title: Large scale modelling of salmon lice (Lepeophtheirus salmonis) infection pressure based on lice monitoring data from Norwegian salmonid farms.
abstract: Infection by parasitic sea lice is a substantial problem in industrial scale salmon farming. To control the problem, Norwegian salmonid farms are not permitted to exceed a threshold level of infection on their fish, and farms are required to monitor and report lice levels on a weekly basis to ensure compliance with the regulation. In the present study, we combine the monitoring data with a deterministic model for salmon lice population dynamics to estimate farm production of infectious lice stages. Furthermore, we use an empirical estimate of the relative risk of salmon lice transmission between farms, that depend on inter-farm distances, to estimate the external infection pressure at a farm site, i.e. the infection pressure from infective salmon lice of neighbouring farm origin. Finally, we test whether our estimates of infection pressure from neighbouring farms as well as internal within farm infection pressure, predicts subsequent development of infection in cohorts of farmed salmonids in their initial phase of marine production. We find that estimated external infection pressure is a main predictor of salmon lice population dynamics in newly stocked cohorts of salmonids. Our results emphasize the importance of keeping the production of infectious lice stages at low levels within local networks of salmon farms. Our model can easily be implemented for real time estimation of infection pressure at the national scale, utilizing the masses of data generated through the compulsory lice monitoring in salmon farms. The implementation of such a system should give the salmon industry greater predictability with respect to salmon lice infection levels, and aid the decision making process when the development of new farm sites are planned.
authors.affiliation: Norwegian Veterinary Institute, PO Box 750, Sentrum, N-0106 Oslo, Norway; Department of Informatics, University of Oslo, PO Box 1080, Blindern, N-0316 Oslo, Norway.
authors.forename: Anja B
authors.initials: AB
authors.lastname: Kristoffersen
authors.affiliation: Norwegian Veterinary Institute, PO Box 750, Sentrum, N-0106 Oslo, Norway.
authors.forename: Daniel
authors.initials: D
authors.lastname: Jimenez
authors.affiliation: Norwegian Veterinary Institute, PO Box 750, Sentrum, N-0106 Oslo, Norway; Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biology, University of Oslo, PO Box 1066, Blindern, N-0316 Oslo, Norway.
authors.forename: Hildegunn
authors.initials: H
authors.lastname: Viljugrein
authors.affiliation: Norwegian Veterinary Institute, PO Box 750, Sentrum, N-0106 Oslo, Norway.
authors.forename: Randi
authors.initials: R
authors.lastname: Grøntvedt
authors.affiliation: Norwegian Institute for Nature Research, Fram - High North Research Centre for Climate and the Environment, NO-9295 Tromsø, Norway.
authors.forename: Audun
authors.initials: A
authors.lastname: Stien
authors.affiliation: Norwegian Veterinary Institute, PO Box 750, Sentrum, N-0106 Oslo, Norway. Electronic address: peder.jansen@vetinst.no.
authors.forename: Peder A
authors.initials: PA
authors.lastname: Jansen
mesh_terms: D000818:Animals; D033342:Copepoda / Q000502:physiology*; D005260:Female; D005393:Fish Diseases / Q000469:parasitology* / Q000635:transmission; D005398:Fisheries; D008954:Models, Biological; D009664:Norway; D008003:Phthiraptera / Q000502:physiology*; D012474:Salmon / Q000469:parasitology*
keywords: Aquaculture; Density effects; Infective stages; Parasites; Spatial models