| Summary: | 碩士 === 國立臺灣海洋大學 === 環境生物與漁業科學學系 === 98 === This study collected trawl fishery fish catch data from Tongkang, which located in the southwest Taiwan, from 1997 to 2007. These data were analyzed through GIS to find the species composition and their spatial-temporal distribution characteristics, and could be use as future fishery management and science research reference in this area.
Within the study period, the fishing vessels obtained 2,169,270 kg fish catch which were classified into 70 species. The dominate species were: non-target species (56.19%), Trichiurus lepturus (13.84%), Psenopsis anomala (4.42%), Loligo edulis (2.41%), Priacanthus macracanthus (2.25%), Muraenesox cinereus (2.21%), Sepia esculenta (1.86%), Johnius amblycephalus (1.31%). None-target species (bycatch) had the highest percentage, but their economic values were the lowest.
On different geographic area, the species composition of fish catch varied with topographic features. The dominant species of Kao-ping continental shelf were Psenopsis anomala (18.66%), Trichiurus lepturus (16.77%) and Loligo edulis (13.89%); the dominant species of Kao-ping submarine canyon were Psenopsis anomala (18.66%), Priacanthus macracanthus (11.55%) and Trichiurus lepturus (11.14%); the dominant species of Kao-ping continental slope were Trichiurus lepturus (16.99%) and Psenopsis anomala (10.57%). It was confirmed that the topography differentiation affected the diversity of species composition.
It is found that the the two major economic fish species of Trichiurus lepturus and Priacanthus macracanthus are related with water depth, and they mainly inhabit the water between 111-160m in depth. The highest CPUE of Trichiurus lepturus was happened between January and February around the area of Kao-ping continental shelf and Kao-ping continental slope. The months between November to next March had high CPUE of Priacanthus macracanthus and its distribution covered the whole fishing ground. The main fishing ground of important species was found having a Southeast–Northwest movement phenomenon when using spatial-temporal GIS to analyze the data collected.
|
|---|
