Delimitation of a continuous morphological character with unknown prior membership: Application of a finite mixture model to classify scapular setae of Abacarus panticis

Tsung Jen Shen, Chi Chien Kuo, Chin Fah Wang, Kun Wei Huang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Unambiguous classification is a prerequisite for the study of polymorphism, but accurate delimitation of continuous morphological characters can be challenging. Finite mixture modeling is a rigorous and flexible approach for delimiting continuous variables with unknown prior membership, but its application to morphological studies remains limited. In this study, the lengths of scapular setae of the eriophyoid mite Abacarus panticis Keifer collected from 18 sites in Taiwan were used as an example to evaluate the eligibility of finite mixture models. We then tested the hypothesis that longer scapular setae can facilitate dispersal. Lastly, we investigate morphological variation in various seta morphs by geometric morphometric techniques. Finite mixture models can satisfactorily classify scapular setae of A. panticis into long and short seta morphs. Abacarus panticis of the long morph only occurred in five sites whereas the short seta morph existed in all study sites. Geometric morphometric analyses revealed a more elongated coxal area in individuals of long morph than in those of short morph. Because the short morph is more widespread in geographical distribution than the long morph, longer scapular setae seem unlikely a specialized adaptation for dispersal. Further studies should capitalize on the finite mixture model in the delimitation of continuous morphological characters.

Original languageEnglish
Pages (from-to)361-375
Number of pages15
JournalExperimental and Applied Acarology
Volume63
Issue number3
DOIs
Publication statusPublished - 2014 Jul

Keywords

  • Eriophyoid mites
  • Geometric morphometrics
  • Intraspecific variability
  • Polymorphism

ASJC Scopus subject areas

  • Ecology
  • Insect Science

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