phylogenetic and functional changes in the microbial community of long-term restored soils under...

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Soil Biology & Biochemistry

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Phylogenetic and functional changes in the microbial community of long-termrestored soils under semiarid climate

Felipe Bastida*, Teresa Hernández, Juan Albaladejo, Carlos GarcíaDepartment of Soil and Water Conservation, CEBAS-CSIC, Campus Universitario de Espinardo, Murcia 30100, Spain

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a r t i c l e i n f o

Article history:Received 21 February 2013Received in revised form24 April 2013Accepted 28 April 2013Available online xxx

Keywords:Bacterial communityFunctionalityFungal communityOrganic amendmentPyrosequencingSemiarid soil

* Corresponding author. Tel.: þ34 968396106; fax:E-mail addresses: [email protected], felipebast

0038-0717/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.soilbio.2013.04.022

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Please cite this article in press as: Bastida, F.,under semiarid climate, Soil Biology & Bioch

a b s t r a c t

In semiarid climates, soils are often found in pre-desertic states with constrained vegetation, organicmatter and ecosystem functionality. These limitations negatively impact soil microbial communitieswhich are important drivers of biogeochemical processes and strongly influence soil quality. The long-term impacts of restoration on the phylogenetic structure and metabolic functionality of soil microbialcommunities were studied in a representative degraded field area located in southeast-Spain. Restora-tion was undertaken 25 years ago by the singly application of two doses of organic domestic waste at65 Mg ha�1 (LD plots) and 195 Mg ha�1 (HD plots). Control soils without amendment were also eval-uated. Pyrosequencing of 16S- and 18S-rRNA genes did not reveal significant differences in phylogeneticdiversity between restored and control soils. However, principal coordinates analysis of unweightedUnifrac distances showed variation in the structure of bacterial and fungal communities of HD plots. Thenumber of Alpha-proteobacteria sequences was higher in HD plots than in LD and control plots, whileActinobacteria abundance diminished in HD plots. In contrast to Basidiomycota, the number of Ascomy-cota sequences responded positively to restoration. Changes in microbial phylogenetic structure wererelated to changes in functional structure established by multivariate analysis of community-level-physiological profiles. Interestingly, despite the absence of phylogenetic diversity, restorationdecreased the catabolic diversity in HD plots. This effect is likely due to the aboveground plant influencesin restored plots. Overall, in the long-term, soil restoration under semiarid conditions did not increasemicrobial diversity but influenced microbial community structure and functionality.

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1. Introduction

The loss of organic matter under semiarid conditions is one ofthe main threats for soil degradation and desertification(Albaladejo et al., 2000). Soil degradation due to organic matterdepletion is known to reduce ecosystem services performed bysoils (Lal, 2004). The extent of this problem is amplified in arid andsemiarid regions, where climatic conditions inhibit the develop-ment of plant cover and the consequent inputs of organic matter(García et al., 1992). Instead, soils advance toward desertificationand damage to the soil ecosystem is expected (Albaladejo and Díaz,1990). In such scenario, the addition of exogenous organic matter isconsidered as an invaluable tool not only for restoring soil qualitybut also to fixing C in such soils (Bastida et al., 2008a); for thisreason, it has been used as a strategy for fighting against degra-dation and for the restoration of soil quality.

þ34 [email protected] (F. Bastida).

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105106107108

et al., Phylogenetic and functemistry (2013), http://dx.do

Microbial communities perform biochemical reactions and ul-timately govern soil quality (Nannipieri et al., 1990). Soil microbiotalargely drives geochemical cycling and their activities are crucial tothe productivity of terrestrial ecosystems (Buckley and Schmidt,2003). Following organic soil amendments, soil microbial com-munities usually experience increases in biomass and activity thatrelease substrates for the further vegetal growth contributing tosoil sustainability (Bastida et al., 2008a).

Previous evidence for short-term changes in microbial com-munity structure after organic restoration was mainly based ondenaturing gradient gel electrophoresis (Crecchio et al., 2004; Roset al., 2006). However, a detailed genomic picture of microbialchanges in long-term remediated soils is not available and severalauthors claimed the need for long-term manipulation studies tounderstand the environmental and biological controls of soilorganic matter, thereby improving predictions of the response ofecosystem functionality to global change (Schmidt et al., 2011).Nevertheless, microbial diversity is complex, and 1 g of soil maycontain billions of individuals encompassing thousands of differentspecies (Torsvik and Ovreas, 2002). Recently, next-generation

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ional changes in the microbial community of long-term restored soilsi.org/10.1016/j.soilbio.2013.04.022

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F. Bastida et al. / Soil Biology & Biochemistry xxx (2013) 1e102

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sequencing techniques have started to provide a deep under-standing of the composition of the soil microbial communities(Fierer and Jackson, 2006; Acosta-Martínez et al., 2008), yet thisunderstanding is still limited on how to correlate changes in mi-crobial community on the genomic-level with measures of meta-bolic functionality and soil quality.

The current study helps to close this gap using next-generationsequencing to provide a detailed analysis of the structure, diversityand taxonomic composition of both bacterial and fungal commu-nities in a control and restored soils. Moreover, biochemical-basedmethods will provide a functional overview of the processespotentially taking place as a consequence of soil restoration.Enzyme activities (Nannipieri et al., 1990) and community-levelphysiological profiles (Garland, 1996) will assess the potentialability of soil microbial communities to metabolize a range ofsubstrates (Oren and Steinberger, 2008). We believe that the jointuse of both genomic- and biochemical-techniques will enrich ourunderstanding of the microbial ecology of soil restoration insemiarid, pre-desertic ecosystems.

Here, we focus on a long-term restoration project located insoutheast Spain where organic amendments were added at twodoses, in one pulse 25 years ago. The field site is located in adegraded soil formed by a marsh lithological substrate. Thetremendous scarcity of water and the low organic carbon contentmake this site as an attractive referent for the study of microbialdynamics in desert-like ecosystems and their long-term responsesto restoration using external sources of organic matter. The envi-ronmental conditions of the study area are widely representative ofother semiarid sites. Previous investigations at the same site havedemonstrated successful effects of the restoration in terms of soilproperties (Stocking and Albaladejo, 1994), development of vege-tation (Díaz et al., 1997), and increases in microbial biomass andrelatedmicrobial activity (Bastida et al., 2008b). In the presentwork,we aim to: i) examining the long-term influences of organicamendment on the microbial diversity and community-structureboth at phylogenetic and functional levels; and ii) describing themain microbial phylum associated with dry-land restoration.Considering the previous knowledge generated at this site and thefact that we observed greater plant cover and carbon storage afterorganic amendment, the following hypotheses were assessed: 1)the higher soil organic matter in restored sites (25 years) wouldprovide a high amount of resources harboring a more diverse mi-crobial community and a change in community structure; 2) vegetalgrowth and plant community could influence bacterial and fungalcommunity structures and, if so, some microbial groups would bepreferentially selected in restored sites; and 3) the increasedabundance of certain microbial groups after long-term restorationwould be associated with variations in the functionality of soil.

2. Material and methods

2.1. Study area, experimental design and sampling

The experimental plots are located in Murcia, in the south-eastern region of Spain, within an area that is largely affected by soildegradation processes. The climate is Mediterranean semiarid. Themean annual rainfall is 300 mm and potential evapotranspirationreaches 1000 mm year�1. The mean annual temperature is 19 �C.The studied soil is poorly developedwith an ochric epipedon as solediagnostic horizon, and is classified as a Xeric Torriorthent (SoilSurvey Staff, 1998). It has not been used for agricultural purposes.Soil is characterized by amarsh lithological substrate and has a verylow total organic carbon content and high electrical conductivity.These characteristics make this soil as adequatemodel for the studyof soil degradation and restoration processes.

Please cite this article in press as: Bastida, F., et al., Phylogenetic and functunder semiarid climate, Soil Biology & Biochemistry (2013), http://dx.do

In October 1988, nine 30 m2 plots were established in this areaand three different treatments were carried out: i) application of alow dose of organic domestic solid waste (DSW) at 65 Mg ha�1 (LDplots); ii) application of a high dose of DSW at 195 Mg ha�1 (HDplots); and iii) soil without amendment (Control plots). All treat-ments were performed in triplicate. The DSW was used to amendthe soil after 15e20 days of natural maturation. The inert and grosscomponents of the DSW were removed by sieving before theremaining organic fraction was incorporated into the top 15 cm ofsoil using a rotary hoe. Further characteristics of thesematerials canbe found in Albaladejo et al. (1994). The control plots, without DSWamendment, were also tilled using a rotary hoe. The DSW wasadded to the soil once, at the beginning of the experiment, 25 yearsago.

Data presented here correspond to the mean and standard de-viation of triplicate values from restored and control plots. For eachplot, eight soil subsamples were randomly collected in autumn2011with hand driven probes (10 cm diameter) to a depth of 15 cm.These eight subsamples were mixed to constitute a single sampleper plot. The samples were sieved to<2mm and stored at 4 �C untilbiochemical analysis. Samples used for molecular analysis werefrozen at �80 �C. Before sieving, all debris and plant material wereremoved. The percentage of plant cover was estimated using thegrid-line intersect method. Vegetation diversity was calculatedusing the ShannoneWeaver index (H).

2.2. Chemical and physico-chemical analyses

The electrical conductivity and pH weremeasured in a 1/5 (w/v)aqueous extract, in a Crison conductivimeter and pH meter,respectively. Total N was determined using Kjeldahl’s method asmodified by Bremner and Mulvaney (1978). Total organic carbon(TOC) was determined by oxidationwith K2CrO7 in an acid mediumand titration of the excess dichromate with (NH4)2Fe(SO4)2(Yeomans and Bremner, 1989).

Awater extract was obtained by shaking for two hours amixtureof soil and distilled water (1:10 soil:water ratio), centrifuging, andfiltering. In this extract, water-soluble C (WSC)was determined by aC analyser for liquid samples (Shimadzu 5050A). Humic substanceswere extractedwith a 0.1M, pH 9.8 sodium pyrophosphate solution(w/v ratio ¼ 1:10), by mechanical shaking for 4 h. Humic substanceC was determined in this extract by a C analyser for liquid samples(Shimadzu 5050A).

2.3. Basal respiration, enzyme activities analyses and communitylevel physiological profiles (CLPPs)

Soil respiration was analyzed by a headspace analyzer (Check-mate II, PBI Dansensor, Denmark) (Bastida et al., 2008a). The b-glucosidase activity was determined according to Eivazi andTabatabai (1987). Invertase activity was measured by the methodof Hoffmann and Pallauf (1965) as modified by García Alvárez andIbáñez (1994).

Biolog ECOMT plates (Biolog, Inc., Hayward, CA, USA) containing31 different C sources and water were used to determine thecommunity level physiological profiling based on carbon sourceutilization. One gram soil samples were shaken in 10 ml of sterilewater at 150 rpm for 15 min at 4 �C. After incubation, liquid extractwas obtained by centrifuging at 15,000 g during 10 min and 100 mlwere inoculated in each plate well. Biolog plates were incubated at28 �C during 7 days. Considering the microbial biomass amount,cell suspensions were diluted to equal biomass with the aim toavoid interferences of the number of cells in the oxidation of sub-strates. The rate of utilization was indicated by the reduction oftetrazolium, a redox indicator dye, which changes from colorless to


Table 1Soil characteristics, respiration and enzyme activities in control and restored plots.

Control plots LD plots HD plots

Mean SD Mean SD Mean SD

pH 7.44 a 0.07 7.67 b 0.03 7.82 c 0.005TOC 6.20 a 0.23 10.0 b 0.26 16.8 c 0.07Nt 0.70 a 0.10 1.51 b 0.42 2.52 c 0.40WSC 140.11 a 20.52 194.11 ab 33.84 214.55 b 28.42HS 2556.93 a 331.01 6091.30 b 622.73 7851.61 c 197.36BR 4.96 a 0.27 9.00 b 2.32 b 15.67 c 2.80DH 1.15 a 0.21 3.58 b 0.03 3.37 b 0.33bG 0.61 a 0.16 3.74 b 0.09 3.72 b 0.35INV 1.29 a 0.57 5.11 b 0.57 5.65 b 0.24VC 41.20 a 0.28 41.67 a 0.81 58.15 b 1.75Hveg 1.28 a 0.18 1.40 ab 0.07 1.81 b 0.07

TOC (Total Organic C, g kg�1), Nt (Total Nitrogen, g kg�1), WSC (Water-soluble C,mg C kg�1), HS (Humic substances C, mg C kg�1), BR (Basal respiration, mg CO2e

C kg�1 day�1), DH (Dehydrogenase activity, mg INTF g�1 h�1), bG (b-glucosidaseactivity, mmols PNP g�1 h�1), INV (Invertase activity, mg glucose g�1 5 h�1), VC(Vegetal cover, %), Hveg (Shannon index for vegetal diversity Q2).

Table 2Functional and phylogenetic diversity, and substrate utilization in control andrestored soils.


Mean SD Mean SD Mean SD

Functionala

Hbio 2.98 b 0.02 2.92 b 0.08 2.56 a 0.14Evenness 1.93 a 0.11 2.00 a 0.09 1.94 a 0.21Richness 29.67 b 2.31 30.00 b 1.73 21.33 a 3.21Cellobiose 2.13 a 0.08 1.83 a 0.56 3.32 b 0.80Mannitol 4.28 b 1.00 3.29 ab 0.81 2.05 a 0.194-OH-benzoic acid 0.57 a 0.08 0.15 a 0.04 3.45 b 0.62a-Keto-glutaric acid 0.04 a 0.01 0.02 a 0.02 2.37 b 1.01L-Serine 0.48 a 0.07 0.49 a 0.20 4.17 b 0.31Phylogeneticb

Bacterial diversity (Hbac) 10.74 a 0.84 10.92 a 0.18 10.14 a 1.08Fungal diversity (Hfun) 5.91 a 1.86 6.68 a 0.57 6.33 a 1.15

a Substrate values are given as AWCD (average well-color development).b Shannon index calculated from the relative phylotype abundance for bacteria

(Hbac) and fungi (Hfun).

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purple. Data were recorded during one week at 590 nm in anautomated plate reader (Multiskan Ascent) until a plateau wasreached. Microbial activity was expressed as average well colordevelopment (AWCD) as described by Garland (1996).

2.4. DNA isolation and amplification

DNAwas isolated from 1.0 g of each homogenized sample usingthe BIO101 FastDNA kit (La Jolla, CA, USA). DNA concentrationswere determined using a NanoDrop 2000c (Thermo Scientific,Wilmington, USA). Recovered DNA was amplified using barcoded16S rDNA and 18S rDNA pyrosequencing tags. A 16S rDNA genefragment was amplified using the primers BSF8 and USR515 andconditions established by Bibby et al. (2010). A 18S rDNA genefragment was amplified using the primer set nu-SSU-0817-59 andnu-SSU-1196-39 and conditions established by Borneman andHartin (2000). All amplicons were cleaned and pooled in equi-molar concentrations into a single tube before sequencing on aRoche 454 GS FLX using titanium chemistry.

2.5. Processing of pyrosequencing data

Raw read output was quality filtered by discarding reads with<200 bp and average quality score <25. Filter-pass reads wereparsed into their respective sample-specific barcode bins only ifthey matched the entire forward primer and barcoded sequence.Forward and reverse primers and barcodes were removed afterbinning. After the quality filtering, all samples were rarefied to1200 sequences per sample (in the case of 16S rDNA) and 7300sequences per sample (in the case of 18S rDNA gene). All sequenceanalyses were conducted using the QUIIME pipeline (Caporasoet al., 2010). Phylotypes were selected at the 97% sequence simi-larity level and the taxonomic identity was determined using theRDP scheme. Rarefaction curves were constructed using theRarefaction tool from the RDP pipeline. The slope of rarefactioncurves was similar for all treatments and no differences appearedbetween treatments for the number of OTUs at each singlenumber of reads (Fig. S1, Supplementary information). The rela-tive abundance of the different phyla (or other taxonomic cate-gories) in each of the 9 samples was calculated. Pairwise distanceswere determined between communities using the unweightedUnifrac method, a metric that measures the phylogenetic relat-edness of whole communities and is well suited for comparingbeta-diversity patterns between complex bacterial communities(Lozupone et al., 2011).

2.6. Statistical analysis

Taxonomic and catabolic diversity for each sample was esti-mated using the ShannoneWeaver index (H) as calculated eitherfrom phylotype relative abundances (Fierer et al., 2012) ornormalized AWCD data after 108 h of incubation in Biolog ECO MTplates (Insam and Goberna, 2004). Substrate richness and evennesswere calculated as described by Zak et al. (1994).

Microbial community structure was visualized using principalcoordinate analysis (PCoA) (Fierer et al., 2012) of: i) UnweightedUnifrac distances for the community phylogenetic structure basedon 16S and 18S gene data; ii) CLPPs to determine the functionalstructure of the community. The AWCD of the five carbon sourcesreceiving the higher factor loading in this multivariate analysiswere selected and showed in Table 2 as an indicative of the pref-erential potential usage of carbon sources.

All analyses were performed in triplicate (n ¼ 3), includingmolecular analyses. Statistical significance was determined usingone-way ANOVAs for each sampling. Post-hoc analysis (P < 0.05


level) was performed using the Tukey HSD test. ANOVA of groupcentroids on principal coordinate one was also performed on thecoordinates of the principal components in order to discriminatetreatments with regard to the functional and phylogenetic struc-ture of the microbial community. Correlation analyses were per-formed using Pearson’s method.

3. Results

3.1. Carbon and nitrogen content, microbial activity and vegetalbiomass

The amounts of total organic carbon and nitrogen, water-solublecarbon, and humic-substances carbon were significantly higher inHD plots versus the control plots (P < 0.05). Total organic carbonand humic substance C were significantly higher in LD plots versusthe control plots (Table 1).

Basal respiration was significantly higher in HD plots comparedto LD plots (P < 0.05) and, in both cases, it was higher than thecontrol plots. Restored plots (LD and HD) showed significant highervalues of hydrolase activities involved in the carbon cycle (b-glucosidase and invertase) than the control (Table 1). However, theenzyme activities in the restored plots were not significantlydifferent from each other.

Vegetal cover resulted significantly higher in HD plots thancontrol and LD plots (P< 0.05). Plant diversity (Hveg) increased withrestoration process, reaching a maximum in the HD plots (Table 1).



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Briefly, plant community was dominated by Gramineae species (upto 75% of the plant cover of each plot). The relative abundance ofGramineae species differed between treatments. For instance, theabundance of Bromus fasciculatus and Lygeum spartum was higherin HD than in control and LD plots and reached up to 80% of theplant cover in HD plots. Contrarily, the abundance of Piptatherummiliaceum was higher in control plots (up to 50%) and decreasedwith soil restoration.

3.2. Barcoded pyrosequencing of 16S and 18S rRNA genes,community structure and diversity

A total of 25,800 16S rRNA gene sequences were retained afterfiltering, corresponding to 114 bacterial classes. A total of 11,100 18SrDNA gene sequences passed quality control and represent 272fungi classes. The slopes of the rarefaction curves were similar forall samples regardless of treatment (Fig. S1, Supplementaryinformation). In order to minimize any bias in the distribution oftaxa, equal sequence numbers were randomly selected for alltreatments for downstream analysis (Fierer et al., 2012).

Principal coordinates analysis revealed that bacterial and fungalcommunity structure in HD plots were significantly different fromthose in control and LD plots, while community structures withinLD and control plots clustered together (Fig. 1). Accordingly, ANOVAof group centroids on principal coordinate one showed that HDplots were significantly different from the control and LD plots.According to the Shannon (H) and Chao (Chao and Bunge, 2002)indexes, there were no significant differences between bacterialand fungal diversity among the restored and control plots (P< 0.05)(Table 2). These results are supported by the absence in the number

PC1 (16.36 %)

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of OTUs per number of reads, as shown in rarefaction curves(Fig. S1, Supplementary information).

3.3. Composition of the bacterial communities

Actinobacteria and Proteobacteria were the dominant in controland restored soils. Within the Proteobacteria, Alpha-proteobacteriashowed the highest relative abundance of sequences, comprisingup to 29.38% of the total. The relative abundance of Alpha-proteo-bacteria was significantly higher (P < 0.05) in HD versus LD plots,with control plots showing the lowest numbers (Fig. 2; Table S1).For Actinobacteria, the relative abundance was lower (P < 0.05) inHD plots (32.9%), compared to LD plots (40.6%) and control (39.9%)plots. The relative abundance of sequences from other phylum suchChloroflexi (up to 7.5%), Planctomycetes (up to 3.4%), Gemmatimo-nadetes (up to 4.6%), or Acidobacteria (up to 3.0%) was lower thanthat of Actinobacteria and Alpha-proteobacteria lineages. Moreover,the relative abundance of these phylawas not significantly differentbetween control and restored plots. However, Bacteroidetes abun-dance was significantly higher in HD (3.7%) compared to LD (2.4%)and control (2.8%) plots (Fig. 2; Table S1). Within Alpha-proteo-bacteria, Rhizobiales and Rhodospirillales were the most abundant.Rhizobiales sequence numbers were significantly higher in HDplots. Actinobacteria was dominated by Actinomycetales and Solir-ubrobacterales, constituting up to 74.4% and 17.7% of the sequences,respectively (Fig. 2; Table S1). However, no significant differenceswere detected, among the restored and control areas, for distinctorders within the Actinobacteria.

3.4. Composition of fungal community

The fungal community was dominated by Ascomycota andrelative abundances were significantly higher in HD plots (93.4%)compared to LD (87.9%) and control (86.0%) plots (Fig. 3; Table S2).Contrarily, the relative abundance of Basidiomycota was lower inrestored plots (4.6 and 1.4%, respectively for LD and HD plots) thanin control (7.2%).

Within the Ascomycota, there were no significant differencesamong treatments, but a slightly higher relative abundance ofPezizomycotinawas observed in control plots versus restored plots.Within Basidiomycota, the class Agaricomycetes was the overalldominant phylotype and the relative number of sequences waslower in HD plots (31.2%) than in control (69.1%) and LD plots(83.0%) (P < 0.05) (Fig. 3; Table S2). In contrast, Tremellomycetessequence numbers increased from control to HD plots.

3.5. Community level physiological profiles (CLPPs)

The functional diversity and community structure wereanalyzed using Biolog ECO plates. Based on carbon utilization pat-terns the catabolic diversity was estimated using the ShannoneWeaver index (Hbio). This index was significantly lower in HD plotsversus control and LD plots (P < 0.05) (Table 2). No significantdifferences were detected between control and LD plots. Therichness (number of substrates utilized) was significantly lower inHD than control and LD plots (P < 0.05) (Table 2).

The functional structure of the microbial community wasascertained using principal coordinates analysis (PCoA) of thenormalized AWCD values for each single substrate (Fig. 4). Principalcomponent 1 accounted for 25.3% of the total systemvariance, withHD plots notably separate from LD and control plots (Fig. 4). The topfive significant loadings substrates from the PCoA were: cellobiose(�0.90), mannitol (0.87), 4-OH-benzoic acid (�0.88), a-keto-glu-tarate (�0.85), and L-serine (�0.85). The AWCD values of thesesubstrates are shown in Table 2. Cellobiose, 4-OH-benzoic acid, a-



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Fig. 2. Changes in the relative abundance of bacteria (a), Alpha-proteobacteria (b), and Actinobacteria (c) in control- and restored-plots. Statistical differences are shown in Table S1(Supplementary information).


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keto-glutarate acid and L-serine had higher AWCD in HD plotscompared to LD and controls plots (Table 2). Interesting, theoxidation of mannitol was significantly lower in HD versus controlplots.

4. Discussion

The ancient addition of exogenous organic matter to the soil in1988 initially provided substrates for microbial and vegetal devel-opment and resulted in improved soil quality indicators (Albaladejoet al., 1994). As observed in Table 1, the increase in the abovegroundbiomass in the restored plots has continuously provided carbon andnitrogen input to soil and served to stimulate microbial activity. In


particular, increased enzyme activity (i.e. invertase and b-glucosi-dase) and basal soil respiration rates are still noticeable.

4.1. Structure and diversity of the microbial communities.Taxonomical and functional perspectives

The development of plant biomass is fundamental for soilrestoration and strongly influences microbial community dynamics(Williams et al., 2013). Both plant abundance and diversity mayexert controls on the belowground microbial community, essen-tially through plant debris and deposition of phytochemicals withinthe rhizosphere (Barea et al., 2002). However, the nature of plantemicrobe interactions is not clear and especially unknown in



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Fig. 3. Changes in the relative abundance of fungi (a), Ascomycota (b), and Basidiomycota (c) in control and restored plots. Statistical differences are shown in Table S2(Supplementary information).


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semiarid areas, precisely where ground cover limits ecosystemsustainability. In our case, vegetal cover and diversity respondedpositively to organic amendment and increased proportionallywith the initial organic amendment dosage.

The absence of significant differences in bacterial and fungaldiversity, as established by 16S and 18S rDNA, contrasted to theincreased plant diversity observed after 25 years (Table 1). Like-wise, Fierer and Jackson (2006) did not found parallelism betweenplant and bacterial diversity, concluding that controls on plant di-versity and microbial diversity may not be the same and that oneshould not necessarily expect higher levels of bacterial diversitywhen plant diversity is also higher. More interestingly, consideringthat carbon availability is the major limiting factor for soil


sustainability in semiarid areas (García et al., 1992), it is expectablea higher phylogenetic diversity in treatments with the highestamount of resources (such as carbon and nitrogen) as a conse-quence of a higher vegetal development (HD plots). However, nosignificant correlation (P < 0.01) was detected between totalorganic carbon, nitrogen, and diversity indices (H0) for bacterial orfungal communities. Additionally, despite pH has been described asa main driver of microbial diversity at different scales (Fierer andJackson, 2006; Lauber et al., 2009; Baker et al., 2009; Shen et al.,2013), we did not find significant correlations between pH andphylogenetic diversity. These results suggest that biodiversity is notsolely controlled by resource amounts or pH in semiarid soils.Instead, lithological substrate, environmental factors (such the high


PC1 (25.28 %)

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0,0

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Fig. 4. PCoA illustrating changes in microbial community structure for catabolic AWCDnormalized data. Legend: C (Control plots); ; (LD plots); B (HD plots).


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temperature and scarcity of water) or biotic competitiveness mayexert control of the microbial diversity (Girvan et al., 2003; Fiererand Jackson, 2006). Abiotic factors tend to be large scale phe-nomena in the control of soil microbial community (Turbé et al.,2010) and the hard environmental conditions in this pre-deserticregion can over-control the diversity of soil microorganisms.

Despite the fact that the restored soils (HD and LD plots) andcontrol plots contain the same level of bacterial and fungal phylo-genetic diversity, the structures of these communities differsignificantly after 25 years. Different authors have observed achange in microbial community structure after short-termamendments (Ros et al., 2006; Innerebner et al., 2006) but resultsdescribing long-term changes are very limited. The variations in thecarbon and nitrogen content and pH after organic amendments,and the consequent plant development can explain the changes inthe structure of microbial community. This assessment remainsclear when analyzing the Pearson correlation coefficients betweenthe calculated Unifrac distances with soil properties. Bacterial andfungal community structures were significantly correlated to pH(Rpearson 0.83, P < 0.01 and Rpearson �0.93, P < 0.01 for bacteria andfungi, respectively). The relation between organic carbon and totalnitrogen with the structure of bacterial community revealednegative correlation coefficients, while positive coefficients wereobserved in the case of fungi. Overall, these results stress the sig-nificant role of pH and nutrients in shaping both bacterial andfungal community structures. In contrast, Lauber et al. (2008) founda marked influence of pH in bacterial community while fungalcommunity was related to nutritional variations but not to pH.Besides the influence of edaphic factors and plant growth afterrestoration, the different composition of plant community mightalso partially influence the structure of the belowground microbialcommunity (Marschner et al., 2001; Bastida et al., 2008a; Williamset al., 2013).

It can be expected that variations in the taxonomical communitystructure may be related to differences in the functional ability ofsoil microbial communities. From a statistical point of view, therelationship between the microbial community structure at thegenomic level and the changes in biochemical functioning of soilsare supported by significant correlation coefficients (P < 0.05) be-tween axis 1 of the PCoA, the five major carbon source loadings inthe CLPPs, and the catabolic diversity (Hbio).

The functional information obtained from the Biolog plates canbe summarized in three points. First, as supported by themoleculardata, functional community structure was different in HD plotscompared to the control and LD plots. Second, cellobiose and


mannitol were observed within the top five substrates scored in theprincipal coordinate analysis of CLPP data. This result points to amajor impact of these dominant-plant compounds on the func-tionality of microbial community. Cellobiose is a product formed bycellulose degradation and mannitol has been described as animportant sugar of plant origin (Loescher et al., 1992). The use ofcellobiose was more efficient in HD than LD and control plots whileoxidation of mannitol was highest in control plot. We suggest thatthe bacterial community in HD plots is more specialized for thedegradation of plant remains with high content in cellulosedegrading products (such cellobiose) than mannitol. Third, thefunctional diversity was lowest in the HD plots as a consequence ofthe lower number of substrates utilized (richness) in comparison tocontrol and LD plots. Functional diversity was negatively correlatedwith total organic C (Rpearson �0.85, P < 0.01) and total N(Rpearson �0.73, P < 0.01). As mentioned above, this could be aconsequence of an adaptation due to abundant plant debris in HDareas. However, microbial communities in LD and control plotsmaybe considered as more generalists. These results contradict withseveral studies considering short-term changes that point to anincrease in soil functional diversity after recent or repeated organicamendment (Gómez et al., 2006; Ros et al., 2006; Hu et al., 2011). Itis likely that opportunistic populations contribute to the increasedfunctional diversity in the short-term due to a richer diversity ofcarbon sources derived directly from organic amendments.

At ecological level, diversity provides insurances against largechange in ecosystem processes (Mooney and Gabriel, 2005) and ithas been stressed that microbial diversity at a functional levelrather than at the phylogenetic level is crucial for the long-termsustainability of an ecosystem (Wang et al., 2011). However, thehigher functional diversity observed in control compared to HDplots could also be seen as a potential benefit. Our highly degradedsoil still keeps the metabolic capacity to process a wide range oforganic substrates but the microbial biomass and the overall rate ofactivity resulted higher in HD plots than in control and fosterbiogeochemical cycling and the sustainability of ecosystem. Recentstudies have also found that long-term maintenance of bare soilconditions did not decrease functional diversity (Hirsch et al., 2009;Guenet et al., 2011). Guenet et al. (2011) found that the productionof carbon pools steaming from microbial turnover may result in alow but constant flow of nutrients that sustain a diverse microbialmetabolism in a bare soil.

4.2. Composition of bacterial and fungal community

Changes in community composition, rather than diversity are ofgreatest importance for carbon dynamics (Nielsen et al., 2011).Different authors have found changes in the microbial communitycomposition after soil restoration (Innerebner et al., 2006; Roset al., 2006). At the short-term, these changes are due mainly tonutritional content improvements of soil and to the development ofopportunistic populations. Long-term changes may be due togreater plant development (García et al., 1994) and changes in plantcommunity structure (Marschner et al., 2001; Bastida et al., 2008a).

Water-soluble C contains labile substrates that are derived fromplant rhizodeposition and may have long-term influences on mi-crobial community (Eilers et al., 2010). The amount of availablecarbon increased with organic amendment, even after 25 years(Table 1). Precisely, copiotrophic organisms are defined as thosethat thrive in conditions with elevated C availability. Certain bac-terial taxa such Beta-proteobacteriamay be considered copiotrophs(Fierer et al., 2007; Langenheder and Prosser, 2008; Fierer et al.,2012). However, we did not observe a positive response of therelative abundance of sequences of Beta-proteobacteria or Actino-bacteria to soil organic restoration after 25 years. Conversely,



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Bacteroidetes, Planctomycetes and Alpha-proteobacteria were themost abundant in HD plots, the same plots that contain the highestamounts of aboveground biomass. In all cases, the proliferation ofthese groups was statistically correlated with total organic C andtotal nitrogen (P < 0.05). In contrast, Knelman et al. (2012) did notfind positive correlation between organic carbon fractions andnutrients and bacterial community composition in a recently de-glaciated soil. Our findings highlight the role of organic carbonthat exerts a deep control on the dynamics of certain microbialgroups in semiarid soils.

Alpha-proteobacteria and Actinobacteria comprised the mostabundant bacterial phyla in this semiarid soil. Rhizobiales, withinthe Alpha-proteobacteria class, also responded positively to thetreatment. Members of Rhizobiales are rhizospheric-plant pro-moting bacteria (Barea et al., 2002), and it is therefore logical to findan increase in the relative abundance of this group in HD plots,where plant growth is also highest. Knelman et al. (2012) found ahigher relative abundance of Alpha-proteobacteria and, particularly,Rhizobiales in vegetated soils.

On the basis of microbial competitiveness, it can be hypothe-sized that the development of Alpha-proteobacteria in restored soilsmay occur at expenses of the decreased abundance of Actino-bacteria in HD plots. Actinobacteria has been described as a domi-nant group in soils under desertic conditions with low nutritionalcontent (Fierer et al., 2012; Wang et al., 2012), as those found incontrol plots. Similarly, Köberl et al. (2011) found a decrease in therelative abundance of Actinobacteria after long-term organicfarming. Interestingly, the decrease in the abundance of Actino-bacteria in HD plots followed the same decay in the abundance ofone of the most dominant plant species, P. miliaceum. Although anunequivocal link between both cannot be established, these resultsreinforce the relationship between plant and microorganisms(Barea et al., 2002).

Bacteroidetes constituted a minor group in comparison to Acti-nobacteria or Alpha-proteobacteria. In agreement with our results,an increase in the relative abundance of Bacteroidetes phylotypeswas observed by other authors after short-term organic restoration(Nemergut et al., 2008; Cytryn et al., 2011) and this trend mimicsalso the patterns of some dominant plant species (B. fasciculatusand L. spartum). Members of Bacteroidetes are often involved in thedegradation of bio-macromolecules such as proteins, cellulose,chitin, pectin, agar or starch (Hugenholtz et al., 1998) and morerecalcitrant compounds (Lipson and Schmidt, 2004). Planctomy-cetes constituted also a minor component of the community.However, it has been demonstrated that soil management andcompost addition may influence Planctomycetes community(Buckley et al., 2006). Other group that represented only minorabundance was Acidobacteria. The number of sequences of thisphylum was not correlated with nutrient level but did so with pH(Rpearson 0.74, P< 0.05) as found by Chaudhry et al. (2012). The highpH of this soil (around 7.5) may be a hostile environment for thisgroup. Contrarily, Acidobacteria represented a very high number ofsequences (up to 30%) in soils with pH below 6.5 (Eilers et al., 2010;Fierer et al., 2012).

Soil harbors a phylogenically diverse community of saprotrophicorganisms that mediate the biogeochemical cycling of carbon andnitrogen, with fungi playing a paramount role (Zak et al., 2011). Asindicated above, we did not observed variations in fungal diversitybut fungal community structure did differ between treatments.Ascomycota dominated the fungal community in this semiarid soil,as described in other soils by Schadt et al. (2003).

Stursova et al. (2012) found that Ascomycota are more involvedin cellulose decomposition compared to Basidiomycota by the DNA-stable-isotope-probing of 13C-enriched-cellulose. Hannula et al.(2012) showed that Ascomycetes rapidly metabolize organic


substrates flowing from the root into the rhizosphere. In our study,the restoration, via the development of plant cover, increasedAscomycota numbers in HD plots while reducing the Basidiomycotapopulations. Positive correlation coefficients (P < 0.05) were foundbetween total organic C, total nitrogen, and humic-substances C forAscomycota; while negative coefficients (P < 0.05) were observedfor Basidiomycota. In detail, humic-substances C but not water-soluble C was significantly correlated with the relative abundanceof these fungi (P < 0.05). This result supports the intrinsic rela-tionship between fungi and the stable carbon pool in soil. Indeed, itis understood that fungi are the main producers of laccases, en-zymes that strongly impact the turnover of soil organic matter andcarbon stabilization processes (Baldrian, 2006; Kellner et al., 2009).

In comparison to Ascomycota, Glomeromycetes represented aminor phylum in this soil and their abundance was reduced in HDin comparison to control and LD plots. This fungal class includesarbuscular mycorrhizal fungi symbiotically living with plants(Alguacil et al., 2009). The greater vegetal cover in HD plots should“a priori” support a more dominant community of Glomeromycetes.Instead, competition against Ascomycota or the scarce developmentof mutualistic plants could have constrained the proliferation ofthis phylum.

A sole addition of an organic amendment on the past displaysecosystem benefits, improving carbon storage and fostering hu-mification and microbial activity of semiarid soils. This studyhighlights that long-term restoration of a semiarid degraded soildid not increase microbial diversity but influenced microbialcommunity structure, functionality, and aboveground plant com-munities. According to the proposed objectives, we concluded that:

1) An increase in the nutrient content of long-term restored soildid not support a more diverse microbial community than thecontrol.

2) The sole application of high-dose of organic waste(195 Mg ha�1) for soil restoration 25 years ago indirectlymodified the structure of bacterial and fungal communities.These effects are mainly mediated by the development ofnatural vegetation and changes in pH, and the content oforganic carbon and nitrogen in soil. However, lower dose(65Mg ha�1) did notmodify such community structure but stillfosters microbial activity at the same level than HD plots.

3) Changes in community structure of the soil amended with thehigh dose of organic waste implied a reduction of functionaldiversity and substrate richness. Although a direct link cannotbe established, the reduction in functional diversity occurs inparallel to the reduction in the abundance of sequences ofActinobacteria and the increase of Bacteroidetes, Alpha-proteo-bacteria, Planctomycetes and Ascomycota organisms.

Overall, microbial community showed an adaptation to theenvironmental conditions and soil properties after long-termrestoration. This adaptation occurs via a change in microbial com-munity structure and an increase in ecosystem functions, andsuggests a higher resilience of the restored soil against climatechange and other negative impacts.

Acknowledgments

F. Bastida is grateful for the financial support of the CSIC and FSE(JAE Doc) and a Marie Curie Reintegration Grant (DYNOMIWAS,PERG07-GA-2010-263897). The authors thank the SpanishMinistryfor the CICYT project (AGL2010-16707) and the Consolider IngenioProgram (CSD 2007-00005). J. Solano and J.L. Ramos are acknowl-edged for their support with genomic methods. We thank B.E.L.Morris for editorial revisions.


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Appendix A. Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.soilbio.2013.04.022.

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