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Journal Article

Citation

Litvaitis JA, Tash JP. Environ. Manage. 2008; 42(4): 688-697.

Affiliation

Department of Natural Resources, University of New Hampshire, Durham, NH 03824, USA. john@uhn.edu

Copyright

(Copyright © 2008, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s00267-008-9108-4

PMID

18427884

Abstract

Among the most conspicuous environmental effects of roads are vehicle-related mortalities of wildlife. Research to understand the factors that contribute to wildlife-vehicle collisions can be partitioned into several major themes, including (i) characteristics associated with roadkill hot spots, (ii) identification of road-density thresholds that limit wildlife populations, and (iii) species-specific models of vehicle collision rates that incorporate information on roads (e.g., proximity, width, and traffic volume) and animal movements. We suggest that collision models offer substantial opportunities to understand the effects of roads on a diverse suite of species. We conducted simulations using collision models and information on Blanding's turtles (Emydoidea blandingii), bobcats (Lynx rufus), and moose (Alces alces), species endemic to the northeastern United States that are of particular concern relative to collisions with vehicles. Results revealed important species-specific differences, with traffic volume and rate of movement by candidate species having the greatest influence on collision rates. We recommend that future efforts to reduce wildlife-vehicle collisions be more proactive and suggest the following protocol. For species that pose hazards to drivers (e.g., ungulates), identify collision hot spots and implement suitable mitigation to redirect animal movements (e.g., underpasses, fencing, and habitat modification), reduce populations of problematic game species via hunting, or modify driver behavior (e.g., dynamic signage that warns drivers when animals are near roads). Next, identify those species that are likely to experience additive (as opposed to compensatory) mortality from vehicle collisions and rank them according to vulnerability to extirpation. Then combine information on the distribution of at-risk species with information on existing road networks to identify areas where immediate actions are warranted.


Language: en

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