ABSTRACT The integration of separate sexes in stock assessment models represents an advancement towards more realistic modeling of interactions between fisheries and target species. However, increased model complexity can also introduce additional uncertainty into the modeling process. Assuming the same biological parameters for males and females in a single‐sex model may not be appropriate for species with significant sexual size dimorphism (SSD), such as the European hake ( Merluccius merluccius ). In this study, we investigated how single‐sex assessment models assuming biological traits (I) combined for males and females, and (II) the female‐only, compare to the population dynamics of a reference two‐sex model, which accounts for sex‐specific differences in growth and natural mortality ( M ). Results show that single‐sex approaches, particularly the female‐only model, may lead to a different population status, underscoring the sensitivity of assessment outputs and management quantities to sex‐structure assumptions in SSD species. However, when sex‐structured survey data are unavailable, a single‐sex combined model may still provide a reasonable approximation of a two‐sex dynamic. Additionally, the two‐sex model's specific indicators such as sex ratio‐at‐length and operational sex ratio (OSR) provide further insights into stock and fishery dynamics, facilitating more informed decision‐making and enabling the development of fleet‐tailored management strategies. Our findings underscore the need for two‐sex models in species with marked SSD and advocate for investment in sex‐specific data collection and refined diagnostic tools to accurately assess model adequacy.

Despite their potential to inform sustainable regional harvest and climate-resilient fisheries management, spatial stock assessment models remain underused for management advice. To identify barriers that inhibit broader use of these methods, we conducted a blinded international simulation experiment mimicking real-world stock assessment development when confronting spatial complexity. Seven analyst teams built spatially aggregated and spatially explicit assessment models using data simulated from high-resolution operating models based on Indian Ocean yellowfin tuna and Ross Sea Antarctic toothfish dynamics. Each team documented how assessment software platform, data analyses, model building approach, and diagnostics influenced model complexity and realism. A consensus emerged on key assessment building approaches: (1) conduct high-resolution data analyses to identify appropriate spatial structure; (2) start with simplified models and incrementally add complexity; (3) iteratively evaluate diagnostics to determine necessary spatial complexity; and (4) maintain models with different spatial structures to aid interpretation. The experiment also revealed several valuable insights for parameterising assessments, including consideration of data pre-processing with spatiotemporal models to better inform data-sparse regions; regression trees to identify fleet and spatial structure; trade-offs in complexity between productivity and movement dynamics to achieve tractable and stable model structures; and ensemble modelling approaches to address structural uncertainty. Our findings demonstrate that international collaborations and simulation experiments are crucial for addressing challenges in implementing spatial stock assessments and for evaluating whether their added complexity is justified given management objectives. Broader collaborations are encouraged to foster innovation in fisheries management and to help recognise the practical trade-offs between model parsimony and complexity.

Rebuilding fish stocks to levels above which they produce Maximum Sustainable Yield (MSY) is a management aim for all European commercially exploited stocks. Progress is typically monitored against the fishing mortality that produces MSY in the long term (F MSY), however, the corresponding biomass target (B MSY) is rarely evaluated nor reported. Here, we analyse a unique database of 73 quantitative ICES stock assessments to provide estimates of B MSY across the Northeast Atlantic and apply a Bayesian state-space model to estimate joint trajectories of F/F MSY and B/B MSY. Our results confirm that median fishing mortality has substantially decreased from its peak in 1999 to just below F MSY in 2020. Despite this, approximately half of the stocks remain fished above F MSY, with 36% exceeding 1.2 x F MSY. Biomass increased on average from below 0.5 B MSY in 2000 to 0.68 B MSY in 2020, but only 40% of stocks are currently above B MSY and only 35% have an age structure that is comparable with fishing at F MSY. Biomass relative to the ICES trigger point (MSY B trigger) indicates that more than 70% of stocks are currently within safe biological limits. However, using MSY B trigger as a surrogate for B MSY results in an over-optimistic classification of stock status, which conflicts with past levels of exploitation and may hinder stock rebuilding and the achievement of MSY objectives. Future projections from individual assessment forecasts predict further increases in B/B MSY under current F levels. However, to achieve B MSY by 2030, a 'perfect' implementation of the ICES Advice Rule would be required.

Reported landings from commercial fisheries are a main source of information on the removed biomass of a species and/or stock from the sea. In many fisheries, however, on-board processing to meet market demand causes a discrepancy between the landed weight and original live weight, necessitating the use of correction factors during data preparation for stock assessment and advice. One such fishery is for northern shrimp (Pan-dalus borealis) in the Skagerrak, Kattegat and northern North Sea. In this fishery, large, often female shrimp are boiled in salt water while on-board to maximise sale prices and scientists currently use a correction factor of 1.13 to account for the weight loss of shrimp from boiling. Here, we investigated this correction factor by conducting a weight loss experiment on-board the Swedish shrimp fishery between 2022 and 2024. We estimate that shrimps lose 10.26 % of their weight during boiling which corresponds to a correction factor of 1.11. Further, we find that weight loss likely varies on a seasonal basis, with more weight being lost during Q2 and Q3 compared to Q1 and Q4, potentially due to changes in the biology of the species as well as environmental conditions. Our findings suggest that the current correction factor used in the assessment of the stock should be reduced for the Swedish fishery and should preferably vary based on when the shrimp are caught. The experimental methodology used here could also be used to estimate weight loss in other shrimp fisheries.

Many animals show phenotypic flexibility in response to a seasonal environment. Especially migratory birds have been found to exhibit striking physiological and behavioural adaptations to overcome the negative impacts of environmental seasonality. Migratory songbirds often show extreme changes in feeding physiology and behaviour before embarking on a migratory flight, including predominantly insectivorous species switching their diet preference to a frugivorous one before autumn migration. Yet, little is known about frugivory during spring migration in temperate zones. In this paper, we report that five songbird species forage on the fruits of two Mediterranean plants, Prasium majus and Rhamnus alaternus, during spring stopover in the Tyrrhenian Sea. Analyses of faecal content showed that fruits of P. majus were generally preferred, with garden warblers (Sylvia borin) having the highest percentage of faecal samples containing seeds of both plants. Availability of ripe P. majus fruits increased over the sampling season and correlated positively with the number of faecal samples containing seeds. Our findings reveal a relevance of fruit at a temperate zone stopover site during spring migration for five passerine species. Frugivory during spring migration may represent an easy means for birds to acquire macronutrients, micronutrients and water. This may be especially important at resource-poor stopover sites and may aid birds' continuation of the northward flight towards their breeding grounds in a timely manner.

At the base of stock assessments, used to monitor invasive aquatic species and to sustainably harvest stocks, are estimates of body growth, a key parameter regulating animal populations. However, due to lack of data, obtaining these estimates can be challenging, but analytical approaches for 'data-poor' situations have been developed. Currently, the Pacific oyster (Magallana gigas) is spreading in northern Europe and a need for management strategies to control the invasion is evident. Using methods developed for data-poor situations, the von Bertalanffy growth function and electronic length-frequency analysis, we analysed 17,289 length measurements of wild Pacific oysters collected between 2007 and 2018 at five sites in Sweden to estimate its growth in temperate waters. We identified two distinct growth patterns, where individuals in habitats with high bivalve density grow faster in length compared to those in less dense habitats. Additionally, we found that Pacific oyster populations in Sweden are still growing towards their asymptotic lengths and that growth is reduced but not stopped during colder months. We conclude that our analysis constitutes the basis for future stock assessment and management of the species in areas with feral populations of commercial interest.

Ensuring the sustainability of fisheries worldwide requires that scientific advice remain effective even when data and capacity are limited. To address these challenges, we propose a hierarchical assessment framework (HAF) capable of integrating auxiliary information, such as empirical indicators for fishing pressure, within a Bayesian state-space biomass dynamic modelling framework. The aim is to provide risk-equivalent advice to ensure that management does not penalise data-limited fisheries with undue precaution (and loss of potential yield), nor expose them to a higher risk of overexploitation. To achieve this, we evaluated performance using classification skill metrics, such as true skill, for stock status relative to maximum sustainable yield (MSY)-based reference points. Results demonstrate that incorporating auxiliary data, particularly fishing mortality indices from periods of high exploitation, substantially improves the accuracy of stock status classification. Adoption of hierarchical assessment frameworks will support targeted data collection and evidence-based, adaptive fisheries management.

Modern management of fish stocks is based on integrating the precautionary approach with the maximum sustainable yield framework. It relies on accurate estimation of precautionary limits, defined as levels of spawning biomass where a stock has reduced reproductive capacity, and harvesting targets aimed to maximise future yields. Therefore, it is heavily depending on productivity assumptions. Most fish stocks are managed assuming that productivity will increase as the stock size decreases (i.e., density dependent compensatory stock and recruitment relationship). However, several biological and ecological processes will result in a decreased productivity below a certain population size, referred to as the Allee effect or depensation. Through a meta-analysis of 81 Northeast Atlantic fish stocks, we investigated the impact of assuming compensatory recruitment in the presence of depensation in fisheries management. Across life histories, depensation results in a 22% reduction of the fishing mortality rate leading to extinction. On average, the maximum reproductive rate per spawning biomass was found at 35% of BMSY, which was also the biomass where stocks have a 5% risk of extinction without fishing. Finally, the presence of depensation resulted in increased rebuilding times when stock spawning biomass falls below the limit reference point. When depensatory effects are present, assuming increasing productivity at low biomass will generally result in over-optimistic perceptions of rebuilding and stock status at biomass below 25% and 45% of BMSY in general, and for pelagic stocks respectively. When not accounted for, depensation will potentially lead to unsustainable harvesting practices of marine living resources.

Modern stock assessment models used to provide management advice on sustainable catches rely on unbiased catch data. Distortion of this data, intentional or not, may increase the uncertainty in the stock perception, jeopardize the assessment of marine resources, and compromise their sustainable management with negative ecological and socio-economic effects. In this study, we apply an analysis of anomalous numbers based on the Newcomb–Benford law (NBL) to test for fisheries catch misreporting. We focus on the Swedish small pelagic fisheries targeting herring and sprat in the Baltic Sea, which are known to be highly problematic due to the pronounced mixing of the two species in their catches and the existence of potential incentives for misreporting. The analyses also include fishery-independent data from international scientific surveys, which are used as standards for the interpretation of the anomalies in the commercial catch data. We demonstrate that data from two Baltic fishery independent surveys conformed to the NBL, while Swedish commercial catch data recorded at sea (logbooks) and onshore (landing declarations) did not, indicating inaccurate reporting of commercial catches. While non-conformity to the NBL may not be considered as proof of misreporting, and to determine the intentionality of misreporting, if any, goes beyond the scope of the paper, we discuss the possible reasons for the observed deviations from the model and recommend the application of this method for quality control of fishery data. Further research (i.e. testing new tools both for detection and estimation of misreporting) should be carried on this fishery with the aim of improving the accuracy of the reported catches. Furthermore, we open the discussion to whether the management should rely on less accurate but more spatially resolved or more accurate but spatially unresolved commercial data. The application of the NBL presented in this study can be readily implemented to other stocks and fishery as a supporting tool to investigate potential misreporting and contribute to improve our understanding of self-reported fisheries data.

In the Northeast Atlantic, the International Council for the Exploration of the Sea (ICES) provides scientific advice under the precautionary approach (PA) and maximum sustainable yield (MSY) principles. F-MSY, the exploitation level that achieves MSY in the long term, is derived in ICES through stochastic simulations with the software EQSIM for most of the stocks. The computed F-MSY is then conditioned on the PA such that fishing at F-MSY does not exceed a 5% probability of the spawning stock biomass falling below the limit reference point B-lim. We compared reference points estimated using EQSIM and a short-cut management strategy evaluation (MSE) tool (RPETool), which approximates a full-feedback control loop, and, differently from EQSIM, mimics the stock assessment advice process, including all data lags, and retains the original structure of the assessment model. Here, we showed that the simplifications of the management system and the assessment model, which are necessary for conducting simulations with EQSIM, result in the breaching of the PA for 3 of 4 recently benchmarked stocks. For the only stock for which the PA was not violated, the EQSIM estimate of F-MSY was still larger than the actual F-MSY estimated within the assessment model, and long-term yields were not maximized. Considering that EQSIM has been used since 2017 to derive reference points in ICES for more than 75% of the data-rich stocks, it is urgent that it is phased out and substituted by a more appropriate approach, like RPETool. Furthermore, the analysis highlights the asymmetry between increased risk of breaching B-lim when fishing at or above F-MSY and low risk in terms of the minimal loss in long-term yield when fishing below F-MSY, with <5% yield loss even if F were reduced to around 60% of F-MSY. Considering the wide ranges of additional uncertainties about the assessment model and the associated F-MSY estimate, we propose that it is time for a paradigm shift within ICES to advocate for F-MSY being the upper limit for advice on fishing opportunities rather than the target.

Migration is an energy‐intensive phase of birds' life cycle, often including the crossing of large ecological barriers during non‐stop flights. Corticosterone (CORT), an adrenocortical hormone also known as the stress hormone, generally rises at the onset of migration to facilitate and sustain high‐energy metabolism. Although birds can select favourable meteorological conditions at departure, weather variability en route may affect the migrants' energy reserves and their ability to cope with other stressors. This study investigated the effects of weather conditions on the physiological status of two nocturnal trans‐Saharan species, the common whitethroat Curruca communis and the garden warbler Sylvia borin , upon arrival at a stopover island after crossing the Mediterranean Sea during pre‐breeding migration. We assessed fuel stores and CORT variations in relation to tailwinds and air temperature experienced over the sea route. Birds that arrived at the stopover site with residual energy reserves after encountering moderate headwinds or lower temperatures had similar baseline CORT concentrations compared to those that migrated with tailwinds and higher temperatures. While both species exhibited a normal stress response to catching and handling, stress‐induced CORT levels were correlated with higher temperature only in garden warblers. Our study provides novel insights into CORT dynamics, suggesting that nocturnal migratory Passerines are not largely affected by weather variability across a marine barrier during pre‐breeding migration if they have sufficient energy reserves.

Growth and maximum age are two key parameters that inform resilience of fish populations to exploitation. Existing information on those for greater weever inhabiting the eastern North Sea is based on the analysis of whole otoliths. Here, we present a reanalysis using sectioned otoliths. The results reveal a different growth pattern and a higher maximum age than that previously reported. The higher maximum age makes greater weever populations more vulnerable to exploitation. Such information can serve as a basis for the estimation of the growth curve that can be used for future assessment of the species.

Migration is an important life-history strategy that is adopted by a significant proportion of bird species from temperate areas. Birds initiate migration after accumulating considerable energy reserves, primarily in the form of fat and muscle. Sustained exercise, such as during the crossing of ecological barriers, leads to the depletion of energy reservesand increased physiological stress. Stopover sites, where birds rest and restore energy, play a fundamental role in mitigating these challenges. The duration of resting at stopover sites is influenced by environmental and physiological conditions upon arrival, and the amount of body fat reserves plays an important role. While sleep is recognized as essential for all organisms, its importance is accentuated during migration, where energy management becomes a survival constraint. Previous research indicated that individuals with larger fat reserves tend to sleep less and favor an untucked sleep posture, influencing energy recovery and anti-predatory vigilance. We explored the relationship between sleep behavior and posture, metabolic state, and energy conservation strategies during migration in the common whitethroat (Curruca communis). We were able to confirm that sleeping in a tucked position results in metabolic energy savings, at the cost of reduced vigilance. However, whitethroats did not show alterations of their sleep patterns as a response to the amount of stored reserves. This suggests that they may not be taking full advantage of the metabolic gains of sleeping in a tucked posture, at least at this stage of their migratory journey. We suggest that, to achieve optimal fuel accumulation and maximize stopover efficiency, whitethroats prioritize increased foraging over modulating their sleep patterns.

Knowledge about sex-specific difference in life-history traits-like growth, mortality, or behavior-is of key importance for management and conservation as these parameters are essential for predictive modeling of population sustainability. We applied a newly developed molecular sex identification method, in combination with a SNP (single nucleotide polymorphism) panel for inferring the population of origin, for more than 300 large Atlantic bluefin tuna (ABFT) collected over several years from newly reclaimed feeding grounds in the Northeast Atlantic. The vast majority (95%) of individuals were genetically assigned to the eastern Atlantic population, which migrates between spawning grounds in the Mediterranean and feeding grounds in the Northeast Atlantic. We found a consistent pattern of a male bias among the eastern Atlantic individuals, with a 4-year mean of 63% males (59%-65%). Males were most prominent within the smallest (< 230 cm) and largest (> 250 cm) length classes, while the sex ratio was close to 1:1 for intermediate sizes (230-250 cm). The results from this new, widely applicable, and noninvasive approach suggests differential occupancy or migration timing of ABFT males and females, which cannot be explained alone by sex-specific differences in growth. Our findings are corroborated by previous traditional studies of sex ratios in dead ABFT from the Atlantic, the Mediterranean, and the Gulf of Mexico. In concert with observed differences in growth and mortality rates between the sexes, these findings should be recognized in order to sustainably manage the resource, maintain productivity, and conserve diversity within the species.

The Precautionary Approach to Fisheries Management requires an assessment of the impact of uncertainty on the risk of achieving management objectives. However, the main quantities, such as spawning stock biomass (SSB) and fish mortality (F), used in management metrics cannot be directly observed. This requires the use of models to provide guidance, for which there are three paradigms: the best assessment, model ensemble, and Management Strategy Evaluation (MSE). It is important to validate the models used to provide advice. In this study, we demonstrate how stock assessment models can be validated using a diagnostic toolbox, with a specific focus on prediction skill. Prediction skill measures the precision of a predicted value, which is unknown to the model, in relation to its observed value. By evaluating the accuracy of model predictions against observed data, prediction skill establishes an objective framework for accepting or rejecting model hypotheses, as well as for assigning weights to models within an ensemble. Our analysis uncovers the limitations of traditional stock assessment methods. Through the quantification of uncertainties and the integration of multiple models, our objective is to improve the reliability of management advice considering the complex interplay of factors that influence the dynamics of fish stocks.

ABSTRACTBiological reference points (BRPs) used in fisheries management do not include density‐dependent (DD) growth, with DD processes only considered in the stock recruitment relationship. Not accounting for DD on somatic growth has led to criticism that such BRPs underestimate the compensatory effects of DD at low stock size, and therefore risk foregone catch opportunities. Here, we analyse 81 stocks from the Northeast Atlantic for evidence of DD growth, defined as the process in which stock size affects somatic weight. We evaluate the following questions: (1) How many stocks have experienced instantaneous DD growth and do stocks of the same species display similar trends? (2) Is there a common instantaneous DD growth relationship shared by all stocks? (3) For stocks exhibiting significant instantaneous DD growth, can we quantify the strength of the relationship? (4) Is DD growth operating as an intra‐cohort process as opposed to an instantaneous effect? Results reveal that only the weight of recruits exhibits a common instantaneous DD growth while the other responses analysed show a positive, noncompensatory effect, suggesting that other processes are at work. All responses examined showed significant temporal autocorrelation, which, when not accounted for, suggest apparent instantaneous DD growth in several stocks. Comparison of instantaneous against intracohort DD growth showed an increase in the number of stocks with significant DD growth, although, as for instantaneous DD growth, this declined greatly when temporal autocorrelation was accounted for. Our results counteract the a priori assumption that DD growth compensation is related only to stock biomass or density, suggesting that DD growth should be dealt case‐by‐case. Consequently, management practices that aim to fish down stock biomass with the anticipation of triggering DD growth will be associated with greater asymmetric risks than keeping biomass at levels where replacement yield does not rely on it.

Larger and older fish contribute disproportionately to spawning and play an important role in the replenishment of exploited stocks. Fishing often removes specific size- and age-classes, with direct impacts on stock productivity and population resilience. Despite this, fisheries advice is commonly based on estimates of spawning stock biomass (SSB) and fishing mortality (F) and makes little reference to the importance of size and/or age structure. Consequently, there is a need for indicators of size and/or age structure to better inform fisheries management and help assess global sustainability goals. Here, we introduce a new age-based indicator ABI(MSY) that monitors age structure relative to the equilibrium age structure at F-MSY. We apply this new indicator to 72 commercially important stocks in the Northeast Atlantic, covering 26 species, which collectively contributed 86% of all commercial catches in the region in 2019. We estimate that 62% (45 stocks) currently have proportionally fewer older fish relative to F-MSY conditions, whereas 38% (27 stocks) have proportionally more older fish; we also note patterns with respect to geographic area and taxonomic family. Simulation testing demonstrated that ABI(MSY) is responsive to overfishing and generally tracks (with high sensitivity and specificity) a common measure of stock depletion, SSB relative to B-MSY. Throughout, we show that ABI(MSY) provides information on the age structure of exploited stocks that is complementary to conventional reference points for SSB and F. Further, the framework used to estimate ABI(MSY )make it well placed for integration into current advisory frameworks on fisheries management.

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