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Improving the interpretation of fuzzy partitions in vegetation science with constrained ordinations

Classification and ordination techniques based in fuzzy set theory are now being commonly used in vegetation studies. However, several problems have been detected in spite of the significant theoretical advantages of the theory. In this paper we have improved the interpretability of fuzzy partitions...

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Published in:Plant ecology 1998, Vol.134 (1), p.113-118
Main Authors: Olano, J.M, Loidi, J.J, Gonzalez, A, Escudero, A
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Language:English
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creator Olano, J.M
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description Classification and ordination techniques based in fuzzy set theory are now being commonly used in vegetation studies. However, several problems have been detected in spite of the significant theoretical advantages of the theory. In this paper we have improved the interpretability of fuzzy partitions by combining fuzzy partitions with correspondence analysis (CA) and detrended canonical correspondence analysis (DCCA) in an analysis of the beech forests of Basque Country, northern Spain. Our results seem to overcome difficulties in the interpretation of multi-group partitions.
doi_str_mv 10.1023/A:1009767714612
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source JSTOR-E-Journals; Springer Nature
subjects Correspondence theory
Fagus
Forest ecology
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Landscape ecology
mathematical models
Ordination
Ordinations
Plant ecology
spatial distribution
species diversity
statistical analysis
Synecology
Talus slopes
Vegetation
title Improving the interpretation of fuzzy partitions in vegetation science with constrained ordinations
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