Bueno C, Sousa C O M, Freitas S R
Universidade Veiga de Almeida, Rio de Janeiro, RJ, Brazil.
Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brazil.
Braz J Biol. 2015 Nov;75(4 Suppl 1):S228-38. doi: 10.1590/1519-6984.12614. Epub 2015 Nov 27.
We believe that in tropics we need a community approach to evaluate road impacts on wildlife, and thus, suggest mitigation measures for groups of species instead a focal-species approach. Understanding which landscape characteristics indicate road-kill events may also provide models that can be applied in other regions. We intend to evaluate if habitat or matrix is more relevant to predict road-kill events for a group of species. Our hypothesis is: more permeable matrix is the most relevant factor to explain road-kill events. To test this hypothesis, we chose vertebrates as the studied assemblage and a highway crossing in an Atlantic Forest region in southeastern Brazil as the study site. Logistic regression models were designed using presence/absence of road-kill events as dependent variables and landscape characteristics as independent variables, which were selected by Akaike's Information Criterion. We considered a set of candidate models containing four types of simple regression models: Habitat effect model; Matrix types effect models; Highway effect model; and, Reference models (intercept and buffer distance). Almost three hundred road-kills and 70 species were recorded. River proximity and herbaceous vegetation cover, both matrix effect models, were associated to most road-killed vertebrate groups. Matrix was more relevant than habitat to predict road-kill of vertebrates. The association between river proximity and road-kill indicates that rivers may be a preferential route for most species. We discuss multi-species mitigation measures and implications to movement ecology and conservation strategies.
我们认为，在热带地区，我们需要采用一种社区方法来评估道路对野生动物的影响，因此，建议针对物种群体而非重点物种采取缓解措施。了解哪些景观特征表明发生了道路致死事件，也可能提供可应用于其他地区的模型。我们打算评估栖息地或基质对于预测一组物种的道路致死事件哪个更相关。我们的假设是：渗透性更强的基质是解释道路致死事件的最相关因素。为了验证这一假设，我们选择脊椎动物作为研究对象，并选取巴西东南部大西洋森林地区的一个公路交叉点作为研究地点。以道路致死事件的有无作为因变量，以景观特征作为自变量，通过赤池信息准则选择自变量，设计逻辑回归模型。我们考虑了一组包含四种简单回归模型的候选模型：栖息地效应模型；基质类型效应模型；公路效应模型；以及参考模型（截距和缓冲距离）。记录了近三百起道路致死事件和70个物种。河流邻近度和草本植被覆盖度这两个基质效应模型，与大多数道路致死的脊椎动物群体相关。在预测脊椎动物的道路致死情况方面，基质比栖息地更相关。河流邻近度与道路致死之间的关联表明，河流可能是大多数物种的优先通行路线。我们讨论了多物种缓解措施以及对移动生态学和保护策略的影响。
