在墨西哥的黑熊 (Ursus americanus) 的道路杀伤风险模型
Zuleyma Zarco-González1, Octavio Monroy-Vilchis2
1Tecnológico Nacional de México/Instituto Tecnológico de Toluca, C.P. 52149, Metepec, México.
Environmental monitoring and assessment
|December 26, 2023
概括
在墨西哥,公路上的屠杀对黑熊构成越来越大的威胁. 这项研究使用MaxEnt模型确定了高风险路段,这对于有针对性的保护和驾驶员安全至关重要.
科学领域:
- 野生动物保护 野生动物保护
- 道路生态学 道路生态学
- 空间分析 空间分析
背景情况:
- 道路杀伤对野生动物种群构成重大威胁,包括墨西哥的黑熊 (Ursus americanus).
- 经济和资源的局限性阻碍了全面的道路杀戮监测和缓解努力.
- 越来越多的黑熊在人居住区附近存在,以及道路事故需要集中研究.
研究的目的:
- 通过使用预测建模,识别高黑熊路杀风险的道路段的特征.
- 绘制这些高风险地区的地图,特别是在受保护的自然区域内.
- 为黑熊提供有针对性的保护战略和道路安全措施提供信息.
主要方法:
- 一个单一的MaxEnt模型被用来预测黑熊道路杀伤风险.
- 数据包括83条道路杀伤记录 (2008-2022) 和16个环境,道路和人类变量.
- 模型性能使用曲线下面面积 (AUC) 和杰克刀分析进行了验证.
主要成果:
- 马克森特模型表现良好 (AUC = 0.96).
- 影响道路杀伤风险的关键因素包括距离水体,保护区,灌木,排水和速度限制的距离.
- 大约3883.25公里的道路被确定为高风险,其中373.10公里位于保护区内.
结论:
- 该研究为优先考虑特定道路段的保护工作提供了关键数据.
- 对于高风险地区,建议使用低成本的缓解策略,如减速和标志.
- 研究结果支持将道路对黑熊种群的影响降至最低,并提高驾驶员的安全.
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