引用本文:
【打印本页】   【下载PDF全文】   View/Add Comment  Download reader   Close
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 2445次   下载 2584 本文二维码信息
码上扫一扫!
分享到: 微信 更多
象山港海洋牧场示范区浮游植物的群落特征及其与环境因子的关系
刘懂1, 陈晨1, 王莉1, 焦海峰1,2, 孙元2, 王一农1, 尤仲杰1,2
1.宁波大学海洋学院 宁波 315211;2.宁波市海洋与渔业研究院 宁波 315012
摘要:
根据2014年4月至2015年1月于象山港海洋牧场示范区和对照区四季的浮游植物及同步的环境调查数据,对浮游植物的群落特征进行研究,并应用冗余分析(RDA)研究了该海域环境因子对浮游植物群落结构的影响。共鉴定出浮游植物95种,隶属于7门59属,主要由硅藻(64种)、绿藻(10种)和甲藻(9种)组成。优势种主要有琼氏圆筛藻(Coscinodiscus jonesianus)、太阳漂流藻(Planktoniella sol)和星脐圆筛藻(C.asteromphalus),且存在明显的季节演替现象。双因素分析结果表明:季节间,浮游植物丰度、多样性指数(Shannon-Wiener多样性、Pielou均匀度和Margalef丰富度)和环境因子(水温、盐度、pH、DO、NO3-N、NO2-N、NH4-N、PO4-P和SiO3-Si)均存在极显著差异(P<0.01),秋、春季全区丰度(121.59和79.39×104个/m3)显著高于冬、夏季(13.05和7.05×104个/m3),多样性指数均表现为冬 > 夏 > 秋 > 春季;区域间,丰度、多样性指数和环境因子均无显著性差异(P>0.05),示范区浮游植物丰度和多样性指数的四季均值都高于对照区。相似性聚类分析、多维尺度分析(nMDS)结果表明,浮游植物群落组成季节性差异显著,区域差异不显著。表明示范区的建设对浮游植物的生长有一定的积极作用,但效果不显著。RDA分析结果表明,盐度、温度、营养盐(NO3-N、PO4-P和SiO3-Si)和DO是影响浮游植物群落结构的主要因子,各种浮游植物对环境因子的响应机制有所不同。
关键词:  象山港  海洋牧场  浮游植物  环境因子  冗余分析
DOI:10.11693/hyhz20160500096
分类号:
基金项目:公益性行业(农业)科研专项,201303047号;国家自然科学基金项目,31671097号;国家海洋局海域使用金专项(2012)。
COMMUNITY STRUCTURE OF PHYTOPLANKTON AND THE RELATIONSHIP WITH ENVIRONMENTAL VARIABLES IN MARINE PASTURE DEMONSTRATION AREA IN XIANGSHAN BAY
LIU Dong1, CHEN Chen1, WANG Li1, JIAO Hai-Feng1,2, SUN Yuan2, WANG Yi-Nong1, YOU Zhong-Jie1,2
1.School of Marine Science, Ningbo University, Ningbo 315211, China;2.Ningbo Academy of Oceanology and Fisheries, Ningbo 315211, China
Abstract:
Based on the phytoplankton and environment data collected from seasonal surveys in the marine pasture demonstration area and the control area of Xiangshan Bay, East China Sea between April 2014 and January 2015, the community structure of phytoplankton was studied and the relationships with environmental variables were evaluated by redundancy analysis. A total of 95 phytoplankton species belonging to 7 phyla and 59 genera were collected, including mainly Bacillariophyta (64 species), Chlorophyta (10 species), and Dinophyta (9 species). Coscinodiscus jonesianus, Planktoniella sol, and C. asteromphalus were the main dominant species. There were obvious seasonal variations in species composition of dominant species. Results of two-way ANOVA show that the phytoplankton abundances, the biodiversity indices (Shannon-Wiener diversity, Pielou evenness, and Margalef richness index) and the environmental variables (temperature, salinity, pH, DO, NO3-N, NO2-N, NH4-N, PO4-P and SiO3-Si) were significantly different in season (P<0.01). The phytoplankton abundances in autumn and spring (121.59 and 79.39×104 cells/m3) were significantly higher than those in winter and summer (13.05 and 7.05×104 cells/m3), and all the biodiversity indices were ranked as winter > summer > autumn > spring. The phytoplankton abundances, biodiversity indices, and environmental variables showed no obvious differences between the two areas (P<0.05). The average annual abundance and all the biodiversity indices were ranked as demonstration area > control area, which agreed with the temporal and spatial distributions of phytoplankton community indicated by clustering and non-metric multidimensional scaling. Therefore, the construction of the marine pasture demonstration area was conducive to the growth of phytoplankton, but the resultant effect was mild. Redundancy analysis suggested that the main variables affecting the community structure were salinity, followed by temperature, nutrition (NO3-N, PO4-P and SiO3-Si), and DO. Different species of phytoplankton respond to these main variables in different ways.
Key words:  Xiangshan Bay  marine pasture  phytoplankton  environmental variables  redundancy analysis
Copyright ©  Editorial Office for Oceanologia et Limnologia Sinica    Copyright©2008 All Rights Reserved
Supervised by: China Association for Science and Technology   Sponsored by: Chinese Society for Oceanology and Limnology, Institute of Oceanology and Limnology, CAS.
Address: 7 Nanhai Road, Qingdao, China.    Postcode: 266071    Tel: 0532-82898753  E-mail: liuxiujuan@qdio.ac.cn  
Technical support: Beijing E-Tiller Co.,Ltd.