Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt
This study models the spatial distribution of yellowfin tuna (YFT) in the Banda Sea using the MaxEnt approach, addressing critical questions about its predictive capability, the influence of environmental variables such as sea surface temperature (SST) and chlorophyll-a concentration, and temporal p...
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| Format: | Article |
| Language: | English |
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Diponegoro University; Association of Indonesian Coastal Management Experts
2025-03-01
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| Series: | Ilmu Kelautan |
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| Online Access: | https://ejournal.undip.ac.id/index.php/ijms/article/view/67214 |
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| author | Sunarwan Asuhadi Mukti Zainuddin Safruddin Safruddin Musbir Musbir |
| author_facet | Sunarwan Asuhadi Mukti Zainuddin Safruddin Safruddin Musbir Musbir |
| author_sort | Sunarwan Asuhadi |
| collection | DOAJ |
| description | This study models the spatial distribution of yellowfin tuna (YFT) in the Banda Sea using the MaxEnt approach, addressing critical questions about its predictive capability, the influence of environmental variables such as sea surface temperature (SST) and chlorophyll-a concentration, and temporal patterns. MaxEnt was chosen for its ability to predict potential distribution areas based on presence data and environmental factors. Data utilized include fish catch records obtained from the fishing logbook of the Ministry of Marine Affairs and Fisheries of the Republic of Indonesia, chlorophyll-a concentration, and SST data sourced from ocean color satellite observations. Model performance was evaluated using the Area Under the Curve (AUC) metric. Study results reveal that significant spatial and temporal variations in YFT distribution are influenced by oceanographic factors, with the model performing best in July (AUC 0.72) and lowest in April, September, and December (AUC ~0.60). SST was the dominant variable in November (82.35%), while chlorophyll-a had the highest contribution in April (83.02%). These findings highlight the dynamic link between tuna distribution and environmental conditions. The spatial maps offer insights for optimizing fishing practices, reducing pressure on overexploited stocks, and supporting sustainable fisheries management through data-driven approaches like MaxEnt. However, the MaxEnt model has limitations such as sensitivity to multicollinearity, overfitting, and low transferability. Future research could enhance accuracy and robustness by using advanced methods like Spatial Maxent, Monte Carlo Variable Selection, or ensemble modeling to support adaptive fisheries management. |
| format | Article |
| id | doaj-art-4b69d7ffffab40f0bf39d51fe2087ed0 |
| institution | DOAJ |
| issn | 0853-7291 2406-7598 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Diponegoro University; Association of Indonesian Coastal Management Experts |
| record_format | Article |
| series | Ilmu Kelautan |
| spelling | doaj-art-4b69d7ffffab40f0bf39d51fe2087ed02025-08-20T02:42:12ZengDiponegoro University; Association of Indonesian Coastal Management ExpertsIlmu Kelautan0853-72912406-75982025-03-0130110311410.14710/ik.ijms.30.1.103-11425477Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEntSunarwan Asuhadi0https://orcid.org/0009-0008-6327-0442Mukti Zainuddin1https://orcid.org/0000-0003-2018-7143Safruddin Safruddin2https://orcid.org/0000-0003-3877-6333Musbir Musbir3https://orcid.org/0000-0001-9447-7990National Research and Innovation Agency, IndonesiaFaculty of Marine Sciences and Fisheries, Hasanuddin University, IndonesiaFaculty of Marine Sciences and Fisheries, Hasanuddin University, IndonesiaFaculty of Marine Sciences and Fisheries, Hasanuddin University, IndonesiaThis study models the spatial distribution of yellowfin tuna (YFT) in the Banda Sea using the MaxEnt approach, addressing critical questions about its predictive capability, the influence of environmental variables such as sea surface temperature (SST) and chlorophyll-a concentration, and temporal patterns. MaxEnt was chosen for its ability to predict potential distribution areas based on presence data and environmental factors. Data utilized include fish catch records obtained from the fishing logbook of the Ministry of Marine Affairs and Fisheries of the Republic of Indonesia, chlorophyll-a concentration, and SST data sourced from ocean color satellite observations. Model performance was evaluated using the Area Under the Curve (AUC) metric. Study results reveal that significant spatial and temporal variations in YFT distribution are influenced by oceanographic factors, with the model performing best in July (AUC 0.72) and lowest in April, September, and December (AUC ~0.60). SST was the dominant variable in November (82.35%), while chlorophyll-a had the highest contribution in April (83.02%). These findings highlight the dynamic link between tuna distribution and environmental conditions. The spatial maps offer insights for optimizing fishing practices, reducing pressure on overexploited stocks, and supporting sustainable fisheries management through data-driven approaches like MaxEnt. However, the MaxEnt model has limitations such as sensitivity to multicollinearity, overfitting, and low transferability. Future research could enhance accuracy and robustness by using advanced methods like Spatial Maxent, Monte Carlo Variable Selection, or ensemble modeling to support adaptive fisheries management.https://ejournal.undip.ac.id/index.php/ijms/article/view/67214maxentspatial distributionyellowfin tunabanda seasea surface temperaturechlorophyll-a |
| spellingShingle | Sunarwan Asuhadi Mukti Zainuddin Safruddin Safruddin Musbir Musbir Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt Ilmu Kelautan maxent spatial distribution yellowfin tuna banda sea sea surface temperature chlorophyll-a |
| title | Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt |
| title_full | Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt |
| title_fullStr | Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt |
| title_full_unstemmed | Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt |
| title_short | Spatial Modeling of Yellowfin Tuna in the Banda Sea Based on Oceanographic Factors Using MaxEnt |
| title_sort | spatial modeling of yellowfin tuna in the banda sea based on oceanographic factors using maxent |
| topic | maxent spatial distribution yellowfin tuna banda sea sea surface temperature chlorophyll-a |
| url | https://ejournal.undip.ac.id/index.php/ijms/article/view/67214 |
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