Wildland Fire Occurrence and Emissions in the … Fire Occurrence and Emissions in the Eastern...

Wildland Fire Occurrence and Emissions in the Eastern United States From 2001 Through 2050

By Todd Hawbaker and Zhiliang Zhu

Professional Paper 1804

U.S. Department of the InteriorU.S. Geological Survey

Chapter 4 ofBaseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Eastern United StatesEdited by Zhiliang Zhu and Bradley C. Reed

U.S. Department of the InteriorSALLY JEWELL, Secretary

U.S. Geological SurveySuzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2014

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprod/.

To order this and other USGS information products, visit http://store.usgs.gov/.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:Hawbaker, Todd, and Zhu, Zhiliang, 2014, Wildland fire occurrence and emissions in the eastern United States from 2001 through 2050, chap. 4 of Zhu, Zhiliang, and Reed, B.C., eds., Baseline and projected future carbon storage and greenhouse gas fluxes in ecosystems of the eastern United States: U.S. Geological Survey Professional Paper 1804, p. 55–79, http://dx.doi.org/10.3133/pp1804.

ISSN 1044-9612 (print) ISSN 2330-7102 (online) ISBN 978-1-4113-3794-7

http://www.usgs.gov

http://www.usgs.gov/pubprod

http://store.usgs.gov

iii

Contents

4.1. Highlights ..............................................................................................................................................554.2. Introduction ..........................................................................................................................................554.3. Methods and Data ...............................................................................................................................57

4.3.1. MTBS Wildland Fire Data .......................................................................................................574.3.2. Fuels and Topography.............................................................................................................574.3.3. Weather and Climate Data .....................................................................................................574.3.4. Baseline Wildland Fire Occurrence and Emissions ..........................................................594.3.5. Projected Future Wildland Fire Occurrence and Emissions ............................................59

4.3.5.1. Ignitions .........................................................................................................................594.3.5.2. Spread ...........................................................................................................................604.3.5.3. Emissions ......................................................................................................................604.3.5.4. Calibration .....................................................................................................................604.3.5.5. Simulations of Future Fires ........................................................................................60

4.3.6. Limitations and Uncertainties ................................................................................................604.4. Results ...................................................................................................................................................62

4.4.1. Baseline Wildland Fires and Emissions ...............................................................................624.4.2. Climate-Change Trends in the Eastern United States .......................................................634.4.3. Projected Future Wildland Fires and Emissions .................................................................664.4.4. Summary of Wildland Fire Occurrence and Emissions of Carbon Fluxes ......................68

Figures 4 – 1. Graphs showing summaries of projected wildland fire ignitions, burned area,

and emissions for the Eastern United States by decade from 2001 through 2050 ...........58 4 –2. Graphs showing the annual number of wildland fires, area burned, and emissions

for the baseline (2001–2008) period of the carbon flux and storage assessment of the Eastern United States .....................................................................................................62

4 –3. Graphs showing the annual number of wildland fires, area burned, and emissions for the baseline (2001–2008) period for the A, Mixed Wood Shield and Mixed Wood Plains, B, Southeastern USA Plains, C, Ozark, Ouachita-Appalachian Forests, and D, Mississippi Alluvial and Southeast USA Coastal Plains ecoregions in the Eastern United States ...............................................................................................................................64

4 –4. Maps showing the projected changes in mean daily temperature and total precipitation by season, calculated using the difference in mean values from 2031 through 2060 and from 1991 through 2021 ............................................................65

4 – 5. Graphs showing summaries of projected wildland fire ignitions, burned area, and emissions for the A, Mixed Wood Shield and Mixed Wood Plains, B, Southeastern USA Plains, C, Ozark, Ouachita-Appalachian Forests, and D, Mississippi Alluvial and Southeast USA Coastal Plains ecoregions by decade from 2001 through 2050 ..............67

iv

Tables 4–1. Summary statistics for the number of wildland fires, area burned, and emissions ........63 4–2. Relative projected changes in the 50th and 95th percentiles for wildfire ignitions,

area burned, and emissions between 2001–2010 and 2041–2050 .......................................68

Chapter 4. Wildland Fire Occurrence and Emissions in the Eastern United States From 2001 Through 2050

By Todd Hawbaker and Zhiliang Zhu

4.1. Highlights

• Duringthebaselineperiodofthewildlandfirepartoftheassessment(2001through2008),themedianofareaburnedbywildlandfireswas1,355squarekilometersperyear(km2/yr),andthe95thpercentilewas4,092km2/yr.

• Duringthebaselineperiodofthewildlandfirepartoftheassessment,themedianofemissionsfromwildlandfireswas5.2teragramsofcarbondioxideequivalentperyear(TgCO2-eq/yr;1.4TgC/yr),andthe95thpercentilewas17.3TgCO2-eq/yr(4.7TgC/yr).

• Duringthebaselineperiodofthewildlandfirepartoftheassessment,themedianofwildfireemissionsintheEasternUnitedStateswasequivalentto0.51percentoftheaverageNEP(279TgC/yr;chap.7),andthe95thpercentilewas1.59percentoftheaverageNEP.

• Duringthebaselineperiodofthewildlandfireassessment,themedianofwildfireemissionsintheEasternUnitedStateswasequivalentto0.09percentoffossilfuelemissionsfortheUnitedStates,andthe95thpercentilewas0.31percentoffossilfuelemissionsfortheUnitedStates.

• Fortheprojectedperiod(2009through2050),wildlandfireoccurrenceandgreenhouse-gasemissionsincreasedintheEasternUnitedStatesunderalloftheclimate-changescenariosconsideredinthisassessment.

• Fortheprojectedperiod,therewassubstantialvariabilityinthedirectionandmagnitudeofchangeamongecoregions,andnotallecoregionsexpe-riencedincreasesinwildlandfireoccurrenceandemissionsunderallclimate-changescenarios.

• Theprojectedmedianamountofareaburnedannuallyfrom2041through2050wasasmuchas51percentgreaterthanthemedianamountofareaburnedannuallyduringthebaselineyears.Themedianannualemissionswereprojectedtoincreasebyasmuchas41percentfromthebaselinemedianannualemissions.

• Extremefireyears(yearsinwhichtheamountofareaburnedarerankedthe95thpercentile)areprojectedtobecomemoreextreme.Theannualareaburnedinextremefireyearswasprojectedtoincreaseby43to122percentfromtheearlyconditions,andthe95thpercentileofannualwildlandfireemissionswasprojectedtoincreaseby41to111percentfromthebaseline95thpercentileestimate.

• PrescribedfireisanimportantlandmanagementtoolintheEasternUnitedStates;however,thelackofaccurateandconsistentdataaboutprescribedfireslimitsunderstandingoftheircontributionstoGHGemissions.

4.2. IntroductionThemethodologyforthisassessment(Zhuandothers,

2010)explicitlyaddressedecosystemdisturbances,includinghuman-andnatural-causedwildlandfires,asrequiredbytheEISA(U.S.Congress,2007).Estimatesforthebaselineandprojectedbiomasscombustionemissionsfromwildlandfiresandeffectsinlong-termcarbonbalancewerecomponentsoftheassessment(fig.1–2).Biomasscombustionemissionresultsarepresentedinthischapter.Thebaselineburnedareasandtheprojectedfuturepotentialburnedareasforwildlandfiresandtheirseverity,describedinthischapter,wereusedasinputintotheassessmentofthelong-termeffectsofecosystemcarbonbalances(chap.5).

WildlandfiresareacriticalcomponentoftheglobalcarboncyclebecausetheyproduceanimmediatereleaseofGHGs—CO,CO2,andCH4—whenbiomassisconsumedthroughcombustion(SeilerandCrutzen,1980).However,previousestimatesofemissionsfromwildlandfiresintheUnitedStateswerehighlyvariable,andafterconvertingthereportedemissionstocarbon-dioxideequivalents,theywereasfollows:

• from15TgCO2-eq/yrin2001to73TgCO2-eq/yrin2008(Giglioandothers,2010;vanderWerfandothers,2010;OakRidgeNationalLaboratory,2012),

• from29TgCO2-eq/yrin2001to199TgCO2-eq/yrin2008(Frenchandothers,2011;MichiganTechResearchInstitute,2012),and

56 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Eastern United States

• from157TgCO2-eq/yrin2002to283TgCO2-eq/yrin2006(WiedinmeyerandNeff,2007).

Whencomparedwiththe2010estimateof1,075TgCO2-eq/yrofnetcarbonfluxfromecosystemsinthecontinentalUnitedStatesreportedbytheEPA(U.S.EnvironmentalProtectionAgency,2012),theannualemis-sionsfromwildlandfireswereequivalentto1to26percentoftheecosystem’stotalannualnetcarbonflux.Incontrast,thecombustionoffossilfuelsproduced5,642TgCO2/yrfrom2001to2008(U.S.EnvironmentalProtectionAgency,2012),andemissionsincreasedatarateof1percentperyear(Pacalaandothers,2007).Basedontheserates,theannualemissionsfromwildlandfireswereequivalentto0.3to5.1percentoftheemissionsfromfossil-fuelconsumption.

Thedifferencesamongthevariabilityandqualityoftheseresults,thespatialandtemporalresolutionofthedata,andassumptionsaboutvariationsincombustionefficiencyweretheprimarysourcesofuncertaintiesinwildlandfireemissionsestimates(Larkinandothers,2009;Frenchandothers,2011).Theassumptionsabouttheproportionofabovegroundbiomassconsumedbywildlandfire,especiallyabovegroundwoodybiomassinforests,canhaveasubstantialinfluenceonemissionestimates(Campbellandothers,2007;Meigsandothers,2009).Themethodsusedtocalculateemissionsreliedonestimatesoftheareathatwasburned,fuelloads(volumeofliveanddeadbiomassavailableforburning),combustionefficiency,andemissionfactors(SeilerandCrutzen,1980;Albiniandothers,1995;WiedinmeyerandNeff,2007;Ottmarandothers,2008).Forexample,theGlobalFireEmissionsDatabase(GFED;Giglioandothers,2010;vanderWerfandothers,2010)estimatesbiomassconsumptionandemissionatfirelocations(includingagriculturalfires)detectedbytheNationalAerospaceandSpaceAdministration’s(NASA)moderateresolutionimagingspectroradiometer(MODIS;Royandothers,2002;Giglioandothers,2003)basedonland-covertypes,combustioncompleteness,soilmoisture,andland-cover-specificemissionfactors.TheGFEDalsoincorporateschangesinfuelloadsusingtheCarnegieAmesStanfordapproachtocharacterizebiomassproduction(Potterandothers,1993,2012).WiedinmyerandNeff(2007)alsousedactivewildlandfireobservationsfromMODISsatellitesensors(Giglioandothers,2003),butcalculatedtheemissionsbasedonstaticland-covertypes,percentageoflandcover,andbiomassat1-kilometer(km)resolution.Frenchandothers(2011)usedtheForestServiceConsumemodel(Ottmarandothers,2008),whichcalculatedfuelconsump-tionandemissionusingfuelloadsderivedfromtheForestServiceFuelCharacteristicClassificationSystem(FCCS;Ottmarandothers,2007)andfuelmoisturesderivedfromweather-stationdata.

Wildlandfiresalsohavelong-termeffectsonecosystemcarbonbalancebyinfluencingtherateofcarbonseques-trationaftercombustion,throughthedecompositionofdeadvegetation(whichcanprovidenutrientstohelpestablishnewvegetation),andbyreducingtherateofphotosynthesis

perunitarea.Becauseofthoseeffects,yearstodecadescanpassbeforecarbonstocksreturntoconditionsbeforethefire(Turnerandothers,1998;Clearyandothers,2010;HurteauandBrooks,2011;Kashianandothers,2012).Iffireregimesarestableandassumingnootherlandmanagement,thelong-termeffectsofwildlandfiresonecosystemcarbonbalancearetypicallynegligiblebecausecarbonsequestrationthroughgrowthofnewvegetationandcarbonlossthroughwildlandfireemissionscancelouteachotheroverlongperiods(Balshiandothers,2009a,b;Flanniganandothers,2009).However,ifafireregimechanges,thenthevulnerabilityforcarbonstorageishighbecausetheamountofcarbonstoredintheecosystemcanbealteredorlostthroughemissions.

Substantialevidenceisavailabletodocumentthatfireregimeshavenotbeenstaticinmoderntimes.Forexample,thefrequencyofwildlandfireshasbeengreatlyreducedsincesettlementoftheUnitedStatesbeganmainlyduetoland-usechangesandthesuccessoffiresuppressioninthepastcentury(Clelandandothers,2004).IntheWesternUnitedStates,thefrequencyofwildlandfireshasbeenincreasingsincethe1990sbecauseofclimatechangesleadingtoanincreasinglyearliersnowmelt(Westerlingandothers,2006).WildlandfiresandemissionstocarboncyclingarelikelytobelessimportantintheEasternUnitedStatesthanintheWesternUnitedStates,butlimitedresearchhasbeenconductedquantifyingrelationshipsbetweenwildfireoccurrenceandclimatechangeintheEasternUnitedStates.Iftheclimateshiftstowarmeranddriercondi-tions,thenincreasesinfirefrequencyandemissionsarelikely.Therefore,anycomprehensiveassessmentofcarbonstorageandfluxesinecosystemsthroughtimemustaccountforthepotentialchangesinwildlandfireoccurrenceandemissions.

Wildlandfireregimesareafunctionoftheinteractionsbetweenvegetation,landuse,andultimately,theclimate(SwetnamandBetancourt,1990;Gedalofandothers,2005;Westerlingandothers,2006;Falkandothers,2007).Achangingclimatemayresultinchangesinwildlandfireregimes,includingtheiroccurrenceandseverity.Hessl(2011)outlinedtheprimarypathwaysthroughwhichclimatechangemayalterwildlandfireregimes,including(1)alteredfuelconditions,suchasachangeinfuelmoisture;(2)alteredfuelloads;and(3)changesinignitionpatterns.TheeffectsofclimatechangeonwildlandfiresintheEasternUnitedStatesareexpectedtobesignificantandresultinchangesinweatherpatternsthatwouldalter(1)ignitionpatterns,(2)wildlandfirebehavior,and(3)toalesserextent,thedistributionofvegetation.Nosinglestudy,however,hasaddressedallthreetypesofchangessimultaneouslyatthescalerequiredbythisassessment(Flanniganandothers,2009).

Previousstudiesprovidedanestimateoftheeffectsofwildlandfiresoncarbonbalanceatanationalscalebutlackedtheregionaldetailrequiredbythisassessment.Furthermore,therewerefewprojectionsoffuturepotentialwildlandfireemissionsthatwereconsistentwiththeexistingbaselineemissionestimates.Therefore,asetofbaselineemissionsandprojectedfuturepotentialemissionswasdevelopedtoensureconsistencythroughoutthisandotherregionalassessments.

Chapter 4 57

Theprimaryquestionsaddressedinthischapterinclude:(1)whatwerethepatternsofwildlandfireoccurrenceandemissionsintheEasternUnitedStates?(2)whatmaybethepotentialchangesinwildlandfireoccurrenceandemis-sionsfortheEasternUnitedStatesunderclimatechange?(3)howdidrecentwildlandfireoccurrenceandemissionsvarytemporallyandspatiallyamongtheecoregionsoftheEasternUnitedStates?and(4)whichecoregionsoftheEasternUnitedStateshavethegreatestpotentialforchangesinfire-occurrenceandemissions?

4.3. Methods and DataThewildfiremodelingandestimationstudyforthe

carbonsequestrationassessmentofecosystemsoftheEasternUnitedStateshadtwotasks:(1)calculatingthebaselinequantitiesforwildlandfireoccurrenceandemissionsand(2)simulatingfuture(2009 –2050)projectionsofwildlandfireoccurrenceandemissionsunderclimate-changescenarios.Themethodsusedforthisstudyarethesamemethods(HawbakerandZhu,2012)usedintheUSGSwesternecosystemcarbonsequestrationassessment(ZhuandReed,2012).Somespecifictechnicalprocessesarecommontobothpartsofthestudy;othermethodsarespecificforasingletask.Thebaselineestimatesforthenumberofwildlandfires,theareaburned,andemissionswerederivedfromtheWildlandFireLeadershipCouncil’sMonitoringTrendsinBurnSeverity(MTBS)database(Eidenshinkandothers,2007)andtheForestService’sFirstOrderFireEffectsModel(FOFEM;Reinhardtandothers,1997)forthemajorGHGsCO2,CO,andCH4.ThismethodwasappliedtoeachwildlandfireintheregionthatwasintheMTBSdatabasetoproduceestimatesofCO2,CO,andCH4emissions(convertedtoCO2equivalents).

Thewildlandfiremodelingapproachusedforthefutureprojectionsinthisassessmentincorporatedthreeprimarycomponents:wildfireignitions,spread,andeffects.Theparametersfortheignitionandspreadcomponentswereselectedthroughacalibrationprocessusingthebaselineobserveddata,whichwereusedtosimulatefuturepotentialwildfiresandburnedareasandthenFOFEMwasusedtoestimateemissionsforthesimulatedburnedareas.ResultsofthebaselineandfutureprojectionsofwildlandfireswereaggregatedtoproduceestimatesofemissionsfortheEasternUnitedStatesasawholeandforeachlevelIIecoregionwithinit(fig.1–1;asdescribedindetailinchapter2ofthisreport).ThedatasetsandmethodsusedbythevariouswildlandfiremodelingcomponentsaredescribedbrieflyinHawbakerandZhu(2012)andinmoredetailinthefollowingsections.

4.3.1. MTBS Wildland Fire DataThelocationsofwildlandfiresweretakenfromMTBS

data(Eidenshinkandothers,2007)andwereusedforbaselineobservationsandtocalibratetheignitionandspreadcompo-nentsofthewildlandfiremodelingsystem.TheMTBSdata

describedfiresthatoccurredfrom1984to2008andcoveredareasthatwerelargerthan404hectares(ha;1,000acres)intheWesternUnitedStatesand202ha(500acres)intheEasternUnitedStates.TheMTBSdatadidnotincludesmallfiresbutcapturedthemajorityoftheareaburnedbecausetheyincludedthelargestfires,whichcontributedmosttototalareaburned(Straussandothers,1989;Stocksandothers,2002).SomeprescribedfiresareincludedintheMTBSdatabase;however,theywereexcludedfromthisassessmentbecausethecompletenessofprescribedfirecoverageintheMTBSdatabasewasuncertainandlikelyunderestimatedactualprescribedfireuseintheEasternUnitedStates.EachwildlandfiredetailedintheMTBSdatabasewasidentifiedinStateorFederalfirerecords,anditsburnscarandseverityweremanuallymappedusingLandsatimageryfrombeforeandafterthefire.BecauseoftheMTBSmethodology,therewasahighdegreeofconfidenceinthespatialandtemporalaccuracyofthewildlandfiredata,whereasotherwildlandfiredatabaseshadknownproblems,includingduplicaterecordsanderroneouslocations(Brownandothers,2002),whichwouldrequirelaboriouserrorcheckingbeforeuse.

4.3.2. Fuels and Topography

Themethodologyforthebaselineandprojectedwildfiresreliedonvegetation,fuels,andtopographydatafromtheLandscapeFireandResourceManagementPlanningTools(LANDFIRE)Program(Rollins,2009)oftheU.S.DepartmentoftheInterior(DOI)andtheU.S.DepartmentofAgriculture(USDA).Thesedataincludedinformationaboutexistingvegetation,fire-behaviorfuelmodels,andtreecanopyfuels(cover,height,baseheight,andbulkdensity),aswellastheelevation,slope,andaspectoftheterrain.Tocalculateemissionsfromwildlandfires,theFuel-LoadingModel(FLM;Lutesandothers,2009)datalayeroftheLANDFIREprogramwasused.Vegetationandfuelswereheldstaticthroughoutthesimulationsforfuturewildfiresandwerenotalteredbysimu-lateddisturbancesandothertypesofLULCchange.Allrasterdatawereaggregatedto250-meter(m)resolutioninordertoimprovetheprocessingefficiencyusinganearest-neighborrule(Lillesandandothers,2007).Thenearest-neighboraggregationwasdesirablebecauseitpreservedtheproportionofvegetative-covertypeswithinthestudyarea,whereasotheraggregationmethodsweremorelikelytoresultincommonvegetative-covertypesbeingoverrepresentedanduncommonvegetative-covertypesbeingunderrepresented.

4.3.3. Weather and Climate Data

Theassessmentmethodologyrequireddailyweatherdata,includingtemperature,precipitation,relativehumidity,andwindspeeds,forthebaselineandfutureperiods.Forthebaselineperiod,griddeddailyweatherdataforthecontermi-nousUnitedStateswith0.125-degree(°)spatialresolution(approximately12km)wereused(Maurerandothers,2002).


Thesedatawereinterpolatedfromweatherstationsandincludedtheminimumandmaximumdailytemperatureanddailyprecipitationfrom1950to2010.Thedataonafternoonwindspeedanddirectionfromthe0.333°(approximately32km)NorthAmericanregionalreanalysis(Mesingerandothers,2006)werejoinedtothe0.125°dailytemperatureandprecipitationdata.

Inordertosimulatetheeffectsoftheclimate-changescenariosonwildlandfireoccurrenceandemissions,downscaledmonthlyclimatedataprovidedbytheWorldClimateResearchProgramme(WCRP)CoupledModelIntercomparisonProjectphase3(CMIP3)multimodeldatasetwereused.TheCMIP3datawerecorrectedforbiasandspatiallydownscaledtomatchthe0.125°-resolutionbaselineweatherdata(Maurerandothers,2007).Forthisanalysis,thedownscaleddatafromtheClimateResearchBranchofEnvironmentCanada’sCanadianCentreforClimateModellingandAnalysis(CCCma)thirdgenerationcoupledglobalclimatemodel(CGCM3.1;FlatoandBoer,2001),theAustralianBureauofMeteorology’sCommonwealthScientificandIndustrialResearchOrganisationMark3.0(CSIROMk3.0;Gordonandothers,2000)climatemodel,andtheModelforInterdisciplinaryResearchonClimateversion3.2mediumresolution(MIROC3.2-medres;HasumiandEmori,2004)foreachofclimate-changescenariosA1B,A2,andB1(chap.2)weredownloadedfromthebiascorrectedanddownscaledWCRPCMIP3climateprojectionsarchive(Maurerandothers,2007;Meehlandothers,2007).TheGCMsandscenarioswereselectedonthebasisoftheirabilitytocapturepastclimatepatterns(Balshiandothers,2009a,b).Additionally,therangeofvariabilityamongtheprojectionsgenerallybracketedtheextremesoftemperatureandprecipitationprojectionsfortheconterminousUnitedStates(Gonzalezandothers,2010).Seasonalsummariesoftheclimateprojectionsweregeneratedforthe1991through2020and2031through2060periods.These30-yearperiods

areafterthebaselineperiod(2001–2008)andthelastdecadeoftheprojections(2041–2050)usedinthisassessment.Differencesintemperatureandprecipitationamongthe1991through2020and2031through2060periodsforthedifferentclimate-changescenarioandGCMsusedinthisassessmentareshowninfigure4–1.

Thedownscaledclimatedataonlyprovidedmonthlytemperatureandprecipitationvalues,soatemporaldisaggregationalgorithm(Woodandothers,2002)wasimplementedtoproducethedailyvaluesnecessaryforwildlandfiresimulations.Thisalgorithmrandomlyrearrangedyear-longsequencesofthebaselineweatherdataforeachfutureyearandthenadjustedthedisaggregateddailyvaluesoftemperatureandprecipitationsothatthemonthlymeansmatchedthevaluesprovidedbythemonthlyclimateforecasts.Usingthismethodology,threereplicateweathersequencesweregeneratedforeachGCMandclimate-changescenariocombinationforatotalof27simulationruns.ThenumberofGCMsusedandreplicaterunswasultimatelylimitedbycomputingpowerandprocessingtimes.

Forthebaselineandfutureclimatechangescenarios,additionalprocessingstepsweretakentoproducetheliveanddeadfuelmoisturevariablesrequiredforsimulatingwildlandfirespreadandbehavior.First,theUniversityofMontanamountainclimatesimulator(MT–CLIM)algorithms(GlassyandRunning,1994)wereusedtocalculaterelativehumiditybasedonminimumandafternoondailytemperatures(Kimballandothers,1997).Oncehumiditywasestimated,theNationalFireDangerRatingSystem(NFDRS)algorithmswereusedtoestimatedailyvaluesforliveanddeadfuelmoistures,aswellaswildlandfirebehaviorindices,suchasanenergyreleasecomponent(ERC;Deemingandothers,1977;Bradshawandothers,1983;Burgan,1988).TheNFDRSalgorithmsrequiredinformationaboutthebeginningofspring(green,up)andfall(brown,down)toestimatelivefuelmoistures.Toaccountforpotentialshiftsinphenology,atechniquewasimplementedthatdeterminedthedatesofseasonal

0

400

600

800

200

1,000

1,200

0

10,000

15,000

5,000

0

20

10

40

30

50

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1

Figure 4–4.

Number of wildland fires per year Area burned, insquare kilometers per year

Emissions, in carbon dioxideequivalent per year

5th percentile

Minimum

95th percentile

50th percentile (median)

Maximum

EXPLANATION

Figure 4 – 1. Graphs showing summaries of projected wildland fire ignitions, burned area, and emissions for the Eastern United States by decade from 2001 through 2050. The x-axis labels indicate the last year in the decade; for example, 2010 on the graph corresponds to the decade from 2001 through 2010. Scenarios A1B, A2, and B1 are from Nakićenović and others (2000).

Chapter 4 59

changesbasedongreen-upandbrown-downdatesusinganindexthatincorporatedthedailyphotoperiod,minimumtemperature,andthevapor-pressuredeficit(Jollyandothers,2005).

4.3.4. Baseline Wildland Fire Occurrence and Emissions

BaselinewildlandfireemissionswerecalculatedforeachburnedpixelintheMTBSdatabaseusingFOFEM,whichusedfuelloadsalongwithfuelmoisturestoestimatetheamountofforestlitteranddowneddeadwoodthatwasconsumed(AlbiniandReinhardt,1995,1997;Albiniandothers,1995).Theconsumptionofduff(decayingforestlitter),trees,plants,andshrubswasestimatedasafunctionoftheregion,season,fuelmoistures,andfuelloads.CanopyfuelconsumptionwasestimatedasafunctionoftheburnseverityprovidedbytheMTBSdata.TheemissionsofCO,CO2,andCH4werethencalculatedbasedontheamountoffuelconsumed,theorganic-mattercontentofthefuel,andhowefficientlyitburned.TherequiredinputdataforFOFEMincludedfuelloads,burnseverity,anddeadandlivefuelmoistures.Tosimplifythereportingofresults,theemissionestimatesweresummarizedforallcarbon-containingconstituentstoCO2equivalentsusingthefollowingequation:

CO2-eq=CO2+(2.33×CO)+(21×CH4). (4 –1)

Fuel-loaddataprovidedanestimateoftheamountofbiomassthatwasavailableforconsumptionandwerederivedfromtheLANDFIREProject’sFLMdatalayer(Lutesandothers,2009).Thesefuel-loaddatawerecategorizedby1-,10-,100-,and1,000-hourfuelclassesfordead,decaying(duffandforestlitter),andlive(grass,shrubs,andtreecanopy)biomass.IntheFOFEM,theamountoftreecanopythatwasconsumedwasadirectfunctionofburn-severityvaluesfromtheMTBSdata.Theamountsofcanopyfoliageconsumedinthehigh,moderate,andlowburn-severitycategorieswereassumedtobe100percent,60percent,and20percent,respectively.Similarly,theconsumptionofthecanopy’sbranchwoodinthehigh,moderate,andlowburn-severitycategorieswassetat50percent,30percent,and10percent,respectively.Thesevalueswerebasedonpreviouslypublishedestimates(Spracklenandothers,2009;Zhuandothers,2010)andonacomparisonofFOFEMemissionswithpreviouslypublishedresultsforselectedwildlandfires.Theemissionswerecalculatedforwildlandfiresbetween2001and2008.Wildlandfiresbefore2001wereexcludedbecausetheLANDFIREfuelsdatawerederivedfromLandsatimageryfromabout2001.

Aftercalculatingemissions,summariesofthewildlandfiredataforeachlevelIIecoregionandfortheentiretyoftheEasternUnitedStatesweregeneratedforthebaselineperiod.Thesesummariesincludetheminimum,mean,median,95thpercentile,andmaximumvaluesfornumberoffiresperyear,areaburnedperyear,andemissionsperyear.Themedianand

95thpercentilesummarystatisticswereassumedtorepresenttypicalandextremefireyears,respectively.

4.3.5. Projected Future Wildland Fire Occurrence and Emissions

Paststudiesgenerallysuggestthattheareaaffectedbylargewildlandfiresandemissionsfromthefireswasafunc-tionofignitionpatternsandfirebehavior,primarilyspread;ignitionpatternsandfirebehaviorwerelargelyinfluencedbyweatherconditions,fuels,andtopography(Caryandothers,2009)andinsomeregions,ignitionswereinfluencedbyhumanactivity(Cardilleandothers,2001;Syphardandothers,2007).Projectingthepotentialchangesinwildfirepatterns,therefore,requiredanunderstandingandaccuratecharacterizationofthedriversthatcreatedtheobservedpatternsofignitions,spread,andemissions(Keaneandothers,2003;Flanniganandothers,2009;Hessl,2011).Accordingly,thewildlandfiremodelingapproachusedforthisassessmentincorporatedthreeprimarycomponents:wildfireignitions,spread,andeffects.Theparametersfortheignitionandspreadcomponentswereselectedthroughacalibrationprocessusingthebaselineobserveddata,whichwereusedtosimulatefuturepotentialwildfires.

4.3.5.1. IgnitionsGenerallinearmodels(GLMs)withabinaryresponse

wereconstructedtopredictdailyignitionprobabilitieswithineach0.125°weathergridcell.Fromthedatadescribedabove,asuiteofpotentialpredictorvariableswascompiledthatincludeddailyweatherstatistics(minimumandmaximumtemperatureandERC),monthlyweathersummaries(temperatureandprecipitation),seasonalweathersummaries(temperatureandprecipitation),andmonthlyandseasonalregionalsummariesoftemperatureandprecipitation.Alsoincludedwithinthe0.125°weathergridcellsaspotentialpredictorsintheGLMmodelingweretheproportionsoflandareaclassifiedaspublicorurbanandexistingvegetationtypegroupsfromtheLANDFIREdatabase.

Mostobservations(gridcellswithdailyweatherdata)hadnodataonignitions;therefore,asubsamplewasselectedusingacase-controlsamplingdesign.Anyobservationwithprecipitationgreaterthan0.25centimeters(cm)wasremoved;thiswasdonetoensurethatignitionprobabilitieswerezeroondayswithsubstantialprecipitationthatwouldlimitfirespread.Allobservationswithignitiondatawereretainedalongwitharandomlyselectedsetofobservationswithoutignitiondata.Thenumberofobservationswithoutignitiondatawas10timesthenumberofobservationswithignitiondata.Thechoiceofdesignwassomewhatarbitrary,butjustifiedbecausethepredictiveperformanceofmodelsusingcase-controlsamplingdesignshasbeenshowntoincreasewiththeratioofcasestocontrols(Hastieandothers,2009).TheinterceptoftheGLMwasadjustedusingequation4–2toaccountforunequalproportionsofcases(ignitions)andcontrols


(non-ignitions)inthesamplecomparedwiththepopulation(Preislerandothers,2004;Hastieandothers,2009).

golgol elpmaselpmas

noitalupopnoitalupop

non ignitions ignitionsnon ignitions ignitions

− −−

(4–2)

TobuildtheGLMs,aninitialsetofpredictorvariableswasselectedusingforwardstepwiseregression,includingonlyvariableswithp-valueslessthanorequalto0.05andlimitingthenumberofpredictorstoone-tenththenumberofwildlandfireobservations.EachGLMwasthenevaluatedandmodi-fiedasneededtoensurethattheselectedpredictorvariablesaccuratelydescribedweatherandclimateconditionsknowntoaffectwildlandfireoccurrenceinagivenecoregion.TheoverallperformanceofthefinalGLMwasjudgedusingtheareaunderthecurve(AUC)ofareceiver-operatorcharacter-isticplot(HanleyandMcNeil,1982).TheAUCmeasuredtheprobabilityofcorrectlyclassifyingarandompairoffireandnonfireobservations;anAUCvalueof0.5indicatedthatthemodelpredictionswereequivalenttoarandomguess,andanAUCvalueof1.0indicatedperfectpredictions.AUCvaluesgreaterthan0.8weregenerallyconsideredtobegood.

4.3.5.2. SpreadDuringthesimulations,theminimumtraveltime(MTT)

algorithm(Finney,2002)wasusedtosimulatethespreadofwildlandfiresafterignition.TheMTTalgorithmhasbeenusedextensivelyforlocal-andnational-scalesimulationsofburnprobability(Calkinandothers,2011;Finneyandothers,2011).Inadditiontoanignitionlocation,theMTTalgorithmreliedonfuels(surfaceandcanopy),topography(elevation,slope,andaspect),weather(windspeedanddirection),andliveanddeadfuelmoisturedata.TheMTTalgorithmalsorequiredaspecifiednumberofdaysandminutesperdaythatawildlandfirecanspread.TheoutputsproducedbytheMTTalgorithmincludedthearrivaltime(durationofthewildlandfiresinceignition)ofeverypixelrepresentingburnedarea,aswellaswildlandfire-behaviormetrics,suchasfirelineintensityandcrown-fireactivity.

4.3.5.3. EmissionsTocalculateemissions,theFOFEM(Reinhardtand

others,1997;ReinhardtandKeane,2009)wasappliedtoeachpixelburnedbythesimulatedwildlandfiresusingthesameprocessingstepsthatwereusedforthebaselineemissions.

4.3.5.4. CalibrationAnumberofcalibrationsimulationswererequired

todeterminetheappropriatenumberofdaysandminutesperdaytoallowwildlandfirestospreadusingtheMTTalgorithm.Theinitialvaluesfortheminimumandmaximumnumberofdaystoallowthespreadandminutesofspread

perdaywereselectedbasedonvaluesderivedfromFederalfirerecords.Ninereplicatesimulationswererunusingtheavailableweatherdata(1984–2008).Afterthesimulationswerecomplete,atwo-sidedt-testwasusedtodetermineiftheannualaverageareaburnedduringthesimulationsdifferedsignificantlyfromtheannualaverageareaburnedbasedonobservationsfromtheMTBSdatabase.Ifthedifferencesweresignificant,thenumberofdaysoffirespreadandtheminutesofspreadperdaywerealteredandthecalibrationprocesswasrepeateduntilthep-valueofthet-testwaslessthan0.05,indicatingthatthecalibrationsimulationsreproducedthebaselinefirepatterns.

4.3.5.5. Simulations of Future FiresAftercalibration,futurepotentialwildlandfireignitions,

spread,andemissionsweregeneratedforthreereplicatesimulationsforeachoftheclimate-changescenariosandGCMs,startingin2001andendingin2050.Thereplicatesimulationswereruntohelpquantifyuncertaintybecauseofthestochasticnatureofthemodels;morereplicatesimula-tionswouldhavebeenideal,butprocessingtimeslimitedthenumberofreplicatestothree.Thesimulatedannualnumberofwildlandfires,areaburned,andemissionsweresummarizedacrosstheGCMsandreplicatesandwereshownasthemedianand95thpercentileforeachclimate-changescenarioforeachdecade,whichrepresentedtypicalandextremefireyears,respectively.Therelativechangebetween2001–2010and2041–2050werereported.Significanceofeachchangewasassessedata0.05-alpha(α)levelusingMonteCarlopermutationtestwith1,000permutations(Hesterbergandothers,2012).

4.3.6. Limitations and UncertaintiesTheresultsgeneratedforthisassessmentforbaseline

wildfireemissionsdifferedandweregenerallylowerthanestimatesofemissionsfromthepeer-reviewedliteraturefortheEasternUnitedStates.Thehighestestimatesofemis-sionsfrompeer-reviewedliteraturewerefromWiedinmyerandNeff(2007),whousedtheactivefireproductfromtheMODISsensorsfrom2002to2006andestimatedthemeanofannualemissionstobe71TgCO2-eqforAlabama,Connecticut,Delaware,Florida,Georgia,Illinois,Indiana,Kentucky,Louisiana,Maine,Maryland,Massachusetts,Michigan,Mississippi,NewHampshire,NewJersey,NewYork,NorthCarolina,Ohio,Pennsylvania,RhodeIsland,SouthCarolina,Tennessee,Vermont,Virginia,WestVirginia,andWisconsin.TheareausedinWiedinmyerandNeff(2007)isnotthesameastheareausedforthisanalysisoftheEasternUnitedStates.

Frenchandothers(2011)calculatedemissionsusingtheMTBSdataandConsumemodel(Ottmarandothers,2008)forwildlandfiresoccurringfrom2001to2008;theresultsareavailableasecoregion-levelsummaries(MichiganTechResearchInstitute,2012).WhentheresultsfromFrenchand

Chapter 4 61

others(2011)weresummarizedacrosstheEasternUnitedStates,theaverageandstandarddeviationofannualemissionswere20.5TgCO2-eqand12TgCO2-eq,respectively.Theemis-sionestimatesfromtheseanalysesweresubstantiallygreaterthantheestimatesproducedforthisassessment.Thedifferencesamongresultsarelikelyduetodifferencesinmethods,data,andtheresolutionofthedataused.WiedinmyerandNeff(2007)reliedon1-km-resolutionactivewildlandfiredatafromMODISandfueldatafromtheFCCS(U.S.DepartmentofAgriculture,ForestService,2012a),whichtypicallyhavehigherfuelloadsthentheFLMdatausedforthisassessment.Theyalsoassumedthatalltheavailablebiomasscouldpotentiallyburn,andthatisoftennotthecase,especiallyforwoodyfuels(Campbellandothers,2007;Meigsandothers,2009).Frenchandothers(2011)alsousedthe1-km-resolutionFCCSfuelsdataandaggregated1-km-resolutionMTBSdata.Thefueldataintheirreportdifferedfromthedatalayerusedinthisassessmentintermsofinformationandresolution.Themethodsusedinthisassessmentmadeuseoffuelmoistures,whicharebasedongriddeddailyweatherdata.ThemethodsusedbyFrenchandothers(2011)alsomadeuseoffuelmoistures,butrecommended10percentlevelsfor1,000-houravailabilityandduffmoistures,whichareveryfavorableconditionsforcombustion.Thefulleffectsofthedifferencesinfuelmapsandmoisturelevelsontheaccuracyoffiremodelingweredifficulttoassess,butthesecomparisonssuggestthattheresultsinthisassessmentaremoreconservativethanpreviouslypublishedestimatesofwildlandfireemissions.

TheMTBSdatausedinthisassessmentdidnotincludesmallwildlandfires,buttheystillcapturedthemajorityoftheareaburnedbecausetheyincludedthelargestwildlandfiresthatcontributedmosttotheamountofareaburned(Straussandothers,1989;Stocksandothers,2002).AcomparisonoftheMTBSdatawiththeFederalwildlandfire-occurrencedatabase(U.S.DepartmentofInterior,2012)showedthattheMTBSlistedonly3percentofallwildlandfiresbutaccountedfor88percentoftheareaburnedintheEasternUnitedStates.Therefore,theresultsofthisassessmentcapturedthegeneralpatternsandtrendsofwildlandfiresintheEasternUnitedStates,butinalllikelihood,underestimatedwildlandfireemissions.

Inthisassessment,thebaselineandprojectedestimatesofareaburnedandemissionsalsodidnotincludetheinfluenceofprescribedandagriculturalfires(forexample,burningcropresidues);however,theemissionsproducedbythosetypesoffiresweresuspectedtobelowrelativetothewildlandfireemissions(Liu,2004;vanderWerfandothers,2010).Theinfluenceofprescribedfiresonemissionswasdifficulttoassessbecausethedatacharacterizingprescribedfiresweregenerallypoorbasedoninconsistentreportingaboutthemacrossthecountry.Theexistingestimatesofemissionsfromprescribedfiressuggestedthattheyproducedonly10percentoftheemissionsfromwildlandfires(Liu,2004),inpartbecauseprescribedfiresusuallyburnunderlessextrememeteorologicalconditionsthanwildlandfires.Theinfluenceofagriculturalfireswasalsoestimatedtobeabout10percentofthewildlandfireemissionsintheGFEDdatabase.

IntheEasternUnitedStates,therelativeamountofemissionsproducedbyprescribedandagriculturalfiresislikelytobemoresubstantialthaninotherpartsoftheUnitedStates,becauseagriculturalfiresarecommonintheregion(Korontziandothers,2006;Tulbureandothers,2011).PrescribedfiresintheEasternUnitedStates,especiallythoseintheSoutheast,accountedfor70percentoftheareaburnedbyprescribedfiresnationwide,andareaburnedbyprescribedfiresinthestudyareawasmorethan2.5timestheareaburnedbywildfires(basedon2002to2008datafromtheNationalInteragencyFireCenter,2012).Unfortunately,recordsformanyprescribedfiresarenotenteredintonational-leveldatabases,soaccuratedatacharacter-izingtheindividuallocationsofeachprescribedfirearenotavailable.IntheMTBSdatabase,theareaburnedbyprescribedfireswasonly18percentofthetotalareaburnedintheEasternUnitedStates.Becauseprescribedfiresburnunderlessextrememeteorologicalconditions,severityandemissionsareexpectedtobelowerthanwildfires(Liu,2004;OutcaltandWade,2004;vanderWerfandothers,2010).However,speculatingaboutthelocationsofprescribedfires,thefuelstheyburnthough,andtheconditionsunderwhichtheyburnwouldlikelyintroduceagreateramountofuncertaintyintotheemissionestimatesprovidedinthisassessment.Theseuncertaintieswillremaindifficulttoresolveuntilbetterinformationisavailableonthetimingandlocationofprescribedfires.

InspiteoftheuncertaintiesaboutthetimingandlocationofprescribedfiresintheEasternUnitedStates,emissionestimateshavebeenincludedintheEPA’sNationalGreenhouseGasEmissionsInventory(U.S.EnvironmentalProtectionAgency,2012)andcanprovidesomeindicationoftheimpactofprescribedfiresonemissions.TheEPAmethodsforwildlandandprescribedfireemissionsfocusonforestsandapplyemissionfactorstocarbonstock-changes.TheEPAestimatesfor2005,2007,and2008forwildfireemissionsaveraged144.3TgCO2-eq/yrandforprescribedemissionsaveraged20.3TgCO2-eq/yrfortheconterminousUnitedStates.Assumingthat70percentofprescribedfiresoccurintheEasternUnitedStates(NationalInteragencyFireCenter,2012),thenaverageannualemissionsfromprescribedfireswouldbe14.2TgCO2-eq/yr,avaluesubstantiallylargerthanthemedianwildfireemissionsfromthebaselineperiodofthisassessment(5.2TgCO2-eq/yr).However,theEPA’swildfireestimatesforthecontinentalUnitedStates(144.3TgCO2-eq/yr)arealsosubstantiallylargerthanthoseproducedforthisassessment,theGreatPlainsassessment(Zhuandothers,2011),andtheWesternassessment(HawbakerandZhu,2012),whichcollectivelyhadamedianvalueof56.0TgCO2-eq/yrandamaximumvalueof101.4TgCO2-eq/yr.

Throughoutthewildlandfiresimulations,vegetationandfuelsremainedstatic,whichintroducedsomelimitationsintotheassessment.Becauseofsuccessionanddisturbances(espe-ciallyanthropogenic,suchasLULCchange),thecompositionandstructureofvegetationmaychangesubstantiallyduringthe50-yearspanusedinthisassessment(Fosterandothers,1998;Gallantandothers,2004;Rhemtullaandothers,2009).


Thesechangescouldresultinalteredsurfaceandcanopyfuelsthatinfluencewildlandfirebehaviorandemissions.Byholdinglanduse,vegetation,andfuelsstatic,theinteractionsamongwildlandfireandLULCchangewereoversimplified,whicharelimitationsthataresharedbymanybroad-scalestudiesofprojectedclimatechangeandwildlandfires.

Vegetationdynamicshaveoftenbeenignoredinclimate-changeprojectionsinpartbecauseofthedifficultyofparameterizingthesuccessionaltrajectoriesofeachindividualecosystemtypeandthelackofinformationabouthowecosystemsmayshiftacrossthelandscapeunderclimatechange.Theinfluencethatvegetationdynamicsmighthavehadontheresultsofthisassessmentisuncertain.Inspiteoftheprojectedincreasesinwildlandfireignitionsandareaburnedsimulatedforthisassessment,theextentoftheareaburnedeachyearwasprojectedtobequitesmallrelativetotheextentofareathatcouldpotentiallyburninanecoregion.Thus,intheecoregionsincludedinthisportionoftheassessment,itisunlikelythattheamountandarrangementofburnablevegetationonthelandscapewilllimitwildlandfires.Shiftsinvegetation,however,mightaffectthetypeofvegetationandtheamountoffuelavailabletoburn;thus,pastwildlandfiresandLULCchangemightalterthefuels,behavior,andemissionsoffuturewildlandfires(Bacheletandothers,2001,2003).

Specifically,intheEasternUnitedStatestheseprocessescouldincludethemesophicationofforestsinthemid-AtlanticthroughoutsouthernAppalachiathatisreducingunderstoryvegetationdensityandtheflammabilityoflitterfuels(NowackiandAbrams,2008).IntheSoutheasternUSAPlainsandtheMississippiAlluvialandSoutheastUSACoastalPlainsecore-gions,crownfireoccurrenceandwildlandfireemissionscouldpotentiallyincreasewithshiftsintheacreageofshort-rotationpineforests,withlittlefiremanagement.DefoliationandmortalityfollowinginsectoutbreakscanaffectsubstantialareasintheEasternUnitedStates.TheeffectsofinsectoutbreaksoncarboncyclingintheEasternUnitedStatescouldincludeshort-termdecreasesinprimaryproductivityandincreasesinrespirationthroughaltereddecompositionrates(Hickeandothers,2012).However,theeffectsofinsectdisturbancesoncarboncyclingatecoregionalscalesarenotwellunderstood,andmodelstopredictwherefutureoutbreaksarelikelyarenotcurrentlyavailable,thustheeffectsofinsectdisturbanceswerenotincorporatedintothisassessment.Theseprocessesandvegetationdynamicsintotheecosystem-disturbancemodelcomponentshouldbeconsideredforincorporationintofuturecarbonassessments(Running,2008;Goetzandothers,2012).

4.4. ResultsResultsforthebaselineandfuturepotentialprojections

ofwildlandfireoccurrenceandemissionsarepresentedusingsummarystatisticsofthemedianand95thpercentilevalues.Thesewereassumedtorepresenttypicalandextremefireyearsrespectively.

4.4.1. Baseline Wildland Fires and Emissions

Duringthebaselineperiod(2001–2008)intheEasternUnitedStates,thenumberofwildlandfiresperyearinatypicalfireyearwas112,butyear-to-yearvariabilitywashigh,andasmanyas186wildfiresoccurredduringextremefireyears(fig.4–2;table4–1).Theareaburnedbywildfiresinatypicalfireyearwas1,355km2,butwasmorethantwicethatinextremefireyears(4,092km2).Annualemissionsfromwildfireswere5.2teragramsofcarbondioxideequivalent(TgCO2-eq)duringtypicalfireyears,butmorethanfourtimesthatamountinextremefireyears(17.3TgCO2-eq).

Combined,theMixedWoodShieldandMixedWoodPlainsecoregionshadtheleastamountoffireactivityamong

2001 2002 2003Year

2004 2005 2006 2007 2008

0

50

150

200

100

0

2,000

1,000

4,000

3,000

5,000

0

5

10

15

20

25

Figure 4–1.

Num

ber o

f wild

fires

Area

bur

ned,

in s

quar

e ki

lom

eter

sEm

issi

ons,

in te

ragr

ams

ofca

rbon

dio

xide

equ

ival

ent

Figure 4 –2. Graphs showing the annual number of wildland fires, area burned, and emissions for the baseline (2001–2008) period of the carbon flux and storage assessment of the Eastern United States.

Chapter 4 63

Table 4–1. Summary statistics for the number of wildland fires, area burned, and emissions.

MetricMixed Wood Shield

and Mixed Wood Plains

Southeastern USA Plains

Ozark, Ouachita- Appalachian Forests

Mississippi Alluvial and Southeast USA

Coastal Plains1

Eastern United States

Number of wildfires per yearMean 9 17 37 58 121Minimum 1 2 13 24 60Median 9 10 41 49 11295thpercentile 17 49 54 97 186Maximum 18 57 59 110 200

Area burned, in square kilometers per yearMean 173 137 311 1,225 1,851Minimum 3 21 60 499 974Median 81 52 382 746 1,35595thpercentile 497 417 462 3,164 4,092Maximum 523 526 470 4,035 5,048

Emissions, in teragrams of carbon dioxide equivalent per yearMean 2.0 0.3 0.8 4.2 7.3Minimum 0.0 0.0 0.2 0.6 2.9Median 1.2 0.1 0.9 2.8 5.295thpercentile 5.8 1.0 1.3 11.9 17.3Maximum 6.0 1.3 1.3 15.6 22.3

1IncludestheEvergladesandTexas-LouisianaCoastalPlainlevelIIecoregionsfortheanalysisofthisassessment.

thefourecoregionsanalyzedintheEasternUnitedStates(fig.4–3A;table4–1).Themediannumberofwildfiresperyearwas9,andthe95thpercentileofwildfiresperyearwas17.Areaburnedduringtypicalfireyearswas81km2andwasashighas497km2inextremefireyears.Emissionswereverylowat1.2TgCO2-eq/yrinatypicalfireyear.However,inspiteofhavingtheleastamountofwildfiresandareaburned,emissionsduringextremefireyearswererelativelyhighinthisecoregionat5.8TgCO2-eq/yr.

IntheSoutheasternUSAPlainsecoregion,themedianvaluesforwildfireoccurrence,areaburned,andemissionswere10wildfiresperyear,52km2/yr,and0.1TgCO2-eq/yr,respectively(fig.4–3B;table4–1).Thenumberofwildfires,areaburned,andemissionsweremuchgreaterduringextremefireyearsat49wildfiresperyear,417km2/yr,and1TgCO2-eq/yr,respectively.

FireoccurrenceintheOzark,Ouachita-AppalachianForestsecoregionduringtypicalfireyearswasgreaterthanintheSoutheasternUSAPlains,MixedWoodShield,andMixedWoodPlainsecoregions(fig.4–3C;table4–1).Thenumberofwildfires,areaburned,andemissionswere41peryear,382km2/yr,and0.9TgCO2-eq/yr,respectively.Ratesofwild-fireoccurrenceandemissionswerenotsubstantiallydifferentduringextremefireyearswhenthenumberofwildfires,areaburned,andemissionswere54peryear,462km2/yr,and1.3TgCO2-eq/yr,respectively.

AmongthefourecoregionsoftheEasternUnitedStates,theMississippiAlluvialandSoutheastUSACoastalPlainsecoregionhadthegreatestnumberofwildfires,areaburned,andemissions(fig.4–3D;table4–1).Duringtypicalfireyears,thenumberofwildfires,areaburned,andemissionswere49peryear,746km2/yr,and2.8TgCO2-eq/yr,respectively.Duringextremefireyears,therewerenearlytwiceasmany

wildfires(97peryear),withmorethanfourtimesasmuchareaburned(3,164km2/yr)andemissions(11.9TgCO2-eq/yr).

4.4.2. Climate-Change Trends in the Eastern United States

IntheEasternUnitedStates,generalwarmingtrendswereprojectedacrossallseasonsandalmostallGCMsbetweenthe1991through2020and2031through2060periods(fig.4–4).Asnotedbefore,tocompareresultsofbaselineandfutureprojectionyears,theseintervalswereusedbecausetheywerecenteredovertheadjustedbaselineperiod(2001through2010,±10years)andthelastdecadeoftheprojections(2041through2050,±10years).Temperatureswereprojectedtoincreaseby1to2degreesCelsius(°C)forallecoregionsandallseasonsacrosstheEasternUnitedStates.Precipitationchangesweremorevariable,butappearedtohaveadecreasingtrend(drier)inthesummerandfall.Patternsofwinterandspringprecipitationvarieddependingontheecoregionandscenario,buttendedtowardincreasedmoistureintheNortheast,UpperGreatLakes,andtheOzarkandAppalachianMountainsanddecreasedintheSoutheasternUSAPlainsandMississippiAlluvialandSoutheastUSACoastalPlainecoregions(fig.4–4).Fortemperatureandprecipitation,thespatialpatternsofchangeweregenerallysimilarforagivenGCMacrossscenarios,butappearedtobemorevariableacrosstheGCMsthanthescenarios.

IntheMixedWoodShieldecoregion,averageseasonaltemperaturechangewasprojectedtobe1.9°C,1.4°C,1.4°C,and1.2°Cforthewinter,spring,summer,andfallseasons,respectively.PrecipitationchangesweremorevariableanddependedonthespecificscenarioandGCM.Ingeneral,


20

15

10

5

0

60

50

40

30

20

10

0

60

50

40

30

20

10

0

600

500

400

300

200

100

0

600

500

400

300

200

100

0

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0

0

40

20

80

60

120

100

0

2,000

5,000

4,000

3,000

1,000

20

15

10

5

0

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0

B. Southeastern USA Plains

C. Ozark, Ouachita−Appalachian Forests

D. Mississippi Alluvial and Southeast USA Coastal Plains

2001 2002 2003Year

2004 2005 2006 2007 2008 2001 2002 2003Year

2004 2005 2006 2007 2008 2001 2002 2003Year

2004 2005 2006 2007 2008

Figure 4–2.

A. Mixed Wood Shield and Mixed Wood Plains

Number of wildfires Area burned,in square kilometers

Emissions, in teragrams ofcarbon dioxide equivalent

600

500

400

300

200

100

0

7

6

5

4

3

2

1

0

Figure 4 –3. Graphs showing the annual number of wildland fires, area burned, and emissions for the baseline (2001–2008) period for the A, Mixed Wood Shield and Mixed Wood Plains, B, Southeastern USA Plains, C, Ozark, Ouachita-Appalachian Forests, and D, Mississippi Alluvial and Southeast USA Coastal Plains ecoregions (U.S. Environmental Protection Agency, 2013a) in the Eastern United States.

Chapter 4 65

Temperature change

Scenario A1B

Precipitation change

Scenario A2

Scenario B1

Winter Spring Summer Fall

CCCM

A CG

CM 3

.1CS

IRO

Mk

3.0

MIR

OC 3

.2 (m

edre

s)CC

CMA

CGCM

3.1

CSIR

O M

k 3.

0M

IROC

3.2

(med

res)

CCCM

A CG

CM 3

.1CS

IRO

Mk

3.0

MIR

OC 3

.2 (m

edre

s)

Winter Spring Summer Fall

Temperature change, in degrees Celsius Precipitation change, in centimeters

–1 0 1 2 3 4 8 –5–7.5 –2.5 –0.5 0 0.5 2.5 5 7.5

EXPLANATION

Figure 4.3.Figure 4 –4. Maps showing the projected changes in mean daily temperature and total precipitation by season, calculated using the difference in mean values from 2031 through 2060 and from 1991 through 2021. Climate data are from Maurer and others (2007). Scenarios A1B, A2, and B1 are from Nakićenović and others (2000). CCCMA CGCM 3.1, Canadian Centre for Climate Modelling and Analysis third generation coupled global climate model; CSIRO Mk 3.0, Commonwealth Scientific and Industrial Research Organisation Mark 3.0; MIROC 3.2 (medres), Model for Interdisciplinary Research on Climate version 3.2 medium resolution.


winterandspringseasonswereprojectedtohaveincreasesinprecipitationof0.5cmand2.4cm,respectively.Precipitationdecreasedinthesummerseasonby0.5cm,andfallprecipita-tionchangedlittle.

WarmingtrendswerealsoprojectedbymostscenariosandGCMsintheSoutheasternUSAPlainsecoregion.Averagewinter,spring,summer,andfalltemperatureswere1°C,1.3°C,1.4°C,and1.3°C,respectively,greaterinthe2031through2050periodthantheywereinthe1991through2020period.Winterandspringprecipitationdecreasedby1.1cmand1.9cm,respectively.SummerandfallprojectionsweremoremixeddependingontheGCMandscenario.Averagesummerprecipitationdecreasedby0.9cm,butaveragefallprecipitationincreasedslightlyby0.3cm.

SimilartotheSoutheasternUSAPlainsecoregion,temperaturechangesintheOzark,Ouachita-AppalachianForestsecoregionincreasedtheleastinwinter(1.2°C)andthemostinspring(1.4°C),summer(1.5°C),andfall(1.3°C).Inallseasons,theGCMsandscenarioswereevenlysplitwithabouthowprecipitationwouldchange:abouthalfofthesimulationsprojecteddrierconditions,andhalfprojectedwetterconditions.WhentheprecipitationchangeprojectionswereaveragedacrossGCMsandscenarios,winterprecipita-tiondecreasedminimallyby0.04cm,springprecipitationdecreasedby0.5cm,summerprecipitationdecreasedby0.9cm,andfallprecipitationincreasedslightlyby0.3cm.

ProjectedchangesintemperaturefortheMississippiAlluvialandSoutheastUSACoastalPlainsecoregionwerethesmallestamongallecoregionsintheEasternUnitedStates.Winter,spring,summer,andfalltemperatureswereprojectedtoincreaseby0.9°C,1.2°C,1.3°C,and1.2°C,respectively,betweenthe1991through2020and2031through2050periods.Precipitationchangeswereconsistentlydrierinthewinterandspringseasons(decreasesof1.4cmand2.5cm,respectively)andtosomeextentinthesummerseason(decreaseof1.6cm),butprecipitationincreasedslightlyinthefallseason(0.6cm).

high-andlow-densityurbanareas,golfcourses,urbanparks,andhighways),publiclands,and(or)areaofwildlandvegeta-tionandagriculturewereoftenincludedaspredictorstoo.Whenincluded,developedlandandagriculturehadnegativerelationshipswithwildfireignitionprobability,andpubliclandsandwildlandvegetationareahadpositiverelationshipswithignitionprobability.

CalibrationsimulationswererunforeachlevelIIIecoregiontoensurethatthepatternsofwildlandfireoccur-rencefrom1984through2008couldbereproduced.Foralltheecoregions,therewasnosignificantdifferenceintheaverageannualburnedareabetweenthecalibrationsimulationandtheobservedvaluesfromtheMTBSdatabase,assumingthatdifferenceswerenotsignificantwhenap-valueof0.05orgreaterwascalculatedusingatwo-sidedt-testthatassumedunequalvariance.Afterthecalibrationprocess,thesimulatedwildlandfireswereallowedtospreadbetween4to24hoursperday,andtheburndurationsrangedfrom1to6days,dependingontheecoregion.

FortheentireEasternUnitedStatesandacrossalltheclimate-changescenarios,theprojectionsimulationsresultedinanincreaseinwildlandfireignitions,areaburned,andemissionsbetweenthefirst(2001–2010)andlast(2041–2050)decades(fig.4–1;table4–2).Intypicalfireyears,themediannumberofignitionswasprojectedtoincrease,rangingfrom36percentunderscenarioB1to42percentunderscenarioA2and75percentunderscenarioA1B.Theareaburnedwasprojectedtoincrease,rangingfroma17percentincreaseinscenarioB1toa51percentincreaseinscenarioA1B.Wildlandfireemissionsfollowedsimilarpatterns,withprojectedincreasesof41percentunderscenarioA1B,25percentunderscenarioA2,and1percentunderscenarioB1.However,thechangesinmedianareaburnedandemissionswerenotstatisticallysignificantata0.05αlevelunderscenarioB1.CharacteristicsofscenariosA1B,A2,andB1areprovidedinchapter2.

Thesimulatedchangesinignitions,areaburned,andemissionsweresignificantlygreaterinextremefireyears(95thpercentile);acrosstheEasternUnitedStates,ignitionswereprojectedtoincreaseby45to153percent,theareaburnedwasprojectedtoincreaseby43to122percent,andemissionswereprojectedtoincreaseby41to111percent(fig.4–1;table4–2).Therateofchangewasgenerallynonlinear,andthegreatestincreasesinignitions,areaburned,andemissionswereprojectedin2021to2030forscenarioA1B,2041to2050inscenarioA2,and2031to2040inscenarioB1.

Therewasalargeamountofvariabilityintheprojectionsoffuturepotentialwildfires,areaburned,andemissionsintheMixedWoodShieldandMixedWoodPlainsecoregions(fig.4–5A;table4–2)andnotallthechangeswerestatisticallysignificantlydifferentfromzero.Ignitionsincreasedbyasmuchas71percentduringtypicalfireyearsandasmuchas43percentduringextremefireyears.Areaburnedandemissionsdidnotnecessarilyincreaseeventhoughignitionsdidunderallscenarios.Duringtypicalfireyears,thechange

4.4.3. Projected Future Wildland Fires and Emissions

GLMswerefittoeachlevelIIIecoregionandusedtogeneratedailyignitionprobabilitiesinthesimulations.Ingeneral,themodelfitsweregoodwiththeAUCvaluesaveraging0.87andrangingfrom0.72to0.93.ThebestmodelfitswereinthelevelIIIecoregionswithintheOzark,Ouachita-AppalachianForestsandtheworstmodelfitwasfortheSouthernFloridaCoastalPlainlevelIIIecoregion(reportedwiththeMississippiAlluvialandSoutheastUSACoastalPlainsecoregioninthisreport).Mostmodelsincludedtheenergyreleasecomponent(ERC)or10-or100-hourdeadfuelmoisturesasapredictoraswellasmonthlyandseasonalweathersummaries(whichcapturedseasonalandyear-to-yearvariability).Mostecoregionsalsoincludedatleastonevegetationpredictor.Developedland(whichincluded

Chapter 4 67

0

20

40

30

10

A. Mixed Wood Shield and Mixed Wood Plains

0

200

100

300

400

500

0

4

8

2

6

0

40

80

20

60

B. Southeastern USA Plains

0

400

800

200

6001.0

1.5

0.5

0

0

400

200

1,000

800

600

C. Ozark, Ouachita−Appalachian Forests

0

6,000

4,000

2,000

12,000

10,000

8,000

0

20

40

10

30

0

100

200

50

150

D. Mississippi Alluvial and Southeast USA Coastal Plains

0

3,000

2,000

1,000

7,000

6,000

5,000

4,000

0

20

10

30

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

2010

2020

2030

2040

2050

Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1

Figure 4–5.

Number of wildland fires per year Area burned, insquare kilometers per year

Emissions, in carbon dioxideequivalent per year

5th percentile

Minimum

95th percentile

50th percentile (median)

Maximum

EXPLANATIONFigure 4 – 5. Graphs showing summaries of projected wildland fire ignitions, burned area, and emissions for the A, Mixed Wood Shield and Mixed Wood Plains, B, Southeastern USA Plains, C, Ozark, Ouachita-Appalachian Forests, and D, Mississippi Alluvial and Southeast USA Coastal Plains ecoregions (U.S. Environmental Protection Agency, 2013a) by decade from 2001 through 2050. The x-axis labels indicate the last year in the decade; for example, 2010 on the graph corresponds to 2001 through 2010. Scenarios A1B, A2, and B1 are from Nakićenović and others (2000).


intheamountofareaburnedrangedasmuchas234percentinscenarioA2,andinemissions,asmuchas246percentinscenarioA2.Thelargeamountofchangeislikelyanartifactofthesmallamountofareaburnedandemissionsduringthebaselineperiod(5km2and0.04TgCO2-eq,respectively),sothatevensmallincreasesresultedinlargerelativechange.Theprojectedchangesforignitions,areaburned,andemissionswerelessinextremefireyearsthanintypicalfireyearsandweremostlynotstatisticallysignificant.Ignitionsincreasedbyasmuchas43percent,areaburnedchangedbyasmuchas65percent,andemissionschangedbyasmuchas26percent,butonlychangesinignitionsunderscenarioA2werestatisti-callysignificant.

IntheSoutheasternUSAPlainsecoregion,projectedchangeswereonlystatisticallysignificantfortypicalfireyearsunderscenarioA1B(fig.4–5B;table4–2),duringwhichignitionsincreasedbyasmuchas40percent,burnedareaincreasedbyasmuchas36percent,andemissionsincreasedbyasmuchas72percent.Projectedchangesforthenumberofwildfires,areaburned,andemissionswerenotstatisticallysignificantforscenarioA1BforextremefireyearsandforscenariosA2andB1fortypicalandextremefireyears.

TheOzark,Ouachita-AppalachianForestsecoregionexperiencedthegreatestamountofchangeintheEasternUnitedStatesinfireoccurrenceandemissionsintypicalandextremefireyears,andthealltheprojectedchangesweresubstantial(fig.4–5C;table4–2).Thenumberofignitionswasprojectedtochangeby56to123percentintypicalfire

yearsand55to207percentinextremefireyears.Projectedchangesinburnedareaweresimilarandincreasedby66to133percentintypicalfireyearsand49to197percentinextremefireyears.Changesinemissionslargelyfollowedchangesinburnedareaandincreasedby64to132percentintypicalfireyearsand48to209percentinextremefireyears.

ProjectedchangesinfireoccurrenceandemissionsintheMississippiAlluvialandSoutheastUSACoastalPlainsecore-giongenerallyincreased(fig.4–5D;table4–2).Decreaseswereprojectedundersomeclimate-changescenarios,butwerenotstatisticallysignificant.Intypicalfireyears,theamountsofchangerangedbyasmuchas30percentforignitions,47percentforareaburned,and36percentforemissions.ThedecreasesoccurredunderscenarioB1,andincreaseswereprojectedforscenariosA1BandA2.Inextremefireyears,fireoccurrenceandemissionsincreasedunderallscenarios.Changesrangedbyasmuchas51percentforignitions,55percentforareaburned,and67percentforemissions.

4.4.4. Summary of Wildland Fire Occurrence and Emissions of Carbon Fluxes

From2001through2008,wildlandfireactivityintheEasternUnitedStateswaslesssubstantialthanotherregionsoftheUnitedStates.Largewildlandfiresnumberedbetween60and200peryearandburned974to5,048km2eachyear.ThesewildlandfiresintheEasternUnitedStates

Table 4–2. Relative projected changes in the 50th and 95th percentiles for wildfire ignitions, area burned, and emissions between 2001–2010 and 2041–2050.

Scenario MetricMixed Wood Shield

and Mixed Wood Plains

Southeastern USA Plains

Ozark, Ouachita- Appalachian Forests

Mississippi Alluvial and Southeast USA

Coastal Plains1

Eastern United States

Percentage of number of wildfires per yearA1B Median 50* 40* 123* 26* 75*A2 Median 71* 18 64* 30* 42*B1 Median 20 8 56* 12 36*A1B 95thpercentile 5 15 198* 41* 141*A2 95thpercentile 43* 28 207* 51* 153*B1 95thpercentile 16 42 55* 25* 45*

Percentage of area burned per yearA1B Median –10 36* 133* 47* 51*A2 Median 234* 27 66* 12 34*B1 Median 79 –4 70* –2 17A1B 95thpercentile –2 –16 162* 19 52*A2 95thpercentile 65* –9 197* 55* 122*B1 95thpercentile 1 –5 49* 22 43*

Percentage of emissions per yearA1B Median 9 72* 132* 36* 41*A2 Median 246* 20 64* 9 25*B1 Median 127 2 70* –17 1A1B 95thpercentile –16 –8 209* 10 41*A2 95thpercentile 26 5 164* 67* 111*B1 95thpercentile 20 –12 48* 12 45*

1IncludestheEvergladesandTexas-LouisianaCoastalPlainlevelIIecoregionsfortheanalysisofthisassessment.

*Changewassignificantat0.05alphalevelsinpermutationtests.

Chapter 4 69

represented23percentofallwildlandfiresthatoccurredintheconterminousUnitedStatesfrom2001through2008andaremappedintheMTBSdatabaseandaccountedfor10percentofalltheareaburned.Themedianofannualemissionswas5.2TgCO2-eq/yr,whichwasequivalentto0.48percentofNEP(chap.5).Theinterannualvariabilityinemissionswashighandrangedfrom2.9to22.3TgCO2-eqintheEasternUnitedStates,whichwasequivalentto0.27to2.05percentofNEP.In2010,themedianofannualwildfireemissionswas5,594TgCO2-eq/yr,equivalentto0.09percentofnationwidefossil-fuelemissions(U.S.EnvironmentalProtectionAgency,2012);minimumwildfireemissionswere0.13percentandmaximumwildfireemissionswere0.40percentofthenationwidefossil-fuelemissions.TherelativecontributionofwildlandfiresoftheEasternUnitedStatestonationwidegreenhouse-gasemissionswassmallwhencomparedthatofotherregionsoftheUnitedStates(Zhuandothers,2010;HawbakerandZhu,2012)andtothecontributionoffossil-fuelemissions.

Wildlandfireignitionsandareaburnedwereprojectedtoincreaseacrossalltheclimate-changescenariosfortheEasternUnitedStatesasawhole,andthechangeswerelargerforextremefireyearsthanfortypicalfireyears.TheannualamountofareaburnedbywildfiresintheEasternUnitedStateswasprojectedtoincreasebyasmuchas51percentfrom1,355km2intypicalfireyearsandasmuchas122percentfrom4,092km2inextremefireyears.Theprojectedchangesinburnedarearesultedinsimilarchangesinemissions,whichincreasedbyasmuchas41percentfrom5.2TgCO2-eqintypicalfireyearsandbetween41and111percentfrom17.3TgCO2-eqinextremefireyears.Thesechangesweredrivenbytheinfluenceofclimatechangeonliveanddeadfuelmoisturelevels,whichinturnhadalargeinfluenceonignitionprobabilities,firespread,fuelconsumption,andemissions.

Themagnitudeanddirectionofchangeofthewildfireprojectionsvariedamongecoregionsandclimate-changescenarios.Theonlyecoregionthathadconsistentincreasesinthenumberofwildfires,areaburned,andemissionsacross

allclimate-changescenarioswastheOzark,Ouachita-AppalachianForestsecoregion.TheMixedWoodShieldandMixedWoodPlainsecoregionsprojectedincreasesinignitionsunderallscenariosandincreasesinareaburnedandemissionsunderscenariosA2andB1,butnotforscenarioA1Bwhereprecipitationprojectionssuggestedawetterclimate.TheSoutheasternUSAPlainsecoregionhadmixedresults,withtypicalfireyearsexperiencingmostlyincreasesinignitions,areaburned,andemissions,butwithextremefireyearsexperiencingdecreasesinareaburnedandemissions.TheMississippiAlluvialandSoutheastUSACoastalPlainsecore-gionexperiencedincreasesinfireoccurrenceandemissionsunderscenariosA1BandA2,butnotunderscenarioB1.

Inthisstudyarea,wildfireemissionswererelativelylowcomparedwithcarbonsequesteredinterrestrialecosystems(chap.5),butthisdoesnotnecessarilymeanthatwildfiresdonothaveimportanteffectsoncarbonbalanceintheEasternUnitedStates.Instead,thelargesteffectsofwildfiresoncarbonbalanceintheEasternUnitedStatesmightbelocal-izedtospecificecosystemsthatcurrentlyhavehighcarbonstorage,butareatriskoflosingcarbonbecauseofincreasedfireactivitiesoralteredfirebehavior.TheseecosystemsmayincludepocosinwetlandswithdeeppeatdepositsalongtheAtlanticcoast(MessinaandConner,1998),southernborealforestsalsowithdeeppeatdepositsandhighfuelloadsintheUpperGreatLakes(Heinselman,1973),pinebarrensintheUpperGreatLakesandNewJersey(Forman,1998;Radeloffandothers,2000),andpineforestsintheSoutheasternUSACoastalPlains(Christensen,1999).Managementeffortsdesignedtomaintainorincreasecarbonstorageintheseecosystemsmaybechallengedbythepotentialcarbonlossesduetotheprojectedclimate-drivenincreasesinwildlandfireactivities.InotherecosystemsintheEasternUnitedStates,wildfireplaysasmallerroleincarboncycling,andothernaturaldisturbancesmaybemoreimportant,forexample,windthrow(CanhamandLoucks,1984;FrelichandLorimer,1991)andanthropogenicLULCchange(chap.3).

Wildland Fire Occurrence and Emissions in the … Fire Occurrence and Emissions in the Eastern...

Documents

Transcript of Wildland Fire Occurrence and Emissions in the … Fire Occurrence and Emissions in the Eastern...