タイランド湾北東沿岸に分布するホンダワラ類の生態

学位の種別: 論文博士審査委員会委員 : （主査）東京大学准教授 小松 輝久, 東京大学准教授 山川 卓, 東京大学准教授 岩滝 光儀, 東北大学准教授 青木 優和, 北里大学准教授 林崎 健一University of Tokyo(東京大学

Fatty acids composition of 10 microalgal species

Fatty acids composition of 10 species of microalgae was determined at the exponential phase and the stationary phase. The microalgae consist of two species of diatoms, Bacillariophyceae, (Nitzschia cf. ovalis, Thalassiosira sp.) five species of green microalgae, Prasinophyceae (Tetraselmis sp.) and Chlorophyceae, (Dictyosphaerium pulchellum, Stichococcus sp., Chlorella sp., Scenedesmus falcatus) and three species of blue green microalgae, Cyanophyceae (Anacystis sp., Synechococcus sp., Synechocystis sp.).Medium for culture diatoms and green microalgae was F/2, and BG-11 media was used for Cyanophyceae. The microalgae were cultured beneath light intensity 143 μEm-2s-1, light: dark illustration 12:12 hrs., temperature 28ºC, and salinities 8-30 psu. The microalgae were harvested for analyzing fatty acid by centrivugal machine at 3500 rpm. for 5 min. at temperature 20ºC and stored at -80ºC prior to analysis.Fatty acids composition of microalgae differed from species to species. The majority fatty acids composition of diatoms at the exponential phase and the stationary phase were C16:1n-7 (17.12-31.47% and 28.22-42.02%), C16:0 (13.25-19.61% and 18.83-20.67%), C20:5 n-3 (16.65-26.67% and 11.32-23.68%) respectively. The principle fatty acids composition of green microalgae, Prasinophyceae, Tetraselmis sp. were C18:3n-3 (16.17-16.67%), C16:0 (15.33-17.45%), C18:1n-9 (12.25-15.43%), C18:2n-6 (9.66-19.97%). The fatty acids composition of green microalgae, Chlorophyceae, were C18:3 n-3 (20.02-26.49% and 15.35- 30.63%), C16:0 (5.76-17.61% and 11.41-20.03%), C18:2n-6 (4.67-17.54% and 7.48-20.61%) respectively. The major amounts of fatty acids content of blue green microalgae were C16:1n-7 (9.28-34.91% and 34.48- 35.04%), C14:0 (13.34-25.96% and 26.69-28.24%), C16:0 (5.89-29.15% and 5.70-16.81%) except for Anacystis sp.which had a high amount of C18:3 n-3 (23.18-27.98%) but low amount of C14:0 (3.66-4.98%).Bacillariophyceae contained the highest amount of highly unsaturated fatty acids (HUFAs) at both growth phases. Prasinophyceae had a small amount while in Chlorophyceae and Cyanophyceae they were not detected. Nitzschia cf. ovalis and Thalassiosira sp. had amount of C20:4n-6 (0.08-4.40%),C20:5 n-3 (11.32- 26.67%) and C22:6 n-3 (0.80-4.20%) respectively. Tetraselmis sp. had amounts of C20:4n-6 and C20:5 n-3 ranging from 0.99-1.13% and 4.18-4.70% respectively. In conclusion, Nitzschia cf. ovalis and Thalassiosira sp. would serve as good nutritional sources of HUFAs for aquaculture animals

THREE SPECIES OF SARGASSUM (PHAEOPHYCEAE) WITH COMPRESSED PRIMARY BRANCHES IN THE GULF OF THAILAND

Three species of Sargassum with compressed primary branches, S. binderi Sonder, S. oligocystum Montagne and S. swartzii (Turner) C.A. Agardh, have been described from the Gulf of Thailand. S. swartzii is the first record of this species from the coast of Thailand. A key for these three species and for each species descriptions have been completed. The clear distinction among these three species is clearly shown and discussed. S. binderi has slender lanceolate leaves, a dentate margin along the compressed stem of its vesicles, and clear spines along the whole margin of the flattened receptacles. S. oligocystum has broader lanceolate leaves with an acute to rounded apex, almost entire, spherical vesicles, and only few spines on the margin of the slightly compressed receptacles. S. swartzii has linear lanceolate leaves, pointed or crowned vesicles, and few spines neat the tip of its almost terete receptacles

Practical mapping methods of seagrass beds by satellite remote sensing and ground truthing

This review introduces practical mapping methods of seagrass beds by satellite remote sensing with ground-truthing surveys. It briefly explains optics for understanding how to map the seagrass beds under the sea. Ground truth data are necessarily used in classifying bottom habitats and evaluating classification accuracies. Ground-truthing surveys are classified into direct methods such as video observation and manta tow with a camera, and indirect methods such as echosounder and sidescan sonar. Seagrass remote sensing begins with relating habitats from ground truth data to pixel values of a satellite image. Since satellite images with high spatial resolution require high precision of positions of ground truth data, ground surveyors need to use GNSSs with sub-meter precision. Image processing procedures are composed of geometric correction, conversion of digital number of an image pixel to radiance or reflectance, atmospheric and water column corrections, image classification, and validation of classification results (accuracy assessment), which are simply explained. It is recommended to use Depth invariant index of Lyzenga (1981) or Bottom Reflectance index of Sagawa et al. (2010) for compensating attenuation of light through atmosphere and water column to obtain better seagrass habitat classification results