Comparing three classification strategies for use in ecology

Abstract

Abstract. 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.