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

到目前为止，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流源来满足。然而，随着风能、波浪能和潮流能等海洋可再生能源的快速发展，其环境和生态效应仍存在不确定性。令人关切的问题包括动物迁徙和觅食行为的中断，动物与水下涡轮机碰撞造成的直接死亡，由于猎物聚集在结构周围而吸引动物，或从首选栖息地迁移。鱼类，特别是海鸟和海洋哺乳动物常见的猎物，其行为的变化可能导致其捕食者觅食行为的变化，如在近海风力涡轮机处观察到的那样。最近的一项研究发现，潮汐涡轮机结构处的鱼群（猎物）通过率高出1.75倍，低速尾流处高出5.66倍[1]。然而，关键的问题仍然是这些猎物丰富度的增加是否反映在捕食者数量或行为的变化，了解潜在的捕食者的反应也有重要的后果，无论是在水上（风）或水下（潮汐）涡轮机叶片的碰撞风险。监管机构需要关于动物分布、水下行为以及与海洋能源开发的相互作用的信息，以便为许可证发放和管理提供信息。安装在海底平台上的多波束声纳已被证明是调查这些知识空白的适当方法[2-4]，可提供关于鱼类、潜水海鸟和海洋哺乳动物的行为、分布和相互作用的连续、精细信息，包括捕食者-猎物行为。这个跨学科的博士学位将开发多波束声纳数据处理算法，用于高能量站点的目标检测，跟踪和分类。该项目将建立在几个现有数据集的基础上，允许研究技术和结果在研究中心/器械/仪器之间的可转移性。分析结果将解决关键的生态和监管问题的捕食者-猎物的相互作用，动物行为和生物物理耦合在MRE网站。该项目还将为未来的数据收集提出建议，以确保测量能够有效地满足与项目合作伙伴苏格兰海洋科学公司合作的监测要求。一套强大和可转移的处理工具将解决行业的不确定性，并回答关于地雷危险教育发展的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，以应用技术和建议。

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.