394
DOI: 10.1002/jpln.201100167
J. Plant Nutr. Soil Sci. 2012, 175, 394–400
Soil carbon dioxide and nitrous oxide emissions during the growing
season from temperate maize-soybean intercrops
Lisa Dyer1, Maren Oelbermann2*, and Laura Echarte3
1
ClimateCHECK, 325 Dalhousie Street, Ottawa, Ontario K1N 7G2, Canada
Department of Environment and Resource Studies, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada
3 EEA INTA Balcarce, Ruta 226 Km. 73,5, C.C. 276 (7620) Balcarce, Argentina
2
Abstract
The Argentine Pampa is one of the major global regions for the production of maize (Zea
mays L.) and soybean (Glycine max L. [Merr.]), but intense management practices have led to
soil degradation and amplified greenhouse-gas (GHG) emissions. This paper presents preliminary data on the effect of maize-soybean intercrops compared with maize and soybean sole
crops on the short-term emission rates of CO2 and N2O and its relationship to soil moisture or
temperature over two field seasons. Soil organic carbon (SOC) concentrations were significantly
greater (p < 0.05) in the maize sole crop and intercrops, whereas soil bulk density was significantly lower in the intercrops. Soil CO2 emission rates were significantly greater in the maize
sole crop but did not differ significantly for N2O emissions. Over two field seasons, both trace
gases showed a general trend of greater emission rates in the maize sole crop followed by the
soybean sole crop and were lowest in the intercrops. Linear regression between soil GHG (CO2
and N2O) emission rates and soil temperature or volumetric soil moisture were not significant
except in the 1:2 intercrop where a significant relationship was observed between N2O
emissions and soil temperature in the first field season and between N2O and volumetric soil
moisture in the second field season. Our results demonstrated that intercropping in the Argentine Pampa may be a more sustainable agroecosystem land-management practice with respect
to GHG emissions.
Key words: Argentine Pampa / complex agroecosystems / global warming / legumes /
Pearson-product moment correlation / soil moisture and temperature
Accepted November 9, 2011
1 Introduction
Intensive agroecosystem management practices have
reduced levels of soil organic carbon (SOC) and augmented
the emission of greenhouse gases (GHG), which have contributed to global warming. Soil CO2 and N2O emissions may
be mitigated through improving crop, soil- and fertilizer-management practices (Adviento-Borbe et al., 2007), and by the
implementation of sustainable agricultural production systems (Verchot et al., 2008).
Intercropping, where more than one crop is grown on the
same land unit at the same time, may be a more sustainable
agricultural production system compared to conventional or
sole-crop systems. Although intercropping is not a new landmanagement concept, especially in tropical regions (Sharma
and Behera, 2009), it is currently gaining recognition in temperate areas (Oelbermann and Echarte, 2011). This is
because intercropping systems have a smaller environmental
impact compared to conventional sole-crop agroecosystems
(Li et al., 2001) and may also be more resilient to local climate change due to their greater structural complexity
compared to sole-crop agroecosystems. In the Argentine
Pampa, intensive production of maize (Zea mays L.) and soybeans (Glycine max L. [Merr.]) has led to soil degradation
(Posse et al., 2010); and as a consequence cereal-legume
intercrops were adopted to minimize losses of soil organic
matter (SOM). Establishing cereal-legume intercrops may
reduce losses of C and N because of an overall increase in
agroecosystem complexity and the complementary use of
resources in time and space (Prasad and Brook, 2005). The
inclusion of legumes with a ceral such as maize (Zea mays
L.) regulates the internal N cycle via N2 fixation (Schipanski,
2010) and reduces the amount of fertilizer required for crop
growth (Inal et al., 2007).
To date, most research on intercrop systems has focused on
grain yield and grain quality, resource use and competition,
nutrient-use efficiency and fertilizer requirements, and weed
and erosion control (Prasad and Brook, 2005; Waddington
et al., 2007). There is little understanding of the underlying
processes involved in the sequestration and stabilization of C
and N in temperate intercropping systems, and only a few
studies have investigated the effects of cereal-legume inter-
* Correspondence: Dr. M. Oelbermann;
e-mail: moelbermann@uwaterloo.ca
2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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J. Plant Nutr. Soil Sci. 2012, 175, 394–400
crops on GHG emissions (Pappa et al., 2011). A field experiment was carried out to quantify the short-term GHG emission rates from maize-soybean (Glycine max [L.] Merr.) intercrops and maize and soybean sole crops. The objectives of
this study were to quantify CO2 and N2O emission rates from
two differently configured maize-soybean intercrops compared to maize and soybean sole crops, and to correlate CO2
and N2O emission rates to soil moisture and temperature
over two field seasons. We hypothesized that due to a more
effective resource-use efficiency, CO2 and N2O emission
rates would be lower in the intercrop treatments. This paper
presents preliminary results on the initial changes in GHG
emissions as a result of intercropping 3 y after this agroecosystem was implemented. It is essential to present preliminary data because it is helpful to draw the first picture on the
effect of cereal-legume intercropping on GHG emissions.
Such information is crucial as it identifies other agroecosystem management practices effective in the mitigation of
GHGs (Rochette and Bertrand, 2008), and also contributes
additional information to the already existing global GHG
databases (Smith et al., 2007; Verchot et al., 2008).
2 Materials and methods
2.1 Site description
The research site was located at the National Institute for Agricultural Technology (INTA) in Balcarce (37°45′ S, 58°18′ W),
in the rolling Argentine Pampa. The average annual precipitation was 860 mm, a mean annual temperature of 13.9°C, and
the site was located 130 m asl (Andrade, 1995). The soil
was classified as a Luvic Phaozem (Mar del Plata series)
(Studdert and Echeverría, 2000), with a loam soil texture
composed of 41.1% sand, 35.8% silt, and 23.1% clay
(Domínguez et al., 2009). The soil pH was 6.2 to a 120 cm
depth (Oelbermann and Echarte, 2011).
The study was a randomized complete block design (RCBD)
with four treatments and three replications per treatment. The
treatments were maize (Zea mays L.) sole crop, soybean
(Glycine max L. [Merr.]) sole crop, 1:2 intercrop, and 2:3 intercrop. The 1:2 intercrop consisted of one row of maize and
two rows of soybeans, and the 2:3 intercrop consisted of two
rows of maize and three rows of soybeans. Since 2007, all
crops were sown on the same plots in consecutive years and
each treatment plot size was 8.8 m × 12 m. These intercrop
configurations and their plant densities were typical of those
currently adopted by landowners in this region. Plant density
(plants m–2) was 4.3 (1:2 intercrop), 5.3 (2:3 intercrop), 8.0
(maize only), and 29 (soybean only), with a 0.52 m distance
between crop rows. The site was under sunflower
(Helianthus annuus L.) production prior to the initiation of the
intercrop study.
Each treatment was mouldboard plowed, and weeds were
controlled by N-phosphonomethyl glycine. Crops in each
treatment were fertilized with P fertilizer (35 kg P ha–1 y–1),
and N fertilizer (granular urea) was applied at a rate of 150 kg
N ha–1 y–1 to the maize sole crop and maize only in the intercrops (by hand to the bottom of the maize stems). Fertilizer
2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Soil greenhouse-gas emissions 395
was applied in November, and soybeans were inoculated
with Bradyrhizobium japonicum. Maize was seeded in late
October and harvested in April; whereas soybeans were
seeded in late November and harvested in May. Only the
grain or pod was removed, and all other crop residues
remained on site. Average steady-state infiltration rates during the 2009/10 growing season were 11.76 mm min–1 (1:2
intercrop), 11.52 mm min–1 (2:3 intercrop), 9.97 mm min–1
(maize sole crop), and 9.41 mm min–1 (soybean sole crop).
2.2 Soil chemical and physical characteristics
Soil was sampled (0–10 cm) in February 2009 (Y1) and in
2010 (Y2) using a soil corer (5 cm inner diameter). Two random samples per treatment replicate were extracted and
composited into one sample. A 20 g subsample of the composited soil per treatment replicate was oven-dried at 105°C
for 48 h to determine bulk density. The remaining soil was
air-dried and sieved (2 mm). Soil carbonates were removed
by adding 150 mL HCl (0.5 M) to 2 g of sieved soil. The mixture was stirred 3 times over a 24 h period, and subsequently
washed by pipetting the HCl from the settled soil and adding
ultrapure water to the soil. This washing procedure was
repeated daily for 4 d after which the soil was dried in an
oven at 40°C for 2 d (Midwood and Button, 1998). The
acid-treated soil was ground in a ball mill (Retsch® ZM1,
Haan, Germany) and analyzed for C and N (Costech 4010,
Cernusco, Italy). Crop-residue biomass data for this site was
obtained from the site manager (data on file) and cropresidue C and N inputs (Tab. 1) were obtained from a previous evaluation of crop-residue C and N concentrations from
this site (Vachon and Oelbermann, 2011). Mean values of C
and N concentrations of crop-residue biomass in all treatments for maize were 42.2% (C) and 0.66% (N), and 44.8%
(C) and 1.4% (N) for soybeans (Vachon and Oelbermann,
2011).
A WET-2 sensor (Delta-T Devices, Cambridge, UK) was
used to quantify soil moisture (% volume) and temperature
(°C) to a 10 cm depth. Measurements of soil moisture and
temperature were taken at the same time, and in the same
location, as GHGs. Ambient temperature and precipitation
data (30 y mean) was obtained from a weather station, operated by the University of Mar del Plata, located adjacent to
our study site.
2.3 Greenhouse-gas emission rates
Greenhouse-gas chambers were constructed from PVC piping (25 cm height, 10 cm radius) (Parkin et al., 2004; Rochette
and Bertrand, 2008). Two sampling chambers per replicate in
each treatment (n = 6) were placed randomly in the soil
(10 cm depth) between crop rows, and between maize and
soybean rows in the intercrops. The chambers were closed
with an insulated (6 mm polyolefin foam [Borealis, Port Murray, USA]) and ventilated (10 cm long, 6 mm inner diameter
clear PVC tube [Fisher Scientific, Mississauga, Canada])
PVC cap with a sampling port.
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396
Dyer, Oelbermann, Echarte
J. Plant Nutr. Soil Sci. 2012, 175, 394–400
Table 1: Annual aboveground (shoots and leaves) crop-residue biomass, biomass C and N input (g m–2 y–1) from maize and soybeans in a
maize and soybean sole crop and in two differently configured intercropping systems in Balcarce, Argentina for the 2008/09 and 2009/10 field
seasons (n = 3). Biomass data on file at INTA. Mean values of C and N concentrations of crop-residue biomass in all treatments for maize were
42.2% (C) and 0.66% (N), and 44.8% (C) and 1.4% (N) for soybeans (Vachon and Oelbermann, 2011).
Soybean sole crop Maize sole crop
Biomass
2008/09
soybean
681
maize
2009/10
total
681
soybean
569
maize
Carbon
2008/09
total
596
soybean
305
maize
2009/10
total
305
soybean
355
maize
total
Nitrogen
2008/09
255
soybean
total
2009/10
10
soybean
total
8
Gases were measured biweekly (Parkin, pers. com., 2006)
from December to February in 2008/09 (Y1) and 2009/10
(Y2). This short-term measurement phase corresponded to
the maximum biomass accumulation of crops, where soil was
not yet completely covered, and to the beginning of crop
senescence at the latter part of the sampling regime. During
sampling, the chambers were capped for 30 min and samples
were extracted from the headspace with an air-tight 5 mL syringe at time 0 (t = 0), 15 (t = 15), and 30 min (t = 30), and
transferred into 3 mL evacuated vials (Labco Ltd., High
Wycombe, UK). Gas samples were analyzed on an Agilent
6890N (Santa Clara, California, USA) gas chromatograph,
and a gas standard (100 ppm CO2 and 10 ppm N2O) was
injected at a 10-sample interval.
CO2 and N2O emission rates were quantified according to
Hutchinson and Mosier (1981):
([C1 – C0] / [C2 – C1]),
(1)
where C0, C1, and C2 are the chamber headspace gas concentrations (ppmv) at t = 0, t = 15, and t = 30. If the outcome
of Eq. 1 was > 1, linear regression was used to calculate the
slope of the concentration vs. time. However, if Eq. 1 yielded
2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
170
177
2187
1306
1496
1476
1673
355
358
2593
1363
1597
2593
1718
1955
76
79
923
551
631
923
627
710
159
160
1094
575
674
1094
734
834
2
2
14
9
10
14
11
12
5
5
8
maize
2:3 intercrop
2187
10
maize
1:2 intercrop
14
9
11
14
14
16
a value of < 1, then linear regression is not appropriate.
Instead the build-up of gas concentration in the chamber
headspace is curvelinear with time, and as such the following
equation was used (Hutchinson and Mosier, 1981):
f0 = V (C1 – C0)2 / (A t1 [2C1 – C2 – C0]) ·
ln ([C1 – C0] / [C2 – C1]),
(2)
where f0 was the quantity gas produced (lL m–2 min–1); V is
the chamber headspace volume (L); A was the soil surface
area (m2); t1 was the time interval between gas-sampling
points (min). The value of the slope from the linear regression
analysis was substituted for f0 in the ideal gas law equation.
Data for atmospheric temperature and pressure used in the
ideal gas law equation were obtained from the INTA meteorological station, located adjacent to the study site. Resulting
values (lmol m–2 min–1) were converted to lg CO2 m–2 h–1
and lg N2O m–2 h–1.
2.4 Statistical analysis
All data were examined for homogeneity of variance and
normality and were found to have normal distributions.
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J. Plant Nutr. Soil Sci. 2012, 175, 394–400
Soil greenhouse-gas emissions 397
Differences between treatments for soil characteristics and
GHG emission rates were analyzed using the univariate
general linear model (ANOVA) in SPSS (SPSS Science Inc.,
1989). Significant differences were further analyzed using
Turkey’s multiple comparison test (Steel, 1997). A paired
t-test was used to compare differences in GHG emission
rates between sampling years (Y1 and Y2) within treatments.
For each treatment, linear regression analysis was used to
determine the relationship between CO2 or N2O emission
rates and soil temperature or volumetric soil moisture. For
all statistical analyses, the threshold probability level was
p < 0.05.
3 Results
3.1 Soil chemical and physical characteristics
The two field season means (Y1 and Y2) of soil physical and
chemical characteristics were significantly different between
treatments (Tab. 2). Soil bulk density was significantly lower
in the intercrops; and SOC concentration (g kg–1) was significantly greater in the maize sole crop and intercrops (Tab. 2).
Soil temperature and moisture varied within each field season
and between the two field seasons. Both soil moisture and
temperature followed a similar pattern to that of the ambient
temperature and precipitation (Fig. 1). Soil moisture was highest in December of Y1 and in February of Y2 (Fig. 1). This
Figure 1: Mean air and soil
(0–10 cm) temperature (X [°C]), and
ambient precipitation (mm) and soil
moisture (䊉 [%vol]) of soybean and
maize sole crop and intercrops (n = 6)
over two field seasons. A) Y1:
December 2008 to February 2009;
B) Y2: December 2009 to February
2010 in the Argentine Pampa.
Table 2: Soil chemical and physical characteristics (mean of two field seasons) to a 10 cm depth in soybean and maize sole crops, and 1:2 and
2:3 intercrops in the Argentine Pampas, Balcarce, Argentina. Standard errors are given in parentheses (n = 3). Values followed by the same
lowercase letter for each soil characteristic and comparing differences between treatments are not statistically different (p < 0.05).
Bulk density / g cm–3
SOC /
g kg–1
Soybean sole crop
Maize sole crop
1:2 intercrop
2:3 intercrop
1.20 (0.1)a
1.20 (0.1)a
1.17 (0.1)b
1.17 (0.1)b
(0.1)a
(0.1)b
(0.2)b
24.41 (0.3)b
23.76
24.58
24.46
TN / g kg–1
2.26 (0.1)a
2.28 (0.1)a
2.27 (0.1)a
2.29 (0.1)a
C : N ratio
(0.2)a
(0.1)a
(0.3)a
10.67 (0.2)a
10.68
SOC stock / g m–2
Soil TN stock / g
m–2
10.79
10.81
2898 (29.8)a
2999 (22.0)b
2861 (17.1)b
2856 (9.0)b
(2.7)a
(3.5)a
(6.8)b
268 (4.5)b
275
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266
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J. Plant Nutr. Soil Sci. 2012, 175, 394–400
Dyer, Oelbermann, Echarte
Soybean
Soil CO2 Emission / μg C m-2 h-1
500
Maize
1:2
2:3
A
450
400
350
300
250
200
150
100
50
0
13-Dec-08
27-Dec-08
10-Jan-09
24-Jan-09
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
7-Feb-09
30
500
Soybean
Maize
1:2
2:3
B
450
Soil CO2 Emission / μg C m-2 h-1
Soil N2O Emission / μg N m-2 h-1
550
28
26
400
24
350
22
300
20
250
18
200
16
150
14
100
12
50
10
0
13-Dec-09
27-Dec-09
10-Jan-10
24-Jan-10
study included a dry (Y1) and a wet (Y2) growing season
showing variable measurements in ambient air temperature
and precipitation, which also reflected a similar variation in
soil temperature and soil moisture. Soil moisture was lower in
Y1 due to a lower amount of precipitation, which was 171 mm
below the 30 y average from December to February.
3.2 Carbon dioxide and nitrous oxide emission
rates
In Y2, the mean CO2 emission rates over the entire sampling
period were significantly lower in the intercrcrops ([299 ± 7] lg C
m–2 h–1 [1:2 intercrop], [300 ± 13] lg C m–2 h–1 [2:3 intercrop])
compared to the sole crops ([384 ± 7] lg C m–2 h–1 [soybean
sole crop], [380 ± 11] lg C m–2 h–1 [maize sole crop]) (Fig. 2).
When comparing differences in CO2 emission rates between
treatments (mean of both field seasons over the entire
sampling period), a lower emission was observed in both
intercrop systems. For example, CO2 emission rates were
(354 ± 14) and (357 ± 13) lg C m–2 h–1 in the soybean and
maize sole crops respectively, whereas that in the intercrops was (284 ± 10) lg C m–2 h–1 (1:2 intercrop) and
2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
7-Feb-10
8
21-Feb-10
Soil N2O Emission / μg N m-2 h-1
398
Figure 2: Soil CO2 (lg C m–2 h–1) and
N2O (lg N m–2 h–1) (lower set of lines)
emission rates from soybean and maize
sole crop and intercrops (n = 6) over two
field seasons. A) Y1: December 2008 to
February 2009; B) Y2: December 2009
to February 2010 in the Argentine
Pampa. Vertical bars represent standard
errors.
(290 ± 17) lg C m–2 h–1 (2:3 intercrop). Intraannual variation
in CO2 emission rates (December to February) were observed in Y1 and Y2 for all treatments (Fig. 2) but were not
significantly correlated to soil temperature (°C) and moisture
(% volume).
When comparing differences in N2O emission rates between
treatments (mean of both field seasons over the entire sampling peirod) lower emissions were observed in the intercrop
systems (Fig. 2). For example, N2O emission rates were
(13.5 ± 0.8) and (14.0 ± 0.7) lg N m–2 h–1 in the soybean and
maize sole crops, respectively, whereas that in the intercrops
was (11.5 ± 0.8) and (12.0 ± 0.8) lg N m–2 h–1 in the 1:2 and
2:3 intercrops, respectively. N2O emissions varied over the
growing season in Y1 and Y2 and were only significantly correlated to soil temperature (Y1; r 2 = 0.866) and soil moisture
(Y2; r 2 = 0.700) in the 1:2 intercrop.
4 Discussion
Soil physical and chemical characteristics were similar to
those reported by others from the same region of the Argenwww.plant-soil.com
J. Plant Nutr. Soil Sci. 2012, 175, 394–400
tine Pampa (Studdert and Echeverría, 2000; Aparicio and
Costa, 2007; Domínguez et al., 2009). Although measureable
differences in the SOC and N (g m–2) stocks were not observed between treatments at this time, and it is expected
that within the short term (≥ 5 y), measurable differences in
the SOC and N stocks will occur between treatments. For
example, Alvarez et al. (1998) reported a measurable difference in the SOC stock after 5 y, whereas Studdert and Echeverría (2000) noted changes after 11 y in this region of the
Argentine Pampa.
Soil CO2 and N2O emission rates for all treatments fell within
the range of values reported in other agroecosystems in the
temperate zone (Omonode et al., 2007; Ellert and Janzen,
2008; Pappa et al., 2011). Values of CO2 and N2O emission
rates from the sole crops, observed in our study, were similar
to those reported by others (Rastogi et al., 2002; Baggs et al.,
2006; Posse et al., 2010). Limited data is available on GHG
emission rates from temperate cereal-legume intercropping
systems, and no data exists for maize-soybean intercropping
systems. In Scotland, Pappa et al. (2011) observed that N2O
production rates from cereal-legume intercrops were either
greater or lower compared to sole crops; noting that the type
of legume cultivar and previous crop-rotation regimes influenced emissions. When comparing CO2 emission rates from
agroecosystems with an annual maize-soybean rotation,
emissions were similar to those of our intercrop systems.
Omonode et al. (2007) found a 16% lower CO2 emission in a
maize-soybean rotation in Indiana compared to a maize sole
crop, and attributed such differences to crop-residue quality.
Greater root biomass and rhizodeposition in the maize sole
crop in our study, compared to the soybean sole crop, may
have also led to a higher CO2 emission rate (Sehy et al.,
2008).
Soil greenhouse-gas emissions 399
ment and cropping systems may have a greater impact on
N2O emissions than the source of mineral N. Additionally,
many of the key factors that increase N2O emissions (soil
temperature, moisture, pH, osmotic stress, and C and N
availability) may be controlled by management practices
such as site-specific N-fertilizer application. In our study, sitespecific application of N fertilizers, where only maize and
maize in the intercrops received N fertilizer, may be a better
management option than sole cropping to help curb N2O
emissions.
5 Conclusions
Our study is unique because it is the first of its kind to evaluate soil CO2 and N2O emissions from a temperate maize-soybean intercrop system, thus addressing a current gap in the
literature. Our results demonstrated that intercropping may
be a more sustainable agroecosystem land-management
practice with respect to GHG emission.
Acknowledgments
Funding for this study was provided by the Natural Science
and Engineering Research Council of Canada (NSERC) and
the Canadian Foundation for Innovation (CFI). This work was
supported by the University of Waterloo, the Instituto Nacional de Tecnología Agropecuaria (INTA), and the Universidad
Nacional de Mar del Plata, the National Research Council of
Argentina (CONICET), and a scholarship to L. Dyer from the
Inter-American Institute for Co-operation on Agriculture
(IICA-Canada).
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