as well as public use impacts in certain key areas of interest to the Tribe within the 

planning area. 

 Concern regarding BLM ability to coordinate consultation with other/all Tribes concerned. 

 Plant collection: Where resources are on BLM-administered land, can the Tribe help manage 

them, increase them, and collect them? Specific collection interests include: 

o Beargrass collection 

o Ferns and peeled chittum 

o Sugar pine and ancient oaks; digger pine in Applegate and Rogue valleys 

o Willamette Valley oak savannah, angelica (Lomatium species), scrub oak, and rocky outcrops 

o Acorns and pileated woodpeckers for feathers; want to ensure that the Tribe can obtain forage 

permits for these resources 

 The Tribe identified a need for improved coordination on memoranda of understanding with other 

Tribes when Tribal territory is impacted. 

Planning considerations 

 Protection of historic trail systems. 

 Preserve some type of visible boundary between the historic reservation lands and BLMadministered lands (e.g., leave large trees). 

 Management of public domain lands in Lincoln County by the Tribes. 

 Management for traditionally collected plants (e.g., beargrass, hazel nuts, angelica) on all BLMadministered lands; stand diversity that encourages spruce, other species important for collection; 
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adverse effects of overly dense timber stands on sugar pine, ancient oaks. Management should 

include heavy thinning or clearcuts to reopen areas for beargrass collection. 

 Identification/interpretation of battle sites. 

 Management for marbled murrelet. 

 Protection of cemetery sites and other archaeological sites and artifacts impacted by inadvertent 

public use or intentional damage and looting. 
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Coquille Indian Tribe 

May 14, 2013 

Tribal Headquarters, North Bend, Oregon 

Tribal participants: Brenda Meade, Chair; Toni Ann Brend, Vice-Chair; Ken Tanner, Chief; George 

Smith, Executive Director; Joan Metcalf, Secretary/Treasurer; Sharon Parrish, Representative; Kippy 

Robbins, Representative; Jason Robison, Natural Resources Director 

BLM attendees: Mark Johnson, Coos Bay District Manager; Ralph Thomas, Coos Bay Associate District 

Manager; Heather Ulrich, RMP Tribal Liaison; Mark Brown, RMP Project Manager; Megan Harper, 

Coos Bay District Public Affairs Officer 

Facilitator: Jim Owens, Cogan Owens Cogan 

General comments and highlights of main Tribal interest topics 

 The Coquille Indian Tribe regained Tribal status in 1989. A 1950’s Court of Claims case 

provided exclusive ancestral territory on BLM-administered lands within the Coos Bay District. 

Other geographic areas outside of this exclusive ancestral territory are of shared interest with 

other Tribes. The Coquille Forest Act of 1996 put 5,400 acres of BLM-administered lands into 

trust for the Tribe to manage. They have a huge stake in BLM plan revisions because of statutory 

direction that requires the Coquille Forest to be managed per the standards and guidelines of 

Federal forest plans “on adjacent or nearby Federal lands.”

 The Tribe expressed concern regarding the economic health of the communities that the Coquille 

and other Tribes work in, and how Tribes influence and contribute to the communities they live 

and work in (e.g., Coquille is the second largest employer in Coos County). 

 Tribal approach is to maintain healthy communities that rely upon timber harvest but still only 

take what is needed and managing for the needs of the earth rather than the needs of humans. 

Living in balance; sustainability from a cultural perspective. 

 In regards to the Tribal Cooperative Management Area (TCMA), consider Adaptive Management 

Area framework with site-specific management prescriptions and intensive monitoring. 

 Tribe desires greater direct involvement in management of Coos Bay Wagon Road lands. Tribe 

has proposed a cooperative management agreement with Coos County; developing a concept 

paper to share with the Congressional delegation. 

 Tribe wants to ensure an ongoing relationship with the BLM beyond this planning process. 

 Interested in discussion of Purpose and Need at a future date. 

Planning considerations 

 Economic values that lead to a sustainable and economically healthy Tribal community. 

 Approach for and addressing management of the Coos Bay Wagon Road and cooperative 

management. 

 Consideration of TCMA in all alternatives based upon Direction from the Secretary of the 

Interior. 

 Concerns regarding climate change and impacts on Tribal resources and natural resources. 

 Adjacency issues in the context of the Tribe’s exclusive ancestral territory.

 Management of natural/cultural resources within riparian areas. 

 The Tribe wants to ensure that the planning effort considers provisions of existing agreements 

with the BLM (e.g., memoranda of understanding and memoranda of agreement). If proposed 

planning considerations are in opposition to, or not fully consistent with agreement provisions, 

further discussions with the Tribe should occur prior to moving forward with such considerations.
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Cow Creek Band of Umpqua Tribe of Indians 

December 18, 2013 

Tribal Headquarters, Roseburg, Oregon 

Tribal participants: Robert Van Norman, Treasurer; Lonnie Rainville, Operations Officer; Tim 

Vredenburg, Director of Forest Management; Amy Amoroso, Director of Natural Resources; Jessie 

Plueard, Archaeologist; Rhonda Malone, Cultural Development Coordinator; Kelly Coates, Fisheries 

Biologist; Heather Bartlett, Environmental Specialist; Scott Van Norman, Wildlife Technician 

BLM attendees: Mark Brown, RMP Project Manager; Abbie Jossie, Roseburg District Manager; Heather 

Ulrich, RMP Tribal Liaison; Molly Casperson, Roseburg District Archaeologist 

Facilitator: Cheyne Rossbach, Roseburg District Public Affairs Officer 

General comments and highlights of main Tribal interest topics 

 Purpose and Need Statement seems too broad and that it will be challenging to develop 

alternatives.

 The Tribe is very aware of the politics surrounding the BLM, specifically proposed legislation 

directed toward BLM-administered lands. Specifically, Congressman DeFazio’s O&C Trust, 

Conservation, and Jobs Act and Senator Wyden’s O&C Act of 2013 and Canyon Mountain Land 

Conveyance Act of 2013.

 There was interest in knowing how the RMP planning process was taking into consideration 

proposed legislation.

 Interest in clarification of the differences between the RMP Purpose and Need statement, current 

practices, and what is in the Northwest Forest Plan.

 There was interest in the definition of “old growth.”

 The public perception of old growth as natural is not true. The character of historic forests was a 

direct result of Tribal management. Recognize historic human involvement in “old growth” 

development in the new definition of old growth – that past humans “created” what is old growth 

today. The idea that pristine or untouched are characteristic of old growth is incorrect.

 How will the BLM balance the needs of the county, who says they need a set amount of money, 

versus the other needs (e.g., northern spotted owl recovery)? Do the perceived needs of the 

counties direct the plan?

 The way the BLM draws lines around resources conflicts with how the Tribe would delineate 

resources and, at times, the BLM and Tribe are not even looking at the same kinds of resources. 

Tribal staffs at the table do not adhere to the silo approach of isolated old growth stands or owls. 

One example where Tribal values and BLM values are in conflict is that old growth is not fire 

resilient like it was 100 years ago because the Tribe is not managing them the way they did 

traditionally (i.e., annual fire cycles).

 It is problematic that the structural complexity of forests related to fires cannot be mapped. The 

forests are not as they should be because management is not as it was historically (Tribal 

management). Another example of the incongruous nature of Federal and Tribal land 

management strategies is diminishing meadows that are important foraging locales for game. 

Definitions and alternatives should be adaptive enough to protect Tribal resources.

 Early seral habitat is important for foraging and hunting, which has little to do with meeting 

timber targets. The Tribe needs to be able to hunt and regular fire cycles are important to create 

habitat.

 The Tribe expressed interest in the differences in the proposed riparian buffer zones. Two 

important issues to the Tribe are clean water and fish.

 There have been Tribal efforts working on lamprey conservation and the Tribe encouraged the 

BLM to raise the bar on conservation efforts as well. Conservation methods for lamprey are also 

good for salmon.
1638 | P a g e

 Water issues include more than quality. There are more streams than in the past, with less water 

in tributaries. Changes like these create systems that are more compatible for invasive or exotic 

species, which directly harm lamprey. Management of upland systems directly affects lamprey. 

The BLM riparian zones may not align with Tribal values. An example of this from the BLM’s 

pilot project includes finding beargrass in no-touch riparian zones. The presence of beargrass in 

these zones suggests it was open at one time, so a no-touch area conflicts with the way the Tribe 

would manage the beargrass. 

 Think of Tribal concerns when you consult with the National Marines Fisheries Service (NMFS) 

or whoever. Your decisions affect how the Tribe can consult for the next year, which ultimately 

affects how the Tribe can manage its own lands. Think of the Federal government’s trust 

responsibility to the Tribe.

 Recreation is important in the new RMP, but off-highway vehicle (OHV) recreation creates issues 

for the Tribe’s cultural sites. As this plan develops, the public will put pressure on the BLM to 

open OHV areas that will directly affect cultural sites.

 This area is the ancestral territory of the Tribe. We have been here for thousands of years and 

intend to stay.

 Beyond archaeological sites, recognize that the Tribe has spiritual sites that have visual and 

auditory sensitivity. Address this with future Visual Resource Inventory efforts.

Planning considerations 

 How would land management actions affect resident deer and elk populations? 

 Interest in BLM’s approach to water, fish, and lamprey conservation.

 Concerns for effects to archaeological and other cultural resources. 

 Consider Tribal views of management and resources, which are typically different from BLM 

perspectives. Tribal perspectives are particularly important in respect to land management, fire, 

water, and riparian area management. 
1639 | P a g e

Klamath Tribes 

July 15, 2013 

Tribal Government Office, Chiloquin, Oregon 

Tribal participants: Perry Chocktoot, Jr., Director of Culture and Heritage; Kathleen Mitchell, General 

Manager 

BLM attendees: Mark Brown, RMP Project Manager; Heather Ulrich, RMP Tribal Liaison; Donald 

Holmstrom, Klamath Falls Field Manager; Brooke Brown, Klamath Falls Resource Area Archaeologist 

Facilitator: Robin Gumpert, DS Consulting 

General comments and highlights of main Tribal interest topics 

 The Tribe’s interest area begins at the top of the Cascade Range.

 The Tribe expressed concern about splitting the Lakeview District into separate RMPs, requiring 

the Tribe to consult with two offices on two different plans. All of the Lakeview District is part of 

the Klamath Tribes’ aboriginal territory.

 Will the RMP result in more or less timber harvested? 

 Grazing allotments affect cultural resources, mostly near fences and water sources and rock 

features. Desire 100 percent survey on all allotments so that the BLM can say for sure what the 

impacts are to sites. 

 Concern over archaeological contracting firms surveying on BLM-administered lands when they 

have no experience in the area and may not have the background to identify and subsequently 

document sites. 

 Desire for the BLM to listen to what the Tribes have to say at all levels of management and 

engage in meaningful consultation. The Tribe and the BLM need to be allies on projects, and this 

occurs with meaningful consultation. 

 The Tribe identified concern that the Purpose and Need includes no Section 106 responsibilities. 

 Meaningful consultation as part of the planning process needs to be captured in the Purpose and 

Need. Tribes are interested in what is going on elsewhere, even if not on their aboriginal lands. 

 Trees have importance to the Tribe, particularly culturally modified tress (cambium peeled trees 

and bow stave trees). Section 106 needs to protect these important areas of cultural interest. 

Spiritual integrity is first and foremost of importance to the Tribe. Tribal Resolution 92-047 states 

that all sites are sacred. 

 Clean water in the Klamath watershed is of great concern. 

 The Tribe has 22 million acres of aboriginal lands, and they are concerned about grazing, timber 

harvest activities, and protecting their sacred sites. The Tribes would like to see preservation of 

their sacred sites. 

 It is frustrating when Tribes feel like they are sharing information and not heard. 

 BLM has come a long way on meaningful consultation, and needs to do this on all projects. Face 

time (face-to-face meetings) means a lot to the Tribe. 

 All of the BLM-administered lands in Klamath County are of interest to the Tribe. There are 

numerous and diverse archaeological, cultural, and spiritual locations within the BLMadministered lands that are of great importance and interest to the Tribe. 

 Primary impacts to Tribal interests are grazing, timber, OHV, and low water exposing sites. 

 The BLM needs to recognize federal trust responsibilities and talk to the Tribe about closures to 

areas affecting sites. The Tribe expressed a need for a memorandum of understanding for 

government-to-government consultation. 

Planning considerations 
1640 | P a g e

 Grazing allotments that affect cultural resources, mostly near fences and water sources, and rock 

features. 

 Protection of culturally modified trees (cambium peeled trees and bow stave trees). 

 Primary impacts to Tribal interests are grazing, timber, public motorized vehicle use, water levels 

in reservoirs. 

Tribal Listening Session Summary 

These five listening sessions provided BLM managers and RMP staff with a greater understanding of 

Tribal histories and their interests in the lands and resources that the BLM manages. As part of the RMP, 

these topics of interest are included as analytical questions in the Planning Criteria and the effects 

analyzed by alternative and the Proposed RMP in Chapter 3. The analysis will inform decision makers on 

how land management actions affect those resources of concern to the Tribes. 

Some of the recurring themes identified during these listening sessions included: 

 Hunting, fishing and plant gathering access 

 Plant collection, management and use 

 Multiple Tribes with interests (sometimes competing) on the same BLM-administered lands; 

 Fish and lamprey 

 Archaeological sites and impacts due to land management actions as well as public use and 

vandalism 

 Cooperative opportunities 

 Climate change 

 Air and water quality 

 Balancing healthy forests and the need for economic stability for the counties and Tribes 

 Land acquisition into Tribal ownership or Tribal management 

 Indigenous landscape studies 

 Management of BLM-administered lands adjacent to Tribal land 

 Land management activities that benefit multiple resources of cultural value 

 Memoranda of understanding 

 Impacts from recreation and public motorized vehicle use to cultural sites 

 Effects of proposed legislation on the planning process 

Detailed notes captured during these sessions will aid managers as they continue managing the lands that 

hold importance to the Tribes. The BLM collected valuable information from these listening sessions that 

will inform land managers beyond the scope of this RMP in carrying out the BLM mission. 
1641 | P a g e

Cultural Plants 

The following are two lists that provide summaries of plants with cultural importance and use to Tribes. 

These plant lists are not exhaustive and include the more commonly known and used plants. Table R-3 is 

compiled from source materials provided by the Klamath Tribes (Klamath Tribes 2007, Oregon Native 

Plant Society 1993, “Common Plant List” n.d., Casey et al. 2010, Anderson et al. 2012). This table 

focuses on plants found in habitats more commonly associated with the Eastside Management Area. 

Table R-4 is compiled from source materials provided by the Coquille Tribe (Fluharty et al. 2010), as 

well as from conversations and consultation meetings with the other Tribes the BLM has been consulting 

(David Harrelson, Confederated Tribes of the Grand Ronde, personal communication, September 19, 

2011; Confederated Tribes of Grand Ronde Tribal Council and staff, May 22, 2013; Robert Kentta, 

Confederated Tribes of Siletz Indians, personal communication, June 7, 2013; Confederated Tribes of 

Siletz Indians Tribal Council and staff, personal communication, June 22, 2105). This table is includes 

plants found in habitats more commonly associated with the moist forest lands in western Oregon. These 

plant lists supplement the discussion in the Tribal Interests section of Chapter 3 (Issue 2), as well as 

provide readers, managers, and others implementing this RMP a base understanding of the variety of 

plants Tribes consider having cultural importance. 

Table R-3. Plants of cultural significance to the Klamath Tribes 

Species Common Name Habitats Known Uses

Achillea millefolium Yarrow

Disturbed sites at all elevations, dry to

moist meadows

Medicinal

Allium acuminatum Wild Onion Various, often dry hillsides, open areas, 

foothills

Edible, household, 

medicinal

Allium tolmiei Wild Onion Moist ground throughout area Medicinal

Allium validum Swamp Onion Meadows, wetlands Edible, medicinal

Alnus crispa Mountain Alder Moist forests, and along streams and 

bogs

Edible, household, 

medicinal, tools

Alnus incana Alder

Streamsides, margins of wetlands and 

lakes

Medicinal, 

household

Amaranthus graecizans Amaranth, Pigweed Weedy, dry/wet areas Edible, household

Amelanchier alnifolia Serviceberry

Dry ground, in clearings, along streams 

and lakes

Edible, medicinal, 

tools 

Angelica lucida,

Apium graveolens Wild Celery Moist semi-shaded soils Edible, medicinal

Apocynum cannibinum Indian Hemp Permanently wet areas, springs or river 

banks

Edible, household, 

medicinal

Apocynum 

adrosaemifolium

Dogbane Roadsides, open forest, dry rocky areas Cordage, thread

Arctostaphylos patula Greenleaf Manzanita Roadsides, open slopes, burned areas Edible, medicinal

Arctostaphylos uva-ursi Bearberry

Moist lodgepole basins and meadow 

edges in pumice soils

Edible

Artemesia cana White Sagebrush

Floodplains, washes, streambanks, sandy

soils

Medicinal

Artemesia tridentata Big Sagebrush

Dry gravely or rocky soils, plains, high 

deserts, lower mountain slopes

Edible, ceremonial, 

household, 

medicinal

Basamorhiza sagittata Arrowleaf 

Balsamroot

Shrublands, juniper/pine woodlands, 

rocky slopes, forest openings

Edible, medicinal

Berberis aquifolia Oregon Grape

Juniper/pine woodlands, rocky slopes, 

mixed conifer forest

Edible, household, 

medicinal

Brodiaea coronaria,

Dichelostem macongesta,

Tritelia hyacinthina

Brodiaea Pine woodlands, meadows, scablands, 

and other shrublands

Edible
1642 | P a g e

Species Common Name Habitats Known Uses

Bryoria spp.

Black Tree Lichen, 

Horsehair Lichen

Grows on coniferous trees, generally 

above the snow line

Edible

Ca1ocedrus decurrens Incense Cedar

Variety of soils, usually on western 

slopes at mid to high elevations; deep 

well-drained slightly acidic sandy loam 

soils

Crafts, edible, 

household, 

medicinal

Calochortus macrocarpus Mariposa Lily Sagebrush community, slopes, flats Edible, medicinal

Camassia quamash Camas Root

Meadows, stream-sides, moist to wet in

spring, moist forested valleys Ceremonial, edible 

Carex scopulorum Sedge Wet areas: streams, lakes, marsh areas Ceremonial, 

edible, household

Ceanothus prostratus Squaw Carpet Dry forest floors Household

Cercocarpus betuloides

Birch Leaf Mountain 

Mahogany

Juniper/pine woodlands, rocky slopes Tools

Cercocarpus ledifolius

Curl Leaf Mountain 

Mahogany

Juniper/pine woodlands, rocky slopes, 

edges of scablands

Medicinal, 

household, tools

Chenopodium fremontii Lamb’s Quarters 

(Gooseroot) Weedy, disturbed areas Edible, household

Chimaphila umbellatum Prince’s Pine Mixed conifer/sub-alpine forest Edible, medicinal

Cimicifuga racemosa Black Cohosh Woodland garden, dappled shade, shady 

edge Edible, medicinal

Claytonia perfoliata Miner’s Lettuce

Disturbed and waste ground, moist banks 

and slopes, partial shade, light soils and 

dry sandy soils

Edible, medicinal

Cornus stonolonifera Red Osier Dogwood Riparian zone Edible, household

Discina perlata Elephant Ear Fungus 

(Pig’s Ear)

Saprobic snowbank fungus found under 

conifers in the spring

Edible

Equisetum arvense Marestail (Horsetail) Road ditches, riparian areas, pond/lake 

margins

Edible, medicinal

Erythronium grandiflorum Avalanche Lily Sagebrush slopes Edible, medicinal

Elymus cinereus,

E. canadensis Giant Wild Rye Dry sandy gravelly or rocky soil Edible, household

Foenicultum vulgare Fennel Well drained soils

Ceremonial, 

edible, household, 

medicinal

Fragaria virginiana Wild Strawberry

Disturbed sites all elevations, lodgepole, 

ponderosa, or mixed conifer forest, 

riparian areas

Edible, medicinal

Fritillaria pudica Yellow Bell Rocky, lithic soils Edible

Heracleum lanatum Cow Parsnip Wet places Edible, medicinal

Juniperus occidentalis Western Juniper Well-drained soils Edible, household, 

medicinal

Lewisia rediviva Bitteroot Low sagebrush scablands, lithic, thin 

rocky soils Edible, ceremonial

Lilium washingtonianum Mountain Lily

Ponderosa pine/mixed conifer, especially 

canopy gaps, and burned clearcuts

Edible

Lomatium californicum

Wild Celery Root

and Leaves

Juniper/pine woodlands, rocky slopes Edible

Lomatium canbyi Canby’s biscuitroot Open, rocky places at low elevations, 

often with sagebrush Edible

Lomatium cous Biscuitroot Dry, often open rocky slopes and flats, 

often with sagebrush Edible

Lomatium dissectum Fernleaf biscuitroot Open, rocky slopes and dry meadows, 

talus

Ceremonial, 

edible, medicinal
1643 | P a g e

Species Common Name Habitats Known Uses

Lomatium macrocarpum,

L. martindalei Wild Carrot

Scablands. Mid to high elevation 

openings, mixed conifer

Ceremonial, 

edible, medicinal

Lomatium nudicaule Pestle parsnip Dry open or lightly wooded areas at low 

to moderate elevations

Edible, household, 

medicinal

Lomatium triternatum

Wild Carrot, Nineleaved Biscuitroot

Juniper/pine woodlands, scablands, 

widespread; open slopes and meadow in 

dry to fairly moist soil at low to 

moderate elevations

Ceremonial, 

edible, medicinal

Lomatium utriculatum Common Lomatium Prairies and other open rocky places 

west of the Cascades Edible, medicinal

Lonicera involucrata Twinberry Moist soil, banks of streams, open 

coniferous forests

Edible, household, 

medicinal

Mentha arvensis Wild Mint Moist sites, often disturbed Edible, medicinal 

Mentzelia laevicaulis Blazing Star Dry, sandy open places Edible

Nicotiana attenuata Coyote Tobacco

Shrublands, juniper/pine woodlands, 

roadsides

Ceremonial

Nuphar lutea ssp. 

polysepala Wocus Lily Ponds, lakes, ditches, open water in marsh

Edible, medicinal

Oryzopsis hymenoides Indian Rice Grass Dry, sandy soil Edible

Osmorhiza occidentalis Western SweetCicely

Semi-shade (light woodland) or no 

shade; requires moist soil

Edible, household, 

medicinal 

Perideridia gairdneri Ipos Scab-rock flats Edible

Philadelphus lewisii Mock Orange

Gullies, water courses, rocky cliffs, talus 

slopes and rocky hillsides of sagebrush 

deserts

Edible, household, 

medicinal, tools

Phragmites communis Arrow Cane Riparian, lake edge Edible, tools

Phragmites austrailis Common Reed

(Arrow Reed) Wetlands, ditches (Highway 97) Crafts, tools

Pinus contorta var.

latifolia Lodgepole Pine Variety of soils, well drained Household

Pinus ponderosa Ponderosa Pine Dry forests, lower slopes Crafts, household

Pinus lambertiana Sugar Pine Forests at moderate altitudes Crafts, edible

Populus tremuloides Aspen Riparian, meadow edges

Household, 

medicinal

Prunus emarginata Bitter Cherry moist slopes and along stream banks Edible, medicinal

Prunus subcordata Wild Plum Juniper/pine woodlands, rocky slopes Edible

Prunus virginiana Chokecherry

Moist, open slopes, streambanks, moist 

areas below rocky outcrops

Ceremonial, 

edible, medicinal

Ribes aureum Golden Currant

In mountains, lower elev. moist sites. In 

desert, along springs, gullies, near water 

sources

Edible

Ribes cereum Wax Currant

Widespread, found in openings in most

habitats

Edible, medicinal, 

tools

Ribes lacustre

Swamp Berries 

(Prickly Currant, 

Black gooseberry)

Riparian areas, springs Edible, medicinal

Rosa gymnocarpa,

R. woodsii Wild Rose/Rose hips

Juniper/pine woodlands, rocky slopes, 

mixed conifer forest, riparian areas

Crafts, edible, 

medicinal, tools

Rosa nutkana Wild Rose/Rose hips Sunny roadside, woodsides, hedges Crafts, edible, 

medicinal, tools

Rubus leucodermis,

R. ursinus Blackberry Disturbed mixed conifer, riparian areas Edible, medicinal

Rubus parviflorus Thimbleberry Riparian zone, forest openings Edible, household, 

medicinal
1644 | P a g e

Species Common Name Habitats Known Uses

Sagittaria cunneata Wild Potato Wetlands, shallow water Edible

Salix lemmonii,

S. geyeriana,

S. exigua,

S. lasiandra,

Salix ssp.

Willow, Pacific 

Willow

Wetlands, riparian areas, ditches, 

lake/pond margins

Edible, household, 

medicinal

Salix scouleri Willow

Disturbed uplands, riparian areas, 

roadsides

Edible, household, 

medicinal

Sambucus nigra ssp. 

caerulea Elderberry

Juniper/pine woodlands, rocky slopes, 

riparian areas; wet areas next to rocks

and walls

Crafts, edible, 

household, 

medicinal

Sambucus pubens American Red Elder Moist to wet soils along streams, in 

woods and open areas

Ceremonial, 

edible, household, 

medicinal

Sassafras albidum Sassafras Moist, well-drained soil Edible, household, 

medicinal

Scirpus acutus Tule Marshes, ditches

Crafts, edible, 

medicinal

Symplocarpus foetidus Skunk Cabbage Marshes, bogs, swampy woods and by 

streams

Cosmetic, edible, 

medicinal

Thelycrania stolonifera Red Willow Semi-shade (light woodland) or no 

shade; requires moist or wet soil

Edible, household, 

medicinal

Trifolium macrocephalum Big Head Clover Dry, rocky soils, among sagebrush, pine Edible

Typha latifolia Cattail Marshes, ditches, lake margins

Edible, household, 

medicinal

Urtica dioica Stinging Nettle Ditches, canals, lake margins, burn piles

Edible, household, 

medicinal

Vaccinium 

membranaceum

Huckleberry

Moist mixed conifer and riparian areas, 

clearings Edible, medicinal

Vaccinium uliginosum Blueberry

Wet meadows, lake margins, lodgepole 

pine swamps

Edible, household

Valeriana sitchensis,

V. edulis Valerian Moist forest; along small streams, springs and seeps, wet/dry meadows Edible, medicinal

Verbascum densiflorum Mullein Waste places, railway embankments and 

similar dry sunny localities Medicinal

Wyethia mollis Mule’s Ears

Shrublands, juniper/pine woodlands, 

rocky slopes, forest openings, dry/wet 

meadows

Edible, medicinal

Xerophyllum tenax Bear grass High open spaces, woodland, sunny 

edge, dappled shade

Crafts, edible, 

household, 

medicinal

Note: ‘Common Plant List’ provided by the Klamath Tribes, Cultural Department, November 4, 2015. 

Table R-4. Common cultural plants of importance to tribes in western Oregon 

Species Common Name Habitats Known Uses

Acer circinatum Vine Maple Moist soils along riparian zones and 

stream banks, shade tolerant Tools

Acer macrophyllum Big-Leaf Maple 

(Oregon Maple)

Rich coarse gravelly soils along coastal 

stream and river banks Clothing, crafts

Achillea millefolium Yarrow (Milfoil) Disturbed soils in well drained 

grasslands and open forest floors Medicinal

Achlys triphylla Vanilla Leaf Moist deep, shaded forest floors, north 

slope openings and road cuts

Aromatics, edible 

flavoring, 
1645 | P a g e

Species Common Name Habitats Known Uses

medicinal

Adiantum aleuticum,

A. pedatum

Maidenhair Fern 

(Five-finger Fern)

Wet seeps, sandy and gravelly stream 

banks, waterfall edges in shady forest 

riparian areas

Crafts (basketry), 

hygiene, 

medicinal

Alnus rubra Red Alder (Coast, 

Western Alder) Widespread, prefers moist shaded areas Dye, medicinal

Amelanchier alnifolia

Service Berry (June 

Berry, Shadbush, 

Saskatoon)

Open to lightly shaded coniferous forest 

edges

Edible, medicinal, 

tools, ropes

Anaphalis margaritacea Pearly Everlasting Open disturbed areas, full sun Medicinal, 

smoking

Angelica lucida

Angelica (Sea 

Watch, Wild 

Celery)

Moist semi-shaded soils, salt tolerant 

usually near the ocean Edible, medicinal

Apocynum 

adrosaemifolium Dogbane Roadsides, open forest, dry rocky areas Tools (cordage, thread)

Arbutus menziesii Madrone Well drained, poor soils with low 

moisture and nutrient content

Edible, medicinal, 

crafts (beads)

Arctostaphylos 

columbiana Hairy Manzanita Rocky open slopes at low elevation and sunny edges of forests Medicinal

Arctostaphylos uva-ursi Kinnikinnick (Bearberry, Uva-ursi)

Ocean beaches to ridge tops, coarse 

sandy soils in partial to light shade

Medicinal, 

smoking

Asarum caudatum Ginger (Wild 

Ginger) Moist, shady forests and stream banks Edible, medicinal, tools

Athyrium filix-femina Lady Fern Prefers shady stream banks, seeps and 

wet forest floors Edible, medicinal

Baccharis pilularis

Coyote Brush 

(Chaparral Broom, 

Kidneywort)

Open dry sites, sea cliffs, bluffs and 

thickets along the coast Edible, medicinal

Calandrina cilata Red Maid (Wild 

Portulaca, Purslane) Grasslands, disturbed sites, pastures Edible, medicinal

Calochortus tolmiei Mariposa Lily 

(Cat’s Ear)

Open coniferous forests and rocky 

meadows Edible

Camassia leichtlinii

C. qualmash Camas Vernally wet meadows that dry by summer

Edible

Carex obnupta

Slough Sedge 

(Slough Grass, Tall 

Basket Grass)

Prefers freshwater shallows, muddy 

meadows, marshes, stream banks Crafts (basketry)

Chamaecyparis 

lawsoniana

Port-Orford-Cedar 

(Lawson’s Cypress) Coastal mixed evergreen forests Clothing, shelter, tools

Claytonia perfoliata Minor’s Lettuce Shaded, moist areas at low to medium 

elevations Edible

Cornus nuttallii Pacific Dogwood Well-drained soils in partial shade Dye, tools

Cornus stolonifera

C. sericea

Red Osier Dogwood 

(Red Willow)

Semi-shaded and open wet areas along 

forested stream and river banks

Edible, medicinal, 

crafts (basketry)

Corylus cornuta Hazel (Hazelnut, 

Beaked Filbert) Open forests, shrublands, moist areas

Clothing, crafts 

(basketry) , edible, 

tools (traps)

Daucus carota

D. pusilius

Wild Carrot (Queen 

Anne’s Lace) Sunny open grasslands and roadsides Edible, medicinal

Delphinium nuttallianum

Larkspur (Twolobed Delphinium, 

Up-land Larkspur)

Open, dry grasslands Insecticide

Dentaria tenella Spring Beauty Open, lightly shaded, moist forested Edible
1646 | P a g e

Species Common Name Habitats Known Uses

foothills

Dicentra formosa Bleeding Heart Moist, shady forests, lowlands to midmontane Medicinal

Epilobium angustifolium Fireweed (Elk 

Bush)

Open, well drained soils in grasslands or 

shrubby edges with full sun often seen 

along road banks

Clothing, 

medicinal, tools

Epilobium glaberrimum Willow-herb Open disturbed areas, post burn areas Medicinal

Equisetum hyemale

E. arvense

Horsetail (Scouring 

Rush, Snake Grass) Open wet to moist places Edible, medicinal, tools

Fragaria chiloensis

F. vesca

Strawberry (Beach, 

Woodland 

Strawberry

Meadows, stream banks, open woods, 

shrublands Edible, medicinal

Fraxinus latifolia Oregon Ash Wet, lowland areas, semi-shade tolerant Tools

Galium asparine

G. triflorum

Bed Straw (Cleavers, 

Goosegrass) Widespread, prefers moist shaded areas Dye, medicinal, tools

Gaultheria shallon Salal Low to mid elevation moist forest edges, 

shrublands, prefers partial shade Edible, medicinal

Goodyera oblongifolia Rattlesnake Plantain

Coniferous forests with decomposing 

leaf litter, non-disturbed sites such as 

old-growth stands

Medicinal

Heracleum lanatum Cow Parsnip (Wild 

Parsnip)

Moist, open to partially shaded areas of 

forest understory, roadsides and meadows Edible

Holodiscus discolor Oceanspray (Arrowwood, Iron-wood) Moist open forest Medicinal, tools

Hypericum anagalloides Bog-Wort (St. 

John’s Bogwort)

Fresh water marshes, pond edges, wet 

areas

Medicinal

Iris tenax

I. douglasiana

Iris (Douglas Iris, 

Oregon Iris)

Open areas, forest edges, roadsides, 

stream banks, grassy margins

Crafts (basketry),

edible, medicinal, 

tools

Juncus effuses Tussock (Common 

Rush/Wire Grass) Moist open grasslands to wet marshes Basketry, hats

Ledum groenlandicum

L. palustre spp.

groenlandicum

Labrador Tea (Bog 

Tea, Ledum)

Poorly drained acidic soils under semishade to open sites under high forest 

canopies

Edible, medicinal, 

smoking

Letharia vulpine

L. columbiana

Wolf Moss (Wolf 

Lichen)

Sunny, dry coniferous forests on 

undisturbed twigs and branches, shade 

tolerant

Dye, medicinal

Lilium columbianum Tiger Lily (Oregon, 

Columbia Lily)

Meadows, thickets, open forest and 

clearings Edible

Lithocarpus densiflorus Tan Oak (Tanbark 

Oak)

Shade tolerant, minor component of the 

Pacific NW mixed evergreen forests Edible

Lomatium triternatum Coastal Biscuit 

Root Mid-mountain open slopes and meadows Edible, medicinal

Lysichitum americanum Skunk Cabbage Acidic wet soils associate with open 

coniferous forests, marshes, stream banks

Edible, medicinal, 

tools

Madia sativa Tarweed (Coast 

Tarweed) Grasslands and disturbed areas Edible

Mahonia (Berberis) 

nervosa

Mahonia (Berberis)

aquifolium

Oregon Grape Moist conifer forests to oak savannas Edible, medicinal, 

dyes

Maianthemum dilatatum May Lily (False 

Lily of the Valley) Any shady, moist habitats, stream banks Edible, medicinal

Menziesia ferruginea False Azalea Moist slopes in shady, open shrub land Edible, tools
1647 | P a g e

Species Common Name Habitats Known Uses

and coniferous forest edges

Myrica californica

Wax Myrtle 

(California 

Bayberry)

Prefers full sun, wet peaty soils, but 

hardy Medicinal

Nuphar polysepalum

Yellow Pond Lily 

(Spatterdock, Cow 

Lily)

Sandy soils, submerged in 1–3 feet of 

still water, prefers full sun Edible

Oxalis oregano Redwood Sorrel Moist forested sites low to mid elevation Edible

Phyllospadix torreyi

P. scouleri

Surf Grass (Sea 

Grass)

Tide pools, coastal surf zones below low 

tide level Crafts (basketry)

Physocarpus capitatus Ninebark (Pacific 

Ninebark)

Prefers shade, tolerates full sun in moist 

areas, low elevation forests, stream and 

river banks, marshes

Medicinal

Picea sitchensis Sitka Spruce Wet meadows, stream banks, open 

woods, shrublands

Crafts (basketry), 

tools

Pinus contorta Shore Pine (Beach 

Pine, Lodgepole)

Low to mid-elevation areas, wet, bogs, 

prefers full sun

Ceremonial, 

medicinal, tools

Pinus lambertiana Sugar Pine Conifer hardwood forests Edible, tools

Pinus sabiniana Digger Pine (Bull or 

Gray Pine) Dry foothill woodlands Crafts (basketry), edible, medicinal

Polypodium glycyrrhiza Licorice Fern Tree trunks in shady forests, mossy logs, 

woody debris Edible, medicinal

Polystichum munitum Sword Fern Understory forested slopes, shady to 

semi-open

Edible, medicinal, 

cooking

Populus balsamifera

P. trichocarpa

Cottonwood (Black 

Cottonwood, 

Balsam Poplar)

Sunny, moist areas forming riparian 

corridors Medicinal, resin

Prunella vulgaris Heal-All (Native 

Heal All, Self-heal)

Moist grasslands, disturbed sites and 

open stream banks Edible, medicinal

Prunus emarginata Wild Cherry (Bitter 

Cherry)

Moist riparian areas, prefers sunny 

stream banks

Edible, medicinal, 

tools

Pseudotsuga menziesii Douglas Fir Widespread, moist, fog belt to drier 

forests

Ceremonial, 

medicinal, tools

Pteridum aquilinum Bracken Fern 

(Brake Fern) Prefers open areas with partial to full sun

Crafts (basketry), 

edible, tools

Pyrus fusca / Malus fusca Crab Apple (Oregon 

or Pacific)

Moist, open shrub lands, open coniferous 

forests below 800 meters Edible, tools

Quercus garryana Oregon White Oak 

(Garry Oak)

Varied western Oregon, mixed conifer

stands Edible

Rhamnus purshiana / 

Frangula purshiana

Cascara (Chittam, 

Buckthorn)

Moist, coastal coniferous forests, often 

associated with red alder

Dye, medicinal, 

tools

Rhododendron 

macrophyllum Rhododendron Moist, coastal and low elevation forest understories, rich acidic soils Tools

Ribes laxiflorum

Black Current 

(Trailing Black 

Currant)

Marshes and wet coastal forests to 

mountain slopes, shade tolerant Edible, medicinal

Rosa gymnocarpa / Rosa 

nutkana Wood Rose Shady understory in mid to low elevation forests

Edible, medicinal, 

ceremonial

Rubus parviflorus Thimbleberry (Wild 

Raspberry) Moist open forests and shrublands Edible, medicinal, soap

Rubus spectabilis Salmonberry Riparian areas, moist forest edges, 

shrubland, prefers partial sun Edible, medicinal

Rubus ursinus Pacific Blackberry Open, disturbed sites in prairies to forests Edible, medicinal

Sagittaria latifolia Wapato Low elevation marshes, ponds, ditches, Edible, medicinal
1648 | P a g e

Species Common Name Habitats Known Uses

(Arrowhead) partly submerged in shallow water

Salix exigua

Sandbar Willow 

(Narrow-leaf 

Willow)

Thickets along coastal stream banks, 

riparian areas, gravel bars

Crafts (basketry), 

tools

Salix hookeriana Hooker’s Willow 

(Coast Willow) Moist open areas in coastal fog belt

Crafts (basketry), 

cordage, fish 

weirs, medicinal

Salix lasiandra Pacific Willow Damp soils, stream banks, floodplains, 

wet meadows

Crafts (basketry), 

medicinal, edible, 

tools

Salix scouleriana

Scouler’s Willow 

(Black Willow, 

Mountain Willow)

Moist pockets of shrublands Smoking, tools, 

tattoo pigment

Sambucus acemosa

S. caerulea

Elderberry (Red and 

Blue)

Sunny openings in moist forests along 

watercourses

Ceremonial, 

edible, medicinal, 

tools

Satureja douglasii

Clinopodium douglasii

Yerba Buena 

(Mountain Tea)

Well drained open, semi-shaded forest 

floors Medicinal

Schoenoplectus pungens

Scirpus pungens Three-Square Sedge Estuarine wetlands, river mouths Crafts (basketry)

Scirpus acutus

Schoenoplectus acutus Tule (Bulrush) Brackish or freshwater areas in shallow muddy meadows, marshes, stream banks Edible, tools

Scirpus maritimus

S. microcarpus

Bulrush (Seacoast 

Bulrush, Smallflowered Bulrush)Marshes, pond margins, wet fields Clothing, edible, 

medicinal

Sphagnum species Moss Moist shaded trees, downed logs and 

soils with high debris content Tools

Stachys mexicana Wood Betony 

(Woundwort)

Grassy wetlands, along banks of open 

water Medicinal

Symphoricarpos albus Snowberry Moist open forests to swampy thickets, 

shade and sun tolerant Medicinal, tools

Sisyrinchium bellum Blue-eyed Grass Sunny to partial shaded grasslands Medicinal, tools

Taxus brevifolia Yew Moist shady forests associated with 

serpentine soils Medicinal, tools

Thuja plicata

Red Cedar (Western 

Red cedar, Canoe 

Cedar)

Moist, mixed evergreen forests, shady 

habitats

Clothing, crafts,

medicinal, shelter, 

tools

Trifolium wormskjoldii Springbank Clover Moist to wet open areas Edible, medicinal

Trillium ovatum Trillium (Birth 

Root, Indian Balm)

Moist, open forests and shrublands as 

understory herb, ravine bottoms, stream 

banks

Medicinal

Triteleia hyacinthine

T. bridgesii 

T. grandiflora

Harvest Lily (Grass 

Nut, White and Blue 

Brodia)

Open, grasslands, wet meadows Edible

Tsuga heterophylla Western Hemlock

Shade tolerant, second generation forest 

tree, likes rotting wood under closed 

canopy

Edible, tools

Typha latifolia Cattail (Flags) Flooded edges of stream, pond, and 

marshes

Clothing, crafts, 

edible, tools

Ulva lactuca

Sea Lettuce (Sea 

Weed, Chinese 

Lettuce)

Calm, sheltered marine environments, 

tidal zones Edible, medicinal

Umbellularia californica Myrtle (Oregon 

Myrtlewood, Open chaparral and grasslands Edible, medicinal
1649 | P a g e

Species Common Name Habitats Known Uses

Pepperwood)

Urtica dioica Nettle (Stinging 

Nettle, Tall Nettle) Moist areas, shaded forests, stream banks Edible, medicinal,tools

Vaccinium ovatum

V. parvifolium

Huckleberry (Black 

and Red)

Open, moist, coniferous forests and 

bordering shrub lands Edible, medicinal

Viola sempervirens

V. glabella

Violet (Evergreen 

Violet, Wood 

Violet)

Moist, open woods and shrublands Edible, medicinal

Woodwardia fimbriata Woodwardia Fern 

(Giant Chain Fern)

Moist, shaded areas along creeks and 

riverbanks, coastal conifer hardwood 

forests

Crafts (basketry)

Xerophyllum tenax Bear Grass Open forest over-story with filtered light Crafts (basketry)

Zigadenus freemontii

Z. micranthus

Death-Camas (Star 

Lily)

Grassy, rocky outcrops or open wooded 

slopes

Poisonous, 

medicinal bulbs 

used carefully
1650 | P a g e

References 

Anderson, M.K., J. Effenberger, D. Joley, and D.J. Lionakis Meyer. 2012. Edible Seeds and Grains of California Tribes and the 

Klamath Tribe of Oregon in the Phoebe Apperson Hearst Museum of Anthropology Collections, University of California, 

Berkeley. USDA NRCS National Plant Data Team. 216 pp. 

http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1075370.pdf. 

Casey, P. A., and R. L. Wynia. 2010. Culturally Significant Plants. USDA NRCS Manhattan Plant Materials Center. Manhattan, 

KS. 54 pp. http://wmc.ar.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1043638.pdf. 

Fluharty, S., D. Hockema, and N. Norris. 2010. Ethnobotany of the Coquille Indians; 100 Common Cultural Plants. Coquille 

Indian Tribe, Cultural Resources Program. North Bend, OR. 

Oregon Native Plant Society. 2007. Common Plants of the Upper Klamath Basin. Oregon Native Plant Society – Klamath Basin 

Chapter. 227 pp. 

The Klamath Tribes, USDA Forest Service, Chiloquin High School, 1993. / ? at a naat stayLA / (“Now we gather [roots, 

berries]”): A treatment of indigenous plants in the Klamath Basin.
1651 | P a g e

Appendix S – Other Wildlife 

Bald Eagle 

Table S-1. Bald eagle nesting habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 247,608 247,608 247,608 247,608 247,608 247,393 247,608

Alternatives/Proposed RMP

2023 239,162 245,926 240,541 237,713 246,257 241,113 251,623

2033 241,217 250,307 248,623 234,618 254,734 247,912 260,791

2043 269,083 284,349 284,691 259,979 290,664 282,197 301,812

2053 283,700 300,363 302,859 273,581 312,466 298,799 320,636

2063 300,862 322,298 325,246 288,660 338,378 319,828 345,936

Table S-2. Bald eagle nesting habitat development in the planning area

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 1,146,747 1,146,747 1,146,747 1,146,747 1,146,747 1,146,532 1,146,747

Alternatives/Proposed RMP

2023 1,138,301 1,145,065 1,139,680 1,136,852 1,145,396 1,140,252 1,150,762

2033 1,140,356 1,149,446 1,147,762 1,133,757 1,153,873 1,147,051 1,159,930

2043 1,168,222 1,183,488 1,183,830 1,159,118 1,189,803 1,181,336 1,200,951

2053 1,182,839 1,199,502 1,201,998 1,172,720 1,211,605 1,197,938 1,219,775

2063 1,697,743 1,719,179 1,722,127 1,685,541 1,735,259 1,716,709 1,742,817
1652 | P a g e

Golden Eagle 

Table S-3. Golden eagle nesting habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 789,751 789,751 789,751 789,751 789,751 787,870 789,751

Alternatives/Proposed RMP

2023 750,166 779,767 770,310 757,922 786,414 772,764 797,483

2033 729,066 782,249 782,891 737,013 802,040 779,784 812,293

2043 787,103 860,962 866,826 796,427 893,766 861,269 909,511

2053 821,344 911,220 930,695 843,357 964,908 920,758 967,010

2063 848,128 957,588 982,160 878,459 1,026,264 969,364 1,018,234

Table S-4. Golden eagle nesting habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 3,225,904 3,225,904 3,225,904 3,225,904 3,225,904 3,224,023 3,225,904

Alternatives/Proposed RMP

2023 3,186,319 3,215,920 3,206,463 3,194,075 3,222,567 3,208,917 3,233,636

2033 3,165,219 3,218,402 3,219,044 3,173,166 3,238,193 3,215,937 3,248,446

2043 3,223,256 3,297,115 3,302,979 3,232,580 3,329,919 3,297,422 3,345,664

2053 3,257,497 3,347,373 3,366,848 3,279,510 3,401,061 3,356,911 3,403,163

2063 4,612,466 4,721,926 4,746,498 4,642,797 4,790,602 4,733,702 4,782,572
1653 | P a g e

Structural Stage Development 

Table S-5. Early Successional forest habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 46,249 46,249 46,249 46,249 46,249 53,459 46,249

Alternatives/Proposed RMP

2023 92,216 91,012 81,747 138,088 69,273 86,427 43,016

2033 101,496 97,831 73,282 180,450 51,793 74,945 9,667

2043 100,324 86,622 105,364 145,343 44,531 78,167 12,233

2053 111,095 79,930 132,251 127,038 47,977 81,505 14,105

2063 110,566 80,089 118,311 131,001 46,001 65,418 14,418

Table S-6. Early Successional forest habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 1,112,694 1,112,694 1,112,694 1,112,694 1,112,694 1,119,904 1,112,694

Alternatives/Proposed RMP

2023 1,158,661 1,157,457 1,148,192 1,204,533 1,135,718 1,152,872 1,109,463

2033 1,088,405 1,084,740 1,060,190 1,167,359 1,038,702 1,061,854 996,579

2043 1,087,233 1,073,531 1,092,273 1,132,252 1,031,440 1,065,076 999,145

2053 1,098,004 1,066,839 1,119,160 1,113,947 1,034,886 1,068,414 1,001,017

2063 1,097,475 1,066,998 1,105,220 1,117,910 1,032,910 1,052,327 1,001,331

Table S-7. Stand Establishment forest habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 388,767 388,767 388,767 388,767 388,767 387,247 388,767

Alternatives/Proposed RMP

2023 393,078 393,271 392,762 392,609 392,885 391,203 393,698

2033 261,528 259,790 261,142 260,643 261,162 266,906 263,693

2043 193,516 189,545 142,827 236,987 169,905 185,587 144,688

2053 169,130 158,823 77,038 243,421 118,027 146,536 75,210

2063 139,442 107,771 24,419 170,143 64,048 101,930 22,334
1654 | P a g e

Table S-8. Stand Establishment forest habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 2,473,304 2,473,304 2,473,304 2,473,304 2,473,304 2,471,784 2,473,304

Alternatives/Proposed RMP

2023 2,477,615 2,477,808 2,477,299 2,477,146 2,477,422 2,475,740 2,478,235

2033 2,277,548 2,275,810 2,277,162 2,276,663 2,277,182 2,282,926 2,279,713

2043 2,130,000 2,126,029 2,079,311 2,173,471 2,106,389 2,122,071 2,081,173

2053 2,105,614 2,095,307 2,013,522 2,179,905 2,054,511 2,083,020 2,011,695

2063 2,075,926 2,044,255 1,960,903 2,106,627 2,000,532 2,038,414 1,958,819

Table S-9. Young forest habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 622,916 622,916 622,916 622,916 622,916 619,631 622,916

Alternatives/Proposed RMP

2023 593,429 559,361 582,353 559,043 565,137 577,103 563,863

2033 621,154 553,647 588,635 563,582 560,568 590,318 550,334

2043 542,593 475,991 516,096 502,575 478,273 514,917 464,112

2053 410,984 347,098 395,704 369,961 347,204 387,248 331,876

2063 361,710 335,731 367,900 393,286 324,719 356,605 294,265

Table S-10. Young forest habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 9,807,038 9,807,038 9,807,038 9,807,038 9,807,038 9,803,753 9,807,038

Alternatives/Proposed RMP

2023 9,777,551 9,743,483 9,766,475 9,743,165 9,749,259 9,761,225 9,747,986

2033 9,953,329 9,885,822 9,920,810 9,895,757 9,892,743 9,922,493 9,882,509

2043 9,954,304 9,887,702 9,927,807 9,914,286 9,889,984 9,926,628 9,875,822

2053 9,822,695 9,758,809 9,807,415 9,781,672 9,758,915 9,798,959 9,743,586

2063 8,295,651 8,269,672 8,301,841 8,327,227 8,258,660 8,290,546 8,228,205
1655 | P a g e

Table S-11. Mature forest habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 515,324 515,324 515,324 515,324 515,324 517,893 515,324

Alternatives/Proposed RMP

2023 530,495 535,495 528,263 510,523 555,899 533,354 570,286

2033 604,423 623,388 617,535 566,186 659,078 612,852 692,423

2043 748,405 753,999 746,035 671,321 807,110 736,129 864,305

2053 862,653 876,970 864,974 781,688 941,998 862,326 1,015,653

2063 907,043 889,737 916,491 792,794 968,826 910,498 1,045,993

Table S-12. Mature forest habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 2,431,709 2,431,709 2,431,709 2,431,709 2,431,709 2,434,278 2,431,709

Alternatives/Proposed RMP

2023 2,446,880 2,451,880 2,444,648 2,426,908 2,472,284 2,449,739 2,486,671

2033 2,520,808 2,539,773 2,533,920 2,482,571 2,575,463 2,529,237 2,608,808

2043 2,664,790 2,670,384 2,662,420 2,587,706 2,723,495 2,652,514 2,780,690

2053 2,062,366 2,076,683 2,064,687 1,981,401 2,141,711 2,062,039 2,215,365

2063 3,584,526 3,567,220 3,593,974 3,470,277 3,646,309 3,587,981 3,723,475

Table S-13. Structurally-complex forest habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 588,435 588,435 588,435 588,435 588,435 583,459 588,435

Alternatives/Proposed RMP

2023 552,481 582,560 576,573 561,435 578,505 573,612 591,365

2033 573,098 627,043 621,105 590,837 629,097 616,678 646,110

2043 576,860 655,541 651,378 605,473 661,880 646,899 676,889

2053 607,836 698,878 691,732 639,592 706,493 684,084 725,384

2063 642,938 748,371 734,577 674,474 758,105 727,248 785,217
1656 | P a g e

Table S-14. Structurally-complex forest habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 1,578,370 1,578,370 1,578,370 1,578,370 1,578,370 1,573,394 1,578,370

Alternatives/Proposed RMP

2023 1,542,416 1,572,495 1,566,508 1,551,370 1,568,440 1,563,547 1,581,271

2033 1,563,033 1,616,978 1,611,040 1,580,772 1,619,032 1,606,613 1,636,016

2043 1,566,795 1,645,476 1,641,313 1,595,408 1,651,815 1,636,834 1,666,795

2053 2,314,443 2,405,485 2,398,339 2,346,199 2,413,100 2,390,691 2,431,962

2063 2,349,545 2,454,978 2,441,184 2,381,081 2,464,712 2,433,855 2,491,796

Table S-15. Early Successional, Stand Establishment, and Young stands with Structural Legacies (1.1, 

2.1, 3.1, 3.3) in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 223,475 223,475 223,475 223,475 223,475 225,291 223,475

Alternatives/Proposed RMP

2023 284,566 225,728 268,316 223,556 253,306 266,574 228,516

2033 301,306 199,160 267,575 196,131 244,514 270,921 204,698

2043 320,868 174,503 277,134 176,150 242,589 288,002 175,062

2053 344,989 149,389 278,851 149,441 235,643 291,343 151,473

2063 367,349 123,248 265,647 124,348 226,262 284,114 128,372

Table S-16. Mature and Structurally-complex stands with Structural Legacies (4.2, 5.1, 5.2, 5.3) in the 

decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 862,411 862,411 862,411 862,411 862,411 860,528 862,411

Alternatives/Proposed RMP

2023 822,156 850,413 840,454 824,563 859,206 842,310 871,438

2033 808,459 858,389 859,842 806,909 882,385 856,446 893,801

2043 884,185 952,884 962,440 879,988 993,084 954,604 1,011,663

2053 923,935 1,005,188 1,026,964 926,363 1,070,004 1,016,855 1,074,271

2063 961,980 1,058,410 1,087,349 962,201 1,141,298 1,072,105 1,136,633
1657 | P a g e

References 

Altman, B., and J. D. Alexander. 2012. Habitat conservation for landbirds in coniferous forests of western Oregon and 

Washington. Version 2.0. Oregon-Washington Partners in Flight. 

http://www.orwapif.org/sites/default/files/Western_Conifer_Plan_new.pdf. 

Altman, B. 2000a. Conservation strategy for landbirds in lowlands and valleys of western Oregon and Washington. Version 1.0. 

Oregon-Washington Partners in Flight. 169 pp. http://www.orwapif.org/sites/default/files/western_lowlands.pdf. 

Altman, B. 2000b. Conservation strategy for landbirds of the east-slope of the Cascade Mountains in Oregon and Washington. 

Version 1.0. Oregon-Washington Partners in Flight, Corvallis, OR. 131 pp. 

http://www.orwapif.org/sites/default/files/east_slope.pdf. 

Duncan, N., T. Burke, S. Dowlan, and P. Hohenlohe. 2003. Survey protocol for Survey and Manage terrestrial mollusks from the 

Northwest Forest Plan, version 3.0. BLM, USFS. 70 pp. http://www.blm.gov/or/plans/surveyandmanage/protocols/. 

Frest, T. J. and E. J. Johannes. 1999. Field guide to Survey and Manage freshwater mollusk species. In Cooperation with the 

USFS Regional Ecosystem Office and USDI BLM Oregon State Office, Portland, OR. BLM/OR/WA/PL-99/045+1792. 128 

pp. http://www.blm.gov/or/plans/surveyandmanage/field.php. 

Hooper, C. 2014. February 19, 2014 e-mail re: 83 feet. U.S. Department of the Interior, Bureau of Land Management, Salem, OR 

Landscape Ecology, Modeling, Mapping and Analysis (LEMMA). 2014. GNN Structure (species-size) maps. 

http://lemma.forestry.oregonstate.edu/data/structure-maps (Accessed 08/05/2014). 

Mellen-McLean, K., B. G. Marcot, J. L. Ohmann, K. Waddell, S. A. Livingston, E. A. Willhite, B. B. Hostetler, C. Ogden, and T. 

Dreisbach. 2012. DecAID, the decayed wood advisor for managing snags, partially dead trees, and down wood for 

biodiversity in forests of Washington and Oregon. Version 2.20. USDA Forest Service, Pacific Northwest Region and 

Pacific Northwest Research Station; USDI Fish and Wildlife Service, Oregon State Office; Portland, Oregon. 

http://www.fs.fed.us/r6/nr/wildlife/decaid/index.shtml (Accessed October 30, 2013). 

Olson, D. H. editor. 1999. Survey Protocols for amphibians under the Survey and Manage provision of the Northwest Forest 

Plan, version 3.0. 314 pp. http://www.blm.gov/or/plans/surveyandmanage/protocols/. 

USDA FS, USDI BLM. 2011. List of Survey and Manage species, Northwest Forest Plan (NWFP) Area – September 29, 2011. 

http://www.blm.gov/or/plans/surveyandmanage/otherresources/related.php. 

USDI BLM. 2008. Final Environmental Impact Statement for the Revision of the Resource Management Plans of the Western 

Oregon Bureau of Land Management Districts. BLM Oregon State Office, Portland, OR. 

http://www.blm.gov/or/plans/wopr/final_eis/index.php. 

Snags and Down Woody Material 

The BLM tabulated the amount of existing snags and down woody material using the BLM’s forest 

inventory data from the Current Vegetation Survey (CVS) – measured permanent plot data. The BLM 

contracted with the forestry consulting firm of Mason, Bruce & Girard of Portland, Oregon, to jointly 

develop and build the Woodstock model described in Appendix C and that consulting firm also computed 

the existing amount of snag and down wood from the CVS plot data and strata that the BLM further 

summarized here in Appendix S.

 Qualifying snag = 5” DBH is smallest recorded in CVS data summary; no minimum height or 

decay class requirement. 

 Qualifying down woody material = Decay Class 1–4, > 4” minimum diameter; exclude decay 

class 5. 

Refer to Appendix C for further information on forest inventory data. 
1658 | P a g e

Existing Snag Density 

Table S-17. Snag density (trees per acre) in the decision area by structural group 

Structural Group

Diameter Class (Inches DBH) Sub-

< 6 6–12 12–18 18–24 24–30 30–36 > 36 < 10 10–20 > 20 All Plots

Early Successional 4.1 6.5 2.2 1.4 0.7 0.6 0.3 9.4 3.7 2.6 15.7 127

Stand Establishment 1.5 3.4 1.2 0.7 0.5 0.2 0.3 4.4 2.0 1.4 7.8 1,313

Young 5.0 9.2 2.0 0.8 0.4 0.3 0.4 12.9 3.6 1.6 18.1 1,666

Mature 5.6 15.9 3.1 1.4 0.8 0.5 0.7 18.9 6.3 2.9 28.1 1,527

Structurally-complex 3.3 8.4 2.7 1.9 1.3 0.9 1.2 10.2 4.8 4.7 19.8 1,617

Weighted Average 3.9 9.4 2.3 1.2 0.8 0.5 0.7 11.8 4.2 2.7 18.7 6,250

Table S-18. Snag density (trees per acre) in the decision area by structural stage 

Structural Stage Diameter Class (Inches DBH) Sub-

< 6 6–12 12–18 18–24 24–30 30–36 > 36 < 10 10–20 > 20 All Plots

Early Successional with

Structural Legacies - 0.8 1.2 0.9 0.3 0.9 0.1 0.8 1.2 2.1 4.1 31

Early Successional 

without Structural 

Legacies

5.4 8.3 2.5 1.6 0.8 0.6 0.4 12.2 4.5 2.7 19.4 96

Stand Establishment with

Structural Legacies 4.3 6.1 1.0 0.6 0.3 0.3 0.1 9.9 1.9 1.1 12.8 211

Stand Establishment 

without Structural 

Legacies

0.9 2.9 1.2 0.7 0.5 0.2 0.3 3.4 2.0 1.4 6.8 1,102

Young – High Density, 

with Structural Legacies 3.1 6.6 2.2 1.2 0.5 0.5 0.6 8.3 4.0 2.2 14.6 417

Young – High Density, 

without Structural 

Legacies

5.7 10.1 1.9 0.7 0.4 0.3 0.3 14.5 3.5 1.3 19.3 1,144

Young – Low Density, 

with Structural Legacies 5.4 10.9 0.7 0.2 0.9 0.5 0.1 16.3 0.9 1.4 18.6 31

Young – Low Density, 

without Structural 

Legacies

4.4 9.5 2.3 1.2 0.7 0.2 0.3 11.8 5.0 1.9 18.6 74

Mature, Single-layered 

Canopy 6.2 19.9 3.6 1.7 1.0 0.5 0.8 22.9 7.6 3.2 33.7 677

Mature, Multi-layered 

Canopy 5.2 12.7 2.7 1.3 0.6 0.5 0.7 15.7 5.3 2.6 23.6 850

Structurally-complex, 

Developed Structurallycomplex3.3 9.5 2.9 1.9 1.0 0.8 1.0 11.4 5.0 4.0 20.4 649

Structurally-complex, 

Existing Old Forest 3.3 7.8 2.5 1.9 1.6 1.0 1.3 9.6 4.7 5.1 19.3 925

Structurally-complex, 

Existing Very Old Forest 3.9 5.0 1.7 2.6 1.6 1.2 3.3 7.3 4.2 7.8 19.4 43

Weighted Average 3.9 9.4 2.3 1.2 0.8 0.5 0.7 11.8 4.2 2.7 18.7 6,250
1659 | P a g e

Table S-19. Snag density (trees per acre) in the northern districts (Coos Bay, Eugene, and Salem) by 

structural group 

Structural Group

Diameter Class (Inches DBH) Sub-

< 6 6–12 12–18 18–24 24–30 30–36 > 36 < 10 10–20 > 20 All Plots

Early Successional - - 0.9 0.3 - 1.2 - - 0.9 1.6 2.5 17

Stand Establishment 0.9 2.3 1.9 1.0 0.8 0.3 0.4 2.8 2.9 2.0 7.7 500

Young 5.7 10.1 2.1 0.9 0.5 0.3 0.5 14.5 3.6 1.9 20.0 847

Mature 5.8 19.8 3.7 1.8 1.0 0.6 1.1 22.2 7.8 3.8 33.8 849

Structurally-complex 2.3 7.5 3.2 2.6 1.7 1.3 2.0 8.5 5.4 6.7 20.6 622

Weighted Average 4.1 11.0 2.8 1.5 1.0 0.6 1.0 13.3 5.1 3.5 22.0 2,835

Table S-20. Snag density (trees per acre) in the northern districts (Coos Bay, Eugene, and Salem) by 

structural stage 

Structural Stage

Diameter Class (Inches DBH) Sub-

< 6 6–12 12–18 18–24 24–30 30–36 > 36 < 10 10–20 > 20 All Plots

Early Successional with

Structural Legacies - - 1.3 0.4 - 1.8 - - 1.3 2.2 3.5 12

Early Successional 

without Structural 

Legacies

- - - - - - - - - - - 5

Stand Establishment with

Structural Legacies 4.0 6.0 1.1 1.5 1.2 - - 10.0 1.6 2.2 13.9 24

Stand Establishment 

without Structural 

Legacies

0.7 2.1 1.9 1.0 0.8 0.4 0.5 2.4 3.0 2.0 7.4 476

Young – High Density, 

with Structural Legacies 2.9 4.5 2.5 1.6 0.5 0.7 1.3 6.5 4.0 3.6 14.1 156

Young – High Density, 

without Structural 

Legacies

6.4 11.4 2.0 0.7 0.5 0.2 0.4 16.5 3.5 1.5 21.5 677

Young – Low Density, 

with Structural Legacies - 24.1 5.3 - 5.3 - - 24.1 5.3 5.3 34.7 2

Young – Low Density, 

without Structural 

Legacies

- 6.0 0.9 1.3 - 0.4 1.3 2.0 5.3 2.7 10.0 12

Mature, Single-layered 

Canopy 6.7 22.3 4.0 1.8 1.2 0.6 0.9 25.3 8.6 3.7 37.6 531

Mature, Multi-layered 

Canopy 4.3 15.6 3.1 1.7 0.7 0.7 1.4 17.1 6.5 3.8 27.5 318

Structurally-complex, 

Developed Structurally 

Complex

2.0 8.8 3.9 2.5 1.6 1.3 1.8 9.1 6.5 6.2 21.8 272

Structurally-complex, 

Existing Old Forest 2.5 6.7 2.6 2.7 1.8 1.2 2.1 8.2 4.6 6.9 19.7 317

Structurally-complex, 

Existing Very Old Forest 3.7 4.4 1.9 2.3 1.1 1.6 3.9 6.6 4.3 8.0 18.8 33

Weighted Average 4.1 11.0 2.8 1.5 1.0 0.6 1.0 13.3 5.1 3.5 22.0 2,835
1660 | P a g e

Table S-21. Snag density (trees per acre) in the southern districts (Klamath Falls, Medford, and 

Roseburg) by structural group 

Structural Group

Diameter Class (Inches DBH) Sub-

< 6 6–12 12–18 18–24 24–30 30–36 > 36 < 10 10–20 > 20 All Plots

Early Successional 4.7 7.4 2.4 1.5 0.8 0.5 0.3 10.8 4.1 2.7 17.7 110

Stand Establishment 1.8 4.1 0.7 0.5 0.3 0.2 0.2 5.4 1.4 0.9 7.8 813

Young 4.2 8.4 1.9 0.7 0.4 0.3 0.2 11.3 3.6 1.3 16.1 819

Mature 5.4 11.0 2.4 1.0 0.5 0.3 0.3 14.8 4.4 1.7 20.9 678

Structurally-complex 3.9 8.9 2.3 1.4 1.1 0.7 0.7 11.3 4.4 3.5 19.2 995

Weighted Average 3.8 8.0 1.9 1.0 0.6 0.4 0.4 10.6 3.5 2.0 16.1 3,415

Table S-22. Snag density (trees per acre) in the southern districts (Klamath Falls, Medford, and 

Roseburg) by structural stage 

Structural Group Diameter Class (Inches DBH) Sub-

< 6 6–12 12–18 18–24 24–30 30–36 > 36 < 10 10–20 > 20 All Plots

Early Successional with

Structural Legacies - 1.3 1.1 1.1 0.6 0.3 0.1 1.3 1.1 2.1 4.5 19

Early Successional 

without Structural 

Legacies

5.7 8.7 2.6 1.6 0.8 0.6 0.4 12.8 4.7 2.9 20.5 91

Stand Establishment with

Structural Legacies 4.4 6.1 1.0 0.5 0.2 0.3 0.1 9.8 1.9 0.9 12.7 187

Stand Establishment 

without Structural 

Legacies

1.1 3.5 0.6 0.5 0.3 0.1 0.3 4.1 1.3 1.0 6.3 626

Young – High Density, 

with Structural Legacies 3.1 7.8 2.0 0.9 0.4 0.3 0.2 9.4 4.0 1.4 14.9 261

Young – High Density, 

without Structural 

Legacies

4.6 8.4 1.8 0.6 0.2 0.3 0.2 11.7 3.4 1.1 16.2 467

Young – Low Density, 

with Structural Legacies 5.8 10.0 0.4 0.2 0.5 0.5 0.1 15.8 0.5 1.2 17.5 29

Young – Low Density, 

without Structural 

Legacies

5.2 10.2 2.5 1.2 0.9 0.2 0.1 13.7 4.9 1.7 20.3 62

Mature, Single-layered 

Canopy 4.3 11.2 2.4 1.1 0.4 0.2 0.2 14.4 3.9 1.4 19.7 146

Mature, Multi-layered 

Canopy 5.7 10.9 2.4 1.0 0.6 0.3 0.3 14.9 4.6 1.8 21.3 532

Structurally-complex, 

Developed Structurallycomplex4.3 9.9 2.2 1.4 0.6 0.4 0.5 13.0 4.0 2.3 19.3 377

Structurally-complex, 

Existing Old Forest 3.7 8.4 2.5 1.4 1.4 0.9 0.8 10.3 4.7 4.1 19.2 608

Structurally-complex, 

Existing Very Old Forest 4.8 7.2 1.1 3.7 3.2 - 1.1 9.6 4.0 7.4 21.1 10

Weighted Average 3.8 8.0 1.9 1.0 0.6 0.4 0.4 10.6 3.5 2.0 16.1 3,415
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Existing Down Woody Material Quantities 

Table S-23. Down woody material cover in the decision area by structural group 

Structural Group Decay Class (Percent Cover) Transects

1 2 3 4 5 All (Number)

Early Successional 0.2% 0.9% 1.5% 0.9% 0.3% 3.8% 254

Stand Establishment 0.2% 0.4% 1.4% 1.6% 0.4% 4.1% 2,626

Young 0.2% 0.4% 1.0% 1.4% 0.6% 3.6% 3,332

Mature 0.3% 0.7% 1.4% 1.8% 0.9% 5.0% 3,054

Structurally-complex 0.3% 0.7% 1.8% 1.5% 0.6% 4.9% 3,234

Weighted Average 0.2% 0.6% 1.4% 1.5% 0.6% 4.4% 12,500

Table S-24. Down woody material cover in the decision area by structural stage 

Structural Stage Decay Class (Percent Cover) Transects

1 2 3 4 5 All (Number)

Early Successional with Structural Legacies 0.2% 1.5% 2.4% 1.3% 0.3% 5.6% 62

Early Successional without Structural Legacies 0.1% 0.7% 1.3% 0.8% 0.3% 3.1% 192

Stand Establishment with Structural Legacies 0.2% 0.3% 0.7% 1.1% 0.8% 3.1% 422

Stand Establishment without Structural Legacies 0.2% 0.4% 1.6% 1.7% 0.4% 4.3% 2,204

Young – High Density, with Structural Legacies 0.2% 0.3% 1.1% 1.2% 0.4% 3.2% 834

Young – High Density, without Structural Legacies 0.3% 0.4% 1.0% 1.5% 0.6% 3.8% 2,288

Young – Low Density, with Structural Legacies 0.1% 0.2% 0.3% 0.2% 0.1% 0.9% 62

Young – Low Density, without Structural Legacies 0.1% 0.9% 1.3% 0.9% 0.3% 3.3% 148

Mature, Single-layered Canopy 0.3% 0.9% 1.5% 1.9% 0.9% 5.5% 1,354

Mature, Multi-layered Canopy 0.2% 0.6% 1.3% 1.7% 0.8% 4.6% 1,700

Structurally-complex, Developed Structurally-complex 0.2% 0.5% 1.5% 1.5% 0.6% 4.3% 1,298

Structurally-complex, Existing Old Forest 0.3% 0.8% 1.9% 1.5% 0.6% 5.2% 1,850

Structurally-complex, Existing Very Old Forest 0.4% 1.2% 5.2% 2.3% 0.9% 10.0% 86

Weighted Average 0.2% 0.6% 1.4% 1.5% 0.6% 4.4% 12,500

Table S-25. Down woody material cover in the northern districts (Coos Bay, Eugene, and Salem) by 

structural group 

Structural Group Decay Class (Percent Cover) Transects

1 2 3 4 5 All (Number)

Early Successional 0.1% 1.6% 2.1% 1.0% 0.4% 5.3% 34

Stand Establishment 0.3% 0.4% 1.5% 1.5% 0.5% 4.1% 1,000

Young 0.3% 0.5% 1.2% 1.7% 0.7% 4.4% 1,694

Mature 0.4% 0.8% 1.6% 1.7% 0.9% 5.4% 1,698

Structurally-complex 0.3% 1.0% 2.7% 1.9% 0.8% 6.8% 1,244

Weighted Average 0.3% 0.7% 1.7% 1.7% 0.8% 5.2% 5,670
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Table S-26. Down woody material cover in the northern districts (Coos Bay, Eugene, and Salem) by 

structural stage 

Structural Stage Decay Class (Percent Cover) Transects

1 2 3 4 5 All (Number)

Early Successional with Structural Legacies 0.2% 2.3% 3.0% 1.4% 0.6% 7.5% 24

Early Successional without Structural Legacies - - - - - - 10

Stand Establishment with Structural Legacies - 0.2% 0.5% 1.3% 0.8% 2.8% 48

Stand Establishment without Structural Legacies 0.3% 0.4% 1.5% 1.5% 0.5% 4.2% 952

Young – High Density, with Structural Legacies 0.3% 0.4% 1.4% 1.7% 0.5% 4.3% 312

Young – High Density, without Structural Legacies 0.3% 0.5% 1.1% 1.7% 0.8% 4.4% 1,354

Young – Low Density, with Structural Legacies 0.8% 2.1% - 1.4% - 4.4% 4

Young – Low Density, without Structural Legacies - 3.2% 2.3% 1.6% 1.0% 8.1% 24

Mature, Single-layered Canopy 0.4% 0.8% 1.6% 1.9% 1.0% 5.6% 1,062

Mature, Multi-layered Canopy 0.3% 0.7% 1.5% 1.5% 0.8% 5.0% 636

Structurally-complex, Developed Structurally-complex 0.2% 0.7% 1.9% 1.6% 0.7% 5.1% 544

Structurally-complex, Existing Old Forest 0.3% 1.3% 3.1% 2.1% 0.9% 7.7% 634

Structurally-complex, Existing Very Old Forest 0.4% 1.5% 6.5% 2.7% 1.0% 12.2% 66

Weighted Average 0.3% 0.7% 1.7% 1.7% 0.8% 5.2% 5,670

Table S-27. Down woody material cover in the southern districts (Klamath Falls, Medford, and 

Roseburg) by structural group 

Structural Group Decay Class (Percent Cover) Transects

1 2 3 4 5 All (Number)

Early Successional 0.2% 0.8% 1.4% 0.9% 0.3% 3.5% 220

Stand Establishment 0.1% 0.5% 1.4% 1.6% 0.4% 4.0% 1,626

Young 0.1% 0.3% 0.8% 1.0% 0.4% 2.7% 1,638

Mature 0.1% 0.7% 1.1% 1.8% 0.8% 4.5% 1,356

Structurally-complex 0.2% 0.5% 1.3% 1.3% 0.5% 3.8% 1,990

Weighted Average 0.2% 0.5% 1.2% 1.4% 0.5% 3.7% 6,830
1663 | P a g e

Table S-28. Down woody material cover in the southern districts (Klamath Falls, Medford, and 

Roseburg) by structural stage 

Structural Stage

Decay Class (Percent Cover) Transects

1 2 3 4 5 All (Number)

Early Successional with Structural Legacies 0.2% 0.9% 2.0% 1.2% - 4.5% 38

Early Successional without Structural Legacies 0.1% 0.7% 1.3% 0.8% 0.3% 3.3% 182

Stand Establishment with Structural Legacies 0.2% 0.3% 0.8% 1.1% 0.8% 3.2% 374

Stand Establishment without Structural Legacies 0.1% 0.5% 1.6% 1.8% 0.3% 4.3% 1,252

Young – High Density, with Structural Legacies 0.1% 0.3% 0.9% 0.9% 0.4% 2.6% 522

Young – High Density, without Structural Legacies 0.2% 0.3% 0.8% 1.1% 0.5% 2.9% 934

Young – Low Density, with Structural Legacies - - 0.3% 0.1% 0.1% 0.7% 58

Young – Low Density, without Structural Legacies 0.1% 0.4% 1.1% 0.7% 0.1% 2.4% 124

Mature, Single-layered Canopy 0.2% 1.1% 1.2% 1.9% 0.5% 4.9% 292

Mature, Multi-layered Canopy 0.1% 0.5% 1.1% 1.8% 0.8% 4.4% 1,064

Structurally-complex, Developed Structurally-complex 0.2% 0.4% 1.2% 1.4% 0.5% 3.7% 754

Structurally-complex, Existing Old Forest 0.2% 0.6% 1.3% 1.3% 0.4% 3.9% 1,216

Structurally-complex, Existing Very Old Forest 0.1% 0.3% 1.0% 0.8% 0.5% 2.7% 20

Weighted Average 0.2% 0.5% 1.2% 1.4% 0.5% 3.7% 6,830

Assumptions for Snag and Down Woody Material Creation or 

Retention Targets 

The BLM developed snag and down woody material creation targets by comparing the amount of existing 

snags and down wood against desired amounts and any deficits from the desired condition was used as a 

creation target for silvicultural treatments (in these types of projects snags and dead wood would be added 

to reach the desired condition). For fuels treatments and salvage projects the BLM established retention 

targets based on the desired condition (in these types of projects snags and dead wood would generally be 

subtracted but only down to the desired condition). 

The concept and assumptions described here were used in the Proposed RMP, Alternative B, and 

Alternative D. The process for BLM used to develop snag and down woody material creation and 

retention targets is outlined in more detail below. 

Step 1. Develop target levels as interpreted by BLM using the Decayed Wood Advisor (DecAID) 

(Mellen-McLean et al. 2012) as a reference. 

 BLM assumed Small/Medium Trees from DecAID provided an appropriate context based on 

typical tree size in projects (refer to SmallMedium_Trees tab). 

o Assume the Small/Medium Trees syntheses from DecAID provide context because QMD 

of trees reported in recent BLM projects is between 10 and 19 inches 98 percent of the 

time. The BLM reviewed 2–3 forest management EAs published by each district during 

2013–2014 (15 total). 

 BLM assumed that the provinces used in DecAID were applicable to the districts as follows: 

o Assume Westside Lowland Conifer-Hardwood in the Oregon Coast Range province 

(WLCH_OCO_S) applied to the west side of Salem District, west side of Eugene 

District, all of Coos Bay District, and the northwest-portion of Roseburg District. 
1664 | P a g e

o Assume Westside Lowland Conifer-Hardwood in the Western Cascades province 

(WLCH_OCA_S) applied to the eastside of Salem District, eastside of Eugene District, 

and the northeast-portion of Roseburg District. 

o Assume Southwest Oregon Mixed Conifer-Hardwood in the Klamath province 

(SWOMC_S) applied to the southern-half of Roseburg District and all of Medford 

District. 

o Assume Eastside Mixed Conifer East Cascades/Blue Mountains (EMC_ECB_S) applied 

to Klamath Falls Field Office. 

 In the Harvest Land Base, the BLM used the 30 percent tolerance levels from DecAID as a 

reference to establish the target levels of snags and down woody material (Table S-29).

In the Late-Successional Reserve and Riparian Reserve, the BLM used the 50 percent tolerance levels 

from DecAID as a reference to establish the target levels of snags and down woody material (Table S30).

Table S-29. Snag and down woody material target levels within the Harvest Land Base 

District/

Field Office Province Snags/Acre Down Wood

> 20” DBH > 10” DBH (Percent Cover)

Coos Bay All 4.8 5.3 3.0

Eugene

OR Coast Range 4.8 5.3 3.0

Western Cascades 4.8 5.3 4.5

Klamath Falls All 2.7 6.7 2.0

Medford All 2.0 4.0 1.4

Roseburg

OR Coast Range 4.8 5.3 3.0

Western Cascades 4.8 5.3 4.5

Klamath 2.0 4.0 1.4

Salem OR Coast Range 4.8 5.3 3.0

Western Cascades 4.8 5.3 4.5

Table S-30. Snag and down woody material target levels within the Late-Successional Reserve and 

Riparian Reserve 

District/

Field Office Province

Snags/Acre Down Wood

> 20” DBH > 10” DBH (Percent Cover)

Coos Bay All 8.1 18.6 6.0

Eugene

OR Coast Range 8.1 18.6 6.0

Western Cascades 8.1 18.6 10.0

Klamath Falls All 4.2 12.5 3.0

Medford All 3.2 7.3 2.0

Roseburg

OR Coast Range 8.1 18.6 6.0

Western Cascades 8.1 18.6 10.0

Klamath 3.2 7.3 2.0

Salem

OR Coast Range 8.1 18.6 6.0

Western Cascades 8.1 18.6 10.0
1665 | P a g e

Step 2. Calculate existing snag density and quantities of down woody material. 

As described above, the BLM tabulated and summarized the existing amounts of snags and down woody 

material using the BLM forest inventory data from CVS plots. Existing amounts are summarized above in 

Table S-17 through Table S-28. 

Step 3. Calculate the deficit or surplus of snags and down woody material. 

 The BLM calculated the deficit or surplus of snags and down woody material by subtracting the 

existing levels from the target levels of dead wood within the Harvest Land Base (Table S-31) 

and the reserves (Table S-32).

Table S-31. Snag and down woody material deficits (-) or surplus (+) within the Harvest Land Base 

District/

Field Office Province

Snags/Acre Down Wood

> 20” DBH > 10” DBH (Percent Cover) (Trees/Acre)

Coos Bay All -1.3 +3.4 +1.4 +6.5

Eugene

OR Coast Range -1.3 +3.4 +1.4 +6.5

Western Cascades -1.3 +3.4 -0.1 -0.3

Klamath Falls All -0.7 -1.2 +1.2 +8.4

Medford All 0.0 +1.5 +1.8 +8.3

Roseburg

OR Coast Range -2.8 0.2 +0.2 +1.0

Western Cascades -2.8 0.2 -1.3 -5.7

Klamath 0.0 +1.5 +1.8 +8.3

Salem

OR Coast Range -1.3 +3.4 +1.4 +6.5

Western Cascades -1.3 +3.4 -0.1 -0.3

Table S-32. Snag and down woody material deficits (-) or surplus (+) within the Late-Successional 

Reserve and Riparian Reserve 

District/

Field Office Province

Snags/Acre Down Wood

> 20” DBH > 10” DBH (Percent Cover) (Trees/Acre)

Coos Bay All -4.6 -9.9 -1.6 -7.1

Eugene

OR Coast Range -4.6 -9.9 -1.6 -7.1

Western Cascades -4.6 -9.9 -5.6 -25.1

Klamath Falls All -2.2 -7.0 +0.2 +1.6

Medford All -1.2 -1.8 +1.2 +7.0

Roseburg

OR Coast Range -6.1 -13.1 -2.8 -12.5

Western Cascades -6.1 -13.1 -6.8 -30.6

Klamath -1.2 -1.8 +1.2 +7.0

Salem

OR Coast Range -4.6 -9.9 -1.6 -7.1

Western Cascades -4.6 -9.9 -5.6 -25.1

Step 4. Convert down woody material deficit to number of trees. 

 The deficit amount of down woody material expressed as percent cover was converted to linear 

feet per acre using a conversion from DecAID: 
1666 | Page

o Percent cover = (linear meters/hectare) / X-variable 

o Where the X-variable varied: 

 Westside Lowland Conifer Hardwoods (both in Oregon Coast Range and 

Western Cascades [WLCH_S]) X-variable = 316.23 

 Southwestern Oregon Mixed Conifer (SWOMC_S) X-variable = 398.9 

 Eastside Mixed Conifer East Cascades (EMC_ECB_S) X-variable = 480.51 

o Linear feet per acre were converted to trees per acre using the assumption that a tree is 93 

feet tall. From BLM forest inventory data, 93 feet is the average tree height of Douglasfir that is 15–16 inches DBH (C. Hooper, BLM, Vegetation Modeling Lead, personal 

communication, February 19, 2014). 

o Converted deficit or surplus in down woody material converted to number of trees per 

acre is shown in Table S-31 and Table S-32. 

Step 5. Interpret snag and down woody material information into management direction. 

 In interpreting the calculated amounts of snags and down woody material that was either deficit 

or surplus, the BLM had several assumptions, including: 

o Actively create additional dead wood (snags) at time of treatment to compensate for the 

calculated deficits (Table S-31 and Table S-32).

o Existing snags and DWM would be retained – even if there are surplus snags or down 

woody material. 

o Snags >20” DBH size class would contribute towards deficits of snags >10” DBH. 

o Snags >20” DBH or >10” DBH would contribute eventually to down woody material 

because ~30 percent fall within 10 years (Snag Dynamics in Western Oregon and 

Washington from Mellen-McLean et al. 2012).

o Total trees/acre to be snagged would be the greatest number of: 20” DBH snag deficit, 

10” DBH snag deficit, or the down woody material deficit. 

o Deficit of >20” DBH snags would be met from this greatest number; balance of trees to 

be snagged would be >10” DBH. 

Fuel-reduction actions in the reserved land use allocations would not reduce snags or down woody 

material below target levels for the reserve ( 

Table S-30). No active recruitment would occur in response to fuel-reduction – only retention down to 

target levels. 

 Table S-30). No active recruitment would occur in response 

to fuel-reduction – only retention down to target levels.
1667 | P a g e

Bureau Sensitive Wildlife Species 

Table S-33. Habitat development for Bureau Sensitive wildlife species documented or suspected to occur in the decision area 

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

BI Tricolored 

blackbird

Agelaius 

tricolor Wet - 2,850 No change

No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

Wetland 

layer

Jack, Klam, 

Mult

ORBIC 

2013

BI Grasshopper 

sparrow

Ammodramus 

savannarum

Early - 25,487 55,477 

(218%)

35,188 

(138%)

53,134 

(208%)

57,469 

(225%)

23,533 

(92%)

35,805

(140%)

11,938 

(47%)

Earlysuccessional 

(1.1, 1.2) or 

Agricultural, 

Grassland, 

Shrub land 

(GNN 2, 6, 7)

Jack, Lane, 

Linn, Polk

NatureServe 

2014

BI Tule goose Anser albifrons 

elgasi Wet - 1,625 No change

No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

Wetland 

layer Klam ORBIC 2013

BI

Dusky 

Canada 

goose

Branta 

canadensis 

occidentalis

Wet - 7,749 No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

Wetland 

layer

Bent, Colu, 

Lane, Linn, 

Mari, Mult, 

Polk, Till, 

Wash, 

Yamh

ORBIC 

2013

BI

Aleutian 

Canada 

goose

Branta 

hutchinsii 

leucopareia

Wet - 7,299 No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

Wetland 

layer

Bent, Colu, 

Coos, Curr, 

Mari, Mult, 

Polk, Till, 

Wash, 

Yamh

ORBIC 

2013

BI Bufflehead Bucephala 

albeola Wet - 15,858 No change

No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

Wetland 

layer

All except 

Bent, Linc, 

Polk

ORBIC 

2013

BI Yellow rail Coturnicops 

noveboracensis Wet - 1,625 No change

No 

change

No 

change

No 

change

No 

change

No 

change

No 

change

Wetland 

layer Klam ORBIC 2013

BI Black swift Cypseloides 

niger X - No Data No Data No Data No Data No Data No Data No Data No Data Waterfalls Doug, Jack, Lane

ORBIC 

2013

BI Snowy egret Egretta thula Wet - 1,625 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer Klam ORBIC 2013
1668 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

BI White-tailed 

kite Elanus leucurus Wet - 7,703 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer

Bent, Clat, 

Coos, Curr, 

Doug, Jack, 

Jose, Lane, 

Polk, Till

ORBIC 

2013

BI

American 

peregrine 

falcon

Falco 

peregrinus 

anatum

X - No Data No Data No Data No Data No Data No Data No Data No Data Cliffs All ORBIC 

2013

BI Tufted puffin Fratercula 

cirrhata NF - 182 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Marine, 

estuarine 

(GNN 11)

Clat, Coos, 

Curr, Lane, 

Linc, Till

ORBIC 

2013

BI Bald eagle Haliaeetus 

leucocephalus Late - 247,608 300,862(122%)

322,298

(130%)

325,246

(131%)

288,660

(117%)

338,378

(137%)

319,828

(129%)

345,936

(140%)

See Chapter 

3

See 

Chapter 3

See Chapter 

3

BI Harlequin 

duck

Histrionicus 

histrionicus Wet - 13,075 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer

Clac, Clat, 

Coos, Curr, 

Doug, 

Klam, Lane, 

Linc, Linn, 

Mari, Mult, 

Till, Wash

ORBIC 

2013

BI Franklin’s 

gull Larus pipixcan Wet - 1,625 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer Klam

Burrows and 

Gilligan 

2003

BI Lewis’s 

woodpecker

Melanerpes 

lewis Early - 12,896 89,420 (693%)

12,249 

(95%)

70,832 

(549%)

8,716 

(68%)

31,361 

(243%)

43,067

(334%)

16,361 

(127%)

Earlysuccessional 

with 

Structural 

Legacies (1.1) 

or Shrub land 

(GNN 7)

Colu, 

Doug, Jack, 

Jose, Klam, 

Lane, Mult

GeoBOB 

2013

BI American 

white pelican

Pelecanus 

erythrorhynchos Wet - 1,625 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer Klam ORBIC 2013

BI

California 

brown 

pelican

Pelecanus 

occidentalis 

californicus

Wet - 4,656 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer

Clat, Coos, 

Curr, Doug, 

Lane, Linc, 

Till

ORBIC 

2013
1669 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

BI

Whiteheaded 

woodpecker

Picoides 

albolarvatus Early - 10,313 72,725 (705%)

11,882 

(115%)

40,209 

(390%)

8,567 

(83%)

24,085 

(234%)

29,051

(282%)

15,923 

(154%)

Earlysuccessional 

with 

Structural 

Legacies (1.1) 

or Shrub land 

(GNN 7)

Doug, Jack, 

Jose, Klam

GeoBOB 

2013; 

NatureServe 

2014

BI Horned grebe Podiceps 

auritus Wet - 6,997 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer

Clat, Coos, 

Curr, Doug, 

Klam, 

Lane, Linc, 

Linn, Till

ORBIC 

2013

BI Red-necked 

grebe

Podiceps 

grisegena Wet - 9,018 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer

Clat, Coos, 

Curr, Doug, 

Jack, Jose, 

Lane, Linn, 

Mari, Mult, 

Polk, Wash, 

Yamh

ORBIC 

2013

BI

Oregon 

vesper 

sparrow

Pooecetes 

gramineus 

affinis

Early - 5,726 28,774 

(503%)

26,868 

(469%)

58,696 

(1025%)

48,788 

(852%)

18,086 

(316%)

31,193

(545%)

1,798 

(31%)

Earlysuccessional 

(1.1, 1.2) or 

Agricultural, 

Grassland, 

Shrub land 

(GNN 2, 6, 7)

Bent, Clac, 

Lane, Linn, 

Mari, Polk

Nature

Serve 2014

BI Purple martin Progne subis NF - 8,682 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Agricultural, 

grassland, 

shrub land, 

woodland

(GNN 2, 6, 

7)

All

ORBIC 

2013; ISSSP 

Fact Sheet

HA Black 

salamander

Aneides 

flavipunctatus Late - 389,409 422,485 (108%)

488,842 

(126%)

508,151 

(130%)

484,370 

(124%)

505,687 

(130%)

494,087 

(127%)

514,176 

(132%)

Young High 

Density with 

Structural 

Legacies 

(3.1), Mature 

(4.1, 4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3)

Jack, Jose NatureServe 

2014
1670 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

HA Cope’s giant 

salamander

Dicamptodon 

copei RR - 31,891 54,247 (170%)

55,037 

(173%)

51,898 

(163%)

48,739 

(153%)

55,292

(173%)

55,098

(173%)

55,685

(175%)

within 1 

SPTH of 

streams3

Clac, Clat, 

Colu, Mult, 

Till, Wash

ORBIC 

2013

HA

Siskiyou 

mountains 

salamander

Plethodon 

stormi Late A, D‡

328,037 365,523

(111%)

432,740

(132%)

447,786

(137%)

425,029

(129%)

447,347

(136%)

434,541

(132%)

457,766

(140%)

Mature (4.1, 

4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3)

Jack, Jose Olson et al.

1999

HA

Foothill 

yellowlegged frogRana boylii RR - 321,122 526,680 

(164%)

544,580 

(170%)

518,121 

(161%)

477,250 

(149%)

546,135 

(170%)

537,999

(168%)

547,918

(171%)

within 1 

SPTH of 

streams3

Coos, Curr, 

Doug, Jack, 

Jose, Klam, 

Lane, Linn, 

Mari

Olson & 

Davis 2009

HR Western 

pond turtle

Actinemys 

marmorata

Wet - 17,976 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer

Bent, Clac, 

Colu, Coos, 

Curr, Doug, 

Jack, Jose, 

Klam, Lane, 

Linn, Mari, 

Mult, Polk, 

Till, Wash, 

Yamh

ORBIC 

2013

HR Painted turtle Chrysemys 

picta Wet - 11,414 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wetland 

layer

Bent, Clac, 

Colu, Lane, 

Linn, Mari, 

Mult, Polk, 

Wash, 

Yamh

ORBIC 

2013

IBI

Western 

ridged 

mussel

Gonidea 

angulata RR - 203,020 352,336(174%)

366,093

(180%)

345,512

(170%)

315,192

(155%)

367,742

(181%)

367,790

(181%)

369,320

(182%)

within 1 

SPTH of 

streams3

Bent, Clac, 

Coos, Curr, 

Doug, Klam, 

Linn, Mult, 

Wash

ORBIC 

2013

IBI Montane 

peaclam

Pisidium 

ultramontanum RR - 1,687 2,541(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 

SPTH of 

streams3

Klam ORBIC 

2013

IG Puget 

oregonian

Cryptomastix 

devia Late A 69,849 104,370(149%)

90,137

(129%)

91,866

(132%)

75,737

(109%)

95,953

(137%)

89,577

(128%)

119,919

(172%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Clac, Colu, 

Mult, 

Wash, 

Yamh

GeoBOB 

2013;

Duncan et 

al. 2003
1671 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IG Olympia 

pebblesnail

Fluminicola 

virens RR - 170,252 297,448 (175%)

310,252

(182%)

290,660

(171%)

264,102

(155%)

311,556

(183%)

307,530

(181%)

313,030

(184%)

within 1 

SPTH of 

streams3

Bent, Clac, 

Colu, Doug, 

Linn, Mari, 

Mult, Wash, 

Yamh

ISSSP Fact 

Sheet 2012; 

ORBIC 

2013

IG Great basin 

ramshorn

Helisoma 

newberryi 

newberryi

RR - 1,687 2,541

(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 

SPTH of 

streams3

Klam ISSSP Fact 

Sheet 2010

IG Oregon 

shoulderband

Helminthoglypta 

hertleini NF - 1,079 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Rock

(GNN 3)

Doug, Jack, 

Jose

ORBIC 

2013

IG Highcap lanx Lanx alta RR - 1,687 2,541

(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 

SPTH of 

streams3

Klam ISSSP Fact 

Sheet 2009

IG Scale lanx Lanx 

klamathensis RR - 1,687 2,541(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 

SPTH of 

streams3

Klam ORBIC 

2013

IG Rotund lanx Lanx 

subrotunda RR - 105,894 187,135(177%)

196,261

(185%)

185,370

(175%)

169,778

(160%)

197,307

(186%)

194,352

(184%)

198,321

(187%)

within 1 

SPTH of 

streams3

Doug ISSSP Fact 

Sheet 2010

IG Newcomb’s 

littorine snail

Littorina 

subrotundata NF - 82 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Marine, 

estuarine

(GNN 11)

Coos, Linc ISSSP Fact 

Sheet

IG Travelling 

sideband

Monadenia 

fidelis celeuthia NF - 628 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Rock

(GNN 3) Jack ORBIC 2013

IG Columbia 

sideband

Monadenia 

fidelis 

columbiana

RR - 4,136 5,824

(141%)

5,983

(145%)

5,326

(129%)

3,979

(96%)

5,983

(145%)

5,918

(143%)

5,983

(145%)

Mesic forest; 

within 1 

SPTH of 

streams3

Mult, Wash ISSSP Fact 

Sheet 2011

IG Green 

sideband

Monadenia 

fidelis flava Mid - 32,579 39,971 (123%)

39,578 

(121%)

41,972 

(129%)

35,767 

(110%)

36,032 

(111%)

42,303

(130%)

45,292 

(139%)

Young High 

Density with 

Structural 

Legacies 

(3.1), Mature 

(4.1, 4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Curry GeoBOB 

2013

IG Modoc Rim 

sideband

Monadenia 

fidelis ssp. nov. 

(Modoc Rim)

NF - 252 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Rock, talus

(GNN 3) Klam ORBIC 2013
1672 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IG Robust 

walker

Pomatiopsis 

binneyi RR - 59,062 80,437(136%)

81,754

(138%)

80,420

(136%)

79,949

(135%)

81,858

(139%)

80,572

(136%)

82,135

(139%)

within 1 

SPTH of 

streams3

Curr, Jose ORBIC 

2013

IG Pacific 

walker

Pomatiopsis 

californica RR - 94,824 164,133(173%)

168,075

(177%)

158,126

(167%)

139,688

(147%)

168,303

(177%)

165,644

(175%)

168,478

(178%)

within 1 

SPTH of 

streams3

Coos, Lane ORBIC 

2013

IG Crater Lake 

tightcoil

Pristiloma 

crateris Late A

§

420,914 564,206

(134%)

612,093

(146%)

611,835

(145%)

533,140

(127%)

644,678

(153%)

598,183

(142%)

708,674

(168%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Polygon of 

counties 

clipped east 

of I-5

Duncan et 

al. 2003

IG Crowned 

tightcoil

Pristiloma 

pilsbryi Late - 21,451 40,295 (188%)

41,433 

(193%)

40,519 

(189%)

41,541 

(194%)

41,529 

(194%)

40,405

(188%)

42,009 

(196%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Till GeoBOB 

2013

IG Shiny 

tightcoil

Pristiloma 

wascoense

X - No Data No Data No Data No Data No Data No Data No Data No Data Ponderosa 

pine forests

Coos, Doug, 

Jack, Mari 

ISSSP Fact 

Sheet

IG Siskiyou 

hesperian

Vespericola 

sierranus Late - 326,439 365,529(112%)

432,746

(133%)

447,793

(137%)

425,035

(130%)

447,354

(137%)

434,541

(133%)

457,772

(140%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Jack, Jose ORBIC 

2013

IG Lined 

ramshorn

Vorticifex 

effusus 

diagonalis

RR - 1,687 2,541

(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 

SPTH of 

streams3

Klam ORBIC 

2013

IICO Siuslaw sand 

tiger beetle

Cicindela 

hirticollis 

siuslawensis

NF - 1,178 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Coastal sand 

dunes

(GNN 5)

Coos, Lane, 

Linc, Till

ORBIC 

2013

IIHY Franklin’s 

bumblebee

Bombus 

franklini NF - 5,117 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Variety of 

flowering 

plants; prairie

(GNN 6, 7)

Doug, Jack, 

Jose

ORBIC 

2013

IIHY Western 

bumblebee

Bombus 

occidentalis NF - 6,430 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Variety of 

flowering 

plants; prairie

(GNN 6, 7)

Clac, Coos, 

Doug, Jack, 

Jose, Klam, 

Lane, Linc, 

Polk

ORBIC 

2013
1673 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IILE Johnson’s 

hairstreak

Callophrys 

johnsoni Late - 1,104,899 1,549,987 (140%)

1,638,115 

(148%)

1,651,075 

(149%)

1,467,275 

(133%)

1,726,938 

(156%)

1,637,746

(148%)

1,831,210 

(166%)

Mature (4.1, 

4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

All NatureServe 

2014

IILE Gray-blue 

butterfly

Plebejus 

podarce 

klamathensis

NF - 2,461 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wet montane 

meadows

(GNN 6)

Doug, Jack, 

Klam

ISSSP Fact 

Sheet 2006

IILE

Coastal 

greenish blue 

butterfly

Plebejus 

saepiolus 

littoralis

NF - 288 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Coastal sand 

dunes

(GNN 5)

Curr, Lane ORBIC 

2013

IILE Mardon 

skipper Polites mardon NF - 2,256 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Meadows

(GNN 6) Curr, Jack

Cons. 

Assess. 

USFWS 

2010

IILE Coronis 

fritillary

Speyeria 

coronis coronis NF - 4,549 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Variety of 

flowering 

plants; prairie

(GNN 6, 7)

Jack, Jose ORBIC 

2013

IIOR

Siskiyou 

short-horned 

grasshopper

Chloealtis 

aspasma

Early - 23,336 44,302 

(190%)

19,290 

(83%)

10,357 

(44%)

21,021 

(90%)

11,604 

(50%)

13,582

(58%)

10,130 

(43%)

Earlysuccessional 

(1.1, 1.2)

Jack, Jose NatureServe 

2014

IITR

Scott’s 

apatanian 

caddisfly

Allomyia scotti RR - 13,583 23,743

(175%)

24,627

(181%)

23,346

(172%)

22,011

(162%)

24,711

(182%)

24,623

(181%)

25,004

(184%)

within 1 

SPTH of 

streams3

Clac ORBIC 

2013

IITR A caddisfly Rhyacophila 

chandleri RR - 164,657 287,787(175%)

300,136

(182%)

282,179

(171%)

254,726

(155%)

301,221

(183%)

296,375

(180%)

302,353

(184%)

within 1 

SPTH of 

streams3

Doug, Lane ORBIC 

2013

IITR

Haddock’s 

rhyacophilan 

caddisfly

Rhyacophila 

haddocki RR - 24,774 39,200(158%)

40,210

(162%)

37,959

(153%)

35,501

(143%)

40,393

(163%)

39,813

(161%)

40,490

(163%)

within 1 

SPTH of 

streams3

Bent, Curr ORBIC 

2013

IITR A caddisfly Rhyacophila 

leechi RR - 96,838 155,487(161%)

160,063

(165%)

151,993

(157%)

137,910

(142%)

160,119

(165%)

157,493

(163%)

160,420

(166%)

within 1 

SPTH of 

streams3

Jack, Lane ORBIC 

2013
1674 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

MA Pallid bat Antrozous 

pallidus Mid - 1,026,908 1,348,033 (131%)

1,435,273 

(140%)

1,471,780 

(143%)

1,305,381 

(127%)

1,522,475 

(148%)

1,462,784

(142%)

1,571,763 

(153%)

Young with 

Structural 

Legacies 

(3.1, 3.3), 

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Coos, Curr, 

Doug, Jack, 

Jose, Klam, 

Lane

NatureServe 

2014

MA Oregon red 

tree vole

Arborimus 

longicaudus Late C 174,495 289,971 (166%)

279,899 

(160%)

279,489 

(160%)

236,047 

(135%)

294,208 

(169%)

277,503

(159%)

313,820 

(180%)

Mature (4.1, 

4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

Defined 

DPS 

Polygon

USFWS 

2011

MA Pygmy rabbit

Brachylagus 

idahoensis 

(Outside 

Columbia Basin)

NF - 63,877 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Sagebrush 

(GNN 8) Klam ORBIC 2013

MA Townsend’s 

big-eared bat

Corynorhinus 

townsendii X - No Data No Data No Data No Data No Data No Data No Data No Data Caves, Mines

Bent, Clac, 

Clat, Coos, 

Curr, Doug, 

Jack, Jose, 

Klam, Lane, 

Mari, Mult, 

Till, Wash

ORRBIC 

2013

MA Spotted bat Euderma 

maculatum - - - - - - - - - - -

Not in 

Decision 

Area: E.

Oregon

ORBBIC 

2013

MA Pacific 

marten Martes caurina Late - 168,181 289,336(172%)

283,384

(168%)

289,229

(172%)

262,261

(156%)

301,325

(179%)

291,717

(173%)

332,169 

(198%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Within 25 

miles of the 

Pacific 

Coast

Assumed 

based on 80 

FR 18749
1675 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

MA Fringed 

myotis

Myotis 

thysanodes Mid - 1,192,066 1,604,929 (135%)

1,672,747 

(140%)

1,721,310 

(144%)

1,522,102 

(128%)

1,782,578

(150%)

1,710,422

(147%)

1,855,364

(156%)

Young with 

Structural 

Legacies 

(3.1, 3.3), 

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Bent, Clac, 

Clat, Colu, 

Coos, Curr, 

Doug, Jack, 

Jose, Klam, 

Lane, Linc, 

Linn, Till, 

Wash

GeoBOB 

2013; 

NatureServe 

2014; 

ORBIC 

2013

MA

Columbian 

white-tailed 

deer

Odocoileus 

virginianus 

leucurus 

(Douglas Co.)

Early - 767 295

(38%)

712

(93%)

747

(97%)

589

(77%)

426

(56%)

577

(75%)

0

(0%)

See Chapter 

3

See 

Chapter 3

See Chapter 

3

Bureau 

Sensitive 

Summary§

n=71 species 

total

n=66 species 

modeled - - -

35 incr.

30 same

1 decr.

4 undet.

33 incr.

30 same

3 decr.

4 undet.

34 incr.

30 same

2 decr.

4 undet.

31 incr.

30 same

5 decr.

4 undet.

33 incr.

30 same

3 decr.

4 undet.

34 incr.

30 same

2 decr.

4 undet.

32 incr.

30 same

4 decr.

4 undet.

-

1 species 

not in 

Decision 

Area

-

* Hab. Group = general categorization of the habitat association assumed by the BLM in this analysis for each species: 

 Early = early-successional forest associate, 

 Mid = mid-seral forest associate, 

 Late = mature, late-successional, or old-growth forest associate, 

 NF = non-forest associate, 

 Oak = oak woodland associate, 

 Wet = wetland associate, 

 RR = stream or riparian-area associate, 

 X = no habitat association used in this analysis. 

† S&M Cat. = Survey and Manage Category based on the December 2003 list (USDA, USDI 2011). Individual categories are summarized below following 2001 ROD Survey and 

Manage Standards and Guidelines (pp. 7–13). 

‡ within 1 SPTH of streams = assumption that habitat for wildlife species associated with streams or near-streams would be modeled by the amount of mature (4.1, 4.2) and 

structurally-complex (5.1, 5.2, 5.3) forest within 1 site potential tree height of the stream. This assumes that, in general, favorable habitat conditions (cool water temperatures, 

shade, abundant down wood) are more prevalent in mature and older forests. 

§ Summary = number of species that under the alternatives would have: an increase (incr.) in habitat available, no change (same) in habitat available, a decrease (decr.) in the 

amount of habitat available, or the habitat availability is undetermined (undet.) or habitat data is unavailable. 

Note: Counties are abbreviated as follows: Bent = Benton, Clac = Clackamas, Clat = Clatsop, Colu = Columbia, Coos = Coos, Curr = Curry, Doug = Douglas, Jack = Jackson, Jose 

= Josephine, Klam = Klamath, Lane = Lane, Linc = Lincoln, Linn = Linn, Mari = Marion, Mult = Multnomah, Polk = Polk, Till = Tillamook, Wash = Washington, Yamh = 

Yamhill. 
1676 | P a g e

Bureau Strategic Wildlife Species 

Table S-34. Habitat development for Bureau Strategic wildlife species documented or suspected to occur in the decision area 

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

BI Rhinoceros 

auklet

Cerorhinca 

monocerata

NF - 236 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Marine, 

estuarine 

(GNN 11)

Clat, Coos, 

Curr, Doug, 

Lane, Linc, 

Till

ORBIC 

2013

BI Trumpeter 

swan

Cygnus 

buccinator Wet - 2,896 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change Wetland layer

Clat, Colu, 

Klam, 

Mult, Polk

ORBIC 

2013

BI Merlin Falco 

columbarius NF - 1,342 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Open areas; 

agricultural, 

grasslands, 

shrub lands

(GNN 2, 6, 7)

Klam ORBIC 

2013

BI Canadian 

sandhill crane

Grus 

canadensis 

rowani

Wet - 150 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change Wetland layer Mult ORBIC 2013

BI Least bittern Ixobrychus 

exilis Wet - 1,625 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change Wetland layer Klam ORBIC 2013

ICL Oregon giant 

earthworm

Driloleirus 

macelfreshi X - No Data No Data No Data No Data No Data No Data No Data No Data Subterranean, loose soils

Bent, Linc, 

Linn, Mari, 

Polk, Yamh

ORBIC 

2013

IG Cascades 

axetail slug

Carinacauda 

stormi Late N 237,164 366,778 (155%)

353,113 

(149%)

353,116 

(149%)

299,286 

(126%)

382,037 

(161%)

352,816

(149%)

422,835 

(178%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Clac, Lane, 

Linn, 

Marion

GeoBOB 

2013; 

NatureServe 

2014

IG Columbia 

duskysnail

Colligyrus sp.

nov. (Columbia) RR - 14,555 25,014(172%)

26,010

(179%)

24,553

(169%)

23,019

(158%)

26,094

(179%)

25,978

(178%)

26,387

(181%)

within 1 SPTH 

of streams3 Clac, Mult ORBIC 2013

IG Casebeer 

pebblesnail

Fluminicola sp.

nov. (Casebeer) RR - 1,687 2,541(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 SPTH 

of streams3 Klam ORBIC 2013

IG Fall Creek 

pebblesnail

Fluminicola sp.

nov. (Fall 

Creek)

RR - 38,075 54,835

(144%)

56,188

(148%)

55,183

(145%)

52,961

(139%)

56,205

(148%)

55,471

(146%)

56,389

(148%)

within 1 SPTH 

of streams3 Jack ORBIC 2013

IG Keene Creek 

pebblesnail

Fluminicola sp. 

nov. (Keene 

Creek)

RR - 39,761 57,376

(144%)

58,731 

(148%)

57,677

(145%)

55,102

(139%)

58,751

(148%)

57,941

(146%)

58,935

(148%)

within 1 SPTH 

of streams3 Jack, Klam ORBIC 2013
1677 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IG Klamath Rim 

pebblesnail

Fluminicola sp. 

nov. (Klamath 

Rim)

RR A

§

1,687 2,541

(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 SPTH 

of streams3 Klam

Frest & 

Johannes 

1999; 

ORBIC 

2013

IG Klamath 

pebblesnail

Fluminicola sp. 

nov. (Klamath) RR - 1,687 2,541(151%)

2,544

(151%)

2,494

(151%)

2,141 

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 SPTH 

of streams3 Klam ORBIC 2013

IG Lost River 

pebblesnail

Fluminicola sp. 

nov. (Lost 

River)

RR - 1,687 2,541

(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 SPTH 

of streams3 Klam ORBIC 2013

IG Odessa 

pebblesnail

Fluminicola sp. 

nov. (Odessa) RR - 1,687 2,541(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 SPTH 

of streams3 Klam ORBIC 2013

IG Toothed 

pebblesnail

Fluminicola sp. 

nov. (Toothed) RR - 38,075 54,835(144%)

56,188

(148%)

55,183

(145%)

52,961

(139%)

56,205

(148%)

55,471

(146%)

56,389

(148%)

within 1 SPTH 

of streams3 Jack ORBIC 2013

IG Salamander 

slug

Gliabates 

oregonius RR - 58,763 100,652(171%)

103,875

(177%)

96,809

(165%)

84,948

(145%)

103,914

(177%)

102,023

(174%)

104,032

(177%)

within 1 SPTH 

of streams3 Lane ISSSP Fact Sheet 2013

IG Barren juga Juga hemphilli 

hemphilli RR - 972 1,271(131%)

1,383

(142%)

1,207

(124%)

1,008

(104%)

1,383

(142%)

1,355

(139%)

1,383

(142%)

within 1 SPTH 

of streams3 Mult ORBIC 2013

IG Chace 

sideband

Monadenia 

chaceana Late B

ǀǀ 648,117 838,467

(129%)

953,640

(147%)

958,674

(148%)

872,477

(135%)

986,526 

(152%)

946,902 

(146%)

1,028,012

(159%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Doug, Jack, 

Jose, Klam

Duncan et 

al. 2003

IG Marsh walker Pomatiopsis 

chacei RR - 9,124 13,502(148%)

14,044

(154%)

13,328

(146%)

12,843

(141%)

14,209

(156%)

14,057

(154%)

14,284

(157%)

within 1 SPTH 

of streams3 Curr ORBIC 2013

IG Broadwhorl 

tightcoil

Pristiloma 

johnsoni Late - 472,142 714,295 (151%)

746,446 

(158%)

738,105 

(156%)

641,727 

(136%)

791,217 

(168%)

741,862

(157%)

833,514 

(177%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Curr, 

Doug, Lane

GeoBOB 

2013

IG Pristine 

springsnail

Pristinicola 

hemphilli RR - 88,985 123,040(138%)

125,281

(141%)

123,483

(139%)

121,075

(136%)

125,237

(141%)

123,340 

(139%)

125,622

(141%)

within 1 SPTH 

of streams3

Jack, Jose, 

Mult

ISSSP Fact 

Sheet
1678 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IG Klamath taildropper

Prophysaon sp. 

nov. (Klamath) Mid - 220,138 234,750 (106%)

293,885 

(133%)

300,640 

(136%)

268,344 

(122%)

294,427 

(133%)

288,412

(131%)

308,387 

(140%)

Young High 

Density with 

Structural 

Legacies (3.1), 

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Jack, Klam GeoBOB 

2013

IG Lost River 

springsnail

Pyrgulopsis sp. 

nov. (Lost 

River)

RR - 1,687 2,541

(151%)

2,544

(151%)

2,494

(151%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 SPTH 

of streams3 Klam ORBIC 2013

IG Dalles 

hesperian

Vespericola 

depressa X - - - - - - - - - -

Not in 

Decision 

Area: Gill, 

Sher, Wasc

ORBBIC 

2013

IG Bald 

hesperian

Vespericola sp. 

nov. (Bald) Wet - 650 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change Wetland layer Lane ORBIC 2013

IICO Marsh ground 

beetle

Acupalpus 

punctulatus Wet - 1,516 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change Wetland layer Bent, Wash ORBIC 2013

IICO Hairy necked 

tiger beetle

Cicindela 

hirticollis 

couleensis

NF - 1,011 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Coastal sand 

dunes

(GNN 5)

Coos ISSSP Fact 

Sheet

IICO Roth’s blind 

ground beetle

Pterostichus 

rothi Late - 40,332 64,866(161%)

64,479

(160%)

63,695

(158%)

58,462

(145%)

67,553

(167%)

63,437

(157%)

69,731

(173%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Bent, Linc ISSSP Fact 

Sheet

IIHE Cooley’s lace 

bug

Acalypta 

cooleyi Late - 163,406 177,635(109%)

224,263

(137%)

231,321

(142%)

209,035

(128%)

229,227

(140%)

220,940

(135%)

56,389

(148%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Jack ORBIC 

2013

IIHE Lillian’s lace 

bug

Acalypta 

lillianis Late - 147,809 230,879(156%)

226,505

(153%)

225,131

(152%)

186,360

(126%)

245,405

(166%)

225,724

(153%)

261,909

(177%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Lane ORBIC 

2013
1679 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IIHE American 

grass bug

Acetropis 

americana NF - 2,850 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Wet grasslands 

(Wetlands 

layer)

Bent, 

Yamh

ORBIC 

2013

IIHE Umbrose 

seed bug

Atrazonotus 

umbrosus X - Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Bent, Mari, Polk

ORBIC 

2013

IIHE

American 

uniqueheaded bug

Boreostolus

americanus X - Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Jack, Lane, Linn

ORBIC 

2013

IIHE Salien plant 

bug

Criocoris 

saliens X - Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Bent, Till ORBIC 2013

IIHE Arizona stink 

bug

Dendrocoris 

arizonensis Oak - 21,677 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Oak 

woodlands Bent, Jack ISSSP Fact Sheet

IIHE Foliaceous 

lace bug

Derephysia 

foliacea NF - 90 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Mountain 

meadows

(GNN 6)

Bent, Lane ORBIC 

2013

IIHE Heidemann’s 

damsel bug

Hoplistoscelis 

heidemanni X - Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Bent, Curr ORBIC 2013

IIHE

Martin’s 

watermeasurer

Hydrometra 

martini RR - 15,649 25,697(164%)

26,166

(167%)

24,631

(157%)

22,658

(145%)

26,184

(167%)

25,756

(165%)

26,206

(167%)

within 1 SPTH 

of streams3 Bent ORBIC 2013

IIHE Oregon plant 

bug Lygus oregonae NF - 1

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Coastal sand 

dunes (GNN 5) Linc, Till ORBIC 2013

IIHE Essig’s plant 

bug

Macrotylus 

essigi Oak - 0

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Oak 

woodlands Lane ORBIC 2013

IIHE Obrien’s seed 

bug

Malezonotus 

obrieni Late - 147,809 230,879(156%)

226,505

(153%)

225,131

(152%)

186,360

(126%)

245,405

(166%)

225,724

(153%)

261,909

(177%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Lane ISSSP Fact 

Sheet

IIHE Mulsant’s 

water treader

Mesovelia 

mulsanti RR - 49,474 90,554(183%)

92,595

(187%)

86,939

(176%)

81,198

(164%)

92,926

(188%)

91,969

(186%)

93,178

(188%)

within 1 SPTH 

of streams3

Bent, Linn, 

Till, Yamh

ORBIC 

2013

IIHE Marsh damsel 

bug

Nabicula 

propinqua X - Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Coos, Till ORBIC 2013

IIHE True fir plant 

bug

Pinalitus 

solivagus X - Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Bent, Jose, Lane

ORBIC 

2013

IIHE Hairy shore 

bug Saldula villosa NF - 68 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Salt marsh 

(GNN 11) Coos ORBIC 2013
1680 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IIHE

California 

shield-backed 

bug

Vanduzeeina 

borealis 

californica

NF - 89 No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Grassland, 

meadows

(GNN 6)

Lane ORBIC 

2013

IILE Hoary elfin Callophrys 

polios maritima NF - 122 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

Coastal sand 

dunes

(GNN 5)

Curr, Linc ORBIC 

2013

IILE

Oregon 

branded 

skipper

Hesperia 

colorado 

oregonia

X - Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Unknown Jack, Jose ORBIC 

2013

IILE Dog star 

skipper

Polites sonora 

siris NF - 156 No Change

No 

Change

No 

Change

No 

Change

No 

Change

No 

Change

No

Change

Grassland, 

meadow

(GNN 6)

Bent, Clat, 

Lane, Linn, 

Mult, 

Yamh

ORBIC 

2013

IIPL A stonefly Capnia kersti RR - 58,763 100,652

(171%)

103,875

(177%)

96,809

(165%)

84,948

(145%)

103,914

(177%)

102,023

(174%)

104,032

(177%)

within 1 SPTH 

of streams3 Lane ORBIC 2013

IITR

Denning’s 

agapetus 

caddisfly

Agapetus 

denningi RR - 38,075 54,835(144%)

56,188

(148%)

55,183

(145%)

52,961

(139%)

56,205

(148%)

55,471

(146%)

56,389

(148%)

within 1 SPTH 

of streams3 Jack ORBIC 2013

IITR

Green 

Springs 

Mountain 

farulan 

caddisfly

Farula davisi RR - 38,075 54,835

(144%)

56,188

(148%)

55,183

(145%)

52,961

(139%)

56,205

(148%)

55,471

(146%)

56,389

(148%)

within 1 SPTH 

of streams3 Jack ORBIC 2013

IITR

Schuh’s 

homoplectran 

caddisfly

Homoplectra 

schuhi RR - 39,761 57,376(144%)

58,731

(148%)

57,677

(145%)

55,102

(139%)

58,751

(148%)

57,941

(146%)

58,935

(148%)

within 1 SPTH 

of streams3 Jack, Klam ORBIC 2013

IITR A caddisfly Lepania 

cascada RR - 20,423 34,609(169%)

35,417

(173%)

33,876

(166%)

31,842

(156%)

35,507

(174%)

35,015

(171%)

35,537

(174%)

within 1 SPTH 

of streams3 Bent, Linc ORBIC 2013

IITR A caddisfly Moselyana 

comosa

RR - 233,650 394,603

(169%)

409,661

(175%

387,834

(166%)

354,497

(152%)

410,867

(176%)

404,695

(173%)

412,497

(177%)

within 1 SPTH 

of streams3

Bent, Clac, 

Doug, Jack, 

Klam, Lane

ORBIC 

2013

IITR A caddisfly Namamyia 

plutonis RR - 176,244 268,808(153%)

275,473

(156%)

263,871

(150%)

246,207

(140%)

275,665

(156%)

271,320

(154%)

276,281

(157%)

within 1 SPTH 

of streams3

Bent, Curr, 

Jack, Jose, 

Lane, Mari

ORBIC 

2013

IITR

Tombstone 

Prairie 

caddisfly

Oligophlebodes 

mostbento RR - 181,543 318,200(175%)

332,404

(183%)

311,879

(172%)

281,770

(155%)

333,633

(184%)

328,366

(181%)

334,882

(184%)

within 1 SPTH 

of streams3

Doug, 

Lane, Linn

ORBIC 

2013
1681 | P a g e

Taxon

Species

Hab. 

Group*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

IITR

O’brien 

rhyacophilan 

caddisfly

Rhyacophila 

colonus RR - 49,938 66,934(134%)

67,710

(136%)

67,093

(134%)

67,106

(134%)

67,649

(135%)

66,515

(133%)

67,851

(136%)

within 1 SPTH 

of streams3 Jose ORBIC 2013

IITR

One-spot 

rhyacophilan 

caddisfly

Rhyacophila 

unipunctata RR - 58,763 100,652(171%)

103,875

(177%)

96,809

(165%)

84,948

(145%)

103,914

(177%)

102,023

(174%)

104,032

(177%)

within 1 SPTH 

of streams3 Lane ORBIC 2013

MA

Gold beach 

pocket 

gopher

Thomomys 

mazama helleri X - No Data No Data No Data No Data No Data No Data No Data No Data Subterranean, loose soils Curr ORBIC 2013

Bureau 

Strategic 

Summary§

n=61 species 

total

n=51 species 

modeled - - -

34 incr.

17 same

0 decr.

9 undet.

34 incr.

17 same

0 decr.

9 undet.

34 incr.

17 same

0 decr.

9 undet.

34 incr.

17 same

0 decr.

9 undet.

34 incr.

17 same

0 decr.

9 undet.

34 incr.

17 same

0 decr.

9 undet.

34 incr.

17 same

0 decr.

9 undet.

-

1 species 

not in 

Decision 

Area

-

* Hab. Group = general categorization of the habitat association assumed by the BLM in this analysis for each species: 

 Early = early-successional forest associate, 

 Mid = mid-seral forest associate, 

 Late = mature, late-successional, or old-growth forest associate, 

 NF = non-forest associate, 

 Oak = oak woodland associate, 

 Wet = wetland associate, 

 RR = stream or riparian-area associate, 

 X = no habitat association used in this analysis. 

† S&M Cat. = Survey and Manage Category based on the December 2003 list (USDA, USDI 2011). Individual categories are summarized below following 2001 ROD Survey and 

Manage Standards and Guidelines (pp. 7–13). 

‡ within 1 SPTH of streams = assumption that habitat for wildlife species associated with streams or near-streams would be modeled by the amount of mature (4.1, 4.2) and 

structurally-complex (5.1, 5.2, 5.3) forest within 1 site potential tree height of the stream. This assumes that, in general, favorable habitat conditions (cool water temperatures, 

shade, abundant down wood) are more prevalent in mature and older forests. 

§ Summary = number of species that under the alternatives and the Proposed RMP would have: an increase (incr.) in habitat available, no change (same) in habitat available, a 

decrease (decr.) in the amount of habitat available, or the habitat availability is undetermined (undet.) or habitat data is unavailable. 

ǀǀ Based upon direction contained in the ROD, equivalent-effort pre-disturbance surveys are required for these mollusk species. 

Note: Counties are abbreviated as follows: Bent = Benton, Clac = Clackamas, Clat = Clatsop, Colu = Columbia, Coos = Coos, Curr = Curry, Doug = Douglas, Gill = Gilliam, Jack 

= Jackson, Jose = Josephine, Klam = Klamath, Lane = Lane, Linc = Lincoln, Linn = Linn, Mari = Marion, Mult = Multnomah, Polk = Polk, Sher = Sherman, Till = Tillamook, 

Wasc = Wasco, Wash = Washington, Yamh = Yamhill. 
1682 | P a g e

Survey and Manage Wildlife Species 

Table S-35. Survey and Manage wildlife species: habitat development 

Taxonomic 

Group

Species

SSS 

Status*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source 

for 

Species 

Range

Common 

Name Scientific Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Amphibians Shasta 

Salamander

Hydromantes 

shastae - A

Not in 

Decision 

Area: 

California

Olson et 

al. 1999

Amphibians

Larch 

Mountain 

Salamander

Plethodon 

larselli - A

Not in 

Decision 

Area: 

Washington

GeoBOB 

2015; 

State 

Director’s 

SSSP list 

(July 13, 

2015)

Amphibians

Siskiyou 

Mountains 

Salamander

Plethodon 

stormi BS D

‡

326,439 365,523

(112%)

432,740

(133%)

447,786

(137%)

425,029

(130%)

447,347

(137%)

434,541

(132%)

457,766

(140%)

Mature (4.1, 

4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3)

Jack, Jose Olson et 

al. 1999

Amphibians Van Dyke’s 

Salamander

Plethodon 

vandykei - A

Not in 

Decision 

Area: 

Washington

GeoBOB 

2013; 

Olson et 

al. 1999
1683 | P a g e

Taxonomic 

Group

Species

SSS 

Status*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source 

for 

Species 

Range

Common 

Name Scientific Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds Great Gray 

Owl Strix nebulosa - A 45,157 116,913 (259%)

77,909 

(172%)

91,599 

(203%)

88,930 

(197%)

42,922 

(95%)

64,255

(142%)

17,354 

(38%)

Young High 

Density with 

Structural 

Legacies (3.1), 

Mature (4.1, 

4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3) or 

GNN NonForest 

Grassland, 

Shrub land, 

Sagebrush (6, 

7, 8) that is < 

650 feet from 

meadows or 

openings (1.1, 

1.2) ≥ 10 acres 

in size

Doug, Jack, 

Jose, Klam, 

Lane, Linn

GeoBOB 

2013

Mammals Red Tree Vole Arborimus 

longicaudus - C 926,858 1,260,016(136%)

1,358,216 

(147%)

1,371,586 

(148%)

1,231,228 

(133%)

1,432,730 

(155%)

1,360,243

(146%)

1,517,390 

(164%)

Mature (4.1, 

4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

All - outside 

defined 

polygon for 

North 

Oregon 

Coast DPS

USFWS 

2011

Mammals

North Oregon 

Coast DPS of 

the Red Tree 

Vole

Arborimus 

longicaudus BS C 174,495 289,971 (166%)

279,899 

(160%)

279,489 

(160%)

236,047 

(135%)

294,208 

(169%)

277,503

(159%)

313,820 

(180%)

Mature (4.1, 

4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

Defined 

DPS 

Polygon; see 

Chapter 3

USFWS 

2011

Mollusks:

Terrestrial

Puget 

Oregonian

Cryptomastix 

devia BS A 69,848 104,370(149%)

90,137

(129%)

91,866

(132%)

75,737

(109%)

95,953

(137%)

89,577

(128%)

119,919

(172%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Clac, Colu, 

Mult, Wash, 

Yamh

GeoBOB 

2013;

Duncan et 

al. 2003

Mollusks:

Terrestrial

Columbian 

Gorge 

Oregonian

Cryptomastix 

hendersoni - A

Not in 

Decision 

Area

Duncan et 

al. 2003
1684 | P a g e

Taxonomic 

Group

Species

SSS 

Status*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source 

for 

Species 

Range

Common 

Name Scientific Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Mollusks:

Terrestrial

Evening 

Fieldslug

Deroceras 

hesperium - B

ǀǀ 546,866 710,856

(130%)

768,810

(141%)

780,754

(143%)

712,028

(130%)

797,683

(146%)

762,415

(139%)

855,358

(156%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Bent, Clac, 

Clat, Colu, 

Jack, Jose, 

Klam, Linc, 

Linn, Mari, 

Mult, Polk, 

Till, Wash, 

Yamh

Duncan et 

al. 2003

Mollusks: 

Aquatic

Klamath Rim 

Pebblesnail

Flumincola n. 

sp. 3 BStr A

§

1,687 2,541

(151%)

2,544

(151%)

2,494

(148%)

2,141

(127%)

2,546

(151%)

2,470

(146%)

2,546

(151%)

within 1 SPTH 

of streams# Klam

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Fredenberg 

Pebblesnail

Flumincola n. 

sp. 11 - A

§

38,075 54,835

(144%)

56,188

(148%)

55,183

(145%)

52,961

(139%)

56,205

(148%)

55,471

(146%)

56,389

(148%)

within 1 SPTH 

of streams# Jack

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Potem 

Pebblesnail

Flumincola n. 

sp. 14 - A

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Flat-top 

Pebblesnail

Flumincola n. 

sp. 15 - A

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Shasta 

Pebblesnail

Flumincola n. 

sp. 16 - A

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Disjunct 

Pebblesnail

Flumincola n. 

sp. 17 - A

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Globular 

Pebblesnail

Flumincola n. 

sp. 18 - A

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Umbilicate 

Pebblesnail

Flumincola n. 

sp. 19 - A

§

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999
1685 | P a g e

Taxonomic 

Group

Species

SSS 

Status*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source 

for 

Species 

Range

Common 

Name Scientific Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Mollusks: 

Aquatic

Lost Creek 

Pebblesnail

Flumincola n. 

sp. 20 - A

§

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Nugget 

Pebblesnail

Flumincola 

seminalis - A

§

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Terrestrial

Trinity 

Shoulderband

Helminthoglypta 

talmadgei - D

‡

Not in 

Decision 

Area

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Keeled 

Jumping-slug

Hemphillia 

burringtoni - E

Not in 

Decision 

Area: 

Washington

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Warty 

Jumping-slug

Hemphillia 

glandulosa - E 108,955 185,830(171%)

171,962

(158%)

170,873

(157%)

148,725

(137%)

180,893

(166%)

167,061

(153%)

196,818

(181%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Bent, Clat, 

Colu, Linc, 

Polk, Till, 

Wash, 

Yamh

GeoBOB 

2013;

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Malone 

Jumping-slug

Hemphillia 

malonei - C 92,029 138,358(150%)

129,886

(141%)

130,366

(142%)

114,988

(125%)

140,038

(152%)

129,910

(141%)

164,778

(179%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Clac, Linn, 

Mari, Mult

GeoBOB 

2013;

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Panther 

Jumping-slug

Hemphillia 

pantherina - B

ǀǀ

Not in 

Decision 

Area: 

Washington

Duncan et 

al. 2003

Mollusks: 

Aquatic Basalt Juga Juga (O) n. sp. 2 - A

Not in 

Decision 

Area: Hood, 

Wasco

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Cinnamon 

Juga Juga (O) n. sp. 3 - A

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Columbia 

Duskysnail

Lyogyrus n. sp. 

1

- A 14,555 25,014

(172%)

26,010

(179%)

24,553

(169%)

23,019

(158%)

26,094

(179%)

25,978

(178%)

26,387

(181%)

within 1 SPTH 

of streams#

Clac, Hood, 

Mult

Frest and

Johannes 

1999
1686 | P a g e

Taxonomic 

Group

Species

SSS 

Status*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source 

for 

Species 

Range

Common 

Name Scientific Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Mollusks: 

Aquatic

Washington 

(Masked) 

Duskysnail

Lyogyrus n. sp. 

2

- A

Not in 

Decision 

Area: 

Washington

Frest and

Johannes 

1999

Mollusks: 

Aquatic

Canary 

Duskysnail

Lyogyrus n. sp. 

3

- A

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

Mollusks: 

Terrestrial

Chace 

Sideband

Monadenia 

chaceana BStr B

ǀǀ 645,732 838,467

(130%)

953,640

(148%)

958,674

(148%)

872,477

(135%)

986,526

(153%)

946,902

(146%)

1,028,012

(159%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Doug, Jack, 

Jose, Klam

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Dalles 

Sideband

Monadenia 

fidelis minor - A

Not in 

Decision 

Area: 

Columbia 

Gorge

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Shasta 

Sideband

Monadenia 

troglodytes 

troglodytes

- A

Not in 

Decision 

Area: 

California

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Wintu 

Sideband

Monadenia 

troglodytes 

wintu

- A

Not in 

Decision 

Area: 

California

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Chelan 

Mountainsnail Oreohelix n. sp. - A

Not in 

Decision 

Area: 

Washington

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Crater Lake 

Tightcoil

Pristiloma 

arcticum 

crateris

BS A

§

420,914 564,206

(134%)

612,093

(146%)

611,835

(145%)

533,140

(127%)

644,678

(153%)

598,183

(142%)

708,674

(168%)

Mature (4.1, 

4.2), and 

Structurallycomplex (5.1, 

5.2, 5.3)

Polygon of 

counties 

clipped east 

of I-5

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Blue-gray 

Taildropper

Prophysaon 

coeruleum - A

Not S&M in 

Oregon; 

S&M in 

California 

and 

Washington

S&M list

(Dec. 

2003)
1687 | P a g e

Taxonomic 

Group

Species

SSS 

Status*

S&M 

Cat.†

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(Counties)

Source 

for 

Species 

Range

Common 

Name Scientific Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Mollusks: 

Terrestrial

Shasta 

Chaparral

Trilobopsis 

roperi - A

Not in 

Decision 

Area: 

California

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Tehama 

Chaparral

Trilobopsis 

tehamana - A

Not in 

Decision 

Area: 

California

Duncan et 

al. 2003

Mollusks: 

Terrestrial Hoko Vertigo Vertigo n. sp. - A

Not in 

Decision 

Area: 

Washington

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Big Bar 

Hesperian

Vespericula 

pressleyi - A

Not in 

Decision 

Area: 

California

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Shasta 

Hesperian

Vespericula 

Shasta - A

Not in 

Decision 

Area: 

California

Duncan et 

al. 2003

Mollusks: 

Terrestrial

Knobby 

Rams-horn

Vorticifex n. sp. 

1

- E

Not in 

Decision 

Area: 

California

Frest and

Johannes 

1999

S&M 

Summary

**

n=43 species 

total

n = 13 species 

modeled - - -

13 incr.

0 same

0 decr.

30 undet.

13 incr.

0 same

0 decr.

30 undet.

13 incr.

0 same

0 decr.

30 undet.

13 incr.

0 same

0 decr.

30 undet.

12 incr.

0 same

1 decr.

30 undet.

13 incr.

0 same

0 decr.

30 undet.

12 incr.

0 same

1 decr.

30 undet.

n=43 species 

total

30 species 

not in 

Decision 

Area

-

* SSS Status = Special Status Species status: BS = Bureau Sensitive, BStr = Bureau Strategic, FP = Federal Proposed (also Bureau Sensitive), FC = Federal Candidate (also 

Bureau Sensitive). 

† S&M Cat. = Survey and Manage Category based on the December 2003 list (USDA, USDI 2011). Individual categories are summarized below following 2001 ROD Survey and 

Manage Standards and Guidelines (pp. 7–13): 

A = Rare, pre-disturbance surveys practical. Manage all known sites and minimize inadvertent loss of undiscovered sites. 

B = Rare, pre-disturbance surveys not practical. Manage all known sites and minimize inadvertent loss of undiscovered sites. 

C = Uncommon, pre-disturbance surveys practical. Identify and manage high-priority sites to provide for reasonable assurance of species persistence. Until high-priority 

sites can be determined, manage all known sites. 

D = Uncommon, pre-disturbance surveys not practical or not necessary. Identify and manage high-priority sites to provide for reasonable assurance of species 

persistence. Until high-priority sites can be determined, manage all known sites. 

E = Rare, status undetermined. Manage all known sites while determining if the species meets the basic criteria for Survey and Manage and, if so, to which category (A, 

B, C, or D) it should be assigned. 
1688 | P a g e

F = Uncommon or concern for persistence unknown, status undetermined. Determine if the species meets the basic criteria for Survey and Manage and, if so, to which 

category (A, B, C, or D) it should be assigned. 

‡ Although pre-disturbance Surveys are deemed practical for this species, continuing pre-disturbance surveys is not necessary in order to meet management objectives. 

§ For these species, until Management Recommendations are written, the following language will be considered part of the Management Recommendation: “Known and newly 

discovered sites of these species will be protected from grazing by all practical steps to ensure that the local population of the species will not be impacted.”

ǀǀ Based upon direction contained in the ROD, equivalent-effort pre-disturbance surveys are required for these mollusk species. 

# within 1 SPTH of streams = assumption that habitat for wildlife species associated with streams or near-streams would be modeled by the amount of mature (4.1, 4.2) and 

structurally-complex (5.1, 5.2, 5.3) forest within 1 site potential tree height of the stream. This assumes that, in general, favorable habitat conditions (cool water temperatures, 

shade, abundant down wood) are more prevalent in mature and older forests. 

** Summary = number of species that under the alternatives and the Proposed RMP would have: an increase (incr.) in habitat available, no change (same) in habitat available, a 

decrease (decr.) in the amount of habitat available, or the habitat availability is undetermined (undet.) or habitat data is unavailable. 

Note: Counties are abbreviated as follows: Bent = Benton, Clac = Clackamas, Clat = Clatsop, Colu = Columbia, Coos = Coos, Curr = Curry, Doug = Douglas, Gill = Gilliam, 

Hood = Hood River, Jack = Jackson, Jose = Josephine, Klam = Klamath, Lane = Lane, Linc = Lincoln, Linn = Linn, Mari = Marion, Mult = Multnomah, Polk = Polk, Sher = 

Sherman, Till = Tillamook, Wasc = Wasco, Wash = Washington, Yamh = Yamhill. 
1689 | P a g e

Table S-36. Survey and Manage wildlife species: land use allocations of known sites in the decision area 

Taxon

Species

SSS 

Status*

S&M 

Cat.†

2007 

Outcome‡

Number of Known Sites

Common Name Scientific Name

(# Sites) (# Sites in Reserved Land-Use Allocations)

Total Sites No Action Alt. A Alt. B Alt. C Alt. D PRMP

Amphibians Larch Mountain 

Salamander Plethodon larselli - A

Insufficient 

Habitat in Part - - - - - - -

Amphibians Siskiyou Mountains 

Salamander Plethodon stormi BS D

Insufficient 

Habitat in Part 213 46 204 177 170 100 184

Birds Great Gray Owl Strix nebulosa - A

Insufficient 

Habitat in Part 1,228#

247 1,014 726 820 739 800

Mammals

Red Tree Vole

(outside of the North 

Oregon Coast DPS)

Arborimus longicaudus - C

Sufficient 

Habitat 7,957 2,669 6,822 5,407 5,175 5,719 5,854

Mammals North Oregon Coast DPS 

of the Red Tree Vole Arborimus longicaudus BS C

Insufficient 

Habitat in Part 395 355 374 370 354 366 357

Mollusks: 

Terrestrial Puget Oregonian Cryptomastix devia BS A

Sufficient 

Habitat 2 2 2 2 2 2 2

Mollusks: 

Terrestrial Evening Fieldslug Deroceras hesperium - B

ǀǀ Sufficient 

Habitat 20 17 16 16 16 17 15

Mollusks: 

Aquatic Klamath Rim Pebblesnail Flumincola n. sp. 3 BStr A

§ Sufficient 

Habitat 3 3 3 3 3 3 3

Mollusks: 

Aquatic Fredenberg Pebblesnail Flumincola n. sp. 11 - A

§ Sufficient 

Habitat 5 5 5 5 5 4 5

Mollusks: 

Terrestrial Warty Jumping-slug Hemphillia glandulosa - E

Sufficient 

Habitat 363 320 319 296 285 237 314

Mollusks: 

Terrestrial Malone Jumping-slug Hemphillia malonei - C

Sufficient 

Habitat 300 97 226 142 113 127 120

Mollusks: 

Aquatic Columbia Duskysnail Lyogyrus n. sp. 1 - A

Sufficient 

Habitat 3 3 3 2 2 3 3

Mollusks: 

Terrestrial Chace Sideband Monadenia chaceana BStr B

ǀǀ Insufficient 

Habitat in Part 114 26 95 87 86 62 91

Mollusks: 

Terrestrial Crater Lake Tightcoil Pristiloma arcticum crateris BS A

§ Sufficient 

Habitat 1 1 1 1 1 1 1

Subtotal by S&M Category

n=7 A - 1,242 261 1,028 739 833 752 814

n=2 B - 134 43 111 103 102 79 106

n=3 C - 8,652 3,121 7,422 5,919 5,642 6,212 6,331

n=1 D - 213 46 204 177 170 100 184

n=1 E - 363 320 319 296 285 237 314

Totals n=14 n=14 - - - 10,60419,767 3,791

(36%)

9,084

(86%)

7,234

(68%)

14,064

(66%)

14,76080

(70%)

7,749

(73%)
1690 | P a g e

* SSS Status = Special Status Species status: BS = Bureau Sensitive, BStr = Bureau Strategic, FP = Federal Proposed (also Bureau Sensitive), FC = Federal Candidate (also 

Bureau Sensitive). 

† S&M Cat. = Survey and Manage Category based on the December 2003 list (USDA, USDI 2011). Individual categories are summarized below following 2001 ROD Survey and 

Manage Standards and Guidelines (pp. 7-13): 

A = Rare, pre-disturbance surveys practical. Manage all known sites and minimize inadvertent loss of undiscovered sites. 

B = Rare, pre-disturbance surveys not practical. Manage all known sites and minimize inadvertent loss of undiscovered sites. 

C = Uncommon, pre-disturbance surveys practical. Identify and manage high-priority sites to provide for reasonable assurance of species persistence. Until high-priority 

sites can be determined, manage all known sites. 

D = Uncommon, pre-disturbance surveys not practical or not necessary. Identify and manage high-priority sites to provide for reasonable assurance of species 

persistence. Until high-priority sites can be determined, manage all known sites. 

E = Rare, status undetermined. Manage all known sites while determining if the species meets the basic criteria for Survey and Manage and, if so, to which category (A, 

B, C, or D) it should be assigned. 

F = Uncommon or concern for persistence unknown, status undetermined. Determine if the species meets the basic criteria for Survey and Manage and, if so, to which 

category (A, B, C, or D) it should be assigned. 

‡ 2007 Outcomes = Outcomes for Survey and Manage species from the 2007 Final Supplement to the 2004 Supplemental Environmental Impact Statement to Remove or Modify 

the Survey and Manage Mitigation Measure Standards and Guidelines (June 2007). The outcomes summarized here are from the 2007 Supplement Alternative 2 where Survey and 

Manage was removed (USDA FS and USDI BLM 2007, pp. 261–262, 278–279, 280–281, 285–286, 291–292): 

Sufficient Habitat = Habitat (including known sites) is sufficient to support stable populations range-wide. 

Insufficient Habitat in Part = Habitat (including known sites) is sufficient to support stable populations range-wide, but habitat or known sites are insufficient to 

support stable populations in a portion of the taxa’s range.

§ For these species, until Management Recommendations are written, the following language will be considered part of the Management Recommendation: “Known and newly 

discovered sites of these species will be protected from grazing by all practical steps to ensure that the local population of the species will not be impacted.”

ǀǀ Based upon direction contained in the ROD, equivalent-effort pre-disturbance surveys are required for these mollusk species. 

# For the great gray owl, the reported “Number of Known Sites” is the number of fauna observations in GeoBOB, and the actual number of known great gray owl “sites” is 

substantially less than these values. However, the numbers of great gray owl observations do provide an indicator of relative differences among the alternatives and the Proposed 

RMP.
1691 | P a g e

Landbird Focal Species 

Table S-37. Habitat development for landbird focal species 

Taxon

Species

Hab. 

Group§

Landbird 

Focal 

Species

(Y/N)

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(By 

County)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds: 

Landbird 

Focal 

Species

Blackthroated Gray 

Warbler

Setophaga 

nigrescens Early Y

*

387,247 139,443 

(36%)

107,772 

(28%)

24,419 

(6%)

170,143 

(44%)

64,049 

(17%)

101,930

(26%)

22,334 

(6%)

Stand 

Establishment 

(2.1, 2.2)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Blue (Sooty) 

Grouse

Dendragapus 

fuliginosus 

sierra

Early Y

*

490,308 284,485 

(58%)

225,647 

(46%)

188,073 

(38%)

339,836 

(69%)

152,395 

(31%)

208,730

(43%)

74,967 

(15%)

Earlysuccessional 

(1.1, 1.2), Stand 

Establishment 

(2.1, 2.2), or 

Young Low 

Density (3.3, 

3.4)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Brown 

Creeper

Certhia 

Americana Late Y

*, ‡

1,101,353 1,549,987 

(141%)

1,638,115 

(149%)

1,651,075 

(150%)

1,467,275 

(133%)

1,726,938 

(157%)

1,637,746

(149%)

1,831,210 

(166%)

Mature (4.1, 

4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Chipping 

Sparrow

Spicella 

passerine Early Y

‡

53,459 110,566 

(206%)

80,089 

(150%)

118,312 

(221%)

131,002 

(245%)

46,001 

(86%)

65,418

(122%)

14,418 

(27%)

Earlysuccessional 

(1.1, 1.2)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Common 

Nighthawk

Chordeiles 

minor Early Y

†

62,141 119,248 

(192%)

88,771 

(143%)

126,994 

(204%)

139,684 

(225%)

54,683 

(88%)

74,100

(119%)

23,100 

(37%)

Earlysuccessional 

(1.1, 1.2) or 

GNN NonForest 

Agricultural, 

Grassland, 

Shrub land (2, 

6, 7)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Fox Sparrow Passerlla 

iliaca Early Y

*

53,459 110,566 

(206%)

80,089 

(150%)

118,312 

(221%)

131,002 

(245%)

46,001 

(86%)

65,418

(122%)

14,418 

(27%)

Earlysuccessional 

(1.1, 1.2)

All NatureServe 

2014
1692 | P a g e

Taxon

Species

Hab. 

Group§

Landbird 

Focal 

Species

(Y/N)

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(By 

County)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds: 

Landbird 

Focal 

Species

Grasshopper 

Sparrow

Ammodramus 

savannarum

Early Y

†

26,225 55,477 

(211%)

35,188 

(134%)

53,134 

(203%)

57,469 

(219%)

23,533 

(90%)

35,805

(137%)

11,938 

(46%)

Earlysuccessional 

(1.1, 1.2) or 

GNN NonForest 

Agricultural, 

Grassland, 

Shrub land (2, 

6, 7)

Jack, 

Lane, 

Linn, 

Polk

NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Hammond’s 

Flycatcher

Empidonax 

hammondii Mid Y

*

1,087,922 1,234,282 

(113%)

1,187,686 

(109%)

1,239,055 

(114%)

1,147,394 

(105%)

1,251,205 

(115%)

1,225,721

(113%)

1,302,043 

(119%)

Young High 

Density (3.1, 

3.2) or Mature 

(4.1, 4.2)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Hermit 

Thrush

Catharus 

guttatus

Mid Y

*

1,087,922 1,234,282 

(113%)

1,187,686 

(109%)

1,239,055 

(114%)

1,147,394 

(105%)

1,251,205 

(115%)

1,225,721

(113%)

1,302,043 

(119%)

Young High 

Density (3.1, 

3.2) or Mature 

(4.1, 4.2)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Hermit 

Thrush

Catharus 

guttatus

Late Y

‡

860,528 961,980 

(112%)

1,058,410 

(123%)

1,087,349 

(126%)

962,201 

(112%)

1,141,298 

(133%)

1,072,105

(125%)

1,136,633 

(132%)

Mature Multilayered Canopy 

(4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Hermit 

Warbler

Setophaga 

occidentalis Mid Y

*

1,087,922 1,234,282 

(113%)

1,187,686 

(109%)

1,239,055 

(114%)

1,147,394 

(105%)

1,251,205 

(115%)

1,225,721

(113%)

1,302,043 

(119%)

Young High 

Density (3.1, 

3.2) or Mature 

(4.1, 4.2)

All

Avian 

Knowledge 

Northwest 

2014

Birds: 

Landbird 

Focal 

Species

Lark Sparrow Chondestes 

grammacus

Early Y

†

43,492 82,557 

(190%)

46,993 

(108%)

61,264 

(141%)

67,724 

(156%)

32,339 

(74%)

42,325

(97%)

17,938 

(41%)

Earlysuccessional 

(1.1, 1.2) or 

GNN NonForest 

Agricultural, 

Grassland, 

Shrub land (2, 

6, 7)

Bent, 

Jack, 

Jose, 

Klam, 

Lane, 

Linn, 

Mult, 

Till

Avian 

Knowledge 

Northwest 

2014
1693 | P a g e

Taxon

Species

Hab. 

Group§

Landbird 

Focal 

Species

(Y/N)

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(By 

County)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds: 

Landbird 

Focal 

Species

Lazuli 

Bunting

Passerina 

amoena

Early Y

*

62,141 119,248 

(192%)

88,771 

(143%)

126,994 

(204%)

139,684 

(225%)

54,683 

(88%)

74,100

(119%)

23,100 

(37%)

Earlysuccessional 

(1.1, 1.2) or 

GNN NonForest 

Agricultural, 

Grassland, 

Shrub land (2, 

6, 7)

All –

except 

Clat

Avian 

Knowledge 

Northwest 

2014

Birds: 

Landbird 

Focal 

Species

Lewis’ 

Woodpecker

Melanerpes 

lewis Early Y

†, ‡

16,743 89,420 

(534%)

12,249 

(73%)

70,832 

(423%)

8,716 

(52%)

31,361 

(187%)

43,067

(257%)

16,361 

(98%)

Earlysuccessional 

with Structural 

Legacies (1.1) 

or GNN NonForest Shrub 

land (7)

Colu, 

Doug, 

Jack, 

Jose, 

Klam, 

Lane, 

Mult

GeoBOB 

2013,N

Birds: 

Landbird 

Focal 

Species

Nashville 

Warbler

Oreothlypis 

ruficapilla Early Y

*, ‡

484,873 284,381 

(59%)

117,859 

(24%)

187,919 

(39%)

339,513 

(70%)

152,196 

(18%)

208,276

(43%)

74,890 

(15%)

Earlysuccessional 

(1.1, 1.2), Stand 

Establishment 

(2.1, 2.2), or 

Young Low 

Density (3.3, 

3.4) within the 

Klamath 

Province

All –

except 

Linc

Avian 

Knowledge 

Northwest 

2014

Birds: 

Landbird 

Focal 

Species

Northern 

Flicker

Colaptes 

auratus

Early Y

*

85,200 228,649 

(268%)

14,382 

(17%)

121,639 

(143%)

13,940 

(16%)

89,418 

(105%)

139,580

(164%)

15,589 

(18%)

Earlysuccessional 

with Structural 

Legacies (1.1) 

or Stand 

Establishment 

with Structural 

Legacies (2.1)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Olive-sided 

Flycatcher

Contopus 

cooperi Early Y

*, ‡

405,075 249,722 

(62%)

117,859 

(29%)

141,484 

(35%)

179,698 

(44%)

108,880 

(27%)

165,488

(41%)

36,629 

(9%)

Earlysuccessional 

with Structural 

Legacies (1.1) 

or Stand 

Establishment 

(2.1, 2.2)

All NatureServe 

2014
1694 | P a g e

Taxon

Species

Hab. 

Group§

Landbird 

Focal 

Species

(Y/N)

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(By 

County)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds: 

Landbird 

Focal 

Species

Orange 

Crowned 

Warbler

Oreothlypis 

celata Early Y

*

53,459 110,566 

(206%)

80,089 

(150%)

118,312 

(221%)

131,002 

(245%)

46,001 

(86%)

65,418

(122%)

14,418 

(27%)

Earlysuccessional 

(1.1, 1.2)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Oregon 

Vesper 

Sparrow

Pooecetus 

gramineus 

affinis

Early Y

†

5,726 28,774 

(503%)

26,868 

(469%)

58,696 

(1025%)

48,788 

(852%)

18,086 

(316%)

31,193

(545%)

1,798 

(31%)

Earlysuccessional 

(1.1, 1.2) or 

GNN NonForest 

Agricultural, 

Grassland, 

Shrub land (2, 

6, 7)

Bent, 

Clac, 

Lane, 

Linn, 

Mari, 

Polk

NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Pacific-slope 

Flycatcher

Empidonax 

difficilis Late Y

*

1,101,353 1,549,987 

(141%)

1,638,115 

(149%)

1,651,075 

(150%)

1,467,275 

(133%)

1,726,938 

(157%)

1,637,746

(149%)

1,831,210 

(166%)

Mature (4.1, 

4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3)

All

Avian 

Knowledge 

Northwest 

2014

Birds: 

Landbird 

Focal 

Species

Pileated 

Woodpecker

Dryocarpus 

pileatus Late Y

*

860,528 961,980 

(112%)

1,058,410 

(123%)

1,087,349 

(126%)

962,201 

(112%)

1,141,298 

(133%)

1,072,105

(125%)

1,136,633 

(132%)

Mature Multilayered Canopy 

(4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

All

Avian 

Knowledge 

Northwest 

2014

Birds: 

Landbird 

Focal 

Species

Purple Finch Haemorphus 

purpureus

Mid Y

*

1,430,557 1,289,215 

(90%)

1,356,356 

(95%)

1,409,909

(99%)

1,316,798 

(92%)

1,423,674 

(100%)

1,387,328

(97%)

1,392,683 

(97%)

Young High 

Density (3.1, 

3.2), Mature 

Multi-layered 

Canopy (4.2), 

or Structurallycomplex (5.1, 

5.2, 5.3)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Pygmy 

Nuthatch

Sitta 

pygmaea

Late Y

‡

10,331 9,439 

(91%)

20,835 

(202%)

20,054 

(194%)

15,014 

(145%)

16,935 

(164%)

19,291

(187%)

17,195 

(166%)

Mature Multilayered Canopy 

(4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

Klam

Avian 

Knowledge 

Northwest 

2014
1695 | P a g e

Taxon

Species

Hab. 

Group§

Landbird 

Focal 

Species

(Y/N)

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(By 

County)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds: 

Landbird 

Focal 

Species

Rufous 

Hummingbird

Selasphorous 

rufus Early Y

*

490,308 284,485 

(58%)

225,647 

(46%)

188,073 

(38%)

339,836 

(69%)

152,395 

(31%)

208,730

(43%)

74,967 

(15%)

Earlysuccessional 

(1.1, 1.2), Stand 

Establishment 

(2.1, 2.2), or 

Young Low 

Density (3.3, 

3.4)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Streaked 

Horned Lark

Eremophila 

alpestris 

strigata

Early Y

†

2,671 20,421 

(765%)

17,796 

(666%)

36,245 

(1357%)

29,977 

(1122%)

13,939 

(522%)

19,846

(743%)

1,092 

(41%)

Earlysuccessional 

(1.1, 1.2) or 

GNN NonForest 

Agricultural, 

Grassland, 

Shrub land (2, 

6, 7).

Bent, 

Clac, 

Linn, 

Mari, 

Polk, 

Yamh

NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Townsend’s 

Warbler

Setophaga 

townsedi Mid Y

*

1,087,922 1,234,282 

(113%)

1,187,686 

(109%)

1,239,055 

(114%)

1,147,394

(105%)

1,251,205 

(115%)

1,225,721

(113%)

1,302,043 

(119%)

Young High 

Density (3.1, 

3.2) or Mature 

(4.1, 4.2)

All

Avian 

Knowledge 

Northwest 

2014

Birds: 

Landbird 

Focal 

Species

Varied 

Thrush

Ixoreus 

naevius Late Y

*

860,528 961,980 

(112%)

1,058,410 

(123%)

1,087,349 

(126%)

962,201 

(112%)

1,141,298 

(133%)

1,072,105

(125%)

1,136,633 

(132%)

Mature Multilayered Canopy 

(4.2) or 

Structurallycomplex (5.1, 

5.2, 5.3)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Vaux’s Swift Chaetura 

vauxi Mid Y

*

988,947 1,090,906 

(110%)

1,156,869 

(117%)

1,219,648 

(123%)

1,062,341 

(107%)

1,267,362 

(128%)

1,205,529

(122%)

1,239,197 

(125%)

Young High 

Density with 

Structural 

Legacy (3.1), 

Mature Multilayered Canopy 

(4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3)

All NatureServe 

2014
1696 | P a g e

Taxon

Species

Hab. 

Group§

Landbird 

Focal 

Species

(Y/N)

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(By 

County)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds: 

Landbird 

Focal 

Species

Western 

Meadowlark

Sturnella 

neglecta Early Y

†

62,141 119,248 

(192%)

88,771 

(143%)

126,994 

(204%)

139,684 

(225%)

54,683 

(88%)

74,100

(119%)

23,100 

(37%)

Earlysuccessional 

(1.1, 1.2) or 

GNN NonForest 

Agricultural, 

Grassland, 

Shrub land (2, 

6, 7)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Western 

Tanager

Piranga 

ludoviciana Early Y

*

436,849 173,919 

(40%)

145,558 

(33%)

69,761 

(16%)

208,834 

(48%)

106,394 

(24%)

143,312

(33%)

60,549 

(14%)

Stand 

Establishment 

(2.1, 2.2) or 

Young Low 

Density (3.3, 

3.4)

All NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

WhiteHeaded 

Woodpecker

Picoides 

albolarvatus Early Y

‡

18,751 72,725 

(388%)

11,882 

(63%)

40,209 

(214%)

8,567 

(46%)

24,085 

(128%)

33,642

(179%)

15,923 

(85%)

Earlysuccessional 

with Structural 

Legacies (1.1) 

or GNN NonForest Shrub 

land (7)

Doug, 

Jack, 

Jose, 

Klam

GeoBOB 

2013; 

NatureServe 

2014

Birds: 

Landbird 

Focal 

Species

Williamson’s 

Sapsucker

Sphyrapicus 

thyroideus Early Y

‡

87,168 215,195 

(247%)

23,098 

(26%)

101,787 

(117%)

22,457 

(26%)

84,237 

(97%)

120,243

(138%)

24,061 

(28%)

Earlysuccessional 

with Structural 

Legacies (1.1), 

Stand 

Establishment 

with Structural 

Legacies (2.1), 

or Young Low 

Density with 

Structural 

Legacies (3.3)

Bent, 

Clac, 

Doug, 

Jack, 

Jose, 

Klam, 

Lane, 

Linn

Avian 

Knowledge 

Northwest 

2014; 

GeoBOB 

2013

Birds: 

Landbird 

Focal 

Species

Wilson’s 

Warbler

Cardellina 

pusilla Mid Y

*

1,137,525 1,268,758 

(112%)

1,225,473 

(108%)

1,284,396 

(113%)

1,186,085 

(104%)

1,293,550 

(114%)

1,267,103

(111%)

1,340,257 

(118%)

Young (3.1, 

3.2, 3.3, 3.4) or 

Mature (4.1, 

4.2)

All NatureServe 

2014
1697 | P a g e

Taxon

Species

Hab. 

Group§

Landbird 

Focal 

Species

(Y/N)

Amount of Habitat (Acres) (Percent) Structural 

Stage(s) for 

Habitat 

Analysis 

(Numeric 

Codes)

Species 

Range 

(By 

County)

Source for 

Species 

Range

Common 

Name

Scientific 

Name

in 2013 in 2063

Current No 

Action Alt. A Alt. B Alt. C Alt. D PRMP

No 

Timber 

Harvest

Birds: 

Landbird 

Focal 

Species

Winter Wren Troglodytes 

hiemalus Mid Y

*

1,230,613 1,670,659 

(136%)

1,432,214 

(116%)

1,776,612 

(144%)

1,559,493 

(127%)

1,845,313 

(150%)

1,764,358

(143%)

1,925,362 

(156%)

Young with 

Structural 

Legacies (3.1, 

3.3), Mature 

(4.1, 4.2), or 

Structurallycomplex (5.1, 

5.2, 5.3)

All –

except 

Linc

Avian 

Knowledge 

Northwest 

2014

Landbird 

Summaryǀǀ

n=34 species 

total

n=34 species 

modeled - - -

26 incr.

0 same

8 decr.

0 undet.

23 incr.

0 same

11 decr.

0 undet.

27 incr.

0 same

7 decr.

0 undet.

23 incr.

0 same

11 decr.

0 undet.

18 incr.

0 same

16 decr.

0 undet.

26 incr.

0 same

8 decr.

0 undet.

13 incr.

0 same

21 decr.

0 undet.

- - -

* Altman and Alexander (2012) 

† Altman (2000a) 

‡ Altman (2000b) 

§ Hab. Group = general categorization of the habitat association assumed by the BLM in this analysis for each species: 

 Early = early-successional forest associate, 

 Mid = mid-seral forest associate, 

 Late = mature, late-successional, or old-growth forest associate, 

 NF = non-forest associate, 

 Oak = oak woodland associate, 

 Wet = wetland associate, 

 RR = stream or riparian-area associate, 

 X = no habitat association used in this analysis. 

ǀǀ Summary = number of species that under the alternatives would have: an increase (incr.) in habitat available, no change (same) in habitat available, a decrease (decr.) in the 

amount of habitat available, or the habitat availability is undetermined (undet.) or habitat data is unavailable. 

Note: Counties are abbreviated as follows: Bent = Benton, Clac = Clackamas, Clat = Clatsop, Colu = Columbia, Coos = Coos, Curr = Curry, Doug = Douglas, Gill = Gilliam, Jack 

= Jackson, Jose = Josephine, Klam = Klamath, Lane = Lane, Linc = Lincoln, Linn = Linn, Mari = Marion, Mult = Multnomah, Polk = Polk, Sher = Sherman, Till = Tillamook, 

Wasc = Wasco, Wash = Washington, Yamh = Yamhill. 
1698 | P a g e

Columbian White-tailed Deer 

High-quality forage habitat would vary among the alternatives over time. High-quality forage habitat in 

oak woodlands would not vary among the alternatives. The BLM calculated high-quality forage habitat 

from Woodstock vegetation model (i.e., early successional structural stages) output. The BLM calculated 

the amount of oak woodland from a separate data layer used by the RMP interdisciplinary team to map 

forest site moisture conditions that included potential vegetation data (lsc_moistdry_pvt_aoi_a_v3_rst). 

These two models overlap spatially, and, while the acreage is informative of relative conditions of deer 

forage habitat, they are not additive.

Table S-38. High-quality forage habitat development for the Columbian white-tailed deer within the 

range of the Lower Columbia River population in the decision area 

Year No Action

(Acres)

Alt. A

(Acres)

Alt. B

(Acres)

Alt. C

(Acres)

Alt. D

(Acres)

PRMP

(Acres)

No Timber 

Harvest

(Acres)

Oak 

Woodland

(Acres)

Current Condition

2013 459 459 459 459 459 459 459 -

Alternatives/Proposed RMP

2023 459 2,973 2,392 3,956 1,905 2,832 459 -

2033 389 3,885 2,575 5,015 1,494 2,772 - -

2043 1,823 2,227 3,519 2,606 584 1,569 - -

2053 2,103 3,477 4,340 3,963 1,347 1,584 - -

2063 987 3,220 3,779 5,316 1,688 1,488 - -

Table S-39. High-quality forage habitat development for the Columbian white-tailed deer within the 

range of the Lower Columbia River population in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

No Timber 

Harvest 

(Acres)

Oak 

Woodland

(Acres)

Current Condition

2013 55,952 55,952 55,952 55,952 55,952 55,952 55,952 -

Alternatives/Proposed RMP

2023 55,952 58,466 57,885 59,450 57,399 58,326 55,952 -

2033 55,794 59,290 57,981 60,420 56,900 58,177 55,405 -

2043 57,229 57,632 58,924 58,011 55,990 56,975 55,405 -

2053 57,509 58,882 59,745 59,368 56,752 56,989 55,405 -

2063 56,393 58,626 59,184 60,721 57,094 56,894 55,405 -
1699 | P a g e

Table S-40. High-quality forage habitat development in conifer forest for the Columbian white-tailed 

deer within the range of the Douglas County population in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

No Timber

Harvest 

(Acres)

Oak 

Woodland

(Acres)

Current Condition

2013 767 767 767 767 767 767 767 1,545

Alternatives/Proposed RMP

2023 1,038 1,317 1,030 1,184 1,171 1,019 729 1,545

2033 1,587 1,676 1,200 1,944 1,370 1,443 684 1,545

2043 1,384 1,342 1,310 1,445 1,054 1,253 432 1,545

2053 983 1,080 1,412 1,160 1,119 1,231 432 1,545

2063 295 712 747 589 426 577 - 1,545

Table S-41. High-quality forage habitat development in conifer forest for the Columbian white-tailed 

deer within the range of the Douglas County population in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP 

(Acres)

No Timber 

Harvest 

(Acres)

Oak 

Woodland

(Acres)

Current Condition

2013 19,439 19,439 19,439 19,439 19,439 19,439 19,439 52,458

Alternatives/Proposed RMP

2023 19,709 19,988 19,701 19,855 19,842 19,691 19,401 52,458

2033 20,258 20,347 19,871 20,615 20,041 20,114 19,356 52,458

2043 20,055 20,013 19,981 20,116 19,726 19,924 19,104 52,458

2053 19,660 19,751 20,083 19,832 19,790 19,902 19,104 52,458

2063 18,966 19,383 19,418 19,260 19,098 19,248 18,671 52,458
1700 | P a g e

Deer and Elk 

Table S-42. High-quality forage habitat development for deer and elk in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 46,249 46,249 46,249 46,249 46,249 53,459 46,249

Alternatives/Proposed RMP

2023 92,216 91,012 81,747 138,088 69,273 86,427 43,016

2033 101,496 97,831 73,281 180,450 51,793 74,945 9,667

2043 100,324 86,622 105,364 145,343 44,531 78,167 12,233

2053 111,095 79,930 132,251 127,038 47,977 81,505 14,105

2063 110,566 80,089 118,311 131,001 46,001 65,418 14,418

Table S-43. High-quality forage habitat development for deer and elk in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 1,112,694 1,112,694 1,112,694 1,112,694 1,112,694 1,119,906 1,112,694

Alternatives/Proposed RMP

2023 1,158,661 1,157,457 1,148,192 1,204,533 1,135,718 1,152,874 1,109,463

2033 1,088,405 1,084,740 1,060,190 1,167,359 1,038,702 1,061,857 996,579

2043 1,087,233 1,073,531 1,092,273 1,132,252 1,031,440 1,065,079 999,145

2053 1,098,004 1,066,839 1,119,160 1,113,947 1,034,886 1,068,417 1,001,017

2063 1,097,475 1,066,998 1,105,220 1,117,910 1,032,910 1,052,330 1,001,331
1701 | P a g e

Fisher 

Fisher Habitat 

Table S-44. Total fisher habitat (denning, resting, foraging combined) in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 574,219 574,219 574,219 574,219 574,219 571,355 574,219

Alternatives/Proposed RMP

2023 540,312 562,929 566,950 556,936 566,614 563,194 571,406

2033 508,448 557,325 564,704 544,409 564,162 557,166 570,339

2043 506,615 579,756 593,507 567,035 591,213 582,294 593,899

2053 514,442 609,830 633,093 600,094 626,542 617,289 623,829

2063 527,502 632,336 662,866 620,639 653,341 645,588 644,357

Table S-45. Fisher denning habitat in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 324,478 324,478 324,478 324,478 324,478 319,503 324,478

Alternatives/Proposed RMP

2023 298,161 320,609 317,328 308,951 315,449 311,941 326,958

2033 288,378 333,386 331,912 320,253 332,599 323,791 345,024

2043 277,816 343,220 343,245 329,545 344,426 335,129 353,797

2053 286,468 364,269 360,761 346,072 366,379 350,910 376,841

2063 292,012 387,886 376,867 365,611 389,533 366,541 398,633

Table S-46. Fisher resting habitat in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 153,657 153,657 153,657 153,657 153,657 156,753 153,657

Alternatives/Proposed RMP

2023 148,819 148,504 149,972 149,670 154,827 153,634 151,470

2033 125,316 132,781 135,607 130,593 137,631 137,063 132,291

2043 150,131 157,106 163,113 153,280 161,670 161,721 164,213

2053 153,310 168,252 188,158 172,182 178,813 184,880 172,239

2063 143,410 162,066 193,001 167,697 172,961 188,043 160,996
1702 | P a g e

Table S-47. Fisher foraging habitat in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 96,084 96,084 96,084 96,084 96,084 95,100 96,084

Alternatives/Proposed RMP

2023 93,332 93,816 99,650 98,315 96,338 97,619 92,977

2033 94,755 91,157 97,184 93,563 93,932 96,312 93,024

2043 78,668 79,430 87,149 84,210 85,117 85,444 75,889

2053 74,664 77,310 84,173 81,840 81,350 81,499 74,748

2063 92,080 82,384 92,998 87,331 90,847 91,004 84,728

Table S-48. Total fisher habitat (denning, resting, foraging combined) in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 4,484,755 4,484,755 4,484,755 4,484,755 4,484,755 4,481,891 4,484,755

Alternatives/Proposed RMP

2023 4,450,848 4,473,465 4,477,486 4,467,472 4,477,150 4,473,729 4,481,942

2033 4,519,548 4,568,425 4,575,804 4,555,509 4,575,262 4,568,266 4,581,440

2043 4,554,018 4,627,160 4,640,911 4,614,438 4,638,616 4,629,697 4,641,302

2053 4,561,846 4,657,234 4,680,496 4,647,498 4,673,945 4,664,693 4,671,232

2063 4,574,905 4,679,739 4,710,269 4,668,042 4,700,745 4,692,992 4,691,760

Table S-49. Fisher denning habitat in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 639,570 639,570 639,570 639,570 639,570 634,595 639,570

Alternatives/Proposed RMP

2023 613,253 635,701 632,420 624,044 630,541 627,033 642,051

2033 603,470 648,479 647,005 635,345 647,691 638,884 660,117

2043 592,908 658,313 658,338 644,638 659,518 650,222 668,889

2053 892,611 970,411 966,903 952,215 972,521 957,052 982,983

2063 898,154 994,028 983,009 971,753 995,675 972,684 1,004,775
1703 | P a g e

Table S-50. Fisher resting habitat in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 825,681 825,681 825,681 825,681 825,681 828,777 825,681

Alternatives/Proposed RMP

2023 820,843 820,527 821,996 821,693 826,851 825,658 823,494

2033 797,339 804,805 807,630 802,617 809,654 809,086 804,315

2043 822,155 829,129 835,136 825,303 833,693 833,744 836,236

2053 534,284 549,226 569,132 553,156 559,787 565,853 553,213

2063 1,241,308 1,259,963 1,290,899 1,265,595 1,270,859 1,285,940 1,258,894

Table S-51. Fisher foraging habitat in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 3,019,504 3,019,504 3,019,504 3,019,504 3,019,504 3,018,519 3,019,504

Alternatives/Proposed RMP

2023 3,016,752 3,017,236 3,023,070 3,021,735 3,019,758 3,021,038 3,016,397

2033 3,118,739 3,115,142 3,121,169 3,117,548 3,117,916 3,120,296 3,117,008

2043 3,138,956 3,139,718 3,147,436 3,144,497 3,145,405 3,145,732 3,136,177

2053 3,134,951 3,137,597 3,144,461 3,142,127 3,141,637 3,141,787 3,135,035

2063 2,435,443 2,425,748 2,436,361 2,430,694 2,434,211 2,434,368 2,428,091
1704 | P a g e

Table S-52. Land use allocations of fisher habitat under the No Action alternative on BLM-administered 

lands 

Year

Within the HLB* Within Reserves*

Total

(Acres) (Percent) (Acres) (Percent) (Acres)

Denning

2013 139,018 43% 185,460 57% 324,478

2023 113,292 38% 184,869 62% 298,161

2033 95,654 33% 192,723 67% 288,378

2043 81,691 29% 196,124 71% 277,816

2053 79,107 28% 207,362 72% 286,468

2063 74,084 25% 217,928 75% 292,012

Resting

2013 84,954 55% 68,704 45% 153,657

2023 81,595 55% 67,224 45% 148,819

2033 65,345 52% 59,971 48% 125,316

2043 78,367 52% 71,764 48% 150,131

2053 79,604 52% 73,706 48% 153,310

2063 74,340 52% 69,070 48% 143,410

Foraging

2013 53,240 55% 42,844 45% 96,084

2023 51,421 55% 41,911 45% 93,332

2033 53,029 56% 41,725 44% 94,755

2043 41,977 53% 36,691 47% 78,668

2053 39,801 53% 34,863 47% 74,664

2063 53,217 58% 38,863 42% 92,080

Total Habitat

2013 277,212 48% 297,007 52% 574,219

2023 246,308 46% 294,004 54% 540,312

2033 214,028 42% 294,419 58% 508,448

2043 202,036 40% 304,579 60% 506,615

2053 198,511 39% 315,931 61% 514,442

2063 201,640 38% 325,862 62% 527,502

Habitat Capable

- 542,082 51% 515,584 49% 1,057,666

* No Action HLB = AMA, CON, GFMA, NGFMA, SGFMA; Reserves = all other allocations 
1705 | P a g e

Table S-53. Land use allocations of fisher habitat under Alternative A on BLM-administered lands 

Year

Within the HLB Within Reserves Total

(Acres) (Percent) (Acres) (Percent) (Acres)

Denning

2013 10,147 3% 314,331 97% 324,478

2023 4,645 1% 315,964 99% 320,609

2033 3,066 1% 330,320 99% 333,386

2043 3,235 1% 339,986 99% 343,220

2053 3,644 1% 360,625 99% 364,269

2063 4,871 1% 383,015 99% 387,886

Resting

2013 11,329 7% 142,329 93% 153,657

2023 10,986 7% 137,518 93% 148,504

2033 8,664 7% 124,117 93% 132,781

2043 11,209 7% 145,896 93% 157,106

2053 12,008 7% 156,244 93% 168,252

2063 16,069 10% 145,997 90% 162,066

Foraging

2013 10,218 11% 85,866 89% 96,084

2023 8,642 9% 85,175 91% 93,816

2033 6,628 7% 84,529 93% 91,157

2043 8,729 11% 70,702 89% 79,430

2053 9,098 12% 68,212 88% 77,310

2063 10,652 13% 71,733 87% 82,384

Total Habitat

2013 31,694 6% 542,525 94% 574,219

2023 24,273 4% 538,656 96% 562,929

2033 18,358 3% 538,967 97% 557,325

2043 23,173 4% 556,584 96% 579,756

2053 24,750 4% 585,081 96% 609,830

2063 31,592 5% 600,744 95% 632,336

Habitat Capable

- 138,903 13% 918,794 87% 1,057,666
1706 | P a g e

Table S-54. Land use allocations of fisher habitat under Alternative B on BLM-administered lands 

Year

Within the HLB Within Reserves Total

(Acres) (Percent) (Acres) (Percent) (Acres)

Denning

2013 54,608 17% 269,870 83% 324,478

2023 46,199 15% 271,128 85% 317,328

2033 47,713 14% 284,200 86% 331,912

2043 51,957 15% 291,288 85% 343,245

2053 54,404 15% 306,357 85% 360,761

2063 53,701 14% 323,166 86% 376,897

Resting

2013 43,414 28% 110,244 72% 153,657

2023 41,878 28% 108,094 72% 149,972

2033 41,063 30% 94,544 70% 135,607

2043 47,903 29% 115,210 71% 163,113

2053 61,529 33% 126,629 67% 188,158

2063 75,290 39% 117,712 61% 193,001

Foraging

2013 19,392 20% 76,692 80% 96,084

2023 23,006 23% 76,644 77% 99,650

2033 20,905 22% 76,280 78% 97,184

2043 22,905 26% 64,244 74% 87,149

2053 21,233 25% 62,941 75% 84,173

2063 28,338 30% 64,660 70% 92,998

Total Habitat

2013 117,413 20% 456,806 80% 574,219

2023 111,083 20% 455,867 80% 566,950

2033 109,681 19% 455,023 81% 564,704

2043 122,765 21% 470,742 79% 593,507

2053 137,166 22% 495,927 78% 633,093

2063 157,328 24% 505,538 76% 662,866

Habitat Capable

- 304,506 29% 753,160 87% 1,057,666
1707 | P a g e

Table S-55. Land use allocations of fisher habitat under Alternative C on BLM-administered lands 

Year

Within the HLB Within Reserves Total

(Acres) (Percent) (Acres) (Percent) (Acres)

Denning

2013 41,854 13% 282,624 87% 324,478

2023 25,995 8% 282,956 92% 308,951

2033 25,725 8% 294,528 92% 320,253

2043 26,943 8% 302,602 92% 329,545

2053 29,206 8% 316,867 92% 346,072

2063 30,293 8% 335,318 92% 365,611

Resting

2013 50,474 33% 103,184 67% 153,657

2023 47,743 32% 101,927 68% 149,670

2033 39,687 30% 90,906 70% 130,593

2043 46,976 31% 106,304 69% 153,280

2053 54,656 32% 117,525 68% 172,182

2063 60,633 36% 107,064 64% 167,697

Foraging

2013 21,680 23% 74,404 77% 96,084

2023 23,525 24% 74,790 76% 98,315

2033 19,296 21% 74,267 79% 93,563

2043 21,315 25% 62,895 75% 84,210

2053 19,999 24% 61,841 76% 81,840

2063 24,594 28% 62,736 72% 87,331

Total Habitat

2013 114,007 20% 460,212 80% 574,219

2023 97,262 17% 459,674 83% 556,936

2033 84,708 16% 459,701 84% 544,409

2043 95,235 17% 471,801 83% 567,035

2053 103,861 17% 496,233 83% 600,094

2063 115,521 19% 505,118 81% 620,639

Habitat Capable

- 320,423 30% 737,243 70% 1,057,666
1708 | P a g e

Table S-56. Land use allocations of fisher habitat under Alternative D on BLM-administered lands 

Year

Within the HLB Within Reserves Total

(Acres) (Percent) (Acres) (Percent) (Acres)

Denning

2013 31,448 10% 293,030 90% 324,478

2023 21,466 7% 293,983 93% 315,449

2033 26,927 8% 306,672 92% 332,599

2043 31,941 9% 312,484 91% 344,426

2053 38,445 10% 327,934 90% 366,379

2063 43,699 11% 345,834 89% 389,533

Resting

2013 51,477 34% 102,181 66% 153,657

2023 53,436 35% 101,392 65% 154,827

2033 46,136 34% 91,494 66% 137,631

2043 53,594 33% 108,076 67% 161,670

2053 64,143 36% 114,670 64% 178,813

2063 68,450 40% 104,511 60% 172,961

Foraging

2013 19,904 21% 76,180 79% 96,084

2023 19,904 21% 76,435 79% 96,338

2033 16,527 18% 77,405 82% 93,932

2043 21,343 25% 63,775 75% 85,117

2053 19,624 24% 61,726 76% 81,350

2063 29,838 33% 61,010 67% 90,847

Total Habitat

2013 102,828 18% 471,391 82% 574,219

2023 94,805 17% 471,809 83% 566,614

2033 88,591 16% 475,571 84% 564,162

2043 106,878 18% 484,335 82% 591,213

2053 122,212 20% 504,330 80% 626,542

2063 141,986 22% 511,355 78% 653,341

Habitat Capable

- 322,728 31% 734,938 69% 1,057,666
1709 | P a g e

Table S-57. Land use allocations of fisher habitat under the Proposed RMP on BLM-administered lands 

Year

Within the HLB Within Reserves Total

(Acres) (Percent) (Acres) (Percent) (Acres)

Denning

2013 47,615 15% 271,887 85% 319,503

2023 38,999 13% 272,942 87% 311,941

2033 37,829 12% 285,962 88% 323,791

2043 40,260 12% 294,869 88% 335,129

2053 40,067 11% 310,843 89% 350,910

2063 39,339 11% 327,202 89% 366,541

Resting

2013 36,078 23% 120,675 77% 156,753

2023 36,427 24% 117,207 76% 153,634

2033 32,839 24% 104,224 76% 137,063

2043 38,277 24% 123,444 76% 161,721

2053 47,470 26% 137,409 74% 184,880

2063 57,484 31% 130,559 69% 188,043

Foraging

2013 15,520 16% 79,580 84% 95,100

2023 17,763 18% 79,855 82% 97,619

2033 17,796 18% 78,517 82% 96,312

2043 18,465 22% 66,979 78% 85,444

2053 16,371 20% 65,129 80% 81,499

2063 22,835 25% 68,169 75% 91,004

Total Habitat

2013 99,214 17% 427,142 83% 571,355

2023 93,189 17% 470,004 83% 563,194

2033 88,463 16% 468,703 84% 557,166

2043 97,002 17% 485,292 83% 582,294

2053 103,908 17% 513,381 83% 617,289

2063 119,658 19% 525,931 81% 645,588

Habitat Capable

- 269,633 25% 788,034 75% 1,057,666
1710 | P a g e

Fisher Habitat Harvested Under Each Alternative and the 

Proposed RMP 

Table S-58. Fisher habitat harvested by the end of each decade under the No Action alternative over 50 

years (2013–2063) 

Year Denning

(Acres)

Resting

(Acres)

Foraging

(Acres)

Total Habitat Harvested

(Acres)

2023 30,356 5,950 1,745 38,051

2033 25,933 7,161 1,548 34,642

2043 21,393 9,824 1,549 32,766

2053 13,182 11,252 1,846 26,280

2063 14,740 5,706 974 21,421

Table S-59. Fisher habitat harvested by the end of each decade under Alternative A over 50 years (2013–

2063) 

Year Denning

(Acres)

Resting

(Acres)

Foraging

(Acres)

Total Habitat Harvested

(Acres)

2023 12,685 6,155 2,249 21,089

2033 5,218 8,536 3,153 16,907

2043 1,365 4,333 1,612 7,309

2053 388 7,130 1,179 8,697

2063 7,310 4,857 1,882 14,049

Table S-60. Fisher habitat harvested by the end of each decade under Alternative B over 50 years (2013–

2063) 

Year Denning

(Acres)

Resting

(Acres)

Foraging

(Acres)

Total Habitat Harvested

(Acres)

2023 40,129 11,092 4,723 55,944

2033 24,429 14,339 4,203 42,971

2043 14,084 17,234 3,088 34,406

2053 9,347 11,564 2,182 23,093

2063 21,440 11,895 2,233 35,569

Table S-61. Fisher habitat harvested by the end of each decade under Alternative C over 50 years (2013–

2063) 

Year Denning

(Acres)

Resting

(Acres)

Foraging

(Acres)

Total Habitat Harvested

(Acres)

2023 30,317 10,252 6,844 47,412

2033 14,892 22,423 4,360 41,674

2043 8,374 16,919 3,879 29,172

2053 5,885 10,186 1,575 17,646

2063 10,575 11,840 2,998 25,413
1711 | P a g e

Table S-62. Fisher habitat harvested by the end of each decade under Alternative D over 50 years (2013–

2063) 

Year Denning

(Acres)

Resting

(Acres)

Foraging

(Acres)

Total Habitat Harvested

(Acres)

2023 21,335 11,831 6,536 39,702

2033 5,620 15,303 5,017 25,940

2043 3,127 12,143 2,992 18,262

2053 790 8,788 1,587 11,165

2063 10,319 5,565 2,501 18,385

Table S-63. Fisher habitat harvested by the end of each decade under the Proposed RMP over 50 years 

(2013–2063) 

Year Denning

(Acres)

Resting

(Acres)

Foraging

(Acres)

Total Habitat Harvested

(Acres)

2023 38,032 10,575 3,594 52,202

2033 21,189 16,593 3,965 41,747

2043 9,197 16,147 4,017 29,360

2053 7,614 11,346 2,085 21,044

2063 18,168 10,682 2,260 31,111

Fisher Population 

Table S-64. Fisher population in the planning area under the No Action alternative 

Year Total Fisher Habitat 

(Acres) Female Fisher* Male Fisher* Total Fisher Population

2013 4,484,755 956 336 1,292

2023 4,450,848 949 334 1,283

2033 4,519,548 963 339 1,302

2043 4,554,018 971 342 1,312

2053 4,561,846 972 342 1,315

2063 4,574,905 975 343 1,318

* Estimated number of fisher assumes full occupancy of habitat based on availability of habitat and mean home range size (mean 

female home range is 4,692 acres, mean male home range is 13,329 acres). 
1712 | P a g e

Table S-65. Fisher population in the planning area under Alternative A

Year Total Fisher Habitat 

(Acres) Female Fisher* Male Fisher* Total Fisher Population

2013 4,484,755 956 336 1,292

2023 4,473,465 953 336 1,289

2033 4,568,425 974 343 1,316

2043 4,627,160 986 347 1,333

2053 4,657,234 993 349 1,342

2063 4,679,739 997 351 1,348

* Estimated number of fisher assumes full occupancy of habitat based on availability of habitat and mean home range size (mean 

female home range is 4,692 acres, mean male home range is 13,329 acres). 

Table S-66. Fisher population in the planning area under Alternative B

Year Total Fisher Habitat 

(Acres) Female Fisher* Male Fisher* Total Fisher Population

2013 4,484,755 956 336 1,292

2023 4,477,486 954 336 1,290

2033 4,575,804 975 343 1,319

2043 4,640,911 989 348 1,337

2053 4,680,496 998 351 1,349

2063 4,710,269 1,004 353 1,357

* Estimated number of fisher assumes full occupancy of habitat based on availability of habitat and mean home range size (mean 

female home range is 4,692 acres, mean male home range is 13,329 acres). 

Table S-67. Fisher population in the planning area under Alternative C

Year Total Fisher Habitat 

(Acres) Female Fisher* Male Fisher* Total Fisher Population

2013 4,484,755 956 336 1,292

2023 4,467,472 952 335 1,287

2033 4,555,509 971 342 1,313

2043 4,614,438 983 346 1,330

2053 4,647,498 991 349 1,339

2063 4,668,042 995 350 1,345

* Estimated number of fisher assumes full occupancy of habitat based on availability of habitat and mean home range size (mean 

female home range is 4,692 acres, mean male home range is 13,329 acres). 

Table S-68. Fisher population in the planning area under Alternative D

Year Total Fisher Habitat 

(Acres) Female Fisher* Male Fisher* Total Fisher Population

2013 4,484,755 956 336 1,292

2023 4,477,150 954 336 1,290

2033 4,575,262 975 343 1,318

2043 4,638,616 989 348 1,337

2053 4,673,945 996 351 1,347

2063 4,700,745 1,002 353 1,355

* Estimated number of fisher assumes full occupancy of habitat based on availability of habitat and mean home range size (mean 

female home range is 4,692 acres, mean male home range is 13,329 acres). 
1713 | P a g e

Table S-69. Fisher population in the planning area under the Proposed RMP

Year Total Fisher Habitat 

(Acres) Female Fisher* Male Fisher* Total Fisher Population

2013 4,481,891 955 336 1,291

2023 4,473,729 953 336 1,289

2033 4,568,266 974 343 1,316

2043 4,629,697 987 347 1,334

2053 4,664,693 994 350 1,344

2063 4,692,992 1,000 352 1,352

* Estimated number of fisher assumes full occupancy of habitat based on availability of habitat and mean home range size (mean 

female home range is 4,692 acres, mean male home range is 13,329 acres). 

Table S-70. Fisher population forecast in the planning area under the No Timber Harvest reference 

analysis

Year Total Fisher Habitat 

(Acres) Female Fisher* Male Fisher* Total Fisher Population

2013 4,485,024 956 336 1,292

2023 4,481,942 955 336 1,291

2033 4,581,440 976 344 1,320

2043 4,641,302 989 348 1,337

2053 4,671,232 996 350 1,346

2063 4,691,760 1,000 352 1,352

* Estimated number of fisher assumes full occupancy of habitat based on availability of habitat and mean home range size (mean 

female home range is 4,692 acres, mean male home range is 13,329 acres). 
1714 | P a g e

Gray Wolf 

Table S-71. Wolf population, control, and depredation in Oregon 

Wolf Statistics 2009*

2010†2011‡2012§2013ǀǀ 2014# Cumulative

Total

Minimum Wolf Population

(# individuals) 16 21 29 46 64 77 Not applicable

Wolf Packs

(# packs) 2 2 4 6 8 9 Not applicable

Wolves Removed

(# individuals removed) 2 - 2 - - - 4

Wolves Removed

(percent of population) 13% - 7% - - - Not applicable

Confirmed Wolf Depredations

(# livestock) 30 8 17 12 12 32 111

* USFWS et al. 2010 

† USFWS et al. 2011 

‡ ODFW 2011 

§ ODFW 2013 

ǀǀ ODFW 2014b 

# ODFW 2015c 

Table S-72. Wolf population, control, and depredation in the northern Rocky Mountain population 

Wolf Statistics 2009*

2010†2011‡2012§2013ǀǀ 2014# Cumulative

Total

Minimum Wolf Population

(# individuals) 2,292 2,045 2,354 2,569 2,613 2,401 Not applicable

Wolf Packs

(# packs) 242 244 287 321 320 313 Not applicable

Wolves Removed

(# individuals removed) 272 260 166 231 202 162 1,293

Wolves Removed

(percent of population) 12% 13% 7% 9% 8% 7% Not applicable

Confirmed Wolf Depredations

(# livestock) 966 465 371 674 632 318 3,426

* USFWS et al. 2010 

† USFWS et al. 2011 

‡ USFWS et al. 2012 

§ USFWS et al. 2013 

ǀǀ USFWS et al. 2014 

# USFWS et al. 2015 
1715 | P a g e

Marbled Murrelet 

Marbled Murrelet Nesting Habitat 

Table S-73. Marbled murrelet nesting habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 493,968 493,968 493,968 493,968 493,968 493,434 493,968

Alternatives/Proposed RMP

2023 502,168 507,622 501,865 477,023 518,431 505,612 528,310

2033 565,762 579,509 569,953 515,784 602,023 569,860 621,274

2043 648,814 660,588 647,416 580,062 691,494 648,415 716,909

2053 733,369 739,298 725,624 648,471 779,791 734,794 811,704

2063 773,852 756,794 771,558 654,988 813,721 778,175 840,024

Table S-74. Marbled murrelet high-quality nesting habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 233,219 233,219 233,219 233,219 233,219 232,493 233,219

Alternatives/Proposed RMP

2023 226,102 231,247 230,737 222,942 232,005 230,505 233,448

2033 252,025 259,411 258,532 244,219 260,620 258,796 263,781

2043 260,610 271,627 271,282 251,518 274,686 271,496 277,291

2053 275,825 286,819 287,764 265,232 290,827 287,891 294,382

2063 294,666 305,620 308,023 276,789 310,055 308,863 319,070

Table S-75. Marbled murrelet nesting habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 5,301,635 5,301,635 5,301,635 5,301,635 5,301,635 5,301,101 5,301,635

Alternatives/Proposed RMP

2023 5,309,835 5,315,289 5,309,532 5,284,690 5,326,098 5,313,279 5,335,977

2033 5,414,289 5,428,036 5,418,481 5,364,311 5,450,550 5,418,388 5,469,801

2043 5,515,882 5,527,656 5,514,484 5,447,131 5,558,562 5,515,483 5,583,977

2053 5,600,437 5,606,367 5,592,692 5,515,539 5,646,859 5,601,862 5,678,772

2063 5,640,921 5,623,862 5,638,627 5,522,056 5,680,789 5,645,244 5,707,093
1716 | P a g e

Table S-76. Marbled murrelet high-quality nesting habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 573,150 573,150 573,150 573,150 573,150 572,424 573,150

Alternatives/Proposed RMP

2023 566,033 571,178 570,669 562,874 571,936 570,437 573,380

2033 591,956 599,342 598,464 584,150 600,551 598,727 603,712

2043 600,542 611,559 611,214 591,449 614,617 611,428 617,222

2053 781,686 792,680 793,625 771,094 796,688 793,752 800,243

2063 800,527 811,481 813,884 782,651 815,916 814,725 824,931

Table S-77. Land use allocations of marbled murrelet nesting habitat under the No Action alternative on 

BLM-administered lands 

Year

Within the HLB* Within Reserves*

Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 82,869 17% 411,099 83% 493,968

2023 79,359 16% 422,809 84% 502,168

2033 85,194 15% 480,568 85% 565,762

2043 97,618 15% 551,196 85% 648,814

2053 107,013 15% 626,356 85% 733,369

2063 113,358 15% 660,494 85% 773,852

* No Action HLB = AMA, CON, GFMA, NGFMA, SGFMA; Reserves = all other allocations 

Table S-78. Land use allocations of high-quality marbled murrelet nesting habitat under the No Action 

alternative on BLM-administered lands 

Year

Within the HLB* Within Reserves*

Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 20,902 9% 212,317 91% 233,219

2023 13,950 6% 212,317 94% 226,267

2033 13,737 5% 238,287 95% 252,025

2043 11,136 4% 249,474 96% 260,610

2053 11,969 4% 263,856 96% 275,825

2063 14,938 5% 279,728 95% 294,666

* No Action HLB = AMA, CON, GFMA, NGFMA, SGFMA; Reserves = all other allocations 
1717 | P a g e

Table S-79. Land use allocations of marbled murrelet nesting habitat under Alternative A on BLMadministered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 42,139 9% 451,829 91% 493,968

2023 29,694 6% 477,927 94% 507,622

2033 26,583 5% 552,926 95% 579,509

2043 28,416 4% 632,172 96% 660,588

2053 30,534 4% 708,764 96% 739,298

2063 22,551 3% 734,242 97% 756,794

Table S-80. Land use allocations of high-quality marbled murrelet nesting habitat under Alternative A on 

BLM-administered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 2,839 1% 230,380 99% 233,219

2023 1,094 0% 230,153 100% 231,247

2033 300 0% 259,111 100% 259,411

2043 317 0% 271,311 100% 271,627

2053 439 0% 286,380 100% 286,819

2063 432 0% 305,188 100% 305,620

Table S-81. Land use allocations of marbled murrelet nesting habitat under Alternative B on BLMadministered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 46,899 9% 447,069 91% 493,968

2023 36,407 7% 465,458 93% 501,865

2033 41,863 7% 528,090 93% 569,953

2043 50,223 8% 597,193 92% 647,416

2053 59,562 8% 666,062 92% 725,624

2063 71,140 9% 700,418 91% 771,558
1718 | P a g e

Table S-82. Land use allocations of high-quality marbled murrelet nesting habitat under Alternative B on 

BLM-administered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 4,070 2% 229,149 98% 233,219

2023 1,571 1% 229,166 99% 230,737

2033 1,123 0% 257,410 100% 258,532

2043 1,571 1% 269,711 99% 271,282

2053 2,238 1% 285,526 99% 287,764

2063 2,832 1% 305,191 99% 308,023

Table S-83. Land use allocations of marbled murrelet nesting habitat under Alternative C on BLMadministered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 115,544 23% 378,424 77% 493,968

2023 83,937 18% 393,086 82% 477,023

2033 77,982 15% 437,802 85% 515,784

2043 86,494 15% 493,568 85% 580,062

2053 103,859 16% 544,612 84% 648,471

2063 89,191 14% 565,797 86% 654,988

Table S-84. Land use allocations of high-quality marbled murrelet nesting habitat under Alternative C on 

BLM-administered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 18,479 8% 214,740 92% 233,219

2023 8,149 4% 214,793 96% 222,942

2033 8,026 3% 236,193 97% 244,219

2043 6,135 2% 245,382 98% 251,518

2053 6,673 3% 258,559 97% 265,232

2063 6,707 2% 270,082 98% 276,789
1719 | P a g e

Table S-85. Land use allocations of marbled murrelet nesting habitat under Alternative D on BLMadministered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 72,062 15% 421,906 85% 493,968

2023 76,716 15% 441,715 85% 518,431

2033 102,559 17% 499,463 83% 602,023

2043 131,995 19% 559,499 81% 691,494

2053 162,477 21% 617,314 79% 779,791

2063 178,386 22% 635,334 78% 813,721

Table S-86. Land use allocations of high-quality marbled murrelet nesting habitat under Alternative D on 

BLM-administered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 6,887 3% 226,332 97% 233,219

2023 5,841 3% 226,163 97% 232,005

2033 7,668 3% 252,952 97% 260,620

2043 10,552 4% 264,134 96% 274,686

2053 13,448 5% 277,379 95% 290,827

2063 14,975 5% 295,081 95% 310,055
1720 | P a g e

Table S-87. Land use allocations of marbled murrelet nesting habitat under the Proposed RMP on BLMadministered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 34,362 7% 459,072 93% 493,434

2023 23,591 5% 482,021 95% 505,612

2033 23,489 4% 546,372 96% 569,860

2043 23,931 4% 624,483 96% 648,415

2053 30,596 4% 704,198 96% 734,794

2063 43,257 6% 734,918 94% 778,175

Table S-88. Land use allocations of high-quality marbled murrelet nesting habitat under the Proposed 

RMP on BLM-administered lands 

Year

Within the HLB Within Reserves Total Nesting Habitat 

(Acres) (Percent) (Acres) (Percent) (Acres)

2013 3,425 1% 229,067 99% 232,493

2023 1,600 1% 228,905 99% 230,505

2033 1,189 0% 257,607 100% 258,796

2043 1,035 0% 270,462 100% 271,496

2053 1,427 0% 286,464 100% 287,891

2063 1,690 1% 307,174 99% 308,863

Kappa Analysis for Marbled Murrelet Habitat 

The BLM calculated the kappa statistic to compare quantitatively the level of agreement between two 

different models of marbled murrelet habitat in the decision area. Competing models can produce results 

that agree (or disagree) simply by chance, and the kappa statistic is a measure of the agreement between 

two models that takes into account the possibility of chance agreement. While interpretations of the kappa 

statistic vary, the BLM used the interpretation summarized by Viera and Garret (2005, p. 362) (Table S89). The BLM calculated the kappa statistic following Fowler et al. (1998) and Veira and Garret (2005). 

Table S-89. Interpretation of the kappa statistic 

Kappa Agreement

< 0 Less Than Chance Agreement (Potential Systematic Disagreement)

0.01–0.20 Slight Agreement

0.21–0.40 Fair Agreement

0.41–0.60 Moderate Agreement

0.61–0.80 Substantial Agreement

0.81–0.99 Almost Perfect Agreement

1.00 Perfect Agreement

Source: Viera and Garret 2005 
1721 | P a g e

The two models compared include the one used by BLM in this Proposed RMP/Final EIS (refer to 

Chapter 3, Marbled Murrelet – Summary of Analytical Methods) and the one described in Chapter 2 of 

Northwest Forest Plan – the First Twenty Years (1994-2013): Status and Trend of Marbled Murrelet 

Populations and Nesting Habitat (Falxa and Raphael 2015). 

The BLM modeled marbled murrelet nesting habitat in the Proposed RMP/Final EIS using the structural 

stage output from Woodstock vegetation modeling for 2013 and assumed: 

 High-quality Nesting Habitat = structural stages 5.1, 5.2, or 5.3; 

 Nesting Habitat = structural stages 3.1, 3.3, 4.1, 4.2, 5.1, 5.2, or 5.3; and 

 Non-habitat = structural stages 1.1, 1.2, 3.2, or 3.4. 

The model from Falxa and Raphael (2015), used habitat classes generated from a MaxEnt analysis that 

utilized GNN from 2012 for the vegetation covariate as well as several other data sources (Falxa and 

Raphael 2015, pp. 68–76) and used four classes of habitat suitability (p. 84): 

 Class 1 = Lowest Suitability 

 Class 2 = Marginal Suitability 

 Class 3 = Moderate Suitability 

 Class 4 = Highest Suitability 

Raphael et al. (2015) often combined Class 3 and Class 4 habitat, which they reported as ‘higher 

suitability’ habitat. 

The two models are coincident on 847,826 acres of BLM-administered lands (3,812,258 pixels that are 30 

 30 meters in size). Table S-90 presents the cross-tabulation of structural stages and habitat classes from 

the two models. 
1722 | P a g e

Table S-90. Cross-tabulation of structural stages used in the Proposed RMP/Final EIS compared with 

habitat classes from Falxa and Raphael (2015) 

Structural Stage (from Proposed RMP/Final EIS 

Analysis)

Habitat Suitability Class

(from Raphael et al. 2015) Totals

Name Code 1 2 3 4

Early Successional with Structural Legacies 1.1 14,633 4,952 452 7 20,044

Early Successional without Structural Legacies 1.2 21,036 3,420 248 7 24,711

Stand Establishment with Structural Legacies 2.1 24,355 14,007 684 133 39,179

Stand Establishment without Structural Legacies 2.2 406,373 125,748 13,106 1,182 546,409

Young – High Density, with Structural Legacies 3.1 93,008 72,946 27,690 5,876 199,520

Young – High Density, without Structural 

Legacies 3.2 692,148 283,847 36,187 3,119 1,015,301

Young – Low Density, with Structural Legacies 3.3 2,732 5,009 4,783 441 12,965

Young – Low Density, without Structural 

Legacies 3.4 18,735 14,434 4,276 400 37,845

Mature, Single-layered Canopy 4.1 213,186 212,971 65,814 11,690 503,661

Mature, Multi-layered Canopy 4.2 140,777 179,385 67,034 18,935 406,131

Structurally-complex, Developed Structurallycomplex 5.1 74,871 170,670 93,228 26,936 365,705

Structurally-complex, Existing Old Forest 5.2 124,569 315,393 119,725 18,040 577,727

Structurally-complex, Existing Very Old Forest 5.3 4,965 29,940 25,102 3,053 63,060

Totals - 1,831,388 1,432,722 458,329 89,819 3,812,258

Note: Values are counts of individual pixels (30  30 meters). 

Using the information from Table S-90, the BLM calculated the kappa statistic for three different 

categorical combinations of model output: 

 High-quality nesting habitat and non-high-quality nesting habitat (Kappa Run #1) 

 High-quality nesting habitat, low-quality nesting habitat, and non-nesting habitat (Kappa Run #2) 

 Nesting habitat and non-nesting habitat (Kappa Run #3) 

The results of the three different runs calculating kappa are summarized below. 

Kappa Run #1 

For comparison of the two models in regards to high-quality nesting habitat versus all other habitat 

qualities (i.e., high-quality vs. non-high quality), the BLM assumed: 

 Raphael et al. (2015) Habitat Classes: 

o High-quality Nesting Habitat = Class 3 or Class 4; and 

o Non-high-quality Nesting Habitat = Class 1 or Class 2. 

 BLM Structural Stages: 

o High-quality Nesting Habitat = structural stages 5.1, 5.2, or 5.3; and 

o Non-high-quality Nesting Habitat = structural stages 1.1, 1.2, 3.1, 3.2, 3.3, 3.4, 4.1, or 

4.2. 

The results suggest that there is ‘fair agreement’ (kappa = 0.22) between the two murrelet habitat models 

in discerning high-quality nesting habitat from non-high quality nesting habitat (Table S-91). The overall 

accuracy is 74 percent between the two models (i.e., the two models produced the same analytical result 

in 74 percent of the pixels). 
1723 | P a g e

Table S-91. Cross-tabulation of marbled murrelet habitat class (from Rachael et al. 2015) high-quality vs. 

non-high quality nesting habitat 

Structural Stage

(from Proposed RMP/Final EIS

Analysis)

Habitat Class

Totals

(Pixels) Non-high-quality

(Pixels)

High-quality

Nesting Habitat

(Pixels)

Non-high-quality 2,543,702 262,064 2,805,766

High-quality Nesting Habitat 720,408 286,084 1,006,492

Totals 3,264,110 548,148 3,812,258

Note: Values are counts of individual pixels (30  30 meters). 

Kappa Run #2 

For comparison of the two models in regards to high-quality nesting habitat, low-quality nesting habitat, 

and non-habitat, the BLM assumed: 

 Raphael et al. (2015) Habitat Classes: 

o High-quality Nesting Habitat = Class 3 or Class 4; 

o Low-quality Nesting Habitat = Class 2; and 

o Non-nesting Habitat = Class 1. 

 BLM Structural Stages: 

o High-quality Nesting Habitat = structural stages 5.1, 5.2, or 5.3; and 

o Low-quality Nesting Habitat = structural stages 3.1, 3.3, 4.1, or 4.2; and 

o Non-nesting Habitat = structural stages 1.1, 1.2, 3.2, or 3.4. 

The results suggest that there is ‘fair agreement’ (kappa = 0.23) between the two murrelet habitat models 

in discerning high-quality nesting habitat, low-quality nesting habitat, and non-nesting habitat from one 

another (Table S-92). The overall accuracy is 51 percent between the two models (i.e., the two models 

produced the same analytical result in 51 percent of the pixels). 

Table S-92. Cross-tabulation of marbled murrelet habitat class (from Raphael et al. 2015) high-quality 

nesting habitat, low-quality nesting habitat, and non-habitat 

Structural Stage

(from Proposed RMP/Final EIS

Analysis)

Habitat Class

Totals

(Pixels) Non-habitat

(Pixels)

Low-quality 

Nesting Habitat

(Pixels)

High-quality 

Nesting Habitat

(Pixels)

Non-habitat 1,177,280 446,408 59,801 1,683,489

Low-quality Nesting Habitat 449,703 470,311 202,263 1,122,277

High-quality Nesting Habitat 204,405 516,003 286,084 1,006,492

Totals 1,831,388 1,432,722 548,148 3,812,258

Note: Values are counts of individual pixels (30  30 meters). 

Kappa Run #3 

For comparison of the two models in regards to nesting habitat versus all non-habitat, the BLM assumed: 

 Raphael et al. (2015) Habitat Classes: 

o Nesting Habitat = Class 2, Class 3, or Class 4; and 

o Non-habitat = Class 1. 

 BLM Structural Stages: 
1724 | P a g e

o Nesting Habitat = structural stages 3.1, 3.3, 4.1, 4.2, 5.1, 5.2, or 5.3; and 

o Non-habitat = structural stages 1.1, 1.2, 3.2, or 3.4. 

The results suggest that there is ‘fair agreement’ (kappa = 0.39) between the two murrelet habitat models 

in discerning nesting habitat from non-habitat (Table S-93). The overall accuracy is 70 percent between 

the two models (i.e., the two models produced the same analytical result in 70 percent of the pixels). 

Table S-93. Cross-tabulation of marbled murrelet habitat class (from Raphael et al. 2015) nesting habitat 

vs. non-habitat 

Structural Stage

(from Proposed RMP/Final EIS

Analysis)

Habitat Class

Totals

(Pixels)

Non-habitat

(Pixels)

Nesting Habitat

(Pixels)

Non-habitat 1,177,280 506,209 1,683,489

Nesting Habitat 654,108 1,474,661 2,128,769

Totals 1,831,388 1,980,870 3,812,258

Note: Values are counts of individual pixels (30  30 meters). 

Overall, the marbled murrelet habitat model in the Proposed RMP/Final EIS appears to have ‘fair 

agreement’ with the habitat model described in Falxa and Raphael (2015). The models seem to agree in 

discerning nesting habitat from non-habitat and high-quality habitat from other stand conditions (either 

non-habitat or low-quality nesting habitat). There is relatively less agreement between the two models in 

discerning high-quality from low-quality habitat as evidenced by low kappa statistics and overall 

accuracy. However, the BLM detected no systematic disagreement between the two models. 

References 

Fowler, L., L. Cohen, and P. Jarvis. 1998. Practical Statistics for Field Biology. Second Editon. John Wiley & Sons, Ltd. West 

Sussex, England. 259 pp. 

Falxa, G. A., M. G. Raphael, technical editors. 2015. Northwest Forest Plan—The first 20 years (1994–2013): status and trend of 

marbled murrelet populations and nesting habitat. Gen. Tech. Rep. PNW-GTR-XXXX. Portland, OR: U.S. Department of 

Agriculture, U.S. Forest Service, Pacific Northwest Research Station. 191 pp. http://www.reo.gov/monitoring/index.shtml. 

Viera, A. J. and J. M. Garret. 2005. Understanding interobserver agreement: the kappa statistic. Family Medicine. 37(5): 360–

363. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.483.429&rep=rep1&type=pdf. 
1725 | P a g e

Marbled Murrelet Designated Critical Habitat 

Table S-94. Marbled murrelet nesting habitat development in designated critical habitat in the decision 

area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 273,174 273,174 273,174 273,174 273,174 273,178 273,174

Alternatives/Proposed RMP

2023 279,663 287,274 277,165 269,436 286,747 280,433 287,761

2033 316,887 331,494 309,895 288,580 328,915 312,096 332,689

2043 362,224 379,380 354,011 328,535 376,676 354,576 381,421

2053 413,282 428,841 398,366 371,044 427,385 403,174 433,432

2063 434,896 442,991 419,668 380,736 440,396 422,335 446,137

Table S-95. Marbled murrelet high-quality nesting habitat development in designated critical habitat in 

the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 154,331 154,331 154,331 154,331 154,331 154,331 154,331

Alternatives/Proposed RMP

2023 154,266 154,515 153,559 149,579 154,097 153,963 154,522

2033 173,468 173,730 172,153 164,803 172,237 172,803 174,105

2043 180,766 181,190 179,316 169,448 180,709 180,202 181,438

2053 190,381 190,596 188,469 177,754 189,304 189,464 191,014

2063 197,017 197,646 194,091 180,763 193,961 196,107 198,051

Table S-96. Marbled murrelet high-quality nesting habitat development in designated critical habitat in 

the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 344,345 344,345 344,345 344,345 344,345 344,345 344,345

Alternatives/Proposed RMP

2023 344,280 344,529 343,573 339,593 344,111 343,977 344,536

2033 363,482 363,744 362,167 354,817 362,251 362,817 364,119

2043 370,780 371,204 369,330 359,462 370,723 370,216 371,452

2053 516,380 516,595 514,468 503,753 515,303 515,463 517,013

2063 523,016 523,645 520,090 506,762 519,960 522,106 524,050
1726 | P a g e

Table S-97. Land use allocations of designated marbled murrelet critical habitat 

Alternative/

Proposed 

RMP

Within the HLB Within Reserves Total Nesting 

(Acres) (Percent) (Acres) (Percent) Habitat (Acres)

No Action*813 0% 479,585 100% 480,398

Alt. A 221 0% 480,177 100% 480,398

Alt. B 43,337 9% 437,061 91% 480,398

Alt. C 106,495 22% 373,903 78% 480,398

Alt. D 96,660 20% 383,738 80% 480,398

PRMP 39,718 8% 440,680 92% 480,398

* No Action HLB = AMA, CON, GFMA, NGFMA, SGFMA; Reserves = all other allocations 

Table S-98. Land use allocations of designated marbled murrelet critical habitat within Zone 1 

Alternative/

Proposed 

RMP

Within the HLB Within Reserves Total Nesting 

(Acres) (Percent) (Acres) (Percent) Habitat (Acres)

No Action*729 0% 408,554 100% 409,283

Alt. A 211 0% 409,072 100% 409,283

Alt. B 30,903 8% 378,379 92% 409,283

Alt. C 79,435 19% 329,847 81% 409,283

Alt. D 82,172 20% 327,110 80% 409,283

PRMP 29,020 7% 380,262 93% 409,283

* No Action HLB = AMA, CON, GFMA, NGFMA, SGFMA; Reserves = all other allocations 

Table S-99. Land use allocations of designated marbled murrelet critical habitat within Zone 2 

Alternative/

Proposed 

RMP

Within the HLB Within Reserves Total Nesting 

(Acres) (Percent) (Acres) (Percent) Habitat (Acres)

No Action*84 0% 71,002 100% 71,087

Alt. A 11 0% 71,076 100% 70,087

Alt. B 12,434 17% 58,653 83% 71,087

Alt. C 27,060 38% 44,027 62% 71,087

Alt. D 14,487 20% 56,600 80% 71,087

PRMP 10,698 15% 60,389 85% 71,087

* No Action HLB = AMA, CON, GFMA, NGFMA, SGFMA; Reserves = all other allocations 
1727 | P a g e

Marbled Murrelet Known Sites and Forecast Sites 

Table S-100. Known marbled murrelet sites and past survey effort in the planning area 

Ownership

Known Occupied 

Marbled Murrelet 

Sites

Marbled Murrelet

Survey Effort

Agency District or Forest (Number) (Acres)

Survey 

Period

(Years)

Stations

(Number)

Survey 

Polygons

(Number)

Survey 

Area

(Acres)

Bureau of Land Management 351 51,995 1991-2014 6,121 1,496 83,234

BLM

Coos Bay 249 29,777 1993-2014 2,245 591 32,402

Eugene 39 6,504 2002-2014 1,286 233 7,039

Medford - - 1993-2014 597 123 10,430

Roseburg 27 8,851 1993-2014 1,592 419 23,459

Salem 36 6,863 1991-2014 401 130 9,904

U.S. Forest Service 417 21,144†1986-2009 Not available

USFS Siuslaw 284* Not 

available 1986-1997

Not available

Rogue-Siskiyou 133 21,144 1991-2009

Oregon Department of 

Forestry 237 21,235 1989-2014 9,650 2,107 300,455

Totals 1,005 94,374 1986-2014 - - -

* Surveyors observed occupied behaviors at 381 survey stations on the U.S. Forest Service’s Siuslaw National Forest. For this 

analysis, BLM assumed that the stations within 400 meters of each other represented the same occupied site since the maximum 

effective distance of a survey station is 200 meters radius (Mack et al. 2003, p. 9). Thus, the 381 survey stations with occupied 

behaviors represent approximately 284 occupied sites. 

† Only includes acreage from the Rogue-Siskiyou National Forest; acreage from the Siuslaw National Forest is not available. 

Table S-101. Decadal forecast (2013–2063) of marbled murrelet occupied sites discovered or lost under 

the No Action alternative 

Decade*

Nesting Habitat in the Decision Area

(Acres)

Occupied Sites Forecast in the Decision Area

(Number)

Totals

In the Harvest Scenario†

Totals

In the Harvest Scenario†

With 

Surveys

Without 

Surveys

Discovered 

and Protected Lost

Current 493,968 - - 2,459 - -

1

st 502,168 37,734 - 2,524 144 -

2

nd 565,762 37,407 - 2,842 165 -

3

rd 648,814 30,237 - 3,254 129 -

4

th 733,369 35,391 - 3,714 165 -

5

th 773,852 37,721 - 3,900 191 -

Totals - 178,491 - - 795 -

* Habitat acreage based on the start of the decade (i.e., 2023, 2033, 2043, 2053, 2063) 

† Nesting habitat would be surveyed under the No Action alternative 
1728 | P a g e

Table S-102. Decadal forecast (2013–2063) of marbled murrelet occupied sites discovered or lost under 

Alternative A 

Decade*

Nesting Habitat in the Decision Area

(Acres)

Occupied Sites Forecast in the Decision Area

(Number)

Totals

In the Harvest Scenario†

Totals

In the Harvest Scenario†

With 

Surveys

Without 

Surveys

Discovered 

and Protected Lost

Current 493,968 - - 2,459 - -

1

st 507,622 - 22,886 2,529 - 106

2

nd 579,509 - 18,105 2,881 - 101

3

rd 660,588 - 20,351 3,278 - 96

4

th 739,298 - 20,857 3,709 - 89

5

th 756,794 - 19,327 3,794 - 89

Totals - - 101,526 - - 481

* Habitat acreage based on the start of the decade (i.e., 2023, 2033, 2043, 2053, 2063) 

† No nesting habitat would be surveyed under Alternative A 

Table S-103. Decadal forecast (2013–2063) of marbled murrelet occupied sites discovered or lost under 

Alternative B 

Decade*

Nesting Habitat in the Decision Area

(Acres)

Occupied Sites Forecast in the Decision Area

(Number)

Totals

In the Harvest Scenario†

Totals

In the Harvest Scenario†

With 

Surveys

Without 

Surveys

Discovered 

and Protected Lost

Current 493,968 - - 2,459 - -

1

st 501,865 24,073 12,370 2,509 132 23

2

nd 569,953 23,948 5,469 2,844 110 10

3

rd 647,416 21,738 6,520 3,225 101 12

4

th 725,624 20,382 4,755 3,660 95 9

5

th 771,558 23,834 7,636 3,903 122 14

Totals - 113,975 36,751 - 559 67

* Habitat acreage based on the start of the decade (i.e., 2023, 2033, 2043, 2053, 2063) 

† Nesting habitat in Zone 1 (0–35 miles) would be surveyed under Alternative B 
1729 | P a g e

Table S-104. Decadal forecast (2013–2063) of marbled murrelet occupied sites discovered or lost under 

Alternative C 

Decade*

Nesting Habitat in the Decision Area

(Acres)

Occupied Sites Forecast in the Decision Area

(Number)

Totals

In the Harvest Scenario†

Totals

In the Harvest Scenario†

With 

Surveys

Without 

Surveys

Discovered 

and Protected Lost

Current 493,968 - - 2,459 - -

1

st 477,023 10,028 47,584 2,422 35 189

2

nd 515,784 11,057 36,788 2,635 34 174

3

rd 580,062 3,089 41,190 2,973 11 178

4

th 648,471 606 47,807 3,373 4 212

5

th 654,988 1,615 51,125 3,415 5 238

Totals - 26,395 224,494 - 89 992

* Habitat acreage based on the start of the decade (i.e., 2023, 2033, 2043, 2053, 2063) 

† Nesting habitat ≥ 120 years of age would be surveyed under Alternative C 

Table S-105. Decadal forecast (2013–2063) of marbled murrelet occupied sites discovered or lost under 

Alternative D 

Decade*

Nesting Habitat in the Decision Area

(Acres)

Occupied Sites Forecast in the Decision Area

(Number)

Totals

In the Harvest Scenario†

Totals

In the Harvest Scenario†

With 

Surveys

Without 

Surveys

Discovered 

and Protected Lost

Current 493,968 - - 2,459 - -

1

st 518,431 38,735 - 2,577 141 -

2

nd 602,023 21,684 - 3,002 74 -

3

rd 691,494 23,508 - 3,440 89 -

4

th 779,791 20,850 - 3,910 92 -

5

th 813,721 45,150 - 4,085 166 -

Totals - 149,928 - - 562 -

* Habitat acreage based on the start of the decade (i.e., 2023, 2033, 2043, 2053, 2063) 

† All nesting habitat would be surveyed under Alternative D 
1730 | P a g e

Table S-106. Decadal forecast (2013–2063) of marbled murrelet occupied sites discovered or lost under 

the Proposed RMP 

Decade*

Nesting Habitat in the Decision Area

(Acres)

Occupied Sites Forecast in the Decision Area

(Number)

Totals

In the Harvest Scenario†

Totals

In the Harvest Scenario†

With 

Surveys

Without 

Surveys

Discovered 

and Protected Lost

Current 493,434 - - 2,459 - -

1

st 505,612 21,331 7,162 2,524 97 13

2

nd 569,860 18,024 3,143 2,838 76 6

3

rd 648,415 11,571 3,758 3,246 42 7

4

th 734,794 13,702 2,586 3,710 69 5

5

th 778,175 18,333 4,723 3,932 91 9

Totals - 82,960 21,371 - 377 39

* Habitat acreage based on the start of the decade (i.e., 2023, 2033, 2043, 2053, 2063) 

† Nesting habitat in Zone 1 (0-35 miles) would be surveyed under the Proposed RMP 

Table S-107. Decadal forecast (2013–2063) of marbled murrelet occupied sites expected under the No 

Harvest reference analysis 

Decade*

Nesting Habitat in the Decision Area 

(Acres)

Occupied Sites Forecast in the Decision Area 

(Number)

Current 494,412 2,461

1

st 528,310 2,624

2

nd 621,274 3,080

3

rd 716,909 3,544

4

th 811,704 4,043

5

th 840,024 4,193

* Habitat acreage based on the start of the decade (i.e., 2023, 2033, 2043, 2053, 2063) 

North Oregon Coast Distinct Population Segment (DPS) 

of the Red Tree Vole 

Table S-108. North Oregon Coast DPS of the red tree vole habitat development in the decision area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 174,495 174,495 174,495 174,495 174,495 174,495 174,495

Alternatives/Proposed RMP

2023 178,193 180,881 176,827 167,096 183,914 177,605 189,994

2033 214,128 218,570 212,751 189,394 225,827 207,486 235,607

2043 246,181 245,961 241,608 211,800 256,326 235,129 268,416

2053 281,094 278,632 274,507 236,514 293,181 272,217 309,872

2063 289,971 279,899 279,489 236,047 294,208 277,503 313,820
1731 | P a g e

Table S-109. North Oregon Coast DPS of the red tree vole habitat development in the planning area 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

No Timber 

Harvest 

(Acres)

Current Condition

2013 741,263 741,263 741,263 741,263 741,263 741,263 741,263

Alternatives/Proposed RMP

2023 744,961 747,649 743,595 733,864 750,682 744,373 756,762

2033 780,896 785,337 779,518 756,161 792,595 774,254 802,375

2043 812,948 812,729 808,376 778,568 823,094 801,897 835,184

2053 847,862 845,400 841,275 803,282 859,949 838,985 876,640

2063 978,930 968,859 968,448 925,006 983,168 966,462 1,002,779

Table S-110. North Oregon Coast DPS of the red tree vole habitat in the Harvest Land Base 

Year No Action 

(Acres)

Alt. A 

(Acres)

Alt. B 

(Acres)

Alt. C 

(Acres)

Alt. D 

(Acres)

PRMP

(Acres)

Current Condition

2013 33,810 21,715 37,846 61,284 58,847 28,529

Habitat Capable 69,758 47,155 83,381 133,847 133,396 61,905

Alternatives/Proposed RMP

2023 36,316 17,779 35,739 49,993 62,055 23,853

2033 46,492 18,466 44,670 52,673 79,939 25,806

2043 52,777 17,616 48,865 55,996 93,221 25,344

2053 55,195 15,703 51,687 58,015 109,727 27,732

2063 55,478 12,862 49,519 51,496 108,764 26,339

Non-forest Habitat 

For the analyses of non-forest habitat types on both BLM-administered lands and on all other ownerships, 

the BLM used the ecological systems data (ESLF Codes and ESLF Names) available in the 2012 

Gradient Nearest Neighbor (GNN) (LEMMA 2014). There are 64 different ecological systems in the 

planning area. 

For simplicity, the BLM grouped and re-classified these 64 categories into 12 similar non-forest habitat 

groups. Refer to Table S-111 (Re-classification of non-forest habitats from GNN) for a complete list of 

the 64 ecological systems in the planning area and the BLM re-classification used in this analysis. 

The BLM assumed that the non-forest habitats would remain in their current condition throughout the 

analysis period (2013–2063). 
1732 | P a g e

Table S-111. Re-classification of non-forest habitats from GNN 

Gradient Nearest Neighbor BLM-reclassification

ESLF 

Code Ecological System Life Form (ESLF) Name Code Name

21 Developed, Open Space

1

Urban/

Developed

22 Developed, Low Intensity

23 Developed, Medium Intensity

24 Developed, High Intensity

61 Orchards Vineyards and Other High Structure Agriculture

81 Pasture/Hay 2 Agriculture

82 Cultivated Cropland

3118 North Pacific Alpine and Subalpine Bedrock and Scree

3 Rock

3128 Inter-Mountain Basins Volcanic Rock and Cinder Land

3129 Rocky Mountain Cliff, Canyon and Massive Bedrock

3140 North Pacific Volcanic Rock and Cinder Land

3155 North Pacific Montane Massive Bedrock, Cliff and Talus

3158 North Pacific Coastal Cliff and Bluff

3167 Mediterranean California Serpentine Barrens

3169 Central California Coast Ranges Cliff and Canyon

3170 Klamath-Siskiyou Cliff and Outcrop

7162 North Pacific Herbaceous Bald and Bluff

9297 Inter-Mountain Basins Alkaline Closed Depression

5258 Inter-Mountain Basins Mixed Salt Desert Scrub 4 Desert 5456 Inter-Mountain Basins Semi-Desert Shrub Steppe

3165 Mediterranean California Northern Coastal Dune

5 Dunes

3177 North Pacific Maritime Coastal Sand Dune and Strand

5205 North Pacific Dry and Mesic Alpine Dwarf-Shrubland, Fell-field and 

Meadow

6

Grassland/

Prairie

5409 Willamette Valley Upland Prairie and Savanna

5452 Columbia Plateau Steppe and Grassland

7102 California Mesic Serpentine Grassland

7103 California Northern Coastal Grassland

7108 Mediterranean California Alpine Dry Tundra

7109 Mediterranean California Subalpine Meadow

7110 North Pacific Montane Grassland

7112 Northern Rocky Mountain Lower Montane, Foothill and Valley 

Grassland

7157 North Pacific Alpine and Subalpine Dry Grassland

8404 Introduced Upland Vegetation – Annual Grassland

8502 Recently burned grassland

9221 Willamette Valley Wet Prairie

9265 Temperate Pacific Montane Wet Meadow

3179 Inter-Mountain Basins Playa

7 Shrubland 5202 Columbia Plateau Scabland Shrubland
1733 | P a g e

Gradient Nearest Neighbor BLM-reclassification

ESLF 

Code Ecological System Life Form (ESLF) Name Code Name

5260 North Pacific Avalanche Chute Shrubland

5261 North Pacific Montane Shrubland

5305 California Xeric Serpentine Chaparral

5311 Northern and Central California Dry-Mesic Chaparral

5457 Northern California Coastal Scrub

7161 North Pacific Hypermaritime Shrub and Herbaceous Headland

9103 Inter-Mountain Basins Greasewood Flat

5256 Great Basin Xeric Mixed Sagebrush Shrubland

8 Sagebrush

5257 Inter-Mountain Basins Big Sagebrush Shrubland

5453 Columbia Plateau Low Sagebrush Steppe

5454 Inter-Mountain Basins Big Sagebrush Steppe

5455 Inter-Mountain Basins Montane Sagebrush Steppe

9321 Columbia Plateau Silver Sagebrush Seasonally Flooded Shrub-Steppe

2201 Open Water (Fresh)

9

Freshwater/

Riparian

3122 Temperate Pacific Freshwater Mudflat

9166 North Pacific Bog and Fen

9173 North Pacific Shrub Swamp

9219 Temperate Pacific Freshwater Aquatic Bed

9220 North Pacific Intertidal Freshwater Wetland

9222 North American Arid West Emergent Marsh

9248 Mediterranean California Subalpine-Montane Fen

9260 Temperate Pacific Freshwater Emergent Marsh

9251 Northern California Claypan Vernal Pool 10 Vernal Pool

2202 Open Water (Brackish/Salt)

11 Marine 9281 Temperate Pacific Tidal Salt and Brackish Marsh

3130 North American Alpine Ice Field 12 Ice
1734 | P a g e

Table S-112. Non-forest habitat within the decision and planning areas 

Structural Stage Decision Area Planning Area

(Acres) (Percent) (Acres) (Percent)

Urban/Developed 11,434 12% 1,061,331 24%

Agricultural 1,951 2% 2,193,206 51%

Rock 1,710 2% 76,278 2%

Desert 9 0% 32 0%

Dunes 1,300 1% 37,611 1%

Grassland 3,795 4% 290,284 7%

Shrubland 2,936 3% 59,616 1%

Sagebrush 63,884 70% 246,644 6%

Freshwater Riparian 4,164 5% 348,773 8%

Vernal Pools 307 0% 7,668 0%

Marine/Tidal 236 0% 16,464 0%

Ice 27 0% 3,335 0%

Totals 91,752 100% 4,341,241 100%

Non-BLM Forest Habitat 

The BLM modeled forest habitat on non-BLM-administered lands within the planning area using the 

2012 GNN structural condition (STRUCCOND) (LEMMA 2014). 

So that the GNN-derived habitat on non-BLM-administered lands could be readily compared with the 

Woodstock-derived forest habitat on BLM-administered lands, the BLM cross-walked the GNN 

STRUCCOND to the Woodstock structural stage categories (Table S-113).
1735 | P a g e

Table S-113. Cross-walk of GNN STRUCCOND to Woodstock structural stages 

GNN STRUCCOND Woodstock Structural Stage

Code Description* Code Structural Stage

0 Non-forest - Non-forest

1 Sparse (CANCOV < 10%) 1.1 Early Successional: with Structural Legacies

1.2 Early Successional: without Structural Legacies

2 Open (CANCOV 10–40%) 2.1 Stand Establishment: with Structural Legacies

2.2 Stand Establishment: without Structural Legacies

3

and

4

Sapling/pole - moderate/closed 

(CANCOV>40, QMD_DOM <

25cm)

Small/medium tree -

moderate/closed (CANCOV ≥ 40, 

QMD_DOM 25–50)

3.1 Young: High Density with Structural Legacies

3.2 Young: High Density without Structural Legacies

3.3 Young: Low Density with Structural Legacies

3.4 Young: Low Density without Structural Legacies

5

Large tree - moderate/closed 

(CANCOV ≥ 40, QMD_DOM 

50–75)

4.1 Mature: Single-layered Canopy

4.2 Mature: Multi-layered Canopy

6

Large/giant tree - moderate/closed 

(CANCOV ≥ 40, QMD_DOM ≥

75)

5.1 Structurally-complex: Developed Structurallycomplex

5.2 Structurally-complex: Existing Old Forest

5.3 Structurally-complex: Existing Very Old Forest

* STRUCCOND Descriptions from LEMMA 2014 

The BLM modeled the structural conditions on non-BLM-administered lands as continuing to provide the 

same distribution of habitat through time as the current condition, except in U.S. Forest Service reserves 

(i.e., Late-Successional Reserve and Congressionally Reserved lands). 

The BLM modeled structural conditions continuing to develop on U.S. Forest Service reserve lands 

through time based on comparison to the mean ages of the Woodstock structural stages on the BLMadministered forestlands (Table S-114).
1736 | P a g e

Table S-114. Assumptions for development of structural stages on non-BLM-administered lands 

Code Structural Stage

Mean 

Age*

(Years)

BLM Assumption for

Forest Habitat Development

on Non-BLM-administered 

lands

1.1 Early Successional: with Structural Legacies 10.3 Pixel stays in Early Successional 

1.2 Early Successional: without Structural Legacies group for 1 decade

2.1 Stand Establishment: with Structural Legacies 24.7 Pixel stays in Stand 

2.2 Stand Establishment: without Structural Legacies Establishment group for 1 decade

3.1 Young: High Density with Structural Legacies

66.5 Pixel stays in Young group for 4 

decades

3.2 Young: High Density without Structural Legacies

3.3 Young: Low Density with Structural Legacies

3.4 Young: Low Density without Structural Legacies

4.1 Mature: Single-layered Canopy 95.6 Pixel stays in Mature group for 3 

4.2 Mature: Multi-layered Canopy decades

5.1 Structurally-complex: Developed Structurallycomplex

160.4 Once a pixel enters Structurally5.2 Structurally-complex: Existing Old Forest complex group, it remains there

5.3 Structurally-complex: Existing Very Old Forest

* Mean age calculated using age on BLM-administered lands. 

The BLM assumed in this modeling that habitat on U.S. Forest Service reserve lands would not develop 

on lands that experience wildfire in the modeling (see the vegetation modeling section in Chapter 3). 

For the purpose of this analysis, the BLM assumed that the future distribution of habitat conditions on 

non-BLM-administered lands and burned, U.S. Forest Service reserve lands would continue to reflect the 

current distribution of habitat conditions. 

On private lands, the assumption that the future distribution of habitat conditions would remain the same 

as current conditions is likely to be a reasonable approximation. On State and U.S. Forest Service nonreserve lands, this assumption is likely to be an underestimate of the future development of habitat. The 

BLM acknowledges that the spatial arrangement of structural conditions would change in the future, but 

lacks information to make more specific projections of how structural conditions would change over time 

on non-BLM-administered lands. This assumption is consistent with the assumption used in the analysis 

of forest structure and spatial pattern in the 2008 FEIS, which describes the limitations on analyzing 

future changes on non-BLM-administered lands and is incorporated here by reference (USDI BLM 2008, 

pp. 532–536). 
1737 | P a g e

Appendix T – Northern Spotted Owl 

Forecasting Habitat Change, and Northern Spotted Owl 

Population Responses, in Washington, Oregon and California 

The U.S. Fish and Wildlife Service used HexSim (Schumaker 2011)—a spatially explicit, individualbased, population model—to help inform its decisions on northern spotted owl recovery and the 

delineation of northern spotted owl critical habitat. The U.S. Fish and Wildlife Service described the 

development and parameterization of its HexSim model in USDI FWS 2011 (pp. Appendix C) and USDI 

FWS 2012. 

Early in its planning process, the BLM sought the advice of federal experts familiar with the applications 

of HexSim and other population models to inform management decisions. Based on its review, the BLM 

chose to use the northern spotted owl HexSim model developed by the U.S. Fish and Wildlife Service to 

inform its decisions on northern spotted owl recovery and the delineation of northern spotted owl critical 

habitat (USDI FWS 2011, pp. Appendix C, and USDI FWS 2012). The BLM did this because: 

 Federal experts familiar with similar models had found HexSim to be as reliable as those models 

while requiring less calibration and time to operate. 

 The U.S. Fish and Wildlife Service had developed its HexSim model through a peer-reviewed process 

and with the advice and assistance of northern spotted owl experts from throughout the northern 

spotted owl’s range.

 The range-wide scale of the U.S. Fish and Wildlife Service HexSim model suited the BLM’s 

analytical needs. 

 The BLM was one of the cooperators that had advised the U.S. Fish and Wildlife Service during the 

development of its HexSim model and, thus, already was familiar with its operation and applications. 

 The BLM determined that it could use the U.S. Fish and Wildlife Service’s model, fully 

parameterized, to meet its specific planning needs with considerable savings in cost and time. 

 The U.S. Fish and Wildlife Service already was familiar with the development and applications of its 

model. Since the U.S. Fish and Wildlife Service would advise the BLM during the development of 

the RMP, and the U.S. Fish and Wildlife Service eventually would render a biological opinion on the 

Proposed RMP, the BLM determined that the U.S. Fish and Wildlife Service’s HexSim model would 

best suit its requirements for evaluating the potential effects of the alternatives and the Proposed RMP 

on northern spotted owl populations.

The BLM did not modify any of the population parameters in the U.S. Fish and Wildlife Service’s 

HexSim model. The only difference between the U.S. Fish and Wildlife Service’s use of its HexSim 

model and the BLM’s use was that the BLM recalibrated the time step that corresponded to the year 2013. 

The U.S. Fish and Wildlife Service calibrated its HexSim model to run with northern spotted owl relative 

habitat suitability surfaces (i.e., digitized geospatial datasets used for computer analyses), which it derived 

using 1996 and 2006 Gradient Nearest Neighbor (GNN) data developed by the U.S. Forest Service 

(Ohmann and Gregory 2002). Relative habitat suitability values range from 0 to 100, with higher numbers 

signifying better habitat value. The values themselves are derived from a variety of biotic and abiotic 

variables, such as the amount of forest canopy cover, mean tree diameter, and degree and direction of 

terrain slope. To create its relative habitat suitability surfaces, the U.S. Fish and Wildlife Service used 

MaxEnt (Phillips et al. 2006) to compare variables present on broad landscapes with those associated with 

known northern spotted owls nest sites.
1738 | P a g e

Concurrent with the U.S. Fish and Wildlife Service process, the U.S. Forest Service created a separate set 

of northern spotted owl relative habitat suitability surfaces to evaluate implementation of the Northwest 

Forest Plan (Davis et al. 2011). The U.S. Forest Service based its surfaces on a unique set of MaxEnt 

models that it also derived using 1996 and 2006 GNN data (Davis et al. 2011, pp. 27–28).46 Differences 

between the two processes included: 

 The two agencies used different variable scales to create their MaxEnt models. The U.S. Forest 

Service variables were specific to 30 × 30-m pixels (Davis et al. 2011, p. 28), whereas the U.S. 

Fish and Wildlife Service variables were at the scale of 200 ha (USDI FWS 2012, p. 84). 

 The two agencies trained their MaxEnt models to geographically different modeling regions 

(Davis et al. 2011, p. 35 and USDI FWS 2011, p. C-13). 

 Whereas the U.S. Forest Service trained its MaxEnt models primarily on discrete variable values, 

which could change independently (Davis et al. 2011, p. 99), the U.S. Fish and Wildlife Service 

trained its MaxEnt models on a combination of discrete and compositional variables. 

Compositional variables are combinations of discrete variables, all of which must be present 

(USDI FWS 2012, p. C-38). 

 The U.S. Forest Service used LandTrendr to examine changes in forest stand conditions from 

1996 to 2006 from timber harvest, insects and disease, and wildfire (Davis et al. 2011, pp. 28, 29, 

121–125). 

Before the BLM northern spotted owl modeling process began, the BLM decided to use Woodstock for 

its planning process to forecast changes in forest stand growth and timber yield variables on the decision 

area (i.e., the BLM-administered lands in the planning area) (see the Vegetation Modeling Section in 

Chapter 3). Therefore, for the northern spotted owl modeling, the BLM created relative habitat suitability 

surfaces for the decision area that changed each decade for five decades (see Chapter 3, Northern Spotted 

Owl), using Woodstock variable outputs. In addition, to generate credible range-wide simulations of 

northern spotted owl demographic responses to the alternatives and the Proposed RMP using HexSim, the 

BLM: 

 Created relative habitat suitability surfaces for all ‘other lands’ (i.e., lands other than BLMadministered lands in the planning area) within the northern spotted owl’s range so that simulated 

northern spotted owls could move across planning area boundaries and respond to habitat 

conditions on all land ownerships inside and outside the planning area, and; 

 Forecasted changes to those surfaces from forest ingrowth, timber harvest, and wildfire at the 

same decadal increments as its Woodstock model, something not done by either the U.S. Forest 

Service or U.S. Fish and Wildlife Service. 

Thus, to simulate habitat conditions on the decision area, the BLM could not use the U.S. Forest Service 

or U.S. Fish and Wildlife Service relative habitat suitability surfaces, because the BLM needed to vary the 

relative habitat suitability surfaces according to each of the alternatives and the Proposed RMP and over 

time, using variables derived from Woodstock. 

 

46 Both the U.S. Fish and Wildlife Service and U.S. Forest Service trained their MaxEnt models using 1996 GNN 

data because the intent was to develop models that predicted the relative habitat suitability for northern spotted owls 

when competitive interactions with barred owl still were relatively uncommon. For this purpose, 1996 GNN data are 

better than 2006 and 2012 GNN data because, when associated with northern spotted owl nesting-roosting location 

data, they better represent the association between habitat conditions and northern spotted owl occupancy before 

later displacements of northern spotted owls by barred owls. Once the models were trained, both agencies projected 

their models to 2006 GNN data, the most recent data available. Hence, throughout the remainder of Section S-A, 

when the BLM refers to U.S. Fish and Wildlife Service 2006 GNN MaxEnt models or U.S. Forest Service 2006 

GNN MaxEnt models it always means models developed with 1996 GNN data and applied to 2006 data. 
1739 | P a g e

To simulate habitat conditions on other lands within the northern spotted owl’s range, the BLM originally 

hoped to build upon the relative habitat suitability surfaces developed by the U.S. Forest Service because: 

 The similarity of scale between the BLM Woodstock variables and the U.S. Forest Service GNN 

variables potentially made it easier for the BLM to merge its relative habitat suitability surfaces 

for BLM-administered lands with those generated by the U.S. Forest Service for other lands; 

 Since Woodstock generates individual variable values, instead of compositional variable values, 

the BLM could more-directly compare its MaxEnt models to those created by the U.S. Forest 

Service, and; 

 Woodstock could generate the same variable values used by the U.S. Forest Service to create its 

relative habitat suitability surfaces, which potentially made the BLM and U.S. Forest Service 

surfaces more compatible. 

In addition, the BLM initially hoped that unpublished U.S. Forest Service LandTrendr results could help 

it forecast habitat changes on other lands. 

Therefore, the BLM programmed Woodstock to generate the same variables used by the U.S. Forest 

Service GNN MaxEnt models (see Davis et al. 2011, p. 99) and, using those variables, planned to apply 

the U.S. Forest Service’s MaxEnt models to the decision area. The BLM initially hoped that there would 

be sufficient compatibility between the relative habitat suitability surfaces generated from the Woodstock 

and GNN datasets so that the BLM could use the Woodstock variable outputs for the decision area and 

the GNN variable outputs for all other lands. If the two sets of variable outputs were insufficiently 

compatible, the BLM could add a stand age variable to the Woodstock outputs to correlate the two 

relative habitat suitability surfaces. 

Unfortunately, as described below under Model 1, the BLM found that the U.S. Forest Service MaxEnt 

models would not work in this way. Subsequently, the BLM went through an iterative process (described 

under models 1–13) to identify and account for design differences between the U.S. Forest Service and 

U.S. Fish and Wildlife Service GNN MaxEnt models so that the BLM could use the HexSim model 

developed by the U.S. Fish and Wildlife Service —with little or no recalibration—with relative habitat 

suitability surfaces that utilized both Woodstock data for the decision area and GNN data for other lands. 

A. Developing MaxEnt Models for the Decision Area

Objectives and Selection Criteria 

Since the BLM initially sought to use the U.S. Forest Service’s GNN MaxEnt models, it first evaluated 

whether doing so was reasonable for its planning purposes. The BLM used three model assessment 

criteria to evaluate the utility of the U.S. Forest Service, and subsequently other, MaxEnt models: 

1) Whether the current-year relative habitat suitability surface generated by the MaxEnt models had 

a strong correlation47 with that generated by the U.S. Fish and Wildlife Service’s MaxEnt models. 

The U.S. Fish and Wildlife Service calibrated its northern spotted owl HexSim model to its own 

relative habitat suitability surface. If the new relative habitat suitability surfaces were strongly 

correlated to the U.S. Fish and Wildlife Service’s surface, the BLM could use the U.S. Fish and 

Wildlife Service’s HexSim model with the new surfaces with relatively little recalibration of the 

HexSim model. However, if they were not strongly correlated, a long and detailed recalibration of 

the HexSim model would be needed. The BLM preferred to avoid a lengthy recalibration. 

 

47 Strong correlation: The BLM, knowing the substantive differences between the origins of the Woodstock and 

GNN datasets, did not choose an a priori minimum correlation coefficient. Instead, the BLM sought for the highest 

correlation coefficient it could achieve with the available datasets, and then determined if the coefficient were 

sufficiently strong to allow the BLM to proceed with its analyses.
1740 | P a g e

2) Whether the relative habitat suitability models applied to BLM-administered lands performed 

similarly48 to those applied to non-BLM-administered lands. The spatial scale for evaluating the 

effects of alternatives and the Proposed RMP on the northern spotted owl population was to occur 

over the entire geographic range of the northern spotted owl, within modeling regions, and at 

smaller scales. Hence, the BLM needed the models to perform similarly on the decision area and 

all other lands within the northern spotted owl’s range.

3) Relative habitat suitability surfaces developed for the decision area had to be derived from the 

forest growth and timber yield variables generated by Woodstock, the most accurate data for 

those lands. 

To determine if criterion 2 were met, the BLM evaluated how its models worked under the No Timber 

Harvest reference analysis by evaluating the portions of the decision area that occurred in various relative 

habitat suitability value bins and strength-of-selection bins (see Model 8, below, the first model so 

evaluated, for more information). This was a heuristic evaluation of the ‘reasonableness’ of the model(s) 

applied to decadal changes according to the No Timber Harvest reference analysis. The BLM forecasted 

changes at decadal intervals for 50 years. If the model(s) worked well, there would be a steady decrease in 

the portion of BLM-administered lands in low relative habitat suitability value bins and increases in the 

proportion of that land in higher relative habitat suitability value bins. This evaluation was heuristic 

because the BLM knew the general trajectory that would be seen if the model(s) worked reasonably well, 

even though it did not know the specific extent of that change. 

Here, the BLM describes its process to develop relative habitat suitability surfaces that met its three 

assessment criteria. Figure T-1 outlines the process. 

 

48 In this context, models ‘performed similarly’ in terms of their relative progressions, over time, through relative 

habitat suitability bins and strength-of-selection bins. See Model 8, below, the first model so evaluated, for 

descriptions of these analyses. 
1741 | P a g e

Figure T-1. Flowchart of the BLM MaxEnt modeling sequence 

Note: ME refers to MaxEnt 

Model 1 

The BLM first conducted range-wide comparisons of the U.S. Forest Service (Davis et al. 2011) and U.S. 

Fish and Wildlife Service (USDI FWS 2011, pp. Appendix C) relative habitat suitability surfaces. The 

BLM overlaid the geographic range of the northern spotted owl with a grid of 86.6-ha hexagons—the grid 

used by the U.S. Fish and Wildlife Service’s HexSim model (USDI FWS 2012, p. 24)—and compared the 

relative habitat suitability values of both sets of models in each hexagon. As shown in Figure T-2 the two 

sets of models produced dissimilar results; the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models 

estimated more of the landscape to be in the lowest (relative habitat suitability values 0–10) and highest 

(values greater than 40) bins, whereas the USDA FS 2006 GNN MaxEnt models estimated more of the 

landscape to be in the middle (values 11–40) bins. These results were not unexpected because, as 

described above, the U.S. Forest Service and U.S. Fish and Wildlife Service calculated relative habitat 

suitability values at different scales. 
1742 | P a g e

Figure T-2. Distribution of hexagons relative habitat suitability scores among various bins from 2006 

GNN MaxEnt models developed by the U.S. Fish and Wildlife Service and the U.S. Forest Service 

Source: USDI FWS 2011, pp. Appendix C; Davis et al. 2011 

The correlation (Pearson r) between hexagon relative habitat suitability values for the two sets of models 

was 0.765. The BLM sought a stronger relationship as well as greater similarity in the distribution of 

relative habitat suitability scores. The BLM determined that the U.S. Forest Service 2006 GNN MaxEnt 

models failed assessment criterion 1. 

Model 2 

The Model 1 results suggested the influence of an artifact-of-scale; i.e., the correlation would have been 

stronger if the two sets of MaxEnt models had been calculated at the same scale. Therefore, the BLM ran 

the comparison again at the 200-ha scale used by the U.S. Fish and Wildlife Service because the GNN 

data in part were derived from satellite imagery, the spatial accuracy of which increases with scale. Stated 

another way, although the GNN variable data reasonably describe forest conditions on a landscape, they 

are less accurate at the 30 × 30 m pixel scale used by the U.S. Forest Service (see Ohmann and Gregory 

2002 and http://www.fs.fed.us/wwetac/projects/ohmann.html). The BLM chose the 200-ha scale, because 

the BLM intended to use its relative habitat suitability surfaces with the U.S. Fish and Wildlife Service’s 

HexSim model, in which simulated northern spotted owls ‘select’ habitat from a relative habitat 

suitability surface, and the scale at which northern spotted owls are known to strongly select habitat is the 

200-ha (i.e., ~ 500-acre) core use area (see Chapter 3, Northern Spotted Owl). 

MaxEnt examines a variety of variables associated with known northern spotted owl nest locations and 

identifies those variables and combinations of variables, and the relative importance of each 

variable/combination, that best discriminate between occupied and available locations. The U.S. Forest 

Service (Davis et al. 2011) divided the northern spotted owl range into six modeling regions and used 

MaxEnt to identify and weigh the best variables/combinations in each region, creating a unique MaxEnt 

model for each region. To alter the scale of the U.S. Forest Service relative habitat suitability surface, the 

BLM ran MaxEnt on the same modeling regions defined by the U.S. Forest Service, using the U.S. Forest 

Service 1996 GNN MaxEnt model for each region, but at the 200-ha scale. In other words, the BLM 

44.0

14.9

12.5 11.1

8.9

5.8

2.3

0.5 0.0

33.8

25.0

18.4

14.1

7.5

1.2 0.1 0.0 0.0

0

5

10

15

20

25

30

35

40

45

50

0–10 11–20 21–30 31–40 41–50 51–60 61–70 71–80 > 81

Percentage of Hexagons

Relative Habitat Suitability Bins

USDI FWS 2011 Davis et al. 2011
1743 | P a g e

created a new set of MaxEnt models (Model 2) by running MaxEnt, with the region-specific models 

developed by the U.S. Forest Service, to calculate new relative habitat suitability values for each 30 × 30-

m pixel based on the mean of the values of each variable within the 200-ha circle around each pixel. 

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt model and the Model 2 

estimated relative habitat suitability for hexagons was 0.770. To meet assessment criterion 1, the BLM 

sought a stronger relationship. 

Model 3 

Keeping in mind that the U.S. Forest Service (Davis et al. 2011) and the U.S. Fish and Wildlife Service 

(USDI FWS 2011) developed their MaxEnt models for different purposes, the BLM addressed another 

difference between the two model sets. The U.S. Forest Service MaxEnt models used northern spotted 

owl nest and pair roost sites from the demographic study areas supplemented by a random subset of 

northern spotted owl pair sites from the 10-year monitoring report training data set (Davis and Lint 2005) 

that were outside of the study area boundaries and spaced no nearer to each other than the mean nearest 

neighbor distance for that modeling region (Ray Davis, U.S. Forest Service, personal communication via 

e-mail to Eric Greenquist, October 21, 2014). In contrast, the U.S. Fish and Wildlife Service MaxEnt 

models considered a subset of all known sites (USDI FWS 2011, p. C-21). Because northern spotted owl 

known nest sites tend to occur at greater densities in better habitat, and in areas that received more survey, 

when MaxEnt considers all sites, it calculates formulas that can be biased by the similarity of the 

variables around proximal sites. To help control for this, the U.S. Forest Service and U.S. Fish and 

Wildlife Service used different approaches to limit the number of known sites MaxEnt could consider 

(i.e., aware of biased datasets, the agencies took different steps to reduce the bias). For Model 3, and all 

subsequent models, the BLM used the same northern spotted owl locations used by the U.S. Fish and 

Wildlife Service. 

The BLM also used the same MaxEnt feature sets used by the U.S. Fish and Wildlife Service. Features, in 

MaxEnt, refer to the functional forms or shapes of relationships evaluated in MaxEnt. The BLM did this 

to determine if it could use variables used by the U.S. Forest Service (albeit, at the different scale) and 

that the BLM could estimate with Woodstock, while, at the same time, minimizing other differences 

between the U.S. Forest Service and the U.S. Fish and Wildlife Service models so that the differences in 

the respective relative habitat suitability surfaces would not be a function of the differences in either 

training location or MaxEnt specifications (e.g., the features used). 

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 3 

estimated relative habitat suitability for hexagons was 0.815, an improvement from previous models. 

Although the BLM determined that this correlation coefficient was sufficiently strong to meet assessment 

criterion 1, it sought a stronger relationship.49

Model 4 

Model 4 was identical to Model 3 except that the BLM returned to the MaxEnt features used by the U.S. 

Forest Service (Davis et al. 2011). The correlation between the U.S. Fish and Wildlife Service 2006 GNN 

MaxEnt models and the Model 4 estimated relative habitat suitability for hexagons was 0.817, nearly 

identical to that of Model 3, indicating that models 3 and 4 were nearly identical in their predictive 

capabilities. 

49 Although the BLM did not set an a priori correlation coefficient to evaluate model assessment criterion 1, 

statisticians commonly consider a Pearson r coefficient above 8.0 to be strong or very strong (e.g., Dancey and 

Reidy 2004). 

 
1744 | P a g e

Model 5 

Model 5 was identical to Model 3 except that the BLM added the abiotic variables elevation, curvature, 

and relative slope position index (USDI FWS 2011, p. C-25 and Table C9). The correlation between the 

U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 5 estimated relative habitat 

suitability for hexagons increased to 0.871. The BLM determined that this correlation coefficient met 

criterion 1, but it evaluated whether a stronger relationship was possible. 

Model 6 

Model 6 was identical to Model 5 except that the BLM redeveloped the variable rasters to match the 

methods used by the U.S. Fish and Wildlife Service (USDI FWS 2011, p. C-60). The BLM generated 

GNN variable rasters using buffered U.S. Forest Service modeling regions to eliminate edge effect. 

Because variable values reflect the mean of all values within a 200-ha circle, the MaxEnt model for a 

modeling region can be influenced by the lack of data beyond the regional boundary (i.e., up to 800 m 

beyond the boundary, the area potentially within the radius of a 200-ha circle). Buffering the modeling 

region caused MaxEnt to clip data at the regional boundary and calculate mean values from only variable 

values within the region. 

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 6 

estimated relative habitat suitability for hexagons was 0.873. The BLM evaluated whether a stronger 

relationship was possible. 

Model 7 

Model 7 was identical to Model 6 except that the BLM masked those portions of western Oregon, such as 

the Willamette Valley and Puget Lowlands that, due to limited habitat, support few, if any, northern 

spotted owls. This forced MaxEnt to consider more subtle associations between northern spotted owl sites 

and the habitat variables associated with those sites. In the BLM MaxEnt analyses, masked areas became 

unavailable to be included in the random subset of available locations to which MaxEnt compared 

locations occupied by northern spotted owls. Masking these areas resulted in MaxEnt formulas based on 

forests in which northern spotted owls occurred compared to other, available, forested areas rather than to 

the broader array of habitat types, some of which were unoccupied by northern spotted owls. This 

eliminated major areas of non-potential habitat from the models. 

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 7 

estimated relative habitat suitability for hexagons was 0.875. 

Through the development of Model 7, the BLM had worked to refine the compatibility of the BLM 

regional MaxEnt models with those used by the U.S. Fish and Wildlife Service in its HexSim model. As 

stated earlier, the BLM saw the opportunity to use the unpublished U.S. Forest Service (Davis et al. 2011) 

LandTrendr data to help it forecast changes in relative habitat suitability values on other lands within the 

northern spotted owl range (lands other than BLM-administered lands in the planning area), and the BLM 

saw the opportunity to use the U.S. Fish and Wildlife Service’s HexSim model to forecast northern 

spotted owl population responses. With a 0.875 correlation between the Model 7 relative habitat 

suitability surfaces and those developed by the U.S. Fish and Wildlife Service (both of which used 2006 

GNN data), the BLM was confident of its reconciliation. 
1745 | P a g e

Model 8 

Beginning with Model 8, the BLM replaced the 2006 GNN variable values for the decision area with 

those produced by Woodstock for 2013. Because the BLM, at this stage, was developing relative habitat 

suitability surfaces for its administered lands within the planning area, the BLM also begin limiting this, 

and subsequent models, to the three western Oregon modeling regions defined by the U.S. Forest Service: 

the Oregon Coast Range, Oregon and California Cascades, and Oregon and California Klamath modeling 

regions (Davis et al. 2011, p. 35). Finally, the BLM added the hinge feature to MaxEnt, adding this 

feature to the threshold, quadratic and linear features the BLM had added to Model 3. Adding the hinge 

feature allowed MaxEnt to consider more subtle associations between variables, an attempt to improve its 

predictive capability. 

With these changes, the BLM began an iterative modeling process to—

1. Project the current MaxEnt model for each of the three western Oregon modeling regions to the 

Woodstock variables (i.e., beginning with Model 8, apply the Model 8 MaxEnt formulas to the 

2013 Woodstock-generated variable values for the decision area) by using the MaxEnt .lamdas 

files from the model developed with the 1996 GNN data;50

2. Evaluate the projected MaxEnt outputs by (a) relative habitat suitability bins and (b) strength-ofselection habitat class distributions51 through the decadal time-series (2013-2063); 

3. Refine the model variables (i.e., generate new models, beginning with Model 9), and; 

4. Repeat steps 1 through 3 with each set of new and refined MaxEnt models until all three of the 

assessment criteria were met. 

As further explanation, MaxEnt is a multivariate model; i.e., its predictions are influenced by both the 

state of individual variables and how each variable co-varies with the other model variables. The U.S. 

Fish and Wildlife Service (USDI FWS 2011) and U.S. Forest Service (Davis et al. 2011) MaxEnt models 

were projected to 2006 GNN data. In contrast, for the decision area, the BLM would use the variable 

values derived from Woodstock. Thus, the BLM began evaluating how the 2006 GNN- and 2013 

Woodstock-derived variables co-varied. 

Figure T-3 shows scatterplots of the relationship between each pair of the biotic variables from 2006 

GNN data (left) and 2013 Woodstock data (right) for the decision area. The BLM did not evaluate abiotic 

variables because the sources of those variables are the same for both models. For the initial comparisons, 

the BLM evaluated 2006 GNN data (the most recent dataset available at the time) and Woodstock’s 

estimates for 2013 conditions on the decision area. It is important to note that the GNN and Woodstock 

datasets were derived through substantively different processes, so the BLM anticipated substantive, 

albeit undefined, differences between the two datasets. 

 

50 To clarify: The BLM developed all of its MaxEnt models using 1996 GNN data, then projected those models to 

2006 GNN, 2012 GNN and 2013 Woodstock data. 

51 Based on its modeling needs (see Chapter 3, Northern Spotted Owl), the BLM divided northern spotted owl 

habitat into categories based on strength-of-selection. This was similar to the process used by the U.S. Fish and 

Wildlife Service (USDI FWS 2011, pp. C-31 – C-39) but, in the BLM’s case, the BLM used four categories: (1) 

‘strongly selected against,’ (2) ‘selected against,’ (3) ‘selected for,’ and (4) ‘strongly selected for.’ For additional 

information, see Sections C of this appendix. 
1746 | P a g e

Figure T-3. Bivariate scatterplots for select 2006 GNN variables for the three western Oregon modeling regions (left) and 2013 Woodstock 

variables for the decision area (right) 

Note: Both matrices display the XY scatter plots for each pair of variables, using a non-linear LOWESS smoother (locally-weighted scatterplot smoothing, a type of nonparametric regression) for the fitted line, in the lower left, the covariate histogram for each pair of variables across the diagonal, and the Pearson’s correlation coefficient for each 

pair of variables in the upper right. Variable abbreviations are defined in the text, below, except DBHC, which refers to the mean trunk diameter of conifers, similar to quadratic 

mean trunk diameter of dominate and co-dominate conifers (QMDC_13). 
1747 | P a g e

The comparisons revealed very different relationships between stand age (AGE in Figure T-3) and 

canopy cover of all conifers (CCC), stand age and stand height (STNDHT), stand age and the number of 

large conifer trees per hectare (TPHC), canopy cover of all conifers and stand height, canopy cover of all 

conifers and stand diameter diversity index (DDI), canopy cover of all conifers and quadratic mean trunk 

diameter of conifers (QMDC), and canopy cover of all conifers and the number large conifer trees per 

hectare. Most disconcerting were the differences in the relationships of conifer canopy cover to stand 

height, diameter diversity index, mean conifer trunk diameter, and the number of large conifer trees per 

hectare. In all cases, Woodstock estimated that, as canopy cover increased beyond approximately 70 

percent, each of these variables would decrease. In contrast, GNN represented these same relationships as 

increasing in all cases, though the rate of increase varied from slight (number of large conifer trees per 

hectare) to rapid (stand height and stand diameter diversity index). 

In accordance with assessment criterion 2 the BLM also compared the models in terms of decadal 

progressions of relative habitat suitability. To this point, the correlations the BLM had calculated were 

between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the BLM 2006 GNN MaxEnt 

models at both modeling region and range-wide scales. For the BLM Woodstock models, the focus of the 

evaluation was the temporal trend in relative habitat suitability and habitat distributions. Given that the 

first projection of habitat change in the BLM’s Woodstock model was the No Timber Harvest reference 

analysis, the BLM expected that the percentage of BLM-administered lands with low relative habitat 

suitability would decrease while the percentage in intermediate and higher relative habitat suitability 

would increase. The BLM based this expectation on its knowledge that northern spotted owls 

preferentially select areas with larger trees and more structural complexity and, as trees get older, they get 

larger, and such forests acquire more structural diversity. The BLM did not have a specific expectation on 

the exact quantity or percentage of BLM-administered lands in lower, intermediate, and high relative 

habitat suitability bins, only of the trends over time in each of those bins. The BLM’s evaluations were 

meant to check on the trends. 

However, as shown in Figure T-4, although the temporal trends in relative habitat suitability showed a 

reduction over time in the percentage of the landscape in the lowest relative habitat suitability categories 

and an increase in the highest relative habitat suitability category, the trend in the intermediate categories 

(40–50, 50–60, 60–70) were in the opposite direction than what was expected, particularity in the Oregon 

and California Cascades Modeling Region (Figure T-4 B).
1748 | P a g e

Figure T-4. No Timber Harvest: distribution of relative habitat suitability by decade for Model 8, on the 

decision area (A and C), and on BLM-administered lands in the Oregon and California Cascades 

Modeling Region (B) 

Note: Histograms A and B show BLM-administered lands in each relative habitat suitability bin at the start of each of six 

decades. Histogram C shows BLM-administered lands in each strength-of-selection bin at the start of each of six decades.

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2013 2023 2033 2043 2053 2063

A

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1749 | P a g e

In part, these trends in variable value with age and relative habitat suitability progression arose because 

the models generated from Woodstock variable data were not always indicative of how forests on BLMadministered lands develop. For example, an existing 140-year-old stand on BLM-administered lands 

does not exhibit the structural characteristics that an existing 40-year-old stand would be expected to 

exhibit in one-hundred years. The 40-year old stand might have received commercial thinning and other 

silvicultural practices that would result in different stand metrics when it eventually becomes 140 years 

old. Timber harvests before 1960 tended to be more extensive and intensive than later harvests, and 

subsequent regeneration commonly occurred through natural seeding. In contrast, timber harvests after 

1960 more likely left legacy trees and riparian buffers, and the subsequent regeneration more commonly 

was the result of planting, fertilization, and thinning. Thus, younger stands on BLM-administered lands 

commonly exhibit some structural characteristics, such as canopy cover, that are greater than those of 

some older stands. 

This analysis revealed that the BLM could not simply use Model 8 with the Woodstock-derived variable 

values. For example, as shown in Figure T-3, in the BLM 2013 Woodstock MaxEnt model, stand height 

was very influential. In the 2006 GNN data, stand height increased nearly linearly with stand age (Figure 

T-3, left matrix, STNDHT/AGE). In contrast, according to the 2013 Woodstock data, stand height 

increased rapidly with increasing age for young stands, but then the rate of increase decreased 

dramatically (Figure T-3, right matrix, STNDHT_13/AGE_13). The effect of these many differences was 

that, when the BLM used the Model 8 MaxEnt formulas (which were derived from 1996 GNN data) with 

the 2013 Woodstock variable values, relative habitat suitability decreased as stands got older, or, at least, 

their rate of increase was less than represented by the GNN data. Therefore, the BLM had to further 

modify the MaxEnt model to better reconcile how the 2013 Woodstock and 2006 GNN variables covaried. 

The BLM dealt with the appreciably different forms of relationships between the 2006 GNN and 2013 

Woodstock variables by removing some of those variables, as described below. At this point, the BLM 

questioned whether it could meet model assessment criteria 2 and 3, especially given that age was an 

influential variable in the models. Additionally, similar to previous models, the BLM evaluated whether it 

could find stronger relationships between its newly developed models and the model developed by USDI 

FWS (2011). 

Model 9 

Model 9 was identical to Model 8 except that the BLM reduced the variable set of each modeling region 

based on its evaluation of differences in 2006 GNN and 2013 Woodstock variable distributions observed 

in the scatterplots and histograms generated by Model 8. The BLM removed those variables that strongly 

influenced a model’s predictions and co-varied with other variables substantially differently within the 

2006 GNN and 2013 Woodstock data. For the Oregon and California Klamath Region the BLM removed 

canopy cover of all conifers (CCC in Figure T-3) and the number of large conifer trees per hectare 

(TPHC); for the Oregon and California Cascades Region the BLM removed stand height (STNDHT) and 

the number of large conifer trees per hectare; and for the Oregon Coast Range Region the BLM removed 

stand height. Removing these variables allowed other variables to become more influential in the models. 

The reduced sets of variables produced what the BLM interpreted as a more reasonable distribution of 

changes in relative habitat suitability by decade, given the habitat change under the No Timber Harvest 

reference analysis. 

Figure T-5 and Figure T-6 compare the results of Models 9 and 8; Model 9 demonstrated a moreexpected distribution of relative habitat suitability by decade. 
1750 | P a g e

Figure T-5. No Timber Harvest: distributions of relative habitat suitability by decade for Model 8 (top) 

and Model 9 (bottom) on the decision area 

Note: The histograms show the portion of BLM-administered lands in each relative habitat suitability bin at the beginning of each 

of six decades. 

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Model 8 - 2013–2063 No Timber Harvest, 10% Bins

2013 2023 2033 2043 2053 2063

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Model 9 - 2013–2063 No Timber Harvest, 10% Bins

2013 2023 2033 2043 2053 2063
1751 | P a g e

Figure T-6. No Timber Harvest: distribution of relative habitat suitability by decade for Model 8 (top) 

and Model 9 (bottom), on the decision area 

Note: The histograms show the portion of BLM-administered lands in each strength-of-selection bin at the beginning of each of 

six decades. 

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 9 

estimated relative habitat suitability for hexagons was 0.875, identical to that of Model 7. Nonetheless, 

the lack of the expected increase in the selected-for habitat class in Figure T-6 indicated the need for 

further refinement. The BLM still questioned whether it could meet model assessment criteria 2 and 3, 

given that age was an influential variable in the models. 

Model 10 

Model 10 was identical to Model 8 except that, for those modeling regions and for those variables that 

showed declines with age, the BLM created regression equations to predict each of those variables as a 

function of age. The regression equations that best fit the data always were logarithmic (threshold) 

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2013 2023 2033 2043 2053 2063
1752 | P a g e

relationships and had the effect of smoothing the associations. The BLM did this because these variables 

appeared in the original 2006 GNN MaxEnt models, but, for the 2013 Woodstock representation of BLMadministered lands, they sometimes showed counter-intuitive relationships—such as mean tree diameter 

and stand height declining as stands aged—only to sometimes increase at older ages. In part, these 

relationships probably were an artifact of limited data; relatively few BLM inventory plots exist in forest 

stands with very old trees. The BLM developed these regression equations within each of the three 

western Oregon modeling regions. The BLM also removed canopy cover of all conifers from the set of 

modeling covariates, because the distribution relative to age, even when regressed, was highly 

inconsistent with GNN canopy cover distributions. 

As shown in Figure T-7, when compared to Model 9, Model 10 generated a more-expected and logical 

trend in relative habitat suitability change over time. The correlation between the U.S. Fish and Wildlife 

Service 2006 GNN MaxEnt models and the Model 10 estimated relative habitat suitability for hexagons 

again was 0.875. However, the BLM subsequently determined that Model 10 was not viable due to issues 

with the stand age variable. 
1753 | P a g e

Figure T-7. No Timber Harvest: distributions of relative habitat suitability by decade for Model 9 (top) 

and Model 10 (bottom) on the decision area 

Note: The histograms show the portion of BLM-administered lands in each relative habitat suitability bin at the beginning of each 

of six decades. 

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Model 9 - 2013–2063 No Timber Harvest, 10% Bins

2013 2023 2033 2043 2053 2063

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Model 10 - 2013–2063 No Timber Harvest, 10% Bins

2013 2023 2033 2043 2053 2063
1754 | P a g e

Woodstock, when it forecasts the treatment of a stand, does not threat stand age consistently. Instead, 

when Woodstock forecasts a treatment, it retains the original stand age or resets the stand age to 0, 

depending on the nature of the treatment (e.g., light thinning versus regeneration harvest). Thus, over 

time, forest stands of the same age value could have substantially different values for other variables. 

Since the BLM was creating relative habitat suitability surfaces for different decadal time steps, it could 

not rely on stand age as a variable. For this reason, Model 10 was not viable. 

Model 11 

Model 11 was identical to Model 8 (using non-regressed covariates) except that the BLM removed age as 

a variable for the reason described under Model 10. Instead, the BLM added the Woodstock “structural 

condition” variable because structural condition is a GNN-defined categorical variable that also can be 

derived from Woodstock data. The GNN structural condition classes included: sparse, open, sapling/pole, 

small/medium tree, large tree, and large/giant tree. 

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 11 

estimated relative habitat suitability for hexagons was 0.876, almost identical to that of Model 9. 

Nonetheless, as shown in Figure T-8, regarding model assessment criterion 2, the modified set of 

variables resulted in relative habitat suitability progressions that the BLM interpreted as less logical than 

expected. 
1755 | P a g e

Figure T-8. No Timber Harvest: distributions of relative habitat suitability by decade for Model 8 (top) 

and Model 11 (bottom) on the decision area 

Note: The histograms show the portion of BLM-administered lands in each relative habitat suitability bin at the beginning of each 

of six decades. 

Model 12 

Model 12 was a combination of the refinements implemented in models 9 and 11. The BLM used the 

same reduced set of variables used in Model 9, and removed age (because of the age-related issues 

described under Model 10) and added structural condition as it had in Model 11. 

Figure T-9 and Figure T-10 compare the decadal relative habitat suitability progressions under Models 9 

and 12. Although Model 9 had generated the best previous distribution, it also included stand age as a 

variable, which Woodstock did not treat in a consistent manner. Model 12 was the best set of revised 

variables the BLM was able to develop. The Model 12 relative habitat suitability progressions were very 

similar to those for Model 9 in terms of showing the expected progression of relative habitat suitability by 

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2013 2023 2033 2043 2053 2063

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Model 11 - 2013–2063 No Timber Harvest, 10% Bins

2013 2023 2033 2043 2053 2063
1756 | P a g e

decade, but also showed slightly lower relative habitat suitability values overall (as seen in the higher 

suitability bins). 

Figure T-9. No Timber Harvest: distributions of relative habitat suitability by decade for Model 9 (top) 

and Model 12 (bottom) on the decision area 

Note: The histograms show the portion of BLM-administered lands in each relative habitat suitability bin at the beginning of each 

of six decades. 

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2013 2023 2033 2043 2053 2063

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Model 12 - 2013–2063 No Timber Harvest, 10% Bins

2013 2023 2033 2043 2053 2063
1757 | P a g e

Figure T-10. No Timber Harvest: distribution of relative habitat suitability by decade for Model 9 (top) 

and Model 12 (bottom) on the decision area 

Note: The histograms show the portion of BLM-administered lands in each strength-of-selection bin at the beginning of each of 

six decades. 

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 12 

estimated relative habitat suitability for hexagons was 0.874. Based on this correlation coefficient and the 

progressions shown in Figure T-9 and Figure T-10, the BLM determined that Model 12 fulfilled its three 

model assessment criteria. 

Model 13 

Model 13 became the final BLM model. It was identical to Model 12, except that the BLM used floating 

point values, rather than integer values, to conform GNN covariate values to Woodstock output precision 

(i.e., to better reconcile the data going into the 2006 GNN and 2013 Woodstock models). Floating point 

values include decimals; integers are whole numbers. 

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2013 2023 2033 2043 2053 2063

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2013 2023 2033 2043 2053 2063
1758 | P a g e

The correlation between the U.S. Fish and Wildlife Service 2006 GNN MaxEnt models and the Model 13 

estimated relative habitat suitability for hexagons was 0.867. For the three western Oregon modeling 

regions, this set of models included eleven variables for each of the modeling regions. Table T-1 shows 

the variables and their relative contributions. As described below, the BLM determined that Model 13 

fulfilled its three model assessment criteria. The BLM’s earlier attempts to fine-tune models so as to 

increase the correlation between its newly-developed models and those of the USDI FWS (2011) were 

reasonable but, by this point, the BLM recognized that hexagon correlations of 0.860 to 0.870 were as 

strong as it likely would get, given inherent differences in the sources of the 2006 GNN and 2013 

Woodstock variables.52

Table T-1. Model 13 variables and percent contributions by modeling region 

Covariate Covariate Description KLAMT ORCAS ORCOA

ccc Canopy cover of all conifers 0.45 1.0213

curv Topographic curvature 5.0242 3.122 2.3622

dbhc Basal-area weighted mean diameter of all live conifers 1.0851 11.3159 0.2664

ddi Diameter diversity index 5.5428 40.1345 12.9418

elev Elevation 1.1043 4.1592 2.6962

evghwd Evergreen hardwood composition type 2.4068 4.1657 7.8237

oak Oak composition type 6.6165 0.8094

pine Pine composition type 2.0507 13.552 6.4613

rpi Relative position index (% slope position in 200 ha 

window) 29.631 12.8439 9.5835

stndht Stand height, computed as average of heights of all 

dominant and co-dominant trees 44.6563

struccond Structural condition (lumping of Johnson and O’Neil’s 

(2001) SIZECL and COVCL 0.3544 4.4098 0.2031

subalp Sub-alpine composition type 1.528 5.0377 1.6429

tphc Density of all live conifers ≥ 75 cm DBH 54.9975

Note: Missing values indicate that the BLM did not use the variable for the modeling region. The modeling regions are the 

Oregon and California Klamath (KLAMT), the Oregon and California Cascades (ORCAS), and Oregon Coast Range (ORCOA), 

described by Davis et al. (2011). 

Before accepting Model 13, the BLM compared the Model 13 distribution of hexagons among relative 

habitat suitability bins with that of the U.S. Fish and Wildlife Service (USDI FWS 2011) 2006 GNN 

MaxEnt model for: (1) the decision area within the three western Oregon modeling regions and (2) all 

lands within those regions. To do this, the BLM “updated” the U.S. Fish and Wildlife Service relative 

habitat suitability surfaces by projecting the U.S. Fish and Wildlife Service’s MaxEnt models, which the 

U.S. Fish and Wildlife Service had trained on 1996 GNN data (see footnote on p. 1), to newly-available 

2012 GNN data (http://lemma.forestry.oregonstate.edu/data/structure-maps). (For brevity, these new 

models hereafter are referred to as the U.S. Fish and Wildlife Service 2012 GNN MaxEnt models, even 

though the BLM created them.) The BLM did this to reduce the temporal differences between the 2006 

GNN and the 2013 Woodstock datasets. 

 

52 GNN variables are derived from vegetation measurements from regional networks of field plots and Landsat 

imagery data to characterize forest vegetation across a region; see Ohmann and Gregory (2002). Woodstock 

variables are derived from BLM Forest Operations Inventory (forest stand exam) data and U.S. Forest Service/BLM 

Current Vegetation Survey 

(https://www.fbo.gov/index?s=opportunity&mode=form&id=bed33e38414e6986bc3dbada90bde22a&tab=core&_c

view=1) data. 
1759 | P a g e

The BLM evaluated relative habitat suitability distributions among eight relative habitat suitability bins 

(the largest bin being greater than 70, because so little of the landscape existed above that value). Thus, 

for the three modeling regions and eight bins, there were 24 modeling region by bin comparisons for the 

two sets of models. As shown in Figure T-11, the largest absolute value of difference was 5 percentage 

points and the smallest difference was 0 percentage points. Of the 24 comparisons, the most frequent 

difference was an absolute value of 1 percentage point (nine times), followed by 5 percentage points and 

4 percentage points (four times each), 2 percentage points and 0 percentage points (three times each), and 

3 percentage points (one time). Thus, the two sets of models predicted similar amounts of the landscape 

(all lands within each modeling region or only BLM-administered lands within each modeling region) 

within each of the relative habitat suitability bins. 
1760 | P a g e

Figure T-11. Comparisons of the distribution of relative habitat suitability at the hexagon scale, on BLMadministered lands (left column), and all lands (right column), in the Oregon and California Klamath, 

Oregon Coast Range and the Oregon and California Cascades modeling regions (described by Davis et al. 

2011) 

Note: The U.S. Fish and Wildlife Service relative habitat suitability surfaces are based on the U.S. Fish and Wildlife Service 

2012 GNN MaxEnt model. The BLM surfaces are based on the BLM 2013 Woodstock Model 13. 

0

0.05

0.1

0.15

0.2

0.25

0–10 10–20 20–30 30–40 40–50 50–60 60–70 >70

Proportion of Hexagons

Relative Habitat Suitability Bins

KLAMT RHS Distribution on BLM Lands

USFWS BLM Model 13

0

0.1

0.2

0.3

0.4

0.5

0.6

0–10 10–20 20–30 30–40 40–50 50–60 60–70 >70

Proportion of Hexagons

Relative Habitat Suitability Bins

KLAMT Region RHS Distribution on All Lands

USFWS BLM Model 13

0

0.05

0.1

0.15

0.2

0.25

0–10 10–20 20–30 30–40 40–50 50–60 60–70 >70

Proportion of Hexagons

Relative Habitat Suitability Bins

ORCOA RHS Distribution on BLM Lands

USFWS BLM Model 13

0

0.1

0.2

0.3

0.4

0.5

0.6

0–10 10–20 20–30 30–40 40–50 50–60 60–70 >70

Proportion of Hexagons

Relative Habitat Suitability Bins

ORCOA Region RHS Distribution on All Lands 

USFWS BLM Model 13

0

0.05

0.1

0.15

0.2

0.25

0–10 10–20 20–30 30–40 40–50 50–60 60–70 >70

Proportion of Hexagons

Relative Habitat Suitability Bins

ORCAS RHS Distribution on BLM Lands

USFWS BLM Model 13

0

0.1

0.2

0.3

0.4

0.5

0.6

0–10 10–20 20–30 30–40 40–50 50–60 60–70 >70

Proportion of Hexagons

Relative Habitat Suitability Bins

ORCAS Region RHS Distribution on All Lands

USFWS BLM Model 13
1761 | P a g e

As shown in Figure T-12, the BLM also found, when mapped, a strong similarity in the spatial 

distribution of relative habitat suitability values between the two sets of models. Most differences were 

minor rather than one model predicting very high suitability for an area while the other model predicted 

very low suitability for that area. 

Figure T-12. Spatial distribution of relative habitat suitability for the U.S. Fish and Wildlife Service 2012 

GNN MaxEnt model (left) and the BLM 2013 Woodstock Model 13 (right) 

Note: Greener areas represent higher relative habitat suitability whereas redder colors represent lower relative habitat suitability. 

Also, before accepting Model 13, the BLM examined the distribution of the northern spotted owl known 

sites used to train Model 13 (training sites) with those known sites withheld from model development 

(test sites) as described in the description of Model 3. There were 2,465 training sites in the northern 

spotted owl range (of which 490 occurred on the decision area) and 925 test sites in the northern spotted 

owl range (of which 164 occurred on BLM-administered lands). 

Figure T-13 compares the range-wide distributions of training sites among relative habitat suitability bins 

for the U.S. Fish and Wildlife Service 1996 GNN MaxEnt models and the BLM 1996 GNN Model 13,53

The distributions are similar. Figure T-14 makes the same comparison of the test sites. The distributions 

 

53 As explained in the footnote on page 1, the U.S. Fish and Wildlife Service used 1996 GNN data to train its 

MaxEnt models. The BLM developed Model 13 using the same data for the comparison. 
1762 | P a g e

are not as similar as for the training sites, which are expected because the models were trained on the 

training sites. Nonetheless, the two distributions in Figure T-14 follow similar trends. 
1763 | P a g e

Figure T-13. Rangewide distribution of relative habitat suitability values among training northern spotted 

owl sites for the U.S. Fish and Wildlife Service 1996 GNN MaxEnt model and BLM’s 1996 GNN Model 

13 

Figure T-14. Rangewide distribution of relative habitat suitability values among test northern spotted owl 

sites for the U.S. Fish and Wildlife Service 1996 GNN MaxEnt model and BLM’s 1996 GNN Model 13

0.01

0.04

0.07

0.11

0.15

0.22 0.23

0.13

0.04

0.00

0.01

0.04

0.07

0.11

0.17

0.25

0.26

0.08

0.01

0

0

0.05

0.1

0.15

0.2

0.25

0.3

0–10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 80–90 90–100

Proportion of Nesting/Roosting Sites

Relative Habitat Suitability Bin

USFWS BLM

0.02

0.03

0.07

0.11

0.19

0.21

0.23

0.12

0.03

0.00

0.01

0.04

0.05

0.09

0.17

0.25

0.27

0.12

0.01 0

0

0.05

0.1

0.15

0.2

0.25

0.3

0–10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 80–90 90–100

Proportion of Nesting/Roosting Sites

Relative Habitat Suitability Bin

USFWS test BLM test
1764 | P a g e

The BLM made similar comparisons for the decision area, this time using the U.S. Fish and Wildlife 

Service 2012 GNN MaxEnt models and the BLM 2013 Woodstock Model 13. Figure T-15 shows the 

distributions for training sites on the decision area; Figure T-16 shows the distributions for test sites on 

the same lands. As expected, the distributions are less similar than the range-wide distributions shown in 

Figure T-13 and Figure T-14 because of the smaller numbers of sites associated with the decision area 

and because of substantive differences in the origins of the 2012 GNN and 2013 Woodstock data. 

Because the Woodstock variables were derived from forest stand exam and Current Vegetation Survey 

plot data (i.e., on-the-ground examination and measurement), the BLM is confident of the accuracy of the 

Woodstock variables for the decision area. Nonetheless, Figure T-13 to Figure T-16 suggest that Model 

13, as used by the BLM, inflates relative habitat suitability values. As explained below, this almost 

certainly is an artifact of truncating Model 13 to BLM-administered lands. 
1765 | P a g e

Figure T-15. Distribution of relative habitat suitability values among training northern spotted owl sites 

on the decision area for the U.S. Fish and Wildlife Service 2012 GNN MaxEnt model and BLM’s 2013 

Woodstock Model 13 

Figure T-16. Distribution of relative habitat suitability values among test northern spotted owl sites on 

the decision area for the U.S. Fish and Wildlife Service 2012 GNN MaxEnt model and BLM’s 2013 

Woodstock Model 13 

0.02

0.04

0.10

0.12

0.19

0.23

0.18

0.11

0.02

0.00

0.01

0.02

0.05

0.08

0.17

0.24 0.24

0.17

0.02

0.00

0

0.05

0.1

0.15

0.2

0.25

0.3

0–10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 80–90 90–100

Proportion of Nesting/Roosting Sites

Relative Habitat Suitability Bin

USFWS BLM

0.01

0.05

0.07

0.14

0.21

0.17

0.20

0.12

0.02

0.01 0.01 0.01

0.02

0.11

0.12

0.17

0.26

0.24

0.05

0.00

0

0.05

0.1

0.15

0.2

0.25

0.3

0–10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 80–90 90–100

Proportion of Nesting/Roosting Sites

Relative Habitat Suitability Bin

USFWS test BLM test
1766 | P a g e

As described above, MaxEnt calculates relative habitat suitability based on variable values within a 200-

ha circle. GNN data, used in the U.S. Fish and Wildlife Service MaxEnt models, were available for all 

lands within the northern spotted owl range. However, the BLM developed Woodstock data only for the 

decision area. The BLM uses Woodstock data, because it is the most accurate data for BLM-administered 

lands. However, an artifact arises when the BLM applies Model 13 to BLM-administered lands that abut 

other lands (i.e., lands within 800 m of BLM-administered lands, which is the radius of a 200-ha circle). 

In this case, the BLM could use Model 13 to calculate relative habitat suitability values for 2013 based on 

2013 Woodstock data for BLM-administered lands and 2012 GNN data for other lands. However, the 

BLM cannot do this for subsequent decades, because there are no reliable data on how individual GNN 

values vary and co-vary over time. As described below, the BLM simulated changes in relative habitat 

suitability values on other lands by developing a 2012 relative habitat suitability surface for each 

modeling region, and then changing relative habitat suitability values according to the calculated effects 

of ingrowth, wildfire, and timber harvest on those values at decadal increments. However, the BLM could 

not do the same for the underlying GNN variable values used to calculate relative habitat suitability. 

Stated another way, Woodstock generates new variable values for BLM-administered lands at decadal 

increments. However, after 2012, there are no comparable GNN values available for other lands abutting 

BLM-administered lands. Thus, after 2013, Model 13 must calculate relative habitat suitability values for 

BLM-administered lands using only Woodstock data. Since forest conditions on BLM-administered lands 

commonly support northern spotted owls better than those on adjacent lands, which frequently are 

industrial timber lands, the BLM method appears to inflate relative habitat suitability values on its own 

administered lands. This is not a weakness of Model 13. Instead, it is an artifact of data limitations for 

other lands within 800 m of the decision area. After publishing the Draft RMP/EIS, the BLM further 

refined its relative habitat suitability forecasts (see Sections A and D of this appendix). 

B. Forecasting Change in Relative Habitat Suitability on 

Other Lands in Washington, Oregon and California for the 

Draft RMP/EIS 

The BLM forecasted changes in relative habitat suitability from ingrowth, large (1,000+-acre) wildfires, 

and timber harvests for all lands within the U.S. portion of the northern spotted owl range. Modifications 

in forest structure and composition at decadal increments on the decision area were incorporated in the 

Woodstock models and reflected in the BLM’s Model 13 relative habitat suitability surfaces. The BLM 

based its forecasted magnitudes of change on all other lands on differences between the U.S. Fish and 

Wildlife Service 1996 and U.S. Fish and Wildlife Service 2006 GNN-based relative habitat suitability 

surfaces. That is, BLM assumed that the decadal change in relative habitat suitability from 1996 to 2006 

would be realized during subsequent decades. 

To estimate rates-of-change from forest ingrowth in decadal increments, the BLM calculated the mean 

difference between 1996 and 2006 for each integer relative habitat suitability value (i.e., the analysis 

determined the mean value in 2006 for all pixels with the same value in 1996). The BLM generated ratesof-change statistics separately for each physiographic province and, within each province, further 

stratified by Congressionally Reserved lands (e.g., designated Wilderness Areas), Federal reserved lands 

(e.g., the Late-Successional Reserve under the Northwest Forest Plan), Federal non-reserved lands (e.g., 

Matrix lands under the Northwest Forest Plan), and non-Federal lands. The BLM excluded pixels from 

the analysis within Monitoring Trends in Burn Severity (http://www.mtbs.gov/) fire perimeters and 

unpublished U.S. Forest Service LandTrendr harvest patches (see Davis et al. 2011) to minimize the 

influence of other agents of change on the ingrowth rates. 

Initially, the BLM included only pixels showing positive or no change between 1996 and 2006 in the 

calculations. The BLM did this because negative change does not reflect forest ingrowth. The BLM used 
1767 | P a g e

those derived rates-of-change to generate projected decadal relative habitat suitability surfaces for other 

lands, combined with the decadal Woodstock projections for BLM-administered lands. However, after 

examining the results, the BLM determined that the rate of ingrowth for forests in the drier portion of the 

northern spotted owl’s range (i.e., most of California, and the eastern Cascades of Washington and 

Oregon) appeared to exceed observed rates. After additional consideration and testing, the BLM truncated 

all negative changes to 0 and all positive changes to 10 because negative changes in relative habitat 

suitability were not indicative of ingrowth and, knowing how habitat develops, rates higher than 10 were 

unrealistic. Although relatively few values exceeded 10, they were sufficiently high to affect mean ratesof-change. The final results were sets of range-wide ingrowth forecasts for strata within each 

physiographic province.54

The BLM used results from Davis et al. (2014) to forecast changes in relative habitat suitability values 

following wildfires. The BLM applied changes only for moderate and high severity fires by habitat class, 

because Davis et al. (2014) determined that low severity fires have a negligible effect on northern spotted 

owl habitat. These findings are supported by Manley’s (2014) descriptions of the effects of fire on 

northern spotted owls. The BLM modeled the spatial locations, extents, and severity of future wildfires 

using the same predicted wildfire dataset included in the Woodstock models, which extends over the nonBLM portions of the northern spotted owl’s range (Appendix D – Modeling Large Stochastic Wildfires 

and Fire Severity Within the Range of the Northern Spotted Owl).

Expanding on the methods described by Davis et al. (2011, pp. 28–30), the BLM used the unpublished 

U.S. Forest Service LandTrendr change detection data to develop range-wide forecasts of decadal rates of 

negative change in relative habitat suitability values following timber harvests. To create potential timber 

harvest patches on other lands, the BLM segmented the U.S. Forest Service 2006 GNN-based relative 

habitat suitability model using eCognition Developer 8 (Trimble Navigation Ltd., Westminster, CO). The 

BLM parameterized the software’s segmentation routine to iteratively group neighboring pixels with 

similar relative habitat suitability values into discrete patches until the mean patch size ± 1 SD within 

each physiographic province and strata most closely approximated those observed in the LandTrendr 

dataset between 1996 and 2006 (Table T-2 and Table T-3). Segmenting the U.S. Forest Service 2006 

GNN-based surface resulted in more realistic representations of harvest treatment patch shapes and 

dimensions than those created using the smoother, 200-ha-scale U.S. Fish and Wildlife Service relative 

habitat suitability surfaces. 

 

54 The BLM subsequently tested methods to refine its forecasts; see Section D of this appendix. Because the U.S. 

Forest Service LandTrendr analysis was based on a 200-ha scale relative habitat suitability surface—i.e., relative 

habitat suitability values are based on the means of variable values within 800 meters of each pixel, the radius of a 

200-ha circle—any negative change in burn and timber harvest areas would affect the relative habitat suitability 

values within 800 m, and not just within the treatment or burn area. The BLM tested masking areas within 800 

meters of burn and treatment areas, and recalculating relative habitat suitability change, and found that this 

eliminated much of the negative change the BLM had detected outside burn and harvest areas. However, the degree 

of change did not cause the BLM to replace its analyses for the Draft RMP/EIS. As described in Section D of this 

appendix, the BLM subsequently tested additional methods to refine its relative habitat suitability surfaces during its 

preparation of the Proposed RMP/Final EIS. 
1768 | P a g e

Table T-2. Metrics, calculated from data developed by Davis et al. (2011), used to forecast decadal (1996–2006) losses of northern spotted owl 

dispersal and nesting-roosting habitat from timber harvest on lands other than BLM-administered lands in the planning area 

Physiographic 

Province

Dispersal 

Habitat in 

1996 

(Acres)

Dispersal 

Habitat 

Harvested 

(Acres)

Dispersal 

Habitat 

Harvested 

(Percent)

NestingRoosting 

Habitat in 

1996 

(Acres)

NestingRoosting 

Habitat 

Harvested 

(Acres)

NestingRoosting 

Habitat 

Harvested 

(Percent)

Habitat 

Harvested 

that was 

NestingRoosting 

(Percent)

10-Year 

Mean 

Loss of 

Habitat to 

Harvest

Mean 

Harvest 

Patch Size 

(Acres)

Stand 

Harvest 

Patch Size 

(Acres)

Federal Non-Reserved Lands†

Washington

Eastern Cascades 128,810 1,208 1% 207,310 1,819 1% 60% 1.0% 20 10

Olympic Peninsula 39,038 128 - 37,275 47 - 27% 0.2% 19 9

Western Cascades 143,116 404 - 288,691 1,025 - 72% 0.3% 19 8

Western Lowlands 11 - - - - - - - - -

Oregon

Coast Range 34,732 265 1% 34,722 135 - 34% 0.6% 21 11

Eastern Cascades 109,494 1,725 2% 145,704 1,756 1% 50% 1.4% 23 13

Klamath 111,577 628 1% 135,992 737 1% 54% 0.6% 18 7

Western Cascades 478,515 3,972 1% 844,548 6,669 1% 63% 0.9% 19 9

Willamette Valley 4 - - - - - - - - -

California

Cascades 110,507 1,386 1% 63,151 1,858 3% 57% 2.1% 33 23

Coast Range 25,543 12 - 11,191 - - 0% - 12 -

Klamath 576,849 2,482 - 657,433 1,845 - 43% 0.4% 17 7

Federal Reserved Lands*

Washington

Eastern Cascades 139,270 606 - 268,674 1,618 1% 73% 0.8% 17 8

Olympic Peninsula 89,086 73 - 277,151 308 - 81% 0.1% 16 5

Western Cascades 182,939 234 - 486,969 443 - 65% 0.1% 18 7

Oregon

Coast Range 118,696 598 1% 266,301 1,103 - 65% 0.5% 20 9

Eastern Cascades 73,898 397 1% 159,868 347 - 47% 0.4% 19 8

Klamath 218,679 103 - 210,418 232 - 69% 0.1% 20 10

Western Cascades 264,104 328 - 740,398 487 - 60% 0.1% 18 7

California

Cascades 67,741 267 - 85,839 239 - 47% 0.3% 22 15

Coast Range 30,071 31 - 25,486 22 - 42% 0.1% 13 3

Klamath 335,682 536 - 579,128 526 - 50% 0.1% 16 5
1769 | P a g e

Physiographic 

Province

Dispersal 

Habitat in 

1996 

(Acres)

Dispersal 

Habitat 

Harvested 

(Acres)

Dispersal 

Habitat 

Harvested 

(Percent)

NestingRoosting 

Habitat in 

1996 

(Acres)

NestingRoosting 

Habitat 

Harvested 

(Acres)

NestingRoosting 

Habitat 

Harvested 

(Percent)

Habitat 

Harvested 

that was 

NestingRoosting 

(Percent)

10-Year 

Mean 

Loss of 

Habitat to 

Harvest

Mean 

Harvest 

Patch Size 

(Acres)

Stand 

Harvest 

Patch Size 

(Acres)

Non-Federal Lands

Washington

Eastern Cascades 319,729 18,536 6% 362,291 24,540 7% 57% 6.3% 30 20

Olympic Peninsula 275,885 33,068 12% 192,741 23,153 12% 41% 12.0% 41 27

Western Cascades 212,118 23,573 11% 120,707 11,207 9% 32% 10.2% 39 27

Western Lowlands 524,668 73,413 14% 149,848 19,729 13% 21% 13.6% 40 27

Oregon

Coast Range 659,641 104,393 16% 483,985 106,584 22% 51% 18.9% 44 30

Eastern Cascades 132,149 15,728 12% 114,531 11,061 10% 41% 10.8% 37 25

Klamath 300,416 26,920 9% 244,411 23,492 10% 47% 9.3% 33 22

Western Cascades 411,318 63,999 16% 260,687 45,250 17% 41% 16.5% 46 33

Willamette Valley 50,477 3,220 6% 37,962 3,553 9% 52% 7.9% 22 12

California

Cascades 184,094 9,049 5% 109,434 6,310 6% 41% 5.3% 20 9

Coast Range 1,189,363 41,598 3% 967,484 36,891 4% 47% 3.7% 20 9

Klamath 382,099 10,094 3% 353,724 10,157 3% 50% 2.8% 19 8

Non-Federal Land Totals by State‡

Washington 1,332,399 148,590 11% 825,587 78,629 10% 35% 10.3% 38 26

Oregon 1,554,001 214,260 14% 1,141,576 189,940 17% 47% 15.2% 42 30

California 1,755,556 60,741 3% 1,430,642 53,358 4% 47% 3.6% 20 9

* Congressionally Reserved and the decision area not included 

† The decision area not included 

‡ Mean harvest patch sizes on non-Federal lands by state are NOT averages of the above physiographic province averages
1770 | P a g e

Table T-3. Changes, calculated from data developed by Davis et al. (2011), in relative habitat suitability 

values from timber harvests occurring in northern spotted owl habitat between 1996 and 2006 by 

physiographic province and Northwest Forest Plan land use allocation 

Physiographic 

Province

Federal Reserved Lands*

Federal Non-Reserved 

Lands†

Non-Federal Lands

Selected 

Against

Selected 

For

Strongly 

Selected 

For

Selected 

Against

Selected 

For

Strongly 

Selected 

For

Selected 

Against

Selected 

For

Strongly 

Selected 

For

Washington

Eastern Cascades -2 -2 - -2 -4 -2 -3 -6 -10

Olympic Peninsula 4 3 - 5 -8 4 -7 -12 -13

Western Cascades 4 2 4 3 -1 -1 -9 -15 -19

Western Lowlands - - - - - - -7 -12 -16

Oregon

Coast Range 2 -2 - -3 1 1 -5 -10 -13

Eastern Cascades 1 1 -4 - -1 -2 -3 -7 -16

Klamath -1 1 -10 - -1 - -3 -5 -4

Western Cascades - -2 -5 1 - -1 -7 -9 -6

Willamette Valley - - - - - - -6 -7 -27

California

Cascades 4 -6 -4 -5 -13 -13 -3 -7 -13

Coast Range -2 -3 - -2 - - 1 1 -1

Klamath 0 1 -1 -1 - 1 -1 -1 -3

* Congressionally Reserved and the decision area not included

† The decision area not included 

Starting with the 2012 relative habitat suitability surface (i.e., the surface the BLM created using 2012 

GNN data with the U.S. Fish and Wildlife Service 1996 GNN MaxEnt models), the BLM forecasted 

changes on other lands from ingrowth, wildfire, and timber treatments before advancing in decadal 

increments for five decades (2013–2063). Modeling each decade in sequence was necessary because 

estimating change in future decadal intervals depended on adjusted values from the previous decade. 

At the beginning of each decade, the BLM applied the rates-of-change in relative habitat suitability value 

from ingrowth and categorized the results into the four habitat suitability classes using the previously 

derived strength-of-selection class breaks: strongly-selected-against, selected-against, selected-for, and 

strongly-selected-for. Next, the BLM adjusted pixel values within the wildfire perimeters predicted to 

occur within the decade depending on the fire severity and corresponding relative habitat suitability class. 

The BLM categorized the resulting continuous surface into habitat classes a second time before adding 

the effects of timber harvests. Finally, the BLM calculated the median habitat class within each candidate 

harvest treatment patch (i.e., the results of the image segmentations described above), and randomly 

selected treatment patches in each province and strata until the area harvested approached, but did not 

exceed, the total decadal treatment area calculated from the LandTrendr data. The BLM then repeated the 

process for the next and subsequent decades. 

The BLM applied the following four selection criteria when selecting timber harvest patches for the 

purpose of forecasting change in relative habitat suitability on lands other than BLM-administered lands: 

 All modeled harvest patches had to exceed 10 acres in size because the BLM anticipated smaller 

timber harvests would be commercially inviable. 

 The BLM did not allow the selection of patches that were more than 500 m from a road because 

of anticipated limitations to commercial access. 
1771 | P a g e

 Patches classified as ‘strongly-selected-against’ were not considered because such stands 

generally would be too young for commercial timber harvest. 

 The BLM did not allow a patch to be selected for treatment twice during the 50-year forecast 

period. Once selected, the rates of change from harvest were applied to the relative habitat 

suitability values within each patch. After harvesting a patch, the BLM allowed ingrowth within 

modeled harvests to progress uninterrupted for the remainder of the planning horizon. 

The BLM applied changes in relative habitat suitability to all lands before updating the pixel values on 

the decision area with the results from Model 13 for the same decade. 

The BLM created only one set of decadal relative habitat suitability surfaces for non-BLM-administered 

lands across the northern spotted owl’s range. The BLM used this single set of surfaces for all evaluations 

of the alternatives, the Proposed RMP, and the No Timber Harvest reference analysis (i.e., only the 

relative habitat surfaces for the decision area changed by alternative or the Proposed RMP). The BLM 

used this final set of relative habitat suitability surfaces, one for each decade between 2013 and 2063, for 

the HexSim population dynamics models. 

C. Additional Notes on the BLM’s Northern Spotted Owl 

Modeling and Analyses for the Draft RMP/EIS 

Sections A and B appeared in Appendix S of the Draft RMP/EIS (USDI BLM 2015). However, the BLM 

did not intend those narratives to be sufficient to allow someone to duplicate BLM processes, only to help 

reviewers better understand the BLM’s analytical processes so they could better interpret results. The 

BLM recorded the steps of its processes in its administrative record. 

The BLM requested review of Appendix S of the Draft RMP/EIS by Drs. Bruce Marcot and Peter 

Singleton of the U.S. Forest Service—experts on northern spotted owl biology and modeling. The 

following section provides additional explanation of the BLM processes through responses to the 

comments of Drs. Bruce Marcot and Peter Singleton. 

Relative Habitat Suitability Surfaces 

Comment: As it explained in its development of models 1–13, the BLM worked to achieve a strong 

correlation between its relative habitat suitability surfaces and those prepared by the FWS on the 

apparent assumption that the FWS’s surfaces were a near-perfect representation of northern spotted owl 

habitat. However, the BLM’s process likely compounded the error inherent in FWS’s surfaces with the 

error inherent in the BLM’s process.

BLM response: The BLM did not assume that the U.S. Fish and Wildlife Service’s relative habitat 

suitability surfaces represented a near-perfect representation of northern spotted owl habitat. Instead, the 

BLM reviewed the U.S. Fish and Wildlife Service’s data and methods for surface development and 

determined that those surfaces (actually, the MaxEnt models developed by the U.S. Fish and Wildlife 

Service to create its surfaces, which the BLM then applied to 2012 GNN data to generate updated 

surfaces) most likely were the most credible range-wide northern spotted owl surfaces available. Second, 

as described above in this appendix, the BLM derived its MaxEnt models independently of the U.S. Fish 

and Wildlife Service’s MaxEnt models, and then examined the degree of fit between the relative habitat 

suitability surfaces derived from the two sets of models to help ensure that HexSim would work with the 

merged surfaces. As described under Model 8, the BLM determined that it could not use stand age as a 

variable in its MaxEnt models because Woodstock calculates stand age differently over time based on 

simulated stand treatment. Since stand age typically is an important variable in the modeling of northern 

spotted owl habitat, the BLM compared the results of its MaxEnt models against those of the most-similar 
1772 | P a g e

and credible models available for the same land base. Although the relative habitat suitability surfaces 

developed by the U.S. Fish and Wildlife Service contain inherent uncertainty, the BLM used a rational 

process to refine and test its models. However, it did not tailor its models to generate surfaces similar to 

the U.S. Fish and Wildlife Service’s surface.

That said, at the time the BLM prepared its northern spotted owl relative habitat suitability surfaces, only 

two comparable range-wide surfaces existed: one produced by the U.S. Fish and Wildlife Service (USDI 

FWS 2011, pp. Appendix C) and one by the U.S. Forest Service (Davis et al. 2011). Since preparation of 

the Draft RMP/EIS, the U.S. Forest Service updated its surfaces using 2012 GNN data (Davis et al. 

2015). Table T-4 compares the acres of northern spotted owl nesting-roosting habitat on federal lands as 

calculated by the U.S. Forest Service using 2012 GNN data (Davis et al. 2015, Table 6) and by the BLM 

using 2013 Woodstock data for the decision area and 2012 GNN data (U.S. Fish and Wildlife Service 

1996 GNN MaxEnt models applied to 2012 GNN data) for other Federal lands. Even though these acres 

were calculated using different datasets, MaxEnt models and analytical scales, the estimates are similar. 

Table T-4. A comparison of the estimated acres of northern spotted owl nesting-roosting habitat on 

Federal lands as calculated by the U.S. Forest Service and the BLM 

Physiographic Province

U.S. Forest Service

(Acres)

BLM

(Acres)

Washington

Olympic Peninsula 737,600 972,223

Western Lowlands 12,900 6,278

Western Cascades 1,169,500 1,238,477

Eastern Cascades 779,400 753,264

Washington Totals 2,699,400 2,970,242

Oregon

Coast Range 506,200 867,550

Willamette Valley 7,500 8,194

Western Cascades 2,371,400 2,112,585

Klamath 932,100 828,637

Eastern Cascades 339,600 508,885

Oregon Totals 4,156,800 4,325,851

California

Coast Range 123,800 103,130

Klamath 1,764,700 1,606,645

Cascades 209,300 142,265

California Totals 2,097,800 1,852,040

Comment: Developing relative habitat suitability surfaces that combine GNN and BLM Woodstock data 

compounds the uncertainty inherent in both datasets, making the surfaces, and the BLM analyses that use 

those surfaces, less reliable.

BLM response: The GNN/CVS data are the most reliable range-wide data available for other (non-BLMadministered) lands in the northern spotted owl’s range. As described in this appendix, the BLM used the 

GNN-derived relative habitat suitability surfaces developed by the U.S. Fish and Wildlife Service (USDI 

FWS 2011, pp. C-16 – C-43) for all lands within the northern spotted owl range except BLM-
1773 | P a g e

administered lands in the planning area. (Again, the BLM used the U.S. Fish and Wildlife Service 1996 

GNN MaxEnt models but applied them to 2012 GNN data, so the BLM did not actually use the U.S. Fish 

and Wildlife Service’s relative habitat suitability surfaces, only its MaxEnt models.)

The Woodstock (BLM data) variable values, which are derived from BLM field operations inventory and 

CVS plot data, are the most reliable data available for the decision area. Since the BLM used GNN- or 

Woodstock-derived relative habitat suitability surfaces appropriate to land base, and ensured, at multiple 

steps, that those surfaces were compatible, the uncertainty inherent in the GNN data does not compound 

the uncertainty inherent in the Woodstock data. Even though there is uncertainty inherent in the merged 

surfaces, because the surfaces are based on the best data available for each land base, the merged surfaces 

likely are more reliable than those derived from only GNN data. 

Because biases or uncertainties in the underlying GNN/Woodstock layers and subsequent relative habitat 

suitability surfaces are used for comparing all alternatives and the Proposed RMP, and because BLM 

interprets the HexSim model results as relative among alternatives and the Proposed RMP, any over- or 

under-estimation of northern spotted owl habitat changes or population responses that may exist would 

exist for all alternatives and the Proposed RMP and would not influence the relative difference(s) among 

alternatives and the Proposed RMP. The BLM acknowledges that the uncertainty inherent in its relative 

habitat suitability surfaces compounds the uncertainty inherent in modeling that relies on those surfaces. 

However, that compounding effect is inherent in all modeling. 

Comment: MaxEnt, which the BLM used to create relative habitat suitability surfaces for its administered 

lands, is prone to over-fitting the data, especially when too many variables are used. 

BLM response: The BLM did not employ the full range of fitting features available in MaxEnt. The BLM 

MaxEnt models relied on 11 covariates specific to each of the western Oregon modeling regions (Table 

T-1). In addition, as described under Model 13, the BLM tested its MaxEnt models with data that had not 

been used to train the models to help ensure that the models did not over-fit the data. 

Comment: How did the BLM use strength-of-selection thresholds to classify northern spotted owl habitat? 

BLM response: Based on its modeling needs (see Chapter 3, Northern Spotted Owl), the BLM divided 

northern spotted owl habitat into categories based on strength-of-selection. This was similar to the process 

used by the U.S. Fish and Wildlife Service (USDI FWS 2011, pp. C-31 – C-39) but, in the BLM’s case, 

the BLM used four categories: (1) strongly selected against, (2) selected against, (3) selected for, and (4) 

strongly selected for. 

To summarize strength-of-selection: If the relative habitat suitability values greater than 45 represent 10 

percent of a modeling region, and 50 percent of the northern spotted owl nests in that region are in areas 

with relative habitat suitability greater than 45, the strength-of-selection value would be 5.0 (50 percent of 

the nests divided by 10 percent of the area, which means that the area was used for nesting five times 

more than would be expected based on its availability). Similarly, if 50 percent of the landscape is in 

areas with relative habitat suitability less than 15, and 10 percent of the nests in that region are in areas 

with relative habitat suitability less than 15, the strength-of-selection would be -5.0 (10 percent of the nest 

sites divided by 50 percent of the area—and multiplied by -1—because the percent of nest sites is less 

than the percent of the area), which means the area was used five times less than would be expected based 

on its availability). 

The BLM created strength-of-selection curves separately for each modeling region. These strength-ofselection-defined categories provided a relatively simple and consistent way to track changes in the 

amount of area containing habitats of differing value to northern spotted owls; with value being defined 
1774 | P a g e

by the owls’ relative attraction or avoidance. The BLM then classified northern spotted owl habitat 

according to strength-of-selection curves following a process used by the U.S. Forest Service (Davis et al. 

2011:36-40) but with its own relative habitat suitability surfaces. Examining the results for each modeling 

region, the BLM found that strength-of-selection curves between -2.75 and 2.75 were relatively flat in 

each modeling region, and then deviated sharply downward (below -2.75) or upward (above 2.75) beyond 

those values. Therefore, values below -2.75 were strongly selected against, values -2.75 – 0 were selected 

against, values 0 – 2.75 were selected for and values greater than 2.75 were strongly selected for. 

Among the modeling regions, the ‘strongly selected for’ category accounted for 3.48 – 12.1 percent of the 

landscape and 15.4 – 72.0 percent of the known northern spotted owl sites; combining it with the 

‘selected for’ category accounted for 18.7 – 35.4 percent of the landscape and 78.4 – 89.9 percent of the 

known northern spotted owl sites. Range-wide, 28.6 percent of the landscape was categorized as either 

‘selected for’ or ‘strongly selected for’ and 83.8 percent of the known owl sites occurred on that 

landscape. Conversely, ~72 percent of the area was ‘selected against’ or ‘strongly selected against’ and 

contained ~17 percent of the known owl sites. Therefore, although the BLM could have chosen other 

values to define categories, the values it chose have real meaning for how northern spotted owls select 

habitat. 

The BLM determined that the ‘selected against’ category in western Oregon described habitat that the 

BLM previously had classified as habitat used only for northern spotted owl dispersal. As described 

above (Table T-4), the BLM also determined that “selected for” and “strongly selected for” were reliable 

predictors of nesting-roosting habitat. Given that northern spotted owls show strongest selection for 

nesting and roosting habitat, less strong selection for foraging habitat, and still weaker selection for 

dispersal habitat, the BLM determined that the “strongly selected for,” “selected for” and “selected 

against” categories, combined, were a reasonable description of habitats that supported dispersing 

northern spotted owls. 

In Table T-4, the BLM compared the acres of nesting-roosting habitat on Federal lands derived by the 

U.S. Forest Service (Davis et al. 2015) and the BLM using their separate models and data sets. In Table 

T-5, the BLM compares the acres of northern spotted owl dispersal habitat on all lands in western Oregon 

(the BLM evaluated dispersal capability and flux only in western Oregon) as calculated by the U.S. Forest 

Service (Davis et al. 2015, Table 12) from 2012 GNN data, and by the BLM using 2013 Woodstock data 

for BLM-administered lands and 2012 GNN data for other lands. Even though the two agencies used 

different datasets and MaxEnt models, the results are similar. And, again, the BLM is confident that its 

2013 data for BLM-administered lands in western Oregon are more reliable than the 2012 GNN data for 

those same lands. 

Table T-5. A comparison of the estimated acres of northern spotted owl dispersal habitat on all lands in 

western Oregon as calculated by the U.S. Forest Service and by the BLM

Oregon Physiographic Province Acres from Davis et al. 2015,

Table 12

Acres calculated

by the BLM

Coast Range 2,589,300 1,961,636

Western Cascades 4,082,000 3,728,991

Klamath 1,918,100 1,960,445

Eastern Cascades 1,307,700 1,035,568

Totals 9,897,100 8,686,640

Comment: The BLM should plot response curves for the range of potential values for each MaxEnt model 

covariate, with other covariates fixed at the mean for each habitat suitability class, to evaluate the 
1775 | P a g e

efficacy of the MaxEnt models for capturing plausible changes in habitat suitability in response to 

changes in forest structure from forest growth or management activities. 

BLM response: The U.S. Fish and Wildlife Service also was asked to provide response curves but 

purposefully did not. Although relative habitat suitability values are intended to predict the relative 

suitability of an area (based on conditions within 800 meters of the focal pixel), the individual variable 

values are not meant to reflect all factors that influence northern spotted owls. Thus, the U.S. Fish and 

Wildlife Service sought a model with good predictive abilities and that was robust and well calibrated. In 

this, it succeeded. Since the BLM’s models are highly correlated with the U.S. Fish and Wildlife 

Service’s models, as verified by the BLM, they should have similar attributes. The BLM is confident that 

its models have good predictive ability and are robust because they predicted both the original data and 

independent data well. 

HexSim 

Comment: The BLM did not perform a sensitivity analysis to determine which covariate values most 

influence its HexSim results.

BLM response: The BLM relied on the sensitivity analyses performed by the U.S. Fish and Wildlife 

Service during the development of its model (USDI FWS 2012, pp. 13–17).The BLM did not modify any 

of the population parameters in the U.S. Fish and Wildlife Service’s HexSim model. The only difference 

between the U.S. Fish and Wildlife Service’s use of its HexSim model and the BLM’s use was that the 

BLM updated northern spotted owl survival and reproduction rates, and barred owl encounter rates, 

according to the results of the 2016 northern spotted owl meta-analysis (provided by Dr. Katie Dugger, 

Oregon State University, the principal author of the meta-analysis; Dugger et al. 2016) and 

recommendations by the U.S. Fish and Wildlife Service, and recalibrated the simulation start time to the 

year 2013. 

Comment: The BLM approach for simulating competitive interactions between barred owls and northern 

spotted owls misrepresents the ecological mechanism that contributes to spotted owls being displaced 

from sites, which many experts believe is interference competition. If interference competition and 

competitive displacement are the mechanisms, which contribute to spotted owl site abandonment, then 

total habitat carrying capacity becomes extremely important because much of that habitat is occupied by 

barred owls. If that is the case, then relatively small changes in habitat amount could produce 

disproportionate changes in northern spotted owl numbers. That relationship is currently masked within 

the BLM HexSim model because encounters with barred owls are represented as a random predation 

effect that has the potential to suppress the northern spotted owl population well below habitat carrying 

capacity.

BLM response: Northern spotted owl survival, as used in the U.S. Fish and Wildlife Service’s HexSim 

model, and subsequently by the BLM, was derived from Forsman et al. 2011 (USDI FWS 2011, pp. C-59, 

C-68 and C-69, and 2012, pp. 10, 13) and, for preparation of the Proposed RMP/Final EIS, from the 2016 

meta-analysis (Dugger et al. 2016). Although survival, as it is used in the model, might not reflect the 

ecological processes, such as interference competition, that cause northern spotted owls to react to barred 

owls in specific ways, it is based on scientific research. 

As explained in the Northern Spotted Owl section of Chapter 3, BLM simulations indicate that, within the 

range of the alternatives and the Proposed RMP examined by the BLM, limited carrying capacity is not a 

basis for BLM decision-making because there are no substantive differences in the northern spotted owl 

responses among alternatives and the Proposed RMP. In addition, all alternatives and the Proposed RMP 

show essentially identical northern spotted owl responses as would occur under the BLM’s No Timber 

Harvest reference analysis. 
1776 | P a g e

Neither the U.S. Fish and Wildlife Service nor the BLM have suggested that barred owl effects are 

random predation effects and not competition effects. The northern spotted owl HexSim model used by 

both the U.S. Fish and Wildlife Service and BLM simply assumes that, if a barred owl is present in a 

northern spotted owl’s territory, survivorship of the spotted owl would decrease according to observed 

rates and probabilities. Neither agency assumed that this decrease was due to predation, starvation, 

competition or any other specific mechanism. The encounters with barred owls in the HexSim model are 

represented only as reductions in survival; scientists have not identified a specific mechanism. Among 

potential causes, displacement from nest sites (competition for nest sites), direct predation of spotted owls 

by barred owls (predation), and competition for food are ideas that have varying levels of support in the 

scientific community, and it is likely that more than one mechanism occurs. 

When barred owl encounters are treated like predation effects, there may be little or no response to 

changes in habitat availability. The U.S. Fish and Wildlife Service found this to be the case when barred 

owl encounter rates exceeded 0.5. However, with barred owl encounter rates at 0.25 or 0.0, the U.S. Fish 

and Wildlife Service found a relatively strong effect of habitat on northern spotted owl populations. Those 

results are logical regardless of whether the actual mechanism is predation, competition or some 

combination. 

Comment: On page 774 of the Draft RMP/EIS, the BLM notes that there is relatively broad consensus 

among northern spotted owl experts that competition with barred owls is a primary contributor to 

northern spotted owl population declines, and the BLM cites Dugger et al. (2011) and Wiens et al. (2014) 

regarding the importance of habitat conservation in the face of competition with barred owls. 

Unfortunately, the HexSim modeling in the BLM analysis does not capture that competitive displacement 

mechanism. This is a particularly difficult problem because representing spatial displacement of northern 

spotted owls by barred owls requires spatially explicit predictions of barred owl occupancy, and such 

information is probably not available for most of the range. One approach for addressing this problem 

would be to run HexSim scenarios both with and without additive mortality from barred owl interactions 

and interpret the outputs from model runs without barred owl impacts as estimates of total owl habitat 

carrying capacity, then compare carrying capacity across management alternatives with the 

understanding that the carrying capacity is in reality likely to be split between spotted owls and barred 

owls due to the displacement pressures of barred owls on spotted owl populations. Even using the 

modified barred owl encounter rates is likely to reduce the sensitivity of the HexSim model to changes in 

habitat amount and distribution. 

BLM response: The suggestion that northern spotted owl population responses to the alternatives and the 

Proposed RMP are “likely to be split” between the effects of habitat and barred owl encounters is too 

suppositional for BLM decision-making processes. Furthermore, the National Environmental Policy Act 

requires the BLM to examine reasonably foreseeable northern spotted owl responses to its alternatives 

and the Proposed RMP. The BLM saw no value in determining if spotted owls would respond better 

under one alternative than another in the absence of barred owls when such absence was not reasonably 

foreseeable, even if the U.S. Fish and Wildlife Service were to implement a control program. That said, 

the BLM discussed the reasonableness of reduced barred owl encounter rates with the U.S. Fish and 

Wildlife Service. The BLM recognizes that both habitat and barred owls have impacts on northern spotted 

owl populations. 
1777 | P a g e

D. How the BLM Refined its Relative Habitat Suitability 

Surfaces between the Draft RMP/EIS and the Proposed 

RMP/Final EIS 

As explained in Appendix S of the Draft RMP/EIS (USDI BLM 2015), the BLM developed, through 

separate processes, northern spotted owl relative habitat suitability surfaces for (1) the decision area 

(using BLM Woodstock covariates) and (2) all lands in the United States’ portion of the northern spotted 

owl range (using GNN covariates). The BLM then deleted those portions of the range-wide surfaces that 

pertained to the decision area and replaced them with the surfaces it developed specifically for those 

lands. Here, the BLM describes how it further refined its relative habitat suitability surfaces since 

publication of the Draft RMP/EIS. 

All Lands in the United States’ Portion of the Northern Spotted 

Owl’s Range

For the Draft RMP/EIS, the BLM forecasted decadal changes in relative habitat suitability over time from 

three causes: large (at least 1,000-acre) wildfires, timber harvest and forest ingrowth (USDI BLM 2015, 

pp. 1480–1485). 

 To forecast large wildfires, the BLM developed the method described in Appendix D of the Draft 

RMP/EIS. 

 To forecast timber harvest, the BLM used unpublished LandTrendr data developed by the U.S. Forest 

Service for 1996–2006 (Davis et al. 2011, pp. 28–30) and projected changes calculated from 1996–

2006, specific to modeling region and land classification, into the future at decadal increments. 

 To forecast forest ingrowth, the BLM initially masked out (1) 1996–2006 wildfire burn patches, (2) 

1996–2006 calculated timber harvest units (based on the 1996–2006 LandTrendr data) and (3) lands 

within 800 meters of those areas (because the BLM relative habitat suitability values of each pixel are 

based on the means of covariate values within 800 meters of the pixel; see USDI BLM 2015, pp. 

1480–1481). In theory, masking out these lands would eliminate all lands that experienced, or were 

influenced by, habitat losses during 1996–2006, leaving only those lands that had experienced 

positive or neutral changes (i.e., forest ingrowth) during that period. 

The BLM verified the reliability of its wildfire methodology through expert review and continued to use it 

for the Proposed RMP/Final EIS. The BLM also determined that its use of LandTrendr was the most 

reliable method for forecasting timber harvest. However, to forecast forest ingrowth, the BLM found that, 

even after it had masked out the lands described above, the remaining lands still exhibited substantial 

habitat loss during 1996–2006 (i.e., the LandTrendr analysis did not account for much of the observed 

habitat loss that occurred during that period). Because the BLM needed to forecast changes in relative 

habitat suitability values from forest ingrowth, and habitat losses during 1996–2006 clearly did not result 

from ingrowth, the BLM compensated by changing all negative changes in relative habitat suitability 

values on unmasked lands during 1996–2006 to 0. In addition, because the BLM felt that positive changes 

in relative habitat suitability values during 1996–2006 greater than 10 were unrealistic, based on how 

northern spotted owl habitat is known to develop, the BLM truncated change values greater than 10 to 10. 

However, even though the BLM determined analytically that the resulting forecasts in forest ingrowth 

realistically followed observed forest structural progressions, it felt that its estimates of forest ingrowth in 

some areas, primarily in northern California, were optimistic and could be improved. 

Following publication of the Draft RMP/EIS, the BLM experimented with dropping the 1996–2006 

LandTrendr analysis. Instead, the BLM used GNN data to estimate changes (both positive and negative) 

from all causes other than large wildfires. Since the 2012 GNN data now were available, the BLM 

estimated such changes during 1996–2012 by: 
1778 | P a g e

 Masking out the decision area, because the BLM was estimating temporal changes in relative habitat 

suitability on other lands in this process; 

 Masking out 1996–2012 wildfire burn patches of at least 1,000 acres, because the BLM would 

forecast habitat changes from large wildfires using its wildfire model; 

 Masking out all lands within 800 meters of the BLM-administered lands and the 1996–2012 large 

wildfire patches. 

 Calculating the observed mean change in each relative habitat suitability value during 1996–2012 for 

the remaining lands (i.e., for all 30 × 30-m pixels with the same relative habitat suitability value in 

1996, calculating the mean change in that value between 1996 and 2012); and 

 Dividing the mean rate-of-change for each relative habitat suitability value by 1.6 to prorate the 16-

year (1996–2012) change to a decadal change (e.g., a mean change in relative habitat suitability value 

during 1996–2012 of +16 was prorated to +10; a mean change of -16 was prorated to -10). 

The BLM calculated such mean changes by land division (i.e., for each physiographic province and, 

within each province, for Congressionally Reserved lands, all other Federal reserved lands, Federal nonreserved lands, and non-Federal lands). Since there are 12 physiographic provinces within the northern 

spotted owl’s range, the BLM calculated 48 sets of mean changes in relative habitat suitability values. 

Because the GNN data were derived from Landsat imagery, the BLM still was concerned that calculated 

mean changes (both positive and negative) for some relative habitat suitability values could be unrealistic 

given how forest structure develops. Although satellite imagery is reliable at the landscape scale, it is less 

reliable at the scale of a 200-ha circle (which has a radius of 800 m), the scale at which the BLM 

calculated relative habitat suitability values. Thus, the BLM anticipated that the values of some individual 

pixels could change to such a degree that they would bias the mean change for certain pixel values (e.g., a 

positive change that exceeds the rate at which forest stands are known to develop). This especially would 

be likely for relative habitat suitability values that were uncommon on the landscape in 1996. 

To address this, the BLM compared, for each land division, decadal rates of change for all data and for 

subsets of data within 1.0, 1.5 and 2.0 standard deviations from the mean change for each relative habitat 

suitability value. The BLM found no appreciable differences between any of the resulting data sets, i.e., 

no evidence that one dataset projected habitat change more accurately than the other datasets. Therefore, 

the BLM chose to use the full dataset for each land division. 

Table T-6 shows, for each physiographic province, forecasts of northern spotted owl habitat change 

during 2013–2063 on non-Federal lands using different methods. Habitat is classified by strength-ofselection, with ‘selected for’ and ‘strongly selected for’ corresponding to northern spotted owl nestingroosting habitat, and these two classes plus ‘selected against’ corresponding to northern spotted owl 

dispersal habitat. Column 1 shows the forecasts that the BLM developed for the Draft RMP/EIS. Column 

2 shows the forecasts according to the full 1996–2012 GNN datasets described in the previous paragraph. 
1779 | P a g e

Table T-6. A comparison of decadal rates of change in relative habitat suitability value on non-Federal 

lands from large wildfires, timber harvest and forest ingrowth, by strength-of-selection category and 

physiographic province, using four methods described in the text 

Physiographic Province Strength-of-Selection Class 1 2 3 4

Oregon Coast Range

Strongly Selected Against -12.29% 25.04% -10.55% -10.74%

Selected Against 63.46% -76.17% 58.22% 59.20%

Selected For 3.56% -99.43% -4.43% -5.09%

Strongly Selected For -31.30% -97.46% -33.36% -30.35%

Oregon Eastern Cascades

Strongly Selected Against -60.02% -78.70% -45.31% -56.83%

Selected Against 45.81% 170.10% 37.22% 24.64%

Selected For 126.66% 47.75% 97.81% 144.29%

Strongly Selected For 49.63% -59.68% 25.50% 60.72%

Oregon Klamath

Strongly Selected Against -21.69% 1.34% -10.39% -13.53%

Selected Against 31.99% 9.71% 23.47% 8.46%

Selected For 31.53% 4.39% 8.39% 43.55%

Strongly Selected For 82.08% -85.47% 23.03% 24.36%

Oregon Western Cascades

Strongly Selected Against -22.98% 34.72% -6.75% -6.62%

Selected Against 69.89% -89.10% 29.41% 28.99%

Selected For 42.91% -96.96% -3.31% -4.11%

Strongly Selected For 47.27% -98.79% -6.29% -3.05%

California Cascades

Strongly Selected Against -29.12% -35.58% -14.78% -21.78%

Selected Against 51.60% 147.96% 19.78% 28.56%

Selected For 62.70% -44.34% 44.03% 54.01%

Strongly Selected For 59.34% -100.00% 27.89% 100.62%

California Coast Range

Strongly Selected Against -50.55% -81.80% -26.80% -48.05%

Selected Against -5.61% -25.23% -1.35% -7.84%

Selected For 10.15% 36.55% 7.08% 31.98%

Strongly Selected For 114.60% 176.84% 51.87% 57.35%

California Klamath

Strongly Selected Against -41.91% -41.00% -28.23% -41.42%

Selected Against -15.98% -0.56% -14.50% 0.96%

Selected For 36.88% 61.08% 39.05% 17.84%

Strongly Selected For 97.68% -12.72% 39.76% 96.46%

Washington Eastern 

Cascades

Strongly Selected Against -21.66% 0.26% -20.77% -21.08%

Selected Against 26.13% 66.58% 41.42% 24.98%

Selected For 41.69% -69.28% 25.84% 44.19%

Strongly Selected For 45.30% -97.29% 12.86% 36.73%

Washington Western 

Lowlands

Strongly Selected Against -6.75% 10.56% -5.92% -5.86%

Selected Against 74.88% -100.00% 65.36% 63.91%

Selected For 9.98% -100.00% 9.98% 13.19%

Strongly Selected For 26.60% -100.00% 29.64% 47.83%

Washington Olympic 

Peninsula

Strongly Selected Against -16.48% 24.65% -14.82% -15.08%

Selected Against 63.15% -43.84% 56.59% 49.07%

Selected For -3.57% -99.79% 5.44% 25.85%

Strongly Selected For 29.10% -100.00% -8.14% -10.01%

Washington Western 

Cascades

Strongly Selected Against -5.24% 9.31% -4.81% -4.73%

Selected Against 51.10% -37.64% 47.10% 45.98%

Selected For 0.29% -88.08% 0.26% 0.45%

Strongly Selected For -2.62% -99.78% -3.34% -2.16%
1780 | P a g e

Regarding the method reflected in Table T-6, Column 2, in the Oregon Coast Range and Oregon Western 

Cascades provinces, the two largest provinces in the decision area, unfiltered rates of change during 

1996–2012 resulted in forecasted losses of 97–99 percent of selected-for and strongly-selected-for habitat 

during the next 50 years. (Not shown in Table T-6, the forecast for the Oregon Coast Range Province 

also showed a 43 percent loss in these classes during 2013–2023.) However, although these forecasts 

reflect observed rates of non-Federal timber harvests that began in the early to mid-1990s and extended to 

the 2008 recession (Gale et al. 2012, pp. 3–11), they cannot continue at this rate in the future and, thus, 

are not reliable for making 50-year forecasts. Stated another way: to lose 97–99 percent of such habitat on 

non-Federal lands during the next 50 years, it would have to be harvested from steep slopes, fragile soils, 

riparian areas, private house lots, State parks and other areas not reasonably subject to timber harvest, or 

burned on unprecedented numbers of acres by unprecedented levels of high-intensity wildfire (Gale et al. 

2012). Thus, the BLM determined that habitat changes that occurred on non-Federal lands during 1996–

2012, although real, were not indicative of future change, because they cannot continue at that rate and, 

therefore, could not be used in their raw form to forecast future change. 

Given these results, the BLM returned to the method it used for the Draft RMP/EIS, with the following 

revisions: 

 To forecast forest ingrowth, the BLM tested limiting positive changes in relative habitat suitability 

values to 1.0, 1.5 and 2.0 standard deviations from the mean instead of simply +10. 

 To forecast timber harvest, the BLM replaced the 2006 LandTrendr analysis with the newly-available 

2012 LandTrendr analysis. 

The results of these changes are shown in columns 3 and 4 of Table T-6; Column 3 is based on limiting 

forest ingrowth rates to 1 standard deviation from the mean; Column 4 is based on limiting ingrowth rates 

to 2 standard deviations from the mean. Because columns 1–4 include the effects of forest ingrowth, 

timber harvest and wildfire on non-Federal lands, the forecasted change values are directly comparable. 

Comparing the values in columns 1, 3 and 4 of Table T-6, the BLM determined that the values in 

columns 3 and 4 likely were more reliable forecasts of habitat change on non-Federal lands given past 

harvest rates and the fact that both sets of values reflected sustainable rates of timber harvest. In addition, 

the values in Column 3 were more conservative than the values in Column 4. After conferring with 

experts who were familiar with the original data and how forests develop in western Oregon (Craig 

Ducey, BLM, Jeffrey Dunk, Humboldt State University, Betsy Glenn, U.S. Fish and Wildlife Service, and 

David LaPlante, Natural Resource Geospatial, pers. com. to Eric Greenquist, various dates during 2015) , 

the BLM determined that the more-conservative Column 3 values, in terms of northern spotted owl 

habitat change on non-Federal lands, were the most realistic forecasts it could make from the available 

data. 

In summary, the BLM determined analytically that the 1996–2012 GNN data, the most accurate data for 

non-BLM-administered lands in the range of the northern spotted owl, could not be used in their raw form 

to forecast habitat changes on those lands during 2013–2063, because observed rates of habitat loss on 

non-Federal lands during 1996–2012 were not indicative of future change. As described above, this 

finding by the BLM accords well with the findings of Gale et al. (2012). Therefore, the BLM explored 

methods to filter the GNN data to generate forecasts that better accord with projections of timber harvest 

on non-Federal lands at rates that could continue into the future. In refining its methods, the BLM chose 

the more conservative of its reliable forecasts: the forecast that showed the largest habitat losses on nonFederal lands that could still continue into the future. To be clear, the BLM does not intend its forecasts of 

range-wide habitat changes to be precise and accurate predictions of future habitat conditions. Instead, 

they are intended only as reasonable and credible approximations of future habitat conditions in each 

province and land classification that can be used to compare northern spotted owl habitat and population 

responses to the different alternatives and the Proposed RMP. 
1781 | P a g e

The Decision Area

For the Draft RMP/EIS, the BLM used only the covariate values derived by Woodstock to calculate 

relative habitat suitability values for BLM-administered lands. This was problematic because, normally, 

the relative habitat suitability value of each 30 × 30-m pixel is calculated from the means of the covariate 

values within 800 meters of the pixel. However, for the years 2023, 2033, 2043, 2053 and 2063 no GNN 

covariate values existed for lands that were within 800 meters of BLM-administered lands. Although the 

BLM can forecast decadal changes in relative habitat suitability values for other lands, as described 

above, it cannot forecast decadal changes in the GNN covariate values that are used to calculate relative 

habitat suitability values. Since Woodstock derives future covariate values only for BLM-administered 

lands, there existed no future covariate values for other lands within 800 meters of BLM-administered 

lands that the BLM could use to calculate relative habitat suitability values on BLM-administered lands 

for the years 2023, 2033, 2043, 2053, and 2063.

For the Draft RMP/EIS, the BLM used only Woodstock-derived covariate values to calculate relative 

habitat suitability on BLM-administered lands, effectively ignoring the influence of other lands within 

800 meters of BLM-administered lands. The only option the BLM had to ignoring the influences of other 

lands within 800 meters of BLM-administered lands was to assume that habitat conditions on those other 

lands would remain static over time (i.e., calculate decadal relative habitat suitability values for BLMadministered lands using the decadal Woodstock covariate values for BLM-administered lands and the 

2012 GNN covariate values for other lands within 800 meters of BLM-administered lands). The BLM 

chose to ignore the influence of other lands, because it determined that the effects of ignoring the other 

lands were negligible where BLM-administered lands abutted reserves on other Federal lands. However, 

where BLM-administered lands abutted non-Federal lands, especially private industrial timberlands, and 

to a lesser extent, Federal non-reserved lands, the BLM determined that its process tended to overestimate 

the relative habitat suitability of the BLM-administered lands.

With its more-conservative forecasts of habitat changes on other lands within the range of the northern 

spotted owl, as described above, the BLM determined that the latter of the two options described above—

use the decadal Woodstock covariate values for BLM-administered lands and the 2012 GNN covariate 

values for other lands within 800 meters of BLM-administered lands—was likely more realistic than 

using only the decadal Woodstock covariates to calculate relative habitat suitability values for BLMadministered lands. The BLM tested modeling relative habitat suitability values on BLM-administered 

lands in two ways:

1. Non-weighted covariate values

 The BLM identified BLM-administered lands within 800 meters of Congressionally Reserved 

lands and other Federal reserves (e.g., the Late-Successional Reserve on U.S. Forest Service

lands). On those BLM-administered lands, the BLM calculated relative habitat suitability values 

using only the Woodstock covariates within 800 meters of each pixel to account for the likelihood 

that habitat development on BLM-administered lands would best represent habitat development 

on the adjacent reserved lands.

 On all other BLM-administered lands, the BLM calculated relative habitat suitability values using 

the decadal Woodstock covariates for the BLM-administered lands within 800 meters of each 

pixel and the 2012 GNN covariate values within 800 meters of each pixel.

2. Weighted covariate values

 The BLM masked Congressionally Reserved lands and other Federal reserves within 800 meters

of BLM-administered lands and excluded the GNN covariate values for those lands from its 

analysis.
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 Within the 800 meters circle around each pixel, the BLM calculated the area of (1) BLMadministered lands plus Congressionally Reserved lands and other Federal reserves, and (2) 

Federal non-reserved lands and non-Federal lands.

 The BLM then weighted the decadal Woodstock covariate values and 2012 GNN covariate values 

within 800 meters of each pixel according to the area of each of the two land classifications; i.e., 

the BLM weighted the decadal Woodstock covariate values according to the portion of the 800 

meters circle represented by BLM-administered lands, Congressionally Reserved lands and other 

Federal reserves, and the 2012 GNN covariate values according to the portion represented by 

Federal non-reserved lands and non-Federal lands.

The BLM found no substantive difference between the two methods in its habitat forecasts for BLMadministered lands over time. Therefore, the BLM chose not to weigh the covariate values, because that 

was the analytically simpler and quicker of the two methods.

E. Developing and Calibrating the BLM HexSim Model 

As described above, the BLM determined that the HexSim model developed by the U.S. Fish and 

Wildlife Service to inform its decisions on northern spotted owl recovery and critical habitat (USDI FWS 

2011, pp. Appendix C, and USDI FWS 2012), with specific changes, could help the BLM meet its 

planning needs. Therefore, the BLM took the U.S. Fish and Wildlife Service’s northern spotted owl 

HexSim model, fully parameterized, and modified it as necessary. The BLM made the following changes: 

 The BLM developed different range-wide relative habitat suitability surfaces that reflected spatiallyexplicit estimates of how forest stands would respond over time to forest ingrowth, timber harvest and 

wildfire on all lands, and also to forest restoration treatments (such as thinning consistent with LateSuccessional Reserve or Riparian Reserve management direction) on the decision area. 

 Although the BLM altered relative habitat suitability values by decade on all lands, as described 

above, the BLM did not otherwise augment or suppress those values. In effect, unlike some U.S. Fish 

and Wildlife Service simulations that limited northern spotted owl nesting to potential critical habitat 

units, the BLM always allowed simulated northern spotted owls to move, forage, and establish nest 

territories on all lands according to local relative habitat suitability values. 

 Because the BLM required both stochastic and non-stochastic simulations of northern spotted owl 

response for the reasons described in Chapter 3 (Northern Spotted Owl, Issue 4), the BLM completed 

500 replicate simulations of each alternative. In contrast, after its Phase 1 modeling, the U.S. Fish and 

Wildlife Service used only stochastic simulations, with 100 replicates per alternative (USDI FWS 

2012, p. 29).

 Although the BLM calibrated the BLM model using the same method used by the U.S. Fish and 

Wildlife Service (USDI FWS 2011, pp. C-71 – C-74), the BLM calibration, described below, yielded 

unique numbers and locations of female northern spotted owls to begin each of the replicate 

simulations. 

 The BLM used observed barred owl encounter rates (for the Draft RMP: Forsman et al. 2011, pp. 

Appendix B, and USDI FWS 2011, p. C-66 and Table C-25; for the Proposed RMP/Final EIS: the 

2016 meta-analysis data provided by Dr. Dugger and as recommended by the U.S. Fish and Wildlife 

Service) for reasons described in Chapter 3 (Northern Spotted Owl Issue 4). 

 Also for reasons described in Chapter 3 (Northern Spotted Owl Issue 4), the BLM simulated 50 years 

(2013–2063) with relative habitat suitability values changing every 10 years according to the BLM 

forecasts, and then held habitat values constant for an additional 50 years. 

Calibration for the Draft RMP/EIS 

The northern spotted owl HexSim model developed by the U.S. Fish and Wildlife Service (USDI FWS 

2011, Schumaker et al. 2014) is an individual-based, spatially explicit, population simulation model. The 

U.S. Fish and Wildlife Service parameterized the model based on empirically derived estimates of age-
1783 | P a g e

specific survival, fecundity, territory and home-range size, and dispersal (USDI FWS 2011 and 

Schumaker et al. 2014). The U.S. Fish and Wildlife Service used its relative habitat suitability surface in 

HexSim to represent resource quality (higher values were of greater quality than lower values). Each of 

the eleven modeling regions (USDI FWS 2011, p. C-13) had different resource targets for northern 

spotted owls, and resource targets varied in relation to home range size (larger targets in areas with larger 

home ranges). For home range size variation, many empirical studies existed and the U.S. Fish and 

Wildlife Service used them to guide its decisions in the development of HexSim (USDI FWS 2011, pp. 

Appendix C, and Schumaker et al. 2014). However, other than variation in home range size, no empirical 

information existed to guide specific decisions on resource targets. Because resource targets—as 

represented by relative habitat suitability—are not real, on-the-ground quantities, they can have no 

empirical basis; they only can be associated with on-the-ground resources. Thus, the authors of the U.S. 

Fish and Wildlife Service’s northern spotted owl HexSim models varied resource targets until resulting 

simulated population sizes were similar to empirically estimated populations of northern spotted owls 

(USDI FWS 2011, pp. Appendix C, and Schumaker et al. 2014). This model calibration happened by 

‘tuning’ (i.e., varying) resource targets by modeling region. The U.S. Fish and Wildlife Service (USDI 

FWS 2011, pp. Appendix C) also calibrated its HexSim model for dispersal such that simulated northern 

spotted owls that dispersed did so in a way that resulted in similar dispersal distance profiles to those 

estimated from empirical studies. For this portion of the calibration, the U.S. Fish and Wildlife Service 

tuned the model by varying the attraction/repulsion of various habitats (relative habitat suitability values) 

as well as the maximum number of 86.6-ha hexagons a dispersing owl could move through while 

attempting to find a territory (USDI FWS 2011, Schumaker et al. 2014). 

The BLM initially intended to use the 2012 GNN version of Model 13 for other lands within the northern 

spotted owl’s range. However, as the BLM evaluated how Model 13 would be used for HexSim 

population dynamics modeling, it evaluated a range of factors that, instead, suggested using the U.S. Fish 

and Wildlife Service MaxEnt model projected to newly available 2012 GNN variables for other lands: 

 The U.S. Fish and Wildlife Service HexSim model had been developed to work with and calibrated to 

the U.S. Fish and Wildlife Service 2006 GNN MaxEnt relative habitat suitability model, and had been 

demonstrated to be well-calibrated to those data (USDI FWS 2011, pp. Appendix C). 

 The BLM’s 2006 GNN version of Model 13 demonstrated a high degree of correlation to the U.S. 

Fish and Wildlife Service 2006 GNN model (correlation coefficient of 0.867). 

 The decision area accounts for about 4 percent of lands in the northern spotted owl’s range. As such, 

relative habitat suitability values on BLM-administered lands would likely have a proportionally 

small effect on overall population response. 

 The U.S. Fish and Wildlife Service initially calibrated its HexSim model by adjusting model 

parameters (i.e., resource targets) separately for each of its eleven modeling regions. The decision 

area is constrained to four of those regions. This meant that, by using the U.S. Fish and Wildlife 

Service 2006 GNN MaxEnt relative habitat suitability surface, five of the eleven modeling regions 

would require no recalibration at all. And, because of the high degree of correlation between the U.S. 

Fish and Wildlife Service’s model and Model 13, the other modeling regions probably would require 

only minor recalibration. 

Given these conditions, the BLM determined that using the U.S. Fish and Wildlife Service 2012 GNN 

model for other lands was reasonable and would require less calibration and re-development of HexSim 

than would be required using the BLM 2012 GNN Model 13 relative habitat suitability surfaces for those 

lands. 

The U.S. Forest Service released its 2012 GNN data at about the same time the BLM reached this phase 

in the project; up to this point, the latest release of these data was for 2006. To create the new 2012 

version of the U.S. Fish and Wildlife Service MaxEnt model, the BLM generated a full set of model 
1784 | P a g e

variable surfaces from the 2012 GNN data, using the same GNN attributes and methods used by U.S. Fish 

and Wildlife Service to generate the original 1996 and 2006 covariate rasters (USDI FWS 2011, 

Appendix C). The BLM then projected the original U.S. Fish and Wildlife Service 1996 MaxEnt model to 

the 2012 covariate rasters separately for each of the eleven U.S. Fish and Wildlife Service modeling 

regions and merged them into a single, seamless, range-wide relative habitat suitability surface. 

To derive the relative habitat suitability surface needed to calibrate HexSim, the BLM then replaced the 

pixels in the U.S. Fish and Wildlife Service 2012 GNN model for the decision area with data from the 

final BLM 2013 Woodstock Model 13 raster. 

Because the BLM created new MaxEnt surfaces for the decision area, the BLM sought to evaluate 

whether the ‘default settings’ of HexSim, as used by the U.S. Fish and Wildlife Service, would work well 

for the BLM, or whether further calibration (fine tuning) was needed before running population 

simulations. In its calibration/tuning of the northern spotted owl HexSim model, the U.S. Fish and 

Wildlife Service (USDI FWS 2011, pp. Appendix C) found that time-step 50 represented a reasonable 

approximation of the present (at the time the U.S. Fish and Wildlife Service did its work). The only 

differences between the data feeding into the northern spotted owl HexSim models by the U.S. Fish and 

Wildlife Service and this effort by the BLM were that: 

 The U.S. Fish and Wildlife Service and the BLM used different MaxEnt relative habitat 

suitability surfaces for the decision area, and; 

 The relative habitat suitability surface for the decision area was estimated for 2013. The BLM 

projected the U.S. Fish and Wildlife Service 1996 GNN MaxEnt models using GNN data from 

2012 (as opposed to 2006, as used by the U.S. Fish and Wildlife Service) for other lands. 

Thus, this new ‘base’ relative habitat suitability surfaces used by the BLM used the identical MaxEnt 

models for all lands except BLM-administered lands in the planning area, and, for those lands, the BLM 

developed a new MaxEnt model (Model 13). Since the correlation between the relative habitat suitability 

surfaces developed by the U.S. Fish and Wildlife Service and Model 13 was so high, the BLM anticipated 

that its HexSim model would require minor, or no, recalibration. 

The BLM began recalibration by using the U.S. Fish and Wildlife Service default HexSim settings, and 

evaluated population estimates for the same eight demographic study areas for which the U.S. Fish and 

Wildlife Service had data (USDI FWS 2011, pp. C-71 – C-75). The BLM ran 20 replicates of HexSim 

(without environmental stochasticity; see Northern Spotted Owl, Chapter 3) for 70 time-steps. Replicates 

refer to the number of distinct simulations that are run. Because HexSim is not a deterministic model, 

several replicates are needed to get an estimate of mean responses (i.e., different replicates will almost 

always vary in their specific population responses). The BLM chose 70 time-steps because it initially 

wanted to evaluate whether, using default settings, simulated demographic study area population sizes 

were more/less similar to empirically-estimated populations before, during, or after time-step 50: the 

time-step that the U.S. Fish and Wildlife Service (USDI FWS 2011, pp. C-71 – C-75) found to be a good 

approximation of ‘now.’ The BLM used the mean population among the 20 replicates to estimate 

simulated population size. For the eight demographic study areas, the BLM used the mean of the three 

years with the largest population to estimate population size (USDI FWS 2011, pp. C-71 – C-75). 

Using default parameters in the northern spotted owl HexSim model, the BLM found that mean 

population size of territorial owls on the eight demographic study areas at time-step 59 corresponded most 

closely with the empirical population estimates. For the demographic study areas, empirical estimates of 

populations ranged from 30 to 130, with the total population on the eight study areas being 756. At timestep 59, mean simulated estimates of populations ranged from 32 to 145, with a total population of 763. 

The pairwise percent differences between empirical and simulated populations on each of the study areas 

varied from 0.54 percent to 41.75 percent, with a mean percentage difference of 4.7 percent. Time-step 55 
1785 | P a g e

had the smallest mean percent difference (-2.3 percent) but the estimate of total population size on the 

eight study areas was 6 percent higher than the empirical estimates. In contrast, the time-step 59 estimated 

total population size on the eight study areas was 0.95 percent larger than the empirical estimate. Figure 

T-17 compares empirical and time-step 59 population estimates in each of the study areas. 

Because the default parameters worked well, the BLM did not further attempt to fine-tune any parameter 

settings and used the default settings. The only difference between the U.S. Fish and Wildlife Service’s 

(USDI FWS 2011) and BLM’s use of the spotted owl HexSim model was that the U.S. Fish and Wildlife 

Service used time-step 50 to represent the current year and the BLM used time-step 59. 

Figure T-17. Comparison of the mean of estimates of territorial northern spotted owls on eight 

demographic study areas estimated in the field (empirical estimates, n = mean of three highest years 

between 1996 and 2006) and estimated using the BLM northern spotted owl HexSim model (mean from 

20 replicates of HexSim at time-step 59) 

Additional Calibration for the Proposed RMP/Final EIS 

The northern spotted owl HexSim model that the BLM used for its Draft RMP/EIS was essentially 

identical to that used by the U.S. Fish and Wildlife Service to inform its decisions on northern spotted owl 

recovery and the delineation of northern spotted owl critical habitat. The U.S. Fish and Wildlife Service 

model relied heavily on demographic parameters from the 2011 northern spotted owl meta-analysis 

(Forsman et al. 2011). Since publication of the Draft RMP/EIS, Dr. Katie Dugger, Oregon State 

University, the principal author of the 2016 northern spotted owl meta-analysis (Dugger et al. 2016), 

provided the BLM with five additional years of (not-yet-published) meta-analysis results on northern 

spotted owl adult fecundity and survival, and barred owl encounter rates. 

43

120

130

30

121 122

111

78

32

135

141

18

122

88

145

82

0

40

80

120

160

Cle Elum Coast

Ranges

HJ

Andrews

Hoopa Klamath Olympic South

Cascades

Tyee

Group Members

Demographic Study Area

Empirical Estimate HexSim Estimate
1786 | P a g e

Fecundity

Dr. Dugger provided meta-analysis results for the eight northern spotted owl demographic study areas on 

Federal land that are used to monitor the Northwest Forest Plan. Fecundity data were stratified among 

three northern spotted owl age classes: 1-year olds (S1), 2-year olds (S2), and greater than or equal to 3-

year olds (adults). The northern spotted owl HexSim model that the BLM used for the Draft RMP/EIS , 

which relied on fecundity data from Forsman et al. 2011, assumed mean fecundity values of 0.070, 0.202, 

and 0.330 for S1, S2, and adults, respectively. Mean (un-weighted) fecundity values among the eight 

demographic study areas from the 2016 meta-analysis were 0.068, 0.215, and 0.326 for S1, S2, and 

adults, respectively. Since these values for each age class were nearly identical, the BLM did not change 

fecundity values in its HexSim model for the Proposed RMP/Final EIS. 

Survival

The U.S. Fish and Wildlife Service used data from Forsman et al. 2011 (p. 32, Table 12) to stratify 

survival rates among S1, S2, and adult owls. The authors of the 2016 meta-analysis did not use the same 

analytic approach used by Forsman et al. (2011). Forsman et al. based their estimates of age-specific 

survival on model averaging. In contrast, for the 2016 meta-analysis, Dugger et al. (2016) based their 

results on the best random effects model for each demographic study area. In addition, Dugger et al. 

estimated only adult survival whereas Forsman et al. estimated survival for each age class. As with the 

fecundity data, Dugger et al. provided estimates of adult survival for the eight Federal land demographic 

study areas. 

For each of the eight demographic study areas, the BLM estimated mean annual survival from the 2016 

meta-analysis and compared them to the model-averaged rates estimated by Forsman et al. (2011) for the 

same demographic study areas. For the eight demographic study areas, the estimates by Forsman et al. 

were larger for three demographic study areas, smaller for three demographic study areas, and identical 

for two demographic study areas. The average difference between the Dugger et al. and Forsman et al. 

estimates was 0.0039 (range -0.003 to 0.025). The grand mean of estimates according to Dugger et al. and 

Forsman et al. were 0.8502 and 0.8463, respectively. 

The BLM did not change survival values in its HexSim model for the Proposed RMP/Final EIS, because 

(1) estimates of adult survival by Dugger et al. and Forsman et al. 2011 were so similar, (2) both sets of 

authors used different approaches to calculate survival, and (3) Dugger et al. did not calculate survival for 

all age classes. 

Barred Owl Encounter Rates

Dr. Dugger provided updated estimates of barred owl encounter rates (the proportion of northern spotted 

owl territories on which surveyors detected barred owls) for each of the eight Federal land demographic 

study areas. She provided the estimates for each year since the studies began (or when barred owls first 

were recorded) through 2013. For the eight demographic study areas, the highest barred owl encounter 

rates occurred in 2013 for four demographic study areas. Seven of the eight demographic study areas 

show very strong linear time trends in barred owl encounter rates. 

For each demographic study area, the BLM compared the mean barred owl encounter rate for the years 

2007–2009 and 2011–2013. The mean percent change for all demographic study areas between these two 

means was 24.04 percent (range 8.37–83.33). Mean change for 2008–2013 was 36.87 percent, and for

2009–2013 was 26.48 percent. Slopes of individual demographic study area linear regressions (barred owl 

encounter rate × time) averaged 0.02 (range 0.004–0.041). Thus, the barred owl encounter rates, on 

average, increased by about 2 percent per year in the eight demographic study areas from approximately 

1990-2013. 
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In the U.S. Fish and Wildlife Service’s HexSim model, the U.S. Fish and Wildlife Service based barred 

owl encounter rates on demographic study area data provided by Forsman et al. (2011). Some 

demographic study areas are completely within one of the U.S. Fish and Wildlife Service’s modeling 

regions, whereas other demographic study areas straddle multiple modeling regions, and some modeling 

regions have no demographic study area. Thus, the U.S. Fish and Wildlife Service used a combination of 

empirical data and professional judgment to ascribe barred owl encounter rates to each of the eleven U.S. 

Fish and Wildlife Service modeling regions. 

For those demographic study areas within a single discrete modeling region, the BLM used the 2013 

barred owl encounter rate from the demographic study area. For those modeling regions where it was less 

clear, the BLM applied the 26.48 percent increase (i.e., the average observed rate of change for all 

demographic study areas during 2009–2013) to the rates used by U.S. Fish and Wildlife Service in its 

HexSim model. Forsman et al. (2011) presented data on barred owl encounter rates through 2008. Thus, 

the BLM determined that using the average percentage increase on demographic study areas from 2009 to 

2013, as the inflation factor was warranted. Table T-7 compares the barred owl encounter rates used by 

the BLM for the Draft RMP/EIS and the Proposed RMP/Final EIS. 

Table T-7. Barred owl encounter rates used by the BLM for the Draft RMP/EIS and Proposed RMP/Final 

EIS 

Modeling Region

Estimated Barred Owl 

Encounter Rates Used for the 

Draft RMP

Estimated Barred Owl 

Encounter Rates Used for the 

Proposed RMP/Final EIS

North Coast and Olympics* 0.505 0.515

East Cascades-North 0.296 0.374

West Cascades-North 0.320 0.405

West Cascades-Central 0.325 0.411

Oregon Coast* 0.710 0.831

West Cascades-South* 0.364 0.442

Inner California Coast Range 0.213 0.269

East Cascades-South* 0.180 0.228

Klamath-Siskiyou-East* 0.245 0.411

Klamath-Siskiyou-West* 0.315 0.398

Redwood Coast 0.205 0.259

* Modeling regions entirely or partially in the planning area

Mean barred owl encounter rates for the eleven modeling regions are 0.334 (Draft RMP/EIS) and 0.413 

(Proposed RMP/Final EIS). Among the eight demographic study areas, Dugger et al. (2016) calculated a 

mean barred owl encounter rate in 2013 of 0.449. 

Hypothetical Barred Owl Control Areas 

For the Draft RMP/EIS, the BLM evaluated northern spotted owl population responses to all alternatives, 

and to the No Timber Harvest reference analysis, using the observed estimated barred owl encounter rates 

shown in Table 3-263 of the Draft RMP/EIS (USDI BLM 2015, p. 778). The BLM also evaluated 

Alternative C and the No Timber Harvest reference analysis using modified barred owl encounter rates 

developed by the U.S. Fish and Wildlife Service, also shown in Table 3-263. The BLM did the 

supplemental analyses to evaluate the degree to which BLM land use allocations could affect northern 

spotted owl population responses if the U.S. Fish and Wildlife Service implemented a barred owl control 

program. 
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As shown on pp. 783–804 of the Draft RMP/EIS, the BLM determined that northern spotted owl 

population responses to all of the alternatives, and to the No Timber Harvest reference analysis, were 

virtually identical because they primarily were determined by the observed estimated barred owl 

encounter rates (i.e., the degree of observed competitive interactions between northern spotted owls and 

barred owls). Since observed estimated barred owl encounter rates from the 2016 meta-analysis increased 

in all modeling regions (Table T-7), the BLM determined that it would learn nothing more by using the 

increased rates for the Proposed RMP/Final EIS. 

Instead, the BLM simulated northern spotted owl population responses under Alternative C, the Proposed 

RMP, and the No Timber Harvest reference analysis using modified barred owl encounter rates in 

simulated barred owl control areas and observed estimated barred owl encounter rates (Table T-7, 

Column 3) in the remainder of each modeling region. The BLM did this to simulate range-wide northern 

spotted owl population responses under each scenario if the U.S. Fish and Wildlife Service were to 

implement a barred owl control program. Applying the modified barred owl encounter rates only in 

control areas more realistically simulates the true effects of a barred owl control program. This was a 

refinement to how the BLM simulated a barred owl control program for the Draft RMP/EIS, in which the 

BLM applied the modified barred owl encounter rate specific to each modeling region to all lands in the 

modeling region. 

The BLM delineated hypothetical barred owl control areas and modified barred owl encounter rates with 

assistance from Jeffrey Dunk, Humboldt State University, David LaPlante, Natural Resource Geospatial, 

and Betsy Glenn, U.S. Fish and Wildlife Service, who helped the BLM develop its analytical 

assumptions. The BLM began with the assumptions that barred owl control would occur—

 Throughout the northern spotted owl’s range;

 On approximately 10 percent of the forested landscape in each modeling region; 

 In the Late-Successional Reserve on Federal lands, on State lands, and in northern spotted owl 

critical habitat on Federal and State lands; 

 In aggregations of the best northern spotted owl habitat; and 

 Within one mile of an improved road. 

To delineate hypothetical control areas, the BLM segregated all lands in each modeling region into 20 

resource bins according to relative habitat suitability value (those pixels with a relative habitat suitability 

value of 96 or higher were placed in Bin 1; those with values 91–95 were placed in Bin 2, etc.). The BLM 

then confined its analysis to those bins with relative habitat suitability values of 35 or higher (i.e., nestingroosting habitat in 13 resource bins). 

The BLM delineated the Late-Successional Reserve on Federal lands, State lands, and northern spotted 

owl critical habitat on Federal and State lands into five distance bins based on their distance from an 

improved road (i.e., those lands within 0.25 mile, 0.50 mile, 0.75 mile, and 1.0 mile of an improved road, 

and beyond 1.0 mile of an improved road). The BLM then confined its analysis to those bins within 1.0 

mile of an improved road (i.e., 4 distance bins).55

This generated a digital map of Federal and State lands segregated into 52 bins (13 resource bins × 4 

distance bins) based on relative habitat suitability value and distance to an improved road. That is, the 30 

× 30-m pixels with highest habitat suitability values and lands nearest roads were placed in lowernumbered bins, respectively, and the BLM multiplied the two bin values for each pixel to rank the pixels, 

with the lowest multiples receiving the highest rank. The BLM then used the zonation model developed 

 

55 The BLM used a Fibonacci sequence where 0.25- and 0.5-mile bands equaled 1, 0.7-mile bands equaled 2, and 

1.0-mile bands equaled 3. 
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by the U.S. Fish and Wildlife Service (USDI FWS 2011, pp. Appendix C, and USDI FWS 2012) to 

aggregate Federal and State lands into barred owl control areas based on relative habitat suitability value 

and nearness to an improved road until 10 percent of the forested landscape in each modeling region had 

been delineated. This process led to the highest value habitat areas within appropriate land allocation 

categories and closest to a road being included in the ‘target area’ first, followed by successively lower 

value habitats down to a value of 35 and greater distances out to 1.0 mile. 

However, in the North Coast and Olympics and West Cascades-North modeling regions, zonation 

delineated only 4.8 percent of the forested landscape in each modeling region, due primarily to the acres 

of roadless lands, such as in Olympic National Park. The BLM conferred with the U.S. Fish and Wildlife 

Service, which recommended that the BLM expand the control areas in other modeling regions until it 

achieved a range-wide total of 10 percent (Betsy Glenn, U.S. Fish and Wildlife Service, pers. com. to Eric 

Greenquist, September 11, 2015). The U.S. Fish and Wildlife Service made this recommendation because 

the added acres mostly would occur in regions with the largest northern spotted owl populations, which is 

how the U.S. Fish and Wildlife Service most likely would design a control program. Figure T-18 shows 

the hypothetical control areas delineated by zonation. 
1790 | Page

Figure T-18. Hypothetical barred owl control areas in the United States’ portion of the northern spotted 

owl’s range

Figure T-18. Hypothetical barred owl control areas in the United States’ portion of the northern spotted 

owl’s range
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Modified Barred Owl Encounter Rates 

As the BLM explained on pp. 778–780 of the Draft RMP/EIS, when simulating northern spotted owl 

responses to a barred owl control program, the BLM used the estimated observed barred owl encounter 

rates (Table 3-263, p. 778 of the Draft RMP/EIS) during the first decade (2013–2023) and the modified 

barred owl encounter rates (same table) during 2023–2063. In two modeling regions with the highest 

estimated observed encounter rates, the BLM phased in the modified rates over the first two decades 

(2013–2033) (USDI BLM 2015, p. 779). 

However, with the delineation of hypothetical control areas for the Proposed RMP/Final EIS, the BLM, 

based on the recommendation of the U.S. Fish and Wildlife Service (Betsy Glenn, U.S. Fish and Wildlife 

Service, personal communication to Eric Greenquist, September 1, 2015), used the observed estimated 

barred owl encounter rates shown in the third column of Table T-7 but, beginning with the second decade 

(i.e., during 2023–2063), reduced the barred owl encounter rate in each of the hypothetical control areas 

to 0.15 to simulate the effects of a targeted barred owl control program (i.e., the BLM continued to use 

the observed estimated encounter rates outside the hypothetical control areas). 
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References 

Dancey, C., and J. Reidy. 2004. Statistics without maths for psychology: using SPSS for Windows, London: Prentice Hall.

Davis, R. J., K. M. Dugger, S. Mohoric, L. Evers, and W. C. Aney. 2011. Status and trends of northern spotted owl populations 

and habitats. General Technical Report PNW-GTR-850. USDA FS, Pacific Northwest Research Station, Portland, OR. 147 

pp. http://www.fs.fed.us/pnw/pubs/pnw_gtr850.pdf.

Davis, R., L. Evers, Y. Gallimore, and C. Belongie. 2014. Modeling large stochastic wildfires and fire severity within the 

northern spotted owl’s range to support the western Oregon plan revision modeling effort. Unpublished manuscript. 8 pp.

Davis, R. J., B. Hollen, J. Hobson, J. E. Gower, and D. Keenum. 2015. Northwest Forest Plan—the first 20 years (1994–2013): 

status and trends of northern spotted owl habitats. Gen. Tech. Rep. PNW-GTR-xxx. Portland, OR: U.S. Department of 

Agriculture, U.S. Forest Service, Pacific Northwest Research Station. xx p. http://www.reo.gov/monitoring/reports/20yrreport/NSO%20Habitat%2020yr%20Report%20-%20Draft%20for%20web.pdf. 

Dugger, K. M., E. Forsman, A. B. Franklin, R. J. Davis, G. C. White, C. J. Schwarz, K. P. Burnham, J. D. Nichols, J. E. Hines, C. 

B. Yackulic, P. F. Doherty, Jr., L. Bailey, D. A. Clark, S. H. Ackers, L. S. Andrews, B. Augustine, B. L. Biswell, J. 

Blakesley, P. C. Carlson, M. J. Clement, L. V. Diller, E. M. Glenn, A. Green, S. A. Gremel, D. R. Herter, J. M. Higley, J. 

Hobson, R. B. Horn, K. P. Huyvaert, C. McCafferty, T. McDonald, K. McDonnell, G. S. Olson, J. A. Reid, J. Rockweit, V. 

Ruiz, J. Saenz, and S. G. Sovern. 2015. The effects of habitat, climate, and barred owls on long-term demography of 

northern spotted owls. The Condor Ornithological Applications 118: 57–116. http://dx.doi.org/10.1650/CONDOR-15-24.1. 

Manley, P. 2014. Declaration of Patricia Manley in support of federal defendants’ opposition to plaintiffs’ motion for preliminary 

injunction, dated October 1. U.S. District Court for the Eastern District of California, Sacramento Division. 12 pp. 

Ohmann, J. L., and M. J. Gregory. 2002. Predictive mapping of forest composition and structure with direct gradient analysis and 

nearest-neighbor imputation in coastal Oregon, USA. Canadian Journal of Forest Research 32(4): 725–741. 

http://www.fsl.orst.edu/clams/download/pubs/CJFR_ohmann_gregory.pdf. 

Phillips, S. J., R. P. Anderson, and R. E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. 

Ecological Modeling 190: 231–259. 

http://web.sci.ccny.cuny.edu/~anderson/publications/PhillipsAndersonSchapire2006EcologicalModelling.pdf. 

Schumaker, N. H. 2011. HexSim (version 2.3). U.S. EPA, Environmental Research Laboratory, Corvallis, OR. 

http://www.epa.gov/hexsim. 

Schumaker, N. H., A. Brookes, J. R. Dunk, B. Woodbridge, J. A. Heinrichs, J. Lawler, C. Carroll, and D. LaPlante. 2014. 

Mapping sources, sinks, and connectivity using a simulation model of northern spotted owls. Landscape ecology 29(4): 

579–592. 

https://www.researchgate.net/profile/Nathan_Schumaker/publication/263725577_Mapping_sources_sinks_and_connectivity

_using_a_simulation_model_of_northern_spotted_owls/links/54199e4a0cf25ebee988778e.pdf. 

USDI FWS. 2011. Revised recovery plan for the northern spotted owl (Strix occidentalis caurina). U.S. Fish and Wildlife 

Service, Region 1, Portland, OR. 258 pp. 

http://www.fws.gov/wafwo/pdf/NSO%20Revised%20Recovery%20Plan%202011.pdf. 

---. 2012. Modeling and analysis procedures used to identify and evaluate potential critical habitat networks for the northern 

spotted owl, submitted to the Federal Register November 21, 2012. Unpublished manuscript 

http://www.fws.gov/oregonfwo/species/data/northernspottedowl/Documents/MODEL_SUPP_Dunk2012AppC.pdf. U.S 

Fish and Wildlife Service, Region 1, Portland, OR. 48 pp. 
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Appendix U – Wild and Scenic River Suitability 

Report Summary

This appendix summarizes the studies completed on 51 rivers, and provides summarized information on 

the six river segments the BLM found to be suitable. Full text of the two Suitability Reports is available 

online at: http://www.blm.gov/or/plans/rmpswesternoregon/recreation.php. 

This appendix additionally summarizes the range of river segments recommended for inclusion in the 

National Wild and Scenic Rivers System (National System) considered among the alternatives within this 

Final EIS. The full evaluation and analysis of the study rivers across the range of alternatives and the 

Proposed RMP is included in Chapter 3 – Wild and Scenic Rivers. 

Introduction, Project Area, and Preliminary 

Determinations 

In October 1990, the US Department of the Interior, Bureau of Land Management’s (BLM) western 

Oregon districts (Coos Bay, Eugene, Klamath Falls Field Office, Medford, Roseburg, and Salem) 

completed the eligibility phase of a Wild and Scenic River (WSR) evaluations as part of the resource 

management plan revision process (USDI BLM 1995). The cumulative result of this planning effort was 

the identification of 51 eligible river segments across western Oregon. 

This current study process assessed the suitability of these 51 river segments that have been previously 

identified as eligible components of the National System. The project area for this suitability study 

includes all BLM-administered river segments within the BLM’s western Oregon district boundaries that 

have been determined to meet the eligibility criteria for Wild and Scenic Rivers. 

Why Conduct a Suitability Study and Why Now? 

Section 5(d)(1) of the WSR Act (Pub. L. 90-542; 16 U.S.C. 1271–1287) directs Federal agencies to 

consider potential Wild and Scenic Rivers in the land use planning process. To fulfill this requirement, 

whenever the BLM undertakes a land use planning effort, the BLM may choose to analyze river and 

stream segments that might be eligible or suitable for inclusion in the National System. The BLM has 

made this decision. 

Steps in the Wild and Scenic River Study Process 

A WSR study process is composed of two main components: the eligibility phase and the suitability 

phase. The BLM has completed the eligibility phase and the suitability phase for all eligible rivers within 

the planning area for the western Oregon RMP. The eligibility and suitability phases were conducted in 

accordance with BLM Manual 6400 – Wild and Scenic Rivers – Policy and Program Direction for 

Identification, Evaluation, Planning, and Management (USDI BLM 2012), The Wild and Scenic River 

Study Process Technical Report (Interagency Wild and Scenic Rivers Coordinating Council 1999), and 

with the Wild and Scenic Rivers Act. 
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Eligibility Phase 

The eligibility studies completed in 1990 determined 51 individual segments within BLM-administered 

lands in western Oregon met the eligibility criteria for inclusion into the National System. Under the 1995 

RMPs, the Records of Decision included these 51 rivers segments as eligible candidates for the National 

System. These segments are currently managed under interim protection until the BLM evaluates their 

suitability. Table U-1 identifies the 51 eligible rivers, their outstandingly remarkable values, tentative 

classifications, total miles, and acres of BLM-administered lands within study river corridors. 

Table U-1. All eligible Wild and Scenic River segments within the decision area 

Study River Name Outstandingly 

Remarkable Values

Tentative 

Classification

River 

Length 

(Miles)

BLMadministered 

Lands

(Acres)

Alsea River Recreation, Fish, Wildlife Recreational 1.1 404

Antelope Creek Fish Recreational 1.3 718

Applegate River Fish Recreational 1.3 839

Big Butte Creek Fish Recreational 2.0 706

Cheney Creek Fish Recreational 2.2 711

Clackamas River Recreation, Fish, Wildlife Recreational 0.0 30

Cow Creek Fish, Wildlife, Historical, 

Cultural Recreational 10.0 3,339

Drift Creek Fish Recreational 0.4 150

Elk Valley Creek Fish Recreational 1.6 464

Fall Creek - Eugene Recreation Recreational 0.4 87

Fall Creek - Salem Fish Recreational 2.4 670

Kilches River Recreation, Fish, Wildlife Recreational 0.0 66

Lake Creek Segment B Recreation, Fish Recreational 0.9 483

Left Fork Foots Creek Fish Recreational 0.1 131

Little Applegate River Fish Recreational 1.7 1,368

Little Luckiamute River Ecology Recreational 0.3 40

Little North Santiam 

River

Scenery, Recreation, Fish, 

Wildlife Recreational 3.5 1,205

Lobster Creek Segment B Fish Recreational 0.1 352

Luckiamute River Ecology Recreational 2.2 624

McKenzie River 

Segment B

Scenery, Recreation, Fish, 

Wildlife Recreational 1.0 56

Middle Santiam River Cultural, Ecology Recreational 0.6 193

Nehalem River Recreation Recreational 0.2 40

Nelson Creek Fish Recreational 2.6 833

Nestucca River Segment 

B*

Scenery, Recreation, Fish, 

Wildlife Recreational 0.6 212

North Fork Clackamas 

River Fish Scenic (Seg. 1)

1.4 389

Recreational (Seg. 2)

North Fork Gate Creek Fish Recreational 0.6 199

North Fork Siletz River Fish, Wildlife, Ecology Scenic 3.5 990

North Fork Trask River Recreation, Fish Recreational 3.0 778
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Study River Name Outstandingly 

Remarkable Values

Tentative 

Classification

River 

Length 

(Miles)

BLMadministered 

Lands

(Acres)

North Santiam River

Scenery, Recreation, Fish, 

Wildlife (Seg. A) Scenic (Seg. A) 1.2

2.7 376 Recreation, Fish, Wildlife 

(Seg. B) Recreational (Seg. B)

Quines Creek Fish Recreational 1.9 816

Riffle Creek Fish Recreational 2.1 762

Rogue River Recreation, Fish Recreational 1.5 754

Sams Creek Fish Recreational 7.3 497

Sandy River Scenery, Recreation, Fish, 

Cultural Recreational 0.7 1,519

Siletz River Scenery, Recreation, Fish, 

Wildlife Recreational 2.0 54

Sixes River Fish, Wildlife, Historical Recreational 1.4 281

South Fork Coos River Recreation, Fish, Wildlife Recreational 1.0 551

South Fork Coquille Fish, Cultural Recreational 0.6 152

South Fork Gate Creek Fish Recreational 1.4 108

South Fork Little Butte 

Creek Fish Recreational 0.0 452

South Fork Trask River Fish Recreational 1.4 69

South Umpqua Fish, Wildlife, Historical, 

Cultural Recreational 0.0 602

South Yamhill River† Cultural, Ecology Recreational 4.7 0

Table Rock Fork –

Molalla River Scenery, Cultural Recreational 0.4 1,480

Trask River Recreation Recreational 1.2 444

Tualatin River Cultural Recreational 18.0 326

Umpqua River

Scenery, Recreation, 

Geology, Fish, Wildlife, 

Historical, Cultural, 

Ecology

Recreational 4.2 2,403

West Fork Illinois River Scenery Scenic 1.1 1,154

Willamette River

Recreation, Fish, Wildlife,

Historical, Cultural, 

Ecology,

Recreational 0.0 83

Wilson River Recreation, Fish, Wildlife Recreational 1.3 109

Yaquina River Fish, Wildlife Recreational 3.5 270

Totals 100.9 29,339

* The BLM concluded through the suitability assessment that a joint suitability study with the U.S. Forest Service is needed to 

make a determination about the segment’s suitability. This segment will continue to receive protection until completion of the 

joint study. 

†

 The BLM discovered through a revalidation of the eligibility determinations that were made in 1992 that the South Yamhill 

River corridor does not include any BLM-administered lands. Therefore, this segment that was previously determined eligible did 

not move forward for suitability evaluation as part of this RMP revision.
1796 | Page

Suitability Phase 

The purpose of the suitability phase of the study process is to determine whether eligible segments would 

be appropriate additions to the National System by considering tradeoffs between corridor development 

and river protection. The suitability evaluation does not result in actual designation but only a 

determination of suitability, which provides a basis for determining which rivers should be recommended 

for inclusion into the National System. The BLM cannot administratively designate a segment via a 

planning decision or other agency decision into the National System, and no segment studied is 

designated or would be automatically designated as part of the National System. Rivers found not suitable 

by the BLM would be dropped from further consideration for inclusion into the National System. 

Suitability Determinations 

Of the 51 stream segments determined to be eligible in the 1990 RMP process, the BLM determined that 

6 segments meet the suitability criteria for recommendation into the National System, 43 segments were 

found not suitable during the BLM’s review, one segment (Nestucca River Segment B) was found to 

warrant further evaluation under a joint study with the U.S. Forest Service to determine suitability, and 

one segment (South Yamhill River) was removed from suitability evaluation because the corridor 

contained no BLM-administered lands. Table U-2 shows the six rivers found suitable. 

Table U-2. Eligible rivers within the decision area that the BLM identified as meeting suitability criteria 

River Segment Name District Suitable River

Tentative Classification River Miles

Little North Santiam River Salem Recreational 3.5

North Fork Siletz River Salem Scenic 3.5

Rogue River Medford Recreational 2.1

Sandy River Salem Recreational 7.3

Table Rock Fork – Molalla River Salem Recreational 4.7

West Fork Illinois River Medford Scenic 4.2

Total Miles 25.3

The following sections summarize the data collected in tables (Table U-3 through Table U-8) the 

followed by Insert map here 

Map U-1 through Map U-6) formats for each of the six suitable rivers. 

1796 | Page

Suitability Phase 

The purpose of the suitability phase of the study process is to determine whether eligible segments would 

be appropriate additions to the National System by considering tradeoffs between corridor development 

and river protection. The suitability evaluation does not result in actual designation but only a 

determination of suitability, which provides a basis for determining which rivers should be recommended 

for inclusion into the National System. The BLM cannot administratively designate a segment via a 

planning decision or other agency decision into the National System, and no segment studied is 

designated or would be automatically designated as part of the National System. Rivers found not suitable 

by the BLM would be dropped from further consideration for inclusion into the National System. 

Suitability Determinations 

Of the 51 stream segments determined to be eligible in the 1990 RMP process, the BLM determined that 

6 segments meet the suitability criteria for recommendation into the National System, 43 segments were 

found not suitable during the BLM’s review, one segment (Nestucca River Segment B) was found to 

warrant further evaluation under a joint study with the U.S. Forest Service to determine suitability, and 

one segment (South Yamhill River) was removed from suitability evaluation because the corridor 

contained no BLM-administered lands. Table U-2 shows the six rivers found suitable. 

Table U-2. Eligible rivers within the decision area that the BLM identified as meeting suitability criteria 

River Segment Name District Suitable River

Tentative Classification River Miles

Little North Santiam River Salem Recreational 3.5

North Fork Siletz River Salem Scenic 3.5

Rogue River Medford Recreational 2.1

Sandy River Salem Recreational 7.3

Table Rock Fork – Molalla River Salem Recreational 4.7

West Fork Illinois River Medford Scenic 4.2

Total Miles 25.3

The following sections summarize the data collected in tables (Table U-3 through Table U-8) the 

followed by Insert map here 

Map U-1 through Map U-6) formats for each of the six suitable rivers. 

1796 | Page

Suitability Phase 

The purpose of the suitability phase of the study process is to determine whether eligible segments would 

be appropriate additions to the National System by considering tradeoffs between corridor development 

and river protection. The suitability evaluation does not result in actual designation but only a 

determination of suitability, which provides a basis for determining which rivers should be recommended 

for inclusion into the National System. The BLM cannot administratively designate a segment via a 

planning decision or other agency decision into the National System, and no segment studied is 

designated or would be automatically designated as part of the National System. Rivers found not suitable 

by the BLM would be dropped from further consideration for inclusion into the National System. 

Suitability Determinations 

Of the 51 stream segments determined to be eligible in the 1990 RMP process, the BLM determined that 

6 segments meet the suitability criteria for recommendation into the National System, 43 segments were 

found not suitable during the BLM’s review, one segment (Nestucca River Segment B) was found to 

warrant further evaluation under a joint study with the U.S. Forest Service to determine suitability, and 

one segment (South Yamhill River) was removed from suitability evaluation because the corridor 

contained no BLM-administered lands. Table U-2 shows the six rivers found suitable. 

Table U-2. Eligible rivers within the decision area that the BLM identified as meeting suitability criteria 

River Segment Name District Suitable River

Tentative Classification River Miles

Little North Santiam River Salem Recreational 3.5

North Fork Siletz River Salem Scenic 3.5

Rogue River Medford Recreational 2.1

Sandy River Salem Recreational 7.3

Table Rock Fork – Molalla River Salem Recreational 4.7

West Fork Illinois River Medford Scenic 4.2

Total Miles 25.3

The following sections summarize the data collected in tables (Table U-3 through Table U-8) the 

followed by Insert map here 

Map U-1 through Map U-6) formats for each of the six suitable rivers. 
1797 | P a g e

Little North Santiam River 

Table U-3. Little North Santiam River study segment 

Segment Description: Willamette National Forest boundary to confluence with North Santiam 

River

Total Segment Length: 17.18 miles

Length on BLM Land: 3.5 miles

Total Segment Length: 4,748 acres

Area on BLM Land: 1,205 acres

Preliminary Classification: Recreational

Outstandingly Remarkable 

Values (ORVs): Scenery, Recreation, Fish, Wildlife

North Fork Siletz River 

Table U-4. North Fork Siletz River study segment

Segment Description: Headwaters to confluence with South Fork Siletz River

Total Segment Length: 10.60 miles

Length on BLM Land: 3.50 miles

Total Segment Length: 3,047 acres

Area on BLM Land: 990 acres

Preliminary Classification: Scenic

Outstandingly Remarkable 

Values (ORVs): Fish, Wildlife, Ecology

Rogue River 

Table U-5. Rogue River study segment

Segment Description: Lost Creek Dam downstream to the confluence of the Applegate River

Total Segment Length: 63.24 miles

Length on BLM Land: 2.10 miles

Total Segment Length: 19,798.13 acres

Area on BLM Land: 753.85 acres

Preliminary Classification: Recreational

Outstandingly Remarkable 

Values (ORVs): Recreation, Fish
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Sandy River 

Table U-6. Sandy River study segment

Segment Description: Mt. Hood National Forest boundary to the east boundary of Sec. 36, T. 

1 S., R. 4 E., W. M. near Dodge Park

Total Segment Length: 26.29 miles

Length on BLM Land: 7.27 miles

Total Segment Length: 8,043.17 acres

Area on BLM Land: 1,518.39 acres

Preliminary Classification: Recreational

Outstandingly Remarkable 

Values (ORVs): Scenery, Recreation, Fish, Cultural 

Table Rock Fork – Molalla River 

Table U-7. Table Rock Fork Molalla River study segment

Segment Description: Headwaters to confluence with Molalla River

Total Segment Length: 13.41 miles

Length on BLM Land: 4.69 miles

Total Segment Length: 4,134.58 acres

Area on BLM Land: 1,480 acres

Preliminary Classification: Recreational

Outstandingly Remarkable 

Values (ORVs): Scenery, Cultural

West Fork Illinois River 

Table U-8. West Fork Illinois River study segment 

Segment Description: Oregon/California state line downstream to 0.4 miles above the 

confluence with the East Fork Illinois River

Total Segment Length: 17.03 miles

Length on BLM Land: 4.19 miles

Total Segment Length: 5,248 acres

Area on BLM Land: 1,154 acres

Preliminary Classification: Scenic

Outstandingly Remarkable 

Values (ORVs): Scenery
1799 | Page

Insert map here 

Map U-1. Little North Santiam River study segment 

Insert map here 

Map U-1. Little North Santiam River study segment 
1800 | Page

Insert map here 

Map U-2. North Fork Siletz River study segment 

Insert map here 

Map U-2. North Fork Siletz River study segment 
1801 | Page

Insert map here 

Map U-3. Rogue River study segment 

Insert map here 

Map U-3. Rogue River study segment 
1802 | Page

Insert map here 

Map U-4. Sandy River study segment 

Insert map here 

Map U-4. Sandy River study segment 
1803 | Page

Insert map here 

Map U-5. Table Rock Fork – Molalla River study segment 

Insert map here 

Map U-5. Table Rock Fork – Molalla River study segment 
1804 | Page

Insert map here 

Map U-6. West Fork Illinois River study segment 

Insert map here 

Map U-6. West Fork Illinois River study segment 
1805 | P a g e

Suitability Reports 

The Wild and Scenic River Suitability Reports on the western Oregon BLM’s eligible river segments 

were published in May 2015. For additional detailed information for each eligible river segment, 

reference the Wild and Scenic River Suitability Reports that have been published as a separate document 

to supplement the RMPs for Western Oregon planning process. Based on the number of eligible rivers 

that the BLM studied, suitability reports have been broken out into two regions. The Northwest WSR 

Suitability Report covers eligible rivers within the Coos Bay, Eugene, and Salem Districts. The Southwest 

WSR report covers eligible rivers in the Medford and Roseburg Districts. These reports are available on 

the RMPs for Western Oregon website at: 

http://www.blm.gov/or/plans/rmpswesternoregon/recreation.php. 

Land Use Plan Alternatives 

Chapter 3 of the Proposed RMP/Final EIS describes the effects that management actions associated with 

each alternative would have on the outstandingly remarkable values (ORVs), water quality, free-flowing 

characteristics, and tentative classification of eligible segments. The effect of the alternatives on eligible 

river segments is assessed by considering the extent to which each alternative protects the ORVs and 

tentative classification. The analysis conducted for this planning effort for water quality determined that 

no alternatives would result in changes to water quality within the decision area (see the Hydrology 

section in Chapter 3). As that analysis has determined that there would be no changes under the 

alternatives, the indicator of water quality has been dropped from the discussion for affects to eligible 

rivers. No actions included in any of the alternatives would change current free-flowing values of any of 

the 51 eligible segments. As there is no action upon which to measure differences for this indicator, it was 

dropped from consideration for affects to eligible rivers, as the BLM assumes there would be no change 

to free-flowing characteristics under any of the alternatives or the Proposed RMP. 

The BLM considers tentative classifications and ORVs protected for a given eligible segment when that 

segment is recommended for inclusion into the National System under an alternative. The BLM considers 

these factors are left unprotected when a particular segment is not recommended for inclusion into the 

National System. Where an alternative does not protect a particular segment, the analysis considers the 

potential effect of other management on the two factors. The analysis contained in this EIS is summarized 

below. 

No Action Alternative 

Under the No Action alternative, the BLM would continue to manage the 51 segments identified as 

eligible during the 1995 RMP process to protect their ORVs, free-flowing condition, water quality, and 

tentative classification as wild, scenic, or recreational until suitability is determined on the 100.9 river 

miles and 29,339 acres within the study river corridors. Under this protective management, the BLM 

would not approve any action that would adversely affect the 51 segments’ ORVs and the BLM assumes 

that these characteristics would persist. 

Alternative A 

Under Alternative A, the BLM would determine that all 51 eligible river segments in the planning area 

are not suitable for inclusion into the National System. The BLM would no longer manage these 100.9 

river miles and 29,339 acres of land to protect their ORVs and tentative classification. While management 

under the guidance of WSR would not occur, the BLM assumed that this change in management would 

only negatively affect miles and acres of eligible rivers that occur in land use allocations or special 
1806 | P a g e

management areas where management direction would be in conflict with retention of the ORVs and 

tentative classification. 

Alternatives B and C/Proposed RMP

Under Alternatives B and C, and the Proposed RMP, the BLM would recommend six segments for 

potential inclusion into the National System (Table U-2). The BLM would continue to manage these six 

segments, totaling 25.3 river miles and 7,102 acres of land, to ensure the continued protection of their 

ORVs, free-flowing condition, water quality, and tentative classification until Congress makes a 

determination whether to designate the segment as part of the National System. The BLM would not 

recommend 43 segments for inclusion into the National System. While management under the guidance 

of WSR would not occur, the BLM assumed that this change in management would only negatively affect 

miles and acres of eligible rivers that occur in land use allocations or special management areas where 

management direction would be in conflict with retention of the ORVs and tentative classification. The 

Nestucca River segment B would continue to receive protection until completion of a joint suitability 

study with the U.S. Forest Service to evaluate suitability is completed. 

Alternative D 

Under Alternative D, the BLM would recommend all 51 eligible segments for inclusion into the National 

System. The BLM would continue managing the segments to protect the ORVs, free-flowing condition, 

water quality, and tentative classification. Implementation of Alternative D would result in effects similar 

to or the same as those described under the No Action alternative, as the BLM would provide protection 

to these river segments until Congress makes a determination whether to designate the segments as part of 

the National System (Appendix B), and the BLM assumes that these characteristics would persist. 
1807 | P a g e

Appendix V – Monitoring Plan for the 

Proposed RMPs 

Monitoring is an essential component of an RMP. Monitoring provides information to determine whether 

the BLM is following the RMP management direction (implementation monitoring) and to verify if the 

implementation of the RMP is achieving plan-level desired results (effectiveness monitoring). 

The monitoring plan for the Proposed RMP focuses specifically on monitoring the implementation and 

effectiveness of the RMP and is not intended as an all-encompassing strategy that addresses all ongoing 

monitoring and research efforts. This monitoring plan does not attempt to address research-based 

questions. There are many ongoing research-based efforts in which the BLM participates that address 

evaluating whether the RMP is based on correct assumptions (validation monitoring). 

The use of this monitoring plan by all BLM offices in the decision area would provide a basis for 

consistent and coordinated monitoring, and allow district information to be compiled and considered at 

the scale of the entire decision area. The BLM would evaluate the monitoring questions at each 

monitoring interval to ascertain if the questions, reporting, methods, sample size, or intervals need to be 

changed. The BLM would make such changes to the monitoring plan through plan maintenance. 

Effectiveness Monitoring 

The BLM would continue to rely on the existing interagency effectiveness monitoring modules to address 

key questions about whether the RMP is effectively meeting its objectives. The existing interagency 

effectiveness modules are aquatic and riparian ecosystems, late-successional and old growth, marbled 

murrelet, northern spotted owl, socioeconomic, and tribal. Although there are differences in the objectives 

in the 1995 RMP and this Proposed RMP, the key questions that the existing interagency effectiveness 

modules are designed to answer are still relevant to the objectives of the Proposed RMP, as detailed 

below. These key questions address fundamental conditions and processes that underlie the objectives of 

both the 1995 RMP and this Proposed RMP. As such, answering these key questions through 

effectiveness monitoring will continue to provide a basis for the BLM to determine whether the RMP is 

effectively meeting its objectives. 

The aquatic and riparian ecosystems effectiveness monitoring program assesses status and trends in 

watershed condition to answer the basic question: 

 Is implementation of the RMP maintaining and restoring aquatic and riparian ecosystems to 

desired conditions on Federal lands in the planning area? 

This monitoring effort determines riparian watershed condition status for every 6th field watershed (with 

> 5 percent Federal ownership along the stream length) based on upslope and riparian data derived from 

GIS layers and satellite imagery. In-channel attributes are also measured using a statistically valid survey 

design to assess aquatic watershed condition. Changes in riparian and aquatic conditions provide 

information for tracking status and trend based on management activities, natural disturbance, and 

wildfire. More information on the aquatic and riparian ecosystems effectiveness monitoring is contained 

in the 20-year Monitoring Report (Miller et al. 2015), which is incorporated here by reference. 

The late-successional and old growth (LSOG) ecosystems effectiveness monitoring program characterizes 

the status and trend of older forests to answer the basic question: 

 Is implementation of the RMP maintaining and restoring late-successional and old growth forest 

ecosystems to desired conditions on Federal lands in the planning area? 
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This monitoring effort determines the current status of forest vegetation from classification of satellite 

imagery and analysis of inventory and other available data. Remote sensing change detection and trend 

analysis provide information for tracking losses and gains in forest conditions from management 

activities, natural succession, and wildfire. More information on the late-successional and old growth 

ecosystems effectiveness monitoring is contained in the 20-year Monitoring Report (Davis et al. in press), 

which is incorporated here by reference. 

The marbled murrelet effectiveness monitoring program assesses status and trends in marbled murrelet 

populations and nesting habitat to answer the basic questions: 

 Are the marbled murrelet populations associated with the planning area stable, increasing, or 

decreasing? 

 Is implementation of the RMP maintaining and restoring marbled murrelet nesting habitat? 

This monitoring effort determines marbled murrelet population size and trends by sampling of 

populations in near-shore waters, using standardized and consistent methodology. Trends in the amount, 

quality, and distribution of nesting habitat in the planning area are evaluated periodically using a model 

approach that applies current vegetation maps along with other data derived from GIS layers and other 

available sources. More information on the marbled murrelet effectiveness monitoring is contained in the 

20-year Monitoring Report (Falxa et al. 2015), which is incorporated here by reference. 

The northern spotted owl effectiveness monitoring program assesses status and trends in northern spotted 

owl populations and habitat to answer the basic questions: 

 Will implementing the RMP reverse the downward trend in spotted owl populations? 

 Is implementation of the RMP maintaining and restoring owl habitat necessary to support viable 

owl populations? 

Population monitoring documents survival, reproductive success, and annual rate of population change in 

northern spotted owl demographic study areas. Maps depicting habitat suitability are produced using 

habitat models applied to current vegetation maps developed by the LSOG monitoring program along 

with other available data sources. More information on the northern spotted owl effectiveness monitoring 

is contained in the draft 20-year Monitoring Report (Davis et al. 2015), which is incorporated here by 

reference. 

The socio-economic effectiveness monitoring program assesses social and economic impacts of Federal 

forest management, framed as two questions: 

 Are predictable levels of timber and non-timber resources available and being produced? 

 Are communities and economies experiencing positive or negative changes that may be 

associated with Federal forest management? 

The key objectives of the socio-economic effectiveness monitoring program are to identify communities 

experiencing significant positive or negative conditions or trends, as well as those that are not, and to 

improve understanding of the relationship between Federal forest management and social and economic 

change. To address the objectives above, the monitoring program analyzes trends in data for timber and 

non-timber resources. The monitoring program considers social and economic indicators derived from 

U.S. census data, analysis of quantitative data from agency databases, along with other available data. 

More information on the socioeconomic effectiveness monitoring is contained in the 20-year Monitoring 

Report (Grinspoon et al. 2015), which is incorporated here by reference. 

The tribal effectiveness monitoring program addresses conditions, trends, and access to resources 

protected by treaty or of interest to American Indian tribes, the condition of and access to religious and 

cultural heritage sites, and the quality of the government-to-government relationship. The basic 

effectiveness monitoring questions are: 

 How well and to what degree is government-to-government consultation being conducted under 

the RMP? 
1809 | P a g e

 Have the goals and objectives of the consultation been achieved? 

 Is the consultation occurring because of effects on resources of tribal interest on Federal lands or 

trust resources on tribal lands? 

Effectiveness monitoring data are collected during interviews using a standardized questionnaire 

developed by Federal agency officials. All federally recognized Tribes with Tribal lands and/or territories 

within the RMP area will be invited to participate in interviews. More information on the tribal 

effectiveness monitoring is contained in the 20-year Monitoring Report (Vinyeta and Lynn 2015), which 

is incorporated here by reference. 

The interagency effectiveness monitoring modules would continue to report every 5 years. The BLM 

would continue to use these reports to state the findings and conclusions made through monitoring, and to

serve as a report to managers and the public. Effectiveness monitoring reports would also include analysis 

of whether the BLM is achieving desired conditions based on effectiveness monitoring questions and, 

where possible, inform adaptive management. 

In addition to the six interagency effectiveness monitoring modules, the BLM would conduct 

effectiveness monitoring of hazardous fuels treatments through the Fuels Treatment Effectiveness 

Monitoring (FTEM) system. The FTEM is a centralized interagency web-based hub for recording on-theground documentation describing the effect of hazardous fuels reduction treatments on the wildland fire 

environment, framed around two key questions: 

 Did the fire behavior change as a result of the treatment (as planned in the treatment objectives)? 

 Did the treatment contribute to control of the fire? 

The FTEM system is intended to identify the extent which hazardous fuels treatments are affecting the 

wildland fire environment. Field personnel from each field office will fill out an online form for every 

hazardous fuels reduction treatment intersected by a wildfire, within 90 days of the wildfire burning in the 

treated area. 

The BLM will conduct monitoring of employment effects on low-income populations in Coos and Curry 

Counties.56 The Proposed RMP/Final EIS identified that the RMP will have disproportionately negative 

employment effects on low-income populations in Coos and Curry counties. Although the BLM will 

monitor the level and type of timber harvest, payments to counties, and changes in resource conditions, 

these measurements will not tell the BLM how low-income populations are being affected. The BLM will 

conduct monitoring, that will identify and track appropriate indicators of social and economic conditions. 

The BLM will conduct primary research, such as focus groups or interviews with community residents, 

leaders, and others, to supplement and interpret the secondary data. The results of the monitoring will 

allow the BLM and its partners to identify environmental justice impacts that have not been mitigated 

through the RMP as implemented or by other means, pointing the way toward potential mitigation 

actions. 

Implementation Monitoring 

The implementation monitoring plan for the Proposed RMP would assess the level of management 

activity and would examine if the BLM is implementing actions in accordance with management 

direction of the RMP. 

 

56 This monitoring component is not effectiveness monitoring in the same sense as the other components described 

in this section, in that it would not be directly evaluating whether the RMP is effectively meeting its objectives. 

Instead, this monitoring would evaluate whether the employment effects in Coos and Curry Counties identified in 

the Proposed RMP/Final EIS are occurring as analyzed and would identify any potential mitigation measures that 

would be revealed by the monitoring of effects, such as changes to the intensity or extent of management actions 

under specific resource programs. 
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The BLM would employ sampling or evaluation of a subset of implementation actions. The BLM has 

designed the monitoring plan for the Proposed RMP to avoid prohibitive costs and effectively answer 

monitoring questions and reporting levels of activities. It is not necessary or desirable for the BLM to 

monitor every implementation action of an RMP. The BLM would select projects to be monitored based 

on those that would yield a greater amount of information or be more beneficial. For example, a random 

sample may result in monitoring of a relatively small straightforward project that would yield limited 

information, whereas a more sophisticated or complex project might be available for monitoring that 

would yield more information or be more effective. As much as possible, project implementation 

monitoring would be integrated among resources and programs. This integration saves time and costs, and 

helps build common information and understanding between various resources and programs. 

The BLM would conduct sampling at the level of the entire administrative unit to which the resource 

management applies (e.g., Medford District or Klamath Falls Field Office). 

The BLM would report implementation monitoring results annually in a monitoring report, which may be 

combined with other documents, such as an annual program summary. The monitoring report would 

report, track, and assess the progress of plan implementation, state the findings and conclusions made 

through monitoring, and serve as a report to managers and the public. Monitoring reports would also 

include any discussions and analysis of non-compliance and recommendations for corrective action. 

Some management direction in the Proposed RMP is not measurable or quantifiable, or does not have a 

standard or threshold of acceptability, and therefore would not lend itself to being addressed through 

monitoring questions that are almost always dependent on a quantifiable basis of measurement. The level 

of activity for certain management direction that does not have standards or thresholds of acceptability 

would be monitored in the form of a program reporting item. The BLM will use the information in the 

program reporting items, to assess the level of management activity and examine if the BLM is 

implementing actions consistent with the analytical assumptions in the Proposed RMP/Final EIS. 

In some cases, where monitoring indicates very high compliance with the plan, the BLM would 

subsequently adjust the frequency or interval of monitoring for cost and time efficiency. 

Monitoring of certain questions would not take place in the early years of implementation, because the 

BLM would not yet have completed projects and, therefore, would not be ready for monitoring. Although 

incomplete projects may be informally examined by managers to assess progress towards implementing 

management actions and achieving objectives, the evaluation of incomplete projects would not be part of 

formal plan monitoring. Not all programs or resources have monitoring questions. 

Monitoring Questions 

Late-Successional Reserve 

M1. Monitoring Question: Have the number of snags been created in the appropriate size classes as 

described in the management direction (Appendix B, Table B-3)?

Monitoring Requirement: Evaluate at least one completed timber sale in a Late-Successional Reserve per 

field office. Report the number of snags created > 20” DBH and > 10” DBH per project.

Monitoring Interval: Annual; change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 
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M2. Monitoring Question: Has the amount of down woody material described in the management 

direction been retained when implementing fuels or prescribed fire treatments (Appendix B, Table B-4)?

Monitoring Requirement: Evaluate at least one fuels or prescribed fire treatment in the Late-Successional 

Reserve per field office. Report the percent cover of down woody material and the method used to 

measure percent cover. 

Monitoring Interval: Annual; change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Late-Successional Reserve – Dry 

M3. Monitoring Question: Have the Medford District and the South River Field Office of the 

Roseburg District applied selection harvest or commercial thinning to meet decadal acreage targets set 

forth in the RMP? Note that acreage in untreated skips counts towards total treatment acreage for this 

calculation. 

Monitoring Requirement: Report acres of thinning and selection harvest sold and the cumulative total 

since approval of the plan. Also, report as an annual average and compare with the annual average 

required to meet decadal acreage targets. 

Monitoring Interval: Annual. 

Riparian Reserve 

Note: Monitoring questions M4–M9 do not apply to Eastside Management Area – Riparian Reserve. 

M4. Monitoring Question: Is the width of the Riparian Reserve established adjacent to regeneration 

harvests in the Moderate Intensity Timber Area or Low Intensity Timber Area in accordance with the 

RMP? 

Monitoring Requirement: Evaluate all streams within at least one completed timber sale per field office. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M5. Monitoring Question: When thinning treatments are applied in the Riparian Reserve along fishbearing streams and perennial streams, is a minimum of 30 percent canopy closure and 60 trees per acre 

retained? Are thinning treatments excluded from the inner zone of the Riparian Reserve along perennial 

and intermittent fish-bearing streams? 

Monitoring Requirement: Evaluate all fish-bearing streams and perennial streams treated within at least 

one completed thinning timber sale per field office. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 
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M6. Monitoring Question: When thinning treatments are applied in the Riparian Reserve along 

intermittent non-fish-bearing streams, is a minimum of 30 percent canopy closure and 60 trees per acre 

retained? Are thinning treatments excluded within inner zone of the Riparian Reserve along intermittent 

non-fish bearing streams? 

Monitoring Requirement: Evaluate 0.25 mile of streams within thinning projects completed within the 

past year per field office. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M7. Monitoring Question: Were Best Management Practices that were identified as applicable (as 

indicated through NEPA decision record or contract stipulations) applied during project implementation? 

Monitoring Requirement: Evaluate at least one project with identified Best Management Practices per 

field office. Projects from any land use allocation may be selected for evaluation. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M8. Monitoring Question: Have the number of snags been created in the appropriate size classes as 

described in the management direction (Appendix B, Table B-3)?

Monitoring Requirement: Evaluate at least one completed timber sale that includes Riparian Reserve per 

field office. Report the number of snags created > 20” DBH and > 10” DBH per project.

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M9. Monitoring Question: Has the amount of down woody material described in the management 

direction been retained when implementing fuels or prescribed fire treatments (Appendix B, Table B-4)?

Monitoring Requirement: Evaluate at least one fuels or prescribed fire treatment in the Riparian Reserve 

per field office. Report the percent cover of down woody material and the method used to measure 

percent cover. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Note: Monitoring question M10 applies only to Eastside Management Area – Riparian Reserve. 

M10. Monitoring Question: Has the amount of streams in proper functioning condition been 

maintained or increased? (Eastside Management Area – Riparian Reserve only) 
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Monitoring Requirement and Monitoring Interval: Monitoring and reporting would be through the use of 

the statewide report, Table 1 from USDI TR-1737-9 1993 (or similar), of lotic and lentic waterbodies in 

properly functioning; functioning at risk with trend up, down or not apparent; and not properly 

functioning. (Note: Table 1 is available online, with instructions, at 

http://www.blm.gov/nstc/library/pdf/Final%20TR%201737-9.pdf and is also provided below (Table V-1

for reference purposes.) 

State: ___________________ 

Table V-1. Example of Table 1–Functioning Condition Status from USDI TR-1737-9 (1993) 

Habitat Types

Proper 

Functioning 

Condition

Functional – At Risk Nonfunctional Trend Unknown Totals

Up

Trend Not 

Apparent

Trend 

Down

Riverine Miles

(Lotic)

Non-riverine Acres

(Lentic)*

* Report only acres associated with lentic riparian-wetland areas. Do not include acres associated with lotic riparian-wetland 

areas. 

Eastside Management Area 

M11. Monitoring Question: Are snags and coarse woody debris retained in accordance with RMP 

requirements? 

Monitoring Requirement: Evaluate at least one completed timber sale. 

Monitoring Interval: Annual, or each year in which there is a completed timber sale. 

M12. Monitoring Question: Is a stand average relative density of 15–55 maintained after commercial 

harvest conducted for the removal and sale of timber and biomass? 

Monitoring Requirement: Evaluate at least one completed timber sale. 

Monitoring Interval: Annual, or each year in which there is a completed timber sale. 

Harvest Land Base 

M13. Monitoring Question: Has the allowable sale quantity been offered for sale within the variation 

provided for in the plan? 

Monitoring Requirement: Report annual sale quantity offered for sale by sustained-yield unit and the 

cumulative total since approval of the plan. Also report as volume offered by harvest type (selection 

harvest, commercial thinning, regeneration harvest, and timber salvage) by sustained-yield unit. 

Monitoring Interval: Annual. 
1814 | P a g e

M14. Monitoring Question: Have the number of snags been created in the appropriate size classes as 

described in the management direction (Appendix B, Table B-2)? 

Monitoring Requirement: Evaluate at least one completed timber sale per field office. Report the number 

of snags created > 20” DBH and > 10” DBH per project.

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M15. Monitoring Question: Are regeneration harvest areas, salvage harvest areas, and group selection 

openings being reforested in accordance with the RMP? 

Monitoring Requirement: Evaluate at least one completed timber sale per field office. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Harvest Land Base – Uneven-Aged Timber Area 

M16. Monitoring Question: Is a stand average relative density of 20–45 percent maintained after 

commercial harvest? 

Monitoring Requirement: Evaluate at least one completed timber sale per field office. Report the stand 

average relative density per stand treated within each timber sale evaluated. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Harvest Land Base – Moderate Intensity Timber Area and Low 

Intensity Timber Area 

M17. Monitoring Question: Is a stand average relative density of 25–45 percent maintained after 

commercial thinning? 

Monitoring Requirement: Evaluate at least one completed timber sale per field office. Report the stand 

average relative density per stand treated within each timber sale evaluated. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M18. Monitoring Question: Are trees retained after regeneration harvest in accordance with targets set 

forth in the RMP? 

Monitoring Requirement: Evaluate at least one completed timber sale per field office. 
1815 | P a g e

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Air Quality 

M19. Monitoring Question: Have smoke intrusions occurred in areas designated as Class I for air 

quality and non-attainment occurred as a result of BLM prescribed fire? 

Monitoring Requirement: Report intrusions through Oregon Department of Forestry as required under the 

Oregon Smoke Management Plan. 

Monitoring Interval: Annual. 

Areas of Critical Environmental Concern 

M20. Monitoring Question: Are important and relevant values being maintained or restored? 

Monitoring Requirement: Evaluate 20 percent of the Areas of Critical Environmental Concern. 

Monitoring Interval: Rotate the monitoring of Areas of Critical Environmental Concern, so that all of the 

areas would be monitored over a 5-year period. 

Rare Plants and Fungi 

M21. Monitoring Question: Is management of plant species that are listed under the Endangered 

Species Act consistent with recovery plans and designated critical habitat? 

Monitoring Requirement: Evaluate at least two completed projects per field office that ‘may affect’ ESAlisted species. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M22. Monitoring Question: Have protection measures maintained populations of BLM special status 

plant and fungi species? 

Monitoring Requirement: Evaluate at least two completed projects per field office in which the BLM 

implemented protection measures for BLM Special Status plant and fungi species. 

Monitoring Interval: Annual. 

Cultural and Paleontological Resources Including American Indian 

Traditional Uses 

M23. Monitoring Question: Were previously unknown sites discovered within project areas after the 

commencement of ground-disturbing activities? If yes, how many? 
1816 | P a g e

Monitoring Requirement: Evaluate at least 20 percent of management activities per field office that 

involve ground disturbance that have been completed within the past year. 

Monitoring Interval: Annual 

M24. Monitoring Question: Have ground-disturbing actions avoided previously recorded sites that are 

listed (or eligible for listing) on the National Register of Historic Places? 

Monitoring Requirement: Evaluate 100 percent of recorded listed or eligible sites that lie within the 

boundaries of a ground-disturbing project after the project is completed. Report number of sites present 

and number of sites avoided. 

Monitoring Interval: Annually when listed or eligible sites are present and avoidance prescribed. 

M25. Monitoring Question: Are mitigation measures employed on sites that are listed (or eligible for 

listing) on the National Register of Historic Places prior to disturbance (when disturbance cannot be 

practically avoided) through practices such as data recovery, including excavation, relocation, or 

documentation? 

Monitoring Requirement: Evaluate 100 percent of sites that are listed (or eligible for listing) on the 

National Register of Historic Places that were at risk of loss from ground disturbing management 

activities that have been completed within the past year. Report number of sites at risk and number of 

sites that were mitigated and with what methods. 

Monitoring Interval: Annual. 

M26: Monitoring Question: Are cultural and paleontological resources that are threatened by natural 

processes or human activity (other than Federal undertakings) stabilized and protected or excavated and 

the data recovered where warranted by the scientific importance of the site? 

Monitoring Requirement: Evaluate 100 percent of cultural and paleontological resources threatened or 

impacted by events that have happened within the past year. Report number of sites threatened or 

impacted and report number of sites stabilized or protected and with what measures. 

Monitoring Interval: Annual. 

Energy and Minerals 

M27. Monitoring Question: Has the level of opportunities for the exploration and development of 

locatable, leasable, and salable mineral resources been maintained? 

Monitoring Requirement: Identify new closures and withdrawals. 

Monitoring Interval: Five years. 
1817 | P a g e

Fire and Fuels Management 

M28. Monitoring Question: Were fuels managed to reduce wildfire hazard, risk to communities, and 

negative impacts to ecosystems, and highly valued resources? 

Monitoring Requirement: Summarize the primary and secondary reason for treatments and the primary 

and secondary initiative for all treatments, based on spatial inventory treatment data. 

Monitoring Interval: Annual. 

M29. Monitoring Question: Have fuels treatments created fuel beds and fuel breaks intended to 

reduce potential fire behavior, reduce potential wildfire severity, or improve fire management 

opportunities? 

Monitoring Requirement: Evaluate at least one treatment per field office. 

Monitoring Interval: Annual. 

M30. Monitoring Question: Did risk-based wildfire management decisions implemented in response 

to natural ignitions include an examination of the full range of fire management options? 

Monitoring Requirement: Evaluate 100 percent of Wildland Fire Decision Support System decisions 

completed. 

Monitoring Interval: Annual. 

M31. Monitoring Question: Did land management treatments intersected by wildfires change fire 

behavior, minimize negative wildfire effects and damage to resource values, or positively contribute 

toward fire management opportunities? 

Monitoring Requirement: Complete a treatment effectiveness assessment of 100 percent of treatments 

intersected by wildfire. 

Monitoring Interval: Annual. 

Hazardous Materials 

M32. Monitoring Question: Has the response to hazardous material incidents included cleanup, proper 

notifications, criminal investigations, and site assessments as applicable? 

Monitoring Requirement: Evaluate 100 percent of hazardous material incidents. 

Monitoring Interval: Annual. 

M33. Monitoring Question: Are hazardous materials stored, treated, and disposed of in accordance 

with applicable laws and regulations? 
1818 | P a g e

Monitoring Requirement: Evaluate 100 percent of district-stored, treated, and disposed hazardous 

materials. 

Monitoring Interval: Annual. 

Invasive Species – Port-Orford-cedar Root Disease (Phytophthora 

lateralis) 

M34. Monitoring Question: Are General Direction requirements from the Record of Decision and 

Resource Management Plan Amendment for Management of Port-Orford-cedar in Southwest Oregon, 

Coos Bay, Medford, and Roseburg Districts (USDI BLM 2004) for maintaining and reducing the risk of 

Phytophthora lateralis infections being implemented? 

Monitoring Requirement: Describe the general activities accomplished for maintaining and reducing the 

risk of Phytophthora lateralis infections, which may include modifying Port-Orford-cedar bough 

collection permits to include prevention practices, applying adaptive management, community outreach, 

and eradication activities. 

Monitoring Interval: Annual. 

M35. Monitoring Question: Are project-specific management actions applied as required in the 

Record of Decision and Resource Management Plan Amendment for Management of Port-Orford-cedar 

in Southwest Oregon, Coos Bay, Medford, and Roseburg Districts (USDI BLM 2004) when a need is 

indicated by using the Port-Orford-cedar Risk Key on page 32? 

Monitoring Requirement: Describe where Port-Orford-cedar root disease management actions have been 

incorporated into project-specific implementation monitoring programs. Port-Orford-cedar root disease 

management actions could include seasonal restrictions, using uninfested water, unit scheduling, 

designating access routes, and public education through signage in site-specific project design and 

implementation. 

Monitoring Interval: Annual. 

Lands, Realty, Access, and Transportation 

M36. Monitoring Question: Have the acres of O&C lands of all classifications and the acres of O&C 

and public domain lands that are available for harvesting been reduced through disposal, exchange, or 

purchase? 

Monitoring Requirement: Review O&C lands records through the Oregon State Office. Evaluate total net 

change in land tenure of O&C lands in the decision area. Evaluate changes at 10-year intervals keyed 

from 1998, the date of the legislation that provides for no net loss of O&C lands. 

Monitoring Interval: Three years. 
1819 | P a g e

Livestock Grazing 

Note: Monitoring questions M37 through M39 apply only to the Medford District and the Klamath Falls 

Field Office of the Lakeview District. 

M37. Monitoring Question: Has the condition of public rangelands been maintained or improved 

compared to the baseline year of 2015? 

Monitoring Requirement and Monitoring Interval: In ‘I’ category allotments, examine trend plots every 

five years, determine condition every 10 years, and record utilization data every other year. In ‘M’

allotments, determine trend and condition every ten years and utilization every five years. Monitoring in 

‘C’ allotments is limited to periodic inventories and observations to measure long-term resource condition 

changes.57

M38. Monitoring Question: Are areas disturbed by natural and human-induced events (including 

wildland fire, prescribed burns, timber-management treatments, and juniper reduction treatments) rested 

from livestock grazing? Is livestock grazing resumed only after a determination that soil and vegetation 

has recovered sufficient to support livestock grazing (except where livestock grazing would either not 

impede site recovery, or where livestock grazing could be used as a tool to aid in achieving recovery 

objectives)? 

Monitoring Requirement: Evaluate 10 percent of disturbance events. 

Monitoring Interval: Annual; change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M39. Monitoring Question: For streams with ESA-listed or anadromous fish species, is livestock 

restricted from riparian areas during spawning, incubation, and until 30 days following the emergence of 

juveniles from spawning beds? 

Monitoring Requirement: Evaluate 20 percent of streams with ESA-listed or anadromous fish species 

within active grazing allotments. 

Monitoring Interval: Annual; change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Recreation 

M40. Monitoring Question: Are Special Recreation Management Areas managed in accordance with 

their planning frameworks? 

Monitoring Requirement: Evaluate 20 percent of the Special Recreation Management Areas. 

Monitoring Interval: Annual. The monitoring of Special Recreation Management Areas would be rotated 

so that over a five-year period 100 percent of the areas would be monitored. 

 

57 Grazing allotments are assigned to one of three management categories: (I) Improve (M) Maintain, and (C) 

Custodial. 
1820 | P a g e

Soils 

M41. Monitoring Question: Have land management actions created more than a 20 percent level of 

detrimental soil conditions at the unit treatment scale? 

Monitoring Requirements: Evaluate 10 percent of each treatment unit per Field Office that has the 

potential to affect the existing soil resource condition. Use Forest Soil Disturbance Monitoring Protocol 

(Page-Dumroese et al. 2009a, 2009b) to determine level of compaction and disturbance, amount of 

organic matter removed, and extent and intensity of prescribed burning or fuel reduction treatment areas. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Visual Resource Management 

M42. Monitoring Question: Is the level of change in character for the areas designated to be managed 

as VRM Class I, II, and III consistent with RMP requirements? 

Monitoring Requirements: Evaluate 20 percent of activities that have the potential to affect the existing 

character in VRM Class I, II, and III. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Wild Horses 

M43. Monitoring Question: Is the population of wild horses in the Pokegama Herd Management Area 

maintained at the appropriate management level of 30–50 head? 

Monitoring Requirement: Report on population surveys or censuses. 

Monitoring Interval: Five years. 

M44. Monitoring Question: Are horses from other herd areas periodically introduced to the Pokegama 

herd to maintain the genetic diversity of the herd? 

Monitoring Requirement: Report all introductions. 

Monitoring Interval: Five years. 

M45. Monitoring Question: Are water developments maintained or established to provide season-long 

water for wild horses within the herd management area? 

Monitoring Requirement: Evaluate 100 percent of water developments. 
1821 | P a g e

Monitoring Interval: Annual; change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Wilderness Characteristics 

M46. Monitoring Question: Are wilderness characteristics maintained in accordance with RMP 

requirements? 

Monitoring Requirements: Report all management activities that would adversely affect wilderness 

characteristics in Wilderness Study Areas and Wilderness Areas and District-Designated Reserve – Lands 

Managed for their Wilderness Characteristics. Monitor for amount of degradation or loss of inventoried 

wilderness characteristics resulting from undue or unnecessary degradation as a result of human or natural 

causes. 

Monitoring Interval: Five years. 

Wild and Scenic Rivers 

M47. Monitoring Question: Are the outstandingly remarkable values of designated Wild and Scenic 

river corridors (including those classified as Wild, Scenic, or Recreational) being maintained? 

Monitoring Requirements: Evaluate 100 percent of BLM-authorized activities that have the potential to 

affect the outstandingly remarkable values of Wild and Scenic River corridors. 

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M48. Monitoring Question: Are the outstandingly remarkable values of the eligible Nestucca River 

Segment B and suitable Little North Santiam River, North Fork Siletz River, Rogue River, Sandy River, 

Table Rock Fork – Molalla River, and West Fork Illinois River Wild and Scenic river corridors (including 

those classified as Wild, Scenic, or Recreational) being maintained? 

Monitoring Requirements: Evaluate 100 percent of BLM-authorized activities that have the potential to 

affect the outstandingly remarkable values of these Wild and Scenic River corridors. 

Monitoring Interval: Annual; change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Wildlife 

M49. Monitoring Question: Is management of species that are listed under the Endangered Species 

Act consistent with recovery plans and designated critical habitat? 

Monitoring Requirement: Evaluate at least two completed projects per field office that ‘may affect’ ESAlisted species. 
1822 | P a g e

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

M50. Monitoring Question: Have BLM actions in the Harvest Land Base caused the abandonment 

(i.e., caused a site to not be occupied during the year following the BLM action) of more than 10 percent 

of northern spotted owl occupied sites in the Harvest Land Base during the first decade of RMP 

implementation, more than an additional 15 percent of northern spotted owl occupied sites in the Harvest 

Land Base during the second decade of RMP implementation, and more than an additional 20 percent of 

northern spotted owl occupied sites in the Harvest Land Base per decade beginning with the third decade 

of RMP implementation? 

Monitoring Requirements: The BLM State Office wildlife program lead will coordinate this monitoring 

requirement. BLM wildlife biologists in each district will estimate the number of sites in the Harvest 

Land Base occupied by a northern spotted owl territorial pair or resident single. Biologists will base their 

estimates on the most recent year of protocol surveys supplemented by the previous four years of protocol 

surveys and, if no protocol surveys of a site has been completed during the previous five years, by the 

most recent ten years of protocol surveys. BLM wildlife biologists in each district will examine all actions 

in the Harvest Land Base implemented under the RMP and estimate the number of northern spotted owl 

occupied sites in the Harvest Land Base that have been abandoned by northern spotted owls due to BLM 

actions in the Harvest Land Base. Although the behaviors of individual northern spotted owl pairs and 

singles vary, in general, the following are evidence that BLM actions caused site abandonment:

 The BLM modified or removed habitat in the nest patch, which commonly extends 300 meters 

from the occupied site. 

 Following a BLM action in the 500-acre core use area surrounding the occupied site, less than 

250 acres of the core use area supported nesting-roosting habitat, when all land ownerships are 

considered, regardless of the amount of nesting-roosting habitat in this area before the BLM 

action. 

 Following a BLM action in the median provincial home range areas surrounding the occupied 

site, less than 40 percent of the home range area supported nesting-roosting habitat, when all land 

ownerships are considered, regardless of the amount of nesting-roosting habitat in this area before 

the BLM action. 

If, following a BLM action, survey indicates that a site is occupied by a territorial pair or resident single, 

the biologist will determine that the BLM action did not cause site abandonment. 

The State Office wildlife program leader will collect results from all BLM districts, make the plan-wide 

monitoring calculations, and report the results to the U.S. Fish and Wildlife Service. 

Monitoring Interval: Biologists will annually document all BLM actions associated with northern spotted 

owl occupied sites in the Harvest Land Base, and every 5 years will estimate the percent of occupied sites 

in the Harvest Land Base that were abandoned due to BLM actions implemented under the RMP. 

M51. Monitoring Question: Have BLM actions avoided adverse effects to Fender’s blue butterfly, 

Oregon silverspot butterfly, Taylor’s checkerspot butterfly, streaked horned lark, vernal pool fairy shrimp, 

Oregon spotted frog, Lower Columbia River Distinct Population Segment of Columbian white-tailed 

deer, or western snowy plover, except when done in accordance with an approved recovery plan, 

conservation agreement, species management plan, survey and monitoring protocol, or critical habitat 

rule, and when the action is necessary for the conservation of the species? 
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Monitoring Requirements: Evaluate at least 20 percent of actions that ‘may affect’ Fender’s blue 

butterfly, Oregon silverspot butterfly, Taylor’s checkerspot butterfly, streaked horned lark, vernal pool 

fairy shrimp, Oregon spotted frog, Lower Columbia River distinct population segment of Columbian 

white-tailed deer, or western snowy plover.

Monitoring Interval: Annual – change interval to once every 3 years if 3 consecutive years of monitoring 

show 100 percent compliance. 

Program Reporting Items 

Program reporting items involve activities that are related to: (1) certain analytical assumptions that are 

pertinent to non-specific management actions; or (2) analytical assumptions pertinent to the analysis of 

environmental consequences in the Proposed RMP/Final EIS. Not all programs or resources have 

reporting items. 

Late-Successional Reserve 

R1. Program Reporting Item: Report the volume of non-ASQ timber offered for sale from the LateSuccessional Reserve. Reporting would be annual. 

Riparian Reserve 

Note: Program Reporting Item R2 does not apply to Eastside Management Area – Riparian Reserve.

R2. Program Reporting Item: Report the volume of non-ASQ timber offered for sale from the 

Riparian Reserve. Reporting would be annual. 

R3. Program Reporting Item: Report the number of fish-passage blockages that have been corrected 

and the number of resulting miles of stream habitat that are newly accessible. Reporting would be annual. 

R4. Program Reporting Item: Report the miles of permanent road construction, road renovation, 

road improvement, and road decommissioning within the Riparian Reserve. Reporting would be annual. 

R5. Program Reporting Item: Report the overall level of stream and riparian restoration activities 

(e.g., placement of large wood and boulders in streams, planting, and thinning). Report the level of stream 

restoration activities in high intrinsic potential streams, or streams with high priority fish populations. 

Reporting would be annual. 

Eastside Management Area 

R6. Program Reporting Item: Report the acres of group selection, commercial thinning, density 

management, and regeneration harvest. Reporting would be annual, or each year in which there is an 

completed timber sale. 
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Harvest Land Base 

R7. Program Reporting Item: Report acres by treatment type for silvicultural treatments listed in 

the following table by Harvest Land Base sub-allocation. Compare against modeling results for the 

appropriate decade of implementation; see Table V-2 and Table V-3 for decade one and two values. See 

the Proposed RMP/Final EIS for subsequent decades. Report commercial thinning, selection harvest, 

regeneration harvest, and timber salvage harvest as acres sold, and report other treatment type categories 

as acres treated. Reporting would be annual. 
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Table V-2. Decade 1 modeled acres by treatment type by Harvest Land Base sub-allocation 

Decade 1

Treatment 

Type‡

Coos Bay Eugene Klamath Falls Medford Roseburg Salem Grand

Total

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

UTA

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

UTA

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

UTA

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

Commercial

Thinning*

840 430 1,270 3,000 420 3,420 - - - - - 200 1,410 1,610 - 4,200 4,580 8,780 6,310 910 7,220 22,300

Selection 

Harvest*

- - - - - - 5,750 - - 5,750 28,170 - - 28,170 1,810 - - 1,810 - - - 35,730

Regeneration 

Harvest*

2,620 510 3,130 9,460 980 10,440 - 110 340 450 - 420 2,590 3,010 - 3,110 3,020 6,130 11,120 1,100 12,230 35,380

Timber Salvage 

Harvest*

- - - - - - - - - - 1,940 - - 1,940 80 220 - 300 - - - 2,240

Reforestation†3,320 650 3,970 12,580 1,300 13,890 1,150 140 430 1,710 6,670 480 2,980 10,130 380 4,160 3,780 8,310 13,350 1,320 14,670 52,690

Manual Cutting 4,450 870 5,320 8,510 880 9,400 580 60 180 810 7,880 500 3,110 11,490 300 2,590 2,360 5,250 11,790 1,170 12,960 45,230

Mulching - - - - - - 350 30 100 480 980 60 360 1,400 260 2,260 2,050 4,580 - - - 6,450

Tubing 1,810 350 2,160 9,460 980 10,440 120 10 30 160 340 30 180 550 260 2,300 2,080 4,640 5,560 550 6,110 24,060

Shading - - - 950 100 1,040 - - - - - - - - - - - - - - - 1,050

Trapping - - - - - - - - - - 650 40 230 920 - - - - 1,670 170 1,830 2,760

Scalping - - - - - - - - - - 660 40 260 960 - - - - - - - 960

Precommercial 

Thinning

3,110 810 3,920 10,900 1,200 12,100 810 160 790 1,760 4,810 460 4,070 9,330 260 3,700 3,640 7,610 12,870 1,150 14,010 48,740

Pruning 260 50 310 1,890 200 2,090 230 20 70 320 330 20 130 480 20 200 180 400 560 60 610 4,220

Stand 

Conversion 100 20 120 - - - - - - - - - - - - - - - - - - 120

* Acreage includes untreated portion of stand (i.e., skips, aggregate retention areas) 

† Natural and artificial reforestation 

‡ These estimates represent analytical results based on the vegetation modeling assumptions described in Appendix C. The BLM has made these assumptions and estimations 

solely for analytical purposes. These acreages of silvicultural treatments by district office and by Harvest Land Base sub-allocation for each decade do not represent management 

direction or restrictions on silvicultural treatments under the RMP. Silvicultural treatments would be implemented consistent with the management direction for the Harvest Land 

Base sub-allocation and consistent with project-level analysis and decision-making.
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Table V-3. Decade 2 modeled acres by treatment type by Harvest Land Base sub-allocation 

Decade 2

Treatment 

Type‡

Coos Bay Eugene Klamath Falls Medford Roseburg Salem Grand

Total

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

UTA

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

UTA

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

UTA

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

MITA

(Acres)

LITA

(Acres)

Total

(Acres)

Commercial 

Thinning*

2,350 520 2,870 11,300 1,100 12,400 - - 20 20 - 50 640 690 - 2,510 5,710 8,220 13,590 1,590 15,180 39,380

Selection 

Harvest*

- - - - - - 7,360 - - 7,360 27,840 - - 27,840 2,210 - - 2,210 - - - 37,410

Regeneration 

Harvest*

1,680 500 2,180 4,450 770 5,220 - 90 350 440 - 200 2,610 2,810 - 3,090 3,380 6,470 8,750 980 9,730 26,850

Timber Salvage 

Harvest*

- - - - - - - - - - 1,610 - - 1,610 - 80 580 660 - - - 2,270

Reforestation†2,140 630 2,770 5,920 1,020 6,940 1,470 110 440 2,020 6,450 230 3,010 9,680 440 3,960 4,950 9,350 10,500 1,170 11,680 42,440

Manual Cutting 2,860 850 3,710 4,010 690 4,700 740 50 180 960 7,640 240 3,140 11,010 350 2,470 3,090 5,920 9,280 1,040 10,310 36,630

Mulching - - - - - - 440 30 110 570 950 30 370 1,340 310 2,150 2,700 5,160 - - - 7,090

Tubing 1,160 340 1,510 4,450 770 5,220 150 10 40 190 330 10 180 530 310 2,180 2,730 5,230 4,380 490 4,870 17,530

Shading - - - 450 80 520 - - - - - - - - - - - - - - - 530

Trapping - - - - - - - - - - 630 20 240 880 - - - - 1,310 150 1,460 2,350

Scalping - - - - - - - - - - 640 20 260 920 - - - - - - - 920

Precommercial 

Thinning

1,680 500 2,180 4,450 770 5,220 1,030 90 350 1,470 4,630 200 2,610 7,440 310 3,170 3,960 7,440 8,750 980 9,730 33,480

Pruning 170 50 220 890 150 1,040 290 20 70 380 320 10 130 460 20 190 240 450 440 50 490 3,040

Stand 

Conversion 70 20 90 - - - - - - - - - - - - - - - - - - 90

* Acreage includes untreated portion of stand (i.e., skips, aggregate retention areas). 

† Natural and artificial reforestation 

‡ These estimates represent analytical results based on the vegetation modeling assumptions described in Appendix C. The BLM has made these assumptions and estimations 

solely for analytical purposes. These acreages of silvicultural treatments by district office and by Harvest Land Base sub-allocation for each decade do not represent management 

direction or restrictions on silvicultural treatments under the RMP. Silvicultural treatments would be implemented consistent with the management direction for the Harvest Land 

Base sub-allocation and consistent with project-level analysis and decision-making. 
1827 | P a g e

Rare Plants and Fungi 

R8. Program Reporting Item: Report the acres of activities designed to maintain or restore natural 

plant communities on non-forest and non-commercial lands. Reporting would be annual. 

Energy and Minerals 

R9. Program Reporting Item: Report the number of biomass utilization projects. Reporting would 

be annual. 

Fire and Fuels Management 

R10. Program Reporting Item: Report the number of acres of hazardous fuels treatments by 

treatment type and by land use allocation (i.e., under burning, broadcast burning, hand pile and burn, 

landing pile and burn, machine pile and burn, slash and scatter, and mastication). Reporting would be 

annual. 

Forest Management 

R11. Program Reporting Item: Report the number of acres of silvicultural treatments by treatment 

type and by land use allocation, including commercial thinning, selection harvest, regeneration harvest, 

timber salvage harvest, reforestation (natural and artificial), manual cutting, mulching, tubing, shading, 

trapping, scalping, pre-commercial thinning, non-commercial thinning, pruning, and stand conversion. 

Report acres of commercial thinning, selection harvest, regeneration harvest, and timber salvage harvest 

as acres sold; report all other treatment types as acres treated. Reporting would be annual. 

Invasive Species 

R12. Program Reporting Item: Report the number of acres of manual, mechanical, cultural, 

chemical, and biological treatments used to manage invasive species infestations. Reporting would be 

annual. 

R13. Program Reporting Item: Report the number of acres of invasive species inventories. Reporting 

would be annual. 

R14. Program Reporting Item: Report the number of acres of inventory, manual, mechanical, 

cultural, and chemical treatments used to manage sudden oak death (Phytophthora ramorum) infections. 

Reporting would be annual. 

Livestock Grazing 

R15. Program Reporting Item: Report the findings of livestock grazing allotments towards meeting 

the Standards for Rangeland Health and Guidelines for Livestock Grazing Management for Public Lands 

Administered by the Bureau of Land Management in the States of Oregon and Washington (USDI BLM 

1997). Reporting would be annual. 
1828 | P a g e

R16. Program Reporting Item: Report the number of acres of prescribed livestock grazing used to 

control invasive plants, reduce fire danger, or accomplish other management objectives. Reporting would 

be annual. 

R17. Program Reporting Item: Report the acres or number of range improvements. Reporting would 

be annual. 

Socioeconomic 

R18. Program Reporting Item: Report the payments to counties associated with BLM-administered 

lands including O&C, Coos Bay Wagon Roads, and Public Domain lands. Reporting would be annual. 

R19. Program Reporting Item: Report receipts from timber sales, special forest products, recreation, 

and permits. Reporting would be annual. 

R20. Program Reporting Item: Report appropriations; number of full time and temporary employees; 

and major new facility developments or improvements. Reporting would be annual. 

Recreation 

R21. Program Reporting Item: Report the number of service-oriented and outreach programs, 

including interpretation and education provided to visitors. Reporting would be annual. 

R22. Program Reporting Item: Report the status of development of comprehensive travel 

management plans for off-highway vehicle management areas and travel management areas. Reporting 

would be annual. 

R23. Program Reporting Item: Within Special Recreation Management Areas (SRMAs), conduct 

visitor studies or on-site monitoring to assess recreation outcome attainment, targeted recreation activity 

participation, and protection of recreation setting characteristics during the primary recreation use season. 

Reporting would be conducted along a rotating schedule, focusing on a cross section of SRMAs within 

one district each year. Monitoring cycle would run every six years between districts. 

Special Forest Products 

R24. Program Reporting Item: Report the number of permits for harvest and collection of special 

forest products. Reporting would be annual. 

Soils 

R25. Program Reporting Item: When greater than 20 percent of the acres treated in any manner have 

detrimental soil disturbance resulting from timber harvest or fuel reduction treatments, report the total 

number of treatment units and the representative percentage of total acres sampled these units entail. Base 

reporting on evaluation of at least 10 percent of the total number of completed timber harvest units and 10 

percent of completed fuel reduction treatment units. Reporting would be annual. 
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Wildlife 

R26. Program Reporting Item: Report the survey effort for marbled murrelet and the outcomes of 

that survey effort. For each survey polygon, report: acres of survey, years surveys were conducted, age of 

stand at time of survey, presence/absence of platform trees, protocol used for the survey, and occupied or 

presence detections of marbled murrelet. For consistency, an example table format is presented below 

(Table V-4). Reporting would be annual. 

Table V-4. Marbled murrelet survey reporting 

Survey Polygon (Name)

Survey 

Area 

(Acres)

Survey 

Date(s) 

(Years)

Stand 

Age 

(Years)

Protocol 

Used

Marbled 

Murrelet 

Detections Occupied Presence None

Sample Project 000 20XX-20XX 000 Citation X X X

R27. Program Reporting Item: Report the number of newly discovered occupied marbled murrelet 

sites. For each newly discovered occupied marbled murrelet site, report: name of site (master site 

number), associated survey that discovered the site, survey dates (years of survey), and acreage included 

in the occupied site designation. For consistency, an example table format is presented below (Table V5). The table should present a running list of all occupied sites designated and the cumulative number and 

acreage of occupied sites. Reporting would be annual. 

Table V-5. Marbled murrelet occupied site

Survey Dates

(Years) Occupied Site Name Associated Survey(Name)

Area Designated

(Acres)

20XX, 20XX Sample Project (MSNO 

XXXX) Sample Project 000

Cumulative Total 000 sites - 000

R28. Program Reporting Item: Report the amount of marbled murrelet nesting habitat that was 

modified or removed within the Harvest Land Base without pre-disturbance surveys (i.e., 35–50 miles 

from the Pacific Ocean except within exclusion Areas C and D as described in Chapter 3 of the Proposed 

RMP/Final EIS). For stands of marbled murrelet nesting habitat modified or removed without surveys, 

report: harvest type, acres, date of treatment, and age at time of treatment. For consistency, an example 

table format is presented below (Table V-6). Reporting would be annual. 

Table V-6. Marbled murrelet nesting habitat modified or removed without surveys 

Project (Name) Harvest Type Area 

(Acres)

Date Modified/

Removed

(Year)

Stand Age at the Time of 

Modification/Removal 

(Years)

Sample Project Harvest Type 000 20XX 000
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R29. Program Reporting Item: Report the survey effort for the red tree vole north of Highway 20 

within the North Oregon Coast DPS and the outcomes of that survey effort. For each survey polygon, 

report: acres of survey, year surveys were conducted, age of stand at time of survey, protocol used for the 

survey, number of active or inactive red tree vole sites discovered, and the total acreage of habitat areas 

established associated with the discoveries. For consistency, an example table format is presented below 

(Table V-7). Reporting would be annual. 

Table V-7. Survey reporting for the North Oregon Coast DPS of the red tree vole 

Survey Polygon 

(Name)

Survey 

Area 

(Acres)

Survey 

Date 

(Years)

Stand 

Age 

(Years)

Protocol 

Used

Red Tree Vole Discoveries

Active 

Sites

(Number)

Inactive 

Sites

(Number)

None

(Number)

Total 

Habitat 

Area 

(Acres)

Sample Project 000 20XX 000 Citation 000 000 000 000

R30. Program Reporting Item (Coos Bay District only): Report number, type, and acres (as 

appropriate) of restoration actions for the western snowy plover. Reporting would be annual. 

R31. Program Reporting Item: (Medford and Salem Districts and Klamath Falls Field Office only) 

Report number and acres of deer and elk forage planting projects within deer and elk management areas. 

Reporting would be annual. 

R32. Program Reporting Item (applies to Eastside Management Area only): Report acres of thinning 

or removal of encroaching western juniper. Reporting would be annual. 
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References 

Davis, R. J., B. Hollen, J. Hobson, J. E. Gower, D. Keenum. 2015. Northwest Forest Plan—the first 20 years (1994–2013): status 

and trends of northern spotted owl habitats. General Technical Report PNW-GTR-XXX. USDA Forest Service, Pacific 

Northwest Research Station, Portland, OR. http://www.reo.gov/monitoring/reports/20yrreport/NSO%20Habitat%2020yr%20Report%20-%20Draft%20for%20web.pdf. 

Davis, R. J., J. L. Ohmann, R. E. Kennedy, W. B. Cohen, M. J. Gregory, Z. Yang, H. M. Roberts, A. N. Gray, and T. A. Spies. in 

press. Northwest Forest Plan–the first 20 years (1994–2013): status and trends of late-successional and old-growth forests. 

General Technical Report PNWGTR-XXX. USDA Forest Service, Pacific Northwest Research Station, Portland, OR. 

http://www.reo.gov/monitoring/reports/20yr-report/LSOG%2020yr%20Report%20-%20Draft%20for%20web.pdf. 

Falxa, G. A., and M. G. Raphael, technical editors. 2015. Northwest Forest Plan—The first 20 years (1994–2013): status and 

trend of marbled murrelet populations and nesting habitat. General Technical Report PNW-GTR-XXX. USDA Forest 

Service, Pacific Northwest Research Station, Portland, OR. http://www.reo.gov/monitoring/reports/20yrreport/MAMU%20GTR_for%20posting_26May2015.pdf. 

Grinspoon, E., D. Jaworski, and R. Phillips. in press. Northwest Forest Plan–The First 20 Years [1994–2013]: Socioeconomic 

Monitoring. USDA Forest Service, Pacific Northwest Research Station, Portland, OR. 

http://www.reo.gov/monitoring/reports/20yr-report/20150511NWFP%20Soc%20Econ%20FinalFullReport.pdf. 

Miller, S. A., S. N Gordon, P. Eldred, R. M. Beloin, S. Wilcox, M. Raggon, H. Andersen, and A. Muldoon. 2015. Northwest 

Forest Plan–The first 20 years (1994–2013): watershed condition status and trend. General Technical Report PNW-GTR932. USDA Forest Service, Pacific Northwest Research Station, Portland, OR. http://www.reo.gov/monitoring/reports/20yrreport/GTR_AREMP_DRAFT_MAY_2015.pdf. 

Page-Dumroese, D. A., A. M. Abbott, and T. M. Rice. 2009a. Forest soil disturbance monitoring protocol—Volume 1: Rapid 

assessment. General Technical Report WO-82a. USDA Forest Service, Rocky Mountain Research Station, Moscow, ID. 35 

pp. http://www.fs.fed.us/rm/pubs_other/wo_gtr082a.pdf. 

---. 2009b. Forest soil disturbance monitoring protocol, Volume 2: Supplementary methods, statistics, and data collection. 

General Technical Report WO-82b. USDA Forest Service, Rocky Mountain Research Station, Moscow, ID. 70 pp. 

http://www.fs.fed.us/rm/pubs_other/wo_gtr082b.pdf. 

USDI BLM. 1997. Standards for rangeland health and guidelines for livestock grazing management for public lands administered 

by the Bureau of Land Management in the states of Oregon and Washington. Oregon State Office, Portland, OR. 22 pp. 

http://www.blm.gov/or/resources/recreation/csnm/files/rangeland_standards.pdf. 

---. 2004. Final - Supplemental Environmental Impact Statement Management of Port-Orford-cedar in Southwest Oregon. SEIS. 

Portland, OR. 

Vinyeta, K., and K. Lynn. 2015. Strengthening the Federal-Tribal Relationship: A Report on Monitoring Consultation under the 

Northwest Forest Plan. USDA Forest Service, Pacific Northwest Research Station, Portland, OR. 

http://www.reo.gov/monitoring/reports/20yr-report/NWFP%20-%20Strengthing%20the%20FederalTribal%20Relationship%20WEB.pdf. 
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Appendix W – Responses to Comments 

This appendix summarizes the substantive comments that the BLM received during the public comment 

period for the Draft RMP/EIS and provides the BLM responses to those comments. 

On April 24, 2015, the BLM released the Draft RMP/EIS announcing a 90-day comment period that 

would conclude on July 23, 2015. On July 13, 2015, the BLM extended the comment period on the Draft 

RMP/EIS until August 21, 2015. The BLM received approximately 4,500 comments on the Draft 

RMP/EIS during the comment period. The BLM received comments from individuals, groups, 

organizations, businesses, elected officials, Federal, state, and local government agencies, and Tribes. All 

comments submitted to the BLM during the comment period are available at 

http://www.blm.gov/or/plans/rmpswesternoregon/comments.php. 

The BLM considered all comments submitted during the comment period. The BLM treated all 

submissions equally and did not give different consideration to submissions based on geographic location, 

organizational affiliation, or other status of the respondents. Additionally, the BLM did not give different 

consideration to comments based on the number of submissions making the same comment. 

The BLM reviewed comments to identify substantive comments, which are comments that—

 Question, with reasonable basis, the accuracy of information in the Draft RMP/EIS, 

 Question, with reasonable basis, the adequacy of, methodology for, or assumptions used for the 

environmental analysis, 

 Present new information relevant to the analysis, 

 Present reasonable alternatives other than those analyzed in the Draft RMP/EIS, and 

 Cause changes or revisions in one or more of the alternatives (USDI BLM 2008, p. 66). 

The BLM summarized these substantive comments into ‘comment summaries.’ Comment summaries are 

statements that identify and describe specific issues or concerns. The BLM combined similar concerns 

voiced in multiple letters into one comment summary. 

This appendix presents the comment summaries and the BLM responses by issue topic. The comment 

summaries and responses are intended to be explanatory in nature; if there are any inadvertent 

contradictions between this appendix and the main chapters of the Proposed RMP/Final EIS, the main 

chapters of the Proposed RMP/Final EIS present the controlling information. 

Comment Summaries and Responses to Comments 

Purpose and Need for Action 

1. Comment Summary: The RMP gives more weight to the ESA than the O&C Act. The O&C Act 

should have priority because it is more specific. Timber production is the overriding objective on 

O&C lands. Secondary uses, such as recreation and the protection of watersheds and wildlife habitat, 

are permitted, but they must be accomplished simultaneously, in coordination with and not at the 

expense of, timber production to benefit local communities.

Response: The O&C Act established sustained-yield timber production as the primary or dominant 

use of O&C lands in western Oregon. However, when implementing the O&C Act, the BLM must do 
1834 | P a g e

so in full compliance with a number of subsequent laws that direct how the BLM accomplishes the 

statutory direction. The BLM based the purpose and need for this RMP revision on the laws that 

apply to the BLM. The BLM designed the alternatives to make a substantial and meaningful 

contribution to meeting each of the purposes (USDI BLM 2015, pp. 10–11). Thus, all of the purposes 

of the action are essential, and none has more importance than other purposes or ‘overrides’ other 

purposes. An alternative that would fail to meet any one of the purposes would not be a reasonable 

alternative. 

2. Comment Summary: The BLM continues to base its approach on a narrow interpretation of BLM 

O&C statutory requirements that has resulted in timber dominance biases throughout the DEIS. We 

request that you at least consider the case law review provided by Scott and Brown (2007) that runs 

contrary to your interpretations of the O&C Act.

Response: The Draft RMP/EIS provided excerpts of the relevant provisions of the O&C Act and 

other major authorizing laws and regulations (USDI BLM 2015, pp. 13–14). The BLM has not 

interpreted the O&C Act, beyond the section in Chapter 1 of the Draft RMP/EIS on the O&C Act and 

the FLPMA. In that section the BLM stated, “Based on the language of the O&C Act, the O&C Act’s 

legislative history, and case law, it is clear that sustained-yield timber production is the primary or 

dominant use of the O&C lands in western Oregon” (USDI BLM 2015, p. 15). While this statement is 

arguably an interpretation, it represents the plain language in existing case law on the O&C Act. The 

commenter suggests that the interpretation in Scott and Brown (2007) is contrary to the BLM 

interpretation. The BLM has reviewed Scott and Brown (2007), an article published in the Journal of 

Environmental Law and Litigation, which provides the authors’ views of the history of the O&C 

lands and the O&C Act. To the extent the above cited statement in the Draft RMP/EIS represents 

BLM legal interpretation, it relies on existing case law. The interpretation of the purpose of the O&C 

Act in Scott and Brown (2007) rests on the assertion that case law on the O&C Act was wrongly 

decided. It is beyond the scope of an RMP to address whether court decisions were wrongly decided. 

The commenter does not explain how they believe that the BLM presenting excerpts from the O&C 

Act or stating the interpretation of the O&C Act in existing case law has resulted in “timber 

dominance biases” in the RMP revision. The BLM based the purpose and need for this RMP revision 

on the laws that apply to the BLM. One of the purposes is to provide a sustained yield of timber. 

Neither the commenter nor Scott and Brown (2007) argue that the provision of sustained yield of 

timber is not a mandate of the O&C Act. Nonetheless, this is one of several purposes, all of which are 

essential, and none has more importance than other purposes. 

Also in the section in Chapter 1 of the Draft RMP/EIS on the O&C Act and the FLPMA, the BLM 

provided the explanation of how the BLM will apply the direction in the O&C Act to resources 

managed under the authority of the FLPMA (USDI BLM 2015, pp. 14–19). This discussion arguably 

represents interpretation by the BLM of the requirements of the O&C Act and the FLPMA. The 

commenter does not raise issue with these explanations. 

3. Comment Summary: The O&C Act specifically mandates that BLM forest management must have 

the objective of “contributing to the stability of local communities and industries” 43 USC 1181(a). 

Resource based industries have high rates of volatility and are therefore unpredictable. The increase 

in timber production with this plan may not be productive in the long term despite what models show.

Introducing greater instability to local economies is an inappropriate outcome for BLM land 

management.
1835 | P a g e

Response: One of the purposes for the RMP revision is to provide for a sustained yield of timber. 

The O&C Act requires that the O&C lands be managed “for permanent forest production, and the 

timber thereon shall be sold, cut, and removed in conformity with the principal of sustained yield for 

the purpose of providing a permanent source of timber supply, protecting watersheds, regulating 

stream flow, and contributing to the economic stability of local communities and industries, and 

providing recreational facilities” (43 U.S.C. 1181a). This passage of the O&C Act establishes 

“contributing to the economic stability of local communities and industries” as one of the purposes 

for which the O&C Act authorizes and directs the selling, cutting, and removing of timber in 

conformity with the principle of sustained yield. It would be inconsistent with the plain language of 

the O&C Act to interpret “contributing to the economic stability of local communities and industries” 

as a goal separate from or competing with sustained-yield timber production (i.e., selling, cutting and 

removing timber in a particular manner and intensity, within certain time-frames, and in particular 

locations as the exclusive means of achieving the O&C Act goals). The commenter’s unsubstantiated 

speculation that timber production may not be “productive in the long-term” does not alter the clear 

legal mandate from the O&C Act to provide for a sustained yield of timber. 

The Draft RMP/EIS analyzed the current conditions and trends in economic conditions and analyzed 

the effects of the alternatives on timber production (USDI BLM 2015, pp. 478–480, 484–488, 509–

516). This analysis specifically and quantitatively describes changes in timber supply, demand, and 

value of timber over time, and acknowledges likely future changes in timber markets based on 

reasonable assumptions. This analysis looks in detail at the effects of the alternatives on community 

stability and resilience, and acknowledges the inherent volatility related to natural resource goods, 

such as timber production. This analysis also describes in detail the importance of timber production 

from the decision area under the alternatives and the Proposed RMP to jobs and earnings. The 

commenter does not identify any flaws in this methodology or errors in the analysis. The commenter 

makes assertions and predictions related to the influence of timber production on communities, but 

provides no information different than that used in the analysis. 

4. Comment Summary: The purpose and need statement improperly makes recovery of the northern 

spotted owl a required component of the RMP although there is no statutory requirement in the ESA 

or any other statute to pursue recovery. Large blocks of old‐growth spotted owl habitat should not be 

a required component of the RMP. Protection of old growth forests on O&C lands is not justified, as 

it is not contributing to the conservation of the spotted owl. Competition from the barred owl 

overrides any other conservation measures.

Response: It is within the BLM’s discretion to include contributing to the conservation and recovery 

of threatened and endangered species as one of the purposes for this RMP revision. The ESA 

(Endangered Species Act) requires Federal agencies to use their legal authorities to promote the 

conservation purposes of the ESA. The ESA defines ‘conservation’ as the methods and procedures, 

which are necessary to bring any endangered or threatened species to the point at which the measures 

provided pursuant to the ESA, are no longer necessary. Thus, it is within the BLM’s authority under 

this mandate in the Endangered Species Act to pursue the conservation and recovery of the northern 

spotted owl as part of the purpose for this action. The Draft RMP/EIS explained why this purpose for 

the northern spotted owl necessarily includes maintaining large, contiguous blocks of latesuccessional forest and maintaining older and more structurally-complex, multi-layered conifer 

forests, based on the existing scientific information and the results of previous analyses. The 

commenter does not specifically address the information in the Draft RMP/EIS explaining why 

maintaining large, contiguous blocks of late-successional forest and maintaining older and more 

structurally-complex, multi-layered conifer forests are necessary components of northern spotted owl 

conservation. 
1836 | P a g e

Among the existing information on the conservation needs of the northern spotted owl, the BLM 

addressed recommendations in the recovery plan for the northern spotted owl. Recovery plans are 

advisory in nature, rather than regulatory. However, the recovery plan for the northern spotted owl 

provides information and advice relevant to the BLM’s purpose of contributing to the conservation 

and recovery of the northern spotted owl, because recovery plans describe reasonable actions and 

criteria that the U.S. Fish and Wildlife Service considers necessary to recover ESA-listed species. As 

detailed in the Draft RMP/EIS, the BLM considered information from the recovery plan in 

formulating the purpose for the action, but did not rely on the information in the recovery plan 

exclusively, in part because as the commenter points out, the recovery plan is advisory rather than a 

binding, regulatory requirement. 

As concluded in the Draft RMP/EIS, the northern spotted owl population is under severe biological 

stress in much of western Oregon, and this population risk is predominately due to competitive 

interactions between northern spotted owls and barred owls (USDI BLM 2015, pp. 774–804). This 

conclusion is consistent with the recovery plan findings, as well as BLM’s independent findings 

through the Draft RMP/EIS. The Draft RMP/EIS acknowledges that habitat management by the BLM 

alone will not be sufficient to produce stable populations of northern spotted owls in some (though 

not all) of the provinces within the planning area. The Draft RMP/EIS specifically details the 

indispensable role of habitat on BLM-administered lands in several provinces. The Draft RMP/EIS 

further identifies and analyzes the effects of a potential mitigation measure of BLM participation in 

barred owl management (USDI BLM 2015, pp. 40, 778–804). The Draft RMP/EIS concludes that 

habitat management by the BLM combined with the mitigation measure related to barred owl 

management would result in substantially improved outcomes for the northern spotted owl 

populations. Barred owl management alone, without maintaining large blocks of habitat and reserving 

older, more structurally-complex forest, would not meet the purpose of the action to contribute to the 

conservation and recovery of the northern spotted owl. The Draft RMP/EIS describes in detail the 

continuing conservation needs of the northern spotted owl related to habitat management by the BLM 

(USDI BLM 2015, pp. 774–804). Thus, the analysis in the Draft RMP/EIS supports the conclusion 

that the greatest contribution to conservation and recovery of the northern spotted owl by the BLM 

would come from a combination of habitat management and participation in barred owl management. 

Additionally, contributing to the conservation and recovery of the northern spotted owl would 

contribute to the additional purpose of providing a sustained yield of timber, particularly in light of 

the guidance for the RMP revision to provide a high degree of predictability and consistency about 

implementing land management actions and a high degree of certainty of achieving desired outcomes 

(see the Guidance for Development of All Action Alternatives section in Chapter 1). Contributing to 

the conservation and recovery of the northern spotted owl is necessary to ensure predictable supply of 

sustained-yield timber production in the future. Further population declines of the northern spotted 

owl could result in additional restrictions on timber harvest, disrupting and limiting the BLM’s ability 

to provide a sustained yield of timber. By protecting and managing habitat now, and participating in 

barred owl management, the BLM can best avoid future, disruptive restrictions on sustained-yield 

timber production. 

5. Comment Summary: The purpose and need statement needs to include reducing catastrophic fire 

risk. It appears that every action alternative developed by the BLM will include logging techniques 

known by the agency to increase fire hazard. This directly inhibits the alleged purpose and need of 

increasing fire resiliency.
1837 | P a g e

Response: The purpose of the action includes restoring fire-adapted ecosystems to increase fire 

resiliency. The Draft RMP/EIS explained that the northern spotted owl recovery plan recommends 

active management within the dry forest landscape to restore ecosystem resiliency. Additionally, in 

order to provide for a sustained yield of timber from public lands under the O&C Act, BLM 

management must account for potential loss of this timber to fire. To the extent possible within the 

decision area, increasing fire resiliency will positively influence fire risk (USDI BLM 2015, p. 10). 

Adding an additional purpose of reducing catastrophic fire risk would not result in any different 

alternatives than those considered in the Draft RMP/EIS. 

Contrary to the commenter’s assertion, the analysis in the Draft RMP/EIS clearly describes that the 

management approach in the Uneven-Aged Timber Area would result in greater resistance to 

replacement fire and that the action alternatives as a whole would result in an overall increase in fire 

resistance relative to current conditions (USDI BLM 2015, pp. 188–195). Furthermore, all 

alternatives would reduce the fire hazard relative to current conditions (USDI BLM 2015, pp. 200–

204). The commenter does not identify any errors in the analysis. 

6. Comment Summary: Addressing climate change and maximizing carbon storage should be part of 

the purpose and need for action.

Response: The BLM based the purpose and need for this RMP revision on the laws that apply to the 

BLM. The BLM has no specific legal mandate to address climate change and maximize carbon 

storage comparable to the legal mandates reflected in the purpose and need for this RMP revision, 

such as, for example, the purpose of contributing to the conservation and recovery of threatened and 

endangered species in accordance with the Endangered Species Act. As such, addressing climate 

change and maximizing carbon storage are not part of the purpose and need for this RMP revision. 

The BLM has various climate-related policies, including the following: 

 Executive Order 13514, which directs agencies to measure, manage, and reduce greenhouse 

gas emissions toward agency-defined targets for agency actions such as vehicle fleet and 

building management 

 Executive Order 13653, which directs agencies to assess climate change related impacts on 

and risks to the agency’s ability to accomplish its missions, operations, and programs and 

consider the need to improve climate adaptation and resilience 

 Secretarial Order 3289, which establishes a Department of the Interior approach for applying 

scientific tools to increase understanding of climate change and to coordinate an effective 

response to its impacts 

 Departmental Manual 523 DM 1, which directs the Department of the Interior agencies to 

integrate climate change adaptation strategies into programs, plans, and operations 

These policies address topics related to greenhouse gas emissions and climate change, but none 

directs the BLM to manage BLM-administered lands specifically for carbon storage. This RMP 

revision is consistent with these policies to the extent they address topics within the scope of this 

planning effort. 

The Draft RMP/EIS analyzed the effects of the alternatives on carbon storage and greenhouse gas 

emissions, assessed climate change-related impacts, and considered potential effects of the 

alternatives in adapting to climate change (USDI BLM 2015, pp. 132–164). 
1838 | P a g e

The Draft RMP/EIS analysis demonstrates that the No Timber Harvest reference analysis represents 

the management approach that would maximize carbon storage (USDI BLM 2015, pp. 134–136), 

which is not a reasonable alternative. Specifically, a purpose of maximizing carbon storage would 

conflict with the purpose of providing a sustained yield of timber, which is an explicit legal mandate 

for the BLM from the O&C Act. 

The Draft RMP/EIS demonstrates that it would not be possible for the BLM to design alternatives 

specifically to “address climate change.” The BLM can only address potential effects of the 

alternatives in adapting to climate change in general, qualitative terms, because of the uncertainties 

associated with projecting future climate change, and the uncertainties associated with the interaction 

of future climate change and land management approaches (USDI BLM 2015, pp. 157–159). 

7. Comment Summary: The stated obligation to provide revenues to Oregon counties by means of 

increased harvest on BLM-administered forested land is, at present, a politically created necessity and 

definitely not one arising from a dearth of actual potential revenue sources. Admittedly, these 

particular tax issues are the province of the elected government of the state of Oregon and are not 

within the administrative or constitutional purview of the Federal Government or its agencies. 

However, the prominent citation of this revenue requirement in the purpose and need section of the 

Draft RMP/EIS makes them an absolutely legitimate and most germane subject for discussion.

Response: The commenter mischaracterizes the purpose and need for action in the Draft RMP/EIS. 

The purposes of the action include providing a sustained yield of timber. The purposes of the action 

do not include, as the commenter mistakenly claims, providing revenues to Oregon counties. The 

commenter mistakenly claims that the purpose and need section of the Draft RMP/EIS prominently 

cites “this revenue requirement.” The O&C Act directs that the U.S. Government shall distribute a 

portion of the receipts from timber sales on O&C lands to the counties with O&C lands. While this 

distribution of a portion of timber receipts is indisputably a requirement on the U.S. Government 

under the O&C Act, the purpose and need for this RMP revision does not specifically include 

providing revenues to counties. In fact, the only mention of revenues in the purpose and need section 

is to recite the FLPMA passage that specifically provides that if there is any conflict between its 

provisions and the O&C Act related to management of timber resources or the disposition of revenues 

from the O&C lands and resources, the O&C Act prevails (i.e., takes precedence) (43 U.S.C. 1701 

note (b), USDI BLM 2015, p. 6). 

The purposes of the action do not include, as the commenter mistakenly claims, increasing the timber 

harvest in the decision area. The purposes of the action include providing a sustained yield of timber, 

but that discussion does not specify any qualitative or quantitative target for timber production, 

beyond the broad direction that alternatives must make a substantial and meaningful contribution to 

meeting each of the purposes for the action (USDI BLM 2015, pp. 6, 10–11). In fact, several of the 

action alternatives would produce less sustained-yield timber harvest than the No Action alternative. 

The commenter’s characterization of the purpose and need for action is mistaken and ignores the 

plain language in the purpose and need discussion in the Draft RMP/EIS. 

8. Comment Summary: The BLM states that a purpose is to coordinate with the Coquille Tribe on 

management of “adjacent and nearby” BLM lands. This purpose will undermine Congressional intent 

by weakening standards on adjacent Federal lands, for the express purpose of ensuring the Tribal 

forest is managed different than the rest of BLM lands.
1839 | Page

Response: The purposes of the action include coordinating management of lands surrounding the 

Coquille Forest with the Coquille Tribe. However, the commenter mistakenly claims that this purpose 

would somehow weaken standards on adjacent Federal lands. There is nothing in the purpose of 

coordinating with the Coquille Tribe that necessarily would require “weakening standards.” The 

alternatives in the Draft RMP/EIS consider a range of management approaches, some of which 

increase protection for some resources and decrease protection for other resources. The commenter 

does not specify which “standards” they believe would be weakened. 

Furthermore, the commenter mistakenly claims that there is an “express purpose” of ensuring that the 

Coquille Forest would be managed differently than the BLM-administered lands. The Draft RMP/EIS 

made no such statement of purpose. In fact, the Draft RMP/EIS stated that the management of the 

Coquille Forest is subject by law to the standards and guidelines of forest plans for adjacent or nearby 

Federal forested land and that the analysis of effects to BLM-administered forested land would 

generally reflect the analysis of effects to resources on the Coquille Forest under each alternative 

(USDI BLM 2015, pp. 10, 661–662). The BLM has added additional text to this discussion in the 

Proposed RMP/Final EIS to clarify the relationship between the RMP and the management of the 

Coquille Forest. 

9. Comment Summary: The EIS should explain the need for logs sourced from public lands, when 

hundreds of millions of board feet are harvested in Oregon and exported to our commercial 

competitors every year.

Response: The need to source logs from BLM public lands within the planning area is described in 

the purpose and need for action (see Chapter 1). The purpose of the action includes providing a 

sustained yield of timber. The O&C Act requires that the Oregon and California Railroad Revested 

Lands and reconveyed Coos Bay Wagon Road Grant lands (O&C lands) be managed “for permanent 

forest production, and the timber thereon shall be sold, cut, and removed in conformity with the 

principal of sustained yield for the purpose of providing a permanent source of timber supply, 

protecting watersheds, regulating stream flow, and contributing to the economic stability of local 

communities and industries, and providing recreational facilities” (43 U.S.C. 1181a). For the public 

domain lands, the FLPMA requires that public lands be managed “on the basis of multiple use and 

sustained yield unless otherwise specified by law” (43 U.S.C. 1701 [Sec. 102.a.7]). The FLPMA also 

requires that “the public lands be managed in a manner which recognizes the Nation’s need for 

domestic sources of minerals, food, timber, and fiber from the public lands” (43 U.S.C. 1701 [Sec. 

102.a.12]).

The Draft RMP/EIS explained that public lands have been a major supplier of timber to mills in 

western Oregon for decades (USDI BLM 2015, pp. 484–486). Once timber is harvested, it flows 

across the region to various processing centers. There are few restrictions on how federal timber 

flows across western United States, with the exception of the ban on the export of timber from federal 

lands and substituting timber from federal lands for exported private timber. The amount of timber 

harvest on other lands and the movement of harvested timber do not alter the applicable statutes, 

regulations, and policies that direct that the BLM-administered lands in the planning area provide a 

sustained yield of timber. 

Relationship of the RMPs to the Northwest Forest Plan 

1839 | Page

Response: The purposes of the action include coordinating management of lands surrounding the 

Coquille Forest with the Coquille Tribe. However, the commenter mistakenly claims that this purpose

would somehow weaken standards on adjacent Federal lands. There is nothing in the purpose of 

coordinating with the Coquille Tribe that necessarily would require “weakening standards.” The 

alternatives in the Draft RMP/EIS consider a range of management approaches, some of which 

increase protection for some resources and decrease protection for other resources. The commenter 

does not specify which “standards” they believe would be weakened. 

Furthermore, the commenter mistakenly claims that there is an “express purpose” of ensuring that the 

Coquille Forest would be managed differently than the BLM-administered lands. The Draft RMP/EIS

made no such statement of purpose. In fact, the Draft RMP/EIS stated that the management of the 

Coquille Forest is subject by law to the standards and guidelines of forest plans for adjacent or nearby

Federal forested land and that the analysis of effects to BLM-administered forested land would 

generally reflect the analysis of effects to resources on the Coquille Forest under each alternative 

(USDI BLM 2015, pp. 10, 661–662). The BLM has added additional text to this discussion in the 

Proposed RMP/Final EIS to clarify the relationship between the RMP and the management of the 

Coquille Forest. 

. Comment Summary: The EIS should explain the need for logs sourced from public lands, when 

hundreds of millions of board feet are harvested in Oregon and exported to our commercial 

competitors every year.

Response: The need to source logs from BLM public lands within the planning area is described in 

the purpose and need for action (see Chapter 1). The purpose of the action includes providing a 

sustained yield of timber. The O&C Act requires that the Oregon and California Railroad Revested 

Lands and reconveyed Coos Bay Wagon Road Grant lands (O&C lands) be managed “for permanent 

forest production, and the timber thereon shall be sold, cut, and removed in conformity with the 

principal of sustained yield for the purpose of providing a permanent source of timber supply, 

protecting watersheds, regulating stream flow, and contributing to the economic stability of local 

communities and industries, and providing recreational facilities” (43 U.S.C. 1181a). For the public 

domain lands, the FLPMA requires that public lands be managed “on the basis of multiple use and 

sustained yield unless otherwise specified by law” (43 U.S.C. 1701 [Sec. 102.a.7]). The FLPMA also 

requires that “the public lands be managed in a manner which recognizes the Nation’s need for 

domestic sources of minerals, food, timber, and fiber from the public lands” (43 U.S.C. 1701 [Sec. 

102.a.12]).

The Draft RMP/EIS explained that public lands have been a major supplier of timber to mills in 

western Oregon for decades (USDI BLM 2015, pp. 484–486). Once timber is harvested, it flows 

across the region to various processing centers. There are few restrictions on how federal timber 

flows across western United States, with the exception of the ban on the export of timber from federal

lands and substituting timber from federal lands for exported private timber. The amount of timber 

harvest on other lands and the movement of harvested timber do not alter the applicable statutes, 

regulations, and policies that direct that the BLM-administered lands in the planning area provide a 

sustained yield of timber. 

9

Relationship of the RMPs to the Northwest Forest Plan 
1840 | Page

10. Comment Summary: In proposing such substantive changes as outlined in the action alternatives, 

the BLM needs to more clearly explain why they are proposing such a substantial departure from the 

science-based NWFP.

Response: The Draft RMP/EIS described the need for revising the RMPs: the substantial, long-term 

departure from the timber management outcomes predicted under the 1995 RMPs and new scientific 

information and policies related to the northern spotted owl (USDI BLM 2015, p. 5). The BLM 

planning regulations require that RMPs “shall be revised as necessary based on monitoring and 

evaluation findings, new data, new or revised policy, and changes in circumstances affecting the 

entire plan or major portions of the plan” (43 CFR 1610.5–6). The BLM has formulated a purpose for 

the RMP revision consistent with applicable statutes, regulations, and policies (USDI BLM 2015, pp. 

5–10). Finally, the Draft RMP/EIS explained the relationship of the RMP revision to the Northwest 

Forest Plan, and specifically, how the BLM addressed the Aquatic Conservation Strategy of the 

Northwest Forest Plan in the RMP revisions (USDI BLM 2015, pp. 20–23). 

Since the adoption of the Northwest Forest Plan, there has been a robust debate about effective 

riparian management strategies for conservation and recovery of ESA-listed fish. Some reviews have 

argued that active management in riparian forests results in short-term adverse effects on fish habitat 

and water quality and have proposed increased restrictions on active management within Riparian 

Reserve to maximize stream shading and the total number of trees available for recruitment to streams 

(e.g., Frissell et al. 2014, Pollock and Beechie 2014). Other reviews have argued that a reliance on 

passive restoration will compromise attainment of long-term ecological goals and have proposed 

more and varied active management approaches within Riparian Reserve to facilitate the growth of 

larger trees and the development of more complex and diverse riparian forests (e.g., Reeves et al. in 

press). 

The purpose and need for this RMP revision clearly identified new scientific information that the 

Northwest Forest Plan did not address; the alternatives in the Draft RMP/EIS address this new 

scientific information. The analysis supporting the Northwest Forest Plan was largely based on 

information in the FEMAT Report, which addressed a very large and diverse assessment area. In 

contrast, the Draft RMP/EIS contains detailed information on conditions within the much smaller 

planning area and includes quantified modeling and analysis specific to the alternatives in the Draft 

RMP/EIS. The BLM based the analysis is the Draft RMP/EIS on detailed information that was not 

available when the Northwest Forest Plan was approved and presents objective, reproducible 

analytical conclusions. The analytical methodology and data in the Draft RMP/EIS is sound. 

This comment from the August 21, 2015 letter from NMFS to the BLM includes the characterization 

of the action alternatives as presenting a “substantial departure” from the Northwest Forest Plan, 

which is not well founded. Each action alternative differs in some components from the Northwest 

Forest Plan (i.e., the No Action alternative), as is appropriate given the purpose and need for the RMP 

revision and the new information. However, for many resources, some action alternatives are more 

protective than the No Action alternative; some action alternatives are less protective. For many 

important features and outcomes, all action alternatives are more protective than the No Action 

alternative (e.g., the extent of the Late-Successional Reserve, the protection of older, more 

structurally-complex forest, the no-thin inner zone of the Riparian Reserve, habitat development for 

the fisher). 

1840 | Page

10. Comment Summary: In proposing such substantive changes as outlined in the action alternatives, 

the BLM needs to more clearly explain why they are proposing such a substantial departure from the 

science-based NWFP.

Response: The Draft RMP/EIS described the need for revising the RMPs: the substantial, long-term 

departure from the timber management outcomes predicted under the 1995 RMPs and new scientific 

information and policies related to the northern spotted owl (USDI BLM 2015, p. 5). The BLM 

planning regulations require that RMPs “shall be revised as necessary based on monitoring and 

evaluation findings, new data, new or revised policy, and changes in circumstances affecting the 

entire plan or major portions of the plan” (43 CFR 1610.5–6). The BLM has formulated a purpose for 

the RMP revision consistent with applicable statutes, regulations, and policies (USDI BLM 2015, pp. 

5–10). Finally, the Draft RMP/EIS explained the relationship of the RMP revision to the Northwest 

Forest Plan, and specifically, how the BLM addressed the Aquatic Conservation Strategy of the 

Northwest Forest Plan in the RMP revisions (USDI BLM 2015, pp. 20–23). 

Since the adoption of the Northwest Forest Plan, there has been a robust debate about effective 

riparian management strategies for conservation and recovery of ESA-listed fish. Some reviews have 

argued that active management in riparian forests results in short-term adverse effects on fish habitat 

and water quality and have proposed increased restrictions on active management within Riparian 

Reserve to maximize stream shading and the total number of trees available for recruitment to streams 

(e.g., Frissell et al. 2014, Pollock and Beechie 2014). Other reviews have argued that a reliance on 

passive restoration will compromise attainment of long-term ecological goals and have proposed 

more and varied active management approaches within Riparian Reserve to facilitate the growth of 

larger trees and the development of more complex and diverse riparian forests (e.g., Reeves et al. in 

press). 

The purpose and need for this RMP revision clearly identified new scientific information that the 

Northwest Forest Plan did not address; the alternatives in the Draft RMP/EIS address this new 

scientific information. The analysis supporting the Northwest Forest Plan was largely based on 

information in the FEMAT Report, which addressed a very large and diverse assessment area. In 

contrast, the Draft RMP/EIS contains detailed information on conditions within the much smaller 

planning area and includes quantified modeling and analysis specific to the alternatives in the Draft 

RMP/EIS. The BLM based the analysis is the Draft RMP/EIS on detailed information that was not 

available when the Northwest Forest Plan was approved and presents objective, reproducible 

analytical conclusions. The analytical methodology and data in the Draft RMP/EIS is sound. 

This comment from the August 21, 2015 letter from NMFS to the BLM includes the characterization 

of the action alternatives as presenting a “substantial departure” from the Northwest Forest Plan, 

which is not well founded. Each action alternative differs in some components from the Northwest 

Forest Plan (i.e., the No Action alternative), as is appropriate given the purpose and need for the RMP 

revision and the new information. However, for many resources, some action alternatives are more 

protective than the No Action alternative; some action alternatives are less protective. For many 

important features and outcomes, all action alternatives are more protective than the No Action 

alternative (e.g., the extent of the Late-Successional Reserve, the protection of older, more 

structurally-complex forest, the no-thin inner zone of the Riparian Reserve, habitat development for 

the fisher). 

1839 | Page

harvest on other lands and the movement of harvested timber do not alter the applicable statutes, 

regulations, and policies that direct that the BLM-administered lands in the planning area provide a 

sustained yield of timber. 

Relationship of the RMPs to the Northwest Forest Plan 
1841 | P a g e

In a December 18, 2015 letter from NMFS to the BLM,58 NMFS clarified that they believe that the 

approach in the Northwest Forest Plan is not the only approach that would ensure the protection and 

recovery of threatened and endangered fish, and that the best available science also supports an 

approach modified from Alternative A or D that would include a one site-potential tree height 

Riparian Reserve on fish-bearing streams and perennial streams. 

11. Comment Summary: The Northwest Forest Plan, particularly the Aquatic Conservation Strategy, 

Survey and Manage program, and reserves, should be treated as a conservation baseline below which 

any reductions in buffer widths and protections are treated as inconsistent with the Plan’s ecosystem 

management and biodiversity emphasis.

Response: The range of alternatives in an EIS for an RMP must present reasonable alternatives to 

accomplishing the stated purpose and need for action. As explained in the Draft RMP/EIS, the 

purpose and need for this RMP revision is different from the purpose and need for the Northwest 

Forest Plan and the 1995 RMPs (USDI BLM 2015, pp. 20–21). The Northwest Forest Plan is not a 

statute or regulation, and the BLM is not required to retain the purpose and need for the Northwest 

Forest Plan. The BLM adopted a purpose and need for this RMP revision that is consistent with the 

agency’s discretion and obligations under the FLPMA, O&C Act, ESA, Clean Water Act, and other 

applicable statutes, as detailed in Chapter 1. While the Northwest Forest Plan is represented in the 

analysis as the No Action alternative, the reasonable action alternatives to accomplish the purpose and 

need for this RMP revision include alternatives that differ from the Northwest Forest Plan. The Draft 

RMP/EIS explained why some elements of the Northwest Forest Plan are not included in the action 

alternatives in the Draft RMP/EIS, with specific detail on the Survey and Manage program and the 

Aquatic Conservation Strategy (USDI BLM 2015, pp. 21–23). Nevertheless, the No Action 

alternative does include all of the elements of the Northwest Forest Plan, and, thus, the BLM has 

retained the discretion to include these elements in the development of the Proposed RMP, because 

they are analyzed in detail in the Draft RMP/EIS. Because the range of alternatives represents the full 

spectrum of reasonable alternatives to accomplishing the purpose and need for this RMP revision, the 

range of alternatives is appropriate. 

Furthermore, as detailed in the response above, the Northwest Forest Plan (i.e., the No Action 

alternative) is intermediate among the action alternatives for many important features and outcomes 

and less protective than all of the action alternatives for many important features and outcomes. Thus, 

the Proposed RMP and several of the action alternatives would provide greater protections than the 

Northwest Forest Plan for some resources. Additionally, as noted above, in a December 18, 2015 

letter from NMFS to the BLM, NMFS clarified that they believe that the approach in the Northwest 

Forest Plan is not the only approach that would ensure the protection and recovery of threatened and 

endangered fish, and that the best available science also supports an approach modified from 

Alternatives A or D that would include a one site-potential tree height Riparian Reserve on fishbearing streams and perennial streams. 

 

58 The BLM includes discussion of the December 18, 2015 letter from NMFS in these responses because the letter 

provides information from a cooperating agency with special expertise relevant to this comment response (see 

Chapter 4). NMFS provided this letter not only in their role as a cooperating agency but also in the context of the 

ESA consultation process. Finally, this letter has particular relevance to these comment responses, because the letter 

directly modifies or alters the comments in their August 21, 2015 letter submitted during the Draft RMP/EIS public 

comment period. 
1842 | P a g e

12. Comment Summary: The Aquatic Conservation Strategy should be maintained under all action 

alternatives and protection strengthened.

Response: As detailed in the Draft RMP/EIS, implementation of the No Action alternative has been 

resulting in improvements in watershed condition (USDI BLM 2015, pp. 221–223, 231, 291–294). 

The Northwest Forest Plan included the Aquatic Conservation Strategy to fulfill nine broad and 

aspirational objectives. The management objectives for the Riparian Reserve in the action alternatives 

and Proposed RMP do not explicitly include the nine Aquatic Conservation Strategy objectives as 

presented in the Northwest Forest Plan. However, the management objectives and management 

direction of the Proposed RMP provide a comparable overall management approach to resources, as 

summarized in Table W-1 below.59

 

Table W-1. Comparison of Northwest Forest Plan Aquatic Conservation Strategy objectives and the 

Proposed RMP 

Northwest Forest Plan 

Aquatic Conservation 

Strategy Objectives

Proposed RMP Management Objectives and Management Direction

1 – Maintain/restore 

watershed and 

landscape-scale features 

to ensure protections of 

aquatic systems

Riparian Reserve management objective – Maintain and restore natural 

channel dynamics and processes and the proper functioning condition of 

riparian areas, stream channels and wetlands by providing forest shade, 

sediment filtering, wood recruitment, stability of stream banks and channels, 

water storage and release, vegetation diversity, nutrient cycling and cool and 

moist microclimate.

Riparian Reserve management direction – Design culverts, bridges, and 

other stream crossings for the 100-year flood event, including allowance for 

bed load and anticipated floatable debris. Design stream crossings with ESAlisted fish to meet design standards consistent with existing ESA consultation 

documents that address stream crossings in the decision area.

Hydrology management direction – Implement road improvement, storm 

proofing, maintenance, or decommissioning to reduce or eliminate chronic 

sediment inputs to stream channels and waterbodies. This could include 

maintaining vegetated ditch lines, improving road surfaces, and installing 

cross drains at appropriate spacing.

2 – Maintain/restore 

spatial and temporal 

connectivity within and 

between watersheds

Fisheries management objective – Maintain and restore access to stream 

channels for all life stages of aquatic species.

Fisheries management direction – Replace stream crossings that currently 

or potentially block or hinder fish passage with crossings that allow aquatic 

species to pass at each life stage and at a range of flows.

3 – Maintain/restore the 

physical integrity of the 

aquatic system

Riparian Reserve management objective – Maintain and restore natural 

channel dynamics and processes and the proper functioning condition of 

riparian areas, stream channels and wetlands by providing forest shade, 

sediment filtering, wood recruitment, stability of stream banks and channels, 

water storage and release, vegetation diversity, nutrient cycling and cool and 

moist microclimate.

Riparian Reserve management objective – Maintain water quality and 

streamflows within the range of natural variability, to protect aquatic 

 

59

 This comparison gives pertinent examples of management objectives and management direction of the Proposed 

RMP that address similar resources as the nine Aquatic Conservation Strategy objectives and is not intended to 

provide a complete description of how the Proposed RMP would address these resources (Appendix B –

Management Objectives and Direction). 
1843 | P a g e

Northwest Forest Plan 

Aquatic Conservation 

Strategy Objectives

Proposed RMP Management Objectives and Management Direction

biodiversity, provide quality water for contact recreation and drinking water 

sources.

Fisheries management objective – Improve the distribution and quantity of 

high quality fish habitat across the landscape for all life stages of ESA-listed, 

BLM special status species, and other fish species.

Fisheries management direction – Create spawning, rearing, and holding 

habitat for fish using a combination of accepted techniques including log and 

boulder placement in stream channels, tree tipping, and gravel enhancement.

4 – Maintain/restore 

water quality

Riparian Reserve management objective – Maintain water quality and 

streamflows within the range of natural variability, to protect aquatic 

biodiversity, provide quality water for contact recreation and drinking water 

sources.

Riparian Reserve management objective – Meet ODEQ water quality

criteria.

Riparian Reserve management objective – Maintain high quality water 

and contribute to the restoration of degraded water quality for 303(d)-listed 

streams.

Riparian Reserve management objective – Maintain high quality waters 

within ODEQ-designated Source Water Protection watersheds.

Hydrology management objective – Maintain water quality within the 

range of natural variability that meets ODEQ water quality standards for 

drinking water, contact recreation, and aquatic biodiversity.

5 – Maintain/restore the 

sediment regime

Riparian Reserve management objective – Maintain and restore natural 

channel dynamics and processes and the proper functioning condition of 

riparian areas, stream channels and wetlands by providing forest shade, 

sediment filtering, wood recruitment, stability of stream banks and channels, 

water storage and release, vegetation diversity, nutrient cycling and cool and 

moist microclimate.

Hydrology management direction – Implement road improvement, storm 

proofing, maintenance, or decommissioning to reduce or eliminate chronic 

sediment inputs to stream channels and waterbodies. This could include 

maintaining vegetated ditch lines, improving road surfaces, and installing 

cross drains at appropriate spacing.

Hydrology management direction – Suspend commercial road use where 

the road surface is deteriorating due to vehicular rutting or standing water, 

or where turbid runoff may reach stream channels.

Hydrology management direction – Decommission roads that are no 

longer needed for resource management and are at risk of failure or are 

contributing sediment to streams, consistent with valid existing rights.

6 – Maintain/restore 

timing, magnitude, 

duration of instream 

flows

Riparian Reserve management objective – Maintain water quality and 

streamflows within the range of natural variability, to protect aquatic 

biodiversity, provide quality water for contact recreation and drinking water 

sources.

Riparian Reserve management direction – Design culverts, bridges, and 

other stream crossings for the 100-year flood event, including allowance for 

bed load and anticipated floatable debris. Design stream crossings with ESAlisted fish to meet design standards consistent with existing ESA consultation 
1844 | P a g e

Northwest Forest Plan 

Aquatic Conservation 

Strategy Objectives

Proposed RMP Management Objectives and Management Direction

documents that address stream crossings in the decision area.

7 – Maintain/restore 

floodplain inundation 

and water table elevation

Riparian Reserve management objective – Maintain water quality and 

streamflows within the range of natural variability, to protect aquatic 

biodiversity, provide quality water for contact recreation and drinking water 

sources.

Riparian Reserve management direction – Design culverts, bridges, and 

other stream crossings for the 100-year flood event, including allowance for 

bed load and anticipated floatable debris. Design stream crossings with ESAlisted fish to meet design standards consistent with existing ESA consultation 

documents that address stream crossings in the decision area.

8 – Maintain/restore 

riparian plant 

species/structural 

diversity

Riparian Reserve management objective – Maintain and restore natural 

channel dynamics and processes and the proper functioning condition of 

riparian areas, stream channels and wetlands by providing forest shade, 

sediment filtering, wood recruitment, stability of stream banks and channels, 

water storage and release, vegetation diversity, nutrient cycling and cool and 

moist microclimate.

Riparian Reserve management direction (Class II and III outer zones) –

Thin stands as needed to promote the development of large, open grown 

trees, develop layered canopies and multi-cohort stands, develop diverse 

understory plant communities, and allow for hardwood vigor and persistence. 

Apply silvicultural treatments to increase diversity of riparian species and 

develop structurally-complex stands.

9 – Maintain/restore 

habitat to support plant, 

invertebrate, and 

vertebrate ripariandependent species

Riparian Reserve management objective – Contribute to the conservation 

and recovery of ESA-listed fish species and their habitats and provide for 

conservation of special status fish and other special status riparian 

associated species.

Riparian Reserve management objective – Maintain and restore natural 

channel dynamics and processes and the proper functioning condition of 

riparian areas, stream channels and wetlands by providing forest shade, 

sediment filtering, wood recruitment, stability of stream banks and channels, 

water storage and release, vegetation diversity, nutrient cycling and cool and 

moist microclimate.

Rare Plants and Fungi management objective – Provide for conservation 

and contribute toward the recovery of plant species that are listed, or are 

candidates for listing, under the ESA.

Rare Plants and Fungi management objective - Provide for the 

conservation of Bureau special status plant and fungi species.

Wildlife management objective – Conserve and recover species that are 

listed, or are candidates for listing, under the ESA and the ecosystems on 

which they depend.

Wildlife management objective – Implement conservation measures that 

reduce or eliminate threats to Bureau Sensitive species to minimize the 

likelihood of and need for listing of these species under the ESA.

The Proposed RMP addresses all four components of the Aquatic Conservation Strategy: Riparian 

Reserve, Key Watersheds, Watershed Analysis, and Watershed Restoration. For each of these 
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components, the Proposed RMP has updated or modified the component, in light of the purpose and 

need for the RMP revision, the management objectives in the Proposed RMP, new scientific 

information, and the BLM’s experience in implementing the 1995 RMPs. The Draft RMP/EIS 

explained the relationship between the alternatives in the Draft RMP/EIS and the Aquatic 

Conservation Strategy of the Northwest Forest Plan (USDI BLM 2015, pp. 22–23). 

The Proposed RMP addresses all components of the Aquatic Conservation Strategy, in an updated 

and modified form. For those resources addressed by the Aquatic Conservation Strategy that are 

related to the purposes of this RMP revision, including the conservation and recovery of threatened 

and endangered fish species, the Proposed RMP would provide comparable protection to the No 

Action alternative. 

13. Comment Summary: The interim Riparian Reserve identified in the FEMAT Report was designed 

to benefit fish as well as riparian species. The DEIS/RMP failed to take a holistic multispecies 

perspective with proposed riparian reserve widths in action alternatives. We assert that RMP 

programmatic planning and analysis must value the multispecies benefits of a two tree riparian 

reserve and not discount them as if salmonids were the only species of concern. The DEIS analysis of 

riparian reserve does not address all the values provided by riparian reserve. The analysis focused 

exclusively on ESA-listed fish and water quality, but riparian reserve also provides value to non‐

aquatic species such as the spotted owl, marbled murrelet, and Pacific fisher, which spend 

disproportionate time on lower slopes near streams. The FEIS should expand the buffer widths in 

Riparian Reserve to account for increasing stressors from potential extreme weather events (floods, 

droughts) due to climate change.

Response: Consistent with the purpose and need for this RMP revision, the BLM established 

management objectives for the Riparian Reserve in the action alternatives and the Proposed RMP that 

focused on fish habitat and water quality. This is in contrast to the nine, broad objectives of the 

Aquatic Conservation Strategy of the Northwest Forest Plan, which included supporting welldistributed populations of riparian-dependent species, based on the U.S. Forest Service’s organic 

statute and implementing regulation. For this RMP revision, the BLM adopted a purpose and need 

that is consistent with the agency’s discretion and obligations under the FLPMA, O&C Act, ESA, 

Clean Water Act, and other applicable statutes. The BLM based the management objectives for the 

Riparian Reserve in the action alternatives and the Proposed RMP on this purpose and need. 

Although the management objectives for the Riparian Reserve in the action alternatives and Proposed 

RMP do not explicitly include the nine Aquatic Conservation Strategy objectives as presented in the 

Northwest Forest Plan, the Proposed RMP does contain comparable management objectives and 

management direction, as summarized above. Furthermore, the discussion in the Draft RMP/EIS 

analyzed the effect of the different Riparian Reserve strategies on the resources associated with the 

nine Aquatic Conservation Strategy objectives. The commenter mistakenly asserts that the analysis 

did not address the effect of the different Riparian Reserve strategies on non-aquatic species. The 

different Riparian Reserve strategies and different analytical assumptions related to Riparian Reserve 

management were all included in the vegetation modeling, which in turn informed the analysis of 

effects on all species, including the northern spotted owl, marbled murrelet, and fisher (USDI BLM 

2015, pp. 100–102, 987–1043). These disclosures of terrestrial species effects presented a reasoned 

analysis based on detailed, quantitative information, including the effects of past actions and 

reasonably foreseeable future actions, and thus provided a ‘hard look’ at the effects of the 

alternatives, including changes in Riparian Reserve design. 
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The commenter does not explain how increasing the Riparian Reserve widths would account for 

“increasing stressors from potential extreme weather events.” For example, the analysis of stream 

shading in the Draft RMP/EIS demonstrated that reducing the Riparian Reserve width from two sitepotential tree heights under the No Action alternative to one site-potential tree height under 

Alternatives A and D, coupled with the management direction within the Riparian Reserve under 

Alternatives A and D, would not result in a measurable difference in stream shading. This conclusion 

is consistent with the FEMAT Report (FEMAT 1993, pp. V-27 – V-28). The commenter does not 

explain why they believe the second site-potential tree height width is necessary to provide stream 

shading or to provide other functions of the Riparian Reserve, or how extreme weather events, such 

as floods and droughts, would alter the stream shading or other functions of the Riparian Reserve. 

The BLM analysis does not support the commenter’s view that the second site-potential tree height is 

necessary to achieve the purpose and need of this RMP revision and management objectives of the 

Proposed RMP. 

14. Comment Summary: A recent review of the NWFP’s ACS in light of scientific advances since 1993 

(Frissell et al. 2014) documented a host of reasons to recommend that Riparian Reserve should be 

expanded and logging activities within them reduced compared to the baseline NWFP (this is 

contrary to the BLM DEIS and therefore the DEIS remains out‐of step with current science).

Response: The BLM has reviewed Frissell et al. 2014, as detailed in the Fisheries section of Chapter 

3. This unpublished report to the Coast Range Association does not present any new scientific 

information. Although it presents numerous citations to existing scientific information (many of 

which are also cited in the Draft RMP/EIS), the report itself is a collection of policy recommendations 

and critiques of administrative policies and legislative proposals, which are generally reflected in the 

substantive comments on the Draft RMP/EIS summarized in this appendix. As such, Frissell et al. 

2014 does not provide any new scientific information relevant for the analysis of the effects of the 

alternatives. 

15. Comment Summary: The Riparian Reserve created by the Northwest Forest Plan (USDA and USDI 

1994) was developed by a broad group of scientists and reflected the general scientific consensus at 

the time as to the level of protection needed for the recovery of salmon over a 100-year time frame 

and was considered by the Federal courts to be the “bare minimum” necessary for the recovery of 

salmon. Several Riparian Reserve options proposed at that time were more protective than the current 

proposed BLM DEIS Riparian Reserve, but were rejected as inadequate. The DEIS is (implicitly) 

making an extraordinary claim; that the FEMAT science team (and the Federal courts) were in error, 

and that up to 81 percent of the existing Riparian Reserve network can be opened for substantially 

increased levels of timber harvest (i.e., the Preferred Alternative B), with little effect on salmon and 

other riparian-dependent species and the habitat upon which they depend.

Response: The management objectives for the Riparian Reserve in the FEMAT Report (which 

supported the Northwest Forest Plan) included supporting well-distributed populations of ripariandependent species. The FEMAT Report concluded that the cumulative effectiveness of riparian 

buffers would be maximized within a distance of one site-potential tree height from the channel or 

less (FEMAT Report, pp. V-27 – V-29). The only effects that the FEMAT Report identified for 

riparian buffers beyond one site-potential tree height from streams were for effects on riparian 

microclimate and wildlife habitat. These are effects that were relevant to the Riparian Reserve 

management objective in the Northwest Forest Plan of supporting well-distributed populations of 

riparian-dependent species; but the FEMAT Report contains no analysis that riparian buffers of two 

site-potential tree heights are necessary for the protection of ESA-listed fish or water quality, which 
1847 | P a g e

are management objectives for the Riparian Reserve in the action alternatives and Proposed RMP in 

this RMP revision. Two of the action alternatives in the Draft RMP/EIS, Alternatives A and D, would 

include a Riparian Reserve of one site-potential tree height on all streams. The FEMAT Report did 

not directly consider such a Riparian Reserve design. Nevertheless, the analytical conclusions in the 

FEMAT Report support that such a design would maximize the cumulative effectiveness of such a 

buffer for effects on fish habitat. Thus, for the purposes of the management objectives for action 

alternatives and Proposed RMP in this RMP revision, the commenter’s assertion that the FEMAT 

Report “rejected as inadequate” the Riparian Reserve designs in all of the action alternatives in Draft 

RMP/EIS is not well founded. 

Moreover, the Draft RMP/EIS does not claim, implicitly or explicitly, that the FEMAT science team 

was in error. The management objectives for the Riparian Reserve in the FEMAT Report (and 

Northwest Forest Plan) differ from the management objectives for the Riparian Reserve in the action 

alternatives in the Draft RMP/EIS. 

This comment, included in the August 21, 2015 letter from NMFS to BLM, concluding that “up to 81 

percent of the existing Riparian Reserve network can be opened for substantially increased levels of 

timber harvest” under Alternative B is based on incorrect analysis, as explained below in response to 

a similar comment. The acreage available for sustained-yield timber harvest would be substantially 

smaller under Alternative B than under the No Action alternative. In a December 18, 2015 letter from 

NMFS to the BLM, NMFS acknowledged that these comments were in error and asked that they be 

ignored. 

The Draft RMP/EIS does not claim, implicitly or explicitly, that the action alternatives would have 

“little effect on salmon and other riparian-dependent species” As explained above, the Draft 

RMP/EIS analyzed the effects of the alternatives on ESA-listed fish and water quality (USDI BLM 

2015, pp. 219–233, 286–318). That analysis demonstrated the comparative effect of the alternatives. 

The Draft RMP/EIS does not make any conclusion about whether such effects are “little.”

The comment from NMFS does not specify which Federal court they claim considers the Riparian 

Reserve design in the Northwest Forest Plan to be the “bare minimum” necessary for the recovery of 

salmon, but the BLM is unaware of any such court ruling. There is no such finding in Seattle 

Audubon Society v. Lyons, 871 F. Supp. 1291 (W.D. Wash. June 6, 1994), which addressed 

challenges to the Northwest Forest Plan. In a December 18, 2015 letter from NMFS to the BLM, 

NMFS specifically withdrew all of their comments related to interpreting judicial decisions on the 

Northwest Forest Plan. NMFS specifically clarified that they believe that the approach in the 

Northwest Forest Plan does not represent a minimum level of protection. As noted above, NMFS 

clarified that the best available science also supports an approach modified from Alternative A or D 

that would include a one site-potential tree height Riparian Reserve on fish-bearing streams and 

perennial streams. 

16. Comment Summary: The BLM should fully comply with the Survey and Manage provisions of the 

Northwest Forest Plan in all the alternatives until Federal agencies protect all remaining late‐

successional habitat and the reserves are fully functional. The program might not be needed if coarse 

filter reserves and older forests were fully functional, but that is not the case. Abandonment of the 

Survey Manage program will increase extinction rates, cause the loss of ecological processes, and 

reduce small Sensitive species buffers that greatly augment habitat connectivity in the highly 

fragmented landscape of western Oregon BLM lands. The BLM must discuss how the decreased 

protection for Survey and Manage species will affect the functionality of the Northwest Forest Plan 

for the U.S. Forest Service. The Survey and Manage program has resulted in significant gains in 
1848 | P a g e

knowledge, reduced uncertainty about conservation, and developed useful new inventory methods for 

rare species. The BLM presents no quantified analysis of the population levels or trends for any of the 

Survey and Manage species to be dropped from the program or the handful that would be managed as 

Bureau Sensitive species.

Response: The Survey and Manage measures were included in the Northwest Forest Plan to respond 

to a goal of ensuring viable, well-distributed populations of all species associated late-successional 

and old-growth forests. As explained in the Draft RMP/EIS, this goal of the Northwest Forest Plan 

was founded on a U.S. Forest Service planning regulation, which did not and does not apply to the 

BLM, and is not a part of the purpose for this RMP revision (USDI BLM 2015, pp. 21–22). The BLM 

based the purpose for this RMP revision on the statutes and regulations that apply to the BLM, as 

detailed in Chapter 1. The BLM will not use the RMP revision process to adopt regulations like those 

that apply only to the U.S. Forest Service. Because the range of alternatives represents the full 

spectrum of reasonable alternatives to accomplishing the purpose and need for this RMP revision, as 

described below, the range of alternatives is appropriate. 

The species viability goal of the Northwest Forest Plan is not part of the purpose for this RMP 

revision. The Draft RMP/EIS explained that the purpose and need for the RMP revision differs from 

the purpose and need for the Northwest Forest Plan and reflects the BLM’s determination that it can 

achieve the goals of the O&C Act and other applicable statutes without the Survey and Manage 

measures (USDI BLM 2015, pp. 20–22). The commenter argues that the Survey and Manage 

measures must be included in the RMP because it is still needed. The Northwest Forest Plan did not 

include the Survey and Manage measures simply for the sake of having a Survey and Manage 

approach. Had that been the case, the Survey and Manage measures would have been reflected in the 

Purpose and Need statement of the Northwest Forest Plan and included in the design of one or more 

of its alternatives. Instead, the Survey and Manage measures were only first identified in the Final 

Supplemental EIS for the Northwest Forest Plan as one mitigation measure to increase the likelihood 

of achieving “viable populations, well-distributed across their current range, of species known (or 

reasonably expected) to be associated with old-growth forest conditions” (USDA FS and USDI BLM, 

1994, p. 3&4-129) – a goal which was founded on a U.S. Forest Service planning regulation that, as 

explained above, did not and does not apply to the BLM. 

The Draft RMP/EIS explained that the BLM does not need the Survey and Manage measures to avoid 

species extinctions or to achieve the purposes of the RMP revision or to meet BLM’s obligations 

under applicable law and regulation. The Proposed RMP represents a management approach that 

provides habitat for species “associated with old-growth forest conditions.” As detailed in the analysis 

in the Proposed RMP/Final EIS, the Proposed RMP would—

 Allocate a larger Late-Successional Reserve network than the No Action alternative;60

 Reserve all of the older and more structurally-complex forests, which generally represents 

“old-growth forest conditions” and thus, by definition, provides high quality habitat for 

Survey and Manage species; 

 Reserve more of the combined mature and structurally-complex forest—which provides 

potential habitat for Survey and Manage species—than the No Action alternative; 

 Provide management direction within the Harvest Land Base to provide for snags, down 

woody debris, leave trees and islands, and a diversity of tree species in the canopy layer, 

 

60 The Final Supplemental EIS for the Northwest Forest Plan identified that the Late-Successional Reserve network 

provides key benefits to Survey and Manage species (USDA FS and USDI BLM 1994a, pp. 3&4-114 – 3&4-177). 

All action alternatives and the Proposed RMP would allocate a Late-Successional Reserve network larger than what 

is provided in the Northwest Forest Plan and thus would generally provide a larger network of habitat for Survey 

and Manage species. 
1849 | P a g e

which would maintain diversity at the stand level, providing a variety of unique habitat 

conditions to support diverse fungi, lichens, bryophytes, and vascular plants, including 

Survey and Manage species; and 

 Continue to provide management for many of the Survey and Manage species as Bureau 

Sensitive species (see the Rare Plants and Fungi and Wildlife sections of Chapter 3). 

As a result of these allocations and management direction, the Proposed RMP would protect the 

majority of the currently known sites of Survey and Manage species in the reserve land use 

allocations and would provide a greater increase in the amount of potential habitat for Survey and 

Manage species over time than the No Action alternative, as detailed in the Rare Plants and Fungi and 

Wildlife sections of Chapter 3 and Appendix S – Other Wildlife (e.g., Table 3-2, Table 3-3, Table 

3-4, Table S-5, Table S-6). 

The BLM has other management tools besides allocating reserves for conserving species that are 

associated with late-successional and old-growth forests. Although the species viability goal of the 

Northwest Forest Plan is not part of the purpose for this RMP revision, the BLM would provide 

management for Survey and Manage species that are also Bureau Sensitive species, consistent with 

BLM policy, under all action alternatives and the Proposed RMP. As detailed in the Rare Plants and 

Fungi and Wildlife sections of Chapter 3, Appendix N – Rare Plants and Fungi, and Appendix S –

Other Wildlife, of the 35 Survey and Manage plant and fungi species in the decision area, 5 are also 

Bureau Sensitive species, and of the 13 Survey and Manage wildlife species in the decision area, 4 are 

also Bureau Sensitive species. The BLM Special Status Species policy directs that the BLM address 

Bureau Sensitive species and their habitats in the planning process, and, when appropriate, 

identify and resolve significant land use conflicts with Bureau Sensitive species. In implementing 

the RMP, the BLM will ensure that actions affecting Bureau Sensitive species will be carried out in a 

way that is consistent with the objectives for managing those species and their habitats at the 

appropriate spatial scale. The application of the BLM Special Status Species policy to provide 

specific protection to species that are listed by the BLM as Sensitive “... on lands governed by the 

O&C Act must be consistent with timber production as the dominant use of those lands” (USDI BLM 

2008, BLM Manual 6840 – Special Status Species Management, sections 6840.06.2A – 6840.06.2E). 

The BLM has addressed the Survey and Manage species that are also Bureau Sensitive species in the 

analysis for this RMP revision, and has resolved land use conflicts as discussed below. Therefore, 

even if habitat and site protection described above were not sufficient to provide adequate habitat for 

such species, before they could need listing under the ESA, the BLM would be able to include such 

species on the BLM Sensitive species list and provide necessary additional management to avoid the 

need for listing. 

The commenter suggests that the Survey and Manage measures must be included in the RMP to 

prevent loss of ecological processes, such as nutrient cycling and nitrogen fixation. The analysis in 

the Draft RMP/EIS does not support the conclusion that the Survey and Manage measures are 

necessary to preserve ecological processes. Survey and Manage species undoubtedly provide 

ecological processes including nitrogen fixation and nutrient cycling. However, the analysis in the 

Draft RMP/EIS demonstrates that such loss of Survey and Manage species is not reasonably 

foreseeable under the action alternatives, given that the action alternatives would generally provide 

more habitat for Survey and Manage species than the No Action alternative and that the BLM would 

provide management for Survey and Manage species that are also Bureau Sensitive species. 

Additionally, the Survey and Manage species are, by definition, rare and limited in occurrence. Thus, 

any speculative loss of ecological processes would be extremely limited in geographic scope, and it 

would not be possible to detect any measurable difference among the alternatives in providing these 
1850 | P a g e

ecological processes. There is no scientific method by which the BLM could measure the possible 

loss of ecological processes related to Survey and Manage species in the analysis. 

The commenter asserts that the Survey and Manage measures must be included in the RMP to 

provide habitat connectivity. As explained above, all action alternatives and the Proposed RMP would 

generally provide a larger network of habitat for Survey and Manage species and that the amount of 

habitat for Survey and Manage species would generally increase over time, as detailed in the Rare 

Plants and Fungi and Wildlife sections of Chapter 3 and Appendix S – Other Wildlife. 

The commenter asserts that the BLM must address how eliminating the Survey and Manage measures 

will affect the “functionality” of the Northwest Forest Plan for the U.S. Forest Service. As described 

above, all action alternatives and the Proposed RMP would generally provide a larger network of 

habitat for Survey and Manage species and that the amount of habitat for Survey and Manage species 

would generally increase over time. Thus, all action alternatives and the Proposed RMP would 

generally provide a comparable or greater contribution to habitat for Survey and Manage species than 

the current condition. In addition, the majority of currently known sites for Survey and Manage 

species would be generally protected in the reserve land use allocations under the action alternatives 

and the Proposed RMP. The action alternatives and the Proposed RMP would provide continued 

management of Survey and Manage species that are Bureau Sensitive species. In light of this 

approach, the analysis in the Proposed RMP/Final EIS does not support the conclusion that the any of 

the action alternatives or the Proposed RMP would result in a loss of “functionality” of the Northwest 

Forest Plan for the U.S. Forest Service. 

The commenter urges retaining the Survey and Manage measures because these measures have 

produced new information and new inventory methods. The BLM does not dispute that the 

implementation of the Survey and Manage measures has resulted in an increase in information about 

such species and the development of inventory methods. While this increase in knowledge is an 

inevitable and beneficial result of such a program, it is not necessary to achieve the purposes of the 

RMP revision or to comply with any law or regulation applicable to the BLM. 

The commenter states that the Draft RMP/EIS does not include quantified population analysis of the 

Survey and Manage species. The commenter is correct. Analysis in an EIS must provide a ‘hard look’

at the effects of the alternatives. A ‘hard look’ is a reasoned analysis containing quantitative or 

detailed qualitative information (USDI BLM 2008, p. 55). The Draft RMP/EIS detailed the 

methodology for analyzing the effects of the alternatives on Survey and Manage species based on 

habitat abundance (USDI BLM 2015, pp. 423, 682–683). This analysis provided detailed and 

quantitative information, which supported reasoned analytical conclusions about the effects of the 

alternatives on Survey and Manage species (USDI BLM 2015, pp. 428–439, 683–694). The Proposed 

RMP/Final EIS has added discussion to explain why the BLM did not provide a quantified population 

analysis of the Survey and Manage species (see the Summary of Analytical Methods in the Rare 

Plants and Fungi and Wildlife sections of Chapter 3). Survey and species data on Survey and Manage 

species are incomplete and insufficient to provide for any meaningful analysis of population trends. 

Instead, the BLM conducted the analysis of effects on Survey and Manage species using the available 

information related to habitat conditions for these species. 

17. Comment Summary: By considering action alternatives that would change the BLM’s land 

management, the agency is essentially considering pulling out of the multi-agency Northwest Forest 

Plan. The BLM cannot do this without causing the entire Northwest Forest Plan to crumble; that is, 

although the action agency here is the BLM, its decisions will by necessity change the validity of the 

U.S. Forest Service’s actions and land management assumptions. The DEIS fails to address or 
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analyze the environmental and cumulative impacts of these alternatives on the continuing validity of 

the Northwest Forest Plan as a whole.

Response: The Draft RMP/EIS clearly states that this RMP revision would replace the 1995 RMPs 

and thereby replace the Northwest Forest Plan for the management of BLM-administered lands in 

western Oregon (USDI BLM 2015, p. 21). The analysis in the Draft RMP/EIS assumed that the U.S. 

Forest Service would continue to manage their lands within the analysis area consistent with their 

existing plans (i.e., the Northwest Forest Plan) (USDI BLM 2015, pp. 95–96). Thus, the analysis in 

the Draft RMP/EIS presents a cumulative analysis of the BLM managing of BLM-administered lands 

under each alternative and the U.S. Forest Service managing of National Forests under the Northwest 

Forest Plan. 

Whether the U.S. Forest Service would need to conduct additional analysis for implementation of 

U.S. Forest Service projects, and whether the U.S. Forest Service would continue to elect to manage 

National Forests under the Northwest Forest Plan in the future are questions beyond the scope of this 

RMP revision process. 

Range of Alternatives 

18. Comment Summary: The No Action alternative of the Draft RMP/EIS is based on implementation 

of the original 1995 RMPs “as written,” not as currently practiced, which makes comparisons of it to 

the action alternatives false and the entire analysis flawed.

Response: The No Action alternative for a RMP revision is no change from the current management 

direction or level of management intensity. In the case of this RMP revision, the implementation of 

the 1995 RMPs has not been consistent with the assumptions of the 1995 RMPs, as detailed in the 

BLM plan evaluations (USDI BLM 2012). As explained in the Draft RMP/EIS, this long-standing 

failure to implement the 1995 RMPs as written is part of the stated need for the RMP revision (USDI 

BLM 2015, p. 5). The Draft RMP/EIS further explained that the BLM cannot analyze continuation of 

the current practices as the No Action alternative, because the current practices have been variable 

and are not sustainable, preventing the projection of the current practices into the future (USDI BLM 

2015, pp. 77–78). Due to this variability in implementation, there is no particular ‘snapshot’ in time 

that the BLM could reasonably select as representative of the 1995 RMPs as implemented; any 

selection of such a ‘snapshot’ in time would be arbitrary, since past practice provides no rational basis 

upon which to project the continuation of practices at any given point in time into the future. The No 

Action alternative in the Draft RMP/EIS explicitly represents no change from the current 

management direction and thus constitutes the appropriate benchmark for comparison to the action 

alternatives. 

The Proposed RMP/Final EIS has added discussion of an alternative that would implement the 1995 

RMPs at the sustained-yield timber harvest levels declared in the 1995 RMPs, and provided an 

explanation of why this alternative was considered but not analyzed in detail. 

Nevertheless, the Draft RMP/EIS and the Proposed RMP/Final EIS describe the combined effects of 

past implementation of the 1995 RMPs, in that the analyses identify a baseline of current conditions 

that reflects the effects of the actual implementation to date. As explained in the Draft RMP/EIS, the 

analyses incorporated the aggregate effect of past actions, including the actual implementation of the 

1995 RMPs, into the existing baseline information (USDI BLM 2015, p. 94). The analyses of the 

effects of the alternatives compare future resource condition against this baseline, thus providing a 
1852 | P a g e

comparison of the effects of the alternatives to the baseline condition created by the actual 

implementation of the 1995 RMPs. 

19. Comment Summary: The BLM should have analyzed the Natural Selection alternative in detail. The 

Natural Selection alternative limits harvest of timber to dead and dying trees because it can generate 

better wood, has hugely less impact on habitats than green tree removal and it retains optimal 

photosynthesis and tree productivity. The Natural Selection alternative produces more timber over the 

long term than other alternatives. The average volume of timber production across the landscape 

under the Natural Selection alternative is greater than BLM’s preferred alternatives [sic] because it 

doesn’t produce areas with little or no production. The Natural Selection alternative offers 

scientifically sound, ecologically credible and legally responsible solutions to the critical issues of the 

21st century including, global climate change, species extinctions, and social‐economic conditions.

Response: The range of alternatives in an EIS for an RMP must present reasonable alternatives to 

accomplishing the stated purpose and need for action. As explained in the Draft RMP/EIS, the BLM 

did not analyze the Natural Selection alternative in detail, because it is not a reasonable alternative. 

Specifically, limiting the harvest of timber to trees that are dead or are dying would not be consistent 

with the requirements of the O&C Act and would not respond to the purpose for the action (USDI 

BLM 2015, p. 79). The commenter asserts that the Natural Selection alternative would, in fact, 

produce more sustained-yield timber than any of the alternatives analyzed in detail (i.e., more than the 

486 MMbf/year under Alternative C), but provides neither an estimate of the amount of timber the 

Natural Selection alternative would provide or support for this claim. It would not be possible to 

quantify the amount of annual timber harvest for a program that would limit timber harvest to dead 

and dying trees because of the inherent unpredictability in the number of trees dying each year, their 

location, or their suitability for wood products. The commenter does not explain why they believe the 

Natural Selection alternative would produce more timber than any of the alternatives, or why such 

harvest would represent the annual productive capacity of the forest. Because the Natural Selection 

alternative would not offer for sale the annual productive capacity of the forest, it is not consistent 

with the O&C Act. Because the Natural Selection alternative would not provide a sustained yield of 

timber, it does not respond to the purpose for the action. Therefore, the Natural Selection alternative 

is not a reasonable alternative and need not be analyzed in detail. 

20. Comment Summary: A small diameter alternative needs to be considered in the FEIS in order to 

provide an adequate range of alternatives under NEPA. None of the BLM alternatives focus 

exclusively on small diameter restoration treatments as the primary objective and thus the DEIS 

remains out-of-compliance with NEPA and best available science. Based on prior calculations (Kerr 

2011) and a one-time entry for timber volume, this could potentially generate about 1.6 billion board 

feet from the Matrix and Adaptive Management Areas.

Response: The range of alternatives in an EIS for an RMP must present reasonable alternatives to 

accomplishing the stated purpose and need for action. One of the purposes of the action is to provide 

for a sustained yield of timber. The Draft RMP/EIS explains that sustained yield of timber is the 

timber volume that a forest can produce in perpetuity at a given intensity of management (USDI BLM 

2015, p. 892). An alternative designed for “one-time entry” with restoration as the primary objective 

would not provide sustained yield of timber. Limiting timber harvest to “one-time entry” and 

establishing restoration of some resource condition as the primary objective would preclude 

producing a given volume of timber in perpetuity at a given intensity of management, as required by 

the O&C Act and specifically described in the purpose for the action. Therefore, such an alternative 
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would not be a reasonable alternative. The Proposed RMP/Final EIS added discussion of this 

suggested alternative as an alternative considered but not analyzed in detail (see Chapter 2). 

21. Comment Summary: Maximum timber production allowable under the O&C Act should be used as 

the baseline against which alternatives are compared. This maximized analysis should be the base 

point on which all other alternatives are measured against and compared, to reflect the true economic 

value of what these alternatives are costing our local communities.

Response: An alternative that would provide “maximum timber production allowable under the O&C 

Act” would not be a reasonable alternative, because it would not meet other purposes of the action, 

including contributing to the conservation and recovery of threatened and endangered species, 

providing clean water, and restoring fire-adapted ecosystems. The Draft RMP/EIS does estimate the 

maximum timber production allowable under the O&C Act, noting that the amount is approximately 

the same as the amount estimated in the 2008 FEIS—1.2 billion board feet per year (USDI BLM 

2015, pp. 261–262). Beyond approximating this timber volume, the BLM did not identify any need to 

use the “maximum timber production allowable under the O&C Act” as a reference analysis in 

comparison to the effects of the alternatives. The commenter does not explain how further analysis of 

this reference analysis would assist in interpreting the results of the analysis, beyond asserting that it 

is the appropriate baseline. The “maximum timber production allowable under the O&C Act” would 

produce substantially more timber harvest, and consequently higher payments to counties, than the 

alternatives; further analysis could give more precision to this analytical conclusion, but would not 

alter this conclusion. In summary, the “maximum timber production allowable under the O&C Act” is 

not a reasonable alternative; the amount of the “maximum timber production allowable under the 

O&C Act” is disclosed in the Draft RMP/EIS; and further analysis of the “maximum timber 

production allowable under the O&C Act” would not improve the analysis of the effects of the 

alternatives and is not essential to a reasoned choice among the alternatives. 

22. Comment Summary: We recommend that at least two other alternatives be added to the final 

analysis. The first would be one that truly integrates and balances ecological, social, and economic 

values. The second would be a more “robust” alternative with a target harvest volume closer to 

biological growth.

Response: The range of alternatives in an EIS for an RMP must present reasonable alternatives to 

accomplishing the stated purpose and need for action. When there are potentially a very large number 

of alternatives, such as this RMP revision, only a reasonable number of alternatives, covering the full 

spectrum of alternatives, must be analyzed in the EIS. The commenter does not specify the 

alternatives that they believe are reasonable and are not within the spectrum of alternatives analyzed 

in detail in the Draft RMP/EIS. The alternatives in the Draft RMP/EIS do “integrate and balance 

ecological, social, and economic values,” to the extent those values are represented by the purposes of 

the action. The commenter does not specifically describe an alternative “with a target harvest volume 

closer to biological growth” that would meet the purposes of the action. The BLM presumes that such 

an alternative would be substantially similar to a “maximum timber production allowable under the 

O&C Act” alternative, which would not be a reasonable alternative, as explained in the comment 

above. The BLM has analyzed in detail the full spectrum of alternatives that would accomplish the 

purpose of the action. That is, it would not be possible to construct an alternative with more timber 

harvest that meets all of the purposes of the action. 
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23. Comment Summary: The design of the alternatives for conservation needs of the spotted owl far 

exceeds a need‐based standard.

Response: For the BLM to consider alternatives reasonable, alternatives must accomplish the 

purposes of the action, which include contributing to the conservation and recovery of threatened and 

endangered species, including the northern spotted owl. The BLM based the analysis of the effects of 

the alternatives on northern spotted owls, in part, on an evaluation of how the alternatives would 

address the conservation needs of the northern spotted owl (USDI BLM 2015, pp. 746–826). The 

commenter confuses the design of the alternatives with the analysis of the effects. Although the 

analysis of effects included an evaluation relative to the conservation needs of the northern spotted 

owl, the BLM designed the alternatives to contribute to the conservation and recovery of the northern 

spotted owl, among other purposes. The purpose of the action is not to satisfy a “need-based 

standard” for the northern spotted owl and no more; the purpose of the action includes contributing to 

the recovery of the northern spotted owl, which the alternatives do to varying degrees. Therefore, the 

alternatives presented in the Draft RMP/EIS represent reasonable alternatives to accomplishing the 

purpose of contributing to the conservation and recovery of the northern spotted owl, among other 

purposes. The commenter points to no legal constraint that would limit the purpose of BLM’s action 

to a “need-based standard” of spotted owl conservation.

24. Comment Summary: The range of alternatives is too narrow and needs to include an alternative with 

a larger Harvest Land Base. The BLM may have arbitrarily limited the size of the Harvest Land Base 

in any action alternative to 30 percent of the forest land in the decision area (DEIS p. 246). We 

recommend an additional action alternative that maximizes the size of the Harvest Land Base and 

reduces reserves to the minimum necessary.

Response: The range of alternatives in an EIS for an RMP must present reasonable alternatives to 

accomplishing the stated purpose and need for action. The commenter mistakenly claims that the 

BLM limited the size of the Harvest Land Base and misunderstood the cited passage in the Draft 

RMP/EIS. The passage in the Draft RMP/EIS describes the outcome of the design of the alternatives, 

not a rule or limitation that the BLM imposed upon the design of the alternatives. The BLM designed 

the alternatives to meet all of the purposes of the action, and the resultant range of alternatives 

includes a Harvest Land Base that ranges from 12 to 30 percent of the decision area. Alternative C 

allocated the largest Harvest Land Base that would meet all of the purposes of the action. Alternative 

C allocated a Late-Successional Reserve network based, in part, on large blocks of habitat to meet 

size and spacing requirements, but no larger. To reduce the Late-Successional Reserve from 

Alternative C would not meet the size and spacing requirements described in the Draft RMP/EIS 

(USDI BLM 2015, pp. 7, 62, 750). Alternative C would provide the least improvement in marbled 

murrelet nesting opportunities and would increase the risk of nest predation compared to the other 

alternatives, and would provide no protection for future occupied nest sites in the Harvest Land Base 

(USDI BLM 2015, pp. 724–736). To provide less protection for the marbled murrelet would not meet 

the purpose of contributing to the conservation and recovery of the marbled murrelet. Alternative C 

allocated the smallest Riparian Reserve of any of the alternatives. The analysis in the Draft RMP/EIS 

identified lower potential wood supply and more susceptibility to increased water temperatures than 

the other alternatives (USDI BLM 2015, pp. 224–228, 232–233). To allocate a smaller Riparian 

Reserve would not meet the purposes of contributing to the conservation and recovery of ESA-listed 

fish and providing clean water. An alternative with a larger Harvest Land Base than the alternatives 

analyzed in detail would not meet all of the purposes of the action. 
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25. Comment Summary: The RMP should consider an alternative that would choose the 50 percent of 

the moist forest landscape with the highest structural complexity weighted by the value of a 

structurally-complex forest at that location. Management activities in this SC area can only promote 

or enhance the structural complexity of these stands. We envision that these large blocks of 

structurally-complex forest will migrate across the landscape as adjacent stands mature and become 

more ecologically valuable. Structurally-complex stands that fall out of the “best 50 percent” are 

available for variable retention harvest. Treat all dry forest stands that are not on a trajectory to 

achieve historic fire resilience within the next 30 years.

Response: The Proposed RMP/Final EIS added discussion of this suggested alternative as an 

alternative considered but not analyzed in detail (see Chapter 2). 

26. Comment Summary: The RMP should include an additional alternative which increases habitat for 

wildlife associated with early successional forests.

Response: The range of alternatives in an EIS for an RMP must present reasonable alternatives to 

accomplishing the stated purpose and need for action. Habitat for wildlife associated with early 

successional forests is not one of the purposes for the action. The commenter does not explain how 

such an alternative would better respond to the purpose and need for action than the alternatives 

analyzed. Nevertheless, under all alternatives, the amount of early successional forest habitat would 

increase in abundance in 50 years. The commenter does not identify a need for a larger increase in the 

abundance of early successional forest habitat than would occur under the alternatives analyzed. 

27. Comment Summary: All alternatives fall short of the requirement of the O&C Act when it comes to 

minimum harvest levels. Harvest levels and annual sale quantities (ASQs) need to be evenly 

distributed throughout the entire 2.4 million acres of BLM managed territory.

Response: The O&C Act does not establish a minimum harvest level. As explained in the Draft 

RMP/EIS, the O&C Act requires that the BLM offer for sale annually “... not less than one-half 

billion feet board measure, or not less than the annual sustained-yield capacity when the same has 

been determined and declared ...”(emphasis added). Previous BLM planning has determined and 

declared the annual sustained-yield capacity, as does this RMP revision, rendering obsolete the 

requirement to offer for sale “... not less than one-half billion feet board measure.” The O&C Act 

does not establish a minimum harvest level in determining and declaring the annual sustained-yield 

capacity or how timber harvest should be distributed within the O&C lands. 

28. Comment Summary: Sub‐alternative B should be considered as a separate alternative on the issue of 

climate change because it decreases the Harvest Land Base and increases reserve areas.

Response: As explained in the Draft RMP/EIS, Sub-alternative B is identical to Alternative B with 

the sole exception that Sub-alternative B included protection of the northern spotted owl habitat in all 

known and historical northern spotted owl sites (USDI BLM 2015, p. 53). The Draft RMP/EIS 

explained that the BLM focused the analysis of Sub-alternative B on the effects on timber production 

and northern spotted owls, because the modification from Alternative B would vary the approach to 

an element of northern spotted owl conservation, and the change in the sub-alternative would directly 

and explicitly alter the approach to timber production (USDI BLM 2015, p. 34). Sub-alternative B is 

almost identical in design to Alternative B, which is analyzed for all resources addressed in the Draft 

RMP/EIS, including climate change. The BLM NEPA Handbook explains that an alternative need not 
1856 | P a g e

be analyzed in detail if it is substantially similar in design to an alternative that is analyzed in detail 

(USDI BLM 2008, p. 52). Therefore, Sub-alternative B need not be fully analyzed for all resources, 

such as climate change. 

29. Comment Summary: The action alternatives will open to timber harvest between 54 and 81 percent 

(509,000–780,000 acres) of the existing Riparian Reserve acreage, with the amounts varying by 

Alternatives A through D. The proposed DEIS alternatives will open Riparian Reserve acreage to 

timber harvest, either through transfer to commercial logging lands (“Matrix” lands) or by allowing 

heavy thinning (75–80 percent tree removal) in the outer zone of the Riparian Reserve.

Response: This analysis in this comment from NMFS is incorrect and fundamentally 

mischaracterizes the land use allocations of the action alternatives. The commenter erroneously 

assumed that all acres that would be in the Riparian Reserve under No Action alternative but not 

under the action alternatives would be reallocated from Riparian Reserve to Harvest Land Base. In 

fact, most acres that would be within the Riparian Reserve under the No Action alternative but are not 

in the Riparian Reserve under action alternatives would be in Late-Successional Reserve or other 

reserve allocations under the action alternatives, and are not “open to timber harvest.” The Harvest 

Land Base in the action alternatives would range from 14 to 30 percent of the BLM-administered 

lands. The data provided in the Draft RMP/EIS demonstrates the error of the commenter’s analysis 

clearly. For example, the commenter claims that 555,662 acres would be “Transferred to matrix [sic] 

lands” under Alternative B; Table 2-5 in the Draft RMP/EIS shows that the Harvest Land Base in 

Alternative B, in its entirety, is only 556,335 acres. As noted in the Draft RMP/EIS, the Harvest Land 

Base in Alternative B (556,335 acres) would be substantially smaller than the Matrix under the No 

Action alternative (691,998 acres) (USDI BLM 2015, pp. 29, 47). In a December 18, 2015 letter from 

NMFS to the BLM, NMFS acknowledged that these comments were in error and asked that they be 

ignored. 

This comment from NMFS mischaracterizes Riparian Reserve thinning in both the No Action 

alternative and the action alternatives. The phrase “heavy thinning” is undefined and open to multiple 

interpretations. Characterizing thinning solely by the number of trees removed— “(75–80 percent tree 

removal)”—is not informative without additional stand metrics because of the variation in tree sizes 

in different stand conditions. The BLM included management direction that required that thinning 

retain both a threshold amount of canopy cover and a density of trees per acre. Alternatives B and C 

include management direction that requires that thinning in the outer zone of the Riparian Reserve 

must maintain at least 50 percent canopy cover and 80 trees per acre. The requirement to maintain at 

least 50 percent canopy cover ensures that at least half of the canopy of the stand would remain after 

thinning. Alternatives A and D include management direction that requires that Riparian Reserve 

thinning in the outer zone of the Riparian Reserve must maintain at least 30 percent canopy cover and 

60 trees per acre (USDI BLM 2015, pp. 946, 959, 972, 981). 

The commenter erroneously characterizes the entire outer zone in the Riparian Reserve in all action 

alternatives as “heavy thinning in RR allowed.” The action alternatives have specific and limited 

purposes for thinning the Riparian Reserve, which would not be relevant in most stand and site 

conditions. For example, given the management direction for thinning in the action alternatives, such 

thinning would rarely if ever be needed or appropriate in mature or structurally-complex stands, 

which currently comprise half of the acreage within one site-potential tree height of streams (USDI 

BLM 2015, p. 225). The Draft RMP/EIS explained that the analysis modeled timber harvest in the 

outer zone under the action alternatives only in stands 30–80 years old (USDI BLM 2015, p. 1028). 

Even in younger, managed stands, many stands would not need thinning for the purposes described in 

the management direction. The Draft RMP/EIS further explained that the analysis assumed only a 
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portion of the eligible acres would be thinned under the action alternatives, ranging from 15 percent 

under Alternatives A and D to 50 percent under Alternatives B and C, in light of the differing 

purposes for outer zone thinning in those action alternatives (USDI BLM 2015, pp. 1029–1033). 

Notwithstanding these statements and analysis in the Draft RMP/EIS, the commenter mistakenly 

asserts that all of the outer zone would be “open to timber harvest” under the action alternatives. 

This comment from NMFS erroneously characterizes that there would be no “heavy thinning”

allowed in the Riparian Reserve under the No Action alternative. The BLM and U.S. Forest Service 

implementation of the Northwest Forest Plan has routinely included thinning similar to that described 

for the action alternatives over the past 20 years of implementation. As stated in the Draft RMP/EIS, 

the BLM has thinned 17,461 acres within the Riparian Reserve since 1995 (USDI BLM 2015, p. 

219). In fact, the modeling for the analysis in the Draft RMP/EIS reveals that the acreage of Riparian 

Reserve thinning would increase from current levels if the BLM were to adopt the No Action 

alternative, resulting in approximately 31,407 acres of Riparian Reserve thinning in the next decade. 

Notwithstanding this empirical information and modeling results, the commenter characterizes the 

entirety of the Riparian Reserve under the No Action alternative as a ‘no-cut’ area. The modeling for 

the analysis in the Draft RMP/EIS further shows that the acreage of Riparian Reserve thinning would 

be substantially higher under the No Action alternative than for any of the action alternatives, which 

would range from 3,655 to 15,958 acres of Riparian Reserve thinning in the next decade. In a 

December 18, 2015 letter from NMFS to the BLM, NMFS acknowledged that these comments 

misrepresented the implementation of the Northwest Forest Plan and asked that these comments be 

ignored. 

30. Comment Summary: General descriptive sections of riparian management in the DEIS assert that 

tree removal in the outer Riparian Reserve will be in the upwards range of 75–80 percent removal 

(e.g., 60–80 TPA retention in stands that average 316 TPA DEIS Figure 3-51) whereas the analytical 

section of the DEIS indicates about 62 percent average removal (i.e., 120 TPA retention/196 TPA 

removal—see DEIS Table C-12). Further, in some instances the amount of tree removal is described 

in terms of canopy cover, whereas elsewhere it is described in terms of relative density.

Response: The commenter confuses management direction, which provides rules for implementation, 

with analytical assumptions about reasonably foreseeable implementation used in the modeling. For 

example, Alternative A includes management direction to “Thin stands as needed to ensure that 

stands are able to provide stable wood to the stream. Maintain at least 30 percent canopy cover and 60 

trees per acre expressed as an average across the riparian reserve portion of the stand” (USDI BLM 

2015, p. 946). The restrictions of 30 percent canopy cover and 60 trees per acre are not analytical 

assumptions or targets, but minimum thresholds that cannot be exceeded. The BLM described 

Riparian Reserve stand thinning thresholds in the action alternatives by canopy cover and trees per 

acre at the express request of NMFS staff working with the Riparian Technical Team (see Chapter 4). 

The commenter misreads Table C-12 in the Draft RMP/EIS, which clearly states a modeling 

assumption for the Riparian Reserve of pre-commercial thinning to 120 trees per acre. This is not the 

commercial thinning resulting in tree removal from the Riparian Reserve. As explained in Appendix 

C – Vegetation Modeling and in the Glossary, pre-commercial thinning is the practice of reducing 

the density of trees within a stand, in which the trees killed are generally not merchantable and are not 

removed from the treated area (USDI BLM 2015, pp. 889, 1012). 

The commenter correctly notes that the effects analysis and management direction describe a variety 

of different measures of stand conditions, but does not assert that the Draft RMP/EIS used any 
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inappropriate measures or suggest any alternative measures. The Draft RMP/EIS included different 

measures of stand conditions where appropriate for different purposes. 

31. Comment Summary: The stated purpose for ‘restoration’ thinning in Riparian Reserve is to create 

structurally-complex forest habitat (Alternatives B and C), to produce large wood that is of a size 

sufficient to remain ‘stable’ in streams (Alternatives A and D), to reduce fire risk (Alternative A) or 

the non-conservation goal of allowing for commercial harvest (Alternatives A, B, C, and D), but 

specific criteria or determining when such ‘restoration’ is needed are lacking.

Response: The commenter is correct in identifying the purposes of Riparian Reserve thinning to 

create structurally-complex forest habitat or to reduce fire risk in Alternatives B and C, to produce 

large wood that is of a size sufficient to remain ‘stable’ in streams, or reduce fire risk in Alternatives 

A and D. However, the commenter is in error in stating that the action alternatives have a goal of 

allowing for commercial harvest in the Riparian Reserve. The action alternatives would allow the 

BLM to make merchantable timber from thinning in the outer zone of Riparian Reserve available for 

sale under some circumstances, but only as a by-product of thinning needed to accomplish the 

purposes described above. The allowance to use commercial harvest to accomplish Riparian Reserve 

objectives does not differ under the No Action alternative and the action alternatives, though the 

specific restoration purpose of that thinning differs. Commercial timber harvest is not a goal of the 

Riparian Reserve under the No Action alternative or any of the action alternatives. 

The action alternatives and the Proposed RMP contain management direction that specifies when and 

where the BLM would implement Riparian Reserve thinning. The BLM would determine whether a 

specific Riparian Reserve stand needs thinning consistent with the management direction of the 

approved RMP as part of project-level design and analysis. 

32. Comment Summary: Fixed width riparian retention figures do not allow for adaptive management 

practices that account for unique features within each management area.

Response: The Northwest Forest Plan explicitly provided for adaptive modification of Riparian 

Reserve widths. This provision in the Northwest Forest Plan failed to result in adaptive modification 

of Riparian Reserve widths. The Proposed RMP includes Riparian Reserve widths that vary by 

classes of subwatersheds. However, neither the Proposed RMP nor the action alternatives would 

allow for adaptive modification of Riparian Reserve widths without an RMP amendment. Providing a 

fixed width of Riparian Reserve is consistent with the guidance for the development of the 

alternatives described in the Draft RMP/EIS, which directed that the BLM develop alternatives to 

provide a high degree of predictability and consistency about implementing land management actions 

and a high degree of certainty of achieving management objectives (USDI BLM 2015, p. 12). 

33. Comment Summary: The BLM failed to consider a full range of alternatives related to wildfire and 

fuels management. The BLM later states, “All of the alternatives have similar management objectives 

and management direction regarding noncommercial natural hazardous fuels reduction treatments. 

Therefore, the BLM assumed in this analysis that similar types and amounts of treatments that have 

occurred over the past decade would continue in the future under any of the alternatives...” In 

essence, this is a “No Action Alternative” and for this reason the BLM needs to revise the RMP/DEIS 

because it did not consider a range of alternatives for fire. While the BLM asserts there would be no 

difference between alternatives relative to wildfire response, it is ignoring that the differences are 

there given the variations in Late Successional Reserve; post fire management of Late Successional 
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Reserve; snag retention; and, the variations in road systems. The BLM needs to address wildfire 

response both in the context of active fire as well as post fire activities.

Response: The alternatives considered in the Draft RMP/EIS do not vary the approach to natural 

hazardous fuels reduction treatments or wildfire management. The BLM treats natural hazardous 

fuels based on existing fuel hazards and operational constraints. The BLM has no basis for an 

alternate approach to treating natural hazardous fuels that would result in different effects on standlevel fire resistance, fire hazard, or landscape fire resilience, and the commenter suggests no alternate 

approach. The Draft RMP/EIS explained that increasing landscape-level fire resilience and standlevel fire resistance and decreasing stand-level fire hazard would increase the effectiveness of 

hazardous fuels treatments, and the alternatives do consider a range of approaches related to 

resilience, resistance, and hazard. However, it is not possible to determine any specific change in the 

effectiveness of hazardous fuels treatments resulting from the alternatives (USDI BLM 2015, pp. 

211–212). 

The alternatives considered in the Draft RMP/EIS do not vary the approach to wildfire management. 

The Draft RMP/EIS explained that the full range of wildfire response tactics would be available under 

all alternatives, and the maintenance of fire suppression-related infrastructure would not change 

among alternatives (USDI BLM 2015, p. 212). The BLM has no basis for an alternate approach to 

wildfire management that would result in different effects, and the commenter suggests no alternate 

approach. The commenter asserts, without foundation, that differences in Late Successional Reserve,

post-fire management of Late-Successional Reserve, snag retention, and the variations in road 

systems would result in difference in wildfire management. 

The BLM does not agree that the allocation of lands to the Late-Successional Reserve in and of itself 

would have any measurable or meaningful effect on wildfire management, and the commenter does 

not explain how they believe that the allocation of lands to the Late-Successional Reserve would 

affect wildfire management. 

Snag retention requirements in post-fire management in the Late-Successional Reserve that leave 

snags in place could pose operational challenges for wildfire management if such stands experience 

an additional future wildfire. As noted in the Draft RMP/EIS, the BLM would be able to conduct 

salvage harvest for purpose of protecting human safety under all alternatives (USDI BLM 2015, p. 

212). Nevertheless, any difference in the abundance of snags in a particular stand in the LateSuccessional Reserve, either because of not conducting salvage harvest or in response to snag 

retention requirements, would represent a very small portion of the overall landscape. As noted in the 

Draft RMP/EIS, approximately 153,500 acres of the decision area have burned in the last 44 years, 

with 16 percent of the area burning twice (USDI BLM 2015, pp. 1051–1052). The acreage that has 

experienced two wildfires over nearly half a century constitutes less than 1 percent of the decision 

area. Any difference in wildfire management because of wildfire reoccurring in such stands in the 

Late-Successional Reserve and posing operational challenges in wildfire management would be small 

in extent, immeasurable, and speculative. 

Finally, the commenter contends that differences in road systems under the alternatives would alter 

wildfire management. As detailed in the Draft RMP/EIS, the alternatives would result very small 

increases in the road network, the differences in the amount of new road construction among the 

alternatives would be negligible relative to the extent of the existing road network, and the BLM has 

no reasonable basis on which to forecast any difference among the alternatives in the amount of road 

decommissioning that the BLM would implement. As a result, there is no basis upon which the road 

system would differ under the alternatives in way that would measurably or meaningfully affect 

wildfire management. 
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In summary, the BLM analyzed in detail the full spectrum of alternatives that would accomplish the 

purpose of the action. The BLM has no apparent basis for an alternate approach to natural hazardous 

fuels reduction or wildfire management, and the commenter suggests none. Constructing a 

hypothetical variation in approach to natural hazardous fuels reduction or wildfire management would 

not improve the analysis of the effects of the alternatives and is not essential to a reasoned choice 

among the alternatives. 

Proposed RMP 

34. Comment Summary: Recommend fish stream Riparian Reserve be defined as 50 percent of the site 

potential tree height, with a suggested 70–105’ width on each side. These are similar, but wider, to the 

Oregon Forest Practices Act buffers, which Watershed Research Cooperative science finds 

sufficiently protects fish and water. Recommend non‐fish stream treed buffer be defined as 30 percent 

of Site Potential Tree height, with a suggested 30’–50’ width each side. These are similar, but wider, 

to the OR Forest Practices Act buffers, which Watershed Research Cooperative science is finding 

sufficiently protects fish and water. Riparian Reserve buffer widths should be defined as slope 

distance. Active management of riparian areas should be encouraged to promote habitat diversity, 

productivity and function for the designated use—fish or domestic or irrigation. Small non‐fish 

streams need only minimal buffering—primarily limited machine/log skid activity, wildlife tree 

location, two to four wildlife trees/acre along a stream, vegetation retention, hardwood and 

reforestation incentives, etc. Fish streams without salmon, steelhead or bull trout should receive a 

significantly narrower Riparian Reserve buffer.

Response: Alternative C allocated the smallest Riparian Reserve of any of the alternatives. The 

analysis in the Draft RMP/EIS identified lower potential wood supply and more susceptibility to 

increased water temperatures than the other alternatives (USDI BLM 2015, pp. 224–228, 232–233). 

The Riparian Reserve widths and management recommended by the commenter would be smaller 

than the Riparian Reserve in Alternative C and would result in less potential wood supply to streams 

and a greater risk of stream temperature increases than Alternative C. Furthermore, the lack of a 

buffer on “small non-fish streams,” as recommended by the commenter, would result in sediment 

delivery to streams that would not meet the purposes of contributing to the conservation and recovery 

of ESA-listed fish and providing clean water. The 2008 FEIS concluded that even a more substantial 

buffer on non-fish-bearing streams would pose a risk of increased fine sediment delivery to streams 

from harvest units (USDI BLM 2008, pp. 765). To allocate a Riparian Reserve as suggested by the 

commenter would not meet the purposes of contributing to the conservation and recovery of ESAlisted fish and providing clean water. 

35. Comment Summary: The State requests that the management practices in the RMP align with the 

Statewide Riparian Management Policy that “sustain streamside and wetland riparian functions that 

support desirable water quality, native fish populations, and wildlife across the state.” Those practices 

may include recruitment of large woody debris to the stream channel, maintaining shade, capturing 

fine sediment, thermal heterogeneity, and physical habitat complexity and connectivity.

Response: The Proposed RMP would “sustain streamside and wetland riparian functions that support 

desirable water quality, native fish populations, and wildlife across the state.” The analysis in the 

Proposed RMP/Final EIS concludes that the Proposed RMP would be as effective as or more 
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effective than all other alternatives, including the No Action alternative, in protecting water quality, 

fish habitat, and riparian habitat (see the Fisheries, Hydrology, and Wildlife sections of Chapter 3). 

36. Comment Summary: The U.S. Fish and Wildlife Service supports the Riparian Reserve approach 

embodied in Alternative A because it provides significant protection for stream shading, sediment 

delivery and aquatic species, while providing more opportunities for restoration forestry projects than 

the design in the other alternatives, including Alternative D.

Response: The Proposed RMP incorporates a Riparian Reserve approach similar to Alternative A for 

streams in Class I and Class II subwatersheds, as described in Chapter 2 of the Proposed RMP/Final 

EIS. The BLM developed this Riparian Reserve approach for the Proposed RMP together with the 

U.S. Fish and Wildlife Service, National Marine Fisheries Service, and Environmental Protection 

Agency, as described in Chapter 4 of the Proposed RMP/Final EIS. 

37. Comment Summary: The process for identifying and managing Key Watersheds should be refined. 

The existing network of Key Watersheds on BLM land does not align well with those areas which are 

the most important for listed fish, and also does not align well with source water watersheds (those 

that provide drinking water). Watersheds containing both high intrinsic potential (HIP) habitat for 

coho salmon or steelhead and critical habitat should receive specific management consideration by 

being managed to minimize risk to shade, temperature, and large wood inputs, and maximize 

certainty around achievable outcomes. This can be accomplished by a strategy built around the 

concepts included in Alternatives A or D. In watersheds that contain neither HIP nor critical habitat, 

intermittent and non‐fish bearing streams should be managed to ensure the protection and 

maintenance of water quality; those streams in “non‐key” watersheds should at a minimum receive 

protection consistent with the riparian strategy presented in Alternative B.

Response: The BLM has addressed the concept of Key Watersheds in the Proposed RMP by varying 

the Riparian Reserve design and management based on the importance of the watershed to ESA-listed 

fish. The BLM developed this Riparian Reserve approach for the Proposed RMP together with the 

U.S. Fish and Wildlife Service, National Marine Fisheries Service, and Environmental Protection 

Agency, as described in Chapter 4 of the Proposed RMP/Final EIS. Under the Proposed RMP, the 

Riparian Reserve design in subwatersheds that are important to ESA-listed fish is based on the 

management concepts in Alternatives A and D, as detailed in Chapter 2 of the Proposed RMP/Final 

EIS. The BLM based this delineation on critical habitat and high intrinsic potential streams, as the 

commenter recommends. Under the Proposed RMP, the Riparian Reserve design in watersheds that 

do not have critical habitat for fish or high intrinsic potential streams is based on the management 

concepts in Alternatives B and C for non-fish-bearing intermittent streams in watersheds, as the 

commenter recommends. 

38. Comment Summary: The FEIS/Proposed RMP should clarify how watershed analysis will be 

brought forward in RMP implementation. Watershed‐scale information is critical for decision‐makers 

to establish the contextual basis for land use activities. In the BLM’s equivalent of watershed 

analysis, the FEIS should include additional detail about how watershed information will be utilized 

and incorporated in the implementation of the RMP.

Response: The BLM has addressed the concept of watershed analysis in Appendix X – Guidance for 

Use of the Completed RMPs in the discussion of watershed-scale information for implementation 

actions. 
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39. Comment Summary: The State recommends Best Management Practices related to roads specify 

that new and replacement stream crossing structures will be consistent with ODFW fish passage laws 

in the RMP.

Response: The Proposed RMP includes management direction and Best Management Practices that 

ensure that new and replacement stream crossing structures would be consistent with both fish and 

aquatic organism passage criteria set forth by NMFS and Oregon State fish passage laws (Appendix 

B – Management Objectives and Direction, Appendix J Appendix I – Best Management Practices).

40. Comment Summary: The BLM should not conduct salvage logging after natural disturbances in 

Key Watersheds, Riparian Reserve, Late Successional Forest Reserve, and designated critical habitat 

of listed species. Scientific consensus on the inadvisability of post disturbance logging largely 

emerged in the years just after FEMAT, hence it is incumbent on BLM to strengthen aquatic 

protections. It is incumbent on BLM to explain its rationale if it chooses to not implement such 

recommendations to improve watershed, water, and fish resource pr

‐

otection from post fire logging.

Response: The Proposed RMP prohibits salvage logging after disturbances in the Late-Successional 

Reserve and Riparian Reserve, except when necessary to protect public safety, or to kee

‐

p roads and 

other infrastructure clear of debris (Appendix B – Management Objectives and Direction). This 

prohibition is consistent with the management objectives of maintaining and developing habitat for 

northern spotted owls and contributing to the conservation and recovery of ESA-listed fish species 

and their habitats and providing for conservation of Bureau Special Status fish and other Bureau 

Special Status riparian associated species, respectively. In the Harvest Land Base, including portions 

of designated critical habitat within the Harvest Land Base, the Proposed RMP directs timber salvage 

harvest after disturbance events, with restrictions and requirements, to recover economic value and to 

minimize commercial loss or deterioration of damaged trees. The management objectives for the 

Harvest Land Base focus on timber production, and specifically include recovering economic value 

from timber harvested after disturbance, such as a fire, windstorm, disease, or insect infestations. 

Therefore, it would be inconsistent with the management objectives to prohibit timber salvage in the 

Harvest Land Base, whether it is within a watershed with designated critical habitat or not. The BLM 

forecasted salvage harvest in the Harvest Land Base in the vegetation modeling. The BLM would 

implement such salvage harvest in the Harvest Land Base consistent with management direction 

regarding retention of live trees and snags and reforestation (Appendix B – Management Objectives 

and Direction). In addition, the Riparian Reserve management along all streams would ensure that 

salvage harvest in the Harvest Land Base, like green tree harvest in the Harvest Land Base, would 

have no effect on ESA-listed fish. 

41. Comment Summary: All alternatives of the RMP should maintain and expand the Adaptive 

Management Area network. Building collaborative process into the mandates of the BLM will build 

trust, encourage transparency, and create more positive outcomes from local land management 

projects. More specifically, the Applegate Valley AMA should be maintained.

Response: The BLM encourages and supports collaborative processes to support local land 

management projects. The Proposed RMP/Final EIS includes discussion of the adaptive management 

process and how the BLM will use adaptive management in the implementation of the RMP. 

However, the BLM does not believe that a separate land use allocation is needed to support such 
1863 | P a g e

collaborative processes. Nothing in the Proposed RMP would preclude the continued collaborative 

process that has been developed associated with the Applegate Valley Adaptive Management Area. 

42. Comment Summary: The BLM should adopt an alternative that minimizes carbon emissions and 

timber harvest and maximizes forest carbon storage.

Response: The BLM has developed the Proposed RMP to be the best approach to meeting all of the 

purposes of the action. Maximizing carbon storage and minimizing greenhouse gas emissions are not 

among the purposes of the action. As explained in the Draft RMP/EIS, the BLM has no specific legal 

or regulatory mandate or policy direction to manage BLM-administered lands for carbon storage. In 

addition, the BLM has various climate-related policies, but none provides an authority for the BLM to 

manage the decision area to minimize carbon emissions above the statutory mandate to manage for a 

sustained yield of timber (USDI BLM 2015, pp. 79–80). 

The BLM has broad authority to analyze and address through the planning process the causes of 

climate change, the effects of the alternatives on carbon storage and greenhouse gas emissions, and 

the effects of climate change combined with the effects of the alternatives. Nevertheless, this broad 

authority does not equate to a specific mandate to minimize greenhouse gas emissions or maximize 

carbon storage. Furthermore, the BLM cannot stretch its mandate to provide a sustained yield of 

timber to encompass maximizing carbon storage or minimizing greenhouse gas emissions. 

The Draft RMP/EIS analyzed the effects of the alternatives on carbon storage and greenhouse gas 

emissions. That analysis demonstrated that there is a general trade-off between the level of sustainedyield timber production and the level of carbon storage and that the level of sustained-yield timber 

production and associated prescribed burning generally would reflect the level of greenhouse gas 

emissions. As such, the management approach that would maximize carbon storage and minimize 

greenhouse gas emissions would be the No Timber Harvest reference analysis, which would not be a 

reasonable alternative (USDI BLM 2015, pp. 132–140). To the extent that carbon storage represents a 

trade-off with sustained-yield timber production, managing for carbon storage would frustrate the 

BLM’s ability to provide for a sustained yield of timber. 

43. Comment Summary: The FEIS should map connectivity corridors, climate refugia, and include 

these areas in Wild and Scenic and Wilderness Study Area proposals to build a robust climate 

conservation strategy.

Response: It would not be appropriate to include connectivity corridors and climate refugia in Wild 

and Scenic River and Wilderness Study Area proposals, as the commenter recommends. 

As explained in the Draft RMP/EIS, in order to be eligible for inclusion into the National Wild and 

Scenic River System, a river segment must be free flowing and contain at least one river-related value 

considered outstandingly remarkable. Under the 1995 RMPs, the BLM found 51 river segments 

eligible. The BLM further evaluated each eligible river segment to determine whether it is suitable for 

inclusion into the National System. The suitability analysis provides the basis for determining which 

rivers to recommend to Congress as potential additions to the National System. The BLM has 

identified six segments that the BLM believes meet the suitability criteria for inclusion in the National 

Wild and Scenic River System (USDI BLM 2015, pp. 847–851). However, connectivity corridors and 

climate refugia are not among the criteria for establishing suitability criteria for inclusion in the 

National Wild and Scenic River System. 
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As explained in the Draft RMP/EIS, the BLM’s authority to conduct wilderness reviews, including 

the establishment of new Wilderness Study Areas, expired on October 21, 1993, pursuant to Section 

603 of the FLPMA. The BLM retained the authority under Sections 201 and 202 of the FLPMA to 

inventory wilderness characteristics and to consider such information during land use planning (USDI 

BLM 2015, p. 371). However, connectivity corridors and climate refugia are not among the criteria 

for evaluating wilderness characteristics. 

Effects Analysis 

44. Comment Summary: The 50-year time frame that all models are based on is unrealistic because of 

so many other variables that could be happening in 50 years to change all the circumstances.

Response: The time frames for the analysis of effects vary by issue. However, the BLM did analyze 

many issues over a 50-year time frame. This time frame for analysis is necessary to address the longterm effects of the agency action, which is required by the Council on Environmental Quality 

regulations for implementing the National Environmental Policy Act (40 CFR 1502.16). The BLM 

NEPA Handbook instructs that the time frames for analysis should be based on the duration of the 

direct and indirect effects of the proposed action and alternatives, rather than the duration of the 

action itself (USDI BLM 2008, p. 58). In addition, analyzing effects over this long time frame helps 

illuminate differences among the effects of the alternatives that may not be apparent over shorter time 

frames. 

45. Comment Summary: The BLM has chosen to bypass or avoid independent peer review of the 

scientific information contained in the DEIS. All models and scientific assessments contained in the 

DEIS should undergo independent scientific peer review.

Response: There is no requirement under NEPA or the BLM planning regulations for an agency to 

conduct peer review on an RMP/EIS. In 2004, the Office of Management and Budget (OMB) issued a 

memorandum requiring peer review for government science documents under the authority of the 

Information Quality Act. That memorandum gave examples of the types of science assessments that 

would require peer review, including “state-of-science reports; technology assessments; weight-ofevidence analyses; meta-analyses; health, safety, or ecological risk assessments; toxicological 

characterizations of substances; integrated assessment models; hazard determinations; or exposure 

assessments” (Office of Management and Budget 2004, p. 11). An RMP/EIS does not constitute a 

government science document for the purposes of that OMB memorandum. 

The BLM NEPA Handbook explains, 

“Analytical documents to support Federal agency decision-making include EISs and EAs, but 

neither are considered publications of scientific research subject to peer review. You may choose 

to have your NEPA analysis reviewed by members of the scientific community as part of public 

review of the document. Such review may be desirable to improve the quality of the analysis or 

share information; this does not constitute formal peer-review” (BLM 2008, p. 55). 

Although there is no requirement for peer review of an RMP/EIS, the BLM did elect to have portions 

of the Draft RMP/EIS reviewed by members of the scientific community. The Proposed RMP/Final 

EIS has added description to Appendix T – Northern Spotted Owl that details the review that the 

BLM conducted on the northern spotted owl analytical methodology. 
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46. Comment Summary: RMP uses the wrong baseline in annual timber harvest in Alternatives, leading 

to false results. The Socioeconomic section’s key points state: “The annual harvest value of timber, 

compared to $23 million to 2012, would increase under all alternatives.” (DRMP/EIS, page 472.) The 

baseline for comparison under NEPA is the current plan, which in the DRMP/EIS is the “No Action 

Alternative as written.” Using the correct baseline, only Alternative C would have an increase in 

value of the timber. The current implementation, as reflected in the 2012 baseline, represents a 

substantial departure from the current plan and reflects and unsustainable harvest of relatively low 

value timber with high associated logging costs.

Response: The No Action alternative presents the effects of implementing the 1995 RMPs as written. 

The Draft RMP/EIS analyzes the effects of the No Action alternative on the annual harvest value of 

timber. The analysis in the Draft RMP/EIS compared the effects of all alternatives to the current 

condition of the resource at issue—the annual harvest value of timber—and so therefore the analysis 

reflects all past timber harvest that occurred under the existing RMP. The most recent data available 

when the BLM was preparing the Draft RMP/EIS was for 2012. The analysis in the Draft RMP/EIS 

allows for comparison of the effects of the alternatives, including the No Action alternative relative to 

the conditions in 2012 and comparison of the effects of the alternatives, including the No Action 

alternative, relative to each other in the future. As evidenced by the commenter’s points, the 

commenter was able to discern accurately from the analysis in the Draft RMP/EIS the relative 

changes in value among the alternatives and compare the changes to the current condition. It is not 

clear what “false results” the commenter perceives or what information they believe the Draft 

RMP/EIS omitted. 

47. Comment Summary: The Oregon Department of Forestry is currently conducting an analysis of 

Riparian Management Areas for private forest management activities under Oregon’s Forest Practices 

Act to inform rule making by the Oregon Board of Forestry (BOF). Their decisions, which will focus 

on the watershed effects of contemporary timber harvest (active management) should be considered 

and where appropriate incorporated into the RMP/EIS for Western Oregon.

Response: On November 5, 2015, the Oregon Board of Forestry voted to develop administrative 

rules that create a 60-foot buffer on small fish-bearing streams and an 80-foot buffer on medium-sized 

fish-bearing streams. These rules do not apply to BLM-administered lands. As of the preparation of 

the Proposed RMP/Final EIS, the State of Oregon has not yet developed these administrative rules. In 

the identification of Alternative B as the preferred alternative, the BLM seeks to develop a Proposed 

RMP that would reduce the risk of adverse effects to ESA-listed fish and water quality compared to 

Alternative B. Given that the Riparian Reserve width on all fish-bearing streams under Alternative B 

would be one site-potential tree height (which generally varies from 140 to 240 feet width in the 

planning area), and that the BLM seeks to reduce the risk of adverse effects to ESA-listed fish and 

water quality compared to Alternative B, an alternative that would provide a substantially smaller 

Riparian Reserve than Alternative B would not be reasonable. 

48. Comment Summary: The BLM has a history of deliberately circumventing the Northwest Forest 

Plan and Aquatic Conservation Strategy. The Aquatic Conservation Strategy is not currently being 

followed and that the DEIS “action” alternatives will never be followed. The cumulative impacts of 

continuing to ignore these legally required, fundamental aquatic ecosystem protections must be fully 

evaluated in the FEIS.
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Response: The BLM has monitored implementation of the 1995 RMPs, consistent with the 

monitoring plans included in the 1995 RMPs. The BLM has documented this implementation 

annually through the individual district Annual Program Summaries (USDI BLM 2015, p. 21). The 

BLM implementation monitoring has found very high compliance of individual projects with the 

management direction of the RMP. This detailed record of implementation monitoring contradicts the 

commenter’s assertion that the BLM has “a history of deliberatively circumventing” the RMP. 

Regardless of whether BLM actions have deliberately circumvented the RMP as the commenter 

asserts or have complied with the 1995 RMPs as the BLM asserts, the effects of those actions are 

included in the environmental baseline used in the effects analysis (USDI BLM 2015, pp. 99, 987–

999). 

The BLM has conducted periodic RMP evaluations (USDI BLM 2012). Plan evaluations review the 

RMP to determine whether the BLM is implementing the plan decisions as expected and the 

associated NEPA analyses are still valid. The most recent plan evaluation concluded that the current 

forest management approach deviates from the RMP assumptions in the extent of timber harvest 

compared to RMP assumptions used to determine the declared ASQ, notably reduced levels of 

regeneration harvest. The plan evaluation did not find that this deviation is resultant from the BLM 

taking any actions that do not comply with the RMP or “deliberatively circumvent” the RMP. 

The commenter asserts that the BLM will never follow any of the action alternatives. The BLM 

analyzes alternatives in an RMP/EIS based on effects that are reasonably foreseeable (40 CFR 

1508.8(b)) and assumes that implementation of actions in compliance with an approved RMP are 

reasonably foreseeable future actions. Reasonably foreseeable future actions are those for which there 

are existing decisions, funding, formal proposals, or which are highly probable, based on known 

opportunities or trends (BLM 2008, p. 59). The commenter provides no foundation for their assertion 

that the BLM will never follow any of the action alternatives. Moreover, if the commenter’s assertion 

were true, it would be impossible to predict future implementation of the RMP. The commenter does 

not explain how the BLM could forecast the effects of the BLM not following the action alternatives 

in future implementation. 

49. Comment Summary: BLM’s large-scale re-formulation of the area and location of forest reserves 

calls for a fundamental re-analysis of the adequacy of the DEIS alternatives to support the habitat 

conditions necessary for recovery of listed fish and conservation of other values fish and wildlife 

species [sic]. The DEIS lacks such an analysis, ignoring without explanation that the FEMAT in 1993 

provided an exemplary template for how to conduct such analyses in a defensible way using best 

available scientific information to inform planning design and NEPA analysis of large-scale forest 

management programs.

Response: The FEMAT Report provided the information available at the time on the effects of 

various alternatives on aquatic and riparian species, which formed the basis for the analysis in the 

supplemental EIS for the Northwest Forest Plan. However, the information in the FEMAT Report 

was limited to generalized statements across a very large and diverse assessment area and the use of 

expert panels. In contrast, the Draft RMP/EIS contains detailed information on conditions within the 

much smaller planning area and conducts quantified modeling and analysis specific to the alternatives 

in the Draft RMP/EIS. The BLM based the analysis is the Draft RMP/EIS on detailed information 

that was not available when the Northwest Forest Plan was approved and presents objective, 

reproducible analytical conclusions. The analytical methodology and data in the Draft RMP/EIS is 

sound. 
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50. Comment Summary: It appears upon analysis that the BLM applies the wrong hierarchy of 

Standards and Guidelines during their implementation of their RMPs (i.e., the mapping/display 

hierarchy on ROD page A5, instead of the correct hierarchy of S&G application on ROD page C‐1) 

for the various land allocations. In short, the BLM is admitting to the public that they generally treat 

the Riparian Reserve in LSR as full on management zones. This issue relates directly to the failure to 

adequately describe and analyze the No Action alternative. In the case of the BLM RMP DEIS, the 

No Action alternative should be all of the following: what the 1995 RMPs say (as written), what they 

legally require (as amended by NWFP and ACS), and how the BLM actually implements them, 

particularly within the designated Riparian Reserve and LSR. Unlike what BLM asserts these are not 

“no holds barred” management zones. Using the correct hierarchy of S&Gs the Riparian Reserve 

protections add to LSR protections. Riparian Reserve standards are more precautionary than LSR 

standards with respect to aquatic conservation.

Response: The commenter misunderstands the data in the Draft RMP/EIS. The presentation of the 

acreage by land use allocation for the No Action alternative by two different hierarchies only 

addresses the data question of how to account for those areas that are allocated to both LateSuccessional Reserve and Riparian Reserve under the No Action alternative. As explained in the 

Draft RMP/EIS, the data presented in the Northwest Forest Plan and the 1995 RMP counted such 

acres as Late-Successional Reserve, and that data is displayed in the Draft RMP/EIS (USDI BLM 

2015, pp. 28–32). The Draft RMP/EIS further displayed the acreage data for the No Action 

alternative if such acres are counted as Riparian Reserve, to facilitate direct comparison with the 

acreage by allocation of the action alternatives (USDI BLM 2015, pp. 32–33). This display of acreage 

data does not make any statement relevant to the management direction (i.e., ‘standards and 

guidelines’) or implementation practices in the areas that are allocated to both Late-Successional 

Reserve and Riparian Reserve under the No Action alternative. The Draft RMP/EIS acknowledges 

that in these areas of overlapping allocations, the management objectives and management direction 

of both the Late-Successional Reserve and Riparian Reserve apply. 

The BLM concurs with the commenter that the No Action alternative should be “what the 1995 

RMPs say (as written).” However, the commenter’s statement that the No Action alternative should 

also be “what they legally require (as amended by the NWFP and ACS)” is mistaken. The Northwest 

Forest Plan did not amend the 1995 RMPs. The BLM developed the1995 RMPs to be consistent with 

the already-adopted Northwest Forest Plan. Thus, there is no difference between the commenter’s 

characterizations of “what the 1995 RMPs say” and “what they legally require.” The commenter 

further asserts that the No Action alternative should be “how the BLM actually implements them.” In 

the case of management within the overlapping acres of Late-Successional Reserve and Riparian 

Reserve, the BLM contends that this is the same as “what the 1995 RMPs say,” based on the 

implementation monitoring documented in district Annual Program Summaries. However, there are 

other aspects of RMP implementation—notably timber harvest in the Matrix—in which “what 

the1995 RMPs say” differs from “how the BLM actually implements them.” The BLM documented 

this difference in the most recent plan evaluation (USDI BLM 2012). The Draft RMP/EIS also 

describes this difference and explains why the No Action alternative in this RMP revision is the 1995 

RMPs as written, rather than attempting to project the current implementation practices (USDI BLM 

2015, pp. 77–79). 

The NEPA and Planning Processes 

51. Comment Summary: The purpose of the “Affected Environment” section in NEPA is to describe all 

issues and resource concerns that occur presently on the landscape, so as not to miss any type of 
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impact as well as to inform cumulative impacts analysis. The BLM must go back and describe all the 

resources that are affected by the RMP revisions in a correctly formulated “Affected Environment” 

section, before selecting “methods” for analysis. Then the BLM must evaluate all direct, indirect, and 

cumulative impacts to the affected resources. A perfect example of this is Key Watersheds. The 

Affected Environment includes a system of Tier 1 and Tier 2 Key Watersheds. The Affected 

Environment section should explain this fact as part of the baseline environmental and resource 

conditions, and present why this is so.

Response: The commenter is mistaken about the nature of the description of the Affected 

Environment in a NEPA analysis. According to CEQ regulations, 

“The environmental impact statement shall succinctly describe the environment of the area(s) to 

be affected or created by the alternatives under consideration. The descriptions shall be no 

longer than is necessary to understand the effects of the alternatives. Data and analyses in a 

statement shall be commensurate with the importance of the impact, with less important material 

summarized, consolidated, or simply referenced” (40 CFR 1502.15). 

The BLM NEPA Handbook further explains, 

“The affected environment section succinctly describes the existing condition and trend of issuerelated elements of the human environment that may be affected by implementing the proposed 

action or an alternative. ... The affected environment section of the environmental analysis is 

defined and limited by the identified issues” (USDI BLM 2008, p. 53). 

The purpose of the affected environment section is not to describe the condition and trend of all 

resources, but rather to describe the condition and trend of resources related to the identified issues. 

The Draft RMP/EIS explained that the BLM conducted scoping to help identify issues and then 

presented the preliminary issues in the Planning Criteria for public review and comment (USDI BLM 

2015, pp. 863–864). The BLM has used the results of this scoping and public involvement to define 

the issues for analysis and has structured the analysis in the Draft RMP/EIS by these defined issues, 

consistent with CEQ regulations and the BLM NEPA Handbook. 

The commenter’s assertion that the Affected Environment includes Key Watersheds demonstrates the 

commenter’s error on this matter. The Key Watersheds are a feature of the 1995 RMPs (i.e., the No 

Action alternative) and the Draft RMP/EIS describes Key Watersheds as such (USDI BLM 2015, pp. 

22–23, 27–28). The Affected Environment describes the existing condition and trend of resources. 

The resources at issue are various elements of the environment, such as water temperature, water 

flows, sediment routing, and fish habitat. The Key Watersheds identified in the No Action alternative, 

in and of themselves, do not constitute a resource needing analysis. The Draft RMP/EIS described the 

current condition and trend of these resources in all watersheds in the decision area, including the Key 

Watersheds identified in the No Action alternative (USDI BLM 2015, pp. 217–235, 286–320). The 

analysis of the No Action alternative included the management of Key Watersheds, and, to the extent 

that there are any differences in environmental effects from the designation of Key Watersheds, such 

differences are reflected in the analysis of the No Action alternative. The Proposed RMP carries 

forward the concept of Key Watersheds from the No Action alternative, in that it varies riparian 

management based on the importance of the subwatershed to the conservation and recovery of ESAlisted fish. Similarly, the analysis of the Proposed RMP in the Proposed RMP/Final EIS also reflects 

the differences in environmental effects from the designation of the three subwatershed classes, and 

reflects the difference in environmental effects of changing the Key Watershed designations in the No 

Action alternative to the three subwatershed classes of the Proposed RMP (see the Fisheries and 

Hydrology sections of Chapter 1). 
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52. Comment Summary: The BLM should have a discrete cumulative effects section, outlining effects 

of each alternative pursuant to NEPA. The BLM does not provide detail or clear rationale on its 

analysis. Its analysis of reasonably foreseeable future effects is extremely narrow. The BLM 

postpones its analysis to other district or site-specific plans. The BLM deflects its duty to analyze 

cumulative effects in the current RMP/DEIS, stating that “[t]here are other broad-scale analyses 

currently underway that the BLM considers as reasonably foreseeable actions for analyzing 

cumulative effects” (DEIS, p. 95).

Response: The CEQ regulations require that an EIS analyzes the environmental effects of the 

alternatives and defines effects as including direct and indirect effects (40 CFR 1502.16, 1508.8). The 

CEQ regulations also define cumulative impacts as “the impact on the environment which results 

from the incremental impact of the action when added to other past, present, and reasonably 

foreseeable future actions regardless of what agency (Federal or non-Federal) or person undertakes 

such other actions” (40 CFR 1508.7). The CEQ regulations do not identify any format requirements 

for cumulative effects analysis and do not require a “discrete cumulative effects section.” The BLM 

NEPA Handbook lays out the steps in cumulative effects analysis but explains that there is not a 

required format or presentation of cumulative effects (BLM 2008, pp. 57–61).

The Draft RMP/EIS explained that there is not a discrete and separate section labeled as cumulative 

effects. The discussion of effects on each resource incorporates the effects of past actions, and 

describes other present actions and reasonably foreseeable actions to provide context in which the 

BLM examined incremental effects, thus revealing the cumulative effects of the alternatives (USDI 

BLM 2015, pp. 93–94). It would not be helpful to provide a separate section labeled as cumulative 

effects in this analysis, because all of the effects of the RMP are cumulative in nature. The effects of 

the RMP on any resource are generally indirect effects that arise from the implementation actions that 

the BLM would conduct in conformance with the RMP. The analysis of effects in the Draft RMP/EIS 

does not address the effects of an individual future implementation action, but the cumulative effects 

of implementation of entire programs of actions (i.e., a collection of reasonably foreseeable future 

actions) under each alternative. The analysis addresses the cumulative effect of implementing a 

combination of multiple programs under each alternative. The analysis summarizes the effects of past 

actions in creating the current condition and trend of resources, as explained in the Draft RMP/EIS. 

The analysis incorporates the effects of reasonably foreseeable future actions by others, as explained 

in the Draft RMP/EIS. For specific issues, the analysis in the Draft RMP/EIS then evaluated how 

these effects combined to form analytical conclusions about the cumulative effects. 

For example, the analysis of marbled murrelet nesting habitat—

 Summarized the effects of past actions in creating the current amounts of nesting habitat; 

 Analyzed the combined effects of all BLM programs under the RMP that would remove 

nesting habitat over time; 

 Analyzed the effects of reasonably foreseeable future actions by others that would remove 

nesting habitat over time; 

 Analyzed the effects of forest development on BLM-administered lands in creating nesting 

habitat over time; and 

 Analyzed the effects of forest development on other lands in creating nesting habitat over 

time. 

The analysis combined all of these effects to describe the amount of nesting habitat under each 

alternative, over time, as a result of all actions that would affect nesting habitat, on BLMadministered lands and across all lands. The BLM provided reasoned conclusions about the 

cumulative effect of the alternatives on marbled murrelet nesting habitat (USDI BLM 2015, pp. 724–

730). This constitutes a complete cumulative effects analysis, consistent with CEQ regulations and 
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the BLM NEPA Handbook. To create a discrete and separate section labeled as cumulative effects 

within this analysis would provide no additional information and would not improve the quality of the 

analysis. 

The commenter mischaracterizes the statement on page 95 of the Draft RMP/EIS and provides an 

incomplete quotation. The full passage in the Draft RMP/EIS reads, “There are other broad-scale 

analyses currently underway that the BLM considers as reasonably foreseeable actions for analyzing 

cumulative effects, including the U.S. Forest Service revision of the Okanagan-Wenatchee Forest 

Plans and the Jordan Cove Energy and Pacific Connector Pipeline Project.” The Draft RMP/EIS 

proceeds to provide lengthy specific discussions of these two reasonably foreseeable future actions 

and how they are addressed in the Draft RMP/EIS (USDI BLM 2015, pp. 95–96). This passage does 

not postpone analysis to other districts or site-specific plans, as the commenter alleges, but addresses 

the cumulative effects of these other actions to the extent they are reasonably foreseeable. This 

passage specifically identifies which other broad-scale analyses are currently underway that the BLM 

considers as reasonably foreseeable actions, and specifically addresses them in this Draft RMP/EIS. 

53. Comment Summary: A monitoring plan should be included as an appendix to the FEIS/ROD. The 

monitoring plan should establish how watershed‐scale information/watershed analysis will inform 

monitoring priorities; lay out monitoring questions that will be used to inform the adaptive 

management process; and discuss how localized monitoring information will be compiled and placed 

in a broader, regional context.

Response: The Proposed RMP/Final EIS includes a monitoring plan for the Proposed RMP in 

Appendix V – Monitoring Plan for the Proposed RMPs. That appendix includes explanation of the 

RMP monitoring in the context of other, broader monitoring efforts. In addition, Appendix X –

Guidance for Use of the Completed RMPs includes discussion about how the BLM will consider and 

incorporate watershed-scale information and describes the adaptive management process. 

54. Comment Summary: In crafting this RMP, the BLM has failed to coordinate with Josephine 

County.

Response: The FLPMA requires the BLM to coordinate with local governments. Under the FLPMA, 

the BLM is required to assure that consideration is given to those state, local, and tribal plans that are 

germane in the development of land use plans for public lands, assist in resolving to the extent 

practical, inconsistencies between Federal and non-Federal Government plans, and shall provide for 

meaningful public involvement of state and local government officials. The FLPMA further states 

that land use plans shall be consistent with state and local plans to the maximum extent while 

remaining consistent with Federal law and the purpose of the FLPMA. 

The BLM reviewed the action alternatives in the Draft RMP/EIS for consistency with Josephine 

County’s Natural Resource Coordination Plan, dated February 18, 2015, and did not find any major 

apparent inconsistencies. The comment does not identify any specific areas where the action 

alternatives in the Draft RMP/EIS would be inconsistent with Josephine County plans and policies 

including the Natural Resource Coordination Plan. 

At the beginning of the RMP revision process, the BLM invited all counties within the planning area 

to be cooperating agencies in the RMP revision, consistent with 40 CFR 1501.6. Josephine County 

declined to be a cooperating agency. On April 28, 2015, the BLM again invited Josephine County to 

be a cooperating agency, but Josephine County again elected not to become a cooperating agency. 
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Sixteen counties within the planning area are cooperating agencies in the RMP revision (USDI BLM 

2015, pp. 866–867). 

55. Comment Summary: The Deer Creek Valley Natural Resources Conservation Association requested 

that they be included on the interdisciplinary team for the RMP, but was denied and told by the BLM 

that “we need to be fair to all stakeholders by providing information and the opportunity for input to 

all non‐governmental entities at the same time.” However, the fire and fuels analysis uses input from 

The Nature Conservancy, which is a non-governmental entity.

Response: The Nature Conservancy conducted analysis under contract to the BLM for the Fire and 

Fuels analysis, as explained in the Draft RMP/EIS (USDI BLM 2015, pp. 177, 1113–1114), because 

of their specialized knowledge and expertise, consistent with 40 CFR 1506.5(c). The Proposed 

RMP/Final EIS has added discussion to provide more detail about this contracted work. The Nature 

Conservancy was not on the Interdisciplinary Team and had no role in the analysis other than the 

specified analysis of landscape resilience in the Fire and Fuels section. The commenter, Mary Camp, 

representing the Deer Creek Valley Natural Resources Conservation Association requested that a 

team from the Deer Creek Valley Natural Resources Conservation Association be included on the 

Interdisciplinary Team. The BLM declined this request, informing her that including members of the 

Deer Creek Valley Natural Resources Conservation Association on the Interdisciplinary Team would 

not be fair to other stakeholders and could be inconsistent with the Federal Advisory Committee Act. 

The only members of the Interdisciplinary Team that are not BLM staff are those contractors 

described in the Draft RMP/EIS (USDI BLM 2015 pp. 177, 875). 

56. Comment Summary: The Draft EIS has little to say about the process that would lead the agency to 

decision-making regarding project design and implementation (placement) beyond generalized 

identification of expected yield. There is little direction on “where to go, when, and why.” The BLM 

should consider incorporating a spatially explicit, prioritized treatment landscape into future agency 

planning across the Medford District BLM. Such an effort could better identify restoration need, 

maximize acres treated as a primarily goal (as opposed to volume generated) and work to strategically 

achieve key goals, including the reduced risk of fire to homes in the Fuels Management Emphasis 

Area.

Response: The management direction for the action alternatives includes abundant management 

direction regarding project design and implementation “beyond generalized identification of expected 

yield.” For example, all action alternatives include management direction for Riparian Reserve that 

includes delineation of an inner zone, in which certain activities are prohibited, and an outer zone, in 

which specific restoration activities, such as stand thinning and fuels treatments, are directed for 

specific purposes. For example, all action alternatives include management direction for post-fire 

salvage harvest, which prohibits salvage harvest in some land use allocations and directs it in other 

land use allocations for specific purposes (USDI BLM 2015, pp. Appendix B). However, the action 

alternatives appropriately do not include a spatially explicit, prioritized plan for fuels treatments. Such 

implementation decisions depend upon site- and project-specific conditions that are best assessed by 

the BLM in project planning and design, rather than in the RMP revision. The Proposed RMP/Final 

EIS has added explanation of how the BLM will implement the approved RMPs (Appendix X –

Guidance for the Use of the Completed RMPs).
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Air Quality 

57. Comment Summary: RMP does not discuss techniques for reducing air quality impacts, such as use 

of forest residues in biodigestion, after disclosing that air quality will decrease under all alternatives.

Response: As explained in the Draft RMP/EIS, ‘air quality’ has a specific regulatory meaning tied to 

Smoke Sensitive Receptor Areas (SSRAs), air quality non-attainment and maintenance areas, and 

mandatory Class I areas. The Draft RMP/EIS disclosed an increased risk of adverse effects on air 

quality (USDI BLM 2015, pp. 119–120), but that does not mean that prescribed burning will result in 

degradation of overall air quality. The intent of the Oregon Smoke Management Plan is to avoid 

adverse impacts to SSRAs and mandatory Class I areas. Compliance with the Oregon Smoke 

Management Plan would adequately manage those risks prohibiting smoke intrusions into SSRAs. 

The BLM has encouraged the use of harvest residues for wood energy or other uses since 2001 as part 

of the National Fire Plan. While biodigestion is not currently available, the BLM makes biomass 

available for utilization as described in the Sustainable Energy section of Chapter 3, and, when 

economically feasible, the biomass may be utilized at one of the cogeneration facilities in the 

planning area. However, the Draft RMP/EIS explained that such use of biomass as an energy source 

remains low to non-existent due to the low value of the product, high transportation costs, and lack of 

facilities that would use the material (USDI BLM 2015, pp. 629–630). Specifically, the use of 

biodigestion on a scale that could affect the air quality analysis is not reasonably foreseeable at this 

time. One company announced plans to construct a cellulosic ethanol plant in Longview, Washington, 

but later cancelled these plans. In June 2015, the State of Oregon announced grant opportunities to 

explore the construction of new biomass heating, co-generation, manufacturing, or other facilities that 

would use woody biomass from forest and fuels management projects, but whether any new facilities 

will result from this grant opportunity and that would service any part of western Oregon is unknown. 

58. Comment Summary: The DEIS fails to address the predictable increase in wildfire from the various 

types of reserves. The DEIS fails to analyze and display the environmental and economic 

consequences of smoke pollution for wildfires and prescribed burning. Please refer to the 

January/February 2006 Journal of Forestry article titled, ‘Investment in Fuel Removals to Avoid 

Forest Fires Result in Substantial Benefits’ by C.L. Mason et al.

Response: The BLM disagrees that it is predictable that wildfires and wildfire emissions would 

increase as a result of establishing the various reserves. The Draft RMP/EIS explained that the BLM 

would conduct thinning in most of the reserves to reduce the risk of uncharacteristic wildfires and 

reduce potential wildfire spread and intensity under all action alternatives (USDI BLM 2015, pp. 

914–916). The BLM has reviewed Mason et al. (2006) and found it to be of limited applicability to 

the concern raised. Both the scientific literature and experience on recent wildfires around the western 

United States have established the economic and ecological values of thinning to reduce crown fire 

risks. While the scientific literature demonstrates the increased potential for larger and more severe 

wildfires in reserves due to changes in the fuelbed characteristics, whether that potential would be 

realized in the BLM-administered lands in the planning area is not known, since realizing that 

potential depends on ignitions, which are inherently uncertain. The literature also is clear that 

landscape context matters; some areas would remain at lower risk due to the lack of ignitions and 

alterations in surrounding fuelbeds. The Draft RMP/EIS disclosed the potential for further 

degradation in air quality arising from changes in fire season length and fire severity resulting from 

climate change (USDI BLM 2015, p. 122). 
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The Draft RMP/EIS analyzed the effects of wildfires only to the extent that wildfire would have a 

cumulative effect together with the effects of the alternatives. Wildfire is not an effect of the BLM 

action. The Draft RMP/EIS displayed the expected change in emissions from prescribed fire and 

wildfire in combination (USDI BLM 2015, pp. 118, 120). The Draft RMP/EIS analyzed smoke from 

wildfires not as an effect of the alternatives, but as a reasonably foreseeable occurrence as part of the 

cumulative effects analysis to provide context. The Proposed RMP/Final EIS has altered the analysis 

to display the expected emissions from wildfire separately from prescribed fire to distinguish the 

effects of the alternatives from other effects. The Draft RMP/EIS disclosed the potential for adverse 

impacts to Smoke Sensitive Receptor Areas, air quality non-attainment and maintenance areas, and to 

mandatory Class I areas from prescribed burning, including a discussion of wildfire smoke (USDI 

BLM 2015, pp. 119–122). 

The Draft RMP/EIS discussed the potential indirect environmental effects of emissions under the 

alternatives, considered in the context of the potential indirect environmental effects of emissions 

from wildfires (USDI BLM 2015, pp. 105–122). The commenter does not identify any indirect 

environmental effects of prescribed burning that the Draft RMP/EIS did not analyze. To ascribe 

indirect economic effects from prescribed burning would be speculative; any economic impact would 

depend on a large number of variables, such as timing and duration of the smoke, locations affected, 

and specific economic sectors potentially adversely affected. While the health effects of smoke are 

well documented in the scientific literature, the economic impacts are not. The commenter does not 

offer any information that would allow the BLM to analyze the indirect economic effect of emissions 

from prescribed burning. 

Areas of Critical Environmental Concern 

59. Comment Summary: The BLM should revise the EIS to include designation of the Hoxie Creek 

potential ACEC in all alternatives because it has been found to meet ACEC eligibility criteria, and it 

requires special management attention to protect its relevant and important values. The Hoxie Creek 

potential ACEC contains old‐growth forest that must be maintained to contribute to northern spotted 

owl recovery, has unique ecological and recreational values needing protection, and is unsuitable for 

timber production due to tree regeneration problems.

Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustained 

yield forest management in areas allocated to timber production on O&C lands.

Consistent with the authority provided by the FLPMA to designate potential ACECs, the BLM 

evaluated nominated and existing ACECs to determine whether relevant and important values are 

present and if special management is needed to maintain those values. The Hoxie Creek potential 

ACEC continues to meet the relevance and importance criteria; however, it occurs within the Harvest 

Land Base land use allocation under Alternatives B and C. The special management attention 

required to maintain the relevant and important values conflicts with the management direction of the 

Harvest Land Base, which is designed to meet the purpose and need described in Chapter 1 for 

managing O&C lands. Under Alternatives A and D, and the Proposed RMP, the Hoxie Creek 

potential ACEC occurs within the Late-Successional Reserve land use allocation, and the special 

management attention required to maintain the relevant and important values are already provided for 

by the management direction for the Late-Successional Reserve.
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Because of these reasons, the BLM would not designate Hoxie Creek potential ACEC as an ACEC 

under any alternative.

The BLM may manage areas identified as unsuitable for sustained-yield timber production (e.g., areas 

or soil conditions for which regeneration would be difficult) through the Timber Production 

Capability Classification (TPCC) system for other uses, if those uses are compatible with the reason 

for which the BLM has reserved these lands (as identified by the TPCC codes). The BLM will 

periodically add or remove areas to those areas reserved through updates to the TPCC system, when 

examinations indicate the change to be appropriate. BLM describes the TPCC system and its use in 

the Woodstock vegetation model in Appendix C – Vegetation Modeling. Neither site-specific 

evaluation by BLM staff nor the TPCC codes for the Hoxie Creek potential ACEC used in the 

Woodstock model have identified stand growth concerns warranting Hoxie Creek stands’ inclusion in 

a TPCC district-designated reserve.

Analysis of northern spotted owls, forest management, recreation, and wildlife all considered the 

lands within the potential Hoxie Creek ACEC for management by the underlying land use allocation 

by each alternative and determined impact to these resources accordingly. 

60. Comment Summary: The BLM should revise the EIS to include designation of the Upper Klamath 

and Upper Klamath Addition potential ACECs in all alternatives because BLM has determined they 

meet ACEC eligibility criteria, and require special management attention to protect their relevant and 

important values. The Upper Klamath and Upper Klamath Addition potential ACECs support 

fisheries, endangered fish, water quality, recreation, unique cultural and historic values needing 

protection by way of ACEC designation.

Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustainedyield forest management in areas allocated to timber production on O&C lands.

The Upper Klamath and Upper Klamath Addition potential ACECs has been found to contain 

relevant and important values for historical, cultural, and scenic resources; fish and wildlife resources; 

and unique ecological communities.

Consistent with the authority provided by the FLPMA to designate potential ACECs, the BLM 

evaluated nominated and existing ACECs to determine whether relevant and important values are 

present and if special management is needed to maintain those values. The Upper Klamath and Upper 

Klamath Addition potential ACECs continue to meet the relevance and importance criteria; however, 

varying portions of these ACECs overlap the O&C Harvest Land Base under the alternatives. The 

majority of the potential ACECs occur within the Harvest Land Base land use allocation under 

Alternatives B and C. The special management attention required to maintain the relevant and 

important values conflict with the management direction of the Harvest Land Base, which is designed 

to meet the purpose and need described in Chapter 1 for managing the O&C lands. The portions of 

these potential ACECs outside of the Harvest Land Base under these alternatives do not meet the 

criteria for ACEC designation. The BLM would not designate these potential ACECs under 

Alternatives B and C.
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Under Alternatives A and D, and the Proposed RMP, the vast majority of the Upper Klamath and 

Upper Klamath Addition potential ACECs occur outside of the Harvest Land Base. The BLM revised 

the boundaries of the Upper Klamath and Upper Klamath Addition potential ACECs for these 

alternatives to exclude areas in the Harvest Land Base. The revised boundaries are available for 

review on the RMP’s online Interactive Map. With these boundary revisions, the special management 

attention required for the revised Upper Klamath and Upper Klamath Addition potential ACECs 

would not conflict with managing O&C lands under Alternatives A and D, and the Proposed RMP. 

Therefore, the BLM would designate these potential ACECs under these alternatives.

Analysis of fisheries, endangered fish, water quality, recreation, and cultural resources all considered 

the lands within the Upper Klamath and Upper Klamath Addition potential ACECs for management 

by ACEC designation or by the underlying land use allocations by each alternative, and determined 

impact to these resources accordingly. The BLM incorporated protection for fisheries and water 

quality into the Riparian Reserve land use allocation and associated management direction. The 

Upper Klamath River Wild and Scenic River and the associated recreation management area provide 

for recreation opportunities in the upper Klamath River.

61. Comment Summary: The BLM should revise the EIS to include protections of municipal water 

supplies and habitat for salmonids and lamprey from mining projects proposed in and near the North 

Fork Chetco, North Fork Hunter Creek, and Hunter Creek Bog potential ACECs. The BLM should 

require coordination with the U.S. Forest Service to protect these values from mining projects 

proposed next to the Hunter Creek Bog potential ACEC.

Response: The BLM would designate the North Fork Chetco, North Fork Hunter Creek, and Hunter 

Creek Bog potential ACECs under all of the action alternatives, including the Proposed RMP. Table 

F-2 in Appendix F – Areas of Critical Environmental Concern provides information about the special 

management direction that BLM would apply to these areas upon designation. These areas would be 

open to leasable mineral entry with no surface occupancy, closed to salable mineral entry, and the 

BLM would recommend these areas to petition for withdrawal from locatable mineral entry. As such, 

mining projects within these ACECs would be required to adhere to these special management 

requirements under all action alternatives. 

In addition to the minerals management provided through special management for the ACECs, 

Appendix B – Management Objectives and Direction provides minerals management direction on all 

lands. Under the action alternatives, including the Proposed RMP, the BLM would manage lands 

within, adjacent to, and upstream from potential ACECs consistent with management direction in 

Appendix B – Management Objectives and Direction. This management direction addresses noticelevel mining proposals and Plans of Operation located within lands or waters known to contain 

proposed or ESA-listed threatened or endangered species or their proposed or designated critical 

habitat. 

Consistent with NEPA requirements, BLM would coordinate with adjacent land managers, including 

the U.S. Forest Service, on an as needed basis during site-specific project planning and during RMP 

implementation.

62. Comment Summary: The BLM should revise the EIS to expand the Wassen Creek potential ACEC 

to protect potential wilderness.
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Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustainedyield forest management in areas allocated to timber production on O&C lands. In preparation for the 

plan revisions, the BLM reviewed the Wassen Creek potential ACEC and, through this review, 

refined the boundaries to exclude areas that do not contain relevant and important values and 

incorporate other areas that do. Coincidentally, the revised Wassen Creek potential ACEC boundary 

now includes more inventoried lands with wilderness characteristics. 

Consistent with the authority provided by the FLPMA to designate potential ACECs, the BLM 

evaluated nominated and existing ACECs to determine whether relevant and important values are 

present and if special management is needed to maintain those values. Relevant and important values 

for the Wassen Creek potential ACEC include scenic, fish and wildlife, and natural process values. 

BLM describes the special management needs for these values in Appendix F – Areas of Critical 

Environmental Concern. Management for wilderness characteristics would be consistent with most, 

but not all of the special management needed for the Wassen Creek potential ACEC’s relevant and 

important values. 

The BLM would not include the management for wilderness characteristics of any inventoried lands 

with wilderness characteristics under Alternative D. In addition, under Alternative D, a portion of the 

Wassen Creek potential ACEC includes areas in the Harvest Land Base allocated to timber 

production on O&C lands. The special management attention required to maintain the relevant and 

important values conflicts with the management direction of the Harvest Land Base, which is 

designed to meet the purpose and need described in Chapter 1 for managing the O&C lands. 

Therefore, under Alternative D the BLM would revise the boundaries of the Wassen Creek potential 

ACEC to exclude areas in the O&C Harvest Land Base and would designate the remaining area as an 

ACEC. The Wassen Creek ACEC designation under Alternative D would overlap with inventoried 

lands with wilderness characteristics, and would provide some protection of those wilderness 

characteristics through special management of the ACEC. 

In contrast, under Alternatives A, B, and C, and the Proposed RMP, the BLM would include the 

management for wilderness characteristics for inventoried lands with wilderness characteristics and 

there are no O&C timberlands underlying the potential ACEC. Under these alternatives, the BLM 

would designate the revised Wassen Creek ACEC that includes the lands with wilderness 

characteristics. 

63. Comment Summary: The BLM should revise the EIS to include designation of the Moon Prairie 

potential ACEC in all alternatives because BLM determined it meets the ACEC eligibility criteria, 

and it requires special management attention to protect its relevant and important values. The Moon 

Prairie potential ACEC contains a late-successional forest with slow growing Pacific yew and is 

unsuitable for timber production due to tree regeneration problems.

Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustainedyield forest management in areas allocated to timber production on O&C lands. 
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The BLM would not designate the Moon Prairie ACEC under Alternatives A, B, C, or D. Consistent 

with the authority provided by the FLPMA to designate potential ACECs, the BLM evaluated 

nominated and existing ACECs to determine whether relevant and important values are present and if 

special management is needed to maintain those values. The Moon Prairie potential ACEC continues 

to meet the relevance and importance criteria; however, it occurs within the Harvest Land Base land 

use allocation under Alternative B. The special management attention required to maintain the 

relevant and important values conflicts with the management direction of the Harvest Land Base, 

which BLM designed to meet the purpose and need described in Chapter 1 for managing the O&C 

lands. 

Under Alternatives A, C, and D, the Moon Prairie potential ACEC occurs within the LateSuccessional Reserve land use allocation, and the special management attention required for 

maintaining the relevant and important values of the ACEC are provided by the management 

direction for the Late-Successional Reserve. Thus, designation of Moon Prairie as an ACEC is 

unnecessary to maintain the relevant and important values under Alternatives A, C, and D.

In preparation for the Proposed RMP and FEIS, BLM refined the boundaries of the Moon Prairie 

potential ACEC to remove the portion within the Late-Successional Reserve and retain the portion 

within the Harvest Land Base. Uneven-aged timber management in the revised potential ACEC 

would contribute to improving forest structure and fire resiliency. Therefore, the BLM would 

designate this smaller, refined boundary of the Moon Prairie ACEC under the Proposed RMP. 

The BLM describes the Timber Productivity Capability Classification (TPCC) and its use in the 

Woodstock vegetation model in Appendix C – Vegetation Modeling. The BLM may manage areas 

identified as unsuitable for sustained-yield timber production through the TPCC system for other 

uses, if those uses are compatible with the reason for which the BLM has reserved these lands (as 

identified by TPCC codes). Neither site-specific evaluation by BLM staff nor the TPCC codes for the 

Moon Prairie potential ACEC used in the Woodstock vegetation model have identified stand growth 

concerns warranting Moon Prairie stands’ inclusion in a TPCC district-designated reserve. The BLM 

will periodically add additional areas to those areas reserved through updates to the TPCC system, 

when examinations indicate that an area meets the criteria for reservation. 

64. Comment Summary: The BLM used an incorrect justification to determine the Umpqua River 

Wildlife Area ACEC no longer meets the ACEC criteria.

Response: The BLM did make an error in the Draft RMP/EIS explaining why the Umpqua River 

Wildlife Area ACEC no longer meets the ACEC criteria. BLM revised the rationale in the Final EIS 

to correct the error. The bald eagle is the single relevant and important value needing special 

management for the Umpqua River Wildlife Area ACEC. Over time, the bald eagle population has 

grown and the species has been delisted and BLM continues to provide protection under the Bureau’s 

Special Status Species program and the Bald and Golden Eagle Protection Act. The bald eagle and 

this population no longer meet the ACEC criteria. 

65. Comment Summary: The BLM should revise the EIS to include designation of the Spencer Creek 

potential ACEC in all alternatives because BLM determined it meets the ACEC eligibility criteria, 

and it requires special management attention to protect its relevant and important values. The Spencer 

Creek potential ACEC contains a natural ecosystem within a unique watershed and provides habitat 

for important and threatened species.
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Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves, or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustained 

yield forest management in areas allocated to timber production on O&C lands. 

Consistent with the authority provided by the FLPMA to designate potential ACECs, the BLM also 

evaluated nominated and existing ACECs to determine whether relevant and important values are 

present and if special management is needed to maintain those values. 

The Spencer Creek potential ACEC continues to meet the relevance and importance criteria; 

however, it occurs within the Harvest Land Base land use allocation under Alternatives B, C, and D. 

The special management attention required to maintain the relevant and important values conflicts 

with the management direction of the Harvest Land Base, which BLM designed to meet the purpose 

and need described in Chapter 1 for managing the O&C lands. 

Under Alternative A and the Proposed RMP, the Spencer Creek potential ACEC occurs within the 

Late-Successional Reserve and Riparian Reserve land use allocations, and the special management 

attention required to maintain the relevant and important values are already provided for by the 

management direction for the Late-Successional Reserve and Riparian Reserve. No additional 

management attention is needed to maintain the relevant and important values. 

For these reasons, the BLM would not designate the Spencer Creek ACEC under any alternative or 

the Proposed RMP. 

66. Comment Summary: The BLM should revise the EIS to designate the Baker Cypress, Cobleigh 

Road, Poverty Flat, Round Top Butte, and Table Rocks potential ACECs as closed OHV 

Management Areas to protect relevant and important values.

Response: The BLM reconsidered the designations for public motorized access for potential ACECs 

in preparation for the Proposed RMP/Final EIS. The BLM changed the designations for public 

motorized access for many areas, including Baker Cypress, Cobleigh Road, Poverty Flat, Round Top 

Butte, and Table Rocks potential ACECs to closed in the Proposed RMP. 

67. Comment Summary: Table Rocks ACEC should be retained as an ACEC and not changed to an 

RMA as the table tops are home to very rare plants and animals that would be negatively impacted by 

a recreation‐focused land use management plan.

Response: A SRMA designation ensures that the important recreation values at Table Rocks (hiking 

and environmental education) are protected through the establishment of supporting management 

actions and allowable use decisions that are reflected in the Recreation Management Area framework 

for the Table Rocks SRMA. These restrictions ensure the protection of the recreation setting 

characteristics and the relevant and important ACEC values. These designations have been analyzed 

in the Proposed RMP/Final EIS and have been found to be compatible. 

68. Comment Summary: The BLM should revise the EIS to allow neither timber harvesting nor 

vegetation management to promote the development or maintenance of late seral habitat in the Little 

North Fork Wilson potential ACEC to protect listed salmonids.
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Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustained 

yield forest management in areas allocated to timber production on O&C lands.

Consistent with the authority provided by the FLPMA to designate potential ACECs, the BLM 

evaluated nominated and existing ACECs to determine whether relevant and important values are 

present and if special management is needed to maintain those values. The special management 

attention required to maintain the relevant and important values includes vegetation management to 

promote the development and maintenance of late-seral habitat. Many forest stands within the 

potential ACEC, which might be good candidates for vegetation treatments, are less than sixty years 

old and adjacent to existing roads.

Analysis of fisheries considered the lands within the potential Little North Fork Wilson ACEC for 

management by the underlying land use allocations by each alternative and determined the impact to 

these resources accordingly. The Proposed RMP/Final EIS provides for ESA-listed fish habitat in the 

Riparian Reserve land use allocation and the associated management direction in Appendix B –

Management Objectives and Direction.

69. Comment Summary: The State recommends existing Little Grass Mountain ACEC in the BLM 

Salem District continue to be included as an ACEC in the EIS.

Response: The BLM evaluates existing, potential, and nominated ACECs to determine if they meet 

the criteria of relevance and importance as defined in 43 CFR 1610.7–2 at the beginning of land use 

planning processes. A Salem District Office interdisciplinary team evaluated the existing Little Grass 

Mountain ACEC and determined that it did not meet the importance criteria. The grassy bald at Little 

Grass Mountain does not contain any values to set it apart from other Coast Range Grassy Balds and 

therefore, does not meet the importance criteria. Little Grass Mountain did not move forward in the 

planning process to be considered as a potential ACEC and was not analyzed in the EIS because it 

does not meet the basic ACEC criteria.

70. Comment Summary: The BLM should revise the EIS to analyze the previously nominated BLM 

Tract T. 20 S., R.3 W., Sec. 31, SW 1/4 for both an Environmental Education Area (EEA) and 

Cottage Grove Old Growth ACEC designation in all alternatives. BLM omitted the nominated EEA 

from Appendix N in the Draft EIS.

Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustainedyield forest management in areas allocated to timber production on O&C lands. 

Consistent with the authority provided by the FLPMA to designate potential ACECs, the BLM also 

evaluated nominated and existing ACECs to determine whether relevant and important values are 

present and if special management is needed to maintain those values. The Cottage Grove Old 

Growth potential ACEC continues to meet the relevance and importance criteria; however, it occurs 

within the Harvest Land Base land use allocation under Alternatives A, B, and C. The special 
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management attention required to maintain the relevant and important values conflicts with the 

management direction of the Harvest Land Base, which is designed to meet the purpose and need 

described in Chapter 1 of the EIS for managing the O&C lands. The BLM would not designate the 

Cottage Grove Old Growth potential ACEC as an ACEC under Alternatives A, B, and C. The BLM 

would designate the Cottage Grove Old Growth potential ACEC under Alternative D and the 

Proposed RMP. 

Consistent with the analytical methods described on page 110 of the Planning Criteria (USDI BLM 

2014), the BLM’s inventory determined this BLM-administered tract of land is not legally accessible 

to the public. The BLM would not consider areas without legal public access as Extensive Recreation 

Management Areas (ERMAs) or Special Recreation Management Areas (SRMAs) and would not 

include them in Appendix O – Recreation.

71. Comment Summary: The BLM should revise the EIS to include designation of the former Long 

Gulch potential ACEC in all alternatives because it meets ACEC eligibility criteria, and it requires 

special management attention to protect its relevant and important values. The former Long Gulch 

potential ACEC overlays lands with wilderness characteristics and must be maintained to protect 

resident northern spotted owls and the low elevation, old‐growth forest.

Response: The BLM evaluates existing, potential, and nominated ACECs to determine if they meet 

the criteria of relevance and importance as defined in 43 CFR 1610.7–2 at the beginning of land use 

planning processes. A Medford District Office interdisciplinary team evaluated the former Long 

Gulch potential ACEC and determined that it did meet the relevance and importance criteria for 

natural systems. Only the unique trellised drainage pattern met the importance criteria because it is 

more than locally significant. The Medford District Office interdisciplinary team determined that 

maintenance of the trellised drainage pattern does not require special management. The former Long 

Gulch potential ACEC did not move forward in the planning process a potential ACEC for analysis in 

the EIS because it does not require special management. 

72. Comment Summary: The BLM should revise the EIS to retain existing ACECs because these 

ACECs contribute to protecting watersheds, regulating stream flows, contributing to economic 

stability of local communities, and provide recreational facilities as mandated in the O&C Act.

Response: The BLM considers potential ACECs for designation where special management to 

protect relevant and important values is identified as needed, where their management would not 

conflict with Congressional reserves or lands under the National Landscape Conservation System, 

and where special management to retain relevant and important values would not preclude sustainedyield forest management in areas allocated to timber production on O&C lands.

Consistent with the authority provided by the FLPMA to designate potential ACECs, the BLM also 

evaluated nominated and existing ACECs to determine whether relevant and important values are 

present and if special management is needed to maintain those values. Some potential ACECs 

continue to meet the relevance and importance criteria and occur within the Harvest Land Base land 

use allocation under some of the alternatives. Under some alternatives and potential ACECs, the 

special management attention required to maintain the relevant and important values conflicts with 

the management direction of the Harvest Land Base, which is designed to meet the purpose and need 

described in Chapter 1 for managing the O&C lands. 
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An ACEC designation is the principle BLM designation for public lands where special management 

is required to protect important natural, cultural, and scenic resources, or to identify natural hazards. 

Contributions toward meeting watershed protection, regulating stream flows, contributing to 

economic stability and recreation facility provision objectives associated with ACEC designations are 

incidental unless they have been evaluated and determined to meet the basic ACEC relevance and 

importance criteria.

73. Comment Summary: The BLM should consider the management recommendations for biological 

diversity and forest composition, structure, and function as described on page 201 of the 

Topsy/Pokegama Landscape Analysis (USDI BLM 1995) related to the relevant and important 

values’ special management need for all potential ACECs within its geographic scope when 

developing the EIS.

Response: Consistent with the authority provided by the FLPMA to designate potential ACECs, the 

BLM evaluated nominated and existing ACECs to determine whether relevant and important values 

are present and if special management is needed to maintain those values. The BLM considered the 

recommendations in the landscape analysis when evaluating areas within the geographic scope of the 

Topsy/Pokegama Landscape Analysis and when determining their need for special management 

under the alternatives.

74. Comment Summary: The EIS should be revised to include definitions for the alternative columns in 

Table F-1 of Appendix F.

Response: The Proposed RMP/Final EIS has been revised to include definitions for the alternative 

columns in Table F-1 of Appendix F – Areas of Critical Environmental Concern.

75. Comment Summary: Maintain Key Watershed designation. The designation of Key Watersheds 

identifies and prioritizes the management of areas of refugia that are crucial to at‐risk and listed fish 

species and the provision of high quality water for over 1.8 million Oregonians who rely on BLM 

land for drinking water.

Response: Chapter 1 describes how BLM would evaluate ACEC nominations, address components 

of the Aquatic Conservation Strategy, and work with the National Marine Fisheries Service, Oregon 

Department of Environmental Quality, and the Environmental Protection Agency to develop 

alternatives to facilitate Endangered Species Act consultation and to satisfy State and Federal water 

quality rules at the RMP level. Under all alternatives in the EIS, the BLM has generated the 

equivalent of watershed analysis as needed for NEPA analysis or ESA consultation for 

implementation actions taken in the future consistent with the plan.

During scoping for this revision, the BLM included in the Notice of Intent an invitation for ACEC 

nominations with a June 7, 2012 due date to ensure the nominations would be considered in the 

analysis. BLM would consider ACEC nominations after determining they meet the relevance and 

importance criteria and the relevant and important values would require special management attention 

for their protection. ACEC nominations received between the Draft EIS and preparation of the Final 

EIS are too late for consideration in this revision.

However, BLM would evaluate proposals for ACEC nominations at any time. Areas found by the 

BLM to meet the ACEC criteria and require special management attention would receive temporary 
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management including reasonable measures necessary to protect the relevant and important resource 

values from degradation until the BLM fully evaluates the potential ACEC through the resource 

management planning process.

76. Comment Summary: The State recommends the BLM revise the EIS to consider a new interagency 

ACEC nomination for “hydrologically unique watersheds that support cold water refugia to aquatic 

biota.” The BLM would collaborate with ODFW and DEQ to develop the ACEC nomination.

Response: Recommendations for a collaboratively developed ACEC nomination received between 

the Draft RMP/EIS and preparation of the Proposed RMP/Final EIS are too late for consideration in 

this revision. 

During scoping for this revision, the BLM included in the Notice of Intent an invitation for ACEC 

nominations with a June 7, 2012, due date to ensure the nominations would be considered in the 

analysis. BLM would consider ACEC nominations after determining they meet the relevance and 

importance criteria and the relevant and important values would require special management attention 

for their protection. At this time, the recommendation is not complete enough for the BLM to 

evaluate as an ACEC nomination.

However, the BLM would evaluate proposals for ACEC nominations at any time. Areas found by the 

BLM to meet the ACEC criteria and that require special management attention would receive 

temporary management including reasonable measures necessary to protect the relevant and 

important resource values from degradation until BLM fully evaluates the potential ACEC through 

the resource management planning process.

Chapter 1 describes how the BLM would evaluate ACEC nominations and how BLM would work 

with the National Marine Fisheries Service, Oregon Department of Environmental Quality and the 

Environmental Protection Agency to develop alternatives to facilitate Endangered Species Act 

consultation and to satisfy State and Federal water quality rules at the RMP level.

77. Comment Summary: The BLM should identify potential climate refugia (e.g., low elevation river 

corridors, north‐facing slopes, elevational and latitudinal corridors, and related high elevation land‐

bridges, see Olson et al. 2012) and include these in a climate‐robust reserve design as ACECs or other 

protective designations.

Response: The BLM has designed land use allocations to respond to the purpose and need. There is 

no purpose and need that would result in a designation of “climate refugia” on the landscape. The 

BLM has considered ACECs in this analysis based upon nominations received and consideration of 

special management and relevant and important values. 

Climate Change 

78. Comment Summary: The carbon analysis is superficial and misrepresents what would occur. 

Carbon calculations must account for the current amount of carbon stored in the area, the risk of loss 

due to natural events and ecosystem processes, transformation into other forms of long-term storage, 

the emissions of wood substitutes for construction and substitutes for fossil fuels, and the changing 

rates of CO2 uptake as a forest ages.
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Response: As explained in the Draft RMP/EIS (USDI BLM 2015, pp. Appendix G) the carbon 

analysis includes the current amount of carbon stored in the area, probable loss due to wildfire, and 

long-term carbon storage in harvested wood products. The BLM lacks the data necessary to evaluate 

potential carbon losses from insects and disease. Only a few studies have measured and analyzed 

carbon losses from decay (respiration) and only under specific circumstances and forest types that the 

BLM cannot extrapolate to cover the decision area. Incorporating decay rates is not a common 

practice in carbon calculations globally or nationally. The BLM incorporated carbon losses from 

thinning into the changes in volume as stands are harvested in the Woodstock model. All alternatives 

would increase carbon storage over time, indicating that carbon sequestration would occur. 

Discussion of the emissions of wood substitutes for construction material is outside the scope of this 

analysis. Discussion of the substitution of wood for fossil fuels in energy production would be 

speculative at this time, as there are no known facilities in operation, construction, or planned that 

would use wood or forest residues for biofuel production within or near the decision area. 

79. Comment Summary: The carbon analysis holds the effect of wildfire constant, which contradicts the 

findings of differences in fire resistance in the Fire and Fuels section.

Response: As stated in the Draft RMP/EIS, the Fire and Fuels section analyzed the potential impacts 

of the different alternatives on wildfire risk, but the BLM has no method to translate these changes in 

risk into meaningful differences in wildfire occurrence and wildfire effects for the alternatives (USDI 

BLM 2015, p. 212). The Draft RMP/EIS discussed the potential for additional loss of carbon due to 

increased wildfire occurrence and severity (USDI BLM 2015, p. 156). 

80. Comment Summary: The carbon storage analysis misuses the Carbon OnLine Tool (COLE).

Response: The BLM recognizes that the data available in the Carbon OnLine Tool (COLE) 

represents smoothed values and includes stands that are uneven-aged. The area the BLM analyzed 

includes uneven-aged stands and most alternatives include uneven-aged management over a portion 

of the decision area. The BLM explored various methods for estimating the carbon in the understory 

as stands age, but found no other methods that could be coupled with the volume and stand age 

information provided by the Woodstock model. Most carbon estimation procedures focus solely on 

the harvestable trees, leaving the BLM with few options to account for all components of 

aboveground carbon. The commenter does not offer an analytical methodology that they believe 

would be superior. 

The Proposed RMP/Final EIS has added comparison of these analytical results with results from other 

analyses. In comparing the estimates in the Draft RMP/EIS with the most recent estimates made by 

the U.S. Forest Service, the BLM estimates were comparable, providing confidence that the BLM’s 

methods provide a reasonable estimation of effects. As stated in the Draft RMP/EIS, different carbon 

storage analysis methods will produce different estimates (USDI BLM 2015, pp. 133, 1106). 

Although the BLM reported the estimated net carbon storage for each alternative, the BLM considers 

the relative differences between the alternatives as more informative than the absolute calculated 

values. 

81. Comment Summary: The DEIS is incomplete in not presenting the best science on carbon flux using 

regionally specific models such as Landcarb.
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Response: The BLM evaluated the use of Landcarb to estimate carbon storage for the different 

alternatives. In its present form, Landcarb can only analyze landscape-scale carbon for the western 

Cascades, which does not cover the entire analysis area. Landcarb analyzes carbon for all Federal 

lands in aggregate, which does not allow the BLM to evaluate the effects of the alternatives on the 

land base separately from other Federal lands. These two factors alone made Landcarb an unsuitable 

method for estimating carbon storage in this analysis. The Carbon OnLine Tool contains regionallyspecific data that encompasses the entire planning area. As discussed in Appendix G of the Draft 

RMP/EIS, the BLM tailored the carbon estimates by generating reports specific to the county or 

counties in which each BLM office occurs (USDI BLM 2015, pp. 1103–1104). 

82. Comment Summary: Carbon stored in wood products should not be included in the carbon 

estimates.

Response: The Intergovernmental Panel on Climate Change (IPCC) considers carbon stored in wood 

products as an important carbon pool (e.g., Chapter 4 in IPCC Guidelines for National Greenhouse 

Gas Inventories, 2006). The Environmental Protection Agency reports carbon stored in harvested 

wood products in use and in solid waste disposal sites (landfills) as a carbon sink in its annual 

greenhouse gas inventories for the United States. The BLM followed these standards in including 

carbon stored in harvested wood products as part of the carbon storage estimations. 

83. Comment Summary: The BLM should include current and regionally appropriate literature from 

Krankina et al. (2014).

Response: The BLM reviewed Krankina et al. (2014) and determined it would not add substantial 

information to the analysis. The carbon storage estimations in Krankina et al. (2014) are for 2008 and 

the data do not identify the amount of carbon estimated to occur on BLM-administered lands within 

the planning area. The BLM carbon analysis used data current as of 2013. The Proposed RMP/Final 

EIS has added discussion that places the estimated carbon storage and carbon density estimates in 

context with U.S. Forest Service lands, State of Oregon lands, and private lands. 

84. Comment Summary: The DEIS should include a recommendation for a carbon tax on logging older 

forests on BLM land in Oregon.

Response: The BLM has no authority to impose taxes. Policy recommendations by the BLM to 

Federal, State, or local government entities with the authority to impose taxes would be beyond the 

scope of a BLM RMP. 

85. Comment Summary: The RMP as proposed would contribute to climate change by reducing the 

amount of carbon stored in the ecosystem.

Response: The commenter is mistaken. The Draft RMP/EIS clearly stated that all alternatives, 

including the No Action alternative, would increase net carbon stores over time on the BLMadministered lands within the decision area (USDI BLM 2015, p. 135). The commenter identified no 

error in this analysis. 
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86. Comment Summary: The carbon section should include a literature review on the importance of 

older forests in carbon storage.

Response: A literature review of the importance of older forests for carbon storage is not necessary to 

understand the potential impacts of the alternatives on carbon storage on BLM-administered lands. 

Since the analysis includes all stands, including older stands, it includes the importance of older 

stands in carbon storage. An extensive discussion of the role of older forests in storing carbon would 

not improve the quality of the analysis or provide for a reasoned choice among alternatives. The BLM 

has not included such a literature review in keeping with CEQ direction that environmental analyses 

should not be encyclopedic in nature but should focus on the information relevant to the decisions to 

be made (40 CFR 1500.4). 

87. Comment Summary: Carbon benefits of fuel reduction logging are scientifically controversial.

Response: The BLM agrees that there is scientific uncertainty about the potential effects of 

hazardous fuels treatments on carbon storage by altering the effects of wildfire on carbon storage. The 

Draft RMP/EIS acknowledged that hazardous fuels treatments can affect wildfire risk, but the BLM 

has no method to translate these changes of risk into meaningful differences in wildfire occurrence 

and wildfire effects for the alternatives (USDI BLM 2015, p. 212). Many studies have demonstrated 

the ability of certain hazardous fuels prescriptions to reduce the potential and actual emissions from 

wildfire at the stand scale, but have not been able to provide the same evidence at the landscape scale, 

largely due to the lack of sufficiently sized fuels treatments to test hypotheses. Most analyses 

examining the carbon implications of thinning to reduce wildfire emissions are conducted using a 

static climate instead of a changing climate and the associated changing wildfire risks, largely due to 

the complexity of incorporating such factors. Further, the Draft RMP/EIS did not claim that 

hazardous fuels reduction treatments would increase carbon storage, but that hazardous fuels 

treatments have the potential to reduce carbon losses and greenhouse gas emissions from wildfires by 

moderating fire behavior and the amount of fuels consumed. 

Many studies indicate that the carbon storage capability of western forests will decline to some 

degree, especially after mid-century. The Proposed RMP/Final EIS added information specific to 

western Oregon discussing potential productivity declines, which would affect potential carbon 

storage regardless of the presence or absence of wildfires and thinning to reduce hazardous fuels. 

Several studies have shown that thinning to reduce hazardous fuels would have dubious carbon 

benefits within forests with long fire return intervals, but that there may be some benefit in forests 

with short fire return intervals. The Proposed RMP/Final EIS has expanded the discussion of the 

effects of thinning on carbon storage in different forest conditions. 

88. Comment Summary: The DEIS does not link the potential impact of climate change on critical tree 

species to the alternatives to know which alternative best meets societal need for minimizing carbon 

emissions while maximizing carbon storage over the coming decades.

Response: The BLM does not have any effective method to link information about potential changes 

in forest composition and productivity to the alternatives. Climate change adaptation and mitigation 

largely occurs at the project level, as managers need to consider how climate change may affect 

specific sites, which is beyond the scope of this analysis. Projections of vegetation change with 

changing climate conditions include uncertainty over the exact type of change, the rate, and the 

magnitude. Evaluating how growth and yield would change as forests change, with and without 

management, would depend greatly on what climate projection is used. The BLM has no basis for 
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determining which climate model is ‘correct.’ Furthermore, the vegetation modeling relies on growth 

and yield modeling based on empirical measurements for a vast array of stand conditions (USDI 

BLM 2015, pp. 991–999). It would be impossible to produce growth and yield modeling for the stand 

conditions across the decision area based on a projection of how such stands would grow in the 

future. As a result, the carbon analysis can only examine the effects of different forest management 

approaches over time assuming stand growth and yield based on empirical measurements (i.e., the 

current conditions). The commenter does not explain how the BLM could reasonably link the 

potential changes in forest composition and productivity to the alternatives. 

The purpose and need for this RMP revision does not include meeting a “societal need for minimizing 

carbon emissions while maximizing carbon storage.” As stated in the response above, the BLM based 

the purpose and need for this RMP revision on the laws that apply to the BLM. The BLM has no 

specific legal mandate to address climate change and maximize carbon storage comparable to the 

legal mandates reflected in the purpose and need for this RMP revision, such as, for example, the 

purpose of contributing to the conservation and recovery of threatened and endangered species in 

accordance with the Endangered Species Act. Therefore, even if the BLM were able to link 

information about potential changes in forest composition and productivity as a result of climate 

change to the alternatives, this information would not be relevant to evaluating how well the 

alternatives would respond to the purpose and need for action. 

89. Comment Summary: The EIS analysis should clearly disclose the carbon consequences of different 

stream buffer widths, reserves verses the harvest land base, reserve size, degree of management 

allowed in reserves, thinning verses regeneration harvest, and different age limits.

Response: The analysis in the Draft RMP/EIS discloses the effects of these factors in the analysis of 

net carbon storage. The alternatives in the Draft RMP/EIS differ in their “stream buffer widths, 

reserves verses the harvest land base, reserve size, degree of management allowed in reserves, 

thinning verses regeneration harvest, and different age limits,” and the Draft RMP/EIS quantitatively 

compares the net carbon storage of the different alternatives over time. The analysis does not attempt 

to particularize the carbon effects of individual land use allocations within each alternative, which 

would be impossible given the integrated nature of the alternatives and the vegetation modeling. 

Regardless, a lengthy discussion of the specific effect of individual land use allocations would not 

improve the quality of the analysis or provide for a reasoned choice among the alternatives. 

90. Comment Summary: The carbon analysis should incorporate the concept of carbon debt to evaluate 

the short- and long-term trade-offs of logging verses conserving and restoring mature and old-growth 

forests.

Response: The BLM investigated the scientific literature concerning the carbon debt concept. This 

literature discusses the term primarily in connection with conversion of tropical forests to crops for 

use in commercial-scale bioenergy production and on the use of boreal forest for the production of 

commercial-scale liquid biofuels. There are no known plants operating, under construction, or 

planned within or near the decision area that would use timber or forest residues to produce liquid 

biofuels. Given this literature, the BLM determined that a discussion of carbon debt would not 

improve the quality of the analysis or provide for a reasoned choice among the alternatives. In 

addition, all alternatives would result in increases in net carbon storage over time, suggesting that no 

carbon debt would be incurred by the various levels of timber harvest in each alternative. 
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91. Comment Summary: The carbon analysis does not separate carbon stored in wood products verses 

carbon stored in live trees.

Response: The Proposed RMP/Final EIS has added discussion disclosing the estimated range of 

carbon stored in wood products. 

92. Comment Summary: The greenhouse gas emissions analysis from forestry operations should be 

analyzed in relation to CEQ’s recommended thresholds and include a social cost of carbon 

calculation. The BLM should remain below the CEQ threshold in order to comply with the White 

House interest in reducing climate change impacts.

Response: The commenter is mistaken about the nature of the suggested threshold in the draft CEQ 

guidance; the CEQ suggested this as a threshold for when to analyze greenhouse gas emissions, not a 

target for management of emissions. In 2014, the CEQ released revised draft guidance for public 

comment that describes how Federal departments and agencies should consider the effects of 

greenhouse gas emissions and climate change in their NEPA reviews (CEQ 2014). This revised draft 

guidance includes the suggestion to use annual emissions of 25,000 Mg CO2e as a reference point for 

indicating when a quantitative analysis of greenhouse gas emissions may be warranted. This guidance 

also clearly states that this suggested reference point is not a target that land management agencies 

must attain. In accordance with this draft guidance, the BLM quantitatively estimated expected 

greenhouse gas emissions from forest management operations, prescribed burning, and livestock 

grazing as well as from wildfire in the Draft RMP/EIS (USDI BLM 2015, pp. 136–140). In addition, 

the Draft RMP/EIS analyzed the social cost of carbon (USDI BLM 2015, pp. 502–523). The 

commenter identifies no error in those analyses.

93. Comment Summary: The BLM’s atmospheric CO2 levels (p. 137) need to be updated to account for 

the global level of 400 ppm that was crossed last year.

Response: The atmospheric CO2 concentration that the BLM reported in the Draft RMP/EIS is an 

average annual concentration as reported by the Global Carbon Project (GCP). The GCP has not 

updated this value for 2014 in time for the preparation of the Proposed RMP/Final EIS. The Proposed 

RMP/Final EIS has updated this information to acknowledge that the data available from the Earth 

System Research Laboratory indicates that the preliminary global average atmospheric CO2

concentrations reached 397.15 ppm in 2014. At the Mauna Loa Observatory, atmospheric CO2

concentrations exceeded 400 ppm in April through June of 2014 and in February through July of 

2015. 

94. Comment Summary: The BLM should not compare logging greenhouse emissions to the entire state 

of Oregon or the nation but to similarly scaled industries in Oregon.

Response: Cumulative effects analysis of greenhouse gas levels is challenging, in part, because of the 

difficulty in setting the geographic scope for the analysis. The Draft RMP/EIS placed BLM 

greenhouse gas emissions from harvest operations and prescribed burning into context with emissions 

from harvest operations and prescribed burning of other forest managers in western Oregon. The 

cumulative effects analysis of greenhouse gas emissions in the Draft RMP/EIS presented the 

incremental effect of the alternatives within the context of cumulative greenhouse gas emission at 

multiple spatial scales, including state and national total emissions (USDI BLM 2015, pp. 139–140). 

The Proposed RMP/Final EIS added discussion of how the proportion of BLM greenhouse gas 
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emissions might change relative to other forest managers (see the Climate Change section of Chapter 

3). The commenter provided no indication as to what industries they consider as “similarly scaled” to 

BLM land management in western Oregon or how placing the BLM emissions in a different context 

would improve the quality of the analysis or provide for a reasoned choice among alternatives. 

95. Comment Summary: Carbon emissions from logging and foregone opportunities for increased 

carbon storage in forests directly conflict with state, Federal, and international greenhouse gas 

reduction goals.

Response: The commenter is mistaken. As clearly stated in the Draft RMP/EIS, all alternatives 

would increase carbon storage relative to the current condition, supporting state, national, and 

international goals to increase carbon storage (USDI BLM 2015, pp. 132–136). 

The Federal government has not established any specific goals with respect to carbon storage and 

does not require that Federal agencies maximize carbon storage. Executive Order 13653, issued on 

November 6, 2013, directs the Federal agencies to develop or modify programs and policies to 

promote “...greater climate resilience and carbon sequestration, or other reductions to the sources of 

climate change.” In response, DOI updated the climate adaptation plan in 2014. The only specific 

direction with respect to carbon storage or carbon sequestration is to consider developing a formal 

policy for DOI bureaus to incorporate carbon storage as an explicit element of resource management 

plans (DOI Climate Change Adaptation Plan, p. 43). As of the preparation of the Proposed 

RMP/Final EIS, neither DOI nor the BLM has issued either draft or final policy that sets carbon 

storage goals. 

The State of Oregon established statewide goals for greenhouse gas emissions reduction, but the focus 

of reductions is on transportation and energy production and use. The Proposed RMP would support 

the State’s 2004 strategy for greenhouse gas reductions by increasing carbon storage.

96. Comment Summary: The BLM discussion of greenhouse gas emissions is too perfunctory and 

essentially dismisses the emissions problem on the basis that these forests represent a small 

percentage of the total emissions of the U.S.

Response: The BLM disagrees that the analysis of greenhouse gas emissions is “too perfunctory.” 

Analysis in an EIS must provide a ‘hard look’ at the effects of the alternatives. A ‘hard look’ is a 

reasoned analysis containing quantitative or detailed qualitative information (USDI BLM 2008, p. 

55). The Draft RMP/EIS presents background on the role of greenhouse gas emissions in climate 

change, quantitatively analyzes the greenhouse gas emissions under each alternative, and places those 

emissions in context of statewide and national emissions and in the context of other forest managers 

with respect to harvest operations and prescribed burning (USDI BLM 2015, pp. 136–140). The Draft 

RMP/EIS provides a reasoned analysis to present analytical conclusions on the comparative effects of 

the alternatives on greenhouse gases. Thus, the Draft RMP/EIS took a ‘hard look’ at greenhouse gas 

emissions. The Draft RMP/EIS presents no conclusion about the extent to which the BLM will 

consider greenhouse gas emissions in the eventual selection of the RMP. The commenter identifies no 

error in this analysis. 

97. Comment Summary: An additional issue of importance is assessing the carbon cost of management 

versus the carbon cost of no management. From a carbon storage perspective, the critical question is 
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how much carbon is emitted through management to prevent wildfire compared to that which would 

be lost by wildfire.

Response: The Draft RMP/EIS quantitatively analyzed the effects on carbon storage of management 

action under the alternatives and the effects of wildfire on carbon storage (USDI BLM 2015, pp. 132–

135). The Proposed RMP/Final EIS added discussion of the potential effects of hazardous fuels 

treatments on carbon storage (see the Climate Change section of Chapter 3). The BLM does not claim 

that forest management would prevent wildfires from occurring, just that management could reduce 

wildfire intensity and severity, potentially reducing greenhouse gas emissions from wildfire, 

particularly in forests adversely affected by fire suppression (USDI BLM 2015, pp. 158–159). The 

Draft RMP/EIS acknowledged that hazardous fuels treatments can affect wildfire risk, but the BLM 

has no method to translate these changes in risk into meaningful differences in wildfire occurrence 

and wildfire effects for the alternatives (USDI BLM 2015, p. 212). The commenter presents no 

additional information that would allow the BLM to analyze quantitatively the changes in wildfire 

occurrence and effects in response to hazardous fuels treatments or other management actions. 

98. Comment Summary: Error in Figure 3-29 concerning annual minimum temperature for the 

Willamette Basin.

Response: The Proposed RMP/Final EIS corrected this figure (see the Climate Change section in 

Chapter 3). 

99. Comment Summary: The description of regional climates is oversimplified; the Willamette Valley 

has a Mediterranean climate.

Response: The Draft RMP/EIS described regional climate types to provide background to the 

analysis. Whether the discussion characterizes the Willamette Valley as a maritime or Mediterranean 

climate type would not alter the analysis of environmental effects of the alternatives or the analytical 

conclusions. Climatologists and geographers over time have classified the climate of the Willamette 

Valley as maritime and as Mediterranean. Two climate classification schemes are available—

Köppen-Gieger and modified Thornthwaite (Kottek et al. 2006, Grundstein 2008). The KöppenGeiger system uses monthly average temperatures and the degree of difference between winter and 

summer precipitation to identify climate categories (Kottek et al. 2006). In contrast, the modified 

Thornthwaite system uses potential evapotranspiration and a moisture index (Grundstein 2008). 

Climate scientists and geographers use the Köppen-Geiger system more widely than the modified 

Thornthwaite, but recognize both. The Köppen-Geiger system for the years 1951 through 2000 

classified all or nearly all of western Oregon, including the Cascade Mountains, as warm temperate 

with warm, dry summers (Kottek et al. 2006), which is typically labeled as coastal Mediterranean or 

Mediterranean. There are some differences on the far northwest Oregon coast in the available maps of 

this classification. The modified Thornthwaite scheme classifies the Willamette Valley as cool-wet, 

the same as the Oregon coast, and the interior valleys of southwest Oregon as cool-moist based on 

climate data from 1970 through 1999 (Grundstein 2008). The presence or absence of a fog belt is not 

relevant under both classification systems. The maritime influence on climate is strongest in winter 

and weakest in summer across the state beyond the immediate coast. However, the Willamette Valley 

does experience a stronger maritime influence in summer than southwest Oregon, as conditions are 

typically cooler and moister with more episodes of low cloud cover and light rain; the period of 

hottest weather is also shorter. The BLM also asked the Oregon Climate Change Research Institute 

whether the Willamette Valley climate should be considered as Mediterranean or maritime (K. Dello, 
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2015 personal communication); they stated that maritime was a better description, but also that such 

designations were not meaningful scientifically. 

100. Comment Summary: The estimates of climate change vulnerability in Table 3-24 should 

include the drought tolerance ratings from Niinemets and Valladares (2006).

Response: The Draft RMP/EIS used information from Devine et al. (2012), which includes a drought 

tolerance rating relative to all other trees in a particular subregion as part of the habitat affinity score 

used to develop an overall climate change vulnerability score (USDI BLM 2015, pp. 145–147). The 

BLM reviewed the information contained in Niinemets and Valladares (2006) and concluded that 

adding the drought tolerance rating from that source would not change the analysis or add value to the 

table. The Devine et al. (2012) data show how the climate vulnerability of a species may vary 

between northwest and southwest Oregon, whereas the Niinemets and Valladares (2006) data does 

not. Thus Devine et al. (2012) provides more specific and relevant information for this analysis than 

Niinemets and Valladares (2006). 

101. Comment Summary: Expand the fire discussion to include more information on how fire 

regimes will change as climate changes.

Response: The Proposed RMP/Final EIS has added discussions of potential changes in fire risk as 

climate changes (see the Climate Change section of Chapter 3). As discussed in the Draft RMP/EIS, 

scale mismatches and the lack of important bottom-up controls on fire in current projections means 

that the BLM cannot be very specific about how and where fire regimes might change as climate 

changes particularly given that the mixed severity fire regime category is very broad (USDI BLM 

2015, p. 156). Within the mixed severity regimes, the proportion of high and low severity patches 

may shift, but the fire regime could remain in the mixed severity category. Further, the breakpoints 

between low, mixed, and high severity regimes are completely subjective, with various scientists 

providing different breakpoints. The BLM typically uses the breakpoints incorporated into 

LANDFIRE (6–25 percent stand-replacement equals low severity, 25–75 percent stand-replacement 

equals mixed, and greater than 75 percent stand-replacement equals high severity), which is a national 

program widely used by agencies and fire scientists and fire ecologists. In addition, as the Draft 

RMP/EIS pointed out, current projections assume that past climate-fire relationships will persist into 

the future (USDI BLM 2015, p. 156). If these relationships do not persist, the BLM has no method to 

determine how and where fire regimes would change. 

102. Comment Summary: Thinning as a climate change adaptation strategy will not increase drought 

resistance in the long-term.

Response: The Draft RMP/EIS stated that Joyce et al. ( 2009), Spies et al. (2010), and Peterson et al.

(2011) summarized specific actions recommended for responding to climate change, including 

thinning forest stands to reduce competition and drought stress (USDI BLM 2015, p. 158). The Draft 

RMP/EIS does not contain an analytical conclusion that thinning, as a climate change adaptation 

strategy, will increase drought resistance in the long term. The Draft RMP/EIS simply described 

recommendations in the existing literature. 

103. Comment Summary: Page 156 claims that more fires equals more homogeneity and that this is 

bad for biodiversity. Regionally specific studies on mixed severity regimes should be cited instead.
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Response: The Draft RMP/EIS did not claim that more fires would result in more homogeneity and 

hence lower biodiversity. Instead, the Draft RMP/EIS stated that the likelihood of such outcomes 

would increase as climate changes and assuming that current fire-climate relationships persist into the 

future. It also states that the outcomes of future fires also depend on bottom-up controls that are not 

incorporated into current projections of wildfires, indicating some uncertainty that the stated potential 

outcomes would occur. The Draft RMP/EIS cited multiple studies concerning projections of increased 

burn severity (USDI BLM 2015, pp. 155–156). The Proposed RMP/Final EIS has added discussion 

and cited additional studies regarding future changes in wildfires, primarily to the drier forests of the 

planning area. 

104. Comment Summary: The section on fire, page 155, needs a comprehensive literature review 

including recent studies that show no increase in fire extent or severity in this region.

Response: The Draft RMP/EIS reported an increase in the proportion of high-severity fire within 

forests in the entire state of Oregon based on Monitoring Trends in Burn Severity data and stated that 

establishing any similar trend or lack of trend is not possible within the planning area due to 

inadequate data (USDI BLM 2015, p. 149). The Draft RMP/EIS cited relevant literature on the effects 

of climate change on wildfire, sufficient to understand the potential cumulative effect of climate 

change and future wildfires together with the effects of the alternatives (USDI BLM 2015, pp. 148–

149, 155–156). A literature review of the effects of climate change on wildfire is not necessary to 

understand the potential impacts of the alternatives. An extensive review of the literature on the effect 

of climate change on wildfires would not improve the quality of the analysis or provide for a reasoned 

choice among alternatives. The BLM has not included such a literature review in keeping with CEQ 

direction that environmental analyses should not be encyclopedic in nature but should focus on the 

information relevant to the decisions to be made (40 CFR 1500.4). 

105. Comment Summary: The RMP should incorporate projections of climate change into vegetation 

and fire behavior modeling.

Response: The Draft RMP/EIS acknowledged the potential effects of climate change on stand 

growth. Separate from the vegetation modeling with Woodstock, the BLM reviewed bioclimatic 

envelope model projections and evaluated the potential effects and associated uncertainty of projected 

climate changes on a variety of forest management outcomes for the planning area conducted using 

the Climate extension of the Forest Vegetation Simulator model (USDI BLM 2015, pp. 152–154). 

The Draft RMP/EIS explicitly explained why the vegetation modeling did not incorporate projections 

of climate change into the simulation of the growth of stands through time. Specifically, to translate 

these broad regional predictions of climate change with substantial uncertainties to projections of how 

and when specific groups of forest stands would change in their patterns of growth and response to 

treatment over the next several decades would be so speculative as to be arbitrary (USDI BLM 2015, 

p. 100). Furthermore, the vegetation modeling relies on growth and yield modeling based on 

empirical measurements for a vast array of stand conditions (USDI BLM 2015, pp. 991–999). It 

would be impossible to produce growth and yield modeling for the stand conditions across the 

decision area based on a projection of how such stands would grow in the future. The commenter 

does not address these explanations. 

The Draft RMP/EIS discussed the potential effects of climate change on future wildfire occurrence 

and severity. The Draft RMP/EIS identified that most climate change projections indicate that 

wildfires are likely to get larger and more severe in the future. The Draft RMP/EIS explicitly 
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explained why the vegetation modeling did not incorporate projections of the effects of climate 

change on future wildfire occurrence and severity. Specifically, the inherent challenges in predicting 

future stochastic events coupled with the uncertainties in climate change predictions make it 

impossible to forecast specifically when and where future wildfires would occur differently than they 

have occurred in the recent past (USDI BLM 2015, pp. 99, 1053–1055). The commenter does not 

address these explanations. 

106. Comment Summary: The FEIS should identify and discuss climate refugia, reserve redundancy, 

and reserve connectivity as strategies to address climate change.

Response: The Proposed RMP/Final EIS added discussion concerning the potential role of various 

types of reserves to serve as climate change refugia (see the Climate Change section of Chapter 3). 

The Draft RMP/EIS discussed the potential role of reserves in providing connectivity and redundancy 

for a wide range of resources (see, for example, USDI BLM 2015, pp. 217–235, 354–356, 701–708, 

and 738–818). 

107. Comment Summary: The DEIS claims that the region is getting drier even though precipitation 

is either equivocal or projected to increase.

Response: The ‘dryness’ of an area is a function of both precipitation and temperature as is readily 

demonstrated by climate data around the world. Two regions may have very similar average annual 

precipitation but the region with a higher average temperature is drier than the region with a lower 

average temperature and generally supports less vegetation. This difference is due to fundamental 

ecosystem processes concerning evapotranspiration demand. As evapotranspiration demand 

increases, a region becomes effectively drier. Every biogeographic vegetation model uses this 

fundamental property to assess how climate influences vegetation distribution and how climate 

change may alter vegetation distribution. As stated in the Draft RMP/EIS, the low increase in 

precipitation when combined with the more substantial increases in temperature, particularly in 

minimum temperature, indicates the region is becoming effectively drier (USDI BLM 2015, p. 143). 

108. Comment Summary: The wildlife and wildlife habitat section on page 157 lacks a 

comprehensive literature review and is missing citations relevant to the region.

Response: As stated in the Draft RMP/EIS, a comprehensive review of the impacts of climate change 

on all fish and wildlife species found within the planning area is not possible (USDI BLM 2015, p. 

150). Instead, the discussion focused on two key species relevant to the purpose and need—northern 

spotted owl and marbled murrelet—as illustrative. The Draft RMP/EIS cited relevant literature on the 

possible impacts of climate change to northern spotted owls and marbled murrelet (USDI BLM 2015, 

p. 157). A literature review of the effects of climate change on wildlife is not necessary to understand 

the potential impacts of the alternatives. An extensive review of the literature on the effect of climate 

change on wildlife would not improve the quality of the analysis or provide for a reasoned choice 

among alternatives. The BLM has not included such a literature review in keeping with CEQ 

direction that environmental analyses should not be encyclopedic in nature but should focus on the 

information relevant to the decisions to be made (40 CFR 1500.4). 
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109. Comment Summary: The recommended actions on page 158 for building resilience are 

incomplete (e.g., Black et al. 2013). What evidence does BLM have that insect outbreaks can be 

suppressed by thinning?

Response: The Draft RMP/EIS does not claim that thinning will suppress insect outbreaks. Instead, it 

cited several climate change adaptation review papers that recommend thinning to increase resistance 

to insects, among other disturbance factors (USDI BLM 2015, p. 158). The BLM reviewed Black et 

al. (2013) and determined it does not add any additional information to the discussion in the Draft 

RMP/EIS. Black et al. (2013) discusses whether thinning can reduce the spread of large landscapescale outbreaks once bark beetles have reached epidemic proportions. Neither the Draft RMP/EIS nor 

the climate change adaptation review papers cited in the Draft RMP/EIS assert that thinning could 

reduce outbreaks once they reach epidemic proportions. Black et al. (2013, p. 62) also reports that 

thinning can reduce the susceptibility to insect attack, thus supporting the adaptive strategy 

recommended in the climate change adaptation review papers cited in the Draft RMP/EIS. 

110. Comment Summary: The discussion on the bottom of page 159 is not based on the best science 

in assuming that reserves are less resilient and resistant to climate change than managed areas.

Response: The Draft RMP/EIS did not claim that reserves are necessarily less resilient and resistant 

to climate change than actively managed areas. The Draft RMP/EIS stated that decreasing the 

management options decreases the opportunities for the BLM to take actions intended to adapt to 

climate change (USDI BLM 2015, p. 159). The previous paragraphs in this section discussed how 

active management provides opportunity for the BLM to increase resistance and resilience to climate 

change in keeping with the types of strategies identified in the Draft RMP/EIS (USDI BLM 2015, pp. 

158–159). The Proposed RMP/Final EIS has added discussion to clarify the potential risks associated 

with minimally managed reserves under changing climate conditions (see the Climate Change section 

of Chapter 3). 

111. Comment Summary: The DEIS is incorrect in stating that large-scale thinning to reduce crown 

fire potential and provide biomass for wood energy would reduce CO2 emissions. Thinning would 

result in long-term carbon emissions because many of the areas thinned would not experience fire 

during the period of treatment effectiveness. Thinning also does not reduce fire occurrence, 

particularly during extreme conditions and especially in the climate-driven fire systems such as this 

region.

Response: The Draft RMP/EIS did not state that large-scale thinning to reduce crown fire potential 

would reduce CO2 emissions as a blanket conclusion. The Draft RMP/EIS reported the findings from 

several studies that indicate thinning and prescribed burning in forests adversely affected by fire 

suppression, largely the drier forests, indicate that such reductions are possible (USDI BLM 2015, p. 

159). The Draft RMP/EIS made no claims nor cited any studies concerning the effects of thinning and 

prescribed burning on the potential future emissions from forests not adversely affected by fire 

suppression, largely the moister forests. The Draft RMP/EIS did not assume that thinning for 

bioenergy production would occur, nor did it discuss the potential effects of wood harvested for 

bioenergy on future CO2 emissions. As discussed in the Draft RMP/EIS, biomass for energy use, 

primarily personal use firewood, is a by-product of forest management for other purposes, with low 

utilization of this potential resource (USDI BLM 2015, pp. 497–498). 

Whether thinned areas would or would not experience fire during the period of treatment 

effectiveness is not known nor is it discussed. While the probability of any specific location burning 
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is very low, several hundred to tens of thousand acres in western Oregon burn every year, primarily in 

the drier forests (see the Fire and Fuels section of Chapter 3). 

The Draft RMP/EIS did not state or conclude that thinning would reduce wildfire occurrence. Instead, 

the Draft RMP/EIS stated that thinning could moderate wildfire effects (USDI BLM 2015, pp. 158–

159). Fire occurrence depends on ignitions. Fire effects depend on the combination of fuels 

characteristics, weather, and topography at the time and location of the wildfire (USDI BLM 2015, 

pp. 173–177). 

112. Comment Summary: The RMP should project the forest composition of southern Oregon under 

the alternatives as climate changes.

Response: The Draft RMP/EIS discussed how climate change could potentially alter forest 

composition and productivity. The Draft RMP/EIS reviewed bioclimatic envelope model projections 

and evaluated the potential effects and associated uncertainty of projected climate changes on a 

variety of forest management outcomes for the planning area conducted using the Climate extension 

of the Forest Vegetation Simulator model (USDI BLM 2015, pp. 152–154). However, the BLM has 

no methodology for projecting how forests within southern Oregon or the rest of the planning area 

would actually change or at what specific rate. Species change ranges as individuals, not as 

community groups, and bottom-up controls on species migration (competition, soils, topography, 

disturbance regimes, and so forth) generally are not widely incorporated into various models of 

changing species ranges largely due to lack of suitable information how these factors affect species 

distributions. The BLM has no way to determine which climate change model is the most appropriate 

for determining the magnitude and rate of change. Lastly, as the climate change impacts literature 

makes clear, climate change is not linear, but proceeds at an irregular rate. All these variables mean 

that any projections the BLM would make about the composition of southern Oregon forests arising 

from climate change with or without the management direction proposed in the different alternatives 

would be speculative. 

113. Comment Summary: It would aid readers to explicitly state in the Key Points which alternative 

increases carbon storage the most and which increases it the least and which alternative emits the 

most greenhouse gases and which the least.

Response: The Proposed RMP/Final EIS has added the suggested information to the key points (see 

the Climate Change section of Chapter 3). 

114. Comment Summary: Contrary to the DEIS analysis, logging will reduce forest resilience and 

BLM needs to recognize this. There is strong evidence that unmanaged forests have great capacity for 

self-correction and self-organization. The BLM should look carefully at all the evidence, including 

competing experts’ viewpoints before concluding that logging is beneficial. Complex native forests 

are more resilient to climate change than logged forests and simplified plantations.

Response: There is scientific uncertainty about the potential effects of different forest management 

strategies on forest resilience in the face of climate change. The Proposed RMP/Final EIS has added 

discussion and citations regarding competing viewpoints on this topic (see the Climate Change 

section of Chapter 3). While the science is clear that complex forests have more resilience to a variety 

of disturbances than simplified forests, there is less evidence that logged forests have less resilience 

than unlogged forests, particularly to climate change. “Logging” is a very broad term that applies to a 
1895 | P a g e

wide range of tree removal, both commercial and non-commercial, and ranging from relatively light 

thinning of the lower tree canopy to clearcutting with no retention of any trees. Further, ‘complexity’

has many facets, not all of which confer resilience to all disturbances and to climate change. Whether 

‘logged’ forests are less resilient to climate change depends on what is removed, what remains, and, 

in the case of regeneration harvesting, what is planted. Thinning, particularly in drier forests, to 

increase resistance to a variety of stressors including climate change is a very common 

recommendation from forest scientists who have studied the implications of climate change on forests 

(USDI BLM 2015, pp. 157–158). 

115. Comment Summary: The DEIS on page 149 and in Appendix D contradict each other. DEIS (p 

149) says “analysis of Oregon large fires using data from the Monitoring Trends in Burn Severity site 

(http://mtbs.gov/index.html) indicates that the proportion of high-severity fire in forests generally has 

increased by 11percent since 1984, with much of the increase since 2000.” This appears to be 

contradicted in DEIS Appendix D which ... examined the MTBS data for any obvious temporal 

trends in wildfire severity, but did not detect a strong signal (Figure D-6). Over the course of 25 

years, there appears to be a slight increase in the percentage of area burned by low and moderate 

severity wildfire, and a slight decrease in the percent of area burned in high severity wildfire, 

although these trends are not statistically significant. ... While several studies have indicated that 

high severity fires are increasing across the western United States (Westerling et al. 2006, Dillon et 

al. 2011a, Miller et al. 2012), no such trends were apparent in the observed record within the range 

of the northern spotted owl (Figure D-6).

Response: The Proposed RMP/Final EIS has rewritten the relevant sentence from page 149 of the 

Draft RMP/EIS to make it clear that the information on page 149 and Appendix D of the Draft 

RMP/EIS do not contradict each other. The two passages address wildfire trends at different scales. 

The statement in the Draft RMP/EIS on page 149 refers to all forests in the entire State of Oregon, 

while Appendix D refers to fires within the range of the northern spotted owl. The Draft RMP/EIS 

also states that there are too few fires that have originated, either on BLM-administered lands or in 

western Oregon, to draw any conclusions on how fire severity and fire season severity may be 

changing (USDI BLM 2015, p. 149). 

116. Comment Summary: DEIS (pp. 149–150) describes increasing stream temperatures as a result 

of climate change. The BLM needs to disclose the likely consequences on cold-water fish and other 

temperature-sensitive aquatic organisms.

Response: The Draft RMP/EIS identified the groups of species most vulnerable to climate change, 

including cold-water fish and other species with narrow temperature requirements (USDI BLM 2015, 

p. 157). The Draft RMP/EIS clearly described the effects of stream temperature on fish (USDI BLM 

2015, pp. 232–233). Given the uncertainties associated with predictions of increasing stream 

temperatures, especially the interaction of increasing air temperatures and changes in stream shading 

(USDI BLM 2015, pp. 156–157, 232–233, 290–294), more detailed predictions of the consequences 

of climate change on cold-water fish and other temperature-sensitive aquatic organisms is not 

possible. The Proposed RMP/Final EIS has added discussion concerning the potential role of inner 

zones of Riparian Reserve (where thinning is restricted) in the action alternatives in providing climate 

refugia (see the Climate Change section of Chapter 3). 

117. Comment Summary: The DEIS does not identify mitigation measures to address the likely 

effects of increasing spring precipitation on northern spotted owl nesting success.
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Response: Mitigation is an important mechanism Federal agencies can use to minimize the potential 

adverse environmental impacts associated with their actions (CEQ 2011, p. 4). An EIS must identify 

all relevant and reasonable mitigation measures. (CEQ, “Forty Most Asked Questions ...” 46 FR 

18027). The commenter does not identify any specific relevant and reasonable measure that they 

believe would reduce or avoid the effect of increasing spring precipitation. Measures that would 

reduce greenhouse gas emissions or increase carbon storage would not be relevant and reasonable 

measures to reduce or avoid the effect of increasing spring precipitation; it is currently beyond the 

scope of existing science to identify a specific source of greenhouse gas emissions and designate it as 

the cause of specific climate impacts in a specific location. Thus, it would not be possible for the 

BLM to identify any relevant and reasonable measures to reduce or avoid the effect of increasing 

spring precipitation. Regardless of whether the BLM could identify such mitigation measures and 

evaluate their effectiveness, such measures would not be relevant to this RMP revision. The 

mitigation measures discussed in an EIS address the effects of the proposed action. Increasing spring 

precipitation is not an effect of the BLM action. 

118. Comment Summary: The DEIS does not adequately address the current scientific understanding 

of the breadth of ways that anticipated climate change will alter the way we expect ecosystems to 

respond to forest management actions, particularly in regards to aquatic resources (e.g., see Dale et al.

2001, Dalton et al. 2013). Watershed resilience in the face of climate change can best be maintained 

by protecting and restoring the suite of natural processes and conditions that characterize natural 

forested riparian areas and floodplains (Seavy et al. 2009, Furniss et al. 2010). This is exactly what 

the ACS was originally designed to accomplish.

Response: The BLM analyzed the ways climate change may interact with BLM management actions 

in western Oregon, including water and aquatic resources, using the current scientific understanding 

(USDI BLM 2015, pp. 141–159). The spatial distribution and magnitude of future temperature and 

precipitation changes in the planning area are likely to be highly variable (Dalton et al. 2013). 

Shorter-term climate patterns are influenced by the Pacific Decadal Oscillation and El Niño-Southern 

Oscillation and deviate from longer-term trends (Dalton et al. 2013). As well, watershed 

characteristics (e.g., location, elevation, geology, vegetation, and dominant precipitation), lead to 

highly variable effects to a climate change trend. The commenter does not address the analysis of 

climate change in the Draft RMP/EIS or identify any errors or deficiencies in that analysis. 

The commenter suggests that protecting natural processes and conditions within Riparian Reserve 

would lead to increased adaptability and resilience to climate change. The analysis in the Draft 

RMP/EIS has shown that the Riparian Reserve design and accompanying management direction 

under the alternatives would maintain resilient forested riparian areas in a managed landscape. 

Specifically, the Riparian Reserve would contribute to the conservation and recovery of ESA-listed 

fish species and their habitats; maintain and restore natural channel dynamics and processes and the 

proper functioning condition of riparian areas, stream channels, and wetlands; maintain high quality 

water (including Source Water Protection watersheds); and contribute to the restoration of degraded 

water quality. 

The commenter suggests that the No Action alternative is the best strategy for maintaining watershed 

resilience in the face of climate change. Given that the BLM fully analyzed the No Action alternative 

in the Draft RMP/EIS, it is unclear how the commenter feels the Draft RMP/EIS did not adequately 

address watershed resilience in the face of climate change. Nevertheless, as shown by the analysis in 

the Proposed RMP/Final EIS (see the Fisheries and Hydrology sections of Chapter 3), the Proposed 

RMP would have effects on aquatic resources that would be similar to the No Action alternative. 
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Therefore, the Proposed RMP would provide a comparably effective strategy for maintaining 

watershed resilience in the face of climate change. 

119. Comment Summary: The RMP/DEIS failed to analyze cumulative stream temperature (climate 

change) increases, which are due in part to logging. Past logging on O&C lands has measurably 

contributed to CO2 pollution, thus triggering the required NEPA cumulative impacts of increased 

stream temperature. The DEIS/RMP failed to disclose the feedback loop of logging/increased CO2

and resulting ongoing/future increased stream temperatures.

Response: The Draft RMP/EIS analyzed the effect of timber harvest under the alternatives on stream 

temperature (USDI BLM 2015, pp. 286–297) and acknowledged the potential future effect of climate 

change on stream temperatures (USDI BLM 2015, pp. 149–150). As explained in response to a 

similar comment below under Hydrology, it is not possible to forecast quantitatively how future 

riparian forest stand development would interact with increasing annual and seasonal air temperatures 

to affect stream temperature. The Draft RMP/EIS acknowledged that timber harvest creates 

greenhouse gas emissions, and that greenhouse gas emissions contribute to climate change (USDI 

BLM 2015, pp. 136–139, 141–142). However, it is not possible to ascribe any specific change in 

climate conditions to a specific emission of greenhouse gases. Furthermore, to the extent that past 

timber harvest in the decision area has contributed to changing climate conditions, the description in 

the Draft RMP/EIS of current condition and trend of climate conditions incorporates the effects of 

past timber harvests. As explained in the Draft RMP/EIS, the analysis generally relies on an aggregate 

description of the current condition and trend of resources, rather than delving into the historical 

details of individual past actions (USDI BLM 2015, p. 94). Finally, the commenter is incorrect in 

referring to ongoing increased stream temperatures. The Draft RMP/EIS explained that, in spite of 

predictions about potential future stream temperature increases, average maximum stream 

temperatures have generally been decreasing over the past decades (USDI BLM 2015, pp. 143, 293–

294). 

 Fire and Fuels 

120. Comment Summary: The BLM should revise the EIS to describe how actions are consistent 

with local and state fire protection plans and policies.

Response: The FLPMA requires that the BLM consider the policies of approved state and tribal land 

resource management programs and develop land use plans that are consistent with state and local 

plans to the maximum extent possible consistent with Federal law (43 CFR 1610.3–1). In this 

particular instance, the Oregon Department of Forestry’s firefighting policy is to “Put out fires 

quickly at the smallest possible size” (http://www.oregon.gov/ODF/Fire/Pages/default.aspx, accessed 

January 14, 2016), whereas Federal Fire policy states that— 

 The protection human life is the first priority and that no natural or cultural resource, home, 

or item of property is worth a human life. 

 The full range of fire management activities will be used to help achieve ecosystem 

sustainability, including its interrelated ecological, economic, and social components. 

 Fire, as a critical natural process, will be integrated into land and resource management plans 

and activities on a landscape scale, and across agency boundaries. Response to wildland fires 

is based on ecological, social and legal consequences of the fire. The circumstances under 

which a fire occurs, and the likely consequences on firefighter and public safety and welfare, 
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natural and cultural resources, and, values to be protected, dictate the appropriate response to 

the fire (USDA and USDI 2009, p. 10). 

As such, the Proposed RMP includes a management objective to participate with communities 

bordering Federal lands in partnership with local, State and Federal stakeholders to reduce the risks 

and threats from wildland fire. The Proposed RMP also includes management direction to apply the 

full range of fire management options in responding to natural ignitions or escaped prescribed fires. 

The BLM may use these fires to achieve management objectives when expected fire behavior and 

potential effects of a fire, or a part of a fire, are aligned with the management objectives and direction 

of the underlying land use allocation and affected resources (Appendix B – Management Objectives 

and Direction). This objective and direction in the Proposed RMP addresses the requirement of the 

FLPMA to develop land use plans consistent with State and local plans to the maximum extent 

consistent with Federal law. 

The BLM added clarification to the Proposed RMP/Final EIS in the background of Issue 3 in the Fire 

and Fuels section to indicate that the BLM participates in the local and state fire protection plans, 

policies, and the Community Wildfire Protection Plan process. 

121. Comment Summary: The BLM should revise the EIS to include different management 

objectives for the ‘dry’ and ‘very dry’ forest types for wildfire resiliency, given the projected climate 

patterns and the lifespan of the RMP.

Response: The BLM included management objectives for wildfire resiliency for dry and very dry 

forest types in the action alternatives and the Proposed RMP, and varied these objectives by varying 

the land use allocations in dry and very dry forest types. The BLM establishes management objectives 

for land use allocations and, as such, land use allocations that address dry forest management (e.g., 

Uneven-aged Timber Management and Late-Successional Reserve – Dry) provide variations to 

objectives that specifically address wildfire resiliency (Appendix B – Management Objectives and 

Direction).

The BLM classified forest types as dry and very dry based upon potential vegetation types and 

location (USDI BLM 2015, pp. 1002–1003). The BLM analyzed varying management objectives and 

applied differing management direction to dry and very dry forest types by varying land use 

allocation definitions of dry under the alternatives. For example, the Harvest Land Base allocates the 

Uneven-aged Timber Management under Alternative B to both dry and very dry forests, whereas 

Alternatives C and D only allocates the Uneven-aged Timber Area to very dry forests. The Proposed 

RMP allocates the Uneven-Aged Timber Management to both dry and very dry forests on the 

Medford District and Klamath Falls Field Office, and to very dry forests within the South River Field 

Office of the Roseburg District. 

122. Comment Summary: Proposed BLM timber management in the DEIS will increase fire and fuel 

hazards in western Oregon forests. The proposal to increase even‐aged, regeneration harvesting on 

public lands is irresponsible and will significantly increase fire/fuel hazards throughout western 

Oregon. The RMP admits that many of the alternatives provided in the DEIS will increase fire and 

fuel hazards by increasing logging slash, encouraging young age classes less resilient to fire.

Response: The commenter is mistaken. Based on analysis in the Draft RMP/EIS, all action 

alternatives would reduce the acres of High and Moderate fire hazard (USDI BLM 2015, p. 202). The 

commenter is also mistaken that the action alternatives would increase even-aged, regeneration 

harvesting. Compared to the No Action alternative, all of the action alternatives would reduce the 
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amount of regeneration harvest in the dry forests. The acres in activity fuel risk categories (USDI 

BLM 2015, pp. 209–211) provide an estimate of potential future work needed to reduce the risk 

associated with harvest activity fuels. Historically, the BLM has treated residual activity fuels 

following timber management activities for both site preparation and hazardous fuels reduction 

purposes. The commenter is mistaken in that many of the alternatives will increase fire and fuel 

hazards by increasing logging slash. As described in the Draft RMP/EIS, Alternatives B and C would 

result in more acres of activity fuels in the High risk category than the No Action alternative, and 

Alternatives A and D would result in fewer acres. All action alternatives would result in fewer acres 

of activity fuels in the Very High risk category than the No Action alternative (USDI BLM 2015, pp. 

210–211). Furthermore, all alternatives include management direction to treat activity fuels, which 

would reduce the potential for activity fuels to contribute to fire hazard. The analysis of the Proposed 

RMP in this Proposed RMP/Final EIS confirms these results, and would result in trends described 

above similarly to Alternative B (see Chapter 3 Fire and Fuels Issues 3 and 4). 

123. Comment Summary: The BLM should revise the EIS because it fails to address, adequately, the 

predictable increase in wildfire, pests, disease, and storm damage due to overcrowded forests in large 

block forests and Riparian Reserve. Alternatives that increase Reserve acreages will increase the risk 

of catastrophic wildfires by allowing more land to be unmanaged.

Response: The BLM does not agree that allocating lands to Late-Successional Reserve or Riparian 

Reserve will result in “overcrowded forests” or a “predictable increase in wildfire, pests, disease, and 

storm damage.” The action alternatives and the Proposed RMP management direction in reserve land 

use allocations, especially in the dry forest, direct the BLM to manage stands to maintain landscape 

resilience and reduce the potential for uncharacteristic disturbances (Appendix B – Management 

Objectives and Direction). Management direction in the Proposed RMP includes direction to treat 

21,500 acres per decade within Late-Successional Reserve – Dry. The Draft RMP/EIS specifically 

discusses analytic results for reserve management effects on fire resistance and fire hazard within 

Wildland Development Areas (USDI BLM 2015, pp. 195, 202, 1134–1135). 

124. Comment Summary: Classifying the region’s forests into dry and moist (DEIS, p. 178) has 

regionally specific biases. DellaSala et al. (2013) indicate that mixed evergreen forests experience 

mixed‐severity fire regimes that cannot be classified using binary classifications systems. 

Classification uncertainty that was not accounted for in BLM’s models needs to be discussed as using 

a simplistic binary classification will bias model outputs resulting in over‐emphasis on thinning that 

could result in type conversions (DellaSala et al. 2013). BLM needs to represent the disagreement in 

the literature between Franklin and Johnson’s (2013) approach (ecoforestry) vs. criticisms by 

DellaSala et al. (2013) as regional uncertainty and lack of scientific agreement.

Response: The Draft RMP/EIS extensively described the classification process for moist and dry 

forest delineations (USDI BLM 2015, pp. 179–180, 1002–1005). As explained in the Draft RMP/EIS, 

the process for moist and dry forest delineations included eco-typing conducted by regional resource 

experts and reviews of these classifications by local resource experts. In no way does this 

classification discount that mixed evergreen forests experience mixed-severity fire regimes. The 

Proposed RMP/Final EIS has expanded this discussion to acknowledge other types of vegetation 

classification systems.

125. Comment Summary: Fire models used in developing RMP alternatives should be approached 

with caution. The EIS is based on untested models (e.g., LANDFIRE, class condition mapping) that 
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have known over‐prediction biases regarding high‐severity fire. BLM applies TNC fire mapping built 

on LANDFIRE and fire regime condition class datasets that have not been ground truthed for 

prediction bias. Model uncertainty needs to be clearly specified in the FEIS. BLM’s reference 

conditions need to be compared to back‐casting and historical accounts of forests in order to be 

regionally appropriate and not based on a non‐validated model. This needs to be corrected by BLM 

by including back‐casting studies to help validate fire models (Whitlock 1992; Colombardi and Gavin 

2010; Baker 2011, 2014; and Dipaolo and Hosten 2015).

Response: The BLM Fire Planning Handbook indicates that Land Use Planning must incorporate 

FRCC (Fire Regime Condition Class) or similar concept (USDI BLM 2012, pp. 2–6). As stated in the 

Draft RMP/EIS, the BLM built the analytic methods in Issue 1 upon the conceptual framework of the 

LANDFIRE Fire Regime Condition Class (FRCC) concept (USDI BLM 2015, p. 177). The Draft 

RMP/EIS discussed several model uncertainties and potential deficiencies as part of the analysis of 

fire resiliency (USDI BLM 2015, pp. 177–178, 1113–1126). As stated in the Draft RMP/EIS, the 

BLM base the natural range of variability on LANDFIRE Biophysical Setting models. These models 

are based on literature, local data, and expert estimate. Further descriptions and references for the 

biophysical setting models are located on the LANDFIRE Program website 

(http://www.landfire.gov/). Use of the LANDFIRE FRCC represents high quality information and 

follows specific policy direction outlined in the BLM Fire Planning Handbook. The Proposed 

RMP/Final EIS has expanded the discussion in the Summary of Analytical Methods in Issue 1 to 

include an acknowledgement of different positions on historic range of variability. 

126. Comment Summary: The BLM should revise the EIS to include a lightning strike analysis to 

determine the risk of losing large blocks of habitat, and the contribution of these landscape features to 

an overall increase of wildfire risk across the landscape.

Response: The BLM did not conduct a lightning strike analysis, because it would not provide 

information necessary to make a reasoned choice between alternatives. The alternatives would have 

no effect on lightning strikes, and the BLM has no reasonable basis on which to evaluate different 

effects of lightning strikes under the alternatives. The Draft RMP/EIS included analysis to identify 

relative risks of large and high-severity wildfires, based on historic fire size, frequency, and severity, 

independent of wildfire ignition cause, to incorporate potential wildfire effects on northern spotted 

owl habitat (Appendix H – Fire and Fuels). This analysis includes the evaluation of lands for their 

relative suitability risk for wildfires, which gives a general sense of forest conditions and their 

locations within the planning area landscape that are most suitable for wildfires. The BLM 

incorporated predictions of fire size, location, and severity into the vegetation modeling. 

127. Comment Summary: Higher fire severity increases the likelihood of transferring wildfire to 

adjoining forestland owners. The BLM should analyze fire severity across the landscape as a function 

of management direction under each alternative in the EIS. The State recommends the BLM should 

work with ODF to develop a high level metric to assess the overall potential transfer of wildfires 

between BLM and private lands.

Response: The Draft RMP/EIS analyzed the effects of the alternatives on fire resistance and fire 

hazard, as such; alternatives resulting in higher fire hazard or lower fire resistance would increase 

the likelihood of transferring wildfire to adjoining landowners. The BLM determined that at this 

scale and scope of analysis, general assumptions regarding forest structure and probable fire 

interaction provided a robust and consistent basis for comparing the effects of the alternatives at an 

appropriate scale. The Draft RMP/EIS did not analyze the effects of the alternatives on fire severity 
1901 | P a g e

directly, because such an analysis would require fine-scale, stand-specific data, particularly related 

to surface fuels and canopy base height changes over time by alternative, which is impractical at this 

scale of analysis. The BLM has clarified information pertaining to ownership patterns and transfer of 

risk in the Background of Fire and Fuels Issue 3. 

128. Comment Summary: Fire risk should be a decision factor among components of alternatives. 

Simple metrics, such as acres treated, can give some rough estimates towards reducing fire risk and 

would be helpful in evaluating management components. With the information provided in the Draft 

RMP/EIS, it is difficult to assess the percentage of acres of dry forests that would be treated over the 

first decade.

Response: The Draft RMP/EIS did include information on acres treated relative to fire risk. The 

analysis described the acres in need of residual harvest activity fuels treatment, and estimated the 

acres of natural hazardous fuels treatments, activity fuels treatments, and silvicultural treatments by 

decade for each alternative (USDI BLM 2015, pp. 240–211, 212, 279–280). As concluded in the 

analysis, the size of the Harvest Land Base and the timber management type and intensity influence 

the amount of acres in each risk category by alternative. The acreage in activity fuels risk categories 

provides an estimate of potential future work needed to reduce the risk associated with activity fuels. 

The purpose and need for the RMP revision includes restoring fire-adapted ecosystems by increasing 

fire resiliency, and the purpose and need noted that active management could positively influence fire 

risk (USDI BLM 2015, p. 10). As such, the BLM will consider how well the alternatives respond the 

purpose of increasing fire resiliency and will evaluate effects of the alternatives on fire risk in 

reaching a decision in the RMP revision. 

129. Comment Summary: The BLM should revise the EIS to incorporate projections of climate 

change into fire behavior modeling.

Response: The Draft RMP/EIS discussed the potential effects of climate change on future wildfire 

behavior. The Draft RMP/EIS identified that most climate change projections indicate that wildfires 

are likely to get larger and more severe in the future. The Draft RMP/EIS explicitly explained why 

the vegetation modeling did not incorporate projections of the effects of climate change on future 

wildfire occurrence and severity. Specifically, the inherent challenges in predicting future stochastic 

events coupled with the uncertainties in climate change predictions make it impossible to forecast 

specifically when and where future wildfires would occur differently than they have occurred in the 

recent past (USDI BLM 2015, pp. 99, 1053–1055). The commenter does not address these 

explanations. 

130. Comment Summary: The BLM should revise the EIS to prohibit salvage harvesting after 

wildfires. Unsalvaged, naturally regenerating stands subjected to high-severity fire should be 

maintained on the landscape to provide important habitat and stand development functions and be 

allowed to regenerate on their own. Logging is not the ecological equivalent to high-severity wildfire 

and salvage logging destroys the natural and biological legacies in post fire landscapes that allow for 

complex forest regeneration.

Response: The Draft RMP/EIS included varied approaches to salvage harvest after disturbances such 

as wildfire (USDI BLM 2015, pp. 41–74). Several action alternatives would prohibit salvage harvest 

in some land use allocations, except where necessary to protect public safety or to keep roads and 
1902 | P a g e

other infrastructure clear of debris. Under the Proposed RMP, salvage harvesting would be 

permissible to recover economic value or minimize economic loss only in the Harvest Land Base. 

The Proposed RMP would prohibit salvage harvesting in Riparian Reserve and Late-Successional 

Reserve, except where necessary to protect public safety or to keep roads and other infrastructure 

clear of debris. 

An alternative that would prohibit salvage harvest on all lands, including the Harvest Land Base 

would not be reasonable because it would not respond to the purpose and need for the RMP revision. 

The Harvest Land Base has management objectives for sustained-yield timber production, which is 

how the alternatives respond to the purpose of the action to provide for a sustained yield of timber. It 

would be unreasonable to prohibit salvage harvest of timber after disturbances in a land use allocation 

dedicated to timber production. 

131. Comment Summary: The BLM should revise the EIS to avoid post‐fire logging in dense, 

mature/old forest stands that experience intense fire; as such, areas tend to provide the highest quality, 

and spatially rarest, complex early seral forest habitat (Swanson et al. 2011, DellaSala et al. 2014). 

The restoration of fire as a process should be a goal in these stands.

Response: The Proposed RMP would prohibit salvage harvest in Late-Successional Reserve, which 

includes older, structurally-complex conifer forest, except where necessary to protect public safety or 

to keep roads and other infrastructure clear of debris. 

The Proposed RMP includes management objectives and management direction related to the 

management of fire as a process on the landscape, including management to restore and maintain 

ecosystem resilience to wildfire, including the application of prescribed fire, and responding to 

wildfires in a manner that provides for public and firefighter safety, while meeting land management 

objectives (Appendix B – Management Objectives and Direction). 

132. Comment Summary: The BLM should revise the EIS because it fails to adequately address the 

direct, indirect, and cumulative impacts that post-fire salvaging has on post‐fire logging feedback 

loops (i.e., whereby areas that burn in a fire are logged and planted with commercial species only to 

burn more intensely in the next fire, and then are logged again later).

Response: There is scientific controversy over the question of whether post-fire salvage harvest 

creates conditions that result in more intense re-burning. A recent publication found that post-fire 

logging reduced woody surface fuels up to four decades following a wildfire in Eastern Washington 

(Peterson, Dodson, and Harrod 2015). Alternatively, a study from the Klamath Region found that

areas that had been salvaged-logged and then planted following the Silver Fire in 1987 burned more 

severely in 2002, relative to previously unmanaged areas (Thompson, Spies, and Ganio 2008). These 

researchers also found that following severe wildfire in this region, young vegetation is at increased 

risk of re-burning at high-severity, regardless of whether it has been managed. The Proposed 

RMP/Final EIS has expanded the discussion of this conflicting science and the BLM identifies how 

this scientific conflict influences the BLM’s ability to predict resource impacts in the Fire and Fuels 

section of Chapter 3.

133. Comment Summary: The BLM should revise the EIS because all alternatives proposed fail to 

adequately address post-disturbance salvage (or fuels mitigation) as a viable alternative to reducing 

high-intensity fires on the landscape.
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Response: All alternatives in the Draft RMP/EIS addressed post-disturbance salvage harvest and 

fuels treatments. The Draft RMP/EIS included varied approaches to salvage harvest after disturbances 

such as wildfire (USDI BLM 2015, pp. 41–74). The commenter does not identify an approach to postdisturbance salvage or fuels mitigation that they believe that the BLM did not analyze in the Draft 

RMP/EIS. 

134. Comment Summary: The BLM should revise the EIS to integrate fish and wildlife habitat 

objectives and mitigation actions into fire restoration and rehabilitation programs and actions 

intended to manage fuels or salvage burned‐over areas.

Response: The alternatives considered in the Draft RMP/EIS included management direction and 

Best Management Practices designed to integrate aquatic habitat objectives and northern spotted owl 

recovery objectives. Under all alternatives, the Riparian Reserve and Late-Successional Reserve 

incorporate direction for the management of fuels in a manner that is beneficial to habitat objectives 

(USDI BLM 2015, pp. Appendix B). Specific Best Management Practices, designed to meet water 

quality goals, apply to fire and fuels management actions, including those for fire restoration and 

rehabilitation (USDI BLM 2015, pp. Appendix I). The commenter does not identify an approach to 

integrating habitat objectives and fire restoration and rehabilitation that they believe that the BLM did 

not analyze in the Draft RMP/EIS. 

135. Comment Summary: The BLM should revise the EIS to include partial salvage approaches in 

land use allocations. The Draft RMP/EIS presents a range of post‐fire salvage options, both within the 

Harvest Land Base and the reserves, that largely either salvage or not within entire land use 

allocations. Application of ‘partial salvage’ approaches could be useful in optimizing ecological 

function, reducing fire transfer risk to adjoining lands, retaining access needs, and providing for 

firefighter safety in subsequent fire events.

Response: The Draft RMP/EIS included varied approaches to salvage harvest after disturbances such 

as wildfire (USDI BLM 2015, pp. 41–74). The commenter mischaracterizes the approach to salvage 

in the alternatives as “either salvage or not.” Several action alternatives would prohibit salvage 

harvest in some land use allocations under some circumstances, and would direct salvage in some 

land use allocations under some circumstances. Under the Proposed RMP, salvage harvesting would 

be permissible to recover economic value or minimize economic loss only in the Harvest Land Base. 

The Proposed RMP would prohibit salvage harvesting in Riparian Reserve and Late-Successional 

Reserve, except where necessary to protect public safety or to keep roads and other infrastructure 

clear of debris. 

136. Comment Summary: BLM needs to manage fire prevention on O&C lands to protect private 

land. The EIS needs to address more than just fire resilience, but also wildfire response—both in the 

context of active fire as well as post‐fire restoration, harvest, and reforestation activities. Congress 

recognized that to avoid problems, the fire protection on O&C lands must be in conformity with the 

fire protection programs of the State of Oregon.

Response: The Draft RMP/EIS explained that the full range of wildfire response tactics would be 

available under all alternatives. Maintenance of fire suppression-related infrastructure would not 

change among alternatives. The ability to conduct salvage harvest for purposes of protecting human 

health and safety within the dry forest would be available under all alternatives. Because these factors 
1904 | P a g e

would not differ among the alternatives, there is no reasonable basis on which to identify a difference 

in the effect of the alternatives on wildfire response at this scale of analysis, beyond the effects to 

landscape-level fire resilience, stand-level fire resistance, and stand-level fire hazard (USDI BLM 

2015, p. 212). The commenter does not address this explanation. 

The Oregon Department of Forestry currently provides fire protection and prevention services on 

Western Oregon BLM-administered lands under the Western Oregon Fire Protection Services 

contract. All alternatives and the Proposed RMP would continue to manage wildfire response 

consistent with current Federal wildland fire policy (USDA and USDI 2009, USDI BLM et al. 2015). 

137. Comment Summary: The BLM should create a land use allocation designating all areas that are 

wildland-urban interfaces and ‘ownership perimeter zones’ (within 1 mile of BLM forest boundaries) 

as ‘fuels management emphasis areas.’ Priority action should be taken to reduce the risk of fire by 

treating forests in this ‘Fuels Management Emphasis Area.’ This area would be managed to address 

the forest protection values of adjacent non‐federal landowners (e.g., roads, wildfire, pests, etc.), and 

the impact of lacking BLM management on these neighboring non‐federal lands.

Response: The BLM has not established a land use allocation designation specifically emphasizing 

fuels management. Across all land use allocations, the BLM has identified management direction to 

“create fuel beds or fuel breaks that reduce the potential for high-intensity fire spread within the 

wildland urban interface and in close proximity to other highly valued resources (Appendix B –

Management Objectives and Direction.) This management direction applies to all alternatives. The 

alternatives did not create a separate land use allocation for fuels management because this 

management direction would be included in all land use allocations in the alternatives. In addition to 

this management direction, the analytic extents of Issues 3 and 4 in the Fire and Fuels section both 

emphasize BLM-administered lands within one mile from Wildland Developed Areas. The Proposed 

RMP/Final EIS expanded the discussion of ownership patterns within the Community Wildfire 

Protection Plan defined Wildland Urban Interface in the Proposed RMP/Final EIS. 

138. Comment Summary: The Draft EIS failed to address a strategy to reduce the number of large 

fires or how the agency intends to reduce the number of acres burned.

Response: None of the alternatives in the Draft RMP/EIS specifically included a strategy to reduce 

the number of large fires or reduce the number of acres burned. As stated in the Draft RMP/EIS, there 

is no accurate way to predict the exact location and timing of wildfires, and there is no reasonable 

basis upon which the BLM could analyze how land management at this scale could affect the number 

of large fires or the number of acres burned (USDI BLM 2015, pp. 211–212). Instead, the purpose of 

the action includes improving the resilience and resistance of frequent fire systems, so that if, and 

when, fires do occur, there would be a lower likelihood that fire would substantially alter forest 

structure, composition, or function. The commenter does not suggest a specific strategy that they 

believe that the BLM did not analyze in the Draft RMP/EIS. 

139. Comment Summary: Since no alternative has substantial decreases in high‐severity fire risks, 

the RMP should include information regarding what additional actions are needed to substantially 

reduce high‐severity fire risk.

Response: The Draft RMP/EIS analyzed in detail the effects of the alternatives on fire resiliency, fire 

resistance, wildfire hazard, and risk from activity fuels. The Draft RMP/EIS did not specifically 
1905 | P a g e

analyze the risk of high-severity fire directly, because such an analysis would require fine-scale, 

stand-specific data, particularly related to surface fuels and canopy base height changes over time by 

alternative, which is impractical at this scale of analysis. The Draft RMP/EIS concluded that all 

alternatives would increase stand-level fire resistance and reduce wildfire hazard on BLMadministered lands compared to current conditions. The commenter does not identify any additional 

alternatives that they believe that the BLM should have analyzed in the Draft RMP/EIS. 

140. Comment Summary: BLM needs to work with USFS to implement a cohesive wildland fire 

management strategy that allows more fires to burn unimpeded in the back country to reduce 

widespread damage to ecosystems from extensive and often ineffective fire suppression (see 

Ingalsbee and Roja 2015).

Response: Currently, the Oregon Department of Forestry provides wildfire protection services on 

BLM-administered lands, and operates in an inter-agency capacity with the U.S. Forest Service for 

border fires, via the Southwest Oregon Interagency Fire Management Plan (USDA FS, USDI BLM, 

ODF, and USDI NPS 2014). None of the alternatives would alter the inter-agency working 

relationships with State or Federal agencies in wildfire response coordination. For management on 

BLM-administered lands, the alternatives include management direction that would allow the use of 

natural fire to meet resource objectives (Appendix B – Management Objectives and Direction).

141. Comment Summary: The RMP addresses fire issues using fundamentally flawed forestry 

management science. The RMP/DEIS fire and fuels treatments are based on faulty premises, instead 

of evolutionary fire science and understanding of natural fire regimes from which native plants and 

animals evolved and of their importance to sustain natural community ecosystems. The approach to 

fire in all alternatives perpetuates unsustainable and destructive timber industry driven forestry 

management paradigm. BLM’s RMP shows inherent biases reflected in the partial treatment of fire as 

a threat that needs suppression via mechanical treatments.

Response: The alternatives considered in the Draft RMP/EIS would allow that all natural ignitions 

can be managed with the full suite of fire management options (Appendix B – Management 

Objectives and Direction), including using fire to meet resource and land use objectives, when and 

where conditions might allow. Nevertheless, all alternatives also provide for a continuing need for 

wildfire suppression and fire risk mitigation, given the checkerboard land ownership pattern and that 

large portions of the decision area lie within 1 mile of human developed areas (USDI BLM 2015, pp. 

197–200). The commenter does not specifically identify what forestry management science used in 

the Draft RMP/EIS that they believe is flawed. 

142. Comment Summary: The EIS needs to include a more comprehensive literature review that 

includes the ecosystem benefits of mixed‐severity fires, studies relevant to the region’s fire regimes or 

forest types, the importance of complex early seral forests and their association with future late‐

successional stand development. BLM’s fire science synthesis and Draft RMP/EIS do not provide a 

comprehensive literature review on the ecological importance of mixed‐severity fires in maintaining 

fire‐dependent biodiversity and complex early seral forests (Swanson et al. 2011, DellaSala and 

Hanson 2015); the complex pattern of fire‐vegetation mosaics in this region is associated with high 

biodiversity (Odion et al. 2010, Donato et al. 2012, DellaSala and Hanson 2015) and complex early 

seral forests (Swanson et al. 2011); heterogeneity in fire behavior is an inherent and resilient property 

of mixed evergreen forests undervalued by BLM. This critically important natural heterogeneity 
1906 | P a g e

needs to be recognized in the Proposed RMP/Final EIS for its biodiversity benefits and not just risks 

to ecosystems.

Response: A literature review of heterogeneity in fire behavior in mixed evergreen forests is not 

necessary to understand the potential impacts of the alternatives on fire resiliency, fire resistance, 

wildfire hazard, and risk from activity fuels. The BLM has not included such a literature review in 

keeping with CEQ direction that environmental analyses should not be encyclopedic in nature but 

should focus on the information relevant to the decisions to be made (40 CFR 1500.4). The BLM has 

reviewed the materials referenced. One reference (Donato et al. 2012) had been included in the Draft 

RMP/EIS (USDI BLM 2015, p. 175), and the Proposed RMP/Final EIS has included several of the 

additional referenced citations where applicable to the planning area and issues being analyzed. 

143. Comment Summary: BLM’s fire synthesis lacks a discussion of uncertainty related to thinning 

efficacy in mixed‐severity systems (see Odion et al. 2014a, DellaSala and Hanson 2015) and the EIS 

should recognize that fuel reduction efforts have limits including: the probability that a treated area 

will intersect a fire is very small (5–8 percent, Rhodes and Baker 2008); thinning is ineffective during 

extreme fire behavior, which may increase over time due to climate change (Littell et al. 2009); 

extensive thinning can contribute to fire spread by opening forest stands to increase wind penetration, 

increased light levels and associated plant growth, and increases in fuel loadings left by thinning 

slash. BLM creates the expectation (without quantifying uncertainty or at least reporting on model 

biases) that thinning will reduce fire intensity in mixed‐severity fire regimes that are mainly climate 

driven fire events. The lack of a uncertainty discussion in the fire section of the Draft RMP/EIS and 

supporting appendix, and BLM’s treatment of thinning as fire remediation, runs counter to several 

studies in the region that were not discussed (e.g., Odion et al. 2004, Thompson and Spies 2007, 

Hanson et al. 2009, Odion et al. 2010, Odion et al. 2014a).

Response: The Draft RMP/EIS acknowledged that extreme weather, drought, and prevailing climatic 

conditions have the ability to result in unexpected and extreme fire behavior, regardless of forest 

structure (USDI BLM 2015, p. 188). The Draft RMP/EIS also discussed the potential effects of open 

stands on fuels and fire behavior, including increased drying and surface winds (USDI BLM 2015, 

pp. Appendix H). Issue 4 of the Fire and Fuels section analyzed the increased wildfire risk that 

activity fuels can potentially pose, if they go untreated. The BLM has incorporated additional 

discussions of uncertainty regarding effectiveness of thinning and fuels treatments in the Proposed 

RMP/Final EIS in the Current Fire Climate Environment and Future Trends section of Chapter 3.

The BLM reviewed the materials referenced. While several of the references are regionally relevant, 

the literature referenced largely refers to the effects of even-aged management (plantations and 

salvage harvest and rapid reforestation) on resulting fire severity, thus providing information related 

to certain types of treatments and forest structure and resulting fire interactions. The BLM has 

incorporated several of these citations in reference to these types of treatments and forest structure. 

Unfortunately, the planning area does not have any regionally specific studies that specifically 

examine the effectiveness of fuels reduction treatments, including uneven-aged management or noncommercial thinning and prescribed burning, on resulting fire severity and fire behavior. As stated, a 

wildfire intersecting a fuels treatment is a relatively rare occurrence. However, over the past few 

years, there have been several opportunities, locally (Douglas Fire Complex, Twincheria Fire, 

Worthington Road Fire, Stratton Fire, Speaker Road Fire, Reeves Creek Fire, and several more), to 

observe compelling anecdotal evidence of these types of treatments moderating the fire behavior and 

fire effects when intersected by wildfires. The Proposed RMP/Final EIS has added expanded 

discussions of the effects of stand treatments on fire behavior and fire effects. 
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144. Comment Summary: For the Klamath‐Siskiyou ecoregion, plantations burned in twice as much 

high severity area compared to natural forests (Odion et al. 2004). The influence of plantation 

management on fuel structure and fire severity needs to be included to present a more complete and 

regionally specific review of the pertinent literature. BLM needs to include the relevant regionally 

specific study (Odion et al. 2004) that documented greater high severity acres in plantations and 

contrast complex early seral with early seral produced by forestry for this table to be based on best 

science. Additionally, long‐unburned areas with closed forest canopies in mixed evergreen forests of 

this region support more low severity fire than recently burned areas (Odion et al. 2004).

Response: The Draft RMP/EIS did reference Odion et al. (2004) and incorporated the findings of 

plantations burning at high fire severity and multi-layered closed canopy forest burning at low fire 

severity in the analytical assumptions (USDI BLM 2015, pp. 193, 197, 1127–1128). 

145. Comment Summary: The Draft RMP/EIS does not include relevant peer‐reviewed studies that 

have shown no recent (since 1984) increases in acres burned or fire severity in this region (see 

Hanson et al. 2009, Odion et al. 2014 a, b). The discussion of presumed recent increases in fire 

extent/severity (p. 176) is based on a citation to an industry document (OFRI) and BLM’s prior 

WOPR and to an analysis by Westerling et al. (2006) that did not show an increase in fire severity nor 

is it appropriate to this region. Industry citations are not peer reviewed documents and neither is the 

BLM’s prior WOPR – BLM needs to rectify the omission of regionally‐specific peer‐reviewed 

literature that runs contrary to BLM’s assumptions.

Response: It is not clear how the commenter believes the cited literature “runs contrary to BLM’s 

assumptions.” The commenter cites studies to support the assertion that there has been no recent 

increase in acres burned or fire severity since 1984. While the Draft RMP/EIS acknowledged studies 

that the frequency of large fires and the acre burned have increased across the West and in Oregon, 

the Draft RMP/EIS modeled future wildfires based on the regional wildfire history from 1970 to 2013 

(USDI BLM 2015, pp. 1045–1056). That is, the Draft RMP/EIS did not project forward any increase 

in acres burned or fire severity compared to the past four decades. The Draft RMP/EIS specifically 

acknowledged the uncertainty around trends related to fire severity and made no attempt to 

incorporate predictions of increased future fire severity (USDI BLM 2015, pp. 1050–1051). The 

BLM has reviewed the references identified and did not cite Hanson et al. (2009) or Odion et al. 

(2014 a/b), because they do not add any relevant information, given that the BLM has already 

concluded that there is no statistically significant trend in fire severity to incorporate into the wildfire 

modeling. 

146. Comment Summary: The Fuels and Fire section’s “Affected Environment” section for Issue 1 

(p. 182) states there is a slight overabundance of early seral without contrasting early seral produced 

by industrial forestry vs. that produced by natural disturbances. There are documented differences in 

habitat quality between the two that need discussion (see Swanson et al. 2011, DellaSala et al. 2014). 

Additionally, Figure 3‐33 lacks acreage value for early seral.

Response: The BLM has added discussion to the Proposed RMP/Final EIS that clarifies the seralstage classification is based on structure and does not necessarily represent a functioning ecological 

state. The BLM has carried this acknowledgement into Issue 1 in the Fire and Fuels section of 

Chapter 3. The Proposed RMP/Final EIS corrected an error in the early seral acreage in Figure 3-33

in the Draft RMP/EIS. 
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147. Comment Summary: The Draft RMP/EIS (p. 186) only mentions fire exclusion as resulting in 

departure from reference condition. The BLM needs to discuss how timber management has 

increased departure from reference conditions as well. BLM’s lack of discussion on timber impacts in 

this section is not based on best science.

Response: The Draft RMP/EIS acknowledged that land management practices, such as timber 

management, combined with fire exclusion, have resulted in stands that are overly dense and missing 

large, fire-resistant trees (USDI BLM 2015, p. 175). 

Fisheries 

148. Comment Summary: Unexplained in the DEIS is the scientific basis for concluding that the 

proposed, substantially smaller Riparian Reserve and the proposed increased timber harvest activities 

within the smaller Reserves are sufficient for the needs of salmon and other riparian-dependent 

species.

Response: The Draft RMP/EIS does not make any comprehensive conclusion about whether the 

Riparian Reserve designs in the action alternatives are “sufficient for the needs of salmon and other 

riparian-dependent species.” The Draft RMP/EIS provides analytical conclusions regarding the 

comparative effect of the alternatives related to specific issues. A conclusion about whether such 

effects constitute a management approach that is “sufficient for the needs” of ESA-listed fish is 

appropriately addressed through the ESA consultation process. 

The commenter incorrectly states that the Draft RMP/EIS is making a conclusion about the 

sufficiency of the management approach for “other riparian-dependent species.” As explained in the 

Draft RMP/EIS, none of the action alternatives in the Draft RMP/EIS includes the Aquatic 

Conservation Strategy in its entirety, as found in the No Action alternative, which included an 

objective of supporting well-distributing populations of riparian-dependent species, based on the U.S. 

Forest Service organic statute and implementing regulations (USDI BLM 2015, pp. 22–23). The 

BLM has not included a management objective for the Riparian Reserve based on the needs of all 

“riparian-dependent species,” but has included objectives consistent with BLM laws, regulations, and 

policy. 

Effects analysis in NEPA documents must demonstrate that the BLM took a ‘hard look’ at the effects 

of the action. A ‘hard look’ is a reasoned analysis containing quantitative or detailed qualitative 

information (USDI BLM 2008, p. 55). The Draft RMP/EIS includes a detailed and quantified analysis 

of the effect of the alternatives on wood supply to streams, sediment delivery to streams, stream 

temperatures, and peak water flows (USDI BLM 2015, pp. 219–233, 286–318). That analysis 

demonstrates that, for each of these issues, some or all of the action alternatives would result in 

effects that are equally protective of ESA-listed fish and water quality as the No Action alternative. 

The analysis in the Draft RMP/EIS contains quantitative information on the significant effects on 

ESA-listed fish at issue and interprets that information to form analytical conclusions about the 

comparative effects of the alternatives. That analysis constitutes a ‘hard look’ and provides the 

scientific basis for evaluating the effects of the alternatives on ESA-listed fish and water quality. 

In a December 18, 2015 letter from NMFS to the BLM, NMFS acknowledged that these comments 

misinterpreted the Draft RMP/EIS and asked that the comments be ignored. NMFS clarified that they 

believe that the approach in the Northwest Forest Plan is not the only approach that would ensure the 
1909 | P a g e

protection and recovery of threatened and endangered fish, and that the best available science also 

supports an approach modified from Alternative A or D that includes a one site-potential tree height 

Riparian Reserve on fish-bearing streams and perennial streams. 

149. Comment Summary: The DEIS should disclose the potential consequences of reducing aquatic 

resource protections for other agencies and conservation and land management efforts.

Response: The commenter’s assertion that all action alternatives would reduce aquatic resource 

protection is without foundation and contrary to the analytical conclusions in the Draft RMP/EIS. The 

reduction in Riparian Reserve buffer size on some streams in the action alternatives does not directly 

equate to adverse effects on ESA-listed fish or water quality. The analysis in the Draft RMP/EIS 

demonstrates that, for each of the significant issues affecting ESA-listed fish and water quality, some 

or all of the action alternatives would result in effects that are as equally protective of ESA-listed fish 

and water quality as the No Action alternative (USDI BLM 2015, pp. 217–235, 286–320). Therefore, 

all of the alternatives have the ability to fulfill the BLM’s present role in coordinating conservation 

and land management efforts with other agencies. The commenter provides no basis for the assertion 

that other agencies’ efforts would be less effective under any of the action alternatives.

150. Comment Summary: The DEIS asserts (p. 225) that there will be no difference in large wood 

production among the alternatives. This assertion is clearly in error, for reasons discussed below, but 

it is also problematic because the basis for this statement was based on the obscure and poorly 

described wood modeling exercise performed as part of the 2008 WOPR FEIS (which was 

subsequently withdrawn, in part due to extensive criticism as to its technical merits).

Response: The commenter mischaracterizes the assertion in the Draft RMP/EIS, which states, “There 

is no meaningful difference discernible at this scale of analysis among the alternatives in their effect 

on potential wood contribution” (USDI BLM 2015, p. 225; emphasis added). The Draft RMP/EIS 

further acknowledges, “There are differences in the design of the alternatives that may have 

differential effects on potential wood contribution that the BLM cannot quantitatively evaluate at this 

scale of analysis.” The Draft RMP/EIS proceeds to address qualitatively the specific differential 

effects that the alternatives could have on potential wood contribution based on Riparian Reserve 

widths, inner zone widths, and management direction for Riparian Reserve thinning (USDI BLM 

2015, pp. 228–230). The commenter does not acknowledge or address this discussion of the specific 

differential effects that the alternatives could have on potential wood contribution. In a December 18, 

2015 letter from NMFS to the BLM, NMFS acknowledged that these comments misinterpreted the 

Draft RMP/EIS and asked that the comments be ignored. 

The commenter mistakenly asserts that the “2008 WOPR FEIS” was withdrawn because of 

“extensive criticism as to its technical merits.” The Secretary of the Interior withdrew the Records of 

Decision for the 2008 FEISs in July 2009, because the approval of the Records of Decision was in 

‘legal error’ because the BLM had not conducted Section 7 consultation under the ESA. In 

withdrawing the Records of Decision, the Secretary raised no question about the technical merits of 

the EIS on which the 2008 FEIS Records of Decision were based, and the Secretary did not withdraw 

the EIS. Subsequent to the withdrawal by the Secretary, the Court in DTO v. Salazar found that the 

Secretary’s decision to withdraw the Records of Decision was arbitrary, capricious, and an abuse of 

discretion. In Pacific Rivers Council et al. v. Shepard, the Court vacated the 2008 FEIS Records of 

Decision, again because the BLM had not completed Section 7 consultation under the ESA, without 

mention of the technical merits of the EIS on which the 2008 FEIS Records of Decision were based. 
1910 | P a g e

Thus, neither the Secretary nor the Court raised any question about the technical merits of the EIS on 

which the 2008 FEIS Records of Decision were based. 

Furthermore, the commenter suggests that the BLM cannot use analytical information from the 2008 

FEIS. It is appropriate for the BLM to rely on information in the 2008 FEIS to the extent it provides 

high quality information relevant to the analysis for this RMP revision. The CEQ regulations direct 

agencies to incorporate such information by reference (40 CFR 1502.21). The BLM NEPA Handbook 

explains that the BLM can incorporate any such information by reference if the information is 

reasonably available for public inspection (USDI BLM 2008, p. 26). The analysis in the 2008 FEIS 

does provide high quality information relevant to this analysis and is available for public inspection. 

Thus, it is appropriate for the Draft RMP/EIS to incorporate that information from the 2008 FEIS by 

reference. 

151. Comment Summary: Assertions that thinning will improve habitat conditions should be viewed 

cautiously and with skepticism. The burden of proof should remain on thinning proponents that 

thinning is likely to accelerate attainment of conservation goals.

Response: RMPs establish management direction to accomplish the management objectives, as 

directed in the BLM planning handbook (USDI BLM 2005, pp. 11–13). Actions implementing the 

RMP must be in conformance with the RMP; this means that the action is specifically provided for in 

the RMP, or if not specifically mentioned, shall be clearly consistent with the terms, conditions, and 

decisions of the approved plan (43 CFR 1601.0–5(b)). That is, the BLM may take actions if the 

actions are specifically directed in the management direction or clearly consistent with the 

management direction of the approved RMP. 

The 1995 RMPs directed the implementation of those silvicultural activities (such as thinning) 

“...needed to attain Aquatic Conservation Strategy objectives.” This required a test of any such 

management actions as thinning against broad-based ecological goals. This approach of testing 

implementation actions against management objectives was generally inconsistent with the BLM 

planning process. As a result, the requirements in the 1995 RMPs unnecessarily confused decisionmaking for thinning in Riparian Reserve by requiring testing site-specific projects against broad and 

aspirational goals at multiple spatial scales. 

In contrast, the Proposed RMP and all action alternatives provide specific management direction 

regarding where and under what circumstances to thin stands in the Riparian Reserve (Appendix B –

Management Objectives and Direction). The evaluation of proposed thinning in the Riparian Reserve 

under the Proposed RMP or any action alternative would be solely a test of conformance with the 

applicable management direction. Under the Proposed RMP and all action alternatives, there would 

be no “burden of proof” related to thinning in the Riparian Reserve beyond evaluating whether the 

action would be consistent with the management direction (as with all implementation actions), and 

there would be no test of such thinning against “attainment of conservation goals.” The BLM would 

evaluate whether implementation actions would be successfully accomplishing management 

objectives in effectiveness monitoring of the RMP (Appendix V – Monitoring Plan for the Proposed 

RMPs).

152. Comment Summary: The RMP needs to include a complete evaluation of how artificial 

fertilizer will influence water resources, anadromous fish, and critical habitat.
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Response: Under all alternatives, the BLM would not apply fertilizer in the Riparian Reserve. The 

Proposed RMP has added specific management direction that would preclude aerial application of 

fertilizer (Appendix B – Management Objectives and Direction). The Riparian Reserve would 

provide sufficient nutrient filtering to ensure that any fertilizer application in the Harvest Land Base 

would not have any significant effect on water resources, anadromous fish, or designated critical 

habitat for fish as discussed in the Fisheries and Hydrology sections of Chapter 3. 

153. Comment Summary: Analysis is needed to address the special needs of streams and cold water 

fish in the Medford BLM District where the dry forest classification dominates.

Response: The potential effects of the alternatives on fish in the dry forest do not differ from the 

other portions of the decision area. The relevant issues for analysis of effects on fish relate to wood 

supply to streams, sediment delivery to streams, and stream temperature. The Draft RMP/EIS 

analyzed these effects similarly in the dry forest as in the rest of the decision area. The commenter 

does not identify any error in that analysis or any significant effect on fish not addressed in that 

analysis. 

154. Comment Summary: There is very little information regarding the shortnose and Lost River 

suckers in the DEIS.

Response: The Proposed RMP/Final EIS has added information on the Lost River and shortnose 

suckers within the planning area (see the Fisheries section in Chapter 3). There is no Lost River 

sucker critical habitat on or adjacent to BLM-administered lands in the planning area. Approximately 

9 miles (7 percent) of shortnose sucker critical habitat is adjacent to BLM-administered lands in the 

planning area and 1,076 acres adjacent to BLM-administered lands, primarily around the Gerber 

Reservoir in the Klamath Falls Field Office. 

155. Comment Summary: The RMP/DEIS inadequately mapped the linear extent of critical habitat 

for federally listed fishes. Critical habitat helps focus Federal, tribal, state, and private conservation 

and management efforts in such areas. Management efforts may address special considerations 

needed in critical habitat areas—including conservation regulations that restrict both private and 

Federal activities.

Response: In conducting the analysis and in designing the alternatives, the BLM used datasets 

provided by the NMFS and BLM datasets on fish presence to map fish-bearing streams and streams 

with critical habitat for ESA-listed fish. The BLM used the NMFS data on critical habitat specifically 

in the design of the subwatershed classes in the Proposed RMP (see Chapter 2). The Proposed 

RMP/Final EIS has included maps of critical habitat in Appendix I – Fisheries. 

156. Comment Summary: The RMP/DEIS fails to disclose that supposedly ‘fishless’ stream channels 

actually provide an important habitat. This could allow more intensive logging practices in areas that 

do not contain fish. The RMP/DEIS fails to identify the need to map these critical habitats as ‘fish’

streams.

Response: The BLM acknowledges that streams that appear to be non-fish-bearing streams can 

provide important habitat under some circumstances, and that non-fish-bearing streams are important 

components of the stream network, affecting downstream fish habitat. Under all action alternatives 
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and the Proposed RMP, the Riparian Reserve is the same for fish-bearing perennial streams, fishbearing intermittent streams, and non-fish-bearing perennial streams. Therefore, all streams that could 

provide habitat for fish would receive the same level of protection under all action alternatives and 

the Proposed RMP. 

157. Comment Summary: The RMP/DEIS failed to analyze migration barriers to federally listed 

fishes. The RMP/DEIS has no plan for the removal of coho passage barriers. The RMP/DEIS fails to 

provide a schedule for removing priority coho passage barriers within the decision area and fails to 

provide coordinated actions with ‘partners’ to remove coho passage barriers within the planning area.

Response: The Analysis of the Management Situation specifically described the fish passage barriers 

in the planning area, their effect on fish populations, and the effect of removal of these barriers on 

fish populations (USDI BLM 2013, p. 36). The Draft RMP/EIS incorporated that discussion by 

reference (USDI BLM 2015, p. 219). There is no reasonable basis on which the BLM could forecast a 

difference among the alternatives or the Proposed RMP in the future removal of fish passage barriers. 

All alternatives include management direction to remove or replace culverts that currently block fish 

passage with culverts that pass fish and aquatic organisms at a range of flows. Removal of passage 

barriers is an important component of watershed restoration. The Proposed RMP/Final EIS has added 

discussion of how the BLM would implement watershed restoration under the Proposed RMP 

(Appendix X – Guidance for the Use of the Completed RMPs). Specifically, the BLM will use the 

BLM Western Oregon Aquatic Restoration Strategy in determining priorities for watershed 

restoration. The BLM Western Oregon Aquatic Restoration Strategy presents a restoration strategy 

that uses a combination of habitat based intrinsic potential modeling and professional field knowledge 

to focus restoration efforts in areas deemed likely to have the highest production potential for fish 

species of interest. 

Although the BLM can coordinate with adjacent landowners in implementing restoration strategies, 

directing the removal of passage barriers on other land ownerships is not within the BLM’s authority 

and not within the scope of the RMP. 

158. Comment Summary: The DEIS/RMP failed to identify locally relevant management direction, 

specific management objectives for critical habitat, and site specific interagency coordination needed 

to recover bull trout.

Response: The Proposed RMP/Final EIS has expanded the discussion of bull trout in the decision 

area (see the Fisheries section of Chapter 3). A total of 3.6 miles of bull trout critical habitat occur 

within the decision area, comprising less than 0.1 percent of bull trout critical habitat. Bull trout are 

affected by the same key ecological processes as the ESA-listed anadromous salmonids in the 

decision area, allowing them to be analyzed together at this scale of analysis. 

159. Comment Summary: Beaver activity increases coho production and needs to be addressed.

Response: The BLM agrees that beaver activity can improve habitat conditions for coho salmon. 

Riparian restoration treatments adjacent to coho salmon streams would promote forage and building 

material by enhancing streamside hardwoods and vegetation diversity. The Proposed RMP has added 

management direction to promote beaver habitat restoration in the Riparian Reserve (Appendix B –

Management Objectives and Direction). 
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160. Comment Summary: The RMP alternatives failed to analyze impacts to the green sturgeon in 

their analysis.

Response: Because of the very limited distribution of the southern DPS of green sturgeon in the 

decision area, the BLM would have very limited ability to affect these fish through land management 

actions. The Proposed RMP/Final EIS has added information regarding the distribution of the 

southern DPS of green sturgeon and its critical habitat relative to BLM-administered lands and 

potential effects in the Background of the Fisheries section in Chapter 3. 

161. Comment Summary: The DEIS/RMP fails to adequately describe how the cumulative effects of 

logging, roads, and other disturbances caused by timber operations have depleted large wood in 

streams and depleted future sources of large wood for 100 years or more.

Response: The Draft RMP/EIS summarized the effect of past actions on large wood in streams and 

the future sources of large wood (BM 2015, pp. 222–223). The Proposed RMP/Final EIS has 

expanded the discussion of the effects of past actions on large wood in streams and the future sources 

of large wood by incorporating by reference background information from the Analysis of the 

Management Situation (USDI BLM 2013, pp. 32–36) and the 2008 FEIS (USDI BLM 2008, pp. 372–

390) regarding key ecological processes affecting fish population and aquatic ecosystems. 

162. Comment Summary: The RMP/DEIS does not provide for streambed stability monitoring.

Response: The Proposed RMP/Final EIS includes a monitoring plan for the Proposed RMP in 

Appendix V – Monitoring Plan for the Proposed RMPs, which specifically states that the BLM 

would continue to rely on the existing interagency effectiveness monitoring modules to address key 

questions about whether the RMP is effectively meeting the objectives. The aquatic and riparian 

effectiveness monitoring program measures in-channel attributes, which provides a basis for 

evaluating streambed stability (Appendix V – Monitoring Plan for the Proposed RMPs).

163. Comment Summary: The RMP/DEIS fails to assess the cumulative effects of decreased summer 

flows in coho critical habitat.

Response: The Proposed RMP/Final EIS has added discussion explaining that the effects on low 

water flows are an issue that the BLM considered but did not analyze in detail. Given the no-harvest 

Riparian Reserve along streams and the limited extent of the Harvest Land Base under all 

alternatives, there is no reasonably foreseeable effect of harvesting outside of Riparian Reserve on 

low water flows (see the Hydrology section of Chapter 3). Given that none of the alternatives would 

have a reasonably foreseeable effect on low water flows, there is no need for an analysis of the 

cumulative effects of other action on low water flows. 

164. Comment Summary: The RMP/DEIS does not address the cumulative effects of mining on coho 

habitat.

Response: The Proposed RMP/Final EIS has added discussion of the potential effects of mining on 

fisheries (see the Fisheries section of Chapter 3). 
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Forest Management 

165. Comment Summary: The BLM should revise the EIS because it applies the wrong definition of 

‘sustain’ to timber harvest calculations. The EIS applies the definition as “supply, support, or 

nourish.” The intended meaning of ‘sustain’ in the O&C Act is to “preserve, maintain, and prolong in 

a conservation context.”

Response: The Draft RMP/EIS appropriately applied the definition of “sustain” in the context of 

forest management for a sustained yield of timber as directed under the O&C Act (Glossary). 

Sustained yield is a forestry term that defines the level of timber harvesting that can take place on a 

forested area in perpetuity, at a given intensity of management; in other words, the level of timber 

harvest that can be maintained over time. 

Therefore, complying with the principles of sustained yield requires the BLM to verify 

mathematically that timber harvest levels will not decline over time due to overcutting practices. For 

the Proposed RMP and alternatives, the BLM has modeled a repeated cycle of harvest and regrowth 

that does not decrease over time (Appendix C  Vegetation Modeling, for more details on 

methodology). The BLM has applied the definition of sustained yield as intended under the O&C 

Act: to provide for a maintainable level of harvest, guarding against the overcutting that the O&C Act 

sought to end. 

166. Comment Summary: The BLM should revise the EIS to distribute harvest levels and annual sale 

quantities (ASQs) evenly throughout the entire decision area.

Response: In accordance with the O&C Act, the BLM calculated a sustained-yield level for each of 

the six designated sustained-yield units, which currently correspond with the boundaries for Coos 

Bay, Eugene, Medford, Roseburg, and Salem Districts, and the area west of Highway 97 in the 

Klamath Falls Field Office. Inputs into this calculation include the inherent timber productivity of the 

land, current timber inventories, intensity of timber harvest, and areas reserved from timber harvest to 

help meet BLM’s obligations under the Clean Water Act and the Endangered Species Act, among 

other laws, as well as meet the purpose and need for the action and the management objectives 

described in the alternatives. The annual sustained yield of timber calculation is an output of these 

various input factors and, because of differences in forest ecosystems and differences in approaches to 

meeting other laws, the result is different sustained-yield volumes in each sustained-yield unit. 

167. Comment Summary: The BLM should revise the EIS to allow for on-site discretion when 

selecting modern harvesting methods rather than limiting them beforehand. The EIS should also 

allow road building where necessary for efficient operations, and reduce the reliance on more 

expensive helicopter logging.

Response: The BLM agrees that many harvesting decisions are best informed based on site-specific 

information. The action alternatives do provide management direction that directs and restricts 

harvesting methods, such as requiring a range of green tree retention levels or a suite of harvesting 

techniques. The BLM has developed these restrictions as necessary to comply with the guidance in 

the RMP revision, which directed that all action alternatives provide a high degree of predictability 

and consistency about implementing land management actions (USDI BLM 2015, p. 12). 
1915 | P a g e

Nevertheless, the BLM disagrees that management direction developed at this planning level would 

unreasonably restrict site-specific decisions to select harvest methods and logging methods prior to 

project implementation. The Proposed RMP allows wide discretion on harvest methods employed and 

includes a comprehensive set of Best Management Practices that BLM timber sale planners can use to 

customize contract stipulations to site-specific conditions. The Proposed RMP also directs the BLM 

to allow new road construction based on operational needs (Appendix B – Management Objectives 

and Direction, Appendix J – Best Management Practices). Helicopter (aerial) yarding will continue 

to be required in certain circumstances based on site-specific information, as the BLM implements the 

RMP; however, the BLM would identify yarding methods based on site-specific review during 

implementation project planning and not on determinations made at this larger-scale of analysis. 

168. Comment Summary: The BLM should revise the EIS because the BLM uses subjective terms to 

describe logging intensity without providing data or literature to support classifications. Retaining 5–

15 percent of the forest in a cut block is more extreme than moderate. The BLM provides no basis for 

quantifying how these intensities relate to wildlife impacts, soil, hydrology, cumulative effects, fire 

risks, etc. What the BLM classifies as low intensity in owl habitat has no basis in any literature on 

intensity of effects of logging on the northern spotted owl.

Response: The BLM chose to label Harvest Land Base sub-allocations in the Draft RMP/EIS 

conceptually, describing the management approaches in each relative to each other. The Harvest Land 

Base sub-allocation names listed in order of intensity from highest to lowest follow: High Intensity 

Timber Area (0 percent retention clearcuts), Moderate Intensity Timber Area (5–15 percent retention 

variable-retention regeneration harvest), Low Intensity Timber Area (15–30 percent retention 

variable-retention regeneration harvest), Uneven-aged Timber Area (fire resiliency uneven-aged 

management), and Owl Habitat Timber Area (owl habitat uneven-aged management). The BLM does 

not use these labels to inform analysis of environmental impacts, only to distinguish one suballocation from another. 

169. Comment Summary: The BLM should revise the EIS because variable-retention or clearcutting 

on BLM lands is not necessary to create complex early successional habitat, since natural 

disturbances have been creating this sort of habitat in abundance. Leaving burned areas unsalvaged 

and unplanted would provide all of the complex early seral habitat necessary, and therefore 

clearcutting is not needed.

Response: The range of alternatives in an EIS for an RMP must present reasonable alternatives to 

accomplishing the stated purpose and need for action. The Draft RMP/EIS evaluated a variety of 

management intensities within the Harvest Land Base in the action alternatives in order to evaluate 

tradeoffs related to timber production and forest structural development, along with other 

environmental effects. As explained in the Forest Management section in Chapter 3, the higher 

intensity management practices tend to produce higher levels of sustained-yield timber production on 

a given acre of timberland. 

All of the action alternatives include either variable-retention harvest or clearcutting on some portion 

of the decision area, to achieve a variety of purposes. All action alternatives would apply either 

variable-retention harvest or clearcutting to produce timber to contribute to the attainment of the 

Allowable Sale Quantity (USDI BLM 2015, pp. 276–280). Alternatives B and D include producing 

complex early successional ecosystems as one of several purposes for applying variable-retention 

harvest (USDI BLM 2015, pp. 949, 951, 978). Alternatives A and C, the only alternatives that would 

apply clearcutting, do not include producing complex early successional ecosystems as one of several 
1916 | P a g e

purposes for applying clearcut harvests. The Draft RMP/EIS did not contend that variable-retention 

harvest was necessary to create complex early successional habitat, only that it was one permissible 

purpose for implementing variable-retention harvest. That it is not the only means to create complex 

early successional habitat does not invalidate the use of variable-retention harvest for that purpose or 

for the several other purposes described in Alternatives B and D. 

170. Comment Summary: The BLM should revise the EIS because the Forest Management section 

gives no information on how reforestation of logged areas would be achieved. The method of 

reforestation affects the quality and duration of the early seral stage that provides vital habitat for 

certain plants and wildlife. Early seral acreages are listed for the alternatives, but no clear definition is 

given of this stage.

Response: The BLM has added to the Proposed RMP/Final EIS additional information on how the 

BLM would achieve reforestation and additional information on the early seral stage of structural 

development (see the Forest Management section in Chapter 3). The definition of seral stage classes, 

including early seral, are included in the Glossary. The Proposed RMP includes management 

direction requiring reforestation within five years after regeneration harvest (Appendix B –

Management Objectives and Direction). However, the Proposed RMP provides flexibility in specific 

reforestation methods based on site-specific conditions. 

171. Comment Summary: The BLM should revise the EIS because Alternative B risks serious 

reforestation failures on the 282,445 acres on which low and moderate intensity practices would be 

applied because of vegetative competition in western Oregon forests. For these reasons, prohibiting 

tree planting seems inappropriate given statutory responsibilities to manage O&C lands for sustainedyield timber production.

Response: The Proposed RMP includes management direction requiring reforestation within five 

years of regeneration harvest in both the Moderate Intensity Timber Area and the Low Intensity 

Timber Area and would allow both natural and artificial reforestation (tree planting) (Appendix B –

Management Objectives and Direction). 

172. Comment Summary: The BLM should revise the EIS to increase the percent of a stand that may 

be left un-stocked after regeneration harvest from 10 percent under Alternative B to 25 percent. This 

would allow for rare situations where up to 25 percent of the stand may be desired to be left unstocked. Page 952 states that up to 10 percent of the stockable stand may be left un-stocked. The 

Service encourages the BLM to consider a higher percentage available for natural regeneration for 

rare situations where up to 25% of the stockable stand may be desired to be left un-stocked.

Response: The Proposed RMP requires the BLM to reforest using natural or artificial regeneration 

within five years of harvest to a minimum stand level average density, which varies by Harvest Land 

Base sub-allocation. This direction in the Proposed RMP affords the BLM the discretion to vary 

planting densities across a harvest unit depending on site-specific information, and does not include 

the specific limitations on stocking in Alternative B. 

173. Comment Summary: The BLM should revise the EIS to include silvicultural management, such 

as longer rotations to achieve a more diverse log supply, which would increase timber values to fulfill 

fiscal responsibility to counties.
1917 | P a g e

Response: Both the Low Intensity Timber Area and the Moderate Intensity Timber Area in the 

Proposed RMP utilize long rotation management as a forest management strategy, resulting in a 

diverse log supply. Additionally, the uneven-aged management approach in the Uneven-aged Timber 

Area involves partial cutting of stands on an irregular re-entry cycle, which would also contribute to 

the variety of sizes and qualities of harvested timber. The BLM added additional information to the 

Forest Management section of the Proposed RMP/Final EIS that reports average regeneration harvest 

ages by alternative, and has provided an estimate of timber harvest volume by log size. 

174. Comment Summary: The BLM should revise the EIS because direction in the LITA and MITA 

in the action alternatives contains direction for tree retention in regeneration harvest dependent on the 

amount of Riparian Reserve area in the stand. This will reduce the quality of habitat for northern 

spotted owls.

Response: The Proposed RMP does not include this management direction when determining 

retention levels for the Low Intensity Timber Area and Moderate Intensity Timber Area. Instead, the 

Proposed RMP requires tree retention based on retention of a portion of the pre-harvest tree basal area 

calculated solely on the timber harvest area. This change allows for clearer management direction and 

facilitates determination of retention levels based on site-specific information during project-level 

implementation planning. 

175. Comment Summary: The BLM should revise the EIS to preclude management that would allow 

canopy closure to fall below 30 percent. Anything below this level leads to high densities of brush, 

increasing catastrophic fire risk.

Response: The BLM disagrees that reducing canopy closure below 30 percent necessarily increases 

catastrophic fire risk. The relationship of canopy closure to fire risk and its relative importance is site 

specific and depends on a number of factors, including ecological context and management 

objectives. Nevertheless, reducing canopy cover below 30 percent is necessary to achieve many forest 

management objectives. To achieve the BLM’s stated purpose of producing a sustained yield of 

timber, creating forest openings large enough to grow new cohorts of trees is necessary. Many species 

in the planning area rely on shrubs, hardwoods, and other sun-loving forest plants for their survival. 

In order to develop multi-layered canopies to enhance ecological outcomes, it may be necessary to 

allow enough sunlight through the canopy to grow a new generation of trees. A thorough analysis of 

the environmental effects of forest management actions on fire and fuels is contained in Chapter 3. 

This analysis did not find that the BLM would implement timber management in a manner that would 

increase the risk of catastrophic fire under any of the alternatives. 

176. Comment Summary: The BLM should revise the EIS to exclude timber salvage as a 

management option after wildfires. Many studies have shown (Beschta et al. 1995) the destructive 

nature of timber salvage and the negative effect it has on forest regeneration. Short-term financial 

gains should not outweigh best ecological practices.

Response: The Proposed RMP directs salvage harvest after disturbances in the Harvest Land Base to 

recover economic value and to minimize commercial loss or deterioration of damaged trees, but 

prohibits salvage harvest in the Late-Successional Reserve and Riparian Reserve except when 

necessary to protect public safety, or to keep roads and other infrastructure clear of debris (Appendix 

B – Management Objectives and Direction). The BLM is aware of studies on the environmental 
1918 | P a g e

impacts due to post-fire salvage logging, including the white paper produced by Beschta et al. (1995). 

That white paper focuses on the wisdom of salvage logging to meet ecological objectives. The BLM 

agrees that there is scientific controversy regarding the justification to salvage burned timber to 

enhance wildlife habitat outcomes. The same level of scientific controversy does not exist related to 

salvaging burned timber to recover economic value or removing dead trees for the purposes of 

protecting infrastructure and providing for public safety. 

177. Comment Summary: The BLM should revise the EIS to include forest management that 

accelerates resilience treatments in the dry and very dry forest types.

Response: All action alternatives and the Proposed RMP would increase resilience treatments in dry 

and very dry forest types compared to current practices. Appendix B – Management Objectives and 

Direction includes management direction for the Proposed RMP relevant to the management of these 

forests in the Uneven-aged Timber Area, the Late Successional Reserve – Dry, and the Riparian 

Reserve – Dry. The management direction for Late Successional Reserve – Dry also includes target 

decadal acreage treatment targets to help meet the purpose of restoring fire-adapted ecosystems. 

178. Comment Summary: The BLM should revise the EIS to retain legacy trees (>120 years) in all 

cases in harvest units, as these trees are the best habitat and most fire resistant.

Response: The Proposed RMP has incorporated management direction to protect large, older trees. 

The BLM disagrees that the best management approach to responding to the purpose and need for the 

RMP revision or meeting all objectives of the Harvest Land Base would be to apply a requirement to 

protect all trees above a 120-year age threshold. Coupled with regeneration harvest with retention or 

uneven-aged stand management, such a requirement would eventually reduce the timber production 

level of the stand, contrary to the purpose of the action to produce a sustained yield of timber. It is 

intuitively clear that if the BLM retains 15–30 percent of the stand basal area (or 5–15 percent in the 

Moderate Intensity Timber Area) and retains all trees over 120 year old, the abundance of trees over 

120 years old will increase through successive harvesting rotations, so that eventually more than 15–

30 percent of the stand basal area will be comprised of trees over 120 years old. Instead, the Proposed 

RMP would protect trees that are old and large in certain land use allocations, while allowing for 

necessary exceptions related to safety and operations. The Proposed RMP also includes management 

direction for the Uneven-aged Timber Area and the Late Successional Reserve – Dry directing the 

BLM to reduce competition around these trees and reduce adjacent fuels to increase tree vigor and 

reduce the risk of tree mortality (Appendix B – Management Objectives and Direction). These 

management directions would protect the majority of legacy trees within harvest units with 

characteristics contributing the most to complex habitat and would provide for forest resiliency. 

179. Comment Summary: The BLM should revise the EIS because cutting timber stands within the 

Deer Creek Watershed contradicts the Medford District BLM’s Water Quality Restoration Plan and is 

environmentally detrimental.

Response: The Water Quality Restoration Plan for the Deer Creek Watershed (USDI BLM 2011b) is 

not an existing decision supported by an EIS that the BLM is carrying forward into the RMPs under 

this revision (see Chapter 1, Existing Decisions). As such, there is no requirement for any of the 

action alternatives or the Proposed RMP to adhere to the goals and objectives established under the 

Water Quality Restoration Plan for the Deer Creek Watershed. The Draft RMP/EIS did not find any 

detrimental environmental impacts to water quality in the decision area, including the Deer Creek 
1919 | Page

watershed, under any of the alternatives (USDI BLM 2015, pp. 286–318). The commenter does not 

identify any errors in that analysis. 

180. Comment Summary: The EIS should not include pre-decisional approval for BLM to conduct 

falling of trees in proposed logging units as a timber cruising mechanism as is shown in Chapter 2 (p. 

39). The impacts of this proposed practice are not disclosed or analyzed in this document, and 

implementation without analysis would violate the NEPA.

Response: This listing of administrative actions is not a “pre-decisional approval” of these actions. 

Land use plans are designed to guide and control future uses, including describing allowable uses (40 

CFR 1601). The Draft RMP/EIS provided a list of administrative activities that would be allowable 

and that the BLM anticipates would occur under all alternatives (USDI BLM 2015, p. 39). The BLM 

would conduct the appropriate NEPA compliance to support decision-making prior to implementation 

of sample tree falling and other administrative actions. 

181. Comment Summary: The BLM should revise the EIS because it fails to describe the connection 

between logging road density and timber harvest density with Port-Orford-cedar root disease 

occurrence. Studies have found that both road networks and timber harvest patchworks were 

significantly related to cedar root rot heterogeneity (Clark 2011).

Response: As explained in the Draft RMP/EIS, the BLM would continue to apply management of 

Port-Orford-Cedar in accordance with the Record of Decision and Resource Management Plan 

Amendment of Management of Port-Orford-Cedar in Southwest Oregon, Coos Bay, Medford, and 

Roseburg District (USDI BLM 2004), and the Draft RMP/EIS incorporated the analysis conducted 

for the 2004 Port-Orford-cedar ROD by reference (USDI BLM 2015, p. 23). 

The implementation of the Proposed RMP is well within the bounds of outcomes considered in the 

2004 ROD for Port-Orford-cedar management. The road construction projected under the Proposed 

RMP would be less than road construction projected under the No Action alternative (see the Trails 

and Travel Management section in Chapter 3), and is within the range of effects considered in 

analysis for the 2004 Port-Orford-cedar ROD. 

The Standards and Guidelines in the 2004 Port-Orford-cedar ROD describe all currently available 

disease-control practices, dividing them between those that should be applied generally (e.g., 

community outreach and restoration) and those that may, depending on site conditions, be applied to 

specific management activities (e.g., road construction and timber sales). For the latter group, the 

2004 Port-Orford-cedar ROD includes a risk key to clarify the environmental conditions that require 

implementation of one or more of the listed disease-controlling management practices (USDI BLM 

2004, pp. 32–37). Under all alternatives and the Proposed RMP, the BLM would apply the risk key 

during site-specific project planning. This approach precludes the need for additional project-specific 

analysis of mid-and large-geographic and temporal-scale effects, because the risk key describes 

conditions where the BLM would apply risk reduction management practices. 

Hydrology 
1920 | Page

182. Comment Summary: Given the impaired nature of so many of our rivers, no increase in 

temperature originating with deliberate BLM actions can be tolerated, let alone the predicted 5 

percent the DEIS identifies as a result of adopting either of the Alternatives B or C.

Response: The Proposed RMP includes a Riparian Reserve design for fish-bearing streams and 

perennial streams that is substantially similar to Alternative D. 

The Draft RMP/EIS analyzed stream shading using two different methodologies. Method A 

concluded that all streams would retain sufficient stream shading to avoid any measurable increase in 

stream temperatures. Method B identified that approximately 5 percent of fish-bearing and perennial 

stream miles under Alternatives B and C and approximately 0.5 percent of fish-bearing and perennial 

streams under the No Action alternative, Alternative A, and Alternative D would be susceptible to 

shade loss that could result in stream temperature increases (USDI BLM 2015, pp. 294–297). The 

analysis in the Proposed RMP/Final EIS concludes that the Proposed RMP would have similar effects 

on stream shade to the No Action alternative, Alternative A, and Alternative D (see the Hydrology 

section of Chapter 3). Under Method B, the analysis concluded that this shade loss would occur if the 

outer zones of the Riparian Reserve were to be treated. Such conditions occur most frequently, where 

the riparian stand nearest the stream has widely spaced trees with a low canopy density. There would 

be no change in stream shading if the BLM were to not thin stands in the outer portions of the 

Riparian Reserve in these susceptible areas. Given that the riparian stands in these susceptible areas 

typically have low tree density and low canopy density, thinning the Riparian Reserve under such 

stand conditions would be unnecessary to comply with the management direction and meet the 

management objectives in any of the alternatives. Under such circumstances, the BLM would either 

defer forest management in the outer zones of these stream segments until the riparian stand nearest 

the stream increased in density or leave the Riparian Reserve un-thinned along these stream segments. 

In either case, it is unlikely that any of these areas susceptible to shade loss that could potentially 

result in stream temperature increases would, in fact, experience stream temperature increases. 

183. Comment Summary: Raising stream temperatures directly inhibits BLM watershed 

management goals and may result in violations of the Clean Water Act associated with TMDL-listed

waterbodies.

Response: The Draft RMP/EIS analyzed the effects of the alternatives on stream temperatures 

through two methodologies that assessed stream shading. The first methodology concluded that all 

alternatives would avoid any measurable increases in stream temperature at this scale of analysis. The 

second methodology found that a small percentage of streams would be susceptible to an increase in 

stream temperatures under all alternatives, including the No Action alternative. The Draft RMP/EIS 

explained that this result does not reflect an actual reduction in stream shading, but a susceptibility to 

such a reduction in stream shading if the BLM thins the outer zone along these streams. If the BLM 

does not thin the stand in the outer zone, no reduction in stream shading would occur (USDI BLM 

2015, pp. 286–297). Thus, the analysis in the Draft RMP/EIS identified a susceptibility to a reduction 

in stream shading that would occur under all alternatives; any actual increase in stream temperature is 

speculative and would depend on project-specific and site-specific conditions. The Proposed 

RMP/Final EIS specifically identifies the stream segments that would be susceptible to a reduction in 

stream shading. 

184. Comment Summary: The Hydrology section (DEIS:286–297) and Fisheries section (DEIS:232–

233) are inadequate because they focused almost entirely on shade models with respect to impacts of 

timber harvest and failed to consider stream temperature change in the context of climate change.

1920 | Page

182. Comment Summary: Given the impaired nature of so many of our rivers, no increase in 

temperature originating with deliberate BLM actions can be tolerated, let alone the predicted 5 

percent the DEIS identifies as a result of adopting either of the Alternatives B or C.

Response: The Proposed RMP includes a Riparian Reserve design for fish-bearing streams and 

perennial streams that is substantially similar to Alternative D. 

The Draft RMP/EIS analyzed stream shading using two different methodologies. Method A 

concluded that all streams would retain sufficient stream shading to avoid any measurable increase in 

stream temperatures. Method B identified that approximately 5 percent of fish-bearing and perennial 

stream miles under Alternatives B and C and approximately 0.5 percent of fish-bearing and perennial 

streams under the No Action alternative, Alternative A, and Alternative D would be susceptible to 

shade loss that could result in stream temperature increases (USDI BLM 2015, pp. 294–297). The 

analysis in the Proposed RMP/Final EIS concludes that the Proposed RMP would have similar effects 

on stream shade to the No Action alternative, Alternative A, and Alternative D (see the Hydrology 

section of Chapter 3). Under Method B, the analysis concluded that this shade loss would occur if the 

outer zones of the Riparian Reserve were to be treated. Such conditions occur most frequently, where 

the riparian stand nearest the stream has widely spaced trees with a low canopy density. There would 

be no change in stream shading if the BLM were to not thin stands in the outer portions of the 

Riparian Reserve in these susceptible areas. Given that the riparian stands in these susceptible areas 

typically have low tree density and low canopy density, thinning the Riparian Reserve under such 

stand conditions would be unnecessary to comply with the management direction and meet the 

management objectives in any of the alternatives. Under such circumstances, the BLM would either 

defer forest management in the outer zones of these stream segments until the riparian stand nearest 

the stream increased in density or leave the Riparian Reserve un-thinned along these stream segments. 

In either case, it is unlikely that any of these areas susceptible to shade loss that could potentially 

result in stream temperature increases would, in fact, experience stream temperature increases. 

183. Comment Summary: Raising stream temperatures directly inhibits BLM watershed 

management goals and may result in violations of the Clean Water Act associated with TMDL-listed

waterbodies.

Response: The Draft RMP/EIS analyzed the effects of the alternatives on stream temperatures 

through two methodologies that assessed stream shading. The first methodology concluded that all 

alternatives would avoid any measurable increases in stream temperature at this scale of analysis. The 

second methodology found that a small percentage of streams would be susceptible to an increase in 

stream temperatures under all alternatives, including the No Action alternative. The Draft RMP/EIS 

explained that this result does not reflect an actual reduction in stream shading, but a susceptibility to 

such a reduction in stream shading if the BLM thins the outer zone along these streams. If the BLM 

does not thin the stand in the outer zone, no reduction in stream shading would occur (USDI BLM 

2015, pp. 286–297). Thus, the analysis in the Draft RMP/EIS identified a susceptibility to a reduction 

in stream shading that would occur under all alternatives; any actual increase in stream temperature is 

speculative and would depend on project-specific and site-specific conditions. The Proposed 

RMP/Final EIS specifically identifies the stream segments that would be susceptible to a reduction in 

stream shading. 

184. Comment Summary: The Hydrology section (DEIS:286–297) and Fisheries section (DEIS:232–

233) are inadequate because they focused almost entirely on shade models with respect to impacts of 

timber harvest and failed to consider stream temperature change in the context of climate change.

1919 | Page

analysis of mid-and large-geographic and temporal-scale effects, because the risk key describes 

conditions where the BLM would apply risk reduction management practices. 

Hydrology 
1921 | P a g e

Response: The Draft RMP/EIS acknowledged the potential future effect of climate change on stream 

temperatures (USDI BLM 2015, pp. 149–150). However, it is not possible to incorporate predictions 

of climate change into the modeling of stream shading and subsequent effects on stream temperature. 

There is much uncertainty regarding climate change and effect upon stream temperature response, 

especially in the next 10–20 years. Despite increased average annual and seasonal air temperatures in 

the planning area, the analysis in the Draft RMP/EIS noted the decreasing stream temperatures at 

long-term monitoring sites within the planning area (USDI BLM 2015, pp. 143, 293–294). Riparian 

forest stand development with corresponding increasing shade has apparently had a countervailing 

effect on warming air temperatures. It is not possible to forecast quantitatively how future riparian 

forest stand development would interact with increasing annual and seasonal air temperatures to 

affect water temperature. 

185. Comment Summary: The BLM is using hydrological analysis that is biased and incomplete 

throughout the entire RMP. The BLM limits the hydrologic analysis to “peak flows.” The BLM must 

address the impacts of all alternatives on low flows not just peak flows. The BLM fails to mention 

that there can be significant impacts caused by even small increases in the 1–2 year peak flows. The 

BLM’s model is biased in that it only considers peak flow impacts to be of concern in the Rain‐on‐

Snow (ROS) transitional zone within watersheds.

Response: There is no substantive basis for the commenter’s assertion that the BLM is using 

hydrological analysis that is biased and incomplete. 

The BLM chose a hydrological analysis that could compare the alternatives and potentially detect a 

change based on the analytical assumptions within the current hydrological understanding on how 

watershed systems work. 

The commenter asserts that the BLM misrepresents Grant et al. (2008) in the peak flow analytical 

procedure when interpreting the peak flow response for the rain hydroregion and the rain-on-snow 

hydroregion in Figures 8 and 10 of Grant et al. (2008). The threshold of response is not an inflection 

point, but is the point where the mean response line crosses into the level of detection. These response 

curves should be applied cautiously when scaling up to larger watersheds such as the subwatershed 

scale (HUC 12) used in this analysis (Grant et al. 2008). Most experimental watershed studies have 

been conducted at the site scale (< 4 mi2). However, the magnitude of peak flow response by forest 

management declines as watershed area increases, for a variety of reasons: storm size and variability 

over a watershed, timing of tributary inputs, conveyance losses, flood-plain storage, and channel 

resistance (Grant et al. and references cited therein 2008). There is no known hydrologic mechanism 

to yield a higher percentage increase in peak streamflows in a larger watershed (Grant et al. 2008). 

Because of these scaling-up challenges, the BLM believes the peak flow analytical procedure is 

conservative in the estimation of effects. 

The BLM has added text to the Proposed RMP/Final EIS to explain that the BLM did not analyze in 

detail the effects of timber harvest on flow attributes other than peak flows (see the Hydrology section 

of Chapter 3). Specifically, the BLM did not analyze in detail the effects on other flow attributes, 

such as timing, annual water yield and low flows because either: (1) an effect is negligible or not 

detectable, (2) climate variability cannot be separated from the effects of forest management, (3) no 

known practicable analysis procedures are available to compare alternatives at the planning area scale 

for contemporary forest practices, or (4) specific and plan-wide streamflow information is not 

available in order to conduct an analysis. The commenter does not provide any alternate 

methodologies to evaluate these hydrological attributes at the planning area scale. 
1922 | P a g e

186. Comment Summary: Overstocked forests will reduce water availability. Too many trees cause 

snow not to reach the ground.

Response: The BLM has added text to the Proposed RMP/Final EIS to explain that the BLM did not 

analyze in detail the effects of timber harvest on water yield (see the Hydrology section of Chapter 3). 

The commenter is correct that dense forests can reduce water availability. Forest evapotranspiration is 

the primary process responsible for changes in water yield as a result of cutting trees or growing trees. 

Results from thirty-nine paired watershed studies referencing changes in water yield from changes in 

forest cover conclude: (1) reduction of forest cover increases water yield, (2) planting forests on bare 

land, meadows or understocked forests decreases water yield, and (3) the response is highly variable 

and at times unpredictable (Brown et al. 2005 and references therein). Snow accumulation in the 

forest depends upon forest structure and density. Nevertheless, none of the alternatives would have a 

significant effect on water availability. Therefore, this issue does not require detailed analysis. 

187. Comment Summary: The RMP needs to assess how clearcutting may deplete ground water 

supplies because regenerating trees are vigorously growing and can absorb greater volumes of water.

Response: The BLM has added text to the Proposed RMP/Final EIS to explain that the BLM did not 

analyze in detail the effects of timber harvest on water yield (see the Hydrology section of Chapter 3). 

Clearcutting or other timber harvest under any of the alternatives would not have a consequential 

effect on ground water supplies. Therefore, this issue does not require detailed analysis. There is little 

substantive basis for the commenter’s conclusions. Paired watershed deforestation experiments 

(including clearcutting) and regrowth of vegetation in experimental studies worldwide, show that 

water yield increases and gradually returns to the control watershed yields in 8–20 years (Brown et al.

2005 and references cited therein). The BLM acknowledges that some studies suggest that young 

forests transpire water to a greater degree than older forests, and this may have something to do with 

leaf area or sapwood area (Moore et al. 2004). However, beyond the reasons why young trees may 

transpire water more efficiently than older trees of the same species in a similar environment, there is 

little information to separate the evapotranspiration demand in young trees from the 

evapotranspiration demand in mature forests. Further, precipitation and runoff processes mask 

influences on water yield from differing vegetation, where a measurable difference in groundwater 

flow or annual yield can be demonstrated. Thus, even if the alternatives could have a consequential 

effect on ground water supplies, it would not be possible to construct an analysis of the effect of 

different harvesting practices on ground water supplies that could show any difference among the 

alternatives. 

188. Comment Summary: Factors such as winter base flows, summer low flows, total flow volumes 

and the timing and duration of flows should be considered within the watershed analysis for each 

alternative.

Response: The Proposed RMP/Final EIS has added explanation of these issues that the BLM 

considered, but did not analyze in detail (see Hydrology section of Chapter 3). 
1923 | P a g e

189. Comment Summary: Alternatives do not properly address all possible sources of water into 

forest hydrological systems.

Response: The analysis in the Draft RMP/EIS analyzed the effects of the alternatives on water 

quality and timing of flows, including effects on stream shade, peak flows, and sediment (USDI BLM 

2015, pp. 286–320). The BLM has added text to the Proposed RMP/Final EIS to explain that the 

BLM did not analyze in detail the effects of timber harvest on water yield (see the Hydrology section 

of Chapter 3). 

190. Comment Summary: The Affected Environment and Environmental Consequences should 

consider the studies and results of the research done by the Oregon State University Watersheds 

Research Cooperative.

Response: The BLM agrees that research done by the Oregon State University Watersheds Research 

Cooperative is relevant and pertinent information for contemporary forest management, but cautions 

that much of the information was developed for industrial forestland. Because of the substantial 

differences between industrial forestland management and the alternatives considered in this analysis, 

especially with regards to riparian stand management, the research from the Oregon State University 

Watersheds Research Cooperative is only of limited relevance. The BLM has included relevant 

information from the research from the Oregon State University Watersheds Research Cooperative in 

the Proposed RMP/Final EIS (see the Hydrology section of Chapter 3). 

191. Comment Summary: The Draft RMP/EIS does not address public safety and conservation 

concerns impacted by shallow, rapidly moving landslides, and also do not address Best Management 

Practices for future harvest to reduce the potential for landslides in proximity to the State’s highway 

system.

Response: The Proposed RMP has added management direction that directly addresses avoiding 

practices that could cause landslides that would damage infrastructure such as highways (see 

Appendix B – Management Objectives and Direction). In addition, the Proposed RMP includes 

unstable lands within the Riparian Reserve, limiting management actions that would occur on 

unstable lands. 

192. Comment Summary: Although regeneration harvest has a higher likelihood of increasing 

landslide frequency, thinning can also increase the frequency of landslides, depending on the harvest 

intensity. Reduced shear strength, associated with increased saturation, results from decreased tree 

canopy interception and reduced transpiration (Swanston 1973, Harr and McCorison 1979, Keim and 

Skaugset 2003, Johnson et al. 2007). NOAA recommends that the BLM analyzes the potential effects 

of thinning on landslide risk, particularly in areas that will receive high intensity thinning 

prescriptions (> 80 trees per acre, post thinning).

Response: The analysis of landslide risk necessarily requires considerable analytical assumptions. 

The BLM analyzed the effect of regeneration harvests on landslide risk. This analysis of regeneration 

harvests would include variable retention harvests that would retain of up to 30 percent of the basal 

area of the stand (e.g., the Low Intensity Timber Area in Alternative B). (The BLM believes the 

commenter meant < 80 trees per acre, post thinning in their comment). 
1924 | P a g e

The Draft RMP/EIS explained the basis for the analytical assumption that commercial thinning would 

not affect landslide risk: residual live trees with intertwined roots promote slope stability and 

transpire water, which helps to lower soil water, a causative factor in slope failures, and many cut 

stumps are root-grafted and continue to contribute to slope stability (USDI BLM 2015, pp. 307–308). 

Landslide density for extreme storms in mixed forests of 10–80 years of age (which includes the ages 

at which stands are typically thinned) is 2.7 times lower than open areas (Miller and Burnett 2007). 

As the commenter acknowledges, thinning has less effect on landslide risk than regeneration harvest. 

The BLM does not contend that thinning has no effect on landslide risk, but only that the effect is 

small and speculative, such that it would not be possible to analyze that risk at the scale of the 

planning area and would not show any measurable effects among the alternatives. 

193. Comment Summary: Best Management Practices are not a Management Direction; there is an 

element of uncertainty related to the location of road construction, therefore we recommend that the 

FEIS should include a comprehensive analysis of landslide risk from new road construction.

Response: It would not be possible to analyze the effects of new road construction on landslide risk 

at the scale of the planning area. Whether new road construction could contribute to landslide risk 

would depend on the specific road location and construction relative to areas of landslide 

susceptibility. The BLM cannot specifically forecast the spatial locations of new road construction 

under the alternatives and therefore cannot match road locations with topographic attributes to 

determine a relative landslide density. 

New road construction is unlikely to contribute to landslide risk. All alternatives would construct little 

new road mileage compared to the existing road network (Draft RMP/EIS, pp. 648–650). New road 

construction would generally not be located in areas of landslide susceptibility. Most new 

construction would likely be short spurs off local roads, because the existing road infrastructure meets 

much of the needs for resources management, especially timber harvest. Under the alternatives 

considered in the Draft RMP/EIS, Best Management Practices would include locating roads on stable 

locations and minimizing construction on steep slopes and high landslide hazard locations (USDI 

BLM 2015, p. 1140). 

It was appropriate for the Draft RMP/EIS to analyze effects incorporating the effect of Best 

Management Practices. As explained in the Draft RMP/EIS, monitoring has shown that the BLM has 

generally applied Best Management Practices appropriately and that Best Management Practices have 

generally been effective (Draft RMP/EIS, p. 1140). Thus, it is highly probable that the BLM will 

continue to apply Best Management Practices appropriately and that they will continue to be 

effective. The commenter does not address these monitoring results or explain how they believe the 

BLM should address what they perceive as “uncertainty” associated with Best Management Practices. 

Nevertheless, the Proposed RMP has added management direction that directly and specifically 

addresses road construction on unstable slopes (Appendix B – Management Objectives and 

Direction). 

194. Comment Summary: The EIS needs to consider potential landslides and other effects from a 

catastrophic Cascadia Subduction Zone earthquake.

Response: A major earthquake on the Cascadia Subduction Zone is possible within the timeframe of 

the landslide analysis, but is not highly probable. The U.S. Geological Survey identifies that the last 

major earthquake on the Cascadia Subduction Zone was about 300 years ago and describes an 

average interval of 500–600 years between great earthquakes on the Cascadia subduction zone 
1925 | P a g e

(Personius and Nelson 2006). Thus, a major earthquake is not reasonably foreseeable for the purposes 

of this landslide analysis and should not be included in the analysis. Furthermore, the effects of a 

major earthquake would not differ among the alternatives. This is because, in the event of a 

magnitude 8–9 earthquake, the main trigger for landslides will be from the extreme shaking intensity 

interacting with susceptible landforms and the degree of soil saturation. Mountain road locations or 

harvest practices will be of inconsequential importance for initiating slope failures, because the 

earthquake will likely trigger all types of landslides from debris-flows to large deep-seated rock slides 

in roaded and unroaded areas alike. 

195. Comment Summary: Best Management Practice ‘R 094’ (in Appendix I) should be re‐

designated as management direction and incorporated into Appendix B. Limiting sediment production 

associated with hauling is an important component of a successful watershed restoration strategy and, 

as such, should carry the weight of management direction.

Response: All action alternatives analyzed in the Draft RMP/EIS included Best Management Practice 

R 094: “Suspend commercial road use where the road surface is deteriorating due to vehicular rutting 

or standing water, or where turbid runoff may reach stream channels.” The Proposed RMP has added 

this requirement as management direction, as the commenter suggests (Appendix B – Management 

Objectives and Direction).

196. Comment Summary: Increased logging in riparian areas will necessitate increased road density 

within sensitive riparian habitats including roads within ‘sediment delivery distance’ (DEIS p. 317). 

The BLM fails to quantify the amount of road to be constructed in Riparian Reserve or the amount of 

sediment that will be added to streams. The BLM neglects to disclose which streams in the planning 

area are currently TMDL listed for sediment and how the agency intends to meet the Clean Water Act 

obligations.

Response: The BLM did quantify and analyze anticipated new road construction within the sediment 

delivery distance of streams. The BLM determined road miles by harvest type and distributed by road 

type (paved, gravel and natural surface) and then quantified and analyzed the resultant sediment 

delivery (USDI BLM 2015, pp. 313–318). The Draft RMP/EIS explained that the existing road 

infrastructure is essentially in place, and relatively few new roads would be constructed in the future 

under any of the alternatives compared to the existing road system. The commenter does not identify 

any flaw or inaccuracy in that analysis. 

The new road construction within the sediment delivery distance of streams almost entirely overlays 

the Riparian Reserve under all alternatives and Proposed RMP. In analyzing sediment delivery to 

streams, the amount of road construction within the sediment delivery distance provides relevant 

information, in contrast to the amount of road construction within the Riparian Reserve land use 

allocation, which differs by alternative. Adding quantification of the amount of road construction 

within the Riparian Reserve would not improve the analysis of effects and it is not relevant to a 

reasoned choice among alternatives. 

The BLM meets the Clean Water Act obligations through the sum of the Riparian Reserve land use 

allocation, management direction, and Best Management Practices. Further, the BLM is an ODEQdesignated management agency to meet Clean Water Act obligations. This means that, in addition to 

the foregoing preventative controls and practices, BLM specialists decide the necessary steps to 

maintain water quality during activity planning and implement those preventative measures. The 
BLM would maintain water quality at the highest practicable level to meet water quality standards 

and TMDL load allocations as set by the State of Oregon’s Department of Environmental Quality.

There are roughly 340 miles of streams in the planning area that are water quality limited for 

sedimentation or turbidity, and approximately 13 percent (or 46 miles) are located in the decision 

area. The BLM does not disclose which streams in the planning area are currently Total Maximum 

Daily Load (TMDL) [303(d)] listed for sediment in the EIS because disclosing this information is not 

relevant to the analysis or making an informed choice among alternatives. Relatively few stream 

miles within the decision area are water quality limited for sediment, and a process exists to restore 

these stream miles (TMDL Implementation Plans). The BLM develops TMDL Implementation Plans 

to identify sources, necessary strategies, and appropriate BMPs to restore water quality limited waters 

and reduce pollution for surface waters on lands within BLM’s jurisdiction.

The commenter mistakenly implies that there would be “increased logging in riparian areas” under 

the alternatives. All action alternatives would have less Riparian Reserve thinning than the No Action 

alternative and most alternatives would have less thinning than the BLM has been implementing in 

the past two decades. 

197. Comment Summary: The FEIS should include specific standards for reducing Total Maximum 

Daily Load (TMDL) from logging roads, thinning, and other logging activities to minimize chronic 

sediment to Surface Water Source Areas.

Response: The Proposed RMP includes specific management direction (Appendix B – Management 

Objectives and Direction) and Best Management Practices (Appendix J Appendix I – Best Management 

Practices) to reduce or avoid sediment delivery to streams from timber harvest, road construction, and 

other management actions. 

198. Comment Summary: Timing of sediment input to a stream is not always equal to timing of 

impact on salmonid fish, and sediment input timing cannot be considered a reasonable criterion for 

concluding that erosion has little effect on these fish. The majority of the suspended sediment analysis 

focuses on the effects from new road construction. Although the DEIS identifies the level of 

suspended sediment generated from existing roads, there is no analysis of effects to ESA listed fish 

compared to natural, background levels of suspended sediment. We recommend that the FEIS include 

a modified sediment analysis that (1) avoids the assumption that the timing of sediment delivery is 

more important than the volume, (2) considers effects of both the existing road network and pr

‐

oposed 

roads, and (3) includes consideration of long term sediment routing and effects.

Response: The commenter is mistaken: the BLM did not assume that the timing of sediment delivery 

is more important than the volume of sediment

‐

 delivery. In evaluating the effects of sediment delivery 

to streams on both water quality and fisheries, the analysis in the Draft RMP/EIS provided a reasoned 

analysis based on the detailed, quantified information on the volume of sediment delivery (USDI 

BLM 2015, pp. 230–233, 313–318). The BLM acknowledges the importance of the timing of 

sediment delivery and maintains that the timing is relevant in the analysis of effects on both water 

quality and fisheries. The timing of sediment delivery is highly linked to sediment yields and water 

flow volume. The analysis did consider the effects of existing and proposed roads. Increasing 

sediment yield with stream discharge has been reported in numerous studies in western Oregon and 

the United States, varying by seasonal trends in precipitation and streamflow (Skaugset et al. 2013, 

Luce and Black 1999). The largest proportion of watershed sediment yield is restricted to a few days 

each year with the largest discharge. The BLM has observed that under normal precipitation and 

1926 | Page
1927 | P a g e

runoff, many roadside ditches carry little to no water or sediment. The BLM expects this seasonal 

pattern of a few large storms in the annual series to produce higher runoff and to yield the majority of 

the sediment load. Nevertheless, the analysis in the Draft RMP/EIS directly addressed the volume of 

sediment delivery under the alternatives in the analysis of effects on water quality and fisheries. 

The BLM modeled sediment yields for new road construction under the alternatives together with the 

sediment yields from existing roads to show long-term potential sediment delivery under the 

alternatives (USDI BLM 2015, pp. 313–318), as the commenter recommends. 

It is not practical to quantify the natural, background levels of suspended sediment in streams at the 

scale of the planning area. Natural background sediment yields vary over a wide range by watershed 

characteristics, area, vegetative cover, land use, and precipitation patterns. Natural background 

sediment yields are difficult to disentangle from land use history including the effect of harvests and 

roads. Watershed-intrinsic factors in managed and unmanaged areas, including widely scattered and 

infrequent landsliding and streambank erosion, heavily influence the natural, background levels of 

suspended sediment in streams. There is no comprehensive data on the natural, background levels of 

suspended sediment in streams across the planning area, and the high variability, both spatially and 

temporally, makes approximation or extrapolation from the existing data inappropriate. 

Although natural, background levels of suspended sediment in streams are highly variable; the 

sediment delivery from road construction under the alternatives is likely to be very small in 

comparison. For example, Zégre (2008) calculated annual sediment yields for small headwaters 

catchments in Hinkle Creek, on western Oregon industrial forestland, in a paired watershed study 

using contemporary forest harvesting. Basin-wide annual sediment yields for this 5-year study 

averaged 134 tons/mile2/year. Comparatively, Table 3-72 Potential fine sediment delivery from 

existing roads (USDI BLM 2015, p. 314) shows modeled potential sediment delivery from roads, 

including BLM-administered and other lands in the planning area, total 13.43 tons/mile2/year. 

Comparing to the Hinkle Creek watershed study, as an example, shows that roads in the planning area 

on multiple ownerships comprise a small proportion of the annual sediment budget. New road 

construction under the alternatives would add less than 1 percent to the sediment yield from the 

existing road system. Thus, using the example of Hinkle Creek, new road construction under the 

alternatives would, on average, add less than 0.001 percent to the natural, background levels of 

suspended sediment in streams. 

Finally, quantified data on the natural, background levels of suspended sediment in streams across the 

planning area is not essential to a reasoned choice among the alternatives. The natural, background 

levels of suspended sediment in streams would not change as a result of any of the alternatives. As 

explained in the Draft RMP/EIS, the relevant analytical threshold for analyzing the effects of 

sediment delivery on fish is the amount of increase in fine sediment over natural levels at the 

watershed scale (USDI BLM 2015, p. 230). The information available to the BLM at the scale of the 

planning area is sufficient to evaluate the increase in sediment delivery relevant to the analytical 

thresholds. More data on the natural, background levels of suspended sediment in streams would not 

improve the evaluation of the alternatives against that analytical threshold or the comparison of the 

relative effects of the alternatives on water quality or fisheries. 

In a December 18, 2015 letter from NMFS to the BLM, NMFS acknowledged that these comments 

misinterpreted the Draft RMP/EIS and asked that the comments be ignored. NMFS clarified that they 

believe that the approach in the Northwest Forest Plan is not the only approach that would ensure the 

protection and recovery of threatened and endangered fish, and that the best available science also 

supports an approach modified from Alternative A or D that includes a one site-potential tree height 

Riparian Reserve on fish-bearing streams and perennial streams. 
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199. Comment Summary: The RMP/DEIS fails to establish temporal baseline water quality 

conditions from known data sets. Water quality data needed to compile baseline water quality 

condition is available from ODEQ.

Response: The BLM is unaware of any water quality data sets that can characterize baseline water 

quality conditions across the intermingled BLM-administered lands in the planning area. The BLMadministered lands are often upstream of other land uses and often meet anti-degradation criteria. The 

ODEQ water quality assessment database referred to by the commenter is inappropriate to analyze 

water quality constituents from BLM–administered lands for the following reasons: 

 The ODEQ stream monitoring sites for the most part are downstream of BLM-administered 

lands 

 The receiving streamflow at the ODEQ monitoring sites normally cross varying ownerships 

upstream, involving a mix of stream-adjoining (or runoff from) forestland owners with 

differing forest practices, and private landowners using agricultural practices 

 The receiving streamflow at the ODEQ monitoring sites may be capturing return flow from 

upstream point sources (e.g., sewage treatment plants, animal feedlots, and log ponds) 

Therefore, it would not be possible to attribute water quality changes from BLM management 

activities relative to this baseline information. Additionally, the ODEQ water quality assessment 

database has a variety of collection methods, making comparisons across this planning area difficult. 

Therefore, a meaningful assessment of BLM water quality conditions across the planning area cannot 

be determined from the ODEQ datasets. 

200. Comment Summary: The BLM failed to address nutrient loading of streams due to logging. The 

DEIS does not disclose impacts to surface waters and fish habitat on and downstream of BLM lands 

from nutrient leaching associated with BLM forest treatments, nor does the DEIS consider possible 

management practices to mitigate harm to downstream waters from nutrient loading. More recent 

studies (e.g., Nieber et al. 2011 and Sweeney and Newbold 2014, and references cited therein) 

suggest that unlogged forest buffers in excess of about 150’ slope distance from surface waters and 

stream channels, including headwater channels with intermittent or ephemeral flow, are needed to 

mitigate nutrient leaching associated with upslope logging the maximum degree practicable (that is, 

with 90% of mobilized nutrients recaptured and retained in soils and vegetation).

Response: The Draft RMP/EIS did not address the issue because timber harvest under the 

alternatives would not have a significant effect on nutrient loading to streams. The Proposed 

RMP/Final EIS added explanation that the BLM did not analyze this issue in detail (see the 

Hydrology section of Chapter 3). 

The nutrients of potential concern for streams are nitrogen and phosphorus. Nitrate, dissolved 

inorganic nitrogen, can enter aquatic ecosystems via point sources (e.g., farm and aquaculture 

wastewater, municipal and industrial sewage) and nonpoint sources (e.g., cultivation of nitrogenfixing crops, use of animal manure and inorganic nitrogen fertilizers, logging and fuels management 

treatments that remove vegetation and increase leaching from forest soils). Streamside areas can 

remove dissolved nitrogen from subsurface water by denitrification, plant uptake, and microbial 

uptake (Sweeney and Newbold 2014 and references therein). Phosphorous as phosphate can be lost 

through soil erosion and, to a lesser extent, to water running over or through soil. Because phosphate 

is relatively immobile in soils, erosion control practices minimize phosphate loading to streams. 
1929 | P a g e

Under all alternatives and the Proposed RMP, allocation and management of the Riparian Reserve 

would reduce or avoid nutrient loading of streams from upslope forest practices. Sweeney and 

Newbold (2014) compared the nitrate removal efficiency and buffer width from 30 studies 

worldwide, half with forest vegetation, and concluded that effective nitrogen removal at the 

watershed scale probably requires buffers at least 100 feet wide, and the likelihood of high removal 

efficiencies continues to increase in buffers wider than 100 feet. Nieber et al. (2011) suggest that 

average nitrogen and phosphorus retention is around 80 percent for 100-foot buffers. The authors 

calculated the percentage removal of nitrogen and phosphorus into wetlands based on two literature 

reviews that covered 55 nationwide research papers. The Riparian Reserve under all alternatives and 

the Proposed RMP for perennial and fish-bearing streams would range from 150 feet to one sitepotential tree height, which compare favorably with effective buffer widths in these references, 

indicating that the Riparian Reserve under all alternatives would provide effective nutrient filters on 

these streams. In a December 18, 2015 letter from NMFS to the BLM, NMFS acknowledged that the 

best available science supports an approach modified from Alternative A or D that includes a one 

site-potential tree height Riparian Reserve on fish-bearing streams and perennial streams. As 

explained above, this buffer width would be sufficient to avoid any measurable increase in nutrient 

levels in streams. 

Riparian Reserve widths of 50 feet on non-fish-bearing intermittent streams in Alternatives B and C 

and in Class III subwatersheds in the Proposed RMP may not, in and of themselves, be sufficient to 

prevent nutrient loading to streams on all sites. Several factors that control buffer effectiveness (e.g., 

vegetation characteristics, slope, soil compaction and texture, percent organic matter, subsurface 

water flux) are dependent on site-specific conditions (Nieber et al. 2011, Sweeney and Newbold 

2014) that cannot be fully assessed at the scale of this analysis. However, the potential for nutrient 

loading in these streams is highly limited. Under the Proposed RMP, the majority of the acreage 

upslope of the Riparian Reserve would be allocated to other reserve land use allocations, limiting the 

extent and intensity of upslope timber harvest. Under the Proposed RMP, Class III subwatersheds 

would constitute a small percentage of the decision area (see Chapter 2). Timber harvest and manual 

application of fertilizer upslope of non-fish-bearing intermittent streams would be staggered in space 

and time, minimizing the potential for cumulative effects from nutrient loading within the analysis 

area. In addition, trees remaining in upland thinned stands and retention trees in regeneration and 

selection harvests would increase their growth rate and uptake of nutrients and water following 

harvest (Ruzicka et al. 2014, Chan et al. 2004, Reiter and Beschta 1995). 

Maintenance of continuous forest cover and sources of large wood on all streams under all 

alternatives and the Proposed RMP, together with continued instream habitat restoration, would 

ensure effective nutrient processing in the decision area, which would further minimize any nutrient 

loading in streams. Peterson et al. 2001 studied nitrogen in headwater streams in North America and 

found that the most rapid uptake and transformation of inorganic nitrogen occurred in the smallest 

streams where large streambed to water volume ratios favor rapid nitrogen uptake and processing. 

Streams with greater complexity, including low-order streams with log and boulder steps and higher 

order streams enhanced with boulders and wood for fish habitat, are more effective at nitrogen uptake 

than those lacking obstructions and backwaters, because the complexity provides more opportunities 

for water to come into contact with stream organisms that process and remove nitrogen (Johnson 

2009). 

As a result on the Riparian Reserve providing an effective nutrient filter on most or all streams, the 

limited extent and intensity of timber harvest and fertilization upslope of the Riparian Reserve, and 

the effective nutrient processing in riparian and aquatic systems, none of the alternatives or the 

Proposed RMP would have a significant effect on nutrient loading in streams. 
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201. Comment Summary: BLM lands are crucial for providing clean drinking water to 1.5 million 

Oregonians, high quality water for listed salmon, habitat for threatened wildlife, and for preparing 

communities and ecosystems for the effects of climate change. Improved drinking water protection 

would entail added emphasis actions. For example, we recommend that Cave Junction and the Kerby 

Water District receive a higher degree of watershed protections and higher priority for restoration. 

Benefits of BLM watersheds are irreplaceable and will only be degraded by logging on LSRs and 

Riparian Reserve.

Response: The BLM’s primary water quality protection strategy is composed of the Riparian Reserve 

land use allocation, especially the inner zone along streams, management direction for the Riparian 

Reserve and hydrology, and the Best Management Practices. These preventative measures have 

complementary goals with Oregon’s drinking water protection program. The Proposed RMP/Final 

EIS has added discussion of the link between BLM’s normal activities and potential water 

contaminants. The BLM has identified the public water systems for lands that BLM administers 

(USDI BLM 2008, Appendix J – Water). This summary includes public water system ID, name, 

source, population served, BLM-administered acres and other acres. 

The drinking water protection program in Oregon is through a partnership between the Oregon 

Department of Environmental Quality (ODEQ) and Oregon Health Authority (OHA). The BLM 

disagrees that source water protection watershed within the East Fork Illinois River needs additional 

protections than what would be provided under the Proposed RMP. The City of Cave Junction’s 

Public Water System (PWS) has a surface source on the East Fork Illinois River. The BLM is a 

minority landowner, with lands occupying 12 percent of the watershed. The OHA has determined that 

the Cave Junction PWS is an outstanding performer. The criteria for outstanding performance 

include, (1) No Maximum Contaminant Level (MCL), Action Level, or Treatment Technique 

violations in the last 5 years; (2) No more than one Monitoring and Reporting violation in the last 3 

years, (3) No significant deficiencies or rule violations identified during the current water system 

survey; and (4) Has not had a waterborne disease outbreak attributable to the water system in the last 

5 years (ODEQ). Thus, there is no evidence to support the argument that this watershed needs 

increased protection for water quality. In addition, the BLM has little ability to affect water quality in 

this watershed because of limited ownership. Nonetheless, the analysis in the Draft RMP/EIS 

concluded that the alternatives would provide for protection of water quality. The commenter does 

not identify any error in that analysis and does not support their claim that the logging proposed under 

the alternatives would result in degraded water quality.

202. Comment Summary: RMP fails to adequately discuss the importance of the Port-Orford-cedar 

to water quality and stream function. RMP fails to assess consequences of root disease risk and lack 

of shade from action alternatives.

Response: The BLM has already analyzed and considered the management of Port-Orford-cedar and 

Port-Orford-cedar root disease in the Final Supplemental EIS Management of Port-Orford-Cedar in 

Southwest Oregon (USDA FS and USDI BLM 2004). The Draft RMP/EIS identified the Record of 

Decision for Management of Port-Orford-Cedar in Southwest Oregon (USDI BLM 2004) as an 

existing decision that the BLM will incorporate into the RMPs (USDI BLM 2015, p. 23). The 

conceptual framework, vectors of disease spread and management practices in the Record of Decision 

for Management of Port-Orford-Cedar in Southwest Oregon are still relevant. There are no effects of 

management of Port-Orford-cedar or Port-Orford-cedar root disease that are substantially different 

than the effects analyzed in the Final Supplemental EIS Management of Port-Orford-Cedar in 

Southwest Oregon. Furthermore, the effects of management of Port-Orford-cedar or Port-Orford-
1931 | P a g e

cedar root disease would not differ among alternatives. Therefore, there is no need for any specific 

additional analysis of management of Port-Orford-cedar or Port-Orford-cedar root disease in this 

RMP revision. 

203. Comment Summary: Factors such as down‐cutting, excessive lateral movement and stream 

bank erosion should be considered in alternatives that manage for increased OHV use.

Response: The BLM agrees that stream stability depends upon intrinsic watershed factors and 

management history. However, the commenter has not shown a causal linkage between OHV use and 

stream stability that the BLM could evaluate to show differences among the alternatives. The BLM 

has included Best Management Practices designed to protect water quality when constructing and 

maintaining OHV trails within Riparian Reserve, including stream crossings (USDI BLM 2015, p. 

1165). 

204. Comment Summary: The DEIS should explain plans to reduce watershed, water quality and 

fishery impacts from roads, inclusive of reduction of road extent through limits on new road 

construction, decommissioning of existing roads, and drainage improvements to ‘stormproof’ roads 

that would remain on the landscape permanently.

Response: The Proposed RMP/Final EIS has added discussion of how the BLM would implement 

watershed restoration (Appendix X – Guidance for Use of the Completed RMPs).

The Draft RMP/EIS included an estimate of 372 miles of permanent road decommissioning to year 

2023 (USDI BLM 2015, p. 318). The BLM typically makes decisions on whether to make specific 

existing roads open or closed to public motorized access through implementation-level travel 

management planning (Appendix X – Guidance for Use of the Completed RMPs) and typically 

makes decision on whether to decommission specific existing roads through project-level planning 

and analysis. The Draft RMP/EIS included estimates of new road construction under the alternatives 

and analyzed the effect of this new road construction. All alternatives would construct little new road 

mileage compared to the existing road network and would make little contribution to existing 

sediment delivery to streams (USDI BLM 2015, pp. 230–233, 313–318, 648–650). The alternatives in 

the Draft RMP/EIS all included limitations on road construction through management direction and 

Best Management Practices. The Draft RMP/EIS included Best Management Practices for road 

stormproofing and road closure and decommissioning (USDI BLM 2015, pp. 1151–1153). 

205. Comment Summary: The gross geomorphic effects of different hydrological features with 

dispersed increases in magnitude might be small due to resilience of channels (Grant et al. 2008); 

however, a variety of effects (fine sediment transport, reduced streambank stability, reduced large 

wood retention) may result in significant effects to ESA‐listed fish habitat at the stream reach scale.

Response: It is not possible, given the scope and scale of the RMP revision, to analyze the effects of 

the alternatives at the stream reach scale. The Draft RMP/EIS discussed how each of these effects 

could affect fish habitat at finer scales. However, the BLM necessarily conducted the detailed, 

quantified analysis in the Draft RMP/EIS of the effects of the alternatives on sediment delivery, peak 

stream flows, and wood supply to streams at broad spatial scales. That analysis concluded that new 

road construction under all alternatives would add less than 1 percent to the sediment yield from the 

existing road system (USDI BLM 2015, p. 315–318). Less than 1 percent of the decision area would 

be susceptible to peak flow increases under any of the alternatives (USDI BLM 2015, pp. 298–306). 
1932 | P a g e

All alternatives would increase the wood supply to streams from the current conditions (USDI BLM 

2015, pp. 219–230). The Draft RMP/EIS acknowledged the possibility of differences in effects at the 

stream reach scale. For example, the analysis of wood supply detailed there are differences in the 

design of the alternatives (specifically, Riparian Reserve widths, inner zone widths, and management 

direction for Riparian Reserve thinning) that may have differential effects on potential wood 

contribution that the BLM cannot quantitatively evaluate at this scale of analysis (USDI BLM 2015, 

pp. 228–230). The commenter does not provide any explanation of how the BLM could conduct such 

analyses for an RMP revision, given the information available and the nature of the proposed action, 

at the stream reach scale. The BLM has designed the Proposed RMP to reduce the risk of adverse 

effects to ESA-listed fish and water quality. Although there may be some variation in the effects from 

reach to reach, the Proposed RMP would result in only minor adverse effects or wholly beneficial 

effects on ESA-listed fish and water quality (see the Fisheries and Hydrology sections of Chapter 3). 

206. Comment Summary: The DEIS does not address the likely effects of fire management on 

riparian and aquatic habitat, particularly in regards to sediment production, riparian forest condition, 

effects of post‐fire salvage logging and increased road construction.

Response: It is not clear what aspects of fire management the commenter believes would have effects 

on riparian and aquatic habitat that the BLM did not analyze in the Draft RMP/EIS. The only 

management actions the commenter specifies are post-fire salvage logging and increased road 

construction. 

The only alternative that would allow salvage logging within the Riparian Reserve is the No Action 

alternative. Under all of the action alternatives, there would be no salvage logging after fires in the 

Riparian Reserve, except when necessary to protect public safety, or to keep roads and other 

infrastructure clear of debris. Salvage logging outside of the Riparian Reserve would have the same 

effects on riparian and aquatic habitat as green tree harvest. The analysis did specifically include postfire salvage harvest in the vegetation modeling (USDI BLM 2015, pp. 98–100). Under all 

alternatives, the inner zone of the Riparian Reserve would provide effective sediment filtration and 

ensure that upslope timber harvest would not result in sediment delivery to streams (USDI BLM 

2015, p. 317). 

The Draft RMP/EIS analyzed the effect of new road construction; all alternatives would construct 

little new road mileage compared to the existing road network and would make little contribution to 

existing sediment delivery to streams (Draft RMP/EIS, pp. 230–233, 313–318, 648–650). The road 

construction necessary to implement salvage logging under the alternatives is included in this analysis 

of new road construction. 

The Draft RMP/EIS incorporated a quantified and spatially explicit prediction of wildfire and postfire salvage harvest under the alternatives. This detailed information was included in the analysis of 

effects. The BLM has addressed all significant effects of salvage logging or attendant new road 

construction on riparian and aquatic habitat in the analysis. 

207. Comment Summary: BLM cannot extend the questionable “improving trend” in AREMP 

monitoring results because these results represent only the first twenty years of ACS implementation. 

As all BLM action alternatives remove ACS protections, the BLM cannot claim that any improving 

trends in watershed conditions, even if real, will continue, as the improving trend depends on full 

ACS implementation moving forward.
1933 | P a g e

Response: The commenter is mistaken in implying the analysis in the Draft RMP/EIS extended the 

AREMP monitoring results into the future. The AREMP monitoring program is ongoing and current 

results show increases in watershed condition scores as well as stream characteristics (e.g., stream 

substrate percent fines, substrate size, and macroinvertebrate assemblages that indicate improving 

watershed health). The Draft RMP/EIS summarized these monitoring reports in describing the current 

condition of watershed resources (USDI BLM 2015, p. 223). The Draft RMP/EIS analyzed the effects 

on future conditions, such as stream shading, sediment delivery, and wood delivery potential, through 

analytical methodologies and modeling described in detail in the Draft RMP/EIS (USDI BLM 2015, 

pp. 217–235, 286–320). The Draft RMP/EIS compares the effects of all alternatives, including the No 

Action alternative (which includes the Aquatic Conservation Strategy), on these watershed resources. 

There is no basis for the commenter’s assertion that the BLM has extended the monitoring results into 

the future. 

Invasive Species 

208. Comment Summary: The EIS should include a complete evaluation of how artificial fertilizer 

application for increased tree growth might support the growth of exotic plants.

Response: The Proposed RMP/Final EIS includes a discussion about non-native invasive plant 

response to forest management fertilization treatments. This discussion is added to the summary of 

analytical methods for the Invasive Plants section of Chapter 3. 

209. Comment Summary: The EIS should address threats to North American ash trees from the 

emerald ash borer and to chinkapin from newly introduced pathogens.

Response: There are many forest pests and pathogens within the planning area or within the State of 

Oregon, including the emerald ash borer and chinquapin disease mentioned. The BLM manages 

infested or infected forests through forest stand manipulation as appropriate to the pest or pathogen. 

Eradication is not always possible. For many of these forest pests and pathogens, forest stand 

manipulation is the only feasible management tool for control. As such, management for most forest 

pests and pathogens would not vary by alternative, and analysis of the effect of the alternatives on 

these forest pests and pathogens would not be informative. The Proposed RMP/Final EIS includes 

management direction to manage forested stands for infestations. 

210. Comment Summary: The EIS should address management of Port-Orford-Cedar (POC) in 

forested stands within the planning area. The EIS should also conduct up to date relevant spatial 

analysis of spread and consequences of POC root disease.

Response: The Proposed RMP/Final EIS addresses Port-Orford-cedar (POC) management in Chapter 

1. The Proposed RMP directs for management of Port-Orford-cedar in accordance with the Record of 

Decision and Resource Management Plan Amendment of Management of Port-Orford-Cedar in 

Southwest Oregon, Coos Bay, Medford, and Roseburg District (USDI BLM 2004). BLM 

acknowledges that some POC root disease has spread since 2004. However, this FEIS and ROD 

conceptual framework, vectors of disease spread and management practices are still relevant. The 

Port-Orford-cedar ROD includes a Risk Key for site-specific analysis to determine where to apply 

risk reduction practices (USDI BLM 2004, pp. 32–37). Management for POC root disease would not 
1934 | P a g e

vary by alternative and analysis of the influence of the alternatives on POC root disease would not be 

informative. 

211. Comment Summary: The EIS undermines BLM policy objectives for the management of 

invasive species and riparian habitats as is evidenced by analysis (pp. 332–335) stating that 

disturbances associated with Riparian Reserve logging will make “riparian habitats more susceptible 

to the introduction and spread of invasive plants.”

Response: The Draft RMP/EIS analyzes the relative risk of introducing and spreading invasive plant 

introductions from the differing alternatives. Risk is not synonymous to likelihood. Project design and 

mitigations applied at project-level implementation planning influence the likelihood of invasive plant 

introduction and spread. The Proposed RMP/Final EIS includes management direction to address 

prevention and management of invasive plant infestations in implementation project design 

(Appendix B – Management Objectives and Direction). The Proposed RMP/Final EIS also 

incorporates the analysis for the Vegetation Treatments Using Herbicides on BLM Lands in Oregon 

Record of Decision (USDI BLM 2010). This Record of Decision addresses mitigation and control 

methods available for use in the event of an introduction. 

212. Comment Summary: The EIS fails to prioritize invasive plants adequately.

Response: The Draft RMP/EIS does not include a prioritization of invasive plant species for 

management because there are no BLM policies, State or Federal regulations directing for a 

prioritization of invasive plant species in land use plans. The BLM districts recognize the Oregon 

Department of Agriculture’s Noxious Weed Control Policy and Classification System, which 

prioritizes listed noxious weed species at the statewide level. BLM Manual 9015 – Integrated Weed 

Management (USDI BLM 1992) provides guidance for setting management priorities by developing 

weed management plans and using a classification system to provide weed management emphasis 

priorities. The BLM most effectively prioritizes invasive plant species at the field office level and 

develops annual weed management plans. The Draft RMP/EIS intentionally does not include 

priorities for invasive plant species. 

213. Comment Summary: The EIS fails to restrict herbicides adequately.

Response: The EIS addresses the parameters for application of herbicides in Chapter 1. The Draft 

RMP/EIS incorporates the analysis for the Vegetation Treatments Using Herbicides on BLM Lands in 

Oregon Record of Decision (USDI BLM 2010). The commenter does not allege or substantiate that 

the 2010 BLM Record of Decision is inadequate. 

214. Comment Summary: The EIS fails to consider general recreational uses and OHV use, 

including illegal use, in its analysis of invasive species.

Response: The Draft RMP/EIS does consider recreation and OHV use in the analysis of invasive 

species. The Draft RMP/EIS incorporates invasive plant analytical assumptions from the Planning 

Criteria (USDI BLM 2014, pp. 90–98), into analysis for invasive plants in Chapter 3. These analytical 

assumptions include identification of locations and activities influencing invasive species introduction 

and spread, including several assumptions about recreation use and OHV use. In addition, Chapter 3 

provides a discussion about illegal OHV use in the invasive plant analysis identifying that BLM lacks 
1935 | P a g e

a basis for characterizing current illegal OHV use or for forecasting illegal OHV use at the scale of 

the planning area. 

215. Comment Summary: The EIS fails to include data or research to support analysis of grazing 

impacts on invasive species.

Response: The Draft RMP/EIS does incorporate extensive data and research to support the analysis 

of grazing impacts on invasive species. The EIS incorporates the analysis for the Vegetation 

Treatments Using Herbicides on BLM Lands in Oregon Record of Decision (USDI BLM 2010) in its 

analysis of invasive species. Changes included in the Invasive Plants section of Chapter 3 identify 

presence of invasive plant species in the areas available for livestock grazing, and provide citations 

supporting assumptions about the risk of invasive plant species introduction and spread associated 

with livestock grazing. 

Lands and Realty 

216. Comment Summary: It is not clear how valid existing water rights and irrigation ditch rights 

would be affected by designation of Right-of-Way avoidance areas and Right-of-Way exclusion areas 

under the alternatives.

Response: Considering the intermingled nature of the BLM-administered lands in the planning area, 

the BLM has granted many rights-of-way, leases, permits, and other established legal rights within 

the decision area over the years. Valid existing rights may pertain to timber sale contracts, mining 

claims, mineral or energy leases, leases, easements, permits, rights-of-way, and water rights. As 

explained in the Draft RMP/EIS, designation of right-of-way avoidance areas and right-of-way 

exclusion areas would guide BLM decisions on future right-of-way requests (USDI BLM 2015, p. 

366). The decisions in the RMPs, including designation of right-of-way avoidance areas and right-ofway exclusion areas, would not alter or extinguish valid existing rights on BLM-administered lands. 

Valid existing rights take precedence over the decisions in the RMPs. 

Lands with Wilderness Characteristics 

217. Comment Summary: Kerby Peak possesses wilderness characteristics and should be protected 

as potential Wilderness Area.

Response: As required under the FLPMA and current BLM policy, the BLM updated the 

wilderness characteristics inventories for western Oregon as part of this plan revision. In 

conducting these inventories, western Oregon BLM districts followed the guidance provided 

in BLM Manual 6310 – Conducting Wilderness Characteristics Inventory on BLM Lands 

(USDI BLM 2012). This manual provides a process for identifying BLM lands that meet the 

following criteria: (1) encompass at least 5,000 acres of roadless, contiguous BLM lands, (2) 

appear to be in a natural condition; (3) provide outstanding opportunities for solitude or 

primitive and unconfined recreation. 

To launch this inventory update, the BLM held a two-day workshop in Roseburg, Oregon, 

during August 2012. The workshop focused on an initial screening of the planning area to 

identify all areas that could potentially meet the minimum size criteria. Geographic 
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Information System (GIS) data were used to (1) identify BLM-administered lands that met the 

size criteria and (2) screen areas that met the size criteria for the absence of roads meeting 

wilderness inventory criteria as identified as part of the BLM’s Ground Transportation 

Network. Based on the outcomes of this screening, western Oregon districts began inventories 

during the summer of 2012. 

Kerby Peak does not encompass at least 5,000 acres of roadless, contiguous Federal lands and, as 

such, was not inventoried for wilderness characteristics during this update. 

218. Comment Summary: The BLM should designate all lands that possess wilderness 

characteristics as Wilderness Study Areas (WSA), and protect the identified wilderness values from 

management activities that would impair them.

Response: The BLM’s authority to designate additional lands as Wilderness Study Areas 

expired on October 21, 1993, as affirmed in the agreement that BLM affirmed in the Utah v. 

Norton wilderness settlement agreement (April 2003). 

219. Comment Summary: The Thompson Cantrall Extensive Recreation Management Area (ERMA) 

overlaps with the Burton Ninemile Lands with Wilderness Characteristics unit and should be 

designated as a closed OHV Management Area.

Response: The Proposed RMP maintains 6,103 acres of lands with wilderness characteristics 

within the Burton Nine Mile unit. Management direction to protect lands with wilderness 

characteristics includes designating these areas as closed for public motorized access 

(Appendix B – Management Objectives and Direction). The Thompson Cantrall ERMA 

management framework under the Proposed RMP would also be designated as a closed for 

public motorized access where the ERMA overlaps with lands with wilderness characteristics 

within the Burton Ninemile unit. 

220. Comment Summary: The Proposed RMP should protect the four lands with wilderness 

characteristics units that were identified in the Applegate Valley (Wellington Butte, Dakubetede, 

Burton Ninemile, and Round Mountain). Specifically, these four areas should be designated as closed

OHV Management Areas. Additionally, China Gulch was identified as an area that possesses 

wilderness characteristics and should be designated as a closed OHV Management Area. China Gulch 

and Wellington lands with wilderness characteristics should be protected. Any future management 

activities that would diminish wilderness characteristics should be prohibited.

Response: Under the Proposed RMP, the BLM would manage all inventoried lands with wilderness 

characteristics that occur outside of the Harvest Land Base for their wilderness characteristics, 

including the Burton Ninemile (6,103 acres) and Roundtop Mountain (5,295 acres) units. Because of 

the incompatibility between managing for wilderness characteristics and sustained-yield timber 

harvest, removal of Harvest Land Base acres causes the Dakubetede and Wellington units to fall 

below the 5,000-acre minimum size threshold in the Proposed RMP. 

221. Comment Summary: The Wellington Butte lands with wilderness characteristics unit should be 

expanded to include the entire headwaters of China Gulch.
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Response: The BLM, Medford District Office, completed a wilderness characteristics inventory 

evaluation for Wellington Butte. The Wellington wilderness characteristics inventory identified a 

contiguous mostly un-entered block of public lands within the middle Applegate watershed. It 

encompasses Wellington Butte in the heart of the area; Sugarloaf, to the northwest of Wellington; the 

headwaters of Long Gulch draining into the Applegate River to the south; all of the headwaters of 

Balls Branch, which drains into Humbug Creek to the west; and the west slopes of Mt. Isabelle. The 

wilderness characteristics inventory examined the area including the headwaters of China Gulch and 

found that this additional landbase did not possess wilderness characteristics. See Wellington 

Mountain wilderness characteristics inventory (USDI BLM 2013) for additional inventory 

information. 

Livestock Grazing 

222. Comment Summary: Grazing acre reductions outlined in the RMP should be prioritized to 

Riparian Reserve and stream buffers. Key ecosystem attributes should be monitored in areas where 

grazing is continued to ascertain whether continued use is consistent with ecological recovery, 

particularly as the climate shifts (Beschta et al. 2012).

Response: For all alternatives except Alternative D, the BLM only considered livestock grazing acre 

reductions as correlated to allotment-scale decisions on availability for livestock grazing. These 

boundaries are set based on fences and topography, which keep livestock within an area. Topography, 

exclosures, and riparian pastures to manage livestock and promote ecological health buffer a large 

majority of streams within existing allotments from livestock use. The Standards for Rangeland 

Health and Guidelines for Livestock Grazing Management for Public Lands Administered by the 

Bureau of Land Management in the States of Oregon and Washington (USDI BLM 1997) rigorously 

assess key ecosystem attributes at the allotment scale to determine if the fundamentals of rangeland 

health including physical function and biological health with elements of law relating to water 

quality, and plant and animal populations and communities are making significant progress toward 

being met or are being met. The BLM establishes short-term and long-term monitoring sites 

throughout allotments to continue to provide updated information on rangeland health. The Draft 

RMP/EIS discussed permitted livestock grazing levels of use in the analysis of Climate Change under 

issue 2 (USDI BLM 2015, pp. 136–140). 

Under Alternative D, the BLM would terminate existing livestock grazing authorizations and make 

all allotments unavailable for livestock grazing. In the analysis of Alternative D, the Draft RMP/EIS 

addressed the effects of no livestock grazing in the decision area (USDI BLM 2015, pp. 379–388). 

223. Comment Summary: The EIS does not identify each stream critical habitat reach for federally 

listed fishes and failed to identify how grazing would be changed to protect and improve critical 

habitat.

Response: The EIS considered rangeland health within each livestock grazing allotment (Appendix 

L – Livestock Grazing), which takes into consideration effects of livestock grazing within critical 

habitat of native, threatened and endangered, and locally important species. Additionally, consultation 

with the U.S. Fish and Wildlife Service and National Marine Fisheries Service regulate livestock 

grazing and monitoring efforts of ESA-listed fish species within riparian areas to maintain critical 

habitat. Rangeland health assessments use all available science and monitoring data including 
1938 | P a g e

condition and trend analysis. The BLM makes specific changes in livestock grazing and AUMs at 

allotment-specific scales when necessary based upon extensive monitoring. 

224. Comment Summary: Alternatives that eliminate livestock grazing by closing allotments to 

livestock grazing and terminating existing grazing authorizations are is in violation of several laws. 

Termination of grazing on BLM lands would render private lands as unavailable for livestock 

grazing.

Response: BLM Land Use Planning Handbook H-1610-1 states that the primary purpose of the land 

use plan is to make land use allocation decisions including identifying lands to be made available or 

unavailable for livestock grazing (USDI BLM 2008 pp. Appendix C, II-B). Making livestock grazing 

unavailable within an alternative of a land use plan is consistent with the FLPMA land use planning, 

taking into consideration the present and potential uses of public lands. Alternatives A, B, and C, and 

the Proposed RMP do not terminate any existing livestock grazing authorizations, as these allotments 

are currently vacant with no current parties proposing to graze. The NEPA process requires the BLM 

to provide an appropriate range of alternatives in the analysis. Alternative D provides a broad range of 

potential management options coinciding with a larger range for analysis purposes. The possibility of 

livestock grazing on allotments could occur through a special use permit, or special agreement with 

the BLM under any alternative. The BLM does recognize decisions to make allotments unavailable 

for livestock grazing may, in some situations, make private land livestock grazing difficult but does 

not make any decisions on private lands as unavailable. None of the alternatives would make a 

decision concerning private lands and do not prohibit fencing on private land. 

225. Comment Summary: The EIS includes management of recreation that is detrimental to livestock 

grazing. Why was the Lost Lake ACEC not to be considered for open to grazing with stipulations?

Response: Additional considerations and analysis were included in the Livestock Grazing section 

with reference to potential effects of a proposed SRMA to acres of available livestock grazing. The 

Lost Creek ACEC/RNA represents an Oregon Natural Areas Plan (ONAP 2015) cell for a midmontaine lake surrounded by mixed-conifer forest. It is an example of a landslide-damned lake. 

Long-term vegetation monitoring plots established in the RNA provide research value as a baseline 

for the Oregon Natural Areas Plan cells this ACEC/RNA represents. Livestock grazing, even with 

stipulations, would degrade the research value of the Lost Creek ACEC/RNA. 

226. Comment Summary: The grazing section contains inaccuracies and fails to provide information 

in a manner that allow the public to understand current grazing management and proposed grazing 

changes. No alternative was considered to increase grazing use. The grazing background section cites 

regulations that are not correct.

Response: The Draft RMP/EIS reported AUMs based on available database information. The BLM 

corrected discrepancies in AUMs on permits and AUMs available within the range database system in 

the Proposed RMP/Final EIS (see the Livestock Grazing section of Chapter 3). The BLM also 

updated information on suspended use in the Proposed RMP/Final EIS. Appendix L – Livestock 

Grazing includes all AUMs, including active use and suspended use. Suspended use otherwise was 

not included in the analysis as these are AUMs not available for use until more site-specific NEPA 

shows forage capacity for them. The purpose of the land use planning process is only to identify 

allotments as available or unavailable to livestock grazing; site-specific NEPA analysis would be 
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required for the BLM to increase AUMs on individual allotments. The BLM revised the Proposed 

RMP/Final EIS with the appropriate livestock grazing regulations in the Background section. 

227. Comment Summary: The EIS fails to identify that livestock grazing can also be used to control 

invasive species, reduce fire danger, and accomplish management objectives. The EIS fails to include 

BMPs to address upland water development for grazing.

Response: Although the RMP designates allotments as available or unavailable for livestock grazing, 

this does not limit the use of livestock grazing as a management tool to obtain other management 

objectives within tiered NEPA analysis. Typically, the BLM directs the use of livestock grazing as a 

tool to obtain specific management objectives through site-specific project planning and analysis. The 

invasive species program has a statewide EIS for managing invasive species with districts to complete 

specific EAs on the implementation of treatment options, which could include livestock grazing. Best 

Management Practices (Appendix J – Best Management Practices) provide compliance with the 

Clean Water Act of 1972 and set out goals and objectives to maintain water quality. Development of 

range improvements is more a management tool for livestock grazing. Conditions for range 

improvements are provided for in 43 CFR 4120.3. Appendix B – Management Objectives and 

Direction contains management direction specific to the design and maintenance of range watersource 

infrastructure. Any range improvement would require more site-specific project planning and 

analysis. 

Minerals 

228. Comment Summary: The BLM should complete the formal Mineral Potential Report and make 

the report available for public review as soon as possible. Appendix L was lacking in specific 

information about the locations of lands available for locatable mineral entry in the Medford District - 

specifically metals.

Response: The BLM did not complete reasonably foreseeable development scenarios and Mineral 

Potential Reports for this RMP revision. The BLM based all estimates on broad scaled “trends” 

review, which is an opinion as opposed to a methodological approach. As clearly stated in the Draft 

RMP/EIS, the RMP revision would only make recommendations for withdrawals, and the BLM 

would prepare mineral potential reports prior to each recommended withdrawal proposal (USDI BLM 

2015, pp. 398–399). 

229. Comment Summary: Will areas that are closed to mineral entry, such as Wilderness Areas, Wild 

and Scenic river segments, and some ACECs and RMAs, be protected from all mining operations?

Response: The RMP would close specific areas to salable mineral development (e.g., rock quarry 

development), as described in the Draft RMP/EIS (USDI BLM 2015, pp. 391–397). The RMP would 

make recommendations about withdrawal of specific areas to locatable mineral entry, but it is not 

within the authority of the BLM to make the withdrawals (USDI BLM 2015, pp. 398–403). The RMP 

would provide stipulations for leasable mineral development in specific areas, but would not close 

areas to leasing (USDI BLM 2015, pp. 403–404). 

The decisions in the RMPs will not alter or extinguish valid existing rights on BLM-administered 

lands. Valid existing rights take precedence over the decisions in the RMPs. Authorization for 
1940 | P a g e

implementing an action that would affect these valid existing rights may be subject to approval by the 

holders of valid existing rights and may not be discretionary to BLM. 

230. Comment Summary: The BLM should investigate the possibility of keeping records on material 

extracted from mining efforts. Something should be done to help pay for the environmental damage 

being done if it is not reclaimed. If it is reclaimed, the money could be refunded to the operator. I 

don’t know if this would be possible under the 1872 mining law but it should be researched.

Response: Record-keeping requirements for individual mining operations would be beyond the scope 

of the RMP revision. The BLM surface regulations for mining require that operators submit to the 

BLM an adequate financial guarantee for all Notices or Plans of Operations until the site is reclaimed. 

231. Comment Summary: Close and rehabilitate rock quarry sites that are close to depletion.

Response: The Proposed RMP includes management direction to reclaim quarries following the 

approved mining and reclamation plan. The BLM typically does not reclaim rock quarry sites that are 

close to depletion because of the potential for future use. 

232. Comment Summary: Develop an inventory of rock quarry sites with current value and viability.

Response: The BLM does have an inventory of rock quarry sites, and the Draft RMP/EIS described 

the currently developed quarry sites (USDI BLM 2015, pp. 392–395). The Proposed RMP/Final EIS 

updated the inventory of currently developed rock quarry sites based on additional information (see 

the Minerals section of Chapter 3). Additionally, there are historical borrow sites throughout the 

decision area that have not been recorded. As noted in the Draft RMP/EIS, the BLM does not have an 

inventory of potential quarry sites, which would be exorbitantly expensive to develop for the decision 

area and would require substantial speculation, given the myriad factors that influence potential 

quarry development. 

National Recreation Trails 

233. Comment Summary: The BLM should consider management direction that protects the Pacific 

Crest Trail by limiting recreational and commercial uses only to those that would not adversely affect 

PCT values and resources. This would include prohibiting or allowing races, endurance events, and 

fundraising.

Response: The BLM established management direction in the Proposed RMP that protects the values 

and uses, recreation setting characteristics and the established recreation outcome objectives for the 

Pacific Crest National Scenic Trail Special Recreation Management Area. The BLM developed the 

Proposed RMP to include management direction that would prohibit Special Recreation Permits that 

could potentially affect Pacific Crest Trail values and resources (Appendix B – Management 

Objectives and Direction). 

234. Comment Summary: The corridor width identified in Alternative B is insufficient to protect the 

Pacific Crest Trail and is inconsistent to managing for a foreground corridor. A 1-mile wide trail 
1941 | P a g e

management corridor would result in a 1/2 mile on each side of the trail and therefore capture the 

foreground as well as maintain a consistent management with adjoining land management agencies.

Response: The Proposed RMP includes a 1-mile wide corridor along the portions of the Pacific Crest 

National Scenic Trail in the decision area. 

235. Comment Summary: The viewshed analysis done for the Pacific Crest National Scenic Trail is 

incomplete. The BLM should revise the viewshed analysis to include lands managed by the USFS. 

This will allow analysis to consider, in addition, the current percentage of lands within the viewshed 

managed by an agency also holding responsibility for management of the Pacific Crest National 

Scenic Trail.

Response: The Proposed RMP/Final EIS has added an updated viewshed analysis that includes all 

U.S. Forest Service lands (see the National Trails System section of Chapter 3). 

Rare Plants and Fungi 

236. Comment Summary: The section on the effects of timber harvest on rare species needs to 

identify, clearly, what criteria would be used to determine if Bureau Sensitive plant protection is 

consistent with timber production. Without clear definitions in the RMP, land managers and other 

entities can dismiss Bureau Special Status designations in the field.

Response: The Bureau Special Status Species policy directs that the BLM address Bureau Sensitive 

species and their habitats in the planning process, and, when appropriate, identify and resolve 

significant land use conflicts with Bureau Sensitive species. In implementing a new RMP, the BLM 

would ensure that actions affecting Bureau Sensitive species would be carried out in a way that is 

consistent with its objectives for managing those species and their habitats at the appropriate spatial 

scale. The application of the Bureau Special Status Species policy to provide specific protection to 

species that are listed as Bureau Sensitive on lands governed by the O&C Act must be consistent with 

timber production as the dominant use of those lands (USDI BLM 2008, BLM Manual 6840 –

Special Status Species Management, sections 6840.06.2A – 6840.06.2E). The action alternatives and 

the Proposed RMP provide discretion for individual BLM implementation decisions regarding 

Bureau Sensitive species and their habitats. The determination of when specific protections to Bureau 

Sensitive species on O&C lands are not consistent with timber production as the dominant use of 

those lands is a determination best made at the project and site level. The Draft RMP/EIS analysis 

assumes that the BLM will implement the BLM Special Status Species policy for Bureau Sensitive 

species, and the commenter provides no foundation for their assertion that managers would “dismiss”

Bureau Sensitive species. 

237. Comment Summary: Population augmentation for threatened and endangered plants and oak 

stand management needs to be included in all alternatives in order to meet BLM policy.

Response: The Proposed RMP includes population augmentation for threatened and endangered 

plants and oak stand management. 
1942 | P a g e

238. Comment Summary: The USFWS recommends specific management activities to contribute to 

the conservation and recovery of the endangered western lily.

Response: Management direction common to all alternatives and the Proposed RMP would require 

the BLM to manage ESA-listed plant species consistent with recovery plans and designated critical 

habitat, including the protection and restoration of habitat; altering the type, timing, and intensity of 

actions, and other strategies designed to recover populations of species. The Proposed RMP includes 

additional management direction designed to contribute to the conservation and recovery of all ESAlisted plant species, including western lily. The proposed management direction would require the 

BLM to manage habitat to maintain populations of ESA-listed, proposed, and candidate plant species 

and to maintain or restore natural processes, native species composition, and vegetation structure in 

natural communities, consistent with the recommendations of the commenter. 

239. Comment Summary: According to the EIS‐volume I page 436‐the impacts from grazing on 

Gentner’s fritillary would be minimal, but other species were not discussed.

Response: The Proposed RMP/Final EIS has added text to clarify that Gentner’s fritillary is the only 

ESA-listed plant species present in any grazing allotment. The Proposed RMP/Final EIS has also 

added text to address potential grazing impacts to other Bureau Special Status plant and fungi species 

(see the Rare Plants and Fungi section of Chapter 3). 

240. Comment Summary: The effects from invasive species on Endangered, Listed, and Bureau 

Sensitive plants caused by grazing in open allotments was not analyzed other than speculative 

statements on page 436‐vol 1.

Response: The BLM addressed the effect of grazing on the introduction and spread of invasive 

species in the Invasive Species section of Chapter 3 in the DEIS. The Draft RMP/EIS stated that 

elimination of grazing would result in increased competition. The Proposed RMP/Final EIS has added 

text to clarify that competition refers to increased production of non-native plant species, including 

noxious weeds, which compete for resources with Bureau Special Status plants (see the Invasive 

Species section of Chapter 3). 

241. Comment Summary: RMP needs to acknowledge that loss of host trees and changes in forest 

conditions has direct and indirect impacts on rare plants and fungi.

Response: The Proposed RMP/Final EIS has included text to address direct and indirect impacts of 

the loss of host trees on rare plants and fungi (see the Rare Plants and Fungi section of Chapter 3). 

242. Comment Summary: RMP inaccurately states that prescribed burning rarely consumes duff, 

snags, or large logs, when in fact prescribed burning can consume all downed woody debris and burn 

20 feet up logs.

Response: The Proposed RMP/Final EIS has revised this discussion to acknowledge that prescribed 

burning can and does sometimes result in the consumption of downed woody debris and impacts to 

soil (see the Rare Plants and Fungi section of Chapter 3). 
1943 | P a g e

243. Comment Summary: The BLM should remove the reference to Dahlberg and Stenlid on page 

416 about sporocarps because it is misleading. The presence of fruiting bodies is very important 

because it demonstrates that a species exists in that location, regardless of the activity or location of 

underground mycelia. The purpose of these surveys is simply to ascertain whether certain species 

occur in the areas being surveyed.

Response: The BLM did not intend to imply that surveys for fungi are not useful in determining 

species presence. The Proposed RMP/Final EIS has revised this statement to clarify that visual 

observation cannot determine the extent of a fungal population, but the presence of sporocarps 

demonstrates that the species is present (see the Rare Plants and Fungi section of Chapter 3). 

244. Comment Summary: “Opportunistic” fungal surveys need to be more clearly defined and the 

EIS should demonstrate that “opportunistic” surveys would be effective in finding rare fungal species. 

If such surveys are inadequate, the proposed timber harvest in all action alternatives could contribute 

to the need to list Sensitive fungi.

Response: The Draft RMP/EIS used the word “opportunistic” to refer to surveys for fungi that are 

incidental to surveys for Bureau Special Status plants (USDI BLM 2015, p. 423). The Proposed 

RMP/Final EIS has replaced this word with language to clarify how and when the BLM would survey 

for fungi and that the BLM Manual 6840 – Special Status Species Management (USDI BLM 2008) 

would apply to all alternatives (see the Rare Plants and Fungi section in Chapter 3). The Proposed 

RMP/Final EIS has added discussion to illustrate how surveys for most fungi, including Bureau 

Sensitive and Survey and Manage species, are considered impractical and acknowledge that impacts 

are likely to occur to undocumented sites of rare and Bureau Sensitive fungi. The discussion in the 

Proposed RMP/Final EIS details that the Proposed RMP would protect most existing habitat for rare 

and Bureau Sensitive fungi species, would protect most known sites within the reserve allocations, 

and would result in an increase in the amount of habitat for rare and Bureau Sensitive fungi species 

(see the Rare Plants and Fungi section in Chapter 3). The commenter’s assertion that the proposed 

timber harvest in all action alternatives could lead to the “need to list Sensitive fungi” is contrary to 

the conclusions of the analysis in the Proposed RMP/Final EIS and is predicated on unsupported 

speculation. 

245. Comment Summary: Surveys for rare and Sensitive fungi need to be carried out in forests 

younger than 180 years old as well as in older forests. The BLM assumed that timber activities would 

not affect Survey and Manage plant and fungi sites directly in the No Action alternative because of 

pre‐disturbance surveys and site protection. This does not take into account the fact that only old 

stands are surveyed. Unless surveys are carried out, timber harvest activities will affect these species. 

This needs to be acknowledged and the effects analyzed in the EIS.

Response: Under the No Action alternative, the BLM would manage Survey and Manage species in 

accordance with the current Survey and Manage requirements. Most Survey and Manage fungi 

species are on the Category B list (i.e., pre-disturbance surveys not practical). Under the No Action 

alternative, the BLM would conduct ‘equivalent effort’ surveys for Survey and Manage fungi species 

for habitat disturbing activities within old-growth forests as defined by the 2000 Final Supplemental 

EIS for Amendment to the Survey and Manage, Protection Buffer, and other Mitigation Measures 

Standards and Guidelines (USDA FS and USDI BLM 2000). The Proposed RMP/Final EIS has added 

discussion to illustrate how surveys for most fungi, including Sensitive and Survey and Manage 

species, are considered impractical and acknowledge that impacts are likely to occur to 

undocumented sites of rare and Bureau Sensitive fungi. 
1944 | P a g e

Recreation and Visitor Services 

246. Comment Summary: The Recreation Management Areas that are proposed in the preferred 

alternative (Alternative B) need to be adjusted to include additional Recreation Management Areas 

proposed in Alternatives C and/or D.

Response: The BLM identified Alternative B as the preferred alternative in the Draft 

RMP/EIS. However, Alternative B does not provide the best possible response to the purpose 

and need of providing recreation opportunities.

Recognizing this, the BLM has developed a Proposed RMP that increases protection of the 

unique recreation settings and increases recreation use. To increase protection of unique 

recreation settings and increase recreation use compared to Alternative B, the Proposed RMP 

includes an approach to the management of recreation resources modified from Alternative C.

Appendix O – Recreation provides a comprehensive list of recreation management areas that the 

BLM is designating under the Proposed RMP. Recreation Management Frameworks describe the 

important recreation values, recreation outcome objectives, supporting management actions and 

allowable use activities for each recreation management area evaluated. The Recreation Management 

Frameworks also describe the types of visitor use for which the BLM would be managing recreation 

in that recreation management area.

247. Comment Summary: Table 3-127 Activity Specific Recreation demand for western Oregon 

communities is inaccurate.

Response: The Draft RMP/EIS presented the activity-specific demand percentages generated 

from individuals who participated in the BLM’s interactive mapping site during the winter of 

2012 (USDI BLM 2015, p. 450). This percentage is specific to those participants that 

responded to the interactive mapping tool.

248. Comment Summary: Access categories should be clearly delineated in recreation analysis due 

to legal access and right-of-way implications.

Response: In all action alternatives, the BLM only proposed recreation management areas 

where the BLM has legal public access. The BLM identified this requirement in the Planning 

Criteria (USDI BLM 2014, p. 110). Since reciprocal right-of-way agreements and some gating 

on BLM and adjacent private lands can prevent visitors from accessing BLM-administered 

lands for recreation use, the BLM first conducted an inventory to determine which BLMadministered lands are legally accessible to the public. 

249. Comment Summary: In the interest of public safety, the RMP should make a management 

commitment to significantly increase law enforcement efforts to enforce target shooting rules. RMP 

management guidelines for target shooting need to be more specific. Creation of no‐shooting buffers 

at trail heads and along trail corridors, both motorized and non‐motorized is essential for public 

safety. Given the nature of the terrain and vegetation in western Oregon, uncontrolled shooting on 
1945 | P a g e

public lands poses a serious threat to recreation users and residents of adjacent lands. Exploding 

targets such as Tannerite should be banned completely on all Western Oregon BLM lands.

Response: Recreation Management Area frameworks contained in Appendix O – Recreation 

identify and establish target-shooting restrictions for individual recreation areas. This includes 

areas identified for trail-based recreation, both motorized and non-motorized. The BLM has 

established these restrictions to protect recreation settings, achieve recreation specific outcome 

objectives, and account for public health- and safety-related concerns. The BLM has not 

established target shooting restrictions on BLM-administered lands outside of proposed 

recreation management areas. The BLM would evaluate additional target shooting restrictions, 

such as banning exploding targets, during implementation-level recreation management 

planning under all alternatives.

250. Comment Summary: Any Designation for OHV use in the Timber Mountain area is not 

appropriate. The existing conditions make the area unsuitable for development of OHV use.

Response: Under the Proposed RMP, the BLM has designated the Timber Mountain Recreation 

Management as limited for public motorized access in order to limit environmental impacts from 

OHV use. The BLM would determine the specific routes and trails that would be open to public 

motorized vehicle use through implementation-level travel management planning subsequent to the 

RMP revision (Appendix X – Guidance for Use of the Completed RMPs). 

The designation of specific routes and trails in implementation-level travel management planning 

would be consistent with the criteria outlined under BLM’s regulatory requirements in 43 CFR 

8342.1. These designation criteria require that trails be located to—

a) Minimize damage to soil, watershed, vegetation, air, or other resources of the public lands; 

b) Minimize harassment of wildlife or significant disruption of wildlife habitats. Special 

attention will be given to protect endangered or threatened species and their habitats; and 

c) Minimize conflicts between off-road vehicle use and other existing or proposed recreational 

uses of the same or neighboring public lands, and to ensure the compatibility of such uses 

with existing conditions in populated areas, taking into account noise and other factors. 

Socioeconomics 

251. Comment Summary: The Draft RMP/Draft EIS failed to quantify many economic benefits of 

conservation.

Response: The Draft RMP/EIS analyzed the relationship between the alternatives and the value of 

ecosystem goods and services associated with BLM-administered lands in Issue 1 of the 

Socioeconomics section (USDI BLM 2015, pp. 478–526). The Proposed RMP/Final EIS includes 

more discussion of the economic importance of non-market benefits to Oregonians and the regional 

economy. 

The analysis includes both market and non-market measures of value. Where reliable data are 

available, the analysis described values in monetary units. Where data are insufficient to allow for 

reliable estimation in monetary units, the analysis describes the value qualitatively, focusing on 

factors that would influence the direction, magnitude, and timing of change in value. 
1946 | P a g e

The BLM based the analysis of value on the underlying physical changes in ecosystems under each 

alternative, compared to current conditions, as described in the other resource sections of the Draft 

RMP/EIS. Thus, if a resource section did not identify variation among alternatives, such as water 

quality, for example, the analysis in the socioeconomic section of the value of the good or service 

associated with that resource also did not show variation. The affected environment described, and 

where data are available, quantified, the value of the resource under current conditions. 

252. Comment Summary: The Draft RMP/Draft EIS failed to relate market and non-market 

economic values.

Response: The BLM has updated the presentation of the market and non-market values analysis in 

Issue 1 of the Socioeconomics section of the Proposed RMP/Final EIS to clarify how the BLM 

estimated the market and non-market values of ecosystem services, and what the values mean in the 

context of the alternatives and the Proposed RMP. 

The Draft RMP/EIS presented the value of ecosystem goods and services in two broad categories: 

those traded in markets (market values), and those not traded in markets (non-market values) (USDI 

BLM 2015, pp. 478–526). The Draft RMP/EIS assessed the value of goods and services traded in 

markets using the market price people are willing to pay for them (e.g., stumpage prices). The Draft 

RMP/EIS assessed the value of goods and services not traded in markets using other measures of 

willingness to pay, derived using scientifically validated and professionally accepted techniques 

outlined in official BLM guidance for estimating non-market values (USDI BLM 2013a). 

These non-market valuation techniques result in monetary estimates for non-market goods and 

services that are comparable to market-based prices. These values are comparable insofar as they both 

reflect changes in society’s overall economic well-being. However, they are not comparable in how 

they contribute to the fiscal status of the economy. By definition, market values are associated with 

monetary transactions that have real financial impacts in communities. Non-market values reflect the 

importance people place on goods and services for which they do not have to pay real money, and 

estimate likely payments if market conditions did exist, such as if the BLM charged people what they 

were willing to pay to use outdoor recreation resources. People’s interactions with these non-market 

goods and services (e.g., participating in a mountain biking trip) may produce financial impacts 

traceable in the economy, but these impacts likely do not reflect the entire value associated with the 

good or service. 

The Draft RMP/EIS contains a reasoned analysis containing quantitative or detailed qualitative 

information on how the alternatives would affect market and non-market values. Thus, the Draft 

RMP/EIS took a ‘hard look’ at the effects on market and non-market values. 

253. Comment Summary: The Draft RMP/Draft EIS inadequately differentiated the fiscal impacts of 

the dollar value estimates of goods and services by benefit type.

Response: The BLM has updated the presentation of the market and non-market values analysis in 

Issue 1 of the Socioeconomics section of the Proposed RMP/Final EIS to clarify how the BLM 

estimated the market and non-market values of ecosystem services, and what the values mean in the 

context of the alternatives and the Proposed RMP. 

The analysis of the value of goods and services is an assessment of the economic value to society of 
1947 | P a g e

goods and services derived from BLM-administered lands, and how those values differ under the 

RMP alternatives. Following BLM guidance (USDI BLM 2013a), the analysis includes both marketbased and non-market goods and services. The analysis estimates both market and non-market values 

using professionally accepted valuation techniques. The resulting market-based and non-market based 

monetary estimates are comparable in the context of determining society’s overall economic wellbeing. However, market and non-market values result in different degrees of fiscal impact in 

economies. 

Market-based values, by definition, show up as monetary transactions in an economy. Non-market 

values, in contrast, do not contribute directly to the fiscal status of an economy. However, they do 

have indirect effects. People routinely make decisions or take actions because of the value they place 

on non-market goods and services. These actions result in monetary transactions that do affect the 

economy, though these transactions typically reflect only a small portion of the total economic value 

of the good or service. In the context of the Proposed RMPs, the most relevant example of this 

relationship is recreation: people do not typically pay to participate in outdoor recreation, but they do 

purchase gear, fuel, and lodging as a result of their participation. These purchases, while 

economically important, are not part of the description of the non-market value of recreation as 

presented in Socioeconomics Issue 1, but are, to the extent data allow, included in the analysis of 

economic impacts, described in Socioeconomics Issue 2, economic activity in the planning area. 

254. Comment Summary: The Draft RMP/Draft EIS failed to recognize the full value of water 

quality, especially variation across alternatives.

Response: The BLM based the analysis of economic value presented in Socioeconomics Issue 1 on 

the underlying physical changes in water quality arising from each alternative, as described in the 

Hydrology section of Chapter 3. In that section, the analysis did not identify variation across 

alternatives with respect to impacts to water quality parameters that contribute to people’s use or 

enjoyment of the resource (e.g., drinking, swimming, fishing, supporting biodiversity, and diluting 

downstream pollution). Thus, the analysis of the value of the good or service associated with water 

quality also did not show variation across alternatives. The Draft RMP/EIS acknowledged the 

importance of water quality services provided by BLM-administered lands, but did not estimate 

specific monetary values because of the uniformity of benefits across alternatives. 

255. Comment Summary: The Draft RMP/Draft EIS failed to estimate the socioeconomic value of 

biodiversity.

Response: The BLM has updated Issue 1 of the Socioeconomics section of the Proposed RMP/Final 

EIS to include more detail from the economic literature about the importance of biodiversity. The 

Draft RMP/EIS described in qualitative terms the value of biodiversity associated with BLMadministered lands and the effects of alternatives. Quantifying in monetary units the value of 

biodiversity of BLM-administered lands would require physical and economic data that is not 

available, and a level of analytical detail and precision that would be too speculative for a planninglevel analysis over a large landscape. 

256. Comment Summary: Loss of survey and manage will impact the local economy by removing 

numerous local survey jobs from the economy. These impacts were not disclosed or analyzed in the 

DEIS.
1948 | P a g e

Response: The loss of survey jobs from the elimination of the Survey and Manage measures is 

speculative. The commenter provided no specific information on the present number of local, 

seasonal survey jobs that the Survey and Manage measures might provide at any point in time during 

a calendar year, or whether these are volunteer or paid positions with any available wage data or other 

economic data that could have been included in the Draft RMP/EIS analysis of socioeconomic 

effects. The BLM would continue to provide management for species listed under the ESA including 

pre-disturbance surveys and surveys to find new populations for plant species listed under the ESA. 

Surveys for Bureau Sensitive species would continue to be an available management tool, to be used 

at the discretion of the BLM. It is speculative to assert that survey jobs would decline under the action 

alternatives or the Proposed RMP, given the management direction to conduct surveys for listed 

species and the discretion to use surveys to manage Bureau Sensitive species. 

257. Comment Summary: The Draft RMP/Draft EIS failed to estimate the value of views to private 

property owners.

Response: The BLM has updated Issue 1 of the Socioeconomics section of the Proposed RMP/Final 

EIS to include a more detailed description of the relationship between property values and scenic 

amenities on BLM-administered lands. The Proposed RMP/Final EIS also includes acknowledgement 

of the relevance of scenic amenities for property values as demonstrated by hedonic analyses 

(analyses of the characteristics or services related to a price of a marketed good). However, 

quantifying in monetary units the impacts of the alternatives on property values would require 

physical and economic data that is not available, and a level of analytical detail and precision that 

would be too speculative for a planning-level analysis over a large landscape. 

258. Comment Summary: The EIS should clearly identify the relative social cost of each alternative, 

specifically with respect to the social cost of carbon.

Response: The BLM has updated Issue 1 of the Socioeconomics section of the Proposed RMP/Final 

EIS to clarify confusion surrounding the description of the effects of the alternatives on the value of 

net carbon storage. The BLM has incorporated into the analysis updated data from the Climate 

Change section and has updated social cost of carbon values from the Interagency Working Group 

(IWG 2015), but the analytical methodology is fundamentally the same as in the Draft RMP/EIS. 

Issue 1 quantifies the value of net carbon storage, relying on carbon storage data presented in the 

Climate Change section that take into account emissions resulting from the alternatives. The value 

reflects the latest Federal estimates of the social cost of carbon, using the guidance and methods 

outlined by the Council on Environmental Quality (IWG 2015). 

259. Comment Summary: The Draft RMP/Draft EIS underestimated the social cost of carbon.

Response: The BLM has updated the social cost of carbon estimates presented in Issue 1 of the 

Socioeconomics section of the Proposed RMP/Final EIS. The estimates rely on the U.S. Interagency 

Working Group on Social Cost of Carbon’s (IWG) latest estimates and methodology, from July of 

2015 (IWG 2015). The IWG’s estimates are the best available estimates of the social cost of carbon at 

the current time. The IWG identifies limitations to the analysis in the 2010, 2013, and 2015 technical 

support documents. These identified limitations include some of the same concerns raised through 

public comments on the Draft RMP/EIS. The IWG acknowledges that these limitations may lead to 

an underestimation of the actual social cost of carbon (IWG 2010, p. 31). The economists charged 

with developing the estimates say they plan to continue to refine their estimates and methods as 
1949 | P a g e

researchers produce better valuation data on a wider range of global damages from climate change. 

Specifically, the Office of Management and Budget states, in responding to the many public 

comments it received on the 2013 Technical Support Document: 

[T]o ensure that the next SCC update keeps up with the latest available science and economics, 

we will seek independent expert advice on opportunities to improve the estimates, including many 

of the approaches suggested by commenters and summarized in the Response to Comments 

document. Specifically, we are asking the National Academies of Sciences, Engineering, and 

Medicine to provide advice on the pros and cons of potential approaches to future updates. Input 

from the Academies, informed by on-going public comment and the peer-reviewed literature, will 

help to ensure that the SCC estimates used by the Federal government continue to reflect the best 

available science and economics. Federal agencies will continue to use the current SCC 

estimates in regulatory impact analysis until further updates can be made to reflect the 

forthcoming guidance from the Academies. (Shelanski and Obstfeld 2015) 

Thus, the BLM believes using the current (2015) social cost of carbon estimates in the Proposed 

RMP/Final EIS is justified, because more comprehensive, peer-reviewed estimates are not available. 

The BLM has reviewed the studies presented by the commenters and the data limitations outlined by 

the IWG itself. To address the uncertainty that arises from these limitations, the BLM has 

incorporated discussion in the Proposed RMP/Final EIS to highlight the uncertainty and the 

implications for management decision-making (see the Socioeconomics section of Chapter 3). 

260. Comment Summary: The Draft RMP/Draft EIS failed to account, properly, for all costs of the 

RMP alternatives, including social, external, and non-market costs.

Response: The Draft RMP/EIS accounted for all costs of the alternatives to the extent practicable. 

The analysis of the value of goods and services presented in Issue 1 of the Socioeconomics section 

captured both market and non-market values, including many values typically identified as ‘external’

to timber harvest calculations. For example, the analysis considered the effects of the alternatives on 

water quality, net carbon storage, and recreation, among many other goods and services. The values 

of these goods and services, described both qualitatively and quantitatively, are presented alongside 

the market values of timber and other traditional extractive uses of BLM-administered lands, so 

readers may compare how each alternative would affect the entire suite of goods and services. Neither 

the CEQ regulations for NEPA nor BLM guidance require a benefit-cost analysis of alternatives. 

Moreover, a benefit-cost analysis would not be appropriate or produce an accurate comparison of 

benefits and costs (external or otherwise) given the level of detail available for each good and service 

across the planning area. 

261. Comment Summary: The EIS should discuss the impacts of differences in timber revenues on 

county services and community capacity not just on payments to counties. 

Response: The Draft RMP/EIS did discuss the impacts of differences in timber revenues on county 

services and community capacity. In Issue 3 of the Socioeconomics section, the analysis focuses on 

the effects of the alternatives on amount of payments to counties from activities on BLMadministered lands. Issue 5 of the Socioeconomics section incorporates output from Issue 3 into its 

analysis of the impacts of the alternatives on community capacity (USDI BLM 2015, pp. 569–588). 

The Draft RMP/EIS provided a historical context for the analysis of how alternatives may affect 

county payments and may affect spending on services. This information includes the relative 

importance of county payments to total county budgets, the types of county services supported by 
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county payments, and the challenges counties have faced and currently face with declining county 

payments from 2003 through 2012 (USDI BLM 2015, pp. 558–559). The Analysis of the 

Management Situation provided additional information, including county payments as a percentage of 

county budgets and as a percentage of county general funds discretional revenue (USDI BLM 2013, 

pp. 96–104). This information also included a description of the Oregon Secretary of State’s 

assessment of financial well-being, which found that all eight of the counties identified as having a 

higher rate of financial distress receive payments from activities on BLM-administered lands. The 

BLM incorporated this information into the Draft RMP/EIS by reference (USDI BLM 2015, p. 529). 

Counties choose how to spend these payments. Counties also decide whether and how to change 

spending on county services in response to changes in payments from activities on BLM-administered 

lands. It is outside the purpose or scope of the analysis to speculate how counties might choose to 

change future spending on county services in response to future changes in payments from activities 

on BLM-administered lands. 

262. Comment Summary: The Draft RMP/EIS used an inappropriate baseline year for analyzing 

payments to counties. The Draft RMP/EIS failed to adequately describe the historical conditions 

regarding county payments as a basis for understanding and providing context for the effects of the 

proposed alternatives on these payments. 

Response: The BLM based its analysis of county payments on the results of the vegetation modeling, 

which included projected timber harvest. The Draft RMP/EIS explained that the analysis used 2012 as 

baseline, because 2012 was the most recent year for which all economic data were available (USDI 

BLM 2015, pp. 527–528, 545, 557). Using the most recent data available assures that the economic 

analysis reflects current conditions and provides readers with a common reference point and context 

for the impacts described in the analysis. The BLM disagrees that its use of 2012 as baseline year is 

inappropriate. 

The Draft RMP/EIS included information on payments to counties for years 2003, 2007, 2010, and 

2012, allowing readers to compare payments in different time periods (USDI BLM 2015, p. 560). The 

Analysis of the Management Situation discussed how county payments would have been significantly 

less in 2007 had they been based on the payment formula in the O&C Act, rather than on the 

payments through the Secure Rural Schools and Community Self-Determination Act (SRS) (USDI 

BLM 2013, p. 103). The BLM provides additional information on payments to counties from 

activities on BLM-administered lands for earlier years on BLM’s website, 

http://www.blm.gov/or/rac/ctypaypayments.php. 

263. Comment Summary: The EIS should be revised to remove bias in its presentation of payment 

mechanisms to counties. The Draft RMP/EIS appears to favor payments under the SRS program 

rather than payments calculated using the O&C Act formula. 

Response: The BLM disagrees that its presentation of payment mechanisms is biased. The Draft 

RMP/EIS identified the uncertain future of SRS payments (USDI BLM 2015, p. 556). In light of this 

uncertainty of continued payments under the SRS formula, the Draft RMP/EIS analyzed the effects of 

the alternatives on county payments using the O&C Act formula. For comparison, the Draft RMP/EIS 

showed county payments in 2012 under both the SRS and the O&C Act formula (USDI BLM 2015, 

p. 561). Regardless, the BLM has no discretion over whether counties receive SRS payments or 

payments using the O&C Act formula. 
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264. Comment Summary: The EIS should acknowledge sources of funding (other than from County 

payments) are or could be available to offset county budget shortfalls. 

Response: The analysis of county payments evaluates how alternatives would affect payments to 

counties from activities on BLM-administered lands. Counties decide how to change spending in 

response to changes in payments from activities on BLM-administered lands. County residents, 

through their elected officials and through votes on taxes or fees, choose how they collect revenues to 

fund county services. How counties could obtain sources of funding other than payments derived 

from activities on BLM-administered lands is beyond the scope of an RMP. 

265. Comment Summary: The EIS fails to take into account the potential responses of other non‐

BLM timberland owners in analyzing market conditions. It also does not include an assessment of the 

rate of harvest on adjacent state and private forestlands and the implications this has for the relative 

value of goods and services from BLM lands. 

Response: The Draft RMP/EIS did include assessments of both potential responses of non-BLM 

timberland owners in assessing market conditions and those owners’ influences on markets in 

deriving values of goods and services on BLM-administered lands. Issue 1 of the Socioeconomics 

section in Chapter 3 discussed both these under the “Market Impacts of Changes in BLM Harvests” 

section. The analysis addressed the market (both price and harvest quantities) impacts of changes in 

BLM timber harvests under each alternative, specifically and quantitatively assessing the estimated 

change in private harvest under each alternative (USDI BLM 2015, pp. 515–516). The analysis 

incorporated these estimated responses to market conditions into the analysis of the values of BLM 

goods and services. The “Market Impacts of Changes in BLM Harvests” section, in part, served to 

help distinguish between gross harvest effects (the BLM Harvest Volumes in Table 3-165) and the 

net harvest effects, which was incorporated into the jobs and earnings analysis in Issue 2 of the 

Socioeconomics analysis. Thus, the BLM believes that the Draft RMP/EIS did take into account the 

potential responses of other non‐BLM timberland owners in analyzing market conditions. 

266. Comment Summary: The EIS should include a detailed assessment of externalities, subsidies, 

missing markets and other timber market failures in the planning area that distort normal market 

conditions. The Draft RMP/EIS was silent on the entire concept of normal markets, market failures, 

and how the proposed increase in logging was justified in the presence of them. 

Response: The BLM used recent as well as historical market trends and levels of activity by timber 

suppliers and buyers to develop the stumpage price projections used in the vegetation modeling in the 

Draft RMP/EIS. The Draft RMP/ EIS presented the historical stumpage prices in western Oregon for 

BLM, U.S. Forest Service, and state and private timber sales (USDI BLM 2015, p. 484–486). For 

BLM timber sales, stumpage is appraised and sold (by auction) in competitive markets at the fair 

market value. For projecting stumpage prices into the future, the BLM generalized trends from the 

volatile nature of the market, as explained the Draft RMP/EIS (USDI BLM 2015, pp. 480–481). 

Timber markets, like other commodity markets, are organic frameworks that operate with little 

structure other than to establish terms of trade. They seek to cover production costs of suppliers and 

to reduce factor costs of production. In the case of both public and private forest management, 

production costs include stand establishment costs, management costs, administrative costs, and 

harvesting costs. Externalities are often mitigated through regulation of forestry practices, such as 

stream buffers or limits on harvesting practices. There is little evidence of subsidies in western 
1952 | P a g e

Oregon timber markets, though Federal agencies may sell some timber at less than the production 

costs, typically as part of restoration strategies to reduce fire risks or to restore habitat. In such cases, 

the timber harvest represents a by-product of other achieving other management purposes. 

Timber markets in western Oregon are both highly competitive and volatile, as underlying market 

determinants shift. Because the BLM sells timber by auction in competitive markets, which represents 

the highest standard for establishing prices, market failures in the western Oregon timber markets do 

not constitute a substantial issue that would alter the analysis of effects of the alternatives on timber 

supply and demand as analyzed in the Draft RMP/EIS. The BLM does not agree that a detailed 

assessment of “externalities, subsidies, missing markets and other timber market failures” is 

necessary to analyze the effects of the alternatives on timber supply and demand. 

The commenter mischaracterizes the alternatives as constituting a “proposed increase in logging.” As 

clearly described in the Draft RMP/EIS, only three of the four action alternatives would provide more 

sustained-yield timber harvest than the volume declared in the 1995 RMPs, and only one of the four 

action alternatives would provide more sustained-yield timber production than the No Action 

alternative (USDI BLM 2015, pp. 262–263). Thus, the alternatives in the Draft RMP/EIS present an 

array of timber harvest levels that range above and below current levels and cannot be characterized 

as a proposed increase in logging. Regardless, the analysis does not purport to justify any particular 

timber harvest level, but to analyze the effects of the alternatives of resources, including timber 

supply and demand. 

267. Comment Summary: The EIS should explain the need for logs sourced from public lands, when 

hundreds of millions of board feet are harvested in Oregon and exported to our commercial 

competitors every year. 

Response: The O&C Act requires that the O&C lands be managed “for permanent forest production, 

and the timber thereon shall be sold, cut, and removed in conformity with the principal of sustained 

yield for the purpose of providing a permanent source of timber supply, protecting watersheds, 

regulating stream flow, and contributing to the economic stability of local communities and 

industries, and providing recreational facilities” (43 U.S.C. 1181a). In Chapter 1 of the Draft 

RMP/EIS, the BLM stated, “Based on the language of the O&C Act, the O&C Act’s legislative 

history, and case law, it is clear that sustained-yield timber production is the primary or dominant use 

of the O&C lands in western Oregon” (USDI BLM 2015, p. 15). The BLM based the purpose and 

need for this RMP revision on the laws that apply to the BLM, and one of the purposes for the RMP 

revision is to provide for a sustained yield of timber. Thus, the BLM has established that the BLMadministered lands in the planning area must provide for a sustained yield of timber, consistent with 

applicable statutes, regulations, and policies (USDI BLM 2015, pp. 5–10). 

The Draft RMP/EIS explained that public lands have been a major supplier of timber to mills in 

western Oregon for decades (USDI BLM 2015, pp. 484–486). Once timber is harvested, it flows 

across the region to various processing centers. There are few restrictions on how Federal timber 

flows across western United States, with the exception of the ban on the export of timber from 

Federal lands and substituting timber from Federal lands for exported private timber. The amount of 

timber harvest on other lands and the movement of harvested timber do not alter the applicable 

statutes, regulations, and policies that direct that the BLM-administered lands in the planning area 

provide a sustained yield of timber. 
1953 | P a g e

268. Comment Summary: The EIS should include a market analysis that is driven by optimization of 

revenue from timber harvests on a per mmbf basis. The BLM might be able to avoid the market 

response that the Draft RMP/EIS says will occur (i.e., reductions in private harvests and at the same 

time increase revenues for Counties without increasing acres treated). 

Response: One of the purposes for the RMP revision is to provide for a sustained yield of timber. 

The alternatives in the Draft RMP/EIS would result in an array of timber harvest levels and a 

consequent array of revenue from timber harvest and payments to counties (USDI BLM 2015, pp. 

509–516, 562–565). However, optimizing revenue from timber harvests or maximizing payments to 

counties were not purposes for the RMP revision. As a result, the BLM did not develop an alternative 

specifically designed to optimize revenue from timber harvests or maximize payments to counties. As 

explained in the comment response above in the Range of Alternatives section, the Draft RMP/EIS 

assessed a reference analysis of “Manage most commercial lands for maximizing timber production,” 

which would produce substantially more timber harvest (and consequently higher payments to 

counties) than the alternatives. However, the reference analysis of “Manage most commercial lands 

for maximizing timber production” would not be a reasonable alternative.

Additionally, the BLM did not develop the analysis of socioeconomic effects to derive a specific 

conclusion. According to CEQ regulations, the analysis in an EIS must provide a full and fair 

discussion of significant environmental issues and shall serve as a means of assessing environmental 

effects rather than justifying decisions already made (40 CFR 1502.1, 40 CFR 1502.2(g)). To design 

the analysis to reach the particular outcome of “optimization of revenue from timber harvest on a per 

mmbf basis” would not be consistent with the requirements for NEPA analysis. 

269. Comment Summary: The EIS should provide a better explanation of recreation participation 

forecasts. The EIS should be revised to better explain the basis for the recreation demand forecasts. 

The Draft EIS was flawed in that it implied a similar value for recreation across alternatives. 

Response: The BLM has revised the recreation participation forecasts to reflect different levels of 

recreation participation and value by alternative and the Proposed RMP in the Proposed RMP/Final 

EIS (see the Socioeconomics section of Chapter 3). 

The recreation participation forecasts in the Proposed RMP/Final EIS are based on trends developed 

by the U.S Forest Service specific to each of 17 categories of outdoor recreation, and include not only 

trends in preferences, but also factor in the effects of population growth, income growth, land use 

change and climate change. The U.S. Forest Service developed the trends for ten-year increments 

through the year 2060 (Bowker et. al. 2012). The BLM aligned these activity-specific forecasts and 

participation trajectories with the outdoor recreation categories monitored and reported within the 

BLM Recreation Management Information System (RMIS) database. The BLM applied the trends to 

the baseline (2012) participation levels by activity type. The recreation demand forecasts in the 

Proposed RMP/Final EIS include all measured recreation on BLM-administered lands, not just those 

proximate to population centers. The BLM included only those recreation activities that are measured 

and included in the RMIS in the basis for future extrapolations. 

In addition to forecasts for overall future participation levels, the Proposed RMP/Final EIS includes 

estimates of changes in outdoor recreation participation (visitor day and visit forecasts) by alternative 

and the Proposed RMP. The BLM based these estimates on different levels of outdoor recreation 

opportunities that would result from differences in Recreation Management Area total acreage by 

alternative and elasticity of demand estimates derived from data collected by the U.S. Census Bureau 
1954 | P a g e

as part of the American Time Use Survey. Appendix P – Socioeconomics provides detail on the 

methods for estimating and applying these demand elasticities. 

270. Comment Summary: The EIS fails to describe how the increased timber harvesting will take 

away the forest resources needed for job growth in the economic sectors such as tourism with long 

term growth potential. 

Response: The BLM does not agree with the commenter’s assertion that timber harvesting 

necessarily would “take away the forest resources needed for job growth” in other sectors, such as 

recreation and tourism. As demonstrated by the analysis in the Draft RMP/EIS, the amount and type 

of recreation opportunities on BLM-administered lands would not be constrained by the level of 

timber harvest, but rather by prioritization of recreation activities and locations, considering the 

overall set of options available to participants in western Oregon. Notably, the amount of recreation 

opportunities and the jobs and revenue associated with recreation shows no clear or direct relationship 

with the amount of timber harvest under the alternatives (USDI BLM 2015, pp. 454–470, 516–520). 

It is possible that timber harvest activities under the alternatives or Proposed RMP would inhibit 

certain types of outdoor recreation in certain specific locations, such as dispersed backcountry 

activities that prioritize wilderness conditions (USDI BLM 2015, pp. 467–468). However, the 

alternatives and the Proposed RMP provide for different recreational values on different portions of 

the landscape, including backcountry and wilderness conditions, but cannot provide for all values on 

every acre. As explained in the Recreation section of Chapter 3, where the BLM would manage 

recreation management areas within the Harvest Land Base, the BLM has determined that recreation 

management can be compatible with sustained-yield timber production. Therefore, allocation of the 

Harvest Land Base would not degrade BLM’s objectives for providing outdoor recreation 

opportunities and associated economic development conditions. 

271. Comment Summary: The BLM should revise the EIS to identify underestimated or omitted jobs 

attributable to recreation and tourism activities, including hunting, fishing, and wildlife viewing. 

Response: The BLM has revised the recreation participation forecasts in the Proposed RMP/Final 

EIS to reflect different levels of recreation participation and value by alternative and the Proposed 

RMP. These varying levels of recreation participation and value would result in varying levels of jobs 

and income attributable to recreation and tourism by alternative and the Proposed RMP in the 

Proposed RMP/Final EIS (see the Socioeconomics section of Chapter 3). 

Tourism in western Oregon is an important and complex component of local and regional economies. 

In the Proposed RMP/Final EIS analysis, the BLM estimates recreation and tourism-based jobs and 

income where there are transactions in the economy expected as a result of BLM resource 

management activities and where data are available to make the estimates. The visitor use estimates 

in the analysis include all recreation activities, including fishing, hunting, and wildlife viewing, and 

both local and non-local visitors (tourists). The Proposed RMP/Final EIS describes the valuation 

methodologies for recreation and visitation (see the Socioeconomics section of Chapter 3).

272. Comment Summary: The BLM should revise the EIS to identify jobs attributable to all 

amenities, both market and non-market that were omitted from the Draft RMP/Draft EIS. 

Response: The BLM believes that the analysis has identified the reasonably foreseeable effects of the 

alternatives on jobs. As noted in the comment response above, the BLM has revised the Proposed 
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RMP/Final EIS to reflect different levels of recreation participation and recreation-related jobs by 

alternative and the Proposed RMP. It is not the intent of this analysis to catalog all the ways in which 

BLM-administered lands contribute to life in western Oregon, however attenuated or speculative the 

connection with the alternatives. The BLM is required under the NEPA to provide analysis of 

significant issues (40 CFR 1501.7(a)(2), 40 CFR 1501.7(a)(3), 40 CFR 1502.1). The BLM also 

analyzes issues where their assessment is necessary to make a reasoned choice between alternatives 

considered (USDI BLM 2008, pp. 40–41). 

Western Oregon is known for amenities that extend and interconnect across all types of public and 

private lands. Amenities include cultural, institutional, and natural features that interact to provide an 

array of benefits for business and residents alike. Economic development in western Oregon often 

draws upon such attributes to attract new businesses or cultivate new ones, resulting in jobs and 

income for residents and newcomers. The BLM-administered lands contribute to this vast array of 

amenities in western Oregon through natural features such as forests, meadows, wildlife habitat, 

streams, topography, and juxtaposition with private lands. The BLM does not dispute that cultural, 

institutional, or natural amenities could be associated with BLM-administered lands in the planning 

area. However, there is insufficient information on such amenities to—

 Identify the production of goods and services associated with these amenities; 

 Forecast any changes in these amenities; and 

 Link any changes in these amenities to the alternatives or the Proposed RMP. 

Without such information, it is not possible to analyze any change in jobs associated with these 

amenities as a reasonably foreseeable effect of the alternatives or the Proposed RMP, beyond the 

effects on jobs analyzed in the Socioeconomics section of Chapter 3. 

273. Comment Summary: The BLM should revise the EIS to correct the number of jobs attributable 

to timber harvest and processing. These were overstated in the Draft RMP/Draft EIS. 

Response: The BLM disagrees that forest product industry jobs were overstated in the Draft 

RMP/EIS. Summaries of firm-level (individual business) data from Oregon Forest Resources Institute 

and from the University of Montana, Bureau of Business and Economic Research provided 

employment and income relationships to timber harvest by product type that are unique to Oregon. 

The BLM used the relationship data in conjunction with timber growth and harvest models to create 

and run seven customized IMPLAN® models of western Oregon (MIG, Inc. 2014) (see Issue 2 of the 

Socioeconomics section of Chapter 3). In addition, the BLM incorporated the effect of BLM harvest 

on other timberland ownerships to account for total market effects on jobs and income. The BLM 

believes that this analysis provides a reasoned analysis of jobs attributable to timber harvest and 

processing based on high quality, detailed, and quantitative information. 

274. Comment Summary: The BLM should revise the EIS using an earlier base year, not 2012, as a 

reference point for comparing jobs by alternative. 

Response: The BLM disagrees that the use of 2012 as baseline year is inappropriate. As explained in 

the comment response above, the BLM used 2012 as the base year for comparing jobs by 

employment because it was the most recent year for which all economic data were available (USDI 

BLM 2015, pp. 527–528, 545, 557). Using the most recent data available assures that the economic 

analysis reflects current conditions and provides readers with a common reference point and context 

for the impacts described in the analysis. In addition, using the most recent year as a benchmark 

assures that production, employment, and payrolls for all industries in the area reflect current business 

conditions. Production processes and relationships, whether in retail, service, or manufacturing 
1956 | P a g e

industries, change over time. Using old benchmarks could easily compromise the analyses, and 

mislead or cloud analysis results. Economic effects that are triggered by changes in BLM 

management start with and move forward from current economic and business conditions as 

described in the Affected Environment sections of the Socioeconomics section in Chapter 3. 

Additionally, the BLM has provided earlier base year information for employment within the 

planning area in the Analysis of the Management Situation (USDI BLM 2013, p. 105), and the BLM 

incorporated this information into the Draft RMP/EIS by reference (USDI BLM 2015, p. 529).

275. Comment Summary: The BLM should revise the EIS to use best available data in conducting 

jobs analysis, including publications by the Oregon Forest Resources Institute. 

Response: The BLM used detailed data from multiple sources in the various employment analyses 

presented in the Draft RMP/EIS, including data from the Oregon Forest Resources Institute and from 

the University of Montana, Bureau of Business and Economic Research. The analysis cites the data 

sources (including the Oregon Forest Resources Institute’s “2012 Forest Report: An economic 

assessment of Oregon’s forest and wood products manufacturing sector”) throughout the analysis of 

the effects of the alternatives and the Proposed RMP on jobs (see the Socioeconomics section of the 

Chapter 3). 

276. Comment Summary: The BLM should revise the EIS to fully consider industry trends when 

analyzing and presenting timber industry jobs by alternative. 

Response: The BLM fully considered historical and trend data as an aggregated description of the 

Affected Environment for the analysis of the alternatives on jobs. The BLM considered and has 

presented historical and trend data for employment, unemployment, and earnings in the planning area 

briefly in the Affected Environment portions of the Socioeconomics section in the Draft RMP/EIS 

(USDI BLM 2015, pp. 484–508, 529–545, 559–561, 576–584), and more fully in the Analysis of the 

Management Situation (USDI BLM 2013, pp. 98–108, 121–127). 

277. Comment Summary: The BLM should revise the EIS to recognize differing log sizes and their 

distribution across BLM districts as well as variations in manufacturing/processing capacity when 

estimating economic effects to the timber industry. 

Response: The Draft RMP/EIS included analysis of differing log sizes that would be harvested under 

each alternative (USDI BLM 2015, pp. 274–275). The jobs and income analysis for Issue 2 in the 

Socioeconomics section recognized three distinct grades of log products harvested from BLMadministered lands: veneer logs, sawlogs, and roundwood/pulpwood. As explained in the Draft 

RMP/EIS, the analysis considered each product using unique job and income relationships per unit 

volume harvested and processed (USDI BLM 2015, p, 548). 

The analysis used data on current log flows between district model areas, so that logs harvested from 

each district were distributed to processing centers according to current product transportation 

patterns. Based on these data, some logs harvested on BLM-administered lands are transported 

outside of western Oregon for processing. This is especially true for harvest from the Klamath Falls 

model area, where data show that 11 percent of logs are processed in California. 
1957 | P a g e

For this analysis, the BLM customized the economic models for the jobs and income analysis to 

represent current industry production (2012), but did not constrain the models to the current 

processing capacity. As such, the models allow production expansion as part of the analysis, if 

needed, to process harvest increases. 

Therefore, the BLM believes that the socioeconomic analysis in the Draft RMP/EIS did recognize 

differing log sizes and their distribution across BLM districts as well as variations in 

manufacturing/processing capacity. 

278. Comment Summary: The BLM should revise the EIS to correct or clarify the application of the 

stability/volatility analysis to avoid erroneous conclusions. The BLM should revise the EIS to reanalyze stability/volatility at a regional or local geographic scale instead of a national scale. 

Response: The BLM disagrees that it has incorrectly applied analysis of stability and volatility in 

analysis in the Draft RMP/EIS. The volatility analysis presented in the Draft RMP/EIS is one way to 

examine the historical pattern of economic growth rates and how BLM management might affect jobs 

and income in western Oregon. 

The timber industry has a long history in western Oregon, but it is not a stagnant one. Like most 

industries, timber-based firms have responded to changing product demands, fluctuating input 

availability, and U.S. business cycles by upgrading production processes to capabilities not seen or 

technologically available in decades past. The volatility analysis of growth rates does suggest that 

industries tied to commodity markets—like wood products —can be vulnerable to highs and lows not 

experienced by some industries. Steady timber harvests may eliminate one factor of industry 

volatility, but it cannot fully offset the volatility of commodity markets that are central to these 

timber-based firms. 

The jobs and income analysis in the Draft RMP/EIS showed how changes in timber harvest are likely 

to translate into an increase (growth) or decrease (contraction) of the timber industry and the local 

economy in the first decade of implementation of the alternatives, while the volatility analysis shows 

how steady such growth could be over many decades given historic patterns. As explained in the 

Draft RMP/EIS, the timber industry contributes high, year-round salaries to western Oregon, 

especially southwestern Oregon, that seasonal recreation-based industries do not, but it also brings a 

level of volatility that recreation-based industries do not (USDI BLM 2015, pp. 529–555). 

The BLM analyzed volatility at a local, district model area scale for portions of the analysis. This 

analysis encompassed all industries in each local area, and provided a local reference point for the 

historic national characteristics of both the timber-related and recreation-related industries. However, 

these data are limited in accounting for influences to the industry that national level data can present. 

The BLM conducted volatility analysis of growth rates for both timber-related and recreation-related 

sectors at the national level primarily to disclose the inherent characteristics of these industries and 

the markets they serve. A common data set at the national level made possible the long-term analysis, 

which better reveals growth patterns characterizing each industry. A national scale is especially 

necessary for timber-related sectors, as industries and harvests in western Oregon are strongly 

influenced by Federal timber management programs that are often driven by Federal Government 

interests rather than by markets. For this reason, national patterns are likely to represent a lower 

bound of growth-rate volatility for timber sectors in western Oregon. 
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279. Comment Summary: The BLM should revise the EIS to use cost relationships that vary by 

program size when estimating agency costs to implement the timber program under each alternative.

Response: The Proposed RMP/Final EIS has revised the cost estimates by using a variety of timber 

program costs per Mbf that better reflect the variation in harvest volume yield per acre and relative 

timber program costs by district and alternative and the Proposed RMP (see Issue 7 in the 

Socioeconomics section of Chapter 3, which reflects this updated information). 

280. Comment Summary: The EIS should be revised to adequately describe and capture the 

relationship between the BLM’s management and social conditions in the Counties including public 

safety, schools, and discretionary spending. The EIS’s capacity and resiliency analysis is flawed 

because it did not address some of issues which are paramount to social well-being: i) impacts to 

school enrollment, which ultimately affects future workforce availability, school funding, and ability 

to offer services; ii) labor force size trends; and iii) employment participation numbers relative to 

unemployment, which is reflected in the related social consequences of unemployment such as 

domestic violence, and drug and alcohol addiction. 

Response: The Draft RMP/EIS analyzed the relationship between BLM’s management and social 

conditions in the counties in several different ways throughout the Socioeconomics section. The 

analysis of socioeconomic resources has two broad emphases: economic growth and stability; and 

social capacity and resiliency (USDI BLM 2015, pp. 473, 570). Issues 3 and 5 addressed public 

safety, schools, and discretionary spending most directly. Issue 3 noted that counties use payments in 

various ways including for public safety, county roads, and education. Issue 3 also described the 

declines in payments to counties since 2003, the financial hardships and challenges that some of the 

counties face, and the different efforts by counties to deal with declines in payments (USDI BLM 

2015, pp. 558–565). 

While the capacity and resiliency analysis did not address every factor contributing to social wellbeing, it included a broad representation of factors. The Affected Environment for Issue 5 provides 

data on 13 metrics including education, unemployment, and health insurance (see Table 3-2, 

Capacity and Resiliency Metrics, in the Draft RMP/EIS). Further, these issues featured frequently in 

interviews with community representatives (see the interview summaries in Appendix P –

Socioeconomics). 

For the analysis in Issue 5, the BLM worked closely with the Cooperating Agencies Advisory 

Group’s Socioeconomics Working Group, as documented in the Planning Criteria (USDI BLM 2014) 

(see the Formal Cooperators section of Chapter 4). Members of that group urged the BLM to explore 

the relationship between the BLM’s management and specific social conditions such as public safety, 

child, family, and community health, school budgets and programs, unemployment, and drug and 

alcohol abuse. The BLM reviewed data on these conditions provided by group members and explored 

the potential, for example, to analyze quantitatively the relationship between an increase or decrease 

in a timber harvest and a change in a social condition, such as a sheriff’s office staffing levels. This 

proved to be not meaningfully possible because of the myriad of other factors that influence social 

conditions and the practical inability to isolate timber harvest volume as a factor affecting such social 

conditions. 

Instead, the BLM opted to explore the relationship qualitatively through interviews with city and 

Tribal representatives capturing personal experiences, perspectives, perceptions, and insights, to help 

tell each community’s “story” in relation to the RMP revision. The Issue 5 of the Socioeconomics 

section of Chapter 3 includes a brief summary of the interviews. Appendix P – Socioeconomics 
1959 | P a g e

provides detailed summaries of each interview. The BLM incorporated the conclusions from the 

interviews into a quantitative analysis to describe how the alternatives and the Proposed RMP would 

affect communities. 

Through the rounded, comprehensive analyses described above, the BLM believes it has adequately 

described the reasonably foreseeable effects of the alternatives and the Proposed RMP on social 

conditions in the counties. 

281. Comment Summary: The EIS’s capacity and resiliency analysis is flawed because it focused on 

cities and ignored the population living in unincorporated areas; these residents have been most 

impacted by changes in federal land management. The selection of cities for inclusion in the analysis 

seems to have been biased towards a desired result. The BLM chose 13 metrics of community 

capacity and resiliency, but they were chosen among a larger set of metrics. The subset of metrics 

chosen failed to accurately reflect the community benefits of forest conservation, leading to the 

conclusion that more logging will provide greater benefits 

Response: Much of the socioeconomic analysis in the Draft RMP/EIS presented effects at the county 

level and, as such, included the effects of the alternatives and the Proposed RMP on the populations 

of both incorporated and unincorporated areas. Therefore, the Draft RMP/EIS did not ignore either 

population. 

The Draft RMP/EIS noted that there are practical difficulties in comprehensively identifying some 

types of communities and in analyzing how the alternatives would affect them. With respect to the 

population living in unincorporated areas, this is largely due to the geographically dispersed nature of 

the residents that make up this population. The Draft RMP/EIS also explained that because much of 

the socioeconomic analysis is at the county level, the BLM opted to gain a different perspective on 

the potential impacts of the alternatives and the Proposed RMP by analyzing communities at the subcounty level (i.e., cities). The Draft RMP/EIS noted that incorporated cities comprise approximately 

70 percent of the population of the planning area, justifying special consideration in the 

socioeconomic analysis (USDI BLM 2015, pp. 569–576). Due to this high percentage of population 

in incorporated cities, the large number of cities, and their wide geographic distribution, and without 

evidence to the contrary, the BLM does not agree that the alternatives or the Proposed RMP would 

have greater effects on community capacity and resiliency for the population in living in 

unincorporated areas than the population in incorporated cities. 

The Draft RMP/EIS disclosed that analyzing all 134 (small and mid-size) cities, including conducting 

personal interviews, would have been impractical, and that the BLM decided that a 10 percent sample 

plus the Tribes would be sufficiently representative of the entire group. The BLM stratified 

(weighted) the sample of cities, so that it would be representative of the diverse geography of the 

planning area, and, within the stratification rules, selected 13 cities at random from the group of 134 

cities. The Draft RMP/EIS clearly described the methodology for stratifying and selecting the cities 

for inclusion, and the random selection ensured that the BLM did not bias the selection towards any 

particular outcome. The BLM developed this methodology in consultation with the Cooperating 

Agencies Advisory Group’s Socioeconomics Working Group (see the Formal Cooperators section of 

Chapter 4). 

The Draft RMP/EIS explained the selection of the capacity and resiliency metrics. The BLM selected 

these metrics to create a data baseline for assessing potential impacts from the alternatives and 

Proposed RMP, not with the intent of reflecting or favoring one type of benefit over another. The 

BLM selected the metrics in consultation with the RMP’s for Western Oregon Cooperating Agencies 
1960 | P a g e

Advisory Group’s Socioeconomics Working Group. The group considered a larger set of potential 

metrics, but, as described in the methods section, selected the final list based on each metric’s 

relevance to the capacity/resiliency question, availability of data across the communities, and analytic 

efficiency (USDI BLM 2015, p. 574). None of the selected metrics are directly related to timber 

harvest or logging, but are generally reflective of broad social or economic conditions, such as 

unemployment rate and median household income. Only one metric is directly related to a resource 

managed by the BLM: acres of outdoor recreation land (USDI BLM 2015, p. 578). Therefore, the 

BLM does not believe that the selection of the metrics failed to reflect benefits of forest conservation 

or was biased towards timber harvest. 

282. Comment Summary: The EIS should be revised to address the issue of the increased cost to 

county governments to provide services such as roads, sheriff patrols, and search and rescue as a 

result of increasing levels of activities on BLM lands. 

Response: The BLM has revised Proposed RMP/Final EIS to include a description of payments for 

services from BLM districts to local jurisdictions and other organizations (see Issue 3 in the 

Socioeconomics section of Chapter 3). The Cooperating Agencies Advisory Group’s Socioeconomics

Working Group discussed this issue, and the City of Sublimity representative described the issue in 

his interview for Issue 5 (see the interview summaries in Appendix P – Socioeconomics). 

The BLM districts contract with local jurisdictions (counties and cities) to provide services such 

noxious weed control, refuse removal, road maintenance and decommissioning, campground 

maintenance, habitat restoration, trail maintenance, law enforcement patrol, and emergency services. 

Payments for such services are highly variable from year to year depending on funding or special 

project needs. It is possible that unreimbursed county government expenses occur in specific 

locations under specific circumstances, but comprehensive data of the cost to county governments of 

providing services on BLM-administered lands is lacking. Therefore, it is not possible to project such 

expenses into the future or to analyze future change in such expenses as an effect of the alternatives 

or the Proposed RMP. 

283. Comment Summary: The EIS should revise its conclusion (p. 472 of the DEIS) that alternatives 

with more logging (i.e., Alternatives B and C) will provide greater benefits in terms of community 

capacity and resiliency in light of the EISs other conclusions that the timber industry is inherently 

volatile, that increased timber harvest may have an adverse effect on community stability, and that the 

social cost of carbon is high. 

Response: The conclusion that Alternatives B and C would make the strongest overall contributions 

to community capacity and resiliency is supported by the analysis of the capacity and resiliency 

metrics in the Draft RMP/EIS (USDI BLM 2015, pp. 472, 584–588). The Draft RMP/EIS discloses 

the volatility of the timber industry and analyzes in detail the social cost of carbon of the alternatives. 

While the analysis of timber industry volatility and the social cost of carbon provided information 

relevant to the discussion of the social and economic effects of the alternatives, it did not alter the 

analysis of the community capacity and resiliency metrics. The Interview Summary and Conclusions 

section of Issue 5 (Capacity and Resiliency) noted that, “With respect to the BLM’s impacts, the way 

the BLM manages timber is by far the number one issue of concern among the communities. The 

primary concern is economic” (USDI BLM 2015, p. 582). Therefore, the BLM has not revised its 

conclusion that Alternatives B and C would make the strongest overall contributions to community 

capacity and resiliency, as demonstrated by the analysis of the capacity and resiliency metrics. 
1961 | P a g e

284. Comment Summary: The EIS should address whether the Proposed RMP will change the State 

of Oregon’s distressed status of any of the counties and its communities to a non-distressed status or 

will the status remain the same or get worse. 

Response: The Draft RMP/EIS discussed distressed areas, which the State defines based on 

indicators that take into account unemployment rates, per capita personal income, change in average 

covered payroll per worker over 3 years, and change in the county’s weighted average employment 

change over 2 years (USDI BLM 2015, pp. 477–478). However, this analysis cannot project how the 

alternatives or the Proposed RMP would change which areas the State identifies as distressed, 

because the BLM cannot project precisely and accurately how the alternatives or the Proposed RMP 

would alter the specific indicators that the State uses to define distressed areas. Nevertheless, the 

Proposed RMP/Final EIS notes in Issues 2, 5, and 6 of the Socioeconomics section of Chapter 3 

where different alternatives or the Proposed RMP could adversely affect different geographic areas 

with respect to employment and earnings and capacity and resiliency. The Proposed RMP/Final EIS 

also notes which of these geographic areas are in distressed areas. 

285. Comment Summary: The EIS’s analysis of environmental justice should include the full 

geographic scope of the impacts of climate change, many of which will occur elsewhere in the U.S. 

and the world, and the fact that the cost of climate change will fall disproportionately on the poor and 

disadvantaged communities. 

Response: The BLM NEPA Handbook explains that the geographic scope of the effects analysis does 

not extend beyond the scope of the direct and indirect effects of the action (BUSDI BLM 2008, pp. 

58–59). The BLM appropriately limited the geographic scope of the environmental justice analysis to 

the counties within the planning area, because these areas reflect the scope of the direct and indirect 

social and economic effects of the alternatives (USDI BLM 2015, pp. 589–591). Climate change, in 

and of itself, is not an effect of the BLM action. The Draft RMP/EIS analyzed the effects of the 

alternatives on carbon storage and greenhouse gas emissions, and described how climate change 

would interact with BLM management actions to alter the potential outcomes for key natural 

resources. As detailed in that analysis, all alternatives would result in a net increase in carbon storage 

over time (USDI BLM 2015, pp. 132–164). Nevertheless, the BLM cannot equate any specific 

greenhouse gas emissions or any specific change in net carbon storage with specific climate change 

effects. Therefore, the BLM does not consider the “the full geographic scope of the impacts of 

climate change” as an effect of the BLM action, and the effects of climate change on poor and 

disadvantaged communities outside of the planning area is beyond the scope of this analysis. 

286. Comment Summary: The EIS should acknowledge that the shift in harvest volume from the 

BLM’s Coos Bay, Roseburg, and Medford Districts to the northern districts will have negative 

impacts on the Coquille Indian Tribe’s ability to harvest and market timber from the Coquille Forest 

and result in decreased timber revenue to the Tribe. 

Response: The Proposed RMP/Final EIS acknowledges that there would be a shift in harvest volume 

generally from southern to northern BLM districts under the Proposed RMP. However, it is not 

reasonably foreseeable that this shift in BLM management of timber would affect the Coquille 

Tribe’s ability to harvest and market timber from the Coquille Forest. 

As explained in the Tribal Interests section of Chapter 3, the Coquille Tribe manages the Coquille 

Forest “subject to the standards and guidelines of Federal forest plans on adjacent or nearby Federal 
1962 | P a g e

lands, now and in the future” per Title V of the Oregon Resource Conservation Act of 1996 (Pub. L. 

104-208). This means that the adopted BLM RMP that applies to the Coos Bay District will also 

apply to the Coquille Forest in that it will establish the suite of possible management approaches 

available for the Coquille Forest. However, the BLM RMP will not determine which specific land use 

allocations apply to which specific portions of the Coquille Forest or the rate or extent of timber 

harvest on the Coquille Forest. Absent such information, the BLM cannot ascribe any particular effect 

of the BLM RMP on the Coquille Tribe as a result of the BLM RMP establishing potential 

management approaches available for the Coquille Forest. 

287. Comment Summary: The RMPs have no provisions for and the EIS does not discuss how the 

BLM intends to go about offsetting both the federal financial costs and negative externalities of an 

increased timber sale program. 

Response: The Draft RMP/EIS presented a detailed analysis of the “federal financial costs” and the 

“negative externalities” associated with timber harvest. 

The commenter mischaracterizes the alternatives as constituting “an increased timber sale program.” 

As clearly described in the Draft RMP/EIS, only three of the four action alternatives would provide 

more sustained-yield timber harvest than the volume declared in the 1995 RMPs, and only one of the 

four action alternatives would provide more sustained-yield timber production than the No Action 

alternative (USDI BLM 2015, pp. 262–263). Thus, the alternatives in the Draft RMP/EIS present an 

array of timber harvest levels that range above and below current levels and cannot be characterized 

as an increased timber sale program. 

The Draft RMP/EIS provided a detailed and quantified analysis of the costs of the alternatives, 

specifically breaking out the costs of the timber sale program (USDI BLM 2015, pp. 599–602). For 

the Proposed RMP/Final EIS, the BLM has revised its cost estimates by using a variety of timber 

program costs per Mbf that better reflect the variation in harvest volume yield per acre and relative 

timber program costs by district and alternative (see the Socioeconomics section of Chapter 3). 

Nevertheless, as stated in the Draft RMP/EIS, “the BLM’s selection of an alternative does not 

authorize funding to any specific project or activity nor does it directly tie into the agency’s budget as 

appropriated annually through the Federal budget process” (USDI BLM 2015, p. 600). Identifying 

funding levels or funding mechanisms for the timber program or any other resource program is 

beyond the scope of an RMP. Thus, the Proposed RMP/Final EIS appropriately does not attempt to 

address whether or how the BLM “intends to go about offsetting ... the federal financial costs ... of 

an increased timber sale program” for the alternatives or the Proposed RMP. 

The commenter does not specify which “negative externalities” they believe result from timber 

harvest. Nevertheless, the Draft RMP/EIS analyzed in detail all significant effects that would be 

caused directly or indirectly by timber harvest under the alternatives (USDI BLM 2015, pp. 105–

862). The specific analyses are too numerous to itemize here, but include analyzing the effects of 

timber harvest on habitat for plants, fish, and wildlife, water quality, soil productivity, particulate 

emissions, greenhouse gas emissions, recreation opportunities, visual quality, jobs, earnings, and 

payments to counties. These analyses describe in detail the externalities, both positive and negative, 

associated with the array of timber harvest levels that would result under the alternatives. Where 

significant adverse effects would occur from timber harvest or other resource management, the 

alternatives in the Draft RMP/EIS vary in their design and consequently vary in the adverse effects 

that would occur. Where adverse effects would occur from timber harvest or other resource 

management under all alternatives, the Draft RMP/EIS considered how to mitigate such adverse 

effects. The Records of Decision for the RMP revision will address mitigation measures that the BLM 
1963 | P a g e

will adopt and mitigation measures that the BLM will not adopt. The BLM will address the extent to 

which it will be “offsetting” negative externalities of timber harvest in the Records of Decision, 

which will explain how the BLM balances the beneficial and adverse effects of timber harvest against 

other resource objectives in selecting an RMP. 

288. Comment Summary: The EIS should expand the economic measures of success to include other 

values such as those achieved by the requirements of the Clean Water and Air Acts, enhancement of 

fisheries, recreation, and other forest resources. 

Response: The Proposed RMP/Final EIS includes a Monitoring Plan with three socioeconomic 

reporting items. The Monitoring Plan notes that such items involve activities that are related to certain 

analytical assumptions that are pertinent to non-specific management actions, or analytical 

assumptions pertinent to the analysis of environmental consequences in the Proposed RMP/Final EIS 

(Appendix V – Monitoring Plan for the Proposed RMPs). The items suggested in the comment are 

not related directly to the analysis of socioeconomic consequences. Instead, the Proposed RMP/Final 

EIS has addressed the analysis of effects on these resources in the sections of Chapter 3 on Air 

Quality, Hydrology, Fisheries, Recreation, and Forest Management, respectively. Furthermore, the 

BLM has included management objectives for Air Quality, Hydrology, Fisheries, Recreation, and 

Forest Management (Appendix B – Management Objectives and Direction). Finally, the BLM has 

addressed monitoring of these resources in both effectiveness and implementation monitoring 

(Appendix V – Monitoring Plan for the Proposed RMPs) 

Soil Resources 

289. Comment Summary: The BLM should have developed a reasonable action alternative that 

would have reduced, as opposed to increased, the amount of detrimental soil disturbance associated 

with intensive harvest activities and road construction that are emphasized in the action alternatives.

Response: The Draft RMP/EIS analyzed the amount of detrimental soil disturbance that would occur 

under the alternatives, in addition to the detrimental soil disturbance that has already occurred. The 

alternatives would result in differing amounts of additional detrimental soil disturbance, based on 

actions such as timber harvest, road construction, and fuels reduction treatments (USDI BLM 2015, 

pp. 608–628). Some amount of additional detrimental soil disturbance is necessarily incidental to 

implementing the management actions necessary to meet the purposes of the action. That is, it would 

not be possible to develop a reasonable alternative that would not result in some amount of additional 

detrimental soil disturbance. To reduce the amount of total detrimental soil disturbance to less than 

the current amount of detrimental soil disturbance would require that the BLM ameliorate more total 

detrimental soil disturbance than any additional detrimental soil disturbance. Such an alternative is 

not feasible, given the economic and technical challenges of ameliorating existing detrimental soil 

disturbance. Amelioration of detrimental soil disturbance, through practices such as tillage, is 

typically only feasible during forest management operations in a stand, such as timber harvest, when 

the necessary machinery is on-site. Identification of specific locations of detrimental soil disturbance 

from past management actions and possible amelioration is typically only feasible with site 

inspections, which typically occur when the BLM is contemplating a new management action, such 

as a timber sale. It is not practical to conduct amelioration of detrimental soil disturbance over a 

substantial acreage in the absence of other forest management actions because of the cost. 

Implementation of such forest management actions would entail additional detrimental soil 
1964 | P a g e

disturbance, further frustrating any attempt to reach a net decrease in total detrimental soil 

disturbance. 

The cost for measures to ameliorate detrimental soil disturbance are highly dependent on site- and 

project-specific factors. Furthermore, implementing such measures during forest management 

operations typically provides efficiencies associated with bringing machinery to the site, which the 

BLM cannot account for in this estimate. Any attempt to estimate average costs for ameliorating 

detrimental soil disturbance in the absence of other forest management actions is highly approximate 

and variable. Nevertheless, based on past project experiences, the BLM estimates an approximate cost 

of $1,000 per acre to ameliorate detrimental soil disturbance. The Draft RMP/EIS identified that there 

are139,299 acres of existing detrimental soil disturbance from past management action, and that the 

alternatives would result in additional detrimental soil disturbance ranging from 18,138 acres under 

Alternative A to 41,506 acres for Alternative C (USDI BLM 2015, pp. 611–612). Thus, an alternative 

that would result in a net decrease in the overall acreage of detrimental soil disturbance would require 

additional funding ranging from more than $18 million under Alternative A to more than $41 million 

under Alternative C, which would represent approximately a quarter to a third of the entire annual 

BLM budget for the decision area. 

290. Comment Summary: The EIS should be revised to include more detailed information on soils, 

including maps of soil regions and more information on soil types.

Response: The Draft RMP/EIS included the appropriate level of information on soils to inform 

decision-making. The planning area covers an extensive area, and tables displaying details on each 

soil type present would be cumbersome, and not provide information necessary to understanding the 

analysis presented. The level of detail desired by the respondent is more informative to project-level 

planning. However, soil-mapping information is publicly available through the Natural Resources 

Conservation Service (NRCS). The NRCS is the Federal agency responsible for soil typing and 

mapping, and information on soils within the planning area can be found using their Web Soil Survey 

application (http://websoilsurvey.sc.egov.usda.gov/App/HomePage.htm). In the implementation of 

the RMP, site-specific analysis prior to management actions will identify soil types, and apply 

appropriate management recommendations for fragile soils found on site. The BLM will identify soils 

unsuitable for sustained-yield timber production and add such areas to those areas reserved through 

updates to the Timber Production Capability Classification system (Appendix V – Monitoring Plan 

for the Proposed RMPs). The BLM can identify more effectively and accurately these specific soil 

types and conditions through site-specific analysis than the coarse and low accuracy mapping that 

would be possible at the scale of the RMP revision. 

291. Comment Summary: The EIS should be revised to include Best Management Practices to 

protect from potential landslides from future harvest near existing State highways and considerations 

for public safety from landslide dangers.

Response: The Proposed RMP includes several Best Management Practices to protect from potential 

landslides in harvest units (Appendix J – Best Management Practices). The BLM designed these 

Best Management Practices to reduce the risk from potential landsliding because of the dangers 

landslides can present to human safety and infrastructure. The BLM does not design Best 

Management Practices differently when they are adjacent to highways—all units and roads are 

afforded equal measures for protection. The management direction contains the operational practices 

for avoiding road construction and future harvests that reduce the high potential areas for landslides 

during management actions. Avoiding unstable slopes and not creating unstable slopes with tillage 
1965 | P a g e

should protect all lands downslope, including State highways, which would also provide for public 

safety protections. 

292. Comment Summary: The EIS should be revised to clearly disclose the locations and analyze the 

impacts of machine piling on soil resources. Machine piling in harvest units can cause soil 

compaction, reduce microbial activity, and affect tree growth.

Response: The Draft RMP/EIS analyzed the effects of machine piling on soil resources, including 

effects on forest productivity, and acknowledged the potential effects of machine piling (USDI BLM 

2015, pp. 608–611, 617–621). The Draft RMP/EIS identified that machine piling would produce 

detrimental soil conditions on between 1,674 to 4,307 acres, depending on alternative. The Draft 

RMP/EIS identified that the effects of machine piling may bring reduced seedling growth or 

vegetative cover of native plants. The discussion describes the impacts from soil compaction, the 

reduction of microbial activity, and the potential reduction of soil processes from accumulated ground 

materials from mastication practices. Because machine-piling locations would be largely dependent 

upon timber harvest locations, it would be speculative to forecast specific machine piling locations at 

this scale of analysis.

293. Comment Summary: The EIS should be revised because it relies on false assumptions that OHV 

users will operate vehicles consistent with BLM decisions and by deferring analysis until future 

implementation planning. Impacts to soil from OHV use are well‐documented, and the EIS fails to 

incorporate analysis on illegal use for this topic.

Response: The Draft RMP/EIS identified that data is unavailable at this scale of analysis to predict 

location or effects of any widespread or systematic illegal OHV use (USDI BLM 2015, p. 623). 

Across the scale of the decision area, the BLM is unable to characterize the current illegal use or 

forecast impacts under any of the alternatives. The BLM assumed for analytical purposes that OHV 

users would operate vehicles in a legal manner consistent with BLM decisions about OHV use. 

Decisions about OHV use in land use planning classify lands as open, limited, or closed. The BLM 

has differed designation of individual routes for OHV use to implementation-level travel management 

planning (Appendix X – Guidance for Use of the Completed RMPs). Where the BLM has sitespecific information about illegal OHV use, such as OHV users creating new trails in areas 

designated as limited to existing roads and trails, the BLM would be able to address management 

through implementation-level travel management planning. 

294. Comment Summary: The EIS should be revised because literature citations used to determine 

the presumed detrimental disturbance to soil from timber harvest activities are outdated, and studies 

used outdated forest practices. The EIS misinterprets the study conclusions cited and applies 

inaccurate measures for analysis.

Response: The Draft RMP/EIS used relevant science for determining analytical methods and 

anticipated effects of harvest activities on soil quality. The BLM determined detrimental disturbance 

percentages from harvest types based upon multiple scientific sources. The commenter did not 

present any alternate studies for the BLM to consider and did not specifically identify misinterpreted 

scientific conclusions. 
1966 | Page

295. Comment Summary: The EIS should be revised because the presumed detrimental disturbance 

levels for timber harvest activities and road construction misrepresent modern forest practices and 

overstate the amount of damage. These blanket assumptions are misleading and wrong because 

detrimental disturbance can be and often is avoided.

Response: The Draft RMP/EIS clearly identified that analytical estimates used for both harvest 

actions and road construction have several limitations, and overestimate the amount of detrimental 

soil disturbance that would occur (USDI BLM 2015, pp. 609–611, 615–621, 625–626). Limitations 

identified include an inability to account for amelioration of detrimental disturbance due to the sitespecific and project-specific elements that effect extent and effectiveness of the actual reductions, the 

inability to determine at this scale of analysis the number of temporary roads that would receive 

decommissioning, and constraints within modeling parameters necessitating fixed-widths for road 

construction. However, at this scale of analysis, the BLM cannot provide more accurate assumptions 

about the effects of actions on soils, and the commenter does not provide more accurate assumptions. 

The BLM generated the acreages of detrimental soil disturbance in the Draft RMP/EIS using the same 

assumptions for all alternatives. Therefore, the analysis provides an effective comparison of the 

relative differences in resource effects. 

Trails and Travel Management 

296. Comment Summary: The Proposed RMP should contain a clear schedule showing the list of 

Travel Management Plans needed for each BLM district with their completion dates over the next 

five years.

Response: The Proposed RMP/Final EIS contains the criteria for managers to apply in determining a 

district-level prioritized implementation travel management planning schedule in Appendix Q –

Public Motorized Access Designation Guidelines. 

297. Comment Summary: The decision to allow unauthorized user-created trails to remain in use 

until a Travel Management Plan is developed rewards illegal and resource-damaging behavior. 

‘Grandfathering’ user-created OHV trails should not be allowed.

Response: The BLM is deferring implementation-level travel management planning in accordance 

with current BLM policy (see the Trails and Travel Management section of Chapter 3). The BLM is 

making area designations of open, limited, or closed for public motorized access through this RMP 

revision. Implementation-level travel management planning will evaluate each route, applying the 

minimization criteria contained in 43 CFR 8342 and the direction in BLM Manual 1626 – Travel and 

Transportation (USDI BLM 2011a) and BLM Handbook 8342 – Travel and Transportation Handbook 

(USDI BLM 2012), which provides policy guidance for incorporating the BLMs Travel and 

Transportation Management (TTM) planning decisions into the land use planning process. Under this 

policy, the area designation of limited to existing roads and trails is an appropriate use of the 

allocation until the BLM completes an implementation-level travel management plan. 

Vegetation Modeling 
1967 | Page

298. Comment Summary: The BLM should revise the EIS because the analysis inflated the 

productivity estimates. The Southern Oregon Forest Restoration Collaborative (SOFRC) provides a 

better estimate of productivity.

Response: As explained in the Draft RMP/EIS, the BLM used the Current Vegetation Survey (CVS) 

permanent inventory plots, and the stand-level information found in the Microstorms database to 

estimate productivity on BLM-administered lands (USDI BLM 2015, pp. 98–102, 987–1043). The 

productivity estimates used by the SOFRC in their Rogue Basin Cohesive Forest Restoration Strategy 

is based upon Gradient Nearest Neighbor (GNN) analysis. This does not provide a better estimate of 

productivity on BLM-administered lands than what the BLM used in the Draft RMP/EIS. The CVS 

inventory data provides a non-biased, impartial estimate of current inventory volume and growth on 

BLM-administered lands. The Microstorms database also provides the best available information on 

forested stands on BLM-administered lands. This database is maintained by the BLM and includes 

descriptions of the forest vegetation, forest treatments, and forest surveys through time. The GNN 

analysis is based on remotely sensed, Landsat data, which is not specific to BLM-administered lands, 

and provides much less detail. The BLM did make use of GNN analysis in innumerable analyses in 

the Draft RMP/EIS, but only on non-BLM-administered lands, where the BLM lacked data 

comparable to the CVS plots and Microstorms database (e.g., USDI BLM 2015, pp. 100, 673, 1453). 

Appendix C – Vegetation Modeling describes how the BLM used CVS and Microstorms data to 

model the forested vegetation. The BLM used many aspects of both data sets in the vegetation 

modeling. The tree lists for each modeling strata came directly from the CVS sub-plot tree lists. The 

BLM compared the growth on the first and second measurement of the permanent plots, with the 

projections from the ORGANON growth model, and found that ORGANON was adequately 

projecting growth. The productivity estimates in the harvest land base in the Draft RMP/EIS are 

similar to what the BLM has measured on the CVS plots. The BLM based the distribution of site 

productivity classes within each modeling unit (district) on the distribution of site productivity classes 

measured on the CVS plots. The productivity has not been “inflated,” as the commenter contends; it 

provides the best representation of the actual measured conditions of forests on BLM-administered 

lands. 

299. Comment Summary: AOCC is concerned about the BLM’s modeling of the alternatives to 

estimate harvest acreage and volume by different harvest types.

Response: As explained in the Draft RMP/EIS, the BLM constrained the modeling of timber harvest 

to the volume of timber that could be produced continuously for 200 years with the management 

practices described in the alternatives from those lands allocated to the Harvest Land Base (USDI 

BLM 2015, p. 102). The BLM did not constrain the modeling of timber harvest to require consistent 

acreages of particular harvest types or consistent timber volumes produced by particular harvest 

types. As a result, the amounts of thinning and regeneration harvest does change throughout the 200-

year modeling horizon. This was intentional, and there are no requirements associated with 

calculating a sustained yield that prohibit a change in the percentage of harvest type in different 

modeling periods. The fewer constraints placed on the timber harvest model, the better the model is 

able to achieve a higher estimate of volume. Placing arbitrary constraints within the Woodstock 

model to achieve even levels of thinning and regeneration harvest for the 200-year modeling horizon 

would have resulted in lower harvest volumes. 

300. Comment Summary: The DEIS fails to disclose maps of the modeled harvest.

1967 | Page

298. Comment Summary: The BLM should revise the EIS because the analysis inflated the 

productivity estimates. The Southern Oregon Forest Restoration Collaborative (SOFRC) provides a 

better estimate of productivity.

Response: As explained in the Draft RMP/EIS, the BLM used the Current Vegetation Survey (CVS) 

permanent inventory plots, and the stand-level information found in the Microstorms database to 

estimate productivity on BLM-administered lands (USDI BLM 2015, pp. 98–102, 987–1043). The 

productivity estimates used by the SOFRC in their Rogue Basin Cohesive Forest Restoration Strategy 

is based upon Gradient Nearest Neighbor (GNN) analysis. This does not provide a better estimate of 

productivity on BLM-administered lands than what the BLM used in the Draft RMP/EIS. The CVS 

inventory data provides a non-biased, impartial estimate of current inventory volume and growth on 

BLM-administered lands. The Microstorms database also provides the best available information on 

forested stands on BLM-administered lands. This database is maintained by the BLM and includes 

descriptions of the forest vegetation, forest treatments, and forest surveys through time. The GNN 

analysis is based on remotely sensed, Landsat data, which is not specific to BLM-administered lands, 

and provides much less detail. The BLM did make use of GNN analysis in innumerable analyses in 

the Draft RMP/EIS, but only on non-BLM-administered lands, where the BLM lacked data 

comparable to the CVS plots and Microstorms database (e.g., USDI BLM 2015, pp. 100, 673, 1453). 

Appendix C – Vegetation Modeling describes how the BLM used CVS and Microstorms data to 

model the forested vegetation. The BLM used many aspects of both data sets in the vegetation 

modeling. The tree lists for each modeling strata came directly from the CVS sub-plot tree lists. The 

BLM compared the growth on the first and second measurement of the permanent plots, with the 

projections from the ORGANON growth model, and found that ORGANON was adequately 

projecting growth. The productivity estimates in the harvest land base in the Draft RMP/EIS are 

similar to what the BLM has measured on the CVS plots. The BLM based the distribution of site 

productivity classes within each modeling unit (district) on the distribution of site productivity classes 

measured on the CVS plots. The productivity has not been “inflated,” as the commenter contends; it 

provides the best representation of the actual measured conditions of forests on BLM-administered 

lands. 

299. Comment Summary: AOCC is concerned about the BLM’s modeling of the alternatives to 

estimate harvest acreage and volume by different harvest types.

Response: As explained in the Draft RMP/EIS, the BLM constrained the modeling of timber harvest 

to the volume of timber that could be produced continuously for 200 years with the management 

practices described in the alternatives from those lands allocated to the Harvest Land Base (USDI 

BLM 2015, p. 102). The BLM did not constrain the modeling of timber harvest to require consistent 

acreages of particular harvest types or consistent timber volumes produced by particular harvest 

types. As a result, the amounts of thinning and regeneration harvest does change throughout the 200-

year modeling horizon. This was intentional, and there are no requirements associated with 

calculating a sustained yield that prohibit a change in the percentage of harvest type in different 

modeling periods. The fewer constraints placed on the timber harvest model, the better the model is 

able to achieve a higher estimate of volume. Placing arbitrary constraints within the Woodstock 

model to achieve even levels of thinning and regeneration harvest for the 200-year modeling horizon 

would have resulted in lower harvest volumes. 

300. Comment Summary: The DEIS fails to disclose maps of the modeled harvest.

1966 | Page

policy, the area designation of limited to existing roads and trails is an appropriate use of the 

allocation until the BLM completes an implementation-level travel management plan. 

Vegetation Modeling 
1968 | P a g e

Response: The Draft RMP/EIS did not include maps of the modeled harvest, because the modeled 

harvest locations only represent a scenario of where the future harvest would actually occur. The 

modeled harvest is one of many different scenarios of where the harvest could occur, and does not 

represent any decision in principle about the specific locations of future harvest. Although the BLM 

used spatially explicit data from modeling outputs for several analyses in the Draft RMP/EIS, spatial 

display of the modeled timber harvest locations would not improve the quality of the analysis and is 

not necessary for a reasoned choice among alternatives. 

301. Comment Summary: The Draft RMP/EIS failed to disclose the hierarchical accounting methods 

for reporting the acreage of the allocations under the alternatives.

Response: The Draft RMP/EIS described the vegetation modeling at length and in extensive detail in 

the Draft RMP/EIS, and that description summarized the information used to account for the acreage 

of the allocations under the alternatives (USDI BLM 2015, pp. 98–102, 987–1043). The Draft 

RMP/EIS did not include the specific and detailed hierarchies used in the vegetation modeling, 

because this is highly technical information that is not essential for the reader to understand the 

effects of the alternatives analyzed and is difficult to understand and interpret correctly without the 

context of all of the technical workings of the vegetation modeling. It is neither necessary nor 

practical to describe in an EIS all of the technical details for the complex vegetation modeling that the 

BLM conducted beyond the summary of that information provided in the Draft RMP/EIS. The BLM 

will provide this technical information upon request.

Wildlife 

302. Comment Summary: The scope of analysis for all wildlife species should be consistent in only 

including BLM‐administered lands.

Response: The BLM generally analyzed the effects of the alternatives on wildlife habitat and wildlife 

species at both the decision area scale (BLM-administered lands only) and at the planning area scale 

(all ownerships). The BLM analyzed the effects at both the decision area and planning area scales to 

evaluate the cumulative effects on wildlife species within the geographic scope of the effects of the 

alternatives and the Proposed RMP. For some wildlife species, data was not available across the 

entire planning area, so the analysis in the Proposed RMP/Final was limited to the decision area. 

303. Comment Summary: The State recommends the BLM use the Oregon Conservation Strategy as 

part of its planning effort, and requests the BLM address in the RMP how it will address these 

statewide key conservation issues on BLM‐administered lands consistent with the goals and actions 

described in the OCS.

Response: The BLM reviewed the conservation actions recommended in the Oregon Conservation 

Strategy against the alternatives, particularly the Proposed RMP, for consistency. The Proposed 

RMP/Final EIS has added specific discussion of consistency with the Oregon Conservation Strategy 

(see the Wildlife section of Chapter 3). 
1969 | P a g e

304. Comment Summary: Alternatives should address how wildlife corridors would be managed. 

The Middle Applegate region is the last mid‐elevation wildlife corridor in the Medford District, yet 

little discussion of migratory corridors is contained in this analysis.

Response: The Draft RMP/EIS analyzed the effects of the alternatives using the availability of 

habitat within species-specific ranges and addressed dispersal for species for which there is sufficient 

information to support analysis. Dispersal and migration of species are dependent upon speciesspecific factors, and generic wildlife corridors do not provide any basis for comparative analysis of 

the effects of the alternatives. The commenter does not identify which species’ dispersal they believe 

that the BLM did not adequately analyze in the Draft RMP/EIS. Without identifying the species, it is 

not possible to analyze the effects of the alternatives on a generic wildlife corridor. 

305. Comment Summary: The DEIS does not reflect some new species listed since 1994‐5.

Response: The Draft RMP/EIS identified all species that are listed under the Endangered Species Act 

as of the preparation of the Draft RMP/EIS. The commenter does not identify which “new species”

that they believe the BLM did not reflect in the Draft RMP/EIS. 

Bald Eagle 

306. Comment Summary: The BLM analyzes impacts to bald eagles at the entire planning level 

scale, and concludes that there will be “indistinguishable” differences between the action alternatives 

at this scale. Given that there are only approximately 250 thousand acres of nesting habitat on BLM 

lands, the BLM should be looking specifically at the impacts to these various habitat patches (older 

forest in close proximity to large waterbodies).

Response: The BLM analyzed the effects to bald eagles at both the decision area and planning area 

scales and for some of the alternatives there were only minor differences in the results. As stated in 

the Draft RMP/EIS and Proposed RMP/Final EIS, the bald eagle habitat analysis indicates that 

Alternatives A, B, and D would have less than a 5 percent difference at the decision area scale and 

less than a 1 percent difference at the planning area scale (the gross acreage difference is < 16,080 

acres). The BLM did note and discuss more meaningful differences in regards to the No Action 

alternative and Alternative C, which the commenter did not acknowledge. 

Bureau Sensitive, Bureau Strategic, Survey and Manage Species, and 

Landbird Focal Species 

307. Comment Summary: The Average Historic Condition (AHC) used as a comparison for habitat 

levels of Bureau Sensitive, Bureau Strategic, or Survey and Manage wildlife species and landbird 

focal species is based on one paper published by Nonaka and Spies in 2005. This paper’s findings 

rely completely on the results of a computer model simulation exercise that is disproven by extensive 

research done on the subject using actual historical records. The model’s outputs are essentially 

fabrications, based entirely on arbitrary modeling formulas and not actual observation. If depicting an 

AHC is necessary to the analysis in the Draft RMP/EIS, research that includes actual historic data 

should be used, rather than relying on a computer model of questionable rigor and usefulness.
1970 | P a g e

Response: The BLM used peer-reviewed, published scientific literature to provide a context for the 

habitat development in the analyses. The purpose of the analysis is to inform the BLM decisionmakers as to the relative differences in effects among the action alternatives, the No Action 

alternative, and the No Timber Harvest reference analysis. The BLM provided representations of 

average historical condition of the forest structural stage composition (e.g., Nonaka and Spies 2005, 

Wimberly 2002) to provide further context of the effects. The modeling in both Nonaka and Spies 

2005 and Wimberley 2002 provide reliable depictions across broad geographic and temporal scales of 

the range of historic forest structural conditions. These two peer-reviewed published papers rely on 

high-quality scientific information as the foundation for their modeling and provide analytical 

conclusions that are generally consistent. It is not possible to rely instead on “actual historical 

records,” as urged by the commenter, because such records are not sufficient to characterize the entire 

landscape of the decision area or planning area over broad temporal scales, which is the necessary 

analytical context that the BLM has used these papers to provide. 

308. Comment Summary: The RMP should look to integrate timber harvest objectives with 

conservation objectives, particularly for complex early seral habitat. In the Wildlife & Wildlife 

Habitat section (p. 157), relevant studies need to be included (e.g., Swanson et al. 2011; Olson et al.

2012; DellaSala et al. 2014) and the distinction between complex early seral (created by natural 

disturbances and impacted by logging) and early seral (created by forestry and in abundance due to 

logging) needs to be made clear in order to represent the best science omitted from the RMP.

Response: All alternatives and the Proposed RMP would increase the amount of early successional 

forest habitat in 50 years and the BLM recognizes the distinction between complex and simple early 

seral forest habitats. The structural stages used throughout the analyses in the Proposed RMP/Final 

EIS have two categories of early seral habitat: Early Successional Forests with Structural Legacies 

and Early Successional Forest without Structural Legacy. The BLM regards Early Successional Forest 

with Structural Legacies as analogous to complex early successional habitat as described by DellaSala 

et al. (2014) and Swanson et al. (2011). In addition, management direction regarding green tree 

retention, snag retention (or creation), and down woody material retention would add to the 

complexity of that early successional habitat. The BLM has reviewed the suggested literature and 

added these citations and discussion of the differences in complex early successional habitat 

development in terms of young stands that do (or do not) have structural legacies to the Proposed 

RMP/Final EIS (see Wildlife section of Chapter 3). The BLM has integrated timber harvest objectives 

with conservation objectives in the design of the action alternatives and the Proposed RMP with 

varying approaches. Specifically, the BLM has incorporated regeneration harvest with varying levels 

and patterns of retention and uneven-aged management approaches into several action alternatives 

and into the Proposed RMP, which would create complex early seral habitats. 

309. Comment Summary: Stream restoration can destroy or prevent the development of open 

habitats that provide turtle nesting habitat as well as sunny areas within the stream environment to 

allow for foraging and basking. The western pond turtle requires aquatic habitat for feeding/basking 

and open upland habitat for nesting/overwintering. 

Response: Under all alternatives, the BLM would manage naturally occurring special habitats, such 

as wetlands and natural ponds, to maintain their ecological function. Additionally, stream restoration 

would benefit pond turtle habitat. Stream restoration actions, such as log and boulder placement and 

fish passage improvements that are beneficial to fish habitat, would also result in short-term increases 

in sediment delivery to stream channels. Removal of culverts and other instream structures like 
1971 | P a g e

blockages would cause stream channel disturbance during summer instream operating periods. The 

addition of structure to stream channels would create additional pools and slow-flowing, shallow 

areas that would be favorable for pond turtles. 

310. Comment Summary: Page 680 of the DEIS indicates that the BLM intends to rely upon 

projected increases in hypothetical habitat for Bureau Sensitive Species (BSS) and (former) Survey 

and Manage species rather than protecting the actual known sites where these species occur. Trading 

occupied actual habitat for hypothetical future habitat is arbitrary and capricious.

Response: The action alternatives would remove Survey and Manage measures, which require predisturbance surveys and protection of known sites. Even in the absence of such measures, habitat and 

sites of Survey and Manage species that fall within the reserve system would generally be protected 

by the management direction of the reserve land use allocations, which would generally protect 

existing Mature and Structurally-complex Forest habitat and foster the development of additional 

Mature and Structurally-complex Forest habitat. Under the No Action alternative, 36 percent of 

known sites of Survey and Manage wildlife species would fall within the reserve system. Under the 

action alternatives and the Proposed RMP, the proportion of sites that would fall within the reserve 

systems would increase substantially: 86 percent under Alternative A, 68 percent under Alternative B, 

66 percent under Alternative C, 70 percent under Alternative D, and 73 percent under the Proposed 

RMP. Thus, the majority of “actual known sites” for Survey and Manage wildlife species would 

continue to be protected under the action alternatives and the Proposed RMP, even without the 

Survey and Manage measures. Even in the absence of the Survey and Manage measure, habitat and 

sites of species that fall within the reserve system would receive some protection. Not all sites within 

reserve land use allocations would necessarily be protected by buffers comparable to the No Action 

alternative. However, management actions in reserves could occur within these sites, but there would 

be a minimal effect to the species based on the type and intensity of allowable treatments. Under all 

action alternatives and the Proposed RMP, management direction in reserves would largely limit 

stand treatments to thinning to improve habitat conditions and fuels treatments to reduce the risk of 

uncharacteristic wildfire, and would generally preclude stand treatments that would remove or 

degrade Mature and Structurally-complex habitat (Appendix B – Management Objectives and 

Direction).

Under the action alternatives, the amount of existing Mature or Structurally-complex Forest habitat 

within the reserve network would increase (from 65 percent under the No Action Alternative to at 

least 72 percent). The Proposed RMP would reserve 83 percent of existing Mature or Structurallycomplex Forest habitat, while only 65 percent is reserved under the No Action alternation. Therefore, 

despite the absence of Survey and Manage measures, more habitat for species associated with older 

forests would be reserved and protected under the Proposed RMP than under the No Action 

alternative. 

In addition to reserving existing older and more structurally-complex, multi-layered conifer forests, 

the acreage of Mature and Structurally-complex Forest (which is a broader category than older and 

more structurally-complex multi-layered conifer forests) in the decision area would increase over 

time under all alternatives. Therefore, the amount of habitat for Survey and Manage wildlife species 

would also increase under all alternatives. 

The BLM does not agree that omitting the Survey and Manage measures from the Proposed RMP is 

arbitrary and capricious. The BLM considers the increased habitat protection and habitat development 

under the Proposed RMP to be a sound management approach for these species. The Proposed RMP 

would protect the majority of the “actual known sites” of Survey and Manage wildlife species, would 
1972 | P a g e

reserve more of the potential habitat for Survey and Manage species than the No Action alternative, 

and would provide a greater increase in the amount of potential habitat for Survey and Manage 

species over time than the No Action alternative. Finally, under the Proposed RMP, the BLM would 

continue to provide management for many of the Survey and Manage species as Bureau Sensitive 

species. The Draft RMP/EIS analyzed the effects of the alternatives on Survey and Manage species, 

and the BLM used that analysis in the development of the Proposed RMP (see the Rare Plants and 

Fungi and Wildlife sections of Chapter 3). 

311. Comment Summary: The RMP must provide more detail and clarification of a monitoring and 

evaluation strategy to determine if protection objectives for Survey and Manage species are being 

achieved during implementation.

Response: Monitoring provides information to determine whether the BLM is following the RMP 

management direction (implementation monitoring) and to verify if the implementation of the RMP is 

achieving plan-level desired results (effectiveness monitoring). The monitoring plan included in the 

Proposed RMP/Final EIS include implementation monitoring questions related to Bureau Special 

Status Species, and the BLM would continue to rely on the existing interagency effectiveness 

monitoring modules to address key questions about whether the RMP is effectively meeting its 

objectives, including the module for late-successional and old growth ecosystems (Appendix V –

Monitoring Plan for the Proposed RMPs). 

The BLM does not agree that the monitoring plan should directly address Survey and Manage 

species, because the Proposed RMP does not have “protection objectives” for Survey and Manage 

species. Given that there is no management direction for Survey and Manage species in the Proposed 

RMP, there is no need to address Survey and Manage species in implementation monitoring. Given 

that there are no management objectives for Survey and Manage species in the Proposed RMP, there 

is no need to address Survey and Manage species in effectiveness monitoring. 

312. Comment Summary: The BLM’s draft RMP for Western Oregon does away with a biologically‐

driven snag retention standard, replacing it with draft standards that treat existing and newly created 

snags as interchangeable, and averages the snag density standards across the “scale of the harvest 

unit” which could be hundreds, if not thousands, of acres.

Response: The alternatives in the Draft RMP/EIS explored a variety of snag retention and creation 

requirements. Alternative A did not include any snag retention or creation targets. Alternative C 

included targets for snag retention or creation in the reserve network similar to those used in the 2008 

FEIS. Alternatives B and D included snag retention and creation targets based on the desired 

conditions for wildlife species as interpreted from the Decayed Wood Advisor (DecAID) (MellenMcLean et al. 2012) in conjunction with estimates of the current abundance of snags and down wood 

from the CVS inventory plots (see the Snags and Down Woody Material section of Appendix S –

Other Wildlife). The BLM maintains that the information from DecAID and CVS inventory plots 

provides information that better reflects the needs of snag-dependent species than the snag retention 

requirements in the 1995 RMPs. The Proposed RMP includes the snag retention and creation targets 

similar to Alternatives B and D. 

The action alternatives do not “treat existing and newly created snags as interchangeable,” contrary to 

the commenter’s assertion. The management direction for Alternatives B and D clearly requires the 

retention of existing snags and separately requires the creation of new snags, independent of the 
1973 | P a g e

amount of existing snags (USDI BLM 2015, pp. 962, 984). The Proposed RMP includes the snag 

retention and creation targets similar to Alternatives B and D. 

In addition, while the management direction for the Proposed RMP directs snag densities at the scale 

of the harvest unit, the commenter’s assertion that harvest units could be “hundreds, if not thousands, 

of acres” is erroneous. Given the typical checkerboard of BLM-administered lands, much of the 

BLM-administered lands occur in square mile sections (640 acres), which are themselves composed 

of a myriad of stand types further intertwined with the Riparian Reserve and other land-use 

allocations. Such practical considerations of land ownership and land use allocations necessarily limit 

timber harvest unit sizes. The output form vegetation modeling for the analysis in this Proposed 

RMP/Final EIS (Appendix C – Vegetation Modeling) indicated that more than 99 percent of 

regeneration harvest units in the first decade of implementation would be less than 100 acres in size, 

and all regeneration harvest units would be less than 250 acres in size. Therefore, there is little 

prospect of BLM implementing extremely large harvest units under any alternative or the Proposed 

RMP. Regardless, the commenter does not explain how providing snags at densities averaged over 

entire harvest units would adversely affect any resources in a manner not addressed in the Draft 

RMP/EIS. 

Deer and Elk 

313. Comment Summary: The DEIS attributes reductions in deer and elk populations to reductions in 

timber harvest levels without considering other factors which may be causing the population declines.

Response: As stated in the Draft RMP/EIS, the Oregon Department of Fish and Wildlife identifies 

availability of early successional forest stages as a potential limiting factor (USDI BLM 2015, 

p. 676). The Proposed RMP/Final EIS has added additional discussion regarding potential sources of 

deer and elk population declines. 

Fisher 

314. Comment Summary: Landscape scale spatially explicit analysis is needed in this RMP process 

to identify critical habitat for fishers for protection and enhancement of key elements.

Response: The Draft RMP/EIS included management direction common to all action alternatives that 

would provide some protection for key elements of fisher habitat (denning structures). The Proposed 

RMP has included additional management direction that would provide protection and enhancement 

of key elements for fisher as well (denning structures and canopy cover) and would avoid disruption 

of normal denning behaviors (Appendix B – Management Objectives and Direction).

315. Comment Summary: The Pacific fisher will be impacted by increased regeneration harvesting, 

increased commercial thinning, decreased riparian buffers, abandonment of the ACS, and increased 

road building proposed in the DEIS. This impact was not adequately analyzed in the DEIS document. 

A detailed analysis of the Pacific fisher, its population, viability, and conservation status under 

different alternatives is needed in the FEIS.
1974 | P a g e

Response: The Draft RMP/EIS conducted a detailed and quantified analysis of the effects of the 

alternatives on fisher habitat. The Proposed RMP/Final EIS has added quantified forecasts of impacts 

to the fisher population in southwestern Oregon. The fisher habitat modeling used the vegetation 

modeling output, which incorporated changes in vegetation over time under the alternatives from 

integrating the effects of timber harvest, wildfire, and forest growth. Therefore, the BLM reflected 

changes in harvest or buffer regimes in the habitat modeling results presented in Chapter 3. 

316. Comment Summary: The State recommends that the BLM identify barriers to dispersal, and 

plan habitat restoration to ensure connectivity and terrestrial corridors for fisher in the RMP.

Response: The Draft RMP/EIS did not identify barriers to fisher dispersal, because the BLM does not 

regard dispersal as a limiting factor for fisher. Fishers have a large home range size (males 13,329 

acres; females 4,692 acres) and the ability to disperse long distances (males disperse an average of 

18.0 miles; females disperse an average of 3.7 miles). Dispersing juvenile fisher are capable of 

moving long distances (up to 84 miles) and navigating across or around various landscape features, 

including rivers, highways, and rural communities. The BLM contends that availability of denning 

habitat and denning structures are more limited and have a more important influence on fisher than 

dispersal. 

317. Comment Summary: The RMP fails to restrict OHV use in areas of denning fishers.

Response: The commenter is mistaken. The action alternatives and the Proposed RMP would restrict 

all management actions that would disturb denning fishers. All action alternatives included 

management direction that would restrict activities that create noise or visual disturbance(s) above 

ambient conditions within 0.5 miles of known fisher natal and maternal den sites from February 1 to 

June 30 (USDI BLM 2015, p. 937). The Proposed RMP includes management direction that the BLM 

would not approve, fund, or carry out actions that would disrupt normal fisher behaviors (e.g., 

foraging, resting, or denning) associated with known natal or maternal denning sites except when 

done in accordance with an approved recovery plan, conservation agreement, species management 

plan, survey and monitoring protocol, or critical habitat rule and the action is necessary for the 

conservation of the species (Appendix B – Management Objectives and Direction). In areas allocated 

as limited for public motorized access, the BLM would consider specific restrictions on OHV use 

near fisher den sites during implementation-level travel management planning (Appendix Q – Public 

Motorized Access Designation Guidelines).

Golden Eagle 

318. Comment Summary: Every action alternative includes more acres designated for ORV use 

while no analysis or data is provided regarding actual impacts to golden eagle populations and 

behavior.

Response: The commenter is mistaken. All action alternatives and the Proposed RMP would 

eliminate areas open to public motorized vehicle use and increase the areas closed to public motorized 

vehicle use (USDI BLM 2015, p. 639). In addition, all action alternatives and the Proposed RMP 

include management direction that would prohibit activities that will disrupt nesting where bald 

eagles or golden eagles are actively nesting common to all alternatives (Appendix B – Management 

Objectives and Direction). All action alternatives and the Proposed RMP would also prohibit 
1975 | P a g e

operation of off-road vehicles within 330 feet of bald eagle or golden eagle nests during the breeding 

season under the action alternatives. Finally, all action alternatives and the Proposed RMP would 

prohibit operation of off-road vehicles within 660 feet of bald eagle or golden eagle nests during the 

breeding season in areas without forest cover or topographic relief to provide visual and auditory 

screening (USDI BLM 2015, p. 936; Appendix B – Management Objectives and Direction). The 

commenter does not explain how public motorized vehicle use could affect golden eagle populations 

in light of these prohibitions. 

Greater Sage-Grouse 

319. Comment Summary: The RMP needs to identify conservation measures in greater sage‐grouse 

habitat.

Response: All action alternatives included the conservation measure to manage unoccupied or 

historic sage grouse habitat consistent with the Oregon Sage-Grouse Action Plan (USDI BLM 2015, 

p. 913). The Proposed RMP has also included conservation measures to cut junipers encroaching on 

unoccupied or historic sage-grouse habitat and to plant native species to improve unoccupied or 

historic sage-grouse habitat (Appendix B – Management Objectives and Direction).

Gray Wolf 

320. Comment Summary: In an effort to most effectively contribute to the conservation and recovery 

of the gray wolf (Canis lupus), the Service would like the BLM to begin its seasonal restriction within 

one mile of an active den on April 1st instead of April 30th. The Service believes that extending this 

restriction to July 15 (as opposed to August 31) would be sufficient to protect the young of the year as 

they are likely to have left their den sites by then.

Response: The Proposed RMP has added management direction restricting activities that create noise 

or visual disturbance(s) above ambient conditions within one mile of known active gray wolf dens 

from April 1 to July 15, consistent with the commenter’s suggestion (Appendix B – Management 

Objectives and Direction). 

321. Comment Summary: The DEIS fails to analyze impacts to wolf from road densities and road 

construction, grazing, and project activities associated with timber harvest. The BLM needs to 

develop standards to ensure that road densities in the forests it manages remain below road densities 

over 1 mile per square mile or manage areas over this road density to prevent any new temporary or 

permanent road construction.

Response: The Proposed RMP/Final EIS includes additional discussion and analysis regarding road 

density and gray wolves (see the Wildlife section in Chapter 3). 

The BLM does not agree that a road-density threshold of 1 mile per square mile is needed for wolf 

conservation. Increased land development (e.g., road development) has the potential to make some 

areas less suitable for wolf occupancy. However, it is unlikely that increased land development in the 

planning area would, in fact, adversely affect wolves. Wolves are habitat generalists and one of the 

most adaptable large predators in the world. They were extirpated in the southern portion of the 
1976 | P a g e

subspecies’ range only because of sustained, deliberate, human-targeted elimination. Land-use 

restrictions on land development are not necessary to ensure the continued conservation of the 

subspecies; even active wolf dens can be quite resilient to nonlethal disturbance by humans. Vast 

areas of suitable wolf habitat and the current wolf population are secure in the subspecies’ range (e.g., 

national parks, wilderness, road-less areas) and are not available for intensive levels of land 

development (78 FR 35681). 

In addition, current road densities on BLM-administered lands are 3.70 miles per square mile (see the 

Trails and Travel Management section of Chapter 3). Given that wolves are actively colonizing and 

establishing packs in areas with an existing road density of 3.70 miles/sq. mile (as evidenced by the 

Rogue pack and Keno pair), the BLM concludes that wolves in the planning area are resilient to road 

densities at current levels. 

Marbled Murrelet 

322. Comment Summary: The State recommends the BLM analyze the number of known or historic 

occupied marbled murrelet sites within 0.25 miles of adjoining private lands to determine the 

potential impact to occupied marbled murrelet sites that span property boundaries and the potential 

impact to timber volume output.

Response: The Draft RMP/EIS identified known and historic marbled murrelet sites (USDI BLM 

2015, pp. 732–733). Segregating these sites by proximity to private lands would not improve the 

quality of the analysis or provide for a reasoned choice among the alternatives. The BLM has no 

reasonable way to predict the management actions private landowners would take in response to 

marbled murrelet sites on BLM-administered lands or estimate whether there would be any effects of 

marbled murrelet sites on BLM-administered lands on the timber volume production of adjacent 

landowners. 

323. Comment Summary: The conservation strategy for marbled murrelets should include protecting 

remaining large patches of older‐aged forests with minimal edge, buffering nest sites from windthrow 

and predators, and maintaining habitat connectivity. The system of LSRs on BLM lands continues to 

be critical to murrelet conservation. The watershed, juxtaposition of occupied murrelet habitat, and 

ownership should all be considered in thinning operations within LSRs or adjacent to older‐aged 

forest.

Response: The BLM would protect all older, more structurally-complex forest through the 

designation of such stands as Late-Successional Reserve, which would benefit marbled murrelets. 

The BLM analyzed the effects of the alternatives on patch size of marbled murrelet nesting habitat 

and discussed the effects of smaller or larger patches on marbled murrelets in Chapter 3. 

324. Comment Summary: Does BLM have data to support its claim on p. 150 that when sufficient 

habitat is present the marbled murrelet population still declines? How can BLM conclude this when 

nearly all habitat (80%) was eliminated on public lands prior to the NWFP?

Response: The commenter mischaracterizes the statement in the Draft RMP/EIS. The Draft RMP/EIS 

did not claim that when sufficient habitat is present, the marbled murrelet population still declines. 

The Draft RMP/EIS stated that even when sufficient high-quality nesting habitat is available, other 
1977 | P a g e

factors (i.e., climate events and climate change) can influence murrelet populations (either positively 

or negatively) by affecting conditions important for prey species (USDI BLM 2015, p. 150). The 

Draft RMP/EIS detailed the variety of the factors affecting marbled murrelet populations, which 

include loss of nesting habitat, but also non-habitat factors. Specifically citing the U.S. Fish and 

Wildlife Service 2009 review, the Draft RMP/EIS identified that changes in prey abundance and 

availability and climate change are among the threats to the marbled murrelet population (USDI BLM 

2015, pp. 720–721). The Draft RMP/EIS acknowledged that there is a strong association between 

total marbled murrelet populations and the total amount of suitable habitat. Nevertheless, there are 

other factors besides habitat affecting marbled murrelet populations. Thus, the BLM maintains that 

even when sufficient high-quality nesting habitat is available, other factors can influence murrelet 

populations. The commenter offers no evidence to dispute this point. 

325. Comment Summary: Alternatives fail to include all of the conservation measures necessary to 

provide for the survival and recovery of Marbled Murrelet populations (e.g., protect all current 

occupied sites on Federal land, protect habitat within 55 miles of the coast, survey habitat within 55 

miles of the coast, and maintain NWFP LSRs).

Response: The Draft RMP/EIS analyzed a range of strategies to contribute to the conservation and 

recovery of marbled murrelets. 

Under the No Action alternative, Alternatives A, B, and D, and the Proposed RMP, the BLM would 

protect all current occupied marbled murrelet sites (USDI BLM 2015, pp. 733–737; see the Wildlife 

section of Chapter 3). 

The BLM does not agree that surveying and protecting all habitat within 55 miles of the coast is 

necessary for the survival and recovery of the marbled murrelet. As explained in the Draft RMP/EIS, 

the BLM describes the inland range of the marbled murrelet based on the two management zones for 

the marbled murrelet established in the Northwest Forest Plan: Zone 1 from the coast to 

approximately 35 miles inland, and Zone 2 from the eastern boundary of Zone 1 to approximately 50 

miles inland from the coast. Marbled murrelet nesting has been documented only up to 47 miles from 

the coast in Oregon. Therefore, the BLM considers the effects to marbled murrelets and their habitat 

within 50 miles of the coast as the appropriate geographic scope. The commenter does not provide 

any evidence that habitat beyond 50 miles from the coast is used by marbled murrelets in the planning 

area. 

The No Action alternative and Alternative D would require surveys and protection of occupied sites 

throughout the marbled murrelet range. Alternative B would require surveys and protection of 

occupied sites in Zone 1, but not in Zone 2. Alternatives A and C would not require surveys and 

protection of occupied sites. The Draft RMP/EIS analyzed the effects of these different approaches 

and projected the potential loss of future occupied sites under each alternative. That analysis 

concluded that the approach in Alternative B would result in the loss of relatively few marbled 

murrelet sites (USDI BLM 2015, pp. 730–736). The BLM developed the Proposed RMP approach to 

marbled murrelet management similar to the approach of Alternative B based on the results of that 

analysis. The commenter does not dispute the accuracy of this analysis. The BLM has updated that 

analysis in the Proposed RMP/Final EIS based on additional information, but the basic analytical 

conclusions about the effects of different marbled murrelet survey and site protection measures 

remain unchanged (see the Wildlife section of Chapter 3). 

The BLM does not agree that maintaining the Northwest Forest Plan Late-Successional Reserve is 

necessary for the survival and recovery of the marbled murrelet. Under all action alternatives, 
1978 | Page

including the Proposed RMP, the Late-Successional Reserve is larger than under the No Action 

alternative (i.e., the Northwest Forest Plan), providing increased benefits to the marbled murrelets. 

The commenter does not explain how maintaining the smaller Late-Successional Reserve under the 

No Action alternative would better contribute to the conservation and recovery of the marbled 

murrelet. Under all action alternatives and the Proposed RMP, more of the current marbled murrelet 

nesting habitat would be within reserve land use allocations than under the No Action alternative. 

Under Alternatives A, B, and D, and the Proposed RMP, the amount of high-quality marbled murrelet 

nesting habitat would increase more than under the No Action alternative (USDI BLM 2015, pp. 726, 

734; see the Wildlife section of Chapter 3). 

The BLM contends that the Proposed RMP would better contribute to the conservation and recovery 

of the marbled murrelet than the No Action alternative, because the Proposed RMP would provide a 

larger Late-Successional Reserve, would reserve more marbled murrelet nesting habitat, and would 

result in a larger increase in high-quality marbled murrelet nesting habitat over time. 

326. Comment Summary: The Preferred Alternative states there will be no disruption to murrelets. 

FWS would like to see it state that no disruption would apply to both known and predicted murrelet 

sites.

Response: The Proposed RMP and Alternative B would restrict activities that disrupt marbled 

murrelet nesting during the nesting period where marbled murrelets are currently nesting. This 

restriction would apply to all sites where marbled murrelets are nesting, including both currently 

known sites and sites that the BLM identifies in the future, consistent with the commenter’s 

suggestion. 

327. Comment Summary: Increased clearcutting within Riparian Reserve is in direct conflict with 

FWS’ 1997 Recovery Plan for the Marbled Murrelet, which recommends that mature forests within 

“secured areas” (such as Riparian Reserve) be protected so they can serve as future nesting habitat for 

the marbled murrelet.

Response: The commenter is mistaken: none of the alternatives would include clearcutting within 

Riparian Reserve. Under all alternatives and the Proposed RMP, the only timber harvest within the 

Riparian Reserve would be thinning in some portions of the Riparian Reserve for some specific 

restoration purposes. Clearcutting is a component of the Harvest Land Base under Alternatives A and 

C; all other alternatives, including the Proposed RMP, would employ regeneration harvest with 

varying levels of stand retention (see the Forest Management section of Chapter 3). Furthermore, 

more of the current marbled murrelet nesting habitat would be within reserve land use allocations 

under the action alternatives and the Proposed RMP compared to the No Action alternative. As a 

result, regardless of the distinction between clearcutting and regeneration harvest with retention, 

several of the action alternatives and the Proposed RMP would result in less timber harvest of 

marbled murrelet nesting habitat across the landscape compared to the No Action alternative (see the 

Wildlife section of Chapter 3). 

North Oregon Coast Distinct Population Segment of the Red Tree 

Vole
1979 | Page

328. Comment Summary: Pages 738 and 744 of the DEIS indicate that Alternatives A and C would 

negatively affect the red tree vole by logging 136 of 383 known sites. Given the acknowledgment that 

“every RTV site in the NOCDPS is critical for persistence” of the species, the contention on page 744 

that the BLM is unsure if such logging would contribute to the need to list the species under the ESA 

is in error.

Response: The statement “Since every red tree vole site in the North Oregon Coast DPS is critical for 

persistence ...” in the Draft RMP/EIS was in error. The BLM could not support that statement given 

the uncertainties around population numbers, trend, and distribution of the North Oregon Coast DPS 

of the red tree vole. The Proposed RMP/Final EIS has deleted this statement. The Proposed 

RMP/Final EIS has updated the discussion of the effects for the North Oregon Coast DPS of the red 

tree vole. Because the population status or population trend of red tree voles in the North Oregon 

Coast DPS is unknown, it is also unknown the extent to which loss of occupied stands would 

negatively affect the population of red tree voles in the North Oregon Coast DPS. In any event, the 

Proposed RMP would include direction to conduct pre-disturbance surveys and known site 

management (habitat areas) for red tree voles in the North Oregon Coast DPS north of Highway 20 

and known site management south of Highway 20 within the reserves.

329. Comment Summary: Analysis of effects to red tree vole does not consider number of sites 

affected or genetic connectedness.

Response: The commenter is mistaken; the Draft RMP/EIS did address the number of sites affected 

and population connectivity. The Draft RMP/EIS considered observations (one measure of the 

number of sites) of red tree voles within the North Oregon Coast DPS. The Draft RMP/EIS included a 

tabulation of the number of observations by land use allocation and forecast the number of future red 

tree vole sites that would be identified and protected under the alternatives. Finally, the Draft 

RMP/EIS included a discussion of the effects of different management approaches on the North 

Oregon Coast DPS of the red tree vole, including how the loss of sites under some alternatives would 

affect population interaction and connectivity in the North Oregon Coast DPS (USDI BLM 2015, pp. 

738–745). 

330. Comment Summary: FWS strongly recommends that, within the North Oregon Coast Distinct 

Population Segment of the red tree vole, BLM carry forward into their RMP the existing management 

that they are doing for the red tree vole under the Survey and Manage standards and guidelines of the 

NWFP.

Response: The No Action alternative and Alternatives B and D would include direction to conduct 

pre-disturbance surveys and known site management (habitat areas) for red tree voles in the North 

Oregon Coast DPS. The Proposed RMP would include direction to conduct pre-disturbance surveys 

and known site management (habitat areas) for red tree voles in the North Oregon Coast DPS north of 

Highway 20 and known site management south of Highway 20 within the reserves. Surveys and 

known site management are some of the primary components of the Survey and Manage measures 

(Appendix B – Management Objectives and Direction).

Northern Spotted Owl 

1978 | Page

p

marbled murrelet nesting habitat across the landscape compared to the No Action alternative (see the 

Wildlife section of Chapter 3). 

North Oregon Coast Distinct Population Segment of the Red Tree 

Vole 

1979 | Page

328. Comment Summary: Pages 738 and 744 of the DEIS indicate that Alternatives A and C would 

negatively affect the red tree vole by logging 136 of 383 known sites. Given the acknowledgment that 

“every RTV site in the NOCDPS is critical for persistence” of the species, the contention on page 744 

that the BLM is unsure if such logging would contribute to the need to list the species under the ESA 

is in error.

Response: The statement “Since every red tree vole site in the North Oregon Coast DPS is critical for 

persistence ...” in the Draft RMP/EIS was in error. The BLM could not support that statement given 

the uncertainties around population numbers, trend, and distribution of the North Oregon Coast DPS 

of the red tree vole. The Proposed RMP/Final EIS has deleted this statement. The Proposed 

RMP/Final EIS has updated the discussion of the effects for the North Oregon Coast DPS of the red 

tree vole. Because the population status or population trend of red tree voles in the North Oregon 

Coast DPS is unknown, it is also unknown the extent to which loss of occupied stands would 

negatively affect the population of red tree voles in the North Oregon Coast DPS. In any event, the 

Proposed RMP would include direction to conduct pre-disturbance surveys and known site 

management (habitat areas) for red tree voles in the North Oregon Coast DPS north of Highway 20 

and known site management south of Highway 20 within the reserves.

329. Comment Summary: Analysis of effects to red tree vole does not consider number of sites 

affected or genetic connectedness.

Response: The commenter is mistaken; the Draft RMP/EIS did address the number of sites affected 

and population connectivity. The Draft RMP/EIS considered observations (one measure of the 

number of sites) of red tree voles within the North Oregon Coast DPS. The Draft RMP/EIS included a 

tabulation of the number of observations by land use allocation and forecast the number of future red 

tree vole sites that would be identified and protected under the alternatives. Finally, the Draft 

RMP/EIS included a discussion of the effects of different management approaches on the North 

Oregon Coast DPS of the red tree vole, including how the loss of sites under some alternatives would 

affect population interaction and connectivity in the North Oregon Coast DPS (USDI BLM 2015, pp. 

738–745). 

330. Comment Summary: FWS strongly recommends that, within the North Oregon Coast Distinct 

Population Segment of the red tree vole, BLM carry forward into their RMP the existing management 

that they are doing for the red tree vole under the Survey and Manage standards and guidelines of the 

NWFP.

Response: The No Action alternative and Alternatives B and D would include direction to conduct 

pre-disturbance surveys and known site management (habitat areas) for red tree voles in the North 

Oregon Coast DPS. The Proposed RMP would include direction to conduct pre-disturbance surveys 

and known site management (habitat areas) for red tree voles in the North Oregon Coast DPS north of 

Highway 20 and known site management south of Highway 20 within the reserves. Surveys and 

known site management are some of the primary components of the Survey and Manage measures 

(Appendix B – Management Objectives and Direction).

Northern Spotted Owl 
1980 | Page

331. Comment Summary: The BLM should include the 2014 northern spotted owl demographic 

meta‐analysis and individual demographic study area annual reports in its analysis.

Response: The commenter appears to confuse the northern spotted owl portion of the Northwest 

Forest Plan 20-year monitoring report (Davis et al. 2015), which was released in draft form, with the 

newest northern spotted owl meta-analysis, which has not yet been released at the time of the 

preparation of the Proposed RMP/Final EIS. The lead author of the new meta-analysis, Dr. Katie 

Dugger, Oregon State University, provided the BLM with meta-analytical results pertaining to 

northern spotted owl populations in the eight Federal demographic study areas, northern spotted owl 

survival and fecundity rates, and barred owl encounter rates. The Proposed RMP/Final EIS has 

updated its northern spotted owl models using those results, as appropriate. The BLM does not use 

the annual results from individual demographic study areas, because they are not analytically credible 

due to their sample sizes; hence, the need for a meta-analysis about every 5 years. 

332. Comment Summary: It makes no sense to manage for northern spotted owl habitat when there 

are other factors affecting northern spotted owl survival. Establishment of large, contiguous blocks of 

late‐successional forest has been shown to not provide any benefit to the conservation of the spotted 

owl due to the overwhelming presence and competition from the barred owl.

Response: Complex problems, such as northern spotted owl recovery, commonly require multiple, 

collaborative solutions. The Draft RMP/EIS demonstrated that habitat management alone would not 

be sufficient for conservation and recovery of the northern spotted owl, but habitat management 

remains a necessary component of northern spotted owl conservation and recovery (USDI BLM 

2015, pp. 746–826). As detailed in the Draft RMP/EIS, the U.S. Fish and Wildlife Service identified 

in the revised recovery plan for the northern spotted owl the continuing need for habitat management 

and also acknowledged the effects of competitive interactions between northern spotted owls and 

barred owls and outlined a strategy to address the barred owl. Thus, the BLM, as recommended by 

the Service’s recovery plan, is addressing the habitat component of northern spotted owl recovery. In 

addition, the Draft RMP/EIS identified a potential mitigation measure of BLM participation in a 

future barred owl management program and analyzed the effectiveness of such a mitigation measure 

(USDI BLM 2015, pp. 40, 778–780). The Proposed RMP has incorporated this mitigation measure 

and has added management direction related to “take” of northern spotted owls (see Chapter 2). 

Therefore, the Proposed RMP includes management of northern spotted owl habitat, management of 

northern spotted owls, and future management of barred owls, all of which are necessary components 

of northern spotted owl conservation and recovery. 

333. Comment Summary: “The RMP ignores the checkerboard character of the majority of the O&C 

lands” and managing for contiguous northern spotted owl habitat is futile because of the checkerboard 

BLM ownership.

Response: The Draft RMP/EIS evaluated northern spotted owl habitat conditions on all land 

ownerships, and the results of that analysis clearly demonstrate that the commenter’s claims are 

incorrect. The Draft RMP/EIS forecasted habitat changes on all land ownerships within the United 

States’ portion of the northern spotted owl’s range and determined that BLM-administered lands in 

the checkerboard ownership are capable of contributing to large habitat blocks of northern spotted 

owl nesting-roosting habitat and to northern spotted owl movement and survival between and through 

the large blocks (USDI BLM 2015, pp. 746–774). The commenter identifies no error in that analysis. 

1980 | Page

331. Comment Summary: The BLM should include the 2014 northern spotted owl demographic 

meta‐analysis and individual demographic study area annual reports in its analysis.

Response: The commenter appears to confuse the northern spotted owl portion of the Northwest 

Forest Plan 20-year monitoring report (Davis et al. 2015), which was released in draft form, with the 

newest northern spotted owl meta-analysis, which has not yet been released at the time of the 

preparation of the Proposed RMP/Final EIS. The lead author of the new meta-analysis, Dr. Katie 

Dugger, Oregon State University, provided the BLM with meta-analytical results pertaining to 

northern spotted owl populations in the eight Federal demographic study areas, northern spotted owl 

survival and fecundity rates, and barred owl encounter rates. The Proposed RMP/Final EIS has 

updated its northern spotted owl models using those results, as appropriate. The BLM does not use 

the annual results from individual demographic study areas, because they are not analytically credible 

due to their sample sizes; hence, the need for a meta-analysis about every 5 years. 

332. Comment Summary: It makes no sense to manage for northern spotted owl habitat when there 

are other factors affecting northern spotted owl survival. Establishment of large, contiguous blocks of 

late‐successional forest has been shown to not provide any benefit to the conservation of the spotted 

owl due to the overwhelming presence and competition from the barred owl.

Response: Complex problems, such as northern spotted owl recovery, commonly require multiple, 

collaborative solutions. The Draft RMP/EIS demonstrated that habitat management alone would not 

be sufficient for conservation and recovery of the northern spotted owl, but habitat management 

remains a necessary component of northern spotted owl conservation and recovery (USDI BLM 

2015, pp. 746–826). As detailed in the Draft RMP/EIS, the U.S. Fish and Wildlife Service identified 

in the revised recovery plan for the northern spotted owl the continuing need for habitat management 

and also acknowledged the effects of competitive interactions between northern spotted owls and 

barred owls and outlined a strategy to address the barred owl. Thus, the BLM, as recommended by 

the Service’s recovery plan, is addressing the habitat component of northern spotted owl recovery. In 

addition, the Draft RMP/EIS identified a potential mitigation measure of BLM participation in a 

future barred owl management program and analyzed the effectiveness of such a mitigation measure 

(USDI BLM 2015, pp. 40, 778–780). The Proposed RMP has incorporated this mitigation measure 

and has added management direction related to “take” of northern spotted owls (see Chapter 2). 

Therefore, the Proposed RMP includes management of northern spotted owl habitat, management of 

northern spotted owls, and future management of barred owls, all of which are necessary components 

of northern spotted owl conservation and recovery. 

333. Comment Summary: “The RMP ignores the checkerboard character of the majority of the O&C 

lands” and managing for contiguous northern spotted owl habitat is futile because of the checkerboard 

BLM ownership.

Response: The Draft RMP/EIS evaluated northern spotted owl habitat conditions on all land 

ownerships, and the results of that analysis clearly demonstrate that the commenter’s claims are 

incorrect. The Draft RMP/EIS forecasted habitat changes on all land ownerships within the United 

States’ portion of the northern spotted owl’s range and determined that BLM-administered lands in 

the checkerboard ownership are capable of contributing to large habitat blocks of northern spotted 

owl nesting-roosting habitat and to northern spotted owl movement and survival between and through 

the large blocks (USDI BLM 2015, pp. 746–774). The commenter identifies no error in that analysis. 

1979 | Page

Highway 20 and known site management south of Highway 20 within the reserves. Surveys and 

known site management are some of the primary components of the Survey and Manage measures 

(Appendix B – Management Objectives and Direction).

Northern Spotted Owl 
1981 | P a g e

334. Comment Summary: The northern spotted owl analyses are missing important information such 

as northern spotted owl migratory habits, the effects of reduced harvest levels under the Northwest 

Forest Plan on barred owl abundance and competition with northern spotted owls, and interbreeding 

by the two species.

Response: The BLM presumes that the commenter confused east-west connectivity between the 

Oregon Cascades and Coast Range with northern spotted owl migration. The BLM correctly 

characterized east-west connectivity as pertaining to northern spotted owl dispersal across the 

landscape by individual owls looking for mates and available nesting habitat (USDI BLM 2015, pp. 

764–774). Northern spotted owls are not migratory, in that the range of the species does not vary by 

season. 

The BLM is unaware of credible data on how past timber harvest levels on BLM-administered lands 

have affected, if at all, competitive interactions between northern spotted owls and barred owls. Thus, 

there is no basis for a credible analysis. The BLM does not address interbreeding between northern 

spotted owls and barred owls, as there is no evidence that interbreeding is having a measurable effect 

on the northern spotted owl population or that the BLM could affect interbreeding through land use 

planning. The commenter does not present any information, evidence, or data that would provide a 

basis for the BLM to analyze the effect of reduced harvest levels on barred owl abundance and 

competition with northern spotted owls, or the effect of interbreeding by the two species. 

335. Comment Summary: The BLM should increase the barred owl encounter rate over time to 

reflect the true growth rate of this population and its effect on northern spotted owls.

Response: The Draft RMP/EIS used observed estimated barred owl encounter rates from the most 

recent northern spotted owl meta-analysis available at that time (USDI BLM 2015, pp. 778–780). The 

Proposed RMP/Final EIS has updated the barred owl encounter rates used in the analysis based on the 

newest northern spotted owl meta-analysis, which had not yet been released at the time of the 

preparation of the Proposed RMP/Final EIS. The commenter’s suggestion that the BLM increase the 

encounter rate over time to reflect “the true growth rate” of the barred owl cannot be done, because, 

as the meta-analyses indicate, barred owl encounter rates change over time differently—and, thus, not 

predictably—in each demographic study area. In addition, the barred owl will reach carrying capacity 

in some areas at some time, and there exists no information that would allow the BLM to predict, 

reasonably, when, where, and at what levels barred owl populations will stabilize. 

The BLM did expanded the analyses of Alternative C and the No Timber Harvest reference analysis 

by using modified barred owl encounter rates developed by the U.S. Fish and Wildlife Service. The 

BLM ran these analyses for Alternative C and the No Timber Harvest reference analysis because 

these would bracket the outcomes of all alternatives using the modified encounter rates (USDI BLM 

2015, p. 779). However, the BLM did this only to determine the range of northern spotted owl 

population responses to a potential future barred owl management program. 

336. Comment Summary: By withdrawing from the Northwest Forest Plan, the BLM puts existing 

habitat conservation plans, the northern spotted owl recovery plan and the basis for northern spotted 

owl critical habitat designations at immediate risk.

Response: The Draft RMP/EIS explained that the BLM needs to revise existing plans to replace the 

1995 RMPs’ land use allocations and management direction because of new scientific information 

and policies related to the northern spotted owl. Since the approval of the 1995 RMPs, there have 
1982 | P a g e

been analyses on the effects of land management on northern spotted owl habitat, demographic 

studies, and analyses of the effects of barred owls on northern spotted owls. In addition, since that 

time, the U.S. Fish and Wildlife Service has developed new policies for northern spotted owls, 

including a revised recovery plan and a new designation of critical habitat (USDI BLM 2015, p. 5). 

The Draft RMP/EIS provides a reasoned analysis based on detailed and quantified information on the 

effects of the alternatives on northern spotted owls and northern spotted owl habitat, including 

designated critical habitat (USDI BLM 2015, pp. 746–826). Therefore, the Draft RMP/EIS took a 

‘hard look’ at the effects of the alternatives on northern spotted owls and northern spotted owl habitat. 

The BLM is unaware of, and the commenter does not identify, any habitat conservation plan that 

would be ‘at risk’ from any of the alternatives.

As verified by the northern spotted owl analysis in the Draft RMP/EIS, which specifically examined 

the consistency of the various alternatives with the northern spotted owl revised recovery plan and 

final rule on northern spotted owl critical habitat, all alternatives would be consistent with the 

recovery plan and final rule, and none would place these strategies ‘at risk.’

Regardless, the CEQ regulations require that an EIS analyze the environmental effects of the 

alternatives and explains that effects include “ecological (such as the effects on natural resources and 

on the components, structures, and functioning of affected ecosystems), aesthetic, historic, cultural, 

economic, social, or health” (40 CFR 1502.16, 1508.8). Habitat conservation plans, recovery plans, 

and critical habitat rules—in contrast to the resources to which they pertain—do not constitute an 

ecological, aesthetic, historic, cultural, economic, social, or health resource that could be affected by 

the BLM action. If a harm does not have a sufficiently close connection to the physical environment, 

NEPA does not apply (Metropolitan Edison Co. v. People Against Nuclear Energy, 460 U.S. 766 

(1983)). The Draft RMP/EIS analyzed the effect of the RMP revision on northern spotted owl and on 

northern spotted owl habitat, including designated critical habitat. Beyond that, the continued validity 

of any habitat conservation plan, recovery plan, or critical habitat rule itself lacks a sufficiently close 

connection to the physical environment to be analyzed in an EIS. 

337. Comment Summary: The documents cited in the Draft RMP justifying the need to maintain 

“large, contiguous blocks of late‐successional forest” are outdated and have since been proven false 

or have been superseded by future decisions.

Response: The Draft RMP/EIS identified that maintaining large, contiguous blocks of latesuccessional forest is a part of the purpose for the action, based on scientific information, the results 

of previous analyses, and the recommendations in the northern spotted owl revised recovery plan 

(USDI BLM 2015, pp. 7–8). 

Although scientists first identified large blocks of older forest as a conservation need of the northern 

spotted owl in 1990, the importance of such large blocks has been reaffirmed by ongoing science. The 

Draft RMP/EIS cited the most recent research in this area, which validates the importance of older 

forest conditions and managing for large blocks of unfragmented older forest (USDI BLM 2015, p. 

774). 

Contrary to the commenter’s claim, the U.S. Fish and Wildlife Service did not dismiss the need for 

large blocks of older forest in the 2011, revised recovery plan for the northern spotted owl or the 2012 

final rule on northern spotted owl critical habitat. Instead, the U.S. Fish and Wildlife Service 

identified management needs in addition to large blocks of older, contiguous forest specifically to 
1983 | P a g e

help compensate for the loss of such blocks fragmented by past management actions. As the U.S. Fish 

and Wildlife Service stated in the 2012 final rule on critical habitat (77 FR 71908): 

“The natural ecological processes and landscape that once provided large areas of relatively 

contiguous northern spotted owl habitat (especially on the west side of the Cascade Range) have 

been altered by a history of anthropogenic activities, such as timber harvest, road construction, 

development, agricultural conversion, and fire suppression. The resilience of these systems is 

now additionally challenged by the effects of climate change. As recommended in the Revised 

Recovery Plan for the Northern Spotted Owl, active forest management may be required 

throughout the range of the owl with the goal of maintaining or restoring forest ecosystem 

structure, composition, and processes so they are sustainable and resilient under current and 

future climate conditions, to provide for the long-term conservation of the species (USFWS 2011, 

p. III–13).”

The commenter does not offer any evidence that including large, contiguous blocks of latesuccessional forest among the purposes of the action was arbitrary or unreasonably narrow. 

338. Comment Summary: Competition between the northern spotted owl and the barred owl will 

increase as late seral and structurally-complex forest is influenced by increased logging. The BLM 

northern spotted owl analysis “is severely flawed and biased towards timber interests.” “An issue of 

particular concern is the proposal of the BLM to increase logging in scope, scale, and intensity 

throughout dry forests in western Oregon.”

Response: The BLM disagrees with the basic claims by this commenter. As the BLM stated in the 

Draft RMP/EIS, “Current research provides no evidence that the BLM can manage individual forest 

stands to provide northern spotted owls with a competitive advantage over barred owls (Dugger et al. 

2011 and Wiens et al. 2014)” (USDI BLM 2015, p. 774). Since that determination is so fundamental 

to the BLM analytical methods, the BLM specifically verified that statement with the subject matter 

experts, the U.S. Fish and Wildlife Service, and multiple northern spotted owl scientists. 

The BLM also disagrees that the northern spotted owl analysis “is severely flawed and biased towards 

timber interests.” The BLM evaluated northern spotted owl habitat and population responses to 

different land management strategies in terms of BLM contributions to the science-based 

conservation needs of the northern spotted owl, and consistency with the 2011 northern spotted owl 

revised recovery plan and 2012 final rule on northern spotted owl critical habitat, and evaluated and 

presented the results. The BLM developed the northern spotted analyses in collaboration with the 

U.S. Fish and Wildlife Service and Federal scientists with expertise in northern spotted owl research, 

analysis, and management. At the request of the BLM, three northern spotted owl scientists who work 

for the U.S. Forest Service, and are outside the BLM planning process, reviewed the BLM’s methods, 

analyses, and conclusions. The BLM went to exceptional lengths to ensure that the northern spotted 

owl analyses were both analytically and scientifically credible, and that the BLM correctly interpreted 

and presented the results of those analyses. 

The science on dry forest management has progressed since approval of the 1994 Northwest Forest 

Plan. The northern spotted owl analyses indicate that, during the next 50 years, dry forests treated 

with low intensity or uneven-age management prescriptions support northern spotted owl habitat 

development and populations almost as well as leaving these lands untreated, and better than under 

the Northwest Forest Plan. 
1984 | P a g e

339. Comment Summary: The BLM appears committed to eliminating the leave tree and wood 

retention standards and guidelines that provide at least some structural complexity in Northwest 

Forest Plan regeneration harvest units. The U.S. Fish and Wildlife Service relied upon the retention of 

structural legacies in harvest units over time in development of the Northern Spotted Owl Recovery 

Plan and in the designation of northern spotted owl critical habitat.

Response: The alternatives in the Draft RMP/EIS considered a range of approaches to “leave tree and 

wood retention” in regeneration harvests. The Proposed RMP includes requirements for retention of 

green trees, snags, and woody debris in regeneration harvests (Appendix B – Management Objectives 

and Direction).

340. Comment Summary: The State of Oregon recommends a requirement for northern spotted owl 

surveys in the Harvest Land Base, and those protections, at a minimum, for northern spotted owl 

known and historic sites within the Harvest Land Base, meet Oregon Forest Practices Act standards.

Response: Congress enacted legislation pertaining to the management of the BLM timberlands 

pursuant to the O&C Act which preempts state law purporting to govern administration of the O&C 

lands, including the Oregon Forest Practices Act. The commenter equates the Harvest Land Base 

allocated under the alternatives with state and private industrial forest lands managed under the Forest 

Practices Act. This ignores the fact that the Harvest Land Base is only one of several proposed land 

use allocations under each alternative, and that the reserve network under each alternative would be 

substantially larger than the Harvest Land Base. Specifically, the Proposed RMP would provide 

substantial support to northern spotted owl conservation and recovery, and continue to exceed the 

protections afforded to the northern spotted owl by the Forest Practices Act. 

341. Comment Summary: The BLM must analyze and disclose the impacts of their activities on 

northern spotted owl survival and recovery, including increases in fire risk.

Response: As explained in the Draft RMP/EIS, the BLM modeled wildfire and included the effects 

of future wildfires in the northern spotted owl habitat modeling on all lands within the range of the 

northern spotted owl (USDI BLM 2015, pp. 748, 811–814, 1045–1056). The commenter identifies no 

error in that analysis. 

342. Comment Summary: Northern spotted owl population trends continue to decline at alarming 

rates (Davis et al. 2015). Decline was steepest on study areas not managed under the Northwest 

Forest Plan (Anthony et al. 2006); thus, the downward trajectory might have been much worse 

without the Forest Plan. BLM needs to include this in the Final EIS.

Response: The Proposed RMP/Final EIS has included the most current information on northern 

spotted owl populations. Speculation about how a different management plan might have affected 

northern spotted owls in the past is neither possible nor relevant to this analysis. The analysis 

considers the cumulative effect of past actions in producing the current baseline condition for 

resources (USDI BLM 2015, p. 94), including northern spotted owl populations. The northern spotted 

owl analyses evaluated northern spotted owl future population responses under each alternative, 

including the No Action alternative, which assumes the continued implementation of the Northwest 

Forest Plan on BLM-administered lands. 
1985 | P a g e

343. Comment Summary: On BLM-administered lands in Oregon, the rate of old forest losses 

reflected by spotted owl habitat loss was more than 2 times that of U.S. Forest Service lands over a 

ten‐year period (Table 4 of Davis et al. 2015). This relatively higher rate of loss on BLM lands needs 

to be acknowledged in the Final EIS.

Response: The commenter misread Table 4 of Davis et al. (2015), which does not distinguish 

between BLM-administered lands and U.S. Forest Service lands. In fact, Davis et al. (2015) provides 

no results specific to BLM-administered lands. 

344. Comment Summary: Federal agencies assume that fire is a leading cause of habitat loss to 

northern spotted owls, yet few empirical studies have actually investigated spotted owl response to 

fire absent post‐fire logging in or around owl territories. The tradeoff between fire risk reduction and 

owl habitat maintenance has seldom, if ever, been systematically evaluated by Federal agencies. Such 

simulation and empirical based studies on impacts of widespread thinning on spotted owls need to be 

included in the RMP. Forest treatments intended to reduce the threat of fire are more likely to cause 

more harm to the northern spotted owl than fire itself.

Response: The Draft RMP/EIS included the effects of wildfire and timber harvest treatments in all of 

the northern spotted owl analyses. The vegetation modeling incorporated the effects of wildfire and 

timber harvest and fuel treatments on forest stand conditions over time (USDI BLM 2015, pp. 98–

102). The northern spotted owl analysis used the results of the vegetation modeling in evaluating 

changes in northern spotted owl habitat over time (USDI BLM 2015, pp. 1453–1455). In this 

analysis, the BLM did model the effects of timber harvest and fuel treatments within the alternatives, 

among other forest management actions, on northern spotted owl habitat over time based on empirical 

information on current stand conditions, the effects of timber harvest and fuel treatments on stand 

conditions, and habitat suitability of different stand conditions. The commenter identifies no error in 

this analysis. 

The treatment of a stand to improve its fire resiliency commonly reduces the immediate value of the 

stand for northern spotted owls. However, the effects of these treatments are temporary, they typically 

occur in younger forest stands that are of less value to northern spotted owls, and they are intended to 

protect adjacent older forest stands from fire ignition in the treated stand. The Draft RMP/EIS 

acknowledged that hazardous fuels treatments can affect wildfire risk, but the BLM has no method to 

translate these changes in risk into meaningful differences in wildfire occurrence and wildfire effects 

for the alternatives (USDI BLM 2015, p. 212). The commenter offers no information that would 

allow such analysis. 

Finally, the goal of fuels management under the alternatives is not limited to northern spotted owl 

habitat management. One of the purposes of the RMP is to restore fire-adapted ecosystems to increase 

fire resiliency (USDI BLM 2015, p. 10). Under all action alternatives, the management objectives for 

fuels management include managing fuels to reduce wildfire hazard, risk, and negative impacts to 

communities and infrastructure, landscapes, ecosystems, and highly valued resources (Appendix B –

Management Objectives and Direction). Therefore, while beneficial and adverse effects to northern 

spotted owls are relevant in the analysis, such effects are not the only consideration in including fuel 

treatments in the action alternatives. 

345. Comment Summary: The Final EIS should provide protections for all suitable spotted owl 

nesting and roosting habitat and not just the high quality habitat areas given owls will use mature 

forests and not just the oldest age classes (Carroll and Johnson 2008).
1986 | P a g e

Response: The Draft RMP/EIS explained why an alternative that would protect all northern spotted 

owl habitat would be substantially similar to Sub-alternative C, which the Draft RMP/EIS analyzed in 

the northern spotted owl analysis (USDI BLM 2015, p. 80). Under Sub-alternative C the BLM 

evaluated the effects of protecting all northern spotted owl nesting-roosting habitat on BLMadministered lands and determined that it would contribute negligible added benefits to northern 

spotted owl conservation when compared to some other alternatives and actually performed less well 

with respect to owl conservation than did some other alternatives (USDI BLM 2015, pp. 746–826). 

346. Comment Summary: The Final EIS should recognize that mixed‐severity fires are not a threat to 

spotted owls in its southern range and manage for heterogeneity produced by these fires. Mixed‐

severity fires provide nesting and roosting habitat in low to moderate burn patches and foraging 

habitat in high‐severity burn complexes (DellaSala et al. 2015). This needs to be recognized by BLM 

as the spotted owl appendix is out‐of‐step with new fire science on owl habitat.

Response: The Draft RMP/EIS modeled the observed effects of high-, moderate- and low-intensity 

wildfires in mixed severity patches on northern spotted owl habitat (USDI BLM 2015, pp. 1045–

1056). The BLM has reviewed DellaSala et al. 2015, which presents literature reviews and policy 

critiques and does not include any scientific information that would alter the empirical information 

used in the wildfire modeling. 

347. Comment Summary: We assert that Federal land spotted owl habitat modeling are not 

adequately incorporating the rapid loss of nesting-roosting-foraging habitat from private land clear 

cutting at scales relevant to existing northern spotted owls.

Response: The Draft RMP/EIS modeled habitat changes on all land ownerships within the northern 

spotted owl range based on observed rates specific to land classification/ownership (USDI BLM 

2015, pp. 1480–1485). The commenter does not identify what habitat loss on private land they 

believe has not be “adequately incorporated” in this modeling.

348. Comment Summary: Impact of sudden oak death on spotted owl habitat not disclosed.

Response: The Draft RMP/EIS modeled habitat changes based on observed rates of change on all 

land ownerships (USDI BLM 2015, pp. 1453–1485). Although the BLM did not specifically breakout 

the impacts of sudden oak death, the effects of sudden oak death are incorporated among the change 

elements identified in the GNN data. It would not improve the quality of the analysis or provide for a 

reasoned choice among the alternatives to break out specifically the effects of sudden oak death on 

northern spotted owl habitat in the modeling. 

349. Comment Summary: It is unlikely any of the BLM’s alternatives will provide the harvest levels 

projected for them given the spotted owl recovery plan and critical habitat designation, which are 

likely to result in restrictions greater than disclosed in the Draft RMP. It is unknown what level of 

constraint will result at project level consultation in terms of avoidance, reduced acreage for harvest, 

or harvesting at lower intensities than stated in RMP.

Response: The northern spotted owl revised recovery plan is advisory. That said, the Draft RMP/EIS 

analyzed the effects of the alternatives in the context of the recommendations in the northern spotted 
1987 | P a g e

owl revised recovery plan (USDI BLM 2015, pp. 746–818). Consistent with Section 7(a)(2) of the 

ESA, the BLM will ensure, in consultation with the U.S. Fish and Wildlife Service, that any action by 

the BLM will not result in the destruction or adverse modification of designated critical habitat for the 

northern spotted owl. The Draft RMP/EIS specifically evaluated the effects of the alternatives on 

designated critical habitat for the northern spotted owl (USDI BLM 2015, pp. 819–826). 

The BLM will also consult with the U.S. Fish and Wildlife Service on individual projects 

implemented under the approved RMP that may affect northern spotted owls or their critical habitat. 

Unless the Service finds jeopardy or adverse modification and offers a reasonable and prudent 

alternative, the BLM would not be constrained from implementing actions under the RMP. 

The commenter provides no information or evidence to support their speculation that there will be 

some unspecified future restrictions on timber harvest. Furthermore, the commenter does not identify 

any change the BLM should make to the analysis in response to their asserted uncertainty. 

350. Comment Summary: If BLM were to adopt a management plan that merely conformed to the 

existing regulatory policies of the spotted owl recovery plan and critical habitat, the levels of 

sustainable harvest would be lower than any alternative BLM has analyzed. The BLM analysis has 

established that the RMP, if fully adhered to, will have a substantial impact on sustained-yield 

management on O&C lands that was not previously revealed publicly.

Response: The commenter does not specify what alternative they believe would conform to the 

“existing regulatory policies of the spotted owl recovery plan and critical habitat” or how such an 

alternative would differ from the alternatives analyzed in the Draft RMP/EIS. By implication, the 

commenter is asserting that the alternatives analyzed in the Draft RMP/EIS would not conform to the 

northern spotted owl revised recovery plan or the critical habitat rule. Based on the analysis in the 

Draft RMP/EIS of the effects of the alternatives on northern spotted owls (USDI BLM 2015, pp. 746–

826), the BLM does not agree with this implied assertion. The commenter does not explain the basis 

for their supposition that such an alternative would have a lower level of “sustainable harvest” than 

the alternatives analyzed in the Draft RMP/EIS. The alternatives analyzed in the Draft RMP/EIS 

would result in sustained-yield harvest levels that would range from 120 MMbf to 486MMbf per 

year. These alternatives cover the full spectrum of reasonable alternatives to accomplishing the stated 

purpose and need for action. 

351. Comment Summary: The BLM did not disclose the extent of spotted owl critical habitat and the 

degree it overlays the Harvest Land Base.

Response: The Proposed RMP/Final EIS has added the acreage of designated critical habitat within 

the Harvest Land Base under each alternative (see the Wildlife section of Chapter 3). 

352. Comment Summary: All the action alternatives analyzed in the RMP DEIS will eliminate 

reserves or allow logging within the reserves that currently serve as habitat for the Northern Spotted 

Owl. The No Action Alternative – compliance with the Northwest Forest Plan – would result in the 

greatest increase in large blocks of suitable habitat by 2050. The RMP EIS fails to discuss or consider 

any of the scientific studies finding that further loss of owl habitat may drive the northern spotted owl 

to extinction. Sustainable Ecosystem Institute, Scientific Evaluation of the Status of the Northern 

Spotted Owl (2004).
1988 | P a g e

Response: The commenter mischaracterizes the action alternatives in the Draft RMP/EIS. None of 

the action alternatives would “eliminate reserves.” In fact, all of the action alternatives would allocate 

more acres to the Late-Successional Reserve than the No Action alternative. The action alternatives 

include a range of approaches to management within reserves, but most, including the Proposed 

RMP, would allow silvicultural treatments within the Late-Successional Reserve comparable to the 

approach in the No Action alternative. The commenter is mistaken about the effects of the No Action 

alternative; the Draft RMP/EIS analysis verified that the No Action alternative would support the 

development of large habitat blocks no better than any other alternative and, in the dry forest, would 

support northern spotted owl conservation less well than several other alternatives (USDI BLM 2015, 

pp. 746–764). The commenter does not identify any error in that analysis. The Draft RMP/EIS cited 

relevant studies and scientific information related to the effects of habitat changes on northern spotted 

owl populations (USDI BLM 2015, p. 774). The only specific study that the commenter suggests is 

cited throughout the Draft RMP/EIS analysis of the northern spotted owl (e.g., BLM 2015, pp. 747, 

749, 751, 764). 

353. Comment Summary: A large block strategy will not protect owls and aid in the recovery of owls 

in Southern Oregon. A finer scale approach to recovery and protection is needed instead of a large 

block reserve for the dry forest. It appears that the RMP analysis of habitat, includes private lands as 

contributing to NSO habitat. You cannot count on private land to meet the obligation of habitat for 

spotted owls. This is a flaw in the analysis assumptions. On the Medford District an owl-by-owl 

strategy is needed rather than a large block design.

Response: The Draft RMP/EIS identified that maintaining large, contiguous blocks of latesuccessional forest is a part of the purpose for the action, based on scientific information, the results 

of previous analyses, and the recommendations in the northern spotted owl revised recovery plan 

(USDI BLM 2015, pp. 7–8). Although scientists first identified large blocks of older forest as a 

conservation need of the northern spotted owl in 1990, ongoing science has reaffirmed the importance 

of such large blocks. The Draft RMP/EIS cited the most recent research in this area, which validates 

the importance of older forest conditions and managing for large blocks of unfragmented older forest 

(USDI BLM 2015, p. 774). The commenter does not offer any evidence that including large, 

contiguous blocks of late-successional forest among the purposes of the action was arbitrary or 

unreasonably narrow. Regarding private land contributions to northern spotted owl conservation, the 

Draft RMP/EIS stated that the analysis would evaluate the BLM’s contribution to a western Oregon 

landscape that supports northern spotted owl conservation (USDI BLM 2015, p. 749). The BLM 

evaluated the contribution of private lands to northern spotted owl recovery because they affect all 

management outcomes. As the BLM analyses verify, the private lands contribute relatively little to 

northern spotted owl conservation, and that affects how the cumulative effect of how the alternatives 

would contribute to northern spotted owl conservation and recovery. 

The commenter asserts “an owl-by-owl strategy is needed rather than a large block design.” Such as 

strategy would not be a reasonable alternative; the purpose and need for the RMP revision specifically 

identified the purpose of maintaining large, contiguous blocks of late-successional forest (USDI BLM 

2015, pp. 7–8). Furthermore, the Background section of the Northern Spotted Owl section in Chapter 

3 details the continuing conservation need of large blocks of nesting, roosting, and foraging habitat. 

An alternative that would not include “a large block design” would not respond to the purpose and 

need for action and would not address the conservation needs of the northern spotted owl. 

354. Comment Summary: It is unclear from the DEIS, but is NRF habitat now being defined as only 

multilayered, multi‐species canopy, diameter over 30 inches DBH and canopy cover over 60% and 
1989 | P a g e

decadence components? Spotted owls can and do nest in forests over 80 years old, even if they have 

not yet developed full decadence components present in unique old‐growth forests like RA 32 habitat.

Response: The BLM is not redefining northern spotted owl NRF (nesting-roosting-foraging) habitat. 

The Draft RMP/EIS cited the description of nesting-roosting-foraging habitat in Thomas et al. (1990) 

and subsequent research that confirmed that this description remains valid (USDI BLM 2015, p. 749). 

This definition does not use an age criterion nor does the analysis in the Draft RMP/EIS, and is 

broader than the description of ‘high-quality’ habitat in Recovery Action 32. For the purposes of 

modeling changes in northern spotted owl habitat over time, the BLM modeled northern spotted owl 

relative habitat suitability over time (USDI BLM 2015, pp. 1453–1485). This modeling did not 

classify stands as simply habitat or non-habitat, but modeled relative habitat suitability from 0 to 100, 

with higher numbers signifying better habitat value. The commenter does not identify any error in this 

analysis. 

355. Comment Summary: Spotted owl habitat suitability is rated on a 0 to 100 scale (higher numbers 

indicating better habitat) and the scale is based upon canopy cover, mean tree diameter, and slope. 

This new metric raises many questions. Exactly what variables were included, and how are they 

weighted? Were legacy trees accounted for or secondary older cohorts accounted for and how? 

Additionally, the BLM divided owl habitat into four categories ‘strongly selected for’, ‘selected for’, 

‘selected against’, and ‘strongly selected against.’ I believe this means that a ‘strongly selected for’ 

area had a high proportion of northern spotted owl nest locations based on the relative habitat 

suitability value. It would be beneficial to the public and our organization to see how this new metric 

rates against the more simple analysis of stand age.

Response: The Proposed RMP/Final EIS has added information to explain further the habitat 

suitability modeling (Appendix T – Northern Spotted Owl).

356. Comment Summary: The BLM is claiming in the RMP that northern spotted owl declines have 

little to do with loss of available late seral and structurally-complex forest habitat. This assumption is 

simply not validated by the best available science.

Response: The commenter appears to be confusing the threats that have caused past population 

declines for the northern spotted owl with the results of the analysis of the future effects of the 

alternatives. The revised recovery plan clearly stated that the northern spotted owl was listed under 

the ESA due to loss of spotted owl habitat because of timber harvesting and was exacerbated by other 

events. In the Draft RMP/EIS, the analysis of northern spotted owl habitat incorporated the aggregate 

effect of past timber harvest into the baseline description of current habitat conditions. The analysis in 

the Draft RMP/EIS evaluated the effects of the alternatives on future amounts and configuration of 

habitat. The analysis in the Draft RMP/EIS also modeled the effect of these future changes in habitat 

and other factors, such as barred owl interactions, on northern spotted owl population responses. The 

Draft RMP/EIS concluded that habitat changes on BLM-administered lands, under the different 

alternatives, had little discernable effect on northern spotted owl population responses due to the 

effects of competitive interactions between northern spotted owls and barred owls (USDI BLM 2015, 

pp. 746–826). That determination is consistent with scientific observation and modeling by other 

subject matter experts throughout the northern spotted owl’s range. The commenter does not identify 

any error in that analysis and does not cite any scientific information that is inconsistent with the 

information in the Draft RMP/EIS. 
1990 | P a g e

357. Comment Summary: A reference analysis should be performed to illustrate the extent to which 

the encounter rate of barred owl and northern spotted owl affects management strategy outcomes.

Response: The Draft RMP/EIS did provide an analysis of the effects of the alternatives at different 

barred owl encounter rates. Based on that analysis, the Draft RMP/EIS concluded that habitat changes 

on BLM-administered lands, under the different alternatives, had little discernable effect on northern 

spotted owl population responses due to the effects of competitive interactions between northern 

spotted owls and barred owls (USDI BLM 2015, pp. 774–804). 

358. Comment Summary: Mark it well: historic, ongoing, and widespread habitat destruction is the 

root cause of the endangerment of the NSO. This premise is as inarguable as it is certain. For the 

authors of the DEIS to throw up their hands, so to speak, and declare that ‘...the BLM has no 

opportunity through habitat management in the Coast Range to reduce risks to the northern spotted 

owl during the next 50 years...’ goes beyond cavalier and enters the realm of the outrageous! The 

BLM must assume the NSO’s ultimate recovery across the decision area, if not the entire planning 

area.

Response: The analytical conclusions in the Draft RMP/EIS are supported by scientifically and 

analytically credible modeling, and are consistent with empirical evidence and multiple, independent 

expert conclusions. The analysis in the Draft RMP/EIS evaluated the effects of the alternatives on 

future amounts and configuration of habitat. The analysis in the Draft RMP/EIS also modeled the 

effect of these future changes in habitat and other factors, such as barred owl interactions, on northern 

spotted owl population responses. The Draft RMP/EIS concluded that habitat changes on BLMadministered lands, under the different alternatives, had little discernable effect on northern spotted 

owl population responses due to the effects of competitive interactions between northern spotted owls 

and barred owls (USDI BLM 2015, pp. 746–826). The commenter observes this analytical 

conclusion, but identifies no error in the analysis. 

Analysis of effects in an EIS must address those effects that are reasonably foreseeable (40 CFR 

1508.8). While the “ultimate recovery” of the northern spotted owl is desirable from both a legal and 

policy standpoint, it is by no means reasonably foreseeable, as evidenced by the discussion of the 

current population condition in the Draft RMP/EIS. The commenter’s assertion that the BLM must 

“assume the NSO’s ultimate recovery” disregards the current condition and trend of the northern 

spotted owl population and the results of the analysis in the Draft RMP/EIS. As noted in the analysis 

in the Draft RMP/EIS, the outcomes for the northern spotted owl population under the No Timber 

Harvest reference analysis at current barred owl encounter rates would be substantially the same as 

the alternatives (USDI BLM 2015, pp. 783–804). In that context, it is unclear how the commenter 

intends that the BLM must “assume the NSO’s ultimate recovery.”

359. Comment Summary: The BLM must manage habitat to allow for northern spotted owl and 

barred owl co-existence and in doing so must protect all habitats. Competition between the spotted 

owl and the barred owl will increase as late seral and structurally-complex forest is influenced by 

increased logging. Further fragmentation and late seral habitat degradation will provide an advantage 

to the barred owl, who can utilize slightly more altered forest habitat.

Response: Currently there is no substantive empirical evidence that northern spotted owls would be 

able to coexist with barred owls in the future as the effects of competitive interactions on the northern 

spotted owl are continuing to increase, and the commenter offers no such evidence. 
1991 | P a g e

The Draft RMP/EIS analyzed the effects of a No Timber Harvest reference analysis, in which the 

BLM forecast northern spotted owl habitat and population responses to a hypothetical management 

scenario in which the BLM conducted no timber harvest. That analysis concluded that protecting all 

habitats, in the absence of barred owl control, would not substantively curb the continued northern 

spotted owl population decline (USDI BLM 2015, pp. 746–826). The commenter identifies no error 

in that analysis. 

360. Comment Summary: Effects to northern spotted owl foraging habitat have not been specifically 

addressed.

Response: The BLM did not specifically address foraging habitat because, unlike nesting-roosting 

and dispersal habitats: (1) there is no accepted description of foraging habitat in terms of stand age, 

stand structure, canopy cover or other metrics the BLM can model, and (2) there is no quantitative 

definition of the necessary amount of foraging habitat in terms of patch size, patch spacing, density 

on the landscape, where it needs to be and when it needs to be there. With no credible metric of how 

much is enough or other benchmarks, the BLM could not state that the contribution of any one 

alternative would be adequate or would not be adequate to contribute to the conservation and 

recovery of the northern spotted owl. Therefore, an analysis specifically evaluating the amount of 

foraging habitat would not improve the quality of the analysis or provide for a reasoned choice among 

the alternatives. This is in sharp contrast to nesting-roosting and dispersal habitats, which have clear, 

science-based thresholds of adequacy. 

361. Comment Summary: In displaying the results of its HexSim model, the BLM provides no 

estimates of variance for any of the modeled northern spotted owl population numbers. It’s important 

to provide some measure of variation in these estimates from HexSim models.

Response: The variance associated with the HexSim model results does not alter the basic analytical 

conclusions in the Draft RMP/EIS. Including variance measures for the results on the HexSim model 

would not improve the quality of the analysis or provide for a reasoned choice among the alternatives. 

362. Comment Summary: How did the BLM come to the conclusion that northern spotted owl 

populations in the western Cascades would be stable? Stability is a description of the trend, not total 

numbers.

Response: The commenter mischaracterizes the analytical conclusions in the Draft RMP/EIS. The 

Draft RMP/EIS stated that the modeling indicated that the northern spotted owl population likely 

would persist in the western Cascades during the next 50 years; the Draft RMP/EIS clearly showed 

that the population is not stable and is not expected to stabilize without a reduction in the barred owl 

encounter rate (USDI BLM 2015, pp. 787, 792). 

Oregon Spotted Frog 

363. Comment Summary: Analysis and survey data are needed for the Oregon spotted frog because it 

has been proposed for Federal listing and proposed critical habitat identified.
1992 | P a g e

Response: The Draft RMP/EIS analyzed the effects of the alternatives on the amount of habitat for 

Oregon spotted frog and its proposed critical habitat. The Proposed RMP/Final EIS has included 

additional information on the current conditions and analyzed effects of the alternatives on the 

Oregon spotted frog and its proposed critical habitat (see the Wildlife section of Chapter 3). 

Western Snowy Plover 

364. Comment Summary: The State recommends changes in OHV use and Recreation Management 

Area (RMA) designations in the RMP that would not increase activities in snowy plover habitat.

Response: The BLM would allocate snowy plover habitat and critical habitat as limited to public 

motorized access under the Proposed RMP. However, the Proposed RMP would specifically direct 

the BLM to not authorize or construct additional roads or trails in within snowy plover habitat or 

designated critical habitat. Furthermore, ACEC management direction under the Proposed RMP 

would preclude additional impacts to snowy plovers resulting from public motorized vehicle use (see 

the Wildlife section of Chapter 3 and Appendix B – Management Objectives and Direction).

365. Comment Summary: To protect snowy plovers adequately at the two sites where BLM lands 

support the species (the New River ACEC and the Coos Bay North Spit [CBNS]), the Service 

recommends the BLM include a set of conservation measures in its RMP.

Response: The Proposed RMP includes management direction intended to conserve snowy plovers. 

The Proposed RMP would provide direction to continue activities that restore or maintain snowy 

plover nesting habitat, as the Coos Bay District has been implementing (e.g., mechanical treatment of 

plowing of European beach grass and augmenting nesting grounds with oyster shells). The Proposed 

RMP also includes direction to avoid disruption of plover nesting behaviors through restricting the 

timing and location of beach access or activities (see the Wildlife section of Chapter 3 and Appendix 

B – Management Objectives and Direction).

Issues Considered but not Analyzed in Detail 

366. Comment Summary: The Siskiyou Mountain Salamander conservation agreement, to which the 

BLM is a party to, indicates that “significant changes in Forest Service or BLM land‐use allocation 

within the area of the conservation strategy” must trigger “immediate review of the Conservation 

Agreement.” This threshold would be triggered by implementation of the RMP as outlined in the 

DEIS and the conservation agreement must be revisited and amended to either reduce logging and 

ground disturbance impacts or proceed towards listing of the SMS due to new threats from BLM 

logging that far exceeds the standards of the NWFP and therefore the assumptions built into the 

Conservation Agreement and Conservation Strategy.

Response: The Proposed RMP would include management direction to manage the Siskiyou 

Mountains salamander consistent with the Conservation Agreement for the Siskiyou Mountains 

Salamander (Plethodon stormi) in Jackson and Josephine Counties of Southwest Oregon; and in 

Siskiyou County of Northern California (August 17, 2007), as amended and as long as that agreement 

is in effect. The option to review and potentially amend this conservation agreement is an 

independent process that is outside of the scope of the RMP revision. 
1993 | P a g e

Wild and Scenic Rivers 

367. Comment Summary: Rough and Ready Creek should be found eligible for potential inclusion 

into the National Wild and Scenic Rivers System.

Response: The BLM has determined that Rough and Ready Creek is not eligible for potential 

inclusion in the National Wild and Scenic Rivers System based on the lack of outstandingly 

remarkable values present within the river corridor. The BLM completed the eligibility 

determinations and subsequent suitability studies for all potential Wild and Scenic Rivers in the 

decision area as part of the 1995 RMPs. As part of this RMP revision, each BLM district re-validated 

all river segments that the BLM had previously found eligible or non-eligible for potential inclusion 

into the National Wild and Scenic Rivers System. The eligibility determination that was performed by 

the Medford District in 1992 for Rough and Ready Creek was re-validated and determined as noneligible based on the lack of outstandingly remarkable values present within the river corridor being 

studied. 

368. Comment Summary: The BLM should not designate the Rogue River as a Wild and Scenic 

River. Designation of this river and the private lands along the river corridor would violate private 

landowners’ rights.

Response: The BLM has not proposed to recommend any non-BLM-administered lands, including 

privately owned lands, for inclusion into the National Wild and Scenic River System anywhere in the 

decision area. The land acres considered under this analysis comprising the Wild and Scenic River 

corridor along the 63 miles of the Rogue River total 754 acres, all of which are BLM-administered 

lands. The 63-mile stretch of the Rogue River and the associated 754 acres of BLM-administered 

lands underwent eligibility and suitability reviews as part of this RMP revision. The details of the 

eligibility and suitability study process for the Rogue River is documented in Section 2, pp. 7–9 of the 

Wild and Scenic Rivers Suitability Report for Southwest Oregon (BLM USDI 2015). The BLM 

followed the methodology to determine whether this eligible river would meet the 13 suitability 

criteria to be appropriate to recommend for inclusion in the National System and found the Rogue 

River to be suitable to recommend for potential inclusion. The Rogue River suitability factor 

assessment is contained in the Wild and Scenic Rivers Suitability Report (pp. 121–139). 

The alternatives consider a range of requisite protections and recommendations for inclusion into the 

National Wild and Scenic River System. Under the No Action alternative, the Rogue River would 

receive protections of the outstandingly remarkable values and tentative classification identified until 

the next land use planning process assessed the suitability of Wild and Scenic Rivers. Under 

Alternatives B, C, and D, and the Proposed RMP, the BLM would recommend the Rogue River for 

inclusion into the National Wild and Scenic River System. Under these alternatives and the Proposed 

RMP, the 63 miles and 754 acres of BLM-administered lands would receive interim management for 

the outstanding remarkable values and tentative classification until Congress either designates the 

river or releases it for other uses. This interim management would apply only to BLM-administered 

lands and would have no bearing on private land management. 
1994 | P a g e

References 

Baker, W. L. 2011. Reconstruction of the historical composition and structure of forests in the middle Applegate area, Oregon 

using the General Land Surveys. 22 pp. 

http://www.blm.gov/or/districts/medford/forestrypilot/files/Citizen7_attachment.pdf. 

Baker, W. L. 2014. Historical northern spotted owl habitat and old-growth dry forests maintained by mixed-severity fires. 

Landscape Ecology 30: 655–666. http://dx.doi.org/10.1007/s10980-014-0144-6. 

Beschta, R. L., C. A. Frissell, R. Gresswell, R. Hauer, J. R. Karr, G. W. Minshall, D. A. Perry, and J. J. Rhodes. 1995. Wildfire 

and salvage logging: Recommendations for ecologically sound post-fire salvage logging and other post-fire treatments on 

federal lands in the west. 16 pp. http://www.saveamericasforests.org/congress/Fire/Beschta-report.htm. 

Bosch, J. M., and J. D. Hewlett. 1982. A review of catchment experiments to determine the effects of vegetation changes on 

water yield and evapotranspiration. Journal of Hydrology 55: 3–23. 

ftp://ftp.aphis.usda.gov/foia/FOLDER_10/AR00037120%20Bosch%20and%20Hewlett%201982.pdf. 

Bowker, J. M., A. E. Askew, H. K. Cordell, C. J. Betz, S. J. Zarnoch, and L. Seymour. 2012. Outdoor recreation participation in 

the United States–Projections to 2060: A technical document supporting the Forest Service 2010 RPA Assessment. General 

Technical Report SRS-160. USDA Forest Service, Southern Research Station, Asheville, NC. 42 pp. 

http://www.srs.fs.fed.us/pubs/gtr/gtr_srs160.pdf. 

Brown, A. E., L. Zhang, T. A. McMahon, A. W. Western, and R. A. Vertessy. 2005. A review of paired catchment studies for 

determining changes in water yield resulting from alterations in vegetation. Journal of Hydrology 310(1–4): 28–61. 

http://dx.doi.org/10.1016/j.jhydrol.2004.12.010. 

California Department of Conservation/California Geological Survey (CADC/CAGS). 2013. Factors affecting landslides in 

forested terrain. Note 50. Sacramento, CA. 6 pp. 

http://www.conservation.ca.gov/cgs/information/publications/cgs_notes/note_50/documents/note50.pdf. 

CEQ. 2011. Appropriate use of mitigation and monitoring and clarifying the appropriate use of mitigated Findings of No 

Significant Impact. Memorandum for heads of federal departments and agencies. January 14, 2011. Washington, D.C. 20 pp. 

https://ceq.doe.gov/current_developments/docs/Mitigation_and_Monitoring_Guidance_14Jan2011.pdf. 

---. 2014. Revised draft guidance on the consideration of greenhouse gas emissions and the effects of climate change in NEPA 

reviews. December 18, 2014. Washington, D.C. 31 pp. 

https://www.whitehouse.gov/sites/default/files/docs/nepa_revised_draft_ghg_guidance_searchable.pdf. 

Chan, S., P. Anderson, J. Cissel, L. Larson, and C. Thompson. 2004. Variable density management in Riparian Reserves: lessons 

learned from an operational study in managed forests of western Oregon, USA. For. Snow Landsc. Res. 78(1/2): 151–172. 

http://www.fs.fed.us/pnw/pubs/journals/pnw_2004_chan001.pdf. 

Clark, W. C. 2011. Road networks, timber harvest, and the spread of Phytophthora root rot infestations of Port-Orford-cedar in 

southwest Oregon. Unpublished MS Thesis. Oregon State University. Corvallis, OR. 85 pp. 

http://ir.library.oregonstate.edu/xmlui/bitstream/handle/1957/23622/ClarkWilliamC2011.pdf?sequence=1. 

Colombaroli, D., and D. G. Gavin. 2010. Highly episodic fire and erosion regime over the past 2,000 y in the Siskiyou 

Mountains, Oregon. PNAS 107(44):18909–18914. http://www.pnas.org/content/107/44/18909.full.pdf. 

DellaSala, D. A., M. L. Bond, C. T. Hanson, R. L. Hutto, R. W. Halsey, and D. Odion. 2013. Open letter to members of Congress 

from 250 scientists concerned about post-fire logging. October 30, 2014. 15 pp. 

http://www.californiachaparral.com/images/Scientist_Letter_Postfire_2013.pdf. 

DellaSala, D. A., M. L. Bond, C. T. Hanson, R. L. Hutto, and D. C. Odion. 2014. Complex early seral forests of the Sierra 

Nevada: What are they and how can they be managed for ecological integrity? Natural Areas Journal 34(3): 310–324. 

http://dx.doi.org/10.3375/043.034.0317. 

DellaSala, D. A., and C. T. Hanson (eds). 2015. The ecological importance of mixed-severity fires: nature’s phoenix. Elsevier, 

United Kingdom (13 chapters). 

Dello, K. 2015. Personal communication. September 11, 2015. Associate Director Oregon Climate Change Research Institute, 

Deputy Director, Oregon Climate Service, Corvallis, OR. 

Dipaolo, D. A., and P. E. Hosten. 2015. Vegetation change following the Forest Reserve Homestead Act of 1906 in the 

Applegate River Watershed, Oregon. Madroño 62(2): 101–114. http://dx.doi.org/10.3120/0024-9637-62.2.101. 

Donato, D. C., J. B. Fontaine, J. L. Campbell, W. D. Robinson, J. B. Kauffman, and B. E. Law. 2006. Post-wildfire logging 

hinders regeneration and increases fire risk. Science 311(5759): 352. http://dx.doi.org/10.1126/science.1122855. 

Donato, D. C., J. L. Campbell, and J. F. Franklin. 2012. Multiple successional pathways and precocity in forest development: can 

some forests be born complex? Journal of Vegetation Science 23(3): 576–584. http://dx.doi.org/10.1111/j.1654-

1103.2011.01362.x. 

Franklin, J. F., K. N. Johnson, D. J. Churchill, K. Hagmann, D. Johnson, and J. Johnston. 2013. Restoration of dry forests in 

eastern Oregon: a field guide. The Nature Conservancy, Portland, OR. 202 pp. 

http://extension.oregonstate.edu/union/sites/default/files/dryforestguide2013.pdf. 

Grundstein, A. 2008. Assessing climate change in the contiguous United States using a modified Thornthwaite climate 

classification scheme. The Professional Geographer 60(3): 398–412. http://dx.doi.org/10.1080/00330120802046695. 

Hanson, C. T., D. C. Odion, D. A. DellaSala, and W. L. Baker. 2009. Overestimation of fire risk in the Northern Spotted Owl 

Recovery Plan. Conservation Biology 23(5):1314–1319. http://johnmuirproject.org/wpcontent/uploads/2014/12/Hansonetal2009CB.pdf. 
1995 | P a g e

Harr, R. D., 1980. Streamflow after patch logging in small drainages within the Bull Run Municipal Watershed, Oregon. 

Research Paper PNW-268. USDA Forest Service, Pacific Northwest Forest and Range Experiment Station, Portland, OR. 16 

pp. http://www.fs.fed.us/pnw/pubs/pnw_rp268.pdf. 

Harr, R. D., and F. M. McCorison. 1979. Initial effects of clearcut logging on size and timing of peak flows in a small watershed 

in western Oregon. Water Resources Research 15(1): 90–94. 

http://www.wou.edu/las/physci/taylor/g473/refs/harr_Mccorisson_1979.pdf. 

Harr, R. D., A. Levno and R. Mersereau. 1982. Streamflow changes after logging 130-year-old Douglas-fir in two small 

watersheds. Water Resources Research 18(3): 637–644. http://dx.doi.org/10.1029/WR018i003p00637. 

Ingalsbee, T., and U. Raja. 2015. The rising cost of wildfire suppression and the case for ecological fire use. In: D. A. DellaSala, 

and C. T. Hanson (eds). The ecological importance of mixed-severity fires: nature’s phoenix. Elsevier, Boston, MA. pp. 

348–371. http://dx.doi.org/10.1016/B978-0-12-802749-3.00012-8. 

Interagency Working Group on the Social Cost of Carbon, United States Government (IWG). 2015. Technical support document: 

Technical update of the cocial cost of carbon for regulatory impact analysis under Executive Order 12866. 21 pp. 

http://www.whitehouse.gov/sites/default/files/omb/inforeg/scc-tsd-final-july-2015.pdf. Retrieved October 22, 2015. 

Interagency Working Group on the Social Cost of Carbon, United States Government (IWG). 2010. Technical support document: 

Social cost of carbon for regulatory impact analysis under Executive Order 12866. 51 pp. 

https://www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf. Retrieved 

October 22, 2015. 

Jones, J. A., and G. E. Grant. 1996. Peak flow responses to clear-cutting and roads in small and large basins, western Cascades, 

Oregon. Water Resources Research 32(4): 959–974. 

http://ir.library.oregonstate.edu/xmlui/bitstream/handle/1957/27734/JonesJuliaCEOASPeakFlowResponses.pdf?sequence=1. 

Jones, J. A. 2000. Hydrologic processes and peak discharge response to forest removal, regrowth, and roads in 10 small 

experimental basins, western Cascades, Oregon. Water Resources Research 36(9): 2621–2642. 

http://ir.library.oregonstate.edu/xmlui/bitstream/handle/1957/27733/JonesJuliaCEOASHydrologicProcessesPeak.pdf?sequen

ce=1. 

Keim, R. F., and A. E. Skaugset. 2003. Modelling effects of forest canopies on slope stability. Hydrological Processess 17(7): 

1457–1467. http://dx.doi.org/10.1002/hyp.5121. 

Kottek, M., J. Grieser, C. Beck, B. Rudolf, and F. Rubel. 2006. World map of the Köppen-Geiger climate classification updated. 

Meteorologische Zeitschrift 15(3): 259–263. http://koeppen-geiger.vu-wien.ac.at/pdf/paper_2006.pdf. 

Littell, J. S., D. McKenzie, D. L. Peterson, and A. L. Westerling. 2009. Climate and wildfire area burned in western U.S. 

ecoprovinces, 1916–2003. Ecological Applications 19(4): 1003–1021. 

http://pubag.nal.usda.gov/pubag/downloadPDF.xhtml?id=34676&content=PDF. 

Luce, C. H., and T. A. Black. 1999. Sediment production from forest roads in western Oregon. Water Resources Research 35(8): 

2561–2570. http://dx.doi.org/10.1029/1999WR900135. 

Moore, G. W., B. J. Bond, J. A. Jones, N. Phillips, and F. C. Meinzer. 2004. Structural and compositional controls on 

transpiration in 40- and 450-year-old riparian forests in western Oregon, USA. Tree Physiology 24: 481–491. 

http://www.geo.oregonstate.edu/files/geo/moore_etal_treephys_04.pdf. 

Moore, R. D. and S. M. Wondzell. 2005. Physical hydrology and the effects of forest harvesting in the Pacific Northwest: a 

review. Journal of the American Water Resources Association 41(4): 763–784. 

http://www.fs.fed.us/pnw/pubs/journals/pnw_2005_moore001.pdf. 

Odion, D. C., E. J. Frost, J. R. Strittholt, H. Jiang, D. A. DellaSala, and M. A. Moritz. 2004. Patterns of fire severity and forest 

conditions in the western Klamath Mountains, California. Conservation Biology 18(4): 927–936. 

http://dx.doi.org/10.1111/j.1523-1739.2004.00493.x. 

Odion, D. C., M. A. Moritz, and D. A. DellaSala. 2010. Alternative community states maintained by fire in the Klamath 

Mountains, USA. Journal of Ecology 98(1): 96–105. http://dx.doi.org/10.1111/j.1365-2745.2009.01597.x. 

Odion, D. C., C. T. Hanson, A. Arsenault, W. L. Baker, D. A. DellaSala, R. L. Hutto, W. Klenner, M. A. Moritz, R. L. Sherriff, 

T. T. Veblen, and M. A. Williams. 2014. Examining historical and current mixed-severity fire regimes in ponderosa pine 

and mixedconifer forests of western North America. PLoS ONE 9: e87852. http://dx.doi.org/10.1371/journal.pone.0087852. 

Office of Management and Budget (OMB). 2004. Issuance of OMB’s “Final Information Quality Bulletin for Peer Review.” 

Washington, D.C. 45 pp. https://www.whitehouse.gov/sites/default/files/omb/memoranda/fy2005/m05-03.pdf. 

Oregon Natural Heritage Advisory Council (ONHAC). 2012. Oregon Natural Areas Plan (ONAP). Oregon Biodiversity 

Information Center, Institute for Natural Resources – Portland, Portland State University, Portland, OR. 198 pp. 

http://orbic.pdx.edu/documents/2010NAP.pdf. 

Personius, S. F., and A. R. Nelson, compilers. 2006. Fault number 781, Cascadia subduction zone, in Quaternary fault and fold 

database of the United States. U.S. Geological Survey. http://earthquakes.usgs.gov/hazards/qfaults. Accessed February 19, 

2016. 

Peterson, D. W., E. K. Dodson, and R. J. Harrod. 2015. Post-fire logging reduces surface woody fuels up to four decades 

following wildfire. Forest Ecology and Management 338: 84–91. 

http://www.fs.fed.us/pnw/pubs/journals/pnw_2015_peterson.pdf. 

Reiter, M. L., and R. L. Beschta. 1995. Effects of forest practices on water. In: Cumulative effects of forest practices in Oregon: 

literature and synthesis. Oregon State University. Corvallis. Chapter 7. 
1996 | P a g e

Rhodes, J. J., and W. L. Baker. 2008. Fire probability, fuel treatment effectiveness and ecological tradeoffs in western US public 

forests. The Open Forest Science Journal 1(1): 1–7. http://www.energyjustice.net/files/biomass/library/Rhodes-Baker.pdf. 

Satterlund, D. R., and P. W. Adams. 1992. Wildland Watershed Management, second edition. John Wiley & Sons, Inc. New 

York. 

Shelanski, H., and M. Obstfeld. 2015. Estimating the benefits from carbon dioxide emissions reductions. WhiteHouse.gov blog 

dated July 2, 2015. https://www.whitehouse.gov/blog/2015/07/02/estimating-benefits-carbon-dioxide-emissions-reductions. 

Retrieved October 22, 2015. 

Skaugset, A., N. Zégre, A. Simmons, and H. Owens. 2013. Local and downstream impacts of contemporary forest practices on 

sediment yield. PowerPoint presentation. 26 pp. 

Swanson, M. E., J. F. Franklin, R. L. Beschta, C. M. Crisafulli, D. A. DellaSala, R. L. Hutto, and F. J. Swanson. 2011. The 

forgotten stage of forest succession: early-successional ecosystems on forest sites. Frontiers in Ecology and the Environment 

9(2): 117–125. http://dx.doi.org/10.1890/090157. 

Swanston, D. N., and C. T. Dyrness. 1973. Stability of steep land. Journal of Forestry 71(5): 264–269. 

Sweeney, B. W., and J. D. Newbold. 2014. Streamside forest buffer width needed to protect stream water quality, habitat, and 

organisms: A literature review. Journal of the American Water Resources Association 50(3): 560–584. 

http://dx.doi.org/10.1111/jawr.12203. 

Thomas, R. B. and W. F. Megahan. 1998. Peak flow responses to clear-cutting and roads in small and large basins, western 

Cascades, Oregon: a second opinion. Water Resources Research 34(12): 3393–3403. 

http://www.geo.oregonstate.edu/classes/geo582/week_7_1_forest_harvest_roads_peaks/thomas_megahan_wrr_98.pdf. 

Thompson, J. R., T. A. Spies, and L. M. Ganio. 2007. Reburn severity in managed and unmanaged vegetation in a large wildfire. 

Proceedings of the National Academy of Sciences 104(25): 10743–10748. http://dx.doi.org/10.1073/pnas.0700229104. 

USDA and USDI. 2009. Guidance for implementation of federal wildland fire management policy. U.S. Department of 

Agriculture and U.S. Department of the Interior, Washington, D.C. 

https://www.nifc.gov/policies/policies_documents/GIFWFMP.pdf. 

USDA FS, USDI BLM, ODF, and USDI NPS. 2014. Southwest Oregon Interagency Fire Management Plan. U.S. Forest Service 

Rogue River-Siskiyou National Forest, BLM Medford District, Oregon Department of Forestry Southwest District, and 

National Park Service Oregon Caves National Monument. 353 pp. 

http://www.fs.usda.gov/Internet/FSE_DOCUMENTS/stelprd3813539.pdf. 

USDI BLM. 1997. Standards for rangeland health and guidelines for livestock grazing management for public lands administered 

by the Bureau of Land Management in the states of Oregon and Washington. Oregon State Office, Portland, OR. 22 pp. 

http://www.blm.gov/or/resources/recreation/csnm/files/rangeland_standards.pdf. 

---. 2004. Record of Decision and Resource Management Plan Amendment of Management of Port-Orford-Cedar in Southwest 

Oregon, Coos Bay, Medford, and Roseburg District. Portland, OR. January 2004. 63 pp. 

http://www.fs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb5316520.pdf. 

---. 2011a. BLM Manual 1626 – Travel and Transportation Management Manual. July 14, 2011. 37 pp. 

http://www.blm.gov/style/medialib/blm/wo/Information_Resources_Management/policy/blm_manual.Par.38105.File.dat/16

26.pdf. 

---. 2011b. Water Quality Restoration Plan for the Deer Creek Watershed (HUC 1710031105). Grants Pass, OR. 19 pp. 

http://www.blm.gov/or/districts/medford/plans/files/deerckwqrp.pdf. 

---. 2012. BLM Handbook H-8342-1 Travel and Transportation Management Handbook. March 16, 2012. 148pp. 

http://www.blm.gov/style/medialib/blm/wo/Information_Resources_Management/policy/blm_handbook.Par.34786.File.dat/

8342.pdf. 

---. 2013. Wellington Mountain (OR11-34) Wilderness Characteristics Inventory. BLM Medford District, Medford/Ashland, OR. 

15 pp. http://www.blm.gov/or/districts/medford/plans/files/medford-wci-wellington.pdf. 

---. 2015. Wild and Scenic Rivers Suitability Report–Southwest Oregon. BLM Oregon/Washington State Office, Portland, OR. 

208 pp. http://www.blm.gov/or/plans/rmpswesternoregon/files/draft/SW_OR_Wild_Scenic_Rivers_Suitability_Report.pdf. 

USDI BLM, USDI NPS, USDI FWS and USDA FS. 2015. Interagency Standards for Fire and Fire Aviation Operations. National 

Wildfire Coordination Group National Fire Equipment System Catalog #2724. Federal Fire and Aviation Task Group, 

National Interagency Fire Center, Boise, ID. 419 pp. 

https://www.nifc.gov/PUBLICATIONS/redbook/2015/RedBookAll.pdf. 

Westerling, A. L., H. G. Hidalgo, D. R. Cayan, and T. W. Swetnam. 2006. Warming and earlier spring increase in western U.S. 

forest wildfire activity. Science 313(5789): 940–943. http://dx.doi.org/10.1126/science.1128834. 

Whitlock, C. 1992. Vegetation and climatic history of the Pacific Northwest during the last 20,000 years: implications for 

understanding present-day biodiversity. The Northwest Environmental Journal 8: 5–28.

http://www.fs.fed.us/rm/pubs/rmrs_gtr292/1992_whitlock.pdf. 

Ziemer, R. L. 1981. Strom flow response to road building and partial cutting in small streams of northern California. Water 

Resources Research 17(4): 907–917. http://www.fs.fed.us/psw/publications/ziemer/Ziemer81a.PDF. 

Zégre, N. P. 2008. Local and downstream effects of contemporary forest harvesting on streamflow and sediment yield. Ph.D. 

dissertation. Oregon State University, Corvallis, OR. 181 pp. 

http://ir.library.oregonstate.edu/xmlui/bitstream/handle/1957/10012/Zegre_Dissertation_2008.pdf?sequence=3.
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Appendix X – Guidance for Use of the 

Completed RMPs 

This appendix describes on how the BLM will implement, evaluate, and change the RMPs after approval 

of the RMP revisions. These descriptions, which provide background information and explanations of 

how the BLM will use the completed RMPs, do not constitute additional requirements beyond the 

management direction described in Appendix B. The BLM may make changes to the processes described 

in this background information through plan maintenance, as explained below, in that changes to 

processes, in and of themselves, would not expand the scope of resource uses or restrictions or change the 

terms, conditions, and decisions of the approved plan. 

Implementation of the Completed RMPs 

At this time, the BLM anticipates issuing two Records of Decision/Resource Management Plans 

(RODs/RMPs): one ROD/RMP that would apply to the Coos Bay District, Eugene District, Salem 

District, and the Swiftwater Field Office of the Roseburg District; and another ROD/RMP that would 

apply to the Klamath Falls Field Office of the Lakeview District, the Medford District, and the South 

River Field Office of the Roseburg District. 

The Records of Decision will only make decisions on lands that fall under BLM jurisdiction (including 

mineral estate). The major provisions of the RMPs will include the following land use plan decisions—

 Objectives for the management of BLM-administered lands and resources; 

 Land use allocations relative to future uses for the purposes of achieving the various objectives; 

and 

 Management direction that identifies where future actions may or may not be allowed and what 

restrictions or requirements may be placed on those future actions to achieve the objectives set for 

the BLM-administered lands and resources. 

Management objectives are descriptions of desired outcomes for BLM-administered lands and resources 

in an RMP; the resource conditions that the BLM envisions or desires would eventually result from 

implementation of the RMP. As such, management objectives are not rules, restrictions, or requirements 

by which the BLM determines which implementation actions to conduct or how to design specific 

implementation actions. 

For some land use allocation decisions, such as the location of the Late-Successional Reserve, Harvest 

Land Base, and District-Designated Reserve – Lands Managed for their Wilderness Characteristics, the 

maps accompanying the approved RMP of these allocations represent the decision. For other land use 

allocation decisions, such as the location of the Riparian Reserve, the decision requires identification of 

features on the ground (e.g., a perennial stream) and the allocation of a corresponding width of Riparian 

Reserve. 

Although the location of the Riparian Reserve will require the identification of specific features on the 

ground, the maps accompanying the approved RMP of the three subwatershed classes for the purpose of 

defining Riparian Reserve widths and management direction (Appendix B) represent the decision. In 

identifying subwatershed classes, the BLM considered the information in critical habitat designations and 

data on high intrinsic potential streams to indicate the importance of subwatersheds to the conservation 

and recovery of ESA-listed fish. However, future changes in designated critical habitat or data on high 

intrinsic potential streams would not alter the identification of subwatershed classes for the purpose of 
1998 | P a g e

Riparian Reserve design and management direction. Any change to the subwatershed classes would 

constitute a change to the approved RMP and such changes would only be made consistent with the 

discussion below in the section on Changes to the Approved RMP. As noted above, the Records of 

Decision will only make decisions on lands that fall under BLM jurisdiction; as such, the identification of 

subwatershed classes within the planning area is only relevant to defining Riparian Reserve widths and 

management direction for streams and water features on BLM-administered lands within the 

subwatershed. 

The decision requires the future allocation of marbled murrelet occupied stands61 to the Late-Successional 

Reserve for occupied sites identified62 after March 26, 2015 as a result of BLM marbled murrelet surveys 

in (1) all land use allocations within 35 miles of the Pacific Coast, and (2) Late-Successional Reserve and 

Riparian Reserve between 35–50 miles from the Pacific Coast and outside of exclusion Areas C and D 

(shown in Figure 3-166). In addition, this decision requires the future allocation of red tree vole “habitat 

areas”63 to the Late-Successional Reserve for occupied sites identified as a result of BLM red tree vole 

surveys within the range of the North Oregon Coast Distinct Population Segment of the red tree vole 

north of Highway 20. 

Through the RMPs, the BLM will determine and declare the annual productive capacity for sustainedyield timber production. In the Records of Decision for the approved RMPs, the BLM will declare the 

annual productive capacity for sustained-yield timber production and describe the level of allowable 

variation in the amount of timber offered for sale in a given time period. In addition, the Records of 

Decision for the approved RMPs will define any necessary transition period from the declarations of the 

annual productive capacity in the 1995 RMPs to the declarations of the annual productive capacity in the 

approved RMPs. The BLM will make the determination and declaration of the annual productive capacity 

for each of the six sustained yield units, which match the five western Oregon BLM district boundaries 

and the western portion of the Klamath Falls Field Office of the Lakeview District. 

Land use plan decisions (land use allocations, management objectives, and management direction) do not 

directly authorize implementation of on-the-ground projects. Land use plan decisions guide and control 

future implementation decisions, which the BLM can carry out only after completion of further NEPA 

compliance and decision-making processes and consultation as appropriate. 

Implementation decisions authorize implementation of on-the-ground projects. Examples of 

implementation decisions include but are not limited to the following: offering a specific tract of timber 

for sale, applying a vegetation treatment, approving or denying an application for a permit, issuing an 

individual grazing lease, designating specific roads and trails as open or closed to motorized travel, or 

completing a specific land exchange. The Proposed RMP does not include any implementation decisions 

to be included in the eventual Records of Decision/Approved RMPs. 

Implementation Planning 

Implementation planning is a process the BLM uses to develop a coordinated strategy to facilitate 

implementation of new land use plans. Consistent with the 2005 BLM Land Use Planning Handbook (H1601-1), the BLM will complete implementation planning within one year of approval of the RMPs. The 

 

61 Marbled murrelet occupied stand refers to all forest stands, regardless of age or structure, within 1/4 mile (1,320 

feet) of the location of marbled murrelet behavior indicating occupancy and not separated from the location of 

marbled murrelet behavior indicating occupancy by more than 328 feet of non-forest. 

62 In this context, “identified after March 26, 2015,” means that survey data for occupied marbled murrelet sites was 

entered into the BLM corporate database after March 26, 2015. 

63 Red tree vole “habitat areas” are described in the management direction (Appendix B).
1999 | P a g e

implementation planning process is a three-step process by which the BLM identifies and outlines work 

tasks to achieve the desired outcomes of one the land use plans. The product of this effort will be a 

worksheet, which outlines implementation actions in correlation to management objectives and direction 

described in the RMPs for 5–10 years. The implementation plan will prioritize work tasks for funding and 

implementation based upon direction provided and given the existing or anticipated resources. 

Implementation planning enables the BLM to prioritize the preparation of implementation decisions. 

Project-level Planning and Analysis 

The BLM will make decisions on specific projects to implement, including on-the-ground locations and 

timing of projects, subsequent to the approval of the RMPs. All implementation decisions must conform 

to the approved RMP, consistent with 43 CFR 1610.5–3. 

Revision of an RMP necessarily involves a transition from the application of the old RMP to the 

application of the new RMP. The planning and analysis of implementation projects typically requires 

several years of preparation before the BLM can reach a decision. Allowing for a transition from the old 

RMP to the new RMP avoids disruption of the management of the BLM-administered lands and allows 

the BLM to utilize work already begun on the planning and analysis of projects. The Records of Decision 

for the approved RMPs will address the application of the RMP to new and ongoing projects. 

The analysis in the Proposed RMP/Final EIS describes the cumulative effect of anticipated 

implementation actions under the RMPs, based on the information available to the BLM at this time and 

forecasting of reasonably foreseeable implementation actions under the RMPs. The analysis in the 

Proposed RMP/Final EIS will provide useful analysis, including cumulative effects analysis, to which 

most implementation-level analyses will tier, consistent with 40 CFR 1502.20. As the BLM plans and 

analyzes implementation actions, the BLM will have better and more specific information on the location, 

scope, and timing of proposed implementation actions, and site-specific conditions for project-level 

NEPA compliance. 

Implementation-level Travel Management Planning 

In accordance with 43 CFR 8342 and current BLM policy, the BLM is deferring implementation-level 

Travel Management Planning during the current RMPs for Western Oregon planning effort. 

Implementation-level TMP is the process of establishing a final travel and transportation network that 

includes route-specific designations within the broader land use planning level designations for public 

motorized access. In the future, implementation-level travel planning will follow a site-specific process 

for selecting a final public road and trail network. The BLM may delineate Travel Management Areas 

within these broader land use planning level designations for public motorized access to address particular 

concerns and prescribe specific management actions for a defined geographic area. The BLM will make 

final route designations within the decision area in comprehensive, interdisciplinary Travel and 

Transportation Management Plans, scheduled to be completed within five years after the completion of 

the western Oregon RMPs. Until implementation-level Travel Management Planning is complete, routes 

and trails would be managed in accordance with their designation of closed or limited to existing routes 

for public motorized travel activities, as described in Appendix Q. Implementation-level Travel 

Management Planning would be conducted within the decision area generally prioritizing planning to 

occur first where the BLM has legal public access and where implementation-level planning is needed to 

reduce threats to resources or to protect public safety. Specific prioritization criteria are listed in 

Appendix Q, and would be applied by each district and field office based upon local knowledge of their 

administrative areas. 
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BLM Participation in Barred Owl Management 

The U.S. Fish and Wildlife Service is currently authorizing the removal of barred owls from four study 

areas in California, Oregon, and Washington to evaluate the feasibility, cost, and effectiveness of barred 

owl removal and the resulting effects to northern spotted owl populations (USDI FWS 2013). In the 

Revised Recovery Plan for the Northern Spotted Owl, Recovery Action 29 describes the design and 

implementation of large-scale barred owl control experiments to assess the effects on spotted owl site 

occupancy, reproduction, and survival (USDI FWS, 2011, p. III-65). Recovery Action 30 calls for 

management to reduce the negative effects of barred owls on spotted owls so that the recovery criterion 

for a stable population trend can be achieved. In the Revised Recovery Plan for the Northern Spotted 

Owl, the U.S. Fish and Wildlife Service acknowledges the need for aggressive strategies to address the 

threat from barred owls in the face of scientific uncertainty, and will employ an active program of 

adaptive management in order to deal with uncertainty and risk (USDI FWS 2011, p. II-6 – II-10). 

Based on information in the Revised Recovery Plan for the Northern Spotted Owl (USDI FWS 2011), the 

analysis in the U.S. Fish and Wildlife Service EIS for Experimental Removal of Barred Owls to Benefit 

Threatened Northern Spotted Owls (USDI FWS 2013), and preliminary results from experimental 

removals (Diller 2013, Diller et al. 2014), barred owl management may result in decreased competition 

between barred owls and northern spotted owls, increased site occupancy by northern spotted owls, and 

increased northern spotted owl survival and reproduction. These outcomes may increase the likelihood of 

recovery of the northern spotted owl. As such, the experimental removals represent an inquiry into the 

best manner in which barred owl management can contribute to the recovery of the northern spotted owl. 

The BLM is cooperating with the U.S. Fish and Wildlife Service and providing financial support for this 

experimental removal of barred owls. Further, when the U.S. Fish and Wildlife Service determines the 

best manner in which barred owl management can contribute to the recovery of the northern spotted owl, 

the BLM would participate in, cooperate with, and provide support for an interagency program for barred 

owl management to implement Recovery Action 30. Barred owl management actions on BLMadministered lands within the range of the northern spotted owl could include BLM participation in 

scheduling, funding, and implementing such actions. These actions would be implemented pursuant to 

appropriate NEPA analysis and decision-making. To the extent the BLM funds implementation of the 

Experimental Removal of Barred Owls to Benefit Threatened Northern Spotted Owls (USDI FWS 2013), 

the NEPA analysis for that action is already completed. The EIS prepared by the U.S. Fish and Wildlife 

Service describes and evaluates nine alternatives for an experimental removal of barred owls on a scale 

sufficient to determine if the removal would increase northern spotted owl site occupancy and improve 

northern spotted owl population trends. Results from these experiments would be used by the U.S. Fish 

and Wildlife Service to inform future decisions on potential, long-term management strategies for barred 

owls (USDI FWS 2013). That analysis is hereby incorporated by reference. 

The BLM and U.S. Fish and Wildlife Service would develop a monitoring program that would evaluate 

whether such a barred owl management program is having the biological benefits to the northern spotted 

owl assumed by the Biological Opinion on the RMP. The BLM and U.S. Fish and Wildlife Service would 

meet as necessary, at least annually, to review the results of the monitoring program. 

Incidental Take of Northern Spotted Owls 

As described under the Proposed RMP in Chapter 2 and Appendix B, upon signing of the ROD/RMP, the 

BLM would not authorize timber sales that would cause the incidental take64 of northern spotted owl 

 

64 The ESA defines ‘take’ as “to harass, harm, pursue, hunt, shoot, wound, kill, trap, capture, or collect, or to attempt 

to engage in any such conduct” 16 U.S.C. 1532(19). The definition of harm is “an act which actually kills or injures 

wildlife. Such an act may include significant habitat modification or degradation where it actually kills or injures 
2001 | P a g e

territorial pairs or resident singles from timber harvest until implementation of a barred owl management 

program consistent with the assumptions contained in the Biological Opinion on the RMP has begun. 

Implementation of a barred owl management program includes the existence of a monitoring program that 

would evaluate whether a barred owl program is having the biological benefits to the northern spotted owl 

assumed by the Biological Opinion on the RMP. 

Whether a specific timber harvest would result in incidental take would be determined on a case-by-case 

basis. Until implementation of a barred owl management program has begun, the BLM would not 

authorize any timber harvest after the signing of the ROD/RMP that it determines would cause incidental 

take of northern spotted owls or is determined to cause incidental take through a Section 7 consultation 

process. The BLM would be authorizing timber harvest that does not result in incidental take of northern 

spotted owls (e.g., harvest in unoccupied home ranges or harvest within occupied home ranges that does 

not constitute incidental take), provided that such harvest otherwise meets BLM’s obligations under ESA 

section 7. 

As part of the process to determine whether a planned timber harvest would result in take of northern 

spotted owls, the BLM would establish whether the northern spotted owl is actually present in the area 

that would be affected by the timber harvest using the best available science at that time, such as through 

pre-project northern spotted owl surveys consistent with USDI Fish and Wildlife Service. 2012. Protocol 

for Surveying Proposed Management Activities That May Impact Northern Spotted Owls. (February 2, 

2011; revised January 9, 2012). The U.S. Fish and Wildlife Service has updated the northern spotted owl 

survey protocol to account for the influence of barred owl and may update it in the future. 

If the BLM and the U.S. Fish and Wildlife Service jointly determine that implementation of a barred owl 

management program has begun, the BLM may proceed with implementation of timber harvest consistent 

with the ROD/RMP that may include incidental take of northern spotted owl territorial pairs or resident 

singles. Any proposed timber harvest that may include such incidental take would be implemented only 

after and consistent with appropriate project-level Section 7 consultation and incidental take statement. 

After implementation of a barred owl management program has begun, the BLM and U.S. Fish and 

Wildlife Service would meet as necessary, at least annually, to review the results of the monitoring 

program. If the BLM or the U.S. Fish and Wildlife Service conclude that the monitoring program shows 

that the results of such a barred owl management program are not consistent with the assumptions in the 

Biological Opinion, the BLM would reinitiate Section 7 consultation on the RMP. 

If the BLM or the U.S. Fish and Wildlife Service concludes that implementation of a barred owl 

management program consistent with the assumptions contained in the Biological Opinion has not begun 

after five years from the effective date of the ROD/RMP, the agencies would meet as necessary, at least 

annually, and evaluate whether implementation of a barred owl management program consistent with the 

assumptions of the Biological Opinion is reasonably certain to occur. If both the BLM and the U.S. Fish 

and Wildlife Service agree that such a barred owl management program is still reasonably certain to 

occur, the BLM would continue to not authorize timber sales that would cause the incidental take of 

northern spotted owl territorial pairs or resident singles from timber harvest. If the BLM or the U.S. Fish 

and Wildlife Service concludes that such a barred owl management program is not reasonably certain to 

occur, the BLM would reinitiate Section 7 consultation on the RMP. 

If implementation of a barred owl management program has not begun after 8 years of the effective date 

of the ROD/RMP, the BLM would reinitiate Section 7 consultation on the RMP. 

 

wildlife by significantly impairing essential behavioral patterns, including breeding, feeding or sheltering” (50 CFR 

17.3); Babbitt v. Sweet Home Chapter of Cmtys. for a Greater Or., 515 U.S. 687, 696-700 (1995). 
2002 | P a g e

If reinitiation of Section 7 consultation on the RMP is triggered for any of the reasons above, the BLM 

would comply with ESA section 7(d) and would not authorize timber harvest that is likely to adversely 

affect the northern spotted owl or likely to adversely affect its critical habitat until consultation is 

complete. 

After implementation of a barred owl management program has begun, the BLM would continue to seek 

to avoid or reduce negative impacts to northern spotted owl sites, to the extent consistent with the 

management objectives and management direction for the Harvest Land Base, as detailed below. 

Management of Northern Spotted Owl Known Sites Associated 

with the Harvest Land Base65

In 2013, an estimated 175 known sites occurred in what would be the Harvest Land Base under the 

Proposed RMP. In addition, the Harvest Land Base under the Proposed RMP would contribute to the 500-

acre core use areas of an additional estimated 660 known sites located in other land use allocations, and to 

the median provincial home range areas of another estimated 250 known sites. Thus, an estimated 1,085 

known sites, or 44 percent of the known sites associated with BLM-administered lands, potentially would 

be affected by BLM management actions in the Harvest Land Base under the Proposed RMP. Given the 

severe biological stressors currently affecting the northern spotted owl, when designing, locating and 

implementing actions in the Harvest Land Base, BLM managers would66 reduce, avoid, or delay negative 

impacts to northern spotted owl known sites located in the Harvest Land Base, and avoid causing the 

abandonment of northern spotted owl known sites located in other land use allocations, to the extent 

consistent with the management objectives and management direction for the Harvest Land Base. 

This guidance is not intended to prevent all negative effects to known sites associated with the Harvest 

Land Base or the eventual loss of known sites in the Harvest Land Base. Instead, this guidance is intended 

to avoid or delay, to the extent consistent with the management objectives and management direction for 

the Harvest Land Base, near-term negative effects to known sites as northern spotted owl habitat 

continues to develop in the reserved land use allocations and the U.S. Fish and Wildlife Service evaluates 

options for barred owl management. 

The following information is intended to help BLM managers implement this guidance. 

 

65 As stated in the beginning of this appendix, this description, which provides background information and 

explanations of how the BLM will use the completed RMPs, does not constitute additional requirements beyond the 

management direction described in Appendix B. This description provides guidance for the timing or order of 

timber harvest in the Harvest Land Base but does not alter which lands are available for timber harvest. Guidance in 

this section for avoiding harvest or prioritizing harvest is in the context of those actions that are allowable consistent 

with the management objectives and management direction for the Harvest Land Base. 

66 As stated above, guidance in this section for avoiding harvest or prioritizing harvest is in the context of those 

actions that are allowable consistent with the management objectives and management direction for the Harvest 

Land Base. Thus, statements throughout this section about actions that the BLM would or would not take are solely 

explanations of how the BLM would use the completed RMPs and do not constitute additional requirements beyond 

the management direction described in Appendix B. 
2003 | P a g e

Known Sites Located in the Harvest Land Base 

With respect to sites currently67 occupied by a northern spotted owl territorial pair or resident single, to 

the extent consistent with the management objectives and management direction for the Harvest Land 

Base, BLM managers would–

 Avoid management actions that would cause the abandonment of more than 10 percent of such sites 

during the first decade of plan implementation, more than 15 percent of such sites during the second 

decade of plan implementation, and more than 20 percent of such sites per decade thereafter. These 

thresholds are intended to reflect site abandonment caused by a BLM action; they are not intended to 

reflect site abandonment from other causes such as displacement by barred owls or habitat losses on 

adjacent lands. If the BLM determines that an action would not cause the incidental taking of a 

territorial pair or resident single, and the U.S. Fish and Wildlife Service concurs with that 

determination, subsequent abandonment of a site associated with the action would not be considered 

as resulting from the action. 

 Give priority to maintaining existing habitat conditions in the associated nest patch, 500-acre core use 

area and median provincial home range area, in that order of priority, to support continued site 

occupancy. 

With respect to sites not currently occupied but known to have been occupied by a territorial pair or 

resident single within the past 5 years, BLM managers would give priority to maintaining existing habitat 

conditions in the nest patch and 500-acre core use area, and maintaining existing nesting-roostingforaging habitat in the associated median provincial home range area, to the extent consistent with the 

management objectives and management direction for the Harvest Land Base. If the BLM cannot 

maintain all existing nesting-roosting habitat in the median provincial home range area, BLM managers 

would give priority to maintaining nesting-roosting habitat closest to the 500-acre core use area and 

maintaining at least 50 percent of the median provincial home range area as nesting-roosting-foraging 

habitat when all lands are considered. 

With respect to sites not currently occupied, but known to have been occupied by a territorial pair or 

resident single within the past 10 years, BLM managers would give priority to maintaining existing 

habitat conditions in the nest patch and maintaining existing nesting-roosting habitat in the 500-acre core 

use area, or promoting the protection and development of nesting-roosting habitat in the nest patch and 

500-acre core use area, to the extent consistent with the management objectives and management 

direction for the Harvest Land Base. 

BLM managers would give priority to implementing management actions that are located outside the 

median provincial home range area of a site, or would affect sites not known to have been occupied by a 

territorial pair or resident single within the past 10 years, over actions that would affect sites that have 

been occupied within the past ten years. 

Known Sites Located Outside the Harvest Land Base 

In 2013, approximately 590 known sites in other BLM land use allocations under the Proposed RMP were 

occupied by a territorial pair or resident single within the past 5 years. In addition, if the U.S. Fish and 

Wildlife Service implements a barred owl management program, the BLM anticipates that northern 

spotted owls would reoccupy currently unoccupied habitat. 

 

67 For the purpose of this guidance, “sites currently occupied” means northern spotted owl sites that the BLM has 

determined are occupied at the time of implementation of the management action. The BLM will determine 

occupancy using the best science available at that time, such as through pre-project northern spotted owl surveys. 
2004 | P a g e

As stated above, when designing, locating and implementing actions in the Harvest Land Base, BLM 

managers would avoid causing the abandonment of northern spotted owl known sites located in other land 

use allocations, to the extent consistent with the management objectives and management direction for the 

Harvest Land Base. 

BLM managers would give priority to actions that affect sites–

 That are not known to have been occupied by a territorial pair or resident single within the past 10 

years. The longer a site has been unoccupied, the less likely it is to be re-occupied by northern 

spotted owls. 

 That have less than 50 percent nesting-roosting-foraging habitat within the associated median 

provincial home range area when all land ownerships are considered. Sites with median 

provincial home range areas supporting less than 50 percent nesting-roosting-foraging habitat are 

less likely to be re-occupied by northern spotted owls until habitat conditions recover. 

 With less than 50 percent of the associated median provincial home range area occurring in the 

Late-Successional Reserve, when all land ownerships and U.S. Forest Service reserves are 

considered. Sites associated with more reserved lands are more likely to be re-occupied by 

northern spotted owls, resist displacement by barred owls and contribute to species recovery. 

BLM managers would avoid actions that—

 Occur in the nest patch of a site. Habitat modification in the nest patch will negatively affect reoccupancy of the site by northern spotted owls until habitat conditions recover. 

 Cause the loss of nesting-roosting-foraging habitat in the 500-acre core use area surrounding a 

site. Sites with core use areas supporting less than 50 percent nesting-roosting-foraging habitat, 

when all land ownerships are considered, are less likely to be re-occupied by northern spotted 

owls until habitat conditions recover. 

 Cause the amount of nesting-roosting-foraging habitat in the median provincial home range area 

surrounding a site to decline below 50 percent, when all land ownerships are considered. 

Best Management Practices 

Best Management Practices (BMPs) are practices that have been determined to be the most effective and 

practicable in preventing or reducing the amount of pollution generated by diffuse sources to a level 

compatible with water quality goals (40 CFR 130.2 [m]). Appendix J – Best Management Practices lists 

these practices and provides a detailed discussion of the role and application of BMPs. Project-level 

planning and analysis will identify the appropriate and applicable BMPs needed to achieve management 

objectives. 

Watershed-Scale Information for Implementation Actions 

The BLM will compile watershed-scale information on aquatic and riparian resources, including 

identifying resource conditions, watershed processes, risks to resources, and restoration opportunities, as 

needed for planning and analysis of implementation actions under the approved RMP. The BLM will 

compile watershed-scale information with the purpose of developing and documenting a scientificallybased understanding of the ecological structures, functions, processes, and interactions occurring within a 

watershed. The number and detail of the aspects considered will depend on the issues pertaining to a 

given watershed and the scope of proposed implementation actions. 

This compilation of watershed-scale information does not constitute a separate or additional analysis 

beyond what the BLM would provide for NEPA or Endangered Species Act compliance for 

implementation actions. The BLM will focus on collecting and compiling information within the 
2005 | P a g e

watershed that is essential for making sound management decisions. This watershed-scale information 

will be relevant to analyzing the effects of implementation actions, determining monitoring and 

restoration needs for a watershed, and developing priorities for funding and implementing actions. 

The BLM will use such watershed-scale information, where appropriate, to facilitate NEPA and 

Endangered Species Act compliance for specific projects. For example, such watershed-scale information 

will typically be relevant in the preparation of biological assessments for consultation with the National 

Marine Fisheries Service and U.S. Fish and Wildlife Service under Section 7(a)(2) of the ESA on the 

effects of implementation actions that may affect ESA-listed fish species or their critical habitat. 

Watershed Restoration 

Watershed restoration will be an integral part of a program to contribute to the conservation and recovery 

of ESA-listed fish and protect water quality. Important components of a watershed restoration program 

include control and prevention of road-related runoff and sediment production, restoration of access to 

stream channels, restoration of instream habitat complexity, and restoration of the condition of riparian 

vegetation. 

Watershed restoration will include road treatments, such as obliteration, decommissioning, closure, or 

upgrading. Upgrading may involve practices such as removing soil from locations where there is a high 

potential of triggering landslides, modifying road drainage systems to reduce the extent to which the road 

functions as an extension of the stream network, and reconstructing stream crossings to reduce the risk 

and consequences of road failures or wash outs. 

Watershed restoration will include maintaining and restoring access to stream channels for all life stages 

of aquatic species. Specific actions will include replacing stream crossings that currently or potentially 

block or hinder fish passage with crossings that allow aquatic species to pass at each life stage and at a 

range of flows. 

Watershed restoration will include instream restoration to create desired levels of channel complexity and 

improve fish habitat. Specific actions may include log and boulder placement in stream channels, tree 

tipping, and gravel enhancement to create spawning, rearing, and holding habitat for fish. 

Watershed restoration will include silvicultural treatments of riparian forest stands, as needed to ensure 

that stands are able to provide trees that would function as stable wood in the stream, to increase diversity 

of riparian species, and develop structurally-complex stands. Watershed restoration will also include fuels 

reduction treatments in riparian forest stands, as needed to reduce the risk of stand-replacing, crown fires. 

The BLM will evaluate restoration opportunities based on watershed-scale information on aquatic and 

riparian resources, considering ecological processes and limiting factors. The BLM will use the BLM 

Western Oregon Aquatic Restoration Strategy in determining priorities for watershed restoration. The 

BLM Western Oregon Aquatic Restoration Strategy presents a restoration strategy that uses a 

combination of habitat based intrinsic potential modeling and professional field knowledge to focus 

restoration efforts in areas deemed likely to have the highest production potential for fish species of 

interest and is incorporated here by reference (BLM 2015b). The BLM may update the Western Oregon 

Aquatic Restoration Strategy periodically, and the BLM will continue to use the updated strategy to guide 

watershed restoration priorities. 
2006 | P a g e

Funding 

Implementation of actions in conformance with the approved RMP will be subject to sufficient funding 

and staffing to complete the necessary analysis and compliance steps and to carry out the actions. The 

RMP sets management objectives and the Proposed RMP/Final EIS analyzes effects based on 

assumptions about implementation of future actions. If the BLM does not implement future actions as 

anticipated in the Proposed RMP/Final EIS, the BLM will consider through plan evaluation whether the 

plan objectives are being met or are likely to be met, as discussed below. 

Timber Production Capability Classification 

The Timber Production Capability Classification is a process of partitioning forestland within the 

sustained yield unit into major classes based on the biological and physical capability of the site to 

support and produce forest products on a sustained yield basis using operational management practices. 

Through the Timber Production Capability Classification, the BLM identifies some sites as unsuitable for 

sustained-yield timber production because of their biological and physical capabilities. Over time, the 

BLM will add additional areas to those areas reserved through updates to the Timber Production 

Capability Classification system, when examinations indicate that an area meets the criteria for 

reservation. The BLM will also delete areas from those areas reserved and return the area to the Harvest 

Land Base through updates to the Timber Production Capability Classification system, when 

examinations indicate that an area does not meet the criteria for reservation. The BLM will implement 

these additions and deletions to the Timber Production Capability Classification through plan 

maintenance, as discussed below, because such changes will represent minor changes based on further 

refining the decision in the RMP. 

Management of Newly Acquired Lands 

Lands may come under BLM administration after approval of the RMPs through exchange, donation, 

purchase, revocation of withdrawals to other Federal agencies, or relinquishment of Recreation and Public 

Purpose leases. Discretionary acquisitions (such as exchanges) would be guided by the acquisition criteria 

described in Appendix K – Lands and Realty. 

The BLM would manage newly acquired or administered lands or interests in lands for the purpose for 

which they were acquired or in a manner that is consistent with management objectives for adjacent 

BLM-administered lands or other BLM-administered lands having similar resource values. For example, 

the BLM would typically manage acquired lands consistent with the land use allocations, management 

objectives, and management direction of comparable or adjacent BLM-administered lands. Newly 

acquired lands, regardless of status, would be subject to non-discretionary access rights provided for 

under the terms and conditions of most reciprocal right-of-way agreements and permits. 

In accordance with Section 205 (e) of the FLPMA (Pub. L. 99-632), lands acquired by the BLM in 

exchange for O&C or Coos Bay Wagon Road (CBWR) lands would have the same status and be 

administered in accordance with the same provisions of law applicable to those lands disposed of; and 

those newly acquired lands would be designated as O&C or CBWR lands, as appropriate, and managed 

under the sustained yield principles as prescribed in the Act of August 28, 1937 and other laws applicable 

to the O&C or CBWR lands. Additionally, lands acquired using proceeds generated from the disposal of 

O&C or CBWR lands under the authority of the Federal Land Transaction Facilitation Act (Pub. L. 106-

248) would also take on the same status as the lands from which the funds were generated (O&C or 

CBWR) and would likewise be managed in accordance with the Act of August 28, 1937 and other 

applicable laws. 
2007 | P a g e

Lands acquired by the BLM that take on the status of either O&C or CBWR lands would require 

classification in accordance with the Act of June 9, 1916, as to power-site, timberlands, or agricultural 

lands. Lands classified as timberland or agriculture would be open to exploration, location, entry, and 

disposition under the general mining laws in accordance with the Act of April 8, 1948. Lands acquired by 

the BLM under Section 205 or 206 of the FLPMA take on the status of ‘acquired lands,’ and therefore 

would not be available for location, lease, or sale until the BLM formally opened the lands to such entry. 

Land acquisitions resulting in net adjustments in the Harvest Land Base may be made without adjusting 

the declaration of the annual productive capacity for sustained-yield timber production or amending the 

RMP, unless the cumulative effects of all changes to the Harvest Land Base indicate that the decadal 

amount of sustained-yield timber production would be modified by more than 10 percent of the declared 

annual productive capacity for sustained-yield timber production. 

Management of Future Proposed Special Areas 

After approval of the RMPs, the BLM could receive recommendations, nominations, or identification of 

new special areas, such as Areas of Critical Environmental Concern or Wild and Scenic Rivers, requiring 

study or evaluation for special management. The BLM would conduct reviews and evaluations of these 

newly proposed or identified areas under the guidance of the national programs and BLM policies 

applicable to their management. Where the BLM determines that values are present, the BLM would 

provide management to protect the values while awaiting further evaluations or designations to the extent 

possible under existing legal authorities. The BLM would consider the protection of any identified values 

through due consideration in site-specific NEPA analysis and decisions in conformance with the 

applicable and current agency policies, BLM manuals, and law. 

Valid Existing Rights 

Other Federal, State, or local government agencies, Tribes, private individuals, or companies may hold 

valid existing rights within the decision area. Considering the intermingled nature of the BLMadministered lands in the planning area, the BLM has granted many rights-of-way, leases, permits, and 

other established legal rights within the decision area over the years. Valid existing rights may pertain to 

timber sale contracts, mining claims, mineral or energy leases, leases, easements, permits, rights-of-way, 

and water rights. Perhaps the most extensive and unique rights are the reciprocal rights-of-way 

agreements with dozens of adjacent landowners established to provide for the logical, effective, and 

efficient development of access on the intermingled lands. 

The decisions in the RMPs will not alter or extinguish valid existing rights on BLM-administered lands. 

Valid existing rights take precedence over the decisions in the RMPs. Authorization for implementing an 

action that would affect these valid existing rights may be subject to approval by the holders of valid 

existing rights and may not be discretionary to BLM. 

Adaptive Management 

In some instances, management direction in the Proposed RMP provides for a range of activities or 

resource uses. In these cases, levels of activities or resource uses would vary within the range prescribed 

by the management direction, without the need for additional planning steps such as plan amendment. 

The BLM would adapt the level of activities within the range given by management direction, depending 

on variation in resource needs or organizational capability. 
2008 | P a g e

In addition to the constraints or latitude provided by management direction, the ability to adapt or change 

management without the use of planning steps or NEPA analyses would be restricted by how much of a 

departure would be from analytical assumptions in the Proposed RMP/Final EIS. This is because the 

BLM derived conclusions regarding environmental consequences from analytical assumptions. Analytical 

assumptions include such things as levels or methods of activities, number of acres treated, and miles of 

roads maintained. 

If the need for adaptive management changes would so alter the implementation of the RMP that the 

environmental consequences would be substantially different than those anticipated in the Proposed 

RMP/Final EIS, then the BLM would engage in additional planning steps and NEPA procedures. The 

BLM would make the determination as to when additional planning steps and NEPA procedures would be 

required through the plan evaluation process, as discussed below. 

The BLM may also apply adaptive management by acting on information found through the monitoring 

questions (Appendix V). Adaptive management associated with monitoring could include corrective 

actions precipitated by findings of non-compliance. Corrective action precipitated by monitoring could 

range from simple changes in administrative procedures, refinements of the plan through plan 

maintenance, or more substantive changes through plan amendment or revision, as discussed below. 

Plan Evaluation 

Evaluation is the process of reviewing the RMPs to determine whether the BLM is implementing the plan 

decisions as expected and the associated NEPA analyses are still valid. The BLM will conduct plan 

evaluations at five-year intervals. In addition to the monitoring results (Appendix V), the BLM will 

examine many of the underlying assumptions regarding levels of activities and anticipated environmental 

consequences at the time of the five-year plan evaluation to determine if the plan objectives are being met 

or are likely to be met. The evaluation will also assess whether changed circumstances or new 

information have created a situation in which the expected impacts or environmental consequences of the 

plan are significantly different from those anticipated in the Proposed RMP/Final EIS. Through the plan 

evaluation, the BLM will make a finding of whether or not a plan amendment or plan revision is 

warranted. 

The BLM could conduct unscheduled plan evaluations to address certain unanticipated events or new 

information that would call into question the underlying analysis and decisions of the plan. 

Changes to the Approved RMPs 

Subsequent to approval of the RMPs, the BLM can make changes to the RMPs through plan maintenance, 

amendment, or revision, consistent with 43 CFR 1610.5. The appropriate mechanism for making changes 

to the RMPs depends on the scope of the changes. 

The approved RMPs may contain data, typographical, mapping, or tabular errors not apparent at the time 

of approval. Many of the decisions in the approved RMPs, such as mapping of land use allocations, are 

based on the BLM data available at the time of RMP approval. As noted above, the map of land use 

allocations accompanying the approved RMPs represents the decision on the mapped allocations. Given 

the extent and detail of the data on resource conditions that the BLM used to determine the location of the 

land use allocations, it is inevitable that there are some errors in that underlying data that, if corrected 

prior to approval of the RMPs, would have resulted in a change in mapped land use allocations. 

Regardless of any such errors in underlying data, the map of land use allocations accompanying the 

approved RMPs represents the decision on those allocations, and changes to those allocations would 
2009 | P a g e

require changes to the approved RMPs. That is, changes to the data that the BLM used to determine the 

location of a mapped land use allocation in the approved RMPs would not automatically result in changes 

to the location of the mapped land use allocation. 

For example, the BLM used existing, district-specific information on structurally-complex forests in part 

to determine the location of the Late-Successional Reserve. Future identification of patches of 

structurally-complex forest not included in the Late-Successional Reserve, in and of itself, would not alter 

the land use allocation. If the BLM identifies substantial areas of errors in the underlying data used to 

determine land use allocation locations, such that the environmental consequences would be substantially 

different than those anticipated in the Proposed RMP/Final EIS, then the BLM would engage in 

additional planning steps and NEPA procedures to make changes to land use allocations. 

For some land use allocation decisions, such as the location of the Riparian Reserve, the decision requires 

identification of features on the ground (e.g., a perennial stream) and the allocation of a corresponding 

width of Riparian Reserve. The BLM would make this identification of features and allocation of a 

corresponding width of Riparian Reserve as needed, generally through project implementation. The future 

identification of features and the allocation of a corresponding width of Riparian Reserve would represent 

implementation of the approved RMP and would not constitute a change to the approved RMP. 

The decision also requires the future allocation of some marbled murrelet occupied stands and red tree 

vole “habitat areas” to the Late-Successional Reserve, as described earlier in this section. The future 

identification of marbled murrelet occupied stands and red tree vole “habitat areas” and allocation to the 

Late-Successional Reserve would represent implementation of the approved RMP and would not 

constitute a change to the approved RMP. 

Plan Maintenance 

The BLM may maintain RMP decisions as necessary to reflect minor changes in data, consistent with 43 

CFR 1610.5-4. Plan maintenance is limited to further refining, documenting, or clarifying a previously 

approved decision. Plan maintenance would not expand the scope of resource uses or restrictions or 

change the terms, conditions, and decisions of the approved plan. The BLM may use plan maintenance to 

adjust the declaration of the annual productive capacity for sustained-yield timber production based on 

minor changes, such as updated operations inventory data. Plan maintenance does not require formal 

public involvement, interagency coordination, or the NEPA analysis required for making new RMP 

decisions. 

Plan Amendments and Revisions 

New information, updated analyses, or new resource use or protection proposals may require amending or 

revising RMPs. 

Plan amendments change one or more of the terms, conditions, or decisions of an approved RMP. Plan 

amendments are most often prompted by the need to—

 Consider a proposal or action that does not conform to the plan; 

 Implement new or revised policy that changes RMP decisions; 

 Respond to new, intensified, or changed uses on public land in the decision area; and 

 Consider significant new information from resource assessments, plan evaluations, monitoring, or 

scientific studies relevant to the effects of the RMP. 
2010 | P a g e

Plan amendments would be accompanied by either an environmental assessment or EIS, depending on the 

scope and environmental effects of the amendment. 

Plan revisions involve preparation of a new plan to replace an existing one. An RMP revision would be 

necessary if monitoring and evaluation findings, new data, new or revised policy, or changes in 

circumstances indicate that decisions for an entire plan or a major portion of the plan would no longer 

serve as a useful guide for resource management. Plan revisions would be accompanied by an EIS. 

References 

Diller, L. V. 2013. To shoot or not to shoot: the ethical dilemma of killing one raptor to save another. The Wildlife Professional 

7(2013): 54–57. http://www.fws.gov/oregonfwo/Documents/BOethics-TWP-Diller%20Winter2013.pdf. 

Diller, L.V., J. P. Dumbacher, R. P. Bosch, R. R. Bown, and R. J. Gutierrez. 2014. Removing barred owls from local areas: 

techniques and feasibility. Wildlife Society Bulletin 38(1): 211–216. 

http://www.fws.gov/oregonFWO/Species/Data/NorthernSpottedOwl/BarredOwl/Documents/Diller.et%20al.2013BOremova

l.pdf. 

USDI FWS. 2011. Revised recovery plan for the northern spotted owl (Strix occidentalis caurina). Region 1. Portland, OR. 258 

pp. http://www.fws.gov/wafwo/pdf/NSO%20Revised%20Recovery%20Plan%202011.pdf. 

---. 2013. Experimental removal of barred owls to benefit threatened northern spotted owls - Final Environmental Impact 

Statement. Portland, OR. 

http://www.fws.gov/oregonfwo/Species/Data/NorthernSpottedOwl/BarredOwl/Documents/Final_EIS.pdf.