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Salmon farming has become a prosperous international industry over the lastdecades. Along with growth in the production farmed salmon, however, anincreasing threat by pathogens has emerged. Of special concern is thepropagation and spread of the salmon louse, Lepeophtheirus salmonis. In orderto gain insight into this parasites population dynamics in large scale salmonfarming system, we present a fully mechanistic stage-structured populationmodel for the salmon louse, also allowing for complexities involved in thehierarchical structure of full scale salmon farming. The model estimatesparameters controlling a wide range of processes, including temperaturedependent demographic rates, fish size and abundance effects on lousetransmission rates, effects sizes of various salmon louse control measures, anddistance based between farm transmission rates. Model parameters were estimatedfrom data including 32 salmon farms, except the last production months for fivefarms which were used to evaluate model predictions. We used a Bayesianestimation approach, combining the prior distributions and the data likelihoodinto a joint posterior distribution for all model parameters. The modelgenerated expected values that fitted the observed infection levels of thechalimus, adult female and other mobile stages of salmon lice, reasonably well.Predictions for the time periods not used for fitting the model were alsoconsistent with the observational data. We argue that the present model for thepopulation dynamics of the salmon louse in aquaculture farm systems maycontribute to resolve the complexity of processes that drive that drive thishost-parasite relationship, and hence may improve strategies to control theparasite in this production system.

A stage-structured Bayesian hierarchical model for salmon lice populations at individual salmon farms - Estimated from multiple farm data sets