Landscape Ecology

, Volume 30, Issue 6, pp 989–1004

Spatial patterns of sea lice infection among wild and captive salmon in western Canada

  • E. E. Rees
  • S. St-Hilaire
  • S. R. M. Jones
  • M. Krkošek
  • S. DeDominicis
  • M. G. G. Foreman
  • T. Patanasatienkul
  • C. W. Revie
Research Article

DOI: 10.1007/s10980-015-0188-2

Cite this article as:
Rees, E.E., St-Hilaire, S., Jones, S.R.M. et al. Landscape Ecol (2015) 30: 989. doi:10.1007/s10980-015-0188-2

Abstract

Context

Parasite transmission between captive and wild fish is mediated by spatial, abiotic, biotic, and management factors. More effective population management and conservation strategies can result from multivariable assessments of factors associated with spatial dynamics of parasite spillover.

Objective

Our study characterised spatial patterns of sea lice (Lepeophtheirus salmonis,Caligus clemensi) infection on out-migrating chum (Oncorhynchus keta) and pink (O. gorbuscha) salmon in an area with Atlantic salmon (Salmo salar) farming.

Methods

A multivariable statistical model for sea louse parasitism of out-migrating chum and pink salmon was developed from 166,316 wild salmon sampled in the Broughton Archipelago, British Columbia, Canada from 2003 to 2012. We assessed for factors hypothesized to influence sea lice infection levels, at the non-motile life stage, including spatial scales of infection sources.

Results

Fish length, sampling year and method were strong explanatory factors. Infection was greatest in higher salinity water. Farmed and wild juvenile salmon infection levels were correlated, on average, within 30 km. Except for 2004, sea lice infection on farms were typically well below the regulatory level (3 motiles per fish). Average intensity of non-motile infections observed on the wild fish were 6.36 (SD = 9.98) in 2004 compared to 1.66 (SD = 1.25) for the other years.

Conclusions

Accuracy of future model estimates will benefit by including hydrodynamic data accounting for anisotropic spread of sea lice from sources. Multivariable statistical modelling over long time series data strengthens understanding of factors impacting wild juvenile salmon infection levels and informs spatial patterns of aquatic epidemiology.

Keywords

Atlantic salmon aquacultureBritish ColumbiaCaligus clemensiLepeophtheirus salmonisPacific salmonSea liceSpatial–temporal modeling

Supplementary material

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Supplementary material 1 (DOCX 1803 kb)
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Supplementary material 2 (DOCX 1803 kb)
10980_2015_188_MOESM3_ESM.docx (16 kb)
Supplementary material 3 (DOCX 15 kb)
10980_2015_188_MOESM4_ESM.docx (19 kb)
Supplementary material 4 (DOCX 19 kb)

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • E. E. Rees
    • 1
  • S. St-Hilaire
    • 1
  • S. R. M. Jones
    • 2
  • M. Krkošek
    • 3
  • S. DeDominicis
    • 4
  • M. G. G. Foreman
    • 5
  • T. Patanasatienkul
    • 1
  • C. W. Revie
    • 1
  1. 1.Department of Health Management, Atlantic Veterinary CollegeUniversity of Prince Edward IslandCharlottetownCanada
  2. 2.Pacific Biological Station, Fisheries and Oceans CanadaNanaimoCanada
  3. 3.Department of Ecology and Evolutionary BiologyUniversity of TorontoTorontoCanada
  4. 4.Marine Harvest CanadaCampbell RiverCanada
  5. 5.Institute of Ocean Sciences, Fisheries and Oceans CanadaSidneyCanada