ICES Journal of Marine Science

Bottom trawls have been used for centuries, yet studies of their impact on marine ecosystems have largely been restricted to recent decades. Here, we reconstruct fishing effort for the international trawler fleets in the North Sea from the age of sail to early steam trawling, by synthesising historical data describing vessel numbers and specifications, gear dimensions, fishing grounds, and operational characteristics. The trawler fleet increased from ca 800 sailing vessels in the 1820s to ca 3500 at the peak in sail trawling in the 1880s. Subsequently, steam trawling fleets emerged, increasing to almost 2000 vessels in the 1910s, while sailing fleets declined. Trawling grounds, covering ca 7% of the North Sea in 1820s, expanded from coastal to offshore grounds, reaching ca 25% in the 1880s, and 46% in the 1910s after the transition to steam trawling. Using a hydro- and aerodynamic approach to model the wind conditions required for sail trawling, we show that about 55% to 80% of the time at sea was suitable for trawling, providing a new quantitative basis for estimating historical fishing effort. The surface area swept by the trawl per year increased from 35,000 km2 in 1820s to 225,000 km2 in 1880s and 500,000 km2 in 1910s, corresponding to ca 60% of present levels. The trawling intensity (swept area ratio) varied between 0.9-1.7 year-1 in the era of sail, increasing to ca 2.0 in the 1910s. The trawling footprint (unique area trawled) increased to 160,000 km2, about half the present level.

As anthropogenic threats have intensified over the past 500 years, we find ourselves in the midst of a sixth mass extinction, with continued losses of biodiversity threatening ecosystem stability. This biodiversity loss has caused species extinctions across taxa, and placed several others at high risk of functional extinction. These disturbance-driven impacts represent one of the most acute biodiversity crises facing global marine systems. Species exhibiting slow life histories characteristically have low resilience to disturbance. Here, we assess the risk of functional extinction and identify policy pathways for population recovery of the slow-living, Critically Endangered elasmobranch, the spinetail devil ray (Mobula mobular). We develop a stochastic, state-structured Integral Projection Model (IPM) parameterised with demographic data collected from fishery landings data in India, the world's largest mobulid fishery, and supplemented with data on vital rates from published literature. Using the IPM, we estimate that the population is declining at approximately 12% annually, experiencing substantial limiting pressure from fisheries overexploitation and failing to approach its biological maximum growth potential. Our results indicate that populations of M. mobular will be at high risk of functional extinction if 'business as usual' harvest scenario persists for another decade. We further show that long-term population recovery is only possible if survival increases significantly across all size classes, especially among large reproductive females, alongside a concurrent increase in fecundity. We conclude that no single policy measure is sufficient to recover population of M. mobular along the southeastern coast of India. Instead, combined protection through maximum bycatch mitigation and protection of nursery areas in no-take zones will be required for population recovery. This research demonstrates that recovery of overexploited populations often requires integrated resource management across life stages, and that the Critically Endangered M. mobular warrants urgent conservation action to avoid functional extinction.

Fishing pressure has substantially increased over time and elasmobranchs are among the most vulnerable marine taxa impacted. 'Small-scale' and 'large-scale' are terms frequently used to describe fisheries, yet definitions used across the globe are inconsistent. The global impact of small-scale fisheries on elasmobranch decline is increasingly evident. However, ambiguous vessel-capacity classifications undermine effective conservation management. Technological advancements have led to the emergence of medium-capacity vessels that sit between small and large-scale classifications, creating regulatory gaps that increase bycatch impacts on vulnerable elasmobranchs. Beyond vessel size, the gear specificities and practices also affect interaction with species caught incidentally, and can alter bycatch risk for vulnerable elasmobranchs. Manta and devil rays (collectively, mobulids) represent a pelagic ray group that includes species listed as Critically Endangered with high risk of extinction, largely due to bycatch threats. To prioritise fisheries management for conservation, we assess the contribution of fishing gear specifications and practices to mobulid bycatch as a case study in their largest fishery globally. We use a Huber-robust extension to a Hurdle negative binomial model to assess the impact of fishery characteristics and operational specificities on mobulid bycatch risk. We find that within the Food and Agriculture Organization (FAO) of the United Nations' broad international fleet classification of small-scale vessels based on overall length ([≤]24 m), the 'medium-capacity vessels' in India are twice as likely to catch mobulids than small-scale vessels. Further, increased fishing intensity, measured in five-day increments, doubles mobulid bycatch risk. Our results indicate the emergence of a distinct medium-capacity fishery class in rapidly developing blue-economy nations, shaped by rising technological capacity and exemptions from large-scale management measures. We propose a comprehensive re-conceptualisation of small-scale fisheries to ensure that advanced medium-capacity vessels are subject to management measures commensurate with their bycatch impact. Our recommended re-conceptualisation is complementary to FAO's SSF characterisation matrix and would promote fishery-level sustainability and enable bycatch risk mitigation for elasmobranchs, including manta and devil rays. Further, for congruence between elasmobranch demography and regulations, we recommend that fisheries management measures distinguish vessel capacities for elasmobranch bycatch risk and apply biologically relevant regulations to the associated fisheries scale.

Offshore wind farms are rapidly expanding to meet growing demands for renewable energy, with development expected to extend further offshore into deeper waters. This expansion requires a robust understanding of the long-term ecological consequences of offshore wind farms (OWFs) and how these may interact with ongoing climate change. We used the coupled hydrodynamic-ecosystem-biogeochemical water-column model (GOTM-ERSEM-BFM) to investigate ecosystem-wide responses to environmental changes associated with OWFs and climate warming. Specifically, we examined OWF-related scenarios of reduced benthic suspension-feeding activity, representing potential effects of contaminant emissions from OWFs, and reduced wind forcing, together with increased sea surface temperature. The scenarios were simulated individually and in combination to explore potential interactive effects. These scenarios were simulated at two contrasting locations in the North Sea, representing a well-mixed coastal site and a seasonally stratified offshore site. The coastal site exhibited comparatively modest ecosystem responses across the scenarios, whereas responses were generally stronger at the deeper offshore site. At the offshore site, changes in stratification altered vertical nutrient dynamics and contributed to pronounced differences in ecosystem responses between the surface and bottom layers. Our results demonstrate that ecosystem responses to OWF-related and climate-driven environmental changes are strongly dependent on local environmental conditions, suggesting that ecological consequences may differ substantially as wind farm development expands into deeper offshore environments.

Given unprecedented environmental change, Pacific salmonids are becoming increasingly threatened; however, genomic technologies provide an opportunity to assess Pacific salmonid resilience to on-going environmental change. Also, given increasing conservation and animal welfare concerns, non-lethal tissue sampling is emerging for assessing the physiological status of wild species. Relatively few studies, however, have compared the transcriptomic response of fish sampled non-lethally versus lethally for fish health and stress quantification. Here, we conducted a comparative gene transcriptional profiling study using 28 qPCR assays on the OpenArray platform as an osmoregulatory stress transcriptional profiling chip. We sampled both non-lethal (gill biopsies, skin swabs, and water [eRNA]) and lethal (whole gill and liver) tissue samples from Chinook salmon (Oncorhynchus tshawytscha) smolts exposed for 0 h, 24 h, and 72 h to freshwater (0 PSU), brackish water (15 PSU) or seawater (30 PSU). We observed that most assays showed higher qPCR amplification success in both non-lethal gill biopsies and lethal gill tissues, compared to other tissues. We found more significant differences in transcript abundance in traditional lethal tissues compared to non-lethal tissues. With increasing duration of salinity exposure, gene transcript levels were typically upregulated in seawater samples compared to freshwater samples for both non-lethal and lethal tissues. The targeted genes for both non-lethal and lethal tissues were significantly and positively correlated across time points. Our findings support the use of non-lethal tissue sampling to improve Chinook salmon hatchery rearing, inform hatchery release timing, and facilitate future field application for the conservation of wild stocks.

The management of Atlantic bluefin tuna (Thunnus thynnus) is currently defined by a long-standing life-history paradox: a stark divergence in maturation schedules between the Eastern and Western stocks. While the Mediterranean contingent matures at approximately 104 cm straight fork length (SFL; age 3-5), the western stock has long been characterized as a late-maturing, at [~]190 cm SFL (age 8+), and as late as age 15.8, based on size-at-catch data in the presumed exclusive spawning areas of the Gulf of Mexico. This discrepancy defies maturity states confirmed by endocrine hormones as well as established life-history principles that link metabolic energetics to reproductive biology. To resolve this critical issue in stock assessment, we present a sensitivity analysis based on the first histological evidence of spawning- capable individuals from 42 bluefin females (97-244 cm curved fork length or [~]95- 236 cm SFL) sampled in June 2025 within the Slope Sea, Northwest Atlantic. This historically overlooked, temperate spawning ground must be recognized and past estimates of stock productivity reevaluated. Our data provide a conservative estimate of length-at-50% maturity, L50 for females at 123.3 cm SFL, effectively reconciling the reproductive parameters of the two stocks based on histology. Our findings align established bluefin tuna metabolic and evolutionary symmetries in life history, irrespective of management boundaries. Incorporating this previously unrecognized spawning group (i.e., smaller, younger fish) calls for a substantial upward revision of Western spawning stock biomass (SSB). This biomass represents an intrinsic biological buffer that could contribute to the Atlantic bluefins adaptation and resilience. Appreciating demographic diversity is critical to accurately diagnosing stock vulnerability, ensuring that management frameworks protect long-term population stability in the face of climate-driven oceanographic shifts and ongoing exploitation pressure.

Fishery-dependent indices of abundance are often used to inform stock assessments, but fishing effort is generally not randomly distributed. Fishers concentrate sampling in locations expected to be profitable, leading to a form of preferential sampling that can bias model-based indices of abundance. We show that when the strength of preferential sampling is constant over time, it biases only the magnitude of an index, which is absorbed by estimated catchability parameters in most stock assessments. A more interesting case arises when the strength of preferential sampling changes over time; in these cases the index trend can be biased in a way that conventional catchability estimation cannot correct. Using simulations structured on long running trawl survey data from the west coast of the USA for shortspine thornyhead (Sebastolobus alascanus), we evaluate two structurally different methods for correcting time-varying trend bias: a joint spatiotemporal model of the density and sampling processes, and a discrete-choice model of fisher location choice. Our simulations include two mechanisms generating preferential biases: effort tracking local density, and effort responding to a spatially structured, but unobserved anomaly that also inflates catch. We show that the ability of the estimation methods to correct bias depends on the mechanism responsible for concentrating effort; while the joint model is robust to both data-generating mechanisms, the discrete choice model is only able to correct biases when the mechanism is anomaly-driven. As a real-world case study, we apply these corrections to simulated preferentially sampled data and include indices in the shortspine thornyhead stock assessment model. We found that uncorrected time-varying preferential sampling positively biased estimates of a major recruitment event and, to a lesser extent, unfished recruitment. This bias propagated through to bias in overfishing limits that grew as the population was projected forward. While bias-corrected indices still produced some positive biases in overfishing limits, these were substantially reduced compared to the naive approach. As the mechanism of preferential sampling is rarely known in advance, our results suggest that the joint model represents a robust default for correcting fishery-dependent indices of abundance.

A high proportion of the world's population relies on marine fisheries as a source of food and employment, highlighting the need for sustainable exploitation strategies. However, fisheries management commonly relies on single-species models that overlook ecological interactions and economic trade-offs, which may lead to stocks being exploited above sustainable levels. To address this gap, we developed a novel size-structured, multispecies bioeconomic module integrated within the spatially explicit, individual-based OSMOSE ecosystem model. OSMOSE represents exploited fish communities in which individuals interact through opportunistic, size-dependent predator-prey interactions which are explicitly incorporated into the bioeconomic framework. The bioeconomic model accounts for multiple species and size classes, allowing for size-dependent market prices. Fishing costs and profits are represented using an extension of the Gordon-Schaefer model to multiple interacting species, while consumer demand is modelled using a nested Dixit-Stiglitz utility function with three levels of constant elasticity of substitution for fish commodity, species and size classes. We present a method for estimating parameters for the bioeconomic module when empirical estimates are unavailable, using the North Sea OSMOSE configuration, which comprises 15 species. Our method successfully estimated the six bioeconomic parameters required to operationalise the model. Results indicate that differences in cost parameters were primarily associated with variability in species biomass rather than fishing gear, while fish prices were more strongly influenced by consumer's demand than by availability. This framework provides a basis for assessing the economic consequences of alternative climate change scenarios and supporting sustainable fisheries management.

In the springs of 2012-2013, Russian Federation scientists conducted aerial surveys of ice-associated seals (including bearded, ribbon, ringed, and spotted seals) in the Sea of Okhotsk and in Russian waters of the western Bering Sea. These instrument-based surveys used a combination of thermal imaging and digital photography to detect and photograph seals basking on sea ice. Initial estimates of seal distribution and abundance from these surveys have been published in Russian journals, but did not make adjustments for observation error. In this paper, we reanalyze these data with the goal of producing spatially explicit estimates of seal abundance that properly account for incomplete detection and species classification errors. Our analysis used estimated relationships between seal abundance and habitat variables to predict abundance in unsurveyed locations, and auxiliary data on detectability to model the observation process. Under this framework, we estimated that in 2012 there were approximately 185,330 bearded seals, 68,564 ribbon seals, 272,609 ringed seals, and 226,003 spotted seals in the western Bering Sea; in 2013, these numbers were 144,105, 39,435, 203,130, and 90,501, respectively. In the Sea of Okhotsk, estimated abundance was 218,740 bearded seals, 221,228 ribbon seals, 179,893 ringed seals, and 169,870 spotted seals (2013 only). These are the first credible estimates of ice-associated seals in the Okhotsk and western Bering Seas, and should be useful for population management and for measuring how density and distribution change as a function of decreasing Arctic sea ice. Declines in seal estimates in the western Bering Sea from 2012 to 2013 mirror patterns observed in the eastern Bering Sea during concurrent U.S. surveys and could represent a decrease in abundance or a substantial decrease in pupping and molting activity.

Increasing fishing pressure, including from small-scale fisheries, has caused declines in more than one-third of all elasmobranch species. Tackling conservation issues in small-scale fisheries requires interdisciplinary approaches due to the coastal community's interdependence on marine resources. To support inclusive policy change and fisher engagement, an understanding of the motivations driving fishers' operational choices (i.e., the retention of elasmobranch bycatch) is needed. We assess the motivational drivers behind bycatch retention of one of the slowest-growing and most vulnerable elasmobranch groups, manta and devil rays (collectively, mobulids), through a case study in India, their largest fishery in the world. We conducted a best-worst scaling survey in the fishery-intensive states of Tamil Nadu and Andhra Pradesh, which make significant contributions to mobulid landings on India's east coast. Our results suggest that fishers exhibit varied motivations for retaining mobulid bycatch across states. Financial motivation to sell mobulids for additional revenue was the most important motivator for bycatch retention in both states. In Tamil Nadu, the top three motivators were all financially driven, whereas in Andhra Pradesh, the top three motivators included both financial and non-financial attributes, such as nutritional importance and storage optimisation. As the first socio-economic study of mobulid fisheries in India, we show that motivations underlying bycatch retention decisions vary geographically and may be influenced by cultural differences between states and the socio-economic characteristics of decision makers. Based on identified fisher motivations, we provide context-specific recommendations to align conservation strategies with the values fishers derive from the mobulid fishery and encourage participation in conservation. These include subsidies for net repair to encourage mobulid release; promotion of a minimum price measure for sustainably sourced alternative species; quality improvement of target species; and increased awareness of national and international regulatory obligations (e.g., CITES, CMS, IOTC).

Chinstrap penguins (Pygoscelis antarcticus) in the Antarctic Peninsula and Scotia Arc regions (CCAMLR subareas 48.1 and 48.2) have experienced substantial declines, yet uncertainty remains about regional variation and conservation priorities. We applied a Bayesian hierarchical model to 1,072 nest counts from 194 colonies (1970 to 2024) to quantify population trends, estimate probabilities of exceeding IUCN Red List thresholds, and assess compensation potential across four locations. The regional population declined by 41.9% over three generations, with 91.4% probability of exceeding the 30% Vulnerable threshold but only 9.2% probability of exceeding the 50% Endangered threshold. Declines were spatially heterogeneous: South Shetland Islands (40.2% of regional population) declined by 74.7% with near-certainty of exceeding both thresholds, while South Orkney Islands showed stability with high uncertainty (median -5%, 95% CI: -31.5% to +36.8%). The probability of increasing colonies compensating for regional losses was only 7%. These results support a three-zone conservation strategy for CCAMLR's proposed Marine Protected Area: urgent protection for the South Shetland Islands, enhanced monitoring for South Orkney and Elephant Islands, and adaptive management for the Antarctic Peninsula. Our uncertainty-quantified framework provides evidence-based guidance for balancing krill fishery access with predator protection in a rapidly changing Southern Ocean.

As climate change continues to disrupt marine ecosystems, reliable body condition indices (BCIs) for sentinel megafauna species such as dolphins will become increasingly important tools for long-term ecosystem monitoring. We developed novel BCIs from routinely collected morphometric measurements and applied them to a 22-year dataset (1998-2019) of 597 stranded common dolphins (Delphinus delphis) from Northwest Spain. BCIs were calculated as residuals from Generalized Additive Models relating body length to girth and blubber thickness measurements, thereby controlling for body size effects. The indices were first validated against visually assessed nutritional status and then used to investigate long-term trends and potential environmental and trophic drivers of body condition. The girth-based BCI outperformed the blubber thickness-based index in predicting nutritional status. The indices differed in their sensitivity to confounding variables. Both indices revealed an increase in male body condition until 2009-2010 followed by a sustained decline through 2019, whereas no long-term trend was detected in females. By integrating data on climate variability (North Atlantic Oscillation), oceanographic conditions (upwelling intensity, sea surface temperature, chlorophyll-a), prey availability, and prey quality, we found evidence that changes in body condition was associated with climate- and oceanography-driven changes in prey communities and reductions in the quality of prey available to dolphins. Our findings suggest that body condition in common dolphins integrates signals across multiple components of marine ecosystems and can serve as a sensitive indicator of ecosystem change. Given growing reports of declining body condition in marine predators worldwide, the approach presented here provides a practical and transferable framework for long-term ecosystem monitoring using existing stranding network datasets.

Once central challenge in adopting ecosystem-based fisheries management (EBFM) is understanding and predicting the interconnected processes, feedbacks, and temporal dependencies that characterize ecosystem dynamics. Structural equation models and structural causal models (SEM and SCM) quantify interconnected relationships and evaluate causality from observational data but cannot readily accommodate the incomplete and irregularly sampled data typical of complex systems. Dynamic structural equation models (DSEM) estimate SEMs but accommodate lagged effects, missing data, and non-linear and non-stationary effects. However, there is little guidance regarding how DSEM can be used to support EBFM, particularly within governance and decision-making contexts. Here, we present three case studies that highlight distinct inferential goals for understanding ecosystem processes in the context of EBFM. First, we quantify ecosystem-level indicators to support monitoring of climate-driven ecosystem changes. Second, we examine whether hypothesized direct and indirect ecosystem linkages improve predictions of recruitment. Finally, we compare support for hypotheses of causal drivers of fish productivity. To provide practical advice, we synthesize lessons learned into a workflow to for others navigating DSEM. We suggest that the first step is identifying the inferential objective, which establishes the foundation for the remainder of the workflow, guiding the development of graphical models, model specification, and the selection of statistical and scientific validation steps (e.g., testing conditional independencies) needed to evaluate hypothesized causal relationships. By integrating observational data, expert knowledge, and mechanistic hypotheses within a unified framework, DSEM is a powerful tool for advancing EBFM, and more broadly, understanding the processes that govern complex ecosystems.

Okanagan sockeye salmon have shown a strong recovery over the past three decades, but the contribution of environmental conditions and management actions to this recovery has not been determined. We developed a hierarchical Bayesian model linking spawner abundances to fry emergence observations to evaluate how flow and water temperature during adult upstream migration and incubation periods influence spawner-to-fry production. Production declined by 62% in years with earlier onset and longer duration of periods when warm river temperatures created barriers to adult migration, indicating that migration conditions can have carry-over effects on reproductive success even when spawners successfully reach the spawning grounds. Additionally, production was 46% lower when flows fell above or below the management target range designed to minimize scour and desiccation during egg incubation. In contrast, we found little support for effects of pre-spawning flows or incubation temperature on production. These findings provide quantitative evidence that current flow management is increasing freshwater spawner-to-fry production and has likely contributed to the Okanagan sockeye recovery. Effective flow management may therefore help offset climate-driven impacts that increasingly threaten this population.

Largemouth bass (Micropterus salmoides) is a globally significant freshwater aquaculture species known for its rapid growth, high-quality flesh, and excellent nutritional value. Given the increasing incidence of hypoxia in its aquaculture setting, understanding the molecular mechanisms underlying gill adaptation to hypoxic stress is critical for improving resilience in this species. To achieve this, we employed full-length transcript sequencing using PacBio Iso-Seq and high-throughput Illumina RNA-seq to construct a comprehensive transcriptome profile. Histological analyses revealed apparent structural alterations in gill tissues under hypoxic stress (dissolved oxygen: 2.0 +/- 0.5 mg/L, duration: 96 h), including curved and swollen gill filaments, apoptosis, and epithelial cell vacuolation. Comparative transcriptomic analysis revealed pronounced shifts in the expression of genes involved in energy metabolism, angiogenesis, immune responses, cell proliferation, and apoptosis. Notably, the down-regulation of genes associated with cell cycle and proliferation suggests that M. salmoides may conserve energy by suppressing cell division under hypoxic conditions. In contrast, the increased expression of apoptosis-related genes, including Caspase 7, indicates that apoptosis may play a protective role to maintain tissue homeostasis under hypoxia. Furthermore, the suppression of chemokine-mediated immune pathways implies that hypoxia redirects energy toward essential metabolic processes at the cost of local immune responses. GO and KEGG enrichment analyses identified TNF- and chemokine-mediated signaling pathways as key regulators for tissue homeostasis and adaptive responses to hypoxic stress. These findings enhance our understanding of the mechanisms underlying hypoxia adaptation and provide valuable genetic resources for breeding strategies aimed at enhancing hypoxia tolerance in M. salmoides.

The Peruvian anchovy (Engraulis ringens) is a small pelagic fish. It is the largest singlespecies fishery in the world and it is used mainly for the production of fishmeal and fish oil. The Peruvian hake (Merluccius gayi) is a predatory demersal fish that is valued for direct human consumption, mainly as frozen products. In this study, I compared the response of both species to certain fishing mortality scenarios using a climatological set-up of the multispecies model OSMOSE for the northern Humboldt Current System. I observed that hake landings benefit from a decreased fishing pressure. In addition, the resilience of the anchovy fishery may increase if a higher threshold for their minimum catch size was implemented. The results of this study provide insights into better management strategies that could be beneficial for the two species based on their life-strategies.

Populations are exposed to multiple anthropogenic stressors simultaneously; however, the combined effects are poorly understood. Climate change is starkly impacting marine ecosystems and consequently fishes, with warming temperatures and increases in frequencies and durations of extreme climate events. Concurrently, plastics, such as nylon used in fishing industries, are contaminating marine waters at unprecedented levels, with detrimental effects on fishes. Here we studied the cumulative effects of warming and nylon microplastic fibres on the behavior and physiology of threespine stickleback (Gasterosteus aculeatus) by exposing fish to conditions of 15{degrees}C and 20{degrees}C and nylon concentrations of 0, 1, 10, and 100 mg/g (mg nylon/g food) for 4 weeks. Feeding rates responded complexly to multiple stressors, as increasing concentrations of plastic reduced feeding rates, with warming having an antagonistic effect. Furthermore, we observed "coughing" behaviors in response to ingestion of microfibres and a unique reselection tendency of food items previously selected by conspecifics. Under warming conditions, critical thermal maximum (CTmax) increased; however, exposure to plastics led to reductions in CTmax and thermal safety margins. Given these results, we anticipate reduced acclimation capacities, greater anxiety, and reductions in foraging efficiencies with increasing concentrations of plastic. Cumulatively, these stressors will yield greater energetic trade-offs and decreased accuracy in food selection with stark implications for marine ecosystem dynamics.

Pacific harbor seals (Phoca vitulina richardii) were surveyed throughout their range along Alaska coasts over a 28-year period. Twelve management stocks, delineated on the basis of evidence for demographic independence, were monitored for abundance and trends. We employed a two-stage Bayesian hierarchical analysis that integrated aerial survey counts with satellite-linked bio-logger haul-out timelines to account for the proportion of seals in the water and not visible to survey observers and cameras. Overall, harbor seals were abundant (201,122 seals in 2023) but, during the span of our study the population (stock) trends varied. The first half of our study was characterised primarily by growth, with a peak abundance of approximately 225,000 seals in 2015. Since then trends have been variable, with some stocks (e.g., Bristol Bay) showing continued growth while others (e.g. Prince William Sound, South Kodiak) declined. The recent regional declines coincided with observed climate anomalies (e.g., marine heatwaves) and the rapid retreat of tidewater glaciers. Our results provide a basis for managing this species in Alaska, which is protected under the Marine Mammal Protection Act; a vital nutritional and cultural resource for Alaska Native communities; and an important sentinel of change in the Northeast Pacific marine ecosystem.

1. Common dolphins (Delphinus delphis) are the most abundant cetaceans off mainland Portugal and a species of conservation and bycatch concern, so reliable abundance estimates are a management priority. Yet no single survey provides adequate spatiotemporal coverage: dedicated programmes offer sparse snapshots, while opportunistic programmes are spatially constrained by their routes. Integrating them is methodologically demanding, and the existing methods that do so in a single model estimate the density of animal groups, not of the individual animals that management often requires. 2. We develop a spatiotemporal marked log-Gaussian Cox process that integrates four structurally distinct surveys through a shared intensity surface, comprising environmental covariates, a latent spatial field, and survey-specific detection functions. Group size enters as a zero-truncated negative binomial mark with its own spatiotemporal field. We apply it to a dedicated aerial survey and three opportunistic ship-based programmes off mainland Portugal, comprising 162,514 km of on-effort transects and 1,756 sightings of 17,000 animals. We fit the model in a Bayesian framework with integrated nested Laplace approximations, yielding seasonally resolved group and animal density surfaces across the Portuguese Exclusive Economic Zone, and abundance estimates with fully propagated uncertainty. 3. Predicted animal density concentrated over the shelf and upper slope in every season, peaking northwest, and increased in shallower, cooler, more productive waters and over steeper seabed. Abundance nearly doubled from summer (77,000 [95% credible interval: 60,000, 98,000]) to winter (146,000 [99,000, 208,000]). Seasons shared 56% of the spatial field's variance, so effort from any programme in any season informed all others, and the seasonal contrast remained estimable despite uneven coverage. 4. Synthesis and applications. Our framework allows managers to combine dedicated surveys with existing platforms of opportunity to estimate animal density by season. Because group size is modelled explicitly, densities are estimated in animals rather than groups, as required for bycatch risk assessment and marine spatial planning. Because each survey enters through its own observation model, the approach accommodates programmes that differ in platform and protocol and transfers to any species or region where several surveys each cover part of a population.

Cold stress is a recurring risk in tropical and subtropical aquaculture nursery ponds, yet warning tools remain limited where continuous automated sensors are impractical. This study developed a low-resource cold-stress early warning framework using four years (2022-2025) of 6-hourly manual air and pond-water temperature readings from a Nile tilapia (Oreochromis niloticus) nursery pond in Cumilla, Bangladesh. Models were fitted on 2022-2023, validated on 2024 for threshold selection, and tested on 2025 as an independent year. Cold stress (daily mean water temperature <20{degrees}C) occurred on 133 days; heat stress (>35{degrees}C) on only 4 days. Air-water coupling was strong overall (r = 0.976) but weakened in winter (r = 0.776) and further within the 18-22{degrees}C boundary zone where cold-stress classification is most sensitive. Solar radiation only marginally increased boundary-zone classification AUC from 0.782 to 0.789. In 6-hour regression, the same-hour-yesterday baseline (MAE = 1.117{degrees}C) nearly matched Extreme Gradient Boosting (XGBoost) with MAE of 1.116{degrees}C, cold-zone bias +0.36{degrees}C, and train-test gap 0.02{degrees}C; Random Forest (RF) and Long Short-Term Memory (LSTM) had MAEs of 1.195{degrees}C and 1.244{degrees}C, respectively. For cold-stress classification, Multiple Linear Regression (MLR) gave the highest F1 (0.755), while XGBoost provided the more protective operating point, detecting 95 of 108 cold-stress readings at 6-hour lead time (sensitivity = 0.880, F1 = 0.739). XGBoost warning skill extended to 12, 18, and 24-hour lead times, with F1 scores of 0.722, 0.646, and 0.704, respectively. The framework converts routine manual thermometer readings into short-lead cold-stress alerts for nursery management decisions. Multi-pond validation is needed before deployment.