Due to their large ecological niche and high commercial value, highly migratory species are exposed to fishing pressure across the Atlantic Ocean. Although international management collects spatial catch and effort data, accuracy and representativeness are difficult to verify. Fleet behavior can increasingly be monitored using ship tracking technologies. Simultaneously, electronic tagging provides location estimates as well as broader insights into seasonal habitat suitability. Here, we combined electronic tagging datasets from 778 satellite and archival tags with environmental data to model distributions for Atlantic Bluefin Tuna, Blue Sharks, Swordfish, and Blue Marlin. We overlaid these maps with longline effort estimates derived from AIS data to identify times and regions of high overlap between species and fleet. Comparing with species-specific catch per unit efforts (CPUEs) reported to management, we identified regions where, for specific species and seasons, reported catches were low compared to species density predicted from presence data and habitat models. This data science approach may be useful to management enforcement agencies and compliance committees, potentially identifying regions where fleets may be under-reporting or other management assumptions may be invalid.

Body size is a fundamental property of animal physiology, growth, and maturation, yet field measurements remain difficult to acquire for large-bodied, highly mobile marine species such as white sharks (Carcharodon carcharias). In this study, we integrate aerial and underwater imagery to obtain high-resolution morphometrics of eastern Pacific white sharks remotely in the Monterey Bay National Marine Sanctuary. We develop and validate a computational pipeline leveraging deep learning analysis of Unoccupied Aircraft System (UAS) imagery to extract shark total length and body condition, given by a span-length ratio. UAS-based morphometric data reveal that white sharks form size-structured aggregations aligned with oceanographic gradients, indicating that coastal areas within Monterey Bay function as key transitional zones along a continuum of ontogenetic habitat use on the central coast of California. Across individuals, extended girth-length scaling relationships indicate proportionally greater girth amongst eastern Pacific white sharks relative to other populations. This pattern is particularly pronounced in females, which exhibit progressively higher body condition with life stage, likely reflecting the energetic demands of reproduction or sex-specific foraging strategies. By linking UAS-derived morphometrics to ecological context, this approach enables a novel population-level investigation of ecological structure, body size, and morphological variation in a marine predator population.

Identifying and preserving biological diversity is fundamental for the conservation of wild populations. The Atlantic bluefin tuna (Thunnus thynnus, ABT) is an apex predator and vital species to the pelagic ecosystems of the North Atlantic Ocean, with populations now rebounding from decades of overfishing due to strict enforcement of conservation measures. Here, we combine high-resolution whole-genome sequencing data with spatial data from electronic tagging to improve our understanding of population structure in ABT. We analyzed 82 whole-genome sequences obtained from mature fish tracked to geographically distinct spawning grounds, as well as larvae representing the two recognized stocks (western and eastern) of ABT. We obtained 11,181,223 single-nucleotide polymorphisms (SNPs) and integrated these genomic data with 12,974 total geolocation days of adult ABT (mean individual deployment length: 271 ± 110.4 days). This extensive dataset of electronic tracks enables spatial assignment of individuals to their respective spawning grounds and the first whole-genome comparison of migratory phenotypes. Both neutral and adaptive SNP markers reflect the same genomic population structure as the spatial movement patterns, likely maintained by natal philopatry, and we highlight candidate genes with potentially adaptive roles. Our analyses show that the two populations diverged ∼27,000 years ago, overlapping with the Last Glacial Maximum, and we suggest that oceanographic variation of the spawning grounds has contributed to shaping present-day bluefin tuna genomic diversity. Overall, these results improve our understanding of adaptive variation in bluefin tuna, which will be important for management decisions.

Advances in life-history research on Atlantic bluefin tuna (ABT; Thunnus thynnus) have informed management measures that supported population recovery amid intensifying human pressures. However, movement data from the eastern Mediterranean (EMED) remain scarce, limiting understanding of basin-scale connectivity. Here, we deployed pop-up satellite archival tags on six ABT off Israel and incorporated two additional individuals tagged in Canada and Norway that subsequently entered the EMED to examine movements in relation to oceanographic conditions. Across 1563 daily positions and 995 archival days, ABT occupied the Levantine and Aegean Seas during summer under warm, stratified conditions consistent with surface-oriented reproductive behaviour. In one individual, high-resolution archival data provided the first behavioural indication of putative spawning in this region. Late-summer dispersal revealed two patterns: EMED residency and westward migration to overwintering grounds in the western Mediterranean, with some individuals continuing into the North Atlantic Ocean. The northern Balearic–Ligurian region emerged as the primary foraging ground for contingents across the Mediterranean, highlighting the need for management that accounts for sub-basin structure and seasonal mixing.

Pacific bluefin tuna (PBT, Thunnus orientalis) is a highly migratory species that mainly inhabits temperate regions of the North Pacific Ocean. To examine the population dynamics of this commercially and ecologically important species, it is essential to understand their spawning migration, since Northwestern Pacific Ocean is their important spawning ground. A total of three PBT were tagged with pop-up satellite archival tags (PSATs) in the spawning season (May) of 2021, and the tags remained affixed for 13, 54 and 61 days, respectively. The linear displacement ranged from 797 to 2743 km from deployment locations to pop-up locations. The deepest descent recorded was 1458 m, and the coldest temperature visited was 2.6 °C. The time spent at depth was significantly different between the daytime and nighttime, where the fish displayed regular crepuscular patterns of ascending into the surface layer at dusk and remaining there until the following dawn, when they descended past the mixed-layer depth. At the spawning grounds, PBT exhibited shallow oscillatory diving behavior and frequently visited the surface during daytime and nighttime with longitudinal movements correlated with sea surface height anomalies and mesoscale eddies. This study tracked adult PBT on their spawning grounds, and insights were gained into spawning migration, seasonal movements, and habitat use of this species in the Northwestern Pacific Ocean.

Climate change is impacting the distribution and movement of mobile marine organisms globally. Statistical species distribution models are commonly used to explain past patterns and anticipate future shifts. However, purely correlative models can fail under novel environmental conditions, or omit key mechanistic processes driving species habitat use. Here, we used a unique combination of laboratory measurements, field observations, and environmental predictors to investigate spatial variability in energetic seascapes for juvenile North Pacific albacore tuna (Thunnus alalunga). This species undertakes some of the longest migrations of any finfish, but their susceptibility to climate-driven habitat changes is poorly understood. We first built a framework based on Generalized Additive Models to understand mechanisms of energy gain and loss in albacore, and how these are linked to ocean conditions. We then applied the framework to projections from an ensemble of earth system models to quantify changes in thermal and foraging habitats between historical (1971–2000) and future (2071–2100) time periods. We show how albacore move seasonally between feeding grounds in the California Current System and the offshore North Pacific, foraging most successfully in spring and summer. The thermal corridors used for migration largely coincide with minimum metabolic costs of movement. Future warming may result in loss of favorable thermal habitat in the sub-tropics and a reduction in total habitat area, but allow increased access to productive and energetically favorable sub-arctic ecosystems. Importantly, while thermal considerations suggest a loss in habitat area, forage considerations suggest that these losses may be offset by more energetically favorable conditions in the habitat that remains. In addition, the energetic favorability of coastal foraging areas may increase in future, with decreasing suitability of offshore foraging grounds. Our results clearly show the importance of moving beyond temperature when considering climate change impacts on marine species and their movement ecology. Considering energetic seascapes adds essential mechanistic underpinning to projections of habitat gain and loss, particularly for highly migratory animals. Overall, improved understanding of mechanisms driving migration behavior, physiological constraints, and behavioral plasticity is required to better anticipate how climate change will impact pelagic marine ecosystems.

Reef manta rays Mobula alfredi are large, filter-feeding elasmobranchs known to aggregate in coastal areas and island archipelagos. Effective spatial conservation strategies, such as marine protected areas (MPAs), for this mobile marine species rely on a comprehensive understanding of movement behavior. To better understand movement patterns, we externally deployed 58 acoustic tags on reef mantas at the Palmyra Atoll National Wildlife Refuge and monitored the presence of mantas on an extensive array of acoustic receivers (n = 85) for close to a decade. We documented an average maximum residency rate of 88% as well as consistent use of all 4 primary habitat types at Palmyra-the lagoon system, reef terrace, forereef, and channel. Notably, the highest rates of detection were recorded in the nutrient rich lagoon habitats (69% of detections). Manta movements displayed a diel structure, with a preference for the forereef, reef terrace, and channel during daylight hours, and the lagoon at night. We also found bimodal peaks of activity during new and full moons. In addition, detections around the atoll increased during the cooler periods of fall and winter. Our findings demonstrate that the no-fishing regulations at Palmyra Atoll are an effective spatial management strategy for this resident population of reef mantas and indicate that reef ecosystems in remote locations may be well-suited for designation as MPAs, offering protection for threatened elasmobranch species.

Large-scale marine protected areas (LSMPAs; > 1000 km2) provide important refuge for large mobile species, but most do not encompass species' ranges. To better understand current and future LSMPA value, we concurrently tracked nine species (seabirds, cetaceans, pelagic fishes, manta rays, reef sharks) at Palmyra Atoll and Kingman Reef (PKMPA) in the U.S. Pacific Islands Heritage Marine National Monument. PKMPA and the U.S. Exclusive Economic Zone encompassed 39% and 54% of species movements (n = 83; tracking duration range: 0.5-350 days), respectively. Species distribution models indicated 73% of PKMPA contained highly suitable habitat. Under two projected future scenarios (SSP 1-2.6, "Sustainability"; SSP 3-7.0, "Rocky Road"), strong sea surface temperature gradients initially could cause abrupt oceanic change resulting in predicted habitat loss in 2040-2050, followed by an equilibrium response and regained habitat by 2090-2100. Current and future suitable habitats were available adjacent to PKMPA, suggesting that increased MPA size could enhance protection. Our three-tiered approach combining animal tracking with publicly available remote sensing data and future projected environmental scenarios could be used to design, study, and monitor protected areas throughout the world. Holistic approaches that encompass diverse species and habitat use can enhance assessments of protected area designs. Animal telemetry and remote sensing may be helpful for ascertaining the extent to which other MPAs protect large mobile species in the future.

The combination of animal-borne telemetry and oceanographic sensor technologies creates an opportunity for marine animals to serve as ocean observing platforms (OOPs), carrying tags that record in situ oceanographic data as they naturally move. In this study, we create a blueprint of shark OOP species selection, quantifying and comparing the potential for species to transmit collected data, the environmental ranges various candidates are expected to encounter, and the oceanographic features they may be expected to resolve. Metrics of data satellite transmission probability, movement behaviors, and environmental sampling ranges are calculated combining historically collected satellite tag data for 11 shark species tagged in the Atlantic and Pacific Ocean basins. Species with the highest satellite data transmission potential include shortfin mako (Atlantic and Pacific) and blue (Pacific) sharks. These species also demonstrated overlap in time and length scales for area-restricted search-like movement behaviors with several mesoscale ocean features, including hurricanes and upwelling events. Additional comparisons of decorrelation time scales between theoretical shark versus glider sampling platforms suggest that shark OOPs have the ability to provide three times more uncorrelated water column temperature and conductivity profiles than gliders at 15% of the operational cost.

Research on the direct effects of capture and tagging on post-release behaviour is typically limited to short-term deployments. To investigate the initial and longer-term behavioural responses to capture and tagging, we deployed eight Cefas G7 tags (1Hz depth and temperature, and 20 Hz triaxial acceleration) for 21–94 hours and 12 Wildlife Computers MiniPATs (depth, temperature, light and triaxial acceleration, each at 0.2 Hz) for 110–366 days on Atlantic bluefin tuna (ABT) in the English Channel. Post-release, ABT exhibited a strong, highly active initial swimming response, consistent with patterns reported in previous bluefin tuna, billfish and elasmobranch tracking studies. Accelerometry tags revealed that activity (VeDBA g), tailbeat amplitude (g) and dominant stroke frequency (Hz) were greater (2.4, 3.2 and 1.4 times respectively) within the first hour post-release than the subsequent 24 hours, stabilising at lower levels within 5–9 hours. However, lower resolution accelerometry data (0.2 Hz), obtained from longer periods from MiniPATs, revealed that fish then maintained this reduced activity for 11 ± 7.9 days (mean ± 1 SD; range: 2–26 days), during which they displayed disrupted diel patterns of activity and allocated on average 5 minutes of each day to burst energy events, compared to 14 minutes (max 74 minutes) during “recovered” periods. Subsequently, their activity levels increased again and were characterised by higher magnitude acceleration events (which may constitute feeding events) and became more active during the day than at night. Year-long deployments revealed that consistent diel vertical migration, diurnal patterns of activity, and increased time allocation to fast starts are normal for ABT off the British Isles in summer months, and their absence at the start of data collection may be related to the effect of capture and tagging, which may be longer lasting, and more complex than previously appreciated.

Context Consumer-grade unoccupied aircraft systems (UAS) are increasingly being used by both scientists and hobbyists in the coastal environment. Marine megafauna are observed via UAS as part of monitoring programs, recreational interests, and scientific research, amassing aerial imagery datasets. Because manual documentation of these datasets is infeasible at scale, efficient approaches leveraging computer vision and deep learning have emerged to detect and classify marine megafauna.Aims This study provides a workflow to quantitatively estimate swimming kinematics tailbeat frequency (TBF) and tailbeat amplitude (TBA) of white sharks (Carcharodon carcharias) from aerial UAS video data.Methods Body pose estimation was performed using computer vision model DeepLabCut to track six key white shark body parts across UAS videos. The relative positions of these body part coordinates were used to compute tail position over time and quantify TBF and TBA across a population of white sharks in Monterey Bay, California.Key results With a training set of just 52 images, the deep residual neural network reaches human-level labeling accuracy of body parts (root mean square error of <1.3 cm). This workflow is applied to 76 focal follows representing 34 individuals to produce TBF (0.43 +/- 0.07 Hz) and TBA (0.24 +/- 0.10 BL) values similar to those derived from biologging devices previously deployed on individuals in this population.Conclusions The results indicated that body pose estimation via DeepLabCut can allow for the rapid extraction of quantitative kinematics such as TBF and TBA in juvenile white shark populations that aggregate in coastal habitats.Implications This approach provides a non-invasive, scalable method to understanding megafauna kinematics in sensitive species that overcomes the logistical barriers of traditional biologging approaches.

Theory predicts that high population density leads to more strongly connected spatial and social networks, but how local density drives individuals' positions within their networks is unclear. This gap reduces our ability to understand and predict density-dependent processes. Here we show that density drives greater network connectedness at the scale of individuals within wild animal populations. Across 36 datasets of spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals and insects, 80% of systems exhibit strong positive relationships between local density and network centrality. However, >80% of relationships are nonlinear and 75% are shallower at higher values, indicating saturating trends that probably emerge as a result of demographic and behavioural processes that counteract density's effects. These are stronger and less saturating in spatial compared with social networks, as individuals become disproportionately spatially connected rather than socially connected at higher densities. Consequently, ecological processes that depend on spatial connections are probably more density dependent than those involving social interactions. These findings suggest fundamental scaling rules governing animal social dynamics, which could help to predict network structures in novel systems.

Marine animals live in a dynamic environment, where a wide range of drivers and processes impact their movements and distributions. These processes occur over multiple spatio-temporal scales, from fine scale phytoplankton blooms and zooplankton patches to larger scale climatic events such as El Niño or climate change. In a dynamic ocean, the predictability of ocean features and processes vary across multiple scales. Marine animals interact with all these processes, and they all have the potential to impact animal distribution. However, which processes and scales predominantly predict the distributions of highly mobile predators is currently unknown. Here, we use electronic tagging data (265 sharks tagged in the Pacific) to investigate the scales of environmental selection of three pelagic shark species (the salmon shark Lamna ditropis, the blue shark Prionace glauca, and the shortfin mako Isurus oxyrinchus) across an array of spatio-temporal resolutions (from 9 km - 1 day to 500 km - climatology) for both Eulerian and Lagrangian variables. While Eulerian and Lagrangian variables at all scales tested have predictive power, we find that the 100 km - 1 year scale best predicted predator locations, indicating that larger scale, annually averaged signals outperform the other scales in predicting predator location.

Deep dives are performed by a range of marine megafauna, yet their function remains poorly understood. Proposed functions include foraging, predator avoidance, and navigation, but limited fine-scale data have hindered rigorous testing of these hypotheses. Here, depth time-series data from eight recovered and 16 non-recovered satellite tags deployed on oceanic manta rays (Mobula birostris) in Indonesia, Peru, and New Zealand were examined to characterise extreme dives and identify their potential function. From a total of 46,945 dives, 79 extreme dives (>500 m) were recorded, 11 of which were documented from recovered tags and associated high sampling frequency. Extreme dives were distinguished by rapid descents (up to 2.9 m s⁻¹), brief horizontal “steps” at depth, gradually slowing ascents, and extended periods spent near the surface both before and after diving. Unlike typical foraging dives, no substantial bottom phase was observed, and vertical oscillations—expected if feeding at depth—were absent. Extreme dives also occurred more frequently with increasing distance from the continental shelf edge as well as preceding periods of high 72h distance travelled, indicating they may inform subsequent movements. We propose that extreme dives enable oceanic manta rays to survey the properties of the water column, likely gathering environmental cues—such as temperature, dissolved oxygen, or geomagnetic gradients—to guide navigation and/or the decision to leave or remain in a general area. In open-ocean environments where external reference points are absent, such costly but infrequent dives may provide critical information for long-distance movements. Our results offer new insights into the role of extreme diving behaviour in oceanic manta rays and highlight the importance of fine-scale data for understanding deep-diving behaviours in marine megafauna.

Context Gaining insights into seasonal aggregations of marine megafauna and how patterns vary among demographic groups is pivotal for evaluating anthropogenic risk exposure and modeling populations and ecosystem dynamics. In California, adult and subadult white sharks recurrently aggregate on the coast near pinniped colonies in fall and winter months, facilitating comprehensive long-term field studies.Aims In this study, we used over 15 years of passive acoustic telemetry data to compare the seasonal dynamics of coastal habitat use for white sharks tagged in central California among four demographic groups (adult females, adult males, subadult females, and subadult males).Methods Acoustic tags were deployed on 355 white sharks at coastal aggregation sites and monitored across a coastal array of underwater receivers from 2006 to 2022. The main aggregation sites of the Northeast Pacific (A & ntilde;o Nuevo, the Farallon Islands and Tomales) were continuously monitored, with an expansion of the acoustic network to the south in the latter years of the study.Key results White sharks were tracked for an average duration of 594 +/- 552 days (mean +/- s.d.), with total track durations ranging up to 3235 days. Notably, adult male sharks exhibited the highest residency to central California coastal aggregation sites and demonstrated earlier seasonal peak densities in late October. Adult female presence peaked in early December. Adult sharks displayed distinct seasonal gaps in detection where they have been shown with satellite tags to migrate offshore, with females displaying much longer average detection gaps than for males (averaging 1.5 years vs 0.7 years). In contrast, subadults exhibited higher coastal affinity with more consistent and widespread detections across a higher number of coastal sites throughout the year, often extending beyond the main aggregation areas outside of the peak aggregation season.Conclusions We hypothesize that the observed differences between demographic groups are attributed to sex- and size-specific foraging and reproductive strategies. The extended receiver network also showed expansive coastal movements and identified potential undescribed aggregation sites.Implications Insights from our extensive acoustic dataset represent a significant advancement in assessing the timing of anthropogenic interactions and modeling both ecosystem and population dynamics.

Understanding the spatial ecology of commercially exploited species is vital for their conservation. Atlantic bluefin tuna (Thunnus thynnus, ABT) are increasingly observed in northeast Atlantic waters, yet knowledge of these individuals’ spatial ecology remains limited. We investigate the horizontal and vertical habitat use of ABT (158 to 241 cm curved fork length; CFL) tracked from waters off the United Kingdom (UK) using pop-up satellite archival tags (n = 63). Analyses reveal distinctive movements from the UK to the Bay of Biscay (BoB) and Central North Atlantic between September and December, and size-specific habitat preferences in May and July—all ABT < 175 cm CFL inhabiting the BoB and 73% of ABT ≥ 175 the Mediterranean Sea. All ABT tracked for more than 300 days (n = 25) returned to waters off the UK the following year, where most stayed (n = 22; 88%) and three continuing north with deployments ending off northwest Ireland. ABT mostly occupied waters between 0 and 20 m (daytime 49 ± 6% of time; nighttime 71 ± 6%). Vertical habitat use was coupled with illumination, mean depth occupied, maximum depth reached, and vertical movement rate increased during the daytime and when moons were brightest. These data provide valuable insights into the spatial ecology of ABT reoccupying northerly foraging areas following decades of absence.

Ecological data are being opportunistically synthesised at unprecedented scales in response to the global biodiversity and climate crises. Such syntheses are often only possible through large-scale, international, multidisciplinary collaborations and provide important pathways for addressing urgent conservation questions. Although large collaborative data syntheses can lead to high-impact successes, they can also be plagued with difficulties. Challenges include the standardisation of data originally collected for different purposes, integration and interpretation of knowledge sourced across different disciplines and spatio-temporal scales, and management of differing perspectives from contributors with distinct academic and cultural backgrounds. Here, we use the collective expertise of a global team of conservation ecologists and practitioners to highlight common benefits and hurdles that arise with the development of opportunistic collaborative syntheses. We outline a framework of “best practice” for developing such collaborations, encompassing the design, implementation, and deliverable phases. Our framework addresses common challenges, highlighting key actions for successful collaboration and emphasizing the support requirements. We identify funding as a major constraint to sustaining the large, international, multidisciplinary teams required to advance collaborative syntheses in a just, equitable, diverse, and inclusive way. We further advocate for thinking strategically from the outset and highlight the need for reshaping funding agendas to prioritize the structures required to propel global scientific networks. Our framework will advance the science needed for ecological conservation and the sustainable use of global natural resources by supporting proto-groups initiating new syntheses, leaders and participants of ongoing projects, and funders who want to facilitate such collaborations in the future.

A numerical model which simulates the adsorption of radionuclides by migrating bluefin tuna in the Mediterranean Sea is described, in order to determine the level of contamination of these fish after a hypothetical nuclear accident and thus be able to assess the possible impact on human consumption. A 4-species foodweb model is incorporated into a Lagrangian model describing physical transport (advection, mixing, radioactive decay and interactions of radionuclides with sediments). Tuna is the last trophic level in the foodweb model and the equation providing the temporal evolution of radionuclide concentration in its flesh is solved along the fish trajectories, which were obtained through electronic tagging of fishes. The model was applied to the western Mediterranean, where several worst-case hypothetical accidents were simulated, both from a coastal nuclear power plant and from a vessel. Resulting Cs-137 concentrations in migrating tuna were similar, or slightly higher, than reported background concentrations in these fishes and well below established safety levels. Maximum calculated concentrations in tuna flesh is in the order of 1 Bq/kg (wet weight). This is due to the rapid movement of the fishes, which spend only limited time over the most contaminated spots.