IOP PUBLISHINGENVIRONMENTAL RESEARCH LETTERS

Environ. Res. Lett. 6 (2011) 024003 (6pp)

doi:10.1088/1748-9326/6/2/024003

Dynamics of the larch taiga–permafrost
coupled system in Siberia under climatechangeNingning Zhang1,2,6, Tetsuzo Yasunari3,4 and Takeshi Ohta4,51Graduate School of Environmental Studies, Nagoya University, Nagoya, Aichi 464-8601,
Japan
2
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and GeophysicalFluid Dynamics, Institute of Atmospheric Sciences, Chinese Academy of Sciences,
Beijing 100029, People’s Republic of China
3
Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya 464-8601, Japan
4
Study Consortium for Earth–Life Interactive Systems (SELIS) of Nagoya University,
Nagoya, Japan
5
Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan
E-mail: zhangningning@lasg.iap.ac.cn

Received 23 November 2010
Accepted for publication 28 March 2011
Published 18 April 2011
Online at stacks.iop.org/ERL/6/024003
Abstract
Larch taiga, also known as Siberian boreal forest, plays an important role in global and regional
water–energy–carbon (WEC) cycles and in the climate system. Recent in situ observations havesuggested that larch-dominated taiga and permafrost behave as a coupled eco-climate system across a
broad boreal zone of Siberia. However, neither field-based observations nor modeling experiments haveclarified the synthesized dynamics of this system. Here, using a new dynamic vegetation model coupledwith a permafrost model, we reveal the processes of interaction between the taiga and permafrost. The
model demonstrates that under the present climate conditions in eastern Siberia, larch trees maintainpermafrost by controlling the seasonal thawing of permafrost, which in turn maintains the taiga by
providing sufficient water to the larch trees. The experiment without permafrost processes showed thatlarch would decrease in biomass and be replaced by a dominance of pine and other species that suffer
drier hydroclimatic conditions. In the coupled system, fire not only plays a destructive role in the forest,
but also, in some cases, preserves larch domination in forests. Climate warming sensitivity experiments
show that this coupled system cannot be maintained under warming of about 2 ◦ C or more. Under suchconditions, a forest with typical boreal tree species (dark conifer and deciduous species) would become
dominant, decoupled from the permafrost processes. This study thus suggests that future global
warming could drastically alter the larch-dominated taiga–permafrost coupled system in Siberia, withassociated changes of WEC processes and feedback to climate.
Keywords: taiga–permafrost, vegetation model, soil hydrology

S Online supplementary data available from stacks.iop.org/ERL/6/024003/mmedia

through physical and biological processes (Bonan 2008). As
one of the largest terrestrial biomes, Siberian boreal forests
store huge amounts of carbon in their biomass and soil, andplay an important role in climate feedback processes (e.g.,
lowers surface albedo, masking the high albedo of snow in
winter, and large evapotranspiration in summer) (Bonan 2008,
Lopez et al 2008). Therefore, taiga is thought to play an

1. Introduction
The world’s forests influence planetary energetics, thehydrologic cycle, and atmospheric composition and climate
6 Address for correspondence: State Key Laboratory of Numerical Modelingfor Atmospheric Sciences and Geophysical Fluid Dynamics, Institute ofAtmospheric Sciences, Chinese Academy of Sciences, Beijing 100029,
People’s Republic of China.
1748-9326/11/024003+06$33.00

1© 2011 IOP Publishing Ltd Printed in the UK

Environ. Res. Lett. 6 (2011) 024003

N Zhang et al

Figure 1. Schematic diagram of feedbacks of soil, vegetation and fire in the Siberian taiga–permafrost system considered in this study(right-side diagram); spatial distribution of larch taiga (left-bottom figure, red area) and boundary of permafrost (left-bottom figure, dashedline and blue line); location (left-bottom figure, green star) and climate of Yakutsk (left-top figure). In the schematic diagram: arrows show
force directions between each factor. ‘+’ (‘−’) means the following the forces direction, there is a positive (negative) correlation between two
factors, and ‘±’ means the correlation is still not clear. The thicker arrows indicate the processes which were better considered in the model
simulation. Dashed arrow indicates the process which is not considered in this study. The words beside each arrow indicate the variables that
control such process.

important role in both the global carbon balance (Piao et al
2008, Euskirchen et al 2006) and regional or continental-scalehydroclimate (Betts 2000, Bonan et al 1992, Chapin et al 2005,
Saito et al 2006). Uniquely in eastern Siberia, the distributionof the nearly homogeneous larch-dominated taiga highly
coincides with the zones of continuous and discontinuous
permafrost (Osawa et al 2009, Stolbovoi and McCallum2002) (figure 1). Unlike other boreal ecosystems, recent insitu observations have shown that the larch taiga–permafrost
system in Siberia has displayed distinct water–energy–carbon(WEC) exchange characteristics including in its temporaland spatial variations (Tanaka et al 2008, Ohta et al 2008,
Sugimoto et al 2002, Maximov et al 2008, Ohta et al 2001).
It suggests that larch has adapted better than other species tothe permafrost environment, forming a larch-dominated taiga–
permafrost coupled system (Osawa et al 2009). Althoughsoil freezing–thawing processes and permafrost have been
introduced to a number of vegetation models to improve
simulations of fire disturbance, soil respiration, and vegetation
dynamics (Beer et al 2007, Sato et al 2010, Tchebakova
et al 2009, Wania et al 2009), most of these studies focusedon carbon exchanges and emphasized vegetation responses toclimate variation. In other words, few models have treated‘larch taiga–permafrost’ as a coupled system in terms of waterand energy exchanges, which could be distinctly different fromother boreal forest biomes.

2. Methodology
To address this issue, we need to introduce a newscheme that integrates vegetation and permafrost, twomajor components in the unique taiga–permafrost system,
which emphasizes the hydrological feedbacks among theseprocesses (figure 1).
Meanwhile, wildfire, as it has
strong mutual influence with taiga–permafrost coupled system,is also considered in the scheme (Osawa et al 2009)(see supplementary ‘Fire’ available at stacks.iop.org/ERL/6/
024003/mmedia). A new dynamic vegetation model DV-FSM,
therefore, was developed by coupling two prototype models,vegetation model FAREAST (see supplementary ‘FAREAST’
available at stacks.iop.org/ERL/6/024003/mmedia) (Yan andShugart 2005, Zhang et al 2009, Shuman and Shugart
2009, Shugart et al 2006) and frozen soil model FSM(Zhang et al 2007).
Moreover, we also introduced a
new biogeophysical process into DV-FSM in order tosimulate the responses of vegetation physiological processes
to soil hydrological seasonal and inter-annual variability,
which in another sense link the simulation of long-term
forest ecological dynamics and short-term soil hydrologicalprocesses (see supplementary, ‘Model Description’ available
at stacks.iop.org/ERL/6/024003/mmedia). Using the model,
this study aimed to prove the importance of the interactionsof permafrost and Siberian larch taiga as a coupled system.
Meanwhile, we conducted an additional experiment to evaluate
the sensitivity of this coupled system to future warming
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climate. As a validation of the model experiment, we adopted
the observed vegetation–permafrost processes at Spasskaya
Pad near Yakutsk in eastern Siberia (Russia), where continuous
observations of energy, water, and carbon fluxes of permafrostvegetation coupled system have been made since 1998 (Ohtaet al 2008, 2001). We conducted different simulations, allforced by the same 1 year length climate forcing dataset. The
dataset is derived from averaged half-hourly observations from2000–4. Time-integration of 1000 years for each plot-scale
simulation started from bare ground condition was repeatedeight times and then averaged for broader spatial scale. To
clarify the importance of the existence of permafrost for
maintaining the Siberian larch taiga–permafrost ecosystem, thefollowing two sets of experiments were conducted.
In the first set of experiments, we introduced four different
runs: control run (CNTL, permafrost–vegetation–fire coupledrun), no fire run (NF, without consideration of fire disturbance),
no permafrost run (NP, without consideration of permafrost
effect), and no permafrost and fire run (NPF). In the NP and
NPF runs, we kept the soil water freezing–thawing process inthe model, but not considering the effect of soil ice blocking thepercolation of soil water. This blocking effect was considered
to be a unique and essential feature of the permafrost system.
In the second set of experiments, four groups ofsimulations with different warming intensity were conducted
to examine the sensitivity of the taiga–permafrost system
to climate warming (see supplementary, ‘Method’ available
at stacks.iop.org/ERL/6/024003/mmedia). We set warming
intensity of study site to approximate 4.5 ◦ C at the end of
the 21st century projected by the Fourth Assessment Reportof the Intergovernmental Panel on Climate Change (IPCCAR4). Similar to the previous experiment, each group included
two runs in which we turned on/off the permafrost effect.
In three groups, summer (JJA) surface air temperature wereadded by 1.12 ◦ C, 2.25 ◦ C, and 4.5 ◦ C (abbreviated below as,for example, +1.12 ◦ C), respectively, over the original forcing
data. In another group, summer surface air temperature of+4.5 ◦ C and precipitation +20% were added to examine thetaiga–permafrost sensitivity to precipitation change under thestrong warming condition. Hereafter, CNTL 1C represented
the control run with temperature of +1.12 ◦ C, and NP 1C
was non-permafrost run with temperature of +1.12 ◦ C.
Accordingly, CNTL 2C & NP 2C and CNTL 4C & NP 4C
represent the runs with temperature of +2.25 ◦ C and +4.5 ◦ C,
respectively.

Figure 2. Time sequence of simulated forest succession and ALT of
permafrost. Colored areas indicate the assembled simulation ofaboveground forest succession from bare ground (first 300 years of1000 years run); dash line is assembled result of simulated annual
maximum ALT; ‘+’ marks are observed aboveground biomass at
different forest stages; pies are observed (left) and simulated (right)
forest composition.

observation-based semi-empirical model output (Shvidenko
et al 2007) (figure 2). The modeled fire-return was about
170 year/plot, in accordance with the field observed fireinterval of 100–200 years (Shvidenko et al 2007, Bonan andShugart 1989). The model also reproduced well the observed
recovering process of forest biomass after fire disturbance (seesupplementary, ‘Fire’ and figure 1 available at stacks.iop.org/
ERL/6/024003/mmedia). The annual maximum thawed layer
thickness (i.e., the active layer is the surficial layer above
the permafrost which thaws during the summer (Burn 1998);
hereafter abbreviated as ALT) could reach 1.8 m in themodel, which is close to the observed depth of 1.5 m. The
model also well reflected changes of ALT in accordancewith annual aboveground vegetation dynamics and disturbance(see supplementary figure 1 available at stacks.iop.org/ERL/6/
024003/mmedia). In the time sequence, ground biomass higher(lower) above intercepts more (less) radiation and therefore
shallows (deepens) the ALT depth (figure 2).
To clarify the effect of permafrost on the abovegroundvegetation composition and its interaction with soil hydrology,
we conducted a model run without permafrost, called the
NP run, and compared it with the CNTL run. Although
the amount of precipitation in the growing season is very
limited (130 mm from May to June in the model forcing data),
a wet spring to dry summer soil-moisture pattern appearedin the CNTL run, but in the NP run (see supplementary
figures 2(a) and (b) available at stacks.iop.org/ERL/6/024003/
mmedia) an overall dry moisture condition appeared in springthrough summer. Soil moisture in summer (JJA) of the CNTL
run was 3–4% (absolute difference in soil volumetric watercontent) higher than that of the NP run (figure 4 leftmost
square and diamond symbols). Accordingly, throughout thegrowing season, the CNTL run showed no clear depression invegetation water uptake associated with the decrease of soil
moisture (figure 3(a)). On the other hand, when permafrost
was removed (NP run), the model showed less vegetation water

3. Results
The model control (CNTL) run was conducted to reproduce
the taiga and permafrost interactions that were observed inlong-term field experiments (Osawa et al 2009, Ohta et al2008). The model successfully reconstructed the larchdominated forest in assembled simulation (figure 2) withbirch and pine appearing occasionally as sub-dominant or
scattered tree species. The simulation result coincides with
the in situ observation (Osawa et al 2009, Ohta et al 2008)(also see supplementary ‘Soil Water Content’ available atstacks.iop.org/ERL/6/024003/mmedia) and in the large-scale
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N Zhang et al

Figure 3. Time sequence of daily vegetation water uptake from different soil depths during the growing season (90–270 days of the year) for(a) CNTL run; (b) difference of NP run from CNTL run; (c) difference of CNTL 4C run from CNTL run; and (d) difference of NP 4C run
from CNTL 4C run.

uptake and a resulting soil drought. The decrease in vegetationwater uptake was found throughout the summer and peaked in
mid-summer, despite the favorable temperature and radiation
conditions for vegetation photosynthesis activity. This result
suggests that vegetation photosynthesis activities of the taiga–
permafrost system might be more vulnerable to mid-summer
drought than to the drought occurred in the early growing
season.
The above results have proved that the active layer serves
as an ‘aquifer’ and the permafrost serves as ‘aquifuge’. To
the soil water availability, this ‘aquifer–aquifuge’ system playsa ‘buffer effect’ through which intensive water input (bysnow meltwater and summer precipitation) is evened out fromearly spring over most of the growing season until midsummer (see supplementary ‘Soil water content’ available
at stacks.iop.org/ERL/6/024003/mmedia). By removing thepermafrost, incoming water drained much faster because there
was no frozen soil to hold the water. For soil moisture,the ‘buffer effect’ was stronger in spring than in summer

due to the shallow ALT and intensive meltwater income (seesupplementary figure 2(b) available at stacks.iop.org/ERL/6/
024003/mmedia), as for vegetation water uptake. This effectwas more obvious in mid-summer than in spring because of the
low water supply and high potential vegetation water demandof summer (figure 3(b)). Therefore, the absence of permafrost
may lead to a larger summer water deficit.
The inter-seasonal hydrological effect of permafrost may
further affect the long-term vegetation dynamics. Model output
indicated that the existence of permafrost (CNTL run) helps
larch survive the summer drought by providing a continuous
supply of water to the top soil layer, whereas the absence of
permafrost (NP run) might lead to fatally dry conditions forlarch (see supplementary figure 3 available at stacks.iop.org/
ERL/6/024003/mmedia). Therefore, in the NP run, larch was
eventually replaced by pine and birch as the dominant species,
which have more roots in deeper soil and can tolerate extreme
drought. Moreover, dry soil induced higher fire frequency
in the NP run than in the CNTL run, resulting in a notable
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N Zhang et al

NP 4C) showed no clear effect of temperature increase onchanges in soil moisture and vegetation biomass (figure 4, reddiamonds and right bar of each group). These experimental
results indicate that the taiga–permafrost coupled system
is more sensitive to the future warming compared to theecosystem without permafrost. Another notable feature underintense warming (+2 ◦ C or more) was the drastic change inbiome (forest) composition as well as biomass, as shown in
the experiments with the permafrost process (left bars of eachexperiment in figure 4). The difference between the CNTL 1C
and NP 1C run is significant, but less difference between
CNTL 4C and NP 4C in terms of forest composition, biomass(figure 4), and soil water uptake (figure 3(d)). This suggeststhat under intense warming (+2 ◦ C or more), the permafrost
effect is drastically weakened, or more realistically, the taiga–
permafrost coupled system might no longer exist. However,in the additional experiments, by increasing the precipitation
intensity by 20% over the NP 4C and CNTL 4C run, thepermafrost effect again came into force (figure 4 rightmostbars), although this precipitation effect was not as remarkableas the temperature effect. That is, the vulnerability of the taiga–
permafrost system under future climate conditions depends
greatly on the intensity of warming, but additionally on theintensity and temporal distribution of precipitation.

Figure 4. Aboveground total biomass (with fractional components ofmajor species) for CNTLrun (left bar) and NP run (right bar)simulated under five different climate conditions. Five bar groups
represent those (from left to right) for the present climate condition;
for temperature conditions of +1.12 ◦ C (above the present);+2.25 ◦ C; +4.5 ◦ C, and +4.5 ◦ C plus precipitation +20% (above thepresent). The name of each experiment was shown on the top of thebar. Two dashed lines in the upper part show changes of summer(JJA) mean soil water for CNTL run (square marks) and NP run(diamond marks), respectively. Note the changes of major species
contributing to the total biomass under the different climate
conditions.

4. Conclusion and discussion
decrease in aboveground biomass in the NP run (figure 4,
leftmost group of bars; see supplementary figure 4 and ‘Fire’available at stacks.iop.org/ERL/6/024003/mmedia).
The vegetation dynamics and its phenological cycle (i.e.,
foliation and broadening and falling leaves etc) block radiation
to prevent frozen soil from thawing in summer and also
suppress the development of other permafrost processes (e.g.,thermokarst, soil fluction, and thermo-erosion) (Ohta et al2008). The limited ALT in summer, in turn, provides sufficientwater for larch trees and lowers the fire frequency to preserve
the aboveground taiga composition and its biomass. In
this manner, under the present climate condition, the taiga
ecosystem is stabilized by coupling with the hydrologicalprocess of permafrost. Thus, the taiga (larch)–permafrost
system can be interpreted as a self-regulating coupled system.
Is this coupled taiga–permafrost system sustainable under
future climate warming? The results of second set ofexperiments show a drastic change of dominant species andbiomass depending on the degree of temperature increase.
Under moderate warming (CNTL 1C, figure 4), larch trees
were still the dominant species, and aboveground biomass
increased. However, under intense warming (CNTL 2C
and CNTL 4C), drastic larch extinction occurred, withdecreased biomass and decreased soil moisture in mid-summer(figure 4, yellow squares). This drought condition was
mainly attributed to the enhanced photosynthesis activity inearly summer (figure 3(c)) and advanced thawing processes(see supplementary figure 2(c) available at stacks.iop.org/
ERL/6/024003/mmedia), both of which were caused by thetemperature increase (see supplementary ‘Warming’ available
at stacks.iop.org/ERL/6/024003/mmedia). In contrast, thesensitivity experiments without permafrost (NP 1C, NP 2C,

Climate has been considered as the most important driver tocontrol the WEC activities in taiga–permafrost system on large
scale. However, in the smaller scale, the lack of a definitive
relationship with climate occurs because energy partitioning
is strongly controlled by vegetation type and structure rather
than directly by climate or latitude (McGuire et al 2002,
Lopez et al 2008). The two sets of numerical experiments
using the new dynamic vegetation–frozen soil coupled model
have revealed that under the present hydroclimatic condition,
the taiga (represented by larch forest) is tightly coupled withthe permafrost, forming a taiga–permafrost coupled system.
In this system, the permafrost maintains soil water for thetaiga by controlling the ALT, while the taiga maintains
the permafrost by controlling canopy radiation interception
through vegetation long-term succession. Though the active
layer seasonal thaw is mainly driven by climate seasonal rotate,
its freezing–thawing process may notably controlled (changed)
by vegetation dynamic.
The warmer climate runs have shown that this coupledsystem can be sustained under a temperature increase of about+1 to +2 ◦ C or less. However, under intense warming of +2 to+4 ◦ C or higher, a drastic change of vegetation (extinction oflarch and its replacement by other boreal and sub-boreal tree
species) is strongly suggested, where the coupling of forestand permafrost would be destroyed or weakened. Moreover,
our results have predicted a decrease in biomass and thetranspiration rate in mid-summer due to drought conditions inthe soil layer under warmer climate (figure 3(c)).
The feedback to climate from the taiga–permafrost systemis still not clear. Some modeling studies showed strong
continental-scale climate effects through vegetation processes
5Environ. Res. Lett. 6 (2011) 024003

N Zhang et al(Betts 2000, Bonan et al 1992, Saito et al 2006, Yasunari et al2006) and through soil freezing–thawing processes (Takata
and Kimoto 2000), separately. The IPCC-AR4 suggested
increasing precipitation in Siberia under the future warmer
condition, but none of the models have considered the effects
by the taiga–permafrost coupled system in their climate
projections. The current study has suggested that decreases
in transpiration and biomass might have negative feedback to
the regional water cycle, including reduction of precipitation.
Future climate prediction studies should, therefore, be
conducted incorporating the vegetation–permafrost coupledsystem demonstrated here, in light of a potentially large impactof this coupled system in the global climate.

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Acknowledgments
This work was supported by the Global Environment Research
Fund of the Ministry of the Environment (A-0902), Japan;
Major State Basic Research Development Program of China(973 Program) (2011CB952004) and Program of Excellent
State Key Laboratory, China (41023002).

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