The relevance of larval biology on spatiotemporal patterns of pathogen connectivity among open-marine salmon farms
Cantrell, Danielle and Filgueira, Ramón and Revie, Crawford W. and Rees, Erin and Vanderstichel, Raphael and Guo, Ming and Foreman, Michael G.G. and Wan, Di and Grant, Jon (2020) The relevance of larval biology on spatiotemporal patterns of pathogen connectivity among open-marine salmon farms. Canadian Journal of Fisheries and Aquatic Sciences, 77 (3). pp. 505-519. ISSN 1205-7533
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Abstract
Warming waters are changing marine pathogen dispersal patterns and infectivity worldwide. Coupled biological-physical modelling has been used in many systems to determine the connectivity of meta-populations via infectious disease particles. Here we model the connectivity of sea lice larvae (Lepeophtheirus salmonis) among salmon farms in the Broughton Archipelago, British Columbia, Canada, using a coupled biological-physical model. The physical model simulated pathogen dispersal, while the biological component influenced the survival and developmental rates of the sea lice. Model results predicted high temporal variability in connectivity strength among farms; an emergent effect from the interacting parts of the simulation (dispersion vs. survival/development). Drivers of temporal variability were disentangled using generalized additive modeling, which revealed the variability was most strongly impacted by the spring freshet, which can act as a natural aid for sea lice control in the Broughton Archipelago. Our results suggest that farm management strategies can benefit by taking into account short-term spikes in regional pathogen connectivity among farms. Additionally, future scenarios of a warming climate with reduced snowpack can make sea lice control more challenging.
Creators(s): |
Cantrell, Danielle, Filgueira, Ramón, Revie, Crawford W. ![]() | Item type: | Article |
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ID code: | 70005 |
Keywords: | larva, salmon farms, marine pathogens, Aquaculture. Fisheries. Angling, Probabilities. Mathematical statistics, Statistics and Probability, Aquatic Science |
Subjects: | Agriculture > Aquaculture. Fisheries. Angling Science > Mathematics > Probabilities. Mathematical statistics |
Department: | Faculty of Science > Computer and Information Sciences |
Depositing user: | Pure Administrator |
Date deposited: | 02 Oct 2019 08:41 |
Last modified: | 03 Jan 2021 02:33 |
URI: | https://strathprints.strath.ac.uk/id/eprint/70005 |
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