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Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data‐model intercomparison
Author(s) -
RestrepoCoupe Natalia,
Levine Naomi M.,
Christoffersen Bradley O.,
Albert Loren P.,
Wu Jin,
Costa Marcos H.,
Galbraith David,
Imbuzeiro Hewlley,
Martins Giordane,
Araujo Alessandro C.,
Malhi Yadvinder S.,
Zeng Xubin,
Moorcroft Paul,
Saleska Scott R.
Publication year - 2017
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/gcb.13442
Subject(s) - environmental science , dry season , seasonality , primary production , amazon rainforest , ecosystem , vegetation (pathology) , atmospheric sciences , carbon cycle , wet season , ecology , biology , geology , medicine , pathology
To predict forest response to long‐term climate change with high confidence requires that dynamic global vegetation models ( DGVM s) 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 , ED 2, JULES , and CLM 3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVM s 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 e ) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA ) exhibited dry‐season declines in GPP and R e consistent with most DGVM s 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. Correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.