Relative Effects of Road Risk, Habitat Suitability, and Connectivity on Wildlife Roadkills: The Case of Tawny Owls (Strix aluco)

António Mira,Sara M Santos,Pedro Beja,Steven M Vamosi,Rui Lourenço

doi:10.1371/journal.pone.0079967

António Mira, Sara M Santos + Show 3 more

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https://doi.org/10.1371/journal.pone.0079967

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Journal: PLoS ONE	Publication Date: Nov 21, 2013
Citations: 109	License type: CC BY 3.0

Affiliation: University of Évora, University of Porto

Abstract

BackgroundDespite its importance for reducing wildlife-vehicle collisions, there is still incomplete understanding of factors responsible for high road mortality. In particular, few empirical studies examined the idea that spatial variation in roadkills is influenced by a complex interplay between road-related factors, and species-specific habitat quality and landscape connectivity.Methodology/Principal FindingsIn this study we addressed this issue, using a 7-year dataset of tawny owl (Strix aluco) roadkills recorded along 37 km of road in southern Portugal. We used a multi-species roadkill index as a surrogate of intrinsic road risk, and we used a Maxent distribution model to estimate habitat suitability. Landscape connectivity was estimated from least-cost paths between tawny owl territories, using habitat suitability as a resistance surface. We defined 10 alternative scenarios to compute connectivity, based on variation in potential movement patterns according to territory quality and dispersal distance thresholds. Hierarchical partitioning of a regression model indicated that independent variation in tawny owl roadkills was explained primarily by the roadkill index (70.5%) and, to a much lesser extent, by landscape connectivity (26.2%), while habitat suitability had minor effects (3.3%). Analysis of connectivity scenarios suggested that owl roadkills were primarily related to short range movements (<5 km) between high quality territories. Tawny owl roadkills were spatially autocorrelated, but the introduction of spatial filters in the regression model did not change the type and relative contribution of environmental variables.ConclusionsOverall, results suggest that road-related factors may have a dominant influence on roadkill patterns, particularly in areas like ours where habitat quality and landscape connectivity are globally high for the study species. Nevertheless, the study supported the view that functional connectivity should be incorporated whenever possible in roadkill models, as it may greatly increase their power to predict the location of roadkill hotspots.

Highlights

Roads affect wildlife by increasing habitat fragmentation, modifying animal behaviour and movements, and increasing mortality as a consequence of road-killing [1]
Overall, results suggest that road-related factors may have a dominant influence on roadkill patterns, in areas like ours where habitat quality and landscape connectivity are globally high for the study species
In this study we examined the relative contribution of general roadkill risk, habitat suitability and landscape functional connectivity in explaining roadkill spatial patterns of tawny owl (Strix aluco L.) in southern Portugal

Summary

Introduction

Roads affect wildlife by increasing habitat fragmentation, modifying animal behaviour and movements, and increasing mortality as a consequence of road-killing [1]. The collision with vehicles is the most visible impact of roads, which in at least some circumstances, may strongly influence the size and dynamics of animal populations [2], and even result in a much larger impact on population genetic diversity than road barrier effects [3] To reduce such impacts, a number of mitigation measures have been conceived, including for instance underpasses, fences, and warning signs [4,5,6]. There is extensive research on the most important factors contributing to roadkill numbers (reviewed in [11]), few studies have used an integrative approach that evaluates the relative importance of both road-specific factors and speciesspecific factors when explaining roadkill spatial patterns This distinction is important because it may imply different options and strategies in mitigation of wildlife road-mortality. Few empirical studies examined the idea that spatial variation in roadkills is influenced by a complex interplay between road-related factors, and species-specific habitat quality and landscape connectivity

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