Forest Health Monitoring: Field Methods Guide

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 EPA/620/R-94/027

 October 1994

 Forest Health Monitoring

 Field Methods Guide

 Technical Director

 Samuel A. Alexander

 U.S. Environmental Protection Agency

Environmental Monitoring and Assessment Program Center

 Research Triangle Park, NC 27709

 and

 Program Manager

 Joseph E. Barnard

 U.S.D.A. Forest Service

 U.S. Forest Service Laboratory

 Research Triangle Park, NC 27709

 Environmental Monitoring Systems Laboratory

 Office of Research and Development

 U.S. Environmental Protection Agency

 Las Vegas, NV 89119

 Printed on Recycled Paper

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 EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page ii of

 xx

 FOREST HEALTH MONITORING

 Field Methods Guide

 edited by

 Nita G. Tallent-Halsell

 Approved by

 Barnard

 'National Program Manger

 Forest Health Monitoring

Samuel A. Alexander

Technical Director

Forest Health Monitoring

 NOTICE

 The U.S. Environmental Protection Agency (EPA), through its Office of Research and 

Development

(ORD), partially funded and collaborated in the research described here, it has been peer 

reviewed by the

Agency and approved as EPA publication.

 Proper citation of this document is:

Tallent-Halsell, N.G. (ed.). 1994. Forest Health Monitoring 1994 Field Methods Guide. EPA/620/R94/027

U.S. Environmental Protection Agency, Washington, D.C.

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 EMAP Forest Monitoring, Section - F:ront, Revision 0, October, 1994, Page iii of xx

 FOREWORD

 In response to legislation and policy requirements, the U.S. Department of Agriculture (USDA)

Forest

Service (FS) and the U.S. Environmental Protection Agency (EPA) must provide periodic reports on

the

nation's forest health, status, and trends. To do this, the FS and EPA have developed a 

cooperative, multiagency monitoring activity within the framework of the EPA's Environmental Monitoring and 

Assessment

Program (EMAP).

 The Forest Health Monitoring (FHM) program is jointly managed and largely funded by the FS 

and EPA

in cooperation with other program participation. FHM partners -- participating State Forestry 

agencies, the
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U.S. Department of the Interior (USDI) Bureau of Land Management, the Tennessee Valley Authority,

and

the USDA Soil Conservation Service - provide additional financial and personnel support. 

Other

cooperators include universities and three additional agencies: USDI's U.S. Fish and Wildlife 

Service, U.S.

Geological Survey, and the National Park Service. The National Association of State Forester 

provides

essential program support, guidance, and assistance.

 The FHM program was developed in response to increasing concern for the health of the 

nation's

forests in light of the potential effects of atmospheric pollutants, global climate change, and a

variety of

insect, disease, and other stressors. To help address these concerns, the FHM program is 

designed to

assist resource managers and policy makers in managing the nation's forest resources, allocating 

funds

for research and development, and evaluating environmental policy for forest resources.

 The specific objectives of this program are to:

 1. Estimate with known confidence the current status, changes, and trends in selected 

indicators of

 forest ecosystem condition on a regional basis;

 2. Identify associations between changes of trends in indicators of forest ecosystem 

condition and

 indicators of natural and human-caused stressors, including changes in forest extent

and

 distribution;

 3. Provide information on the health of the nation's forest ecosystems in annual 

statistical summaries

 and periodic interpretive reports for use in policy and management decisions;

 4. Identify mechanisms of ecosystem structure and function through long-term 

monitoring of

 ecosystem processes at intensively monitoring sites representing major forest 

ecosystems;

 5. Improve the effectiveness and efficiency of forest health monitoring through directed 

research; and

 6. Integrate forest health monitoring with other EMAP resource groups in order to 

complete multi-

 ecosystem assessments.

 During the past three years, the agencies participating in the FHM program have worked to 

develop

a national sampling design to identify and develop indicators that can be used to assess forest 

health, and

to begin implementing data collection from a national sample of monitoring sites. The 

organizational

structure for planning, managing, and implementing the program has evolved gradually and is 

still being

developed. An overview of the current organizational structure is provided in Figure 1.

 in

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 Forest Health Monitoring field work in 1994 will include detection monitoring activities 

in the

northeastern and northcentral, southeastern and western states, including Maine (ME), New 

Hampshire

(NH), Vermont (VT), Massachusetts (MA), Connecticut (CT), Rhode Island (Rl), New Jersey (NJ), 

Delaware

(DE), Maryland (MD), Virginia (VA), Minnesota (MN), Wisconsin (Wl), Michigan (Ml), Georgia 

(GA),

Alabama (AL), Colorado (CO), and California (CA). Additional FHM field activities will be 

occurring in

Washington (WA) and Oregon (OR) as the Pacific Northwest Pilot Study (PNW-PS).

 The FHM Field Methods Guide documents all field measuring activities and collection 

being

implemented across the nation. Note, a number of regional variations do exist. Regional versions 

of this

field guide contain only those activities being implemented in that region. The FHM Field 
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Methods Guide

are integral parts of the FHM Quality Assurance Project Plan (Cline (ed.) 1994).

 The purpose of this guide is to document and encourage standardization of data collection 

procedures

for all 1994 FHM field activities. The following sections of this guide contain detailed 

instruction for locating

and establishing sample plots and for correcting and recording observational and measurement data

for

individual indicators in detection monitoring. In addition, it includes a general field 

logistics plan and a

safety plan identifying potential field hazards, recommended precautions, and accident 

reporting

procedures.

 IV

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 National Program Manager

 USDA Forest Service

 Joseph E. Barnard

Technical Director

 U.S. EPA, EMAP

 Samuel A. Alexander

 FHM Deputies

 State/Federal

 Technical Groups

 Regional

 Coordinators

 Cooperating Federal

 Agency Coordinators

 BLM;SCS; TVA

 Program Area

 Coordinators

 Indicator Leads

Figure 1. Forest Health Monitoring organization structure.

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 Table of Contents

Section Title

 Page

Notice »

Contributors xii

Acronyms xiv

Acknowledgements xv

Glossary xvi

Section 1. Site Condition, Growth, and Regeneration 1 of 86

1.0 Quick Reference Tally PDR Screens . 2 of 86

1,1 Overview 9 of 86

1.2 Sample Collection, Preservation, and Storage 10 of 86

1.3 Equipment and Supplies 11 of 86

1.4 Calibration and Standardization 12 of 86

1.5

1.6

Quality Assurance 12 of 86

Procedures 19 of 86

1.7 References 85 of 86

Section 2. Crown Condition Classification 1 of 23

2.1 Overview 2 of 23

2.2 Sample Collections, Preservation, and Storage 6 of 23

2.3 Equipment and Supplies 7 of 23

2.4 Calibration and Standardization 7 of 23

2.5 Quality Assurance 10 of 23

2.6 Procedure 11 of 23

2.7 References 23 of 23

Section 3. Damage and Catastrophic Mortality Assessment 1 of 22

3.0 Quick Reference 2 of 22

3.1 Overview 3 of 22

3.2 Sample Collection 4 of 22

3.3 Equipment and Supplies 4 of 22

3.4 Calibration and Standardization 4 of 22

3.5 Quality Assurance 4 of 22

3.6 Procedures 5 of 22
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3.7 References 19 of 22

Appendix 3.1 Catastrophic Mortality Assessment 20 of 22

Section 4. Photosynthetically Active Radiation (PAR) Indicator 1 of 18

4.1 Overview 2 of 18

4.2 Sample Collection, Preservation, and Storage 4 of 18

4.3 Equipment and Supplies 4 of 18

4.4 Calibration and Standardization 4 of 18

4.5 Quality Control 7 of 18

4.6 Procedures 8 of 18

4.7 References 18 of 18

 VI

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Section 5. Vegetation Structure 1 of 12

5.1 Overview 2 of 12

5.2 Plant Sample Collection and Handling 3 of 12

5.3 Equipment and Supplies 5 of 12

5.4 Calibration and Standardization 5 of 12

5.5 Quality Assurance 5 of 12

5.6 Procedure 6 of 12

5.7 References 12 of 12

Section 6. Ozone Bioindicator Plants 1 of 21

6.1 Overview 2 of 21

6.2 Sample Collection, Preservation, and Storage 3 of 21

6.3 Equipment and Supplies 3 of 21

6.4 Calibration and Standardization 4 of 21

6.5 Quality Assurance 4 of 21

6.6 Procedure 7 of 21

6.7 References 16 of 21

Appendix 6.A Ozone Bioindicator Plants 17 of 21

Section 7. Lichen Communities 1 of 11

7.1 Overview 2 of 11

7.2 Sample Collection, Preservation, and Storage 3 of 11

7.3 Equipment and Supplies 6 of 11

7.4 Calibration and Standardization 6 of 11

7.5 Quality Assurance 6 of 11

7.6 Procedure '. 9 of 11

7.7 References 11 of 11

Section 8. Field Logistics 1 of 12

8.1 Overview 2 of 12

8.2 Training 2 of 12

8.3 Field Logistics 3 of 12

8.4 Data Transfer and Sample Handling 9 of 12

8.5 .Debriefing 12 of 12

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 Appendices

Appendix A U.S. Tree Species Codes 1 of 8

Appendix B State and County FIPS Codes 1 of 9

Appendix C Forest Type Descriptions 1 of 10

Appendix D Land Use Classifications ' 1 of 3

Appendix E Safety Plan 1 of 10

 Figures

1-1 National FHM plot layout is designed around four points (subplot centers) 22 of 86

1-2 Terrain position 39 of 86

1-3 Boundary delineation 42 of 86

1-4 Distinctions among trees less than 5.0 in. (12.7 cm) DBH 45 of 86

1-5 Where to measure diameter breast height in a variety of situations 52 of 86

1-6 Points of diameter measurement on woodland trees 54 of 86

1-7 Relative crown positions of dominant (D), codominant (C),

 intermediate (I), and overtopped (O) trees 64 of 86

1-8 Location of four subplot offset points 79 of 86

1-9 Locating offset point #3 , 79 of 86

1-10 Locating other subplot centers 80 of 86

1-11 Locating offset points from each other on the same subplot 81 of 86
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1-12 Locating the microplot center from subplot offset points 82 of 86

1-13 Referencing trees to offset points 83 of 86

1-14 Estimating boundaries from offset points 83 of 86

1-15 Subplot limiting distances from offset point #4 84 of 86

2-1 Crown density - foliage transparency card 8 of 23

2-2 Crown grid 9 of 23

2-3 Sapling live crown ratio determination examples 13 of 23

2-4 Crown rating example 15 of 23

2-5 Crown rating example, hardwood 16 of 23

2-6 Crown rating example, pine 17 of 23

2-7 Crown diameter determination 18 of 23

2-8 Live crown ratio determination examples 20 of 23

3-1 Location codes for the damage indicator 6 of 22

3-2 The damage runs from stump to crownstem 7 of 22

3-3 A canker which exceeds threshold 13 of 22

3-4 Multiple damage in "stump" and lower bole 14 of 22

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 Figures Cont'd

4-1 PAR sampling scheme 3 of 18

4-2 Solar declination (D) in degrees 11 of 18

4-3 Ambient station setup 12 of 18

5-1 Plant specimen label used for vegetation structure indicator 4 of 12

5-2 Portable data recorder screen 4 of 12

5-3 Layout of quadrats on each subplot 7 of 12

5-4 Collapsible 1 m2 quadrat sampling frame and placement of telescoping pole

 on quadrat 8 of 12

6-1 Example of a well drawn map locating the bioindicator site for a permanent detection

 monitoring plot 9 of 21

7-1 Conceptual model of the lichen community indicator : 2 of 11

7-2 Plot packing slip for lichen communities 4 of 11

7-3 Form used for mailing lichen community specimens, one form per box 5 of 11

7-4 Lichen sampling area 10 of 11

 IX

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 Tables

1-1 Plot-Level Note Screen 2 of 86

1-2 Plot Identification Screen 2 of 86

1-3 Condition Classification Screen 2 of 86

1-4 Site-Tree Screen 3 of 86

1-5 Point-Level Descriptors Screen 3 of 86

1-6 Boundary Delineation Screen 4 of 86

1-7 Understory Vegetation Screen 4 of 86

1-8 Microplot Seedling Screen 4 of 86

1-9 Microplot Sapling Screen 5 of 86

1-10 Subplot Tree Screen 6 of 86

1-11 Full-Hectare Boundary Screen (CA/PNW PS Only) 7 of 86

1-12 Full-Hectare Tree Screen (CA/PNW PS Only) 7 of 86

1-13 Full-Hectare Tree Mortality Screen 8 of 86

1-14 Plot-Level Note Screen - Nonforested/Access Denied/Dangerous Plots 8 of 86

1-15 Plot Identification Screen - Nonforested/Access Denied/Dangerous Plots 8 of 86

1-16 Site Condition, Growth, and Regeneration Measurement Quality Objectives 12 of 86

1-17 English and Metric Slope Distance Correction Factors 38 of 86

1-18 Valid Micropiot Tree History Codes by Measurement Types 49 of 86

1-19 Valid Subplot Tree History Codes by Measurement Types 58 of 86

1-20 Valid Full-Hectare Tree History Codes by Measurement Types 69 of 86

1-21 Tree Sizes Sampled for Mortality by Plot Type 72 of 86

1-22 Distances and Azimuths Between Subplots 2-4 80 of 86

1-23 Distances and Azimuths Between Offset Points 81 of 86

1-24 Directions from Offset Points to Microplot Centers 82 of 86

1-25 Limiting Distances to 18 Points on the Subplot 84 of 86

2-1 PDR Prompt Codes 5 of 23

2-2 Crown Diameter Codes 6 of 23

2-3 Live Crown Ratio, Crown Density, Crown Dieback, and
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 Foliage Transparency Codes 6 of 23

2-4 Crown Classification Measurement Quality Objectives 10 of 23

3-1 Damage Measurement Quality Objectives 4 of 22

5-1 PDR Screens and Codes 9 of 12

6-1 Measurement Quality Objectives 5 of 21

7-1 Measurement Quality Objectives and Their Method of Assessment 7 of 11

7-2 Summary of 1993 SE and SAMAB Demonstrations

 Lichen Community Data Quality 9 of 11

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 Tables Cont'd

8-1 FHM Crew Types, Definitions, and Regions or States Implementation 2 of 12

8-2 FHM Key Positions per Region and Crew Type 3 of 12

8-3 Field Work Time Allocation 4 of 12

8-4 Suggested Work Flow Pattern (Forester and Botanist Crew Working Together

 on 1/4 plot) 5 of 12

8-5 Suggested Work Flow Pattern (Forester Crews - Mt2 Plots) 5 of 12

8-6 Suggested Work Flow Pattern (Forester Crews - Mt1/3 Plots/No PAR, Lichens

 or Vegetation Measurements Being Collected) 5 of 12

8-7 Suggested Work Flow Pattern (1/4 Crew (CO)) . 5 of 12

8-8 Suggested Work Flow Pattern (1/4 Crew (CA & PNW Pilot Study)) 6 of 12

 XI

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 Contributors

(listed alphabetically by organization, location, name, and contribution, lead author listed in 

bold)

Colorado State Forest Service, 214 Forestry Building, Colorado State University, Fort Collins, 

CO

80523

M. Schomaker (Damage and Mortality Assessment)

Illinois Wesleyan University, Department of Biology, Bloom, IL 61702

J. Dey (Lichen Community)

Lockheed Environmental Systems & Technologies Company, 980 Kelly Johnson Dr., Las Vegas, NV

89119

R.L. Tidwell (Logistics & Safety)

Oregon State University, Dept. of General Science, Weniger355, OSU, Corvallis OR 97331-6505

B.M. McCune (Lichen Community)

Tennessee Valley Authority, Ridgeway Road, Forestry Building, Morris, TN 37828

N.S. Nicholas (Logistics & Safety)

University of Massachusetts, Dept. of Forestry and Wildlife Manage., Amherst, MA 01003

G. Smith (Ozone Bioindicator Plants)

USDA Forest Service, Anchorage Forest Sciences Lab, 201 e. 9th, Suite 303, Anchorage, AK 99501

V.J. LaBau (Site Condition, Growth and Regeneration)

USDA Forest Service, Forest Inventory and Analysis, 200 Weaver Blvd, Southeastern Experiment

Station, Asheviile, NC 29804

W. Bechtold (Site Condition, Growth and Regeneration)

B. Brantley (Ozone Bioindicator Plants)

USDA Forest Service, Forest Pest Management, RT 3 Box 1249A, Asheviile, NC 28806

R.L. Anderson (Crown Condition Classification)

W. Hoffard (Damage and Mortality Assessment)

USDA Forest Service, U.S. Forest Service Lab, 3041 Comwallis Rd, Research Triangle Park, NC

27709

J. Barnard (Foreword)

K.W. Stolte (Crown Condition Classification)

USDA Forest Service, Northeastern Area State and Private Forestry, Concord Mast Rd., Durham, NH

03824

S. Cox (Damage and Mortality Assessment)
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I. Miller (Crown Condition Classification)

M. Miller-Weeks (Damage and Mortality Assessment)

USDA Forest Service, Northeastern Area, State and Private Forestry, 5 Radnor Corporation Center,

100 Matsomford Rd., Suite 200, Radnor, PA 19087

W. Burkman (Crown Condition Classification & Damage and Mortality Assessment)

 XII

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USDA Forest Service, Northeastern Area, State and Private Forestry, 1992 Folwell Ave., St. Paul,

MN

55108

M. Mielke (Damage and Mortility Assessment)

USDA Forest Service, Forest Science Lab, 507 25th St. Ogden, UT 84401

W. McLain (Site Condition, Growth, and Regeneration)

P. Rogers (Site Condition, Growth, and Regeneration & Glossary)

USDA Forest Service, Research Lab, 5985 Highway K, Rhinelander, Wl 54501

J.G. Isebrands (PAR)

S. Steele (PAR)

J. Van Cleve (PAR)

USDI Bureau of Land Management, Oregon State Office, c/o U.S. EPA, EMSL-LV, 944 E. Harmon Ave.

Las Vegas, NV 89119

S. Cline (Vegetation Structure Indicator)

N. Tallent-Halsell (Logistics)

USDI Bureau of Land Management, Oregon State Office, c/o U.S. EPA, Environmental Reseach

Laboratory, 200 S.W. 35th St. Corvallis, OR 97333

M. Stapanian (Vegetation Structure Indicator)

U.S. EPA, U.S. Forest Service Lab, 3041 Cornwallis Rd, Research Triangle Park, NC 27709

S.A. Alexander (Foreword)

 XIII

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 ACRONYMS

3-D - three-dimensional

MS - atomic absorption spectrometry

BLM - Bureau of Land Management

DBH - diameter at breast height

DRC - diameter at root collar

EMAP - Environmental Monitoring and Assessment Program

EMSL-LV - U.S. EPA Environmental Monitoring Systems Laboratory in Las Vegas

EPA - Environmental Protection Agency

FIA - Forest Inventory and Analysis

FS - Forest Service

FY - fiscal year

FHM - Forest Health Monitoring

GIS - Geographic Information System

GMT - Greenwich Mean Time

GPS - Global Positioning System

ICP-OES - inductively coupled plasma-optical emission spectroscopy

ID - identification

IM - information management

IRC - independent regional coordinator

MEI - maximum expression of injury

MLRA - major land resource area

MQO - measurement quality objective

MSDR - measurement system detection reference samples

MSFD - measurement system field duplicate samples

NCSS - National Cooperative Soil Survey

PAR - photosynthetically active radiation

Pb - the element lead

PC - personal computer

PDR - portable data recorder

PL - Preparation Laboratory

PVC - polyvinyl chloride

QA • - quality assurance

QC - quality control

SA - selective availability

SCS - Soil Conservation Service
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SOP - standard operating procedure

Sr - the element strontium

USDA - United States Department of Agriculture

USDI - United States Department of the Interior

USGS - United States Geological Survey

TVA - Tennessee Valley Authority

XRF - X-ray fluorescence spectroscopy

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 ACKNOWLEDGEMENTS

 Special appreciation goes to the following persons: E. Eastman for her assistance with the 

Foreword;

C. Chojnacky, C. Liff, W. McLain, P. Rogers, C. Scott, S. Solano and C. Bylin for their 

assistance with

Site Condition, Growth, and Regeneration; J. Van Cleve for his assistance with PAR; R. O'Brien 

and F.

Peterson for their assistance with the Vegetation Structure indicator; J. Peck, K. Heiman, S. 

Will-Wolf, D.

Cassell, R. Rosentreter, A. Debolt and numerous anonymous reviewers for their suggestions on the 

Lichen

Community method and manuscript. K. Stolte instigated the Lichen Community method by declaring 

the

need for a user-friendly method for studying lichen communities and initially sponsoring its 

development.

The rest of the FHM staff has been helpful, and the Lichen Community staff appreciate their 

efforts; D.L.

Cassell and J. Hazard for their overall statistical support; B. Conkling and F. Lopez for their 

overall

assistance and support; S. Burns for her excellent graphics assistance; and the staff of Applied

Technology

Associates, Las Vegas, NV, without their valuable and expert word processing, graphics, and 

editing

support this document would never have been completed.

 The following individuals are acknowledged for their review and subsequent suggestions and 

comments

on the methods and manuscript: S. Abboud (Alberta Research Council, Alberta, CAN), S. Alexander 

(U.S.

EPA), B. Anderson (USDA FS), C. Bylin (USDA FS), J. Bofinger (New Hampshire Division of Forest 

and

Lands), G. Canterbury (University of Montana), D. Cassell (USDI BLM), S. Cline (USDI BLM), G. 

Collins

(U.S. EPA), B. Conkling (North Carolina State University), J. Dale (USDA FS), W. Dorsey 

(Maryland Dept.

of Natural Resources), S. Draggan (U.S. EPA), A. Gillespie (USDA FS), J. Hyland (Alabama 

Forestry

Commission), W. Kinney (U.S. EPA), L. Kirkland (U.S. EPA), W. McLain (USDA FS), A. Pitchford

(U.S.

EPA), R. Rhoades (USDA FS), P. Rogers (USDA FS), S. Solano (USDA FS), R. Schonbrod (U.S. EPA),

T. Scherbatskoy (University of Vermont), M. Stapanian (USDI BLM), C. Thomas (USDA FS), H. Trial 

(Maine

Forest Service), J. Vissage (USDA FS), L. Williams (U.S. EPA), S. Wilmont (Vermont Dept. of 

Forests,

Parks and Recreation), and numerous anonymous reviewers.

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 GLOSSARY

Ambient Station - The place where the quantum sensors are set up to measure incoming light in a 

forest

opening or unshaded area.

Annular Subplot - The area ranging from 24.0 ft (7.32 m) and 58.9 ft (17.95 m) around each 

subplot center,

designated for potentially destructive sampling procedures. Some destructive sampling is 

restricted to a

smaller area within the annular plot (45.0-58.9 ft) to avoid damaging the environment at the 

subplot

perimeter.

Baseline - A method employed in plot establishment to determine actual photo scale in the 
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vicinity of the

plot by measuring the distance on the ground between two visible points on the photo. See 

Section 1, Plot

Establishment for a step by step procedure.

Beam Fraction - The percentage of light that is direct sunlight, not diffuse. It is a measure 

of cloudiness.

Bioindicators - Plant species that are sensitive to ozone and exhibit visible symptoms of 

injury.

Ceptometer - An instrument used to measure PAR under canopy.

Condition Boundary - A boundary established by the field crew to delineate between two distinct 

condition

classes encountered on a plot (see Condition Class). Multiple condition boundaries may be 

established

by a field crew. Boundaries should always be documented on the plot sketch map. 

Additionally,

boundaries which cross subplots or microplots are further documented in the PDR.

Condition Class - A spatial representation of present environmental conditions on the plot in 

terms of five

key land cover variables: Land Use, Forest Type, Stand Origin, Stand Size, and Past 

Disturbance. New

condition classes are assigned when one or more of these variables changes. Except for urban 

land uses,

a condition must be at least an acre in size to be recognized as a distinct condition. 

Condition classes are

numbered sequentially as they are encountered on the plot and referenced by that same code 

on

subsequent encounters.

Cover (canopy cover) - The area described by individual plant canopies within or overlapping the

sampling

area. Canopies are visualized as polygons that are vertically projected to the ground surface to

determine

the percent of the quadrat area (1 m2) covered by each plant species in the stratum (see also 

Crown

Cover).

Crown - The foliated portion of a tree or other plant.

Crown Cover - An area percentage of ground obscured by plant cover when viewed from above. When

associated with a specific area (i.e., a plot or quadrat), stems of plants do not necessarily 

have to fall within

that area for portions of the plant to be counted.

Crustose - A crust-like growth form of lichen that is tightly appressed to the substrate, like

paint, and

generally attached by all of the lower surface.

Dead Tree - Any dead tree standing upright and being greater than 5 inches DBH. Stumps or broken

trees

less than 4.5 feet in height are not recorded as dead trees.

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DBH - Diameter at Breast Height. Normally this diameter measurement is taken 4.5 ft (1.37 m) 

above the

forest floor on the up hill side of the tree. Adjustments are made for bole irregularities (see 

DBH,

Section 1).

Destructive Sample - Any sampling method which involves sampling activities that are potentially 

damaging

to the vegetation from which the samples were extracted.

DRC - Diameter at Root Collar. This was designed as a multi-stem equivalent of the DBH whereby

all

stems of woodland species trees (marked by "ww" in the species list) are measured at their base

and

aggregated into a single value using the formula shown in the DRC section of the field guide.

EMAP - Environmental Monitoring and Assessment Program. A program within the Environmental

Protection Agency set up to undertake long term monitoring and evaluation of ecosystems. EMAPForests
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with FHM form one of multiple ecosystems that fall under the EMAP umbrella.

FHM - Forest Health Monitoring. A National program for monitoring the long term health of the

nation's

forest ecosystems. This program is sponsored jointly by the Environmental Protection Agency and 

the U.S.

Forest Service in cooperation with the National Association of State Forester and other state, 

federal, and

private organizations.

FIA - Forest Inventory and Analysis. A program within U.S. Forest Service Research assigned the 

task

of measuring and analyzing forest resources at the State, Regional, and National levels.

Foliose - A "leaf-like" growth form of lichen that is essentially two-dimensional, and is 

usually made up of

repeatedly branching lobes, and has a definite upper and lower surface.

Forest - Land which is at least 10% stocked with any combination of trees found in the FHM 

species list

AND at least one acre in size. Adjacent nonforest inclusions less than one acre in size are 

considered

forest land.

Forest Type - A grouping, or association, of species which comprise plurality of stocking on a 

given site

at the present time. Forest type is most often selected from the species which make up the 

forest canopy,

not the understory. In cases of recent disturbance, forest type may be determined from the 

current

regeneration.

Fruticose - A three-dimensional growth form of lichen including forms that are pendulous and 

stringy,

upright, or shrub-like.

Hex - A 40° km2 hexagon which surrounds the sample point. The data collected on the plot, in 

many

cases, are expanded to represent the entire area of the hexagon. This hexagon is the 

fundamental unit

for the EMAP sample grid.

Hex Number - A unique seven digit code representing the sample plot and ail data collected on 

that plot.

Improved Road - This is a road that is graded, ditched, or otherwise maintained as a permanent

travel

route. For the purpose of FHM field plots, improved roads will be considered an urban land use 

because

reforestation is actively being prevented.

Indicator - A characteristic of the environment that, when measured, quantifies the magnitude of

stress,

habitat characteristics, degree of exposure to the stressor, or degree of ecological response 

to the

exposure. Indicators may be of a biotic or abiotic nature.

 XVII

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 EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page xviii of xx

Interveinal - Between veins on the leaves of plants. In terms of bioindicators, this is the 

area of the upper

leaf surface where symptoms of ozone injury are most often observed.

Land - This includes (1) areas of dry ground temporarily or partly covered by water, such as 

marshes,

swamps, and river flood plains; (2) streams, sloughs, estuaries and canals less than 120 ft in 

width; and

(3) lakes, reservoirs, and ponds smaller than 1 acre in size. Land/Water boundaries for larger 

bodies of

water (> 1 acre) should always be established at the high water mark.

Leaf Area Index (LAI) - The canopy leaf area per unit of ground area. It is an index of forest 

health and

productivity.

Lichen - A lichen is a symbiotic association between a fungus and a photosynthetic partner 

(either green
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algae or cyanobacteria).

Lichen Plot - The area to be sampled for lichen communities. For standard FHM plots, the lichen 

plot is

a circular area with a 120-foot radius centered on subplot 1, but excluding the four subplots. 

The area of

the lichen plot is 0.378 hectares or 0.935 acres.

Macrolichen - Foliose and fruticose lichens.

Microplot - A circle offset 90° and 12 ft (3.66 m) from each subplot center for the purpose of 

measuring

understory vegetation and regeneration trees (i.e., saplings and seedlings). The microplot is 

6.8 ft (2.07

m) in radius. It is .offset to minimize trampling damage on the microplot.

Monitoring - The collection of information over time to determine the effects of resource 

management and

to identify changes in natural systems.

Mortality Tree - A standing or downed tree (1.0 inches DBH/DRC a larger) that was sampled at the

previous inventory, but no longer has any living tissue above 4.5 ft.

Nonforest - (see also Forest Land) This is land that (1) has historically not supported 

forests (e.g., barren,

alpine tundra); (2) was formerly forested, but has been converted to a nonforest land use (e.g.,

cropland,

lawn, or improved pasture);'or (3) presently meets the stocking requirements for forest land, 

but human

activity on that land prevents natural succession of the site (e.g., golf courses, cemeteries, 

urban parks and

picnic grounds, and forested home sites with lawns). Other nonforested conditions include a land

use or

corridor of any width maintained by humans as a long-term nonforested site. Examples of these 

conditions

include right-of-ways for improved roadways, rail lines, canals, powerlines (above and below 

ground), and

pipelines.

Non-Stocked Forest Land - Formerly forested land which (1) recently met the stocking and/or 

regeneration

requirements of forested land; (2) does not meet those requirements because trees have 

temporarily been

removed or destroyed; and (3) has the potential to regenerate to forest because there are no 

conflicting

land uses. Examples of non-stocked forests include incidents of recent clearcutting, fire, or 

windthrow.

Off-plot - The area outside of the sample hectare (186.2 ft radius from plot center).

Off-frame - Generally refers to FHM activities which take place off of the network of regular 

field plots, and

not associated with any particular hex centers. Off-frame work is usually done at experimental

sites in

conjunction with indicator development and testing.

On-Plot - The area within the sample hectare (186.2 ft radius from plot center). See Off-Plot.

 xviii

-------

 EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page xix of xx

Ozone - A gaseous air pollutant that causes injury to sensitive plants, also known as 

bioindicators. Ozone

is taken in through the stomata of susceptible plants causing visible damage to the upper leaf 

surface.

PAR - Photosynthetically Active Radiation. The portion of light spectrum that plants use for 

photosynthesis.

FHM uses the percent transmitted PAR (ratio of PAR under the canopy to the ambient, incoming PAR

at

the site) and the calculated leaf are a index.

Pathogen - An organism capable of causing disease.

PDR - Portable Data Recorder. The PDR is the primary field tool used by crews to record and 

download

data for future analysis.
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Phenological Status - Presence and condition of flowers, fruits, and leaves.

Plot Center - The center point of the FHM field sample, also known as subplot #1, point #1, or 

location

center. •

Quadrat Frame - A collapsible square frame made of plastic pipe that defines the perimeter of a 

quadrat.

Each side of the frame is 1 m long.

Quantum Sensor - A device that measures the quantity of light reaching its surface.

Remeasurement - Any plot visit, excepting the initial plot establishment, conducted for the 

purpose of

gathering comparative data to previous visits. Multiple remeasurements allow analysts to assess 

changes

in forest conditions over time.

Reserved Forest Land (Timberland) - Land reserved from wood products utilization by statute or

administrative designation. Some examples of reserved forest land are National Parks, wilderness 

areas,

state, county, municipal, and other lands expressly prohibiting wood product extraction.

Reference Point (RP) - A prominent tree, or other landmark, which is easily detected on an 

aerial

photograph and on the ground. The reference point (also called Starting Point) is most commonly

used

as the point of origin for chaining into the plot center. Remeasurement crews begin their 

search for the

plot center by first locating the reference point.

Sapling - A live tree at least 1.0 inch (2.54 cm) and less than 5.0 inches (12.7 cm) DBH/DRC.

Appendix A lists all FHM tree species measured for both timberland and woodland.

Seedling - A live tree less than 1.0 inches DBH/DRC and greater that 12 inches in height is a 

seedling.

Trees less than 12 inches in height are considered seedlings as part of understory vegetation 

coverage

estimate. Appendix A lists all FHM tree species measured for both timberland and woodland.

Specimen Tree - Trees systematically selected by the field crew within the annular plot 

expressly for the

purpose of destructive sampling.

Specimen, Vegetation - A sample of an unknown that is collected pressed and shipped to a 

herbarium for

identification. Vegetation specimens are collected outside of the quadrats.

Starting Point (SP) - See Reference Point.

 xix

-------

 EMAP Forest Monitoring, Section - Front, Revision 0, October, 1994, Page xx of xx

Stipple - Pigmented spots (up to a few millimeters in diameter) suggesting ozone damage to 

bioindicator

plants. Stipples are generally observed on the upper surface of leaves.

Stocking - An expression of the extent to which growing space is effectively utilized by trees.

Stratum - (plural: strata) A class of vegetation height in which vegetation structure 

measurements are

obtained (e.g., 0-2 ft, 2-6 ft, 6-16 ft, and > 16 ft). Vegetation measurements are obtained 

within each

stratum in each quadrat.

Subplot - The basic sampling unit for trees 5.0 in DBH and larger on an FHM plot. Each of four 

subplots

is 1/24 acre (1/60 hectare) in area, and 24.0 feet in radius (7.32 meters). Subplot 1 is 

located at the plot

center, while the remaining three subplots are located 120 ft (36.6 cm) and 360° (#2), 120° 

(#3), and 240°

(#4) from the plot center (see Figure 1.1).

Substrate (ground substrate) - Organic and inorganic material on the ground within the 

vegetation quadrat.

Examples include: mineral soil, rock, water, dead wood (> 10 cm), litter and branches (< 10 

cm), exposed
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roots, roads, dung, and trash.

Timberland Species - These are tree species commonly having a dominant single stem at the base 

which

are traditionally measured at breast height. Appendix A lists all FHM tree species measured for

both

timberland and woodland.

Tree - Any tree at least 5.0 inches (12.7 cm) DBH/DRC. See Timberland and Woodland Species for 

further

clarification.

Unimproved Road - A road which is not periodically maintained as a transportation route (see 

Improved

Road). An unimproved road is considered the same condition as the area surrounding it. If the 

road acts

as a boundary between forest and non-forest conditions, it is considered a transition zone in 

which a forest

may reestablish itself, and is therefore part of the adjacent forested condition.

Voucher Leaf Samples - Three leaves with ozone injury that are collected from a bioindicator 

plant,

pressed, and mailed to the national ozone indicator lead (Gretchen Smith).

Water- As a land use classification, water is defined as streams, sloughs, estuaries, and canals

more than

120 feet (36.6 m) in width; and lakes, reservoirs, and ponds more than 1 acre in size.

Witness Trees - Trees to which distances and azimuths are recorded for the purpose of 

relocating a

particular point on the ground. In addition to plot centers, witness trees may be used to 

monument starting

points and intermediate points along the course to plot center.

Woodland - Forest land with 10 percent or more crown cover in (1) woodland species, or (2) 

timber species

and woodland species, but less than 5 percent crown cover in timber species; or forest land with

sufficient

woodland species reproduction (minimum of 40 seedlings/saplings per acre).

Woodland Species - These are tree species commonly having multiple stems near their base, or 

those

which have a typical morphology not conducive to measuring diameters a breast height. These 

species

are measured using a diameter at root collar formula (DRC), which accounts for multiple stems 

originating

at a single base, as a DBH equivalent. Appendix A lists all FHM tree species measured for both 

timberland

and woodland.

 xx

-------

 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 1 of 86

 Section 1. Site Condition, Growth, and Regeneration

Section/Title

1.0 Quick Reference Tally PDR Screens 2 of 86

1.1 Overview 9 of 86

 1.1.1 Scope and Application 9 of 86

 1.1.2 Summary of Method 9 of 86

 1.1.3 Interferences 10 of 86

 1.1.4 Safety 10 of 86

1.2 Sample Collection, Preservation, and Storage 10 of 86

1.3 Equipment and Supplies 11 of 86

1.4 Calibration and Standardization 12 of 86

1.5 Quality Assurance 12 of 86

 1.5.1 Measurement Quality Objectives 12 of 86

 1.5.2 Method Performance 19 of 86

 1.5.3 Corrective Action 19 of 86

1.6 Procedures 19 of 86

 1.6.1 Permanent Plot Design and Forest Plot Establishment 21 of 86

 1.6.1.1 Plot Design "! 21 of 86

 1.6.1.2 Forest Plot Establishment 21 of 86

 1.6.2 Plot-Level Data 25 of 86

 1.6.2.1 Plot-Level Notes 25 of 86

 1.6.2.2 Plot Identification 25 of 86

 1.6.2.3 Condition Classification 29 of 86

 1.6.2.4 Site-Tree Data 34 of 86
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 1.6.3 Point-Level Area Descriptors 37 of 86

 1.6.3.1 Point Description 37 of 86

 1.6.3.2 Boundary Delineation 41 of 86

 1.6.4 Microplot Understory Vegetation 44 of 86

 1.6.5 Microplot Tree Data 46 of 86

 1.6.5.1 Seedlings 46 of 86

 1.6.5.2 Saplings 48 of 86

 1.6.6 Subplot Tree Data 57 of 86

 1.6.7 Full-Hectare Plots (CA/PNW PS only) 66 of 86

 1.6.7.1 Full-Hectare Boundary Delineation (CA/PNW PS Only) .- 66 of 86

 1.6.7.2 Full-Hectare Large-Tree Cruise (CA/PNW PS Only) 68 of 86

 1.6.7.3 Full-Hectare Mortality Plot (CA/PNW PS Only) 72 of 86

 1.6.8 Nonforest/Access Denied/Dangerous Plots 75 of 86

 1.6.8.1 Plot-Level Notes 75 of 86

 1.6.8.2 Plot Identification 75 of 86

 1.6.9 Offset Procedures 78 of 86

1.7 References 85 of 86

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 2 of 86

1.0 Quick Reference Tally PDR Screens

Table 1-1. Plot-Level Note Screen (Subsection 1.6.2.1)

Measurement Variable

Notes

PDR Prompt

(Notes)

Meas. Meas. Meas. Page

Type 1 Type 2 Type 3

x x, D Sec. 1, p.25

Table 1-2. Plot Identification Screen (Subsection 1.6.2.2)

Measurement Variables

State

County

Hexagon Number

Plot Number

Project

QA status

Crew Type

Measurement Type

Old Plot Status

Current Plot Status

Month

Day

Year

Elevation

Tally! -TallyS

Interim Disturbance 1-3

Interim Disturbance Year 1-3

'Only on newly forested plots.

Table 1-3. Condition Classification

Measurement Variables

Condition Class Change

Condition Class

Land Use Class

Forest Type

Stand Origin

Stand Size

Past Disturbance 1

Disturbance Year 1

Past Disturbance 2

Disturbance Year 2

Past Disturbance 3

Disturbance Year 3

Previous Stand Age

Stand Age

PDR Prompt

(State)

(Cnty)

(Hex Num)

(Plot Num)

(Project)

(QA Stat)

(CrewTyp)
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(MeasTyp)

(OldStat)

(CurStat)

(Month)

(Day)

(Year)

(Elev)

(Tally!.. .5)

(Dstrbl...3)

(DstYrL.3)

Screen (Subsection 1.6.2.3)

PDR Prompt

(CC_Chg)

(CndCIs)

(LU CIs)

(ForTyp)

(StdOrg)

(StdSize)

(Dstrbl)

(DstYrl)

(Dstrb2)

(DstYr2)

(DstrbS)

(DstYrS)

(PrAge)

(StAge)

Meas. Meas. Meas.

Type 1 Type 2 Type 3 Page

x D D 25,App.B

x D D 25,App.B

x D D 25

x D D 25

x x x 25

x x x 25

x x x 26

x x x 26

D D 26

x x x 26

x x x 27

x x x 27

x x x 27

x x1 27

x x x 27

x 28

x 28

Meas. Meas. Meas. Page

Type ! Type 2 Type 3

x 30

x x1 30

x x1 30,App.D

x x1 30,App.C

x x' 31

x x' 31

x x 3!

x x 32

x x 32

x x 32

x x 32

x x 32

D 32

x x 32

'These data are supplied on computer-generated plot maps.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 3 of 86

Table 1-4. Site-Tree Screen (Subsection 1.6.2.4)

Measurement Variables

Tree Type

Site-Tree History

Tree Number

Point Number

Previous Condition Class

Condition Class

Species
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Old DBH

DBH

DBH Check

Horizontal Distance

Azimuth

Crown Class

Tree Height

Tree Age at DBH

Notes

Description

Competing Basal Area

Crown Diameter Wide

Crown Diameter 90°

Live Crown Ratio

Crown Density

Crown Dieback

Foliage Transparency

Location 1...3

Damage 1 ...3

Severity 1...3

'Age is not recorded for downloaded

Table 1-5. Point-Level Descriptors

Measurement Variables

Previous Point History

Point History

Slope Correction

Percent Slope

Aspect

Terrain Position

Subplot Condition List

Subplot Center Condition

Microplot Center Condition

Subplot Offset

Microplot Offset

PDR Prompt

(TreeTyp)

(SitHist)

(Tree#)

(Point*)

(PrCndCI)

(CondCIs)

(Sped)

(PrDBH)

(DBH)

(DBHChk)

(HDist)

(Azi)

(Crown Cl)

(TotHt)

(DbAge)

(Notes)

(Desc)

(CmpBA)

(CrDiaW)

(CrDia9)

(CRatio)'

(CrnDen)

(CrnDbk)

(FolTrn)

(Locatnl ..3)

(Damag1..3)

(Sevrty1..3)

trees. It is computed at processing.

Screen (Subsection 1.6.3)

PDR Prompt

(PrPnHst)

(PnHst)

(SICor)

(%Slope)

(Aspct)

(TerrPos)

(SbCdList)

(SbCtrCd)

(MpCtrCd)

(SbOffst)

(MpOffst)

Meas.

Typel
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X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Meas.

Type 1

X

X

X

X

X

X

X

X

X

X

Meas. Meas.

Type 2 Type 3

X

X

D

x,D

D

X

x,D

D

X

X

x,D

x,D

X

X

X1

x,D

x,D

X

X

X

X

X

X

X

X

X

X

Meas. Meas.

Type 2 Type 3

D

X

D x,D

X1

X1

X1
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X2

X2

X2

D x,D

D x,D

Page

34,57

34

35

35

35

35

35

35

35,57

35,57

35

35

35,57

35

35

36

36

36

Sec.2, p. 14

14

19

19

21

21

Sec. 3, p.3-5

3-8

3-12

Page

37

37

37

37

38

38

39

39

39

39,78

40,78

1 Only on newly forested points.

2 These data are supplied on computer-generated plot maps.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 4 of 86

Table 1-6. Boundary Delineation Screen (Subsection 1.6.3.2)

Measurement Variables

Boundary Change

Plot Type

Offset Point

Contrasting Condition

Left Azimuth

Left Distance

Comer Azimuth

Comer Distance

Right Azimuth

Right Distance

PDR Prompt

(Bd Chg)

(PlotTyp)

(OffstPt)

(Contend)

(LftAz)

(LftDs)

(CnrAz)

(CnrDs)

(RgtAz)

(RgtDs)
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Meas.

Typel

X

X

X

X

X

X

X

X

X

Meas. Meas.

Type 2 Type 3

X

, X1

X1

X1

X1

X1

X1

X1

X1

x'

Page

42

42

42

43

43

43

43

43

43

43

'These data are supplied on computer-generated plot maps.

Table 1-7. Understory Vegetation

Measurement Variables

Percent Moss

Percent Lichens

Percent Ferns

Percent Herbs

Percent Shrubs

Percent Seedlings

Screen (Subsection 1.6.4)

PDR Prompt

(%Moss)

(%Lichn)

(%Fems)

(%Herbs)

(%Shrubs)

(%Seeds)

Meas.

Type 1

X

X

X

X

X

X

Meas. Meas.

Type 2 Type 3

X

X

X

X

X

X

Page

44

44

44

44

44
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45

Table 1-8. Mlcroplot Seedling Screen (Subsection 1.6.5.1)

Measurement Variables

Species

Condition Class

Crown Class

Seedling Count

Crown Vigor

PDR Prompt

(Speci)

(CondCIs)

(CrownCI)

(#Seeds)

(CrnVigr)

Meas.

Type 1

X

X

X

X

X

Meas. Meas.

Type 2 Type 3

X

X

X

X

X

Page

46,App.A

46

46

47

Sec.2, p. 11

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 5 of 86

Table 1-9. Microplot Sapling Screen (Subsection 1.6.5.2)

Measurement Variables

Tree Number

Previous Condition Class

Condition Class

Offset Point

Old Tree History

Last Tree History

Current Tree History

Fader (CA)

Species

Old DBH

DBH

DBH Check

Live/Dead (CA PNW PS)

Old Stem Count (W)

Stem Count

Old Diameter at Root Collar (W)

Diameter at Root Collar

Horizontal Distance

Azimuth

Estimated Mortality Year (CA/PNW)

Mortality Year

Nonforest Year

Ground Year

Cause of Death

Crown Class

Notes

Description

Crown Vigor

Crown Diameter Wide (CA/PNW PS)

Crown Diameter 90° (CA/PNW PS)

Live Crown Ratio

Crown Density (CA/PNW PS)

Crown Dieback (CA/PNW PS)

Foliage Transparency (CA/PNW PS)

Location 1...3

Damage 1...3

Severity 1..3
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Live Tree (CA/PNW PS)

Cause of Death (CA/PNW PS)

PDR Prompt

(Tree#)

(PrCndCI)

(CondCIs)

(OffstPt)

(OldHst)

(LstHst)

(SapHst)

(Fader)

(Spec!)

(PrDBH)

(DBH)

(DBHChk)

(Live)

(PrtfStems)

(Stems)

(PrDRC)

(DRC)

(HDist)

(Azi)

(EMortYr)

(MortYr)

(NonFYr)

(GmdYr)

(Cause)

(CrownCI)

(Notes)

(Desc)

(CrnVigr)

(CrDiaW)

(CrDiaQ)

(CRatio)

(CrnDen)

(CrnDbk)

(FolTrn)

(Locatn1..3)

(Damag1..3)

(Sevrty1..3)

(Live)

(Caus1.2)

Meas.

Type 1

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X
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X

X

Meas.

Type 2

D

D

D

D

X

D

D

D

D

D

D

X

X

X

X

X

x,D

x,D

X

D

X

X

X

Meas.

TypeS

D

D

X

x,D

D

D

X

X

x,D

D

X

X

D

X

D

X

x,D

x,D

X

X

X

X

X

x,D

x,D

X

X

X

X

X

X

X

X

X
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X

Page

Sec.3, p.48

48

48

48,78

48

48

48

50

SO.App.A

50

51

52

52

53

53

53

53

54

55

55

55

55

55

55

56

56

56

Sec.2, p. 12

14

14

19

19

21

21

Sec.3, p.5

8

12

20

20

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 6 of 86

Table 1-10. Subplot Tree Screen (Subsection 1.6.6)

Measurement Variables

Tree Number

Previous Condition Class

Condition Class

Offset Point

Old Tree History

Last Tree History

Current Tree History

Fader (CA/PNW PS)

Species

Old DBH

D8H

DBH Check

Live/Dead (CA PNW PS)

Old Stem Count (W)

Stem Count (W)

CHd Diameter at Root Collar (W)

Diameter at Root Collar (W)

Horizontal Distance

Azimuth

Estimated Mortality Year (CA/PNW)

Mortality Year

Nonforest Year

Ground Year

Cause of Death

Crown Class

Notes

Description

Crown Diameter Wide

Crown Diameter 90"

Liva Crown Ratio

Crown Density
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Crown Dieback

Foliage Transparency

Location 1...3

Damage 1 ...3

Severity 1...3

Cause of Death (CA/PNW PS)

PDR Prompt

(Tree*)

(PrCndCI)

(CondCIs)

(OffstPt)

(OldHst)

(LstHst)

(TrHist)

(Fader)

(Speci)

(PrDBH)

(DBH)

(DBHChk)

(Live)

(PrtfStems)

(#Stems)

(PrDRC)

(DRC)

(HDist)

(Azi)

(EMortYr)

(MortYr)

(NonFYr)

(GmdYr)

(Cause)

(CrownCI)

(Notes)

(Desc)

(CrDiaW)

(CrDia9)

(CRatio)

(CrnDen)

(CrnDbk)

(FolTrn)

(Locatn1..3)

(Damag1..3)

(Sevrty 1..3)

(CausL. 2)

Meas.

Typel

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X
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X

X

Meas.

Type 2

D

D

D

D

X

D

D

D

D

D

D

X

X

X

X

X

x,D

x,D

D

D

D

X

X

X

X

X

X

Meas.

TypeS

D

D

X

x,D

D

D

X

X

x,D

D

X

X

D

X

D

X

x,D

x,D

X

X

X

X

X

x,D

x,D

X

X

X

X

X

X

X

X

X

Page
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57

57

57

57

57

57

57

59

59, App.A

60

60

61

61

61

61

61

61

62

62

63

63

63

63

63

63

64

65

Sec.2, p. 14

14

19

19

21

21

5

8

12

20

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 7 of 86

Table 1-11. Full-Hectare Boundary Screen (CA/PNW PS Only) (Subsection 1.6.7)

Measurement Variables

Hectare Center Condition

Hectare Contrasting Condition

Left Azimuth

Corner Azimuth

Corner Distance

Right Azimuth

Table 1-12. Full-Hectare Tree Screen

Measurement Variables

Hectare Tree Type

Tree Number

Previous Condition Class

Condition Class

Tree Location

Old Tree History

Current Tree History

Species

Old DBH

DBH

DBH Check

Point Number

Horizontal Distance

Azimuth to nearest point

Mortality Year

Nonforest Year

Ground Year

Cause of Death

Crown Class

Notes

Description

Crown Vigor

Crown Diameter Wide (CA/PNW PS)

Crown Diameter 90° (CA/PNW PS)

Live Crown Ratio

Crown Density (CA/PNW PS)

Crown Dieback (CA/PNW PS)
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Foliage Transparency (CA/PNW PS)

Location 1...3

Damage 1 ...3

Severity 1..3

PDR Prompt

(CtrCd)

(Contend)

(LftAz)

(CnrAz)

(CnrDs)

(RgtAz)

(CA/PNW PS Only) (Subsection

PDR Prompt

(HTrTyp)

(Tree*)

(PrCndCI)

(CondCIs)

(TrLoc)

(OldHst)

(SapHst)

(Sped)

(PrDBH)

(DBH)

(DBHChk)

(Point*)

(HDist)

(Azi)

(MortYr)

(NonFYr)

(GrndYr)

(Cause)

(CrownCI)

(Notes)

(Desc)

(CrnVigr)

(CrDiaW)

(CrDia9)

(CRatio)

(CrnDen)

(CrrtDbk)

(FolTrn)

(Locatn1..3)

(Damag1..3)

(Sevrty1..3)

Meas.

Typel

X

X

X

X

X

X

1.6.7.2)

Meas.

Type 1

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X
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X

X

X

X

X

X

X

Meas. Meas.

Type 2 Type 3

x,D

x,D

x,D

x,D

x.D

x,D

Meas.

Type3

x,D

D

D

X

X

D

X

x,D

D

X

X

x,D

x,D

x,D

X

X

X

X

X

x,D

x,D

X

X

X

X

X

X

X

X

X

X

Page

67

67

67

67

67

67

Page

68

68

68

68

68

69

69

70,App.A

70,60

70,60

70,61

70

70

70

71,63

71,63

71,63

71,63

71,63

71,64

71,65
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Sec.2, p. 12

14

14

19

19

21

21

5

8

12

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 8 of 86

Table 1-13. Full-Hectare Tree Mortality Screen (Subsection 1.6.7.3)

Measurement Variables

Hectare Tree Type

Condition Class

Tree Location

Mortality Status

Species

DBH

Point Number

Horizontal Distance

Azimuth

Mortality Year

Cause of Death (Primary)

Cause of Death (Secondary)

Notes

Description

PDR Prompt

(HTrTyp)

(CondCIs)

(TrLoc)

(MorStat)

(Speci)

(DBH)

(Point*)

(HDist)

(Azi)

(MortYr)

(Causl)

(Caus2)

(Notes)

(Desc)

Meas.

Type 1

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Table 1-14. Plot-Level Note Screen - Nonforested/Access Denied/Dangerous Plots (Subsection
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Measurement Variable

Notes

1 Downloaded information is provided on

Table 1-15. Plot Identification Screen

Measurement Variables

State

County

Hexagon Number

Plot Number

Project

QA status

Crew Type

Measurement Type

CHd Plot Status

Current Plot Status

Month

Day

Year

Land Use at Point 1

Land Use at Point 2

Land Use at Point 3

Land Use at Point 4

PDR Prompt

(Notes)

hard copy.

Meas.

Typel

X

- Nonforested/Access Denied/Dangerous

PDR Prompt

(State)

(Only)

(Hex Num)

(Plot Num)

(Project)

(QA Stat)

(CrewTyp)

(MeasTyp)

(OldStat)

(CurStat)

(Month)

(Day)

(Year)

(CtrLUI)

(CtrLU2)

(CtrLUS)

(CtrLU4)

Meas.

Typel

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Meas.

Type 2

X

Meas.

TypeS

X

X

X

X
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X

X

X

X

X

X

X

x,D

1.6.8.1)

Meas.

TypeS

x'

Page

~73

73,57

73

73

73,App.A

73,60

73

73

74

74

74,63

74,63

74,64

74,65

Page

75

Plots (Subsection 1 .6.8.2)

Meas.

Type 2

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Meas.

TypeS

X

X

X

X

X

X

X

X

x'

X

X

X

X

X

X

X

X

Page

76,25,App.B

76,25,App.B

76,25

76,25

76,25

76,25

76,26
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76,26

76,26

76,26

76,27

76,27

76,27

76,App.D

76,App.D

76,App.D

76,App.D

'Downloaded information is provided on hard copy.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 9 of 86

1.1 Overview

1.1.1 Scope and Application

 Estimation of growth (stand dynamics) and measurement of trees and stands (stand structure) 

are

important Forest Health Monitoring (FHM) program objectives. Stand dynamics includes three 

elements

that are important "indicators" of forest health: (1) rates of regeneration, (2) survivor 

growth, and (3)

mortality. These data are obtained by remeasuring trees on permanent plots through a 

series of

successive inventories (Husch et al., 1972). They are usually expressed in terms of numbers of 

trees,

basal area, or volume. Characterization of stand structure yields a snapshot of stand conditions

at each

measurement interval. It embodies numerous parameters that describe the settings in which 

individual

trees or groups of trees exist. These parameters are generally area-based, either calculated 

directly from

the tree tally (e.g., stand density) or assigned by definition (e.g., terrain position). Data 

pertaining to stand

structure are valuable because they permit stratification of a forest into meaningful 

subgroups. An

additional objective of FHM site condition, growth, and regeneration measurements is providing a 

basic plot

framework upon which to conduct field activities associated with other forest health 

indicators not

traditionally associated with forest mensuration (i.e., vegetation structure, lichen communities,

ozone

bioindicator species, and PAR). As such, these indicators can be directly correlated with stand 

dynamics

and stand structure.

1.1.2 Summary of Method

 FHM sampling activities fall into three general categories. Measurement Type 1 (Mt1) 

describes

activities conducted when a portion of the national plot grid is activated the first time. At 

that time, all plots

are visited regardless of whether or not they are forested. In general, if any portion of a 

FHM plot is

forested, and access can safely be gained, that plot is a forest plot. If access is denied to 

an entire plot,

or it is hazardous to occupy an entire plot, or no portion of a plot is forested, that plot is a

nonforest plot.

 All FHM plots, both forested and nonforested, are revisited on a 4-year cycle in order to 

reconcile all

changes that have occurred since the previous survey. These subsequent 4-year remeasurements 

are

referred to as measurement type 3 (Mt3) surveys. In some regions, annual, interim, 

measurement type

2 (Mt2) surveys are conducted between Mt1 and Mt3 to update the tree crown and damage data for 

trees

tallied during the pervious years. Only plots which were determined to be forested during the 

Mt1/Mt3

years are visited during Mt2.

 All FHM site condition, growth, and regeneration data; crown condition classification data 

(Section 2);

and damage and mortality assessment data (Section 3) are collected on portable data recorders 

(PDRs)

with the aid of a program called "Tally". The Tally program prompts crews to enter measurements 
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as they

complete each plot. Tally incorporates numerous list, range, and logic checks to verify the 

accuracy of the

data. Lists of variable codes are described in this and subsequent sections and in the PDR 

help menu.

 There are seven versions of Tally, each designed for specific regional and/or measurement 

type

variations.

 1. New Eastern forest plots (Mt1/Mt3)

 2. Mt2 (East)

 3. Mt3 (East)

 4. Nonforest/No access/dangerous plots (Mt1/Mt2/Mt3)

 5. Mt1 Colorado (CO)

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 10 of 86

 6. Mt1 California (CA)/Pacific Northwest Pilot Study (PNW PS)

 7. Mt1 Minnesota (MN)

 More than one version of Tally may be used for each of the three measurement types.

 Mt1 Versions 1, 5, 6, and 7 are used to initially install forests plots in the eastern 

U.S., CO, CA,

 PNW PS, and MN, respectively. Version 4 is used for all nonforested Mt1 plots 

regardless of

 region.

 Mt2 Version 2 is used for forested Mt2 plots. If a Mt2 plot that was previously 

forested has since

 become nonforest, Version 4 is used rather than Version 2.

 Mt3 Version 3 is used to remeasure previously established forested plots that are still 

forested. If

 a previously forested plot has since become nonforest when approached for Mt3, 

Version 4

 is used. If a plot which was previously recorded as being nonforest has since become

forest,

 Version 1 is used.

 This section documents plot establishment and plot evaluation procedures associated with 

collecting

Tally data. These methods and procedures apply to the 1994 field season; they were compiled 

and

modified from the previous FHM Field Methods Guide (Conkling and Byers, 1993), U.S. Forest 

Service

Forest Inventory and Analysis (FIA) field guides (U.S. Department of Agriculture 1981; 1988; 

1989a; 1989b;

1992; 1993), and from EPA-EMAP Standard Operating Procedures. The methods and procedures

described herein apply to field activities in all areas of the United States.

1.1.3 Interferences

 Several uncontrollable environmental and site conditions have hindered or slowed Tally 

measurement,

including (1) poor weather conditions such as gusting wind, heavy rain, and dark overcast skies;

(2) steep

and/or unstable slopes; (3) dense and diverse understory vegetation which constrains free 

movement upon

the plot; and (4) thick canopy immediately overhead that obscured clear view of plot. Suspend

data

collection under severe weather conditions, such as strong winds and heavy rainfall. Review 

offset

procedures (Subsection 1.6.9) in applicable steep and/or unstable slopes.

1.1.4 Safety

 No specialized safety precautions are necessary. Follow general safety precautions for 

conducting

fieldwork (See Appendix E).

1.2 Sample Collection, Preservation, and Storage

 Tally protocols do not require the deliberate collection of samples, yet if a species is 

encountered which

is not listed in Appendix A and there is uncertainty whether it should be tallied as a tree, 

bring branch

samples of foliage from the plot to the State FHM Project Coordinator or Field Supervisor for 
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identification.

Collect samples outside of the subplots from similar specimens and make a note to change the 

species

code later.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 11 of 86

1.3 Equipment and Supplies

 The list below includes all equipment and supplies needed for two trained and certified 

persons to

perform all measurements described in this section. Equipment and supplies associated with PDRs 

are

discussed in FHM Field Methods Guide, Volume II. Regions using the metric system should use 

equipment

calibrated in metric units. Those using the English system will use equipment calibrated in 

English units.

Equipment:

 1 first aid kit

 2 hard hats

 2 pocket-size field methods guides

 2 compasses

 2 clinometers (with percent scale)

 2 prisms or angle gauges (10-factor English, 2.5 metric) (Mt1 and Mt3 only)

 2 cruiser vests

 • 1 utility belt

 1 increment borer (with sheath) (Mt1 and Mt3 only)

 1 hatchet and sheath

 1 nail pouch

 2 diameter tapes (with holder)

 2 loggers tapes

 1 loggers tape refill

 1 clipboard

 • 2 protractors

 2 photo scales

Consumable Supplies:

 tree tags and nails

 tree paint (no lead or copper)

 pins/stakes for subplot and microplot centers

 blank 3.5-inch formatted disks for data transfer

 disk mailers

Field Documentation:

 For Plot Reconnaissance:

 state maps with plot locations designated

 county maps with plot locations designated

 aerial photographs with plot locations designated

 FHM program brochures for interested landowners

 copies of completed landowner permission forms

 starting-point notes from the previous visit (Mt2 and Mt3 only)

 hand-sketched plot diagrams from the previous visit (Mt2 and Mt3 only)

 For Data Collection:

 • blank starting point notes

 blank plot sketch maps

 blank Tally sheets for use in the event of PDR failure

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 12 of 86

 • hard copy of downloaded data (Mt2 and Mt3 only)

 • computer-generated plot diagrams (Mt2 and Mt3 only)

1.4 Calibration and Standardization

 Purchase tapes to required specifications. Tapes should be maintained in working order and 

do not

require calibration. Check the compass regularly against known directions. In the field, avoid 

magnetic

interference. Use the compass without correction for declination (magnetic north). Check PDR 

functions

prior to departing for field. Include backup battery with supplies in case of primary battery 

failure.

1.5 Quality Assurance

1.5.1 Measurement Quality Objectives

 Table 1-16 displays the Measurement Quality Objectives (MQOs) associated with the forest 
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site

condition, growth, and regeneration data. The table lists the bounds of accuracy that are 

considered

acceptable with respect to data measurement or observation. Variable names are given in the 

first column,

reporting units in the second column, and the Data Quality Limits (DQLs) in the third column.

 Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives

 Variables

Reporting Units

 Data Quality Limits

 PLOT IDENTIFICATION (FOREST)

 State

 County

 Hexagon Number

 Plot Number

 Measurement Type

 Project

 QA Status

 Crew Type

 Old Plot Status

 Current Ptot Status

 Month

 Day

 Year

 Elevation

 Tally 1-5

 Interim Disturbance

 Disturbance Year

FIPS codes

FIPS codes

EMAP hex code

number

3 classes

2 classes

3 classes

2 classes

3 classes

6 classes

12 classes

31 classes

31 classes

100 ft (10 m)

FHM code

17 classes

years

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

95% agreement

NA, crew dependent

NA, crew dependent

99% agreement

90% @ +1 - 200 ft (100 m)

NA, crew dependent

90% agreement

90% @ + / - 2 years

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 13 of 86

Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives

Variables

Reporting Units

Data Quality Limits

CONDITION CLASSIFICATION

Condition Class Change

Condition Class

Land Use Class

Forest Type

Stand Origin

Stand Size

Past Disturbance

Disturbance Year
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Previous Stand Age

Stand Age

SITE-TREE DATA

Site-tree History

Tree Type

Tree Number

Point Number

Previous Condition Class

Condition Class

Species

Old DBH

DBH

DBH Check

Horizontal Distance

Azimuth

Crown Class

Tree Height

Tree Age at DBH

Notes

Description

Competing Basal Area

2 classes

9 classes

15 classes

122 classes

3 classes

4 classes

17 classes

years

years

years

3 classes

2 classes

'number

4 classes

9 classes

9 classes

314 classes

0.1 in (0.1 cm)

0.1 in (0.1 cm)

3 classes

0.1 ft (0.1 m)

1°

5 classes

1 foot (0.5 m)

years

2 classes

alphabetic field

ff/ac (m2/ha)

90% agreement

NA, arbitrary value

90% forest vs nonforest

90% agreement to broad type

90% agreement

85% agreement

85% agreement

85% @ + / - 2 years

NA, downloaded

85% @ + / -10 years

95% agreement

90% agreement

NA, downloaded

NA, arbitrary

NA, downloaded

95% agreement

95% to genus, 90% to species

NA, downloaded

90% @ + / - 5% of True DBH

90% agreement

90% @ + / - 1 ft (0.3 m)

90% @ + / - 10°

85% agreement

90% @ + / - 3% of True Site

Tree Height

90% @ + / - 5 years

NA, discretionary

NA, discretionary
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90% @ + / - 20 sq ft (5 sq m)

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 14 of 86

Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives

Variables

POINT DESCRIPTION

Previous Point History

Point History

Slope Correction

Percent Slope

Aspect

Terrain Position

Subplot Condition List

Subplot Center Condition

Microplot Center Condition

Subplot Offset

Microplot Offset

BOUNDARY DELINEATION

Boundary Change

Plot Type

Offset Point

Contrasting Condition

Left Azimuth

Left Distance

Comer Azimuth

Comer Distance

Right Azimuth

Right Distance

MICROPLOT UNDERSTORY VEGETATION

Percent Moss

Percent Lichens

Percent Ferns

Percent Herbs

Percent Shrubs

Percent Seedlings

Reporting Units

2 classes

2 classes

0.1 ft (0.1 m)

1 percent

1"

7 classes

9 classes

9 classes

9 classes

2 classes

2 classes

2 classes

2 classes

5 classes

9 classes

1°

0.1 ft (0.5 m)

1°

0.1 ft (0.5 m)

1°

0.1 ft (0.5m)

5% classes

5% classes

5% classes

5% classes

5% classes

5% classes

Data Quality Limits

NA, downloaded

90% agreement

90% @ + / - 1 ft (0.3

90%@+/-10%

90% @ + / - 30°

90% agreement

90% agreement

90% agreement

90% agreement

90% agreement
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90% agreement

90% agreement

95% agreement

90% agreement

90% agreement

90% @+ 7-15°

90% @ + / - 1 ft (0.3

90% @ + /- 15°

m)

m)

90% @ + 1 - 5 ft (2 m)

90% @ + /- 15°

90% @ + / - 1 ft (0.3

90% @ + / - 20%

90% @ + / - 20%

90% @ + / - 20%

90% @ + / - 20%

90% @ + / - 20%

90% @ + / - 20%

m)

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 15 of 86

Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives

Variables

MICROPLOT SEEDLINGS

Species

Condition Class

Crown Class

Seedling Count

Crown Vigor Class

MICROPLOT SAPLINGS

Tree Number

Previous Condition Class

Condition Class

Offset Point

Old Tree History

Last Tree History

Current Tree History

Fader (CA)

Species

Old DBH

DBH

DBH Check

Old Stem Count

Stem Count

Old DRC

DRC

Horizontal Distance

Azimuth
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Mortality Year

Est. Mortality Year (CA)

Nonforest Year

Ground Year

Cause of Death

Crown Class

Notes

Description

Reporting Units

314 classes

9 classes

5 classes

number

3 classes

number

9 classes

9 classes

5 classes

1 4 classes

1 4 classes

1 4 classes

2 classes

314 classes

0.1 in (0.1 cm)

0.1 in (0.1 cm)

3 classes

number

number

0.1 in

0.1 in (0.1 Cm)

1 ft (0.5 m)

1°

year

year

year

year

year

5 classes

2 classes

alphabetic field

Data Quality Limits

90% to genus, 80% to species

90% agreement

85% agreement

90% @ + / - 3

90% agreement

NA, downloaded

NA, Downloaded

90% agreement

90% agreement

NA, downloaded

NA, downloaded

95% agreement

90% agreement

95% to genus, 85% to species

NA, downloaded

90% @ + / - 5% of True DBH

85% agreement

NA, downloaded

85% agreement

NA, downloaded

85% @ + / - 0.2 in (0.5 cm)

90% @ + / - 1 ft (0.3 m)

90% @ + /- 10°

85% @ + / - 2 years

85% @ + / - 2 years

85% @ + / - 2 years

85% @ + / - 2 years

85% agreement

85% agreement

NA, discretionary

NA, discretionary

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 16 of 86
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Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives

Variables

SUBPLOT TREES

Tree Number

Previous Condition Class

Condition Class

OHset Point

Old Tree History

Last Tree History

Current Tree History

Fader (CA)

Species

Old DBH

OBH

DBH Check

Old Stem Count

Stem Count

OldDRC

DRC

Horizontal Distance

Azimuth

Mortality Year

Est. Mortality Year (CA)

Nonforest Year

Ground Year

Cause of Death

Crown class

Notes

Description

Reporting Units

number

9 classes

9 classes

5 classes

14 classes

1 4 classes

1 4 classes

2 classes

314 classes

0.1 in (0.1 cm)

0.1 in (0.1 cm)

3 classes

number

number

0.1 in

0.1 in (0.1 Cm)

1 ft (0.5 m)

1°

year

year

year

year

year

5 classes

2 classes

alphabetic field

Data Quality Limits

NA, downloaded

NA, downloaded

90% agreement

90% agreement

NA, downloaded

NA, downloaded

95% agreement

90% agreement

95% to genus, 85% to species

NA, downloaded

90% @ + / - 5% of True DBH

85% agreement

NA, downloaded

85% agreement

NA, downloaded

85% @ + / - 0.2 in (0.5 cm)

90% @ + / - 1 ft (0.3 m)

90% @ +/- 10°

85% @ + / - 2 years

85% <3> + / - 2 years

85% @ + / - 2 years

85% @ + / - 2 years
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85% agreement

85% agreement

NA, discretionary

NA, discretionary

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 17 of 86

Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives

Variables

FULL-HECTARE BOUNDARY DELINEATION

Hectare Condition List

Hectare Center Condition

Contrasting Condition

Lett Azimuth

Corner Azimuth

Corner Distance

Right Azimuth

FULL-HECTARE LARGE TREES

Hectare Tree Type

Tree Number

Previous Condition Class

Condition Class

Tree Location

Old Tree History

Current Tree History

Species

Old DBH

DBH

DBH Check

Point Number

Horizontal Distance

Azimuth to nearest point

Mortality Year

Nonforest Year

Ground Year

Cause of Death

Crown Class

Notes

Description

Reporting Units

9 classes

9 classes

9 classes

1°

1°

0.1 ft (0.5 m)

1°

2 classes

number

9 classes

9 classes

3 classes

1 1 classes

1 1 classes

314 classes

0.1 in (0.1 cm)

0.1 in (0.1 cm)

3 classes

4 classes

1 ft (0.5 m)

1°

year

year

year

year

5 classes

2 classes

alphabetic field

Data Quality Limits

90% agreement

90% agreement

90% agreement

90% @ + / - 15°

90% @ + /- 15°

90% @ + / - 5 ft (2 m)

90%@+/-15°
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95% agreement

NA, downloaded

NA, downloaded

90% agreement

95% agreement

NA, downloaded

95% agreement

95% to genus, 85% to species

NA, downloaded

90% @ + / - 5% of True DBH

85% agreement

NA, arbitrary

90% @ + / - 1 ft (0.3 m)

90% @ +/- 10°

85% @ + / - 2 years

85% @ + / - 2 years

85% @ + / - 2 years

85% agreement

85% agreement

NA, discretionary

NA, discretionary

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 18 of 86

Table 1-16. Site Condition, Growth, and Regeneration Measurement Quality Objectives

Variables

FULL-HECTARE MORTALITY

Hectare Tree Type

Condition Class

Tree Location

Mortality Status

Species

DBH

Point Number

Horizontal Distance

Azimuth

Mortality Year

Cause of Death (primary)

Cause of Death (secondary)

Notes

Description

PLOT IDENTIFICATION (NONFOREST)

State

County

Hexagon Number

Plot Number

Measurement Type

Project

QA Status

Crew Type

Old Plot Status

Current Plot Status

Month

Day

Year

Land Use at Point 1

Land Use at Point 2

Land Use at Point 3

Land Use at Point 4

Reporting Units

2 classes

9 Classes

3 classes

3 classes

314 classes

0.1 in (0.1 cm)

4 classes

1 ft (0.5 m)

1°

year

year

year

2 classes

alphabetic field

FIPS codes

FIPS codes
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EMAP hex code

number

3 classes

2 classes

3 classes

2 classes

3 classes

6 classes

1 2 classes

31 classes

number

1 5 classes

15 classes

1 5 classes

15 classes

Data Quality Limits

95% agreement

90% agreement

95% agreement

95% agreement

90% to genus, 80% to species

90% @ + / - 5% of True DBH

NA, arbitrary

90% @ + / - 1 ft (0.3 m)

90% @ +/- 10°

85% @ + / - 2 years

85% agreement

85% agreement

NA, discretionary

NA, discretionary

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

99% agreement

90% agreement

90% agreement

90% agreement

90% agreement

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 1.5.2 Method Performance

 Expected data measurement performance is indicated in the third column of Table 1 -16. For 

instance,

for the DBH data variable, these data will be measured to the nearest 0.1 inch for English and

to the

nearest 0.1 cm for metric. An acceptable accuracy or performance criteria, as measured on 

Reference

Plots or in Field Audits, is that the crews will be within 5 percent of the true value (as 

measured by an audit

team) on 90 percent of their measurements.

 These comparisons are based on numbers of observations for matching entities. That is, prior

to

making a comparison, it must be determined that the same tree or Condition Class is involved. 

In some

cases, arbitrary values cannot be directly compared. For example, crews are allowed to choose 

site trees,

and then reference them to any point. Prior to comparisons involving site trees, it must be 

verified that the

same tree is referenced to the same point. Most notably, Condition Classes are identified by 

arbitrary

numbers assigned by crews. These numbers can change with the order in which the plot is 

completed and

can also change between surveys. Prior to comparison of values involving Condition Class, it 
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must be

established that all Condition Classes have been assigned the same numbers, or otherwise 

matched.

Variables affected by this caveat include: Condition Class, Subplot Condition List, Subplot

Center

Condition, Microplot Center Condition, and Contrasting Condition.

 1.5.3 Corrective Action

 Reference plot data and/or audit results will be evaluated for indications of data 

measurement

deviations in excess of the MQOs. Crews with unacceptable MQO deviations will be advised of 

problem

situations and special attention will be directed to followup training or other appropriate 

action. Within a

short period after retraining, followup audits will be conducted to verify that subsequent 

measurements are

within MQOs. See FHM Quality Assurance Plan (Cline (ed.), 1994) for a full explanation of this 

corrective

process.

1.6 Procedures

 Tally prompts the field crew for the measurements required at each plot. This section is 

organized

similar to the way information is presented on the PDR screens. A Quick Reference Guide to all 

Tally

Screens has been provided in Subsection 1.0. The tables in the quick reference guide serve as 

indices

to Section 1, indicating the pages where Tally variables are defined. In cases where the same 

variable

appears on multiple screens (e.g., DBH), a cross reference is provided to the page where the 

most

comprehensive description is given. All site condition, growth, and regeneration measurement 

variables

are discussed in Section 1. Most crown condition classification and damage and mortality 

assessment

variables are introduced in Section 1, yet are discussed more fully in Sections 2 and 3, 

respectively.

Although the lists of variables are organized by PDR screen, the order of the variables within 

each figure

of the screen may not match the current ordering of variables on the PDR screen. Additionally, 

some of

the screens shown here are optional, to be activated only in certain regions. As an example, 

the

full-hectare boundary and full-hectare tree screens will be done in California and Pacific 

Northwest Pilot

Study only.

 The tables listed in the Quick Reference Guide indicate which variables are prompted for 

forest plots

under each of the three measurement types. A "x" in one of these tables means that the 

variable is

prompted for a particular measurement type, and the crew will be prompted to complete that 

field. Other

variables will either be provided from previous field visits (downloaded) or, if not applicable 

to that field visit,

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 20 of 86

will not be presented. A "D" means that the variable has been downloaded from previous field 

visits. A

"x,D" will be downloaded from existing Tally data, but new data are required for new forest 

plots and new

sample trees. Only if a mistake was made during a previous visit will crews have an opportunity 

to change

some of the codes that have been downloaded. Whenever a downloaded variable is changed, an

explanation is required in the field notes.

 Variables followed by "(W)" are scheduled for collection in western states only. Variables 

followed by

"(CA/PNW PS)" are scheduled for collection in CA and the PNW PS only.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 21 of 86

 1.6.1 Permanent Plot Design and Forest Plot Establishment

1.6.1.1 Plot Design

 The FHM national sampling scheme is discussed at length by Overton et al. (1990). The 

sampling

framework is based upon a triangular grid of 40 km2 hexagons that spans the entire U.S. The grid

contains

atotal of 12,600 hexagons (about 1/16 of the U.S. land area). FHM ground plots are 

systematically located

within 1 kilometer of each hexagon center.

Procedure

 Each FHM plot consists of a series of fixed-area, circular subplots tied to a cluster of 

four points that

are spaced 120 ft (36.6 m) apart (Figure 1-1). A cluster design was chosen because it has proven

to be

cost-effective for extensive surveys (Scott et al., 1983; Scott, 1993). The key sampling unit 

for most tree

measurements is the 1/24-acre (1/60-hectare) subplot (Figure 1-1). Each subplot includes a 

1/300-acre

(1/750-hectare) microplot, offset from subplot center to avoid trampling. Seedlings, saplings, 

and other

vegetation are measured on the microplot.

 Other FHM measurements are made on the plot as well. Lichen community is sampled in a 

circular

area with a 120-ft radius centered in the middle of subplot 1 and excluding the four subplots. 

Non-timber

vegetation measurements are collected at points offset from the subplot center points at 30°, 

150°, and

270° azimuths. PAR measurements are made on a grid of seven stations located on each of the 

subplots

as shown in Figure 4-1. Ozone bioindicator plants are sampled at the most easily accessible 

opening that

is within three miles +/- 300 ft (91 m) elevation of the detection monitoring plot.

 The center of subplot 1, or point 1, is also the center of overall plot. The other subplot 

centers (or

points) are located as follows: point 2 is 360° and 120 ft (36.6 m) from point 1; point 3 is 

120° and 120 ft

(36.6 m) from point 1; and point 4 is 240° and 120 ft (36.6 m) from point 1. Microplot centers 

are located

90° and 12 ft (3.66 m) from the center of each subplot.

 All compass readings on FHM plots are taken from magnetic north, and not corrected for 

declination.

Field data are recorded in metric units in Forest Service (FS) Regions 5, 6, and 10 (Pacific 

Northwest,

California, Hawaii, and Alaska). All other FS regions use English units.

1.6.1.2 Forest Plot Establishment

 A FHM plot is installed at all sample locations where any portion of a 1/24-acre (1/60-

hectare) subplot

is forested (e.g., a timberland, reserved timberland, or woodland land use). A plot is not 

established where

all four subplots are obviously nonforest. To qualify as forest, an area must meet Forest 

Inventory and

Analysis (FIA) specifications for timberland, reserved timberland, or woodland. These 

specifications are

provided in Appendix D.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 22 of 86

 Azimuth 1 -2 360°

 Azimuth 1-3120°

 Azimuth 1 -4 240°

 Subplot

 24.0' radius (7.32 m).

Annular Plot

58.9'radius (17.95m).

 Distance between

 points is 120" (36.6m).

 Microplot
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 6.8" radius (2.07 m) 12' @

 90° azimuth from subplot

 centers (3.66 m).

 0195msd94.fig-1

Figure 1-1. National FHM plot layout is designed around four points (subplot centers).

 if a land owner refuses access to a forested sample plot, do not attempt to visit the plot, 

rather report

the refusal to the field supervisor. If the field supervisor cannot obtain permission, the plot 

is set aside until

the next Mt3, when access will again be requested. No substitute plot is established. A similar 

procedure

applies to plots where access is preempted by safety considerations. Hazardous plots are not 

occupied

until the situation is rectified.

Plot Establishment Procedures

Scaling a Course to Sample Plot

 For initial plot establishment, and for future measurements where the previously established 

course is

unsuitable, a new course to the sample plot must be scaled from aerial photography. Always 

select a

prominent landmark or physical feature for a starting point (e.g., field corners, buildings, 

bridges,

intersections of roads, streams, or ditches). If necessary, reference the starting point with 

one or more

witness trees. Pinprick and label the images of the starting point and plot center (subplot #1)

on the

photograph. Scale a new course to the sample plot as follows:

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 23 of 86

 1. Establish a baseline by selecting two points that are at least 600 ft (182.9 m) apart 

and clearly

 identifiable on the photo and on the ground.

 2. Measure the distance between these two points on the ground and note the azimuth of the

 direction the measurement is taken.

 3. Pinprick these two points on the photo and measure the distance between them using a 

photo

 scale.

 4. To compute the Photo Scale Reciprocal (PSR), divide the horizontal ground distance by 

the photo

 distance.

 5. Measure the distance on the photo between the starting point and the plot center and 

multiply that

 number by the PSR to get the horizontal ground distance between the two.

 6. Find the azimuth from the starting point to the plot center by placing the 

protractor at the

 intersection of the baseline and the starting point to plot center line on the back of 

the photo,

 making sure the protractor is face down.

 7. Using the azimuth of the baseline as a reference, find the course to plot center azimuth

by reading

 the number where the course line meets the edge of the protractor.

Establishing a ground course to the sample plot

 1. Using a compass and tape, follow the azimuth and distance from the starting point to 

plot center.

 2. Horizontal distance should be corrected for slope, but record slope distance in the 

field notes.

 3. Reference all line segments exceeding 500 ft (150 m) with witness trees. Mark shorter 

segments

 in areas where relocation difficulties might be expected.

 4. At the end of the course, check the photograph to verify that the ground location of the

plot center
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 is correct.

 5. If the 24 ft (7.32 m) radius around subplot #1 contains no forest, establish a turning 

point and

 proceed to the lowest-numbered subplot that does contain forest.

 6. Place a permanent marker in the ground at the lowest-numbered forested subplot and 

reference

 it with two witness trees. The witness trees should be placed outside the 24 ft (7.32 

m) subplot

 radius, approximately at right angles to each other with respect to the subplot 

center.

 7. Also place permanent ground markers at the center of the other three subplots, but it 

is not

 necessary to reference them with witness trees.

Witness Tree Marking Procedures

 1. Tag or otherwise mark starting points, starting-point witness trees, line trees, and

plot-center

 witness trees according to the usual procedures followed by the local FIA Unit. Avoid 

scribing any

 trees with 58.9 ft of a subplot center.

 2. Avoid penetration of the cambium when scribing trees.

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Course Documentation

 Preprinted field notes will be provided for plot relocation. A written description of the 

starting point will

be included in the appropriate section of the notes. The following information should be recorded

on the

preprinted field notes:

 1. Whenever practical, add information that will help locate the plot without the aid of a

photograph.

 2. Sketch a map of the course from the starting point to the center of the lowest-numbered

forested

 subplot.

 3. Record the slope distances (to the nearest foot [0.1 meter]) and azimuths of all line 

segments

 between the starting point, line trees, turning points, prominent physical features, and 

plot center.

 Slope distances are counted as cumulative until the azimuth changes.

 4. At the lowest-numbered forested subplot, record the species, DBHs, slope distances, and

azimuths

 of two witness trees. Ail distances and azimuths should be measured to the center of a 

tree at its

 base.

 5. Also sketch the positions of the two witness trees as well as any other features of 

the plot that

 might facilitate future relocation on the preprinted plot diagram.

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 1.6.2 Plot-Level Data

 1.6.2.1 Plot-Level Notes

 The plot-level notes screen (Table 1-1) may contain notes from previous field crews. These 

could be

 extremely important and should be reviewed before starting the plot. Do not delete any notes 

downloaded

from previous visits. New notes can be typed in the PDR alphabetic fields found at the end

of the

downloaded notes. Additionally, using some codes automatically prompts further explanation be 

added to

the notes. All notes are reviewed by the regional coordinator when the data are processed. If 

appropriate,
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they will be downloaded to future field crews.

 1.6.2.2 Plot Identification

 Plot identification data provide information concerning the crew members, date, and 

other

circumstances associated with each plot.

Procedure

 The Quick Reference Plot Identification Screen (Table 1 -2) lists the plot identification 

variables. Record

the appropriate codes for each variable.

 STATE

 Two-digit FIPS codes are listed in Appendix B.

 COUNTY

 Three-digit FIPS codes are listed in Appendix B.

 HEXAGON NUMBER

 Record the unique 7-digit EMAP code assigned to each 40-km2 hexagon. These are provided 

on

 the field maps and/or the PDR.

 PLOT NUMBER

 • Plot numbers are used to identify individual plots when more than one plot occurs 

within the same

 hexagon. Record the 1 -digit code that applies. In cases where only one plot is located

in the

 hexagon, assign a "1" in this field.

 PROJECT

 Specify whether the plot is a standard detection plot or a special demonstration plot.

 Code Definition

 1 Detection Monitoring

 2 Demonstration Project

 QA STATUS

 Indicate whether or not the plot is being measured for Quality Assurance (QA) purposes.

QA field

 plots are plots on the regular grid that are remeasured for QA by both regular field and 

QA crews.

 QA reference plots are special plots that have been established solely for QA purposes. 

They are

 not part of the regular grid, usually located near regional training centers, and 

measured by both

 regular and expert field crews.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 26 of 86

 Definition

 Standard field plot

 QA field plot

 QA reference plot

 Training plot

 Botched plot

CREW TYPE

 Specify whether the plot is being measured by a regular field crew or QA crew or an expert 

crew

 consisting of indicator leaders.

 Code Definition

 1 Regular field crew

 2 QA field crew

 3 Expert crew

MEASUREMENT TYPE

 Indicate whether this is a new plot (Mt1), a plot being remeasured as part of the annual 

tree crown

 and damage update (Mt2), or a plot being remeasured as part of the 4-year Mt3 remeasurement

 cycle.

 Definition

 New plot - First time this plot has been established.

 Annual measurement - Plot is being remeasured as part of the annual crown

 and damage assessment.

 3 Periodic measurement - Plot is being remeasured as part of the 4-year Mt3

 remeasurement cycle.
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OLD PLOT STATUS

 This code indicates plot status the last time a Mtl or Mt3 survey was conducted at this 

location.

 For Mt2 and Mt3 surveys, old plot status has been downloaded from the current plot status

 recorded at the previous inventory.

 Definition

 Forest Plot - Plot had at least one forested condition class that was occupied

 and measured in the normal manner.

 2 Nonforest plot - Plot did not have any forested condition classes.

 3 Forest plot, access denied - Plot had at least one forested condition class,

 yet access had been denied to the entire plot.

 4 Forest plot, dangerous access - Plot had at least one forested condition

 class, yet dangerous conditions prevented access to the entire plot.

 5 Lost data - Plot had at least one forested condition class, yet the data that

 were or should have been collected at that time are not available.

CURRENT PLOT STATUS

 Indicate the status of this plot at the current time.

 Definition

 Forest Plot - Plot has at least one forested condition class that can be 

visited

 and measured in the normal manner.

 Nonforest plot - Plot does not have any forested condition classes. (Note:

 Also assign this code to plots that cannot be visited because of access

 problems if it is obvious that the plot contains no forested condition classes.)

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 Code Definition

 3 Forest plot, access denied - Plot has at least one forested condition class,

 yet access has been denied to entire plot. Use code 1 if access is denied to

 only part of the plot.

 4 Forest plot, dangerous access - Plot has at least one forested condition

 class, yet dangerous conditions prevent access to the entire plot. Use code 1

 if access is prevented to only part of the plot.

 5 Lost data - Plot has at least one forested condition class that has been or

 can be visited and remeasured, yet the data may have been lost. (Note:

 This code is valid only after the close of field season.)

MONTH, DAY, YEAR

 Record 2-digit codes to identify the month, day, and year when the plot is measured (e.g., 

record

 July 14, 1994 as 07 14 94).

ELEVATION

 Obtain elevation data from USGS topographic maps, generally the 7 1/2 minute series 

quadrangle.

 Locate the plot center on the map. Record elevation as a 3-digit code, rounding to the 

nearest 100

 ft and dropping the last two digits. In metric, elevation is rounded to the nearest 10 

m. For

 example, 240 ft is coded 002; 5,600 is 056; 240 m is coded 024; while 1,800 m is 180. If 

the

 elevation is unknown at the time the plot is occupied, record 999.

TALLY1 - TALLY5

 All FHM field personnel have been assigned a 7-digit Cruiser I.D. code. Record the I.D. of 

each

 crew member or visitor participating in site condition, growth and regeneration, crown 

classification,

 or damage/mortality field measurements (up to a maximum of five). Cruiser I.D. codes 

are

 sequenced as follows:

 The first two digits identify the agency with whom the crew member is employed.

 Code Definition

 11 Forest Service, FHM Research

 12 Forest Service, State and Private Forestry

 13 Forest Service, National Forest Systems

 14 Environmental Protection Agency (including contractors)

 15 State

 16 Bureau of Land Management

 17 Tennessee Valley Authority

 18 National Park Service

 19 Soil Conservation Service

 20 Bureau of Indian Affairs

 90 Other
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 The second two digits specify the federal agency or state affiliation. FS agency branches,

 independent contractor, and other codes are listed below. State employees should use the 2-

digit

 state FIPS code (Appendix B). Non-Forest Service federal employees should use the "other" 

code.

 Code Definition

 01 Region 1 (Northern Region)

 02 Region 2 (Rocky Mountain Region)

 03 Region 3 (Southwestern Region)

 04 Region 4 (Interrnountain Region)

 05 Region 5 (Pacific Southwest Region)

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 Code Definition

 06 Region 6 (Pacific Northwest Region)

 07 Northeastern Area

 08 Region 8 (Southern Region)

 09 Region 9 (Eastern Region)

 10 Region 10 (Alaska Region)

 22 Intermountain Station

 23 North Central Station

 24 Northeast Station

 26 Pacific Northwest Station

 27 Pacific Southwest Station

 28 Rocky Mountain Station

 29 Southeast Station

 30 Southern Station

 31 Independent Contractor

 90 Other

 The last three digits correspond to the personal identification number assigned to each 

crew

 member at the beginning of the field season.

INTERIM DISTURBANCE 1-3

 Describe up to three treatments or disturbances that have occurred since this plot was last 

visited

 by a field crew. This information will be downloaded as plot-level notes to future crews to

aid

 condition classification at the next Mt3 survey. If there are more than three, describe the

additional

 disturbance in the plot-level notes.

 Code Definition

 0 None

 1 harvest

 2 commercial thinning

 3 selective cutting and highgrading

 4 other cutting

 5 site preparation

 6 artificial regeneration on existing forest

 7 artificial regeneration on nonforest

 8 prescribed burning

 9 other silvicultural (i.e., injection, herbicide, fertilizer)

 10 natural reversion on nonforest

 11 disease

 12 insects

 13 weather

 14 wildfire

 15 grazing

 16 Other

INTERIM DISTURBANCE YEAR 1-3

 Record the year (2-digit) during which an interim disturbance occurred.

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 1.6.2.3 Condition Classification

 The FHM plot configuration is locked into a fixed pattern and subplots are never moved 

(rotated or

 substituted). As a result, some plots may straddle more than one land use or forest 

condition. To

 compensate for this and to enable stratification of the data by meaningful stand and area 

descriptors, all

 subplots and microplots are mapped by condition class (Scott and Bechtold, 1994)..
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 Procedure

 A condition class is defined by five variables: (1) Land Use, (2) Forest Type, (3) Stand 

Origin, (4)

 Stand Size, and (5) Past Disturbance. New conditions are recognized each time a distinct change

occurs

 for one or more of these variables on the plot. As different conditions are encountered, they 

are defined

 by recording all five variables associated with the new condition class.

 To qualify as a separate condition, a change must be obvious and the contrasting condition 

must be

 at least 1 acre (0.4 hectare) in size. The only exception to the 1-acre (0.4-hectare) rule is

a maintained

 nonforest inclusion in a forest environment (i.e., house site, powerline, improved road).

 Examples of situations where separate condition classes will NOT be recognized include the 

following:

 • transition zones

 natural nonforest inclusions less than 1 acre (0.4 hectare) in size (i.e., rock 

outcrops, openings,

 lakes)

 streams less than 30 ft (9 m) wide

 unimproved woods roads (e.g., not ditched)

 fire lines

 contrasting forest conditions less than 1 acre (0.4 hectare) in size.

 Situations where changes in condition class WILL be recognized include the following:

 contrasting land uses and forest conditions greater than 1 acre (0.4 hectare) in size

 all maintained, human-caused, nonforest inclusions regardless of size or width (i.e., 

powerlines,

 improved roads, house sites, canals)

 linear strips of forest in a FOREST matrix (stream margins) regardless of width, as long

as the

 condition is at least 1 acre (0.4 hectare) [Note: linear strips of forest in a 

NONFOREST matrix

 (riparian forest in a grassland environment) must be at least 120 ft (36.6 m) wide to 

qualify as

 forest].

 On new forest plots (Mt1 or newly forested Mt3), condition classes are recorded as 

they are

 encountered at the plot. However, at Mt3 plots, crews are provided with computer-generated plot

diagrams

 showing how condition classes were defined during the previous Mt1/Mt3 visit. If no change has 

occurred,

the Mt3 crew should rerecord the condition class data provided on the plot diagram. If change

has

 occurred, or an error was made during the previous visit, ignore the condition class provided

on the plot

diagram and enter the revised condition class data.

 The quick reference condition classification screen (Table 1-3) lists the variables 

describing condition

classification.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 30 of 86

CONDITION CLASS CHANGE

 Indicate whether or not the data for this condition class are being copied from the 

computer-

 generated plot map. All data copied from the data diagram will be checked for 

transcription errors

 when the data are processed.

 Code Definition

 0 The condition class is different from the plot map.

 1 The condition class has been copied from the plot map.

CONDITION CLASS

 An arbitrary number is used to identify and map different land uses and forest conditions

occurring

 on a plot. Once a number is assigned, that number is reused whenever the same condition 

class

 is encountered on the plot. Most plots will have only one or two conditions, but as many
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as nine

 can be recorded. On new plots (Mt1 and newly forested Mt3), number condition 

classes

 consecutively as they are encountered. On Mt3 plots, use the same numbers assigned at the

 previous inventory, if they still apply. (Code 1 = Condition 1 ... Code 9 = Condition 

9)

LAND USE CLASS

 Record the appropriate land use. For sampling purposes, Timberland (01), Reserved 

Timberland

 (12), and Woodland (13) are all considered forest land uses. Definitions and additional 

information

 concerning land use classification are provided in Appendix D.

 Code Definition

 0 Lost data / lost plot

 1 Timberland

 2 Cropland

 3 Improved pasture

 4 Rangeland

 5 Idle farmland

 6 Other farmland

 7 Urban and other development

 8 Marsh

 9 Water

 10 Access denied

 11 Dangerous condition

 12 Reserved Timberland

 13 Woodland

 14 Rocky, barren, excessively steep terrain (nonforest)

 15 Natural alpine clearing (nonforest)

FOREST TYPE

 Detailed Forest Types are arranged into major Forest-Type Groups recognized by the 

Society of

 American Foresters (Eyre, 1980). A list of species associations that correspond to the 

various

 Forest Types is provided in Appendix C.

 Forest type is based on the stocking of all live trees in the sampled condition. 

Overtopped trees

 are not usually considered. When assigning forest type, it may be necessary to look 

beyond the

 trees tallied in that condition. If Tally trees alone do not accurately reflect the 

forest type, include

 a note of explanation.

 AH species associated with a forest type need not be present for that type to apply. For 

example,

 if red maple predominates on a wet to very wet site, then the type is Black ash/American 

elm/Red

 maple even though Black ash and American elm are absent (see Appendix C, code 710).

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 If a stand is at early serai stage, forest type is derived from seedling or sapling cover 

alone. If a

 disturbance is very recent, and there is less than 10 percent stocking (Appendix D), use 

code 0999

 to denote a nonstocked plot. Remeasurements will trace the development of this tract toward

a

 specific forest type as reforestation takes place.

STAND ORIGIN

 Examine the plot for evidence of tree planting or seeding and assign the appropriate code.

 Code Definition

 1 Natural stand, no evidence of planting or direct seeding

 2 Softwoods planted or seeded

 3 Hardwoods planted or seeded

STAND SIZE

 Record the stand size based on the average DBH of all live trees that are not overtopped.

 Code Definition

 1 Sawtimber - softwood or woodland > 9.0 in (22.9 cm) DBH/DRC

 Sawtimber - hardwood > 11.0 in (27.9 cm) DBH/DRC

 2 Poletimber - softwood or woodland > 5.0 in - 8.9 in (12.7 - 22.8 cm) DBH/DRC

 Poletimber - hardwood > 5.0 in - 10.9 in (12.7 - 27.8 cm) DBH/DRC

 3 Sapling/seedling < 5.0 in (12.7 cm) DBH/DRC
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 4 Nonstocked

PAST DISTURBANCE 1

 The area affected by any human-caused or natural treatment or disturbance must be at least 

1

 acre (0.4 hectare). Record up to three significant treatments and/or disturbances. In 

most cases,

 only the disturbances listed below are significant. In cases where "other" categories are 

used

 (other cutting, other silvicultural, and other), describe the situation further in the notes. For new

 plot establishment (Mt1 or newly forested Mt3 plots), the disturbance must be clearly 

visible and

 recent enough to affect current competitive conditions or otherwise influence stand health.

 For Mt3 remeasured forest plots, recognize only those disturbances that have occurred in the

four

 years since the previous Mt1/Mt3 survey. Review the plot-level notes to determine which

 disturbances were recorded during previous visits. These should not be rerecorded because 

only

 disturbances that have happened since then are relevant. However, if plots have been 

annually

 revisited (Mt2), interim disturbances may be recorded in plot-level notes. Because 

disturbances

 occurred during Mt2 visits since previous Mt1/Mt3 visits, they should be recorded during the 

Mt3

 visit, as well. When evaluating disturbance notes from previous visits, any disturbances 

with a date

 equal or prior to the previous Mt1/Mt3 survey should be ignored.

 Code Definition

 0 None

 1 harvest

 2 commercial thinning

 3 selective cutting and highgrading

 4 other cutting

 5 site preparation

 6 artificial regeneration on existing forest

 7 artificial regeneration on nonforest

 8 prescribed burning

 9 other silvicultural (i.e., injection, herbicide, fertilizer)

 10 natural reversion on nonforest

 11 disease

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 Definition

 insects

 weather

 wildfire

 grazing

 Other

DISTURBANCE YEAR 1

 Record the year (2-digit) in which Disturbance 1 occurred. For new plot establishment (Mt1 

or

 newly forested Mt3 plots), there is no time limit on recognition of past disturbances, as 

long as they

 are still visibly impacting the stand. Remeasured Mt3 plots will not be assigned a 

disturbance that

 happened before the previous Mt1/Mt3 survey.

PAST DISTURBANCE 2

 If a stand has experienced more than one disturbance, record the second disturbance here. 

See

 Past Disturbance 1 for coding instructions.

DISTURBANCE YEAR 2

 Record the year in which Past Disturbance 2 occurred.

 instructions.

See Disturbance Year 1 for coding

PAST DISTURBANCE 3

 If a stand has experienced more than two disturbances, record the third disturbance here. 

See

 Past Disturbance 1 for coding instructions.

DISTURBANCE YEAR 3

 Record the year in which Past Disturbance 3 occurred.

 instructions.

See Disturbance Year 1 for coding

PREVIOUS STAND AGE

 Previous stand age is downloaded from "STAND AGE" recorded during the previous Mt1 or Mt3
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 survey. If this condition has not experienced any major treatment or disturbance, previous 

stand

 age can be used as a guide to determine current stand age.

STAND AGE

 An estimate of stand age is required for every forested condition class defined on a plot. 

Stand

 age is usually highly correlated with stand size and should reflect the average age of all 

trees that

 are not overtopped. Unlike the procedure for Site-tree age, estimates of stand age should 

range

 back to the time of tree establishment (e.g., not age at DBH). Note: For planted stands, 

estimate

 age based on the year the stand was planted (e.g., do not add in the age of the planting 

stock).

 Stand age is different from other condition class variables in that the decision to create 

a separate

 condition class is rarely based solely on age. If the difference between two conditions 

does not

 involve land use, forest type, stand origin, stand size, or disturbance history, do not 

recognize two

 separate condition classes. The only exception is when two saw timber stands are the same 

in

 every respect, but they differ in age by more than 50 years.

 Determination of stand age involves the extraction of tree cores. Cores are not usually 

taken from

 trees within 58.9 ft (17.95 m) of any subplot center. This is required in order to protect 

trees on

 any subplot from potential damage caused by the coring process. Trees must be cored off 

plot, yet

 still within the same condition class to which the age data applies. CAUTION: When trees 

are

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 33 of 86

chosen beyond 58.9 ft of the subplot center, make sure they are not located on an adjacent

subplot.

To estimate stand age, select three or four dominant or codominant trees from the overstory. If

the overstory covers a wide range of tree sizes and species, try to select the trees 

accordingly, but

it is not necessary to core additional trees in such stands. The variance associated with mean

stand age increases with stand heterogeneity, and additional cores are not likely to improve the

estimate. Core each tree at DBH and count the rings from the outside edge of the core to the 

pith.

Add in the number of years that passed from germination until the tree reached DBH to determine

the total age of the tree. Unless more specific information is provided at training, add 5 

years to

all eastern species, 5 years to western hardwoods, and 10 years to western softwoods. Assign

a weight to each core by visually estimating the percentage of total overstory trees it 

represents.

Make sure the weights from all cores add up to 1.0, compute the weighted average age, and

record. For example, if three trees aged 34, 62, and 59 years represent 25 percent, 60 percent,

and 15 percent of the overstory, respectively, the weighted stand age should be:

 (34 x .25) + (62 x .60) + 59 x (.15) = 55 years.

In some cases, it may be possible to avoid coring trees to determine age. If a stand has not 

been

seriously disturbed since the previous Mt1 or Mt3 survey, simply add the number of years since

the previous survey to the previous stand age. In other situations, cores collected from site 

trees

(Subsection 1.6.2.4) can be used to estimate Stand Age.

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1.6.2.4 Site-Tree Data

 Site-tree data provide a measure of site productivity by quantifying the height-to-age 

relationship of

dominant and codominant trees. Site-tree data are required for every forested condition class 

defined on

a plot, if suitable site trees are available. National guidelines require only one site tree 

per forested

condition class, yet in some FHM regions more may be selected. The preferred number of site 

trees will

be specified at training. On plots where suitable site trees are not available, the 

corresponding PDR
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warning should be overridden.

Procedure

 Site-trees should be selected from species common to the overstory of the condition class 

being

sampled. If possible, choose a species with clearly visible annual rings and a central stem. Use

only trees

that have remained in a dominant or codominant crown position throughout their entire life span. Reject

trees that exhibit signs of damage, trees with ring patterns that exhibit signs of suppression, 

trees less than

20 years old, trees less than 5.0 inches (12.7 cm) DBH, trees with rotten cores, and woodland 

species.

 Site-tree procedures include the extraction of tree cores. Site-tree cores are not usually

taken from

trees within 58.9 ft (17.95 m) of any subplot center. These trees must be selected off plot yet

within the

same condition class that they represent. CAUTION: When trees are chosen beyond 58.9 ft (17.95 

m)

of the subplot center, make sure they are not located on an adjacent subplot.

 In some cases, it may be possible to use previously gathered site tree data. Crews are 

encouraged

to reuse the downloaded tree data if the tree still qualifies. The current age of downloaded 

site trees will

be computed from past data files when the data are processed, so it is not necessary to re-core 

these

trees.

 The quick reference site-tree screen (Table 1-4) lists the site-tree variables.

 TREE TYPE

 In past years, foliage samples, tree cores, and other specimens were collected from 

"specimen

 trees." For convenience, site tree data and specimen tree data were combined on the same

PDR

 screen. In 1994, specimen trees will not be selected nor will tree related specimens 

be collected;

 therefore, the tree type variable automatically sets to "1".

 Code Definition

 1 Site Tree Only

 2 Specimen Tree Only

 3 Site tree and specimen tree

 SITE-TREE HISTORY

 Indicate whether a downloaded site tree is suitable for reuse as a site tree. This field

automatically

 set to "1" for Mt1 plots. Note: No site trees are available for downloading to Mt3 

plots in 1994,

 therefore this field is automatically set to "1".

 Code Definition

 1 First time tree used

 2 Downloaded site tree, still suitable for site tree

 3 Downloaded site tree, no longer suitable for site tree

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TREE NUMBER

 The same procedure for subplot trees in Subsection 1.6.6 applies.

POINT NUMBER

 Record the number of the point to which the site tree distance and azimuth are measured.

PREVIOUS CONDITION CLASS

 Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 survey.

CONDITION CLASS

 Record the Condition Class in which the site tree is currently located. (Code 1 = 

Condition 1 —

 Code 9 = Condition 9).

SPECIES

 Select the appropriate species code from Appendix A.

OLD DBH

 Downloaded from "DBH" recorded during the previous Mt1/Mt3 survey.
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DBH

 Use the same procedures described for subplot trees in Subsection 1.6.6.

DBH CHECK

 Use the same procedures described for subplot trees in Subsection 1.6.6.

HORIZONTAL DISTANCE

 Measure and record the horizontal distance to the nearest 0.1 ft (0.1 m) from the subplot 

center

 to the pith at the base of the site tree.

AZIMUTH

 From subplot center, view the base of the site tree with a compass. Record the azimuth (to 

the

 nearest degree) as a 3-digit code ranging from 001 to 360. Use 360 for north.

CROWN CLASS

 Use the same procedures described for subplot trees in Subsection 1.6.6. Site trees must be

 dominant or codominant.

TREE HEIGHT

 With a clinometer or other approved instrument, measure the total length of the site tree 

from the

 ground to the top of the tree. Record the 3-digit code to the nearest 1 ft (0.1 m).

TREE AGE AT DBH

 Drill the site tree at DBH with an increment borer. Count the rings from the outside edge 

of the

 core to the pith. Record the age of the tree at DBH (3-digit code). Do not attempt to add 

in the

 time it took the tree to reach DBH.

 Use the following procedure to estimate the age of the tree if the radius is greater than 

the length

 of the increment borer.

 1. Bore into the tree as far as possible, extract the core, and count the rings.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 36 of 86

 2. Count the number of rings in the inner 2 inches (5 cm) of the core.

 3. While the increment borer is still in the tree, measure the length of the borer that is

exposed.

 4. Subtract this length (step 3) from the total length of the increment borer.

 5. Divide tree DBH by 2.

 6. Subtract step 4 from step 5 to find the distance short of the center.

 7. Divide step 6 by 2 (or 5 if metric) to determine how many 2 inch (5 cm) lengths are 

needed

 to make up the missing distance.

 8. Multiply step 7 by the number of rings counted in step 2.

 9. Add step 8 to the total number of rings in the extracted core (step 1) to determine the

tree

 estimated age at DBH.

 10. Note "extrapolated age" in notes.

NOTES

 Indicate if any notes are to be recorded for this tree. A "1" downloaded to this field 

indicates the

 presence of notes from a previous field crew.

 Code Definitions

 0 No notes will be recorded for this tree.

 1 Written notes will be recorded for this tree.

DESCRIPTION

 Record tree-level notes in the alphabetic field on the PDR. These notes will be reviewed by

the

 regional coordinator and passed onto future crews, if appropriate.

COMPETING BASAL AREA
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 Using a 10 English-factor (2.5 metric) prism, estimate the basal area of other trees 

competing with

 the site tree. This is accomplished by centering the prism over a point 3 ft (1 m) due north

of the

 face of the site tree at DBH, counting the number of trees that are "in" (5.0 inches (12.7 

cm) DBH

 and larger), and then multiplying the tree count by the prism factor. Do not include the 

site tree

 in the count. "Borderline" trees should be counted as a half tree. Record the estimate as a 

3-digit

 code in square feet per acre (square meters per hectare). For example, 12.5 trees tallied 

with a

 10-factor prism equal 125 sq. ft of basal area is recorded as 125.

ADDITIONAL CROWN AND DAMAGE VARIABLES

 Use crown classification procedures described for subplot trees in Section 2 for: Crown 

Diameter

 Width, Crown Diameter 90°, Live Crown Ratio, Crown Density, Crown Dieback, and Foliage

 Transparency.

 Use damage classification procedures described for subplot trees in Section 3 for: Location

1-3,

 Damage 1-3, and Severity 1-3.

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1.6.3 Point-Level Area Descriptors

1.6.3.1 Point Description

 Each subplot is described by a series of area parameters relating to topographic features 

and existing

cover type. These data also relate to the microplot, since the microplot is contained within 

the subplot

perimeter.

Procedure

 The quick reference point-level area descriptors screen (Table 1 -5) lists variables which 

apply to each

subplot. All condition classes occurring within the perimeter of the subplot should be 

recognized and

defined as soon as the subplot center is established.

 PREVIOUS POINT HISTORY

 Downloaded from "Point History" recorded during the previous Mt1/Mt3 survey.

 POINT HISTORY

 Indicate whether or not this point currently has at least one forested condition class.

 Code Definitions

 0 Entire subplot nonforest

 1 At least one accessible forest condition on subplot (land use class 1, 12, 

or

 13)

 SLOPE CORRECTION

 Distance must be added to adjust for slope if the slope between points is greater than 5

percent.

 Record distance in 0.1 ft (0.1 m) added to the standard 120 ft (36.6 m) distance between

subplot

 1 and subplots 2-4. The English and metric distances which should be added are found in 

Table

 1-17. As an example, 1.3 ft (0.4 m) should be added to a slope distance of 120 ft (3.6 

m) if the

 slope is 15 percent. The multipliers in Table 1-17 can be used to convert any 

horizontal distance

 to slope distance and slope distance to horizontal distance.

 PERCENT SLOPE

 Record the angle of slope to the nearest percent. Percent slope is determined by sighting

the

 clinometer along a line parallel to the average incline (or decline) of the subplot. 

This angle is

 measured along the shortest pathway downslope before the drainage direction changes. To

 measure percent slope, observer #1 should stand uphill 50 ft (15 m) from subplot center 

and sight

 observer #2, who is directly downhill 50 ft (15 m) from subplot center. Sight observer 
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#2 at the

 same height as the eye-level of observer #1. Read the slope directly from the percent 

scale of the

 clinometer. The use of other scales requires conversion to percent.

 Code Definition

 000 0 to 4 percent slope

 005 5 percent slope

 006 6 percent slope

 155 155 Percent slope

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Table 1-17. English and Metric Slope Distance Correction Factors

Percent

Slope

5

10

15

20

25

30

35

40

45

50

55

60

65

70

80

90

100

110

120

130

140

150

Horizontal to Slope

Multiplier

1.001

1.005

1.011

1.020

1.031

1.044

1.059

1.077

1.097

1.118

1.141

1.166

1.193

1.221

1.281

1.345

1.414

1.487

1.562

1.640

1.720

1.803

Slope to Horizontal

Multiplier

0.999

0.995

0.989

0.980

0.970

0.958

0944

0.929

0.912

0.894

0.876

0.858

0.838

0.819

0.781
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0.743

0.707

0672

0.640

0.610

0.581

0.555

Feet added per 120ft

0.1

0.6

1-3

2.4

3.7

5.3

7.1

9.2

11.6

14.2

16.9

19.9

23.2

26.5

33.7

41.4

49.7

58.4

67.4

76.8

86.4

96.4

Meters added per 36.6

m

0.0

0.2

0.4

0.7

1.1

1.6

2.2

2.8

3.6

4.3

5.2

6.1

7.1

8.1

10.3 •

12.6

15.2

17.8

20.6

23.4

26.4

29.4

 ASPECT

 Aspect specifies the direction of slope for land surfaces with at least 5 percent slope. 

Aspect is

 measured with a hand compass between the same two points where slope was measured. Aspect

 is measured to the nearest degree. Record 000 if percent slot is less than 5 percent.

 TERRAIN POSITION

 This is the position of the subplot in relation to the surrounding topography. See

 Figure 1-2 for examples of different terrain positions.

 Definition

 Top and upper slopes - convex region on the upper part of the slope profile;

 may be either xeric or mesic depending on aspect.

 2 Midsiope - uniform, fairly straight region of the middle part of the slope

 profile; may be either xeric or mesic depending on aspect

 3 Bench - area of level terrain, with midslope above and lower slope below.

 4 Lower slope - concave region on the lower part of the slope profile.

 5 Flatland - level or near-level terrain not part of or related to major 

elevational

 change; may have minimal elevational change (e.g., rolling uplands,

 flatwoods, deep sands).

 6 Bottomland - level terrain; normally well drained but subject to occasional

 flooding (e.g., flood plains of rivers and streams.)

 7 Wet bottomlands - level terrain; generally having year-round abundance or

 overabundance of water (e.g., swamps, small drains, bays, and wet

 pocosins.)
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 Top and

 upper slopes

 Midslope

 Wet Bottomland

 Bottomland

Flatland

 Lower

 slope

 0195msd94.fig-2

Figure 1-2. Terrain position.

 SUBPLOT CONDITION LIST

 This is a listing of all condition classes located within the 24-ft (7.32-m) radius 

around the subplot

 center. A maximum of four conditions is permitted at any individual subplot (a total of 

nine is

 permitted for an entire plot). Condition classes are defined in Subsection 1.6.2.3. If a

condition

 class has already been defined at a previously completed subplot, use the same conditionclass

 number whenever that condition is encountered. Define new conditions as they are 

encountered.

 If more than one condition class is listed here, boundary data are required. If only one

condition

 class is listed, this condition is automatically assigned to the subplot center and 

microplot center.

 SUBPLOT CENTER CONDITION

 This is the Condition Class of the subplot center.

 corresponds to the subplot center.

 MICROPLOT CENTER CONDITION

 This is the condition class at the microplot center.

 corresponds to the microplot center.

 Record the previously defined condition that

 Record the previously defined condition that

 SUBPLOT OFFSET

 Whenever possible, all subplot boundary and tree data should be recorded from, and 

referenced

 to, the subplot center. If some obstruction prevents the collection of any subplot data 

from subplot

 center, then record these data from one of the four offset points on the subplot 

perimeter. (See

 Subsection 1.6.9.) The use of code 1 here activates the PDR to prompt for the offset 

position from

 which data are being recorded.

 Code Definition

 0 All subplot data referenced to subplot center

 1 Some subplot data referenced to one or more subplot offset points

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MICROPLOT OFFSET

 Whenever possible, all microplot boundary and tree data should be recorded from, and 

referenced

 to, the microplot center. If some obstruction prevents the collection of any microplot data

from

 microplot center, then these data should be recorded from one of the four cardinal offset 

points on

 the subplot perimeter. (See Subsection 1.6.9.) The use of code 1 here activates the PDR to

 prompt for the subplot offset position from which data are being recorded.

 Code Definition

 0 All microplot data referenced to microplot center

 1 Some microplot data referenced to one or more subplot offset points

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 1.6.3.2 Boundary Delineation

 All subplots that straddle more than one condition class are mapped by delineating the 

boundaries

 between contrasting conditions. Boundary data are required any time the subplot condition list 
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indicates

 more than one condition. Boundary data are used to compute the area of all subplot fragments

by

 condition class. In addition to the recording procedures described herein, detailed maps of 

condition class

 boundaries should also be sketched onto preprinted plot diagrams.

 Microplots that straddle more than one condition are handled in the same manner.

 Procedure

 Delineate the boundary of each condition class that differs from the condition at a subplot 

center with

 a series of reference points. Boundary delineation is accomplished by recording azimuths and 

distances

 from the subplot center to the reference points (Figure 1-3). Each boundary is marked by a 

maximum of

 three points - two where the boundary intersects the subplot circumference and one "corner" 

point between

 the two end points, if necessary. Unless offset points are used, only the corner points 

require a distance,

 since the distance from the center to the circumference is always equal to the subplot radius. 

In rare cases

 when boundary data are being referenced to offset points (Subsection 1.6.9), distances 

to the

 circumference points are necessary.

 Microplot boundaries are delineated and referenced to the microplot center in the same 

manner

 described for subplots.

 When a boundary between forest and nonforest is clearly marked (i.e., by a fence, fireline, 

ditch), the

 boundary should follow the stems of the trees at the forest edge. When a boundary between 

two

 contrasting forest conditions is not clearly marked, "average in" the boundary between the two 

conditions.

 Upon remeasurement, do not move boundaries unless there has been a definite change, an 

obvious

 mistake by the previous crew occurs, or a clear boundary is no longer detectable.

 When the boundary between two different conditions is separated by a narrow linear inclusion

(i.e.,

woods road, fireline, ditch), always establish the boundary to the nearest edge of the 

inclusion.

 On new forest plots (Mt1 or newly forested Mt3), boundaries are recorded as they are 

encountered on

the plot. However, Mt3 crews are provided with computer-generated plot diagrams that show 

how

boundaries were located during the previous Mt1/Mt3 visit. If there has been no change, the 

current Mt3

crew should rerecord the boundary data provided on the plot diagram. If change has occurred or 

an error

was made during the previous visit, disregard the boundary data provided on the plot diagram and

enter

the correct boundary data.

 The quick reference boundary screen (Table 1-6) lists the boundary delineation variables.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 42 of 86

 Right Azimuth /^

 "TM""^^TM"TMi"^

 Forested

 (Condition #1)

' Left Azimuth

 Clearcut

 (Condition #2)

 Right Azimuth

 Cropland

 (Condition #3)

 Corner Azimuth !

 .. *• «•_ <

 Left Azimuth

 0195fnsd94.fig-3

Figure 1-3. Boundary delineation.

 BOUNDARY CHANGE
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 Indicates whether or not the data for this boundary are being copied from the computergenerated

 plot map. All data copied from the plot diagram will be checked for transcription errors 

when data

 are being processed.

 Code Definition

 0 The boundary is different from the plot map.

 1 The boundary has been copied from the plot map.

 PLOT TYPE

 Specify whether the boundary data is for a subplot or microplot.

 Code Definition

 1 Subplot boundary

 2 Microplot boundary

 OFFSET POINT _,/r> ^

 Record the position from which boundary distances and azimuths are being measured 

(Subsection

 1.6.9). This variable will not appear on the PDR and is automatically set to "0" unless 

Subplot

 Offset = 1 or Microplot Offset = 1.

 Code Definition

 0 Normal position (subplot or microplot center)

 1 North offset point

 2 East offset point

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 43 of 86

 Definition

 South offset point

 West offset point

CONTRASTING CONDITION

 Record the condition class that contrasts with the condition class located at the subplot or

microplot

 center (e.g., the condition class on the other side of the boundary line). (Code 1 = 

Condition 1...

 Code 9 = Condition 9) '

LEFT AZIMUTH

 The azimuth (001-360°) to the farthest left point (facing the contrasting condition) where 

the

 boundary intersects the subplot or microplot circumference (Figure 1-3).

LEFT DISTANCE

 The horizontal distance (to nearest 1 ft [0.1 mj) from an offset point to the farthest left 

point (facing

 the contrasting condition) where the boundary intersects the subplot or microplot 

circumference.

 This variable is required only when the boundary data are being recorded from one of the 

four

 subplot offset points (e.g., when Offset Point = 1, 2, 3, or 4).

CORNER AZIMUTH

 The azimuth (000-360°) from the subplot or microplot center to a corner or curve in a 

boundary

 (Figure 1-8). If a boundary is best described by a straight line between the two 

circumference

 points, then record 000 for corner azimuth (000=none).

CORNER DISTANCE

 The horizontal distance (to 1 ft [0.1 m]) from the subplot or microplot center to a boundary

corner

 point.

RIGHT AZIMUTH

 The azimuth (001-360°) to the farthest right point (facing the contrasting condition) 

where the

 boundary intersects the subplot or microplot circumference (Figure 1-3).

RIGHT DISTANCE

 The horizontal distance (to nearest 1 ft [0.1 m]) from an offset point to the farthest 

right point

 (facing the contrasting condition) where the boundary intersects the subplot or 

microplot

 circumference. This variable is required only when the boundary data are being recorded 

from one

 of the four subplot offset points (e.g., when Offset Point = 1, 2, 3, or 4).
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1.6.4 Microplot Understory Vegetation

 Crown canopy cover of understory vegetation (Daubenmire, 1959; Mueller-Dumbois and 

Ellenberg,

1974) Is assessed for six types of understory vegetation: mosses, lichens, ferns, herbs, and 

shrubs. Tree

seedlings less than 1 ft (0.3 m) in height are also counted as understory vegetation. These 

estimates are

used to describe the understory plant community and potential understory/overstory competition 

factors.

They are not meant to provide data for detection of species changes.

Procedure

 Visually estimate the cover occupied by each vegetation type described below. This is done 

on the

6.8 ft (2.07 m) radius microplot, which is offset 90° and 12 ft (3.66 m) from each subplot 

center. Estimate

the cover of each life form independently and express it as the percentage of ground surface 

under live

aerial plant parts (Avery, 1975). Include all foliage inside the microplot perimeter -- not 

just the foliage of

plants with stems in the circle. Because of layering, the total cover of all six life forms 

could exceed 100

percent.

 If a microplot boundary results in a microplot that is only partially forested, base the 100

percent on

the forested position of the microplot and do not discount the cover estimate for the nonforest 

area.

 Code Definition

 00 absent

 01 trace

 05 5% cover

 10 10% cover

 15 15% cover

 20 20% cover

 95 95% cover

 99 100% cover

 The quick reference microplot understory vegetation screen (Table 1-7) lists understory 

measurement

variables.

 PERCENT MOSS

 Only include moss on the ground.

 PERCENT LICHENS

 Only include lichens on the ground.

 PERCENT FERNS

 Record fern cover for all ferns present.

 PERCENT HERBS

 Herbs are forbs (herbaceous broad-leaved plants), vines, grasses, and grass-like 

plants.

 PERCENT SHRUBS

 Shrubs are all woody-stemmed species not measured as trees.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 45 of 86

 PERCENT SEEDLINGS

 Record seedling cover only for tree species less than 12 inches (0.30 m) in height. 

Measure height

 perpendicular to the ground. Seedlings greater than 12 inches (0.30 m) in height are not

measured

 as part of the understory data, rather are measured as part of the tree data described

in

 Subsection 1.6.5.1 (Figure 1-4).

 > 1.0 in. (2.54 cm) DBH

 > 1 ft. (0.3 m) tall

 < 1.0 in. (2.54 cm) DBH

 < 1 ft. (0.3 m) tall
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 t^fi'tft^j'kf'y^#tff^^

 Understory

 Seedling

Microplot

Seedling

Microplot

 Sapling

0195msd94.fig-4

Figure 1-4. Distinctions among trees less than 5.0 in. (12.7 cm) DBH.

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1.6.5 /If/crop/of Tree Data

 Rates of regeneration constitute an important aspect of forest health and are obtained by 

tallying

seedlings and saplings (trees less than 5.0 inches [12.7 cm] DBH). Seedlings and saplings are

too

numerous to be measured on the subplots within a reasonable time, therefore they are tallied on 

the

smaller microplots. Besides providing information concerning regeneration, these data are 

used to

supplement the subplot tree data, since a variety of understory tree species never reach the 

5.0 inch

(12.7 cm) diameter threshold required for inclusion on the subplots, even when fully grown. All

living trees

less than 5.0 inches (12.7 cm) DBH encountered the first time a microplot is established, and 

all trees that

grow into each microplot thereafter, are monitored until they either die or grow over the 5.0 

inch (12.7)

diameter threshold and into the subplot. The procedures described below form the basis of an 

intricate

accounting system by which these trees are selected for long-term monitoring and then followed 

as stands

develop over time. Microplot sampling procedures incorporate two different protocols as described

below

-- one for seedlings and one for saplings.

1.6.5.1 Seedlings

Procedure

 Microplot seedlings are trees at least 12 inches (0.3 m) in height but less than 1.0 inch 

(2.54 cm) DBH

(timber species) and woodland species with no stem 1.0 inch (2.54 cm) or more DRC (Figure 

1.4).

Seedlings less than 12 inches (0.3 m) are tallied with the understory vegetation (Subsection 

1.6.4).

Seedlings can originate from seeds, sprouts, or layering, and are measured on the 1/300-acre 

(1/750

hectare) microplot (radius is 6.8 feet [2.07 m]) offset 90° and 12 feet (3.66 m) from each 

subplot center.

They are tallied in groups by (1) species, (2) condition class, (3) crown class, and (4) crown 

vigor class.

In other words, count the trees by species and then:

 • Divide the species counts into condition classes.

 Divide the species/tree condition counts into crown classes.

 Divide the species/tree condition/crown counts into crown vigor classes.

(NOTE: Include only seedlings with stems inside the microplot perimeter.)

 The quick reference microplot seedling screen (Table 1-8) lists variables to be entered in 

the PDR.

 SPECIES

 Select the appropriate species code from the list in Appendix A. If you encounter a 

species not

 listed in Appendix A and are not sure if it should be tallied as a tree, consult your 

Field Supervisor.

 If species cannot be determined in the field, bring branch samples of foliage from the 

plot to your

 State FHM Project Coordinator or Field Supervisor for identification. Collect samples 

outside of

 the subplots from similar specimens and make a note to change the species code later.
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 CONDITION CLASS

 Record the Condition Class within which the seedlings are located. If more than one 

Condition

 Class is present on the microplot, the seedlings should be grouped separately by 

condition class.

 CROWN CLASS

 Rate seedling crowns in relation to the sunlight received and proximity to neighboring 

trees. This

 includes all trees, not just other seedlings.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 47 of 86

 Code Definition

 1 Open grown. Seedlings whose crowns have received full light from above and from all

 sides during early development and most of their life. Their crown form or shape 

appears

 to be free of influence from neighboring trees.

 2 Dominant. Seedlings with crown extending above the general level of the crown cover 

and

 receiving full light from above and partly from the sides. These trees are taller 

than the

 average trees in the stand and their crowns are well developed, but they could be

 somewhat crowded on the sides.

 3 Codominant. Seedlings with crowns at the general level of the crown canopy. 

Crowns

 receive full light from above, but little direct sunlight penetrates their sides. 

Usually they

 have medium-sized crowns and are somewhat crowded from the sides. In stagnated

 stands, codominant trees have small-sized crowns and are crowded on the sides.

 4 Intermediate. These seedlings are shorter than dominant and codominant, but their

 crowns extend into the canopy of codominant and dominant trees. They receive little 

direct

 light from above and none from the sides. As a result, intermediates usually have 

small

 crowns and are very crowded from the sides.

 5 Overtopped. Suppressed seedlings with crowns entirely below the general level of 

the

 crown canopy that receive no direct sunlight either from above or the sides.

SEEDLING COUNT

 Record the number of seedlings in each (1) species, (2) condition class, (3) crown class, 

and (4)

 crown vigor class category. If a category has 100 or more trees, record 99.

CROWN VIGOR

 Use the crown classification procedure described for Crown Vigor in Section 2.

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1.6.5.2 Saplings

Procedure

 Saplings are live trees between 1.0 inch (2.54 cm) and 4.9 inches (12.69 cm) DBH/DRC (Figure

1-4).

They are alive if they have any living parts (leaves, buds, cambium) at or above DBH. Saplings 

that have

been temporarily defoliated are still alive. Like seedlings, all sapling variables are measured 

on a single

1/300-acre microplot (6.8 feet radius) offset from each subplot center. Unlike seedlings, 

saplings are tallied

separately. Start at an azimuth of 001° from microplot center and continue clockwise around the 

microplot.

The quick reference microplot sapling screen (Table 1-9) lists the variables to be recorded.

 TREE NUMBER

 Tree numbers are recorded by field crews on special QA reference plots only (QAStat=3). 

On all

 other plots, tree numbers are assigned during data processing after the field season. 

This field is

 therefore not presented to Mt1 crews. Once assigned, tree numbers are permanent and 

are

 downloaded to future Mt2 and Mt3 crews.

 PREVIOUS CONDITION CLASS

 Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 

survey.
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 CONDITION CLASS

 Record the condition class in which each sapling is presently located.

 OFFSET POINT

 Record the position from which the tree distances and azimuths are being measured. 

(See

 Subsection 1.6.9.) This variable will not appear on the PDR and is automatically set to 

"0" unless

 Subplot Offset = 1 or Microplot Offset = 1.

 Code Definition

 0 Normal position (subplot or microplot center)

 1 North offset point

 2 East offset point

 3 South offset point

 4 West offset point

 OLD TREE HISTORY, LAST TREE HISTORY, CURRENT TREE HISTORY

 Tree history codes track the status of the sample tree through each 4-year measurement 

cycle.

 Old Tree History is the status of the tree during the previous Mt1 or Mt3 survey. Last 

Tree History

 is the status of the tree during the previous survey. Both of these values have been 

downloaded

 into the PDR and cannot be modified. Old Tree History and Last Tree History may or may 

not be

 the same. In the absence of Mt2 surveys, Last Tree History will equal Old Tree 

History. If interim

 Mt2 surveys have been conducted, Last Tree History would be the status of the tree at 

the

 previous Mt2 survey.

 Current Tree History is the present status of the tree and is depicted by the codes 

listed below.

 The Current Tree History recorded is used to determine which additional variables will be

displayed

 on the PDR. A complete listing of Current Tree History codes is shown in Table 1-18. An

'x' has

 been placed beside those Current Tree History codes that are valid for microplot trees.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 49 of 86

Table 1-18. Valid Microplot Tree History Codes by Measurement Types

Code

01

02

03

04

05

06

07

08

09

10

11

12

13

14

Current Tree History Mt1

Live/Survivor tree x

Ingrowth tree on microplot

Ingrowth tree on subplot

Outgrowth tree from microplot

Dead tree (qualifies as a snag)

Dead tree (does not qualify as a snag)

Cut tree

Land use change

Missed live tree

Extra tree

Access Denied

Dangerous condition

Lost Data

Missed Snag

Mt2

X

X
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X

X

X

X

X

X.

X

X

Mt3

X

X

X

X

X

X

X

X

X

X

X

X

 Further elaboration on microplot tree history codes is provide below.

 Code 01. Live/Survivor trees on the microplot are live trees 1.0-4.9 inches (2.54-12.6 

cm) DBH.

 Code 01 is used in the following cases:

 A live Mt1 sapling encountered for the first time.

 A downloaded sapling on an Mt2 plot that is still alive regardless of current 

DBH.

 A live Mt3 sapling encountered for the first time (newly forested plots, points, 

and condition

 classes). These are added by scrolling past all downloaded trees on the 

appropriate

 point(s).

 • A downloaded sapling on an Mt3 plot that is still alive and still less than 5.0 

inches (12.7

 cm) DBH.

 Code 02. Ingrowth trees on the microplot are trees on previously forested condition 

classes that

 have grown above the 1.0 inch (2.54 cm) DBH threshold since the previous Mt1/Mt3 survey. 

This

 code is valid only for Mt3 plots.

 Code 03. Ingrowth trees on the subplot are trees on previously forested condition classes

that

 have grown above the 5.0 inch (12.7 cm) DBH threshold since the previous Mt1/Mt3 

survey.

 These trees were not previously located on the microplot, and this code is reserved for 

subplot

 trees.

 Code 04. Outgrowth trees from the microplot are downloaded microplot saplings that have 

grown

 above the 5.0 inch (12.7 cm) DBH threshold since the previous Mt1/Mt3 survey. This code 

is valid

 only for Mt3 plots. If such trees are encountered on Mt2 plots, they would be assigned 

code 01.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 50 of 86

 Code 05. The only time a tree on a microplot qualifies as a snag is when a downloaded 

sapling

 grows above 5.0 inches (12.7 cm) DBH, then dies, and is still standing on its own. This 

code is

 valid for Mt2 and Mt3 plots.

 Code 06. A downloaded sapling that has died and does not qualify as a snag.

 Code 07. A downloaded sapling that has been cut.

 Code 08. A downloaded sapling on land that has since been withdrawn from a forest land use,

 regardless of whether the tree is alive or dead.
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 Code 09. A tree that should have been tallied as a microplot sapling at the previous 

Mt1/Mt3

 survey but was missed. It is added to the PDR by scrolling past all downloaded trees on 

the

 appropriate point.

 Code 10. A downloaded tree that was tallied as a microplot sapling at the previous Mt1/Mt3 

survey

 but should not have been.

 Code 11. A downloaded sapling on land to which access has been denied.

 Code 12. A downloaded sapling on land that is too hazardous to occupy.

 Code 13. A downloaded sapling on a plot that cannot be relocated. This code is valid only 

after

 the close of the field season.

 Code 14. This is a snag that should have been tallied on the subplot at the previous 

Mt1/Mt3

 survey but was missed. This code is reserved for the subplot.

FADER (CA/PNW PS Only)

 Fader trees have fading foliage and are expected to die within the next year.

 Code Definition

 0 Not a fader tree

 1 Fader tree

SPECIES

 Select the appropriate species code from the list in Appendix A. If you encounter a species 

not

 listed in Appendix A and are not sure if it should be tallied as a tree, consult your Field

Supervisor.

 If species cannot be determined in the field, bring branch samples of foliage from the plot 

to your

 State FHM Project Coordinator or Field Supervisor for identification. Collect samples 

outside of

 the subplots from similar specimens and make a note to change the species code later.

OLD DIAMETER at BREAST HEIGHT

 This is the DBH that was assigned at the previous Mt1 or Mt3 survey. It has been downloaded

 from the previous inventory. Any change made to this field signifies a misclassification at

the time

 of the previous inventory. "DBHCheck" should be set to 1 and an explanation is required in 

the

 notes if the old DBH is changed.

 If a tree was missed during a previous survey (Current Tree History, code 09), estimate 

the

 diameter at the time the tree was missed, and then record the estimated old DBH.

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DIAMETER at BREAST HEIGHT

 Measure diameter at 4.5 ft (1.37 m) above the groundline, on the uphill side of the tree. 

If the tree

 has been measured during a previous survey, remeasure DBH at the painted mark. If the paint

 is starting to wear off, mark the tree again at the same spot.

 If this is the first time the tree has been measured, mark the point of measurement with a 

thin line

 of paint placed 0.1 inch (1 crn) below the point of measurement. Mark the tree before the 

taking

 the measurement, and then use a D-tape to measure outside bark diameter. Round the diameter

 down to the last 0.1 inch (1 mm) and code as 3 digits (4 digits in metric). For example, 

3.68

 inches is coded 036 (36.84 cm is coded as 0368).

 Upon encountering any irregularities such as swellings, bumps, depressions, or branches, 

mark

 and measure diameter immediately above the irregularity wherever the stem form appears 

normal.

 For fenceline trees that contain wire, mark and measure the diameter at the normal 4.5 ft 

(1.37 m)

 height. Mark and measure swell-butted trees (such as cypress, tupelo, sitka spruce, and 

redwood)
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 at 1.5 ft (0.5 m) above the pronounced swell or bottleneck if the bottleneck is more than 

3.0 ft

 (1 m) high (Figure 1-5).

 Forked trees require special attention. In order to qualify as a fork, the stem in 

question must be

 at. least 1/3 the diameter of the main stem and must branch out from the main stem at an 

angle

 of 45 degrees or less.

 Trees forked below 1 ft (.3 m) are considered to be two separate trees. Distances and 

azimuths

 are measured individually to each tree, so they may differ. In the case of stump sprouts 

or clumps

 that are forked below 1 ft (.3 m), horizontal distance (and azimuth) is measured to where 

the stem

 enters the stump, so it is possible for some stems to be within the limiting distance of 

the plot and

 others to be beyond the limiting distance. DBH is measured for each stem at 4.5 ft (1.37 m)

above

 the ground.

 Trees that have no forks below 4.5 ft (1.37 m) are measured as one single tree. If a fork 

occurs

 at or immediately above 4.5 ft (1.37 m), mark and measure diameter below the fork just 

beneath

 any swelling that would inflate DBH.

 Trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m) are handled differently. All forks are measured

 individually, but only one distance and azimuth (to the central stump) is used for all. 

Thus, in the

 case of stump sprouts or clumps that are forked above 1 ft (.3 m), the limiting distance 

is the same

 for all forks--they are either all on, or all off the plot.

 For trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m), the DBH of each fork is measured 

at a

 point 3.5 ft (1.07 m) above the crotch where the bark separates. It is possible to have 

multiple

 forks, but count only forks that originate from the main stem (i.e., never count a fork that 

originates

 from another fork). If a main stern forks again within 3.5 ft of a lower fork, measure up 

another 3.5

 ft (1.07 m) from the second fork. For example, a tree with a main stem that forks at 2.0 ft 

(0.61

 m) and 5.0 ft (1.52 m) requires three DBH measurements. The lower fork is measured at a 

point

 3.5 ft (1.07 m) above the crotch. Since the main stem forks again within 3.5 ft (1.07 m) of 

the

 lower crotch, the upper two forks are measured at a point 3.5 ft (1.07 m) above the second 

fork.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 

52 of 86

 t

 • DBH

 • DBH

 4.5' (1.37 m)

 4.5' (1.37 m)

 1 .Tree on slope.

 2. Tree on level ground.

 4.5'(1.

 Diameter

 Point

 j»»k*«» If— Diameter

 Point 4.5'(1.37

 $?^

 2. Tree on 

level ground.

 Diameter

 Point

 5' (1.07 m)

 4.5' (1.37 m)

 4. Tree forks at or
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 above 4.5 feet

 5. Tree forks below 4.5 feet

 6. Tree with branch.

Diameter

Point

 3' (1 m) or more

 4.5' (1.37 m)

 S^J^^SMgg

7. Tree with swell at 4.5 feet.

 Diameter Point

 ,1.5' (0.37m)

 8. Bottleneck tree.

 9. Windthrown/dead tree

 0195msd94.fig-5

 Figure 1-5. Where to measure diameter breast height in a variety of situations.

 Upon remeasurement, if a previously tallied fork has died, move the 

point of DBH on the living

 stem back to where it would have been if there had never been a fork, 

and record a "1" for DBH

 CHECK. In addition, make a note that a fork has died and the point of 

DBH has been moved.

 DBH CHECK

 Identify any irregularities in DBH measurement positions (e.g., 

abnormal swellings, diseases,

 damage, new measurement positions, etc.) that invalidate the use of 

this tree in diameter

 growth/change analyses. Upon diameter remeasurement, DBH check will 

always equal 1 if the tree

 is measured somewhere other than the paint mark left by the previous 

crew (e.g., a fork dies and

 the point of measurement is moved back to 4.5 ft [1.37 m]). DBH check 

should also be set to 1

 if either DBH or old DBH has been estimated for any reason (e.g., a 

missed tree). Whenever code

 1 is used, further explanation is required in the notes.

 Code Definition

 0 No problem with DBH Measurement

 1 Irregular DBH measurement

 LIVE/DEAD TREE (CA/PNW PS Only)

 Specify whether the tree is alive, standing dead, or dead and down.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 53 of 86

 Code Definition

 0 Tree is living.

 1 Tree is standing dead.

 2 Tree is dead and down.

OLD STEM COUNT (WEST ONLY)

 For western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). This is the stem count recorded at the previous Mt1 or Mt3 

survey.

STEM COUNT (WEST ONLY)

 For western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). If there is at least one stem 1.0 inches (2.54 cm) DRC or 

greater, then

 record the total number of stems measured for DRC (e.g., all qualifying stems). Note that

all

 qualifying stems must be at least 1.0 inches (2.54 cm) in diameter at the root collar and 

contribute

 to the overall crown. For dead stems, a judgement call must be made as to whether they had

 contributed to the crown at one time, or whether they were just interior branches. Dead 

stems

 must still be at least 1.0 (2.54 cm) inches in diameter at the base.

OLD DIAMETER AT ROOT COLLAR (WEST ONLY)

 For western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). This is the diameter at root collar (DRC) recorded at the 

previous Mt1

 or Mt2 survey.

DIAMETER at ROOT COLLAR (WEST ONLY)

 For Western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). All western woodland species are measured for diameter at root 

collar

 (DRC). This procedure has been adopted as a multistem equivalent to the DBH. Tally 
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woodland

 saplings with at least one stem greater than or equal to 1.0 inches (2.54 cm) and a 

cumulative

 DRC less than 5.0 inches (12.70 cm). Measure all qualifying stems and calculate the DRC 

using

 the formula below.

 ]P (stem diameter^

 Round the result to the nearest 0.1 inch (2 mm) and record. For single-stemmed woodland 

trees,

 the DRC is equal to the diameter of that stem at its root collar. The PDR is equipped with

a

 program for calculating this formula in the "Pop Up" menu. This "Pop Up" program is limited 

to a

 total of 13 stems. If more than 13 stems are encountered, DRC must be manually calculated.

 Record all pertinent stem measurements on the supplemental Multistemmed Woodland Tally form

 to provide for future tracking of individual stem data. Record dead stems with the small 

letter "d"

 following the 3 digit code (4 digit metric).

 Some woodland trees, particularly juniper and oak, are extremely variable in form. Measure 

the

 DRC of stems so that the measurements are consistent with the volume above the stem(s),

 especially when trees are extremely deformed at the base. For example, when a single 

diameter

 measurement taken below several main stems originating near the root collar does not 

reasonably

 represent the tree volume of the stems, individually measure the qualifying stems (above the

single

 diameter location) and compute the DRC (see Figure 1-6). When in doubt, measure individual

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 54 of 86

 stems rather than one large stem. Mark the point of diameter with paint to maintain 

consistency

 upon remeasurement.

 Whenever DRC is impossible or extremely difficult to measure with a diameter tape (e.g., 

due to

 thorns, extreme limbiness, packrat's nest), the stem(s) may be measured to the last 

whole inch

 (centimeter) with the measurement poles. In this case, always record the stem(s) to the 

nearest

 1-inch (1-cm) class and use these values in DRC computations.

 1. Measure at ground line

 when reasonable.

 3. Multistemmed above

 diameter.

 5. Measure missing stem(s).

 Compute DRC.

 2. Measure above butt swell.

4. Excessive diameter below stems.

 Measure stems. Compute DRC.

6. Multistemmed at or below

 ground. Compute DRC.

 0195msd94.fig-6

Figure 1-6. Points of diameter measurement on woodland trees. Measure just above ground level 

and above any swell

present.

 HORIZONTAL DISTANCE

 Measure the horizontal distance (to the nearest 0.1 ft [0.1 m]) from the microplot center

to the

 pith at the base of the sapling.

 NOTE: For trees forked at or above 1 ft (.3 m), record the distance to the central stem 

at

 ground level for all forks. For trees forked below 1 ft (.3 m), record the distance to 

where each

 individual stem enters the stump (or clump).

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 For all western woodland trees, the horizontal distance should be taken from the "geographic

 center" to the subplot/microplot center. The geographic center is a point of equal distance

 between all stems tallied for a given woodland tree. If only one stem is tallied, the 

procedure is
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 the same as for timber trees.

 NOTE: For Mt3 surveys, if a tree has grown out of the microplot (Current Tree History, 04 or

 05), the must be remeasured from the subplot center.

AZIMUTH

 From microplot center, sight the base of each tree with a compass (sight the geographic 

center for

 western woodland species). Record azimuth (to the nearest degree) as a 3-digit code ranging 

from

 001 to 360. Use 360 for due north.

 NOTE: For Mt3 surveys, if a tree has grown out of the microplot (Current Tree History, 04 or

05),

 the azimuth must be remeasured from the subplot center.

 NOTE: For trees forked at or above 1 ft (.3 m), record the azimuth to the central stem at 

ground

 level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each 

individual

 stem enters the stump (or clump).

MORTALITY YEAR

 In the case of tree histories 05, 06 and 07, record the year (2-digit) in which the sapling 

died or

 was felled.

ESTIMATED MORTALITY YEAR (CA/PNW PS Only)

 In the case of Mtl mortality, record the year (2-digit) in which the sapling died.

NONFOREST YEAR

 In the case of tree history code 08, record the year (2-digit) in which the land use became

 nonforest.

GROUND YEAR

 • Record the year (2-digit) in which a snag falls to the ground or no longer stands on its 

own.

CAUSE OF DEATH

 Assign a cause of death to all trees that have died or been cut since the previous survey. 

In some

 cases, it will be difficult to determine cause of death, but do not guess. If uncertain, 

use code 800.

 If a cause of death is not on the list, use code 999 and explain in the notes. Code 001 is 

assigned

 at processing for all trees that are dead when initially encountered (e.g., MT1 snags).

 Code Definition

 001 Dead tree when first encountered

 100 Insects

 210 Blister rust (CA/PNW PS only)

 200 Disease

 300 Fire

 400 Animal

 500 Weather

 600 Suppression / Competition

 700 Logging and related; human damage

 800 Unknown'

 999 Other than described above; needs explanation in notes.

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CROWN CLASS

 Rate the sapling's crown in terms of sunlight received and proximity to its neighbors. See

 Subsection 1.6.6 for a more comprehensive description of the crown class coding system.

 Code Definition

 1 Open Growth

 2 Dominant

 3 Codominant

 4 Intermediate

 5 Overtopped (suppressed)

NOTES

 Indicate if any written notes are to be recorded for this tree. A "1" downloaded to this 

field

 indicates the presence of notes from a previous field.

 Code Definition

 0 No notes will be recorded for this tree.
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 1 Written notes will be recorded for this tree

DESCRIPTION

 Record tree-level notes in the alphabetic field provided on the PDR. These notes will be 

reviewed

 by the regional coordinator and passed on to future crews if appropriate.

ADDITIONAL CROWN AND DAMAGE VARIABLES

 The following crown classifications are described in Section 2: Crown Vigor, Crown Diameter 

Wide

 (CA), Crown Diameter 90° (CA), Live Crown Ratio (CA), Crown Density (CA), Crown Dieback 

(CA),

 and Foliage Transparency (CA).

 The following damage classifications are described in Section 3: Location 1-3, Damage 1-3, 

and

 Severity 1-3.

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1.6.6 Subplot Tree Data

 Trees 5.0 inches (12.7 cm) DBH and larger are the main focus of FHM detection monitoring. 

Even

after a tree completes its life cycle, it continues to influence biodiversity by providing 

valuable habitat for

wildlife and by contributing to the nutrient cycling process. All trees encountered the first 

time a plot is

established, and all trees that grow into each subplot thereafter, are monitored until they are

dead and

down. The procedures described below form the basis of an intricate accounting system by which 

these

trees are selected for long-term monitoring and then followed as stands develop over time.

Procedure

 Tally all living trees and standing dead trees (snags) 5.0 inches (12.7 cm) DBH/DRC and 

larger on

each 1/24 acre (1/60 hectare) subplot. Trees are alive if they have any living parts (leaves, 

buds cambium)

at or above DBH. Trees that have been temporarily defoliated are still alive. To qualify as a 

snag, a dead

tree must stand at least 4.5 ft (1.37 m) above the ground and be at least-5.0 inches (12.7 cm) 

in diameter

at DBH. Snags must be self supporting, so dead trees supported by other trees (or other snags)

do not

qualify. Begin tallying trees at an azimuth of 001° from subplot center and continue clockwise 

around the

subplot. Record the measurement variables listed on the quick reference subplot tree screen 

(Table 1-10).

 TREE NUMBER

 Tree numbers are recorded by field crews on special QA reference plots only (QAStat=3). 

On all

 other plots, tree numbers are assigned during data processing after the field season. 

This field is

 therefore not presented to Mt1 crews. Once assigned, tree numbers are permanent and 

are

 downloaded to future Mt2 and MT3 crews.

 PREVIOUS CONDITION CLASS

 Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 

survey.

 (Code 1 = Condition 1... Code 9 = Condition 9).

 CONDITION CLASS

 Record the condition class in which each tree is presently located. (Code 1 = Condition 1

... Code

 9 = Condition 9).

 OFFSET POINT

 Record the position from which the tree distances and azimuths are being measured. This 

variable

 will not appear on the PDR and is automatically set to "0" unless Subplot Offset = 1 or 

Microplot

 Off set = 1.

 Code Definition
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 0 Normal position (subplot or microplot center)

 1 North offset point

 2 East offset point

 3 South offset point

 4 West offset point

 OLD TREE HISTORY, LAST TREE HISTORY, CURRENT TREE HISTORY

 Tree history codes track the status of the sample tree through each 4-year measurement 

cycle.

 Old Tree History is the status of the tree at the previous Mt1 or Mt3 survey. Last tree

History is

 the status of the tree at the previous survey. Both of these values have been downloaded 

into the

 PDR and can not be modified. Old Tree History and Last Tree History may or may not be 

the

 same. In the absence of Mt2 surveys, Last Tree History will equal Old Tree History. If 

interim Mt2

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 surveys have been conducted, Last Tree History would be the status of the tree at the 

previous

 Mt2 survey.

 Current tree history is the present status of the tree and is depicted by the codes 

listed below.

 The Current Tree History recorded is used to determine which additional variables will 

be displayed

 on the PDR. A complete listing of Current Tree History codes is shown (Table 1-19). An 

'x' has

 been placed beside those current tree history codes that are valid for microplot trees.

Table 1-19. Valid Subplot Tree History Codes by Measurement Types

Code

01

02

03

04

05

06

07

08

09

10

11

12

13

14

Current Tree History

Live/Survivor tree

Ingrowth tree on microplot

Ingrowth tree on subplot

Outgrowth tree from microplot

Dead tree (qualifies as a snag)

Dead tree (does not qualify as a snag)

Cut tree

Land use change

Missed live tree

Extra tree

Access Denied

Dangerous condition

Lost Data

Missed Snag

Mt1 Mt2

X X

X X

X

X

X

X

X

X

X

X

X

Mt3
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X

X

X

X

X

X

X

X

X

X

X

X

 Further elaboration on subplot tree history codes is provided below.

 Code 01. Live/Survivor trees on the subplot are live trees equal to or greater than 5.0 

inches (12.7

 cm) DBH. Code 01 is used in the following cases:

 A live Mt1 tree encountered for the first time.

 A downloaded Mt2 or Mt3 tree that is still alive.

 • A live Mt3 tree encountered for the first time (newly forested plots, points, and

condition

 classes). These are added by scrolling past all downloaded trees on the 

appropriate

 point(s).

 Code 02. This code is for trees that grow above the 1.0 inch (2.54 cm) diameter 

threshold on the

 microplot and is reserved for microplot trees only.

 Code 03. Ingrowth trees on the subplot are trees on previously forested condition 

classes that

 have grown above the 5.0 inch (12.7 cm) DBH threshold since the previous MT1/MT3 survey.

 These trees were not previously located on the microplot; trees that grow above 5.0 

inches (12.7

 cm) on the microplot are assigned code 04 and are recorded on the microplot screen.

 Code 04. This code is for trees that grow above the 5.0 inch (12.7 cm) DBH threshold

on the

 microplot and is reserved for microplot trees only.

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 Code 05. Snags are standing dead trees equal to or greater than 5.0 (12.7 cm) inches DBH.

 Code 05 is used on the subplot in the following cases:

 A Mt1 snag encountered for the first time.

 A downloaded Mt2 or Mt3 tree (or snag) that is currently a snag.

 A Mt3 snag encountered for the first time. Most often, new Mt3 snags are associated 

with

 newly forested plots, points, and condition classes. Occasionally, a tree will grow 

into the

 subplot and die before ever being tallied as a live tree. All of these cases are 

added to

 the PDR by scrolling past all downloaded trees on the appropriate point(s).

 Code 06. A downloaded tree that has died and fallen, or a snag that has fallen.

 Code 07. A downloaded tree or snag that has been cut.

 Code 08. A tree on land that has been withdrawn from a forest land use, regardless of 

whether

 the tree is alive, dead, standing, or down.

 Code 09. A tree that should have been tallied as a live subplot tree at the previous Mt1/Mt3

survey

 but was missed. It is added to the PDR by scrolling past all downloaded trees on the 

appropriate

 point.

 Code 10. A downloaded tree that was tallied as a subplot tree at the previous Mt1/Mt3 

survey but

 should not have been.

 Code 11. A downloaded tree to which access has been denied.

 Code 12. A downloaded tree on land that is too hazardous to occupy.
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 Code 13. A downloaded tree on a plot that cannot be relocated. This code is valid only after

the

 close of the field season.

 Code 14. This is a snag that should have been tallied on the subplot at the previous 

Mt1/Mt3

 survey but was missed. If a tree has grown above 5.0 inches (12.7 cm) and died since the 

last

 Mt1/Mt3, it should be assigned code 05 instead of code 14.

FADER (CA/PNW PS Only)

 Fader trees have fading foliage and are expected to die within the next year.

 Code Definition

 0 Not a fader tree

 1 Fader tree

SPECIES

 Select the appropriate species code from Appendix A. If you encounter a species not 

listed in

 Appendix A and are not sure if it should be tallied as a tree, consult your Field 

Supervisor. If

 species cannot be determined in the field, bring branch samples of foliage from the plot to

your

 State FHM Project Coordinator or Field Supervisor for identification. Collect samples outside

of

 the subplots from similar specimens and make a note to change the species code later.

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OLD DIAMETER at BREAST HEIGHT

 This is the DBH that was assigned at the previous Mt1 or Mt3 survey. It has been downloaded

 from the previous inventory. Any change made to this field signifies a misclassification at

the time

 of the previous inventory. "DBHCheck" should be set to 1 and an explanation is required in 

the

 notes if the old DBH is changed.

 If a tree was missed during a previous survey (Current Tree History, code 9), estimate the 

diameter

 at the time the tree was missed, and then record the estimated old DBH.

DIAMETER at BREAST HEIGHT

 Measure diameter at 4.5 ft (1.37 m) above the groundline, on the uphill side of the tree. If

the tree

 has been measured during a previous survey, remeasure DBH at the painted mark. If the 

paint

 is starting to wear off, mark the tree again at the same spot.

 If this is the first time the tree has been measured, mark the point of measurement with a 

thin line

 of paint placed 0.1 inch (1 cm) below the point of measurement. Mark the tree before the 

taking

 the measurement, and then use a D-tape to measure outside bark diameter. Round the diameter

 down to the last 0.1 inch (1 mm) and code as 3 digits (4 digits in metric). For example, 

3.68

 inches is coded 036 (36.84 cm is coded as 0368).

 Upon encountering any irregularities such as swellings, bumps, depressions, or branches, mark

 and measure diameter immediately above the irregularity wherever the stem form appears 

normal.

 Forfenceline trees that contain wire, mark and measure the diameter at the normal 4.5 ft 

(1.37 m)

 height. Mark and measure swell-butted trees (such as cypress, tupelo, sitka spruce, and 

redwood)

 at 1.5 ft (0.5 m) above the pronounced swell or bottleneck if the bottleneck is more than 

3.0 ft (1

 m) high (Figure 1.5).

 Forked trees require special attention. In order to qualify as a fork, the stem in question

must be

 at least 1/3 the diameter of the main stem and must branch out from the main stem at an 

angle

 of 45 degrees or less.

 Trees forked below 1 ft (.3 m) are considered to be two separate trees. Distances and 

azimuths
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 are measured individually to each tree, so they may differ. In the case of stump sprouts or

clumps

 that are forked below 1 ft (.3 m), horizontal distance (and azimuth) is measured to where 

the stem

 enters the stump, so it is possible for some stems to be within the limiting distance of the

plot, and

 others to be beyond the limiting distance. DBH is measured for each stem at 4.5 ft (1.37 m)

above

 the ground.

 Trees that have no forks below 4.5 ft (1.37 m) are measured as one single tree. If a fork 

occurs

 at or immediately above 4.5 ft (1.37 m), mark and measure diameter below the fork just 

beneath

 any swelling that would inflate DBH.

 Trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m) are handled differently. All forks are

measured

 individually, but only one distance and azimuth (to the central stump) is used for all. 

Thus, in the

 case of stump sprouts or clumps that are forked above 1 ft (.3 m), the limiting distance is 

the same

 for all forks-they are either all on, or all off the plot.

 For trees forked between 1 ft (.3 m) and 4.5 ft (1.37 m), the DBH of each fork is measured 

at a

 point 3.5 ft (1.07 m) above the crotch where the bark separates. It is possible to have 

multiple

 forks, but count only forks that originate from the main stem (i.e., never count a fork 

that originates

 from another fork). If a main stem forks again within 3.5 ft of a lower fork, measure up 

another 3.5

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 61 of 86

 ft (1.07 m) from the second fork. For example, a tree with a main stem that forks at 2.0 ft 

(0.61

 m) and 5.0 ft (1.52 m) requires three DBH measurements. The lower fork is measured at a 

point

 3.5 ft (1.07 m) above the crotch. Since the main stem forks again within 3.5 ft (1.07 m) of 

the

 lower crotch, the upper two forks are measured at a point 3.5 ft (1.07 m) above the second 

fork.

 Upon remeasurement, if a previously tallied fork has died, move the point of DBH on the 

living

 stem back to where it would have been if there has never been a fork, and record a "1" for 

DBH

 CHECK. In addition, make a note that a fork has died and the point of DBH has been moved.

DBH CHECK

 Identify any irregularities in DBH measurement positions (e.g., abnormal swellings, diseases,

 damage, new measurement positions, etc.) that invalidate the use of this tree in 

diameter

 growth/change analyses. Upon diameter remeasurement, DBH check will always equal 1 if the 

tree

 is measured somewhere other than the paint mark left by the previous crew (e.g., a fork dies 

and

 the point of measurement is moved back to 4.5 ft [1.37 m]). DBH check should also be set to 

1

 if either DBH or old DBH has been estimated for any reason (e.g., a missed tree). Whenever 

code

 1 is used, further explanation is required in the notes.

 Code Definition

 0 No problem with DBH Measurement

 1 Irregular DBH measurement

LIVE/DEAD TREE (PNW PS Only)

 Specify whether the tree is alive, standing dead, or dead and down.

 Code Definition

 0 Tree is living.

 1 Tree is standing dead.

 2 Tree is dead and down

OLD STEM COUNT (WEST ONLY)

 For western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). This is the stem count recorded at the previous Mt1 or Mt3 
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survey.

STEM COUNT (WEST ONLY)

 For western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). If there is at least one stem 1.0 inches (2.54 cm) DRC or 

greater, then

 record the total number of stems measured for DRC (e.g., all qualifying stems). Note that 

all

 qualifying stems must be at least 1.0 inches (2.54 cm) in diameter at the root collar and 

contribute

 to the overall crown. For dead stems, a judgement call must be made as to whether they had

 contributed to the crown at one time, or whether they were just interior branches. Dead 

stems

 must still be at least 1.0 inches (2.54 cm) in diameter at the base.

OLD DIAMETER AT ROOT COLLAR (WEST ONLY)

 For western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). This is the diameter at root collar (DRC) recorded at the 

previous Mt1

 or Mt2 survey.

DIAMETER at ROOT COLLAR (WEST ONLY)

 For western woodland species only. Western woodland species are denoted by a "(ww)" in the

 species list (Appendix A). AH western woodland species are measured for diameter at root 

collar

 (DRC). This procedure has been adopted as a multistem equivalent to the DBH. Tally woodland

 trees with at least one stem greater than or equal to 1.0 inches (2.54 cm) and a cumulative

DRC

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 of 5.0 inches (12.7 cm) or greater. Measure all qualifying stems and calculate the DRC using 

the

 formula below.

 DRC =

stem diameter^1

 Round the result to the nearest 0.1 inch (2 mm) and record. For single-stemmed woodland 

trees,

 the DRC is equal to the diameter of that stem at its root collar. The PDR is equipped 

with a

 program for calculating this formula in the "Pop Up" menu. This "Pop Up" program is limited 

to a

 total of 13 stems. If more than 13 stems are encountered, DRC must be manually calculated.

 Record all pertinent stem measurements on the supplemental Multistemmed Woodland Tally form

 to provide for future tracking of individual stem data. Record dead stems with the small 

letter "d"

 following the 3 digit code (4 digit metric).

 Some woodland trees, particularly juniper and oak, are extremely variable in form. Measure 

the

 DRC of stems so that the measurements are consistent with the volume above the stem(s),

 especially when trees are extremely deformed at the base. For example, when a single 

diameter

 measurement taken below several main stems originating near the root collar does not 

reasonably

 represent the tree volume of the stems, individually measure the qualifying stems (above the

single

 diameter location) and compute the DRC (see Figure 1-6). When in doubt, measure individual

 stems rather than one large stem. Mark the point of diameter with paint to maintain 

consistency

 upon remeasurement.

 Whenever DRC is impossible or extremely difficult to measure with a diameter tape (e.g., due

to

 thorns, extreme limbiness, packrat's nest), the stem(s) may be measured to the last whole 

inch

 (centimeter) with the measurement poles. In this case, always record the stem(s) to the 

nearest

 1-inch (1-cm) class and use these values in DRC computations.

HORIZONTAL DISTANCE

 Measure the horizontal distance (to the nearest 0.1 foot [0.1 m]) from the subplot center to

the pith

 at the base of the tree.

 For all western woodland trees, the horizontal distance should be taken from the 

"geographic

 center" to the subplot/microplot center. The geographic center is a point of equal distance 

between
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 all stems tallied for a given woodland tree. If only one stem is tallied, the procedure is

the same

 as for timber trees.

 NOTE: For trees forked at or above 1 ft (.3 m), record the distance to the central stem at 

ground

 level for all forks. For trees forked below 1 ft (.3 m), record the distance to where each 

individual

 stem enters the stump (or clump).

AZIMUTH

 From subplot center, sight the base of each tree with a compass (sight the geographic 

center for

 western woodland species). Record azimuth (to the nearest degree) as a 3-digit code ranging 

from

 001 to 360. Use 360 for due north.

 NOTE: For trees forked at or above 1 ft (.3 m), record the azimuth to the central stem at 

ground

 level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each 

individual

 stem enters the stump (or clump).

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 MORTALITY YEAR

 In the case of tree histories 05, 06 and 07, record the year (2-digit) in which the tree 

died or was

 felled.

 ESTIMATED MORTALITY YEAR (CA/PNW PS)

 In the case of Mt1 mortality, record the year (2-digit) in which the tree died.

 NONFOREST YEAR

 In the case of tree history, code 08, record the year (2-digit) in which the land use 

become

 nonforest.

 GROUND YEAR

 Record the year (2-digit) in which a snag falls to the ground or no longer stands on its 

own.

 CAUSE OF DEATH

 Assign a cause of death to all trees that have died or been cut since the previous 

survey. In some

 cases, it will be difficult to determine cause of death, but do not guess. If uncertain, 

use code 800.

 If a cause of death is not on the list, use code 999 and explain in the notes. Code 001 

is assigned

 at processing for all trees that are dead when initially encountered (e.g., MT1 snags).

 Code Definition

 001 Tree dead when first encountered

 100 Insects

 210 Blister rust (CA/PNW PS only)

 200 Disease

 300 Fire

 400 Animal

 500 Weather

 600 Suppression/Competition

 700 Logging and related; human damage

 800 Unknown

 000 No secondary cause

 999 Other than described above; needs explanation in notes.

CROWN CLASS

 Rate the tree crown in terms of sunlight received and proximity to neighboring trees (Figure

1-7).

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 0195msd94.fig7

Figure 1-7. Relative crown positions of dominant (D), codominant (C), intermediate (I), and 

overtopped (O) trees.

 Definition

 Open Grown. Trees whose crowns have received full light from above and

 from all sides during early development and most of their life. Their crown
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 form or shape appears to be free of influence from neighboring trees.

 2 Dominant. Trees with crown extending above the general level of the crown

 cover and receiving full light from above and partly from the sides. These

 trees are taller than the average trees in the stand and their crowns are 

well

 developed, but they could be somewhat crowded on the sides.

 3 Codominant. Trees with crowns at the general level of the crown canopy.

 Crowns receive full light from above but little direct sunlight penetrates 

their

 sides. Usually they have medium-sized crowns and are somewhat crowded

 from the sides. In stagnated standards, codominant trees have small-sized

 crowns and are crowded on the sides.

 4 Intermediate. These trees are shorter than dominant and codominants, but

 their crowns extended into the canopy of codominant and dominant trees.

 As a result, intermediates usually have small crowns and are very crowded

 from the sides.

 5 Overtopped. Suppressed trees with crowns entirely below the general level

 of the crown canopy that receive no direct sunlight either from above or the

 sides.

 NOTES

 Indicate if any written notes are to be recorded for this tree. A "1" downloaded to 

this field

 indicates the presence of notes from a previous field.

 Code Definition

 0 No notes will be recorded for this tree.

 1 Written notes will be recorded for this tree

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DESCRIPTION

 Record tree-level notes in the alphabetic field provided on the PDR. These notes will be 

reviewed

 by the regional coordinator and passed onto future crews if appropriate.

ADDITIONAL CROWN AND DAMAGE VARIABLES

 The following crown classifications are described in Section 2: Crown Vigor, Crown 

Diameter

 Wide, Crown Diameter 90°, Live Crown Ratio, Crown Density, Crown Dieback, and Foliage

 Transparency.

 The following damage classifications are described in Section 3: Location 1-3, Damage 1-3, 

and

 Severity 1-3.

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 1.6.7 Full-Hectare Plots (CA/PNW PS only)

 Full-hectare plots are available for situations where the 1/6-acre (l/l5th-hectare) area 

covered by the

four subplots is too small to provide an accurate estimate of tree and stand characteristics. 

Full-hectare

plots are done for two reasons: (1) To obtain more sample trees in stands containing extremely 

large

trees, such as redwoods and sequoias, and (2) to obtain better estimates of tree mortality. 

Full-hectare

plots are supplementary. They do not replace the standard subplots, so the regular plot network 

remains

consistent across the landscape.

 Full-hectare plots include the circular area defined by a 186.2 ft (56.4 m) radius 

extending from the

center of Subplot 1. Both boundary and tree data are recorded on the full hectare. Two types of 

trees are

tallied: (1) Large, living trees greater than or equal to 40 inches (100 cm) DBH (Subsection 

1.6.7.2), and

(2) mortality trees (Subsection 1.6.7.3). "Fader" trees are counted among the living and the 

dead on the

full hectare. These trees are trees with fading foliage that are expected to die within the 

next year.

Although they are tallied as living trees on the standard FHM subplots and microplots, and as 

large trees

on the full hectare (if they are at least 40 inches (100 cm) DBH), they are recorded again on 

the mortality
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plot to provide consistency with Forest Pest Management (FPM) mortality data.

1.6.7.1 Full-Hectare Boundary Delineation (CA/PNW PS Only)

 All full-hectare plots that straddle more than one condition class are mapped by 

delineating the

boundaries between contrasting conditions. These procedures are similar to those used for 

mapping

subplots (see Subsection 1.6.3.2), except there are no provisions to reference full-hectare 

boundaries to

offset points.

 Boundary data are used to compute the area of all fragments on the hectare by condition 

class. In

addition to recording the boundary information described below, a map of condition boundaries 

should also

be sketched on pre-printed plot diagrams.

Procedure

 Delineate the boundary of each condition class that differs from the condition at a fullhectare plot

center with a series of reference points. Boundary delineation is accomplished by recording 

azimuths and

distances from the plot center to the perimeter reference points. Each boundary is marked by 

a maximum

of three points-two where the boundary intersects the circumference of the hectare, and one 

"corner" point

between the two end points, if necessary. Only the corner points require a distance, since the 

distance

from the center to the perimeter is constant.

 When a boundary between forest and nonforest is clearly marked (i.e., by a fence, fireline, 

ditch), the

boundary should follow the stems of the trees at the forest edge. When a boundary between 

two

contrasting forest conditions is not clearly marked, "average in" the boundary between the two 

conditions.

Upon remeasurement, do not move boundaries unless there has been a definite change, an obvious

mistake made during the previous visit, or a clear boundary is no longer detectable.

 When the boundary between two different conditions is separated by a narrow linear inclusion

(woods

road, fireline, ditch), always establish the boundary to the nearest edge of the inclusion. 

The quick

reference full-hectare boundary screen (Table 1-11) lists the full-hectare boundary delineation 

variables.

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HECTARE CENTER CONDITION

 This is the Condition Class of the hectare plot center. Record the previously defined 

condition that

 corresponds to the subplot center.

HECTARE CONTRASTING CONDITION

 Record the Condition Class that contrasts with the Condition Class located at the hectare 

plot

 center (i.e., the Condition Class on the other side of the boundary line).

LEFT AZIMUTH

 The azimuth (001-360°) to the farthest left point (facing the contrasting condition) where 

the

 boundary intersects the hectare perimeter.

CORNER AZIMUTH

 The azimuth (000-360°) from the hectare plot center to a corner or curve in a boundary. If 

a

 boundary is best described by a straight line between the two circumference points, then 

record

 000 for corner azimuth (000=none).

CORNER DISTANCE

 Using a distance range finder or other accepted method, approximate the distance from the 

hectare

 plot center to the boundary corner point. Record hectare distances to the nearest 1 ft 

(0.1 m).
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RIGHT AZIMUTH

 The azimuth (001-360°) to the farthest right point (facing the contrasting condition) where 

the

 boundary intersects the hectare perimeter.

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1.6.7.2 Full-Hectare Large-Tree Cruise (CA/PNW PS Only)

 The purpose of the full-hectare cruise is to obtain better estimates of tree and stand 

characteristics

associated with extremely large trees. This screen is activated on any plot that has at least 

one forested

condition class on one of the regular subplots and has at least one tree 40 inches (100 cm) DBH 

or larger

within 186.2 ft (56.4 m) of the center of Subplot 1. Once prompted, the full-hectare module 

remains active

in future surveys until there are no longer any trees greater than 40 inches (too cm) on the 

hectare. The

full-hectare large tree screen is used in conjunction with the Full-Hectare Boundary 

Delineation module,

so Tally trees can be assigned to the appropriate condition classes. Western woodland species 

are not

tallied on the full hectare.

 Tree data from the full-hectare cruise are supplemental to data gathered on the subplots 

and

microplots. The full-hectare cruise is therefore conducted somewhat independently of the standard

subplots

and microplots, but Condition Classes defined on subplots are also used for the full hectare. 

Only trees

40 inches (100 cm) DBH and larger are tallied as part of the large-tree cruise. All fullhectare tree Tally

will also be mapped on hard copy.

The quick reference full-hectare tree screen (Table 1-12) lists the full-hectare large tree 

variables.

Procedure

 HECTARE TREE TYPE

 Specify whether the tree is being measured as a large tree or a mortality tree on the 

full-hectare

 plot. The use of Code 1 will activate the prompts for full-hectare large trees, code 2

will activate

 the prompts for full-hectare mortality trees. Note: Large fader trees, as well as large 

mortality

 trees (downloaded Mt3 trees with current tree histories of 06) are measured twice on 

the full

 hectare-once as Hectare Tree Type 1 and again as Hectare Tree Type 2.

 Code Definition

 1 Full-hectare large tree (including large faders)

 2 Full-hectare mortality tree (including all faders)

 TREE NUMBER

 Tree numbers are recorded by field crews on special QA reference plots only (i.e., QA 

Status =

 3). On all other plots, tree numbers are assigned during data processing after the field

season.

 This field is therefore not presented to Mt1 crews. Once assigned, tree numbers are 

permanent

 and are downloaded to future Mt2 and Mt3 crews.

 PREVIOUS CONDITION CLASS

 Downloaded from the "Condition Class" assigned to this tree at the previous Mt1/Mt3 

survey.

 CONDITION CLASS

 Using the same procedures described for subplot trees in Subsection 1.6.1, record the 

Condition

 Class in which the tree is currently located. The tree must be in one of the conditions

in the

 Hectare Condition List. (Code 1 = Condition ... Code 9 = Condition 9).

 TREE LOCATION

 Record the appropriate code.
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 Code Definition

 0 Tree does not occur on subplot or microplot

 1 Tree occurs on subplot

 2 Tree occurs on microplot

 OLD TREE HISTORY, CURRENT TREE HISTORY

 Tree history codes track the status of the sample trees through each 4-year measurement 

cycle.

 Old Tree History is the status of the tree at the previous Mt1 or Mt3 survey (there is 

no provision

 for Mt2 full-hectare plots). Old Tree History has been downloaded and cannot be 

modified.

 Current Tree History is the present status of the tree. Select the code below that best 

describes

 the sample tree. The Current Tree History recorded by the field crew is utilized to 

determine which

 additional variables will be displayed on the PDR. A complete listing of full-hectare 

tree history

 codes is provided below (Table 1-20). An 'x' has been placed beside those Current Tree

History

 codes that are valid for full-hectare large trees. Not all of the tree history codes 

utilized for regular

 subplot trees are valid for full-hectare trees. Note that snags are not distinguished

from other

 mortality on the hectare.

Table 1-20. Valid Full-Hectare Tree History Codes by Measurement Types

Code

01

03

06

07

08

09

10

11

12

13

Current Tree History Mt1

Live/Survivor tree x

Ingrowth tree on full hectare

Dead tree

Cut tree

Land use change

Missed live tree

Extra tree

Access Denied

Dangerous condition

Lost Data

Mt3

x

x

x

x

x

x

x

x

x

x

Further elaboration on full-hectare tree history codes is provided below:

 Code 01. Live/Survivor trees on the hectare are live trees equal to or greater than 40.0 

inches

 (100 cm) DBH. Code 01 is used in the following cases:

 A live Mt1 tree encountered for the first time.

 A downloaded hectare tree that is still alive.

 A live Mt3 tree encountered for the first time (newly forested plots, points, and

condition

 classes). These are added by scrolling past all downloaded trees on the 

appropriate

 point(s).

 A fader tree (which should be assigned damage code 26).

 Code 03. Ingrowth trees on the hectare are trees on previously forested condition classes

that
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 have grown above the 40.0 inch (100 cm) DBH threshold since the previous Mt1/Mt3 survey. 

This

 also includes fader trees.

 Code 06. A downloaded hectare tree that has died or become a fader tree. Snags are not

 distinguished from other dead trees on the hectare mortality screen.

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 Code 07. A downloaded hectare tree that has been cut.

 Code 08. A downloaded hectare tree on land that has been withdrawn from a forest land use,

 regardless of whether the tree is alive, dead, standing, or down.

 Code 09. A tree that should have been tallied as a live large hectare tree at the previous 

Mt1/Mt3

 survey but was missed. It is added to the PDR by scrolling past all downloaded trees on the

 appropriate point.

 Code 10. A downloaded hectare tree that was tallied at the previous Mt1/Mt3 survey but 

should

 not have been.

 Code 11. A downloaded hectare tree to which access has been denied.

 Code 12. A downloaded hectare tree on land that is too hazardous to occupy.

 Code 13. A downloaded hectare tree on a plot that cannot be relocated. This code is valid 

only

 after the close of the field season.

SPECIES

 Select the appropriate species code list (Appendix A). Woodland species not tallied.

OLD DBH

 Use the same procedures described for subplot trees in Subsection 1.6.6.

DBH

 Use the same procedures described for subplot trees in Subsection 1.6.6.

DBH CHECK

 Use the same procedures described for subplot trees in Subsection 1.6.6.

POINT NUMBER

 Full-hectare trees can be referenced to the center of the most convenient subplot. Record 

the

 number of the subplot to which the tree is referenced. There is no provision for referencing

trees

 to offset points on the full-hectare plot. Note: Borderline trees must be checked with 

a tape,

 measured from the center of Subplot 1.

HORIZONTAL DISTANCE

 Measure the horizontal distances to sample trees from the center of the most convenient

 subplot to the center of the tree at its base. Record the distance to the nearest 0.1 ft 

(0.1 m).

 NOTE: For trees forked at or above 1 ft (.3 m) record the distance to the central stem at 

ground

 level for all forks. For trees forked below 1 ft (.3 m), record the distance to where each 

individual

 stem enters the stump (or clump).

AZIMUTH TO NEAREST POINT

 From the center of the most convenient subplot, view the center of the tree at its base.

 Record the azimuth (to the nearest degree) as a 3-digit code ranging from 001 to 360. Use 

360

 for north.

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 NOTE: For trees forked at or above 1 ft (.3 m) record the azimuth to the central stem at 

ground
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 level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each 

individual

 stem enters the stump (or clump).

MORTALITY YEAR

 Use the same procedures described for subplot trees in Subsection 1.6.6.

NONFOREST YEAR

 Use the same procedures described for subplot trees in Subsection 1.6.6.

CAUSE OF DEATH

 Use the same procedures described for subplot trees in Subsection 1.6.6.

CROWN CLASS

 Use the same procedures described for subplot trees in Subsection 1.6.6.

NOTES

 Use the same procedures described for subplot trees in Subsection 1.6.6.

DESCRIPTION

 Use the same procedures described for subplot trees in Subsection 1.6.6.

ADDITIONAL CROWN AND DAMAGE VARIABLES

 Use the same crown classification procedures described for subplot trees in Section 2 for: 

Crown

 Diameter Wide, Crown Diameter 90°, Live Crown Ratio, Crown Density, Crown Dieback, and

 Foliage Transparency.

 Use the same damage classification procedures described for subplot trees in Section 3 

for:

 Location 1-3, Damage 1-3, arid Severity 1-3.

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1.6.7.3 Full-Hectare Mortality Plot (CA/PNW PS Only)

 Compared to the other components of stand dynamics (survivor growth and regeneration), 

mortality

is a relatively rare occurrence. The main function of the full-hectare mortality cruise is to

provide an

estimate of mortality during the initial Mt1 survey rather than waiting four years for mortality

data from the

Mt3 remeasurement. This screen is activated on any plot that has at least one forested condition

class on

one of the regular subplots. It must be used in conjunction with the Full-Hectare Boundary 

Delineation

screen, so mortality trees can be assigned to the appropriate condition classes (see Subsection 

1.6.7.1).

 Data from the full-hectare mortality cruise are supplemental to data gathered on the 

subplots and

microplots. Mortality data are gathered only from forested condition classes. Ignore mortality

occurring

in condition classes that are currently nonforest, even though the area may have previously 

been forest.

The full-hectare cruise is conducted somewhat independently of the standard subplots and 

microplots,

except that Condition Classes defined on the subplots are also used for the full hectare. All 

trees tallied

as part of the mortality plot will be mapped on the field form.

Procedure

 Mortality trees have no living cambium above DBH; they can either be standing or on the 

ground.

"Fader trees are also tallied as mortality. Western woodland species are not counted on the 

Full-Hectare

Mortality Plot. Cut trees are also excluded because of difficulties in reconstructing pre-cut 

data. Note that

the procedures described below also apply to situations where there has been catastrophic 

mortality (i.e.,

fire, insect infestations).

 On Mt1 plots, and other forest plots where a previous full-hectare mortality sample does not

exist, mark

all qualifying mortality trees with a double blaze 1 foot (0.30 m) high on the stump (mark 

"faders" with red
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crayon at DBH). Mark and tally all mortality trees (standing and down) meeting the following 

specifications:

(1) trees 11.0 inches (27.9 cm) and larger that have died during the previous 5 years on the 

full-hectare

circle surrounding Subplot 1; (2) trees 5.0 -10.9 inches (12.7 - 27.8 cm) that have died within 

the previous

5 years on the four 1/24th acre (1/60th hectare) subplots and (3) trees 1.0 - 4.9 inches (2.54 -

12.6 cm)

that have died within the past five years on the four microplots (Table 1-21). Guidelines to 

identify 5-year

mortality trees are provided in Section 3.

Tablo 1-21. Tree Sizes Sampled for Mortality by Plot Type

 Tree Size at DBH1 plot TyPe

 inches centimeters Microplot Subplot Full Hectare

1,0-4.9

5.0-10.9

11.0 +

2.54-12.6

12.7-27.8

27.9 +

X

X X

X X

X

'Trees less than 5.0 inches (12.7 cm) are referenced to the microplot center. All larger trees 

are referenced to subplot center.

 On remeasured Full-Hectare Mortality Plots (Mt3), identify all trees that have died since 

the previous

(Mt1 or Mt3) survey, ignoring any trees blazed or marked as having died prior to the last 

survey. Mark and

tally all new mortality trees as described above.

 The quick reference hectare mortality screen (Table 1-13) lists the hectare mortality 

variables.

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HECTARE TREE TYPE

 Specify whether the tree is being measured as a large tree on the full-hectare plot or a 

mortality

 tree on the full-hectare plot. The use of Code 1 will activate the prompts for full-hectare

large

 trees, code 2 will activate the prompts for full-hectare mortality trees. Note: Large fader

trees, as

 well as large mortality trees (downloaded Mt3 trees with current tree histories of 06) are 

recorded

 twice on the full hectare-once as Hectare Tree Type 1 and again as Hectare Tree Type 2.

 Code Definition

 1 Full-hectare large tree (including large faders)

 2 Full-hectare mortality tree (including all faders)

CONDITION CLASS

 Using the same procedures described for subplot trees in Subsection 1.6.6, record the 

Condition

 Class in which the tree is currently located. The tree must be in one of the conditions in

the

 Hectare Condition List.

TREE LOCATION

 Record the appropriate code. Reconstruct the location of the standing stump for mortality 

trees

 that are down.

 Code Definition

 0 Tree does not occur on subplot or microplot

 1 Tree occurs on subplot

 2 Tree occurs on microplot

MORTALITY STATUS

 Select the code below that best depicts the current status of the tree.

 Code Definition

 01 Mortality Tree (standing
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 02 Mortality Tree (down)

 04 Fader Tree

SPECIES

 Select the appropriate species code (Appendix A). Woodland species not tallied.

DBH

 If DBH can still be measured, use the same procedures described for subplot trees in 

Subsection

 1.6.3. If bark is missing, estimate what the diameter would be with bark. If only a 

stump is

 present, estimate DBH according to guidelines presented at training.

POINT NUMBER

 Trees 11.0 inches (27.9 cm) DBH and larger can be referenced the tree to the center of the 

most

 convenient subplot. Smaller trees are referenced to the center of the subplot or microplot 

on which

 they occur. There is no provision for referencing trees to offset points. Record the 

number of the

 point to which the tree is referenced.

HORIZONTAL DISTANCE

 Measure all distances to sample trees from the center of the subplot to which the tree is

 referenced, to the center of the tree at its base. Reconstruct the location of the 

standing stump

 for mortality trees that are down. Record the distance to the nearest 0.1 ft (0.1 m). 

Borderline

 trees must be checked with a tape, measuring from the center of the hectare.

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 NOTE: For microplot mortality trees less than 5.0 inches (12.7 cm) DBH, reference the tree 

to the

 microplot center instead of the subplot center.

 NOTE: For trees forked at or above 1 ft (.3 m) record the distance to the central stem at 

ground

 level for all forks. For trees forked below 1 ft (.3 m), record the distance to where each

individual

 stem enters the stump (or clump).

AZIMUTH

 From the center of the subplot or microplot to which the tree is referenced, view the center

of the

 tree at its base. Estimate the location of the standing stump for mortality trees that are 

down.

 Record the azimuth (to the nearest degree) as a 3-digit code ranging from 001 to 360. Use 

360

 for north.

 NOTE: For microplot mortality trees less than 5.0 inches (12.7 cm) DBH, reference the tree 

to the

 microplot center instead of the subplot center.

 NOTE: For trees forked at or above 1 ft (.3 m) record the azimuth to the central stem at 

ground

 level for all forks. For trees forked below 1 ft (.3 m), record the azimuth to where each 

individual

 stem enters the stump (or clump).

MORTALITY YEAR

 Record the 2-digit year in which the tree died.

CAUSE OF DEATH (PRIMARY)

 Use the same procedures described for subplot trees in Subsection 1.6.6, assigning the cause

 estimated to be the "primary" cause of death.

CAUSE OF DEATH (SECONDARY)

 Use the same procedures described for subplot trees in Subsection 1.6.6, assigning the cause

 estimated to be the "secondary" cause of death, if appropriate. If only a "primary" cause 

of death

 is apparent, record 000 for this entry.

CROWN CLASS

 Estimate the crown class occupied by the tree at the time it died according to procedures 

described
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 for subplot trees in Subsection 1.6.6.

NOTES

 Use the same procedures described for subplot trees in Subsection 1.6.6.

DESCRIPTION

 Use the same procedures described for subplot trees in Subsection 1.6.6.

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 1.6.8 Nonforest/Access Denied/Dangerous Plots

 This section describes field procedures for nonforest and inaccessible plots. These plots 

are of interest

 from the standpoint that they may once have been forest, or that they may revert to forest or 

become

 accessible in the future. Thus, they are monitored to account for lands that move into and out

 of the forest land base. Only basic plot identification data are recorded on these plots.

 A plot is considered nonforest if no part of it is currently located in forest (Land Use 

1, 12, or 13). A

 plot is inaccessible if it potentially contains forest, but access is prevented to the entire 

plot by the land

 owner or because of some hazardous situation.

 No ground plots are established at nonforest or inaccessible sample locations. If a forest 

plot has been

 converted to nonforest or becomes inaccessible, the old plot is abandoned. If a nonforest plot becomes

 forest or access is gained to a previously inaccessible plot, a new forest ground plot is

 installed from scratch.

 All nonforest and inaccessible plots are visited at Mt1 and Mt3 surveys in order to 

determine if they

 have reverted to forest or become accessible. The only nonforest/inaccessible plots visited at 

Mt2 surveys

 are those plots that were forest at the last visit.

 Procedure

 The "Nonforest/No Access/Dangerous Plot" version of Tally should be used if no part of a 

plot is

 currently located in accessible forest (Land Use codes 01,12, and 13) regardless of whether or 

not the plot

 was previously forest. Trees on previously forested plots will be reconciled at data 

processing.

 Remember, there is a distinction between plots that have been clearcut and plots that have 

been

 converted to another land use. A clearcut plot is considered to be forest until it is actively

converted to

 another land use. Additional information concerning land use classifications is contained in 

Appendix D.

 In cases where a plot is inaccessible, but obviously contains no forest, assign the plot 

to the

 appropriate nonforest land use. Access-denied and dangerous land uses are used only if there 

is a

 possibility the plot contains forest.

 It is not necessary to establish or maintain any starting points, witness trees, boundaries,

etc., on

 nonforest or inaccessible plots.

 1.6.8.1 Plot-Level Notes

 Type all notes into the fields provided on the PDR. Notes are reviewed by the regional 

coordinator

when the data are processed. If appropriate, they will be passed to future field crews in the 

form of hard

copy.

 1.6.8.2 Plot Identification

 Record the appropriate codes for each variable. The quick reference nonforest plot-level 

note screen

(Table 1-15) lists the variables recorded on nonforest plots.
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STATE

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

COUNTY

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

HEXAGON NUMBER

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

PLOT NUMBER

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

PROJECT

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

QA STATUS

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

CREW TYPE

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

MEASUREMENT TYPE

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

OLD PLOT STATUS

 Use the same procedures described for forest plots in Subsection 1.6.2.2. For Mt3 

plots,

 information concerning Old Plot Status will be provided on hard copy.

CURRENT PLOT STATUS

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

MONTH, DAY, YEAR

 Use the same procedures described for forest plots in Subsection 1.6.2.2.

LAND USE AT POINT 1...4

 Record the appropriate land use at the center of each subplot. Timberland (01), Reserved

 Timberland (12), and Woodland (13) are considered forest land uses and are invalid for 

nonforest

 plots. All other land uses are valid for this screen. Definitions and additional 

information

 concerning land-use classifications are provided in Appendix D.

 Code Definition

 0 Lost data / lost plot

 1 Timberland

 2 Cropland

 3 Improved pasture

 4 Rangeland

 5 Idle farmland

 6 Other farmland

 7 Urban and other development

 8 Marsh

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Code Definition

 9 Water

 10 Access denied

 11 Dangerous condition

 12 Reserved Timberland

 13 Woodland

 14 Rocky, barren, excessively steep terrain (nonforest)

 15 Natural alpine clearing (nonforest)

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 1.6.9 Offset Procedures

 Because subplot locations are fixed and cannot be moved or rotated, the subplot center may 

fall in the
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middle of a tree, stream, building, or some other obstruction. Since it is impossible to occupy

the point

underthese circumstances, distances and azimuths to boundaries and trees cannot be measured. 

Instead,

four points can be established on the subplot perimeter, offset 24.0 ft (7.32 m) in the four 

cardinal directions

from the subplot center. These serve as reference points for tree selection, instead of the 

subplot center.

Microplot boundary and tree data also can be recorded from subplot offset points if there is an 

obstruction

at a microplot center.

Procedure

 When a subplot or microplot center cannot be established because of an obstruction, any one 

of four

subplot offset points can be used to reference boundaries or trees. That is, all distances and 

azimuths that

would normally be taken from a subplot or microplot center are instead taken from one or more 

subplot

offset points. Subplot offset points are.located on the perimeter of the subplot in one of the 

four cardinal

directions (360, 090, 180, and 270°) from the subplot center (Figure 1-8).

 Code Definition

 0 Normal position (subplot or microplot center)

 1 North offset point

 2 East offset point

 3 South offset point

 4 West offset point

 Obstructions that necessitate the use of offset points can also make travel to and around 

the plot

difficult. The following illustrations provide information that facilitate plot establishment and

measurement

in such cases.

Case 1: An obstruction occurs at the center of Subplot 1.

 If an obstruction prevents access to the center of Subplot 1, then stop at or before the 

obstruction,

offset 24.0 ft (7.32 m) in one of the cardinal directions (360, 090, 180, or 270°), and 

complete the course

to arrive at one of the offset points. For example, say the course to plot center is 375 ft 

(114.3 m) at 34°,

the obstruction extends 17 ft (5.18 m) from plot center, and the most convenient offset point is

#3. Stop

at 358.0 ft (109.12 m), proceed 24.0 ft (7.32 m) at 180°, and then go 17.0 ft (5.18 m) at 

34°. This is will

position you at Offset Point 3 (Figure 1-9).

 If Subplot 1 cannot be occupied, Subplot centers 2, 3, and 4 must be found by starting 

from one of

Subplot 1's offset points. Travel 120.0 ft (36.6 m) in the prescribed direction (360, 120, or 

240°) to arrive

at the same offset point at the next subplot 1. Then measure 24.0 ft (7.32 m) back to subplot

center.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 79 of 86

Figure 1-8. Location of four subplot offset points.

 24.0 ft at 180'

Figure 1-9. Locating offset point #3.

Case 2: An obstruction hinders travel from Subplot 1 to Subplots 2, 3, and 4.

 If an obstruction occurs at the center of Subplot 1 or between Subplot 1 and Subplots 2, 3, 

or 4, then

Subplots 2-4 can be reached from each other (e.g., travel from Point 2 to Point 3) (Figure 1-

10). The

azimuths and distances between subplots are given in Table 1-21. If the direction is reversed 

from what

is shown in the Table 1-22 (e.g., subplot 3 to subplot 2), then use the backsight for the 

azimuth.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 80 of 86

Figure 1-10. Locating other subplot centers.

Table 1-22. Distances and Azimuths Between Subplots 2-4
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 Subplot Numbers

 From To

 Azimuth Backsight

 -degrees-

 -Distance-

 feet meters

 2

 2

 3

3

4

4

150

210

270

330

030

090

207.8

207.8

207.8

63.4

63.4

63.4

Case 3: An obstruction occurs at the center of Subplot 2, 3, or 4.

 This situation is handled the same as Case 1. Stop at or before the obstruction, proceed 

24.0 ft

(7.32 m) in one of the cardinal directions, and then finish chaining to the subplot. This will 

position you at

the targeted offset point.

Case 4: No portion of Subplot 1 can be occupied, not even the offset points.

 This situation is handled similarly to Case 1 except that instead of proceeding to an 

offset point on

Subplot 1, proceed directly to another subplot center. Stop at or before the obstruction, proceed

120 ft

(36.6 m) in one of the prescribed directions (360, 120, or 240°), and then finish chaining to 

the subplot.

This will position you at the center of the selected subplot.

Case 5: Locating offset points from each other on the same subplot.

 Once one offset point is determined, the location of other offset points can be found as 

indicated in

Table 1-23 (Figure 1-11).

Case 6: Locating the microplot center from subplot offset points.

 A microplot center can be located from subplot offset points as indicated in Table 1-24 

(Figure 1-12).

Use offset point 2 whenever possible.

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Table 1-23. Distances and Azimuths Between Offset Points

 To offset point •

 North (1) East (2) South (3) West 

(4)

 From Offset Point Azi Dist Azi Dist Azi Dist Azi Dist

 North (1)

 East (2)

 South (3)

 West (4)

deg

315

360

045

 ft

13533.9

 33.9

 48.0

 33.9

 deg

180

045

090

 English Units -

 ft deg

 48.0 225

 225

 33.9
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 48.0

135

 ft

 33.9

 33.9

 33.9

 deg

 270

 315

 — Metric Units —

 m

 48.0

 33.9

 deg

 m

 deg

 m

 deg

 m

 North (1)

 East (2)

 South (3)

 West (4)

315

360

045

 10.3

 14.6

 10.3

135

045

090

 10.3

 10.3

 14.6

180

225

135

14.6

10.3

10.3

225

270

315

10.3

14.6

10.3

Figure 1-11. Locating offset points from each other on the same subplot.

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Table 1-24. Directions from Offset Points to Microplot Centers

North (1)

Azi

def

153

Distance

ft

26.8

m

8.2

East (2)

Azi

deg

270

Distance

ft

12.0

m

3.7

South

Azi

deg
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027

(3)

Distance

ft

26.8,

m

8.2

West (4)

Azi

Distance

deg ft m

090 36.0 1 1

.0

 01B5nlBCflM.IO-12

Figure 1-12. Locating the mlcroplot center from subplot offset points.

Case 7: Tallying trees from offset points.

 Not all trees may be visible from the initial offset point. It is permissible to use more 

than one offset

point to Tally trees. Both subplot and microplot trees can be tallied from the subplot offset 

(Figure 1-13).

Thus, in the unusual case where a microplot center cannot be occupied, and there are still 

microplot trees

to be tallied, they should be measured from a subplot offset point (i.e., there is no provision 

for establishing

offset points on the microplot perimeter).

 Using the horizontal distance from an offset point to a tree, the PDR will automatically 

check borderline

trees and issue a warning if a tree is not located within the perimeter of the subplot (or 

microplot). If a tree

Is out, either hit the HOME key and record the next tree's data or hit the DELETE LINE key.

Case 8: Recording boundaries from offset points.

 Choose one offset point from which the left, right, and comer azimuths and distances can be 

measured.

If possible, select an offset point which is on the same side of the boundary as the subplot 

center.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 83 of 86

 0195msd94.Ig.13

Figure 1-13. Referencing trees to offset points.

 When referenced to an offset point, it is difficult to pinpoint where a boundary crosses the

subplot

perimeter. Left and right azimuths and distances from an offset point to the edge of the 

subplot will often

have to be estimated and should be measured to points on the boundary that are close to the 

subplot

perimeter (Figure 1-14). From the recorded data, the exact points of intersection will be 

computed at the

time of data processing.

 0195msd94.fg-l4

Figure 1-14. Estimating boundaries from offset points.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 84 of 86

Case 9: Checking limiting distances from offset points without a PDR.

 Table 1-25 lists the angle and limiting distance to 18 perimeter points on the subplot 

(Figure 1-15).

The angle is the difference between the azimuth to subplot center (180, 270, 360, or 90°) and 

the azimuth

to the tree. This angle should never be more than 90°. Borderline trees should be tallied and 

will be

checked later during data processing.

Table 1-25. Limiting Distances to 18 Points on the Subplot

Angle

dog

0

5

10

15
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20

25

30

35

40

ft

48.0

47.8

47.2

46.3

45.1

43.5

41.6

39.3

36.8

— Distan earn

14.64

14.57

14.39

14.11

13.75

13.26

12.68

11.98

11.27

deg

45

50

55

60

65

70

75

80

85

Angle

ft

sag

30.8

27.5

24.0

20.3

16.4

12.4

8.3

4.2

-Distan earn

10.33

9.39

8.38

7.32

6.16

5.00

3.78

2.53

1.28

 0195msdM.lig.15

Figure 1-15. Subplot limiting distances from offset point #4.

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 1.7 References

 Avery, T.E. 1975. Natural Resources Measurements. McGraw Hill, New York.

 Cline, S.P. (ed). 1994. Forest Health Monitoring Quality Assurance Plan. In Preparation. U.S.

 Environmental Protection Agency, Washington, D.C.

 Conkling, B.L. and G.E. Byers (eds.). 1993. Forest Health Monitoring Field Methods Guide. 

Internal

 Report. U.S. Environmental Protection Agency, Las Vegas, NV.

 Daubenmire, R. 1959. A canopy coverage method of vegetational analysis. Northwest Sci. 33:43-

64.
Forest Health Monitoring: Field Methods Guide

https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=300041HI.TXT[6/8/2017 11:40:05 AM]

 Eyre, F.H., ed. 1980. Forest Cover Types of the United States and Canada. Society of American

 Foresters, Washington, DC. 148 pp.

 Husch, B., C.I. Miller, and T.W. Beers. 1972. Forest Mensuration. The Ronald Press Company 

New

 York. 410pp.

 Mueller-Dombois, D. and H. Ellenberg. 1974. Aims and Methods of Vegetation Ecology. John Wiley

and

 Sons, New York. 547 pp.

 Overton, W.S., D. White, and D.L. Stevens. 1990. Design report for EMAP (Environmental 

Monitoring

 and Assessment Program). EPA/600/3-91/053, U.S. Environmental Protection Agency, Office of

 Research and Development, Washington, D.C.

 Scott, C.T., A.R. Ek, and T.R. Zeisler. 1983. Optimal spacing of plots comprising clusters 

in extensive

 forest inventories, p. 707-710 in Renewable Resource Inventories for Monitoring Changes and

 Trends. Corvallis, OR. Soc. Amer. For. SAF 83-14.

 Scott, C.T. 1993. Optimal design of a plot cluster for monitoring. K. Rennolls and G. Gertner 

(eds.).

 In The Optimal Design of Forest Experiments and Forest Surveys, London, England, Sept. 10-14,

 1991. Sch. of Math., Stat. and Computing, Univ. of Greenwich, London, p. 233-242.

 Scott, C.T., and W.A. Bechtold. 1994. Procedures to handle inventory cluster plots that 

straddle two or

 more conditions. Submitted to Forest Science.

 U.S. Department of Agriculture, Forest Service. 1981. Resources evaluation field instructions 

for

 California, 1981-84. Unpublished field guide on file at: U.S. Department of Agriculture, 

Forest

 Service, Pacific Northwest Forest and Range Experiment Portland, OR.

 U.S. Department of Agriculture, Forest Service. 1988. Field instructions for the fourth 

inventory of

 Pennsylvania 1988 - 1989. Unpublished field guide on file at: U.S. Department of 

Agriculture,

 Forest Service, Northeastern Forest Experiment Station, Radnor, PA.

U.S. Department of Agriculture, Forest Service. 1989a. Forest Survey Inventory Work Plan, Alabama

 1989-1990. Unpublished field guide on file at: U.S. Department of Agriculture, Forest 

Service,

 Southern Forest Experiment Station, Starkeville, MS. 61 p. plus appendices.

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 EMAP Forest Monitoring, Section 1, Rev. No. 0, October, 1994, Page 86 of 86

U S Department of Agriculture, Forest Service. 1989b. North central region forest inventory and

 " analysis field instructions. Unpublished field guide on file at: U.S. Department of 

Agriculture, Forest

 Service, North Central Forest Experiment Station, St. Paul, MN. 99 p.

U S. Department of Agriculture, Forest Service. 1992. Utah forest survey field procedures, 1992-

1993.

 Unpublished field guide on file at: U.S. Department of Agriculture, Forest Service, 

Intermountam

 Research Station, Interior West Resource Inventory, Monitoring, and Evaluation Program, 

Ogden,

 UT. 232 p.

U.S. Department of Agriculture, Forest Service. 1993. Field instructions for the southeast. 

Unpublished

 field guide on file at: U.S. Department of Agriculture, Forest Service, Southeastern Forest

 Experiment Station, Asheville, NC.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 1 of 23

 Section 2. Crown Condition Classification

Section/Title

2.1 Overview 2 of 23

 2.1.1 Scope and Application 2 of 23
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 2.1.2 Summary of Method ; 3 of 23

 2.1.3 Interferences 3 of 23

 2.1.4 Safety 4 of 23

 2.1.5 Definitions and Codes 4 of 23

2.2 Sample Collections, Preservation, and Storage 6 of 23

2.3 Equipment and Supplies 7 of 23

2.4 Calibration and Standardization , ; 7 of 23

2.5 Quality Assurance 10 of 23

 2.5.1 Crown Classification Measurement Quality Objectives 10 of 23

 2.5.2 Data Quality Procedures 10 of 23

 2.5:3 Crown Rating Precautions 10 of 23

2.6 Procedure ••,:••;-.- 11 of 23

 2.6.1 Seedling Procedure ......"."".". 11 of 23

 2.6.1.1 Vigor Class 11 of 23

 2.6.2 Sapling Procedure 12 of 23

 2.6.2.1 Vigor Class 12 of 23

 2.6.2.2 Live Crown Ratio 12 of 23

 2.6.3 Crown Evaluation Procedures for Trees 5..Q inches (12.7 cm) DBH and Larger .. 14 of 23

 2.6.3.1 Crown Diameter Measurements ,;.'.. , 14 of 23

 2.6.3.2 Live Crown Ratio 19 of 23

 2.6.3.3 Crown Density 19 of 23

 2.6.3.4 Crown Dieback 21 of 23

 2.6.3.5 Foliage Transparency 21 of 23

2.7 References 23 of 23

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2.1 Overview

 A multitude of abiotic and biotic influences shape forest trees, individual tree, seedling 

and sapling

vigor, and growth are determined by a variety of physiological and external influences, such 

as

physiological age, available light, water and nutrients. This section describes protocols to 

rate seedling,

sapling, and tree crown conditions. Procedures will be discussed beginning with seedlings, 

followed by

saplings and ending with crown evaluation for trees.

2.1.1 Scope and Application

 Individual tree vigor and growth are also determined by physiological age and available 

water,

nutrients, and light resources at a site. Both climate and site affect resource 

availability, but a tree's

position relative to its neighbors becomes critical when determining the amount of water, light, 

and nutrients

that are available for any one tree. Because of these tree-stand interactions, both standlevel data and

individual tree data must be collected.

 Seedlings are trees at least 12 inches (30 cm) or greater in height but less than 1 inch 

(2.54 cm) in

diameter at breast height (DBH) [or diameter at root collar (DRC) in the West]. All seedling 

variables are

measured on each 1/300 acre (1/750 hectare) microplot (6.8 ft [2.07 m] radius) offset from each 

plot center

at a distance of 12 ft (3.66 m), due east (90°) from each subplot center. Seedlings can 

originate from

seeds, sprouts, or layering. Only one indicator is recorded for seedlings, vigor class. Vigor

class is

determined for each -seedling but then aggregated by species, crown position, condition class, 

and vigor

class when recorded. Seedling measurements will only be done during plot establishment (Mt1) 

and when

plot remeasurement (Mt3) occurs to reduce damage to seedlings.

 Saplings are tree species with DBH (or DRC in the West) between 1.0 inch (2.54 cm) and 4.9 

inches

(12.69 cm). Like seedlings, all sapling variables are measured on each 1/300 acre (1/750 

hectare)

microplot (6.8 ft [2.07 m] radius) offset a distance of 12 ft (3.66 m), due east (90 degrees)

from each

subplot center. Sapling vigor class, as well as live crown ratio, is determined for each 

sapling. Any foliage

below the point used for live crown ratio is not considered in vigor class determination. 

Sapling vigor class
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is evaluated during plot establishment (Mt1) and then annually (Mt2). Live crown ratio is 

evaluated during

plot establishment (Mt1). Live crown ratio is also recorded during annual crown measurements 

(Mt2) when

live crown ratio changes by more than 15% (3 classes) and completely reevaluated when 

plot

remeasurement (Mt3) occurs.

 Crown evaluations describe tree conditions. An observed tree condition results from the 

preceding

year's growth processes, which are influenced by site, stand density, and external stresses. 

Therefore,

crown evaluations that quantitatively assess current tree conditions become an integrated measure

of site,

stand density, and external stresses.

 In the eastern U.S., crown diameter has been related to the size of hardwood trees (Francis, 1986;

Sprinz and Burkhart, 1987), and crown density has been related to the growth of loblolly pines

(Grano,

1957; Anderson and Beianger, 1987; Anderson et al., 1992; Belanger and Anderson, 1991). In the 

western

U.S., live crown ratio and crown density have been related to growth and survivorship of 

conifers (Dolph,

1988). Other crown variables, crown dieback, foliage transparency, and crown density, can be 

related to

insect defoliation and subsequent growth and survivorship effects on both conifers and 

hardwoods

(Kuhlman, 1971). In general, trees with high scores for live crown ratio, crown density, and 

crown diameter,

and low scores for crown dieback and foliage transparency, have increased potential for carbon 

fixation,

nutrient storage, and increased potential for survival and reproduction.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 3 of 23

2.1.2 Summary of Method

 Only one indicator is recorded for seedlings, vigor class. Vigor class is determined for 

each seedling

but then aggregated by species and vigor class when recorded. Seedling measurements will only be

done

during plot establishment (Mt1) and when plot remeasurement (Mt3) occurs to reduce damage to 

seedlings.

Sapling vigor class, as well as live crown ratio, is determined for each sapling. Any foliage 

below the point

used for live crown ratio is not considered in vigor class determination. Sapling vigor class 

is evaluated

during plot establishment (Mt1) and then annually (Mt2). Live crown ratio is evaluated 

during plot

establishment (Mt1). Live crown ratio is also recorded during annual crown measurements (Mt2) 

when live

crown ratio changes by more than 15% (3 classes), and completely re-evaluated when plot 

remeasurement

(Mt3) occurs.

 The FHM crown rating technique helps describe current tree condition. As part of this 

system, various

tree conditions and damage assessments are taken to describe attributes on all live trees 5.0 

inches (12.7

cm) DBH (or DRC in the West) or larger on the four FHM subplots. The organization of various

measurements is listed below.

 Crown Evaluation Measurements

 (1) crown diameter wide and 90°

 (2) live crown ratio,

 (3) crown density,

 (4) crown dieback,

 (5) foliage transparency.

[Note: Measurements are listed in order of data collection on each tree].

 Crown diameter and live crown ratio are done during plot establishment (Mt1) and 

during

remeasurement (Mt3). These variables are remeasured during annual crown measurements (Mt2) when

live crown ratio changes by more than 15% (3 classes) or individual crown diameter measurements 

(crown

diameter wide or crown diameter 90) changes by more than 5 ft (1.5 m). The other crown 
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measures

(crown density, crown dieback, and foliage transparency) are measured annually (Mt1, 2, and 3).

2.1.3 Interferences

 Several uncontrollable environmental and site conditions have hindered or slowed the crown 

condition

classification measurements, including (1) poor weather conditions such as gusting wind, heavy 

rain, and

dark overcast skies; (2) steep and/or unstable slopes; (3) dense understory vegetation which 

prohibits free

ground movement; and (4) thick canopy immediately overhead that obscures full view of the tree 

canopy.

Suspend data collection under severe weather conditions, such as strong winds and heavy 

rainfall.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 4 of 23

2.1.4 Safety

 No specialized safety precautions are necessary. Follow general safety precautions for 

conducting

fieldwork (See Appendix E).

2.1.5 Definitions and Codes

Definitions

 For the purposes of this guide, three crown areas are clearly defined: top, outer sides, and

base.

Three other areas also need to be defined: crown diameter, crown form, and branch.

Top

 The tree top is the highest point of a standing tree. Younger trees usually have conical 

shaped crowns

and the main terminal stem is the top. Older trees and many hardwoods have globose and flattopped

crowns, where a lateral branch is the highest point. For some measurements (live crown ratio), 

only the

highest live branch is considered, while other measurements include dead top. Crown measurements,

such

as crown density, assess how much of the expected crown is present and include all dead branches

and

snag branches (old dead branches which have lost most of the small branches and twigs, less than

1 inch

[2.54 cm] diameter at the base). Crown dieback measurements concern recent branch mortality and 

do

not include snag branches.

Base

 The crown base is defined here as the lowest live part of the crown. Include most of the 

crown

branches but exclude epicormic shoots and straggler branches that usually do not contribute much

to the

tree's growth. Most measurements define the live crown base by drawing a horizontal line from 

the bottom

of the lowest foliage of the obvious crown (usually the largest branches at the crown bottom) 

across the

trunk Thus the base of the branch may be above or below this line. Then, if any branches 

greater than

1 inch (2 54 cm) in diameter are within 5 ft (1.5 m) below this line, the base is moved down to 

the base

of the foliage on that branch. Continue to move down the trunk until no 1 inch (2.54 cm) 

diameter

branches are found within 5 ft (1.5 m). The crown base then becomes the horizontal line at the 

bottom

of the foliage of the lowest qualifying branch where it intersects the trunk.

 Occasionally all original major crown branches are dead or broken and an abundance of new 

branches

are developing. At first, before branches reach the 1 inch (2.54 cm) diameter size, the 

tree for this

measurement has no crown. When new branches reach the 1 inch (2.54 cm) diameter limit, a new 

crown

is forming. The previous obvious crown base here would be the dead branches, while many of the 

live
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branches with foliage may be below this point. The recommendation is to find the line for the 

lowest live

branch (1 inch diameter [2.54 cm] or larger) that meet the 5 ft (1.5 m) rule. These situations 

are likely to

occur in areas of heavy thinning, commercial clearcuts, and severe weather damage.

Sides of the Crown

 Most measurements consider the crown in a two-dimensional perspective, the way it would 

appear

when reflected in a mirror. The side boundaries are limited by a line drawn from branch tip to 

branch tip,

except when branches are widely separated. For the purpose of foliage abundance (foliage 

transparency),

the line would encircle each separated branch. For crown density, the perimeter is drawn from 

branch tip

to branch tip, and open spaces become part of the crown density measurement. Occasionally, a 

branch

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 5 of 23

 may protrude abnormally, but the lateral crown line may be drawn across the portion of the 

branch that

 contains most of the tips.

 Crown diameter

 Crown diameter is defined as the average of two diameter measurements: 1) widest distance 

anywhere

 in the crown between two live branches (the drip line), and 2) the perpendicular distance to 

the first

 measurement. Abnormally long branches sticking out beyond the edge of the crown are not used 

in

 establishing the extent of a crown.

 Crown shape

 Crown shape is a silhouette of an average open-grown tree. Usually, silhouettes are 

derived from

 vigorously growing trees and tend to be species specific. With age, tree crowns tend to flatten

out. Crown

 shapes are important when measuring crown density and will be used in the future with tree 

height, live

 crown ratio, crown density, and crown diameter to estimate crown biomass. Crown shape is used 

as an

 outline for the sides of the tree, and voids of branches are considered as a loss in density 

for this

 measurement.

 Branch

 A live branch is defined as any woody lateral growth supporting foliage and larger than 1-

inch at the

 base just above the swelling where it joins the main stem. Dead branches have no minimum size 

to be

 included for crown dieback estimates. Lower dead branches are not included in crown dieback. 

Dead

 upper crown branches without twigs (branches less than 1-inch diameter) are considered as old 

dead, or

 snag branches, and are not included in crown dieback estimates, but are included in crown 

density

 estimates. Secondary growth, less than 1-inch diameter, such as water sprouts, suckers, or 

epicormics,

 are excluded from the branch definition. After a sudden release or damage, a tree may have 

very dense

 foliage, but by definition no crown. These situations can be coded as follows: live crown 

ratio - 00, crown

 density -00, crown diameter (wide and 90 degrees) - 0, crown dieback - 99, and foliage 

transparency - 99.

 Codes

 General Codes

 Table 2-1 lists the PDR Prompt Codes.

Table 2-1. PDR Prompt Codes

 Variables
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 PDR Code

 Seedling Measurements:

 Seedling Vigor

 Sapling Measurements

 Sapling Vigor

 Live Crown Ratio

 Trees >5.0 in dbh:

 Crown Diameter Wide

 Crown Diameter 90 Degrees

 Live Crown Ratio

 Crown Density

 Crown Dieback

 Foliage Transparency

SeedVig

SapVig

CRatio

CrDiaW

CrDai9

CRatio

Cm Den

CrnDbk

FolTrn

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 6 of 23

 The following are the codes for seedling vigor:

 Code

 1

 2

 3

Definition

100 to 80% crown area with normal foliage, 1/3 or more of seedling height in

foliage, and less than 5% dieback in the upper or outer-exposed portion of the

crown.

79 to 21% crown area with normal foliage.

20 to 1% crown area with normal foliage.

 The following are the codes for sapling vigor:

 Code

 1

 2

 3

Definition

100 to 80% crown area with normal foliage, 1/3 or more of sapling height in

foliage, and less than 5% dieback in the upper or outer-exposed portion of the

crown.

79 to 21% crown area with normal foliage.

20 to 1% crown area with normal foliage.

 Table 2-2 lists codes which should be used for the Crown Diameter measurements.

Tablo 2-2. Crown Diameter Codes

Code

00

01

02

03

99

Definition (national)

Epicormic branches only

< 1.5 ft

1.6 to 2.5 ft

2.6 to 3.5 ft

>99.6ft

Code

000

001

002

003

995

Definition (California)

Epicormic branches only

<0.15 m

0.16to 0.25 m

0.26 to 0.35 m

>99.6 m
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 Table 2-3 lists codes which should be used for Live Crown Ratio, Crown Density, Crown 

Dieback, and

Foliage Transparency.

Table 2-3 LIva Crown Ratio, Crown Density, Crown Dieback, and Foliage Transparency Codes

Code

00

05

10

15

20

25

30

Definition

0%

1-5%

6-10%

11-15%

16-20%

21-25%

26-30%

Code

35

40

45

50

55

60

65

Definition

36-40%

41-45%

46-50%

51-55%

56-60%

61-65%

Code

70

75

80

85

90

95

99

Definition

71-75%

76-80%

81-85%

86-90%

91-95%

96-100%

 Note: Class code is the percentage of the upper limit of the class, i.e. Code 10 is 6% to 10%, 

etc. Also for live crown ratio the

 code 00 is used for trees with epicormic branches only.

 2.2 Sample Collections, Preservation, and Storage

 No material samples are collected.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 7 of 23

2.3 Equipment and Supplies

 The list below includes all equipment and supplies needed for two persons to 

perform all

measurements described in this section. All measurements are recorded on portable data 

recorders

(PDRs).

 Binoculars - required, 1 set per field crew

 Crown Density - Foliage Transparency Card - required (provided), 1 for each field crew 

personnel

 75-ft loggers tape (or equivalent) - required, 1 per field crew

 Clinometer - optional, 1 per field crew

 Crown Grid - optional, 1 per field crew
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2.4 Calibration and Standardization

 General calibration and standardization protocols should be applied to field equipment. 

Purchase tapes

to required specifications. Tapes should be maintained in working order and do not require 

calibration upon

confirmation of accuracy. Use the crown density - foliage transparency card to calibrate the 

observer's

eyes at the start of every day and on those trees that do not fit into an obvious class.

 The crown density - foliage transparency card (Figure 2-1) should be used as a training aid 

until crew

personnel are comfortable with both ratings. White areas of the card represent skylight visible 

through the

crown area and black areas represent some aspect of the tree. For crown density, hold the card 

so that

"Crown Density" is right-side up ("Foliage Transparency" should be upside down). Use the numbers 

that

are right-side up. Conversely, for foliage transparency, make sure that "Foliage Transparency" 

is right-side

up. Crews should refer to specific crown density or foliage transparency sections for a 

definition of aspects

that are included in the crown rating. Crews should use the card to calibrate their eyes at the 

start of each

day and on those trees that do not fit into an obvious class.

 The back of the crown density - foliage transparency card has two uses: for crown density 

when a

portion of the crown is missing and a general scale for estimating live crown ratio. Crews 

should refer to

the crown density and live crown ratio sections to use this side of the card.

 A crown grid is used in training for crown area estimation. The crown grid was developed 

from similar

grids used to estimate areas on maps. The area does not represent a quantitative unit since the grid is

intended to determine proportions. The central square has 100 dots, and each peripheral square

has 25

dots (Figure 2-2). The grid may be copied on a transparency and mounted on thick PlexigiasTM 

with clear

cellophane tape for field use.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 8 of 23

 Crown Density Scale

 65 55 45 35 25 15

 & &'\ /::r*i /'*\

 $& © 0

 9S 9£ 5V 99 99 9Z

 eieos AouejedsuejjL e5e||oj

Front

Back

 Density of Tree, Present

 35 45 55 65 75

 85 95

g>10

"^20

§ 30

§40

£50

"o 60

§70

5£ 80

O)

0.90

5

5

5

5

5

5

5

5

5

15

15

15
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10

10

10

5

5

5

25

20

20

15

15

10

10

5

5

35

30

25

25

20

15

15

10

5

45

40

35

30

25

20

15

10

5

50

45

40

35

30

25

20

15

10

60

55

50

40

35

30

20

15

10

70

60

55

45

40

30

25

15

10

80

70

60

55

45

35

30

20

10

90

80

70

60

50

40

30

20

10

o
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5"

<3

0

J2-

3

I

o

o

tD

CD

 CD

 o

00

o

o

 c

 Cj

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 to

 o

T"

 o

~r

 Figure 2-1. Crown density - foliage transparency card (front and back).

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 9 of 23

Figure 2-2. Crown grid.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 10 of 23

2.5 Quality Assurance

2.5.1 Crown Classification Measurement Quality Objectives

 Table 2-4 lists Crown Classification Measurement Quality Objectives.

Table 2-4 Crown Classification Measurement Quality Objectives

 Variable

 Reporting

 Units

 Data Quality

 Limits

 Vigor Class

 (Seedling and Sapling)

 Crown Diameter Wide1

 Crown Diameter 90 Degrees'

 Live Crown Ratio

 Crown Density

 Crown Dieback

 Foliage Transparency

 3 classes

1 ft (30 cm)

1 ft (30 cm)

21 classes

21 classes

21 classes

21 classes

90% agreement

90% @ ± 5 ft (1.5 m) or 10% of the-mean

(whichever is larger)

90% @ ± 5 ft (1.5 m) or 10% of the mean

(whichever is larger)

90% @ ± 10% (2 classes)

90% @ ± 10% (2 classes)

90% @ ± 10% (2 classes)

90% @ ± 10% (2 classes)

'Only evaluated as the difference between the mean of the 2 crown diameter measurements.

2.5.2 Data Quality Procedures
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 Sources of measurement differences include boundary estimates for the crown and the affected 

area,

ability to detect damage, and rater's ability to estimate crown conditions. Differences between 

observers

can be minimized by open and frequent communication between crew members. Consistency and 

quality

are also encouraged by changing observation positions and repeating estimation 

procedures.

 In addition, remeasurements may differ because of weather conditions, particularly light, 

and when a

sufficient amount of time has passed to allow changes in the tree itself. Remeasurements 

taken

immediately after the original measurement is best to determine variability among raters. This 

procedure

should be used during the training and certification program. All remeasurements should be 

completed

less than two weeks after trees were originally rated.

 Crown indicators (crown diameter measurements, live crown ratio, crown density, crown 

dieback, and

foliage transparency) can be easily reproduced partly because the indicators are easy to apply and

because of data quality expectations of ± 10 percent (or 2 classes), 90% of the time. To meet

these

standards, proper training and follow-up are vital throughout the program. All crown rating 

procedures

require two individuals to rate each tree for each variable and agree on a final value to enter 

into the PDR

(exception: crown diameter wide and crown diameter 90).

2.5.3 Crown Rating Precautions

 The following areas show where crown indicators could be difficult to evaluate and crews 

must be

especially careful:

Distance from the tree -

 Crews must attempt to stay at least 1/2 to 1 tree length from trees. Some ratings change 

with proximity

to the tree. In some situations, it is impossible to satisfy this step, so the crew should try to do the best

in each case.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 11 of 23

View of the crown -

 In a forest, getting a good perspective of the crown becomes difficult. Overlapping 

branches,

background trees, and lack of a good viewing area can cause problems. Crews need to move 

laterally to

search for a good view. Density of stands may prohibit a full view. Take special care when 

rating such

trees.

Climatic Conditions -

 Cloudy or overcast skies, fog, rain, and poor sun angle may affect estimates.. Live crown 

ratio and

crown diameter may be affected but to a lesser degree than other crown indicators. Crown density

tends

to be over- or under-estimated because light does not project well through the foliage or, in 

some cases,

the light may be too bright for a good estimate. Crown dieback may be under-estimated because 

it is

difficult to see dead twigs and/or differentiate defoliated twigs from dead twigs. Foliage 

transparency

estimates could be affected in either direction because it is hard to discern foliage from 

branches. The data

quality expectation standard helps because crews can normally be within ± 10 percent, even in 

poor

weather conditions. However, crews need to be especially careful during poor lighting conditions.

Crews

should move around a tree to get another view, even if the view appears adequate at a specific 

location.
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Heavy defoliation -

 During heavy defoliation, crown dieback may be over-estimated and foliage transparency may

be

under-estimated due to the difficulty in differentiating dead twigs from defoliated twigs. 

The use of

binoculars may help in separating dead twigs from defoliated twigs.

Leaning trees -

 Trees that are leaning cause a major problem in estimating many crown variables. In these 

situations,

record crown variables as best as possible for the tree as it actually occurs rather than as it

might appear

if standing upright and also record in the tree note field that it is leaning. This will allow 

for a better data

interpretation.

2.6 Procedure

2.6.1 Seedling Procedure

2.6.1.1 Vigor Class

 Vigor class measures seedling visual crown vigor. Seedlings are classified for (1) high 

vigor, (2)

moderate vigor, or (3) low vigor. The middle class (2) is largest because the objective is to

separate

excellent seedlings (1) from very poor ones (3) and place all others in the middle class (2). 

The easiest

method for vigor classification is to determine whether the seedling meets the criteria for 

class (1) or (3).

If it does not, the seedling belongs in class (2).

Vigor Class Definitions

Vigor Class 1 - Class (1) seedlings must have more than 1/3 of the height in foliage, have less

than 5%

 dieback* in the upper half of the crown or outer-exposed portion of the crown, 

and 80

 percent or more of the foliage is normal (at least 50 percent of the individual 

leaf normal

 and present). Greater than 5% dieback in the upper or outer-exposed portion of 

the crown

 is considered abnormal.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 12 of 23

Vigor Class 2 - These seedlings do not meet Class 1 or 3 criteria. They may have any crown 

length, may

 or may not have dieback, and between 21 and 79 percent of the foliage is 

classified as

 normal.

* Dieback is defined as branch mortality which begins at the terminal portion of a branch and 

proceeds

toward the trunk. When whole branches are dead in the upper crown, without obvious signs of 

damage

such as breaks or animal injury, assume that the branches died from the terminal down.

Vigor Class 3 - Class (3) seedlings may have any live crown length and should have 1 to 20 

percent

 normal foliage. (Or the percent of foliage missing on branches with dieback and 

percent

 of abnormal foliage when combined, should equal 80 percent or more of the 

crown.)

 Branches that are dead because of normal shading are not included.

2.6.2 Sapling Procedure

2.6.2.1 Vigor Class

 Vigor class measures sapling visual crown vigor. Saplings are classified for (1) high 

vigor, (2)

moderate vigor, or (3) low vigor. The middle class (2) is largest because the objective is to 

separate

excellent saplings (1) from very poor ones (3) and place all others in the middle class (2). The

easiest
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method for vigor classification is to determine if the sapling meets criteria for class (1) or 

(3). If it does not,

classify it as a (2).

Vigor Class Definitions

Vigor Class 1 - Class (1) saplings must have more than 1/3 of the sapling height in foliage, 

have less than

 5% dieback* in the upper half of the crown or outer-exposed portion of the crown,

and 80

 percent or more of the foliage is normal (at least 50 percent of the individual 

leaf normal

 and present). Greater than 5% dieback in the upper or outer-exposed portion of 

the crown

 is considered abnormal.

Vigor Class 2 - These saplings do not meet Class 1 or 3. They may have any crown length, may or 

may

 not have dieback, and between 21 and 79 percent of the foliage is classified as 

normal.

Vigor Class 3 - Class (3) saplings may have any live crown length and should have 1 to 20 

percent normal

 foliage. (Or the percent of foliage missing on branches with dieback and 

percent of

 abnormal foliage when combined, should equal 80 percent or more of the crown.)

 Branches that are dead because of normal shading are not included.

* Dieback is defined as branch mortality which begins at the terminal portion of a branch and 

proceeds

toward the trunk. When whole branches are dead in the upper crown, without obvious signs of 

damage

such as breaks or animal injury, assume that the branches died from the terminal down.

2.6.2.2 Live Crown Ratio

 Determine sapling live crown ratio by dividing the live crown length by total tree height 

to last live

branch. Crown length is the distance between the tree top (dieback and dead branches are not 

included)

and the obvious bottom where crown foliage exists. If the crown bottom is difficult to 

identify, select a base

below "most" of the foliage. The definition of the live crown base for saplings is slightly 

different than for

trees 5.0 inches DBH (or DRC in the West) and larger, because the 5 ft/1 inch rule does not 

apply in this

case. Do not include occasional "leafed twigs" branches or leaves on the main stem below the 

main mass

of foliage (Figure 2-3).

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 13 of 23

 Sapling Crown Ratio

 0%

 Leafed twigs

 or Epicormics

 only

10%

 30%

Simple

 30%

Leafed twigs

ignored, crown

dieback not

included

 0195msd94.«g2.3

 60%

Separated

branches included,

jcwer leafed twig

ignored

Figure 2-3. Sapling live crown ratio determination examples.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 14 of 23
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2.6.3 Crown Evaluation Procedures for Trees 5.0 inches (12.7 cm) DBH and

 Larger

 The various crown indicators are designed to work together. Each indicator comprises a 

piece of

information that can be used individually or as a factor in combination with other indicators. 

Live crown

ratio is a measure of crown length and its relationship to total tree height. Trees with higher

live crown

ratios are typically viewed as healthier and faster-growing.

 Crown diameter is a measure of crown width. Wider crowns are often associated with fastergrowing

trees and are normally indicators of stocking. Once the live crown ratio and crown diameter

are

determined, the next logical step is to measure how much of a crown exists. Crown density, which

includes

foliage, branches, and reproductive structures, measures the crown biomass. Crown dieback defines

how

much of the crown does not have foliage but has fine twigs, indicating a loss of vigor or growth

potential.

Foliage transparency estimates how dense the foliage is on branches, indicating stress due to foliar

damage or defoliation.

 Some people want to know why both crown density and foliage transparency are determined when

they

seem to be inverse measures. This is true on trees having a full crown, with no crown dieback,

and no

open areas in the crown. However, the average tree does not have a full, uniform crown. For 

example,

a tree with 80 percent crown dieback could have a few living branches with a foliage 

transparency rating

of 5 percent, but the crown density rating would be 15 percent. (Crown density rating considers

a normal,

forest-grown crown form and then makes an estimate of how much is present on the tally tree. 

Foliage

transparency rating considers the foliated part of the crown only.) Some examples of crown 

silhouettes

and various limitations on crown measures are in Figures 2-4 through 2-6.

 All of these indicators have been combined into a model called the Visual Crown Rating 

Model. It is

clear that each indicator adds to the overall rating given each tree. It is important to realize

that the model

is designed to rate trees on how they look, from thriving to almost dead.

2.6.3.1 Crown Diameter Measurements

 Crown diameter at the widest point, if viewed from the air, is the diameter of a circle 

including all

foliage. Measure it at the crown's widest point with a tape by having one observer stand under 

the drip

line at the crown's edge, opposite an observer at the other side of the crown; this is the crown

diameter

wide measurement. A second measurement is made at 90 degrees to the crown diameter at the 

widest

point (crown diameter 90) using the same procedures (Figure 2-7).

 Determine drip line end points by looking up perpendicular to the tape and projecting where 

crown edge

branches would hit the ground if they fell. Occasionally, a branch may protrude abnormally, but

the lateral

crown line may be drawn across the portion of the branch that contains most tips. It is helpful

to use a

device, such as a clinometer, that allows the observer to measure a line perpendicular to the 

ground. The

device should be used for training and to check estimates made during the operational field 

season. If you

cannot see the crown edge from the drip line, both observers should move an equal distance from 

the tree

and project the crown for an estimate. All measurements are rounded to the nearest foot (nearest

0.1 m

in California) and both measurements are recorded in the PDR.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 15 of 23

 Crown Density Outline —»^
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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 16 of 23

 Crown Density Outline

 CiZJ

 Exclusion Areas for

 Foliage Transparency**

 (Crown Dieback)

 Crown Outline for Crown

 Dieback and Foliage

 Transparency

 Base of Live Crown

 Exclusion Areas for

 Crown Dieback and

 Foliage Transparency

Figure 2-5. Crown rating example, hardwood.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 17 of 23

 Crown Density Outline

 ^f N- %X •C-

 * •• v •.

 ,

 \ ^^----\-^ --.'- -^*^.

 i *—.1 -, l^^*S^!!>^ ^iM1^

 ; iwi ^

 Crown Dieback f

 and Foliage

 Transparency

 EBB Exclusion Areas for

 Crown Dieback and

 Foliage Transparency

Figure 2-6. Crown rating example, pine.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 18 of 23

 Crown Diameter

 Crown Diameter (wide) ->

 Side view

 •i^~>*

 ', &"{?*•?',' t

 N , <* I

•«—•Crown Diameter (90°)

 •\*. W J

 ^ •- S ^ •- •• ^ fff ts?Jfff****f"

 •- *"" ^-*A ^5«.'s^, MM*' 6i95m««M.ll82.7

 90° from side view

 Top view of crown diameter.

Figure 2-7. Crown diameter determination.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 19 of 23

2.6.3.2 Live Crown Ratio

 Live crown ratio is the percentage of total tree height which supports live green foliage 

that is effectively

contributing to tree growth. Live crown ratio is determined by the ratio of crown length to 

total tree live

height (Figure 2-8). Crown length is determined from the crown top with the last live branch 

(dieback on

the upper portion of the crown is not part of the live crown) to the obvious crown base. Many 

times there

are additional live branches below the obvious crown. These branches are only included if they 
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have a

basal diameter greater than 1 inch (2.54 cm) and are within 5 ft (1.5 m) of the base of the 

obvious crown.

The crown base is that point on the main bole perpendicular to the lowest foliage on the last 

branch that

is included in the live crown. The crown base is determined by the foliage and not by the point

where a

branch intersects with the main bole. Live crown ratio is measured by two raters.

 Raters step back about 1/2 to 1 tree length from the base of the tree and move sideways at 

least 10

ft (3 m) to obtain a good view of the crown. An individual can use the live crown ratio scale 

on the back

of the crown density-foliage transparency card to help in estimating live crown ratio. To use 

the scale, hold

the card in one hand and move the card closer or farther from your eye until the 0 is at the 

live top of the

tree and the 99 is at the base of the tree (ground). Then place your finger at the base of the 

live crown.

The number on the scale provides the live crown ratio. Interpolate to the nearest 5% if the 

point is between

two values on the scale. A clinometer can also be used to verify the live crown ratio by 

determining the

values of both heights and determining the ratio of the two values. This is very useful during 

training but

is not necessary under field conditions.

 When the two raters disagree in their estimates, they should discuss the reasons for their

ratings.

Either a rater will change his or her estimate, or the two ratings will be averaged and the 

class recorded.

The estimate is placed into one of 21 five percentage classes. Codes are structured to the 

nearest 5

percent to be consistent throughout this guide with other procedures and to allow estimator 

flexibility.

2.6.3.3 Crown Density

 Crown density estimates the tree crown condition in relation to a normal, healthy, forest 

tree and also

serves as an indicator of expected growth in the near future. Crown density is the amount of

crown

branches, foliage, and reproductive structures that blocks light visibility through the crown. 

Each species

of tree has a normal crown that varies with the site, genetics, tree damage, etc. Higher crown 

density

estimates are indicative of faster growth, while lower crown density measures indicate slower 

growth.

 Crown density rating is measured by two persons. Individuals should stand about 1/2 to 1 

tree length

away from the tree and move sideways at least 10 ft (3 m) to obtain a good view of the 

crown. To

determine the crown outline, select the point on the stem used for live crown ratio and project

a normal

crown for that tree. Foliage below the crown base is not included in the crown. Project halfsided trees

as full crowns, and include crown dieback and open areas in this outline. In many cases, 

portions of the

tree outline may not be complete, i.e., half-sided trees, and in these situations it may be 

easier to determine

the percent of the tree missing and the crown density of the tree's remaining portion. Then use

the table

in Figure 2-1 (Back) to arrive at the final crown density for that tree.

 After determining the outline, the two persons should hold the crown density - foliage 

transparency card

(Figure 2-1) along the line of sight and estimate what percentage of the outlined area is 

blocking sunlight.

Try to place trees in 10 percent classes; use a 5 percent class if you cannot decide which 10 

percent class

to use. If you disagree on a rating, discuss and adjust it as needed. In most cases, two 

scores can be

averaged. Two raters may try trading places if their difference is greater than 10 percent or 

two classes.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 20 of 23

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 21 of 23

 2.6.3.4 Crown Dieback

 Crown dieback is defined as branch mortality which begins at the terminal portion of a 

branch and

 proceeds toward the trunk. When whole branches are dead in the upper crown, without obvious 

signs of

 damage such as breaks or animal injury, assume that the branches died from the terminal down. 

Snag

 branches without smaller branches, 1 inch (2.54 cm) or less in diameter at the base, will not 

be considered

 as part of the crown. Dead branches below the upper half of the crown are assumed to have died

from

 competition and shading, and are not considered as part of crown dieback.

 Estimate crown dieback in 5 percent classes, based on the whole crown present at the 

time of

 observation. The crown base should be the same position that is used for the live crown ratio 

estimate.

 Assume that the perimeter of the crown is a two-dimensional outline from branch-tip to branchtip.

 Crown dieback rating is obtained by two raters. Raters should step back about 1/2 to 1 

tree length

 from the tree base and move sideways at least 10 feet (3 m) to obtain a good view of the 

crown.

 Binoculars should be used to assist in the data collection. Observers should be conscious of 

lighting

 conditions and how they affect the day's observations. Under limited-light conditions, 

observers should take

 extra time because poor lighting can make the measurement more difficult.

 First, the raters should mentally draw a two-dimensional crown outline. Second, block in 

the affected

 area. Third, the proportion of the affected area should be estimated in 5 percent classes and

recorded.

 When two raters disagree in their estimates, they should discuss the reasons for their rating. 

Either a rater

 will change his or her estimate or the ratings should be averaged and the class of the estimate

recorded.

 Differences may be due to differences in crown conditions, the estimate of the rater, or both.

 2.6.3.5 Foliage Transparency

 Foliage transparency is defined as the amount of skylight visible through the live, 

normally foliated

 portion of the crown or branch. Each tree species has a normal range of foliage transparency. 

Changes

 in foliage transparency occur as a result of current damage, frequently referred to as 

defoliation, or from

 reduced foliage resulting from stresses during preceding years.

 Estimate foliage transparency in 5 percent classes based on the live, normally foliated 

portion of the

 crown and branches using the crown density - foliage transparency card (Figure 2-1). Dead 

branches,

 crown dieback and missing branches or areas where foliage is expected to be missing are deleted

from

 the estimate.

 Large uniform crowns are rated as if the whole crown should be foliated. When defoliation 

is severe,

 branches alone will screen the light, but the raters should exclude the branches from foliage 

and rate the

 area as if the light was penetrating. For example, an almost completely defoliated dense 

spruce may have

 less than 20 percent light coming through the crown, but it will be rated as highly transparent

because of

the missing foliage. Old trees, and some hardwood species, have crown characteristics with 

densely
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foliated branches which are spaced far apart in the crown. These spaces between branches should

not

be included in the foliage transparency rating. When foliage transparency in one part of the 

crown differs

from another part, the average foliage transparency is estimated and recorded.

 Foliage transparency should be rated by two raters. Raters should step back about 1/2 to 1 

tree length

from the tree base and move sideways at least 10 ft (3 m) to obtain a good view of the crown. 

First, raters

will mentally draw a two-dimensional crown outline. Second, the foliated area will be blocked 

into the crown

outline. Third, estimate the transparency of the foliated area in 5 percent classes and record.

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 EMAP Forest Monitoring, Section 2, Rev. No. 0, October, 1994, Page 22 of 23

 When two raters disagree in their estimates, they should discuss the reasons for their 

rating. Either

a rater will change his or her estimate or the ratings should be averaged and the class of the 

estimate

recorded. Differences may be due to differences in crown conditions, the estimate of the rater, 

or both.

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2.7 References

Anderson, R.L. and R.P. Belanger. 1987. A crown rating methods for assessing tree vigor of 

loblolly

 and shortleaf pines. In, D.R. Phillips, camp., Proceedings of the fourth biennial southern 

silvicultural

 research conference. Nov. 4-6, 1986; Atlanta, GA. USDA Forest Service Gen. Tech. Rep. SE42,

 Asheville, NC. pp. 538-543.

Anderson, R.L., W.G. Burkman, I. Millers, and W.H. Hoffard. 1992. Visual crown rating model for

 upper canopy trees in the eastern United States. USDA Forest Service, Region 8/Northeastern

 Area. 15p.

Belanger, R.P. and R.L. Anderson. 1991. A guide for visually assessing crown densities of 

loblolly and

 shortleaf pines. USDA Forest Service Res. Note SE-352. 10p.

Dolph, K.L. 1988. Predicting height increment of young-growth conifers in the Sierra Nevada. 

USDA

 Forest Service Res. Paper PSW-191. 7p.

Francis, J.K. 1986. The relationship of bole diameters and crown widths of seven bottomland

 hardwood species. USDA Forest Service Res. Note. SO-328. 3p.

Grano, C.X. 1957. Growth of loblolly pine seed trees in relation to crown density. J. For. 

55(11):852.

Kuhlman, H.M. 1971. Effects of insect defoliation on growth and mortality of trees. Annual Rev. 

of

 Entomology 16:289-324.

Sprinz, P.T. and H.E. Burkhart. 1987. Relationships between tree crown, stem, and stand

 characteristics in unthinned loblolly pine plantations. Can. J. For. Res. 17(6):534-538.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 1 of 22

 Section 3. Damage and Catastrophic Mortality Assessment

Section/Title

Page

3.0 Quick Reference 2 of 22

3.1 Overview 3 of 22

 3.1.1 Scope and Application 3 of 22

 3.1.2 Summary of Method 3 of 22

 3.1.3 Interferences 3 of 22

 3.1.4 Safety 3 of 22

3.2 Sample Collection 4 of 22

3.3 Equipment and Supplies 4 of 22

3.4 Calibration and Standardization 4 of 22
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3.5 Quality Assurance 4 of 22

 3.5.1 Measurement Quality Objectives 4 of 22

3.6 Procedures 5 of 22

 3.6.1 Locationl 5 of 22

 3.6.2 Damagel 8 of 22

 3.6.3 Location and Damage Combinations 10 of 22

 3.6.4 Severity! 12 of 22

 3.6.5 Procedures to Record Multiple Occurrences of

 the Same Damage 18 of 22

 3.6.6 Procedures to Measure Circumference Affected 18 of 22

 3.6.7 Location2 18 of 22

 3.6.8 Damage2 18 of 22

 3.6.9 Severity2 18 of 22

 3.6.10 Locations 18 of 22

 3.6.11 Damages 18 of 22

 3.6.12 SeverityS 18 of 22

3.7 References 19 of 22

Appendix 3.1 Catastrophic Mortality Assessment 20 of 22

 Procedure 20 of 22

 Table 3-1 Guide for Estimating Time Since Death 21 of 22

 General Guides for Postdating Mortality 22 of 22

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 EMAP Forest Monitoring, Section 3, Rev. No. 0; October, 1994, Page 2 of 22

3.0 Quick Reference

 Definition

 No damage

 Roots (exposed) and "stump" (12 in [30 cm] in height from ground level)

 Roots and lower bole

 Lower bole (lower half of the trunk between the "stump" and base of the live 

crown)

 Lower and upper bole

 Upper bole (upper half of the trunk between "stump" and base of the live crown)

 Crownstem (main stem within the live crown area, above the base of the live crown)

 Branches (woody stems other than main stem)

 Buds and shoots (the most recent year's growth)

 Foliage

Damage

 Code Description

Severity Threshold

(in 10% classes to 99%)

 01 Canker 20%

 02 Conks, fruiting bodies, and other indicators of advanced decay none*

 03 Open wounds 20%

 04 Resinosis or gummosis 20%

 11 Broken bole or roots less than 3 ft (0.91 m) from bole none

 12 Brooms on roots or bole none

 13 Broken or dead roots( >3 feet from bole) 20%

 21 Loss of apical dominance, dead terminal 1%

 22 Broken or dead branches 20%

 23 Excessive branching or brooms 20%

 24 Damaged foliage buds or shoots 30%

 25 Discoloration of foliage 30%

 31 Other none

 *20% for roots >3 feet from bole or branches.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 3 of 22

3.1 Overview

3.1.1 Scope and Application

 Damage caused by pathogens, insects, air pollution, and other natural and man-made 

activities can

affect the growth and development of trees. Damage caused by any of these agents, either singly

or in

combination, can significantly affect forest health. Identifying the signs and symptoms of 

damage provides

valuable information concerning the forest's condition and indicates possible causes of 

deviation from

expected conditions. For Forest Health Monitoring (FHM), damage signs and symptoms are recorded 

if,

by definition, the damage could kill the tree or affect the long-term survival of the tree.

 This definition of damage was developed to improve data quality and to improve the 
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repeatability of

measurements. Only those damage categories that could kill the tree or have the potential to 

affect the

long-term survival of the tree are recorded. The cause of damage is not recorded due to 

variability among

raters The damage categories are prioritized based on location, eliminating uncertainties due

to the

estimate of observers." Minimum thresholds and severity classes exist for appropriate damage 

categories.

 Obvious signs of catastrophic events such as fire, bark beetles, wilts, beaver, wind, or 

logging may

cause mortality to trees when no previous significant signs of damage were present. 

Identification of these

major agent groups can help explain sudden, unexpected causes of mortality. Due to the 

complicated

interactions of biotic and abiotic agents, this level of evaluation is not generally repeatable. 

However when

the signs are obvious even to the casual observer, this datum, together with the damage 

indicator

information, can provide valuable insight to the causes of deviations from expected conditions.

3.1.2 Summary of Method

 Damage signs and symptoms are recorded on all live saplings 1.0 inch (2.54 cm) to 4.9 

inches (12.5

cm) DBH on the 1/300 acre (1/750 hectare) microplot and all live trees 5.0 inches (12.7 cm) DBH and

larger on the 1/24 acre (1/60 hectare) subplot. Also included in this section is Catastrophic

Mortality

Assessment protocols (Appendix 3.1).

 Due to the difficulty in incorporating proposed changes into the Tally program at this time,

the "cause

of death" codes used in 1994 will be the same as those used in 1993. Some codes will be 

eliminated and

others'combined during post processing for analysis purposes. Insect/disease, fire, animal, 

weather,

logging/human damage, and unknown/other will be the major agent groups used for analysis.

3.1.3 Interferences

 Several uncontrollable environmental and site conditions have hindered or slowed the damage 

and

mortality assessment measurements, including (1) poor weather conditions such as gustmg wind, 

heavy

rain and dark overcast skies; (2) steep and/or unstable slopes; (3) dense understory vegetation

which

prohibits free ground movement; and (4) thick canopy immediately overhead that obscures full 

view of the

tree. Suspend data collection under severe weather conditions, such as strong winds and heavy 

rainfall.

 3.1.4 Safety

 No specialized safety precautions are necessary. Follow general safety precautions for 

conducting

fieldwork. (See Appendix E.)

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 4 of 22

3.2 Sample Collection

 No material samples are collected.

3.3 Equipment and Supplies

 Two trained and certified persons should be able to perform measurements using only a 

diameter tape.

Binoculars are helpful yet optional. All measurements are recorded on portable data recorders 

(PDRs).

 In case of PDR failure, record the appropriate code for up to three damage types for each 

tree in the

appropriate column.

Location

(1) (2) (3)
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Damage

(1) (2) (3)

Severity

(1) (2) (3)

3.4 Calibration and Standardization

 General calibration and standardization protocols should be applied to field equipment. 

Purchase tapes

to required specifications. Tapes should be maintained in working order and do not require 

calibration upon

confirmation of accuracy.

3.5 Quality Assurance

3.5.1 Measurement Quality Objectives

 Table 3-1 lists Damage Measurement Quality Objectives.

Table 3-1. Damage Measurement Quality Objectives

Variable

No damage

Location

Damage

Severity

All

No. of Units

1

10

13

10

258 combinations

Acceptable Range

90% agreement

90% agreement

85% agreement

80% + or - class

80% complete agreement

(+ or - 1 severity class)

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3.6 Procedures

 The tree is observed from all sides starting at the roots. Damage signs and symptoms are 
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prioritized

and recorded based on location in the following order: roots, roots and lower bole, lower bole, 

lower and

upper bole, upper bole, crownstem, branches, buds and shoots, and foliage recorded as location 

code 0-9.

 Within any given location, the hierarchy of damage follows the numeric order of damage types 

possible

for that location. The numeric order denotes decreasing significance as the code number goes 

up, i.e.,

damage 01 is more significant than damage 25. A maximum of three damages are recorded for each 

tree.

If a tree has more than three damages that meet the threshold levels, the first three that are 

observed

starting at the roots are recorded.

 When multiple damages occur in the same place, the most damaging is recorded. For example, 

if a

canker, damage code 02, meets the threshold and has a conk growing in it, record only the 

canker.

Another example is, if an open wound meets threshold and also has resinosis, record only the 

open wound.

 Specific causal agents are not identified through the coding system. One goal of FHM is the 

detection

of change. The identification of specific causal agents is one of the objectives of Evaluation 

Monitoring.

If the field crew can identify specific causal agents, the agents should be included in the 

"notes" section

for individual trees. In the future, codes for specific causal agents may be added.

3.6.1 LOCATION1

 LOCATION1 is the location (LOCATN1) on the tree where DAMAGE1 is found (see Figure 3-1). If 

the

same damage continues into two or more locations, record the appropriate code listed below, or

if the

combination of locations does not exist (damage extends from crownstem to roots), record the 

lowest

location (see Figure 3-2). Multiple damages may occur in the same location, but record the 

higher priority

damage (lower code number) first. If the damages are coincident (a conk within a canker), record 

only the

higher priority damage.

 Definition

 No damage

 1 Roots (exposed) and "stump" (12 inches (.3 m) in height from ground level)

 2 Roots and lower bole

 3 Lower bole (lower half of the trunk between the "stump" and base of the live crown)

 4 Lower and upper bole

 5 Upper bole (upper half of the trunk between "stump" and base of the live crown)

 6 Crownstem (main stem within the live crown area, above the base of the live crown)

 7 Branches (woody stems other than main stem)

 8 Buds and shoots (the most recent year's growth)

 9 Foliage

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 6 of 22

 12" I "STUMP-TOP

 FOLIAGE

 (09)

 BUDS/SHOOTS

 (08)

 BRANCHES

 (07)

 CROWNSTEM

 (06)

 BASE OF UVE

 CROWN

 MIDPOINT OF BOLE

 MIDWAY BETWEEN CROWN

 BASE AND "STUMP"

 ROOTST STUMP"

 (01)

 

0195mad94-2Q

Figure 3-1. Location codes for the damage indicator.
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 Exposed

 Decay Column

Figure 3-2. The damage runs from stump to crownstem. Code here should be 02 (roots and "stump" 

and lower bole)

which represents the lowest locations of this multi-location damage.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 8 of 22

3.6.2 DAMAGE1

 DAMAGE1 is the first damage observed that meets the damage threshold definition in the 

lowest

location. Damage categories are recorded based on the numeric order which denotes 

decreasing

significance from damage 01 - 31.

FHM Damage codes and definitions:

 Code Description

 01 Canker

 Cankers may be caused by various agents but are most often caused by fungi. The bark

and

 cambium are killed, and this is followed by death of the underlying wood, although 

the causal

 agent may or may not penetrate the wood. This results in areas of dead tissue that 

become

 deeper and wider, or galling (including galls caused by rusts) on roots, bole, or 

branches. (For

 procedures on how to measure multiple cankers see Sections 3.6.5 and 3.6.6.) A 

canker may

 be:

 Annual (enlarges only once and does so within an interval briefer than the growth 

cycle of the

 tree, usually less than one year),

 Diffuse (enlarges without characteristic shape or noticeable callus formation at 

margins), or

 Perennial (enlarges during more than one year - often has a target appearance).

 02 Conks, fruiting bodies, and other indicators of advanced decay. Fruiting bodies on 

the main

 bole, crownstem, and at the point of the branch attachment are decay indicators. 

"Punky

 wood" is present when openings larger than the width of a pencil occur in the main 

bole.

 Punky wood is evidenced by soft, often moist, and degraded tissue.

 Open cracks that do not qualify as open wounds because they do not meet that 

threshold

 should be coded here even if they have no obvious signs of punky wood. A fire scar 

at the

 base of a tree is an indicator of decay.

 Cavities into the main bole from old branches are indicators of decay.

 Open wound in contact with the ground is an indicator of decay.

 Rotten branches or branches with conks are not indicators of decay unless the 

threshold is met

 (>20% of branches are affected).

 Rotting stumps associated with coppice regeneration (e.g., northern pin oak, red 

maple) are

 excluded from coding.

 03 Open wounds

 An opening or series of openings where bark has been removed or the inner wood has 

been

 exposed and no signs of advanced decay are present. Pruning wounds that cut into the 

wood

 of the main stem are coded as open wounds, if they meet the threshold; those which 

leave the
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 main stemwood intact are excluded. (For procedures on how to measure open wounds 

see

 Sections 3.6.5 and 3.6.6.)

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 9 of 22

Code Description

04 Resinosis or gummosis

 Areas of resin or gum (sap) exudation on branches and trunks. (For procedures on how to

 measure resinosus or gummosis, see Sections 3.6.5 and 3.6.6.)

11 Broken bole or roots less than 3 feet (.91 m) from bole

 Broken roots within 3 feet (.91 m) of bole either from excavation or rootsprung for any 

reason.

 For example, those which have been excavated in a road cut or by animals.

 Stem broken in the bole area (below the base of the live crown) and tree still alive.

12 Brooms on roots or bole

 Clustering of foliage about a common point on the trunk. Examples include ash yellows

 witches' brooms on white and green ash and eastern and western conifers infected with 

dwarf

 mistletoes.

13 Broken or dead roots (beyond 3 feet (.91 m))

 Roots beyond 3 feet (.91 m) of bole that are broken or dead.

21 Loss of apical dominance, dead terminal

 Mortality of the terminal of the crownstem caused by frost, insect, disease, or other 

causes.

22 Broken or dead

 Branches or shoots that are broken or dead. Dead branches attached to the bole below the

 base of the live crown are not coded.

23 Excessive branching or brooms

 Brooms are a dense clustering of twigs or branches arising from a common point that occur

 within the live crown area. Includes abnormal clustering of vegetative structures and 

organs.

 This includes witches' brooms caused by ash yellows on green and white ash and those

 caused by dwarf mistletoes.

24 Damaged foliage or shoots

 Insect feeding, shredded or mechanically damaged or distorted foliage or shoots affecting 

at

 least 30% of foliage or shoots. Also includes herbicide-damaged shoots.

25 Discoloration of foliage

 At least 30% of the foliage is more than 50% affected. Affected foliage must be more of 

some

 color other than green. If the observer is unsure if the color is green, it is 

considered green

 and not discolored.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 10 of 22

 Code Description

 31 Other

 Use when no other explanation is appropriate. Specify in comments section of PDR for 

"tree

 notes."

3.6.3 LOCATION and DAMAGE Combinations

 The following table depicts the possible combinations of damage by location, "Y" indicates a

valid

combination, and "N" indicates an invalid combination.

Damage

Location

1

2

3

4

5

6

7

8

9

01

Y

Y

Y

Y

Y

Y

Y

N

N
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02

Y

Y

Y

Y

Y

Y

Y

N

N

03

Y

Y

Y

Y

Y

Y

Y

N

N

04

Y

Y

Y

Y

Y

Y

Y

N

N

11

Y

Y

Y

Y

Y

N

N

N

N

12

Y

Y

Y

Y

Y

N

N

N

N

13

Y

N

N

N

N

N

N

N

N

21

N

NN

N

N

Y

N

N

N

22

N

N

N

N

N

N

Y

N

N

23
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N

N

N

N

N

N

Y

N

N

24

N

N

N

N

N

N

N

Y

Y

25

N.

N

N

N

N

N

N

N

Y

31

Y

Y

Y

Y

Y

Y

Y

Y

Y

Determining Damage by Location

 For each of the following location codes, possible damage codes and damage definitions 

are

presented.

Code Location

1 Roots, within 3 feet (.91 m) of bole to 12 inches (.3 m) in height on the bole ("stump") 

- (Code 13,

 if appropriate, for roots beyond 3 feet (.91 m) from bole)

 01 Canker - exceeds 20% of circumference of "stump".

 02 Conk, fruiting body, or other indicators of advanced decay, or if open wound is in

contact

 with the ground - any occurrence.

 03 Open wounds - exceeds 20% of circumference of "stump" and are not in direct 

contact with

 the ground - any occurrence.

 04 Resinosis or gummosis - flow width exceeds 20% of circumference of "stump".

 11 Broken bole or roots less than 3 feet (.91 m) from bole - any occurrence.

 12 Brooms on roots and bole - any occurrence.

 13 Broken or dead - exceeds 20% of roots, beyond 3 feet (.91 m) of bole, broken or 

dead

 31 Other.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 11 of 22

Code Location

2 Roots and lower bole

 01 Canker - exceeds 20% of circumference at the point of occurrence.

 02 Conk, fruiting body, or other indicators of advanced decay, or if open wound is in

contact

 with the ground - any occurrence.

 03 Open wounds - exceeds 20% of circumference at the point of occurrence, and are not

in

 direct contact with the ground.

 04 Resinosis or gummosis - flow width exceeds 20% of circumference at the point 

of

 occurrence.

 11 Broken bole or roots less than 3 feet (.91 m) from bole - any occurrence.

 12 Brooms on roots and bole - any occurrence.
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 31 Other.

3 Lower bole - same as roots and lower bole.

4 Lower and upper bole - same as roots and lower bole.

5 Upper bole - same as roots and lower bole.

6 Crownstem

 01 Canker - exceeds 20% of circumference of crownstem at the point of occurrence.

 02 Conk, fruiting body or other indicators of advanced decay - any occurrence.

 03 Open wounds - exceeds 20% of circumference of crownstem at the point of 

occurrence.

 04 Resinosis or gummosis - flow width exceeds 20% of circumference of crownstem at 

the

 point of occurrence.

 21 Loss of apical dominance, dead terminal - any occurrence.

 31 Other.

7 Branches

 01 Canker - exceeds 20% of circumference on at least 20% of branches.

 02 Conks, fruiting bodies and other indicators of advanced decay - more than 20% of

 branches affected.

 03 Open wounds - exceeds 20% of circumference on at least 20% of branches.

 04 Resinosis or gummosis - flow width exceeds 20% of circumference on at least 20% 

of

 branches.

 22 Broken or dead - more than 20% of branches affected.

 23 Excessive branching or brooms - more than 20% of branches affected.

 31 Other.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 12 of 22

Code Location

8 Buds and shoots

 24 Damaged buds, shoots or foliage - more than 30% of buds and shoots damaged more

 than 50%.

 31 Other.

9 Foliage

 24 Damaged buds, shoots or foliage - more than 30% of foliage damaged more than 50%.

 25 Discoloration of foliage - more than 30% of foliage discolored more than 50%.

 31 Other.

3.6.4 SEVERITY1

 SEVERITY1 is amount of affected area (above threshold) in LOCATION1 recorded for

DAMAGE1. Severity codes vary depending on the type of damage recorded. The codes and

procedures for SEVERITY1 values are:

Code 01 - Canker

 Measure the affected area from the margins (outer edges) of the canker or gall within any

3 foot

(.91 m) vertical section in which at least 20% of circumference is affected at the point of 

occurrence.

See Figure 3-3.

 Severity classes for code 01 (percent of circumference affected):

 Classes Code

 20-29 2

 30-39 3

 40-49 4

 50-59 5

 60-69 6

 70-79 7

 80-89 8

 90-99 9

Code 02 - Conks, fruiting bodies, and other indicators of advanced decay
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 Severity classes for code 02:

 None. Enter code 0 regardless of severity.

Code 03 - Open wounds

 The damaged area is measured at the widest point between the margins of the exposed wood

within any 3 foot (.91 m) vertical section in which at least 20% of the circumference is 

affected at the

point of occurrence. See Figure 3-4.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 13 of 22

Figure 3-3. A canker which exceeds threshold. Since 40% of circumference is visible from any 

side, and since over half

the visible side Is taken up by the canker, it obviously exceeds the 20% minimum circumference 

threshold.

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Figure 3-4. Multiple damage in "stump" and lower bole. Approximately 40% of tree circumference; 

B=portion of tree

circumference affected by damage; C=vertical distance within one meter; D=midpoint of occurrence 

at which

circumference is measured.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 15 of 22

 Severity Classes for code 03 (percent of circumference affected):

Classes

20-29

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

2

3

4

5

6

7

8

9

Code 04 - Resinosis or gummosis

 Resinosis or gummosis is measured at the widest point of flow within any 3 foot (.91 m) 

vertical section

in which at least 20% of the circumference is affected at the point of occurrence.

 Severity classes for code 04 (percent of circumference affected):

Classes

20-29

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

2

3

4

5

6

7

8

9

Code 11 - Broken bole or roots less than 3 feet (.91 m) from bole

 Severity classes for code 11:

 None. Enter code 0 regardless of severity.

Code 12 - Brooms on roots or bole

 Severity classes for code 12:

 None. Enter code 0 regardless of severity.

Code 13 - Broken or dead roots
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Over 20% of roots beyond 3 feet (.91 m) of bole that are broken or dead.

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 Severity classes for code 13 (percent of roots affected):

Classes

20-29

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

2

3

4

5

6

7

8

9

Code 21 - Loss of apical dominance, dead terminal

 This damage has no threshold for recording but is recorded, if it occurs, in 10% classes as 

percent of

crownstem affected. Use trees of the same species and general DBH class in the area or look 

for

crownstem on the ground to aid in estimating percent affected.

 Severity classes for code 21:

Classes

01-09

10-19

20-29

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

0

1

2

3

4

5

6

7

8

9

Code 22 - Broken or dead branches (within the live crown)

Over 20% of branches are broken or dead.

 Severity classes for code 22 (percent of branches or shoots affected):

Classes

20-29

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

2

3

4

5

6

7

8

9

Code 23 - Excessive branching or brooms.
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Over 20% of crownstem or branches affected with excessive branching or brooms.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 17 of 22

 Severity classes for code 23 (percent of area affected):

Classes

20-29

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

2

3

4

5

6

7

8

9

Code 24 - Damaged buds, shoots or foliage

At least 30% of the buds, shoots or foliage (i.e., chewed or distorted) are more than 50% 

affected.

 Severity classes for code 24:

Classes

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

3

4

5

6

7

8

9

Code 25 - Discoloration of Foliage

At least 30% of the foliage is more than 50% affected.

 Severity classes for code 25 (percent affected):

Classes

30-39

40-49

50-59

60-69

70-79

80-89

90-99

Code

3

4

5

6

7

8

9

Code 31 - Other

 Severity classes for code 31:

 None. Enter code 0 regardless of severity. Describe condition in notes.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 18 of 22

 3.5.5 Procedures to Record Multiple Occurrences of the Same Damage

 Damage codes 01 (canker), 03 (open wounds), and 04 (resinosis/gummosis) must meet a 

threshold

 of 20 percent of the circumference at the point of occurrence, within any 3 foot (.91 m) 

section. Multiple

 cankers or open wounds which are directly above one another pose no more threat to long term 

tree
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 survival than would a single damage incidence of the same width. However, should multiple 

damages be

 located horizontally within any 3 foot (.91 m) section, the translocation of water and 

nutrients would be

 significantly affected. The widths of each individual damage are added and compared as a 

percent, to the

 total circumference at the midpoint of the 3 foot (.91 m) section (Figure 3-2).

 3.6.6 Procedures to Measure Circumference Affected

 A practical approach is to observe every face of the "stump", bole, or crownstem. About 40% 

of the

 circumference of a face can be observed at any one time. The damage is measured horizontally 

between

 the margins (see Figure 3-4). If the cumulative area affected within a 3 foot (.91 m) section 

exceeds 1/2

 of any face, then the 20% minimum threshold has been met. The percent of the circumference 

affected

 by damage is then estimated in 10% classes. If in doubt, measure the damage and circumference

with

 a linear tape.

 3.6.7 LOCATION2

 LOCATION2 is the location (LOCATN2) on the tree where the DAMAGE2 is found. See LOCATION1

 for codes. If damage continues into two or more locations for which a code does not exist, use

lowest

 location (see Subsection 3.6.1).

 3.6.8 DAMAGE2

 DAMAGE2 is the second damage observed that meets the damage threshold definition in the 

lowest

 location. Damage categories are recorded for a given location based on numeric order from 01- 

31 (see

 Subsection 3.6.2).

 3.6.9 SEVERITY2

 SEVERITY2 is the severity class for DAMAGE2. See SEVERITY1 (Subsection 3.6.4) for codes.

 3.6.10 LOCATIONS

 This is the location (LOCATN3) on the tree where the DAMAGES is found. See LOCATION1 for 

codes.

 If damage continues into two or more locations for which a code does not exist, use lowest 

location (see

Subsection 3.6.1).

3.6.11 DAMAGES

 DAMAGES is the third damage observed that meets the damage threshold definition in the 

lowest

location. Damage categories are recorded for a given location based on numeric order from 01 -

31 (see

Subsection 3.6.2).

3.6.12 SEVERITY3

 SEVERITY3 is the severity class for DAMAGES. See SEVERITY! (Subsection 3.6.4) for codes.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 19 of 22

3.7 References

Johnson, W.T., H.H. Lyon. 1988. Insects That Feed on Trees and Shrubs. Comstock Publishing

 Associates, Cornell University Press, Ithaca, NY.

Sinclair, W.A., H.H. Lyon, W.T. Johnson. 1987. Diseases of Trees and Shrubs. Comstock 

Publishing

 Associates, Cornell University Press, Ithaca, NY.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 20 of 22

 Appendix 3.1 Catastrophic Mortality Assessment

 Obvious signs of catastrophic events such as fire, bark beetles, wilts, beaver, wind, or 
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logging may

cause mortality to trees when no previous significant signs of damage were present. 

Identification of these

major agent groups can help explain sudden, unexpected causes of mortality. Due to the 

complicated

interactions of biotic and abiotic agents, this level of evaluation is not generally repeatable. 

However, when

the signs are obvious even to the casual observer, this datum, together with the damage 

indicator

information, can provide valuable insight to the causes of deviations from expected conditions.

 Due to the difficulty in incorporating proposed changes into the Tally program at this time,

the "cause

of death" codes used in 1994 will be the same as those used in 1993. Some codes will be 

eliminated and

others combined during post processing for analysis purposes. Insect/disease, fire, animal, 

weather,

logging/human damage, and unknown/other will be the major agent groups used for analysis.

 Cause of death is recorded for all saplings 1.0 inch (2.54 cm) DBH and larger on the 

microplot, and

all trees 5.0 inches (12.7 cm) DBH and larger on the subplot that were recorded as live trees 

during the

previous inventory.

Procedure

Record the appropriate 3-digit code for each cut or dead tree tallied. From the list below, 

specify the final

causal agent group that most likely resulted in tree death. Code 001 is assigned at processing

for all trees

that are dead when initially encountered (e.g., Mt1 snags).

CAUSE OF DEATH

 Code Definition

 001 Tree dead when first encountered

 100 Insect

 200 Disease

 201 Fire

 300 Blister Rust (CA)

 400 Animal

 500 Weather

 600 Suppression/Competition

 700 Logging and related human damage

 800 Unknown

 999 Other than described above; needs explanation in notes

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 21 of 22

Tabl» 3-1. Guide for Estimating Time Since Death (CA/PNW PS Only)

 Died within past 5 years

Species

Died more than 5 years ago

 Often some foliage left; 30+% twigs left; few branches falling; some Sugar Pine

 bark loosening; green to deteriorated sapwood; Blue stain fungi or

 Polyporus volvatus present or drying up.

 Often some foliage left; 60+% twigs left; very few branches falling; Western

 bark intact; sapwood green to gray, sound; Little or no fungi. Redcedar

 Often some foliage left; 30+% twigs left; small branches falling;

 some bark loosening; green to deteriorated sapwood; Blue stain

 fungi or Polyporus volvatus present or drying up.

Ponderosa Pine

 Sometimes some foliage left; 10+% twigs left; small branches Douglas-Fir

 falling; some top breakage; bark sloughing on small trees; sapwood

 green to deteriorating; Polyporus volvatus and/or Fome pinocola

 present, the latter on small trees.

 Sometimes some foliage left; 5+% twigs left; limbs intact to starting True Firs

 to fall; bark intact to beginning to slough; sapwood green to having

 considerable rot; Polvporus volvatus and/or Fomes pinocola

 appearing.

 Sometimes some foliage left; 20+% twigs left; some small tree Western hemlock

 branches falling; bark intact to loosening on smaller trees; sapwood

 stained to deteriorating Fungi may include Polyporus volvatus

 and/or Fomes pinicola.
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 Some foliage teft, 75+% twigs & 30+% branches left; bark intact. White pine

 Some foliage left; 30+% twigs & 50+% branches left; little bark

 sloughing.

 Some foliage left; 75+% twigs & branches left.

 Some foliage left

 HARDWOODS

 50+% bark attached in some degree.

 50% or more of bark still attached to the bole in some degree.

 50% or more of bark still attached to the bole in some degree.

Spruce

Lodgepole pine

Pinyon

Aspen

Cotton wood

Other Hardwoods

(i.e., Oaks)

No foliage; <30% of the twigs left;

many limbs falling; bark loose &

sloughing; sapwood deterioration

almost complete; miscellaneous

species of fungi.

No foliage; <60% of the twigs left;

some limbs falling; large pieces of

bark striping off; sapwood sound;

fungi few.

No foliage; <30% of the twigs left;

many limbs falling; bark loose &

sloughing; sapwood deterioration

severe; miscellaneous species of

fungi.

No foliage; <10% of the twigs left;

limbs falling; about 50% with tops

broken; bark sloughing;

considerable sap rot; Fomes

pinicola and other corks common.

No foliage; <5% of the twigs left;

many limbs falling; bark loose and

sloughing; sapwood deterioration

complete; miscellaneous species

of fungi present.

No foliage; <20% of the twigs left;

many limbs falling; bark loose and

sloughing; sapwood deterioration

almost complete; Fomes pinicola

common.

No foliage; 75% of less twigs left;

many big limbs gone; much bark

sloughing (except small trees).

No foliage; 30% or less twigs &

50% or less branches left; bark

sloughing. Big limbs gone.

No foliage; 75% or less twigs &

branches left; bark sloughing.
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No foliage left.

No foliage; bark 50% or less

attached.

No foliage; bark completely free of

bole or less than 50% attached in

any degree.

No foliage; bark completely free of

bole or less than 30% attached in

any degree.

In all cases, the presence of sporophora or sapwood rotting fungi such as Polyporus rolvalis, 

Fomes pinicola, etc., will be accepted

as evidence that the tree has been dead more than 5 years.

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 EMAP Forest Monitoring, Section 3, Rev. No. 0, October, 1994, Page 22 of 22

 GENERAL GUIDES FOR POSTDATING MORTALITY

1. Large trees generally deteriorate more slowly than small trees.

2. Douglas-fir usually deteriorates more slowly than hemlock or true firs. Cedars deteriorate 

the slowest

 of all trees.

3. Deterioration often depends on the local environment.

4. Blue stain usually appears in the sapwood during the first year.

5. Fomes pinicola (red belt fungus) usually produces conks the third year after death. It is 

yellowish in

 color for the first 3 years, appearing in bark crevasses. As it grows older, it develops 

reddish margins

 and grows to a large bracket shape. It is a perennial conk. Each year it lays down a new 

belt of

 growth which can be counted to age mortality.

6. Sapwood usually completely deteriorates in 5 years in Douglas-fir; sooner in hemlock and 

true firs.

7. Heartwood deteriorates 2 cm to 15 cm in 8-10 years.

8. Foliage is usually absent after 3 years in conifers, sooner in deciduous.

9. Most twigs and small branches are absent after 5 years.

10. Large limbs usually begin falling in 8-10 years.

11. Tops start breaking up in most standing trees in 8-10 years, sooner in Douglas-fir.

12. Trees with > 50% of the bark detached have been dead over 5 years.

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 EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 1 of 18

 Section 4. Photosynthetically Active Radiation (PAR) Indicator

Section/Title Page

4.1 Overview 2 of 18

 4.1.1 Scope and Application '. . . . 2 of 18

 4.1.2 Summary of Method 2 of 18

 4.1.3 Interferences 2 of 18

 4.1.4 Safety 3 of 18

4.2 Sample Collection, Preservation, and Storage 4 of 18

4.3 Equipment and Supplies 4 of 18

 4.3.1 Equipment and Apparatus 4 of 18

 4.3.2 Consumable Supplies 4 of 18

4.4 Calibration and Standardization 4 of 18

 4.4.1 Ceptometer 4 of 18

 4.4.2 Quantum Sensors 5 of 18

 4.4.3 Reprogramming the LICOR 1000 Datalogger 5 of 18

4.5 Quality Control 7 of 18

 4.5.1 Data Quality 8 of 18

 4.5.2 Method Performance 8 of 18

4.6 Procedures 8 of 18

 4.6.1 Sample Collection 8 of 18

 4.6.1.1 Timing of Measurements 9 of 18
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 4.6.1.2 Weather Considerations 9 of 18

 4.6.2 Ceptometer - Basic Operation 9 of 18

 4.6.3 Daily Operations 10 of 18

 4.6.3.1 Ambient Measurements 10 of 18

 4.6.3.2 Daily Programming of the Ambient Station Datalogger 13 of 18

 4.6.3.3 PAR Grid Establishment 14 of 18

 4.6.3.4 Under-Canopy Measurements 15 of 18

 4.6.3.5 Deactivate Ambient Station 16 of 18

 4.6.3.6 Downloading Data 16 of 18

 4.6.4 Preventative Maintenance 17 of 18

4.7 References 18 of 18

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 EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 2 of 18

4.1 Overview

4.1.1 Scope and Application

 Measurements of solar radiation intercepted by the canopy are fundamental for interpreting 

the

productivity and function of plant communities (Norman and Campbell, 1989). Photosynthetically 

active

radiation (PAR) is the quantity of light between the 400-700 nm wavelengths of the spectrum and 

is that

part of the spectrum that plants use for photosynthesis. The amount of PAR that is transmitted 

through

a plant canopy can be expressed as the ratio of PAR under the canopy to the total ambient 

(incoming) PAR

at the site. This ratio can be used to estimate Leaf Area Index (LAI), an indicator of canopy 

condition, and

upon remeasurement, can be combined with growth measurements to estimate growth efficiency, an

important indicator of forest health (Waring and Schlesinger, 1985). PAR can also be combined 

with

companion indicators of site condition, growth, regeneration, vegetation structure, crown 

assessment,

and/or remote sensing to assess canopy condition with a multivariate indicator approach.

 In the past, reliable ground-level measurements of transmitted solar radiation were 

difficult to achieve

and were typically characterized by significant temporal and spatial variability. Ambient PAR 

measurements

vary depending upon cloud conditions, time of day, and solar angle (i.e., location and time of 

season). This

method uses a portable integrating radiometer called a Ceptometer (Decagon Devices, Inc., 

Pullman, WA)

for estimating PAR in combination with quantum sensors (LI-COR, Lincoln, NE) to estimate 

transmitted

PAR in various forest types and stand conditions.

4.1.2 Summary of Method

 PAR is measured with specialized quantum sensors that are responsive to solar radiation in 

the

400-700 nm waveband. Ambient PAR is measured with two independent quantum sensors placed in a

nearby open area and connected to a datalogger. One quantum sensor is shaded, and one is left in

full

sun. The shaded quantum sensor measures diffuse PAR, which allows determination of beam 

fraction:

an indicator of cloudiness. Under-canopy PAR is measured with the ceptometer, which has a wand with

a linear array of 80 quantum sensors coupled to an internal integrating datalogger. Under-canopy

and

ambient PAR are measured in synchrony to estimate transmitted PAR and canopy leaf area index.

 PAR measurements are obtained during a standard sampling window from 1200 hrs to 1400 hrs

daylight time (standard zone time, i.e., 1100 and 1300). This window is necessary to minimize 

the effects

of solar angle upon transmitted PAR. The measurement window is most important late in the field 

season.

 PAR measurements are made on a grid of 28 sample points, 7 at each of the 4 subplots 

(Figure 4-1).

This allows remeasurement of sample points for quality control (QC). Furthermore, this system 

allows us

to estimate the spatial and temporal variability of PAR and to scale up from the subplot level 

to the plot

level. Studies have shown that measurement of 7 points per subplot is sufficient to accurately 
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characterize

the subplot while minimizing sampling time.

4.1.3 Interferences

 • Rain - on the sensors may affect the readings. On rainy days, PAR sampling must be done 

either

 before rain begins or after the rain has ceased. There will be plots on which PAR cannot

be

 sampled because of rain.

 • Heavy wind - could topple the ambient station. (There are no documented cases of 

this

 happening. In winds that strong, get out of the woods for safety's sake.)

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 EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 3 of 18

 Dense underbrush requires the sampler to employ a "stab" technique when using the 

ceptometer,

 which takes more time than when in the open.

 Steep slopes require more care to be taken in keeping the ceptometer level during 

sampling.

 Long distance to open areas may require a hike to set up the ambient sensors. However, 

new

 shade disk positioning methods have eliminated the need to recheck the shade disk 

immediately

 prior to ceptometer sampling.

 270

 Sample Subplot

 PAR Sample Locations

 Subpbd: 1-7

 Subpb<2: 8-14

 SubpbtS: 15-21

 SubpbU: 22-28

Figure 4-1. PAR sampling scheme. Subplot example on left shows sampling point layout according 

to azimuth.

Diagram on right shows 7-point grid for each subplot of the 4 fixed-area subplot cluster. A 

total of 28 points will be

sampled per location.

4.1.4 Safety

 Vehicle safety is important.

 Ceptometers and plastic flags have sharp, pointed ends.

 Poor footing could lead to falls.

 Heat exhaustion can occur during summer days, therefore, plenty of water should be 

available, and

 sun protection should be used.

 Insect bites and poison ivy/oak are potential hazards.

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 EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 4 of 18

 4.2 Sample Collection, Preservation, and Storage

 PAR measurements are taken in the field with a portable ceptometer, under the canopy, and 

with

 quantum sensors in the open (ambient). The under-canopy measurements are stored in memory by 

the

 ceptometer and the measurements taken in the open areas are stored in a datalogger attached to 

two (2)

 quantum sensors; one shaded, and one unshaded. The measurements are downloaded to a

 microcomputer (PC) at the end of the day and then sent to a mainframe computer for backup and 

analysis.

 Collection of the data follows procedures outlined in Section 4.6.

 No material samples are collected or stored.

 4.3 Equipment and Supplies

 4.3.1 Equipment and Apparatus

 • 1 ceptometer, Decagon Devices, Inc. Model SF-80 with case

 • 2 quantum sensors, LI-COR LI-190, calibrated to a standard

 • 1 datalogger, LI-COR 1000

 • 1 platform for mounting quantum sensors with attached and adjustable black disk for shade

 • 1 tripod
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 • 1 hand compass (shared with crew)

 • 1 measuring tape - with trailer (shared)

 • 1 timepiece (wristwatch)

 • 1 portable microcomputer (PC) at office or motel

 • 1 datalogger shelter (constructed from 2 empty bleach bottles)

 • 1 backpack

 • 1 protractor

 • 1 six-inch rule

 • 1 screwdriver

 • Rite in the Rain field notebook

 • Laminated HELP sheets

 • Cables for downloading ceptometer and datalogger to PC

 4.3.2 Consumable Supplies

 • 10 "AA" batteries for ceptometer (5, plus 5 spares)

 • 12 "D" batteries for datalogger (6, plus 6 spares)

 • 2 soft, clean cloths

 • 1 bottle 50% ethyl alcohol

 • 50 plastic flags (25 one color; 25 another)

4.4 Calibration and Standardization

4.4.1 Ceptometer

 A ceptometer has a wand comprised of an array of 80 quantum sensors. The end sensor is 

calibrated

by the manufacturer. The other 79 sensors need to be calibrated to match the end sensor whenever

the

batteries are changed. Calibration is done at the beginning of the field season by the PAR 

coordinator and

by the PAR crew member, if the batteries are changed during the season. Recalibration should be

done

on a clear day. To calibrate the ceptometer:

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 EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 5 of 18

 1. Set the ceptometer to Function 7.

 2. Then hold down buttons A and B and press the Function key. When the letters "PLL" 

appear on

 left hand side of display, the probe is calibrated (Decagon Devices, Inc., 1989).

 The PAR coordinator will perform additional calibration at the beginning of the field season

by collecting

simultaneous readings under uniform conditions from each ceptometer and the specific pair of 

quantum

sensors to be used with that ceptometer. Regressing the readings will provide a ceptometerspecific

multiplier which is applied to the data during analysis.

4.4.2 Quantum Sensors

 The quantum sensors for measuring ambient PAR are factory calibrated. The specific 

calibration

multiplier to be used with each sensor is printed on a card attached to the quantum sensor 

cable. These

multipliers are programmed into the datalogger; it is extremely important that quantum sensors A

and B

not be confused. Always use sensor A as the full ambient sensor on datalogger channel 1. Always 

use

sensor B as the black disk (shaded) sensor on channel 2. If the sensors are mixed up, the 

calibration

constants will not be correct.

 Synchronize the wristwatch, ceptometer, and datalogger each day.

4.4.3 Reprogramming the LICOR 1000 Datalogger

 The six "D" cells in the LI-COR should last the entire field season. If they do not, then 

you will need

to reprogram the LI-COR. Reprogramming the LI-COR informs the datalogger how and when to record

measurements.

 An internal lithium cell will retain datalogger memory, including channel configurations and 

stored data,

for a short time while the batteries are removed. Changing batteries promptly when the "LO" low

battery

warning appears may avoid the need to reprogram the LI-COR. If reprogramming becomes necessary,
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here is how to do it:

 1. Press "FCT ON" to turn on the LI-COR. The display will first read "LI1000.02.02" (the 

name of the

 resident software) and then will display some numbers and letters such as "11 O.OUM". 

The

 specific display may vary.

 2. Press "CFG" to enter the configuration mode. LI-COR will prompt, "mode is ". 

Choices are

 INSTantaneous or LOG; use LOG. Using the up or down arrow, scroll through the menu 

until

 display reads "mode is LOG", then press "ENTER."

 3. LI-COR will prompt, "ch1 is ". Choices are OFF, LIGHT, GENeral, or THERMocouple; 

use

 LIGHT. Using the up or down arrow, scroll through the menu until display reads "ch1 is 

LIGHT",

 then press "ENTER."

 4. LI-COR will prompt, "range= ". Choices are A, 1, 2, 3, or 4; use A for automatic. 

Using the up

 or down arrow, scroll through the menu until display reads "range= A", then press 

"ENTER."

 5. LI-COR will prompt, "mult= ". The datalogger requires the calibration multiplier 

for channel

 1. The calibration multiplier is determined at the factory and printed on a card 

attached to each

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 EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 6 of 18

 quantum sensor. Since currently programming channel 1, which is always used with Sensor

A

 (the full ambient sensor), enter the calibration multiplier found on the card attached 

to Sensor A,

 use the number keys (left arrow will undo mistakes), and press "ENTER" when ready.

 6. LI-COR will prompt, "label= ". Enter UM (jamoles/nf/second). Accessing letters on 

the Ll-

 COR's keypad is a two-key operation. The letters in the upper left comer of each 

key are

 accessed by first pressing the up arrow, then the key. Letters in the lower left comer 

of each key

 are accessed by pressing the down arrow, then the key. Pressing T, 3, t, 2 should 

display UM.

 Press "ENTER" when ready.

 7. LI-COR will prompt, "per= ". This is the logging period, in minutes, over which 

readings will be

 taken and averaged. Using the up or down arrow, scroll through the menu until the 

display reads

 "per= 1", then press "ENTER."

 8. LI-COR will prompt, "reset= HHMM". This is the time each day when logging is to 

begin.

 Use numbered keys to enter 1100, and press "ENTER."

 9. LI-COR will prompt, "thr= ". The datalogger requires a threshold level below which

data will not

 be stored in memory. To collect and log all data enter "00.00" using the numbered keys, 

and press

 "ENTER."

 10. LI-COR will prompt, "store= ". The LI-COR reads the sensors every 5 seconds. To 

average

 these readings and log the mean each minute, use the up or down arrow to scroll through 

the

 menu until the display reads "store= MEAN", then press "ENTER."

 11. LI-COR will prompt, "min/max= ". To log the minimum and maximum readings for each 

sensor,

 scroll through the menu until the display reads "min/max= YES", and press "ENTER."

 12. LI-COR will prompt, "time stamp= ". Use the up or down arrow to scroll through 

the menu until

 the display reads "time stamp= NO", then press "ENTER."
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 13. Channel 1 is now programmed. The LI-COR will now prompt, "ch2 is ". Return to 

step 3

 above and repeat the procedure for channel 2. All entries will be the same as for 

channel 1 except

 the multiplier. Since channel 2 is always used with Sensor B (shaded ambient, or black 

disk

 sensor), use the calibration multiplier for that sensor when programming channel 2.

 14. Upon completion of configuration of channel 2, the LI-COR will go on to channel 3, then

4, up

 through 8, followed by channels A, B, and M. Turn all of these channels OFF at step 3.

 15. After turning OFF channel M, the datalogger will automatically exit the configuration 

mode. The

 display will read "1M O.OUM" or something similar. The precise display depends on 

whether or not

 there are data points in memory.

 It will be necessary to define date and hex number prompts. Press the "FCT ON" key to bring 

up a list

of auxiliary functions.

 16. Using the up or down arrow, scroll through the menu until the display reads, "FCT:Def 

Prompts",

 then press "ENTER."

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 EMAP Forest Monitoring, Section 4, Rev. No. 0, October, 1994, Page 7 of 18

 17. LI-COR will display "PROMPT1: ". Using the up and down arrows in conjunction with the

 ' numbered keys as before, "1, 4, T, 7, i, 6, T, 1," to display DATE. Press "ENTER" when 

ready.

 18. LI-COR will display "PROMPT2: ". Press "-1, 0, t, 1, I, --," to display HEX. Press 

"ENTER"

 when ready.

 19. LI-COR will display "PROMPTS: ". Third prompt is not used, therefore press "ENTER."

 20. The display now reads "FCT:Def Prompts". Press the "FCT ON" key to exit the list of 

auxiliary

 functions, returning to the "1M O.OUM" display. The second field in this display, "M", 

indicates the

 LI-COR is in LOG mode.

 The basic programming for the LI-COR LI-1000 datalogger is now complete. Daily programming 

and

logging may proceed; otherwise, save memory space and batteries by placing the datalogger in

INSTantaneous mode and turning it off (the LI-COR never sleeps when in LOG mode).

 21. Press the "CFG" key to enter configuration mode. LI-COR will display "mode is LOG".

 22. Press either the up or down arrow so the display reads "mode is INST", and press 

"ENTER."

 23. Display should read "ch1 is LIGHT". Press the "CFG" key to exit configuration mode.

 24. Display should read "11 O.OUM". The second field in this display, "I", indicates that the

datalogger

 is in INSTantaneous mode. Press the "OFF" key to shut the machine down.

 In summary form, here are the settings to select from the configuration menus:

 mode =

 ch1 =

 range =

 mutt =

 label =

 per =

 reset =

 thr =

 store =

 min/max =

 time stamp =

LOG

LIGHT

A

SPECIFIC NO. FOR EACH QUANTUM SENSOR
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UM

1

1100

00.00

MEAN

YES

NO

4.5 Quality Control

 The regional PAR trainer/auditor will visit the field crew and conduct a field audit of at 

least one (1) plot

per crew early in the season. The auditor will take independent measurements on all four 

subplots of each

site immediately after the field crew to check the crew methodology and the data quality. The 

PAR auditor

will then review PAR data downloading procedures and data files for the day and storage of PAR 

data files

to date. This duplicate procedure provides an estimate of the reproducibility of PAR 

measurements. The

data collected by the PAR auditor will be kept separate from the field data. The PAR auditor 

will also work

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 with the field crew on any logistical problems, such as ensuring the ambient station readings 

are taken for

 the full measurement period.

 4.5.1 Data Quality

 Sources of error include incorrect calibration, incorrect instrument operation, incorrect 

location of

 sample stations, failure to position shade disk properly, and asynchrony of time among 

instruments. These

 errors can be minimized by training and adhering to standard procedures.

 Data completeness is the most important data quality concern. The most common reason for

 incomplete data is failure to store the average ceptometer readings. The operator must give 

careful

 attention to the sequence of ceptometer buttons to push, and ensure that the desired 

operation has

 occurred as each button is pushed. In cases where PAR points are visited out of order, it is 

essential to

 include a note in the comment section.

 The following table serves as a reference in the field to help ensure that the ceptometer 

data are

 complete.

 Ceptometer reading expected

 Sample locations after storing a value.

 Subplot 1 (7 sample points) 1, 2 7

 Subplot 2 (7 sample points) 8, 9, .... 14

 Subplot 3 (7 sample points) 15, 16, ..., 21

 Subplot 4 (7 sample points) 22, 23 28

 4.5.2 Method Performance

 Method performance is excellent except on rainy days. Crews should be aware that they may 

add an

 hour to sampling window, if necessary, on rainy days. Performance depends upon the crew's 

thoroughness

 and adherence to the methods. There are very few equipment concerns and data completeness is 

usually

 above 85%.

 4.6 Procedures

 4.6.1 Sample Collection

 PAR measurements are taken simultaneously at the plot and at the "ambient station." The 

ambient

 station is set up in the morning and allowed to run all day. Ceptometer measurements are made 

during

the sampling window (12:00 to 2:00 daylight time). It usually takes about 45 minutes to 

collect the
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ceptometer measurements for an entire plot. Since all measurements are time stamped, ambient 

station

data and ceptometer data can be matched up later for analysis.

 A single ambient station with two quantum sensors is needed. Locate the station in an open 

area that

is free from shade and as near to the FHM plot as possible. Preferably, the area is located in

a large

clearing, but a roadway is allowed if it is sufficiently wide enough that shadows do not fall on

the quantum

sensors. In some situations, you may need to use large gaps in the forest canopy itself. If the

unshaded

area at the ambient station is less than 10 m x 10 m (30 ft x 30 ft), make a note in the 

comment section

on the portable computer after downloading the ceptometer data. Quantum sensor "B" will be 

shaded to

collect diffuse (indirect) PAR, while unshaded sensor "A" collects all incoming PAR to the site.

The ambient

station should be run continuously for the entire work day.

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 Under-canopy sampling points are the subplot locations where PAR is measured with the 

ceptometer.

A grid of seven PAR points will be sampled at each of the four subplots (Figure 4-1). The 

subplot grid will

be flagged with temporary flags during plot establishment by either the foresters or the PAR 

person. The

subplot grid helps all crew members by delineating the subplot boundaries. Use of temporary 

flags also

ensures that QA samples are taken at the same locations within the stand; QA measurements will 

be taken

immediately after initial sampling on audit days.

4.6.1.1 Timing of Measurements

 Because measured PAR depends on sun angle, it is critical that the ceptometer procedures 

be

performed between 12:00 and 2:00 (daylight time). Usually this will require less than one 

hour. If the

starting time is delayed, PAR should be taken anyway as long as samples can be collected before 

3:00

p.m. (daylight time). Note this discrepancy in the comments file when downloading. All 

measurements

should be taken on the same day.

4.6.1.2 Weather Considerations

 1. Do not take measurements in steady rain.

 2. If rain causes sampling to be delayed, go ahead and collect PAR measurements until 3:00. Skip

 the PAR procedures entirely if no measurements can be taken until after 3:00 p.m. because

of rain.

 Take measurements early if necessary to beat an approaching storm, but never sample 

earlier than

 11:00 a.m. (daylight time). In other words, you may stretch the sampling window by an 

hour in

 either direction if necessary, yet be sure to record this in the comments section when 

downloading.

 3. If rain starts after sampling has begun, keep the ceptometer dry until rain stops. Dry 

off the

 ambient station quantum sensors, then resume sampling.

 4. On rain-interrupted days, cease sampling by 3:00 p.m. at the latest, even if all samples

have not

 been collected.

 5. Always download any data that have been collected, even on rainy days when only a 

partial

 sample can be obtained. Clear the memory (see step 2 of 4.6.3.4) to clear ceptometer for 

the next

 day's sample.

 6. Measurements can be taken regardless of cloud conditions.

4.6.2 Ceptometer - Basic Operation
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 The following procedures are performed as part of ceptometer operation:

 1. Clean the white surface of the probe with alcohol (see Section 4.6.4).

 2. Set time of day: Select Function 6 on the ceptometer. Button A sets the hour and button 

B sets

 the minute. Synchronize with ambient datalogger time clock and field crew timepiece 

(wristwatch).

 3. Activate the ceptometer by pressing the function key; it deactivates automatically 

(without memory

 loss) after a 7-minute time-out period. Select function 1, PAR.

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 4. Hold the Ceptometer level to the ground during operation (use bubble level on display 

panel) with

 arms outstretched, at waist height. Avoid shading the probe with the body.

 Different measurements may be made with the ceptometer. By pressing the function key, one of

eight

functions can be selected. The selected function is indicated by a small arrow pointing to the 

function

number above the display. Use function 1 for PAR sampling.

4.6.3 Daily Operations

4.6.3.1 Ambient Measurements

 When the crew reaches the plot location, use the following procedure to position the black 

disk so that

sensor B will be shaded during the 12:00 to 2:00 sampling window. The black disk provides 2 

hours and

20 minutes of shade for sensor B.

 1. Locate the ambient station in an open area as near as possible to the plot (preferably

within

 400 m). The sensors have a 45° range of view so the ambient station should be at least 

one tree

 height away from surrounding trees, if possible.

 2. Set up the tripod. Use rubber tips or spikes as needed, lift center column to 1 meter 

height. If on

 steep ground, shorten the uphill leg so center column is approximately vertical.

 3. Attach platform to the tripod, and place quantum sensors A and B on the platform. 

Sensor A

 measures full sun, and sensor B measures shaded light. Each sensor has a specific 

calibration

 multiplier. Do not interchange sensors.

 4. Determine the sun zenith angle at solar noon, p, which is the angle of the sun from 

vertical:

 P= L - D

 L is the latitude of the plot, and

 D is the solar declination.

 L, the latitude of the plot, is contained within the hex number. The first two digits of

the hex

 number represent the latitude of the plot in degrees.

 D, the solar declination, varies with the day of year and is listed in Figure 4-2.

 Example: Plot number 4709464 on July 1st.

 L = 47 (the first two digits of the hex number)

 D = 23 (from the Solar Declination table)

 P = 47 - 23 = 24 degrees.

 5. Use protractor and 6-inch ruler to set the black disk at p degrees from vertical. A 

5° error is

 acceptable. The disk should be 15 cm (6 inches) above the sensor. See Figure 4-3.

 6. Level the platform using tripod controls. Place compass adjacent to platform and rotate

platform

 until the full ambient end points clue south (true south - add or subtract magnetic 

declination as

 needed). Use caution; each degree of rotation moves the shade window by about 3 

minutes.
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 May

 Jura

 July

 August

 Ssptorriber

 May

 June

 July

 Auguit

 Stpfeirtor

 16

 Day of Month

 6789

 10 11

 12

 13 14

 17 18 19 20

 Day of Month

 21 22 23

 24 25 26 27 28

 15

15

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23

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-1

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10

-2

21

23

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10

-2

22

23

19

9

-2

22

19

9

Figure 4-2 Solar declination (D) In degrees.

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 True

 South

Figure 4-3 Ambient station setup. Sensor A measures full sun. Sensor B is shaded by the black 

disk. By adjusting

angle p according to plot latitude and day of year, and aligning platform to true south (plus or

minus a small longitude

correction), sensor B will be shaded during the sampling window.

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 7. Correct for current position within time zone. Time zones are centered on 15-degree 

meridians

 (eastern = 75, central = 90, mountain = 105, pacific = 120). The sun will be directly 

over the

 central meridian at noon (1:00 daylight time); current position may be a few degrees 

east or west,

 therefore, a correction must be made so that the shadow cast by the black disk will 

correspond with

 local time.

 The longitude of the plot is contained within the hex number: digits 3 through 5 represent 

the longitude

of the plot. Find the difference in degrees between plot longitude and central meridian. 

Multiply this

difference by 1.5. Rotate the platform by this amount so that the south end moves toward central

meridian.

Example: Hex number 4709464.

 Longitude: 094 (digits 3 - 5 of hex number)

 Central meridian: 90 (Central time zone)

 Difference: 94 - 90 = 4 degrees

 Correction required: 4 x 1.5 = 6 degrees

 Since the central meridian is east of the plot (longitudes increase from east to west), 

rotate the south

end of the sensor mounting platform 6 degrees to the east. This will position the shade disk 

so that the

shadow will run on local time.

 8. Stand behind the setup and recheck the azimuth from a distance to make sure the compass

was

 not affected by metal. Tighten tripod controls. Make sure each sensor is level.

 9. Perform daily programming of the datalogger (Section 4.6.3.2). When complete, place 

datalogger

 inside its shelter.

 The ambient station may now be left unattended for the rest of the day.

 In most cases, the longitude correction will be provided ahead of time by the regional PAR 

coordinator.

Provided will be the "target azimuth" for each plot which incorporates both magnetic 

declination and the

time zone correction.

4.6.3.2 Daily Programming of the Ambient Station Datalogger

 Each day you need to synchronize the datalogger with your wristwatch, enter the date and hex

number

and put the datalogger in LOG mode. (You will have taken it out of LOG mode the previous 

afternoon in

order to power down.) Here are the steps to follow to prepare the LI-COR for the day's logging.

 1. Press "FCT ON" to turn on the LI-COR. The display will first read "LI1000.02.02" and 

then will

 display numbers like "11 O.OUM." The specific display depends on data stored in memory.

 2. Press the "TIME" key. The date will be displayed, followed by "YYMMDD". If the date is 

correct,

 press "ENTER." Otherwise, use the numbered keys to enter the correct date in year-monthday

 format (the left arrow key will undo mistakes) and press "ENTER."

 3. LI-COR will display the time of day, followed by "HHMM." Adjust to match your watch 

using the

 numbered keys (hours-minutes, 24 hour clock), and press "ENTER".

 4. LI-COR will display numbers and letters as in step 1, for instance, "11 O.OUM".

 5. Press "FCT ON" a second time to bring up a list of auxiliary functions. Using the up or

down

 arrow, scroll through the menu until the display reads, "FCT:Log Remarks".

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 6. Press "ENTER." The LI-COR will read "LOG REMARKS," then it will prompt, "DATE 

:940721."

 The date shown will be the last day you did PAR. Use numbered keys to enter today's date 

using

 year-month-day format. The left arrow will erase mistakes. Press "ENTER" when ready.

 7. LI-COR will prompt "HEX :3712061." The hex shown will be the last one on which PAR data 

was

 collected. Use the numbered keys to enter today's hex number, and press "ENTER."

 8. LI-COR will prompt" : " We don't use the third remark, so press "ENTER." The 

display will

 now read "FCT:Log Remarks."

 9. Press the "FCT ON" key to exit the list of auxiliary functions, returning to "11 

O.OUM."

 10. Press "CFG" to enter the configuration mode. LI-COR will prompt "mode is INST."

 11. Use the up or down arrow to make the display read "mode is LOG", and press "ENTER."

 12. Display will read "ch1 is LIGHT." Press "CFG" to exit configuration mode. Now the 

display shows

 a data point like "1M O.OUM." (The exact numbers will vary with light levels.) When in 

LOG mode,

 the "M" in the second field, following the "1."

 The datalogger is now reading channels 1 and 2 every five seconds and averaging the readings

every

minute. At the programmed time (11:00 a.m.), readings will be stored in memory. Until that 

time, the

datalogger will measure but not record data. NOTE: If you set up the ambient station after 11:00

a.m.,

the datalogger will measure but not record data until the following morning!

 To prevent this from happening, put the datalogger into LOG mode before 11:00 a.m., even 

if you are

not yet on site. If you put the LI-COR into LOG mode while en route to the plot, it will begin

logging at

11:00 a.m., even though the quantum sensors are not attached. When you get to the plot, 

attach the

quantum sensors and proceed as usual.

 If you still miss the 11:00 a.m. deadline, you will need to reprogram the LI-COR to begin 

logging at a

later time. Follow the instructions in Section 4.4.3, except the time to enter at the "reset= HHMM"

prompt should be the present time, plus 5 or 10 minutes to allow for reprogramming.

 For example, you have missed 11:00 a.m. start and realize at 11:30 that the LI-COR is still

in INST

mode. If you put it in LOG mode now, it will not record data until tomorrow morning. You 

need to

reprogram the datalogger to begin logging at 11:40 a.m. The other menu selections will all 

remain the

same, therefore enter "ENTER" at each prompt. When prompted for "reset= HHMM", enter "1140". 

This

will need to be repeated for both channel 1 and channel 2. (Remember afterwards to change the

reset

time for both channels back to 11:00 a.m. prior to the next day's plot.)

4.6.3.3 PAR Grid Establishment

 It is easiest to establish the PAR grid at each subplot during initial plot layout (see 

Figure 4-1). Be

careful of the microplots and the vegetation structure quadrants to avoid trampling or 

disturbing vegetation.

In many cases, the foresters will establish the PAR plot.

 1. Locate center point of subplot 1 and flag. Stake the measuring tape at subplot center.

 2. With the compass located over the center point, establish point 2 (as numbered in 

Figure 4-1) by

 heading 30° azimuth for a distance of 7.3 m (24 feet) horizontal. Mark this point with a

flag the

 same color as used at subplot center (e.g., yellow).

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 3. Establish points 3, 4, 5, 6, and 7 by heading 7.3 m (24 feet) horizontal from the 

subplot center at

 azimuth bearings 90°, 150°, 210°, 270°, and 330°, respectively. Marking these points with

flags

 of contrasting color (e.g., pink) makes it easier to keep track of position.

 4. Repeat these steps on subplots 2, 3, and 4.

 At each subplot, the subplot center and the PAR grid point at 30° will be flagged in one 

color while the

remaining points will be flagged with another color.

4.6.3.4 Under-Canopy Measurements

 1. Clean the ceptometer probe by rubbing the white surface with a soft cloth dipped in 

alcohol.

 2. Clear memory on ceptometer. Select Function 8, hold down button A and press Button B. 

The

 display will indicate "POOOO" (meaning: the number of averages that are currently stored 

in memory

 is zero).

 3. Check time of day by selecting Function 6. Adjust if necessary to match your watch. The

"A" key

 changes hours, the "B" key changes minutes. The ceptometer has a 24-hour clock, therefore

1:00

 p.m. is 1300.

 4. Prepare for sampling. Select Function 1. The display indicates PAR on the right side and

sample

 number of the left side of the display. The PAR number will change as the ceptometer is 

moved.

 5. At PAR point 1, the first under-canopy sampling location, perform the following 

procedure:

 (a) Stand over the sample point with the ceptometer at waist height. Arms should be 

extended

 so that the body will not shade the sensors. Hold the ceptometer level. Press 

button A and

 hold down while turning in a circle. The ceptometer will take 4 samples per second 

while the

 A key is held down. If the turn is obstructed, release button A temporarily, move 

past the

 obstruction (e.g., shrub), and press button A again to complete the turn. When 

complete,

 release the A key. The ceptometer will display the number of readings taken at the 

left and

 the last PAR reading on the right. Collect 30 or more readings at each grid point. 

When

 "stabbing" in heavy underbrush, attempt to distribute the readings evenly around 

the full circle.

 (b) Press button B to display average.

 (c) Press button B again to store the average. The ceptometer will display "P00001" to 

indicate

 that 1 reading has been stored in memory. Make sure that the number of readings 

stored in

 memory corresponds with the PAR point just sampled! Proceeding to the next point 

and

 pressing A before saving the average will erase the data.

 (d) After making sure that the average has been saved, press button A once to clear

 readings and reset the sample counter.

 6. Move to the next under-canopy sampling point on subplot 1 in sequence.

 7. Repeat steps 5 and 6 until all 7 sampling points on subplot 1 have been sampled. 

IMPORTANT:

 After all of the 7 points on a subplot have been sampled, make sure that the record 

count is

 correct. If the record count is not correct, make a note in the notebook. Then enter 

these notes

 in the comment field when downloading the data in step 1 of Section 4.6.3.6. The 

following format

 should be used (for example): "After completing subplot 2, ceptometer only had 13 

records." Do
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 not attempt to erase data or to add missing data.

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 8. Repeat: Steps 5-7 at subplots 2, 3, and 4 in sequence. When finished, return 

ceptometer to

 carrying case.

4.6.3.5 Deactivate Ambient Station

 At the end of the work day, return to the ambient station. End the recording session by 

putting the

datalogger into the INSTantaneous mode:

 1. Press "FCT ON." LI-COR will display "1 Ml O.OUM."

 2. Press "CFG" to enter configuration mode. LI-COR will display "mode is LOG."

 3. Use up or down arrow to scroll display to "mode is INST," and press "ENTER."

 4. Press "CFG" to exit configuration mode. LI-COR will display "11 O.OUM."

 5. Press "OFF" to shut down the LI-COR. Data in memory is safe.

4.6.3.6 Downloading Data

 1. To download the data from the ceptometer and the datalogger to a microcomputer (PC), 

complete

 these procedures following the prompts from the PC.

 (a) Press F2 to select "PAR Services" from the main menu.

 (b) Press F1 to activate the ceptometer download procedure on the PC menu.

 (c) Connect the interface cable between the PC and ceptometer.

 (d) Follow PC prompts to enter state, hex number, plot ID, QA status, crew type, and 

sky

 conditions. "F1" is a help key that accesses menu choices for each of these entries. 

Choices

 for sky conditions are full sunshine, few clouds, many clouds, or overcast.

 (e) Select function 8 on the ceptometer.

 (f) Press button B to send the accumulated values to the PC. The display will count the 

records

 as they are sent. When the PC requests a second transfer, press button B again.

 (g) If both transfers match byte for byte, the PC will prompt you to enter comments about

the plot.

 Type in all comments written in the pocket notebook. Any information concerning 

weather, plot

 conditions (e.g. brushiness or steepness), missed or out of order data points, etc., 

should be

 included. Note the forest type. Press ESC when finished with comments.

 (h) Use any key to return to the main menu.

 2. Download the LI-1000 Datalogger.

 (a) Press F2 to select "PAR Services" from the main menu.

 (b) Press F2 again to call up the datalogger dump program.

 (c) Read the message about hex numbers and press any key. A box is displayed 

showing

 information about the software.

 (d) Press any key. The top 2/3 of the screen is now blank, and the bottom 1/3 lists

various

 function key assignments.

 (e) Securely connect the proper cables between the PC and the LI-1000 datalogger.

 (f) On the PC, press the F1 key, then the I key, highlight "LI-1000, Li-1200 

Datalogger".

 Press Return key.

 (g) On the PC, to name the file, press F6. Type in the 7-digit hex number followed 

by the 1-

 digit plot number, and press Return.

 (h) On the datalogger, press FCT/ON.

 (i) On the datalogger, press OUT.

 (j) On the datalogger, use up/down arrows to select the baud rate of 48 and press 

ENTER.

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 (k) On the datalogger, select H for horizontal format. Display will read "form=H". 
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Press

 ENTER.

 (I) On the datalogger, the next display will be "len = ". Enter the number 80. 

Press ENTER.

 (m) On the datalogger, the next question is "dump all = yes", toggle answer and press

ENTER.

 The display will show "dumping". The data dump can be aborted by pressing the OUT

key

 again. When the data dump is complete, the display will read 11 XX.XXUM.

 (n) On the PC, press Alt-X to exit the program.

 (o) Check the PC or disk directory to make sure the transfer was successful. An 8-

hour data

 file will be approximately 24000 bytes.

 (p) Follow the PC instructions to make a backup copy of the file.

To clear the memory for the next plot's data:

 3. Press "FCT ON" to enter the list of auxiliary functions. LI-COR will display "FCT:Log 

Remarks."

 4. Use the up or down arrow to scroll display until it reads "FCT:Clear Ram," and press 

"ENTER."

 5. Display reads "OK Clear Mem NO." Scroll to YES and press "ENTER." The datalogger

 memory is now cleared.

 6. Press "FCT ON" to exit the auxiliary functions. Display reads "11 O.OUM."

 7. Press "OFF" to shut down the LI-COR.

4.5.4 Preventative Maintenance

 1. Always keep the white surface of the ceptometer probe clean to assure accurate readings. To

 clean the probe, use alcohol and a soft cloth. Rub the surface until it appears clean.

 2. Change batteries (see User's Manual) prior to the field season and whenever the display 

indicates

 "LO" when the ceptometer is activated. Field calibration is required after batteries are 

changed.

 3. Always transport the ceptometer in the protective carrying case. Shield the ceptometer 

from shock

 damage by securing it to some part of the vehicle during travel to and from plot 

locations.

 4. The ceptometer is a fragile and expensive electronic instrument. Never use it as a tool 

for anything

 other than the designed purpose. Protect the probe from shock damage by avoiding impact 

with

 trees while moving from location to location.

 5. Keep the ceptometer dry and in the carrying case when not in use. It is neither waterproof nor

 water-resistant. Bring the ceptometer into the hotel at night to prevent heat damage and

theft.

 6. Use only water to clean the quantum sensors. Keep them in a carrying case while 

transporting

 them from location to location. Keep the datalogger in a cool place, out of the sun when 

it is not

 in use. Also, bring the quantum sensors and the datalogger into the hotel when not in 

use.

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4.7 References

Decagon Devices, Inc. 1991. Application note: canopy leaf area index from sunfleck ceptometer 

PAR

 measurements. Decagon Devices, Inc., Pullman, Washington, 3 pp.

Decagon Devices, Inc. 1989. Sunfleck ceptometer user's manual. Decagon Devices Inc Pullman WA

 28 p.

Norman, J. and G. Campbell. 1989. Canopy structure. In: Pearcy, R., J. Ehleringer, H. Mooney, 
Forest Health Monitoring: Field Methods Guide

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and P.

 Rundel, eds. 1989. Plant Physiological Ecology. Chapman and Hall, London, p. 301-325.

Waring, R.H. and W.H. Schlesinger. 1985. Forest ecosystems: concepts and management. Academic

 Press, Orlando, FL.

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 1 of 12

 Section 5. Vegetation Structure

Section/Title

5.1 Overview 2 of 12

 5.1.1 Scope and Application 2 of 12

 5.1.2 Summary of Method 2 of 12

 5.1.3 Interferences 2 of 12

 5.1.4 Safety 3 of 12

5.2 Plant Sample Collection and Handling 3 of 12

5.3 Equipment and Supplies 5 of 12

5.4 Calibration and Standardization 5 of 12

5.5 Quality Assurance 5 of 12

 5.5.1 Training 5 of 12

 5.5.2 Measurement Quality Objectives (MQOs) 6 of 12

 5.5.3 Collection of Quality Control Data 6 of 12

 5.5.3.1 Remeasurements and Audits 6 of 12

 5.5.3.2 Calculation of Achieved Data Quality 6 of 12

 5.5.4 Method Performance 6 of 12

5.6 Procedure 6 of 12

 5.6.1 Overview 6 of 12

 5.6.2 Quadrat Layout 6 of 12

 5.6.3 Vegetation Structure Measurements 7 of 12

 5.6.4 Documentation of Plot Conditions 11 of 12

5.7 References 12 of 12

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 2 of 12

 5.1 Overview

 5.1.1 Scope and Application

 The vegetation structure indicator provides information on species composition, relative 

amounts of

 cover, and spatial distribution of vascular plants in the forests. Further, it quantifies 

habitat structure, which

 strongly influences wildlife diversity (DeGraaf and Rudis, 1983). Plants are one of the many 

taxa (e.g.,

 arthropods, vertebrates, nematodes) that should be measured in order to fully assess forest 

biodiversity

 on a regional scale. Vegetation structure complements other indicators, particularly PAR, 

wildlife habitat,

 crown condition, growth, regeneration, mortality, and species diversity.

 5.1.2 Summary of Method

 Vegetation measurements are taken in small permanent 1 m* quadrats that are systematically 

laid out

 on each subplot (3 per subplot or 12 per plot). On each quadrat, three basic types of data are

recorded:

 (1) plant species identification, (2) height class(es) (stratum or strata) at which each 

species occurs, and

 (3) plant canopy cover. Collect data by stratum. There are four strata, defined below. Start 

at the lowest

 stratum and work up, using the quadrat frame and height pole to define the sampling area. 

Specimens

 of all plants present in the quadrats that cannot be confidently identified to the species 

level should be

 collected off-plot, labelled, pressed, and submitted for subsequent identification. Record all

data on the

 appropriate screen on the portable data recorder (PDR). The PDR data file for each plot should 

be closed

 before leaving the field and later that day downloaded to the field crew's laptop computer for 

transmission

 to the central data base.

 5.1.3 Interferences

 Several uncontrollable environmental and site conditions have hindered or slowed vegetation 
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structure

 measurements, including (1) poor weather conditions such as gusting wind, heavy rain, and 

dark overcast

 skies; (2) steep and/or unstable slopes; (3) dense and diverse understory vegetation; (4) the

phenological

 and/or maturity stage of plant(s); and (5) thick vegetation immediately overhead that obscured 

the view of

 the taller vegetation. Follow these guidelines to reduce the effects of interferences on 

proper data

 collection:

 1. Suspend data collection under severe weather conditions, such as strong winds and heavy 

rainfall.

 2. In areas with thick vegetation, each side of the collapsible quadrat frame should be slid

carefully

 through the vegetation separately and then attached at comers. The frame should be 

completely

 assembled and the height pole in place before vegetation measurements begin; all vegetation 

should

 hang freely and naturally about the frame and pole. First, record the cover of taller and/or

abundant

 species in each layer before searching for shorter or obscure species growing below them. 

See

 Subsection 5.6.4 for additional details.

3. On steep and/or unstable slopes, avoid the area immediately upslope from the quadrat 

sampling area.

 Stand below or to the side of the sampling frame to avoid falling or sliding into the 

sampling area and

 disturbing the vegetation and ground surface. Next, level the quadrat frame, and proceed 

with

 measurements.

4. Immature plants or plants not flowering or fruiting have affected the level and accuracy of

identification.

 In addition, plants either expanding or dying back have hindered both identifications and 

canopy cover

 estimates. For either situation, collect the most complete plant specimen that is 

possible and

 appropriate, including roots, stem and leaves, and fruit, seeds, or cones. If the plant 

sample is dry and

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 3 of 12

 brittle, soak it in water before pressing. See Subsection 5.2 for additional details. 

Meanwhile, the

 canopy cover of each plant species should be estimated as it exists at the time of sampling,

ignoring

 whether it is expanding or dying.

5. When thick vegetation is immediately overhead, the height pole should be leveled and raised 

through

 the vegetation as necessary to provide a reference for estimating the cover of taller 

vegetation covering

 the quadrat.

5.1.4 Safety

 No specialized safety precautions are necessary. Follow general safety precautions for 

conducting

fieldwork (see Appendix E).

5.2 Plant Sample Collection and Handling

 Plant specimens should be collected in the field for three reasons: 1) to obtain the most 

accurate

taxonomic identification (FHM is concerned with basic biodiversity elements, including species, 

varieties

and subspecies, endemics, exotics, and threatened and rare plants); 2) to obtain a quality 

assurance check

of field identifications (FHM is providing policy-relevant information so the level of 

uncertainty must be

known); and 3) to secure a permanent record of the plants sampled (FHM is a long-term program 

so

activities and data bases must be thoroughly documented).

 Specimens of all plants present in the quadrats that cannot be confidently identified to 
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species should

be collected off-plot, labeled, pressed, and dried for shipping and subsequent identification 

by the field

botanist or a cooperating herbarium. Field specimens permit field identifications to be 

confirmed, corrected,

or improved (e.g., from genus only to species). Subsequently, field specimens will serve as 

documentation

of the presence of the species on a plot and as a permanent record of the identity of the 

sampled plant.

 Follow these guidelines when collecting plants and handling specimens for identification:

1. Each botanist should record his/her most accurate taxonomic field identification for each 

vascular plant

 encountered. However, a specimen of each unique plant should be collected for identification 

and/or

 verification except when the plant in question is common or abundant, widespread, and wellknown

 (i.e., 'its species identity is known with complete confidence). Most tree and some shrub 

species fit this

 exception. However, many herbaceous species do not.

2. Supply as complete as specimen as possible. Do not "top" or "end snatch" plants. 

Underground parts

 should be collected for complete identification (e.g., bulbs of Allium or rhizomes of 

perennial grasses).

 Fruit should be collected, especially for oaks and pines.

3. Collected plant specimens should be stored temporarily in either (1) large, scalable plastic

bags held

 in a 3-ring binder or (2) a magazine or stack of newspapers until field work is completed. 

Large

 specimens should be bent or broken along the stem to fit in the bags or papers. Brittle 

specimens

 should be wetted with water to prevent or lessen breakage of leaves and fruits. Separate 

nuts, fruits,

 or cones should be placed in the same bag if possible. Otherwise, the nuts or cones can be 

labeled

 identically and stored separately. High heat and humidity will damage specimens stored in 

plastic

 bags.

4. Complete a label with the appropriate number for each specimen (Figure 5-1). This provides 

a unique

 reference code of plot number, subplot number, quadrat number and the plant identification 

number

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 4 of 12

 entered in the PDR (i.e., field 1 in Figure 5-2). This code will be used to match the 

specimen with the

 correct data line in the PDR. Remove the sticky back from the label. Attach the label 

directly to the

 stem of the specimen so that the information on the label is clearly visible.

 5. After the field work has been completed on the plot, plant specimens should be removed 

from the

 plastic bags or magazines and arranged on dry, folded newsprint for pressing and drying. As

the two

 presses fill up with fresh specimens, the drier plants should be moved to the storage

box for

 subsequent mailing. More detailed instructions for pressing plants will be given at the 

training sessions

 prior to the beginning of the field season.

 6. Pressed plant specimens should be mailed regularly to the plant taxonomist for 

identification or

 verification. Packages should be mailed weekly or after specimens from 3 plots have 

accumulated.

 Additional written guidelines for plant sampling and handling based on Radford et al. 

(1974) and

 Walters and Keil (1988) will be supplied at training, along with instruction.

00000

HEX NO.

DATE

HABITAT
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00000

HEX NO.

DATE

HABITAT

00000

STATE

COUNTY

DATE

HABITAT

 Figure 5-1. Plant specimen label used for vegetation structure indicator.

 Subplot 1

 Trample: _

 Quadrant 1

FIA Condition:

 Dominant mircohabitat 

 Start: Stop:

 Sub/Spc

 ST CC

 Enter Trample Code

Figure 5-2. Portable data recorder screen.

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 5 of 12

5.3 Equipment and Supplies

 The equipment needed to measure vegetation structure includes:

 • Loggers tape and hand compass for quadrat layout

 • Hammer; long, thick plastic tent stakes to monument quadrat locations for relocation; 

and quiver

 to hold stakes

 • One collapsible, plastic pipe, quadrat sampling frames (1 m )

 • Short (5-6 m/16-20 ft), telescoping height pole (equipped with leveling device and 

pointed foot

 attachment to securely set pole vertically) for measuring upper strata heights, the 

location of tall

 overhanging vegetation, and the heights of tall shrubs

 • 15x hand lens, binoculars, metric ruler, and regional/local plant taxonomy handbooks to

aid in plant

 species identification

 • Portable data recorder with two extra batteries; backup supply of field sheets

 • Three-ring binder and large plastic bags for holding plant specimens collected in the 

field, pre-

 printed waterproof labels, and indelible ink pens or magazines

 • Two plant press frames (ca. 12x18 inch or 30 x 50 cm), with corrugated cardboard sheets 

(50),

 blotter paper sheets (200), newspapers (200 pages), small paper bags (50) for pressing 

and drying

 field specimens, and four (4), 1-inch wide binder straps

 • Sturdy box (ca. 12x18 inch or 30 x 50 cm) for storing, transporting, and shipping 

dried plant

 specimens removed from the plant press

 • Cruiser vest

 • Internal frame backpack

 • Hand trowel

 • Pocket knife

 • Snake leggings, gloves, insect and tick repellent

 • Bee sting and snake bite antidotes

 • Quadrat levelers

5.4 Calibration and Standardization

 Purchase tapes to required specifications. Tapes should be maintained in working order and 

do not

need calibration. Check the compass regularly against known directions. In the field, avoid 

magnetic

interference. Use the compass without correction for declination (magnetic north).

5.5 Quality Assurance

5.5.1 Training

 Indicator leads direct training of botanists. Trainers should meet during a pretraining 

session to

troubleshoot methods and refine the written protocols. These meetings should be in conditions 
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similar to

field settings, (i.e., similar forest types and equipment). Follow pretraining with a training

session for the

field teams.

 During the training session, trainers will test the botanists for comparability after 

complete training of

the vegetation structure protocol. The test should consist of a series of on-plot and 

between-plot

remeasurements and calculations of method precision. Use estimates of method precision in the 

field as

quidelines for data acceptability. The botanists will also be trained and tested on plant 

identifications skills

using specimens collected from last year's plots. In order to be certified, botanists must 

perform at or

above a specified level of accuracy on test plots. Certification is discussed in greater detail

in FHM Quality

Assurance Plan (Stapanian and Cline, 1994).

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 6 of 12

 5.5.2 Measurement Quality Objectives (MQOs)

 For the training session, the MQOs are as follows:

 1. Difference in total number of species per plot: not to exceed + 10%.

 2. Plant community similarity: > 75%.

 3. Absolute difference in abundance of each plant species (cover):

 Strata 3 & 4:+ 15%

 Strata 1 &2: +10%.

 These MQOs are not based on data previously collected, therefore, revisions are quite 

likely. Use data

 from the remeasurement program of the training session to estimate measurement quality 

objectives for

 the field work.

 5.5.3 Collection of Quality Control Data

 5.5.3.1 Remeasurements and Audits

 The entire crew should also remeasure predetermined "quality control" plots during the field

season

 (preseason [training], mid-season, and post-season [debriefing]). These remeasurements can be 

used to

 estimate variation due to measurement error and season. In addition, botanists will be audited 

in the field

 at least once in order to minimize errors in procedure.

 5.5.3.2 Calculation of Achieved Data Quality

 Quality control data should be analyzed and reported as a component of the overall 

population

 variation. Variation should be assessed from control charts of quantitative measurements and 

frequency

 distributions of qualitative measurements.

 5.5.4 Method Performance

 Method performance will be determined through analyses of quality control data collected 

during the

 field season. A series of reference plots will be visited by the crew several times during 

the year to

 estimate bias, within-and between-crew variation, and within-year variation.

 5.6 Procedure

 5.6.1 Overview

 For the vegetation structure measurements, the sequence of activities at each subplot is: 

(1) establish

 sample locations for quadrats (Figure 5-3), (2) measure vegetation within each quadrat, and (3)

photograph

the subplot to document conditions.

 5.6.2 Quadrat Layout

 The first step is to define the sample areas for the vegetation measurements. Quadrats are 
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established

 15 ft (4.57 m) from each subplot center along 30° (no. 1), 150° (no. 2), and 270° (no. 3) 

azimuths (Figure

5-3).

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Figure 5-3. Layout of quadrats on each subplot. Quadrats are 1 m2 and subplot 168 m2 drawn to 

scale.

1. Site the 30° azimuth and measure and mark 15- and 18.28-ft (4.57- and 5.57-m) horizontal 

distances.

2. Mark the two distances permanently with long, heavy, plastic tent stakes to serve as 

reference corners

 for remeasurement of the quadrat. o

3. Place one side of the sample frame directly on or next to these stakes, since the azimuth 

line defines

 the left edge of the sampling area.

4. Assemble and level the other sides of the quadrat frame to define the horizontal sample 

area (Figure

 5-4).

5. Set the telescoping height pole vertically in the ground at or near the center of the plot 

to aid definition

 of the vertical sample areas and determination of "in or out" plant cover in higher strata 

(Figure 5-4).

6. Make the vegetation measurements as described in 5.6.3.

7. Repeat steps 1 -6 for quadrat layout and vegetation measurements for quadrats 2 and 3 on the

subplot.

8. Repeat steps 1-7 for subplots 2-4.

5.6.3 Vegetation Structure Measurements

 Measure vegetation structure immediately after you establish a quadrat. The objectives 

of the

 procedure are 1) to identify all plant species present within each sample quadrats, and 2) 

to measure

 the amount to their canopy cover both individually and collectively.

 Record the following header information for each quadrat: subplot no., quadrat no., 

disturbance

 ("trample") code (see Table 5-1 a for codes and definitions), FIA condition code (from FIA 

crew leader),

 dominant microhab'rtat (Table 5-1b), start time and stop time (from PDR internal clock).

(NOTE: Enter the data for each quadrat on a separate PDR screen (Figure 5-2). The PDR quadrat 

screen

has 40 columns and 16 rows visible at once and scrolls up and down line by line after the 16th

row. This

setup allows the field botanist to see all or most of the previous entries made on the quadrat. 

The stop

time is the last item recorded for the quadrat; the program returns to this item after all 

vegetation data are

recorded and it must be filled in to exit and begin the next quadrat.)

1.

2.

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 8 of 12

 a.

 Inside dimensions 1 m x 1 m

 Ignore overlap of

 same species

 Add individual

 polygons to determine

 total for species

 Count overlap of

 plant and substrate

 separately

 Count overlap

 of two different

 species separately

 Count overlap of two

 different substrates separately

 1/2" 

- 3/4" Plastic pipe

 

(thick-walled) divided

 into 
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10-cm segments

 using

black tape or paint

 Removable

S~ plastic corners

 b.

Figure 5-4. a) Collapsible 1 m2 quadrat sampling frame and b) placement of telescoping pole on 

quadrat.

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 9 of 12

 Table 5-1. PDR Screens and Codes

a) Disturbance codes (Trampling)

 1 none/slight 0-10% of quadrat disturbed

 2 moderate >10-50% of quadrat disturbed

 3 heavy >50% of quadrat disturbed

b) dominant microhabitat

 1 Mineral Soil/Sediment; physically weathered soil parent material that may or may not also 

be chemically and biologically

altered

 2 Rock: a large rock or boulder or accumulations of pebbles or cobbles

 3 Standing water/Flooded: ponded or flowing water that is not contained within banks

 4 Stream: body of flowing water contained within banks

 5 Dead wood: log and slash (> 10 cm diameter), stump

 6 Litter/duff: accumulation of organic matter over forest mineral soil, including branches 

and limbs

 <10 cm diameter and bark

 a-< 1 cm continuous

 b-> 1 cm continuous

 7 Live roots/bole: living roots at the base of trees or exposed at the surface of the 

forest floor or soil and cross-sectioned area

 of live tree boles at ground-line.

 8 Road

 9 Cow pie

 10 Trash/junk

c) vegetation strata (O'Brien and Van Hooser, 1983)

 Code Definition Strata Height

 1 Ground/bryophyte/low herb layer 0-2 ft (0-0.61 m)

 2 High herb/low shrub layer 2-6 ft (0.61 -1.83 m)

 3 High shrub/low tree layer 6-16 ft (1.84-4.88 m)

 4 Middle/upper tree layer >16 ft (>4.88 m)

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 10 of 12

Table 5-1. PDR Screens and Codes (cont.)

d) identification of plant species

 Species codes for vascular plants will come from a standard national list (Soil Conservation

Service, 1982). Species codes

are typically a 4-letter code, formed by the first two (2) letters of genera and species. 

Replicates of the base 4-letter code are

differentiated by adding a sequential number, forming a 5- or 6-digit code (4 letters plus 1 or 

2 numbers). Similarly, a variety or

subspecies are indicated by adding their first letter to the base 4-letter code, forming a 5-

digit code. An example is shown below.
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A different coding format is used if the plant cannot be confidently identified to the species 

level. Specimens should be collected

for such "unknown" plants (Subsection 5.2). The specimen number on the preprinted label for the 

specimen should be entered as

the species on the PDR. When a specimen for an unknown can not be found, the botanist should 

enter an "x" (representing an

unknown species for which there is no specimen) followed by a consecutive number, (representing 

the sequential numbering of

unknowns on the plot) and a short descriptor (e.g., herb). Numbering starts over on each new 

plot.

Phylogentic Determination

1. Genera / species / subsp. or var.

 Astragolus adsurgens subsp. rebustion or

 A. adsurgens var. tamaraicans

2. Genera species

 A. adsurgens

 Code

ASADR2

ASADT

ASAD

3. Make and record separately three types of vegetation structure measurements:

 a) Identification of plant species,

 b) Stratum (ST) of plant, and

 c) Amount of plant canopy cover (CC).

 The following guidelines should be observed during measurements and data recording:

1. Begin measurements and data recording in the lowest stratum (0 - 2 ft, Table 5-1 b) and work

upward,

 making sure to stay within the predefined horizontal and vertical boundaries of the sampling

areas

 (Subsection 5.6.2, Figure 5-4).

2. First identify the dominant microhabitat (Table 5-1c) and plant species (Table 5-1 d) in 

the vertical

 stratum (Figure 5-4) and record on PDR (Figure 5-3).

 a) Plants are identified with the highest level of taxonomic accuracy possible, preferably

to species,

 and if applicable and possible, to subspecies or variety. Use the 4- or 5-character 

abbreviation

 (Soil Conservation Service, 1982). Similarly, unknown species are identified with the 

highest level

 of taxonomic accuracy possible. When the botanist encounters a plant which he/she can 

not

 confidently identify to species, a specimen should be collected off-quadrat (Subsection

5.2). The

 specimen number from the preprinted label should be entered in the species field on the

PDR

 screen. If no specimen of the "unknown" plant can be found, then an "x" followed by a 

consecutive

 number (1, 2, 3...) and a descriptor (e.g., herb) should be entered.

 b) The species list for each stratum should be as comprehensive as possible, including 

species of

 vascular plants (herbs, shrubs, vines, grasses, ferns, and trees), bryophytes (mosses 

and

 liverworts), and lichens. Priority is given to terrestrial vascular plants rooted in 

the soil, other

 ground substrates, or those overhanging the quadrat. Mosses, liverworts, and lichens 

should be

 recorded and scientifically named if possible. If they cannot be named scientifically, 

then they

 should be named as "moss," "liver," or "lien," followed by a consecutive number (1, 2,

3...) if more

 than one species is apparent. Epiphytes (e.g., lichens and mosses on tree boles or 

branches) will

 not be sampled on quadrat.

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 EMAP Forest Monitoring, Section 5, Rev. 0, October, 1994, Page 11 of 12

3. Next record the vertical stratum code (1-4) of the plant species cover (Table 5-1 b) on the 

PDR (ST in

 Figure 5-2). Plant species growing in more than one stratum will have multiple entries, 

with one record

 for each stratum. In these cases, record the same plant codes used in field 1 for each 
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stratum.

4. Directly estimate the canopy cover (CC) of every plant species within a stratum to the 

nearest one

 percent (no classes) and record (Figure 5-2).

 a) Canopy cover is estimated in two steps following the rationale of Daubenrnire (1968). 

First, the

 natural extent of individual plant canopies within or overlapping the sample area are 

visualized as

 polygons (Figure 5-4). Conceptually, the polygons define a plant species' sphere of 

influence

 above- and below-ground, including any natural openings of each canopy. Then, the 

polygon

 areas are vertically projected to the ground surface to determine the percent of the 

quadrat area

 (1 m2) covered by each plant species in the stratum. Superimposed canopies of different 

species

 are determined separately, while the overlap of superimposed canopies of the same species

is

 ignored (Figure 5-4).

 b) Use the guides on the sampling frame to successively delimit the quadrat area covered 

by the

 vertically projected canopy of each plant species in the stratum (Figure 5-4). For 

example, there

 are 100,1 dm2 (1%) and 4, 25 dm2 (25%) areas in a 1 m2 sampling frame. The larger areas 

can

 be used initially to determine if plant species canopy cover is >75, 50-75, 25-50, or 

<25%, while

 the smaller 1 dm segments can be used to aid subdividing the larger areas to arrive at

a final

 percent cover estimate for the species.

5. Repeat steps 1-4 for each stratum of the quadrat.

6. After completing measurements for all strata on the quadrat, collect (off-plot) specimens 

of all plants

 not positively identified by species and specimens of known species encountered for the 

first time.

 Refer to Subsection 5.2 for a complete description of plant collection and handling 

procedures.

7. Repeat steps 1-6 for quadrats 2 and 3.

8. Repeat steps 1-7 on quadrats of subplots 2-4.

5.5.4 Documentation of Plot Conditions

 Environmental and disturbance factors encountered on the plot should be documented in the

disturbance codes. This information assists the indicator in data analysis and interpretation 

and provides

information on plot aesthetics.

 The foresters have been instructed to provide the botanists with their general descriptions

of forest,

topographic, and soil conditions for each subplot. Supplement these descriptions, as 

necessary, with

unique or special conditions affecting plant distribution and growth that may be encountered on 

particular

quadrats.

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5.7 References

Archambault, L, B.V. Barnes, and J.A. Witter. 1989. Ecological species groups of oak ecosystems 

of

 southeastern Michigan. For. Sci. 35: 1058-1074.

Atkeson, T. D. and A.S. Johnson. 1979. Succession of small mammals on pine plantations in the

 Georgia Piedmont. Amer. Midi. Nat. 101: 385-392.

Childers, E.L., T.L. Sharik, and C.S. Adkisson. 1986. Effects of loblolly pine plantations on 

songbird

 dynamics in the Virginia Piedmont. J. Wildl. Manage. 50: 406-413.

Cline, S.P. 1992. Vegetation Structure indicator. IN Forest Health Monitoring 1992 Activities 
Forest Health Monitoring: Field Methods Guide

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Plan.

 S.A. Alexander and J.E. Barnard. EPA/620/R-93/002. U.S. Environmental Protection Agency,

 Washington, D.C.

Daubenmire, R. 1968. Plant communities: a textbook of plant synecology. Harper & Row, New York.

DeGraaf, R.M. and D.D. Rudis. 1983. New England Wildlife: Habitat, natural history, and 

distribution.

 USDA Forest Service. NE For. Exp. Stn. Gen. Tech. Rpt. NE-108. 491 p.

Felix, A.C. Ill, T.L. Sharik, and B.S. McGinnes. 1986. Effects of pine conversion on food 

plants of

 northern bobwhite quail, eastern wild turkey, and white-tailed deer in the Virginia piedmont.

South.

 J. Appl. For. 10:47-52.

Miller, P.R. and J. R. McBride. 1975. Effects of air pollution on forests. IN Mudd, J.B. and 

T.T.

 Kozlowski (eds.) Responses of Plants to Air Pollution. Academic Press, N.Y. pp. 175-235.

O'Brien, R. and D. Van Hooser. 1983. Understory vegetation inventory: an efficient procedure. 

USDA

 Forest Service. Intermt. Forest and Range Exp. Stn., Ogden, UT. Res. Paper INT-323. 6p.

Radford, A., W. Dickison, J. Massey, and C.R. Bell. 1974. Collection and field preparation of

 specimens. Chapter 18. IN Vascular plant systematics. Harper and Row. pp 387-398.

Repenning, R.W. and R.F. Labisky. 1985. Effects of even-age timber management on bird 

communities

 of the longleaf pine forest in northern Florida. J. Wildl. Manage. 48: 895-911.

Soil Conservation Service. 1982. National list of scientific plant names. Vol. 1. List of plant 

names.

 USDA Soil Conservation Service. Ecological Sciences Staff. Washington D.C. SCS-TP-159. 416p.

Stapanian, M.A. and S.P. Cline. 1994. Vegetation structure indicator, jn Cline, S.P. and C. 

Palmer.

 Forest Health Monitoring: 1994 Quality Assurance Project Plan.

Walters, D. and D. Keil. 1988. Collecting and preserving plants for study. Chapter 6 IN Vascular

plant

 taxonomy. Kendall and Hunt, pp 55-67.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 1 of 21

 Section 6. Ozone Bioindicator Plants

Section/Title Page

6.1 Overview 2 of 21

 6.1.1 Scope and Application 2 of 21

 6.1.2 Summary of Method 2 of 21

 6.1.3 Interferences 3 of 21

 6.1.4 Safety 3 of 21

6.2 Sample Collection, Preservation, and Storage 3 of 21

6.3 Equipment and Supplies 3 of 21

 6.3.1 Equipment and Apparatus 3 of 21

 6.3.2 Consumable Supplies 4 of 21

6.4 Calibration and Standardization 4 of 21

6.5 Quality Assurance 4 of 21

 6.5.1 Training 4 of 21

 6.5.2 Field Audits/Remeasurement 5 of 21

 6.5.3 Voucher Specimens (Pressed Leaves With Symptoms) 5 of 21

 6.5.4 Measurement Quality Objectives 5 of 21

 6.5.5 Method Performance 6 of 21

 6.5.6 Communications 6 of 21

6.6 Procedure 7 of 21

 6.6.1 Evaluation Window 7 of 21

 6.6.2 Site Selection 7 of 21

 6.6.2.1 New Plots (Mt1) 8 Of 21

 6.6.2.2 Established Plots (Mt2 and Mt3) 9 of 21

 6.6.3 Species Selection 10 of 21

 6.6.4 Plant Selection ...: 10 of 21

 6.6.5 Symptom Identification and Scoring 11 of 21

 6.6.6 Collection of Leaf Samples 13 of 21

 6.6.7 Crew Member Responsibilities 14 of 21

 6.6.8 Reference Plot Methods 14 of 21
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 6.6.9 Data Sheets 15 of 21

6.7 References 16 of 21

Appendix 6.A Ozone Bioindicator Plants 17 of 21

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6.1 Overview

 Plant species that respond to ambient levels of air pollution with distinct visible foliar 

symptoms are

used as bioindicators of pollution stress (Manning and Feder, 1980). Field studies and/or 

fumigation

experiments have identified ozone sensitive species (Davis and Umbach, 1981; Duchelle and Skelly,

1981;

Krupa and Manning, 1988). Foliar injury symptoms include distinct patterns of coloration, often 

associated

with accelerated senescence. Ozone is the only regional gaseous air pollutant that is frequently

measured

at known phytotoxic levels (Cleveland and Graedel, 1979; Lefohn and Pinkerton, 1988); thus, the 

focus of

this indicator in detection monitoring will be only on ozone. Suitable sites close to the FHM 

detection

monitoring plots will be selected for ozone injury evaluations. The foliage of sensitive 

plants will be

examined for the presence or absence of ozone injury, and the amount and severity of injury 

will be

recorded. Reference plots will be established in different physiographic or political regions 

(e.g., states or

USFS regions) to improve the regional assessment of this indicator. Reference plot evaluations 

are done

using the same methodology as the on-frame activities and are just as important.

6.1.1 Scope and Application

 The scope of this indicator is national, but information on the occurrence of phytotoxic 

ozone exposures

at the regional or state level is also obtained. Procedures are amended regionally as needed, 

particularly

with regard to suitable sites and target species. Other variables, such as number of species, 

number of

plants, and methods of scoring are standardized nationally. In general, the formulation of 

procedures and

the reporting and assessment goals were developed with the following considerations:

 1. Keeping the evaluation of ozone indicator plants close enough to the detection plots to 

avoid

 problems with inclusion probabilities and create links between phytotoxic levels of ozone

on the

 sensitive species and other detection plot indicators;

 2. Keeping estimated errors for the detection plot below 10%. We attempted to devise a 

method that

 can be reproduced by an audit crew within 10% for the selection of ozone-sensitive species, 

symptom

 identification, and quantification of injury; and

 3. Addressing seasonal variability in ozone injury. We know that ozone injury must reach an

undefined

 threshold within a leaf before the injury becomes visible to the human eye, and then tends 

to be

 cumulative over the growing season until Fall senescence masks the symptoms.

6.1.2 Summary of Method

 Crew procedures include the selection of a suitable site for symptom evaluation, 

identification of one

to three known ozone-sensitive species at the site, and identification of ozone injury on the 

foliage of up

to 30 plants of each species. Each plant is evaluated for the percentage of injured area and 

severity of

injury on a five point scale. Field crews record information on the location and size of the 

opening used for

biomonitoring and record injury amount and severity ratings for each plant.

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 To eliminate problems with seasonal variability in ozone response, all foliar evaluations are

conducted

during a two-to-three week window towards the end of the growing season. Foliar injury data are 

also

collected, during the evaluation window, from off-frame reference plots established in each 

state by

Regional Cooperators. The reference plots are standardized for certain site characteristics that

influence

ozone uptake by sensitive plants (Heck, 1968; Krupa and Manning, 1988). They are intended to 

provide

ozone injury information under optimal conditions of field exposure and to improve the 

regional

responsiveness of the ozone indicator.

 Voucher specimens (pressed leaves with symptoms) are collected for each species for proper 

symptom

identification. Additional quality control measures include field audits and remeasurement of 

10% of the

biomon'rtoring sites.

6.1.3 Interferences

 Primary interferences to consider are the lack of suitable sites and/or target species at 

some detection

plots. These detection plots are not directly evaluated for this indicator. Establishing 

reference plots helps

address this issue. Ozone is a regional pollutant, understood to have regional effects on 

vegetation. The

data collected at reference plots within each physiographic region should, therefore, have some 

application

to detection plots within the same region.

 The other serious consideration is discriminating ozone foliar injury symptoms from other

abiotic or

biotic foliar injury symptoms. Since the target species selected for these studies were selected 

because

of their sensitivity and distinctness of symptom, this should be an issue that can be adequately

addressed

in training.

6.1.4 Safety

 No specialized safety precautions are necessary. Follow general safety precautions for 

conducting

fieldwork (see Appendix E).

6.2 Sample Collection, Preservation, and Storage

 Leaf samples are collected by field crews. They are to be placed in a small plant press 

immediately

after removal from the selected plant. This is to preserve the integrity of the leaf sample 

and the injury

symptoms until they can be verified by the National Indicator Lead. Samples should not be 

exposed to

excess humidity or allowed to dry up too quickly. They should not be stored for any length of 

time outside

of a plant press. The sooner the pressed leaves are mailed to the National Indicator Lead, the 

better. A

data sheet identifying the field crew and plot location is to be filled out and mailed with each

sample.

6.3 Equipment and Supplies

6.3.1 Equipment and Apparatus

 - Reference photographs to aid in symptom identification.

 - A small plant press with cardboard inserts to store leaves with ozone injury for 

quality control

 purposes.

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 6.3.2 Consumable Supplies

 - Stamped, addressed envelopes to mail to the National Lead for validation of the correct 

ozone-
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 injury symptoms on each species.

 Flagging: for temporary marking of sites or sample plants.

 Field data sheets:

 (a) for documenting the presence and amount of ozone injury on each plot in the 

event

 of a PDR failure and for mapping the location of the suitable sites.

 (b) for recording information about the pressed leaf samples for quality control

purposes.

 6.4 Calibration and Standardization

 The field crew foresters will be trained in species and symptom identification and 

quantification of foliar

 injury symptoms.

 6.5 Quality Assurance

 One individual in each region assumes quality control responsibilities for the field 

season. These

 Regional Indicator Leads meet during a preseason session to refine methods and establish a 

unified

 approach to training, audits, and debriefing. Their responsibilities include: (1) training and 

certifying the

 state trainers and/or field crews as needed for their region, (2) documenting hot audits of 

the field crews,

 (3) overseeing the field crew refresher session held just prior to the evaluation window for 

this indicator,

 (4) validating the ozone injury symptom recorded by the field crews and cooperators on the 

detection and

 reference plots, (5) assisting in the field with remeasurement procedures for symptom 

quantification, and

 (6) conducting a debriefing session for the indicator.

 Quality control reports are prepared by the National Indicator Lead with input from the 

Regional Leads

 as needed. These reports will discuss all issues related to quality assurance and quality 

control including

 results of the training sessions and field audits, debriefing comments from the field crews, and an

 evaluation of remeasurement and reference plot data.

 Quality control activities of direct interest to the field crews are discussed below. 

Additional detail is

 provided in the 1994 Quality Assurance Project Plan for the ozone indicator.

 6.5.1 Training

 Each field crew member is trained and tested for familiarity with the site selection, 

species selection,

 and data collection procedures, and their ability to recognize ozone injury and discriminate 

against

 mimicking symptoms. Although field crews are certified during the regular preseason training 

session, they

 must also participate in a refresher session held just prior to the beginning of the evaluation

window for this

 indicator.

 The Regional Indicator Lead is available to answer questions and provide retraining as 

needed

throughout the field season.

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5.5.2 Field Audits/Remeasurement

 A field audit crew remeasures a subsample of the detection plots in each region. Auditing 

procedures

cover species selection, symptom identification, and quantification of injury, as well as foliar 

sample

collection, preservation and shipment.

 Field crew supervisors audit the field crews and remeasure one bioindicator site in their 

jurisdiction.

The Regional Indicator Leads assist with these audit and remeasurement activities as needed.
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6.5.3 Voucher Specimens (Pressed Leaves With Symptoms)

 Field crews and cooperators collect leaf samples on the detection plots and on the 

reference plots

according to procedures outlined in Subsection 6.6.6. These voucher specimens are pressed and 

mailed

to the National Indicator Lead for validation of the ozone symptom.

6.5.4 Measurement Quality Objectives

 Table 6-1 lists measurement quality objectives. The measurement error limits for this 

indicator are set

at 10% for the training of the field crews. We expect that the crews will identify the species 

and pollutant

symptoms and be able to estimate the amount and severity of injury within one class at least 90%

of the

time.

 We expect that field audit crews will get the same results as the field crews at least 90% 

of the time

when selecting the indicator species and quantifying ozone injury. The ozone symptom will be 

validated

for each injured species on each plot with the use of a leaf voucher. There must be no 

differences between

the crew and expert identification of the ozone symptom.

Table 6-1. Measurement Quality Objectives

Plot Level Variables

Bioindicator species

For each species:

No, stems evaluated

No. stems inj/No. stems eval

Amount of injury

Severity of injury

Symptom verification (TS)*

Symptom verification (FS)

Reporting Units

species code

number

ratio

5 classes

5 classes

yes or no

yes or no

Data Quality Limits

+•/- 1 species

+/- 10%

+/- 10%

90% @ +/- 1 class

90% @ +/- 1 class

90% agreement

100% agreement

* TS - Training Session; FS » Reid Session

 Results of the field audits and remeasurement activities described in Subsection 6.5.2 will 

be used to

determine if the measurement quality objectives are being met. Regional Leads and 

State

Coordinators/Field Supervisors who are certified for the ozone indicator have the authority to 

implement

whatever corrective action is needed in the field (e.g., retraining and retesting).

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 6 of 21

 6.5.5 Method Performance

 Method performance will be determined through analyses of the quality control data collected 

at the

 training sessions and during the field season.

 In 1992 and 1993, field crews trained and tested at the beginning of the field season 

easily met

 certification standards for species and symptom identification. Field audits conducted within 

two weeks of

 the training session confirmed that all crews were proficient in the field methods for the 

ozone indicator.
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 In 1994, because data collection occurs late in the season, a refresher training course and 

late season

 audit have been added to the quality control procedures. In addition, remeasurement procedures 

(absent

 in 1992 and 1993) have been added.

 Results of the audit and remeasurement procedures will be used to assess the ability of the 

field crews

 to meet measurement quality objectives with respect to identification of bioindicator species, 

number of

 stems evaluated, number of stems injured, amount of injury, and severity of injury. Voucher 

leaf samples

 will also be used to assess measurement quality for identification of the ozone injury 

symptom. If the

 measurement quality objectives (discussed in detail in the 1994 Quality Assurance Project Plan)

are not

 met, the data will not be used.

 6.5.6 Communications

 Any questions arising during the field season that cannot be answered by the Field 

Supervisor or State

 Coordinator, should be directed to the Regional Lead for the ozone indicator. If any field crew

orcooperator

 is uncertain about who to call for information, they should contact the National Lead at the 

number listed

 below. All data sheets and voucher specimens are mailed to the National Lead.

 National Lead and Regional Lead for the Northeast and Mid-Atlantic:

 Gretchen Smith Phone:(413)545-1680

 Holdsworth Hall

 University of Massachusetts

 Department of Forestry and Wildlife Management

 Amherst, MA 01003-0130

Regional Lead for the Southeast and South:

 Beth Brantley Phone: (704) 257-4857

 USDA Forest Service - FPM

 200 Weaver Blvd.

 Ashville, NC 28804

Regional Lead for the Lake States:

 Ed Hayes Phone: (507) 285-7428

 Minnesota Department of Natural Resources

 2300 Silver Creek Rd. NE

 Rochester, MN 55906

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6.6 Procedure

 NOTE: In the following discussion, use of the word "plot" refers to the permanent FHM 

detection

monitoring plot. Use of the word "site" refers to the open area used for the ozone indicator 

evaluations.

 The procedures for documenting the occurrence of ozone air pollution injury on sensitive 

bioindicator

species include the selection of a suitable site for symptom evaluation, identification of 1-3 

known ozonesensitive species at the site, and evaluation of injury amount and severity on the foliage of 

10-30 plants

of each of three species. If three species cannot be found at a site, a lesser number of 

species is still

evaluated. If 30 plants of each species cannot be found at the site, a lesser number (between 

10 and 30)

can be evaluated. Each individual plant with ozone injury is scored for amount and severity of 

injury. If a

plant does not have ozone injury, it is still tallied with zeros for these measurements. A data 

sheet and

map, identifying key characteristics of the bioindicator site, is prepared for each plot. If a 

plot has no

bioindicator site, this information is recorded on the PDR.
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 All foliar evaluations are conducted during a two-to-three week window towards the end of 

the field

season. This is necessary to eliminate differences between plots that are caused by timing. 

During the

evaluation window, a minimum of seven plots per crew are evaluated for ozone injury. If 

crews have

completed the detection monitoring plots prior to the opening of the window, they must return 

to a minimum

of seven plots for the specific purpose of completing the bioindicator measurements.

 In the following discussion, it should be noted that site selection procedures depend on 

whether crews

are establishing new plots (Mt1) or revisiting established plots (Mt2 and Mt3). However, 

procedures for

species and plant selection, symptom identification and scoring, and collection of leaf 

samples for

remeasurement are the same for all crews, regardless of measurement type.

6.6.1 Evaluation Window

 Quantifying ozone injury on the FHM detection plots is limited to a two-to-three week period

in late-July

to mid-August. The evaluation window for crews in the Northern Region (NO) begins 8 August and 

extends

through 19 August. In the Southeastern (SE) and Southern (SO) Regions, the window is open from 

25 July

through 12 August. A PDR edit check will prompt the field crews at the start and end of the 

evaluation

period.

 States in the NO, SE, and SO that are new to this indicator collect the ozone injury data on

whatever

plots they visit during the prescribed evaluation period. States in the NO, that have 

established bioindicator

sites, are provided with a list of preferred plots to visit during the evaluation window. 

Specific procedures

are outlined in the following section.

6.6.2 Site Selection

 States in the Northern (NO), Southeastern (SE), and Southern (SO) Regions, that are new to 

this

indicator, complete the site selection procedures described below at each detection plot visited

by the crews

during the field season. However, the subsequent procedures for species and plant selection, and

symptom

quantification are completed only if the evaluation window is open at the time of the plot 

visit. States in the

NO with established sites may choose to select and map new sites as needed throughout the field 

season,

but the focus of the field activities should be on symptom quantification during the two-week 

evaluation

period.

 Crews are given maximum flexibility to select the bioindicator evaluation site that, in 

their judgement,

provides the best opportunity for quality data collection. A crew locates and maps the 

largest, most easily

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 8 of 21

 accessible opening that is within three miles and +/- 300 feet (91 m) elevation of the 

detection monitoring

 plot. The crew is not expected to measure distance or elevation, but to use the numbers given 

as general

 guidelines in the site selection process. There are no minimum plot size or distance 

requirements, but a

 site must contain at least ten individuals of at least one bioindicator species to be evaluated

for ozone

 injury.

 The site is described as an open area because this is the usual case, but there may be some

instances

 where the appropriate number of bioindicator plants are found under the canopy. The best site 

may be

 found along the vehicle access route to the plot or within walking distance of the course-toplot (or whatever

 alternate course may have been established to access the FHM plot). No more than 30 minutes 
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should be

 spent locating the bioindicator evaluation site.

 Once an evaluation site has been located, a permanent map is made by the crew which will 

be used

 by audit and regular crews in subsequent visits to the plot (see Figure 6-1). This map is 

attached to the

 original plot data sheet with the sketch map of plot location, so that it is readily available

to whoever needs

 it.

 NOTE: Examples of suitable openings include old logging sites and abandoned pasture or 

farmland

 where you are reasonably certain that soil/site conditions are stable and free of chemical 

contaminants.

 Avoid open areas where plants are obviously stressed by some other factor that could mimic the

ozone

 response. Do not select a site under a high-tension power line or on or near an active or 

reclaimed landfill.

 6.6.2.1 New Plots (Mt1)

 Site selection procedures begin wfth an in-office review of the plot photos or, in the 

field, if no suitable

 opening is visible on the plot photos. Candidate sites must be easily accessible open areas 

that are within

 three miles or +/- 300 feet (91 m) elevation of the detection plot and more than 100 feet (30 

m) from a busy

 (paved) road. There are no additional site selection criteria other than the requirement that 

there be at least

 ten individuals of at least one bioindicator species on site.

 Ideally, candidate sites are visited prior to the beginning of the field season by a 

reconnaissance team.

 If this is not possible, site selection occurs at the time of plot establishment. A plot 

without a suitable site

 (no opening or less than the minimum number of plants or species) is not evaluated for this 

indicator.

 The characteristics of a preferred evaluation site are as follows: (1) opening >0.5 acre, 

(2) soil/site

 conditions with low drought potential and adequate fertility, (3) more than ten individuals of 

more than one

 species, and (4) easy access from car or course-to-plot. These are not meant to be used as site

selection

 criteria but to assist the crew in selecting the best site when more than one option is 

available to them.

 When site selection occurs at the time of plot establishment, the following procedures are 

followed:

 Crews screen candidate sites along the vehicle access route and course-to-plot, keeping in 

mind the

characteristics of a preferred site as described above. Final site selection and mapping occurs

as the last

plot activity on the way back to the vehicle. This allows the crew to select the best site for 

evaluation after

viewing all the possibilities.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 9 of 21

 Pa-lunbo

 • woodsJKoad

 From SS go 7.5'± to

 clump of milkwead.

 Ihara ara scattered black

 cherry along- tha easterly

 a Ida of tha open fiald.

 Refer to the plot data sheet for

 hex code number 4407255 for directions

 to tha starting point.

Figure 6-1. Example of a well drawn map locating the bioindicator site for a permanent detection

monitoring plot.

 The best site is the largest, easily accessible opening, with the most ozone indicator 

species. However,

size should not be a determining factor unless the candidate sites are all less than 0.5 acre. 

If two sites

are >0 5 acre, select the site with the most plants or species. If two sites are similar in size

and number
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of plants and species, select the site which appears to have the most favorable soil/site 

conditions (e.g.,

low drought potential and adequate fertility). These statements are provided as guidelines, not 

as rules that

must be followed in the site selection process. The intention is to provide the field crews 

with maximum

flexibility to select the bioindicator site that provides the best opportunity to collect 

quality data.

 Once a bioindicator site is selected, the field crew records the estimated size (half-acre 

increments)

of the site opening and other key site characteristics identified on the PDR or data sheet. On a

separate

data sheet, the crew maps the location of the site relative to the detection plot or some other

obvious and

permanent marker. Directions to the site, including road names and distances, are included as 

needed. The

map will be used by audit and regular crews in subsequent visits to the site.

6.6.2.2 Established Plots (Mt2 and Mt3)

 States in the NO, SE, and SO Regions, that are new to this indicator, should follow 

procedures outlined

in the previous section for new plots (Mt1). Procedures for crews in the NO, that have 

established

bioindfcator sites, are as follows: Each crew is provided with a preferred list of plots to 

visit during the twoweek evaluation window. Preferred plots are those that provide the best opportunity to detect 

injury if

phytotoxic ozone concentrations are present on the plot. Once the evaluation window opens, crews

complete the bioindicator measurements on as many of the preferred plots as possible. If there 

are no

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 preferred plots in their area, or if they are logistically unable to visit them, bioindicator 

measurements are

 made on whatever plots they visit during the evaluation window.

 If crews have completed the FHM detection plots prior to the opening of the window, they 

must return

 to a minimum of seven plots (preferred or otherwise) for the specific purpose of completing the

bioindicator

 measurements. The seven plot minimum is a recommended goal. Logistics or an absence of 

suitable

 evaluation sites may make it impossible for some crews to meet this goal. For example, it is 

understood

 that most of the plots in Northern Maine can not be evaluated for this indicator due to the 

complete

 absence of bioindicator species in the area.

 6.6.3 Species Selection

 At the selected bioindicator site, the crew evaluates between 10 and 30 individuals of up 

to three

 bioindicator species. If three species can not be found at the site, then a lessor number of 

species is still

 evaluated. A prioritized list of species is provided to the field crews for each region. The 

top three species

 in each list are the first priority for choice of species.

 Field crews record the species code number for each selected species in the PDR or on the 

data

 sheet. The target species and codes for each region are:

 Northern Region (NE. mAtl. and LS sub-regions)

Code Definition

915 Blackberry

762 Black Cherry

365 Common Milkweed

621 Yellow Poplar

541 White Ash

364 Big Leaf Aster

366 Dogbane

Scientific Names

Rubus allegheniensis
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Prunus serotina

Asclepias syrica

Liriodendron tulipifera

Fraxinus americana

Aster macrophylum

Apocynaceae androsaemifolium

Southeastern and Southern Regions

Code Definition

915 Blackberry

762 Black Cherry

365 Common Milkweed

621 Yellow Poplar

541 White Ash

6.6.4 Plant Selection

Scientific Names

Rubus allegheniensis

Prunus serotina

Asclepias syrica

Liriodendron tulipifera

Fraxinus americana

 After site and species selection, the next task is to contiguously sample 10-30 individual 

plants of each

species. The following procedures help the crews to collect the bioindicator data in as 

systematic a way

as possible.

 1. Identify a starting point at the edge of the opening. This point should be mapped on the

plot data

 sheet so that audit and regular crews evaluate roughly the same population of plants in 

subsequent

 visits to the plot.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 11 of 21

 2. Move away from the starting point, towards the center of the opening.

 3. Begin locating individuals in a sweeping pattern, selecting plants that are growing 

under the same

 or similar growing (microhabitat) conditions. Do not skip plants with little or no injury.

 4. Select the more exposed plants (high sunlight exposure) and avoid suppressed and 

shaded

 individuals. Plants along the edge of an opening may be used if, in your judgement, they

receive

 direct sunlight for three to four hours each day.

 5. Evaluate the foliage that you can see and touch on 30 plants of each species in the 

opening (a

 minimum of 10 plants must be found for a species to be evaluated).

 6. Record both the amount and severity of injury for each plant evaluated (with or without

symptoms)

 on the PDR or data sheet.

 NOTE: Milkweed and blackberry spread vegetatively. This means that neighboring plants are 

often

genetically identical. To avoid repeat sampling of clonal material take several steps between 

each plant

selected for evaluation. With blackberry, it is often difficult to distinguish individual plants 

or stems. In this

case, use an approximate 2-foot square area to represent a single plant.

 On average, it should take no more than 45-60 minutes to locate and evaluate the 

bioindicator plants

at each plot.

6.6.5 Symptom Identification and Scoring

 &

 Symptoms of air pollution injury are taught intensively in training, with emphasis on 

appearance,

patterns, and discrimination from any mimicking symptoms. The bioindicator species selected for 

each

region are those that have been determined through field and laboratory studies to be highly 

sensitive to

ozone air pollution. However, within a species, differences in genetics between individuals 
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result in

differential sensitivities to ozone. This means that you often find an individual of a species 

with severe air

pollution injury growing immediately adjacent to another individual of the same species with 

few or no

symptoms.

 In addition to genetics, the age of the leaves (position on the stem, branch, or rosette) 

affects a plant's

susceptibility to ozone air pollution. In general, leaves at 75% full expansion are the most 

sensitive and tend

to show symptoms most definitively toward the center of the leaf. Older leaves show symptoms 

more

widespread over the leaf surface, while younger leaves show symptoms more commonly near the leaf

tip.

If leaves on one branch are affected, then leaves at a similar leaf position on another branch

should be

affected, especially for branches on the same side of the plant under similar environmental 

conditions (sun

or shade leaves).

 When scoring foliar symptoms on bioindicator plants check for the following characteristics 

of ozone

injury:

 - Symptoms are more severe on mid-aged and older leaves. New leaves will have no or very 

little

 injury.

 Symptoms are most likely confined to the upper leaf surface.

 - Check leaves covering each other. Overlapped leaves will have no injury on the bottom 

leaf.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 12 of 21

 There will be some uniformity to size and shape of the lesions on a leaf.

 Almost all exposed branches on a plant will be affected to some degree.

 Symptoms are more often visible as tiny purple-red to black spots (stippling) and less 

often as

 small white to tan flecks.

 Later in the growing season, stippling may be associated with leaf yellowing or 

premature

 senescence. Check the ground for fallen leaves.

 Each plant with ozone injury is evaluated for the percent of the plant that is injured and 

the average

severity of injury. This information will be used to calculate an injury index value for each 

plant and a mean

value for each species at each plot location. For each plant located, the percentage of injured 

area and

the severity of injury are both rated on a scale of 0 to 5 (see below).

 Percentage of injured area is determined by estimating the proportion of live crown or leaf 

area injured

relative to the total leaf area. Severity of injury is determined by estimating the mean 

severity of symptoms

on injured foliage. If a plant does not have injury, it is still tallied with zeros for these 

measurements.

Percent Scale:

0= no injury

1= 1 to 6% [of the live crown, or leaf area, (for percent estimate) or injured leaf (for 

severity estimate)

 with ozone symptoms]

2= 7 to 25% [..with ozone symptoms]

3= 26 to 50% [..with ozone symptoms]

4= 51 to 75% [..with ozone symptoms]

5= > 75% [of the live crown, or leaf area, (for percent estimate) or injured leaf (for 

severity estimate)

 with ozone symptoms]

Proceed as follows:
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 1. Record the injury amount and the injury severity ratings for each plant on the PDR or 

data sheet.

 2. Use the notes section on the PDR or data sheet to briefly describe what you saw and 

recorded as

 ozone injury for each species. Use the terminology discussed in training whenever 

possible (e.g.,

 stipple, mottle, fleck, chlorosis, etc.).

 3. Collect a voucher leaf sample (one for each species evaluated at each location) and 

mail them to

 the National Lead using the guidelines presented in Subsection 6.6.6.

 NOTE: Do not take measurements in steady rain. Foliar symptoms are easiest to see under 

overcast

skies. Bright sun will make it difficult to see the ozone stipple. Stand so that you reduce the

glare on the

leaf surface. Long periods without rain will inhibit symptom development even on the most 

sensitive plants.

If you are experiencing below average rainfall for your area, please note this in the PDR or on 

the data

sheet.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 13 of 21

6.6.5 Collection of Leaf Samples

 The voucher leaf samples are a critical aspect of the data collection procedures as they 

provide the

necessary validation of the ozone injury symptom observed in the field by the field crews. 

During the

evaluation window, a voucher leaf sample must be collected for each injured species evaluated on

the

bioindicator site. For example, if a field crew records ozone injury on blackberry, black 

cherry, and milkweed

then a minimum of one leaf voucher from each of the three species is collected and mailed to the

National

Indicator Lead.

 Field Collection: The voucher consists of three leaves that clearly show the ozone injury 

symptom.

Ideally, these are three leaves with high amounts of foliar injury symptoms. If this is not 

possible, send

whatever leaf sample is available even if it's only one leaf with faint symptoms. Cut the leaf 

at the petiole

with hand clippers or a sharp knife.

 If the leaves are wet when you cut them, shake off any excess moisture and pat dry. The 

samples do

not have to be completely dry at this point. Place the samples into the plant press you were 

provided at

training. Each leaf is placed in the press so that it does not overlap another leaf. Include a 

small label with

each leaf sample you place into the plant press that identifies which plot the sample came from 

and the

date. Small labels are provided for this purpose. Record the information on the labels with 

indelible ink and

then wrap them around the petiole of one leaf per sample so that the back sides stick together 

and will not

slip off the leaf. If you forget to take the plant press with you into the field, then place 

the leaves and

accompanying label between pages of a notebook, or otherwise keep as flat as possible.

 NOTE: Blackberry leaves consist of 3-7, mostly 5 leaflets. Select the whole leaf when 

preparing a

voucher sample. Injury will tend to be more pronounced on second year canes bearing fruit and 

flowers.

 Mailing Procedure: Vouchers may be mailed in bulk at the end of the evaluation window, or 

earlier,

depending on your work schedule. It is very important to mail only dry, pressed leaf samples. 

Before

mailing, make sure you have filled out the upper half of the voucher data sheet. This sheet is 

filled out on

the same day the sample is collected even if the sample is not mailed on that day. Although it

is not a

requirement, please take the time to include a brief description of your findings on the voucher

data sheet.
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This could include observations on the weather, on injury amount and severity, or on general 

plot

conditions. Examples: "It's been 14 days now without rain," "Every plant showed the same 

response and

it was very obvious," or "This was a highly disturbed site." Include anything that you think 

might help in

the interpretation of the results.

 The lower half of the voucher data sheet is filled out by the National Lead to whom you are 

sending

the sample. Place the voucher data sheet and the leaf sample into a mailing envelope addressed 

to the

National Indicator Lead. Include as many samples as fit easily into each mailing envelope. Mail 

the voucher

first class.

 The National Lead returns a copy of the voucher data sheet to you by return mail to let 

you know

whether or not you correctly diagnosed the ozone symptom. The copy of the voucher sheet that is 

returned

to you will include an explanation of why your diagnosis was correct or incorrect. This is for 

your information

only. You do not need to save the sheet unless you feel it could be helpful for future 

reference. Don't

hesitate to call your Regional Indicator Lead anytime you have a question on procedures or 

diagnosis.

 NOTE: Field crews are encouraged to mail leaf samples for symptom verification at any time 

during

the field season even though the requirement to do so is in effect only during the evaluation 

window. Keep

in mind that the more voucher samples you send in for verification, the greater confidence we 

can have

in the plot findings for this indicator.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 14 of 21

6.6.7 Crew Member Responsibilities

 1. Two crew members are trained for this indicator and are responsible for site 

selection, plant

 selection, and ozone injury evaluations.

 2. The two trained crew members should assist each other in the site selection process. 

Once a site

 is selected, one crew member should be responsible for mapping the site on the data 

sheet, while

 the other crew member begins to search for plants for each bioindicator species.

 3. One crew member should be responsible for evaluating the plants while the other crew 

member

 records the injury scores on the PDR or data sheet. The other crew member should counsel

the

 evaluating crew member when there is doubt concerning the nature or severity of injury.

 4. The crew member who evaluates the plants for injury should be responsible for 

collecting and

 mailing the voucher sample with air pollution symptoms.

6.6.8 Reference Plot Methods

 In addition to the regular FHM detection plots that are evaluated by the field crews for 

this indicator,

a subset of reference plots is established in each region to represent the local plant 

populations and

environmental conditions. This is not an auxiliary effort, but an integral part of the 

detection-level activities

for this indicator.

 Reference plots possess attributes of an ideal site for evaluating ozone injury on sensitive

species.

They are larger than three acres, contain the maximum number of indicator species, and have 

soil/site

conditions with low drought potential and adequate fertility. These plots are evaluated for 

ozone injury using

the same methods as on the detection plots, and during the same timeframe (i.e., from 8 

August to 19

August in the North and from 25 July to 12 August in the South and Southeast).
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 In New England and the Mid-Atlantic states, the reference plot system is already in place 

and personnel

are available to conduct the field evaluations. In the South and the Lake states, additional 

cooperators will

be identified for this task. All reference plot personnel are trained and tested along with the 

regular field

crews.

 NOTE: In most states, the regular detection plot crews are not involved in the reference 

plot activities.

The site selection criteria for the reference plots are as follows:

 - > 3 acres.

 - contain the maximum number of indicator species

 - have soil/site conditions that favor injury.

 - have southwest aspects or be relatively flat (Eastern region).

 - have low drought potential.

 NOTE: The reference plot may be the same as one of the detection plot suitable sites (i.e., 

on-frame),

as long as the site selection criteria for reference plots are met.

Once a reference plot is selected, proceed as follows:

 1. Record the estimated size of the opening (half-acre increments) and other key site 

characteristics

 identified on the PDR or data sheet.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 15 of 21

 2. On a separate data sheet, map the location of the site relative to some obvious and 

permanent

 marker. Directions to the plot, including road names and distances, are included using 

standard

 FHM procedures.

 3. Once the reference plot has been appropriately mapped for easy relocation, begin the 

species and

 plant selection procedures. These procedures are identical to those presented in 

Subsections 6.6.3

 and 6.6.4 and are not repeated here.

 NOTE: Ideally, a reference plot has close to 30 individual plants of at least three 

bioindicator

 species. If not, a lessor number of plants and species may be evaluated.

 4. Adhere to the guidelines presented in Subsection 6.6.5 for symptom identification and 

scoring.

 5. Voucher leaf samples must be collected, according to guidelines presented in Subsection 

6.6.6,

 and mailed to the National Indicator Lead.

 The reference plot system improves the regional assessment of this indicator. It is expected

to minimize

uncertainty factors (e.g., the variable soil/site conditions encountered on the FHM detection 

plots) and

ensure the regional responsiveness of the bioindicator data.

6.6.9 Data Sheets - Detection Plot and Reference Plot Procedures

 (see Appendix 6.A)

 1. Ozone Bioindicator Plants -1994 Data Sheet for Site Characteristics and Symptom 

Quantification.

 2, Ozone Bioindicator Plants -1994 Data Sheet for Mapping the Bioindicator Site Location. 

(All data

 codes on back side.)

 3. Ozone Bioindicator Plants -1994 Data Sheet for the Voucher Leaf Sample.

 Field crews and cooperators, in all regions, return data sheet #1 and #3 to Gretchen Smith 

at the end

of the field season, or earlier, as the work schedule permits. The original of data sheet #2 

remains with the
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permanent plot file. A copy of data sheet #2 should be mailed to Gretchen Smith at the end of 

the field

season. Refer to Subsection 6.5.6 for Gretchen Smith's mailing address.

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6.7

 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 16 of 21

References

Cleveland, W.S. and T.E. Graedel. 1979. Photochemical air pollution in the Northeast United 

States.

 Science 204: 1273-1278.

Davis, D.D., and D.M. Umbach.1981. Susceptibility of tree and shrub species and response of 

black

 cherry foliage to ozone. Plant Disease 65:904-907.

Duchelle, S.F.and J.M. Skelly. 1981. Response of common milkweed to oxidant pollution in the

 Shenandoah National Park in Virginia. Plant Disease 65: 661-663.

Horsefall, J.G. and E.B. Cowling.1978. Pathometry: the measurement of plant disease, pp. 119-

136. In:

 J.G. Horsefall and E.B. Cowling (eds.), Plant Disease, an Advanced Treatise, Vol II. Academic

 Press, New York, 436 pp.

Krupa, S.V., and WJ. Manning. 1988. "Atmospheric ozone: formation and effects on vegetation,"

 Environ. Pollut. 50:101-137.

Lefohn, A.S. and J.E. Pinkerton. 1988. High resolution characterization of ozone data for sites 

located

 in forested areas of the United States. JAPCA 38(12) :1504-1511.

Manning, W.J., and W.A. Feder. 1980. Biomonitoring Air Pollutants with Plants, Applied Science 

Publ.

 Ltd., London, 142pp.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 17 of 21

 Appendix 6.A OZONE BIOINDICATOR PLANTS -1994

 Site Characteristics

ST

CTY

HEXAGON

MO

DAY

TALLY 1

TALLY 2

 ' Please put a checkmark beside the correct information.

Ptot size:

 > 3.0 acres

 0.5 to 3.0 acres

 < 0.5 acres

Approximate elevation (feet):

Slope (Aspect):

 flat

 10-45%

 >45%

Soil depth:

 bedrock not exposed

 bedrock exposed

 Terrain position:

 lowland

 hillside

 ridgetop

 Soil drainage:

 well-drained
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 wet

 very dry

 Disturbance:

 no disturbance

 evidence of overuse

 other

Comments:

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 18 of 21

 OZONE BIOINDICATOR PLANTS - 1994

 Foliar Injury Data

Record species code number from the list below (choose up to 3):

915 Blackberry 762 Black cherry 365 Common milkweed 621 Yellow poplar

541 White ash 364 Big leaf aster 366 Dogbane

Use the codes below (percent injury scale, 0-5) to:

0 = No injury; 1 = 1-6%; 2 = 7-25%; 3 = 26-50%; 4 = 51-75%; 5 = >75%

Record the percent of the leaf area injured relative to the total leaf area (amt).

Record the average severity of symptoms on the injured leaves (sev).

 SPECIES CODE

Plot Type

 _ Detection Mon.

 _ Reference

 Remeas.

Plant

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

'17

18

19

20

21

22

23

24

25

26

27

28

29

30

amt
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sev

 amt

 sev

 amt

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 19 of 21

 OZONE BIOINDICATOR PLANTS 1994

ST

CTY

HEXAGON

MO

DAY

TALLY 1

TALLY 2

 Map of the Bioindicator Site Location

Please include the following information on the map:

Location of site relative to detection plot; road names and distance as needed; North arrow.

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 20 of 21

 OZONE BIOINDICATOR PLANTS - 1994

 General Information

Preferred site characteristics:

* largest, most easily accessible opening

* within 3 miles & +/- 300 feet in elevation of

 FHM detection monitoring plot
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* good soil conditions

* at least 10 individuals of one bioindicator

 species present

« free from chemical contaminants

Sampling the bioindicator site:

* identify starting point (put on map)

* move towards center of opening

* locate plants in a sweeping pattern

* do not skip plants with little or no injury

 * avoid suppressed or shaded plants

 * evaluate foliage on each plant for amount

 and severity of injury

 Ozone injury characteristics:

 * usually present on mid-aged and older

 leaves

 * on the upper leaf surfaces

 * overlapped leaves will have no injury on the

 bottom leaf

 * spots are uniform in size and shape', most

 often tiny purple-red to black spots

 * almost all leaves exposed to sunlight will

 have injury

Amount = Percent of leaf area injured relative to the total leaf area.

Severity = Average severity of symptoms on the injured leaves.

 Rating scale for amount and severity of ozone injury:

 0 = 0% 3 = 26-50%

 1 = 1-6% 4 = 51-75%

 2 = 7-25% 5 = >75% 

Leaf images are upper bounds of each rating class for the severity estimates:

 0%

 6%

25%

50%

 75%

 100 %

 1 = 1-6% 2 = 7-25 % 3 = 26-50 % 4 = 51-75 %

 5 = >75 %

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 EMAP Forest Monitoring, Section 6, Rev. No. 0, October, 1994, Page 21 of 21

 OZONE BIOINDICATOR PLANTS - 1994

 Voucher Leaf Samples

FIELD CREW

ST

CTY

HEXAGON

MO

DAY

TALLY 1

TALLY 2

Name, address, and phone number where you can be contacted:

Bloindicator species:.

Notes: 

Mail this sheet with the leaf sample to:

QA/QC PERSON

 GRETCHEN SMITH

 Dept. of Forestry, Holdsworth Hall

 University of Massachusetts

 Amherst, MA 01003

 Positive for ozone symptom

 Negative for ozone symptom

Explanation:

Date received:.

Notes:

Sample condition:

Questions? Call your regional bioindicator lead:
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Northeast and Mid-Atlantic: Gretchen Smith (413) 545-1680

South and Southeast: Beth Brantley (704) 257-4857

Lake States: Ed Hayes (507) 285-7428

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 1 of 11

 Section 7. Lichen Communities

Section/Title

7.1 Overview 2 of 11

 7.1.1 Scope and Application 2 of 11

 7.1.2 Summary of Method 2 of 11

 7.1.3 Interferences 3 of 11

 7.1.4 Safety 3 of 11

7.2 Sample Collection, Preservation, and Storage 3 of 11

 7.2.1 Sample Procurement 3 of 11

 7.2.2 Sample Mailing 4 of 11

7.3 Equipment and Supplies 6 of 11

 7.3.1 Equipment and Apparatus 6 of 11

 7.3.2 Consumable Supplies 6 of 11

7.4 Calibration and Standardization 6 of 11

7.5 Quality Assurance 6 of 11

 7.5.1 Measurement Quality Objectives 6 of 11

 7.5.2 Certification 7 of 11

 7.5.3 Audits 7 of 11

 7.5.4 Remeasurements 8 of 11

 7.5.5 Debriefing 8 of 11

 7.5.6 Method Performance 9 of 11

7.6 Procedure 9 of 11

7.7 References 11 of 11

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 2 of 11

7.1 Overview

7.1.1 Scope and Application

 The purpose of the lichen community indicator is to use lichen species and communities as 

biomonitors

of change in air quality, climate change, and/or change in the structure of the forest community. Lichen

communities are excellent indicators of air quality, particularly long-term averages of 

sulfur dioxide

concentrations (Hawksworth and Rose, 1976; Smith et al., 1993; van Dobben, 1993).

 Lichen communities provide information relevant to several key assessment questions, 

including those

concerning the contamination of natural resources, biodiversity, and sustainability of timber 

production

(Figure 7-1). Lichens not only indicate the health of our forests, but there is a clearly 

established linkage

to environmental stressors, as described below.

 LICHEN

 COMMUNITY

 INDICATES

CONDITION OF

RESOURCE

Forest productivity,

biodiversity

 ENVIRONMENTAL

 STRESSORS

 N- and S-bascd air

 pollutants: direct loxicity

 and acidifying and

 fcrliliang effects.

Figure 7-1. Conceptual model of the lichen community indicator.

7.1.2 Summary of Method

 The objectives of this task are to determine the presence and abundance of macrolichen 

species on

woody plants in each plot (using the 120-foot radius core of the plot) and to collect samples to

be mailed
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to lichen experts.

 The method has two parts which are performed at the same time:

 1. Make a collection of voucher specimens for identification by a specialist, the 

collection

 representing the species diversity of macrolichens on the plot as fully as 

possible. The

 population being sampled consists of all macrolichens occurring on woody plants, 

excluding the

 0.5 m basal portions of trees and shrubs. Include fallen branches in your sampling.

 2. Estimate the abundance of each species. Note that the crew member responsible for 

this task

 is not required to accurately assign species names to the lichens (that is done 

later by a

 specialist) but must be able to make distinctions among species.

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 3 of 11

 7.7.3 Interferences

 This method may be used in any season or weather condition. It should not be used in poor 

light,

 however, because the method requires careful discrimination among species in the field. 

Therefore, it

 should not be performed within an hour of sunset or sunrise, or during dark, rainy 

conditions. Another

 common interference is to have a tough plot with other crew members who are impatient to leave 

the plot.

 Chances are that you will have to wait for them at some point. Remind them of this and proceed 

with your

 task, or, if it is a recurrent problem, discuss it with your crew leader to see if you can 

devise a more

 equable work loads.

 7.1.4 Safety

 Only minor hazards are associated with the method. Care should be used when removing 

lichens

 specimens with a knife or chisel. The knife should have a locking blade or fixed blade. Trees 

should not

 be climbed to procure specimens.

 7.2 Sample Collection, Preservation, and Storage

 7.2.1 Sample Procurement (note: Portable Data Recorder not used)

 1. Optimally collect a palm-size (about 5-10 cm in diameter) sample of fruticose and 

foliose growth

 forms. This includes all species that are three-dimensional or flat and lobed. Even 

minute

 fruticose and lobate forms should be included. Squamulose species and Cladonia 

squamules

 lacking upright stalks should not be included. In many cases a much smaller sample 

should be

 ""obtained because of the scarcity of the species.

 Collecting large samples improves the likelihood that the specialist can properly name your 

collections.

 2. Place each specimen in a separate #2 brown paper bag and label the bag with appropriate 

codes:

 Bag (species) number (sequentially as collected).

 Relative abundance. (Feel free to revise this rating as collection proceeds and you

become

 more familiar with the plot.)

 Often there will be more than one species on a given bark sample. If there is any 

chance of

 ambiguity about which species in the bag corresponds with the abundance rating, 

write a

 descriptive clarifying phrase, such as "the white one" or 'the sorediate one," on 

the bag.

 Label the bag with an indelible marker. If the bags are damp, a soft pencil (No. 2 or 
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softer) will work

better than an alcohol marker.

 3. When finished for the day, or earlier as time allows, label all of the paper bags from 

that day with

 the plot ID code (the hexagon code number for that plot). At this time you should add 

sequential

 bag numbers if you did not do that in the field.

 4. Be sure that the "Plot Packing Slip" (Figure 7-2) is completely filled out.

 5. Place all of the specimen bags from a given plot WITH the Plot Packing Slip into a 

larger brown

 paper bag. Record plot ID code, your name, and date on outside of bag. Fold the top of

the large

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 4 of 11

 bag closed. The redundancy in all of this labelling may seem unnecessary, but it has 

proved quite

 helpful in resolving problems of mislabeled material.

 6. Store bags in a dry place until you mail them. Specimens must be thoroughly air dried 

to avoid

 fungal decay. If specimens were wet when collected, the individual bags should be spread 

out and

 dried inside or in the sun as soon as possible.

7.2.2 Sample Mailing

 After the first two plots are completed, mail the specimens to the lichen specialist right 

away. The

purpose of this is to allow immediate feedback to the field crews concerning specimen quality 

and quantity.

Thereafter, mail the bags each week or every other week to the lichen specialist. You should 

have the

name and address of the lichen specialist. In case of doubt, contact Bruce McCune (503-737-

1741 or

mccuneb@bcc.orst.edu). Bags should be packed closely, but without excessive crushing, in 

sturdy

cardboard boxes. Bags from several plots can be mailed in the same box. Enclose in the box a 

Lichen

Specimen Mailing Form (Figure 7-3) specifying the box's contents. Extra copies of the Mailing 

Form can

be found in the notebook of lichen training materials under "Mailings."

 Lichen Communities

 PLOT PACKING SLIP

 FHM, 1994

 Plot hex number:.

 Date: 

 State:

County:.

Crew Member's Name:

 Crew number:

 A copy of this sheet will be part of the permanent record for this plot. PLEASE COMPLETE

 IT FULLY.

 Record the time lichen sampling began:

 Record the time lichen sampling ended:

 Total time spent sampling the plot:

 Comments about the plot, the lichens, the vegetation, and/or the weather:

 REMEMBER:

 Record the abundance code on each bag!

 Remember to look for the common species.

 Try to put only one species in each bag.

 Figure 7-2. Plot packing slip for lichen communities. Complete this form and insert it into the

bag containing all of the

 smaller bags for a single plot.

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 5 of 11

 LICHEN SPECIMEN MAILING FORM

 Please enclose a copy of this form whenever these specimens are mailed. Keep a copy for 

your

records.
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FIELD CREW TO LICHEN SPECIALIST:

Sent by: 

Sender's comments:

Received: 

Comments:

 Date

 to:

LICHEN SPECIALIST TO STORAGE:

Sent by: 

Sender's comments: 

Received: 

Comments: 

 Date

 to:

CONTENTS

 Hex number

State

County

Notes

Figure 7-3. Form used for mailing lichen community specimens, one form per box.

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 6 of 11

7.3 Equipment and Supplies

7.3.1 Equipment and Apparatus

 Locking-blade or fixed-blade knife (ca. 4" blade) with belt sheath.

 • 14X hand lens (Bausch & Lomb Hastings Triplet).

 • Fanny pack.

 Regional guides for lichen identification. Different guides will be needed for different 

areas:

 Northeast, Lake States, and Southeast:

 Hale, M.E. 1979. How to Know the Lichens. 2nd Ed. Wm. C. Brown, Dubuque, Iowa.

 Colorado, California, and Pacific Northwest:

 Hale, M.E. and M. Cole. 1988. Lichens of California. University of California Press, 

Berkeley. 254

 pp.

 Hand pruners (useful for collecting small branch segments).

 • 1-inch wide chisel (Northeast and Southeast only; useful for collecting samples from 

tough-barked

 hardwoods. You may wish to make a sheath from a piece of cardboard and strapping tape or 

save

 the plastic cap that comes on some chisels).

7.3.2 Consumable Supplies

 • #2 brown paper bags (or next size smaller), averaging 20 per plot.

 • Black waterproof markers for writing plot ID'S and abundance data on paper bags.

 Larger brown paper bags (16.5 x 9.5 inch or similar size), one per plot.

 Soft pencils (No. 2 or softer).

 6 mailing forms (supplied in Lichen Community Training Manual).

7.4 Calibration and Standardization

 Calibration and Standardization is not applicable in this section.

7.5 Quality Assurance

 Data quality will be measured at (1) post-training certification, (2) field audits, and 

(3) plot

remeasurements. Each of these is discussed briefly below, and at length in the QA Project Plan.

(Cline

et at., 1994) See also Subsection 7.5.6, "Method Performance," for QA results from recent 

years.

7.5.7 Measurement Quality Objectives (MQOs)

 Data must be collected within certain standards of quality (Table 7-1). Remeasurements and 

audits

will be conducted during the field season as ways of evaluating data quality. Corrective action 

(retraining

and retesting) will be taken if standards are not met.

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Table 7-1. Measurement Quality Objectives and Their Method of Assessment

 MQO

 Method of Assessment

 Precision

 Bias

 Accuracy

 Completeness

12% Deviation between index scores from repeat measurements of the same plot

12% Signed deviation from "true" index scores, as determined from expert data. In

 practice, obtaining 65% or more of the expert's species will yield index scores that

 meet this MQO

12% Absolute deviation from "true" index scores, as determined from expert data. In

 practice, obtaining 65% or more of the expert's species will yield index scores that

 meet this MQO

90% Percentage of forested plots with lichen data

 Accuracy can be expressed in terms of the percent deviation between index scores of two 

independent

samples of the same lichen plot, one of which is collected by a lichen specialist and is 

considered the true

species composition. "Index scores" in this case tell where a plot falls on a climatic gradient

and on an air

quality gradient. This percent deviation is calculated as:

 100 * (expert's score - trainee's score) / length of the gradient.

 The signed deviation expresses bias. The absolute deviation expresses accuracy. These 

calculations

are possible only for those regions that are in the "application phase" of the lichen community 

indicator,

meaning that a gradient model of lichen communities has already been constructed. As of March 

1994,

this model is available only for the southeastern U.S. We have found, however, that if the 

trainee obtains

65% or better of the specialist's species list, the index scores will mostly fall within 10% of

the expert's.

Therefore, this 65% figure is used as an operational goal for training, certification, and 

audits. It is referred

to below as our "field MQO", and is used as a readily calculated basis for providing rapid 

feedback to the

crew.

 Precision is estimated from remeasurements of the same crew on the same plot. For the 

lichen

community indicator, it is assessed with the percent deviation between index scores, calculated 

as

 100*(trainee's 1st score - trainee's 2nd score)/length of the gradient,

 where index scores are calculated by applying the regional gradient model.

 Another aspect of quality control is making sure that the voucher specimens are 

adequate, not

decomposed, and being received by the lichen specialist. If problems are perceived either by the 

field crew

or the lichen specialist, they should contact each other and/or the indicator lead.

7.5.2 Certification

 Only people who have successfully completed lichen training and certification should collect 

the lichen

community data. You are certified by performing the lichen community method on a test plot and

meeting

the field MQO (65% of the expert's species list). Your trainer completes a form (see QA Plan) 

that records

your score and certification. You will receive supplemental training and retesting if you fail 

the initial test.

7.5.3 Audits

 Audits serve two primary purposes: (1) check in with the field crew to see if they are 

having any
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difficulties with the method, and (2) documenting the data quality. The first objective is 

achieved by talking

with the crew, observing the method in progress, and providing immediate feedback. The second 

objective

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 8 of 11

is met by calculating numerical scores (comparing results to those of the lichen specialist) 

based on the

field crew sampling a plot without interference from the auditor. One or more plots will be 

examined per

audit. The lichen community audit proceeds in four steps. Note that the early steps provide 

immediate

feedback to the crew, but the later steps quantify the data quality with increasing rigor.

 1. The auditor asks the crew member if they have questions concerning the method before 

the

 sampling begins, then discusses those problems with the crew member. (If time allows the 

auditor

 to be present for two plots, the first plot should be done more interactively, with 

the specialist

 helping the crew rather than as a test plot.)

 2. The auditor then allows the crew member to sample on their own but observing at a 

distance the

 manner in which the crew member covers the plot. At the end of the plot, the lichen 

specialist then

 quickly assesses the number and quality of specimens and provides immediate feedback on 

the

 specimens and other aspects of technique (for example, if the person camps out on one 

tree and

 doesn't see a lot of the plot). Normally it is fairly easy for a specialist to judge how 

well someone

 is doing, even before the final scores are in.

 3. The specialist identifies the lichens, then evaluates the number of species obtained by 

the crew

 member as a percentage of the specialist's. These values are reported by the specialist 

to the

 Indicator lead and crew member as soon as possible. In some cases this can be reported 

to the

 crew member in the field, but if time or weather does not allow complete field 

identifications by the

 specialist, those figures may be delayed by a week. In the past we have found that if 

trainees

 obtain 65% or better of the number of species obtained by the specialist, the plot index 

scores

 (item 4 below) will mostly fall within 10% of the specialist's.

 4. After the data are delivered from the specialist to the indicator lead, the species 

scores for both

 the crews and the specialists are entered into data files. The indicator lead then 

calculates plot

 index scores for each QA plot for both the crews and the specialists. This requires 

application of

 the multivariate lichen gradient model for that specific region. Until those models are

built for each

 region, the results cannot be delivered during the field season. The crew's score is 

then expressed

 as a deviation from the expert's. This is the most important numerical descriptor of

the data

 quality, because it takes into account the mix and abundance of species.

7.5.4 Remeasurements

 Plot remeasurements are an important part of ensuring comparability between crews and 

between

years. Each region is handling this QA task in different ways. "Reference crews" resample 

selected plots

done by the regular field crews. Alternatively, "reference plots" are sampled by multiple crews 

and/or by

a single crew on multiple dates. Your crew leader will inform you about the remeasurement method

used

In your area.

7.5.5 Debriefing

 We schedule time at the end of the field season to leam from you. This will happen via a 
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questionnaire

(see QA plan). In some cases a lichen specialist or their representative will solicit feedback 

from you in

person. Your comments during debriefing are collated and summarized by the indicator lead and 

become

part of the basis for improving the method for next year.

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 9 of 11

7.5.6 Method Performance

 The performance of the method is assessed by evaluating measurement quality objectives (MQOs)

for

precision, accuracy, and completeness. Our QA results from the 1993 Southeast and SAMAB

demonstrations are summarized below (Table 7-2). Average accuracy and bias are expressed with 

respect

to index scores on two lichen community gradients. Gradient 1 is a regional climatic gradient. 

Gradient

2 is an air quality gradient. The MQO of 90% completeness was exceeded.

Table 7-2. Summary of 1993 SE and SAMAB Demonstrations Lichen Community Data Quality

 % Deviation from expert

 No. of Gradient 1 Gradient 2

 Species, % of Index Index

 expert

 QA activity Ace. Bias Ace. Bias

Certifications (N=7)

Audits (N=3)

Reference Plots* (N=16)

74%

50%

61%

2.7

10.3

4.4

+2.4

+3.7

+2.4

2.1

6.0

11.1

-2.1

+2.7

-10.5

* excluding two minimal-effort outliers

7.6 Procedure

 1. The area to be sampled (henceforth the "lichen plot") is a circular area with 120-foot 

radius

 centered on the macroplot, excluding the four subplots (see Figure 7-4). The area of the

lichen

 plot is 40715 ft2 = 3782 m2 = 0.378 ha = 0.935 acres.

 (Note: For off-frame applications where subplots have NOT been set up, an equal area is 

sampled by

 using a 34.7 m = 114 ft radius circular plot, sampling the whole area within that radius.)

 2. Record the time sampling begins on the "Plot Packing Slip" (you will be given a supply 

of these

 at the beginning of the field season). Sampling continues for a maximum of two hours or 

until 10

 minutes elapse with no additional species recorded. At least 45 minutes in the East and

30

 minutes in the West must be spent searching the plot, even if very few lichens are 

present.

 3. Take a reconnaissance walk through the lichen plot, locating lichen epiphytes on woody 

plants and

 collecting voucher samples and assigning abundances as you go. The following method 

is

 suggested. Begin at approximately 100 ft due north from plot center, measuring with your

eye to

 the limiting boundary of 120 ft and continue to the right in a sinuous manner until you 

reach the

 perimeter of subplot 3. (The perimeter of the subplot will have been flagged.) The

same

 procedure is followed between subplots 3 & 4 and 4 & 2. The idea behind this approach 
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is that

 you can scan the whole area but intensely scrutinize selected areas to best represent the

diversity

 on the plot (see item 6 for more details). If time allows, make additional circuits of 

the plot,

 searching for substrates or spots that were not visited on the first pass.

 4. Lichen species with the following growth forms will be collected: fruticose and foliose 

(i.e.,

 macrolichens).

 5. Inspect woody plants (trees and shrubs > 0.5 m tall) within the lichen plot for lichen

species.

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 10 of 11

 Subplot

 24.0' radius

Annular plot

59.9' radius .

 Distance between

 points is 120°

 Azimuth 1-2 360°

 Azimuth 1-3 120°

 Azimuth 1-4 240

 Microplot

 6.8' radius

 12'offset

 90° az. from

 subplot center

Figure 7-4. Lichen sampling area. The shaded area is the "lichen plot."

 6. Be careful to inspect the full range of substrates and microhabitats available: shaded 

and exposed,

 conifers and hardwoods, fallen upper branches and lower branches, large shrubs, and 

trees in

 particular topographic positions (for example, you would check in a draw or ravine on an 

otherwise

 uniform slope, so long as it occurs within the lichen plot). Rotten logs or other semipermanent

 features of the forest floor should NOT be sampled. Also, stumps should not be sampled.

 7. Abundance ratings. Record relative abundance within the lichen plot. Relative abundance

for each

 species is estimated as follows:

 Code Abundance

 1 Rare (< 3 individuals in area)

 2 Uncommon (4-10 individuals in area)

 3 Common (> 10 individuals in area but less than half of the boles and branches 

have that

 species present)

 4 Abundant (more than half of boles and branches have the subject species present)

 8. Collect a sample of each putative species, place it in a small paper bag, label the 

bag with a hex

 number (you can do this at the end of the day), bag number (sequentially as collected), 

and record

 relative abundance. Feel free to revise the abundance rating as collection proceeds. 

Also record

 any comments on the outside of the bag. For more details, see "Sample Procurement" 

above.

 After completing the task, check each bag to be sure that each bag has a hex ID code 

number and

 abundance code.

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 EMAP Forest Monitoring, Section 7, Rev. No. 0, October, 1994, Page 11 of 11

 9. How to handle uncertainties: The field crew will frequently have uncertainties 

about the

 classification of an organism. The following rules for the field crew are designed to 

put the onus

 of the responsibility for classification on the specialist, not the field crew.

 a. When in doubt, assume it is a lichen.
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 b. When the growth form is in doubt, assume it is a macrolichen.

 c. When species distinctions are in doubt, assume that two different forms are different

species.

 The purpose of these rules is to encourage the field crew to make as many distinctions in 

the field as

possible. The specialist can later adjust the data by excluding specimens that are not 

macrolichens and

by combining forms that were considered separately by the field crew but are actually the same 

species.

For more information, see the material distributed at your training session.

 10. Wrap-up. Complete the "Plot Packing Slip." Record the time lichen sampling ended and any

other

 comments about the plot, the lichens, the vegetation, weather conditions, your mood, 

etc. This

 is important information for future evaluations of the relationship between effort and 

data quality.

 There may also be extenuating factors that allowed you to do an especially good job on 

this plot

 (a recent storm blew down lots of fresh branches) or an especially bad job (it was dark).

7.7 References

Brodo, I. M. 1991. Lichens of the Ottawa Region. National Museums of Canada.

Dey, J. P. 1978. Fruticose and foliose lichens of the high-mountain areas of the southern

 Appalachians. Bryologist 81:1 -93.

Hale, M.E. 1979. How to Know the Lichens. 2nd Ed. Wm. C. Brown, Dubuque, Iowa.

Hale, M.E. and M. Cole. 1988. Lichens of California. University of California Press, Berkeley. 

254 pp.

McCune, B. 1988. Lichen communities along O3 and SO2 gradients in Indianapolis. Bryologist 

91:

 223-228.

McCune, B. 1992. Field Key to the Lichens of the Northwest Forests West of the Cascade Crest. 

Dept.

 Botany and Plant Pathology, Oregon State University, Corvallis. 19 pp.

McCune, B. and J. Peck. 1994. Lichen Communities Training Document. Oregon State University,

 Department of Botany and Plant Pathology, Corvallis, Oregon.

Smith, C., L. Geiser, L. Gough, B. McCune, B. Ryan, and R. Showman. 1993. Species and

 communities. Chapter 4 In Lichen as Bioindicators of Air Quality. USDA Forest Service Gen. 

Tech.

 Rep. RM-224.

van Dobben, H. 1993. Vegetation as a monitor for deposition of nitrogen and acidity. PhD

 Dissertation, Utrecht University, Netherlands. 214 pp. (privately published)

Vitt, D.H., J.E. Marsh, and R.B. Bovey. 1988. Mosses Lichens and Ferns of Northwest North 

America.

 Lonepine Publishing. 296 pp.

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 Section 8. Field Logistics

Section/Title

 Page

8.1 Overview 2 of 12

8.2 Training : 2 of12

8.3 Field Logistics 3 of 12

 8.3.1 Sampling Responsibilities 3 of 12

 8.3.2 Work Flow 4 of 12

 8.3.3 Crew Responsibilities and Activities 6 of 12

 8.3.3.1 Sampling Schedule 6 of 12

 8.3.3.2 Assembly of Field Crew 6 of 12

 8.3.3.3 Transportation 7 of 12

 8.3.3.4 Sampling Site Location 7 of 12

 8.3.3.5 Plot Establishment 7 of 12

 8.3.3.6 Ensuring Adherence to Sampling Protocol 7 of 12

 8.3.3.7 Ensuring Proper Use of Field Equipment 7 of 12

 8.3.3.8 Equipment Maintenance 8 of 12

 8.3.3.9 Maintaining Site Integrity 8 of 12

 8.3.3.10 Daily Communication 8 of 12
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8.4 Data Transfer and Sample Handling 9 of 12

 8.4.1 Data Transfer 9 of 12

 8.4.2 Sample and Voucher Specimens Handling 9 of 12

 8.4.3 Sample Maintenance Until Shipping 9 of 12

 8.4.4 Sample Transfer and Tracking 10 of 12

 8.4.5 Sample Shipping 10 of 12

 8.4.6 Shipping Destinations . 10 of 12

8.5 Debriefing 12 of 12

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8.1 Overview

 Each Forest Health Monitoring (FHM) region conducts logistics in a manner most suitable for

the

requirements and constraints of that region. While crew configuration and/or coordination 

activities may

vary across states and regions, the measurement and collection protocols remain constant. The 

following

section describes field personnel responsibilities and activities and suggests a number of 

possible sampling

scenarios. Additionally, this section discusses training, sample maintenance, data transfer and 

debriefing

activities.

 Ultimately, each region and crew type will develop field logistics optimal for their 

specific requirements

and constraints. FHM crew types, definitions, and the regions or states of implementation are 

provided in

Table 8-1.

8.2 Training

 Field activities are preceded by training and certification. Training activities 

start with national

pretraining where the indicator leads train regional instructors or trainers. All regional 

trainers must

complete training and be certified prior to training regional or state field crews. In 1994, 

pretraining will be

held May 2-6, in Asheville, NC.

 Regional and state training sessions are held following pretraining. After completing 

training, trainers

will test the field crew personnel for comparability. Upon satisfactory completion of the test, 

personnel will

be considered certified. The primary objective of the certification process is for field 

personnel to

demonstrate proficiency in established, fixed, measurement protocols, ease of adherence to 

established

guidelines and to be able to perform comparably between the FHM regions.

 Immediately following certification, crews will visit practice/training plots before 

beginning formal FHM

field collection.

Table 8-1. FHM Crew Types, Definitions, and Regions or States Implementation ^^^

 CREW TYPES

 DEFINITION

 REGION/STATE

 Forester or Core4 crew

 Botany Crew

 Interpenetrating or 1/4 crew

Two-person crew which measures site

condition, growth, and regeneration,

crown classification, damage and

mortality assessment, and ozone

bioindicator plants. This crew, when

visiting a plot with a botanist crew, may

assist with PAR and lichen community

variables.

Two-person crew with at least one who

is qualified as a field botanist. This

crew measures vegetation structure,

PAR, and lichen community variables.

This crew may assist with ozone

bioindicator plants if time allows.

Three- or four-person crew which
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measures site condition, growth, and

regeneration, crown classification,

damage and mortality assessment,

ozone bioindicator plants (eastern

crews only), vegetation structure, PAR,

and lichen community variables.

 North, South (Alabama 

[AL])

 North, South (AL)

Three person crew: Southeast (Georgia

[GA], Virginia [VA]), and Intermountain

(Colorado [CO])

Four person crew: West (California

[CA]) and Pacific Northwest Pilot Study

(PNW PS).

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8.3 Field Logistics

8.3.1 Sampling Responsibilities

 In all regions each crew member will be required to assume full responsibility for specific

tasks. Listed

below are suggestions for the key position assignment per region and/or crew type.

Table 8-2. FHM Key Positions per Region and Crew Type

ACTIVITY

Sampling Schedule

"Srevi Assembly &

Coordination (Crew Leader)

CREW TYPE

Forester Crew

Botanist Crew

1/4 Crew

"Fb7esteF& 1/4 crews

Botanist Crew

LEAD

State Coordinator

Field Coordinator

Field Coordinator

"Forester I

Botanist I (Bot. Crew will

REGION/STATE

North, AL

North, AL

GA, VA, CO, CA, PNW PS

"North, AL, GA, VA", CO, CA,

PNW PS

North, AL

"TransplirtaTion To site"

"SltoTocatton

"WoFestabiishrnerit

"Slte~6on<5for7. Growth""

 Regeneration. Crown

 Condition Classification,

 Damage and Mortality

 Assessment (Tally)

 Forester & 1/4 crews

 Botanist crew

 ""FbresterT "Bofahlsf& 174 '

 crews

 ~ "ForesterT "Botanist"& 177esteF&~l74 Grew"

 Botanist Crew

 All

 ~ Forester (I

 Botanist II

 Forester II & Botanist

 Forester II & Logistician

 ""KiresteFl

 Botanist I

 "AT"

 North, AL
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 North, AL

 CO, GA, VA

 CA, PNW PS

"Communications"'

 PNW PS

 North, AL

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 Field personnel will each have primary responsibility for completion of one or more tasks as

shown in

Tables 8-2. While task completion may require more than one individual's effort, there will be 

one person

assigned to assume full accountability. Some of the crew members will be cross-trained in 

several other

measurement indicators other than those specifically assigned to them, yet varies per region. 

Crosstraining is beneficial because the time some task requires depends on plot location and 

condition. As the

crews become more familiar and proficient, the field personnel can redistribute workloads to 

increase

efficiency and productivity. However, if a crew member has not been trained and certified to 

carry out a

task, then they can not make the measurement. Even if a crew member, who was crosstrained/certified,

samples on a particular day, the crew member originally assigned still has primary 

responsibility for a

particular indicator measurement and remains accountable for quality and completion of that 

measurement.

8.3.2 Work Flow

 Tables 8-3 approximates the amount of time estimated for task completion for all 

preparation, sampling,

and data/sample management activities.

 Tables 8-4 through 8-8 suggests just one field work flow pattern possible per crew scenario 

and region.

Ultimately, each region/state will develop the work flow pattern best suited for that area.

 In general, the forester I and forester II will be working together for the majority of the 

day. Their tasks

are plot establishment, site condition, growth and regeneration, visual crown rating, and damage

and

mortality measurements. When ozone bioindicator plants are collected within the assigned twoweek

window, the forester I and II will collect those samples as well. The botanist will be 

responsible for

vegetation structure. Other measurements, such as PAR and lichen community, can be measured and

collected by the forester I, II, botanist I, II, or logistician depending on the region.

 Sample handling and shipping and data transfer will be the responsibility of the measurer as

assigned

within a region. For example, in the North and Northeast, the botanist I will transfer 

vegetation data and

handle and ship vegetation samples, while the botanist II will transfer PAR measurements and 

handle and

ship the lichen samples.

 A number of voucher specimens will be collected at each plot. These will be prepared and 

analyzed

and incur a significant cost from collection through analysis and interpretation. It is 

imperative that their

integrity be maintained. All samples must be dried first. The person who collects the sample is 

responsible

for packaging and labeling it in the field and in handling and shipping from the hotel or 

office.

Table 8-3. Field Work Time Allocation

Measurements

Plot establishment

Mensuration/

Crowns/Damage

Samples

Collected

no

no

Forester I
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1 hour

5 hour

Forester II

1 hour

5 hour

Botanist I

.5 hour

N/A

Botanist II

.5 hour

N/A

Logistician

.5 hour

N/A

 PAR (Set-up, measurements

 and ambient sensor check)

 no

 N/A

2 hour

 N/A

 2 hour

 2 hour

Lichen community

Vegetation Structure

Ozone Bioindicator Plants

(Two-week window only)

yes

yes

yes

N/A

N/A

1 hour

2 hour

N/A

1 hour

2 hour

6 hour

N/A

2 hour

N/A

N/A

2 hour

N/A

N/A

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Table 8-4. Suggested Work Flow Pattern (Forester and Botanist Crew Working Together on 1/4 Plot) 

 Wow /.-Forester I, II establish plot. Botanist I establishes Vegetation Structure (VS) 

quadrants. Botanist II sets up PAR

 ambient station and flags PAR measuring points.

 Hour 2: Forester I, II begin Site Condition, Growth, and Regeneration/Crowns/Damage (Tally) 

sampling. Botanist I begins VS

 sampling. Botanist II begins lichen community sampling.

 Hour 3: Forester I, II continue Tally sampling. Botanist I continues VS sampling. Botanist II 

continues lichen community

 sampling until complete.

 How4:Forester I, II continue Tally sampling. Botanist I continues VS sampling. Botanist II 

carries out PAR sampling (*) until

 complete.

 Hour 5: Forester I, II continue Tally sampling until complete. Botanist II continues PAR 

sampling until complete.
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 Forester I, II carry out Ozone Bioindicator Plants sampling during two-week window only. 

Forester I, II may leave plot upon

 completion of Tally and Ozone. Botanist I & II continue VS sampling until complete.

 (*) PAR must be done between 1200 to 1400. Foresters assist Botanist with PAR, lichen 

community or vegetation structure if

 time allows.

Table 8-5. Suggested Work Flow Pattern (Forester Crews - Mt2 Plots) 

 Full Day: Forester I, II begin Mt2 Tally sampling. Forester I, II carry Ozone Bioindicator 

Plants sampling during two-week

 window only. . 

Table 8-6. Suggested Work Flow Pattern (Forester Crews - Mt1/3 Plots/No PAR,

Lichens or Vegetation Measurements Being Collected) 

 Hour 1: Forester I, II establish plot.

 Remaining Day: Forester I. II begin Mt1 Tally sampling. Forester I, II carry out Ozone 

Bioindicator Plants sampling during two-

 week window only. 

Table 8-7. Suggested Work Flow Pattern (1/4 Crew (CO))

 Hour 1: Forester I, II establish plot. Botanist establishes VS (Vegetation Structure) 

quadrants. Forester II sets up PAR

 ambient station and flags PAR measuring points.

 Hour 2: Forester I. II begin Tally sampling. Botanist begins VS sampling.

 Hour 3: Forester I, II continue Tally sampling. Botanist continues VS sampling.

 Hour 4: Forester I continues Tally sampling. Botanist' begins Lichen Communities sampling. 

Forester II begins PAR

 measurements.

 Hour 5: Forester I continues Tally sampling. Botanist continues Lichen Communities sampling 

until complete. Forester II

 begins PAR measurements until complete.

 Hour 6: Forester I, II continue Tally sampling until complete. Botanist continues VS sampling 

until complete.

 (*) PAR must be done between 1200 to 1400.

 'Forester I may assist or replace Botanist when sampling Lichens, if time allows. 

-------

 EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 6 of 12

Table 8-8. Suggested Work Flow Pattern (1/4 Crew (CA & PNW Pilot Study)) 

 Hour 1: Forester I, II establish plot. Botanist establishes VS (Vegetation Structure) quadrants.

Logistician sets up PAR

 ambient station and flags PAR measuring points.

 Hour 2: Forester I, II begin Tally sampling. Botanist and Logistician begin VS sampling.

 Hour 3: Forester I, II continue Tally sampling. Botanist and Logistician continue VS sampling.

 Hour 4: Forester I continues Tally sampling. Forester II begins Lichen Communities sampling. 

Logistician begins PAR

 measurements. Botanist continues VS sampling.

 Hour 5: Forester I continues Tally sampling. Forester II continues Lichen Communities sampling 

until complete. Logistician

 continues PAR measurements until complete. Botanist continues VS sampling.

 Hour 6: Forester I, II continue Tally sampling until complete. Botanist and Logistician 

continue VS sampling until complete.

 (*) PAR must be done between 1200 to 1400. Forester I & II may assist Botanist and Logistician

if time allows.

8.3.3 Crew Responsibilities and Activities

 The crew's daily field activities will be supervised by one member of the crew who will be 

designated

by the field coordinator. The crew leader will supervise all field operations and, if 

necessary, resolve all
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discrepancies or issues at the site. The field crew leader has the responsibility of:

 • Maintaining sampling schedule.

 • Assembly of field crew.

 • Transportation to the sampling site.

 • Ensuring adherence to sampling protocol.

 • Ensuring proper use of field equipment.

 • Maintaining site integrity.

 • Daily communication.

 Any crew member can be assigned to serve as crew lead.

8.3.3.1 Sampling Schedule

 The initial sampling schedule will be coordinated by the field or state coordinator. The 

field or state

coordinator will work with the crew leader to determine the most appropriate timeline and 

seasonal itinerary

to meet program goals yet maintain sample integrity and crew morale. The crew leader will be 

responsible

for sampling a certain number of plots within an index period and have ultimate responsibility

to meet

sampling quota while maintaining the quality of the measurements and samples and following 

standard

protocol. The crew leader must also be attentive in assessing field crew morale while planning a

productive

sampling schedule.

8.3.3.2 Assembly of Field Crew

 Each crew must assemble at an appropriate, pre-determined time and place each scheduled 

sampling

day, generally designated by the crew leader. Each crew member should be given the opportunity 

to note

the location and route to the plot, and review site specific safety information. The crew 

leader will also

determine rendezvous points to assemble the crew after scheduled time off (i. e., after 

weekends, holidays).

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 EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 7 of 12

8.3.3.3 Transportation

 The crew leader should assign transportation responsibility within the crew. This individual 

will be

responsible for providing and maintaining overall adequate, efficient transportation to the 

sample site, as

well as hotel accommodations and eating establishments, if plot location and schedule require. 

Most of

the crew members will be assigned a field vehicle and will be responsible for the care and 

maintenance

of that vehicle. Crews must make efficient.use of vehicles and not use the vehicles for nonwork related

activities unless otherwise approved by the field or state coordinator.

8.3.3.4 Sampling Site Location

 In some states, FIA photopoints are used for the sampling plots. Other plot locations are 

based on

the EMAP hex grid system. Information packets pertaining to each sampling sites should be 

provided by

the field or state coordinator and include maps, landowner information, local emergency 

information, and

any existing directions to the plots. Foresters will follow standard FIA protocol in locating 

sampling sites.

Procedures for this activity are detailed in Section 1.

8.3.3.5 Plot Establishment

 The forester I and forester II will be responsible for establishing the plot. Details of 

this procedure are

provided in Section 1. However, Section 1 only details establishment of the plot for tally. 

Vegetation

structure and PAR subplots must also be established. It is very important that the plot 

establishment be

accomplished in a sequence that 1) maintains plot integrity for other measurements (i.e., 

regeneration

measurements before vegetation structure measurements), and 2) allows field crew members to start
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data

collection activities as soon as possible in order to finish sampling within a reasonable 

timeframe. To

accomplish this, the foresters should work with the botanist (s) and/or logistician to develop a

standard plot

layout procedure appropriate for their specific field crew.

8.3.3.6 Ensuring Adherence to Sampling Protocol

 The crew leader is expected to have a basic knowledge of all sampling procedures and be 

able to

determine whether crew members are adhering to sampling protocols. It is suggested that the 

crew attend

all possible additional training sessions to become familiar with other crew members' sampling 

tasks. If

protocols appear to be inconsistent or arc- being misinterpreted, the crew leader should 

address the

inconsistency during communications update with field or state coordinators, who should contact 

regional

indicator leads. It is of primary importance that problems be rectified prior to visiting 

another FHM plot.

8.3.3.7 Ensuring Proper Use of Field Equipment

 Some field equipment will require special care (i.e., PDRs, laptop computers, printers, 

ceptometers and

dataloggers) and proper use. The assigned crew member(s) must be familiar with the proper 

use of

equipment and if necessary assist crew members if problems occur. Crew members will inform the 

crew

leader of equipment that is destroyed or in need of repair. The crew leader is responsible for 

addressing

the equipment problems. For those crews which communicate via the EPA VAX network, equipment 

needs

or repairs can be communicated in the note section of the daily communication update. For those 

without

VAX capabilities, equipment needs or repairs can be communicated to field or state 

coordinators via

telephone.

-------

 EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 8 of 12

8.3.3.8 Equipment Maintenance

 During orientation and training, each field crew member will be provided equipment and an 

inventory

list of the equipment they will receive. If equipment is damaged during field activities, the 

item should be

identified on the inventory list and the service or repair that may be required should be 

specified. The crew

members must inform the crew leader, who will inform the field coordinator of the damaged 

equipment.

The crew leader is responsible for disclosing this information through the periodic 

communications update.

If available, the field crew member will use replacement equipment. If supplies run low or an 

item of

equipment is needed, notify the field coordinator by means of the VAX or DG computer system or

telephone.

 At the end of the field season, crews will return all equipment to the field 

coordinator. The field

coordinator and each crew member will check off each item on the inventory list that was 

provided at the

beginning of the field season to each field crew member. All items must be accounted. Items 

will be

inspected for damage and their condition recorded.

8.3.3.9 Maintaining Site Integrity

 During sampling, flagging will be placed around the site to mark various sampling points 

(vegetation

and PAR measurement points). All flagging must be removed after sampling has been completed. 

The

crew leader will be responsible for maintaining plot integrity and anonymity when sampling is 

completed

and will direct all of the crew members to assist in these activities.

8.3.3.10 Daily Communication
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 Regional field communications vary. Forester crews usually will be able to depend on the 

telephone

to communicate with field or state coordinators, while botanist and 1/4 crew communications most

likely

will be able to communicate electronically through laptop computers using the telephone system in

the hotel

the crew is staying or an available office. A communications package and modem will connect 

the laptop

computer to either the VAX or DG computer systems. When using the VAX, an "update" screen will 

appear

and request the following information:

 • Field Crew ID.

 • Visitor(s) (i.e., auditors, Indicator leads).

 Field crew location (hotel name, address, telephone number).

 • Expected location of next day.

 • Hexagon sampled that day and data collected on the plot.

 • Comments/Problems/Mail messages to other crews and/or non-field personnel.

 The botanist or forester II may fill out the update; however, it is the crew leader's 

responsibility to make

sure that the update is filled out each night the field crew is collecting data, whether 

or not data is

transmitted that night. This update will be electronically sent to the VAX computer which will 

then be used

to update DG and EMAIL accounts of appropriate individuals in FHM. The crew leader is also 

required to

read all incoming communications to the crew and make sure all messages are relayed to 

appropriate

individuals. Instructions for this operation are presented in the FHM PDR Guide.

 Some hotels have hardwire phone lines, prohibiting the connection of the laptop to the 

telephone

system. In this instance, the crew should contact their field or state coordinator via 

telephone. Additionally,

the data collected for that day and sample tracking information should be loaded on a floppy 

disk. The

floppy disk is created each time a shipment of samples is created.

-------

 EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 9 of 12

 If communication using the laptop computer or the telephone is impossible, then the crew 

leader is

responsible for calling the field or state coordinator as soon as possible. The appropriate 

telephone

numbers and times of contact for the field coordinator will be given during regional training.

8.4 Data Transfer and Sample Handling

 All field positions are responsibility for the following activities:

 • Data transfer.

 • Sample maintenance.

 • Sample transfer and tracking.

 • Sample shipping.

8.4.1 Data Transfer

 Completed data from PDRs and ceptometers must be uploaded to laptop computers daily and

transferred to the VAX computer. Instructions for these operations are presented in the FHM PDR

Guide.

8.4.2 Sample and Voucher Specimens Handling

 Vegetation voucher specimens lichen samples, and ozone bioindicator plant voucher specimens 

will

be collected from the plots. The number of samples and vouchers expected from each plot are 

identified

in the appropriate methods section.

8.4.3 Sample Maintenance Until Shipping

 All samples and vouchers should be packaged by the field crew in a manner that will 

maintain integrity.

Vegetation voucher specimens are to be placed in zip-lock bags or arranged in a magazine (See 

Section

5) until they can be placed into a plant press later that day. Ozone bioindicator plant voucher
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specimens

are to be placed in a plant press in the field. More specific sample handling instructions are

outlined below.

Lichens

 1.' Lichen samples will be carried off the plot in the labeled #2 brown paper bags by the 

collector.

 Bags will be appropriately marked with the words "Lichen Community."

 2. If specimens were wet when collected, then the individual bags should be spread out and 

left with

 the tops open for the evening in the hotel room in order to dry out the samples.

 3. Place all voucher bags from a given plot into a larger brown paper bags. Record plot ID 

code and

 date.

 4. Staple or tape the top of the large bag closed and store in a dry place.

Vegetation Voucher Specimens

 1. The vegetation voucher specimens will be carried off the plot placed between the pages 

of

 magazines or in labeled zip-lock bags arranged in a three-ring binder notebook.

 2. After every day of sampling, the botanist will place the specimens in a plant press to 

dry.

Ozone Bioindicator Voucher Specimens (East only)

 1. The ozone bioindicator voucher specimens will be carried off the plot in a plant press, 

each sample

 with a label with the plot number and date collected.

-------

 EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 10 of 12

 2. Fill out the upper half of a "Sample Voucher Sheet" the same day of collection for each 

ozone

 bioindicator voucher specimen.

 3. After samples are dried and pressed, they should be placed in a unsealed ziplock bag, 

each

 accompanied with its corresponding "Sample Voucher Sheet."

8.4.4 Sample Transfer and Tracking

 Samples and specimens must be tracked as they are transferred from field to hotel/office to 

herbaria,

laboratory, or indicator lead. Each big bag of lichens (which contains all lichens from one 

plot) is to be

treated as an individual sample and given just one sample number. Each plot's worth of 

vegetation

vouchers is to be treated as one sample and given just sample number. Each plot's worth of 

bioindicator

plant vouchers is to be treated as one sample and given just one sample number.

Procedure

 1. Vegetation voucher specimens will be sent in boxes as soon as they are dry on a weekly 

basis.

 Ozone bioindicator plant specimens will be sent by regular mail at the close of the 

ozone

 bioindicator evaluation window (Northeast, August 19 and Southeast, August 12). Lichen 

samples

 will be shipped by regular mail in separate boxes as soon as a box is full.

5.4.5 Sample Shipping

 Administrative shipping protocols vary per region. The field crews will be either provided 

with a number

of Federal Express shipping labels or directed to cover the cost of shipping/mailing to be 

reimbursed per

regional protocol. The field coordinator will provide more specific guidance per region or crew.

When using

Federal Express, the crew may call Federal Express (800-238-5355) and arrange for pickup of 

the

packages at the hotel/office.

8.4.6 Shipping Destinations

 Once the samples are packed, they should be shipped according to sample. Ozone bioindicator 

plant
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voucher specimens must be pressed and dried prior to shipping to:

Gretchen Smith

Department Forestry, Holdsworth Hall

University of Massachusetts

Amherst, MA 01003

(413)545-1680

Vegetation voucher specimens, having been pressed and dried, should be sent as soon as possible 

to the

respective regional herbium at:

California:

Attention: FHM

Herbium, Department of Botany

CordieyHall 2082

Corvallis, OR 97331-2902

(503) 737-4106

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 EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 11 of 12

Colorado:

Renee O'Brien

USDA Forest Service

507 25th St.

Ogden. UT 84401

(801) 625-5371

PNW Pilot Study:

Attention: FHM

Herbium, Department of Botany

CordleyHall 2082

Corvallis, OR 97331-2902

(503) 737-4106

Southeast/Southern:

Dr. B. E. Woffard

University of Tennessee

Department of Botany

437 Hesler Biology Building

Knoxville, TN 37996

(615)974-6212

New England and Lake States:

Dr. Garrett Crow

Department of Plant Biology

Neismith Hall

University of New Hampshire

Durham, NH 03824

(603) 862-3865

Maryland and New Jersey:

Herbarium Curator

Department of Biology

West Virginia University

Morgantown, WV 26506-6057

(304) 293-5201

Lichen samples should be thoroughly air-dried and sent when the box is full to the appropriate 

regional

lead:

California, PNW Pilot Study & Colorado:

Bruce Ryan

Department of Botany & Microbiology

Arizona State University

Tempe, AZ 85287

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 EMAP Forest Monitoring, Section 8, Rev. No. 0, October, 1994, Page 12 of 12

Southeast/ June 13 - July 21:

Jonathan Dey

Biology Department

Illinois Wesleyan University

Bloomington, Illinois 61702

(309) 556-3057
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Southeast/July 22 - end of season:

Karin Heiman

50 Rector Branch Road

Marshall, NC 28753

(704) 649-3804

Northeast

Susan Will-Wolf

Department of Botany, Birge Hall

University of Wisconsin

430 Lincoln Dr.

Madison, Wl 53705-1381

(608) 262-2179

8.5 Debriefing

 Upon completion of field activities, crews will be given an opportunity to evaluate the 

field activities,

measurement protocols, the Field Guide, and logistics. Initially, crews will be given a 

"Debriefing

Questionnaire" to complete prior to any formal debriefing meeting. In some areas, the 

questionnaires are

tallied and the results are presented at the debriefing meeting. The debriefing lends crews an 

opportunity

to further present and discuss issues. These meetings are held soon after field collection is 

finished in late

August or September.

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 EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 1 of 8

 Appendix A

 U.S. Tree Species Codes

 Most species encountered in the continental United States and considered to be trees by FHM

are

listed below. When in doubt about whether a species not listed is a tree, consult your Field 

Supervisor.

Western woodland species are prefaced with "(ww)".

Code

Common Name

Genus

Species

010 firsp.

011 Pacific silver fir

012 balsam fir

014 bristlecone fir

015 white fir

016 Fraserfir

017 grand fir

018 corkbark fir

019 subalpinefir

020 California red fir

021 Shasta red fir

022 noble fir

041 Port-Orford-cedar

042 Alaska-Yeilow-cedar

043 Atlantic white-cedar

050 Cypress

051 Arizona cypress

052 Baker cypress

058 (ww) Pinchot juniper

059 (ww) Red berry juniper

060 Redcedar/Juniper

061 Ashe juniper

062 (ww) California juniper

063 (ww) Alligator juniper

064 (ww) Western juniper

065 (ww) Utah juniper

066 (ww) Rocky Mountain juniper

067 southern redcedar

 -Softwoods-

 Abies

 Abies

 Abies

 Abies

 Abies

 Abies
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 Abies

 Abies

 Abies

 Abies

 Abies

 Abies

 Chamaecyparis

 Chamaecyparis

 Chamaecyparis

 Cupressus

 Cupressus

 Cupressus

 Juniperis

 Juniperis

 Juniperis

 Juniperis

 Juniperis

 Juniperis

 Juniperis

 Juniperis

 Juniperus

 Juniperus

 sp.

 amabilis

 balsamea

 bracteata

 concolor

 fraseri

 grandis

 lasiocarpa var. arizonica

 lasiocarpa

 rnagnifica var. magnifica

 magnifica var. shastensis

 procera

 lawsoniana

 nootkatensis

 thyoides

 sp.

 arizonica

 bakeri

 pinchotii

 erythrocarpa

 sp.

 ashei

 Californica

 deppeana

 occidentalis

 osteosperma

 scopulorum

 sillcicola

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 EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 2 of 8

Code Common Name Genus Species

 Softwoods

068

069 (ww)

-070

071

072

073

081

090

091

092

093

094

095

096

097

098

101
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102

103

104

105

1 06 (ww)

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

eastern redcedar

one-seed juniper

larch (introduced)

tamarack (native)

subalpine larch

western larch

incense-cedar

spruce

Norway spruce

Brewer spruce

Engelmann spruce

white spruce

black spruce

blue spruce

red spruce

Sitka spruce

whitebark pine

bristlecone pine

knobcone pine

foxtail pine

jack pine

common pinyon

sand pine

lodgepole pine

coulter pine

shortleaf pine

slash pine

Apache pine

limber pine

Mexican white pine

spruce pine

Jeffrey pine

Sugar pine

Chihuahua pine

Western white pine

bishop pine

longleaf pine

ponderosa pine

table mountain pine

monterey pine

red pine

Juniperus

Juniperis

Larix

Larix

Larix

Larix

Libocedrus

Picea

Picea

Picea

Picea

Picea

Picea

Picea
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Picea

Picea

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

virginiana

monosperma

sp.

laricina

lyallii

occidentallis

decurrens

sp.

abies

breweriana

engelmannii

glauca

mariana

pungens

rubens

sitchensis

albicaulis

aristata

attenuate

balfouriana

banksiana

edulis

clausa

contorta

coulteri

echinata

elliottii

engelmannii

flexilis var. reflexa

flexilis var. reflexa

glabra

jeffreyi

lambertiana

leiophylla

monticola

muricata

palustris

ponderosa

pungens

radiata

resinosa

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Code

EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 3 of 8

 Common Name Genus Species

126 pitch pine

127 Grey pine

128 pond pine

129 eastern white pine
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130 Scotch pine

131 loblolly pine

132 Virginia pine

133 (ww) Singleleaf pinyon

134 (ww) Border pinyon

135 Arizona pine

136 southwestern white pine

137 washoe pine

138 four-leaf pine

139 Austrian pine

140 (ww) Mexican pinyon pine

201 bigcone Douglas-fir

202 Douglas-fir

211 redwood

212 giant sequoia

221 baldcypress

222 pondcypress

231 Pacific yew

241 northern white-cedar

242 western redcedar

251 California torreya

260 hemlock

261 eastern hemlock

262 Carolina hemlock

263 western hemlock

264 mountain hemlock

300 (ww) acacia

310 maple

311 Florida maple

312 bigleaf maple

313 boxelder

314 black maple

315 striped maple

316 red maple

317 silver maple

318 sugar maple

319 mountain maple

321 (ww) Rocky Mountain maple

 -Softwoods

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pinus

Pseudotsuga

Pseudotsuga

Sequioa

Sequoiadendron

Taxodium

Taxodium

Taxus

Thuja

Thuja

Torreya

Tsuga

Tsuga

Tsuga

Tsuga

Tsuga

Acacia

Acer

Acer

Acer

Acer

Acer

Acer

Acer

Acer

Acer

Acer
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Acer

rigida

sabiniana

serotina

strobus

sylvestris

taeda

virginiana

monophylla

discolor

ponderosa var. arizonica

strobiformis

washoensis

quadrifolia

nigra

cembroides

macrocarpa

menziesii

sempervirens

giganteum

distichum

distichum var. nutans

brevifolia

occidentalis

plicata

Californica

sp.

canadensis

caroliniana

heterophylla

mertensiana

sp.

sp.

barbatum

macrophyllum

negundo

nigrum

pennsylvanicum

rubrum

saccharinum

saccharum

spicatum

glabrum

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Code

EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 4 of 8

Common Name Genus Species

 -Hardwoods

322 (ww) Bigtooth Maple

330 buckeye, horsechestnut

331 Ohio buckeye

332 yellow buckeye

333 California buckeye

341 ailanthus

350 alder

351 red alder

352 white alder

353 Sitka alder

354 thinleaf alder

355 European alder

356 serviceberry

361 Pacific madrone

367 pawpaw

370 birch sp.

371 yellow birch

372 sweet birch

373 river birch

374 water birch

375 paper birch

376 western paper birch

377 Alaska paper birch

378 northwestern paper birch

379 gray birch

381 chittamwood, gum bumelia

391 American hornbeam,

 musclewood
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400 hickory sp.

401 water hickory

402 bitternut hickory

403 pignut hickory

404 pecan

405 shellbark hickory

407 shagbark hickory

408 black hickory

409 mockernut hickory

421 American chestnut

422 Allegheny chinkapin

423 Ozark chinkapin

430 chinkapin

431 golden chinkapin

Acer

Aesculus

Aesculus

Aesculus

Aesculus

Ailanthus

Alnus

Alnus

Alnus

Alnus

Alnus

Alnus

Amelanchier

Arbutus

Asimina

Betula

Betula

Betula

Betula

Betula

Betula

Betula

Betula

Betula

Betula

Bumelia

Carpinus

Carya

Carya

Carya

Carya

Carya

Carya

Carya

Carya

Carya

Castanea

Castanea

Castanea

Castanopsis

Castanopsis

grandidentatum

sp.

glabra

octandra

californica

altissima

sp.

rubra

rhombifolia

sinuata

tenuifolia

glutinosa

sp.

menziesii

triloba

sp.

alleghaniensis

lenta

nigra

occidentalis

papyrifera

papyrifera var. commutata

papyrifera var. neoalaskana

papyrifera var. subcordata
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populifolia

lanuginosa

caroliniana

sp.

aquatica

cordiformis

glabra

illinoensis

laciniosa

ovata

texana

tomentosa

dentata

pumila

ozarkensis

sp.

chrysophylla

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EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 5 of 8

 Common Name Genus Species

^r w w

450

451

452

460

461

462

463

471

475 (ww)

476 (ww)

477 (ww)

478

479

481

491

492

500

510

521

531

540

541

542

543

544

545

546

547

551

552

555

571

580

581

591

600

601

602

603

604

605

606

\-4zttT\\nif\r\ri'

cataipa

southern cataipa

northern cataipa

hackberry sp.

sugarberry

hackberry

netleaf hackberry

eastern redbud

curileaf mountain-mahogany

alder-leaf mountain-mahogany
Forest Health Monitoring: Field Methods Guide

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hairy mountain-mahogany

birchleaf mountain-mahogany

dwarf mountain-mahogany

yellowwood cladrastis

flowering dogwood

Pacific dogwood

hawthorn

eucalyptus

common persimmon

American beech

ash

white ash

Oregon ash

black ash

green ash

pumpkin ash

blue ash

velvet ash

waterlocust

honeylocust

loblolly-bay

Kentucky coffeetree

Mountain silverbell

Carolina silverbell

American holly

walnut

butternut

black walnut

California black walnut

southern California black

walnut

palo verde

palo verde

Cataipa

Cataipa

Cataipa

Celtis

Celtis

Celtis

Ceitis

Cercis

Cercocarpus

Cercocarpus

Cercocarpus

Cercocarpus

Cercocarpus

Cladrastis

Cornus

Cornus

Crataegus

Eucalyptus

Diospyros

Fagus

Fraxinus

Fraxinus

Fraxinus

Fraxinus

Fraxinus

Fraxinus

Fraxinus

Fraxinus

Gleditsia

Gleditsia

Gordonia

Gymnocladus

Halesia

Halesia

Ilex

Juglans

Juglans

Juglans

Juglans

Juglans

Leguminosae

Leguminosae

sp.

bignonioides

speciosa
Forest Health Monitoring: Field Methods Guide

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sp.

laevigata

occidentalis

reticulata

canadensis

ledifolius

montanus

breviflorus

betuloides

intricatus

kentukea

florida

nuttallii

sp.

sp.

virginiana

grandifolia

sp.

americana

latifolia

nigra

pennsylvanica

profunda

quadrangulata

velutina

aquatica

triacanthos

lasianthus

dioicus

sp.

Carolina

opaca

sp.

cinerea

nigra

hindsii

californica

parkinsonia

cercidium

-------

Code

EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 6 of 8

Common Name Genus Species

611 sweetgum

621 yellow-poplar

631 tanoak

641 Osage-orange

650 magnolia sp.

651 cucumbertree

652 southern magnolia

653 sweetbay

654 bigleaf magnolia

660 apple sp.

661 Oregon crab apple

680 mulberry sp.

681 white mulberry

682 red mulberry

691 water tupelo

692 ogeechee tupelo

693 blackgum

694 swamp tupelo

701 eastern hophornbeam,

 ironwood

711 sourwood

712 paulownia, empress tree

721 redbay

722 water elm, planer tree

730 sycamore California

731 sycamore

740 cottonwood

741 balsam poplar

742 eastern cottonwood

743 bigtooth aspen

744 swamp cottonwood

745 plains cottonwood

746 quaking aspen
Forest Health Monitoring: Field Methods Guide

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747 black cottonwood

748 fremont poplar

749 narrowleaf cottonwood

752 silver poplar

755 (ww) mesquite

760 cherry, plum spp.

761 pin cherry

762 black cherry

763 chokecherry

764 plums, cherries,

 except 762

 -Hardwoods

Liquidambar

Liriodendron

Lithocarpus

Maclura

Magnolia

Magnolia

Magnolia

Magnolia

Magnolia

Malus

Malus

Morus

Morus

Morus

Nyssa

Nyssa

Nyssa

Nyssa

Ostrya

Oxydendrum

Paulownia

Persea

Planera

Platanus

Platanus

Populus

Populus

Populus

Populus

Populus

Populus

Populus

Populus

Populus

Populus

Populus

Prosopis

Prunus

Prunus

Prunus

Prunus

Prunus

styraciflua

tulipifera

densiflorus

pomifera

sp.

acuminata

grandiflora

virginiana

macrophylla

sp.

fusca

sp.

alba

rubra

aquatica

ogeche

sylvatica

sylvatica var. biflora

virginiana

arboreum

tomentosa

borbonia

aquatica

californica

occidentalis
Forest Health Monitoring: Field Methods Guide

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spp.

balsamifera

deltoides

grandidentata

heterophylla

sargentii

tremuloides

trichocarpa

fremontii

angustifolia

alba

sp.

sp.

pensylvanica

serotina

virginiana

sp.

-------

Code

EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 7 of 8

 Common Name Genus Species

765

766

800

801

802

803 (ww)

804

805

806

807

808

809

810(ww)

811

812

813

814 (ww)

815

816

817

818

819

820

821

822

823

824 .

825

826 (ww)

827

828

829 (ww)

830

831

832

833

834

835

836

837

Canada plum Prunus

wild plum

oak

coastal live oak,

California live oak

white oak

Arizona white oak, Gray oak

swamp white oak

canyon live oak

scarlet oak
Forest Health Monitoring: Field Methods Guide

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blue oak

durand oak

northern pin oak

emery oak

engelmann oak

southern red oak

cherrybark oak,

swamp red oak

gambel oak

Oregon white oak

bear oak, scrub oak

shingle oak

California black oak

turkey oak

laurel oak

valley oak,

California white oak

overcup oak

bur oak

blackjack oak

swamp chestnut oak

chinkapin oak

water oak

nuttall oak

Mexican blue oak

pin oak

willow oak

chestnut oak

northern red oak

shumard oak

post oak

delta post oak

black oak

Prunus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

nigra

.americana

spp.

agrifolia

alba
Forest Health Monitoring: Field Methods Guide

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arizonica, grisea

bicolor

chrysolepsis

coccinea

douglassi

durandii

ellipsoidalis

emoryi

engelmannii

falcata var. falcata

falcata var. pagodaefolia

gambelii

garryana

ilicifolia

imbricaria

kelloggii

laevis

laurifolia

lobata

lyrata

macrocarpa

marilandica

michauxii

muehlenbergii

nigra

nuttalii

oblongifolia

palustris

phellos

prinus

.rubra

shumardii

stellata

stellata var. Mississippiensis

velutina

-------

 EMAP Forest Monitoring, Appendix A, Rev. No. 0, October, 1994, Page 8 of 8

Code Common Name Genus Species

 Hardwoods838 live oak

839 interior live oak

840 dwarf post oak

841 dwarf live oak

842 bluejack oak

843 (ww) silverleaf oak

848 western Oak (Deciduous)

849 western Oak (Evergreen)

899 scrub oak

901 black locust

902 (ww) New Mexico locus

920 willow

921 peachleaf willow

922 black willow

928 diamond willow

931 sassafras

935 American mountain-ash

936 European mountain-ash

950 basswood

951 American basswood

952 white basswood

970 elm

971 winged elm

972 American elm

973 cedar elm

974 Siberian elm

975 slippery elm

976 September elm

977 rock elm

981 California laurel

990 (ww) Arizona ironwood

991 salt cedar

992 sparkleberry

993 chinaberry

994 Chinese tallowtree
Forest Health Monitoring: Field Methods Guide

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995 tung-oil tree

996 smoketree

998 not listed

999 unknown

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Quercus

Robinia

Robinia

Salix

Salix

Salix

Salix

Sassafras

Sorbus

Sorbus

Tilia

Tilia

Tilia

Ulmus

Ulmus

Ulmus

Ulmus

Ulmus

Ulmus

Ulmus

Ulmus

Umellularia

Olneya

Tamarisk

Vaccinium

Melia

Sapium

Aleu rites

Cotinus

virginiana

wislizenii

stellata var stellata

sp.

incana

hypoleucoides

spp.

spp.

sp.

pseudoacacia

neomexicana

sp.

amygdaloides

nigra

eriocephala

albidum

americana

aucuparia

sp.

americana

heterophylla

sp.

alata

americana

crassifolia

pumila

rubra

serotina

thomasii

californica

tesota

sp.

arboreum

azedarach

sebiferum

fordii

obovatus
Forest Health Monitoring: Field Methods Guide

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-------

 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 1 of 9

 Appendix B

 State and County FIPS Codes

(01)

(001)

(003)

(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

(031)

(033)

(035)

(037)

(039)

(041)

(043)

(045)

(047)

(049)

(051)

(053)

(055)

(057)

(059)

(061)

(063)

(065)

(067)

(069)

(071)

(073)

(075)

(077)

(079)

(081)

(083)

(085)

(087)

(089)

Alabama

Autauga

Baldwin

Barbour

Bibb

Blount

Bullock

Butler

Calhoun

Chambers

Cherokee

Chilton

Choctaw

Clarke

Clay

Cleburne

Coffee

Colbert

Conecuh

Coosa

Covington

Crenshaw

Cullman

Dale

Dallas

De Kalb

Elmore

Escambia

Etowah
Forest Health Monitoring: Field Methods Guide

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Fayette

Franklin

Geneva

Greene

Hale

Henry

Houston

Jackson

Jefferson

Lamar

Lauderdale

Lawrence

Lee

Limestone

Lowndes

Macon

Madison

(091)

(093)

(095)

(097)

(099)

(101)

(103)

(105)

(107)

(109)

(111)

(113)

(115)

(117)

(119)

(121)

(123)

(125)

(127)

(129)

(131)

(133)

(06)

(001)

(003)

(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

(031)

(033)

(035)

(037)

(039)

(041)

Marengo

Marion

Marshall

Mobile

Monroe

Montgomery

Morgan

Perry

Pickens

Pike

Randolph

Russell

St Clair

Shelby

Sumter

Talladega

Tallapoosa

Tuscaloosa

Walker

Washington
Forest Health Monitoring: Field Methods Guide

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Wilcox

Winston

California

Alameda

Alpine

Amador

Butte

Calaveras

Colusa

Contra Costa

Del Norte

El Dorado

Fresno

Glenn

Humboidt

Imperial

Inyo

Kern

Kings

Lake

Lassen

Los Angeles

Madera

Marin

(043)

(045)

(047)

(049)

(051)

(053)

(055)

(057)

(059)

(061)

(063)

(065)

(067)

(069)

(071)

(073)

(075)

(077)

(079)

(081)

(083)

(085)

(087)

(089)

(091)

(093)

(095)

(097)

(099)

(101)

(103)

(105)

(107)

(109)

(111)

(113)

(115)

Mariposa

Mendocino

Merced

Modoc

Mono

Monterey

Napa

Nevada

Orange

Placer

Plumas

Riverside

Sacramento

San Benito

San Bernardino

San Diego

San Francisco

San Joaquin

San Luis Obispo

San Mateo
Forest Health Monitoring: Field Methods Guide

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Santa Barbara

Santa Clara

Santa Cruz

Shasta

Sierra

Siskiyou

Solano

Sonoma

Stanislaus

Sutler

Tehama

Trinity

Tulare

Tuolumne

Ventura

Yolo

Yuba

(08) Colorado

(001) Adams

(003) Alamosa

(005) Arapahoe

(007) Archuleta

(009) Baca

(011) Bent

-------

 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 2 of 9

 (013)

 (015)

 (017)

 (019)

 (021)

 (023)

 (025)

 (027)

 (029)

 (031)

 (033)

 (035)

 (037)

 (039)

 (041)

 (043)

 (045)

 (047)

 (049)

 (051)

 (053)

 (055)

 (057)

 (059)

 (061)

 (063)

 (065)

 (067)

 (069)

 (071)

 (073)

 (075)

 (077)

 (079)

 (081)

 (083)

 (085)

. (087)

 (089)

 (091)

 (093)

 (095)

 (097)

 (099)

 (101)

 (103)

 (105)

 (107)

 (109)

 (111)

 (113)

 Boulder
Forest Health Monitoring: Field Methods Guide

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 Chaff ee

 Cheyenne

 Clear Creek

 Conejos

 Costilla

 Crowley

 Custer

 Delta

 Denver

 Dolores

 Douglas

 Eagle

 Elbert

 El Paso

 Fremont

 Garfield

 Gilpin

 Grand

 Gunnison

 Hinsdale

 Huerfano

 Jackson

 Jefferson

 Kiowa

 Kit Carson

 Lake

 La Plata

 Larimer

 Las Animas

 Lincoln

 Logan

 Mesa

 Mineral

 Moffat

 Montezuma

 Montrose

 Morgan

 Otero

 Ouray

 Park

 Phillips

 Pitkin

 Prowers

 Pueblo

 Rio Blanco

 Rio Grande

 Routt

Saguache

San Juan

San Miguel

 (115) Sedgewick

 (117) Summit

 (119) Teller

 (121) Washington

 (123) Weld

 (125) Yuma

 (09)

 (001)

 (003)

 (005)

 (007)

 (009)

 (011)

 (013)

 (015)

 Connecticut

 Fairfield

 Hartford

 Litchfield

 Middlesex

 New Haven

 New London

 Tolland

 Windham

(10) Delaware

(001) Kent

(003) New Castle

(005) Sussex

(13)

(001)

(003)
Forest Health Monitoring: Field Methods Guide

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(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

(031)

(033)

(035)

(037)

(039)

(043)

(045)

(047)

(049)

(051)

Georgia

Appling

Atkinston

Bacon

Baker

Baldwin

Banks

Barrow

Bartow

Ben Hill

Berrien

Bibb

Bleckley

Brantley

Brooks

Bryan

Bulloch

Burke

Butts

Calhoun

Camden

Candler

Carroll

Catoosa

Charlton

Chatham

 (053) Chattahoochee

 (055) Chattooga

 (057) Cherokee

 (059) Clarke

 (061) Clay

 (063) Clayton

 (065) Clinch

 (067) Cobb

 (069) Coffee

 (071) Colquitt

 (073) Columbia

 (075) Cook

 (077) Coweta

 (079) Crawford

 (081) Crisp

 (083) Dade

 (085) Dawson

 (087) Decatur

 (089) De Kalb

 (091) Dodge

 (093) Dooly

 (095) Dougherty

 (097) Douglas

 (099) Early

 (101) Echols

 (103). Effingham

 (105) Elbert

 (107) Emanuel

 (109) Evans

 (111) Fannin

 (113) Fayette

 (115) Floyd
Forest Health Monitoring: Field Methods Guide

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 (117) Forsyth

 (119) Franklin

 (121) Fulton

 (123) Gilmer

 (125) Glascock

 (127) Glynn

 (129) Gordon

 (131) Grady

 (133) Greene

 (135) Gwinnett

 (137) Habersham

 (139) Hall

 (141) Hancock

(143) Haralson

(145) Harris

(147) Hart

(149) Heard

(151) Henry

(153) Houston

-------

 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 3 of 9

(155)

(157)

(159)

(161)

(163)

(165)

(167)

(169)

(171)

(173)

(175)

(177)

(179)

(181)

(183)

(185)

(187)

(189)

(191)

(193)

(195)

(197)

(199)

(201)

(205)

(207)

(209)

(211)

(213)

(215)

(217)

(219)

(221)

(223)

(225)

(227)

(229)

(231)

(233)

(235)

(237)

(239)

(241)

(243)

(245)

(247)

(249)

(251)

(253)

(255)

(257)

Irwin

Jackson

Jasper

Jeff Davis

Jefferson

Jenkins
Forest Health Monitoring: Field Methods Guide

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Johnson

Jones

Lamar

Lanier

Laurens

Lee

Liberty

Lincoln

Long

Lowndes

Lumpkin

Me Duffie

Me Intosh

Macon

Madison

Marion

Meriwether

Miller

Mitchell

Monroe

Montgomery

Morgan

Murray

Muscogee

Newton

Oconee

Oglethorpe

Paulding

Peach

Pickens

Pierce

Pike

Polk

Pulaski

Putnam

Quitman

Rabun

Randolph

Richmond

Rockdale

Schley

Screven

Seminole

Spalding

Stephens

(259)

(261)

(263)

(265)

(267)

(269)

(271)

(273)

(275)

(277)

(279)

(281)

(283)

(285)

(287)

(289)

(291)

(293)

(295)

(297)

(299)

(301)

(303)

(305)

(307)

(309)

(311)

(313)

(315)

(317)

(319)

(321)

(23)

(001)

(003)

(005)
Forest Health Monitoring: Field Methods Guide

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(007)

(009)

(011)

(013)

(015)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

Stewart

Sumter

Talbot

Taliaferro

Tattnall

Taylor

Telfair

Terrell

Thomas

Tift

Toombs

Towns

Treutlen

Troup

Turner

Twiggs

Union

Upson

Walker

Walton

Ware

Warren

Washington

Wayne

Webster

Wheeler

White

Whitfield

Wilcox

Wilkes

Wilkinson

Worth

 Maine

 Androscoggin

 Aroostook

 Cumberland

 Franklin

 Hancock

 Kennebec

 Knox

 Lincoln

 Lincoln

 Oxford

 Penobscot

 Piscataquis

 Sagadahoc

 Somerset

 Wald

 Washington

 (031) York

(24) Maryland

(100) Allegany

(003) Anne Arundel

(005) Baltimore

(009) Calvert

(011) Caroline

(013) Carroll

(015) Cecil

(017) Charles

(019) Dorchester

(021) Frederick

(023) Garrett

(025) Harford

(027) Howard

(029) Kent

(031) Montgomery

(033) Prince Georges

(035) Queen Annes
Forest Health Monitoring: Field Methods Guide

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(037) St. Marys

(039) Somerset

(041) Talbot

(043) Washington

(045) Wicomico

(047) Worcester

(510) Baltimore City

(25) Massachusetts

(001) Barnstable

(003) Berkshire

(005) Bristol

(007) Dukes

(009) Essex

(011) Franklin

(013) Hampden

(015) Hampshire

(017) Middlesex

(019) Nantucket

(021) Norfolk

(023) Plymouth

(025) Suffolk

(027) Worcester

(029) Washington

(031) York

(26) Michigan

(001) Alcona

(003) Alger

-------

 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 4 of 9

(005) Allegan

(007) Alpena

(009) Antrim

(011) Arenac

(013) Baraga

(015) Barry

(017) Bay

(019) Benzie

(021) Berrien

(023) Branch

(025) Calhoun

(027) Cass

(029) Charlevoix

(031) Cheboygan

(033) Chippewa

(035) Clare

(037) Clinton

(039) Crawford

(041) Delta

(043) Dickinson

(045) Eaton

(047) Emmet

(049) Genesee

(051) Gladwin

(053) Gogebic

(055) Grand Traverse

(057) Gratiot

(059) Hillsdale

(061) Houghton

(063) Huron

(065) Ingham

(067) Ionia

(069) losco

(071) Iron

(073) Isabella

(075) Jackson

(077) Kalamazoo

(079) Kalkaska

(081) Kent

(083) Keweenaw

(085) Lake

(087) Lapeer

(089) Leelanau

(091) Lenawee

(093) Livingston

(095) Luce

(097) Mackinac

(099) Macomb
Forest Health Monitoring: Field Methods Guide

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(101) Manistee

(103) Marquette

(105) Mason

(107)

(109)

(111)

(113)

(115)

(117)

(119)

(121)

(123)

(125)

(127)

(129)

(131)

(133)

(135)

(137)

(139)

(141)

(143)

(145)

(147)

(149)

(151)

(153)

(155)

(157)

(159)

(161)

(163)

(165)

(27)

(001)

(003)

(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

(031)

(033)

(035)

Mecosta

Menominee

Midland

Missaukee

Monroe

Montcalm

Montmorency

Muskegon

Newaygo

Oakland

Oceana

Ogemaw

Ontonagon

Osceola

Oscoda

Otsego

Ottawa

Presque Isle

Roscommon

Saginaw

St. Clair

St. Joseph

Sanilac

Schoolcraft

Shiawassee

Tuscola

Van Buren

Washtenaw

Wayne
Forest Health Monitoring: Field Methods Guide

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Wexford

Minnesota

Aitkin

Anoka

Becker

Beltrami

Benton

Big Stone

Blue Earth

Brown

Carlton

Carver

Cass

Chippewa

Chirago

Clay

Clearwater

Cook

Cottonwood

Crow Wing

(037) Dakota

(039) Dodge

(041) Douglas

(043) Faribault

(045) Fillmore

(047) Freeborn

(049) Goodhue

(051) Grant

(053) Hennepin

(055) Houston

(057) Hubbard

(059) Isanti

(061) Itasca

(063) Jackson

(065) Kanabec

(067) Kandiyohi

(069) Kittson

(071) Koochiching

(073) Lac qui Parle

(075) Lake

(077) Lake of the Woods

(079) Le Sueur

(081) Lincoln

(083) Lyon

(085) McLeod

(087) Mahnomen

(089) Marshall

(091) Martin

(093) Meeker

(095) Mille Lacs

(097) Morrison

(099) Mower

(101) Murray

(103) Nicollet

(105) Nobles

(107) Norman

(109) Olmsted

(111) Otter Tail

(113) Pennington

(115) Pine

(117) Pipestone

(119) Polk

(121) Pope

(123) Ramsey

(125) Red Lake

(127) Redwood

(129) Renville

(131) Rice

(133) Rock

(135) Roseau

(137) St. Louis

-------

 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 5 of 9

(139) Scott

(141) Sherbume

(143) Sibley

(145) Stearns

(147) Steele
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(149) Stevens

(151) Swift

(153) Todd

(155) Traverse

(157) Wabasha

(159) Wadena

(161) Waseca

(163) Washington

(165) Watonwan

(167) Wilkin

(169) Winona

(171) Wright

(173) Yellow Medicine

(33) New Hampshire

(001) Belknap

(005) Cheshire

(009) Grafton

(011) Hillsborough

(013) Merrimack

(015) Rockingham

(017) Strafford

(019) Sullivan

(34)

(001)

(003)

(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

(031)

(033)

(035)

(037)

New Jersey

Atlantic

Bergen

Burlington

Camden

Cape May

Cumberland

Essex

Gloucester

Hudson

Hunterdon

Mercer

Middlesex

Monmouth

Morris

Ocean

Passaic

Salem

Somerset

Sussex

 (039) Union

 (041) Warren

(37) North Carolina

(181) Vance

(183) Wake

(185) Warren

(187) Washington

(189) Watauga

(191) Wayne

(193) Wilkes

(195) Wilson

(197) Yadkin

(199) Yancey

(023) Burke

(025) Cabarrus

(027) Caldwell

(029) Camden

(031) Carteret

(033) Caswell
Forest Health Monitoring: Field Methods Guide

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(035) Catawba

(037) Chatham

(039) Cherokee

(041) Chowan

(043) Clay

(045) Cleveland

(047) Columbus

(049) Craven

(051) Cumberland

(053) Currituck

(055) Dare

(057) Davidson

(059) Davie

(061) Dupli

(063) Durham

(065) Edgecombe

(067) Forsyth

(069) Franklin

(071) Gaston

(073) Gates

(075) Graham

(077) Granville

(079) Greene

(081) Guilford

(083) Halifax

(085) Harnett

(087) Haywood

(089) Henderson

(091) Hertford

(093) Hoke

(095)

(097)

(099)

(101)

(103

(105)

(107)

(109)

(111)

(001)

(003)

(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(113)

(115)

(117)

(119)

(121)

(123)

(125)

(127)

(129)

(131)

(133)

(135)

(137)

(139)

(141)

(143)

(145)

(147)

(149)

(151)

(153)

(155)

(157)

(159)

(161)

(163)

(165)

(167)

(169)

(171)

 (173)
Forest Health Monitoring: Field Methods Guide

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Hyde

Iredell

Jackson

Johnston

Jones

Lee

Lenoir

Lincoln

McDowell

Alamance

Alexander

Allegheny

Anson

Ashe

Avery

Beaufort

Bertie

Bladen

Brunswick

Buncombe

Macon

Madison

Martin

Mecklenburg

Mitchell

Montgomery

Moore

Nash

New Hanover

Northhampton

Onslow

Orange

Pamlico

Pasquotank

Pender

perquimans

Person

Pitt

Polk

Randolph

Richmond

Robeson

Rockingham

Rowan

Rutherford

Sampson

Scotland

Stanly

Stokes

Surrey

 Swain

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 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 6 of 9

(175) Transylvania

(177) Tyrrell

(179) Union

(41)

(01)

(03)

(05)

(07)

(09)

(11)

(13)

(15)

(17)

(19)

(21)

(23)

(25)

(27)

(29)

(31)

(33)

(35)

(37)

(39)

(41)
Forest Health Monitoring: Field Methods Guide

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(43)

(45)

(47)

(49)

(51)

(53)

(55)

(57)

(59)

(61)

(63)

(65)

(67)

(69)

(71)

Oregon

Baker

Benton

Clackamas

Clatsop

Columbia

Coos

Crook

Curry

Deschutes

Douglas

Gilliam

Grant

Harney

Hood River

Jackson

Jefferson

Josephine

Klamath

Lake

Lane

Lincoln

Linn

Malheur

Marion

Morrow

Multnomah

Polk

Sherman

Tillamook

Umatilla

Union

Wallowa

Wasco

Washington

Wheeler

Yamhill

(44) Rhode Island

(001) Bristol

(003) Kent

(005) Newport

(007) Providence

(009) Washington

(45) South Carolina

(001) Abbeville

(003) Aiken

(005) Allendale

(007) Anderson

(009) Bamberg

(011) Barnwell

(013) Beaufort

(015) Berkeley

(017) Calhoun

(019) Charleston

(021) Cherokee

(023) Chester

(025) Chesterfield

(027) Clarendon

(029) Colleton

(031) Darlington

(033) Dillon

(035) Dorchester

(037) Edgefield

(039) Fairfield

(041) Florence

(043) Georgetown
Forest Health Monitoring: Field Methods Guide

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(045) Greenville

(047) Greenwood

(049) Hampton

(051) Horry

(053) Jasper

(055) Kershaw

(057) Lancaster

(059) Laurens

(061) Lee

(063) Lexington

(065) Me Cormick

(067) Marion

(069) Marlboro

(071) Newberry

(073) Oconee

(075) Orangeburg .

(077) Pickens

(079) Richland

(081) Saluda

(083) Spartanburg

(085) Sumter

(087) Union

(089) Williamsburg

(091) York

 (47) Tennessee

 (001) Anderson

(003)

(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

(031)

(033)

(035)

(037)

(039)

(041)

(043)

(045)

(047)

(049)

(051)

(053)

(055)

(057)

(059)

(061)

(063)

(065)

(067)

(069)

(071)

(073)

(075)

(077)

(079)

(081)

(083)

(085)

(087)

(089)

(091)

(093)

(095)

(097)

(099)

(101)

(103)

Bedford

Benton

Bledsoe

Blount
Forest Health Monitoring: Field Methods Guide

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Bradley

Campbell

Cannon

Carroll

Carter

Cheatham

Chester

Claiborne

Clay

Cocke

Coffee

Crockett

Cumberland

Davidson

Decatur

De Kalb

Dickson

Dyer

Fayette

Fentres

Franklin

Gibson

Giles

Grainger

Greene

Grundy

Hamblen

Hamilton

Hancock

Hardeman

Hardin

Hawkins

Haywood

Henderson

Henry

Hickman

Houston

Humphreys

Jackson

Jefferson

Johnson

Knox

Lake

Lauderdale

Lawrence

Lewis

Lincoln

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 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 7 of 9

(105)

(107)

(109)

(111)

(113)

(115)

(117)

(119)

(121)

(123)

(125)

(127)

(129)

(131)

(133)

(135)

(137)

(139)

(141)

(143)

(145)

(147)

(149)

(151)

(153)

(155)

(157)

(159)

(161)
Forest Health Monitoring: Field Methods Guide

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(163)

(165)

(167)

(169)

(171)

(173)

(175)

(177)

(179)

(181)

(183)

(185)

(187)

(189)

Loudon

Me Minn

Me Nairy

Macon

Madison

Marion

Marshall

Maury

Meigs

Monroe

Montgomery

Moore

Morgan

Obion

Overton

Perry

Pickett

Polk

Putnam

Rhea

Roane

Robertson

Rutherford

Scott

Sequatchie

Sevier

Shelby

Smith

Stewart

Sullivan

Sumner

Tipton

Trousdale

Unicoi

Union

Van Buren

Warren

Washington

Wayne

Weakley

White

Williamson

Wilson

(50) Vermont

(001) Addison

(003) Bennington

(005) Caledonia

(007) Chittenden

(009) Essex

(011) Franklin (775)

(013) Grand Isle (780)

(015) Lamoille (790)

(017) Orange (800)

(019) Orleans (810)

(021) Rutland (820)

(023) Washington (830)

(025) Windham (093)

(027) Windsor (003)

 (005)

 (007)

(51) Virginia (009)

(001) Accomack (011)

(840) Winchester City (013)

(193) Westmoreland (015)

(195) Wise (017)

(197) Wythe (019)

(199) York (021)
Forest Health Monitoring: Field Methods Guide

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(510) Alexandria City (023)

(515) Bedford City (025)

(520) Bristol City (027)

(530) Buena Vista City (029)

(540) Charlottesville City (031)

(550) Chesapeake City (033)

(560) Clifton Gorge City (035)

(570) Colonial Heights City (036)

(580) Covington City (037)

(590) Danville City (041)

(595) Emporia City (043)

(600) Fairfax City (045)

(610) Falls Church City (047)

(620) Franklin City (049)

(630) Fredericksburg City (051)

(640) Galax City (053)

(650) Hampton City (057)

(660) Harrisonburg City (059)

(670) HopewellCity (061)

(678) Lexington City (063)

(680) Lynchburg City (065)

(683) Manassas (067)

(685) Manassas Park (069)

(690) Martinsville City (071)

(700) Newport News City (073)

(710) Norfolk City (075)

(720) Norton City (077)

(730) Petersburg City (079)

(735) Poquoson (081)

(740) Portsmouth City (083)

(750) Radford City (085)

(760) Richmond City (087)

(770) Roanoke City (089)

Salem City

South Boston City

Staunton City

Suffolk City

Virginia Beach City

Waynesboro City

Williamsburg City

Isle of Wight

Albe marie

Allegheny

Amelia

Amherst

Appomattox

Arlington

Augusta

Bath

Bedford

Bland

Botetourt

Brunswick

Buchanan

Buckingham

Campbell

Caroline

Carroll

Charles City

Charlotte

Chesterfield

Clarke

Craig

Culpeper

Cumberland

Dickenson

Dinwiddie

Essex

Fairfax

Fauquier

Floyd

Fluvanna

Franklin

Frederick

Giles

Gloucester

Goochland

Gray son

Greene

Greensville

Halifax
Forest Health Monitoring: Field Methods Guide

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Hanover

Henrico

Henry

-------

 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 8 of 9

(191) Washington

(095) James City

(097) King and Que

(099) King George

(101) King William

(103) Lancaster

(105) Lee

(107) Loudoun

(109) Louisa

(111) Lunenberg

(113) Madison

(115) Mathews

(117) Mecklenburg

(119) Middlesex

(121) Montgomery

(125) Nelson

(127) New Kent

(131) Northampton

(133) Northumberla

(135) Nottoway

(137) Orange

(139) Page

(141) Patrick

(143) Pittsylvania

(145) Powhatan

(147) Prince Edward

(149) Prince George

(153) Prince Willia

(155) Pulaski

(157) Rappahannock

(159) Richmond

(161) Roanoke

(163) Rockbridge

(165) Rockingham

(167) Russell

(169) Scott

(171) Sehenandoah

(173) Smyth

(175) Southampton

(177) Spotsylvania

(179) Stafford

(181) Surry

(183) Sussex

(185) Tazewell

(187) Warren

(35) Washington

(001) Adams

(003) Asotin

(005) Benton

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

(029)

(031)

(033)

(035)

(037)

(039)

(041)

(043)

(045)

(047)

(049)

(051)

(053)
Forest Health Monitoring: Field Methods Guide

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(055)

(057)

(059)

(061)

(063)

(065)

(067)

(069)

(071)

(073)

(075)

(077)

(54)

(001)

(091)

(003)

(005)

(007)

(009)

(011)

(013)

(015)

(017)

(019)

(021)

Chelan

Clallam

Clark

Columbia

Cowlitz

Douglas

Ferry

Franklin

Garfield

Grant

Grays Harbor

Island

Jefferson

King

Kitsap

Kittitas

Klickitat

Lewis

Lincoln

Mason

Okanogan

Pacific

Pend Oreilie

Pierce

San Juan

Skagit

Skamania

Snohomish

Spokane

Stevens

Thurston

Wahkiakum

Walla Walla

Whatcom

Whitman

Yakima

West Virginia

Barbour

Highland

Berkeley

Boone

Braxton

Brooke

Cabell

Calhoun

Clay

Doddridge

Fayette

Gilmer

(023)

(025)

(027)

(029)

(031)

(033)

(035)
Forest Health Monitoring: Field Methods Guide

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(037)

(039)

(041)

(043)

(045)

(049)

(051)

(053)

(047)

(055)

(057)

(059)

(065)

(061)

(063)

(069)

(071)

(073)

(075)

(077)

(079)

(081)

(083)

(085)

(087)

(089)

(091)

(093)

(095)

(097)

(099)

(101)

(103)

(105)

(107)

(109)

Grant

Greenbriar

Hampshire

Hancock

Hardy

Harrison

Jackson

Jefferson

Kanawha

Lewis

Lincoln

Logan

Marion

Marshall

Mason

McDowell

Mercer

Mineral

Mingo

Moegan

Monogalia

Monroe

Ohio

Pendleton

Pleasant

Pocahontas

Preston

Putnam

Raleigh

Randolph

Ritchie

Roane

Summers

Taylor

Tucker

Tyler

Upshup

Wayne

Webster

Wwetzel

Wirt

Wood

Wyoming

(55) Wisconsin

(001) Adams
Forest Health Monitoring: Field Methods Guide

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(003) Ashland

(005) Barren

(007) Bayfield

(009) Brown

-------

 EMAP Forest Monitoring, Appendix B, Rev. No. 0, October, 1994, Page 9 of 9

(011)

(013)

(015)

(017)

(019)

(021)

(023)

(025)

(027)

Buffalo

Burnett

Calumet

Chippewa

Clark

Columbia

Crawford

Dane

Dodge

(029)

(031)

(033)

(035)

(037)

(039)

(041)

(043)

(045)

(047)

(049)

(051)

(053)

(055)

(057)

(059)

(061)

(063)

(065)

(067)

(069)

(071)

(073)

(075)

(077)

(078)

(079)

(081)

(083)

(085)

Door

Douglas

Dunn

Eau Claire

Florence

Fond du Lac

Forest

Grant

Green

Green Lake

Iowa

Iron

Jackson

Jefferson

Juneau

Kenosha

Kewaunee

La Crosse

Lafayette

Langlade

Lincoln

Manitowoc

Marathon

Marinette
Forest Health Monitoring: Field Methods Guide

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Marquette

Menominee

Milwaukee

Monroe

Oconto

Oneida

(087)

(089)

(091)

(093)

(095)

(097)

(099)

(101)

(103)

(105)

(107)

(109)

(111)

(113)

(115)

(117)

(119)

(121)

(123)

(125)

(127)

(129)

(131)

(133)

(135)

(137)

(139)

(141)

Outagamie

Ozaukee

Pepin

Pierce

Polk

Portage

Price

Racine

Rich land

Rock

Rusk

St. Croix

Sauk

Sawyer

Shawano

Sheboygan

Taylor

Trempealeau

Vernon

Vilas

Walworth

Washburn

Washington

Waukesha

Waupaca

Waushara

Winnebago

Wood

-------

 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 1 of 10

 Appendix C

 Forest Type Descriptions

Eastern Forest Type Descriptions

0000 WHITE/RED/JACK PINE GROUP

 0010 Jack pine: Associates-red pine, northern pin oak, quaking and bigtooth aspen, paper 

birch, black

 spruce, and white spruce. Sites-generally driest, most porous sands but also on more moist,

sandy

 soils near swamps and on rocky hills and lodges.
Forest Health Monitoring: Field Methods Guide

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 0020 Red pine: Associates-white, jack, or pitch pine; northern pineoak; white oak; red 

maple; paper

 birch; quaking and bigtooth aspen, chestnut oak, northern red oak, and hemlock. Sitesspotty

 distribution in Northeast and sandy and gravelly locations or dry sandy loam soils; often in

plantations.

 0030 White pine: Associates-pitch pine, gray birch, aspen, red maple, pin cherry, white 

oak, paper

 birch, sweet birch, yellow birch, black cherry, white ash, northern red oak, sugar maple, 

basswood,

 hemlock, northern white-cedar, yellow-poplar, white oak, chestnut oak, scarlet oak, and 

shortleaf pine.

 Sites-wide variety, but best development on well drained sands and sandy loams.

 0040 White pine/hemlock: Associates-beech, sugar maple, basswood, red maple, yellow birch,

black

 cherry, white ash, paper birch, sweet birch, northern red oak, white oak, chestnut oak, 

yellow-poplar,

 and cucumbertree. Sites-wide variety but favors cool locations, moist ravines, and north 

slopes.

 0050 Hemlock: Associates-beech, sugar maple, yellow birch, basswood, red maple, black cherry,

 white ash, white pine, paper birch, sweet birch, northern red oak, and white oak. Sites-cool

locations,

 moist ravines, and north slopes.

 0060 Scotch pine: plantation type, not naturally occurring.

 0070 Ponderosa pine:

0100 SPRUCE/FIR GROUP

 0110 Balsam fir: Associates-black, white, or red spruce; paper or yellow birch; quaking or

bigtooth

 aspen, beech; red maple; hemlock; tamarack; black ash; or northern white-cedar. Sites-upland

sites

 on low lying moist flats and in swamps.

 0120 Black spruce: Associates-white spruce, balsam fir, jackpine, quaking aspen, paper 

birch,

 tamarack, northern white-cedar, black ash, or red maple. Sites-acid peat swamps but also on 

moist

 flats and uplands.

 0130 Red spruce/balsam fir: Associates-red maple, paper birch, whitepine, hemlock, white 

spruce,

 and northern white-cedar. Sites-moderately drained to poorly drained flats or on thin-soiled

upper

 slopes.

 0140 Northern white-cedar: Associates-tamarack, yellow birch, paperbirch, black ash, red 

maple,

 white pine, and hemlock. Sites-slow drainage (not stagnant bogs) areas that are not 

strongly acid.

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 2 of 10

 0150 Tamarack (eastern larch): Associates-northern white cedar, red maple, black ash, and 

quaking

 aspen. Sites-wet swamps.

 0160 White spruce: Associates-black spruce, balsam fir, quaking aspen, paper birch, jack 

pine, red

 spruce, sugar maple, beech, and yellow birch. Sites-moist, sandy loam or alluvial soilsfound on

 many different sites but especially typical of stream banks, lake shores, and adjacent 

slopes.

 0170 Norway spruce: plantation type, not naturally occurring.

 0180 Larch (introduced): plantation type, usually Japanese larch, European larch, or a hybrid

of the

 two (Dunkeld larch) - not naturally occurring. Sites-well-drained uplands; heavy plantation

in New

 York.
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 0190 Red Spruce: Associates-vary widely and may include red maple, yellow birch, eastern 

hemlock,

 eastern white pine, white spruce, northern white-cedar, paper birch, pin cherry, gray birch,

mountain

 ash, beech, striped maple, sugar maple, northern red oak, red pine, and aspen. Sitesinclude

 moderately well drained to poorly drained flats and thin-slopes and on varying acidic soils 

in abandoned

 fields and pastures. This code should be used where red spruce comprises a plurality or 

majority of

 the stand's stocking but where balsam fir is either nonexistent or has very little 

stocking. Otherwise

 the plot would be coded 130, red spruce/balsam fir.

0200 LONGLEAF/SLASH PINE GROUP

 0210 Longleaf pine: Longleaf pine occurs as a pure type or comprises a majority of the 

trees in the

 overstory. Associates-slash, loblolly and shortleaf pine, southern red oak, blackjack oak, 

water oak,

 persimmon, and sweetgum. Sites-those areas that can and do burn on a periodic basisusuaily

 occurs on middle and upper slopes with a low severity of hardwood and brush competition. 

Regional

 distribution-coastal plain and piedmont units.

 0220 Slash pine: Slash pine is pure or provides a majority of the stocking. Associates-on 

moist sites;

 a wide variety of moist-site hardwoods, pond pine, and pondcypress. On dry sites; a wide 

variety of

 dry-site hardwoods, longieaf, loblolly, and sand pine. Sites-both moist and well-drained 

flatwoods, and

 bays. Regional distribution-coastal plain and piedmont units from North Carolina to Florida.

0300 LOBLOLLY/SHORTLEAF PINE GROUP

 0310 Loblolly pine: Associates-sweetgum, southern red oak, post oak, blackjack oak, 

blackgum,

 yellow-poplar, and pond pine. Sites-in Delaware and Maryland both on upland soils with 

abundant

 moisture but good drainage and on poorly drained depressions.

 0320 Shortleaf pine: Associates-white oak, southern red oak, scarlet oak, black oak, 

hickory, post oak,

 blackjack oak, blackgum, red maple, pitch pine, and Virginia pine. Sites-low, well drained 

ridges to

 rocky, dry, south slopes and the better drained spur ridges on north slopes and also on old 

fields.

 0330 Virginia pine: Associates-shortleaf pine, white oak, chestnut oak, southern red oak, 

black oak,

 sweetgum, red maple, blackgum, and pitch pine. Sites-dry sites, often abandoned fields.

 0340 Sand pine: Sand pine occurs in pure stands or provides a majority of the 

stocking.

 Associates-dwarf live oak, dwarf post oak, turkey oak, persimmon, and longieaf pine. Sitesdry,

 acidic, infertile sands. Regional distribution-found chiefly in the central peninsula and 

panhandle of

 Florida, although planted stands extend into the sandhills of Georgia and South Carolina.

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 3 of 10

 0350 Eastern redcedar: Associates-gray birch, red maple, sweetbirch, Virginia Pine, shortleaf

pine,

 oak. Sites-usually dry uplands and abandoned fields on limestone outcrops and other shallow

soils

 but can grow well on good sites.

 0360 Pond pine: Associates-loblolly pine, sweetgum, baldcypress, and Atlantic white-cedar. 

Sites-

 rare, but found in southern New Jersey, Delaware, and Maryland in low, poorly drained acres,

swamps,

 and marshes.

 0370 Spruce pine: Spruce pine comprises a majority of the stocking. Associat"es--any of the 

moist site

 softwood or hardwood species. Sites-moist or poorly drained areas. Regional distribution-this
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type

 is rarely encountered and is found almost exclusively in the coastal plain.

 0380 Pitch pine: Associates-chestnut oak, scarlet oak, table-mountain pine, black oak, and 

blackgum.

 Sites-relatively infertile ridges, dry flats, and slopes.

 0390 Table-mountain pine: Associates-chestnut oak, scarlet oak, pitch pine, pine, and 

black oak.

 Sites-poor, dry, often rocky slopes.

0400 OAK/PINE GROUP

 0410 White pine/northern red oak/white ash: Associates-red maple, basswood, yellow birch, 

bigtooth

 aspen, sugar maple, beech, paper birch, black cherry, hemlock, and sweet birch. Sites-deep, 

fertile,

 well-drained soil.

 0420 Eastern redcedar/hardwood: Associates-oak, hickory, walnut, ash, locust, dogwood, 

blackgum,

 hackberry, winged elm, shortleaf pine, and Virginia pine. Sites-usually dry uplands and 

abandoned

 fields.

 0430 Longleaf pine/scrub oak: Longleaf pine and scrub oaks-primarily turkey, bluejack, 

blackjack, and

 dwarf post oak-comprise the type. Associates-southern scrub oaks in the understory. Sitescommon

 on sandhills where soils are dry, infertile, and coarse textured. Regional distributioncoastal plain and

 piedmont units.

 0440 Shortleaf pine/oak: Associates-(oaks generally include white, scarlet, blackjack, black,

post, and

 southern red) hickory, blackgum, sweetgum, Virginia pine, and pitch pine. Sites-generally in

dry, low

 ridges, flats, and south slopes.

 0450 Virginia pine/southern red oak: Associates-black oak, scarlet oak, white oak, post oak,

blackjack

 oak, shortleaf pine, blackgum, hickory, pitch pine, table-mountain pine, chestnut oak. 

Sites-dry slopes

 and ridges.

 0460 Loblolly pine/hardwood: Associates-wide variety of moist and wet site hardwoods 

including

 blackgum, sweetgum, yellow-poplar, red maple, white and green ash, and American elm; on 

drier sites

 associates include southern and northern red oak, white oak, post oak, scarlet oak, 

persimmon, and

 hickory. Sites-usually moist to very moist though not wet all year but also on drier sites.

 0470 Slash pine/hardwood: Slash pine and a variable mixture of hardwoods comprise the 

type.

 Associates-codominant with the slash pine component are sweetbay, blackgum, loblollybay,

 pondcypress, pond pine, Atlantic white-cedar, red maple, ash, and water oak. Sitesundrained or

 poorly drained depressions such as bays or pocosins and along pond margins. 

Regional

 distribution-primarily coastal plain units.

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 4 of 10

 0480 Scarlet oak: Associates-black oak, southern red oak, chestnut oak, white oak, post oak,

hickory,

 pitch pine, blackgum, sweetgum, black locust, sourwood, dogwood, shortleaf pine, and 

Virginia pine.

 Sites-dry ridges, south- or west-facing slopes and flats but often moister situations 

probably as a result

 of logging or fire.

 0490 Other oak/pine:

0500 OAK/HICKORY GROUP

 0510 Post, black, or bear oak: Associates-blackjack oak, hickory, southern red oak, white 
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oak, scarlet

 oak, shingle oak, live oak, shortleaf pine, Virginia pine, blackgum, sourwood, red maple, 

winged elm,

 hackberry, chinkapin oak, shumard oak, dogwood, and eastern redcedar. Sites-dry uplands and

 ridges.

 0520 Chestnut oak: Associates-scarlet oak, white oak, black oak, post oak, pitch pine, 

blackgum,

 sweetgum, red maple, red oak, shortleaf pine, Virginia pine. Sites-rocky outcrops with thin

soil, ridge

 tops.

 0530 White oak/red oak/hickory: Associates-scarlet oak, bur oak, pinoak, white ash, sugar 

maple, red

 maple, walnut, basswood, locust, beech, sweetgum, blackgum, yellow-poplar, and dogwood. 

Sites-

 wide variety of well drained upland soils.

 0540 White oak: Associates-black oak, northern red oak, bur oak, hickory, white ash, yellowpoplar.

 Sites-scattered patches on upland, loamy soils but on drier sites than type 530.

 0550 Northern red oak: Associates-black oak, scarlet oak, chestnut oak, and yellow-poplar. 

Sites-

 spotty distribution on ridge crests and north slopes in mountains but also found on rolling 

land, slopes,

 and benches on loamy soil.

 0560 Yellow-poplar/white oak/northern red oak: Associates-blackoak, hemlock, blackgum, and 

hickory.

 Sites-northern slopes, coves, and moist flats.

 0562 Sweetgum/yellow-poplar: Associates-red maple, white ash, green ash, and other moist 

site

 hardwoods. Sites-generally occupies moist, lower slopes.

 0564 Yellow-poplar: Associates-black locust, red maple, sweet birch, cucumbertree, and 

other

 moist-site hardwoods (except sweetgum, see type 562) and white oak and northern red oak 

(see type

 560). Sites-lower slopes, northerly slopes, moist coves, flats, and old fields.

 0570 Southern scrub oak: This forest cover type consists of a mixture of scrub oaks that may

include

 several of the following species: turkey oak, bluejack oak, blackjack oak, dwarf post oak,

and dwarf

 live oak. Sites-dry sandy ridges-the type frequently develops on areas formerly occupied by 

longleaf

 pine. Regional distribution-common throughout all coastal plain units and into the lower 

piedmont.

 0580 Black locust: Associates-many species of hardwoods and hardpines may occur with it in 

mixture,

 either having been planted or from natural seeding. Sites-may occur on any well-drained soil

but best

 on dry sites, often in old fields.

 0590 Mixed central hardwoods: Associates~Any mixture of hardwoods of species typical of the 

upland

 central hardwood region, should include at least some oak. Sites-wide variety of upland 

sites.

 0592 Sassafras/persimmon: Associates-elm, eastern redcedar, hickory, ash, sugar 

maple,

 yellow-poplar, and oaks. Sites-abandoned farmlands and old fields.

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 5 of 10

 0594 Central hardwood reverting field: Associates--any commercial or noncommercial pioneer 

species

 commonly found in the oak/hickory region except black locust (see type 0580), yellow-poplar 

(see type

 564), sassafras or persimmon (see type 0592), or eastern redcedar (see type 0350). Sitesabandoned

 farmlands and old fields.

0600 OAK/GUM/CYPRESS GROUP
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 0610 Swamp chestnut oak/cherrybark oak: Associates-white ash, hickory, white oak, shumard 

oak,

 blackgum, sweetgum, southern red oak, post oak, American elm, winged elm, yellow-poplar, 

and

 beech. Sites-within alluvial flood plains of major rivers on all ridges in the terraces and

on the best

 fine sandy loam soils on the highest first bottom ridges.

 0620 Sweetgum/Nuttall oak/willow oak: Associates-green ash, American elm, pecan, cottonwood, 

red

 maple, honeylocust, and persimmon. Sites-very wet.

 0630 Sugarberry/American elm/green ash: Associates-pecan, blackgum, persimmon, honeylocust, 

red

 maple, hackberry, and boxelder. Sites-low ridges and flats in flood plains.

 0650 Overcup oak/water hickory: Associates-willow oak, American elm, green ash, 

hackberry,

 persimmon, and red maple. Sites--in South within alluvial flood plains in low, poorly 

drained flats with

 clay soils; also in sloughs and lowest backwater basins and low ridges with heavy soils that

are subject

 to late spring inundation.

 0660 Atlantic white-cedar: Associates-North includes gray birch, pitch pine, hemlock, 

biackgum, and

 red maple. South includes pond pine, baldcypress, and red maple. Sites-usually confined 

to

 sandy-bottomed, peaty, interior, and river swamps, wet depressions, and stream banks.

 0670 Baldcypress/water tupelo: Associates-willow, red maple, American elm, persimmon, 

overcup

 oak, and sweetgum. Sites-very low, poorly drained flats, deep sloughs, and swamps wet most

all the

 year.

 0680 Sweetbay/swamp tupelo/red maple: Associates-blackgum, loblolly and pond pines, American

 elm, and other moist-site hardwoods. Sites-very moist but seldom wet all year-shallow ponds,

muck

 swamps, along smaller creeks in Coastal Plain (rare in Northeast).

 0690 Palm/mangrove/other tropical:

 0692 Mangrove: Forests in which mangrove comprises a majority of the stocking.

 Associates-cabbage palm on some of the higher sites in the area. Sites-predominantly salt 

marshes;

 mangrove frequently develops its own island or shoreline made up of a dense mat of root 

structures.

 Regional distribution-restricted to South Florida and the Keys.

 0694 Palm: Cabbage palm comprises a plurality of the stocking. This type can occur as a pure

stand.

 Associates-slash pine, dwarf live oak, live oak, laurel oak, water oak, baldcypress, 

pondcypress, red

 maple, redcedar, redbay, and loblolly pine. Sites-coastal dunes and floodplains of major 

rivers north

 of Florida; in Florida the type occurs on moist sites such as marsh islands, marshy 

shorelines, and

 floodplains. Regional distribution-coastal plain units from North Carolina to the southern 

tip of Florida.

 0696 Other tropical: Forests in which other tropical species, singly or in combination, 

comprise a

 majority of the stocking. The species may include melaleuca, Australian pine, sable palm, 

and any of

 the miscellaneous citrus species encountered in the southernmost region of Florida. 

Associates-wide

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 6 of 10

 variety of species indigenous to south Florida. Sites-wide variety. Regional distributionrestricted

 exclusively to south Florida.

0700 ELM/ASH/RED MAPLE GROUP

 0710 Black ash/American elm/red maple: Associates-silver maple, swampwhite oak, sycamore, pin

 oak, blackgum, white ash, and cottonwood. Sites-moist to wet areas, swamps, gullies, and 
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poorly

 drained flats.

 0720 River birch/sycamore: Associates-red maple, black willow, and other moist-site 

hardwoods.

 Sites-moist soils at edges of creeks and rivers.

 0730 Cottonwood: Associates-willow, white ash, green ash, and sycamore. Sites-streambanks 

where

 bare, moist soil is available.

 0740 Willow: Associates-cottonwood, green ash, sycamore, pecan,. American elm, red maple, 

and

 boxelder. Sites-streambanks where bare, moist soil is available.

 0750 Sycamore/pecan/American elm: Associates-boxelder, green ash, hackberry, silver 

maple,

 cottonwood, willow, sweetgum, and river birch. Sites-bottomlands, alluvial flood plains of 

major rivers.

0800 MAPLE/BEECH/BIRCH GROUP

 0810 Sugar maple/beech/yellow birch: Associates-basswood, red maple, hemlock, northern red 

oak,

 white ash, white pine, black cherry, sweet birch, American elm, rock elm, and eastern 

hophornbeam.

 Sites-fertile, moist, well-drained sites.

 0820 Black cherry: Associates-sugar maple, northern red oak, red maple, white ash, basswood,

sweet

 birch, butternut, American elm, and hemlock. Sites-fertile, moist, well-drained sites.

 0830 Black walnut: Associates-yeilow-poplar, white ash, black cherry, basswood, beech, sugar

maple,

 oaks, and hickory. Sites-coves and well-drained bottoms.

 0840 Red maple/northern hardwoods: Associates-the type is dominated by red maple and some of

 the wide variety of northern hardwood associates include sugar maple, beech, birch, aspen, as

well

 as some northern softwoods like white pine, red pine, and hemlock; this type is often manmade and

 may be the result of repeated cuttings. Sites-uplands.

 0850 Red maple/central hardwoods: Associates-the type is dominated by red maple and some of 

the

 wide variety of central hardwood associates include upland oak, hickory, yellow-poplar, black

locust,

 sassafras as well as some central softwoods like Virginia and shortleaf pines. Sites-uplands

(see type

 0840).

 0880 Northern hardwood reverting field: Associates-any commercial or noncommercial 

pioneer

 species commonly found in the northern hardwood region except aspen (see type 0910) and gray

birch

 (see type 0930). Sites-abandoned farmlands and old fields.

 0890 Mixed northern hardwoods: Associates-wide variety of upland hardwoods typical of 

northern

 hardwood or cover hardwood types where the sugar maple-beech-yellow-birch combination or

 blackcherry alone do not comprise a plurality of stocking. Sites-upland, well drained, 

fertile.

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 7 of 10

0900 ASPEN/BIRCH GROUP

 0910 Aspen: Associates-paper birch, pin cherry, bur oak, green ash, American elm, balsam 

poplar,

 and boxelder. Sites-all kinds of soils except very driest sands and wettest swamps; found 

on burns,

 clearcuts, and abandoned land.

 0920 Paper birch: Associates-aspen, white pine, yellow birch, hemlock, red maple, northern 

red oak,

 and basswood. Sites-wide range of upland site, common on burns or clearcuts.

 0930 Gray birch: Associates-oaks, red maple, white pine, and others. Sites-poor soils of 
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abandoned

 farms and burns.

 0998 INDETERMINATE-to be used only when a plot cannot be classified into one of the types 

listed

 above. A detailed note describing the situation must appear in the general notes.

 0999 NONSTOCKED-the site qualifies as forest but is presently stocked with too few trees to 

assign

 a forest type.

Western Forest Type Descriptions

 All Western Forest Type Groups, for the purpose of Condition Classification, are based on 

the

predominance of stocking, except for codes 9001 and 3097 below. The stocking will be based on 

some

field procedure application (a tree count by species) using a predetermined, regionally 

appropriate prism.

 See the instructions for determining Forest Type calls in the two special mixed stand 

conditions (codes

9001 and 3097) below.

1200 DOUGLAS-FIR TYPE GROUP

 1201 Bigcone Douglas-fir

 1202 Douglas fir

2100 MAJOR PINE TYPE GROUP

 2108 Lodgepole pine

 2116 Jeffrey pine

 2117 Sugar pine

 2119 Western white pine

 2122 Ponderosa pine

3000 WESTERN FIR-SPRUCE TYPE GROUP

 3010 Fir

 3011 Pacific silver fir

 3014 Bristlecone fir

 3015 White fir

 3016 Fraser Fir

 3017 Grand fir

 3019 S.ubalpinefir

 3020 California red fir

 3021 Shasta red fir

 3022 Noble fir

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 8 of 10

 3090 Spruce

 3092 Brewer spruce

 3093 Engelmann spruce

4000 HEMLOCK-SPRUCE TYPE GROUP

 4098 Sttka spruce

 4242 Western redcedar

 4263 Western hemlock

 4264 Mountain hemlock

5200 REDWOOD/SEQUIOA TYPE GROUP

 5211 Redwood

 5212 Giant sequoia

6300 WESTERN HARDWOODS

 6300 Acacia

 6310 Maple

 6312 Bigleaf maple

 6321 Rocky Mountain maple

 6350 Alder

 6351 Red alder

 6360 Madrone

 6361 Pacific madrone

 6370 Birch

 6374 Water birch

 6375 Paper birch

 6430 Chinkapin

 6431 Golden chinkapin

 6475 Curl leaf mountain mahogany
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 6478 Birch-leaf mountain mahogany

 6492 Pacific dogwood

 6510 Eucalyptus

 6540 Ash

 6542 Oregon ash

 6600 Walnut

 6631 Tanoak

 6660 Apple

 6661 Oregon crab apple

 6730 Sycamore

 6740 Cottonwood

 6746 Quaking aspen

 6747 Black cottonwood

 6748 Fremont cottonwood

 6749 Narrowleaf cottonwood

 6755 Mesquite

 6800 Oak

 6801 California Live oak

 6805 Canyon live oak

 6807 Blue oak

 6811 Engelmann oak

 6815 Oregon white oak

 6818 California black oak

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 9 of 10

 6821 California white oak

 6826 Chinkapin oak

 6839 Interior live oak

 6848 Western oak-deciduous

 6849 Western oak-evergreen

 6920 Willow

 6981 California-laurel

7000 MISCELLANEOUS WESTERN SOFTWOODS

 7041 Port-orford-cedar

 7042 Alaska-cedar

 7051 Arizona cypress

 7060 Juniper

 7062 California juniper

 7064 Western juniper

 7065 Utah juniper

 7073 Western larch

 7081 Incense-cedar

 7101 Whitebark pine

 7102 Bristlecone pine

 7103 Knobcone pine

 7104 Foxtail pine

 7106 Common pinyon

 7109 Coulter pine

 7113 Limber pine

 7114 Mexican white pine

 7120 Bishop pine

 7124 Monterey pine

 7127 Grey pine

 7133 Singleleaf pinyon

 7137 Washoe pine

 7138 Four-leaved pine

 7140 Mexican pinyon

 7141 Pinyon-Juniper

 7231 Pacific yew ,

 7251 California Torreya

 7990 Arizona ironwood

 7991 Salt cedar

 Forest Type codes required for FIA reports will be computed at each FIA regional office 

using existing

computer algorithms.

9000 MIXED CONIFERS

 9001 Mixed conifers, California. Algorithm for determining this type: This pertains only to

conifer

stands with a mix of Douglas-fir, white fir, red fir, ponderosa pine, Jeffery pine, sugar pine, 

and incense

cedar:

 1) If Douglas-fir occurs as the plurality stocking species in any of the following 
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counties (see county

code list section 2.11): Codes 15, 23,41,45,55, 81,85,87, 97, then the Forest Type is Dougl~Mir 

(1202).

For other counties, if the predominant species is Douglas-fir in a mix with other species, th?> 

•. -est Type

is Mixed Conifer (9001). If these conditions do not exist, then go to 2.

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 EMAP Forest Monitoring, Appendix C, Revision 0, October, 1994, Page 10 of 10

 2) Anytime sugar pine or incense cedar occur as a plurality in a mix of the above Mixed 

Conifers

species, we have a Mixed Conifer Type (9001). If these conditions do not exist, then go to 3.

 3) Anytime there is a combined stocking of over 50% in Jeffery and Ponderosa pine, the 

Forest Type

call goes to the predominant pine (either 2116 or 2122). Otherwise, go to 4.

 4) Anytime there is a combined stocking of over 50% in white fir, California red fir, 

and/or shasta red

fir, the Forest Type call goes to the predominating fir (either 3015, 3020, or 3021). 

Otherwise, go to 5.

 5) If there is over 80% stocking in any of the other species (1 above), the type call is 

given to the

individual species with the stocking over 80%; see codes in Major Pine Group (2108-2122), 

above.

Otherwise, go to 6.

 6) All other combinations of the above Mixed Conifers species will be classed as Mixed 

Conifers

(9001).

3097 Mixed Engelmann spruce/subalpine fir. Algorithm for determining this type:

 1) If the combined stocking of Engelmann spruce and subalpine fir does not carry the 

plurality of

stocking, it is not a mixed type. The type is called on which other species carries the 

plurality (see above).

If the combined plurality is there, go to 2.

 2) If Engelmann spruce is greater or equal to 20% and subalpine fir is 0-19, the type is

given to

Engelmann spruce (see code 3093 above). Otherwise, go to 3.

 3) If Engelmann spruce stocking is less than 20% and subalpine fir stocking is greater than

0%, the

type is mixed Engelmann spruce/subalpine fir (3097). And, if Engelmann spruce and subalpine fir 

are both

greater or equal to 20%, the type is Mixed Engelmann spruce/subalpine fir (3097).

 4) There is one more condition: If subalpine fir has stocking greater than 0% and there 

is no

Engelmann spruce present, the type is Mixed Engelmann spruce/subalpine fir (3097). This 

is to

accommodate the fact that Intermountain FIA never sets up a category to take all subalpine fir 

stands in

the subalpine fir type (no pure subalpine fir type exists).

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 EMAP Forest Monitoring, Appendix D, Rev. No. 0, October, 1994, Page 1 of 3

 Appendix D

 Land Use Classifications

Overview

 The primary objective of land use classifications is to separate forest land from 

inaccessible and

nonforest land uses. The land use classes recognized by FHM have largely been adopted from FIA 

in

order to retain consistency between FHM and FIA data sets.

Forest Land

 Forest is land that is at least 10 percent stocked with tree or woodland species, or 

currently nonstocked
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but formerly having such stocking; and not developed for use other than growing trees. Thus, 

stands that

have recently been clearcut, but not developed to another land use still qualify as forest. 

Commercial tree

plantations (except orchards and Christmas trees) are classified as forest. Table 1 provides 

approximate

guidelines as to how many trees are necessary to meet the 10 percent stocking requirement.

Table 1. Number of Trees Required for 10% Stocking, by DBH Class

 DBH Class'

Size of Area

Inches

Seedlings

2

4

6

8

10

12

14

16

18

20

Centimeters

-

5

10

15

20

25

30

35

40

45

50

1 Acre

100

94

77

57

40

26

19

15

12

10

9

1/24 Acre

4

4

3

3

2

1

1

1

1

1

1

1 Hectare

250

234

192

142

100

65

48

38

30

25

22

1/60 Hectare

4

4

3

3

2

1

1

1

1
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1

1

'Seedlings, 2 inch (5 cm), and 4 inch (10 cm) trees occurring in clumps are counted as 1.

 To qualify as forest, the site in question must be attached to forest land that is at least 

1 acre (0.4

hectare) in area and at least 120 ft (36.6 m) wide. Note that wooded areas less than 120 ft 

(36.6 m) wide

are considered forest if attached to forest land that meets the minimum size requirements. 

Strips of trees

in a nonforest matrix that do not meet these minimum qualifications are not recognized as forest

and should

be assigned the same land use as the surrounding nonforest area.

 Within forested areas, include as forest such associated features as unimproved woods roads, 

firelines,

rock outcrops and natural openings less than 1 acre (0.4 ha), and streams less than 30 ft 

(9 m) wide). •

Exclude all other land uses developed by man, regardless of size (i.e., improved roads, utility 

rights-of-way,

house sites, canals).

 Forest land is subdivided into three different categories-timberland, reserved timberland, 

and woodland

(Land Use codes 01, 12 and 13, respectively). If any part of a plot is assigned one of these 

three land

uses, that entire plot is classified as a forest plot. Timberland is capable of producing 20 cu

ft of wood per

acre (1.4 m3/ha) per year, whereas woodland is not. Reserved timberland meets the minimum 

productivity

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requirements but has been withdrawn from commercial timber production by law. Examples of 

reserved

timberiand include national parks, wilderness areas, and some state parks.

 In some cases, the separation between timberiand and woodland is difficult. Follow regional 

FIA

procedures to separate timberiand from woodland in borderline cases. Since FHM sampling 

procedures

conducted on all three types of forest are identical, distinctions between timberiand and 

woodland are not

critical in such situations and can be verified with growth data obtained from the plot.

Inaccessible Forest

 Whole plots or portions of plots can be inaccessible because permission is denied by the 

landowner

(Land Use code 10), or because some hazardous condition prevents occupation of the site (Land 

Use code

11). Land Use codes 10 and 11 should not be utilized if the inaccessible area would 

otherwise be

classified nonforest. In such cases, use the appropriate nonforest land use code. However, if 

there is any

chance the site in question might be forest, classify it as inaccessible forest.

 If a potential forest plot is entirely inaccessible, it should be assigned a Current Plot 

Status of "3" if

permission has been denied, or "4" if it is a dangerous plot (Section 1). Procedures for 

recording plots that

are entirely inaccessible are outlined in Section 1.

Nonforest Land

 Nonforest is land currently developed for use other than growing trees; land that has never 

attained

the minimal stocking to qualify as forest; or land that does not meet the minimum area to 

qualify as forest.

Procedures for recording plots that are entirely nonforest are outlined in Section 1. Various 

nonforest land

uses recognized by FHM are defined as follows:

 Cropland (Land Use code 02). Land that has been actively cultivated within the past 2 

years, including

 orchards and Christmas tree plantations but excluding improved pasture.

 Improved Pasture (Land Use code 03). Land currently improved for grazing by fencing, 

cultivation,

 seeding, irrigation, or clearing of trees and brush.
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 Rangeland (Land Use code 04). Land on which the natural plant cover is composed of 

vegetation

 valuable for forage (native grasses, forbs, and shrubs) and less than 10 percent stocked 

with tree or

 woodland species.

 Idle Farmland (Land Use code 05). Former croplands, orchards, or improved pastures that 

have not

 been tended within the past 2 years and are less than 10 percent stocked with tree or 

woodland

 species.

 Other Farmland (Land Use code 06). This includes area such as farmsteads, bams, and 

other

 buildings.

 Urban and other development (Land Use code 07). These include suburban areas developed for

 residential, industrial, or recreational purposes; schools; cemeteries; improved roads; 

railroads; airports;

 beaches; powerlines and other rights-of-way; canals; or other nonforest land not included in

any other

 specified land use.

 Marsh (Land Use code 08). Land characteristically supporting low, herbaceous, or shrubby 

vegetation;

 intermittently covered with water; and jess than 10 percent stocked with trees or woodland 

species.

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Water (Land Use code 09). Streams, sloughs, and estuaries more than 30 ft (9 m) in width. 

Lakes,

reservoirs, and ponds more than 1 acre (0.4 ha) in size.

Rocky, barren, excessively steep terrain (Land Use code 14). Naturally occurring areas of rock 

talus,

outcrops, cliffs, or steep terrain that do not support 10 percent tree stocking.

Natural alpine clearings (Land Use code 15). Nonforested alpine openings that are not 

specifically

used as rangeland for domestic livestock. These areas are characterized as having native 

grasses,

forbs, and shrubs as the predominant cover.

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 EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 1 of 10

 Appendix E

 Safety Plan

Section/Title

 Page

1 Overview 2 of 10

2 Potential Field Hazards 2 of 10

3 Travel 2 of 10

 3.1 Defensive Driving 3 of 10

 3.2 Accident Reporting 3 of 10

 3.2.1 Operator's Responsibilities 3 of 10

 3.2.2 Supervisor's Responsibilities 3 of 10

 3.3 Travel itinerary 3 of 10

 3.4 Animal Travel 4 of 10

 3.4.1 Assigning and Handling Stock 4 of 10

 3.4.2 Horse Riding 5 of 10

 3.4.3 Packing x. . 6 of 10

4 Weather Extremes 6 of 10

5 Terrain 6 of10

6 Insect Pests, Poisonous Organisms, Large Mammals 7 of 10

7 Sampling and Sampling Equipment 7 of 10

8 Tree Hazards 8 of 10

9 Training 8 of 10

10 Documentation 8 of 10

11 Personal Protection 10 of 10

12 Accident Reporting 10 of 10

13 Safety Equipment 10 of 10

14 Visitor Safety Precautions 10 of 10
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1 Overview

 Safety is a critical component of any field operation. Field personnel must be aware of 

potential safety

hazards, follow all project safety protocol and equipment guidelines, and be prepared for 

emergency

situations. This plan addresses potential safety hazards of field sampling and identifies 

required safety

protocols. Individual federal, state, and private participants .must also follow their 

individual agency safety

guidelines that supplement requirements outlined in this plan.

 Regional coordinators are responsible for the appropriate safety training being completed 

during field

crew training prior to the field season.

(NOTE: Operations, field crew, and supervisory personnel involved in FHM studies must read and

fully

understand all safety procedures contained in this plan.)

2 Potential Field Hazards

 Field samplers will encounter hazardous field operations about which they must be aware and 

informed

concerning proper precautions. Some potential hazards discussed in this section are:

 • Travel.

 • Weather extremes.

 • Terrain.

 • Insect pests, poisonous organisms, large mammals.

 • Sampling equipment (firearms).

 • Tree hazards.

 • Sampling.

3 Travel

 Vehicles used for traveling on backroads should be well maintained to ensure safe 

travel. Clean

windows and headlights frequently to reduce dirt and grime buildup from off-road travel. Fourwheel drive

vehicles and vehicles with high clearance are preferred. Table 1 lists items required for field

vehicles.

Table 1. Required Vehicle Items

 1. Spare tire, jack, lug wrench

 2. Fire extinguisher

 3. Shovel

 4. Winch/come-along *

 5. Flashlight

 6. Spare fuses

 7. Tow strap*

 8. Gas can

9. Cleaning fluid, wipes

10. Jump cables

11. Flares

12. Short wave radio *

13. Toolkit

14. Spare belts & hoses

15. Accident reporting kit

16. Water container

 Suggested in at least one vehicle as determined by the regional coordinator.

 Wear seat belts at all times while the vehicle is in motion. Drivers must follow all rules 

and regulations

of the state in which they are traveling. Never use a vehicle which is unsafe. Make necessary 

repairs as

soon as any unsafe condition develops. If long trips to remote sites occur, acquire extra 

gasoline and store

it in an approved carrying container. Store extra potable water in vehicles.

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3.1 Defensive Driving

 Defensive driving training and certification is strongly suggested and may be required at 

the discretion
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of the regional coordinator.

 1. Make sure driver is well-rested and alert.

 2. Ensure any medication taken does not cause drowsiness.

 3. Limit daily travel to 400 miles per person. If possible, rotate driving 

responsibilities.

 4. Make all drivers aware of the travel itinerary and planned routes. Vehicles should 

attempt to travel

 within view of each other.

 5. If possible, drivers should not ride alone.

 6. All passengers must wear seat belts.

 7. No smoking is allowed in vehicles.

 8. No drinking and driving. Use the designated driver system.

3.2 Accident Reporting

3.2.1 Operator's Responsibilities

 Drivers should follow accident-reporting protocols of their agency. They must know and 

understand

these protocols. Follow these procedures after an accident:

 1. Stop immediately and determine whether anyone is injured. Help any injured secure 

prompt

 medical care.

 2. Take all precautions to prevent additional accidents by placing flares and stationing 

persons to

 direct traffic. . .

 3. Notify all proper authorities as required by law and your supervisor and regional 

logistics

 lead/coordinator.

 4. Do not sign any papers or make any statements concerning liability except as instructed

by your

 agency's guidelines.

 5 If practicable, fill out a motor vehicle accident report according to your applicable 

federal or state

 guidelines. Specific guidelines will be in the vehicle. You can fill out the report 

later, but it must

 be submitted to the supervisor before the close of business the following day.

 6. If you receive a citation, subpoena, summons, tag, or ticket as a result of driving a 

project vehicle,

 you should notify your supervisor immediately.

 3.2.2 Supervisor's Responsibilities

 Whenever a vehicle operator is injured and cannot comply with the above requirements, the 

field

 supervisor should report the accident to the state, county, or municipal authorities as required

by law, and

 complete and process applicable federal or state forms. Supervisors should immediately notify 

the regional

 coordinator or his/her representative of the accident so that an investigating officer can be 

appointed.

 3.3 Travel Itinerary

 Use the crew update system (see Section 8) to communicate travel itineraries to management.

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3.4 Animal Travel (from the USDA Health and Safety Code Handbook on Stock,

Pack, and Riding Safety)

 Accept only animals known to have or at least display no dangerous habits. Make an effort to

discover

dangerous habits of strange animals without endangering yourself. If dangerous habits are 

discovered and

cannot be corrected easily, remove the animals from service. Assign only thoroughly experienced 

persons

the job of breaking and training saddle and pack stock. Stock used by employees must be gentle 

and

properly broken.

3.4.1 Assigning and Handling Stock

 Use care in assigning stock to employees; all stock can be potentially dangerous.

 Speak to animals when approaching them; avoid approaching them from the rear.
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 Handle animals carefully after prolonged layoffs.

 Always lead an animal around after being saddled and before being mounted or packed. Keep a 

firm

hold on reins or lead rope. Never wrap them around the hand. The lead rope should be 

approximately

10 feet in length and should be smoothly braided at the free end with no knots or loops. Avoid 

excess lead

rope that may become entangled with hands or feet.

 Never carry equipment on a saddle horse. Do not carry tools and equipment in your hands 

while

riding.

 Before saddling, and at the end of each day's use, brush stock. Rub down lathered horses 

with a cloth

and walk them until dry.

 When tying a horse:

 1. Avoid slack that might entangle horse or person. Tie with no more than 4 feet of slack 

and make

 the tie at least 4 feet above the ground.

 2. Avoid tying to a wire fence.

 3. Never position yourself directly in front of a solidly tied animal.

 4. Tie horse to an object he cannot walk completely around, whenever possible.

 5. Use a halter if the horse is to be tied for long periods. Use a rolling slipknot around 

the object to

 which the horse is to be tied. Never use the bridle reins to tie an animal.

 6. Use cotton ropes at least Va-inch diameter for picket and lead ropes.

 7. Unless picketing, never tie a horse to a small log or any other object the horse can 

move. Slight

 movement of an object can frighten the animal.

 8. Stand or kneel to the side when hobbling animals.

 Keep stock away from loose wire. Clear away loose wire and other hardware.

 Never feed or water a sweaty horse until it has cooled off, except when on the trail, and 

use is to

continue after watering.

 Be specifically careful when feeding several horses together in a pasture or corral. Some 

of the most

gentle saddle animals are fighters at feeding time.

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3.4.2 Horse Hiding

 When saddling, always make sure rigging, latigos, and cinches are in condition.

 Wear riding boots, field boots, or workshoes that will not hang up in stirrups. See that 

only experienced

riders wear spurs.

 Wear snug-fitting clothing. Wear chaps in brushy country. Do not wear a hardhat.

 When off the horse, check position of blanket and saddle and tightness of cinch. Look for 

worn or

broken straps, cinches, reins, and in brushy country, for trash under blanket.

 When dismounting, move left foot back so ball of foot is in stirrup before swinging off.

 Mounting -

 Before mounting:

 1. Lead a horse a short distance after cinching.

 2. Check cinch again.

 3. Take up slack in reins.

 4. Bridle stock before mounting.

 5. Check stirrups for correct positions.

 a. Rider should stand close to left shoulder, facing animal's rear.

 b. Take mane or saddle horn in left hand, gripping reins firmly, near rein tight, off 

rein slack, so

 twist of wrist can pull horse to you if it becomes unruly.

 c. Turn back side of near stirrup toward rider.
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 d. Place left foot in stirrup.

 e. Grasp saddle horn with right hand and swing into saddle quickly but lightly.

 f. Avoid scratching horse with spurs or heels when mounting.

 6. Insert only toe of boot into stirrup. Do not shove feet clear into stirrups. If wearing

field shoes, ride

 on balls of feet.

 Riding --

 1. Be alert to animal's movements and guide it firmly but gently. Test animal's reining 

habits. Do not

 hold a tight rein unless necessary to restrain forward movements.

 2. Sit straight in the saddle and keep reins gathered in so horse knows you are in command.

For

 comfort, carry about half of your weight in the stirrup and the other half on your 

buttocks.

 3. Be alert for insects and animals that may spook your stock.

 4. Never wrap or tie reins around the saddle horn.

 5. Never ride a horse when lightening storm is nearby.

 6. Always keep lead ropes free when leading stock while riding a saddle horse. Never tie 

the lead

 rope around the lead horse's saddle horn or wrap rope around hand.

 7. Watch the slack in the lead rope to avoid animal's straddling or stepping over it, and 

to keep it from

 getting under the lead horse's tail.

 8. Get off and lead a horse across excessively rocky or steep terrain and corduroy, or 

pole bridges.

 9. Never run a horse on hard pavement, frozen ground, uphill, downhill, or in deep snow.

 10. Never shoot firearms while on horseback.

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 11. When riding, it is good practice to carry a sharp knife to cut rope, cinches, or pack 

straps in

 emergencies.

 12. If riding alone, carry a radio. If no radio is available, travel in pairs.

 13. Never ride stock bareback without a bridle. Have inexperienced riders always ride with 

a saddle.

3.4.3 Packing

 Always treat pack animals as dangerous.

 Have only trained people load or unload stock.

 Keep animal's back clean; keep saddle pad straight, saddle blanket smooth, saddle properly 

fitted and

tight, and side packs of nearly equal weight.

 Tie pack animals short to a solid post or hitching rack, with heads pulled slightly up.

 Coil lash and sling ropes. Hang on pack saddles until actual packing begins, and 

immediately after

unloading.

 Tie pack string together with rope so animals can free themselves in case of accident. A 

1/4-inch loop

tied to the rigging reins or pack saddles makes a good place to tie the lead ropes of an animal 

being led.

Make the rigging rope on a pack saddle about 1/4-inch size. If an animal in the string falls 

off a precipitous

trail, the rope can break, reducing the chances of injury to other stock in the pack string.

4 Weather Extremes

 The field crew leader should follow daily and weekly weather forecasts.

 Field crews should prepare for the summer weather conditions of heat and rain with 

appropriate gear.

 Each person should carry a day's supply of water. Bring extra water in transport vehicles. 

Apportion

field equipment and samples properly to all field crew members for transport in and out of the 

field. Each

field crew member should have a set of rain gear. Avoid working in thunderstorms. If caught 

in a

thunderstorm, set down all equipment made of metal and proceed to vehicles. If in a remote 

location, seek
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low ground. Do not lean against or seek shelter in tall or exposed trees.

5 Terrain

 Field crews will be exposed to dangerous terrain conditions such as:

 • Steep slopes.

 • Thick underbrush (thorns, roots, etc.).

 • Loose rock conditions.

 • Wet, slippery ground.

 • Stream/marsh lands.

 • Fence crossing.

 • Deep water.

 Field wear should include weather-proof field boots with ankle support and slip-resistant 

(Vibramtm or

similar material) soles. Long pants and shirts are required to reduce cuts and scrapes. Safety 

glasses are

suggested to protect against eye injury. All field crew members should wear a hard hat.

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6 insect Pests, Poisonous Organisms, Large Mammals

 Field personnel may be exposed to insect pests and poisonous organisms such as:

 • Mosquitoes • Bees/Hornets

 • Biackflies • Ticks (for example, Lyme disease and Rocky Mountain

 • Ants Spotted Fever)

 • Poison ivy • Snakes

 • Poison sumac • Poison oak

 The regional coordinator or logistics lead should complete a personal and medical information

form for

all field crew personnel (Figure 1) before field sampling begins. Other people visiting the 

plot, such as audit

staff or managers, should also complete a medical information form before travelling to the 

field. Keep a

copy on hand at the sampling site and distribute it to proper management personnel. This form 

lists crew

members and their allergies to insect pests and medicines. Proper medicine should be available 

for any

field crews with known allergic reactions to insects. Clothes covering the legs and arms can 

help protect

against insect pests. Insect repellant should be available to field crew members. Snake bite 

kits should

be available in regions known for poisonous snakes. Approach dogs with care. Consider dog 

repellant

as standard gear. Poison oak areas should be handled by applying TecNu"" or a similar product 

before

going into the field.

7 Sampling and Sampling Equipment

 Sampling can be hazardous if a person places undue strain upon himself or herself. During 

training,

proper use of equipment and the limitations of field crew personnel should be 

addressed.

 PERSONAL AND MEDICAL INFORMATION FORM

 NAME: 

 LOCAL ADDRESS: PERMANENT ADDRESS:

 LOCAL PHONE NUMBER: PERMANENT PHONE NUMBER:

 NEXT-OF-KIN NAME:

 ADDRESS:

 PHONE NUMBER:

 RELATIONSHIP TO YOU:

 HEALTH CONCERNS TO BE AWARE OF (please include allergies, etc.):

 DO YOU WEAR CONTACT LENSES? GLASSES?
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 DO YOU WEAR CORRECTIVE LENSES FOR READING? DRIVING? BOTH?

 • B you need to wear corrective lenses to do your job, please keep an extra pair with you 

at all times or else keep a copy of your

 proscription on hand.

Figure 1. Personal and Medical Information Form.

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 If not used properly and with care, some sampling equipment can be hazardous. Keep cutting

instruments (hand pruners, knives) sharp and closed when not in use. Maintain sheaths for 

cutting

instruments in good condition. Alert stock packers of sharp or awkward equipment before packing

so that

appropriate adjustments can be made. Take care in packing and transporting equipment in and out 

of the

field. Use equipment according to instructions and routinely examine it for damage.

 Wear gloves when possible when working with sampling equipment. Wear eye protection when 

digging

soil pits and pole pruning. Field crew personnel must wear hard hats when working near branch 

collection

activities or during local windy conditions.

 Each field crew should carry a first aid kit with the contents listed in Table 2. It is 

strongly suggested

that all field personnel be certified in CPR and first aid; this may be mandatory at the 

discretion of the

regional coordinator.

Table 2. Contents of a First Aid Kit Carried by Field Crews

 1. Small gauze pads (4)

 2. Large gauze pad (1)

 3. Large muslin bandages (2)

 4. Adhesive bandages (16)

 5. Eye dressing unit (1)

 6. Antiseptic unit of povidone iodine (1)

 7. Roll of 2-inch wide elastic bandage (1)

 8. Roll of adhesive tape (1)

9. Ophthalmic irrigation solution

10. Aspirin tablets

11. Forceps

12. Scissors

13. Medihaler-Epi (asthma)

14. Chlor-Amine tablets

15. Instructions for using above items

8 Tree Hazards

 Trees can present hazards including dead trees that remain upright or lean against other 

trees and

dead limbs which remain in branches. Upon disturbance during travel to, from, or at a site, 

and during

branch sampling, limbs and trees can fall. When traveling through the forest, be aware of 

hazards in the

overstory. Wear a hard hat at all times in the forest. Branch samplers should know the location

of each

field crew member and warn personnel when dropping or lowering branches.

9 Training

 During field training, review all aspects of the safety plan. Crew leaders should conduct 

a 5-minute

"refresher" safety training before beginning a new week's work. Field crew personal and 

medical

information forms (Figure 1) should be completed prior to training.

10 Documentation

 The Field Crew Personal and Medical Information Form (Figure 1) and Emergency Reference 

Form

(Figure 2) should be completed before entering the field.

 The Field Crew Medical Information Form contains basic information on each field crew 

member. This

form should be completed after hiring and before sampling begins. Completed forms should be 

available

to each crew leader and kept with plot packets carried in field vehicles.
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 The Emergency Reference Form identifies emergency information within the state and county in

which

the field crew is working. This information should be available to each field crew member 

before sampling

begins in a county. Completed forms should be kept with plot packets carried in field 

vehicles. The

regional coordinator or logistics lead is responsible for completing these forms and informing 

crew leaders

of their responsibilities to carry the forms in field vehicles.

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 EMAP Forest Monitoring, Appendix E, Rev. No. 0, October, 1994, Page 9 of 10

 FOREST HEALTH MONITORING

 EMERGENCY REFERENCE SHEET

HEXAGON ID NUMBER

STATE:

 COUNTY:

HOME OFFICE: (specific for each logistics/regional coordinator)

POLICE:

LOCAL:

STATE:

FIRE DEPARTMENT:

USDA-FOREST SERVICE RANGER STATION:

STATE FORESTRY COMMISSION:

LOGISTICS/REGIONAL COORDINATOR:

NE Detection Monitoring: Andy Gillespie, USDA-FS, Radnor, PA.

SE Detection Monitoring: Bill Bechtold, USDA-FS, Asheville, NC.

AL Detection Monitoring: John Vissage, USDA-FS, Starkville, MS.

CO Detection Monitoring: Bill McLain, USDA-FS, Ogden, UT.

CA Detection Monitoring: Leon Liegel, USDA-FS PNW, Corvallis, OR. 503-750-7299 (office)

 503-750-7348 (after hrs)

Regional/ State/ Field Coordinator

 215-975-4035 (office)

 704-257-4357 (office)

 601-323-8162 (office)

 801-625-5381 (office)

(Please add the name and number of key point-of-contact in your region or state.)

HOSPITAL/CLINIC:

DIRECTIONS TO HOSPITAL/CLINIC:

Figure 2. Emergency Reference Sheet

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11 Personal Protection

 The following items of personal gear are required for field sampling:

 • Hard hats.

 • Safety glasses.

 • Work boots with Vibramtm soles or similar traction.

 • Work gloves.

 • Rain gear.

 • Foil fire survival kit for fire areas.

 In addition, each crew member should have a day's supply of water available. Adequate 

amounts will

vary depending on local terrain and weather conditions.

12 Accident Reporting

 If a field crew person is injured, notify the crew leader immediately. The injured person,

unless

incapacitated, provides first aid treatment to himself or herself, and, if necessary, should be 

assisted to the

nearest medical facility. The person must immediately notify the regional coordinator or 

logistics lead so

that the accident can be properly documented.

13 Safety Equipment

 Vehicles should maintain the equipment listed in Table 1.

 • Maintain a field crew first-aid kit as listed in Table 2.

 A snake bite kit should be available in regions where poisonous snakes exist.

 The emergency telephone numbers and radios should be available for med-evac if a hospital

is

 not < 1 hour driving time from a field plot.
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14 Visitor Safety Precautions

 All visitors to FHM field activities (auditors, indicator representatives, managers, etc.) 

must inform the

Regional Logistics Lead/Field/State Coordinator before joining a field team on a plot. The 

Regional

Logistics Lead/Field/State Coordinator will coordinate the visit so that visitors bring 

appropriate attire, food,

and water and are aware of unique safety concerns for particular areas (e.g., elevational 

gradient, steep

slopes, poisonous plants).

 OU.S. GOVERNMENT PRINTING OFFICE: 1995-650-006-22021

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