An approach toward understanding wildlife-vehicle collisions
An approach toward understanding wildlife-vehicle collisions
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DOI：
10.1007/s00267-008-9108-4
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发表时间：
2008-10-01
影响因子：
3.5
通讯作者：
Tash, Jeffrey P.
中科院分区：
文献类型：
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作者：
Litvaitis, John A.;Tash, Jeffrey P.
道路对环境最显着的影响是与车辆相关的野生动物死亡。了解导致野生动物与车辆碰撞的因素的研究可以分为几个主要主题，包括（i）与道路死亡热点相关的特征，（ii）识别限制野生动物种群的道路密度阈值，以及（iii）包含道路信息（例如，邻近度、宽度和交通量）和动物运动的特定物种车辆碰撞率模型。我们认为碰撞模型为了解道路对多种物种的影响提供了大量机会。我们使用碰撞模型和布兰丁龟 (Emydoidea blandingii)、山猫 (Lynx rufus) 和驼鹿 (Alces alces) 的信息进行了模拟，这些物种是美国东北部特有的物种，与车辆碰撞特别令人担忧。结果揭示了重要的物种特异性差异，候选物种的交通量和移动速率对碰撞率影响最大。我们建议未来减少野生动物与车辆碰撞的努力更加积极主动，并提出以下协议。对于对驾驶员构成危险的物种（例如，有蹄类动物），识别碰撞热点并采取适当的缓解措施来改变动物的运动方向（例如，地下通道、围栏和栖息地改造），通过狩猎减少有问题的游戏物种的数量，或改变驾驶员的行为（例如，当动物靠近道路时向驾驶员发出警告的动态标牌）。接下来，确定那些可能因车辆碰撞而遭受附加（而不是补偿性）死亡率的物种，并根据灭绝的脆弱性对它们进行排名。然后将高危物种的分布信息与现有道路网络的信息结合起来，以确定需要立即采取行动的区域。
Among the most conspicuous environmental effects of roads are vehicle-related mortalities of wildlife. Research to understand the factors that contribute to wildlife-vehicle collisions can be partitioned into several major themes, including (i) characteristics associated with roadkill hot spots, (ii) identification of road-density thresholds that limit wildlife populations, and (iii) species-specific models of vehicle collision rates that incorporate information on roads (e.g., proximity, width, and traffic volume) and animal movements. We suggest that collision models offer substantial opportunities to understand the effects of roads on a diverse suite of species. We conducted simulations using collision models and information on Blanding's turtles (Emydoidea blandingii), bobcats (Lynx rufus), and moose (Alces alces), species endemic to the northeastern United States that are of particular concern relative to collisions with vehicles. Results revealed important species-specific differences, with traffic volume and rate of movement by candidate species having the greatest influence on collision rates. We recommend that future efforts to reduce wildlife-vehicle collisions be more proactive and suggest the following protocol. For species that pose hazards to drivers (e.g., ungulates), identify collision hot spots and implement suitable mitigation to redirect animal movements (e.g., underpasses, fencing, and habitat modification), reduce populations of problematic game species via hunting, or modify driver behavior (e.g., dynamic signage that warns drivers when animals are near roads). Next, identify those species that are likely to experience additive (as opposed to compensatory) mortality from vehicle collisions and rank them according to vulnerability to extirpation. Then combine information on the distribution of at-risk species with information on existing road networks to identify areas where immediate actions are warranted.