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DOI	10.1016/j.agrformet.2019.05.005
	A data-conditioned stochastic parameterization of temporal plant trait variability in an ecohydrological model and the potential for plasticity
	Liu, Shaoqing 1; Ng, Gene-Hua Crystal 1,2
通讯作者	Liu, Shaoqing
来源期刊	AGRICULTURAL AND FOREST METEOROLOGY
ISSN	0168-1923
EISSN	1873-2240
出版年	2019
卷号	274 页码:184-194
英文摘要	Recent studies have begun to incorporate spatially variable plant traits into ecohydrological models, but temporal trait variability remains under-studied. Because of its potential to influence ecosystem function, representing stress-induced temporal trait variability into models should be a research priority. We present a new data-model integration approach to identify temporal variability in plant traits and generate stochastic-in-time model parameterizations. The data-conditioned stochastic parameterization was developed within the CLM 4.5 model utilizing global trait data as prior information and tested for a desert shrubland site. A synthetic experiment demonstrated that the framework successfully uncovered time-varying trait values. Using in-situ ecohydrological observations, we found the specific leaf area (SLA) for a common broadleaf-evergreen-shrub to be temporally dynamic and significantly correlated with seasonal water availability. We constructed a regression model based on the data-conditioned SLA estimates and soil wetness and used it to generate stochastic SLA parameters for a 40-year hindcast simulation. The stochastic-in-time SLA parameters resulted in greater productivity and water use efficiency than a standard static parameter. Our stochastic-in-time method can help evaluate stress-induced trait plasticity that extends our understanding beyond sparse spatial plant trait database and improve our ability to simulate carbon and water fluxes under global change.
英文关键词	Plant trait Data-model integration Ecohydrological models Stochastic parameterization Temporal trait variability
类型	Article
语种	英语
国家	USA
收录类别	SCI-E
WOS记录号	WOS:000471356600017
WOS关键词	GROSS PRIMARY PRODUCTION ; ENSEMBLE KALMAN FILTER ; PHOTOSYNTHETIC PARAMETERS ; LEAF TRAITS ; HYDROLOGIC CHARACTERIZATION ; INTERANNUAL VARIABILITY ; PHENOTYPIC PLASTICITY ; STOMATAL CONDUCTANCE ; DATA ASSIMILATION ; VEGETATION MODEL
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/2XILL650/213960
作者单位	1.Univ Minnesota Twin Cities, Dept Earth Sci, Minneapolis, MN 55455 USA; 2.Univ Minnesota Twin Cities, St Anthony Falls Lab, Minneapolis, MN USA
推荐引用方式 GB/T 7714	Liu, Shaoqing,Ng, Gene-Hua Crystal. A data-conditioned stochastic parameterization of temporal plant trait variability in an ecohydrological model and the potential for plasticity[J],2019,274:184-194.
APA	Liu, Shaoqing,&Ng, Gene-Hua Crystal.(2019).A data-conditioned stochastic parameterization of temporal plant trait variability in an ecohydrological model and the potential for plasticity.AGRICULTURAL AND FOREST METEOROLOGY,274,184-194.
MLA	Liu, Shaoqing,et al."A data-conditioned stochastic parameterization of temporal plant trait variability in an ecohydrological model and the potential for plasticity".AGRICULTURAL AND FOREST METEOROLOGY 274(2019):184-194.