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

Abstract

For successful evaluation of the overall effects of salmon louse infestation on brown trout population dynamics, it is crucial to have a realistic understanding of how lice infestation distributions are generated and how they should be interpreted. Here, we simulated the potential effects of spatio-temporal variance in lice larvae densities, temporal variance in sea trout marine migration timing and spatial variance in marine habitat use on lice infestation distributions. We show that, when sampling populations with individual variation in marine behaviour, e.g. from post-smolts to veteran migrants, we must expect multi-modal mixture lice infestation distributions. Applying standard statistical distributions, such as the Poisson, negative binomial or zero-inflated distributions, can be too simplistic and give biased results. Temporary increases in salmon lice load in a given area may have inconsistent effects among individuals of a population and may be critical for vulnerable groups such as post-smolts, dependent on timing. For many analyses, it will be necessary to resolve the contributions from groups of fish with different lice infestation expectations due to spatio-temporal differences in habitat use within the overall mixture distribution. Another consequence is that different data sources, obtained by different methods or sampled at different locations and periods, must be expected to give different lice infestation distributions, even when sampling the same population. We also discuss additional factors that may complicate the interpretation of salmon lice infestation distributions on sea trout, such as lice-induced mortality, and behavioural changes, such as premature return to less saline water for delousing.

Salmon louse infestation levels on sea trout can be predicted from a hydrodynamic lice dispersal model

“…Sea trout display a diversity of marine migration patterns and life-history strategies (Davidsen et al, 2014). Thus, samples of sea trout collected will likely consist of several subpopulations with different lice infestation rates and distributions, depending on marine residence time and habitat use (Diserud et al, 2020). Sea trout with high lice infestations have a higher probability of dying or prematurely returning to freshwater (Serra-Llinares et al, 2020), and this group may therefore be under-represented in catch samples.…”

“…Two specific ways to improve further studies are to detail the information on individual fish sampled: (a) genetic analysis that reveals from where each sampled sea trout have originated would reduce the variability and improve our ability to predict lice infestations on the fish (Diserud et al, 2020); (b) analyses of scales may reveal the migratory history of the individual fish. Most important is the timing of the shift from freshwater to sea water.…”

Factors influencing return rate and marine residence duration in sea trout populations in Central Norway

“…Migration behaviour may also modify L. salmonis infestations on sea trout. For instance, individuals which migrate to areas without salmon farms, those that make brief returns to fresh or brackish water and/or individuals with shorter overall marine residence durations may benefit from lower exposure to L. salmonis infective stages (Diserud et al ., 2020; Serra‐Llinares et al ., 2020). Low salinity waters reduce the survival of L. salmonis (Andrews & Horsberg, 2020; Bricknell et al ., 2006), in addition to reducing the effects of lice‐induced osmotic stress to infected trout (Birkeland & Jakobsen, 1997; Wells et al ., 2007).…”