RESEARCH ARTICLE Open Access
Comparative phylogeography of two related
plant species with overlapping ranges in Europe,
and the potential effects of climate change on
their intraspecific genetic diversity
Gemma E Beatty, Jim Provan*
Abstract
Background: The aim of the present study was to use a combined phylogeographic and species distribution
modelling approach to compare the glacial histories of two plant species with overlapping distributions, Orthilia
secunda (one-sided wintergreen) and Monotropa hypopitys (yellow bird’s nest). Phylogeographic analysis was carried
out to determine the distribution of genetic variation across the range of each species and to test whether both
correspond to the “classic” model of high diversity in the south, with decreasing diversity at higher latitudes, or
whether the cold-adapted O. secunda might retain more genetic variation in northern populations. In addition,
projected species distributions based on a future climate scenario were modelled to assess how changes in the
species ranges might impact on total intraspecific diversity in both cases.
Results: Palaeodistribution modelling and phylogeographic analysis using multiple genetic markers (chloroplast
trnS-trnG region, nuclear ITS and microsatellites for O. secunda; chloroplast rps2, nuclear ITS and microsatellites for
M. hypopitys) indicated that both species persisted throughout the Last Glacial Maximum in southern refugia. For
both species, the majority of the genetic diversity was concentrated in these southerly populations, whereas those
in recolonized areas generally exhibited lower levels of diversity, particularly in M. hypopitys. Species distribution
modelling based on projected future climate indicated substantial changes in the ranges of both species, with a
loss of southern and central populations, and a potential northward expansion for the temperate M. hypopitys.
Conclusions: Both Orthilia secunda and Monotropa hypopitys appear to have persisted through the LGM in Europe
in southern refugia. The boreal O. secunda, however, has retained a larger proportion of its genetic diversity in
more northerly populations outside these refugial areas than the temperate M. hypopitys. Given that future species
distribution modelling suggests northern range shifts and loss of suitable habitat in the southern parts of the
species’ current distributions, extinction of genetically diverse rear edge populations could have a significant effect
in the rangewide intraspecific diversity of both species, but particularly in M. hypopitys.
Background
Paleoclimatic evidence indicates that the Earth’s tem-
perature has been continually changing over time [1-3].
The glacial and interglacial cycles that characterised the
Quaternary period (ca. 2.6 MYA - present) have had a
significant effect on the distributions of species, particu-
larly in the northern latitudes [4,5]. Temperate species
were generally confined to low-latitude refugia through-
out glacial periods and recolonized from these areas as
the climate warmed during interglacials [6,7]. For plant
species, however, whose spread is primarily via dispersal
of seeds, the capacity to track changes in suitable habitat
is limited, particularly for animal-dispersed species [8].
Understanding the past movements of species may
help us understand how present and future climate
change might affect species’ ranges [9,10]. Within the
last decade, it has become evident that anthropogeni-
cally induced climate change is causing shifts in the
* Correspondence: J.Provan@qub.ac.uk
School of Biological Sciences, Queen’s University Belfast, 97 Lisburn Road,
Belfast BT9 7BL, Northern Ireland
Beatty and Provan BMC Evolutionary Biology 2011, 11:29
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© 2011 Beatty and Provan; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.

(A) (B)
(C) (D)
(E) (F)
(G) (H)
Figure 1 Distributions of O. secunda and M. hypopitys, and modelled LGM, current and future distributions. (A) Distribution of
O. secunda (Source: Naturhistoriska riksmuseet) (B) Distribution of M. hypopitys (Source: Naturhistoriska riksmuseet) (C) Modelled LGM (ca. 18 KYA)
distribution of O. secunda (D) Modelled LGM (ca. 18 KYA) distribution of M. hypopitys (E) Modelled current distribution of O. secunda (F) Modelled
current distribution of M. hypopitys (G) Modelled future (2100) distribution of O. secunda (D) Modelled future (2100) distribution of M. hypopitys.
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sensitivity-specificity sum maximisation approach [33]
and the performance of the models were tested using
25% of the occurrence data points to determine the area
under the receiver operating characteristic (ROC) curve
(AUC).
Molecular genetic analyses - O. secunda
206 individuals were sequenced for the chloroplast trnS-
trnG intergenic spacer. A product was amplified using
the O. secunda-specific primers and reaction conditions
described in [34]. 5 μl PCR product were resolved on
1.5% agarose gels and visualised by ethidium bromide
staining, and the remaining 15 μl sequenced in both
directions using the BigDye sequencing kit (V3.1; Applied
Biosystems) and run on an AB 3730XL DNA analyser.
154 individuals were sequenced for a section of
the nuclear ITS region. Primers were designed from
GenBank sequence accession number AF133747:
OS-ITS-F 5’-TGTTTGTACACTTGGGGAAGC-3’ and
OS-ITS-R 5’-TCGCGGTCAATGTACCGTAG-3’. PCR
and sequencing were carried out as described in [34],
except that an annealing temperature of 55°C was used
for the PCR.
218 individuals were genotyped for five O. secunda
microsatellite loci previously described in [35]. Forward
primers were modified by the addition of a 19 bp M13
tail (5’-CACGACGTTGTAAAACGAC-3’) and reverse
primers were modified by the addition of a 7 bp tail
(5’-GTGTCTT-3’). PCR was carried out in a total
volume of 10 μl containing 100 ng genomic DNA, 10
Table 1 Orthilia secunda populations analysed in this study
Country Location Code Lat Long Ncp NITS Nmicro Collector
Austria Radmer an der Stube ATRS 47.5556 14.7861 5 2 5 Apollonie Mayr
Steiermark ATS1 47.4967 14.3522 7 5 8 Peter Schönswetter
Steiermark ATS2 47.4389 14.9233 8 7 8 Peter Schönswetter
Czech Republic Kosatky CZKO 50.3178 14.6719 7 6 7 Petr Kotlik
Estonia Jõgevamaa EEJO 58.6338 26.9453 7 2 8 Teene Talve
Nigula Nature Reserve EENN 58.0194 24.6825 7 5 8 M. Reintal
Põlvamaa EEPO 58.0956 27.0302 8 4 8 T. Oja
France Cervieres FRCE 44.8667 6.7225 7 5 8 Rolland Douzet
Sauvas FRSA 44.6004 5.9037 5 4 7 Arne Saatkamp
Station Alpine Joseph Fourier FRJF 45.0360 6.4002 6 5 8 Rolland Douzet
Ireland Correl Glen IECG 54.4372 -7.8744 4 4 4 Gemma Beatty
Cranny Burn IECB 54.9114 -6.0409 4 4 4 Gemma Beatty
Italy Valle D’Aosta ITVA 45.7125 7.1639 6 5 6 Nationaal Herbarium Nederland
Montenegro Durmitor Mountains MEDM 43.1611 19.2028 8 7 8 Anna & Michal Ronikier
Komovi Massif MEKM 42.6947 19.6672 5 4 5 Anna & Michal Ronikier
Norway Buskerud NOBU 60.1208 10.3833 8 6 8 Andreas Tribsch
Oslo NOOS 59.9939 10.7064 8 6 8 Andreas Tribsch
Selvikstaken NOSE 58.8625 6.0750 4 4 4 Andreas Tribsch
Troms Fylke NOTF 68.9500 19.7500 4 4 5 W. Paul
Poland Bialystok PLBI 53.1167 23.1167 8 4 8 Ada Wroblewska
Kielce PLKI 50.8400 20.5800 5 5 5 W. Paul
Pomorze Zachodnie PLPZ 54.0047 19.9983 7 6 8 Joanna Julia & Lech Galosz
Scotland Glen Glass SCGG 57.6816 -4.4226 4 4 4 Peter McEvoy
Glen Mhor SCGM 56.8844 -3.6315 4 4 4 Peter McEvoy
Slovakia Muranska Planina SKMP 48.7825 19.9600 8 5 8 Anna & Michal Ronikier
Nizke Tatry SKNT 48.9983 19.5875 8 5 8 Anna & Michal Ronikier
Slovensky Raj SKSR 48.9305 20.2897 2 2 2 Anna & Michal Ronikier
Zapadne Tatry SKZT 49.1453 19.7850 7 6 7 Anna & Michal Ronikier
Slovenia Kaminske Alpe SIKA 46.3922 14.6000 8 6 8 Peter Schönswetter
Sweden Flurkmark SEFL 64.1273 20.1322 8 7 8 Stefan Ericsson
Lomselenas SELO 65.1441 17.3139 8 6 8 Stefan Ericsson
Ranas SERA 59.8128 18.2883 5 1 8 Arne Anderberg
Switzerland Chasseron CHCH 46.8287 6.5508 6 6 6 Philippe Druart
Valais CHVA 46.0000 7.6833 5 5 5 Nationaal Herbarium Nederland
206 154 218
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pmol of dye-labelled M13 primer (6-FAM or HEX), 1
pmol of tailed forward primer, 10 pmol reverse primer,
1× PCR reaction buffer, 200 μM each dNTP, 2.5 mM
MgCl2 and 0.25 U GoTaq Flexi DNA polymerase (Pro-
mega). PCR was carried out on a MWG Primus ther-
mal cycler using the conditions described in [35] and
genotyping was carried out on an AB3730xl capillary
genotyping system. Allele sizes were scored in GENE-
MAPPER V4.1 using ROX-500 size standards and were
checked by comparison with previously sized control
samples.
Molecular genetic analyses - M. hypopitys
100 individuals were sequenced for a section of the chlor-
oplast rps2 gene. Primers were designed from GenBank
sequence accession number AF351956 (Bidartondo and
Bruns 2001): MH-rps2-F 5’-TTCGCCGATTTAGTAT-
CACG-3’ and MH-rps2-R 5’-GGGATTCCCAAAGTAA-
TACATTCTA-3’. PCR and sequencing were carried out
as described in [34].
100 individuals were sequenced for a section of the
nuclear ITS region. Primers were designed from Gen-
Bank sequence accession number AF384126 [36]: MH-
ITS-F 5’-GGTTGGCCTACCCTTTATTTT-3’ and MH-
ITS-R 5’-GAAGTAATCCAATCATAACACTGACA-3’.
PCR and sequencing were carried out as described in
[34], except that an annealing temperature of 55°C was
used.
111 individuals were genotyped for five M. hypopitys
microsatellite loci previously described in [37] -
Mono02, Mono15, Mono20, Mono21 and Mono22.
Three additional loci developed using the ISSR-cloning
technique outlined in [38] were also used (Table 2). For-
ward primers were modified by the addition of a 19 bp
M13 tail (5’-CACGACGTTGTAAAACGAC-3’) and
reverse primers were modified by the addition of a 7 bp
tail (5’-GTGTCTT-3’). PCR was carried out in a total
volume of 10 μl containing 100 ng genomic DNA,
10 pmol of dye-labelled M13 primer (6-FAM or HEX),
1 pmol of tailed forward primer, 10 pmol reverse
primer, 1× PCR reaction buffer, 200 μM each dNTP,
2.5 mM MgCl2 and 0.25 U GoTaq Flexi DNA polymer-
ase (Promega). PCR was carried out on a MWG Primus
thermal cycler using the conditions described in [39]
and genotyping was carried out on an AB3730xl capil-
lary genotyping system. Allele sizes were scored in
GENEMAPPER V4.1 (Applied Biosystems) using ROX-
500 size standards and were checked by comparison
with previously sized control samples.
Data analysis
Alignments were constructed using BIOEDIT (V7.0.9.0)
[40] for the O. secunda chloroplast trnS-trnG intergenic
spacer and nuclear ITS, and for the M. hypopitys chloro-
plast rps2 and nuclear ITS. Length variation at any
mononucleotide repeat regions was removed, since the
bidirectional mutation model operating at such regions
can give rise to homoplasy [41]. The alignments were
used to construct statistical parsimony networks using
the TCS software package (V1.2.1) [42]. Where reticula-
tions were present in the networks, these were broken
following the rules described in [43].
Table 2 Monotropa hypopitys populations analysed in this study
Country Location Code Lat Long Ncp NITS Nmicro Collector
Austria Karnten ATKA 46.5228 13.9539 2 2 2 Peter Schönswetter
Czech Republic Polom CZPO 49.7892 15.7595 1 1 1 Jakub Tiesetel
England Peasmarsh ENPE 50.9667 -0.6667 6 6 8 Jonathan Simmons
Estonia Jõgevamaa EEJO 58.6338 26.9453 6 6 8 Teene Talve
Põlvamaa EEPO 58.0956 27.0302 7 8 8 T. Ota
Ireland Ely Lodge IEEL 54.4567 -7.9002 8 7 8 Gemma Beatty
Straidkilly IEST 54.9914 -6.0409 8 7 8 Gemma Beatty
Poland Czarne Lake PLCL 53.4667 20.6000 8 7 8 Ada Wroblewska
Lake Golun PLLG 54.0047 17.9983 8 8 8 Ada Wroblewska
Knyszyn PLKN 53.3333 22.9167 8 8 8 Joanna Julia & Lech Galosz
Romania Retezat Mountains RORM 45.3097 22.9678 8 8 8 Anna & Michal Ronikier
ROVG 46.2070 25.5400 4 4 6 Anna Maria Csergo
Slovakia Muranska Planina SKMP 48.7825 19.9600 2 2 2 Anna & Michal Ronikier
Nizke Tatry SKNT 48.9983 19.5875 4 4 6 Anna & Michal Ronikier
Slovenia Dolenjska SIDO 45.9236 15.0958 2 3 3 Peter Schönswetter
Soca Valley SISV 46.3450 13.6800 8 8 8 Peter Schönswetter
Sweden Ranas SERA 59.8128 18.2883 3 4 4 Arne Anderberg
Switzerland Chasseron CHCH 46.8287 6.5508 5 5 5 Philippe Druart
100 100 111
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Tests for linkage disequilibrium between pairs of
microsatellite loci in each population were carried out
in the program FSTAT [44]. Levels of genetic diversity
were calculated for populations with a sample size of
N ≥ 4. Gene diversity (H) based on haplotype frequen-
cies for the O. secunda chloroplast trnS-trnG region and
nuclear ITS, and the M. hypopitys chloroplast rps2 and
nuclear ITS, and observed and expected heterozygosity
(HO and HE) based on nuclear microsatellite allele fre-
quencies were calculated using the ARLEQUIN software
package (V3.01) [45]. Population structuring based on
the microsatellite data was determined using the
STRUCTURE software package (V 2.2) [46]. Five inde-
pendent runs were carried out for all values of K, the
number of clusters, between 2 and 20. The program was
run each time using 50,000 burn-in iterations followed
by 500,000 Markov Chain Monte Carlo iterations, and
the most likely value of K was determined using the ΔK
statistic [47].
Results
Species distribution modelling
For all models, the area under the receiver operating
curve (AUC) statistic was consistently higher than 0.95,
indicating good performance.
Distribution modelling for O. secunda and M. hypop-
itys at the LGM indicated extensive areas of suitable
habitat for both species in southern Europe (Figures 1C
and 1D). For O. secunda, two of the French populations
(FRSA and FRCE), one of the Swiss populations
(CHVA) and the two populations from Montenegro lay
within the suitable climate envelope indicated by the
ENM. None of the M. hypopitys populations studied lay
within the suitable climate envelope indicated by
the ENM.
The future distribution model indicated an extensive
loss of suitable habitat for O. secunda relative to the
modelled current climate envelope (Figure 1E), particu-
larly in northern central Europe (Figure 1G). The major-
ity of the suitable remaining habitat in southern Europe
would be largely restricted to the mountainous regions
of the Pyrenees, the Alps, the Carpathians and the Dina-
ric Alps. For M. hypopitys, the model indicated a general
northward shift in the species’ distribution, with a loss
of suitable habitat in southeastern Europe but an
increase in northern Europe, particularly in Scandinavia
(Figures 1F and 1H).
O. secunda phylogeography
Removal of length polymorphism at three mononucleo-
tide repeat regions from the chloroplast trnS-trnG align-
ment resulted in an overall alignment length of 495 bp
and seven distinct haplotypes (Table 3; Figure 2;
GenBank sequence accession numbers HQ864688-
HQ864694). Three of these (Haplotypes 5, 6 and 7)
were unique to a single individual. The three most com-
mon haplotypes exhibited a general north-south split,
with the Haplotype 2 (yellow) found predominantly in
southern populations whilst northern populations con-
tained primarily the two blue haplotypes (Haplotypes 1
and 3). Two populations contained all three of these
haplotypes: the FRCE population (France) and the
SKMP population (Slovakia). The fourth non-unique
haplotype, Haplotype 4 (green), was found in a single
individual in both the ATST1 (Austria) and the SELO
(Sweden) populations.
The 475 bp nuclear ITS alignment contained five dis-
tinct haplotypes (Table 3; Figure 3; GenBank sequence
accession numbers HQ864695-HQ864699). The most
Table 3 Diversity statistics for O. secunda populations
Country Code HE cpDNA haplotype ITS haplotype
1 2 3 4 5 6 7 1 2 3 4 5
Austria ATRS 0.729 - 5 - - - - - 5 - - - -
ATS1 0.529 - 6 - 1 - - - 7 - - - -
ATS2 0.629 - 5 2 - 1 - - 8 - - - -
Czech Republic CZKO 0.736 7 - - - - - - 4 2 - - -
Estonia EEJO 0.768 1 - 6 - - - - 1 - - - -
EENN 0.752 - 1 6 - - - - - - 5 - -
EEPO 0.797 - 7 1 - - - - 1 - - - -
France FRCE 0.737 4 2 1 - - - - 3 1 - - 1
FRSA 0.811 5 - - - - - - 2 - - 2 -
FRJF 0.765 6 - - - - - - 5 - - - -
Ireland IECG 0.400 - 4 - - - - - 4 - - - -
IECB 0.643 - 4 - - - - - 4 - - - -
Italy ITVA 0.637 6 - - - - - - 5 - - - -
Montenegro MEDM 0.757 8 - - - - - - 7 - - - -
MEKM 0.807 4 - 1 - - - - 4 - - - -
Norway NOBU 0.727 3 4 - - - 1 - 6 - - - -
NOOS 0.839 - 4 4 - - - - 5 - - 1 -
NOSE 0.839 - - 4 - - - - 4 - - - -
NOTF 0.409 - 3 1 - - - - 4 - - - -
Poland PLBI 0.493 8 - - - - - - 4 - - - -
PLKI 0.582 5 - - - - - - 5 - - - -
PLPZ 0.770 7 - - - - - - 6 - - - -
Scotland SCGG 0.429 - - 4 - - - - 4 - - - -
SCGM 0.529 - 4 - - - - - 4 - - - -
Slovakia SKMP 0.807 4 2 2 - - - - 4 1 - - -
SKNT 0.772 7 - - - - - 1 5 - - - -
SKSR NC 2 - - - - - - 2 - - - -
SKZT 0.763 7 - - - - - - 6 - - - -
Slovenia SIKA 0.755 8 - - - - - - 4 2 - - -
Sweden SEFL 0.517 - 4 3 1 - - - 7 - - - -
SELO 0.435 - 1 7 - - - - 6 - - - -
SERA 0.735 - 3 2 - - - - 1 - - - -
Switzerland CHCH 0.673 6 - - - - - - 6 - - - -
CHVA 0.755 5 - - - - - - 5 - - - -
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common haplotype, Haplotype 1 (red), was found in all
populations with the exception of the EENN population
(Estonia). Only six populations exhibited any within-
population variation (FRCE, FRSA [both France], SIKA
[Slovenia], SKMP [Slovakia], CZKO [Czech Republic]
and NOOS [Norway]) and only the FRCE population
contained more than two haplotypes. The EENN popu-
lation was fixed for Haplotype 3 (blue), which was not
found elsewhere.
No significant linkage disequilibrium was detected
between pairs of microsatellite loci after sequential Bon-
ferroni correction. Between 16 and 30 alleles were
detected at the five loci studied (mean = 20.20) and
levels of expected heterozygosity (HE) calculated for
populations with a sample size of N ≥ 4 ranged from
0.400 (IECG [Ireland]) to 0.839 (NOOS and NOSE
[both Norway]), with a mean value of 0.677 (Table 3;
Figure 4). The STRUCTURE analysis of the microsatel-
lite data indicated that the most likely number of
genetic clusters was K = 2 (Figure 5).
M. hypopitys phylogeography
The 320 bp chloroplast rps2 alignment contained seven
distinct haplotypes (Table 4; Figure 6; GenBank
sequence accession numbers HQ864700-HQ864706).
The two most common haplotypes, Haplotypes 1 and 2
(depicted in blue and yellow), exhibited a largely east-
west split. Only four populations exhibited any within-
population variation (ATKA [Austria], SIDO [Slovenia],
RORM and ROVG [both Romania]) and of these, only
the RORM population contained more than two
haplotypes.
The 287 bp nuclear ITS alignment contained three
distinct haplotypes (Table 4; Figure 7; GenBank
sequence accession numbers HQ864707-HQ865709).
The distribution of these haplotypes was broadly con-
gruent with that of the chloroplast rps2 haplotypes.
Only the CHCH (Switzerland), SIDO (Slovenia), SKNT
(Slovakia) and ROVG (Romania) populations exhibited
Figure 2 Geographical distribution of O. secunda chloroplast
trnS-trnG haplotypes. Pie chart sizes are approximately
proportional to sample size, with the smallest circles representing
N = 1 and the largest representing N = 8. Inset shows the
phylogenetic relationships between the seven haplotypes. Small
black circles represent unique haplotypes i.e. those found in a single
individual. The population of origin of each unique haplotype is
indicated.
Figure 3 Geographical distribution of O. secunda nuclear ITS
haplotypes. Pie chart sizes are approximately proportional to
sample size, with the smallest circles representing N = 1 and the
largest representing N = 8. Inset shows the phylogenetic
relationships between the five haplotypes.
0.400 – 0.499
0.500 – 0.599
0.600 – 0.699
0.700 – 0.799
0.800 – 0.899
Figure 4 Expected heterozygosity (HE) in O. secunda
populations based on five nuclear microsatellite loci. Circle sizes
are indicative of level of HE (see inset).
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any within-population variation, with all three haplo-
types being found in the SIDO population.
No significant linkage disequilibrium was detected
between pairs of microsatellite loci after sequential Bon-
ferroni correction. Between 10 and 22 alleles were
detected at the eight loci studied (mean = 15.125) and
levels of expected heterozygosity (HE) calculated for
populations with a sample size of N ≥ 4 ranged from
0.370 (IEST [Ireland]) to 0.750 (CHCH [Switzerland]),
with a mean value of 0.629 (Table 4; Figure 8). The
STRUCTURE analysis of the microsatellite data indi-
cated that the most likely number of genetic clusters
was K = 2 (Figure 9).
Discussion
It is now apparent that phylogeographic inferences
based on a single, non-recombining marker can be mis-
leading [48,49]. Consequently, phylogeographic studies
Figure 5 Assignment of O. secunda populations to K = 2
clusters based on STRUCTURE analysis of the nuclear
microsatellite data.
Table 4 Diversity statistics for M. hypopitys populations
Country Code HE cpDNA haplotype ITS haplotype
1 2 3 4 5 6 7 1 2 3
Austria ATKA NC 1 - 1 - - - - - 2 -
Czech Republic CZPO NC 1 - - - - - - 1 - -
England ENPE 0.624 - 6 - - - - - 6 - -
Estonia EEJO 0.690 - 6 - - - - - - 6 -
EEPO 0.573 7 - - - - - - - 8 -
Ireland IEEL 0.500 8 - - - - - - 7 - -
IEST 0.370 8 - - - - - - 7 - -
Poland PLCL 0.516 - - 8 - - - - 7 - -
PLLG 0.716 - 8 - - - - - - 8 -
PLKN 0.740 - 8 - - - - - - 8 -
Romania RORM 0.731 - 4 - 1 1 1 1 - 8 -
ROVG 0.710 3 - - 1 - - - 3 1 -
Slovakia SKMP NC 2 - - - - - - 2 - -
SKNT 0.682 4 - - - - - - 3 1 -
Slovenia SIDO NC - - 1 1 - - - 1 1 1
SISV 0.530 8 - - - - - - 8 - -
Sweden SERA 0.674 - 3 - - - - - 4 - -
Switzerland CHCH 0.750 5 - - - - - - 4 - 1
Figure 6 Geographical distribution of M. hypopitys chloroplast
rps2 haplotypes. Pie chart sizes are approximately proportional to
sample size, with the smallest circles representing N = 1 and the
largest representing N = 8. Inset shows the phylogenetic
relationships between the eight haplotypes. Open diamonds
represent missing haplotypes.
Figure 7 Geographical distribution of M. hypopitys nuclear ITS
haplotypes. Pie chart sizes are approximately proportional to
sample size, with the smallest circles representing N = 1 and the
largest representing N = 8. Inset shows the phylogenetic
relationships between the three haplotypes. Open diamonds
represent missing haplotypes.
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are increasingly using multiple genetic markers and/or
palaeodistribution modelling to draw more reliable
inferences on population history. The results of the
paleodistribution modelling and the patterns of genetic
variation revealed by the phylogeographic analyses sug-
gest that both Orthilia secunda and Monotropa hypop-
itys persisted throughout the LGM in Europe in
southern refugia. Although both species generally exhib-
ited a “southern richness vs. northern purity” distribu-
tion of genetic variation [21], this was more pronounced
in the temperate M. hypopitys, where the only popula-
tions that displayed any within-population genetic varia-
tion for both the chloroplast rps2 and nuclear ITS
regions were located closest to the modelled refugial
areas. Northern populations of O. secunda were more
diverse, but the signatures of refugial areas i.e. high
diversity coupled with unique haplotypes [27] were
restricted to southern populations.
Based on the weight of evidence across modelling and
the different markers used, our findings indicate a possi-
ble refugial area for O. secunda in Europe located in the
vicinity of the French Alps. A second area of high diver-
sity and endemic haplotypes included the Austrian Alps
and Slovakia, but these populations lie outside the suita-
ble climate envelope indicated by the palaeodistribution
model. Nevertheless, although the precise locations of
putative refugia are difficult to identify accurately, it is
clear that the majority of genetic diversity is contained
in southern populations. The occurrence of a fixed
endemic ITS haplotype in one of the Estonian popula-
tions (EENN) more likely represents a relatively recent
mutation that has become fixed through genetic drift,
rather than indicating an extreme northern refugium.
For M. hypopitys, the modelling and genetic data both
indicated a likely refugial area in southeastern Europe.
The identification of two genetic clusters with a broadly
northern/eastern vs. southern/western geographical dis-
tribution for both species based on microsatellite data
could indicate isolation in separate refugia followed by
differential recolonization after the retreat of the ice
[24].
Many studies have used modelling approaches to
determine the effects of present and future climate
change on the distribution ranges of plant species (e.g.
[50-52]). We can extend this approach to investigate the
potential effects of such distribution changes on intras-
pecific genetic diversity. The future modelled distribu-
tions of both O. secunda and M. hypopitys indicate
substantial changes in the ranges of both species. For
M. hypopitys in particular, these changes could have a
profound impact on the genetic diversity of the species
in Europe. Previous studies have suggested that range
contraction during previous phases of climate change
was characterized by population extinction, rather than
migration [6,53]. Although the future model indicates a
range expansion at the northern edge, it also suggests
extensive loss of suitable habitat in southeastern Europe.
Given that this area represents the centre of genetic
diversity for the species, extinction of these populations
would lead to massive loss of genetic diversity since
more northerly populations are genetically depauperate
relative to populations in the southeast. A northern
expansion of the species’ range would not counter this,
because the leading edge colonization would be from
these low-diversity northern populations. Northern
populations of O. secunda, however, tended to be more
genetically diverse than those of M. hypopitys.
0.300 – 0.399
0.400 – 0.499
0.500 – 0.599
0.600 – 0.699
0.700 – 0.799
Figure 8 Expected heterozygosity (HE) in M. hypopitys
populations based on five nuclear microsatellite loci. Circle sizes
are indicative of level of HE (see inset).
Figure 9 Assignment of M. hypopitys populations to K = 2
clusters based on STRUCTURE analysis of the nuclear
microsatellite data.
Beatty and Provan BMC Evolutionary Biology 2011, 11:29
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Consequently, the loss of southern and central European
O. secunda populations indicated by the species distri-
bution model would not have the same overall effect on
total intraspecific genetic diversity across the continent.
Nevertheless, although the populations from the species’
centres of diversity in the French and Austrian Alps
would still lie within the future modelled climate envel-
ope, this would most likely be as a result of altitudinal
migration, since the mountain ranges of southern and
eastern Europe represent the only climatically suitable
areas in the region. Whilst altitudinal migration offers
some short-term potential for countering the effects of
climate change [54-57], its scope is ultimately limited
[58]. The situation in Europe is somewhat different
from that in North America, where the occurrence of
northern refugia for both species means that a lower
proportion of the total genetic diversity in the continent
is concentrated in southern populations [[34], Beatty &
Provan, unpublished results] and thus the impact of loss
of rear-edge populations might not be as extreme. It
should also be borne in mind that models of future
(and, indeed, past) climate are not guaranteed to be
100% accurate, and that many other factors such as
changes in species tolerances through adaptation and
species-species interactions will also determine species
current and future ranges. Nevertheless, at least in Eur-
ope, the adverse encroachment of human activity on the
boreal and temperate woodlands that form the natural
habitat for these species, coupled with the fact that cli-
mate is changing faster now than at any time in the
past, means that the impacts on the gene pools and sub-
sequent adaptive potential of these, and possibly many
other species, are likely to be potentially serious.
Conclusions
Both Orthilia secunda and Monotropa hypopitys appear
to have persisted through the LGM in Europe in south-
ern refugia. The boreal O. secunda, however, has
retained a larger proportion of its genetic diversity in
more northerly populations outside these refugial areas
than the temperate M. hypopitys. Given that future spe-
cies distribution modelling suggests northern range
shifts and loss of suitable habitat in the southern parts
of the species’ current distributions, extinction of geneti-
cally diverse rear edge populations could have a signifi-
cant effect in the rangewide intraspecific diversity of
both species, but particularly in M. hypopitys.
Acknowledgements
We are extremely grateful to everybody who provided samples for this
project (listed in Tables 1a and 1b). Jan Wieringa (Nationaal Herbarium
Nederland) provided valuable herbarium specimens. Gemma Beatty’s PhD
research is funded by the Department of Agriculture and Rural
Development, Northern Ireland.
Authors’ contributions
Both authors conceived and designed the study. GEB carried out the
laboratory work. Both authors analysed the data and wrote the manuscript.
Received: 4 September 2010 Accepted: 27 January 2011
Published: 27 January 2011
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doi:10.1186/1471-2148-11-29
Cite this article as: Beatty and Provan: Comparative phylogeography of
two related plant species with overlapping ranges in Europe, and the
potential effects of climate change on their intraspecific genetic
diversity. BMC Evolutionary Biology 2011 11:29.
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