通过使用可解释的机器学习方法,确定人类活动和自然因素对中国鸟类物种丰富的综合影响
Qi Liu1, Zeqiang Wu1, Shaoyan Feng1
1State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing, 210023, China.
Journal of environmental management
|February 12, 2025
概括
人类活动威胁着鸟类的生存. 这项研究使用先进的建模来确定中国鸟类物种丰富的关键驱动因素,揭示了GDP和土地利用等因素对保护工作至关重要.
科学领域:
- 生态生态学 生态生态学
- 生物多样性保护 生物多样性保护
- 机器学习在生态学中的应用
背景情况:
- 升级的气候变化和城市化对鸟类物种的生存构成重大威胁.
- 了解环境和人类对鸟类物种丰富性的影响,对于有效的保护战略至关重要.
- 以前的鸟类生物多样性建模通常依赖于传统的统计或单模型方法.
研究的目的:
- 用机器学习和统计建模的新组合,预测和解释中国的鸟类物种丰富性.
- 确定影响鸟类物种丰富性的关键自然和人为因素.
- 为保护鸟类生物多样性提供基于数据的建议.
主要方法:
- 利用来自中国的综合公民科学鸟类数据库.
- 采用一种新的综合方法,结合了极端梯度提升 (XGBoost),夏普利添加式扩展 (SHAP) 和结构方程建模 (SEM).
- 将XGBoost的性能与其他四种用于预测鸟类物种丰富性的模型进行了比较.
主要成果:
- 在XGBoost模型中,鸟类物种丰富度的预测性能优越 (测试R2为0.84).
- 影响鸟类物种丰富性的关键因素包括GDP,风速,经度,农田面积,污水处理率,GDP增长,森林面积和次要产业比率.
- 结构方程建模证实了自然和人为因素对鸟类物种丰富性的相互作用作用.
结论:
- 这项研究强调了迫切需要保护鸟类的必要性,这是罕见或危物种的数量证明的.
- 综合经济发展和环境管理对于有效的生物多样性政策至关重要.
- 建议包括利用GDP为政策,植树,优化农业和改善污水处理以改善鸟类生态系统健康.
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