Using biological–physical modelling for informing sea lice dispersal in Loch Linnhe, Scotland. Issue 6 (7th August 2017)

• Record Type: Journal Article
• Authors: Salama, N K G; Dale, A C; Ivanov, V V; Cook, P F; Pert, C C; Collins, C M; Rabe, B
• Is Part Of: Journal of fish diseases. Volume 41:Issue 6(2018)
• Page Start: 901
• Page End: 919
• Publication Date: 2017-08-07
• Subjects: biological–physical model -- disease management -- dispersal modelling -- salmon aquaculture -- sea lice; Fishes -- Diseases -- Periodicals; 639.3
• DOI: 10.1111/jfd.12693
• Languages: English
• ISSNs: 0140-7775

Abstract

Abstract: Sea lice are a constraint on the sustainable growth of Scottish marine salmonid aquaculture. As part of an integrated pest management approach, farms coordinate procedures within spatial units. We present observations of copepodids being at relatively greater density than nauplii in upper waters, which informs the development of surface layer sea lice transmission modelling of Loch Linnhe, Scotland, for informing farm parasite management. A hydrodynamic model is coupled with a biological particle‐tracking model, with characteristics of plankton sea lice. Simulations are undertaken for May and October 2011–2013, forced by local wind data collected for those periods. Particles are continually released from positions representing farm locations, weighted by relative farm counts, over a 2‐week period and tracked for a further 5 days. A comparison is made between modelled relative concentrations against physical and biological surveys to provide confidence in model outputs. Connectivity between farm locations is determined in order to propose potential coordination areas. Generally, connectivity depends on flow patterns in the loch and decreases with increased farm separation. The connectivity indices are used to estimate the origins of the sea lice population composition at each site, which may influence medicinal regimens to avoid loss of efficacy.