The identification of wildlife-vehicle collision hotspots: Citizen science reveals spatial and temporal patterns

Ecological Processes

Rosario Balestrieri¹  Marco Basile¹  Francesco Valerio² 

[1] Associazione per la Ricerca, la Divulgazione e l’Educazione Ambientale – ARDEA;Mediterranean Institute for Agriculture, Environment and Development, Instituto de Investigação e Formação Avançada, Universidade de Évora;

关键词: Roadkill;    Land cover;    Road ecology;    Seasonal trend;    Spatial prioritization;    Urban wildlife;   

DOI  :  10.1186/s13717-020-00271-4

来源: DOAJ

【 摘 要 】

Abstract Linear infrastructures (e.g., roads, railways, pipelines, and powerlines) pose a serious threat to wildlife, due to the risk of wildlife-vehicle collisions (roadkills). The placement of mitigation measures, such as crossing structures, should consider species’ life cycles and ecological requirements. Such an assessment would require data collection over large areas, which may be possible by employing citizen science. In this study, we aimed to identify spatio-temporal trends of roadkill occurrence using citizen science data from one of the most urbanized and biodiversity-rich regions of Italy. Temporal trends were analyzed using generalized additive models, while landscape patterns were assessed by identifying significant thresholds over land cover gradients, related to increases in relative roadkill abundance, by employing threshold indicator taxa analysis. Our approach recorded a total of 529 roadkills, including 33 different species, comprising 13 mammal, 10 bird, 6 reptile, and 2 amphibian species. Statistical analysis indicated significant temporal trends for the red fox, the European hedgehog, the stone marten and the European badger, with peaks in roadkill occurrence between the winter and spring months. Relative roadkill abundance increased mostly in landscapes with anthropogenic land cover classes, such as complex cultivations, orchards, or urban surfaces. Our results allowed us to develop a map of potential roadkill risk that could assist in planning the placement of mitigation measures. Citizen science contributions from highly populated areas allowed data collection over a large area and a dense road network, and also directly led to the evaluation of management decisional options.

【 授权许可】

Unknown