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Fine-scale roadkill risk models: understanding the intersection of wildlife and roads

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Abstract

Robust, spatially explicit approaches accounting for ecological drivers are needed to identify environmental correlates of roadkill and set conservation priorities. We predicted wildlife road mortality across a nationwide road network using species distribution models with environmental covariates. We applied MaxEnt to a citizen science database of > 60,000 roadkill records to predict roadkill probability. Twenty-eight environmental covariates at 50 m spatial resolution were included, such as road type and land cover composition. We focused on ecological guilds and endangered species: common venomous snakes (CVS), semiaquatic and aquatic snakes (SAS), turtles, and the Maki’s keelback snake (Hebius miyajimae, HM). All predictive models performed well with AUCs > 0.7. Projected roadkill risks for CVS, SAS, turtles, and HM were highest in montane regions, coastal lowlands, the southwestern coast, and parts of central Taiwan, respectively. Roadkill projection models performed well across ecological levels and scales. Road-type strongly influenced roadkill risk. As predictions and variable importance differed across guild and species models, individual models need to be produced for each group of interest. Additionally, the project emphasizes the importance of systematic collection of roadkill data, which contributes to both informing conservation action and engaging the public in wildlife education. We discovered novel findings on predicted high- and low-risk areas for groups with conservation need and produced interactive roadkill risk maps as a conservation tool for managers and practitioners. Importantly, this methodology is not limited to Taiwan; it can be applied anywhere with sufficient roadkill and environmental data and is scalable to address the ecological question of interest.

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Data availability

Data for this study will be made available upon request. However, all TaiRON data on non-protected species is open and available on their website, https://roadkill.tw/, with free user registration.

Code availability

Full code for this study will be made available upon request. Example code for the Turtle guild is included in supplementary materials.

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Acknowledgements

We thank the Taiwan Roadkill Observation Network citizen scientists, Yu-Kai Chen, Chih-Yun Chen, Yi-Lun Lin, Pei-Chen Lin, Pei-Tsen Liao, Yu-Chen Hung, and Hung-Nien Chen for their participation in data collection, and Drs. Rodney van der Ree and Jane Elith for theoretical guidance.

Funding

Support was provided by the National Science Foundation—East Asia and Pacific Summer Institute (#1514955), U.S. Fulbright Student Program—Taiwan, Texas A&M University—Ecology & Evolutionary Biology, Friends of Sunset Zoo Conservation Grant, International Herpetological Society research grant, East Texas Herpetological Society—James R. Dixon Grant, and the Taiwan Agricultural Council and Environmental Protection Administration. These sources funded data collection efforts of authors in Taiwan. Analysis, interpretation, and writing were supported by the Australian Government Endeavour Research Fellowship and the Texas A&M University—Office of Graduate and Professional Studies Dissertation Fellowship.

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Authors and Affiliations

  1. Biodiversity Research and Teaching Collections, Department of Wildlife & Fisheries Sciences, and Applied Biodiversity Science Program, Texas A&M University, 534 John Kimbrough Blvd, College Station, TX, USA

    Kristina Chyn

  2. Zoology Department, Taiwan Endemic Species Research Institute, No. 1號, Minsheng East Road, Jiji Township, Nantou County, Taiwan

    Te-En Lin

  3. School of BioSciences, University of Melbourne, Parkville, VIC, Australia

    David P. Wilkinson

  4. Entomology Department, Texas A&M University, 534 John Kimbrough Blvd, College Station, TX, USA

    Kristina Chyn & James L. Tracy

  5. Department of Ecology and Conservation Biology, Texas A&M University, 534 John Kimbrough Blvd., College Station, TX, USA

    A. Michelle Lawing

  6. Ecology & Evolutionary Biology, Texas A&M University, 534 John Kimbrough Blvd, College Station, TX, 77843, USA

    Kristina Chyn

  7. Biodiversity Research and Teaching Collections, Department of Ecology and Conservation Biology Applied Biodiversity Science Program, Texas A&M University, 534 John Kimbrough Blvd., College Station, TX, USA

    Lee A. Fitzgerald

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  1. Kristina Chyn
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Contributions

KC, JT, and LF conceived the study concept; TL led and funded data collection; KC, JT, DW, ML, and LF designed methodology and interpreted the results, KC, DW, JT, and ML performed analyses; KC wrote the manuscript; JT and LF provided technical and theoretical guidance, all authors contributed to and approved the final manuscript.

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Correspondence to Kristina Chyn.

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Chyn, K., Lin, TE., Wilkinson, D.P. et al. Fine-scale roadkill risk models: understanding the intersection of wildlife and roads. Biodivers Conserv 30, 139–164 (2021). https://doi.org/10.1007/s10531-020-02083-6

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