A landscape genetics approach for quantifying the relative influence of historic and contemporary habitat heterogeneity on the genetic connectivity of a rainforest bird

Authors

  • DAVID C. PAVLACKY JR,

    1. School of Biological Sciences, University of Queensland, Brisbane, Qld 4072, Australia,
    2. Centre for Applied Environmental Decision Analysis, Ecology Centre, University of Queensland, Brisbane, Qld 4072, Australia,
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  • ANNE W. GOLDIZEN,

    1. School of Biological Sciences, University of Queensland, Brisbane, Qld 4072, Australia,
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  • PETER J. PRENTIS,

    1. Australian Centre for Evolutionary Biology and Biodiversity, School of Earth and Environmental Sciences, University of Adelaide, Adelaide, SA 5000, Australia,
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  • JAMES A. NICHOLLS,

    1. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK,
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  • ANDREW J. LOWE

    1. Australian Centre for Evolutionary Biology and Biodiversity, School of Earth and Environmental Sciences, University of Adelaide, Adelaide, SA 5000, Australia,
    2. State Herbarium and Bioknowledge, South Australia Plant Biodiversity Centre, Adelaide, SA 5005, Australia
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  • This research is part of David Pavlacky's PhD thesis on the landscape genetics of logrunners and spatial ecology of rainforest birds. Associate Professor Anne Goldizen's research focus is the behavioural ecology and conservation of vertebrates. Peter Prentis is a postdoctoral researcher using genetic and ecological techniques to answer applied and theoretical questions in evolutionary biology. James Nichols is a postdoctoral researcher using molecular tools to investigate evolutionary and ecological questions. Professor Andrew Lowe's research focus is the survival and adaptation of species to anthropomorphized landscapes, including selection pressures across a range landscape types.

David Pavlacky, Fax: + 1 970 472 9031; E-mail: david.pavlacky@uqconnect.edu.au

Abstract

Landscape genetics is an important framework for investigating the influence of spatial pattern on ecological process. Nevertheless, the standard analytic frameworks in landscape genetics have difficulty evaluating hypotheses about spatial processes in dynamic landscapes. We use a predictive hypothesis-driven approach to quantify the relative contribution of historic and contemporary processes to genetic connectivity. By confronting genetic data with models of historic and contemporary landscapes, we identify dispersal processes operating in naturally heterogeneous and human-altered systems. We demonstrate the approach using a case study of microsatellite polymorphism and indirect estimates of gene flow for a rainforest bird, the logrunner (Orthonyx temminckii). Of particular interest was how much information in the genetic data was attributable to processes occurring in the reconstructed historic landscape and contemporary human-modified landscape. A linear mixed model was used to estimate appropriate sampling variance from nonindependent data and information-theoretic model selection provided strength of evidence for alternative hypotheses. The contemporary landscape explained slightly more information in the genetic differentiation data than the historic landscape, and there was considerable evidence for a temporal shift in dispersal pattern. In contrast, migration rates estimated from genealogical information were primarily influenced by contemporary landscape change. We discovered that landscape heterogeneity facilitated gene flow before European settlement, but contemporary deforestation is rapidly becoming the most important barrier to logrunner dispersal.

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