Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison.
| Autor: | Restrepo-Coupe N; Plant Functional Biology and Climate Change Cluster, University of Technology Sydney, Sydney, NSW, Australia.; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA., Levine NM; Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA.; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA., Christoffersen BO; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA.; Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, USA.; Department of Atmospheric Sciences, University of Arizona, Tucson, AZ, USA., Albert LP; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA., Wu J; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA.; Biological, Environmental & Climate Sciences Department, Brookhaven National Lab, Upton, NY, USA., Costa MH; Department of Agricultural Engineering, Federal University of Vicosa, Vicosa, Brazil., Galbraith D; School of Geography, University of Leeds, Leeds, UK., Imbuzeiro H; Department of Agricultural Engineering, Federal University of Vicosa, Vicosa, Brazil., Martins G; Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil., da Araujo AC; Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil.; Embrapa Amazônia Oriental, Belem, Brazil., Malhi YS; Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK., Zeng X; Department of Atmospheric Sciences, University of Arizona, Tucson, AZ, USA., Moorcroft P; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA., Saleska SR; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA. |
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| Jazyk: | angličtina |
| Zdroj: | Global change biology [Glob Chang Biol] 2017 Jan; Vol. 23 (1), pp. 191-208. Date of Electronic Publication: 2016 Aug 29. |
| DOI: | 10.1111/gcb.13442 |
| Abstrakt: | To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, 'soil water stress' and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (R (© 2016 John Wiley & Sons Ltd.) |
| Databáze: | MEDLINE |
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