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Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 9, NO. 4, PAGES 407-437, DECEMBER 1995 Vegetation/ecosystemmodeling and analysis project- Comparing biogeography and biogeochemistrymodels in a continental-scale study of terrestrial ecosystemresponses to climate change and C02 doubling VEMAP Members1 Abstract. We comparethe simulationsof threebiogeography models (BIOME2, Dynamic GlobalPhytogeography Model (DOLY), andMapped Atmosphere-Plant Soil System(MAPSS)) andthree biogeochemistry models (BIOME-BGC (BioGeochemistryCycles), CENTURY, and TerrestrialEcosystem Model (TEM)) for the conterminousUnited Statesunder contemporary conditionsof atmosphericCO2 and climate. We alsocompare the simulationsof thesemodels underdoubled CO2 and a rangeof climatescenarios. For contemporaryconditions, the biogeographymodels successfully simulate the geographicdistribution of majorvegetation types andhave similarestimates of areafor forests(42 to 46% of the conterminousUnited States), grasslands(17 to 27%), savannas(15 to 25%), and shrublands(14 to 18%). The biogeochemistry modelsestimate similar continental-scale netprimary production (NPP; 3125 to 3772 x 10•2 gC yr'•) andtotal carbon storage (108 to 118x 10•5 gC) for contemporaryconditions. Among the scenariosof doubledCO2 and associatedequilibrium climates produced by the threegeneral circulationmodels (Oregon State University (OSU), GeophysicalFluid DynamicsLaboratory (GFDL), andUnited KingdomMeteorological Office (UKMO)), all threebiogeography models showboth gains and losses of totalforest area depending on the scenario(between 38 and53% of conterminousUnited Statesarea). The only consistentgains in forestarea with all threemodels (BIOME2, DOLY, andMAPSS) were underthe GFDL scenariodue to largeincreases in precipitation.MAPSS lostforest area under UKMO, DOLY underOSU, andBIOME2 under bothUKMO and OSU. The variabilityin forestarea estimates occurs because the hydrologic cyclesof the biogeographymodels have different sensitivities to increasesin temperatureand CO2. However,in general,the biogeographymodels produced broadly similar results when incorporatingboth climatechange and elevated CO2 concentrations. For thesescenarios, the NPP estimatedby the biogeochemistrymodels increases between 2% (BIOME-BGC with UKMO climate)and 35% (TEM with UKMO climate). Changesin total carbonstorage range from losses of 33% (BIOME-BGC with UKMO climate)to gainsof 16% (TEM with OSU climate). The CENTURY responsesof NPP and carbonstorage are positiveand intermediateto the responsesof BIOME-BGC and TEM. The variabilityin carboncycle responses occurs because the hydrologic andnitrogen cycles of the biogeochemistrymodels have differentsensitivities to increasesin temperatureand CO2. When the biogeochemistrymodels are run with the vegetationdistributions of the biogeographymodels, NPP rangesfrom no response(BIOME-BGC with all three biogeographymodel vegetations for UKMO climate)to increasesof 40% (TEM with MAPSS vegetationfor OSU climate). The total carbonstorage response ranges from a decreaseof 39% (BIOME-BGC with MAPSS vegetationfor UKMO climate)to an increaseof 32% (TEM with MAPSS vegetationfor OSU andGFDL climates).The UKMO responsesof BIOME-BGC with MAPSS vegetationare primarilycaused by decreasesin forestedarea and temperature-induced water stress.The OSU and GFDL responsesof TEM with MAPSS vegetationsare primarily causedby forestexpansion and temperature-enhanced nitrogen cycling. •J M. Melillo, The EcosystemsCenter, Marine Biological Service,Raleigh, North Carolina;A. Haxeltine, Universityof Lund, Laboratory,Woods Hole, Massachusetts;J. Borchers,U.S. Department Lund, Sweden; A. Janetos, National Aeronautics and Space of Agriculture Forest Service, Oregon State University, Corvallis; J. Administration,Washington, D.C.; D. W. Kicklighter,The Ecosystems Chaney,U.S. Departmentof ForestService, Oregon State University, Center,Marine BiologicalLaboratory, Woods Hole, Massachusetts;T. Corvallis;H. Fisher,University Corporation for AtmosphericResearch, G. F. Kittel, UniversityCorporation for AtmosphericResearch, Boulder, Boulder, Colorado; S. Fox, U.S. Departmentof Agriculture Forest Colorado; A.D. McGuire, Alaska Cooperative Fish and Wildlife ResearchUnit, Universityof Alaska-Fairbanks;R. McKeown, Natural ResourcesEcology Laboratory, Colorado State University, Fort Collins; Copyright1995 by the AmericanGeophysical Union. R. Neilson,U.S. Departmentof AgricultureForest Service, Oregon State University,Corvallis; R. Nemani,University of Montana,Missoula; D. Papernumber 95GBO2746. S. Ojima, Natural ResourcesEcology Laboratory,Colorado State 0886-6236/95/95GB-02746510.00 University,Fort Collins; T. Painter,Center for RemoteSensing and 407 408 VEMAP MEMBERS: COMPARING BIOGEOGRAPHY AND BIOGEOCHEMISTRY MODELS EnvironmentalOptics, University of California, SantaBarbara; Y. Pan, currentlyis not sufficientto allow the identificationof the "best" The EcosystemsCenter, Marine Biological Laboratory,Woods Hole, modelsor to acceptas correcttheir predictions. Thus in any Massachusetts;W. J. Parton,Natural ResourcesEcology Laboratory, effort to provide more realistic simulationsof ecological ColoradoState University, Fort Collins,Colorado; L. Pierce,Department of Biological Sciences,Stanford University, Stanford, California; L. response,it is importantto employ severalmodels of eachtype Pitelka, Electric Power ResearchInstitute, Palo Alto, California; C. andto comparemodels that attemptto simulatethe sametypes of Prentice,University of Lund, Lund, Sweden;B. Rizzo, Departmentof response.In this paperwe presentan overviewof the resultsof EnvironmentalSciences, University of Virginia, Charlottesville;N. A. the Vegetation/EcosystemModeling and Analysis Project Rosenbloom,Department of Geology,Institute of Arctic and Alpine Research,University of Colorado,Boulder; S. Running,University of (VEMAP), an international collaborative exercise involving Montana, Missoula; D. S. Schimel, University Corporation for investigatorsfrom thirteeninstitutions. AtmosphericResearch, Boulder, Colorado; S. Sitch,University of Lund, Lund, Sweden; T. Smith, Department of EnvironmentalSciences, University of Virginia, Charlottesville;I. Woodward,Department of Animal andPlant Sciences, University of Sheffield,Sheffield, England. Approach Introduction Overview The atmosphericconcentrations of the major long-lived We comparethe simulationsof three biogeographymodels greenhousegases continue to increasebecause of humanactivity. (BIOME2, DOLY, and MAPSS) and three biogeochemistry Changesin greenhousegas concentrations and aerosolsare likely models (BIOME-BGC, CENTURY, and TEM) for the to affect climate through changesin temperature,cloud cover, conterminousUnited Statesunder contemporaryconditions of and precipitation[Intergovernmental Panel on Climate Change atmosphericCO2 and climate. We alsocompare the simulations (IPCC), 1992; Charlsonand Wigley, 1994; Penner et al., 1994]. of these models under doubled CO2 and a range of climate Changesin landcover and landuse may alsoinfluence climate at scenarios.In addition,we simulatea coupledresponse by using the regionalscale [Dirmeyer, 1994; Trenberthet al., 1988;Nobre the biogeographymodel outputs as inputsto the biogeochemistry et al., 1991]. Predictionsof the climate system'sresponse to models. altered forcing are shifting from a simplisticview of global It is often difficult to identify the sourceof incon'sistenciesin warming to a more complexview involving a range of regional outputs from model intercomparisons.Differences in model responses, aerosol offsets and large scale feedbacks and outputsmay arise from differencesin conceptualizationof the interactions. There is considerable concern over the extent to problem, implementationat different spatial or temporalscales, which these changescould affect both natural and human- or use of different input data sets. Contrastsin model dominated ecosystems[Meli!!: :: ::!., '_990; Walker, 1994; conceptualizationscan occur either with the use of different Schimel et al., 1994]. Becausethe responseof the climate algorithmsor parametervalues. In order to examine how systemto anthropogenicforcing will likely have considerable differentalgorithms or parametervalues of identicalalgorithms spatial complexity, a capability to assessspatial variationsin influence change,we attemptto minimize the other sourcesof ecologicalresponse to climateforcing is critical. variation by using a common input databaseand a common On the basisof our understandingof ecologicalprinciples, we spatialformat. In this section,we (1) describethe modelsused in can expectthat changesin climateand atmosphericcomposition this project,(2) presentthe input database,and (3) discussthe should affect both the structure and function of terrestrial l•roject'sexperimental design. ecosystems. Structuralresponses include changesin species compositionand in a variety of vegetationcharacteristics such as canopyheight and rootingdepth. Functionalresponses include Model Descriptions changes,in the cycling of carbon,nutrients (e.g., nitrogen, phosphorus,sulfur) and water. Models of how ecosystemstructure (biogeography models) BiogeographyModels. The biogeographymodels predict the and function(biogeochemistry models) might respondto climate dominanceof variousplant life formsin differentenvironments, changeexist, but generallyhave been developedindependently. basedon two types of boundaryconditions: ecophysiological In recentyears, both types of modelshave been exercisedfor constraints and resource limitations. Ecophysiological
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