Using agent-based modelling to predict the role of wild refugia in the evolution of resistance of sea lice to chemotherapeutants
McEwan, Gregor F. and Groner, Maya L. and Fast, Mark D. and Gettinby, George and Revie, Crawford W. (2015) Using agent-based modelling to predict the role of wild refugia in the evolution of resistance of sea lice to chemotherapeutants. PLoS ONE, 10 (10). e0139128. ISSN 1932-6203 (https://doi.org/10.1371/journal.pone.0139128)
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Abstract
A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments.
ORCID iDs
McEwan, Gregor F., Groner, Maya L., Fast, Mark D., Gettinby, George and Revie, Crawford W. ORCID: https://orcid.org/0000-0002-5018-0340;-
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Item type: Article ID code: 64217 Dates: DateEvent20 October 2015Published8 September 2015AcceptedSubjects: Agriculture > Aquaculture. Fisheries. Angling
Science > MicrobiologyDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 04 Jun 2018 10:03 Last modified: 11 Nov 2024 12:00 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/64217