The Amazon tropical evergreen forest is an important component of the global carbon budget. Its forest floristic composition, structure, and function are sensitive to changes in climate, atmospheric composition, and land use. In this study biomass and productivity simulated by three dynamic global vegetation models (Integrated Biosphere Simulator, Ecosystem Demography Biosphere Model, and Joint UK Land Environment Simulator) for the period 1970-2008 are compared with observations from forest plots (Rede Amazonica de Inventarios Forestales). The spatial variability in biomass and productivity simulated by the DGVMs is low in comparison to the field observations in part because of poor representation of the heterogeneity of vegetation traits within themodels. We find that over the last four decades the CO2 fertilization effect dominates a long-term increase in simulated biomass in undisturbed Amazonian forests, while land use change in the south and southeastern Amazonia dominates a reduction in Amazon aboveground biomass, of similar magnitude to the CO2 biomass gain. Climate extremes exert a strong effect on the observed biomass on short time scales, but the models are incapable of reproducing the observed impacts of extreme drought on forest biomass. We find that future improvements in the accuracy of DGVM predictions will require improved representation of four key elements: (1) spatially variable plant traits, (2) soil and nutrients mediated processes, (3) extreme event mortality, and (4) sensitivity to climatic variability. Finally, continued long-term observations and ecosystem-scale experiments (e. g. Free-Air CO2 Enrichment experiments) are essential for a better understanding of the changing dynamics of tropical forests.
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Natl Inst Space Res INPE, Sao Jose Dos Campos, BrazilNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Rezende, Luiz F. C.
de Castro, Aline Anderson
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Natl Inst Space Res INPE, Sao Jose Dos Campos, BrazilNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
de Castro, Aline Anderson
Von Randow, Celso
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Natl Inst Space Res INPE, Sao Jose Dos Campos, BrazilNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Von Randow, Celso
Ruscica, Romina
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Univ Buenos Aires, Fac Ciencias Exactas & Nat, Buenos Aires, DF, Argentina
Univ Buenos Aires, CONICET, Ctr Invest Mar & Atmosfera CIMA, Buenos Aires, DF, Argentina
UBA, CNRS, IRD,UMI 3351,IFAECI, CONICET,Inst Francoargentino Estudio Clima & Impa, Buenos Aires, DF, ArgentinaNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Ruscica, Romina
Sakschewski, Boris
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Potsdam Inst Climate Impact Res PIK, Potsdam, GermanyNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Sakschewski, Boris
Papastefanou, Phillip
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Tech Univ Munich TUM, Munich, GermanyNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Papastefanou, Phillip
Viovy, Nicolas
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Lab Sci Climat & Environm LSCE, Gif Sur Yvette, FranceNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Viovy, Nicolas
Thonicke, Kirsten
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Potsdam Inst Climate Impact Res PIK, Potsdam, GermanyNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Thonicke, Kirsten
Sorensson, Anna
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Univ Buenos Aires, Fac Ciencias Exactas & Nat, Buenos Aires, DF, Argentina
Univ Buenos Aires, CONICET, Ctr Invest Mar & Atmosfera CIMA, Buenos Aires, DF, Argentina
UBA, CNRS, IRD,UMI 3351,IFAECI, CONICET,Inst Francoargentino Estudio Clima & Impa, Buenos Aires, DF, ArgentinaNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Sorensson, Anna
Rammig, Anja
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Tech Univ Munich TUM, Munich, GermanyNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil
Rammig, Anja
Cavalcanti, Iracema F. A.
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Natl Inst Space Res INPE, Sao Jose Dos Campos, BrazilNatl Inst Space Res INPE, Sao Jose Dos Campos, Brazil