Many industries rely on wave data to understand the potential for wave energy extraction, or to understand the wave environment for the design of marine structures and to plan operations and maintenance. Three ocean reanalysis datasets, ERA5, WAVEWATCH III and Copernicus Global Ocean Waves Analysis and Forecast, are compared to in-situ wave buoy data collected along the north of Scotland. All reanalysis datasets correlated well with the wave buoy data, with the Copernicus Global Ocean Waves Analysis and Forecast dataset being statistically the closest to the buoy data. However, all three reanalysis datasets underpredict significant wave height during extreme wave events. From comparisons of the wave buoy data at one site, it was found that although extreme events are underpredicted, the WAVEWATCH III reanalysis data performed the best, although still under predicted extreme wave heights. Of the reanalysis models compared against wave buoy data here, it is suggested that for extreme wave analysis the WAVEWATCH III model is recommended, whilst for long term statistics and weather windowing the Copernicus Global Ocean Waves Analysis is a good option. Whilst reanalysis data sets are a valuable resource for marine renewable energy, developers should be aware of the limitations of these datasets, in particular for extreme wave conditions.

This study investigated wave power at a remote site in Indonesia where in-situ data are scarce to inform feasibility and design parameters for a modular wave energy converter. The methodology was developed using models to assess initial wave energy, and to validate these models using remote-sensing data in the absence of in-situ observational data, intended to also be used more widely in data-poor locations to provide an assessment of wave energy site suitability. To assess the available wave energy, two models were employed: the Copernicus WAVERYS global wave model and a high-resolution model using open-source hydrodynamic modelling software. Affordable bathymetric data were used, and due to the lack of in-situ wave data for validation, the model’s precision was confirmed by comparing it with the existing satellite altimeter data. The high-resolution model indicated a redistribution of wave energy around the target area in the southern region of Sumbawa Island, revealing an average wave energy potential of 18 kW/m over a decade at the location. The analysis showed the area to be suitable for this demonstration project, and the methods used here could be employed at other remote sites in the Indonesian archipelago.

Floating offshore wind is expected to expand globally into further offshore, deeper and highly productive shelf seas to utilise increased and more consistent wind energy. Marine mammals represent mobile species that connect across regions and can indicate wider ecosystem changes. To date, only a handful of ecological impact studies have been conducted at floating offshore wind farms, due to the infancy of the technology and small numbers of operational sites. Understanding how floating offshore wind could alter ecosystem functions and impact species at individual and population levels will be essential to mitigate potential negative ecological impacts as the sector expands. Currently, numerous floating offshore wind sites are planned or already in development. Therefore, evaluating current knowledge and remaining knowledge gaps will benefit future projects in assessing ecological impacts and determining where additional research should be conducted. This review summarises the positive and negative ecological impacts that have been previously highlighted as potential impacts from floating offshore wind, focusing on marine mammals, whilst also considering prey and broader trophic interactions. Current studies at operational floating offshore wind sites are summarised and discussed in context of observed and/or anticipated impacts. Finally, key outstanding research areas are suggested in relation to each impact.

Environmental interactions of marine renewable energy developments vary from fine-scale direct (e.g. potential collision) to indirect wide-scale hydrodynamic changes altering oceanographic features. Current UK Environmental Impact Assessment (EIA) and associated Habitats Regulations Appraisal (HRA) guidelines have limited focus on underlying processes affecting distribution and movements (hence vulnerability) of top predators. This study integrates multi-trophic ship survey (active acoustics and observer data) with an upward-facing seabed platform and 3-dimensional hydrodynamic model as a process-driven framework to investigate predator-prey linkages between seabirds and fish schools. Observer-only data highlighted the need to measure physical drivers of variance in species abundances and distributions. Active acoustics indicated that in situ (preferable to modelled) data were needed to identify temporal changes in hydrodynamics to predict prey and consequently top predator presence. Revising methods to identify key habitats and environmental covariates within current regulatory frameworks will enable more robust and transferable EIA and HRA processes and outputs, and at larger scales for cumulative and strategic-level assessments, enabling future modelling of ecosystem impacts from both climate change and renewable energy extraction.

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.

The diet of the European Shag Gulosus aristotelis was assessed at one of their most northerly roosts in the UK; Bluemull Sound, Shetland. One pellet and 40 faecal samples were collected during the non-breeding season. The most frequent prey was Velvet Swimming Crab Necora puber, while the highest number of otoliths were from Saithe Pollachius virens and estimated mean (+/- sd) fish length was 143.9 +/- 66.9 mm (range 81.4-223.6 mm).

Mapping tidal currents is important for a variety of coastal and marine applications. Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive. Previous application of particle image velocimetry to tidal current measurements demonstrated that accuracy depends on site and environmental conditions. This study compares surface velocimetry techniques across a range of these conditions. Various open-source tools and image pre-processing methods were applied to six sets of videos and validation data that cover a variety of site and weather conditions. When wind-driven ripples are present in imagery, it was found a short-wave celerity inversion performed best, with mean absolute percentage error (MAPE) of 5–6% compared to surface drifters. During lower wind speeds, current-advected surface features are visible and techniques which track these work best, of which the most appropriate technique depends on specifics of the collected imagery; MAPEs of 9–21% were obtained. This work has quantified accuracy and demonstrated that surface current maps can be obtained from drones under both high and low wind speeds and at a variety of sites. By following these suggested approaches, practitioners can use drones as a current mapping tool at coastal and offshore sites with confidence in the outputs.

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.

1. The Chagos Archipelago's vast no-take marine protected area (MPA, 640,000 km2) provides refuge for elasmobranchs facing unsustainable depletion by fisheries. Nonetheless, illegal, unreported and unregulated (IUU) fishing poses a substantial threat, and potential future changes to the use of the MPA could render elasmobranchs increasingly vulnerable to exploitation, putting geographically isolated populations, such as reef manta rays (Mobula alfredi) at risk of local extinction. Therefore, the species' long-term movements and habitat use must be identified to help prioritize current enforcement activity and inform future spatial planning. 2. Passive acoustic telemetry and modelled environmental data were used to investigate variations in 42 tagged M. alfredi utilization of a meso-scale aggregation hotspot, Egmont Atoll, between 2019 and 2022. 3. Mobula alfredi displayed the highest levels of residency ever reported (77%), with prolonged absences (>2 months) limited to seven individuals. Egmont atoll was used year-round, with activity peaks during the southeast monsoon (April - November), particularly at sites on the southwest, while sites on the northwest were predominately frequented in the northwest monsoon (December-March). Tags were most likely to be detected when the Indian Ocean Dipole (IOD) was in a positive phase with a greater mixed layer depth, associated with a depression of chlorophyll alpha levels in the Indian Ocean. Thus, M. alfredi may be particularly reliant on Egmont Atoll, where they are predominantly observed feeding, when prey resources are limited elsewhere. 4. In a region where the threat of fisheries is of increasing concern, the identification of crucial M. alfredi habitats is essential for conservation management planning. Given the significant role of Egmont Atoll for the local population, regular IUU enforcement patrols are crucial, particularly during the southeast monsoon. Any future changes to the MPA should prioritize preserving and actively enforcing no-take regulations at Egmont Atoll.

The drive globally to develop more efficient, low-cost renewable energy generating devices to combat climate change, means there are often novel technologies being installed whose environmental effects are unquantified. Frequently, a lack of quantification of such device parameters is compounded by a lack of ecological data, which would facilitate Environmental Impact Assessments (EIAs). This absence of fundamental information may lead to unfocused, unstandardised, costly and time-consuming EIAs. For such cases where both energy device and ecological data are missing, we propose a streamlined desk-based scoping process to direct survey and monitoring efforts. We combined a series of flexible methods, transferable to multiple locations and scenarios; a Activity-Pressure-Stressor framework and associated impact pathways, a Weight of Evidence (WoE) analysis and a Receptor Sensitivity Index (RSI). These were parameterised using data obtained from the literature, with a standardised, robust process and format. This process enabled many potential impact pathways, with unknown consequences, to be robustly consolidated and assessed for their likelihood given the location and conditions, yet these methods have not been previously explicitly combined. Our combined assessment methods identified the most likely impact pathways, and particular taxa that were sensitive to the renewable energy development concerned, and although we found that the lack of consistent, standardised data meant that the scale and strength of species responses remained uncertain, we were able to produce clear monitoring goals to increase efficiency of EIAs. We recommend that this combination of methods is employed when faced with a ‘blank canvas’ scenario, to standardise the scoping procedure and focus standardised data collection and improve environmental impact assessment.

The use of floating photovoltaic systems in freshwater and marine environments is forecast to increase dramatically worldwide within the next decade in response to demands for accelerated decarbonisation of the global economy whilst avoiding competition for land, particularly near population centres. The potential environmental impacts of this expanding, novel technology are gradually becoming apparent and warrant consideration. This study reviews and evaluates the various potential environmental impacts of introducing floating photovoltaic arrays into aquatic (freshwater and marine) ecosystems based on the current state of floating photovoltaic technology and known impacts of similar industries. Environmental impacts of floating photovoltaic systems fall into several categories including shading, impacts on hydrodynamics and water-atmosphere exchange, energy emissions, impacts on benthic communities, and impacts on mobile species. The social acceptability of floating photovoltaic systems and the ability for long-term coexistence with other activities and interests are also discussed. Floating photovoltaic systems have an important role to play in global decarbonisation, but close collaboration between stakeholders will be required to better understand potential environmental and social impacts of this new technology. Development and validation of appropriate monitoring methods at scale, and consideration of long-term, equitable solutions to identified impacts, is important to enable sustainable expansion of this industry.

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 the rapid expansion of offshore windfarms (OWFs) globally, there is an urgent need to assess and predict effects on marine species, habitats, and ecosystem functioning. Doing so at shelf-wide scale while simultaneously accounting for the concurrent influence of climate change will require dynamic, multitrophic, multiscalar, ecosystem-centric approaches. However, as such studies and the study system itself (shelf seas) are complex, we propose to structure future environmental research according to the investigative cycle framework. This will allow the formulation and testing of specific hypotheses built on ecological theory, thereby streamlining the process, and allowing adaptability in the face of technological advancements (e.g. floating offshore wind) and shifting socio-economic and political climates. We outline a strategy by which to accelerate our understanding of environmental effects of OWF development on shelf seas, which is illustrated throughout by a North Sea case study. Priorities for future studies include ascertaining the extent to which OWFs may change levels of primary production; whether wind energy extraction will have knock-on effects on biophysical ecosystem drivers; whether pelagic fishes mediate changes in top predator distributions over space and time; and how any effects observed at localized levels will scale and interact with climate change and fisheries displacement effects.

Unmanned Aerial Vehicles (UAVs), or drones, offer the ability to collect cost-effective fine-scale imagery that is suitable for the capture of concurrent hydrodynamic and faunal data within tidal stream environments. This is a necessary stage of information gathering to inform tidal energy device design, advise control and maintenance strategies and better inform environmental consenting processes. For this study a total of sixty-three UAV surveys were undertaken within the Inner Sound of the Pentland Firth, Scotland, UK, over two 4-day periods in 2016 and 2018. The aims of this data collection effort were to characterise bathymetrically driven hydrodynamic features, comprising of kolk-boil distribution, presence, and area, as well as marine life such as seabird distributions, presence, and orientation relative to the flow. To achieve this, a method to extract quantifiable metrics from UAV imagery was required. This paper details the processes and methodology to create a graphical user interface (GUI) to provide these outputs rather than examining specific results. It includes an explanation of the criteria that the GUI needed to meet to be able to process the imagery, a description of the workflow and an explanation of the sub-routines required such as image registration and calibration. The outputs of the GUI, and their relevance to tidal energy developments, are also discussed. Finally, this paper details future work incorporating computer vision techniques to improve the accuracy, reliability, and processing speed of the GUI.

The drive globally to develop more efficient, low-cost renewable energy generating devices means there are often novel technologies being installed whose environmental effects are unquantified. Frequently, a lack of quantification of such device parameters is compounded by a lack of ecological data, which would facilitate Environmental Impact Assessments (EIAs). This absence of fundamental information may lead to unfocused, unstandardised, costly and time-consuming EIAs.For such cases where both energy device and ecological data are missing, we propose a streamlined desk-based scoping process to direct survey and monitoring efforts. We combined a series of flexible methods, transferable to multiple locations and scenarios; a Driver-Pressure-State-Impact-Response (DPSIR), a Weight of Evidence (WoE) analysis and a Receptor Sensitivity Index (RSI). These were parameterised using data obtained from the literature, with a standardised, robust process and format. This process enabled many potential impact chains with unknown consequences to be robustly consolidated and assessed for their likelihood given the location and conditions, yet these methods have not been previously explicitly combined.Our combined assessment methods identified the most likely impact pathways, and particular taxa that were sensitive to the renewable energy development concerned, and although we found that the lack of consistent, standardised data meant that the scale and strength of species responses remained uncertain, we were able to produce clear monitoring goals to increase efficiency of EIAs. We recommend that this combination of methods is employed when faced with a ‘blank canvas’ scenario, to standardise the scoping procedure and focus standardised data collection and improve environmental impact assessment.

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.

Marine Renewable Energy (MRE) extraction in the UK has until now focused on offshore wind turbines, with targets of 34 GW by 2020. Wave and tidal energy follow this trend, with targets of 1-2 GW 1 . By 2050, most accessible MRE sources will be exploited or close to being fully exploited 2 . However, little is known of the general effects of installation and operation. Impacts on the surrounding ecosystems have been predicted as varying from benign to adverse 3,4 . Experience gained over the years, and around the world, has been summarised in recent reviews, which all highlight the need for more generic modes of assessment 5-7 . MRE developers have also stressed the need for an improved understanding of the baseline environment 8 , measuring common impacts with easily adaptable technologies.

Understanding the complexity of environmental impacts of tidal and wave energy converters (TECs, WECs) still presents a major challenge to the expansion of the marine renewable energy (MRE) industry, particularly for new developments. Using the stressor-receptor framework, we broadly introduce the main environmental effects and potential impacts that are considered for TEC and WEC developments. We first provide an overview of the legislation that governs the need to consider the environmental impacts, and the diverse approaches taken to assess them. We then outline potential effects of relevance to the abiotic and biotic environment in the vicinity of TECs and WECs. These include receptor responses to changes in hydrodynamics and sediments, habitat modification, animal collision risk with dynamic parts of devices, and energy emissions including receptor responses to noise and electromagnetic fields associated with installations. We provide an overview of how changes may directly and indirectly influence components of the ecosystem (e.g., habitats, species, processes). In doing so, we highlight the tools presently in use to monitor or research these effects, identify knowledge gaps, as well as future research needs and strategies. A better understanding of the effects of diverse installations will ultimately support the expansion of the MRE industry. Furthermore, this knowledge will facilitate assessments of cumulative effects and inform marine spatial planning, supporting the implementation and management of sustainable developments in our ocean.

Resource quantification is vital in developing a tidal stream energy site but challenging in high energy areas. Drone-based large-scale particle image velocimetry (LSPIV) may provide a novel, low cost, low risk approach that improves spatial coverage compared to ADCP methods. For the first time, this study quantifies performance of the technique for tidal stream resource assessment, using three sites. Videos of the sea surface were captured while concurrent validation data were obtained (ADCP and surface drifters). Currents were estimated from the videos using LSPIV software. Variation in accuracy was attributed to wind, site geometry and current velocity. Root mean square errors (RMSEs) against drifters were 0.44 m s(-1) for high winds (31 km/h) compared to 0.22 m s(-1) for low winds (10 km/h). Better correlation was found for the more constrained site ((r)2 increased by 4%); differences between flood and ebb indicate the importance of upstream bathymetry in generating trackable surface features. Accuracy is better for higher velocities. A power law current profile approximation enables translation of surface current to currents at depth with satisfactory performance (RMSE = 0.32 m s(-1) under low winds). Overall, drone video derived surface velocities are suitably accurate for "first-order" tidal resource assessments under favourable environmental conditions. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license

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.