1Faculty of Marine Science and Fisheries, Hasanuddin University, Indonesia
2Indonesian National Institute of Aeronautics and Space (LAPAN) Parepare, Indonesia
3Jl. Jend. A. Yani KM. 6, Kota Parepare, 91112 Indonesia, Indonesia
BibTex Citation Data :
@article{IK.IJMS9212, author = {Mukti Zainuddin and Safruddin Safruddin and Muhammad Selamat and Aisjah Farhum and Sarip Hidayat}, title = {Prediction of Potential Fishing Zones for Skipjack Tuna During the Northwest Monsoon Using Remotely Sensed Satellite Data}, journal = {ILMU KELAUTAN: Indonesian Journal of Marine Sciences}, volume = {22}, number = {2}, year = {2017}, keywords = {}, abstract = { One of economically important fish in the Bay of Bone is Skipjack tuna which their distribution and migration are influenced by surrounding environment. This study aims to investigate the relationship between skipjack tuna and their environments, and to predict potential fishing zones (PFZs) for the fish in the Bone Bay-Flores Sea using satellite-based oceanography and catch data. Generalized additive models (GAMs) were used to assess the relationship. A generalized linear model(GLM) constructed from GAMs was used for prediction. Monthly mean sea surface temperature (SST) and chlorophyll-a during the northwest monsoon (December-January) together with catch data were used for the year 2012-2013. We used the GAMs to assess the effect of the environment variables on skipjack tuna CPUE (catch per unit effort). The best GLM was selected to predict skipjack tuna abundance. Results indicated that the highest CPUEs (fish/trip) occurred in areas where SST and chlorophyll-a ranged from 29.5°-31.5°C and 0.15 - 0.25 mg m -3 , respectively. The PFZs for skipjack were closely related to the spatial distribution of the optimum oceanographic conditions and these mainly developed in three locations, northern area of Bone Bay in December, in the middle area of the bay (4°-5.5°S and 120.5°-121.5°E) during January and moved to the Flores Sea in February. The movement of skipjack concentration was consistent with the fishery data. This suggests that the dynamics of the optimum oceanographic signatures provided a good indicator for predicting feeding grounds as hotspot areas for skipjack tuna in Bone Bay-Flores Sea during northwest monsoon. Keywords : skipjack tuna, potential fishing zones, satellite based-oceanographic data, Northwest monsoon }, issn = {2406-7598}, pages = {59--66} doi = {10.14710/ik.ijms.22.2.59-66}, url = {https://ejournal.undip.ac.id/index.php/ijms/article/view/9212} }
Refworks Citation Data :
One of economically important fish in the Bay of Bone is Skipjack tuna which their distribution and migration are influenced by surrounding environment. This study aims to investigate the relationship between skipjack tuna and their environments, and to predict potential fishing zones (PFZs) for the fish in the Bone Bay-Flores Sea using satellite-based oceanography and catch data. Generalized additive models (GAMs) were used to assess the relationship. A generalized linear model(GLM) constructed from GAMs was used for prediction. Monthly mean sea surface temperature (SST) and chlorophyll-a during the northwest monsoon (December-January) together with catch data were used for the year 2012-2013. We used the GAMs to assess the effect of the environment variables on skipjack tuna CPUE (catch per unit effort). The best GLM was selected to predict skipjack tuna abundance. Results indicated that the highest CPUEs (fish/trip) occurred in areas where SST and chlorophyll-a ranged from 29.5°-31.5°C and 0.15 - 0.25 mg m-3, respectively. The PFZs for skipjack were closely related to the spatial distribution of the optimum oceanographic conditions and these mainly developed in three locations, northern area of Bone Bay in December, in the middle area of the bay (4°-5.5°S and 120.5°-121.5°E) during January and moved to the Flores Sea in February. The movement of skipjack concentration was consistent with the fishery data. This suggests that the dynamics of the optimum oceanographic signatures provided a good indicator for predicting feeding grounds as hotspot areas for skipjack tuna in Bone Bay-Flores Sea during northwest monsoon.
Keywords: skipjack tuna, potential fishing zones, satellite based-oceanographic data, Northwest monsoon
Article Metrics:
Last update:
Proceedings of the International Conference on Radioscience, Equatorial Atmospheric Science and Environment and Humanosphere Science
Last update: 2024-12-26 03:23:45
The status of catch per unit effort (Cpue) and utilization rate of skipjack tuna (katsuwonus pelamis) in the kolaka waters, southeast Sulawesi, Indonesia
Aqua MODIS and altimetry satellite data utilization for determining the effective time and area of fishing in South Sulawesi
Fishing gear allocation and catch landing of purse seine in southern coast of sulawesi, indonesia
Copy this form and after filling it, please send it to ijms@live.undip.ac.id:
COPYRIGHT TRANSFER STATEMENT
When this article is accepted for publication, its copyright is transferred to ILMU KELAUTAN Indonesian Journal of Marine Sciences, UNDIP. The copyright transfer covers the non exclusive right to reproduce and distribute the article, including reprints, translations, photographic reproductions, microform, electronic form (offline, online) or any other reproductions of similar nature.
The author warrants that this article is original and that the author has full power to publish. The author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. In regard to all kind of plagiarism in this manuscript, if any, only the author(s) will take full responsibility. If the article is based on or part of student’s skripsi, thesis or dissertation, the student needs to sign as his/her agreement that his/her works is going to be published.
Title of article :...........................................................................................................................Name of Author(s) :...........................................................................................................................Author’s signature :...........................................................................................................................Date :...........................................................................................................................
View My Stats