Connectivity modelling and network analysis of sea lice infection in Loch Fyne, west coast of Scotland

Abstract

Sea lice are a persistent threat in many areas where salmon farming is practised. In common with the management of disease, infection levels are typically controlled by operating sites within distinct geographical areas, allowing for coordinated treatment and fallow cycles. However, the hydrodynamic connectivity and consequent transmission of lice larvae between sites is often not well understood, which limits our ability to optimise the spatial distribution of farms to minimise infection. We used a multistage modelling approach to investigate the transmission of sea lice larvae between salmon aquaculture sites in Loch Fyne, Scotland. A finite element hydrodynamic model was forced using meteorological data collected over the study period. Output from this model was used to drive a particle-tracking model. The latter model implemented the development and mortality of larvae to estimate the probability of successful larval dispersal between sites. In turn, these dispersal probabilities were used to define a network describing the sea lice metapopulation (its habitat defined by the aquaculture sites). Methods from graph theory allow the identification of those sites in the network that are likely to be key for the control of sea lice in the loch population as a whole. Model outputs were compared with data from a campaign of plankton tows and with lice abundance data from aquaculture sites. The general pattern of abundance was reasonably well replicated, albeit with some notable discrepancies. These differences are worth investigating further, as they may be suggestive of sources of infection by wild fish or of inadequacies in the model.