Picture offshore wind farm

Open Access research that is improving renewable energy technology...

Strathprints makes available scholarly Open Access content by researchers across the departments of Mechanical & Aerospace Engineering (MAE), Electronic & Electrical Engineering (EEE), and Naval Architecture, Ocean & Marine Engineering (NAOME), all of which are leading research into aspects of wind energy, the control of wind turbines and wind farms.

Researchers at EEE are examining the dynamic analysis of turbines, their modelling and simulation, control system design and their optimisation, along with resource assessment and condition monitoring issues. The Energy Systems Research Unit (ESRU) within MAE is producing research to achieve significant levels of energy efficiency using new and renewable energy systems. Meanwhile, researchers at NAOME are supporting the development of offshore wind, wave and tidal-current energy to assist in the provision of diverse energy sources and economic growth in the renewable energy sector.

Explore Open Access research by EEE, MAE and NAOME on renewable energy technologies. Or explore all of Strathclyde's Open Access research...

Identifying epidemiological factors affecting sea lice (Lepeophtheirus salmonis)abundance on Scottish salmon farms using general linear models

Revie, C.W. and Gettinby, G. and Treasurer, J.W. and Wallace, C. (2003) Identifying epidemiological factors affecting sea lice (Lepeophtheirus salmonis)abundance on Scottish salmon farms using general linear models. Diseases of Aquatic Organisms, 57 (1-2). pp. 85-95. ISSN 0177-5103

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

The variation in Lepeophtheirus salmonis sea lice numbers across 40 Scottish salmon farm sites during 1996 to 2000 was analysed using mean mobile abundance for 3 important 6 mo periods within the production cycle. Using statistical regression techniques, over 20 management and environmental variables suspected to have an effect on controlling lice populations were investigated as potential risk factors. The findings and models developed provide a picture of mobile L. salmonis infestation patterns on Scottish farm sites collectively. The results identified level of treatment, type of treatment, cage volume, current speed, loch flushing time and sea lice levels in the preceding 6 mo period to be key explanatory factors. Factors such as stocking density, site biomass, water temperature and the presence of neighbours, previously cited to be important correlates of sea lice risk from analysis of individual sites over time, were not found to be important. Variation in mobile abundance in the first half of the second year of production could be adequately explained (adjusted R2 between 55 and 72%) by the recorded data, suggesting that there is scope for management to control L. salmonis abundance, though much of the variation remains unexplained.