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Graphic abstract Food from the sea can make a larger contribution to healthy and sustainable diets, and to addressing hunger and malnutrition, through improvements in production, distribution and equitable access to wild harvest and mariculture resources and products. The supply and consumption of seafood is influenced by a range of ‘drivers’ including ecosystem change and ocean regulation, the influence of corporations and evolving consumer demand, as well as the growing focus on the importance of seafood for meeting nutritional needs. These drivers need to be examined in a holistic way to develop an informed understanding of the needs, potential impacts and solutions that align seafood production and consumption with relevant 2030 Sustainable Development Goals (SDGs). This paper uses an evidence-based narrative approach to examine how the anticipated global trends for seafood might be experienced by people in different social, geographical and economic situations over the next ten years. Key drivers influencing seafood within the global food system are identified and used to construct a future scenario based on our current trajectory (Business-as-usual 2030). Descriptive pathways and actions are then presented for a more sustainable future scenario that strives towards achieving the SDGs as far as technically possible (More sustainable 2030). Prioritising actions that not only sustainably produce more seafood, but consider aspects of access and utilisation, particularly for people affected by food insecurity and malnutrition, is an essential part of designing sustainable and secure future seafood systems. Supplementary Information The online version contains supplementary material available at 10.1007/s11160-021-09663-x.

This a preprint and has not been peer reviewed. Data may be preliminary.

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Marine ecosystem forecasting is an important innovation in fisheries science with considerable value for industry and management, providing new data‐driven means of predicting the distribution and availability of commercially exploited fish stocks over a range of timescales, including near‐real‐time and seasonal. Marine ecosystem forecasting is rapidly advancing as a field, yet tools produced for fisheries to date focus primarily on predicting species distributions. The next generation of marine ecosystem forecasting products could be enhanced by also incorporating predictions of biological characteristics of fish caught, such as body condition and epidemiological status, thereby expanding the utility of these methods beyond predicting distribution alone. Improving the biological dimensions of marine ecosystem forecasting could allow for optimization of efficiencies in wild‐capture fisheries by minimizing discarding and waste and maximizing the value of landed fish. These advancements are of direct benefit to industry and management, address several of the United Nations Sustainable Development Goals pertaining to fisheries sustainability and have the potential to support the maintenance of global food and micronutrient security under rapidly changing environmental conditions. Here, we describe the current state of the art in marine ecosystem forecasting; review the physical‐biological linkages that underlie variability in the body condition of commercially valuable fish and shellfish with particular reference to marine climate change; and outline key considerations for the next generation of marine ecosystem forecasting tools for wild‐capture fisheries.

Marine ecosystems and their associated biodiversity sustain life on Earth and hold intrinsic value. Critical marine ecosystem services include maintenance of global oxygen and carbon cycles, production of food and energy, and sustenance of human wellbeing. However marine ecosystems are swiftly being degraded due to the unsustainable use of marine environments and a rapidly changing climate. The fundamental challenge for the future is therefore to safeguard marine ecosystem biodiversity, function, and adaptive capacity whilst continuing to provide vital resources for the global population. Here, we use foresighting/hindcasting to consider two plausible futures towards 2030: a business-as-usual trajectory (i.e. continuation of current trends), and a more sustainable but technically achievable future in line with the UN Sustainable Development Goals. We identify key drivers that differentiate these alternative futures and use these to develop an action pathway towards the desirable, more sustainable future. Key to achieving the more sustainable future will be establishing integrative (i.e. across jurisdictions and sectors), adaptive management that supports equitable and sustainable stewardship of marine environments. Conserving marine ecosystems will require recalibrating our social, financial, and industrial relationships with the marine environment. While a sustainable future requires long-term planning and commitment beyond 2030, immediate action is needed to avoid tipping points and avert trajectories of ecosystem decline. By acting now to optimise management and protection of marine ecosystems, building upon existing technologies, and conserving the remaining biodiversity, we can create the best opportunity for a sustainable future in 2030 and beyond.

Spatial variations in tuna population and abundance are strongly linked to large-scale climate fluctuations, such as the Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO). However, the mechanisms underlying the association of climate indices with yellowfin tuna (YFT) abundance and habitat preference remain unclear. We analysed long-term longline fishery data for YFT and oceanic climate variability index data for 1971–2018. The standardized catch per unit effort (CPUE) of Indo-Pacific Ocean YFT was higher during negative AMO and positive PDO phases. In tropical Pacific Ocean, the trend of YFT habitat preference exhibited seesaw patterns because of the distinct environmental factors influenced by the PDO phase. The PDO changed the environmental parameters throughout the tropical Indian Ocean such that the habitat preference of YFT remained consistent throughout. However, the variations in habitat suitability did not correspond to the distribution or standardized CPUE of YFT throughout the Pacific Ocean during AMO events. Moreover, the changes in habitat suitability had a positive periodicity of 8–16 years with AMO in the Indian Ocean, but revealed opposite trends with the distribution or standardized CPUE of YFT. Our results provide sufficient information to distinguish the variations between PDO phase changing and YFT standardized CPUE/ habitat preference. Furthermore, the AMO phase shift period 60–100 years longer than that of the PDO (20–30 years), and models employing time series of fishery and environmental data must be extended the time period of our study to make the AMO match the fishery data more complete.

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