Counting sea lice on Atlantic salmon farms : empirical and theoretical observations
Heuch, Peter A. and Gettinby, George and Revie, Crawford (2011) Counting sea lice on Atlantic salmon farms : empirical and theoretical observations. Aquaculture, 320 (3-4). pp. 149-153. (https://doi.org/10.1016/j.aquaculture.2011.05.002)
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This communication briefly reviews some of the factors which have shaped the current protocols for lice counting on salmon farms and points out that the motivation for counting is not always the same. It is also apparent that a number of widely accepted assumptions, such as those relating to presumed lice population distributions or the ability to pre-select highly infested cages, cannot be uncritically accepted. Recent research from Scotland, Norway and Canada has demonstrated that the fish on farm sites are clustered in cages which have significant differences in lice abundance. Moreover, the prevalence and distribution of lice in farmed and wild fish populations have distinct patterns. At low prevalence the distributions can be described by the negative binomial distribution, whereas at high prevalence lice tend to be normally distributed. The monitoring strategy of sampling the most infested cage on a farm for early detection of a breach of treatment trigger levels for lice is flawed. These findings need to be taken into account when sampling protocols for lice are designed. In particular, precision in estimating prevalence and abundance of lice on the site requires random sampling from many cages. There is no evidence of systematic bias rising from the use of farm staff counting sea lice compared with dedicated counting teams.
ORCID iDs
Heuch, Peter A., Gettinby, George and Revie, Crawford ORCID: https://orcid.org/0000-0002-5018-0340;-
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Item type: Article ID code: 34472 Dates: DateEvent1 November 2011Published12 May 2011Published OnlineSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics
Faculty of Science > Computer and Information SciencesDepositing user: Pure Administrator Date deposited: 18 Oct 2011 11:58 Last modified: 11 Nov 2024 09:53 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/34472