Application of CO2 concentration gradient method for determining soil respiratory
fluxes and time delays between photosynthesis and soil respiration
Jukka Pumpanen1, Liisa Kulmala1, Pertti Hari1, Rodrigo Vargas2, Anne Ojala3, Timo Vesala4, and
Eero Nikinmaa1
1
Department of Forest Ecology, P.O. Box 27, FI-00014 University of Helsinki, Finland
Department of Environmental Science Policy and Management. University of California, Berkeley,
California, USA
3
Department of Ecological and Environmental Sciences, University of Helsinki, Niemenkatu 73, FI15140 Lahti, Finland
4
Department of Physics, P.O. Box 64, FI-00014 University of Helsinki, Finland.
[email protected], [email protected], [email protected],
[email protected], [email protected], [email protected]
2
INTRODUCTION
Soil CO2 efflux forms a substantial part of the ecosystem respiration contributing 4662% of the annual ecosystem respiration (Wang et al. 2004). Recent studies with
physiological manipulation or isotope labeling techniques have shown that as much as half of
the carbon released in soil respiration is originated from recent photosynthate (Högberg and
Read 2006). The new carbon, which is fixed during the previous days in photosynthesis
would thus have at least similar importance as a driver of soil biological processes as the
older carbon originating from the decomposition of shoot and root-derived litter. Currently,
the most widely used method for monitoring CO2 effluxes from soil is based on different
kinds of chambers attached on the soil surface. However, flux measurements on the soil
surface do not give information on the vertical distribution of CO2 sources and its seasonal
dynamics, which might be significant e.g. in boreal forests (Pumpanen et al. 2008)..
Soil CO2 efflux can also be derived from CO2 concentration gradients between soil and
the atmosphere and between different soil layers. Recently a number of studies have been
conducted to determine soil CO2 efflux from concentration gradients (Pumpanen et al. 2003
and 2008, Pihlatie et al. 2007, Tang et al. 2003, Jassal et al. 2004 and Vargas and Allen
2008). The gradient method provides a good opportunity for studying the processes
underlying soil CO2 effluxes without disturbing the soil environment. By studying the soil
profile CO2 concentrations it is also possible to determine the contribution of biological
activity at different depths of the soil to the total soil CO2 efflux in situ with a relatively small
disturbance to the respiratory mechanisms, such as fine roots and mycorrhiza.
We have applied soil CO2 concentration gradients for determining the soil CO2 efflux
and the vertical distribution of soil CO2 fluxes. In addition, we have studied the seasonal time
lags between photosynthesis and respiration using cross-correlation analysis between daily
mean values of soil respiration, temperature and gross primary productivity (Vargas et al.
2010a). Lately we are applying wavelet coherence analysis as a novel time-series method for
studying the temporal correlation between photosynthesis and soil respiration (Grinsted et al.,
2004, Vargas et al. 2010b). Furthermore, with this analysis now it is possible to determine not
only the temporal correlation between two time series, but also it is possible quantify the
phase difference or time-lag between them.
Substantial proportion of the respiratory activity of boreal forests is taking place below
the snowpack in winter. However, the measurement of soil gas fluxes through snowpack is
difficult with traditional chamber methods where the artificial air circulation generated by the
pump can modify the air pressure just above the soil and thus perturb the vertical pressure
gradient. Even a small pressure difference between the inside of the chamber and the
atmosphere, as low as 1 Pa, has been shown to cause significant errors to the measured CO2
efflux (Pumpanen et al. 2004). In a porous material, such as snow this is a particularly serious
problem. To avoid these problems, we have developed and constructed a CO2 profile
measurement system, which can be used for monitoring CO2 concentration gradient inside
the snow pack with minimal disturbance. Similar system was also adopted to measurements
of the photosynthesis lake algae (Hari et al. 2008).
MATERIALS AND METHODS
These novel methods have been tested at SMEAR II station (Station for Measuring
Forest Ecosystem-Atmosphere Relations) in a 45 year-old boreal coniferous forest stand in
Southern Finland (61º 51´N lat, 24º 17´E long, 180 m above sea level). The annual mean
temperature of the area is +2.9°C; January is the coldest month (mean –8.9oC) and July the
warmest (mean +15.3oC). The yearly precipitation averages 700 mm (Climatological
statistics in Finland, 1991). The site was sown with Scots pine seeds in 1962 on burned,
mechanically prepared soil. The soil is Haplic podzol on glacial till (FAO-UNESCO, 1990),
which is confined to a homogeneous bedrock at an average of 50-70 cm depth preventing the
vertical movement of water and air. Detailed information about the measurement station has
been provided by Hari and Kulmala (2005).
The primary method for determining CO2 concentrations in the profiles is Vaisala
GMP343 diffusion type CO2 probes (Vaisala Oyj., Vantaa, Finland). The novelty with these
sensors, compared with the technology most often applied in CO2 measurements is that they
are rugged in design, small (length 180 mm, ø55 mm, weight 360 g), have low power
consumption (<3.5 W), and are much more affordable in price than traditional CO2 gas
analysers. These characteristics make them possibly suitable for extensive field studies. The
probe is covered with a cap made of sintered PTFE enabling gas exchange between the soil
and the probe and protecting the probe from water. We have installed these sensors in a
vertical soil profile to measure soil CO2 efflux and production. In the snowpack and lake
measurements, we have used similar sensors connected to stainless steel metal tubings (inner
ø 6 mm) and elastic silicone rubber tubes (inner ø 6 mm, membrane thickness 1 mm) with
stainless steel coil inserted inside the tube. Air inside the tube system is circulated with small
diaphgram gas sampling pumps (KNF-Neuberger, Stockholm, Sweden). The system is
described in more detail in Hari et al. (2008).
Calculation of diffusion in the soil profile and in the snow requires information on the
porosity of the material, its water content and temperature. The total porosity of the soil was
obtained from soil water retention curves determined separately for each soil layer (Mecke
and Ilvesniemi, 1999) and in the snowpack the porosity was calculated based on the snow
water content. We recorded soil temperatures at the same depths as the CO2 concentration
using silicon temperature sensors (Philips KTY81-110, Philips semiconductors, Eindhoven,
the Netherlands) and volumetric water content was monitored with TDR-method (Tektronix
TDR-100 cable radar, Tektronix Inc., Redmond, WA). Volumetric water content was used to
calculate the diffusivity of each soil layer. We calculated CO2 flux between soil layers and in
the snowpack based on Fick’s first law of diffusion and by using the model presented by
Pumpanen et al. (2003, 2008). The CO2 movement between layers and from soil to the
atmosphere is mediated by diffusion, which is dependent on the total porosity of subsequent
soil layers, soil water content, the distance and the concentration gradient between the layers.
RESULTS AND DISCUSSION
Vertical distribution in the soil and in the snow
The soil air CO2 concentration gradient showed a clear vertical pattern the
concentrations being highest in the deepest soil horizons (Fig. 1a). Similar pattern was also
observed in the snow pack (Fig. 1 b). CO2 concentrations in the soil followed the diurnal and
seasonal temperature pattern, but also the soil water content affected the CO2 concentration.
The respiratory activity determined from the CO 2 concentrations in different soil horizons
also showed a clear vertical distribution the surface layers contributing more than 2/3 of the
total respiration. In the winter the contribution of deeper soil layers became more significant
(Pumpanen et al. 2003, 2008). These values are relatively well in accordance with Glinski
and Stepniewski (1985) and Pietikäinen et al. (1999) who stated that over 90% of soil
respiration activity is concentrated in the uppermost 10 cm of the soil.
5000
4500
CO2soil_22cm
CO2soil_12cm
CO2 concentration (ppm)
4000
CO2soil_7cm
3500
CO2soil_2cm
3000
2500
2000
1500
1000
500
0
9.3.07
18.1.07
29.11.06
10.10.06
21.8.06
2.7.06
13.5.06
24.3.06
2.2.06
14.12.05
25.10.05
Date
1000
CO2snow_1m
CO2 concentration (ppm)
900
CO2snow_30cm
CO2snow_15cm
800
CO2snow_5cm
700
600
500
400
300
13.5.06
23.4.06
3.4.06
14.3.06
22.2.06
2.2.06
13.1.06
24.12.05
4.12.05
14.11.05
Date
Fig.1 Daily average CO2 concentrations at different depths (a) in the soil and (b) in the
snowpack.
The CO2 efflux determined from the concentration gradients followed the diurnal
temperature fluctuation the surface soil temperatures having the most effect on the CO2
efflux. The night time CO2 effluxes determined from the concentration profiles were in
relatively good agreement with the CO2 efflux measured by the chamber method (Pumpanen
et al. 2008). However, the profile-based efflux was very sensitive to the fluctuation in the
ambient CO2 concentration directly above the soil surface and in the humus layer. This
fluctuation is probably due to other mechanisms of gas transport than diffusion such as mass
flow of CO2 in vertical wind. In order to estimate the soil CO2 efflux and respiration in the
humus layer more accurately especially during turbulent conditions, the mass flow of CO2 in
horizontal and vertical wind should be taken into account in the calculation.
Soil CO2 and photosynthesis
Reichstein et al. (2005) demonstrated that the long-term and short-term temperature
responses in ecosystem respiration are very different in summer active ecosystems such as
boreal forests. They developed an algorithm where 15-day time periods were used to estimate
the temperature sensitivity of respiration in different forest ecosystems across Europe and
compared that to the annual temperature response. Based on this algorithm, we assumed that
the temperature responses fitted over the whole spring period reflects the increase in
respiration component, which is originated from the photosynthetic products allocated to
roots such as root exudates. The amount of recent photosynthate increases slowly in the
course of spring along with the increasing photosynthesis, and this can be seen in root and
rhizosphere respiration on a longer time scale whereas the temperature response of respiring
organisms is more instantaneous process, which takes place within minutes.
Temperature response values (Q10) of soil respiration calculated for one week periods
and averaged over the whole spring in Hyytiälä were 2.54 in A-horizon, 3.66 in B-horizon
and 13.14 in C-horizon. When fitted over the whole spring, the Q10 values A-, B- and Chorizon were 3.56 (std err. 0.06), 5.57 (std err. 0.06) and 17.45 (std err. 0.35), respectively
(Pumpanen et al. 2008). These values are much higher compared to those calculated over one
week periods indicating increasing respiration of roots and ectomycorrhizal fungi during the
course of the spring. Based on the temperature responses, we estimated the contribution of
root and rhizosphere respiration in the soil to range from 2-4% in late winter to 32-35% in the
summer the contribution being highest in the C-horizon.
In the cross-correlation analysis we observed no time lags between temperature and soil
CO2 efflux and negative time lags between photosynthesis and soil CO 2 efflux (24 days) on a
seasonal scale (Vargas et al. 2010a). This could be interpreted as the seasonal pattern of soil
CO2 efflux could be driven first by a substantial increase in heterotrophic activity (after an
increase in temperature) followed by an increase in autotrophic activity (after an increase in
temperature followed by an increase in photosynthesis). In addition, we have observed a
significantly positive (P<0.05) relationship between mean annual photosynthesis and mean
annual soil CO2 efflux (Vargas et al. 2010a). Also the wavelet coherence analysis has shown
a strong temporal correlation between soil CO2 efflux and canopy photosynthesis especially
at the 1-day periods but this relationship is not consistent in time (Vargas et al. 2010b). Thus,
these analyses have shown the potential implications of continuous measurements of
photosynthesis and soil CO2 efflux at the site and have motivated further research questions
about the vertical distribution of soil CO2 production in the soil and the influence of
photosynthesis at multiple time scales.
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