Variants of polar ordination

H.G. Gauch; W.M. Scruggs

doi:10.1007/bf00228478

A comparative study of five cerrado areas in southern Mato Grosso, Brazil

Edinburgh Journal of Botany ◽

10.1017/s0960428600003036 ◽

1991 ◽

Vol 48 (3) ◽

pp. 307-332 ◽

Cited By ~ 15

Author(s):

A. T. Oliveira-Filho ◽

F. R. Martins

Keyword(s):

Community Structure ◽

Comparative Study ◽

Hierarchical Classification ◽

Floristic Composition ◽

Mato Grosso ◽

Savanna Woodland ◽

Classification Techniques ◽

Polar Ordination ◽

Cerrado Savanna

Quantitative descriptions of the woody flora and soil analyses are given for five areas of cerrado (savanna woodland) near Cuiabá, Mato Grosso state, Brazil. Comparisons are made of the floristic composition and community structure of these areas using polar ordination and hierarchical classification techniques.Descrições quantitativas da flora lenhosa e anâlises de solos são apresentadas para cinco áreas de cerrado nas proximidades de Cuiabá, Mato Grosso. São realizadas comparações entre estas areas em composição florística e estrutura comunitária utilizando técnicas de ordenação polar e classifiçãcao hierárquica.

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Reciprocal Averaging and Polar Ordination as Techniques for Analyzing Lotic Macroinvertebrate Communities

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f80-174 ◽

1980 ◽

Vol 37 (9) ◽

pp. 1358-1364 ◽

Cited By ~ 11

Author(s):

Joseph M. Culp ◽

Ronald W. Davies

Keyword(s):

Cluster Analysis ◽

Field Data ◽

Environmental Gradient ◽

Environmental Data ◽

Macroinvertebrate Communities ◽

Reciprocal Averaging ◽

Spatial And Temporal Patterns ◽

Polar Ordination ◽

Ordination Techniques ◽

Group Relationships

Reciprocal averaging and polar ordination techniques were applied to lotic macroinvertebrate field data to determine the relative performance of these techniques in lotic benthic community analyses. It was found that, because of inherent problems with endpoint determinations, polar ordination should only be used where a well-defined environmental gradient exists. Reciprocal averaging ordination produced interpretable axes and was preferred over polar ordination because endpoint determination was objective and simultaneous species–site ordinations were produced. Reciprocal averaging ordination allowed groupings of sites similar to those determined through cluster analysis to be recognized, while providing a visual representation of between-group relationships superior to that of cluster dendrograms. Combined with subsequent analyses of environmental data, reciprocal averaging ordination can be an excellent technique for summarizing spatial and temporal patterns of lotic macroinvertebrate communities.Key words: ordination, reciprocal averaging, benthic, lotic, communities, clustering

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A classification-ordination analysis of a Belgian mixed forest in the transition zone of two phytogeographical districts. II. Spring data

Silva Gandavensis ◽

10.21825/sg.v45i0.974 ◽

1979 ◽

Vol 45 ◽

Author(s):

P. Van Hecke ◽

I. Impens ◽

T. Van Tilborgh

Keyword(s):

Mixed Forest ◽

Minimum Variance ◽

Species Classification ◽

Pair Group ◽

Polar Ordination ◽

Paper Cover ◽

Moss Layer ◽

Percentage Extraction ◽

Group Centroid ◽

Height Data

From 115 quadrats, laid out in the same way and on the same coordinates as described in a first paper, cover-abundance and height data were collected in april 1976 on 58 taxa, belonging to the upper and lower herb layer, on the moss layer as a whole and on the litter. They were submitted to four classification methods, namely Unweighted pair-group centroid technique (UPGC), normal Association analysis (NAA) , agglomerative normal and inverse Information analysis (NIA and IIA), Minimum variance clustering (MVC), and to four ordination methods, namely Beals' Polar ordination (POS), Simple ordination (SO), Optimized polar ordination (OPO) and Position vectors ordination (PVO). The only divisive method (NAA) produces more than sufficient results: they are slightly better with the 1%-stopping rule especially when no species reduction is involved. NAA and NIA give quite similar results. From the three agglomerative techniques, the greatest number of vegetation- clusters (7), recognizable in the field, has been obtained with MVC, the poorest picture however by UPGC. With regard to the forest-structure, the better results are with NIA, followed by MVC. Moreover. NIA applied in a quantitative way, is less appropriate. The outcome of species classification is not interpretable. The ordination results obtained by OPO and PVO are better as compared to those from POB and SO, as well in discovering gradients as clusters, the gradients particularly reflect changes in cover-abundance and height. In the ordination of vegetation quadrats, the total of the efficiency ratios extracted for the first three axes in PVO and GPO are respectively four and three times higher than with SO. Concerning the structure quadrats, the percentage extraction values are very high and very alike. Comparing the spring with the summer forest, UPGC distinguishes more identifiable vegetation types in the summer data, NAA on the contrary in the spring data.

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