MEPS 679:133-147 (2021)  -  DOI: https://doi.org/10.3354/meps13875

ABSTRACT: Transmission of pathogens increases with population density associated with larger populations within farms and higher number of farms within an area. These pathogens can also spill over (or back) into wild populations. Owing to transmission between and from farms, many diseases are best managed at an area level. Current area management practice in Scotland was developed 20 yr ago, but as aquaculture evolves, farm size and environmental exposure will change. To assess if potential aquaculture management changes require spatial disease management changes, 3 scenarios for particle spread to help inform on pathogen transmission are evaluated: (1) current farm distribution, (2) medium-term development (farms in exposed coastal areas), and (3) long-term development (offshore farms). Climatological output from a hydrodynamic model is used to drive movements of passive particles representing infectious pathogens released from these farms. The potential distribution of particles allows assessment on possible transmission of infection, around farm locations, subject to various modelling assumptions and limitations. Dispersal distances increased with time in all scenarios. For medium-term development, the average dispersal distance (3.0 ± 1.3 km) was marginally larger than dispersal from existing sites (2.7 ± 1.6 km) after 12 h, whereas for the longer-term development, this was 4.8 ± 2.9 km. These results indicate that short- to medium-term aquaculture expansion is consistent with existing disease management areas, at least from these models. However, offshore aquaculture may result in transmission distances for pathogens that exceed existing limits, and therefore will likely require re-assessment of management areas, subject to consideration of all relevant epidemiological factors.

KEY WORDS: Marine pathogens · Disease mitigation · Bio-physical modelling · Spatial management · Disease management area · Atlantic salmon · Coupled hydrodynamic-particle-tracking models