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<p>Wild ungulate-vehicle collisions (UVC) in Europe have dramatically increased, creating serious conservation, economic and health problems. To examine which temporal and environmental features promote UVC involving the three most abundant and widely distributed wild ungulate species in Portugal (wild boar, red deer and roe deer), we used Generalized Linear Models, using a database of 3,374 UVC (2019–2022). We evaluated the influence of hour, day, month, hunting season, breeding season, lunar phase, meteorological conditions and land cover on the patterns of the wild ungulate-vehicle collisions. Temporally and spatially, UVC were not randomly distributed and the distribution was species-specific. Different factors explained the vehicle collisions for different species, being precipitation, time after dusk, forest and urban area around the collisions the drivers common for all the species. Hunting season also explained the wild boar collisions and both hunting and breeding season explained both wild boar and roe deer vehicle-collisions. Our results may be considered an important step towards the development of nationwide and space-time collision risk maps to be incorporated on navigation and mapping services. The information provided in this study emphasis the need for the optimization of ongoing mitigation measures and the need to focus them on periods of elevated collision risk, namely during twilight periods.</p> Graphical Abstract <p></p>

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Wrong place at the wrong time: patterns explaining ungulate-vehicle collisions in Portugal

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月28日

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  • Rita Tinoco Torres,
  • Tomé Neves,
  • Clara Grilo,
  • Pedro Leite,
  • Mariana Rossa,
  • João Carvalho

摘要

Wild ungulate-vehicle collisions (UVC) in Europe have dramatically increased, creating serious conservation, economic and health problems. To examine which temporal and environmental features promote UVC involving the three most abundant and widely distributed wild ungulate species in Portugal (wild boar, red deer and roe deer), we used Generalized Linear Models, using a database of 3,374 UVC (2019–2022). We evaluated the influence of hour, day, month, hunting season, breeding season, lunar phase, meteorological conditions and land cover on the patterns of the wild ungulate-vehicle collisions. Temporally and spatially, UVC were not randomly distributed and the distribution was species-specific. Different factors explained the vehicle collisions for different species, being precipitation, time after dusk, forest and urban area around the collisions the drivers common for all the species. Hunting season also explained the wild boar collisions and both hunting and breeding season explained both wild boar and roe deer vehicle-collisions. Our results may be considered an important step towards the development of nationwide and space-time collision risk maps to be incorporated on navigation and mapping services. The information provided in this study emphasis the need for the optimization of ongoing mitigation measures and the need to focus them on periods of elevated collision risk, namely during twilight periods.

Graphical Abstract