Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison

Restrepo-Coupe, Natalia; Levine, Naomi M.; Christoffersen, Bradley O.; Albert, Loren P.; Wu, Jin; Costa, Marcos H.; Galbraith, David; Imbuzeiro, Hewlley; Martins, Giordane; da Araujo, Alessandro C.; Malhi, Yadvinder S.; Zeng, Xubin; Moorcroft, Paul; Saleska, Scott R.

doi:10.1111/gcb.13442

Title: Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison

Journal Article · Mon Aug 29 00:00:00 EDT 2016 · Global Change Biology

DOI:https://doi.org/10.1111/gcb.13442· OSTI ID:1341704

^[1];

^[2]; Christoffersen, Bradley O. ^[3]; Albert, Loren P. ^[4]; Wu, Jin ^[5]; Costa, Marcos H. ^[6]; Galbraith, David ^[7]; Imbuzeiro, Hewlley ^[6]; Martins, Giordane ^[8]; da Araujo, Alessandro C. ^[9]; Malhi, Yadvinder S. ^[10]; Zeng, Xubin ^[11]; Moorcroft, Paul ^[12]; Saleska, Scott R. ^[4]

Univ. of Technology Sydney, Sydney, NSW (Australia). Plant Functional Biology and Climate Change Cluster; Univ. of Arizona, Tucson, AZ (United States). Dept. of Ecology and Evolutionary Biology
Univ. of Southern California, Los Angeles, CA (United States). Dept. of Biological Sciences; Harvard Univ., Cambridge, MA (United States). Dept. of Organismic and Evolutionary Biology
Univ. of Arizona, Tucson, AZ (United States). Dept. of Ecology and Evolutionary Biology; Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. of Arizona, Tucson, AZ (United States). Dept. of Atmospheric Sciences
Univ. of Arizona, Tucson, AZ (United States). Dept. of Ecology and Evolutionary Biology
Univ. of Arizona, Tucson, AZ (United States). Dept. of Ecology and Evolutionary Biology; Brookhaven National Lab, Upton, NY (United States). Biological, Environmental & Climate Sciences Dept.
Federal Univ. of Vicosa, Vicosa (Brazil). Dept. of Agricultural Engineering
Univ. of Leeds, Leeds (United Kingdom). School of Geography
Inst. Nacional de Pesquisas da Amazonia (INPA), Manaus (Brazil)
Inst. Nacional de Pesquisas da Amazonia (INPA), Manaus (Braz; Embrapa Amazonia Oriental, Belem (Brazil)
Univ. of Oxford (United Kingdom). Environmental Change Inst.
Univ. of Arizona, Tucson, AZ (United States). Dept. of of Atmospheric Sciences
Harvard Univ., Cambridge, MA (United States). Dept. of Organismic and Evolutionary Biology

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 (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.

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Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC00112704

OSTI ID:: 1341704

Report Number(s):: BNL-113452-2017-JA; R&D Project: 21087; YN0100000

Journal Information:: Global Change Biology, Vol. 23, Issue 1; ISSN 1354-1013

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 97 works

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