Application of machine learning to identify predators of stocked fish in Lake Ontario : using acoustic telemetry predation tags to inform management-Reference-Cited by-同舟云学术

Application of machine learning to identify predators of stocked fish in Lake Ontario : using acoustic telemetry predation tags to inform management

Published:2020-11-03 Issue:1 Volume:98 Page:237-250
ISSN:0022-1112
Container-title:Journal of Fish Biology
language:en
Short-container-title:J Fish Biol

Author:

Klinard Natalie V.¹^ORCID,Matley Jordan K.¹,Ivanova Silviya V.¹,Larocque Sarah M.¹,Fisk Aaron T.¹,Johnson Timothy B.²

Affiliation:

1. Great Lakes Institute for Environmental Research, University of Windsor Windsor Ontario Canada

2. Ontario Ministry of Natural Resources and Forestry, Glenora Fisheries Station Picton Ontario Canada

Funder

Great Lakes Fishery Commission

Ministry of Natural Resources

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

Subject

Aquatic Science,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfb.14574

Reference71 articles.

1. Baldwin B.(1999).Native prey fish re‐introduction into Lake Ontario: Bloater (Coregonus hoyi). Lake Ontario Technical Committee Discussion Paper. London Ontario Canada: Great Lakes Fishery Commission.

2. Bence J. R. Dobiesz N. E. Madenjian C. P. Argyle R. Barbiero R. Bowlby J. N. Claramunt R. M. O'Gorman R. &Schaner T.(2008).Top‐down effects of open‐water salmonine predators in the Great Lakes(Quantitative Fisheries Center Technical Report T2009‐07). East Lansing MI: Michigan State University.

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