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Developing a correction factor to apply to animal–vehicle collision data for improved road mitigation measures

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TLDR
A method to calculate a correction factor for large mammal carcass data reported through road survey will improve the understanding of the magnitude and cost of AVCs and improve information about AVCs where little is known.
Abstract
Context Road mitigation to reduce animal–vehicle collisions (AVCs) is usually based on analysis of road survey animal carcass data. This is used to identify road sections with high AVC clusters. Large mammals that are struck and die away from a road are not recorded nor considered in these analyses, reducing our understanding of the number of AVCs and the cost–benefit of road mitigation measures. Aims Our aim was to develop a method to calculate a correction factor for large mammal carcass data reported through road survey. This will improve our understanding of the magnitude and cost of AVCs. Method Citizen scientists reported animal carcasses on walking surveys along transects parallel to the highway and reported observations using a smartphone application at three sites over a 5-year period. These data were compared with traditional road survey data. Key result We found that many large mammals involved in AVCs die away from the road and are, therefore, not reported in traditional road surveys. A correction factor of 2.8 for our region can be applied to road survey data to account for injury bias error in road survey carcass data. Conclusions For large mammals, AVCs based on road survey carcass data are underestimates. To improve information about AVCs where little is known, we recommend conducting similar research to identify a correction factor to conventionally collected road survey carcass data. Implications Identifying road mitigation sites by transportation agencies tends to focus on road sections with above-threshold AVC numbers and where cost–benefit analyses deem mitigation necessary. A correction factor improves AVC estimate accuracy, improving the identification of sites appropriate for mitigation, and, ultimately, benefitting people and wildlife by reducing risks of AVCs.

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References
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Journal Article

Review of Human Injuries, Illnesses, and Economic Losses Caused by Wildlife in the United States

TL;DR: A survey of state agricultural and wildlife professionals found that 27 wildlife species were listed by at least 1 respondent as causing the greatest economic losses in the respondent's state (Conover and Decker 1991) as mentioned in this paper.
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Ungulate Traffic Collisions in Europe

TL;DR: In this paper, the authors reviewed European and North American and Japanese literature on ungulate traffic collisions and found no strong evidence of the effects of permanent warning signs, 90° light mirrors, scent, or acoustic fencing on the number of kills per crossing.
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Cost–Benefit Analyses of Mitigation Measures Aimed at Reducing Collisions with Large Ungulates in the United States and Canada: a Decision Support Tool

TL;DR: In this paper, the authors presented a costbenefit model for determining mitigation measures to reduce ungulate-vehicle collisions, including vehicle repair costs, human injuries and fatalities, towing, accident attendance and investigation, monetary value to hunters of an animal killed in a collision, and cost of disposal of the animal carcass.
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How long do the dead survive on the road? Carcass persistence probability and implications for road-kill monitoring surveys.

TL;DR: In this paper, the authors describe and model carcass persistence variability on the road for different taxonomic groups under different environmental conditions throughout the year, and also assess the effect of sampling frequency on the relative variation in road-kill estimates registered within a survey.

Wildlife-Vehicle Collision Reduction Study: Report to Congress

TL;DR: According to as mentioned in this paper, there are an estimated one to two million collisions between cars and large animals every year in the U.S. This presents a real danger to human safety as well as wildlife survival.
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