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The Mayan octopus (Octopus maya) and the American octopus (O. americanus) are the two species that support the octopus fishery on the Campeche Bank. The large-scale fleet catches both species. However, landings are recorded as American octopus in the official statistics, and this causes a problem for the management of the fishery. The large-scale octopus fishery on the Campeche Bank was studied using a model based on data from interviews with skippers. A total of 180 valid interviews were conducted in the base ports of Progreso and Yucalpeten (Yucatan), representing 51.1% of the skippers in the fleet in 2019. This information was used for the first time to estimate catch per unit effort (CPUE) and total catches for each octopus species. The mean CPUE ranged between 50 and 500 kg day-1, with minimums of 10 kg day-1. The mean estimated potential catches ranged from 5069 to 3456 t per year for O. maya and from 4113 to 2805 t per year for O. americanus. The relationship between official landings and estimated catches showed a significant correlation (rxy=0.898). The total estimated catches were on average 20% lower than the official landings of O. americanus. The origin of this discrepancy is discussed.

Catch per unit of effort (CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model (GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatial- GLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran’s I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.

In this study, we applied generalized additive model to investigate the influence of spatial temporal variables and vessel length on catch per unit-effort (CPUE) of Atlantic bluefin tuna (ABFT) purse seine fishery using catch and effort data from commercial logbooks and field surveys from 1992 to 2006. The vessel lengths of sampled purse seines ranged from 20 to 64 m. The number of ABFT caught within each operation varied between 1 and 2000. A total of 386 CPUE values for ABFT were calculated 0.05 and 60 t ⋅ (haul day)–1 with mean CPUE of 5.51 ± 0.54 t ⋅ (haul day)–1. Although the sea surface temperature had little influence on the CPUE, the effect of time and spatial variables, vessel length and salinity was found as significant. In conclusion, the spatial dynamics of ABFT should be considered if the impact of fisheries on the ecosystem is to be reduced.

The silver-cheeked toadfish (Lagocephalus sceleratus) is an invasive species of highest concern. Its population must be controlled to mitigate its negative impacts on marine ecosystems, fishers, fisheries and human health. This study thoroughly investigates the biology, diet and catchability of the L. sceleratus stock from Finike, Turkey from March 2017 to February 2018 in order to better manage its invasion. A total of 751 specimens were sampled for this study with a M/F ratio of 1.25/1. The species becomes sexually mature at three and a half years of age, and Lm50 was 41.39 cm for males and 42.08 cm for females. Its spawning season in this region was from June to August, peaking in July. Its diet was mostly crustaceans in spring, fish in summer and both fish and crustaceans in winter. This species consumed a large amount of other pufferfish species, resulting in over a quarter of its fish diet. The trophic level of L. sceleratus was 4.41, demonstrating that it is indeed a top predator carnivore in the eastern Mediterranean Sea. Ingested fishing gear parts such as net pieces and hooks were found in about 10% of the fish. A slight modification of longlines using steel branch lines and a swivel hook resulted in double the catch per unit effort than standard longlines, so this technique can be used to target and control more of this invasive species, which is a national priority.

Fishing gear-based landings or survey methods are often used to make assessments of species stock abundance. In order to convert catch into abundance values, estimates or assumptions are made on the catch efficiency of the gear-based method. This is the case in areas where flat oysters, Ostrea edulis , are surveyed for fisheries and conservation objectives in a range of projects across Europe. Flat oyster dredge efficiency assumptions vary widely from 5–30% in published studies and uncertainty in what is an appropriate efficiency estimate has led some survey teams to switch to Catch-per-unit-effort (CPUE), where CPUE is also of concern should catch efficiency change with shellfish density, ground type or some other unmeasured variable such as shellfish distribution. We undertook an experimental approach to estimate dredge efficiency in a standard ladder dredge used to harvest and survey adult flat oysters in the UK and Ireland. The dredge efficiency trials assessed how efficiency was influenced by oyster density (between 1 and 2.2 oysters m 2 ), distribution (clumped vs uniform) and ground types across a gradient of more hard to more soft surface sediments. Dredge efficiency was significantly affected by oyster distribution, but also density and ground hardness as well as their interactions. While a median value between 7 and 10% seems an appropriate universal ladder dredge efficiency to adopt, ground type and distribution had such an effect that local conditions may effect this considerably. Catch efficiency was negatively density-dependent, this makes CPUE methods challenging where oyster densities are likely to vary. Practitioners, regulators and researchers conducting surveys can improve CPUE approaches through standard techniques and knowledge of how catch efficiency varies as we have presented here.

The muskrat (Ondatra zibethicus) is an invasive species in Europe. The extensive waterways of the Netherlands provide ideal habitat for muskrats, and a large population established itself after arrival in 1941. A control program was put into effect immediately because muskrat burrowing can compromise the integrity of dikes and, hence, poses a significant public safety risk. The current (2015) annual catch of approximately 89,000 individuals is equivalent to approximately 0.30 muskrats/km of waterway, well above the national objective in spite of decades of effort. The control program is expensive (€35 M annually) and contested by animal rights groups. These factors created the need for a careful evaluation of the full range of control possibilities, from ‘no control’ to ‘extermination.’ As part of this, we experimentally evaluated the validity of a previously published correlation (based on historical data) between catch and effort. We raised or lowered removal effort (2013–2016) in a stratified random sample of 117 5-km × 5-km ‘atlas squares’ from the national grid. We found that catch-per-unit effort (CPUE) decreased after effort was increased, and rose after effort was decreased, by amounts slightly greater than expected based on the correlational data, though confidence intervals enclose zero. As anticipated, CPUE varied consistently and strongly between seasons. The biggest (and unanticipated) effects were those of the catch in the preceding 3 years (‘history’), and surrounding area (‘neighborhood’). Our experiment confirms estimates of intensity of control required to lower muskrat populations. These results will help with more effective allocation of control effort, and better-informed evaluation of the economic costs of various control options.

The European pilchard (Sardina pilchardus), also known as sardine, is one of the important small pelagic species in terms of biomass and commercial interest in its areas of occurrence. In Northwest Africa, little is known about this species regarding its status and biology. However, for effective management of this resource, it is vital to understand its distribution and parameters that may influence its catch rate. The present study aims to standardize the catch per unit effort (CPUE) for the European pilchard and examine the influence of environmental factors on the catch rate distribution of sardines in Northwest African waters. This information would be analyzed based on various data schemes provided by the Fishery Committee for the Eastern Central Atlantic (FAO-CECAF). Generalized Additive Model (GAM) and Generalized Linear Model (GLM) were developed for this analysis. GAM was used to determine which environmental variable had the greatest effect on the distribution of European sardines, while GLM was used for the CPUE standardization of European sardines. The results suggest that Catch, Sea surface temperature (SST), Coastal upwelling index (CUI) and Chlorophyll-a Concentration (Chl) were the variables with high influence on the distribution of European pilchard. The standardised CPUE results by GLM showed distinct CPUE peaks around 2000, 2006, and 2013–2014. The most recent years (after 2015) show lower CPUE values than the earlier periods, suggesting potential changes in fishing efforts. The study showed the effect of ecological, environmental factors resulting from climate change on sardine population information.

Small-scale fisheries are globally marginalized by management institutions; thus, they have to endure the consequences of ineffective regulations, environmental uncertainty, social traps and market inequity. Small-scale fisheries in Peru, one of the world’s leading fishing countries, are important contributors to national employment, food security and gross domestic product. Yet, relatively little is known about these fisheries and their evolution, except for the fact that the Peruvian small-scale fleet size is rapidly increasing. Here, we developed several indicators to assess changes in the fishing efficiency and economic performance of this fleet. Segmented regression analysis was used to identify statistically significant breakpoints and changes in their trajectories between 1950–2018. Our results suggest that fishing effort has strongly increased, and at much faster rates than the catches, particularly since 2006. The combined effect of these trends results in significant declines in the fleet’s ratio indicators (i.e., catch per unit of effort, revenue per unit of effort, and fisher’s incomes relative to Peru’s minimum wage), suggesting that the growing fishing effort is unsustainable and uneconomic. The behavior of these indicators differs within the fleet, depending on the vessel’s main fishing method. Most small-scale fishers are currently living in relative poverty. Yet, fishers using the least selective fishing gears, or engaged in illegal fishing, had the most stable incomes over the past decade. These findings are discussed in detail by exploring the social, legal and economic drivers fostering fleet growth. Finally, a list of general recommendations aimed at improving fisheries sustainability and fisher’s wellbeing was produced, based on the local context, fisheries literature and common sense.

Catch-per-unit-effort (CPUE) standardization in fisheries is a critical foundation for conducting stock assessment and fishery conservation. The Pacific sardine (Sardinops sagax) is one of the economically important fish species in the Northwest Pacific Ocean (NPO). Hence, the importance of choosing an appropriate CPUE standardization model cannot be overstated when it comes to achieving a precise relative abundance index for the efficient management of Pacific sardine fishery. This study’s main aim was to assess and compare the efficacy of three models, specifically the General Linear Model (GLM), the Generalized Linear Mixed Model (GLMM), and the spatio-temporal GLMM (VAST), in the CPUE standardization for Pacific sardine fishery in the NPO, with the ultimate goal of identifying the most appropriate model. An influence analysis was applied to analyze the impact of individual variables on the disparity among standardized and nominal CPUE, and the main explanatory variables influencing standardized CPUE were identified. A coefficient–distribution–influence (CDI) plot was generated to analyze the impact of the different models on the annual standardized CPUE. Additionally, a simulation testing framework was developed to evaluate the estimated accuracy of the three models. The results indicated that the standardized CPUE and the nominal CPUE exhibited similar trends between 2014 and 2021 for the three models. Compared to the GLM and the GLMM, the VAST demonstrates larger conditional R2 and smaller conditional AIC, indicating a better performance in standardizing the CPUE for Pacific sardines due to its consideration of spatial and temporal variations. The interaction terms within the three models exert significant influences on the annual standardized CPUE, necessitating their inclusion in the model construction. CDI plots indicate that the spatio-temporal influence of the VAST model exhibits a smaller variation trend, suggesting that the VAST is more robust when standardizing the CPUE for Pacific sardines. Simulation testing additionally demonstrated that the VAST model displays smaller model root mean squared error (RMSE) and bias, establishing it as the superior performer for standardizing CPUE. Our results provide a theoretical basis for the scientific management of Pacific sardines in the NPO and can be extended to CPUE standardization for other small pelagic fish species worldwide.

This study examined long-term trends (1991–2019) in landings and fish community structure in the four Egyptian Nile Delta lakes. Using fisheries data, we explored trends in the catch per unit effort (CPUE) and temporal dynamics of landings and fishing effort. Non-metric Multidimensional Scaling (nMDS) and Similarity Percentage Analysis (SIMPER) were employed to assess long-term changes in fish community structure. The results revealed variable productivity across the lakes. Lake Manzala often exhibited higher yields between 1991 and 2004, and notably in 2013 (e.g., 62,372 tons), while Lake Burullus peaked at 81,399 tons in 2019. A reciprocal trend was often observed in their total yields. Lake Burullus catches were dominated by Tilapia and Mullets, while Edku and Mariout showed lower productivity. CPUE patterns varied, with Lake Manzala showing a notable increase, peaking at approximately 52 tons per boat per year in 2013, and Lake Burullus experienced a sharp increase to about 29 tons per boat per year in 2019. A shift towards amateur fishing was observed predominantly in Lake Manzala, alongside a decline in traditional licensing. An increase in fishers operating without boats was also noted across all the Northern Lakes, with contributions from Lake Edko and Lake Manzala. nMDS and SIMPER analyses revealed distinct temporal groupings of years within each lake, indicating significant shifts in fish community structure, likely in response to invasive species, pollution, and habitat degradation. These findings underscore the need for lake-specific management and long-term monitoring to address unsustainable fishing and ecological changes, ensuring biodiversity conservation and fisheries sustainability in the region.