DOI: 10.5061/dryad.sc88q
title: Data from: Performance of partial statistics in individual-based landscape genetics

description: Individual-based landscape genetic methods have become increasingly
 popular for quantifying fine-scale landscape influences on gene flow. One
 complication for individual-based methods is that gene flow and landscape
 variables are often correlated with geography. Partial statistics,
 particularly Mantel tests, are often employed to control for these
 inherent correlations by removing the effects of geography while
 simultaneously correlating measures of genetic differentiation and
 landscape variables of interest. Concerns about the reliability of Mantel
 tests prompted this study, in which we use simulated landscapes to
 evaluate the performance of partial Mantel tests and two ordination
 methods, distance-based redundancy analysis (dbRDA) and redundancy
 analysis (RDA), for detecting isolation by distance (IBD) and isolation by
 landscape resistance (IBR). Specifically, we described the effects of
 suitable habitat amount, fragmentation and resistance strength on metrics
 of accuracy (frequency of correct results, type I/II errors and strength
 of IBR according to underlying landscape and resistance strength) for each
 test using realistic individual-based gene flow simulations. Mantel tests
 were very effective for detecting IBD, but exhibited higher error rates
 when detecting IBR. Ordination methods were overall more accurate in
 detecting IBR, but had high type I errors compared to partial Mantel
 tests. Thus, no one test outperformed another completely. A combination of
 statistical tests, for example partial Mantel tests to detect IBD paired
 with appropriate ordination techniques for IBR detection, provides the
 best characterization of fine-scale landscape genetic structure. Realistic
 simulations of empirical data sets will further increase power to
 distinguish among putative mechanisms of differentiation.
description: MER_14_0246_RcodeR code for spatial principal components analysis, partial Mantel test, distance-based redundancy analysis, and redundancy analysisSimulationResults_MER_14_0246Test statistics and p-values from simulated data. IBR corresponds to landscapes that had a pixel resistance of 5 or higher and all pixels had a resistance of 1 in the IBD landscapes. Results are separated by statistical test and type of landscape.SampleInputFile_CDPOPInput file for CDPOP. All categories are described in the CDPOP manual.SampleResistanceFileSample Resistance File that is an input for Mantel tests and CDPOP.CoordinatesSample Coordinate File that is an input for dbRDA and RDA.ExampleBufferFileExample of a the percent of habitat found in a buffer around each individual. This file is an input for RDA and dbRDA.ExampleEuclideanDistanceExample of a Euclidean distance file that is used as an input for both CDPOP and Mantel tests.ExampleGenepopFileExample of a genepop file that is the input to both Spagedi and adegenet to calculate Rousset's a and sPCA scores respectively.ExampleRoussetsafileExample of a matrix of Rousset's a between all individuals calculated in Spagedi. These serve as the response variable in both partial Mantel tests and dbRDA.ExamplesPCAScoresFileExample of scores from the first two sPCA axes calculated in adegenet. This data serves as the response variable in RDA.SampleResistanceFileExample of pair-wise resistances values calculated in ArcGIS. These files serve as the input for CDPOP and partial Mantel tests.