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The multifaceted impacts of ‘ghost fishing’ are currently representing severe threats to the marine environment, with detrimental effects on ecosystems, species, and habitats. This article examines whether and how the tuna-RFMOs have implemented legal obligations applicable to minimize catch by abandoned, lost, or otherwise discarded fishing gear through a systematic assessment of all their adopted conservation and management measures between 2000 and 2023. The study yields several findings, including that two of the organizations at present have not adopted any measures to minimize catch by lost, abandoned, or otherwise discarded fishing gear, and that there generally exists considerable gaps between what is required as a matter of international law regulating fishing gear, and the efforts currently taken by the tuna-RFMOs to minimize ‘ghost fishing.’

The aquaculture sector is in pursuit of sustainable and cost-effective raw materials for feed, and the copepod Calanus finmarchicus is a marine zooplankton species of commercial interest because of its high abundance in northern areas. These copepods have the potential to meet the demand for vast quantities of marine raw materials. However, the lack of an energy- and catch-efficient trawl technology has limited the development of this fishery. Therefore, this study investigated the effect of two central trawl net design parameters mesh size and taper angle to identify which values that provide optimal trade-off balance between gear drag and catch efficiency. We conducted flume tank experiments using a series of plankton nets varying in mesh size (250–1000 μm), solidity ratio (0.54–0.76), and taper angle (5°– 30°) to acquire data on gear drag. The same nets were then used in fishing trials to obtain data on their catch performance. This study shows that zooplankton nets with a mesh size of approximately 500 μm and a low taper angle of about 5° provided the best trade-off between drag and catch performance.

Trammel nets are one of the least selective fishing gears and are known to catch a variety of species, many of which are discarded, including important invertebrates that are considered habitat-forming species. Although there are few studies focusing on this type of by-catch, these habitat-forming species include corals and sponges that are vulnerable to disturbances from fishing activities using bottom contact gear. Experimental fishing was conducted off the port of Portimão (southern Portugal) from November 2021 to April 2022 using standard and modified trammel nets rigged to be lifted off the bottom with the objective of reducing invertebrate by-catch and impacts on the bottom habitat. The modified lifted net caught 36% less by-catch of invertebrates in numbers than the standard net, with no significant decrease of biomass and value of target species. The results obtained with the two net types are discussed, as well as the necessity for good video recording equipment that can improve sampling accuracy, and the usefulness of interviewing the fishers on net performance after experimental fishing was conducted.

Background Depression, a prevalent mental disorder, has shown an increasing trend in recent years, imposing a significant burden on health and society. Adequate sleep has been proven to reduce the incidence of depression. This study seeks to explore how Weekend Catch-up Sleep (WCS) is connected with the prevalence of depression in the American population.Methods The National Health and Nutrition Examination Survey (NHANES) provides representative data for the U.S. population. We utilized data from the 2017–2018 and 2019–2020 cycles. Depression was operationally defined as a PHQ-9 score exceeding 10. WCS duration was categorized into five groups: no change in sleep duration (=0 h), decreased sleep duration (0 h, ≤1 h), moderate catch-up sleep duration (>1 h, Results Among the 8039 individuals, the distribution of WCS duration was as follows: no change (WCS = 0 h) in 2999 individuals (37.3 %), decreased sleep (WCS P = 0.007).Conclusion The prevalence of depression in individuals engaging in weekend catch-up sleep for 1 to 2 h is lower than those who do not catch up on weekends. This discovery on the treatment and prevention of depression provides a new perspective. However, further prospective research and clinical trials are needed for a comprehensive investigation.

Efficient management of set-net fisheries can be achieved by predicting fish catches in advance. We aimed to estimate fish catch volumes using machine learning based on the data obtained from past set-net fisheries. We also suggested that the estimation can be conducted without the installation of special sensors, such as fish finders, sonars, and cameras, in the set nets. Therefore, a special feature of this study is the construction of a machine learning model using marine environmental images around the set net. In particular, the distribution images of water temperature and current at a certain water depth were applied to the model. In set-nets where migratory fish are caught, ocean data related to migration routes can be useful for estimation. The images used in this study included the water temperature at a depth of 100 m, absolute velocity at a depth of 50 m, and sea surface temperature for comparison. We then classified the fish catch into three classes as follows: chum salmon, yellowtail, and Japanese common squid in Iwate Prefecture, Japan. Consequently, our results achieved an accuracy of approximately 70–80% compared with the validation and test dataset with the water temperature at depths of 100 m. They showed higher accuracy than the sea surface temperature and absolute velocity at a depth of 50 m. This study indicates the usefulness of image-based classification for predicting the volumes of fish caught by set nets.