干旱区生态环境知识资源中心(Arid): Environment-sensitivity functions for gross primary productivity in light use efficiency models

Arid

DOI	10.1016/j.agrformet.2021.108708
	Environment-sensitivity functions for gross primary productivity in light use efficiency models
	Bao, Shanning; Wutzler, Thomas; Koirala, Sujan; Cuntz, Matthias; Ibrom, Andreas; Besnard, Simon; Walther, Sophia; Sigut, Ladislav; Moreno, Alvaro; Weber, Ulrich; Wohlfahrt, Georg; Cleverly, Jamie; Migliavacca, Mirco; Woodgate, William; Merbold, Lutz; Veenendaal, Elmar; Carvalhais, Nuno
通讯作者	Bao, SN ; Carvalhais, N (corresponding author), Max Planck Inst Biogeochem, Dept Biogeochem Integrat, Jena, Germany. ; Carvalhais, N (corresponding author), Univ Nova Lisboa, Fac Ciencias & Tecnol, Dept Ciencias & Engn Ambiente, FCT,DCEA, P-2829516 Caparica, Portugal.
来源期刊	AGRICULTURAL AND FOREST METEOROLOGY
ISSN	0168-1923
EISSN	1873-2240
出版年	2022
卷号	312
英文摘要	The sensitivity of photosynthesis to environmental changes is essential for understanding carbon cycle responses to global climate change and for the development of modeling approaches that explains its spatial and temporal variability. We collected a large variety of published sensitivity functions of gross primary productivity (GPP) to different forcing variables to assess the response of GPP to environmental factors. These include the responses of GPP to temperature; vapor pressure deficit, some of which include the response to atmospheric CO2 concentrations; soil water availability (W); light intensity; and cloudiness. These functions were combined in a full factorial light use efficiency (LUE) model structure, leading to a collection of 5600 distinct LUE models. Each model was optimized against daily GPP and evapotranspiration fluxes from 196 FLUXNET sites and ranked across sites based on a bootstrap approach. The GPP sensitivity to each environmental factor, including CO2 fertilization, was shown to be significant, and that none of the previously published model structures performed as well as the best model selected. From daily and weekly to monthly scales, the best model's median Nash-Sutcliffe model efficiency across sites was 0.73, 0.79 and 0.82, respectively, but poorer at annual scales (0.23), emphasizing the common limitation of current models in describing the interannual variability of GPP. Although the best global model did not match the local best model at each site, the selection was robust across ecosystem types. The contribution of light saturation and cloudiness to GPP was observed across all biomes (from 23% to 43%). Temperature and W dominates GPP and LUE but responses of GPP to temperature and W are lagged in cold and arid ecosystems, respectively. The findings of this study provide a foundation towards more robust LUE-based estimates of global GPP and may provide a benchmark for other empirical GPP products.
英文关键词	Carbon assimilation Radiation use efficiency Model comparison Model equifinality Diffuse fraction Sensitivity formulations Randomly sampled sites Temporal scales
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:000724254300003
WOS关键词	APPROXIMATE BAYESIAN COMPUTATION ; NET PRIMARY PRODUCTIVITY ; WATER-VAPOR EXCHANGE ; LAND-COVER CHANGE ; CARBON-DIOXIDE ; EDDY COVARIANCE ; TERRESTRIAL ECOSYSTEMS ; INTERANNUAL VARIABILITY ; TEMPERATURE RESPONSE ; DIFFUSE-RADIATION
WOS类目	Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS研究方向	Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/374493
作者单位	[Bao, Shanning; Wutzler, Thomas; Koirala, Sujan; Besnard, Simon; Walther, Sophia; Sigut, Ladislav; Weber, Ulrich; Migliavacca, Mirco; Carvalhais, Nuno] Max Planck Inst Biogeochem, Dept Biogeochem Integrat, Jena, Germany; [Cuntz, Matthias] Univ Lorraine, UMR Silva, INRAE, AgroParisTech, F-54000 Nancy, France; [Ibrom, Andreas] Tech Univ Denmark DTU, Environm Engn, Lyngby, Denmark; [Besnard, Simon] Wageningen Univ & Res, Lab Geoinformat Sci & Remote Sensing, Wageningen, Netherlands; [Sigut, Ladislav] Czech Acad Sci, Dept Matter & Energy Fluxes, Global Change Res Inst, Belidla 986-4a, Brno 60300, Czech Republic; [Moreno, Alvaro] Univ Valencia, Image Proc Lab, Valencia, Spain; [Wohlfahrt, Georg] Univ Innsbruck, Dept Ecol, Innsbruck, Austria; [Cleverly, Jamie] Univ Technol Sydney, Sch Life Sci, Terr Ecosyst Res Network, Broadway, NSW, Australia; [Woodgate, William] Univ Queensland, Sch Earth & Environm Sci, St Lucia, Qld 4067, Australia; [Woodgate, William] CSIRO, Land & Water, Canberra, ACT 2601, Australia; [M...
推荐引用方式 GB/T 7714	Bao, Shanning,Wutzler, Thomas,Koirala, Sujan,et al. Environment-sensitivity functions for gross primary productivity in light use efficiency models[J],2022,312.
APA	Bao, Shanning.,Wutzler, Thomas.,Koirala, Sujan.,Cuntz, Matthias.,Ibrom, Andreas.,...&Carvalhais, Nuno.(2022).Environment-sensitivity functions for gross primary productivity in light use efficiency models.AGRICULTURAL AND FOREST METEOROLOGY,312.
MLA	Bao, Shanning,et al."Environment-sensitivity functions for gross primary productivity in light use efficiency models".AGRICULTURAL AND FOREST METEOROLOGY 312(2022).