Introduction
The majority of the northern peatlands developed during the Holocene
ca. 8–12 thousand years (kyr) ago after the deglaciation of the
circum-Arctic region (MacDonald et al., 2006). The availability of new land
surfaces owing to ice retreat (Dyke et al., 2004; Gorham et al., 2007),
climate warming following deglaciation (Kaufman et al., 2004), increased
summer insolation (Berger and Loutr, 2003), more pronounced seasonality (Yu
et al., 2009), greenhouse gas emissions (MacDonald et al., 2006) and elevated
moisture conditions (Wolfe et al., 2000) are some of the factors that
promoted the rapid expansion of the northern peatlands. Moderate plant
productivity together with depressed decomposition due to saturated
conditions led to a surplus of carbon (C) input relative to output, resulting
in the accumulation of peat (Clymo, 1991). Peatlands of the Northern
Hemisphere are estimated to have sequestered approximately 350–500 PgC
during the Holocene (Gorham, 1991; Yu, 2012).
Peatlands share many characteristics with upland mineral soils and non-peat
wetland ecosystems. However, they constitute a unique ecosystem type with
many special characteristics, such as a shallow water table depth, C-rich
soils, a unique vegetation cover dominated by bryophytes (hereinafter
referred to as “mosses”), spatial heterogeneity, anaerobic biogeochemistry
and permafrost in many regions. Due to their high C density and the
sensitivity of their C exchange with the atmosphere to temperature changes,
these systems are an important component in the global C cycle and the
coupled Earth system (MacDonald et al., 2006). Lately, considerable effort
has been made to incorporate peatland accumulation processes into models
with the purpose of understanding the role of peatlands in sequestering C,
thereby lowering the radiative forcing of past climates (Frolking and Roulet,
2007; Wania et al., 2009a; Frolking et al., 2010; Kleinen et al., 2012; Tang
et al., 2015) and how they might affect future climate warming and C
cycling (Ise et al., 2008; Swindles et al., 2015).
Clymo (1984) developed a simple one-dimensional peat accumulation model and
described the main processes and mechanisms involved in peat growth and its
development. This model became the starting point for later work in many peat
growth modelling studies. Hilbert et al. (2000) developed a theoretical peat
growth model with an annual step, modelling the interaction between peat
accumulation and water table depth using two coupled non-linear differential
equations. Using a similar approach, Frolking et al. (2010) developed a
complex Holocene peat model by combining the dynamic peat accumulation model
of Hilbert et al. (2000) with a peat decomposition model (Frolking et al.,
2001). They showed that the model performed fairly well in simulating the
long-term peat accumulation, vegetation and hydrological dynamics of a
temperate ombrotrophic bog in Ontario, Canada. Though the models mentioned
above are detailed enough to capture the peat accumulation and decomposition
processes quite robustly, they lack soil freezing–thawing processes, and this
limits their application over regions where such processes occur. Wania et
al. (2009a) were the first to account for peat dynamics in a model for large-area
application by incorporating peatland functionality in the LPJ-DGVM model,
which was designed for regional and global simulation of ecosystem responses to climate
change (Sitch et al., 2003). Their approach included a number of novel
features, such as a detailed soil freezing–thawing scheme,
peatland-specific plant functional types (PFTs) and a vegetation inundation
stress scheme, but it employed a two-layer representation of the peat profile,
which is not as detailed as the process-based dynamic multilayer approaches
taken by Bauer et al. (2004), Heinemeyer et al. (2010) and Frolking et
al. (2010). Other model representations have also included peatland processes
in their frameworks (Morris et al., 2012; Alexandrov et al., 2016; Wu et al.,
2016) and been shown to perform reasonably at different sites. In addition,
some of these models have been applied over large areas (Kleinen et al.,
2012; Schuldt et al., 2013; Stocker et al., 2014; Alexandrov et al., 2016) to
simulate regional peatland dynamics.
Though much information is available about the past and present rates of C
accumulation in the literature, recent syntheses have highlighted the
existing spatial gaps in data availability across the pan-Arctic
(45–75∘ N) region (Yu et al., 2009; Loisel et al., 2014). The
extent and remoteness of many locations present challenges for the reliable
estimation of total C, basal ages and accumulation rates of peat carbon. This
demands the use of process-based modelling for upscaling and interpolation
across the pan-Arctic distribution area. We employed LPJ-GUESS, an
individual- and patch-based dynamic ecosystem model (Smith et al., 2001)
extended to represent the characteristic vegetation, biogeochemical and
hydrological dynamics of high-latitude peatlands to simulate C accumulation
of peatlands across the pan-Arctic region under past, present and future
climates (Chaudhary et al., 2017a). The model accounts for the close
intercoupling between peatland and permafrost dynamics, which is critical for
the evolution of these ecosystems and their carbon dynamics in the warming
regional climate. We assess the potential effects of historical and projected
climate and atmospheric CO2 on peatland C balances and permafrost
distribution at the regional scale across the pan-Arctic region.
Methodology
Model description
LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) is a process-based
model of vegetation dynamics, plant physiology and the biogeochemistry of
terrestrial ecosystems. It simulates vegetation structure, composition and
dynamics in response to changing climate and soil conditions based on an
individual- and patch-based representation of the vegetation and ecosystems
of each simulated grid cell and is optimized for regional and global
applications (Smith et al., 2001, 2003; Miller and Smith, 2012). The model
has been evaluated in comparison to independent datasets and other models in
numerous studies; see e.g. McGuire et al. (2012), Piao et al. (2013), Smith
et al. (2014) and Ekici et al. (2015).
We employed a customized Arctic version of the model (Miller and Smith, 2012)
that has been developed to include dynamic, multilayer peat accumulation
functionality and permafrost dynamics. The model represents the major
physical and biogeochemical processes in upland and wetland arctic
ecosystems, including an expanded set of plant functional types (PFTs)
specific to these areas (McGuire et al., 2012; Miller and Smith, 2012). The
revised model is described in outline below, while a full description can be
found in Chaudhary et al. (2017a). In our approach, vegetation and peatland C
dynamics are simulated on multiple connected patches to account for the
functional and spatial heterogeneity in peatlands. The simulated PFTs have
varied structural and functional characteristics and can establish in each
connected patch and compete for soil resources, space and light. The
composition in terms of relative PFT abundance and the physical structure of
the plant community are emergent outcomes of this competition. The model is
initialized with a random surface comprised of 10 patches of uneven height.
Heterogeneity in the height of adjacent patches is a precondition for
hydrological redistribution between them, which mediates vegetation
succession and affects the peat accumulation rate, as described below. The
soil–peat column is represented by four different vertically resolved
layers. A dynamic single snow layer overlays the peat column, represented by
a dynamic litter–peat layer consisting of a number of sublayers, updated
yearly, that depends on thickness. Underneath the peat column is a fixed 2 m
deep mineral soil column consisting of 0.1 m thick sublayers, which is
underlain by a 48 m deep “padding” column consisting of relatively thicker
sublayers. The soil temperature is updated daily for each sublayer at
different depths, enabling the simulation of a dynamic soil thermal profile
as a basis for the representation of permafrost (Wania et al., 2009a). The
fractions of ice and water as well as the mineral and peat fractions in each
layer govern the heat capacities and thermal conductivities and affect the
freezing and thawing processes of soil water in peat and mineral soil layers
(Wania et al., 2009a). The fractions of water and ice in the sublayers are
updated each day depending upon variation in soil temperature and fractional
mineral content, following Hillel (1998). A detailed description of the
permafrost and soil temperature scheme is available in Chaudhary et
al. (2017a), Miller and Smith (2012) and the references therein.
A water bucket scheme was used to simulate peatland hydrology in which the
assumption is made that precipitation (rain) and snowmelt are the main input
of water. Evapotranspiration, drainage, surface and base runoff are the major
water balance processes in the peat layers (Gerten et al., 2004). The model
also includes lateral flow of water between patches, an important governing
process of vegetation and C dynamics of peatlands that is lacking in most
peatland models (Chaudhary et al., 2017b). A simple lateral flow scheme
connects higher elevated patches (hummocks) to lower depressions (hollows).
The water table position (WTP) of individual patches is reset to the mean
landscape WTP on each daily time step, effecting lateral flow from patches
with a higher WTP following the current day's rainfall, snowmelt and
evapotranspiration fluxes to those with lower WTP. This in turn affects the
plant productivity and decomposition rates in each patch and results in
dynamic surface conditions over time.
Five PFTs are used to represent the main functional elements of peatland
vegetation: graminoids (Gr), mosses (M), high summergreen shrubs (HSS),
low summergreen shrubs (LSS) and low evergreen shrubs (LSE). PFTs differ in
the physiological, morphological and life history characteristics that govern
their interactions and responses to climate and an evolving system state. Key
PFT parameters in the present study include C allocation, phenology, rooting
depth, tolerance for waterlogging and decomposability of PFT-derived litter
(Miller and Smith, 2012). Prescribed bioclimatic limits (Miller and Smith,
2012) and favoured annual average WTP (aWTP) ranges determine PFT
presence or absence (see Table A1 in the Appendix) and reflect their bioclimatic distribution. Shrubs are favoured in dry conditions (Malmer et al., 2005) where
aWTP is below -25 cm (we use a sign convention in which a negative value
of WTP signifies a water table below the peat surface). Conversely, mosses
and graminoids are more vulnerable to dry conditions. Graminoids favour
saturated conditions and establish when aWTP is above -10 cm, while mosses
establish when the aWTP is between +5 and -50 cm. The establishment
function is implemented annually and dependent on aWTP.
Peat accumulation arises from the balance between the annual addition of new
litter layers on top of the mineral soil column and the daily decomposition
rate. C originating from different PFTs accrues as litter in the peat layers
at variable rates depending on differences in PFT mortality, productivity and
leaf turnover. The accumulated peat decomposes on a daily time step based on
the plant litter types in each layer of a patch with decomposition rates that
are controlled by soil physical and hydrological properties in each layer.
Differences in peat decomposition rates among PFTs arise from their intrinsic
properties and structure, parameterized using an initial decomposition rate,
ko (see Table A1; Aerts et al., 1999; Frolking et al., 2001;
Chaudhary et al., 2017a), which is assumed to decline over time (Clymo et
al., 1998).
The way plants access water from the mineral soil and dynamic peat layers in
each patch, which is dependent on the combined depth of dynamic peat layers
and the mineral soil layers, necessitated a readjustment of the soil layer
representation relative to the standard version of LPJ-GUESS. In the modified
water uptake scheme, there are two static underlying mineral soil layers: an
upper mineral soil (UMS) layer and a lower mineral soil (LMS) layer at 0.5
and 1.5 m of depth, respectively. The fraction of roots in these two layers
in the absence of peat is prescribed for each PFT and determines the daily
plant uptake of water from the mineral soil (Table A1; Chaudhary et al.,
2017a). We assigned rooting depth fractions of 0.7 and 0.3 to the shrub PFTs
UMS and LMS, respectively, while graminoids were assumed to have relatively
shallow rooting depths with fractions of 0.9 and 0.1 in the UMS and LMS,
respectively (Bernard and Fiala, 1986; Malmer et al., 2005; Wania et al.,
2009b). During the initial stages of peat accumulation, plant roots are still
present in both in UMS and LMS, but as peat builds up part of the root
fraction is transferred to the growing peat layers, allowing plants to access
water from the peat soil. Mosses are assumed to take up water from the top 50
cm of peat (Shaw et al., 2003; Wania et al., 2009b) once peat height exceeds
50 cm. Before this, mosses take water only from the mineral soil. All other
PFTs can take up water from both mineral soil layers and peat layers until
peat height reaches 2 m, after which they can only access water from the
peat soil layers.
Mean modelled C accumulation rates at different timescales in 10
geographical zones.
Zone
Region
Latitude
Longitude
No. of
LARCA
ARCA
NFRCA
range (λ)
range (φ)
points (n)
(g C m-2 yr-1)
(g C m-2 yr-1)
(FTPC8.5)
(g C m-2 yr-1)
A
Scandinavia
50 to 75
0 to 30
20
17.2 ± 7.4
13.6 ± 18.2
-5.2 ± 18.4
B
Europe
45 to 75
-10 to 60
20
14.2 ± 3.7
14.2 ± 14.6
-28.1 ± 28.5
C
North-western Siberia
60 to 75
50 to 120
20
24.6 ± 14.6
35.9 ± 18.9
40.3 ± 12.1
D
South-western Siberia and parts of central Asia
45 to 60
50 to120
20
16.7 ± 8.6
39.1 ± 25.1
20.1 ± 21.2
E
Far eastern Russia and parts of central Asia
45 to 75
120 to 180
20
26.8 ± 13.8
50.7 ± 43.6
42.1 ± 23.5
F
Alaska
55 to 75
190 to 220
12
26.4 ± 16.3
32.2 ± 31.3
55.5 ± 16.3
G
Western Canada
50 to 75
220 to 240
13
26.6 ± 14.7
32.2 ± 36.5
38.5 ± 16.2
H
Central Canada and parts of the US
45 to 60
240 to 270
20
18.3 ± 7.9
24.8 ± 12.2
3.1 ± 21.0
I
Eastern Canada and parts of the US
45 to 60
270 to 300
20
25.3 ± 11.8
28.2 ± 22.1
-5.21 ± 26.1
J
Northern Canada
60 to 75
240 to 300
15
14.5 ± 14.8
23.7 ± 28.9
52.3 ± 19.2
–
Pan-Arctic
45 to 75
0 to 360
180
20.8 ± 12.3
29.4 ± 27.8
18.3 ± 47.2
Simulation protocol and data requirements
Hindcast experiments
To initialize the model with vegetation in equilibrium with early Holocene
climate, the model was run from bare ground surface conditions for the first
500 years by repeatedly recycling the first 30 years of the Holocene climate dataset (see
below). The mineral and peat layers were forced to remain saturated for the
entire initialization period. The peat decomposition, soil temperature and
water balance calculations began when the peat column reached a minimum
thickness of 0.5 m. We adopted this model initialization strategy to avoid
a sudden collapse of the peat column in very dry conditions: continuous dry periods tend to increase
temperature-dependent decomposition,
particularly for shallow peat layers, reducing the accumulation rate.
Location of 180 randomly selected simulation sites spread across 10
geographical zones between 45 and 75∘ N.
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To adequately represent the peatland history and dynamics across the major
bioclimatic domains of the pan-Arctic region, the model was applied at 180
grid points (referred to as “sites” below) distributed among 10
geographical zones spanning the circum-Arctic from 45 to 75∘ N
(Fig. 1); each zone is represented by 10–20 randomly selected points (see
Fig. 1 and Table 1). While peatland initiation started at ca. 12–13 kyr BP
in high-latitude areas, the majority of peatlands formed after 10 kyr BP
(MacDonald et al., 2006). Therefore, each simulation was run for 10 100
years and was comprised of three distinct climate forcing periods. The first
phase, the Holocene, lasted from 10 kyr before present (BP) until 0 BP.
During this period, the model was forced with daily climate fields
(temperature, precipitation and cloudiness) constructed by interpolating
between monthly values from 10 000 calendar years before present (cal BP)
until 1900. The monthly Holocene climate forcing data were prepared by the
delta-change method by applying relative monthly anomalies in temperature and
precipitation for the nearest GCM grid cell (see Sect. 2.3.2) to the site
location to their average monthly values from the CRU TS 3.0 global gridded
climate dataset (Mitchell and Jones, 2005) from the period 1901 to 1930. We
then linearly interpolated the values between the millennium time slices to
get values for each year of the simulation. This method conserves interannual
variability for temperature and precipitation from the baseline historical
climate (1901–1930) throughout the simulation. Finally, the monthly Holocene
temperature values were interpolated to daily values, while total monthly
precipitation was distributed randomly among the number (minimum 10) of rainy
days per month. For cloudiness, the monthly CRU values from the years
1901–1930 were repeated for the entire simulation period. The second
historical phase ran from 1901 until 2000. During this period, we forced the
model with the CRU data. Finally, the future scenario phase (see Sect. 2.3.2)
ran from 2001 until 2100, applying anomalies extracted for the RCP8.5-forced
GCM climate fields (Sect. 2.3.2) for each location. Annual CO2
concentration values to force our model from 10 kyr BP to 1850 AD were
interpolated from the millennial values used as a boundary condition in the
Hadley Centre Unified Model (UM; Miller et al., 2008) time slice experiments
that were run for each millennium from 10 kyr BP to 1850 AD. From the year
1850 to 2000, we used CO2 values from atmospheric or ice core
measurements.
Accurate prediction of total C accumulation at any particular location
depends on selecting the right inception period, the C content and lability
of the peat material, its bulk density over time and depth and local
hydro-climatic conditions (Clymo, 1992; Clymo et al., 1998). Bulk density and
C fraction values vary widely among different peatlands, and reliable
estimates are often lacking (Clymo et al., 1998). Basal ages, which are proxies
for peatland initiation history, are often hard to determine and are not
available for many key peatland types. For example, eastern Siberia and
European Russia are regions that have not been well studied in this regard
(Loisel et al., 2014; Yu et al., 2014a). We therefore started simulations at
the same time (10 kyr BP) for all 180 sites and fixed initial bulk
densities to 40 kg C m-3.
Commonly used measures of peat accumulation rate: long-term
(apparent) rate of C accumulation (LARCA), recent rate of C accumulation
(RERCA), actual (true) rate of C accumulation (ARCA), simulated future
long-term (apparent) rate of C accumulation (FLARCA) and near future rate
of C accumulation (NFRCA; adapted from Rydin and Jeglum, 2013).
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The carbon accumulation rate (CAR) of a peatland is the balance between
biological inputs (litter addition) and outputs (decomposition and leaching);
both input and output fluxes are quite sensitive to climate variability
(Clymo, 1991). The long-term (apparent) rate of C accumulation (LARCA) expresses
the rate of C accumulated in a peatland since its inception (Clymo et al.,
1998) and is a useful metric of the sequestration capacity of peatlands
because the current C uptake rate (ARCA; here specified as the recent
30 years) is a snapshot in time that is not expected to reflect the C balance
dynamics through the history of the peatland (Lafleur et al., 2001; Roulet et
al., 2007). We calculated the rate of C accumulation as LARCA and as the actual (net)
rate of C accumulation (ARCA; see Fig. 2). We also calculated the near future
rate of C accumulation (NFRCA) from 2001 to 2100 for the 10 studied
zones (see below).
Summary of hindcast and global change experiments.
Experiment
Experiment
Description of hindcast
no.
name
and future experiments
1.
BAS
Base experiment
2.
T8.5
RCP8.5 temperature only
3.
P8.5
RCP8.5 precipitation only
4.
C8.5
RCP8.5 CO2 only
5.
FTPC8.5
RCP8.5 including all treatments
Climate change experiments
To investigate the sensitivity of CAR to climate change, future experiments
were performed (see Table 2) by extending the base experiment (BAS) covering
the Holocene and recent past climate (to year 2000) for an additional century
to the year 2100 (Table 2). Climate output from the Coupled Model
Intercomparison Project Phase 5 (CMIP5) RCP8.5 (Moss et al., 2010) runs
performed with the Hadley Global Environment Model 2 (HadGEM2-ES; Collins et
al., 2011) was used to provide anomalies for future climate forcing.
HadGEM2-ES is an updated version of the same model chosen for the Holocene
anomaly fields. It is in the middle of the range of models contributing to
the CMIP5 ensemble in terms of simulated temperature change across the Arctic
region (Andrews et al., 2012; Klein et al., 2014). Atmospheric CO2
concentrations for model input were taken from the RCP8.5 scenario extracted
from the International Institute for Applied Systems Analysis website (IIASA;
http://tntcat.iiasa.ac.at/RcpDb/; page visited 14 June 2017). In the
first three experiments, the single-factor effect of temperature (T8.5),
precipitation (P8.5) and CO2 (C8.5) was examined, followed by a combined
experiment (FTPC8.5) in which change in all three drivers was used to force
the model. The model output variables examined here include total CAR, net
primary productivity (NPP), net ecosystem C exchange (NEE), permafrost
distribution, active layer depth (ALD) and regional soil C balance.
Model evaluation
To evaluate the model, we compared simulated CAR with regional Holocene C
accumulation records synthesized across the pan-Arctic region, hereinafter
referred to as the “literature range”. We also compared the model results for
millennial time slices with Holocene LARCA values based on the 127 sites
analysed by Loisel et al. (2014) and the 33 sites analysed by Yu et
al. (2009). The Loisel et al. (2014) dataset is more comprehensive and
contains more basal points compared to Yu et al. (2009). In Yu et al. (2009),
many key regions, such as the Hudson Bay Lowlands, western Europe, and western
and eastern Siberia, are not present, while the Loisel et al. (2014) dataset
omits some regions, such as eastern Siberia and European Russia. Furthermore,
the points in these two datasets were limited to areas south of
69∘ N (< 69).
(a) Simulated and observed mean C accumulation rate
(g C m-2 yr-1) for each 1000-year period for the last
10 000 years. Red: simulated mean (and standard error of the mean) CAR
based on 180 random sites. Blue and black points are observed C accumulation
rates (g C m-2 yr-1) based on 127 (Loisel et al., 2014; blue
points) and 33 sites (Yu et al., 2009; black points) across the northern
peatlands with error bars showing the standard errors of the means.
(b) Mean C accumulation rate (g C m-2 yr-1) for each
zone (Fig. 1) for each 1000-year period for the last 10 000 years
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Results
In Sect. 3.1, we discuss the simulated temporal and spatial patterns of
peatland C accumulation across the pan-Arctic region. Drivers and response
mechanisms underlying the simulated patterns are discussed in Sect. 3.2.
Hindcast experiment
The mean modelled CAR among all 180 sites was 35.9 g C m-2 yr-1,
after which it followed a similar temporal pattern to observed CAR values
(Fig. 3a; Yu et al., 2009; Loisel et al., 2014). The observed rate
calculated by Yu et al. (2009) shows a dip after 5 kyr BP, but the modelled
result exhibited no such deviation (Fig. 3a). The observed rate reported by
Loisel et al. (2014) is a little higher than the simulated rate before 4 kyr
BP and for the present climate. Modelled CAR was higher at the beginning of
the simulation except in Zone J (Fig. 3b). Zones A and B covering the
Scandinavian and European regions had high CAR in the beginning of the
Holocene, which then declined through the Holocene, while Zone E covering
eastern Siberia displays a peak suggesting an accelerated rate of C
accumulation by the year 1900. Almost all regions exhibited similar CAR for
7–8 kyr BP and followed different trajectories thereafter.
Simulated Holocene peat accumulation rates across the 10
zones considered in this study (blue dots) and for the pan-Arctic region as a
whole (dashed black line). The x axis shows the number of sites partitioned
into 10 zones. The black dashed line is the pan-Arctic average with standard
deviation (black line outside the y axes) and the red dashed line is the
average among zones with the standard deviation as a light red patch.
(I) Simulated long-term (apparent) rate of C accumulation (LARCA);
(II) simulated actual (true) rate of C accumulation (ARCA) for the last
30 years. Blue bars show the difference between ARCA and LARCA mean values
for the respective zone (II - I).
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Scandinavia (Zone A), Europe (B), south-western Siberia (D), central Canada (H)
and northern Canada (J) exhibit lower LARCA values compared to the pan-Arctic
average (Fig. 4 I and bars; positive bar value means C source) with northern
Canadian (J) and European (B) sites accumulating the lowest amounts of carbon
(14.5 ± 14.8 and 14.2 ± 3.7 g C m-2 yr-1,
respectively) through the Holocene. The other five zones (C, E, F, G and I)
showed relatively higher mean LARCA values, and the peatlands in eastern
Siberia (E), Alaska (F) and western Canada (G) had the highest mean LARCA
values (26.8 ± 13.8, 26.4 ± 16.3 and
26.6 ± 14.7 g C m-2 yr-1, respectively). The global mean
LARCA (black dashed line) for the 10 zones was
20.8 ± 12.3 g C m-2 yr-1 (Fig. 4I and Table 1).
Modelled September ice fraction (0–1) in the peat soil (as a proxy
for permafrost distribution) interpolated among simulation points averaged
over (a) 1990–2000 and (b) 2090–2100. (c)
Continuous and discontinuous permafrost zones and the modelled mean September
active layer depth (ALD in cm) interpolated among simulation points for
(d) 1990–2000 and (e) 2090–2100. (f) Net change in
total ALD (e–d).
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Modelled mean C accumulation rate (g C m-2 yr-1)
interpolated among simulation points for (a) 1990–2000 and
(b) 2090–2100; (c) net change in total accumulation rate
(b–a).
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Comparing mean ARCA for each zone with the respective LARCA values indicates
that the majority of sites accumulated relatively more C in the last 30 years
except Scandinavia (A), while in Europe (B) the changes were almost
negligible (Fig. 4II). The global mean ARCA for the last 30 years was
29.4 ± 27.8 g C m-2 yr-1, suggesting an upward trend in CAR
since the beginning of the Holocene (Fig. 4II and Table 1).
Simulated C accumulation rate (blue lines) for each zone (refer to
Figs. 1 and 4) and across the pan-Arctic region. The black dashed line is the
pan-Arctic average with standard deviation (black line outside); the red
dashed line is the average for the respective zone with the standard
deviation as a light red patch. (I) Average simulated near future rate of C
accumulation (NFRCA) for 2001–2100 in the FTPC8.5 experiment; (II) simulated
NFRCA in the T8.5 experiment, (III) simulated NFRCA in the P8.5 experiment
and (IV) simulated NFRCA in the C8.5 experiment. Blue bars show the
difference between the FLARCA and LARCA values for each zone.
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Interpolated values of permafrost (characterized in this study by ice
fraction in the peat soil), ALD, CAR and accumulated litter are presented for
the recent past and future climate in Figs. 5, 6 and A1. Figure 5a shows that
permafrost was widely distributed from Siberia to Canada and in parts of
northern Scandinavia around the end of the 20th century according to our model.
The majority of these permafrost areas were associated with shallow active
layers (ALD < 100 cm), while in the southern parts of Siberia and
Canada the active layers are relatively deeper (Fig. 5d). The presence of
permafrost shows no simple relationship to peatland CAR (Fig. 6a), ranging
from moderate to high litter accumulation in different permafrost areas
(Fig. A1a). Large parts of western Canada, Alaska and Siberia accumulated
relatively high amounts of C by the year 2000 (Fig. A1a) according to our
model.
Climate change experiment
In the FTPC8.5 experiment, in which all the drivers were combined, the global
mean FLARCA (20.78 g C m-2 yr-1) was largely unchanged from the
mean LARCA (20.8 g C m-2 yr-1; see Figs. 2, 4I and 7I).
However, the change in CAR was quite evident in certain geographic
zones (Fig. 7I and bars; positive bar value means C source). Some regions
showed an increase in C accumulation, while others become C neutral or sources
of C. While Scandinavian (A), European (B) and central and eastern Canadian (H,
I) sites are projected to become C sources (Fig. 7I and bars), the remaining
zones are projected to become stronger sinks in this scenario. For example,
the uptake capacity of northern Canadian (J) sites is projected to increase
fourfold, to 52.3 ± 19.2 g C m-2 yr-1 from (its LARCA
value of) 14.5 ± 14.8 g C m-2 yr-1 (Table 1 and Fig. 7I).
All zones showed a decline in CAR in the T8.5 experiment relative to the
recent historical climate (Fig. 7II); the positive effects of temperature on
soil organic matter decomposition rates explain this change. An exception to
this general pattern is seen for northern Canada (Zone J) where warming has a
positive effect on CAR (Fig. 7II and bars): higher temperatures create a more
suitable environment for plant growth in this region where cold weather and
permafrost limit plant (and therefore litter) production under present
climate conditions (see Fig. A2j). The mean modelled global NFRCA in the T8.5
experiment from 2000 to 2100 was 1.52 g C m-2 yr-1
(Fig. 7II; black dashed line). This was a significant drop when compared to
modelled LARCA and ARCA. In this experiment, the ESM-derived (Collins et al.,
2011) surface air temperature anomalies used to force our model increase by
approximately 5 ∘C by 2100 relative to 2000. Higher temperature is
associated with elevated decomposition rates, leading to more C loss and
higher heterotrophic respiration. Projected precipitation increases in the
P8.5 experiment resulted in higher CAR in all zones (Fig. 7 III and bars).
Regionally, Siberian and far eastern Russian (C, D, E), Alaskan (F) and Canadian
(G, H, I, J) sites showed the largest changes, while very little change was
seen for Scandinavia (A) and Europe (B). Elevated atmospheric CO2
enhanced photosynthesis, which led to higher CAR in the C8.5 experiment in all
zones (Fig. 7IV and bars).
Our simulations suggest that the significant temperature increase implied by
the RCP8.5 future scenario will lead to the disappearance or fragmentation of
permafrost from the peat soil and deeper active layers (Fig. 5b and e).
Additional soil water changes resulting from the effects of higher
temperatures on evapotranspiration rates could then either suppress or
accelerate the decomposition rate at many peatland locations (Fig. 7II).
Effects of precipitation changes and rising CO2 concentrations on plant
productivity can offset decomposition changes in terms of effects on the peat
accumulation rate. In the Siberian (C, D and E) and Alaskan (F) zones, the
projected higher decomposition rates are compensated for by higher plant
productivity due to increases in soil moisture and CO2 fertilization
(Fig. 7III and IV; bars), leading to a net increase in CAR by 2100 in this
scenario.
From Fig. 5b, it is evident that permafrost area declines, remaining limited
to central and eastern parts of Siberia and the northern Canadian region under
the future experiment in our model (FTPC8.5). Permafrost disappears from
large parts of western Siberia and southern parts of Canada with very little
remaining presence in Scandinavia (Fig. 5b). This degradation (Fig. 5f) leads
to wetter conditions initially in large areas of peatlands currently
underlain by permafrost. Wetter conditions together with CO2
fertilization lead to high CAR in these areas with high C build-up. In
contrast, non-permafrost peatlands showed a decline in CAR and in total
litter accumulation due to higher decomposition rates (Figs. 6b, c and A1b,
c) as a result of increases in evapotranspiration, which draw down WTP.
Discussion
Recent CAR tends to be higher compared to LARCA because older peat would have
experienced more decay losses, leaching and erosion (Lafleur et al., 2001).
This is clearly reflected in our result (Table 1) where
LARCA < ARCA in most cases, even though in our study only decay
losses were considered. The variability in LARCA among sites within a region
with relatively similar climate highlights the influence of local factors
(Borren et al., 2004). If climate was the major driving factor behind
observed variations in LARCA, then all the peatland types within one climate
zone would be expected to have similar LARCA values. LARCA is highly
influenced by local hydrology, topography, climate conditions, permafrost,
fire events, substrate, microtopography and vegetation succession (Clymo,
1984; Robinson and Moore, 2000; Beilman, 2001; Turunen et al., 2002; Turetsky
et al., 2007).
Some studies attribute differences in LARCA values to the overrepresentation
of terrestrialized peatlands and an underrepresentation of paludified or
shallow peatlands (Botch et al., 1995; Tolonen and Turunen, 1996; Clymo et
al., 1998) in estimations of this metric. Our model initialization allowed
vegetation to reach an equilibrium with the climate of 10 kyr ago, but the
model ignores the presence of ice over some parts of the study area at this
time, thus overestimating the vegetation cover at the beginning of the
simulation and leading to higher CAR than observed (Fig. 3a, b). In addition,
the underlying topography is a major factor for peat initiation and lateral
expansion of any peatland complex, but no such data are available for regional
simulations. Therefore, we assumed a moist and on average uneven horizontal
soil surface upon which peatland could potentially form at each of our 180
simulation points, ignoring the role of underlying topography and its effects
on water movement within a basin (Tang et al., 2015). However, the lateral
exchange between higher and lower patches within an overall horizontal
landscape was included in our model (see Sect. 2).
The mean modelled LARCA across the pan-Arctic study area was
20.8 ± 12.3 g C m-2 yr-1, which is a value that falls within the
reported range for northern peatlands, namely
18.6–22.9 g C m-2 yr-1 (Yu et al., 2009; Loisel et al., 2014).
However, the Loisel et al. (2014) dataset is not completely representative of
the pan-Arctic region, and data from some key regions are missing, such as
eastern Siberia and European Russia (Yu et al., 2014a). The Loisel et al.
(2014) dataset includes points that are mainly from deep or central parts and
shallow peat basins are underrepresented (MacDonald et al., 2006; Gorham et
al., 2007; Korhola et al., 2010). Furthermore, the dataset is limited to
areas south of 69∘ N. Inclusion of shallow peatland complexes and
more subarctic and arctic sites in the syntheses might conceivably bring
down the mean observed pan-Arctic LARCA value. Nevertheless, the overall
trend of the modelled pan-Arctic averaged CAR (n=180) for the last
10 kyr is quite similar to these published syntheses (Fig. 3a and b and
Table 1).
Suitable climate and optimal local hydrological conditions influenced by
favourable underlying topographical settings accelerated CAR, which led to the
formation of large peatland complexes in the pan-Arctic region (Yu et al.,
2009). High CAR is associated with high plant productivity and a moist
climate, leading to shorter residence time in acrotelm layers with generation
of recalcitrant peat or a combination of any of these factors (Yu, 2006). In
many regions, CAR is also influenced by the presence of permafrost. Under
stable or continuous permafrost conditions, CAR slows down or ceases
(Zoltai, 1995; Blyakharchuk and Sulerzhitsky, 1999) due to low plant
productivity. CAR may also become negative due to wind abrasion and
thermokarst erosion, but these factors are not considered in our simulations.
In contrast, areas underlain by sporadic and discontinuous permafrost
sequester relatively more C (Kuhry and Turunen, 2006).
Significant increases in temperature are expected at high latitudes in the
coming century, even under the most optimistic emissions reduction scenarios.
Under these conditions, some peatlands could sequester more C (Charman et
al., 2013), while others could turn into C sources and degrade (Ise et al.,
2008; Fan et al., 2013). Permafrost peatlands are sensitive ecosystems and
respond quite rapidly to temperature change and other aspects of
climate (Christensen et al., 2004). The formation of thermokarst lakes,
degradation of palsa, flooding and subsidence of the land surface are key
features that might indicate and result from rapid warming and
permafrost decay. Soil subsidence-driven pond formation has been observed to
lead to a total shift from a recalcitrant moss-dominated vegetation community
to dominance by non-peat-forming taxa, such as Carex spp. (Malmer et
al., 2005). However, the complex physical dynamics inducing such changes are
not included in our model.
Observed regional long-term rate of peatland C accumulation across
northern latitude areas.
Individualzone
Country
Extent
Type
No. of cores (sites)
Climatezone
LARCAmean(range)(gCm-2 yr-1)
Reference
Zone Aand B
Scandinavia and Europe
1.
Finland
Entire
Bogs and fens
1028
Subarcticand boreal
26.1 (2.8–88.6)
Tolonen and Turunen (1996)
2.
Finland
Haukkasuo
Bogs
79
Boreal
19.1 (16.7-22.3)
Makila (1997)
3.
Finland
Entire
Bogs and fens
–
Subarcticand boreal
21
Clymo et al. (1998)
4.
Sweden
North
Bogs and fens
10
Boreal
16 (8–32)
Klarqvist et al. (2001a)
5.
Finland
Entire
Bogs and fens
1302
Subarcticand boreal
18.5 (16.9–20.8)
Turunen et al. (2002)
6.
Finland
Luovuoma
Fen
58
Subarctic
11.8 (5–30)
Makila and Moisanen (2007)
7.
Finland
South andcentral
Bogs and fens
10
Subarcticand boreal
21.7 (19.4–24)
Makila (2011)
8.
Scotland
North
Bogs
3
Boreal
21.3 (11.5–35.2)
Anderson (2002)
Zone C,D and E
Siberia and far eastern Russia
1.
FSUa
Entire
Bogs and fens
–
Subarcticand boreal
30
Botch et al. (1995)
Siberia
West
Bogs
–
Subarcticand boreal
31.4–38.1
Botch et al. (1995)
2.
Siberia
North-west
Bogs and fens
11
Boreal
17.3 (12.1–23.7)
Turunen et al. (2001)
3.
Siberia
North-west
Bogs and fens
23
Subarctic
17.1 (5.4–35.9)
Beilman et al. (2009)
4.
Siberia
South-west
Bogs and fens
8
Boreal
19–69
Borren et al. (2004)
5.
Siberia
Kamchatka
Bogs
–
–
44.8
Botch et al. (1995)
6.
Siberia
Sakhalin
Bogs
–
–
44.8
Botch et al. (1995)
7.
Siberia
Far eastern region
Bogs
–
–
33.6
Botch et al. (1995)
8.
Siberia
Yakutia
Polygonpeatland
4
Subarctic
10.6 (8.9–13.8)
Gao and Couwenberg (2015)
Zone Fand G
Western Canada and Alaska
1.
W. Canada
–
Bogs and fens
–
Arctic,subarcticand boreal
19.4
Vitt et al. (2000)
2.
Alaska
South-central
Bogs and fens
4
Boreal
15 (5–20)
Jones and Yu (2010)
3.
Alaska
South-central
Bogs and fens
4
Boreal
11.5b
Loisel and Yu (2013)
4.
Alaska
–
Bogs and fens
–
Subarcticand boreal
12.6 (8.6–16.6)
Gorham (1991)
Continued.
Individualzone
Country
Extent
Type
No. of cores (sites)
Climatezone
LARCAmean(range)(gCm-2 yr-1)
Reference
Zone Hand I
Central and eastern Canada
1.
E. Canada
Hudson BayLowlands,Ontario
Bogs and fens
17
Subarctic
18.5 (14–38)
Packalen andFinkelstein (2014)
2.
E. Canada
Hudson BayLowlands,Ontario
Bogs and fens
1
Subarctic
18.9 (8.1–36.7)
Bunbury et al. (2012)
3.
E. Canada
Hudson BayLowlands, Quebec
Bogs and fens
2
Subarctic
24 (23.2–24.2)
Lamarre et al. (2012)
4.
E. Canada
James BayLowlands, Quebec
Bog
3
Boreal
16.2 (14.4–18.9)
van Bellen et al. (2011)
5.
E. Canada
James BayLowlands, Quebec
Bogs and fens
13
Subarcticand boreal
23.6 (17.6–38.5)
Gorham et al. (2003)
6.
N. America and E. Canada
Maine,NewfoundlandandNova Scotia
Bogs
3
Boreal
34.8 (28.5–45)
Charman et al. (2015)
7.
E. Canada
New Brunswick, Quebec,Ontario,Prince EdwardIsland,Nova Scotia
Bogs
15
Subarcticand boreal
19 (5.1–34.6)
Turunen et al. (2004)
8.
C. Canada
Upper Pintofen, Alberta
Fen
1
Boreal
31.1
Yu et al. (2003)
9.
C. Canada
Goldeye Lake
Fen
1
Boreal
25.5 (7.8–113)
Yu (2006)
10.
C. Canada
Central
Bogs and fens
14
Subarcticand boreal
24.8 (8–37.5)
Yu (2006)
11.
C. Canada
Alberta
Fens
4
Boreal
32.5 (21.4–44.2)
Yu et al. (2014b)
12.
C. Canada
Mariana Lake
Fen
Boreal
33.6 (7–70.6)
Nicholson and Vitt (1990)
13.
E. Canada
Hudson Bayand James Bay Lowlands
Bogs
8
Subarcticand boreal
23.95 (16.5–33.9)
Holmquist and MacDonald (2014)
14.
E. Canada
James BayLowlands, Quebec
Bogs
4
Boreal
22.5 (9.1–41.7)
Loisel and Garneau (2010)
15.
E. Canada
Quebec
Bogs
21
Subarcticand boreal
26.1 (10–70)
Garneau et al. (2014)
Zone J
Northern Canada
1.
N. Canada
–
–
22
Subarctic
0.2–13.1
Robinson and Moore (1999)
2.
N. Canada
Nunavut, Northwest Territories
Polygonpeatlands
4
Subarcticand low arctic
14.1 (12.5–16.5)
Vardy et al. (2000)
3.
N. Canada
Yukon
–
–
Subarctic
11
Ovenden (1990)
4.
N. Canada
–
–
–
Subarctic
9
Tarnocai (1988)
5.
N and C.Canada
Selwyn Lakeand EnnadaiLake
Peat plateau
2
Subarctic
12.5–12.7
Sannel and Kuhry (2009)
6.
N. Canada
Baffin Island
–
–
Arctic andsubarctic
0.2–2.4
Schlesinger (1990)
a FSU is the former Soviet Union.
b CAR over the past 4000 years.
In our scenario simulations (Table 2), we find that higher temperature leads
to thawing of permafrost that in turn increases the moisture availability, at
least initially. The rise in temperature also results in early spring
snowmelt and a longer growing season (Euskirchen et al., 2006), while in the
same time frame atmospheric CO2 concentration will also increase. These
factors lead to increases in plant productivity, leading to higher CAR (Klein
et al., 2013; Chaudhary et al., 2017a), even in cases where moisture- and
temperature-driven peat decomposition also speeds up.
High temperature and limited moisture conditions with limited or no
permafrost have been generally found to accelerate peat decomposition
(Franzén, 2006; Ise et al., 2008; Bragazza et al., 2016). This will also
result in the drawdown of water position and dominance of woody shrubs. The
latter trend, namely an expansion of shrubs across the Arctic and beyond in
the next half of the 21st century, is in keeping with other studies (Sturm et
al., 2005; Loranty and Goetz, 2012). Conversely, warmer and wetter future
climate conditions, in combination with CO2 fertilization, could lead to
increased CAR in areas projected to have a higher precipitation rate,
compensating for the temperature enhancement of decomposition.
We now go on to discuss the simulated responses of peatland to the
differential climate conditions of the studied regions in relation to
available literature.
Scandinavia and Europe (zones A and B)
The modelled averaged LARCA for the Scandinavian region (Zone A) was
17.2 ± 7.4 g C m-2 yr-1, within the reported literature
range between 11.8 and 26.1 g C m-2 yr-1 (Tolonen and Turunen,
1996; Makila, 1997; Clymo et al., 1998; Makila et al., 2001; Makila and
Moisanen, 2007; Fig. 4 Zone A and Table 3). A more representative LARCA
estimate derived from 1302 dated peat cores from all Finnish undrained
peatlands is 18.5 g C m-2 yr-1 (Turunen et al., 2002), which is
also quite close to our estimate. LARCA estimates from 10 sites in northern
Sweden ranged from 8 to 32 g C m-2 yr-1 with an average of
16 g C m-2 yr-1 (Klarqvist et al., 2001a). Estimates of LARCA
from Karelia in European Russia are reported as 20 g C m-2 yr-1
(Elina et al., 1984). The recent observed rate (ARCA) ranges between
8.1 and 23 g C m-2 yr-1 (mean 12.1 g C m-2 yr-1) for
Scandinavia (Korhola et al., 1995), which can be compared to the modelled ARCA
value (13.6 ± 18.2 g C m-2 yr-1) in this zone.
The modelled LARCA (14.2 ± 3.7 g C m-2 yr-1) for central
and eastern Europe (Zone B) is relatively low. However, while some sites in
this region are reported as being quite productive
(21.3 ± 3.7 g C m-2 yr-1; Anderson, 2002), long-term CAR
estimates are available for relatively few sites (Charman, 1995; Anderson,
1998), making a comparison difficult. The points that fall in the British
Isles showed lower modelled LARCA (12–14 g C m-2 yr-1) values
than the observed literature range, indicating shortcomings in the simulation of
local hydrological conditions or a possible bias in the climate forcing of
our model. A decline in CAR in Scandinavia and Europe over recent decades is
apparent in our simulations. Some observational studies also point to a
reduced rate of C accumulation in recent years for this region (Clymo et al.,
1998; Klarqvist et al., 2001b; Gorham et al., 2003). This slowing has been
attributed to an increase in decay rates due to climate and hydrological
changes, the development of a stable structure (Malmer and Wallen, 1999),
divergence in the rate of nutrient supply or a combination of these factors
(Franzén, 2006). Our model predicts that the C balance of Scandinavian
peatlands will decrease after 2050 and become C neutral, with peatland in the
European region becoming a C source in the same time frame (Fig. 7I zones A
and B). The simulated future C losses are associated with an increase in the
decomposition rate due to higher temperatures and a lower soil water table,
the latter resulting from the combination of marginal or no increase in
precipitation and soil water loss due to higher evapotranspiration.
Siberia (zones C and D) and far eastern Russia (zone E)
Large peatland complexes were formed in western Siberia during the Holocene
and around 40 % of the world's peat deposits are found in this region,
covering more than 300 million ha (Turunen et al., 2001; Bleuten et al.,
2006). LARCA for western Siberia has been estimated at 5.4 to
38.1 g C m-2 yr-1 (Beilman et al., 2009). The modelled LARCA for
the north-west and south-west region is 24.6 ± 14.6 and 16.7 ± 8.6,
respectively (Fig. 4I Zones C and D and Table 3). The combined average
modelled LARCA for the northern and south-western Siberian (C + D) zones is
20.6 g C m-2 yr-1. Turunen et al. (2001) report average LARCA
from 11 sites in north-western Siberia at 17.3 g C m-2 yr-1 (range
from 12.1 to 23.7 g C m-2 yr-1). Botch (1995) estimated relatively
higher LARCA (31.4–38.1 g C m-2 yr-1) for the raised string
bogs in western Siberia. These observations are in line with our modelled
range of 24.6 ± 14.6 g C m-2 yr-1 for the north-western
sites.
Borren et al. (2004) found LARCA values between
19 and 69 g C m-2 yr-1 for the southern taiga zones of south-western
Siberia. The modelled LARCA value for the south-western zone (D) is
16.7 ± 8.6 g C m-2 yr-1. The apparent underestimation by
our model could be explained by the relatively larger area encompassed by our
simulations, extending into warmer southerly areas with limited peat
accumulation compared to the aforementioned study (Fig. 5 Zones C and D and
Table 3). Borren and Bleuten (2006) modelled a LARCA range of
10–85 g C m-2 yr-1 (mean 16 g C m-2 yr-1) for a
large mire complex in south-western Siberia, and our value falls within this
range.
The mean observed LARCA was 10.6 ± 5.5 g C m-2 yr-1 for a
permafrost polygon peatland of far eastern Russia (Gao and Couwenberg, 2015).
Botch et al. (1995) cite CAR values of 44.8 g C m-2 yr-1 for
both the Kamchatka and Sakhalin regions and 33.6 g C m-2 yr-1 for
far eastern regions. Our modelled estimate of
26.8 ± 13.8 g C m-2 yr-1 is broadly comparable to the
range of these observations.
Our model predicted that the sink capacity (22.7 g C m-2 yr-1)
of the entire Russian region (C, D and E) was higher than the pan-Arctic
average (Fig. 4 and Table 3). In the future, higher temperature and
precipitation, together with increases in snow depth, result in permafrost
degradation that will lead to a deeper active layer in the western part of
Siberia (Fig. 5b, e). Plants experience improved hydrological conditions due
to a deeper ALD. Thawing of the permafrost in the peat and mineral soils
coupled with a longer growing season and CO2 fertilization leads to
higher plant productivity, offsetting the higher decomposition rate and leading
to an increase in CAR (Fig. 6b, c). Hence, this region is projected to act as
a C sink in the future (Fig. 7I). It is notable in our simulations that
temperature increases in the T8.5 experiment have a very limited overall
effect on decomposition rates in Russia (Zones C, D and E), while precipitation
and CO2 fertilization have a positive effect on C build-up (Fig. 7II, III
and IV).
Canada (Zones G to J) and Alaska (Zone F)
Canada's Mackenzie River basin and the Hudson Bay Lowlands are two of the largest
peatland basins in the world (Beilman et al., 2008). The individual observed
C accumulation rates vary considerably across Canada, and the LARCA for the
entire Canadian region ranges from 0.2 to 45 g C m-2 yr-1 (see
Table 3). The modelled mean LARCA value averaged among Zones G to J (the entire
Canadian region) is 21.2 g C m-2 yr-1. Most observational
studies have been carried out in the western and central regions of Canada
(Halsey et al., 1998; Vitt et al., 2000; Beilman, 2001; Yu et al., 2003;
Sannel and Kuhry, 2009). However, in recent years, studies have been
conducted in the Hudson Bay Lowlands and the James Bay Lowlands of eastern Canada (Loisel
and Garneau, 2010; van Bellen et al., 2011; Bunbury et al., 2012; Lamarre et
al., 2012; Garneau et al., 2014; Holmquist and MacDonald, 2014; Packalen and
Finkelstein, 2014). Observed LARCA in Zone I is relatively low, as peatlands
initiated later in this region due to a late Holocene thermal maximum
(5.0–3.0 kyr; Yu et al., 2009) and the presence of the remnants of the
Laurentide ice sheet (Gorham et al., 2007). In our model simulations, all
peatlands were initiated at the same time and we have not considered the
influence of ice sheet cover, which explains the higher modelled CARs
(25.3 ± 11.8 g C m-2 yr-1) in the eastern region. The
observed LARCA of the three main eastern regions in Canada is as follows: Quebec
(26.1 g C m-2 yr-1; Garneau et al., 2014), Hudson Bay Lowlands
(18.5 g C m-2 yr-1; Packalen and Finkelstein, 2014) and James
Bay Lowlands (23.9 g C m-2 yr-1; Holmquist and MacDonald,
2014). Other studies in the area have similar values (see Table 3). Our
simulations suggest that permafrost will disappear from large areas of
southern Canada under the RCP8.5 climate change scenario, leading to deeper
ALD (Fig. 5b, e). While western and northern Canadian regions sequester C at
higher rates from 2001 to 2100 in our simulations, central and eastern parts
turn into a C source over the same time period (Fig. 6c). Decomposition rates
will increase due to higher temperatures, overriding the positive gains due
to precipitation and C fertilization in central and eastern regions (Fig. 7
Zones H and I).
The majority of simulated points in northern Canada (Zone J) are in the
continuous or discontinuous permafrost region (Sannel and Kuhry, 2009).
Observed LARCA values in this zone vary from 0.2 to
16.5 g C m-2 yr-1 (see Table 3). Similarly, the modelled CAR of
the northern Canadian sites was lowest
(14.5 ± 14.8 g C m-2 yr-1) as a result of cold climate
conditions (Table 4). The mean temperature in this zone is around
-15 ∘C with a short growing season and low precipitation,
the majority of which falls as snow. In some sites, negligible CARs were
noticed due to extremely cold climate conditions that limited plant
productivity. In other subarctic regions, similar effects of cold climate
and permafrost conditions have been observed. For instance, LARCA ranges from
12.5 to 16.5 g C m-2 yr-1 for the central polygon peatlands in
western Canada (Vardy et al., 2000) and 11 g C m-2 yr-1 in the
northern Yukon (Ovenden, 1990). Similarly, polygon peat plateaus in eastern
Siberia have sequestered C at low rates (10.2 g C m-2 yr-1;
Gao and Couwenberg, 2015). Lately, owing to recent climate warming and
permafrost thaw, bioclimatic conditions have changed in these peatlands and
many of them have seen twofold to threefold increases in CAR (Ali et al., 2008;
Loisel and Garneau, 2010), indicating a recent shift toward an increased C
sink capacity. A fourfold increase in CAR associated with permafrost thaw
and increased primary productivity was simulated under future warming by our
model (Table 1 and Fig. 7 Zone J).
Alaska hosts around 40 million ha of peatland area (Kivinen and Pakarinen,
1981). Studies show that LARCA in this region ranges from 5 to
20 g C m-2 yr-1 (see Table 3). Our modelling results
(26.4 ± 16.3 g C m-2 yr-1) may be overestimations (Table 1
and Fig. 4 Zone F). The higher CAR values in our simulations are caused by
high plant productivity, moist climate conditions, the generation of
recalcitrant peat or a combination of these factors. This overestimation of
CAR in Alaska casts doubt on the simulated large future sink capacity of the
study area (55.5 ± 16.3 g C m-2 yr-1) under the RCP8.5
scenario.
Future climate impacts on peatlands
Our simulations under the RCP8.5 future forcing indicate a sharp reduction in
the area underlain by permafrost, for example in western Siberia and western
Canada, leading to an initial increase in moisture conditions or wet surfaces
there. The increase in moisture conditions can dampen the amplifying effects
of temperature on decomposition rates, leading to net increase in CAR
(Figs. 5, 6 and 7). By 2100, our model indicates that permafrost areas will
be limited to eastern Siberia, northern and western Canada and parts of
Alaska (Fig. 5b).
In the future, areas currently devoid of permafrost, mainly Europe and
Scandinavia, eastern parts of Canada and European Russia, could lose a
substantial amount of C due to the drying of peat in conjunction with a deeper
WTP (Figs. 6 and 7). In a modelling study, Ise et al. (2008) used a coupled
physical–biogeochemical soil model at a site in northern Manitoba, Canada
and found that peatlands could respond quickly to warming, losing labile soil
organic carbon during dry periods. Similarly, Borren and Bleuten (2006),
using a three-dimensional dynamic model with imposed artificial drainage to
simulate the Bakchar bog in western Siberia, indicated that LARCA will drop
from 16.2 to 5.2 g C m-2 yr-1 during the 21st century due to
higher decomposition linked to reduced peat moisture content. Our simulations
are based on climate forcing derived from the RCP8.5 scenario output from one
Earth system model (HadGEM2-ES). We expect that simulated changes in
permafrost and C accumulation would be more moderate and slower if the model
were forced with more moderate levels of climate change.
Overall, we found that Scandinavia, Europe, Russia and central and eastern
Canadian sites could turn into C sources, while C uptake could be enhanced at
other sites (Figs. 6 and 7). The greatest changes were evident in eastern
Siberia, north-western Canada and in Alaska. Peat production was initially
hampered by permafrost and low productivity due to the cold climate in these
regions, but initial warming coupled with a moisture-rich environment and
greater CO2 levels could lead to rapid increases in CAR by 2100 in this
scenario. In contrast, sites that experience reduced precipitation rates and
that are currently without permafrost could lose more C in the future.