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

使用多波束声纳监测海洋可再生能源站点的动物行为和环境相互作用

• 批准号: 2452463
• 金额: --
• 依托单位: University of the Highlands and Islands
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2452463
• 关键词: Using; multibeam; sonar; monitor; animal

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.

到目前为止，英国海上风电装机容量为8.5千兆瓦，估计目前英国20%的电力需求可以通过波浪和潮流来源来满足。然而，随着海洋可再生能源(包括风能、波浪能和潮汐能)的快速发展，围绕其环境和生态影响的不确定性依然存在。令人担忧的问题包括动物迁徙和觅食行为中断、动物与水下涡轮机相撞导致的直接死亡、猎物聚集在建筑物周围引起的动物吸引力、或从优先栖息地转移。鱼类物种行为的变化，特别是海鸟和海洋哺乳动物常见的猎物，可能会导致近海风力涡轮机观察到的捕食者觅食行为的变化。最近的一项研究发现，潮汐涡轮机结构的鱼群(猎物)通过率是1.75倍，低速尾流的通过率是5.66倍[1]。然而，关键的问题仍然是，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也对与水面(风)或水下(潮汐)涡轮机叶片相撞的风险产生重要影响。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调查这些知识差距的适当方法[2-4]，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。这一跨学科的博士学位将开发多波束声纳数据处理算法，用于高能场所的目标检测、跟踪和分类。该项目将建立在几个现有数据集的基础上，从而能够调查技术和成果在地点/设备/仪器之间的可转移性。对结果的分析将解决关于捕食者-猎物相互作用、动物行为和MRE地点生物物理耦合的关键生态学和调节器问题。该项目还将与项目伙伴苏格兰海洋科学合作，为今后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。一套强大和可转移的加工工具将解决行业的不确定性，并回答关于MRE开发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。