Skipjack tuna habitat in the western North Pacific was studied from satellite remotely sensed environment and catch data, using generalized additive models and geographic information systems. Weekly resolved remotely sensed sea surface temperature, surface chlorophyll, sea surface height anomalies and eddy kinetic energy data were used for the year 2004. Fifteen generalized additive models were constructed with skipjack catch per unit effort as a response variable, and sea surface temperature, sea surface height anomalies and eddy kinetic energy as model covariates to assess the effect of environment on catch per unit effort (skipjack tuna abundance). Model selection was based on significance of model terms, reduction in Akaike's Information Criterion, and increase in cumulative deviance explained. The model selected was used to predict skipjack tuna catch per unit effort using monthly resolved environmental data for assessing model performance and to visualize the basin scale distribution of skipjack tuna habitat. Predicted values were validated using a linear model. Based on the fourparameter model, skipjack tuna habitat selection was significantly (P < 0.01) influenced by sea surface temperatures ranging from 20.5 to 26°C, relatively oligotrophic waters (surface chlorophyll 0.08-0.18, 0.22-0.27 and 0.3-0.37 mg m )3 ), zero to positive anomalies (surface height anomalies 0-50 cm), and low to moderate eddy kinetic energy (0-200 and 700-2500 cm 2 s -2 ). Predicted catch per unit effort showed a trend consistent with the north-south migration of skipjack tuna. Validation of predicted catch per unit effort with that observed, pooled monthly, was significant (P < 0.01, r 2 = 0.64). Sea surface temperature explained the highest deviance in generalized additive models and was therefore considered the best habitat predictor.

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In this paper, we attempt to develop a reasonable catch forecasting method for skipjack tuna caught in the northeastern waters of Japan. In developing such a method, it is very important to find the main factors which control the catch fluctuations. The conventional method is based on the data of mean length and mean fatness of the fish harvested just before the fishing season, and the reproductive relationship estimated using the catch history. This approach, however, failed to forecast the catch in the years when the catch was extremely high. In this study, we therefore focused on the relationship be tween catches in the northeastern waters of Japan and the following three variables; (1) catch caught in the waters off Chiba Prefecture, (2) the Kuroshio current pattern, (3) the first date of capture of skip jack tuna in the waters off Chiba Prefecture, and then forecasted the catch using regression analysis The results showed that the accuracy of forecasting was very high almost every year including year when the catch was very high. It is considered that the method proposed here overcomes the problems of the conventional method.

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