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Soc. Open Sci."],"published-print":{"date-parts":[[2024,6]]},"abstract":"<jats:p>\n                    Marine predators are integral to the functioning of marine ecosystems, and their consumption requirements should be integrated into ecosystem-based management policies. However, estimating prey consumption in diving marine predators requires innovative methods as predator\u2013prey interactions are rarely observable. We developed a novel method, validated by animal-borne video, that uses tri-axial acceleration and depth data to quantify prey capture rates in chinstrap penguins (\n                    <jats:italic>Pygoscelis antarctica<\/jats:italic>\n                    ). These penguins are important consumers of Antarctic krill (\n                    <jats:italic>Euphausia superba<\/jats:italic>\n                    ), a commercially harvested crustacean central to the Southern Ocean food web. We collected a large data set (\n                    <jats:italic>n<\/jats:italic>\n                    = 41 individuals) comprising overlapping video, accelerometer and depth data from foraging penguins. Prey captures were manually identified in videos, and those observations were used in supervised training of two deep learning neural networks (convolutional neural network (CNN) and V-Net). Although the CNN and V-Net architectures and input data pipelines differed, both trained models were able to predict prey captures from new acceleration and depth data (linear regression slope of predictions against video-observed prey captures = 1.13;\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u2248 0.86). Our results illustrate that deep learning algorithms offer a means to process the large quantities of data generated by contemporary bio-logging sensors to robustly estimate prey capture events in diving marine predators.\n                  <\/jats:p>","DOI":"10.1098\/rsos.240271","type":"journal-article","created":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T19:06:53Z","timestamp":1718737613000},"update-policy":"https:\/\/doi.org\/10.1098\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Identifying prey capture events of a free-ranging marine predator using bio-logger data and deep learning"],"prefix":"10.1098","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6566-0443","authenticated-orcid":true,"given":"Stefan","family":"Schoombie","sequence":"first","affiliation":[{"name":"Department of Statistical Sciences, Centre for Statistics in Ecology, Environment and Conservation (SEEC), University of Cape Town , Cape Town 7701, South Africa"},{"name":"National Institute for Theoretical and Computational Sciences , South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lor\u00e8ne","family":"Jeantet","sequence":"additional","affiliation":[{"name":"African Institute for Mathematical Sciences , Cape Town 7945, South Africa"},{"name":"Department of Mathematical Sciences, Stellenbosch University , Stellenbosch 7602, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marianna","family":"Chimienti","sequence":"additional","affiliation":[{"name":"Centre D\u2019\u00c9tudes Biologiques de Chiz\u00e9, UMR7372 CNRS-La Rochelle , Villiers-en-Bois, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grace J.","family":"Sutton","sequence":"additional","affiliation":[{"name":"Department of Environment &amp; Genetics, and Research Centre for Future Landscapes, La Trobe University , Melbourne, VIC 3086, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6561-7069","authenticated-orcid":true,"given":"Pierre A.","family":"Pistorius","sequence":"additional","affiliation":[{"name":"Marine Apex Predator Research Unit, Department of Zoology and Institute for Coastal and Marine Research, Nelson Mandela University , Gqeberha 6031, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuel","family":"Dufourq","sequence":"additional","affiliation":[{"name":"African Institute for Mathematical Sciences , Cape Town 7945, South Africa"},{"name":"Department of Mathematical Sciences, Stellenbosch University , Stellenbosch 7602, South Africa"},{"name":"African Institute for Mathematical Sciences, Research and Innovation Centre , Kigali, Rwanda"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew D.","family":"Lowther","sequence":"additional","affiliation":[{"name":"Norwegian Polar Institute , Troms\u00f8, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2905-6297","authenticated-orcid":true,"given":"W. 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