Detection and avoidance of tidal turbines by fishes

我的研究项目集中在沿海地区工业发展对洄游鱼类资源的影响。鱼类与大型（大坝、堤道、桥梁）和小型（涵洞、鱼道）障碍物之间复杂的相互作用在大多数淡水系统中都有发生，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，这种相互作用很难量化。海洋环境中潮汐能基础设施的发展是鱼类洄游面临的一个新的全球性挑战。如果在运行的涡轮机和洄游的鱼类之间存在空间和时间重叠，我们需要确定鱼类是否能够在它们的路径上发现并避开涡轮机。如果它们不能避开涡轮机，那么鱼与涡轮机的相互作用对鱼的健康和生存有什么影响？涡轮类型、水流速度和鱼的行为是精确构建和验证鱼-涡轮碰撞模型所必需的关键组件。在本研究计划中，我们将采用协作逐步过程：1)在高噪声环境中测试新的创新声学标签技术；2)开发一种合适的阵列几何形状，用于在100米的尺度上跟踪标记鱼类，预测三维定位精度为0.2米；3)标记迁徙的底栖和远洋鱼类，量化它们探测和避免在不同流速下操作潮汐涡轮机的能力。研究表明，当鱼接近涡轮机时，在低流速下会改变方向、深度和方向。我们预测，当比较接近涡轮机的鱼的数据和不直接靠近涡轮机的鱼的数据时，行为的变化将是明显的。结果将为鱼轮机在变流速下相互作用的预测模型提供信息。该方案的结果将普遍适用于预测潮汐能开采对全球高能量环境中物种和物种群的影响。正确预测潮汐涡轮机对鱼类资源的负面影响对加拿大经济至关重要。例如，仅在大西洋省份，2012年就收获了616,944吨鱼，价值9.77亿美元，就业人数为61,256人。因此，减少已经受到压力的商业鱼类资源的健康和丰富程度的经济影响可能会对沿海经济和加拿大整体经济产生巨大影响。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，这使我们无法全面了解潮汐能开发的生物后果。此外，由于缺乏关于潮汐能潜在影响的可靠科学数据，这项技术有望减少碳排放，而加拿大可能因此成为沿海地区潮汐能基础设施生产的全球领导者，这将推迟这项技术的决策过程。

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.