Statistical modelling of sea lice count data from salmon farms in the Faroe Islands.
J Fish Dis
; 41(6): 973-993, 2018 Jun.
Article
em En
| MEDLINE
| ID: mdl-29148591
ABSTRACT
Fiskaaling regularly counts the number of sea lice in the attached development stages (chalimus, mobiles and adult) for the salmon farms in the Faroe Islands. A statistical model of the data is developed. In the model, the sea-lice infection is represented by the chalimus (or mobile) lice developing into adult lice and is used to simulate past and current levels of adult lice-including treatments-as well as to predict the adult sea lice level 1-2 months into the future. Time series of the chalimus and adult lice show cross-correlations that shift in time and grow in size with temperature. This implies in situ the temperature-dependent development times of about 56 down to 42 days and the inverted development times (growth rates) of 0.018 up to 0.024 lice/day at 8-10°C. The temperature dependence DT=α1T+α2α3=17,840T+7.439-2.128is approximated byD1T=105.2-6.578T≈49 days at the mean temperature 8.5°C-similar to DchaT=100.6-6.507T≈45 days from EWOS data. The observed development times at four sites for a year (2010-11) were 49, 50, 51 and 52 days, respectively. Finally, we estimate the sea lice production from fish farms to discuss approaches to control the sea lice epidemics-preferably by natural means. This study is useful for understanding sea lice levels and treatments, and for in situ analysis of the sea-lice development times and growth rates.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Salmão
/
Copépodes
/
Ectoparasitoses
/
Doenças dos Peixes
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
País/Região como assunto:
Europa
Idioma:
En
Revista:
J Fish Dis
Assunto da revista:
BIOLOGIA
/
MEDICINA VETERINARIA
Ano de publicação:
2018
Tipo de documento:
Article
País de publicação:
ENGLAND
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ESCOCIA
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GB
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GREAT BRITAIN
/
INGLATERRA
/
REINO UNIDO
/
SCOTLAND
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UK
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UNITED KINGDOM