Collisions with vehicles represent the main conflict between infrastructures and wildlife, causing damages to both humans and animals. As to the latter, road mortality is a growing phenomenon and the largest single cause of death for many vertebrates. When focusing on endangered species, the Eurasian otter (Lutra lutra) is among the most vulnerable to road-kills, which represent the predominant cause of deaths recorded in Europe. We propose a large scale spatially-explicit assessment of road-kill risk for the Eurasian otter in Italy as a tool to identify road stretches at high collision risk, thus optimizing the location of mitigation measures. The modelling approach was produced for South Central Italy, hosting the only remnant viable population of otters in Italy. We used a maximum entropy approach including 56 road collision events recorded between 2004 and 2016 through a citizen science initiative, along with seven environmental predictors measured on 1 km grid cells. Four predictors were selected to describe roads characteristics, i.e. density of highways, and of state, regional and local roads. The remaining three variables referred to the quality of otter habitat in the surrounding of the collision sites, i.e. elevation, density of freshwater bodies, and a measure of landscape heterogeneity calculated on land-cover categories. The model achieved a good predictive accuracy (AUC > 0.8; Boyce index > 0.8). The collision probability was mostly affected by elevation, density of state roads, and density of freshwater bodies. Specifically, collision risk was higher in areas at low elevation and medium density of state roads located near rivers and wetlands. In addition, model predictions evidenced that implementing mitigation measures along 10% of road network in the study area could have potentially hampered ca. 50% of otter casualties recorded during the study period.

Where will it cross next? Optimal management of road collision risk for otters in Italy

Fabrizio, Mauro;Di Febbraro, Mirko
;
Loy, Anna
2019

Abstract

Collisions with vehicles represent the main conflict between infrastructures and wildlife, causing damages to both humans and animals. As to the latter, road mortality is a growing phenomenon and the largest single cause of death for many vertebrates. When focusing on endangered species, the Eurasian otter (Lutra lutra) is among the most vulnerable to road-kills, which represent the predominant cause of deaths recorded in Europe. We propose a large scale spatially-explicit assessment of road-kill risk for the Eurasian otter in Italy as a tool to identify road stretches at high collision risk, thus optimizing the location of mitigation measures. The modelling approach was produced for South Central Italy, hosting the only remnant viable population of otters in Italy. We used a maximum entropy approach including 56 road collision events recorded between 2004 and 2016 through a citizen science initiative, along with seven environmental predictors measured on 1 km grid cells. Four predictors were selected to describe roads characteristics, i.e. density of highways, and of state, regional and local roads. The remaining three variables referred to the quality of otter habitat in the surrounding of the collision sites, i.e. elevation, density of freshwater bodies, and a measure of landscape heterogeneity calculated on land-cover categories. The model achieved a good predictive accuracy (AUC > 0.8; Boyce index > 0.8). The collision probability was mostly affected by elevation, density of state roads, and density of freshwater bodies. Specifically, collision risk was higher in areas at low elevation and medium density of state roads located near rivers and wetlands. In addition, model predictions evidenced that implementing mitigation measures along 10% of road network in the study area could have potentially hampered ca. 50% of otter casualties recorded during the study period.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/98286
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