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引用本文:张文静,董志军,孙西艳,张晨,刘永亮,侯朝伟,赵建民.2018年烟台四十里湾及其邻近海域网采浮游植物群落结构的时空变化.海洋与湖沼,2020,51(5):1151-1161.
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2018年烟台四十里湾及其邻近海域网采浮游植物群落结构的时空变化
张文静1,2, 董志军1,2, 孙西艳1,2, 张晨1,2, 刘永亮1,2, 侯朝伟1,2, 赵建民1,2
1.中国科学院烟台海岸带研究所 牟平海岸带环境综合试验站 烟台 264003;2.中国科学院海洋大科学研究中心 青岛 266071
摘要:
本文基于2018年5月(春季)、8月(夏季)、11月(秋季)和2019年1月(冬季)季度航次调查,采用冗余分析(RDA)和Bray-Curtis相似性聚类分析方法,讨论了烟台四十里湾及其邻近海域网采浮游植物丰度、优势种组成、多样性指数、均匀度指数的分布特征以及浮游植物与环境因子的关系。本年度调查共发现浮游植物4门69属116种,其中硅藻门50属85种,甲藻门15属27种,着色鞭毛藻门3属3种,未定类1种(三深碎裂藻,Ebria tripartita)。浮游植物丰度在8月份达到年度最高值,为2.89×108cells/m3,秋季次之,春季最低,春、秋、冬季浮游植物丰度均为~105cells/m3。硅藻门在4个季节中均占绝对优势,除春季出现甲藻门(夜光藻)优势种外,其余季节浮游植物优势种均为硅藻门。相邻季节浮游植物优势种更替明显,未出现4个季节共有的优势种。浮游植物多样性和均匀度指数均在夏季达到最低值,分别为1.58和0.31。RDA排序分析显示,不同季节影响浮游植物群落分布的环境因子不同,总体来讲,温度、溶解氧浓度、SiO32-浓度和NO3-浓度对浮游植物的丰度和平面分布有显著影响。Bray-Curtis相似性聚类结果显示,2018年每个季节浮游植物群落分布均可分为两个类群,其分布受营养盐分布的影响较为明显。
关键词:  四十里湾及其邻近海域  浮游植物群落结构  时空变化  环境因子
DOI:10.11693/hyhz20191200252
分类号:Q948.8
基金项目:中国科学院“美丽中国”先导专项资助项目,XDA23050303号,XDA23050301号
SPATIAL AND TEMPORAL DISTRIBUTION OF NET-SAMPLED PHYTOPLANKTON COMMUNITY IN SISHILI BAY AND ITS ADJACENT WATER, YANTAI IN 2018
ZHANG Wen-Jing1,2, DONG Zhi-Jun1,2, SUN Xi-Yan1,2, ZHANG Chen1,2, LIU Yong-Liang1,2, HOU Chao-Wei1,2, ZHAO Jian-Min1,2
1.Muping Coastal Environmental Research Station, Yantai Institute of Coastal Zone Reseach, Chinese Academy of Sciences, Yantai 264003, China;2.Center for ocean mega-science, Chinese Academy of Sciences, Qingdao 266071, China
Abstract:
Four quarterly investigations were conducted in Sishili Bay (Yantai, Shandong Province) and its adjacent water during April, August and November 2018 and January 2019, from which synchronized hydrological data were acquired. Using Redundancy analysis (RDA) and Bray-Curtis similarity cluster analysis, the distribution of net-sampled phytoplankton abundance, dominant species, Shannon diversity index (H'), evenness index (J) were calculated, and the relationship between phytoplankton community and environmental factors were analyzed. Four classes including 69 genera and 113 species were identified, including 85 species in 50 genera of Bacillariophyta, 27 species in 15 genera of Pyrrophyta, 3 species in 3 genera of Chromophyta, and 1 indefinite taxonomic status species Ebria tripartite. The abundance reached a peak in summer, and order was summer (2.89×108cells/m3) > autumn (8.92×105cells/m3) > winter (6.52×105cells/m3) > spring (1.50×105cells/m3). Diatom was dominated in the whole phytoplankton abundance in all four seasons. All of the dominant species in 2018 were Bacillariophyta except for a Pyrrophyta species Noctiluca scintillans appeared in spring. There were no dominant species shared by the four seasons. H' and J were the lowest in summer, which was 1.58 and 0.31, respectively. Redundancy analysis (RDA) indicated that the environmental factors that influenced the spatial and temporal distribution of phytoplankton varied in season. In spring, the temperature [correlated-weight (CW)=0.62, P<0.05] and the concentrations of SiO32- (CW=0.54, P<0.05) and NO3-(CW=-0.44, P=0.05) were shown significantly related to phytoplankton community and distribution; in summer, salinity (CW=-0.88, P<0.05) showed negative relationship with phytoplankton; in autumn, SiO32- concentration (CW=-0.77, P<0.05) turned to be correlated with phytoplankton; and in winter, nutrients levels were high enough to support phytoplankton growth, and temperature (CW=-0.75, P<0.05) and dissolved oxygen (CW=0.86, P<0.05) were the main factors that influenced phytoplankton community distribution. Bray-Curtis similarity cluster analysis showed that phytoplankton community could be divided into two groups in all four seasons due to the effects of nutrients that one group was near Yantai Port and the other group in midwest of the investigated region in spring; centralized distribution group C and scattered group D in summer; in autumn group E and F distributed in the east and midwest of Yangma Island respectively; and in winter nearshore and offshore groups respectively.
Key words:  Sishili Bay and its adjacent water  phytoplankton community  spatial and temporal distribution  environmental factors
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