{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T12:55:25Z","timestamp":1792846525527,"version":"4.5.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T00:00:00Z","timestamp":1786924800000},"content-version":"vor","delay-in-days":68,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100007917","name":"U.S. Department of Agriculture, Agricultural Research Service","doi-asserted-by":"crossref","award":["number 58-6064-3-017"],"award-info":[{"award-number":["number 58-6064-3-017"]}],"id":[{"id":"10.13039\/100007917","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100007917","name":"U.S. Department of Agriculture, Agricultural Research Service","doi-asserted-by":"crossref","award":["number 58-6064-3-017"],"award-info":[{"award-number":["number 58-6064-3-017"]}],"id":[{"id":"10.13039\/100007917","id-type":"DOI","asserted-by":"crossref"}]},{"name":"CRIS project","award":["2030-32000-011-000-D"],"award-info":[{"award-number":["2030-32000-011-000-D"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mov Ecol"],"DOI":"10.1186\/s40462-026-00668-4","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:22:40Z","timestamp":1781108560000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Use of deep learning to predict chronic wasting disease status based on animal movement"],"prefix":"10.1186","volume":"14","author":[{"given":"Raymond L.","family":"Blaha","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher J.","family":"Silva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephanie A.","family":"Cunningham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melia T.","family":"DeVivo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David R.","family":"Edmunds","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie R.","family":"Boudreau","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,10]]},"reference":[{"key":"668_CR1","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1111\/ele.12917","volume":"21","author":"ER Dougherty","year":"2018","unstructured":"Dougherty ER, Seidel DP, Carlson CJ, Spiegel O, Getz WM. Going through the motions: incorporating movement analyses into disease research. Ecol Lett. 2018;21:588\u2013604. https:\/\/doi.org\/10.1111\/ele.12917.","journal-title":"Ecol Lett"},{"key":"668_CR2","doi-asserted-by":"publisher","first-page":"1290","DOI":"10.1111\/ele.13986","volume":"25","author":"MQ Wilber","year":"2022","unstructured":"Wilber MQ, Yang A, Boughton R, Manlove KR, Miller RS, Pepin KM, et al. A model for leveraging animal movement to understand spatio-temporal disease dynamics. Ecol Lett. 2022;25:1290\u2013304. https:\/\/doi.org\/10.1111\/ele.13986.","journal-title":"Ecol Lett"},{"key":"668_CR3","doi-asserted-by":"publisher","first-page":"89","DOI":"10.7589\/0090-3558-16.1.89","volume":"16","author":"ES Williams","year":"1980","unstructured":"Williams ES, Young S. Chronic wasting disease of captive mule deer: a spongiform encephalopathy. J Wildl Dis. 1980;16:89\u201398. https:\/\/doi.org\/10.7589\/0090-3558-16.1.89.","journal-title":"J Wildl Dis"},{"key":"668_CR4","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1354\/vp.42-5-530","volume":"42","author":"ES Williams","year":"2005","unstructured":"Williams ES. Chronic wasting disease. Vet Pathol. 2005;42:530\u201349. https:\/\/doi.org\/10.1354\/vp.42-5-530.","journal-title":"Vet Pathol"},{"key":"668_CR5","doi-asserted-by":"publisher","first-page":"e3089","DOI":"10.1002\/eap.3089","volume":"35","author":"WE Moss","year":"2025","unstructured":"Moss WE, Binfet J, Hall LE, Allen SE, Edwards WH, Jennings-Gaines JE, Cross PC. The effectiveness of harvest for limiting wildlife disease: Insights from 20 years of chronic wasting disease in Wyoming. Ecol Appl. 2025;35:e3089. https:\/\/doi.org\/10.1002\/eap.3089.","journal-title":"Ecol Appl"},{"key":"668_CR6","doi-asserted-by":"publisher","first-page":"e0186512","DOI":"10.1371\/journal.pone.0186512","volume":"12","author":"MT DeVivo","year":"2017","unstructured":"DeVivo MT, Edmunds DR, Kauffman MJ, Schumaker BA, Binfet J, Kreeger TJ, et al. Endemic chronic wasting disease causes mule deer population decline in Wyoming. PLoS ONE. 2017;12:e0186512. https:\/\/doi.org\/10.1371\/journal.pone.0186512.","journal-title":"PLoS ONE"},{"key":"668_CR7","doi-asserted-by":"publisher","first-page":"e0161127","DOI":"10.1371\/journal.pone.0161127","volume":"11","author":"DR Edmunds","year":"2016","unstructured":"Edmunds DR, Kauffman MJ, Schumaker BA, Lindzey FG, Cook WE, Kreeger TJ, et al. Chronic Wasting Disease Drives Population Decline of White-Tailed Deer. PLoS ONE. 2016;11:e0161127. https:\/\/doi.org\/10.1371\/journal.pone.0161127.","journal-title":"PLoS ONE"},{"key":"668_CR8","doi-asserted-by":"publisher","first-page":"e0278366","DOI":"10.1371\/journal.pone.0278366","volume":"17","author":"SJ Chiavacci","year":"2022","unstructured":"Chiavacci SJ. The economic costs of chronic wasting disease in the United States. PLoS ONE. 2022;17:e0278366. https:\/\/doi.org\/10.1371\/journal.pone.0278366.","journal-title":"PLoS ONE"},{"key":"668_CR9","doi-asserted-by":"publisher","first-page":"e1578","DOI":"10.1002\/wsb.1578","volume":"49","author":"AS Mohr","year":"2025","unstructured":"Mohr AS, Henry ME, Wojcik B, Anhalt-Depies C, Storm DJ. The decline of deer hunting: Demographic analysis and future projections of Wisconsin deer hunters. Wildl Soc Bull. 2025;49:e1578. https:\/\/doi.org\/10.1002\/wsb.1578.","journal-title":"Wildl Soc Bull"},{"key":"668_CR10","unstructured":"US Fish and Wildlife Service. 2022 National survey of fishing, hunting, and wildlife-associated recreation. Technical report. 88 p. https:\/\/www.fws.gov\/media\/2022-national-survey-fishing-hunting-and-wildlife-associated-recreation."},{"key":"668_CR11","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1080\/10871200490479963","volume":"9","author":"RC Bishop","year":"2004","unstructured":"Bishop RC. The economic impacts of Chronic Wasting Disease (CWD) in Wisconsin. Hum Dimens Wildl. 2004;9:181\u201392. https:\/\/doi.org\/10.1080\/10871200490479963.","journal-title":"Hum Dimens Wildl"},{"key":"668_CR12","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1002\/wsb.639","volume":"40","author":"JE Miller","year":"2016","unstructured":"Miller JE, Miller DA. Introduction: Ecological, biological, economic, and social issues associated with captive cervids. Wildl Soc Bull. 2016;40:7\u20139. https:\/\/www.jstor.org\/stable\/wildsocibull2011.40.1.7.","journal-title":"Wildl Soc Bull"},{"key":"668_CR13","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1016\/j.bbadis.2006.10.010","volume":"1772","author":"CJ Sigurdson","year":"2007","unstructured":"Sigurdson CJ, Aguzzi A. Chronic wasting disease. Biochem Biophys Acta. 2007;1772:610\u20138. https:\/\/doi.org\/10.1016\/j.bbadis.2006.10.010.","journal-title":"Biochem Biophys Acta"},{"key":"668_CR14","doi-asserted-by":"publisher","first-page":"2629","DOI":"10.1099\/0022-1317-83-10-2629","volume":"83","author":"MA Wild","year":"2002","unstructured":"Wild MA, Spraker TR, Sigurdson CJ, O\u2019Rourke KI, Miller MW. Preclinical diagnosis of chronic wasting disease in captive mule deer (Odocoileus hemionus) and white-tailed deer (Odocoileus virginianus) using tonsillar biopsy. J Gen Virol. 2002;83:2629\u201334. https:\/\/doi.org\/10.1099\/0022-1317-83-10-2629.","journal-title":"J Gen Virol"},{"key":"668_CR15","doi-asserted-by":"publisher","first-page":"551","DOI":"10.20506\/rst.11.2.611","volume":"11","author":"ES Williams","year":"1992","unstructured":"Williams ES, Young S. Spongiform encephalopathies in Cervidae. Rev Sci Tech. 1992;11:551\u201367. https:\/\/doi.org\/10.20506\/rst.11.2.611.","journal-title":"Rev Sci Tech"},{"key":"668_CR16","doi-asserted-by":"publisher","first-page":"305","DOI":"10.20506\/rst.21.2.1340","volume":"21","author":"ES Williams","year":"2002","unstructured":"Williams ES, Miller MW. Chronic wasting disease in deer and elk in North America. Rev Sci Tech. 2002;21:305\u201316. https:\/\/doi.org\/10.20506\/rst.21.2.1340.","journal-title":"Rev Sci Tech"},{"key":"668_CR17","doi-asserted-by":"publisher","first-page":"465","DOI":"10.7589\/0090-3558-18.4.465","volume":"18","author":"ES Williams","year":"1982","unstructured":"Williams ES, Young S. Spongiform encephalopathy of Rocky Mountain elk. J Wildl Dis. 1982;18:465\u201371. https:\/\/doi.org\/10.7589\/0090-3558-18.4.465.","journal-title":"J Wildl Dis"},{"key":"668_CR18","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1177\/030098589303000105","volume":"30","author":"ES Williams","year":"1993","unstructured":"Williams ES, Young S. Neuropathology of chronic wasting disease of mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni). Vet Pathol. 1993;30:36\u201345. https:\/\/doi.org\/10.1177\/030098589303000105.","journal-title":"Vet Pathol"},{"issue":"5","key":"668_CR19","doi-asserted-by":"publisher","first-page":"e11418","DOI":"10.1002\/ece3.11418","volume":"14","author":"GM Barrile","year":"2024","unstructured":"Barrile GM, Cross PC, Stewart C, Malmberg J, Jakopak RP, Binfet J, Monteith KL, Werner B, Jennings-Gaines J, Merkle JA. Chronic wasting disease alters the movement behavior and habitat use of mule deer during clinical stages of infection. Ecol Evol. 2024;14(5):e11418.","journal-title":"Ecol Evol"},{"key":"668_CR20","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1002\/jwmg.21341","volume":"82","author":"DR Edmunds","year":"2018","unstructured":"Edmunds DR, Albeke SE, Grogan RG, Lindzey FG, Legg DE, Cook WE, et al. Chronic wasting disease influences activity and behavior in white-tailed deer. J Wild Manag. 2018;82:138\u201354. https:\/\/doi.org\/10.1002\/jwmg.21341.","journal-title":"J Wild Manag"},{"key":"668_CR21","doi-asserted-by":"publisher","first-page":"e70001","DOI":"10.1002\/wmon.70001","volume":"217","author":"MLJ Gilbertson","year":"2025","unstructured":"Gilbertson MLJ, Ketz AC, Hunsaker MA, Walsh DP, Storm DJ, Turner WC. White-tailed deer habitat use and implications for chronic wasting disease transmission. Wildl Monogr. 2025;217:e70001. https:\/\/doi.org\/10.1002\/wmon.70001.","journal-title":"Wildl Monogr"},{"key":"668_CR22","doi-asserted-by":"publisher","first-page":"503","DOI":"10.7589\/0090-3558-41.3.503","volume":"41","author":"CE Krumm","year":"2005","unstructured":"Krumm CE, Conner MM, Miller MW. Relative vulnerability of chronic wasting disease infected mule deer to vehicle collisions. J Wildl Dis. 2005;41:503\u201311. https:\/\/doi.org\/10.7589\/0090-3558-41.3.503.","journal-title":"J Wildl Dis"},{"key":"668_CR23","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1098\/rsbl.2009.0742","volume":"6","author":"CE Krumm","year":"2010","unstructured":"Krumm CE, Conner MM, Hobbs NT, Hunter DO, Miller MW. Mountain lions prey selectively on prion-infected mule deer. Biol Lett. 2010;6:209\u201311. https:\/\/doi.org\/10.1098\/rsbl.2009.0742.","journal-title":"Biol Lett"},{"key":"668_CR24","doi-asserted-by":"publisher","first-page":"e4019","DOI":"10.1371\/journal.pone.0004019","volume":"3","author":"MW Miller","year":"2008","unstructured":"Miller MW, Swanson HM, Wolfe LL, Quartarone FG, Huwer SL, Southwick CH, et al. Lions and prions and deer demise. PLoS ONE. 2008;3:e4019. https:\/\/doi.org\/10.1371\/journal.pone.0004019.","journal-title":"PLoS ONE"},{"key":"668_CR25","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1186\/s12874-024-02214-5","volume":"24","author":"Y Xiao","year":"2024","unstructured":"Xiao Y, Chen Y, Huang R, Jiang F, Zhou J, Yang T. Interpretable machine learning in predicting drug-induced liver injury among tuberculosis patients: model development and validation study. BMC Med Res Methodol. 2024;24:92. https:\/\/doi.org\/10.1186\/s12874-024-02214-5.","journal-title":"BMC Med Res Methodol"},{"key":"668_CR26","doi-asserted-by":"publisher","first-page":"471371","DOI":"10.1155\/2015\/471371","volume":"2015","author":"TT Nguyen","year":"2015","unstructured":"Nguyen TT, Huang JZ, Nguyen TT. Unbiased feature selection in learning random forests for high-dimensional data. Sci World J. 2015;2015:471371. https:\/\/doi.org\/10.1155\/2015\/471371.","journal-title":"Sci World J"},{"key":"668_CR27","doi-asserted-by":"publisher","unstructured":"Bank D, Koenigstein N, Giryes R. Autoencoders. In: Rokach L, Maimon O, Shmueli E, editors. Machine learning for data science handbook: data mining and knowledge discovery handbook. 3rd ed. Cham: Springer; 2023. p. 353\u2013374. https:\/\/doi.org\/10.1007\/978-3-031-24628-9_16.","DOI":"10.1007\/978-3-031-24628-9_16"},{"key":"668_CR28","doi-asserted-by":"publisher","first-page":"66","DOI":"10.3390\/robotics9030066","volume":"9","author":"OK Isik","year":"2020","unstructured":"Isik OK, Hong J, Petrunin I, Tsourdos A. Integrity analysis for GPS-based navigation of UAVs in urban environment. Robotics. 2020;9:66.","journal-title":"Robotics"},{"key":"668_CR29","unstructured":"Calenge CadehabitatHR. Home range estimation. R package 0.4.22. 2024. https:\/\/github.com\/clementcalenge\/adehabitathr."},{"key":"668_CR30","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1186\/s40462-021-00281-7","volume":"9","author":"M van de Kerk","year":"2021","unstructured":"van de Kerk M, Larsen RT, Olson DD, Hersey KR, McMillan BR. Variation in movement patterns of mule deer: have we oversimplified migration? Mov. Ecol. 2021;9:44. https:\/\/doi.org\/10.1186\/s40462-021-00281-7.","journal-title":"Ecol"},{"key":"668_CR31","doi-asserted-by":"publisher","unstructured":"Fleming CH, Calabrese JM, Dong X, Winner K, Reineking B, P\u00e9ron G, et al. ctmm: Continuous-time movement modeling. 2025. https:\/\/doi.org\/10.32614\/CRAN.package.ctmm.","DOI":"10.32614\/CRAN.package.ctmm"},{"key":"668_CR32","unstructured":"R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing;2024. https:\/\/www.r-project.org\/."},{"key":"668_CR33","doi-asserted-by":"publisher","DOI":"10.1201\/9780429459016","volume-title":"Spatial data science with applications in R","author":"E Pebesma","year":"2023","unstructured":"Pebesma E, Bivand R. Spatial data science with applications in R. 1st ed. New York, New York: Chapman and Hall\/CRC; 2023. https:\/\/doi.org\/10.1201\/9780429459016.","edition":"1"},{"key":"668_CR34","doi-asserted-by":"crossref","unstructured":"Pebesma E. Simple features for R: Standardized support for spatial vector data. The R Journal. 2018;10:439\u201346. https:\/\/journal.r-project.org\/archive\/2018\/RJ-2018-009\/RJ-2018-009.pdf.","DOI":"10.32614\/RJ-2018-009"},{"key":"668_CR35","doi-asserted-by":"crossref","unstructured":"Wickham H. In: Gentleman R, Hornik K, Parmigiani G, editors. ggplot2: Elegant graphics for data analysis. New York, New York: Springer-; 2016. https:\/\/doi.org\/10.1007\/978-3-319-24277-4.","DOI":"10.1007\/978-3-319-24277-4"},{"key":"668_CR36","doi-asserted-by":"publisher","first-page":"2825","DOI":"10.5555\/1953048.2078195","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Gael Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: Machine learning in Python. J Mach Learn Res. 2011;12:2825\u201330. https:\/\/doi.org\/10.5555\/1953048.2078195.","journal-title":"J Mach Learn Res"},{"key":"668_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v028.i05","volume":"28","author":"M Kuhn","year":"2008","unstructured":"Kuhn M. Building Predictive Models in R Using the caret Package. J Stat Softw. 2008;28:1\u201326. https:\/\/doi.org\/10.18637\/jss.v028.i05.","journal-title":"J Stat Softw"},{"key":"668_CR38","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart DE, Hinton GE, Williams RJ. Learning representations by back-propagating errors. Nature. 1986;323:533\u20136. https:\/\/www.nature.com\/articles\/323533a0.","journal-title":"Nature"},{"key":"668_CR39","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/BF00332918","volume":"59","author":"H Bourlard","year":"1988","unstructured":"Bourlard H, Kamp Y. Auto-association by multilayer perceptrons and singular value decomposition. Biol Cybern. 1988;59:291\u20134. https:\/\/doi.org\/10.1007\/BF00332918.","journal-title":"Biol Cybern"},{"key":"668_CR40","unstructured":"Baldi P. Autoencoders, unsupervised learning, and deep architectures. In: Proceedings of ICML Workshop on Unsupervised and Transfer Learning. 2012;27:27\u201339. https:\/\/proceedings.mlr.press\/v27\/baldi12a\/baldi12a.pdf."},{"key":"668_CR41","unstructured":"Goodfellow I, Bengio Y, Courville A. In: T, editor. Deep Learning. Cambridge, MA: The MIT Press; 2016. https:\/\/mitpress.mit.edu\/9780262035613\/deep-learning\/."},{"key":"668_CR42","doi-asserted-by":"publisher","first-page":"7937","DOI":"10.1038\/s41467-023-43455-0","volume":"14","author":"Y Baig","year":"2023","unstructured":"Baig Y, Ma HR, Xu H, You L. Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics. Nat Commun. 2023;14:7937. https:\/\/doi.org\/10.1038\/s41467-023-43455-0.","journal-title":"Nat Commun"},{"key":"668_CR43","doi-asserted-by":"crossref","unstructured":"Zhou C, Paffenroth RC. Anomaly detection with robust deep autoencoders. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD \u201917); 2017 Aug 13\u201317; Halifax, NS, Canada. New York (NY): ACM; 2017. p. 665\u2013674. https:\/\/www.eecs.yorku.ca\/course_archive\/2017-18\/F\/6412\/reading\/kdd17p665.pdf.","DOI":"10.1145\/3097983.3098052"},{"key":"668_CR44","unstructured":"Abadi M, Agarwal A, Barham P, et al. TensorFlow: large-scale machine learning on heterogeneous systems. 2015. https:\/\/www.tensorflow.org\/."},{"key":"668_CR45","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1111\/1365-2656.12379","volume":"85","author":"E Gurarie","year":"2016","unstructured":"Gurarie E, Bracis C, Delgado M, Meckley TD, Kojola I, Wagner CM. What is the animal doing? Tools for exploring behavioural structure in animal movements. J Anim Ecol. 2016;85:69\u201384.","journal-title":"J Anim Ecol"},{"key":"668_CR46","doi-asserted-by":"publisher","first-page":"e70323","DOI":"10.1111\/1365-2664.70323","volume":"63","author":"D Kim","year":"2026","unstructured":"Kim D, Michelot T, Mertes K, Stabach JA, Fieberg J. Detecting disease progression from animal movement using hidden Markov models. J Appl Ecol. 2026;63:e70323.","journal-title":"J Appl Ecol"},{"key":"668_CR47","doi-asserted-by":"publisher","first-page":"103401","DOI":"10.1016\/j.ecoinf.2025.103401","volume":"23","author":"V Sethi","year":"2025","unstructured":"Sethi V, Spiegel O, Salter R, Cain S, Toledo S, Getz WM. An information theory framework for hierarchical path segmentation and analysis of animal movement. Ecol Inf. 2025;23:103401.","journal-title":"Ecol Inf"},{"key":"668_CR48","doi-asserted-by":"publisher","first-page":"1741","DOI":"10.1890\/14-1401.1","volume":"96","author":"CC Wilmers","year":"2015","unstructured":"Wilmers CC, Nickel B, Bryce CM, Smith JA, Wheat RE, Yovovich V. The golden age of bio-logging: How animal\u2010borne sensors are advancing the frontiers of ecology. Ecology. 2015;96:1741\u201353. https:\/\/doi.org\/10.1890\/14-1401.1.","journal-title":"Ecology"}],"container-title":["Movement Ecology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40462-026-00668-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40462-026-00668-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40462-026-00668-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T02:46:03Z","timestamp":1786934763000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s40462-026-00668-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,10]]},"references-count":48,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["668"],"URL":"https:\/\/doi.org\/10.1186\/s40462-026-00668-4","relation":{},"ISSN":["2051-3933"],"issn-type":[{"value":"2051-3933","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,10]]},"assertion":[{"value":"9 February 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"All procedures were approved by the University of Wyoming Institutional Animal Care and Use Committee (A-3216-01) and Wyoming Game and Fish Department (Permit No. 33\u2013751).","order":1,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"57"}}