Developing models for investigating the environmental transmission of disease-causing agents within open-cage salmon aquaculture

Abstract

Global aquaculture production continues to increase across a variety of sectors, including Atlantic salmon production in Scotland. One limitation to the expansion of open-cage aquaculture is disease-induced stock losses as well as the potential for disease agents from farms interacting with other farms and possibly with wild salmonids. Epidemiological studies of diseaseagent transmission often omit environmental transmission of organisms, although this process is an integral part of parasite spread and incidence. Within the aquatic environment, water movements enable pathogens and parasites to potentially be transmitted over long distances. As pathogens and parasites are transported, their status can change; they can degrade or, in the case of sea lice, develop into an infectious stage. A combination of biological and physical models is required to understand the transmission of disease-causing organisms. Here we propose a set of components that have been implemented in a range of modelling studies of sea lice dispersal, and describe how such attributes have been used in developing a study in one of Scotland's largest fjordic systems. By developing descriptive simulation model frameworks, which are validated using physical and biological observations, alternative methods of integrated pest management can be investigated and developed. The identification of dispersal routes of sea lice and establishment of potential farm−farm connections can inform sea lice management.

Statistical and ecological challenges of monitoring parasitic salmon lice infestations in wild salmonid fish stocks

“…Such variations that cannot be fully predicted are common in many ecological studies and although not all relevant details may ever be available, it would likely have been possible to reduce the noise and improve the models by having a more thorough sampling design and higher number of data points. Further, recent approaches of spatiotemporal models of salinity, temperature and currents in the fjords may improve the availability of relevant environmental data (Asplin et al 2011, Salama & Rabe 2013, Johnsen et al 2014. Although statistical models based on rather coarse-scale proxy data can be used to identify factors influencing the infection pressure on wild salmonids, as we have tried here, this approach may not be that useful for determining whether individual areas have a lice problem owing to finer-scale environmental variation.…”

A method of estimating in situ salmon louse nauplii production at fish farms

“…Highest copepodid densities are commonly observed in near-shore environments, ideal for intercepting migrating hosts (Costello 2006). This is most probably a result of the copepodids drifting with the surface currents influenced by wind (Salama & Rabe 2013, Asplin et al 2014, á Norði et al 2015.…”

Salmon lice (Lepeophtheirus salmonis) development times, body size, and reproductive outputs follow universal models of temperature dependence

“…Environmental conditions are critical in the dispersal and epidemiology of marine pathogens (McCallum et al 2004;Murray 2009;Salama and Rabe 2013). Water temperatures control the metabolic rate of fundamental biochemical processes (Gillooly et al 2001) and thereby regulate growth and development rates of marine organisms.…”