Mapping distribution patterns of skipjack tuna during January-May in the Makassar Strait

Abstract

Skipjack tuna is an important fishery species, targeted by purse seine and handline fisheries in Makassar Strait. Fish distribution patterns are markedly influenced by several underlying oceanographic factors. This study aimed to assess the relationship between skipjack CPUE and some oceanographic variables, and map out the distribution pattern of this fish in the study area during January-May 2018. To meet these objectives, we combined satellite data of sea surface temperature (SST) and chlorophyll-a concentration (chl-a) with catch data. We used generalized additive models (GAMs) to explore skipjack abundance in relation to the oceanographic conditions and we employed the gravity centre of fishing ground movements to map the fish distribution pattern. Results indicate that SST and chl-a significantly influenced skipjack tuna CPUE. The fish schools were mostly located in the eastern Makassar Strait. In January skipjack schools were initially in Majene offshore waters and moved to Mamuju waters in February. The skipjack schools returned to the border area between Polman and Majene waters in March and then made a continuous migratory journey to the south-western areas of Barru and Pare-pare offshore waters in April. In May, the skipjack tuna returned to concentrate in southern areas of Majene waters. We proposed that the fish schools followed a clock-wise distribution movement pattern where the habitat displacements may have a link with the dynamic ranges of preferred oceanographic conditions (habitat hotspots). It is likely that these areas provide good feeding opportunities for skipjack tuna.

Mapping spatial-temporal skipjack tuna habitat as a reference for Fish Aggregating Devices (FADs) settings in Makassar Strait, Indonesia

“…chlorophyll-a front area (Hidayat et al 2019a). These events are mainly related to SSC and SST (Zainuddin et al 2019) and corroborate our argument for determining the habitat of skipjack tuna using these two parameters. This study resulted in a high PHI value (PHI > 75%) to identify areas with fishing opportunities.…”

“…This method represents specific water characteristics in several coordinate points, and in the end, these coordinates are tested based on their performance in several months outside the time of analysis (January-October 2020). The formula used to determine the gravity center for a potential area is as follows (Zainuddin et al 2019):…”

The use of statistical models in identifying skipjack tuna habitat characteristics during the Southeast Monsoon in the Bone Gulf, Indonesia

“…Oceanographic phenomena in the waters, such as frontal oceanic zones, eddies, and upwelling areas, often occur with different characteristics as seen in the Bone Gulf and the Flores Sea (Zainuddin et al 2017(Zainuddin et al , 2019Hidayat et al 2019b). This event makes the waters very dynamic and affects the horizontal distribution of fish in the Bone Gulf.…”

DINAMIKA DAERAH PENANGKAPAN TUNA MADIDIHANG (Thunnus albacares) DI PERAIRAN LAUT BANDA

“…Analisis dinamika musim penangkapan menggunakan metode presentase rata-rata (The Average Percentage Methods) menurut runtun waktu dalam periode pengamatan (Kakenusa, 2006). Hubungan hasil tangkapan ikan dan dinamika parameter oseanografi (suhu permukaan laut, dan densitas klorofil-a) dengan menggunakan model statitstik Generalized Additive Model (GAM) (Safruddin et al, 2018;Zainuddin et al, 2019) dengan formula sebagai berikut: CPUE = α 0 +s1 (SPL) + s2 (klorofil-a) + ε dimana α 0 = konstanta; s n = smoothing function; βn (parameter oseanografi) = variabel bebas; ε =: standar error; g μij = pusat gravitasi bulanan tempat penangkapan ikan di posisi bujur dan lintang pada posisi Lij; CPUE = upaya penangkapan per unit (hasil tangkapan ikan /set) Gambar 1. Peta Daerah Operasi Penangkapan Tuna Madidihang Di Laut Banda…”