Acta Theriol (2014) 59:317–324
DOI 10.1007/s13364-013-0161-x
ORIGINAL PAPER
Habitat preferences in gray marmots (Marmota baibacina)
Věra Pavelková Řičánková & Jan Riegert & Eva Semančíková &
Martin Hais & Alžběta Čejková & Karel Prach
Received: 2 March 2013 / Accepted: 30 July 2013 / Published online: 14 August 2013
# Mammal Research Institute, Polish Academy of Sciences, Białowieża, Poland 2013
Abstract We examined habitat preferences of the Southern
Altai subspecies of gray marmots (Marmota baibacina
baibacina) both at the small and large scale. Considerable differences in habitat use among the gray marmot (sub)species
complex have been described; Marmota kastschenkoi possibly
represents the only forest-dwelling Palearctic marmot. Our results show that habitat use in Southern Altai marmots is determined mainly by vegetation type. The Altai marmots preferred
grasslands and shrublands and their distribution was limited to
the alpine zone above timberline. Marmots clearly avoided
woodlands, even the forest edges and forest-steppe areas with a
tree cover greater than 10 %. Gray marmots occur rarely in
habitats occupied by alpine pikas, whereas presence of ground
squirrels had no effect on marmot distribution. Altai marmots
preferred mesic habitats with permeable subsoil layers.
Livestock grazing and human disturbance did not affect marmot
occurrence. Habitat requirements of examined Altai subspecies
M. baibacina baibacina differ from the forest-steppe M.
kastschenkoi; nevertheless, the ecological factors to which the
forest-dwelling species responds remain to be analyzed. A recent
speciation process in gray marmot complex was followed by the
evolution of ecological requirements resulting in adaptation to
forest dwelling.
Keywords Forest-steppe marmots . Ground squirrels .
Habitat preferences . Marmota baibacina . Pikas
Communicated by: Andrzej Zalewski
V. P. Řičánková (*) : J. Riegert : E. Semančíková : M. Hais :
A. Čejková : K. Prach
Faculty of Sciences, University of South Bohemia, Branisovska 31,
370-05 Ceske Budejovice, Czech Republic
e-mail: [email protected]
Introduction
Habitat use of the burrowing herbivores is usually determined
by vegetation and soil characteristics. Relative importance of
the vegetation structure and soil type in species habitat choice
depends on the scale and varies temporally (e.g., Hoogland
1996; Kinlaw 1999; Wang et al. 2003; Lombardi et al. 2007).
Determining the relationship between the species occurrence
and environmental features is crucial for understanding differences in distributions of closely related species.
The gray marmot (Marmota baibacina Kastschenko 1899)
is considered to occupy the broadest range of habitats among
species of Palearctic marmots (Bibikov 2004). Gray marmots
are found in alpine steppes and meadows of the Altai and TienShan Mountains, in dry steppes of the central Kazakhstan hills,
as well as in woodlands of Southern Siberia (Galkina 1970).
The species inhabits all altitudinal belts from 150 to 3,500 m
above sea level (asl; Galkina 1970).
The range of gray marmots was significantly reduced following the Holocene (Gromov and Erbayeva 1995). Climatic
changes and subsequent habitat fragmentation resulted in
diversification into the three main subspecies of gray marmots, the Altai (M. baibacina baibacina), Tien-Shan
(Marmota baibacina centralis), and forest-steppe marmots
(Marmota baibacina kastschenkoi) (Yudin et al. 1979;
Gromov and Erbayeva 1995). Forest-steppe marmots (M.
baibacina kastschenkoi) are now recognized as a distinct
species M. kastschenkoi Stroganov et Judin 1956 (Brandler
and Lyapunova 2009; Steppan et al. 2011). The gray marmot
complex thus consists of the two subspecies of M. baibacina
and recently derived M. kastschenkoi.
Palearctic marmots are associated with grasslands, except
for M. kastschenkoi which is believed to be the only forestdwelling species (Brandler 2003a; Bibikov 2004). This adaptation may have evolved as a response to changes in the
Holocene landscape, when the cold-steppe was replaced by
forest-steppe vegetation (Brandler 2003a). M. kastschenkoi
318
now occupies steppes as well as broad-leaved and pine forests
of the South Siberian lowland (Galkina 1970; Yudin et al.
1979; Brandler 2003b; Taranenko 2011).
Nevertheless, the Tien-Shan marmot (M. baibacina
centralis) colonies are frequently found in the zone of spruce
forest (Ismagilov 1956). Habitat use of M. baibacina baibacina
has been predominantly examined in the forestless Mongolian
Altai, where the subspecies inhabits steppes and meadows
on mountain slopes and foothills (Rogovin 1992; Brandler
et al. 2010b). Habitat preferences of the Altai subspecies
(M. baibacina baibacina) thus remain unclear with respect to
possible forest dwelling.
Generally, marmot habitat preferences appear to be evolutionary conservative, closely related species tend to occupy
similar environments (Davis 2005). Much of the marmot
intraspecific variation is phenotypic, which may be the optimal solution to living in a variable environment (Armitage
2005). Yellow-bellied marmots (Marmota flaviventris) occupy various habitats from semideserts at low elevations through
woodland and forest openings to the alpine zone (Frase and
Hoffmann 1980). The common feature of these different
habitats is the presence of rocks sufficiently large to provide
shelter (Svendsen 1976).
In the contact zone with the tarbagan (Marmota sibirica),
M. baibacina baibacina are associated with rock outcrops
with bouldery screes (Rogovin 1992; Brandler et al. 2010b).
Many factors were proposed to limit gray marmot distribution:
presence of meadow and steppe vegetation, topographic relief,
permafrost and soil layer depth, or spatially extensive view
sheds (Galkina 1970).
Southern Altai marmots (M. baibacina baibacina) represent the population of from which forest-steppe marmots
(M. kastschenkoi) have evolved during the last 20–12,000 years
(Grosval'd and Kotlyakov 1989; Brandler 2003a, c; Brandler
et al. 2010a). By examining the key factors that influence
habitat use of M. baibacina baibacina in Southern Altai, we
attempt to reveal possible origin of forest dwelling in gray
marmot complex.
We suppose that forest dwelling could be the outcome of
habitat flexibility of gray marmots. Occurrence of gray marmots could be limited by other ecological factor(s) than vegetation and observed differences could result from the ability
to use both forest and steppe habitats according to their
availability. Altai marmots thus would not display preferences
for either vegetation type.
Alternatively, gray marmots could be limited by vegetation
type. Affinity to the forest habitat observed in M. kastschenkoi
could be a result of the general preferences for woodlands
common in the gray marmot complex. In such case, Altai
marmots would display preferences for woodland habitat.
Forest avoidance in the Altai marmots would indicate
a major shift in ecological requirements in forest-dwelling
M. kastschenkoi.
Acta Theriol (2014) 59:317–324
Methods
Study area
The study area is situated in the Altai Mountains in the
Russian Federation on the territory of the Altai Republic along
the borders of Kazakhstan, China, and Mongolia. The area is
between latitudes 49°10′ and 49°55′ N and longitudes 86°50′
and 88°30′ E (coordinate system WGS 84). The region of
study is delimited by the Southern Chuya Range in the north,
the Tarkhata mountain pass in the east, the Ukok Quiet Zone
and the Tabon Bogdo Ula Mountain in the south, and by the
Koksu and Argut River valleys in the west (Fig. 1). Research
was conducted during the summers (July and August) of 2003
through 2005.
The region represents a complete sequence of altitudinal
vegetation zones, including semi-desert, steppe, forest-steppe,
taiga, sub-alpine, and alpine-tundra, although steppe patches
occur as high as the sub-alpine belt. The eastern part of the
area lacks the typical altitudinal pattern of vegetation belts.
Elevations range from 1,200 to 4,120 m asl. The forest line is
at about 2,200 m asl. The area is characterized by grasslands
(cover 47 % of the study area), tall grass and forbs stands
(13 %), woodlands (mostly larch taiga; 11 %), and shrubs
(mostly Betula rotundifolia; 10 %).
The region's climate is strongly continental. The average
July temperature in the Ukok Plateau (2,300–2,500 m asl) is
9.4 °C, whereas the average January temperature is −27 °C
(Kharlamova 2004). Most of the area is underlain by perennial
permafrost; the active thaw layer is usually 30–70 cm thick
(Chlachula 2001).
As with the annual temperatures, rates of precipitation vary
greatly according to the particular topographic setting. Most
of the precipitation falls on the western and northwestern
slopes (400–500 mm per year). The eastern part of the study
area is semi-arid, with a precipitation approximately 200 mm
per year (Kharlamova 2004). Traditional extensive livestock
raising is the major land use.
Data collection
A total of 92 transects were established where terrain topography made it possible at random order. Each transect was
approximately 1 km long. Position of transects to the slope
varied; most of them were established along the elevation
gradient. Along each transect, six square 50×50 m plots were
established at 200-m intervals (following Allainé 1994).
Intervals between plots were measured from the center of
the plots.
During the 3 years of the study, environmental conditions
did not vary substantially. Different places were sampled each
year. The data collection on transects was carried out by a
single person (first author). Each plot was thoroughly checked
Acta Theriol (2014) 59:317–324
319
Fig. 1 Location map of the study
area in the Southern Altai
Mountains, Altai Republic,
Russia. Black circles transects
with gray marmots Marmota
baibacina, open circles transects
without marmots
for the presence of marmot burrows. Sites occupied by marmots were not previously known. Active burrows were differentiated from old and inactive ones by the presence of fresh
soil deposits, feces, and runways (Ricankova et al. 2006).
Only active marmot burrow systems were considered unequivocal detections in the analysis.
The ecological parameters estimated in each plot were
assigned to five groups: (1) environment, (2) management,
(3) vegetation, (4) geology, and (5) other burrowing mammalian herbivores. Environmental features measured at the small
scale included elevation, slope, and orientation (i.e., aspect) as
described in Table 1. At the large scale, we estimated climate
parameters, elevation, and terrain ruggedness (Table 1). The
mean annual temperature and precipitation within the transects were obtained from WORLDCLIM (Hijmans et al.
2004). This database is a set of global climate layers with a
spatial resolution of 1 km2.
Human disturbance sampled at the small scale covers both
direct anthropogenic disturbance and impact of livestock grazing. We recognized three categories of human disturbance—
high, medium, and low. Human disturbance was considered
high when the plot contained evidence of intensive human
activity (i.e., presence of tracks, yurt or chalet(s), and signs of
grazing by domestic livestock), medium when the plot
contained only signs of grazing (without tracks, yurt, or chalet(s)), and low when there was no evidence of human activity
or livestock grazing. Land use category, used at the large scale,
describes the seasonality of pastureland use by domestic livestock (i.e., sheep, goats, cattle, horses, camels, and yaks).
Small-scale vegetation parameters include plant cover,
height of herbs and shrubs, and vegetation units (Table 1).
We defined plant cover as the proportion of the plot covered
by herbs and grasses, shrubs, trees, or by any combination of
these life forms. Coverage of the different life forms is independent of each other and together may constitute more than
100 %. The average height of herbaceous and shrub cover was
divided into three categories reflecting the height of the gray
marmot (ca. 50 cm; Ismagilov 1956).
Vegetation units (Table 1) were delimited using the prevailing growth forms and habitat preference of plant species
(Mueller-Dombois and Ellenberg 1974). We recognized woodland, shrubland, tall grass, and grassland units. Grassland category includes short-grass steppes, short-grass alpine
meadows, and nonwoody vegetation of slope debris and screes.
At the large scale, grasslands were divided to alpine grasslands
above the timberline (~2,000 m asl) and grasslands bellow the
timberline. Tall grass vegetation category includes tall forb and
secondary meadows and vegetation of treeless wetlands.
Woodlands consist of larch taiga and broadleaved vegetation
of alluvial woodlands. Shrubs category includes mostly B.
rotundifolia, Potentilla fruticosa, and Caragana sp. Largescale vegetation units (Table 1) were estimated using land cover
classification from Landsat satellite ETM+ data acquired in
2000 (two scenes, 144/26 and 144/25). Resulting classification
was calibrated using our field knowledge of the area.
Geology variables used at the small scale describe soil type,
subsoil layers, and the relative surface humidity of the
plot (Table 1; for details, see Ricankova et al. 2006). Soil
320
Table 1 Explanatory variables
used to characterize habitat of
Marmota baibacina in Southern
Altai Mountains. The details of
small- and large-scale are described in text
Acta Theriol (2014) 59:317–324
Variable
Environment
Elevation
Terrain ruggedness
Slope
Orientation to cardinal
points
Mean annual temperature
Mean annual
precipitation
Management
Human disturbance
Land use
Vegetation
Herb cover
Bush cover
Tree cover
Vegetation units
Height of herbs
Height of bush
Geology
Soil
Subsoil layers
Relative surface humidity
Other species
Spermophilus undulatus
Ochotona alpina
Steppe pikas
Description
Small
scale
Large
scale
Elevation (in meters above sea level) (limits, 1,231–3,084)
Categorical variable: (1) low, slope<10° without vertical
structures; (2) medium, slope>10° without vertical
structures; (3) high, slope>10° with vertical structures
Average slope (in degrees; limits, 0–45)
Categorical variable: (1) N, (2) NW, (3) NE, (4) S, (5) SW,
(6) SE, (7) W, (8) E
Mean annual temperature (in degree Celsius; limits, −8 °C
to +0.1 °C)
Mean annual precipitation (in millimeters; limits, 185–480)
X
X
X
Categorical variable: (1) low, (2) medium, (3) high
Categorical variable: (0) no grazing, (1) winter grazing, (2)
summer grazing, (3) year-round grazing
X
Areal percentage cover of herbs (nonwoody vegetation;
limits, 2–100 %)
Areal percentage cover of shrubs (woody vegetation <2 m in
height; limits, 0–90 %)
Areal percentage cover of trees (woody vegetation, >2 m tall;
limits, 0–80 %)
Small scale: (1) woodland, (2) shrubland, (3) tall grass
vegetation, (4) grassland
Large scale: (1) woodland, (2) shrubland, (3) tall grass
vegetation, (4) grassland (bellow timberline), (5) alpine
grassland (above timberline)
Average height of nonwoody vegetation. Categorical variable:
(0) <10 cm, (1) 10–50 cm, (3) >50 cm
Average height of woody vegetation <2 m in height.
Categorical variable: (0) absent, (1) <50 cm, (2) >50 cm
X
X
X
X
X
X
X
X
X
X
X
X
Categorical variable: (1) Brunisol, (2) Luvisol, (3) Regosol
Categorical variable: (1) Impermeable subsoil layers, (2)
permeable subsoil layers
Categorical variable: (1) arid, (2) mesic, (3) humid
X
X
Presence or absence of active burrows of S. undulatus within
the plot
Presence or absence of any evidence of O. alpina within the plot
X
Presence or absence of any evidence of Ochotona daurica
and/or O. pallasi burrows within the plot
characteristics were described according to the Expert
Committee on Soil Survey (1987).
The presence of long-tailed ground squirrels (Spermophilus
undulatus Pallas 1778), alpine pikas (Ochotona alpina Pallas
1773), and steppe pikas (Ochotona pallasi Gray 1867 and
Ochotona daurica Pallas 1776) in each plot was recorded to
estimate the possible influence of interspecific competition on
habitat use of marmots. The presence of the other burrowing
herbivores was used for both small and large scale. Populations
of steppe pikas had been extirpated within our study areas a few
X
X
X
X
X
X
years before the start of our research and re-established 3 years
after the end of field research. We included the presence of the
pika burrows in our dataset because of the possibility of past
competition between pikas and marmots.
Data analysis
To avoid autocorrelations of vegetation cover data, we
computed principal component analysis (CANOCO for
Acta Theriol (2014) 59:317–324
Table 2 Factors affecting large
and small scale occurrence of
gray marmots in the Southern
Altai Mountains (GLM analysis,
forward selection, small scale:
n=554 plots, covariate=transect;
large scale: n=92 transects)
M marmot occurrence, V vegetation units, AP alpine pika, SP
steppe pika, T tree cover, H surface humidity, Her height of
herbs, SL subsoil layers
321
Scale
Model
Small scale
Null (M~+1, transect~
random effect)
M~V
Large scale
d.f.
Chi
P
F
2
M~V+AP
M~V+AP+T
M~V+AP+T+H
M~V+AP+T+H+Her
M~V+AP+T+H+Her+SL
Null (marm~+1)
M~V
M~V+SP
Windows software; Braak and Šmilauer 1998, visualized in
CANODRAW; Šmilauer 1992) for both small- and large-scale
data to uncover possible relationships among tested factors
(Table 1). Categorical variables were implemented as supplementary variables.
Percent of explained
variability
5
7.3
33.835
<0.00001
6
7
9
11
12
1
5
6
4.4
2.6
4.1
4.3
2.0
20.541
11.881
19.382
20.124
9.151
<0.00001
0.00057
<0.00001
<0.00001
0.00249
33.9
4.0
<0.000001
<0.05
10.773
5.103
On small scale, we found that bush cover and tree cover
were correlated. Bush cover variable was therefore removed
from further analyses. We selected tree cover because we
wanted to examine its possible ecological importance for
marmots. On large scale, the land use was correlated with
Fig. 2 Percentages of habitat categories of gray marmots Marmota baibacina in the Southern Altai Mountains. White bars percentage of habitat
categories, black bars percentage of each habitat category used by marmots
322
elevation. Therefore, we excluded land use from further largescale analyses.
We analyzed the preferences of gray marmots using R
software (R Development Core Team 2008). Small-scale data
were computed with linear mixed effect model with
random effects under formula: model <−lmer (marmot
occurrence~+factors+(1|transect)+(1|year), family=binomial,
data=file name), where transect and year were defined as
random effect. The factor transect was used to avert the occurrence of spatial autocorrelation. Forward selection was
performed manually by repeated comparing the null (or last)
model with other possible models using ANOVA function and
Akaike's An Information Criterion (AIC). This enabled us to
define the best final model. Large-scale data were computed by
generalized linear models (GLM) with logit–link function under formula: model <−glm (marmot occurrence~+factors,
family=binomial, data=file name), using factor year as a covariate. Forward selection was computed using step function
with AIC. Both the models were finished when no other
variables were recommended by AIC. Therefore, we show only
factors with significant effect on marmot occurrence. Factors
used for each analysis are shown in Table 1. Elevation data
used for the large-scale analysis represent the mean value of the
different plots of each transect (Table 1).
We plotted the used/available percentage within each habitat category on the small scale for the purpose of data visualization. These percentages were computed as the number of
plots where marmots occurred divided by the total number of
plots with this type of habitat. The ratio was converted to
percentages. The relationships between the proportions of
category use and category availability were expressed by
Manly's standardized selection ratio Bi with 95 % confidence
intervals (Manly et al. 2002).
Results
Evidence of marmot habitation was detected in 42 (45.6 %) of
the 92 transects and in 111 (20 %) of the 554 plots investigated. Nine abandoned burrow systems were not included in our
analyses.
At small scale, vegetation type explained most of the variability of marmot occurrence (Table 2). Marmots preferred
grasslands (Bi =0.6091; 95 % CI, 0.3758–0.8424). Lower preferential coefficient was found also for shrubs (Bi =0.1690; 95 %
CI, 0.0459–0.2921) and they clearly avoided woodlands
(Fig. 2a). Marmots also preferred sites where alpine pika was
absent (Fig. 2b; Bi = 0.8330; 95 % CI, 0.6403–0.1026).
Simultaneously, marmots were present almost exclusively on
sites with tree cover up to 10 % (Fig. 3c; Bi =1.0000; 95 % CI,
1.000–1.0000), permeable subsoil layers (Fig. 2d; Bi =0.9894;
95 % CI, 0.9748–1.0039), and mesic humidity (Fig. 2e;
Bi =0.7190; 95 % CI, 0.4904–0.9476). Finally, the marmots
Acta Theriol (2014) 59:317–324
Fig. 3 The projection scores of the significant large-scale data variables
of gray marmot habitat use. Principal component analysis, I and II
canonical axes explain 91.4 % of variability. Black circles vegetation
categories, triangles presence (plus sign) or absence (minus sign) of gray
marmots and steppe pikas
preferred height of herbs between 10 and 50 cm (Fig. 2f;
Bi =0.7190; 95 % CI, 0.4904–0.9476). None of the other environmental factors influenced marmot habitat use.
On large scale, marmot distribution was significantly affected by the vegetation category of the transect (Table 2).
Marmots preferred alpine grassland (Bi =0.5576; 95 % CI,
0.7738–0.34145) and shrub vegetation (Bi =0.4424; 95 %
CI, 0.6587–0.2262). Marmots did not occur in woodland, tall
grass vegetation, and grassland below the timberline (Fig. 3).
Occurrence of steppe pikas was also significantly linked to
that of marmots (Table 2). Pikas invariably shared their habitat
with marmots, but the number of recorded transects with
steppe pika burrows was very small (n=6 transects of 42 total
transects occupied by marmots; Bi =0.7049; 95 % CI, 0.4167–
0.9932). Both marmots and steppe pikas were absent from 50
transects. Occurrence of the long-tailed ground squirrels or
alpine pikas did not affect marmot habitat utilization. Terrain
ruggedness, mean annual temperatures, mean annual precipitation, altitude, and presence of other burrowing herbivores
did not influence marmot habitat use.
Discussion
Our results show that the habitat use of gray marmot in
Southern Altai is influenced mainly by vegetation type. The
Altai marmots prefer grasslands and shrublands of the alpine
Acta Theriol (2014) 59:317–324
zone, avoid forests and tall grass vegetation, and their distribution is limited to the alpine zone above timberline.
Altai marmots clearly avoided coniferous taiga forests and
the broadleaved vegetation of alluvial woodlands as well.
They even avoided the forest edges and forest-steppe areas
with a tree cover greater than 10 %. Similar preferences were
found in the Alpine marmot (Allainé 1994; Lopez et al. 2010).
M. marmota is found in nearly all types of vegetation above
the timberline. The complexity of vegetation is very important
for the Alpine (Müller 1992) and Altai marmots (Galkina
1970) favoring mosaics of meadow-steppe vegetation found
particularly on the Ukok Plateau.
Habitat requirements of the other (sub)species of gray
marmot complex seem to differ from the examined population
from Southern Altai Mts. M. kastschenkoi occupies coniferous
and broadleaved forests, tolerating high vegetation cover and
spatially limited view sheds (Yudin et al. 1979). Galkina
(1970) documented a marmot settlement in a pine forest with
dense shrubs and herbaceous vegetation reaching a height of
2 m. Nevertheless, key ecological factors to which M.
kastschenkoi responds remain to be analyzed.
In contrast to the examined population of M. baibacina
baibacina, the Tien-Shan subspecies (M. baibacina centralis)
occurs also in a spruce forest zone (Ismagilov 1956).
However, it is not known whether M. baibacina centralis
truly occupies forests or are restricted to grassland patches in
the forest zone.
The differences in the use of steppe or forest habitat probably result from different evolutionary history of the
(sub)species and consequent specialization to different habitats. The recent origin of the forest dwelling in gray marmot
complex is rather unexpected because of the trend of related
marmot species to occupy similar environments (Davis 2005).
Moreover, the sister species of the gray marmot is Marmota
bobac, a species associated exclusively with a steppe habitat
(Steppan et al. 2011; Bibikov 2004).
The examined population of the gray marmot complex
display habitat requirements characteristic for a mountain
steppe species. Besides their general preference for grasslands,
Altai marmots seem to prefer similar habitat as steppe pikas
(mostly O. daurica; Tupikova 1989) on the large scale.
Abandoned burrows of steppe pikas were found solely on
the Ukok Plateau, an area occupied by the largest marmot
population. Unfortunately, the number of recorded transects
with steppe pikas was too low to allow any further conclusions. On the other hand, Altai marmots occur rarely in
habitats occupied by alpine pikas (O. alpina). The alpine pikas
are found mostly in the talus and less in taiga forests
(Tupikova 1989); both these habitats were not favored by gray
marmots.
Gray marmots seemed to be constrained in their habitat
choice by soil humidity, a permeability of subsoil layers
reflecting soil insulation quality, permafrost depth, and possibly
323
also the concentration of respiratory gasses in burrows. Better
drainage and reduced humidity are expected to increase soil
aeration preventing the formation of permafrost, decreasing
CO2 concentration in the burrow atmosphere, and may also
increase the insulation quality of the hibernacula (Burda et al.
2007). Similarly, Marmota monax burrow occurrence is closely
associated with a specific “sandy loam” soil and a Marmota
himalayana settlement was found exclusively in a deep layer of
light soil (Moss 1940; Nikol'skii and Ulak 2006).
Our results show that vegetation is the most important
factor determining gray marmot habitat use despite the pronounced differences in the vegetation categories occupied by
the other (sub)species. Recent speciation process in gray
marmot complex was probably followed by the evolution of
ecological requirements, resulting in adaptation to forest
dwelling. Further research of habitat requirements in M.
baibacina centralis and M. kastschenkoi would help to clarify
the observed pattern.
Acknowledgments We are grateful to Yurii V. Antaradonov, Prof. Yurii
V. Tabakaev, and Dr. Albert Kamenov for granting permission to work in
a frontier zone and for logistic support. We thank all expedition participants for their help with transect recording, guides for assistance, and our
horses for their exceptional patience and endurance. Thanks to Jiri
Chlachula for the estimation of geological parameters and organization
of expeditions. Oleg Brandler kindly provided fundamental literature and
Zdenek Fric created the location map. We thank Radim Sumbera, Erik
Beever, Jan Zrzavy, Petr Smilauer, and anonymous referees for helpful
suggestions to the earlier versions of the manuscript. This research was
supported by the Czech Ministry of Education (MSM 6007665801,
MSTV Podpora 2003), the Czech Literary Foundation and Czech Science
Foundation #P504/11/0454.
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