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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.

Abstract: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.Weconclude 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]