Understanding the Relative Cost-Effectiveness of Sea Lice Management Measures for Farmed Salmon Production in Scotland
Toma, Luiza and Shrestha, Shailesh and Leinonen, Ilkka and Boerlage, Annette and Jansen, Mona Dverdal and Revie, Crawford W. and Reeves, Aaron (2020) Understanding the Relative Cost-Effectiveness of Sea Lice Management Measures for Farmed Salmon Production in Scotland. Norwegian Institute for Natural Research, Edinburgh. (https://www.gov.scot/publications/understanding-re...)
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Abstract
The sea louse Lepeophtheirus salmonis is a key parasite of cultured Atlantic salmon throughout most farmed salmon producing countries, including Scotland. The louse feeds on the salmon, and causes multi million pound commercial losses to the salmon aquaculture industry globally. Its life-cycle includes free-living life stages, and life stages attached to fish. The sea-louse life cycle is heavily affected by water temperatures, making the louse more abundant in summer and autumn months, and thus more sensitive to climate change, which may increase management challenges in the future. Sea lice infestation can lead to reduced salmon welfare and lower productivity at farm level through low feed efficiency or growth reduction. Furthermore, the value of salmon at harvest may be reduced, and environmental costs of salmon production may increase due to inefficient resource use, greenhouse gas emissions and nutrient pollution as a result of lower productivity. Sea lice control involves measurable economic and environmental costs as well as costs that are more difficult to monetise, such as costs related to fish welfare and public perceptions.
ORCID iDs
Toma, Luiza, Shrestha, Shailesh, Leinonen, Ilkka, Boerlage, Annette, Jansen, Mona Dverdal, Revie, Crawford W. ORCID: https://orcid.org/0000-0002-5018-0340 and Reeves, Aaron;-
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Item type: Report ID code: 83740 Dates: DateEvent7 September 2020Published1 September 2020AcceptedSubjects: Agriculture > Aquaculture. Fisheries. Angling
Science > Mathematics > Probabilities. Mathematical statisticsDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 18 Jan 2023 16:39 Last modified: 05 Dec 2024 01:26 URI: https://strathprints.strath.ac.uk/id/eprint/83740