Towards enabling sustainable expansion of offshore wind while protecting marine benthic biodiversity and functioning (B-EcoWIND)

实现海上风电的可持续扩张，同时保护海洋底栖生物多样性和功能（B-EcoWIND）

• 批准号: NE/X008991/1
• 负责人: Martin Solan
• 金额: $ 114.12万
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FX008991%2F1
• 关键词: Towards; enabling; sustainable; expansion; offshore

Meeting energy demands in the most sustainable way is a major challenge for society. Offshore wind farms - groupings of wind turbines on submerged sediments - offers part of the solution for the energy transition that is needed to mitigate climate change, and the UK has committed to a dramatic and rapid expansion of wind farms in the seas around the UK. However, shelf sea sediments host diverse and productive communities that play a very important role in processing nutrients and carbon that underpin the entire food web. Many species are also important prey items for higher trophic levels, including sea mammals and birds. At the same time, many sediment-dwelling species, such as clams, worms, shrimp and some fish are so intimately associated with the sediment environment that they are particularly susceptible to disturbance. This raises concern as the expansion of offshore wind currently underway means that marine ecosystems are highly likely to experience a large proportional change in biodiversity and ecosystem functioning if marine policy and the management of increasing pressures on UK marine ecosystems is not correctly guided.In this project, we have assembled marine ecologists, engineers and computational scientists to work together to understand ecosystem responses to the cumulative pressures of a large increase in deployment of offshore wind, considered in combination with other pressures that marine ecosystems are facing caused by human activity (bottom fishing, shipping) and the effects of climate change (acidification, warming, low oxygen). To do this, we will collate available data on many aspects of the marine environment and fill in gaps in these data by collecting targeted information about how species interact and behave around offshore wind structures using autonomous vehicles and use artificial intelligence algorithms to identify any associations and patterns. This analysis will also tell us which species are vulnerable to change and highlight areas of concern. Next, we will carry out a series of experiments that will test whether representative species are susceptible to certain types of noise and vibration, electromagnetism and localised heating which are common sources of disturbance associated with wind farms. We will also bring back intact assemblages from areas experiencing different levels of fishing intensity and expose them to the same pressures to see whether species that are experiencing one set of pressures will respond in the same way as those that are not experiencing other pressures. This will tell us how species respond under current conditions, but the pace of climate change means that an additional set of pressures will also effects these species. Hence, we will carry out the same experiments under simulated future conditions (warmer and with altered seawater chemistry). The results of these experiments will tell us whether species benefit or are compromised by certain combinations of pressures, and our expectation is that some species and communities will fair better than others. We will use this information to develop models that allow us to predict how other species that we have not considered, but which share similar traits, may respond. To do this we will use sophisticated statistical models that take into account wider information and make predictions about what marine systems in the future might look like in the future under different scenarios of habitat use, human activity and climate change. In a final step, we will develop a decision support tool that will allow the complexities, including positive and negative feedbacks, to be taken into account by decision and policy makers so they can see the likely consequences of consenting offshore wind in specific locations. Our tool will support the sustainable growth of the offshore wind industry by helping decision makers to make informed decisions that minimise pressure on our marine ecosystems.

以最可持续的方式满足能源需求是社会面临的一项重大挑战。海上风电场-水下沉积物上的风力涡轮机组-为缓解气候变化所需的能源转型提供了部分解决方案，英国已承诺在英国周围海域迅速扩大风电场。然而，陆架海沉积物中存在着多种多样的多产群落，它们在处理支撑整个食物网的营养物质和碳方面发挥着非常重要的作用。许多物种也是较高营养级的重要猎物，包括海洋哺乳动物和鸟类。与此同时，许多沉积物栖息物种，如蛤、蠕虫、虾和一些鱼类，与沉积物环境密切相关，特别容易受到干扰。这引起了人们的关注，因为目前正在进行的海上风电的扩张意味着，如果海洋政策和对英国海洋生态系统日益增加的压力的管理没有得到正确的指导，海洋生态系统很可能会经历生物多样性和生态系统功能的大比例变化。工程师和计算科学家共同努力，了解生态系统对海上风电部署大幅增加的累积压力的反应，考虑到人类活动（底鱼捕捞、航运）和气候变化的影响（酸化、变暖、低氧）给海洋生态系统带来的其他压力，为此，我们将整理有关海洋环境许多方面的可用数据，并通过收集有关物种如何使用自动驾驶车辆在海上风力结构周围互动和行为的有针对性的信息来填补这些数据中的空白，并使用人工智能算法来识别任何关联和模式。这项分析还将告诉我们哪些物种容易受到变化的影响，并突出关注的领域。接下来，我们将进行一系列实验，测试代表性物种是否容易受到某些类型的噪音和振动，电磁和局部加热，这些都是与风电场相关的常见干扰源。我们还将从经历不同捕捞强度的地区带回完整的组合，并将它们暴露在相同的压力下，以观察正在经历一组压力的物种是否会以与未经历其他压力的物种相同的方式做出反应。这将告诉我们物种在当前条件下的反应，但气候变化的速度意味着一系列额外的压力也将影响这些物种。因此，我们将在模拟未来的条件下（更温暖和海水化学变化）进行相同的实验。这些实验的结果将告诉我们物种是否受益于某些压力组合，我们的期望是一些物种和社区会比其他物种和社区更好。我们将利用这些信息来开发模型，使我们能够预测我们没有考虑过的其他物种，但具有相似特征，可能会做出反应。为了做到这一点，我们将使用复杂的统计模型，这些模型考虑到更广泛的信息，并预测未来海洋系统在栖息地利用、人类活动和气候变化的不同情景下可能会是什么样子。在最后一步，我们将开发一个决策支持工具，使决策者和政策制定者能够考虑到包括积极和消极反馈在内的复杂性，以便他们能够看到在特定地点同意海上风电的可能后果。我们的工具将通过帮助决策者做出明智的决策，最大限度地减少对海洋生态系统的压力，来支持海上风电行业的可持续发展。