Roadkill-Data-Based Identification and Ranking of Mammal Habitats

Andrius Kučas,Linas Balčiauskas

doi:10.3390/land10050477

Abstract

Wildlife–vehicle collisions, as well as environmental factors that affect collisions and mitigation measures, are usually modelled and analysed in the vicinity of or within roads, while habitat attractiveness to wildlife along with risk to drivers remain mostly underestimated. The main goal of this study was the identification, characterisation, and ranking of mammalian habitats in Lithuania in relation to 2002–2017 roadkill data. We identified habitat patches as areas (varying from 1 to 1488 square kilometres) isolated by neighbouring roads characterised by at least one wildlife–vehicle collision hotspot. We ranked all identified habitats on the basis of land cover, the presence of an ecological corridor, a mammalian pathway, and roadkill hotspot data. A ranking scenario describing both habitat attractiveness to wildlife and the risk to drivers was defined and applied. Ranks for each habitat were calculated using multiple criteria spatial decision support techniques. Multiple regression analyses were used to identify the relationship between habitat ranks, species richness, and land cover classes. Strong relationships were identified and are discussed between the habitat patch ranks in five (out of 28) land cover classes and in eight (out of 28) species (97% of all mammal road kills). We conclude that, along with conventional roadkill hotspot identification, roadkill-based habitat identification and characterisation as well as species richness analysis should be used in road safety infrastructure planning.

Highlights

Wildlife–vehicle collisions (WVCs) pose a threat to human life and biological diversity and result in damage to property [1,2,3,4,5,6]
Multiple regression analyses were used to identify the relationship between habitat ranks, species richness, and land cover classes
We identified 281 state-owned roads with at least one KDE+ cluster (Figure 3): main roads/highways; 107 national roads; and 156 regional roads

Summary

Introduction

Wildlife–vehicle collisions (WVCs) pose a threat to human life and biological diversity and result in damage to property [1,2,3,4,5,6]. Additional road safety infrastructure elements such as repellents, reflectors, noise, and natural predators can be used; these focus on a single and/or multiple wildlife species. They repel, attract, or redirect wildlife with different ecological and financial efficiencies [9,10,11,12,13,14,15,16,17,18]. The selection of tangible multi-scale [19], multi-objective, and multifunctional WVC mitigation measures is the focus of a considerable research challenge [20]

Results

Discussion

Conclusion