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AI-Driven Conservation of the Endangered Twisted Yew ( Taxus contorta Griff.) in the Western Himalaya

Author

Listed:
  • Salahud Din

    (Center for Plant Sciences and Biodiversity, University of Swat, Charbagh 19120, Pakistan)

  • Haidar Ali

    (Center for Plant Sciences and Biodiversity, University of Swat, Charbagh 19120, Pakistan)

  • Thomas Panagopoulos

    (Faculty of Science and Technology, University of Algarve, Campus de Gambelas, 8000 Faro, Portugal)

  • Jan Alam

    (Department of Botany, Hazara University, Mansehra 21300, Pakistan)

  • Saira Malik

    (Center for Plant Sciences and Biodiversity, University of Swat, Charbagh 19120, Pakistan)

  • Hassan Sher

    (Center for Plant Sciences and Biodiversity, University of Swat, Charbagh 19120, Pakistan)

Abstract

Conserving the threatened West Himalayan endemic T. contorta (Taxaceae) is critical due to extinction risks from skewed male- or female-only populations. This study employs ChatGPT-driven artificial intelligence (AI) analysis for textual synthesis and preliminary hypothesis generation to identify favorable propagation sites for T. contorta within the Swat district of Pakistan. Over three years (2019–2021), eleven male- or female-only populations of T. contorta were surveyed. Environmental data from NASA POWER were analyzed using ChatGPT 3.5 to predict suitable propagation sites, which were then mapped in Google Earth Pro. PCA and hierarchical clustering were applied to identify key environmental variables. Out of 63 generated points, 58 were accurately located in Swat with 92% geographic accuracy, while species-specific general knowledge accuracy was 100%. All points fell within the pre-established T. contorta spatial range in Pakistan, with 21 unique sites meeting optimal conditions. Field surveys confirmed 16 new populations. These findings underscore the promising role of AI-driven analysis in conservation planning by identifying and supporting habitat restoration efforts. A bidirectional integration of AI and SDM, combined with remote sensing technologies, represents a novel approach for the effective conservation of endangered plant species.

Suggested Citation

  • Salahud Din & Haidar Ali & Thomas Panagopoulos & Jan Alam & Saira Malik & Hassan Sher, 2025. "AI-Driven Conservation of the Endangered Twisted Yew ( Taxus contorta Griff.) in the Western Himalaya," Sustainability, MDPI, vol. 17(19), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8541-:d:1756472
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    References listed on IDEAS

    as
    1. Shawkat Ali & Haidar Ali & Omid Ghadirian Baharanchi & Hassan Sher & Rasoul Yousefpour, 2024. "Investigating Endemic Species Conservation Hotspots Based on Species Distribution Models in Swat Region, Hindu Kush Pakistan," Land, MDPI, vol. 13(6), pages 1-18, May.
    2. T. W. Crowther & H. B. Glick & K. R. Covey & C. Bettigole & D. S. Maynard & S. M. Thomas & J. R. Smith & G. Hintler & M. C. Duguid & G. Amatulli & M.-N. Tuanmu & W. Jetz & C. Salas & C. Stam & D. Piot, 2015. "Mapping tree density at a global scale," Nature, Nature, vol. 525(7568), pages 201-205, September.
    3. Shcheglovitova, Mariya & Anderson, Robert P., 2013. "Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes," Ecological Modelling, Elsevier, vol. 269(C), pages 9-17.
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