Salmon lice infestations on sea trout predicts infestations on migrating salmon post-smolts. (1st June 2017)

• Record Type: Journal Article
• Authors: Vollset, Knut Wiik; Halttunen, Elina; Finstad, Bengt; Karlsen, Ørjan; Bjørn, Pål Arne; Dohoo, Ian
• Editors: Gibbs, Mark
• Is Part Of: ICES journal of marine science. Volume 74:Number 9(2017)
• Page Start: 2354
• Page End: 2363
• Publication Date: 2017-06-01
• Subjects: aquaculture -- conservation -- fish farming -- Lepeophtheirus salmonis -- management -- parasite -- salmonids -- salmon lice -- Salmo salar; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsx090
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: Impacts of sea lice ( Lepeophtheirus salmonis or Caligus spp. ) on wild salmonids is currently one of the most important issues facing management of fish farms in salmon producing countries in the northern hemisphere. Surveillance of sea lice on wild Atlantic salmon ( Salmo salar ) is often hampered by the ability to catch enough migrating post-smolts. Therefore, sea lice abundance on anadromous trout ( Salmo trutta ) is often used to infer sea lice abundance on migrating salmon post-smolt. However, the assumption that there is a relationship between the abundance of lice on salmon and trout has never been tested. Here we use a dataset of sea lice on salmon post-smolt and sea trout that have been caught simultaneously in trawl hauls, to evaluate the correlation in abundance of sea lice between the two species using various statistical models. We demonstrate that trout generally has higher abundances of sea lice than salmon. Average lice per gram fish on sea trout (log transformed) predicted the abundance of lice on salmon best. Negative binomial models of lice counts were preferable to using trout lice counts as direct estimates of salmon lice abundance, and they had better predictive ability than logit models of high (vs. low) lice counts. Including the size of the salmon increased the predictive ability of the model, but these data are not generally available. The effect of salmon weight may have been a direct effect of body size, or an indirect effect of time spent in marine waters. Finally, we predict lower salmon lice counts on migrating salmon with our selected binomial model than with the current method of using trout lice counts as a direct estimator on salmon lice counts, and demonstrate that management advice would change considerably depending on the chosen method.