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@article{914406,
author = {Tichý, Lubomír and Chytrý, Milan and Hájek, Michal and Talbot, Stephen S. and BottaandDukát, Zoltán},
article_location = {Oxford},
article_number = {2},
keywords = {Cluster analysis; Cover transformation; Dendrogram; Optimal number of clusters; Ordinal clustering; Resemblance measures; Stopping rules; TWINSPAN},
language = {eng},
issn = {1100-9233},
journal = {Journal of Vegetation Science},
title = {OptimClass: Using species-to-cluster fidelity to determine the optimal partition in classification of ecological communities},
url = {http://www3.interscience.wiley.com/journal/123193144/abstract},
volume = {21},
year = {2010}
}
TY - JOUR
ID - 914406
AU - Tichý, Lubomír - Chytrý, Milan - Hájek, Michal - Talbot, Stephen S. - Botta-Dukát, Zoltán
PY - 2010
TI - OptimClass: Using species-to-cluster fidelity to determine the optimal partition in classification of ecological communities
JF - Journal of Vegetation Science
VL - 21
IS - 2
SP - 287-299
EP - 287-299
PB - Wiley-Blackwell
SN - 11009233
KW - Cluster analysis
KW - Cover transformation
KW - Dendrogram
KW - Optimal number of clusters
KW - Ordinal clustering
KW - Resemblance measures
KW - Stopping rules
KW - TWINSPAN
UR - http://www3.interscience.wiley.com/journal/123193144/abstract
N2 - Question: Community ecologists are often confronted with multiple possible partitions of a single set of records of species composition and/or abundances from several sites. Different methods of numerical classification produce different results, and the question is which of them, and how many clusters, should be selected for interpretation. We demonstrate a new method for identifying the optimal partition from a series of partitions of the same set of sites, based on number of species with high fidelity to clusters in a partition (faithful species). Methods: The new method, OptimClass, has two variants. OptimClass 1 searches the partition with the maximum number of faithful species across all clusters, while OptimClass 2 searches the partition with the maximum number of clusters that contain at least a preselected minimum number of faithful species. Faithful species are determined based on the P value of the Fisher's exact test, as a measure of fidelity. OptimClass was tested on three vegetation datasets that varied in species richness and internal heterogeneity, using several classification algorithms, resemblance measures and cover transformations. Results: Results from both variants of OptimClass depended on the preselected threshold P value for faithful species: higher P gave higher probability that a partition with more clusters was selected as optimal. Good partitions, in terms of OptimClass criteria, involved flexible beta clustering, and also ordinal clustering. Good partitions were also obtained with TWINSPAN when the required number of clusters was small, or UPGMA when the required number of clusters was large. Poor partitions usually resulted from classifications that used resemblance measures and cover transformations emphasizing differences in species cover; this is not unexpected because OptimClass uses a presence/absence-based fidelity measure. Conclusions: If the aim of a classification is to obtain clusters rich in faithful species, which can be subsequently used as diagnostic species for identification of community types, OptimClass is a suitable method for simultaneous choice of the optimal classification algorithm and optimal number of clusters. It can be computed in the JUICE program.
ER -
TICHÝ, Lubomír, Milan CHYTRÝ, Michal HÁJEK, Stephen S. TALBOT a Zoltán BOTTA-DUKÁT. OptimClass: Using species-to-cluster fidelity to determine the optimal partition in classification of ecological communities. \textit{Journal of Vegetation Science}. Oxford: Wiley-Blackwell, roč.~21, č.~2, s.~287-299. ISSN~1100-9233. 2010.
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