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Investigating the relationship between species and environmental conditions is key for the correct management of highly migratory large pelagic species like silky shark (Carcharhinus falciformis). This species is currently ranked as vulnerable by the International Union for Conservation of Nature and the population trend may be decreasing globally. Tuna fisheries annually catch around 5 million tons worldwide but may have effects on the ecosystem, including impacts on certain sensitive non-target species. We provide the first insights into the environmental preferences of silky shark in the Atlantic Ocean by modelling their presence from tropical tuna purse seine observer data (~ 7500 fishing sets between 2003 and 2015) with a set of biotic and abiotic oceanographic factors, spatial–temporal terms and fishing operation variables. Oceanographic data (sea surface temperature, sea surface temperature change, salinity, sea surface height, chlorophyll-a, chlorophyll-a change, oxygen, and current information such as speed, direction and eddy kinetic energy) were downloaded and processed from the EU Copernicus Marine Environment Monitoring Service. Results provide information on the hotspots dynamics of silky shark as well as its habitat preferences. Models detected a significant relationship between seasonal upwelling events, mesoscale features and silky shark presence and suggested strong interaction between productive systems and the spatial–temporal distribution of the species. The model also highlighted both persistent (i.e. Gabon) and temporary areas (i.e. Guinea and southern-central tropical Atlantic Ocean) for silky shark in the region. This information could be used to assist tuna regional fisheries management organizations in the conservation and management of this vulnerable non-target species.

To protect the most vulnerable marine species it is essential to have an understanding of their spatiotemporal distributions. In recent decades, Bayesian statistics have been successfully used to quantify uncertainty surrounding identified areas of interest for bycatch species. However, conventional simulation-based approaches are often computationally intensive. To address this issue, in this study, an alternative Bayesian approach (Integrated Nested Laplace Approximation with Stochastic Partial Differential Equation, INLA-SPDE) is used to predict the occurrence of Mobula mobular species in the eastern Pacific Ocean (EPO). Specifically, a Generalized Additive Model is implemented to analyze data from the Inter-American Tropical Tuna Commission’s (IATTC) tropical tuna purse-seine fishery observer bycatch database (2005–2015). The INLA-SPDE approach had the potential to predict both the areas of importance in the EPO, that are already known for this species, and the more marginal hotspots, such as the Gulf of California and the Equatorial area which are not identified using other habitat models. Some drawbacks were identified with the INLA-SPDE database, including the difficulties of dealing with categorical variables and triangulating effectively to analyze spatial data. Despite these challenges, we conclude that INLA approach method is an useful complementary and/or alternative approach to traditional ones when modeling bycatch data to inform accurately management decisions.

Floating objects drifting in the surface of tropical waters, also known as drifting fish aggregating devices (DFADs), attract hundreds of marine species, including tuna and non-tuna species. Industrial tropical purse seiners have been increasingly deploying artificial man-made DFADs equipped with satellite linked echo-sounder buoys, which provide fishers with information on the accurate geo-location of the object and rough estimates of the biomass aggregated underneath, to facilitate the catch of tuna. Although several hypotheses are under consideration to explain the aggregation and retention processes of pelagic species around DFADs, the reasons driving this associative behavior are uncertain. This study uses information from 962 echo-sounder buoys attached to virgin (i.e. newly deployed) DFADs deployed in the Western Indian Ocean between 2012 and 2015 by the Spanish fleet (42,322 days observations) to determine the first detection day of tuna and non-tuna species at DFAD and to model the aggregation processes of both species group using Generalize Additive Mixed Models. Moreover, different seasons, areas and depths of the DFAD underwater structure were considered in the analysis to account for potential spatio-temporal and structure differences. Results show that tuna species arrive at DFADs before non-tuna species (13.5±8.4 and 21.7±15.1 days, respectively), and provide evidence of the significant relationship between DFAD depth and detection time for tuna, suggesting faster tuna colonization in deeper objects. For non-tuna species, this relationship appeared to be not significant. The study also reveals both seasonal and spatial differences in the aggregation patterns for different species groups, suggesting that tuna and non-tuna species may have different aggregative behaviors depending on the spatio-temporal dynamic of DFADs. This work will contribute to the understanding of the fine and mesoscale ecology and behavior of target and non-target species around DFADs and will assist managers on the sustainability of exploited resources, helping to design spatio-temporal conservation management measures for tuna and non-tuna species.

Growth models describe the change in length or weight as a function of age. Growth curves in tunas can take different forms from relatively simple von Bertalanffy growth curves (Atlantic bluefin, albacore tunas) to more complex two- or three-stanza growth curves (yellowfin, bigeye, skipjack, southern bluefin tunas). We reviewed the growth of the principal market tunas (albacore, bigeye, skipjack, yellowfin and the three bluefin tuna species) in all oceans to ascertain the different growth rates among tuna species and their implications for population productivity and resilience. Tunas are among the fastest-growing of all fishes. Compared to other species, tunas exhibit rapid growth (i.e., relatively high K ) and achieve large body sizes (i.e., high L ∞ ). A comparison of their growth functions reveals that tunas have evolved different growth strategies. Tunas attain asymptotic sizes ( L ∞ ), ranging from 75 cm FL (skipjack tuna) to 400 cm FL (Atlantic bluefin tuna), and reach L ∞ at different rates ( K ), varying from 0.95 year −1 (skipjack tuna) to 0.05 year −1 (Atlantic bluefin tuna). Skipjack tuna (followed by yellowfin tuna) is considered the “fastest growing” species of all tunas. Growth characteristics have important implications for population dynamics and fisheries management outcomes since tunas, and other fish species, with faster growth rates generally support higher estimates of Maximum Sustainable Yield (MSY) than species with slower growth rates.

In the eastern Pacific Ocean, the tropical tuna purse-seine fishery incidentally captures high numbers of five mobulid bycatch species; all of which are classified as mortalities by the Inter-American Tropical Tuna Commission due to uncertainties in post-release mortality rates. To date, the factors (operational or environmental) leading to the capture of these species by the fishery have not been well studied. Here, we developed Generalized Additive Models for fisheries observer data to analyze the relationships between the presence/absence of Mobula mobular bycatch and oceanographic conditions, the spatial and temporal variability in fishing location, and the set type (associated with dolphins, free-swimming tuna schools or floating objects). Our results suggest that chlorophyll concentration and sea surface height are the most important variables to describe the presence of M. mobular in conjunction with geographic location (latitude and longitude) and set type. Presence of the species was predicted in waters with chlorophyll concentrations between 0.5-1 mg·m-3 and with sea surface height values close to 0; which indicates direct relationships with productive upwelling systems. Seasonally, M. mobular was observed more frequently during December-January and August-September. We also found the highest probability of presence observed in School sets, followed by Dolphin sets. Three areas were observed as important hotspots: the area close to the coastal upwelling of northern Peru, the area west to Islands Colon Archipelago (Galapagos) and the area close to the Costa Rica Dome. This information is crucial to identify the mobulids habitat and hotspots that could be managed and protected under dynamic spatial management measures to reduce the mortality of mobulid rays in the eastern Pacific purse-seine fishery and, hence, ensure the sustainability of the populations of these iconic species.

More than a decade of bottom-up collaborative workshops and research with fishers from the principal tropical tuna purse seine fleets to reduce ecological impacts associated with the use of fish aggregating devices (FADs) has yielded novel improved sustainable fishing practices in all oceans. This integrative effort is founded on participatory knowledge-exchange workshops organized by the International Seafood Sustainability Foundation (ISSF), referred to as “ISSF Skippers Workshops”, where scientists, fishers, and key stakeholders examine and develop together ways and tools to minimize fishery impacts. Workshops organized since 2010 have reached fleet members in 23 countries across Asia, Africa, the Americas, Europe, and Oceania, with over 4,000 attendances, mostly skippers and crew, operating in the Indian, Atlantic, and Pacific oceans. Structured and continued open transparent discussions on ocean-specific options to minimize FAD associated bycatch, ghost fishing and marine pollution have produced an array of novel co-constructed solutions and a better understanding of ecosystem and fishery dynamics. Dedicated at sea research cruises in commercial purse seiners have enabled testing some of the ideas proposed in workshops. Results obtained were then communicated back to fishers for a double loop learning system resulting in solution refinement and/or adoption. Furthermore, fishers’ increased trust and stewardship have stimulated unprecedented large-scale science-industry research projects across oceans, such as multi-fleet biodegradable FAD trials, the adoption and widespread use of non-entangling FADs, and the development and adoption of best practices for the safe handling and release of vulnerable bycatch. This model of collaborative research is broadly applicable to other natural resource conservation fields. Support for long-term inclusive programs enabling harvesters to proactively collaborate in impact mitigation research contributes to improved scientific advice, voluntary compliance, and adaptive management for lasting sustainability trajectories.

Tunas sustain important fisheries that face sustainability challenges worldwide, including the uncertainty inherent to natural systems. The Kobe process aims at harmonizing the scientific advice and management recommendations in tuna regional fisheries management organizations (RFMOs) toward supporting the sustainable exploitation of tunas globally. In this context, we review the similarities and differences among tuna RFMOs, focusing on stock assessment methodologies, use of information, characterization of uncertainty and communication of advice. Also, under the Kobe process, tuna RFMOs have committed to a path of adopting harvest strategies (HSs), also known as management procedures (MPs), which are the series of actions undertaken to monitor the stock, make management decisions, and implement the management measures. The adoption of HSs for tuna stocks is supported by Management Strategy Evaluation (MSE), which is considered the most appropriate way to assess the consequences of uncertainty for achieving fisheries management goals. Overall, notable progress has been made in achieving some of the Kobe objectives, but there are still some aspects that are inconsistent and need to be agreed upon, due to their management implications. First, not all RFMOs report on stock status based on maximum sustainable yield (MSY) as a reference. Instead, some use depletion level to represent the available fish biomass. Also, the definition of overexploited is not common in all oceans. Finally, very few stock assessments characterize all major sources of uncertainty inherent to fisheries. With regards to HSs, two different approaches are being followed: One is designed to adopt an automatic decision rule once the stock status and management quantities have been agreed upon (harvest control rules (HCRs), not strictly an HS) and the other aims at adopting all the components of HSs (data, use of information and decision rule).

Natural geochemical markers in the otolith of yellowfin tuna ( Thunnus albacares ) were used to establish nursery-specific signatures for investigating the origin of fish captured in the western Atlantic Ocean (WAO). Two classes of chemical markers (trace elements, stable isotopes) were used to first establish nursery-specific signatures of age-0 yellowfin tuna from four primary production zones in the Atlantic Ocean: Gulf of Mexico, Caribbean Sea, Cape Verde, and Gulf of Guinea. Next, mixture and individual assignment methods were applied to predict the origin of sub-adult and adult yellowfin tuna from two regions in the WAO (Gulf of Mexico, Mid Atlantic Bight) by relating otolith core signatures (corresponding to age-0 period) to baseline signatures of age-0 fish from each nursery. Significant numbers of migrants from Caribbean Sea and eastern Atlantic Ocean (EAO) production zones (Gulf of Guinea, Cape Verde) were detected in the WAO, suggesting that fisheries in this region were subsidized by outside spawning/nursery areas. Contributions from local production (Gulf of Mexico) were also evident in samples from both WAO fisheries, but highly variable from year to year. High levels of mixing by yellowfin tuna from the different production zones and pronounced interannual trends in nursery-specific contribution rates in the WAO emphasize the complex and dynamic nature of this species’ stock structure and population connectivity. Given that geographic shifts in distribution across national or political boundaries leads to governance and management challenges, this study highlights the need for temporally resolved estimates of nursery origin to refine assessment models and promote the sustainable harvest of this species.

Reproductive timing can be defined as the temporal pattern of reproduction over a lifetime. Although reproductive timing is highly variable in marine fishes, certain traits are universal, including sexual maturity, undergoing one or more reproductive cycles, participating in one or more spawning events within a reproductive cycle, release of eggs or offspring, aging, and death. These traits commonly occur at four temporal scales: lifetime, annual, intraseasonal, and diel. It has long been known that reproductive timing affects reproductive success, especially in terms of the onset of sexual maturity and the match or mismatch between seasonal spawning and offspring survival. However, a comprehensive understanding of variability in reproductive timing over species, populations, and temporal scales is lacking. In addition, there is a need to assess how variability in reproductive timing affects a population's resilience. Because natural selection occurs at the individual level, this necessitates an understanding of within-population (i.e., individual) variability in reproductive timing and how fishing may impact it through age truncation and size-specific selectivity or fisheries-induced evolution. In this paper, we review the temporal aspects of reproductive strategies and the four most-studied reproductive timing characteristics in fishes: sexual maturity, spawning seasonality, spawning frequency, and diel periodicity. For each characteristic, we synthesize how it has traditionally been measured, advances in understanding the underlying physiology, its role in equilibriumbased fish population dynamics, and its importance to reproductive success. We then provide a review of emerging methodology—with an emphasis on ovarian histology—to improve our ability to assess variability in reproductive timing both among populations and within populations.