Tuna Species Research Articles

Transcriptome characterization of gonadal sex differentiation in Pacific bluefin tuna, Thunnus orientalis (Temminck et Schlegel)

Tunas (genus Thunnus) are one of the most ecologically and commercially important fish worldwide. To establish a biological basis for reproduction in this globally essential species, we have recently studied crucial reproductive aspects of the Pacific bluefin tuna (T. orientalis; PBT), as a model of tuna species, based on our closed-cycle aquaculture technology. In this study, we clarified the global expression profile of the genes regulating gonadal sex differentiation in PBT, as this developmental process is vital to sexual reproduction. Based on the results of our comparative (RNA-sequencing) and temporal (qRT-PCR) transcriptome analyses using the updated genome dataset, we propose the molecular mechanisms of gonadal sex differentiation in PBT. In female gonads, foxl2 and cyp19a1a (coding aromatase) are expressed at the onset of sex differentiation. Active aromatase-mediated estrogen biosynthesis, which includes positive regulation of cyp19a1a expression by Foxl2, induces ovarian differentiation. By contrast, dmrt1 and gsdf are upregulated in differentiating male gonads lacking active estrogen synthesis. Dmrt1 and Gsdf would mainly promote testicular differentiation. Furthermore, androgen biosynthesis is upregulated in differentiating male gonad. Endogenous androgens may also be vital to testicular differentiation. This study provides the first comprehensive data clarifying the molecular basis for gonadal sex differentiation in tunas.

A fast and non-invasive imaging procedure to fight red tuna fraud

Recently, a food fraud regarding tuna samples has been detected in Europe. Some batches of tuna treated with illegal adulterants like vegetable extracts, including beetroot, were detected after several cases of food poisoning. This paper proposes a new fast and non-destructive technique based on smartphone imaging which contributes to the fight against tuna fraud. The color of different samples of three species of tuna (Thunnus thynnus, Thunnus albacares and Thunnus obesus) has been analyzed by a colorimetrically characterized smartphone. Descriptive analysis of the samples shows that different species of tuna can be grouped by their color in CIELAB space, and that samples adulterated with beetroot extracts can be detected by the proposed image processing procedure. A logistic regression model was implemented to distinguish between real and fraudulent samples, and its suitability checked by k-folding cross validation (n = 189), achieving a 0.59% false positive rate with a 10% false negative rate.

Estimation of Atlantic bonito (Sarda sarda) stock status in the Senegalese Exclusive Economic Zone (SEEZ) from the catch-based model (CMSY) and length-based bayesian estimation (LBB) method

Among the seven major small tuna species defined in the ICCAT priority list for future studies, Atlantic bonito (Sarda sarda) is the most heavily targeted by artisanal and industrial fisheries in many coastal areas. Considering this high pressure and the limits of previous studies on its status in some areas of the Atlantic Ocean, this study focused on assessing the Atlantic bonito stock mainly harvested by the artisanal fisheries in the Senegalese Exclusive Economic Zone (SEEZ) using two data-limited approaches (LBB and CMSY). These models used the recorded length composition, catch, and CPUE data for Atlantic bonito caught by various fishing gears to provide significant fisheries reference points to evaluate the stock status of this species. The LBB model indicated an Atlantic bonito healthy stock status with B/BMSY values ranging from 1.3 to 1.6 and B/B0 values varying from 0.47 to 0.61 of the main scenarios performed (BON_AFG_CL, BON_GN_Length, and BON_PS_Length). The results estimated by LBB are consistent with those obtained by CMSY. The CMSY model results demonstrate that the SEEZ Atlantic bonito stock is in a sound condition in the final year of the main scenarios analyzed (BON, BON-bt, BON-GN-bt, and BON-PS-bt) with sustainable relative stock biomass (B2018/BMSY= 1.13 to 1.3) and fishing pressure levels (F2018/FMSY= 0.52 to 1.43). However, the results of the two models show that longlines and sleeping nets negatively affect this species’ stock in this area, showing a slightly overfished and overfished stock status, respectively. The results of the scenarios formulated by these two fishing gears (BON_LL_Length, BON_SN_Length for LBB and BON-LL-bt, BON-SN-bt for CMSY) are below the reference values. LBB shows Lc/Lc_opt values ranging from 0.61 to 1, B/BMSY from 0.49 to 1, and B/B0 from 0.18 to 0.39. For CMSY, these two scenarios show a B/BMSY varying between 0.33 and 0.8.

Climate change to drive increasing overlap between Pacific tuna fisheries and emerging deep-sea mining industry

In ocean areas beyond national jurisdiction, various legal regimes and governance structures result in diffused responsibility and create challenges for management. Here we show those challenges are set to expand with climate change driving increasing overlap between eastern Pacific tuna fisheries and the emerging industry of deep-sea mining. Climate models suggest that tuna distributions will shift in the coming decades. Within the Clarion-Clipperton Zone of the Pacific Ocean, a region containing 1.1 million km2 of deep-sea mining exploration contracts, the total biomass for bigeye, skipjack, and yellowfin tuna species are forecasted to increase relative to today under two tested climate-change scenarios. Percentage increases are 10–11% for bigeye, 30–31% for skipjack, and 23% for yellowfin. The interactions between mining, fish populations, and climate change are complex and unknown. However, these projected increases in overlap indicate that the potential for conflict and resultant environmental and economic repercussions will be exacerbated in a climate-altered ocean. This has implications for the holistic and sustainable management of this area, with pathways suggested for closing these critical gaps.

Climate Change Potential Impacts on the Tuna Fisheries in the Exclusive Economic Zones of Tonga

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.

Seasonal Migration Zone of Skipjack Tuna (Katsuwonus pelamis) in the South Java Sea Using Multisensor Satellite Remote Sensing

Skipjack tuna (Katsuwonus pelamis) is the most dominating tuna species caught in the Indian Ocean. However, tuna fishermen in the Indian Ocean still face difficulties determining potential skipjack tuna fishing grounds due to limited geographic information. An attempt to improve information regarding potential skipjack tuna fishing grounds is through modeling the SST, SSC, SSH, and SSS oceanographic parameters with skipjack tuna distribution using GIS. The characteristics of the skipjack tuna habitat can be found through the generalized additive model (GAM) statistical analysis using data of skipjack tuna catch and oceanographic parameters from satellite imagery. The integrated GIS and GAM methods can improve the study of the habitat of skipjack tuna species. Therefore, this research is aimed at analyzing the condition and SST, SSC, SSH, and SSS variations in 2016-2021 in the South Java Sea; at predicting the correlation of SST, SSC, SSH, and SSS towards skipjack tuna catch in 2016-2021 in the South Java Sea using GAM; and at creating a map of skipjack tuna seasonal migration zones. The data included skipjack tuna catches, number of trips, and skipjack tuna fishing coordinates in 2016-2021 from PPS Cilacap and PPP Pondokdadap. The oceanographic parameter data in 2016-2021 was derived from Aqua MODIS level 3 (SST and SSC) and CMEMS (SSH and SSS) satellite imagery. The results showed that the average values of oceanographic parameters at skipjack tuna fishing ground coordinates in the South Java Sea (2016-2021) were SST (26.050-30.816°C), SSC (0.094-0.564 mg/m3), SSH (0.268-0.639 m), and SSS (33.075-34.514 psu). The best GAM modeling was the combination of four oceanographic parameter variables with an AIC value of 45357.92. Skipjack tuna in the South Java Sea migrates southeast during the west monsoon season to the first transitional season and tends to migrate northwest during the east monsoon season to the second transitional season.

Industrial fisheries have reversed the carbon sequestration by tuna carcasses into emissions.

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.

Role of environmental conditions in structuring the stock trajectory of Thunnus albacares, Th. alalunga and Th. obesus in the South Pacific Region

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.

Assessing the impact of growth on estimates of fishing mortality — An illustration with Indian Ocean bigeye tuna

Growth is a crucial biological feature and a key component in quantitative fish population stock assessments. Regional tuna fisheries management organizations have conducted extensive sampling programs to measure the growth of tuna species more accurately over the last decades. Although research improved growth estimates in most cases, competing or conflicting estimates of growth characteristics due to differences in sampling coverage, aging techniques, and modeling methodologies can introduce significant bias and uncertainty in the stock assessment. In the Indian Ocean, the recently determined growth curve for the bigeye tuna stock differs significantly from the length-at-age relationship now used in stock assessment. This study looked at how new growth affected estimation of fishing mortality for bigeye tuna caught with longline. Under steady-state assumption, the analytical method derives the fishing mortality and selectivity parameters from the longline length frequency dataset, conditioned on the growth and natural mortality factors. Simple simulations were used to validate the estimator’s performance. According to the estimates, the annual fishing mortality rates under the new growth curve will be 100%–200% higher than those under the current growth curve. The findings were also supported by an integrated Stock Synthesis model that was derived and simplified from the current bigeye tuna assessment model, as well as the length-based spawning potential ratio method, which used the same length frequency dataset as input. We emphasize that using a basic model to analyze the impact of alternative or competing growth scenarios on key management quantities can help decision makers easily understand the outcomes of more complex models, increasing the transparency of the stock assessment process.

Influence of El Niño‐Southern Oscillation on bigeye and yellowfin tuna longline catch per unit effort in the equatorial Pacific

AbstractBigeye 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.

Foraging patterns and trophic interactions of sympatric populations of young-of-the-year bluefin and skipjack tunas in the East Atlantic (Gulf of Cadiz)

Foraging patterns and trophic interactions of young-of-the-year Atlantic bluefin (Thunnus thynnus, ABFT) and skipjack (Katsuwonus pelamis, SKJ) tunas co-occurring in coastal waters off the Gulf of Cadiz (GoC, East Atlantic Ocean) were investigated using stomach content and stable isotope analyses. Both species fed primarily on epipelagic fishes such as European anchovy (Engraulis encrasicholus), sardine (Sardina pilchardus) and Atlantic chub mackerel (Scomber colias). In SKJ, a positive correlation was found between δ15N values of muscle and liver and straight fork length (SFL). Differences in liver δ15N values suggest that ABFT were recently foraging at higher trophic levels than SKJ. Isotopic niche areas estimated by standard ellipse areas (SEAC) and kernel utilization density (KUD) analyses showed a broader niche for SKJ compared to ABFT, indicating a more diverse diet in the former species. There was no significant niche overlap between both tuna species, suggesting trophic niche partitioning and reduced competition for the resources.

High throughput identification of tuna (Thunnus spp.) larvae in the Gulf of Mexico using unlabeled-probe high-resolution melting analysis (UP-HRMA).

The genus Thunnus (family Scombridae) comprises eight species of tunas of which all but one are targeted by industrialized fisheries. While 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 molecular species identification. Here we investigate short amplicon (SA) and unlabeled probe (UP) high-resolution melting analysis (HRMA) as a low-cost, high-throughput molecular genotyping assay capable of distinguishing between albacore tuna (T. alalunga), blackfin tuna (T. atlanticus), bigeye tuna (T. obesus), Atlantic bluefin tuna (T. thynnus), and yellowfin tuna (T. albacares) in the Gulf of Mexico. While SA-HRMA of variable regions in the NADH dehydrogenase subunit 4 (ND4) and subunit 5 (ND5), and subunit 6 (ND6) of the mitochondrial DNA (mtDNA) genome did yield some species-specific diagnostic melting curves (ex. 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°C, 62°C, 59°C, 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.

Automated Identification of Morphological Characteristics of Three Thunnus Species Based on Different Machine Learning Algorithms

Tuna are economically important fish species. The automated identification of tuna species is of importance in fishery production and resource assessment in that it would facilitate the informed monitoring of tuna fishing vessels and the establishment of electronic observer systems. As morphological characteristics are important for tuna identification, this study aims to verify the performance of the automated identification of three Thunnus species through morphological characteristics based on different machine learning algorithms. Firstly, morphological outlines were visually analyzed using EFT (elliptic Fourier transform) and CNN (convolutional neural network). Then, the EFT feature data and deep feature data of the tuna outline images were extracted, and principal component analysis of the two different morphological characteristics was performed. Finally, different machine learning algorithms were used to analyze the identification performance of tuna of the same genus and different species. The experimental results showed that EFT features had the highest identification accuracy in KNN (K-nearest neighbor), with 90% for T. obesus, 90% for T. albacores, and 85% for T. alalunga. Deep features had the best identification performance in SVM (support vector machine), with 80% for T. obesus, 90% for T. albacores, and 100% for T. alalunga. Deep features were better than EFT features in identification performance. The biodiversity and intergeneric differences among tuna species can be well analyzed using these two different morphological characteristics. Machine learning algorithms open up the way for rapid near-real-time electronic observer systems in these important international fisheries.

Risk Assessment and Characterization in Tuna Species of the Canary Islands According to Their Metal Content

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.

DNA metabarcoding to assess prey overlap between tuna and seabirds in the Eastern tropical Atlantic: Implications for an ecosystem-based management

Overfishing has been drastically changing food webs in marine ecosystems, and it is pivotal to quantify these changes at the ecosystem level. This is especially important for ecosystems with a high diversity of top predators such as the Eastern Atlantic marine region. In this work we used high-throughput sequencing methods to describe the diet of the two most abundant tuna species, the Skipjack tuna (Katsuwonus pelamis) and the Yellowfin tuna (Thunnus albacares), highly targeted by fisheries off west Africa. We also explored prey diversity overlap between these tuna species and the seabird species breeding in Cabo Verde that are most likely to share prey preferences and suffer from bycatch, the Brown booby (Sula leucogaster) and Cape Verde shearwater (Calonectris edwardsii). Overall, the diet of both tuna species was more diverse than that of seabirds. Skipjack tuna diet was dominated by prey from lower trophic levels, such as krill, anchovies, and siphonophores, while the Yellowfin tuna diet was mainly based on epipelagic fish such as flying and halfbeak fishes. Some of the most abundant prey families detected in the Yellowfin tuna diet were shared with both seabird species, resulting in a high prey diversity overlap between this tuna species and seabirds These results have implications for the management of tuna fisheries in the Eastern Tropical Atlantic, because a large decrease of both tuna species might have cascading effects on both primary and secondary consumer levels, and the decrease of these underwater predators may have implications on the viability of tropical seabird populations.

Automatic classification of the phenotype textures of three Thunnus species based on the machine learning SVM algorithm

Tuna resources are an important part of China's pelagic fishery production. However, for China's tuna fishery, tuna species caught at sea are still manually classified, which is a time-consuming and inefficient process; so China's tuna fishery needs to develop toward automation. This study uses gray-level co-occurrence matrix (GLCM) and VGG16 to visualize phenotypic texture through local images of three Thunnus species. At the same time, texture feature index data (TFD), deep feature data (DFD), and their combined feature data (CFD) are obtained from texture images. Support vector machine (SVM) with different kernel functions is used to classify phenotypic texture of tuna automatically. The study shows that visualized texture images of different tuna using GLCM and VGG16 have biological characteristics. In the classification results without cross-validation, the average classification accuracy of TFD in polynomial was 83%, the average classification accuracy of DFD in RBF (Radial basis function) was 93%, and the average classification accuracy of CFD in RBF was 95%. It is concluded that tuna phenotype texture can be efficiently classified by using SVM with different kernel functions.

What about the Arsenic? Health Risk Assessment in Canned Tuna Commercialized in Northern Spain

The incorrect labeling, as well as the bioaccumulation of heavy metals in seafood, represent a recurring problem worldwide, not only for natural resources but also for the consumers’ health. Heavy metals can be accumulated through the food chain and transferred to the final human consumer. Despite its toxicology, arsenic does not have a concentration limit on food, unlike other heavy metals like cadmium, mercury, and lead. Tuna species, with a worldwide distribution and high per capita consumption, represent a well-known toxicological issue caused by heavy metals. In this context, 80 samples of canned tuna were analyzed to check if the information contained in the label was correct and complete. Genetic identification was made by sequencing a fragment of 16S rDNA from 80 samples. For the heavy metal quantification, only those samples with the complete FAO fishing area information on the label were analyzed. Only 29 out of 80 samples presented enough information on the labels for the analysis. Some of the canned tuna commercialized in Spanish markets surpassed the safety standard levels established by the Joint FAO/WHO Expert Committee on Food Activities (JECFA) under the consumption rates of 300 g and 482 g per week. However, the carcinogenic risk (CRlim) for arsenic in all cans and all scenarios was higher than the safety levels.

Implications for the global tuna fishing industry of climate change-driven alterations in productivity and body sizes

Tunas and billfishes are the main large pelagic commercial fish species. Tunas comprised around 5.5 million tonnes and USD 40 billion in 2018. Climate change studies and projections estimate that overall, global fisheries productivity will decrease due to climate change. However, there are seldom projections of the climate-driven productivity of the higher trophic levels where tunas and billfishes belong. In this work, we use a mechanistic model to evaluate the effects of climate change and fishing for globally distributed and commercially exploited seven tuna species and swordfish which are divided into 30 stocks for management purposes, under a range of climate change (RCP 2.6 and 8.5) and fishing scenarios (from no fishing to 1.5 times the fishing mortality (F) at the Maximum Sustainable Yield, FMSY) from two Earth System Models (IPSL and MEDUSA). The results suggest that high trophic level species will be more impacted by climate change than by fishing pressure under the assumption that they remain nearby their MSY levels. However, no-fishing scenarios project much higher biomass. The overall productivity of the target species will decrease by 36% and only the Pacific bluefin showing a slight increase in the future. Five species; Atlantic and Southern bluefins, swordfish, bigeye, and albacore are estimated to decrease in biomass and size at different rates. These species represent almost a third of the landings in the Atlantic Ocean and 10% in the Pacific Ocean being the bluefins, the highest-valued tuna species. On average, the body size is expected to decrease up to 15% by 2050. Fish price and demand are partially driven by body size and therefore, revenues can be reduced even in stocks with an increase in productivity. The fishing industry can adapt to the changing climate by increasing the value of fish through sustainability certifications and reducing fuel consumption and time at sea with higher digitalization. Reducing fuel consumption would also be an additional mitigation measure to climate change since it would reduce CO2 emissions.

DNA sequencing shows that tropical tuna species misidentification can be an underestimated issue in fish landings

Taxonomic identification of food is a key component to the correct implementation of traceability pipelines during fish processing. Genetic methods have increased exponentially our discrimination power at the species level. In this context, sustainable management of tuna fisheries can clearly profit from the implementation of this kind of quality control procedures, although they are more difficult to implement at the earlier stages of tuna processing, from harvest to the arrival of fish landings at a processing plant. Here we provide a case study using tuna landings to a processing plant in Cabo Verde, an important small island developing State, which supplies mainly the European Union region. Using DNA sequencing based species identification of tissue samples, we found a taxonomic miss-assignment of species identity in 33% of the individuals in the three target tuna species, Bigeye ( Thunus obesus ), Yellowfin ( Thunus albacares ), and Skipjack ( Katsuwonus pelamis ). More than half of Yellowfin samples were wrongly assigned as bigeyes or skipjacks. We also found that many bigeyes were wrongly assigned as yellowfins or skipjacks. None of the skipjacks were incorrectly assigned. The proportion of Yellowfin samples incorrectly assigned as bigeye was significantly higher than the samples of bigeye incorrectly assigned as yellowfins. These results clearly prove the need for improved traceability processes, which should encompass the whole processing pipeline, from harvesting to the consumer. • DNA sequencing found issues of species traceability on tuna landings in Cabo Verde. • Miss-assignment of species identity occurred in 33% of the tuna individuals. • Miss-assignment did not occur in Skipjack tunas, only in Yellowfin and Bigeye tunas.

Effects of Vertical Water Column Temperature on Distribution of Juvenile Tuna Species in the South China Sea

In this study, we conducted two surveys in the central and southern parts of the South China Sea, in autumn 2012 and spring 2013. Six juvenile tuna species were caught in each survey. Gradient forest analysis (GFA) and a generalized additive model (GAM) were used to analyze the relationship between the catch per unit effort (CPUE) for the juvenile tuna species and six sea temperature indices for the South China Sea. In the GFA, the temperature difference between the sea surface and 50 m depth (D50) showed the highest importance to CPUE than other indices, which indicates that D50 was the best predictor of the abundance of juvenile tuna species. The GAM analysis showed that lower deep-water temperature, a shallow mixed layer depth, and a higher difference in temperature between the surface and deeper water were associated with increased CPUE. The results indicate that a relatively rapid decrease in vertical water temperature is favorable for the aggregation of juvenile tuna. These results contribute to understanding of the distribution mechanism of juvenile tuna species in the South China Sea and provide a scientific basis for the rational development and utilization of tuna resources.