Providing a detailed estimate of mortality using a simulation-based collision risk model

Abstract

Marine renewables could form a significant part of the green energy mix. However, a potential environmental impact of tidal energy converters (TECs) is collision risk between a device and animal, which has been a significant barrier in the consenting process. While it is important to understand the number of collisions of an animal with the device, the relative speed at which an animal collides with the device, and the point on the animal where collision occurs, will determine whether a collision is fatal, which is important in understanding population-level impacts. Using a simulation-based collision risk model, this paper demonstrates a novel method for producing estimates of mortality. Extracting both the speed and the location of collisions between an animal and TEC, in this instance a seal and horizontal axis turbine, collision speed and location of collision are used to produce probabilities of mortality. To provide a hypothetical example we quantified the speed and position at which a collision occurs to estimate mortality and, using collision position, we determine all predicted collisions with the head of the animal as fatal, for example, whilst deeming other collisions non-fatal. This is the first collision risk model to incorporate speed at the point of contact and the location where the collision occurs on the animal, to estimate the probability of mortality resulting from a collision. The hypothetical scenarios outline how these important variables extracted from the model can be used to predict the proportion of fatal events. This model enables a comprehensive approach that ultimately provides advancements in collision risk modelling for use in the consenting process of TECs. Furthermore, these methods can easily be adapted to other renewable energy devices and receptors, such as wind and birds.

Comparability of Outputs between Traditional and Simulation-Based Approaches to Collision Risk Modelling

“…The advantages of the SBA (Table 5), such as altering input parameters (e.g., angle of approach) [21] and estimating mortality [22], allow for more refined collision risk estimates that can better quantify uncertainties relating to key knowledge gaps, such as animal behavior when near the TEC(s). These can be incorporated in a flexible and transparent manner as requested by regulators, which would provide a more comprehensive assessment that can aid the decision-making process.…”

“…These can be incorporated in a flexible and transparent manner as requested by regulators, which would provide a more comprehensive assessment that can aid the decision-making process. For example, Horne et al [22] demonstrated the application of a threshold approach to estimating mortality, whereby mortality was considered to occur above a certain speed of collision. That threshold could be increased (more precautionary) or decreased (less precautionary) as required and presented in a transparent fashion, as the speed of all collisions can be extracted from the SBA model [22].…”

“…For example, Horne et al [22] demonstrated the application of a threshold approach to estimating mortality, whereby mortality was considered to occur above a certain speed of collision. That threshold could be increased (more precautionary) or decreased (less precautionary) as required and presented in a transparent fashion, as the speed of all collisions can be extracted from the SBA model [22]. With simulations taking days to run, the computational requirements of the SBA may be a factor in deciding if its use is required.…”

“…As demonstrated here with the angle of approach, there are limitations to incorporating additional parameters into the Band model and ERM, whereas this is straightforward for the SBA. Consequently, as the SBA allows a range of input parameters and scenarios to be modeled [21], this provides the opportunity to assess ranges within parameters (e.g., swim speeds, animal size and shape, and dive profiles) to calculate collision risk and mortality estimates [22], which is often not possible, or at best, limited, when using the Band model or ERM. Furthermore, understanding to what extent parameters influence collision risk estimates is little understood, and by assessing a range of inputs, SBA model outputs could be gathered and used to better inform empirical data collection.…”

“…The SBA uses similar information to the Band model and ERM; however, outputs are more detailed, such as the different probabilities of collision over the swept area of the TEC [21]. Additionally, the model can also extract information such as the relative speed of each individual collision and the location of that collision on both the animal's body and the device, which is valuable information when estimating the likelihood of mortality [22]. The SBA therefore offers potential advantages in scenarios where more detail in collision risk estimates is needed by allowing the user to address a range of collision risk scenarios and parameters for animals and TECs.…”