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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 |
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container_title | Plant ecology |
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creator | Olano, J.M Loidi, J.J Gonzalez, A Escudero, A |
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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