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Abstract The management and conservation of tuna and other transboundary marine species have to date been limited by an incomplete understanding of the oceanographic, ecological and socioeconomic factors mediating fishery overlap and interactions, and how these factors vary across expansive, open ocean habitats. Despite advances in fisheries monitoring and biologging technology, few attempts have been made to conduct integrated ecological analyses at basin scales relevant to pelagic fisheries and the highly migratory species they target. Here, we use vessel tracking data, archival tags, observer records, and machine learning to examine inter‐ and intra‐annual variability in fisheries overlap (2013–2020) of five pelagic longline fishing fleets with North Pacific albacore tuna (Thunnus alalunga, Scombridae). Although progressive declines in catch and biomass have been observed over the past several decades, the North Pacific albacore is one of the only Pacific tuna stocks primarily targeted by pelagic longlines not currently listed as overfished or experiencing overfishing. We find that fishery overlap varies significantly across time and space as mediated by (1) differences in habitat preferences between juvenile and adult albacore; (2) variation of oceanographic features known to aggregate pelagic biomass; and (3) the different spatial niches targeted by shallow‐set and deep‐set longline fishing gear. These findings may have significant implications for stock assessment in this and other transboundary fishery systems, particularly the reliance on fishery‐dependent data to index abundance. Indeed, we argue that additional consideration of how overlap, catchability, and size selectivity parameters vary over time and space may be required to ensure the development of robust, equitable, and climate‐resilient harvest control rules. 

Abstract The dynamics of marine systems at decadal scales are notoriously hard to predict—hence references to this timescale as the “grey zone” for ocean prediction. Nevertheless, decadal-scale prediction is a rapidly developing field with an increasing number of applications to help guide ocean stewardship and sustainable use of marine environments. Such predictions can provide industry and managers with information more suited to support planning and management over strategic timeframes, as compared to seasonal forecasts or long-term (century-scale) predictions. The most significant advances in capability for decadal-scale prediction over recent years have been for ocean physics and biogeochemistry, with some notable advances in ecological prediction skill. In this paper, we argue that the process of “lighting the grey zone” by providing improved predictions at decadal scales should also focus on including human dimensions in prediction systems to better meet the needs and priorities of end users. Our paper reviews information needs for decision-making at decadal scales and assesses current capabilities for meeting these needs. We identify key gaps in current capabilities, including the particular challenge of integrating human elements into decadal prediction systems. We then suggest approaches for overcoming these challenges and gaps, highlighting the important role of co-production of tools and scenarios, to build trust and ensure uptake with end users of decadal prediction systems. We also highlight opportunities for combining narratives and quantitative predictions to better incorporate the human dimension in future efforts to light the grey zone of decadal-scale prediction.