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For the deep\u2010diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal\u2013vertical movement model results with spatial\u2013temporal kernel density estimates and threat data (gear\u2010specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (\n                    <jats:italic>n<\/jats:italic>\n                    \u00a0=\u00a028 leatherback tracks, 2004\u20132007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space\u2010use estimates to create maps of relative risk of turtle\u2013fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high\u2010risk interactions with turtles in a residential, deep\u2010diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) (\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/www.upwell.org\/sptw\">https:\/\/www.upwell.org\/sptw<\/jats:ext-link>\n                    ), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high\u2010risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial\u2013temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors.\n                  <\/jats:p>","DOI":"10.1111\/cobi.14114","type":"journal-article","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T06:40:31Z","timestamp":1684478431000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species"],"prefix":"10.1111","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9225-4355","authenticated-orcid":false,"given":"Nicole","family":"Barbour","sequence":"first","affiliation":[{"name":"Chesapeake Biological Laboratory University of Maryland Center for Environmental Science Solomons Maryland USA"},{"name":"Department of Biology University of Maryland College Park Maryland 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