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    Please use this identifier to cite or link to this item: http://ir.cnu.edu.tw/handle/310902800/2384


    標題: 河口浮游矽藻之生態指標研究
    Study on the planktonic diatom communities as ecological indicator of estuaries
    作者: 賴雪端
    貢獻者: 生物科技系
    關鍵字: 河口
    浮游矽藻
    優勢種
    生態指標
    Estuary
    planktonic diatom
    ecological indicator
    日期: 2005
    上傳時間: 2008-07-31 14:37:41 (UTC+8)
    出版者: 台南縣:嘉南藥理科技大學生物科技系
    摘要: 本研究利用多變數分析法探討不同污染程度
    之將軍溪、曾文溪及二仁溪等三河口之環境因子及
    浮游性矽藻之生態指標性。為評估影響水質變化之
    主要因子,應用主成份分析及集群分析探討13 個
    環境變數,包括水溫, DO, EC, pH, Salinity, Chl.a,
    NO3-N+NO2, NH4-N, TKN, TN, SiO3, PO4-P 及TP
    等季節變化之最大變異數, 並以non-metric
    multi-dimensional scaling (NMDS)及BioEnv analysis
    探討環境因子與浮游矽藻間的關係。此外亦偵測重
    金屬銅、鎘、鉻、鋅、鉛、鎳,及鐵等之污染物之
    濃度。結果共發現26 種浮游矽藻,分屬於19 屬。
    其它尚有甲藻、綠藻及藍綠藻等非矽藻類浮游藻
    類。主成份分析13 個環境變數顯示:共可萃取出三
    個特徵值大於1 之主成份,佔總變異數之87.8%,
    其中第一成份之特徵值為7.0,變異數為54.3%,
    主要與TKN, PO4-P, TP, TN,及Chl. a 之相關性最
    高,顯示浮游藻類之季節性變化與氮與磷等營養源
    之關係最顯著。
    This study focused on the ecological indicators of
    environmental variables and phytoplankton from three
    various polluted estuaries (JJR, TWR, ERE) in four
    seasons by using multivariate analysis. Principal
    component analysis (PCA) and cluster analysis (CA)
    were applied to data matrix (mean values of water
    column ) of 13 referred variables, including water
    temperature, DO, EC, pH, Salinity, Chl.a,
    NO3-N+NO2, NH4-N, TKN, TN, SiO3, PO4-P and TP,
    in order to assess the seasonality of the respective
    patterns and to highlight areas of similar variables
    influence. BioEnv analysis was also done by the
    non-metric multi-dimensional scaling (NMDS) and
    Spearman rank correlation to realize the relationship
    between environmental factors and phytoplankton. In
    addition, some heavy metals of Cu, Cd, Cr, Zn, Pb, Ni
    and Fe were also detected. A total of 26 diatom taxa
    from 19 genera were identified. The other species
    including dinoflagellates, green alge and blue green
    algae also identified. The results of PCA analysis
    revealed that 3 principal components were reduced
    from 13 environmental variables. These 3 principal
    components could explain 87.8 % of the total variance.
    Principal component 1 appeared as eigenvalue of 7.0
    and explained 54.3% of total variance, which had
    large positive loadings with the nutrients of TKN,
    PO4-P, TP, TN,及Chl. a, The results showed that the
    seasonal variation of planktonic algae had high
    significant with the nutrients of nitrogen and
    phosphorus.
    關聯: 計畫編號:NSC 94-2611-M-041 -001
    Appears in Collections:[生物科技系(所)] 科技部計畫

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