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Reducing the uncertainty of parameters controlling seasonal carbon and water fluxes in Chinese forests and its implication for simulated climate sensitivities
Li, Y (Li, Yue)1; Yang, H (Yang, Hui)1; Wang, T (Wang, Tao)2,3; MacBean, N (MacBean, Natasha)4; Bacour, C (Bacour, Cedric)5,6; Ciais, P (Ciais, Philippe)5; Zhang, YP (Zhang, Yiping)7; Zhou, GS (Zhou, Guangsheng)8,9; Piao, SL (Piao, Shilong)1,2,3; Piao, SL
刊名GLOBAL BIOGEOCHEMICAL CYCLES
2017
卷号31期号:8页码:1344-1366
关键词Net Ecosystem Exchange Land-surface Model Global Vegetation Models Earth System Models Eddy-covariance Terrestrial Biosphere Data Assimilation Future Climate Environmental Controls Nonlinear Inversion
DOI10.1002/2017GB005714
文献子类Article
英文摘要Reducing parameter uncertainty of process-based terrestrial ecosystem models (TEMs) is one of the primary targets for accurately estimating carbon budgets and predicting ecosystem responses to climate change. However, parameters in TEMs are rarely constrained by observations from Chinese forest ecosystems, which are important carbon sink over the northern hemispheric land. In this study, eddy covariance data from six forest sites in China are used to optimize parameters of the ORganizing Carbon and Hydrology In Dynamics EcosystEms TEM. The model-data assimilation through parameter optimization largely reduces the prior model errors and improves the simulated seasonal cycle and summer diurnal cycle of net ecosystem exchange, latent heat fluxes, and gross primary production and ecosystem respiration. Climate change experiments based on the optimized model are deployed to indicate that forest net primary production (NPP) is suppressed in response to warming in the southern China but stimulated in the northeastern China. Altered precipitation has an asymmetric impact on forest NPP at sites in water-limited regions, with the optimization-induced reduction in response of NPP to precipitation decline being as large as 61% at a deciduous broadleaf forest site. We find that seasonal optimization alters forest carbon cycle responses to environmental change, with the parameter optimization consistently reducing the simulated positive response of heterotrophic respiration to warming. Evaluations from independent observations suggest that improving model structure still matters most for long-term carbon stock and its changes, in particular, nutrient-and age-related changes of photosynthetic rates, carbon allocation, and tree mortality.
学科主题普通生物学
WOS研究方向Environmental Sciences & Ecology; Geology; Meteorology & Atmospheric Sciences
语种英语
WOS记录号WOS:000409481500009
内容类型期刊论文
源URL[http://ir.itpcas.ac.cn/handle/131C11/8009]  
专题青藏高原研究所_图书馆
通讯作者Piao, SL
作者单位1.Peking Univ, Sinofrench Inst Earth Syst Sci, Coll Urban & Environm Sci, Beijing, Peoples R China.
2.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Alpine Ecol & Biodivers, Beijing, Peoples R China.
3.Chinese Acad Sci, CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China.
4.Univ Arizona, Sch Nat Resources & Environm, Tucson, AZ USA.
5.UVSQ, CEA CNRS, Lab Sci Climat & Environm, Gif Sur Yvette, France.
6.NOVELTIS, Labege, France.
7.Chinese Acad Sci, Xishuangbanna Trop Bot Garden, Key Lab Trop Forest Ecol, Mengla, Peoples R China.
8.Chinese Acad Meteorol Sci, Beijing, Peoples R China.
9.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China.
推荐引用方式
GB/T 7714
Li, Y ,Yang, H ,Wang, T ,et al. Reducing the uncertainty of parameters controlling seasonal carbon and water fluxes in Chinese forests and its implication for simulated climate sensitivities[J]. GLOBAL BIOGEOCHEMICAL CYCLES,2017,31(8):1344-1366.
APA Li, Y .,Yang, H .,Wang, T .,MacBean, N .,Bacour, C .,...&Piao, SL.(2017).Reducing the uncertainty of parameters controlling seasonal carbon and water fluxes in Chinese forests and its implication for simulated climate sensitivities.GLOBAL BIOGEOCHEMICAL CYCLES,31(8),1344-1366.
MLA Li, Y ,et al."Reducing the uncertainty of parameters controlling seasonal carbon and water fluxes in Chinese forests and its implication for simulated climate sensitivities".GLOBAL BIOGEOCHEMICAL CYCLES 31.8(2017):1344-1366.
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