全球碳循环-ModelingCarbonCycle碳循环模型-

Lecture5:ModelingCarbonCycleI.ModelOverviewWhatisamodel?Whydoweneedthemodel?Therolesofmodels

II.IntroductiontoCarbonModels

Empiricalmodels ProcessmodelsHybridmodelsStrengthandweaknessIII.ModelApplications

Challenge:ModelvalidationTRIPLEXmodelWhatisaModel?

AmodelisanabstractionofarealsystemWeusemodelsintwoways:-conceptualmodel-formalmodel

RealsystemModelModelCatalog

Conceptual(WordorFlowcharts)Models:usedtorepresentourconceptsorknowledgeanddescribetheinteractionsbetweenthecomponentsofasystemMathematical(Statistical)Models:usedtopresenttheaconceptualModelorothertypesbyusingmathematicalnotation.ComputerSimulationModels:MathematicalmodelscabbetranslatedIntocomputerlanguagesandimplementedonacomputer

WhyDoWeNeedModels?Threemethodstoassesstheeffectsofachangingenvironmentonecosystems(Botkin1993): (a)ourknowledgeofthepast(b)presentmeasurements(c)ourabilitytoprojectintothefuture

OurknowledgeofthepastandpresentmeasurementshavebeenoflimiteduseLong-termmonitoringoftheforesthasprovendifficultduetocostandlong-termcommitmentCurrentexperimentaltechniquesarenotdirectlyapplicabletocomplicatedenvironmentalchangeTheRolesofModels

Modelsasresearchtools

toincreaseourknowledgeModelsasmanagementtool

tohelptomakedecisionsModelsaseducationtools

tohelptounderstandtheEarthsystemEmpiricalvs.ProcessModels

Empirical(statistical)models:

arederivedfromlargeamountsoffielddata,anddescribecarboncycle(ortreegrowth)asaregressionfunctionofvariables(biotic:age,basalarea,density;abiotic:temp.prec.,radiation,lightetc.)FirstglobalNPPmodel(MIAMImode:Lieth,1975)HelmutLieth(1975)developedthisfirstglobalNPPmodeltoquantifytherelationshipbetweenNPPandthemeanannualtemperatureandtotalprecipitationusing52fieldsites Ref.Lieth,H.1975.In:Lieth,HandR.H.Whittaker(eds.).PrimaryProductivityofBiosphere,Springer-Verlag,NewYork,USA,pp.237-263.

MIAMIModel(Lieth,1975)NPPT=3000/(1+e(1.315-0.119T))orNPPp=3000(1-e-0.000664P)WhereNPP:(g/m2/yr) T:meanannualtemperature(ºC) P:totalannualprecipitation(mm)

GlobalNPPwasestimatedabout63x1015gCyr-1(assumingnaturevegetation),whichissurprisinglysimilartothesatellitepictureof“greenness”(NDVIforJune1982byNASA)

(kgC/m2/yr)(kgC/m2/yr)(kgC/m2/yr)Empiricalvs.ProcessModelsProcess(Mechanistic)Models:aredevelopedtorepresentkeyecosystemprocessesorsimulatethedependenceofcarboncycleonanumberofinteractingprocesses(suchasphotosynthesis,respiration,decomposition,andnutrientcyclingetc…)MajorProcessesofaComprehensiveProcessModelEnergybalanceCarbonbalanceNutrientbalanceWaterbalanceCurrentProcess-BasedModelsSpatialScalesOrgan(LeaforCanopy)modelse.g.Farquhar’sModels(Farquharetal,1980);FOEST-BGC(RunningandCoughlan,1988);MAESTRO(WangandJarvis,1990);BIOMASS(McMurtrieetal.1990);B.Individualtreeecophysiologicale.g.ECOPHYS(Rauscheretal.1990);TREGRO(WinsteinandYanai,1994);TREE-BGC(Koroletal.,1994)C.

Communitymodels(gaporsuccessionmodels)e.g.JABOWA(Botkinetal.1972);FORET(ShugartandWest,1977);ZELIG(SmithandUrban,1988);LINKAGE(PastorandPost,1985)D.

Standor

Ecosystemmodelse.g.

PnET(AberandFederer,1992);CENTURY(Partonetal.(1987);TRIPLEX(Pengetal.2002)E.

Landscapemodelse.g.FIRE-BGC(Keaneetal.,1996);LANDIS(Heetal.1996)F.

Globalmodelse.g.BIOME3(HaxeltineandPrentice,1996);MAPSS(Neilson,1993);IBIS(Foleyetal.,1996)Process(Mechanistic)ModelsFarquhar’sModels(Farquharetal,1980):isoneofmostphysiologicallysoundpresentlyavailablemodeltoquantifytheleafPhotosynthesisofC3plants.ThemodelsimulatesthephotosyntheticrateofC3plantsasafunctionofleafirradiance,inter

Netphotosynthesis(µmm-2s-1)isexpressedas:A=Vc–0.5V0–Rd(1)WhereVcandV0areratesofcarboxylationandoxygenation,respectivelyRdisdarkrespirationTheterm:Vc–0.5V0isexpressedbyFarquharetal(1980)as:Vc–0.5V0=min{Wc,Wj}(1-I/Ci)(2)Where{}denotestheminimumof,Wc:theRubiscolimitedrateofcarboxylation,Wj:theribulosebisphosphate(RuBP)-limitedrateofcarboxylationwhenRuBPregerenerationislimitedbyelectrontransport.

I:theCO2compensationpointintheabsentofdarkrespirationCi:

theintercellularCO2concentration

So,A=min{Wc,Wj}(1-I/Ci)––Rd(3)Farquhar’’sModelsTherateWcisexpressedas:Wc=VcmaxCi/[Ci+Kc(1+[O]/Ko)](4)WhereVcmaxisthemaximumcarboxylationrateKcandKoaretheMichaelis-MentenkineticcoefficientsforCO2andO2TherateWjcanbeexpressedas:Wj=J(Ci-I)/(4Ci––8I)(5)WhereJisthepotentialrateofelectrontransportanddependentonlightAccordingtoCollatzetal(1991),Rd=0.015Vcmax(6)References:1.Farquhar,G.D.,S.vonCaemmererandJ.A.Berry.1980.AbiochemicalmodelofphtosyntheticCO2assimilationinLeaveofC3Species.Planta,149:78-90.2.Collatz,G.J.,J.T.Ball,C.GrivetandJ.A.Berry.1991.Physiologicalandenvironmentalregulationofstomatalconductance,photosynthesisandtranspiration:Amodelthatincludesalaminarboundarylayer.Agric.For.Meteorol.54:107-136Farquhar’sModelsWhatistheCENTURY?CENTURY,asdevelopedbyPartonetal.(1987,1993),isaprocess-basedecosystemmodelofplant-soil,whichsimulatesthelong-termbiogeochemicalcyclesofC,N,P,andSforvariousecosystems,includinggrassland,agriculturalland,savannasandforests.Website:/projects/century/nrel.htmCENTURY4.0Submodelsforestproductionsoilorganicmatter/decompositionwaterbudgetgrassland/cropmanagementandeventsschedulingfunctionsTimestep:monthlyCarbonpools(boxes)andfluxes(arrows)inCENTURY4.0ATMOSPHERELeafFineBranchesLargeWoodCoarseRootFineRootVEGETATIONSurfaceLitterMetab.Struc.DeadLargeWoodDeadFineBranchesDeadCoarseRootSurfaceMicrobeActiveSOMSlowSOMPassiveSOMLITTERSOILNPPASSIMILATIONLeachedCPlantRespirationMicrobialRespirationSoilRespirationCO2CO2CO2CO2CO2RootLitterMetab.Struc.(Pengetal.1998)Majorstrengthandweaknessofempiricalmodels:Describethebestrelationshipbetweenthemeasureddataandthevariablesarenotrobust,forexample,foranalyzingtheconsequencesofenvironmentalstressandclimaticchangesMajorstrengthandweaknessofprocessmodels:theinclusionoftheecophysiologicalprinciplesandtheirlong-termforecastingabilitywithinchangingenvironmentsMostprocess-basedmodelsareresearchtoolsandarenotappropriateformanagementapplicationsTheyaretoocomplexandrequirealargeamountofinformationandinputs

StrengthandWeaknessofProcessModels“Empiricalandprocessmodelscanbemarriedintohybridmodelsinwhichtheshortcomingsofbothapproachescanbeovercometosomeextent.Specifically,incorporatingthekeyelementsofempiricalandprocessapproachesintoahybridecosystemmodelingapproachcanresultinamodelthatpredictsforestgrowth,productionandcarbondynamicsinboththeshortandlongterm.””RationaleforHybridModels(Peng,For.Ecol.Manag.,2000)HybridmodelingisapromisingapproachthatbridgesthegapsbetweenempiricalandprocessmodelsFormoredetaileddiscussions,pleasetrytoread:1)Peng,2000.Growthandyieldmodelsforuneven-agedstands:past,presentandfuture.ForestEcologyandManagement.132:259-2792)Peng,2000.Fromstaticbiogeographicalmodeltodynamicglobalvegetationmodel:aglobalperspectiveonmodellingvegetationdynamics.135:33-54(canbedownloadedfromwebsite:www.crc.uqam.ca-under““Publication””)Challenge:ValidationCalibrationistheestimationandadjustmentofmodelparametersandconstantstoimprovetheagreementbetweenmodeloutputandadataset.Validationistestingamodeltoseehowwellitpredicts.(Howwelldoesthemodelcapturethestructure,controls,anddynamicsofarealforestecosystem).Firstquestionsis:whatvariabledowewanttovalidate(test)?Thesecondquestionisfindingadequatedata.WaringandRunning(1998)recommendagroupofvariablesthatcanbeaccuratelymeasuredinthefieldandreflectarangeofforestinteractionlinkedcarbon,nitrogenandwatercycles.Theseinclude:Leafareaindex(LAI)Netprimaryproductivity(NPP)StembiomassLeaflitterfallLeafnitrogencontentTotalHeightDiameteratbreastheight(DBH)BasalArea(BA)TotalVolumeVariablesforValidatingProcessModelGreenhouseorexperimentaldataTreegrowthplots(PSP,TSP)Forestinventory(NPP,BFluxtower(CO2,NPP,NEPetc..)RemoteSensing(LAI,NDVI-NPP)Paleoecologicaldata(tree-ring,pollen)DataforValidatingProcessModelTRIPLEX:AgenerichybridmodelforpredictingforestgrowthandcarbonandnitrogendynamicsDevelopedbasedonwell-establishedmodels:3-PG(LandsbergandWaring,1997)TREEDYN3.0(Bossel,1996)CENTURY4.0(Partonetal.,1987,1993)Bridgesthegapbetweenforestgrowthandyieldandprocess-basedCbalancemodelsCanbeusedfor:1)Makingforestmanagementdecisions(e.g.,G&Yprediction)2)Quantifyingforestcarbonbudgets3)Assessingtheeffectsofclimatechangeonforestecosystems(Pengetal.2002,Ecol.Model,153:109-130)RealBiologicalSystem:JackP (Ontario,Canada)KeyFeaturesofTRIPLEX:Drivingvariables(maininputs):Monthlyclimatedata;LAI;Ndepositionandfixationrate;geo-locationMassbalances:C,N,andwaterpoolsandfluxesfullybalancedTimestep:MonthlyCfluxandallocationcalculation;annualtreegrowth,C,N,andwaterbudgetOutputs:H,DBH,BA,volume,NPP,biomass,soilC,N,andwaterdynamicsModellingstrategy:OOP(objective-orientedprogramming-C++)andmodelreuseapproachesTREEDYN3(Bossel,1996);3-PG(LandsbergandWaring,1997);CENTURY4.0(Partonetal.,1993)TemperatureNmineralizationNStoreLeachingNlimitationPrecipitationSoilwaterRunoffMoisturePool:Process:IncrementHeightDiameterVolumeBasalAreaMortalityDisturbanceThinningTreenumberHarvestingWoodproductionAtmosphericCO2GPPCAllocationLeafsCNRootsWoodCNCLitterfallCNStructureMetabolicCNCNActive(C,N)Slow(C,N)Passive(C,N)NDecomposition(C,N)TRIPLEXModelFrameworkSolarradiation11/15/2022TRIPLEX1.0UserInterfaceT(Pengetal.2002)12PSP(0.08haeach)Foresttype:Jackpine(PinusbanksianaLamb.)SABOCTMTOneCaseStudyBO:Boreal;CT:CoolTemperate;MT:ModerateTemperate;SA:SubarticOntarioLocation:Longlac(KimberlyClarkLtd.)LonglacWehave6consecutivemeasuremUsefirstmeasurements(1952)tocalibratetheTRIPLEXmodelUsetheother5measurementstovalidate(1957-1982)CalibrationandValidationforTRIPLEXModelComparisonofSimulationsandObservations(soliddiagonalisthe1:1line;N=60)SimulatedRelativeError

(=[simulation-observation]/observation)±10%±15%±20%±25%ComparisonofAveragedSimulationsandObservations-HeightComparisonofAveragedSimulationsandObservations-TreeVolumeComparisonofAveragedSimulationsandObservations-StemDensityComparisonofAveragedSimulationsandObservations-AbovegroundBiomass(Hegyi,1972)CanadaOntarioLongitudeandLatitude:-80.7,48.8Temperature:1.2oCPrecipitation:814.8mmStudyarea:LakeAbitibiModelForestModelingForestGrowthandCarbonDynamicsatLandscapelevelinLakeAbitibiModelForest(May12,2002)MethoTRIPLEXmodelNCDynamicsBiomassNPPSoilC&NDBHHeightVolume…...ArcGISArcViewSpatialDistributionSimulationModelOutputsModelinputsForestLAMFLocaldata(standsandspatialdata)SoilOntarioLandInventoryPrimelandInformationSystem(OLIPIS)AsoilprofileandorganiccarbondatabaseforCanadianforestClimateDatabasefromEnvironmentCanadaCanadianCentreforClimateModeling(CCCMadatabase)Modelvalidation32blackspruce,9jackpine,8tremblingaspenplots(measuredin1995)TRIPLEXvs.ForestInventoryTRIPLEXvs.PSPFig.4ThecomparisonbetweenNPP(tCha-1yr-1)simulationsatlandscape(a)andremotesensing(b)levelsfortheLAMFin1994.(a)wasbasedontheTRIPLEXmodelsimulationfor1994(averaged3.28tCha-1yr-1,SD=0.79),and(b)wasconvertedusingspatialdatafromLiuetal.(2002)for1994(averaged3.08tCha-1yr-1,SD=1.15).Thegridsizeis3x3km.TRIPLEX(Zhouetal,2005)(b)RemoteSensing(Liuetal,2002)ComparingNPPSpatialDistributionatLandscapeLevelKappaStatistic(k)=0.55Goodagreementif0.55<K<0.7SimulatedBiomass(tha-1)in2000SimulatedNPP(tCha-1yr-1)in2000BiomassCpool:55.5Aboveground:42.2Belowground:13.3HarvestingCAbout0.1Crelease:1.0Cupdate:3.0Netcarbonbalance(NCB)=2.0MtCCbudgetofLAMFforestecosystemin2000:LitterandSoilCpool:83.7Unit:MtCTRIPLEX-FluxModelDevelopmentNCCO2WaterLightreactionsO2CalvincycleSugarH2OCO2StomaCellShadedleafEnergyTRIPLEX-Flux(twoleaves,daily)TRIPLEX1.0(bigleaf,monthly)SunlitleafModelTestingfor2Fluxtowersites(Fluxnet-Canada)110yrsblackspruce75yrsmixedwoodModelValidation––OBSFluxTowerDailySimulationusingTRIPLEX-fluxNEPModelValidation––UsingOBSFluxTowerDailySimulationusingTRIPLEX-fluxBorealMixedwoodSite(Ontario)Ontariostationin2004SensitivityNEPtoTincreaseNEPTemperatureincrease(C)Ca(CO2concentrationincrease)NEPSensitivityNEPtoCOSimulationresultcomparisonUncertaintiesandLimitationsModelstructure,process,mechanismandinputsUncertaintyinobservations(eddy-fluxmeasureunderestimationofnight-timerespiratoryfluxes;LackofenergybalanceclosureGap-fillingformissingdata(about12%error)Disturbances:fire,insects,airpollution(ozone,UVB),DOCScalingup—siteheterogeneity(speciescompositionandsoiltexture)

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