Observation-based assessment of secondary water effects on seasonal vegetation decay across Africa.

Autor:	Küçük Ç; Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.; Hydro-Climate Extremes Lab (H-CEL), Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium., Koirala S; Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany., Carvalhais N; Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.; Center for Environmental and Sustainability Research (CENSE), Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, Portugal., Miralles DG; Hydro-Climate Extremes Lab (H-CEL), Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium., Reichstein M; Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany., Jung M; Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.
Jazyk:	angličtina
Zdroj:	Frontiers in big data [Front Big Data] 2022 Sep 09; Vol. 5, pp. 967477. Date of Electronic Publication: 2022 Sep 09 (Print Publication: 2022).
DOI:	10.3389/fdata.2022.967477
Abstrakt:	Local studies and modeling experiments suggest that shallow groundwater and lateral redistribution of soil moisture, together with soil properties, can be highly important secondary water sources for vegetation in water-limited ecosystems. However, there is a lack of observation-based studies of these terrain-associated secondary water effects on vegetation over large spatial domains. Here, we quantify the role of terrain properties on the spatial variations of dry season vegetation decay rate across Africa obtained from geostationary satellite acquisitions to assess the large-scale relevance of secondary water effects. We use machine learning based attribution to identify where and under which conditions terrain properties related to topography, water table depth, and soil hydraulic properties influence the rate of vegetation decay. Over the study domain, the machine learning model attributes about one-third of the spatial variations of vegetation decay rates to terrain properties, which is roughly equally split between direct terrain effects and interaction effects with climate and vegetation variables. The importance of secondary water effects increases with increasing topographic variability, shallower groundwater levels, and the propensity to capillary rise given by soil properties. In regions with favorable terrain properties, more than 60% of the variations in the decay rate of vegetation are attributed to terrain properties, highlighting the importance of secondary water effects on vegetation in Africa. Our findings provide an empirical assessment of the importance of local-scale secondary water effects on vegetation over Africa and help to improve hydrological and vegetation models for the challenge of bridging processes across spatial scales. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Küçük, Koirala, Carvalhais, Miralles, Reichstein and Jung.)
Databáze:	MEDLINE
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