A metapopulation model reveals connectivity-driven hotspots in treatment resistance evolution in a marine parasite

Abstract

In salmon aquaculture, the sustainable management of salmon lice (Lepeophtheirus salmonis) is limited by the adaptive capacity of the parasite. This is evident in the repeated evolution of pesticide resistance in the salmon louse population. To better prepare for resistance, we constructed a numerical metapopulation model that predicts the evolutionary dynamics of lice across an interconnected farm network. This model integrates within-farm population dynamics and between-farm louse dispersal, the latter using outputs from a state-of-the-art particle-tracking model. Distinct from previous metapopulation models, it also simulates spatial and temporal genetic variation arising from selection. The model was parameterized to simulate the evolution of resistance to the pesticide azamethiphos on farms in southern Norway. It successfully reproduced the rapid (within 10 years) evolution of azamethiphos resistance following extensive delousing treatments. It also identified strong spatial patterns in resistance, with regions of high farm connectivity being potential hotspots of louse adaptation. Rates of infestation and evolution were significantly reduced when highly connected farms were excluded from the simulation, compared to when low-connectivity or random sites were excluded. This model can be a valuable tool for coordinating pest management at a regional scale, in a way that slows or prevents the spread of resistance.

Evolutionary predictions for a parasite metapopulation: Modelling salmon louse resistance to pest controls in aquaculture

“…As in Coates et al. (2022), the resistant allele, R, started at a very low frequency ( p = 0.005) throughout the metapopulation.…”

“…In all scenarios, the R allele had an additive effect, so that the fitness of heterozygotes was midway between that of the homozygotes. As in Coates et al (2022), the resistant allele, R, started at a very low frequency (p = 0.005) throughout the metapopulation.…”

“…Evolutionary models offer the opportunity to explore how the pressures experienced on farms shape the epidemiology and evolution of parasites across very large spatial and temporal scales; scales that would be difficult to test empirically (Haridas & Tenhumberg, 2018;Liang et al, 2013;Onstad et al, 2013;Sisterson et al, 2005). Coates et al (2022) constructed a model that simulated the metapopulation dynamics of salmon lice (Lepeophtheirus salmonis) infesting Atlantic salmon (Salmo salar) farms in southern Norway. Salmon lice are the most significant parasite affecting salmonid aquaculture, posing major economic, ecological and welfare problems (Torrissen et al, 2013).…”

“…Coates et al. (2022) constructed a model that simulated the metapopulation dynamics of salmon lice ( Lepeophtheirus salmonis ) infesting Atlantic salmon ( Salmo salar ) farms in southern Norway. Salmon lice are the most significant parasite affecting salmonid aquaculture, posing major economic, ecological and welfare problems (Torrissen et al., 2013).…”

Research pre-empting parasite adaptation is key to sustainable disease management in aquaculture

“…If these 2 types of models can be integrated into one that captures both metapopulation and evolutionary dynamics (e.g. Coates et al 2022), then the options for exploring louse adaptation at a regional scale are vast. The under lying machinery of such a model could also be adapted for a range of other para site and/or aquaculture systems.…”