Predicting Road Encounter Hotspots for Infrequently Detected Species with Haphazardly Collected Data – a Case Study with Blanding’s Turtle (Emydoidea blandingii )

Predicting Road Encounter Hotspots for Infrequently Detected Species with Haphazardly Collected Data – a Case Study with Blanding’s Turtle (Emydoidea blandingii ) | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Ecology and Evolution This is a preprint and has not been peer reviewed. Data may be preliminary. 4 November 2025 V1 Latest version Share on Predicting Road Encounter Hotspots for Infrequently Detected Species with Haphazardly Collected Data – a Case Study with Blanding’s Turtle (Emydoidea blandingii ) Authors : Sean Jackson , Alexandra Burrows , Glenn Johnson , Eric McCluskey 0000-0003-0726-663X , and Tom Langen 0000-0003-4267-820X [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176225252.23820366/v1 240 views 169 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract For road mitigation measures to prevent roadkill and conserve landscape connectivity to be effective, the measures must be located where animals are most likely to encounter roads. However, accurate identification of road encounter hotspots is difficult when presence records are sparse and collected haphazardly, often the case with small, uncommon species. Blanding’s turtle Emydoidea blandingii (BT) is a threatened species for which road-mortality contributes to population declines. Using fortuitous detections of BT along roads, we investigated whether it is possible to predict road encounter hotspots throughout an extensive road network with such data. We applied three approaches: (1) general linear modeling (GLM) to infer landscape features associated with BT road encounter records; (2) after locating spatial clusters of encounters, GLM was used to identify landscape features associated with these hotspots; and (3) BT least cost movement paths were delineated within the landscape and sites where paths crossed roads were located. Predicted hotspots based on the modeled movement trajectories were then compared with BT road encounter hotspots. BT locations were positively associated with presence of wetlands and negatively associated with grasslands and developed land use. Hotspots were located along predicted BT least cost movement paths, indicating that behavioral movement models are useful for predicting encounter locations. Each of the three modeling approaches identified valid landscape indicators of BT road encounter hotspots, and a significant fraction of road encounter records came from a small number of hotspot sites, located along the predicted movement paths. Overall, we conclude that it is possible to generate predictive models of road encounter hotspots even when data are sparse, collected unsystematically, and subject to spatial biases in reporting across a road network, and these models can be applied throughout a road network to identify road segments that are good candidates for effective road mitigation. Supplementary Material File (ms lmvalidation_3nov25 final.docx) Download 103.31 KB Information & Authors Information Version history V1 Version 1 04 November 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Ecology and Evolution Keywords freshwater natural history none of the above statistical terrestrial vertebrate Authors Affiliations Sean Jackson Clarkson University View all articles by this author Alexandra Burrows Clarkson University View all articles by this author Glenn Johnson SUNY Potsdam View all articles by this author Eric McCluskey 0000-0003-0726-663X Grand Valley State University View all articles by this author Tom Langen 0000-0003-4267-820X [email protected] Clarkson University View all articles by this author Metrics & Citations Metrics Article Usage 240 views 169 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Sean Jackson, Alexandra Burrows, Glenn Johnson, et al. Predicting Road Encounter Hotspots for Infrequently Detected Species with Haphazardly Collected Data – a Case Study with Blanding’s Turtle (Emydoidea blandingii ). Authorea . 04 November 2025. DOI: https://doi.org/10.22541/au.176225252.23820366/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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