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### 稀有种不同处理对典范对应分析排序结果影响的比较

1. 山西师范大学生命科学学院, 山西临汾 041004
• 收稿日期:2014-07-18 接受日期:2014-11-02 出版日期:2015-02-01 发布日期:2015-03-10
• 通讯作者: 张钦弟,毕润成
• 作者简介:

# 共同第一作者

• 基金资助:
山西省化学优势重点学科建设生态化学子项目(912019)、山西省青年科技研究基金(2013- 021030-3)、山西师范大学校科学研究基金(ZR1218)和山西师范大学生命科学学院科学研究基金(SMYKZ-19)

### Comparison of different treatments of rare species in canonical correspondence analysis

CAO Jing, MIAO Yan-Ming, FENG Fei, XU Qiang, ZHANG Qin-Di*(), BI Run-Cheng*()

1. College of Life Science, Shanxi Normal University, Linfen, Shanxi 041004, China
• Received:2014-07-18 Accepted:2014-11-02 Online:2015-02-01 Published:2015-03-10
• Contact: Qin-Di ZHANG,Run-Cheng BI
• About author:

# Co-first authors

Abstract: <i>Aims</i>

Rare species can indicate certain ecological significance. Studies of rare species on plant community structure and composition were still insufficient. Our objective was to compare the results of three different treatments, eliminating, downweighting and untreated rare species in canonical correspondence analysis (CCA), and to verify the influences of rare species.

<i>Methods</i>

For assessing the impact of different treatments CCA, different data of plant communities and environment from southern Lüliang Mountain, eliminating rare species, downweighting rare species, and untreated data sets, were used in the CCA analyses, respectively. Spearman rank correlation coefficient was taken to test the correlation of corresponding ordination axis.

<i>Important findings</i>

The performances of three methods were basically the same when the number of environmental factors was less. But some differences were existed on the explanation tendency for each environmental factor. Base on the correlation analyses, the consistency of untreated CCA and downweighting rare species CCA was better than that of eliminating rare species CCA and downweighting rare species CCA. If the correlation analysis was based on quadrat coordinates of environmental data only, the correlation between eliminating rare species CCA and downweighting of rare species CCA was a little higher. For the first four axes, untreated CCA and the downweighting rare species CCA were correlated significantly and correspondingly. If the analysis were based on environmental and species data, eliminating rare species CCA and the downweighting rare species CCA were significantly correlated for the three first corresponding axes. However, the correlation based on species data only showed insignificant for the first four corresponding axes. Considering the interpretation quantity of species-environment variance, the downweighting rare species is the best method in the three treatments. Three methods are arranged in the order for accurately reveal species and environment relations as follows: downweighting rare species CCA, untreated CCA and eliminating rare species CCA.