Yellowfin tuna (Thunnusalbacares) fishing ground forecasting model based on bayes classifier in the South China Sea

• Autorzy: Zhou W. , Li A. , Ji S. , Qiu Y.

Identyfikatory

DOI

10.1515/pomr-2017-0076

• Języki publikacji: EN

Abstrakty

EN

Using the yellowfin tuna (Thunnusalbacares,YFT)longline fishing catch data in the open South China Sea (SCS) provided by WCPFC, the optimum interpolation sea surface temperature (OISST) from CPC/NOAA and multi-satellites altimetric monthly averaged product sea surface height (SSH) released by CNES, eight alternative options based on Bayes classifier were made in this paper according to different strategies on the choice of environment factors and the levels of fishing zones to classify the YFT fishing ground in the open SCS. The classification results were compared with the actual ones for validation and analyzed to know how different plans impact on classification results and precision. The results of validation showed that the precision of the eight options were 71.4%, 75%, 70.8%, 74.4%, 66.7%, 68.5%, 57.7% and 63.7% in sequence, the first to sixth among them above 65% would meet the practical application needs basically. The alternatives which use SST and SSH simultaneously as the environmental factors have higher precision than which only use single SST environmental factor, and the consideration of adding SSH can improve the model precision to a certain extent. The options which use CPUE’s mean ± standard deviation as threshold have higher precision than which use CPUE’s 33.3%-quantile and 66.7%-quantile as the threshold

Słowa kluczowe

EN

Bayes classifier; South China Sea; yellowfin tuna; fishing ground forecasting

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2017
• Tom: S 2
• Strony: 140--146
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Zhou W.

• Faculty of East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences 200090 Shanghai, China

autor

Li A.

• Faculty of East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences 200090 Shanghai, China
• College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China

autor

Ji S.

• Key Laboratory of East China Sea and Oceanic Fishery Resources Exploitation and Utilization, Ministry of Agriculture, China, 200090 Shanghai, China

autor

Qiu Y.

• South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China

Bibliografia

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• 19. Stech J L, Zagaglia C R, Lorenzzetti J A. 2004. Remote sensing data and longline catches of yellowfin tuna (Thunnusalbacares) in the equatorial Atlantic. Remote Sensing of Environment, 93(1-2):267-281.
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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).