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Plant Water Uptake Thresholds Inferred From Satellite Soil Moisture

Bassiouni, Maoya and Good, Stephen P. and Still, Christopher J. and Higgins, Chad W. (2020). Plant Water Uptake Thresholds Inferred From Satellite Soil Moisture. Geophysical Research Letters. 47 , e2020GL087077 , 1-12
[Research article]

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Empirical functions are widely used in hydrological, agricultural, and Earth system models to parameterize plant water uptake. We infer soil water potentials at which uptake is downregulated from its well‐watered rate and at which uptake ceases, in biomes with <60% woody vegetation at 36‐km grid resolution. We estimate thresholds through Bayesian inference using a stochastic soil water balance framework to construct theoretical soil moisture probability distributions consistent with empirical distributions derived from satellite soil moisture observations. The global median Nash–Sutcliffe efficiency between empirical soil moisture distributions and theoretical distributions using reference constants, inferred median parameters per biome, and spatially variable inferred parameters are 0.38, 0.59, and 0.8, respectively. Spatially variable thresholds capture location‐specific vegetation and climate characteristics and can be connected to biome‐level water uptake strategies. Results demonstrate that satellite soil moisture probability distributions encode information, valuable to understanding biome‐level ecohydrological adaptation and resistance to climate variability.

Authors/Creators:Bassiouni, Maoya and Good, Stephen P. and Still, Christopher J. and Higgins, Chad W.
Title:Plant Water Uptake Thresholds Inferred From Satellite Soil Moisture
Series Name/Journal:Geophysical Research Letters
Year of publishing :2020
Article number:e2020GL087077
Number of Pages:12
Publisher:Wiley, American Geophysical Union
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Agricultural Science
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Type of IDID
ID Code:17134
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Crop Production Ecology
Deposited By: SLUpub Connector
Deposited On:26 Jun 2020 08:18
Metadata Last Modified:15 Jan 2021 19:17

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