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Monitoring and managing fisheries bycatch is increasingly recognized as a critical component of robust fisheries management frameworks. This review, addressing this subject, begins by defining bycatch and analyzing the reasons it happens, from accidental to intentional discarding. It identifies the most common species composing bycatch of the main tuna fisheries using purse seine and longline gear. Considerations of options available to estimate bycatch, their potential biases and uncertainties, and ways to address these issues are discussed. The formulas used to estimate bycatch also point to the options to reduce them, lowering bycatch per unit of effort or lowering effort itself. It shows that a mean can be reduced by reducing all its component figures, or by eliminating the high values at the extreme of the distribution (i.e., where a small proportion of events causes a large proportion of the problem), a common issue in bycatch. A generic strategy is described that can be applied to all gears and fisheries, and it is then described for the fisheries of interest, showing examples of its application. These cover many mitigation actions based on gear and operational changes. Management options aiming at reducing bycatch are also mentioned. A detailed description of the ways the strategy has been implemented for purse seiners and longliners is provided. Finally, market strategies, education and awareness of stakeholders, mainly fishers, and some potential future developments are briefly described.

Fisheries have impacted seabird populations worldwide, either via bycatch mortality or resource depletion. Understanding the overlap between seabird distributions and fisheries is an important element for bycatch risk assessment, though the drivers of variation in seabird–fishery overlap are not well understood for some seabird populations. Here, we quantified the spatial overlap between foraging Cory’s shearwaters Calonectris borealis during the breeding season and commercial fisheries operating within the Portuguese Exclusive Economic Zone. In addition, we evaluated whether overlap varied as a function of an individual’s boldness, sex or breeding stage. For this, we GPS tracked 361 foraging trips by 72 Cory's shearwaters nesting at Berlenga Island, Portugal, over 5 consecutive breeding seasons (2012–2016). Simultaneously, we used fishing effort data from Global Fishing Watch detailing the distribution of industrial fisheries within the temporal and spatial range of Cory's shearwater tracks. Although fishing vessels were present during 88.1% of foraging trips, Cory's shearwaters spent only on average 13.3% of the time foraging in the same areas as fisheries. Such low spatial overlap is likely driven by high prey availability near the colony and suggests low direct competition for resources. We also found variation in overlap with fisheries across the breeding period, with Cory's shearwaters spending approximately 11% more time foraging in the same areas as fixed gear and purse seine vessels during pre-laying than during chick-rearing. Surprisingly, no sex or boldness-related differences were found in the overlap with any fishing gear. Our findings have implications for understanding within population variation in the overlap between fisheries and seabirds and, in turn, bycatch risk.

The purse seine fishery in the Mediterranean represents about 60% of the international catch for Atlantic Bluefin Tuna (Thunnus thynnus). Yet, tagging operations from this segment of the fisheries remain rare and despite its potential importance for management, several aspects related to the migratory behavior of Atlantic Bluefin Tuna from these areas remain unaddressed. In the present manuscript, we report the results of two tagging operations carried out on a commercial purse seiner during two consecutive years in the spawning ground around the Maltese islands in the Central Mediterranean Sea. During these operations, eight individuals were tagged and the results showed that the larger fish (> 200 cm) undertook large-scale migrations outside the Mediterranean, whereas smaller individuals did not. This study suggests that size might affect the migratory behavior of Atlantic Bluefin Tuna, and underlines the potential of large-scale tagging operations from spawning grounds to address scientific questions having significant management implications.

An unmanned surface vehicle (USV) with a fish attraction lamp was developed to assist in the nighttime operations of a Japanese purse seine fishery. The USV weighs about 15 kg, is equipped with a 200 W underwater light-emitting diode (LED), and can be radio-controlled to move on the sea surface. The purse seiner shoots a net to surround the lighting boat to catch fish gathered by fish attraction lamps. The USV was deployed on the sea surface from the purse seiner during the net-hauling operation and replaced the lighting boat to continue fish attraction after shooting the net. The time required for each operation using the USV and conventional lighting boat operations was compared, and it was found that the time required for the lighting boat for fish attraction after shooting the net was reduced by about 10 min per haul when the USV was used. On the other hand, the time required by the purse seiner to shoot and haul the net and the catch amount did not change. The USV can contribute to time savings in operation and safety improvements in the purse seine fishery.

Small pelagic fish caught with mini purse seines (MPS) in the Java Sea has been exploited for a long time and causes resource sustainability. Policies in preserving natural resources require scientific studies that can provide management options. This research was conducted from March to July 2017 at PPN Pekalongan by recording catches and measuring fork length (FL). The composition of the MPS catch showed that 64% were small pelagic and dominated by Goldstripe sardinella (Sardinella gibbosa) 56.3%, Bigeye scad (Selar crumenophthalmus) 19.3%, and the scads (Decapterus spp) 12.3%, other species with small numbers including Yellowstripe scad ( Selaroides leptolepis ) by 2.5%. This Yellowstripe scad has a length of between 4.5-18.5 cm FL (average of 10.86 cm FL). The estimated natural mortality (M) is less than the fishing mortality (F). The level of exploitation (E=0.70) indicates that it is overfishing. The management operations that need to be taken to preserve the yellowstripe scad are by regulating the fishing area, determining the size of the allowed MPS nets, and limiting MPS attempts in the Java Sea.

The escalating impact of anthropogenic activities on global climate patterns necessitates urgent measures to reduce emissions, with the maritime industry playing a pivotal role. This article aims to examine the adoption of International Maritime Organization energy efficiency measures for the often-overlooked fishing vessels and their contribution to the overall maritime decarbonization efforts. The article analyzes the attained technical efficiency indices of a case study large-scale fishing vessel and compares them with those of two cargo ships where IMO measures already apply. To support the proposal, a comprehensive analysis of the energy efficiency indices of eight large purse seine fishing vessels is also presented. The results show that large-scale fishing vessels of 400 GT and above could be subject to the IMO energy efficiency measures. The operational challenges, unique to the fishing sector, suggest that sector-specific considerations may be required to integrate the fishing fleet into the already existing IMO energy efficiency guidelines. Looking ahead, this article explores the benefits of aligning Regulation (EU) 2023/957 and IMO guidelines, as well as applying the IMO Carbon Intensity Indicator (CII) in assessing the operational environmental impact of fishing operations, emphasizing the importance of including these vessels in the current regulatory frameworks to promote decarbonization.

For large-scale tropical tuna purse-seine fisheries, it is prohibitively costly to obtain adequate sampling coverage to estimate fleet-level catch composition solely from sample data. Logbook or observer data, with complete fleet coverage, are often available but may be considered unreliable for species composition. Previous studies have developed models, trained with sample data, to predict set-level species compositions based on environmental and operational covariates. Here, models were developed to predict well-level species composition from uncorrected observer data and covariates affecting the observers’ view of the catch during loading, with port-sampling data as the response variable. The analysis used paired, well-level data from sets made on floating objects by the Eastern Pacific Ocean tuna purse-seine fleet during 2023–2024. Results indicated that, overall, observer data proportions of bigeye (BET) and yellowfin tunas tended to be greater than the model-estimated proportions, with the opposite occurring for skipjack tuna (SKJ). However, vessel effects sometimes modified these tendencies. Model complexity was greatest for BET and least for SKJ. For BET, observer data proportions and model-estimated proportions were more similar when the vessel had a hopper. They were also more similar in 2023 as compared to 2024, suggesting sample data for bias adjustments should be collected annually. The approach shows potential for predicting the species composition of unsampled wells.

Aim: Predicting distribution patterns of whale sharks (Rhincodon typus, Smith 1828) in the open ocean remains elusive owing to few pelagic records. We developed multivariate distribution models of seasonally variant whale shark distributions derived from tuna purse-seine fishery data. We tested the hypotheses that whale sharks use a narrow temperature range, are more abundant in productive waters and select sites closer to continents than the open ocean. Location: Indian Ocean. Methods: We compared a 17-year time series of observations of whale sharks associated with tuna purse-seine sets with chlorophyll a concentration and sea surface temperature data extracted from satellite images. Different sets of pseudoabsences based on random distributions, distance to shark locations and tuna catch were generated to account for spatiotemporal variation in sampling effort and probability of detection. We applied generalized linear, spatial mixed-effects and Maximum Entropy models to predict seasonal variation in habitat suitability and produced maps of distribution. Results: The saturated generalized linear models including bathymetric slope, depth, distance to shore, the quadratic of mean sea surface temperature, sea surface temperature variance and chlorophyll a had the highest relative statistical support, with the highest percent deviance explained when using random pseudoabsences with fixed effect-only models and the tuna pseudo-absences with mixed-effects models (e.g. 58% and 26% in autumn, respectively). Maximum Entropy results suggested that whale sharks responded mainly to variation in depth, chlorophyll a and temperature in all seasons. Bathymetric slope had only a minor influence on the presence. Main conclusions: Whale shark habitat suitability in the Indian Ocean is mainly correlated with spatial variation in sea surface temperature. The relative influence of this predictor provides a basis for predicting habitat suitability in the open ocean, possibly giving insights into the migratory behaviour of the world's largest fish. Our results also provide a baseline for temperature-dependent predictions of distributional changes in the future.

This research focuses on the relationships between fishing success and various influential factors by using a statistical model based on observed data. The potential factors that significantly impact fishing success results were determined using in situ dataset collected with geographic coordinates in 126 fishing operations by three purse seines. A generalized additive model (GAM) for catch variables of Atlantic bluefin tuna Thunnus thynnus (presence–absence) was used to analyse fishing success under different variables: fishing operation (shooting duration, closing the racing duration, setting speed, sinking speed), gear design (length–height ratio), geophysical coordinates (latitude and longitude) and environmental conditions (sea surface temperature, depth, current speed at 10 m). The best fit model results showed that sea surface temperature makes a major contribution to the successful fishing of T. thynnus, as evidenced in previous work. In addition, some other factors (depth, shooting duration, closing the lacing duration, current speed at 10 m, setting speed, sinking speed, and length–height ratio) also affect the success of T. thynnus fishing in the Eastern Mediterranean Sea. These results help to indicate several fishing strategies that will be adopted to encourage fishers to increase their efforts.

Prigi waters in East Java, Indonesia have dominant fishing potential, especially bullet tuna (Auxis rochei). The capture of A. rochei in Prigi generally uses small pelagic purse seine. Overfishing efforts cause A. rochei production to fluctuate every year. In addition, this decline in production can be influenced by oceanographic parameters. The purpose of this study was to understand the conditions of oceanographic parameters (SST, chlorophyll-a, salinity) and their relationship to A. rochei for determining potential fishing zones. The research was carried out from February to April 2024. The research method was carried out by directly measuring oceanographic parameters and using satellite image data. Data analysis uses satellite image data verification tests and in-situ data. The data captured are real-time. A multiple linear regression analysis for determining the optimal parameter combination is carried out to obtain the fishing potential zone. A 1 ppt change in salinity resulted in an increase of 5,276.53 kg in the catch of A. rochei. Meanwhile, simultaneous testing obtained a significance result of 0.008 which means that the variables SST, chlorophyll-a, and salinity together influence the catch of A. rochei. Testing partially SST, and salinity affects (p<0.05) A. rochei, but chlorophyll-a alone does not affect A. rochei. The value of the determination coefficient was 0.796, which means that the influence of SST, chlorophyll-a, and salinity variables on the variable A. rochei was 79.6%, while 20.4% was influenced by other factors that were not included in the regression model. The mapping of the Fishing Potential Zone (ZPPI) can be used as a reference for determining the A. rochei fishing area as a prevention of a decline in A. rochei production in Prigi. ZPPI is an important process to improve the efficiency and sustainability of the fishing industry.