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<p>The increasing fragmentation of habitats is accelerating biodiversity loss, particularly in high-altitude cities’ ecologically fragile green spaces (GSs). The scientific assessment of the distribution patterns of biodiversity (DPOB) in the Circum-Erhai Lake region (CELR) is of great significance for sustainability. We identified GSs using fractional vegetation coverage. The InVEST habitat quality (HQ) module assessed HQ, while GIS evaluated ecological sensitivity (ES). Subsequently, using HQ and ES as environmental variables, we applied the MaxEnt Model to predict the suitable habitat of key species. Finally, HQ, ES, and species distribution results served as proxies for biodiversity to predict DPOB. Key findings: (1) CELR’s overall biodiversity is relatively high, showing a “high in forests, low along Erhai shores” pattern. (2) Core GSs are scarce (1.36% of total GS area). (3) The GSs with high quality ecosystem dominate in high-altitude forests (70.60%). (4) The GSs suitable for key species (18.87%) are mainly distributed in flat areas on the west bank of Erhai Lake. (5) The GSs of non suitable area cover 219.23&#xa0;km²(20.19%). Based on the ecosystem and biodiversity levels, we constructed a hierarchical planning framework for GSs around the Erhai Lake area. The findings of this study contribute to identifying priority areas for biodiversity conservation and facilitate the development of sustainable ecological management strategies.</p>

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Analysis of biodiversity distribution patterns around the plateau lake based on the MaxEnt and InVest models

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月1日

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  • Pinjie Luo,
  • Yijiao Li,
  • Hua Xu,
  • Yuhong Song

摘要

The increasing fragmentation of habitats is accelerating biodiversity loss, particularly in high-altitude cities’ ecologically fragile green spaces (GSs). The scientific assessment of the distribution patterns of biodiversity (DPOB) in the Circum-Erhai Lake region (CELR) is of great significance for sustainability. We identified GSs using fractional vegetation coverage. The InVEST habitat quality (HQ) module assessed HQ, while GIS evaluated ecological sensitivity (ES). Subsequently, using HQ and ES as environmental variables, we applied the MaxEnt Model to predict the suitable habitat of key species. Finally, HQ, ES, and species distribution results served as proxies for biodiversity to predict DPOB. Key findings: (1) CELR’s overall biodiversity is relatively high, showing a “high in forests, low along Erhai shores” pattern. (2) Core GSs are scarce (1.36% of total GS area). (3) The GSs with high quality ecosystem dominate in high-altitude forests (70.60%). (4) The GSs suitable for key species (18.87%) are mainly distributed in flat areas on the west bank of Erhai Lake. (5) The GSs of non suitable area cover 219.23 km²(20.19%). Based on the ecosystem and biodiversity levels, we constructed a hierarchical planning framework for GSs around the Erhai Lake area. The findings of this study contribute to identifying priority areas for biodiversity conservation and facilitate the development of sustainable ecological management strategies.