Status Of Fish Stocks Research Articles

Estimates of life-history and growth parameters of exploited fish species in lakes Edward and George: Implications on exploitation status, population dynamics, management, and conservation of native species.

Adequate knowledge is essential for responsible inland fisheries. However, many inland fisheries lack monitoring, and therefore, decision-making for fisheries management is not reliable. In this paper, we used data from surveys and literature to estimate the life-history and growth parameters of 16 exploited fish stocks in the Ugandan part of Lake Edward and Lake George (East Africa). The estimated parameters are pivotal indicators of fish stock status, particularly in data-poor fisheries. The estimated parameters included maximum length (Lmax) and mean length (Lmean) as indicators of size structure in experimental and commercial catches, coefficients of length-weight relationships, length at 50% maturity (Lm50), fecundity, von Bertalanffy parameters, total mortality (Z), and natural mortality (M). These parameters were estimated using empirical formulae, statistical methods, and analyses of length frequencies. Only two stocks of semutundu Bagrus docmak exhibited significant and increasing trends in Lmax (Lake Edward) and Lmean (Lake George). The estimates for the remaining parameters were consistent with those in FishBase and other literature resources, either for the same species or related species. This consistency indicates their reliability for application in decision-making and further assessments. Some parameters showed evidence of unsustainable fishing. For example, estimates of Lm50 for four of the assessed stocks belonging to two species (Nile tilapia Oreochromis niloticus and marbled lungfish Protopterus aethiopicus) were lower than baseline estimates in the studied waterbodies. Furthermore, the Lmean in catches for all the stocks were less than the optimum lengths (Lopt), which maximize catches with a minimal impact on biomass and size structure. No significant changes in Lmean, length-frequency distributions, and size at maturity could be attributed to the management changes implemented in 2018, probably because it is too early to observe changes in these parameters. However, there are positive signs attributable to the changes in management as shown by a high proportion of mature individuals in commercial catches for most of the stocks for which the proportion was calculated, and an increase in Lmean and Lmax for some stocks, such as B. docmak, in commercial or experimental catches. New estimates from this study will enhance decision-making and further assessments of fisheries. Routine monitoring is recommended to update and improve the estimates.

Fish Stock Status and Its Clues on Stocking: A Case Study of Acanthopagrus schlegelii from Zhanjiang Coastal Waters, China

Fish Stock Status and Its Clues on Stocking: A Case Study of Acanthopagrus schlegelii from Zhanjiang Coastal Waters, China

Distribution and abundance of ichthyoplankton in natural al artificial reefs in Edremit Bay, Northern Aegean Sea, Türkiye

Edremit Bay is one of the important areas for small–scale fishing in the North Aegean Sea. For this reason, more detailed ichthyoplankton studies should be continued to evaluate the fish stock status of the region, calculate the adult fish biomass, and determine the spawning period, place, and time of fish species. In addition, from 2011 to 2013, artificial reefs were constructed in Edremit Bay. Regular investigation of fish eggs and larvae in the region influenced by the Edremit Bay artificial reef would provide better knowledge of the structure and function of the local ecosystem and provide a basis for monitoring the marine ecosystem in the area. The current research examined the species abundance and distribution of surface plankton samples collected in 2015 and 2016. The evaluation also included the influence of abiotic environmental factors such as temperature, pH, chlorophyll a (chl–a), salinity, depth, and dissolved oxygen. Throughout the research, 3345 eggs and 176 larvae were analyzed. 57 species of eggs and larvae were identified. Eggs were not found in the natural reef (S3) in the summer and winter of 2015, while the highest egg abundance (212.83·100 m-3) was recorded in the natural reef (S1) in the summer of 2016. Larvae were not found in the natural reefs (S2 and S3) in the summer, autumn and winter of 2015 and in the artificial reefs (S4 and S5) in the summer and autumn in 2015 while the highest larvae abundance (8.12·100 m-3) on the artificial reef (S1) in summer 2016. Although the natural reefs had the highest number of species (30 species), the artificial reefs showed the lowest species diversity (17 species).

Management strategy evaluation operating model conditioning: a swordfish case study

Evaluation of fish stock status is a key step for fisheries management. Tuna Regional Fisheries Management Organizations (t-RFMOs) are moving towards management strategy evaluation (MSE), a process that combines science and policy and depends on technical aspects, developed by scientists, designed to meet management objectives established by managers and other stakeholders. In the Indian Ocean, the current management advice for swordfish (Xiphias gladius) is based on an ensemble of 24 models considering four areas of uncertainty about the stock dynamics. There is an ongoing MSE process for swordfish, and this paper describes the methodology being applied for the conditioning of the operating model (OM), including model selection and validation. In the MSE, nine sources of uncertainty were considered, each being characterized by 2–3 levels. A partial factorial design was employed to reduce the number of models from a full factorial design to those needed to encompass the overall uncertainty. A selection and validation process was carried out, filtering models that converged, showed good predictive skills, and provided plausible estimates. Overall, the estimated spawning stock biomass (SSB) relative to SSB at maximum sustainable yield (MSY), and fishing mortality (F) relative to FMSY encompasses the estimates of the stock assessment ensemble at the most optimist area of the distribution. The MSE for swordfish is an ongoing process that is expected to provide more robust management advice in the future. Further developments to the OM can still occur, but the methods presented herein can be applied to this, or other species, MSE processes.

Length-Weight Relationship and Condition Factor of Fishes in Two Major Rivers, the Chao Phraya and the Bang Pakong, in Thailand.

Length-weight relationship (LWR) was used as a tool to assess the status of fish stocks, through condition factor, in major rivers in Thailand. Fifty-one fish species from each river, i.e., The examined for LWR using 11 years of monitoring data (2010-2020) for Bang Pakong and 14 years of monitoring data (2007-2020) for Chao Phraya, which comprised 57,871 samples. The parameters for LWR and condition factor were examined by species and by body shape, i.e., ovate, oblong, elongate or eel-like. The coefficient of determination (r 2 ) of all log-transformed LWRs was greater than 0.90. Parameter b of LWR ranged between 2.06 and 3.46 (median = 3.00) for fishes from the Chao Phraya River and between 1.72 and 3.68 (median = 2.76) for fishes from the Bang Pakong River. The overall condition factor, which implies the well-being that indicates the health or fattening of the fishes in a stock, ranged between 0.93 and 1.09. There was no significant difference in the overall well-being (P = 0.279) between the two rivers. Fishes with oblong and elongate shapes in the Chao Phraya River showed higher median values of parameter b of LWR than those from the Bang Pakong River. However, there was no significant difference (P > 0.05) in the well-being of the fish stocks between the two rivers when pooled by shape. The findings are fundamental information for fish stock assessment in the two rivers, which greatly support the small-scale fisheries in Thailand.

State and exploitation of commercial fish stocks in the Russian part of the Baltic Sea, Curonian, Kaliningrad and Finnish Gulfs

The aim of this article: to assess the condition and level of exploitation of commercial fish species in the Russian parts of the Baltic Sea (including the Gulf of Finland), the Curonian and Kaliningrad (Vistula) Lagoons.Methods used: the stocks of commercial fish species in the Baltic Sea and its bays are transboundary. For several decades, as part of the international regulation of fisheries in the Baltic Sea, scientific cooperation has been carried out between the countries of the European Union and the Russian Federation at the International Council for the Exploration of the Sea (ICES). During the period from 1992 to the present, AtlantNIRO has organized and carried out a significant amount of comprehensive research work in the Baltic Sea. In total, more than 70 hydroacoustic, bottom and environmental surveys were completed. Long-term (more than 60 years) studies of aquatic biological resources of commercial fish species are also carried out in the Curonian and Kaliningrad (Vistula) Lagoons. For many years, scientific cooperation has been carried out on the study of the bays with the Lithuanian and Polish republics, respectively.Novelty: in the modern period, analysis of research on the state and exploitation of stocks of commercial fish species in the Russian part of the Baltic is carried out for the first time.Result: the volume of production of aquatic biological resources (ABR) in the Baltic Sea has currently reached an “extreme high point”, and a slight decrease should be expected in the near future. In the Curonian and Kaliningrad (Vistula) Lagoons, the condition of the stocks of the main commercial fish is satisfactory, which allows for stable production of aquatic fish.Practical significance: in modern conditions, information on the state of fish stocks in the region will allow solving problems of managing these resources, including planning for the near future the possible volumes of their production by fishing organizations.

Rejection sampling and agent-based models for data limited fisheries

Many of the world’s fisheries are “data-limited” where the information does not allow precise determination of fish stock status and limits the development of appropriate management responses. Two approaches are proposed for use in data-limited stock management strategy evaluations to guide the evaluations and to understand the sources of uncertainty: rejection sampling methods and the incorporation of more complex socio-economic dynamics into management evaluations using agent-based models. In rejection sampling (or rejection filtering) a model is simulated many times with a wide range of priors on parameters and outcomes are compared multiple filtering criteria. Those simulations that pass all the filters form an ensemble of feasible models. The ensemble can be used to look for robust management strategies, robust to both model uncertainties. Agent-based models of fishery economics can be implemented within the rejection framework, integrating the biological and economic understanding of the fishery. A simple artificial example of a difference equation bio-economic model is given to demonstrate the approach. Then rejection sampling is applied to an agent-based model for the hairtail (Trichiurus japonicas) fishery, where an operating model is constructed with rejection/agent-based methods and compared to known data and analyses of the fishery. The usefulness of information and rejection filters are illuminated and efficacy examined. The methods can be helpful for strategic guidance where multiple states of nature are possible as a part of management strategy evaluation.

Monitoring Small-Pelagic Fishery Utilization in Java Sea Based on Fishing Log Book

The most attention issue of sustainable fisheries management is related to the availability of catch and fishing efforts data with the spatio-temporal distribution. The monitoring data plays important to evaluate the fish stock status and fishery dynamic in the waters. As dependent-fishery data, logbook data is a reliable data source for estimating the utilization rate of fish resources and designing effective regulation tools in fisheries management areas. This study aims to analyze catch composition, spatial and temporal distribution, and productivity (catch per unit effort) of small-pelagic purse seine fisheries in the Java Sea using fishing logbook data. The result shows the highest It was found that the catch composition of small pelagic purse seines was dominated by longtail tuna/kawa-kawa, scad (Decapterus spp.), and sardinella fimbriata with the highest catches annually occurring in September 2021, March 2020, and November 2019. However, the highest productivity was achieved in September 2021, May 2020 and June 2019, namely 1,290 kg/setting/day, 1,700 kg/setting/day, and 1,660 kg/setting/day, respectively. Regarding spatial distribution, the highest productivity was in the northern and central parts of the Java Sea and the southern parts of Kalimantan.

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.

Explaining technical change and its impacts over the very long term: The case of the Atlantic sardine fishery in France from 1900 to 2017

As an industry based upon the harvesting of wild resources, the fishery is often used in economics to showcase the effects of its specific nature on human behavior and the impacts of that behavior on the fish stock itself. The common-pool status usually encountered in the use of these resources makes them especially vulnerable to major shifts in the supporting ecosystems, but also to rapid technical change. In most other parts of the economy, technical change and the creative destruction that it brings along are viewed positively, and even given central role in recent theories of growth. Happily for the creatures of the ocean that are hunted, fishers do not fit the mould of Schumpetarian entrepreneurs bent on creative destruction. However, the technology that does drift onto boats has had concerning effects on the status of fish stocks with important economic and cultural consequences. We present a narrative of the French sardine fishery using the evolutionary theory of technical change. The wild binary segmentation approach was applied on a time-series of French sardine landings from 1900 to 2017. This analysis revealed three significant production change points associated with important technical changes in the fishery. The first change point, in 1927, is related to the introduction of the purse-seine in France. The introduction of the mid-water trawl is the second change point in the early 1970s. A third change point occurred in 1998, where we see a reswitch from mid-water trawl to purse-seine. Collectively, these results highlight the technological changes in sardine production that occurred, but more importantly, the impacts of these changes both on the structure of the population of sardines, and on the industry. The lesson we derive from this case study is that technical change should be considered as a succession of shifts rather than a unidirectional history.

Age validation of Black Rockfish, Copper Rockfish, and Cabezon using secondary ion mass spectrometry (SIMS) to elucidate seasonal patterns in otolith stable oxygen isotopes

Stock assessors commonly use models that incorporate biological data such as fish length and age to determine the status of fish stocks and how different management scenarios affect stock size. Ages used in assessment models need to be accurate and precise because ageing error can affect many model inputs and potentially result in stock mismanagement. Despite the requirement for sound age data, few studies have investigated accuracy of ages for groundfish captured in coastal nearshore waters off Oregon, USA. In this study, we validate otolith ages for Black Rockfish (Sebastes melanops), Copper Rockfish (Sebastes caurinus) and Cabezon (Scorpaenichthys marmoratus), three species with recreational and commercial importance to Oregon. Ages obtained by traditional break-and-burn methods were validated using secondary ion mass spectrometry (SIMS) to examine otolith stable oxygen isotope ratios (δ18O) over a fish’s lifetime. This technique relies on the inverse relationship that exists between otolith δ18O and ambient water temperature, and independent counts of δ18O maxima should be comparable to ages obtained by visual counts of otolith growth marks laid down during cold water periods. Locations of δ18O maxima in otolith chronologies matched well with locations of visual growth marks in otoliths of all three species, maxima counts were strongly positively correlated with age, and variation in otolith δ18O decreased with age. However, significant variability in the δ18O chronologies caused by variability in intra-seasonal upwelling and resulting water temperature variations made maxima counts difficult in several samples. Correct interpretation of chronologies required knowledge of location of the first annulus, the compression of growth zones with age, and an assumption of the seasonal amplitude of the ambient water δ18O.

Applying life history traits to eco-labelling schemes for fisheries management: A case study in Taiwan

Eco-labelling scheme is an emerging management strategy for promoting the sustainable development of marine resources and fisheries. The recommendation lists for seafood that reflects the status of exploited fish stocks, based on scientific evidences and categorize species accordingly is a commonly used eco-labelling scheme. Nevertheless, the status of fish stocks may be influenced by abiotic factors and biotic factors which may affect the categorization of fish species in recommendation lists. In this study, four life history traits (maximum length, length at maturity, age at maturity and growth coefficient) and two ecological parameters (trophic level and unit price) of 35 marine fishes in the waters around Taiwan were examined through multivariate statistical analysis and compared against the Seafood Guide Taiwan. Two main factors were identified through principal component analysis. The first factor was correlated with maximum length, length at maturity and growth coefficient, and the second factor was correlated with age at maturity and trophic level. Two fish groups were identified according to the PCA bi-plot. The Best Choices and Good Alternatives categories had higher growth coefficients, and the Avoid group had a smaller age at maturity. The results indicated that the life history traits of fish stocks may serve as complementary information to seafood guides, and may have substantial implications for the future planning of eco-labelling schemes. Nevertheless, when developing a framework for a domestic eco-labelling scheme, the decision-makers should consider the applicability of framework components in the global market as well as research on fish stock status and management strategies.

Community‐based monitoring, assessment and management of data‐limited inland fish stocks in North Rupununi, Guyana

AbstractInland fisheries are important for food security in communities around the world, especially in developing countries. In North Rupununi, Guyana, the state of exploited stocks is poorly understood, and fishery monitoring and assessment are challenging because diverse fishing gears and target species are distributed across a heterogeneous landscape. This complexity created an opportunity for community‐based monitoring (CBM) to support data‐limited assessment. Standardised CBM was established for the North Rupununi as part of a new inland fisheries management plan initiated by indigenous community groups with support from the government. Quantitative length‐based assessments undertaken for target stocks suggested moderate levels of exploitation consistent with local perception. Our study highlights that local experts and community participants with different levels of training can collect accurate biodiversity data. Further development of CBM is important in North Rupununi. We recommend using local ecological knowledge indicators to track spatial and temporal patterns in exploitation and fish stock status.

AMPLE: An R package for capacity building on fisheries harvest strategies.

Fisheries harvest strategies are formal frameworks that represent a best-practice approach for sustainable fisheries management. A key component of a harvest strategy is a 'pre-agreed rule', known as a harvest control rule (HCR), that sets fishing opportunities, e.g. catch limits, based on an estimate of fish stock status, e.g. estimated stock biomass. The harvest strategy development process is driven by stakeholders who are required to make a range of informed decisions, including on the selection of the preferred HCR. Capacity building may be required to facilitate the stakeholder engagement, particularly regarding the technical components of harvest strategies, including HCRs. The AMPLE package for R provides three interactive apps that support capacity building and stakeholder engagement on HCRs. These apps have been used during in-country national workshops around the western and central Pacific Ocean (WCPO) to support the development of harvest strategies for the Western and Central Pacific Fisheries Commission. These apps include several novel features: they take users from a gentle introduction to how HCRs work, to using methods for testing, comparing and selecting a preferred HCR from a suite of candidates. They include an introduction to the impact of uncertainty on the performance of an HCR, introduce performance indicators and discuss methods for selecting the preferred HCR based on management objectives. As such they provide a more detailed overview of HCRs than currently existing alternatives. These apps provide an effective platform for hands-on learning and have proven to be successful at supporting capacity building on HCRs in the WCPO. For example, using them for group activities and competitions stimulated productive discussions and increased understanding. As the model fishery in AMPLE is generic and not based on a real example, the apps will also be of interest to scientists, managers and stakeholders developing harvest strategies in other regions.

Fishery Status and Rebuilding of Major Economic Fishes in the Largest Freshwater Lake in China Based on Limited Data

Poyang Lake, the largest freshwater lake in China, possesses abundant fishery resources, but its fish stock status is still unclear. In this work, the stock status of and fishing efforts of nine major economic fishes in the Poyang Lake were estimated from 2000 to 2019 with a catch-based maximum sustainable yield (CMSY) model based on catch and resilience data. It was further predicted whether the biomass of those fishes could be restored to support maximum sustainable yield (Bmsy) under the policy of “Ten years fishing moratorium in the Yangtze River”. The results showed that goldfish Carassius auratus, grass carp Ctenopharyngodon idella, and black carp Mylopharyngodon piceus suffered from higher fishing efforts and low biomass in the past 20 years; bighead carp Hypophthalmichthys nobilis, yellow catfish Tachysurus fulvidraco, and common carp Cyprinus carpio responded differently to their fishing efforts; silver carp Hypophthalmichthys molitrix, Amur catfish Silurus asotus, and mandarin fish Siniperca chuatsi were underexploited. Six species were overfished in 2019, and their biomass would be expected to recover for sustainable exploitation during the fishing moratorium, except for M. piceus. This study provided a case study of feasible freshwater fishery evaluation in limnetic ecosystems.

Estimating the total allowable catch and management of Threadfin porgy (Evynnis cardinalis) fisheries in the northern South China Sea based on sampling surveys conducted at fishing ports

In order to develop a method that apply sampling survey data randomly obtained at fishing ports to fish stock assessments, based on fish landing surveys conducted at fishing ports in the northern South China Sea (SCS), 19 Threadfin porgy (Evynnis cardinalis) catch per unit effort (CPUE) datasets were collected for fishing vessels with different gear types and engine powers and incorporated into surplus production models. Considering only the fitting performance, the Schaefer model had the best overall goodness of fit, followed by the Fox, CYP, W–H, and Schnute models. Among fishing vessels with different gears and engine powers, the data were best fitted for single-trawl vessels powered by 301–400-kW engines and for gillnet vessels powered by > 200-kW engines. Eight model expressions were superior and selected for subsequent analyses based on their goodness of fit and relative residuals. The Kobe plot analysis results showed an optimistic fish stock status when using the four model expressions, required more caution when using three model expressions and output pessimistic estimations using one model expression. Considering the incomplete information acquired, a compromising decision-making method was used to derive a 2017 northern SCS E. cardinalis total allowed catch (TAC) of 44,691.21 t. The different conclusions drawn from estimations using CPUEs reflect variable exploitation and utilization fish stock statuses among fishing vessels with different gears and engine powers. Hence, the fishing operations were grouped according to their CPUE relationship, and recommendations regarding optimum fishing efforts were assigned to the groups following a fundamental principle: to improve fishery TAC management, fishing efforts should be reduced if the fish stock assessment is pessimistic and maintained if the assessment is optimistic. This study providing a feasible technical method for the TAC management of China's offshore fisheries.

A history and evaluation of catch‐only stock assessment models

AbstractUnderstanding the status of fish stocks is a critical step in ensuring the ecological and economic sustainability of marine ecosystems. However, at least half of global catch and a vast majority of global fisheries lack formal stock assessments, largely due to a lack of sufficient data. Catch data, loosely referring to any catch records be it inclusive of discards or not, are the only type of fishery data available across a wide range of fisheries at a global scale. This has given rise to a long list of so‐called “catch‐only” models, intended to estimate aspects of stock status based primarily on characteristics of a fishery's catch history. In this paper, we review the history, performance and potential of “catch‐only” models to estimate stock biomass status. While individual catch‐only models often report good performance, repeated efforts to examine the performance of these models have consistently found them to be imprecise and biased when applied to new data‐limited fisheries. We demonstrate that a large reason for this is the simple lack of information on stock status contained in the shape of a catch history alone. Off‐the‐shelf use of catch‐only models can lead to poor and biased estimates of stock status, potentially hindering efforts at effective management.

Scoring the status of UK shared and national fish stocks around the time of Brexit

A Stock Penalty Scoring (SPS) was developed and used to rank the status of fish stocks in the UK EEZ at the time of Brexit. Most of the stocks had negative scores (of relatively less concern) but 19% had positive scores (of more concern). This latter group included many inshore crab and lobster stocks, often assumed to be fished using low-impact methods. Fisheries managers thus need to urgently address problems of over-exploitation in this sector. Policy makers should also not assume that if stock biomass is slightly above Bmsy.trigger then the stock has been rebuilt to an adequate level consistent with legal obligations. The UK 2020 Fisheries Act states that stocks must be maintained above Bmsy, not Bmsy.trigger. For most UK stocks, fishing should be kept below Fmsy to allow stocks to rebuild which should deliver economic and ecosystem benefits in the medium to longer-term. Of the stocks examined, 43% lacked reference points and could not be ranked using the SPS. Although these stocks only contributed 11% of total landings, they include many of local economic importance, and species of conservation concern. Implementing either regular assessments (e.g. for scallops), developing proxy measures (e.g. for skates and rays), or novel techniques (e.g. eDNA) are urgently required to improve their monitoring. The UK aspires to deliver “world class fisheries management” but this will require adequate resourcing of fisheries science and regular monitoring of progress. The SPS approach may provide an additional useful tool for tracking progress in fisheries management post-Brexit.

LIMIT REFERENCE POINTS OF FISHING PARAMETERS IN LAKES AND RESERVOIRS OF KAZAKHSTAN

The article deals with the problems of regulating commercial fishing in the water bodies of Kazakhstan. Analysis of data on fishing in large reservoirs of the Republic of Kazakhstan shows that along with natural changes in the fish stocks (when the water level in the reservoir decreases), the fishing intensity makes the greatest impact on the state of fish stocks. Today a pre-existing limiter as the fishing regime (the number of fishing gear and fishermen) completely has fallen out of the fishing control mechanisms. According to some reports, the catch of fish with fishing gear available to fishermen, increases the established limits by 1.5–2 times. Thus, the possible catch significantly exceeds the registered (official) catch. It is proposed to use the regulation of the fishing regime (the number of fishing gear, fishing vessels, fishermen) as a measure that determines the limits of safe effort and to limit unrecorded fishing on water bodies. The number of fishermen in the pond should not only meet the criteria for safe effort, but also allow fishing organizations to conduct profitable fishing. The calculation of the maximum allowable number of fishing performance indicators (limit reference points of fishing effort) are given.

Automating fish age estimation combining otolith images and deep learning: The role of multitask learning

Knowledge on the age of fish is vital for assessing the status of fish stocks and proposing management actions to ensure their sustainability. Prevalent methods of fish ageing are based on the readings of otolith images by experts, a process that is often time-consuming and costly. This suggests the need for automatic and cost-effective approaches. Herein, we investigate the feasibility of using deep learning to provide an automatic estimation of fish age from otolith images through a convolutional neural network designed for image analysis. On top of this network, we propose an enhanced - with multitask learning - network to better estimate fish age by introducing as an auxiliary training task the prediction of fish length from otolith images. The proposed approach is applied on a collection of 5027 otolith images of red mullet (Mullus barbatus), considering fish age estimation as a multi-class classification task with six age groups (Age-0, Age-1, Age-2, Age-3, Age-4, Age-5+). Results showed that the network without multitask learning predicted fish age correctly by 64.4 %, attaining high performance for younger age groups (Age-0 and Age-1, F1 score > 0.8) and moderate performance for older age groups (Age-2 to Age-5+, F1 score: 0.50−0.54). The network with multitask learning increased correctness in age prediction reaching 69.2 % and proved efficient to leverage its predictive performance for older age groups (Age-2 to Age-5+, F1 score: 0.57−0.64). Our findings suggest that deep learning has the potential to support the automation of fish age reading, though further research is required to build an operational tool useful in routine fish aging protocols for age reading experts.