Inter-American Tropical Tuna Commission

Global declines in oceanic whitetip shark Carcharhinus longimanus populations have resulted in international protections and a ‘threatened’ listing under the United States Endangered Species Act in 2018. Despite having international regulations on catch and trade of C. longimanus populations, large gaps remain in our understanding of their basic biology, ecology, and population structure. The main Hawaiian Islands (MHIs), USA, are thought to be a biologically important area for central Pacific C. longimanus , where commercial and recreational fishers have reported seasonal spikes in abundance and interaction rates. Using photo-identification of dorsal fin patterns, this study describes population demographics, reproductive activity, fishery interactions, and associative behaviors of C. longimanus around the MHIs. From 2006 to 2024, 383 individuals were identified, with 42 individuals sighted more than once. The highest number of encounters was recorded during the spring (March-May) and the lowest in winter (December-February). The sex ratio was ~2:1 females:males (females n = 241: males n = 108), and 42 females (17.4%) had visible mating scars while 87 females (36.1%) had distended abdomens, possibly indicating pregnancy. Fishery interactions were observed on 157 individuals (26.3% of all encounters), and 46.8% of sharks observed in this study were found within 0.4 km of a fish aggregation device, while 19.2% were found in association with marine mammals. These results provide baseline information on C. longimanus around the MHIs and are necessary to inform conservation and management efforts for this protected species throughout the central Pacific Ocean.

The Silky Shark (Carcharhinus falciformis) is highly vulnerable to population decline, yet leads shark bycatch in some of the world’s largest tuna fisheries. As such, this species provides an appropriate case study for regional fisheries management organizations—exemplified by the Inter-American Tropical Tuna Commission—to develop conceptual population assessment frameworks that integrate diverse data streams to elucidate population structure and dynamics of assessed species. Using genetic, movement, life history, and small- and large-scale fishery-dependent data from across much of the Silky Shark’s Pacific Ocean range, we found preliminary evidence for a three-stock model—southern, central, and northern—in the eastern Pacific Ocean (EPO). Length distributions of Silky Sharks varied with latitude and across fishery gears and strategies. The predominance of small juveniles, including neonates, caught on or near the continental shelf by small-scale fisheries and offshore by purse seines set on floating objects, including fish aggregating devices, suggested that Silky Sharks use both shelf-edge habitats and offshore areas as pupping and/or nursery areas. Finally, we showed that sex ratios favored females in oceanic and equatorial zones, where most Silky Shark bycatch in large-scale fisheries occurs. Our study serves as a roadmap to comprehensively understand spatial population dynamics of common bycatch species lacking a dispersive larval phase, such as elasmobranchs, by integrating genetic, biological, ecological, and fisheries data. Specifically, our work can inform stock assessments and management measures that may improve Silky Shark conservation in the EPO and elsewhere.

Prey selectivity, diel feeding patterns, and effects of light intensity on prey consumption, growth and survival of laboratory-reared yellowfin tuna (YFT) Thunnus albacares larvae were studied at the Inter-American Tropical Tuna Commission’s, Achotines Laboratory in the Republic of Panama. Prey selectivity analysis (Pearre’s c index) for first-feeding larvae (~3-4.5 mm standard length ‘SL’) indicated that, within mixed-prey assemblages containing wild-plankton (WP) (copepods), enriched rotifers, enriched Artemia nauplii, and yolk-sac larvae (YSL) of YFT, rotifers were the prey of preference until the onset of piscivory on YSL prey at ~6 mm SL, a period in which larvae exhibited an increase in caloric intake and exponential growth. Flexion and post-flexion larvae (~5-12.5 mm SL), when foraging under low food concentrations (30 WP l ⁻¹ ), also selected rotifers and YSL. Under high food concentrations (300 WP l ⁻¹ ) larvae preferentially selected Artemia nauplii and YSL. Minimum light levels at which foraging occurred decreased with larval growth, and post-flexion larvae were successfully feeding at light levels as low as 0.025 µmol s ⁻¹ m ⁻² . Prey consumption of first-feeding larvae was significantly higher under higher light conditions (7-25 µmol s ⁻¹ m ⁻² ) while prey consumption of flexion larvae was not affected by lower light conditions (2 µmol s ⁻¹ m ⁻² ). Survival and standardized cohort biomass were significantly higher in treatments with higher light levels. Constructing knowledge of YFT larval feeding dynamics provides greater understanding of the early life history and underlying factors related to pre-recruit survival, providing scientific support for assessments of population fluctuations of adult YFT.

Sustainable development aspires to “leave no one behind”¹. Even so, limited attention has been paid to small-scale fisheries (SSF) and their importance in eradicating poverty, hunger and malnutrition. Through a collaborative and multidimensional data-driven approach, we have estimated that SSF provide at least 40% (37.3 million tonnes) of global fisheries catches and 2.3 billion people with, on average, 20% of their dietary intake across six key micronutrients essential for human health. Globally, the livelihood of 1 in every 12 people, nearly half of them women, depends at least partly on small-scale fishing, in total generating 44% (US$77.2 billion) of the economic value of all fisheries landed. Regionally, Asian SSF provide fish, support livelihoods and supply nutrition to the largest number of people. Relative to the total capture of the fisheries sector (comprising large-scale and small-scale fisheries), across all regions, African SSF supply the most catch and nutrition, and SSF in Oceania improve the most livelihoods. Maintaining and increasing these multidimensional SSF contributions to sustainable development requires targeted and effective actions, especially increasing the engagement of fisherfolk in shared management and governance. Without management and governance focused on the multidimensional contributions of SSF, the marginalization of millions of fishers and fishworkers will worsen.

The use of marine protected areas (MPAs) is expanding around the world. MPAs can have a wide variety of objectives (e.g., science, conservation, food security, cultural value), and scientific guidance on how to design MPAs to achieve objectives is often based on simulation modeling. Many different models may all provide an answer to questions such as the predicted change in population biomass and fisheries catches resulting from th implementation of an MPA. When multiple levels of model complexity are all in theory capable of answering the same question, and the models cannot be confronted with data directly, the decision of what level of model complexity to use can be ad hoc. In this, paper I compare the predicted effects of MPAs on catch and biomass produced by a spatially explicit age-structured multi-species and multi-fleet (High-definition) model to the predictions generated by a two-patch surplus production (Low-definition) model, fitted to emulate the High-definition model. I found that in many cases, the predictions made by the two models were markedly different, with the Low-definition model frequently predicting substantially higher biomass benefits from MPAs than the High-definition model, and in some cases incorrectly estimating the direction (positive or negative) of the MPA effects. However, I also found that the Low-definition model has strategic value for broad classification and ranking exercises. My results show that care should be taken in selecting and interpreting the results of MPA simulation models and that research is needed to understand what models are best suited to what policy recommendations when multiple viable options exist.

Spillover is a term commonly applied to the dispersal of fish and/or larvae from inside a closed area to areas open to fishing. The presence of spillover is often quantified by measuring gradients in attributes such as abundance or catch rates near the boundaries of closed areas or by measuring higher abundance inside closed areas compared to outside. It is commonly assumed that such gradients or ratios indicate that the closed area has benefitted the fishery and the total abundance of fish. We explore this assumption using a spatially explicit model of closed areas with different intensities of fishing and fish movement, and we find that such gradients will be expected any time there is higher abundance inside the closed area. However, such gradients do not necessarily indicate a benefit to the fishery either in terms of total catch or catch rate, and unless pre-closure fishing was intense, total abundance is not expected to rise significantly. We examine case studies that argue that spillover exists and leads to fishery benefits. We then evaluate the evidence for net benefits in these case studies and find those with evidence of net benefits all come from places where fishing pressure was intense. While most analysis come from quite small coastal closed areas, two studies of very large open-ocean closed areas are discussed, and we find that both suggest little overall impact on the tuna populations that support the main commercial fisheries affected by the closures in question.

Stock depletion level is an important concept in the assessment and management of exploited fish stocks because it is often used in conjunction with reference points to infer stock status. Both the depletion level and reference points can be highly dependent on the stock–recruitment relationship. Here, we show how depletion level is estimated in stock assessment models, what data inform the depletion level, and how the stock–recruitment relationship influences the depletion level. There are a variety of data that provide information on abundance. In addition, to estimate the depletion level, unexploited absolute abundance needs to be determined. This often means extrapolating the abundance back in time to the start of the fishery, accounting for the removals and the productivity. Uncertainty in the depletion level arises because the model can account for the same removals by either estimating low productivity (e.g., low natural mortality) and high carrying capacity or high productivity and a low carrying capacity, and by estimating different relationships between productivity and depletion level, which are strongly controlled by the stock–recruitment relationship. Therefore, estimates of depletion are particularly sensitive to uncertainty in the biological processes related to natural mortality and the stock–recruitment relationship and to growth when length composition data are used. In addition, depletion-based reference points are highly dependent on the stock–recruitment relationship and need to account for recruitment variability, particularly autocorrelation, trends, and regime shifts. Future research needs to focus on estimating natural mortality, the stock–recruitment relationship, asymptotic length, shape of the selectivity curve, or management strategies that are robust to uncertainty in these parameters. Tagging studies, including close-kin mark-recapture, can address some of these issues. However, the stock–recruitment relationship will remain uncertain.

Purse‐seine tropical tuna fishing in the eastern tropical Pacific Ocean (EPO) results in the bycatch of several sensitive species groups, including elasmobranchs. Effective ecosystem management balances conservation and resource use and requires considering trade‐offs and synergies. Seasonal and adaptive spatial measures can reduce fisheries impacts on nontarget species while maintaining or increasing target catches. Identifying persistently high‐risk areas in the open ocean, where dynamic environmental conditions drive changes in species’ distributions, is essential for exploring the impact of fisheries closures. We used fisheries observer data collected from 1995 to 2021 to explore the spatiotemporal persistence of areas of high bycatch risk for 2 species of oceanic sharks, silky shark (Carcharhinus falciformis) and oceanic whitetip shark (Carcharhinus longimanus), and of low tuna catch rates. We analyzed data collected by fisheries scientific observers onboard approximately 200 large purse‐seine vessels operating in the EPO under 10 different flags. Fishing effort, catch, and bycatch data were aggregated spatially and temporally at 1° × 1° cells and monthly, respectively. When areas of high fishing inefficiency were closed the entire study period and effort was reallocated proportionally to reflect historical effort patterns, yearly tuna catch appeared to increase by 1–11%, whereas bycatch of silky and oceanic whitetip sharks decreased by 10–19% and 9%, respectively. Prior to fishing effort redistribution, bycatch reductions accrued to 21–41% and 14% for silky and oceanic whitetip sharks, respectively. Our results are consistent with previous findings and demonstrate the high potential for reducing elasmobranch bycatch in the EPO without compromising catch rates of target tuna species. They also highlight the need to consider new dynamic and adaptive management measures to more efficiently fulfill conservation and sustainability objectives for exploited resources in the EPO.

Scientists often collect samples on characteristics of different observation units and wonder whether those characteristics have similar distributional structure. We consider methods to find homogeneous subpopulations in a multidimensional space using regression tree and clustering methods for distributions of a population characteristic. We present a new methodology to estimate a standardized measure of distance between clusters of distributions and for hierarchical testing to find the minimal homogeneous or near-homogeneous tree structure. In addition, we introduce hierarchical clustering with adjacency constraints, which is useful for clustering georeferenced distributions. We conduct simulation studies to compare clustering performance with three measures: Modified Jensen–Shannon divergence (MJS), Earth Mover’s distance and Cramér–von Mises distance to validate the proposed testing procedure for homogeneity. As a motivational example, we introduce georeferenced yellowfin tuna fork length data collected from the catch of purse-seine vessels that operated in the eastern Pacific Ocean. Hierarchical clustering, with and without spatial adjacency constraints, and regression tree methods were applied to the density estimates of length. While the results from the two methods showed some similarities, hierarchical clustering with spatial adjacency produced a more flexible partition structure, without requiring additional covariate information. Clustering with MJS produced more stable results than clustering with the other measures.

Purse‐seine fishers using drifting fish aggregating devices (dFADs), mainly built with bamboo, plastic buoys, and plastic netting, to aggregate and catch tropical tuna, deploy 46,000–65,000 dFADs per year in the Pacific Ocean. Some of the major concerns associated with this widespread fishing device are potential entanglement of sea turtles and other marine fauna in dFAD netting; marine debris and pollution; and potential ecological damage via stranding on coral reefs, beaches, and other essential habitats for marine fauna. To assess and quantify the potential connectivity (number of dFADs deployed in an area and arriving in another area) between dFAD deployment areas and important oceanic or coastal habitat of critically endangered leatherback (Dermochelys coriacea) and hawksbill (Eretmochelys imbricata) sea turtles in the Pacific Ocean, we conducted passive‐drift Lagrangian experiments with simulated dFAD drift profiles and compared them with known important sea turtle areas. Up to 60% of dFADs from equatorial areas were arriving in essential sea turtle habitats. Connectivity was less when only areas where dFADs are currently deployed were used. Our simulations identified potential regions of dFAD interactions with migration and feeding habitats of the east Pacific leatherback turtle in the tropical southeastern Pacific Ocean; coastal habitats of leatherback and hawksbill in the western Pacific (e.g., archipelagic zones of Indonesia, Papua New Guinea, and Solomon Islands); and foraging habitat of leatherback in a large equatorial area south of Hawaii. Additional research is needed to estimate entanglements of sea turtles with dFADs at sea and to quantify the likely changes in connectivity and distribution of dFADs under new management measures, such as use of alternative nonentangling dFAD designs that biodegrade, or changes in deployment strategies, such as shifting locations.

Introduction Worldwide coastal fish resources face severe threats from fisheries overexploitation. However, the evaluation of abundance trends in most coastal fisheries is constrained by limited data. This study took blackmouth croaker (Atrobucca nibe), a stock depleted by coastal trawl fishery in southwestern Taiwan, as an example to showcase the development of a relative abundance index from data-limited fishery (only landing data were available). Methods This study employed unique data sourcing from voyage data recorders (VDRs) to estimate fishing effort (in combination with landing data to estimate the catch per unit effort, CPUE) that demonstrated the potential application in global data-limited fisheries and assessed alternative approaches for predictors of fishery-targeting practices to condition effort for producing more accurate metrics of relative abundance. The nominal CPUE was standardized using three statistical models: generalized linear model, generalized additive model (GAM), and vector-autoregressive spatiotemporal models (VASTs) with two treatments of each of the four effects: environmental (sea temperature, salinity, density of mixing layer, seafloor temperature, and chlorophyll), vessel, spatial, and targeting effects. A total of 15 models were designed and compared for these effects, and their explanatory power (EP) was evaluated using cross-validation R ² and other metrics. Results and discussion Results indicated that the targeting effect exerted the most significant influence on standardization and was suggested to be addressed through the principal component analysis (PCA) approach. Both vessel and spatial effects demonstrated considerable influence, whereas the environmental effect exhibited a limited impact, possibly due to the small fishing area in this study. Regarding models’ EP, given the nonlinear nature of the PCA algorithm and environmental data, the study highlighted the superiority of the GAM over linear-based models. However, incorporating nonlinear features in VAST (M15) makes it the most effective model in terms of predictive power in this study. Concerning the stock status, despite variations in relative CPUE trends among major models, a general declining trend since 2015 signals the potential decline of the blackmouth stock and urges fishery managers to consider further design of management measures.

Spillover is a term commonly applied to the movement of fish from inside a closed area to areas open to fishing outside of the closure and is usually identified by gradients in abundance or catch rates near the boundaries. It is commonly assumed that such gradients indicate that the closed area has benefitted the fishery and the total abundance of fish. We explore this assumption for spatially explicit models of closed areas with different intensities of fishing and fish movement and find that such gradients will be expected any time there is higher abundance inside the closed area. However, under most conditions it does not indicate a benefit to the fishery either in terms of total catch of catch rate, and unless fishing is intense total abundance is not expected to rise significantly. We examine one specific case of estimates spillover from the Papahānaumokuākea marine monument, one the largest no-take areas in the world, and see no evidence of spillover for yellowfin tuna and very slight evidence for bigeye tuna. These results are consistent with the theoretical models, the biology of the species and the intensity of fishing.

The Eastern Pacific population of leatherback turtles Dermochelys coriacea is Critically Endangered, with incidental capture in coastal and pelagic fisheries as one of the major causes. Given the population’s broad geographic range, status, and extensive overlap with fisheries throughout the region, identifying areas of high importance is essential for effective conservation and management. In this study, we created a machine-learning species distribution model trained with remotely sensed environmental data and fishery-dependent leatherback presence (n = 1088) and absence data (>500000 fishing sets with no turtle observations) from industrial and small-scale fisheries that operated in the eastern Pacific Ocean between 1995 and 2020. The data were obtained through a participatory collaboration between the Inter-American Convention for the Protection and Conservation of Sea Turtles and the Inter-American Tropical Tuna Commission as well as non-governmental organizations to support the quantification of leatherback vulnerability to fisheries bycatch. A daily process was applied to predict the probability of leatherback occurrence as a function of dynamic and static environmental covariates. Coastal areas throughout the region were highlighted as important habitats, particularly highly productive feeding areas over the continental shelf of Ecuador, Peru, and offshore from Chile, and breeding areas off Mexico and Central America. Our model served as the basis to quantify leatherback vulnerability to fisheries bycatch and the potential efficacy of conservation and management measures (Griffiths & Wallace et al. 2024; Endang Species Res 53:295-326). In addition, this approach can provide a modeling framework for other data-limited vulnerable populations and species.

Industrial tuna and artisanal fisheries targeting multiple species in the eastern Pacific Ocean (EPO) interact with the Critically Endangered East Pacific (EP) leatherback turtle Dermochelys coriacea. In 2021, a revised Inter-American Tropical Tuna Commission (IATTC) resolution on sea turtles aimed to reduce sea turtle bycatch in EPO industrial tuna fisheries and ensure their safe handling and release. A new ecological risk assessment approach—Ecological Assessment for the Sustainable Impacts of Fisheries (EASI-Fish)—was used to assess vulnerability status and to better understand the potential efficacy of 70 scenarios that compared simulated conservation and management measures (CMMs) for EPO industrial (purse-seine and longline) and artisanal (longline and gillnet) fisheries to the status quo in 2019. In 2019, a fishing mortality proxy (F ̃ 2019) and the breeding stock biomass per recruit (BSR2019) exceeded precautionary biological reference points (F80% and BSR80%), classifying the stock as ‘most vulnerable’. Industrial and artisanal longline fisheries had the highest impacts because they had the highest areal overlap with the modelled EP leatherback distribution. Of the 70 CMM scenarios, 42 resulted in significant improvements in vulnerability status (i.e. to ‘least vulnerable’). The use of large circle hooks, finfish bait, and best handling and release practices each decreased vulnerability; however, the most effective scenarios involved using these 3 measures in concert. The benefits predicted from EASI-Fish for CMM scenarios assume full compliance and attaining the modelled levels of efficacy, our modelling provides stakeholders with evidence-based recommendations to address key threats to EP leatherback turtles to improve their conservation status by reducing fishing impacts.

The incidental capture of non-target species (bycatch) in tuna fisheries impacts some marine vertebrates, particularly species with vulnerable life histories such as manta and devil rays (mobulids). There is broad interest in reducing mobulid bycatch in tuna purse seine fisheries, with existing efforts mainly focusing on reducing post-capture mortality rates. We explore a novel potential pre-capture mobulid bycatch avoidance strategy for the tuna purse seine fishery using communication between fishing vessels and associated spotter helicopters. We conducted a survey of tuna purse seine helicopter pilots, spotters, and fishers operating in the eastern Pacific Ocean (n = 33) to ascertain the ability of helicopter crew to detect mobulids prior to capture and communicate bycatch avoidance with vessel crew. Results indicate over half of the helicopter crew report being “always” or “sometimes” able to sight and identify mobulids and that helicopter crew regularly communicate mobulid sightings to the vessel already. Given that an average of 63% of class-6 vessel trips between 2017 to 2022 carried onboard helicopters, our results suggest that helicopter-vessel communication could be feasible and scalable for mobulid bycatch detection, enabling potential bycatch avoidance and early alerts for proper handling protocols. We also identify the potential use of helicopter detection to improve research efforts for mobulid conservation (e.g., data collection of population and habitat observations). This study is the first to investigate the utility of helicopter-vessel communication as a bycatch mitigation strategy for elasmobranchs and identifies research and management directions that could be further investigated to avoid bycatch of mobulids.

Spatial models enable understanding potential redistribution of marine resources associated with ecosystem drivers and climate change. Stock assessment platforms can incorporate spatial processes, but have not been widely implemented or simulation tested. To address this research gap, an international simulation experiment was organized. The study design was blinded to replicate uncertainty similar to a real‐world stock assessment process, and a data‐conditioned, high‐resolution operating model (OM) was used to emulate the spatial dynamics and data for Indian Ocean yellowfin tuna ( Thunnus albacares ). Six analyst groups developed both single‐region and spatial stock assessment models using an assessment platform of their choice, and then applied each model to the simulated data. Results indicated that across all spatial structures and platforms, assessments were able to adequately recreate the population trends from the OM. Additionally, spatial models were able to estimate regional population trends that generally reflected the true dynamics from the OM, particularly for the regions with higher biomass and fishing pressure. However, a consistent population biomass scaling pattern emerged, where spatial models estimated higher population scale than single‐region models within a given assessment platform. Balancing parsimony and complexity trade‐offs were difficult, but adequate complexity in spatial parametrizations (e.g., allowing time‐ and age‐variation in movement and appropriate tag mixing periods) was critical to model performance. We recommend expanded use of high‐resolution OMs and blinded studies, given their ability to portray realistic performance of assessment models. Moreover, increased support for international simulation experiments is warranted to facilitate dissemination of methodology across organizations.

Fishers have intensively used drifting fish aggregating devices (DFADs) over the last three decades to facilitate their catch of tropical tunas. DFADs increase purse‐seine efficiency, potentially increasing tuna fishing mortality. They could also have impacts on tuna natural mortality and reproductive potential, and assessing the consequences of their presence at sea on tuna populations is a challenge. The use of DFADs results in a major increase in the number of floating objects, which are spatially heterogeneous at sea. To date, no converging scientific results exist regarding the effects of DFADs on the large‐scale movements and behaviour of tuna, mainly due to the difficulty of disentangling the respective roles of DFADs and environmental factors. Some biological indices show that tuna condition is lower when associated to a floating object than in a free‐swimming school. However, it is not clear whether this is the cause or the consequence of the association nor if it has long‐term effects on individuals' fitness. Further scientific progress requires (i) the collection of time series of indicators to monitor habitat change, individual behaviour, individual fitness, and population dynamics and (ii) experimental studies to identify the underlying behavioural and biological processes involved in associative behaviour. The extent of the modification of the surface habitat by the massive deployment of DFADs and the current uncertainty of the possible long‐term consequences on the individual fitness and dynamics of tuna populations argue for the need for increased awareness of this issue by Regional Fisheries Management Organisations regulating tuna fishing.

Background The Yellowfin tuna (Thunnus albacares) is a large tuna exploited by major fisheries in tropical and subtropical waters of all oceans except the Mediterranean Sea. Genomic studies of population structure, adaptive variation or of the genetic basis of phenotypic traits are needed to inform fisheries management but are currently limited by the lack of a reference genome for this species. Here we report a draft genome assembly and a linkage map for use in genomic studies of T. albacares. Methods and results Illumina and PacBio SMRT sequencing were used in combination to generate a hybrid assembly that comprises 743,073,847 base pairs contained in 2,661 scaffolds. The assembly has a N50 of 351,587 and complete and partial BUSCO scores of 86.47% and 3.63%, respectively. Double-digest restriction associated DNA (ddRAD) was used to genotype the 2 parents and 164 of their F1 offspring resulting from a controlled breeding cross, retaining 19,469 biallelic single nucleotide polymorphism (SNP) loci. The SNP loci were used to construct a linkage map that features 24 linkage groups that represent the 24 chromosomes of yellowfin tuna. The male and female maps span 1,243.8 cM and 1,222.9 cM, respectively. The map was used to anchor the assembly in 24 super-scaffolds that contain 79% of the yellowfin tuna genome. Gene prediction identified 46,992 putative genes 20,203 of which could be annotated via gene ontology. Conclusions The draft reference will be valuable to interpret studies of genome wide variation in T. albacares and other Scombroid species.

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.