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<p>Narrow endemic species represent irreplaceable components of regional biodiversity, yet their restricted distribution renders them highly susceptible to habitat degradation and climate change. The present investigation employed Ecological Niche Modelling (ENM) using MaxEnt to assess the potential distribution, ecological drivers and conservation implications of two endemic herbs—<i>Helichrysum cutchicum</i> (C.B.Clarke) R.S.Rao &amp; Deshp. and <i>Tephrosia jamnagarensis</i> Santapau—of Gujarat, India. Models were developed using climatic, edaphic and topographic variables along with occurrence records, and evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) and the True Skill Statistic (TSS). The model for <i>H. cutchicum</i> showed strong predictive performance (AUC = 0.959; TSS = 0.802), identifying precipitation seasonality (Bio 15) as the most influential variable, followed by maximum temperature of the warmest month (Bio 05) and annual precipitation (Bio 12). In contrast, the model for <i>T. jamnagarensis</i> was unreliable (AUC = 0.5; TSS = 0.4) due to extreme data scarcity (<i>n</i> = 1), highlighting a key limitation of ENM for data-deficient species. Habitat suitability mapping revealed that 17,592.85&#xa0;km² (9.69% of Gujarat) is potentially suitable for <i>H. cutchicum</i>, primarily in the Kachchh and Devbhumi Dwarka districts. However, only 9.39% of this suitable area overlaps with existing protected areas, indicating substantial conservation gaps. Suitable habitats intersect four wildlife sanctuaries, offering opportunities for in situ conservation enhancement, while extensive suitable areas outside protected zones require landscape-level planning and community-based management. These spatial outputs provide a vital scientific basis for prioritising habitat restoration and extending conservation efforts to safeguard the endemic flora of Gujarat.</p>

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Unveiling the secret lives of endemic plants and understanding exclusive species of Gujarat, India through ecological niche modelling

  • 期刊论文

  • 发表日期：

    2026年3月2日

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  • Pankajkumar C. Prajapati,
  • G. Sandhya Kiran,
  • Agradeep Mohanta,
  • Kavi K. Oza,
  • Shrishti Rajput

摘要

Narrow endemic species represent irreplaceable components of regional biodiversity, yet their restricted distribution renders them highly susceptible to habitat degradation and climate change. The present investigation employed Ecological Niche Modelling (ENM) using MaxEnt to assess the potential distribution, ecological drivers and conservation implications of two endemic herbs—Helichrysum cutchicum (C.B.Clarke) R.S.Rao & Deshp. and Tephrosia jamnagarensis Santapau—of Gujarat, India. Models were developed using climatic, edaphic and topographic variables along with occurrence records, and evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) and the True Skill Statistic (TSS). The model for H. cutchicum showed strong predictive performance (AUC = 0.959; TSS = 0.802), identifying precipitation seasonality (Bio 15) as the most influential variable, followed by maximum temperature of the warmest month (Bio 05) and annual precipitation (Bio 12). In contrast, the model for T. jamnagarensis was unreliable (AUC = 0.5; TSS = 0.4) due to extreme data scarcity (n = 1), highlighting a key limitation of ENM for data-deficient species. Habitat suitability mapping revealed that 17,592.85 km² (9.69% of Gujarat) is potentially suitable for H. cutchicum, primarily in the Kachchh and Devbhumi Dwarka districts. However, only 9.39% of this suitable area overlaps with existing protected areas, indicating substantial conservation gaps. Suitable habitats intersect four wildlife sanctuaries, offering opportunities for in situ conservation enhancement, while extensive suitable areas outside protected zones require landscape-level planning and community-based management. These spatial outputs provide a vital scientific basis for prioritising habitat restoration and extending conservation efforts to safeguard the endemic flora of Gujarat.