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Risk of impact of marine fishes to fishing and climate change (including ocean acidi- fication) depend on the species’ ecological and biological characteristics, as well as their exposure to over‐exploitation and climate hazards. These human‐induced haz- ards should be considered concurrently in conservation risk assessment. In this study, we aim to examine the combined contributions of climate change and fishing to the risk of impacts of exploited fishes, and the scope for climate‐risk reduction from fisheries management. We combine fuzzy logic expert system with species dis- tribution modeling to assess the extinction risks of climate and fishing impacts of 825 exploited marine fish species across the global ocean. We compare our calcu- lated risk index with extinction risk of marine species assessed by the International Union for Conservation of Nature (IUCN). Our results show that 60% (499 species) of the assessed species are projected to experience very high risk from both over- fishing and climate change under a “business‐as‐usual” scenario (RCP 8.5 with cur- rent status of fisheries) by 2050. The risk index is significantly and positively related to level of IUCN extinction risk (ordinal logistic regression, p20%) chance of having high extinction risk in the next few dec- ades (equivalent to the IUCN categories of vulnerable, endangered or critically endangered). Areas with more at‐risk species to climate change are in tropical and subtropical oceans, while those that are at risk to fishing are distributed more broadly, with higher concentration of at‐risk species in North Atlantic and South Pacific Ocean. The number of species with high extinction risk would decrease by 63% under the sustainable fisheries‐low emission scenario relative to the “business ‐as‐usual” scenario. This study highlights the substantial opportunities for climate ‐risk reduction through effective fisheries management.

Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species' sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biological and ecological attributes of many marine species, as well as inherent uncertainties in the assessment process, climate change vulnerability assessments in the marine environment frequently focus on a limited number of taxa or geographic ranges. As climate change is already impacting marine biodiversity and fisheries, there is an urgent need to expand vulnerability assessment to cover a large number of species and areas. Here, we develop a modelling approach to synthesize data on species-specific estimates of exposure, and ecological and biological traits to undertake an assessment of vulnerability (sensitivity and adaptive capacity) and risk of impacts (combining exposure to hazards and vulnerability) of climate change (including ocean acidification) for global marine fishes and invertebrates. We use a fuzzy logic approach to accommodate the variability in data availability and uncertainties associated with inferring vulnerability levels from climate projections and species' traits. Applying the approach to estimate the relative vulnerability and risk of impacts of climate change in 1074 exploited marine species globally, we estimated their index of vulnerability and risk of impacts to be on average 52 ± 19 SD and 66 ± 11 SD, scaling from 1 to 100, with 100 being the most vulnerable and highest risk, respectively, under the 'business-as-usual' greenhouse gas emission scenario (Representative Concentration Pathway 8.5). We identified 157 species to be highly vulnerable while 294 species are identified as being at high risk of impacts. Species that are most vulnerable tend to be large-bodied endemic species. This study suggests that the fuzzy logic framework can help estimate climate vulnerabilities and risks of exploited marine species using publicly and readily available information.

Human-driven global change is causing ongoing declines in biodiversity worldwide. In order to address these declines, decision-makers need accurate assessments of the status of and pressures on biodiversity. However, these are heavily constrained by incomplete and uneven spatial, temporal and taxonomic coverage. For instance, data from regions such as Europe and North America are currently used overwhelmingly for large-scale biodiversity assessments due to lesser availability of suitable data from other, more biodiversity-rich, regions. These data-poor regions are often those experiencing the strongest threats to biodiversity, however. There is therefore an urgent need to fill the existing gaps in global biodiversity monitoring. Here, we review current knowledge on best practice in capacity building for biodiversity monitoring and provide an overview of existing means to improve biodiversity data collection considering the different types of biodiversity monitoring data. Our review comprises insights from work in Africa, South America, Polar Regions and Europe; in government-funded, volunteer and citizen-based monitoring in terrestrial, freshwater and marine ecosystems. The key steps to effectively building capacity in biodiversity monitoring are: identifying monitoring questions and aims; identifying the key components, functions, and processes to monitor; identifying the most suitable monitoring methods for these elements, carrying out monitoring activities; managing the resultant data; and interpreting monitoring data. Additionally, biodiversity monitoring should use multiple approaches including extensive and intensive monitoring through volunteers and professional scientists but also harnessing new technologies. Finally, we call on the scientific community to share biodiversity monitoring data, knowledge and tools to ensure the accessibility, interoperability, and reporting of biodiversity data at a global scale.

6 pages, 5 figures, supporting information https://doi.org/10.1073/pnas.1900194116.-- All data reported in this paper are archived and publicly available at http://dataservices.gfz-potsdam.de/pik/showshort.php?id=escidoc:2956913., While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends, Financial support was provided by the German Federal Ministry of Education and Research through ISI-MIP (Grant01LS1201A1), the European Union’s Horizon 2020 Research and Innovation Program (Grant 678193), and the Ocean Frontier Institute (Module G). We acknowledge additional financial support as follows: to H.K.L., W.W.L.C., and B.W. from the Natural Sciences and Engineering Research Council (NSERC) of Canada; to D.P.T. from the Kanne Rasmussen Foundation Denmark; to A.B.-B. from the NSERC Transatlantic Ocean Science and Technology Program; to W.W.L.C. and T.D.E. from the Nippon Foundation-Nereus Program; to E.D.G., M.C. and J. Steenbeek from the European Union’s Horizon 2020 Re-search and Innovation Program (Grants 682602 and 689518); to E.A.F., J.L.B., andT.R. from Commonwealth Scientific and Industrial Research Organization and the Australian Research Council; to N.B., L.B., and O.M. from the French Agence Nationale de la Recherche and Pôle de Calcul et de Données pour la Mer; and to S.J. from the UK Department of Environment, Food and Rural Affairs

Climate change is projected to redistribute fisheries resources, resulting in tropical regions suffering decreases in seafood production. While sustainably managing marine ecosystems contributes to building climate resilience, these solutions require transformation of ocean governance. Recent studies and international initiatives suggest that conserving high seas biodiversity and fish stocks will have ecological and economic benefits; however, implications for seafood security under climate change have not been examined. Here, we apply global-scale mechanistic species distribution models to 30 major straddling fish stocks to show that transforming high seas fisheries governance could increase resilience to climate change impacts. By closing the high seas to fishing or cooperatively managing its fisheries, we project that catches in exclusive economic zones (EEZs) would likely increase by around 10% by 2050 relative to 2000 under climate change (representative concentration pathway 4.5 and 8.5), compensating for the expected losses (around −6%) from ‘business-as-usual’. Specifically, high seas closure increases the resilience of fish stocks, as indicated by a mean species abundance index, by 30% in EEZs. We suggest that improving high seas fisheries governance would increase the resilience of coastal countries to climate change.

The global ocean is projected to be warmer, less oxygenated and more acidic in the 21st century relative to the present day, resulting in changes in the biogeography and productivity of marine organisms and ecosystems. Previous studies using a Dynamic Bioclimate Envelope Model (DBEM) projected increases in potential catch in high latitude regions and decreases in tropical regions over the next few decades. A major structural uncertainty of the projected redistribution of species and fisheries catches can be attributed to the habitat suitability algorithms used. Here, we compare the DBEM projections of potential catches of 500 species of exploited marine fishes and invertebrates from 1971 to 2060 using three versions of DBEM that differ by the algorithm used to predict relative habitat suitability: DBEM-Basic, DBEM-Maxent and DBEM-Aquamaps. All the DBEM models have similar skill in predicting the occurrence of exploited species and distribution of observed fisheries production. Globally, the models project a decrease in catch potential of 3% to 13% by 2050 under a high emissions scenario (Representative Concentration Pathway 8.5). For the majority of the modelled species, projections by DBEM-Maxent are less sensitive to changes in ocean properties than those by DBEM-Aquamaps. The mean magnitude of projected changes relative to differences between projections differ between regions, being highest (>1 times the standard deviation) in the tropical regions and Arctic Ocean and lowest in three of the main Eastern Boundary Upwelling regions, the eastern Indian Ocean and the Southern Ocean. These results suggest that the qualitative patterns of changes in catch potential reported in previous studies are not affected by the structural uncertainty of DBEM, particularly in areas where catch potential was projected to be most sensitive to climate change. However, when making projections of fish stocks and their potential catches using DBEM in the future, multiple versions of DBEM should be used to quantify the uncertainty associated with structural uncertainty of the models. Overall, this study contributes to improving projection of future changes in living marine resources by exploring one aspect of the cascade of uncertainty associated with such projections.

Climate change is shifting the abundance and distribution of marine species with consequences for ecosystem functioning, seafood supply, management and conservation. Several approaches for future projection exist but these have never been compared systematically to assess their variability. We conducted standardized ensemble projections including 6 global fisheries and marine ecosystem models, forced with 2 Earth-system models and 4 emission scenarios in a fished and unfished ocean, to derive average trends and associated uncertainties. Without fishing, mean global animal biomass decreased by 5% (±4%) under low and 17% (±11%) under high emissions by 2100, primarily driven by increasing temperature and decreasing primary production. These climate-change effects were slightly weaker for larger animals and in a fished ocean. Considerable regional variation ranged from strong biomass increases in high latitudes to strong decreases in mid-low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to differences among ecosystem or Earth-system models were similar, suggesting equal need for model improvement. Our ensemble projections provide the most comprehensive outlook on potential climate-driven ecological changes in the ocean to date. Realized future trends will largely depend on how fisheries and management adapt to these changes in a changing climate.

Projections of the impacts of climate change on marine ecosystems are a key prerequisite for the planning of adaptation strategies, yet they are inevitably associated with uncertainty. Identifying, quantifying, and communicating this uncertainty is key to both evaluating the risk associated with a projection and building confidence in its robustness. We review how uncertainties in such projections are handled in marine science. We employ an approach developed in climate modelling by breaking uncertainty down into (i) structural (model) uncertainty, (ii) initialization and internal variability uncertainty, (iii) parametric uncertainty, and (iv) scenario uncertainty. For each uncertainty type, we then examine the current state-of-the-art in assessing and quantifying its relative importance. We consider whether the marine scientific community has addressed these types of uncertainty sufficiently and highlight the opportunities and challenges associated with doing a better job. We find that even within a relatively small field such as marine science, there are substantial differences between subdisciplines in the degree of attention given to each type of uncertainty. We find that initialization uncertainty is rarely treated explicitly and reducing this type of uncertainty may deliver gains on the seasonal-to-decadal time-scale. We conclude that all parts of marine science could benefit from a greater exchange of ideas, particularly concerning such a universal problem such as the treatment of uncertainty. Finally, marine science should strive to reach the point where scenario uncertainty is the dominant uncertainty in our projections.

The research leading to these results has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration (FP7/2007-2013) within the Ocean of Tomorrow call under Grant Agreement No.266445 for the project Vectors of Change in Oceans and Seas Marine Life, Impact on Economic Sectors (VECTORS). This work is also a contribution to the EU Cost Action FA1004 "Conservation Physiology". PS acknowledges support from the UK Natural Environment Research Council and Department for Environment, Food and Rural Affairs [grant number NE/L003279/1, Marine Ecosystems Research Programme. The authors wish to thank Drs. Jason Link, Elizabeth Fulton and Oivind Fiksen as well as an anonymous reviewer for their helpful comments on an earlier version of this manuscript. This work also benefitted from discussions among members of the ICES Working Group on Integrated Physical biological and Ecosystem Modelling (WGIPEM) and the ICES-PICES Strategic Initiative on Climate Change Impacts on Marine Ecosystems (SICCME). Academic press ltd- elsevier science ltd London Si Marine & Freshwater Biology; Oceanography Iences, v367, p2979 Iences, v367, p1607; International audience; We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

1. Climate change can affect the survival, colonization and establishment of non-native species. Many non-native species common in Europe are spreading northwards as seawater temperatures increase. The similarity of climatic conditions between source and recipient areas is assumed to influence the establishment of such species, however, in a changing climate those conditions are difficult to predict. 2. A risk assessment methodology has been applied to identify non-native species with proven invasive qualities that have not yet arrived in north-west Europe, but which could become problematic in the future. Those species with the highest potential to become established or be problematic have been taken forward, as well as some that may be economically beneficial, for species distribution modelling to determine future potential habitat distributions under projected climate change. 3. In the past, species distribution models have usually made use of low resolution global environmental datasets. Here, to increase the local resolution of the distribution models, downscaled shelf seas climate change model outputs for north-west Europe were nested within global outputs. In this way the distribution model could be trained using the global species presence data including the species' native locations, and then projected using more comprehensive shelf seas data to understand habitat suitability in a potential recipient area. 4. Distribution modelling found that habitat suitability will generally increase further north for those species with the highest potential to become established or problematic. Most of these are known to be species with potentially serious consequences for conservation. With caution, a small number of species may present an opportunity for the fishing industry or aquaculture. The ability to provide potential future distributions could be valuable in prioritizing species for monitoring or eradication programmes, increasing the chances of identifying problem species early. This is particularly important for vulnerable infrastructure or protected or threatened ecosystems.

Species distribution models (SDMs) are important tools to explore the effects of future global changes in biodiversity. Previous studies show that variability is introduced into projected distributions through alternative datasets and modelling procedures. However, a multi-model approach to assess biogeographic shifts at the global scale is still rarely applied, particularly in the marine environment. Here, we apply three commonly used SDMs (AquaMaps, Maxent, and the Dynamic Bioclimate Envelope Model) to assess the global patterns of change in species richness, invasion, and extinction intensity in the world oceans. We make species-specific projections of distribution shift using each SDM, subsequently aggregating them to calculate indices of change across a set of 802 species of exploited marine fish and invertebrates. Results indicate an average poleward latitudinal shift across species and SDMs at a rate of 15.5 and 25.6 km decade−1 for a low and high emissions climate change scenario, respectively. Predicted distribution shifts resulted in hotspots of local invasion intensity in high latitude regions, while local extinctions were concentrated near the equator. Specifically, between 10°N and 10°S, we predicted that, on average, 6.5 species would become locally extinct per 0.5° latitude under the climate change emissions scenario Representative Concentration Pathway 8.5. Average invasions were predicted to be 2.0 species per 0.5° latitude in the Arctic Ocean and 1.5 species per 0.5° latitude in the Southern Ocean. These averaged global hotspots of invasion and local extinction intensity are robust to the different SDM used and coincide with high levels of agreement.

Over-exploitation and economic underperformance are widespread in the world's fisheries. Global climate change is further affecting the distribution of marine species, raising concern for the persistence of biodiversity and presenting additional challenges to fisheries management. However, few studies have attempted to extend bioclimatic projections to assess the socio-economic impacts of climate-induced range shifts. This study investigates the potential implications of changes in relative environmental suitability and fisheries catch potential on UK fisheries by linking species distribution modelling with cost-benefit analyses. We develop scenarios and apply a multimodel approach to explore the economic sensitivity of UK fisheries and key sources of uncertainty in the modelling procedure. We projected changes in maximum potential catch of key species and the resulting responses in terms of net present value (NPV) over a 45-year period under scenarios of change in fuel price, discount rate and government subsidies. Results suggest that total maximum potential catch will decrease within the UK EEZ by 2050, resulting in a median decrease in NPV of 10%. This value decreases further when trends of fuel price change are extrapolated into the future, becoming negative when capacity-enhancing subsidies are removed. Despite the variation in predictions from alternative models and data input, the direction of change in NPV is robust. This study highlights key factors influencing future profitability of UK fisheries and the importance of enhancing adaptive capacity in UK fisheries.

Fishers and scientists have known for over 100 years that the status of fish stocks can be greatly influenced by prevailing climatic conditions. Based on historical sea surface temperature data, the North Sea has been identified as one of 20 ‘hot spots’ of climate change globally and projections for the next 100 years suggest that the region will continue to warm. The consequences of this rapid temperature rise are already being seen in shifts in species distribution and variability in stock recruitment. This chapter reviews currentevidence for climate change effects on fisheries in the North Sea—one of the most important fishing grounds in the world—as well as available projections for North Sea fisheries in the future. Discussion focuses on biological, operational and wider market concerns, as well as on possible economic consequences. It is clear that fish communities and the fisheries that target them will be very different in 50 or 100 years’ time and that management and governance will need to adapt accordingly

Commercial fishing is an important socio-economic activity in coastal regions of the UK and Ireland. Ocean–atmospheric changes caused by greenhouse gas emissions are likely to affect future fish and shellfish production, and lead to increasing challenges in ensuring long-term sustainable fisheries management. The paper reviews existing knowledge and understanding of the exposure of marine ecosystems to ocean-atmospheric changes, the consequences of these changes for marine fisheries in the UK and Ireland, and the adaptability of the UK and Irish fisheries sector. Ocean warming is resulting in shifts in the distribution of exploited species and is affecting the productivity of fish stocks and underlying marine ecosystems. In addition, some studies suggest that ocean acidification may have large potential impacts on fisheries resources, in particular shell-forming invertebrates. These changes may lead to loss of productivity, but also the opening of new fishing opportunities, depending on the interactions between climate impacts, fishing grounds and fleet types. They will also affect fishing regulations, the price of fish products and operating costs, which in turn will affect the economic performance of the UK and Irish fleets. Key knowledge gaps exist in our understanding of the implications of climate and ocean chemistry changes for marine fisheries in the UK and Ireland, particularly on the social and economic responses of the fishing sectors to climate change. However, these gaps should not delay climate change mitigation and adaptation policy actions, particularly those measures that clearly have other ‘co-benefits’. Copyright © 2012 John Wiley & Sons, Ltd.

Species distribution models are important tools to explore the effects of future global change on biodiversity. Specifically, AquaMaps, Maxent and the Sea Around Us Project algorithm are three approaches that have been applied to predict distributions of marine fishes and invertebrates. They were designed to cope with issues of data quality and quantity common in species distribution modelling, and especially pertinent to the marine environment. However, the characteristics of model projections for marine species from these different approaches have rarely been compared. Such comparisons provide information about the robustness and uncertainty of the projections, and are thus important for spatial planning and developing management and conservation strategies. Here we apply the three commonly used species distribution modelling methods for commercial fish in the North Sea and North Atlantic, with the aim of drawing comparisons between the approaches. The effect of different assumptions within each approach on the predicted current relative habitat suitability was assessed. Predicted current distributions were tested following data partitioning and selection of pseudoabsences from within a specified distance of occurrence data. As indicated by the test statistics, each modelling method produced plausible predictions of relative habitat suitability for each species, with subsequent incorporation of expert knowledge generally improving predictions. However, because of the differences between modelling algorithms, methodologies and patterns of relative suitability, comparing models using test statistics and selecting a ‘best’ model are not recommended. We propose that a multi-model approach should be preferred and a suite of possible predictions considered if biases due to uncertainty in data and model formulation are to be minimised.

Studies have demonstrated ways in which climate-related shifts in the distributions and relative abundances of marine species are expected to alter the dynamics and catch potential of global fisheries. While these studies assess impacts on large-scale commercial fisheries, few efforts have been made to quantitatively project impacts on small-scale subsistence and commercial fisheries that are economically, socially and culturally important to many coastal communities. This study uses a dynamic bioclimate envelope model to project scenarios of climate-related changes in the relative abundance, distribution and richness of 98 exploited marine fishes and invertebrates of commercial and cultural importance to First Nations in coastal British Columbia, Canada. Declines in abundance are projected for most of the sampled species under both the lower (Representative Concentration Pathway [RCP] 2.6) and higher (RCP 8.5) emission scenarios (-15.0% to -20.8%, respectively), with poleward range shifts occurring at a median rate of 10.3 to 18.0 km decade(-1) by 2050 relative to 2000. While a cumulative decline in catch potential is projected coastwide (-4.5 to -10.7%), estimates suggest a strong positive correlation between the change in relative catch potential and latitude, with First Nations' territories along the northern and central coasts of British Columbia likely to experience less severe declines than those to the south. Furthermore, a strong negative correlation is projected between latitude and the number of species exhibiting declining abundance. These trends are shown to be robust to alternative species distribution models. This study concludes by discussing corresponding management challenges that are likely to be encountered under climate change, and by highlighting the value of joint-management frameworks and traditional fisheries management approaches that could aid in offsetting impacts and developing site-specific mitigation and adaptation strategies derived from local fishers' knowledge.

Marine eutrophication refers to an ecosystem response to the loading of nutrients, typically nitrogen (N), to coastal waters where several impacts may occur. The increase of planktonic growth due to N-enrichment fuels the organic carbon cycles and may lead to excessive oxygen depletion in benthic waters. Such hypoxic conditions may cause severe effects on exposed ecological communities. The biologic processes that determine production, sink, and aerobic respiration of organic material, as a function of available N, are coupled with the sensitivity of demersal species to hypoxia to derive an indicator of the Ecosystem Response (ER) to N-uptake. The loss of species richness expressed by the ER is further modelled to a marine eutrophication Ecosystem Damage (meED) indicator, as an absolute metric of time integrated number of species disappeared (species yr), by applying a newly-proposed and spatially-explicit factor based on species density (SD). The meED indicator is calculated for 66 Large Marine Ecosystems and ranges from 1.6 × 10 −12 species kgN −1 in the Central Arctic Ocean, to 4.8 × 10 −8 species kgN −1 in the Northeast U.S. Continental Shelf. The spatially explicit SDs contribute to the environmental relevance of meED scores and to the harmonisation of marine eutrophication impacts with other ecosystem-damage Life Cycle Impact Assessment (LCIA) indicators. The novel features improve current methodologies and support the adoption of the meED indicator in LCIA for the characterization of anthropogenic-N emissions and thus contributing to the sustainability assessment of human activities.

The Paris Conference of Parties (COP21) agreement renewed momentum for action against climate change, creating the space for solutions for conservation of the ocean addressing two of its largest threats: climate change and ocean acidification (CCOA). Recent arguments that ocean policies disregard a mature conservation research field, and that protected areas cannot address climate change may be over-simplistic at this time when dynamic solutions for the management of changing oceans are needed. We propose a novel approach, based on spatial meta-analysis of climate impact models, to improve the positioning of marine protected areas to limit CCOA impacts. We do this by estimating the vulnerability of ocean ecosystems to CCOA in a spatially-explicit manner, and then co-mapping human activities such as the placement of renewable energy developments and the distribution of marine protected areas. We test this approach in the NE Atlantic considering also how CCOA impacts the base of the food web which supports protected species, an aspect often neglected in conservation studies. We found that, in this case, current regional conservation plans protect areas with low ecosystem-level vulnerability to CCOA, but disregard how species may re-distribute to new, suitable and productive habitats. Under current plans, these areas remain open to commercial extraction and other uses. Here, and worldwide, ocean conservation strategies under CCOA must recognize the long-term importance of these habitat refuges, and studies such as this one are needed to identify them. Protecting these areas creates adaptive, climate-ready and ecosystem-level policy options for conservation, suitable for changing oceans. This article is protected by copyright. All rights reserved.

The ocean provides food, economic activity, and cultural value for a large proportion of humanity. Our knowledge of marine ecosystems lags behind that of terrestrial ecosystems, limiting effective protection of marine resources. We describe the outcome of 2 workshops in 2011 and 2012 to establish a list of important questions, which, if answered, would substantially improve our ability to conserve and manage the world’s marine resources. Participants included individuals from academia, government, and nongovernment organizations with broad experience across disciplines, marine ecosystems, and countries that vary in levels of development. Contributors from the fields of science, conservation, industry, and government submitted questions to our workshops, which we distilled into a list of priority research questions. Through this process, we identified 71 key questions. We grouped these into 8 subject categories, each pertaining to a broad component of marine conservation: fisheries, climate change, other anthropogenic threats, ecosystems, marine citizenship, policy, societal and cultural considerations, and scientific enterprise. Our questions address many issues that are specific to marine conservation, and will serve as a road map to funders and researchers to develop programs that can greatly benefit marine conservation. Setenta y Un Preguntas Importantes para la Conservación de la Biodiversidad Marina Resumen Los océanos proporcionan alimento, actividad económica y valor cultural para una gran porción de la humanidad. Nuestro conocimiento de los ecosistemas marinos está atrasado con respecto al que tenemos de los ecosistemas terrestres, lo que limita la protección efectiva de los recursos naturales. Describimos el resultado de dos talleres en 2011 y 2012 para establecer una lista de preguntas importantes, las cuales al ser respondidas, mejorarían sustancialmente nuestra habilidad de conservar y manejar los recursos marinos del mundo. Entre los participantes se incluyeron a individuos de la docencia, el gobierno y organizaciones no-gubernamentales, con una amplia experiencia que atraviesa disciplinas, ecosistemas marinos y países que varían en el nivel de desarrollo. Los contribuyentes de los campos de la ciencia, la conservación, la industria y el gobierno, presentaron preguntas a nuestros talleres, las cuales separamos en una lista de preguntas de investigación prioritarias. Por medio de este proceso, identificamos 71 preguntas clave. Las agrupamos en ocho categorías temáticas, cada una perteneciente a un componente amplio de la conservación marina: pesquerías, cambio climático, otras amenazas antropogénicas, ecosistemas, ciudadanía marina, política, consideraciones sociales y culturales, y la iniciativa científica. Nuestras preguntas se dirigen a muchas cuestiones que son específicas de la conservación marina, y servirán como una ruta a seguir para patrocinadores e investigadores que busquen desarrollar programas que puedan beneficiar ampliamente a la conservación marina.

The inherent complexity of the environment is such that attempts to model it must operate under simplifications and assumptions. Considering predictions from alternative models, with a range of assumptions and data requirements, therefore provides a more robust approach. The intractability and uncertainty resulting from a suite of predictions may hinder the application of science in policy, where a single prediction with little ambiguity or uncertainty would be most desirable. Few studies modelling species' distributions attempt to present multi-model outputs in a format most useful to the non-modelling community, and none of these have done so for the marine environment. The problem of uncertainty is particularly prevalent in predicting the distribution of invasive alien species under climate change. As invasive alien species are one of the main drivers of biodiversity loss and may incur significant economic costs, the benefit of applying predictions to highlight areas of possible establishment and inform policy and management may be large. An ensemble prediction is used to assess the distribution of suitable habitat for the Pacific oyster, Crassostrea gigas, in UK waters both currently and in the future. The ensemble incorporates predictions from three species distribution models, using data from two global climate models. A method is developed highlighting the agreement of the ensemble, further applying threshold values to retain information from constituent predictions in the final map of agreement. Ensemble predictions made here suggest that Pacific oyster will experience an opening of suitable habitat in northern UK waters, reaching the Faroe Islands and the eastern Norwegian Sea by 2050. Habitat suitability will increase with warming temperatures in the English Channel and Central North Sea for this species. The approaches applied here can be incorporated into risk assessment frameworks for invasive species, as stipulated in the Convention on Biological Diversity.

Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina). ISSN:1932-6203

The Fifth Assessment Report of the Intergovernmental Panel on Climate Change highlights that climate change and ocean acidification are challenging the sustainable management of living marine resources (LMRs). Formal and systematic treatment of uncertainty in existing LMR projections, however, is lacking. We synthesize knowledge of how to address different sources of uncertainty by drawing from climate model intercomparison efforts. We suggest an ensemble of available models and projections, informed by observations, as a starting point to quantify uncertainties. Such an ensemble must be paired with analysis of the dominant uncertainties over different spatial scales, time horizons, and metrics. We use two examples: (i) global and regional projections of Sea Surface Temperature and (ii) projection of changes in potential catch of sablefish (Anoplopoma fimbria) in the 21st century, to illustrate this ensemble model approach to explore different types of uncertainties. Further effort should prioritize understanding dominant, undersampled dimensions of uncertainty, as well as the strategic collection of observations to quantify, and ultimately reduce, uncertainties. Our proposed framework will improve our understanding of future changes in LMR and the resulting risk of impacts to ecosystems and the societies under changing ocean conditions.