Changes in soil aggregation and microbial community structure control carbon sequestration after afforestation of semiarid shrublands

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Changesinsoilaggregationandmicrobialcommunitystructurecontrolcarbonsequestrationafterafforestationofsemiaridshrublands

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NoeliaGarcia-Franco

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M.Martínez-Mena

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Soil Biology & Biochemistry 87 (2015) 110e121

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Soil Biology & Biochemistry

journal homepage: www.elsevier .com/locate/soi lbio

Changes in soil aggregation and microbial community structurecontrol carbon sequestration after afforestation of semiaridshrublands

N. Garcia-Franco a, M. Martínez-Mena a, *, M. Goberna a, b, J. Albaladejo a

a Soil and Water Conservation Department, CEBAS-CSIC (Spanish Research Council), Campus de Espinardo, P.O. Box 164, 30100 Murcia, Spainb Centro de Investigaciones sobre Desertificaci�on (CIDE-CSIC), Carretera Moncada-N�aquera km. 4.5, 46113, Valencia, Spain

a r t i c l e i n f o

Article history:Received 27 October 2014Received in revised form27 March 2015Accepted 24 April 2015Available online 11 May 2015

Keywords:Microaggregates within macroaggregatesSoil C poolsOrganic amendmentsMicrobial activityBasal respirationPriming effect

* Corresponding author. Tel.: þ34 968 396263; faxE-mail address: [email protected] (M. Martíne

http://dx.doi.org/10.1016/j.soilbio.2015.04.0120038-0717/© 2015 Elsevier Ltd. All rights reserved.

a b s t r a c t

Changes in plant cover after afforestation induce variations in litter inputs and soil microbial communitystructure and activity, which may promote the accrual and physical-chemical protection of soil organiccarbon (SOC) within soil aggregates. In a long-term experiment (20 years) we have studied the effects, onsoil aggregation and SOC stabilization, of two afforestation techniques: a) amended terraces with organicrefuse (AT), and b) terraces without organic amendment (T). We used the adjacent shrubland (S) ascontrol. Twenty years after stand establishment, aggregate distribution (including microaggregateswithin larger aggregates), sensitive and slow organic carbon (OC) fractions, basal respiration in macro-aggregates, and microbial community structure were measured. The main changes occurred in the toplayer (0e5 cm), where: i) both the sensitive and slow OC fractions were increased in AT compared to Sand T, ii) the percentage and OC content of microaggregates within macroaggregates (Mm) were higherin AT than in S and T, iii) basal respiration in macroaggregates was also higher in AT, and iv) significantchanges in the fungal (rather than bacterial) community structure were observed in the afforested soils(AT and T) e compared to the shrubland soil. These results suggest that the increase in OC pools linked tothe changes in microbial activity and fungal community structure, after afforestation, promoted theformation of macroaggregates e which acted as the nucleus for the formation and stabilization of OC-enriched microaggregates.

© 2015 Elsevier Ltd. All rights reserved.

1. Introduction

Among the ecosystem services provided by soils, climate changemitigation through C sequestration is of growing interest. Thisarises especially from the suggested limitations of emissions, basedon a C credit trading system, in the Kyoto Protocol(Intergovernmental Panel on Climate Change,1997; Six et al., 2002).Soil organic carbon (SOC) sequestration may be achieved by meansof afforestation and other types of land-use conversion (De Gryzeet al., 2004). Despite the considerable SOC sequestration potentialof afforestation the results reported by different studies are con-tradictory (Wiesmeier et al., 2009; Cao et al., 2010; Lagani�ere et al.,2010). This may be attributed to: (a) the environmental conditions,mainly rainfall regimes, and (b) according to the case of

: þ34 968 396213.z-Mena).

afforestation (to introduce trees for the first time in the area) orreforestation (to re-plant a formerly wooded area). A better un-derstanding is needed of the mechanisms and factors controllingthe accrual and stabilization of SOC following afforestation.

The amount and quality of plant litter inputs is a key factorcontrolling the accumulation of SOC (K€ogel-Knabner, 2002), whilepromoting the processes involved in soil aggregation (Abiven et al.,2007). Physical soil properties such as soil structure or aggregationregulate many biological and chemical soil processes linked with Csequestration. Particularly, the formation of soil aggregates pro-motes the protection of organic matter against decomposition andoxidation (Jastrow et al., 2007). According to the conceptual modelof Golchin et al. (1994), the fresh and labile pools of organic mattercause a rapid stimulation of the soil microbiota, accompanied by asignificant increase in macroaggregates formation. Other authorsshowed significant correlations between the labile C pools and soilaggregation (Bhattacharyya et al., 2012). In addition, the O-alkylgroups e such as those of carbohydratese have been considered as

Table 1Soil properties of the topsoil (0e5 cm depth) in AT (afforested þ organic amend-ment), T (afforested), and S (shrubland).

Soil properties Treatments

S T AT

Organic carbon (g kg�1) 12.8 ± 0.7a 12.5 ± 0.7a 22.6 ± 2.5bTotal N (%) 0.19 ± 0.01ab 0.15 ± 0.02a 0.23 ± 0.02bAvailable P (mg kg�1) 8.9 ± 0.1b 4.8 ± 0.1a 24.9 ± 1.0cAvailable K

(meq 100 g�1 soil)0.72 ± 0.03c 0.39 ± 0.01a 0.57 ± 0.02b

pH 8.1 ± 0.18a 8.0 ± 0.1a 7.9 ± 0.1aCarbonates (%) 29.5 ± 1.1a 41.4 ± 1.5b 47.2 ± 1.3bBulk density (g cm�3) 1.13 ± 0.06a 1.26 ± 0.01a 0.84 ± 0.19bWater holding capacity (%)Field capacity (�33 kPa) 21.9 ± 1.4b 16.2 ± 0.6a 22.0 ± 1.0bPermanent wiltingpoint (�1500 kPa)

10.5 ± 1.2a 10.8 ± 0.7a 12.7 ± 0.6ª

Available water content (%) 11.5 ± 1.6b 5.4 ± 0.5a 9.3 ± 0.5bTexture Loam Loam Silt loam

Numerical values are means ± standard errors for n ¼ 6. Different letters in rowsindicate significant differences between treatments (Tukey's test, P < 0.05).

N. Garcia-Franco et al. / Soil Biology & Biochemistry 87 (2015) 110e121 111

a major source of labile organic C for microbial activity, fosteringthe binding of clay and silt-size particles and the formation ofmicroaggregates within macroaggregates, increasing the stabilityof soil aggregates (Jastrow,1996; Six et al., 2000a). In addition to thesubstantial role of labile organic matter inputs, many studies havepointed out the important function of soil microorganisms in theformation and stabilization of soil aggregates (Díaz et al., 1994;Siddiky et al., 2012). The microorganisms act in two ways: a)fungal hyphae favor the mechanical union of soil particles and b)the exudation of byproducts promotes the coalescence of primaryparticles (De Gryze et al., 2005; Helfrich et al., 2008). Generally,fungi are thought to be more important in soil aggregate formationthan bacteria (De Gryze et al., 2005). This has led to the suggestionthat manipulations to enhance C sequestration should includeshifting the soil microbial community towards an increased fungalcomponent (Jastrow et al., 2007). In this sense, the change of mi-crobial structure or the introduction of microorganisms into thesoil, with lasting effects, is very difficult to tackle with currenttechnologies (Jastrow et al., 2007). A possible option could be tocause changes in the vegetation cover through afforestation, sincethe vegetation type can influence the microbial community struc-ture (Costa et al., 2006). Afforestation is a key land-use changeacross the world and is considered to be a dominant factor con-trolling ecosystems functioning and biodiversity; however, theresponse of soil microbial communities to this change is not wellunderstood (Macdonald et al., 2009). Here, we intend to increaseour knowledge of this response, by using next-generationsequencing techniques to provide a detailed analysis of the struc-ture, diversity, and taxonomic composition of both the bacterialand fungal communities in natural shrubland and afforested soilunder semiarid conditions.

In a previous publication, from the same experimental area,Garcia-Franco et al. (2014) showed that, based on results obtained20 years after the plantation of trees, the afforestation of semiaridshrublands may result in either sequestration or loss of organic C inthe ecosystem depending on the site preparation technique used.So, after 20 years the afforestationwith soil organic amendment ledto an increase of 1.3 kg C m�2 in the ecosystem, while without soilamendment a decrease of 0.6 kg C m�2 occurred. Here, we inves-tigate the mechanisms of the processes defining the accrual andstabilization of SOC in afforested semiarid soils. Based on the earlierresults, we hypothesized that the plantation of Pinus halepensiswould increase fresh litter inputs into the soil, leading to (1)changes in soil organic C fractions which can related to soil organicC pools with different turnover rates, (2) changes in soil aggregate-size distribution due to the formation of new macroaggregates andorganic C enriched microaggregates within macroaggregates, (3)increase in basal respiration within the macroaggregates as an in-dicator of higher microbial activity, which might be related withorganic C protection in microaggregates formed within macroag-gregates, (4) changes in the microbial populations structure due tothe increase in ectomycorrhizal fungi associated with P. halepensis,which can produce aggregate-stabilizing mycelia, and (5) a closecorrelation between these changes in soil aggregation and micro-bial structure and activity. In our hypothesis we are assuming: (a)the OC accrual in microaggregates within macroaggregates isconsidered as an indicator of soil C stabilization and long-termsequestration (Six et al., 2013), and (b) the separated soil organicC fractions, arising from the fractionation procedure used, corre-spond to the sensitive and slow pools of Roth C (Zimmermann et al.,2007).

This long-term experiment was performed under environ-mental conditions typical of Mediterranean semiarid areas, so theresults could be extrapolated to extensive areas of land around theworld. The specific objectives of this study were to analyze the

effects of the afforestation of degraded shrublands on: 1) changesin soil aggregation, 2) changes in the soil microbial communitystructure, and 3) physicalechemical processes of SOC protectionand stabilization.

2. Material and methods

2.1. Site description and experimental design

The study area was located in the Sierra de Carrascoy (Murcia),Southeast Spain (37� 530N, 1� 150W, 180 m a.s.l). The climate issemiarid, with an average annual precipitation of 300 mm and amean annual temperature of 18 �C. The mean annual potentialevapotranspiration is 900e1000 mm y�1. The soils are classified asHaplic Calcaric Leptosolwith inclusions of Haplic Calcisols and LepticCalcisols (FAO, 2006). The lithology is constituted by hard andcompact limestone rocks. The fertility of the soils after each treat-ment is showed in Table 1. The dominant vegetation is composed ofspecies typical of Mediterranean shrublands, such as Rosmarinusofficinalis L., Thymus vulgaris L., and Anthyllis cytisoides L. withscattered P. halepensis. Miller.

The experiment site was established in October 1992 in an areaof 1800 m2 and consisted of three 20 m � 30 m plots located on aneast-facing hillside (25% mean slope), to test the following affor-estation techniques: a) mechanical terracing with a single appli-cation of 10 kg m�2 of an organic amendment, which consisted ofthe organic waste of urban soil refuse (USR) (García et al., 1998), andP. halepensis plantation (plot AT), and b) mechanical terracing andP. halepensis plantation, without organic amendment (plot T)addition. To test these afforestation techniques, an adjacent Medi-terranean shrubland was considered as the control plot (S). Moredetails about these afforestation techniques are given in Garcia-Franco et al. (2014).

2.2. Soil sampling design

In April 2012, 20 years after afforestation, a randomized soilsampling trial was designed to assess the effects of the tested fac-tors. Six (1 m � 1 m) soil sampling sub-plots were selected at eachplot (18 sampling sites). The separation between sampling sites wasabout 10 m in one direction and 15 m in the other. The samplingsites were located under trees in treatments AT and T and undershrubs in the control S. At each sampling site, soil samples werecollected from three soil depths: 0e5 cm, 5e20 cm, and 20e25 cm

N. Garcia-Franco et al. / Soil Biology & Biochemistry 87 (2015) 110e121112

(54 sampling points for the whole experiment). At each samplingpoint, soil samples were randomly collected as a composite of threesubsamples. Soil DNA extractions, aimed at analyzing the com-munity structure of soil bacteria and fungi, were performed incomposite surface samples (0e5 cm) collected in three samplingsites per treatment.

2.3. Analytical methods

2.3.1. Soil organic C fractionation procedureTo test the changes in SOC fractions with different turnover rates

(hypothesis 1), the organic fractions were separated with a com-bined physical and chemical method, according to Zimmermannet al. (2007). Thirty grams of soil (<2000 mm) were added to150 mL of water and dispersed using a calibrated ultrasonic probe-type with an output energy of 22 J mL�1. Application of more en-ergy may disrupt the coarse sand-sized SOM (Amelung and Zech,1999). The dispersed suspension was then wet-sieved over a 63-mm-aperture sieve until the rinsing water was clear. The fraction>63 mm, containing the sand fraction and stable aggregates (S þ A)together with particulate organic matter (POM), was dried at 40 �Cand weighed. The suspension <63 mm was filtered through a 0.45-mm-aperture nylon mesh and the material >0.45 mm was dried at40 �C and weighed. The POM was separated by stirring the fraction>63 mmwith sodium polytungstate at a density of 1.6 g cm�3 (Cerliet al., 2012). Themixturewas centrifuged at 1000� g for 15min andthe light fraction was decanted. Both fractions were washed withdeionized water to remove all the sodium polytungstate, dried at40 �C, and weighed. The OC concentrations were determined inevery fraction using an Elemental Analyzer (LECO TRUSPEC CN,Michigan, USA). The samples were analyzed in triplicate. The OCcontent for each fraction was calculated with the followingequation:

ðOCÞ ¼ ðOCÞfraction*ðfraction proportionÞsoil�g C kg�1 soil

�

In this study, we have processed the SOC fractions in two maingroups according to their turnover rates: i) a sensitive fraction(OCs) formed by the free particulate organic matter, which corre-spond to the light fraction separated by stirring the fraction >63 mmwith sodium polytungstate at a density of 1.6 g cm�3, and ii) a slowfraction (OCsw) constituted by the OC stabilized in aggregates(heavy fraction >63 mm) combinedwith the OC associatedwith clayand silt (<63 mm fraction). The separation of these two groups wasbased in the study of Zimmermann et al. (2007), in which a strongcorrelation was found between the separate SOC fractions (sepa-rated with the above procedure) and the sensitive and slow SOCpools used in Roth C.

2.3.1.1. Characterization of the OCs fraction. The molecular compo-sition of the OCs fraction at 0e5 cm depth was determined by 13C-NMR spectroscopic analysis, using a Varian Unity 300 spectrometer.Samples were filled into zirconium dioxide rotors (7 mm diameter)and spun in a magic angle spinning probe, at a rotation speed of4.0 kHz to minimize chemical anisotropy. A ramped 1H pulse wasused during a contact time of 1 ms to prevent Hartmann-Hahnmismatches. The contact time was 1500 ms. For each sample,20,000 runing was carried out before the final spectrum. For inte-gration, chemical shift regions were used as follows: i) aliphatic oralkyl-C (0e45 ppm) of lipids, fatty acids, and plant aliphatic poly-mers; (ii) O-alkyl-C (45e110 ppm) deriving primarily from poly-saccharides (cellulose and hemicelluloses), but also from proteinsand side chains of lignin; (iii) aromatic or aryl-C (110e162 ppm),deriving from lignin and/or protein; and finally (iv) carbonyl-C(162e190 ppm) from aliphatic esters, carboxyl groups, and amide

carbonyls. Integration of the peaks within each of the chemical shiftregions allowed estimation of the relative C contents, expressed aspercentages of the total area (Helfrich et al., 2006).

2.3.2. Soil aggregate-size distributionTo test the changes in soil aggregate-size distribution due to the

formation of new macroaggregates and organic C enriched micro-aggregates within macroaggregates (hypothesis 2), aggregate-sizeseparation was performed by the wet-sieving method of Elliott(1986). Briefly, 100 g of air-dried (5-mm-sieved) soil were placedon top of a 2000-mm sieve and submerged for 5 min in deionizedwater at room temperature. The sieving was performed manuallyby moving the sieve up and down 3 cm, 50 times, for 2 min e toachieve aggregate separation. A series of three sieves (2000, 250,and 63 mm) was used to obtain four aggregate fractions: i)>2000 mm (large-macroaggregates; LM), ii) 250e2000 mm (small-macroaggregates; SM), iii) 63e250 mm (microaggregates; m), andiv) <63 mm (silt plus clay-size particles; s þ c). The aggregate-sizeclasses were oven dried (50 �C), weighed, and stored in glass jarsat room temperature (21 �C). Sand correction was performed foreach aggregate-size class because sand was not considered to bepart of the aggregates (Elliott et al., 1991).

Microaggregates contained within both the large- and small-macroaggregates (LMm and SMm, respectively) were mechani-cally isolated according to the methodology described by Six et al.(2000b) and Denef et al. (2004). Briefly, a 10-g macroaggregatesubsample was immersed in deionized water on top of a 250-mmmesh screen, inside a cylinder. The macroaggregates were shakentogether with 50 glass beads (4 mm diameter) until completemacroaggregate disruption was observed. Once the macroaggre-gates had been broken up, microaggregates and other <250 mmmaterial passed through the mesh screen with the help of acontinuous water flow. The material retained on the 63-mm sievewas wet sieved to ensure that isolated microaggregates were waterstable (Six et al., 2000b). The OC determination was performedseparately for all aggregate size classes, using an ElementalAnalyzer (LECO TRUSPEC CN. Michigan, USA).

Samples were analyzed in triplicate. The OC content for thewater-stable aggregate-size classes was calculated, at the soil level,with the following equation:

OC ¼ ðOCÞfraction*ðagg:proportionÞsoilðg C=kgsoilÞ

2.3.3. Diversity and structure of soil microorganismsTo test the changes in themicrobial populations structure due to

the increase in ectomycorrhizal fungi associated with P. halepensis(hypothesis 4), soil DNA was extracted by using the FastDNA Kit(Qbiogene Inc., Irvine, USA) and purified on Low Melting Pointagarose gel 1.25 (wt/vol) containing 2% polyvinylpyrrolidone (PVP)(Young et al., 1993). The DNA extracts were analyzed on 1% agarosegels and their final concentrations quantified with a Nanodrop2000 (Thermo Scientific, Wilmington, USA). The universal Eubac-terial primers BSF8 (50-TCAGAGTTTGATCCTGGCTCAG-30) andUSR515 (50-CACCGCCGCKGCTGGCA-3) were used for amplifyingthe 16S rRNA V3 fragment (Bibby et al., 2010). The universaleukaryotic primers nu-SSU-0817-59 (50TTAGCATGGAATAATRRAATAGGA-30) and nu-SSU-1196-39 (50-TCTGGACCTGGTGAGTTTCC-30) were used for amplifying the 18S rRNA V4 fragment(Borneman and Hartin, 2000). The amplifications were performedin a MyCyclerTm Thermal cycler (Bio-Rad Laboratories Inc., Hercu-les, USA). The PCR conditions used for amplification of the 16S rRNAfragment were: 94 �C for 5 min, followed by 30 cycles consisting of30 s at 94 �C, 30 s at 56 �C, and 90 s at 72 �C, and a final elongationstep at 72 �C for 10min. The 18S rRNA genewas amplified using the

Table 2Sensitive OC fraction (OCs) and slow OC fraction (OCsw) concentrations(g C kg�1soil) in AT (afforested þ organic amendment), T (afforested), and S(shrubland), in the bulk soil at 0e5, 5e20, and 20e25 cm depth.

Depth (cm) S T AT

Sensitive fraction (OCs)0e5 4.02 ± 0.10aC 5.90 ± 0.78aB 11.65 ± 1.20bB5e20 2.59 ± 0.21aB 3.10 ± 0.26aA 3.46 ± 0.34aA20e25 1.74 ± 0.24aA 2.45 ± 0.22aA 1.72 ± 0.31aASlow fraction (OCsw)0e5 8.78 ± 0.45bAB 5.87 ± 0.26aA 10.92 ± 0.59cB5e20 9.40 ± 0.73cB 5.09 ± 0.17aA 7.02 ± 0.45bA20e25 7.28 ± 0.46bA 5.61 ± 0.52aA 5.62 ± 0.35aA

Numerical values are means ± standard errors for n ¼ 6. Different lowercase lettersin rows indicate significant differences between treatments at each depth withineach OC fraction. Different uppercase letters in columns indicate significant differ-ences between depths within each treatment (Tukey's test, P < 0.05).

Table 3Relative contents (%) of alkyl-C, O-alkyl-C, aryl-C, and carbonyl-C in the sensitivefraction for the afforested treatments (AT and T) and shrubland (S), at 0e5 cm depth.

Functionalgroup

Chemical shiftregions (ppm)

Relative content (%)

S T AT

Alkyl-C 0e45 33.2 ± 0.05a 31.7 ± 0.8a 30.3 ± 0.6aO-Alkyl-C 45e110 45.1 ± 0.25a 49.2 ± 0.7b 51.1 ± 1.1bAryl-C 110e165 12.5 ± 0.05b 10.2 ± 0.2a 10.4 ± 0.3aCarbonyl-C 165e220 9.25 ± 0.15a 8.8 ± 0.4a 8.2 ± 0.6a

Numerical values are means ± standard errors for n ¼ 6. Different letters in rowsindicate significant differences between treatments (Tukey's test, P < 0.05).

N. Garcia-Franco et al. / Soil Biology & Biochemistry 87 (2015) 110e121 113

following protocol: 94 �C for 2 min then 35 cycles of 94 �C for 10 s,56 �C for 10 s, and 72 �C for 30 s, followed by 72 �C for 2 min. Theamplicon length and concentration were estimated, and an equi-molar mix of all amplicon libraries was used for tag-encoded FLX-titanium amplicon pyrosequencing (Roche, Basel, Switzerland). Itshould be noticed that this PCR-based technique could underesti-mate low abundant groups in the bulk soil such as Glomeromycota.

The sequences were processed using QIIME v. 1.5.0 (Caporasoet al., 2010) e by selecting sequences with a quality score >25,containing no ambiguous bases, without any primer mismatches,and with a sequence length between 200 and 400 bp. After qualitychecking, counting, sorting, and denoising, chimeras were identi-fied using ChimeraSlayer (Haas et al., 2011). Clustering of the se-quences into operational taxonomic units (OTUs) was performedusing UCLUST (Edgar, 2010) and a cutoff value of 97% sequenceidentity. The most abundant sequence type within each OTU wasselected to represent the respective OTU in further analysis. Thetaxonomic assignment was performed according to RDP (Wanget al., 2007) and the BLAST data base of the NCBI. The Chao1 andShannon indices were calculated from 5986 to 5575 seqs/samplesfor bacteria and fungi, respectively, to estimate taxon richness anddiversity. Principal coordinate analysis (PCoA), using weightedUniFrac distances, was used to visualize differences in microbialcommunity structure across the treatments (Hamady et al., 2010).Sequences generated in this study were deposited in EMBL withinthe study with accession number PRJEB7535 (http://www.ebi.ac.uk/ena/data/view/PRJEB7535).

2.3.4. Soil respiration measurements in macroaggregates(>250 mm)

To test the increase in basal respiration within the macroag-gregates as an indicator of higher microbial activity (hypothesis 3),the amount of CO2eC released daily per kg of soil macroaggregatewas measured during the incubation under controlled conditions(Nannipieri et al., 1990). Soil respiration was analyzed by placing15 g of soil macroaggregates, moistened to 60% of their water-holding capacity, in hermetically sealed 125-ml flasks during a31-day incubation period at 28 �C (Bastida et al., 2007). Threerepetitions were made per sample. The CO2 released was measuredperiodically (every day for the first 4 days and then weekly) usingan infrared gas analyzer (Toray PG-100, Toray Engineering Co. Ltd.Japan). After eachmeasurement, the stoppers were removed for 1 hto balance the atmosphere inside and outside the bottles.

2.4. Statistical analyses

Prior to the analyses, the normality of the datawas proved usingthe KolgomoroveSmirnov test and the homogeneity of varianceswith the Levene test. Data that were not distributed normally (LM,SM, LMm, OC-LM, OC-SM, OC-SM, and OC-SMm) were ln-transformed. To compare all the soil variables between treat-ments, a General Linear Models (GLM) procedure was carried out econsidering treatment and depth as fixed factors. To test the hy-pothesis 5, Pearson correlations were used in order to explore therelationships between the functional OC fraction (OCs and OCsw) inbulk soil and the distribution of aggregates and their associatedorganic carbon, as well as the relationships between basal respi-ration and the distribution of aggregates and their associatedorganic carbon. The analyses were computed with SPSS 19.0 (Chi-cago, IL, USA) and the significance was set at p < 0.05.

To compare the soil microbial communities of the treatments,analysis of variance using distance matrices was performed withthe vegan package for R (ADONIS, R Development Core Team 2011;Oksanen et al., 2013). The statistical significance was tested against999 null permutations. The effect of the treatments on the relative

abundance of bacterial and fungal phyla (arcsine-transformeddata), as well as richness (Chao 1), number of unique OTUs anddiversity (Shannon index) was analyzed with a GLMs using R. Totest the influence of soil parameters (bulk density, available watercontent, clay, silt, and sand contents, pH, carbonates, available P,and labile OC) on the microbial communities, we computed cor-relations between the soil physical-chemical and (bacterial orfungal) OTU abundance distance matrices through Mantel tests,with the vegan package for R. Similarly, matrix correlations be-tween OTU abundance and aggregate-size distance matrices wereperformed to test for the influence of themicrobial communities onthe distribution of soil aggregates.

3. Results

3.1. Changes in SOC fractions after afforestation

A significant increase in the sensitive OC fraction (OCs) and theslow OC fraction (OCsw) was found in AT e compared to S e in the0e5 cm layer, while on the contrary, OCsw was significantlydecreased in AT compared to the S treatment in deeper layers.When afforestation was performed without amendment (T) a sig-nificant decrease of the OCsw fraction was found e compared totreatment S e through the whole profile, while no changes wereobserved in the OCs fraction (Table 2). In addition, significant dif-ferences in the chemical composition of the OCs fraction at 0e5 cmdepth were found between the afforested (AT and T) and theshrubland (S) soils, the former showing higher percentages of O-alkyl C and lower percentages of aryl C materials (Table 3). Nodifferences were detected among treatments with regard to therelative contents of the alkyl-C or carbonyl-C materials (Table 3).

3.2. Distribution of water-stable aggregate-size classes

Macroaggregates (>250 mm) was the predominant aggregate-size class for all treatments and depths, representing between 65

N. Garcia-Franco et al. / Soil Biology & Biochemistry 87 (2015) 110e121114

and 80% of the bulk soil. In general, in the afforested soils a decreasein the percentage of macroaggregates and an increase in that ofmicroaggregates were observed with depth. Also, in soil S an in-crease in the microaggregates percentage with depth was found.Likewise, the silteclay particles percentage increased with depth inall treatments.

The T treatment generally gave the lowest proportion of large-and small-macroaggregates (LM and SM, respectively) along thesoil profile, while soils in AT and S treatments tended to havesimilar percentages of both macroaggregates. The afforested soils(AT and T) showed a lower proportion of microaggregates,compared to S, across the depths, while the opposite trend occurredwith silteclay particles (Fig. 1).

3.3. Organic carbon associated with aggregate-size classes

The OC associated with macroaggregates (>250 mm) repre-sented 47% of the total SOC in the topsoil and increased to 76% atthe deepest layer (20e25 cm) in AT. The opposite trend wasobserved in T and S, in which the OC in macroaggregates reached66% and 73%, respectively, of the total SOC in the top soil anddecreased to about 30% and 50%, respectively, below 5 cm depth.

A reduction in the OC concentrations associated with all theaggregate-size classes was found in soil T compared to S, at alldepths. Soil AT had similar OC-LM (>2000 mm) and OC-m(250e63 mm) concentrations to S along the soil profile (Fig. 2).The OC associated with the silteclay fraction (<63 mm) was higherin AT than in T and S in the top layer, whereas AT showed the lowestOC in silteclay content below 5 cm depth (Fig. 2). The OC-LM(>2000 mm) decreased with depth in all treatments, whereas theOC-SM (2000e250 mm) content only decreased with depth in theafforested treatments.

Fig. 1. Weight percentage of the water-stable aggregate-size classes distribution (gaggregate 100 g�1 soil): >2000 mm (large-macroaggregates; LM), 250e2000 mm(small-macroaggregates; SM), 63e250 mm (microaggregates; m), and <63 mm(silt þ clay fraction; s þ c) in the 0e5, 5e20, and 20e25 cm soil layers of the AT(afforested þ organic amendment), T (afforested), and S (shrubland) soils. Numericalvalues are means ± standard errors for n ¼ 6. Bars with different lowercase lettersindicate significant differences between treatments at each depth and different up-

3.4. Proportion of microaggregates within macroaggregates and theassociated organic carbon

The AT treatment produced a higher proportion of micro-aggregates, within both large and small-macroaggregates, than Sand T at 0e5 cm depth. In turn, T and S did not show any differ-ences. Below 5 cm depth, no differences were found between ATand S, while T showed the lowest percentages (Table 3). The per-centage of microaggregates occluded within macroaggregatesdecreased with depth in the afforested soils while an increase ofsmall macroaggregates was observed in soil S.

The OC associated with microaggregates within macroaggre-gates showed the same pattern among treatments as the percent-age of microaggregates mentioned above e soil AT showing higherOC associated with large and small macroaggregates, at the surface,with respect to S and T (Table 3). Below 5 cm depth, the T treatmentexhibits the lowest OC concentrations in macroaggregates, whileno differences were found between AT and S. Decreases with depthof OC in macroaggregates were observed in the afforestationtreatments, these reductions being more drastic in T than in AT(Table 3).

percase letters indicate significant differences between depths within each treatment(Tukey's test, P < 0.05).

3.5. Soil respiration measurements

Significant differences in the basal respiration in macroaggre-gates were found between treatments. The AT treatment gave ahigher basal respiration than treatments S and T, at all depths(Fig. 3). At the surface, basal respiration was higher in soil T than inS, while below 5 cm no significant differences were observed be-tween them.

3.6. Correlations between functional OC pools, basal respiration,and microaggregates within macroaggregates

Due to the similar characteristics and behavior of large and smallmacroaggregates in all the treatments, we grouped both size-classes together as macroaggregates >250 mm (M), to facilitate

Fig. 2. Organic carbon content (g kg�1 soil) of soil aggregates: >2000 mm (large-macroaggregates; LM), 250e2000 mm (small-macroaggregates; SM), 63e250 mm(microaggregates; m), and <63 mm (s þ c) in the 0e5, 5e20, and 20e25 cm soil layersof the AT (afforested þ organic amendment), T (afforested), and S (shrubland) soils.Numerical values are means ± standard errors for n ¼ 6. Bars with different lowercaseletters indicate significant differences between treatments at each depth and differentuppercase letters indicate significant differences between depths within each treat-ments (Tukey's test, P < 0.05).

Fig. 3. Basal respiration in macroaggregates (BR-M: mg CO2eC kg�1 day�1) in the 0e5,5e20, and 20e25 cm soil layers, as affected by the AT (afforested þ organic amend-ment), T (afforested), and S (shrublands) treatments. Numerical values aremeans ± standard errors. Bars with different lowercase letters indicate significantdifferences between treatments at each depth and different uppercase letters indicatesignificant differences between depths within each treatment (Tukey's test, P < 0.05).

Table 4Weight percentage (%) and organic carbon concentration (g C kg�1 soil) of micro-aggregates within macroaggregates: LMm (microaggregates within large-macroaggregates) and SMm (microaggregates within small-macroaggregates) at0e5, 5e20, and 20e25 cm soil depth, as affected by the AT (afforested þ organicamendment), T (afforested), and S (shrubland) treatments.

Treatments

S T AT

Weight (%)LMm0e5 cm 14.7 ± 2.0aA 17.1 ± 1.5aC 21.6 ± 2.1bB5e20 cm 24.2 ± 1.8cB 11.7 ± 1.5aB 20.7 ± 2.4bAB20e25 cm 17.4 ± 1.5bA 3.0 ± 0.1aA 17.8 ± 1.4bASMm0e5 cm 14.4 ± 1.5aA 15.4 ± 1.5aA 27.5 ± 1.5bC5e20 cm 22.3 ± 1.9bB 14.5 ± 1.5aA 20.4 ± 1.0bB20e25 cm 23.7 ± 1.5bB 14.0 ± 0.9aA 16.4 ± 3.1aAOC (g C kg�1 soil)OC-LMm0e5 cm 1.3 ± 0.2aA 1.3 ± 0.2aB 2.0 ± 0.2bB5e20 cm 2.1 ± 0.2bB 0.5 ± 0.1aA 1.3 ± 0.1abA20e25 cm 1.2 ± 0.2bA 0.1 ± 0.03aA 1.1 ± 0.3bAOC-SMm0e5 cm 1.3 ± 0.2aA 1.4 ± 0.2aB 2.7 ± 0.3bB5e20 cm 1.9 ± 0.2bA 0.7 ± 0.2AaB 1.8 ± 0.2bA20e25 cm 1.5 ± 0.3bA 0.5 ± 0.2aA 1.3 ± 0.1bA

Numerical values are means ± standard errors for n ¼ 6. Different lowercase lettersin rows indicate significant differences between treatments at each depth. Differentuppercase letters in columns indicate significant differences between depths withineach treatment (Tukey's test, P < 0.05).

N. Garcia-Franco et al. / Soil Biology & Biochemistry 87 (2015) 110e121 115

the interpretation of the correlations. Significant differences werefound between the treatments (Table 5).

Significant, positive correlations were found between the sen-sitive OC fraction (OCs) and the percentage of macroaggregates andOC associated with macroaggregates, for all treatments. However,for the slow fraction (OCsw), only in treatment AT was there a tight

correlation with the percentage of macroaggregates and OC inmacroaggregates. In a similar way, OCs and OCsw were correlatedwith the percentage of microaggregates within macroaggregatesand its associated OC only for the AT treatment. The OCs fractionwas correlated with micro within macroaggregates in treatment T,but in S no correlations were found between these parameters.Negative correlations between both SOC fractions and the

Table 5Pearson correlation coefficients between the sensitive fraction (OCs), slow fraction(OCsw), basal respiration (BR), aggregates percentage, and aggregate-associated OC.

Correlations: Treatments

S T AT

OCs (g kg�1):M (%) 0.816** 0.684** 0.828**m (%) 0.471 �0.714** �0.836**Mm (%) �0.733 0.683** 0.860**OC-M (g kg�1) 0.780** 0.659** 0.931**OC-m (g kg�1) 0.341 0.046 �0.433OC-Mm (g kg�1) �0.182 0.451 0.864**BR (mg CO2eC kg�1 d�1) 0.877** 0.784** 0.925**OCsw (g kg�1):M (%) 0.567* 0.093 0.786**m (%) �0.345 �0.281 �0.867**Mm (%) �0.018 0.048 0.752**OC-M (g kg�1) 0.552* 0.316 0.743**OC-m (g kg�1) 0.273 �0.032 �0.449OC-Mm (g kg�1) 0.474 0.235 0.746**BR (mg CO2eC kg�1 d�1) 0.245 0.261 0.896**BR-M (mg CO2eC kg�1 d�1)M (%) 0.798** 0.817** 0.933**m (%) �0.486 �0.922** �0.918**Mm (%) �0.838** 0.855** 0.911**OC-M (g kg�1) 0.719** 0.985** 0.917**OC-m (g kg�1) 0.138 0.098 �0.481*OC-Mm (g kg�1) �0.435 0.823** 0.819**

*P < 0.05; **P < 0.01. M: percentage of macroaggregates (>250 mm: LM þ SM); m:microaggregates (250e63 mm), Mm: percent of microaggregates within macroag-gregates; OC-M: organic carbon content in macroaggregates; OC-m: organic carboncontent in microaggregates; OC-Mm: organic carbon content in microaggregateswithin macroaggregates; BR: basal respiration in macroaggregates.

Fig. 5. Means ± standard errors (n ¼ 3) for the relative abundance of fungal taxa in thesoil surface layer (0e5 cm), in AT (afforested þ organic amendment), T (afforested),and S (shrubland) soils. Bars with different lowercase letters indicate significant dif-ferences between treatments (P < 0.05).

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percentage of microaggregates not occluded within macroaggre-gates were found in the afforested soils, mainly in AT.

The basal respiration in macroaggregates showed strong cor-relationswith the percentage of macroaggregates and its associatedOC in all treatments. It is important to note the strong correlationsbetween basal respiration and the percentage of micro withinmacroaggregates: positive in treatments AT and T and negative in S.In turn, basal respiration and OC associated with micro withinmacroaggregates showed close correlations in the afforested soils.As occurred with OCs, the basal respiration was negatively corre-lated with the percentage of free microaggregates in treatments ATand T. Finally, basal respiration was correlated with OCs in alltreatments, but with OCsw only in AT.

Fig. 4. Means ± standard errors (n ¼ 3) for the relative abundance of bacterial phyla inthe soil surface (0e5 cm), in AT (afforested þ organic amendment), T (afforested), andS (shrubland). No significant differences were detected across treatments.

3.7. Changes in the soil microbial community

3.7.1. Soil bacterial communityThe bacterial community structure did not differ significantly

across treatments, based on the OTU distance matrices (F ¼ 1.16,R2 ¼ 0.279, P ¼ 0.104). However, PCoA based on weighted Unifracdistance matrices, which include a phylogenetic component, sug-gested a distinct bacterial community structure in soils undershrubland, compared to afforested areas (Fig. 6a). No relationshipwas found between a battery of nine physical and chemical pa-rameters and the bacterial community structure in the soils(r ¼ 0.076, P ¼ 0.283). The same result was found when eachparameter was tested individually. The bacterial richness Chao1,the number of unique OTUs, and Shannon's index did not differamong treatments either (Table 6).

The relative abundance of most of the dominant bacterial phyla(Proteobacteria, Actinobacteria, Chloroflexi, Bacteroidetes, Gemmati-monadetes, Planctomycetes, and Acidobacteria) was not statisticallydifferent among treatments (Fig. 4). The abundance of other phyla,comprising those with relative abundances below 1% or notassignedwith sufficient confidence to any known bacterial phylum,did not differ significantly among treatments (Fig. 4).

3.7.2. Soil fungal communityThe fungal community structure differed significantly across

treatments (t ¼ 1.60, R2 ¼ 0.348, P < 0.05; Fig. 6b). This wasmediated by the differences in the soil physical and chemical pa-rameters (r ¼ 0.468, P < 0.05). Particularly important were the in-dividual effects of carbonate (r¼ 0.408, P < 0.05) and sand contents(r ¼ 0.439, P < 0.05). In addition, fungal richness was significantlyhigher in AT compared to S (F ¼ 2.90, P < 0.05), while that in T didnot differ significantly from the other two treatments (Table 6). Nodifferences were found in the number of unique fungal OTUs orShannon's index (Table 6).

The relative abundance of the dominant fungal taxon (Saccha-romyceta) was not statistically different among treatments (Fig. 5).Mitosporic Ascomycota was more abundant in S than in AT, whiletheir abundance in T did not differ significantly from that in S or AT.Other Ascomycotawere significantly more abundant in AT than in Tand S. The Basidiomycota (Agaricomycotina) were significantlymoreabundant in AT than in S, while their abundance in T did not differsignificantly from that in S or AT. The Chytridiomycota weresignificantly higher in S than in the other treatments.

Fig. 6. Dot-plots obtained from principal coordinate analyses, representing (a) thebacterial and (b) the fungal community structure in every treatment: AT(afforested þ organic amendment), T (afforested), and S (shrubland).

Table 6Soil bacterial and fungal richness and diversity in afforested (AT and T) and shrub-land (S) soils at 0e5 cm depth.

S T AT

BacteriaNumber of unique OTUs 3230 ± 82.8a 3271 ± 138a 3509 ± 57.6aChao1 11,071 ± 372a 10,647 ± 869a 12,286 ± 386aShannon 10.7 ± 0.1a 10.78 ± 0.2a 11.01 ± 0.1aFungiNumber of unique OTUs 1737 ± 11.4a 1707 ± 138.2a 1934 ± 64.5aChao1 4374 ± 243a 5519 ± 498ab 6046 ± 439bShannon 8.69 ± 0.1a 7.8 ± 0.6a 8.7 ± 0.2a

Numerical values are means ± standard errors for n ¼ 3. Different letters in rowsindicate significant differences between treatments (P < 0.05).

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Finally, the abundance of other fungal taxa, comprising thosewith relative abundances below 1% (i.e. Glomeromycota, and Neo-callimastigomycota) or not assigned with sufficient confidence toany known fungal taxon, was significantly higher in T and AT thanin S (Fig. 5).

In addition, the distribution of aggregate-size classes wassignificantly correlated with the community structure of soil fungi(r ¼ 0.378, P < 0.05), but not with that of soil bacteria (r ¼ �0.003,P ¼ 0.52). The same trend was found for the basal respirationmeasured in soil macroaggregates (BR-M), which correlatedsignificantly with the community structure of soil fungi (r ¼ 0.462,P ¼ 0.01), but not with that of bacteria (r ¼ 0.056, P ¼ 0.35).

4. Discussion

4.1. Changes in soil aggregation

Twenty years after the afforestation, the percentage of water-stable aggregates differed significantly across the treatments. Areasafforested with P. halepensis and receiving no organic amendments(T) showed the lowest percentages of large- and small-macroaggregates, suggesting mechanical disturbance of the soilstructure owing to the terracing works. This initial impact was fol-lowed by an active process of new macroaggregates formation(>250 mm) in the organically-amended, afforested soils (AT), whichbehaved similarly to the shrubland soils e particularly in the topsoillayers. This suggests that theorganic amendmentsoffset thenegativeimpact of the terraces. Similar soil structure deterioration followingmechanical terracing was described by other authors (Barber andRomero, 1994). Likewise, other studies reported increases in soilaggregation due to both soil afforestation (Caravaca et al., 2002;Khale et al., 2005) and soil organic amendment (Díaz et al., 1994).

Afforestation and amendment (treatment AT) increased notonly the percentage of macroaggregates (>250 mm) but also thepercentage of microaggregates occluded inside the macroaggre-gates. In addition, the OC concentration in these new micro-aggregates formed in AT soil was higher than in the non-occludedmicroaggregates existing in the soil before afforestation, as washypothesized above. Overall, these results suggest a hierarchicalorder of aggregation in AT, in which macroaggregates were thenucleus for microaggregate formation in the center of macroag-gregates (Oades, 1984). Similar to previously described models ofsoil aggregation (see Six et al., 2004, for a review), we suggest thatin a first stage following afforestation the organic amendmentquickly induced the formation of macroaggregates due to: a) anincrease in microbial activity, and b) inputs of binding agents likepolysaccharides (Díaz et al., 1994; Golchin et al., 1994). Over time,this initial effect of the organic amendment was gradually main-tained by fresh plant material entering the soil, derived from thegrowth of the planted vegetation (see discussion below). In a sec-ond stage, inside these macroaggregates, the presence of decom-posed organic matter, metabolites and biogenic products,polyvalent cations, and other binding agents promoted the solid-phase reaction between organic matter and clay and silt particlese leading to the formation of stable microaggregates (Edwards andBremner, 1967; Golchin et al., 1994). In treatment T, the soil con-ditions e very low soil organic matter, little microbial activity, andfew biomass inputs e were totally unfavorable for aggregates for-mation and the process unfolded very slowly.

4.2. Factors controlling changes in soil aggregation

In order to know the relative contribution of each factor to thesoil aggregation and the carbon stabilization and sequestration

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capacity in the afforested areas, we analyzed the changes whichoccurred after each treatment.

4.2.1. Quality and amount of soil organic inputsOrganic amendments significantly increased the percentage of

stable aggregates in the first years following the AT treatment(Querejeta et al., 2000). Similar results have been reported world-wide (Bartoli et al., 1992; Clark et al., 2009) and, specifically, underthe same environmental conditions and with the same organicamendments as ours (Roldan et al., 1996). It is worth mentioning,however, that not all organic amendments have the same effect onsoil aggregation (Clark et al., 2009). The ability to promote theformation of new macroaggregates depends on: a) the content oftransient binding agents such as polysaccharides or fresh plantmaterial, and b) the amounts of microbially available C that canpromote fungal proliferation (Lucas et al., 2014). In this experiment,the organic amendment had a high content of carbohydrates (seeQuerejeta et al., 1998); it is likely that this was a key factor in theinitial stages of macroaggregate formation due to its double actionas a binding agent and as a stimulating microbial resource.

Several studies have shown that the effects of soil organicamendments are temporary, mainly appearing in the first weekafter addition (Debosz et al., 2002; Clark et al., 2009). This isattributed to the rapid turnover of labile organic pools, as Díaz et al.(1994) reported for polysaccharides. In this study, afforestation plusa single initial amendment (AT) led to an increase in the soil OCsand OCsw fractions, while afforestation without organic matteraddition did not increase the OCs fraction and led to a reduction ofOCsw compared to the shrubland. These changes probably are aresponse to the higher biomass production, and thus litter inputs,in AT compared to the other treatments (Garcia-Franco et al., 2014).Other authors obtained similar results after afforestation onabandoned agricultural soils (Lagani�ere et al., 2010; Wei et al.,2013). In this way, the initial effects of the organic amendmenton soil aggregation continued for treatment AT due to the increasesin OC fractions.

Besides quantitative changes in OC fractions, the quality of OCsplays an important role in soil aggregation and C sequestration(Steffens et al., 2009). We found that the composition of OCs inafforested soils showed an increase in O-alkyl C, such as that foundin carbohydrates, with respect to the shrubland soil. The O-alkyl Ccompounds are considered as indicators of the amount of organicbinding agents, which improvemacroaggregate formation (Degens,1997). Several authors showed that carbohydrates were signifi-cantly correlated with aggregate stability (Martens andFrankenberger, 1992). Our results agree with those of Steffenset al. (2009), who found greater aggregate stability to be associ-ated with large contributions of O-alkyl C from the labile fraction ofsoil organic matter.

Altogether, our results suggest that the increase of the SOCfractions, mainly OCs and the higher carbohydrates concentrationin these fraction, after afforestation plus organic amendment led toan increase of the soil carbon sequestration capacity, induced bynew aggregates formation. An important proportion of this OCcame from microaggregates enriched in OC and occluded withinmacroaggregates e as can be deduced from the positive correlationbetween this occluded OC and both Oc fractions, especially OCs(Table 4). Other authors also obtained positive correlations be-tween labile C fractions and macroaggregates (Bhattacharyya et al.,2012).

4.2.2. Changes in microbial activity and structureWith regard to the implications of the microbial community for

soil aggregate formation and C sequestration, we must discuss twoaspects: a) microbial activity (hypothesis 3), and b) community

structure (hypothesis 4). Basal respiration, an estimate of the totalmicrobial activity in soils (Vanhala et al., 2005), was significantlyhigher in macroaggregates of afforested soils receiving amend-ments (AT), compared to the other treatments. Afforestation per-formed without amendments (T), however, led to a lowermacroaggregates basal respiration than in the shrubland. Similarly,in the literature the responses of microbial activity to afforestationare various. Several studies showed decreases in microbial activityin afforested areas (Goberna et al., 2007; Chen et al., 2008); incontrast, other authors reported increases inmicrobial activity afterafforestation (Mao and Zeng, 2010). This apparent discrepancy ismainly due to the previous use and characteristics of the soils, theafforestation method, or the stand age.

The tight correlations between basal respiration in macroag-gregates and the percentage of macroaggregates (>250 mm) in alltreatments suggest that this microbial activity could be an impor-tant factor in the new macroaggregates formation. In accordancewith these results, many studies have indicated the key role ofmicrobial populations in soil aggregate formation (Siddiky et al.,2012; Daynes et al., 2013). However, the correlations betweenbasal respiration in macroaggregates with the percentage of micro-within macroaggregates (BR-Mm) and basal respiration with OCassociated to micro-within macroaggregates (BR-OCMm), showedvery different behavior between the native shrubland and theafforested soils, with respect to aggregation processes and Csequestration. The strong, positive correlations between BR-Mmand BR-OCMm in soils AT and T suggest an active, microbial-induced process of microaggregates formation inside larger ag-gregates e much more active in AT as discussed above e whichprotects the OC associated with these microaggregates, increasingits turnover time and leading to present C sequestration in theafforested ecosystems.

These changes in SOM turnover induced by easily available Cinputs are widely known as the priming effect (Blagodatsky et al.,2010). As a result of priming, the decomposition of SOM by soilmicrobes is stimulated by the supply of fresh C as a source of energy(Fontaine et al., 2011; Van Groenigen et al., 2014). Paradoxically, inthis study the increase in microbial activity in the macroaggregatesled to an increase in C sequestration potential. This indicates thatthe SOM dynamic in the macroaggregates is controlled, at least inpart, by microbial populations e as has been shown by other au-thors (Baumann et al., 2013). Two mechanisms have been sug-gested to explain how this priming effect leads to C sequestration: i)the existence of a bank mechanism that regulates nutrients and Csequestration in soil: priming effect is low when nutrient avail-ability is high, allowing sequestration of nutrients and carbon; incontrast, microbes release nutrients from SOM when nutrientavailability is low (Fontaine et al., 2011), and ii) the MicrobialEfficiency-Matrix Stabilization, which integrates plant litterdecomposition with SOM stabilization: labile plants constituentsare the dominant source of microbial products. These microbialproducts of decompositionwould thus become themain precursorsof stable SOM by promoting aggregation and through strongchemical bonding to the mineral matrix (Cotrufo et al., 2013).

Our results, in agreement with both mechanisms, maycontribute to a more detailed knowledge of SOM stabilizationpathways in macroaggregates of semiarid forest ecosystems. Thebank mechanism can be corroborated by the comparison ofnutrient availability and SOM accumulation between the AT and Streatments (Table 1). Due to the high nutrient availability, thestimulation of SOM decomposition (priming effect) in AT was low,allowing C sequestration. In addition, the increase in OCs in soil ATwas a dominant source for microbial products of decompositionand fungal hyphae: these were the main precursors of SOM stabi-lization through promotion of macroaggregates formation. Inside

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these macroaggragates, the strong chemical bonding betweenorganic matter and mineral soil particles led to stable micro-aggregates formation, which was favored by the clay mineralogyand abundance of Ca2þ in the soil matrix.

Therefore, our results suggest a pathway for the physical-chemical protection of SOM and C sequestration, through the for-mation of OC-enriched microaggregates occluded in macroaggre-gates (Fig. 7). We hypothesize that this is a self-protection systemdeveloped by the soil, inside the macroaggregates, to offset thepotential effect on SOM decomposition induced by the increase ofmicrobial activity. This process was activated in the soil followingthe increase in the inputs of fresh plant residues after afforestationwith the AT treatment. Our results seem to confirm the hypothesis5 and show the importance of microbial activity enhancement inthe afforestation methodologies employed in semiarid areas withthe purpose of C sequestration.

By contrast, in the shrubland a negative correlation betweenbasal respiration in macroaggregates and the percentage of microwithin macroaggregates was found. This suggests that an aggre-gates breakdown process occurred, promoted by the microbial ac-tivity. The degree of conservation or loss of resources, such as soilnutrients, is considered to be crucial in dryland ecosystem dynamic(Scanlon et al., 2007). We hypothesized that this process wasinduced by a bank mechanism: due to the reduction of fresh litterinputs, because of degradation of shrubs by external stresses(Mayor et al., 2013), soil nutrient availability decreased (Bautistaet al., 2007) e promoting microbial decomposition of stable SOMand organo-mineral bonds, which led to aggregates disruption.Therefore, we consider that the key factor e for the activation ofeither the self-protection organic carbon system or the aggregatedisruption model ewas the input of plant litter into the soil, as thisregulates the soil food web (Fig. 7).

Fig. 7. Diagram showing the soil organic carbon dynamic in: (i) semiarid areas with a welldegraded (pathway 2).

In addition, these results suggest that the correlations betweenthe microbial activity in macroaggregates (measured as basalrespiration) and the percentage of microaggregates within mac-roaggregates and the OC concentration in microaggregates withinmacroaggregates could be valid indicators of SOC gains or losses.Positive correlations indicate soil C sequestration and negativecorrelations indicate soil C emission processes. The advantage ofthese indicators is that the measurement at a point in time allowsthe determination of the trend of a dynamic process, not needinglong time periods to establish the soil C dynamic in the ecosystem.Evidently, further research under different environmental condi-tions is needed to validate this hypothesis.

The afforestation treatments (mainly AT), led to long-term shiftsin the fungal community structure, diversity, and relative abun-dance of several major fungal taxa, compared to the referenceshrubland. However, the soil bacterial communities were not sosensitive to afforestation. The changes in the fungal communitystructure seem to have been mediated mainly by the shifts in theplant cover, due to the afforestationwith pine trees, as suggested bythe increase in the relative abundance of Agaricomycotina. Thistaxon includes ectomycorrhizal fungi that are associated with P.halepensis (Roldan and Albaladejo, 1994). This is in agreement withprevious studies which reported that bacterial communities pri-marily respond to changes in the physical-chemical characteristicsof the substrate, while fungal communities are more sensitive toland uses changes (Ros et al., 2006; Macdonald et al., 2009).

In our study, the distribution of aggregate-size classes correlatedsignificantly with the community structure of the soil fungi but notwith that of the soil bacteria. This agrees with previous surveys thatattributed a stronger influence on soil aggregation to fungi, relativeto bacteria (De Gryze et al., 2005; Zhang et al., 2012). Particularly,members of the Agaromycotina have been reported to produce

-preserved vegetation (pathway 1), and (ii) semiarid areas which vegetation has been

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considerable amounts of aggregate-stabilizing mycelia (Caravacaet al., 2002). We also detected that the fungal (but not the bacte-rial) community structure was significantly associated with thebasal respiration measured in the macroaggregates. This agreeswith the notion that fungi metabolize low quality substrates moreefficiently (Six et al., 2006) than bacteria do (Holland and Coleman,1987; Griffith and Bardgett, 2000).

Facedwith the question “were the changes in fungal communitystructure, after afforestation, involved in the promotion of soil ag-gregation?”, our findings suggest an affirmative response. Wefound the following changes in afforested areas, in comparison toshrubland: 1) an increase in Agaromycotina e a fungal group whichcan produce considerable amounts of aggregates-stabilizingmycelium (Caravaca et al., 2002), 2) a decrease in Chry-tridiomycota e a unicellular fungus unable to produce mycelia, and3) an increase in species richness. We think that these changesincreased the amount and diversity of biotic bonding agents andfostered the formation of macroaggregates. This affirmationmay besupported by the significant correlations found between the fungalcommunity structure and aggregate size distribution, and betweenthe fungal community structure and basal respiration in macro-aggregates, at the surface layer, in all the treatments tested.

5. Conclusions

Qualitative and quantitative changes in OC fractions linked tothe shifts in microbial activity within macroaggregates and fungalcommunity structure after afforestation, performed with an initialorganic amendment, promoted the formation of macroaggregatesoccluding and protecting OC-rich microaggregates inside. Theaccrual and physical-chemical stabilization of OC in this hierar-chical structure is a key aspect with respect to increasing ormaintaining soil C stocks. Overall, our results revealed that land-usechanges involving increases in: 1) sensitive OC fractions, and 2)fungal populations capable of producing large amount of mycelia,are suitable to prevent and mitigate the negative impacts of cli-matic change on soil quality.

In addition, we suggest that the correlations between the basalrespiration in macroaggregates and percentage of microaggregateswithinmacroaggregates could be an indicator of the organic carbondynamic in the soil. Further research is needed to validate thisindicator.

Acknowledgments

This research was found by the Spanish Research, Developmentand Innovation Plan IþDþI 2008-2011 (Project AGL2010-20941).We want to thanks Drs. Angelika K€olbl and Markus Steffens fromthe Research Department Ecology and Ecosystem Management(Techische Munchen Universitat, Germany) who help us in theRMN results interpretation. Our thanks to the technical staff of Soiland Water Conservation Group from CEBAS-CSIC, who help us inthe laboratory and field work.

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