Predicting the suitable habitat distribution of greater amberjack using the MaxEnt model with fishery and remote sensing data in the surrounding waters of Taiwan.

Mubarak Mammel, Baker Matovu, Sajna Beegum, Abdul Azeez Pokkathappada, Ming-An Lee, Li-Chi Cheng

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Mubarak MammelDepartment of Environmental Biology and Fisheries Science, National Taiwan Ocean University, No.2, Beining Rd., Zhongzheng Dist, Keelung City, 20224, Taiwan. mubarakagt@gmail.com.ORCID 0000-0002-5546-2531

Baker MatovuDepartment of Environmental Biology and Fisheries Science, National Taiwan Ocean University, No.2, Beining Rd., Zhongzheng Dist, Keelung City, 20224, Taiwan.ORCID 0000-0002-1814-5705

Sajna BeegumGovernment College of Education, Affiliated with Pondicherry University, Kadmat Island, Lakshadweep, India.ORCID 0009-0009-7526-5015

Abdul Azeez PokkathappadaICAR-Central Marine Fisheries Research Institute, Kochi, 682018, Kerala, India.

Ming-An LeeDepartment of Environmental Biology and Fisheries Science, National Taiwan Ocean University, No.2, Beining Rd., Zhongzheng Dist, Keelung City, 20224, Taiwan. malee@mail.ntou.edu.tw.ORCID 0000-0001-6970-7643

Li-Chi ChengCoastal and Offshore Fishery Research Center, Fisheries Research Institute, Ministry of Agriculture, No. 6 Yugang N. 3rd Rd., Qianzhen Dist, Kaohsiung City, 806043, Taiwan.

Funding

National Science and Technology Council 114-2611-M-019 -005

6 · The paper itself

Abstract

The increasing availability of satellite-derived remotely sensed oceanographic data offers significant potential for evaluating changes in habitat suitability driven by oceanographic phenomena and for informing scientific management strategies, particularly when coupled with maximum entropy (MaxEnt) methods. Oceanographic variables, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height (SSH), sea surface chlorophyll-a concentration (CHL), mixed layer depth (MLD), and eddy kinetic energy (EKE), alongside fishery data from Taiwanese fishing vessels, were collected for the period 2014-2019. The MaxEnt model is a widely employed method for predicting species' geographical distributions by analyzing species occurrence data in relation to environmental variables. Our results indicated that the annual response curves of habitat suitability were significantly influenced by environmental factors. Specifically, optimal environmental conditions for high habitat suitability were identified as SST > 24 °C, SSS < 35 PSU, SSH between 0.41 and 0.64 m, CHL > 0.22 mg/m

Indexed as

EcosystemFisheriesFishesRemote Sensing TechnologyAnimalsModels, TheoreticalSalinitySeasonsTaiwanTemperatureHabitat selectionHabitat suitability indexMaximum entropy modelOceanographic variableSatellite data

Identifiers

PMID42717223

DOI10.1038/s41598-026-60453-6

PMCPMC13558566

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