Supporting Information
Materials and Methods
Multiplex PCR Amplification, Cloning and Sequencing
The first step PCR consisted of: 3,2 µl MgCl2 (25 mM), 2 µl BSA (10 mg/ml), 2 µl AmpliTaq Gold
buffer, 0,2µl dNTPs (25 mM each), 0,4 µl AmpliTaq Gold (5u/µl), 3 µl Primer mix (1 µM each); 5 µl
template and water were added to a final volume of 20 µl. PCRs were run under the following
conditions: 94 C for 1 min followed by 30 cycles of 94 C for 20 s, 56 C for 30 s, 72 C for 30 s and a
final extension step of 72 C for 4 min. We subsequently added 5 µl of a 1/50 dilution of the first step
PCR as template to the second step PCR. Second step PCR: 3,2 µl MgCl2 (25 mM), 2 µl BSA (10 mg/
ml), 2 µl AmpliTaq Gold buffer, 0,2 µl dNTPs (25 mM each), 0,05 µl AmpliTaq Gold (5u/ µl), 3 µl
Primer mix ( 10 µM each); water was added to a final volume of 20 µl. PCR conditions: 94 C for 9 min
followed by 30 cycles of 94 C for 20 s, 56 C for 30s, 72 C for 30 s and a final extension step of 72 C
for 4 min.
All PCR products for the 32 individuals that gave successful amplifications were cloned using the
Invitrogen TOPO TA cloning kit following the manufacturer’s protocol. From each cloned PCR
product between 3 and 8 white colonies were picked. Colonies were picked with a pipette tip and
dissolved in 30 µl of double distilled water. Colonies were lysed by heating the cells for 10 min at 95 C.
Cell lysates were amplified with M13 primers using the following PCR protocol: 4 µl MgCl2 (25 mM),
4µl 10xPCR buffer, 0,5 µl dNTPs (25 mM each), 1 µl Taq polymerase, 1 µl M13 primers(10 µM
each); 3 µl cell lysate and water were added to a final volume of 40 µl. Cycling conditions consisted of
94 C for 5 min followed by 40 cycles of 94 C for 30 s, 55 C for 45 s, 72 C for 45 s and a final extension
step of 72 C for 10 min. Colony PCR products were cleaned with a Qiagen kit following the
manufacturer’s protocol, cycle sequenced and analyzed on an ABI 3730 sequencer.
Ecological Niche Modeling
Species occurrence records
Geo-referenced records from GBIF and its thematic nodes such as MaNIS yielded a small set of
records even when geo-referencing records according to best practices (Chapman et al., 2006). Thus,
we used additional resources in order to enhance the number of records available for modeling. The
first resource is the Biological Inventory of the World’s Protected Areas from U.C. Davis
(http://www.ice.ucdavis.edu/ bioinventory/bioinventory.html). Centroids of protected areas containing
both collared lemmings and narrow-skulled voles were calculated, along with radius uncertainty. The
second resource was the Siberian Museum and collection (http://szmn.sbras.ru/indeng.htm) that
includes a number of specimen records for both species, including localities. Those records that could
be unambiguously located were also included in this analysis, although shifting place names in Siberia
meant that only a subset of records could be geo-referenced. We also utilized records of the collared
lemming from Wickström et al. (2003) and Prost et al. (2010).
Modeling parameters, masking and validation
Because the default settings in Maxent have been shown to be inferior to tuned settings in simulations,
we used a model selection process recently incorporated into the software program ENMTools (Warren
et al., 2008, Warren et al., 2010) to determine the best regularization parameter values. We tested beta
regulation values of 1, 2, 3, 4, 5, 6, 7, 8 and 9 in Maxent, and used output suitability scores, occurrence
data and lambda values to calculate AIC and BIC values to determine the best models. We also used
the “clamping” setting to determine non-analogous climates in the past and future. For all other
parameters, the Maxent default settings for model construction were used. Results of model selection
are presented in the main text. To optimize models, we limited the spatial extent of present-day
predictions to avoid including regions where the species is absent for reasons other than unsuitable
conditions in terms of the environmental variables used in modeling (Anderson &
Raza, 2010,
Peterson et al., 2011). Thus, present-day ENMs were developed within a mask bounded by 24º N, and
84º N for the Holarctic collared lemming, and a mask bounded by 50º E, 150º E, 36º N, and 80º N for
the narrow-skulled vole, with all projected models developed within a mask bounded by 24º N, and 84º
N. Model testing included calculating AUC scores (reported in the main text) and comparing model
results to an independent dataset of fossils collated from multiple sources. We only considered fossils
found between 44-20kya, which borders the time periods of maximum glacial extent in the Holarctic
and
Nearcitc.
Sources
of
localities
and
dates
were
from
the
NOW
fossil
database
(http://www.helsinki.fi/science/now/) and from the literature (including (Borodin et al., 2011, Guthrie,
1968, Houmark-Nielsen, 1999, Khenzykhenova, 2008, Musil, 2010, Ponomarev et al., 2012).
We also checked how close range centroids aligned between the Bioclim and Maxent results for the
present. We did so by first converting our raster results to polygons and then calculating the centroid
for the polygon(s) that contained species occurrences. . That is, we excluded disjunct polygons that
lacked evidence of species presences in this calculation. We did not examine results in the past or
future for two reasons. First, Bioclim and Maxent set different masking extents when projecting into
the past or future. Second, the results in the present capture the key differences between approaches in
terms of niche space calculation, probability of occurrence and thresholds.
Results
Approximate Bayesian Computation performance for the narrow-skulled vole
We carried out a leave-one-out cross validation to test if in principle we should be able to distinguish
between the proposed models given our data (see Table S6). In general, we have to note that
mitochondrial data, being a single genetic locus has limited power to infer complicated demographics
(models). However, here, we proposed and tested only simple models. The analysis shows an overall
sufficient discrimination power between models. However, we found some ambiguity in the
assignments, which will be discussed below.
We were not always able to infer the constant size model as the best supported one, which is not
unexpected since our ancient increase models include wide priors (which allow for an almost constant
demography). This result implies that our approach cannot unambiguously discriminate between a
constant population size model and one with a weak population increase. However, the constant size
model was inferred as the best model in 556, 565 and 579 iterations out of 1000 runs for the tolerance
levels of 0.03, 0.06 and 0.12, respectively, while 290, 300 and 301 iterations were wrongly assigned to
the ancient increase model and 149, 131 and 119 to the ancient increase with subsequent bottleneck
model, which shows that given our data the distinction between these models and the constant size
model can be difficult. In a similar vein, we were not always able to distinguish between the two
bottleneck scenarios. However, this does not influence our inference, given the weak support of these
two models. The ancient increase model was inferred as the best supported model in almost all of its
cross-validation iterations (874, 892 and 899 out of 1000 iterations), which supports our empirical
model selection result. This shows that our approach should have enough power to reliably infer this
model as the best supported model. The ancient increase with subsequent bottleneck model showed a
similar support as the constant population model with a support slightly over 500 of the iterations (535,
534 and 523) and confusion with the constant size (215, 211 and 218) and the ancient increase model
(214, 216 and 221).
Results of validation of models using fossils and comparison of modeling methods.
6/8 of collared lemming and 9/12 of narrow-skulled vole fossil localities were located in suitable
habitats based on paleoclimate modeling and considering the more relaxed thresholds (see Supporting
Figures S6 and S7). The models for the narrow-skulled vole in particular appear to under-predict the
geographical distribution of the taxon in Western Europe at the height of the last glaciation. These
results may reflect environmental and biological complexities such as locally adapted variants that
have gone extinct, the existence of cryptic, microclimatic refugia, or declining sink populations in
marginal habitats. However, methodological explanations cannot be excluded, including issues with
the temporal precision of the fossil material, the exact concordance between the ages of the fossils and
the paleoclimatic reconstructions in a rapidly fluctuating late Pleistocene environment, and uncertainty
in the paleoclimatological models themselves. We do note, though, that the models still both perform
fairly well. Other modeling strategies that would use all the specimens, including fossils, and their
associated contextual climatological data, are another option we did not pursue due to uncertainties
with temporal precision and paleoclimate modeling. Further modeling approaches are certainly well
worth exploring.
We found that geographical centroids for Maxent and Bioclim results in the present were very similar
especially given that both species geographic ranges extend over millions of square kilometers. For the
narrow-skulled vole the results show very close alignment with a centroid latitude and longitude of
52.9N, 100.72E for Maxent results and 52.92N and 99.95E for Bioclim, representing an offset of 52km
between the two models. For the collared lemming, the results are 69.45N, 111E for Maxent and
70.48N, 116.5E for BioClim, representing an offset of 239 km. Bioclim, as expected tends to overfit
models leading to less suitable overall habitat, likely explaining centroid offsets and overall overlap.
Supporting Figure Captions
Figure S1: Discriminant Analysis of Principal Components (DAPC) analysis of the Ural samples
for the narrow-skulled voles. Plot of the first two principal components obtained in the DAPC
analysis considering the three groups: 1) Southern (red) , 2) Middle (green) and 3) Northern Ural
(blue) samples. Label numbers are shown at the center of dispersion for each cluster, delineated by
ellipses. Dots represent individuals.
Figure S2: Spatial statistical parsimony haplotype network. The colors correspond to the respective
geographical regions: (blue) samples from Northern Ural, (green) Middle Ural and (red) Southern Ural.
Haplotypes are represented by ellipses. The number of sequences sharing the same haplotype is
indicated by the numbers (only numbers greater than one are shown). White ellipses correspond to
haplotypes found in the entire sampling, but not the particular location. Two haplotypes are connected
by a line if they are separated by one mutation, each additional mutation is indicated by a small black
dot. Shared haplotypes between locations are connected by two vertical lines.
Figure S3: Cross-validation plots for the model selection using tolerance levels of 0.03 (a) and
0.06 (b) and 0.12 (c). A total of 1000 iterations per model were chosen for cross-validation. M1:
constant population size, M2: bottleneck, M3: bottleneck with subsequent exponential increase, M4:
ancient increase and M5: ancient increase with subsequent bottleneck. The colors range from dark
(Model 1) to light (Model 5).
Figure S4: Posterior distributions for the parameters inferred in the ABC analysis. (a) female
effective population size, (b) expansion timing (years), (c) expansion intensity and (d) mutation rate
(%/bp/Myrs). Distributions for the prior are shown as doted lines, the distribution of the rejection and
the non-linear regression method are shown in black and red, respectively.
Figure S5: Ecological Niche Models for the LGM for the collared lemming, including known
occurrences. Red dots indicate LGM coordinates for occurrences of the collared lemming.
Figure S6: Ecological Niche Models for the LGM for the narrow-skulled vole, including known
occurrences. Red dots indicate LGM coordinates for occurrences of the narrow-skulled vole.
Figure S7: Scatterplot showing annual mean temperature and precipitation values for each
sampled species occurrence used in niche modeling for the collared lemming and the narrowskulled vole. Although both taxa are found in very cold conditions, the narrow-skulled vole is clearly
found across a much broader range of temperatures than the collared lemming. Based on permutation
tests both mean temperature and precipitation are important contributors to the niche model results.
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