Spatial distribution models for the four commercial tuna in the sea of maritime continent using multi-sensor remote sensing and maximum entropy

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

doi:10.1016/j.marenvres.2024.106540

Spatial distribution models for the four commercial tuna in the sea of maritime continent using multi-sensor remote sensing and maximum entropy

Mar Environ Res. 2024 May 3:198:106540. doi: 10.1016/j.marenvres.2024.106540. Online ahead of print.

Authors

Affiliations

¹ National Research and Innovation Agency Republic of Indonesia (BRIN), Jakarta, Indonesia. Electronic address: emiyati@gmail.com.
² National Research and Innovation Agency Republic of Indonesia (BRIN), Jakarta, Indonesia.
³ Arctic Research Center, Hokkaido University, N21 W11 Kita-Ku, Sapporo, 001-0021, Japan.
⁴ Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University, Bogor, Indonesia.
⁵ Ministry of Marine Affairs and Fisheries Republic of Indonesia (MMAF), Jakarta, Indonesia.

PMID: 38704933
DOI: 10.1016/j.marenvres.2024.106540

Abstract

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.

Keywords: Habitat; Marine ecology; Maritime continent; Maximum entropy; Multi-sensor; Remote sensing; Species distribution; Tuna.