Journal of Avian Biology 46: 462–475, 2015 doi: 10.1111/jav.00679 ¢ 2015 The Authors. Journal of Avian Biology ¢ 2015 Nordic Society Oikos Subject Editor: Javier Perez-Tris. Editor-in-Chief: Jan-Åke Nilsson. Accepted 5 March 2015

Evidence for strong genetic structure in European populations of the little owl Athene noctua Irene Pellegrino, Alessandro Negri, Giovanni Boano, Marco Cucco, Torsten N. Kristensen, Cino Pertoldi, Ettore Randi, Martin Šálek and Nadia Mucci I. Pellegrino, A. Negri and M. Cucco ([email protected]), Univ. of Piemonte Orientale, DISIT, viale Michel 11, IT-15121 Alessandria, Italy. – N. Mucci and E. Randi, ISPRA, via Ca’ Fornacetta 9, IT-40064 Ozzano dell’Emilia, Italy. – G. Boano, Natural History Museum of Carmagnola, Cascina Vigna, IT-10022 Carmagnola, Italy. – T. N. Kristensen, C. Pertoldi and ER, Dept of Chemistry and Bioscience, Section of Biology and Environmental Science, Fredrik Bajers Vej 7H, DK-9220 Aalborg East, Denmark. CP also at: Aalborg Zoo, Aalborg, Denmark. – M. Šálek, Inst. of Vertebrate Biology, Academy of Sciences of the Czech Republic, Květná 8, CZ-60365 Brno, Czech Republic, and Dept of Zoology, Faculty of Science, Univ. of South Bohemia, Branišovská 31, CZ-37005 České Budějovice, Czech Republic.

The little owl Athene noctua is a widespread species in Europe. This mainly sedentary owl experienced reduction in population sizes in some areas due to habitat loss and modification of the landscape. To assess the genetic structure of the populations of western and central Europe, we analysed 333 specimens from 15 geographical areas at 13 microsatellite loci. Statistical analyses and Bayesian clustering procedures detected two major genetically distinct clusters, the first distributed from Portugal to the Czech Republic and the second from the Balkans to Italy. The second cluster was further split into three groups, located in Italy, Sardinia and the Balkans. These groups match four previously-described mtDNA haplogroups, and probably originated from the isolation of little owl populations in Sardinia and in three glacial refugia (Iberia, south Italy and Balkans) during the ice ages. High genetic admixture was recorded in central and northern Europe, probably as a consequence of the expansion from the refugia during interglacial. The main colonization route originated from the Iberian Peninsula towards central and northern Europe. Contact zones with colonization events from Italy and the Balkans were detected respectively in northern Italy and central Europe. Genetic indices show the existence of moderate levels of genetic variability throughout Europe, although evidence of recent evolutionary bottlenecks was found in some populations. Estimation of migration rates and approximate Bayesian computations highlighted the most likely phylogeographical scenario for the current distribution of little owl populations.

Animal populations can vary in abundance and range distribution over time. Population changes can be driven by natural or competition events, although the impact of human activities has become decisive for the survivor of species in the last millennia, representing the main cause of habitat loss, isolation and fragmentation for many species and populations. In the last decades also global climate changes contributed to altered environmental conditions. Several ornithological studies have documented the effects of global changes on local population dynamics such as phenology (many bird species reproduce or arrive earlier to breeding habitats on high latitude breeding grounds (Jiguet et al. 2010), changes of distribution (Crick 2004), and altitudinal limits (Jiguet et al. 2010). Population genetics is an useful tool to investigate population dynamics at present and in the past, inferring the occurrence of events such as bottlenecks, expansions, movements and related gene flow (Allendorf et al. 2012). Microsatellites represent the most popular and versatile marker type (Sunnucks 2000, Selkoe and Toonen 2006) for ecological applications. Besides individual identification, 462

parentage assignment and kinship analyses (Jones and Ardren 2003, Ringler 2012), or sex identification (Nesje and Roed 2000), microsatellites have been employed to investigate population structure (Procházka et al. 2011), genetic flow between different areas (Zink and Barrowclough 2008, Chaves et al. 2012), effective population size during bottleneck events (Barton and Wisely 2012), colonization, selection and drift processes (Estoup and Clegg 2003, Clegg and Phillimore 2010, Spurgin et al. 2014). Also mtDNA is often used to investigate the demographic changes or colonization events in wild populations (Selkoe and Toonen 2006, Fuchs et al. 2007). Although mtDNA and nDNA analyses sometimes lead to contrasting results (Brito 2005, 2007), the literature supports using a multigene approach in order to obtain reliable results from phylogeographic studies and produce complementary data that enable reconstructing a species phylogeographic history. Several genetic and paleontological studies on plants and animals revealed the existence of three major glacial refugia in Europe during the Last Glacial Maximum: south Iberia, south Italy and south Greece (Taberlet et al. 1998, Cheddadi

et al. 2006, Sommer and Nadachowski 2006, Liepelt et al. 2009). Furthermore several extra-Mediterranean (Schmitt and Varga 2012) and north African refugia have been identified (Godoy et al. 2004, Habel et al. 2011). Postglacial colonization from southern refugia followed different patterns depending on dispersal behaviour which is influenced by the biology and ecology of the species, barriers in the landscape and geomorphology (Taberlet et al. 1998, Hewitt 2004, Gómez and Lunt 2007). Taxa expanding northward from a glacial refugia came into contact with taxa expanding from other glacial refugia in areas known as suture zones, characterized by genetic admixture (Hewitt 2011). Phylogenetic analyses have confirmed the existence of three major glacial refugia and suture zones for many European avian species, e.g. green woodpecker Picus viridis (Perktas et al. 2011, Pons et al. 2011), Savi’s warbler Locustella luscinioides (Neto et al. 2012), the blue tit Cyanistes complex (Illera et al. 2011) and several other passerine bird species (Aliabadian et al. 2005). North Europe was recolonized from glacial refugia by bird species expanding from different refugia: from the Balkans (e.g. tawny owl Strix aluco, Brito 2005, 2007), from south Italy (e.g. dipper Cinclus cinclus, Hourlay et al. 2008), or from the Iberian Peninsula (e.g. little owl Athene noctua, Pellegrino et al. 2014). Despite historical isolation should have favoured population structuring, in some bird species molecular analysis showed no phylogeographic structure (Hung et al. 2013, Kraus et al. 2013, Perktas and Quintero 2013). This suggests that geographical barriers did not play the same role for all species and that dispersal behaviour could vary due to social as well as ecological factors. The little owl is a small nocturnal species, with short distance dispersal (Cramp 1985, Van Nieuwenhuyse et al. 2008). It is distributed throughout the Palaearctic regions, from Iberia to China, in north Africa and Arabia (Cramp 1985). It is strongly associated with open agricultural landscapes. In northern and central Europe, populations size are rapidly declining likely due to environmental modification, habitat loss, degradation and pollution (Brink et al. 2003, Šálek and Schröpfer 2008, Šálek and Lövy 2012, Thorup et al. 2013). The species is listed as a ‘SPEC 3’ species (i.e. a species whose global populations are not concentrated in Europe, but which have an unfavourable conservation

status in Europe; Tucker and Heath 1994). A previous study on the species using mtDNA markers (control region and COI) found four distinct European clades distributed respectively in the three main glacial refugia (Iberian, Italian and Balkan Peninsulas) and in Sardinia (Pellegrino et al. 2014), with contact zones in north Italy and in Hungary. The molecular analyses revealed the existence of a strong phylogeographic pattern in another European strigid, twany owl (Brito 2005, 2007), while no structure was observed in Tengmalm’s owl Aegolius funereus (Broggi et al. 2013), snowy owl Bubo scandiacus (Marthinsen et al. 2009) and Ural owl Strix uralensis (Hausknecht et al. 2014). Tawny owl and little owl survived in the same three major refugia during the last ice age (south Italy, Balkans, and Iberian Peninsula), but they experienced different recolonization routes. Tawny owl expanded mainly from the Balkans and little owl mainly from the Iberian Peninsula. Contact zones between clades were found in Iberia and in France for tawny owl and in central Europe and north Italy for little owl. In this study thirteen microsatellites loci were used with the aim: 1) to describe the genetic variability in European little owl; 2) to examine the structure of European little owl populations; 3) to obtain insights on past bottleneck events and gene flow; 4) to analyse admixture between clusters and 5) to compare the distribution of the present genotypes with the pattern of postglacial recolonization previously inferred from mtDNA (Pellegrino et al. 2014). Our results will yield an understanding of the genetic structure and level of genetic variation in this species that experience a decrease in population size in many European countries and can be used by wildlife managers for conservation and restoration plan purposes.

Methods Sample collection and DNA extraction A total of 333 samples were collected from 15 countries across western and central Europe (Fig. 1, Supplementary material Appendix 1, Table 1). Tissues (blood, plucked feathers, or muscle) were collected from natural history

Figure 1. Sampling sites and genotype structure of individuals. Pie charts show the proportion of the four clusters calculated by the structure analysis (K  4, same colours as Fig. 3) in each sampled population.

463

Table 1. Groups and population used in the analysis, including origin and number of individuals in each pool. Group Iberia

North central Europe

Balkan

Italy

Number of individuals Population Country

Number of individuals

Data analysis

47 PT ES

Spain Portugal

18 29

FR DK CZ

16 20 11

AT HU RO

France Denmark Czech Republic Austria Hungary Romania

BG MK MK GR GR

Bulgaria Macedonia Albania Greece Cyprus

14 14 7 20 5

IT_S IT_C IT_Sar IT_N IT_N

South Italy Central Italy Sardinia island North Italy Switzerland

23 33 12 51 5

102

16 19 20

60

124

museums, recovery centres, road killed individuals, or during bird banding. Tissue and feathers samples were individually stored in ethanol at 20oC, blood samples were kept in Longmire Buffer (Longmire et al. 1997) and preserved at 2–4oC. Tissue and blood genomic DNA was isolated using a NucleoSpin¡Tissue kit (Macherey-Nagel, Düren, Germany). For feathers, the calamus was placed in a lysis buffer (FLB Macherey-Nagel, Düren, Germany, designed for small DNA quantities), exposed to thermal shock in liquid nitrogen and left for prelysis at 56oC overnight. DNA amplification and genotyping Each individual was genotyped at 13 polymorphic microsatellite loci (Supplementary material Appendix 2). We used the six most polymorphic primers, previously isolated in little owl (Aurelle 2010), while other seven primers were selected after testing for cross-amplification from those previously isolated in other Strigiform species (Thode et al. 2002, Hsu et al. 2003, Proudfoot et al. 2005, Burri et al. 2008). We utilized the following protocol: (94oC  5 min), 29–32 cycles at (94oC  45 s) (TDoC  45 s) (72oC  45 s), and a final extension at 72oC for 7 min. We applied a ‘touch-down’ thermal protocol where the annealing temperature was lowered 0.5oC per cycle, starting from 60oC until a temperature of 55oC for Ath3-4-5-7-9-10 primers, and starting from 55oC until a temperature of 50oC for 15A6, Oe045, Oe085, FEP043, Oe053, Ta212 and Ta216 primers. Amplifications were performed in a Bio-Rad C1000 thermal cycler. Negative controls were included for both the extraction and amplification procedures. After PCR, loci tagged with two different labels were combined and 464

run on an ABI-3130xl automated sequencer using rox350 size. Results were analysed in GeneMapper ver. 4.0 (Applied Biosystems).

In order to perform the analyses, individuals were gathered in four groups representing four European areas separated from geographical barriers (Table 1, column 1) and in 15 populations, (Table 1, column 3), corresponding to areas sampled. Adopted grouping is detailed for each analysis. Allele frequencies, standard diversity indices, observed heterozygosity (HO) and expected heterozygosity (HE) for each locus and population were calculated using GenAlex ver. 6 (Peakall and Smouse 2006) and patterns of differentiation were visualized by a factorial correspondence analysis (FCA) of individual multilocus scores using Genetix 4.05 (Belkhir et al. 2004). We investigated the occurrence of population structure calculating a discriminant analysis of principal components (DAPC) with Adegenet 1.2-8 (Jombart et al. 2010) package in R (R Core Team). This approach reduced genetic data to principal components to ensure that variables used in the discriminant analysis are uncorrelated. The inference of the most likely number of clusters was based on the Bayesian information criterion (BIC; Schwarz 1978). DAPC plot and Bayesian information criterion (BIC) graphs were obtained by retaining a number of principal components (PCs) representing 100% of the total variation of the sample set. We investigated genetic structure also using multilocus genotypes and Bayesian clustering procedures. We used Structure 2.3 (Pritchard et al. 2000, Falush et al. 2003) to infer the number of K unknown populations (genetic clusters) in which the sampled multilocus genotypes could be subdivided. We run admixture model with correlated allele frequencies as suggested by Falush et al. (2003). Analyses were performed with K  1–10, 50  105 iterations following a burn-in period of 50  104 iterations, and all simulations were independently replicated ten times for each K. In order to assess the best K value supported by the data, we used the LnP(D) and Evanno et al. (2005) methods in the software Structure Harvester 0.6.93 (Earl and von Holdt 2012). To align the cluster membership coefficients of the five structure runs and to display the results, we used CLUMPP ver. 1.1.2 (Jakobsson and Rosenberg 2007) and Distruct ver. 1.1 (Rosenberg 2003). Population differentiation was tested between all population pairs and among all populations, at each locus and over all loci, using FSTAT 2.9.3.2. (Goudet 1996). Departures from Hardy–Weinberg equilibrium (HWE) at each locus and within each population, linkage disequilibrium for all pairwise combinations of loci and unbiased estimates of FST (Weir and Cockerham 1984) were computed, using exact tests, in Genepop 3.4 (Raymond and Rousset 1995, Rousset 2008) with Markov chain parameters left at the default settings (Raymond and Rousset 1995). ARLEQUIN 3.5 (Excoffier and Lischer 2010) estimated the genetic variance within and between the 15 sampled populations through a hierarchical analysis of molecular variance (AMOVA, Excoffier et al. 1992), and the presence of

isolation-by-distance through a Mantel test, running 1000 bootstrap iterations. The geographic distance connecting samples was represented by Euclidean (linear geographic) distances computed in QGis (QGIS Development Team 2014). We detected the occurrence of genetic bottlenecks using two different approaches. First, we applied the Wilcoxon’s test to compute three mutational models in the program BOTTLENECK 1.2.02 (Cornuet and Luikart 1996): the infinite allele model (IAM, Maruyama and Fuerst 1985), the two phase model (TPM, Di Rienzo et al. 1994) and strict stepwise mutation model (SMM, Ohta and Kimura 1973). These methods detect departure from mutation–drift equilibrium as assessed by heterozygosity excess or deficiency, enabling detection of recent genetic bottlenecks. Then, we computed the M ratio test, using the software M_P_Val (Garza and Williamson 2001). The significance of an observed M value is determined by comparing it to a distribution of M values calculated from theoretical populations in mutation–drift equilibrium; the Mc was calculated using Critical_M (Garza and Williamson 2001). The analysis was run assuming a TPM (Di Rienzo et al. 1994) with proportion of one-step mutations, ps  0.88, average size of non one-step mutations, ∆g  2.8 and Theta Q  10 as suggested by Garza and Williamson (2001).

performed 5 independent runs of 3  106 iterations including a burn-in of 10%, and a sampling frequency of 2000 to ensure convergence of the MCMC. Delta values were varied for all parameters to obtain the acceptance rates between 40 and 60% of the total iterations (Wilson and Rannala 2003). Mixing and convergence of MCMCs were visually assessed using Tracer 1.6 (Rambaut et al. 2014). Finally we used STRUCTURE, with prior population information model (USEPOPINFO  1; MIGRPRIOR  0.05) under the admixture model with allele frequencies uncorrelated, to investigate the movement of individuals between predefined geographical populations. Approximate Bayesian computation was used to interpret the routes of recolonization from glacial refugia in DIYABC 2.0.3 (Cornuet et al. 2010). The four groups formerly identified (lberia, central Europe, Balkan and Italy) were analyzed and a total of 3  610 simulated dataset was generated using the default set mutation model of STRs. Population sizes were set as uniform and times of split and merge were t3  t2  t1. Three scenarios of recolonization of central Europe were tested: 1) recolonization from Iberia Peninsula; 2) recolonization from Balkans; 3) recolonization from both lberia and Balkans.

Results

Identification of admixture areas and gene flow

Genetic variability

Identification of contact zones, admixture areas and existence of gene flow was detected using STRUCTURE. Genotypes clustering with an individual membership value lower than 0.90 were considered admixed (Barilani et al. 2007). To identify samples showing discordance between nuclear and mitochondrial DNA, we compared the mtDNA control region haplotypes previously analyzed by Pellegrino et al. (2014), with genotypes resulting from the present study (data available for 269 out of 333 individuals). Migration rate was estimated using the Bayesian inference approach implemented in BayesAss 3.0.3 and 1.3 (Wilson and Rannala 2003). In keeping with the authors’ recommendation, we

All loci were polymorphic in every population. The number of alleles per locus ranged from a maximum of 23 in Oe045 locus to 4 in Ta212. Average number of alleles per locus varied from 4 in Sardinia to 7.8 in north Italy (Table 2). We found 26 private alleles in 12 populations, the number of private alleles per population ranging from zero in three different populations to four in the populations from Sardinia and north Italy. Observed heterozygosity ranged from 0.454 in Austria to 0.699 in Czech Republic (mean 0.593), while expected heterozygosity varied from 0.507 in Sardinia to 0.688 in

Table 2. Genetic diversity in sampling populations. N  sample size, Ao  average number of alleles per locus, Ae  average number of effective alleles per locus, Ap  number of private alleles, Ar  allelic richness, Ho  observed heterozygosity, He  expected heterozygosity, F  fixation index. Standard errors in brackets. Pop PT ES FR DK CZ AT HU RO BG MK GR IT_S IT_C IT_Sar IT_N Total mean

N

Ao

Ae

Ap

Ar

Ho

He

F

18 29 16 20 11 16 19 20 14 21 25 23 33 12 56 333

4.923 (0.525) 6.000 (0.588) 5.077 (0.593) 4.923 (0.537) 5.077 (0.560) 4.462 (0.386) 5.846 (0.750) 5.615 (0.626) 5.154 (0.541) 6.000 (0.784) 6.154 (0.831) 6.231 (0.907) 7.000 (0.906) 4.000 (0.543) 7.769 (1.014) 5.615 (0.186)

3.152 (0.326) 3.382 (0.401) 3.373 (0.450) 3.151 (0.344) 3.478 (0.373) 2.378 (0.240) 3.789 (0.515) 3.509 (0.422) 3.077 (0.434) 3.721 (0.504) 4.019 (0.597) 4.023 (0.516) 4.254 (0.582) 2.720 (0.377) 4.584 (0.685) 3.507 (0.122)

1 0 3 3 1 3 1 0 1 2 2 0 1 4 4 –

4.502 4.746 4.693 4.410 5.077 4.077 5.195 4.984 4.845 5.115 5.307 5.371 5.431 3.959 5.825 6.202

0.585 (0.074) 0.537 (0.076) 0.587 (0.081) 0.592 (0.066) 0.699 (0.069) 0.454 (0.067) 0.683 (0.071) 0.563 (0.070) 0.588 (0.088) 0.616 (0.084) 0.587 (0.088) 0.579 (0.076) 0.619 (0.066) 0.550 (0.092) 0.650 (0.069) 0.593 (0.019)

0.605 (0.067) 0.606 (0.074) 0.625 (0.054) 0.618 (0.053) 0.653 (0.050) 0.516 (0.055) 0.647 (0.063) 0.621 (0.071) 0.571 (0.070) 0.613 (0.083) 0.620 (0.084) 0.656 (0.072) 0.684 (0.060) 0.507 (0.080) 0.688 (0.066) 0.615 (0.017)

0.024 (0.058) 0.120 (0.060) 0.078 (0.082) 0.042 (0.059) –0.050 (0.078) 0.178 (0.089) –0.062 (0.044) 0.079 (0.036) –0.013 (0.062) –0.018 (0.035) 0.109 (0.059) 0.142 (0.049) 0.102 (0.044) –0.081 (0.046) 0.086 (0.037) 0.049 (0.015)

465

northern Italy (mean 0.615). Estimates of Wright’s fixation index (FIS) revealed that populations from Austria, Denmark, France, Italy, Romania, Greece and Spain had significantly greater than zero values, indicating widespread departure from HWE (Table 2), while those from Bulgaria, Hungary, Sardinia, Macedonia, Portugal and Czech Republic were in Hardy–Weinberg equilibrium. No evidence for linkage disequilibrium was found between loci and populations (after Bonferroni correction). Genetic structure Results of a discriminant analysis of principal components (DAPC) showed that the first three DA eigenvalues and the first 100 retained PCs explained the observed variance (Supplementary material Appendix 4). Bayesian information criterion (BIC) found three-five clusters best representing the genetic subdivision of the dataset. Clusters at K  3 (data not shown) grouped respectively: 1) Spain, Portugal, France, Denmark, and Austria, 2) Italy and Sardinia, 3) Balkan regions. At K  4 (Fig. 2a) Austrian samples grouped separately in a cluster and at K  5 (Fig. 2b) Sardinian and some Italian individuals split from Italy. A DAPC scatterplot

of the first two principal components (Fig. 2c) showed three distinct groups, the first including Sardinia and Italy; the second Spain, Portugal, France, Denmark, and Austria; the third all the Balkan populations (Romania, Bulgaria, Greece, and Macedonia) and Czech Republic. Hungary was plotted between the Balkans and north-western European populations. The scatterplot (Fig. 2d) of the second and third principal component axis evidenced the separation of Sardinia. The FCA plotting of individual genotypes supported the same clear separation between the four little owl groups (figure not shown). Results from STRUCTURE supported the presence of 3 genetic clusters (greater ∆K, Supplementary material Appendix 4). We explored the individuals assignment from K  2 to K  5 in order to examine the sequential splits. At K  2 (Fig. 3a) the first cluster included individuals from Spain, Portugal, France, Denmark, Austria, and Czech Republic, the second included the samples from Italy, Sardinia, Switzerland, Greece, Romania, Macedonia, and Bulgaria (Fig. 3a). At K  3 (Fig. 3b), this second cluster was split in two groups, and the individuals from Greece, Bulgaria, and Romania were separated from Italian, Sardinian and Swiss individuals. At K  4 (Fig. 3c and Fig. 1), Sardinian

Figure 2. Results from multivariate analyses DAPC for populations of little owl. (a) and (b) individuals assignment to each identified cluster K  4 and K  5; (c) and (d) scatterplot of the multivariate analysis DAPC for populations of little owl. Populations (groups) are displayed by different colours and inertia ellipses. Dots represent individuals. (c) First two principal components of the DAPC. (d) DAPC axes 1 and 3.

466

Figure 3. Individual assignment probabilities for K  2 (a), K  3 (b), K  4 (c), and K  5 (d) found by structure analyses and computed in CLUMPP from 5 independent runs. Each vertical line represents one individual and shows its inferred cluster membership. Each colour represents a single genetic cluster. Colour legend: green: western cluster; red: Balkan cluster; blue: south Italian cluster; yellow: Sardinian cluster.

individuals were clustered in a separate group. Considering K  5 (Fig. 3d) we noted that some individuals were assigned to the fifth cluster, distinct from the Sardinian, and without a significant geographic structure. Population differentiation and analysis of population variance AMOVA analysis revealed that 81.6% of the total genetic variance was distributed within individuals, while 10.2 and 8.2% was distributed respectively among populations and individuals within populations. These values agree with the results obtained analysing the samples in four groups (Table 3). Among populations FST-values were mostly significant (average value  0.156; Supplementary material Appendix 3). Lowest and highest differentiations were found

respectively within and between the main genetic groups (Balkans, north-western Europe, Sardinia, and Italy). The largest differentiation was found between Denmark and Sardinia, while minimum differentiation was found between north east Spain and Portugal. In the Sardinia population, allelic richness, the mean number of alleles per polymorphic locus, and heterozygosity observed were similar to those found in other populations (Table 2); thus there is no strong evidence of founder effect. Identification of admixture areas and gene flow Individuals were plotted on a geographic map and coloured differently according to the cluster assignment (Fig. 1). Birds from Hungary always showed admixed genotypes: 49.4% were assigned to the Balkans cluster and 42.6% to

Table 3. Results from analysis of molecular variance (AMOVA) for different grouping methods. 15 populations Source of variation Among populations Among individuals within populations Within individuals Total

Sum of squares

Variance components

4 groups Percentage variation

Sum of squares

Variance components

Percentage variation

358.09

0.480

10.17

196.79

0.382

7.98

1470.53

0.387

8.21

1631.84

0.555

11.60

1282.00 3110.63

3.850 4.717

81.62 100

1282.00 3110.63

3.850 4.787

80.43 100

467

the NW European cluster. At K  2, Swiss and north Italian samples showed clear admixture between Balkan and north-west European clusters. At K  3 and K  4, the same genotypes were shared between the Italian and north-west European clusters. Moreover, at K  3 and K  4 the samples from central and south Italy were associated to both Balkan and NW European clusters. Outside of Sardinia, the highest percentage of membership to the Sardinian cluster (qi ranging from 0.74 and 0.89%) was detected in two individuals from south Italy (Sicily), two from Albania, and two from Greece. Comparison between nuclear and mtDNA (Pellegrino et al. 2014) showed discordance in 54 Italian samples previously ascribed by mtDNA to the Balkan haplogroup: 47 samples were assigned by microsatellites to the Italian cluster and seven showed Italian, Balkan, Sardinian, NW European or admixed genotypes (Fig. 1). Discordance was observed also in eight samples with the south Italian haplotype (seven from Italy and one from Switzerland) that showed Sardinian, Balkan or mixed genotypes. Five individuals from north Italy belonging to the NW European haplogroup were assigned by nuclear DNA to the south Italian cluster. We detected no discordance between nuclear and mtDNA for samples collected in Sardinia. All samples from France, Spain, Portugal, Denmark, and Czech Republic (except one) showed concordance between haplotypes and genotypes. Some samples from Hungary, one from Austria, Romania, and Czech (a) N1 N2 N3 N4 N1+N3

Republic showed discordance between nuclear and mtDNA data, with admixed or NW Europe genotypes. BayesAss allowed the estimation of recent migration events. Inferred mean non-migration rate was 0.75 (95% confidence intervals: 0.68–0.99). Migration rate values indicated the presence of gene flow from: 1) south and central Italy to north Italy; 2) Spain and France to Portugal; 3) Czech Republic to Denmark; 4) Bulgaria and Romania to Macedonia. Results from STRUCTURE migrants analysis partly complied with those obtained by BayesAss; structure detected low proportion of migrants (4.2–6.9%) between Portugal and Spain, and also revealed gene flow between Czech Republic, Austria, Hungary, and Macedonia. These data confirmed the absence of gene flow between Balkan and Iberian areas. Post-probabilities detected with the logistic approach in DIYABC revealed that central Europe was recolonized from both western and eastern Europe, although the post probability is smoothly higher in the first scenario (recolonization from Iberian peninsula) than in the second (Fig. 4). Post probability values were 0.05 [0.04–0.05] for the first scenario, 0.02 [0.02– 0.03] for the second and 0.93 [0.93–0.94] for the third. Isolation by distance and recent bottleneck events The Mantel test on geographic and genetic distances yielded a significant correlation coefficient between geographic and genetic distances (rxy  0.271, p 0.01).

Scenario 1

Scenario 2

Scenario 3

(Warning ! Time is not to scale)

(Warning ! Time is not to scale)

(Warning ! Time is not to scale)

t3

N1 N2 N3 N4 N1+N3

t3

BK

CE

t2

t2

t1

t1

t1

IB

1.0

0.8

0.8

0.6

0.6

0.4

0.4

0.2

0.2

0.0

0

100

200

Scenario 1

300 Scenario 2

400

CE

IT

IT

IB

PP = 0.0242 [0.0219 - 0.0266]

Direct

1.0

500

Scenario 3

0

0

BK

PP = 0.0450 [0.0414 - 0.0487]

(b)

t3

t2

0

IT

N1 N2 N3 N4 N1+N3

BK

CE

IB

PP = 0.9307 [0.9264 - 0.9350]

Logistic regression

0.0 28500 29000 29500 30000 30500 31000 31500 Scenario 1

Scenario 2

Scenario 3

Figure 4. (a) Scenarios explored in DIYABC. In the first, colonization of central Europe is from Iberian Peninsula, in the second, from Balkans region, in the third, from both the glacial refugia. PP  posterior probabilities for each scenario. (b) Direct and logistic regression plots. Posterior probabilities are reported on the y axis.

468

Table 4. Bottleneck and M-Ratio results in little owl. Values are shown for each population and for four groups. Listed by column are p-values (TPM, IAM, SMM), M-ratio and MC for population bottleneck testing. Significant p-value are reported in bold.

Populations

Groups

Sampling regions

IAM p-values

TPM p-values

SMM p-values

M-ratio

MC

Portugal Spain France Denmark Czech Republic Austria Hungary Romania Bulgaria Macedonia Greece South Italy Central Italy Sardinia North Italy Iberian Peninsula N-C Europe Balkans Italy

0.0522 0.08771 0.0012 0.0006 0.0681 0.6848 0.0012 0.0681 0.5693 0.0134 0.0342 0.0007 0.0012 0.2334 0.0067 0.0081 0.0002 0.0640 0.0017

0.2661 0.8501 0.0681 0.0327 0.1677 0.0803 0.0574 0.5417 0.3013 0.1763 0.0923 0.0134 0.0681 0.5185 0.0574 0.6221 0.0803 0.9697 0.1099

0.9097 0.0167 0.4973 0.8394 0.6848 0.0040 0.4973 0.2439 0.0342 0.3394 0.7334 0.9097 0.1698 0.6772 0.7513 0.1099 0.0052 0.0342 0.0681

0.91 0.78 0.85 0.88 0.87 0.71 0.71 0.76 0.81 0.77 0.89 0.69 0.54 0.84 0.83 0.17 0.68 0.74 0.49

0.489 0.53 0.47 0.50 0.43 0.47 0.49 0.50 0.46 0.51 0.52 0.51 0.55 0.44 0.59 0.62 0.64 0.60 0.65

Bottleneck events were tested both under the assumptions of IAM, TPM and SMM by two-tailed Wilcoxon test for heterozygote excess or deficiency. Evidence for genetic bottlenecks was found by IAM in seven populations (p 0.01): north, central and south Italy, Hungary, Macedonia, France, Denmark. Deficiency was detected under TPM in populations from south Italy and Denmark. SMM provided evidence of bottleneck events in Spain, Austria, Bulgaria, and in the north central Europe group (Table 4). The observed M-ratio values was lower than the commonly used bottleneck threshold (0.68; Garza and Williamson 2001) ranging from 0.43 (Czech Republic) to 0.59 (north Italy). All the populations, except for central Italy, had an upper 95% CI above the threshold, indicating a lack of severe bottleneck events. Central Italy showed M  0.54 and Mc  0.55 (Table 4). When we analyzed the samples subdivided in the four groups, we found that the Iberian group showed a low M-ratio (0.17).

Discussion Genetic variability Results obtained in this study show moderate levels of genetic variation in the European population of little owl despite the fact that the species has experienced a significant decline in population sizes across Europe. The average heterozygosity was similar to those reported in two other European strigiformes: from 0.57 to 0.70 in tawny owl (Brito 2007) and from 0.59 to 0.71 in barn owl Tyto alba (Antoniazza et al. 2010). Comparable values were found also for some Palearctic birds of prey, such as the white-tailed sea eagle Halieetus albicilla (Honnen et al. 2010) and griffon vulture Gyps fulvus (Le Gouar et al. 2008). In our study, the highest heterozygosities were found in populations from Czech Republic, Hungary and north Italy, corresponding to the contact areas of haplogroups described

by Pellegrino et al. (2014). A similar result was also found in tawny owl, where populations sampled close to postglacial contact zones showed the highest values (Brito 2007). The lowest heterozygosity values were observed in little owls from Austria, but here we cannot rule out that sampling may have affected the result as samples from Austria were collected from a single locality. The highest number of alleles was found in central and north Italy, corresponding to areas in which Italian, Iberian and Balkan haplogroups are present (Pellegrino et al. 2014). Refugial populations should have a higher genetic diversity than populations established after the most recent glacial cycle (Hewitt 2000). However, as in tawny owl (Brito 2007), we did not find a pattern of decreasing genetic diversity with latitude. This could be related to a mixture of genomes in northern areas, possibly due to a secondary contact between populations originating from different southern refugia (Hewitt 2001). Genetic structure Our data revealed the existence of a genetic structure, although a different number of genetic groups was retrieved when different statistical approaches were applied. DAPC identified five clusters while STRUCTURE only identified three. These retrieving are not necessary in contradiction because the two genetic approaches estimate the genetic structure at different levels: STRUCTURE identifies the highest-level of the genetic structure, while DAPC scrutinizes the finest level of genetic structure (Jombart et al. 2010). The identification of five groups in DAPC may be influenced by the presence of an Austrian group. However, this may not be due to a real genetic difference of this population, since samples were collected in the same locality and their allele frequencies could have affected the estimation method. Conversely, the identification of four clusters supported the phylogeographic structure previously found by Pellegrino et al. (2014). At K  4 populations were divided 469

in four main geographical groups: 1) the NW Europe cluster, ranging from Portugal to Austria; 2) the Italian cluster, comprising continental Italy and Switzerland; 3) the Sardinian cluster; and 4) the Balkan cluster, ranging from Cyprus to Czech Republic. These four clusters included Sardinia and the Iberian, Italian, and Balkan refugia. Several studies on the phylogeography of European species have described the same three major glacial refugia in plants (Médail and Diadema 2009, Tzedakis et al. 2013) and animal species (Joger et al. 2007, Lehtonen et al. 2009). In this study, the postglacial colonization of central Europe originated both from Iberian Peninsula and Balkans, although a main contribution of western Europe was detected. This pattern was exemplified by Taberlet et al. (1998) on the brown bear Ursus arctos, and similar patterns was found in other vertebrate (Hewitt 1999, Ruedi and Castella 2003, Michaux et al. 2004) and invertebrate species (Habel et al. 2005, 2009). In Strigiformes, a study on tawny owl highlighted the same three major refugia (Balkans, south Italy and Iberian Peninsula) but, unlike little owl, the postglacial colonization of north Europe originated from Balkan areas (Brito 2005, 2007). Postglacial expansion patterns may have been influenced by elevation and relief, palaeoecological conditions after the last glacial maximum, and different habitat preferences (Schmitt 2007). Indeed, the little owl breeds in open areas while tawny owl prefers wooden areas (Cramp 1985, Šálek and Lövy 2012). However, proof that the postglacial expansion of the two owls mirrored the expansion of forest and open areas is still lacking. The Pyrenees, Alps and Scandinavian mountains often acted as barriers or suture zones in Europe (Hewitt 2000). Our data suggest that the Alps represented the main obstacle to the expansion of little owl. This barrier probably prevented the diffusion of Italian genomes out of the Peninsula and strongly limited the penetration of NW European genotypes from the west. The genetic flow between Italy and Dalmatia seems currently hampered by the Julian and Dinaric Alps, but gene flow could have occurred more easily along the Adriatic coast during the recent glacial maximum, when the Adriatic sea receded several hundred kilometres southwards (Zonneveld 1996, Taberlet et al. 1998). The current geographical analysis of microsatellite data agrees with previous findings based on mtDNA (Pellegrino et al. 2014), the two markers showing a concordant geographical pattern. Admixed and contact zones Postglacial expansion from refugia can lead populations that diverged in distant geographical areas to meet and merge. The encounter can generate a genetic admixture that can be detected in contact zones (Hewitt 2001, 2011). In little owl, we found several hybrid individuals in Hungary, northcentral Italy, and some coastal Mediterranean localities. In particular, Hungarian samples showed mixed NW Europe and Balkan genotypes and occupied an intermediate position between these two main groups in the multivariate analysis plot. Mitochondrial DNA confirmed the pattern of admixture that was found by microsatellite analysis. Future sampling of neighbouring areas would be useful to shed light on the extent of the contact zone between NW European and Balkan genomes, and to test whether the expansion of 470

NW European genomes towards the Balkan Peninsula and vice versa could be hampered by ecological selection pressures such as habitat differences (Hewitt 2001, Dorken and Pannell 2007, Antoniazza et al. 2010). In Italy, nuclear and mitochondrial DNA described different genetic compositions. Particularly, in northern and central Italy 56% of the individuals assigned by nuclear DNA to the Italian cluster showed Balkan mtDNA. This discrepancy could be due to differential movements in cold and warm ages. Colder periods probably contributed to the expansion of Balkan individuals into northern and central Italy, while warmer ages contributed to a northward expansion from southern Italy. As suggested by various authors (Barton 1993, Chan and Levin 2005), asymmetrical mating could have produced an asymmetrical mtDNA introgression. A similar discordance between mtDNA and nuclear data was found in tawny owl in northern Italy by Brito (2007), and in hares Lepus sp. in Spain by Melo-Ferreira et al. (2009). The contact zone between Italian and Balkan genomes may be wider than we report here, and perhaps extends through Slovenia and Croatia. More detailed and focused samples collected across Adriatic areas are needed for characterizing the genetic structure in this contact area. Considering other European species a similar contact zone located in north Italy was found in the pine marten Martes martes (Ruiz-González et al. 2013), while in the dipper Cinclus cinclus a contact zone ranging from Luxemburg to Hungary was detected (Hourlay et al. 2008). A focused sampling on German populations of little owl may reveal a similar pattern also for our study species. In other European Strigiformes, clear-cut hybrid zones were absent because genetic structure was lacking (Marthinsen et al. 2009, Broggi et al. 2013, Hausknecht et al. 2014). In tawny owls different pathways resulted in different contact zones, and maximum admixture was found on the Iberian Peninsula (Brito 2007). Sardinian genotypes were clearly associated with a single cluster, suggesting an isolation process that prevented gene flow with the continent. However, traces of Sardinian and Italian genotypes were found in some distant Mediterranean areas (Fig. 3). There are several non-exclusive explanations for the clustering of these individuals in the Sardinian genetic group. Sardinian genotypes could have originated from a Mediterranean population located in an area that was not sampled in this study. An alternative explanation involves ancient human translocations. It is well known that several species inhabiting Sardinia were introduced to the island during historical times (Vigne 1992, Scandura et al. 2009). Little owl could have been introduced by hunters: the species was traditionally employed as live decoy to catch small birds in Italy since Roman times (Bianchi Bandinelli 1970). Alternatively, ancient human-mediated translocation could have occurred because little owl was considered a symbol of protection and victory in Athens and Roman myths (Van Nieuwenhuyse et al. 2008). Diodorus reported that in 301 BC. Agathocles released many little owls to galvanize his troops before defeating the Carthaginians (Tillyard 1908). Finally, the presence of Sardinian genotypes in other Mediterranean areas could be related to occasional longdistance movements that could have contributed to shared genetic pools.

Bottleneck events and gene flow The population bottleneck analysis revealed a deficiency of heterozygosity in 7 populations out of 15 under the IAM (France, Denmark, Hungary, Macedonia, north, central and south Italy, no Sardinia). The TPM detected deficiency in 2 populations only (S-Italy and Denmark) and SMM revealed evidence of bottlenecks in Spain, Austria, and Bulgaria. Generally we did not find evidence of bottlenecks in populations that are currently decreasing in size or that encountered a severe reduction in last few decades (i.e. Czech Republic, Šálek and Schröpfer 2008, Šálek 2014; Netherlands, Gouar et al. 2011; Switzerland, Juillard 1989; Poland, Żmihorski et al. 2009). In Denmark, where the little owl is also facing a strong decline (Thorup et al. 2013), a recent study did not reveal evidence of bottlenecks under TPM while IAM showed evidence of bottlenecks (Pertoldi et al. 2012). The discrepancy between models could be related to the different ability of the mutation models to detect bottleneck events. Empirical data suggest that the SMM is the most appropriate model for microsatellite loci with 3- to 5-bp repeats, while IAM is more suitable for shorter repeats (Cornuet and Luikart 1996). Despite the evidence for recent bottlenecks found by BOTTLENECK analyses, no population size reduction events were detected, using M-ratio tests, with the exception of the owl population in central Italy. These tests provided evidence of population decline over different time scales. M-ratio may not detect recent population size reductions because populations recently in decline will not have had time to recover from the genetic signatures associated with bottleneck detection methods (Garza and Williamson 2001). The Mantel test on geographic and genetic distances yielded a significant correlation, indicating a relationship between geographic and genetic distances. This finding is in line with the typical pattern of isolation by distance, where individuals that are geographically close tend to be genetically more similar than individuals that are far apart (Meirmans 2012). Bayesian analysis on migration rates showed high nonmigration rates. This is expected in a sedentary species like the little owl (Cramp 1985, Van Nieuwenhuyse et al. 2008, Abadi et al. 2010, Newton 2010). Gene flow may be related to accidental movements, juvenile dispersal or unknown migratory movements as suggested by Holroyd and Trefry (2011). However some authors demonstrated that this species tends to make only short distance dispersal (Schaub et al. 2006, Sunde et al. 2009). Italian areas showed low dispersal rates and the flows were limited to populations within the Italian Peninsula. There was no recent emigration from Italy and Sardinia toward other European regions. FST values showed that most populations differ from each other, while we detected no significant FST values between neighbouring populations (i.e. Bulgaria-Macedonia and Hungary-Austria). This high differentiation supports a strong phylogeographic structure and a gene flow limited to neighbouring areas only. Our results also confirm that the maximum dispersal distances of the little owl do not exceed a few hundred kilometres, as suggested from bird ringing data (Spina and Volponi 2008, Van Nieuwenhuyse et al. 2008, Holroyd and Trefry 2011). Our result is likely linked to the short distance dispersal for this species. A similar pattern was

found in another European sedentary species like the rock ptarmigan Lagopus lagopus (Bech et al. 2009). Systematic evaluations Our data on microsatellites and a previous study on mtDNA (Pellegrino et al. 2014) clearly identified four separate European genetic groups of little owl. These findings can be compared to the subspecific distribution proposed by different ornithologists (Vaurie 1960, Cramp 1985, del Hoyo et al. 1999) for European subspecies: A. n. noctua in Italy and central Europe; A. n. vidalii in western and NW Europe, and A. n. indigena in the Balkan regions, south Russia, Caucasus, south-west Siberia, Turkey and Middle East. Genetic data were thus somewhat at odds with morphology-based subspecies taxonomy and phylogeographic distribution. In north west and central Europe we detected no trace of south Italian genomes, and we found a contact zone between three main genetic groups in northern Italy that was not described in the literature. Indeed, little owl subspecies are difficult to distinguish using classic plumage and biometric criteria because geographical variation is small and there is a clear effect of habitat on plumage colour (Cramp 1985). Available data on vocal features are of little help for subspecies identification: this species is difficult to study due to a high variety of vocalizations (22 different calls, Exo and Scherzinger 1989). Although differences in calls and songs between certain populations have been documented (Exo 1990, Hardouin et al. 2006), a complete picture of the vocal characteristics of the various potential subspecies is still lacking. More studies on plumage, biometric, and vocal characteristics are needed to establish clear and reliable criteria for subspecific identification. The subspecies A. n. sarda was described for Sardinia, but the validity is debated (del Hoyo et al. 1999, König et al. 2008). Our results do not disprove the validity of this subspecies. To confirm the taxonomic status it would be worth broadening the genetic analyses to include a larger number of Sardinian samples and individuals from Corsica, where the species has begun to breed recently (Yeatman-Berthelot and Jarry 1995). Future studies should investigate genetic differentiation in a wider area embracing the entire distributional range of the species with particular attention to Mediterranean north Africa in order to complete the knowledge of genetic diversity, especially in not yet sampled declining populations. This is an important step for effective management efforts and species conservation. Conclusions Our findings showed a strong genetic structure and no evidence of genetic depletion in European little owl populations, although in several countries the species is currently declining. The genetic data presented here will be useful for restocking programs of endangered populations: stable populations, as those in Italy, Portugal, Greece or Romania could in the future be a source of individuals. Genetic characterization provides useful information in order to identify populations that are genetically suitable to prevent negative genetic consequences in endangered populations and in species management (Crandall et al. 2000). The strong genetic structure and diversity of European little owls suggest that 471

their management units should encompass areas of limited extension, and prospective restocking programs should be set up from nearby stable populations. Many reintroduction programs are based on birds bred in captivity and it is important that these birds are of local origin. Acknowledgements – We thank curators and directors of the following Museums, Collections and Wildlife Recovery Centres (CRFS): R. Toffoli, E. Gavetti (MRSN Torino, Italy); G. La Gioia (MSN Salento, Calimera, Italy); G. Vaschetti (CRFS Racconigi, Italy); A. Damiano (CRFS LIPU Molise, Italy); U. Chalvien (MCSN Pordenone, Italy); C. Carbonero (CRFS Valenza, Italy); A. De Faveri, N. Baccetti (ISPRA Ozzano, Italy); M. Sarà (Mus. Univ. Palermo, Italy); G. Chiozzi (MSN Milano, Italy); G. Tozzi (CSN Prato, Italy); P. Pedrini, M. C. Deflorian (MTSN Trento, Italy); S. Mazzotti (MCSN Ferrara, Italy); V. Burresi (CRFS LIPU Magenta, Italy); E. Borgo (MCSN Genova, Italy); G. Delitala (Univ. Sassari, Italy); C. Vallarini (WWF Rovigo, Italy); C. Manicastri, C. Marangoni (MCZ Roma, Italy); F. Silvano (MSN Stazzano, Italy); M. Aliabadian (ZMA Amsterdam, Netherlands); Stavros Kalpakis (EKPAZ Aegina, Greece); M. Ganoti (ANIMA Athens, Greece); P. Lymberakis (NHM Crete, Greece); P. Sweet (AMNH NY, USA); I. Rey Fraile (MNCN Madrid, Spain); J. M. Pons, E. Pasquet (MNHN Paris, France); Z. Boev (NMNHS Sofia, Bulgaria); O. Hameau (CRFS LPO Hyeres, France); J. Fjeldså (SNM Copenaghen, Denmark); E. Garcia Franquesa (MCN Ciutadella, Barcelona, Spain); E. Obón, J. Mayné (CRFS Torreferrussa, Spain); J. P. Granadeiro (MNHN Lisboa, Portugal); Y. Yom Tov (Univ. Tel Aviv, Israel); H. Frey, R. Faust (EGS Haringsee, Austria); R. Tomè (STRIX, Portugal); P. Cardia (CIBIO, Vairão, Portugal); C. Blaize (Ass. CHENE, Allouville Bellefosse, France); J. Plass (Biologiezentrum Linz, Austria); J. H. Reichholf (ZSM Munich, Genrmany). We also thank R. Balestrieri, A. Corso, D. De Rosa, M. Della Toffola, N. Di Lucia, A. Galietti, M. Grussu, B. Guasco, R. Ientile, D. Lobue, P. Meneguz, D. Pellegrino, D. Pisu, R. Rua, S. Sava, A. Volpe (Italy), P. Lecomte, M. Penpeny (France), D. Portolou (Greece), J. Ročnová (Czech Republic) and R. Lardelli (Switzerland) for generously providing samples. Thanks also are extended to O. Janni for English revision of the manuscript. This study was supported by ATF Alessandria, MURST grants, the research aim of the Academy of Sciences of the Czech Republic (RVO 68081766) and by a grant from the Grant Agency of the Univ. of South Bohemia 168/2013/P. CP was supported by a grant from Danish Natural Science Research Council (grant numbers: 11-103926, 09-065999, 95095995), the Carlsberg Foundation (grant number 2011-01-0059) and the Aalborg Zoo Conservation Foundation (AZCF). TNP was supported via a Sapere aude grant from the Danish Natural Science Research Council (grant number: DFF – 4002-00036).

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Supplementary material (Appendix JAV-00679 at www.avianbiology.org/readers/appendix ). Appendix 1–4.

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Supplementary material

JAV-00679 Pellegrino, I., Negro, A., Boano, G., Cucco, M., Kristensen, T. N., Pertoldi, C., Randi, E., Šálek, M. and Mucci, N. 2015. Evidence for strong genetic structure in European populations of the little owl Athene noctua. – J. Avian Biol. doi: 10.1111/jav.00679

Appendix 1 List of sampled individuals used in this study. Samples are sorted by populations. Appendix 2 Microsatellites loci used in the present study including primer sequence, allele size inbp, source and species for which loci were isolated. Appendix 3 Pairwise values of FST (microsatellites) among populations of little owl Athene noctua. Values marked with asterisk are significant (p < 0.05 ). Appendix 4 Estimated number of populations (K) from the software Structure for the European little owl. (a) Rate of change in log-likelihood values (ΔK) (Evanno et al. 2005). The maximum ΔK indicates the most likely number of populations. (b) The mean ln P(D) (Pritchard et al. 2000) of 5 runs conducted for each K for the multilocus genotype data generated. A plateau in likelihood values indicates the most likely number of populations. (c) Inference of the number of genetic clusters by discriminant analysis of principal components (DAPC). "

APPENDIX((1 Institution(abbreviations ANIMA M.,Šálek, Ass.CHENE BZL CRASOACCAR CRFSOLIPUOMI CRFSOLIPUOMO CRFSOPO CRFST CRSFSOLPOOPACA CSN EGS ISPRA MCCI MCN MCSNF MCSNP MNCN MNHN MSNG MTSN MUHNAC MZD NHMC NHMD NMNHS OFP STRIXOCIBIO WWFORO

Association,for,the,Protection,and,Welfare,of,Wildlife,,Greece,,(M.,Ganoti), Institute,of,Vertebrate,Biology,,Academy,of,Sciences,of,the,Czech,Republic,(M.,Šálek) Association,CHENE,,France,(C.,Blaize) Biologiezentrum,Linz,,Austria,(J.,Plass) Associazione,Centro,Cicogne,e,Anatidi,di,Racconigi,,Italy,(G.,Vaschetti) ,CRFS,Lipu,La,Fagiana,,Pontevecchio,di,Magenta,,Italy,(V.,Burresi) CRFS,LIPU,Molise,,Italy,(A.,Damiano) CRFS,Parco,Fluviale,del,Po,e,del,Torrente,Orba,,Italy,(C.,Carbonero) Centre,de,Recuperació,de,Fauna,Salvatge,de,Torreferrussa,,Spain,(J.,C.,FernándezOOrdóñez,,E.,Obón,,J.,Mayné) Centre,Regional,du,sauvegarde,de,la,faune,sauvage,(Olivier,Hameau) Centro,di,Scienze,Naturali,,,Prato,,Italy,(G.,Tozzi) EGS,,Eulen,und,Greifvogel,Schutz,Oesterreich,(H.,Frey,,R.,Faust) Istituto,Superiore,per,la,Protezione,e,la,Ricerca,Ambientale,,Italy,(A.,De,Faveri) Museo,civico,di,Storia,Naturale,di,Carmagnola,,Italy,(G.,Boano) Franquesa,Museo,de,Ciencias,Naturales,,de,la,Ciutadella,,Barcelona,,Spain,(E.,Garcia) Museo,Civico,di,Storia,Naturale,di,Ferrara,,Italy,(S.,Mazzotti) Museo,Civico,di,Storia,Naturale,,Pordenone,,Italy,(U.,Chalvien) Museo,Nacional,de,Ciencias,Naturales,,Madrid,,Spain,(I.,Rey,Fraile) Muséum,national,d'Histoire,naturelle,Paris,,France,(J.,M.,Pons,,Eric,Pasquet) Museo,Civico,di,Storia,Naturale,di,Genova,,Italy,(E.,Borgo) Museo,Tridentino,di,Scienze,Naturali,,Italy,(P.,Pedrini,,M.,C.,Deflorian) Museu,Nacional,de,História,Natural,,Lisboa,(J.,P.,Granadeiro) Museo,di,Zoologia,P.,Doderlein,,Università,di,Palermo,,Italy,(M.,Sarà) Natural,History,Museum,of,Crete,,Greece,(P.,Lymberakis) Natural,History,Museum,Of,Denmark,,Copenhagen,,Denmark,(J.,Fjeldså) Bulgarian,Academy,Of,Sciences,National,Museum,of,Natural,History,Sofia,,Bulgaria,(Z.,Boev) Osservatorio,Faunistico,Provinciale,di,Lecce,,,Museo,di,Calimera,,Italy,(G.,La,Gioia) STRIX,Ambiente,e,Inovação,(R.,Tomè),,O,Centro,de,Investigação,em,Biodiversidade,e,Recursos,Genéticos,,Spain,(P.,Cardia,CIBIO) WWF,Rovigo,,Italy,(C.,Vallarini)

Alb280 Alb281 Alb282 Alb283 Alb284 Alb285 Alb286 Aus348 Aus349 Aus350 Aus351 Aus352 Aus353 Aus354 Aus355 Aus356 Aus357 Aus358 Aus359 Aus447 Aus449 Aus451 Aus457 Bul287 Bul288 Bul291 Bul302 Bul338 Bul339 Bul436 Bul437 Bul438 Bul439 Bul440 Bul441 Bul442 Bul443 Cyp459 Cyp460 Cyp106 Cyp278 Cyp279

Locality Albania,(cost(area,(Shkoder Albania,(cost(area,(Mifol Albania,(cost(area,(Xarre Albania,(cost(area,(Sarande Albania,(cost(area,(Sarande Albania,(cost(area,(Sarande Albania,(cost(area,(Sarande Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Vienna,(NorthAEast(Austria Austria,(Naarn(im(Machlande,((Holzleiten(13 Austria,(Weidenholz,((nordwestlich(Waizenkirchen Austria,(Waizenkirchen Austria Bulgaria,(Central(Bulgaria,(Čargan Bulgaria,(Central(Bulgaria,(Elenovo Bulgaria,(Central(Bulgaria,(Goljan(manastil Bulgaria,(Central(Bulgaria,(Konevo Bulgaria,(Central(Bulgaria,(Ognen Bulgaria,(Central(Bulgaria,(Iskra Bulgaria,(Central(Bulgaria,(Goljan(manastil,( Bulgaria,(Central(Bulgaria,(Ognen,(north(end(of(village Bulgaria,(Central(Bulgaria,(Ognen,(east(end(of(village Bulgaria,(Central(Bulgaria,(Goljan(manastil Bulgaria,(Central(Bulgaria,(Mežda Bulgaria,(Central(Bulgaria,(Goljan(manastil Bulgaria,(Central(Bulgaria,(Nedjalsko,(found(dead Bulgaria,(Central(Bulgaria,(Konevo Cypro,(greek(part,(Politico Cypro,(greek(part,(Mammari Cyprus,(Cyprus,(Petra(Romiou Cyprus,(greek(part,(Astromeritis,(

Appendix S1

Source

Museum5Specimen5or5Original5ID

M. Šálek

122

M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek

123 124 125 126 127 128 EO2534 HF49437 EO2530 WAAEO2435 HF3455 HF49450 HF3454 HF3456 HF3988 HF41267 EO2383 HF39882 2006/349 2002/379 1992/66 2004/381 56 58 62 70 69 73 65 66 67 64 61 63 92 71 179 180

(EGS (EGS (EGS (EGS (EGS (EGS (EGS (EGS (EGS (EGS (EGS (EGS BZL BZL BZL BZL

M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek

NHMC M. Šálek

177

Alb280 CzR204 CzR206 CzR207 CzR208 CzR229 CzR230 CzR231 CzR232 CzR233 CzR234 CzR235 Denm210 Denm211 Denm212 Denm213 Denm214 Denm215 Denm216 FrN124 FrN125 FrN126 FrN127 FrN385 FrN386 FrN387 FrN388 FrN389 FrN390 FrN90 FrS199 FrS200 FrS201 FrS89 FrS91 Gre103 Gre104 Gre116 Gre117 Gre118 Gre119 Gre120

Locality Cyprus,(greek(part,(Agios(loannis Czech(Rep.,(Susany,(Susany Czech(Rep.,(Upohlavy,(Upohlavy Czech(Rep.,(Cerniv,(Cerniv Czech(Rep.,(Moraveves,(Moraveves Czech(Rep.,(Moraveves,(Moraveves Czech(Rep.,(Moraveves,(Moraveves Czech(Rep.,(Moraveves,(Moraveves Czech(Rep.,(Moraveves,(Moraveves Czech(Rep.,(Moraveves,(Moraveves Czech(Rep.,(Moraveves,(Moraveves Czech(Rep.,(Moraveves,(Moraveves Denmark,(Rødhøjvej,((Nørager Denmark,(Farsø Denmark,(Farsø Denmark,(Løgstør Denmark,(Farsø Denmark,(Flamsted Denmark,(Års,((Jylland France,(ÎleAdeAFrance,(Paris,(Paris France,(ÎleAdeAFrance,(Paris,(Paris France,(ÎleAdeAFrance,(Paris,(Paris France,(ÎleAdeAFrance,(Paris,(Paris France,(Normandia,(Hattenville((76) France,(Normandia,(Touffreville(la(Corbeline((76) France,(Normandia,(Normanville((76) France,(Normandia,(Offranville((76) France,(Normandia,(Haute(Normandie France,(Normandia,(Hattenville((76) France,(Vosges,(Vosges France,(06(Alpes(Maritimes((Region(Provence(Alpes(Cote(d'Azur) France,(06(Alpes(Maritimes((Region(Prtovence(Alpes(Cote(d'Azur) France,(84(Vaucluse(((Region(Provence(Alpes(Cote(d'Azur) France,(Drome,(Drome France,(Drome,(Drome Greece,(South(central(Greece,(Perama Greece,(Thrace,(Dadia(forest(reserve Greece,(Pieria,(Veria Greece,(Pieria,(Veria Greece,(Pieria,(Veria Greece,(Dodecaneso,(Rhodes

Appendix S1

Source

Museum5Specimen5or5Original5ID

M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek

178

(NHMD (NHMD (NHMD (NHMD (NHMD (NHMD (NHMD P.(Lecomte(&(M.(Penpeny P.(Lecomte(&(M.(Penpeny P.(Lecomte(&(M.(Penpeny P.(Lecomte(&(M.(Penpeny Ass.CHENE Ass.CHENE Ass.CHENE Ass.CHENE Ass.CHENE Ass.CHENE

MNHN CRSFS-LPO-PACA CRSFS-LPO-PACA CRSFS-LPO-PACA

MNHN MNHN NHMC NHMC ANIMA ANIMA ANIMA ANIMA

5 2 7 8 1 12 6 141346 141350 142117 141831 142121 142119 142120 FR1 FR2 FR3 FR4 62r2009 79r2009 57r2009 48r2009 xr2009 59r2009 MNHN,(((V7 AE633174 AE633175 AE633176 MNHN,((d19 MNHN,((D8

Alb280 Gre121 Gre122 Gre123 Gre316 Gre318 Gre319 Gre419 Gre420 Gre421 Gre422 Gre423 Gre424 Gre425 Hung268 Hung269 Hung270 Hung271 Hung272 Hung273 Hung274 Hung275 Hung276 Hung326 Hung327 Hung328 Hung329 Hung330 Hung331 Hung332 Hung360 Hung361 Hung362 ItC107 ItC108 ItC109 ItC147 ItC149 ItC150 ItC152 ItC155 ItC157

Locality

Appendix S1 Greece,(Dodecaneso,(Rhodes Greece,(Dodecaneso,(Rhodes Greece,(Attica,(Markopoulo Greece,(Attica,(Markopoulo Greece,(north(Greece,(Kato(Apostoli Greece,(north(Greece,(Fillaria Greece,(north(Greece,(Laka Greece,(north(Greece,(Fillaria Greece,(north(Greece,(Fillaria Greece,(north(Greece,(Laka Greece,(north(Greece,(Laka Greece,(north(Greece,(farm(3km(from(Laka Greece,(north(Greece,(farm(3km(from(Laka Greece,(north(Greece,(Audrion Hungary,(National(park(Hortobagy,(Szásztek Hungary,(National(park(Hortobagy,(Tiszafured Hungary,(National(park(Hortobagy,(Ohat Hungary,(National(park(Hortobagy,(Mezokovesd Hungary,(National(park(Hortobagy,(Tizababolna Hungary,(National(park(Hortobagy,(Ohat(raliway(station((5(km(from(Ohat(village),( Hungary,(National(park(Hortobagy,(Hortobagy Hungary,(National(park(Hortobagy,(Debrecen Hungary,(National(park(Hortobagy,(Debrecen Hungary,(National(park(Hortobagy,(Hortobagy Hungary,(National(park(Hortobagy,(Hortobagy Hungary,(National(park(Hortobagy,(Hortobagy Hungary,(National(park(Hortobagy,(Debrecen Hungary,(National(park(Hortobagy,(Debrecen Hungary,(National(park(Hortobagy Hungary,(National(park(Hortobagy,(Mezokovesd Hungary,(National(park(Hortobagy,(Cucuvea,(Station(for(the(handicap(birds(Hortobagy Hungary,(National(park(Hortobagy,(Mezokovesd Hungary,(National(park(Hortobagy,(Ohyo,(farm(2(km(from(Ohyo Italy,(Emilia(Romagna,(Ferrara Italy,(Emilia(Romagna,(Ferrara Italy,(Emilia(Romagna,(Ferrara Italy,(Lazio,(Roma,(Roma Italy,(Marche,(Fermo,(Fermo Italy,(Marche,(Pesaro(Urbino,(Pesaro Italy,(Marche,(Pesaro(Urbino,(Pesaro Italy,(Marche,(Pesaro(Urbino,(Pesaro

Source

Museum5Specimen5or5Original5ID

ANIMA ANIMA ANIMA ANIMA M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek

151 160 165 161 162 166 167 169 171 173 1 2 3 4 8 9 10 14 15 12 11 13 16 17 20 6 19 7 26

MCSNF MCSNF MCSNF ISPRA ISPRA ISPRA ISPRA ISPRA

7661 5704 5794 9490 7414

Alb280 ItC19 ItC20 ItC22 ItC246 ItC252 ItC257 ItC29 ItC30 ItC31 ItC32 ItC33 ItC34 ItC461 ItC462 ItC463 ItC466 ItC467 ItC468 ItC469 ItC58 ItC59 ItC95 ItC96 ItC97 ItN10 ItN100 ItN101 ItN102 ItN11 ItN12 ItN136 ItN137 ItN138 ItN139 ItN140 ItN146 ItN154 ItN16 ItN162 ItN164 ItN165

Locality Italy,(Marche,(Pesaro(Urbino,(Pesaro Italy,(Toscana,(Prato,(Prato Italy,(Toscana,(Prato,(Prato Italy,(Toscana,(Firenze,(Signa Italy,(Lazio,(Latina,(Fondi Italy,(Lazio,(Roma,(Albano(Laziale Italy,(Emilia(Romagna,(ForlìACesena,(Igea(Marina(ABellaria Italy,(Toscana,(Pistoia,(Pistoia Italy,(Toscana,(Pistoia,(Pistoia Italy,(Toscana,(Pistoia,(Quarrata Italy,(Toscana,(Firenze,(Calenzano Italy,(Toscana,(Firenze,(Campi(Bisenzio( Italy,(Toscana,(Firenze,(Signa( Italy,(Toscana,(Pistoia(,(Agliana Italy,(Toscana,(Pistoia(,(Pistoia Italy,(Toscana,(Pistoia(,(Chiesina(Montalese Italy,(Toscana,(Pistoia(,(Quarrata Italy,(Toscana,(Prato,(Montemurlo Italy,(Toscana,(Pistoia(,(Pontelungo Italy,(Emilia(Romagna,(Val(Trebbia,( Italy,(Lazio,(Frosinone,(Sora Italy,(Lazio,(Latina,(Latina Italy,(Emilia(Romagna,(Ferrara,(Rossonia Italy,(Emilia(Romagna,(Ferrara,(Ostellato Italy,(Emilia(Romagna,(Ferrara,(Ro Italy,(Piemonte,(Alessandria,(Predosa( Italy,(Friuli(Venezia(Giulia,(Pordenone,(Corva Italy,(Friuli(Venezia(Giulia,(Pordenone,(Villotta(Chions Italy,(Friuli(Venezia(Giulia,(Pordenone,(Oecenico(di(Zoppola Italy,(Piemonte,(Cuneo,(Cuneo Italy,(Piemonte,(Torino,(Cavour Italy,(Trentino(Alto(Adige,(Trento,(Riva(del(Garda( Italy,(Trentino(Alto(Adige,(Trento,(Borgo(Val(Sugana Italy,(Friuli(Venezia(Giulia Italy,(Friuli(Venezia(Giulia Italy,(Friuli(Venezia(Giulia Italy,(Liguria,(La(Spezia,(La(Spezia Italy,(Liguria,(Savona,(Savona Italy,(Piemonte,(Alessandria,(Spineto(Alessandria) Italy,(Lombardia,(Milano,(Limbiate Italy,(Lombardia,(Pavia,(Pavia

Appendix S1

Source

Museum5Specimen5or5Original5ID

ISPRA CSN CSN CSN A.(Galietti A.(Corso S.(Sava CSN CSN CSN CSN CSN CSN CSN CSN CSN CSN CSN CSN MSNG MZD MZD MCSNP MCSNP MCSNP MCCI MCSNP MCSNP MCSNP MCCI MCCI MTSN MTSN MTSN MTSN MTSN ISPRA ISPRA MCCI CRFSALIPUAMI CRFSALIPUAMI

9486 1875 1959 2057 TH9164

1447 1411 1209 1829 1524 1333 1386/06 1811/06 1740/06 1223/06 1108/06 1917/06 MSNG(47105

MCCI(197

MCCI(635 MCCI(1821 187/208 206/208

7419 8589 MCCI(185 344 689

Alb280 ItN166 ItN167 ItN168 ItN169 ItN170 ItN184 ItN185 ItN187 ItN247 ItN256 ItN321 ItN39 ItN40 ItN41 ItN42 ItN43 ItN471 ItN473 ItN475 ItN476 ItN477 ItN478 ItN482 ItN76 ItN8 ItN80 ItN81 ItN82 ItN83 ItN85 ItN86 ItN88 ItN9 ItN98 ItN99 ItS110 ItS148 ItS203 ItS236 ItS24 ItS248

Locality Italy,(Liguria,(Savona,(Capo(Noli Italy,(Liguria,(Imola,(Porto(Maurizio Italy,(Liguria,(Genova,(Voltri,((loc.(Brusinetti Italy,(Liguria,(Genova,(Sestri(Levante Italy,(Liguria,(Imola,(Sanremo Italy,(Liguria,(Savona,(Savona Italy,(Piemonte,(Cuneo,(Peveragno Italy,(Piemonte,(Asti,(Valle(Rej Italy,(Piemonte,(Torino,(Carmagnola Italy,(Friuli(Venezia(Giulia,(Gorizia,(Staranzano(/Isola(della(Cona Italy,(Veneto,(Rovigo,(Badia(Polesine Italy,(Veneto,(Rovigo,(Badia(Polesine Italy,(Piemonte,(Asti,(Nizza(Monferrato Italy,(Piemonte,(Asti,(VaglieranoAValle(Rej Italy,(Piemonte,(Asti,(Tigliole Italy,(Piemonte,(Asti,(Lipu(Asti Italy,(Piemonte,(Cuneo,(Cavallermaggiore Italy,(Liguria,(Imperia Italy,(Liguria,(Genova,(Borgoratti Italy,(Lombardia,(Milano,(Pantigliate Italy,(Lombardia,(Milano,(Cuggiono Italy,(Lombardia,(Pavia,(Rivanazzano Italy,(Lombardia,(Milano,(Assago Italy,(Lombardia,(Pavia,(Frascarolo Italy,(Lombardia,(Pavia,(Sannazzaro(de(Burgondi Italy,(Piemonte,(Cuneo,(Savigliano( Italy,(Lombardia,(Pavia,(Bressana(Bottarone Italy,(Lombardia,(Pavia,(Mondondone Italy,(Lombardia,(Pavia,(Stradella Italy,(Lombardia,(Pavia,(Frascarolo Italy,(Sardegna,(Oristano,(Oristano Italy,(Toscana,(Lucca,(Lucca Italy,(Piemonte,(Cuneo,(Alba Italy,(Piemonte,(Alessandria,(San(Giorgio(Monferrato Italy,(Friuli(Venezia(Giulia,(Pordenone,(Vigonovo(Fontanafredda Italy,(Friuli(Venezia(Giulia,(Pordenone,(Rauscedo Italy,(Sicilia,(Siracusa Italy,(Sicilia,(Palermo,(Palermo Italy,(Sicilia,(RiberaACattolica(Eraclea Italy,(Sicilia,(ForlìACesena,(RiberaACattolica(Eraclea Italy,(Puglia,(Lecce,(Calimera(

Appendix S1

Source

Museum5Specimen5or5Original5ID

MSNG MSNG MSNG MSNG MSNG MSNG MCCI MCCI MCCI S.(Sava WWFARO WWFARO MCCI MCCI MCCI MCCI CRASAACCAR MSNG MSNG CRFSALIPUAMI CRFSALIPUAMI CRFSALIPUAMI CRFSALIPUAMI CRFSALIPUAMI CRFSAPO MCCI CRFSAPO CRFSAPO CRFSAPO CRFSAPO M.(Grussu D.(Lo(Bue CRASAACCAR MCCI MCSNP MCSNP A.(Corso ISPRA

MSNG(700 MSNG(674 MSNG(650 MSNG(628 MSNG(596 MSNG(439 MCCI(2806 MCCI(2321 MCCI(410

MCCI(2510 MCCI(2479 MCCI(2515 MCCI(2514 T(49069 MSNG(53347 MSNG(33313 277A2008 528A2008 442A2008 548A2008 173 35(07 MCCI(1824

172

Strix(726(Gpso

6831

N.(di(Lucia

N.(di(lucia OFP

402/06

Alb280 ItS249 ItS25 ItS250 ItS251 ItS26 ItS345 ItS346 ItS347 ItS36 ItS37 ItS38 ItS434 ItS435 ItS50 ItS51 ItS56 ItS57 Sard143 Sard209 Sard433 Sard500 Sard501 Sard502 Sard503 Sard504 Sard505 Sard506 Sard92 Mac292 Mac294 Mac295 Mac297 Mac298 Mac299 Mac300 Mac301 Mac341 Mac342 Mac343 Mac344 Mac409

Locality Italy,(Campania,(Avellino,(Conza( Italy,(Campania,(Salerno,(Foria(di(Centola Italy,(Puglia,(Lecce,(Calimera( Italy,(Sicilia,(Agrigento,(Sciacca Italy,(Campania,(Salerno,(Foria(di(Centola Italy,(Puglia,(Lecce,(Calimera( Italy,(Molise Italy,(Campania,(Salerno Italy,(Campania,(Salerno Italy,(Puglia,(Bari,(Bitetto( Italy,(Puglia,(Lecce,(Calimera( Italy,(Puglia,(Lecce,(Calimera( Italy,(Sicilia,(Messina(,(S.(Mauro Italy,(Sicilia,(Messina,(Messina Italy,(Molise,(Campobasso,(Bojano Italy,(Molise,(Campobasso,(S.(Martino(in(Pensilis Italy,(Sicilia,(Agrigento,(Agrigento Italy,(Sicilia,(Palermo,(Mondello Italy,(Sardegna,(Medio(Campidano,(Guspini Italy,(Sardegna Italy,(Sardegna,(Nuoro,(Lanusei Italy,(Sardegna,(Asinara Italy,(Sardegna,(Asinara Italy,(Sardegna,(Asinara Italy,(Sardegna,(Asinara Italy,(Sardegna,(Asinara Italy,(Sardegna,(Asinara Italy,(Sardegna,(Asinara Italy,(Sardegna,(Oristano,(Stagno(di(Santa(Giusta Macedonia,(Central(and(East(part,(Crničani Macedonia,(Central(and(East(part,(Nogaevci Macedonia,(Central(and(East(part,(Tři(češni Macedonia,(Central(and(East(part,(Ulavci Macedonia,(Central(and(East(part,(Krivogaštani Macedonia,(Central(and(East(part,(Gorno(selo Macedonia,(Central(and(East(part,(Dupjačani Macedonia,(Central(and(East(part,(Zabrčani(village Macedonia,(Central(and(East(part,(Crničani,(Dorjan(lake Macedonia,(Central(and(East(part,(Dupjačani Macedonia,(Central(and(East(part,(Dupjačani Macedonia,(Central(and(East(part,(Nebregovo,(Prilep

Appendix S1

Source R.(Balestrieri A.(Galietti OFP N.(di(Lucia,((A.(Volpe A.(Galietti OFP D.(De(Rosa A.(Galietti A.(Galietti OFP OFP OFP MZD MZD CRFSALIPUAMO CRFSALIPUAMO MZD MZD A.(Negri D.(Pellegrino MZD D.(Pisu D.(Pisu D.(Pisu D.(Pisu D.(Pisu D.(Pisu D.(Pisu M.(Grussu M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek

Museum5Specimen5or5Original5ID

439/06

403/06

429/06 406/06 MZD(1878 MZD(1594 MCCI(301 MCCI(804

MZD(1877 T43428 T43426 T43433 T43424 T37580 T43444 T43443 96 104 105 108 113 115 117 120 103 118 119 121

Alb280 Mac93 Por364 Por370 Por371 Por372 Por373 Por375 Por376 Por378 Por380 Por382 Por384 Por491 Por494 Por495 Por496 Por497 Por498 Por499 Rom305 Rom306 Rom307 Rom308 Rom309 Rom310 Rom311 Rom312 Rom313 Rom322 Rom323 Rom324 Rom325 Rom335 Rom336 Rom337 Rom415 Rom416 Rom417 Rom418 SpC68 SpC69

Locality Macedonia,(Central(and(East(part,(Crničani,(Farm(5km(from(village Macedonia,(Central(and(East(part,(Kardifakovo Portogallo Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Portogallo,(Baixo(Alentejo,(S.(Marcos(da(Atabueira/(Cabeça(da(Serra Romania,(Delta(of(river(Danube,(Sarichioi Romania,(Delta(of(river(Danube,(Sarinasuf Romania,(Delta(of(river(Danube,(Zebil Romania,(Delta(of(river(Danube,(Plopul Romania,(Delta(of(river(Danube,(Visina Romania,(Delta(of(river(Danube,(Visina Romania,(Delta(of(river(Danube,(Plopul Romania,(Delta(of(river(Danube,(Victoria Romania,(Delta(of(river(Danube,(Nufaru Romania,(Delta(of(river(Danube,(Sarinasuf Romania,(Delta(of(river(Danube,(Zebil Romania,(Delta(of(river(Danube,(Sarinasuf Romania,(Delta(of(river(Danube,(Malcoci Romania,(Delta(of(river(Danube,(Victoria Romania,(Delta(of(river(Danube,(Bestepe Romania,(Delta(of(river(Danube,(Plopul Romania,(Delta(of(river(Danube,(Sarinasuf,(South(end(of(village Romania,(Delta(of(river(Danube,(Agighiol,(wind(power(station Romania,(Delta(of(river(Danube,(Plopul Romania,(Delta(of(river(Danube,(Hotel(Wels,(5(km(from(Bestepe Spain,(Madrid,(Soto(de(VinuelasAMadrid

Appendix S1

Source

Museum5Specimen5or5Original5ID

M. Šálek M. Šálek MUHNAC STRIX-CIBIO STRIX-CIBIO

99 100 398AAD k005119 k005115

STRIX-CIBIO STRIX-CIBIO STRIX-CIBIO STRIX-CIBIO STRIX-CIBIO STRIX-CIBIO STRIX-CIBIO STRIX-CIBIO

k005112 k005071 K003853 k005069 k003628 k005065 k003695 k003696 Koo3681 Koo3688 Koo5101 Koo3878 Koo3681 Koo5118 Koo3838 31 32 35 43 39 40 44 47 50 33 36 34 53 48 49 46 51 30 45 37 10478

STRIXACIBIO STRIXACIBIO STRIXACIBIO STRIXACIBIO STRIXACIBIO STRIXACIBIO STRIXACIBIO M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek M. Šálek

MNCN

Alb280 SpC70 SpC71 SpC72 SpC73 SpC74 SpC75 SpNE217 SpNE218 SpNE219 SpNE220 SpNE221 SpNE222 SpNE223 SpNE224 SpNE225 SpNE226 SpNE227 SpNE228 SpNE258 SpNE259 SpNE260 SpNE261 SpNE262 SpNE263 SpNE264 SpNE265 SpNE320 Swi188 Swi189 Swi253 Swi254 Swi255

Locality Spain,(Toledo,(Toledo Spain,(Madrid,(Madrid Spain,(Madrid,(Guadalix(de(la(SierraAMadrid Spain,(Madrid,(VillaverdeAMadrid Spain,(Ciudad(Real,(P.N(CabanerosACiudad(Real Spain,(Ciudad(Real,(P.N(CabanerosACiudad(Real Spain,((Caceres,((Cáceres Spain,(Almenar Spain,(Castillonroy Spain,(Orriols Spain,(Roses,( Spain,(Granadella,(( Spain,(Cistella Spain,(Arenys(de(Munt Spain,(Tarragona Spain,(Corçà Spain,(Banyoles Spain,(Torregrossa Spain,(Reus Spain,(Barcellona,(Sabadell Spain,(Barcellona,(Badalona Spain,(Barcellona Spain,(Barcellona,(Sentmenat Spain,(Barcellona,(Santa(Coloma(de(Cervellò Spain,(Barcellona,(Vic Spain,(Barcellona,(Santa(Coloma(de(Cervellò Spain,(Barcelona,( Spain,(Barcelona Svizzera,(Valle(del(Ticino Svizzera,(Valle(del(Ticino Svizzera,(Ticino,(Canton(Ticino Svizzera,(Ticino,(Canton(Ticino Svizzera,(Ticino,(Canton(Ticino

Appendix S1

Source

Museum5Specimen5or5Original5ID

MNCN MNCN MNCN MNCN MNCN MNCN MNCN MCN MCN MCN MCN MCN MCN MCN MCN MCN MCN MCN MCN

10485 10498 10499 10673 10793 10794 17988 95A0961AT 95A0972AT 98A0404AT 98A0405AT 99A0992AT 2000A0569AT 2000A1099AT 2002A0498AT 2007A0438AT 2008A0928AT 99A0994AT 99A0995AT TF/2007/1742 TF/2007/2036 T0081623 TF/2008/1041 TF/2009/3849 TF/2007/1839 TF/2006/3039 TF/2005/3001 TF(093765

CRFST CRFST CRFST CRFST CRFST CRFST CRFST CRFST CRFST

R.(Lardelli( R.(Lardelli R.(Lardelli( R.(Lardelli( R.(Lardelli(

10 9

Appendix(2 !! ! Microsatellites!loci!used!in!the!present!study!including!primer!sequence,!allele!size!in!bp,!source! and!species!for!which!loci!were!isolated.! (

Name

Primer sequences

bp

15A6F

ACCTCAGAAGCAGACAGAACC

21

15A6R

CCTTTGCGATTGCTGTAAC

19

Oe045F

GTATGTTCTACGTTGGATTTCCA

23

Oe045R

AAACCTGGCAAGTGCTGTT

19

Oe085F

TGCACAGAAATGAAGAAGAG

20

Oe085R

GGGTTTCTCAAAACAGGCAGG

21

FEPO43F

CGTGAAGGTAAGAGGAGCTGG

21

FEPO43R

GGAGGGAGCCTGGAAATGG

19

Oe053F

CTCTGCATCTTAACGCACAGGAC

23

Oe053R

CCTCCAAGTGGACAGGAAAAGC

22

Ta-212F

AGGGCTGTGCTTCCACTC

18

EU220187R

TGCCAAAACACCATCACC

18

Ta-216F

CAGGCTTCTTCTGAGGTCC

19

EU220190R

GCATTGTGAAAGGGTTTACTG

21

Atn3F

CACTCAGTTTTCCCCCAAGA

20

GU252347R

AATGGGCACTGGTGAAAGAG

20

Atn4F

AAGTAATAAACTTAGTGCCTGGTTTT 26

GU252348R

CAAAGGCTCTCCTTGGATGT

20

Atn5F

TAGAGCAGCAGTCCCCATTT

20

GU252349R

AGATGGATGGATGGATGGAG

20

Atn7F

GCTCCTAATAGATGAAGCCAAA

22

GU252351R

CGAGTAGATTGGGACTGGTGA

21

Atn9F

TTCTGCTATTCAGGCTGCTG

20

GU252353R

TGGGTCATCATGGAACACTG

20

Atn10F

TCTTCATGACCAAAGGATACCTC

23

GU252354R

GAAATGGAGAAAGGAGCCAAC

21

Reference

Species

Thode et al., 2002

Strix occidentalis lucida

Hsu et al., 2003

Otus elegans

Hsu et al., 2006

Otus elegans

Proudfoot et al., 2005

Glaucidium brasilianum

Hsu et al., 2003

Otus elegans

Burri et al., 2008

Tyto alba

Burri et al., 2008

Tyto alba

Aurelle et al., 2010

Athene noctua

Aurelle et al., 2010

Athene noctua

Aurelle et al., 2010

Athene noctua

Aurelle et al., 2010

Athene noctua

Aurelle et al., 2010

Athene noctua

Aurelle et al., 2010

Athene noctua

! Appendix(3. !Pairwise!values!of!FST!(microsatellites)!among!populations!of!little!owl!Athene&noctua.!!Values!marked!with!asterisk!!are!significant!(P