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Modeling Parasite Dynamics on Farmed Salmon for Precautionary Conservation Management of Wild Salmon

Overview of attention for article published in PLOS ONE, April 2013
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Title
Modeling Parasite Dynamics on Farmed Salmon for Precautionary Conservation Management of Wild Salmon
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0060096
Pubmed ID
Authors

Luke A. Rogers, Stephanie J. Peacock, Peter McKenzie, Sharon DeDominicis, Simon R. M. Jones, Peter Chandler, Michael G. G. Foreman, Crawford W. Revie, Martin Krkošek

Abstract

Conservation management of wild fish may include fish health management in sympatric populations of domesticated fish in aquaculture. We developed a mathematical model for the population dynamics of parasitic sea lice (Lepeophtheirus salmonis) on domesticated populations of Atlantic salmon (Salmo salar) in the Broughton Archipelago region of British Columbia. The model was fit to a seven-year dataset of monthly sea louse counts on farms in the area to estimate population growth rates in relation to abiotic factors (temperature and salinity), local host density (measured as cohort surface area), and the use of a parasiticide, emamectin benzoate, on farms. We then used the model to evaluate management scenarios in relation to policy guidelines that seek to keep motile louse abundance below an average three per farmed salmon during the March-June juvenile wild Pacific salmon (Oncorhynchus spp.) migration. Abiotic factors mediated the duration of effectiveness of parasiticide treatments, and results suggest treatment of farmed salmon conducted in January or early February minimized average louse abundance per farmed salmon during the juvenile wild salmon migration. Adapting the management of parasites on farmed salmon according to migrations of wild salmon may therefore provide a precautionary approach to conserving wild salmon populations in salmon farming regions.

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Geographical breakdown

Country Count As %
United Kingdom 1 1%
Canada 1 1%
Unknown 78 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 24%
Researcher 14 18%
Student > Bachelor 11 14%
Other 7 9%
Student > Master 6 8%
Other 12 15%
Unknown 11 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 36%
Environmental Science 18 23%
Veterinary Science and Veterinary Medicine 3 4%
Earth and Planetary Sciences 3 4%
Computer Science 2 3%
Other 11 14%
Unknown 14 18%