稀有种不同处理对典范对应分析排序结果影响的比较

doi:10.17521/cjpe.2015.0016

摘要/Abstract

摘要：

运用吕梁山南段植物群落及其环境调查数据, 比较研究不同稀有种处理(剔除稀有种、稀有种不做处理与降低稀有种权重3种方法处理)对典范对应分析(CCA)排序结果的影响, 并用Spearman秩相关系数检验对应排序轴的相关性。结果表明3种方法的分析效果基本一致, 但它们对环境因子的解释趋势有差异。基于环境数据、物种数据和样方数据的排序轴相关分析结果显示: 未处理稀有种的CCA与降低稀有种权重的CCA吻合度高于剔除稀有种的CCA与降低稀有种权重的CCA的吻合度, 未处理稀有种的CCA与降低稀有种权重的CCA的前4轴呈极显著的一一对应关系; 剔除稀有种的CCA和降低稀有种权重的CCA仅在基于环境数据和样方数据分析时前3轴呈极显著的一一对应关系, 而在基于物种数据的相关分析时前4轴的对应相关性不显著。从物种-环境关系的解释量上来看, 降低稀有种权重的CCA最优, 剔除稀有种的CCA和未处理稀有种的CCA次之。结合对应排序轴的相关性分析和物种-环境关系累计解释量来看, 这3种稀有种处理方法在准确地揭示物种与环境关系时的顺序依次为: 降低稀有种权重>对稀有种不做处理>剔除稀有种。

关键词: 稀有种, 典范对应分析(CCA), 植物群落排序, 吕梁山南段

Abstract: Aims

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.

Methods

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.

Important findings

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.

Key words: rare species, canonical correspondence analysis (CCA), plant community ordination, southern Lüliang Mountain

曹静, 苗艳明, 冯飞, 许强, 张钦弟, 毕润成. 稀有种不同处理对典范对应分析排序结果影响的比较. 植物生态学报, 2015, 39(2): 167-175. DOI: 10.17521/cjpe.2015.0016

CAO Jing,MIAO Yan-Ming,FENG Fei,XU Qiang,ZHANG Qin-Di,BI Run-Cheng. Comparison of different treatments of rare species in canonical correspondence analysis. Chinese Journal of Plant Ecology, 2015, 39(2): 167-175. DOI: 10.17521/cjpe.2015.0016

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2015.0016

https://www.plant-ecology.com/CN/Y2015/V39/I2/167

图/表 7

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		排序轴 Ordination axis
		1	2	3	4
物种-环境关系方差解释的累计百分比 Cumulative percentage variance of species-environment relation (%)	未对稀有种处理的CCA Untreated rare species CCA	33.0	55.6	74.1	87.4
	降低稀有种权重的CCA Downweighting of rare species CCA	39.2	60.0	76.9	89.4
	剔除稀有种的CCA Eliminating rare species CCA	34.2	56.6	75.4	88.5

		排序轴 Ordination axis
		1	2	3	4
物种-环境关系方差解释的累计百分比 Cumulative percentage variance of species-environment relation (%)	未对稀有种处理的CCA Untreated rare species CCA	33.0	55.6	74.1	87.4
	降低稀有种权重的CCA Downweighting of rare species CCA	39.2	60.0	76.9	89.4
	剔除稀有种的CCA Eliminating rare species CCA	34.2	56.6	75.4	88.5

	未对稀有种处理的CCA Untreated rare species CCA				降低稀有种权重的CCA Downweighting of rare species CCA				剔除稀有种的CCA Eliminating rare species CCA
	排序轴 Ordination axis				排序轴 Ordination axis				排序轴 Ordination axis
	1	2	3	4	1	2	3	4	1	2	3	4
海拔 Elevation	0.912^*	0.155	-0.004	0.165	-0.854^*	0.199	-0.042	0.200	-0.882^*	0.237	-0.024	0.044
坡度 Slope	0.518	-0.111	0.385	-0.362	-0.540	-0.081	0.388	-0.252	-0.514	-0.078	0.418	0.133
坡向 Aspect	0.415	-0.005	-0.640^*	-0.195	-0.458	-0.021	-0.615^*	-0.260	-0.403	-0.026	-0.586^*	0.237
水分条件 Moisture condition	-0.494	0.761^*	0.065	-0.040	0.558	0.662^*	0.018	-0.018	0.549	0.702^*	0.038	0.027
人为干扰强度 Density of human disturbance	-0.428	-0.358	0.115	-0.601^*	0.352	-0.270	0.325	-0.588^*	0.386	-0.411	0.107	-0.608^*

	未对稀有种处理的CCA Untreated rare species CCA				降低稀有种权重的CCA Downweighting of rare species CCA				剔除稀有种的CCA Eliminating rare species CCA
	排序轴 Ordination axis				排序轴 Ordination axis				排序轴 Ordination axis
	1	2	3	4	1	2	3	4	1	2	3	4
海拔 Elevation	0.912^*	0.155	-0.004	0.165	-0.854^*	0.199	-0.042	0.200	-0.882^*	0.237	-0.024	0.044
坡度 Slope	0.518	-0.111	0.385	-0.362	-0.540	-0.081	0.388	-0.252	-0.514	-0.078	0.418	0.133
坡向 Aspect	0.415	-0.005	-0.640^*	-0.195	-0.458	-0.021	-0.615^*	-0.260	-0.403	-0.026	-0.586^*	0.237
水分条件 Moisture condition	-0.494	0.761^*	0.065	-0.040	0.558	0.662^*	0.018	-0.018	0.549	0.702^*	0.038	0.027
人为干扰强度 Density of human disturbance	-0.428	-0.358	0.115	-0.601^*	0.352	-0.270	0.325	-0.588^*	0.386	-0.411	0.107	-0.608^*

未对稀有种处理的CCA Ordination axis of untreated rare species CCA	降低稀有种权重的CCA Ordination axis of downweighting of rare species CCA				剔除稀有种的CCA Ordination axis of eliminating rare species CCA	降低稀有种权重的CCA Ordination axis of downweighting of rare species CCA
未对稀有种处理的CCA Ordination axis of untreated rare species CCA	1	2	3	4	剔除稀有种的CCA Ordination axis of eliminating rare species CCA	1	2	3	4
1	-1.000^**	-0.1	-0.1	0.4	1	1.000^**	0.1	0.1	-0.4
2	0.1	1.000^**	-0.5	0.8	2	0.1	1.000^**	-0.5	0.8
3	0.1	-0.5	1.000^**	-0.2	3	0.1	-0.5	1.000^**	-0.2
4	-0.3	0.900^*	-0.6	0.900^*	4	-0.5	0.1	-0.4	0.1