RESEARCH ARTICLE Network analysis reveals strong seasonality in the dispersal of a marine parasite and identifies areas for coordinated management Francisca Samsing . Ingrid Johnsen . Tim Dempster . Frode Oppedal . Eric A. Treml Received: 10 May 2017 / Accepted: 22 July 2017 / Published online: 29 July 2017 Ó Springer Science+Business Media B.V. 2017 Abstract 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 develop- ment times, oceanographic processes and the topo- logical 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-associ- ated clusters of farms. Keywords Connectivity Á Spatial epidemiology Á Cluster analysis Á Sea lice Á Lepeophtheirus salmonis Á Disease management Introduction Large-scale epidemics are affecting ecologically and economically important marine species (Harvell et al. 2004; McCallum et al. 2004). The origins of most of Electronic supplementary material The online version of this article (doi:10.1007/s10980-017-0557-0) contains supple- mentary material, which is available to authorized users. F. Samsing (&) Á T. Dempster Á E. A. Treml School of BioSciences, University of Melbourne, Victoria 3010, Australia e-mail: francisca.samsing@unimelb.edu.au I. Johnsen Á F. Oppedal Institute of Marine Research, Norway, P. O. Box 1870, Nordnes, 5817 Bergen, Norway 123 Landscape Ecol (2017) 32:1953–1967 DOI 10.1007/s10980-017-0557-0