Chapter 5. Forecasts of Forest conditions · chAPTeR 5. Forecasts of Forest Conditions Robert Huggett, David N. Wear, Ruhong Li, John Coulston, and Shan Liu1 key FiNDiNGS • Among

73chAPTeR 5. Forecasts of Forest Conditions

RobertHuggett,DavidN.Wear,RuhongLi, JohnCoulston,andShanLiu1

key FiNDiNGS

•Amongthefiveforestmanagementtypes,onlyplantedpineisexpectedtoincreaseinarea.In2010plantedpinecomprised19percentofsouthernforests.By2060,plantedpineisforecastedtocomprisesomewherebetween24and36percentofforestarea.

•Althoughpredictedratesofchangevary,allforecastsrevealthatlandusechangesandconversiontopineplantationswillresultinacontinuingdownwardtrendinnaturallyregeneratedpinetypes.

•Changesinforesttypesareinfluencedbyurbanizationandtimbermarkets:hardwoodtypesaremoststronglyinfluencedbyurbanization;softwoodtypesaremostsensitivetofuturetimbermarketconditions.

•Reversinga50-yeartrendofaccumulatingabout2.5billioncubicfeetperyear,forestbiomassisforecastedtoincreaseslightlyoverthenext10to20yearsandthendeclinegradually.

•Afteraccountingforharvests,forestgrowth,landuse,andclimatechange,thetotalcarbonpoolrepresentedbytheSouth’sforestsisforecastedtoincreaseslightlyfrom2010to2020/2030andthendecline.

•Urbanizationpatternsarethedominantdeterminatesofthesizeofthefutureforestcarbonpool,althoughstrongerforestproductmarketscanamelioratecarbonlosses.

•Becauseofincreasesintimbersupplyfrom1990to2010,removalsofforestbiomass(growingstock)areforecastedtoincreaseforallCornerstones,includingthosethatprojectdecreasingprices.Thisreflectsanoutwardshiftintimbersupplyassociatedwithforestinventoriesbetween1990and2010.

1RobertHuggettisaResearchAssistantProfessor,DepartmentofForestryandEnvironmentalResources,NorthCarolinaStateUniversity,Raleigh,NC27695.DavidN.WearistheProjectLeader,CenterforIntegratedForestScience,SouthernResearchStation,U.S.DepartmentofAgricultureForestService,Raleigh,NC27695.RuhongLiisaResearchAssociate,DepartmentofForestryandEnvironmentalResources,NorthCarolinaStateUniversity,Raleigh,NC27695.JohnCoulstonisaSupervisoryResearchForester,ForestInventoryandAnalysisResearchWorkUnit,SouthernResearchStation,U.S.DepartmentofAgricultureForestService,Knoxville,TN37919.ShanLiuisaResearchAssistant,DepartmentofForestryandEnvironmentalResources,NorthCarolinaStateUniversity,Raleigh,NC27695.

•Removalsofsoftwoodpulpwoodareresponsivetofuturesforforestplantingandproductprices.Underahighpricefuture,softwoodpulpwoodoutputwouldincreaseby56percent,roughlyequaltotheexpansionobservedbetween1950and2000.

•Althoughtheoveralllossofuplandhardwoodacreageisforecastedtobeintherangeof8to14percent,theoak-hickoryforesttyperemainsessentiallyconstantwhiletheareasofotherforesttypesdeclineathigherrates.Theyellow-poplarforesttypeisforecastedtodeclinethemost,withthehighestlossesforecastedforthePiedmont.

•Theageandspeciesstructureofsoftwoodforesttypesaremoststronglyinfluencedbyforestharvestingandmanagementtiedtotimbermarkets.Thisisnotthecaseforhardwoodforests.

•Thefuturestructureofhardwoodforestsismoststronglyaffectedbyurbanization-drivenlandusechanges(increasedpopulationgrowthandincome).

•Reductionsofnaturallyregeneratedpineforestsarenotequallydistributedamongageclasses.Mid-ageandearly-ageforestsdecline,butold-ageforestsremainrelativelyconstant.

•Thedistributionofuplandandlowlandhardwoodsshifts,withlessoftheseforestmanagementtypesclassifiedasearlyageandmoreclassifiedasolderage.

iNTRoDucTioN

TheSouth’sforestshavebeenshapedbyalonghistoryofharvesting,forestmanagement,andlanduseconversions.Europeansettlersbeganawaveoffarmingandlandclearingthatcontinuedtoexpanduntilaround1920(USDAForestService1988).Startinginthe1920s,extensivefarmabandonmentresultedinwidespreadforestestablishmentandold-fieldsuccession.Withthisperiodofforestrecovery,forestareaandforestbiomassgrewsteadilythroughmuchofthe20thcenturyandforestareapeakedinthe1960s.Inthe1970sand1980s,industrialscaleagricultureledtosomelossesinforestacreageespeciallyintheMississippiAlluvialValley,andinthe1990s,urbanizationbecamethedominantdynamicaffectingforestarea(WearandGreis2002).Despitetheselossessincethe1970s,thevolumeofgrowingstock(ameasureofstandingforestbiomass)grewbymorethan75percentwhileindustrialoutputofwoodproductsmore

Chapter 5. Forecasts of Forest conditions

74The Southern Forest Futures Project

thandoubledoverthelasthalfofthe20thcentury(Wearandothers2007).

TheexpansionoftimberharvestsintheSouthoutpacedthatofallotherregionsoftheUnitedStates.Asof2007,theSouth’stimberoutputwasmorethantwice1952levels.About60percentofalltimberproducedintheUnitedStateswasfromsouthernforests(Smithandothers2009)comparedtoabout40percentin1962,indicatingashiftingofproductioncapacitytotheregionaswellasincreasedoutput.ThisrelocationofproductiveactivityreflectstheSouth’scomparativeadvantageingrowingtimberandanewproductmixthatfavorssmallerdiametertrees.Whilesoftwoodscompriseamajorityofharvests(69percent),hardwoodharvestsarealsosubstantial.

Thischapterexplorestheongoingandpotentialfuturechangesaffectingsouthernforests.Severaluncertainties

cloudourabilitytopredictthatfuture.AstheSouth’seconomyexpands,populationandattendanturbanizationcontinuetooutpaceallotherregions.Attheendofthe20thcentury,shiftsinmarketdemandslowedthesteadyprogressionoftimberharvesting.Newpoliciespursuenewdemandsfortimbertoprovidecellulose-basedbioenergy.Anticipatedclimatechangesraisekeyquestionsaboutthefutureproductivityandcompositionofforests.Andalthoughforestsarebytheirnaturedynamic,therehavebeenbothanaccelerationandaninteractionofchangesinsouthernforeststhatcannotbeunderstoodwithoutcomprehensiveanalysis.

Amodelingsystemdesignedtoforecasttheinteractionsofvarioussocial,economic,andbiophysicaldriversandthestructureandextentoffutureforestsisusedinthischaptertoexploretheimplicationsofthechangesthatwillaffectsouthernforests(seetextboxonfollowingpage,table5.1,andfig.5.1).Keytothesystemisasetofscenarios,called

Table 5.1—Definition of Cornerstone Futures used in the Southern Forest Futures Project, based on two storylines from the 2010 Resources Planning Act (RPA) Assessment and three general circulation models

cornerstone Futures RPA Storylines General circulation

modelTimber prices

Planting ratesTag label label

economic growth

Population growth

A High growth/high prices A1B High Moderate MIROC Increasing BaseB High growth/low prices A1B High Moderate CSIRO Decreasing BaseC Low growth/high prices B2 Low Low CSIRO Increasing BaseD Low growth/low prices B2 Low Low Hadley Decreasing BaseE High growth/high prices/high planting A1B High Moderate MIROC Increasing HighF Low growth/low prices/low planting B2 Low Low Hadley Decreasing Low

Figure5.1—ThesixCornerstoneFuturesdefinedbypermutationsoftwo2010ResourcesPlanningAct(RPA)Assessment/IntergovernmentalPanelonClimateChangestorylinesandtwotimberpricefutures;andthenextendedbyevaluatingincreasedanddecreasedforestplantingrates.


CornerstoneFutures,whichweredevelopedtorepresentabroadrangeofplausiblefutures(chapter2).ForeachCornerstoneFuture,themodelingsystemsimulateschangesinforestarea,shiftsamongforesttypes,theamountanddistributionofforestbiomass,harvestremovals,andchangesintheforestcarbonpool.Totheextentpossible,weexaminevariationacrossthefivesubregionsoftheSouthandfocusonthespatialdistributioninforestconditions.Thesefindingsprovideafoundationforfurtherexplorationoftimbermarkets(chapter9),bioenergyfutures(chapter10),andimpactsonwildlife,biodiversity,andforestcommunities(chapter14).

meThoDS

TheresultsexaminedinthischapterarebasedontheU.S.ForestAssessmentSystem,amodelingsystemdesignedtoforecastalternativefuturesforU.S.forests.2TheU.S.ForestAssessmentSystemisaforward-lookingadjuncttotheForestInventoryandAnalysis(FIA)ProgramoftheForestService,U.S.DepartmentofAgriculture,andwasimplementedbyresearchanddevelopmentstaffoftheForestService.TheFIAprogramprovidesnationwidemonitoringthroughrepeatedinventoriesthatprovideconsistencyovertimeandahighlevelofdetail.TheU.S.ForestAssessmentSystemaccountsforchangesdrivenbymultiplevectorsincludingbiological,physical,andhumanfactorstogenerateforecastsofforestinventories.Themodelingapproachisdesignedtoaddresschangingclimate,market-driventimberharvesting,andlandusechangesalongwithchangesdrivenbysuccessionaltransitionsinforestconditions.

Ageneralschematicofthismodelingsystem(fig.5.2)startswithasetofinternallyconsistentcombinationsofsocial,economic,andtechnologyforecastsdefinedastheCornerstoneFutures(alsocalledCornerstonesinthisbook)forthisapplicationoftheU.S.ForestAssessmentSystem.LinkedtotheCornerstonesarevariousgeneralcirculationmodels(climatemodels,orGCMs),eachselectedtodefineaclimateforecastthatisconsistentwiththeCornerstone.Alsolinkedaredatafromaforestinventoryserver,whichdefinesstartingconditionsforallplotsintheforestinventory.

Themodelingframeworkatthecenterofthissystem(middlecolumnoffig.5.2)showshowfutureforestconditionsaredrivenbybiologicaldynamics—suchasgrowthandmortality—whichinturnareaffectedbyclimatefactors.Inaddition,humanchoicesregardingallocationsamonglandusesandthedisposalofforestland,timberharvesting,andforestmanagementalsoaffectchangesinforests.Theinterplayofallofthesefactorsyieldsasetofoutputs,each

2BecauseofdatalimitationstheU.S.ForestAssessmentSystemdoesnotyetaddresschangesinforestconditionsinTexasandOklahomaoutsideoftheireasternsurveyunitsthatareheavilyforested.

The cornerstone Futures

TheSouthernForestFuturesProjectusessixCornerstoneFutures(labeledwithlettersAtoF)toprovidealternativescenariosregardingthefutureofseveralexogenousvariables(table5.1).Thesearebasedonacombinationofcounty-levelpopulation/incomeprojectionsfromtheResourcesPlanningAct(RPA)andIntergovernmentalPanelonClimateChange(IPCC)Assessments,assumptionsaboutfuturetimberscarcity,andassumptionsabouttreeplantingrates(seechapter2fordetails).

TwoRPA/IPCCstorylines,labeledA1BandB2areusedfortheCornerstones.B2providesalowerrateofpopulationgrowth(a40percentincreasebetween2010and2060),andA1Bprovidesasomewhathigherrateofgrowth(60percent).IncomegrowthishigherwithA1B.Bothofthesestorylinesareconnectedtodetailedglobaleconomic/demographicscenariosthataredescribedintheIPCCandRPAreports(IPCC2007a,2007b;USDAForestService2012).

Timberpricefutureseitheraddressincreasingordecreasingscarcitywithanorderlyprogressionofrealpricesfortimber:eitherincreasingordecreasinginrealtermsatonepercentperyearfromabasein2005through2060.WealsoholdtherealreturnstocropsconstantthroughouttheforecastsforallCornerstoneFutures.

AnotherelementofthestorylinesembeddedintheseCornerstonesistheclimateforecastedusinggeneralcirculationmodels(GCMs)appliedtotheassumptionsofthestorylines.Forecastvariablesincludechangesintemperature,precipitation,andderivedpotentialevapotranspirationdownscaledtocounties.WeutilizethreedifferentGCMsinconstructingtheCornerstonestoaddressthepotentialvariabilityinspatialdistributionofresultingchangestoforests.Moredetailonclimateinputstotheforecastsiscontainedinchapters2and3.

Infigure5.1,thesixCornerstoneFuturesaredisplayedinadiagramthatemphasizestheirkeyvariables.CornerstonesA-DaredefinedbythematrixformedbyintersectingRPA/IPCCstorylinesA1BandB2withincreasinganddecreasingtimberpricefuturesasdescribedabove.ThesefourCornerstonesusehistoricaltreeplantingratesfollowingharvests(byStateandforesttype)toforecastfutureplanting.CornerstonesEandFdepartfromthesefourbyeitheraugmentingplantingratesforCornerstoneA(E)orbydecreasingplantingratesforCornerstoneD(F).


ofwhichdescribesforestprojectionsthatareconsistentwiththeflowofforestproductsandlanduses.Changesinwater,biodiversity,andotherecosystemservicescanalsobederivedfromtheforecastedchangesinforestconditionsandlanduses.Manyofthesearedescribedinsubsequentchapters.

Theforestdynamicsmoduleofthisframeworkprovidestheoutputsdiscussedintheresultssectionofthischapter.Withinthismodulethefutureofeveryplotintheforestinventoryisprojectedinamultiplestageprocess(seeWearandothers[2013]fordetailsonmodelingapproaches).Aharvestchoicemodelassignsamanagementintensitychoice(noharvest,partialharvest,orfinalharvest)basedontimberprices(fromaforestproductsmodule)andtheconditionoftheplot(Polyakovandothers2010).Theageofeachplotisdeterminedforthenextperiod,andifharvested,theplotisdeterminedtobenaturallyregeneratedorplanted.Forecastedclimateincludingtemperatureandprecipitationisassignedandforestconditionsontheplotareinferredbasedontheharvest/noharvestdecision,age,andclimateselection.

PlantingprobabilitiesarebasedonthefrequencyofplantingonharvestedplotsbasedontheforesttypeandStateforthe

mostrecentinventoryperiod.Giventhehighplantinglevelsobservedoverthisperiod,forecastedrateswereadjusteddownwardby50percentforCornerstoneFuturesA-D.Thehigh-plantingCornerstoneFuture(E)uses75percentofthehistoricalplantingrateswhilethelow-plantingCornerstoneFuture(F)uses25percent.

Toincorporateforestmarketdata,weadoptedasimplifiedprocessthatspecifiesapricetrajectoryforeachCornerstoneFutureandprovidesinputbothonindividualplot-harvestdecisionsandontheoverallsupplyoftimber.Consistentwiththeory,higherpricesyieldmoreharvestingandlargertimbersupplies;lowerpricesyieldsmallertimbersupplies.Harvestchoicemodelsarebasedonempiricalanalysisandareconsistentwithharvestingbehaviorobservedinthelate1990sandearly2000s.

Thelandusemodule(fig.5.2)describedinchapter3(seealsoWear2011)simulateschangesinallusesoflandandisdrivenbypopulationandincomegrowthalongwiththepricesoftimberproducts.Projectionsofforestareafromthelandusemodulefeedintotheforestdynamicsmoduleandtheprojectionoffuturemarketconditions.Changesforecastedatthecountylevelfornon-FederallandarebasedonNational

Figure5.2—SchematicoftheU.S.ForestAssessmentSystem.


ResourcesInventorydata(chapter3)andareusedtorescalethearearepresentedbyeachplotinthecounty(alsoknownasplotexpansionfactors).

Theassignmentoffutureplotconditionsusesaresamplingofhistoricalplotrecordscalledwhole-plotimputation(Wearandothers2013),whichinvolvestheselectionofahistoricalplotwithcomparableconditionstorepresenteachplotlocationinthefuture.Theselectedhistoricalplotisascloseaspossibletotheoriginalplotlocationtoallowfororderlychangesinconditions,e.g.,ifplotconditionsareforecastedtobewarmer,theresamplingalgorithmwouldfirstlookwithinthesamesurveyunittofindahistoricalplotwithsimilartemperatureincreases.Findingnone,thealgorithmwouldextendthesearchtoadjacentunitsuntilanappropriatematchisfound.Thisprocessisrepeatedforeverytimestep(orintervalbetweenmeasurementsorprojections)togenerateplotforecastsovertime.Theinventoryforecastiscompletedbycouplingtheplotforecastwiththelanduseforecasts,whichareappliedtoadjustthearearepresentedbyeachnon-Federalplotwithineachcounty(throughtheplotexpansionfactordescribedabove).

Theforestdynamicsmodelisbasedonseveralprobabilities,includingprobabilisticharvestchoice,forestinvestment,andforesttransitionmodelsthatareimplementedwithrandomdrawsfromprobabilitydistributions,andawhole-plotimputationthatisbasedonarandomselectionofasubsetofhistoricalplotswithreplacement.Forecaststhereforemayvarybetweenrunsofthemodel.Theforecastsforthe50-yearsimulationinthischapterarebasedon26runs,oneofwhichwasselectedasrepresentativebasedoncentraltendencyacrossseveralvariables.Thefullsuiteof26runsoffersinformationabouttheuncertaintyoftheforecastsandisusedwheneverconfidenceintervalsareneeded.

ThetimestepofthesimulationdependsontheFIAinventoriesthatunderliemuchofthemodeling(Wearandothers2013).BecausestartingyearsandtimestepvaryfromStatetoState,theforecastperiodsarestaggeredacrosstheregion,e.g.,aStatemighthaveatimestepof6yearsstartingin2007,whileanotherStatemighthaveatimestepof6yearsstartingin2008.Forreportingacrosstheregion,weselected10-yearintervals,eachbeginningwithazero-endingyear,e.g.,1990,andthenattachedforecastsfromthenearestyeartothereferenceddecade—identicaltohowFIAassignsyearsforaggregateinventories(Smithandothers2007).

Thereportsandmapsinthischaptershowchangingforestconditionsfortheforecastperiod(2010to2060)inenoughdetailtodepictacompleteforestinventoryforeachStateintheSouth.Wefocusedonforecastingthevolumeofforestbiomass,theareaofforestsbytypeandageclass,thecarboncontainedinabove-andbelowgroundpools,andremovalsfromforestsdeterminedbyforestproductharvestsandland

usechanges.OurapproachwastosummarizetotalchangesfortheSouthandtheirdistributionacrosssubregions.

DATA SouRceS

ForeachState,FIAplotrecordswereavailabletopopulatetheforestdynamicsmodelandconducttheresampling.Werequiredatleasttwoinventorypanelsofmatchedplots,ideallywithbothderivedfromthecontinuousinventorydesignthatwasimplementedin1998toreplacecomplete-but-periodicinventoriesofthepastwithannualupdates.Becauseofchangesintheplotmeasurementapproach,wedeterminedthatitwasimportanttousetwopanelsofcomparabledesigntoconstructtransitionmodelsforkeyvariables.Sowhenfacedwiththedilemmaofonlyoneavailablecontinuousinventory,weoptedforpanelsfromtwoolder(periodic)inventoriesratherthanrelyontwodifferentdesigns.

FrompubliclyavailableplottableslocatedontheFIAWebsite,weextractedrawdataonplotcharacteristics,discretelandscapefeatures,andmeasurementsoftreeslargerthan1-inchd.b.h.Wewerealsograntedaccesstoconfidentialplotlocationdata,allowingustoconducttheplotmatchingneededtoevaluatetransitionsovertime.Expansionfactors,theareaassociatedwitheachplot,wereattachedtotheplotswiththeappropriatetables.Eachplot’scountylinksittothelandusemodel(seechapter3).

BecausetheFIAinventoryisextensive,weperformedsomemanipulationsontherawdatatoallowustosummarizevaluesforanalysis.Biomassvariables,suchasthevolumeandnumberofgrowing-stocktrees,werecalculatedonaperacrebasisusingalgorithmsderivedfromMilesandothers(2001)toaccountforchangesinsurveymethodologyovertheyears.Forexample,plotsintheannualinventorypanelsweredividedintocomponentstocapturecondition-leveldetailssuchasforesttype.AsavalidationstepwegeneratedtotalvaluesforStatesandsurveyunits,whichcouldthenbecomparedwithpublishedreportsandconfirmtheaccuracyofthealgorithms.

Changesinalgorithms,recording,andmeasurementtechniquescreateddataanomaliesinmanyinventories.WecomparedattributesacrossinventoriesineachStatetodeterminewheredataadjustmentswererequired.Thiswasespeciallycrucialwhenconductingtheanalysisoftransitions.

CarbonestimatesareattachedtoeachhistoricalplotusingmodelsdevelopedandappliedbyFIAusingtheU.S.ForestCarbonCalculationTool(Smithandothers2007).ThistoolincorporatesestimatesderivedfromfieldmeasuresintotheFORCARB2modeltoprovidecarboninventoriesthatareconsistentwithstandardsdevelopedbythe


populationgrowthismoderatebutincomegrowthisstrong(resultinginhighurbanization),andtimberpricesarefalling(resultinginshiftsofforestlandtoagriculturaluses).Figure5.3alsoshowsthatpriceeffectsdominatetheprojectionofforestarea,withthehighestforestlossassociatedwithCornerstonesthathavedecreasingprices(B,D,andF);thethreeCornerstoneswiththelowestforestlosshaveincreasingprices(A,C,andE).

ForestlossesareespeciallyhighinafewareasoftheSouth(fig.5.4).ForallCornerstoneFuturesforestlossesareconcentratedinthePiedmontfromnorthernGeorgiathoughNorthCarolinaandpartsofVirginia,theAtlanticandGulfofMexicocoastalareas,andtheareasurroundingHouston.Theincome-fueledurbanizationinCornerstonesAandBspreadslowintensityforestlossesacrossabroaderareaoftheSouth(chapter3).ForallCornerstones,thenumberofacreslostislargestintheCoastalPlainandsmallestintheMississippiAlluvialValleyandtheMid-South.ThepercentofacreslostislargestinthePiedmontfollowedbytheAppalachian-CumberlandhighlandsandtheCoastalPlain.

Forestareachangealsovariesacrossthefiveforestmanagementtypes:plantedpine,naturalpine,oak-pine,uplandhardwood,andlowlandhardwood.Theuplandandlowlandhardwoodtypesareforecastedtocomprisebetween51and53percentofallforestsin2060,adeclinefromabout54percentin2010(fig.5.5).Thegreatestchangeshoweverarefoundamongthesoftwoodtypes(plantedpine,naturalpine,andoak-pine).Theseforestdynamicsareheavilyinfluencedbymanagementforforestproducts,whichinturnisdrivenbytimbermarketconditions,andbytherateofforestplanting.

Planted pine–OfthefiveforestmanagementtypesintheSouth,onlyplantedpineisforecastedtoincreaseinspiteofoveralldeclinesinforestedarea.TheSouthnowcontains39millionacresofplantedpine(about19percentoftotalforestarea),theculminationofanupwardtrendthatstartedinthe1950s.Ourprojectionsofplantedpinearedrivenbyurbanization,timberprices,andplantingrates(fig.5.6).CornerstoneE,characterizedbyarelativelyhighlevelofurbanizationaswellashightimberpricesandplantingrates,producesthelargestexpansioninplantedpine(thoughatrateslowerthanthoseexperiencedinthe1990s)andyieldsanincreaseof28.2millionacresby2060(about560,000acresperyear).UnderthisCornerstone,34percentofforestswouldbeplantedpinein2060.Conversely,CornerstoneF,characterizedbyarelativelylowlevelofurbanizationaswellaslowtimberpricesandplantingrates,yieldsthesmallestgaininplantedpineareawithanincreaseof7.8millionacresby2060(24percentofforestarea).TheremainingCornerstoneshaveprojectionsthatareintermediatetotheseresults.TheyclusteraroundtheforecastforCornerstoneDwithitslowertimberpricesandslowerurbanization:againof16.8million

acres(about0.3millionacresperyear)withplantedpinecomprising28percentoftheforestacreagein2060.

Natural pine—Forecastedlossesintheareaofnaturallyregeneratedpineforesttypesmirrorthegainsinplantedpineforestsandarethereforerelated,albeitinversely,totheconditionofforestproductsmarkets(fig.5.6).Thelargestdecreaseinnaturalpine—alossof58percentfrom31.5millionacresin2010to13.5millionacresin2060—isassociatedwithCornerstoneE,whichhasthehighestplantingrates.ThesmallestdeclineoccurswithCornerstoneF,withitslowertimberpricesandplantingrates,butlossesarestillsubstantial—7.6millionacresor25percentfrom2010to2060.RegardlessoftheCornerstoneevaluated,naturallyregeneratedpinetypesareforecastedtodecline,continuingatrendthathasdominatedforesttypedynamicssincethe1960s.

Oak-pine—Theareaoftheoak-pineforestmanagementtypealsodeclinesforallCornerstoneFutures,withasimilarpatternofchangebutsmalleracreageandpercentchangesthanisforecastedfornaturalpines(fig.5.6).Aswithnaturalpine,oak-pineismoreheavilyinfluencedbytimbermarketconditionsthanbyurbanizationrates.Oak-pinedeclinesrangefrom8.5millionacres(38percent)to3.9millionacres(17percent)bytheyear2060.

Upland hardwood—Atmorethan80millionacresin2010,uplandhardwoodsarethepredominantforesttypeintheSouth,morethandoubletheareaofthenextlargestforesttype.UplandhardwoodsareforecastedtodeclineforallCornerstoneFutures(fig.5.6),andvariationsinforecastsareassociatedmorewiththerateofurbanizationthanwithtimbermarketfutures.ThethreeCornerstoneswiththelowestuplandforestlossareassociatedwithlowerurbanization(CornerstonesC,D,andF),andthethreewiththehighestlossareassociatedwiththehigherurbanizationforecasts(CornerstonesA,B,andE).Lossofuplandhardwoodforestsrangesfrom5.9millionacres(about8percent)forCornerstoneCto11.2millionacres(14percent)forCornerstoneB.ForCornerstoneE,whichisalsocharacterizedbyhightimberpricesbutwithevenhigherratesofplanting,theprojectedtotalareaofplantedpineforestwouldbenearlyequaltouplandhardwoodforestsin2060,asthestimulatingeffectsofpriceandplantingonthepinetypecombineswiththedepressingeffectsofurbanizationonthehardwoodtype.

Lowland hardwood—Theareaoflowlandhardwoodforestsisalsomoresensitivetotherateofurbanizationandlesssensitivetoforestproductsmarketsthanthesoftwoodtypes.Forthisforestmanagementtype(fig.5.6),forecastsindicatelossesrangingfrom1.7millionacres(5percent)to4millionacres(12percent)by2060fromabaseof32millionacresin2010.Therelativerankingofchange


acrossCornerstoneFuturesisidenticaltotheforecastsforuplandhardwoodtypes.Lowlandforestsloseproportionallylessareathantheotherforesttypesthatexperiencelosses.

TheforecastsofforesttypedynamicsvaryacrosstheFuturesProjectsubregions(figs.5.7,5.8,and5.9).Forestlosses,especiallyconcentratedinthePiedmontandAppalachian-Cumberlandregions(figs.5.7),andintensivemanagementintheCoastalPlaininfluenceforesttypesdifferently.TheCoastalPlain,with82percentofplantedpinein2010,experiencesthegreatestgrowthinplantedpinearea,from32millionacresto43millionacres.DeclinesinnaturallyregeneratedpinearegreatestintheCoastalPlainaswell.UplandhardwoodlossesaregreatestinthePiedmontandintheAppalachian-Cumberlandsubregionreflectingtheinfluenceofurbanizationonthesetypes.ChangesinlowlandhardwoodtypesaremoreevenlyspreadacrosstheSouth.

Forest Biomass Forecasts

Ofthevariousmetricsavailableformeasuringbiomasschangesforasiteinaforestinventory,weoptedtofocusonthevolumeofgrowingstockbecauseitisausefulindexbothfortimberanalysisandformeasuringotherecosystemservices.Totalgrowingstockvolumesareforecastedtochangeinresponsetobothlandusechangesandtimberharvestinglevels(fig.5.10).Fromabaseofabout292billioncubicfeetin2010,inventoriesincreaseatmostbyabout11percentin2060underthelow-urbanization/low-timber-priceCornerstoneD.Thesmallestincreaseintotalgrowingstockinventoriesisfoundwiththehigh-urbanization/high-timber-priceCornerstoneA,withanincreaseinvolumeto2030andthenadeclineovertheremainderoftheforecastperiod.UnderthisCornerstone,thevolumein2060isabout1percenthigherthanvaluesobservedin2010.

Patternsofchangedifferbetweenhardwoodandsoftwoodcomponentsoftheinventoryandgenerategenerallycountervailingchanges.UnderallCornerstones,softwoodgrowingstockinventoriesincrease(fig.5.11).Forthelow-urbanization/low-timber-priceCornerstoneD,softwoodinventoriesincreasefromabaseofabout121billioncubicfeetin2010toasmuchas148billioncubicfeet(37billioncubicfeetor22percent).Thesmallestincreaseis15percent(18billioncubicfeet)forthehigh-urbanization/high-timber-pricesCornerstoneA.

Hardwoodgrowingstockinventoriesrevealdifferentpatternsofchange.Startingfromabout171billioncubicfeetin2010,hardwoodgrowingstockvolumespeaksomewherebetween2020and2040forallCornerstonesandthendeclinetotheyear2060(fig.5.11).ThemostpronounceddeclinesareforCornerstonesAandE,bothofwhichhavehighratesofurbanizationandhightimberprices.DeclinesfortheseCornerstonesareintherangeof15billioncubicfeet

(9percent)from2010to2060.CornerstonesFandDresultinincreasesof3billioncubicfeet(2percent)forthesameperiod.

ThesechangesingrowingstockvolumedepartfromhistoricalpatternsofvolumeaccumulationintheSouth.Between1963and2010southernforestsaccumulatedabout2.5billioncubicfeetperyearorroughly70percent.Hardwoodforestsaccountedformostofthisbiomassaccumulation(61percent).Althoughgrowthisprojectedtocontinueoveratleastthenext10years,growingstockvolumereachesamaximumandthendeclinessomewhatoverthefollowing40years(fig.5.12),withhardwoodgrowingstocksdeclining,especiallyinresponsetourbanization(CornerstoneA),whilesoftwoodvolumesincreaseonlyslightly.

Figures5.13,5.14,and5.15showcounty-levelchangesingrowingstockvolumefrom2010to2060forthehigh-urbanization/high-timber-pricesCornerstoneA.Whilesoftwoodgrowingstockincreasesoverall,areaswithlargeincreasesinplantedpine(fig.5.8)showdeclinesinsoftwoodgrowingstockvolumesasoldernaturallyregeneratedpineforestsarereplacedbyyoungerplantedpineforests(fig.5.14).Declinesinhardwoodgrowingstockvolumesbetween2010and2060aremorewidespreadandgenerallyorganizedbyurbanizationpatterns(fig.5.15).EasternKentuckyandfarwesternVirginiashowthegreatestgainsinhardwoodgrowingstockvolumes.

Forest carbon Forecasts

Weestimatethecarbonstoredinsouthernforestsin2010atabout12.4billiontons,includingcarbonstoredineightpools:downtrees,standingdeadtrees,litter,soilorganiccarbon,livetreesabovegroundandbelowground,andunderstoryplantsabovegroundandbelowground.Abovegroundlivetreesandsoilorganicmaterialcomprise80percentofthetotalcarbonstock.Forecastsoffutureforestcarbonstocksreflectchangesintheamountofforestareaandthecompositionoftheforestinventory.However,themodeltracksonlythecarbonpoolinforestsanddoesnotaccountforcarbontransferstoagriculturalandotherlandusepools.Likewise,themodeldoesnotaccountforcarbonthatleavesforestsasproductsandmayremainsequesteredforlongperiodsoftimeinhousingorotherenduses(e.g.,Heathandothers2011).

Changesinforestcarbonpoolsreflectbothchangesingrowingstockvolumesandchangesinforestarea(figs.5.16and5.17).UndermostCornerstones,treecarbonpeaksin2020andthenlevelsoffordeclines;theexceptionisthelow-urbanization/high-timber-pricesCornerstoneCwhoseforecastpeaksin2030.Atmost,theforestcarbonpoolin2060is5percentsmallerthanthepoolin2010(anetemissionofabout600milliontons).Carbonaccumulatesasaresultofnetbiomassgrowthonforestedlands(fig.5.17.F),but


Figure5.10—Totalgrowingstockvolume,2010to2060,byCornerstoneFuture.

thesegainsareoffsetbythelossofforestedlandthroughurbanizations(i.e.,thelossofsoilcarbonshowninfig.5.17.D).

TheclusteringofcarbonforecastsinFigure5.16revealstheinterplayofurbanizationandtimberprices.Theforecastswiththehighestamountofcarbonin2060areforthelow-urbanizationCornerstones(C,D,andF).Thelowestcarbonforecastedisforthehigh-urbanizationCornerstones(A,B,andE).However,withineachofthesetripletsthelowestamountofcarbonisassociatedwithlowtimberprices(CornerstonesB,D,andF)whilehighertimberpricesandresultingintensiveforestmanagementleadtohighercarbonsequesteredintheforestpool.Thissuggeststhaturbanizationpatternsdominatetheforecastsofcarbonstoragewhilestrongerforestproductmarketscanamelioratecarbonlosses.

Forest Removals Forecasts

RemovalsfromgrowingstockareforecastedtoincreaseforallCornerstoneFuturesreflectingbothlandusechangesandtimberharvesting(fig.5.18).From2010to2060,removalsareforecastedtoincreasebyasmuchas85percent(thehigh-urbanization/high-timber-price/more-plantingCornerstoneE)

andaslittleas35percent(thelow-urbanization/low-timber-price/low-plantingCornerstoneF).ThedominantfactorthataffectsthenumberofremovalsisthepriceprojectionfortimberthatisassociatedwitheachCornerstone.ThemostremovalsareassociatedwithhighpriceCornerstones(A,C,andE)whilethelowestremovalsareassociatedwithlowpriceCornerstones(B,D,andF).Evenwithdecliningprices,harvestsareprojectedtoincrease,reflectingpreviousforestinvestments,maturationofforestinventories,andremovalsassociatedwithforestlosses.

Theforecastsgeneratedistinctlydifferentremovalpatternsforhardwoodsandsoftwoods(fig.5.19).Softwoodremovalsareforecastedtoincreasesteadilyovertheprojectionperiodandatratescomparabletorecenthistory.Forhardwoods,forecastedremovalsincreasefrom2010to2020andthenleveloffformostCornerstones.Theincreaseinthefirstdecadereflectstherecoveryfromsuppressedremovalsleadinguptoandduringthe“greatrecession”(2005to2010).Trendsinlaterdecadesreflectadeclineinhardwoodgrowingstockinventories,mostespeciallyinthepulpwoodsizeclasses.

Amongproducts,softwoodpulpwoodremovalsarethemostvariableacrossCornerstones,withforecastsranging


between2,800millioncubicfeetforthelow-plantingfutureofCornerstoneFand3,900millioncubicfeetforthehigh-plantingfutureofCornerstoneEby2060(seechapter9foradiscussionoftimbersupplyandtimbermarketforecastsrelatedtotheCornerstoneFutures).Historically,becausethepinesarethedominantplantationspecies,pinepulpwoodhasbeenthemostprice-responsivetimberproductintheSouth.5Overthelongrun,thehigh-pricefuturesofCornerstonesAandCproducemorepulpwoodthanthelow-pricefuturesofCornerstonesBandD,andthehigh-prices/more-plantingfutureofCornerstoneEproducesthemostsubstantialincreaseinsoftwoodpulpwoodoutput(about56percent).

SoftwoodsawtimberremovalsalsoshowstronggrowthpotentialacrosstheCornerstonesandarealsostronglyaffectedbypriceforecasts(fig5.19).Incontrasttopulpwoodhowever,sawtimberoutputlevelsoffovertimeandisnotstronglyinfluencedbyplantingrates.NaturallyregeneratedsitesarematuringintheSouth,resultingingrowth-inducedsupplyincreases.Thisexplainswhyitispossibleforsoftwoodsawtimberoutputtoremainstableorincreasewith

5Econometricstudiesshowthatsawtimberproductsarethemostprice-responsiveintheshortrun.However,inthelongrun,investmentsinnewpineplantationshaveledtosubstantialincreasesinpulpwoodproduction.

decreasingprices.Softwoodsawtimberoutputeventuallylevelsoffastheareaofnaturalpinedeclinesovertime.

WhilestillseparatedbylowandhighpriceCornerstones,hardwoodremovalforecastsvarymuchlessthansoftwoodremovals(figs.5.20).Afterincreasingfrom2010to2020,hardwoodremovalsareforecastedtodeclineforthelowpriceCornerstones(B,D,andF).ForthehighpriceCornerstones(A,C,andE),removalsincreaseuntil2030,whentheybegintoleveloff.Incontrasttothesoftwoods,directinvestmentinsouthernhardwoodforestshasbeennegligible,andnoneisprojectedforthefuture.Theresultisasteadydropinhardwoodforestareaandinhardwoodgrowingstockinventories.

Whenconsideredtogether,growingstockandremovalforecastsindicateacontinuationofsomeimportanthistoricaltrends.Removalsareforecastedtoincreasesubstantiallyinspiteofalevelingoffofinventories(fig.5.21).Thisreflectsanongoingtransitionfromaforestminingapproachtoanagriculturalmodelofforestproduction.Plantedpinemanagementallowsformoreproductionfromasmallerlandbasewithamorefrequentcaptureofforestgrowth.Thismeanslowerinventoriesonthegroundcomparedtonaturallyregeneratedforests.

Figure5.12—Historical(1962to1999)andforecasted(2020to2060)hardwoodandsoftwoodgrowingstockinventories,forCornerstonesAandD.


Forest condition Forecasts

TheU.S.ForestAssessmentSystemisdesignedtoreplicateinventoriesacrossbroadareas—e.g.,aggregatesofatleastseveralcounties—andforbroadforesttypegroupings.However,theresampling/imputationapproachdoesprovidesomeinsightsintohowdriversofchangemayalterforestcompositionatafinerscale,e.g.,figure5.22showsforestforecastsofhardwoodtypesforthehigh-urbanization/low-timber-priceCornerstoneB,whichleadstheotherCornerstonesindeclinesofforestarea.ForthisCornerstone,allhardwoodtypesareforecastedtolose16millionacres(14percent)butnotalloftheforesttypesloseareaatthesamerate.Oak-hickorylosesabout1percentcomparedto10percentormoreforallotherforesttypes.Themostsubstantiallossesarefortheotherhardwoodandyellow-poplartypes,whichlose26percent(6millionand4millionacres,respectively).Diggingabitdeeper,lossesoftheyellow-poplarforesttypeareexpectedtobeabout25percentintheCoastalPlain(1.4millionacres)andtheAppalachian-Cumberlandsubregion(1millionacres),comparedtoamoresubstantiallossof34percentinthePiedmont(1.6millionacres).

Theforecastedareaofsoftwoodtypesisshowninfigure5.23.Loblolly-shortleafpineisthedominanttypeanditsareastaysroughlylevelthroughtheforecastperiod.Althoughoverallforestareaisexpectedtodeclineandsoftwoodremovalsareforecasttoincrease,continuedinvestmentinplantationsenablesthistypetomaintainitsarea.Longleaf-slashpineisforecastedtoincreaseslightlywhileoak-pineisexpectedtodecline.Allothertypesexhibitverylittlechange.

Anotherelementofforestconditionsthatmaybeespeciallyimportantforwildlifeistheageclassdistributionofforesttypes(chapter6).Figure5.24showsforecastsofageclassesforbroadforesttypesforthehigh-urbanization/high-timber-prices/more-plantingCornerstoneE.Early-ageforestsarethosethatarelessthan20yearsold,mid-ageforestsarebetween20and70yearsold,andold-ageforestsaregreaterthan70yearsold.BecauseCornerstoneEhasthelargestchangeinforestmanagementtypes(fig.5.5)andthemostharvesting(fig.5.18),itisa“best”casefortheproductionofearly-ageforests.

Figure5.16—Totalforestcarbonstock,2010to2060,byCornerstoneFuture.


Figure5.18—Forecastsoftotalremovalsfromgrowingstock,2010to2060,byCornerstoneFuture.

Figure5.19—Forecastedremovalsfromsoftwoodgrowingstock,2010to2060,byCornerstoneFuture.

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Withtheexceptionofplantedpine,allforesttypesareforecastedtoexperienceadeclineinearly-ageforeststhroughouttheforecastperiodforCornerstoneE.Plantedpineforestsareforecastedtoshifttheirage-classdistributionstowardmoremid-ageforestsastherateofplantingdeclinesfromitspeakinthelate1990s.Mid-ageforestareaincreasesstrongly,whileearly-ageforestareaincreasesatamoremoderaterate.Therearepracticallynoacresofold-ageforestintheplantedpineforesttype.

HighharvestratesandconversiontoplantedpineinCornerstoneEshiftstheage-classdistributionofthenaturallyregeneratedpinetypes.Theareaofold-agenaturalpinestaysrelativelyconstantwhilemid-ageforestsdeclineby13millionacres(about64percent)andearly-ageforestsdeclinebyabout4.5millionacres(58percent).Oak-pineshowsasimilarpatternofageclasschanges.

Incontrasttothesoftwoods,hardwoodforecastsshowanincreaseinold-ageforests.Foruplandhardwoods,theareaofmid-ageforestsisforecastedtodeclineby14millionacres(downfrom59percentin2010to47percentin2060).Overthissameperiod,old-ageforestsareforecastedtoincreaseby12millionacres(upfrom20to40percent)andearly-ageforestsdecreaseby8millionacres(downfrom21to13percent).Overall,theshiftamongageclassesrevealsthattheearly-agecomponentoftheuplandhardwoodtypedeclinesby44percentatthesametimethattheold-agecomponentincreasesby71percent.

Thepatternofchangeforlowlandhardwoodforesttypesissimilartochangesinuplandhardwoodforesttypes,butchangesoccuratdifferentrates.Themid-agecomponentoflowlandhardwoodforestsdeclinesbyabout5millionacres(26percent),theold-agecomponentincreasesbyabout4millionacres(77percent),andtheearly-agecomponentdeclinesbyabout2millionacres(33percent).Aswiththeuplandforesttypes,whilethetotalareaoftheforesttypedeclines,theaverageageoftheforesttypeincreases.

ContrarytoCornerstoneE,CornerstoneF(fig.5.25)ischaracterizedbylessplantingandalowerharvestrate(fig.5.18).TheresultsforCornerstonesEandFthereforebrackettheage-classresultsforallCornerstones.ForCornerstoneF,theareaofearly-ageplantedpinedeclinesovertime(incontrasttoincreasessimulatedunderCornerstoneE),andtheageclassdistributionapproachesastasis.

CornerstoneFalsoresultsinlessdramaticchangesinareaofnaturalpinewhencomparedtoCornerstoneE,withmorestabilityintheearly-ageclass,increasesintheold-ageclass,anda33-percentreductionindeclinesofthemid-agedclass.Thispatternismirroredintheoak-pineageclasses.Forhardwoodforesttypes,however,thereislittledifferencebetweenCornerstonesEandF.Thisindicatesthat

managementchangesstronglyinfluencetheagestructuresofthesoftwoodforesttypesbuthavelittleinfluenceontheagestructuresofhardwoodforesttypes.

DiScuSSioN AND coNcluSioNS

Anumberofforcesofchangewillaffectthedevelopmentofforestsoverthenext50years.TheU.S.ForestAssessmentSystem,whichaccountsforlandusechanges,climatechange,andforestmanagement,isusedheretoforecastforestconditionsforsixCornerstoneFutures.EachCornerstonedescribesthefutureintermsofhumanpopulation,personalincome,climate,andthemarketsforproductsfromrurallanduses.AcrossalloftheseCornerstones,totalforestareadeclinesandchangesamongbroadforestmanagementtypesaresubstantial.Amongthefiveforestmanagementtypes,onlyplantedpineisexpectedtoincreaseinareafrom2010to2060.In2010,plantedpinecomprised19percentofsouthernforests.By2060plantedpineisforecastedtocomprisesomewherebetween24and36percentofforestarea.Themidpointofthisrangeofgrowth(20-72percent)isconsistentwitharecentstudybyZhangandPolyakov(2010)thatforecastsa40percentexpansioninplantedpineintheSouth.

Foresttypesareinfluenceddifferentiallybyurbanizationandtimbermarketdynamics.Ingeneral,hardwoodsaremorestronglyinfluencedbyurbanization,andsoftwoodsaremorestronglyinfluencedbyforestmanagement.Althoughpredictedratesofchangevary,allforecastsrevealthatlandusechangesandconversiontopineplantationswillresultinacontinuingdownwardtrendinnaturallyregeneratedpinetypes.HardwoodtypesaremoststronglyinfluencedbyurbanizationandallCornerstoneFuturesshowdeclinesinhardwoodareathatvaryindirectproportiontoratesofurbanization.

NearlyallforestsintheSouthhavebeenharvestedatleastonceandmuchoftheregion’sforestsaretheresultofreforestationandanaccumulationofbiomass.Afteralongperiodofaccumulatingbiomass,theSouth’sforestsareforecastedtoreachamaximumby2030andthentoeitherleveloffordecline.

Southernforestsalsodefinealargepoolofterrestrialcarbonamountingto12.3billiontons.Mirroringchangesingrowingstockvolumessomewhat,thispoolofcarbonisforecastedtoreachapeakfrom2020to2030,andthendeclineovertime.Urbanizationpatternsarethedominantdeterminatesofthesizeofthefutureforestcarbonpool,althoughstrongerforestproductmarketscanamelioratecarbonlosses.

Forestforecastsaddresschangeinclimatevariablesbyassociatingforecasted,multipleyearaveragesoftemperatures,precipitation,andpotentialevapotranspiration


withhistoricalconditions.Thepotentialeffectsofotherchanges,mostnotablyCO2enrichmentdonotentertheanalysis.ControlledexperimentsshowincreasedproductivitywithCO2fertilizationbutalsohighlighttheimportantinteractionwithnitrogen,precipitation,andotherclimateandsitevariablesindeterminingresponse(McCarthyandothers2011).Thesetypesofimpactsonproductivityarerelativelysubtlecomparedtothevariabilityoffieldinventorymeasurementsandcouldnotbefactoredintotheforecasts.Thepotentialeffectsofatmosphericcarbononforestbiomassataregionalscaleremainsanimportantuncertainty.

TheSouthproducesthemajorityoftimberproductsintheUnitedStates(morethan60percent)includingadiversityofbothhardwoodandsoftwoodoutputs.ForestmanagementhasincreasedharvestingthroughouttheSouthsincethe1960s,andtheoutputperunitofgrowingstockhasincreasedasmanagementhasintensified.Themostimportantfactorinchangingtheproductivityofsouthernforestsistheexpansionintheamountofplantedpineforests.Becauseofincreasesintimbersupplyfrom1990to2010,removalsofforestbiomass(growingstock)areforecastedtoincreaseforallCornerstones,eventhosethatprojectdecreasingprices.Removalsofsoftwoodpulpwoodareresponsivetofuturesforforestplantingandproductprices.Underahighpricefuture,softwoodpulpwoodoutputwouldincreaseby56percent,roughlyequaltotheexpansioninoutputobservedbetween1950and2000.TheseprojectionsofremovalsarebasedonthepriceassumptionsoftheCornerstoneFuturesandnotonforecastsofdemand.TimberharvestforecastsundervariousmarketconditionslinkedtotheCornerstonesarediscussedinchapters9and10.

Thecombinationoflandusechange,managementintensities,andclimateresultinanumberofchangesinthecompositionandstructureoftheregion’sforests.Theforesttypecompositionofthebroadforestmanagementgroupsareforecastedtochangeandtheagestructureoftheseforestsarealsoaltered.Althoughtheoveralllossofuplandhardwoodacreageisforecastedtobeintherangeof8to14percent,theoak-hickoryforesttyperemainsessentiallyconstant.Theyellow-poplarforesttypeisforecastedtodeclinethemost,withthehighestlossesforecastedforthePiedmont.Theageandspeciesstructureofsoftwoodforesttypesismoststronglyinfluencedbyforestharvestingandmanagementtiedtotimbermarkets,whilethefuturestructureofhardwoodforestsismoststronglyaffectedbyurbanization-drivenlandusechanges(increasedpopulationgrowthandincome).Reductionsofnaturallyregeneratedpineforestsarenotequallydistributedamongageclasses:mid-ageandearly-ageforestsdeclinebutold-ageforestsremainrelativelyconstant.Forhardwoods,theagedistributionofbothuplandandlowlandhardwoodtypesshift,withlessoftheseforesttypesclassifiedasearlyageandmoreclassifiedasolderage.

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Documents

Chapter 5. Forecasts of Forest conditions · chAPTeR 5. Forecasts of Forest Conditions Robert Huggett, David N. Wear, Ruhong Li, John Coulston, and Shan Liu1 key FiNDiNGS • Among