Plant soil interactions alter carbon cycling in an upland grassland soil

12 Pages·2013·2.61 MB·English

by  Bruce C. Thomson

ORIGINALRESEARCHARTICLE
published:10September2013
doi:10.3389/fmicb.2013.00253
Plant soil interactions alter carbon cycling in an upland
grassland soil
BruceC.Thomson1*,NickJ.Ostle2,NiallP.McNamara2,SimonOakley2,AndrewS.Whiteley3,
MarkJ.Bailey1 andRobertI.Griffiths1
1CentreforEcologyandHydrology,Wallingford,Oxfordshire,UK
2CentreforEcologyandHydrology,Lancaster,Lancashire,UK
3SchoolofEarthandEnvironment,TheUniversityofWesternAustralia,Crawley,WA,Australia
Editedby: Soil carbon (C) storage is dependent upon the complex dynamics of fresh and native
PerBengtson,LundUniversity, organic matter cycling, which are regulated by plant and soil-microbial activities. A
Sweden fundamental challenge exists to link microbial biodiversity with plant-soil C cycling
Reviewedby: processes to elucidate the underlying mechanisms regulating soil carbon. To address
MarkA.Bradford,YaleUniversity,
this, we contrasted vegetated grassland soils with bare soils, which had been plant-free
USA
FeikeA.Dijkstra,TheUniversityof for 3 years, using stable isotope (13C) labeled substrate assays and molecular analyses
Sydney,Australia of bacterial communities. Vegetated soils had higher C and N contents, biomass, and
*Correspondence: substrate-specific respiration rates. Conversely, following substrate addition unlabeled,
BruceC.Thomson,Centrefor native soil C cycling was accelerated in bare soil and retarded in vegetated soil;
EcologyandHydrology,Maclean
indicativeofdifferentialprimingeffects.Functionaldifferenceswerereflectedinbacterial
Building,BensonLane,Crowmarsh
Gifford,Wallingford,OX108BB,UK biodiversity with Alphaproteobacteria and Acidobacteria dominating vegetated and bare
e-mail:[email protected] soils, respectively. Significant isotopic enrichment of soil RNA was found after substrate
addition and rates varied according to substrate type. However, assimilation was
independentofplantpresencewhich,incontrasttolargedifferencesin13CO respiration
2
rates,indicatedgreatersubstrateCuseefficiencyinbare,Acidobacteria-dominatedsoils.
Stable isotope probing (SIP) revealed most community members had utilized substrates
with little evidence for competitive outgrowth of sub-populations. Our findings support
theories on how plant-mediated soil resource availability affects the turnover of different
pools of soil carbon, and we further identify a potential role of soil microbial biodiversity.
Specificallyweconcludethatemergingtheoriesonthelifehistoriesofdominantsoiltaxa
can be invoked to explain changes in soil carbon cycling linked to resource availability,
and that there is a strong case for considering microbial biodiversity in future studies
investigatingtheturnoverofdifferentpoolsofsoilcarbon.
Keywords:uplandacidicgrassland,bacteria,substrate-specificrespiration,primingeffects,substratecarbonuse
efficiency,T-RFLP,RNAstableisotopeprobing,soilorganiccarbon
INTRODUCTION particularlytoelucidatetheroleofsoilbiodiversityintheterres-
In terrestrial ecosystems the amount of organic C stored in soil trial C balance and wider sustainability of soils (Bardgett et al.,
is largely dependent upon a dynamic balance between inputs, 2008;Patersonetal.,2009).
mostlyfromplants(HopkinsandGregorich,2005),andrespired Whenstudyingsoilorganicmatterdynamics,isotopelabeled
outputsfromsoil(Kuzyakov,2002).Plantcommunitiesdirectly substrate additions often reveal changes in the decomposition
affectsoilCstorageastheyprovidearangeofCresources,mainly rates of unlabeled native soil organic carbon (SOC); a phe-
in the forms of root exudates and detritus, which are decom- nomenon termed the priming effect (Bingeman et al., 1953).
posed at different rates by the soil biota (De Deyn et al., 2008; Primingeffectscanbeeitherpositiveornegativeandarethought
Patersonetal.,2009).Soilmicrobialcommunitiesareknownto to be important in determining a soil’s C storage potential
beincrediblydiverseandareessentialfordecomposition(Schimel (Kuzyakov et al., 2000). Positive priming describes increased
and Schaeffer, 2012), yet there is little evidence that below- nativesoilorganicmattercyclingfollowingfreshsubstrateinputs,
groundmicrobialbiodiversityaffectssoilorganicmatterturnover whereasnegativeprimingistheconversedeclineinnativecycling
(Nannipierietal.,2003).Indeed,ithasbeensuggestedthatabi- followinginputs.Theunderlyingmechanismsaffectingthemag-
otic factors, and not microbial community structure, regulate nitude and direction of priming are not yet fully understood,
mineralizationrates(Kemmittetal.,2008).Withmajoradvances despite many lab and field based studies examining potential
inunderstandingglobalsoilmicrobialbiodiversity(Fiereretal., factors, such as: vegetation presence (Brant et al., 2006; Guenet
2009),itisalsoimperativeweimproveourunderstandingofthe et al., 2010); resource availability (Kuzyakov and Demin, 1998;
diversityandactivityofsoilmicrobeswithinafunctionalcontext, Fontaine et al., 2004a; Kuzyakov and Bol, 2006); and substrate
www.frontiersin.org September2013|Volume4|Article253|1
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
qualityandquantity(DeNobilietal.,2001;Pascaultetal.,2013). explore the use of an RNA-based SIP approach to investigate
Therearefurthercomplicationsastothesourceofthenativecar- activecommunitiesdegradingdifferentCsources,andtofurther
bonbeingassessedinprimingeffectsstudies,beitfromturnover ourunderstandingofsoilprimingeffects.
of non-living soil organic matter (termed real priming effects),
orfromtheendogenousmetabolismofmicroorganisms(appar- MATERIALSANDMETHODS
entprimingeffects)(DalenbergandJager,1981;Belletal.,2003; FIELDSITE,SOILSAMPLING,ANDPROPERTIES
BlagodatskayaandKuzyakov,2008).Wedonotenterthisdebate Soil(10cmdepth)wascollectedinautumnatanupland,grass-
here, and will henceforth use the term SOC to refer to carbon land experiment located at the Rigg Foot field site, Sourhope,
presentinbothlivingandnon-livingcomponentsofexistingsoil Scotland, UK (GR NT854 196 at 300m above sea level). In a
organicmatter,priortofreshorganiccarbon(FOC)addition. previousexperiment,soilbacterialcommunitystructureandres-
Severalrecenttheorieshaveproposedthatabetterunderstand- piration rates were found to vary at the field scale as a result
ingoftheroleofsoilmicrobialcommunitiesmayberequiredto of the topography of the experimental site, which led to water-
fullyunderstandprimingeffects(Fontaineetal.,2003;Fontaine logging in certain areas (Thomson et al., 2010). Therefore, in
andBarot,2005;KuzyakovandBol,2006).Fontaineetal.(2003), this experiment we chose to examine replicates from within a
in particular, detailed hypothetical models based on microbial single experimental block. The experimental block comprised
population dynamics and soil nutrient conditions which placed of a 10m2 area of control grassland (hereon referred to as
microbialdiversityandactivityasakeydriverofprimingeffects. vegetated treatment), within which a 4m2 defoliated plot had
Here,microbialpopulationswithdifferentlifehistoriesarecon- beenestablishedandcoveredwithapermeableblackmembrane,
sidered to respond differently to added carbon inputs, where for 3 years preceding this experiment, to prevent plant growth
copiotrophs(r-strategists)rapidlyutilizetheaddedFOC,whereas (hereon referred to as bare treatment). Three replicate mono-
oligotroph(K-strategist)populationsmoreefficientlychannelthe liths (60cm × 60cm) were sampled from the vegetated and
energy gained from FOC into degrading SOC. This theory also bare areas within close proximity of each other to minimize
emphasizesthatplantsmayhaveanimportantroleindrivingsoil variation in environmental conditions; ensuring that the main
primingeffectsastheydeterminesoilfertility,andaffectmicro- difference between treatments was the presence or absence of
bial community structure and functional activity by providing plants.Samplesweretransportedimmediatelytothelaboratory
FOC inputs of differing resource value (Griffiths et al., 2003; where they were fresh sieved to 2mm, roots removed by hand
Johnsonetal.,2003;Bardgett,2005). thenstoredat4◦Cuntilrequiredforanalysesand13Csubstrate
InFontaine’stheory(Fontaineetal.,2003)itwaspositedthat, additionexperiments.
afterutilizingFOC,particularmicrobialpopulationsincreasein Experimental microcosms were set-up using 100ml air-tight
sizeresultinginagreaterturnoverofSOC.Therefore,itissup- containers(Lock&Lock,Armorica,Petersfield,UK)modifiedto
posed that monitoring differences in soil microbial community include a rubber septum (SubaSeal, Sigma-Aldrich, Poole, UK)
structure,alongsidesoilCfluxes,couldprovideinsightsintothe for headspace gas sampling. Triplicate microcosms (20g sieved
microbial populations contributing to the direction and mag- soil)wereestablishedtoenabledestructivesamplingat0(priorto
nitude of soil priming effects. Whilst some studies have simply substrateaddition),24,72,and193htoexamineextractedRNA,
monitored microbial communities in conjunction with soil res- andtotalandfunctionalbacterialcommunitiesinvegetatedand
piration measures (Falchini et al., 2003; Landi et al., 2006; De baretreatments(equalingatotalof78microcosms).Theserepli-
Graaffetal.,2010;Guenetetal.,2010),othershavetraced13C- cateswerealsousedforCO samplingontenoccasions(0,12,24,
2
labeledsubstratesintolipidbiomarkers(Nottinghametal.,2009). 48,72,96,120,144,168,and193h).
Additionally, stable isotope probing (SIP) of nucleic acids has CandNcontentswereanalyzedwithanElementarVarioEL
been undertaken to permit more detailed molecular analyses elemental analyser (Elementar Analysensysteme GmbH, Hanau,
of the diversity of active microbes (Bernard et al., 2007, 2012; Germany). Deionized water was added to soil to provide a 1:1
Pascault et al., 2013). These few studies have shown that pop- mixture and pH was measured using an HI 8424 pH meter
ulation shifts in active microbes can be associated with changes (Hanna Instruments Srl, Italy). Moisture (%) was calculated by
◦
in soil C turnover, yet more studies are still needed to synthe- drying overnight at 105 C then re-weighing to measure water
sizeandstrengthencurrenttheoriesontherelationshipsbetween loss.Microbialbiomassmeasurementswerebasedonanalysisof
microbialbiodiversityandthecyclingofdifferentpoolsofSOC. phospholipid fatty acids (PLFAs), using a previously described
In a previous study we showed that field-based removal of method (Bardgett et al., 1996). Phospholipids were extracted
vegetationfromanacidicgrasslanddecreasedsoilresourceavail- from 1.5g soil (fresh weight) and extracts analyzed using an
ability, soil respiration rates and changed bacterial community Agilent 6890 Gas Chromatograph (Zebron ZB-5 Capillary GC
structure to favor presumed oligotrophic taxa (Thomson et al., Column 60m × 0.32mm × 0.25μm). Individual PLFA peaks
2010).Usingthesesametreatments,hereweseektoinvestigatein wereidentifiedbasedonretentiontimesofknownbacterialfatty
moredetailtheroleofvegetation(presenceorabsence),resource acid standards (Sigma-Aldrich, Dorset, UK). Concentrations of
availability and bacterial biodiversity on the specific cycling of individualfattyacidswerecalculatedusingastandard19:0peak
labile FOC and native SOC. Three 13C labeled substrates will asareference.TotalsoilmicrobialPLFAconcentrationswerecal-
be used to examine how the type of substrate, as a proxy for culatedfromallmeasuredPLFAs(15:0,15:0i,15:0a,14:0,16:0i,
labile FOC resources, affects the observed patterns. Total bacte- 16:0,16:1,16:1ω5,16:1ω7,17:1ω8,7Me-17:0,br17:0,17:0i,17:0a,
rial community responses will be assessed and we also seek to br18:0,18:1ω5,18:1ω7,18:0,19:1,7,8cy-19:0).
FrontiersinMicrobiology|TerrestrialMicrobiology September2013|Volume4|Article253|2
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
13CSUBSTRATEINCUBATIONEXPERIMENT where tot-substrate13C = total respiration minus 13C respired
Fully labeled (99 atom%) 13C-glucose, 13C-glycine, and 13C- following substrate amendment (mg g−1 dry soil h−1), and
phenol(CambridgeIsotopeLaboratoriesInc.Andover,UK)were tot_soilresp=totalsoilrespirationfromthewatercontroltreat-
weighed and dissolved in distilled H O. The 13C labeled sub- ment(mgg−1drysoilh−1).
2
stratesolutionsweresterilizedthrougha0.2μmfilter(Sartorius,
Göttingen, Germany) and added at a rate of 0.4mg 13C g−1
TOTALBACTERIALCOMMUNITYSTRUCTURE
dry soil. For the glucose, glycine and phenol incubations 200,
Nucleic acids were extracted from 0.5 g soil using a previ-
250, and 220μl of substrate solution was added, respectively to
ously described method (Griffiths et al., 2000) and were finally
each microcosm. Filter sterilized, distilled H O was also used
2 re-suspendedinmolecular-gradeH O.Terminalrestrictionfrag-
2
as a control treatment. After the addition of substrate solution
ment length polymorphism (T-RFLP) analysis of soil bacte-
or distilled H O, soil was stirred once to mix substrates before
2 rialcommunitieswasperformedusingdilutedextractednucleic
the initial gas sampling (0 h). Moisture contents were main-
acids with 16S rRNA gene primers 63F (Marchesi et al., 1998)
tainedthroughoutbyweighingandrewetting.Ateachsampling,
(fluorescently-labeledwithD4bluedye)(Sigma-Proligo,Dorset,
microcosms were sealed shut and headspace gas samples taken
UK) and 519R (Lane, 1991) (MWG Biotech, London, UK).
immediatelyandafter3htodeterminethesoilrespiratoryCO
2 Amplicons were then digested with MspI restriction enzyme
◦
flux.Microcosmsweremaintainedatapproximately15 C(mean
(New England Biolabs Inc., Ipswich, MA, USA) prior to frag-
summertemperature)inatemperaturecontrolledroom.
ment analysis using a Beckman Coulter CEQ 2000XL capil-
larysequencer(BeckmanCoulterCorporation,California,USA).
CO2AND13C–CO2ANALYSES Terminal restriction fragment (T-RF) relative abundances were
CO measurementsweremadewithaPerkinElmerAutosystem
2 calculated as the ratio between the fluorescence of individual
XLGasChromatograph(PerkinElmer,Waltham,MA,USA),fit-
◦ T-RFsandthetotalintegratedfluorescenceofallT-RFs.
tedwithaflameionizationdetector,operatedat350 C.CO was
2
isothermally separated with nitrogen as the carrier gas flowing
at30cm3 min−1 ona2mcolumnpackedwithPoropakQ.The STABLEISOTOPEANALYSESOFSOILRNA
detector response was calibrated using a certified gas standard SoilRNAwaspurifiedfromtotalnucleicacidsextractionsusinga
containing500μll−1CO innitrogen(AirProducts,Leeds,UK). RNA/DNAminikit(Qiagen,Crawley,UK)accordingtotheman-
2
Betweensamplingeventslidswereleftopentoallowmicrocosms ufacturer’s instructions. To assess the amount of substrate 13C
tovent. incorporation into soil RNA, 13C:12C isotope analysis was per-
To analyze respired 13CO , headspace gas sampled from formed using a method previously described (Manefield et al.,
2
microcosmswasinjectedintoaTraceGaspre-concentratorunit 2002a). RNA (1μg) was cut with sucrose to provide a mini-
(Micromass,Manchester,UK),and13Ccontentwassubsequently mumCcontentof25μg.Sampleswerethenfreeze-driedfor16h
quantified using gas chromatography isotope ratio mass spec- priortocombustiontoCO2usingaCarlo-ErbaN1500Elemental
trometry (GC-IRMS) (Micromass, Manchester, UK). Analysis Analyser (Carlo-Erba, Valencia, CA, USA). Abundances of 13C
was performed at the NERC Life Sciences Mass Spectrometer wereexpressedasδ13Cvalues,usingthefollowingequation:
Facility, CEH Lancaster using their standard protocols (uncer-
tainty better than 0.3%). Abundances of 13C were expressed as δ13C (%)=[(Rsample÷Rstandard)−1]×1000
13Catom%i.e.:
whereR andR arethe13C:12Cratioofsoilextracted
13Catom%=[(R )÷(R +1)]×100 sample standard
sample sample RNAandPeeDeeBelemnitestandard,respectively.
Substrate 13C incorporated into RNA (μg μg−1 RNA) was
whereR isthe13C:12CratioofanalyteCO .
sample 2 calculatedforeachsamplingeventusingthefollowingequation:
(cid:3) (cid:4)
RESPIRATIONCALCULATIONS
The amount of substrate 13C respired as 13CO –C (mg g−1 13CsubstrateinRNA=[ RNA13Catom%÷100 ×25]
2
dry soil h−1) was calculated for each sampling event using the −sucrose13C
equation:
(cid:2)(cid:3) (cid:4) (cid:5)
13Cfromsubstrate= respCO ÷100 ×13Catom%excess whereRNA13Catom%=13Catom%ofRNA;sucrose13C=the
2 amount of 13C (μg ) in sucrose standard used to cut extracted
whererespCO =thefluxoftotalCO –Crespiredfromsoilover RNA;and25=minimumCcontentinμg.
2 2
3hateachtimepoint,and13Catom%excess=the13Catom% To investigate microbial substrate C use efficiency, we exam-
difference between two measurements taken 3h apart at each inedtheamountofsubstrate13CassimilatedintoRNAcompared
samplingtimepoint. to the amount of substrate 13C respired, based on a previously
Rates of unlabeled SOC turnover following substrate addi- describedcalculation(Freyetal.,2001;Brantetal.,2006):
tion were calculated using an equation previously described by (cid:2)(cid:3) (cid:4) (cid:3)
Fontaineetal.(2004a,b): substrateCuseefficiency= RNA13C ÷ RNA13C
(cid:6) (cid:7)(cid:8)
(cid:3) (cid:4)
unlabeledSOCturnover= tot-substrate13C−tot_soilresp + substrate13C
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Thomsonetal. Vegetation,soilbacteria,andprimingeffects
whereRNA13C=theamountof13Cincorporatedintoextracted treatment compared to the vegetated soil (P<0.05, F =70.49,
RNA(μgμg−1RNA),andsubstrate13C=cumulativesubstrate- F=63.78,andF=23.27forsoilCandNcontents,andmicro-
specificrespiration(μgg−1drysoil). bial biomass, respectively). The C:N ratio was less in vegetated
soil,althoughnotsignificantlyso.Additionally,therewerenosig-
RNASTABLEISOTOPEPROBING nificantdifferencesin%moistureandsoilpHbetweenthetwo
SIPanddenaturinggradientgelelectrophoresis(DGGE)analysis soiltreatments(Table1).
were performed similarly to Manefield et al. (2002a). Extracted
RNA was subjected to isopycnic density gradient centrifugation GROSSRESPIRATIONISHIGHERINVEGETATEDSOIL
in caesium trifluoroacetate gradients containing deionised for- Cumulative soil basal respiration was significantly higher (P<
mamide. Gradients were loaded with 500ng of extracted RNA 0.05, F=315.47) in vegetated soil compared to the bare
andspunat136,000×gfor42hat20◦C.Followingcentrifuga- (Figure1), by the end of the experiment. Similarly, total res-
tion,sampleswerefractionatedfor30sperfractionataflowrate piration following substrate addition was greatest in vegetated
of3.3μls−1,resultinginatotalof20fractionspersample.RNA soil regardless of which substrate was added (P<0.05, glucose
was precipitated from each gradient fraction by incubating at F=13.74; glycine F=184.84; phenol F=35.17). By examin-
−20◦Cwithisopropanolfollowedbycentrifugationat16,000×g ingtheshapeoftherespirationcurves,rateswereshowntodiffer
◦
for30minat4 C.Finally,fractionsweredriedundervacuumand depending on substrate added. Following glucose addition, res-
RNAdissolvedinRNase-freewater. piration was greatest at the start of the experiment, tailing off
Precipitated RNA from density gradient fractions was toward the end. Yet, for glycine and phenol lower levels of res-
reverse transcribed using reverse primer 519r (MWG Biotech, pirationweresustainedforalongerperiodoftime,anddisplayed
London, UK) and avian myeloblastosis virus reverse transcrip- abiphasicrespirationresponse(datanotshown).Inbothtreat-
tase (Promega, Southampton, UK). cDNA was then amplified ments, mean cumulative total respiration rates were ranked in
usingbacterial16SrRNAgeneprimersGC338Fand519r(MWG the following order: glycine > glucose > phenol. In vegetated
Biotech,London,UK).DGGEanalysiswasperformedwitha10% soil, mean cumulative total respiration was significantly higher
(wt/vol)acrylamidegelcontainingadenaturantgradientof30– following glycine addition compared to the glucose and phenol
60%.DenaturinggradientgelswerecastandrunusingtheIngeny incubations;however,therewasnosignificantdifferencebetween
◦
PhorU2 system (Goes, The Netherlands) at 60 C and 200V for glucoseandphenolmeancumulativetotalrespiration(basedon
8h.ApproximateamountsofRT-PCRproductwereloadedinto confidence interval ranges following a One-Way ANOVA with
eachlaneonthegeltoexamineactivebacterialcommunities.Gels Tukey’s post hoc test). Contrastingly, in bare soil, phenol total
weresubsequentlystainedwithSYBRgoldnucleicacidgelstain respiration was significantly less than glucose or glycine, and
(Molecular Probes, Invitrogen, Paisley, UK), then visualized by there were no significant differences between the glucose and
UVtrans-illumination. glycine treatments. Basal respiration was more than two times
greaterinthevegetatedcontroltreatmentthanthebare,though
STATISTICALANALYSES this magnitude of difference was not observed in total respi-
Cumulative respiration data, RNA 13C incorporation and sub- ration rates. This emphasizes that C processing, in terms of
strate C use efficiency were examined for significant differ- total amounts of respiration following substrate addition, dif-
ences between treatments with a One-Way analysis of variance feredtothatofnativeorganicmatterrespirationbetweenthetwo
(ANOVA) combined with Tukey’s post hoc testing with a family treatments.
error rate set at 5, using MINITAB release 14 (MINITAB Inc.).
Statisticalanalysesofsoilbacterialcommunitieswereperformed INCREASEDFOCMINERALISATIONINVEGETATEDSOIL
with the vegan library (Oksanen et al., 2009) of the R software Inordertospecificallyexamineproportionsof13ClabeledFOC
package(RCoreDevelopmentTeam,2005).Briefly,aBray-Curtis and unlabeled SOC mineralized, headspace gases were analyzed
distancematrixofbetweensampledissimilaritieswascalculated using GC-IRMS to determine the specific amount of respired
and subsequently represented through two-dimensional non- 13CO . By the end of the incubation, cumulative substrate-
2
metric multidimensional scaling (NMDS), using the metaMDS specific respiration was significantly higher in vegetated soil
function.Differencesincommunitieswerequantifiedbypermu- compared to bare soil for all substrate additions (P<0.05,
tational multivariate analysis of variance (PERMANOVA) using 13C-glucoseF=11.32;13C-glycineF=336.72;13C-phenolF=
theadonisfunction,andgroupdispersions(betadiversity)were 51.14) (Figure1). Over the entire duration of the experiment,
further assessed using the betadisper function. To assess differ- 13C-substratesweremineralizedinthefollowingorder:glycine>
encesintherelativeabundancesofparticularterminalrestriction glucose > phenol for both vegetated and bare soils. In veg-
fragments(T-RFs)betweentreatments,similaritiesofpercentages etated soil, total cumulative 13C-substrate mineralization was
(SIMPER)analysis(Clarke,1993)wasperformedusingthePAST significantly different between all substrates (based on confi-
statisticalpackage(http://folk.uio.no/ohammer/past). denceintervalrangesfollowingaOne-WayANOVAwithTukey’s
post hoc test). In bare soil, however, there were found to be
RESULTS nosignificantdifferencesbetweenglucoseandglycine,andglu-
EFFECTSOFVEGETATIONREMOVALONSOILPROPERTIESAND coseandphenolmineralizationrates.Bothsubstrate-inducedand
BIOMASS substrate-specific respiration data revealed very similar patterns
After 3 years without plant cover, soil C and N contents, and in terms of treatment differences between bare and vegetated
microbial biomass were significantly lower in the bare soil soils,andsoilrespirationresponsestosubstrateamendment.
FrontiersinMicrobiology|TerrestrialMicrobiology September2013|Volume4|Article253|4
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
Table1|Meansoilpropertiesinvegetatedandbaresoils.
C(gg−1soil) N(gg−1soil) C:N SoilpH Moisture(%) Microbialbiomass
(PLFAµgg−1drysoil)
Vegetated 0.119(0.001) 0.0094(0.0002) 12.70(0.33) 4.81(0.03) 54.00(0.58) 102.40(9.11)
Bare 0.097(0.002) 0.0070(0.0002) 13.57(0.26) 4.77(0.01) 53.67(1.67) 57.47(1.91)
P 0.001 0.001 0.109 0.22 0.86 0.008
F 70.49 63.78 4.24 0.17 0.04 23.27
Standarderrorofthemean(SEM)inparentheses(n=3).SignificantdifferencescalculatedusingOne-WayANOVA.
FIGURE2|Effectsofsubstrateadditionupondominantsoilbacterial
populationsinvegetatedandbaresoils.Two-dimensionalNMDS
FIGURE1|Labeled FOCandunlabeled SOCturnover invegetated ordinationanalysisofbacterialT-RFLPdatafromsoilsincubatedwith
andbaresoilsamended withlabile13Csubstrates.Meantotal 13C-labeledglucose,glycine,andphenol,andthewatercontroltreatments
respiration(12CSOCand13CFOC),substrate-specific respiration at0,24,72,and193h.Differencesintherelativeabundancesof
(13CFOC)and12Cprimingeffectsinvegetated andbaresoilsfollowing AlphaproteobacteriaandAcidobacteriaT-RFswerefoundtoaccountforthe
theadditionof 13C-labeledglucose,glycine,andphenol. Primingeffects majorityofdifferencesbetweenvegetatedandbaresoilcommunities.
werebasedonunlabeledSOCturnoverratesafterFOCaddition,relative Bacterialcommunitiesfromvegetatedandbaresoilsaredenotedbyblack
to12CSOCmineralizationinthecontrolsoil.ErrorbarsareSEM(n=3). andgraysymbols,respectively.
ACCELERATEDSOCTURNOVERINBARESOILSFOLLOWINGFOC inSOCdecompositionrelativetothewatercontrol(61,51,and
ADDITION 38%meanincreaseforglucose,glycineandphenol,respectively).
The difference in 12C respiration between substrate amended Withineachsoiltreatment,thecumulativeamountofSOCmin-
soils and the water controls was inferred to have arisen from eralized over the duration of the experiment was unaffected by
the decomposition of SOC in response to the addition of FOC the type of FOC added (vegetated soil P = 0.21; bare soil P=
(the priming effect). The direction and intensity of unlabeled 0.29).ThisshowsthatregardlessofthenatureofFOCadded,the
SOC turnover varied with soil treatment, FOC type and incu- presence or absence of vegetation had significant consequences
bation time (Figure1, red lines). For all FOC additions there for unlabeled SOC turnover; with consistent positive priming
was a significant difference in mean cumulative SOC turnover (acceleratedunlabeledSOCturnover)inbaresoilsandnegative
between vegetated and bare soils (P<0.05, glucose F=39.29; priming(retardedunlabeledSOCturnover)invegetatedsoils.
glycine F =68.03; phenol F=44.58). For vegetated soil, irre-
spective ofthe FOC used, addition oflabile 13C led to a cumu- TOTALBACTERIALCOMMUNITYSTRUCTURE
lative decrease in SOC mineralization compared to the control Two-dimensionalNMDSanalysiswasperformedtoexploreany
incubation (11, 7, and 15% mean decrease for glucose, glycine differences in bacterial community structure between vegetated
andphenol,respectively).Conversely,inthebaresoils,additionof andbaresoilsacrosstheincubations(Figure2).Thepresenceor
lowmolecularweightFOCbroughtaboutacumulativeincrease absence of plants was shown to be the main factor responsible
www.frontiersin.org September2013|Volume4|Article253|5
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
for community differences as vegetated and bare soils were FOC.Differencesinratesof13Cincorporationwereparticularly
clearly separated along the first axis. The effect of the vegetated pronounced for glucose amended soils, as the total 13C incor-
and bare treatments on soil bacterial community structure was porationintoRNAfromglucosewasthree-tofour-foldgreater
alsoshowntobesignificantwhenanalyzedwithPERMANOVA than glycine or phenol 13C. Throughout the experiment there
(R2 =0.53,P<0.05).NMDSanalysisalsoshowedlittlechange was no consistent difference in RNA 13C incorporation rates
in bacterial communities after exposure to FOC or at differ- betweenvegetatedandbaresoils;significantdifferenceswereonly
entsamplingeventsthroughouttheincubation.However,inthe observed 24h after glucose addition (P<0.05, F=8.31), and
bare treatment there were distinct differences in the bacterial 72hand193hafterphenoladdition(P<0.05,F=11.77;P=
communities analyzed prior to FOC addition as these samples 0.004,F=31.92)(Figure4A).
grouped separately from all other samples. Additionally, bare To further investigate FOC dynamics across treatments, we
soil communities across all substrate additions and time points calculated and contrasted substrate 13C use efficiencies, deter-
weresignificantlymorevariablethanvegetatedsoilcommunities mined as the ratio of RNA incorporated 13C to respired sub-
(betadisper,P<0.05). strate 13C (Figure4B). Here we assume RNA incorporation
SIMPERanalysishighlightedthattheT-RFswhichaccounted rates reflect the amount of FOC being assimilated into cel-
forapproximately55%ofthedissimilaritybetweenthevegetated lular components as opposed to being respired for catabolic
and bare soil bacterial communities were 53, 55, 76, 77, 78, 97, metabolism (Manzoni et al., 2012). In terms of the differences
99, 110, 111, 112, 113, 227, 229, and 396 nucleotides (n.t.) in between applied substrates, glucose 13C was consistently uti-
length.Usingdatafromapreviousinsilicoendonucleaserestric- lized more efficiently than the other two substrates indepen-
tiondigestof16SrRNAgeneclonelibrariesfromvegetatedand dently of vegetation presence or absence. Additionally, mean
baresoils(Thomsonetal.,2010),wecouldconfidentlyidentifyall utilizationefficiencieswereconsistentlyhigherinbaresoilinde-
buttwo(97and99n.t.)oftheseT-RFsattheclasslevel(Table2). pendent of FOC type, with significant differences 24h after
Only minor variations in the relative abundances of these taxa glucoseaddition(P<0.05,F=12.25);24,72,and193hfollow-
occurredovertimeandbetweensubstrateadditionsinvegetated ingglycineaddition(P<0.01,F=22.28;P=0.01,F=19.81;
andbaresoils,withthemaintreatmentdifferencesbeingasignif- P<0.01,F =33.01);and193hafterphenoladdition(P<0.01,
icantly greater relative abundance of Alphaproteobacteria T-RFs F=51.12).
in vegetated soil (P<0.05, F=104.18) and Acidobacteria T-
RFsinbaresoil(P<0.05,F=16.86)(Figure3).Furthermore,
SIPREVEALSNODIFFERENCEBETWEEN“TOTAL”AND“ACTIVE”
themeanratioofAlphaproteobacteriatoAcidobacteriaT-RFswas
COMMUNITIES
significantlyhigher(P<0.05,F=51.64)invegetatedsoilthan
Toexaminethebacterialpopulationsactivelyutilizingtheadded
baresoil,withvaluesof1.69and1.22,respectively.
substrates, density gradient centrifugation was used to isolate
13CenrichedRNA,priortomolecularanalyses.Consistentwith
13CINCORPORATIONINTOSOILRNA previous studies, reproducible linear gradients were achieved
Dynamicmeasurementsof13Cincorporationintoextractedsoil (Figure5A) spanning a density range of approximately 1.75–
RNA were performed to assess microbial utilization of added 1.85g ml−1(Manefield et al., 2002b; Whiteley et al., 2007). We
Table2|Analysisofdominantbacterialtaxainvegetatedandbaresoils.
Contribution Cumulative% Vegetatedsoilabundance Baresoilabundance ID
55 3.185 8.767 0.0798 0.143 Acidobacteria
113 2.645 16.05 0.133 0.08 Alphaproteobacteria
112 2.098 21.82 0.00455 0.0457 Alphaproteobacteria
227 1.799 26.77 0.0632 0.0275 Acidobacteria
99 1.682 31.41 0.00867 0.0422 Unclassified
53 1.343 35.1 0.0595 0.0828 Acidobacteria
78 1.089 38.1 0.0334 0.0123 Alphaproteobacteria
76 1.071 41.05 0.0311 0.0104 Alphaproteobacteria
110 0.9677 43.71 0.11 0.0986 Alphaproteobacteria
111 0.9456 46.32 0.00647 0.0163 Alphaproteobacteria
97 0.9057 48.81 0.0033 0.0213 Unclassified
229 0.8751 51.22 0.0477 0.0314 Acidobacteria
77 0.8027 53.43 0.0189 0.00328 Alphaproteobacteria
396 0.6228 55.14 0.0332 0.0258 Alphaproteobacteria
MeanrelativeabundancesofdominantT-RFscontributingtoapproximately55%ofthetotaldissimilarity(n=39).ResultsfromSIMPERanalysisarelistedinorder
ofdecreasingimportance.NumbershighlightedinboldindicatewhetheraparticularT-RFwasmoreabundantinthevegetatedorbaresoil.TheidentitiesofT-RFs
arebasedon16SrRNAgeneclonelibrariesfromapreviousstudy(Thomsonetal.,2010).
FrontiersinMicrobiology|TerrestrialMicrobiology September2013|Volume4|Article253|6
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
FIGURE4|Differencesinsubstrate13Cutilisationinvegetatedand
FIGURE3|Relativeabundancesofdominantbacterialtaxaovertime, baresoils.Meanassimilationofglucose,glycineandphenol13CintoRNA
followinglabilesubstrateadditions.Totaledrelativeabundancesof extractedfromsoil(μg13Cμg−1RNA)(A).Glucose13Cincorporationwas
AcidobacteriaT-RFs(black),AlphaproteobacteriaT-RFs(white),andT-RFs greaterthantheotherFOCadditions,althoughtherewerenoconsistent
representingallothertaxa(gray)invegetated(A)andbare(B)soils(n=3, effectsbetweenvegetatedandbaresoils.MeanFOCuseefficiency,
errorbarsareSEM). displayedastheratioofRNA13Cincorporationtorespiredsubstrate
(RNA13C:13CO2-Cμgg−1drysoil)(B).FOCwasconsistentlyutilisedmore
efficientlyinbaresoil.ErrorbarsareSEM(n=3).Significantdifferences
denotedby∗.
thensoughttoidentifyspecificfractionscontaining 13Clabeled
RNA, which could be subsequently examined for all substrate
additions. All 20 gradient fractions from unlabeled (0h) and DISCUSSION
glucose-labeled (24h) samples from the vegetated treatment This study combined a 13C tracer approach with molecular
were amplified by reverse transcription PCR. Amplicons were methodologiestoexamineFOCandSOCdynamicsinrelationto
only found in fractions 3–15 (buoyant densities of 1.75–1.85g vegetation-inducedchangesinsoilresourceavailabilityandbac-
ml−1)and subsequentDGGEanalysisrevealed that, despite the terialcommunities.SoilCandNcontents,microbialbiomassand
presence of some weak bands in the first three “heavy” frac- basal respiration were greater in vegetated soil which is consis-
tions(3–5)beforesubstrateaddition,24hafterincubationwith tent with current knowledge on how plants affect soil resource
13C-labeled glucose, DGGE banding patterns were clearly more availability and stimulate microbial communities (Nguyen and
intense; indicating that 13C labeled RNA had been separated Guckert, 2001; Orwin et al., 2010; Thomson et al., 2010).
intothesefractions(Figure5B).Fractionfour(buoyantdensity Substrate additions revealed that, generally, resources of differ-
1.84g ml−1 ± 0.013) was then selected to examine the bac- ingqualityweredecomposedatdifferentrates,asfoundinother
terial populations actively utilizing 13C-labeled glucose, glycine studies (Webster et al., 1997; Schmidt et al., 2004; Brant et al.,
and phenol prior to (0h; unlabeled RNA) and 24h after FOC 2006; Hartley et al., 2010; Bradford et al., 2013), but rates were
addition (labeled RNA), through 16S rRNA-SIP and DGGE consistently higher in vegetated soil independent of substrate
analyses (Figure5C). Despite subtle differences in band inten- type.However,despitebaresoilsbeingmuchlessactiveindegrad-
sities, the DGGE banding patterns illustrate that most commu- ingaddedFOCsubstrates,unlabeledSOCcyclingwasmarkedly
nity members originally present in the soil became enriched increased,indicativeofpositiveprimingeffects.Incontrast,unla-
in substrate 13C after 24h incubation. This suggests that the beledSOCturnoverwasretardedinthevegetatedsoilsfollowing
differences in “total” bacterial communities between vegetated theaddition ofFOCexemplifying negative primingeffects. The
and bare soils are likely indicative of the differences in “active” directionsoftheseprimingphenomenawerethereforedependent
communities degrading the added FOC, and we found no evi- on the presence or absence of plants and associated changes in
dencethatlimitedsub-populationsofbacteriawereimplicatedin resource availability and not the type of FOC input used in the
FOCdegradation. assay.
www.frontiersin.org September2013|Volume4|Article253|7
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
positiveprimingeffectshavebeenobservedinshorttermassays
on forest soils which had reduced soil C content due to the
exclusionofplantinputsfor6years(Brantetal.,2006).Moregen-
erally,otherstudieshavealsoreportedstrongestpositivepriming
effects in soils with comparatively reduced resource availability
(Fontaineetal.,2004b;HamerandMarschner,2005a,b).Negative
primingeffectsarenotdocumentedasfrequentlyaspositiveones
and whilst there are several potential causes (Kuzyakov et al.,
2000;Blagodatskayaetal.,2007)itisthoughtthattheymaysim-
plyarisethroughpreferentialsubstrateutilization,whereorgan-
isms switch from degrading SOM to the fresh labile substrate
(Sparlingetal.,1982;KuzyakovandBol,2006).
Vegetated and bare soils were dominated by
AlphaproteobacteriaandAcidobacteria,respectively,inagreement
with previous theories that proteobacterial taxa are generally
competitively adapted and dominate in soils of higher resource
availability, whilst Acidobacteria dominate in more resource
limited environments (Smit et al., 2001; Griffiths et al., 2003;
Cleveland et al., 2007; Fierer et al., 2007; Philippot et al., 2009;
Eilers et al., 2010; Thomson et al., 2010; Will et al., 2010).
Therefore,wepostulatethatdifferencesinlabileFOCandnative
SOCprocessingbetweenvegetatedandbaresoilsmay,inaddition
to simple changes in biomass, be also attributable to changes
in dominant taxa. That is, vegetated soils, by virtue of higher
resource availability, are dominated by fast growing r selected
taxa, represented by the Alphaproteobacteria which are likely
adapted to the fast utilization of labile substrates in the forms
FIGURE5|Stableisotopeprobingofbacterialcommunitiesutilizing of root exudates and rhizodeposits. Conversely, the resource
13C-labeledsubstrates.BuoyantdensityofextractedRNAingradient starved bare soils are dominated by K selected communities
fractions3–15followingisopycnicdensitygradientcentrifugation(A).Error such as the Acidobacteria, which are adapted to more efficient,
barsarestandarddeviationsofthemean(n=4).DGGEprofilesofbacterial
slow growth under limiting conditions. In support of this, a
communitiespresentindensitygradientfractions3–15fromvegetated
soilsattime0and24haftertheadditionof13Cglucose(B).Density previous experiment (Fierer et al., 2007;Bradford et al., 2008b)
gradientfractions3–5wereshowntocontain13ClabeledRNA,asindicated directly manipulated forest soil resource availability through
byageneralcommunityshiftintothesefractionsafterlabeledglucose repeated sucrose additions, and found low additions generated
addition.DGGEprofilesofbacterialcommunitiespresentin“heavy”
Acidobacteria-dominated communities which were associated
densitygradientfractionfourfromvegetatedandbaresoils,beforeand
with less respiration and long term C loss; whereas high rates
24haftertheadditionof13C-labeledglucose(Glu),glycine(Gly),andphenol
(Phe);Mdenotesmarkerlanes(C). of addition favored Proteobacteria with increased respiration
responses and long term C gain. We feel these findings are
analogous to those in our present study, where the removal of
Whilst isotope labeled substrate additions represent a use- plantsloweredresourceavailability,decreasedrespiratoryactivity
ful assay exploring potential activities with regard to FOC and and C storage whilst selecting for an Acidobacteria-dominated
SOC cycling, such short-term assays can be criticized for not community. We note that both studies have focused on acidic,
discriminating between “real” or “apparent” priming effects lowdiversitysoilswhicharetypicallydominatedbyAcidobacteria
(Blagodatskaya and Kuzyakov, 2008). Additionally, it has been and Proteobacteria, highlighting the need for more distributed
discussed how simple measures of function based on respired studies encompassing different soils and plant communities in
C should be used cautiously in inferring longer term dynamics order to generalize associations linking plant-driven resource
of SOM (Bradford et al., 2008a; Conant et al., 2011). However, availability,microbialcommunitiesandsoilcarbonstorage.
we found that the direction of unlabeled SOC turnover follow- Despite identifying a potentially widespread associative rela-
ing FOC addition reflected longer term changes in soil carbon tionship on how resources control bacterial biodiversity and C
stocks,whereincreasedSOCcyclinginthebaresoilswasindica- storage, there remains a challenge to definitively link resource
tive of an overall decrease in soil C content. In the absence of driven changes in communities with explicit roles in C cycling;
plantsmicrobesmustutilizeCfromanextantpool;andregard- be it the proposed role of K selected taxa in SOC turnover or r
less of whether this pool is within existing biomass or native selected taxa in preferential FOC use. To further investigate the
SOCtheendresultwillbeCloss(assuminglimitedinputsfrom flowoflabileFOCintoactivemicrobialcommunitiesacoupled
autotrophic carbon fixation). Therefore, based on our results, molecular and isotopic tracer approach was undertaken. Such
the short term FOC addition assays proffer a window on these SIP approaches are believed to shed more light on the explicit
processes,withthedirectionsofprimingeffectsbeingreflectiveof mechanisms linking microbes with both FOC and SOC cycling
longertermchangesinsoilC.Supportingourfindings,increased (Bernard et al., 2007, 2012; Pascault et al., 2013). However, we
FrontiersinMicrobiology|TerrestrialMicrobiology September2013|Volume4|Article253|8
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
detected few differences between labeled (active) and unlabeled simply by considering past evidence that FOC inputs will be
(total)communities24haftereachsubstrateamendmentindicat- catabolizedforenergygaininsteadofbeingconvertedtobiomass
ingmanycommunitymembershadreceivedsubstrateC,rather when C resources are plentiful (Bremer and Kuikman, 1994;
thanspecificactivesub-populations.Incontrast,apreviousstudy Nguyen and Guckert, 2001) or more likely, when N is limit-
has shown that the addition of labile substrates can shift com- ing with respect to plentiful C (Schimel and Weintraub, 2003).
munities favoring specific bacterial taxa (Goldfarb et al., 2011). Conversely,inbaresoilunderassumedClimitation(orClimita-
However,nearlytentimesmoreCwasaddedinthisstudycom- tionwithrespecttoN)thesetheoriessuggestmoreenergyfrom
paredtoours,potentiallyexplainingwhywefailedtoobserveany FOC inputs would be channeled into biomass generation. Our
specificpopulation“enrichment”effectseitherinourTRFLPor findingsadditionallyidentifythatthebiodiversityofsoilmicrobes
SIPdata. may also be a factor to consider in explaining these processes,
Enrichmentoftheentirebacterialcommunityhasbeendoc- though it is apparent that more quantitative approaches are
umented before in soil SIP studies (Rangel-Castro et al., 2005) required to assess the flow of C through specific community
and is likely due to the universal rapid degradability of simple members in order to reveal how populations with different life
substrates by soil microbes. Therefore, we found little evidence history strategies process distinct C pools. In this regard, fur-
tosuggestthatcertaindiscretepopulationsofbacteriawerepref- therinsightsintothefunctionalrolesplayedbyspecificmicrobial
erentiallyutilizingsubstratesresultinginoutgrowthineitherveg- groups in degrading FOC inputs may be gleaned by assess-
etatedorbaresoils.This,therefore,contradictssuppositionsthat ing specific assimilation rates into separated RNA pools using
particular members of communities with different life history morequantitativeapproachessuchasmagneticbeadcaptureSIP
strategiesareexclusivelyutilizingFOCsubstrates,butsuggestsall (Macgregor et al., 2002) targeted at specific taxa (e.g., hypothe-
membersarecapableofaccessingthesesimplecompounds.This sisedr-andK-strategisttaxa).Moreover,tospecificallyexamine
isconceivablesince,despiteanassumedpreferenceforgrowthin SOC degradation and issues pertaining to soil priming, these
resourcelimitedenvironments,K-strategistsarealsoconsidered methodscouldbecoupledwithnovelexperimentalapproachesto
effectiveatscavengingdifferentsubstrates(Pianka,1970;Button, quantitativelytraceCfromtheSOCpooldirectly(Blagodatskaya
1993; Bernard et al., 2007; Fierer et al., 2007). Indeed, such etal.,2011).Wedo,however,alsoidentifyanadditionalcompli-
theories have been invoked to explain priming effects, whereby catingissuewhereby,particularlyforthevegetatedsoils,substrate
easily-assimilatedFOCinputsareutilizedbyK-strategiststodrive “use” may not mean substrate “assimilation” and this should
SOCmineralization(Fontaineetal.,2003),thoughbasedonthe beconsideredinfuturesoilslinkingmicrobialcommunitiesand
SIPresultswewereunabletoproveordisprovethesetheories. functionalityusingsuchisotopetracingapproaches.
Thequantitativeanalysesof13CincorporationintobulkRNA To conclude, in this upland grassland ecosystem, the field
poolsrevealedfurtherinsightsintomicrobialCprocessingresult- removalofplantsforseveralyearsdecreasedsoilresourcesresult-
ingfromdifferentsubstrateadditionstovegetatedandbaresoils. ing in differential rates of FOC and SOC cycling which are
Firstly, we observed that for all soils more glucose was assimi- potentially explainable by considering emerging theories on the
latedintoRNAthantheothertwosubstrates,whichisconsistent life histories of microbial taxa. Our results suggest that base-
with other studies contrasting glucose, glycine and phenol uti- line soil resource availability, controlled by plants, can have a
lization (Brant et al., 2006; Rinnan and Baath, 2009; Bradford pronounced effect on soil bacterial communities and associated
et al., 2013; Frey et al., 2013). Despite these studies using other activities in cycling different soil carbon pools. An additional
biomarkers such as fatty acids and total biomass, it is apparent finding of note was that the direction of the priming effect was
that relatively high glucose-C use efficiency compared to other independentofthetypeofsubstrateused,thereforefuturestud-
substrates may be a general phenomenon occurring widely in ies investigating a wider range of soils could perhaps focus on
soils.ThismaybeduetoglucoseCbeingpreferentiallyincorpo- using a single substrate. Coupling isotope and tracer method-
ratedintostructuralcomponents(asitrequiresnoextracellular ologies was useful in providing new insights into the microbial
enzymaticbreakdown),whereasglycine,asasourceofbothCand cyclingofFOCinputsbutfurtherdevelopmentsarerequiredto
N, gets catabolically metabolized as an energy source (Webster quantitatively assess flows into different taxa, and notably trace
et al., 1997; Hartley et al., 2010) and phenol requires extracel- SOCpoolsdirectly.Wefeeltheseresultsprovideastrongcasefor
lular enzymatic degradation before it can be accessed by the considering microbial biodiversity and the development of fur-
microbialcommunity(PowlowskiandShingler,1994;Freyetal., thermolecularapproachesinfuturestudiesseekingtounderstand
2013).Thesefindingareofwiderrelevanceindemonstratinghow thedifferentialcyclingofdifferentsoilcarbonpools,betheyFOC
different types of FOC inputs are stored or lost from soil and inputsofdifferentqualityornativeSOC.
indicatethatsoilRNAisapotentiallyusefulbiomarkerforassess-
ingthemetabolicfateofdifferentFOCinputsintosoilmicrobial ACKNOWLEDGMENTS
communities. We thank Darren Sleep, Helen Grant, and Andy Stott at the
Secondly, although significant 13C incorporation into RNA NERC/CEHstableisotopefacilityfortheirassistanceincarrying
was found for all samples post-labeling, there were few differ- outsoilCandN,and13CRNAand13CO analyses.Weappre-
2
encesinratesofuptakebetweenvegetatedandbarecommunities. ciate the anonymous reviewers’ constructive comments which
Without a full mass balance calculation these results should be improvedthemanuscript.ThanksalsotoAshishMalikforhelp-
interpretedwithsomecaution;nonethelessitisclearthatinvege- ful discussions. This work was partly funded by the European
tatedsoilsagreaterproportionof13Cwasrespired,asopposedto Commission project, EcoFINDERS (FP7-264465) and a NERC
assimilated,comparedwiththebaresoils.Thiscanbeexplained UKstudentship.
www.frontiersin.org September2013|Volume4|Article253|9
Thomsonetal. Vegetation,soilbacteria,andprimingeffects
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