A Conditional probabilistic encounter-impact model for fish-turbine interactions

Abstract

Knowledge gaps exist in the collective effort to quantify risks and impacts of fish-turbine interactions. Empirical data and modeling studies have characterized stages of fish approach and pass through hydrokinetic turbines, but there has not been a comprehensive model that quantifies conditional occurrence probabilities of fish approaching and then interacting with a turbine in sequential steps. When calculating conditional probabilities, the probability of each step occurring is, in part, dependent on the occurrence of the previous step in the sequence. We combined acoustic data measurements and when data limited, published probabilities to estimate conditional probabilities of tidal turbine impacts on marine animals. The encounter-impact probability model includes approach, entrainment, and impact phases. The approach phase includes probabilities of entry into a spatial domain and zone of influence, followed by entrainment to the device. Each model component of an encounter includes probabilities of active or passive avoidance. Impacts are defined as fish collisions with a device, blade strikes by a rotating blade, and/or a collision followed by a blade strike. Probabilities are estimated using acoustic data from surveys in Admiralty Inlet, WA USA for Pacific herring (Clupea pallasii) encountering an axial or cross-flow turbine during day or night. Conditional probabilities are additive or multiplicative depending if events are cumulative or sequential. Impact probabilities for collisions and blade strikes are estimated individually and then combined to estimate the probability of overall impacts. Probabilities of occurrence for each model component range from 0.0000242 to 0.40. Impact probabilities for collision followed by a blade strike was lowest with estimates ranging from 0.0000242 to 0.0678. Impact probabilities for blade strike had the highest probabilities ranging from 0.000261 to 0.40. Overall impact probabilities had wide variability from 0.00110 to 0.689. Maximum probabilities occurred in each model component and overall impact probabilities for a cross-flow turbine at night with no active or passive avoidance. Estimates were lowest when probabilities were conditional on sequential events, and when active and passive avoidance was applied for an axial-flow turbine during the day. As expected, conditional probabilities were typically lower than equivalent model component and overall probabilities published in the literature. The encounter-impact conditional probability model can be applied to any marine animal in any environment for any hydrokinetic device. Estimating impact probabilities for Pacific herring in Admiralty Inlet for two device types illustrates utilization of existing data and simultaneously identifies data gaps needed to fully calculate empirical-based probabilities for any specific site-species scenario. As additional monitoring data are collected, accuracy of impact risks due to encounters of marine animals with hydrokinetic devices will increase and be confidently used in establishing regulatory policy.