Using multibeam sonar to monitor animal behaviour and environmental interactions at marine renewable energy sites

Lead Research Organisation: University of the Highlands and Islands
Department Name: The North Highland College UHI

Abstract

To date, there are 8.5 GW of installed UK offshore wind capacity, and it is estimated 20% of current UK electricity demand could be met with wave and tidal stream sources. However, with rapid development of marine renewable energy (MRE) including wind, wave and tidal stream energy, uncertainty remains surrounding the environmental and ecological effects. Concerns include disruption of migratory and foraging animal behaviour, direct mortality from animal collision with underwater turbines, attraction of animals as a result of prey aggregation around structures, or displacement from preferred habitats.

Changes in behaviour of fish species, in particular those which are common prey of seabirds and marine mammals, could lead to changes in foraging behaviour of their predators as observed at offshore wind turbines. A recent study found 1.75 times higher fish school (prey) passage rates at tidal turbine structures, and 5.66 times higher in low speed wakes [1]. However, key questions remain about whether these increases in prey abundance are reflected in changes in predator numbers or behaviour; understanding potential predator responses also has important consequences for collision risk with either above water (wind) or below water (tidal) turbine blades. Regulators need information on animal distribution, underwater behaviour and interactions with marine energy developments to inform licensing and management.

Multibeam sonar mounted on seabed platforms has been demonstrated as a suitable method to investigate these knowledge gaps [2-4], providing continuous, fine-scale information on the behaviour, distribution and interactions of fish, diving seabirds and marine mammals, including predator-prey behaviour.

This inter-disciplinary PhD will develop algorithms for multibeam sonar data processing for target detection, tracking and classification in high energy sites. The project will build on several existing datasets allowing investigation of the transferability of techniques and results between sites / devices / instruments. Analysis of the results will address key ecological and regulator questions on predator-prey interactions, animal behaviour, and biophysical coupling at MRE sites.

The project will also develop recommendations for future data collection to ensure measurements can effectively meet monitoring requirements in collaboration with the project partner Marine Scotland Science. A robust and transferable suite of processing tools will address industry uncertainty and answer the crucial ecological questions on the environmental effects of MRE development. The student will be able to engage in future data collection opportunities to apply the techniques and recommendations.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007342/1 01/10/2019 30/09/2027
2452463 Studentship NE/S007342/1 01/10/2020 31/03/2024 Nicholas Petzinna