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，大概率会映射出其应对捕食风险的天然反应模式，包括穿越过程中无反应、停顿、避让或加快行进速度。我们基于上述预期生成了粗尺度行为预测模型，该模型可通过GPS无线电遥测（GPS radiotelemetry）技术进行验证。我们以阿尔伯塔省北部工业道路沿线时空动态变化的车辆交通为背景，通过对狼獾（Gulo gulo luscus）的空间利用开展集成步选择分析（integrated step-selection analysis），对上述预测模型进行了评估。我们对比了三类备选模型的拟合优度：道路回避模型、道路附近加速模型，以及兼具道路回避与道路附近加速的组合模型。我们预测狼獾会避让道路并在道路附近提升行进速度，且此类行为的强度会随车流量增大而增强。研究发现，该区域车辆交通流量相对较低（0~30辆/12小时），但该变量对于解释狼獾的空间利用模式具有重要意义。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加快行进速度。狼獾的移动速率随车流量增大而提升，但其道路回避行为则未呈现此规律。我们认为，移动行为是一种细尺度响应，相较于生境选择，其对车辆交通的响应更为敏感。本研究证实，无论车流量高低，道路均会降低狼獾的生境质量，并成为其移动的障碍；而高车流量道路的负面影响可能最为显著。我们提出，应将野生动物在道路附近的行为视为一个连续谱系，且若要精准建模道路附近的野生动物行为，需同时对移动行为与生境选择进行量化分析。若要减缓道路对狼獾的负面影响，需采取道路集中布设、道路封闭或通行管理等措施。