Detection and avoidance of tidal turbines by fishes

鱼类对潮汐涡轮机的检测和避免

• 批准号: RGPIN-2017-04301
• 负责人: Stokesbury, Michael
• 金额: $ 1.75万
• 依托单位: Acadia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=745902
• 关键词: Detection; avoidance; tidal; turbines; fishes

My research program focuses on the impact of industrial developments in the coastal zone on migratory fish resources. Complex interactions between fishes and large (large dams, causeways, bridges) and small (culverts, fishways) scale obstructions occur in most freshwater systems, but are difficult to quantify due to a lack of equipment that can provide accurate and precise 3-d data on fish behaviour. A new global challenge for fish migration is the development of tidal energy infrastructure in the marine environment. If there is spatial and temporal overlap between operating turbines and migratory fishes, we need to determine if fishes are able to detect and avoid turbines in their path. If they cannot avoid the turbines what is the impact of fish-turbine interaction on fish health and survival? The type of turbine, current speed and fish behaviour are critical components necessary to accurately construct and validate fish-turbine collision models. In this research program, we will use a collaborative stepwise process to: 1) test new innovative acoustic tagging technology in high noise environments; 2) develop an appropriate array geometry for tracking tagged fishes on a scale of 100s of m with a predicted 3-d positional accuracy of 0.2 m; and 3) tag migratory benthic and pelagic fishes to quantify their ability to detect and avoid operating tidal turbines at varying current speeds. Fish have been shown at low current speeds to change orientation, depth and direction when approaching a turbine. We predict that changes in behaviour will be obvious when data from fish approaching a turbine and data from fish not in the direct vicinity of a turbine are compared. Results will inform predictive models of fish-turbine interactions at variable current speeds. The results of this program will be generally applicable to prediction of effects of tidal energy extraction on species and species groups in high energy environments globally. The proper prediction of negative effects of tidal turbine operation on fish resources is critical to the Canadian economy. For example, in the Atlantic Provinces alone in 2012, 616,944 mt of fish were harvested, with a value of $977 million and employment of 61,256 people. So, the economic effect of reducing the health and abundance of already stressed commercial fish resources is likely to have a large effect on coastal economies, and Canada's economy as a whole. Our inability to effectively predict the negative effects of operation of tidal turbines on migratory fish health keeps us from understanding the full range of biological consequences of tidal power developments. Moreover, the lack of credible scientific data on the potential impacts of tidal power will delay the decision-making process on a technology that shows promise for reducing carbon emissions, and for which Canada could become a global leader in the production of tidal power infrastructure for the coastal zone.

我的研究项目主要集中在沿海地区的工业发展对洄游鱼类资源的影响。在大多数淡水系统中，鱼类与大型（大坝、堤道、桥梁）和小型（涵洞、鱼道）障碍物之间存在复杂的相互作用，但由于缺乏能够提供准确和精确的鱼类行为三维数据的设备，因此难以量化。鱼类洄游面临的一个新的全球性挑战是在海洋环境中发展潮汐能基础设施。如果在运行的涡轮机和洄游鱼类之间存在空间和时间上的重叠，我们需要确定鱼类是否能够探测并避开它们路径上的涡轮机。如果它们不能避开涡轮机，那么鱼类与涡轮机的相互作用对鱼类健康和生存的影响是什么？涡轮机的类型、当前速度和鱼的行为是精确构建和验证鱼-涡轮机碰撞模型所必需的关键组成部分。在这项研究计划中，我们将使用一个合作的逐步过程：1）在高噪声环境中测试新的创新声学标记技术：2）开发一个适当的阵列几何跟踪标记的鱼类在100米的规模与预测的三维定位精度为0.2米;以及3）标记底栖和中上层洄游鱼类，以量化它们在不同流速下探测和避免操作潮汐涡轮机的能力。在低流速下，鱼在接近涡轮机时会改变方向、深度和方向。我们预测，当鱼接近涡轮机的数据和鱼不在涡轮机附近的数据进行比较时，行为的变化将是明显的。结果将告知鱼涡轮机的相互作用在可变的当前速度的预测模型。该项目的结果将普遍适用于预测全球高能量环境中潮汐能提取对物种和物种群的影响。正确预测潮汐涡轮机运行对鱼类资源的负面影响对加拿大经济至关重要。例如，2012年仅大西洋沿岸各省就捕捞了616 944公吨鱼，价值9.77亿美元，就业人数为61 256人。因此，减少已经紧张的商业鱼类资源的健康和丰富的经济影响可能会对沿海经济和加拿大的整体经济产生重大影响。我们无法有效地预测潮汐涡轮机对洄游鱼类健康的负面影响，使我们无法理解潮汐发电发展的全部生物后果。此外，缺乏关于潮汐发电潜在影响的可靠科学数据将推迟对一项有望减少碳排放的技术的决策过程，加拿大可能成为沿海地区潮汐发电基础设施生产的全球领导者。