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<p>The White-rumped Vulture is a critically endangered species, facing rapid population declines across South and Southeast Asia due to habitat loss, anthropogenic disturbances, and toxicological pressures. This study uses species distribution modeling (SDM) to assess the current and future habitat suitability for the White-rumped Vulture across its geographic range in the region. We employed MaxEnt, a machine learning algorithm, to model habitat suitability based on 1,248 occurrence records from 2018 to 2024 and 19 bioclimatic, geomorphometric, and anthropogenic variables. The model achieved an excellent Area Under the Curve (AUC) value of 0.937, indicating strong predictive performance. Our results indicate that approximately 20.74% of the study area is currently classified as highly suitable habitat, with India, Pakistan, and Nepal hosting the most significant extents. However, projections for 2040, 2070, and 2100 under two Shared Socioeconomic Pathways (SSPs) SSP 126 (low emission) and SSP 370 (high emission) predict significant habitat loss, particularly under SSP 370, where highly suitable habitat may decrease by up to 60% by 2100. The study also identifies substantial gaps in conservation infrastructure, with over 88% of the highly suitable habitat unprotected. This study highlights the urgent need for region-specific conservation strategies that integrate habitat protection, restoration, and the mitigation of toxicological risks to ensure the long-term survival of the White-rumped Vulture.</p> Graphical Abstract <p></p>

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Multi-scale modeling of habitat suitability and human-induced risk for the critically endangered white-rumped vulture (Gyps bengalensis) in South and Southeast Asia

  • 期刊论文

  • 发表日期：

    2026年5月28日

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  • Gulzaman William,
  • Zafeer Saqib,
  • Abdul Qadir,
  • Ayesha Siddiqua,
  • Zaki ul Zaman Asam,
  • Mujahid Farid,
  • Muhammad Jamshed Iqbal Chaudhry

摘要

The White-rumped Vulture is a critically endangered species, facing rapid population declines across South and Southeast Asia due to habitat loss, anthropogenic disturbances, and toxicological pressures. This study uses species distribution modeling (SDM) to assess the current and future habitat suitability for the White-rumped Vulture across its geographic range in the region. We employed MaxEnt, a machine learning algorithm, to model habitat suitability based on 1,248 occurrence records from 2018 to 2024 and 19 bioclimatic, geomorphometric, and anthropogenic variables. The model achieved an excellent Area Under the Curve (AUC) value of 0.937, indicating strong predictive performance. Our results indicate that approximately 20.74% of the study area is currently classified as highly suitable habitat, with India, Pakistan, and Nepal hosting the most significant extents. However, projections for 2040, 2070, and 2100 under two Shared Socioeconomic Pathways (SSPs) SSP 126 (low emission) and SSP 370 (high emission) predict significant habitat loss, particularly under SSP 370, where highly suitable habitat may decrease by up to 60% by 2100. The study also identifies substantial gaps in conservation infrastructure, with over 88% of the highly suitable habitat unprotected. This study highlights the urgent need for region-specific conservation strategies that integrate habitat protection, restoration, and the mitigation of toxicological risks to ensure the long-term survival of the White-rumped Vulture.

Graphical Abstract