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Monitoring and assessment of natural resources often require inputs from multiple data sources. In fisheries science, for example, the inference of a species’ abundance distribution relies on two main data sources, namely commercial fisheries and scientific survey data. Despite efforts to combine these data into an integrated statistical model, their coupling is frequently hampered due to differences in their sampling designs, which imposes distinct bias sources in the estimator of the abundance distribution. We developed a flexible species distribution model (SDM) that can integrate both data sources while filtering out their relative bias contributions. We applied the model on three different age groups of the western Baltic cod stock. For each age group, we tested the model on (1) survey data and (2) integrated data (survey + commercial) as a means to compare their differences and investigate how the inclusion of commercial fisheries data improved the spatiotemporal abundance estimator and parameter estimates. Moreover, we proposed a novel validation approach to evaluate whether the inclusion of commercial fisheries data in the integrated model is not in direct contradiction with the survey data. Following our approach, the results indicated that the use of commercial fisheries data is suitable for the integrated model. Across all age groups, our results demonstrated how commercial fisheries supplied additional information on cod’s spatiotemporal abundance dynamics, highlighting sometimes abundance hot spots that were not detected by the survey model alone. Additionally, the integrated model provided a reduction of up to 20% and 10% in the uncertainty (SE) of the predicted abundance fields and fixed-effect parameters, respectively. The proposed model represents thus a valuable benchmark for evaluating spatiotemporal dynamics of fish, and strengthens the science-based advice for marine policymakers.

The ubiquity of data-limited, data-absent, and unmanaged fisheries around the world illustrates a significant need for enhanced monitoring of living marine resources beyond conventional agency-led programs. While quantitative stock assessments represent the gold standard for fisheries management, simple length-based datasets alone can provide important insights into fishery status and can be collected by citizen and community scientists. Here, we demonstrate the performance of Ocean Ruler, a web-based tool that uses computer vision software and digital edge detection to measure individual lengths of harvested catch from images submitted by users (e.g., fishers, scientists, fisheries managers). Specifically, we compared software-derived measurements to conventional hand measurements to estimate rates of software bias and measurement error across four fishery groups in commercial, recreational, and artisanal fisheries that operate along the coast of California, USA and Baja California, Mexico. Through collaboration with local fishing communities, we demonstrate minimal software bias across three out of the four fishery groups, with minor, yet consistent overestimation observed while using the tool to estimate finfish lengths. We also note that efforts must be made to reduce software measurement error, despite achieving acceptable levels of accuracy on average in many cases. Nevertheless, we believe our efforts represent early successes in integrating machine learning tools with citizen and community science to generate management-relevant fishery size-structure data. Such approaches, when implemented effectively, have the potential to directly support management of living marine resources, particularly in small-scale, data-limited contexts.

In length-based stock assessments for data-poor fisheries, commercial fishing data is often used due to its cost-effectiveness and accessibility. However, factors such as gear selectivity, seasonal closures, minimum conservation reference size (MCRS) regulations, and market-driven harvesting practices can render commercial catch data unrepresentative of the true population structure. Reliance on such data without correction or complementary sampling may lead to biased stock assessments, undermining effective fisheries management. This study investigates how length data from commercial fisheries and experimental sampling influence the estimation of biological reference points (BRPs) and explores differences in catch compositions between these data sources. Between June 2021 and May 2022, a study was conducted at Lake Eğirdir (Isparta, Türkiye), involving 10 different stations. A total of 400 fyke nets were deployed, consisting of 200 experimental and 200 commercial ones. The experimental fyke nets had a stretched mesh size of 18 mm, while the commercial ones had a mesh size of 34 mm. These nets were evenly distributed, with 40 nets at each station. TropFishR package was used for estimating of the life history parameters and stock assessment. The comparison of catch composition was performed using “ Length-dependent catch comparison” and “catch ratio” analyses through the SELNET program. As a result, it has been determined that, due to the potential size selectivity feature, the commercial fyke net is unsuccessful in catching small-sized individuals (<4 cm carapace length), while the experimental fyke net is unsuccessful in catching advanced-sized crayfish (>6.5 cm carapace length). The estimated BRPs showed significant differences depending on the data source, and there were also differences of up to 56% in the recommended total allowable catch ( TAC ) amounts. As a result, it is considered that relying solely on commercial or experimental fyke nets for crayfish may be misleading, and it would be more appropriate to use both for successful sampling and stock assessment.

Understanding the spatial pattern of human fishing activity is very important for fisheries resource monitoring and spatial management. The environmental preferences of tropical tuna purse seine fleet in the Western and Central Pacific Ocean (WCPO) were constructed and compared at different spatial scales based on the fishing effort (FE) data from the available automatic identification system (AIS) and commercial fishery data compiled from the Western and Central Pacific Fisheries Commission (WCPFC), using maximum entropy (MaxEnt) methods. The MaxEnt models were fitted with FE and commercial fishery data and remote sensing environmental data. Our results showed that the area under the curve (AUC) value each month based on the commercial fishery data (1°) and FE at 0.25° and 0.5° spatial scales was greater than 0.8. The AUC values each month based on the FE data at a 1° scale ranged from 0.775 to 0.829. The AUC values based on commercial fishing data at the 1° scale were comparable to the model results based on FE data at the 0.5° scale and inferior to the model results based on FE data at the 0.25° scales. Overall, the sea surface temperature (SST), temperature at 100 metres (T100), oxygen concentration at 100 metres (O100) and total primary production (PP) had the greatest influence on the distribution of the purse seine tuna fleet. The oxygen concentration at 200 metres (O200), distance to shore (DSH), dissolved oxygen (Dox), EKE, mixed layer depth (Mld), sea surface salinity (SSS), salinity at 100 metres (S100) and salinity at 200 metres (S200) had moderate influences, and other environmental variables had little influence. The suitable habitat areas varied in response to environmental conditions. The purse seine tuna fleet was mostly present at locations where the SST, T100, O100, O200 and PP were 28–30 °C, 27–29 °C, 150–200 mmol/m3 and 5–10 mg/m−3, respectively. The MaxEnt models enable the integration of AIS data and high-resolution environmental data from satellite remote sensing to describe the spatiotemporal distribution of the tuna purse seine fishery and the influence of environmental variables on the distribution, and can provide forecasts for fishing ground distributions based on future remote sensing environmental data.

Recreational fisheries managers are often challenged by the lack of long-term data to monitor the status and trends of fisheries. Tournament records may provide a useful source of information to identify long-term trends in recreational fisheries. The Bonefish fishery in the Florida Keys (USA) has experienced a long-term and sequential period of decline that has been quantified with multiple data-poor assessments. The fishery also has a long tradition of supporting recreational fishing tournaments that date to the late 1950s. Here, we use recreational fishing tournament records to track the status and trends of the Bonefish fishery. We validated trends in tournament records by comparing time series changepoints with changepoints observed with angler logbooks and Local Ecological Knowledge (LEK) surveys. We compiled partial records for nine candidate tournaments. Only one tournament had sustained records that were suitable for analysis (Islamorada All Tackle Bonefish Invitational Bonefish and Permit Championship 1968–2021). Changepoint analysis identified several changepoints in catch rates, fish size, and participation that coincide with changepoints identified through analysis of angler logbooks and LEK surveys from previous research. The congruence of changepoints identified among the three data sources suggests that these tournament records are tracking the status and trends of the Bonefish fishery. Optimistically, we identified a recent two-fold increase in Bonefish catch rates beginning in 2015, potentially suggesting a rebound in the fishery, which reflects anecdotal angler reports. Our results highlight the potential for tournament record data to contribute to status and trend assessments of recreational fisheries.

Mediterranean large-body sharks face a high risk of extinction, with population declines that could potentially be worse than the global trend. However, in the basin, there is little quantitative information on the long-term pattern of their populations. Here, we relied on local ecological knowledge (LEK) by tapping into the collective memory of professional fishers to tracing back the spatiotemporal changes in catch and abundance of four large-bodied sharks—hammerheads ( Sphyrna spp.), sandbar shark ( Carcharhinus plumbeus ), shortfin mako ( Isurus oxyrinchus ), and blue shark ( Prionace glauca )—inhabiting the waters off the Pelagie Archipelago (Strait of Sicily, Central Mediterranean) over three different periods (1961–1980s, target shark fishery; 1981–2000s, declining shark fishery; and 2001–2020s, no target shark fishery). A Productivity Susceptibility Analysis (PSA) was then conducted to combine fishers’ knowledge and biological data to assess the vulnerability of the four shark species in each period. Fishers reported a general perception of a reduction in abundance and catches over 60 years. Overall, a significant reduction in catches was observed for C. plumbeus (87%) and Sphyrna spp . (100%) , and three major aggregation sites were suggested. Vulnerability was high for all species across the three time periods, except for P. glauca, classified as moderately vulnerable until the 2000s. Notably, fishers reported that C. plumbeus and Sphyrna spp. were specifically targeted from the 1960s until the 1990s, with Sphyrna spp. potentially suffering decades of targeted fishing pressure. These results showed that in a data-poor fishery region, integrating fishers’ knowledge into ecological risk assessments effectively identifies the most vulnerable shark species throughout the history of the fishery and facilitates the development of urgent conservation actions needed for potentially extirpated and locally threatened shark populations.

Spatial data are key to fishery management; however, most often the spatial distribution of marine populations and fishing dynamics are poorly documented, especially for recreational fish species. The combination of fisheries-dependent data (FDD) obtained from logbooks, and local ecological knowledge (LEK) gathered from key stakeholders could be a powerful approach to inform data gaps in data-limited fisheries. In this study, we used both FDD from guides’ catch reports and LEK using an online survey and key-informant interviews to reconstruct the spatial changes in bonefish (Albula vulpes) catch and fishing effort throughout South Florida over the past 35–40 years, and better understand the extent and spatial patterns of the bonefish decline described in previous studies. Although anglers perceived a decline of bonefish numbers across all fishing areas (26 to 53% drop across Biscayne Bay, the Florida Keys, and Florida Bay), the start of the bonefish decline in Florida Bay resulted in the highest drop in bonefish number (53%); thus, indicating both regional and localized decline events affecting bonefish abundance. Within Florida Bay, LEK and FDD concurred with an initial drop in bonefish at Inner Bay, followed by a greater magnitude of decline at Outer Bay. Metrics of effort derived from the survey and interviews depicted a shrinkage and aggregation in the spatial distribution of fishing and a shift of fishing activities toward the Lower Keys. In sum, the spatiotemporal patterns of catch and effort obtained from LEK and FDD allowed us to understand where, when and how this data-limited species declined in South Florida.

Capture fisheries in developing countries provide significant animal protein and directly supports the livelihoods of several communities. However, the misperception of biophysical dynamics owing to a lack of adequate scientific data has contributed to the suboptimal management in marine capture fisheries. This is because yield and catch potentials are sensitive to the quality of catch and effort data. Yet, studies on fisheries data collection practices in developing countries are hard to find. This study investigates the data collection methods utilized by fisheries technical officers within the four fishing regions of Ghana. We found that the officers employed data collection and sampling procedures which were not consistent with the technical guidelines curated by FAO. For example, 50 instead of 166 landing sites were sampled, while 290 instead of 372 canoes were sampled. We argue that such sampling errors could result in the over-capitalization of capture fish stocks and significant losses in resource rents.

Fisheries provide critical economic, cultural, and ecological benefits to developing coastal countries such as The Bahamas. However, effective management remains challenging, particularly for traditional species such as spiny lobster, queen conch, and Nassau grouper. Despite existing regulations, overfishing and habitat degradation from both commercial and recreational sectors continue to threaten these populations, while limited data on stock size and total catch constrain assessment efforts. To address these gaps, we conducted stock assessments for key traditional and recreational species by reconstructing catch time series and analyzing them using the CMSY++ stock assessment model, which is suited for data-limited contexts. Twelve species were evaluated, including two invertebrates (queen conch and Caribbean spiny lobster), two large pelagic fishes (wahoo and dolphinfish), and eight demersal species (groupers, snappers, and hogfish), using a combination of fishery-dependent and fishery-independent data on historical exploitation and relative abundance. The resulting biomass trajectories indicate strong stock depletions for most of these species. These findings highlight an urgent need for improved management and provide a scientific basis for targeted conservation strategies for the resilience, and long-term sustainability of Bahamian fisheries under increasing environmental and anthropogenic pressures.

The lack of information regarding the conditions of grouper and snapper fishing activities in Sumbawa waters is one of the reasons for local government difficulties in making policies related to grouper and snapper fisheries management. This data is very important for decisions that need to be implemented at community level. In making this decision, the West Nusa Tenggara (NTB) provincial government needs information on catch composition and productivity in grouper and snapper fishing units, fishing grounds, and the fishing season for grouper and snapper in Sumbawa waters. Sumbawa waters are the largest production contributor to grouper and snapper fisheries in NTB Province. The dominant species of grouper and snapper caught in Sumbawa waters are Lutjanus argentimaculatus, Lutjanus malabaricus, Plectropomus leopardus, and Epinephelus coioides. These four species are also caught by fishermen under their sexual maturity length in Sumbawa waters. Grouper and snapper fishing units used by fishermen in Sumbawa waters have a productivity between 5.42 - 22.28 kg/trip. The grouper fishing seasons in Sumbawa waters are in March-April, June, August-September, and November, while the snapper fishing season in Sumbawa waters is in January-March, May-June, and September.