Copping, A.E.; Hasselman, D.J.; Bangley, C.W.; Culina, J.; Carcas, M. A Probabilistic Methodology for Determining Collision Risk of Marine Animals with Tidal Energy Turbines. J. Mar. Sci. Eng.2023, 11, 2151.
Copping, A.E.; Hasselman, D.J.; Bangley, C.W.; Culina, J.; Carcas, M. A Probabilistic Methodology for Determining Collision Risk of Marine Animals with Tidal Energy Turbines. J. Mar. Sci. Eng. 2023, 11, 2151.
Copping, A.E.; Hasselman, D.J.; Bangley, C.W.; Culina, J.; Carcas, M. A Probabilistic Methodology for Determining Collision Risk of Marine Animals with Tidal Energy Turbines. J. Mar. Sci. Eng.2023, 11, 2151.
Copping, A.E.; Hasselman, D.J.; Bangley, C.W.; Culina, J.; Carcas, M. A Probabilistic Methodology for Determining Collision Risk of Marine Animals with Tidal Energy Turbines. J. Mar. Sci. Eng. 2023, 11, 2151.
Abstract
Commercial development of tidal stream energy is hampered by technical and financial challenges, and impeded by uncertainty about potential environmental effects that drive environmental risk assessments and permitting (consenting) processes. The effect of greatest concern for operational tidal stream energy devices is the potential for marine animals to collide with turbine blades, resulting in injury or death. Due to the turbulent and often turbid waters that frequently characterize tidal turbine sites, there is an absence of empirical evidence about collisions with marine animals. This paucity of observations often leads to risk-averse permitting decisions that further restrict the deployment of tidal energy devices that are needed to collect this evidence. This paper relies on the framework of stressors and receptors that is used widely in marine energy studies and outlines a stepwise probabilistic methodology that applies existing knowledge to further elucidate the risk to marine animals from operational tidal turbines. A case study using striped bass from the Bay of Fundy, Canada, accompanies the methodology, to partially demonstrate its application.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
