| The ablacore (Thunnus alalunga) is one of the main targets in tuna longline fishery, which is mainly caught by China (including Taiwan province), Japan and other countries. The South Pacific is the important fishing ground for Thunnus alalunga, accounting for about 50% of the total catch. In the recent years, with many countries joining into the South Pacific albacore fisheries, and increasingly strict international management of albacore, it is need for conducting the fisheries resource assessment and management. With the rising of international oil prices, it's more important to effectively find out the main fishing ground to reduce the fuel cost. Therefore, the establishment of albacore predicting model and the development for corresponding fisheries software is very important for sustainable utilization.According to Chinese fishery data from albacore tuna fishery in the South Pacific, combined with satellite remote sensing of sea surface temperature, deep water temperature, sea surface height and Chlorophyll a concentration, the relationship between fishing ground and marine environment factors are analyzed in the South Pacific. Also the suitability index model is established by using a linear regression, and the HSI model by using arithmetic mean model (AMM). Finally, the fishery forecasting system is developed by use of IDL lauguage. The results are as follow:(1) The result shows that the fishing grounds are distributed in the waters of 12°S-14°S and 172°E-175°E, and the suitable SST ranged from 29 to 30℃during January to April. During May to June, the fishing grounds are located in the waters of 10°S-15°S and 174°E-175°E, and the suitable SST is 28-29℃. In July the production was highest in the whole year, the fishing grounds are distributed in the areas of 10°S-15°S, 170°E-175°E and 23°S-24°S, 175°E-177°E, its suitable SST are 27-29℃and 23-24℃respectively. During August to September, the monthly fishing grounds are distributed in the areas of 24°S-26°S and 174°E-176°E, 13°S-16°S and 173°E-175°E respectively, the monthly suitable SSTs are 21-23℃and 27-28℃respectively. In October the fishing ground is distributed in the waters of 12° S-17°S, 173°E-176°E and 14°S -15°S, 159°E-161°E, and its suitable SST is 27-29℃. During November to December, the monthly fishing grounds are located in the areas of 16°S-19°S and 171°E-174°E, 19°S-22°S and 173°E-175°E, their monthly suitable SSTs are 28-29℃. The K-S test indicated that the formation of fishing grounds is closely related with SST.(2) The result shows that the suitable ranges of T55, T105, T155, T205, sea surface height (SSH) and CHL-a from January to December are variable. In January, the suitable ranges are 28-29℃, 24-26℃, 23-24℃, 21℃, 0.8-0.9m, 0.04 mg/m3 respectively. In February the suitable ranges of these environmental variables are 28-29℃, 24-26℃, 23-24℃, 21℃, 0.8-0.9m, 0.04 mg/m3 respectively. In March the suitable ranges of these environmental variables are 28-29℃, 26-27℃, 23-24℃, 21℃, 0.8-0.9m and 0.02 mg/m3 respectively. In April the suitable ranges of these environmental variables are 27-29℃, 27-28℃, 24-25℃, 22℃, 0.8-1.0m, 0.04 mg/m3 respectively. In May the suitable ranges of these environmental variables are 28-29℃, 26℃, 26℃, 21℃, 0.9m, 0.02 -0.04 mg/m3 respectively. In June the suitable ranges of these environmental variables are 27-28℃, 25-27℃, 23-25℃, 21-22℃, 0.9-1.0m, 0.04 mg/m3 respectively. In July the suitable ranges of these environmental variables are 27-28℃, 27℃, 21℃, 21-22℃, 0.9m, 0.04 mg/m3 respectively. In August the suitable ranges of these environmental variables are 21-22℃and 26-27℃, 21℃and 26-27℃, 20-23℃, 19-21℃, 0.6-0.9m, 0.06-0.08 mg/m3 respectively. In September the suitable ranges of these environmental variables are 27℃, 27℃, 25℃, 21℃, 1.0m, 0.02 mg/m3 respectively. In October the suitable ranges of these environmental variables are 26-27℃, 26℃, 24℃, 22℃, 0.9-1.0m, 0.08 mg/m3 respectively. In November, the suitable ranges of these environmental variables are 26-27℃, 25-27℃, 23-25℃, 21-22℃, 0.9m, 0.08 mg/m3 respectively. In December the suitable ranges of these environmental variables are 24-25℃, 22-24℃, 21-23℃, 20-21℃, 0.9m and 0.08 mg/m3 respectively.(3) The suitability index model for each environmental factor is set up by using of non-linear regression. The results showed that all the models of suitability index show significant (P<0.05) . Also the HSI model is established by using of AMM.(4) Coded with Visual programming language IDL and ANSI C, and combined with the marine environments data derived from satellite remote sensing, we developed a platform for forecasting fishing ground with multi-source information integration on the basis of HSI model. (5) The 5 levels for both the HSI index and the products data are derived by using the natural boundary method and are used to verify the accuracy of the model. The result showed that the accuracy rate of forecasting fishing ground was 62% during January to March, and reached 83% during April to June, 61% in early July and September, 59% in late July and August and 74% during October to December. The average accuracy rate in total reached 70%. The results showed that the established HSI model can be used to predict the fishing ground of albacore accurately in the South Pacific. |
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