Abstract
The most important concern for permitting tidal and river turbines is the collision risk of marine animals with the turbine blades. Our understanding of the risk to individual fish from colliding with turbine blades is poor; if these collisions were to occur, it is unknown whether fish will sustain recoverable injuries or be killed. Equally unknown is the impact these collisions might have on populations, particularly for threatened, endangered, or commercially managed fish species. In addition to observations of interactions of fish with turbines, numerical models need to be developed or expanded to predict impacts on fish populations. These models could replace expensive and technically challenging monitoring programs in high energy, often murky, tidal or river waters.
In this project, a multi-pronged approach was taken to (1) assess the state of knowledge and key uncertainties in studies of collision risk, (2) lay out the steps needed to estimate collision risk effects on fish populations, and (3) identify knowledge gaps and the research needed to fill them. This approach included a workshop with experts, a literature review of modeling and empirical studies, the development of a research framework, and the identification of case studies to address through future work.
First, parameters needed for models for collision risk of fish and data available from empirical studies were compared. This comparison highlighted the discrepancy between parameters needed in models and available data. Empirical data are lacking for collision risk assessment, mainly due to the difficulty in monitoring encounter and collision events. Therefore, collision risk models include a large range of parameters that are mainly based on broad assumptions. Significant parameters to consider in collision risk assessment and consequences on populations were identified in this project such as fish length, detection distance of the turbine, or time the fish spends in risk area or depth.
Next, a research framework was developed using the status of key species to assess the consequences of collision on individual fish and potential impacts on listed and managed populations. The research framework highlights the priorities needed to assess fish collision risk for a tidal or river energy project development. Based on the regulatory status of fish species of interest, the framework identifies the preferred scale and type of study, including the variability among fish species of regulatory interest which can be adapted to migratory and sessile fish, pelagic or demersal fish, fish with different life histories or seasonality, and fish in temperate or tropical regions. From this framework, species were selected to pursue the further development of case studies for collision risk assessment.
Targeted research studies should be developed to fill the data gaps between parameters needed for models and data available from empirical studies. For protected species, the development and use of technologies to determine fish presence and assess their behavior in the nearfield is recommended. Long-term monitoring around deployed turbines will be needed to determine potential interactions between fish and turbines and better understand the likelihood of collisions. These data will inform encounter rate and collision risk models for fish individuals. For managed fish species, it is recommended to work with fisheries agencies that can provide stock assessments and use specific repeated protocols to collect their data. These data can then be used in a model to evaluate the potential effects of collision risk on the population.
Based on existing studies of collision risk and identified knowledge gaps, next steps to resolve the risk of turbine collision on fish were proposed. For example, comparing model results between sites and species to highlight patterns among study designs and species, and initiate a data transferability approach; or applying population-level effects to localized populations that overlap with marine energy development areas.
This project is a first step towards the future development of effective and robust numerical models for assessing the collision risk of fish around turbines. This overall effort will achieve a balanced and accurate estimate of the severity of collision risk to fish at the population scale.