effects of reduced tillage on net greenhouse gas fluxes from loamy sand soil under winter crops in...

Agriculture, Ecosystems and Environment 128 (2008) 117–126

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Agriculture, Ecosystems and Environment

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Effects of reduced tillage on net greenhouse gas fluxes from loamy sand soilunder winter crops in Denmark

Dmitri Chatskikh *, Jørgen E. Olesen, Elly M. Hansen, Lars Elsgaard, Bjørn M. Petersen

Department of Agroecology and Environment, University of Aarhus, Faculty of Agricultural Sciences, PO Box 50, DK-8830 Tjele, Denmark

A R T I C L E I N F O

Article history:

Received 11 December 2007

Received in revised form 8 May 2008

Accepted 15 May 2008

Available online 30 June 2008

Keywords:

Nitrous oxide

Soil respiration

Ploughing

Direct drilling

Winter oilseed rape

Winter wheat

Modelling

FASSET

CN-SIM

GWP

A B S T R A C T

The environmental consequences of changing from conventional to reduced soil tillage in winter crops

are yet poorly understood under North European conditions. Soil tillage intensity may affect both crop

growth and soil carbon (C) and nitrogen (N) turnover and balances, including emissions of greenhouse

gases (GHG) such as CO2 and N2O. In this study we compared the effects of conventional tillage (CT) using

mouldboard ploughing to 20 cm depth, reduced tillage (RT) using rotary harrowing to 8–10 cm depth and

direct drilling (DD) with disk coulters on fluxes of CO2 and N2O from loamy sand soil under winter oilseed

rape (Brassica napus L.) followed by winter wheat (Triticum aestivum L.). The measurements were

conducted by use of chambers over a period from August 2003 to July 2005 in a soil tillage experiment

established in Denmark in 2002. To integrate information on the C and GHG budgets for the experiment,

the FASSET model was used with no recalibration in a two-step modelling procedure. First, we fitted the

soil organic matter (SOM) model of FASSET to give the observed ratio of soil CO2 respiration from the CT

and DD treatments by scaling all decomposition and maintenance parameters for the DD treatment with

the same value (d), called the ‘‘tillage factor’’. Second, the complete FASSET model was run with default

parameter value for ploughing depth in CT (d = 1.00) and the estimated value for DD (d = 0.57), in order to

quantify the cumulated CO2 and N2O emissions. Both measurements and model simulations showed that

the combined global warming potential (GWP) from CO2 and N2O emissions was lower from reduced

tillage treatments (RT and DD) than from conventional tillage. Thus, compared with CT, modelled

reduced soil tillage treatments decreased GHG emissions by 0.56 (RT) and 1.84 (DD) Mg CO2-

eq. ha�1 year�1. Similar differences between treatments were obtained for simulations over 30 years of

observed weather for the specific site. In both cases, negative GWPs for the studied site were obtained. A

sensitivity analysis showed that the simulated GHG emissions were primarily influenced by changes in

SOM model parameters, whereas observed changes in soil water retention affected only N2O emissions,

and soil temperature had only minor effects.

� 2008 Elsevier B.V. All rights reserved.

1. Introduction

In Europe the adoption of conservation tillage, which combinesreduced soil tillage intensity and balanced plant residue manage-ment and leads to less energy consumption and soil qualityimprovement, has been quite slow (Tebrugge and During, 1999).The adoption of reduced tillage practices may also be able toincrease or at least stabilise the carbon (C) content in thepreviously ploughed soil layer under arable cropping. Such effectshave been demonstrated under North American (Paustian et al.,1997) and some European conditions (Smith et al., 1998). It istherefore reasonable to consider reduced tillage as a strategy for

* Corresponding author. Tel.: +45 89991843; fax: +45 89991619.

E-mail address: [email protected] (D. Chatskikh).

0167-8809/$ – see front matter � 2008 Elsevier B.V. All rights reserved.

doi:10.1016/j.agee.2008.05.010

reducing net CO2 emissions and improving soil C sequestration inagricultural fields, although these effects may depend onenvironmental conditions (Ogle et al., 2005).

The intensification of soil tillage practices in arable cropping,especially mouldboard ploughing with increasing ploughingdepth, has generally resulted in reductions of soil C pool sizescompared to grasslands or native ecosystems (Potter et al., 1999;Soussana et al., 2004). However, the impact of soil tillage on realfarms varies geographically and temporally, because, firstly, theeffect of tillage on turnover of soil organic matter (SOM) interactswith soil type and climatic conditions (Ogle et al., 2005; Six et al.,2002), and, secondly, because soil tillage may influence cropgrowth and thus the soil C input differently (Paustian et al., 1997),again depending on local conditions. The rate of change in soil Cstorage will also depend on the size of the soil C stock (Smith et al.,1998). Ploughing of grassland (with large soil C stocks) thus leads

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to a rapid decline in soil C content (Soussana et al., 2004), whereasthe decline in soil C is much smaller in soils under arable cropping(Christensen and Johnston, 1997). There is usually only a slowincrease in soil C following conversion to reduced or no-tillagepractices (Ogle et al., 2005).

Other greenhouse gases (GHG) besides CO2, notably nitrousoxide (N2O) and methane (CH4), may also be affected by soil tillage(Robertson et al., 2000). To evaluate the net effect of tillage on GHG,it is necessary to consider the different global warming potentials(GWP) of the GHGs. CH4 and N2O have estimated GWPs that are,respectively, 25 and 298 times higher than that of CO2 (IPCC, 2007).Increased soil tillage activity may slightly decrease CH4 emissionsfrom soils, because CH4-oxidising bacteria are negatively affectedby soil disturbance (Hutsch, 2001). However, this effect is smalland can largely be ignored (Robertson et al., 2000; Six et al., 2004).On the other hand, there is a risk of increased N2O emissions underno-tillage and reduced tillage (Smith et al., 2000; Six et al., 2004).

Thus, soil tillage may affect the emissions of both CO2 and N2Othrough effects on soil structure (Ball et al., 1999) and the degree towhich crop residues and manure are incorporated into the soil(Oorts et al., 2007). The higher aeration in tilled soil increasesoxygen availability, possibly resulting in increased aerobic turn-over in the soil and thus an increased potential for gaseousemissions (Skiba et al., 2002). At the same time, aeration is able toreduce the prevalence of anaerobic microsites in the soil, wheredenitrification will occur. The incorporation of crop residues in thesoil will increase the availability of organic matter for themicroorganisms (Carter, 1986), leading to increased CO2 emissionsand possibly increased N2O emissions due to an associatedenhancement of soil N turnover (Oorts et al., 2007).

The objectives of this study were: (1) to determine howemissions of CO2 and N2O from the soil are affected byconventional and reduced tillage practices in autumn-sown cropsand (2) to quantify the C and the GHG budget for an experimentwith different tillage treatments by means of dynamic modelling ofthe agroecosystem.

2. Materials and methods

Measurements were carried out between August 2003 andSeptember 2005 in winter oilseed rape (Brassica napus L.) followedby winter wheat (Triticum aestivum L.) in a soil tillage experimentinitiated in 2002 at Research Centre Foulum in Denmark. The soilwas a loamy sand (8.8% clay, 3.8% organic matter, pH(CaCl2) = 6.1),classified as a Typic Hapludult (USDA, 1998) and Anthric Umbrisol(FAO, 1998).

2.1. Design of the experiment

The experiment was conducted in a randomised block designwith conventional tillage (CT), reduced tillage (RT) and directdrilling (DD) in four replicates. The soil tillage treatments wereperformed in plots of 72 m � 6 m, but the measurements wererestricted to a subplot of 30 m2. Both the CT and RT treatmentswere stubble cultivated to 8–10 cm depth using a rotary harrow,and the CT treatment was subsequently mouldboard ploughed to20 cm depth followed by rolling before sowing. Sowing in the CTtreatment was performed with a Nordsten Lift-o-matic CLH300traditional seed drill, whereas a Gaspardo Scan-Seeder DP300 withdisk coulters was used in the RT and DD treatments.

The experiment was initiated in autumn 2002 with sowing ofwinter barley (Hordeum vulgare L.). After harvest on 4 August 2003the barley straw was left on the ground. Weeds were sprayed withglyphosate on 5 August 2003. Harrowing (RT, CT) and ploughing(CT) followed by rolling was carried out on 14 August and followed

by sowing of winter oilseed rape in all treatments on 15 August. Alltreatments were sprayed with clomazone against weeds on 17August. The DD treatment was sprayed with glyphosate on 18August. On 2 September 2003 all treatments were sprayed withfluazifop-P-butyl. On 12 March 2004, 71 kg N ha�1 in NH4NO3

(50:50) was applied by mechanical spreading in all treatments.Manure (untreated pig slurry) was applied with trail hoses (25 cmdistance between hoses) on 21 April at a rate of 40 Mg ha�1 or872 kg dry matter ha�1, equivalent to 124 kg total–N ha�1, ofwhich 111 kg ha�1 was NH4–N. The winter oilseed rape washarvested on 2 August, and on 3 August the RT was harrowed to 3–4 cm depth. The RT and DD treatments were sprayed withglyphosate on 10 September 2004. Ploughing was carried out in theCT treatment on 24 September, followed by harrowing in the RTand CT treatments and sowing in all treatments on the same date.Fertiliser N was applied by mechanical spreading of NH4NO3

(50:50) on 4 and 26 April 2005 at rates of 72 and 100 kg N ha�1,respectively. All treatments were sprayed with tribenuron andiodosulfuron on 16 April to control weeds. The winter wheat washarvested on 18 August 2005. Diseases and insect pests werecontrolled using fungicides and insecticides in both yearsaccording to normal Danish agricultural practice (Anonymous,2002).

Daily standard meteorological data for 1961–2005 wereobtained from the meteorological station at Foulum (568290N,098340E; elevation 56 m a.s.l.) situated within 1 km from theexperimental site.

2.2. CO2 and N2O fluxes

Soil CO2 respiration was measured by a dynamic system (PPSystems, U.K.) consisting of a chamber (SRC-1) and an infrared gasanalyser (IRGA, EGM). The chamber had a diameter of 10 cm andheight of 15 cm; the measuring period was set to 120 s. In the firstyear (2003) the chambers were placed in the field directly on top ofthe soil. In the second year the chambers were attached topermanently installed metal frames (three frames in each plot).The measurements were carried out on bare soil in the same plotsin both winter oilseed rape (August–December 2003 and March–June 2004) and winter wheat (August–October 2004 and March–July 2005).

Starting in August 2003 and until July 2005 fluxes of N2O weremeasured using static chambers. The gaseous measurements wereperformed in ‘‘event-related’’ (see e.g. Smith and Dobbie, 2001)campaigns, related to soil tillage and N application.

Measurements of N2O fluxes before and after tillage underwinter oilseed rape were carried out with small cylindrical staticchambers (16 cm in diameter and 22 cm high), five for each plot.Duplicate 5-ml gas samples were taken from each chamber threetimes with intervals of 30–45 min. The 5-ml gas samples weresaved in evacuated 3-ml glass vials (Venoject) at overpressure(leakage <4% per week), and the gas probes were analysed thesame or the next day on a Varian 3300 GC with ECD detector(Chatskikh and Olesen, 2007).

The rest of the N2O measurements were done with largersquare static chambers (75 cm � 75 cm � 25 cm), which wereplaced on top of metal frames installed permanently in the soil. Thegas sampling intervals were increased up to 60 min during periodsof low N2O fluxes. A tube with a small diameter and smallventilators inside the chambers supported a stable air pressure andmixing of the air within the chamber. The gas sampling andanalyses were done as described for the small chambers; seePetersen (1999) for details.

The accumulation rate of N2O in the atmosphere inside thechamber was calculated using a simple linear regression between

D. Chatskikh et al. / Agriculture, Ecosystems and Environment 128 (2008) 117–126 119

concentration and sample time, t. The N2O efflux, E (g N2O–N m�2 h�1), was calculated by:

E ¼ dN2O

dt

VM

AVm(1)

where dN2O/dt is the accumulation rate of N2O in the air inside thechamber (ppm h�1), A is the chamber’s area (0.0201 and 0.5625 m2

for small and big chambers, respectively), V is the chamber volume(3.217 and 140.6 L for small and big chambers, respectively), M isthe mass of N per mol of N2O (28 g mol�1), and Vm is molecularvolume for N2O (23.2 L mol�1 at 10 8C). Correction for water andtemperature of the sample was found insignificant (P < 0.05).

Daily fluxes were calculated from the measured CO2 and N2Ofluxes by correcting for the diurnal variation using the proceduredescribed by Chatskikh and Olesen (2007). To compare observedand simulated data cumulated N2O emissions were calculated bylinear interpolation of the daily fluxes.

2.3. Soil water and temperature

Soil water content at 0–30 cm depth was measured manuallyon a daily basis using TDR (time domain reflectometry), and soiltemperature at 5 cm depth was measured automatically every10 min as described in Chatskikh and Olesen (2007).

2.4. Crop measurements

The grains and seeds were harvested at maturity using a plotcombine harvester for yield determination. To determine drymatter (DM) in above-ground biomass (seeds and straw) sampleswere taken from two 0.5 m2 areas in each plot at maturity. DM wasdetermined after drying the plant samples at 80 8C for 24 h. Thegrain DM was determined by near-infrared transmission (NIT)(Buchmann et al., 2001). The C content in grain, seed and straw wasassumed at 45% of DM (Petersen et al., 2005a,b).

2.5. Soil C and GHG budget calculation

A two-step modelling procedure was used to estimate soil C andGHG budget for the DD, RT and CT treatments. The effect of soiltillage (‘‘tillage factor’’) on SOC turnover was estimated with theSOM CN-SIM model (Petersen et al., 2005a,b) using observed soilCO2 respiration, and the tillage factor was subsequently applied inthe FASSET model (Berntsen et al., 2003) for simulating effects ofthe three soil tillage systems on net GHG emissions. The FASSETmodel was not recalibrated or adjusted, because it includes thesame SOM model, and the estimated turnover parameters fromCN-SIM can therefore be used directly (Berntsen et al., 2004, 2005).Both models were run with daily time step.

2.5.1. Estimation of the effect of soil tillage on SOM turnover

The SOM model (CN-SIM) described by Petersen et al. (2005a,b)was used to simulate changes in soil C for the DD and CTtreatments to a depth corresponding to the ploughed layer in theCT treatment. An organic residue that enters the SOM model is splitinto two organic pools (AOM1 and AOM2) of the modelled soillayer depending on the type and quality of the residue. The AOMpools are decomposed by two microbial pools (SMB)—a slowlydecomposing SMB1 pool and a faster decomposing SMB2 pool.Residues from the SMB2 pool go to a soil microbial residue (SMR)pool, while residues from the SMB1 pool go to a native organicmatter pool in soil (NOM). It is assumed that part of the organicmatter in soil is inert (IOM). The soil CO2 respiration in the modelresults from the two SMB pools. The rate of maintenance

respiration is controlled by a maintenance coefficient. The soil Cpools will decay using first-order kinetics determined by adecomposition coefficient.

The model was parameterised for soil under regular or othertypes of mechanical disturbance on long- and short-term Europeandatasets (Petersen et al., 2005a,b) and these parameters wereapplied to the CT treatment. However, a scenario analysis indicatedthat this parameterisation overestimates turnover under condi-tions with restricted soil tillage (Berntsen et al., 2006a). Thus, it ishypothesised that the appropriate simulation of the tillage effectson soil C turnover could be achieved by including the ‘‘tillagefactor’’ (d) multiplier [0, 1], which is applied to all decompositionand maintenance coefficients in the SOM model. CT a priori has thed value of 1.00. The d value for reduced soil tillage could be found bysimultaneous scaling of maintenance and decomposition para-meters for all pools (except inert IOM) by including differences inplant residue incorporation and soil water content between soiltillage treatments. The d value was estimated for each of fourmeasuring periods (2003–2005) in two replicates by adjusting d toobtain the same observed (Obs) and simulated (Sim) ratios ofcumulated soil CO2 respiration from DD and CT:

PCODD

2PCOCT

2

!Obs

¼P

CODD2P

COCT2

!Sim

(2)

Estimates of C inputs for the SOM model were established byconsidering three C input sources: shoot residues that are notharvestable, shoot residues that may be harvested (e.g. straw) androot residues and root-derived organic C released during growth.The allometric relations between yields and these C sources wereconstructed by considering: (1) the harvested primary product(grain or seed) relative to the total above-ground production(harvest index); (2) the fraction of the secondary product (straw)relative to the total above-ground production that could beharvested; (3) the fraction of the total net production that isallocated to root-derived C. Given these three parameters and thefraction of the secondary product that is harvested, the C input tothe soil was calculated. The harvest index for the primary productwas estimated as 0.39 for both crops (Katterer et al., 2004), and theharvestable secondary product relative to the primary product wasestimated as 0.55 (Anonymous, 2004). The fraction of netassimilation allocated to root-derived C was set to 0.17 and 0.25for winter barley and winter oilseed rape, respectively, assumingthat the translocation of C to winter barley roots is only 65% of thatto wheat roots (Kuzyakov and Domanski, 2000). Based on data forwinter wheat, 70% of the root-derived C was assumed to bedeposited in the topsoil (0–25 cm) (Katterer et al., 1993).

It was assumed that 95%, 50% and 5% of plant residues placed onthe soil surface were incorporated into the soil for the soil tillageoperations CT, RT and DD, respectively. The transfer of surfaceplant residues to the uppermost soil layer was described by first-order kinetics, where temperature and precipitation are limitingenvironmental factors (Stroo et al., 1989). The following simplifiedmodel was used to calculate the amount of plant residues placedon the soil surface after soil tillage operations on a daily basis:

Rn ¼ Rn�1 � expð�k �min½F�ðTnÞ; FðPrnÞ�Þ (3)

where R is dry matter of above-ground residues (kg ha�1), n is timein days, k is a transport coefficient, F*(T) is a factor depending onmean daily air temperature T (8C), and F(Pr) is a water limitingfactor, which depends on daily precipitation (Pr). The k-value wasestimated for decomposition rate of residues of small grain cropsas 0.033 (Steiner et al., 1999). The daily reduction in surfaceresidues is added to the top soil layer.

Table 1Summarised meteorological data used for the modelling

Period

2004 2005 30 years 1976–2005 Normal 1961–1990

Mean annual temperature and total annual precipitation

Air temperature (8C) 8.2 8.1 7.6 7.3

Precipitation (mm) 710 551 673 703

Mean temperature and precipitation sum for May–July

Air temperature (8C) 12.8 13.4 13.4 13.1

Precipitation (mm) 179 189 163 164


The temperature response was taken from Kirschbaum (1995):

FðTnÞ ¼ a exp bþ c � Tn1� 0:5Tn

d

� �� (4)

where a = 7.24, b = �3.432, c = 0.168, d = 36.9. The response wasnormalised for [0, 1] to obtain F*(T), which gave temperatures closeto the temperature coefficient proposed by Stroo et al. (1989) andused for small grain crops by Steiner et al. (1999).

The precipitation response was also normalised for [0, 1]. F(Pr)is set to 1 for precipitation >4 mm, which represents maximumwetness of surface residues (Steiner et al., 1994). The responsedeclines with precipitation divided by 4 for precipitation <4 mm.To include influence of the previous precipitation events in F(Pr),we assumed that half of the current F(Pr) value will be added to theF(Pr) for the following day, but still limiting F(Pr) to a maximumvalue of 1.

The pre-experiment history of the site was simulated usingobserved meteorological data (Table 1) and vegetation data (notshown) to achieve reasonable initialisation of the SOM model poolsat the starting point (the beginning of the soil tillage experiment).The calculations were performed in Excel 2000 using VBA (VisualBasic for Applications).

2.5.2. Soil C and GHG budget estimates

The soil CO2 respiration was measured over the bare soil.However, the soil C and GHG budgets for the system should includethe total soil–plant–atmosphere system, which is not included inthe CN-SIM model. Therefore, the FASSET soil–plant–atmosphere–management model was used for estimating the soil C and GHGbudgets using the parameterisation for conventional tillage basedon Berntsen et al. (2003, 2004, 2005).

The FASSET model, which applies a daily time step, simulates Nturnover and crop production as affected by daily weather andavailability of water and N (Olesen et al., 2002). Modelling of soilCO2 respiration and soil N2O emissions is based on Petersen et al.(2005a,b) and Chatskikh et al. (2005), respectively. To initialise theFASSET model pools, a seven-year pre-experiment history of thesite was simulated as suggested by Berntsen et al. (2004).

The estimated average d value for the DD topsoil was used in theFASSET model for the unploughed layers of all treatments. Themeasured soil water retention was used for CT and DD topsoil(Chatskikh and Olesen, 2007) and subsoil (not statisticallydifferent, thus data not shown). Because there was no measuredsoil water retention for the RT treatment, we used the one for CT.Furthermore, we assumed that the d value for the harrowed layerin RT was the same as for CT. The last assumption is based on thefact that the tillage depth in RT is approximately half that of CT.

Additional studies were performed for DD on effects on soil Cbudget and GHG emissions of (1) changed soil water retention byapplying the measured for CT water retention to DD, and (2)changed temperature by adding the measured difference in dailysoil temperatures between DD and CT to the air temperature.

Additionally, the effects on GHG emissions due to the estimateduncertainty in d were simulated for DD using the measured soilwater retention from CT. The climate effects on GHG emissionswere simulated by using the observed crop management data in2004 to 2005 and meteorological datasets covering the periodbetween 1976 and 2005 starting with different years.

The C and GHG budgets were calculated on an annual basis for theperiod from 01 August 2003 to 01 August 2005 and included soil Cinput (C input from manure and crop residues above- and below-ground including rhizodeposition) and soil C output (soil CO2

respiration) components. Further, change in soil C (calculated asdifference between soil C input and soil C output) and N2O emissionswere converted into CO2-equivalents based on GWPs (IPCC, 2007) toform CO2 and N2O soil GHG budgets, respectively, and the total GHGbudget was estimated as the sum of these two budgets.

2.6. Statistical analyses

An analysis of variance by the ANOVA procedures of the SASStatistical Analysis System (SAS Institute, 1999) was used toanalyse the measurements. Analyses of normality and variancehomogeneity showed no need for data transformations. Tocompare the means of the different treatments the S.E. (standarderror) and LSD (least significant difference) were calculated.

3. Results

Overall, the meteorological data showed that the measuringperiod was 0.8–0.9 8C warmer than the site climatological normal(Table 1). The difference in the measured daily mean soiltemperatures between CT and DD treatments at 5 cm depthvaried between �1.0 and +1.3 8C. On average, it was 0.2 8C lowerfor DD than for CT for May–July in 2003–2005. During themeasuring periods the soil water content was consistently lower inconventional treatment than in reduced soil tillage treatments(Figs. 1c to 4c).

3.1. Measured fluxes of CO2 and N2O

Large spatial (large S.E.) and temporal variations were observedin CO2 and N2O fluxes in the measuring periods (Figs. 1a,b to 4a,b).The average daily soil CO2 respiration was significantly higher forCT than for RT and DD treatments, whereas the N2O emissions didnot show consistent differences under CT and reduced tillagetreatments (Table 2).

Generally, ploughing (CT) significantly enhanced measured soilCO2 respiration compared to no-till (DD) during the entire season(Figs. 1a to 4a). Lower treatment-related mean daily soil CO2

respiration rates were observed under winter wheat compared towinter oilseed rape. The average mean daily soil CO2 respiration inreduced tillage (RT and DD) was, respectively, 29% and 38% lowerthan CT in the spring and 20% lower for both reduced tillagetreatments in the autumn.

Fig. 2. Measured (without correction for diurnal variation) mean soil surface fluxes

of CO2 (a) and N2O (b) and soil water content at 0–30 cm depth (c) for the different

tillage treatments (CT, conventional tillage; RT, reduced tillage; DD, direct drilling)

in spring 2004. Bars indicate S.E. (n = 4), and arrows indicate time of N applications

(N, 71 and N, 124) with doses in kg ha�1. Daily mean air temperature (line) and

precipitation (bars) for the site are shown at the bottom (d).




in autumn 2003. Bars indicate S.E. (n = 4), and arrows indicate time of harrowing

(HA), ploughing (PL) and sowing of winter oilseed rape (R). Daily mean air

temperature (line) and precipitation (bars) for the site are shown at the bottom (d).


As an average of observation periods, N2O emissions were in theorder CT > RT � DD. However, the emissions did not differsystematically between the soil tillage treatments in individualperiods (Table 2), e.g. there were higher N2O emissions from RTcompared with DD and CT in autumn after the sowing of winterwheat in 2004 (Fig. 3b; Table 2).

Table 2Mean daily soil CO2 respiration (kg CO2–C ha�1 day�1) and N2O (g N2O–N ha�1 day�1)

Treatment Observation period (days)

Autumn

CO2 N2O

Winter oilseed rape 2003–2004

August 15th–October 27th (74)

CT 89 (�10) 6.8 (�1

RT 82 (�12) 5.8 (�0

DD 73 (�3) 4.3 (�0

LSD 9 0.6

Winter wheat 2004–2005

September 16th–October 08th (23)

CT 44 (�13) 7.7 (�1

RT 26 (�7) 8.5 (�0

DD 34 (�6) 6.9 (�0

LSD 9 0.8

The gaseous fluxes were corrected for diurnal variation. LSD: least significant differenc

3.2. Crop yields and modelling of soil C budget, N2O emissions and

GHG budget

Overall, there was a tendency for CT to give the highest yieldswith the lowest variability, although in winter barley a slightlyhigher yield was observed in RT. For the three years in total there

emissions, observed during 4 studied periods

Spring

CO2 N2O

March 15th–May 15th (66)

.0) 71 (�7) 3.1 (�0.6)

.6) 55 (�7) 2.9 (�0.4)

.3) 50 (�1) 6.5 (�1.9)

5 1.4

March 30th–May 22nd (54)

.1) 70 (�18) 5.4 (�1.0)

.6) 45 (�10) 3.2 (�0.5)

.8) 37 (�4) 3.3 (�0.5)

10 0.7

e at 95% confidence. S.E. is shown is brackets.




in spring 2005. Bars indicate S.E. (n = 4), and arrows indicate time of N applications

(N, 72 and N, 100) with doses in kg ha�1. Daily mean air temperature (line) and

precipitation (bars) for the site are shown at the bottom (d).




in autumn 2004. Bars indicate S.E. (n = 4), and arrows indicate time of harrowing

(HA), ploughing (PL), sowing of winter wheat (W). Daily mean air temperature (line)

and precipitation (bars) for the site are shown at the bottom (d).


was no difference between CT and DD treatments in measuredharvestable C (Table 3).

Using these data as C inputs for the SOM model, the d value wasestimated at 0.57 (�0.15). This value refers to the average of the four

Table 3Measured C (Mg C ha�1 year�1) and N (kg N ha�1 year�1) in grain/seed (harvested) and

Treatments

CT

Winter barley 2002–2003

Harvested C 2.12 (�0.05)

Harvested N 91 (�6)

C in above-ground residue 2.44 (�0.11)

N in above-ground residue 43 (�9)

Winter oilseed rape 2003–2004





Winter wheat 2004–2005





LSD: Least significant difference at 95% confidence. S.E. is shown is brackets.

replicates and four periods (Table 2), and the value in brackets reflectsparameter uncertainty.

The C and GHG budget was simulated for two years (from 01August 2003 to 01 August 2005) using the FASSET model (Table 4).

in straw (above-ground residue) used for the modelling

LSD

RT DD

2.18 (�0.08) 1.83 (�0.24) 0.12

93 (�5) 80 (�12) 8

2.50 (�0.15) 2.26 (�0.25) 0.17

35 (�10) 41 (�2) 7

1.90 (�0.15) 2.10 (�0.11) 0.12

121 (�10) 138 (�7) 8

4.26 (�0.34) 4.16 (�0.41) 0.34

65 (�9) 72 (�12) 9

3.63 (�0.11) 3.74 (�0.11) 0.10

141 (�9) 159 (�12) 10

4.96 (�0.50) 4.94 (�0.56) 0.47

71 (�7) 69 (�11) 8

Table 4Simulated soil C and GHG budget (net emissions) from 01 August 2003 to 01 August 2005 using the FASSET model

Treatments

CT RT DD DD* DD**

Harvested C (grain/seed) 2.73 2.69 2.59 2.60 (�0.08) 2.58

Soil C budget (Mg C ha�1 year�1)

Soil C input

C in above-ground residue 3.05 3.05 3.01 3.01 (�0.05) 3.02

C in below-ground residue, including rhizodeposition 2.14 2.11 2.05 2.05 (�0.05) 2.06

Manure 0.21 0.21 0.21 0.21 0.21

Soil C output

Soil CO2 respiration 4.40 4.28 3.95 3.95 (�0.28) 3.93

Change in soil C (Soil C input–soil C output) 1.00 1.09 1.32 1.32 (�0.19) 1.36

Soil N2O emissions (kg N2O–N ha�1 year�1) 3.81 3.32 2.40 2.81 (�0.32) 2.37

Soil GHG budget (GWP, Mg CO2-eq. ha�1 year�1)

CO2 budget �3.67 �4.00 �4.84 �4.84 �4.98

N2O budget 1.78 1.55 1.12 1.32 1.11

Total GHG budget �1.88 �2.44 �3.72 �3.52 �3.88

* The same water retention as for CT was used. Parameter’s uncertainty due to the estimated d value shown in brackets.** The measured difference in soil temperature between CT and DD was used.


The model captured relative differences in both harvested grainand seed (Obs = 0.22 + 0.97 � Sim; R2 = 0.93) and in above-groundC (Obs = 0.13 + 1.00 � Sim; R2 = 0.89). As an average for the twoyears, relative differences between CT and DD in modelledharvested C were the same as in the measured data (Table 4 vs.Table 3). However, the average harvested yields were under-estimated in both treatments by 11%, whereas C in above-groundresidues was underestimated only in DD. Nevertheless, there wereonly small differences in simulated vs. measured harvestable C(5.8 Mg C ha�1 vs. 5.9 Mg C ha�1 and 5.6 Mg C ha�1 vs. 6.1 MgC ha�1 for CT and DD, respectively).

The FASSET model captured a large part of the measuredvariation in N2O emissions (Fig. 5), which were cumulated on aweekly basis to decrease the daily weather and spatial variationeffects (Chatskikh et al., 2005; Chatskikh and Olesen, 2007).Calculated according to Berntsen et al. (2006b), the RMSE(g N ha�1 week�1) showed that simulated emissions agreed wellwith observations (14 (CT), 11 (RT) and 17 (DD)), while themodelling efficiency (EF) showed that the FASSET model described

Fig. 5. Simulated vs. observed N2O emissions cumulated on weekly basis for the

different tillage treatments (CT, conventional tillage; RT, reduced tillage; DD, direct

drilling). Bars indicate S.E. (n = 4) for observed data.

the emissions significantly better than a mean value (0.77 (CT),0.81 (RT) and 0.67 (DD)). However, the model underestimated thehighest fluxes, especially after manure application. The possiblereasons for this are discussed in Chatskikh et al. (2005).

Both measured data (Table 2) and simulations (not shown)showed that mean daily N2O emissions from CT and RT werehigher in 2004–2005 than in 2003–2004. Since measured CO2 andN2O fluxes were not available for the entire period andmeasurements of soil CO2 respiration were performed on baresoil (not in the crop), only tendencies could be derived fromTables 2 and 4. The trends in overall cumulated CO2 and N2Oemissions were found to decrease in order CT > RT > DD in bothsimulated and observed data. However, the simulated resultsshowed much higher N2O emissions from CT than for reducedtillage treatments, while there were much smaller differences inthe measured N2O fluxes (13–37% vs. 9–11%). The opposite picturewas found for soil CO2 respiration (3–10% vs. 24–30%). Suchdifferences between simulated and measured emissions maypartly be explained by the fact that some non-fertilised periodswere not included in measurements.

Soil CO2 respiration levels lower than total C input in 2003–2005 resulted in a simulated build-up of soil organic C for alltreatments (Table 4). Net C sequestration was larger in the RT andDD treatments than in CT with additional 0.09 and0.32 Mg C ha�1 year�1, respectively.

Using a 30-year meteorological data series (1976–2005) forsimulations instead of data from the measuring period only, onaverage resulted in a smaller increase in soil C sequestration.However, simulated N2O emissions were higher for the 30-yearmeteorological data series (compare net emissions in Tables 4 and 5).

In the simulated GHG budget for CT, the GWP of soil Csequestration was almost double that of the N2O emissions

Table 5Simulated soil C and GHG budget (net emissions) as averaged for a 30-year

meteorological data series (1976–2005) using the FASSET model

Treatments

CT RT DD

GHG budget (GWP, Mg CO2-eq. ha�1 year�1)

CO2 budget �2.79 �3.12 �3.97

N2O budget 2.30 2.10 1.55

Total GHG budget �0.49 �1.02 �2.42


(Table 4). For RT total GHG emissions were reduced by0.56 Mg CO2-eq. ha�1 year�1 compared with CT, and the DDtreatment resulted in additional GHG emission reductions of1.28 Mg CO2-eq. ha�1 year�1. For both reduced tillage treatmentsCO2 budget played a major role in total GHG budget. Also as anaverage over the 30-year series total GHG emissions declined inthe order CT > RT > DD, and the differences between the treat-ments remained similar to the original meteorological data(Tables 4 and 5).

The simulated effects of the DD treatment in Table 4 resultedfrom changes in both SOM turnover (with changing values of d) andsoil water retention characteristics. Using the same soil waterretention in DD as in CT did not change the GHG balancedramatically, but N2O emissions increased to a level in between RTand DD. Applying the measured differences between CT and DDsoil temperatures in DD** (Table 4) gave a small reduction insimulated emissions of both CO2 and N2O. The effect of varying d-values within the uncertainty range was more pronounced forchange in soil C than for soil N2O emissions (Table 4).

4. Discussion

4.1. Measured and modelled CO2 and N2O emissions

Both modelled and measured fluxes in the present studyshowed that the reduced soil tillage practices (RT and DD)significantly decreased soil CO2 respiration compared to CT.Similar results were also found by Bauer et al. (2006).

Our averageCO2 flux (69,52and49 kg C ha�1 day�1 forCT, RTandDD, respectively) was in accordance with other studies (e.g. Jensenet al., 1996; Janssens et al., 2000; Pumpanen et al., 2004). However, itwas somewhat higher than in other soil tillage experiments, e.g.24 kg C ha�1 day�1 (Ball et al., 1999), 7–39 kg C ha�1 day�1

(Kessavalou et al., 1998) and 11 kg C ha�1 day�1 (Kabwe et al.,2005). Eriksen and Jensen (2001) found average soil surface CO2

fluxes of 18 to 35 kg C ha�1 day�1 depending on tillage intensity ingrassland located close to our experimental site. These values arecomparable to those from the reduced tillage treatments underwinter wheat. The reason for the high average fluxes in the presentstudy is uncertain, but the use of small chambers may in comparisonwith other systems systematically overestimate flux rates (Janssenset al., 2000; Pumpanen et al., 2004). Indeed, Jensen et al. (1996)observed large differences between static and dynamic chambers onanother site in Denmark, with dramatic overestimations for thehighest CO2 peaks, possibly related to a high spatial variation. Thuswe chose to compare soil CO2 respiration across soil tillagetreatments in terms of relative differences instead of using widelyrecommended adjustment factors for dynamic chambers.

Still, our measurements of soil CO2 respiration (Figs. 1–4;Table 2) corresponded well with those by Bauer et al. (2006) interms of giving larger differences between conventional andreduced tillage in spring than in autumn. The lower soil CO2

respiration in DD than CT (Figs. 1a to 4a; Table 2) mirrored ourearlier findings for spring barley in the same experiment(Chatskikh and Olesen, 2007). Our results are also consistent withthe on average 33% difference between conventional and reducedtillage management measured by Bauer et al. (2006) and the 27%between conventional and fallow tillage practice measured byKessavalou et al. (1998). Ball et al. (1999) attributed suchdifferences in soil respiration to higher water-filled pore spacevalues in the no-till treatments compared with the tilled, resultingin a lower oxygen availability in the no-till treatments.

The results did not show a pronounced increase in N2Oemissions from no-till, which accords with the findings ofKessavalou et al. (1998) and Liu et al. (2004). There were

significantly higher mean daily N2O emissions in autumn thanin spring irrespective of tillage treatment, except in spring 2004 forDD (Table 2). This is unexpected, since N application usually leadsto increased N2O fluxes during the following period (Bouwmanet al., 2002; Kaiser et al., 1998). However, in our experiment, whereN was only applied in spring, the high N uptake capacity of thewinter crops (Table 3) may have reduced soil mineral N and thusthe sources for N2O emissions. Higher N2O emissions wereobserved from spring barley than from winter oilseed rape inthe same experimental year (Chatskikh and Olesen, 2007).Similarly, Ball et al. (1999) and Skiba et al. (2002) reported highermeasured N2O emissions from spring barley as compared to winterbarley.

We found significant differences in N2O effluxes betweentillage treatments. However, the effects varied between the fourperiods, and no overall consistent picture could be drawn(Table 2). Kessavalou et al. (1998) similarly found that one yearproduced only marginal differences between tillage treatments inN2O emissions, while in the following year significantly higheremissions were observed for ploughed than for no-tilled sites.Some studies involving only one year of observations havereported significant effects of tillage on N2O emissions, albeit indifferent directions (e.g. Skiba et al., 2002 vs. Chatskikh andOlesen, 2007). This indicates that tillage effects on N2O emissionsmay be highly dependent on local climate, soil and managementconditions.

Direct effects of tillage management on soil microbiology weremeasured in the present crop rotation during autumn 2003 (Olesenet al., 2005). Enzyme activities (arylsulfatase) and microbialbiomass indicators (dehydrogenase activity) were rather stablebefore and after tillage treatments (within 12% and 5%, respec-tively). So, these parameters could not explain treatmentdifferences in GHG emissions. Yet, assays of potential ammo-nium-oxidation indicated that CT reduced the activity of ammo-nium-oxidizing bacteria by 20%, thus potentially affecting Ncycling in the soil (Olesen et al., 2005).

The estimated d value of 0.57 for DD means that decompositionand maintenance for all SOM pools in the model were reduced by43%. Our ‘‘tillage factor’’ d value is similar to the so-called clteff’

values (multipliers for cultivation’s effect on decomposition) usedby Leite et al. (2004) for active and passive SOM pools in amodelling study with the Century model on Brazilian grasslandsconverted to reduced tillage. Our d value resulted in simulated soilrespiration reductions of only 11% in DD compared to CT (Table 4).Oorts et al. (2007) also reported relatively low decay rates in no-tillthat were 8–9% smaller than in conventional tillage.

In this study both decomposition and maintenance parameterswere multiplied by the d value, and since there are different effectson C balance of changing these parameters, depending on modelpool (Petersen et al., 2002), this partly explains the small responseof soil CO2 respiration to the parameter changes. Another reason isrelated to the different effects of parameter changes on theturnover of the various SOM pools with a higher response of theslow compared to the fast pools within the study period (Leiteet al., 2004; Oorts et al., 2007).

In accordance with earlier studies (e.g. Kessavalou et al., 1998),we found consistently higher volumetric soil water contents underreduced tillage treatments compared to CT. However, this does notappear to have consistently stimulated N2O emissions or CO2

respiration in our experiment or in other studies (e.g. Burford et al.,1981; Aulakh et al., 1984). These effects were supported by themodelling study, when differences in soil water retention had beenincluded along with differences in SOM turnover rates (DD* vs. DDin Table 4). Soil temperature differences between tillage treat-ments are usually ignored as a determining factor for GHG


emissions, even though cooler soil temperatures are typicallyobserved in spring in no-till (e.g. Kessavalou et al., 1998). Thesensitivity analyses in Table 4 showed that changes in the SOMmodel parameters gave the largest effects on GHG emissions.Changes in soil water retention also influenced emissions, inparticular of N2O, even considering the uncertainty in the d value,whereas soil temperature effects were minor.

4.2. The C and GHG budget

The modelled difference in change of total soil C between DD andCT of 0.32 Mg C ha�1 year�1 is in line with an average C sequestra-tion rates of ca. 0.2–0.4 Mg C ha�1 year�1 found by Six et al. (2002)and slightly higher than the rates reported by West and Post (2002)and by Robertson et al. (2000). Furthermore, Six et al. (2004)reported a much higher uncertainty for N2O emissions along withmore or less consistent C sequestration of ca. 0.2 Mg C ha�1 year�1

over a 20-year-period. These uncertainties in both CO2 and N2Oemissions are comparable to modelled differences between experi-mental years and estimated for the 30-year meteorological series(Table 5 vs. Table 4). Thus, it could be concluded that climaticvariability influenced modelled soil C budgets less than N2Oemissions, which may partly have been due to interannualdifferences in rainfall patterns (Table 1; Figs. 1d–4d).

The simulated impact of GHG emissions on GWP changedconsiderably with soil tillage practice. This was due to, equally,reductions in soil CO2 respiration and N2O emissions. Simulateddifferences in total GWP emissions of 0.56 (CT-RT) and 1.84 (CT-DD) Mg CO2-eq. ha�1 year�1 are in accordance with the currentlyestimated levels presented by Six et al. (2004) and Robertson et al.(2000).

Some long-term tillage experiments and modelling studieshave shown that differences in C sequestration constitute the maindifference in GWP for changes in soil tillage (Robertson et al., 2000;Grant et al., 2004). It should be noted that our experiment wasnewly established and thus the results obtained cover mostlyshort-term effects. To extend the results to the long-term, theestimated benefits of reduced tillage on GHG emissions could beoffset by an increased soil C pool, which may, in fact, stimulate N2Oemissions (Grant et al., 2004; Li et al., 2005). On the other hand, Sixet al. (2002) presented summarised datasets for temperateclimates, which indicate that N2O emissions could be larger fromno-tillage compared with conventional tillage during the firstyears after conversion, but this difference was reduced and evenreverted in the longer term. Apart from the different explanation ofthe results obtained either by meta-analysis or by modelling, theglobal warming potential estimation is still highly uncertain.Improvements in estimations of N2O emissions, the most dynamicpart of the GHG budget, are limited mostly by uncertainties due tospatial and temporal variability (Bouwman, 1990), which suffergreatly from the absence of proper knowledge of the mechanismsconnecting N2O production and emission sites. Freibauer et al.(2004) thus reported a level of uncertainty in estimating potentialC sequestration rates well in excess of 50%.

5. Conclusions

The study showed smaller soil CO2 respiration for direct drillingcompared with mouldboard ploughing (CT) and large interannualvariability in effects on N2O emissions in typical Danish soil andclimatic conditions. The estimated net GHG budget was lower inreduced tillage treatments (RT and DD) compared to conventionaltillage, and was generally affected by differences in both soil CO2

respiration and N2O emissions. The tillage effects on CO2 and N2Oemissions were estimated to be mediated by changes in SOM

turnover and soil water retention. The variability in the emissionsby crop and year could be partly explained by year-to-yearvariation in climatic and management conditions through effectson C input, SOM turnover and the soil environment. The use of a‘‘tillage factor’’ for scaling modelled soil turnover processes underreduced and no-tillage appeared to capture observed relativedifferences in GHG emissions.

Acknowledgements

This work was supported by the Danish Ministry of Food,Agriculture and Fisheries under the research program ‘‘Agriculturefrom a holistic resource perspective’’ and by the InternationalResearch School of Water Resources (FIVA). We thank JørgenBerntsen, Finn P. Vinther, Per Schjønning, Lars Munkholm, FinnHenning Christensen, Lars Andreasen, David Croft, Per Drøscher,Flemming Steffensen, Stig T. B. Rasmussen, Bodil B. Christensenand Margit Agerholm Schacht for valuable professional assistance.We are much obliged to Per Ambus from the Risø NationalLaboratory for providing help with N2O analysis in spring-summer2005 and to Liselotte Meltofte who made those analyses.

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