Title: Threshold-based disease treatment approach modulates economic, conservation and evolutionary trade-offs in sea louse-salmon aquaculture system
Authors: Laurinne J Balstad, Sean C Godwin, Martin Krkosek, Mark A Lewis, Marissa L Baskett
Abstract: Mitigating negative downstream impacts of parasitic disease in domestic settings is difficult: reducing parasite loads has economic and conservation benefits, but treatment is often expensive, and frequent treatment can lead to resistance evolution. The sea louse-salmon aquaculture case highlights these challenges. In the sea louse-salmon system, managers use discrete treatment applications to control louse burdens, applying treatment only when there is sufficiently high parasite burden. Such discrete treatment application could moderate evolutionary, conservation and economic outcomes by changing the relative parasite burdens across environments, but this type of effect has been largely ignored by past work. Here, we create a model that incorporates discrete, threshold based treatment and host movement patterns, which mimics the sea louse-salmon system. Our model shows that simultaneous economic and conservation win-wins are possible: there are treatment thresholds choices that lead to relatively high wild juvenile salmon population sizes and relatively low economic losses, especially when treatment is very effective or treatment is cheap. However, positive evolutionary outcomes are harder to capture and occur most often when treatment efficacy is low and treatment threshold is either (a) near zero, or (b) very high. Alternative management levers, such as careful farm placement and conservation of wild fish, can help slow resistance evolution. Expanding the management toolbox beyond choices of treatment threshold and treatment efficacy could help managers better capture positive economic, evolutionary and conservation outcomes in the system.
Keywords: Salmon aquaculture, sea lice, treatment resistance, parasite refugia, expenditure frontiers, macroparasites
Repository: Code for model simulations, base model parameters, and figures.