Dawson Clara, Villamagna Amy M, Martin Rebecca A, Moll Remington J
Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, USA.
Department of Environmental Science & Policy, Plymouth State University, Plymouth, NH, USA.
Environ Manage. 2025 Aug;75(8):2089-2102. doi: 10.1007/s00267-025-02188-0. Epub 2025 May 20.
Road networks fragment wildlife habitat and impede wildlife connectivity, which leads to elevated wildlife-vehicle collision (WVC) risk and increased danger to humans and wildlife. Habitat connectivity has been linked to WVC hotspot location and intensity, but this relationship likely depends on landscape context and road characteristics, which may be nonlinear due to varying habitat availability. Our objective was to evaluate factors affecting WVC location and intensity across New Hampshire, USA, with a focus on habitat connectivity. We assessed the relationship between WVCs and five connectivity models using generalized additive models and compared connectivity effects to road and land cover characteristics. We found that a barrier-sensitive wildlife species connectivity model was the best predictor of WVC hotspots and had a strong, negative nonlinear relationship with collision intensity. We also found that a simple forest variable performed almost as well as the complex connectivity model. WVC hotspots did not differ from adjacent roads or regional roads in terms of connectivity, except that traffic volume was higher at hotspots. Our findings suggest that the relationship between habitat connectivity and WVCs depends on broader landscape context and likely exhibits nonlinearity. Our work also demonstrates that some connectivity models are better predictors of WVCs than others, emphasizing the role of species-specific habitat connectivity assessments. These results can inform WVC mitigation planning and enhance understanding of habitat connectivity's role in broader landscapes.
道路网络分割了野生动物栖息地，阻碍了野生动物的连通性，这导致野生动物与车辆碰撞（WVC）风险增加，对人类和野生动物的危险也增大。栖息地连通性与WVC热点的位置和强度有关，但这种关系可能取决于景观背景和道路特征，由于栖息地可用性不同，这种关系可能是非线性的。我们的目标是评估影响美国新罕布什尔州WVC位置和强度的因素，重点是栖息地连通性。我们使用广义相加模型评估了WVC与五种连通性模型之间的关系，并将连通性效应与道路和土地覆盖特征进行了比较。我们发现，一种对障碍敏感的野生动物物种连通性模型是WVC热点的最佳预测指标，并且与碰撞强度呈强烈的负非线性关系。我们还发现，一个简单的森林变量的表现几乎与复杂的连通性模型一样好。WVC热点在连通性方面与相邻道路或区域道路没有差异，只是热点处的交通量更高。我们的研究结果表明，栖息地连通性与WVC之间的关系取决于更广泛的景观背景，并且可能呈现非线性。我们的工作还表明，一些连通性模型比其他模型更能预测WVC，强调了特定物种栖息地连通性评估的作用。这些结果可为WVC缓解规划提供参考，并增进对栖息地连通性在更广阔景观中作用的理解。
