Increased frequency and changed methods in the treatment of sea lice (Lepeophtheirus salmonis) in Scottish salmon farms 2005-2011

A modeling study of the impact of treatment policies on the evolution of resistance in sea lice on salmon farms

Salmonid aquaculture is an important source of nutritious food with more than 2 million tonnes of fish produced each year (Food and Agriculture Organisation of the United Nations, 2019). In most salmon producing countries, sea lice represent a major barrier to the sustainability of salmonid aquaculture. This issue is exacerbated by widespread resistance to chemical treatments on both sides of the Atlantic. Regulation for sea lice management mostly involves reporting lice counts and treatment thresholds, which depending on interpretation may encourage preemptive treatments. We have developed a stochastic simulation model of sea lice infestation including the lice life-cycle, genetic resistance to treatment, a wildlife reservoir, salmon growth and stocking practices in the context of infestation, and coordination of treatment between farms. Farms report infestation levels to a central organisation, and may then cooperate or not when coordinated treatment is triggered. Treatment practice then impacts the level of resistance in the surrounding sea lice population. Our simulation finds that treatment drives selection for resistance and coordination between managers is key. We also find that position in the hydrologically-derived network of farms can impact individual farm infestation levels and the topology of this network can impact overall infestation and resistance. We show how coordination and triggering of treatment alongside varying hydrological topology of farm connections affects the evolution of lice resistance, and thus optimise salmon quality within socio-economic and environmental constraints. Network topology drives infestation levels in cages, treatments, and hence treatment-driven resistance. Thus farmer behaviour may be highly dependent on hydrologically position and local level of infestation.

Drug and pesticide usage for sea lice treatment in salmon aquaculture sites in a Canadian province from 2016 to 2019

We used 4 years of publicly available data (2016–2019) on chemical usage at salmon sites with information on production, stocking, locations and environmental conditions to explore patterns of anti-sea lice treatments in a Canadian province. Results show that sequential chemical treatments are prevalent, emamectin benzoate (EMB) with azamethiphos being the most used combination with a decrease in ivermectin usage. Relatively high rates of usage of EMB per fish biomass may point to potential lice resistance patterns with information needed on mechanisms and local populations. Lower or no chemical usage at some sites indicate less sea lice infestations likely influenced by localized site conditions (coves), and a lessened need for medication due to the usage of cleaner fish and possibly other non-chemical methods (not documented in this report). The year/climate influenced chemical input only in sites with higher treatment levels likely due to effects on sea lice growth and reproduction. Observed differences between years are warmer surface temperature in the fall, a higher freshwater input in spring, and stronger wind conditions for 2017 and 2018 with more medication usage for these two years. The lack of significant effect of site distances calculated in zones of influence based on 24 h potential connectivity patterns highlight the need to refine the resolution of hydrodynamic processes.

Negative effects of the sea lice therapeutant emamectin benzoate at low concentrations on benthic communities around Scottish fish farms

Emamectin benzoate is used as an in-feed treatment for the control of sea lice parasites in all of the main farmed Atlantic salmon (Salmo salar) facilities worldwide (Norway, Chile, Scotland and Canada). Investigations into its effect on non-target benthic fauna resulting from its excretion from farmed fish and uneaten feed have been limited. This paper presents the findings from a study that intended to assess the impact of emamectin benzoate on benthic fauna using a new low detection method for emamectin benzoate. Eight fish farms in the Shetland Isles, Scotland were surveyed, with sediment sampled along transects radiating from the farms analysed for benthic ecology, sediment chemistry and sediment veterinary medicine residues (analysed for emamectin benzoate and teflubenzuron). Canonical Correspondence Analysis (CCA) and Generalised Linear Mixed Modelling (GLMM) were used to assess which environmental parameters observed during the survey had the biggest effect on benthic community composition and abundance, and more specifically crustacean abundance and richness. Emamectin benzoate was found in 97% of samples, demonstrating widespread dispersion in the sediments sampled. The CCA showed that species composition was predominantly ordinated along a gradient of particle size, with a secondary axis dominated by a change in emamectin benzoate and organic carbon enrichment. Peaks in abundance of crustacean species were predicted to be organised along a gradient of emamectin benzoate concentration. The GLMM corroborated this by showing that emamectin benzoate had the strongest negative effect on total crustacean abundance and species richness, though there was some degree of collinearity with organic carbon, that had a smaller effect. Overall, this study shows that, following its use as an in-feed treatment for sea lice, emamectin benzoate residues are more widely distributed in the benthic environment than previously thought, and have a statistically significant effect on benthic ecology at the concentrations observed in this study.

Using biological-physical modelling for informing sea lice dispersal in Loch Linnhe, Scotland

Sea lice are a constraint on the sustainable growth of Scottish marine salmonid aquaculture. As part of an integrated pest management approach, farms coordinate procedures within spatial units. We present observations of copepodids being at relatively greater density than nauplii in upper waters, which informs the development of surface layer sea lice transmission modelling of Loch Linnhe, Scotland, for informing farm parasite management. A hydrodynamic model is coupled with a biological particle-tracking model, with characteristics of plankton sea lice. Simulations are undertaken for May and October 2011-2013, forced by local wind data collected for those periods. Particles are continually released from positions representing farm locations, weighted by relative farm counts, over a 2-week period and tracked for a further 5 days. A comparison is made between modelled relative concentrations against physical and biological surveys to provide confidence in model outputs. Connectivity between farm locations is determined in order to propose potential coordination areas. Generally, connectivity depends on flow patterns in the loch and decreases with increased farm separation. The connectivity indices are used to estimate the origins of the sea lice population composition at each site, which may influence medicinal regimens to avoid loss of efficacy.