Predicting spatiotemporal patterns of road mortality for medium-large mammals

Journal of Environmental Management
Fernando AscensãoArnaud Desbiez

Abstract

We modelled the spatiotemporal patterns of road mortality for seven medium-large mammals, using a roadkill dataset from Mato Grosso do Sul, Brazil (800 km of roads surveyed every two weeks, for two years). We related roadkill presence-absence along the road sections (1000 m) and across the survey dates with a collection of environmental variables, including land cover, forest cover, distance to rivers, temperature, precipitation and vegetation productivity. We further included two variables aiming to reflect the intrinsic spatial and temporal roadkill risk. Environmental variables were obtained through remote sensing and weather stations, allowing the estimate of the roadkill risk for the entire surveyed roads and survey periods. Overall, the models could explain a small fraction of the spatiotemporal patterns of roadkills (<0.23), probably due to species being habitat generalists, but still had reasonable discrimination power (AUC averaging 0.70 ± 0.07). The intrinsic spatial and temporal roadkill risk were the most important variables, followed by land cover, climate and NDVI. We show that identifying spatiotemporal roadkill patterns may provide valuable information to define specific management actions focused on road sectio...Continue Reading

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Citations

Jan 13, 2021·Scientific Reports·Pedro Enrique Navas-SuárezJose Luiz Catão-Dias
Aug 10, 2020·Journal of Environmental Management·Andrius Kučas, Linas Balčiauskas

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