||Abstract of "The impact of climate change on resources and fishing ground of distant-water tuna fisheries": 1. "Impact of climatic change on major tuna stocks in the Pacific Ocean and Atlantic Ocean" : Based on the study of previous years, we try to evaluate the possible change trend of albacore, yellowfin, bigeye tunas and swordfish by utilizing the methodology established and multi-scale data of remote sensing as well as the future climate scenario simulation provided by IPCC. We aim to identify hotspots with climate impact and discuss future problems faced by industry and management. The result indicated that under A1B scenario hook rate of most area of the two Oceans will decrease over 50% in spite of the variation among species. In the Pacific Ocean, the hot spot of hook rate decline may occurs between 0°N and 20°S but those for North Pacific are dispersed. In the Atlantic Ocean, relatively high decreased areas are located in waters of low latitude and west of Africa. Due to empirical model for some species has low variance explained and high uncertainty of environmental simulation factors, we should be very conservative about the present evolution before we have carried out the latest evolution with improved model and more up-to-date IPCC simulation data. 2. "Effects of climate change on the tuna and billfish fishery Indian Ocean" : The purposes of this study were to investigate whether the climatic and marine environmental variations affect catche and distribution of tunas in the Indian Ocean. We modeled the effect of SST warming in a site-selection model i.e., scenarios given in the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC, 2007). The longline fishery data were used to evaluate transient relationships of the marine environmental change with catch rates and distributions of the fishing grounds and were also used to predict potential albacore habitats. Spatial distributions of nominal CPUE showed that high CPUE values were mainly concentrated in the southern Indian Ocean. The scenario SST and SSH showed the SST and SSH were increased from 2001 to 2100, especially SSH were increased faster in the Arabian Sea and Bay of Bengal. All variables included in the GAM selection process were significant (p＜0.01). The cumulative deviance explained by the selected GAM model was 65.9%. A normal quantile-quantile plot fitted to examine sample versus theoretical quantiles shows a nearly straight 1:1 line, implying that application of a Gaussian distribution was ideal. Almost half of the explained deviance was associated with longitude and latitude, and the CPUE also showed the negative and positive correlation with SST and SSH, separately.To predict spatial patterns of potential albacore habitats, statistical models were applied with the GAM model. The result showed the CPUE were decreased in the A2 scenario in the Indian Ocean. It indicated that CPUE were decreased about 10~15% in the southern Indian Ocean in the 2080 based on the 2008. However, the CPUE of albacore were increased about 0~5% in the high latitude area in the Indian Ocean.