Sustainable Fisheries Management Research Articles

The dynamics of social-ecological interactions in the PAAP (fisheries access management area) Taluk Lasolo Region, North Konawe Regency, Southeast Sulawesi Province: A comprehensive approach to sustainable renewal

Abstract This research aims to study the dynamics of social-ecological interactions in the Teluk Lasolo PAAP (Fisheries Access Management Area) in North Konawe Regency, Southeast Sulawesi Province. The study adopts a comprehensive approach to sustainable development, utilizing Social-Ecological Network Analysis (SENA). The Teluk Lasolo PAAP area is a complex environment with small-scale fisheries as a crucial component of the coastal ecosystem. Using the SENA method, this research analyzes the interactions between social and ecological dimensions in the context of fisheries management based on access rights. The study also considers economic aspects, governance, and resource utilization within the social-ecological network. The case study is conducted in the Teluk Lasolo area to understand the complex dynamics among various stakeholders, fishing communities, and the coastal ecosystem. The findings of this research will provide profound insights and knowledge about the factors influencing the sustainability of small-scale fisheries and offer recommendations for sustainable updates in fisheries resource management in the region. In conclusion, this research highlights the importance of a comprehensive approach involving social-ecological interactions in managing small-scale fisheries. The results of this study are expected to make a positive contribution to the development of sustainable fisheries management strategies in the Teluk Lasolo PAAP area and other coastal regions. Kata kunci : Kawasan PAAP Teluk Lasolo, Jejaring Sosial-Ekologi, Perikanan Skala Kecil, Pengelolaan Perikanan Berbasis Hak akses Perikanan.

Leveraging deep learning for coastal monitoring: A VGG16-based approach to spectral and textural classification of coastal areas with sentinel-2A data

Coastal ecosystems are vital for the planet's health, providing essential habitats for diverse species and supporting human communities. However, these complex environments face increasing threats from climate change and human activities. Effective monitoring of these areas requires large-scale, efficient, and accurate methods. This study explores the potential of deep learning for automated coastal land cover classification using Sentinel-2A satellite imagery on the Google Earth Engine (GEE) platform. We investigate the impact of transfer learning and spectral band combinations on classification accuracy for five coastal types: artificial, bedrock, sandy, muddy, and vegetation-covered. Our findings demonstrate that a pre-trained VGG16 Convolutional Neural Network (CNN) with transfer learning significantly improves classification accuracy (average 19.3% increase) compared to using default weights. Notably, including the near-infrared (NIR) band in training data leads to superior results, particularly for artificial and bedrock coastlines, where the NIR band's effectiveness in separating land-water boundaries enhances classification accuracy. These results highlight the potential of deep learning for large-scale, automated coastal monitoring, informing applications in sustainable fisheries management, coastal vulnerability assessment, and marine ecosystem conservation.

Krisis Biodiversitas Perairan: Investigasi Solusi Berbasis Komunitas untuk Pemulihan Ekosistem Aquatik

Crisis aquatic biodiversity is a critical environmental issue, triggered by human activities such as overfishing, pollution, and climate change, which have serious impacts on the stability of ecosystems and the climate change, which has serious impacts on the stability of ecosystems and the livelihoods of coastal communities. livelihoods of coastal communities. This research aims to examine community-based solutions in restoring degraded aquatic ecosystems, with a focus on the integration of sustainable aquaculture technologies and aquaponic systems. The methodology used was a comprehensive literature analysis of scientific articles, journals and relevant publications. The research findings show that sustainable fisheries management, habitat restoration, environmental education and awareness, implementation of environmentally education and environmental awareness, the application of environmentally friendly technologies, and the development of supportive policies are the main strategies for sustainable fisheries management. development of supportive policies are key strategies in improve conservation effectiveness. The implications of this research show that a community-based approach is not only effective for the conservation of aquatic biodiversity, but also provides practical guidance for policymakers and non-governmental organizations in designing and implementing community-based policy makers and non-governmental organizations in designing and implementing more holistic and effective ecosystem restoration programs that are more holistic and sustainable.

Evaluating the economic impact of distant water fleet activities on small-scale fishers in the South China Sea

This study assesses the economic impact of the People's Republic of China's Distant Water Fleet (DWF) on small-scale fisheries (SSFs) in the South China Sea (SCS), a vital area for marine biodiversity and the livelihoods of coastal communities. Through analysis of vessel tracking and local fisheries statistics from 2012 to 2020, the research investigates the effects of DWF activities on marine fish capture rates and socio-economic indicators in Indonesia, Malaysia, the Philippines, and Vietnam. Results indicate that a 1 % increase in PRC DWF activity leads to a 0.1 % decrease in SSF marine capture in Indonesia's FMA 711, a 0.05 % reduction in Malaysia, a 0.01 % drop in the Philippines, and a 0.04 % decrease in Vietnam. These findings highlight the significant negative impact of PRC's DWF presence on local marine fish captures, suggesting adverse effects on SSF livelihoods. The study underscores the importance of implementing sustainable fishing practices and strengthening regional cooperation to mitigate the negative consequences of foreign DWF activities on local economies and ecosystems. This research contributes to the discourse on marine policy and sustainable fisheries management in the SCS, emphasizing the critical need for international collaboration to address the challenges of DWF operations.

Integrating the water-energy-food nexus and LCA + DEA methodology for sustainable fisheries management: A case study of Cantabrian fishing fleets

The fishing sector constitutes an important source of economic revenue in northern Spain. In this context, various research studies have focused on the application of the five-step Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methodology to quantify environmental impacts of fishing systems. However, some of them have used environmental indicators that focus on individual environmental issues, hindering the goal of achieving integrated resource management. Therefore, in this study, the Water-Energy-Food (WEF) Nexus is employed as an integrative perspective that considers the synergies and trade-offs between carbon footprint, energy requirements, and water demand.The main objective of this study is to evaluate the operational efficiency and environmental impacts of Cantabrian fishing fleets. To this end, the combined use of LCA and DEA, along with the WEF Nexus, was applied to the Cantabrian purse seine fleet. DEA matrices were generated using the LCA-derived WEF nexus values as inputs to calculate efficiency scores for each vessel. Subsequently, based on the efficiency projections provided by the DEA model, a new impact assessment was performed to understand the eco-efficiency and potential environmental benefits of operating at higher levels of efficiency within this fleet.The average efficiency of the fleet was above 60 %. Inefficient units demonstrated a greater potential to reduce their environmental impacts (up to 65 %) by operating according to efficiency projections. Furthermore, the results revealed a strong dependence of environmental impacts on one of the operational inputs, i.e., fuel consumption. These findings highlight the significance of embracing holistic approaches that combine technical, economic, and social factors to achieve a sustainable balance in fisheries systems. In this regard, the five-step LCA + DEA method applied in conjunction with the WEF Nexus emerged as a suitable tool for measuring operational and environmental objectives.

ASSESSMENT OF THE RESOURCES SUSTAINABILITY USING RESOURCE UTILISATION AND CATCH PROJECTION APPROACH: CASE OF PRIGI GULF INDONESIA

Utilisation of fisheries resources requires good management to maintain the sustainability of fish resources. Based on these conditions, this study aims to analyse the status of fish resource utilisation and estimate fish catches in the following year. The data collection is secondary data from Prigi Fishery Port, East Java, from June to September 2023. This study evaluates biological surplus production relationships. Next, due to the time series data, the forecasting performance uses Holt-Winter’s exponential smoothing. The modelling shows that the best estimation value in the Fox model is based on the highest R2 (0,614) and the effort coefficient (0.000034). The maximum sustainable yield (CMSY) and the optimum catch effort (EMSY) values were 10.006 tonnes/year and 29,425 trips/year, respectively. It shows that biological overfishing has yet to occur. The average production forecasting results in 2021-2023 decreased 8.5% from the previous year. Forecasting fish catches in 2021 exceeds CMSY, but in 2022 and 2023, production is still below CMSY. The circumstance indicates that fishing operations are inefficient because the catch obtained is projected to be smaller with fixed effort. Possible management strategies, therefore, include creating sustainable fisheries management through improved work variation for fishers in the off-season.

Optimal mesh size of traps for marbled flounder (Pseudopleuronectes yokohamae) based on biological and economic factors

AbstractGear selectivity is crucial in fisheries management because it influences the size and species of fish caught, with traditional methods often basing optimal mesh size on the mature length of a target species. However, to ensure sustainable fisheries, both biological aspects of resource protection and fishing operation efficiency must be considered. This study aimed to determine the ideal mesh size for trap fishing of marbled flounder (Pseudopleuronectes yokohamae) in Gyeongsangnam‐do, South Korea, by using biological and economic factors for sustainable fisheries management. We sampled fish caught in traps of varying mesh sizes (35, 50, 65, 80, and 100 mm) and developed two models based on fish maturity, bycatch ratio, and CPUE. Model 1 used a maturity criterion of 17.8 cm, and Model 2 used the legal minimum length limit of 20 cm. Net selectivity curves indicated that the optimal mesh size ranged 50–65 mm based only on a minimum mature body length of 17.8 cm. In contrast, the optimal mesh size based on both biological and economic factors ranged 57.5–90 mm. Our findings could guide policymakers in enhancing marble flounder population management strategies through policy adjustments in mesh size and gear restrictions.

Long‐term changes in taxonomic and functional composition of European marine fish communities

Evidence of large‐scale biodiversity degradation in marine ecosystems has been reported worldwide, yet most research has focused on few species of interest or on limited spatiotemporal scales. Here we assessed the spatial and temporal changes in the taxonomic and functional composition of fish communities in European seas over the last 25 years (1994–2019). We then explored how these community changes were linked to environmental gradients and fishing pressure. We show that the spatial variation in fish species composition is more than two times higher than the temporal variation, with a marked spatial continuum in taxonomic composition and a more homogenous pattern in functional composition. The regions warming the fastest are experiencing an increasing dominance and total abundance of r‐strategy fish species (lower age of maturity). Conversely, regions warming more slowly show an increasing dominance and total abundance of K‐strategy species (high trophic level and late reproduction). Among the considered environmental variables, sea surface temperature, surface salinity and chlorophyll‐a most consistently influenced communities' spatial patterns, while bottom temperature and oxygen had the most consistent influence on temporal patterns. Changes in communities' functional composition were more closely related to environmental conditions than taxonomic changes. Our study demonstrates the importance of integrating community‐level species traits across multi‐decadal scales and across a large region to better capture and understand ecosystem‐wide responses and provides a different lens on community dynamics that could be used to support sustainable fisheries management.

The dynamics of catching aquatic bioresources in the south of Ukraine: Analysis, challenges and prospects for their solution in the context of sustainable development

Given the significance of fish farming as a promising sector of Ukraine’s agriculture, and the Mykolaiv, Odesa, and Kherson regions are characterised by a significant number of natural and artificial water bodies, the study of aquatic bioresource catching indicators in the south is both important and timely. The research aimed to determine trends in aquatic bioresource catching in southern Ukraine during the period 2018-2023 and to analyse the factors influencing the extraction of aquatic bioresources. This article presents overall catch statistics, as well as catch data for inland waters of the south and aquaculture conditions over the past six years. It has been established that the catch of aquatic biological resources in southern Ukraine has been declining each year from 2018 to 2023. The negative trends in aquatic bioresource catching, both in aquaculture and natural water bodies, are linked to several factors. In particular, the decline in catches has been influenced by: COVID-19; the unstable military and political situation in Ukraine, associated with Russian military aggression; outdated material and technical base of fishing enterprises; lack of government subsidies and foreign investment in the sector; imperfections in the systems of control and regulation of the extraction of aquatic bioresources; and irrational use of the bioproductive potential of water bodies in southern Ukraine. Based on a scientific analysis of the dynamics of aquatic bioresource extraction in southern Ukraine and the identification of key factors contributing to the decline in catches, a set of measures has been developed to positively impact the fishing industry. These measures include: attracting foreign investment in fish farming; improving the quality of monitoring, regulation, and control over aquatic bioresource catching at local, regional, and state levels; restoring critical fish farming infrastructure damaged by Russian aggression; ensuring sustainable fisheries management; and introducing EU best practices into Ukrainian fish farming. The scientific results obtained from this research can be used in practice to ensure the sustainable development of fisheries in southern Ukraine

Let’s measure it: An approach of high-resolution estimates of bottom fixed net fishing effort at national level

Fisheries are one of the most important food sources for human consumption whilst being amongst the most impacting and extractive activities happening within the marine environment, which makes it imperative to properly manage this activity. To improve fisheries management, the precise quantification of fishing effort is of the outmost importance. Yet, present methods for effort estimation, especially at broad scales, are hampered by difficulties in data access and usually rely on coarse effort metrics or on costly data collection for quantifying fishing effort with higher resolution. In the present work, we propose an approach of high-resolution fishing effort estimates of net fishing, as length of nets operated by a given fleet, at the national level. It relies on sampling of effort, derived from classified and easy to access vessel tracking data – AIS, and fishery dependent data – logbook and landings data. The proposed methodology combines trip-based effort estimates, derived from AIS data, as a foundation to extrapolate the total fishing effort, through the number of fishing trips linked to official landings and logbook data. It is estimated that in the years from 2014 to 2020 an average of 180 200 km of static nets (gillnets and trammel nets), which corresponds to approximately 4.5 and 210 times the lengths of the equator and the Portuguese Atlantic coastline respectively, are used in Portuguese mainland waters each year, by a fleet of slightly more than 100 vessels. The presented methodology allows to quantify and study the variation of the nominal fishing effort, at country level, with a higher resolution than what is usually used and at very low cost. We argue that such methodologies need to be developed and explored in order to have better and more comprehensive estimates of fishing effort which will contribute and improve the sustainable management of fisheries and the marine environment.

Croakers in three coastal areas of Lagos state, Nigeria: Sustainability levels and stakeholders’ perceptions on the use of ecosystem-based fisheries management

Croakers are an economically important fish species in Nigeria. Croakers are harvested by artisanal and industrial fisheries, providing a significant source of income and livelihood for coastal communities. Yet, human activities pose a significant threat to the survival of croakers in Nigeria. This study aims to evaluate the sustainability of croakers in the coastal waters of Lagos, Nigeria. The study also examines stakeholders' perceptions of Ecosystem-Based Fisheries Management (EBFM) as a tool for sustainable fisheries management in Nigeria. Questionnaires are used to collect data, and the Multidimensional Scaling Tool “Rapfish” is used to assess the sustainability level of croakers in three study areas. The results indicate that stakeholders have a positive attitude toward implementing EBFM. The sustainability analysis indicates degrees of sustainability of croakers at the boundary of being “less sustainable”. Specifically, the sustainability scores along the five dimensions analyzed are Ecological sustainability (55.69 %), economic (56.35 %), ethical (54.02 %), social (42.31 %), and technological sustainability (57.51 %). Based on these findings, the study derives several policy recommendations to improve the sustainability of croakers in Nigeria.

Existing datasets uncover complex interactions driving catches of a data‐poor recreational fishery in South Australia

AbstractUnderstanding drivers of effort and catch is important for sustainable management of recreational fisheries. For the Pipi (Latona deltoides) fishery in South Australia as a case study, publicly available datasets on fisher demography, market forces and internet connectivity improved understanding of fisher motivations and capabilities, identified different historical periods in the fishery and addressed temporal gaps in effort and catch estimates from on‐site surveys. Most variables were correlated with recreational effort and catch estimates from on‐site surveys and principal component analysis identified 2013–2014, 2015–2018 and 2019–2022 as distinct periods in the Pipi fishery. Results corroborated studies and anecdotal information that suggested declining availability and higher prices of local, commercially caught Pipi, and reduced imports of bivalves from Asia that previously supplied the South Australian bait market. Reduced availability and higher prices of Pipi likely motivated recreational fishers to gather their own bait to increase catch over the years. Similarly, increased internet and smartphone access and increased numbers of utility vehicles aided recreational catch efficiency of Pipi. Effective management of recreationally harvested resources requires understanding of external processes that drive fisher motivations and capabilities, particularly for stocks that are shared among fisheries. The need for improved data on fisher behaviour for management of recreational fisheries can be addressed by leveraging external information from available datasets. We recommend that the temporal gap between surveys should be less than 5 years, supplemented by analysing behavioural information collected from fishers during interviews.

Utilizing IOT and Geospatial Analytics for Sustainable Fisheries Management

This study developed a software application that integrates Internet of Things (IoT) devices and weather data to visualize prime fishing locations using advanced spatial data techniques. The application features a dashboard that processes and displays real-time data, providing insights into fishing trends, fisherman activities, boat locations, and environmental conditions. The application uses the Graham scan method to generate a GIS grid heatmap for visualizing fish populations and trends, enhancing fisheries management capabilities. Comprehensive testing and refinement ensured the application's usability and adaptability. The results demonstrated high user satisfaction, with a 91% rating in usability and accuracy. The Graham Scan method successfully mapped fishing zones, achieving a 97.96% overlap in spatial-temporal data analysis, proving essential for data-driven decision-making in sustainable fisheries management.

Migratory Ecology of Pseudoplatystoma fasciatum in the Amazon Basin Revealed by Otolith Microchemistry

Fish migrate for varied reasons, including to avoid predators and to access feeding, spawning, and nursery habitats, behaviors that enhance their survival and reproductive rates. However, the migratory ecology of many important fishes, especially those in river–floodplain ecosystems, remains poorly understood. One fish of the Amazon Basin whose migratory behavior is poorly understood is the catfish Pseudoplatystoma fasciatum. Here, we used otolith elemental microchemistry to characterize the migration ecology of P. fasciatum in the Amazon Basin. The main research questions of this study were: (1) does P. fasciatum move between waters with different Sr isotopic signatures (87Sr/86Sr) and chemical compositions? (2) What distance do they migrate? (3) Is the migration of P. fasciatum related to age? And (4) does P. fasciatum migrate mainly upstream, downstream, or in both directions? We assessed whether P. fasciatum migrates between waters with different 87Sr/86Sr values, comparing the Sr isotopic signature of otolith transects of each individual with the range of Sr isotopic signatures within the respective rivers. We found that 34% of the 71 fish analyzed migrated between rivers with different Sr isotopic signatures and 66% did not. The mean migration distance migrated was 126 km, with most specimens migrating between 72 and 237 km. Apparently, no fish of age one or age six or older migrated. All fish that migrated were between two and five years of age, with 20% of the specimens that migrated being two years old, 40% three years old, 30% four years old, and 20% five years old. Sixty-six percent of all individuals that migrated between rivers with different Sr signatures did so bidirectionally, while 33% moved unidirectionally. According to our definition of homing behavior in which fish migrated back to the same river where they were born, 41% of all fish that migrated displayed apparent homing behavior. Our findings provide insights into the migratory ecology of P. fasciatum, corroborating and refining knowledge reported in the literature. Our results on the migratory ecology of P. fasciatum have implications for sustainable fisheries conservation and management: conserving P. fasciatum requires habitat maintenance and suitable fishing practices in spawning and nursery habitats, and managers must consider large geographic areas for effective fishery management and conservation.

Forecasting fish recruitment using machine learning methods: A case study of arabesque greenling

Fish recruitment prediction is one of the most challenging topics in fisheries science. The recruitment of arabesque greenling in northern Hokkaido, Japan, which has been annually assessed for population size, greatly fluctuates. Whether the cause of fluctuation is environment or overfishing is controversial. We use a machine learning method for predicting the recruitment of arabesque greenling. Biological, fisheries-related, and environmental factors were included in the predictive models as feature variables. A gradient boosting model (GBM) showed better predictive performance compared with a simple hockey-stick stock-recruitment curve (HS), linear regression model (LRM), generalized additive model (GAM), and a random forest model (RFM) in terms of relative bias and relative root mean square error for recruitment prediction in the last 5 years. The most influential feature for GBM was spawning stock biomass in the last year, followed by the fishing rate for older fish and recruitment at the last year. The sea temperatures (STs) at the depth of 0, 50, 100, and 200 m were unimportant predictors in GBM. The difference in important predictors among models suggests the importance of nonlinearity and incorporating multiple variables simultaneously. This study highlights the potential usefulness of GBM for fish recruitment forecast and thereby sustainable fisheries management.

Sexual Dimorphism in Commercially Important Fish Species in India: A Review

Sexual dimorphism in fishes is an important biological aspect, which helps distinguish males and females based on various primary and secondary sexual characteristics. Based on sexual dimorphic characteristics fishes can be categorized as monomorphic, temporary dimorphic and permanent dimorphic. These characters can be either persistent or non-persistent types in fishes. Sexual dimorphism also can be determined using biometric characteristics as well. In fish, males typically display more conspicuous sexual characteristics compared to females, including the development of vibrant colouration, nuptial tubercles, or the formation of accessory organs. Sexual dimorphism is a significant trait helpful in categorizing and classifying fish species more accurately. It also has significant implications for commercial fisheries, which can aid in catch from the wild. This also can contribute to understanding the intricacies of aquatic ecosystems but also underscores the practical applications of studying sexual dimorphism in the context of sustainable fisheries management.

Using shell shape analysis based on landmarks to trace the geographical origin of the common cockle (Cerastoderma edule)

Determining the geographical origin of seafood is crucial for regulators and fishing industries who seek to prevent commercial fraud, enforce food safety regulations, and encourage high standards in sustainable fisheries management. The cockle, Cerastoderma edule (Linnaeus 1768), is a key species in estuarine ecosystems and is harvested all over Europe. Therefore, traceability tools using quick and inexpensive techniques to identify the origin of this bivalve are of paramount importance to support law enforcement. In this work, we explore the potential of using Geometric Morphometric (GM) methods to identify the geographical origin of cockle specimens. This method is based on landmarks identified in the shell to trace the origin of specimens obtained in nearby aquatic systems (from <35 km to <250 km distance). Specimens were collected in five aquatic systems (Ria de Aveiro, the Tagus and Sado estuaries, and the Albufeira and Óbidos coastal lagoons) in Portugal. Shells were digitalized and 16 landmarks were identified in each right valve and analyzed using Generalized Procrustes Superimposition. The discriminating power for traceability of 12 statistical and machine learning methods was assessed based on the corresponding shape variables, using R and Python (Linear Discriminant Analysis (LDA), Canonical Variable Analysis (CVA), Principal Component Analysis (PCA), Between-Group PCA (bgPCA), Partial Least Squares Discriminant (PLSD), Classification Regression Tree (CRT), Logistic Regression (LR), Random Forest (RF), Gradient Boosting (GB), K Nearest Neighbors (KNN), Support Vector Machines (SVM), Extending Gradient Boosting (XGBoost) and Neural Networks (NNET). LDA, CVA, SVM, and NNET demonstrated greater accuracy and a F1-score >80%, even with a small and unbalanced sample size. The highest percentage of correctly assigned individuals was obtained in the Tagus estuary (mean 89%) and in the Albufeira lagoon (mean 93%), which were also the systems with more specimens measured (174 and 59 respectively), whereas the worst results were obtained in the Sado estuary (50%, 56 specimens). In the Albufeira coastal lagoon, the best classification methods reached 100% correct classifications. It further highlights the importance of establishing statistical standards, such as the ones developed in the current work, to evaluate different methods, as small changes in the procedure may cause substantial differences in the results and conclusions. The revision of previous works (presented as a table) showed often >90% of correct classification in both bivalves and gastropods, highlighting the potential of the techniques for other mollusks. Our results support the use of GM based on landmarks as a reliable tool for bivalve's traceability, since it is a quick, simple and inexpensive approach. Further research should extend these findings to other species and other shape analysis techniques.

The Causes and Consequences of Public Misunderstanding of Shark Conservation.

Sharks and their relatives face serious conservation challenges. In addition to more effective implementation of regulations already on the books, they need more and stronger conservation and management policies to prevent the extinction of many species, which would have associated negative ecological and economic consequences. Many members of the public are aware of and concerned by shark conservation challenges, but there is widespread misunderstanding of the threats to sharks and the available policy solutions to address those threats. Such misunderstanding has been spread by both well-intentioned but uninformed shark enthusiasts (i.e., people who care and want to help but have limited or incorrect knowledge of key facts and evidence) and also by extremist activist organizations (i.e., those far outside of mainstream norms). Specifically, many members of the public incorrectly believe that the practice of shark finning (and associated demand for shark fins) is the largest or only threat to sharks. In general, the public is far less familiar with widely used and effective tools such as sustainable fisheries management as a solution to shark conservation threats. Many members of the public incorrectly believe that banning the 1% of the global shark fin trade that is the most sustainable will be a major victory for shark conservation. Many members of the public are heavily influenced by information from uninformed extremists rather than from experts. These misunderstandings result in suboptimal policy outcomes, and even conflict between stakeholder groups that ostensibly share goals or desired outcomes. This perspective summarizes a decade of work attempting to understand the causes and consequences of widespread misunderstanding about shark conservation threats and solutions, mapping each along the Science-Policy Interface. It also proposes solutions focusing on sharing our hard-earned expertise with the interested public in an accessible format.

Potential of communication devices for estimating the fishing effort of purse seine fleets

Fishing impacts the marine environment significantly, and quantifying this impact requires precise fishing effort data. This study explores the challenges associated with accurately estimating fishing effort by purse seiners and proposes a solution using records collected from real-time communication devices on fishing fleets. The estimation of fishing effort based on high-frequency GPS data can be verified with the onboard visual records. Additionally, by linking vessels within a fleet, the method utilizes information from carriers (vessels that transport fish) to enhance the estimation. Through the use of generalized additive models, this study effectively estimates the fishing effort of Japanese purse seiners, demonstrating their accuracy. Furthermore, by incorporating carrier information, models based on matched records prove to have superior predictive performance compared to those based on fishing vessel or carrier records alone. These findings lay the foundation for the potential of this approach to provide precise and cost-effective information for sustainable fishery management. The affordability of GPS devices and the common requirement of communication devices across various fleets further support the feasibility of implementing this approach.

Assessing the use of Fisher knowledge in oceanic eco-social networks of Peru: A comprehensive approach to sustainable fisheries management and governance

This study is the first attempt to determine the local stability and resilience of the highly exploited oceanic ecosystem of Peru, integrating the use of fisher knowledge (FK) by government institutions (GI), which could increase sustainable governance and improve the design of management strategies. To do this, five simplified semi-quantitative eco-social models with different levels of complexity were constructed. The Routh-Hurwitz local stability criterion 1 (RH1) showed that all models (with and without the link between FK and GI) exhibited the highest percentages of transient stable states in the scenario of demand and fishers in self-negative feedback (D- & F-). Only the least complex eco-social models (models 1 and 2) exhibited an increase in the average values of Fs (stability) and Fn (resilience) when connecting FK with GI, whereas the more complex models showed the opposite trend. Although the link that connects FK by GI would allow increasing the number of stable transient states in the most complex eco-social models (models 3, 4 and 5), however FK would be self-controlled, that is, an evaluation of the quantity and quality of the information available is required. Since the models constructed are simplifications of the eco-social system studied, they allowed us to identify the conditions of stable/resilient (sustainable) scenarios, which would help us in decision-making and governance based on the use of FK in Peruvian fisheries management and monitoring.