Spatial Distribution Models for the Four Commercial Tuna in the Sea of Maritime Continent using Multi-Sensor Remote Sensing and Maximum Entropy

金枪鱼 黄鳍金枪鱼 长鳍金枪鱼 图努斯 环境科学 海面温度 渔业 海洋学 空间分布 炸鸡金枪鱼 海面高度 地理 生物 遥感 地质学
作者
Emi Yati,Lilis Sadiyah,Fayakun Satria,Irene D. Alabia,Sayidah Sulma,Teguh Prayogo,Sartono Marpaung,Hastuadi Harsa,Dony Kushardono,Jonson Lumban Gaol,Aris Budiarto,Diding Sudira Efendi,Sri Patmiarsih
出处
期刊:Marine Environmental Research [Elsevier BV]
卷期号:198: 106540-106540 被引量:1
标识
DOI:10.1016/j.marenvres.2024.106540
摘要

The dynamic of marine environmental parameters affects the distribution of commercial tuna in the sea of the maritime continent. Hence, the objectives of this study are to develop spatial distribution models for the four main tuna species in the Maritime continent's sea with reasonable accuracy, identify their correlation with marine environmental parameters, and investigate areas of interaction between those tuna species. The study develops the distribution models for albacore (Thunnus alalunga), bigeye (Thunnus obesus), yellowfin (Thunnus albacares), and skipjack (Katsuwonus pelamis) tuna species, utilizing multi-sensor satellite remote sensing and maximum entropy. The results show models have good performance, focusing on environmental factors such as sea surface temperature (SST), chlorophyll-a (CHL), and sea surface height anomalies (SSHA), combined with eddy kinetic energy (EKE). Seasonal variations in potential tuna habitats are revealed, emphasizing the influence of those marine environmental conditions. From December to May, the four commercial tuna species were distributed in conditions characterized by SST of 26-31.5°C, CHL levels of 0-3 mg/l, SSHA of -0.3 to 0.2 m, and EKE of 0-1 m2/s2, while from June to November, they experienced SST of 23-31°C, CHL levels of 0-4 mg/l, SSHA of -0.5 to 0.3 m, and EKE of 0-1.1 m2/s2. The spatial persistence of the four tuna species emerged mainly around the south sea of Java, with skipjack being the most common species found in the sea of the maritime continent. With sufficient and evenly distributed tuna presence records, the results indicate the potential for extrapolation beyond the training data to estimate habitat suitability for the four commercial tuna distributions. The results also suggest potential competition between tuna species sharing ecological niches and highlight possible overlapping areas where different tuna species interact with the same fishing gear.
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