Using road patrol data to identify factors associated with carnivore roadkill counts

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dc.contributor.author Williams, Samual T.
dc.contributor.author Collinson, Wendy J.
dc.contributor.author Patterson-Abrolat, Claire
dc.contributor.author Marneweck, David G.
dc.contributor.author Swanepoel, Lourens H.
dc.date.accessioned 2020-07-09T13:38:30Z
dc.date.available 2020-07-09T13:38:30Z
dc.date.issued 2019-03-29
dc.description Supplementary material: Figure S1: Histogram showing distribution of serval roadkill counts in relation to a range of distributions
dc.description Figure S2: Scatter plot of fitted vs residual values for the full generalized linear mixed model with negative binomial distribution
dc.description Figure S3: Mantel tests for the full generalized linear mixed model with negative binomial distribution
dc.description Figure S4: Variogram from for residuals for the full generalized linear mixed model with negative binomial distribution
dc.description Supplemental Information 1: Summary of full generalized linear mixed model with negative binomial distribution
dc.description.abstract As the global road network expands, roads pose an emerging threat to wildlife populations. One way in which roads can affect wildlife is wildlife-vehicle collisions, which can be a significant cause of mortality through roadkill. In order to successfully mitigate these problems, it is vital to understand the factors that can explain the distribution of roadkill. Collecting the data required to enable this can be expensive and time consuming, but there is significant potential in partnering with organisations that conduct existing road patrols to obtain the necessary data. We assessed the feasibility of using roadkill data collected daily between 2014 and 2017 by road patrol staff from a private road agency on a 410 km length of the N3 road in South Africa. We modelled the relationship between a set of environmental and anthropogenic variables on the number of roadkill carcasses, using serval (Leptailurus serval) as a model species. We recorded 5.24 serval roadkill carcasses/100 km/year. The number of carcasses was related to season, the amount of wetland, and NDVI, but was not related to any of the anthropogenic variables we included. This suggests that roadkill patterns may differ greatly depending on the ecology of species of interest, but targeting mitigation measures where roads pass through wetlands may help to reduce serval roadkill. Partnering with road agencies for data collection offers powerful opportunities to identify factors related to roadkill distribution and reduce the threats posed by roads to wildlife. en_ZA
dc.description.department Mammal Research Institute en_ZA
dc.description.librarian hj2020 en_ZA
dc.description.sponsorship National Research Foundation of South Africa en_ZA
dc.description.uri https://peerj.com en_ZA
dc.identifier.citation Williams, S.T., Collinson, W., Patterson-Abrolat, C. et al. Using road patrol data to identify factors associated with carnivore roadkill counts. Peer J 2019, 7:e6650. http://DOI.org/10.7717/peerj.6650. en_ZA
dc.identifier.issn 2167-8359 (online)
dc.identifier.other 10.7717/peerj.6650
dc.identifier.uri http://hdl.handle.net/2263/75116
dc.language.iso en en_ZA
dc.publisher Peer J en_ZA
dc.rights © 2019 Williams et al. Distributed under Creative Commons CC-BY 4.0 en_ZA
dc.subject Road ecology en_ZA
dc.subject Human-wildlife conflict en_ZA
dc.subject Wildlife management en_ZA
dc.subject Wildlife-vehicle collision en_ZA
dc.title Using road patrol data to identify factors associated with carnivore roadkill counts en_ZA
dc.type Article en_ZA


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