英文摘要 |
The Bigeye tuna (BET) and yellowfin tuna (YFT) are both the major target fishes of Taiwanese commercial tuna longline fishery (LL) in the Atlantic Ocean. In this study, we collected the Taiwanese LL fishery data, environment variables during the period of 1998~2007 to investigate the relationship between longline catch data and the oceanic environmental factors by factor analysis. GIS system is also used to combine this data set in order to investigate the relationship between the distribution of tunas and the oceanic environmental factors.
The three fishery area delimited by ICCAT and catch rate distribution in the Atlantic Ocean showed that the area II are the most important area in the Atlantic Ocean, the catch percentage in this area are 84%. In addition, the BET shows the averaged CPUE of whole Atlantic Ocean is 2.72 (inds/1000 hooks), the CPUE in area II are 3.93. The GIS maps with CPUE showed the high CPUE areas have the east-west spatial variations and the high CPUE areas always focused on the high PP areas. After factor analysis analyzing, the results shows high interrelated between SLL CPUE and NPP in second factor. Further, high CPUE and catch of DLL BET was appeared with the increasing of NTA index decreasing. Beside these factors, we also estimate the vertical temperature in 150 m has better R squared than other depth to explain the BET variation.
The yellowfin tuna (YFT) is one of the major target fishes of Taiwanese commercial tuna longline fishery (LL) in the Atlantic Ocean. In this study, we collected the Taiwanese LL fishery data, environment variables such as sea surface temperature (SST), sub-surface temperature, sea surface higher (SSH), chlorophyll-a concentration (Chl-a), net primary production (NPP) and North Tropic Atlantic Index (NTA) during the period of 1998~2007 to investigate the relationship between longline catch data and the oceanic environmental factors by principal components analysis (PCA). GIS system is used to combine this data set in order to investigate the relationship between the distribution of yellow-fin tuna and the oceanic environmental factors.
The eight yellow-fin tuna longline fishery areas were delimited by ICCAT in the Atlantic Ocean showed that the sub-area 3~4 are the most important area in the Atlantic Ocean, the catch percentage in this area are 73.6% respectively. In addition, the CPUE shows the averaged CPUE of whole Atlantic Ocean is 0.77(inds/1000 hooks), the CPUE in sub-area 3~4 is 1.24(inds/1000 hooks). The GIS maps of SST, PP with CPUE showed the high CPUE areas have the east-west spatial variations and the high CPUE areas always focused on the high PP areas. After Principle Component Analysis (PCA) analyzing, the first principle shows high interrelated between CPUE, SST, sea temperature at 105 and 328m, SSH and NTA index factors in the first principle. The second principle shows that the catch of yellow-fin tuna was high interrelated with the temperature subtraction of sub-area 3 and sub-area 3. Further, high CPUE of yellow-fin tuna are appeared with the increasing of sub-surface temperature in 2003~2005, especially in 2005. It also reveals a yearly evolution of CPUE, catch and oceanic condition in the Atlantic Ocean. |