Towards unification of national vegetation classifications: A comparison of two methods for analysis of large datasets

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Publikace nespadá pod Pedagogickou fakultu, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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BRUELHEIDE Helge CHYTRÝ Milan

Rok publikování 2000
Druh Článek v odborném periodiku
Časopis / Zdroj Journal of Vegetation Science
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www http://www.sci.muni.cz/botany/chytry/JVS2000.pdf
Obor Ekologie - společenstva
Popis In European phytosociology, national classifications of corresponding vegetation types show considerable differences even between neighbouring countries. Therefore, the European Vegetation Survey project urgently needs numerical classification methods for large datasets that are able to produce compatible classifications using datasets from different countries. We tested the ability of two methods, TWINSPAN and COCKTAIL, to produce similar classifications of wet meadows (Calthion, incl. Filipendulenion) for Germany (7909 relevés) and the Czech Republic (1287 relevés) in this respect. In TWINSPAN, the indicator ordination option was used for classification of two national datasets, and the extracted assignment criteria (indicator species) were applied crosswise from one to the other national dataset. Although the datasets presumably contained similar community types, TWINSPAN revealed almost no correspondence between the groups derived from the proper classification of the national dataset and the groups defined by the assignment criteria taken from the other national dataset. The reason is probably the difference in structure between the national datasets, which is a typical, but hardly avoidable, feature of any pair of phytosociological datasets. As a result, the first axis of correspondence analysis, and consequently the first TWINSPAN division, are associated with different environmental gradients; the difference in the first division is transferred and multiplied further down the hierarchy. COCKTAIL is a method which produces relevé groups on the basis of statistically formed species groups. The user determines the starting points for the formation of species groups, and groups already found in one dataset can be tested for existence in the other dataset. The correspondence between the national classifications produced by COCKTAIL was fairly good. For some relevé groups, the lack of correspondence to groups in the other national dataset could be explained by absence of the corresponding vegetation types in one of the countries, rather than by methodological problems.
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