Plant Ecology & Diversity
Vol. 1, No. 2, November 2008, 197–207
A bridge or a barrier? Beringia’s influence on the distribution and diversity of tundra plants
TPED
Eric G. DeChaine*
Of bridges and barriers in Beringia
Department of Biology, Western Washington University, Bellingham, USA
(Received 13 December 2007; final version received 4 April 2008)
Background: Evidence strongly suggests that Beringia was a refugium for tundra taxa throughout the Quaternary (the last 2
million years). However, the genetic consequences of the repeated formation and flooding of the Bering Land Bridge
remain uncertain.
Aims: The goal of this paper was to determine the role that the unique environmental history of Beringia played in the
diversification of tundra flora.
Methods: I adopted a comparative coalescent approach to test models of divergence for arctic flora within Beringia. The
literature was surveyed for phylogeographic studies that sampled broadly across the region and incorporated molecular
markers appropriate for coalescent analyses. Of the 13 possible taxa, only two fit these criteria: Saxifraga oppositifolia
(Saxifragaceae) and Vaccinium uliginosum (Ericaceae). Observed gene trees were compared with a distribution of trees
simulated under neutral coalescence to test models of population divergence. Population models fell within two major
categories reflecting the importance of either the Bering Land Bridge or the Bering Sea dispersal barrier on the distribution
of genetic diversity in the species.
Results: Both species fit ‘bridge’ models, but S. oppositifolia supported a model of eastward migration while V. uliginosum
fits a unified Beringia refugium model. The evolutionary implications of these findings are discussed.
Conclusions: The limited number of studies emphasises the need for more sequence-based research in the region. This will
help resolve the history of the Beringia tundra ecosystem, which has important implications for the diversification of tundra
flora, the history of Beringia, and the potential consequences of climate change on the distribution of biological diversity.
Keywords: comparative phylogeography; coalescence; arctic refugia; Bering Land Bridge; Quaternary climate cycles
Introduction
By repeatedly redefining the geographic distribution of
continental ice sheets, mountain glaciers, land bridges,
seaways and open habitat, the Quaternary climate cycles
played a dominant role in shaping geographic ranges of
species, genetic divergence within species, and the composition of ecological communities (Webb and Bartlein
1992; Bond et al. 1993; Hewitt 1996, 2000; Avise 2000).
The climate oscillated throughout the Quaternary (the last
2 million years) with pronounced cycles of approximately
100,000 year cold glacial periods, interrupted by about
20,000 years of warm interglacial over the last 700,000
years, as demonstrated through sea bed cores, pollen cores
and ice cores from Antarctic and Greenland glaciers
(Imbrie et al. 1989; Bennett 1997; Landwehr et al. 1997;
Winograd et al. 1997; Petit et al. 1999; North Greenland
Ice Core Project Members 2004). In response to paleoclimatic fluctuations, geographic ranges of species tracked
suitable environmental conditions across this shifting
landscape (e.g. West 1980; Coope 1995). During glacial
episodes, vast areas of the northern hemisphere were
repeatedly blanketed by ice, while smaller regions provided suitable habitat throughout the Quaternary and thus
served as refugia for species (Betancourt et al. 1990;
Hewitt 1996; Avise 2000; Stewart and Lister 2001;
Tzedakis et al. 2002). Refugia played a critical role in
*Email: [email protected]
ISSN 1755-0874 print/ISSN 1755-1668 online
© 2008 Botanical Society of Scotland and Taylor & Francis
DOI: 10.1080/17550870802328660
http://www.informaworld.com
preserving genetic variation by (1) providing a range of
environments through climate changes such that populations were able to persist within a given region and (2)
promoting genetic divergence among geographically isolated populations (Hewitt 1996, 2000). As the climate
warmed and glaciers retreated, temperate populations
expanded and became re-connected, while the
distributions of cold-adapted species shrank and became
fragmented. In this way, the climatic vicissitudes of
the Quaternary generated the cyclical expansion and contraction of species ranges and influenced their evolutionary trajectories (Pielou 1991; Hewitt 1996, 2000; Avise
2000; Petit et al. 2003). No environmental region on Earth
has been more sensitive to climatic change than the Arctic
(Bartlein et al. 1997; Watson et al. 1998; IPCC 2007)
Several refugia within the Arctic (e.g. the Canadian
Arctic Archipelago, Greenland, eastern North America,
Beringia and the Taymyr Peninsula of Siberia) have been
proposed based on phytogeographical (e.g. Hultén 1937),
pollen and macrofossil (e.g. Edwards et al. 2000; Sher
et al. 2005) and molecular (e.g. Abbott et al. 2000) evidence. Of these, Beringia is arguably the best-documented
refugium. Hultén (1937) hypothesised that Beringia, an
expanse of the Arctic extending from the Lena River just
west of the Verkhoyansk Mts in northeast Russia to the
Mackenzie River in northwest North America and from
198
E.G. DeChaine
the Arctic Ocean to mountains in southern Siberia and
Alaska (Figure 1), was never glaciated, but rather provided
refuge for tundra species throughout the Quaternary. Beringia likely remained unglaciated because the growth of
massive glaciers was inhibited by the region’s low precipitation (Hopkins 1967) and its location, geographically
distant from the nuclei of ice-sheet formation (Greenland
[Richmond 1965] and Severnaya Zemlya [Möller et al.
2006]). Geological (Hamilton and Thorson 1983; Porter et
al. 1983), phytogeographical (e.g. Hopkins 1967), palynological and macrofossil (Nimis et al. 1998; Edwards et al.
2000; Tarasov et al. 2000; Brubaker et al. 2005; Sher et al.
2005; Birks 2008) and molecular evidence from plants
(Tremblay and Schoen 1999; Abbott et al. 2000; Abbott
and Brochmann 2003; Dobes et al. 2004; Abbott and
Comes 2004; Alsos et al. 2005; Thompson and Whitten
2006; Brochmann and Brysting 2008), fungi (Geml et al.
2006), and animals (MacNeil and Strobeck 1987;
Bernatchez and Dodson 1991; Quinn 1992; Weider and
Hobaek 1997; Reiss et al. 1999; Ehrich et al. 2000;
Hundertmark et al. 2001; Federov et al. 2003; Cook et al.
2004; Galbreath and Cook 2004; Waltari et al. 2004) support the Beringia refugium hypothesis. During glacial
periods, mountain glaciers and massive ice sheets bounded
Beringia, cutting the flora and fauna within the region off
from other parts of the tundra (Richmond 1965; Pielou
1991). Within Beringia, the tundra was expansive, but heterogeneously distributed and mixed with grasslands and
forest (Ritchie and Cwynar 1982; Schweger 1982; Guthrie
2001; Yurtsev 2001; Brubaker et al. 2005; Swanson 2006).
This could have allowed populations to persist within the
region for long periods of time and potentially diverge
from one another through isolation (Abbott et al. 2000;
Abbott and Brochmann 2003). Thus, the relative ecological stability of the region provided long-standing tundra
habitat, making Beringia a major refugium in the Arctic as
Figure 1. Quaternary environmental change in Beringia and accompanying models of population divergence. Maps of the Arctic are
shown for (a) glacial and (b) interglacial times, based on the distribution of land, sea, and ice during the Last Glacial Maximum (LGM) as
per CLIMAP (1981), West (1996), Svendsen et al. (2004) and the present, respectively. In both illustrations, the Arctic Circle is approximated by a dashed line, glaciers are shown in dark grey, and land extensions appear in light grey. In (a) Beringia is delineated by black
lines and the approximate location of the Verkhoyansk Mts (V) and Mackenzie River (M) are shown. Potential refugia (NR = northern
Russia, WB = western Beringia, EB = eastern Beringa, and ENA = eastern North America) are labelled in (B). The population divergence
models discussed in the text are shown in parts c–f.
Of bridges and barriers in Beringia
well as serving as an especially important conduit, via the
Bering Land Bridge, for flora, fauna and human migration
between the Palearctic (Eurasia) and the Nearctic (North
America) (e.g. Hoffecker et al. 1993; Donoghue and Smith
2004).
Shortly after Hultén (1937) proposed the Beringia
refugium hypothesis based on phytogeographical data,
Hopkins (1959) demonstrated that the region experienced
repeated changes in sea level associated with the
paleoclimatic cycles. As the climate cooled with the onset
of a glacial period, water became locked up in ice and sea
levels dropped, transforming the ‘monotonously flat’
Bering-Chuckchi undersea platform into the Bering Land
Bridge (Hopkins 1959), expanding the area of available
terrestrial habitat, and connecting western (northeastern
Russia) and eastern (northwestern North America)
Beringia (Figure 1a). Because eastern Beringia was cut off
from the rest of North America by glaciers, it essentially
became part of Siberia, biogeographically (Hopkins 1967).
The land bridge would have facilitated gene flow among
populations within a united Beringia. Higher sea levels in
warm periods (Figure 1b), either interstadials nested
within a glacial period or during interglacial episodes, submerged the land bridge beneath the Bering Sea (Hopkins
1973; Marincovich and Gladenkov 1999). The Bering Sea
acted as a dispersal barrier for terrestrial species, dividing
populations in western and eastern Beringia from one
another. Further east and west, the retreat of continental
glaciers would have permitted population expansion and
mixing within each continent. Because of the unique
environmental history of the region, the inhabitants of
Beringia experienced repeated cycles of isolation within a
unified Beringia interrupted by separation across the
Bering Sea.
A unifying bridge
The emergence of the Bering Land Bridge during glacial
periods facilitated dispersal between northeastern Eurasia
and northwestern North America (reviewed in Waltari et
al. 2007), but movement of individuals would have been
restricted to within Beringia due to bordering continental
ice sheets and mountain glaciers. From a demographic
perspective, populations had the opportunity to mix substantially within Beringia, depending on environmental
factors and availability of suitable habitat, but would have
remained isolated from populations outside the region.
Isolation and population mixing within a unified Beringia
would have maintained genetic variation within the region
and promoted genetic divergence among Beringia and
neighbouring glacial refugia (e.g. northern Russia and
eastern North America; Figure 1c). In addition to population mixing, contiguous eastward and/or westward range
expansion across the bridge could have permitted colonisation of previously unoccupied habitat. From geological
evidence indicating the sequential opening and closing of
the Bering Land Bridge followed by the opening and
closing of an ice-free corridor from Alaska to the rest of
199
North America, Hopkins (1967) hypothesised a series of
‘one-way valves’ to explain why dispersal was predominantly from west to east, with only limited flow in the
opposite direction. From this, contiguous, directional
range expansion across the bridge would have led to
stepwise genetic divergence from the source population to
newly colonised areas. As additional habitat became available through de-glaciation and species’ ranges continued
to expand, populations in newly colonised areas would
harbour increasingly more derived lineages, yielding
paraphyletic gene trees (Figure 1d; Eastward Bridge). In
either case, the Bering Land Bridge opened a route
connecting the Palearctic and Nearctic, making subsequent genetic exchange between the regions possible.
A divisive barrier
During warm climatic episodes, the Bering Sea flooded
the land bridge, formed a barrier to east–west dispersal for
terrestrial taxa, and physically isolated populations in western
and eastern Beringia from one another (Gladenkov et al.
2002; Lozhkin 2002). This vicariant event punctuated
periods of unification, likely initiating genetic divergence
(differentiation among populations) between Palearctic
and Nearctic populations, depending on the duration of
isolation. Because genetic divergence is governed by gene
flow, genetic drift and natural selection (Slatkin 1987),
isolation would have promoted divergence and possibly
speciation (Mayr 1963; Lewontin 1974; Bush 1975;
Endler 1977). Though interglacials were typically of
shorter duration than glacial periods, genetic divergence
across the Bering Sea has been inferred for several northern taxa (e.g. Ehrich et al. 2000; Federov et al. 2003). The
genetic consequences of this vicariant event could take on
two main forms: (1) a deep division between Eurasian and
North American lineages due to the Bering Barrier with
closer relationships among populations within a continent
(Figure 1e) or (2) Divided Refugia representing isolation
among all potential refugia (Figure 1f) in the region
(northwestern Russia, western Beringia, eastern Beringia
and northeastern North America). These two scenarios
depended on the degree to which populations within a continent were able to mix, because the Bering Land Bridge
would have been sundered as continental glaciers melted.
By allowing populations to remain in place throughout the
climate cycles and providing an intermittent dispersal
corridor, Beringia could have played a key role in the
evolution of tundra taxa, preserving genetic variation
throughout the Quaternary and promoting east-west
genetic divergence across the Bering Sea.
While the flora of Beringia shared a common history
of paleoclimatic cycles, the myriad bridging and barring
events provided multiple opportunities for population reshuffling and isolation, each of which likely impacted
species differently and to a different degree owing to
species-specific biological constraints, dispersal capacities
and historic distributions (West 1964, 1980; Bennett 1990,
2004; Coope 1995; Elias 1996; Whitlock and Bartlein
200
E.G. DeChaine
1997; Peterson and Denno 1998; Taberlet et al. 1998;
Hewitt 1999; Jackson and Overpeck 2000; Barnosky
2001; Davis and Shaw 2001). Furthermore, because the
formation and inundation of the bridge were recurrent
events, the demographic histories of different species may
have been strongly affected by similar events, but at different times. For instance, the flooding of one land bridge
may have been a critical event in the history of a given
species, whereas the magnitude of that specific event was
potentially of less importance to other taxa. Evolution during the Quaternary must of course be viewed as an ongoing process, wherein the geographic distribution of genetic
variation in a given species fluctuated continually in
response to cyclic environmental conditions. In some species, recurrent genetic changes due to population oscillations could have confounded the historic signal. Yet, if one
paleoclimatic event had greater demographic and genetic
consequences than another, that event would have left a
more evident footprint in the evolutionary path of a
species.
The overarching goal of this study was to investigate
the role that the unique environmental history of Beringia
played in the distribution and diversification of species in
the arctic tundra. The tundra flora is an excellent model for
examining the paleo-environmental history of Beringia.
The Arctic has been an exciting landscape for floral diversification due to its unique geographic position, dynamic
climate history, dramatic species range shifts, and the
long-term persistence of tundra. I adopted a comparative
coalescent approach (DeChaine and Martin 2006) to test
five potential models of population divergence using
published datasets on plants whose ranges span Beringia
and neighbouring refugia in Russia and North America
(Figure 1).
(1) Unified Beringia Model. Unification of populations within Beringia and isolation from neighbouring refugia (following Hultén 1937)
maintained three independent populations:
Northern Russia, Beringia, eastern North America
(Figure 1c);
(2) Eastward Bridge Model. One-way contiguous
range expansion eastwards (following the oneway valve hypothesis of Hopkins 1967) led to a
paraphyletic tree with basal populations in the
west and derived populations in the east
(Figure 1d);
(3) Westward Bridge Model. Same as the Eastward
Bridge Model, but with westward migration;
(4) Barrier Model. The Bering Sea separated populations, promoting genetic divergence, such that
populations east and west of the Bering Sea form
monophyletic clades and the greatest degree of
divergence is between the Palearctic and Nearctic
(Figure 1e);
(5) Divided Refugia Model. Divergence governed the
geographic distribution of genetic variation such
that one expansive population was fragmented by
the ice sheets of the glacial periods and the Bering
Sea producing a star-like phylogeny with four
refugia (Figure 1f).
Determining the processes affecting the distribution,
diversity and history of tundra flora is central to understanding the history of the Arctic biome and its role in
species diversification.
Materials and methods
In order to investigate how the Beringia tundra ecosystem
was impacted by Quaternary climate cycles, I performed a
comparative phylogeographic analysis on two species of
tundra angiosperms based on phylogeographic estimates
from the literature. The phylogeographic approach examines the contemporary geographic distribution of genetic
variation within and among populations to infer the demographic history of a species and how paleoclimatic events
(e.g. flooding of the Bering Land Bridge) impacted
divergence (Avise 2000). In turn, the field of comparative
phylogeography attempts to infer the evolutionary history
of an ecosystem, such as the tundra, by comparing genealogical estimates of history (gene trees) from multiple
species, and thus provides a framework for understanding
the assemblage, structure and evolution of communities
(Bermingham and Moritz 1998; Moritz and Faith 1998;
Arbogast and Kenagy 2001). When evaluating the
evolutionary history of an ecosystem, analyses must
accommodate the stochastic variation in genealogies due
to the coalescent process and life history strategies of each
species. A growing body of comparative studies have
taken this approach (e.g. Carstens et al. 2005a,b;
DeChaine and Martin 2005, 2006; Hickerson and
Cunningham 2005). Parameters associated with different
aspects of genetic variation, such as mutation rates, effective population size and divergence time, can vary widely
among genes and across taxa due to the stochastic nature
of the coalescent process (reviewed in Nordburg 2001).
Coalescent methods explicitly account for the uncertainty
in the estimates of historical events and are specifically
tuned to the focal taxa through the use of probabilistic
models to generate expected distributions for relevant
parameters (Kingman 1982; Wakeley 2008). These estimates can then be used to test phylogeographic hypotheses
developed from independent data (e.g. geologic or paleoclimatic records).
The literature was surveyed for phylogeographic studies that focused on plant species whose distributions
included Beringia. The criteria for choosing whether or
not to include a species in this comparative study were
based on the availability of several types of data: (1) representative sampling of populations within the various
refugia (northwestern Russia, western Beringia, eastern
Beringia and eastern North America) was the single, most
limiting factor. Due to small sampling sizes, Eurasian
samples were included within the northern Russia populations; (2) in order to perform tests based on coalescent
Of bridges and barriers in Beringia
theory, gene trees estimated from independent markers
were required. Appropriate markers included sequence
data and chloroplast RELPs (restriction fragment length
polymorphism), because organelles are expected to evolve
as a single locus (McCauley 1995). While AFLP (amplified fragment length polymorphism) data are excellent for
population genetic studies, they are not appropriate for
testing coalescent models because they sample the entire
genome and are not independent (Hartl 2000). Finally, (3)
estimates of divergence (either percent divergence or
diversity estimates that could serve as proxies for relative
differences in divergence between clades or effective population size) were sought in order to provide relative differences in branch lengths. Of the thirteen taxa examined
(Table 1), only two species (Figure 2) met the criteria for
this comparative coalescent analysis. This dearth of data
Table 1.
201
underscores the need for further studies on plants in the
region.
The idea of the comparative coalescent approach
(DeChaine and Martin 2006) is to test the observed gene
trees reconstructed from genetic data within each region
against an expected distribution of gene trees generated
from coalescent simulations, to determine which model of
history best fits each species and whether Beringia plants
responded similarly to climate cycles.
To do so, population divergence models (Figure 1)
were created based on paleoclimatic chronologies (Imbrie
et al. 1989; North Greenland Ice Core Project Members
2004), geological data (Hopkins 1967) and biogeographic
inferences (Hultén 1937; Abbott and Brochmann 2003).
Each population model is comprised of the tree topology,
estimates of effective population size for each population,
Review of phylogeographic research on plants in Beringia.
Taxon
Angiosperms
Arabis spp. (Brassicaceae)
Cassiope tetragona (Ericaceae)
Dryas integrifolia (Rosaceae)
Juncus biglumis (Juncaceae)
Potentilla sect. Niveae
(Rosaceae)
Saxifraga hirculus
(Saxifragaceae)
Saxifraga oppositifolia
(Saxifragaceae)
Saxifraga rivularis
(Saxifragaceae)
Townsendia hookeri
(Asteraceae)
Vaccinium uliginosum
(Ericaceae)
Veronica alpina (Plantaginaceae)
Gymnosperms
Picea glauca (Pinaceae)
Larix spp. (Pinaceae)
NR* WB
EB
ENA
Markers
10
40
2
0
19
120
382
82
5
107
cpDNA (trnL intron, trnL/F, rpoC1)
AFLP
cpDNA RFLP
cpDNA (trnL/F, rsp16), AFLP
cpDNA (microsatellites), AFLP
Dobes et al. 2004
Eidesen et al. 2007b
Tremblay and Schoen 1999
Schönswetter et al. 2007
Eriksen and Töpel 2006
0
0 180
0
cpDNA RFLP
Hollingsworth and Gornall 2006
38
40 119
171
cpDNA RFLP
0
26
0
5
0
0
57
0
2
49
References
9
3
24
7
AFLP
Abbott et al. 2000;
Abbott and Comes 2004
Jørgensen et al. 2006
0
0
5
0
cpDNA (trnK, ndhF)
Thompson and Whitton 2006
12
8
17
12
3
0
2
9
cpDNA (trnL/F, trnS/G),
nDNA (ITS), AFLP
cpDNA (trnL/F), AFLP
Alsos et al. 2005;
Eidesen et al. 2007a
Albach et al. 2006
0 144
110
0
144
0
cpDNA (trnL/F, trnL-T, ndhK-C)
mtDNA RFLP
Anderson et al. 2006
Semerikov and Polezhaeva 2007
0
0
Sample sizes within each region (NR = northern Russia, WB = western Beringia, EB = eastern Beringia and ENA = eastern North America), the type of
genetic marker used to infer population processes, and references are given for each species. *Numbers are shown only for individuals sampled from
northern Russia, though the region (NR) could have included additional individuals from throughout Europe. In cases where actual sample sizes were not
included in the manuscript, sample sizes were estimated based on available data.
Figure 2. Gene trees of species used in the comparative coalescent analyses. The genealogies of Saxifraga oppositifolia (Abbott et al.
2000) and Vaccinium uliginosum (Alsos et al. 2005) are shown with the geographic distribution of lineages marked by horizontal lines
and labels. NR = northern Russia, WB = western Beringia, EB = eastern Beringa, and ENA = eastern North America.
202
E.G. DeChaine
and time (in generations) given as branch lengths in generations (Figure 1). For both species, I arbitrarily assumed
an overall Ne = 1000 (following Knowles 2001, where Ne
is the effective population size) because no direct estimates were available from the literature. Because the relationship between Ne and branch lengths is sufficient for
these analyses and is expected to be proportional under
neutral coalescence, unless one is attempting to estimate
specific dates where direct estimates of Ne are required the
actual estimate of Ne did not impact the results (Nordburg
2001). Thus, each model could be tuned to individual species using relative estimates of diversity or % divergence
for each population. From these estimates of divergence,
the proportion of total Ne (a fraction of 1000) for each
population (Nep) was estimated. Branch lengths were also
adjusted relative to estimates of Nep, so that tests of each
model could be performed over a range of relative branch
lengths. Because of the lack of robust estimates of Ne, the
models of population divergence are necessarily simple.
Coalescent simulations of genealogies constrained
within models of population divergence (Figure 1) were
performed with MESQUITE 2.0 (Maddison and Maddison
2006), following Knowles (2001). Briefly, genetic and
population data (e.g. number and distribution of haplotypes, sample sizes, percent divergence between each population) were incorporated into the simulations, to tune the
simulated genealogies to a given species. Gene trees were
simulated by constraining the coalescence of lineages
within the topology, branch lengths, Ne and Neps for a
given model. This yielded 1000 simulated gene trees for
both species within each model of divergence, over a
range
The expected distribution of discordance between a
gene trees and the population model was measured by S,
the number of parsimony steps in a character (using the
source population as the character state) for a gene tree,
such that a greater degree of discord between the model of
divergence and the gene tree leads to an increase in S
(Slatkin and Maddison 1989). Under this test, discordance
could be caused by migration if the populations have been
separated for a long duration (N >> sample size), or
incomplete lineage sorting. Overall, the coalescent simulations produced a null distribution of 1000 S-values for
each model of population divergence, over a range of
branch lengths. The S-value from the published gene tree
for each species was compared with the null distribution
from the simulations (Figure 3) to test statistically whether
Table 2.
Figure 3. Testing models of divergence. (a) The amount of discord between the observed tree based on genetic data and the
population model (using the Bering Barrier model as an example
in the illustration) was measured by S (Slatkin and Maddison
1989). (b) The S-value for the observed tree was compared to
distribution of S-values derived from the coalescent simulations.
If the observed S fell outside of the expected distribution, then
the model was rejected as in this hypothetical example.
the observed tree (Figure 2) could have been generated
under the expected distribution for the population
model. If the observed S did not fit the expected distribution (α = 0.05 or 0.1) for a given model, that model was
rejected (Figure 3). If the observation fell within the
expected distribution for a model of population divergence, that model was not rejected, but rather was
accepted as a possible scenario that could have led to the
distribution of genetic variation observed today.
The possibility of long distance colonization (LDC)
has not been ignored in these analyses, particularly
because this probabilistically rare event has likely played a
large role in the distribution of arctic species (Alsos et al.
2007). The rapid dispersal of one or a few propagules over
vast distances is independent of land bridges and could
occur at any time that a suitable habitat existed. Because
LDC, unlike contiguous range expansion, is associated
with a strong founder effect as evinced by low genetic
diversity in the new population and does not follow a stepwise progression of lineage divergence, species that experienced LDC would most likely reject all population
models tested in this study. But, the possibility of LDC
cannot be ruled out by these models.
Results
Tests of population divergence models (Table 2) illustrate
the greater influence of the ‘bridge’ scenario on Beringia
taxa and that species responded individually to historic
environmental changes associated with paleoclimatic
cycles. The S-value for the gene tree of a species was
calculated and compared with the expected distribution of
Fit of observed genealogies to models of population divergence.
Model of population divergence
Study taxa
S
Saxifraga oppositifolia
Vaccinium uliginosum
4
6
Unified Beringia
0.054
0.155
Eastward Bridge
0.163
0.042
Westward Bridge
0.054
0.019
Bering Barrier
0.009
0.003
Isolated Refugia
0.028
0.003
P-values are shown for the fit of each species observed S-value to the expected distribution of S-values generated through coalescent simulations for each
model of population divergence. Significant fits (where the model could not be rejected even at α = 0.1) of observed gene trees to population models are
highlighted in bold.
Of bridges and barriers in Beringia
S-values estimated through coalescent simulations of
genealogies constrained within each model to determine
whether the observed tree could have been generated
under a given model of population divergence. Both ‘barrier’ models were rejected by both species at α = 0.05.
Saxifraga oppositifolia most strongly fit the Eastward
Bridge model (P = 0.163), but narrowly failed to reject the
other ‘bridge’ models at α = 0.05. Vaccinium uliginosum
rejected all but the Unified Beringia model (P = 0.155).
Discussion
The formation, rather than the flooding, of the Bering
Land Bridge had a profound influence on the evolutionary
history of both species of tundra plants examined in this
study. Only the ‘bridge’ models of population divergence
were supported by the comparison of observed gene trees
to the expected distributions generated through coalescent
simulations. The ‘barrier’ models were all rejected (even
at α = 0.1), and thus divergence under the simple vicariant
scenarios (given the model parameters) could not have
yielded the geographic distribution of genetic variation
observed today. Though both S. oppositifolia and V. uliginosum fit ‘bridge’ models, the two species responded differently to the unification and isolation of Beringia during
glacial episodes.
The demographic history of S. oppositifolia inferred
from chloroplast RFLPs demonstrates that the Bering
Land Bridge served as a corridor for eastward migration
for this species, though the other bridge models, Unified
Beringia and Westward Migration, could not be rejected at
α = 0.05. A significant fit between the observed chloroplast RFLP tree and the Eastward Migration model of
population divergence corroborates previous analyses of
the evolutionary history of this species. Abbott and colleagues (Abbott et al. 2000; Abbott and Brochmann 2003;
Abbott and Comes 2004) inferred that Beringia served as a
refugium for S. oppositifolia during glacial times and that
the species likely experienced contiguous range expansion
from there; though eastward migration was likely, the
dispersal direction remained uncertain. Fossil data demonstrate that the species was in the region throughout the
Pleistocene glacial cycles (Goetcheus and Birks 2001).
Furthermore, the inferences for S. oppositifolia support the
geologically based one-way valve hypothesis of Hopkins
(1959), which states that due to the sequential timing of
the opening and closing of glacial and land bridge
corridors (valves), eastward migration was favoured over
multi-directional range expansion. The combination of a
poorly resolved phylogeny based on cpDNA RFLPs and
the competing impacts of multiple, recurrent historic
events probably had a large effect on the inability of
simulation tests to discern among the various bridge
models for this species at the α = 0.05 level.
Vaccinium uliginosum rejected all models except that
of a Unified Beringia. Explicit tests of possible population
models illustrate the importance of an isolated population
of V. uliginosum in Beringia, as suggested by earlier
203
studies. Previously, Beringia was inferred to be a likely
site of origin of the species, a region where the species
could have survived continuously throughout the Quaternary, and an area from which expansion occurred (Alsos et
al. 2005; Eidesen et al. 2007a). The authors suggested that
polyploidisation events added to the uncertainty in resolving the history of this species. Even in the face of a
complex history of polyploidy, the coalescent tests clearly
showed that a unified Beringia served as a refugium for
V. uliginosum, at the very least. Unlike S. oppositifolia,
there is no evidence from the coalescent simulations that
V. uliginosum experienced unidirectional range expansion,
but rather the tests support the hypothesis that refugial
populations remained mostly isolated from one another.
Better estimates of Ne and mutation rates for this species
would enable more robust tests of when divergence among
the refugia occurred.
The results of these analyses suggest that, to the degree
that these two species represent the arctic flora, the unification of Beringia has played a stronger role in intraspecific histories than has separation of regions due to the rise
of the Bering Sea. From a demographic perspective, this
means that dispersal and population mixing has had a
greater influence than vicariance, or erased previous
signatures of vicariance, on the evolutionary histories of
species within Beringia. This genetic signature fits with
expectations from the paleoclimatic chronology (Hopkins
1959; Richmond 1965) – a unified Beringia existed during
protracted glacial episodes (approximately 100,000 years),
while the higher sea levels associated with interglacials
were of shorter duration (about 20,000 years). Isolation
across the Bering Sea was either not complete, such that
gene flow was possible among Russian and Alaskan populations, or populations were not isolated for long enough
duration to allow genetic drift or local environmental
selection to yield genetic divergence between the regions.
However, at a larger scale extending beyond Beringia,
both dispersal and vicariance have had significant effects,
as demonstrated by the eastward migration of S. oppositifolia and isolation among refugial populations in V. uliginosum. Beringia had a large impact on the geographic
distribution of genetic variation in arctic flora, providing
habitat for long-term persistence of lineages and a means of
connecting Palearctic and Nearctic populations.
The inferences based on the arctic plants examined in
this study fit the general pattern exhibited by the terrestrial
fauna of Beringia (reviewed in Waltari et al. 2007) – a
greater importance of the Palearctic-Nearctic connection
via the Bering Land Bridge over the divisive influence of
the Bering Sea dispersal barrier. While the review of transBeringian taxa revealed that the majority of interspecific
studies exhibited eastward migration, only 9 of the 16
intraspecific studies did so. Based on previous analyses,
S. oppositifolia and V. uliginosum did not provide a unidirectional genetic signal, but rather one of expansion out of
Beringia. The explicit test of population models in this
study revealed that S. oppositifolia actually does most
strongly fit a model of eastward migration as well.
204
E.G. DeChaine
Obviously, with only two species of plants available for
analyses and both of them exhibiting individual responses
to environmental changes, any generalisations about the
flora of Beringia would be premature.
The limited number of studies on arctic flora amenable
to statistical phylogeographic analyses (the two species
investigated herein) highlights the need for further
research.
Because of the large uncertainty in parameters estimated from a single locus, this comparative analysis was
necessarily limited to very simple models of population
divergence. Better estimates of species’ histories, effective
population sizes and divergence times could be accomplished through multi-locus analyses (Jennings and
Edwards 2005). In addition, more realistic population
models could be developed by including paleodistribution
models tuned to each species (Carstens and Richards
2007; Richards et al. 2007), as well as by making direct
comparisons with fossils records as they become available
(e.g. Goetcheus and Birks 2001). The incorporation of
multiple genes, parameter estimates with narrower confidence intervals and geographic models specific to the species of interest, would yield more robust estimates of tree
topologies, divergence times, and migration rates, and thus
a more complete estimate of history. Finally, increasing
not only the number of species, but also the phylogenetic
and ecological breadth of study species will provide a
more complete picture of how the tundra flora in general
responded to the unique environmental history of
Beringia. The field of comparative phylogeography in the
Arctic is burgeoning (e.g. Alsos et al. 2007; Waltari et al.
2007; Brochmann and Brysting 2008), but there is a great
need for more research couched in a hypothesis-testing
framework before a general understanding of the history
of the region and the specific role(s) that Beringia played
in the distribution and diversification of arctic plants will
be gleaned.
Conclusions
Because tundra plants have likely persisted in the region
throughout the Quaternary and are abundant and accessible, the flora is an excellent model for investigating the
history of Beringia, and yet, only two studies have been
performed using genetic data appropriate for coalescent
analyses. The two species examined herein support two
different models, both of which underscore the importance
of the Bering Land Bridge in the evolutionary history of
the region. Investigations of additional species using
multi-locus, coalescent techniques will greatly expand our
understanding of the history of Beringia. Moreover, understanding the history and distribution of the arctic flora is
gaining urgency because of the profound effect of climate
change. Rapid changes in the tundra due to global warming and land-uses (Nelleman et al. 2001) are forcing the
distribution of the arctic tundra to shift in response.
Indeed, species new to the Arctic are colonising the tundra
(Walker et al. 2006). Uncovering which historic events
had the largest genetic consequences for arctic flora will
not only aid in our understanding of the role that climate
cycles played in species evolution, but also provide an
explicit timeframe of events that likely impacted the rest
of the flora and fauna of Beringia. Just as documenting the
distribution of arctic flora is a crucial step in monitoring
long-term changes for the region (Walker et al. 2005), the
vegetation history provides a chronology for myriad natural climate change experiments linked to the region’s
geology, hydrology and ecology and is critical for making
predictions of how species may be affected by future
warming (Prentice et al. 1992; Araújo et al. 2008).
Acknowledgements
I would like to thank Richard Abbott and the Botanical Society
of Scotland for the invitation to present these findings at the
symposium on the ‘History, evolution, and future of arctic and
alpine flora’ in St Andrews, Scotland 2007. This work was
funded by the National Science Foundation (ARC-0714232) and
grants from Western Washington University.
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