Similarity indices for spatial ecological data

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

We present a method for assessing similarity between species maps of presence and absence or abundance that emphasizes global features while ignoring minor local dissimilarities. The method arranges sites into small groups, or cliques, and allows controlled changes to be made within cliques to reduce the influence of local discrepancies. Resulting: measures of similarity are visually more satisfactory than traditional indices. We show that the similarity indices are useful for model selection by comparing observed spatial patterns with those predicted by different fitted models. Examples are provided for spatial distributions of oribatid mites (Acari, Oribatei), woodlarks (Lullula arborea), and red deer (Cervus elaphus).

Original languageEnglish
Pages (from-to)495-501
Number of pages7
JournalBiometrics
Volume57
Publication statusPublished - Jun 2001

Keywords

  • best attainable match
  • matching coefficient
  • maximum matching in bipartite graph
  • minimum attainable distance
  • species map
  • WILDLIFE

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