Spatial ordination of vegetation data using a generalization of Wartenberg's multivariate spatial correlation
Spatial ordination of vegetation data using a generalization of Wartenberg's multivariate spatial correlation
复制标题
使用 Wartenberg 多元空间相关性的推广对植被数据进行空间排序
DOI:
10.3170/8-18312
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发表时间:
2008
期刊:
影响因子:
--
通讯作者:
F. Débias
中科院分区:
文献类型:
--
作者:
S. Dray;S. Saïd;F. Débias
Abstract Question: Are there spatial structures in the composition of plant communities? Methods: Identification and measurement of spatial structures is a topic of great interest in plant ecology. Univariate measurements of spatial autocorrelation such as Moran's I and Geary's c are widely used, but extensions to the multivariate case (i.e. multi-species) are rare. Here, we propose a multivariate spatial analysis based on Moran's I (MULTISPATI) by introducing a row-sum standardized spatial weight matrix in the statistical triplet notation. This analysis, which is a generalization of Wartenberg's approach to multivariate spatial correlation, would imply a compromise between the relations among many variables (multivariate analysis) and their spatial structure (autocorrelation). MULTISPATI approach is very flexible and can handle various kinds of data (quantitative and/or qualitative data, contingency tables). A study is presented to illustrate the method using a spatial version of Correspondence Analysis. Location: Territoire d'Etude et d'Expérimentation de Trois-Fontaines (eastern France). Results: Ordination of vegetation plots by this spatial analysis is quite robust with reference to rare species and highlights spatial patterns related to soil properties. Nomenclature: Tutin et al. (2001).