Introduction
The evidence for climate change is irrefutable, and the necessity of
mitigating climate change is now accepted. Yet, there are still large
uncertainties on the effectiveness of the measures that could be taken to
reduce greenhouse gas (GHG) emissions by land-use management (Smith et al., 2008; Ciais et
al., 2011).
There are several reasons for these uncertainties. While inventories can be
made of the different carbon pools (Bellamy et al., 2005), carbon pool
changes are small and difficult to detect; they require sampling programs
with periodic revisits over many years. Thus, the magnitude and variability
of CO2 fluxes, both sinks and sources, between the soil and the
atmosphere are difficult to quantify and they may not have been accurately
assessed. This is particularly the case for CO2 fluxes associated with
land use and land management, such as deforestation and changes in
agricultural practice (Al-Kaisi and Yin, 2005; Alluvione et al., 2009;
Dilling and Failey, 2012).
Soils are the largest terrestrial pool of carbon (C), storing 2344 Pg C
(1 Pg = 1 billion tonnes) of soil organic carbon (SOC) in the top 3 m (Jobbágy and Jackson, 2000). Tilling the soil before planting for
seedbed preparation and weeding has been a common practice in agriculture
since Neolithic times (McKyes, 1985). This technique is energy intensive and
also affects SOC stocks. Tilling changes the balance between organic carbon
put into the soil by plants and rendered available for soil
micro-organisms, and carbon output as greenhouse gases (GHGs) due to organic
matter decomposition (Rastogi et al., 2002). Soil tillage may also lead to
the vertical and lateral export of particulate and dissolved organic carbon
by leaching and erosion (Jacinthe et al., 2002; Mchunu et al.,
2011).
Soil tillage is estimated to have decreased SOC stocks by two-thirds from
pre-deforestation levels (Lal, 2003). But this estimate is highly uncertain,
due to the lack of detailed site-level meta-analysis for different climates,
soil types and management intensities.
Six et al. (2000, 2004) reported that tillage induces soil disturbance and
disruption of soil aggregates, exposing the protected SOC to microbial
decomposition and thus causing carbon loss from soils through CO2
emissions and leaching. Tillage is also responsible for soil compaction, soil
erosion and loss of soil biodiversity (Wilson et al., 2004). In some
instances, tillage is thought to have caused a net sink of atmospheric
CO2, for instance by displacing SOC to deeper soil horizons or
accumulation areas where it decomposes more slowly (Baker et al., 2007; Van
Oost et al., 2007). Soil tillage also modifies the mineralization rates of
nutrients, which feeds back on soil carbon input, implying that the effect of
tillage on the balance of SOC needs to be considered at ecosystem level
(Barré et al., 2010).
At the present time, tillage is being increasingly abandoned as the use of mechanized
direct planters becomes widespread and weed control is performed with
herbicides or in a more ecologically friendly way by using cover crops and
longer crop rotations.
The consequences of this change in practice on soil properties and soil
functioning are numerous. Importantly, it also raises the unsolved question:
what is the impact of tillage abandonment on GHG emissions and climate
change? Common wisdom is that no-tillage (or zero-tillage) agriculture
enhances soil carbon stocks (Peterson et al., 1998; Six et al., 2002; West
and Post, 2002; Varvel and Wilhelm, 2008) by reducing soil carbon loss as
CO2 emission (Paustian et al., 1997; West and Post, 2002; Dawson and
Smith, 2007). For instance, Paustian et al. (1997) reviewed 39 paired
comparisons and reported that abandonment of tillage increased SOC stocks in
the 0–0.3 m layer by an average of 258 g C m-2 (i.e. 8 %).
Ussiri and Lal (2009) observed a 2-fold increase of SOC stocks in the top
0.3 m of soil (800 vs. 453 g C m-2) after 43 years of continuous
Zea mays (maize) under no-tillage compared to tillage. Virto et
al. (2012), in a meta-analysis based on 92 paired comparisons. reported that
SOC stocks were 6.7 % greater under no-tillage than tillage.
While a consensus seemed to exist on
the potential of no-tillage for carbon sequestration and climate change
mitigation, several voices alerted the scientific and policy communities to
some possible flaws in early reports (Royal Society, 2001; VandenBygaart and
Angers, 2006; Baker et al., 2007; Luo et al., 2010; Dimassi et al. 2014;
Powlson et al., 2014). VandenBygaart and Angers (2006) indicated that the
entire plow depth had to be considered for not overstating zero-tillage
impact on SOC storage. To our knowledge, Baker
et al. (2007) were the first to point out that the studies concluding on
carbon sequestration under no-tillage management had only considered the
topsoil (to a maximum of 0.3 m), while plants allocate SOC to much greater
depths. False conclusions may be drawn if only carbon in the topsoil is
measured. Using 69 paired experiments worldwide where soil sampling depth extended
to 1.0 m, Luo et al. (2010) found that conversion from tillage to no-tillage
resulted in significant topsoil SOC enrichment, but did not increase the
total SOC stock in the whole soil profile. Dimassi et al. (2014) even
reported SOC losses over the long term.
Evidence for greater CO2 emissions from land under tillage as opposed to a
no-tillage regimen has been widely reported (e.g. Reicosky, 1997; Al-Kaisi
and Yin, 2005; Bauer et al., 2006; Sainju et al., 2008; Ussiri and Lal,
2009). For instance, in a study performed in the US over an entire year,
Ussiri and Lal (2009) found that, tillage emits 11.3 % (6.2 vs. 5.5 Mg of
CO2-carbon per hectare per year, CO2-C ha-1 yr-1) more
CO2 than no-tillage. Similarly, all the field surveys by Alluvione
et al. (2009) reported that land under tillage had 14 % higher
CO2 emissions than land with no-tillage. Al-Kaisi and Yin (2005) found
this difference to be as much as 58 %. A few in situ studies, however,
found CO2 emissions from no-tillage soils to be similar to those from
tilled soils (Aslam et al., 2000; Oorts et al., 2007; Li et al., 2010).
However, Hendrix et al. (1988) and Oorts et al. (2007) found greater CO2
emissions from untilled compared to tilled soils, with Oorts et al. (2007)
reporting that no-tillage increased CO2 emissions by 13 % compared
to tillage. In a further example, Cheng-Fang et al. (2012) showed that in
central China, no-tillage increased soil CO2 emissions by 22–40 %
compared with tillage. Oorts et al. (2007) attributed the larger CO2
emissions from no-tilled soil compared to tilled soil to increased
decomposition of the weathered crop residues lying on the soil surface. Crop
residue management has been shown to greatly impact CO2 emissions from
soils under both tillage and no-tillage (Oorts et al., 2007; Dendooven et
al., 2012). Jacinthe et al. (2002) reported annual CO2 emissions to be
43 % higher with tillage compared to no-tillage with no mulch, but found
a 26 % difference for no-tillage with mulch. Some other authors
associated the changes in CO2 emissions following tillage abandonment to
shifts in nitrogen fertilization application and in crop rotations (Al-Kaisi
and Yin, 2005; Álvaro-Fuentes et al., 2008; Cheng-Fang et al., 2012).
Sainju et al. (2008) working in North Dakota pointed to CO2 flux
differences between tilled and untilled soils only for fertilized fields,
while other studies pointed to the absence of nitrogen impact (Drury et al.,
2006; Cheng-Fang et al., 2012). Crop type and crop rotation may also
constitute important controls on the CO2 efflux differences between
tillage and no-tillage, mainly through differences in root biomass and its
respiration and nitrogen availability (Amos et al., 2005; Álvaro-Fuentes
et al., 2008). Omonode et al. (2007) found a 16 % difference in CO2
outputs between tillage and no-tillage under continuous maize, while Sainju
et al. (2010b) found no difference between continuous barley and barley–pea
rotations.
Micro-climatic parameters such as soil temperature and precipitation are
other likely controls of the response of soil CO2 emissions to tillage
(Flanagan and Johnson, 2005; Lee et al., 2006; Oorts
et al., 2007). These controls also need further appraisal.
The existence of research studies from different soil and environmental
conditions worldwide opens the way for a more systematic assessment of
tillage impact on soil CO2 emissions and their controls. Meta-analysis
is commonly used for combining research findings from independent studies and
offers a quantitative synthesis of the findings (Rosenberg et al., 2000;
Borenstein et al., 2011). This method has been used here in order to assess
the effects of background climate (arid to humid), soil texture (clayey to
sandy), crop types (maize, wheat, barley, paddy rice, rapeseed, fallow and
grass), experiment duration, nitrogen fertilization, crop residue management
and crop rotations on the CO2 emission responses of soils following
tillage abandonment. CO2 emissions from soil with tillage and no-tillage
were compared for 174 paired observations across the world.
Materials and methods
Database generation
A literature search identified papers considering in situ soil CO2
emissions and topsoil (0–0.03 m depth) SOC changes under tillage and
no-tillage management regimes. Google, Google scholar, Science Direct,
Springerlink, and SciFinder were used. In order to make the search process as
efficient as possible, a list of topic-related keywords was used such as
“soil carbon losses under tillage compared to no-tillage”, “soil CO2
emissions under tillage and no-tillage”, “land management practices and
greenhouse gases emissions”, “land management effects on CO2
emissions”, “effects of tillage vs. no-tillage on soil CO2 emissions”
and “SOC”. Many studies reported soil CO2 emissions and SOC for
cropland systems, but only those that reported CO2 emissions measured in
the field for both tillage and no-tillage from the same crop and during the
same period were used. In addition, we selected only studies that
consistently reported total soil respiration (heterotrophic + belowground
autotrophic respiration). The crops considered in this study were maize,
wheat, barley, oats, soybean, paddy rice and fallow. The practices considered
as tillage in this review are those that involve physical disturbance of the
topsoil layers for seedbed preparation, weed control, or fertilizer
application. Consequently, conventional tillage, reduced tillage, standard
tillage, minimum tillage and conservation tillage were all considered as
tillage. However, only direct seeding and drilling were considered as
no-tillage, among different practices reported in the reviewed literature.
The studies used in the meta-analysis covered 13 countries (USA, Spain,
Brazil, Canada, China, Denmark, France, Finland, New Zealand, Lithuania,
Mexico, Argentina, and Kenya). A total of 46 peer-reviewed papers with 175
comparisons for soil CO2 emissions and 162 for SOC content
(SOCC) were identified. Table 1 summarizes information on site
location, climatic conditions, crop rotation systems, and average CO2
emissions under tilled and untilled soils. Most of the data (37 %) came
from USA, followed by Canada, China and Spain (11 % each), and Brazil
(9 %). There was only one study from Africa, conducted in Kenya by Baggs
et al. (2006).
References included in database with locations, mean annual
precipitation (MAP), mean annual temperature (MAT), climate, land use,
no-tillage comparisons, average tillage (T), and no-tillage (NT) CO2
emissions.
SN.
Author (s)
Country
Comparisons
MAP
MAT
Climate
Land use
No-tillage vs.
CO2 emissions
mm
∘ C
gCO2-C m-2 yr-1
T
NT
1
Ahmad et al. (2009)
China
2
2721
17
Humid
Rice–rapeseed
CT
857
888
2
Al-Kaisi and Yin (2005)
USA
4
889
10
Humid
Maize–soybean
ST&DT&CP&MP
292
206
3
Alluvione et al. (2009)
USA
2
383
11
Arid
Maize
CT
490
599
4
Almaraz et al. (2009a)
Canada
2
979
6
Humid
Soybean
CT
747
523
5
Almaraz et al. (2009b)
Canada
4
979
6
Humid
Maize
CT
1269
1374
6
Alvarez et al. (2001)
Argentina
1
1020
17
Humid
Wheat-soybean
CT
2154
1533
7
Álvaro-Fuentes et al. (2008)
Spain
24
415
15
Arid
Wheat–barley–fallow–rapeseed
CT&RT
2311
1891
8
Aslam et al. (2000)
New Zealand
1
963
13
Humid
Maize
MP
2306
2281
9
Baggs et al. (2006)
Kenya
2
1800
24
Humid
Maize–fallow
CT
171
215
10
Brye et al. (2006)
USA
4
1282
16
Humid
Wheat–soybean
CT
3264
2604
11
Carbonell-Bojollo et al. (2011)
Spain
3
475
25
Arid
Wheat–pea–sunflower
CT
298
100
12
Chatskikh and Olesen (2007)
Denmark
2
704
7
Humid
Barley
CT&RT
117
102
13
Cheng-Fang et al. (2012)
China
4
1361
17
Humid
Rice–rapeseed
CT
636
699
14
Chavez et al. (2009)
Brazil
1
1755
19
Humid
Oats–soybean–wheat–maize
CT
464
573
15
Datta et al. (2013)
USA
1
1016
11
Humid
Maize
CT
438
634
16
Dendooven et al. (2012)
Mexico
2
600
14
Arid
Maize–wheat
CT
100
100
17
Drury et al. (2006)
USA
3
876
9
Humid
Wheat–maize–soybean
CT
575
559
18
Elder and Lal (2008)
USA
1
1037
11
Humid
Maize–wheat
MT
225
189
19
Ellert and Janzen (1999)
Canada
5
400
5
Arid
Wheat–fallow
CT&RT
406
186
20
Feizienė et al. (2010)
Lithuania
24
500
18
Humid
Wheat-rapeseed-barley-pea
CT&RT
302
296
21
Hovda et al. (2003)
Canada
2
979
6
Humid
Maize
CT
1342
1277
22
Jabro et al. (2008)
USA
1
373
14
Humid
Sugarcane
CT
3424
2247
23
Lee et al. (2009)
USA
3
564
16
Arid
Maize–sunflowers-pea
ST
933
917
24
Li et al. (2010)
China
4
1361
17
Humid
Rice–rapeseed
CT
284
328
25
Li et al. (2013)
China
2
1361
18
Humid
Rice
CT
2196
1534
26
Liu et al. (2006)
China
4
550
13
Humid
Maize
RT &PT
1340
1194
27
López-Garrido et al. (2009)
Spain
1
484
17
Arid
Wheat–sunflower–pea
CT
1080
943
28
López-Garrido et al. (2014)
Spain
3
484
17
Humid
Wheat–pea–red clover
CT
1075
887
29
Lupwayi et al. (1998)
Canada
1
336
-1
Arid
Wheat–pea–red clover
CT
621
464
30
Morell et al. (2010)
Spain
8
430
14
Arid
Barley
CT&MP
300
229
31
Mosier et al. (2006)
USA
9
382
11
Arid
Maize
CT
387
351
32
Menéndez et al. (2008)
Spain
2
350
16
Arid
Wheat–sunflower
CT
183
214
33
Omonode et al. (2007)
USA
4
588
19
Humid
Maize
MP&CP
273
268
34
Oorts et al. (2007)
France
2
650
11
Humid
Maize–wheat
CT
475
620
35
Pes et al. (2011)
Brazil
2
1721
19
Humid
wheat–soybean
CT
1387
1004
36
Regina and Alakukku (2010)
Finland
6
585
4
Humid
Barley-wheat-oats
CT
1856
2009
37
Reicosky and Archer (2007)
USA
1
301
5
Humid
Maize–soybean
MP
5807
1545
38
Ruan and Robertson (2013)
USA
1
890
10
Humid
Soybean
CT
1825
1533
39
Sainju et al. (2008)
USA
4
368
14
Arid
Barley–pea
CT
6726
4217
40
Sainju et al. (2010a)
USA
6
350
16
Humid
Barley–pea
CT
240
208
41
La Scala Jr. et al. (2001)
Brazil
4
1380
21
Humid
Maize
ROT&CP&DO&HO
1264
657
42
La Scala Jr. et al. (2005)
Brazil
4
1380
21
Humid
Maize
CT
758
518
43
La Scala Jr. et al. (2006)
Brazil
2
1380
21
Humid
Sugarcane
RT&CT
5435
2604
44
Smith et al. (2011)
USA
1
796
17
Humid
Maize–soybean
CT
141
152
45
Smith et al. (2012)
USA
4
1370
17
Humid
Maize–soybean
CT
970
935
46
Ussiri and Lal (2009)
USA
2
1037
11
Humid
Maize–soybean
CT&MT
721
500
Several soil variables were considered, as follows: SOCC (%),
soil bulk density (ρb, g cm-3), and soil texture (clay, silt, and
sand, %) in the 0–0.03 m layer. In addition, mean annual temperature
(MAT, ∘C) and mean annual precipitation (MAP, mm), crop types, crop
rotations, nitrogen fertilization rate, experiment duration and crop residue
management were also considered.
Data for soil CO2 emissions (n= 46) were obtained for all studies by
using open chambers and reported on an area basis. Soil CO2 emissions
were directly extracted from the papers and were standardized to g
CO2-C m-2 yr-1. Thirty-eight studies gave SOCC for
both tillage and no-tillage. Four studies (Hovda et al., 2003;
Álvaro-Fuentes et al., 2008; Lee et al., 2009; Dendooven et al., 2012)
gave SOCC, in term of the mass of carbon in the 0–0.03 m layer
and per unit area (kg C m-2). Finally, for the four remaining studies,
SOCC was extracted from other publications describing measurements
at the same site. SOCC was estimated from soil organic carbon
stocks (SOCS kg C m-2) and bulk density following Eq. (1)
by Batjes (1996):
SOCS=SOCC×ρb×T(1-PF100)b,
where SOCS is the soil organic C stock (kg C m-2);
SOCC is soil organic C content in the ≤ 2 mm soil material
(g C kg-1 soil); ρb is the bulk density of the soil
(kg m-3); T is the thickness of the soil layer (m); PF is the
proportion of fragments of > 2 mm in percent; and b is a
constant equal to 0.001.
Information on MAP and MAT was extracted from the papers, but were estimated
in nine studies where such information was not provided, based on the
geographic coordinates of the study site and using the WORLDCLIM climatology
(Hijmans et al., 2005) with a spatial resolution of 30 s. In eight
studies where soil texture was only given as textural class, particle size
distribution was estimated using the adapted soil texture triangle (Saxton et al.,
1986).
Table 2 shows the variables used in categorizing the experimental
conditions. The climatic regions were extracted directly from the papers and
categorized into arid and humid climate (Köppen, 1936). SOCC were
categorized into three categories following Lal (1994): low (SOCC < 10 g C kg-1),
medium (10–30 g C kg-1), and high
(> 30 g C kg-1). Soil texture was categorized based on the
soil textural triangle (Shirazi and Boersma, 1984) into three classes (clay,
loam, and sand). Fertilization rate for this meta-analysis was classified
into the categories defined by Cerrato and Blackmer (1990) as follows: low when below
100 kg N ha-1 and high when above 100 kg N ha-1.
Categories used in describing the experimental conditions.
Categorical variable
Level 1
Level 2
Level 3
SOCC
Low
Medium
High
(< 10 g kg-1)
(10–30 g kg-1)
(> 30 g kg-1)
Climate
Arid
Humid
Soil texture
Clay
Loam
Sand
(> 32 % clay)
(20–32 clay)
(< 20 % clay)
Experiment duration
< 10 years
≥10 years
Nitrogen fertilizer
Low
high
(< 100 kg N ha-1)
(≥ 100 kg N ha-1)
Crop residues
Removed
Returned
Crop rotation
No rotation
Rotation
In addition, no-tillage treatment was classified as short duration when
< 10 years, or long duration when exceeding 10 years. Crop residue
was either left on the soil surface or removed after harvest with no
distinction between removal proportions. Crop rotations were divided into
two categories: a series of different types of crop in the same area classed
as “rotation”, or continuous monoculture, classed as “no rotation”.
Meta-analysis
The response ratio (R) of CO2 emissions to SOC under tillage (T) and
no-tillage (NT) was calculated using Eqs. (2) and (3). As common practice,
natural log of the R (lnR) has been calculated as an effect size of
observation (Hedges et al., 1999).
lnR=ln(CO2T/CO2NT)lnR=ln(SOCT/SOCNT)
The MetaWin 2.1 software (Rosenberg et al., 2000) was used for analyzing the
data and generating a bootstrapped (4999 iterations) to calculate 95 %
confidence intervals. The means of effect size were considered to be
significantly different from each other if their 95 % confidence
intervals were not overlapping and were significantly different from zero if
the 95 % level did not overlap zero (Gurevitch and Hedges, 2001).
Discussion
Overall influence of tillage on SOCC and soil CO2
emissions
Our meta-analysis shows that tillage has a significant impact on decreasing
topsoil (0–0.03 m) organic carbon content (SOCC) and increasing
CO2 emissions, with 10 % lower SOCC and 21 % greater
CO2 emission in tilled than untilled soils. Lower SOCC and
greater CO2 emissions under tillage reflect faster organic matter
decomposition as a result of greater soil aeration and incorporation of crop
residues to the soil, and breakdown of soil aggregates, which all render the
organic material more accessible to decomposers (Reicosky, 1997; Six et al.,
2002, 2004). However, results from the literature do not always agree with
this. In case of soil carbon, for example, Cheng-Fang et al. (2012) found
7–48 % greater SOCC under tilled rice in China, when Ahmad et
al. (2009) observed no significant differences. In case of soil CO2
emissions, while for instance Ussiri and Lal (2009) for a 43 years maize
monoculture in USA observed 31 % greater CO2 emissions from tilled
than from no-tilled soils, Curtin et al. (2000) and Li et al. (2010) found no
significant difference in CO2 emissions between these treatments while
Oorts et al. (2007) reported greater soil CO2 emission under no-tillage
(4064 kg CO2-C ha-1) compared to tillage
(3160 kg CO2-C ha-1), which they attributed to greater soil
moisture content and amount of crop residue on the soil surface.
Principal components analysis (PCA) using the different
environmental factors as active variables and soil CO2 emission
difference between T and NT (ΔCO2T-NT) as the
supplementary variable.
Influence of climate
Although there was no significant difference between arid and humid climates,
CO2 emissions and SOCC changes between untilled and tilled
soils tended to be greater in arid than in humid climates (Fig. 1a). In
support, Álvaro-Fuentes et al. (2008), who investigated tillage impact on
CO2 emissions from soils in a semiarid climate, attributed the observed
large difference between tillage and no-tillage to differences in soil water
availability. At humid sites high soil moisture favour high decomposition
rates resulting in small differences between tilled and untilled soils, while
large differences develop in arid climates with much lower soil water content
(Fortin et al., 1996; Feizienė et al., 2011). This supports the idea that
the soil response to tillage is affected by climate thresholds (Franzluebbers
and Arshad, 1996).
Influence of soil properties
Soil organic carbon content
The decrease of CO2 emission differences between tillage and no-tillage
with increasing SOCC is most likely due to diminishing
inter-aggregate protection sites as SOCc level increases. Several studies
have shown that carbon inputs into carbon-rich soils show little or no
increase in soil carbon content with most of the added carbon being released
to the atmosphere, while carbon inputs in carbon-depleted soils translate to
greater carbon stocks because of processes that stabilize organic matter
(Paustian et al., 1997; Solberg et al., 1997; Six et al., 2002). Another
reason, which does not involve stabilization, is the fact that soils that
have been depleted in carbon tend to recover and accumulate SOC until
equilibrium is reached (Carvalhais et al., 2008). Therefore, abandoning
tillage in soils with low SOCC tends to offer greater protection of
SOC than in soils with inherently high SOCC levels. In support,
Lal (1997) reported low SOCC and aggregation correlations under
high SOCC soils, which suggests that substantial proportions of the
SOC were not involved in aggregation. Hence, the greater difference of
CO2 emissions between tilled and untilled soils for carbon-depleted
soils compared to carbon-rich soils may be due to much greater stabilization
of extra SOC delivered to the carbon-depleted soil by protection in soil
aggregates within the topsoil layers (0.0–0.05 m). Tillage of
carbon-depleted soils is likely to lead to the breakdown of more soil
aggregates, thus leading to greater decomposition of the residues added under
no-tillage, as hypothesized by Madari et al. (2005) and Powlson et
al. (2014).
Soil texture
Soils under zero tillage emitted less CO2 than tilled soils, and the
CO2 emission difference was the greatest in sandy soils (Fig. 3).
Further, in sandy soils, as indicated by Fig. 3, the largest CO2
emission difference is mirrored by the largest SOCC difference.
Greater SOCC and then CO2 differences under sandy soils might
be due to the lower resistance of soil aggregates to disaggregation, with
tillage accelerating aggregate breakdown and decreasing organic matter
protection, which causes a fast loss of soil carbon. Differences in CO2
emissions between treatments were greater in sandy than in clayey soils
(Fig. 3). This might be due to the fact that sandy soils have higher
porosity, allowing changes in soil management to translate into large
variations in the gas fluxes to the atmosphere (Rastogi et al., 2002; Bauer
et al., 2006). These suggestions contrast, however, with the results of, for
instance, Chivenge et al. (2007) working in Zimbabwe and in other locations
where little impact of tillage on carbon sequestration was found under sandy
soils as compared to clayey ones.
Influence of the duration since tillage abandonment
The differences in SOCC between tilled and untilled soils increased
with the time since abandonment of tillage (Fig. 5b). When abandonment of
tillage took place before less than 10 years, there were no differences in
SOCC between tillage and no-tillage, but for longer durations,
tilled soils had 14 % less SOCC than untilled soils. This can
be explained by the progressive increase of soil carbon accumulation with
time as a result of the retention of a fraction of the crop residue under
no-tillage. This explanation is consistent with the results of Paustian et
al. (1997) and Ussiri and Lal (2009). Six et al. (2004) reported that the
potential of no-tillage to mitigate global warming is only noticeable a long
time after (> 10 years) a no-tillage regime has been adopted.
This would suggest that shifts in CO2 emission differences between
tillage and no-tillage will occur over time; this could not be observed in
our analysis (Fig. 5a) because the majority of experiments in this study were
less than 10 years in length. Further, in some cases no-tillage leads to
carbon loss in the topsoil layer (0–0.3 m) during the first years of
adoption (Halvorson et al., 2002; Six et al., 2004), a response which can be
attributed to slower incorporation of surface residues into the soils by soil
fauna. However, different studies give contrasting results; for instance, the
long-term no-tillage experiments in northern France by Dimassi et al. (2014)
showed that SOC increased in the topsoil (0–0.1 m) during 24 years after
tillage abandonment, then did not increase, whereas SOC continuously
decreased below 0.1 m. A loss of SOC following tillage abandonment was also
suggested by Luo et al. (2010) and Baker et al. (2007).
Crop types, residue management, and crop rotation
The no-tillage minus tillage variations of CO2 emission and
SOCC between crop types are correlated with the quantity and
quality of crop residue (Fig. 4a–b). Both quantity and quality of crop
residues are important factors for soil carbon sequestration and CO2
emissions, and are highly dependent on crop type. Reicosky et al. (1995),
reported that corn returned nearly twice as much residue than soybean, and
that soybean residues decomposed faster because of their lower C : N ratio.
Thus, maize residues result in higher soil organic matter than soybean.
Al-Kaisi and Yin (2005) also reported reduced soil CO2 emissions and
improved soil carbon sequestration in maize-soybean rotations due to better
residue retention. Reicosky (1997) summarized that maximizing residue
retention results in carbon sequestration with subsequent decrease in
CO2 emissions. However, several recent studies pointed to the lack of
impact of residue management on soil carbon, with Lemke et al. (2010) showing
that crop-residue removal in a 50-year experiment did not significantly
(P > 0.05) reduce soil carbon, and Ren et al. (2014) showing
that inputs from wheat straw and manure up to 22 ton ha-1 yr-1
could not increase soil carbon over 4 years. De Luca et al. (2008) explained
the lack of crop residue impact on soil carbon with the very low amount of
carbon in residues compared to the bulk soil in their study, while Russell et
al. (2009), having investigated several systems, pointed out to a concomitant
increase of organic matter decomposition with carbon input rates.
Wilson and Al Kazi (2008) indicated that continuous corn cropping systems had
higher soil CO2 emissions than corn-soybean rotations because of a
greater residue amount. Van Eerd et al. (2014) concluded from winter that
wheat–legumes rotations yielded higher carbon input during wheat
cultivation, due to a greater belowground allocation. The present analysis suggests
that tilled soils have significantly greater CO2 emissions than
no-tilled soils irrespective of the crop rotation system (Fig. 8). This is
likely because crop rotation increases SOCC, microbial activity,
and diversity. For instance, Lupwayi et al. (1998, 1999) found greater soil
microbial biomass under tillage legume-based crop rotations than under
no-tillage with tillage increasing the richness and diversity of active soil
bacteria by increasing the rate of diffusion of O2 and the availability
of energy sources (Pastorelli et al., 2013). This study showed that
continuous monoculture did not result in significantly different CO2
between tilled and untilled soils (Fig. 8a). Rice is one crop often produced
under a continuous monoculture practice; however, in this meta-analysis,
paddy rice did not show significant difference of CO2 emissions between
tillage and no-tillage. Li et al. (2010) and Pandey et al. (2012) attributed
the lack of difference to anaerobic soil conditions occurring under both
practices.
Nitrogen fertilization
The differences of CO2 between tillage and no-tillage did not differ
with nitrogen fertilizer level (Fig. 6a), confirming observations by
Alluvione et al. (2009) and Almaraz et al. (2009b). This result could be due
to the fact that nitrogen fertilization increases productivity and carbon
inputs to the soil under both tilled and untilled systems, which may override
nitrogen effects on decomposition such as shown by Russell et al. (2009).
Increasing SOC as a response to nitrogen fertilization was found under
no-tillage during a period of 4 years (Morell et al., 2010), and during the
50 year experiment of Lemke et al. (2010). Yet Sainju et al. (2008) reported
the opposite: a 14 % increase of soil CO2 flux with nitrogen
fertilizer, because fertilizer application stimulated biological activity,
thereby producing more CO2, and causing SOCC decline (Khan et
al., 2007; Mulvaney et al., 2009). In contrast, Wilson and Al Kazi (2008)
showed that increasing N fertilization generally decreased soil CO2
emissions, with a maximum decrease of 23 % from 0–135 kg N ha-1
to 270 kg N ha-1 occurring during the growing season, which might be
explained by a series of mechanisms, including the inhibition of soil enzymes
and fungus and the reduction of root activity.
Overall, these results pointed to little benefit in not tilling clayey soils
with high SOCC, with the highest no-tillage benefits occurring under
sandy soils with low SOCC. This can be explained by differences in soil
aggregate stability. Indeed, since the stability of soil aggregates shows a
positive correlation with clay and organic matter content, clayey and
organic soils produce stable aggregates which are likely to be more
disaggregated by tillage compared to sandy aggregates of low carbon content.
The SOC protected within soil aggregates under no-tillage becomes exposed
under tillage because of aggregate dispersion; which explains the greater
reduction in CO2 emission with no-tillage under sandy soils. Rather,
emission is likely to be reduced under zero tillage as a result of improved
soil aggregate stability and the associated protection of decomposed and
stable organic matter. Crop management such as fertilization and crop type,
or climate are shown to have little effect on aggregation. Our analysis did
not include time since cessation of tillage as a specific predictor and
classified instead the experiments into two simple categories (short vs.
long term).
Conclusion
The aim of this study was to provide a comprehensive quantitative synthesis
of the impact of tillage on CO2 emissions using meta-analysis. Three
main conclusions can be drawn. Firstly, tillage systems had 21 % greater
CO2 emissions than no-tillage, worldwide. Secondly, the reduction in
CO2 emissions following tillage abandonment was greater in sandy soils
with low SOCC compared to clayey soils with high SOCC. Thirdly,
crop rotation significantly reduced the CO2 emissions from untilled
soil, by 26 % compared to tilled soil, while continuous monocultural
practice had no significant effect. This is most probably due to the fact
that crop rotation can increase SOCC and more microbial activity under
a tilled compared to an untilled treatment. These results emphasize the
importance of including soil factors such as texture, aggregate stability
and organic carbon content in global models of the carbon cycle.
Long-term process studies of the entire soil profile are needed to better
quantify the changes in SOC following tillage abandonment and to clarify the
changes in the dynamics of carbon inputs and outputs in relation to changes
in microbial activity, soil structure and microclimate. In addition, more
research is needed to identify the underlying reasons why, over a long period
of time, the abandonment of tillage results in a decrease in integrated
CO2 emissions, that appears to be much higher than the observed increase
in SOCS. The goal remains to design agricultural practices that are
effective at sequestering carbon in soils.
Finally, one future application of these data could be to use them to
calibrate soil carbon models. The models could be run with prescribed inputs
(from observation sites) used to simulate decomposition and the mass balance
of SOC over time for different climates, soil texture and initial SOC content
with respect to the theoretical value assuming equilibrium of decomposition
and input (Kirk and Bellamy, 2010). Most soil carbon models developed for
generic applications (e.g. RothC, DNDC, and CENTURY) would be suitable tools
for exploitation of the data presented here (Adams et al., 2011).