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Natural and Anthropogenic Drivers of Venerable Tree Distribution on A Tropical Island
  • +6
  • Qian Li,
  • JOSEP PADULLES CUBINO,
  • Mir Muhammad Nizamani,
  • Mei-Hui Zhu,
  • Guo-Qing Wang,
  • Yun-Hao Bai,
  • Jian-Peng Cui,
  • David Lindenmayer,
  • Huafeng Wang
Qian Li
Hainan University Sanya Nanfan Research Institute
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JOSEP PADULLES CUBINO
Masaryk University
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Mir Muhammad Nizamani
Hainan University Sanya Nanfan Research Institute
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Mei-Hui Zhu
Hainan University Sanya Nanfan Research Institute
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Guo-Qing Wang
Hainan University Sanya Nanfan Research Institute
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Yun-Hao Bai
Peking University College of Urban and Environmental Sciences
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Jian-Peng Cui
Hainan University Sanya Nanfan Research Institute
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David Lindenmayer
Australian National University
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Huafeng Wang
Hainan University Sanya Nanfan Research Institute

Corresponding Author:[email protected]

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Abstract

Hainan Province, a tropical island region in China, boasts a rich diversity of natural resources, including a substantial population of venerable trees (VTs). VTs, or venerable trees, represent an important ecological and cultural resource. However, accelerated urbanization and increased human activities pose significant threats to their survival. This study investigates the status of VTs in Hainan Province, analyzing key characteristics such as age, height, diameter at breast height (DBH), and crown width. We evaluated 373 species and 18,459 VTs, examining the natural and anthropogenic factors that drive their distribution. Results indicate a rich and diverse species composition, with a pyramidal age structure, where VT numbers decline with increasing age, suggesting a sufficient reserve of younger VTs. Spatial distribution patterns reveal a clustering of VTs, with higher densities in northern Hainan and reduced presence in coastal and seaward urban areas compared to inland regions. The optimal model identified habitat heterogeneity and environmental energy as the primary drivers of VT species diversity, with MAPR (maximum minus minimum precipitation) emerging as the strongest predictor of species richness. The best combination model showed a greater independent effect on VT species diversity patterns than the other models, which had lower values. Based on these findings, we propose protective measures to address the current threats and preservation challenges facing Hainan’s ancient trees.