Abstract
Development of marine renewable energy (MRE) has been hindered by the need for information about potential environmental effects. Monitoring of these effects, however, is expensive and it is not always clear how to efficiently collect data for a wide range of possible effects. Monitoring guidelines are needed for developers and regulators to use when planning and consenting MRE projects. Predictive modeling of environmental effects can help determine what needs to be monitored, while also estimating what effects might occur and their magnitude. Modeling for environmental effects of MRE is at different stages of maturity and applicability depending upon the type of impact being considered.
We reviewed models of six categories of stressors: collision risk, underwater noise, electromagnetic fields (EMFs), changes in habitat, displacement of marine species, and changes in oceanographic systems. Receptors were species or groups of species potentially affected by the stressors. Collision risk models are a developing field of modeling specific to MRE and are limited by insufficient data regarding avoidance or evasion and the outcomes of collisions, and by the challenges of monitoring animals very close to operating devices to derive such data. Underwater noise models are well-developed but applications to MRE remain few, with a limited understanding of the behavioral and long-term effects of noise on animals and populations. The physics of EMFs is well-understood, but we did not find any models for MRE or close analogs. As seen with the previously mentioned stressors, the effects of EMFs on physiology and behavior and how they affect populations over time are not well-understood.
Models of habitat changes have been developed for other purposes and can be used for MRE, but the few published studies are primarily theoretical, because of the lack of field testing and validation with MRE projects. Displacement of marine species has not yet been modeled. To model displacement, approaches used for the effects of underwater noise on populations and for changes in habitat could be adapted. This would require measuring the movement of animals relative to the presence of devices (for displacement) and distinguishing it from other drivers of behavior (noise, changes in habitat conditions). Hydrodynamic and wave models for predicting changes in oceanographic systems are well-developed, but their validation with data from active MRE projects is limited. These models frequently provide physical inputs to models of other stressors, so their accuracy is critical for overall estimates of stressor effects.
Most models require site-specific data for environmental parameters and species distribution. Physiological, behavioral or demographic data are best collected from the project site, but may be obtained from other sources when necessary. Monitoring of physical data is relatively straightforward, though consideration must be given to spatial coverage and time frames needed to adequately measure natural variability. Behavioral data for modeled species and linkages between stressors and effects on survival and reproduction present significant information gaps. Validation of MRE models is uncommon and mostly applied to baseline conditions because of the small number of operating MRE devices.
This review provides insight into the options available for modeling MRE-related stressors, the information needed to parameterize models, and development needs. The goal of strengthening the connection between models and monitoring is to work toward guidelines for effective and consistent monitoring, better use of monitoring data, and improved project evaluation. Common information needs among models for different stressors can strategically inform monitoring campaigns and create efficiencies for projects as a whole. Project characteristics should be compared to potential models because there is no universal set of models suitable for all MRE devices and locations. Modeling should be used iteratively with ongoing monitoring to characterize uncertainties and as a basis for consultation between developers and regulators.