Changes in CO2 emissions after crop conversion from continuous maize to alfalfa

Giorgio Alberti a,*, Gemini Delle Vedove a, Michel Zuliani a, Alessandro Peressotti a,Simona Castaldi b, Giuseppe Zerbi a

a Department of Agriculture and Environmental Sciences, University of Udine, via delle Scienze 208, 33100 Udine, Italyb Department of Environmental Sciences, Second University of Naples, via Vivaldi 43, 81100 Caserta, Italy

Agriculture, Ecosystems and Environment 136 (2010) 139–147

A R T I C L E I N F O

Article history:

Received 25 August 2009

Received in revised form 9 December 2009

Accepted 11 December 2009

Available online 6 January 2010

Keywords:

Maize

Alfalfa

NEP

NBP

C cycle

A B S T R A C T

Mitigation strategies for the reduction of carbon dioxide emissions are the central focus of the Kyoto

Protocol and international scientific efforts. Agriculture plays a substantial role in the balance of the most

significant greenhouse gases (CO2, N2O, CH4), mostly attributed to management practices. In this study,

we present data on the effects of a conversion from a cropland (Zea mays L.) to N2-fixing grassland

(Medicago sativa L.) on C cycle in an agricultural area of Northern Italy. Net ecosystem production (NEP)

and net biome production (NBP) have been followed for 2 years by mesuring CO2 fluxes by paired eddy

covariance stations (EC) and continuous soil respiration measurements (SR). Root exclusion subplot

replicates were also used to estimate heterotrophic respiration (Rh). The comparison between the net

primary production (NPP) inventory estimation and NPP based on measured CO2 fluxes (EC and Rh)

showed excellent agreement for both land uses. An increase in NEP was observed 2 years after

conversion from corn to alfalfa (+281 g C m�2), however, in terms of NBP, maize was a lower source of C

(�96 g C m�2) than alfalfa (�354 g C m�2). From the present study, it appears that this type of land

conversion is not an effective measure of C sequestration in the short term (1–3 years).

� 2009 Elsevier B.V. All rights reserved.

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1. Introduction

Management strategies to increase the carbon sink of agriculturalsoils have gained great importance since the Kyoto Protocol wassigned in 1997. Croplands represent about 12% of the earth’s surface(Wood et al., 2000) and can have equal or greater net ecosystemproduction (NEP) than several natural ecosystems (Law et al., 2002;Hollinger et al., 2004). An important consequence often associatedwith the conversion of native ecosystems to croplands is thereduction of soil organic carbon (SOC) (Houghton et al., 1983).Therefore, different agronomic strategies have been suggested andtested in order to reduce CO2 emissions and increase SOC. Thesemeasures include the conversion of arable land to perennial foragecrops and the implementation of crop management practices, suchas the elimination of tillage and the introduction of rotations basedon N2-fixing plants (Lal and Bruce, 1999; Lal et al., 1999; Lal, 2002).For example, the conversion from mouldboard ploughing to no-tillwas found to increase the C sink up to 57� 14 g C m�2 y�1 (West andPost, 2002). Similarly, when continuous maize crops are converted tograsslands, an increase of soil C storage between 0.5 and1.0 t C ha�1 y�1 was reported by IPCC (2000), calculated over 50 years.Although several studies investigated changes in soil carbon stocks

* Corresponding author. Tel.: +39 0432 558608; fax: +39 0432 558603.

E-mail address: alberti@uniud.it (G. Alberti).

0167-8809/$ – see front matter � 2009 Elsevier B.V. All rights reserved.

doi:10.1016/j.agee.2009.12.012

associated with changes in crop management or in land use (Deen andKataki, 2003; Su, 2007), limited information exists regarding thepotential of C sequestration of high yield maize under differentmanagement options (i.e. Robertson et al., 2000). Also lacking are short-term studies examining C losses/gains associated with the conversionof maize crops to alfalfa.

Two parameters are particularly important when a compre-hensive C balance for agro-ecosystem is performed. The first is netbiome production (NBP), which is a measure of C storage in theecosystem and also accounts for carbon losses, due to harvestmaterial (Anthoni et al., 2004). The second is net ecosystemexchange of carbon (NEE) which expresses the potential of eachagro-ecosystem to fix C or to release C by both autotrophic andheterotrophic respiration. The traditional way of addressing netcarbon exchange of an ecosystem over multiple years involvesquantifying temporal changes in biomass and soil carbon.However, changes in soil organic matter become apparent afterdecades rather than years and thus soil sampling techniques doesnot allow going insight changes in the short term. The eddycovariance technique has been used widely to determine NEE(Baldocchi, 2003) because it is scale appropriate and provides amethod to assess net CO2 exchange at ecosystem level, it producesa direct measure of net ecosystem exchange (NEE), it is able tomeasure ecosystem CO2 exchange across a spectrum of timescalesand the area sampled by this technique (footprint) range betweenhundred meters to several kilometres. This technique has been

G. Alberti et al. / Agriculture, Ecosystems and Environment 136 (2010) 139–147140

used in agriculture to investigate the effects of irrigation on grossprimary production (GPP) (Suyker et al., 2004), to quantify themagnitude of the storage terms on the surface energy balance(Meyers and Hollinger, 2004), to quantify dynamics of the Bowenratio (Baker et al., 1999), and to assess the influence of differentagricultural management strategies (Baker and Griffis, 2005;Hollinger et al., 2004; Ammann et al., 2007). Due to highbackground SOC stocks and high spatial heterogeneity (Don et al.,2007), the eddy covariance technique is a superior tool formeasuring short-term C gains/losses during the first years afterland use change when compared with SOC stock inventories.

At present, there are few studies where a complete ecosystemapproach (NBP, NEE, soil respiration, soil C storage) is used toquantify the net C gains/losses resulting from land conversion inagro-ecosystems. In this study, a full C balance approach was usedto investigate short-term effects (2 years) of land conversion fromcontinuous maize (Zea mays L.) to alfalfa (Medicago sativa L.) onNEE and NBP. NEE was evaluated using a micrometeorologicalapproach based on simultaneous (paired) eddy flux measurementscoupled with continuous heterotrophic respiration measurements.In order to validate NPP data obtained with these techniques (eddyNEE + heterotrophic respiration measurements), periodic growthanalysis were also carried out to estimate total biomass (above-and below-ground). The specific objectives of this study were: (i) toquantify the net gains/losses of C due to the land use change bycomparing the total NEP and NBP in the two crops, (ii) to comparetwo different approaches of estimating net primary production(NPP), that of growth analysis and combined data of eddycovariance versus automated soil respiration.

2. Materials and methods

2.1. Site description

An agricultural field of 13.3 ha was selected N–E Italy (468000 N138010 E) in the late fall of 2006. In this field, irrigated maize (Zea

mays L.) was cultivated during the last 30 years and the soil wastilled using a winter plow to a depth of 0.35 m and a spring soilpreparation (5 cm) prior to sowing. A quite constant high yield(10–11 Mg ha�1 dry matter) was achieved using a sprinklerirrigation system and adding chemical fertilizers used in accor-dance with standard practices.

Soil can be classified as a Chromi-Endoskeletic Cambisol (FAO,2006) with the following characteristics in the 0–30 cm horizon:total SOC = 48.4 � 8.5 t C ha�1, total N = 4.2 � 1.1 t N ha�1, soil bulk

Table 1Crop management details, grain and grass yields for the two land uses during 2007 (C

biomass) (�standard deviation).

Site Year Tillage date Planting date

C–C 2007 December 15, 2006 April 4

2008 December 12, 2007 April 4

C–A 2007 February 21, 2007 March 2

2008

density = 1.25 � 0.15 g cm�3, soil field capacity = 23% v/v, wiltingpoint = 12% v/v and pH = 7.1 � 0.02.

At the beginning of the experiment (December 2006) the studyarea was divided into two sections so to obtain an eastern area of8.6 ha and a western area of 4.7 ha. Maize was cultivated in the Eastfield using similar management practices described above in 2007and 2008 (thereafter continuous–corn, C–C). At sowing (72,000seeds ha�1 and 74,000 seeds ha�1 in 2007 and 2008, respectively),54 kg ha�1 N were added to the soil as (NH4)2SO4 in both the yearsand 205 kg ha�1 N were added on April 2007 as (NH4)2HPO4 and359 kg ha�1 N were added on May 2008 as Urea. Instead, the Westfield was converted to fodder alfalfa (Medicago sativa L.), with a latewinter (February 2007) plowing at 0.35 m (thereafter corn–alfalfa,C–A). At sowing, 39 kg ha�1 of seeds were used. No N fertilizationwas performed in C–A. Weed control was performed on C–C usingisoxaflutole 75%, terbutylazine and dimethenamide.

For each crop (maize and alfalfa), three replicates (10 � 10 m)were established to study C dynamics, crop growth, biomasspartitioning and soil respiration. The main management opera-tions for the C–C and C–A plots are reported in Table 1 and thedifferences in terms of water and nutrient (i.e. nitrogen) supplieswere typical for the two different crops.

2.2. Environmental measurements

A weather station was placed in each field and equipped tomeasure soil temperature at three depths using thermocouples (5,15 and 25 cm), soil water content (0–20 cm), using three (time)domain reflectometers (TDR CS616, Campbell Scientific, Logan,UT), incoming and outcoming short wave radiation (CMP3, Kippand Zonen), incoming long wave radiation (CG3, Kipp and Zonen),incoming and outcoming photo flux density (PPFD, LI-190SLquantum sensor, LiCor, Lincoln, NE), net radiation (NR-LITE, Kippand Zonen), air temperature and humidity (HMP45AC, Vaisala),soil heat flux (5 and 15 cm) using four soil heat flux plates(Marlow) and precipitation.

To obtain corrected surface values of soil heat flux (QG), heatstorage between soil surface and the depth of the plate (S) was addedto the measured flux (QGm) (Ochsner et al., 2007; Cava et al., 2008):

QG ¼ QGm þ S (1)

The ground heat storage is expressed by the equation:

S ¼Z z¼zd

s¼0cv

dT

dtdz (2)

–C = maize cropland; C–A = forage crop; grain and grass yields are reported as dry

Harvest date Applied N

(kg N ha�1)

Maize or alfalfa

yield (Mg ha�1)

September 6 259 11.0�0.6

September 25 413 9.2�0.8

May 21 – 4.50�0.83

June 18 – 4.36�0.37

July 17 – 3.47�0.35

August 17 – 3.13�0.26

October 1 – 2.51�0.08

Total 18.0�1.0

May 6 – 2.61�0.32

June 19 – 3.22�0.09

July 15 – 4.78�0.13

August 6 – 2.23�0.20

September 9 – 1.33�0.15

October 20 – 0.79�0.08

Total 15.0�0.44

G. Alberti et al. / Agriculture, Ecosystems and Environment 136 (2010) 139–147 141

where cv is the volumetric heat capacity of the soil, zd is the depthof the buried plate (5 cm), dT is the change in soil temperature at2.5 cm in the half hour interval (dt).

All variables were measured at 0.1 Hz and then averaged half-hourly.

2.3. Eddy covariance measurements

An eddy covariance flux tower was installed in August 2006 ineach field (C–C and C–A) to assess mass, momentum and energyecosystem exchanges. The measurement height was 2.5 m fromthe ground for C–A and from 2.5 m up to 4.5 m for C–C dependingon the canopy height during the year. Each eddy covariance systemhad a sonic anemometer (Young, USA) and an open path infraredgas analyser (Li-7500, Licor, USA). The Li-7500 was pointedtowards the north by an angle of 208 to minimise solar radiationinfluence and to facilitate the shedding of water droplets from thesensor lenses after rain events. Data from the sonic anemometerand the open path IRGA were recorded at a frequency of 20 Hz(Matese et al., 2008). Ecosystem fluxes of CO2, momentum,sensible (H) and latent heat (LE) were averaged on a half-hourlybase. The applied methodology was based on the Euroflux protocol(Aubinet et al., 2000) with the Webb Pearman Leuning correction(WPL; Webb et al., 1980) and Burba et al. (2008) correction for LI-7500 heat exchange (method 4). All the post-processing elabora-tions and frequency response corrections have been performedusing EdiRe Data software (University of Edinburgh, 1999) andquality assessment and quality check analysis (QA/QC) wereconducted according to Foken and Wichura (1996). As well-known, open path IRGA provides inadequate and erroneous dataduring rainy or foggy conditions, or when water condensationoccurs on the instrument optical lens, especially in autumn.Typically, the malfunctioning of IRGA, in such conditions, causesthe occurrence of spikes, and in this case a spike analysis algorithmis applied to accept or discard data, before the QA/QC analysis.Finally, to eliminate the influence of a nearby farm, fluxes at C–Awere excluded with wind direction in the range 180–3608,although fluxes from the excluded wind directions may still partlyderive from C–A. This was a conservative means to restrict thesource area to C–A and exclude all the other land use types. Toassume comparability of fluxes from both the sites, data from 1808to 3608 wind directions were also excluded at the C–C site.

A gap-filling procedure was applied to obtain daily fluxes(Reichstein et al., 2005; http://gaia.agraria.unitus.it/database/eddyproc/index.html) when the QA/QC criteria were not satisfiedand when a lack of turbulent transport was evidenced by the data.The partitioning of NEE between gross primary productivity (GPP)and total ecosystem respiration (TER) was also performedaccording to Reichstein et al., 2005.

2.4. Footprint analysis

Footprint analysis was performed using the approach proposedby Gockede et al. (2008) and developed to produce a flux qualityevaluation for meteorological measurement sites in complexterrain. A matrix representing different land uses at our site wasproduced and roughness lengths, wind speed and direction,Obukhov length for each 30 min time step were used in themodel to compute the contribution of each land use type to themeasured flux. More details about this type of footprint analysiscan be found in Gockede et al. (2004, 2008). To analyze results, weidentified the following classes:

- h

omogeneous measurements: 95% or more of the flux is emittedby the specified target land cover type. Systematic bias by fluxcontributions from other land cover types is negligible.

- r

epresentative measurements: 80–95% of the flux is emitted bythe target land cover type. We chose the 80%-threshold to limitpossible disturbing influences of non-target land cover types onthe measured fluxes to a low level.

- a

cceptable measurements: 50–80% flux contribution is emittedby the target land cover type.

- d

isturbed measurements. Less than 50% flux contribution fromthe target land cover type.

2.5. Soil respiration measurements

Continuous soil respiration measurements were performedevery 2 h using three automated soil respiration systems. A detaileddescription of the system is reported in Delle Vedove et al. (2007).Briefly, each system was a closed dynamic system according toLivingston and Hutchinson (1995) and operated twelve automatedsoil respiration chambers. Each chamber consisted of a steel collar(20 cm of diameter and 8 cm height) and a DC motor closing a steellid. This was positioned to end up on the North side of the collarwhen was open in vertical position, so to avoid shadowing of thechamber. During the operation, air was circulated between the soilchamber and the infrared gas analyzer (IRGA, SBA-4, PP-System), at aconstant flow rate (0.5 l min�1). The system used the rate of increaseof CO2 within each chamber to estimate, by an empirical diffusionmodel, the gas efflux (mmol m�2 s�1).

Three chambers were placed in each replicate: two chamberswere used to estimate total soil respiration and one was used toestimate heterotrophic respiration (Rh) on a root exclusionsubplot. Soil below this last chamber was isolated with a rootexclusion stainless-steel cylinder opened on both ends (32 cmdiameter, 40 cm height). The steel cylinders were placed in thefield after sowing. Soil CO2 flux was measured every 2 h.

2.6. Growth analysis

The above- and below-ground dry biomass and leaf area index(LAI), in the maize field, were measured three times during thegrowing season by destructive sampling. Dry weight of each plantcomponent (foliage, stem, roots, cob) was determined after oven-drying at 70 8C for 48 h. Root biomass was measured up to 30 cmdepth. Furthermore, on ten sampled plants and on ten not-harvested plants selected in each maize plot, the followingvariables were measured five times during the growing season:basal diameter (D), total height (H), minimum and maximumdiameter (Dmin and Dmax) and length of each ear (Ls). Usingallometric regression models between the above mentionedvariables and the dry weight measured on the ten harvestedplants, it was possible to estimate crop biomass and LAI. Grainyield, for each plot, was determined by harvesting an inner area of36 m2 on each plot at the end of the growing season. Crop residuesafter harvest were estimated on three 1 m2 subplots for each plot.

Above-ground biomass of alfalfa was measured by destructivesampling, on an area of 0.03 m2, for each plot, three times beforethe first harvest and six times thereafter. Leaf area and specific leafarea were determined on sub-samples of plants, in order toestimate LAI. At the end of November 2007, a soil profile trenchwas opened down to 30 cm depth, for each plot, to estimate totalroot biomass and root to shoot ratio (R:S).

Maize and alfalfa yields were assessed by measuring fresh weighton 32 m2 for each replicate at each harvest. The moisture contentwas determined on a sub-sample, oven-dried at 70 8C for 48 h.

Root biomass was derived multiplying total above-ground NPP(standing biomass + harvested material) by R:S.

Carbon and nitrogen content, for each plant component ofmaize and alfalfa, were determined using a CHN ElementalAnalyzer (NA1500 Series 2, Carlo Erba Instruments, Rodano, Italy).

G. Alberti et al. / Agriculture, Ecosystems and Environment 136 (2010) 139–147142

2.7. Overall carbon budget

Assuming that the C removed as harvested material has arelative short life, net biome production (NBP) of the ecosystemcan be calculated according to Anthoni et al. (2004) as

NBP ¼ annual NEP� Ch

where ‘‘annual NEP’’ is annual net ecosystem production (it isequal and opposite in sign to annual NEE measured using EC)and Ch is the amount of the carbon removed with harvestedbiomass (yield).

3. Results

Air and soil temperature, precipitation, irrigation and soil watercontent (SWC) are reported in Fig. 1. SWC was maintained close thefield capacity throughout the growing season by sprinklerirrigation. The peak leaf area index was 4.1 and 8.8 for C–C andC–A, respectively. Maize yields were 11.0 � 0.57 Mg ha�1 and9.2 � 0.80 Mg ha�1 of dry matter in 2007 and 2008, respectively.The C–A yields were 18.0 � 1.0 and 15.0 � 0.4 Mg ha�1 of dry matter(sum of five harvests in 2007 and six harvests in 2008; Table 1).

The majority of the 30-min flux measurements analyzed in thisstudy were emitted from the specified target crop type (maize oralfalfa) for both the eddy covariance stations (flux contribution of a

Fig. 1. Monthly mean values of air temperature (Ta at 2 m; solid line) and monthly rainfa

solid line) and irrigation (vertical bars) for C–C (panel B) and C–A (panel C).

30-min averaged flux >50%). If only wind sectors below 1808 areconsidered (see Section 2), more than 90% and 99% of half hour datawere emitted from the specified target for C–C and C–A,respectively (Table 2). Furthermore, a good agreement was foundbetween energy fluxes measured at the eddy station and energybalance, calculated at the weather stations using net radiationand soil heat fluxes, for both treatments (C–C: slope = 0.88,intercept = 23.2, R2 = 0.83; C–A: slope = 0.83, intercept = 10.6,R2 = 0.97).

Daily Net Ecosystem Exchange (NEE) values relative to thewhole study period (December 2006–November 2008) werecomputed for both land uses and the time series graphs of carbonfluxes from C–C and C–A (Fig. 2) clearly show the difference of C3and C4 net production rates. The C4 crop (maize) had a maximumrate of net C uptake of 18.1 g C m�2 day�1, while the C3 crop(alfalfa) had a maximum net uptake of 10.8 g C m�2 day�1. C–Cshowed the same trend in daily NEE during both growing seasonbut the maximum daily C uptake was less the second year probablybecause a different maize variety was sown. The differencebetween C–C and C–A was particularly evident in spring, when thealfalfa crop stored more C because of its earlier growth, and fromAugust thereafter, because of the earlier maize senescence (Fig. 3).As a consequence, on a yearly basis, C–A showed a higher NEE thanC–C in both the years (Table 3; Fig. 4), although the difference wassmaller in the second year. Even though C–A had a higher albedo

ll (vertical bars) (panel A); monthly mean soil water content (at 0.00–0.15 m depth;

Fig. 2. Daily net ecosystem exchange (NEE; solid symbols) measured using eddy covariance technique and heterotrophic respiration (open symbols) measured using

automated soil respiration chamber on root exclusion subplots for C–C (A) and C–A (B). Vertical bars indicate standard deviation for soil respiration (n = 3).

Table 3Carbon balance components for the C–C and C–A fields (�standard deviation where computed, n = 3).

Year Site NEP (�NEE)a g C m�2 Rhb g C m�2 Chc g C m�2 NBPd g C m�2

2007 C–C 473 613�14 484�25 �11

C–A 616 584�7 793�45 �177

2008 C–C 343 601�18 428�26 �85

C–A 481 495�14 658�38 �177

Total C–C 816 1214�23 912�36 �96

C–A 1097 1079�15 1451�59 �354

a NEP = Net Ecosystem Production; NEE = Net Ecosystem Exchange.b Rh = heterotrophic respiration.c Ch = harvest material.d NBP = Net Biome Production.

Table 2Representativeness results for the specified target land cover type: values indicate the percentage of 30-min measurements for each site that fall within the wind sector and

within each of the three categories shown by wind sector (C–C = maize cropland; C–A = forage crop). In grey, wind sectors not considered in the present study are reported.

Wind sector (degree) % of 30 min time step >95% of flux from target >80% of flux from target >50% of flux from target

C–C

�308 10.4 58.2 99.8 100.0

30–608 13.0 1.3 99.8 100.0

60–908 20.9 0.7 99.8 100.0

90–1208 7.7 6.4 99.7 100.0

120–1508 6.9 0.0 90.3 100.0

150–1808 9.5 98.7 99.9 100.0

180–2108 5.3 0.0 62.9 100.0

210–2408 5.3 1.2 97.7 100.0

240–2708 4.9 0.1 95.6 99.7

270–3008 4.1 0.2 97.4 99.9

300–3308 6.6 0.7 99.3 100.0

�3308 5.5 43.6 99.7 100.0

C–A

�308 10.4 61.0 99.8 100.0

30–608 13.0 1.5 99.8 100.0

60–908 20.9 0.9 100.0 100.0

90–1208 7.7 7.7 99.7 100.0

120–1508 6.9 91.7 100.0 100.0

150–1808 9.5 98.8 99.9 100.0

180–2108 5.3 66.8 100.0 100.0

210–2408 5.3 1.2 98.0 100.0

240–2708 4.9 0.1 96.0 99.8

270–3008 4.1 0.2 97.7 100.0

300–3308 6.6 0.7 99.4 100.0

�3308 5.5 49.4 99.7 100.0

G. Alberti et al. / Agriculture, Ecosystems and Environment 136 (2010) 139–147 143

Fig. 4. Yearly net ecosystem production (NEP), heterotrophic respiration (Rh), harvest material (harvest) and net biome production (NBP) for maize (C–C) and alfalfa (C–A)

during the first and the second year of the experiment.

Fig. 3. Daily difference in net ecosystem exchange (NEE) between the two land uses calculated as C–A minus C–C. A negative value means a net gain of carbon for C–A relative

to C–C.

G. Alberti et al. / Agriculture, Ecosystems and Environment 136 (2010) 139–147144

that C–C (Table 4), it registered a higher GPP in both the years thusshowing a higher radiation use efficiency (RUE) and a longergrowing season. Furthermore, comparing GPP values derived fromNEE partitioning with potential values derived from radiation useefficiency (RUE) multiplied by intercepted photosynthetic activeradiation (Monteith, 1977), C–A was close to or higher than thepotential GPP while C–C showed a lower value the second year. C–C had a higher Rh than C–A (607 g C m�2 y�1 and 540 g C m�2 y�1,respectively). In total, C–C respired 135 g C m�2 more than C–A atthe end of the second year (Fig. 5; Table 3). Thus, the conversionfrom C–C to C–A caused a decrease in soil C emissions ofapproximately 67 gC m�2 y�1.

The comparison between NPP estimated using the combinationof eddy covariance and soil respiration chambers (NPPEDDY =�NEE � Rh) and NPP estimated using growth analysis was assessed

Table 4Measured values of average (avg) and maximum (max) leaf area index (LAI), total inco

primary production derived from NEE partitioning according to Reichstein et al. (200

(GPPpotential = 1.4 gC MJ�1�PARintercepted) for C–C and C–A fields during the growing sea

Treatment Year Growing season

length (days)a

LAI (m2 m�2) PAR (

Avg Max Incom

C–C 2007 127 2.2 4.1 1.30

2008 144 2.5 4.1 1.54

C–A 2007 178 2.7 6.7 1.66

2008 163 3.0 8.8 1.63

a C–C growing season length in days: harvest–25th April; C–A growing season lengt

as a benchmark of integrated EC and SR fluxes measurements. Theregression analysis of cumulated NPP fluxes and growth analysisdata during the growing season (from sowing to harvest for maizeand from sowing to the end of second year for alfalfa) was good forboth crops (Fig. 6).

The measured Ch in C–A (726 g C m�2 y�1 on average) washigher than in C–C (456 g C m�2 y�1 on average) and irrigatedmaize was a lower source of C in terms of NBP (�48 g C m�2 y�1)than irrigated alfalfa (�177 g C m�2 y�1), mainly due to theintensive harvesting applied to the C–A field.

At the end of the second year, C–C had a NBP of�96 g C m�2 andC–A had a NPB of �354 g C m�2 (Table 3) and C–A emitted258 g C m�2 more than C–C in terms of NBP. However, a differentbehaviour between the 2 years was detected: C–A was a net sourcein terms of NBP in comparison to C–C (�166 g C m�2) during the

ming, intercepted and reflected photosynthetic active radiation (PAR), total gross

5) (GPPmeas) and potential gross primary production according to Monteith, 1977

son.

GJ m�2) GPPmeas

(gC m�2)

GPPpot (gC m�2)

ing Intercepted Reflected

1.03 0.07 1471 1442

1.23 0.08 1148 1722

1.08 0.20 1738 1512

0.97 0.20 1398 1358

h in days: last harvest of the season–1st march.

Fig. 6. Comparison between net primary production (NPP) calculated using eddy covariance and heterotrophic respiration and NPP assessed using growth analysis for C–C (A)

and C–A (B) during the growing season. Horizontal bars indicate standard deviation among plots (n = 3). (A: slope 1.01, R2 = 0.96; B: slope 0.95, R2 = 0.98). In red the NPP at the

end of the growing season for both the years of the experiment.

Fig. 5. Cumulative heterotrophic respiration (main plot) estimated using automated soil respiration chambers (C–C = continuous line; C–A = dotted line) and annual

heterotrophic respiration with standard deviation (vertical bar) for the two land uses (image on the upper left).

G. Alberti et al. / Agriculture, Ecosystems and Environment 136 (2010) 139–147 145

first year, but in the second year the difference decreased(�92 g C m�2).

4. Discussion

Our paired eddy covariance measurement design allowed us todetect the influence of land use change on C fluxes withoutconfounding influences relating to meteorological variability(Kowalski et al., 2004; Ammann et al., 2007). In fact, our footprintanalysis showed that the majority of the 30-min measurementswere dominated by flux emitted from the specified target landcover type (maize or alfalfa) for both the eddy covariance stations.Thus, according to Gockede et al. (2008), the measurements atboth the eddy sites could be used without additional footprintfilters, as the influence of disturbing heterogeneities is very low.Furthermore, the slope of the regression between energy fluxesmeasured at the eddy station and energy balance at the weatherstation is well within the range found by Twine et al. (2000) andWilson et al. (2002) who examined data from FLUXNET sitesthroughout the United States and Europe.

Daily Net Ecosystem Exchange (NEE) are quite close to thosereported by Hollinger et al. (2004) and Grant et al. (2007) formaize (maximum uptake of 18.5 g C m�2 day�1) and a soybean

(maximum uptake of 8.9 g C m�2 day�1) and annual NEE data arein agreement with results of Verma et al. (2005) which alsoevidenced an increase in NEE in a irrigated maize-soybean rotationin comparison to irrigated continuous maize during the first year ofmeasurement, and a significant decrease in the two followingyears.

Even though, the eddy covariance measurements are notreplicated, the comparison between NPP estimated using thecombination of eddy covariance and soil respiration chambers(NPPEDDY = �NEE � Rh) and NPP estimated using growth analysisin the replicated plots showed a strong agreement between thetwo approaches (Fig. 6). However, the higher scatter registered inC–C could be due to inaccuracies in allometric equations appliedduring the growing season, while in C–A the NPP was estimatedwith more accuracy using destructive subplots. In fact, below-ground biomass estimates are more difficult to evaluate, especiallyfor alfalfa, but our estimations of below-ground NPP for alfalfausing growth analysis (628 � 83 g m�2 and 1287 � 109 g m�2 at theend of the first and second year, respectively) and R:S coefficient(0.29) are well between the ranges reported previously by Bray(1963) and Bolinder et al. (2002).

The accumulation of soil organic C is the result of a delicatebalance between C fixation and microbial decay of senescent

G. Alberti et al. / Agriculture, Ecosystems and Environment 136 (2010) 139–147146

vegetation (mainly root mass and residues). Conversion to alfalfachanged the dynamic equilibrium between inputs and outputsestablished in the previous 30 years of intensive maize monocul-ture. Input of organic matter to soil decreased as outputs (Rh): theconversion from C–C to C–A caused a decrease in soil C emissions ofapproximately 67 gC m�2 y�1 mainly because to the absence oftillage-induced aeration and to stronger soil aggregation (Paustianet al., 1997). A stronger Rh reduction in C–A during the second yearsince conversion could have been expected. If Rh in C–C and C–Awere not different during the first year (supposedly, around 80% ofmaize residues [400 gC m�2] and 2% of soil C stock [100 gC m�2]were respired by microbes in both treatments), the second year aRh reduction of around 400 gC m�2 in C–A should have beendetected as the results of no residue inputs. Previous studies(Cardon et al., 2001; Bowden et al., 2004; Ding et al., 2007) haveshown that N fertilization reduced soil respiration because ofdifferent mechanisms (i.e. pH decrease, increase in soluteconcentration, inhibition of the synthesis and activity of certainenzymes) and thus, the fact that C–A respiration was higher thanexpected during the second year could be explained as aconsequence of the absence of N fertilizations. However, it isnot clear whether the response of soil respiration to N fertilizationis temporary or not.

As a consequence of the change in the dynamic equilibriumbetween inputs and outputs, C–A was a net source in terms ofNBP in comparison to C–C. Yearly values of NEP and NBP derivedby eddy covariance are in agreement with NEP and NBPestimated in the replicated plots (Fig. 7) confirming that theC–A is a source of carbon in both years. Similarly, Verma et al.(2005) and Grant et al. (2007) reported that, accounting for the

Fig. 7. Comparison between yearly values of net ecosystem exchange (NEP; panel A)

and net biome production (NBP, panel B) calculated using eddy covariance

technique (black column) or net primary production, heterotrophic respiration and

harvest measured in the plots (white columns). Vertical bars indicate standard error

(n = 3).

grain C removed during harvest, irrigated continuous maize isnearly C neutral or a slight source of C and that irrigated maize–soybean rotation is a moderate source of C. In the present study,C–C is nearly C neutral because the considered soil is close tomaximum carbon capacity. In fact, according to the approachproposed by Six et al. (2002) and based on soil C protectivecapacity, we calculated a C saturation deficit around zero. Ourresults are also in agreement with Hollinger et al. (2004) whoreported a net release of C (NBP) for soybean in a maize–soybeanrotation, but are in contrast with Bernacchi et al. (2005) whomeasured an increase in NBP after soybean cultivation and withSu (2007) who found an increase in organic carbon in 0–5 cmsoil layer after 4 years since conversion from maize to alfalfabecause maize stalks and main roots were removed after harvestthus reducing the soil carbon input.

5. Conclusions

The results from this study showed that: (i) the conversion frommaize to alfalfa in the short-term period increased C uptake interms of NEE and it decreased soil CO2 efflux; (ii) eddy covariancecoupled with continuous soil respiration measurements is asuitable tool to assess carbon balance in agro-ecosystems; (iii) 2years after the conversion from maize to alfalfa there was a net lossof carbon in terms of net biome production (NBPC–C � NBPC–

A = �258 gC m�2 in 2 years). From the present study it appears thatthis type of land conversion is not an effective measure of Csequestration in the short term (1–3 years), but it could be in thelong term as reported by Robertson et al. (2000): the difference inC balance between maize and alfalfa would further decline in thenext years until a new dynamic equilibrium between residueinputs and Rh will be established in the alfalfa field. However,further measurements are needed to verify this hypothesis.Furthermore, in order to assess the overall GHG balance afterthe conversion from maize to alfalfa, experimental measurementson N2O fluxes are needed.

Acknowledgements

This research was founded by the Italian National ResearchProgramme ‘‘CarboItaly’’, Italian project PRIN2005-(071990_005),European Interreg Cadses project ‘‘CarbonPro’’ and EU NitroEuropeproject. We would like to thank Diego Chiaba, Matteo Danelon,Erica Tomat for the help during field and lab work. We also thankMaria Francesca Cotrufo, Costanza Zavalloni and Melissa Haendelfor the useful discussions and suggestions, Matthias Gockede forthe help with footprint analysis.

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