DOI: 10.5061/dryad.8v5p3
title: Data from: Climatic suitability, isolation by distance and river resistance explain genetic variation in a Brazilian whiptail lizard

description: Spatial patterns of genetic variation can help understand how
 environmental factors either permit or restrict gene flow and create
 opportunities for regional adaptations. Organisms from harsh environments
 such as the Brazilian semiarid Caatinga biome may reveal how severe
 climate conditions may affect patterns of genetic variation. Herein we
 combine information from mitochondrial DNA with physical and environmental
 features to study the association between different aspects of the
 Caatinga landscape and spatial genetic variation in the whiptail lizard
 Ameivula ocellifera. We investigated which of the climatic, environmental,
 geographical and/or historical components best predict: (1) the spatial
 distribution of genetic diversity, and (2) the genetic differentiation
 among populations. We found that genetic variation in A. ocellifera has
 been influenced mainly by temperature variability, which modulates
 connectivity among populations. Past climate conditions were important for
 shaping current genetic diversity, suggesting a time lag in genetic
 responses. Population structure in A. ocellifera was best explained by
 both isolation by distance and isolation by resistance (main rivers). Our
 findings indicate that both physical and climatic features are important
 for explaining the observed patterns of genetic variation across the xeric
 Caatinga biome.
description: Table
 S1Table S1. Samples of
 Ameivula ocellifera used in the present study (336 samples). A map code
 number (see Figure 1) is presented for each sample, along with locality,
 state, institution of origin, voucher number, laboratorial code number,
 geographic coordinates (longitude and latitude in decimal degrees), and
 GenBank accession numbers.Table
 S2Table S2. Pairwise FST
 distances matrix (lower diagonal) and significant FST p-values (upper
 diagonal) for the 46 sampled localities of Ameivula ocellifera. Negative
 values in FST matrix were replaced with zeros to perform the analyses of
 genetic differentiation (more details in the “Genetic diversity and
 differentiation” section).Table
 S4Table S4. Climate and
 environmental values for each locality used to test genetic diversity in
 Ameivula ocellifera through linear regression or simultaneous
 autoregression analyses. Nucleotide diversity (π); climatic suitability
 from current and Last Glacial Maximum (LGM, 21 kyr) periods; isothermality
 (BIO3), temperature seasonality (BIO4), minimum temperature of coldest
 month (BIO6), annual mean temperature (BIO1), annual precipitation
 (BIO12), net primary productivity (NPP), actual evapotranspiration (AET),
 topographic complexity (TC), and distance from center of diffusion (DCD).
 Letters after BIO3, BIO4 and BIO6 variables represent current (C) and LGM
 (L) climate conditions.Table
 S6Table S6. Pairwise
 connectivity distance matrix for the 46 sampled localities of Ameivula
 ocellifera based on its current climatic suitability.Table
 S7Table S7. Pairwise
 connectivity distance matrix for the 46 sampled localities of Ameivula
 ocellifera based on its LGM climatic suitability.Table
 S8Table S8. Pairwise
 connectivity distance matrix for the 46 sampled localities of Ameivula
 ocellifera based on Caatinga main rivers.Table
 S9Table S9. Pairwise
 resistance distance matrix for the 46 sampled localities of Ameivula
 ocellifera based on Caatinga slope gradient.Table
 S10Table S10. Pairwise
 resistance distance matrix for the 46 sampled localities of Ameivula
 ocellifera based on Caatinga roughness gradient.Script_GDMR-script used to evaluate the contribution of environment and space in explaining genetic differentiation in Ameivula ocellifera using Generalized Dissimilarity Modelling (GDM).