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ABSTRACT Accuracy of catch landing data reported by captains of commercial vessels is crucial in the assessment of marine species stocks and in fisheries policy and management. However, this data can be subject to estimation biases, such as a tendency to inflate some catches (to the detriment of others) and refusal to fill in logbooks. We assessed the accuracy of catch reports from the Spanish tropical tuna purse seine fleet (which accounts for 26% of catches in the Indian Ocean) using Benford's law, a mathematical principle effective for detecting irregularities across multiple datasets. During 2013–2020, including periods before and after the implementation of total allowable catch (TAC) limits in 2017, reported catches differed from Benford's expected distribution, especially for bigeye tuna, indicating potential inaccuracies in reported catches. Changes in data reporting after TAC limits were imposed in 2017 suggested modifications in fishing operations and reporting practices. Use of Benford's law highlighted its potential as an auditing tool in fisheries management and provided insights into data integrity that are crucial for sustainable fisheries governance. [ABSTRACT FROM AUTHOR]

Managing populations of wild harvested species requires the ability to regularly provide accurate abundance assessments. For most marine species, changes in abundance can only be monitored indirectly, using methods reliant on harvest-based indices, with significant inherent limitations surrounding the estimation and standardization of harvest effort. Tropical tunas are some of the most exploited marine species in the world and are among several species in critical need of alternative methods for estimating abundance. Addressing this concern, we developed the Associative Behaviour-Based abundance Index (ABBI), designed to provide direct abundance estimates for animals, which exhibit an associative behaviour with aggregation sites. Its implementation in the western Indian Ocean on skipjack tuna (Katsuwonus pelamis), yellowfin tuna (Thunnus albacares) and bigeye tuna (Thunnus obesus), revealed similar trajectories in their relative abundance. The ABBI stands as a potentially promising alternative to enhance traditional tropical tuna stock assessments methods, as well as a new opportunity to assess the abundance of other wild species that display an associative behaviour with physical structures found in their natural environment. [ABSTRACT FROM AUTHOR]

Age-reading protocols for tuna species using annual growth zones in thin-cut transverse otolith sections have produced greater age estimates than previous methods. Lifespan estimates for yellowfin (YFT) and bigeye (BET) tuna (Thunnus albacares and T. obesus) were validated up to 16–18 years in the western North Atlantic Ocean using bomb 14C dating and the current study extends the approach to YFT and BET of the western and central Pacific Ocean (WCPO). Archived otoliths from young-of-the-year (YOY) tuna caught in the WCPO were analysed for 14C to establish a reference chronology covering 30 years (1989–2019). This YOY 14C time series exhibited strong concordance with existing coral-otolith 14C references for the tropical-subtropical Pacific Ocean and was combined as a single chronology. Otolith cores from YFT aged 1–14 years and BET aged 1–13 years from presumed annual counts were analysed for 14C. These measurements aligned with the reference chronology for the calculated hatch years for both species. These findings provide strong evidence that growth zones in thin-sectioned otoliths are deposited annually for YFT and BET of the WCPO and that age interpretation is correct using the current age reading protocol with little to no bias. [ABSTRACT FROM AUTHOR]

Introduction: A sustainable fishery relies on consistent and substantial recruitment. There is, however, considerably high mortality among fish larvae during their early development. One of the most important factors determining larval survival is foraging success. Bigeye tuna is among the most important commercial species in the Indian Ocean. Despite being routinely researched and assessed, it remains unclear how food availability affects the recruitment success of bigeye tuna. Methods: In this study, we used phytoplankton size (MD50) as an indicator of prey availability and investigated the connection betweenMD50 and bigeye tuna recruitment from 2000 to 2018 through the Beverton-Holt stock-recruitment function. The Indian Ocean was divided into four regions to accommodate spatial differences. Results: As a result, larger MD50 could bring higher recruitment, particularly in the eastern and southern Indian Ocean. Based on the analysis, we inferred that for bigeye tuna, the eastern Indian Ocean is the primary spawning ground, and the peak spawning period falls in Season 2 (April-June). Discussion: The conclusions provide valuable insights for understanding the recruitment characteristics of bigeye tuna in the Indian Ocean. [ABSTRACT FROM AUTHOR]

Accurate habitat prediction of Bigeye Tuna, the main fishing target of tuna pelagic fishery, is of great significance to the fishing operation. In response to the fact that most of the current studies use single-source data for habitat prediction, and the association between spatiotemporal features and habitat distribution is not fully explored and that this has limited the further improvement of prediction accuracy, this paper analyzes the spatiotemporal distribution of the characteristics of Bigeye Tuna's highly migratory nature. Additionally, it puts forward a method of habitat prediction that utilizes heterosource remote-sensing data for the four-dimensional time–space–environment–spectrum (TSES) for deep-level feature extraction. First, a multi-source heterogeneous dataset was constructed by combining the spatiotemporal distribution characteristics of the product-level environmental remote-sensing data and the L1B-level original spectral remote-sensing data, and then a multi-branch, dynamic spatiotemporal feature extraction, Long Short-Term Memory Network (LSTM) time-series model was constructed to extract the characteristics of the heterogeneous data. This model was constructed to fully explore and utilize the multidimensional deep-level TSES distribution features affecting the habitat prediction. Finally, the two types of heterogeneous data were subjected to the weighted average-based decision-level fusion to obtain the final prediction results. The experimental results show that compared with other methods, the proposed method in this paper outperforms traditional machine-learning models and other single-source, data-based time-series models, with R2 reaching 0.96278 and RMSE decreasing to 0.031361 in the validation experiments of these models. In contrast, the method in this paper demonstrates good generalization ability and achieves accurate prediction of future fishery distribution. [ABSTRACT FROM AUTHOR]

Tropical tuna fisheries support some of the largest artisanal and industrial fisheries worldwide. Approximately 37% of the tropical tuna catch by industrial purse seiners is obtained from tuna associated with drifting fish aggregating devices (DFADs), where three tuna species coexist: skipjack (Katsuwonus pelamis) , bigeye (Thunnus obesus), and yellowfin tuna (Thunnus albacares) , with stocks subject to different health status. Purse seine fishers heavily rely on acoustic technology to detect and assess the quantity of tuna at DFADs. Yet, accurately distinguishing between species using solely acoustic methods is limited by insufficient knowledge about each species' acoustic response across frequencies. This study was carried out on six swimbladdered individuals belonging to two sets with mean lengths of 51.9 ± 9.5 and 52.9 ± 2 cm. It focuses on the frequency response obtained from ex situ measurements of yellowfin tuna recorded at 38, 70, 120, and 200 kHz, which revealed a flat response across frequencies, with b20 values of −72.4 ± 9, −73.2 ± 8, -72.3 ± 8, and −72.3 ± 9 dB, respectively. These results, contrast with previous findings on bigeye and skipjack, demonstrating the discrimination potential of acoustics in these three species. To harness this potential, a discrimination algorithm was developed. [ABSTRACT FROM AUTHOR]

Bigeye tuna Thunnus obesus is an important migratory species that forages deeply, and El Niño events highly influence its distribution in the eastern Pacific Ocean. While sea surface temperature is widely recognized as the main factor affecting bigeye tuna (BET) distribution during El Niño events, the roles of different types of El Niño and subsurface oceanic signals, such as ocean heat content and mixed layer depth, remain unclear. We conducted A spatial-temporal analysis to investigate the relationship among BET distribution, El Niño events, and the underlying oceanic signals to address this knowledge gap. We used monthly purse seine fisheries data of BET in the eastern tropical Pacific Ocean (ETPO) from 1994 to 2012 and extracted the central-Pacific El Niño (CPEN) indices based on Niño 3 and Niño 4 indexes. Furthermore, we employed Explainable Artificial Intelligence (XAI) models to identify the main patterns and feature importance of the six environmental variables and used information flow analysis to determine the causality between the selected factors and BET distribution. Finally, we analyzed Argo datasets to calculate the vertical, horizontal, and zonal mean temperature differences during CPEN and normal years to clarify the oceanic thermodynamic structure differences between the two types of years. Our findings reveal that BET distribution during the CPEN years is mainly driven by advection feedback of subsurface warmer thermal signals and vertically warmer habitats in the CPEN domain area, especially in high-yield fishing areas. The high frequency of CPEN events will likely lead to the westward shift of fisheries centers. [ABSTRACT FROM AUTHOR]

Several odontocete species depredate catch and bait from fishing gear, resulting in their bycatch and causing substantial economic costs. There are no known mitigation methods for odontocete depredation in pelagic longline fisheries that are effective, do not harm odontocetes and are commercially viable. Understanding odontocetes' depredation strategies can contribute to mitigating this human-wildlife conflict. Using observer data from the Hawaii-based tuna longline fishery, this study summarized teleost and elasmobranch species-specific mean posterior odontocete depredation rates using a simple Bayesian binomial likelihood estimator with a Bayes-Laplace prior. Depredation rates of species with sufficient sample sizes ranged from a high of 1.2% (1.1 to 1.3 95% highest posterior density interval or HDI) for shortbill spearfish to a low of 0.002% (0.001 to 0.003 95% HDI) for blue shark. Depredation of catch is a rare event in this fishery, occurring in about 6% of sets. When depredation did occur, most frequently odontocetes depredated a small proportion of the catch, however, there was large variability in depredation rates between teleost species. For example, bigeye tuna was two times more likely to be depredated than yellowfin tuna (odds ratio = 2.03, 95% CI: 1.8–2.3, P<0.0001). For sets with depredation, 10% and 2% of sets had depredation of over half of the captured bigeye tuna and combined teleosts, respectively. All elasmobranch species had relatively low depredation rates, where only 7 of almost 0.5M captured elasmobranchs were depredated. Odontocetes selectively depredate a subset of the teleost species captured within sets, possibly based on net energy value, chemical, visual, acoustic and textural characteristics and body size, but not median length, which was found to be unrelated to depredation rate (Pearson's r = 0.14, 95% CI: -0.26 to 0.50, p = 0.49). Study findings provide evidence to support the identification and innovation of effective and commercially viable methods to mitigate odontocete depredation and bycatch. [ABSTRACT FROM AUTHOR]

Oxygen minimum zones in the open ocean are predicted to significantly increase in volume over the coming decades as a result of anthropogenic climatic warming. The resulting reduction in dissolved oxygen (DO) in the pelagic realm is likely to have detrimental impacts on water-breathing organisms, particularly those with higher metabolic rates, such as billfish, tunas, and sharks. However, little is known about how free-living fish respond to low DO environments, and therefore, the effect increasing OMZs will have cannot be predicted reliably. Here, we compare the responses of two active predators (bigeye tuna Thunnus obesus and yellowfin tuna Thunnus albacares) to DO at depth throughout the eastern Pacific Ocean. Using time-series data from 267 tagged tunas (59,910 days) and 3D maps of modelled DO, we find that yellowfin tuna respond to low DO at depth by spending more time in shallower, more oxygenated waters. By contrast, bigeye tuna, which forage at deeper depths well below the thermocline, show fewer changes in their use of the water column. However, we find that bigeye tuna increased the frequency of brief upward vertical excursions they performed by four times when DO at depth was lower, but with no concomitant significant difference in temperature, suggesting that this behaviour is driven in part by the need to re-oxygenate following time spent in hypoxic waters. These findings suggest that increasing OMZs will impact the behaviour of these commercially important species, and it is therefore likely that other water-breathing predators with higher metabolic rates will face similar pressures. A more comprehensive understanding of the effect of shoaling OMZs on pelagic fish vertical habitat use, which may increase their vulnerability to surface fisheries, will be important to obtain if these effects are to be mitigated by future management actions. [ABSTRACT FROM AUTHOR]

Static and dynamic area‐based management tools hold substantial potential to balance socioeconomic benefits derived from fisheries and costs from bycatch mortality of at‐risk species. Palau longline fisheries have high bycatch of at‐risk species including the olive ridley marine turtle and silky and blue sharks. This study analyzed a two decades‐long time series of observer and electronic monitoring datasets from the Palau distant‐water and locally‐based pelagic longline fisheries. An interpretable or explainable machine learning‐based modeling approach was used to derive spatially resolved species‐specific catch rate predictions. These models were conditioned on a suite of potentially informative environmental, bathymetric, ocean‐climate metric, vessel, monitoring system, and set‐specific operational predictors. Overall, there would be limited ecological tradeoffs from focusing fishing effort within primary catch rate hotspots for target bigeye and yellowfin tunas. Mean field prediction surfaces also defined catch rate hotspots for at‐risk species of silky and blue sharks, olive ridley turtle, and pelagic stingray, which did not overlap the hotspots for target species. The predicted target species hotspots, however, overlap olive ridley and pelagic stingray warmspots. Results also identify opportunities for temporally dynamic spatial management to control catch rates of target and bycatch species. Management of fishery operational predictors of fishing depth and soak duration present additional opportunities to balance catch rates of at‐risk bycatch and target species. A transition to employing fleetwide or vessel‐based output controls that effectively constrain the fishery would alter the spatial management strategy to focus on zones with the lowest ratio of at‐risk bycatch to commercial catch. Our findings support evidence‐informed evaluation of spatial management strategies and complementary measures to meet objectives for balancing socioeconomic benefits derived from target species catch with costs to threatened species. [ABSTRACT FROM AUTHOR]

The management of fish aggregating devices (FAD) creates heated debates in tuna fishery management organizations striving to reduce the number of deployed floating objects. Through several econometric models and a machine learning approach, we evaluate the consequences of three management scenarios on the catch and profit of the French purse‐seine fleet operating in the Indian Ocean: (1) a half reduction in the number of authorized buoys per vessel, (2) a 72‐day closure of FAD fishing with and (3) without re‐allocation of effort on free schools. The results show a significant decrease of fleet profits by 7%, 10% and 18% respectively. We hypothesize an "economic trap" of FAD fishing caused by the far greater efficiency of this harvesting technique for larger vessels searching for economies of scale, and by the overfished status and catch limitation of yellowfin (Thunnus albacares) and bigeye (Thunnus obesus) tunas in the Indian Ocean. The results are compared with other studies looking at the impact of FAD management measures in other oceans. [ABSTRACT FROM AUTHOR]

Climate change-induced variabilities in the environment and fishing pressure affect the distribution and abundance of bigeye tuna in the Pacific Ocean. Understanding the causal relationships among these factors is complicated and challenging. We constructed a multi-output neural network model based on data from four types of bigeye tuna fisheries (longline and purse seine in the west-central and eastern Pacific Ocean, respectively) and marine environmental data, aiming to analyse the response of bigeye tuna to natural and anthropogenic factors from 1995 to 2019 in the Pacific Ocean. The input layer weights were used to explore the importance of environmental variable, while the output layer weights evaluated the contribution of fishing operations. These factors determined the final spatiotemporal distribution and abundance dynamics for bigeye tuna. The optimal model predicted a strong correlation between the locations of major habitats and El Niño southern Oscillation (ENSO) events, indicating that bigeye tuna abundance dynamics respond to the intensity of climate variability. During El Niño events, suitable conditions lead to an expansion of the main habitats east of 170°W, while during La Niña events, the strengthening of the westward advection leads to the contraction of major habitats west of 170°W. Furthermore, the resource abundance of bigeye tuna is predicted to be higher during moderate to weak El Niño events than during strong El Niño events. The abundances in purse seine and longline-dependent fisheries demonstrate significant different distribution patterns under different ENSO events, reflecting the unique environmental preferences at different life stages of bigeye tuna. Given the increasing frequency of climate variability and escalating fishing pressures, our findings provide beneficial insights for the sustainable development of bigeye tuna resource in the Pacific Ocean. [ABSTRACT FROM AUTHOR]

Summary: The objective of this research is to investigate the impact of different hydrolysis (chemical, enzymatic and microbiological) methods of Bigeye tuna waste (Thunnus obesus) on yield, degree of hydrolysis (DH), chemical composition, amino acid profile, functional properties and microbial quality of FPH produced. The enzymatic technique produced the highest yield (11.04%) and the greatest DH (39.04%) while it gave the lowest average peptide chain length (2.56) (P < 0.05). Also, protein and fat (76.37% and 10.82%, respectively) were the highest in the enzymatic hydrolyzed fish (FPH‐E) followed by microbial fermentation (FPH‐M) (P < 0.05). In FPH‐E, FPH‐M and chemical fish protein hydrolysates (FPH‐C), the essential to non‐essential amino acid ratios were 2.43, 1.79 and 0.51, respectively. They also had good functional properties, although they were less than FPH‐C in terms of water binding capacity (3.47 and 4.18 g g−1), oil binding capacity (9.84 and 7.38 g g−1) and foaming capacity (25% and 30%, respectively), and their foam stability rate was high. All FPHs products had a low range of microbial counts, with the FPH‐M exhibiting the greatest total count of bacteria, lactic acid bacteria and moulds and yeasts. Therefore, the biologically extracted FPH especially FPH‐E has the best compositions and qualities, making them an alternative ingredient for fish meal in fish feed formulation. [ABSTRACT FROM AUTHOR]

Understanding the reproductive characteristics of a species is of crucial for accurate stock assessment and management plans to ensure sustainable fisheries. In this study, the size at 50% sexual maturity (L50) parameters in different bio-ecological provinces were estimated for bigeye tuna, Thunnus obesus, sampled from the Eastern Pacific Ocean tuna fisheries-dependent survey from 2013 to 2019. The overall sex ratio of the catch during the sampling differed significantly from 1:1. Bigeye tuna exhibit sexual dimorphism in the growth of males and females, with a clear shift in predominance from female to male with increasing sizes. In the North Pacific Sub-tropical Gyre (east) (NPST-east), North Pacific Tropical Gyre (NPTG), Pacific North Equatorial Countercurrent (PNEC), and Pacific Equatorial Divergence (PEQD), females (meals) reached sexual maturity round 102 cm (106 cm), 106 cm (100 cm), 125 cm (110 cm), and 113 cm (110 cm), respectively, the estimated L50 of bigeye tuna was 124.08 cm, 121.97 cm, 139.92 cm and 132.45 cm, respectively. The degree of populations mixing between equatorial (PNEC and PEQD) and high-latitude regions (NPST-east and NPTG) is extremely small, but it is reasonably high between the NPST-east and NPTG or PNEC and PEQD. These parameters were significantly different, suggesting the occurrence of a spatial difference in the size-at-maturity of bigeye tuna between these bio-ecological provinces. The findings of this study provide the key information for understanding the life history of bigeye tuna in the Eastern Pacific Ocean and will contribute to the conservation and sustainable yield of this species.

The lifestyle and culture of South Pacific Island countries have been long intertwined with oceanic resources. These countries are heavily dependent on tuna resources for their economies and socioeconomic livelihoods. Despite their importance, the mechanisms behind tuna stock trajectory patterns need to be better understood. With changing climatic and environmental conditions, it has become vital to understand the impact of these changes on tuna resources and if possible include them in long-term tuna harvest and management plans. A significant portion of the stock dynamics of yellowfin tuna (Thunnus albacares), albacore tuna (Th. alalunga) and bigeye tuna (Th. obesus) in the South Pacific Region may possibly be explained only by the environmental factors of sea surface temperature (SST) and Atlantic Multidecadal Oscillation AMO. The relationship of monthly SST and AMO was investigated with time series stock patterns of Th. albacares, Th. alalunga and Th. obesus in the Eastern and Western Pacific Ocean for the years 1972 to 2019. Monthly variables that exhibited significant correlation with CPUE variables were used in the Generalised Linear Model and Generalized Additive Model to reproduce the CPUE trajectory of the three tuna species from 1972 to 2019. Results showed that a significant portion of stock dynamics of Th. albacares, Th. alalunga and Th. obesus can be explained well by two environmental conditions of SST and AMO. This shows that a large portion of tuna variation in the Eastern and Southern Pacific is related to environmental conditions. Models with single variables are evidence of the significant individual effect of SST and AMO on stock time series of each tuna species. Models with two variables had a better fit in comparison to models with a single variable for all tuna stocks. Possibilities of two significantly different patterns in the trajectory of the three tuna species and environmental conditions used in the models were also observed. The trajectory patterns seemed to change around the 1990s and had significantly different means, indicating possible regime shifts. Environmental conditions play a highly significant role in structuring tuna stock trajectory in the South Pacific and need to be included in tuna management / harvest plans to ensure sustainability of this important resource. The importance of regime shifts should be recognised and further investigated for possible inclusion in tuna sustainability plans due to their influence on long-term tuna trajectory patterns.

Bigeye tuna (BET) and yellowfin tuna (YFT) are economically important target species of pelagic fisheries worldwide, especially for tropical Pacific nations whose economies and food sources are heavily affected by commercial and sustenance tuna fishing. The El Niño‐Southern Oscillation (ENSO) has a strong effect on the oceanographic conditions in the equatorial Pacific, including BET and YFT equatorial habitat and fishing grounds. For optimal fisheries management, the effects of environmental variability such as ENSO on the stocks and on the performance of fisheries must be known and predictable. However, besides some model predictions, the effects of ENSO on these two tuna species are not well understood. In this study, I investigate the statistical relationships between past ENSO conditions and equatorial fisheries using the Multivariate ENSO Index, sea surface temperature (SST), and catch and effort records from the longline fisheries in the region. Results of this study indicate that El Niño events have both delayed and concurrent positive effects on BET and YFT catch per unit effort (CPUE). The delayed positive ENSO effect on CPUE is hypothesized to be the result of enhanced recruitment acting via different mechanisms in the west than in the east. The concurrent positive effects on CPUE could be due to catchability, abundance, and/or vertical distribution of BET and YFT relative to fishing gear and require further investigation. Further exploration of the mechanisms that may underlie the results presented here could lead to predictability of CPUE of these two tuna species. [ABSTRACT FROM AUTHOR]

To understand the effects of the machine learning models and the spatial resolutions on the prediction accuracy of bigeye tuna (Thunnus obesus) fishing grounds, logbook data of 13 Chinese longliners operating in the high seas of the Atlantic Ocean from 2016 to 2019 were collected. The environmental factors were selected based on the correlation analysis of calculation of catch per unit effort (CPUE) and the marine vertical environmental factors. Five machine learning models: random forest, gradient‐boosting decision tree, K‐nearest neighbor, logistic regression and stacking ensemble learning (STK) within four spatial resolutions of.5° ×.5°, 1° × 1°, 2° × 2° and 5° × 5° grids were constructed and compared. Results showed that (1) the prediction performance of STK model was the best, with the highest scores of the four evaluation indexes, accuracy (Acc), precision (P), recall (R), and F1‐score (F1), and the highest correct prediction rate for predicting "high CPUE fishing ground"; (2) models within the spatial resolution of 1° × 1° grids predicted the better results compared with.5° ×.5°, 2° × 2° and 5° × 5° grids; (3) the vertical environmental factors selected based on the correlation analysis could be used as reliable predictors in the models. Results suggested that using STK within 1° × 1° grids could improve the generalization performance and prediction accuracy for predicting the bigeye tuna fishing grounds in the Atlantic Ocean. [ABSTRACT FROM AUTHOR]

The Tongan fisheries targeting the species of albacore (Thunnus alalunga), bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis), and yellowfin tuna (Thunnus albacares), comprising the main tuna catch landed, within the EEZ of Tonga is critical to the economy of Tonga. Thus, it is crucial to study the spatiotemporal pattern of their catch and the influence of environmental and physical variables, in addition to the month and year of the catch. To this end, sets of eight generalized additive models were applied to model the distribution of these four species. Selection among competing models was carried out based on k-fold cross-validation, using RMSPE prediction error as a measure of model predictive performance. The following sets of predictors were considered; sea surface temperature, sea surface chlorophyll, bottom depth, month, and year. In addition, to assess the influence of fronts, gradients in SST and Chl-a were computed and used as predictors. Catch year was the most important variable for all, except Albacore tuna, for which month was the important variable. The third most important variable was SST for albacore and bigeye tuna, whereas bottom depth was the most important variable for skipjack and yellowfin tuna. A standardized index of CPUE indicates mostly inter-annual variation in CPUE for albacore and bigeye tuna, whereas a it indicates a general increase in CPUE for skipjack and yellowfin tuna. Hotspots of albacore tuna catches are around the northern and southern edges of the exclusive economic zone and typically during the months of June to August. The bigeye tuna hotspots were concentrated on the eastern side of the islands, in waters overlying trenches; this was most obvious during the months of January to June. Skipjack tuna hotspots were near the edges of the exclusive economic zone, although it is caught in smaller amounts to the three tuna species considered and higher catch rates were observed only after 2014. For yellowfin tuna, the highest catch rates were concentrated around the islands and descending towards the southern edge of the EEZ. As part of the initiative of this study to support national optimal resource management, this study generated standardized CPUE (indices of abundance), an important input in stock assessment, and also looked into the potential influence of environmental and physical variables on the CPUE of these valuable tuna stocks within the EEZ of Tonga. [ABSTRACT FROM AUTHOR]

To limit climate warming to 2°C above preindustrial levels, most economic sectors will need a rapid transformation toward a net zero emission of CO2. Tuna fisheries is a key food production sector that burns fossil fuel to operate but also reduces the deadfall of large‐bodied fish so the capacity of this natural carbon pump to deep sea. Yet, the carbon balance of tuna populations, so the net difference between CO2 emission due to industrial exploitation and CO2 sequestration by fish deadfall after natural mortality, is still unknown. Here, by considering the dynamics of two main contrasting tuna species (Katsuwonus pelamis and Thunnus obesus) across the Pacific since the 1980s, we show that most tuna populations became CO2 sources instead of remaining natural sinks. Without considering the supply chain, the main factors associated with this shift are exploitation rate, transshipment intensity, fuel consumption, and climate change. Our study urges for a better global ocean stewardship, by curbing subsidies and limiting transshipment in remote international waters, to quickly rebuild most pelagic fish stocks above their target management reference points and reactivate a neglected carbon pump toward the deep sea as an additional Nature Climate Solution in our portfolio. Even if this potential carbon sequestration by surface unit may appear low compared to that of coastal ecosystems or tropical forests, the ocean covers a vast area and the sinking biomass of dead vertebrates can sequester carbon for around 1000 years in the deep sea. We also highlight the multiple co‐benefits and trade‐offs from engaging the industrial fisheries sector with carbon neutrality. [ABSTRACT FROM AUTHOR]

Age-based stock assessment of globally important species, like bigeye tuna Thunnus obesus (Lowe, 1839), is urgently required to develop appropriate management plans for fisheries sustainability. This study aimed to estimate age and growth parameters using annual increments count of sectioned-otoliths, which effectively employed for age determination of tunas. Samples were collected from Indonesian tuna longline catch landed in the Port of Benoa from March until December 2017. Multi-models were employed to obtain robust growth parameters, and Akaike Information Criterion (AIC) was relied for the best fit model selection among those evaluated. Growth band formation was validated using marginal analysis (MI), indicating that one ring is deposited yearly and slow growth peaked during July (Australian winter). The von Bertalanffy growth model was selected as the best model fitting growth parameters from raw age data, as expressed as Lt = 183.49 (1-e-0.134(t+2.991)). Large variances in growth were detected at the same age, with the oldest age of 15. Over 50% of fish in the Indonesian catch were <5 years old, that may have implications for fisheries sustainability. [ABSTRACT FROM AUTHOR]

Bigeye tuna (Thunnus obesus), a kind of delicious seafood, can be processed to be several valuable products. To maintain the product quality, harvested tunas had been strictly persevered, transported and frozen at low temperature. This study was carried out to determine the technological mode of the freezing process of the fillet tuna to find the optimum temperature and freezing time to reduce mass loss and keep its quality. The combining twolevel orthogonal arrays was used to build the relationship between objective functions and income variables. The results found the optimized freezing mode of the fillet tuna: the freezing environment temperature was -42.5oC and the freezing time was 2.12h. Carrying out the experiment with optimized freezing mode, showed that the temperature at the end of the fillet tuna freezing process was reached at -22.5oC and the yield of weight loss was is 3.1%. That meaned all internal water of the product was completely crystallized and the loss of quality was negligible. The freezing mode can be applied in industrial scale for the frozen fillet tuna manufacturing process. [ABSTRACT FROM AUTHOR]

The distribution of marine species is changing as a direct result of climate change. Large pelagic highly migratory species (HMS), like tunas, billfishes, and sharks, are particularly sensitive to environmental change due to their migratory nature and use of large‐scale ocean features. These temporal and spatial shifts are likely reflected in the Atlantic HMS recreational fishery and could have downstream effects on coastal communities. We utilized dockside intercept data from the Large Pelagics Survey (LPS) from 2002 to 2019, which conducts sampling from June to October and spans Maine to Virginia, USA. We assessed how species catch composition has changed and developed spatiotemporal models to understand latitudinal and temporal shifts in the recreational catch of 12 HMS groups. Latitudinal shifts were significantly affected by Northeast Shelf SST for 11 of the 12 HMS groups and ranged from 3 ± 1 km°C−1 for the large bluefin tuna to 40 ± 1 km°C−1 for the blue shark. In addition, the estimated day of the year when the first 25% of bigeye tuna intercepts occurred, happened over 50 days earlier in 2019 compared to 2002, suggesting the initial catch is happening earlier in recent years. These results suggest that changes in species distribution and phenology are affecting where and when HMS recreational catch occurs. Understanding these shifts would allow managers to be more responsive and flexible and also help communities prepare for changes, whether it would be a switch to a new species or shifts in the fishing season. [ABSTRACT FROM AUTHOR]

The potential impacts of climate change on the distribution of tuna in Pacific Island countries' exclusive economic zones have yet to be investigated rigorously and so their persistence and abundance in these areas remain uncertain. Here, we estimate optimal fisheries areas for four tuna species: albacore (Thunnus alalunga), bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis), and yellowfin (Thunnus albacares). We consider different climate change scenarios, RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5, within a set of tuna catch records in the exclusive economic zone of Tonga. Using environmental and CPUE datasets, species distribution modelling estimated and predicted these fisheries areas in the current and future climatic scenarios. Our projections indicate an expansion in area and a shift of productive areas to the southern part of this exclusive economic zone of Tonga. This is an indication that future climatic scenarios might be suitable for the species under study; however, changes in trophic layers, ocean currents, and ocean chemistry might alter this finding. The information provided here will be relevant in planning future national actions towards the proper management of these species. [ABSTRACT FROM AUTHOR]

The genus Thunnus (family Scombridae) comprises eight species of tunas of which all but one are targeted by industrialized fisheries. Although intact individuals of these species can be distinguished by morphological characteristics, researchers and managers often rely on dressed, frozen, juvenile or larval fish samples, which often necessitates the identification of molecular species. Here the authors investigate short amplicon (SA) and unlabelled probe high‐resolution melting analysis (UP‐HRMA) as a low‐cost, high‐throughput molecular genotyping assay capable of distinguishing between albacore tuna (Thunnus alalunga), blackfin tuna (Thunnus atlanticus), bigeye tuna (Thunnus obesus), Atlantic bluefin tuna (Thunnus thynnus) and yellowfin tuna (Thunnus albacares) in the Gulf of Mexico. Although SA‐HRMA of variable regions in the NADH dehydrogenase subunit 4 (ND4) and subunit 5 (ND5), and subunit 6 (ND6) of the mtDNA genome did yield some species‐specific diagnostic melting curves (e.g., ND4 assay can reliably distinguish Atlantic bluefin tuna), genotype masking produced excessive variation in melting curves for reliable multi‐species identification. To minimize the genotyping masking of SA‐HRMA a 26 base pair long UP containing four SNPs was developed within a 133 bp segment of ND4. The UP‐HRMA is able to reliably distinguish Gulf of Mexico species T. thynnus, T. obesus, T. albacares and T. atlanticus by UP melting temperature at 67, 62, 59 and 57°C, respectively. The developed UP‐HRMA assay is a lower‐cost, higher‐throughput, alternative to previously published molecular assays for tuna identification that can be easily automated for large data sets, including ichthyological larval surveys, fisheries specimens lacking distinguishing morphological characteristics or detection of fraudulent trading of tuna species. [ABSTRACT FROM AUTHOR]

Sample cross-contamination remains a pervasive issue in genetics and genomics. With growing reliance on molecular methods for managing marine resources, the need to ensure the integrity of tissue samples that underpin these methods has never been more pressing. We conducted an experiment on wild-caught bigeye tuna (Thunnus obesus) to assess cross-contamination risk under seven at-sea and laboratory-based tissue sampling treatments. The six at-sea treatments (T1–T6) differ in sampling equipment, cleaning, and storage procedures. Combining observed heterozygosity (H o) and relatedness coefficients (r) to flag cross-contamination, treatments T2–T6 proved effective at mitigating contamination risk. Each exhibited significantly smaller mean H o and less H o variability compared with intentionally contaminated samples in the T1 treatment. In T2-T6, no samples flagged as contaminated based on H o outlier thresholds and elevated r were traced to the point of sampling at sea. Laboratory-based subsampling of T1 tissue (T7) also led to significantly smaller, less variable H o values compared to T1, suggesting that recovery of samples contaminated onboard, or those of unknown provenance, is possible. We show that simple adjustments to current tissue sampling protocols dramatically reduce cross-contamination risk for downstream genetic analyses on tunas and potentially on other species and fisheries. [ABSTRACT FROM AUTHOR]

Bigeye tuna (Thunnus obesus) is economically vital in the Indian Ocean, targeted extensively for commercial fishing. Research using a blend of quantitative and qualitative Indian Ocean Tuna Commission (IOTC) data from 1950 to 2021 uncovered insights. Around 35 countries participated in Indian Ocean bigeye tuna fishing, annually yielding 21 to 162,220 t over the study period. Yet, since 1999, catches dwindled, dipping below 100,000 t from 2014 to 2021. The highest quantity of bigeye tuna captured in the Indian Ocean during this period was by longliners under the flag of Taiwan, Province of China, accounting for 24.08% of the total catch. Thailand's catch, by contrast, accounted for 14,676 t (0.30%) and came from purse seines and longlines. The Western Indian Ocean was the primary fishing ground for bigeye tuna, followed by the Eastern Indian Ocean. However, the stock of bigeye tuna is currently overfished and subject to overfishing, with 2021 catches amounting to 95,400 t, representing a 5% increase from 2020. To address this issue, an allocation based on the catch during 2012-2016 was recommended for Contracting Parties and Cooperating Non-Contracting Parties. A conceptual model has been created to ensure bigeye tuna sustainability through four processes: apply management regulations, recommend total allocation catch (TAC) for 2024-2025, control actual catch, and revisit/readjust TAC if needed. The model promotes long-term sustainability. To ensure compliance with IOTC Conservation and Management Measures for bigeye tuna, Thailand must align national law with the IOTC Resolution, notably Royal Ordinance on Fisheries B.E. 2558 (2015) and its B.E. 2560 (2017) amendment. This legal synchronization is crucial, especially for quota transfers and chartering. [ABSTRACT FROM AUTHOR]

Mitigating bycatch of non-target fish species is a common objective in fisheries management that may be supported by the gathering of data from fishery observer programs and quantitative analysis of bycatch risk factors. We build three GLM models based on Chinese tuna longline fishery observer data in terms of analysis of total bycatch rate (TB rate), total bycatch ratio (TB ratio), and species-specific bycatch rate, respectively. The positive log-linear models assumed a Gaussian observation error model and a linear combination of categorical independent variables, including area, year, month, depth, and bycatch species. Results show that distributions of TB rate and TB ratio followed different trends and a latitudinal decrease was observed from both the northern and southern hemisphere of the equator. Comprehensively, the Pacific is a better place to fish compared to the Indian and Atlantic Oceans in terms of relatively lower TB rate and TB ratio. Fishing in open oceans can somehow avoid a high TB ratio than fishing in coastal waters. As a result, we recommend area 2SW, 2SE, 2 NW, 14SW, 14SE, and 14 NW as appropriate fishing ground for Albacore (Thunnus alalunga) while area 11N,  11S, 18SW, and 18SE to be appropriate fishing ground for fishing bigeye tuna (Thunnus obesus). Setting fishing gears deeper than 500 m would also help to get a low TB rate and TB ratio. [ABSTRACT FROM AUTHOR]

Bioaccumulation is the process by which living organisms accumulate substances, such as pesticides, heavy metals, and other pollutants, from their environment. These substances can accumulate in the organism's tissues over time, leading to potential health risks. Bioaccumulation can occur in both aquatic and terrestrial ecosystems, and can have a significant impact on the health of both humans and wildlife. The objective of this study is to find out if the concentrations of metals in the tuna species of the Canary Islands are suitable for human consumption and if they pose a health risk. Fifteen samples of Acanthocybium solandri, Katsuwonus pelamis, Thunnus albacares, Thunnus obesus and Thunnus thynnus present in canaries were analyzed. Ten grams of muscle were taken from each specimen and the metals Al, Cd, Cr, Cu, Fe, Li, Ni, Pb and Zn were determined by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The tuna species that presented more metals with a higher concentration compared to the others was T. thynnus, reaching up to 100 times more than the other studied species in Fe content with 137.8 ± 100.9 mg/Kg, which may be due to the fact that it is the largest species that reaches ages of more than fifteen years. The species Thunnus thynnus should not be suitable for commercialization according to the current legislation on the concentrations of Cd in blue fish, since 75% of the specimens studied exceeded the concentration legislated for Cd. A total of 40% of the studied specimens of this this species exceeded the legislated values for the concentration of Pb in oily fish meat, so this species must be monitored to ensure that it does not pose a risk to human health. [ABSTRACT FROM AUTHOR]

Subseasonal to decadal ocean forecasting can make significant contributions to achieving effective management of living marine resources in a changing ocean. Most applications rely on indirect proxies, however, often measured at the ocean surface and lacking a direct mechanistic link to the dynamics of marine populations.Here, we take advantage of three‐dimensional, dynamical reconstructions and forecasts of ocean biogeochemistry based on a global Earth system model to hindcast and assess the capacity to anticipate fluctuations in the dynamics of bigeye tuna (Thunnus obesus Lowe) in the Pacific Ocean during the last six decades. We reconstructed spatial patterns in catch per unit effort (CPUE) through the combination of physiological indices capturing both habitat preferences and physiological tolerance limits in bigeye tuna.Our analyses revealed a sequence of four distinct regimes characterized by changes in the zonal distribution and average CPUE of bigeye tuna in the Pacific Ocean. Habitat models accounting for basin‐wide fluctuations in the thermal structure and oxygen concentration throughout the water column captured interannual fluctuations in CPUE and regime switches that models based solely on surface information were unable to reproduce. Decade‐long forecast experiments further suggested that forecasts of three‐dimensional biogeochemical information might enable anticipation of fluctuations in bigeye tuna several years ahead.Synthesis and applications. Together, our results reveal the impact of variability of biogeochemical conditions in the ocean interior on the dynamics of bigeye tuna on the Pacific Ocean, raising concerns about the future impact of ocean warming and deoxygenation. The results also lend support to incorporating subsurface biogeochemical information into ecological forecasts to implement efficient dynamic management strategies and promote the sustainable use of marine living resources. [ABSTRACT FROM AUTHOR]

Oceanic temperature fluctuations are one of the leading factors affecting marine fish populations. Indian Ocean Dipole (IOD), characterized as the sea surface temperature (SST) anomaly change, is an ocean–atmosphere interactive process causing interannual climate variability in the Indian Ocean. Influences of the IOD on the tuna catch rates are supported by previous research. Yet, there remains limited information about the impacts on the abundance of tuna stocks. In this study, we used the standardized Catch Per Unit Effort (CPUE) index to present the stock abundance and compared the effects of the IOD on the bigeye tuna (Thunnus obesus) and yellowfin tuna (Thunnus albacares) among different management areas of the Indian Ocean Tuna Commission (IOTC). Results show significant correlations between IOD events on both species' abundance in the tropical western Indian Ocean. However, in the tropical eastern Indian Ocean and the southern Indian Ocean, neither bigeye nor yellowfin tuna abundances were significantly correlated by the IOD. For the whole Indian Ocean, IOD was significantly correlated uniquely with the yellowfin tuna abundance. Our results emphasized the importance of evaluating the climate variability effects over fisheries abundance species by species and per fishing areas analyses. [ABSTRACT FROM AUTHOR]

A recent Atlantic-wide tag-recapture experiment run by the International Commission for the Conservation of Atlantic Tunas was an opportunity to directly validate otolith increment deposition rates for bigeye tuna (Thunnus obesus) and yellowfin tuna (T. albacares) in the region. Age and time at liberty were estimated by using annual and daily increment counts for sectioned otoliths from sampled fish previously injected with oxytetracycline and later recaptured. The use of annual increment counts resulted in greater age estimates than those from daily increment counts for fish >55 cm straight fork length (SFL). Use of daily increment counts led to underestimation of time at liberty for fish >55 cm SFL at recovery, compared with known times at liberty. In contrast, predictions based on annual increment counts are accurate across the entire size range of sampled fish, validating the notion that increments are deposited annually. We therefore recommend that counting annual increments be the preferred method for aging yellowfin and bigeye tuna from the Atlantic Ocean and that the use of daily increments for aging be limited to young of the year. Aging fish accurately is important for stock assessments in which data on age and growth play an increasingly essential role in examining population dynamics. It is crucial that otolith reading practices and analyses based on age data reflect the most up-to-date recommendations for age estimation. [ABSTRACT FROM AUTHOR]

This study analyses the mercury (Hg) concentration in the meat of Thunnus albacares and Thunnus obesus caught from the western equatorial Atlantic Ocean. The objective was to estimate the Hg intake via tuna ingestion and presents the possible health risk assessment. For T. albacares and T. obesus, the median concentration was 212 ng·g-1 and 475.1 ng·g-1 wet weight, respectively. The Hg concentrations were below the maximum tolerable limit established by international and Brazilian regulations for fishery products. The consumption would pose a risk for human populations that ingest more than 80 g·day-1. Regular monitoring of both human consumption rates and Hg levels in fish are recommended. [ABSTRACT FROM AUTHOR]

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Indices of relative abundance directly inform how population abundance changes over time, providing one of the most important pieces of information for a stock assessment. Ideally, indices of abundance should be calculated based on fishery-independent survey data. Survey data are characterized by a spatially random or fixed sampling design, and consistent employment of the same fishing gear and fishing operation across time. However, the unavailability of survey data for most tuna species means that the derivation of abundance indices for these species comes solely from fishery-dependent catch-per-unit-effort (CPUE). We conduct two simulation experiments, based on real fishery-dependent longline data, to quantitatively evaluate the impacts of reduced fishing effort on the standardized longline CPUE for bigeye tuna in the eastern Pacific Ocean. The key findings of the two simulation experiments are 1) a reduced spatial coverage of CPUE data leads to increased bias in the abundance index; 2) the index bias has a minor long-term trend if the reduced spatial coverage of CPUE data is not caused by local depletion; and 3) that bias has a positive long-term trend (i.e., hyper-stable abundance index) if the reduced spatial coverage of CPUE data co-occurs with a local depletion in the abandoned area. This bias, however, can be significantly reduced if the CPUE standardization model includes a temporal correlation structure in spatiotemporal random fields. In addition, the CPUE standardization model provides more realistic estimates of the coefficient of variation of fish abundance when its spatiotemporal random fields are assumed to be correlated in time. This study underscores the necessity of accounting for the temporal correlation structure in spatiotemporal random fields in cases where local depletion and depletion-driven fishery contraction co-occur. [ABSTRACT FROM AUTHOR]

The influence of bait type and leader material on target and bycatch species was assessed through fishing experiments in the Portuguese shallow pelagic longline fishery in the Atlantic Ocean. Wire leaders were found to decrease catch rates of commercially valuable species such as bigeye tuna and yellowfin tuna, while increasing catch rates of elasmobranchs, including the blue shark and shortfin mako. The odds ratios of capture swordfish and tunas also decrease when using wire leaders, while elasmobranchs have higher odds ratios of capture and at-haulback mortality when using wire leaders. Squid bait led to higher catches of targeted tuna species, however it also resulted in higher catches of marine turtles. For most of the taxa caught at-haulback mortality risk was found to be higher on squid bait, which may be related with increased deep-hooking events. While bait type and leader material did not significantly affect size selectivity for most species, wire leaders were found to retain larger blue sharks and fish bait attracted smaller-sized swordfish. This study showed that banning wire leaders on pelagic longline fisheries is an effective measure for reducing the retention of pelagic shark species, particularly of large size blue sharks. • Wire leaders led to reduced catch rates of tuna species. The odds of capturing swordfish were also lower with wire leaders. • Wire leaders increased catch rates of elasmobranchs, including the blue shark and shortfin mako. • This study supports the exclusion of wire leaders in pelagic longline fisheries to reduce retention of pelagic shark species. • Squid bait increased tuna catches but resulted in higher marine turtle catches and higher risk of at-haulback mortality. [ABSTRACT FROM AUTHOR]

Food fraud is common in the tuna industry because of the economic benefits involved. Ensuring the authenticity of tuna species is crucial for protecting both consumers and tuna stocks. In this study, GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry-based metabolomics were used to investigate the metabolite profiles of three commercial tuna species (skipjack tuna, bigeye tuna and yellowfin tuna). A total of 22 and 77 metabolites were identified with high confidence using GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry, respectively. Further screening via chemometrics revealed that 38 metabolites could potentially serve as potential biomarkers. Hierarchical cluster analysis showed that the screened metabolite biomarkers successfully distinguished the three tested tuna species. Furthermore, a total of 27 metabolic pathways were identified through enrichment analysis based on the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways. [ABSTRACT FROM AUTHOR]

In response to concerns about the stock status of bigeye tuna (BET) in the Eastern Pacific Ocean, the Inter-American Tropical Tuna Commission adopted additional management measures for BET in 2021, including an individual-vessel catch threshold system for the purse-seine fishery. Development of an enhanced port-sampling program for estimation of trip-level BET catch was also mandated to support member countries and their purse-seine vessels in their conservation efforts. To this end, a pilot study was conducted in the ports of Manta and Posorja, Ecuador, in 2022. In these ports, well unloading often takes place with small containers, which are used to transport fish from inside the well to the vessel's wet deck. Using a high-frequency systematic sampling protocol, 63 wells of 37 trips with catch exclusively from floating-object (OBJ) sets were sampled from the start to the end of unloading, at a fixed interval from a random starting point, sampling about 10 % of all the containers of fish unloaded from each well. Notable large-scale pattern in the proportion of BET per container was found for 38 of the 56 wells that had BET catch. The proportion of BET per container, which could be high at the beginning, middle or end of the well unloading, sometimes varied by 0.40 or more. The magnitude of this large-scale within-well pattern had a significant increasing relationship with the number of OBJ sets associated with the well catch, consistent with variability in species composition among OBJ sets being an important factor in determining variability in species composition during catch unloading. Simulation studies demonstrated that such large-scale within-well pattern has potential implications for OBJ-set well-level sampling design, where, as expected from sampling theory, a systematic sampling protocol for containers of fish generally resulted in lower mean squared error (MSE) on the proportion of BET in the well, compared to simple random sampling of containers of fish. The reduction in MSE was largely due to a reduction in variance. Simulations also showed that the within-well variance component of the trip-level estimator for the proportion of BET can be larger than the among-well variance component, unless the within-well sampling coverage is relatively high. To minimize the negative impact of within-well variability on the precision of the estimator, results indicate that for a sampling protocol with one systematic sample per well, the within-well coverage should be at least 2 % of containers of fish unloaded from the well, and preferably more than 3 %. Finally, simulation studies were conducted with observer well plan data from 2013 to 2022 to put the well-level results in a larger context. Results indicated that the level of within-well sampling coverage may affect the variance on fleet-level estimates of the proportion of BET in the catch, with potentially substantially higher variance when the within-well sampling coverage is low. Taken together, these results suggest that both the type of within-well sampling and the level of within-well sampling coverage have important implications for the variance on BET catch estimates, from the well level to the fleet level. [ABSTRACT FROM AUTHOR]

It is challenging in fisheries stock assessment to estimate cohort dynamics from length‐based data for hard‐to‐age stocks, and existing approaches, for example, age‐structured catch‐at‐length models (ACL) are unable to account for length‐dependent processes within each cohort. Fisheries‐dependent data are usually considered the default input to stock assessment models. However, with widespread recognition of the uncertainty of fisheries‐dependent data and the increasing availability of high‐quality survey data, a new situation emerges in some fisheries where a stock assessment model based only on survey data can provide good estimation of population dynamics. We develop an age‐ and length‐structured statistical catch‐at‐length model (ALSCL) to estimate age‐based dynamics from survey catch‐at‐length data. This approach also provides a good basis to then integrate fisheries‐dependent data in the model. ALSCL can explicitly include length‐dependent mortality and growth within each cohort by simultaneously tracking the three‐dimensional dynamics across time, age, and length. We first use simulations of yellowtail flounder (Limanda ferruginea, Pleuronectidae) and bigeye tuna (Thunnus Obesus, Scombridae) to demonstrate that ALSCL outperforms ACL by providing more accurate estimates of age‐based population dynamics when length‐dependent processes are important. Next, we apply ALSCL to estimate the cohort dynamics of female yellowtail flounder on the Grand Bank off Newfoundland using survey catch‐at‐length, weight‐at‐length, and maturity‐at‐length data. We consider ALSCL as a hybrid between ACL and length‐structured stock assessment models that keeps the advantages of both, and its ability to simultaneously track age and length dynamics is an important step toward the next‐generation of fisheries stock assessment models. [ABSTRACT FROM AUTHOR]

Sushi and sashimi are seafood products that are widely consumed worldwide, including China. Currently, they are also sold through alternative channels such as e-commerce. In this study, 60 Japanese Seafood Products (JSPs) suitable for sushi and sashimi preparations (fish meat or roe) were purchased on Chinese e-commerce and analyzed. Initially, the trade name accuracy and the labeling compliance with the Chinese standard for pre-packaged food were evaluated. Then, the species composition of the JSPs was assessed by the molecular analysis of two genetic targets (COI and cytb). Finally, the results of the molecular analysis were compared with the trade name reported on the label, and the mismatching rate (MR) was calculated. None of the JSPs labels reported the scientific name of the species. Sixteen different trade names were found, of which only 37.5% could be assigned to a taxonomic level (species or genus). In the other cases, umbrella terms were used. Overall, 66.7% of the JSPs were fully compliant with the Chinese standard. Eighty-seven percent of the JSPs were molecularly authenticated to the species level. Overall, an MR of 11.7% was observed. The mismatched JSPs were labelled as "Snapper", "Herring roe" and "Bigeye tuna". The use of umbrella trade names can facilitate the placing on the market of species involved in traceability, economic and sustainability issues. Indeed, some of the recovered species were listed in the IUCN Red List of Threatened Species. DNA analysis was once again proved as an efficient tool to unmask and fight seafood frauds. • The label of 60 Japanese Seafood Products purchased on e-commerce was analyzed. • The species composition of the JSPs was assessed by a DNA analysis. • An overall mismatching rate of 11.7% was observed. • Some of the recovered species were listed in the IUCN Red List. • Umbrella trade name and its implications on traceability and sustainability were discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] • Peptides of 45 tuna samples and 15 processed real samples of 3 types were detected. • Venn analysis showed the peptides of three tuna species were quite different. • The screened peptide biomarkers were effective in discriminating three tuna species. The risk of tuna adulteration is high driven by economic benefits. The authenticity of tuna is required to protect both consumers and tuna stocks. Given this, the study is designed to identify species-specific peptides for distinguishing three commercial tropical tuna species. The peptides derived from trypsin digestion were separated and detected using ultrahigh-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF/MS) in data-dependent acquisition (DDA) mode. Venn analysis showed that there were differences in peptide composition among the three tested tuna species. The biological specificity screening through the National Center for Biotechnology Information's Basic Local Alignment Search Tool (NCBI BLAST) revealed that 93 peptides could serve as potential species-specific peptides. Finally, the detection specificity of species-specific peptides of raw meats and processed products was carried out by multiple reaction monitoring (MRM) mode based on a Q-Trap mass spectrometer. The results showed that three, one and two peptides of Katsuwonus pelamis , Thunnus obesus and Thunnus albacores , respectively could serve as species-specific peptides. [ABSTRACT FROM AUTHOR]

The dynamic of marine environmental parameters affects the distribution of commercial tuna in the sea of the maritime continent. Hence, the objectives of this study are to develop spatial distribution models for the four main tuna species in the Maritime continent's sea with reasonable accuracy, identify their correlation with marine environmental parameters, and investigate areas of interaction between those tuna species. The study develops the distribution models for albacore (Thunnus alalunga), bigeye (Thunnus obesus), yellowfin (Thunnus albacares), and skipjack (Katsuwonus pelamis) tuna species, utilizing multi-sensor satellite remote sensing and maximum entropy. The results show models have good performance, focusing on environmental factors such as sea surface temperature (SST), chlorophyll-a (CHL), and sea surface height anomalies (SSHA), combined with eddy kinetic energy (EKE). Seasonal variations in potential tuna habitats are revealed, emphasizing the influence of those marine environmental conditions. From December to May, the four commercial tuna species were distributed in conditions characterized by SST of 26–31.5 °C, CHL levels of 0–3 mg/l, SSHA of −0.3 to 0.2 m, and EKE of 0–1 m2/s2, while from June to November, they experienced SST of 23–31 °C, CHL levels of 0–4 mg/l, SSHA of −0.5 to 0.3 m, and EKE of 0–1.1 m2/s2. The spatial persistence of the four tuna species emerged mainly around the south sea of Java, with skipjack being the most common species found in the sea of the maritime continent. With sufficient and evenly distributed tuna presence records, the results indicate the potential for extrapolation beyond the training data to estimate habitat suitability for the four commercial tuna distributions. The results also suggest potential competition between tuna species sharing ecological niches and highlight possible overlapping areas where different tuna species interact with the same fishing gear. • The species distribution models for the four tuna species, which performed well, were developed. • Environmental factors affecting tuna distribution in the sea of the Maritime Continent: SST, CHL, SSHA, and EKE. • Seasonal variations for the distribution of the four tuna species were revealed with skipjack being the most common species. • Tuna species distributed mainly persisted in the southern Java Sea. • This study also reveals overlapping areas of tuna habitats and their interactions with the same fishing gear. [ABSTRACT FROM AUTHOR]

Shewanella putrefaciens can cause the spoilage of seafood and shorten its shelf life. In this study, both strains of S. putrefaciens (YZ08 and YZ-J) isolated from spoiled bigeye tuna were subjected to in-depth phenotypic and genotypic characterization to better understand their roles in seafood spoilage. The complete genome sequences of strains YZ08 and YZ-J were reported. Unique genes of the two S. putrefaciens strains were identified by pan-genomic analysis. In vitro experiments revealed that YZ08 and YZ-J could adapt to various environmental stresses, including cold-shock temperature, pH, NaCl, and nutrient stresses. YZ08 was better at adapting to NaCl stress, and its genome possessed more NaCl stress-related genes compared with the YZ-J strain. YZ-J was a higher biofilm and exopolysaccharide producer than YZ08 at 4 and 30 °C, while YZ08 showed greater motility and enhanced capacity for biogenic amine metabolism, trimethylamine metabolism, and sulfur metabolism compared with YZ-J at both temperatures. That YZ08 produced low biofilm and exopolysaccharide contents and displayed high motility may be associated with the presence of more a greater number of genes encoding chemotaxis-related proteins (cheX) and low expression of the bpfA operon. This study provided novel molecular targets for the development of new antiseptic antisepsis strategies. [ABSTRACT FROM AUTHOR]

SUMMARY: Effects of frozen storage temperature on the quality and oxidative stability of lightly salted tuna were investigated. The bright and vivid colour became totally brown after 4 weeks at −20 °C and 8 weeks at −30 °C, where the a*/b* value decreased from 1.35 to 0.38 and 0.58, respectively. Discoloration and lipid oxidation occurred concurrently in lightly salted tuna flesh, and it was speculated that the oxidation of oxymyoglobin to metmyoglobin exacerbated lipid oxidation and vice versa. Storage at −40 °C or lower temperatures effectively suppressed the discoloration and maintained the high water‐holding capacity and unique textural properties of lightly salted flesh. It was attributed to the reduction in the conformational changes and particularly hydrophobic interactions among proteins, protecting the myoglobin from oxidative damages during frozen storage. Considering the quality maintenance and energy savings, storage at −40 °C was appropriate for lightly salted tuna flesh. [ABSTRACT FROM AUTHOR]

Cookiecutter sharks are pelagic ectoparasites that feed on pieces of flesh from large marine animals. Knowledge on these sharks is still rather scant, with the few existing works successfully using bites found on prey to reveal ecological patterns. This study aims to identify cookiecutter shark bite patterns on pelagic fishes in aggregated schools to gain an understanding of the ecology of these sharks. Data were collected by accompanying landings and onboard in tuna fishing vessels in the western equatorial Atlantic Ocean off Brazil. A total of 138 bite wounds were found on the bigeye tuna (Thunnus obesus), common dolphinfish (Coryphaena hippurus), skipjack tuna (Katsuwonus pelamis), and yellowfin tuna (Thunnus albacares). The most bitten species were the bigeye and yellowfin tuna, together accounting for 85% of all bites. Our findings offer novel insights into ectoparasitic ecology between cookiecutter sharks and pelagic fishes, identifying three major patterns: (i) preference of the sharks for the ventral surface of pelagic fishes; (ii) plasticity in biting tactics, with both bottom-up and lateral attacks; and (iii) habitat-dependent bite incidence (larger sharks commonly bite the skipjack tuna in epipelagic zones, whereas smaller sharks predominantly bite the bigeye tuna in mesopelagic zones). These results contribute to narrowing the gaps in knowledge on the ecology of the elusive, dwarf cookiecutter sharks. Further studies are needed for a better understanding of how shark-pelagic fish interactions are affected by the fishing of aggregated schools. [ABSTRACT FROM AUTHOR]

The majority of fishery stocks in the world are data limited, which limits formal stock assessments. Identifying the impacts of input data on stock assessment is critical for improving stock assessment and developing precautionary management strategies. We compare catch advice obtained from applications of various data-limited methods (DLMs) with forecasted catch advice from existing data-rich stock assessment models for the Indian Ocean bigeye tuna (Thunnus obesus). Our goal was to evaluate the consistency of catch advice derived from data-rich methods and data-limited approaches when only a subset of data is available. The Stock Synthesis (SS) results were treated as benchmarks for comparison because they reflect the most comprehensive and best possible scientific information of the stock. This study indicated that although the DLMs examined appeared robust for the Indian Ocean bigeye tuna, the implied catch advice differed between data-limited approaches and the current assessment, due to different data inputs and model assumptions. Most DLMs tended to provide more optimistic catch advice compared with the SS, which was mostly influenced by historical catches, current abundance and depletion estimates, and natural mortality, but was less sensitive to life-history parameters (particularly those related to growth). This study highlights the utility of DLMs and their implications on catch advice for the management of tuna stocks. [ABSTRACT FROM AUTHOR]