Mitigating road impacts on animals through learning principles

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• 作者：D. S. Proppe ; N. McMillan ; J. V. Congdon ; C. B. Sturdy
• 关键词：Road ; Noise ; Learning ; Conditioning ; Mitigation ; Wildlife ; Bird
• 刊名：Animal Cognition
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：20
• 期：1
• 页码：19-31
• 全文大小：565KB
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Behavioral Sciences; Zoology; Psychology Research;
• 出版者：Springer Berlin Heidelberg
• ISSN：1435-9456
• 卷排序：20

文摘

Roads are a nearly ubiquitous feature of the developed world, but their presence does not come without consequences. Many mammals, birds, reptiles, and amphibians suffer high rates of mortality through collision with motor vehicles, while other species treat roads as barriers that reduce gene flow between populations. Road effects extend beyond the pavement, where traffic noise is altering communities of songbirds, insects, and some mammals. Traditional methods of mitigation along roads include the creation of quieter pavement and tires and the construction of physical barriers to reduce sound transmission and movement. While effective, these forms of mitigation are costly and time-consuming. One alternative is the use of learning principles to create or extinguish aversive behaviors in animals living near roads. Classical and operant conditioning are well-documented techniques for altering behavior in response to novel cues and signals. Behavioral ecologists have used conditioning techniques to mitigate human–wildlife conflict challenges, alter predator–prey interactions, and facilitate reintroduction efforts. Yet, these principles have rarely been applied in the context of roads. We suggest that the field of road ecology is ripe with opportunity for experimentation with learning principles. We present tangible ways that learning techniques could be utilized to mitigate negative roadside behaviors, address the importance of evaluating fitness within these contexts, and evaluate the longevity of learned behaviors. This review serves as an invitation for empirical studies that test the effectiveness of learning paradigms as a mitigation tool in the context of roads.