Application of machine learning algorithms to identify cryptic reproductive habitats using diverse information sources.

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作者： Jacob W,Brownscombe ^[1] ; Lucas P,Griffin ^[2] ; Danielle,Morley ^[3] ; Alejandro,Acosta ^[4] ; John,Hunt ^[4] ; Susan K,Lowerre-Barbieri ^[4] ; Aaron J,Adams ^[5] ; Andy J,Danylchuk ^[6] ; Steven J,Cooke ^[7]

作者单位： Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel by Drive, Ottawa, ON, K1S 5B6, Canada. jakebrownscombe@gmail.com. ^[1] Department of Biology, Dalhousie University, 1355 Oxford Street, Halifax, NS, B4H 4R2, Canada. jakebrownscombe@gmail.com. ^[2] Department of Environmental Conservation, University of Massachusetts Amherst, 160 Holdsworth Way, Amherst, MA, 01003, USA. ^[3] Florida Fish and Wildlife Conservation Commission, 2796 Overseas Highway, Suite 119, Marathon, FL, 33050, USA. ^[4] Florida Fish and Wildlife Conservation Commission, Fish and Wildlife Research Institute, 100 8th Avenue Southeast, St. Petersburg, FL, 33701, USA. ^[5] Fisheries and Aquatic Science Program, School of Forest Resources and Conservation, University of Florida, 7922 Northwest 71st Street, Gainesville, FL, 32653-3071, USA. ^[6] Bonefish and Tarpon Trust, 135 San Lorenzo Ave., Suite 860, Coral Gables, FL, 33146, USA. ^[7] Florida Atlantic University Harbor Branch Oceanographic Institute, 5600 North Highway A1A, Fort Pierce, FL, USA. ^[8] Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel by Drive, Ottawa, ON, K1S 5B6, Canada. ^[9]

关键词 Conservation Ecology Machine learning Marine biology Spawning aggregations

主题词算法(Algorithms);动物(Animals);生态系统(Ecosystem);佛罗里达(Florida);生殖(Reproduction)

DOI 10.1007/s00442-020-04753-2

PMID 33006076

发布时间 2020-10-19

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准确一般字义偏差语意偏离译文作用小提交