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

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.

The effect of temperature on ability of Lepeophtheirus salmonis to infect and persist on Atlantic salmon

“…Due to the negative effects of infection, authorities impose strict regulations on the aquaculture industry to reduce the number of parasites produced on farmed fish and the spread of infective larvae to wild fish (Forseth et al., 2017; Olaussen, 2018). For example, in Norway, aquaculture farm sites are required to quantify the level of infection on their fish (Nekouei et al., 2018; Torrissen et al., 2013; Vollset et al., 2017) and report these numbers weekly to the Norwegian Ministry for Food and Fisheries (Anon., 2012). Counting of salmon lice on fish is demanding due to the small size of the early parasitic stages, especially the copepodid and the first chalimus stage, which are ≤ 1.4 mm (Eichner, Hamre, & Nilsen, 2015).…”

Evaluation of a national operational salmon lice monitoring system—From physics to fish

“…The observations of salmon lice infestations on sea trout is used in the annual risk assessment of the environmental impact of Norwegian salmon farming [ 62 ]. However, recent investigations comparing trawled trout and salmon have shown that there is a correlation between lice levels, but also that trout generally has higher abundance of lice than salmon [ 68 ]. These results are important to consider when assessing the overall risk in a production zone but will not affect the correlation between modeled infestation pressure and observed lice on wild fish found here.…”

Salmon louse infestation in wild brown trout populations generates multi-modal mixture distributions

“…For successful evaluation of the effect of salmon lice on sea trout population dynamics, it is crucial to have a realistic understanding of the salmon louse infestation process under different scenarios of lice larvae densities. Lice infestation models exist for Atlantic salmon (Sandvik et al 2016, Kristoffersen et al 2018 but because the marine habitat use and behaviour of sea trout differs substantially from that of Atlantic salmon (Vollset et al 2017), a dedicated lice infesta-tion model for sea trout is required. In addition, controlled infestation challenges suggest that different host species may differ in their susceptibility to salmon lice (Bui et al 2018).…”

“…Salmon louse infestation in wild sea trout populations must therefore be expected to generate multi-modal mixture distributions. Most studies of salmon louse infestation distributions either use the Poisson (Murray 2002, Patanasatienkul et al 2015 or the negativebinomial distribution (Heuch et al 2011, Vollset et al 2017, 2018a; these approaches may be too simplistic because they assume all lice counts are observations from the same distribution. Alternatively, zero-inflated distributions, which can be considered to be a 2-modal version of the mixture distribution where the 'false zeros' are from a group of fish that have not been exposed to salmon louse, have been used (Kristoffersen et al 2013, Helland et al 2015.…”