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Our general purpose is to support the use of known-biomass production models (KBPMs), illustrating their usefulness by addressing the evolution of surplus production (SP) over time and the factors affecting it (e.g. environment). We also demonstrate the utility of KBPMs for multispecies management objectives or for estimating maximum sustainable yield reference points without a stock recruitment function, among other worthwhile applications. To do so, we present different uses of KBPMs, illustrating their application on demersal species in the International Council for the Exploration of the Sea (ICES) area, specifically for megrim, white anglerfish and European hake stocks. The proposed analytical approach involved fitting single-species and multispecies KBPMs, conducting retrospective analyses and assessing the effects of environmental variability on SP. The findings show that, in general, stock SP increased after a decline in biomass and SP, except for white anglerfish in the southern area. Megrim stocks are the least productive, while hake and northern anglerfish are the most productive. Retrospective analysis revealed SP shifts in northern hake stock for reasons other than biomass variability. Hence, the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation (AMO), two key climate variability modes in the North Atlantic, were tested for their links to SP, revealing a positive connection between SP and AMO, although further research is necessary. Beyond the specific results of our particular KBPM application, our main conclusion is that KBPMs can serve as a tool complementary to more complex assessment models for resolving unaddressed issues and crosschecking available assessment results., Nuestro objetivo principal es promover el uso de los modelos de producción de biomasa conocida (KBPMs, por su sigla en inglés), destacando su utilidad para abordar la evolución de la producción excedente (SP, por sus siglas en inglés) a lo largo del tiempo y los factores que inciden en ella, como los aspectos ambientales. También demostramos la utilidad de los KBPMs en objetivos de gestión multiespecífica o en la estimación de puntos de referencia vinculados al rendimiento máximo sostenible, prescindiendo de una relación stock-reclutamiento, entre otras aplicaciones de interés. Con este propósito, se exponen diversos usos de los KBPM, ejemplificándolos a través de su aplicación en especies demersales de la zona ICES (International Council for the Exploration of the Sea), específicamente en las poblaciones de gallo, rape blanco y merluza europea. El enfoque analítico propuesto implica el ajuste de KBPM monoespecíficos y multiespecíficos, la realización de análisis retrospectivos y la evaluación de los efectos de la variabilidad ambiental en la SP. Los resultados muestran que, en términos generales, la SP de los stocks ha experimentado un aumento después de una disminución en la biomasa y la SP, con la excepción del rape blanco en la zona sur. Las poblaciones de gallo muestran la menor productividad, mientras que las de merluza y rape del norte son las más productivas. El análisis retrospectivo revela cambios en la SP del stock de merluza norte debidos a razones distintas a la variabilidad en la biomasa. Por lo tanto, se exploró la relación entre la Oscilación del Atlántico Norte (NAO) y la Oscilación Multidecenal del Atlántico (AMO), dos modos clave de variabilidad climática en el Atlántico Norte, y se identificó una relación positiva entre la SP y la AMO. No obstante, es necesario continuar con investigaciones adicionales para comprender completamente este comportamiento. Más allá de los resultados específicos derivados de nuestra aplicación de los KBPM, nuestra con

The proportion of mature fish at length is one of the most important population attributes when evaluating reproductive potential for fish stock assessment purposes. Bias in maturity ogive parameters can lead to fishery management decisions based on misspecified biological reference points. These parameters can vary spatially and temporally, and this variability should be understood and included in the assessment models. However, integrating this variability becomes challenging when specific spatial-dependent ogives cannot be used in the stock assessment model. Hence, this study proposes a novel use of a multivariate response Bayesian regression model, employing an integrated nested Laplace approximation to estimate a single global maturity ogive using data from various spatial areas. This model explicitly accounts for differences in the sampling process and combines in formation from different areas to estimate shared maturity ogive parameters using joint-likelihood procedures. The model is applied to the European hake stock in ICES (International Council for the Exploration of the Sea) Divisions 27.8.c and 27.9.a, serving as a practical guide. In this model, we have considered different predictors to handle the relationship between the probability of being mature and the length and year covariates. Our results suggest that the logistic formulation correctly captures the relationship between the probability of being mature and length. For year variability, including a year factor covariate or year random effect in the predictor model produces similar values of goodness of fit measures. Copyright © 2024 Canadian Science Publishing

The use of management strategy evaluation (MSE) to support fisheries decision-making has increased worldwide over the last thirty years. Management strategy evaluation fits well within the advisory process, providing stability and consistency with long-term management objectives. If successfully implemented, it allows understanding and assessing of the consequences of management options, makes trade-offs explicit, identifies strategies that work reasonably well in favourable and challenging times, and balances competing objectives. The depth and breadth of a given MSE approach fit in a continuum between desk MSEs and full MSEs, based on the degree of stakeholder and analyst participation required. Evidence shows that for MSE to deliver in the real world, participatory processes are a critical component exhibiting opportunities for improvement. In 2022, the Spanish Institute of Oceanography launched a research project ¿New tools for mathematical modelling in the scientific advice of Spanish fisheries (Math4Fish)¿. While the main goal is improving stock assessment models, it includes MSE developments for three species ¿ European hake (Merluccius merluccius), European anchovy (Engraulis encrasicolus) and common sole (Solea solea). During the implementation, it became evident that readiness for MSE influences outcomes. How ready managers, scientists and stakeholders are to use the MSE framework is somehow taken for granted. Readiness, however, goes beyond process design, technical expertise and models¿ fitness to encompass context-dependent attributes. This talk explores the critical features of the management system and the actors involved that need to be addressed. Building on the preliminary findings from the Math4Fish project, the notion of readiness assessment before developing MSE is introduced.

The two-sample problem refers to the comparison of two probability distributions via two independent samples. With high-dimensional data, such comparison is performed along a large number p of possibly correlated variables or outcomes. In genomics, for instance, the variables may represent gene expression levels for p locations, recorded for two (usually small) groups of individuals. In this paper we introduce TwoSampleTest.HD, a new R package to test for the equal distribution of the p outcomes. Specifically, TwoSampleTest.HD implements the tests recently proposed by (Cousido- Rocha, Uña-Álvarez, and Hart 2019) for the low sample size, large dimensional setting. These tests take the possible dependence among the p variables into account, and work for sample sizes as small as two. The tests are based on the distance between the empirical characteristic functions of the two samples, when averaged along the p locations. Different options to estimate the variance of the test statistic under dependence are allowed. The package TwoSampleTest.HD provides the user with individual permutation p-values too, so feature discovery is possible when the null hypothesis of equal distribution is rejected. We illustrate the usage of the package through the analysis of simulated and real data, where results provided by alternative approaches are considered for comparison purposes. In particular, benefits of the implemented tests relative to ordinary multiple comparison procedures are highlighted. Practical recommendations are given.

Small-scale fisheries (SSFs) are major contributors to global catches and local economies, yet SSFs have historically been under-represented in national and international policies. In the European Union (EU), more than 80% of the fishing fleet is considered small-scale, and Galicia (NW Spain) is one of the most fisheries-dependent regions in Europe, with around 4000 fishing vessels, of which ~90% are registered as artisanal vessels. However, due to various data limitations, there is a lack of formal assessment of the main commercial species that could be used to implement better management practices. To overcome this shortcoming, and considering that length-frequency data from fisheries catches are probably the most common source of demographic information, a number of length-based methods (LBM) are available as potential assessment tools for use in data-limited scenarios. Therefore, in order to provide insight into the stock status of the main fishery resources of the Galician SSF (12 species of Teleostei, two Chondrichthyes, two Crustacea and two Cephalopoda), we applied two of the most commonly used LBMs, namely length-based indicators (LBI) and length-based spawning potential ratio (LBSPR), and one of the few models that relax the equilibrium assumption, such as the lengthbased integrated mixed effects (LIME). The selected LBMs were applied to the individual size data collected by the Galician Regional Government through the on-board monitoring programme of the SSF fleet, managed by its Technical Unit for Small-scale Fisheries (UTPB), for the period 2000 - 2022. To get an idea of the performance of the LBMs, for each stock we compared the results of the data-limited assessment with time series of the abundance index resulting from the standardization of catch-per-unit-of-effort (CPUE) data collected by the UTPB. This study represents a major step forward in the development of a stock assessment and management framework for one of Europe’s most important SSF flee

Fishing is one of the most widespread and important human activities in coastal ecosystems and it plays a fundamental role in employment and the economy of coastal communities. However, in the period 2020–2021, the global outbreak of COVID-19 negatively affected fishing economic activity. Against this background, Andalusia (South of Spain) is an important region in which the resilience of different fishing exploitation systems can be studied, but within the same social and economic framework. Therefore, the main study aim was to investigate the resilience of fishing activity to the COVID-19 pandemic in two Andalusian fishing grounds (i.e. Atlantic and Mediterranean). We analysed daily landings and the first-sale prices of fresh fish of the most caught species in both fishing grounds, while taking into account the different seasonal behaviour of the fisheries. Generalised Linear Models were used to compare the data, which were obtained during periods in which the COVID-19 severity levels differed. These levels were implemented according to political measures. The final objective was to understand how the degree of industrialisation in the fleets can hinder or help maintain the economic activity of fisheries during major crises

Summary The Neotropics have vast river catchments with untapped hydroelectric potential, but there are multiple expected negative impacts of dams, including those on local food security and livelihoods. Yet, monitoring of dam effects on subsistence is rare, particularly during initial implementation. Our study assessed changes in human fish consumption near the Belo Monte Dam in the Brazilian Amazon during the period 2012-2021, which covers construction, operation and a severe El Niño-induced drought. Over time, fish became less common and were consumed in smaller amounts, even though fewer people shared meals. The largest changes occurred between 2013 and 2016 (post-construction but prior to full operation), resulting in a downward trend in fish consumption, particularly during the drought season. Adding more fish species to the diet did not increase consumption per person. These changes in fish consumption suggest that they stem from environmental impacts of the project (e.g., reduced river level), despite secondary effects from climatic events. These findings underscore the urgent need for comprehensive assessments of the social and ecological impacts of large infrastructure projects in the Amazon, along with sustainable and equitable management strategies to ensure food security and meet the needs of local communities.

Management strategy evaluation (MSE) generally involves defining a decision problem, specifying objectives, and simulating the managed system to help evaluate uncertainties, risks, and trade-offs of management alternatives. Stakeholders' involvement is a core component of MSE to design pragmatic and applicable management strategies that are robust to uncertainty and balance ecological, economic and social objectives. Knowledge advances and computational capabilities allow fisheries scientists to generate evidence practically and transparently. Transparency is a cornerstone fisheries management principle with inherent paradoxes (Wilson, 2009). For instance, assessment models can be used to build political options into the models as alternatives. Hence, scientists can deliver advice that makes explicit the trade-offs and consequences of policy objectives. Under this perspective, the Math4Fish project involves natural and social scientists , managers (Spanish General Secretariat for Fisheries) and representatives of the fishing sector to jointly define management strategies to be simulated in MSE environments for the European hake, Merluccius merluccius (Linnaeus, 1758), southern stock in the Iberian Peninsula (International Council for the Exploration of the Sea divisions 8c9a). Workshops were held to introduce the fishing sector and managers mathematical modelling tools to evaluate management strategies for hake, as well as to propose information to explore/simulate different scenarios. During our experience, the allocation of quotas based on selectivity criteria between fishing gears has emerged as a scenario worth exploring. The redistribution of resources between the different fleet segments is a sensitive issue that causes tensions. Scientifically, quota redistribution simulations can be carried out, and the results analysed and compared with the current situation, highlighting the scope and limitations of the analysis. This would benefit a structured dialogue on

[EN] European hake (Merluccius merluccius) is a commercially important resource in Iberian Atlantic waters. Despite the recovery plan implemented in 2006 and the multiannual management plan for western waters, fishing mortality is still higher than that corresponding to the maximum sustainable yield for the southern European hake stock. The biological processes underlying the dynamics of this stock and its life history traits are essential for assessing population productivity and resilience, making them basic information for management. We analysed the temporal variability of size at maturity (L50) of this species and the main factors influencing it in Atlantic Iberian waters from 1982 to 2019. The annual variability of L50 for each sex was modelled with generalized additive models, considering explanatory environmental variables (Atlantic Multidecadal Oscillation, North Atlantic Oscillation and sea surface temperature) and biological variables (biomass, spawning biomass at length and relative condition factor). The results showed that the L50 of males decreased by a total of 12.9 cm and L50 of females decreased by a total of 10.9 cm from 1982 to 2019. For females the significant explanatory variables were year, spawning biomass at length, biomass and the North Atlantic Oscillation, while for males only year was an explanatory variable. These results are important for understanding the status of the European hake population, signalling that L50 is a good indicator for predicting future population dynamics., [ES] La merluza europea (Merluccius merluccius) es un recurso comercialmente importante en aguas Atlánticas Ibéricas. A pesar del plan de recuperación puesto en marcha en 2006 y del plan de gestión plurianual de las aguas occidentales, la mortalidad por pesca sigue siendo superior a la correspondiente al rendimiento máximo sostenible de la población de merluza del sur de Europa. Comprender los procesos biológicos que subyacen a la dinámica de este stock y proporcionar información sobre los rasgos de la historia de vida es fundamental para evaluar la productividad y la resiliencia de la población, convirtiéndolos en información básica para la gestión. Analizamos la variabilidad temporal de la talla de madurez (L50) y los principales factores que influyen en ella, desde 1982 hasta 2019 en aguas Atlánticas Ibéricas. La variabilidad anual de L50 para cada sexo se modeló con Modelos Aditivos Generalizados considerando variables ambientales explicativas (Oscilación Multidecadal del Atlántico, Oscilación del Atlántico Norte y Temperatura Superficial del Mar), y variables biológicas (biomasa, biomasa reproductora por talla y factor de condición relativo). Los resultados mostraron que la de los machos disminuyó en un total de 12,9 cm y la L50 de las hembras disminuyó en un total de 10,9 cm de 1982 a 2019. Para las hembras las variables explicativas significativas fueron año, biomasa de desove por talla, biomasa y NAO, mientras que para los machos solo el año. Estos resultados son importantes para comprender el estado de la población de merluza europea, lo que destaca que la L50 es un buen indicador para predecir la dinámica futura de la población.

Southern European hake (Merluccius merluccius) is a quite relevant stock in social and economic terms in Iberian waters. Even though there are some knowledge gaps that have complicated the implementation of a data rich model to provide a sound catch advice and it is currently assessed with a data limited model. Due to the need for a new assessment model, it was decided to use Stock Synthesis (SS) (Methot and Wetzel (2013), as it is one of the main models currently used for age- and length-based species (such as the South Atlantic hake stock). As an integrated model, SS allows the input of incomplete trends of data from different sources, such as catch data, catch per unit effort (CPUE) and survey indices. Among the multiple configurations of SS, we can find the alternative of single biology (sex, growth and natural mortality), as established in the previous stock assessment model, or separate sexes. In addition, this model allows to indicate that each stock entity starts to grow in the first month of the year, but also different recruitment peaks can be specified. It is important to mention that i) European hake is a highly dimorphic species as females are considerably larger than males, ii) this stock presents different spawning peaks throughout the year and iii) information on the sex-separated size distribution and hence the sex ratio of the stock has been recently obtained from oceanographic surveys. For these reasons, alternative SS models with various configurations have been tested for this species. Results are presented and discussed together in order to find the best alternative for the assessment of this stock.

In the Iberian Coast region, the common sole (Solea solea) is considered a very relevant species due to its high commercial value. Despite its importance, the current status of this stock is still poorly known due to the scarcity of available data to apply formal assessment methods. In data-poor situations length-based methods have been widely applied to estimate biological parameters and to understand the dynamics of marine stocks. In this study we evaluate the status of common sole in the Iberian Coast region using the following three different length-based methods: (1) the length-based indicators, (2) the length-based spawning potential ratio and (3) the mean length-based mortality estimators. Overall, the three methods agree that this stock appears to be exploited at the maximum sustainable yield level, the immatures are well preserved whereas the proportion of large mature individuals is relatively low, although it has been increased in the last years. Assessing the status of this valuable stock through data-limited methods is the first step towards designing and implementing effective management measures.

The common sole (Solea solea) is a species of flatfish of great commercial relevance in the northern Atlantic Iberian waters. Although many studies investigated the early life-stage of this species, little is known on the adult phases and the size structure of the population. Here we provide an analysis of the spatiotemporal distribution of adult’s common sole occurrence, conditional-to-presence biomass and median length in northern Atlantic Iberian waters using a Bayesian approach and three different spatiotemporal model structures that characterize the fundamental distributional patterns of fish as either persistent, opportunistic or progressive. Results highlight that the distribution of common sole adults in the area has been persistent over the years and that is partially affect by the bathymetry. Three main abundance hotspots were identified coinciding with spatial closure areas restricted to the fishing activity. Additionally, results show that small specimens tend to aggregate in shallower waters, while larger specimens inhabit deeper waters. Understanding the spatiotemporal distribution of the common sole population could improve our knowledge of this species and help to design more accurate biomass index that could be used to calibrate stock assessment models.

Atlantic chub mackerel is a pelagic species present in the Atlantic Ocean that in recent decades has expanded northwards in the eastern Atlantic. Fish samples were collected in scientific surveys and commercial catches between 2011 and 2019. We analysed the geographical variation of the biological parameters (age, length, weight and condition), as well as the length-weight relationship, maturity-at-length and spawning season onset and duration in five geographical areas (from south to north): the Canary Islands, Gulf of Cadiz, western Portuguese coast, northwestern Spanish coast and Canta-brian Sea. The influence of sea surface temperature (SST) on fish length was modelled as a potential driver of geographical variability. All biological parameters increased progressively northwards, while the spawning season was delayed and prolonged with increasing latitude, from January in the Canary Islands to May-August in the Cantabrian Sea, when SST was between 15°C and 19°C. SST had a positive effect on length in three study areas and a negative one in two of them, suggesting that each group is at a different position within their thermal tolerance range. Deviance from the geographical pattern of some biological parameters in the Gulf of Cadiz suggests that it could be a hinge or mixing zone between Atlantic African, Mediterranean and Atlantic Iberian population components.

In the Iberian Coast region, the common sole (Solea solea) is considered a very relevant species due to its high commercial value. Despite its importance, the current status of this stock is still poorly known due to the scarcity of available data to apply formal assessment methods. In data-poor situations length-based methods have been widely applied to estimate biological parameters and to understand the dynamics of marine stocks. In this study we evaluate the status of common sole in the Iberian Coast region using the following three different length-based methods: (1) the length-based indicators, (2) the length-based spawning potential ratio and (3) the mean length-based mortality estimators. Overall, the three methods agree that this stock appears to be exploited at the maximum sustainable yield level, the immatures are well preserved whereas the proportion of large mature individuals is relatively low, although it has been increased in the last years. Assessing the status of this valuable stock through data-limited methods is the first step towards designing and implementing effective management measures

Length-based methods have been widely applied to estimate biological parameters and understand the dynamics of marine resource populations within data-limited stocks. However, to date few studies have tested the sensitivity of parameters in length-based methods examining stocks with different traits and fishery contexts. In the Bay of Biscay and the Iberian Coast ecoregion, SE Europe (International Council for the Exploration of the Sea - ICES, Divisions 8 and 9a), many commercial resources are considered data-limited, and either little is known about their fisheries stock statuses or gaps remain in currently available assessments. Therefore, this study focuses on two of the most used length-based methods, which ICES considers to be the most appropriate to evaluate data-limited stocks, namely length-based indicators (LBI) and the length-based spawning potential ratio (LBSPR). Both methods have been applied to assess the stock statuses of various relevant species in the study area, such as: the small-spotted catshark (Scyliorhinus canicula), European anchovy (Engraulis encrasicolus), blackspot seabream (Pagellus bogaraveo), pouting (Trisopterus luscus), pollack (Pollachius pollachius), and Norway lobster (Nephrops norvegicus). For each stock, model results were compared with available knowledge on their current status. Furthermore, this paper discusses whether unexpected results are related to violations of the main model assumptions (constant total mortality and recruitment, and logistic selectivity) or to a lack of representativeness of stock length composition. A sensitivity analysis was conducted on the two most important input parameters: L∞ (von Bertalanffy asymptotic average maximum body size) and M/k (ratio of natural mortality to von Bertalanffy growth rate). This analysis concluded that the variation/misspecification of both parameters (M/k and L∞) had a considerable impact on the results given by both methods, and that this effect is more significant in th

Increasing the knowledge of approaches to estimate the status of data-limited stocks is of crucial importance since the vast majority of stocks are data-limited, i.e., there is not enough data to conduct a fully integrated statistical catch-at-age or at-length assessment. Among the different data-limited methods, surplus production models (SPMs) are usually considered the most complete data-limited assessment methods since they are the only method that provides a full stock assessment. Due to high interest in the application of SPMs for assessing data-limited stocks, our contribution focuses on providing a practical review of these models and their corresponding characteristics. Additionally, we review the use of the surplus production concept in the “known biomass production models”, highlighting their potential through examples of relevant applications. After a general introduction to the formulation of SPMs, their framework and features, this review focuses on the SPMs most frequently applied by well-known marine research organisations: ASPIC (a stock-production model incorporating covariates), SPiCT (surplus-production model in continuous time) and JABBA (just another Bayesian biomass assessment). For each model, we provide details of its formulation and main features, in addition to evaluating the quality and characteristics of the available software. Based on this information, our comparative study highlights the advantages and disadvantages of each of the three SPMs. The conclusion provides recommendations for their use in the assessment of data-limited stocks, facilitating a decision about whether SPMs constitute an appropriate tool for guidance on and assessment of specific stocks. Finally, we evaluate which of the SPMs considered in this paper should be applied.

Surplus production models (SPMs) were among the assessment methodologies recommended for improve the reliability of stock assessments in data-limited situations, which only require time series of an index of expoitable biomass and catch data. In our study we analyze on two well- known SPMs: SPiCT (A Stochastic surplus Production model in Continuous Time) and ASPIC (A Stock-Production Model Incorporating Covariate), through simulated data which simulates the real dynamic of a fishery system. Different settings have been simulated, testing (1) the intensity of observation errors; (2) fisheries for which available historical data started after the start of the exploitation period; (3) the process error’s impact. A Montecarlo procedure has been used to compute the veracity of the estimated biomass trajectory, parameters and reference points. The derived results are compared to real values of our simulated population through measures such as the root of the mean square error (RMSE) and mean absolute percentage error (MAPE) to understand which factors affect the model performance and our ability to advise on sustainable management. The results obtained show how SPiCT allows obtaining more accurate estimates than ASPIC in almost all situations considered