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Roadkill is affected by various factors, including road attributes and traffic volume. It is theorized that the effect of traffic volume on roadkill probability should be unimodal. However, empirical evidence for this theory is lacking. Using a large\u2010scale roadkill database of 18 wildlife species in Israel, encompassing 2846\u00a0km of roads over 10\u00a0years, we explored the effects of traffic volume and road attributes (e.g., road lighting, verge vegetation) on roadkill probability with a multivariate generalized linear mixed model. A unimodal effect of traffic volume was identified for the striped hyena (\n                    <jats:italic>Hyaena hyaena<\/jats:italic>\n                    ), whereas 5 species demonstrated a novel quadratic U\u2010shaped effect (e.g., golden jackal [\n                    <jats:italic>Canis aureus<\/jats:italic>\n                    ]). Four species showed a negative linear effect (e.g., wild boar [\n                    <jats:italic>Sus scrofa<\/jats:italic>\n                    ]). We also identified varying effects of road attributes on roadkill. For instance, road lighting and roadside trees decreased roadkill for several species, whereas bus stops and concrete guardrails led to increased roadkill. The theorized unimodal effect of traffic volume may only apply to large, agile species, and the U\u2010shaped effect could be related to intraspecies variability in traffic avoidance behavior. In general, we found that both high\u2010traffic and low\u2010traffic roads can pose a high mortality risk for wildlife. It is therefore important to monitor roadkill on low\u2010traffic roads and adapt road attributes to mitigate roadkill. Road design for effective roadkill mitigation includes reducing the use of concrete guardrails and median barriers where possible and avoiding dense bushes in verge landscaping. These measures are complemented by employing wildlife detection systems, driver warnings, and seasonal speed reduction measures on low\u2010traffic roads identified as roadkill hotspots.\n                  <\/jats:p>","DOI":"10.1111\/cobi.14159","type":"journal-article","created":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T06:41:22Z","timestamp":1691476882000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Wildlife mortality risk posed by high and low traffic roads"],"prefix":"10.1111","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9024-9384","authenticated-orcid":false,"given":"Dror","family":"Denneboom","sequence":"first","affiliation":[{"name":"Human and Biodiversity Research Lab, Faculty of Architecture and Town Planning Technion \u2013 Israel Institute of Technology  Haifa Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Avi","family":"Bar\u2010Massada","sequence":"additional","affiliation":[{"name":"Faculty of Natural Sciences University of Haifa  Kiryat Tivon Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Assaf","family":"Shwartz","sequence":"additional","affiliation":[{"name":"Human and Biodiversity Research Lab, Faculty of Architecture and Town Planning Technion \u2013 Israel Institute of Technology  Haifa Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,2,23]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.5296\/ije.v4i2.1962"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.3390\/ani11030799"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jenvman.2022.115903"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biocon.2020.108902"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/jwmg.21467"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40823-017-0020-6"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10344-020-01397-8"},{"key":"e_1_2_6_9_1","unstructured":"BioGIS. 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