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Hiroyuki Mizuta The Korean Society of Phycology 2002 ALGAE Vol.17 No.2
Seasonal changes of pigment compositionin two intertidal red algae, Gloiopeltis furcata (Postels et Ruprecht) J. Agardh, and Porphyra yezoensis Ueda, were investigated. Chlorophyll α and phycoerythrin levels were high during winter, but decreased in late spring or summer, with accompanying discoloration from deep red to green or yellow. This discoloation corresponded closely to the fluctuationof phycoerythrin content. Nevertheless, photosynthesis capacity was maintained by the increasing water temperature in the field, suggesting that large amounts of phycoerythrin are not necessary for photosynthesis. Phycoerythrin conten correlated significantly with nitrogen content in both species when the nitrogen level was greater than the level of critical content (1.30% DW in G. furcata, and 2.26% DW in P. yezoensis), indicating that phycoerythrin plays a more important role in the nitrogen status as a nitrogen pool than that of nitrogen critical content. Furthermore, the dependence level of the alage on phycoerythrin as a nitrogen pool was greater in P. yezoensis than in G. furcata because of the remarkable increase of phycoerythrin content in P. yezoensis with increasing jnitrogen content.
Exploratory Methods for Joint Distribution Valued Data and Their Application
Igarashi, Kazuto,Minami, Hiroyuki,Mizuta, Masahiro The Korean Statistical Society 2015 Communications for statistical applications and me Vol.22 No.3
In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.