Publications and Research
Document Type
Article
Publication Date
Winter 2-25-2013
Abstract
Habitat fragmentation due to both natural and anthropogenic forces continues to threaten the evolution and maintenance of biological diversity. This is of particular concern in tropical regions that are experiencing elevated rates of habitat loss. Although less well-studied than tropical rain forests, tropical dry forests (TDF) contain an enormous diversity of species and continue to be threatened by anthropogenic activities including grazing and agriculture. However, little is known about the processes that shape genetic connectivity in species inhabiting TDF ecosystems. We adopt a landscape genetic approach to understanding functional connectivity for leaf-toed geckos (Phyllodactylus tuberculosus) at multiple sites near the northernmost limit of this ecosystem at Alamos, Sonora, Mexico. Traditional analyses of population genetics are combined with multivariate GIS-based landscape analyses to test hypotheses on the potential drivers of spatial genetic variation. Moderate levels of within-population diversity and substantial levels of population differentiation are revealed by FST and Dest. Analyses using structuresuggest the occurrence of from 2 to 9 genetic clusters depending on the model used. Landscape genetic analysis suggests that forest cover, stream connectivity, undisturbed habitat, slope, and minimum temperature of the coldest period explain more genetic variation than do simple Euclidean distances. Additional landscape genetic studies throughout TDF habitat are required to understand species-specific responses to landscape and climate change and to identify common drivers. We urge researchers interested in using multivariate distance methods to test for, and report, significant correlations among predictor matrices that can impact results, particularly when adopting least-cost path approaches. Further investigation into the use of information theoretic approaches for model selection is also warranted.
Figure S1. Structure results illustrating changes in ln Pr(X|K) under the aspatial model. b) Structure results based on the second order rate of change (ΔK method) under the aspatial model. For each K, 10 independent simulations were performed. https://doi.org/10.1371/journal.pone.0057433.s001 (TIF)
Figure_S2.tif (647 kB)
Figure S2. Structure results illustrating changes in ln Pr(X|K) under the spatial model. b) Structure results based on the second order rate of change (ΔK method) under the spatial model. For each K, 10 independent simulations were performed. https://doi.org/10.1371/journal.pone.0057433.s002 (TIF)
Table_S1.docx (40 kB)
Table S1. Genetic diversity statistics per locus and population for Phyllodactylus tuberculosus sampled throughout the Alamos, Sonora region. https://doi.org/10.1371/journal.pone.0057433.s003 (DOCX)
Table_S2.docx (15 kB)
Table S2. Multiple regression on distance matrices (MRM) results showing the relationship between pairwise genetic distance (linearized Dest) and least-cost path cost distances incorporating landscape heterogeneity. Candidate models tested were based on a priori hypotheses and to minimize collinearity among predictors. Optimal cost values used to parameterize resistance surfaces prior to calculating each least-cost path were selected based on Mantel r correlation coefficients. VIF = Variance Inflation Factor. https://doi.org/10.1371/journal.pone.0057433.s004 (DOCX)
Table_S3.docx (16 kB)
Table S3. Multiple regression on distance matrices (MRM) results showing the relationship between pairwise genetic distance (linearized Dest) and resistance distances incorporating landscape heterogeneity. Candidate models tested were based on a priori hypotheses. Optimal cost values used to parameterize resistance surfaces prior to calculating resistance distances were selected based on Mantel r correlation coefficients. VIF = Variance Inflation Factor. https://doi.org/10.1371/journal.pone.0057433.s005 (DOCX)
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Comments
This article originally appeared in PLoS ONE, available at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0057433
© 2013 Blair et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.