Two-Step Vegetation Analysis Based on Very Large Data Sets

A two-step method for the classification of very large phytosociological data sets is demonstrated. Stratification of the set is suggested either by area in the case of a large and geographically heterogeneous region, or by vegetation type in the case of a set covering all the plant communities of a...

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Bibliographic Details
Published in:Vegetatio 1987-01, Vol.68 (3), p.139-143
Main Authors: Van der Maarel, Eddy, Espejel, Ileana, Moreno-Casasola, Patricia
Format: Article
Language:English
Subjects:
Animal and plant ecology
Animal, plant and microbial ecology
Arithmetic mean
Biological and medical sciences
Coastal ecology
Datasets
Dunes
Fundamental and applied biological sciences. Psychology
General aspects
Information classification
Ordination
Plant communities
Species
Synecology
Vegetation
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Summary:A two-step method for the classification of very large phytosociological data sets is demonstrated. Stratification of the set is suggested either by area in the case of a large and geographically heterogeneous region, or by vegetation type in the case of a set covering all the plant communities of an area. First, cluster analysis is performed on each subset. The resulting basic clusters are summarized by calculating a 'synoptic cover-abundance value' for each species in each cluster. All basic clusters are then subjected to the same procedure. Second order clusters are interpreted as community types. The synoptic value proposed reflects both frequency and average cover-abundance. It is emphasized that a species should have a high frequency to be used as a diagnostic species. The method is demonstrated with a set of 1138 relevés and 250 species of coastal sand dune vegetation in Yucatan treated with the programs TWINSPAN and TABORD. Some problems and perspectives of the approach are discussed in the light of hierarchy theory and classification theory.
ISSN:0042-3106
1573-5052
DOI:10.1007/BF00114714