農業部-水產試驗所全球資訊網農業部-水產試驗所全球資訊網

本研究利用廣義加法模式 (GAM) 探討1998至2004年台灣小型鮪延繩釣雨傘旗魚 (sailfish) 的時空分布特性及其與海洋環境因子之相關性。其中，海洋環境因子包含衛星遙測海面水溫、海洋水色及海面高度等影像資料。利用廣義加法模式逐步分析結果顯示，影響雨傘旗魚棲息分布的最主要海洋環境因子是海面水溫，至於海洋水色及海面高度影響並不顯著。此外，雨傘旗魚的時空分布，也受時間變數中的年別及月別參數，及空間變數中的作業海域經度、緯度與作業水深等影響，並發現也與大尺度氣候變遷指標，如PDO及SOI等指數有相關性。其中，本研究結果發現雨傘旗魚主要漁期發生於每年5至11月份，其中6及7月份是主要盛漁期。另外，雨傘旗魚的主要漁獲海面水溫介於28 ~ 30 °C，其中最高單位努力漁獲量則發生於海面水溫29 °C海域。此外，本研究利用廣義加法模式建立之雨傘旗魚單位努力漁獲量與海洋環境因子之關係式，推算結果也與名目單位努力漁獲量，呈現顯著高度相關 (R2 = 0.52, p<0.000)。

This study applied the generalized additive models (GAMs) to examine the relationship between sailfish catch per unit effort (CPUE) from 1998 to 2004 and environmental variables, which included satellite-derived remote sensing data and other spatio-temporal variables in the marginal seas of the northwestern Pacific Ocean. The results of the stepwise GAMs analysis found less important influences upon sailfish CPUE from chlorophyll-a concentration (Chl-a) and sea surface height anomaly (SSHA). The final GAMs fitting model was constructed by the spatio-temporal variables, including the year, month, latitude, longitude, sea surface temperature (SST), Pacific decadal oscillation (PDO), southern oscillation index (SOI), and the bathymetry of operational factors. There was a significant relationship (R2 = 0.52, P < 0.0000) among the predicted values of GAMs analysis and nominal sailfish CPUE. It showed that the relatively high sailfish CPUE was found in June and July and a higher sailfish CPUE between 28 °C and 30 °C SST. The highest value of sailfish CPUE was found in 29 °C SST. These results can benefit to examine progressively the feeding and spawning habitats and its possible migratory route of sailfish in the northwestern Pacific Ocean.