Scientific article
OA Policy
English

Phylogeography and support vector machine classification of colour variation in panther chameleons

Published inMolecular ecology, vol. 24, no. 13, p. 3455-3466
Publication date2015-05-24
First online date2015-05-24
Abstract

Lizards and snakes exhibit colour variation of adaptive value for thermoregulation, camouflage, predator avoidance, sexual selection and speciation. Furcifer pardalis , the panther chameleon, is one of the most spectacular reptilian endemic species in Madagascar, with pronounced sexual dimorphism and exceptionally large intraspecific variation in male coloration. We perform here an integrative analysis of molecular phylogeography and colour variation after collecting high‐resolution colour photographs and blood samples from 324 F. pardalis individuals in locations spanning the whole species distribution. First, mitochondrial and nuclear DNA sequence analyses uncover strong genetic structure among geographically restricted haplogroups, revealing limited gene flow among populations. Bayesian coalescent modelling suggests that most of the mitochondrial haplogroups could be considered as separate species. Second, using a supervised multiclass support vector machine approach on five anatomical components, we identify patterns in 3D colour space that efficiently predict assignment of male individuals to mitochondrial haplogroups. We converted the results of this analysis into a simple visual classification key that can assist trade managers to avoid local population overharvesting.

Keywords
  • Furcifer pardalis
  • Colour patterns
  • Panther chameleon
  • Phylogeography
  • Speciation
  • Supervised learning
  • Support vector machine classification
Citation (ISO format)
GRBIC, Dorde et al. Phylogeography and support vector machine classification of colour variation in panther chameleons. In: Molecular ecology, 2015, vol. 24, n° 13, p. 3455–3466. doi: 10.1111/mec.13241
Main files (1)
Article (Published version)
Identifiers
Journal ISSN0962-1083
75views
221downloads

Technical informations

Creation18/04/2024 07:35:23
First validation30/04/2024 09:52:28
Update30/04/2024 09:52:28
Status update30/04/2024 09:52:28
Last indexation01/11/2024 09:23:37
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack