This article appeared in a journal published by Elsevier. The attached
copy is furnished to the author for internal non-commercial research
and education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling or
licensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of the
article (e.g. in Word or Tex form) to their personal website or
institutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies are
encouraged to visit:
http://www.elsevier.com/copyright
Author's personal copy
Forest Ecology and Management 261 (2011) 1090–1098
Contents lists available at ScienceDirect
Forest Ecology and Management
journal homepage: www.elsevier.com/locate/foreco
Soil CO2 efflux in an Afromontane forest of Ethiopia as driven by seasonality and
tree species
Yonas Yohannes a,b,∗ , Olga Shibistova a,c , Asferachew Abate a , Masresha Fetene d , Georg Guggenberger a
a
Institute of Soil Science, Leibniz Universität Hannover, Herrenhäuser Str. 2, 30419 Hannover, Germany
Forestry Research Center, Ethiopian Institute of Agricultural Research, P.O. Box 41957, Addis Ababa, Ethiopia
VN Sukachev Institute of Forest, SB-RAS, Akademgorodok, 660036 Krasnoyarsk, Russian Federation
d
Department of Biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia
b
c
a r t i c l e
i n f o
Article history:
Received 27 June 2010
Received in revised form
24 December 2010
Accepted 25 December 2010
Available online 15 January 2011
Keywords:
Croton macrostachys
Ethiopia
Podocarpus falcatus
Prunus africana
Soil CO2 efflux
Soil moisture
Soil respiration
Soil temperature
Tropical forest
a b s t r a c t
Variability of soil CO2 efflux strongly depends on soil temperature, soil moisture and plant phenology.
Separating the effects of these factors is critical to understand the belowground carbon dynamics of forest
ecosystem. In Ethiopia with its unreliable seasonal rainfall, variability of soil CO2 efflux may be particularly
associated with seasonal variation. In this study, soil respiration was measured in nine plots under the
canopies of three indigenous trees (Croton macrostachys, Podocarpus falcatus and Prunus africana) growing
in an Afromontane forest of south-eastern Ethiopia. Our objectives were to investigate seasonal and
diurnal variation in soil CO2 flux rate as a function of soil temperature and soil moisture, and to investigate
the impact of tree species composition on soil respiration. Results showed that soil respiration displayed
strong seasonal patterns, being lower during dry periods and higher during wet periods. The dependence
of soil respiration on soil moisture under the three tree species explained about 50% of the seasonal
variability. The relation followed a Gaussian function, and indicated a decrease in soil respiration at
soil volumetric water contents exceeding a threshold of about 30%. Under more moist conditions soil
respiration is tentatively limited by low oxygen supply. On a diurnal basis temperature dependency
was observed, but not during dry periods when plant and soil microbial activities were restrained by
moisture deficiency. Tree species influenced soil respiration, and there was a significant interaction effect
of tree species and soil moisture on soil CO2 efflux variability. During wet (and cloudy) period, when
shade tolerant late successional P. falcatus is having a physiological advantage, soil respiration under
this tree species exceeded that under the other two species. In contrast, soil CO2 efflux rates under light
demanding pioneer C. macrostachys appeared to be least sensitive to dry (but sunny) conditions. This is
probably related to the relatively higher carbon assimilation rates and associated root respiration. We
conclude that besides the anticipated changes in precipitation pattern in Ethiopia any anthropogenic
disturbance fostering the pioneer species may alter the future ecosystem carbon balance by its impact
on soil respiration.
© 2010 Elsevier B.V. All rights reserved.
1. Introduction
Despite of the general concern that tropical forests, and particularly intact African forests may play an important role as a carbon
sink in the global terrestrial carbon cycle (Ciais et al., 2009; Lewis
et al., 2009; Stephens et al., 2007), the size of the carbon stocks and
the carbon fluxes in these ecosystems still remain highly uncertain,
especially with respect to potential effects of climate change and
anthropogenic disturbances.
∗ Corresponding author. Present address: Institute of Soil Science, Leibniz Universität Hannover, Herrenhäuser Str. 2, 30419 Hannover, Germany.
Tel.: +49 51176219015; fax: +49 5117625559.
E-mail addresses: yonyoh4@gmail.com, yonas@ifbk.uni-hannover.de
(Y. Yohannes).
0378-1127/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.foreco.2010.12.032
Soil CO2 efflux is one of the largest components in the terrestrial carbon budget (Raich and Schlesinger, 1992), with the
global magnitude in the order of 98 Pg C per year (Bond-Lamberty
and Thomson, 2010). Contributing more than 50% to the ecosystem respiration across variety of biomes (Janssens et al., 2001;
Schlesinger, 1997; Shibistova et al., 2002), soil respiration determines the ecosystem carbon balance and thus an ecosystem sink
or source activity (Valentini et al., 2000). Yet to date there has only
been a limited amount of data available on soil efflux and its abiotic
and biotic determinants for Eastern Africa (Werner et al., 2007) and,
likewise, comparative studies across major ecosystems are scarce
(Bahn et al., 2010).
Among the climatic conditions controlling soil respiration in
different ecosystems on hourly, weekly and seasonally scale, soil
temperature and soil moisture are considered to be the two most
Author's personal copy
1091
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
18
2008
2009
2008
2009
Air temperature, oC
17
200
150
16
100
15
50
14
13
Precipitation, mm
influential parameters (Davidson et al., 1998; Reichstein et al.,
2003; Rustad et al., 2000). While the relationship between soil CO2
efflux and soil temperature often is described by a simple exponential function (Davidson et al., 2000; Lloyd and Taylor, 1994; Qi
et al., 2002), there is no common agreement on the type of relation
between soil moisture and soil respiration. For example, working
in an old-growth neotropical forest in Costa Rica, Schwendenmann
et al. (2003) found a parabolic relation, while Kosugi et al. (2007),
working in a Southeast Asian lowland rain forest, identified a linear
dependence of soil CO2 efflux on soil moisture. Epron et al. (2004)
used an exponential regression to fit a relation between soil water
content and the seasonal variability of soil respiration. Strong effect
of soil moisture on temporal pattern of soil respiration has been
shown in some tropical forests and plantations (e.g., Epron et al.,
2004; Hashimoto et al., 2004; Kosugi et al., 2007; Ohashi et al.,
2008), but just a weak (Salimon et al., 2004) or even no correlation
(Adachi et al., 2006) between soil temperature and soil respiration
in primary and secondary forests has been reported. In a tropical plantation of New French Guiana, Bréchet et al. (2009) showed
no significant relationship between soil respiration and both, soil
temperature and soil moisture on a seasonal scale.
Spatial variability of soil CO2 efflux is primarily affected by
biotic factors. So Bréchet et al. (2009) stated that variability of soil
respiration was mainly explained by leaf litterfall. Oscar (2007)
emphasised the role of different tree species and noted that their
different fine root production explained much of the spatial variability in soil CO2 efflux. Leaf and total aboveground litter (leaf, bark
and woody debris) have also been reported to have an effect on soil
respiration (Epron et al., 2004).
In this context, long term measurements of soil CO2 efflux with
concurrent climatic record are needed to understand the influence
of abiotic and biotic drivers on the magnitude of soil CO2 efflux.
Here, we report on seasonal and diurnal pattern of soil respiration measured underneath a natural mixed evergreen-deciduous
Afromontane forest, growing in Ethiopia, East Africa. The Munessa
Shashemene forest is one of the largest Afromontane forests in the
country. The soil organic carbon pool (0–60 cm depth) of the forest
is appreciably high (134 Mg ha−1 ) and is within the range of similar
ecosystems (Lemenih and Itanna, 2004). We carried out our studies under three different tree species: Croton macrostachys Hochst,
Podocarpus falcatus (Thumb.) R.BR.ex and Prunus africana (Hook.
F.) Kalkman. These tree species differ in a variety of traits, such
as crown architecture (Bekele-Tesemma et al., 1993), depth and
distribution of roots (Fritzsche et al., 2006), and CO2 assimilation
rate and water relation (Fetene and Beck, 2004; Lüttge et al., 2003).
The tree species also represent different functional types according
to Whitmore (1989). Croton macrostachys is a pioneer deciduous
tree, while P. falcatus and P. africana are late successional evergreen
trees, the first being coniferous and the second broadleaf. Podocarpus falcatus and P. africana are among tree species that are locally
threatened by extinction as a result of illegal cutting and encroachment. Such activities created gaps that favor the abundance of
the pioneer tree species C. macrostachys and diverse shrubs at the
expense of climax species. This anthropogenically driven change in
relative abundance of tree species may bring modifications in the
stand-level carbon balance.
The objective of the present study was, first, to analyze seasonal and diurnal variation in soil CO2 flux rate as a function
of soil temperature and soil moisture. Since Ethiopia is characterized by a strong seasonality of precipitation, we assume soil
moisture as the major abiotic driving factor. As a second objective, we were addressing the impact of different functional-type
forest tree species on soil CO2 efflux. Here, we hypothesised that
soil CO2 efflux under deciduous pioneer C. macrostachys shows a
larger seasonal variability than that under the late successional tree
species.
x
Jan Feb Mar
Apr May
Jun
Jul Aug Sep
Oct Nov Dec
0
Month
Fig. 1. Monthly total precipitation (bar graph) and mean monthly air temperature
(line graph) for the years 2008 and 2009 measured at the Kuke field station being
adjacent to the experimental plots (data from Strobl et al., unpublished). x shows
missed data in November 2009 due to rain gauge failure.
2. Materials and methods
2.1. Study site
The Munessa-Shashemene forest is located in Oromia Regional
State on the eastern escarpment of the southern Main Ethiopian
Rift Valley, about 240 km south of Addis Ababa. The forest area,
23,000 ha in size, is divided into three blocks; namely Gambo, Sole
and Degaga. For the present study, the experimental plots were
established in the Degaga block (07◦ 25′ 51′′ N and 038◦ 51′ 52′′ E). The
elevation is at 2266–2279 m above sea level. Mean annual temperature is 15 ◦ C and mean annual precipitation is about 1200 (data
from Ethiopian Meteorological Agency at Degaga town, 07◦ 26′ 00′′ N
and 038◦ 50′ 26′′ E). The study site is located at the central area of
the country, with a minor rainy season occurring from March to
May and a major rainy season from July to November (Griffits,
1972). Own meteorological records since 2001 show that 80% of
the annual precipitation fell in the major rainy season from July to
November, and no clear indication of a minor rainy season could
be made (Strobl et al., unpublished). Further, the monthly precipitation pattern outside the major rain season varied considerably,
e.g. in the years 2008 and 2009 (Fig. 1). Total annual precipitation
in both years was similar, with 1133 mm in 2008 and 1036 mm
in 2009. Mean annual air temperature corresponded well to the
average value, with 14.7 ◦ C in 2008 and 15.3 ◦ C in 2009.
Soils of the study area are rich in clay evolved from volcanic
parent material (Fritzsche et al., 2007). At the experimental plots
they were classified as Mollic Nitisols according to the WRB system (FAO, 1998). Vegetation of the natural forest is dominated
by the canopy species P. falcatus and C. macrostachys. Other plant
species with relatively less abundance include P. africana, Syzygium guineense (Wild.) DC., Celtis africana Burm. f. and Pouteria
adolfi-friederici (Engl.). The forest is strongly degraded by grazing
and illegal logging activities leading to its transformation from a
primary to secondary forest.
2.2. Experimental setup and soil CO2 efflux measurement
Since a major goal of our study was to assess the temporal
and spatial variability of the soil CO2 efflux with respect to the
interrelationship of tree species with abiotic factors, the study was
carried out on an individual tree basis. In June 2008, for each of
the three tree species, C. macrostachys, P falcatus and P. africana,
three individual juvenile trees of the third height class (Tesfaye
et al., 2010) were selected. In total, nine experimental plots were
Author's personal copy
1092
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
Table 1
Basic characteristic of the soils under the studied trees.
Tree/soil depth
C. macrostachys
0–10 cm
10–25 cm
P. falcatus
0–10 cm
10–25 cm
P. africana
0–10 cm
10–25 cm
a
b
c
d
e
f
Sanda (g kg−1 )
Silta (g kg−1 )
Claya (g kg−1 )
Cb (g kg−1 )
Nb (g kg−1 )
pHc
CECd
(mmol(+) kg−1 )
BSe (%)
Pavail f (mg kg−1 )
211 ± 6
219 ± 2
379 ± 20
301 ± 24
410 ± 26
480 ± 25
138 ± 20
64 ± 8
11.7 ± 0.6
5.9 ± 0.5
6.7 ± 0.04
6.5 ± 0.44
732 ± 24
498 ± 63
100
100
26 ± 8.5
9.5 ± 5.1
180 ± 3
214 ± 4
409 ± 20
304 ± 20
411 ± 17
482 ± 24
116 ± 11
66 ± 13
11.5 ± 0.5
6.5 ± 0.8
6.5 ± 0.15
6.2 ± 0.20
565 ± 55
376 ± 42
100
100
15 ± 2.4
8.6 ± 2.4
195 ± 5
222 ± 8
405 ± 37
319 ± 27
400 ± 32
459 ± 36
122 ± 9
80 ± 3
12.2 ± 0.3
8.2 ± 0.3
6.6 ± 0.13
6.5 ± 0.16
640 ± 45
497 ± 49
100
100
16 ± 3.0
8.6 ± 0.3
Measured by the pipette method (Gee and Bauder, 1986).
Total carbon and nitrogen measured by dry combustion (Elementar Vario EL, Hanau, Germany).
Analyzed potentiometrically in 1 M KCl [1:2.5 (m/v)].
Cation exchange capacity determined with the BaCl2 compulsive exchange method (Gillman and Sumpter, 1986).
Base saturation.
Available phosphorus measured after extraction with Bray I (Bray and Kurtz, 1945). Values are mean and standard deviation of three replicated samples.
established, with three replicates for each tree species within a
distance of about 100 m. For characterization of the soils underneath the canopies, soil samples were collected from each plot
before the start of soil CO2 efflux measurement campaign. Core
soil samples (cylindrical steel core with 4.0 cm diameter) were
obtained separately in triplicate from 0–10 and 10–25 cm depths
under the canopy of each experimental tree. Soil samples collected
under the canopies of same tree species were bulked. According to
Table 1, the soil under C. macrostachys tends to have a higher pH,
appears to be richer in organic carbon and nitrogen, and has a larger
cation exchange capacity and more available phosphorus than that
under the other tree species. The better soil nutritional status
under C. macrostachys is likely due to the larger nutrients content in its leaves as compared to the other two tree species (Zech,
unpublished). With litter fall, the nutrients are returned to the
topsoil.
To assess the seasonal and diurnal variation of soil CO2 efflux,
five permanent soil collars (20 cm in diameter and 5 cm long) made
from PVC were inserted in the soil at randomly selected positions
underneath the canopy of each individual tree. To minimize any
influence of mechanical disturbance of soil surface on diffusion
rates, and to avoid cutting of fine roots, the soil collars were inserted
into the soil not more than 2 cm. The collars were sealed at the outside with fine sand. Herbaceous understory vegetation was avoided
during collar set-up. However, when, in the following two years
period, any vegetation grew inside the collars, it was clipped back.
Once inserted, soil collars were left in place throughout the measurement period.
Soil CO2 efflux from the forest floor was measured using an
Infrared Gas Analyzer (Li-8100, LI-COR, Lincoln, NE, USA) supplied
by a LI-8100-103 Soil Survey Chamber. For each measurement,
the soil respiration chamber was placed on each collar, and CO2
flux rate was automatically calculated from exponential regression of increasing CO2 concentration over the 2–3 min following
chamber equilibration. For each of the tree species mean CO2
efflux rates were calculated from the 15 chamber measurements
obtained during individual sampling events. The measurements
began on July 11, 2008 and have been carried out on a weekly basis
between 12:00 h and 15:00 h until July 24, 2010 with the exception of October–November, 2009 due to an instrument failure. No
measurements were also taken during or immediately following
rainfall. Diurnal soil CO2 efflux measurements were performed over
a 24 h period at a 4 h interval. Three days representing different soil
moisture categories were selected: 03 July 2008 (wet season); 06
December 2008 (transition from wet to dry season) and 15 March
2009 (dry season).
Soil temperature (◦ C) at a depth of 0.1 m was monitored within
10–20 cm distance of each collar simultaneously with soil CO2
efflux measurements using a thermocouple probe (Li-8100-201)
connected to the Li-8100. The volumetric soil water content at
0.06 m depth was measured adjacent to each PVC collar with a theta
probe (ML2, Delta-T Device Ltd., Cambridge, UK) at three replicates
around the collars (the data is available from May 30, 2009).
At a representative place between the plots air temperature
underneath the forest canopy, canopy precipitation and soil moisture data were obtained at a weather station. Temperature was
measured continuously using 8-bit temperature sensor (Onset
Computer Corporation, Bourne, Massachusetts), while precipitation was measured on weekly basis using five randomly distributed
polyethylene funnels with a 120 mm upper diameter. Volumetric
soil water content was recorded using frequency-domain reflectometer (ECHO probe, Decagon Devices Inc., Pullman, WA) probe
installed at 0.1 m depth.
2.3. Data analysis
We separated dry and wet periods following the approaches of
Gibbs and Maher (1967), where the distribution of precipitation
events over a long-term record is divided into sections for each
ten percent of the distribution. Such rainfall deciles were calculated from ten years historical rainfall data (1998–2007) obtained
from a nearby metrological station (Degaga town 07◦ 26′ 00′′ N and
038◦ 50′ 26′′ E). By definition, the fifth decile is the median, and it
is near normal classification of wet and dry periods. According to
Gibbs and Maher (1967), we used the fifth decile range as a cut-off
for dry and wet period classification. Based on that months with
more than 55.2 mm rainfall were defined as wet periods and the
drier periods are months that received less than 55.2 mm rainfall. This categorized December 2008 to May 2009, December 2009
and January 2010, and March 2010 as dry months while the other
months belonged to the wet seasons.
To account for changes in the environmental variables, soil
moisture and soil temperature and their interactions with the tree
species over the course of the study periods were analyzed with
regression approaches to analysis of variance (ANOVA). A general
linear model was fitted with soil CO2 efflux rate as response, and
tree species and season (wet vs. dry) as categorical explanatory variables. Soil moisture and soil temperature were fitted into the model
as numerical covariates. The model terms were fitted sequentially
and ANOVA (type I sums of squares) was computed leading to
F-tests for the main effects and interactions. We fitted the covariates sequentially in the order soil moisture then soil temperature.
Author's personal copy
1093
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
Homoscedastic residuals were obtained with untransformed values. Statistical differences were significant if the probability of type
I error was less than 0.05. On the other hand, to analyze the interannual soil CO2 variability among and between the tree species,
we averaged soil CO2 efflux data over the wet and dry periods for
both years of observations. Then the data set was analyzed using a
three-way ANOVA, with factor effects (tree species, years of observation (first year vs. second year), and season (wet vs. dry)). When
ANOVA results indicated significant difference, Tukey’s HSD test
was performed.
The data for all measurements with both, soil moisture and
soil temperature values available from 30 May 2009 to the end
of the experiment, were analyzed using nonlinear regression. The
objective of the analysis was to describe the dependence of soil
respiration on soil moisture alone and jointly with soil temperature under the three tree species separately. Models were fit using
non linear least squares method in R 2-11.0 (R Development Core
Team, 2009). The performances of the equation were evaluated
by goodness-of-fit measures (Root Mean Square Error (RMSE), and
r2 ). Since in preliminary graphical analysis, the non-linear relation
between soil respiration and soil moisture was prominent, while a
potential dependency of soil respiration on soil temperature was
only weak, we initially modelled the dependency of respiration on
soil moisture by different nonlinear models. The Gaussian model
was fitting best for all three species both in terms of maximal r2
values and fitting the downturn of soil respiration rates for high
soil moisture values (Eq. (1)). After fitting the first part, different
models for including the effect of soil temperature were added: a
linear regression (Eq. (2)), a linear regression including an interaction term for temperature and soil moisture (Eq. (3)). After that
the reduction of the residual sums of squares (at costs of additional
parameters) were tested using F-tests:
2
(1)
2
(2)
2
(3)
SR = a ∗ exp(−0.5 ∗ ((SM − x0 )/b) )
SR = a ∗ exp(−0.5 ∗ ((SM − x0 )/b) ) + c ∗ ST
SR = a ∗ exp(−0.5 ∗ ((SM − x0 )/b) ) + c ∗ ST + d ∗ ST ∗ SM
where SR is soil respiration (mol m−2 s−1 ), SM is soil moisture (%),
ST is soil temperature (◦ C) and a, b, c, d, and x0 are fitted parameters. To describe the relationships between soil respiration rate (SR)
and soil temperature (ST) at a diurnal scale, a single exponential
function (Eq. (4)) was used:
SR = a ∗ expb∗ST
(4)
Annual soil CO2 efflux was estimated by extrapolating each
weekly measurement to a 7-day period. Where there were missing
data due to rainfall incidence or failure of instrument, soil CO2 efflux
was estimated based on the Gaussian relation of soil moisture and
soil temperature with soil CO2 efflux for the different tree species
shown in Table 3. Since the linear relation between the volumetric
soil water content measured at the weather station and underneath
the individual tree species was close (r2 = 0.94 for C. macrostachys;
r2 = 0.93 for P. falcatus; r2 = 0.93 for P. africana), the former was used
to simulate the latter in cases of gaps.
All graphing and statistical analysis was performed using R 211.0 or SigmaPlot version 11 (Systat Software Inc., San Jose, CA,
USA).
3. Results
3.1. Seasonal variability of soil CO2 efflux
Soil CO2 efflux rates varied between 2 and 7 mol m−2 s−1
(Fig. 2). In general, the respiration rates followed changes in the
precipitation and the resulting changes in the volumetric soil water
Table 2
Analysis of variance for the net effect of explanatory variable tree species, season,
and covariates (soil moisture and soil temperature), and their interaction.
Effect
df
SS
(% SS)a
F
p-Value
Tree
Season
SM
ST
Tree:season
Tree*SM
Tree*ST
Season:SM
Season:ST
SM*ST
Residual
2
1
1
1
1
2
2
1
1
1
89
12.970
59.767
33.494
6.531
1.844
5.488
0.332
0.332
12.395
2.017
14.985
8.35
38.49
21.57
4.21
1.18
3.53
0.21
7.98
3.49
1.29
38.516
354.982
198.937
38.792
5.476
16.298
0.984
73.622
32.387
11.981
<0.001
<0.001
<0.001
<0.001
0.005
<0.001
0.3776
<0.001
<0.001
<0.001
a
% SS indicate increases in multiple r2 (explained variance) due to the addition
of this term. df, degree of freedom; SS, sum of square; SM, soil moisture; ST, soil
temperature.
content, which varied considerably between 8% and 39%, being
on average 16% and 28% for dry and wet months, respectively.
So during rainy periods from July to November 2008, from July
to November 2009 and from May to July 2010 (end of observation period) soil CO2 efflux rates mostly exceeded 4 mol m−2 s−1 .
Drying out of the soil with the onset of dry periods in December
2008 and December 2009 resulted in a continuous decline in the
soil respiration rates. Remarkable is the pronounced response of
the soil CO2 efflux on individual rain events during or at the end
of a dry period, e.g. in January or April 2009. Table 2 displays the
net effect of tree species, season, the covariates soil moisture and
soil temperature, and their interaction on the dependent variable
soil CO2 efflux. The ANOVA shows that seasonal changes exerted
the strongest influence on soil CO2 efflux in the Munessa forest,
followed by the covariate soil moisture. Seasonality accounted for
38% of variability, with F (1, 89) = 354.98, p < 0.001, indicating significant difference in the response variable soil CO2 efflux in wet
and dry periods. Soil moisture explained 22% of the overall variances with F (1, 89) = 198.93, p < 0.001. There was also a significant
interaction effect of soil moisture and seasonal variability on soil
CO2 efflux with F (1, 89) = 73.62, p < 0.001.
Using the data set available from 30 May 2009, we assessed the
dependence of soil CO2 efflux rate on soil moisture individually
under the three different tree species. Under all three tree species
soil respiration rates steadily increased with increasing volumetric soil water content threshold level (Fig. 3). After exceeding this
threshold, soil respiration decreased with increasing volumetric
soil water content. The Gaussian Equation (1) shows that the effect
of soil moisture had a significant (p < 0.05) relationship with soil
CO2 efflux that explained about 50% for C. macrostachys, 56% for P.
falcatus, and 58% for P. africana (Table 3).
In contrast to soil moisture, soil temperature at 0.1 m soil depth
did not vary much, ranging from about 15 ◦ C to 20 ◦ C. The higher
soil temperatures were recorded during the dry periods (Fig. 2). The
influence of soil temperature on the overall variation of soil CO2
efflux was smaller as compared with that of soil moisture and tree
species. Considering soil temperature as covariate and incorporated
in the general linear model, it explains only 4% of the variability of
soil CO2 efflux (Table 2). This is also mirrored in Fig. 4, showing a
high degree of scatter between soil temperature and soil respiration.
We also used the same data set to show the joint effects of soil
moisture and soil temperature on soil CO2 efflux rate. The inclusion of the soil temperature in the data analysis (Eq. (2)) increased
the r2 values only weakly and slightly reduced the RMSE (Table 3).
The intercepts of the models with the linear trend of soil temperature terms were slightly lower than those with just soil moisture
(Table 3). However, the pLinear test, which compares the addi-
Author's personal copy
1094
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
24
a
22
40
35
20
30
25
18
20
16
15
14
10
12
5
Precipitation
b
9
7
200
150
5
100
3
50
Precipitation [mm]
204
177
149
92
121
64
37
9
324
352
298
241
268
213
185
157
129
73
101
45
17
327
355
299
271
215
1
243
Soil respiration [µmol m-2 s-1]
Soil moisture [%]
Soil temperature [°C]
45
C. macrostachys
P. falcatus
P. africana
Soil moisture
0
|-------------2008------------|-------------------------------2009---------------------------|-------------------2010--------------|
DOY
Fig. 2. Seasonal courses of daily mean volumetric soil water content and soil temperature under the canopy (a), weekly canopy precipitation and soil CO2 efflux rate measured
under three tree species (b). Each data point for soil respiration and soil temperature is a mean of fifteen measurements and for precipitation is a mean of five measurements.
Error bars indicate standard deviation. Data gaps are due to rain events or instrument failure. Periods with light grey background indicate dry periods as calculated by the
approaches of Gibbs and Maher (1967).
tional effects of the linear regression (soil temperature) relative
to the previous Gaussian model (soil moisture term in Eq. (1)), was
not significant (Table 3). Inclusion of the joint effects of the linear trend depended on soil temperature and the interaction of soil
P. falcatus
P. africana
10
-2
-1
Soil respiration [µmol m s ]
C. macrostachys
moisture and soil temperature (Eq. (3)) brought small differences
in r2 and the RMSE values, indicating that the interaction term was
more influential than soil temperature alone for C. macrostachys
(p < 0.001) and P. africana (p = 0.002).
8
6
4
2
0
1
5
9 13 17 21 25 29 33 37 41 1
5
9 13 17 21 25 29 33 37 41 1
5
9 13 17 21 25 29 33 37 41
Soil moisture [%]
Fig. 3. Relationship between soil CO2 efflux rate (SR) and volumetric soil water content (SM) at 0.06 m soil depth. The parameters of the Gaussian function (Eq. (1)) are shown
in Table 3.
Author's personal copy
1095
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
Table 3
Comparative values of regression coefficients, r2 and RMSE using the Gaussian and a linear regression, a linear regression including an interaction term for soil temperature
and soil moisture.
Parameter
a
b
c
d
xo
pC
pLinear
pLT T:M
pInteraction
r2
RMSE
C. macrostachys
P. falcatus
Eq. (1)
Eq. (2)
5.29
18.14
–
–
27.27
<0.0001
–
–
–
0.4975
0.931
4.84
11.71
0.02
–
27.45
<0.0001
0.3245
–
–
0.4975
0.900
Eq. (3)
2.34
9.88
0.03
0.006
18.32
<0.0001
–
<0.0001
<0.0001
0.5317
0.900
P. africana
Eq. (1)
Eq. (2)
Eq. (3)
Eq. (1)
Eq. (2)
6.42
17.27
–
–
30.60
<0.0001
–
–
–
0.556
1.137
7.32
18.81
−0.05
–
30.65
<0.0001
0.1683
–
–
0.558
1.136
5.82
17.90
−0.137
0.006
24.33
<0.0001
–
0.056
0.050
0.562
1.132
5.67
18.26
–
–
30.28
<0.0001
–
–
–
0.574
0.866
4.91
16.48
0.05
–
30.44
<0.0001
0.0811
–
–
0.577
0.864
Eq. (3)
3.23
14.31
0.012
0.0042
24.29
<0.0001
0.002
0.002
0.585
0.856
Eq. (1): SR = a*exp(−0.5*((SM − x0 )/b)2 ), Eq. (2): SR = a*exp(−0.5*((SM − x0 )/b)2 ) + c*ST and Eq. (3): SR = a*exp(−0.5*((SM − x0 )/b)2 ) + c*ST + d*ST*SM, where a, b, c, d and x0 are
the fitted parameters; r2 is the correlation coefficient, SM is volumetric soil moisture content in %, SR is soil respiration in mol m−2 s−1 and ST is soil temperature in ◦ C, pC (p
value of complete model), pLinear (the linear regression of ST relative to the previous model including the Gaussian model for SM). pLT T:M (p-value for adding a linear trend
and a linear interaction for ST and SM to the Gaussian model fitted with SM). pInteraction (p-value for adding just a linear interaction term ST:SM to the Gaussian model with
linear regression for SM).
of soil CO2 efflux rates was observed for all the plots in the dry
period.
3.2. Diurnal variability of soil CO2 efflux
The volumetric soil water contents in the days representing
wet, transition and dry conditions were 26%, 19% and 11%, respectively. The diurnal pattern of the soil temperature was similar for
the different seasons, with minima in early morning and maxima
in afternoon (not shown). The lowest mean daily soil temperature
was recorded under all trees in December, and there were no significant differences in soil temperature for P. falcatus and P. africana
plots between dry and wet seasons (Fig. 5). Under C. macrostachys,
the soil temperatures were higher as compared to other plots due
to the less dense canopy and showed maxima during the dry and
sunny March term. The season was exerting a strong influence on
the soil CO2 efflux rates. Largest values were obtained in the July
measurement, representing the wet period and optimal soil moisture, while in March the smallest diurnal CO2 efflux rates were
obtained. The impact of the season on temperature dependency
of the diurnal CO2 efflux is also reflected by the Q10 values calculated from the exponential function in Fig. 5 (i.e., exp10b ). Q10 values
of 3.2 for C. macrostachys, 4.5 for P. falcatus, and 2.7 for P. africana
during the wet season indicated a higher temperature sensitivity
of soil respiration than respective Q10 values of 2.0. 1.6, and 2.0
in the transition season. In contrast to wet and transition seasons
where the pattern of the soil CO2 efflux rates followed the diurnal
soil temperature fluctuations, no diurnal temperature dependency
It has been shown that the tree species was the third significant
factor affecting soil CO2 efflux variability F (2, 89) = 38.51, p < 0.001
(Table 2). Tree species contributed with 8% to the overall variance.
Further, the significant interaction effects of tree species and soil
moisture (p < 0.001) indicates that the change in soil CO2 efflux rate
as a function of soil moisture was not uniform under the different tree species. This is also obvious from the Gaussian functions
(Table 3). The threshold level when higher soil moisture leads to a
decline of the soil CO2 efflux decreased in the order P. falcatus (volumetric soil water content 31%), P. africana (30%), C. macrostachys
(27%). Likewise, absolute largest soil respiration rates at optimum
soil moisture were observed under P. falcatus (Fig. 3). In contrast,
it appears that the decrease in soil CO2 efflux with decreasing soil
moisture was least for C. macrostachys followed by P. africana, while
P. falcatus exhibited the steepest decline in soil respiration with
drying out of the soil. This result is mirrored by the three-way
ANOVA showing that soil respiration did vary significantly (p < 0.05)
between the tree species during wet periods (Fig. 6). In both years
under study, the mean soil respiration rate during the wet period
P. falcatus
P. africana
-1
Soil respiration [µmol m s ]
C. macrostachys
3.3. Tree species variability in soil CO2 efflux
-2
8
6
4
2
0
13
15
17
19
21
13
15
17
19
21
13
15
17
Soil temperature [°C]
Fig. 4. Relationship between soil CO2 efflux rate (SR) and soil temperature (ST) at 0.1 m soil depth.
19
21
Author's personal copy
1096
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
C. macrostachys
P. africana
P. falcatus
Soil respiration [µmol m-2 s-1]
9
; r = 0.50 SR = 0.58*exp
; r = 0.57 SR = 2.00*exp
July
SR = 0.69*exp
December SR = 1.66*exp
March
8
7
; r = 0.78
SR = 0.86*exp
; r = 0.27
; r = 0.76
SR = 1.31*exp
; r = 0.89
6
5
4
3
2
1
13
15
17
19
13
21
15
17
19
21
13
15
17
19
21
Soil temperature [°C]
Fig. 5. Diurnal dependence of soil CO2 efflux rate (SR) on soil temperature (ST) at 0.1 m soil depth. Each data point is the mean of fifteen measurements made per sampling
hour. The equations represent July and December measurements, respectively.
was highest under P. falcatus. In contrast, there were no significant
differences (p > 0.05) in the soil CO2 efflux rate under the three tree
species during the dry season.
4. Discussion
4.1. Variability of soil respiration related to soil moisture
Soil respiration [µmol m-2 s-1]
Soil respiration under the canopy of all three tree species
showed pronounced seasonal variation. It is evident that these
seasonal changes are generally driven by the precipitation pattern and its response variable volumetric soil water content. The
strong positive relationship between soil moisture and soil respiration is in agreement with previous studies in tropical forest
ecosystems where a majority of biological processes coincides with
moisture dynamics (e.g., Epron et al., 2004, 2006; Hashimoto et al.,
2004; Nsabimana et al., 2009; Salimon et al., 2004; Werner et al.,
2007). In general, the highest soil respiration rate during the wet
periods may have resulted from the high physiological activity
of both plants and microorganisms (Lee et al., 2002) in not limiting soil moisture conditions. Besides this general effect of soil
moisture on soil respiration rates, rewetting of the soil after dry
periods causes a short-lived but strong increase in soil CO2 efflux.
This observation is known as “Birch effect” and is the result of
burst mineralization of labile soil organic matter that has been
accumulated during the dry period and is available to microor-
First year wet periods
First year dry periods
Second year wet periods
Second year dry periods
8
5
c
a
b
a
b
4
d
c
6
b
a
b
b
b
2
0
C. macrostachys
P. falcatus
P. africana
Fig. 6. Comparison of soil CO2 efflux between wet and dry periods for both years of
observation (July 11, 2008 to July 10, 2009 and July 11, 2009 to July 17, 2010). Bar
graphs following a different letter are significantly different (Tukey’s HSD, p < 0.05).
Error bars indicate standard deviation.
ganisms after re-wetting of the soil (Birch, 1964; Jarvis et al.,
2007).
At our study, volumetric soil water content was positively
related to soil CO2 efflux rates only when it was below around 30%,
at higher values there appeared a negative relation. Since volumetric soil water contents of up to 42% were measured, soil respiration
rates were below the maximum values under these wet conditions. Excess soil moisture may negatively affect CO2 efflux rates
by reducing soil aeration and thus CO2 diffusivity (Janssens and
Pilegaard, 2003). Oxygen deficit as result of too high soil moisture
decreases activity of plant roots (Adachi et al., 2006) and the heterotrophic decomposition of soil organic matter (Linn and Doran,
1984). This may be particularly the case in the clayey soils under
study. An alternative explanation is based on the photosynthetic
activity of the trees. The periods with the most amount of precipitation are associated with conditions of low photosynthetic active
radiation in the Munessa forest with c. 1–4 mol m−2 leaf area d−1
(Seyoum et al., in preparation). This translates to small carbon
assimilation rates and, consequently, to small rates of autotrophic
soil respiration.
4.2. Variability of soil respiration related to soil temperature
We examined possible seasonal effects of soil temperature on
soil respiration and found little relation for the investigated forest ecosystem. The apparent weak contribution of soil temperature
unlike to soil moisture is partly due to the relatively small temperature fluctuations in this ecosystem being not sufficient enough to
drive seasonal variations in soil respiration. Further, soil temperature tended to be higher during the dry periods when soil CO2 efflux
was restrained by low soil moisture. Similar observations have been
found in other tropical forest ecosystem where soil temperature
is relatively constant within the year and poorly correlated with
soil respiration (e.g., Davidson et al., 2000; Hashimoto et al., 2004;
Kiese and Butterbach-Bahl, 2002; Nsabimana et al., 2009). In other
biomes such as boreal and temperate forests, there is a wide range
of seasonal temperatures that leads to seasonal variation in soil respiration rate (Davidson et al., 1998; Malhi et al., 1999; Shibistova
et al., 2002).
Over diurnal pattern, when soil moisture is assumed to be
almost constant, soil temperature is considered to be a major control of soil CO2 efflux (e.g., Chang et al., 2008). Also we found a
positive relation between soil temperature and soil respiration, as
long as soil moisture is not limiting as is the case at the July and
December measurements. The Q10 values suggest that the more
favorable is the soil moisture the more prominent is the tem-
Author's personal copy
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
perature dependency of the diurnal soil CO2 efflux. This may be
attributed to increasing soil organic matter mineralization rates
with increasing temperature. But according to Tang et al. (2005),
largest soil respiration rates in the afternoon rather suggest that
biotic processes, coupled to photosynthesis, carbon allocation to
roots and autotrophic may control diurnal CO2 efflux.
4.3. Effects of trees on soil CO2 efflux
Our analysis demonstrated that different tree species affected
soil respiration. At optimum soil moisture, the soil CO2 efflux under
P. falcatus exceeded that under the other two tree species (Fig. 3).
Several biotic factors such as assimilation rate, root density, phenological differences, soil microbial activity and diversity (Epron
et al., 2006; Raich and Tufekcioglu, 2000; Vanhala, 2002) might
explain this observation. During the wet season with dominantly
clouded sky, the shade tolerant P. falcatus is having a physiological
advantage as compared with the light demanding C. macrostachys
in terms of carbon assimilation (Seyoum et al., in preparation). So
it seems reasonable that the higher soil respiration rate during the
wet period under the canopy of P. falcatus than under the other two
tree species is associated with the cumulative metabolic activities
of the plant.
The situation changes when the dry season is progressing. With
decreasing soil moisture, soil respiration decreased under all three
tree species, however, the change in magnitude of soil CO2 efflux
rate under P. falcatus was larger than under C. macrostachys and
P. africana. The least soil moisture sensitivity was observed for C.
macrostachys. Probably, this reflects the different sensitivity of the
three tree species on soil moisture. Seyoum et al. (in preparation)
analyzed particularly larger values of carbon assimilation and transpiration for C. macrostachys than for the other two tree species
during the dry season. This pronounced photosynthetic activity of
C. macrostachys during the dry period probably results in a relative
large root respiration, thus causing a less pronounced decline in
CO2 efflux during conditions of low soil moisture than for the other
two tree species.
4.4. Annual soil CO2 efflux
Cumulative annual soil CO2 efflux was highest under P. falcatus
with 144 mol m−2 in the first year and 162 mol m−2 in the second year of observation. Respective values for C. macrostachys were
131 mol m−2 and 135 mol m−2 , and for P. africana 140 mol m−2 and
156 mol m−2 . With that the cumulative annual soil CO2 efflux falls
within the range of other published estimates of secondary tropical forests in eastern Amazon (150 mol CO2 m−2 year−1 ; Davidson
et al., 2000), tropical monsoon forests in Thailand (213 mol
CO2 m−2 year−1 ; Hashimoto et al., 2004), monospecifc forest plantation in Rwanda (112 mol CO2 m−2 year−1 , Nsabimana et al.,
2009), and moist tropical lowland forest in Panama (128 mol
CO2 m−2 year−1 , Sayer et al., 2007). In most studies soil collars
were installed randomly over the whole experimental plots. In
the present study collars were installed randomly but underneath
the canopy of our experimental trees. Wiseman and Seiler (2004)
showed that measurement position had significant effect on soil
respiration, and soil CO2 efflux rates were consistently near the
trees. This suggested that the estimated annual soil respiration
probably reflects a comparatively higher CO2 efflux rate than at
a completely randomized design at the forest ecosystem level.
As shown in Table 2, the season is having the strongest influence
on the soil respiration. The mean soil CO2 efflux rate was higher
during the wet period than during the dry period, independently
of the study tree and the year of observation (Fig. 6). When the
two study years are compared, there were no differences in the soil
CO2 efflux rates neither for the wet period nor for the dry period
1097
(except the second year wet period observation under P. africana).
However, during the first year of observation six months were classified as dry periods, whereas at the second year only three months
fell into this category because of a more homogenous distribution of
the precipitation. Hence, the higher soil CO2 efflux rates during the
second year of observation could be related to fewer periods where
soil respiration was restrained due to low soil moisture. This shows
that the precipitation pattern is having a strong impact on the soil
cumulative soil respiration in the Afromontane forest.
5. Conclusions
The soil CO2 fluxes from soil to atmosphere in the Munessa forest is primarily controlled by soil moisture, and with that by the
precipitation pattern. Therefore, the length of dry and wet seasons is of utmost importance for the soil CO2 efflux and the whole
carbon balance of this ecosystem. In Ethiopia, predicted future
changes in precipitation pattern are likely to have considerable
direct effects on soil CO2 efflux over most of the year. However,
this study also shows that biological variability is an important
factor, because different functional types of trees are responding
differently on precipitation pattern with respect to soil CO2 efflux.
Since anthropogenic impact to the forest structure, e.g. by changes
in the intensity of grazing-induced disturbance, favors the pioneer
C. macrostachys at the cost of the late successional tree species, this
adds another important driving factor in the seasonal and annual
variability of soil respiration at local scales. Interestingly the late
successional P. falcatus shows a larger variability is soil CO2 efflux
rates than the pioneer C. macrostachys that colonizes disturbed
niches.
Acknowledgments
We would like to thank Deutsche Forschungsgesellschaft (DFG)
for financial support of the study within the project package PAK
188. We thank Deksiso Bulcha, Getu Tadesse, Temesgen Yohannes,
Abule Loya, and Awol Assefa for their assistance and support in
collecting data in the field. We also thank Roger-Michael Klatt,
Ulrike Pieper, Pieter Wiese and Holger Ciglasch for their laboratory assistance in soil analysis. Likewise we are grateful to Frank
Schaarschmidt and Hany El Kateb for their advice in statistical analysis.
References
Adachi, M., Bekku, Y.S., Rashidah, W., Okuda, T., Koizumi, H., 2006. Differences in soil
respiration between different tropical ecosystems. Appl. Soil Ecol. 34, 258–265.
Bahn, M., Reichstein, M., Davidson, E.A., Grunzweig, J., Jung, M., Carbone, M.S., Epron,
D., Misson, L., Nouvellon, Y., Rouspard, O., Savage, K., Trumbore, S.E., Gimeno,
C., Yuste, J.C., Tang, J., Vargas, R., Janssens, I.A., 2010. Soil respiration at mean
annual temperature predicts annual total across vegetation types and biomes.
Biogeoscience 7, 2147–2157.
Bekele-Tesemma, A., Birnie, A., Tengnaes, B., 1993. Useful Trees and Shrubs for
Ethiopia, Identification, Propagation and Management for Agricultural and Pastoral Communities. Regional Soil Conservation Unit/SIDA, RSCU, Nairobi.
Birch, H.F., 1964. Mineralisation of plant nitrogen following alternate wet and dry
conditions. Plant Soil 20, 43–49.
Bond-Lamberty, B., Thomson, A., 2010. Temperature-associated increases in the
global soil respiration record. Nature 464, 579–582.
Bray, R.H., Kurtz, L.T., 1945. Determination of total organic and available forms of
phosphorus in soils. Soil Sci. 59, 39–45.
Bréchet, L., Ponton, S., Roy, J., Freycon, V., Coûteaux, M., Bonal, D., Epron, D., 2009. Do
tree species characteristics influence soil respiration in tropical forests? A test
based on 16 tree species planted in monospecific plots. Plant Soil 319, 235–246.
Chang, S.C., Tseng, K.F., Wang, C.P., Wu, J.T., 2008. Soil respiration in subtropical
montane forest in Taiwan. Agric. For. Meteorol. 148, 788–798.
Ciais, P., Piao, S.-L., Cadule, P., Friedlingstein, P., Chédin, A., 2009. Variability
and recent trends in the African terrestrial carbon balance. Biogeoscience 6,
1935–1948.
Davidson, E.A., Belk, E., Boone, R.D., 1998. Soil water content and temperature as
independent or confounded factors controlling soil respiration in a temperate
mixed hardwood forest. Global Change Biol. 4, 217–227.
Author's personal copy
1098
Y. Yohannes et al. / Forest Ecology and Management 261 (2011) 1090–1098
Davidson, E.A., Verchot, L.V., Cattánio, J.H., Ackerman, I., Carvalho, J.E.M., 2000.
Effects of soil water content on soil respiration in forests and cattle pastures
of eastern Amazonia. Biogeochemistry 48, 53–69.
Epron, D., Nouvellon, Y., Roupsard, O., Mouvondy, W., Mabiala, A., Saint-Andre, L.,
Joffre, R., Jourdan, C., Bonnefond, J., Berbigier, P., Hamel, O., 2004. Spatial and
temporal variations of soil respiration in Eucalyptus plantation in Congo. For.
Ecol. Manage. 202, 149–160.
Epron, D., Bosc, A., Bonal, D., Freycon, V., 2006. Spatial variation of soil respiration
across a topographic gradient in a tropical rain forest in French Guiana. J. Trop.
Ecol. 22, 565–574.
FAO, ISRIC, ISSS, 1998. World Reference Base for Soil Resources, vol. 84. Food and
Agriculture Organization of the United Nations, Rome, Italy.
Fetene, M., Beck, E., 2004. Water relations of indigenous versus exotic tree species,
growing at the same site in a tropical montane forest southern Ethiopia. Trees
18, 428–435.
Fritzsche, F., Abate, A., Fetene, M., Beck, E., Stephan, W., Guggenberger, G., 2006.
Soil–plant hydrology of indigenous and exotic trees in an Ethiopian montane
forest. Tree Physiol. 26, 1043–1054.
Fritzsche, F., Zech, W., Guggenberger, G., 2007. Soils of the Main Ethiopian Rift Valley
escarpment: a transect study. Catena 70, 209–219.
Gee, G.W., Bauder, J.W., 1986. Particle-size analysis. In: Klute, A. (Ed.), Methods of
Soil Analysis Part 1, second ed., Agronomy Series No. 9. American Society of
Agronomy, Madison, Wisconsin, pp. 383–411.
Gibbs, W.J., Maher, J.V., 1967. Rainfall Deciles as Drought Indicators. Bureau
of Metrology, Bulletin No. 48. Common Wealth of Australia, Melbourne, p.
37.
Gillman, G.P., Sumpter, E.A., 1986. Modification to the compulsive exchange method
for measuring exchange characteristics of soils. Aust. J. Soil Res. 24, 61–
66.
Griffits, J.F., 1972. Ethiopian highlands. In: Griffits, J.F. (Ed.), Climate of Africa. World
Survey of Climatology, vol. 10, pp. 369–387.
Hashimoto, S., Tanaka, N., Suzuki, M., Inoue, A., Takizawa, H., Kosaka, I., Tanaka, K.,
Tantasirin, C., Tangtham, N., 2004. Soil respiration and soil CO2 concentration in
a tropical forest, Thailand. J. For. Res. 9, 75–79.
Janssens, I.A., Pilegaard, K., 2003. Large seasonal changes in Q10 of soil respiration in
a beech forest. Global Change Biol. 9, 911–918.
Janssens, I.A., Lankreijer, H., Matteucci, G., Kowalski, A.S., Buchmann, N., Epron, D.,
Pilegaard, K., Kutsch, W., Longdoz, B., Gruenwald, T., Montagnani, L., Dore, S.,
Rebmann, C., Moors, E.J., Grelle, A., Rannik, U.E., Morgenstern, K., Oltsev, S.,
Clement, R., Gudmundsson, J., Minerbi, S., Berbiger, P., Ibrom, A., Moncrieff, P.J.,
Aubinet, M., Bernhoffer, C., Jensen, N.O., Vesala, T., Granier, A., Schulze, E.-D.,
Lindroth, A., Dolman, A.J., Jarvis, P.D., Cuelemans, R., Valentini, R., 2001. Productivity overshadows temperature in determining soil and ecosystem respiration
across European forests. Global Change Biol. 7, 269–278.
Jarvis, P., Rey, A., Petsikos, C., Wingate, L., Rayment, M., Pereira, J., Banza, J., David, J.,
Miglietta, F., Borghetti, M., Manca, G., Valentini, R., 2007. Drying and wetting of
Mediterranean soils stimulates decomposition and carbon dioxide mission: the
“Birch effect”. Tree Physiol. 27, 929–940.
Kiese, R., Butterbach-Bahl, K., 2002. N2 O and CO2 emissions from three different tropical forest sites in the wet tropics of Queensland, Australia. Soil Biol.
Biochem. 34, 975–987.
Kosugi, Y., Mitani, T., Itoh, M., Noguchi, S., Tani, M., Matsuo, N., Takanashi, S., Ohkubo,
S., Nik, A.R., 2007. Spatial and temporal variation in soil respiration in a Southeast
Asian tropical rainforest. Agric. For. Meteorol. 147, 35–47.
Lee, M., Nakane, K., Nakatsubo, T., Mo, W., Koizumi, H., 2002. Effects of rainfall events
on soil CO2 flux in a cool temperate deciduous broad-leaved forest. Ecol. Res. 17,
401–409.
Lemenih, M., Itanna, F., 2004. Soil carbon stocks and turnovers in various vegetation types and arable lands along an elevation gradient in southern Ethiopia.
Geoderma 123, 177–188.
Lewis, S.L., Lopez-Gonzalez, G., Sonke, B., Affum-Baffoe, K., Baker, T.R., Ojo, L.O.,
Phillips, O.L., Reitsma, J.M., White, L., Comiskey, J.A., Djuikouo, K.M-N., Ewango,
C.E.N., Feldpausch, T.R., Hamilton, A.C., Gloor, M., Hart, T., Hladik, A., Lloyd, J.,
Lovett, J.C., Makana, J.-R., Malhi, Y., Mbago, F.M., Ndangalasi, H.J., Peacock, J.,
Peh, K.S.H., Sheil, D., Sunderland, T., Swaine, M.D., Taplin, J., Taylor, D., Thomas,
S.C., Votere, R., Wöll, H., 2009. Increasing carbon storage in intact African tropical
forests. Nature 457, 1003–1006.
Linn, D.M., Doran, J.W., 1984. Effect of water filled pore space on CO2 and
NO production in tilled and non tilled soils. Soil Sci. Soc. Am. J. 48, 1267–
1272.
Lloyd, J., Taylor, J.A., 1994. On the temperature dependence of soil respiration. Funct.
Ecol. 8, 315–323.
Lüttge, U., Berg, A., Fetene, M., Nauke, P., Peter, D., Beck, E., 2003. Comparative characterization of photosynthetic performance and water relations of native trees
and exotic plantation trees in an Ethiopian forest. Trees 17, 40–50.
Malhi, Y., Baldocchi, D.D., Jarvis, P.G., 1999. The carbon balance of tropical, temperate
and boreal forests. Plant Cell Environ. 22, 715–740.
Nsabimana, D., Klemedtson, L., Kaplin, B.A., Wallin, G., 2009. Soil CO2 flux in six
monospecific forest plantations in Southern Rwanda. Soil Biol. Biochem. 41,
396–402.
Ohashi, M., Kumagai, T., Kume, T., Gyokusen, K., Saitoh, T.M., Suzuki, M., 2008. Characteristics of soil CO2 efflux variability in an aseasonal tropical rainforest in
Borneo Island. Biogeochemistry 90, 275–289.
Oscar, J.V-B., 2007. Relationships among litterfall, fine-root growth, and soil respiration for five tropical tree species. Can. J. For. Res. 37, 1954–1965.
Qi, Y., Xu, M., Wu, J., 2002. Temperature sensitivity of soil respiration and its effects
on ecosystem carbon budget: nonlinearity begets surprises. Ecol. Model. 153,
131–142.
R Development Core Team, 2009. R: A Language and Environment for Statistical
Computing. R Foundation for Statistical Computing, Vienna, Austria.
Raich, J.W., Tufekcioglu, A., 2000. Vegetation and soil respiration: correlations and
controls. Biogeochemistry 48, 71–90.
Raich, J.W., Schlesinger, W.H., 1992. The global carbon dioxide flux in soil respiration
and its relationship to vegetation and climate. Tellus 44B, 81–99.
Reichstein, M., Rey, A., Freibauer, A., Tenhunen, J., Valentini, R., Banza, J., Casals, P.,
Cheng, Y., Grünzweig, J.M., Irvine, J., Joffre, R., Law, B.E., Loustau, D., Miglietta,
F., Oechel, W., Ourcival, J.M., Peressotti, A., Ponti, F., Qi, Y., Rambalm, S., Rayment, M., Romanya, J., Rossi, F., Tedeschi, V., Tirone, G., Xu, M., Yakir, D., 2003.
Modeling temporal and large-scale spatial variability of soil respiration from
soil water availability, temperature and vegetation productivity indices. Global
Biogeochem. Cycles, doi:10.1029/2003GB002035.
Rustad, L.E., Huntington, T.G., Boone, R.D., 2000. Controls on soil respiration: implications for climate change. Biogeochemistry 48, 1–6.
Salimon, C.A., Davidson, E.A., Victoria, R.L., Melo, A.W.F., 2004. CO2 flux from soil
in pastures and forests in southwestern Amazonia. Global Change Biol. 10,
833–843.
Sayer, E.J., Powers, J.S., Tanner, E.V.J., 2007. Increased litterfall in tropical forest
boosts the transfer of soil CO2 to the atmosphere. PLoS ONE 2 (12), e1299,
doi:10.1371/journal.pone.0001299.
Schwendenmann, L., Veldkamp, E., Brenes, T., O’Brien, J.J., Mackensen, J., 2003. Spatial and temporal variation in soil CO2 efflux in an old-growth neotropical rain
forest, La Selva, Costa Rica. Biogeochemistry 64, 111–128.
Schlesinger, W.H., 1997. Biogeochemistry: An Analysis of Global Change. Academic
Press, San Diego, CA.
Shibistova, O., Lloyd, J., Zrazhevskaya, G., Arneth, A., Kolle, O., Knohl, A., Astrakhantseva, N., Shijneva, I., Schmerler, J., 2002. Annual ecosystem respiration budget
for a Pinus sylvestris stand in central Siberia. Tellus 54B, 568–589.
Stephens, B.B., Gurney, K.R., Tans, P.P., Sweeney, C., Peters, W., Bruhwiler, L., Ciais,
P., Ramonet, M., Bousquet, P., Nakazawa, T., Aoki, S., Machida, T., Inoue, G., Vinnichenko, N., Lloyd, J., Jordan, A., Heimann, M., Shibistova, O., Langenfelds, R.L.,
Steele, L.P., Francey, R.J., Denning, A.S., 2007. Weak northern and strong tropical land carbon uptake from vertical profiles of atmospheric CO2 . Nature 316,
1732–1735.
Tang, J., Baldocchi, D.D., Xu, L., 2005. Tree photosynthesis modulates soil respiration
on a diurnal time scale. Global Change Biol. 11, 1298–1304.
Tesfaye, G., Teketay, D., Fetene, M., Beck, E., 2010. Regeneration of seven indigenous
tree species in a dry Afromontane forest southern Ethiopia. Flora 205, 135–143.
Valentini, R., Matteucci, G., Dolman, A.J., Schulze, E.D., Rebmann, C., Moors, E.J.,
Granier, A., Gross, P., Jensen, N.O., Pilegaard, K., Lindroth, A., Grelle, A., Bernhofer, C., Grunwald, T., Aubinet, M., Ceulemans, R., Kowalski, A.S., Vesala, T.,
Rannik, U., Berbigier, P., Loustau, D., Guomundsson, J., Thorgeirsson, H., Ibrom,
A., Morgenstern, K., Clement, R., Moncrieff, J., Montagnani, L., Minerbi, S., Jarvis,
P.G., 2000. Respiration as the main determinant of carbon balance in European
forests. Nature 404, 861–865.
Vanhala, P., 2002. Seasonal variation in the soil respiration rates in coniferous forest
soils. Soil Biol. Biochem. 34, 1375–2137.
Werner, C., Kiese, R., Butterbach-Bahl, K., 2007. Soil-atmosphere exchange of N2 O,
CH4 , and CO2 and controlling environmental factors for tropical rain forest sites
in western Kenya. J. Geophys. Res. 112, doi:10.05029/02006jd007388.
Whitmore, T.C., 1989. Canopy gaps and the two major groups of forest trees. Ecology
70, 536–538.
Wiseman, P.E., Seiler, J.R., 2004. Soil CO2 efflux across for age classes of plantation
loblolly pine (Pinus taeda L.) on the Virginia Piedmont. For. Ecol. Manage. 192,
297–311.