DOI: 10.5061/dryad.15dv41nxm
title: Data for: The central Alps comprise a major dispersal barrier between western and eastern populations of two butterfly species

description: Aim: Environmental and species-specific factors shape spatial patterns in
 genetic diversity and population structure. Comparing different species
 within the same area helps to disentangle more general from
 species-specific factors affecting such geographic patterns. Here, we
 examined genetic diversity and population structuring through geographic
 features in two alpine butterfly species. Location: European Alps. Taxon:
 Copper butterflies (Lycaena spp.). Methods: We sampled 21 Lycaena
 hippothoe and 14 L. virgaureae populations with 18 individuals per
 population. We analysed the genetic diversity and structure of
 these populations by using 14 and nine microsatellite markers for L.
 hippothoe and L. virgaureae , respectively. Results: We found higher
 number of alleles, allelic richness, observed heterozygosity, FST values
  and more genetic clusters in L. hippothoe than in L. virgaureae.
 Both species displayed a major genetic barrier in the central Alps.
 Western and eastern L. hippothoe populations but central L. virgaureae
 populations showed the highest genetic diversity. Main Conclusions: The
 population genetic structures of both Copper butterflies seemed to be
 strongly affected by population history and demography. Patterns indicate
 for both species a western and an eastern glacial refuge. The high genetic
 diversity and pronounced population structure found in L. hippothoe seems
 to be related to a low dispersal ability and closed populations with high
 local abundances as opposed to L. virgaureae. The higher dispersal of the
 latter likely caused hybridisation in the central alpine contact zone
 boosting genetic diversity, which was not the case in L. hippothoe. These
 findings suggest that different conservation strategies are needed for
 these closely related species.
description: The study area is located
 in the European Alps, including sampling sites in Austria (Salzburg,
 Tyrol, Vorarlberg), Italy (South Tirol, Lombardy), and Switzerland
 (Graubünden), spanning an altitudinal range from ca. 1260 to 2240 m a.s.l.
 (Figure 1, Table 1). We sampled 21 and 14 populations with 18 individuals
 each in 2017-19 for <em>L. hippothoe</em> and <em>L.
 virgaureae</em>, respectively. Butterflies were caught with an
 insect net in the field, one leg was removed and stored in 100% ethanol
 until DNA extraction. Afterwards, we released the butterflies immediately
 and marked all sampled individuals before release to avoid the recapture
 of individuals (Marschalek et al., 2013). DNA was extracted with the
 E.Z.N.A. ® Tissue DNA Kit (Omega bio-tek, Germany) following the
 manufacturer’s instructions. In this study, we used 14 and nine
 microsatellite markers for <em>L. hippothoe</em> and
 <em>L. virgaureae</em> (for details see Trense et al., 2019;
 Supplementary Table S1). Genotyping the microsatellites was performed on
 an ABI 3130XL sequencer (Applied Biosystems, Germany) and the length of
 microsatellite loci was determined using the program GENEIOUS version
 11.1.5 (Kearse et al. 2012; https://www.geneious.com). The microsatellite loci were
 checked for potential null alleles using the program MICROCHECKER version
 2.2.3 (van Oosterhout et al., 2004). Numbers of alleles, alleles per
 locus, polymorphic loci, gene diversity, inbreeding coefficient
 (F<sub>IS</sub>),
 <em>F<sub>ST</sub></em> and
 <em>R<sub>ST</sub></em> value, observed
 (H<sub>O</sub>) and expected heterozygosity
 (H<sub>E</sub>), and analyses of molecular variance (AMOVA)
 were computed with ARLEQUIN version 3.5 (Excoffier & Lischer,
 2010). Number of private alleles, Nei’s genetic distance (Nei, 1972), and
 unbiased Nei’s genetic distance were calculated using GENALEX version 6.51
 (Peakall & Smouse, 2006, 2012). FSTAT version 2.9.3 (Goudet, 1995)
 was used to calculate allelic richness and FREENA to control for the
 impact of null alleles on <em>F<sub>ST</sub></em>
 values (Chapuis & Estoup, 2007). Linkage disequilibrium and
 Hardy-Weinberg equilibrium (HWE) were tested with GENEPOP version 4.2
 (Raymond & Rousset, 1995; Rousset, 2008). Resulting
 <em>p</em>-values for
 <em>F<sub>ST</sub></em> values were corrected for
 multiple testing using the Bonferroni Holm method (Holm, 1979).