Plant Soil (2010) 336:219–231
DOI 10.1007/s11104-010-0468-1
REGULAR ARTICLE
Linking root production to aboveground plant
characteristics and water table in a temperate bog
Meaghan Thibault Murphy & Tim R. Moore
Received: 22 December 2009 / Accepted: 11 June 2010 / Published online: 25 June 2010
# Springer Science+Business Media B.V. 2010
Abstract Fine root production and its relationships to
aboveground plant components and environmental
drivers such as water table have been poorly quantified
in peatland ecosystems, despite being the primary input
of labile carbon to peat soils. We studied the relationship
between fine root (< 1 mm) production, aboveground
biomass and growing season water table within an
ombrotrophic peatland in eastern Ontario. We installed
80 in-growth bags (10 cm diameter) to measure fine root
production over the full range of 40 cm in water table
depth. The point-intersect method was used to estimate
peak aboveground biomass components (total, leaf and
stem) for the 0.36 m2 area surrounding each in-growth
bag. Mean fine root production was 108±71 g m-2 y-1
and was strongly related to both aboveground biomass
and water table. Linear regression analysis showed
strong allometric relationships between fine root
production and aboveground biomass for shrubs (r2 =
0.61, p<0.001), suggesting that fine root production
estimates can be approximated using aboveground
biomass data. Water table had a significant effect on
the allocation of biomass to fine roots, leaves and
stems with a deeper water table significantly increasing
Responsible Editor: Gerlinde De Deyn.
M. T. Murphy (*) : T. R. Moore
Department of Geography and Global Environmental
and Climate Change Centre, McGill University,
805 Sherbrooke Street West,
Montreal, Quebec H3A 2K6, Canada
e-mail: [email protected]
both fine root production at depth and at each depth
increment. Shrub biomass allocation to leaves and
stems similarly shifted, with greater investment in
stems relative to leaves with a deeper water table. As a
result, greater fine root biomass was produced per unit
leaf biomass in areas with a deeper water table,
illustrating an important tradeoff between leaf and fine
root tissues in drier conditions. Our results indicate that
any drop in water table will likely increase aboveground biomass stocks and the influx of labile carbon
to peat soils via fine roots and leaves.
Keywords Root production . Allometry . Water-table .
Bogs
Introduction
Peatlands are a significant atmospheric carbon (C) sink,
storing up to 300 to 455 Pg C (∼30% of the global soil C
pool) in their soils (Turunen et al. 2002). This
atmospheric C-sink depends upon the maintenance of
peatland hydrology and temperature regimes, which
are likely to change in response to climate change, as a
result of increases in temperature and growing season
length (IPCC 2007) and increased evapotranspiration
and lowered water table levels in non-permafrost
peatlands. Such changes are also likely to significantly
alter the vascular vegetation composition, growth, and
biomass allocation patterns in these ecosystems with
numerous implications for ecosystem C cycling.
220
While Sphagnum is the main contributor to peat
formation in these systems, vascular plants also play
an important role in the cycling of C and nutrients
through above- and belowground biomass production,
turnover and decomposition. Vascular plants dominate the living plant biomass in peatlands, comprising
70% of aboveground biomass (Bubier et al. 2006) and
all belowground biomass. Belowground vascular
plant biomass can be equal to or greater than
aboveground biomass (Murphy and Moore in prep).
The fine roots and leaves of vascular plants are the
primary source of labile C to peatland soil and the
decomposition of these tissues is a key component of
nutrient cycling and a major contributor to soil carbon
dioxide flux. Understanding patterns of plant biomass
allocation to fine roots and leaves across natural
variations in water table can provide insight into how
plants may respond to future shifts in hydrology
induced by climate change.
While there are numerous studies on aboveground
biomass in peatlands, far less is known about the
belowground component (e.g. Backéus 1990; Saarinen
1996; Finér and Laine 2000; Weltzin et al. 2000),
particularly fine root production and how it relates to
aboveground plant tissues. Significant allometric relationships between root and shoot biomass have been
reported for numerous types of vegetation (e.g. Ledig
et al. 1970; Kohyama and Grubb 1994) and have
recently been quantified for the first time for vascular
shrubs in a bog system (Murphy et al. 2009b).
These biomass relationships are useful in estimating relative growth and allocation patterns to perennial tissues over time but they are unable to provide
insight into the recent allocation to foliage and fine
roots (King et al. 1999) and the functional trade-offs
between photosynthesis in leaves and nutrient and
water absorption by fine roots (e.g. Körner and
Renhardt 1987; Mortimer 1992; King et al. 1999;
Shipley and Meziane 2002). Because of the significant spatial variation in fine root and leaf biomass,
estimating relationships between fine root production
and leaf biomass and production can provide key
insights into vascular plant community biomass
allocation patterns. Elucidating how these relationships may shift in response to variations in key
environmental drivers such as water table sheds light
on the adaptive strategies of vascular plants in these
systems and how they may respond to global change
phenomena such as water table drawdown.
Plant Soil (2010) 336:219–231
We explored the relationship between belowground plant production, aboveground biomass components (i.e. total, stem, and leaf), and water table
depth at a bog in eastern Ontario, Canada. The goals
of our study were to 1) quantify belowground
production and its distribution with depth, 2) determine the impact of water table depth on total fine root
production and its distribution with depth, 3) determine the relationship between fine root production
and aboveground biomass components (i.e. total,
stem, and leaf) and 4) whether these relationships
change with water table depth. We anticipated a
rooting profile with peak production in the upper soil
profile which declines with depth in response to
similar declines in soil properties (oxygen content,
nutrient availability). We expected growing season
water table depth to be a major factor explaining the
spatial variability in root production as it limits the
total volume of aerated soil available to woody root
systems and their maximum rooting depth. Because
of the tight links between above and belowground
plant functions, we anticipated strong positive relationships between fine root production and aboveground biomass, and expected to find stronger
relationships between fine root production and leaf
biomass than either total aboveground biomass or
stem biomass, as root growth is limited by the supply
of photosynthates from leaves. As a result of these
strong links between above- and belowground components, areas with a deeper water table would have
both higher root production and aboveground biomass. Finally, we anticipated that water table depth
would influence patterns of plant allocation to
functionally different parts (leaves, stems, roots).
Greater allocation to fine root production per unit
aboveground biomass would occur in areas with
deeper water tables. We hypothesized that in this
nutrient-limited system, plants would opt to invest
more in roots to improve nutrient acquisition in drier
environments than in aboveground tissues.
Materials and methods
Site
Mer Bleue is a bog located east of Ottawa, Ontario,
Canada (45.40˚N, 75.50˚W). Peat formation began
8500 years ago and peat depth ranges between 2 and
Plant Soil (2010) 336:219–231
5 m (P.J.H. Richard, unpublished). Mean annual
temperature is 6.3°C and mean annual precipitation
is 943 mm (Environment Canada 2006). Average
growing season length (i.e. total number of days that
mean annual temperature exceeds 5°C) is 182 days
beginning in mid-April and ending in mid-October
(EarthInfo 2005).
Woody, ericaceous shrubs are the dominant vascular plants at Mer Bleue. These include the evergreen
Chamaedaphne calyculata Moench, Ledum groenlandicum Oeder, Kalmia angustifolia L., Andromeda
glaucophylla Link. and Vaccinium oxycoccus L., and
the deciduous Vaccinium myrtilloides Michx. The tree
species Larix laricina (Duroi) K. Koch. and Betula
populifolia Marshall are found sporadically through
the bog. The dominant herbaceous species is the
tufted sedge Eriophorum vaginatum L. but Maianthemum trifolium Sloboda is also common. The
distribution of species is related to hummock and
lawn microtopography and water table position, with
V. myrtilloides and C. calyculata found mostly in drier
areas of the peatland while K. angustifolia and E.
vaginatum prefer wetter areas (Bubier et al. 2006).
Measurements
In-growth bags
Fine root production was measured using in-growth
bags, constructed using a plastic mesh material (2×
1 mm) filled with unfertilized dehydrated milled
commercial Sphagnum/bog peat. The milled peat had
to be moistened with water prior to filling the bags in
order to reduce the loss of peat through the bag mesh
and to better approximate the moisture content of the
peat at the site. Once filled, the bags were 10 cm in
diameter and 70 cm long (i.e. longer than the intended
depth of insertion, to aid in core retrieval).
Installation sites were randomly selected within
hummock and lawn communities to capture a sufficient range in water table levels and aboveground
biomass stocks for consequent regression analyses of
these variables against fine root production. Bags
were pushed vertically into a hole in the peat slightly
smaller in diameter than the bags, ensuring good
contact between the bags and the surrounding peat. 80
bags were installed to depths between 45 and 55 cm
below the surface in June 2006. In some very dry
locations, cores were inserted to a greater depth (i.e.
221
60 cm) to ensure that the entire rooting profile was
sampled. In September 2006, removal of test bags
indicated little fine root growth into the bags, likely
due to the initial disturbance during installation and as
a result, the in-growth bags were removed in
November 2007. The total root biomass removed
from the cores was considered to be the root
production over the 2007 growing season.
Once removed, in-growth bags were frozen until
they were processed by thawing and cutting into
10 cm depth increments, beginning at the surface. All
roots were removed by hand from the peat. Roots in
the in-growth bags were <1 mm in diameter, and most
were first through fifth order roots in the branching
sequence ranging from 0.1 to 0.05 mm in diameter.
Roots of this branching order and diameter for
ericaceous species have been described by
Valenzuela-Estrada et al. (2008) as true fine roots
responsible for the uptake of water and nutrients.
Because tree, shrub, and herb roots were visually
distinguishable from one another, roots were separated into these three vegetation types and classified as
either living or dead. Tree in-growth roots had a
network of long roots with short thick roots branching
off, which are typical of both L. laricina and B.
populifolia. The ericaceous shrub roots were lighter in
color and often extremely fine. Herb roots were white
and thicker than both tree and shrub roots. Dead roots
were distinguished by being brittle and/or darker in
color (see Aerts et al. 1989; Sjörs 1991; Laiho &
Finér 1996).
Following separation, all roots were oven-dried for
48 h at 78°C and then weighed. The total in-growth root
weight represents the rate of fine root production over
1 year. Mean total fine root production as well as
production by depth and by functional group (tree,
shrub, herb) are reported along with standard deviations.
Aboveground biomass estimation
The aboveground vascular biomass surrounding each
in-growth bag was estimated using the point intersect
method (e.g. Jonasson 1988). Regression equations
were developed from aboveground biomass measurements at reference plots at the site and then used to
estimate aboveground biomass surrounding each ingrowth core. Equations were also developed for two
plant functional groups i.e. ericaceous shrubs and
herbs but not trees, as no trees were present
222
Plant Soil (2010) 336:219–231
aboveground in the immediate vicinity of any of the
in-growth bags although they were close by. The
regressions were based upon 26 0.6×0.6 m reference
quadrats selected to provide a range in aboveground
biomass and measured at the site in June 2007 once
plants had leafed out. Quadrats were sampled using
an 11×11 grid-pattern of 121 intersection points,
where the pins were passed vertically through the
vegetation at 61 of these points (i.e. every other point
in the grid) to reduce sampling time. Vegetation
contacts with pins were classified by species and
plant part (stem, leaf, flower, or fruit). Following
sampling in June, the plot vegetation was clipped at
the top of the moss layer and sorted by species and
plant part. The plant material was oven dried for 48 h
at 78°C and weighed.
Regression equations for aboveground biomass
based upon quadrat hits were developed for total
herbs, total shrubs, shrub stems, and shrub leaves.
Total biomass was derived by summing total shrub
and total herb estimates. The biomass for each group
was regressed against the total number of pin contacts
for each group using a linear regression model
ðy ¼ mx þ bÞ. These regressions from reference plots
were used to estimate aboveground biomass surrounding the in-growth bags (Table 1).
The point-intersect sampling around the in-growth
cores occurred between mid-July and mid-August
when aboveground biomass reaches its yearly peak.
These biomass estimates assume that point-intersect
relationships developed in June after plants had
leafed-out would be similar in July and August. In
instances when pins hit the in-growth bags, the
average number of hits per pin drop was used so as
not to skew the results. Mean biomass estimates are
reported in gm-2 along with standard deviations for
shrubs and herbs. Shrubs were further separated into
mean leaf and stem biomass.
Table 1 Point intersect regression equations for the estimation
of aboveground biomass (g m-2) at Mer Bleue bog using
contacts (x) at 61 intersection points
Aboveground biomass n
p
r2
Equation
Herb
26 < 0.001 0.89 y=0.20 x–1.18
Shrub total
26 < 0.001 0.76 y=0.90 x–13.67
Shrub leaves
26 < 0.001 0.46 y=0.36 x+8.71
Shrub stems
26 < 0.001 0.77 y=1.09 x+12.43
We also estimated the proportional area of the
different shrub species, termed total species coverage,
by summing the total number of hits for each species
within the quadrat.
Water table
Water table was measured manually 3 times in May,
July/August, and November 2007 using wells (n=80)
installed to a depth of 70 cm near each in-growth bag.
In the growing season following the removal of the
bags, we measured water levels in both the wells and
the in-growth bag holes to correct for any water table
depth differences between the holes and their reference wells. Water table levels at a subset of bags were
measured more frequently (6 times during the
growing season) to track how closely the wells
followed water table trends measured continuously
at the nearby eddy covariance flux tower. Pearson
correlations (r) between the measurements at each ingrowth bag well and those at the tower well ranged
from 0.99 to 0.76. As a result, we were able to
estimate mean, maximum and minimum water table
depth for each in-growth bag for the 2007 growing
season.
Statistical analysis
Vertical fine root production distributions were modeled using the asymptotic equation described by Gale
and Grigal (1987) and Jackson et al. (1996) for root
biomass. The equation:
Y ¼ 1 bd
ð1Þ
models the cumulative root fraction (Y) as a function
of soil depth (d, cm) with β as the biomass
distribution parameter. High β values (e.g. 0.96)
indicate a greater proportion of roots at depth, while
low values (e.g. 0.85) indicate a shallow root
distribution (Jackson et al. 1996). To determine the
role of water table on ß, ß values were calculated for
each in-growth bag and regressed against mean
growing season water table depth.
Linear regression analysis was also used to explore
the relationships among root production, aboveground
biomass components (total shrub, shrub leaf, shrub
stem), and water table depth. Model normality was
evaluated using Kolmogorov-Smirnov normality test
following Lilliefors procedure and, when necessary,
Plant Soil (2010) 336:219–231
223
variables were log-transformed. All analyses were
done using SYSTAT v. 10 (SPSS, Inc. 2000)
Results
Root production
Individual core root production values ranged from 11
to 282 g m-2 y-1 with a mean of 108±71 gm-2 y-1,
dominated by shrubs (96±8 %) (Table 2). Only a small
percentage of the roots in the cores were visibly dead
(0.35±1.15%). Root production declined significantly
with soil depth (Kruskal-Wallace non-parametric test,
p<0.001) (Table 3), with the exception of the 0–10 cm
and 10–20 cm depth increments, which had statistically similar rates of root production. Relationships
between root production and depth were reflected in
similarly significant shrub root production versus depth
relationships. Neither herb nor tree root production
differed across depth classes.
The majority of the shrub root production (72%)
occurred in the top 20 cm of the soil (Fig. 1a) and the
cumulative proportion of shrub root production with
depth was well modeled by the asymptotic equation
X=1- ßd, with an overall ß value of 0.935 (r2 =0.980).
Higher ß values were associated with a deeper
growing season water table, indicating a greater
proportion of root production occurring at depth
(Fig. 1b). An insufficient amount of herb and tree
root production made it impossible to accurately
model similar relationships with these plant functional
types.
Table 2 Belowground production (g m-2 y-1) and
aboveground biomass
(g m-2) at Mer Bleue Bog
along with mean growing
season water table depth
(cm below surface)
Aboveground biomass
Aboveground vascular biomass ranged from 121 to
971 g m-2, with a mean of 514 g m-2, composed
primarily of shrubs (99%), of which 46% was stem
biomass, 27% was leaf biomass, and the remainder
was inflorescence (Table 2). The mean root production of 108 g m-2 y-1 thus corresponds to 20 % of total
aboveground biomass and 68 % of peak leaf biomass.
Shrub species coverage was highest for C. calyculata
(46%) followed by L. groenlandicum (20%), K.
angustifolia (13%), V. oxycoccus (11%), V. myrtilloides (9%), and K. polifolia (2%). Both C. calyculata
and V. myrtilloides showed an increase in species
coverage with increasing water table depth, while the
coverage of other species showed the opposite trend
(Table 4).
Linear regression analysis outputs between belowground fine root production and aboveground biomass
components are reported in Table 5. Belowground
production was positively related to total aboveground
biomass (n=80, r2 =0.28, p<0.001, Table 5) and was
stronger for shrubs alone (n=79, r2 =0.62, p<0.001,
Table 5). Shrub stem biomass explained a greater
proportion of the variation in shrub root production
(r2 =0.62, p<0.001, Fig. 2) than shrub leaf biomass
(r2 =0.47, p<0.001, Fig. 2).
Water table
Mean growing season water table, calculated using
extrapolations between in-growth wells and continuous tower water table measurements, averaged across
Property
N
Mean±SD
Max.
Min.
Total root production
80
108.4±71.2
282.1
11.2
Shrub root production
80
106.0±71.1
277.6
11.2
Herb root production
80
1.0±2.6
12.7
0
Tree root production
80
1.4±5.0
38.6
0
Total aboveground biomass
80
514.1±204.7
971.5
120.6
Shrub aboveground biomass
80
508.6±208.6
971.5
120.6
Shrub leaf biomass
80
138.0±43.2
232.7
51.9
Shrub stem biomass
80
233.9±112.4
498.1
62.3
Herb aboveground biomass
80
5.9±14.4
74.1
0
Growing season water table depth
80
-58.0
-15.0
-42.0±9.0
224
Table 3 Mean root production (gm-2 y-1) by depth and
vegetation type. Letters
denote statistically significant differences between
soil depth classes using the
non-parametric
Kolmogorov-Smirnov test
Plant Soil (2010) 336:219–231
Depth (cm)
Total
0 to 10
38.1±19.1
a
37.8±19.1
10 to 20
30.2±20.0
a
20 to 30
21.2±19.0
30 to 40
12.5±13.2
40 to 50
5.2±7.3
d
50 to 60
0.6±1.6
e
all in-growth bag locations was 42±6 cm below the
peat surface, fluctuating by 25 cm over the course of
the season (Table 2). The 2007 mean water table
levels for the growing season are similar to the 9 year
mean of 43±11 cm for the site (1999–2007) (Fig. 3).
Fig. 1 a Mean cumulative
shrub fine root production
fraction and depth from the
surface. Error bars are standard deviation of the
mean. The dotted line
represents the asymptotic
regression to the data using
the equation x=1–ß d, where
ß describes the relative proportion of root located at
depth (see Gale and Grigal
1987; Jackson et al. 1996).
b Relationship between the
ß parameter and mean
growing season water table
depth determined for each
in-growth bag
Shrub
Herb
Tree
a
0.04±0.16
0.33±1.48
29.7±20.2
a
0.15±0.45
0.40±1.60
b
20.6±18.7
b
0.18±0.57
0.40±3.29
c
11.9±12.9
c
0.32±0.97
0.22±1.41
0.26±0.95
0.04±0.39
0.04±0.34
0.01±0.06
4.9±7.2
d
0.5±1.5
e
Over the 8 years of data collection, growing season
water table has varied from a minimum depth of 34±
4 cm in 2006 to a maximum depth of 50±10 in 1999.
Growing season water table level was positively
related to the maximum depth of fine root production
Plant Soil (2010) 336:219–231
225
Table 4 Mean contributions of individual species to aboveground cover (%) at cores grouped by mean growing season water table
depth
WT (cm)
n
% of total hits
CC
15-30
30-40
VM*
13
22.0±27.0a
28
a
34.6±23.7
ab
0.6±1.6a
6.5±11.9
ab
LG
KA
20.4±19.9
21.0±26.5a
ab
KP
VO*
EV
MT
0.3±0.5
17.3±20.1ab
17.1±20.8
1.0±2.8
1.7±4.7
14.5±17.2a
6.6±14.0
1.0±1.7
b
4.9±10.7
0.2±0.5
2.1±3.7
0.2±0.4
19.2±21.6
15.8±22.1
b
b
1.4±3.0
12.0±12.4
0.8±2.8
2.5±5.4a
40-50
20
48.2±29.5
11.0±14.5
16.5±14.8
5.6±9.1
50-60
19
58.2±28.5b
17.3±21.6b
13.5±12.7
5.3±4.6b
Letters denote statistically significant differences (p<0.05) in species aboveground cover across four different water table depth
classes using ANOVA
*Denotes differences (p<0.05) using the non-parametric Kolmogorov-Smirnov test
(Fig. 4). Overall, the maximum depth of fine root
production was greater than the mean growing season
water table depth. In all but five of these cases, shrub
roots were found at the maximum rooting depth,
indicating that the maximum water table depth is a
good indicator of the maximum depth of root
production (Fig. 4).
Similarly, total fine root production and fine root
production at each depth was positively related to
growing season water table depth (Fig. 5). The r2
values were 0.44 (0–10 cm), 0.56 (10–20 cm), 0.52
(20–30 cm), 0.58 (30–40 cm), 0.59 (40–50 cm) and
0.41 (50–60 cm), all significant at p<0.001.
Total aboveground biomass, total shrub aboveground biomass, and shrub leaf and stem biomass
were all significantly positively related to mean
growing season water table depth (Table 5). However,
total shrub biomass and shrub stem biomass had the
strongest relationship to growing season water table
depth, with r2 values of 0.53 and 0.55, respectively.
aboveground
biomass
components
as aboveground
well as the ratios
aboveTable 55 Linear
Linearregression
regression
for for
1) allometric
1) allometric
relationships
relationships
between fine
root production
(R) (g
m-2 y-1) and
biomass
(A)
ground
biomass:fine
rootproduction,
productionand(AR),
shrub leaf:stem
and 2) growing
) andtable
aboveground
depth (cm below
surface)
and fine root
aboveground
biomass
between
(g m-2) components,
fine root production
(R) (gseason
m-2 y-1water
components,
and 2) growing
season water
biomass ratios
leaf biomass
biomass:root
components
biomass (A) as
(g well
m-2) as
the ratios aboveground
biomass:fine
root production
(AR), (LS),
shrubshrub
leaf:stem
ratiosproduction
(LS), shrubratios
leaf
table depth (cm
below surface)
andand
fineshrub
root stem
production,
and production
(LR) and ratios
shrub (SR)
stem biomass:root production ratios (SR)
biomass:root
production
ratios (LR)
biomass:root
Dependent variable
r2
Independent variable
n
Total aboveground biomass
80
p
Equation
1
Total root production
a
0.28 < 0.001 R=0.16 A+30.77
Shrub root production
Shrub aboveground biomass 79
Shrub root production
Shrub stem biomass
80
0.62 < 0.001 Log10(R)=1.31 Log10 (A)–1.12
Shrub root production
Shrub leaf biomass
80
0.47 < 0.001 Log10(R)=1.74 Log10 (A) -1.79
Total aboveground biomass
Water table
80
0.35 < 0.001 Log10(A)=0.016 WT+1.99
Shrub aboveground biomass
Water table
80
0.53 < 0.001 Log10(A)=0.015 x+2.05
Shrub stem biomass
Water table
80
0.55 < 0.001 Log10(A)=0.017 WT+1.62
Shrub leaf biomass
Water table
80
0.38 < 0.001 Log10(A)=0.01 WT+1.74
Shrub leaf:stem ratio
Water table
80
0.26 < 0.001 SL=-0.01 WT+1.15
Total root production
Water table
80
0.59 < 0.001 R=5.69 WT–122.50
Shrub aboveground biomass:
Water table
fine root production ratio
Shrub stem biomass: fine root production ratio Water table
80
0.29 < 0.001 Log10(AR)=–0.014 WT+1.33
80
0.23 < 0.001 Log10(SR)=–0.012 WT+0.90
0.62 < 0.001 R=0.26 A–28.33
2
Variables were log transformed when necessary to obtain normality of model residuals
a
An outlier was removed to achieve normal distribution of residuals
226
Plant Soil (2010) 336:219–231
Fig. 2 Relationships
between fine root production and the aboveground
biomass components, shrub
stem biomass and shrub leaf
biomass. Lines and equations represent outputs from
linear regression analysis.
Values had to be log transformed to achieve normality
of model residuals
The shrub leaf:stem ratio also declined significantly
with increasing water table depth (r2 =0.26, p<0.001)
(Table 5). There were no significant relationships
between water table depth and either herb or tree
aboveground biomass due the large number of sites
where they were present only in small amounts or
absent.
The ratio between aboveground biomass and belowground production decreased with increasing water
Fig. 3 Daily water table
depth over the growing season (May to October) for
2007, mean 2007 growing
season water table depth,
mean daily water table for
1999-2007 (all based on
tower data), and the mean
water table level for all ingrowth core wells at three
sample dates during the
growing season). Error bars
are standard deviations for
the mean daily water table
depth (1999–2007)
table depth (n=80, r2 =0.29, p<0.001). Deeper water
tables yielded significantly lower shrub stem biomass:
fine root production ratios (r2 = 0.23, p < 0.001)
(Fig. 6a) and the leaf biomass: fine root production
ratios significantly declined with increasing water table
depth (Spearman rank correlation=-0.731, p<0.001)
(Fig. 6b). There was no significant relationship
between aboveground herb biomass and herb fine root
production.
Plant Soil (2010) 336:219–231
227
Fig. 4 Relationship
between maximum rooting
depth below the surface)
and mean growing season
water table depth below the
surface (cm) as calculated
from well and tower data.
Dotted line represents a 1:1
relationship and the solid
line represents the linear
regression
Discussion
Root production
The in-growth method to determine fine root production has often been criticized in studies that last less
than 2 years, given the delay of root growth into bags
following installation, which can also differ across
species (Persson 1979; Neill 1992; Finér and Laine
2000). We noted a similar delayed response in root
growth after the first summer of installation, as very
few roots had penetrated a group of 5 in-growth bags
that were removed in September 2006. We attribute
this limited response in the first growing season to
Fig. 5 Relationship
between total root production (gm-2 y-1) and growing
season water table depth
below the surface (cm)
disturbance and believe our root production estimate
(108±71 g m-2 ) to be a more accurate reflection of
root growth over the 2007 growing season; however,
an additional 3 months of incubation in 2006
(September to November) has likely produced a
over-estimation of annual production. Finér and Laine
(2000) have reported root production values between
60 and 225 g m-2 y-1 derived from a 3-year in-growth
bag study in other Finnish peatlands. The dwarf-shrub
pine bog site from that study yielded root production
similar to ours (119 g m-2 y-1, derived from subtracting production estimates from year 1 and 2 in-growth
bags). Root production in another Finnish bog system
yielded considerably smaller rates of production over
228
Plant Soil (2010) 336:219–231
Fig. 6 Relationships between water table and a
shrub stem biomass: shrub
fine root production ratio,
and b shrub leaf biomass:
shrub fine root production
ratio. Lines represent output
from linear regression analysis. Spearman rank correlation was conducted for the
dataset whose model residuals were normal following
log transformation
a 1 year incubation period (62±29 g m-2 y-1 )
(Murphy et al. 2009a).
Overall root production is highest in the upper
20 cm of the peat profile (comprising 72% of total
root production) and declines significantly at subsequent depths. Plants likely concentrate their root
production in the upper soil profile in response to
greater oxygen and nutrient availability in these upper
peat layers. In bog systems, surface litter decomposition and atmospheric deposition are the primary
processes that provide plant nutrients, concentrating
them in the upper profile. This contrasts with coarse
root biomass, which does not decline with depth in
this peatland (Murphy et al. 2009b) likely due to the
dominance of buried stems comprising the coarse root
fraction (Wallén 1986).
Water table and root production
The considerable spatial variation in root production
(11, to 282 g m-2 y-1) at Mer Bleue is closely linked to
variations in water table depth. Our study indicates
that in areas with a deeper water table, total root
production, root production at depth, and maximum
rooting depth are all higher likely as a result of a
greater volume of aerated soil in these environments.
While root production declines with depth across all
sample locations regardless of water table depth, the
Plant Soil (2010) 336:219–231
proportion of roots at depth increases in locations
with deeper water tables. The dominant shrubs at Mer
Bleue have root systems that are poorly adapted to
anoxia, as shown by the limited root growth occurring
below the maximum growing season water table
where soils remain waterlogged throughout the
growing period. Given that the water table fluctuated
by ∼30 cm over the course of the growing season, it
appears that the plants can increase their rooting depth
accordingly both through the growing season, and
potentially across years.
Because woody species appear to capitalize on
lower water table periods during the growing season
by increasing rooting depth during these periods,
annual variations in growing season water table depth
can have significant implications for both root
production rates and the volume of soil that fine roots
can exploit. Continuous water table data collected
from 1999–2007 indicate that the water table trends
for the 2007 growing season were similar to the
9-year mean. However, trends can vary considerably
from year to year, particularly at the peak of the
growing season (August) when plants are most active.
Both in 2001 and 2002, maximum water table depth
was over 20 cm below the maximum depth recorded
for 2007 and lasted for 4 and 5.5 weeks, respectively.
Thus considerable variation in both the duration of the
water table drawdown as well as its extent can likely
produce significant inter-annual variation in fine root
production that can contribute to significantly to interannual variations in ecosystem C cycling.
The influence of water table on rooting depth may
be less sensitive in systems that are dominated by
other plant functional types such as sedges. Sedges
such as E. vaginatum have aerenchyma (air channels)
in their roots, which facilitate the transfer of oxygen
from aboveground to the rhizosphere, allowing roots
to survive well below the water table. At Mer Bleue,
several cores that were dominated by E. vaginatum
roots had maximum rooting depths that exceeded the
maximum growing season water table depth.
Vascular plant species distributions are closely tied
to water table level at Mer Bleue. Our study indicates
that C. calyculata and V. myrtilloides increase their
relative aboveground coverage as water table
becomes progressively deeper. The other shrubs and
the herbs increase their coverage as water becomes
shallower. Similar observations linking water table
and species distributions have been made previously
229
at this site (Bubier et al. 2006). While we were unable
to distinguish shrub root in-growth by species, the
relative contributions of different shrub roots to total
production likely differs depending on water table
depth. Thus, a portion of the variability in the
relationship between root production and water table
could be explained by these shifts in species composition, if different species have inherently different
root production rates and rooting distributions.
Allometry and water table
We found strong allometric relationships between root
production and aboveground biomass at our site,
which could be used to estimate root production
within and among shrub-dominated bogs (Murphy et
al. 2009a). Relationships were strongest when only
shrubs were considered because the ability of herbs to
extend roots into anoxic layers contributes to inherent
differences in root:shoot allocation among plant
functional types (Murphy et al 2009b) and thus to
weaker above- belowground relationship when all
growth forms are considered together. As with
biomass, root production relationships might be
further improved if broken down by species (Mokany
et al. 2006, Murphy et al. 2009b). However, it
remains impossible to visually distinguish shrub fine
roots by species in in-growth bags.
These positive relationships between aboveground
biomass and root production reflect the functional
importance of both roots and shoots in resource
demand and acquisition. Greater aboveground biomass and root production will increase demands for
photosynthates from shoots and nutrients and water
from roots, which in turn increases allocation to these
organs. The overall driver of variations in aboveground biomass and root production is water table
level. Water table level limits the volume of aerated
soil that shrubs can exploit for nutrients, restricting
overall plant size and growth (Gorham 1991, Choi et
al. 2007). As water table level declines, shrub
biomass and root production increase.
Given that higher root production increases the
demand for photosynthates, we expected that root
production would be better predicted by leaf rather
than stem biomass as leaf biomass approximates
potential photosynthate production (e.g. Vanninen
and Mäkelä 1999; Poorter and Nagel 2000). However
the stronger relationship between root production and
230
stem biomass is likely a reflection of larger plants
requiring more water and nutrients from belowground. Additionally, stem biomass shows a much
more plastic response to spatial differences in water
table than leaves, better reflecting overall shifts in
total plant size (Murphy et al 2009a).
While the overall effect of lower water table levels
is larger aboveground biomass and faster rates of
belowground fine root production, there are important
shifts in relative allocation between aboveground
components (leaf and stem) and belowground production. Aboveground, shrubs allocate proportionally
more biomass to stems (via increase density and
height) than leaves with increasing water table depth,
(Table 5) (Luken et al. 1985, Murphy et al. 2009a, b).
In response to light competition from increased
aboveground growth, plants increase stem height to
reduce leaf shading and improve light capture (Aerts
et al. 1991)
Overall, more biomass is allocated to fine root
production per unit of stem (Fig. 6a) or leaf biomass
(Fig. 6b) with a deeper water table corresponding to
similar shifts in wetland water table manipulations
(Megonigal and Day 1992; Weltzin et al. 2000).
Weltzin et al. (2000) noted that while drier plots had
greater biomass production above and belowground,
the increase was significantly greater belowground.
The observed trade-offs between leaves and fine roots
in this study have been noted by others in relation to
the availability of resources (King et al. 1999; Shipley
and Meziane 2002). Based on optimal growth theory
(e.g. Thornley 1972; Chapin et al. 1987), plants favor
allocation to plants parts responsible for obtaining the
resources most limiting to plant growth. At Mer
Bleue, resource acquisition belowground (i.e. water
and nutrients) appears to be the priority for plants in
drier areas.
Implications for C cycling
The patterns observed across micro-sites in this
system correspond to similar plant responses to water
table drawdown observed in manipulation experiments (e.g. Weltzin et al. 2000, Murphy et al. 2009a)
suggesting that spatial variations in water table can
serve as a proxy for community responses to water
table drawdown. Overall, the increase in fine root
production in lower water table environments represents a significant increase in C flux to peat.
Plant Soil (2010) 336:219–231
Minirhizotron experiments indicate that fine root
lifespan is less than 0.2 years for Vaccinium spp.
(Valenzuela-Estrada et al. 2008) and 0.5 to 2.5 years
for tree species (Withington et al. 2006). Increased
additions of this labile carbon or the exudates that live
fine roots produce may either increase peat decomposition via a priming effect (e.g. Dijkstra et al.
2006), or slow soil organic matter decomposition as
microbes preferentially use high quality exudates in
place of soil organic matter or root litter for substrate
(Loya et al. 2004). Additionally, the greater aboveground biomass stocks (particularly leaf biomass) can
yield greater aboveground litter inputs to soils. Future
research is needed to determine the fate of various
plant components including fine roots, leaves and
stems produced in these systems and the overall effect
of these changes to ecosystem C cycling.
What is clear from this study is that significant
differences in biomass allocation to various plant
parts emerge within sites based upon spatial variations
in water table. Thus, in order to understand the
variability in fine root production in relation to
biomass stocks within and among sites, a clear
understanding of water table characteristics and
dynamics is essential.
Acknowledgements The authors thank the Fond Québécois
pour la Recherche sur la Nature et les Technologies and the
Natural Sciences and Engineering Research Council of Canada
for funding. We thank the National Capital Commission for
permission to use Mer Bleue. We thank Lillian Ames, Jacob
Pluta, and Nicole Sanderson for their help in the lab as well as
Iva Borojevik, Greg McKay, and Rose Smith for their help in
the field. We thank Elyn Humphrey for providing tower water
table data. Finally we thank the anonymous reviewers for their
comments on the manuscript.
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