Species-richness of the Anopheles annulipes Complex (Diptera: Culicidae) Revealed by Tree and Model-Based Allozyme Clustering Analyses

Abstract

The Australasian Anopheles annulipes complex contains at least ten sibling species, some of which are important vectors ormyxomatosis in rabbits. We aimed to establish how many species occurred among specimens from 61 sites throughout Australia, scored for 32 putative allozyme loci. We compared the number or species predicted from treebased clustering or operational taxonomic units (OTUs) with that from a novel model-based Bayesian clustering approach for individual genotypes. We rejected the hypothesis of conspecificity of OTUs if they differed by at least 20% fixed differences and 0.300 Nei's standard genetic distance D. According to these criteria, 18-25 species occur, making this the most species-rich anopheline complex known to date. A conservative estimate from the Bayesian analysis was 15-20 species. There was large overlap in the assignment of individuals to clusters inferred from the Bayesian and tree-based analyses. The genetic clustering of northern and southern distributed species and an apparent cline in alleles of the enzyme glucose phosphate isomerase suggest that a latitude-dependent factor, such as temperature, may have played a role in speciation and the subsequent distribution of species. Ecological niche modelling of clusters predicted that none occur in New Guinea, emphasizing that additional, as yet unsampled, species may occur.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA506153

Entities

People

  • Desmond H. Foley
  • Joan H. Bryan
  • Richard Charles Wilkerson

Organizations

  • Walter Reed Army Institute of Research

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Biological Sciences
  • Biology
  • Birds
  • Chemistry
  • Chromosomes
  • Clustering
  • Computer Programs
  • Computers
  • Data Analysis
  • Entomology
  • Genetics
  • Lepidoptera
  • Molecular Biology
  • New Guinea
  • Spreadsheet Software

Fields of Study

  • Environmental science

Readers

  • Molecular Genetics
  • Neural Network Machine Learning.
  • Vector-Borne Disease and Entomology

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Biotechnology