DOI: 10.5061/dryad.490p9
title: Data from: Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme

description: Genetic data are increasingly used in landscape ecology for the indirect
 assessment of functional connectivity, i.e. the permeability of landscape
 to movements of organisms. Among available tools, matrix correlation
 analyses (e.g. Mantel tests or mixed models) are commonly used to test for
 the relationship between pairwise genetic distances and movement costs
 incurred by dispersing individuals. When organisms are spatially
 clustered, a population-based sampling scheme (PSS) is usually performed,
 so that a large number of genotypes can be used to compute pairwise
 genetic distances on the basis of allelic frequencies. Because of
 financial constraints, this kind of sampling scheme implies a drastic
 reduction in the number of sampled aggregates, thereby reducing sampling
 coverage at the landscape level. We used matrix correlation analyses on
 simulated and empirical genetic datasets to investigate the efficiency of
 an individual-based sampling scheme (ISS) in detecting
 isolation-by-distance and isolation-by-barrier patterns. Provided that
 pseudo-replication issues are taken into account (e.g. through restricted
 permutations in Mantel tests), we showed that the use of inter-individual
 measures of genotypic dissimilarity may efficiently replace
 inter-population measures of genetic differentiation: the sampling of only
 three or four individuals per aggregate may be sufficient to efficiently
 detect specific genetic patterns in most situations. The ISS proved to be
 a promising methodological alternative to the more conventional PSS,
 offering much flexibility in the spatial design of sampling schemes and
 ensuring an optimal representativeness of landscape heterogeneity in data,
 with few aggregates left unsampled. Each strategy offering specific
 advantages, a combined use of both sampling schemes is discussed.
description: Microsatellite data for
 the alpine newt in Burgundy, FranceData were collected in
 the field (Burgundy, France). The "Clusters" column gives the
 name of sampled aggregates (see publication for details). Geographical
 coordinates (WGS84) are given in "X" and "Y" columns.
 The 24 other columns (two columns per microsatellite locus) provide
 genotype of each individual in the form of allele
 sizes.Empirical_data.txtSimulated data used to compare ISS and PSS.Data were simulated using the CDpop software. Each line stands for one individual. The "Dataset" column provides the name of each simulated dataset. The "Aggregate", "X" and "Y" columns provide the population of origin and the relative X-Y coordinates of each individual, respectively. The 20 other columns (A1-A2, B1-B2, ..., J1-J2) provide the simulated genotype of each individual at ten microsatellite loci (A to J). There are ten possible alleles for each locus.Simulated_data.txtList of aggregates located on in each side of the barrier in simulated datasetsThis file provides the relative location of simulated aggregates (1-160) on each side of the barrier. The "NE" column gives the list of aggregates located on the northeast side of the barrier; the "SW" column gives the list of aggregates located on the southwest side of the barrier.Barrier_data.txtMatlab script for Mantel tests with restricted permuationsThis script is to be used in the MATLAB software coding environment (Mathworks, Inc.) to perform Mantel tests with restricted permuations. Details are provided in the script.RestrictedMantel.m