臺灣博碩士論文加值系統

本研究蒐集臺灣鮪釣漁船於印度洋釣獲黃鰭鮪的漁獲統計資料與多衛星和模式演算之不同水文環境資料，除了分析印度洋黃鰭鮪的時空間分布外，亦利用主成分分析及小波轉換分析法解明漁況與海洋環境變動關係，以及探討氣候變異與變遷下對黃鰭鮪漁況和時空間分布的影響。結果如下:
(一) 印度洋黃鰭鮪漁獲區域主要集中於阿拉伯海和中西印度洋兩個海域，分別各占印度洋黃鰭鮪總漁獲量之35%和47%，其中阿拉伯海之主要漁期集中於每年第一、二季，此時季平均名目單位努力漁獲量(catch per unite effort, CPUE)約為14.92 (fish/103 hooks)且季平均漁獲量約為401公噸，主要捕獲單尾平均漁獲重量大於30公斤的黃鰭鮪。而中西印度洋黃鰭鮪之漁獲量與努力量皆為印度洋最高之海域，但其名目CPUE無明顯的季節變動，其平均名目CPUE約為3.13 (fish/103 hooks)。至於南印度洋於每年6–10月時亦有大量的努力量集中於該海域，但黃鰭鮪之月別名目CPUE皆小於2(fish/103 hooks)。
(二) 阿拉伯海黃鰭鮪之CPUE主要與水溫、混合層深度與葉綠素a濃度變化有關。該海域於每年第二季表水溫最高時之海況穩定，水深105m之次表層水溫變化不明顯，而黃鰭鮪CPUE則有正向之變動趨勢，反之當第三季索馬利亞附近海域湧昇強度增強時，表水溫變低且水深105m之次表層水溫變化較劇烈，CPUE呈現的下降趨勢。此外，漁場位置亦主要分布於葉綠素a濃度值較高的區域，且與CPUE存在著1–3個月延遲的正向關係，此一現象顯示CPUE之變動可能受到餌料生物變動的影響。而高CPUE現象之出現則與混合層深度變動有關，當混合層深度較淺，單位體積內魚群密度的增加，致使淺層式鮪釣(regular longline, RLL)較易有高CPUE出現，反之，當混合層深度變深時，較高的海水溫度會增加黃鰭鮪的來游量且棲息深度也隨之變深，因此深層式鮪釣(deep longline, DLL)漁況較易出現高CPUE現象。而阿拉伯海與中西印度洋之RLL與DLL CPUE與海洋環境因子間之長期關係隨著時間推移有不同之周期變動，兩者皆於1980年代初期至1990年代中期RLL、DLL CPUE與表水溫和印度洋偶極模指數呈現顯著的正相關變動關係，並與混合層深度皆在著3年的變動周期關係。
(三) 鮪延繩釣黃鰭鮪的漁場重心位置會與印度洋偶極正負值有相似的變動趨勢，當偶極值為負時(負事件)，在西印度洋海域由於黃鰭鮪的最適表水溫(26–29.5°C)與淨初級生產力(220–380 C/m2/d)範圍的面積增加，也會使得黃鰭鮪的CPUE有上升的趨勢，但在偶極值為正時(正事件)，由於表水溫普遍高於黃鰭鮪的最適水溫範圍，且淨初級生產力減少，導致CPUE呈現下降的趨勢。顯示氣候變異所造成的海洋環境改變是影響黃鰭鮪鮪釣漁況的重要因子之一。

Yellowfin tuna (YFT; Thunnus albacares) is one of the main target species of the commercial tuna longline (LL) fishery and has a long history of being the subject of scientific research in the Indian Ocean. In this study, we collected Taiwanese LL fishery data and environment variables during the period of 1980–2005. The principal component analysis (PCA) and wavelet analysis were used to investigate the relationship between LL catch data of YFT and oceanic environmental factors. The results were summarized as below:
In the Indian Ocean, YFT is one of the most important target species in the Arabian Sea and Western-Center Indian Ocean. The major fishing season in the Arabian Sea is in the first and second quarters with a average nominal catch per unit effort (CPUE) about 14.92 fish/103 hooks and a average catch about 401 metric tons. In the Western-Center Indian Ocean, the catch and effort were the highest in all of the Indian Ocean and the average nominal CPUE was about 3.13 fish/103 hooks. Although there were highest effort in the Southern Indian Ocean from June to September, but the average nominal CPUE was lower than 2 (fish/103 hooks) and the average catch was lower than 50 metric tons.
Results of the PCA showed that monthly variations in values were significantly correlated with the sea surface temperature (SST), subsurface temperature at 105 m and chlorophyll-a concentration. In April and May, the SST was generally higher with deep mixed layer depth. After July, a drop in the temperature below the preferred temperature range for YFT is probably the reason why the CPUE subsequently decreased. In addition, the CPUE at a given time was significantly affected by chlorophyll-a concentrations 1–3 months prior to that time were probably due to a lag effect of trophic transformation. The regular LL (RLL) CPUE had a negative coefficient and deep LL (DLL) had a positive coefficient with the mixed layer depth anomaly. This implies that the shallow mixed layer depth produces a high CPUE for the RLL and the deep mixed layer depth causes a high CPUE for the DLL. In the long-term time series analysis, the main factor causing interannual variations in the CPUE of the RLL and DLL might change with time. RLL and DLL CPUE values showed positive correlations with SST and Dipole Mode Index from the beginning of the 1980s to the middle of the 1990s. The RLL and DLL CPUE were found to have a significant coherence of the two phases with a periodicity of 3 yr with and mixed layer depth.
Finally, we investigated the catches and distributions of yellowfin tuna in relation to climatic and marine environmental variations in the Indian Ocean. The gravity of yellowfin tuna fishing grounds showed similar variations with a climatic index, and an advanced time series analysis also showed a significant negative correlation between the climatic index and the CPUE with a periodicity of 2–3 yr. It suggested that decreases in areas of SST and net primary production optimal for YFT during positive Indian Ocean Dipole events would decrease the CPUE in the western Indian Ocean, while an increase in optimal areas would result in an increased CPUE in negative Indian Ocean Dipole events, especially in the Arabian Sea and surrounding seas of Madagascar.

目 錄............................................................................................I
表目錄.......................................................................................IV
圖目錄........................................................................................V
謝辭...........................................................................................XI
摘要.........................................................................................XII
Abstract.................................................................................XIV
第一章 導論...............................................................................1
1.1印度洋黃鰭鮪分布與鮪釣概況.....................................1
1.2印度洋海洋環境與氣候的變異.....................................2
1.3海洋環境變動對鮪類分布與資源之影響.....................3
1.4衛星遙測影像資料之應用.............................................5
1.5研究動機與目的……………………………….………6
第二章 黃鰭鮪漁況與海洋環境之關係...................................8
2.1材料與方法.....................................................................8
2.1.1漁獲資料收集與分析……….……………..……….……….8
2.1.2 泛線性模式CPUE標準化……….……………………….10
2.1.3 水文環境資料蒐集……….……………………………….11
2.1.4主成份分析法……….………………………………..……13
2.1.5 時間序列分析法…………………………………………..14
2.2印度洋黃鰭鮪漁獲資料之時空間分布.…..…….........18
2.3阿拉伯海漁況與海洋環境之特性................................20
2.3.1 阿拉伯海之海洋環境..………….………….….….……....21
2.3.2 阿拉伯海黃鰭鮪漁況變動………………….………....…22
2.3.3 影響黃鰭鮪漁況之主要環境因子……….…....................23
2.4 阿拉伯海與中西印度洋鮪釣作業型態與海洋環境之時序列分析.................................................................24
2.4.1淺層與深層式鮪釣黃鰭鮪之漁況…………….…….……25
2.4.2漁況與環境因子間之時序列變動趨勢……..….….….….26
2.5 討論…………………………………………….….…27
2.5.1 阿拉伯海海洋環境特性………………………..………...27
2.5.2 黃鰭鮪漁況與環境因子間的關係…………………….....28
2.5.3 1993與2004年黃鰭鮪高漁獲量之探討…………..............29
2.5.4 海洋環境變化對於鮪釣作業型態之影響…………..…...31
第三章 氣候變異與變遷對黃鰭鮪時空間分布之影響.........35
3.1 引言..............................................................................35
3.2 材料與方法..................................................................36
3.2.1漁獲資料收集與分析……………………………..………36
3.2.2 海洋環境資料蒐集……………………………………….37
3.2.3 漁獲重心之計算………………………………………….38
3.2.4 時間序列分析法………………………………….………38
3.3 氣候變異與黃鰭鮪時空間分布..................................39
3.3.1黃鰭鮪分布、漁況與印度洋偶極模指數.………….……39
3.3.2黃鰭鮪CPUE與DMI指數之時序列分析………….......39
3.4氣候變異對印度洋黃鰭鮪漁場之影響.......................40
3.4.1黃鰭鮪漁場重心與DMI變動之關係……………………40
3.4.2氣候變異對黃鰭鮪最適潛在棲地位置分布變動……..…40
3.5 討論..............................................................................42
3.5.1 氣候變異對黃鰭鮪漁況與分布之影響………………..……42
3.5.2 氣候變遷效應對黃鰭鮪漁場之影響…………………..……45
第四章 結論與未來展望.........................................................47
4.1 結論..............................................................................47
4.2 未來展望......................................................................48
References.................................................................................52
Tables and contents……..........................................................59
Figures and captions................................................................67

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