The Impact of Climate Change

on America’s Forests

The Impact of Climate Change

on America’s Forests

U.S. DEPARTMENT OF AGRICULTURE FOREST SERVICE

A Technical Document Supporting the 2000

USDA Forest Service RPA Assessment

A Technical Document Supporting the 2000

USDA Forest Service RPA Assessment
*OYCE,INDA!"IRDSEY2ICHARDTECHNICALEDITORS4HEIMPACTOFCLIMATECHANGEON!MERICAS

FORESTS!TECHNICALDOCUMENTSUPPORTINGTHE53$!&OREST3ERVICE20!!SSESSMENT'EN

4ECH2EP2-23
'42
&ORT#OLLINS#/53$EPARTMENTOF!GRICULTURE&OREST3ERVICE2OCKY

-OUNTAIN2ESEARCH3TATIONP

+EYWORDSFORESTPRODUCTIVITYVEGETATIONCHANGECARBONSEQUESTRATIONMITIGATIONFORESTSECTOR

TIMBERINVENTORYSOILCARBONCARBONACCOUNTINGAFFORESTATIONDEFORESTATION

!BSTRACT

4HIS REPORT DOCUMENTS TRENDS AND IMPACTS OF CLIMATE CHANGE ON !MERICAS FORESTS AS REQUIRED

BY THE 2ENEWABLE 2ESOURCES 0LANNING !CT OF  2ECENT RESEARCH ON THE IMPACT OF CLIMATE

ANDELEVATEDATMOSPHERICCARBONDIOXIDEONPLANTPRODUCTIVITYISSYNTHESIZED-ODELINGANALYSES

EXPLORE THE POTENTIAL IMPACT OF CLIMATE CHANGES ON FORESTS WOOD PRODUCTS AND CARBON IN THE

5NITED3TATES

4HISPUBLICATIONISALSOAVAILABLEONTHEWEBATHTTPWWWFSFEDUSRM

#OVERPHOTOBY,ANE%SKEW

9OUMAYORDERADDITIONALCOPIESOFTHISPUBLICATIONBYSENDING

YOUR MAILING INFORMATION IN LABEL FORM THROUGH ONE OF THE

FOLLOWINGMEDIA0LEASESENDTHEPUBLICATIONTITLEANDNUMBER

 4ELEPHONE 	


 %MAIL RSCHNEIDER FSFEDUS

 &AX 	


 -AILINGADDRESS 0UBLICATIONS$ISTRIBUTION

  2OCKY-OUNTAIN2ESEARCH3TATION

  70ROSPECT2D

  &ORT#OLLINS#/
#ONTENTS

%XECUTIVE3UMMARY  

#HAPTER/VERVIEW!SSESSINGTHE)MPACTSOF#LIMATE#HANGEON53&ORESTS  

 ,INDA!*OYCEAND2ICHARD"IRDSEY

  )NTRODUCTION  

  4HE3YNTHESISOF3CIENTIlC)NFORMATION  

  5NDERSTANDINGTHE$YNAMICSOF#LIMATE  

  0REDICTING&UTURE#LIMATESANDTHE6EGETATION2ESPONSE 

  )MPACTOF#LIMATE#HANGEON&ORESTS7OOD0RODUCTSAND#ARBON  

#HAPTER"IOME2EDISTRIBUTION5NDER#LIMATE#HANGE  

 $OMINIQUE"ACHELETAND2ONALD0.EILSON

  )NTRODUCTION"ACKGROUND  

  -ETHODOLOGY  

  2ESULTS 

  3IMULATION5NCERTAINTIES  

  -ODEL,IMITATIONS 

  #ONCLUSIONS  

#HAPTER%COSYSTEM0RODUCTIVITYANDTHE)MPACTOF#LIMATE#HANGE  

 ,INDA*OYCEAND-ARTHA.UNGESSER

  )NTRODUCTION  

  0LANTAND%COSYSTEM0RODUCTIVITY  

  0OTENTIAL6EGETATIONAND#URRENT6EGETATION$ESCRIPTIONS 

  0ROJECTING%COSYSTEM0RODUCTIVITYAT$IFFERENT3PATIAL3CALES  

  #ONCLUSIONS  

#HAPTER-ODELING#LIMATE#HANGE)MPACTSONTHE&OREST3ECTOR  

 *OHN2-ILLS2ALPH!LIG2ICHARD7(AYNESAND$ARIUS!DAMS

  )NTRODUCTION  

  #OMPARISONOF-ODEL3TRUCTURES  

  2ESULTS 

  -ODEL5NCERTAINTIES 

  #ONCLUSIONS  

4HE)MPACTOF#LIMATE#HANGEON!MERICAS&ORESTS

!4ECHNICAL$OCUMENT3UPPORTINGTHE53$!

&OREST3ERVICE20!!SSESSMENT

,INDA!*OYCEAND2ICHARD"IRDSEY4ECHNICAL%DITORS
#HAPTER#ARBON3EQUESTRATIONIN7OODAND0APER0RODUCTS 

 +ENNETH%3KOGAND'ERALDINE!.ICHOLSON

  )NTRODUCTION  

  -ETHODS  

  2ESULTS 

  #ONCLUSIONS  

#HAPTER3OIL#ARBON!CCOUNTINGAND!SSUMPTIONSFOR&ORESTRYAND

&OREST
2ELATED,AND5SE#HANGE  

 ,INDA3(EATHAND*AMES%3MITH

  )NTRODUCTION  

  &OREST#ARBON!CCOUNTING  

  3OIL#ARBON!CCOUNTING3YSTEMSFOR&ORESTAND,AND5SE#HANGE  

  #OMPARISONOF!CCOUNTING3YSTEMS  

  2ECENT$EVELOPMENTS  

  3UMMARY  

#HAPTER#ONSIDERATIONSFOR)NTERPRETING0ROBABILISTIC%STIMATESOF

5NCERTAINTYOF&OREST#ARBON 

 *AMES%3MITHAND,INDA3(EATH

  )NTRODUCTION  

  !&OREST#ARBON"UDGET-ODEL&/2#!2"  

  5NCERTAINTY 

  -ETHODOF3IMULATING5NCERTAINTY  

  2ESULTSAND$ISCUSSION  

  3UMMARY  

#HAPTER-ITIGATION!CTIVITIESINTHE&OREST3ECTORTO2EDUCE%MISSIONSAND

%NHANCE3INKSOF'REENHOUSE'ASES 

 2ICHARD"IRDSEY2ALPH!LIGAND$ARIUS!DAMS

  )NTERNATIONAL.EGOTIATIONSTO3TABILIZE'REENHOUSE'ASES  

  3UMMARYOF&ORESTRY/PTIONSTO2EDUCE%MISSIONSOR%NHANCE3INKS  

  4HE53#LIMATE#HANGE!CTION0LAN  

  -ETHODOLOGYFOR%STIMATING-ITIGATION0OTENTIAL  

  4HE"ASELINE#ARBON"UDGETFOR53&ORESTLAND  

  %VALUATIONOF3ELECTED-ITIGATION/PTIONS  

  6ERIlCATION  

  #OSTSOF-ITIGATION0OLICIES  

  /THER#ONSIDERATIONSIN0OLICY&ORMULATION 

  #ONCLUSIONS0OTENTIALFOR-ITIGATION4HROUGH&ORESTRY!CTIONSINTHE53  

4HE!UTHORS  
53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

%XECUTIVE3UMMARY

4HE INCREASING CONCENTRATION OF ATMOSPHERIC CARBON

DIOXIDEHASRAISEDCONCERNSABOUTTHEVULNERABILITYOFFOR


ESTSTOPOTENTIALCHANGESINCLIMATEANDCLIMATEVARIABILITY

4HESECONCERNSHAVEPROMPTEDGOVERNMENTSAROUNDTHE

WORLDTOCOMMISSIONTECHNICALASSESSMENTSONTHEIMPACT

OFCLIMATECHANGEONTHEENVIRONMENTANDTHEECONOMY

"ASEDONTHECURRENTSCIENTIlCINFORMATIONWITHINTHESE

ASSESSMENTSGOVERNMENTSHAVEINITIATEDNEGOTIATIONSON

POLICY ACTIONS TO REDUCE GREENHOUSE GAS EMISSIONS AND

TOADDRESSTHEVULNERABILITIESOFTHEECOLOGICALECONOMIC

AND SOCIAL SYSTEMS TO CLIMATE CHANGE #RITICAL TO POLICY

FORMULATIONISAPERIODICSYNTHESISOFTHEEVER
EXPANDING

KNOWLEDGE ON FOREST ECOLOGY THE IMPACT OF CLIMATE ON

FORESTSANDOFFORESTSONCLIMATEFORESTMANAGEMENTTHE

SOCIO
ECONOMICVALUEOFTREESANDFORESTSANDTHEROLEOF

FORESTSINTHEGLOBALCARBONCYCLE

4HE &OREST 3ERVICE CONDUCTS PERIODIC ASSESSMENTS OF

THE CONDITION OF FOREST AND RANGELAND RESOURCES UNDER

THEAUTHORITYOFTHE2ENEWABLE2ESOURCES0LANNING!CT

20!	4HESTRUCTUREOFTHESEPERIODICASSESSMENTSALLOWS

FOR THE SYNTHESIS AND INTEGRATION OF THE CURRENT STATE OF

SCIENTIlC KNOWLEDGE !S PART OF THE 20! PROCESS THIS

REPORTSYNTHESIZESCURRENTINFORMATIONTHATASSESSESTHE

IMPACTOFCLIMATECHANGEON53FORESTS3IXPOLICYQUES


TIONS CRITICAL TO UNDERSTANDING THE IMPACT OF GLOBAL CLI


MATE CHANGE ON CURRENT AND FUTURE TRENDS

 FORM THE

BASIS FOR THIS REPORT 4HE lRST CHAPTER DESCRIBES MAN


DATES AND STRUCTURES OF SYNTHESIZING SCIENTIlC INFORMA


TIONONTHEFORESTSECTORDESCRIBESCURRENTUNDERSTANDINGS

OFTHEGLOBALCLIMATEANDCLOSESWITHTHEPOLICYQUESTIONS

ADDRESSEDINTHISASSESSMENT4HENEXTCHAPTERSADDRESS

THESIXPOLICYQUESTIONSWHICHWESUMMARIZEHERE

7HATARETHE,IKELY%FFECTSOF)NCREASING

!TMOSPHERIC#ARBON$IOXIDEAND0ROSPECTIVE

#LIMATE#HANGESON%COSYSTEM0RODUCTIVITYAS

-EASUREDBY#HANGESIN.ET0RIMARY0RODUCTIVITY

*OYCEAND.UNGESSERTHISVOLUME	SUMMARIZERECENT

EXPERIMENTAL DATA AND MODELING ANALYSES THAT ENHANCE

OURUNDERSTANDINGOFTHEPOTENTIALIMPACTOFCARBONDIOX


IDE AND CLIMATE ON FORESTS !NALYSES OF THE IMPACT OF

CLIMATE CHANGE ON FOREST PRODUCTIVITY BASED ON EXPERI


MENTALRESEARCHANDMODELINGWOULDSUGGESTTHATFOREST

PRODUCTIVITYMAYINCREASEUNDERELEVATEDCARBONDIOXIDE

BUTTHATTHELOCALCONDITIONSOFMOISTURESTRESSANDNUTRI


ENTAVAILABILITYWILLSTRONGLYTEMPERANYRESPONSE.EW

lELDEXPERIMENTSONVEGETATIONANDRECENTMETA
ANALYSIS

STUDIES OF THE ACCUMULATED EXPERIMENTAL DATA DEMON


STRATE THAT ELEVATED CARBON DIOXIDE HAS BEEN SHOWN TO

INCREASEPLANTGROWTHBY
PERCENTWITHEXPERIMEN


TAL RESULTS VARYING WIDELY 4HIS OPTIMAL RESPONSE IS AN

ASSUMPTIONWITHINTHEECOLOGICALMODELSUSEDTOEXAM


INETHEIMPACTOFCLIMATECHANGEONVEGETATION(OWEVER

WHENTHEMODELSAREIMPLEMENTEDACROSSTHEGEOGRAPHI


CALLYDIVERSELANDSCAPESOFTHE5NITED3TATESTHEMODEL

RESPONSES TO ELEVATED CARBON DIOXIDE ARE SUBSTANTIALLY

LOWERLESSTHANPERCENTBYECOSYSTEMTYPEREmECTING

LOCAL CONDITIONS OF MOISTURE STRESS AND NUTRIENT AVAIL


ABILITY*OYCEAND.UNGESSERTHISVOLUME	COMPARETHE

MAGNITUDEOFTHESEMODELEDRESPONSESTOFORESTGROWTH

RESPONSESFROMTIMBERMANAGEMENT4HEYCONCLUDETHAT

THEGROWTHRESPONSETOTIMBERMANAGEMENTISLARGERTO

PERCENT	THANTHEPROJECTEDPRODUCTIVITYRESPONSEFROM

CHANGESINCARBONDIOXIDEORCLIMATETOPERCENT	

*OYCEAND.UNGESSERTHISVOLUME	ALSOEXAMINEDTHE

IMPLICATIONSOFTWOMODELINGASSUMPTIONSINTHELAST20!

ASSESSMENT 	 CLIMATE AND VEGETATION WERE IN EQUILIB


RIUMAND	THESPATIALSCALEOFTHEECOLOGICALMODELWAS

ANADEQUATESCALEFORNATIONALLEVELANALYSES-OSTMOD


ELINGANALYSESOFTHEIMPACTOFCLIMATECHANGEINCLUDING

THE20!ANALYSISUSEINPUTDATAGRIDDEDATA
KMSCALE

TO DESCRIBE THE DOMINANT CLIMATE AND LAND SURFACE FEA


TURESOFLARGEREGIONSSUCHASTHE5NITED3TATES*OYCEAND

.UNGESSER CONCLUDED THAT MOVING THE CLIMATE CHANGE

ANALYSES TO A lNER SPATIAL SCALE FOR EXAMPLE 
KM s


KM GRID SIZE DID NOT NECESSARILY IMPROVE THE ESTI


MATESOFTHEIMPACTOFCLIMATECHANGEONFORESTPRODUC


TIVITY!NALYSESDONEATTHEKMSCALEWEREADEQUATETO

ADDRESSNATIONALANDREGIONALISSUESEXCEPTINAREASWHERE

A MOSAIC OF FOREST TYPES OCCURRED OR WHERE TEMPERATURE

ANDPRECIPITATIONGRADIENTSWERELARGE)NCORPORATINGLAND

USECHANGESAPPEARSTOBEACRITICALNEXTSTEPINTHEANALYSIS

OFTHEIMPACTOFCLIMATECHANGEONFORESTPRODUCTIVITY

4O7HAT'EOGRAPHIC%XTENT7ILL0OTENTIAL%COSYSTEM

4YPES#HANGEOR-OVE!CROSSTHE5NITED3TATESAS

-EASUREDIN#OMPOSITIONAND"OUNDARY#HANGES

"ACHELETAND.EILSONTHISVOLUME	CONCLUDETHATTHE

FOLLOWINGCHANGESCOULDOCCURINTHEVEGETATIONDISTRIBU


TIONACROSSTHE5NITED3TATESASARESULTOFCLIMATECHANGE

	BOREALFORESTSANDTAIGA
TUNDRAREGIONSAREPREDICTEDTO

MOVENORTHWARDATTHEEXPENSEOFTHETUNDRA	WARMER

*OYCE,!"IRDSEY2-ILLS*(EATH,0ROGRESS

TOWARDANINTEGRATEDMODELOFTHEEFFECTSOFGLOBALCHANGEON

5NITED3TATESFORESTS)N"IRDSEY2-ICKLER23ANDBERG$;ET

AL=EDS53$!&OREST3ERVICE'LOBAL#HANGE2ESEARCH

0ROGRAM(IGHLIGHTS
'EN4ECH2EP.%
2ADNOR

0!53$EPARTMENTOF!GRICULTURE&OREST3ERVICE.ORTHEAST


ERN&OREST%XPERIMENT3TATION


%8%#54)6%35--!29
 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

 %XECUTIVE3UMMARY

SCENARIOSPRODUCETHELARGESTIMPACTSONTHEBOREALFOREST

BUTMAYALSOBERESPONSIBLEFORFORESTDIEBACKONTHECON


TERMINOUS53	NORTHWESTANDSOUTHEASTFORESTSMIGHT

INITIALLYEXPANDTHENLATERCONTRACTINAREAAND	SOUTH


WESTERN DESERT SPECIES MAY MOVE INTO THE 'REAT "ASIN

REGION 4HE CHOICE OF CLIMATE CHANGE SCENARIO AND THE

TREATMENTOFCARBONDIOXIDEEFFECTSINEACHMODELSTRONGLY

INmUENCE THE SIMULATIONS AND THE UNCERTAINTY IN THEM

2ESULTSMAYINDICATETHEDIRECTIONOFPOSSIBLECHANGEBUT

SHOULD NOT BE TAKEN AS SOLID PREDICTIONS $ISTURBANCE

REGIMESWILLBEAFFECTEDBYCLIMATECHANGEBUTTHEYARE

DIFlCULTTOSIMULATEANDAFFECTTHEOUTCOMEOFTHEMODELS

-OREOVERIMPORTANTFACTORSNOTINCLUDEDINTHESEMODELS

SUCHASGRAZINGWEEDINVASIONSDISEASEANDPESTSAND

CHANGESINLANDUSECOULDDRASTICALLYALTERTHERESPONSEOF

THEVEGETATIONTOCLIMATICCHANGES

7HAT#HANGESIN&OREST0RODUCTIVITY7ILL/CCURAS

-EASUREDBY#HANGESIN6OLUME'ROWTHAND

"IOMASS

7HAT!RETHE0OTENTIAL)MPACTSONTHE&OREST3ECTOR

5NDER#LIMATE#HANGEAS-EASUREDBY%MPLOYMENT

AND4IMBER0RICES

7HEN&OREST0OLICY1UESTIONSFORTHE20!

!SSESSMENT3UCHAS2EDUCED.&3(ARVEST

!RE%XAMINED7ITHAND7ITHOUT#LIMATE#HANGE

$OTHE&OREST3ECTOR)MPACTS$IFFER'REATLYIN

-AGNITUDEOR+IND

-ILLSETALTHISVOLUME	DESCRIBETHEUSEOFTWOFOREST

SECTORMODELS4!--AND&!3/-	TOESTIMATETHEEFFECTS

OF CLIMATE CHANGE ON FORESTS "OTH MODELS DISCUSSED IN

THISCHAPTERHAVEBEENUSEDTOEXAMINEAVARIETYOFPOLICY

ANDMANAGEMENTSCENARIOSINCLUDINGINVESTMENTBEHAV


IOROFPRIVATEOWNERSLINKAGESBETWEENFORESTRYANDAGRI


CULTURE AND IMPACT OF ALTERED TRADE mOWS ON THE FOREST

SECTORGLOBALLY"OTHMODELSSHAREANUMBEROFCHARACTER


ISTICS IN MODELING TIMBER DEMAND AND SUPPLY BUT THEY

DIFFERINTHEIRSELECTIONCRITERIAFORLANDMANAGEMENT5SE

OFBOTHTHE4!--AND&!3/-MODELSREVEALSTHEDIF


FERENCES BETWEEN 	 LIKELY FUTURE PATHS FOR THE FOREST

SECTOR IF HISTORICAL RELATIONSHIPS BETWEEN KEY VARIABLES

CONTINUEVERSUS	PRODUCTIONPOSSIBILITIESANDOPTIMAL

RESPONSES TO EXTERNAL EVENTS EG CLIMATE CHANGE	 AND

POLICIES&!3/-ASSUMESPERFECTKNOWLEDGEOFTHEFUTURE

ANDOPTIMALADJUSTMENTSINTHEUNFETTEREDCASE5NDERA

CLIMATECHANGESCENARIO&!3/-SHOWSAGREATERSHIFTTO

PINEPLANTATIONSANDASTIMBERPRICESFALLANINCREASEIN

LANDMOVINGFROMFORESTTOAGRICULTUREANDADECREASEOF

INVESTMENTINPINEPLANTATIONS

"OTHMODELSCHALLENGEECOLOGISTSANDPOLICYANALYSTS

TOBEEXPLICITINTHESIZELOCATIONANDTIMINGOFVARIOUS

IMPACTSTOCONSIDERTHETRANSITIONFROMCURRENTVEGETA


TIONANDTOGAUGETHETRADEOFFSBETWEENNEAR
TERMPOLICY

CONCERNSANDLONG
TERMECOLOGICALIMPACTS"OTHMODELS

OFFER A COMMON FRAMEWORK FOR INTEGRATING BIOPHYSICAL

ANDSOCIALSYSTEMSANDFORTRACINGHOWCHANGESINTYPI


CALLYBIOPHYSICALATTRIBUTESGROWTHAREAOFCERTAINTYPES

ETC	 AFFECT VARIOUS MEASURES OF ECONOMIC BENElTS AND

COSTS)NTHATROLETHESEMODELSOPERATEATTHEINTERFACEOF

SCIENCEANDPOLICYWHERETHEEMPHASISISONHOWMODELS

IMPROVE THE INFORMATION AVAILABLE FOR DECISION MAKERS

THATSAMEINFORMATIONFROMTHEPOLICYPERSPECTIVEHELPS

SHAPEPERCEPTIONSABOUTTHEEFFECTIVENESSOFVARIOUSMAN


AGEMENTACTIONS

7HAT!RETHE/PPORTUNITIESAND#OSTSOF%MISSIONS

-ITIGATION5SING&OREST%COSYSTEM-ANAGEMENTAND

&OREST0RODUCTS4ECHNOLOGIES

)NCREASINGTHEAMOUNTOFCARBONTHATISSTOREDINFORESTS

COULDMITIGATETHEEMISSIONSOFCARBONDIOXIDEFROMFOSSIL

FUELCOMBUSTION1UANTIFYINGTHEAMOUNTOFCARBONTHAT

COULDBESTOREDANDTHEAMOUNTOFCARBONTHATISREMOVED

THROUGHHARVESTISCRITICALINEVALUATINGTHEOPPORTUNITIES

ANDCOSTSOFTHISTYPEOFMITIGATION4HECARBONBUDGET

APPROACHUSESINVENTORYANDlELDRESEARCHDATATOCOM


PUTE THE EXCHANGE OF CARBON BETWEEN FORESTS AND THE

ATMOSPHERE 7HEN LINKED TO TIMBER INVENTORY MODELS

THESEBUDGETSCANBEUSEDTOANALYZETHEIMPACTSOFALTER


NATIVE POLICY CONSIDERATIONS ON CARBON STORAGE 7HEN

LINKED TO FOREST SECTOR MODELS THESE BUDGETS CAN FACILI


TATEANEXAMINATIONOFTHEOPPORTUNITIESANDCOSTSUSING

FORESTMANAGEMENTTOMITIGATECARBONEMISSIONS

(EATHAND3MITHTHISVOLUME	EXAMINETWOACCOUNT


INGSYSTEMSFORSOILCARBON	THEACCOUNTINGFRAMEWORK

USEDBY"IRDSEYAND(EATHINTHE20!ASSESSMENT

AND	THEFRAMEWORKPRESENTEDINTHE.ATIONAL'REEN


HOUSE'AS)NVENTORIESOFTHE)NTERNATIONAL0ANELON#LI


MATE #HANGE )0##	 "OTH SYSTEMS BASE PREDICTIONS ON

FORESTINVENTORYVARIABLESOFVOLUMEANDAREA"OTHMETH


ODSRECOGNIZETHEIMPORTANCEOFPREVIOUSLANDUSE4HE

)0## DEFAULT SYSTEM EXPLICITLY COUNTS SOIL CARBON LOSS

WHEN FORESTS ARE CLEARED AND CULTIVATED BUT DOES NOT

INCLUDETHEACCUMULATIONOFSOILCARBONDUETOAFFORESTA


TIONALTHOUGHSOILCARBONINCREASESDUETODIFFERINGAGRI


CULTURALTILLAGEPRACTICESAREINCLUDED	"IRDSEYAND(EATH

EXPLICITLYACCOUNTFORTHEACCUMULATIONOFSOILCARBONDUE

TOAFFORESTATIONBUTDONOTEXPLICITLYCOUNTSOILLOSSAFTER

DEFORESTATION 4HIS IS BECAUSE THE 20!ANALYSIS FOCUSED

ONLYONCARBONINTHEFORESTSECTOR$EFORESTEDAREASWERE

ASSUMED COUNTED IN THE AGRICULTURAL OR URBAN SECTOR

NOTFORESTSANDOVERTHELAST
YEARSMORELANDHAS

BECOMEAFFORESTEDTHANDEFORESTED
53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

%XECUTIVE3UMMARY

2ECENTSCIENTIlCSTUDIESINDICATETHATHARVESTINGMAY

INmUENCE SOIL CARBON AN INITIAL SLIGHT INCREASE FOLLOWED

BYADECREASEANDlNALLYANINCREASE(EATHAND3MITH

THIS VOLUME	 SPECULATE THAT SOIL CARBON WILL EVENTUALLY

RETURNTOPRE
HARVESTLEVELS4HISCORRESPONDSTOTHEPAT


TERNINTHESOILCARBONASSUMPTIONSINTHE20!ANALYSIS

4HEMAGNITUDEOFTHEEFFECTSEEMSTODEPENDONTHELEVEL

ANDTYPEOFDISTURBANCEFROMLOGGINGOPERATIONS#ONSID


ERATIONOFTHEOVERALLLEVELOFDISTURBANCEINHARVESTING

OPERATIONS IN COUNTRIES WITH ACTIVE FOREST MANAGEMENT

COULDBEUSEDTOREVISESOILCARBONASSUMPTIONSACCORD


INGLY 3OIL CARBON DECREASES FOR 
 YEARS FOLLOWING

DEFORESTATIONANDCULTIVATIONANDTHENREMAINSRELATIVELY

CONSTANTFOLLOWINGAFFORESTATIONSOILCARBONINCREASESATA

MOREGRADUALRATETHANTHERATEATWHICHITHADDECREASED

EVENTUALLYBECOMINGSOMEWHATSTABLE

3MITH AND (EATH THIS VOLUME	 PRESENT SOME USEFUL

CONSIDERATIONSFORINTERPRETINGANDUSINGINFORMATIONFOR

PROBABILISTICASSESSMENTSOFUNCERTAINTY4HEYEMPHASIZE

THECONSEQUENCESOFSUMMARIZINGUNCERTAINTYASWELLAS

HOWSUCHSUMMARIESCANAFFECTTHEPERCEPTIONOFUNCER


TAINTYINSUBSEQUENTUSEOFTHEINFORMATION%XAMPLESARE

PRESENTEDFROMTHEIRCURRENTFORESTCARBONBUDGETMODEL


INGEFFORTSWHERETHEYEMPLOYPROBABILISTICDElNITIONSOF

UNCERTAINTYIN-ONTE#ARLOSIMULATIONS

3KOG AND .ICHOLSON THIS VOLUME	 PROVIDE HISTORICAL

ESTIMATESANDPROJECTIONSOFCARBONSEQUESTEREDINWOOD

AND PAPER PRODUCTS IN THE 5NITED 3TATES AND COMPARE

THEMTOAMOUNTSSEQUESTEREDIN53FORESTS4HESTOCKS

OFCARBONINFORESTSINWOODANDPAPERPRODUCTSINUSE

ANDINDUMPSANDLANDlLLSARELARGEANDINCREASING3INCE

ANESTIMATED0GBILLIONMETRICTONS	OFCARBON

HAVEACCUMULATEDANDCURRENTLYRESIDEINWOODANDPAPER

PRODUCTSINUSEANDINDUMPSANDLANDlLLSINCLUDINGNET

IMPORTS&ORPURPOSESOFCOMPARISONTHECURRENTINVEN


TORY OF CARBON IN FOREST TREES IS  0G AND IN FOREST

UNDERSTORYmOORANDSOILS0G.ETSEQUESTRATIONIS

COMPUTED AS NET IMPORTS OF WOOD AND WOOD PRODUCTS

MINUSTHEEMISSIONSFROMDECAYANDBURNINGEACHYEAR

.ETSEQUESTRATIONOFCARBONIN53WOODANDPAPERPROD


UCTSISPROJECTEDTOINCREASEFROM4GYEARINTO

4GYEARBYWHILENETSEQUESTRATIONTOFORESTSISPRO


JECTEDTODECREASEFROMTO4GYEAR4GISMILLION

METRICTONS	.ETSEQUESTRATIONISINCREASINGINPRODUCTS

AND LANDlLLS BECAUSE OF AN INCREASE IN WOOD CONSUMP


TIONANDADECREASEINDECAYINLANDlLLSCOMPAREDWITH

PHASED
OUT DUMPS !NNUAL NET SEQUESTRATION TO FOREST

PRODUCTANDLANDlLLCARBONSTOCKSISSLIGHTLYGREATERTHAN

ANNUAL REMOVAL OF CARBON FROM THE ATMOSPHERE BY 53

ACTIVITIES&ORESTPRODUCTANDLANDlLLSTOCKSWERE4G

INWHILENETSEQUESTRATIONTOFORESTSPRODUCTSAND

LANDlLLSWAS4GIN4HISDIFFERENCEISBECAUSENET

SEQUESTRATIONTOSTOCKSINCLUDENETIMPORTSWHILEANNUAL

NET REMOVALS FROM THE ATMOSPHERE DOES NOT 4HE CHOICE

OF ACCOUNTING INmUENCES THE CARBON STORAGE RESULTS AND

ISCRITICALINDECISIONSABOUTWHICHCOUNTRIESWILLRECEIVE

CREDITFORSEQUESTERINGCARBON

"IRDSEYETALTHISVOLUME	CONCLUDETHATTHEPOTENTIAL

FOR INCREASING CARBON STORAGE IN FORESTS IN THE 5NITED

3TATESISQUITELARGE0OTENTIALCARBONSTORAGEISGOVERNED

BYTHEBIOLOGICALPOTENTIALOFFORESTLANDTOMAINTAINBIO


MASSTHEAVAILABILITYOFSUITABLELANDFORFORESTSANDTHE

COSTSANDTRADEOFFSASSOCIATEDWITHINCREASINGANDMAIN


TAINING PROTECTING	 A HIGHER LEVEL OF CARBON IN FORESTS

!LTHOUGHITISPRACTICALLYIMPOSSIBLETOMAINTAINALLFOR


ESTS AT MAXIMUM GROWTH AND CARBON STORAGE SIMULTA


NEOUSLY THERE IS A BIOLOGICAL AND ECONOMIC POTENTIAL TO

INCREASEGROWTHRATESANDTHEAMOUNTOFCARBONSTORED

0ROJECTIONSINDICATETHATEVENWITHOUTAFORESTCARBON

PROGRAMSUBSTANTIALINCREASESINFORESTCARBONARELIKELY

CONSEQUENCES OF CURRENT TIMBER MARKET ACTIVITIES AND

FORESTRY POLICIES 4HERE IS SOME UNCERTAINTY OVER TIME

ESPECIALLY IF CLIMATE CHANGE IMPACTS ON ECOSYSTEMS ARE

SUBSTANTIALANDCAUSECATASTROPHICREDUCTIONSINBIOMASS

AS FOREST ECOSYSTEMS ATTEMPT TO ADAPT 4HE STORAGE OF

CARBON IN FORESTS IS GENERALLY CONSIDERED A SHORT
TERM

ACTIVITY BECAUSE OF THESE LIMITS "UT TO THE EXTENT THAT

REDUCTIONS ARE NEEDED SOONER RATHER THAN LATER FORESTRY

ACTIONSCOULDBEANINTEGRALPARTOFANYCOMPREHENSIVE

GREENHOUSEGASREDUCTIONSTRATEGY

"IRDSEYETALTHISVOLUME	ECHO3KOGAND.ICHOLSON

THISVOLUME	INIDENTIFYINGTHEIMPORTANCEOFTHEAMOUNT

OFCARBONSTOREDINWOODPRODUCTSINUSEORPERMANENT

DISPOSAL	"IRDSEYETALTHISVOLUME	NOTETHATITISALSO

POSSIBLE TO REDUCE GREENHOUSE GAS EMISSIONS FROM THE

FORESTSECTORBYINCREASINGENERGYEFlCIENCYINCONVERTING

TIMBERTOPRODUCTS

3IZE OF PROGRAMS GEOGRAPHIC LOCATION AND COST ESTI


MATES VARY WIDELY BECAUSE OF DIFFERENCES IN HOW PAST

BEHAVIORISCONSIDEREDDIFFERENCESINCARBONACCOUNTING

ANDDIFFERENCESINMODELPARAMETERS#ONSIDERINGCOSTS

ANDPOTENTIALIMPACTSANDRECOGNIZINGTHATSOMEOPTIONS

HAVE NOT BEEN ANALYZED SUFlCIENTLY hIMPROVED FOREST

MANAGEMENTv APPEARS TO OFFER THE MOST COST
EFFECTIVE

MEANSTOSEQUESTERADDITIONALCARBONINFORESTECOSYSTEMS

IN THE SHORT TERM 6ERIlCATION OF CARBON CHANGES ATTRIB


UTABLE TO FOREST MANAGEMENT MAY BE DIFlCULT BECAUSE

WE LACK SUFlCIENT EXPERIMENTAL RESEARCH THAT QUANTIlES

IMPACTSOFSPECIlCPRACTICESONDIFFERENTCARBONPOOLS

!FFORESTATION COSTS ARE HIGH RELATIVE TO REFORESTATION

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VERSITY0RESS
18 USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000.

Biome Redistribution Under Climate Change

Dominique Bachelet, Oregon State University

Ronald P. Neilson, USDA Forest Service, Pacific Northwest Research Station

Introduction/Background

General warming in the Northern Hemisphere has 

been recorded since the end of the 1800s following the 

Little Ice Age (Folland et al. 1990). Records of glacier 

retreat during the last 100 years over the entire globe 

(Oerlemans 1994) independently confirmed the recorded 

trend in global temperature rise. Several studies have 

illustrated various responses to this climate forcing, i.e., 

the recorded changes in temperature and precipitation 

concurrent with the increase in atmospheric CO2 concentration, increases in density of tree populations (Morin 

and Payette 1984; Payette and Filion 1985; Scott et al. 

1987), declines in tree populations (Hamburg and Cogbill 

1988), treeline displacement (Lescop-Sinclair and Payette 

1995) or lack thereof (MacDonald et al. 1998), lengthening of the growing season (Mynemi et al. 1997), and 

enhanced tree growth (Jacoby et al. 1996). It is critical that 

we identify the tools needed to estimate potential consequences of climate change on forest ecosystems (Joyce 

and Birdsey this volume) and develop management practices and policies adapted to projected drifts in the geographic distribution of ecosystems.

Emanuel et al. (1985), who used the Holdridge lifezone model (Holdridge 1947), and Box (1981) were among 

the first to use correlational models between average climate and vegetation distribution to predict the responses 

of vegetation to climate change using general circulation 

model (GCM) climate simulations. The Holdridge lifezone classification relates the distribution of major ecosystems to mean annual biotemperature, mean annual 

precipitation, and the ratio of potential evapotranspiration to precipitation (Holdridge 1947). It was used by 

several authors (Emanuel et al. 1985; Prentice and Fung 

1990; Smith et al. 1992) to examine potential global shifts 

in major ecosystems with climate change (Dale 1997). 

Results from Smith et al. (1992) showed a global decrease 

in the extent of tundra and desert, with a concurrent 

increase in grassland area, under four different GCM climate change scenarios. Results also showed an increase 

in tropical forest area and the replacement of tundra by 

boreal forests. These static models offer simplicity and 

availability but: 1) they do not take into account seasonality; 2) they have strict climate boundaries which create 

problems for representing transitional vegetation; and 

3) they cannot include any direct CO2 effect or indicate 

changes in vegetation density, runoff, or nutrient fluxes. 

Over 100 “gap” model studies have also been conducted 

to simulate the impacts of global change on forests (Smith 

and Shugart 1996; Dale and Rauscher 1994; Smith et al. 

1992). These models predict the establishment, growth, 

and death of individual trees for all potential species on a 

site. They include a wide range of disturbances such as fire, 

blowdown, insect defoliation, and drought. Simple rules 

are used to simulate succession in most forests. Comparative studies showed that seemingly similar models could 

yield totally different projections of future forest composition (for example, Bugmann 1997), since there is considerable uncertainty about the appropriate formulation of 

environmental influences on demographic processes. Early 

versions of gap models had been developed for current 

climate. Their applicability to changing climate conditions 

and increasing CO2 concentration was questionable (for 

example, Loehle and Leblanc 1996). However, a second 

generation of gap models was developed with improved 

formulations of key relationships, including physiological 

mechanisms, thus allowing more mechanistic calculations 

of environmental effects on tree growth. Functional types 

were used to reduce the numbers of site-specific parameters required to run the models (Friend et al. 1997). Unfortunately, there has not been enough time yet for results 

from climate change research with these newer models to 

be widely circulated and published.

Biogeography models such as DOLY (Woodward and 

Smith 1994), MAPSS (Neilson 1995), and BIOME2 or 3 

(Haxeltine et al. 1996), which are based on ecophysiological constraints and resource limitations, have been considered the next generation of equilibrium spatial models 

(Monserud and Leemans 1992). They are capable of simulating impacts on natural vegetation at all scales from 

global to continental, regional, and local (Smith et al. 

1994) and have been used in several global climate change 

studies (IPCC 1996; VEMAP Members 1995; Neilson et al. 

1998). 

The objective of this chapter is to address the following 

question: To what geographic extent will potential ecosystem types change or move across the United States, as 

measured in composition and boundary changes? To do 

so, we used results from three different studies (Neilson 

et al. 1998; VEMAP Members 1995; Neilson and Drapek 

1998), which are summarized in table 2.1. Three different 

models (DOLY, MAPSS, BIOME2 and its later version 

BIOME3) were run at two spatial resolutions (half-degree 

latitude × half-degree longitude, and 10 km) for two 

geographic extents (North America and the conterminous United States). Older and newer GCM-generated 

climate scenarios were used to describe the impacts of 

CHAPTER 2
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 19

Biome Redistribution Under Climate Change Bachelet and Neilson

Table 2.1—Summarized description of the three studies used in this article to illustrate the impact of climate change on biome distribution. FAR = First Assessment Report (IPCC 1990) including climate change scenarios from GFDL-R30, GISS, OSU, UKMO; SAR = 

Second Assessment Report (IPCC 1996) including climate change scenarios from HADCM2SUL and HADCM2GHG (see table 3 for 

details on scenarios).

Region of study Biogeography Climate change Climate data

 (project) models Resolution Reference scenario source

North America MAPSS 0.5° latitude Neilson et al. 1998 FAR and SAR Leemans and

BIOME3 × longitude Cramer 1991

Conterminous MAPSS 0.5o latitude VEMAP Members 1995 FAR Kittel et al. 1995

USA (VEMAP) DOLY × longitude

BIOME2

Regional USA MAPSS 10 km Neilson and Drapek 1998; FAR and SAR NOAA-EPA 1997

Borchers and Neilson 1998

the improvements made in projecting future climates on 

ecological simulation results. The rationale for using this 

approach is that: 1) focusing on the entire North American 

continent enables us to include entire biomes regardless 

of political boundaries; 2) focusing on the U.S. enables 

us to address nationally relevant issues and to compare 

MAPSS results with other model projections; and 3) a 

10 km resolution is a more adequate scale to focus on 

regional impacts. A different baseline climatic dataset was 

used for each of the three studies, which explains the differences between the North American study and VEMAP, 

both of which were performed at the same half-degree 

resolution. Using results from these studies increases the 

information gain about U.S. forests and also emphasizes 

the uncertainties associated with the results.

Methodology

Biogeography Models

Models

Process-based biogeography models simulate the dominance of various plant lifeforms in different environments based on ecophysiological constraints, such as 

growing degree days and minimum winter temperatures, 

and resource limitations such as available soil water for 

plant uptake and available sunlight for the understory 

canopy (VEMAP Members 1995). These models simulate 

potential “climax” vegetation at steady state under any 

climate, past, present, or future (Neilson and Running 

1996).

Most of the results presented in this chapter come 

from the MAPSS (Mapped Atmosphere Plant Soil System) 

model (Neilson 1995; Neilson and Marks 1994). It includes 

a water submodel that calculates plant available water 

and a rule-based submodel that determines the climatic 

zone, the lifeform, and the plant type as a function of 

temperature thresholds and water availability. The maximum potential leaf area index (LAI) a site can support is 

calculated iteratively. It uses an aerodynamic approach 

sensitive to canopy characteristics to calculate evapotranspiration. Grasses and trees have different rooting 

depths in a multi-layer soil and compete for available soil 

water, while shading by trees limits grass growth. Vegetation classification in MAPSS is based on the presence/

absence and LAI values of three types of lifeforms—trees, 

shrubs, and grasses—with their leaf characteristics, thermal affinities, and seasonal phenology. The woody components, trees or shrubs, are assumed to be dominant and 

mutually exclusive. MAPSS includes a fire submodel that 

maintains transition zones such as the prairie peninsula. 

The model has been run at two different resolutions: 1) 10 

km; and 2) half degree latitude-longitude resolution for 

VEMAP and the North American study.

BIOME2 and DOLY are two other biogeography models 

that have been compared to MAPSS in VEMAP (VEMAP 

Members 1995). The newer version of BIOME2, BIOME3, 

was later compared to MAPSS in the North American 

study (Neilson et al. 1998). BIOME3 builds upon BIOME2 

but contains a more process-based canopy physiology, 

optimizing carbon gain through photosynthesis with radiation and water balance constraints on stomatal conductance. In BIOME2 and BIOME3 (Haxeltine and Prentice 

1996; Haxeltine et al. 1996; Prentice et al. 1992), plant 

functional types (PFT) are calculated using a small set 

of ecophysiological constraints such as minimum temperature tolerance. Gross primary production (GPP) is 

calculated for each PFT as a function of photosynthetically active radiation (PAR) based on the Farquhar photosynthesis equation (Farquhar et al. 1980). GPP is then 

reduced by soil water availability and temperature lim-
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ICAL &LUID $YNAMICS ,ABORATORY MODEL '&$,
2	 AND THE

5NITED +INGDOM -ETEOROLOGICAL /FlCE MODEL 5+-/	 &ROM

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SPHERIC
OCEANIC'#-USEDTOSIMULATECLIMATEWASTHE(ADLEY

#ENTRE4RANSIENTGENERALCIRCULATIONMODELWITH(!$#-35,	

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 4EMPERATURE #	 0RECIPITATION	

 7ORLD 53 7ORLD 53

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 /35     

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 '&$,
2    

 5+-/    

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 (!$#-'('    

 (!$#-35,     
53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

"IOME2EDISTRIBUTION5NDER#LIMATE#HANGE "ACHELETAND.EILSON

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NARIOSCANBEFOUNDIN.EILSONAND$RAPEK	

2ESULTS

.ORTH!MERICAN)MPACTS

%FFECTSOF#/-!0332ESULTS7ITH

&!23CENARIOS

2ESULTSFROMRUNNINGTHEEQUILIBRIUMVEGETATIONDIS


TRIBUTIONMODEL-!033FORTHE.ORTH!MERICANREGION

HALFDEGREELATITUDE
LONGITUDERESOLUTION	WITHANDWITH


OUTA#/EFFECTFORTHREE'#-SCENARIOSAREILLUSTRATEDIN

TABLE-AJORAGREEMENTSCANBEIDENTIlED	DECREASES

IN THE AREA OF BOTH TUNDRA AND TAIGA
TUNDRA FROM 

TO  PERCENT AND FROM  TO  PERCENT RESPECTIVELY	

	INCREASESINTHEAREALEXTENTOFSAVANNASFROMPER


CENTWITHTHE#/EFFECTTOPERCENTWITHOUT	AND	

DECREASESINTHEAREAOFSHRUBLANDSFROMTOPERCENT	

7HENTHE#/EFFECTISINCLUDEDPERCENTDECREASEIN

STOMATALCONDUCTANCE	TEMPERATEEVERGREENANDTEMPER


ATEMIXEDFORESTSAREPREDICTEDTOINCREASEINAREAWITH

THELARGESTINCREASESPREDICTEDUNDERTHE5+-/SCENARIO

PERCENTANDPERCENTRESPECTIVELY	

#OMPARISON"ETWEEN")/-%AND-!033

5SING3!23CENARIOS

-!033 SIMULATIONS USING THE (ADLEY #ENTRE SCENAR


IOS(!$#-35,AND'('	ARECOMPAREDTOTHOSEOF

")/-%INTABLE4HEMODELSPREDICTOPPOSITETRENDS

FOR BOTH THE BOREAL CONIFEROUS FOREST AND THE TEMPERATE

EVERGREENFOREST")/-%GROUPSBOREALFORESTANDTAIGA


TUNDRAINTOONEVEGETATIONTYPEWHILE-!033DOESNOT

-!033PREDICTSLARGEDECREASESINTHETAIGA
TUNDRAAREA

EASTERN #ANADA AND !LASKA lG 	 WHICH MATCHES

")/-% SIMULATIONS OF BOREAL FOREST AREA INCREASE BUT

-!033ALSOSIMULATESSMALLINCREASESINTHEBOREALFOREST

AREA PROPER 4HUS THE TWO MODELS ARE CONSISTENT WITH

EACHOTHERWITHRESPECTTOHIGH
LATITUDEECOSYSTEMSWITH

APPARENT DIFFERENCES ONLY INDICATING DIFFERENT CLASSIlCA


TION SCHEMES &OR ALL SCENARIOS BOTH MODELS AGREE ON

SIMULATING	LARGEDECREASESINTHEAREAOFPURETUNDRA

REPLACED BY THE WARMER TAIGA
TUNDRA 	 LARGE INCREASES

IN THE TEMPERATE MIXED FOREST TABLE 	 MOVING WEST


WARD IN THE 5NITED 3TATES AND NORTHWARD INTO #ANADA

lG	AND	LARGEDECREASESINTHEAREAOFARIDLANDS

TABLE	THATAREREPLACEDBYGRASSLANDSlG	7HEN

THE#/

EFFECTISNOTINCLUDEDINTHEMODELSBOTHSIMULATE

INCREASESINTHEEXTENTOFSAVANNASANDGRASSLANDS

7ITH THE (!$#-35, SCENARIO -!033 SIMULATES

LARGE SHIFTS OF .ORTHWEST TEMPERATE EVERGREEN FORESTS

TO !LASKA REPLACING THE TAIGA
TUNDRA AREA lG 	 BUT

")/-% SHOWS A MUCH SMALLER EXPANSION NOT SHOWN

HERElG#
ANDIN.EILSONETAL	4HEYBOTHSIM


ULATEANEXPANSIONOFTHESOUTHEASTERNTEMPERATEMIXED

FORESTATITSWESTERNEDGE

#ONTERMINOUS53)MPACTS

#OMPARISON"ETWEEN$/,9")/-%AND

-!0335SING&!23CENARIOS

4HREEBIOGEOGRAPHICALMODELS$/,9")/-%AND

-!033	WEREUSEDTOSIMULATEVEGETATIONDISTRIBUTION

FORCURRENTCLIMATECONDITIONSANDFUTURECLIMATECONDI


TIONSUNDERTHREEDIFFERENT'#-S4HETHREEBIOGEOGRA


PHYMODELSPRODUCESIMILARMAPSOFCURRENTVEGETATION

DISTRIBUTION7HETHERTHE#/EFFECTISINCLUDEDORNOT

-!033AND")/-%SIMULATEALOSSOFALPINETUNDRA

ANDBOREALCONIFEROUSFORESTAREATABLE	$/,9SIM


ULATESANINCREASEINALPINETUNDRAWHENTHE#/EFFECT

IS INCLUDED FOR ALL CLIMATE CHANGE SCENARIOS $/,9

ONLY SIMULATES AN INCREASE IN THE EXTENT OF THE BOREAL

CONIFEROUS FOREST UNDER THE /35 SCENARIO WHEN THE

#/ EFFECT IS INCLUDED 7HEN THE #/ EFFECT IS NOT

INCLUDED -!033 SIMULATES A DECREASE IN TEMPERATE

FORESTS ACCOMPANIED BY AN INCREASE IN SAVANNAS AND

GRASSLANDS ON THE OTHER HAND ")/-% SIMULATES AN

INCREASE IN TEMPERATE FORESTS AND TROPICAL BROADLEAF

FORESTAREASATTHEEXPENSEOFSAVANNASSHRUBLANDSAND

ARIDLANDS"OTH$/,9AND-!033SIMULATEINCREASES

INARIDLANDAREA$/,9PRODUCESAGREATEREXPANSION

OFFORESTSINTOTHE'REAT0LAINSANDPRODUCESLITTLEFOREST

DIEBACKUNDERALTEREDCLIMATENOTSHOWNHERE	(OW


EVER$/,9ALSOPRODUCESFARMOREDRAMATICINCREASES

INTHEEXTENTOF3OUTHWESTDESERTSTHANEITHER-!033

OR ")/-% TABLE 	 4HE ONLY GENERAL AGREEMENTS

IN 6%-!0 FOR ALL SCENARIOS AND ALL MODELS ARE THAT

SHRUBLAND AREA DECREASES WHEN THE EFFECT OF #/

 IS

INCLUDEDANDWHENITISNOTTUNDRAANDBOREALFOREST

AREASDECREASE!MOREDETAILEDANALYSISOFTHESERESULTS

ISPRESENTEDIN.EILSONAND#HANEY	

%FFECTSOF#/-!0332ESULTSWITH

&!23CENARIOS

4HERE ARE LARGE DIFFERENCES BETWEEN -!033 RESULTS

WHETHERTHEEFFECTOF#/ISINCLUDEDORNOT&OREXAMPLE

-!033SIMULATEDLARGEDECREASESnPERCENT	INTHE

AREAOFTEMPERATEMIXEDFORESTINTHEEASTERN5NITED3TATES

FOR hWARMERv SCENARIOS SUCH AS THE 5+-/ AND '&$,

WHEN THE #/ EFFECT WAS NOT INCLUDED 4HESE DECREASES

WEREGREATLYREDUCEDnPERCENT	WHENWATERUSEEFl

 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

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4ABLE0ERCENTAGEOFSIMULATEDAREAFOREACHSIMPLIlEDVEGETATIONTYPEUNDERCURRENTCLIMATEFOR.ORTH!MERICAATAHALFDEGREE

LATITUDE
LONGITUDERESOLUTIONBYTHEBIOGEOGRAPHYMODEL-!0334OTALAREAIS

KM0ERCENTAGECHANGEINAREAFOREACH

VEGETATIONTYPEFROMCURRENTCLIMATETOFUTURECLIMATECONDITIONSWITHNO#/

EFFECT!	ANDWITH#/EFFECT"	0ERCENTAGECHANGEIN

VEGETATIONTYPEAREAISCALCULATEDASSCENARIOnCURRENT	CURRENT4HEATMOSPHERICGENERALCIRCULATIONMODELSUSEDTOSIMULATECLIMATE

&!2SCENARIOS	WERETHE/REGON3TATE5NIVERSITYMODEL/35	THE'EOPHYSICAL&LUID$YNAMICS,ABORATORYMODEL'&$,
2	AND

THE5NITED+INGDOM-ETEOROLOGICAL/FlCEMODEL5+-/	

 #URRENT

 OFTOTALLANDAREA	 /35$	 '&$,
2$	 5+-/$	

!7ITHNO#/

EFFECT

 4UNDRA  n n n

 4AIGAn4UNDRA  n n n

 "OREALCONIFEROUSFOREST    n

 4EMPERATEEVERGREENFOREST  n n 

 4EMPERATEMIXEDFOREST  n  n

 3AVANNAWOODLAND    

 3HRUBWOODLAND  n n n

 'RASSLAND    

 !RIDLAND   n 

"7ITH#/EFFECT

 4UNDRA  n n n

 4AIGAn4UNDRA  n n n

 "OREALCONIFEROUSFOREST    n

 4EMPERATEEVERGREENFOREST    

 4EMPERATEMIXEDFOREST    

 3AVANNAWOODLAND    

 3HRUBWOODLAND  n n n

 'RASSLAND  n  

 !RIDLAND   n 

CIENCYWASINCREASEDTABLE	7ITHAMILDERSCENARIO

LIKE/35THESEFORESTSCOULDEVENINCREASEINTHEIREXTENT

BYABOUTPERCENTIFSTOMATALCONDUCTANCEISREDUCED

UP TO  PERCENT BY ELEVATED #/ CONCENTRATION AS IT IS

ASSUMED IN -!033 TABLE 	 )N THE EARLY STAGES OF

WARMINGWHENTEMPERATUREINCREASESARESMALLA#/




INDUCED INCREASE IN WATER USE EFlCIENCY COULD RESULT IN

ANEXPANSIONOFTEMPERATEFORESTSINTONEIGHBORINGDRIER

AREASANDACONCURRENTINCREASEINFORESTDENSITYTHROUGH


OUTMUCHOFTHECURRENTFORESTDISTRIBUTION(OWEVERAS

THE #/ EFFECTS SATURATE AND TEMPERATURES CONTINUE TO

INCREASE THE ELEVATED EVAPORATIVE DEMAND COULD THEN

OVERWHELMTHEINCREASEDWATERUSEEFlCIENCYANDTEM


PERATE FORESTS COULD CONTRACT IN AREA AND UNDERGO A

DROUGHT
INDUCED DECLINE IN VEGETATION DENSITY .EILSON

AND$RAPEK	#OMPLEXRESPONSESOFTHEVEGETATION

TO CHANGES IN THEIR CLIMATIC ENVIRONMENT AND IN THE

ATMOSPHERIC#/CONCENTRATIONARETOBEEXPECTED%ARLY

RESPONSESTOTHE#/FERTILIZATIONEFFECTLEADINGTOAGREEN


INGOFTHELANDMAYBEFOLLOWEDBYFORESTDIEBACKSDUETO

INCREASEDWARMINGANDDROUGHTSTRESS

2EGIONAL)MPACTS

2ESULTS&ROM-!033AND/THER-ODELS5SING

&!2AND3!23CENARIOS

-!033SIMULATIONSATTHEKMRESOLUTIONUSINGTHE

(ADLEY#ENTRESULFATEAEROSOLSCENARIOlGANDTABLE

	SHOWTHATCONIFEROUSFORESTSINNORTHERN-INNESOTA

7ISCONSINAND-ICHIGANUPPERPENINSULA	AREDISPLACED

BYTEMPERATEMIXEDFORESTSEXPANDINGFROMTHEEASTAND

SOUTH &OR ALL &!2 SCENARIOS -!033 SIMULATES LARGE

DECREASESINTHETEMPERATEMIXEDFORESTANDBOREALFOREST

AREAAROUNDTHE'REAT,AKESREGIONWHICHAREREPLACEDBY

SAVANNASANDGRASSLANDSlGSAND	7ITHhWARMv

CLIMATE CHANGE SCENARIOS SUCH AS THE 5+-/ AND TO A

LESSEREXTENTTHE'&$,
2-!033SIMULATESTHEFRAG


MENTATION OF THE SOUTHEASTERN TEMPERATE MIXED FOREST

WHICHISREPLACEDBYDRIERECOSYSTEMSSUCHASSAVANNAS

AND GRASSLANDS lG 	 7ITH COOLER SCENARIOS SUCH AS

/35 -!033 SIMULATES AN INCREASE IN FORESTED AREAS IN

AND AROUND THE 7ILLAMETTE 6ALLEY IN THE 0ACIlC .ORTH

53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

"IOME2EDISTRIBUTION5NDER#LIMATE#HANGE "ACHELETAND.EILSON

4ABLE0ERCENTAGEOFSIMULATEDAREAFOREACHSIMPLIlEDVEG


ETATIONTYPEUNDERCURRENTCLIMATE!	FOR.ORTH!MERICAATAHALF

DEGREELATITUDE
LONGITUDERESOLUTIONBYTHEBIOGEOGRAPHYMODELS

-!033AND")/-%4OTALAREAIS

KM0ERCENTAGE

CHANGEINAREAFOREACHVEGETATIONTYPEFROMCURRENTCLIMATETO

FUTURE CLIMATE CONDITIONS WITH NO #/

 EFFECT "	 AND WITH #/

EFFECT#	0ERCENTAGECHANGEINVEGETATIONTYPEAREAWASCALCU


LATEDASSCENARIOnCURRENT	CURRENT4HEATMOSPHERICGENERAL

CIRCULATIONMODELUSEDTOSIMULATECLIMATE3!2	WASTHE(ADLEY

#ENTREMODELWITHOUTAEROSOLS(!$#-'('	ANDWITHSULFATE

AEROSOLS(!$#-35,	")/-%GROUPSTOGETHERBOREALFOREST

ANDTAIGA
TUNDRADENOTESAVEGETATIONTYPETHATDIDNOT

EXISTINCURRENTCLIMATECONDITIONS.!CORRESPONDSTOAVEGETA


TIONTYPETHATDIDNOTEXISTINEITHERCURRENTORFUTURECLIMATES	

!#URRENTCLIMATE -!033 ")/-%

4UNDRA  

4AIGAn4UNDRA 

"OREALCONIFEROUSFOREST  

4EMPERATEEVERGREENFOREST  

4EMPERATEMIXEDFOREST  

4ROPICALBROADLEAFFOREST  

3AVANNAWOODLAND  

3HRUBWOODLAND  

'RASSLAND  

!RIDLAND  

 .OAEROSOLS 3ULFATEAEROSOLS

"&UTURECLIMATE

WITHNO#/

EFFECT -!033 ")/-% -!033 ")/-%

4UNDRA n n n n

4AIGAn4UNDRA n .! n .!

"OREALCONIFEROUSFOREST  n  n

4EMPERATEEVERGREEN

 FOREST  n  n

4EMPERATEMIXEDFOREST    

4ROPICALBROADLEAFFOREST .!  .! 

3AVANNAWOODLAND    

3HRUBWOODLAND n   

'RASSLAND    

!RIDLAND n n n n

#&UTURECLIMATEWITH#/

EFFECT

4UNDRA n n n n

4AIGAn4UNDRA n .! n .!

"OREALCONIFEROUSFOREST  n  n

4EMPERATEEVERGREEN

 FOREST  n  n

4EMPERATEMIXEDFOREST    

4ROPICALBROADLEAFFOREST    

3AVANNAWOODLAND   n 

3HRUBWOODLAND n n  

'RASSLAND n  n n

!RIDLAND n n n n

WESTANDONTHEWESTERNEDGEOFTHESOUTHEASTERNFORESTS

lG 	 -ESQUITE
OAK WOODLANDS CURRENTLY IN CENTRAL

4EXAS WOULD SHIFT NORTH INTO THE 'REAT 0LAINS REGION

WHILE THE GRASSLANDS WOULD REPLACE THE SEMI
DESERTS OF

EASTERN 4EXAS SOUTHERN .EW -EXICO WESTERN!RIZONA

ANDEASTERN#ALIFORNIA5NDERTHE5+-/SCENARIOlG

ANDTABLE	SOUTHWESTERNWARM
DESERTSPECIESCOULD

EXTEND INTO COLD
DESERT REGIONS AS FAR NORTH AS EASTERN

/REGONAND7ASHINGTONORINTHECASEOFTHE/35SCE


NARIOlG	REMAINABOUTWHERETHEYARETODAY

-EANANNUALTEMPERATURESHAVEINCREASEDGLOBALLYBY

 #PERCENTURYANDBY #INTHESOUTHWESTERNDESERT

REGIONOFTHE5NITED3TATESBETWEENAND,ANE

ET AL 	 %MANUEL ET AL 	 SUGGESTED A POSSIBLE

FUTURE INCREASE OF UP TO  PERCENT IN DESERT LAND AREA

OF .ORTH !MERICA 0REDICTIONS FROM 6%-!0 -EMBERS

	SIMULATIONSHALFDEGREELATITUDE
LONGITUDERESOLU


TION	INCLUDINGBOTHCLIMATECHANGEANDINCREASED#/

SHOW BOTH DECREASES AND INCREASES IN THE AREAL EXTENT

OF SUBTROPICAL SHRUBLANDS SOUTHWESTERN DESERTS	 3INCE

THERMALCONSTRAINTSHAVEKEPTSOUTHWESTERNSPECIESFROM

MOVINGNORTHWARDANINCREASEINTEMPERATUREATHIGHER

LATITUDE AND SUFlCIENT AVAILABLE WATER SHOULD ENABLE

THOSE DESERT SPECIES TO REACH THE 'REAT "ASIN AREA )N

FACT-!033SIMULATESANORTHERNMIGRATIONANDEXPAN


SIONOFSUBTROPICALMIXEDSHRUBSAVANNASINTOTHE'REAT

"ASINREGIONANDASFARNORTHASEASTERN7ASHINGTON9ET

EXPANSION OF DESERT SPECIES DOES NOT NECESSARILY IMPLY

INCREASEDDESERTIlCATION)NFACT-!033SIMULATESUPTO

APERCENTINCREASEINLEAFAREAINDEXPRIMARILYGRASS


LAND	 IN THE SOUTHWESTERN DESERT REGION OF THE 5NITED

3TATESWHEREGRASSESCANOUTCOMPETESHRUBSUNDERFUTURE

WETTERCONDITIONS

#OMPARISONS BETWEEN -!033 AND THE 0N%4 MODEL

!BER AND &EDERER 	 OVER THE 3OUTHEAST ARE CONSIS


TENTINTERMSOFFORESTDECLINEBUTNOTINTERMSOFRUNOFF

"ORCHERSAND.EILSON	0N%4SIMULATEDINCREASESIN

ANNUALRUNOFFFROMTOPERCENTASEVAPOTRANSPIRA


TIONWASALTEREDBYCLIMATECHANGESCENARIOSANDFOREST

DEATHWASOCCURRINGWITHOUTREPLACEMENT-C.ULTYETAL

	0N%4DOESNOTINCLUDEANUNDERSTORYTHUSWHEN

FORESTS DECLINE NO OTHER VEGETATION TYPES REPLACE THEM

AND RUNOFF INCREASES )N -!033 WHEN FORESTS DECLINE

SHRUBSANDGRASSESINCREASEANDMAYUSEASMUCHORMORE

WATERPRODUCINGDECLINESINRUNOFF0N%4ALSOSIMULATED

SEVERE REDUCTIONS IN ANNUAL .00 ON LOBLOLLY PINE SITES

IN4EXASnPERCENT	-ISSISSIPPInPERCENT	&LORIDA

nPERCENT	AND6IRGINIAnPERCENT	WITHCLIMATESCE


NARIOSBASEDONHISTORICALRECORDSFROMTO!BER

ETAL-C.ULTYETALAANDB	

%VENINREGIONSWHERETHEVEGETATIONTYPEWOULDNOT

CHANGE IT COULD EITHER INCREASE IN DENSITY OR DECLINE

7HERE VEGETATION DENSITY CHARACTERIZED IN -!033 BY

LEAFAREAISDECREASINGSOMELEVELOFVEGETATIONDIEBACK

IF FORESTED	 CAN BE EXPECTED OR AT LEAST A REDUCTION IN
26 USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000.

Bachelet and Neilson Biome Redistribution Under Climate Change

Figure 2.1–Top: Aggregated potential vegetation classes simulated for the North American region at a half degree latitude-longitude 

resolution and for the United States at a 10 km resolution for current climate conditions. Bottom: Areas where new vegetation classes 

are simulated in future climate conditions by the MAPSS model using the Hadley Centre climate change scenario including sulfate 

aerosols (HADCM2SUL). Areas where there is no change in vegetation type remain white.
53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

"IOME2EDISTRIBUTION5NDER#LIMATE#HANGE "ACHELETAND.EILSON

4ABLE0ERCENTAGEOFSIMULATEDAREAFOREACHSIMPLIlEDVEGETATIONTYPEUNDERCURRENTCLIMATEINTHECONTERMINOUS53ATAHALF

DEGREELATITUDE
LONGITUDERESOLUTIONFORTHE6%-!00ROJECT!	4HREEBIOGEOGRAPHYMODELSWEREUSED-!033")/-%AND$/,9

4OTALAREAIS

KM0ERCENTAGECHANGEINAREAFOREACHVEGETATIONTYPEFROMCURRENTCLIMATETOFUTURECLIMATECONDITIONSWITH

NO#/

EFFECT"	ANDWITH#/EFFECT#	0ERCENTAGECHANGEINVEGETATIONTYPEAREAISCALCULATEDASSCENARIOnCURRENT	CURRENT

4HEATMOSPHERICGENERALCIRCULATIONMODELSUSEDTOSIMULATECLIMATE&!2	WERETHE'EOPHYSICAL&LUID$YNAMICS,ABORATORYMODEL

'&$,
2	THE/REGON3TATE5NIVERSITYMODEL/35	ANDTHE5NITED+INGDOM-ETEOROLOGICAL/FlCEMODEL5+-/	DENOTES

AVEGETATIONTYPETHATDIDNOTEXISTINCURRENTCLIMATECONDITIONS.!CORRESPONDSTOAVEGETATIONTYPETHATDIDNOTEXISTINCURRENTCLIMATE

CONDITIONSANDDOESNOTEXISTEITHERINFUTURECLIMATECONDITIONS	

6EGETATIONCLASSES -!033 ")/-% $/,9

!#URRENTCLIMATE

 4UNDRA   

 "OREALCONIFEROUSFOREST   

 4EMPERATEEVERGREENFOREST   

 4EMPERATEMIXEDFOREST   

 4ROPICALBROADLEAFFOREST   

 3AVANNAWOODLAND   

 3HRUBWOODLAND   

 'RASSLAND   

 !RIDLAND   

 -!033 ")/-% $/,9

6EGETATIONCLASSES '&$, /35 5+-/ '&$, /35 5+-/ '&$, /35 5+-/

"&UTURECLIMATEWITHNO#/

EFFECT

 4UNDRA n n n n n n n n n

 "OREALCONIFEROUSFOREST n n n n n n n n n

 4EMPERATEEVERGREENFOREST n n n    n n n

 4EMPERATEMIXEDFOREST n n n     n 

 4ROPICALBROADLEAFFOREST .! .! .!    .! .! .!

 3AVANNAWOODLAND    n n n  n n

 3HRUBWOODLAND   n n n n n n n

 'RASSLAND    n n  n  n

 !RIDLAND    n n n   

#&UTURECLIMATEWITH#/EFFECT

 4UNDRA n n n n n n   

 "OREALCONIFEROUSFOREST n n n n n n n  n

 4EMPERATEEVERGREENFOREST       n n n

 4EMPERATEMIXEDFOREST n  n      

 4ROPICALBROADLEAFFOREST .! .! .!    .! .! .!

 3AVANNAWOODLAND  n  n n n n n n

 3HRUBWOODLAND n n n n n n n n 

 'RASSLAND n n  n n  n  n

 !RIDLAND n  n n n n   

THESTANDINGCROP"OTH&!2AND3!2SCENARIOSINDICATE

THAT RELATIVELY LARGE REGIONS OF THE 5NITED 3TATES WOULD

UNDERGOSUCHREDUCTIONSORINCREASES.EILSONETAL	

(OWEVERhHOTTERvMORESEVERESCENARIOSSUCHAS5+-/

INDICATE VEGETATION DIEBACK OR STANDING CROP REDUCTION

OVERMOSTOFTHE53

-ORE$ETAILED#ONSIDERATIONS!BOUT

53&ORESTS7ITH&!2AND3!23CENARIOS

.EILSONAND#HANEY	TRANSLATEDTHE-!033VEG


ETATIONTYPESINTOFORESTTYPECATEGORIES-!033ASSESS

 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

"ACHELETAND.EILSON "IOME2EDISTRIBUTION5NDER#LIMATE#HANGE

4ABLE0ERCENTAGEOFSIMULATEDAREAFOREACHVEGETATIONTYPEUNDERCURRENTCLIMATEINTHECONTERMINOUS53ATAKMRESOLUTION

BYTHEBIOGEOGRAPHYMODEL-!033ANDPERCENTAGECHANGEINAREAFOREACHVEGETATIONTYPEFROMCURRENTCLIMATETOFUTURECLIMATE

CONDITIONSWITHNO#/

EFFECT!	ANDWITH#/EFFECT"	4OTALAREAISKM4HEATMOSPHERICGENERALCIRCULATIONMODELS

USEDTOSIMULATECLIMATEWERETHE'ODDARD)NSTITUTEFOR3PACE3TUDIES')33	THE'EOPHYSICAL&LUID$YNAMICS,ABORATORYMODEL

'&$,
2	THE/REGON3TATE5NIVERSITYMODEL/35	THE5NITED+INGDOM-ETEOROLOGICAL/FlCEMODEL5+-/	ANDTHE(ADLEY

#ENTREMODELWITHOUTAEROSOLS(!$#-'('	ANDWITHSULFATEAEROSOLS(!$#-35,	.OTEIN"#URRENTCLIMATE	ISWITHOUT#/

EFFECT0ERCENTAGECHANGEINVEGETATIONTYPEAREAISCALCULATEDASSCENARIOnCURRENT	CURRENT

 #URRENT	 ')33 '&$, /35 5+-/ #-'(' #-35,

!.O#/

EFFECT

 4UNDRA  n n n n n n

 4AIGAn4UNDRA  n n n n n n

 "OREALCONIFEROUSFOREST  n n n n n n

 4EMPERATEEVERGREENFOREST  n n n n n n

 4EMPERATEMIXEDFOREST  n n n n n 

 3AVANNAWOODLAND       n

 3HRUBWOODLAND  n n  n n 

 'RASSLAND       

 !RIDLAND      n 

"7ITH#/

EFFECT

 4UNDRA  n n n n n n

 4AIGAn4UNDRA  n n n n n n

 "OREALCONIFEROUSFOREST  n n n n n n

 4EMPERATEEVERGREENFOREST     n  

 4EMPERATEMIXEDFOREST   n n n  

 3AVANNAWOODLAND       n

 3HRUBWOODLAND  n n n  n 

 'RASSLAND  n    n n

 !RIDLAND   n   n n

MENT CLASSES	 CORRESPONDING TO AN AGGREGATION OF THE

20!FORESTTYPES7EUSETHESAMEAPPROACHTABLE!IN

!PPENDIX!	 TO PRESENT SOME OF OUR RESULTS WITH MORE

DETAILSABOUTSPECIlCFORESTTYPES

7ITH3!2SCENARIOS')33AND'&$,
2-!033AT

THEKMRESOLUTION	SIMULATESANOVERALLINCREASEINTOTAL

FOREST AREA AND SMALL DECREASES  TO  PERCENT	 WITH

/35AND5+-/SCENARIOSTABLE	5SINGEITHER&!2OR

3!2SCENARIOSTHEMODELSIMULATESDECREASESTO

PERCENT	INNORTHEASTMIXEDFORESTAREAESPECIALLYMIXED

WOODLANDSPERCENT	WHICHAREREPLACEDBYSOUTHEAST

MIXED PINES AND HARDWOOD FOREST TYPE THAT ARE MOVING

NORTHWARDANDEXPANDINGINAREABYTOPERCENTTABLE

	7ITH&!2SCENARIOS-!033SIMULATESADECREASEIN

EASTERNHARDWOODFORESTSTOPERCENT	WITH3!2SCE


NARIOS IT SIMULATES AN INCREASE EXCEPT IN THE CASE OF THE

OAK
HICKORYFORESTSWHICHAREPREDICTEDTODECREASEBY

PERCENTWHENTHE(!$#-35,SCENARIOISUSED

7ITHBOTH&!2AND3!2SCENARIOS-!033SIMULATESA

LARGEDECREASEINTHEAREAOFWESTERNlRANDSPRUCEFORESTS

TOPERCENT	ANINCREASEINCOASTALSPRUCEHEMLOCK

ANDREDWOODFORESTSTOPERCENT	ANDANINCREASE

INWESTERNHARDWOODSTOPERCENT	7ITH3!2SCE


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USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 29

Biome Redistribution Under Climate Change Bachelet and Neilson

Figure 2.2—Areas where new vegetation classes are simulated in future climate conditions by MAPSS using 3 FAR climate change 

scenarios: OSU, GFDL-R30, and UKMO, in the conterminous United States at a 10 km resolution. Areas where there is no change in 

vegetation type remain white.

sink (sequestration of carbon) to a net source (release of 

carbon) of CO2 (Anderson 1991; Oechel et al. 1993). Soil 

warming would also affect methane fluxes from tundra 

plant communities directly affected by drier soil surfaces 

and the resulting increased surface oxidation. The frozen 

soils of boreal forests contain one of the largest pools of 

carbon (Dixon et al. 1994; Gorham 1991) in the terrestrial 

biosphere: 200–500 Gt of carbon (1Gt = 109 metric tons). 

Goulden et al. (1998) used eddy correlation, chamber, 

and laboratory techniques to measure carbon balance in 

a typical black-spruce boreal forest site in Canada. They 

concluded that the deep soil carbon pool was not in equilibrium and discussed the possibility that soil C losses 

might be due to climate warming since Oechel et al. (1993) 

already reported such findings. Projected shifts in vegetation types due to climate warming would probably accentuate soil carbon losses.

Also see Heath and Smith (this volume), Smith and 

Heath (this volume), Birdsey (this volume), and Skog 

and Nicholson (this volume) for additional discussions of 

carbon sequestration in forests and wood products.

CO2 Impacts on Physiological Processes

Elevated CO2 has been documented to increase productivity, nitrogen efficiency, and water-use efficiency 

(IPCC 1996; Bazzaz et al. 1996). Wullschleger et al. (1995) 

reviewed 58 studies where a doubling of atmospheric CO2

concentration resulted in a 32 percent average increase 

in plant dry mass. Norby (1996) studied seven broadleaf 

species under a doubling of atmospheric CO2 concentration over a wide range of conditions, and recorded a 

29 percent increase in annual growth per unit leaf area. 

Eamus (1991) reported reductions of leaf conductance to 
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 4UNDRA    n n n

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  n 
 n

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 !RIDLAND    n n n
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 33

Biome Redistribution Under Climate Change Bachelet and Neilson

Figure 2.3—Aggregated potential vegetation classes simulated by MAPSS for current conditions (top) and areas where new vegetation 

classes are simulated by MAPSS using the GFDL-R30 climate change scenario (bottom) at a 10 km resolution (right) and at a halfdegree resolution (VEMAP) (left) in the conterminous United States. Areas where there is no change in vegetation type remain white.

accurately represent the constantly evolving interactions 

between atmosphere, ocean, and land. In reality, there is 

no “average” year and thus equilibrium models such 

as MAPSS simulate vegetation distributions that do not 

and will not have an exact analog in nature (Borchers 

and Neilson 1998). The value of equilibrium projections, 

however, is that they depict theoretical equilibrium states 

or potential natural “climax” that the vegetation might 

evolve toward, a concept that has guided decision-making 

in forest management and silviculture for many years.
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REGIMESWHICHWILLBEAFFECTEDBYGLOBALCLIMATECHANGE

$ALE 	 &UTURE CLIMATE COINCIDENT WITH CHANGES IN

lREMANAGEMENTPRACTICESANDPOSSIBLEFORESTDECLINEOR

DIEBACK COULD BRING LONGER lRE SEASONS AND POTENTIALLY

MORE FREQUENT AND LARGER lRES IN ALL FOREST ZONES EVEN

THOSE THAT DO NOT CURRENTLY SUPPORT lRE	 &OSBERG 

&LANNIGANAND6AN7AGNER+INGAND.EILSON

7OTTON AND &LANNIGAN  0RICE AND 2IND  &OS

53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

"IOME2EDISTRIBUTION5NDER#LIMATE#HANGE "ACHELETAND.EILSON

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THCENTURYHASALLOWEDBIOMASSINMANYINTERIORFORESTS

TOINCREASECONSIDERABLYOVERHISTORICLEVELS!GEE	

7ITHINCREASEDBIOMASSFORESTSTRANSPIREALMOSTALLAVAIL


ABLESOILWATERANDBECOMEVERYSENSITIVETOEVENSMALL

VARIATIONSINDROUGHTSTRESS&ORESTSARETHENHIGHLYSUS


CEPTIBLETOCATASTROPHIClRESEVENWITHOUTGLOBALWARM


ING.EILSONETAL3TOCKS3TOCKSETAL	

&ORESTSINTHEINTERIOROF.ORTH!MERICAAREEXPERIENCING

INCREASEDFREQUENCIESOFDROUGHTSTRESSPESTINFESTATIONS

ANDCATASTROPHICSTAND
REPLACINGlRES!GEE	4HIS

SEQUENCEOFEVENTSISAREASONABLEANALOGFORWHATCOULD

HAPPEN TO FORESTS OVER MUCH LARGER AREAS IN THE ZONES

INDICATEDBYTHEBIOGEOGRAPHYMODELSTOUNDERGOALOSS

OFBIOMASSORLEAFAREADUETOTEMPERATURE
INDUCEDTRAN


SPIRATION INCREASES AND DROUGHT STRESS /VERPECK ET AL

+INGAND.EILSON	"ECAUSElREMEDIATESRAPID

CHANGEVEGETATIONCHANGECOULDBESIGNIlCANTLYAFFECTED

BYCHANGESINlREFREQUENCY

4HEABILITYTOPREDICTCHANGESINTHEFREQUENCYORINTEN


SITYOFEXTREMEWEATHEREVENTSSUCHASDROUGHTmOODING

HAILHURRICANESANDTORNADOESUSINGGLOBALANDREGIONAL

MODELSISLIMITEDBYTHEIRLACKOFSMALLSCALESPATIALAND

TEMPORALRESOLUTIONANDUNCERTAINTIESABOUTREPRESENTA


TIONOFPROCESSES)0##	

#ONCLUSIONS

#URRENTPUBLISHEDASSESSMENTSOFBIOSPHERICRESPONSES

TO CLIMATE CHANGE ARE BASED ON EQUILIBRIUM MODELS OF

THE TERRESTRIAL BIOSPHERE SUCH AS -!033 ")/-% OR 

AND $/,9 4HESE MODELS SIMULATE THE COMBINATION OF

PLANTLIFEFORMSTHATAREINSTEADYSTATEWITHAGIVENCLI


MATEGIVENAPARTICULARSOILENVIRONMENT4HESEMODELS

WHENRUNWITHVARIOUSSCENARIOSOFCLIMATECHANGESHOW

ASERIESOFSTRONGRESPONSES

	"OREAL FOREST AND TAIGA
TUNDRA REGIONS ARE PREDICTED

TO MOVE NORTHWARD OR UPWARD IN ELEVATION AT THE

EXPENSEOFTHE#ANADIANORALPINETUNDRABOREALFOR


ESTSAREALSOSIMULATEDTOEXPERIENCEDIEBACKSOFVARI


OUS DEGREES ALONG THE SOUTHERN OR LOWER ELEVATIONAL

LIMITSUNDERALLCLIMATECHANGESCENARIOS	4HEBOREAL

FOREST SIMULATED IN -INNESOTA FOR CURRENT CLIMATIC

CONDITIONSTOTALLYDISAPPEARSWITHEVENMILDCLIMATE

CHANGE SCENARIOS SUCH AS THE (!$#-35, 5PPER

ELEVATIONAL OR NORTHERN BOUNDARIES ARE PREDICTED TO

SHIFTUPSLOPEORNORTHWARD

	7ARMERSCENARIOSPRODUCETHELARGESTIMPACTSONTHE

BOREALFORESTBUTAREALSORESPONSIBLEFORFORESTDIEBACK

INTHECONTERMINOUS5NITED3TATES

	.ORTHWESTANDSOUTHEASTFORESTSMIGHTINITIALLYEXPAND

THEN LATER CONTRACT IN AREA &OR THE WARMER CLIMATE

CHANGE SCENARIOS -!033 SIMULATED EXTENSIVE FRAG


MENTATION OF THE EASTERN TEMPERATE MIXED FORESTS

WHICHAREVERYSENSITIVETOCHANGESINAVAILABLEWATER

ANDTHUSTOANYPOSITIVEEFFECTOFELEVATED#/



	3OUTHWESTERNDESERTSPECIESMAYMOVEINTOTHE'REAT

"ASIN REGION GIVEN ADEQUATE THERMAL AND HYDROLOGIC

CONDITIONS

4HETREATMENTOF#/EFFECTSINEACHOFTHETHREEBIO


GEOGRAPHYMODELSSTRONGLYINmUENCESTHEIRSIMULATIONS

ANDEXPLAINSSOMEOFTHEDIFFERENCESAMONGTHEM2ESULTS

FROMTHESEEQUILIBRIUMMODELSALSOCLEARLYDEPENDONTHE

CLIMATECHANGESCENARIOTHATWASUSEDFORTHEASSESSMENT

!LTHOUGHTHEREISAGROWINGCONSENSUSABOUTTHEINCREASE

INFUTUREGLOBALAVERAGETEMPERATURETHEREISLITTLEAGREE


MENT ON THE MAGNITUDE AND TIMING OF THE CHANGES IN

THE HYDROLOGICAL CYCLE IN VARIOUS REGIONS OF THE WORLD

-OREOVERLARGEUNCERTAINTIESREMAINABOUTTHEREGIONAL

CHANGES OF THE VARIOUS CLIMATE VARIABLES +ATTENBERG ET

AL	4HEREFOREASSESSMENTSOFFUTUREVEGETATIONDIS


TRIBUTION CARRY THE UNCERTAINTY INTRINSIC TO THE CLIMATE

CHANGESCENARIOSANDSHOULDNOTBECONSIDEREDASSOLID

PREDICTIONS %QUILIBRIUM MODELS BY DElNITION DO NOT

SIMULATE DYNAMIC OR TRANSIENT CHANGES IN VEGETATION

ASSEMBLAGES4HERATEOFCHANGEPREDICTEDBYTHECLIMATE

MODELS MAY EXCEED HISTORICAL RATES OF CHANGE +IRSCH


BAUM ET AL 	 3IMULATION RESULTS MAY THUS BE USED

TO INDICATE THE DIRECTION OF POSSIBLE CHANGE BUT NOT TO

ESTIMATETHETIMEITMIGHTTAKEAPARTICULARPLANTTYPETO

REACHANEWSITE#RAMERAND3TEFFEN	

-OVEMENTOFTHEVARIOUSECOSYSTEMSMAYALSOBECON


STRAINED AFTER THEIR INITIALLY RAPID EXPANSION BY VARIOUS

FACTORS SUCH AS LACK OF SEED DISPERSAL OR ESTABLISHMENT

LACKOFSEASONALTHERMALREQUIREMENTSFORESTABLISHMENT

POORSOILSORUNFAVORABLELANDUSESUCHASURBANIZATION

ORCULTIVATION&OREXAMPLETHEEXTENTOFTHETEMPERATE

MIXED FOREST ZONE NEAR THE 'REAT ,AKES INCREASES OR

DECLINESDEPENDINGINPARTONSOILPROPERTIES0OSTAND

0ASTOR 	 -OREOVER VEGETATION TYPES WILL PROBABLY

NOTBEDISPLACEDHOMOGENEOUSLY$IFFERENTASSEMBLAGES

MAY APPEAR AND DISAPPEAR OVER LONG PERIODS OF TIME

(UNTLEYETAL,ENIHANAND.EILSON	ANDTHEIR

COMPOSITIONWILLBESTRONGLYAFFECTEDBYCHANGESINDIS


TURBANCEREGIMES

#HANGESINBOUNDARIESLIMITEDBYWATERBALANCEAREDIFl


CULTTOPREDICTBECAUSEOFTHECOMPLEXINTERACTIONSBETWEEN

CHANGESINTEMPERATUREPRECIPITATIONAND#/CONCENTRA


TION )NCREASES IN RAINFALL ARE IN SOME CASES SUFlCIENT TO

BALANCE INCREASES IN EVAPORATIVE DEMAND AND IN OTHER

CASESTHEYARENOT#/
INDUCEDCHANGESINWATERUSEEFl


CIENCYCOULDREVERSEAPOTENTIALDROUGHTRESPONSEFORCER


TAINPLANTS.ORTHERNSTATESSUCHAS-INNESOTA-ICHIGAN

AND 7ISCONSIN WOULD ENDURE DISPLACEMENT OF FORESTS BY
 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

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TIONTHATWOULDBEMEDIATEDBYDROUGHTANDlRE&UTURE

CLIMATE CHANGES COINCIDENT WITH CHANGES IN lRE MANAGE


MENTPRACTICESANDPOSSIBLEFORESTDECLINEORDIEBACKCOULD

BRINGLONGERlRESEASONSANDPOTENTIALLYMOREFREQUENTAND

LARGERlRESINALLFORESTZONES$ROUGHTANDFORESTDIEBACK

COULDINCREASETHEFUELLOADANDTRIGGERMOREFREQUENTAND

LARGERlRESWHILEINCREASEDGROWTHGIVENCLIMATICOSCILLA


TIONSWOULDALSOINCREASETHEFUELLOAD4HEIMPORTANCEOF

lREONVEGETATIONCHANGECOULDINCREASEANDMEDIATERAPID

CHANGES-OREOVERINTHEEARLYSTAGESOFWARMINGWHEN

TEMPERATUREINCREASESARESMALLA#/
INDUCEDINCREASEIN

WATERUSEEFlCIENCYCOULDRESULTINANEXPANSIONOFTEMPER


ATE FORESTS INTO NEIGHBORING DRIER AREAS AND A CONCURRENT

INCREASEINFORESTDENSITYTHROUGHOUTMUCHOFTHECURRENT

FOREST DISTRIBUTION &OR EXAMPLE -!033 SIMULATES THE

EXPANSIONOFTHETEMPERATEEVERGREENFORESTINTO#ANADA

WHERE IT REPLACES THE TAIGA
TUNDRA )T ALSO SIMULATES THE

EXPANSIONOFTHEEASTERNTEMPERATEMIXEDFORESTWESTWARD

INTOTHECENTRAL5NITED3TATESATTHEEXPENSEOFSAVANNAS!

SIMILAR SHIFT OF NORTHWESTERN FORESTS INTO DRIER AREAS IS

SIMULATEDUNDERTHEMODERATEWARMINGSCENARIOS!STHE

#/EFFECTSATURATESANDTEMPERATURESCONTINUETOINCREASE

HOWEVER THE ELEVATED EVAPORATIVE DEMAND COULD OVER


WHELMTHEINCREASEDWATERUSEEFlCIENCY4EMPERATEFORESTS

COULDTHENCONTRACTINAREAANDUNDERGOADROUGHT
INDUCED

DECLINEINVEGETATIONDENSITY.EILSONAND$RAPEK	

#OMPARINGTHEhWARMERvCLIMATECHANGESCENARIOSWITH

COOLERONESILLUSTRATESWHATMIGHTHAPPENTOTHESOUTHEAST


ERN MIXED FOREST WHERE EXTENSIVE FRAGMENTATION IS SIM


ULATEDTOOCCURWITHHIGHERTEMPERATURES4HEBENElCIAL

EFFECTSOFELEVATED#/COULDMAKEALARGEDIFFERENCEINTHE

RESPONSEOFTHESOUTHEASTERNFORESTSTOTHEWARMING

&INALLYWEWANTTOEMPHASIZETHATIMPORTANTFACTORS

SUCHASGRAZINGBYHERBIVORESINVASIONSBYWEEDSDIS


EASESANDPESTSANDCHANGESINLANDUSEDUETOHUMAN

DEVELOPMENTCOULDDRASTICALLYALTERTHERESPONSESOFVEG


ETATIONTOCLIMATICCHANGES4HEREISCURRENTLYNOMODEL

THATINCORPORATESALLTHESEFACTORSANDADDINGSUCHCOM


PLEXITYTOCURRENTLYEXISTINGMODELSWOULDALSOINCREASE

THEMARGINOFUNCERTAINTYINTHERESULTINGPREDICTIONS#LI


MATECHANGEASSESSMENTSSHOULDTHUSINCLUDETHESEFAC


TORSBUTNEWMETHODSNEEDTOBEDEVELOPEDTORETAINTHE

USEFULNESS OF MODEL SIMULATIONS BY KEEPING THE UNCER


TAINTYMANAGEABLE

!CKNOWLEDGMENTS

4HISWORKWASSUPPORTEDBYTHE53$!&OREST3ERVICE

0.7.%3%3TATIONS0.7
	ANDTHE53'3"2$

#!



	

4HIS PAPER COULD NOT HAVE BEEN WRITTEN WITHOUT THE

HELPOF2AY$RAPEK/REGON3TATE5NIVERSITYWHOSESKILLS

IN UNEARTHING ARCHIVED DATA AND MAPS ARE UNEQUALED

4HE AUTHORS WANT TO THANK THE REVIEWERS OF THE EARLY

DRAFTOFTHISCHAPTER3TEVE7ONDZELL#HRIS$ALY,INDA

(EATH2ICHARD"IRDSEYAND,INDA*OYCE4HEYALSOWANT

TO THANK THE FOLLOWING REVIEWERS FOR THEIR HELPFUL COM


MENTSONTHElNALDRAFTOFTHECHAPTER,LOYD)RLAND"RENT

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,ITERATURE#ITED

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 HALFDEGREEn.ORTH!MERICA KMn53

-ODELRESOLUTION $ECREASE )NCREASE $ECREASE )NCREASE

6EGETATIONCLASSES

 4UNDRA    

 4AIGA
4UNDRA    

 "OREALCONIFEROUSFOREST    

 4EMPERATEEVERGREENFOREST    

 4EMPERATEMIXEDFOREST    

 3AVANNAWOODLAND    

 3HRUBWOODLAND    

 'RASSLAND    

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2SCENARIOISAPPLIEDANDTHE#/

EFFECTISINCLUDEDIN-!033

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LONGITUDERESOLUTION	THE6%-!0PROJECTATTHESAMERESOLUTIONASTHE

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 HALFDEGREEn.ORTH!MERICA HALFDEGREEn6%-!053	 KMn53

-ODELRESOLUTION $ECREASE )NCREASE $ECREASE )NCREASE $ECREASE )NCREASE

6EGETATIONCLASSES

 4UNDRA      

 4AIGAn4UNDRA      

 "OREALCONIFEROUSFOREST      

 4EMPERATEEVERGREENFOREST      

 4EMPERATEMIXEDFOREST      

 3AVANNAWOODLAND      

 3HRUBWOODLAND      

 'RASSLAND      

 !RIDLAND      
#(!04%2

%COSYSTEM0RODUCTIVITYANDTHE)MPACTOF#LIMATE#HANGE

,INDA!*OYCE53$!&OREST3ERVICE2OCKY-OUNTAIN2ESEARCH3TATION

-ARTHA.UNGESSER-!4#/-

)NTRODUCTION

%ARLIERANALYSESOFTHESUPPLYANDDEMANDOFTIMBER

ASSUMEDTHECONTINUATIONOFHISTORICALCLIMATEANDTHUS

DIDNOTEXPLICITLYINCORPORATEFACTORSSUCHASTEMPERATURE

ORPRECIPITATIONINTOTHEPROJECTIONSOFTIMBERGROWTH&OR


ESTS ARE ADAPTED TO LOCAL CLIMATES AND CHANGES IN THESE

CLIMATES ARE LIKELY TO IMPACT FUTURE FOREST GROWTH AND

TIMBEROUTPUTS7ITHINTHESTRATEGICPLANNINGPROCESSOF

THE&OREST3ERVICE*OYCEETAL	THEANALYSISOFECO


SYSTEMPRODUCTIVITYASINmUENCEDBYCLIMATICFACTORSHAS

BEENIDENTIlEDASACRITICALQUESTIONINORDERTOADDRESS

THECHALLENGINGPROBLEMSASSOCIATEDWITHCLIMATECHANGE

s 7HAT ARE THE LIKELY EFFECTS OF INCREASING ATMOSPHERIC

CARBONDIOXIDEANDPROSPECTIVECLIMATECHANGEONECO


SYSTEM PRODUCTIVITY AS MEASURED BY CHANGES IN NET

PRIMARYPRODUCTIVITY

)NTHELAST20!!SSESSMENT53$!&OREST3ERVICE	

THECONSEQUENCESOFELEVATEDCARBONDIOXIDEANDCLIMATE

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INED USING CLIMATE MODEL SCENARIOS AND AN ECOLOGICAL

MODEL4%-*OYCEETAL	4HESERESULTSWERETHEN

USED TO EXAMINE THE IMPACT OF CLIMATE CHANGE ON THE

SUPPLYANDDEMANDFORTIMBERPRODUCTSONPRIVATETIM


BERLANDS IN THE 5NITED 3TATES SEE lG  *OYCE AND

"IRDSEYTHISVOLUME	)NTHISANALYSISMOSTOFTHEFOREST

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THIS CHANGE IN HARVESTABLE INVENTORIES TIMBER HARVESTS

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REGIONS ADJUSTED TO TAKE ADVANTAGE OF LOWER COST RAW

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TALDATAANDMODELINGANALYSESENHANCETHEPICTUREOFTHE

POTENTIAL IMPACT OF CARBON DIOXIDE AND CLIMATE CHANGE

ONFORESTS)NTHISCHAPTERWEPRESENTTHERESULTSOFSUCH

RESEARCH

.EWEXPERIMENTSONTHEIMPACTOFCARBONDIOXIDEON

VEGETATIONANDMETA
ANALYSESOFTHEACCUMULATEDRESEARCH

HAVEDEMONSTRATEDTHEIMPACTOFCARBONDIOXIDEONPLANT

PROCESSES)NTHISCHAPTERWECOMPARETHEIMPACTOFELE


VATEDCARBONDIOXIDEONECOSYSTEMPRODUCTIVITYASDETER


MINEDFROMRECENTEXPERIMENTALDATAWITHPRODUCTIVITY

RESULTSFROMTHELAST20!ANDOTHERECOLOGICALMODELANAL


YSES)NADDITIONWEEXPLOREWHETHERTHESEPOTENTIALPRO


DUCTIVITYSHIFTSAREWITHINTHERANGEOFPRODUCTIVITYSHIFTS

THATTIMBERMANAGEMENTTREATMENTSCOULDINDUCEINMAN


AGEDFORESTS7ECOMPARETHERESULTSOFECONOMICRESEARCH

ANALYZINGTHEPOTENTIALTOINCREASETIMBERGROWTHASAN

INCENTIVETOSTORECARBONWITHTHESEPROJECTEDCHANGESIN

PRODUCTIVITYFROMCLIMATECHANGE

)NTHELAST20!!SSESSMENTTWOOFTHEMODELINGASSUMP


TIONSWERE	CLIMATEANDVEGETATIONWEREINEQUILIBRIUM

AND	THESPATIALSCALEOFTHEECOLOGICALMODELWASANADE


QUATE SCALE FOR NATIONAL LEVEL ANALYSES 2ECENT MODELING

STUDIESHAVEEXAMINEDTHESEASSUMPTIONS

)N MOST ECOLOGICAL MODELS EVEN NOW	 VEGETATION IS

REPRESENTED AS PRISTINE MATURE VEGETATION RATHER THAN

THEACTUALVEGETATIONOFMANYDIFFERENTAGECLASSESSUC


CESSIONAL STAGES INTRODUCED SPECIES AND MANAGEMENT

HISTORIES &URTHER FOR BOTH THE ECOLOGICAL AND THE ECO


NOMIC MODELS A BROAD RANGE OF HABITATS AND SPECIES

WEREAGGREGATEDINTOECOSYSTEMSORTIMBERMANAGEMENT

TYPES RESPECTIVELY FOR MODELING PURPOSES 4HE VEGETA


TION AGGREGATION SCHEMES AND THE NATURE OF THE SPATIAL

EXTRAPOLATIONDIFFERBETWEENTHEECOLOGICALANDTHEECO


NOMICMODELS4HEIMPLICATIONSOFANECOLOGICALVERSUS

ATIMBERMANAGEMENTCLASSIlCATIONSCHEMEAREDISCUSSED

INTHISCHAPTER

#OMPUTATIONAL PROBLEMS ARISE WHEN INTEGRATING OR

LINKING MODELS THAT OPERATE AT DIFFERENT TEMPORAL AND

SPATIALSCALES#OMPUTATIONALLIMITATIONSFORCEATRADEOFF

BETWEENTHESPATIALEXTENTOFTHEANALYSISOFTENDICTATED

BY POLICY CONSIDERATIONS	 AND THE GRAIN OF THE ANALYSIS

#LIMATE MODELS IN ORDER TO COMPUTE GLOBAL DYNAMICS

OPERATE AT LARGE SPATIAL SCALES GRID CELLS RANGE FROM 

DEGREES TO  DEGREES RESULTING IN COARSE RESOLUTION OF

MOUNTAINOUS REGIONS AND SMALL SCALE CLIMATE FEATURES

-ESO
SCALE CLIMATE MODELING NOW OFFERS A lNER DEPIC


TIONOFCLIMATEFEATURESANDTHEPOSSIBILITYTOINCORPORATE

THEEFFECTSOFVEGETATIONANDLANDUSEFEEDBACKSONTOTHE

ATMOSPHERIC PROCESSES BUT AT LARGE COMPUTATIONAL COST

'IVENTHISOPPORTUNITYITISIMPORTANTTOUNDERSTANDTHE

UTILITYOFGOINGTOAlNERSCALEINTHEECOLOGICALANALYSES

BECAUSETHECOMPUTATIONALINTENSITYINCREASESBYANORDER

OFMAGNITUDEWHENAKMSCALEISUSEDINSTEADOFTHE

TRADITIONAL  DEGREE SCALE )N THIS CHAPTER WE REPORT

RESEARCHRESULTSQUANTIFYINGTHECLIMATECHANGERESPONSES

INECOSYSTEMPRODUCTIVITYATlNERVERSUSCOARSERSPATIAL

SCALES

53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 
 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

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INCREASEDFROMPERCENTTOPERCENTDEPENDINGUPON

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TIONS!LARGEMODELINGSTUDYCOMPAREDTHERESPONSESOF

SEVERALBIOGEOCHEMISTRYMODELSFORALLECOSYSTEMSWITHIN

THECONTERMINOUS5NITED3TATESTOALTEREDCLIMATEANDELE


VATEDCARBONDIOXIDE6%-!0MEMBERS	!VERAGED

ACROSSALLECOSYSTEMS.00RESPONSESINCREASEDFROM

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WERE HIGHER THAN THE RESPONSES FOR THE #ENTURY -ODEL

0ARTONETAL	ANDTHE"IOME
"'#MODEL2UN


NING2UNNINGAND#OUGHLAN	TABLE	4HE

LARGEST .00 RESPONSE FOR BOTH 4%- AND #ENTURY 

AND  PERCENT RESPECTIVELY	 WAS FOR THE 5+-/ SCE


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"'#PER


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"'#!TTHEGLOBALSCALE

THE.00RESPONSESTOCLIMATECHANGEANDELEVATEDCARBON

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LOWERTHANTHE.00RESPONSESREPORTEDFORTHELAST20!

ANALYSIS(OWEVERTHISRESULTREmECTSTHEGLOBALEXTENTOF

THESEMEASURES

4HESEPROJECTEDRESPONSESTOALTEREDCLIMATEANDELE


VATEDATMOSPHERICCARBONDIOXIDEINCORPORATETHEVARIA


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OR THE GLOBE )N CONTRAST EXPERIMENTAL STUDIES EXPLORE

THE UNDERLYING MECHANISMS FOR A PLANTS RESPONSE TO A

CHANGE IN ATMOSPHERIC CARBON DIOXIDE IN A CONTROLLED

ENVIRONMENT %LEVATED ATMOSPHERIC CARBON DIOXIDE HAS

BEENSHOWNTOINCREASEPHOTOSYNTHESISENHANCERATESOF

CARBONASSIMILATIONINCREASESTEMANDROOTBIOMASSAND

INTERACTWITHOTHERPLANTNUTRIENTS#EULEMANSAND-OUS


SEAU#URTISAND7ANG-C'UIREETALB

3AXEETAL	)NAREVIEWOFWOODYPLANTS#EULEMANS

AND-OUSSEAU	REPORTEDTHEMEANBIOMASSINCRE


MENTFROMELEVATED#/WASPERCENTFORCONIFEROUS

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PERCENT&ORDECIDUOUSTREESTHERANGEWASFROMnTO

PERCENT3UMMARIZINGSTUDIESNOTINVOLVINGSTRESS

COMPONENTS 3AXE ET AL 	 REPORTED LARGER AVERAGE

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TERMBIOMASSINCREMENTDIFFERENCESUNDERELEVATED

#/FORCONIFERSOFPERCENTANDSMALLERAVERAGESFOR

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53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

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4EMPERATECONIFERXEROMOPHIC    

4HESE RESPONSES FROM EXPERIMENTAL STUDIES ARE NOT

WITHOUTCONTROVERSY/FPARTICULARCONCERNISWHETHERTHE

RESPONSEISSUSTAINEDOVERTHELIFESPANOFTHETREE-OST

OFTHESESTUDIESAREDONEWITHSEEDLINGSORJUVENILETREES

.ORBY ET AL 	 CONCLUDED THAT A RESPONSE IN PRO


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MAYBECANCELEDBYLATERPHYSIOLOGICALORMORPHOLOGICAL

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POPULAR ,IRIODENDRON TULIPIFERA

,	 WHOLE
PLANT CARBON STORAGE DID NOT INCREASE EVEN

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LEVELPHOTOSYNTHESISANDLOWERRATESOFFOLIAR

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0AN ET AL 	 EXAMINED THE MODELED RESPONSES

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7HEN EXAMINED FOR UNDERLYING DIFFERENCES 0AN ET AL

	NOTEDTHATTHETHREEMODELSTENDTOAGREEINTHEIR

PROJECTEDESTIMATESOF.00RESPONSETODOUBLEDCARBON

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IMPACTSTUDIESTHEREISLITTLE

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LEVEL RESPONSE OF

.00TOELEVATED#/ALONGCLIMATICGRADIENTS0ANETAL

	 4HESE BIOGEOCHEMISTRY MODELS SERVE AS DIFFERENT

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7HEN EXPERIMENTAL STUDIES SINCE 	 REPORTING

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IRRIGATIONFERTILIZATION   4OWNEND	

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IRRIGATION  4OWNEND	

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 7ILKINSETAL	

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"ETULALENTA 3TEMMASSROOTMASSLEAFMASS   2OCHEFORTAND"AZZAZ

     	

"ETULAPAPYRIFERA 4OTALBIOMASSlNECOARSEROOTMASS   "ERNTSONAND"AZZAZ

     	

"ETULAPAPYRIFERA 3TEMMASSROOTMASSLEAFMASS   2OCHEFORTAND"AZZAZ

     	

"ETULAPOPULIFOLIA 3TEMMASSROOTMASSLEAFMASS   2OCHEFORTAND"AZZAZ

     	

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&ORESTTYPE '&$,
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1

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4EMPERATEDECIDUOUS n     

4EMPERATEMIXED      

4EMPERATEBROAD
LEAVEDEVERGREEN    

4EMPERATEFORESTWETLAND n     

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.UNGESSERETAL	
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RESPONSESOFLEAFAREAANDLEAFNITROGENCONTENTALONG

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s7HATISTHERELATIVEROLEOFCHANGESINNITROGENREQUIRE


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IES SHOULD MEASURE THE mUXES AND THE POOLS OF CARBON

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OF ECOSYSTEMS /UR UNDERSTANDING OF THESE PROCESSES

IS THE BASIS FOR THE DEVELOPMENT OF POLICIES ON CARBON

SEQUESTRATIONOPTIONSINFORESTS

#LIMATE6ERSUS-ANAGEMENT)NmUENCESIN

4IMBER0RODUCTIVITY

4HEPRODUCTIVITYSHIFTSINTHELAST20!CLIMATECHANGE

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SEEN UNDER ECONOMIC OPPORTUNITIES FOSTERED BY TIMBER

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TIAL TO INCREASE TIMBER GROWTH FOR CARBON STORAGE "IO


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MEASURED PLOTS	 FOR EACH SITE CLASS FOREST MANAGEMENT

TYPEANDTREATMENTOPPORTUNITYONTIMBERLANDSUITABLE

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CALOPPORTUNITIESEXISTTOINCREASETIMBERGROWTHBYABOUT

BILLIONCUBICFEETOVERMILLIONACRESANINCREASE

OF  PERCENT OVER THE CURRENT NET ANNUAL GROWTH OF 

BILLIONCUBICFEET3EVERALDECADESWOULDBEREQUIREDTO

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ECONOMIC OPPORTUNITIES 6ASIEVICH AND!LIG 	 ESTI


MATEDTHATNETANNUALGROWTHCOULDBEINCREASEDBY

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NET ANNUAL GROWTH #APITAL INVESTMENT COSTS WOULD BE

BILLION4HESEBIOLOGICALANDECONOMICOPPORTUNI


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NOTBEINGSEENUNTILNEARTHEENDOFTHESTCENTURY4HUS

TIMBERMANAGEMENTCOULDPOTENTIALLYENHANCEFORESTPRO


DUCTIVITYTOALARGERDEGREETOPERCENT	THANISCUR


RENTLYPROJECTEDFORTHEPRODUCTIVITYRESPONSESTOCHANGES

INCARBONDIOXIDEORCLIMATETOPERCENTTABLE	

0OTENTIAL6EGETATIONAND#URRENT

6EGETATION$ESCRIPTIONS

)N THE LAST &OREST 3ERVICE CLIMATE CHANGE ASSESSMENT

.00RESPONSEFROMTHEECOLOGICALMODEL4%-	WASUSED

TO ADJUST GROWTH IN THE FOREST SECTOR MODEL 4!--


!4,!3
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OF.00RESPONSESFROMTHEECOSYSTEMCLASSIlCATIONUSED

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!4,!3
.!0!0MODEL

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	 4HE &OREST 3ERVICE INVENTORY CLASSIlES FOREST LAND

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!4,!3
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TOACOMMERCIALTREESPECIESFOREXAMPLE$OUGLASlRORTO

ACLASSOFlBERSUCHASSOFTWOODMIX4HE4!--
!4,!3


.!0!0 MODEL WAS NOT DEVELOPED TO MODEL GEOGRAPH


ICALLY RESOLVED DATA HENCE THE YIELD TABLES REPRESENTED

LARGERGEOGRAPHICREGIONSTYPICALLYAMULTI
STATEGROUP


INGOFOWNERSHIP
FORESTTYPE
AGECLASSES

&ORTHE4%-MODELSIMILARTOOTHERBIOGEOCHEMISTRY

MODELSDATAFROMINTENSIVELYSTUDIEDECOSYSTEMSREPRE


SENTATIVEOFPARTICULARVEGETATIONTYPESAREUSEDFORCAL


IBRATION OF MODEL BEHAVIOR 4HESE MODELS ARE SPATIALLY

EXTRAPOLATED BY USING VEGETATION MAPS &OR THE 4%-

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!TLASFORESTSECTORMODEL

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$OUGLASlR
MIXED 8

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0UREHEMLOCK 8

&IR
SPRUCE 8 8  8 8

4RUElR  8 8

0INES 8

,ODGEPOLEPINE  8   8

0ONDEROSAPINE  8 8 8 8

3OFTWOODMIX 8

*ACKPINE      8

2EDPINE      8

7HITEPINE      8

7HITE
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JACKPINE       8

3PRUCE
lR      8 8

2EDALDER 8

2EDWOOD   8

(ARDWOODMIX 8

(ARDWOOD   8  8

-IXEDCONIFER   8

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/AK
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,OWLANDHARDWOODS      8

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/AK
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%LM
ASH
REDMAPLE       8

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BEECH
BIRCH       8

!SPEN
BIRCH       8

0LANTEDPINE        8

.ATURALPINE        8

5PLANDHARDWOOD        8

,OWLANDHARDWOOD        8

GRID CELL -C'UIRE ET AL 	 AND THESE TYPES WERE

THEN AGGREGATED INTO A SMALLER SET OF ECOSYSTEM TYPES

INCLUDINGFORESTTYPESBOREALFORESTBOREALFORESTWET


LAND TEMPERATE CONIFEROUS FOREST TEMPERATE DECIDUOUS

FORESTTEMPERATEMIXEDFORESTTEMPERATEBROADLEAFEVER


GREENFORESTANDTEMPERATEFORESTWETLAND4HISSPATIALLY

EXPLICIT VEGETATION INFORMATION IS THEN USED TO EXTRAPO


LATETHEECOLOGICALMODELTOTHELARGERSPATIALSCALEOFTHE

5NITED3TATES)NTHELAST20!ANALYSIS*OYCE	.00

RESPONSESTOCLIMATECHANGEWERECOMPUTEDFOREACH

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!4,!3
.!0!0

MODEL

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%YRE	THISCLASSIlCATIONWASUSEDTOLINK4%-ECO


SYSTEMTYPESWITHTIMBERMANAGEMENTTYPESTABLE	

4HE CONVERSION PROCESS INVOLVED ASSOCIATING THE 4%-

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CELL-C'UIREETAL	TOTHEFORESTTYPECORRESPONDING

TOTHAT0.6TYPEASDElNEDBY'ARRISONETAL	

3EVERALASSUMPTIONSWEREMADEIFNOGRIDCELLWITHIN

AREGIONWASDOMINATEDBYTHE0.6TYPEASSOCIATEDWITH

THE FOREST MANAGEMENT TYPE 4HIS SITUATION MIGHT ARISE
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*OYCEAND.UNGESSER %COSYSTEM0RODUCTIVITYANDTHE)MPACTOF#LIMATE#HANGE 4ABLE4RANSLATIONOFTHE&OREST#LASSIlCATIONUSEDINTHE&OREST3ERVICE&)!INVENTORYUSING0OTENTIAL6EGETATIONOF+àCHLER	TOTHE6%-!0CLASSIlCATION 6%-!0VEGETATION +UCHLER &)! 4%- "OREALCONIFEROUS	 
7ESTERNSPRUCE
lR	 &IR
SPRUCE	 "OREALCONIFEROUSFOREST


3OUTHWESTERNSPRUCE
lR	 &IRSPRUCE	
'REAT,AKESSPRUCE
lR	 3PRUCE
lR	
.ORTHEASTERNSPRUCE
lR	 3PRUCE
lR	

 
3OUTHEASTERNSPRUCE
lR	 3PRUCE
lR	4EMPERATEMARITIME 
3PRUCE
CEDAR
HEMLOCK	 (EMLOCK
3ITKASPRUCE	 -ARITIMETEMPERATECONIFEROUSFOREST

CONIFEROUSFOREST	 
#EDAR
HEMLOCK
$OUGLASlR	 $OUGLAS
lR	


3ILVERlR
$OUGLASlR	 &IR
SPRUCE	
&IR
HEMLOCK	 &IRSPRUCE	
-IXEDCONIFER	 0ONDEROSAPINE	
2EDWOOD	 2EDWOOD	

4EMPERATECONTINENTAL 
2EDlR	 &IR
SPRUCE	 #ONTINENTALTEMPERATECONIFEROUSFORESTCONIFEROUSFOREST	 
0INE
CYPRESS	 0ONDEROSAPINE	


,ODGEPOLEPINE
SUBALPINE	 ,ODGEPOLEPINE	

 0ONDEROSASHRUBNONE	 0ONDEROSAPINE	 7ESTERNPONDEROSA	 0ONDEROSAPINE	 $OUGLASlR	 $OUGLASlR	 #EDARHEMLOCKPINE	 7ESTERNWHITEPINE	 'RANDlR$OUGLASlR	 ,ARCH	 %ASTERNPONDEROSAPINE	 0ONDEROSAPINE	 "LACK(ILLSPINE	 0ONDEROSAPINE	 0INE$OUGLASlR	 0ONDEROSAPINE	 !RIZONAPINE	 &IR
SPRUCE	 3PRUCElR
$OUGLASlR	 &IR
SPRUCE	 'REAT,AKESPINE	 7HITE
RED
JACKPINE	#OOLTEMPERATE -OSAICOFCEDARHEMLOCK
$OUGLAS $OUGLASlR	 CONTINENTALTEMPERATECONIFEROUSMIXEDFOREST	  lRFORESTAND/REGONOAKWOODS	  FORESTTEMPERATEDECIDUOUSFOREST .ORTHERNHARDWOODS	 -APLE
BEECHBIRCH	 .ORTHERNHARDWOODSlR	 -APLE
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BIRCH	 .ORTHERNHARDWOODSSPRUCE	 -APLE
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CONTINUED
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#ALIFORNIAMIXEDEVERGREEN	 $OUGLASlR	 CONTINENTALTEMPERATECONIFEROUS MIXEDFOREST	 
"LACKBELT	 /AK
HICKORY	 FORESTTEMPERATEDECIDUOUS


,IVEOAKSEAOATS	 /AK
GUM
CYPRESS	 FORESTTEMPERATEBROADLEAVED

 
#YPRESSSAVANNA	 /AK
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CYPRESS	 EVERGREENFOREST 
-ANGROVE	 /AK
GUM
CYPRESS	


/AK
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PINE	 ,OBLOLLYSHORTLEAFPINE	

   ANDOAK
PINE	


3OUTHERNMIXED	 ,ONGLEAF
SLASHPINE	

  ANDOAK
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3ANDPINESCRUB	 ,OBLOLLY
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3UBTROPICALPINEFOREST	 ,ONGLEAF
SLASH	4EMPERATEDECIDUOUSFOREST	 
/REGONOAKWOODS	 7ESTERNHARDWOODS	 4EMPERATEDECIDUOUSFOREST


.ORTHERNmOODPLAIN	 %LM
ASH
COTTONWOOD	
-APLE
BASSWOOD	 -APLE
BEECH
BIRCH	
/AK
HICKORY	 /AK
HICKORY	
%LM
ASH	 %LM
ASH
COTTONWOOD	
"EECHMAPLE	 -APLE
BEECH
BIRCH	
-IXEDMESOPHYTIC	 -APLE
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BIRCH	
!PPALACHIANOAK	 /AK
HICKORY	

+àCHLERNUMBERINGSCHEME4HElRSTNUMBERINEACHBOXISTHENUMBERREPORTEDINTHE+àCHLERPUBLICATION4HENUMBERIN	AFTERTHETYPENAMEISTHENUMBERREPORTEDONTHE

MAPWHICHWASALSOTHENUMBERUSEDINTHE&OREST3ERVICEPUBLICATIONMAPPING&2%3%COSYSTEMSANDTHE+àCHLER3YSTEM)N6%-!0VEGETATIONTYPESREPRESENTEDBYMAPSYMBOLSNEVERDOMINATEDATTHELONGITUDEsLATITUDEGRIDCELLREPRESENTATION4YPES

-ESQUITEBOSQUES3EAOATSPRAIRIEAND.ORTHERNCORDGRASSPRAIRIEARENON
FORESTTYPES&ORTHESETYPES)USEDATABLEPROVIDEDBY$AVE+ICKLIGHTERTHATHADIDENTIlEDTHE

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BIRCHTYPE)NTHE%ASTTHISTYPEWASINDEXEDTOTHESERALSTAGESOF.ORTHERNHARDWOODS.ORTHERN

HARDWOODS
lRFORESTSAND.ORTHERNHARDWOODS
SPRUCEFORESTANDIDENTIlEDASTEMPERATEDECIDUOUS6%-!0TYPE)NTHE7ESTTHISTYPEWASALSOCODEDASTEMPERATEDECIDUOUS6%-!0TYPE!LL&)!WESTERNHARDWOODSTYPEWEREIDENTIlEDASTEMPERATEDECIDUOUS6%-!0TYPE
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IF CLIMAX VEGETATION WERE NOT DOMINANT WITHIN PARTS OF

THEREGIONORIFTHECOMMERCIALSPECIESHAPPENEDNOTTO

BETHETREESPECIESNAMEDINTHECLIMAXTYPE&OREXAM


PLESOFTWOODMIXAFORESTMANAGEMENTTYPEUSEDINTHE

0ACIlC.ORTHWEST
WESTTIMBERSUPPLYREGIONWASAMIX

OFTWOFORESTTYPESREDWOODANDLARCH.O0.6TYPEWAS

REPRESENTATIVEOFREDWOODWITHINTHE0ACIlC.ORTHWEST


WESTREGIONWESTSIDEOF/REGONAND7ASHINGTON	4HE

NEAREST 0.6 TYPE WAS THE REDWOOD TYPE IN THE 0ACIlC

3OUTHWESTREGION(ERETHEASSUMPTIONWASMADETHAT

THERESPONSETOCLIMATECHANGEWOULDBEMOREAPPROPRI


ATELY DESCRIBED BY USING A SIMILAR ECOSYSTEM TYPE BUT

OUTSIDE OF THE REGION RATHER THAN A DIFFERENT VEGETATION

BUTINSIDETHEREGION)NANOTHEREXAMPLEINTHE0ACIlC

.ORTHWEST
WEST REGION RED ALDER WAS A FOREST MANAGE


MENTTYPETHATDIDNOTHAVEACORRESPONDING0.6TYPE

!CCORDINGTO%YRE	REDALDERISASUCCESSIONALTYPE

REPLACEDBYTHE0ACIlC$OUGLASlRANDWESTERNHEMLOCK


SITKA SPRUCE TYPES %YRE 	 DID ASSIGN RED ALDER TO

THEINVENTORYTYPEOFWESTERNHARDWOODSAND'ARRISON

ET AL 	 ASSIGNED THE 0.6 TYPE /REGON OAKWOOD

WITHTHEINVENTORYTYPEOFWESTERNHARDWOODS(OWEVER

THIS0.6TYPEOCCURSSOLELYALONGTHE/REGON
#ALIFORNIA

BORDER IN THE 0ACIlC .ORTHWEST
WEST REGION AND RED

ALDERISCOMMONONBOTTOMLANDSSHELTEREDCOVESAND

ON MOIST SLOPES OF THE #OAST AND #ASCADE RANGES %YRE

	4HUSTHE0.6TYPEASSOCIATEDWITHTHECLIMAXVEG


ETATIONTHATTYPICALLYREPLACESREDALDERTHECEDARHEM


LOCK
$OUGLASlRTYPEWASUSEDTOMODIFYTHEYIELDTABLE

FORREDALDER

)N THE 0ACIlC .ORTHWEST
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DOMINATEANYOFTHEGRIDCELLSWITHINTHISREGION!CCORD


INGTO%YRE	LODGEPOLEPINEWITHINTHISREGIONWAS

ASSOCIATED WITH SUBALPINE lR %NGELMANN SPRUCE WHITE

SPRUCEAND2OCKY-OUNTAIN$OUGLASlR4HE0.6TYPES

WITH THESE ASSOCIATES lR
HEMLOCK $OUGLAS lR WESTERN

SPRUCE
lR	WEREUSEDTODElNETHERESPONSEOFLODGEPOLE

PINEWITHINTHISREGION

4HE ASPEN
BIRCH TYPE USED AS A FOREST MANAGEMENT

TYPEINTHE.ORTHEASTREGIONISCONSIDEREDBY+àCHLERTO

BEASERALVEGETATIONREPLACEDBY.ORTHEASTERNSPRUCE
lR

%YRE	CONSIDEREDASPEN
BIRCHTOBEABOREALHARD


WOOD!SPENWILLBEREPLACEDBYTHE0.6TYPESOFNORTH


ERN HARDWOODS OR SPRUCE
lR TYPES AND SUCCESSION TO

THESETYPESISMORERAPIDTHANTOPINE%YRE	4HE

VOLUME OF ASPEN
BIRCH WAS MODIlED BY THE 4%- .00

RESPONSEFROMANAGGREGATIONOF.ORTHEASTERNSPRUCElR

NORTHERN HARDWOODS AND NORTHERN HARDWOODS
SPRUCE

0.6TYPES

)NTHE3OUTHERNREGIONPLANTEDPINEANDNATURALPINE

WERETWOFORESTMANAGEMENTTYPESTABLE	4HEREWERE

NOCORRESPONDING0.6TYPESFORTHESEFORESTTYPES&OR

THELAST20!ANALYSISTHEOAK
HICKORYPINEANDTHESOUTH


ERN MIXED FOREST 0.6 TYPES WERE USED TO ASSESS THE

IMPACT OF CLIMATE CHANGE ON TIMBER VOLUME OF THE TWO

FORESTMANAGEMENTTYPES

#LEARLYTHEREARELIMITATIONSWITHASSIGNINGFORESTMAN


AGEMENTTYPESTOPOTENTIALNATURALVEGETATIONTYPES%CO


LOGICALMODELSREPRESENTTHEMOSTCURRENTUNDERSTANDING

OFHOWECOLOGICALPROCESSESOPERATEATTHEECOSYSTEMSCALE

4HE POTENTIAL DISTRIBUTION OF THESE ECOSYSTEMS IMPLIES

A SIMILARITY OF ECOSYSTEM FUNCTION WITHIN THE RANGE OF

EACH ECOSYSTEM TYPE AS WELL AS A GEOGRAPHIC PRESENCE

UNALTEREDBYLANDUSE&ORESTMANAGEMENTMODELSHAVE

FOCUSEDONTHEYIELDOFWOODFROMFORESTLAND4HEAGGRE


GATIONOFINVENTORYPLOTSINTOAFORESTMANAGEMENTTYPE

IMPLIES A SIMILARITY IN TIMBER PRODUCTION WITH THE GEO


GRAPHICRANGEOFTHATFORESTMANAGEMENTTYPE&ORBOTH

OFTHESECLASSIlCATIONSYSTEMSTHEECOSYSTEMDYNAMICSOR

TIMBERPRODUCTIONWITHINATYPEMAYBEQUITEVARIABLE

#URRENT LAND USES HAVE ALTERED POTENTIAL DISTRIBUTIONS

)NVENTORYDATAISMORELIKELYTOREPRESENTTHECURRENTDIS


TRIBUTIONOFFORESTS

5SE OF VEGETATION TYPES PRESENTS PROBLEMS BY POTEN


TIALLYIGNORINGDIFFERENCESBETWEENSPECIESANDNEWASSOCI


ATIONSANDHOWBOTHMAYAFFECTECOSYSTEMSUNDERCLIMATE

CHANGE 4HE ASSUMPTION THAT SPECIES ASSOCIATIONS WILL

REMAINCONSTANTISACONSEQUENCEOFLUMPINGSPECIES
SPE


CIlCINFORMATIONINTOAhTYPEv+IRSCHBAUMAND&ISCHLIN

	3PECIESASSOCIATIONSHAVEBEENVERYDIFFERENTINTHE

PASTUNDERDIFFERENTCLIMATES$AVIS	REPORTSPALEO


ECOLOGICALEVIDENCEOFCOMMUNITYTYPESNOLONGERPRES


ENT SUCH AS THE SPRUCE
OAK WOODLAND ASSOCIATION 4HE

APPROACH OF USING FUNCTIONAL TYPES (ENDERSON
3ELLERS

AND-C'UFlE7OODWARDETAL	INLIEUOFSPE


CIESINCLIMATECHANGEMODELINGISATTRACTIVEBECAUSETHIS

APPROACH REDUCES THE COMPUTATIONAL COMPLEXITY ASSOCI


ATEDWITHPROJECTINGEACHPLANTSPECIES(OWEVERTHEUSE

OF FUNCTIONAL TYPES OFTEN ASSUMES THAT THESE GROUPINGS

OF SPECIES WILL REMAIN TOGETHER AND RESPOND TO CLIMATE

CHANGE AS A UNIT 4HE USE OF FUNCTIONAL TYPES RAISES THE

ISSUEOFWHETHERhFUNCTIONALTYPESvPRESERVESPECIESDIF


FERENCES3OLBRIG	4HEVALUEOFTHESEFUNCTIONALTYPES

IS THAT THEY GROUP SIMILAR PHYSIOLOGICAL AND ECOLOGICAL

ROLES 3OLBRIG  6INTON AND "URKE 	 BUT SPECIES

BEHAVIORALDIFFERENCESMAYBEOVERLOOKED&OREXAMPLEIS

THERATEOFREACHINGEQUILIBRIUMWITHCLIMATETHESAMEFOR

ALLSPECIESWITHINAFUNCTIONALGROUP

3IMILARLYTHEAGGREGATIONOFDIVERSETREESPECIESINTO

FORESTMANAGEMENTTYPESPRESENTSPROBLEMSBYIGNORING

POTENTIALDIFFERENCESBETWEENCOMMERCIALTIMBERSPECIES

ANDHOWCLIMATECHANGEMIGHTALTERWOODlBERPRODUC


TIONFOREXAMPLEHOWVOLUMESMIGHTSHIFTWHENWOOD

DEVELOPSANDTHEQUALITYOFWOODUNDERALTEREDCLIMATE

%XPERIMENTALRESULTSSUGGESTTHATTHERESPONSESTOCLIMATE

CHANGEMIGHTBEGENERAIFNOTSPECIESSPECIlCSEEEARLIER

DISCUSSION	
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%COSYSTEM0RODUCTIVITYANDTHE)MPACTOF#LIMATE#HANGE *OYCEAND.UNGESSER

7ITHIN THE LAST 20! ANALYSIS THE IMPACT OF CLIMATE

CHANGEON.00WASASSESSEDUSINGTHEHISTORICALRANGEOF

TEMPERATEFORESTSlG	NOTTHECURRENTDISTRIBUTIONAS

AFFECTEDBYLANDUSE4HUSTHEECOLOGICALVARIABILITYANA


LYZEDUNDERCLIMATECHANGEREPRESENTEDAGREATERECOLOGI


CALAMPLITUDETHANFORESTSCURRENTLYREPRESENT4HESPATIAL

DISTRIBUTIONOFEXISTINGFORESTSUSINGTHEFORESTMANAGE


MENT TYPE CLASSIlCATION HAS BEEN RECENTLY MAPPED 7E

USEDTHISSPATIALDISTRIBUTIONTODEVELOPAMAPOFVEGETA


TIONCLASSIlEDBYTHESAMESYSTEMUSEDBYTHE6%-!0

MEMBERS4HEFORESTMANAGEMENTTYPEINFORMATIONWAS

AVAILABLE AT THE  KM SCALE 7E IDENTIlED A +àCHLER

0.6 TYPE FOR EACH GRID CELL ON THE FOREST MANAGEMENT

MAPBASEDON'ARRISONETAL	TABLE	/NCETHE

+àCHLERTYPEWASASSOCIATEDWITHEACHGRIDCELLWETHEN

USEDTHECLASSIlCATIONGIVENIN6%-!0MEMBERS	

TOLINKTHECELLTOA66%'TYPETABLE	4HEMAPWAS

THEN RESAMPLED TO THE  KM SCALE lG 	 4HE lNER

SCALEOFTHISMAPALLOWSSMALLERISOLATEDPATCHESOFFOREST

TOREMAINONTHEMAPPARTICULARLYINTHE3OUTHWESTAND

INTHE'REAT0LAINS(OWEVERTHISDISTRIBUTIONCONTRASTS

WITH THE DISTRIBUTION USED IN THE LAST 20!ANALYSIS lG

	INTHEDRASTICALLYREDUCEDAREAOFFORESTSINTHEEAST


ERN PART OF THE 5NITED 3TATES AND IN THE PATCHINESS OF

THE FORESTS ACROSS THE 5NITED 3TATES 4HE AREA OF FORESTS

IN THE -IDWEST REGION AND THE -ISSISSIPPI 2IVER VALLEY

DECLINESWHENTHELANDUSEINAGRICULTUREISREMOVED4HE

HOMOGENEITYOFVEGETATIONTYPESISLESSENEDINlGURE

PARTICULARLY FOR THE .EW %NGLAND STATES WHERE BOREAL

TEMPERATE CONIFEROUS AND COOL TEMPERATE MIXED FOREST

TYPESINTERMINGLEINCONTRASTTOTHEUNIFORMITYINlGURE

 4HIS RE
EXAMINATION OF FOREST TYPES lG 	 COULD

BEUSEDASTHEBASISFORANANALYSISOFTHEIMPACTOFCLI


MATECHANGEONFORESTPRODUCTIVITY)TWOULDLIKELYREmECT

THE POTENTIAL SHIFTS IN FOREST PRODUCTIVITY MORE CLOSELY

BECAUSECLIMATESHIFTSINREGIONSOFEXISTINGFORESTSWOULD

BEUSEDASCLIMATEINPUTTOAMODELSUCHAS4%-

0ROJECTING%COSYSTEM

0RODUCTIVITYAT$IFFERENT

3PATIAL3CALES

#LIMATETOPOGRAPHYVEGETATIONANDSOILSINPUTDATA

FORECOLOGICALMODELSUSEDINLARGE
SCALEINTEGRATEDASSESS


MENTSARETYPICALLYGRIDDEDATTHEDEGREELONGITUDEBY

DEGREELATITUDESCALE#RAMERETAL(EIMANNET

AL+ICKLIGHTERETAL-ELILLOETAL6%-!0

MEMBERS 	 5SE OF GRIDDED INPUT DATA IMPLICITLY

ASSUMESTHATTHEMEANORDOMINANTSURFACEFEATURESREP


RESENTTHEENTIREGRIDCELL)NHERENTINTHISASSUMPTIONIS

THEUNCERTAINTYWITHWHICHTHISGRIDDEDVALUEREPRESENTS

THE HETEROGENEITY OF THE ACTUAL COARSE GRID CELL FEATURES

AND THE REPRESENTATIVENESS OF THIS GRIDDED VALUE WHEN

USEDINTHEECOLOGICALMODELSTODESCRIBETHEBIOLOGICAL

PROCESSESOPERATINGWITHINTHEGRIDCELL7HILEOPPORTU


NITIESEXISTTOMOVETHEANALYSISOFTHEIMPACTOFCLIMATE

CHANGEONFORESTSTOAlNERGRIDSCALETHISREDUCTIONIN

GRIDSIZEWOULDINCREASETHEPROCESSINGTIMEBYANORDER

OFMAGNITUDE(ENCEITISIMPORTANTTOASSESSTHEUNCER


TAINTYTHATAGGREGATIONOFCLIMATEDATACONTRIBUTESTOTHE

ESTIMATION OF FOREST PRODUCTIVITY UNDER CLIMATE CHANGE

.UNGESSER ET AL 	 USED THE 4ERRESTRIAL %COSYSTEM

-ODEL4%-VERSION-C'UIREETALA	TOEVALUATE

THEUTILITYOFMOVINGTHECLIMATECHANGEIMPACTANALYSIS

FROMTHEDEGREESCALEUSEDINTHELAST20!ANALYSISTO

THEKMSCALE

4HEEFFECTOFAGGREGATIONONTHEESTIMATIONOFPRODUCTIV


ITYHASBEENSTUDIED.ETPRIMARYPRODUCTION.00	ESTI


MATESDIFFEREDBYPERCENTWHENCOARSEGRAINVERSUSlNE

GRAINSOILSDATAWEREUSEDASINPUTDATAFORTHE0N%TMODEL

,ATHROPETAL	0IERCEAND2UNNING	OBTAINED

OVERESTIMATESOFUPTOPERCENTIN.00FROMTHE&/2%34


"'#MODELWHENSUB
GRIDVARIATIONSINCLIMATETOPOGRA


PHYSOILSANDVEGETATIONWEREAVERAGEDACROSSASERIESOF

GRAINSIZESFROMKMTODEGREE-OSTOFTHISERRORWAS

PRODUCEDBYAVERAGETEMPERATUREWHILEAVERAGETOPOGRA


PHYSOILSANDVEGETATIONTYPESALSOCONTRIBUTED

.UNGESSER ET AL 	 EXAMINED THE IMPACT OF TWO

DIFFERENTSPATIALRESOLUTIONSONTHESIMULATEDFORESTECO


SYSTEMRESPONSESFORABASELINECLIMATEANDTWOCLIMATE

CHANGESCENARIOS4HE4%-MODELUSESSPATIALLYRESOLVED

INFORMATIONONCLIMATEMONTHLYPRECIPITATIONMONTHLY

MEANAIRTEMPERATUREANDCLOUDINESS	SOILTEXTUREPER


CENTSANDSILTANDCLAY	VEGETATIONTYPEANDELEVATION

4HElNERESOLUTIONGRIDCELLSWEREKMINSIZEAND

OFTHESECELLSWERENESTEDWITHINACOARSERESOLUTIONGRID

CELLOFAPPROXIMATELYAHALFDEGREEINSIZEKM	4HE

KMsKMRASTERDATAFORCLIMATEMONTHLYPRECIPITA


TIONMONTHLYMEANAIRTEMPERATURE	WEREOBTAINEDFROM

.EILSONPERSONALCOMMUNICATION	ASDESCRIBEDIN$ALY

ETAL	-ARKS	AND.EILSON	&ORTHE

KMsKMINPUTDATATHElNESCALEINPUTDATASETSFOR

CONTINUOUS VARIABLES WERE AVERAGED TO THE  KM s 

KMRESOLUTION!VERAGINGTOTHE
KMSCALERESULTSINTHE

SMOOTHING OUT OF PRECIPITATION AND TEMPERATURE VALUES

ALONGTHEGRADIENTSOFCHANGEANDTHELOSSOFlNERDETAIL

INSOMEAREASlGAND	!REASOFlNESCALEPATCHI


NESS OF PRECIPITATION IN THE WESTERN MOUNTAINS AND THE

SOUTHERN COASTAL PLAINS ARE SMOOTHED OUT AT THE 
KM

GRIDSCALElG	!NNUALAVERAGETEMPERATUREVALUES

AREINmUENCEDINAREASWHERETHEREISSUBSTANTIALTEMPER


ATUREVARIABILITYSUCHASAROUNDTHEMOUNTAINOUSAREASIN

THE7ESTlG	

4HEHISTORICALRANGEOFTEMPERATEFORESTSWASTHESPA


TIAL EXTENT OF THE .UNGESSER STUDY +àCHLER VEGETATION
56 USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000.

Joyce and Nungesser Ecosystem Productivity and the Impact of Climate ChangeFigure 3.1—Forest type distribution used in the last RPA analysis (Joyce et al. 1995).
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 57

Ecosystem Productivity and the Impact of Climate Change Joyce and NungesserFigure 3.2—VEMAP vegetation classification associated with the current distribution of forests based on USDA Forest Service inventory plots. 
58 USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000.

Joyce and Nungesser Ecosystem Productivity and the Impact of Climate Change

Figure 3.3—Baseline annual precipitation at 50 km scale and 10 km scales.
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 59

Ecosystem Productivity and the Impact of Climate Change Joyce and Nungesser

Figure 3.4—Baseline annual average temperature at 50 km and 10 km scales.
 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

*OYCEAND.UNGESSER %COSYSTEM0RODUCTIVITYANDTHE)MPACTOF#LIMATE#HANGE

WASDIGITIZEDFROMTHEMAP+àCHLER	ATKM

RESOLUTION 3TEVE (ODGE PERSONAL COMMUNICATION	 AND

WASRECLASSIlEDTO4%-VEGETATIONTYPES&ORTHEKM

sKMINPUTDATATHElNESCALEINPUTDATASETFORVEG


ETATIONWEREAGGREGATEDTOTHEKMsKMRESOLUTION

THROUGHTHEUSEOFTHEMAJORITYRULEPROPORTIONALAGGRE


GATION METHOD OF #OSTANZA AND -AXWELL 	 7HILE

THE COARSE RESOLUTION GRIDS INCLUDE SIX VEGETATION TYPES

lG	ASEVENTHTYPETEMPERATEEVERGREENBROADLEAF

APPEAREDINONLYTHREEGRIDCELLSATTHElNERESOLUTION!LL

FORESTTYPESTHATCOMPRISEDGREATERTHANPERCENTOFTHE

TOTALAREAWITHINTHE
KMGRIDSRETAINEDATLEASTPER


CENTOFTHEIRTOTALAREAWHENAGGREGATEDTOTHEKMGRID

SIZE4HERARERFORESTTYPESBOREALWETBOREALTEMPERATE

FOREST WETLAND AND TEMPERATE BROADLEAF EVERGREEN LOST

FROM  TO  PERCENT OF THEIR AREA UNDER THE PROPOR


TIONALAGGREGATIONRULE2ARETYPESDISPERSEDACROSSTHE

LANDSCAPEWEREMOSTLIKELYTOBELOSTINTHEAGGREGATION

&OREXAMPLETHEBOREALGRIDCELLSIN.EW%NGLANDDISAP


PEAR AT THE 
KM SCALE lG 	 3IMILARLY SOME OF THE

FORESTEDBOREALWETLANDFORESTSINTHENORTHERN-IDWEST

ARELOSTATTHE
KMSCALE

!NAGGREGATIONERRORWASCOMPUTEDASTHEDIFFERENCE

OFTHE
KMESTIMATEOF.00ANDTHE
KMESTIMATEOF

.00DIVIDEDBYTHE
KMESTIMATEOF.004HISAGGREGA


TIONERRORWASCOMPUTEDFORTHEBASELINERUNSBASELINE

CLIMATEAND#/LEVELSOFMEQL	

E NPP NPP NPP B =∗ − 100 ( 10 50 10 )/

 	

WHERE %" IS THE RELATIVE AGGREGATION ERROR AND

d 100 NPP NPP /NPP GQ50 GQ50 50 50 =∗ − IS

( )

THEAVERAGEOFTHEMEANANNUAL.00ING#MYRESTI


MATESFORTHElNEGRIDCELLSAND.00ISTHEESTIMATE

OFTHE.00ATTHECOARSEGRIDSCALE

4HE.00RESULTSFORTHEKMREmECTlNERSCALEPAT


TERNSTHANTHEKMRESULTSlG	BUTTHESEPATTERNS

ARENOTSUFlCIENTTOGENERATELARGEAGGREGATIONERRORSAT

THENATIONALFORESTTYPEORGRIDCELLSCALE4HE.00ESTI


MATEFORALLFORESTSATTHENATIONALEXTENTDIFFEREDBYLESS

THAN  G#M BETWEEN THE lNE AND COARSE RESOLUTION

SCALESVERSUSG#MTABLE	!GGREGATION

ERRORBASEDONTHESEGRIDCELLSISVERYSMALLANDNEGA


TIVEn	%STIMATESOF.00ATTHE
KMGRIDSCALEDIF


FEREDFROMTHECORRESPONDINGAVERAGEFORTHE
KMGRID

CELLS BY LESS THAN  PERCENT ACROSS MOST OF THE HISTORIC

RANGEOFTEMPERATEFORESTS4HESMALLESTAGGREGATIONERROR

WASFOUNDGENERALLYTHROUGHOUTTHE%ASTAND3OUTHEAST

ASWELLASINTHEWESTERNMOUNTAINS2ARELYWEREAGGRE


GATION ERROR DIFFERENCES GREATER THAN  PERCENT AT THE

INDIVIDUALGRIDCELLLEVEL4HESELARGERAGGREGATIONERRORS

OCCURREDAROUNDTHE'REAT,AKESINNORTHERN.EW%NG


LAND AND IN THE 2OCKY -OUNTAINS "Y FOREST TYPE THE

AGGREGATION ERRORS WERE STILL SMALL LESS THAN  PERCENT

%STIMATESOF.00DIFFEREDBYLESSTHANG#MINMOST

CASES TABLE 	 4HE LARGEST AGGREGATION ERROR OCCURRED

4ABLE.ETPRIMARYPRODUCTION.00	FORBASELINECLIMATE

6ALUESARENETPRIMARYPRODUCTIONING#MREPORTEDVALUESARE

MEANSANDSTANDARDDEVIATIONSAREINPARENTHESESFOLLOWEDBY

RANGES4HEhN	vISTHENUMBEROFCOARSERESOLUTIONGRIDCELLSIN

EACHFORESTTYPE

&OREST4YPEN	 2ESOLUTION .00

"OREAL	 &INE 	 n

 #OARSE 	 n

&ORESTEDBOREAL &INE 	 n

WETLAND	 #OARSE 	 n

-IXEDTEMPERATE	 &INE 	 n

 #OARSE 	 n

#ONIFERS	 &INE 	 n

 #OARSE 	 n

$ECIDUOUS	 &INE 	 n

 #OARSE 	 n

4EMPERATEFORESTED &INE 	 n

 WETLAND	 #OARSE 	 n

!,,&/2%343	 &INE 	 n

 #OARSE 	 n

INBOREALANDFORESTEDBOREALWETLANDFORESTSWITHPOSI


TIVEVALUESOFANDPERCENTRESPECTIVELY%STIMATES

OF .00 FOR BOREAL FOREST AT THE 
KM GRID SCALE WERE

LESSTHANTHE
KMESTIMATEBYAPPROXIMATELYG#M

TABLE	

4HE CLIMATE CHANGE SCENARIOS TEMPERATURE PRECIPI


TATION	 AT THE  KM SCALE WERE BASED ON TWO '#-S

USED IN THE LAST 20! ANALYSIS THE 'EOPHYSICAL &LUID

$YNAMICS ,ABORATORY 1
mUX '&$,
1	 -ANABE AND

7ETHERALD 	 AND /REGON 3TATE 5NIVERSITY /35	

MODELS3CHLESINGERAND:HAO	5SINGTHESAMEPRO


TOCOLASFORBASELINECLIMATElNERESOLUTIONCLIMATEINPUT

DATAWEREAVERAGEDWITHINACOARSEGRIDTOSERVEASCOARSE

RESOLUTION INPUTS TO 4%- 6ALUES FOR FOREST TYPE ELEVA


TIONANDSOILSREMAINUNCHANGEDFROMTHEBASELINESIM


ULATION 4HE CLIMATE CHANGE SCENARIOS INCLUDED A #/

CONCENTRATIONOFPPMV!GGREGATIONERRORIN.00FOR

THE TWO CLIMATE CHANGE SCENARIOS WAS COMPUTED IN THE

SAMEMANNERASTHEBASELINEAGGREGATIONERROR

'RID
LEVELRESPONSEOFNETPRIMARYPRODUCTIVITYTOTHE

CLIMATECHANGESCENARIOSWERECALCULATEDAS

d 100 NPP NPP /NPP , OS10 OS10 10 10 =∗ − ( )

 	

d 100 NPP NPP /NPP , OS50 OS50 50 50 =∗ − ( )

 	

d 100 NPP NPP /NPP , and GQ10 GQ10 10 10 =∗ − ( )

 	

d 100 NPP NPP /NPP GQ50 GQ50 50 50 =∗ − ( )

 	
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 61

Ecosystem Productivity and the Impact of Climate Change Joyce and Nungesser

Figure 3.5—Vegetation types mapped at 50 km and 10 km scales.
62 USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000.

Joyce and Nungesser Ecosystem Productivity and the Impact of Climate Change

Figure 3.6—Baseline net primary productivity (NPP) at 50 km and 10 km scales.
53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

%COSYSTEM0RODUCTIVITYANDTHE)MPACTOF#LIMATE#HANGE *OYCEAND.UNGESSER

WHERE D/3 D/3 D'1 AND D'1 ARE .00RESPONSES

FOREACHlNED?	ANDCOARSED?	RESOLUTIONGRIDTOTHE

/35ANDTHE'&$,
1CLIMATESCENARIOS4HISMETRICISTHE

DELTATHATISPASSEDTOTHEFORESTSECTORMODELANDUSEDTO

MODIFYTIMBERVOLUMEINCREASESINTHEINVENTORYMODEL

.ETPRIMARYPRODUCTIVITYFORALLFORESTSINCREASEDUNDER

BOTHCLIMATECHANGESCENARIOSATBOTHRESOLUTIONS5NDER

THE/35CLIMATE.00OFALLFORESTSINCREASEDAPPROXIMATELY

 PERCENT ABOVE THE BASELINE .00 RESPONSE WHEREAS

UNDER THE '&$,
1 CLIMATE .00 OF ALL FORESTS INCREASED

LESSTHANPERCENTlG	7ITHINEACHCLIMATECHANGE

SCENARIOTHERESPONSETOCLIMATECHANGEATTHECOARSERES


OLUTIONDIFFEREDBYLESSTHANPERCENTFROMTHERESPONSE

ATTHElNERRESOLUTION!GGREGATIONERRORFORALLFORESTSFOR

THE/35CLIMATEnPERCENT	WASSIMILARTOTHEERRORFOR

THE'&$,
1CLIMATEnPERCENT	ANDBOTHRESULTSWERE

SIMILARTOTHEAGGREGATIONERROROFTHEBASELINECLIMATEn

PERCENT	4HESPATIALPATTERNSOFTHESEAGGREGATIONERRORS

WERE SIMILAR BETWEEN THE TWO CLIMATE SCENARIOS AND THE

BASELINEACROSSTHEHISTORICRANGEOFTEMPERATEFORESTS

7ITHINFORESTTYPES.00INCREASEDFROMTOPER


CENTVARYINGBYCLIMATESCENARIO4HE.00RESPONSEFOR

BOREAL FORESTS AND FORESTED BOREAL WETLANDS WAS  TO 

PERCENT GREATER UNDER THE '&$,
1 CLIMATE THAN UNDER

THE/35CLIMATE(OWEVERFORMIXEDTEMPERATEDECID


UOUS AND TEMPERATE FORESTED WETLAND .00 UNDER THE

/35 CLIMATE WAS  TO  PERCENT GREATER THAN UNDER

THE'&$,
1CLIMATE7ITHINEACHCLIMATESCENARIOFOREST

.00RESPONSESATTHECOARSESCALEDIFFEREDBYLESSTHAN

PERCENTFROMTHE.00RESPONSETOCLIMATECHANGEATTHE

lNERRESOLUTIONFORALLFORESTTYPESEXCEPTCONIFERWHICH

DIFFERED BY LESS THAN  PERCENT 4HE ERROR IN ALL THREE

CLIMATE SCENARIOS WAS HIGHEST IN THE BOREAL FORESTS AND

FORESTED BOREAL WETLANDS  AND  PERCENT RESPEC


TIVELY	 4HE ABSOLUTE VALUE OF THE AGGREGATION ERROR FOR

THE OTHER FORESTS WAS LESS THAN  PERCENT 'EOGRAPHI


CALLYAGGREGATIONERRORFORBOTH/35AND'&$,
1ISCON


CENTRATED IN THE SAME AREAS AS THAT OF BASELINE CLIMATE

AROUND THE 'REAT ,AKES IN .EW %NGLAND AND IN THE

2OCKY -OUNTAINS 4HE SMALLEST AGGREGATION ERROR LESS

THAN  PERCENT WAS FOUND IN THE 3OUTH AND THE -ID


!TLANTICANAREATHATHADTHEGREATESTDIFFERENCESINTHE

.00RESPONSETOCLIMATECHANGEnTOPERCENT

2ELATIVETOTHEBASELINETHEPERCENTINCREASESORDECREASES

IN.00ARESIMILARACROSSTHElNEANDCOARSERESOLUTIONS

WITHIN A CLIMATE CHANGE SCENARIO BUT DIFFER SIGNIlCANTLY

ACROSSSCENARIOSlG	0ERCENTINCREASESIN.00WERE

SIMILARUNDERBOTHCLIMATESCENARIOSINTHE7ESTBUTTHE

RESPONSESINTHE3OUTHAND-ID
!TLANTICFORESTSWEREDRA


MATICALLYDIFFERENT&ORTHE'&$,
1CLIMATETHESOUTHERN

ANDMID
!TLANTICFOREST.00DECLINEDUPTOPERCENTREL


ATIVETOTHEBASELINE.00WHEREASUNDERTHE/35CLIMATE

THESEFORESTSINCREASEDIN.00FROMTOPERCENT

4HE 
KM GRID
CELL RESOLUTION IS MOST RELEVANT TO

STAND
LEVEL FOREST MANAGERS !GGREGATION ERROR AT THIS

SCALE IS LESS THAN  PERCENT TWO STANDARD DEVIATIONS	

WHICHISWITHINTHEPERCENTPRECISIONTHATSTAND
LEVEL

.00ISMEASURED/URANALYSESINDICATETHATAGGREGATION

ERROR IS THE LARGEST IN TRANSITION REGIONS AND IN REGIONS

WITHSUBSTANTIALVARIABILITYINAIRTEMPERATURE!GGREGA


TIONERRORISPRIMARILYASSOCIATEDWITHTHEREPRESENTATION

OF A MOSAIC OF FOREST TYPES WITH A SINGLE FOREST TYPE AT


KM RESOLUTION 4HIS SOURCE OF AGGREGATION ERROR CAN

EASILYBEMINIMIZEDBYMAKING.00ESTIMATESFOREACH

FORESTTYPEWITHINA
KMGRIDCELLANDAGGREGATINGESTI


MATESBASEDONTHEPROPORTIONOFEACHFORESTTYPEWITHIN

THEGRIDCELL4HISAPPROACHHASBEENUSEDBY"ONAN	

ASAMEANSOFREPRESENTINGVEGETATIVEHETEROGENEITYFOR

ESTIMATINGCARBONWATERANDENERGYEXCHANGEINTHESUR


FACEBOUNDARYLAYEROFGENERALCIRCULATIONMODELS0IERCE

AND2UNNING	ALSOFOUNDTHATAVERAGINGTEMPERA


TURESUBSTANTIALLYINmUENCEDAGGREGATIONERRORINREGIONS

OFCOMPLEXTERRAIN)TMAYBEPOSSIBLETOACHIEVECOMPUTA


TIONALEFlCIENCYAT
KMRESOLUTIONBYAGGREGATINGTEM


PERATUREFORALIMITEDNUMBEROFELEVATIONBANDSMAKING

.00ESTIMATESFOREACHELEVATIONBANDANDAGGREGATING

ESTIMATESBASEDONTHEPROPORTIONOFEACHELEVATIONBAND

WITHINTHEGRIDCELL.UNGESSERETAL	

4HERESOLUTIONOFFORESTTYPESISMOSTRELEVANTTOCOUN


TRY
SPECIlC ECONOMIC ASSESSMENTS OF THE IMPACTS OF CLI


MATE CHANGE ON TIMBER RESOURCES &OR EXAMPLE RELATIVE

CLIMATICRESPONSESOF.00FORDIFFERENTFORESTTYPESINDIF


FERENTREGIONSWEREUSEDASINPUTSFORTHELAST20!*OYCE

ETAL	%XCEPTFORBOREALFORESTSANDFORESTEDBOREAL

WETLANDSTHEMEANAGGREGATIONERROROFBASELINE.00ESTI


MATESISLESSTHANPERCENTFOREACHFORESTTYPE)NCONTRAST

AGGREGATION ERROR FOR BOREAL FORESTS AND FORESTED BOREAL

WETLANDSISAPPROXIMATELYPERCENT4HISLEVELOFERRORIS

CAUSEDPRIMARILYBYTHEOVER
REPRESENTATIONOFBOREALAND

BOREALWETLANDFORESTSANDUNDER
REPRESENTATIONOFMORE

HIGHLYPRODUCTIVEFORESTSINTHE
KMSIMULATION

)NCOMPARISONTOTHEBASELINESIMULATIONSMEANAGGRE


GATIONERRORFORTHEABSOLUTEESTIMATESOFEACHFORESTTYPE

INTHECLIMATECHANGESIMULATIONSISSIMILAREXCEPTFORTEM


PERATECONIFERFORESTnPERCENTFOR/35ANDnPER


CENTFOR'&$,VSnPERCENTFORBASELINECLIMATE	3IMILAR

TOAGGREGATIONERRORTHERELATIVERESPONSESOF.00ATEACH

RESOLUTIONARESIMILAREXCEPTFORCONIFERFORESTSAND

PERCENT LOWER RESPONSE FOR THE lNE RESOLUTION /35 AND

'&$,SIMULATIONS	4HENEGATIVEAGGREGATIONERRORSAND

LOWER RESPONSES FOR TEMPERATE CONIFER FORESTS ARE ASSOCI


ATED WITH THE AVERAGING OF TEMPERATURE IN THE COMPLEX

TERRAININTHENORTHERN2OCKY-OUNTAINSANDINWESTERN

7ASHINGTON/REGONAND#ALIFORNIA"ECAUSEDIFFERENCES

BETWEENTHERESPONSESOF.00ATDIFFERENTRESOLUTIONSARE

SMALLCOMPAREDWITHTHERESPONSESTODIFFERENTCLIMATESCE


NARIOSTHEYCOULDBEIGNOREDINIMPACTASSESSMENTSTHAT

EVALUATESENSITIVITIESTODIFFERENTCLIMATECHANGESCENARIOS

4HENATIONALRESOLUTIONISMOSTRELEVANTTOGLOBALECO


NOMICASSESSMENTSOFTHEIMPACTSOFCLIMATECHANGEON
64 USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000.

Joyce and Nungesser Ecosystem Productivity and the Impact of Climate Change

Figure 3.7—Net primary productivity at 50 km and 10 km scales from the GFDL-Q climate scenario.
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 65

Ecosystem Productivity and the Impact of Climate Change Joyce and NungesserFigure 3.8—Forest responses to two climate change scenarios (OSU, GFDL-Q) at 10 km (fine grid) and 50 km (coarse grid) scales.
 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

*OYCEAND.UNGESSER %COSYSTEM0RODUCTIVITYANDTHE)MPACTOF#LIMATE#HANGE

TIMBERRESOURCES4HERELATIVECLIMATICRESPONSESOF.00

OFHARDWOODSANDSOFTWOODSFORDIFFERENTREGIONSWERE

USED AS INPUTS FOR A NATIONAL ASSESSMENT 0EREZ
'ARCIA

ET AL 	 &OR THE CONTERMINOUS 5NITED 3TATES AGGRE


GATION ERROR WAS  PERCENT IN THE BASELINE SIMULATION

PERCENTINTHE/35SIMULATIONANDPERCENTINTHE

'&$,SIMULATION2ESPONSESOF.00ACROSSTHETWOSPA


TIALSCALESWEREANDPERCENTLOWERFORTHE/35AND

'&$,SIMULATIONS"ECAUSETHESEDIFFERENCESAREMINUS


CULEINCOMPARISONTOTHENATIONAL.00RESPONSESTHEY

CANBEIGNOREDINIMPACTASSESSMENTSTHATEVALUATESENSI


TIVITIESTODIFFERENTCLIMATECHANGESCENARIOS

4HESE RESULTS INDICATE THAT .00 RESPONSES OF 4%-

TO PROJECTED CLIMATE CHANGE ARE INSENSITIVE TO THE RESO


LUTION OF INPUTS BUT THAT AGGREGATION ERROR OF ABSOLUTE

.00ESTIMATESISSENSITIVETOTHERESOLUTIONOFINPUTSFOR

SOMESITUATIONS%XCEPTFORTRANSITIONAREASANDREGIONS

WITH SUBSTANTIAL TEMPERATURE VARIABILITY THESE SIMULA


TIONSINDICATETHATTHEUSEOFORESOLUTIONPROVIDESAN

ACCEPTABLELEVELOFAGGREGATIONERRORATTHETHREESCALESOF

ANALYSISINTHISSTUDY

)TISIMPORTANTTORECOGNIZETHATTHECONCLUSIONSINTHIS

STUDYAREBASEDONTWORESOLUTIONSANDONEBIOGEOCHEM


ISTRYMODEL0IERCEAND2UNNING	USEDADIFFERENT

BIOGEOCHEMISTRYMODELTOSIMULATE.00FORVARIOUSRES


OLUTIONS RANGING FROM  KM TO  KMIN A REGION OF

COMPLEX TOPOGRAPHY !T THE COARSEST SCALE THEY FOUND

COARSE
RESOLUTION .00 WAS OVERESTIMATED BY UP TO 

PERCENTRELATIVETO.00ESTIMATESATTHElNESTRESOLUTION

4HERESULTSOF.UNGESSERETAL	QUALITATIVELYAGREE

WITHTHOSEOF0IERCEAND2UNNING	

"ECAUSEMOSTLARGE
SCALEBIOGEOCHEMISTRYMODELSARE

PARAMETERIZED WITH STAND
LEVEL DATA A SYSTEMATIC ANAL


YSIS OF AGGREGATION ERROR WITH SEVERAL BIOGEOCHEMISTRY

MODELSACROSSARANGEOFSPATIALRESOLUTIONSFROMSTAND

TO   EG  M TO  KM TO  KM TO  KM	

SHOULDBEUNDERTAKENINDIFFERENTFORESTREGIONSTODETER


MINE WHETHER OUR CONCLUSIONS AND THOSE OF 0IERCE AND

2UNNING	AREROBUST

&INALLYITISIMPORTANTTOVERIFYTHECONCLUSIONABOUT

THE INSENSITIVITY OF .00 RESPONSES TO THE RESOLUTION OF

INPUTSWITHOTHERBIOGEOCHEMISTRYMODELS"YCLARIFYING

THE SCALING ISSUES ASSOCIATED WITH .00 ESTIMATES AND

RESPONSESTHESESUGGESTEDSTUDIESWOULDIMPROVEIMPACT

ASSESSMENTSTHATRELYONTHEESTIMATESOFLARGE
SCALEECO


LOGICALMODELS

#ONCLUSIONS

!NALYSES OF THE IMPACT OF CLIMATE CHANGE ON FOREST

PRODUCTIVITYBASEDONEXPERIMENTALRESEARCHANDMODEL


INGWOULDSUGGESTTHATFORESTPRODUCTIVITYMAYINCREASE

UNDER ELEVATED CARBON DIOXIDE BUT THAT THE LOCAL CON


DITIONS OF MOISTURE STRESS AND NUTRIENT AVAILABILITY WILL

STRONGLYTEMPERANYRESPONSE0ROJECTEDINCREASESINPRO


DUCTIVITYFROMCARBONDIOXIDEFERTILIZATIONAPPEARTOBE

WITHINTHESAMEMAGNITUDEASPOTENTIALINCREASESINPRO


DUCTIVITY FROM TIMBER MANAGEMENT TREATMENTS 2ElNE


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!CKNOWLEDGMENTS

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TRIBUTIONS TO THE AGGREGATION RESEARCH DESCRIBED IN THIS

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INVESTMENTS CASE ARE CLOSER TO THOSE PROJECTED BY THE

4!-- MODEL FOR COMPARABLE SCENARIOS 5SE OF BOTH

THE 4!-- AND &!3/- MODELS REVEALS THE DIFFERENCES

BETWEEN 	 LIKELY FUTURE PATHS FOR THE FOREST SECTOR IF

HISTORICAL RELATIONSHIPS BETWEEN KEY VARIABLES CONTINUE

VERSUS	PRODUCTIONPOSSIBILITIESANDOPTIMALRESPONSES

TO EXTERNAL EVENTS EG CLIMATE CHANGE	 AND POLICIES

&!3/- ASSUMES PERFECT FORESIGHT AND OPTIMAL ADJUST


'LOBALCHANGEMITIGATIONANALYSESUSINGTHE&!3/-MODEL

AREDISCUSSEDINCHAPTEROFTHISREPORT
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 75

Modeling Climate Change Impacts on the Forest Sector Mills, Alig, Haynes, and Adams

ments in the unfettered case. As such it shows a greater 

shift to pine plantations, and as timber prices fall, an 

increase in land moving from forest to agriculture and a 

decrease of investment in pine plantations. 

With FASOM having all four key timber supply modeling elements as endogenous components, a different 

set of projected adjustments (both temporally and across 

regions) are possible than with TAMM. A range of adjustments is discussed in Chapter 8, where analyses of global 

change mitigation strategies using the FASOM model are 

reviewed.

Model Uncertainties

These two forest sector models are useful in developing a portfolio of possible impacts of human uses (in 

a commodity sense) on forests under climate change. 

Such factors are not normally considered with most climate change simulation models. They show how and the 

extent that climate-change influences on U.S. timberlands 

will be mitigated by market feedbacks between the natural resource base and the production and consumption 

of forest products. This helps place the issue in context. 

As shown in figure 4.2, the prospective impacts on the 

U.S. forest sector of one view of global climate change is 

overshadowed in the near term by other contemporary 

policy concerns such as habitat conservation strategies 

that involve reductions of timber harvest on federal timberlands in the west (e.g. Adams et al. 1996b). This raises 

questions about the timing of the often cited prospective 

catastrophic ecological declines associated with climate 

change and the accompanying specter of economic dislocation within the U.S. forest sector. This scenario needs to 

be examined in light of the extent and speed of changes 

induced by price signals from timber markets. That is, to 

what extent will the expectations of lower prices in the 

future associated with climate-change reduce land management actions taken in the next decade?

Figure 4.2—Softwood lumber price index under different views of the future including one prospective view of climate change. (The 

CEA projection represents the results from an alternative macro economic forecast developed by the Council of Economic Advisers in 

1994.) Source: Haynes et al. 1995. 1982 = 100
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)NTRODUCTION

#OMPREHENSIVELARGE
SCALECARBONACCOUNTINGSYSTEMS

ARENEEDEDASNATIONSAGREETOWORKTOWARDREDUCINGTHEIR

GREENHOUSE GAS '('	 EMISSIONS (OWEVER ADOPTING A

STANDARD ACCOUNTING SYSTEM IS DIFlCULT BECAUSE MULTIPLE

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CLEARLYINANACCOUNTINGSYSTEMTHATISEASYTOUSE

/RGANIC CARBON IN SOIL BELOW THE FOREST mOOR IS ONE

COMPONENT OF FOREST CARBON THAT IS PARTICULARLY CONTEN


TIOUS -EASURING SOIL CARBON IS TIME
CONSUMING COSTLY

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! COMPARISON OF TWO CARBON ACCOUNTING METHODS

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APPARENT LOSS OF FOREST SOIL CARBON TO THE ATMOSPHERE IS

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TORY ESTIMATES AREAS ARE BASED ON HISTORICAL ESTIMATES

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!SSUMPTIONS ABOUT THE DYNAMICS OF SOIL CARBON OVER

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!FTER THREE YEARS TOTAL MINERAL SOIL CARBON INCREASED 

PERCENTCOMPAREDTOPRE
HARVESTVALUESWHICHWASNOT

STATISTICALLYSIGNIlCANTATP	!FTEREIGHTYEARSTOTAL

MINERALSOILCARBONDECREASEDPERCENTRELATIVETOPRE


HARVEST VALUES SIGNIlCANT AT P 4HE CARBON POOL

IN THE n CM LAYER DID NOT DIFFER P	 FROM PRE


HARVEST VALUES BUT THE CARBON POOLS IN THE n AND


#HORIZONLAYERSDECREASEDSIGNIlCANTLYP	0ER


CENT CARBON OF THE ORGANIC MATTER CHANGED SIGNIlCANTLY

P	 AFTER EIGHT YEARS IN SEVERAL OF THE LOWER LAYERS

*OHNSON ET AL 	 AND SIGNIlCANT P	 INCREASES

INBULKDENSITYWERENOTEDINTHETOPCMAFTERTHREE

YEARS*OHNSONETAL	3URPRISINGLYTHEMINERALSOIL

ORGANICMATTERPOOLREMAINEDBASICALLYUNCHANGEDEIGHT

YEARSAFTERCUTTING-G#PERHAVERSUS-G#PER

HA	4HUSMEASURINGONLYSOILORGANICMATTERANDASSUM

 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

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&IGURE4RENDOFSOILORGANICCARBONAFTERPRE
HARVESTLOW

INTENSITY BURNS AND CLEARCUT HARVEST OF A 
YEAR
OLD LOBLOLLY

PINESTANDONERODEDSOILFOLLOWING6AN,EARETAL	

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THETRUECARBONDYNAMICS

4HECONTRASTBETWEENTHE(UBBARD"ROOKRESULTSAND

PREVIOUSSTUDIESTHATSHOWEDNOSIGNIlCANTEFFECTSOFHAR


VESTINGONSOILCARBONWASDISCUSSEDBY*OHNSON	

/NE REASON PROPOSED FOR THE CONTRAST WAS THAT STUDIES

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TURBED SITES IN HIS STUDY WHILE &EDERER 	 ALLOWED

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EXTENSIVE NETWORK OF LOGGING ROADS -IXTURE OF THE TOP

LAYERS MADE DELINEATION OF THE FOREST mOOR AND MINERAL

SOILMUCHMOREDIFlCULTANDMAYHAVECONTRIBUTEDTOTHE

nCMLAYERINCREASINGINSOILCARBONEIGHTYEARSAFTER

HARVEST(UNTINGTONAND2YAN	4HEAPPARENTEFFECT

OFHARVESTINGONSOILCARBONINMINERALSOILMAYBEMORE

DIRECTLYAFUNCTIONOFSOILDISTURBANCEATTHETIMEOFHAR


VEST !NOTHER POSSIBLE REASON IS THAT THE USE OF CHRO


NOSEQUENCESINSOMESTUDIESMAYINADVERTENTLYINCLUDE

UNKNOWNSITE
SPECIlCEFFECTS

3OIL CARBON DYNAMICS QUALITATIVELY SIMILAR TO THOSE

FOUND AT (UBBARD "ROOK HAVE ALSO BEEN IDENTIlED IN

OTHER FOREST TYPES AS WELL 6AN ,EAR ET AL 	 COM


BINEDSAMPLINGATMOSTLYTHEnCMSOILDEPTHn

SAMPLESATTHREETOlVEPERMANENTSAMPLINGLOCATIONSAT

SEVERALWATERSHEDSATTHREEDEPTHS	WITHMODELEDINFOR


MATIONATMOSTLYTHEnCMDEPTH4HEYSTUDIEDSOIL

CARBON DYNAMICS AFTER HARVEST OF A 
YEAR
OLD LOBLOLLY

PINE FOREST ON AN ERODED PREVIOUSLY CULTIVATED SITE IN

THE 0IEDMONT OF THE SOUTHEASTERN 5NITED 3TATES 4HEY

FOUNDANINCREASINGSOILCARBONTRENDAFTERHARVESTWHICH

QUICKLY DECREASED BELOW PRE
HARVEST CARBON BUT BY 

YEARSAFTERHARVESTITHADINCREASEDABOVEPRE
HARVESTSOIL

CARBONLEVELS4HISISILLUSTRATEDINlGUREWHICHSOME


WHATRESEMBLESTHEOLDERACCEPTEDTHEORYOFSOILCARBON

DYNAMICS SHOWN IN lGURE  (OWEVER SOME OF THEIR

INFORMATIONINTHEnCMHORIZONWASESTIMATEDNOT

MEASURED

0ENNOCKANDVAN+ESSEL	CONDUCTEDASTUDYON

CHRONOSEQUENCESTOEXAMINETHEEFFECTSOFCLEARCUTTINGIN

SIX ASPEN
WHITE SPRUCE STANDS IN CENTRAL 3ASKATCHEWAN

#ANADA4HEYSAMPLEDFROMTOCM2ESULTSSHOWED

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LESS THAN lVE YEARS AFTER THE CLEARCUT WITH A SIGNIlCANT

DECREASEOFPERCENTnYEARSAFTERCLEARCUTTINGASCOM


PARED TO MATURE FORESTS (OWEVER ONE CAUTION IN INTER


PRETINGTHERESULTSISTHATTHEYDIDNOTSEPARATETHEFOREST

mOOR FROM THE MINERAL SOIL SURFACE ON CLEARCUT SITES THAT

HADBEENPREPAREDFORTREEPLANTING4HESURFACELAYERWAS

MISSING OR VERY THIN ON THESE SITES AND IT WAS FELT THAT

MEASURING THE FOREST mOOR SEPARATELY WOULD HAVE INTRO


DUCEDMOREERRORTHANMEASURINGITWITHTHEMINERALSOIL

3AMPLINGFROMACHRONOSEQUENCESUGGESTSANINCREASE

INSOILCARBONWITHREFORESTATIONEVENWHERETHETRANSI


TORY INCREASE IMMEDIATELY AFTER HARVEST DID NOT APPEAR

5SINGACHRONOSEQUENCE%NTRYAND%MMINGHAM	

FOUND AN INCREASE IN SOIL CARBON IN THE TOP  CM OF

$OUGLASlRSTANDSOFINCREASINGAGE4HESTANDSWERECAT


EGORIZEDASYOUNG
GROWTHABOUTYEARSOLD	SECOND


GROWTH ABOUT  YEARS OLD	 AND OLD
GROWTH FROM 

TO  YEARS OLD	 3OIL CARBON ALMOST DOUBLED BETWEEN

YOUNG
GROWTH AND SECOND
GROWTH BUT THE INCREASE WAS

NOT SIGNIlCANT AT P 3OIL CARBON OF THE OLD GROWTH

WASALMOSTTHREETIMESTHATOFYOUNG
GROWTHANDITWAS

SIGNIlCANTLYGREATERP	THANBOTHYOUNGERGROUPS

3TRONG	STUDIEDlVECUTTINGTREATMENTSWITHTHREE

REPLICATIONSEACHINNORTHERNHARDWOODSINNORTHEASTERN

7ISCONSINUSINGACHRONOSEQUENCEPRE
TREATMENTVALUES

WERE NOT KNOWN FOR EACH TREATMENT	 4HE FORESTS WERE

LOGGEDINTHEEARLYSANDWEREGENERALLYEVEN
AGED

4HESTUDYWASINITIATEDINANDHASBEENCONTINUING

FORYEARS4HETREATMENTSINCLUDEDREPLICATIONSOFCON


TROLDIAMETER
LIMITCUTANDTHREELEVELSOFINDIVIDUALTREE

SELECTION.OTREESWERECUTINTHECONTROLALLTREES

CMANDLARGERWERECUTININTHEDIAMETER
LIMITCUT

AND HEAVY MEDIUM AND LIGHT INDIVIDUAL TREE SELECTION

WASPERFORMEDINAND4HEREWAS

NO STATISTICAL DIFFERENCE P	 IN SOIL CARBON IN THE

nCMHORIZONBUTTHEREWASASIGNIlCANTDIFFERENCEIN

THEnCMDEPTHANDTHEREWASATRENDOFINCREASING

SOILCARBONASBASALAREAINCREASED4HISIMPLIESTHATSOIL

CARBON MAY DECREASE WITH INCREASING HARVEST INTENSITY

5NFORTUNATELYBECAUSETHISSTUDYUSESACHRONOSEQUENCE

ITMAYBETHATTHESOILCARBONDIFFERENCESBETWEENTREAT


MENTSAREDUETOINITIALSITEDIFFERENCESNOTTOHARVESTING

INTENSITY
53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n 

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/THER STUDIES WERE REVIEWED BUT MAY BE OF LIMITED

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BYYEARSAFTERCLEARCUTTINGUNDERREGENERATIONRELATIVE

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STANT IN THEIR CALCULATION OF TOTAL SOIL CARBON 4HE THREE

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RESIDUES LEFT ON SITE	 HARVESTING ALL ABOVEGROUND TREE

PARTSEXCEPTNEEDLESANDWHOLETREEHARVESTINGNORESI


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BULKDENSITYSOILCARBONINCREASEDFAIRLYCONSISTENTLYIN

THEnCMLAYERBYABOUT-G#PERHANOTSTATISTI


CALLY SIGNIlCANT AT P	 ON EACH SITE 4HERE WERE NO

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/PERATORSTRIEDTOAVOIDSOILCOMPACTIONANDMIXINGOF

SOILLAYERS"LACKAND(ARDEN	STUDIEDTHEEFFECTOF

CLEARCUTTINGINAMIXEDCONIFERSTANDIN#ALIFORNIA4HEY

SAMPLEDSOILINTHEnCMLAYERINSTANDSOFSIXDIFFER


ENTAGESBUTFOUNDNOSTRONGLYCONSISTENTTREND4HEYDID

NOTETHEYOUNGERSTANDSnYEARSOLD	INGENERALCON


TAINEDMORESOILCARBONTHANTHEOLD
GROWTHSTAND4HEY

CONCLUDEDTHATOTHERFACTORSBESIDESHARVESTINGCONFOUND

RESULTS7EALSOREVIEWEDOTHERSTUDIESBUTWEDECIDED

NOTTOINCLUDETHEMBECAUSETHEYINCLUDEDONLYPERCENT

CARBON OR WERE LIMITED IN DURATION OR IN DEPTH FOR

INSTANCE+NOEPPAND3WANK	

!FFORESTATIONAND$EFORESTATION

7E REVIEW AFFORESTATION AND DEFORESTATION STUDIES

TOGETHER BECAUSE SOILS IN 53 FORESTS ARE GENERALLY

ACCEPTEDTOLOSESOILCARBONWHENCLEAREDANDCULTIVATED

ANDTHENACCUMULATESOILCARBONAFTERTHELANDISREVEG


ETATED WITH FOREST &OREST SOIL EVENTUALLY ACCUMULATES

CARBON TO A MAXIMUM LEVEL REGARDLESS OF PREVIOUS

LAND USE UNLESS SEVERE EROSION HAS OCCURRED 3IMILARLY

EXPECTEDDECREASESINSOILCARBONPARTLYDEPENDONUSE

AFTER DEFORESTATION SUCH AS ANNUAL CROPS PASTURE LAND

ORURBANDEVELOPMENT&OREXAMPLEASMENTIONEDPRE


VIOUSLY $AVIDSON AND !CKERMAN 	 CONCLUDE SOIL

CARBONDECREASESREGIONALLYBYPERCENTRANGINGFROM

TOPERCENT	INTHEENTIRESOILCOLUMNWHENFORESTSARE

CLEAREDANDTHELANDCULTIVATED

4HEPERCENTLOSSISGENERALLYACCEPTEDASTHEMAG


NITUDEOFSOILCARBONCHANGEFORDEFORESTATIONANDCULTI


VATIONHOWEVERTHELENGTHOFTIMEOVERWHICHTHELOSS

TAKESPLACEISSTILLBEINGDEBATED(OWLONGDOESITTAKETO

REACCUMULATESOILCARBONTOITShMAXIMUMvLEVEL(UN


TINGTON 	 STUDIED A CHRONOSEQUENCE OF SITES IN THE

0IEDMONT OF THE SOUTHEASTERN 5NITED 3TATES MEASURING

SOILCARBONTOTHEDEPTHOFMFORSOMESITES!NUPPER

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WAS ESTIMATED USING CURRENT SOIL CARBON IN THE n

CMLAYERANDTHELOWERBOUNDWASESTIMATEDUSINGSOIL

CARBON IN SIMILAR SOILS CURRENTLY UNDER CULTIVATION IN

THEAREA5SINGTHESEUPPERANDLOWERBOUNDS(UNTING


TON 	 ESTIMATES A RANGE WITHIN WHICH SOIL CARBON

ACCUMULATESAFTERFORESTREGENERATIONONTHESELANDS(IS

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OFTO-G#PERHAPERYEARnPERCENT	ACCU


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,EARETAL	WORKINGONTHE0IEDMONTIN3OUTH#AR


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PERCENT	OVERAPERIODOFYEARS4HISPERCENTAGEIS

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SITE3CHIFFMANAND*OHNSON	ESTIMATEDABOUT

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4RENDSOF3OIL#ARBONIN#URRENT,ITERATURE

"ASEDONTHISPRELIMINARYREVIEWSOILCARBONDYNAM


ICS FOLLOWING HARVEST APPEAR TO DEPEND ON THE AMOUNT

OF DISTURBANCE CAUSED BY LOGGING OPERATIONS 4HE DIS


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CAUSESOILCARBONTOINCREASEINITIALLYINTHElRSTFEWYEARS
 53$!&OREST3ERVICE'EN4ECH2EP2-23n'42n

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1UANTITATIVEESTIMATESOFCARBONINVENTORIESARENEEDED

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POOLSIZESFORHARDWOODTREESSOFTWOODTREESUNDERSTORY

#(!04%2
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 103

Considerations for Interpreting Probabilistic Estimates of Uncertainty of Forest Carbon Smith and Heath

forest floor, and soil based principally on age and volume 

inputs. An example of such a relationship is shown as the 

solid line in figure 7.1. Here, forest floor carbon inventory is 

estimated from stand age. Subsequent reference to a “FORCARB parameter” refers to this type of functional relationship. Carbon pools are then expanded to total carbon for 

large areas of similar forest-type and productivity within a 

region. These large areas are termed “forest management 

units” (103 to 107 ha with a median of 180,000 ha for the 

1990 inventory). Regional subtotals are formed and, finally, 

summed to a national total. Private timberlands in the 

48 contiguous states are represented by results presented 

here, which include 216 forest management units. Carbon 

budget projections are presented in greater detail in Heath 

and Smith (2000). The basic sequence of a FORCARB simulation is illustrated in figure 7.2.

Uncertainty

Some level of uncertainty is usually a part of any 

model, assessment, or decisionmaking whether or not it 

is an explicitly considered part of the process. A widely 

used and potentially general term such as “uncertainty” 

can be confusing or misleading unless it is adequately 

defined (Hattis and Burmaster 1994; Shackley and Wynne 

1996). At its simplest level, uncertainty can be the state of 

not knowing, or the inability to quantify something with 

a single discrete value. Sources of uncertainty can vary 

widely, and as a consequence, attempts to narrow the definition can require reference to variability, ignorance, systematic error, unknowns, expert opinion, semantics, or 

misapplication of a model (Morgan and Henrion 1990; 

Hattis and Burmaster 1994; Rowe 1994; Ferson and Ginzburg 1996; Cullen and Frey 1999). In earlier literature 

(largely stemming from Knight 1921), scientists were careful to define the risk of an event by a probability based 

on documented frequencies of occurrence. Risk was contrasted with uncertainty where such probabilities could 

not be assigned. However, current applications employ a 

range of definitions for uncertainty, including probability; 

furthermore, valid definitions of probabilities can include 

observed frequency or even subjective expectation (Hoffman and Hammonds 1994; Reckhow 1994; Dakins et al. 

1996; Schimmelpfennig 1996; Paoli and Bass 1997; Haynes 

and Cleaves 1999). We use a probabilistic definition of 

uncertainty.

An unknown, but unique, inventory of carbon exists 

within a given forest management unit for a particular 

year. Our inability to precisely specify that value is the 

general definition of uncertainty we employ here. This 

concept of uncertainty implies that we can specify a range 

Figure 7.1—An example of a typical functional relationship (or 

FORCARB model parameter) used to project forest floor carbon 

inventory based on stand age (solid line). Probability bands 

illustrate our meaning and use of uncertainty in “FORCARB 

parameters” for this analysis. The bands indicate the 5th, 25th, 

50th (expected value), 75th, and 95th percentiles (bottom to top 

respectively) of the probability distribution around the dependent 

variable. (Relationship is from a Douglas fir forest management 

unit.)

of possible values and an associated likelihood for values 

within that range. This describes a probability distribution, or more properly, a probability density function 

(PDF). Thus, we use PDFs as convenient quantitative 

and graphical representations of uncertainty (Vose 1996; 

Cullen and Frey 1999). 

The effect of this definition of uncertainty, applied to 

estimating carbon for a given subset of a forest management unit, is illustrated in figure 7.1. The broken lines 

are probability bands indicating specific points on dependent variable PDFs–or uncertainties–about exact values 

of carbon per unit area. These probabilities reflect uncertainty in predicting carbon from stand age. Normally 

distributed PDFs were assumed to describe uncertainty 

about FORCARB parameters (details in Heath and Smith, 

2000). No assumption of normality was required for this 

model: its use was simply a convenience for describing 

assumed expected values with symmetrical distributions. 

Analyses would ideally address all sources of uncertainty 

relevant to policymakers’ questions about forest carbon 

inventory and flux. However, as mentioned above, a pragmatic first step is to focus on uncertainty internal to FORCARB. Therefore, uncertainties presented here are limited 

to this portion of the potentially much larger system of 

models that describe forests.
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112 USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000.

Mitigation Activities in the Forest Sector to Reduce Emissions and 

Enhance Sinks of Greenhouse Gases

Richard Birdsey, USDA Forest Service, Northeastern Research Station

Ralph Alig, USDA Forest Service, Pacific Northwest Research Station

Darius Adams, Oregon State University

International Negotiations to 

Stabilize Greenhouse Gases

In June 1992, representatives from 172 countries gathered at the “Earth Summit” in Rio de Janeiro to discuss 

environmental issues. The United Nations Framework 

Convention on Climate Change (FCCC) was adopted to 

achieve “. . . stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent 

dangerous anthropogenic interference with the climate 

system. Such a level should be achieved within a time 

frame sufficient to allow ecosystems to adapt naturally 

to climate change, to ensure that food production is not 

threatened, and to enable economic development to proceed in a sustainable manner.” The nonbinding goal of 

the Convention was “to return emissions of greenhouse 

gases to their 1990 levels by the end of the decade.” 

The United States responded to the FCCC in 1993 with 

the “Climate Change Action Plan,” a collection of about 

40 individual programs covering emissions reductions, 

energy efficiency, and productivity enhancements including forestry activities.

At the first Conference of the Parties to the FCCC in 

1995, it was concluded that voluntary commitments were 

inadequate and would not be met by most developed 

countries. Negotiators then agreed to the need for specific 

limits on greenhouse gas emissions beyond the year 2000. 

The U.S. position on mitigation of greenhouse gas concentrations was clearly stated at the second Conference of 

the Parties in 1996. Three elements were seen as necessary 

for ratification of a treaty: 1) realistic and binding targets; 

2) flexibility in implementation; and 3) the participation 

of developing countries. 

The third Conference of the Parties, held in Kyoto, 

Japan, in December 1997, produced an agreement known 

as the “Kyoto Protocol” that contained the first two elements: 1) binding targets, and 2) flexible implementation. 

The U.S. President promised to negotiate an amendment 

to the agreement covering the participation of developing 

countries prior to submitting the agreement to the Senate 

for ratification. Under the terms of the agreement, the 

United States is bound to reduce emissions of greenhouse 

gases 7 percent below 1990 levels by 2008-2012. This is a 

substantial reduction given that emissions are expected 

to rise substantially during this period due to population 

growth and economic expansion. Various countries and 

groups of countries have different reduction targets (and 

increases in some cases). 

The role of forestry and land use change has been controversial throughout the international negotiation process. There are different opinions around the globe on 

whether forestry activities should be counted or not. A 

country’s position depends on factors such as whether 

their forests are currently or prospectively a net source or 

sink for carbon dioxide (CO2), whether carbon (C) stock 

changes in forests can be measured and verified, and 

the relative emphasis that should be placed on reducing 

emissions versus increasing sequestration. Some countries expressed concern that forest responses to “natural” 

factors such as increased atmospheric CO2 (which may 

increase growth) would allow a country to claim credit 

for greenhouse gas reductions that are not associated with 

specific activities.

The Kyoto Protocol attempted to reconcile the diversity 

of viewpoints on land use change and forestry. According 

to article 3.3 of the Protocol, land-use change and forestry 

activities that can be counted toward the emissions reduction target include afforestation, reforestation, and deforestation since 1990 if the changes in stocks can be verified. 

According to most interpretations of the Kyoto Protocol, 

forest management activities alone are not sufficient to 

allow an area of forest to count toward the emissions 

reduction target. Article 3.4 provides an opportunity for 

nations to propose including additional activities such as 

forest management. The agreement does include sustainable forest management as part of a general statement 

supporting sustainable development and protection and 

enhancement of sinks. 

The language, terminology, and accounting methods 

contained in the agreement are somewhat vague, and can 

be interpreted in different ways. Definitions of key terms 

such as “reforestation” are not stated, which becomes a 

problem for implementation because there are many different definitions in use throughout the world. The proposed accounting system is vague. For example, it is not 

clear whether harvested timber should be counted as a 

forest sink and if so, under which circumstances it could 

be counted.

To address these issues, the FCCC asked the Intergovernmental Panel on Climate Change (IPCC) to establish 

an expert panel to develop a special report on the land 

CHAPTER 8
USDA Forest Service Gen. Tech. Rep. RMRS–GTR–59. 2000. 113

Mitigation Activities in the Forest Sector Birdsey, Alig, and Adams

use change and forestry provisions of the Kyoto Protocol. That group reviewed definitions, accounting issues, 

and activities that could potentially be included within 

the terms of the Protocol, and documented the various 

options for eventual reconciliation during the ongoing 

Conferences of Parties.

This chapter addresses options in the United States 

forestry sector to reduce emissions of greenhouse gases 

and to increase the rate of carbon sequestration in forest 

ecosystems. We summarize the various options that have 

been proposed in the literature, review the methodologies 

used to analyze options and compute baseline estimates, 

evaluate the potential for implementing various options 

and the expected changes in emissions or sequestration, 

and review costs and other considerations in implementing mitigation policies.

Summary of Forestry Options 

to Reduce Emissions or 

Enhance Sinks

Numerous forestry options to mitigate atmospheric 

buildup of CO2 have been proposed. These options are 

categorized below according to whether their primary 

or direct effect is on emissions reduction, sink enhancement, or a combination of emissions reduction and sink 

enhancement. Each of the options has indirect effects so 

that the three categories are not mutually exclusive. For 

example, forest management activities not only affect C 

storage in forest ecosystems, but affect the kind of products that may be produced from harvested wood, which 

in turn impacts energy use in two ways: 1) burning of 

byproducts to substitute for fossil fuel, and 2) substitution 

of wood products for similar products that use different 

amounts of energy in the production process (Marland et 

al. 1997).

Emissions Reduction

Reducing emissions is the most direct way to stabilize 

greenhouse gas concentrations in the atmosphere. Activities involving trees and forests may also achieve emission 

reductions indirectly, for example, by substituting one 

product for another, or by reducing demand for energy. 

In this section we identify the various forestry options 

for reducing emissions and the logic behind their potential inclusion as part of a comprehensive accounting for 

greenhouse gas sources and sinks.

Substitute Wood Products for More 

Energy-Intensive Products

Some wood products used in construction can be manufactured with less energy than non-wood substitutes 

such as aluminum and concrete (Skog et al. 1996). To the 

extent that such substitution is practical and economic, 

an increase in these wood products and a corresponding 

decrease in their substitutes reduces energy demand and 

associated emissions. The effectiveness of product substitution is based on a number of factors such as relative 

costs of inputs and elasticity of demand.

Reduce Demand for Energy in Growing Timber, 

Harvesting, and Wood Processing

Energy is used in establishing plantations, managing forests, harvesting timber, and manufacturing wood products. 

Efficiency of energy use can be increased through engineering at each step in the manufacturing process. Adoption of 

more energy-efficient practices depends on economic evaluation (U.S. Congress, Office of Technology Assessment 1991).

Reduce Biomass Burning (Wildfires)

Protecting forests from wildfire maintains standing 

biomass or allows biomass to increase. In some cases, particularly in the Western United States, fire protection has 

resulted in overstocked stands and large amounts of biomass in dead and dying trees, posing a substantial risk of 

catastrophic wildfire or other natural disturbance such as 

an insect or disease outbreak (Sampson and Clark 1996). 

Both the long- and short-term consequences of fire protection must be considered in evaluating this option.

Sink Enhancement

Sink enhancement technologies are designed to offset 

emissions by storing more C in forest ecosystems and 

wood products. Because much of the forest area in the 

United States is managed for timber products on recurring cycles of harvest, regeneration, and growth, there are 

opportunities to increase the average amount of standing biomass while still producing wood products. The 

harvested C that ends up in wood products and landfills 

is usually counted as an addition to the total amount of 

C sequestered. During the manufacturing process, wood 

waste that is burned for energy is sometimes counted to 

the extent that wood fuel is substituted for fossil fuel.

Afforest Marginal Cropland and Pasture

Conversion of cropland and pasture to forest, either 

by tree planting or natural afforestation, usually increases 
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FOREST SERVICE

ROCKY MOUNTAIN RESEARCH STATION

GENERAL TECHNICAL REPORT RMRS-GTR-59

SEPTEMBER 2000