Stock Assessment Methods Research Articles

Seasonal Spatio-Temporal Model Improves Refined Stock Assessment and Management of Japanese Sardine (Sardinops melanostictus) in the Northwest Pacific Ocean

Accurate estimation of fish stock abundance and exploitability is critical for effective fishery management; however, fishery-dependent data are often affected by temporal and spatial heterogeneities due to the seasonal migration of fish, posing challenges for refined stock management. Previous studies have largely ignored these spatio-temporal dynamics, assuming static populations. This study develops a seasonal spatio-temporal model for Japanese sardine (Sardinops melanostictus) in the Northwest Pacific Ocean (NPO), using fishery-dependent data from 2014 to 2022. Seasonal standardized abundance indices (spring, summer, autumn, and an overall average) were generated and integrated with the abundance maximum sustainable yield (AMSY) method for stock assessment. The performance of the AMSY method using a spatio-temporal index was compared with the conventional model-based index, showing the superiority of the spatio-temporal approach. Results indicate a gradual increase in sardine abundance, with a significant shift in the center of gravity toward the northeast. The stock is in a sustainable state with a 94.8–99% probability of recovery. Although the stock is recovering, careful management is advised to prevent future declines. This framework offers a novel approach for assessing distant water and coastal fishery resources.

Empirical validation of integrated stock assessment models to ensuring risk equivalence: A pathway to resilient fisheries management.

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.

Probability ogives for trends in stock biomass and fishing mortality from landings time series

AbstractMost fisheries are conducted without any scientific knowledge about the size and productivity of the stocks that support them. This navigation in the dark in most fisheries is a major obstacle in making them sustainable sources of nutrition for people in general and income for fishers and other economic actors along supply chains. Fisheries that have not been assessed generally are data‐intermediate and data‐poor, the latter usually having annual time series of landings as the single piece of data available. A major effort in the last two decades has been directed toward developing ‘catch‐only’ stock assessment methods, although some of these methods have been tested and found deficient. Here we provide a novel approach to using annual landing time series as the single source of data to qualitatively judge the condition of un‐assessed stocks using frequentist cumulative probability ogives, both in terms of stock biomass and fishing mortality. A meta‐analysis of the FishSource database allowed us to infer statistical patterns from hundreds of assessed fisheries and thousands of annual landings, biomass, and fishing mortality observations. Four stock‐management types were considered separately in the analysis: short‐lived and others (mid‐ to long‐lived) stocks, controlled or not controlled by catch limits. Obtained cumulative probability ogives provide clear evaluations of stock biomass and fishing mortality trends in all four stock‐management types, leading to actionable information on probable current status and future trends. Using these probability ogives, we developed decision trees that lead to qualitative scores on the exploitation status of un‐assessed stocks.

Building confidence: Developing image-based methods to incorporate fishery-collected data in the American lobster stock assessment

The American lobster, Homarus americanus, supports the most valuable single-species fishery in North America; however to-date, a reliable and robust method to determine age does not exist, and thus some of the more traditional catch-at-age stock assessment methods cannot be used to determine status. In lieu of this, the Atlantic States Marine Fisheries Commission’s American Lobster Stock Assessment Model uses a probabilistic growth transition matrix to determine how lobsters of different sizes will grow and recruit into the fishery. Developing and updating the growth transition matrix to reflect current growth dynamics requires estimates of molt increment and interval. Tagging studies are an inexpensive method to collect this type of information, but relying on fishing industry reported recapture data and buy-in can be challenging, resulting in varied return rates and uncertainty in measurement accuracy. Here, we report on a subset of recaptured lobsters released in the Gulf of Maine and Georges Bank regions between 2015 and 2020, where in addition to recapture locations, harvesters were encouraged to submit images of recaptured lobsters alongside a standard lobster gauge as a scale to estimate carapace length. Some fishermen were able to provide both direct measurements and images. Images were analyzed in ImageJ to estimate individual lobster carapace length (CL); and each image was assigned a quality score. For all groups, image-derived lengths were correlated with measured observations, regardless of the overall image quality, with only a slight underestimation at the maximum end of CL. This image-based method for length estimation provides high-quality length predictions regardless of image quality and can significantly increase the likelihood of harvesters contributing data with broad potential to engage commercial fisherman in collaborative science. Using this method we were able to expand the dataset of length records from this project by 251 or 33 %, providing additional data at a rate similar to tagging an additional 6000 lobsters.

Azov sea fishes stock assessment by swept area method through bootstrap

Recently driven changes in habitat conditions in the Azov Sea make classic applications of swept area method inconsistent. Swept area stock assessment method modification for stock estimation of aquatic biological resources through nonparametric bootstrap is presented. New approach is tested against classic calculated results of swept area method for next fish species: Azov anchovy, tulka, turbot and Black-Azov sea shad according to data collected during 2022. Results comparison of classic and modified through bootstrap stock assessment methods leads no significant deviations in mean value estimation. Maximum difference between mean estimates of stock size was 3,75%. Confidential intervals width difference between reviewed methods, in general, was not significant. Most valuable difference in confidential intervals was detected in BCa approach against classic method with quantile approach (due to methodological features of BCa in bias correction procedure). The new stock assessment approach for swept area method though bootstrap permit to calculate statistically valid estimates, their confidential intervals and perform input data validation. The absence of significant differences in the results by the classical and proposed methods indicates the further applicable possibility of classic method even in normality violation in source samples. The normality requirements in methodology of classic approach, probably, is redundant.

The Abundance оf Black Grouse in Northern Eurasia

This paper presents the estimate results of the average annual abundance of black grouse (Lyrurus tetrix L., 1758), made on the material of data bank (ISEA SB RAS) for groups of physico-geographical countries within the borders of the USSR 1990. On the East European and West Siberian plains, value of grouse abundance and total number were calculated on average separately for the first and second half of summer and in winter, mainly from 1960 to 2020, for physicogeographical countries – only for the first half of summer. The under-accounting of birds was revealed in the second half of summer on the both plains territory, which was made up with the help of additional calculations. As a result, value of the abundance and total number of birds were obtained for natural zones and subzones within Russia and the USSR, separately on the East European and West Siberian plains. A significant similarity of the grouse stock estimation results by weighted averages, separately by landscape groups, and by a simple average for the entire territory of a physico-geographical country or several of them in the first half of summer is shown. The second method of stock assessment compared with the first one gave results that differ for those plains within confidence intervals at a confidence level of 0.1. On the groups of physico-geographical countries territories in the first half of summer, the highest average annual values of the abundance and number of black grouse are appropriate of the European territory and the Urals as a whole, as well as in Western Siberia. The lowest values are typical for Central Asia and Kazakhstan.

Quantitative Assessment of Ailia coila (Hamilton, 1822) Fish Population in Kaptai Lake: A Length‐Based Approach

ABSTRACTThe Ailia coila, a small indigenous freshwater fish species in Kaptai Lake, plays a crucial role in providing employment, food, and financial security for the local people. With a high market demand, the average production of this species over the last 5 years reached about 112.27 metric tons. However, there has been a notable decline in Ailia coila fish production in Kaptai Lake in recent years. Therefore, to understand the current stock status of this species, this study employed a length‐based stock assessment method the “length‐based spawning potential ratio (LB‐SPR)”. Between August 2022 and March 2023, a total of 1219 individuals were collected through fortnightly sampling from two fish landing centers (BFDC fishery ghat and Kaptai boat ghat) and two local markets (Banarupa Bazar and Reserve Bazar). The maximum length of Ailia coila was recorded at 15.7 cm in total length, with an average length of 11.1 (±4) cm. The length‐weight relationship was estimated as W = 0.01084 L2.599 (R2 = 0.75). The value of shape parameter ‘b’ is smaller than three which indicate a negative allometric growth pattern. The estimated asymptotic length (L∞) and length at first maturity (L50%) were found to be 16.84 and 10.54 cm, respectively. The LB‐SPR revealed that the fishery is currently experiencing overfishing, with the spawning biomass (SPR = 32%) below the target reference point. The mean estimate of fishing mortality relative to natural mortality (F/M) was 3.07, more than three times the threshold F/M = 1, indicating extreme fishing mortality in this fishery. The estimated length at first capture (SL50%) was significantly higher than the length at first maturity (L50%), suggesting that the fishing is predominantly targeting mature fishes. To enhance the spawning biomass and ensure the sustainability of the fishery, it is imperative to reduce the current fishing pressure and implement appropriate management measures.

Economic valuation of selected ecosystem services in Islamabad Capital Territory (ICT), Pakistan.

Payment for ecosystem services (PES) is a mechanism where a consumer is able and ready to pay for the protection of the precise ecosystem service and there must be a provider such as local societies receiving an economic resource, who in return, must have the ability to maintain that ecosystem service. Economic valuation provides basis for payment for ecosystem services. Therefore, objective of this study was to evaluate tourism and carbon stock services of the Islamabad Capital Territory (ICT), Pakistan. Two forest zones (Chirpine and Scrub) of Islamabad capital territory (ICT) were selected for estimation of carbon stock and their carbon credits and carbon worth, a questionnaire-based survey was conducted for tourism as a payment for ecosystem services. The method for carbon stock assessment was systematic sampling for Chirpine forest whereas random sampling was done for scrub forest. The size of sampling plot was 17.84 m radius, and a total of 93 plots (49 Scrub zone and 44 Chirpine zone) was taken in the study area. The carbon stock of both zones (Chirpine and Scrub zone) is 22556.75 ton/ha (Chirpine 20105.79, Scrub 2450.96) and total carbon dioxide sequestered by both zone is 82557.72 ton/ha (Chirpine 73587.2, Scrub 8970.52), total carbon credits of both zone is 302160.87 (Chirpine 269328.97, Scrub 32831.9) and the carbon worth of both Chirpine and scrub zone is 4532418.92 $ (Chirpine 4039937.09$, Scrub 492481.83$). Similarly, from tourism point of view, in Shakar Parian, 94% tourists were agreed for PES whereas 6% were disagreed for the PES (the 6% tourist were disagreed to contribute for PES, 40% were agreed for Rs.5 contribution and 54% for Rs.10.). moreover, in Lake view Park, 97% tourists were agreed and 3% are disagreed (In Lake View Park 5% tourists were disagreed for the PES contribution whereas 32% were agreed for Rs.5 and 63% were for Rs.10). In Damen e Koh, around 87% tourist were agreed and 13% were disagreed, (24% were agreed for the contribution of Rs.5 and 63% tourists were agreed for the contribution of Rs.10). In Marghazar Zoo, 93% tourists were agreed (22% were agreed for contribution of Rs.5 and 71% tourist were agreed for contribution of Rs.10) and 7% are disagreed for PES whereas 7% tourists were not agreed for contribution. PES may implement to compensate forest and parks manager to ensure better management of the forests and parks. Due to prime location and scenic beauty of the ICT, it has huge potential for implementation of PES mechanism for sustainable forest management and conservation. Therefore, it is recommended that Capital Development Authority (CDA) Islamabad should devise a plan for implementation of PES in forests and parks of ICT for its sustainable management of recreational and forest resources.

Assessment of Seabream Fisheries Stock of Oman Using the Monte Carlo Catch Maximum Sustainable Yield and the Bayesian Schaefer Model Methods

The establishment of managerial approaches for the sustainable use of fishery resources depends on a critical understanding of the stock status. The Monte Carlo catch maximum sustainable yield (CMSY) method and a Bayesian state–space implementation of the Schaefer model (BSM) are recent, but widely used, stock assessment methods for data-limited situations. Here, CMSY and BSM were used to evaluate the state and exploitation level of the seabream population. Collections of catch and effort data from 1988 to 2021, pertaining to time series, were obtained from the Fishery Statistics Book published by the Ministry of Agriculture, Fisheries and Water Resources of Oman. The CMSY and BSM results were similar, indicating that the seabream stock of Oman was overfished, as B/BMSY = 0.96 (<1) and F/FMSY = 1.25 (>1). The probability that the stock was being overfished and undergoing overfishing in 2021 was 53%, while the probability that the stock was healthy (high biomass and low fishing pressure) was only 16.2%, when the target should be higher than 75%. The conclusions are of a preliminary nature owing to the utilization of comparatively new methodologies employed to generate them, which commonly validate the condition and utilization of the populations under investigation. Our research suggests that the seabream population in Oman is overfished, and reducing fishing activity is necessary to restore its abundance.

Low optimal fisheries yield creates challenges for sustainability in a climate refugia

AbstractReducing resource depletion and promoting ecosystem‐based management are considered key climate change adaptation policies. Therefore, the resource status of an identified climate refugia in a semi‐enclosed bay on the Kenya–Tanzania border was evaluated for sustainability. Both fisheries stock and catch assessment methods found low production and excess effort. Stock recovery in closures (up to 45 years) determined the best‐fit r and K values, which established a maximum sustainable production (MSY) of 2.98 ± 0.45 (SEM) tons/km2/year. Stock estimates in the bays' fishing grounds indicated that biomass was below the MSY and predicted to produce 1.8 ± 1.0 (SEM) or 1.1 ton/km2/year below the optimal MSY. However, landed fish at five studied fishing villages varied greatly from 0.22 to 2.9 tons/km2/year. MSY in the refugia was therefore considerably lower than estimates in nearby ocean‐exposed locations, which has been estimated at 5–7 tons/km2/year. Therefore, low to modest capture rates of fish will be required to allow the recovery needed to achieve sustainability and restore the refugia's ecology. The refugia's highest stocks and near‐MSY yields were captured in the national reserve. Therefore, broader implementation of the reserve's gear‐restriction policies should restore fisheries. High spatial variability in yield patterns indicate interactions between fisheries management, compliance, trade connections, and governance. In climate refugia, reducing cumulative impacts will require knowing and managing for lower fisheries production limits.

New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY++ method

Following an introduction to the nature of fisheries catches and their information content, a new development of CMSY, a data-limited stock assessment method for fishes and invertebrates, is presented. This new version, CMSY++, overcomes several of the deficiencies of CMSY, which itself improved upon the “Catch-MSY” method published by S. Martell and R. Froese in 2013. The catch-only application of CMSY++ uses a Bayesian implementation of a modified Schaefer model, which also allows the fitting of abundance indices should such information be available. In the absence of historical catch time series and abundance indices, CMSY++ depends strongly on the provision of appropriate and informative priors for plausible ranges of initial and final stock depletion. An Artificial Neural Network (ANN) now assists in selecting objective priors for relative stock size based on patterns in 400 catch time series used for training. Regarding the cross-validation of the ANN predictions, of the 400 real stocks used in the training of ANN, 94% of final relative biomass (B/k) Bayesian (BSM) estimates were within the approximate 95% confidence limits of the respective CMSY++ estimate. Also, the equilibrium catch-biomass relations of the modified Schaefer model are compared with those of alternative surplus-production and age-structured models, suggesting that the latter two can be strongly biased towards underestimating the biomass required to sustain catches at low abundance. Numerous independent applications demonstrate how CMSY++ can incorporate, in addition to the required catch time series, both abundance data and a wide variety of ancillary information. We stress, however, the caveats and pitfalls of naively using the built-in prior options, which should instead be evaluated case-by-case and ideally be replaced by independent prior knowledge.

New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY++ method

Following an introduction to the nature of fisheries catches and their information content, a new development of CMSY, a data-limited stock assessment method for fishes and invertebrates, is presented. This new version, CMSY++, overcomes several of the deficiencies of CMSY, which itself improved upon the “Catch-MSY” method published by S. Martell and R. Froese in 2013. The catch-only application of CMSY++ uses a Bayesian implementation of a modified Schaefer model, which also allows the fitting of abundance indices should such information be available. In the absence of historical catch time series and abundance indices, CMSY++ depends strongly on the provision of appropriate and informative priors for plausible ranges of initial and final stock depletion. An Artificial Neural Network (ANN) now assists in selecting objective priors for relative stock size based on patterns in 400 catch time series used for training. Regarding the cross-validation of the ANN predictions, of the 400 real stocks used in the training of ANN, 94% of final relative biomass (B/k) Bayesian (BSM) estimates were within the approximate 95% confidence limits of the respective CMSY++ estimate. Also, the equilibrium catch-biomass relations of the modified Schaefer model are compared with those of alternative surplus-production and age-structured models, suggesting that the latter two can be strongly biased towards underestimating the biomass required to sustain catches at low abundance. Numerous independent applications demonstrate how CMSY++ can incorporate, in addition to the required catch time series, both abundance data and a wide variety of ancillary information. We stress, however, the caveats and pitfalls of naively using the built-in prior options, which should instead be evaluated case-by-case and ideally be replaced by independent prior knowledge.

Rapid approach for assessing an unregulated fishery using a series of data‐limited tools

AbstractObjectiveFisheries provide countless benefits to human populations but face many threats ranging from climate change to overfishing. Despite these threats and an increase in fishing pressure globally, most stocks remain unassessed and data limited. An abundance of data‐limited assessment methods exists, but each has different data requirements, caveats, and limitations. Furthermore, developing informative model priors can be difficult when little is known about the stock, and uncertain model parameters could create misleading results about stock status. Our research illustrates an approach for rapidly creating robust initial assessments of unregulated and data‐limited fisheries without the need for additional data collection.MethodsOur method uses stakeholder knowledge combined with a series of data‐limited tools to identify an appropriate stock assessment method, conduct an assessment, and examine how model uncertainty influences the results. Our approach was applied to the unregulated and data‐limited fishery for Crevalle Jack Caranx hippos in Florida.ResultResults suggested a steady increase in exploitation and a decline in stock biomass over time, with the stock currently overfished and undergoing overfishing. These findings highlight a need for management action to prevent continued stock depletion.ConclusionOur approach can help to streamline the initial assessment and management process for unregulated and data‐limited stocks and serves as an additional tool for combating the many threats facing global fisheries.

A simulation-based option to assess data-limited fisheries off West African waters

Most sophisticated stock assessment models often need a large amount of data to assess fish stocks, yet this data is often lacking for most fisheries worldwide, resulting in the increasing demand for data-limited stock assessment methods. To estimate fish stock status, one class of these data-limited methods uses simply catch time series data and, in other instances, life history information or fishery characteristics. These catch-only methods (COMs) built differently are known to make assumptions about changes in fishing effort and may perform differently under various fishing scenarios. As a case study, this paper used European anchovy (Engraulis encrasicolus) caught in the northwest African waters, though very economically and ecologically important, but still unassessed. Our study investigated the performance of five COMs under different fishing scenarios using as a reference the life-history information of the European anchovy captured in this region of the Atlantic. Hence, the present study developed a simulation approach to evaluate the performance of the five COMs in inferring the stock biomass status (B/BMSY) with consideration of different fishing scenarios under prior information true to anchovy. All five COMs mostly underestimated B/BMSY throughout the simulation period, especially under constant fishing mortality, and in the last five years of the simulation during all fishing scenarios. Overall, these COMs were generally poor classifiers of stock status, however, the state-space COM (SSCOM) generally performed better than the other COMs as it showed possibilities of recovering an overfished stock. When these methods were explored using actual anchovy catch data collected in the northwest African waters, SSCOM yielded results that were deferred from the other COMs. This study being the first to assess this species’ stock in this area using a suite of COMs, presents more insights into the species stock status, and what needs to be considered before scientifically putting in place management measures of the stock in the area.

Eulachon migration patterns in the lower Fraser River revealed through acoustic telemetry

AbstractObjectiveThe Fraser River in British Columbia, Canada, historically supported productive Indigenous, recreational, and commercial fisheries for Eulachon Thaleichthys pacificus. Although Eulachon spend most of their lives in the marine environment, they spawn in freshwater and it is hypothesized that habitat degradation in the Fraser River has contributed to population decline. A greater understanding of Eulachon life history strategies is necessary to develop species recovery strategies. The purpose of this study was to provide insight into population demographics, migration timing, residence time, travel speed and distance, and movement patterns of Eulachon traveling in the Fraser River by conducting index netting and acoustic telemetry.MethodsIn total, 244 Eulachon were acoustically tagged at the mouth of the Fraser River, and their movements were monitored using acoustic receivers in the lowermost 70 km of the Fraser River and in the Pitt River (a tributary to the Fraser River) over a 2‐year period.ResultTagged Eulachon displayed heterogeneous movement behaviors and a protracted migration period between February and May. Eulachon index gill netting revealed three discrete migration groups matching traditional ecological knowledge from Indigenous knowledge holders. There were shifts in population demographics, with sex ratios changing from predominately males to females throughout the migration. Residence time within the estuarine salt wedge and river was short. Upstream travel speeds varied significantly between sexes and slowed as fish traveled upstream.ConclusionOverall, Eulachon travel speeds, travel distances, and residence times, along with size and sex effects, provided insights into movement patterns. These results will increase our understanding of sex‐specific risks related to instream disturbance, harvest, and predation and will inform management decisions regarding protection of critical habitats. The observed patterns highlight the need for stock assessment methods to consider all discrete migration groups and will assist in prioritizing species recovery efforts.

Spatially explicit stock assessment uncovers sequential depletion of northern shrimp stock components in the North Sea

Abstract Space is a critical component of fisheries management. Despite this, very few of the world's fish and shellfish stocks are currently assessed using methods that are spatially structured. In the Northeast Atlantic, northern shrimp in the North Sea and Skagerrak, is currently assessed using a spatially structured assessment model. This metapopulation model includes two spatial units (the Norwegian Deep and the Skagerrak), however, in the recent past, the fishery on northern shrimp in the North Sea also occurred in a third neighbouring fishing area, the Fladen Ground. Here, we have reconstructed the dynamics of northern shrimp in the Fladen Ground using historic landings, a standardized commercial index of abundance and fragmented survey data and integrated this third spatial unit into the assessment model of the stock. In doing so, we find evidence of sequential spatial depletion, whereby high rates of fishing mortality have successively eroded stock components in a west to east pattern of overexploitation and produced cryptic collapses. This finding is the first documented case of sequential spatial depletion in the Northeast Atlantic, a phenomenon that could be common and largely overlooked by stock assessment methods that are inherently non-spatial.

Data-poor stock assessment of Narrow-Clawed Crayfish (Pontastacus leptodactylus) in Keban Dam Lake (Türkiye) Using CMSY Method

In this study, as a data-poor fish stock assessment method CMSY was used to assess the current stock status of the Keban reservoir crayfish stock due to not having further data set for using the data-rich models. A total of 27 years catch data (from 1995 to 2021) was used in the analysing process of study. Estimated CMSY model parameters with confidence intervals are as follows: r=0.426 (0.357 - 0.509) year-1, k=146 (118 - 180) ton, MSY=15.7 (13.0 - 18.0) ton, B2021=77.9 (59.5 - 86.7) ton, BMSY=72.8 (58.9 - 89.9) ton, F2021 = 0.295 (0.265 - 0.386) year-1, FMSY = 0.213 (0.179 - 0.254) year-1, B2021/ BMSY = 1.07 (0.818 - 1.190) and F2021/FMSY = 1.38 (1.240 - 1.81). Our study has found that the crayfish population in the Keban reservoir has been in decline due to overfishing since the late 1990s. However, the population has shown signs of recovery since 2013 due to reduced fishing activity. After all overexploitation occurred again in 2021. Our analysis also showed that the current quota of 30.5 tons is significantly higher than the MSY of 15.7 tons. Therefore, it is recommended to reduce the crayfish quota to 15.7 tons in order to sustain the population and prevent further decline.

Management Suggestions Based on a Data-Poor Stock Assessment Method to Avoid an Artisanal Fishery Collapse in Mexico

Fishing is a beneficial activity for populations settled near bodies of water. It can be split into industrial and artisanal fishing; the latter is more important from global, cultural, economic, and social points of view. Mugilids are of great commercial interest for artisanal fisheries due to their wide distribution and diverse uses; in Mexico, this resource stands out because it ranks fourth in the specific composition of catches and has shown a growing trend in yields in recent years (2008-2020). Therefore, an evaluation of the stock and behavior of the fisheries were undertaken in support of resource sustainability. We suggest that an active regulation measure be taken along with already existing passive measures. The exploitable biomass was estimated at 12,040 t, BMSY=11,424 t, and MSY=2,900 t. The resource is in decline with a tendency to overexploitation, and it could collapse if no action is taken. Therefore, we propose incorporating a temporal ban and an annual catch quota of 2,900 t to the current regulation, as well as using the methods and parameterization in this study for future evaluations.

Using the best of two worlds: A bio‐economic stock assessment (BESA) method using catch and price data

AbstractReliable stock assessments are essential for successful and sustainable fisheries management. Advanced stock assessment methods are expensive, as they require age‐ or length‐structured catch and detailed fishery‐independent data, which prevents their widespread use, especially in developing regions. Furthermore, modern fisheries management increasingly includes socio‐economic considerations. Integrated ecological‐economic advice can be provided by bio‐economic models, but this requires the estimation of economic parameters. To improve accuracy of data‐limited stock assessment while jointly estimating biological and economic parameters, we propose to use price data, in addition to catches, in a new bio‐economic stock assessment (‘BESA’) approach for de‐facto open access stocks. Price data are widely available, also in the Global South. BESA is based on a state‐space approach and uncovers biomass dynamics by use of the extended Kalman filter in combination with Bayesian estimation. We show that estimates for biological and economic parameters can be obtained jointly, with reliability gains for the stock assessment from the additional information inherent in price data, compared to alternative assessment methods for data‐poor stocks. In a real‐world application to Barents Sea shrimp (Pandalus borealis, Pandalidae), we show that BESA benchmarks well also against advanced stock assessment results. BESA can thus be both a stand‐alone approach for currently unassessed stocks as well as a complement to other available methods by providing bio‐economic information for advanced fisheries management.

Burrow emergence rhythms of deep-water Mediterranean Norway lobsters (Nephrops norvegicus) revealed by acoustic telemetry

N. norvegicus supports one of the most commercially-important fisheries in the Mediterranean, and there is considerable interest in developing non-invasive sampling stock assessment methods. Currently, stock assessments are conducted via trawling or by UnderWater TeleVision (UWTV) surveys with limited capacity to provide direct population data due to the burrowing behavior of the species. Here, we used acoustic telemetry to characterize the burrow emergence and movement patterns of N. norvegicus in relation to internal tides and inertial currents in deep-sea habitats of the northwestern Mediterranean. We deployed acoustic tags on 25 adults between May and June 2019, and collected up to 4 months of detection data from each tag. Tagged lobsters spent approximately 12% of their time in door-keeping (i.e., detections at burrow entrance with no displacements) but differences existed among the different behavioral rhythms identified. We observed that mixed day-night, tidal and inertial rhythms in field settings were similar to those observed in laboratory tests. The presence of mixed day-night and tidal periodicity poses the question of why N. norvegicus exhibits flexible responses to environmental cues other than photoperiod. It is possible that tidal regulation of locomotor activity could reduce energy expenditure in relation to hydrodynamic drag. Inertial periodicity occurs in animals with no clear burrowing-oriented activity (always present on the seabed). Possibly, inertial-related movements are the result of a disruption of the biological clock. Our results are discussed in the context of how burrow emergence rhythms may bias UWTV surveys and how novel in situ monitoring approaches address these biases.