Data from: Roads elicit negative movement and habitat-selection responses by wolverines (Gulo gulo luscus)

Wildlife behavior when crossing roads is likely to mirror natural responses to predation risk including not responding, pausing, avoiding, or increasing speed during crossing. We generated coarse-scale behavioral predictions based on these expectations that could be assessed with GPS radiotelemetry. We evaluated our predictions using an integrated step-selection analysis of wolverine (Gulo gulo luscus) space use in relation to spatially and temporally dynamic vehicle traffic on industrial roads in northern Alberta. We compared support for alternative models of road avoidance, increased speed near roads, and road avoidance and increased speed near roads. We predicted that wolverines would avoid roads and increase their speed near roads and that these behaviors would increase with traffic volume. We found that vehicle traffic was relatively low (0 – 30 vehicles/12 hours) but important for explaining wolverine space use. Top winter and summer models indicated that wolverines avoided and increased speed near roads. Wolverine movement but not avoidance increased with traffic volume. We suggest that movement is a fine-scaled response that is more responsive to vehicle traffic than habitat selection. We show that roads, regardless of traffic volume, reduce the quality of wolverine habitats and act as barriers to movement and that higher-traffic roads might be most deleterious. We suggest that wildlife behavior near roads should be viewed as a continuum and that accurate modeling of behavior when near roads requires quantification of both movement and habitat selection. Mitigating the effects of roads on wolverines would require clustering roads, road closures, or access management.

野生动物穿越道路时的行为模式，大概率会映射其应对捕食风险的自然响应策略，具体表现为无反应、停顿、避让，抑或是穿越过程中提升移动速度。我们基于上述预期生成了粗尺度行为预测，该预测可通过GPS无线电遥测（GPS radiotelemetry）进行评估。我们针对阿尔伯塔省北部工业道路上时空动态变化的车流量，结合狼獾（Gulo gulo luscus）的空间利用数据，通过整合步选择分析（integrated step-selection analysis）对上述预测进行了验证。我们对比了三类备选模型的拟合支持度：道路避让模型、道路附近提速模型，以及兼具道路避让与道路附近提速的复合模型。我们预测，狼獾会主动避让道路并在道路周边提升移动速度，且此类行为的强度会随车流量的增加而增强。研究发现，该区域车流量相对较低（0~30辆/12小时），但车流量仍是解释狼獾空间利用模式的关键因素。最优的冬季与夏季模型均显示，狼獾会避让道路并在道路附近提升移动速度。狼獾的移动速率随车流量增加而升高，但其对道路的避让程度并未随车流量变化产生显著差异。我们认为，移动速率是一种细尺度响应，相比生境选择，其对车流量的响应敏感度更高。本研究证实，无论车流量大小，道路均会降低狼獾生境的质量，并成为其移动扩散的障碍；而高车流量道路的负面影响可能更为显著。我们提出，野生动物在道路附近的行为应被视为一个连续谱系，对道路周边行为的精准建模需要同时量化移动模式与生境选择两个维度。若要缓解道路对狼獾种群的负面影响，需采取道路集中布设、道路封闭或是通行权限管控等措施。