Figure S1 (a) The chloroplast haplotype network of Callitris

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Figure S1
(a) The chloroplast haplotype network of Callitris columellaris species complex, reconstructed by
median joining network method using NETWORK v. 4.6.0.0 [1] with C. endlicheri (GenBank:
AB723699) as an outgroup. The size of the circles in the haplotype network is proportional to the
haplotype frequency, and missing haplotypes are indicated by rectangles. (b) The neighbour-joining
tree of the twelve genetic clusters were estimated by STRUCTURE v. 2.3 [2] based on nuclear
EST-SSR genotype data. The circle size is proportional to the expected heterozygosity of each
cluster. The colours used in the network and tree match those in figure 2.
(a)
(b)
C. endlicheri
10 steps
0.01
Figure S2
The log-likelihood of the data L(K), and the second-order rate change of L(K) (ΔK) [3] are plotted
against the number of genetic clusters (K) assumed in the STRUCTURE analysis [2]. Although ΔK
showed a clear peak at K=2, its clustering pattern was too simple to even delineate any
morphological species, and not consistent with the structure in the distance-based network in figure
2c. On the other hand, the L(K) increased consistently with increasing number of clusters and
reached a plateau around K=10–15. The distribution of the individual trees assigned to given clusters
in K=10–15 was geographically structured, which was compatible with both the nuclear genetic
structure estimated by the distance-based network and chloroplast DNA haplotypes (figure 2a).
Among the plausible number of genetic clusters, we consider K=12 to be the smallest K that can
capture most of the structure in the data and which seemed biologically sensible [4], because further
clustering of K>12 made little change to the overall genetic structure.
Figure S3
Geographic distribution of the summary statistics used in the demographic analysis based on nuclear EST-SSR markers [(a) mean number of alleles across
loci (Na), (b) expected heterozygosity (He), (c) mean allele size variance across loci (VAR) and (d) mean M index across loci (MGW)]. The distribution of
the species complex is indicated by light-grey colour shading.
(a)
(b)
He
Na
0.21 - 0.25
0.25 - 0.29
0.29 - 0.32
1.70 - 2.12
2.12 - 2.53
2.53 - 2.95
0.32 - 0.36
2.95 - 3.37
0.36 - 0.40
3.37 - 3.78
0.40 - 0.44
3.78 - 4.20
(c)
(d)
MGW
ASV
0.80 - 1.68
1.68 - 2.56
2.56 - 3.45
3.45 - 4.33
4.33 - 5.21
5.21 - 6.10
0.54 - 0.62
0.62 - 0.69
0.69 - 0.77
0.77 - 0.85
0.85 - 0.92
0.92 - 1.00
Figure S4
Geographic distribution of the median value of log-transformed ratio of population size (NC / NA) in
the demographic analysis based on nuclear EST-SSR markers. The population size change ratio is
proportional to the size of circle, and the colour of circles are conditioned by the selected
demographic scenarios (light blue: “reduction”, white: “no change” or “indecisive”, and pink:
“expansion”). The interior arid zone is indicated by light-grey colour blobs.
Population size
change ratio
0.2
1.0
3.0
10.0
Figure S5
The results of demographic analyses for pooled population data using an Approximate Bayesian
Computation method implemented in DIYABC-v1.0.4.46beta [5]. (a) Population size change ratio
for pooled populations (red: mostly arid, blue: monsoon tropics, gray: mostly temperate). (b)
Converted time parameters for the populations in which the stable scenario was not rejected. The
two broken gray lines represent the time envelopes when generation time was assumed as its
minimum (20 years) and maximum (70 years), respectively. (c) Posterior distribution of the effective
population size for each population group (black: NC, gray: NA). The broken line shows prior
distribution. Population groups which showed significant deviation from “size change scenario” are
indicated by asterisks.
Figure S6
The results of demographic analyses for pooled population data using a Bayesian method
implemented in msvar1.3 [6]. (a) Population size change ratio for pooled populations (red: mostly
arid, blue: monsoon tropics, gray: mostly temperate). (b) Converted time parameters for the
population. The two broken gray lines represent the time envelopes when generation time was
assumed as its minimum (20 years) and maximum (70 years), respectively. (c) Posterior distribution
of the effective population size for each population group (black: NC, gray: NA). The broken line
shows prior distribution. Note that MCMC chains did not converge for one population group [Ccol
(EC)], as indicated by asterisk.
Figure S7
Population size change ratio of the ten replicated data sets simulated under a demographic scenario
of 10× population expansion. The black and gray lines respectively represent the density estimates
using an Approximate Bayesian Computation method implemented in DIYABC-v1.0.4.46beta [5]
and a Bayesian method implemented in msvar1.3 [6]. The vertical broken line shows the expected
change ratio [log10(10) = 1.0].
References
1.
Bandelt H.J., Forster P., Rohl A. 1999 Median-joining networks for inferring intraspecific
phylogenies. Mol Biol Evol 16(1), 37-48.
2.
Pritchard J.K., Stephens M., Donnelly P. 2000 Inference of population structure using
multilocus genotype data. Genetics 155(2), 945-959.
3.
Evanno G., Regnaut S., Goudet J. 2005 Detecting the number of clusters of individuals using
the software STRUCTURE: a simulation study. Mol Ecol 14(8), 2611-2620.
4.
Pritchard J.K., Wen X., Falush D. 2009 Documentation for structure software: Version 2.3.
http://pritchbsduchicagoedu/structure_software/release_versions/v232/structure_docpdf.
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Cornuet J.M., Santos F., Beaumont M.A., Robert C.P., Marin J.M., Balding D.J., Guillemaud T.,
Estoup A. 2008 Inferring population history with DIY ABC: a user-friendly approach to
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Bayesian
computation.
Bioinformatics
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2713-2719.
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Storz J.F., Beaumont M.A. 2002 Testing for genetic evidence of population expansion and
contraction: An empirical analysis of microsatellite DNA variation using a hierarchical
Bayesian model. Evolution 56(1), 154-166.
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