Offshore renewable developments - developing marine mammal dynamic energy budget models: report

A report detailing the Dynamic Energy Budget (DEB) frameworks and their potential for integration into the iPCoD framework for harbour seal, grey seal, bottlenose dolphin, and minke whale (building on an existing DEB model for harbour porpoise to help improve marine mammal assessments for offshore renewable developments.

11 Summary and future requirements

In this report we have provided detailed descriptions of DEB models for harbour seals, grey seals, bottlenose dolphins and minke whales in UK waters. These can be added to the suite of DEB models, all based on the template developed by Hin et al. (2019), that already includes models for harbour porpoise, long-finned pilot whale, Cuvier’s beaked whale, Blainville’s beaked whale, beluga and Pacific walrus. In principle, the same template could be used to develop DEB models for other cetacean species (e.g., Risso’s dolphin, white-sided and white-beaked dolphins) likely to be affected by offshore wind farm construction in UK waters. However, this would be challenging because of the lack of data on key demographic parameters (age-specific growth rates, age-specific survival rates, length-mass relationships, and lactation durations) for these species. In addition, there is little or no information on how these species react to the noise associated with wind farm construction. Although it may be possible to “borrow” values for the relevant parameters from other related species, this would introduce additional uncertainty into model predictions that would be difficult to quantify.

The model descriptions in this report have been structured using the ODD protocol recommended by Grimm et al. (2020) for documenting agent-based models. Descriptions of this kind are widely accepted as Supplementary Information (SI) for journal articles that report results obtained using such models and will simplify the production of such articles because the same SI can be used multiple times. The models have also been calibrated using the POM approach developed by Grimm et al. (2005).

We investigated the effects of disturbance on vital rates for harbour seals, grey seals, bottlenose dolphins and minke whales (Sections 5.3, 6.3, 7.3 and 8.3). Grey seals appear to be more vulnerable to the effects of disturbance than the other three species, but these results should be treated with caution because only a relatively small set of plausible model parameter values was used in the simulations for the other three species.

We have demonstrated in Section 9.3 how the DEB models developed for this study and the harbour porpoise DEB model are capable of generating the relationships required to replace the transfer functions in iPCoD. These transfer functions, which established the relationship between days of disturbance experienced and their effect on vital rates, were derived using formal EE approaches. Although the way in which these transfer functions were derived is more precisely documented than those developed using EE, it should be recognised that the DEB-derived functions rely on two key sets of assumptions. First, they are based on a set of equations and parameter values sourced from across the marine mammal and energetics literature that may not be appropriate for the species to which they are applied. Second, they assume that the only effect of disturbance from human noise on vital rates is the result of a reduction in energy intake and that this reduction is directly related to the duration of any behavioural changes caused by disturbance. The predictions of a DEB model are highly dependent on how many hours of lost foraging are specified to occur as a result of disturbance. The validity of this assumption will need to be evaluated carefully if DEB-derived functions are used to replace the EE-derived transfer functions in iPCoD.

Loss of foraging opportunities is only one of the three potential effects of behavioural change on vital rates documented by Southall et al. 2021. The others are increased predation risk and impaired reproductive behaviour. It is likely that the experts involved in the iPCoD EEs took account of all three potential effects when they predicted the effects of different amounts of disturbance on vital rates. On the other hand, the experts were asked to evaluate the effects of disturbance at any time of year on vital rates. However, the DEB models have clearly indicated that a reduction in energy intake is only likely to affect the vital rates of certain life history stages (particularly pregnant and lactating females, and recently weaned calves or pups) at certain times of year. These findings can be used to identify opportunities for risk mitigation through the timing of operations in a way that is not possible using the EE-derived transfer functions.

We have also described how the uncertainty associated with the many model parameter values can be accounted for and developed a novel and efficient method using ABC to quantify the uncertainty associated with parameters that are not directly observable. By sampling from the resulting posterior probability distributions, it will be possible to generate the equivalent of the thousands of different “virtual” expert relationships between vital rates and the number of days of disturbance that are currently used to evaluate uncertainty in iPCoD. This method can be readily applied to any of the existing DEB models developed using the Hin et al. (2019) template. However, it should be recognised that the uncertainty that is captured by this approach (which relates to uncertainty in model parameter values) is fundamentally different from the uncertainty associated with the EE-derived transfer functions. The latter related to the variation among experts in the predicted form of the transfer functions and the experts’ evaluations of their confidence in the shape of the functions.

Finally, we carried out preliminary trials using output from the DEPONS model (Nabe‑Nielsen et al., 2018) to show how telemetry data can be used to estimate the cumulative exposure of different individuals in a harbour porpoise population to disturbance from piling activity.

It is clear from the uncertainty and sensitivity analyses that much of the uncertainty about the effects of disturbance on vital rates is related to uncertainty around the choice of a suitable value for the FMR multiplier (sigma_M). Further research to clarify the causes of variation in FMR between and within species would provide a more robust quantification of this uncertainty than we have been able to provide.

The other set of parameters that make a substantial contribution to uncertainty are those relating to the development of foraging efficiency. Information regarding the way in which the foraging efficiency of pups and calves develops in the post-weaning period, either from direct observation or telemetry, would be particularly valuable.

Finally, understanding the effects of disturbance on foraging remains key to such models.

The final set of parameters that contribute substantially to uncertainty are those relating to the threshold body condition for starvation (ρs) and the risk of starvation-related mortality (μs). Further research on the relationship between body condition and the risk of mortality is required to resolve this.

Finally, in the time available, we were unable to consider the effects on the predictions of the DEB models of environmental stochasticity and individual variation in the parameters that determine growth, feeding efficiency and the threshold for reproduction. Incorporation of this variation would undoubtedly make the model predictions more realistic. Further research is required to determine the magnitude and importance of their effects.



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