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For many aquatic species, vision is important for detecting prey, predators, and conspecifics; however, the potential impacts of visual cues from offshore wind turbines have not been investigated in these crucial contexts. There is the possibility of visual cues, originating from moving wind turbine blades, propagating through the air–water interface to impact visually sensitive species. Two classes of visual cues are possible: direct motion cues originating as light reflected from moving turbine blades and indirect cues resulting from an interruption of direct sunlight causing dynamic shadowing when the sun, blade, and receptor are aligned. In both cases, the propagation of cues across the air–water interface is governed by physical principles but modulated in potentially complex ways by the aspects of the local environment that vary with time. Evidence for the extent of the exposure of aquatic organisms to the visual cues arising from moving turbine blades and for the potential response of receptor organisms is sparse. This study considers the physics involved to support the formulation and testing of robust biological hypotheses. Marine migratory salmonid species are considered as an example species because their behaviour in the marine environment is relatively well documented. This study concludes that the aquatic receptor organisms present in the uppermost layer of the sea in the vicinity of wind turbines are potentially exposed to direct motion cues originating from moving turbine blades and also, when the sun elevation angle is greater than ca. 20°, to dynamic shadowing cues.

Tidal stream environments are important areas of marine habitat for the development of marine renewable energy (MRE) sources and as foraging hotspots for megafaunal species (seabirds and marine mammals). Hydrodynamic features can promote prey availability and foraging efficiency that influences megafaunal foraging success and behaviour, with the potential for animal interactions with MRE devices. Uncrewed aerial vehicles (UAVs) offer a novel tool for the fine-scale data collection of surface turbulence features and animals, which is not possible through other techniques, to provide information on the potential environmental impacts of anthropogenic developments. However, large imagery datasets are time-consuming to manually review and analyse. This study demonstrates an experimental methodology for the automated detection of turbulence features within UAV imagery. A deep learning architecture, specifically a Faster R-CNN model, was used to autonomously detect kolk-boils within UAV imagery of a tidal stream environment. The model was trained on pre-existing, labelled images of kolk-boils that were pre-treated using a suite of image enhancement techniques based on the environmental conditions present within each image. A 75-epoch model variant provided the highest average recall and precision values; however, it appeared to be limited by sub-optimal detections of false positive values. Although further development is required, including the creation of standardised image data pools, increased model benchmarking and the advancement of tailored pre-processing techniques, this work demonstrates the viability of utilising deep learning to automate the detection of surface turbulence features within a tidal stream environment.

Tidal energy is a rapidly developing area of the marine renewable energy sector that requires converters to be placed within areas of fast current speeds to be commercially viable. Tidal environments are also utilised by marine fauna (marine mammals, seabirds and fish) for foraging purposes, with usage patterns observed at fine spatiotemporal scales (seconds and metres). An overlap between tidal developments and fauna creates uncertainty regarding the environmental impact of converters. Due to the limited number of tidal energy converters in operation, there is inadequate knowledge of marine megafaunal usage of tidal stream environments, especially the collection of fine-scale empirical evidence required to inform on and predict potential environmental effects. This review details the suitability of using multirotor unmanned aerial vehicles within tidal stream environments as a tool for capturing fine-scale biophysical interactions. This includes presenting the advantages and disadvantages of use, highlighting complementary image processing and automation techniques, and showcasing the limited current examples of usage within tidal stream environments. These considerations help to demonstrate the appropriateness of unmanned aerial vehicles, alongside applicable image processing, for use as a survey tool to further quantify the potential environmental impacts of marine renewable energy developments.

With rising interest in marine renewable energy (MRE) associated with offshore wind, waves, and tidal flows, the effects of device placement on changes in animal behaviour require proper assessment to minimise environmental impacts and inform decision making. High-frequency multibeam echosounders, or imaging sonars, can be used to observe and record the underwater movement and behaviour of animals at a fine scale (tens of metres). However, robust target detection and tracking of closely spaced animals are required for assessing animal–device and predator–prey interactions. Dual-frequency multibeam echosounders combine longer detection ranges (low frequency) with greater detail (high frequency) while maintaining a wide field of view and a full water column range compared to acoustic or optical cameras. This study evaluates the performance of the Tritech Gemini 1200ik imaging sonar at 720 kHz (low frequency) and 1200 kHz (high frequency) for small target detection with increasing range and the ability of the two frequency modes to discriminate between two closely spaced targets using a 38.1 mm tungsten carbide acoustic calibration sphere under controlled conditions. The quality of target detection decreases for both modes with increasing range, with a 25 m limit of detection at high frequency and a low-frequency mode able to detect the target up to 30 m under test conditions in shallow water. We quantified the enhanced performance of the high-frequency mode in discriminating targets at short ranges and improved target detection and discrimination at high ranges in the low-frequency mode.

Abstract Driven by the necessity to decarbonize energy sources, many countries are targeting tidal stream environments for power generation. However, these areas can act as foraging hotspots for marine top predators, such as seabirds. Thus, it is important to understand the ecological interactions influencing predator behavior and distribution in these areas, to determine the potential ecological implications of marine renewable devices. This study used concurrent observations of foraging seabirds, physical hydrodynamics, and prey presence across a tidal stream environment, before and after the installation of a commercial turbine array close to the island of Stroma, Scotland. There were three main findings: First, benthic foraging seabirds showed a clear preference for certain sections around Stroma where sandeels were detected, while pelagic foraging seabirds were seen all around Stroma. Second, there was a positive effect of water velocity on the number of pelagic foragers and common guillemots. Third, there was a positive effect of the presence of fish schools on the number of pelagic seabirds and common guillemots, in both the same and the previous transects. Thus, it is possible that seabirds target areas of predictable food sources during periods where prey might be easily accessed (e.g., periods of fast flows). Given the difference in the distribution between seabird categories, it is likely that marine renewable devices will impact each category differently. We conclude that any impact on sandbank locations, sandeels preferred habitat, due to the presence of tidal turbines is likely to alter the distribution of benthic foraging seabirds. For pelagic foraging seabirds and common guillemot, changes in prey presence and accessibility (depth and level of aggregation/disaggregation) will have a stronger effect on seabird presence. This study highlights the need to include concurrent physical and biological data when assessing the ecological impacts of tidal turbines.

Tidal stream environments exhibit fast current flows and unique turbulent features occurring at fine spatio-temporal scales (metres and seconds). There is now global recognition of the importance of tidal stream environments for marine megafauna. Such areas are also key to the development of marine renewable energy due to the reliable and predictable nature of tidally driven flows. Bed-derived turbulent features, such as kolk-boils, transport organic material to the surface and may increase the availability of prey species (fish) for foraging marine megafauna (seabirds and marine mammals). Quantification of animal association and interactions with turbulent features is required to understand potential environmental impacts of tidal energy developments in these sites. Downward-facing unmanned aerial vehicle (UAV) imagery was collected within the Pentland Firth, UK. Resulting imagery was used to quantify the density distribution of pursuit-diving seabirds, called auks (of the family Alcidae), distribution in comparison relation to concurrent surface imagery of kolk-boils and, analyse evaluate spatial relationships with individual kolk-boil features, and quantify body orientation relative to the water flow. Although variability was present, auk density distribution was generally correlated with that of kolk-boils throughout the study area; however, spatial analysis highlighted an overall trend of finer-scale dispersion between individual auks and kolk-boils. Auk orientation on the surface was primarily observed across the flow throughout ebb and flood tidal phases. These results suggest that auks may be associating with kolk-boil peripheries. Similarly, it may be energetically beneficial to orientate across the flow while maintaining observation of current flow or searching for shallow prey species and potential threats in the environment. This work demonstrates that UAV imagery was appropriate for quantification of fine-scale biophysical interactions. It allowed for concurrent measurement of hydrodynamic and predator metrics in a challenging environment and provided novel insights not possible to collect by conventional survey methodology. This technique can increase the evidence base for assessment of potential impacts of marine renewable energy extraction on key marine species.

In recent years, the remote sensing of marine plastic litter has been rapidly evolving and the technology is most advanced in the visible (VIS), near-infrared (NIR), and short-wave infrared (SWIR) wavelengths. It has become clear that sensing using VIS-SWIR bands, based on the surface reflectance of sunlight, would benefit from complementary measurements using different technologies. Thermal infrared (TIR) sensing shows potential as a novel method for monitoring macro plastic litter floating on the water surface, as the physics behind surface-leaving TIR is different. We assessed a thermal radiance model for floating plastic litter using a small UAV-grade FLIR Vue Pro R 640 thermal camera by flying it over controlled floating plastic litter targets during the day and night and in different seasons. Experiments in the laboratory supported the field measurements. We investigated the effects of environmental conditions, such as temperatures, light intensity, the presence of clouds, and biofouling. TIR sensing could complement observations from VIS, NIR, and SWIR in several valuable ways. For example, TIR sensing could be used for monitoring during the night, to detect plastics invisible to VIS-SWIR, to discriminate whitecaps from marine litter, and to detect litter pollution over clear, shallow waters. In this study, we have shown the previously unconfirmed potential of using TIR sensing for monitoring floating plastic litter.

In the dynamic environments targeted for marine renewable energy extraction, such as tidal channels, the natural distribution of fish and behavioural impacts of marine renewable energy installations (MREIs) are poorly understood. This study builds on recent methodological developments to reveal the behaviour of fish schools using data collected by a seabed-mounted echosounder deployed in extreme tidal flows and in the wake of a MREI (composed of the foundation of a full-scale tidal stream energy turbine). The results show a significant change (p

High-flow tidal stream environments, targeted for tidal turbine installations, exhibit turbulent features, at fine spatio-temporal scales (metres and seconds), created by site-specific topography and bathymetry. Bed-derived turbulent features (kolk-boils) are thought to have detrimental effects on tidal turbines. Characterisation of kolk-boils is therefore essential to inform turbine reliability, control, and maintenance strategies. It will also improve the understanding of potential ecological interactions with turbines, as marine animals use these sites for foraging. Unmanned aerial vehicle (UAV), or drone, imagery offers a novel approach to take precise measurements of kolk-boil characteristics (distribution, presence, and area) at the surface. This study carried out sixty-three UAV surveys within the Inner Sound of the Pentland Firth, Scotland, UK, over four-day periods in 2016 and 2018. Kolk-boil characteristics were examined against relevant environmental covariates to investigate potential drivers of presence and area. The results show that distribution at the surface could be predicted based on tidal phase, with current velocity significantly influencing presence above 3.0 m/s. The technique can be used to inform turbine development, micro-siting and provide better understanding of environmental implications of turbine operation. Finally, it highlights the suitability of UAVs for capturing rapid fine-scale hydrodynamic data in the absence of in situ measurements.

The growth of the marine renewable energy sector requires the potential effects on marine wildlife to be considered carefully. For this purpose, utilization distributions derived from animal-borne biologging and telemetry data provide accurate information on individual space use. The degree of spatial overlap between potentially vulnerable wildlife such as seabirds and development areas can subsequently be quantified and incorporated into impact assessments and siting decisions. While rich in information, processing and analyses of animal-borne tracking data are often not trivial. There is therefore a need for straightforward and reproducible workflows for this technique to be useful to marine renewables stakeholders. The aim of this study was to develop an analysis workflow to extract utilization distributions from animal-borne biologging and telemetry data explicitly for use in assessment of animal spatial overlap with marine renewable energy development areas. We applied the method to European shags (Phalacrocorax aristotelis) in relation to tidal stream turbines. While shag occurrence in the tidal development area was high (99.4%), there was no overlap (0.14%) with the smaller tidal lease sites within the development area. The method can be applied to any animal-borne bio-tracking datasets and is relevant to stakeholders aiming to quantify environmental effects of marine renewables.