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

dc.contributor.authorWilliams, Samual T.
dc.contributor.authorCollinson, Wendy J.
dc.contributor.authorPatterson-Abrolat, Claire
dc.contributor.authorMarneweck, David G.
dc.contributor.authorSwanepoel, Lourens H.
dc.contributor.emaildavid.marneweck@up.ac.zaen_ZA
dc.date.accessioned2020-07-09T13:38:30Z
dc.date.available2020-07-09T13:38:30Z
dc.date.issued2019-03-29
dc.descriptionSupplementary material: Figure S1: Histogram showing distribution of serval roadkill counts in relation to a range of distributions
dc.descriptionFigure S2: Scatter plot of fitted vs residual values for the full generalized linear mixed model with negative binomial distribution
dc.descriptionFigure S3: Mantel tests for the full generalized linear mixed model with negative binomial distribution
dc.descriptionFigure S4: Variogram from for residuals for the full generalized linear mixed model with negative binomial distribution
dc.descriptionSupplemental Information 1: Summary of full generalized linear mixed model with negative binomial distribution
dc.description.abstractAs 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.departmentMammal Research Instituteen_ZA
dc.description.librarianhj2020en_ZA
dc.description.sponsorshipNational Research Foundation of South Africaen_ZA
dc.description.urihttps://peerj.comen_ZA
dc.identifier.citationWilliams, 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.issn2167-8359 (online)
dc.identifier.other10.7717/peerj.6650
dc.identifier.urihttp://hdl.handle.net/2263/75116
dc.language.isoenen_ZA
dc.publisherPeer Jen_ZA
dc.rights© 2019 Williams et al. Distributed under Creative Commons CC-BY 4.0en_ZA
dc.subjectRoad ecologyen_ZA
dc.subjectHuman-wildlife conflicten_ZA
dc.subjectWildlife managementen_ZA
dc.subjectWildlife-vehicle collisionen_ZA
dc.titleUsing road patrol data to identify factors associated with carnivore roadkill countsen_ZA
dc.typeArticleen_ZA

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