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ABSTRACT Groundwater‐dependent vegetation (GDV) plays a critical role as a natural barrier against aeolian erosion in dryland ecosystems. Despite its ecological significance, the full extent of GDV's functions remains not yet fully understood due to limitations in field data availability, spatial variability, and intricate groundwater‐vegetation dynamics. This study employs machine learning techniques to distinguish GDVs from non‐GDVs in the middle to lower reaches of the hyper‐arid Shule River Basin (China), generating a comprehensive GDV map. Additionally, using the revised wind erosion equation model, we quantified their sand fixation capacity (represented by sand fixation amount and rate) over the period 2011–2022. Our findings reveal that GDVs, occupying a larger area than non‐GDVs, play a stabilizing and pivotal role in sand fixation by contributing over 65% of the region's vegetation total sand fixation amount. Specifically, GDVs' average annual fixation amount (418.18 t) and rate (5.10%) both substantially outperform those of non‐GDVs (207.93 t and 2.66%, respectively). Groundwater availability exerts a substantial influence on GDVs' sand fixation amount, as indicated by the significant negative correlation between groundwater depth and sand fixation amount ( r = −0.37, p < 0.05). Certain deep‐rooted species (e.g., Tamarix ramosissima , Populus euphratica ) demonstrate exceptional sand‐fixation ability, as evidenced by the abundant fine sediments trapped under their canopies. The study underscores the importance of prioritizing the identification and preservation of large, high‐functioning GDV units. By strategically leveraging GDV's inherent ecological advantages, this approach provides a sustainable pathway to effectively combat desertification and enhance ecosystem resilience in hyper‐arid regions.
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Yuanyuan Ma
Chinese Academy of Sciences
Hu Liu
Chinese Academy of Sciences
Lingfei Zhong
Northwest Normal University
Land Degradation and Development
Chinese Academy of Sciences
University of Chinese Academy of Sciences
Istanbul Technical University
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Ma et al. (Tue,) studied this question.
synapsesocial.com/papers/6a2261bef1cd006d1cff4e37 — DOI: https://doi.org/10.1002/ldr.70685
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