The co-location of offshore windfarms and decapod fisheries in the UK: Constraints and opportunities

The offshore wind sector in the UK is expanding rapidly and is set to occupy significant areas of the coastal zone, making it necessary to explore the potential for co-location with other economic activities. The presence of turbine foundations introduces hard substrates into areas previously dominated by soft sediments, implying that artificial reef effects may occur, with potential benefits for fisheries. This review focuses on the possibilities for locating fisheries for two commercially important decapods, the brown crab Cancer pagurus and the European lobster Homarus gammarus, within offshore wind farms. Existing understanding of habitat use by C pagurus and H. gammarus suggests that turbine foundations have the potential to act as artificial reefs, although the responses of these species to noise and electromagnetic fields are poorly understood. Offshore wind farm monitoring programmes provide very limited information, but do suggest that adult C pagurus associate with turbine foundations, which may also serve as nursery areas. There was insufficient deployment and monitoring of rock armouring to draw conclusions about the association of H. gammarus with offshore wind farm foundations. The limited information currently available demonstrates the need for further research into the ecological and socioeconomic issues surrounding fishery co-location potential.

The co-location of offshore windfarms and decapod fisheries in the UK: Constraints and opportunities

The offshore wind sector in the UK is expanding rapidly and is set to occupy significant areas of the coastal zone, making it necessary to explore the potential for co-location with other economic activities. The presence of turbine foundations introduces hard substrates into areas previously dominated by soft sediments, implying that artificial reef effects may occur, with potential benefits for fisheries. This review focuses on the possibilities for locating fisheries for two commercially important decapods, the brown crab Cancer pagurus and the European lobster Homarus gammarus, within offshore wind farms. Existing understanding of habitat use by C pagurus and H. gammarus suggests that turbine foundations have the potential to act as artificial reefs, although the responses of these species to noise and electromagnetic fields are poorly understood. Offshore wind farm monitoring programmes provide very limited information, but do suggest that adult C pagurus associate with turbine foundations, which may also serve as nursery areas. There was insufficient deployment and monitoring of rock armouring to draw conclusions about the association of H. gammarus with offshore wind farm foundations. The limited information currently available demonstrates the need for further research into the ecological and socioeconomic issues surrounding fishery co-location potential.

Valuation of ecological and amenity impacts of an offshore windfarm as a factor in marine planning

Integrated marine planning, which must take into consideration environmental and social impacts, is being introduced widely in Europe, the USA, Australia and elsewhere. Installation of offshore windfarms creates impacts both on local marine ecosystems and the view of the seascape and is one of multiple activities in the marine area that must be addressed by marine planning. The impacts on people's values (and hence welfare) of changes in ecology and amenity that could arise from the installation of a windfarm in the Irish Sea were assessed using a discrete choice experiment administered through an online survey. The ecological changes investigated were: increased species diversity resulting from artificial reef effects, and the effect of electromagnetic fields from subsea cables on marine life; whilst the amenity change was the visibility of offshore turbines from land. Respondents expressed preferences for ecological improvements but had less clear preferences regarding the height and visibility of the turbines. In particular distance decay effects were observed with respondents further away from the coast being less concerned about visual impact created by offshore turbines. Understanding ecological and amenity impacts and how they are valued by people can support the decisions made within marine planning and licensing.

Recovery of a biodiversity action plans species in northwest England: possible role of climate change, artificial habitat and water quality amelioration. Occasional Publication of the Marine Biological Association 16

The honeycomb reef worm Sabellaria alveolata is recognised as being an important component of intertidal communities. It is a priority habitat within the UK Biodiversity Action Plan and as a biogenic reef forming species is covered by Annex 1 of the EC habitats directive. S. alveolata has a lusitanean (southern) distribution, being largely restricted to the south and west coasts of England. A broad-scale survey of S. alveolata distribution along the north-west coasts was undertaken in 2003/2004. These records were then compared with previous distribution records, mainly those collected by Cunningham in 1984. More detailed mapping was carried out at Hilbre Island at the mouth of the River Dee, due to recent reports that S. alveolata had become re-established there after a long absence.

Automatic classification of field-collected dinoflagellates by artificial neural network

Automatic taxonomic categorisation of 23 species of dinoflagellates was demonstrated using field-collected specimens. These dinoflagellates have been responsible for the majority of toxic and noxious phytoplankton blooms which have occurred in the coastal waters of the European Union in recent years and make severe impact on the aquaculture industry. The performance by human 'expert' ecologists/taxonomists in identifying these species was compared to that achieved by 2 artificial neural network classifiers (multilayer perceptron and radial basis function networks) and 2 other statistical techniques, k-Nearest Neighbour and Quadratic Discriminant Analysis. The neural network classifiers outperform the classical statistical techniques. Over extended trials, the human experts averaged 85% while the radial basis network achieved a best performance of 83%, the multilayer perceptron 66%, k-Nearest Neighbour 60%, and the Quadratic Discriminant Analysis 56%.