期刊
REMOTE SENSING OF ENVIRONMENT
卷 93, 期 1-2, 页码 267-281出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2004.07.015
关键词
generalized additive models; remote sensing; yellowfin tuna; Thunnus albacores; tropical Atlantic; CPUE; longline
This study investigates the relationship between yellowfin tuna (Thunnus albacares) caught in the tropical Atlantic between 15degreesS and 15degreesN and 10degreesW and 55degreesW by the northeast Brazilian longline fleet, and environmental variables obtained from remote sensors such as sea surface temperature (AVHRR/NOAA), chlorophyll-a concentration (SeaWiFS/SeaStar), sea surface height anomaly (TOPEX/Poseidon), and wind velocity (Scatterometer/ERS-1 and -2). The observed relationships between longline catch data, expressed as catch per unit effort (CPUE), and the satellite data were analysed using the statistical method of generalized additive models (GAMs). CPUE was calculated as the number of fish caught by 100 hooks in V latitude by V longitude square grid and integrated into a month of fishing activity for the period of 1995-2000. Results obtained showed evidences of non-linear relationships between catch yields and environmental data. The largest CPUE of yellowfin tuna in the region seems to be strongly associated with the Intertropical Convergence Zone (ITCZ) position and its temporal variability. In the model, this was confirmed by the highest correlation of CPUE with the meridional wind component. This result also indicates 5degreesS as the southern limit for a larger concentration of this species during the most productive fishing period between March and May. In decreasing order of importance, sea surface temperature, chlorophyll-a concentration and sea surface height anomaly, albeit statistically significant, seemed to be of secondary importance in controlling this species abundance in the region. (C) 2004 Elsevier Inc. All rights reserved.
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