当前位置: 首页 > 文章 > 柘林湾附近海域大型底栖动物物种多样性 中国水产科学 2015,22 (3) 501-516
Position: Home > Articles > Macrobenthic species diversity in the waters surrounding Zhelin Bay Journal of Fishery Sciences of China 2015,22 (3) 501-516

柘林湾附近海域大型底栖动物物种多样性

作  者:
舒黎明;陈丕茂;黎小国;秦传新;于杰;周艳波;袁华荣
单  位:
农业部南海渔业资源环境科学观测实验站;中国水产科学研究院海洋牧场技术重点实验室;中国水产科学研究院南海水产研究所
关键词:
物种多样性;大型底栖动物;聚类分析;方差分析;柘林湾
摘  要:
依据柘林湾附近海域2013年2月、5月、8月和12月的大型底栖动物的定量采样数据,对该海域的大型底栖动物物种多样性进行研究。结果表明,全年共出现大型底栖动物89种,全年平均Margalef丰富度指数为1.73,Shannon-Wiener多样性指数为1.84,Pielou均匀度指数为0.88;单因素方差分析表明,4个季度的丰富度指数、多样性指数和均匀度指数均不存在显著性差异;丰度的k-优势度曲线表明,4个季度的多样性水平为冬>春≈秋>夏。R型聚类结果表明,丰富度指数、多样性指数和均匀度指数可以归为一类群;曲线拟合表明多样性指数与丰富度指数之间、多样性指数与种类数之间、丰富度指数与种类数之间的相关性相对较高。Q型聚类结果表明,大致可将28个站位分成3类群或者5类群。
译  名:
Macrobenthic species diversity in the waters surrounding Zhelin Bay
作  者:
SHU Liming;CHEN Pimao;LI Xiaoguo;QIN Chuanxin;YU Jie;ZHOU Yanbo;YUAN Huarong;South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences; Scientific Observing and Experimental Station of South China Sea Fishery Resources and Environment, Ministry of Agriculture of China; Key Laboratory of Marine Ranching Technology, Chinese Academy of Fishery Sciences;
关键词:
species diversity;;macrobenthos;;cluster analysis;;analysis of variance;;Zhelin Bay
摘  要:
Macrobenthic species diversity in the waters surrounding Zhelin Bay was studied based on the quantitative data of macrobenthos sampled in February, May, August, and December 2013. The results show that 89 macrobenthic species were sampled in 2013. Mean Margalef richness index, Shannon-Wiener index, and Pielou evenness index values were 1.73, 1.84, and 0.88, respectively. One-way analysis of variance showed that the richness, diversity, and evenness indices were not significantly different among seasons. The k-dominance curve of abundance showed that the seasonal trend in species diversity was winter > spring ? autumn > summer. An R-type cluster analysis showed that the richness, diversity, and evenness indices could be classified as a cluster. The correlations between the diversity index and richness index, the diversity index and species number, and the richness index and species number were relatively high. A Q-type cluster analysis showed that the 28 sampling stations could be classified into three or five clusters.

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