Population structure of spotted salamanders (Ambystoma maculatum) in a fragmented landscape.

Academic Article


  • Understanding the impacts of landscape-level processes on the population biology of amphibians is critical, especially for species inhabiting anthropogenically modified landscapes. Many pond-breeding amphibians are presumed to exist as metapopulations, but few studies demonstrate the extent and consequences of this metapopulation structure. Gene flow measures may facilitate the construction of more realistic models of population structure than direct measures of migration. This is especially true for species that are cryptic, such as many amphibians. We used eight polymorphic microsatellite loci to determine the genetic population structure of spotted salamanders (Ambystoma maculatum) breeding at 17 ponds in northeastern Ohio, a landscape fragmented by roads, agriculture, urban areas and the Cuyahoga River. Using a variety of analyses (Bayesian clustering, F-statistics, AMOVA) we generated a model of salamander population genetic structure. Our data revealed patterns of genetic connectivity that were not predicted by geographical distances between ponds (no isolation by distance). We also tested for a relationship between population structure and several indices of landscape resistance, but found no effect of potential barriers to dispersal on genetic connectivity. Strong overall connectivity among ponds, despite the hostile habitat matrix, may be facilitated by a network of riparian corridors associated with the Cuyahoga River; however, high gene flow in this system may indicate a general ability to disperse and colonize beyond particular corridors.
  • Authors

  • Purrenhage, Jennifer
  • Niewiarowski, PH
  • Moore, FB-G
  • Status

    Publication Date

  • January 2009
  • Published In

  • Molecular Ecology  Journal
  • Keywords

  • Ambystoma
  • Animals
  • Bayes Theorem
  • Ecosystem
  • Gene Flow
  • Genetic Variation
  • Genetics, Population
  • Geography
  • Microsatellite Repeats
  • Ohio
  • Population Dynamics
  • Sequence Analysis, DNA
  • Digital Object Identifier (doi)

    Pubmed Id

  • 19192178
  • Start Page

  • 235
  • End Page

  • 247
  • Volume

  • 18
  • Issue

  • 2