Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management

Context: Sea lice are the most significant parasitic problem affecting wild and farmed salmon. Larval lice released from infected fish in salmon farms and their transport by water masses results in inter-farm networks of lice dispersal. Understanding this parasite connectivity is key to its control and effective management. Objectives: Quantify the spatial and seasonal patterns in sea lice (Lepeophtheirus salmonis) dispersal in an area with intensive salmon farming. Identify emergent clusters in the network, where associated salmon farms could be used for coordinated management and spatial planning of the industry. Methods: We used a biophysical model to simulate lice dispersal from 537 salmon farms along the Norwegian coastline for two seasons (spring and winter) from 2009 to 2014. We used network analysis to characterize dispersal pathways and quantify the spatial and temporal patterns in connectivity. Results: Lice dispersal patterns and network metrics varied greatly between seasons, but differences were consistent amongst years. Winter networks presented more connections, and links were on average two times longer (average winter median = 36.5 ± 7.6 km, mean ± SE; average spring median = 17.8 ± 1.7 km). We identified 12 emergent farm clusters, which were similar across seasons and with the production areas for salmon aquaculture proposed by the Norwegian government. Conclusions: Seasonal variations in lice development times, oceanographic processes and the topological arrangement of salmon farms affect lice dispersal patterns. We have identified a biologically meaningful and politically tractable alliance structure for sea lice management consisting of closely-associated clusters of farms.