The precautionary approach to fisheries management requires accounting of uncertainty to ensure stock sustainability. Most fisheries management is based on a single-species approach, with stocks assumed independent of one another, even though it is known that stocks interact through predation and competition for resources. The strength of these interactions depends on the relative abundance and size/age composition of stocks, but they are usually treated as fixed. Therefore, a key question is: can we simultaneously adopt the precautionary approach for multiple stocks while accounting for these interactions? Here we examine the impact of stock interactions on calculations of precautionary reference points for nine stocks in the North Sea. We combined four multispecies models using an ensemble model to rigorously quantify uncertainty and explore the rates of fishing mortality that leads to groups of stocks being fished according to the precautionary approach. We found that relaxing the assumption of stock independence meant that no fishing at all was only precautionary for six of nine stocks, and no fishing strategy was precautionary for all nine. We suggest that it is necessary to account for multispecies interactions when calculating precautionary reference points.

Thousands of Marine Protected Areas (MPAs) have been designated around the globe to conserve benthic habitats, following the adoption of Convention on Biodiversity Aichi Target 11 and widespread endorsement of the '30by30' initiative. When designed and managed effectively, MPAs can enrich biodiversity, enhance ecosystem services and regulate stakeholder access. High quality dedicated monitoring programmes are essential to determine MPA effectiveness at the correct spatial and temporal scales; however, such programmes can be fraught with complexities and many MPAs have not yet implemented them following designation. There is, therefore, a clear need and opportunity for scientists to share and draw on collective experiences to help reduce barriers to successful MPA monitoring. This study synthesises lessons learned and challenges encountered in the English MPA monitoring programme, reflecting on solutions and future directions. Twenty-three MPA moni-toring reports were reviewed and the key findings were extracted. The majority were centred around the need to consider monitoring approaches at the scale of each individual MPA, rather than adoption of generic 'one-size -fits-all' practices. Various challenges were found to be inherent, whilst some were prioritised for further development: MPA-scale measures of condition, fishing activity data, seabed imagery acquisition and analysis, DNA technologies, habitat mapping, and ecosystem approaches to MPA monitoring. This study highlights the benefits of strong multi-disciplinary partnerships for addressing the complex issues encountered in MPA monitoring programmes. We endorse further studies, technical advancements and a more holistic ecosystem approach to understanding human impacts on the benthos, thus optimising MPA management and positive conservation outcomes.

1. Evidence-based decisions relating to effective marine protected areas as a means of conserving biodiversity require a detailed understanding of the species present. The Caribbean island nation of St Lucia is expanding its current marine protected area network by designating additional no-take marine reserves on the west coast. However, information on the distribution of fish species is currently limited. 2. This study used baited remote underwater stereo-video to address this shortcom-ing by investigating the effects of depth and seabed habitat structure on demersal fish assemblages and comparing these assemblages between regions currently afforded different protection measures. 3. From the 87 stations visited a total of 5,921 fish were observed comprising 120 fish taxa across 22 families. Species richness and total abundance were higher within the highly managed region, which included no-take reserves. Redundancy analysis explained 17% of the total variance in fish distribution, driven predominantly by the seabed habitats. The redundancy analysis identified four main groups of demersal fishes each associated with specific seabed habitats. 4. The current no-take marine reserves protected two of these groups (i.e. fishes associated with the ‘ soft corals, hard corals or gorgonians ’ and ‘ seagrass ’ groups). Importantly, habitats dominated by sponges, bacterial mats, algal turfs or macroalgae, which also supported unique fish assemblages, are not currently afforded protection via the marine reserve network (based on the five reserves studied). These results imply that incorporation of the full breadth of benthic habitat types present would improve the efficacy of the marine reserve network by ensuring all fish assemblages are protected.

Sedimentation rate data are applied in a range of studies such as understanding the sediment carbon budget and accumulation of pollutants in marine sediments. Over many years, sedimentation rate samples have been collected within the Baltic Sea. However, to understand patterns in sedimentation rates more broadly across this sea basin requires converting these point data into continuous spatial predictions. The generation of continuous maps remains problematic and under-studied. This study explores the feasibility of machine learning to estimate sedimentation rates, using 137Cs measurements from the Baltic Sea. A random forest model was applied to predict sedimentation rates based on a range of predictor variables that related to the hydrodynamic regime, bathymetric complexity of the seabed, substrate type and proximity to sediment sources. The accuracy of this prediction was tested against an independent set of sedimentation rate samples that had been withheld from model training. The model was also compared against a simple spatial interpolation to assess whether machine learning produces an improvement on previously applied methods. Overall, the modelling approach explained 41.9% of the variance, far surpassing the spatial interpolation method (4.2% variance explained). This study is a first step towards the spatial prediction of sediment accumulation rates in a repeatable and validated way, but further refinement is desirable to improve the accuracy of the predictions. We discuss the potential sources of model error that could have limited the success of this approach and suggest how some of these could be addressed. Our results indicate that short-term sedimentation rates are highest in small coastal basins, while rates in the deep basins of the Baltic Sea are generally low, thereby seemingly contradicting long held views of the deep-basins as the major depocentres in the Baltic Sea. This apparent contradiction might be attributed to the higher spatial detail of our analysis and differences in the time scales of analysis, indicating that sedimentation patterns in the Baltic Sea might be complex in space and time.

Baited remote underwater stereo‐video systems (stereo‐BRUVs) are a popular tool to sample demersal fish assemblages and gather data on their relative abundance and body size structure in a robust, cost‐effective and non‐invasive manner. Given the rapid uptake of the method, subtle differences have emerged in the way stereo‐BRUVs are deployed and how the resulting imagery is annotated. These disparities limit the interoperability of datasets obtained across studies, preventing broadscale insights into the dynamics of ecological systems. We provide the first globally accepted guide for using stereo‐BRUVs to survey demersal fish assemblages and associated benthic habitats. Information on stereo‐BRUVs design, camera settings, field operations and image annotation are outlined. Additionally, we provide links to protocols for data validation, archiving and sharing. Globally, the use of stereo‐BRUVs is spreading rapidly. We provide a standardized protocol that will reduce methodological variation among researchers and encourage the use of Findable, Accessible, Interoperable and Reusable workflows to increase the ability to synthesize global datasets and answer a broad suite of ecological questions.

The ocean floor, its species and habitats are under pressure from various human activities. Marine spatial planning and nature conservation aim to address these threats but require sufficiently detailed and accurate maps of the distribution of seabed substrates and habitats. Benthic habitat mapping has markedly evolved as a discipline over the last decade, but important challenges remain. To test the adequacy of current data products and classification approaches, we carried out a comparative study based on a common dataset of multibeam echosounder bathymetry and backscatter data, supplemented with groundtruth observations. The task was to predict the spatial distribution of five substrate classes (coarse sediments, mixed sediments, mud, sand, and rock) in a highly heterogeneous area of the south-western continental shelf of the United Kingdom. Five different supervised classification methods were employed, and their accuracy estimated with a set of samples that were withheld. We found that all methods achieved overall accuracies of around 50%. Errors of commission and omission were acceptable for rocky substrates, but high for all sediment types. We predominantly attribute the low map accuracy regardless of mapping approach to inadequacies of the selected classification system, which is required to fit gradually changing substrate types into a rigid scheme, low discriminatory power of the available predictors, and high spatial complexity of the site relative to the positioning accuracy of the groundtruth equipment. Some of these issues might be alleviated by creating an ensemble map that aggregates the individual outputs into one map showing the modal substrate class and its associated confidence or by adopting a quantitative approach that models the spatial distribution of sediment fractions. We conclude that further incremental improvements to the collection, processing and analysis of remote sensing and sample data are required to improve map accuracy. To assess the progress in benthic habitat mapping we propose the creation of benchmark datasets.

The potential risk to the marine environment of oil release from potentially polluting wrecks (PPW) is increasingly being acknowledged, and in some instances remediation actions have been required. However, where a PPW has been identified, there remains a great deal of uncertainty around the environmental risk it may pose. Estimating the likelihood of a wreck to release oil and the threat to marine receptors remains a challenge. In addition, removing oil from wrecks is not always cost effective, so a proactive approach is recommended to identify PPW that pose the greatest risk to sensitive marine ecosystems and local economies and communities. This paper presents a desk-based assessment approach which addresses PPW, and the risk they pose to environmental and socio-economic marine receptors, using modelled scenarios and a framework and scoring system. This approach can be used to inform proactive management options for PPW and can be applied worldwide.

Sediment maps developed from categorical data are widely applied to support marine spatial planning across various fields. However, deriving maps independently of sediment classification potentially improves our understanding of environmental gradients and reduces issues of harmonising data across jurisdictional boundaries. As the groundtruth samples are often measured for the fractions of mud, sand and gravel, this data can be utilised more effectively to produce quantitative maps of sediment composition. Using harmonised data products from a range of sources including the European Marine Observation and Data Network (EMODnet), spatial predictions of these three sediment fractions were generated for the north-west European continental shelf using the random forest algorithm. Once modelled these sediment fraction maps were classified using a range of schemes to show the versatility of such an approach, and spatial accuracy maps were generated to support their interpretation. The maps produced in this study are to date the highest resolution quantitative sediment composition maps that have been produced for a study area of this extent and are likely to be of interest for a wide range of applications such as ecological and biophysical studies.

Thematic maps are important for a range of disciplines including spatial planning and ecosystem status assessments. Despite an increasing focus on accuracy assessment methods to ensure maps are fit for purpose, the adoption of these recommendations has not been widespread. We present a methodology which utilises boot-strap aggregation and adheres to recommended practices for accuracy assessments. Furthermore, additional information is extracted from the model outputs to produce spatial maps of confidence also supporting map interpretation. The methodology has been applied to two study sites using both pixel-based and object-based units of analyses. Accuracy assessments for both study sites identified the classes that were responsible for most of the map error. In addition, spatially explicit confidence maps supported our understanding of the sources of error. This paper provides a useful methodology to improve accuracy assessment and reporting and is well suited to studies where groundtruth data are limited.

Summary To generate realistic predictions, species distribution models require the accurate coregistration of occurrence data with environmental variables. There is a common assumption that species occurrence data are accurately georeferenced; however, this is often not the case. This study investigates whether locational uncertainty and sample size affect the performance and interpretation of fine‐scale species distribution models. This study evaluated the effects of locational uncertainty across multiple sample sizes by subsampling and spatially degrading occurrence data. Distribution models were constructed for kelp (Ecklonia radiata), across a large study site (680 km2) off the coast of southeastern Australia. Generalized additive models were used to predict distributions based on fine‐resolution (2·5 m cell size) seafloor variables, generated from multibeam echosounder data sets, and occurrence data from underwater towed video. The effects of different levels of locational uncertainty in combination with sample size were evaluated by comparing model performance and predicted distributions. While locational uncertainty was observed to influence some measures of model performance, in general this was small and varied based on the accuracy metric used. However, simulated locational uncertainty caused changes in variable importance and predicted distributions at fine scales, potentially influencing model interpretation. This was most evident with small sample sizes. Results suggested that seemingly high‐performing, fine‐scale models can be generated from data containing locational uncertainty, although interpreting their predictions can be misleading if the predictions are interpreted at scales similar to the spatial errors. This study demonstrated the need to consider predictions across geographic space rather than performance alone. The findings are important for conservation managers as they highlight the inherent variation in predictions between equally performing distribution models, and the subsequent restrictions on ecological interpretations.

Maps that depict the distribution of substrate, habitat or biotope types on the seabed are in increasing demand by marine ecologists and spatial planners, underpinning decision making in relation to marine spatial planning and marine protected area network design. Yet, the science discipline of image-based seabed mapping has not fully matured and rapid progress is needed to improve the reliability and accuracy of maps. To speed up the process we have conducted a literature review of common practices in terrestrial image classification based on remote sensing data, a related discipline, albeit with a larger scientific community and longer history. We identified the following key elements of a mapping workflow: (i) Data pre-processing, (ii) Feature extraction, (iii) Feature selection, (iv) Classification, (v) Post-classification enhancements, and (vi) Evaluation of classification performance. Insights gained from the review served as a baseline against which recent seabed mapping studies were compared. In this way we identified knowledge gaps and propose modifications to the mapping workflow. A main concern in current seabed mapping practice is that a large amount of often correlated predictor features is extracted, creating a multidimensional feature space. To effectively fill this space with an appropriate amount of training samples is likely to be impossible. Hence, it is necessary to reduce the dimensionality of the feature space via data transformation [e.g. principal component analysis (PCA)] or feature selection and remove correlated features. We propose to make dimensionality reduction an integral part of any mapping workflow. We also suggest to adopt recommendations for accuracy assessment originally drawn up for terrestrial land cover mapping. These include the publication of two or more measures of accuracy including overall and class-specific metrics, publication of associated confidence limits and the provision of the error matrix.

The conservation of many endothermic species depends critically on the availability of suitable retreat sites, yet we know little about the variation in thermal quality of such microhabitats. Studies of thermal habitat suitability for birds and mammals must account for the effect of endothermic heat production on their microclimates. For example, endotherms may significantly raise the air temperature in their retreat sites and this effect must be considered when assessing retreat site quality. We devised an inexpensive means by which to construct pseudo-endothermic 'environmental temperature' models with the use of disposable heat pads. We applied this technique to investigate thermal aspects of nest box design, illustrating the potential positive and negative effects of nest box insulation depending on the environmental context. We suggest that, from a thermal perspective, the avoidance of heat stress is an important and underappreciated issue in the retreat site selection of endotherms.