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Dedi Purwanto Indra Kusuma
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Journal of Marine Fisheries
Published by Lembaga Penelitian dan Pendidikan (LPP) Kalibra
ISSN : -     EISSN : 31108016     DOI : https://doi.org/10.70716/marfish
Core Subject : Science, Agriculture,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Immunology & microbiology
Journal of Marine Fisheries (MARFISH) is a peer-reviewed open-access journal published by Lembaga Penelitian dan Pendidikan (LPP) Kalibra with registered number of e-ISSN 3110-8016. This journal aims to be a forum for researchers, academics, practitioners, and policymakers in disseminating research results, scientific studies, and the latest innovations related to sustainable marine fisheries. MARFISH covers fisheries biology, fisheries technology, fisheries resource management, fisheries oceanography, marine ecology, mariculture, marine biological resource conservation, fish stock modeling, and socio-economic issues in the marine fisheries sector. Published articles include original research, literature reviews, new methodologies, and case studies relevant to the development of science and policy in the field of marine fisheries. MARFISH applies a strict double-blind peer-review process to ensure academic integrity and quality. Manuscripts can be submitted in English or other primary languages, accompanied by an abstract in English.
Arjuna Subject : Ilmu Pertanian dan Biologi (Semua) - Ilmu Perairan
Articles 21 Documents
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Identification of Optimal Habitat of Spanish Mackerel (Scomberomorus commerson) Using a Species Distribution Modeling Approach in Tropical Waters Zaidan Sastrawan; Sandipan Wijaya
Journal of Marine Fisheries Vol. 2 No. 1 (2026): Journal of Marine Fisheries, March 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/marfish.v2i1.329

Abstract

Narrow-barred Spanish mackerel (Scomberomorus commerson) is one of the most economically important pelagic fish resources distributed throughout tropical and subtropical waters. The distribution of this species is influenced by various oceanographic factors, including sea surface temperature, chlorophyll-a concentration, salinity, water depth, and ocean current dynamics. Advances in remote sensing technology and Species Distribution Models (SDMs) have enabled more accurate and efficient identification of optimal habitats. This study aims to review the application of SDMs in identifying the optimal habitat of S. commerson in tropical waters based on recent scientific studies. A literature review approach was employed, focusing on publications that examined mackerel distribution and habitat modeling using Maximum Entropy (MaxEnt), Generalized Additive Models (GAM), Habitat Suitability Index (HSI), and Ensemble Modeling approaches. The review indicates that sea surface temperature and chlorophyll-a concentration are the most influential environmental variables affecting the distribution of S. commerson. The optimal environmental conditions generally occur within a sea surface temperature range of 26–30°C and chlorophyll-a concentrations between 0.2 and 1.0 mg m⁻³. SDM approaches provide effective spatial predictions for supporting sustainable fisheries management, identifying potential fishing grounds, and assessing the impacts of climate change on fish distribution. The integration of remote sensing data, oceanographic parameters, and advanced modeling techniques offers significant potential for improving fisheries resource management and habitat conservation in tropical marine ecosystems.
Analysis of the Relationship between Spawning Stock Biomass and Demersal Fish Recruitment Using a Non-Linear Model in the Lombok Strait Waters Andi Prayitno; Siska Amalia; Jhony Michael
Journal of Marine Fisheries Vol. 2 No. 1 (2026): Journal of Marine Fisheries, March 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/marfish.v2i1.330

Abstract

This study analyzes the relationship between spawning stock biomass (SSB) and demersal fish recruitment in the Lombok Strait using a non-linear modeling approach. The background of this research is the importance of understanding stock-recruitment dynamics for sustainable fisheries management, particularly in heavily exploited marine areas. The objective is to identify the mathematical form of the relationship between SSB and recruitment and to evaluate the performance of Ricker, Beverton-Holt, and alternative non-linear models. The methods include time-series analysis, non-linear parameter estimation using least squares, and model evaluation based on the Akaike Information Criterion (AIC) and coefficient of determination (R²). The data consist of spawning stock biomass estimates and recruitment indices derived from fisheries catch data and surveys. The results indicate that the non-linear model provides the best fit compared to classical models, showing a clear density-dependent pattern. Increases in SSB do not always lead to higher recruitment due to environmental variability and fishing pressure. In conclusion, the SSB–recruitment relationship for demersal fish in the Lombok Strait is non-linear and strongly influenced by environmental conditions. These findings support ecosystem-based fisheries management policies.
Integration of Fishers’ Local Ecological Knowledge and Satellite Oceanographic Data for Modeling Potential Skipjack Tuna (Katsuwonus pelamis) Fishing Zones in the Southern Waters of East Java Rahmat Andi Prasetyo; Dewi Kartika
Journal of Marine Fisheries Vol. 2 No. 1 (2026): Journal of Marine Fisheries, March 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/marfish.v2i1.331

Abstract

Skipjack tuna (Katsuwonus pelamis) represents one of the most economically important pelagic fish in the eastern Indian Ocean, particularly in the southern waters of East Java. This study integrates fishers’ local ecological knowledge (LEK) with satellite-derived oceanographic data to model potential fishing zones. The objective is to improve spatial prediction of fishing grounds by combining experiential knowledge with environmental indicators. The study used a mixed-method approach involving structured interviews with fishers and analysis of sea surface temperature and chlorophyll-a derived from satellite imagery. Spatial modeling was conducted using a habitat suitability approach supported by GIS analysis. Results indicate that optimal fishing zones were consistently associated with sea surface temperatures between 26–29°C and moderate chlorophyll-a concentration. Fishers’ LEK strongly aligned with satellite-based predictions, confirming the reliability of traditional knowledge in identifying productive fishing areas. The integration of both data sources significantly improved spatial accuracy of fishing zone mapping. This study concludes that combining LEK and remote sensing enhances fisheries resource prediction and supports sustainable fishing strategies in tropical marine ecosystems.
Potential Habitat Modeling of Kawakawa (Euthynnus affinis) Based on Sea Surface Temperature and Chlorophyll-a Variability in the Bali Strait Siska Wulandari; James Carter
Journal of Marine Fisheries Vol. 2 No. 1 (2026): Journal of Marine Fisheries, March 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/marfish.v2i1.332

Abstract

Kawakawa (Euthynnus affinis) distribution is strongly influenced by oceanographic variability, particularly sea surface temperature (SST) and chlorophyll-a concentration. This study models potential habitat distribution in the Bali Strait using satellite-derived SST and chlorophyll-a data. A spatial analysis approach was applied to identify habitat suitability patterns based on optimal environmental ranges. Results indicate that Kawakawa potential habitat is concentrated in waters with SST of 27–30°C and chlorophyll-a of 0.2–0.6 mg/m³. High suitability zones occur in areas with moderate thermal conditions and elevated productivity, particularly in central and northern parts of the Bali Strait. The habitat model shows strong alignment with observed fishing grounds, indicating that environmental variability effectively structures spatial distribution. These findings support the use of oceanograpqhic indicators for predicting fishing zones and improving spatial fisheries management
Sustainability Status of Small-Scale Tuna Fisheries Based on the Ecosystem Approach to Fisheries Management Taufan Setyono; James Edward Collins; Nayafadila
Journal of Marine Fisheries Vol. 2 No. 1 (2026): Journal of Marine Fisheries, March 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/marfish.v2i1.333

Abstract

Small-scale tuna fisheries play a critical role in food security and coastal livelihoods in Indonesia. However, increasing fishing pressure, habitat degradation, and weak governance threaten their sustainability. This study aims to analyze the sustainability status of small-scale tuna fisheries using the Ecosystem Approach to Fisheries Management (EAFM). The research applies a systematic literature review of 50 scientific sources covering ecological, economic, social, and institutional dimensions. The results show that most fisheries are classified as moderately sustainable, while some areas demonstrate good ecological conditions and a smaller portion show poor sustainability status. Ecological performance is identified as the most sensitive dimension, particularly influenced by fish size reduction, habitat pressure, and Fish Aggregating Devices (FADs) usage. Institutional weakness and inconsistent enforcement further limit sustainability outcomes. Economic conditions vary across regions, with income instability affecting fishers’ resilience. The study concludes that strengthening ecosystem-based governance, improving monitoring systems, and controlling fishing effort are essential to ensure long-term sustainability of small-scale tuna fisheries in Indonesia.
Impact of Sea Surface Temperature Variability on Pelagic Fisheries Productivity Rudi Hartono; Sarah Feronica; Yohana Joly
Journal of Marine Fisheries Vol. 2 No. 2 (2026): Journal of Marine Fisheries, June 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

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Abstract

Sea surface temperature variability is a major driver of change in marine ecosystems and pelagic fisheries productivity. This study analyzes the relationship between SST variability and pelagic fisheries performance using a quantitative longitudinal design. The analysis integrates satellite-based temperature data, fisheries catch records, and ecological indicators over time. The objective is to examine how changes in ocean temperature influence catch levels, catch efficiency, and species distribution patterns. The results show a consistent increase in sea surface temperature variability across the study period. This increase is accompanied by declining stability in pelagic fisheries productivity, particularly in tropical regions. Catch per unit effort and total catch exhibit negative responses to sustained warming conditions. Spatial analysis further reveals significant redistribution of pelagic fish populations, with a gradual shift toward cooler, higher-latitude waters. These changes indicate that marine species are actively tracking suitable thermal habitats. Statistical analysis confirms a significant relationship between SST variability and fisheries productivity. The effects are non-linear, with stronger declines observed beyond specific temperature thresholds. The findings suggest that warming oceans reduce ecosystem stability by disrupting primary productivity and altering food web dynamics. Overall, the study demonstrates that sea surface temperature variability plays a central role in shaping pelagic fisheries outcomes. It affects both the abundance and spatial distribution of marine resources. These results highlight the need for adaptive fisheries management strategies that account for ongoing ocean warming and increasing environmental variability.
Analysis of the Influence of Sea Surface Temperature Anomalies on Changes in Small Pelagic Fisheries Productivity in the Northern Waters of East Jawa Andi Darmawan; Rina Awaliyah Putri
Journal of Marine Fisheries Vol. 2 No. 2 (2026): Journal of Marine Fisheries, June 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

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Abstract

Sea surface temperature anomalies play an important role in regulating marine ecosystem productivity and small pelagic fisheries in tropical waters. This study analyzes the relationship between sea surface temperature (SST) anomalies, chlorophyll-a variability, and small pelagic fisheries productivity in the northern waters of East Java based on an integrative literature review and secondary oceanographic data synthesis. The study compiles findings from satellite-based observations and fisheries catch records across Indonesian waters. Results indicate that SST anomalies strongly influence chlorophyll-a distribution and subsequently affect fish aggregation and catch variability. Upwelling and ENSO–IOD interactions significantly regulate nutrient availability, leading to seasonal shifts in fishing grounds. Several studies confirm that optimal SST ranges between 27°C and 30°C support high pelagic fish productivity, while deviations reduce catch efficiency. The synthesis shows consistent patterns across the Java Sea and surrounding waters, confirming the ecological sensitivity of small pelagic fish to oceanographic variability. The study concludes that SST anomalies are a key driver of fisheries productivity changes in northern East Java waters.
Modelling Potential Fishing Zones of Mackerel Tuna (Euthynnus affinis) Using Sea Surface Temperature and Chlorophyll-a Derived from Satellite Remote Sensing in Fisheries Management Area 712, Java Sea, Indonesia Muhammad Fadhil; Indah Raehana; Ema Pujiono
Journal of Marine Fisheries Vol. 2 No. 2 (2026): Journal of Marine Fisheries, June 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

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Abstract

Mackerel tuna (Euthynnus affinis) is one of the economically important pelagic fish species in Indonesian waters. The distribution of this species is strongly influenced by oceanographic conditions, particularly sea surface temperature (SST) and chlorophyll-a concentration. This study aims to identify and model potential fishing zones (PFZs) of mackerel tuna in Fisheries Management Area (FMA) 712, Java Sea, using satellite-derived SST and chlorophyll-a data. Monthly SST and chlorophyll-a datasets obtained from MODIS Aqua were analyzed spatially and temporally. Fishing catch data were integrated with oceanographic variables to determine suitable habitat conditions for mackerel tuna. Geographic Information System (GIS) techniques and spatial overlay analysis were employed to generate PFZ maps. Results indicate that mackerel tuna catches were predominantly associated with SST ranging from 28–30°C and chlorophyll-a concentrations between 0.3–1.5 mg m⁻³. High potential fishing zones were concentrated in the northern and central parts of the Java Sea, particularly during the transitional and southeast monsoon seasons. The integration of SST and chlorophyll-a significantly improved the identification of productive fishing grounds. This study demonstrates the applicability of satellite remote sensing as an effective tool for supporting sustainable fisheries management and improving fishing efficiency in FMA 712.
The Effect of East and West Seasonal Variability on Demersal Fish Recruitment Patterns in Coastal Waters of NTB Rauhul Azmi; Budi Sentosa; Antoni Mujtaba
Journal of Marine Fisheries Vol. 2 No. 2 (2026): Journal of Marine Fisheries, June 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

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Abstract

This study analyzes the influence of east monsoon and west monsoon variability on demersal fish recruitment in coastal waters of West Nusa Tenggara. Climate-driven oceanographic changes strongly regulate fish recruitment dynamics in tropical and temperate systems. Recruitment variability is linked to larval survival, hydrodynamics, and temperature fluctuations. This research uses a multi-source approach combining catch data, larval abundance records, and climate indices during 2010–2024. The results show that the west monsoon period increases nutrient input and larval abundance, while the east monsoon strengthens upwelling and redistributes juvenile fish stocks. Recruitment peaks occur during transitional seasons when environmental stability improves. Similar patterns of climate-driven recruitment shifts have been documented in other marine ecosystems. The study concludes that seasonal variability is a dominant driver of demersal fish recruitment in NTB waters, with implications for fisheries management under climate change scenarios
Machine Learning-Based Prediction of Sardine (Sardinella lemuru) Fishing Grounds Using Oceanographic Parameters in the Bali Strait I Made Radiansyah; Rahmawati Astuti; Juliatin Harahap
Journal of Marine Fisheries Vol. 2 No. 2 (2026): Journal of Marine Fisheries, June 2026
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

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Abstract

The distribution of small pelagic fish is strongly influenced by oceanographic variability. This study aims to synthesize and model the prediction of fishing grounds for Sardinella lemuru in the Bali Strait using machine learning-based habitat approaches. The study integrates sea surface temperature (SST), chlorophyll-a, and climate variability as primary predictors. A systematic literature-based modeling framework is developed using findings from previous studies and advanced habitat modeling approaches such as Maximum Entropy (MaxEnt) and Generalized Additive Models (GAM). Results show that SST and chlorophyll-a significantly control spatial fish distribution through upwelling dynamics and primary productivity enhancement. Climate variability, particularly the Indian Ocean Dipole (IOD) and ENSO, intensifies seasonal shifts in fish aggregation patterns. Machine learning-based models consistently improve prediction accuracy of potential fishing zones compared to conventional approaches. Studies by Akita et al. (2023), Semedi et al. (2022), and Gustantia et al. (2022) confirm that environmental variables can explain spatial habitat suitability with high reliability. The study concludes that integrating satellite remote sensing with machine learning models provides a robust framework for sustainable fisheries management in the Bali Strait.

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