CAJ | 학술논문

为研究崂山湾人工鱼礁区浮游植物群落结构与环境因子的关系，于2011年3、6、9、12月对崂山湾3个人工鱼礁区(峰山区、仰口区、港东区)进行取样调查。4次采样共鉴定浮游植物69种，其中3、9、12月优势种都为甲藻门中的中肋骨条藻(Skeletonema costatum)，并且9月鱼礁区浮游植物密度远大于其他月份浮游植物密度。应用Canoco for Windows 4.5软件对获得的浮游植物数据和环境因子数据进行典范对应分析(Canonical correspondence analysis)，作出物种与环境因子关系的二维排序图。结果表明，影响礁区浮游植物分布的主要环境因子依次为磷酸盐、温度、硅酸盐。
위연구로산만인공어초구부유식물군락결구여배경인자적관계，우2011년3、6、9、12월대로산만3개인공어초구(봉산구、앙구구、항동구)진행취양조사。4차채양공감정부유식물69충，기중3、9、12월우세충도위갑조문중적중륵골조조(Skeletonema costatum)，병차9월어초구부유식물밀도원대우기타월빈부유식물밀도。응용Canoco for Windows 4.5연건대획득적부유식물수거화배경인자수거진행전범대응분석(Canonical correspondence analysis)，작출물충여배경인자관계적이유배서도。결과표명，영향초구부유식물분포적주요배경인자의차위린산염、온도、규산염。
In this study, we examined the phytoplankton community in the artificial reef areas of Laoshan Bay, and analyzed the relationships between phytoplankton and environment factors. Hence we provided references for the construction and evaluation of artificial reefs. The data and water samples were collected from four surveys in three artificial reef areas (Fengshan, Yangkou and Gangdong) of Laoshan Bay from March to December in 2011. By using Primer 5.0, we calculated the Shannon-Wiener, Margalef andPielou of the phytoplankton community. We monitored the quarterly changes of phytop-lankton community with cluster analysis, and applied Canonical Correspondence Analysis (CCA) to explore the relationship between phytoplankton species and the environmental factors using Canoco 4.5. In four surveys we identified a total of 69 species with microscope. We found that the dominant species wasSkeletonema costatum in March, September and December, and it wasNavicula spp in June.The density of phytoplankton in December was 49.78×105cell/m3, which was the lowest in this survey. The density of phytoplankton in September was up to 408.65×105 cell/m3, which was the highest among all months. Shannon-WienerandMargalef varied from 2.034 to 2.83, and from 5.27 to 7.25 respectively, both of which reached the maximum in September and the minimum in December. The range of Pielou was 0.58-0.78, and it reached the maximum in June and the minimum in December. According to the cluster analysis, the degree of similarity between March and June was 43.02%, and it was up to 42.38% between September and December. The species-environment bi-plots were drawn based on the results of CCA. The results showed that phosphate, temperature and silicate were the most important factors that influenced the distribution of phytoplankton species.