Global critical soil moisture thresholds of plant water stress. Fu, Z., Ciais, P., Wigneron, J., Gentine, P., Feldman, A. F., Makowski, D., Viovy, N., Kemanian, A. R., Goll, D. S., Stoy, P. C., Prentice, I. C., Yakir, D., Liu, L., Ma, H., Li, X., Huang, Y., Yu, K., Zhu, P., Li, X., Zhu, Z., Lian, J., & Smith, W. K. Nature Communications, 15(1):4826, June, 2024.
Global critical soil moisture thresholds of plant water stress [link]Paper  doi  abstract   bibtex   
Abstract During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θ crit ). Better quantification of θ crit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θ crit . We find an average global θ crit of 0.19 m 3 /m 3 , varying from 0.12 m 3 /m 3 in arid ecosystems to 0.26 m 3 /m 3 in humid ecosystems. θ crit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θ crit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θ crit , has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.
@article{fu_global_2024,
	title = {Global critical soil moisture thresholds of plant water stress},
	volume = {15},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-024-49244-7},
	doi = {10.1038/s41467-024-49244-7},
	abstract = {Abstract
            
              During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θ
              crit
              ). Better quantification of θ
              crit
              is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θ
              crit
              . We find an average global θ
              crit
              of 0.19 m
              3
              /m
              3
              , varying from 0.12 m
              3
              /m
              3
              in arid ecosystems to 0.26 m
              3
              /m
              3
              in humid ecosystems. θ
              crit
              simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θ
              crit
              reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θ
              crit
              , has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.},
	language = {en},
	number = {1},
	urldate = {2024-11-26},
	journal = {Nature Communications},
	author = {Fu, Zheng and Ciais, Philippe and Wigneron, Jean-Pierre and Gentine, Pierre and Feldman, Andrew F. and Makowski, David and Viovy, Nicolas and Kemanian, Armen R. and Goll, Daniel S. and Stoy, Paul C. and Prentice, Iain Colin and Yakir, Dan and Liu, Liyang and Ma, Hongliang and Li, Xiaojun and Huang, Yuanyuan and Yu, Kailiang and Zhu, Peng and Li, Xing and Zhu, Zaichun and Lian, Jinghui and Smith, William K.},
	month = jun,
	year = {2024},
	pages = {4826},
}
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