Changes in vegetation-water response in the Sahel-Sudan during recent decades

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Study region: The Africa Sahel-Sudan region, defined by annual rainfall between 150 and 1200 mm. Study focus: Understanding the mechanism of vegetation response to water availability could help mitigate the potential adverse effects of climate change on global dryland ecosystems. In the Sahel-Sudan region, spatio-temporal changes and drivers of the vegetation-water response remain unclear. This study employs long-term satellite water and vegetation products as proxies of water availability and vegetation productivity to analyze changes in vegetation-water sensitivity and the cumulative effect duration (CED) representing a measure of the legacy effect of the impact of water constraints on vegetation. A random forest model was subsequently used to analyze potential climatic drivers of the observed vegetation response. New hydrological insights for the region: During 1982–2016 we found a significant decrease (p < 0.05) in the sensitivity of vegetation productivity to water constraints in 26% of the Sahel-Sudan region, while 9% of the area showed a significantly increased sensitivity, mainly in the sub-humid zone. We further showed that CED significantly increased and decreased, respectively in around 9% of the study area in both cases. Our climatic driver attribution analysis suggested the existence of varying underlying mechanisms governing vegetation productivity in response to water deficit across the Sahel-Sudan dryland ecosystems. Our findings emphasize the need for diverse strategies in sustainable ecosystem management to effectively address these varying mechanisms.

OriginalsprogEngelsk
Artikelnummer101672
TidsskriftJournal of Hydrology: Regional Studies
Vol/bind52
Antal sider10
ISSN2214-5818
DOI
StatusUdgivet - 2024

Bibliografisk note

Funding Information:
This work was supported by the China Scholarship Council [grant number 20196400012]. R.F. Acknowledge support by the Villum Foundation through the project ‘Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics’ [DeReEco, grant number 34306] and by the Independent Research Fund Denmark [grant number 2032-00026B]. This work was also supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme [grant number 947757 TOFDRY] and a DFF Sapere Aude [grant number 9064-00049B].

Funding Information:
This work was supported by the China Scholarship Council [grant number 20196400012 ]. R.F. Acknowledge support by the Villum Foundation through the project ‘Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics’ [DeReEco, grant number 34306 ] and by the Independent Research Fund Denmark [grant number 2032-00026B ]. This work was also supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme [grant number 947757 TOFDRY ] and a DFF Sapere Aude [grant number 9064-00049B ].

Publisher Copyright:
© 2024 The Authors

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