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Identifying landscape predictors of ocelot road mortality

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Abstract

Context

For depleted wildlife populations, understanding and effectively mitigating the direct and indirect impacts of roads can be a key component of recovery efforts. The ocelot is a federally endangered wild felid at risk of local extinction in south Texas, where vehicle collisions are their largest known source of mortality.

Objectives

To support road mortality mitigation, we evaluated mortality risk across the south Texas road network. We also assessed whether a sympatric carnivore, the bobcat, could serve as a surrogate to inform mortality risk.

Methods

We used several presence-only species distribution models to evaluate a suite of candidate landscape and road attributes and identify those associated with elevated road mortality risk using a 35-year wild felid road mortality dataset. Consensus predictions among models identified high-risk road segments for ocelots and bobcats. We compared predictions between species to determine overlap of high-risk areas.

Results

Areas where core ocelot habitat intersected roadways represented the greatest mortality risk, reflecting ocelot reliance on intact habitat and avoidance of degraded and fragmented landscapes. Bobcat road mortality risk had similar relationships to landscape features, with nearly all areas classified as high-risk for ocelots also identified as high-risk for bobcats.

Conclusions

Ocelots are vulnerable to road mortality in areas where roads intersect their intact scrub habitat. Bobcats, with appropriate data filters in place, are an acceptable surrogate for informing ocelot road mortality, particularly when ocelot mortality data are limited and for time-sensitive conservation decision-making. For ocelots and other fragmentation-intolerant carnivore species, wildlife underpasses and fencing in focused areas where roads and intact habitat intersect may be feasible options to reduce road mortality.

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Acknowledgements

Thank you to researchers in addition to U.S. Fish and Wildlife biologists who have collected road mortality data since 1983. Thanks to two anonymous reviewers for providing constructive comments that improved this manuscript. We also appreciate reviews by M. Sternberg (USFWS), M. Jennings, A. Nara and L. McClenaghan (SDSU). This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. (1321850).

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Correspondence to Greta M. Schmidt.

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Schmidt, G.M., Lewison, R.L. & Swarts, H.M. Identifying landscape predictors of ocelot road mortality. Landscape Ecol 35, 1651–1666 (2020). https://doi.org/10.1007/s10980-020-01042-4

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  • DOI: https://doi.org/10.1007/s10980-020-01042-4

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