Interspecific Associations in Phytosociological Data Sets: How Do They Change between Local and Regional Scale?

Interspecific Associations in Phytosociological Data Sets: How Do They Change between Local and Regional Scale?

Interspecific associations detected in phytosociological data sets sampled in local areas can reflect locally specific combinations of environmental factors and may thus differ from the interspecific associations existing on a regional scale. As a result, vegetation units derived from numerical clas...

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Veröffentlicht in:Plant Ecology. - Springer Science + Business Media. - 173(2004), 2, Seite 247-257
1. Verfasser: Kuželová, Ilona (VerfasserIn)
Weitere Verfasser: Chytrý, Milan
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2004
Zugriff auf das übergeordnete Werk:Plant Ecology
Schlagworte:Ecological scale Numerical methods Phytosociology Plant communities Sociological species groups Vegetation survey Information science Biological sciences Mathematics Religion Physical sciences
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520 |a Interspecific associations detected in phytosociological data sets sampled in local areas can reflect locally specific combinations of environmental factors and may thus differ from the interspecific associations existing on a regional scale. As a result, vegetation units derived from numerical classifications of local data sets can accurately reflect local environmental gradients, but their boundaries or spectra of diagnostic species must be frequently adjusted when transferred to the regional scale. Local vegetation classifications can be useful for some purposes, but regional classifications are superior, as they facilitate communication among the researchers from different areas. We demonstrated changes in interspecific associations between regional and local scale, using a data set of 14 589 relevés of herbaceous vegetation of the Czech Republic, and 16 local subsets of this national data set. We focused on sociological species groups, derived statistically in the national data set. Changes in coherence of these groups when applied to the local data sets were described on the basis of statistical association between the relevés containing some species of these groups and the species belonging vs. not belonging to these groups. The results were summarized using the principal components analysis (PCA). In addition, relevé data sets were compared with respect to presence/absence of sociological species groups, using the principal coordinate analysis (PCoA). The results of PCA and PCoA were compared by Procrustean analysis. Local data sets differed from the national data set to different extent. The national data set was more remote to the local data sets if the analysis focused on the coherence of species group rather than on presence/absence. The species groups from the national data set retained most of their coherence in low-altitude hilly landscapes with thermophilous flora, i.e., the most diverse landscape type of the Czech Republic. On the other hand, many species groups from the national data set could not be recognized in mountainous areas or flat lowlands. These results suggest that interspecific associations existing on regional scale are best reproduced in those local areas which have a high habitat heterogeneity or which have a central position along the major gradients existing on regional scale. 
540 |a Copyright 2004 Kluwer Academic Publishers 
650 4 |a Ecological scale 
650 4 |a Numerical methods 
650 4 |a Phytosociology 
650 4 |a Plant communities 
650 4 |a Sociological species groups 
650 4 |a Vegetation survey 
650 4 |a Information science  |x Data products  |x Datasets 
650 4 |a Biological sciences  |x Biology  |x Botany  |x Plant ecology  |x Vegetation 
650 4 |a Mathematics  |x Mathematical analysis  |x Principal components analysis 
650 4 |a Religion  |x Theology  |x Practical theology  |x Religious practices  |x Ordination 
650 4 |a Physical sciences  |x Earth sciences  |x Geography  |x Geomorphology  |x Topography  |x Lowlands 
650 4 |a Biological sciences  |x Biology  |x Botany  |x Plants 
650 4 |a Biological sciences  |x Ecology  |x Population ecology  |x Synecology 
650 4 |a Biological sciences  |x Biology  |x Biological taxonomies  |x Species 
650 4 |a Information science  |x Information analysis  |x Data analysis  |x Data reduction  |x Cluster analysis 
650 4 |a Physical sciences  |x Earth sciences  |x Geography  |x Land  |x Landscapes 
655 4 |a research-article 
700 1 |a Chytrý, Milan  |e verfasserin  |4 aut 
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773 1 8 |g volume:173  |g year:2004  |g number:2  |g pages:247-257 
856 4 0 |u https://www.jstor.org/stable/20146640  |3 Volltext 
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