Canadian Journal of Fisheries and Aquatic Sciences

Many Sockeye salmon (Oncorhynchus nerka) populations have declined over recent decades, and climate change is likely to exacerbate these declines through direct and indirect ecological effects. The response to the associated environmental changes is likely to vary among life stages, populations, and regions. Quantitative estimates of climate change driven impacts that account for this variability could fill a critical gap and provide forward-looking insights into how sockeye are expected to respond to future climate-driven change across their lifecycle. To address this need we developed a hierarchical population dynamics model parameterized with juvenile, adult return and spawner abundance data from 13 sockeye salmon populations from Washington State to northern British Columbia. We used a formal causal inference framework that paired salmon abundance data with a suite of environmental covariates hypothesized to represent ecological conditions across the lifecycle. We used the model to estimate population-specific responses to each environmental driver, then combined parameter estimates with projections from down-scaled climate change models to estimate productivity responses to anticipated environmental change. We found that historical sockeye productivity was strongly associated with environmental covariates, which explained more interannual variability in return abundance than spawner abundance in most populations. However, the life stages and specific environmental covariates with the largest impacts differed among populations and regions, often displaying a latitudinal gradient. Increases in coastal ocean temperatures and mixed layer depth generally had negative effects though they varied among regions. Increased freshwater summer rearing and return migration temperatures had weaker but consistently negative effects. Under future climate conditions, projected changes in these environmental covariates are expected to result in substantial declines in productivity across most populations. Sockeye salmon display varying degrees of sensitivity to climate change across life stages, populations, and regions. Effective future management will require explicitly accounting for these life stage and population-specific responses.

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.

Capelin (Mallotus villosus), a key forage fish in the Northwest Atlantic, links zooplankton to predators including commercial fishes, seabirds, and marine mammals, yet its life-cycle movements in the Gulf of St. Lawrence (GSL) remain poorly understood. Between 2022 and 2024, otoliths from 927 individuals collected during and after spawning were analysed by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS). Building on previous work on regional structuring, seven trace elements (Li, B, Mg, K, Zn, Sr, Ba) were used to discriminate three regions. Early-life regional signatures were inferred through an edge-to-core approach, assigning otolith core chemistry to one of these regions using quadratic discriminant analysis. The core was treated as an integrated early-life signal (late-larval to early juvenile period) rather than a strictly natal signature. Spatial variation in core chemistry was consistent across cohorts, mirroring the stability documented on the otolith edge. Results revealed widespread dispersal alongside partial regional residency: individuals with northeastern early-life signatures showed the strongest correspondence between early-life and capture regions, whereas other regions were more connected. Fish sampled during spawning were more often reassigned to their inferred early-life region than post-spawning fish, a regional-scale homing-like pattern consistent with regional spawning fidelity. This coexistence of dispersive and resident strategies likely generates a portfolio effect buffering the population against environmental variability and localised reproductive failures.

Downstream migration and sea entry are periods of high mortality for sea trout smolts and migration timing is a critical aspect of survival. We aimed to investigate migration timing of PIT-tagged sea trout smolts across a latitudinal gradient in five freshwater systems across Europe: Norway, Sweden, Denmark, France and Portugal. In two systems, smolt migration was further examined to assess a) differences in sex, body size and condition between autumn and spring migrants; b) the influence of spatial origin within the stream; and c) relationships between individual body size and migration date. Tagged smolts were not detected migrating in the Portuguese watershed. Spring migration timing differed significantly between watersheds in Norway, Sweden, Denmark and France. Generally, there was a trend of earlier migration at lower latitudes. Autumn vs spring migration was examined in Gudso-Denmark. Autumn migrants were larger in both length and mass, with no differences in sex ratios or body condition. Fish originating from an upstream site were more likely to migrate in the autumn compared to the spring and vice versa. Size dependent migration was found in the Swedish system, Haga [a]-Sweden, with larger individuals migrating earlier in the spring than smaller individuals. Outward-migrating smolts were also more likely to originate from a downstream site than an upstream site. Overall, these results show both large-scale geographic and fine-scale individual influences on migration timing. Given that climate change may have large impacts on migration patterns in sea trout, understanding variability in migratory patterns across a latitudinal gradient is an important tool for predicting responses to environmental changes.

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.

Here, we report the first genetic confirmation of golden mussels (Limnoperna fortunei) in North America, and the subsequent development, optimization, and deployment of golden mussel eDNA monitoring procedures. Aquatic species invasions are economically costly, disrupt ecosystem functionality, and impact native aquatic communities. Early detection of new invasive species enables rapid response via implementation of effective eradication or control measures and is key for reducing harmful outcomes. Initial species detection and taxonomic identification can be aided by genetic methods that have high detection sensitivity and accuracy. Genetic methods such as environmental DNA (eDNA) sampling can be used to detect invasive species before they become established in new systems, providing an early alert system to inform resource managers. Golden mussels were first detected in North America in October 2024 near the Port of Stockton in the San Francisco Estuary (SFE). The SFE is particularly vulnerable to invasion due to the access and connectivity provided by the presence of engineering infrastructure and shipping lanes. Collaborative efforts between public agencies and academic institutions are underway to develop a coordinated detection and response plan. Early detection followed by a rapid response is the best defense against prolific invasive species, such as the golden mussel.

The moonfish Mene maculata (Bloch and Schneider, 1801), the sole extant species of the family Menidae, is widely distributed in the Indo-West Pacific. Although its spawning season has previously been inferred from seasonal variation in the gonadosomatic index (GSI), the histological basis for interpreting GSI as an indicator of spawning-capable status remains limited. Here we describe the gonadal structure of male and female M. maculata and evaluate how GSI and standard length relate to spawning-capable status based on germ cell development. The testis was lobular and exhibited an unrestricted spermatogonial distribution, a structure widely observed among neoteleosts, indicating that the phylogenetic distinctiveness of M. maculata was not associated with a distinctive testicular structure. In the spawning-capable female, oocytes at multiple developmental stages, from primary growth to oocyte maturation, co-occurred within the ovary, indicating asynchronous ovarian development. This finding suggests that M. maculata may be a batch spawner rather than a total spawner as previously inferred. The spawning-capable female had a GSI consistent with previously inferred spawning season estimates. By contrast, histologically examined males were spawning capable at GSI values lower than those previously associated with the inferred spawning season, suggesting that male spawning-capable status may persist beyond the period inferred from elevated GSI alone. This study provides the first histological description of reproductive biology in the phylogenetically distinctive M. maculata and establishes a histological basis for interpreting GSI as a reproductive indicator.

Knowledge regarding variation in habitat use among individuals is crucial for understanding population dynamics and for management and conservation measures. This is especially important for diadromous fishes that shift between habitats, being affected by external pressures and environmental change in different habitats over ontogeny. Herer, we assessed individual variation in habitat use of European eel along a salinity gradient, ranging from fully marine to freshwater in northern Europe, using otolith microchemistry data from >3600 eel together with established time-series segmentation and clustering methods. We show that eel display high degree of individual variation in habitat use. Assigned life-histories included coastal resident, freshwater resident, and coastal and freshwater habitat shifting individuals. Coastal resident eels were observed in a large range of salinities. Given the widespread occurrence of migration barriers in freshwater, it is unknown whether the coastal resident eel preferred that habitat, or if it was the only available habitat for them. Our findings nonetheless highlight the need to include coastal habitats when assessing population development and silver eel production of the critically endangered European eel.

Absorption of CO2 by global oceans is decreasing pH resulting in ocean acidification (OA). Impacts on shellfish have been documented in ecologically and commercially important species. We examined the influence of diet and OA between two populations of red abalone (Haliotis rufescens) a species of aquaculture importance and declining wild populations. Populations experience different exposure histories: strong upwelling (Van Damme, California [VD]) historically exposed to low-pH conditions and weak-intermittent upwelling (Santa Barbara, California [SB]). Abalone were cultured under control-pH or OA-conditions and fed crustose coralline algae (CCA) or diatoms used in aquaculture. We tested treatment effects of population, settlement diet, and OA-exposure on survival as influenced by larval-energy stores. Survival in both populations was enhanced by CCA when cultured under both treatment conditions; however, by later stages, this effect remained only for SB. SB had reduced post-settlement survival when cultured under OA-conditions, whereas post-settlement survival of VD was not. Diet affected the relationship between larval-energy and post-settlement survival; a positive relationship when fed diatoms and a negative relationship with CCA. The relationship between larval energy and post-settlement survival was stronger in VD. CCA enhanced juvenile growth in SB cultured abalone at both three-months and one-year post-settlement. Settlement diets can reduce the impacts of OA on early-life stages of abalone, but population differences driven by underlying energetics affect the consistency of this outcome. These findings illuminate the impacts from OA, suggesting populations may be at risk, and inform strategies for developing and sustaining shellfish aquaculture in the face of changing ocean conditions.

Space-for-time Cormack-Jolly-Seber (CJS) models have been developed to estimate survival of migrating animals that are imperfectly detected at spatially discrete sampling stations. However, space-for-time CJS models typically ignore survival over time and age-specific probability of movement, missing the diversity of life history strategies. To address these limitations, we extended space-for-time Cormack-Jolly-Seber models to explicitly incorporate time, age, and individual-level covariates to account for diverse life history strategies. We incorporate a sub-model that includes uncertainty in individuals age using a finite-mixture model. The detection and transition probabilities were parameterized using generalized linear models, facilitating flexible model specification and inclusion of spatiotemporal and individual covariates. We apply the model to detections of juvenile steelhead (Oncorhynchus mykiss) from two populations in the Snake River Basin in Idaho, USA, to estimate trends in survival with respect to population, age, time, and the length of individuals. Additionally, we generalized the model so that it can be applied to other systems and populations with different life history strategies and monitoring infrastructure.

Habitat degradation and biodiversity loss in the Black and Azov Seas necessitate improved tools for spatially explicit conservation planning. We employed stacked species distribution modelling (SSDM) to assess habitat quality for the three resident cetacean species, the common dolphin (Delphinus delphis ponticus), the bottlenose dolphin (Tursiops truncatus ponticus), and the harbour porpoise (Phocoena phocoena relicta), which serve as apex predators and indicators of ecosystem health. Occurrence data were compiled from the Global Biodiversity Information Facility (GBIF), and ensemble species distribution models (ESDMs) were constructed using nine algorithms within the SSDM framework, with eight environmental predictors extracted from Bio-ORACLE v3.0. Individual ESDMs demonstrated excellent predictive performance (AUC: from 0.82 to 0.83; TSS: from 0.65 to 0.67; prop.correct: from 0.82 to 0.83). However, the initial continuous stacking method (pSSDM) yielded low community-level prediction success (0.36), prompting evaluation of three correction approaches. The Probability Ranking Rule (PRR) substantially improved performance (prediction.success = 0.459, sensitivity = 0.704, Jaccard = 0.465), effectively mitigating the overprediction bias inherent in stacked models. Species richness mapping identified multi-species hotspots along the southwestern Black Sea shelf, the Crimean coast, the Kerch Strait, and parts of the eastern coast, while the deep central basin exhibited the lowest richness. Variable importance ranking revealed bathymetry as the primary community-level driver (41.2%), followed by dissolved oxygen (13.8%), sea surface temperature (11.9%), and salinity (10.4%). Species-specific importance patterns confirmed ecological niche segregation, with common dolphins favouring deeper offshore waters and bottlenose dolphins and harbour porpoises associated with shallower shelf environments. The moderate richness observed in the highly productive northwestern shelf, despite high nutrient inputs, may reflect a combination of natural factors (elevated turbidity, reduced salinity) and anthropogenic pressures (fisheries bycatch, shipping, coastal development, and military activity) that limit species co-occurrence. Our findings demonstrate that PRR-corrected SSDM provides a robust framework for mapping cetacean habitat quality and identifying conservation priorities in the Black and Azov Seas, offering an evidence-based tool to inform ecosystem-based management in this ecologically unique and increasingly pressured marine region.

Genomic prediction of complex traits is limited when phenotype records are restricted and when using linear models. Increasing the amount of phenotypic data with high-throughput, image-based phenotyping could result in better genomic prediction and stronger signals in variant detection. Here, we analysed phenotypic and genomic data from a selectively bred cohort of the Australasian snapper (Chrysophrys auratus) to identify genetic variants associated with growth traits. We used a high-throughput phenotyping pipeline to extract 13 measurements of size from images. Phenotypic correlations among image-derived and manually measured traits (weight, fork length), together with heritabilities, were analysed. All measurements were significantly positively correlated with each other, and heritability ranged from 0.20-0.38. Genome-wide association studies (GWAS) identified 28 growth-associated SNPs, while GBLUP was used to predict phenotypes, and XGBoost machine-learning models were used to jointly predict phenotypes and report important variants. Both GBLUP (mean R2 = 0.50) and XGBoost (mean R2 = 0.77) performed well on the training data, but performance dropped on testing sets (both = 0.11), which decreased further when accounting for genetic relatedness (both = 0.06). Despite this, approximately 20% of the genetic variance for growth traits was captured by the models, and feature importance from XGBoost reflected signals seen in GWAS. Our findings highlight the utility of integrating computer vision-based phenotyping with GWAS, GBLUP, and ML for trait prediction. Despite detecting shared biological signals as GWAS, genomic prediction faces challenges with population structure and relatedness that are inherent in breeding programmes of mass spawning species, including many aquatic species. Article summaryIncorporating genetic information into selective breeding programmes can accelerate gains but may also miss gene interactions in complex traits. Machine learning approaches, such as decision trees, can capture those relationships and potentially improve genomic predictions. We used high-throughput computer vision phenotyping to uncover biological signal for genetic growth variants involved in the Australasian snapper. Both types of models captured 18-40% of the genetic variation, but the prediction accuracies were hampered by the population structure in this cohort of mass-spawning fish.

Littoral mysids facilitate benthic-pelagic coupling through horizontal migration, yet quantitative monitoring in structurally complex habitats remains methodologically challenged where traditional active gears fail. We evaluated the efficacy of standardized light traps for monitoring littoral mysids (Neomysis integer, Praunus flexuosus) and mesopredatory three-spined sticklebacks (Gasterosteus aculeatus) in the northern Baltic proper, Baltic Sea. Using a paired experimental design with predator-exclusion and unmodified traps, alongside concurrent passive benthic trapping, we assessed abiotic drivers affecting catchability, biotic interactions, and statistical power to monitor changes in population size over time. Results indicated significant biotic interference: unmodified traps attracted high densities of sticklebacks, which reduced mysid catches by approximately 85% through predation or behavioural avoidance. Consequently, physical predator exclusion is mandatory for accurate mysid sampling. Generalized Linear Mixed Models (GLMMs) confirmed that catch rates for all taxa were primarily driven by night duration rather than water temperature. While passive benthic trap catches tracked metabolic activity (peaking in warm summer months), light trap efficiency peaked in spring and collapsed during summer, confirming that sampling efficiency was strictly limited by the short duration of the night. Simulation-based power analysis revealed a stark contrast in monitoring utility based on spatial aggregation. For highly aggregated mysids, the method demonstrated low precision (Power < 0.25 to detect a 50% decline), rendering it suitable primarily for detecting substantial population collapses (>90%). In contrast, for less aggregated sticklebacks, the method achieved a more robust statistical power (>0.80 for a 60% decline), validating light traps as a precise tool for monitoring these abundant mesopredators. We conclude that light traps fill a critical methodological gap for winter and early spring monitoring when traditional passive gears underperform. Appropriate abundance indices should be based on statistical models accounting for night duration and strictly employ physical exclusion barriers when targeting mysids.

Artificial intelligence (AI)-based image analysis can efficiently estimate fish length, but differences in devices, imaging conditions, operators, and AI models limit comparability among surveys. We propose a standardization framework that estimates a bin-specific error matrix from paired reference measurements and AI-derived lengths and applies it to standardize (correct) AI-derived length-frequency distributions. The Richardson-Lucy expectation-maximization algorithm was used, with the number of iterations selected via cross-validation. Simulations based on empirical length-frequency data from 110 species showed that standardization reduced relative bias and distributional discrepancy; median relative-bias and root mean square error ratios were below 1, and the performance was more affected by the amount of paired data than by the number of cross-validation folds. In real data from 957 Japanese jack mackerel, standardized AI-derived distributions approached human-observer histograms, although discrepancies remained in the range of 160-230 mm. The proposed framework provides a practical approach for improving the comparability of image-derived length-frequency data using paired calibration data, without retraining the underlying AI model.

The corticotropin-releasing factor (CRF) system is a major neural regulator of stress responses in vertebrates. However, stress-related roles for the CRF system in other tissues--and whether these roles vary between stressor types--remain unclear. To address this gap, we first characterized the CRF system in the gills and intestine of rainbow trout (Oncorhynchus mykiss) and then evaluated how it is transcriptionally regulated following either an immune (vaccination) or osmotic (seawater transfer) stressor. Additionally, since the CRF system is involved in food intake regulation, we also evaluated whether feeding state affects the intestinal CRF system. Vaccination against Vibrio anguillarum reduced CRF system activity in the intestine--as indicated by elevations in CRF binding protein transcripts paired with reductions in ligand (crfa2) and receptor (crfr1b) transcripts--but did not affect the gill CRF system. In contrast, seawater transfer caused the abundance of most CRF system transcripts to increase in the middle (but not posterior) portion of the intestine, while transcript levels of CRF binding proteins and receptors in the gills declined. Finally, levels of CRF system transcripts in the intestine varied with feeding state in a region-specific manner. In the middle intestine, transcript levels of most components declined with fasting and increased when feeding was resumed, whereas the opposite pattern occurred in the posterior intestine. Overall, our results implicate the peripheral CRF system as a stressor- and epithelial tissue-specific modulator of immune and osmoregulatory functions in teleosts.

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.

Environmental DNA (eDNA) has emerged as a promising tool for estimating fish abundance, yet linking eDNA concentration to true density remains a significant challenge in seasonal systems, where the signal is strongly influenced by temperature. We investigated whether eDNA can serve as an abundance index for three-spined stickleback (Gasterosteus aculeatus) in four coastal bays of the Baltic Sea (5.7-20.5{degrees}C, April-July 2023), by pairing eDNA sampling with two trap types of contrasting catchability. Light traps capture fish by phototactic attraction during darkness, so their catchability is driven primarily by night duration rather than temperature, while benthic traps respond to temperature through the same activity-driven mechanism as eDNA production. The temperature sensitivity of eDNA estimated from field data was far higher than physiological expectation (Q10 = 12.4, against a maximum metabolic rate benchmark of Q10 = 3.5), indicating that the field temperature signal reflects ecological change in addition to metabolism. We then compared how well three eDNA predictors tracked a combined trap-based abundance index: uncorrected eDNA, eDNA corrected with the temperature response constrained to the laboratory metabolic rate (a first-principles correction), and eDNA corrected with the response estimated from the field data. Uncorrected and first-principles-corrected eDNA were both strong predictors of abundance (standardised slopes of 0.45 and 0.43), whereas the field-corrected predictor was not (0.08). Uncorrected and first-principles-corrected eDNA performed comparably because temperature and abundance increased together over the season; the first-principles correction is nonetheless preferable, as it remains reliable when this covariation is unknown a priori. We conclude that estimating a temperature correction from field data should be avoided in seasonal eDNA monitoring, because it removes the abundance signal together with the temperature effect and assumes a stability in abundance that cannot be verified without independent reference data.

Fledging is a critical period of a seabird life cycle. Using satellite telemetry, we compared movements and survival proxies (transmission duration) of chinstrap penguin fledglings tracked in 2017 (n=8) and 2025 (n=17) relative to krill fishing vessel activity. In 2017, fishing vessels operated intensively near colonies during summer, resulting in early, frequent encounters (median 1.3 days post-fledging) and short transmission durations (median 9.2 days). In 2025, reduced fishing delayed encounters (median 10.0 days) and tripled tracking duration (median 24.0 days). Hidden Markov Models revealed that vessel encounters reduced the probability of transitioning from foraging to transit behavior ({beta} = -0.76), an effect stronger than the productivity ({beta} = -0.11). While 87.5% of 2017 fledglings ceased transmission prematurely within weeks (half of those right after entering areas intensively used by fishing vessels), 65% of 2025 fledglings survived beyond March, with half of those five transmitting until May after dispersing eastward to the South Orkney Islands. These findings suggest that spatiotemporal overlap with krill fisheries during the critical post-fledging window affected foraging behavior and was associated with shorter transmission durations. Our results support further research of post-fledging penguin ecology to better understand the potential impact of fishery, and, following the precautionary principle, support fishing seasonal protection of important areas during critical periods of krill predators life cycle.

A comprehensive understanding of life history is vital to successful species conservation and management. When different life history stages are accompanied by considerable morphological or cryptic variation, such as the egg and larval phases exhibited by most fishes, genomic tools are essential for identifying species so that early-life ecology questions can be studied. Genotyping-in-thousands by sequencing (GT-seq) has recently emerged as a targeted and efficient approach for species identification. We leveraged existing genomic and transcriptomic data to develop a GT-seq panel capable of differentiating the members of the Coregonus artedi complex, a radiation of salmonids in the Laurentian Great Lakes whose members are indistinguishable with mitochondrial DNA barcoding loci and are the focus of bi-national conservation initiatives. Our panel of 494 loci was able to assign fishes in the C. artedi complex to species and lake. We examined cross-amplification in other coregonines with overlapping distributions and found that congeneric Lake Whitefish (C. clupeaformis) cross-amplified at 94% of loci and confamilial Round and Pygmy Whitefish (Prosopium spp.) cross-amplified at 42% and 38% of loci, respectively. We adapted bioinformatic probes to account for Prosopium-specific variants including 22 new SNPs and developed a whitelist of 428 SNPs capable of distinguishing these whitefishes. Finally, we demonstrated performance by identifying 3,066 coregonine larvae and juveniles collected in spring 2019-2021 from Lake Superior. These results hold promise for future insights into the species-specific ecology of early life coregonines and demonstrate the flexibility of GT-seq panels, which may cross-amplify hundreds of informative genome-wide loci in related taxa.

Japanese chum salmon supported by one of the world largest hatchery programs have experienced severe declines in marine survival and egg size. To investigate the underlying mechanisms, we analyzed a 21-year time series (1999-2019) of reproductive traits of age-4 chum salmon from 13 rivers together with climate and salmon abundance data using a bootstrap-supported Bayesian network. Here, we assumed that environmental variables can affect the chum salmon populations, but not vice versa, and that there could be maternal effect on reproductive traits, but not the other way around. These constraints enabled us to infer the causal links that shaped the biogeography of North Pacific chum salmon. Global warming caused a decline in Japanese chum salmon abundance, resulting in the increase of the competing Russian chum, which in turn decreased the female body size, fecundity, and egg size of Japanese chum. These findings suggest that climate-driven warming may have exposed genetic effects of hatchery practices, contributing to fitness decline in Japanese chum salmon and the ecological reorganization of chum salmon populations in the North Pacific.