Context

Identifying risk zones for wildlife-vehicle incidents is essential for creating effective mitigation efforts on major road networks. Wildlife-vehicle collision data are often used to identify hotspot areas without consideration of species spatial distributions.

Objectives

Evaluating both can reveal spatiotemporal patterns that can improve mitigation success.

Methods

We summarized elk-vehicle incident (EVI) data on State Route 20 (SR 20) in Washington State between 2012 and 2019. We also collared 23 elk residing in the vicinity of SR 20 and used GPS location data to identify home ranges and road crossings. We compared EVI and elk road crossing data to identify hotspot locations on SR 20 to help inform mitigation.

Results

Our EVI and elk crossing data had a non-random distribution along a 38 km section of SR 20 associated with the 95% home ranges of 8 female elk sub-herds. We found EVI data alone were an effective indicator of elk spatial distribution and movement in relation to collision hotspots along SR 20. Our results also indicated a strong association between elk crossings and EVIs by milepost. While the spatial distribution of elk sub-herds was a good predictor of EVI risk zones, EVI frequency was not associated with an increase in elk population.

Conclusions

Classifying EVI and road crossing distributions as high risk zones is the first step preceding mitigation and protection measures to prevent elk-vehicle collisions. Specific identification of hotspots will result in more effective and successful installations of high cost mitigation efforts such as wildlife crossing structures.

中文翻译：

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确定华盛顿州20号州际公路上的麋鹿车辆事故热点

语境

确定野生动植物车辆事故的危险区域对于在主要道路网络上进行有效的缓解工作至关重要。野生动物与车辆的碰撞数据通常用于识别热点区域，而无需考虑物种的空间分布。

目标

评估两者都可以揭示可提高缓解成功率的时空模式。

方法

我们对2012年至2019年华盛顿州20号州际公路（SR 20）上的麋鹿车辆事故（EVI）数据进行了汇总。我们还对居住在SR 20附近的23只麋鹿进行了圈养，并使用GPS位置数据来识别房屋范围和道路交叉口。我们比较了EVI和麋鹿过马路数据，以识别SR 20上的热点位置，以帮助缓解风险。

结果

我们的EVI和麋鹿穿越数据在SR 20的38公里处具有非随机分布，与8个雌性麋鹿群的95％原始范围相关。我们发现单独的EVI数据是与SR 20沿线碰撞热点相关的麋鹿空间分布和运动的有效指标。我们的结果还表明，按里程碑，麋鹿过境点和EVI之间有很强的联系。尽管麋鹿群的空间分布可以很好地预测EVI风险区，但EVI频率与麋鹿种群的增加无关。

结论

将EVI和道路交叉口分布归类为高风险区是缓解和保护措施以防止麋鹿车辆碰撞的第一步。热点的特定识别将导致更有效，更成功地安装高成本缓解措施，例如野生生物穿越结构。