Response to M Krkošek, C W Revie, B Finstad and C D Todd's comment on Jackson et al. ‘Impact of <scp>L</scp>epeophtheirus salmonis infestations on migrating Atlantic salmon, <scp>S</scp>almo salar L., smolts at eight locations in Ireland with an analysis of lice‐induced marine mortality’

Jackson, David W.; Cotter, D.; O'Donohoe, P.; Kane, Frank; McDermott, Tom; Kelly, S.; Drumm, A.

doi:10.1111/jfd.12239

Cited by 4 publications

(1 citation statement)

References 11 publications

(18 reference statements)

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“…This means that, by necessity, manipulative studies are rare compared with correlative studies. Even when manipulative studies have been possible [3,69], debate and controversy have persisted [70,71]. Another major challenge is the fact that a negative statistical result does not necessarily translate to a negative biological conclusion.…”

Section: Discussionmentioning

confidence: 99%

Lessons from sea louse and salmon epidemiology

Groner

Rogers

Bateman

et al. 2016

Phil. Trans. R. Soc. B

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Effective disease management can benefit from mathematical models that identify drivers of epidemiological change and guide decision-making. This is well illustrated in the host-parasite system of sea lice and salmon, which has been modelled extensively due to the economic costs associated with sea louse infections on salmon farms and the conservation concerns associated with sea louse infections on wild salmon. Consequently, a rich modelling literature devoted to sea louse and salmon epidemiology has been developed. We provide a synthesis of the mathematical and statistical models that have been used to study the epidemiology of sea lice and salmon. These studies span both conceptual and tactical models to quantify the effects of infections on host populations and communities, describe and predict patterns of transmission and dispersal, and guide evidence-based management of wild and farmed salmon. As aquaculture production continues to increase, advances made in modelling sea louse and salmon epidemiology should inform the sustainable management of marine resources.

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Section: Discussionmentioning

confidence: 99%

Lessons from sea louse and salmon epidemiology

Groner

Rogers

Bateman

et al. 2016

Phil. Trans. R. Soc. B

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Context-dependent impact of an ectoparasite on early marine growth in Atlantic salmon

2019

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Salmon lice infestations on sea trout predicts infestations on migrating salmon post-smolts

Vollset

Halttunen

Finstad

et al. 2017

ICES Journal of Marine Science

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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.

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Response to M Krkošek, C W Revie, B Finstad and C D Todd's comment on Jackson et al. ‘Impact of Lepeophtheirus salmonis infestations on migrating Atlantic salmon, Salmo salar L., smolts at eight locations in Ireland with an analysis of lice‐induced marine mortality’

Cited by 4 publications

References 11 publications

Lessons from sea louse and salmon epidemiology

Lessons from sea louse and salmon epidemiology

Context-dependent impact of an ectoparasite on early marine growth in Atlantic salmon

Salmon lice infestations on sea trout predicts infestations on migrating salmon post-smolts

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