Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1111/gcb.13442 |
Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison | |
Restrepo-Coupe, Natalia1,2; Levine, Naomi M.3,4; Christoffersen, Bradley O.2,5,6; Albert, Loren P.2; Wu, Jin2,7; Costa, Marcos H.8; Galbraith, David9; Imbuzeiro, Hewlley8; Martins, Giordane10; da Araujo, Alessandro C.10,11; Malhi, Yadvinder S.12; Zeng, Xubin6; Moorcroft, Paul4; Saleska, Scott R.2 | |
2017 | |
发表期刊 | GLOBAL CHANGE BIOLOGY
![]() |
ISSN | 1354-1013 |
EISSN | 1365-2486 |
出版年 | 2017 |
卷号 | 23期号:1 |
文章类型 | Article |
语种 | 英语 |
国家 | Australia; USA; Brazil; England |
英文摘要 | 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 Caxiuana 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 (Jaru 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. Correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments. |
英文关键词 | Amazonia carbon dynamics dynamic global vegetation models ecosystem-climate interactions eddy covariance seasonality tropical forests phenology |
领域 | 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000390218300017 |
WOS关键词 | ENVIRONMENT SIMULATOR JULES ; NET PRIMARY PRODUCTION ; LEAF-AREA INDEX ; INTERANNUAL VARIABILITY ; WATER FLUXES ; PHOTOSYNTHETIC SEASONALITY ; STOMATAL CONDUCTANCE ; TROPICAL FOREST ; RAIN-FOREST ; CLIMATE |
WOS类目 | Biodiversity Conservation ; Ecology ; Environmental Sciences |
WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/17577 |
专题 | 气候变化 资源环境科学 |
作者单位 | 1.Univ Technol Sydney, Plant Funct Biol & Climate Change Cluster, Sydney, NSW, Australia; 2.Univ Arizona, Dept Ecol & Evolutionary Biol, Tucson, AZ 85721 USA; 3.Univ Southern Calif, Dept Biol Sci, Los Angeles, CA 90089 USA; 4.Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USA; 5.Los Alamos Natl Lab, Earth & Environm Sci Div, Los Alamos, NM USA; 6.Univ Arizona, Dept Atmospher Sci, Tucson, AZ USA; 7.Brookhaven Natl Lab, Biol Environm & Climate Sci Dept, Upton, NY 11973 USA; 8.Univ Fed Vicosa, Dept Agr Engn, Vicosa, MG, Brazil; 9.Univ Leeds, Sch Geog, Leeds, W Yorkshire, England; 10.INPA, Manaus, Amazonas, Brazil; 11.Embrapa Amazonia Oriental, Belem, Para, Brazil; 12.Univ Oxford, Environm Change Inst, Sch Geog & Environm, Oxford, England |
推荐引用方式 GB/T 7714 | Restrepo-Coupe, Natalia,Levine, Naomi M.,Christoffersen, Bradley O.,et al. Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison[J]. GLOBAL CHANGE BIOLOGY,2017,23(1). |
APA | Restrepo-Coupe, Natalia.,Levine, Naomi M..,Christoffersen, Bradley O..,Albert, Loren P..,Wu, Jin.,...&Saleska, Scott R..(2017).Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison.GLOBAL CHANGE BIOLOGY,23(1). |
MLA | Restrepo-Coupe, Natalia,et al."Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison".GLOBAL CHANGE BIOLOGY 23.1(2017). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论