DOI: 10.5061/dryad.qt3j5
title: Data from: Using a reference population yardstick to calibrate and compare genetic diversity reported in different studies: an example from the brown bear.

description: In species with large geographic ranges, genetic diversity of different
 populations may be well studied, but differences in loci and sample sizes
 can make the results of different studies difficult to compare. Yet, such
 comparisons are important for assessing the status of populations of
 conservation concern. We propose a simple approach of using a single
 well-studied reference population as a "yardstick" to calibrate
 results of different studies to the same scale, enabling comparisons. We
 use a well-studied large carnivore, the brown bear (Ursus arctos), as a
 case study to demonstrate the approach. As a reference population, we
 genotyped 513 brown bears from Slovenia using 20 polymorphic
 microsatellite loci. We used this dataset to calibrate and compare
 heterozygosity and allelic richness for 30 brown bear populations from 10
 different studies across the global distribution of the species. The
 simplicity of the reference population approach makes it useful for other
 species, enabling comparisons of genetic diversity estimates between
 previously incompatible studies and improving our understanding of how
 genetic diversity is distributed along a species range.
description: Brown bear genotypes
 from Slovenia (Northern Dinaric Mountains) - tab delimited
 txtThe dataset contains
 genotypes of 513 brown bears genotyped on 20 microsatellite loci. They
 were obtained by genotyping tissue samples of legally killed bears between
 2003 and 2008. The genotypes are mostly complete, there are missing data
 on a single locus in two samples (denoted "NA"). | Columns in
 the table: | sample - laboratory name of the sample | sex - sex of the
 animal (recorded by the field crew and rechecked by genotyping the SRY
 marker) | Genotypes: alleles at each locus are recorded in two columns,
 e.g. Cxx20_1, Cxx20_2. Missing data are recorded as "NA". |
 Note: this dataset mostly corresponds to the dataset used in the
 manuscript: Skrbinšek T, Jelenčič M, Waits L, Kos I, Jerina K, Trontelj P
 (2012). Monitoring the effective population size of a brown bear (Ursus
 arctos) population using new single-sample approaches. Molecular Ecology
 21(4): 862-875. Data: doi:10.5061/dryad.22rm1728. This present dataset
 doesn't have age data for the animals, but includes genotypes of
 three additional individuals for which we had no age data
 available.Slovenia_Bear_Genotypes.txtBrown bear genotypes from Slovenia (Northern Dinaric Mountains) - MS ExcelThe dataset contains genotypes of 513 brown bears genotyped on 20 microsatellite loci. They were obtained by genotyping tissue samples of legally killed bears between 2003 and 2008. The genotypes are mostly complete, there are missing data on a single locus in two samples (denoted "NA"). | Columns in the table: | sample - laboratory name of the sample | sex - sex of the animal (recorded by the field crew and rechecked by genotyping the SRY marker) | Genotypes: alleles at each locus are recorded in two columns, e.g. Cxx20_1, Cxx20_2. Missing data are recorded as "NA". | Note: this dataset mostly corresponds to the dataset used in the manuscript: Skrbinšek T, Jelenčič M, Waits L, Kos I, Jerina K, Trontelj P (2012). Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches. Molecular Ecology 21(4): 862-875. Data: doi:10.5061/dryad.22rm1728. This present dataset doesn't have age data for the animals, but includes genotypes of three additional individuals for which we had no age data available.Slovenia_Bear_Genotypes.xlsxR package "resamplediversity" containing genotypes of brown bears from Dinaric Mountains and all functions required to use the reference population approach.This is an R package containing all data and functions for running analyses presented in the manuscript. You will need R (www.r-project.org). You will need to install adegenet package (command: install.packages("adegenet")), and then this downloaded file (command: install.packages(file.choose(),repos=NULL)). Select resamplediversity_1.0.zip when the "File" dialog pops up. When the package is installed, invoke it from within R with library(resamplediversity). There is a user-friendly vignette: vignette("resamplediversity").resamplediversity_1.0.zipVignette for "resamplediversity" package.User friendly, hands-on, example based tutorial to the data and functions provided in resamplediversity package. Includes a walk-through through the analyses presented in the manuscript.resamplediversity-vignette.pdf