THE GENETIC IMPACT OF CHAMOIS MANAGEMENT IN THE DINARIDES

Abstract

The Dinaric Mountains in Slovenia, Croatia and Bosnia and Herzegovina provide a unique system to address the effects of past hunting on the genetic structure of Northern chamois (Rupicapra rupicapra) and possible hybridization in the contact zone in the Velebit Mountains. The northern Dinaric Mountains should be occupied by Alpine chamois (Rupicapra rupicapra rupicapra) while the central and southern areas are inhabited by the Balkan chamois (R. rupicapra balcanica). This is the first study to characterize the genetic variation in chamois populations in the area. We used microsatellite and mitochondrial markers to analyze the genetic variation and structure of chamois populations from different geographical areas with different histories. Specifically, the influence of recent human translocations and geographical isolation on the genetic architecture of chamois populations was explored in the assumed contact zone. We successfully genotyped 74 individual samples and the number of alleles/locus ranged from 6 to 20 with a mean of 9.20. Allelic richness across populations ranged from 2.94 in the Prenj Mountains (Bosnia and Herzegovina) to 3.56 in the Biokovo Mountains (Croatia). A similar pattern was also observed for heterozygosity, ranging between 0.729 and 0.572, and expected heterozygosity, between 0.762 and 0.644 in the Prenj and Biokovo Mountains, respectively. The global FST for 7 population samples was 0.103 ± 0.047 (range = 0.0156 – 0.185). The Structure tree clusters separated samples from the northern Dinaric Mountains from those of the southern Dinaric Mountains into 2 clusters according to geographic location. The results obtained using a Bayesian clustering methodology was similar. By using mtDNA variation in chamois from Slovenia, Croatia and Bosnia and Herzegovina, the existence of Alpine chamois haplotypes in northern areas and Balkan chamois haplotypes in southern areas was confirmed. These results confirm the impact of recent human management (i.e., translocation) into the Velebit Mountains, which established a new contact (hybridization) zone between the subspecies. Therefore, future translocations must be planned carefully to avoid compromising genetic integrity and posing a serious risk to native species, as in this case.

Full text

Featured Article
The Genetic Impact of Chamois Management
in the Dinarides
NIKICA

SPREM,
1
Faculty of Agriculture, Department of Fisheries, Beekeeping, Game Management and Special Zoology, University of Zagreb,
Svetosimunska cesta 25, Zagreb 10000, Croatia
ELENA BUZAN, Science and Research Centre, Institute for Biodiversity Studies, University of Primorska, Garibaldijeva 1, Koper 6000, Slovenia
ABSTRACT The Dinaric Mountains in Slovenia, Croatia, and Bosnia and Herzegovina provide a unique
system to address the effects of past hunting on the genetic structure of northern chamois (Rupicapra
rupicapra) and possible hybridization in the contact zone in the Velebit Mountains. The northern Dinaric
Mountains should be occupied by alpine chamois (Rupicapra rupicapra rupicapra), whereas the central and
southern areas are inhabited by the Balkan chamois (R. rupicapra balcanica). This is the first study to
characterize the genetic variation in chamois populations in the area. We used microsatellite and
mitochondrial markers to analyze the genetic variation and structure of chamois populations from different
geographical areas with different histories. Specifically, we explored the influence of recent human
translocations and geographical isolation on the genetic architecture of chamois populations in the assumed
contact zone. We successfully genotyped 74 individual samples and the number of alleles/locus ranged from 6
to 20 with a mean of 9.20. Allelic richness across populations ranged from 2.94 in the Prenj Mountains,
Bosnia and Herzegovina to 3.56 in the Biokovo Mountains, Croatia. A similar pattern was also observed for
heterozygosity, ranging between 0.729 and 0.572, and expected heterozygosity, ranging between 0.762 and
0.644 in the Prenj and Biokovo mountains, respectively. The global genetic distance (F
ST
) for 7 population
samples was 0.103 0.047 (range ¼0.0156–0.185). The STRUCTURE tree clusters separated samples
from the northern Dinaric Mountains from those of the southern Dinaric Mountains into 2 clusters
according to geographic location. The results obtained using a Bayesian clustering methodology was similar.
By using mtDNA variation in chamois from Slovenia, Croatia, and Bosnia and Herzegovina, the existence of
alpine chamois haplotypes in northern areas and Balkan chamois haplotypes in southern areas was confirmed.
These results confirm the impact of recent human management (i.e., translocation) into the Velebit
Mountains, which established a new contact (hybridization) zone between the subspecies. Therefore, future
translocations must be planned carefully to avoid compromising genetic integrity and posing a serious risk
to native species, as in this case. Ó2016 The Wildlife Society.
KEY WORDS Balkan Peninsula, Dinaric Mountains, hybridization zone, microsatellites, mtDNA, Rupicapra
rupicapra.
Chamois populations are classified into 2 species based on
their morphological and behavioral characteristics (Grubb
2004): Pyrenean chamois (Rupicapra pyrenaica), which is
distributed in the Pyrenees, the Cantabrian Mountains, and
the Apennines, and northern chamois (R. rupicapra), which
extend from the Alps to the Carpathians, the Balkan
Mountains, and farther eastward into Asia. Furthermore,
on the basis of their morphological traits and geographical
distribution, and based on the biological species concept
(BSC; Mayr 1942), there are 7 recognized subspecies of
northern chamois (Masini and Lovari 1988, Corlatti et al.
2011): chartreuse (R. rupicapra cartusiana), alpine (R. rupicapra
rupicapra), Tatra (R. rupicapra tatrica), Carpathian (R.
rupicapra carpatica), Balkan (R. rupicapra balcanica), Caucasian
(R. rupicapra caucasica), and Anatolian chamois (R. rupicapra
asiatica). Two of the 7 subspecies of northern chamois
recognized in the various mountain systems they occupy
within Europe are in the Dinaric region (Corlatti et al. 2011):
alpine chamois and Balkan chamois. Both have a possible
contact zone and may hybridize in the northern Velebit
Mountains (Frkovic2008).
During the early 1900s, chamois populations in the Dinaric
region were extirpated because of unsustainable hunting,
poaching, livestock grazing, predation, and natural events
(Frkovic 2009). The last records of chamois in the Velebit
massif date back to 1907, when several animals were observed
that later could not be found (Skorup 2005). Historical data
and archaeological research confirmed the great abundance
of the chamois population in the northwestern Dinaric
Received: 20 October 2014; Accepted: 14 March 2016
1
E-mail: elena.buzan@famnit.upr.si
The Journal of Wildlife Management; DOI: 10.1002/jwmg.21081

Sprem and Buzan The Chamois Hybridization Zone 1

Mountains in Croatia and western Bosnia and Herzegovina,
but as a result of predation, natural events, and unsustainable
hunting, the population was extirpated before their
taxonomic classification was assessed (Miracle and Sturdy
1991, Miculinic 2012). The main reason for the population’s
disappearance was attributed to intensive livestock grazing,
hunting, and poaching, which forced the chamois out of its
range in the early 1900s (Frkovic 2008). Small numbers of
chamois were regularly encountered only at sites on Mount
Risnjak along the border with Slovenia (Frkovic 2009). This
deleterious human impact was counterbalanced by reintro-
ductions after World War II that neglected genetic issues.
Chamois were translocated into the Dinaric Mountains
between 1964 and 1978 with chamois originating from
different areas (

Sprem et al. 2015). Forty-eight animals
(36 F, 12 M) were translocated to the Biokovo and northern
Velebit Mountains from the Prenj Mountains in Bosnia and
Herzegovina. There was also 1 translocation to the northern
Velebit Mountains from the Kamnik Alps in Slovenia (3 F,
2 M). Translocations also occurred in the central Velebit
Mountains in 1939 and 1956, though the origin of these
animals was unknown. However, these attempts failed; the
chamois present today spread from the northern Velebit
areas (

Sabic and Lalic 2005, Frkovic 2008).
Regardless of its current status, the chamois population of
the northwestern Dinaric Mountains in Croatia is listed in
Red Book of Mammals of Croatia as a regionally extinct
species (Tvrtkovic and Grubesic 2006), whereas in Bosnia
and Herzegovina, the chamois is listed as vulnerable (Adamic
et al. 2006). However, in both countries, the chamois is
considered a game species and is hunted in accordance with
hunting regulations. The species is listed in Annex V of the
European Union Habitat Directive and Appendix III of
the Bern Convention, and Balkan chamois is included
in Annexes II and IV of the European Union Habitats
Directive and Appendix III of the Bern Convention. A
recent study (Buzan et al. 2013) did not confirm the
presence of the 2 subspecies (alpine and Balkan) or the
hypothesis of a hybridization zone in the northwestern
part of the Dinaric Mountains in Slovenia. The authors
reported that endemic phylogeographic lineages are
frequently confined to small ranges in the central Balkan
Peninsula, whereas the northern periphery is occupied by
widespread lineages that evolved in more northern refugia
(Buzan et al. 2010).
Chamois populations in Croatia provide a unique opportu-
nity to address the issues of the effects of past management on
genetic structure and possible hybridization where the
subspecies (alpine and Balkan) overlap (i.e., contact zone).
This is first study on genetic aspects of the population in
the 50 years since the successful translocation to the Dinaric
Mountains. We make special reference and search for
answers to historical data, conjectures, and theory reported
by previous authors about the ongoing translocation. Our
objective was to use microsatellite and mitochondrial markers
to analyze the genetic variation and structure of chamois
populations from different geographical areas with different
histories. Specifically, we explored areas in the contact zone,
assessed the influence on the population structure of recent
translocations, and examined how geographical isolation
is reflected in the genetic architecture of the chamois
populations. Finally, we compared our results with literature
to analyze the subspecific status of the chamois in the
northwestern Dinaric Mountains.
STUDY AREA
The Dinaric massif extends over Slovenia and Albania
(645 km), and is characterized by small plateaus and
meadows. The study area includes elevations between
518 m and 1,831 m, and is composed mainly of fir (Abies
alba) and spruce (Picea abies;Orsanic et al. 2005). The upper
forest limit, mainly >1,400 m above sea level, comprises
stands of the Dinaric Mountain pine (Hyperico grisebachii–
Pinetum mugo) association (Vukelic 2012). The climate is
humid-boreal with a Mediterranean influence, a mean
annual temperature of 7.78C and a mean annual rainfall of
2,079 mm (Vukelic 2012). Topographically, the area is
highly heterogeneous, interrupted by ditches, bays, and
rocks, which are developed on limestone and dolomite
bedrock. Throughout the study area, lower elevation lands
are mostly privately owned and under agricultural produc-
tion, whereas upper elevation lands are predominantly
state-owned timberlands under commercial management.
Besides chamois, 5 ungulate species are present: wild boar
(Sus scrofa), roe deer (Capreolus capreolus), red deer (Cervus
elaphus), fallow deer (Dama dama), and European mouflon
(Ovis musimon). Also, 3 large carnivores occur in this region:
brown bear (Ursus arctos), gray wolf (Canis lupus), and
Eurasian lynx (Lynx lynx).
The history of chamois in the study area is different
and 3 chamois populations (i.e., northern Velebit, central
Velebit, Biokovo) were recently established through
translocation. In most sites, chamois populations are stable,
whereas chamois in the Prenj Mountains are virtually
extinct (Table 1). All but 2 populations originate from
native populations in Croatia. The first exception is the
Balkan chamois population from the Prenj Mountains
(Prenj) in Bosnia and Herzegovina, which participated
in the reintroduction at certain sites in Croatia (Frkovic
2008). The second is the population of alpine chamois
(Gotenica) from the neighboring Dinaric Mountains,
Goteniski Sneznik, in Slovenia.
METHODS
Analysis of Genetic Markers and Genotyping
We obtained tissue and hair samples from 74 chamois in
2010 and 2012 during legal culls by hunters according game
management plans (approved by a competent Ministry) and
from natural deaths in subpopulations from 7 sampling sites
(Fig. 1) across the Dinaric Mountain massif: Gotenica
(n¼10), Gorski Kotar (n¼11), northern Velebit (n¼12),
central Velebit (n¼7), Dinara (n¼3), Biokovo (n¼16),
and Prenj (n¼15).
We performed DNA extractions using commercial Qiagen
DNeasy
1
kits (Qiagen, Dusseldorf, Germany) following
2 The Journal of Wildlife Management 9999()

the manufacturer’s protocol, in a volume of 200 mL. We
sequenced mtDNA regions to identify the subspecific
provenance of the chamois populations. We amplified the
partial cytochrome b gene (cyt b, 349 bp) and its control
region (CR, 475 bp) using universal primers and the
polymerase chain reaction (PCR) protocol outlined in
Rodrıguez et al. (2009, 2010). Each sample was twice
isolated and amplified. We sequenced parallels with DNA
concentration >5 ng twice in the forward and reverse
direction to confirm the fragment sequence (the error rate
was <0.6%).
We amplified 20 microsatellite loci in 3 multiplex sets,
containing 7, 6, and 7 microsatellites, respectively, using the
protocol described in Zemanova et al. (2011). For all 3 sets,
Table 1. Location, sample size, and brief history of the chamois populations investigated in Slovenia, Croatia, and Bosnia and Herzegovina, 2010 and 2012.
Area Location
Sample
size Brief description of populations
Gotenica (GOT) N 4583604700 E1484305100 10 Stable and constant population of northern chamois, current population
size ¼250 individuals
Gorski Kotar (GKO) N 4582604300 E1484702200 11 Stable and constant population of northern chamois in area bordering Slovenia,
current population size ¼350 individuals
North Velebit (NVE) N 4484605800 E1485502000 12 Reintroduced population with 10 animals (5 M:5 F) from Prenj (Balkan chamois)
and 5 animals (2 M:3 F) from Kamnik Alps (alpine chamois) during 1974–1978,
current population size ¼450–500 individuals
Central Velebit (CVE) N 4484002800 E1580100600 7 Reintroduced population with unknown origin of the animals in 1939 and 1956,
current population size ¼300–350 individuals
Dinara (DIN) N 4385700500 E1682902700 3 Very small native population of Balkan chamois shared between Bosnia and
Herzegovina, current population size ¼60 individuals
Biokovo (BIO) N 4382002900 E1780301000 16 Reintroduced population with 48 animals (12 M:36 F) from Prenj (Balkan chamois)
during 1964–1969, current population size ¼400–450 individuals
Prenj (PRE) N 4383300500 E1785205500 15 Virtually extinct native population of Balkan chamois, with only 50 individuals
remaining from a few thousand in the 1980s
Figure 1. Distribution of chamois in the Dinaric Mountains in Slovenia, Croatia, andBosnia and Herzegovina in 2010 and 2012. Sampling sites are indicated
by their 3-letter code. The pie charts in the map indicate the frequency of the mtDNA haplotypes in each locality of the study area within the distribution
range of chamois in southeastern Europe: GOT ¼Gotenica Mountains; GKO ¼Gorski Kotar; NVE ¼North Velebit Mountains, CVE ¼Central Velebit
Mountains; DIN ¼Dinara Mountains; BIO ¼Biokovo Mountains, PRE ¼Prenj Mountains. The pie charts indicate the location. The dashed lines
represent mountain edge.

Sprem and Buzan The Chamois Hybridization Zone 3

we performed PCR and fragment analysis using the protocol
described in Buzan et al. (2013). We examined microsatellite
genotypes using GeneMapper software (Life Technologies,
Carlsbad, CA).
We performed genotyping on 74 samples using 20
unlinked microsatellite loci, and performed sequencing on
45 samples because the extraction of DNA was limited by the
quantity of available tissue. We pre-screened all samples for
DNA concentration and used only samples with >5 ng/ml
for a study with nuclear markers. To confirm the genotypes,
we re-amplified approximately 30% of the individual
genotypes that were suspected of allelic dropout (i.e.,
homozygous at particular loci), and obtained the same
genotypes for the replicates. Overall genotyping error rate
based on repeat typing was 3.5%.
Mitochondrial DNA—Phylogenetic Reconstruction
We assembled the mitochondrial sequences using Program
CodonCode Aligner 1.63 (Ewing et al. 1998). We aligned the
resulting consensus sequences using ClustalW 4.0, imple-
mented in the MEGA package 6.0 (Tamura et al. 2013). We
combined the pooled dataset (2 regions) of 45 individuals
sequenced in this study with previous data on 7 subspecies of
chamois (Rodrıguez et al. 2010, Buzan et al. 2013). We
designated the mtDNA haplotypes using the same combina-
tion of fragments as described in Buzan et al. (2013). In the
newly sequenced data, we computed the haplotypes in
DNASP 5.10 (Librado and Rozas 2009). We analyzed
phylogenetic relationships using the same methods and
outgroups as in Buzan et al. (2013). We used the neighbor-
joining and Bayesian approaches under different models of
nucleotide substitution. The neighbor-joining tree, based on
the number of substitutions/site under the Jukes–Cantor
model, was constructed from the pooled sequences of 108
chamois haplotypes. We assessed the reliability of the nodes
by 1,000 bootstrap replicates (BP). We obtained the Bayesian
tree using MrBayes 3.1.2 (Huelsenbeck and Ronquist 2001,
Ronquist and Huelsenbeck 2003).
We used jModeltest 2.1.2 (Guindon and Gascuel 2003,
Darriba et al. 2012) to determine the most appropriate
model of DNA substitution under the Akaike’s Information
Criterion (AIC), corrected AIC (AIC
c
), and Bayesian
Information Criterion (BIC). The jModeltest selected the
Hasegawa, Kishino, and Yano model (HKY) including
invariable sites (I) and rate variation among sites (G),
HKY þGþI(G¼0.2488 and I¼0.2645) model to be the
most appropriate substitution model for the control region
haplotypes dataset and the HKY þG(G¼0.2835) model
for cyt bhaplotypes dataset. We ran 4 Monte Carlo Markov
chains simultaneously for 2 million generations, with the
resulting trees sampled every 100 generations. We used
Bayesian posterior probabilities (BPP) to assess branch
support of the Bayesian tree. We checked convergence by
examining the generation plot and visualized it with
TRACER 1.4 (Rambaud and Drummond 2007).
Genetic Variation of Individual Loci
We tested the exact probability test for each locus and
population to test the deviation of the observed genotype
frequency from the Hardy–Weinberg equilibrium (HWE)
using the software Genepop 4.1.3 (Rousset 2008). We set
the basic level of significance to 0.05 and applied a sequential
Bonferroni procedure for multiple comparisons. The
presence of null alleles may cause a significant heterozygote
deficit and deviation from the HWE. We, therefore,
estimated the proportion of null alleles at each locus in
each population using FreeNA (Chapuis and Estoup 2007).
We calculated the mean number of alleles, and observed (H
o
)
and expected (H
e
; Nei 1978) heterozygosities for each locus
in all populations using Genetix 4.05.2 (Belkhir et al. 1996–
2004). We estimated the allelic richness in the population
using the rarefaction procedure implemented in FSTAT
2.9.3.2 (Goudet 2001). We did not calculate genetic diversity
for population Dinara because of the small sample size
(n¼3).
Genetic Variability Among Populations
We used FreeNa to estimate a global genetic distance (F
ST
)
,
with a confidence interval of 95%, assessed with 1,000
permutations. We estimated pairwise F
ST
in Genetix
according to Weir and Cockerham (1984), and tested
significant differences of F
ST
estimators from 0 with 1,000
permutations in the same program.
We applied the Mantel test to matrices of F
ST
/(1 F
ST
)
estimates based on microsatellite marker data and the natural
logarithm of geographic distances between 6 sampling areas
to test for the pattern of isolation by distance. Samples
from population Dinara were not included in this analysis
because of a small sample size. We tested significance of the
correlation using 1,000 permutations. We estimated and
tested slope of the linear regression of F
ST
/(1 F
ST
) on the
natural logarithm of geographic distances between sampling
areas. We performed all the calculations using R software (R
core team 2013). We used the Genetix package to investigate
the genetic relationships among all genotyped individuals by
factorial correspondence analysis (FCA).
Finally, to analyze population structure, we identified
genetic structure using Bayesian algorithms implemented in
BAPs 4.1 (Corander et al. 2008) and STRUCTURE 2.3.2
(Falush et al. 2003) programs. In Program STRUCTURE,
we tested various measures for different genetic populations
or clusters (K), from 1 to 10, running the analysis 10 times for
each K under a model assuming admixture and correlate
allele frequency. We performed 20 runs with a burn-in
period of 100,000 replications and a run length of 1,000,000
Markov chain Monte Carlo iterations for a number of
clusters ranging from K ¼1 to 10. The first mentioned model
admits mixed ancestry of individuals caused by admixture
and hybridization. We combined the results of replicated
runs for each value of K from 2 to 10 using the Greedy
algorithm of CLUMPP 1.1.1 (Jakobsson and Rosenberg
2007) and displayed the summary outputs graphically
using DISTRUCT 1.1 (Rosenberg 2004). In addition, we
applied the ad hoc summary statistic DK developed by
Evanno et al. (2005), which is based on the rate of change
of the estimated likelihood between successive K values.
We used Structure Harvester (Earl and vonHoldt 2012)
4 The Journal of Wildlife Management 9999()

to generate graphs for the mean log posterior probability of
the data (mean SD).
Using allele frequencies and the HWE, the BAPs
program estimates the structure of populations by clustering
individuals (or groups of individuals [populations]) into
genetically distinguishable groups. The incorporation of
geographical information into the analysis is also possible, by
including the geographic coordinates of sampling localities.
We considered individuals from 1 locality as 1 population
sample (1 group) and we performed 20 independent runs
examining the spatial mixture analysis of groups of
individuals (spatial clustering of groups). We used the
default values and allowed K to vary from 1 to 10.
RESULTS
Mitochondrial DNA Variation
We amplified and sequenced fragments of cyt band CR from
45 individuals. Eleven haplotypes of cyt b(deposited in
GenBank under Accession Nb. KP730607–KP730617
[HRC1–HRC11]) and 10 haplotypes of the control region
were defined (deposited in GenBank under Accession Nb.
KP730618–KP730627 [HRCR1–HRCR10]). The com-
bined alignment contained 16 haplotypes defined by 45
variable sites and 76 haplotypes of combined sequences
downloaded from GenBank. Both the neighbor-joining and
Bayesian trees (Fig. 2) revealed the 3 well-supported major
Figure 2. The phylogeny of chamois in Slovenia, Croatia, and Bosnia and Herzegovina from samples collected in 2010 and 2012 constructed by neighbor-
joining and Bayesian analysis of the 108 haplotypes resulting from the combined sequences of the partial cytochrome b and partial control region (764 bp).
Neighbor-joining bootstrap support and Bayesian posterior probability indices are shown below each branch. The GenBank haplotypes of Balkan chamois
are indicated with a &symbol and new Balkan haplotypes with a ~symbol. The new chamois haplotypes are indicated with a *symbol and haplotypes
from Buzan et al. (2013) with a symbol. Clade mtWest, clade mtCentral, and clade mtEast represent the 3 major mitochondrial lineages recognized
by Rodrıguez et al. (2010).

Sprem and Buzan The Chamois Hybridization Zone 5

clades previously defined by Rodrıguez et al. (2010): mtWest
(mtW), mtCentral (mtC), and mtEast (mtE). Clade mtW is
composed of haplotypes from the Iberian Peninsula
(Pyrenean chamois) and the western Alps (alpine chamois),
Clade mtC groups haplotypes from the Apennines
(Pyrenean chamois) and the Massif of Chartreuse (alpine
chamois), and Clade mtE groups all haplotypes from the
central Alps to the Caucasus. The new haplotypes from
northwestern Dinaric Mountains clustered into Clade mtE,
together with haplotypes from Slovenia and from the central
and eastern Alps in a highly supported cluster (BP ¼92,
BPP ¼0.98). The haplotypes from the Biokovo, Dinara,
Velebit, and Prenj mountains grouped together with the
haplotype of Balkan chamois from the Carpathians (Serbia;
ref. nb. Bao017 in Rodrıguez et al. 2010). Six haplotypes
from the Velebit Mountains also belong to this clade, which
is likely the consequence of past chamois translocations
(BP ¼90, BPP ¼0.97). Although some branching was
poorly resolved, both trees showed the same topology and
new, well-distinguished haplotypes of alpine chamois from
the northern part of the Dinaric massif and Balkan chamois
haplotypes from the Central Dinaric Mountains (BP ¼81,
BPP ¼0.83). All haplotypes were highly geographically
associated, despite the indication of translocations in the
Velebit Mountains (Fig. 1). Seven unique haplotypes were
found in 4 locations (Gotenica, northern Velebit, Biokovo,
Prenj). Populations from the Dinara Mountains and the
Biokovo Mountains shared the Balkan haplotypes with the
nearby Prenj Mountains, whereas the Velebit Mountains
shared alpine haplotypes with the Gorski Kotar and
Gotenica Mountains.
Hardy–Weinberg Equilibrium and Intra-Population
Genetic Diversity
We successfully genotyped 74 individual samples and the
amplification success varied (91–100%). We estimated 67%,
81%, and 75% null alleles/population at the SY58, SY259,
and BM1258 loci, respectively, using FreeNA software. We,
therefore, excluded these 3 loci and the monomorphic locus
INRA 121. Thus, only 16 microsatellite loci with <7% of
null alleles over all samples were finally used in all analyses.
To confirm the genotypes, we re-amplified approximately
10% of the individual genotypes suspected of allelic dropout
(i.e., homozygous at particular loci), and obtained the same
genotypes for the replicates.
The populations Prenj, Biokovo, and Gorski Kotar showed
significant deviation from HWE on the basis of F
IS
(significant positive values) We found further evidence of
Prenj and Gorski Kotar deviating from HWE based on exact
tests in Genepop (P¼0.05). The deviation from HWE did
not remain significant after Bonferroni correction (Table 2).
The number of alleles/locus ranged from 6 to 20 with a
mean of 9.20. The allelic richness across populations ranged
from 2.94 (Biokovo) to 3.24 (Prenj). A similar pattern
was also observed for H
o
(range ¼0.644–0.573) and
H
e
(range ¼0.698–0.647; Table 2).
Spatial Genetic Structure and Isolation by Distance
The global F
ST
for the 7 population samples was
0.103 0.047 (range ¼0.016–0.185). The highest F
ST
value
was observed between the Gorski Kotar and the Biokovo
populations (Table 3). The FCA plot based on individual
genotypes clearly separated Balkan chamois and alpine
chamois along the first factorial axis (Fig. 3). The first
axis (explaining 38.3% of variation, P¼0.34) separated
the 3 Dinaric Mountains populations (Prenj, Biokovo,
and Dinara) from all other populations. The second axis
(explaining 23.3% of variation, P¼0.20) mainly separated
the individuals from the northern Dinaric Mountains from
the alpine chamois subspecies.
We obtained similar results in the STRUCTURE analysis.
The best model indicated 5 clusters (using DK according to
Evanno et al. [2005]; Fig. S1, available online in Supporting
Information). This result clearly separated samples from the
northern Dinaric Mountains (alpine chamois) in 3 clusters
and samples from the southern Dinaric Mountains (Balkan
chamois) in 2 clusters according to geographic location
(Fig. 4).
Table 2. Genetic diversity in chamois populations in Slovenia, Croatia, and Bosnia and Herzegovina, 2010 and 2012. H
e
¼expected and H
o
¼observed
heterozygosity, F
IS
¼inbreeding coefficient, HWE ¼Hardy-Weinberg equilibrium, A ¼number of alleles, and AR ¼allelic richness (calculated by the
rarefaction method for the lowest sample size n¼7). Standard deviations are for average values.
Population (n)H
e
SD H
o
SD F
IS
HWE A SD AR SD
GOT (10) 0.678 0.201 0.612 0.236 0.011 0.072 4.751.79 3.19 0.83
GKO (11) 0.652 0.164 0.573 0.192 0.0870.0054.681.61 3.01 0.71
NVE (12) 0.673 0.216 0.614 0.202 0.044 0.546 5.18 2.43 3.19 0.97
CVE (7) 0.684 0.152 0.607 0.258 0.047 0.179 4.25 1.35 3.13 0.73
BIO (16) 0.647 0.112 0.589 0.158 0.1060.167 4.87 1.36 2.94 0.50
PRE (15) 0.698 0.110 0.644 0.197 0.0730.0195.68 1.76 3.24 0.59
P<0.05 for HWE and F
IS
(before Bonferroni correction).
Table 3. Pairwise values of genetic distance (F
ST
) among chamois
populations in Slovenia, Croatia, and Bosnia and Herzegovina, 2010 and
2012, (GOT ¼Gotenica, GKO ¼Gorski Kotar, NVE ¼North Velebit,
CVE ¼Central Velebit, BIO ¼Biokovo, PRE ¼Prenj) based on 20
microsatellite loci calculated as described in Weir and Cockerham (1984).
Population GOT GKO NVE CVE BIO
GOT
GKO 0.095
NVE 0.092 0.079
CVE 0.055 0.114 0.091
BIO 0.179 0.197 0.045 0.184
PRE 0.109 0.105 0.110 0.137 0.085
6 The Journal of Wildlife Management 9999()

In BAPs, we obtained the highest marginal likelihood
indicating maximized posterior probability in spatial
clustering of groups (i.e., population samples) for the model
of K ¼5 (Fig. 5). Geographically, close populations were
clustered together. Two alpine chamois populations from the
north Dinaric Mountains clustered together. Populations
Gotenica and Gorski Kotar formed 2 independent clusters.
The Balkan chamois population from the Prenj Mountains
was separated from the populations in the Biokovo
Mountains and Dinara Mountains. The clustering of
populations revealed the same pattern as the STRUCTURE
analysis, suggesting robust population structure. Microsatel-
lite-based genetic distances were not significantly correlated
with geographical distances among populations, and slope of
the linear regression was not significantly different from 0
(slope ¼0.0199, r
2
¼0.16, P¼0.1381; Fig. 6), suggesting
that there is no underlying isolation by distance between
populations.
DISCUSSION
Phylogeography of Chamois in the Dinaric Mountains
The genetic information obtained in this study confirmed
that the Dinaric Mountains are inhabited by 2 northern
chamois subspecies: alpine and Balkan chamois. The recent
study from the northernmost part of Dinaric Mountains
failed to find different subspecies (Buzan et al. 2013).
According to the present study, the Balkan haplotypes reach
their northern boundary within the Velebit Mountain.
By using mtDNA variation in chamois from Slovenia,
Croatia, and Bosnia and Herzegovina, the existence of
alpine haplotypes was confirmed at the sites Gotenica,
central Velebit, and Gorski Kotar, and Balkan haplotypes at
the sites Prenj, northern Velebit, central Velebit, Biokovo,
and Dinara. In the phylogenetic tree, the haplotypes C6–
C10 and C12–C16 clustered together with the Balkan
haplotype from the Carpathian Mountains in Serbia. This
Figure 3. A 2-dimensional plot of the factorial correspondence analysis performed using GENETIX for samples of chamois collected in Slovenia, Croatia, and
Bosnia and Herzegovina in 2010 and 2012. Individuals from different subspecies or locations (identified by mtDNA) are indicated by different symbols.
GOT ¼Gotenica, GKO ¼Gorski Kotar, NVE ¼North Velebit, CVE ¼Central Velebit, DIN ¼Dinara, BIO ¼Biokovo, PRE ¼Prenj. The first axis
explained 38.3% of the variance, and the second explained 23.3% of the variance.
Figure 4. Genetic structure (from Program STRUCTURE) of chamois within 7 sampled areas in Slovenia, Croatia, and Bosnia and Herzegovina from samples
collected in 2010 and 2012. Each individual is represented by a line proportionally partitioned into shaded segments corresponding to its membershipina
specific cluster (K). Black lines separate the individuals from different sampling areas. GOT ¼Gotenica, GKO ¼Gorski Kotar, NVE ¼North Velebit,
CVE ¼Central Velebit, DIN ¼Dinara, BIO ¼Biokovo, PRE ¼Prenj.

Sprem and Buzan The Chamois Hybridization Zone 7

phylogenetic relationship confirms the existence of endemic
Balkan haplotypes in the Prenj, Dinara, and Biokovo
mountains but also reveals the result of recent translocations
in the Velebit Mountains (Fig. 2). The Balkan Peninsula
houses the main European biodiversity centers for chamois
and the distribution pattern of the endemic phylogeo-
graphical lineages is evident in the central part of the
peninsula, whereas the northern part is occupied by
widespread lineages (Previsic et al. 2009, Buzan et al. 2010).
Although translocations make sense only when the
principal cause of extinction has been eliminated, most
translocations were used primarily to increase species
populations as a result of strong hunter interest in obtaining
an additional game species (Apollonio et al. 2014). The same
interest led to chamois translocations in the Biokovo and
Velebit mountains from 1964 to 1978. The newly founded
populations adapted well in a very short time (Frkovic 2008).
However, only 10 years after the translocation had taken
place, hunting began in the Biokovo Mountains (

Sabic and
Lalic 2005), whereas hunting in the Velebit Mountains
started many years later, with the first harvest in 1996.
Currently, the populations are stable at both locations.
Taking into account the recorded data (documented
translocations), the mtDNA results presented here show
that the signature of recent translocations in the Velebit
Mountains (northern Velebit and central Velebit) is visible in
the recent genetic composition and has established a new
contact (hybridization) zone between the alpine and Balkan
subspecies (Fig. 2). We were able to record successful
translocations in the central Velebit Mountains, which is
contradictory to the conjectures of other authors (Frkovic
1981, Skorup 2005) about the unsuccessful translocation and
the theory of its spread from the northern Velebit Mountains
(Frkovic 2008). None of the mtDNA haplotypes were shared
between northern Velebit and central Velebit (Fig. 1).
Genetic Diversity
The genetic diversity in chamois populations (Gotenica,
Gorski Kotar, northern Velebit, central Velebit) was slightly
lower in term of allelic richness and observed heterozygosity
than those reported by Buzan et al. (2013) and other authors
(Crestanello et al. 2009, Soglia et al. 2010). These differences
may be due partly to larger samples used by Buzan et al.
(2013), and to the different microsatellites used in
Crestanello et al. (2009) and Soglia et al. (2010).
The lower genetic diversity in the central Dinaric
Mountains could indicate stronger genetic drift within these
populations than in the northern Dinaric Mountains
described by Buzan et al. (2013), and obviously the existence
of gene flow between the Alps and Dinaric Mountains in the
contact area contribute to higher genetic diversity. Wild
ungulates have historically been used for hunting in Europe.
Therefore, the great numbers of former reintroductions
(usually undocumented) were connected with poor manage-
ment practices by hunters, such as very high hunting bags.
During the past 30 years, roe deer have been introduced to
the western Italian Alps and the Apennines and as a result,
the endemic Italian roe deer (Capreolus c. italicus)was
subjected to introgressive hybridization with non-native
stock (Focardi et al. 2009). A recent genetic study detected
the highest haplotype diversity in reintroduction areas and
the lowest in isolated genetically distinct population of
Italian roe deer (Mucci et al. 2012). A similar situation was
reported with the endemic Iberian roe deer subspecies
(Capreolus c. decorus) in Portugal following the introduction
of animals from genetically distinct populations from France
(Royo et al. 2007). In the early 1960s, alpine chamois were
introduced to the Tatra Mountains in Slovakia, and
hybridization occurred with the genetically less diverse
endemic Tatra chamois (Findo and Skuban 2010).
The consequence of introductions from the genetically
distinct Balkan chamois (Prenj) population has not left its
mark in the genetic richness of the Velebit Mountains and
Biokovo Mountains populations. The genetic richness was
comparable to those obtained for the Dinaric populations in
Buzan et al. (2013).
Figure 5. The genetic structure of chamois populations in Slovenia,
Croatia, and Bosnia and Herzegovina, 2010 and 2012, based on spatial
clustering of groups of individuals using Bayesian analysis in Program BAPs.
The best model divided 7 population samples (GOT ¼Gotenica, GKO ¼
Gorski Kotar, NVE ¼North Velebit, CVE ¼Central Velebit, DIN ¼
Dinara, BIO ¼Biokovo, PRE ¼Prenj) into 5 clusters (K; top frame). Fixed
K¼2 (bottom frame) separated alpine chamois and the Balkan chamois
population.
8 The Journal of Wildlife Management 9999()

Historical data beginning from 1966 state that the
population from the Prenj Mountains numbered roughly
4,000 individuals (Gafic and Dzeko 2009), a level main-
tained until the early 1990s. In the recent war, the population
was decimated by illegal hunting with up to 95% of the
stock lost, and today it numbers about 50 individuals
(Frkovic 2008). Despite this recent event that swept through
in the course of only 2–3 generations, significant differences
in the genetic variation were not found in comparison to
other sites. The recent genetic variation could be also a
consequence of a past, large effective population size and
its ancient inherent diversity or, perhaps, the existence
of restored connectivity from just the few neighboring
remaining patches in the area (

Cvrsnica Mountains).
Genetic Differentiation and Population Relationship
The global F
ST
value was 0.103, and this value is easily
explained because our data includes a wider range of the
Dinaric Mountains, with 2 geographical populations
recognized as subspecies. The geographical isolation of
populations is clearly evident from mtDNA; 8 of the 16
haplotypes encountered were unique (e.g., c1 in Gotenica, c4
in Gorski Kotar, c8 and c9 in northern Velebit, c10 and c11
in central Velebit, c12, c13, and c14 in Biokovo, c14 in
Prenj). The presence of unique haplotypes in populations
from the Velebit Mountains (C8, C9, and C10) perhaps
suggests that not all the chamois disappeared from these sites
in the early 1900s, as was previously believed (Skorup 2005).
Levels of genetic differentiation vary among groups, and we
did not confirm a significant isolation by distance pattern
over the range of the studied area (Fig. 6). This could suggest
existing gene flow between populations, despite the different
history of each population or clusters of populations and
recent human-mediated reintroduction.
The signature of the translocation is visible in the
mitochondrial variation; we found the Balkan haplotype
(from Prenj) in northern Velebit (c6) and Biokovo populations
(c16). Lessons from past translocations highlight the risk
of genetic admixture with introduced conspecifics and loss
of endemic diversity from the native taxon, which today has
become a major conservation issue (Focardi et al. 2009).
Although the overall picture poses several puzzles, the
results were consistent across all tests, supporting the strong
differentiation in these chamois populations. The results of
FCA clearly separate northern alpine chamois (Gotenica,
Gorski Kotar, northern Velebit, and central Velebit) from
southern Balkan chamois populations (Dinara, Biokovo,
and Prenj). The results support 2 different geographical
populations and confirm the historical data (Frkovic 2009)
and Bayesian clustering. The STRUCTURE analysis with
K¼2 gave a clear split between alpine chamois (Gotenica,
northern Velebit, central Velebit, and Gorski Kotar) and
Balkan chamois (Prenj, Biokovo, and Dinara) populations.
In addition, even in the best model with K¼5 populations,
we failed to find a signal of Balkan genotypes in the Velebit
Mountains populations. Only a weak signal of different
genotypes could be noted. It is likely that the genetic signal of
the Prenj Mountains population was lost in the nuclear
data (but is still evident in mtDNA; Fig. 1). It is now well
established that STRUCTURE can sometimes fail to
detect population genetic structure at lower levels of genetic
differentiation, especially when using a smaller number of
individuals or loci (Kalinowski 2011, Frantz et al. 2012,

Sprem et al. 2013). The clustering of chamois populations
Figure 6. Isolation-by-distance in Dinaric Mountains chamois populations in Slovenia, Croatia, and Bosnia and Herzegovina, 2010 and 2012. We calculated
genetic distance (F
ST
) and plotted F
ST
/(1F
ST
) against the natural log of geographical distance (km). The genetic and geographical distances are not
significantly correlated. Slope of the linear regression ¼0.0199, r
2
¼0.16, P¼0.138.

Sprem and Buzan The Chamois Hybridization Zone 9

supports their differentiation into 5 geographically associated
clusters and reveals a strong substructure within mountain
ranges with suboptimal chamois habitat. Population from
the Velebit Mountains clustered together, as did the
populations from the Biokovo and Dinara mountains. All
other populations are associated with genetically indepen-
dent clusters. Evidently, small groups of chamois may remain
isolated in restricted habitat patches, separated by extensive
forest with no chamois habitat between, with occasional but
very restricted gene flow between patches. The similar
population structure revealed by the spatial model in BAPs
and the non-spatial model in STRUCTURE indicates that
the differentiation between populations is so strong that it
was even detected by the less sensitive model (Chen et al.
2007, Safner et al. 2011).
The small population size and low genetic variability of the
chamois populations in the Dinaric Mountains make them
vulnerable to many factors. Illegal poaching and transloca-
tion have given rise to a distinct substructuring of the existing
gene pool. In a review paper, Corlatti et al. (2011) pointed to
the same threats to the populations (i.e., hybridization,
translocations), which may increase the risk of losing
differentiated gene pools and cause genetic extinction of
taxa (e.g., chartreuse chamois, Tatra chamois, and Balkan
chamois). Balkan chamois, a charismatic ungulate with
endangered status, could serve as an excellent flagship species
for the conservation of mountain ecosystems in the Balkan
Peninsula. In Croatia and Bosnia and Herzegovina, the
species is protected by the national and European legislation.
The translocation to the Dinaric Mountains (especially
Biokovo Mountains) has twice the benefit because this is one
of the main reasons for the reappearance of the 3 large
predators in the area (i.e., brown bear, gray wolf, and
European lynx), which has ultimately had a positive
consequence in restocking the natural community of large
mammals and increasing the biodiversity of the area
(Apollonio et al. 2014). Translocations and subsequent
hybridization between individuals from different populations
or taxa have had a significant genetic impact on alpine and
Balkan chamois in the Dinaric Mountains. Unfortunately,
the results of the present study show that the translocation of
individuals from geographically (and therefore genetically)
distant populations have resulted in a hybrid zone in the
Velebit Mountains, which can be detrimental to the
conservation of the species.
MANAGEMENT IMPLICATIONS
Conservation units for the alpine and Balkan chamois need
to be defined for future management strategies, which may or
may not include translocations with individuals carrying the
appropriate genetic background. In the meantime, the
interspecific hybridization occurring in the Velebit Moun-
tains should be regarded as an ongoing and unplanned
experiment and the evolutionary consequences of this process
should be carefully monitored. Because the current range of
the Balkan chamois in the Prenj Mountains does not
correspond to the actual habitat suitability and it is on the
verge of extinction, the feasibility could be evaluated to use
the Biokovo Mountain population as a source for trans-
locations to the former habitats. The 5 clusters, re-evaluated
with a spatial analysis of genetic variation, have undergone
independent demographic histories and should be regarded
as independent units for management purposes. We reject
the presumption of the homogeneity of the chamois
populations of the Dinaric Mountains. Considering the
population structuring of the Velebit, Dinara, and Biokovo
mountain populations, which seem likely able to maintain
viable populations, there should be restricted gene flow
from the west (introduced northern Velebit and Biokovo
population), having lost the signal (nuclear markers) of
their founder population and only exhibiting their own
genetic makeup. Further research on the genetic structure of
these populations has the potential to deepen the insight
into any gene flow and to define the contact zone where
hybridization of the subspecies is taking place. For the
effective future management of the Velebit Mountain
population, it is crucial to establish whether chamois really
did disappear from the area prior to the implementation
of translocations.
ACKNOWLEDGMENTS
We thank the associate editor, 2 anonymous reviewers, and
T. Safner for helpful comments on earlier drafts of the
manuscript, and L. Zanella for proofreading the manuscript.
LITERATURE CITED
Adamic, M.,

Z. Rapaic, Z. Popovic, S. Kunovac, M. Koprivica, V. Soldo, B.
Markovic, R. Maunaga, M. Micevic, and V. Ilic. 2006. Endangered game
species in Bosnia and Herzegovina–Final report. Megaprojekt/Waldpro-
jekt, Banja Luka, Bosnia and Herzegovina. [In Bosnian.]
Apollonio, M., M. Scandura, and N.

Sprem. 2014. Reintroductions as a
management tool for European ungulates. Pages 46–77 in R. Putman and
M. Apollonio, editors. Behaviour and management of European
ungulates. Whittles Publishing, Dunbeath, Caithness, United Kingdom.
Belkhir, K., P. Borsa, L. Chikhi, N. Raufaste, and F. Bonhomme. 1996–
2004. GENETIX 4.05, logiciel sous Windows TM pour la ge
ne
tique des
populations. Laboratoire Ge
nome, Populations, Interactions, CNRS
UMR 5000, Universitede Montpellier II, Montpellier, France.
Buzan, E. V., D. W. Forster, J. B. Searle, and B. Krystufek. 2010. A new
cytochrome b phylogroup of the common vole (Microtus arvalis) endemic
to the Balkans and its implications for the evolutionary history of the
species. Biological Journal of the Linnean Society 100:788–796.
Buzan, V. E., J. Bryja, B. Zemanova, and B. Krystufek. 2013. Population
genetics of chamois in the contact zone between the Alps and the Dinaric
Mountains: uncovering the role of habitat fragmentation and past
management. Conservation Genetics 14:401–412.
Chapuis, M.-P., and A. Estoup. 2007. Microsatellite null alleles and
estimation of population differentiation. Molecular Biology and Evolution
24(3):621–631.
Chen, C., E. Durand, F. Forbes, and O. Francois. 2007. Bayesian clustering
algorithms ascertaining spatial population structure: a new computer
program and a comparison study. Molecular Ecology Notes 7:747–756.
Corander, J., J. Sire
n, and E. Arjas. 2008. Bayesian spatial modelling of
genetic population structure. Computational Statistics 23:111–129.
Corlatti, L., R. Lorenzini, and S. Lovari. 2011. The conservation of the
chamois Rupicapra spp. Mammal Review 41(2):163–174.
Crestanello, B., E. Pecchioli, C. Vernesi, C. Mona, N. Martınkova, M.
Janiga, H. C. Hauffe, and G. Bertorelle. 2009. The genetic impact of
translocations and habitat fragmentation in chamois (Rupicapra spp).
Journal of Heredity 100:691–708.
Darriba, D., G. L. Taboada, R. Doallo, and D. Posada. 2012. jModelTest 2:
more models, new heuristics and parallel computing. Nature Methods
9:772.
10 The Journal of Wildlife Management 9999()

Earl, D. A., and B. M. vonHoldt. 2012. STRUCTURE HARVESTER: a
website and program for visualizing STRUCTURE output and
implementing the Evanno method. Conservation Genetics Resources
4:359–361.
Evanno, G., S. Regnaut, and J. Goudet. 2005. Detecting the number of
clusters of individuals using the software STRUCTURE: a simulation
study. Molecular Ecology 14:2611–2620.
Ewing, B., L. Hillier, M. C. Wendl, and P. Green. 1998. Base-calling of
automated sequencer traces using Phred. I. Accuracy assessment. Genetics
Research 8:175–185.
Falush, D., M. Stephens, and J. K. Pritchard. 2003. Inference of population
structure using multilocus genotype data: linked loci and correlated allele
frequencies. Genetics 164:1567–1587.
Findo, S., and M. Skuban. 2010. Ungulates and their management in
Slovakia. Pages 262–290 in M. Apollonio, R. Andersen, and R. Putman,
editors. European ungulates and their management in the 21st century.
Cambridge University Press, Cambridge, United Kingdom.
Focardi, S., P. Montanaro, V. La Morgia, and F. Riga, editors. 2009. Piano
d’azione nazionale per il capriolo italico (Capreolus capreolus italicus).
Quaderni Conservazione della Natura 31, Ministero Ambiente ISPRA,
Italy.
Frantz, A. C., S. Bertouille, M. C. Eloy, A. Licoppe, F. Chaumont, and
M. C. Flamand. 2012. Comparative landscape genetic analyses show a
Belgian motorway to be a gene flow barrier for red deer (Cervus elaphus),
but not wild boars (Sus scrofa). Molecular Ecology 14:3445–3457.
Frkovic, A. 1981. Naseljavanje divokoze u loviste “Senjski Sjeverni
Velebit”. Goransko-Primorsko sumsko gospodarstvo, Delnice, Croatia.
[In Croatian.]
Frkovic, A. 2008. Reintroduction of chamois in Northern Velebit.

Sumarski
list 11–12:543–550. [In Croatian with English summary.]
Frkovic, A. 2009. Chamois in Gorski Kotar. Risnjak National Park, Crni
Lug, Croatia. [In Croatian.]
Gafic, M., and

S. Dzeko. 2009. Prenj. Turisticka zajednica Kantona
Sarajevo, Sarajevo, Bosnia and Herzegovina. [In Bosnian.]
Goudet, J. 2001. FSTAT, a programme to estimate and test gene diversities
and fixation indices (version 2.9.3). http://www2.unil.ch/izea/softwares/
fstat.html. Accessed 3 Mar 2015.
Grubb, P. 2004. Order Artiodactyla. Pages 637–743 in D. E. Wilson, and
D. M. Reeder, editors. Mammal species of the world. A taxonomic and
geographic reference, third edition, volume 1. John Hopkins University
Press, Baltimore, Maryland, USA.
Guindon, S., and O. Gascuel. 2003. A simple, fast and accurate method to
estimate large phylogenies by maximum-likelihood. Systematic Biology
52:696–704.
Huelsenbeck, J. P., and F. Ronquist. 2001. MrBayes: Bayesian inference of
phylogeny. Bioinformatics 17:754–755.
Jakobsson, M., and N. A. Rosenberg. 2007. CLUMPP: a cluster matching
and permutation program for dealing with label switching and multi-
modality in analysis of population structure. Bioinformatics 23:1801–
1806.
Kalinowski, S. T. 2011. The computer program STRUCTURE does not
reliably identify the main genetic clusters within species: simulations and
implications for human population structure. Heredity 106:625–632.
Librado, P., and J. Rozas. 2009. DnaSP v5: a software for comprehensive
analysis of DNA polymorphism data. Bioinformatics 25:1451–1452.
Masini, F., and S. Lovari. 1988. Systematics, phylogenetic relationships, and
dispersal of the chamois (Rupicapra spp.). Quaternary Research 30:339–
349.
Mayr, E. 1942. Systematics and the Origin of Species. Columbia University
Press, New York, New York, USA.
Miculinic, K. 2012. Archeozoological study of the former presence of larger
mammals. Rewilding Europe-Velebit, Zagreb, Croatia.
Miracle, P., and D. Sturdy. 1991. Chamois and the karst of Herzegovina.
Journal of Archaeological Science 18:89–108.
Mucci, N., F. Mattuci, and E. Randi. 2012. Conservation of threatened local
gene pools: landscape genetics of the Italian roe deer (Capreolus c. italicus)
populations. Evolutionary Ecology Research 14:897–920.
Nei, M. 1978. Estimation of average heterozygosity and genetic distance
from a small number of individuals. Genetics 89:583–590.
Orsanic, M, D. Tomljanovic, and J. Tomljanovi
c. 2005. Managing forests of
Northern Velebit. Pages 73–98 in J. Vukelic, editors. Forests and Forestry
of Northern Velebit, Hrvatske sume d.o.o., Zagreb, Croatia. [In
Croatian.]
Previsic, A, C. Walton, M. Kucinic, P. T. Mitrikeski, and M. Kerovec. 2009.
Pleistocene divergence of Dinaric Drusus endemics (Trichoptera,
Limnephilidae) in multiple microrefugia within the Balkan Peninsula.
Molecular Ecology 18:634–647.
Rambaud, A., and A. J. Drummond. 2007. Tracer, version 1.4. http://beast.
bio.ed.ac.uk/Tracer. Accessed 3 Mar 2015.
Rodrıguez, F., S. Hammer, T. Perez, F. Suchentrunk, R. Lorenzini, J.
Michallet, N. Mantinkova, J. Albornoz, and A. Dominguez. 2009.
Cytochrome b phylogeography of chamois (Rupicapra spp.). Population
contractions, expansions and hybridizations governed the diversification of
the genus. Journal of Heredity 100:47–55.
Rodrıguez, F., T. Perez, S. Hammer, J. Albornoz, and A. Domınguez. 2010.
Integrating phylogeographic patterns of microsatellite and mtDNA
divergence to infer the evolutionary history of chamois. BMC Evolutionary
Biology 10:222–214.
Ronquist, F., and J.P. Huelsenbeck. 2003. MrBayes 3: Bayesian phylogenetic
inference under mixed models. Bioinformatics 19:1572–1574.
Rosenberg, N. A. 2004. DISTRUCT: a program for the graphical display of
population structure. Molecular Ecology Notes 4:137–138.
Rousset, F. 2008. Genepop’007: a complete reimplementation of the
Genepop software for Windows and Linux. Molecular Ecology Resources
8:103–106.
Royo, L., G. Pajares, I.

Alvares, I. Fernandez, and F. Goyache. 2007.
Genetic variability and differentiation in Spanish roe deer (Capreolus
capreolus): a phylogeographic reassessment within the European frame-
work. Molecular Phylogenetics and Evolution 42:47–61.

Sabic, B., and N. Lalic. 2005. Game management plan for state hunting
ground no. XVII/1 “Biokovo" for the period from 01 April 2005 to
31 March 2015. Hrvatske sume d.o.o. Zagreb, Makarska, Croatia.
[In Croatian.]
Safner, T., M. P. Miller, B. H. McRae, M. J. Fortin, and S. Manel. 2011.
Comparison of Bayesian clustering and edge detection methods for
inferring boundaries in landscape genetics. International Journal of
Molecular Sciences 12:856–889.
Skorup, V. 2005. Big game and hunting. Pages 141–169 in J. Vukelic,
editors. Forest and forestry of Northern Velebit. Hrvatske sume d.o.o.
Zagreb, Zagreb-Senj, Croatia. [In Croatian.]
Soglia, D., L. Rossi, E. Cauvin, C. Citterio, E. Ferroglio, S. Maione, P. G.
Meneguz, V. Spalenza, R. Rasero, and P. Sacchi. 2010. Population genetic
structure of alpine chamois (Rupicapra r. rupicapra) in the Italian Alps.
European Journal of Wildlife Research 56:845–854.

Sprem, N., C. A. Frantz, V. Cubric-Curik, T. Safner, and I. Curik. 2013.
Influence of habitat fragmentation on population structure of red deer in
Croatia. Mammalian Biology 78:290–295.

Sprem, N., D. Zanella, D. Ugarkovic, I. Prebanic, P. Gancevic, and L.
Corlatti. 2015. Unimodal activity pattern in forest-dwelling chamois:
typical behaviour or interspecific avoidance? European Journal of Wildlife
Research 61:789–794.
Tamura, K., G. Stecher, D. Peterson, A. Filipski, and S. Kumar. 2013.
MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0.
Molecular Biology and Evolution 30:2725–2729.
Tvrtkovic, N., and M. Grubesi
c. 2006. Chamois. Pages 42–43 in N.
Tvrtkovic, editor. Red Book of Mammals of Croatia. Ministry of Culture
and State Institute for Nature Protection, Zagreb, Croatia.
Vukelic, J. 2012. Forest vegetation in Croatia. University of Zagreb Faculty
of Forestry, Zagreb, Croatia. [In Croatian.]
Weir, B. S., and C. C. Cockerham. 1984. Estimating F-Sstatistics for the
analysis of population structure. Evolution 38:1358–1370.
Zemanova, B., P. Hajkova, J. Bryja, J. Zima Jr.,A. Hajkova, and J. Zima. 2011.
Development of multiplex microsatellite sets for noninvasive population
genetic study of the endangered Tatra chamois. Folia Zoologica 60:70–80.
Associate Editor: Emily Latch.
SUPPORTING INFORMATION
Additional supporting information may be found in the
online version of this article at the publisher’s website.

Sprem and Buzan The Chamois Hybridization Zone 11