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<p>Understanding the drivers shaping biodiversity patterns, including the spatial distribution of ancient trees, is essential for effective conservation planning. Ancient trees are ecologically and culturally important, yet their persistence is increasingly threatened by urban expansion and other human activities. In this study, we compiled a comprehensive dataset of 18,581 records of living ancient trees across Hainan Province, China (70 families, 174 genera, 305 species). After excluding grids with missing environmental variables, 18,459 trees were retained for modeling. We analyzed species composition, age structure, and spatial distribution, and explored their drivers using Ordinary Least Squares (OLS) regression and Spatial Lag Models (SLM). The results showed high species diversity and a pyramidal age structure, indicating a relatively stable population with continuous recruitment into older age classes. Spatially, the trees exhibited significant clustering, with higher densities in western and northern regions and markedly lower concentrations in highly urbanized coastal zones. Habitat heterogeneity, particularly the difference between maximum and minimum annual precipitation (MAPR), emerged as the predominant predictor of species richness and abundance across most age classes. In&#xa0;contrast, the distribution of the youngest ancient trees (Grade Ⅲ) and overall tree density were primarily associated with socioeconomic factors, especially accessibility. Based on these results, our findings suggest that effective conservation of ancient trees requires not only the maintenance of environmental heterogeneity but also careful regulation of human accessibility. The regulation of human accessibility here should aim to strike a balance between effective conservation management and minimizing human interference, especially in rapidly urbanizing landscapes, to ensure their long-term persistence.</p>

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Habitat heterogeneity and socioeconomic factors shape the spatial patterns of ancient trees on Hainan, China

  • 期刊论文

  • 发表日期：

    2026年3月18日

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  • Qian Li,
  • Jiali Yuan,
  • Qingqing Cao,
  • Josep Padullés Cubino,
  • Mir Muhammad Nizamani,
  • Meihui Zhu,
  • Guoqing Wang,
  • Yunhao Bai,
  • Huafeng Wang

摘要

Understanding the drivers shaping biodiversity patterns, including the spatial distribution of ancient trees, is essential for effective conservation planning. Ancient trees are ecologically and culturally important, yet their persistence is increasingly threatened by urban expansion and other human activities. In this study, we compiled a comprehensive dataset of 18,581 records of living ancient trees across Hainan Province, China (70 families, 174 genera, 305 species). After excluding grids with missing environmental variables, 18,459 trees were retained for modeling. We analyzed species composition, age structure, and spatial distribution, and explored their drivers using Ordinary Least Squares (OLS) regression and Spatial Lag Models (SLM). The results showed high species diversity and a pyramidal age structure, indicating a relatively stable population with continuous recruitment into older age classes. Spatially, the trees exhibited significant clustering, with higher densities in western and northern regions and markedly lower concentrations in highly urbanized coastal zones. Habitat heterogeneity, particularly the difference between maximum and minimum annual precipitation (MAPR), emerged as the predominant predictor of species richness and abundance across most age classes. In contrast, the distribution of the youngest ancient trees (Grade Ⅲ) and overall tree density were primarily associated with socioeconomic factors, especially accessibility. Based on these results, our findings suggest that effective conservation of ancient trees requires not only the maintenance of environmental heterogeneity but also careful regulation of human accessibility. The regulation of human accessibility here should aim to strike a balance between effective conservation management and minimizing human interference, especially in rapidly urbanizing landscapes, to ensure their long-term persistence.