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

迄今为止，英国海上风电装机容量为8.5吉瓦，据估计，目前英国20%的电力需求可以通过波浪和潮汐能来满足。然而，随着风能、波浪能和潮汐能等海洋可再生能源的快速发展，其对环境和生态的影响仍存在不确定性。人们担心的问题包括破坏动物的迁徙和觅食行为，动物与水下涡轮机碰撞导致的直接死亡，猎物聚集在建筑物周围导致动物被吸引，或从首选栖息地迁移。正如在海上风力涡轮机上观察到的那样，鱼类行为的变化，特别是那些海鸟和海洋哺乳动物的常见猎物，可能导致其捕食者觅食行为的变化。最近的一项研究发现，在潮汐涡轮机结构中，鱼群（猎物）通过的速度要高出1.75倍，而在低速尾流[1]中，鱼群通过的速度要高出5.66倍。然而，关键问题仍然存在，即这些猎物丰度的增加是否反映在捕食者数量或行为的变化上；了解潜在的捕食者反应对于降低与水上（风）或水下（潮汐）涡轮叶片的碰撞风险也具有重要意义。监管机构需要有关动物分布、水下行为以及与海洋能源开发相互作用的信息，以便为许可和管理提供信息。安装在海底平台上的多波束声纳已被证明是研究这些知识缺口的合适方法[2-4]，它提供了关于鱼类、潜水海鸟和海洋哺乳动物的行为、分布和相互作用的连续的、精细的信息，包括捕食者-猎物行为。该跨学科博士将开发多波束声纳数据处理算法，用于高能场所的目标检测、跟踪和分类。该项目将建立在几个现有的数据集上，允许调查技术和结果在地点/设备/仪器之间的可转移性。分析结果将解决主要的生态和调控问题，包括捕食者-猎物相互作用、动物行为和生物物理耦合。该项目还将与项目合作伙伴海洋苏格兰科学公司合作，为未来的数据收集提出建议，以确保测量能够有效地满足监测要求。一套强大的、可转让的加工工具将解决工业不确定性，并回答有关MRE开发对环境影响的关键生态问题。学生将能够参与未来的数据收集机会，应用这些技术和建议。

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.