Comparing Three Classification Strategies for Use in Ecology
- Resource Type
- research-article
- Authors
- Belbin, Lee; McDonald, Cam
- Source
- Journal of Vegetation Science, 1993 Apr 01. 4(3), 341-348.
- Subject
- Agglomerative Strategy
ALOC
Clustering Algorithm
Divisive Strategy
TWINSPAN
UPGMA
Species
Ordination
Datasets
Ecological modeling
Wildlife ecology
Vegetation
Synecology
Algorithms
Ecology
Test data
- Language
- English
- ISSN
- 11009233
16541103
We compare three common types of clustering algorithms for use with community data. TWINSPAN is divisive hierarchical, flexible-UPGMA is agglomerative and hierarchical, and ALOC is non-hierarchical. A balanced design six-factor model was used to generate 480 data sets of known characteristics. Recovery of the embedded clusters suggests that both flexible UPGMA and ALOC are significantly better than TWINSPAN. No significant difference existed between flexible UPGMA and ALOC.