| Summary: | 碩士 === 國立臺灣海洋大學 === 環境生物與漁業科學學系 === 98 === Empirical Habitat Suitability index (HSI) has been widely used to examine the quality of terrestrial animal, but rarely used in highly migratory fish like tuna. In this study, we used GIS technique to establish empirical models of HSI for yellowfin tuna (YFT) in the Western and Central Pacific Ocean (WCPO). Daily catch data from Taiwanese purse seiner fishery during 2003-2007 were aggregated monthly into 1 by 1 degree and then conduct data match process to obtain monthly average values for the multi-environmental factors, including sea surface temperature (SST), chlorophyll-a (SSC), height (SSH) and salinity (SSS). According to the frequency distribution of each factor on which YFT were caught, we transformed the values of the 4 factors into suitability index (SI) ranged from low to high (0-100%). These SI values were then combined into different empirical HSI models and the optimum one were selected by General Linear model. With the HSI, we have the major results of the analysis are as follows:
1. The optimum ranges of SST, SSC, SSH and SSS for YFT are 27.2～32.5 ℃, 0.02-0.18 mg/m3, 1.51～2.23 m and 34.22-35.25psu.
2. The optimum empirical HSI for TFT’s in the study area is converting the for SI (SST, SSH, SSC and SSS) by arithmetic mean model, by which the correct prediction rate is 71.97%.
3. The HSI began to increase and expand eastwards in March to April and rapid declined in November to next February in the study area. There was an agreement between the average HSI and total YFT catch. Also the high HSI area synchronized with the displacement of CPUE.
In this study, we used 4 kinds of surface variables derived from satellite to develop HSI for YFT in the WCPO. The HSI has been proved to a valid index for YFT habitat suitability in large-scale ocean and should be useful to measure the overall habitat able trend for YFT under future climate change in the region. However, the HSI is still unable to be used for fishing ground search due to the limitation of remote sensing data in temporal scale and the lack of subsurface information. There are more effort need to be further inserted for a more applicable HSI in operational level.
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