Biochar alters the soil microbiome and soil function

23 Pages·2017·2.69 MB·English

Biochar alters the soil microbiome and soil function:
results of next-generation amplicon sequencing across
Europe
Joseph R. Jenkins, Maud Viger, Elizabeth C. Arnold, Zoe M. Harris, Maurizio
Ventura, Franco Miglietta, Cyril Girardin, Richard J. Edwards, Cornelia
Rumpel, Flavio Fornasier, et al.
To cite this version:
JosephR.Jenkins,MaudViger,ElizabethC.Arnold,ZoeM.Harris,MaurizioVentura,etal.. Biochar
alters the soil microbiome and soil function: results of next-generation amplicon sequencing across
Europe. Global Change Biology - Bioenergy, 2017, 9 (3), pp.591-612. ￿10.1111/gcbb.12371￿. ￿hal-
01541800￿
HAL Id: hal-01541800
https://hal.sorbonne-universite.fr/hal-01541800
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GCBBioenergy(2017)9,591–612,doi:10.1111/gcbb.12371
Biochar alters the soil microbiome and soil function:
results of next-generation amplicon sequencing across
Europe
JOSEPH R. JENKINS1, MAUD VIGER1, ELIZABETH C. ARNOLD1, ZOE M. HARRIS1,
MAURIZIO VENTURA2, FRANCO MIGLIETTA3,4, CYRIL GIRARDIN5, RICHARD J.
EDWARDS1,6, CORNELIA RUMPEL5,7, FLAVIO FORNASIER8, COSTANZA ZAVALLONI9,
GIUSTINO TONON2, GIORGIO ALBERTI3,9 andGAIL TAYLOR1
1CentreforBiologicalSciences,UniversityofSouthampton,SouthamptonSO171BJ,UK,2FacultyofScienceandTechnology,
FreeUniversityofBolzano/Bozen,PiazzaUniversit(cid:1)a1, 39100Bolzano,Italy,3MountForProjectCentre,EuropeanForest
Institute,ViaE.Mach1, 38010SanMichelea/Adige,Trento,Italy,4FoxLab,Forest&WoodScience,FondazioneE.Mach,Via
E.Mach1, 38010SanMichelea/Adige,Trento,Italy,5Ecosys,UMRINRA-AgroParisTECH,B^atimentEGER, AileB, 78820
Thiverval-Grignon,France,6SchoolofBiotechnologyandBiomolecularSciences,UniversityofNewSouthWales,Kensington,
Sydney,NSW 2052Australia,7IEES,UMR7618,CNRS-UPMC-UPEC-INRA-IRD,B^atimentEGER, AileB, 78820
Thiverval-Grignon,France,8AgriculturalResearchCouncil(CRA),ResearchCentrefortheSoil-PlantSystem,viaTreste23,
34170Gorizia,Italy,9DepartmentofAgriculturalandEnvironmentalSciences,UniversityofUdine,ViadelleScienze206,
33100Udine,Italy
Abstract
Wide-scale application of biochar to soil has been suggested as a mechanism to offset increases in CO emis-
2
sions through the long-term sequestration of a carbon rich and inert substance to the soil, but the implications
of this for soil diversity and function remain to be determined. Biochar is capable of inducing changes in soil
bacterial communities, but the exact impacts of its application are poorly understood. Using three European
sites [UK SRC, short rotation coppice, French grassland (FR) and Italian SRF, short rotation forestry (IT)] trea-
ted with identical biochar applications, we undertook 16S and ITS amplicon DNA sequencing. In addition, we
carried out assessments of community change over time and N and P mobilization in the UK. Significant
changes in bacterial and community structure occurred due to treatment, although the nature of the changes
varied by site. STAMP differential abundance analysis showed enrichment of Gemmatimonadete and Acidobacte-
ria in UK biochar plots 1 year after application, whilst control plots exhibited enriched Gemmataceae, Isosphaer-
aceae and Koribacteraceae. Increased mobility of ammonium and phosphates was also detected after 1 year,
coupled with a shift from acid to alkaline phosphomonoesterase activity, which may suggest an ecological and
functional shift towards a more copiotrophic ecology. Italy also exhibited enrichments, in both the Proteobacte-
ria (driven by an increase in the order Rhizobiales) and the Gemmatimonadetes. No significant change in the
abundance of individual taxa was noted in FR, although a small significant change in unweighted UNIFRAC
occurred, indicating variation in the identities of taxa present due to treatment. Fungal b diversity was affected
by treatment in IT and FR, but was unaffected in UK samples. The effects of time and site were greater than
that of biochar application in UK samples. Overall, this report gives a tantalizing view of the soil microbiome
at several sites across Europe and suggests that although application of biochar has significant effects on
microbial communities, these may be small compared with the highly variable soil microbiome that is found
in different soils and changes with time.
Keywords: 16SrDNA, Acidobacteria, Alphaproteobacteria Bacteria, amplicon, biochar, fungi, ITS, metabarcoding, microbiome,
Proteobacteria,Rhizobiales,soil
Received22October2015;revisedversionreceived15April2016andaccepted19April2016
Introduction
Soil contains thousands of bacterial and fungal taxa of
Correspondence:GailTaylor,tel.[phone],fax+440 which the majority remain uncharacterized and their
2380594469,e-mail:[email protected] effects on soil function are yet to be elucidated. Whilst
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.
ThisisanopenaccessarticleunderthetermsoftheCreativeCommonsAttributionLicense,
whichpermitsuse,distributionandreproductioninanymedium,providedtheoriginalworkisproperlycited. 591
592 J. R. JENKINS et al.
wehave someunderstanding ofthefactors whichdrive although decreases (Dempster et al., 2011; Paz-Ferreiro
microbial diversity (Fierer et al., 2012; Serna-Chavez et al., 2011; Carlsson et al., 2012) or no change have also
et al., 2013), we know relatively little about community beenobserved(Galvezet al.,2012;Bammingeret al.,2014).
changes in soils below the level of phylum. Although Microbial biomass is also altered following biochar
the driving factor in bacterial community diversity has application, with increases (Kolb et al., 2009; Belyaeva &
been determined to be pH (Fierer & Jackson, 2006), we Haynes,2011;Paz-Ferreiroet al.,2011),decreases(Demp-
still have limited knowledge on the impacts of ecosys- steret al.,2011)andnochange(Castaldiet al.,2011;Gal-
temsmanipulationexperimentsinthesecommunities. vez et al., 2012; Bamminger et al., 2014; Ventura et al.,
There has been much discussion regarding the use of 2014) all reported. Again, these are primarily short-term
biochar (pyrolysed biomass) as both a soil conditioner pot experiments, enabling accurate measurement of
and a method for carbon sequestration (Lehmann et al., microbialbiomass,withthetrade-offoflimitedvalidityin
2006; Major, 2010; Mao et al., 2012). Addition of biochar termsofeffectsoftreatment insitu.Therefore,itappears
to soil has also been shown to increase plant growth thatarangeofmicrobialresponsestobiocharapplication
(Barontiet al.,2010;Vaccariet al.,2011;Joneset al.,2012; canoccur,dependingonthebiochar(itsfeedstock,nutri-
Viger et al., 2015), possibly related to altered abiotic entcontentandpyrolysistemperature),theinitialedaphic
characteristics including increased pH, cation exchange conditions(pH,soilorganicmatter(SOM),soilmoisture,
capacity (CEC) and improved soil water content (Ver- bulk density and aeration), land use and management
heijen et al., 2010; Jeffery et al., 2011; Jones et al., 2012). regimes, vegetation types and the microbial community.
The soil physico-chemical changes induced by biochar Effects of biochar treatment have also been noted on
additionmayalsoplayapivotalroleindeterminingsoil microbial community structures, with decreases in
bacterial biodiversity because pH influences the biogeo- Betaproteobacteria, Bacteroidetes, Firmicutes, Proteobacteria
graphical distribution of bacteria (Fierer & Jackson, and Planctomycetes noted (Kolton et al., 2011; Ding et al.,
2006).Shiftsinmicrobialcommunitiesmayresultfroma 2013; Hu et al., 2014), as have (sometimes contradictory)
wide range of biochar-mediated interactions, including increases in Bradyrhizobiaceae, Hyphomicrobiaceae, Actino-
variations in microbial signalling (through sorption of mycetes, Chloroflexi, Nitrospiraceae, Proteobacteria, Tricho-
the molecules themselves; Masiello et al., 2013), derma, Pseudomonas, Actinobacteria, Baceroidetes, Firmicutes
increased transfer of electrons, resulting in augmenta- and Gemmatimonadetes (Graber et al., 2010; Anderson
tion of biological processes (Cayuela et al., 2013), shifts et al.,2011;Khodadadet al.,2011;Koltonet al.,2011;Ding
inmicrobialNcycling(Harteret al.,2014)anddecreased et al.,2013;Chenet al.,2014;Huet al.,2014).Thesestudies
abundanceoffungirelativetobacteria(whichcoulduti- suggest that biochar-mediated bacterial shifts have the
lize biochar substrates for growth; Gomez et al., 2014). potentialtochange the mineralization ofnutrients inthe
The increased fertility associated with biochar amend- soil (Kolton et al., 2011), or impact on biocontrol, plant
ment could be linked to these changes in the micro- growth promotion and organic compound degradation
biome.Forexample,additionofbiocharhasbeenfound (Graber et al., 2010). Few studies have determined the
to increase the abundance of bacteria and archaea oxi- impactofbiocharonfungalabundanceanddiversity,but
dizing ammonia to nitrates and nitrites (Prommer et al., these communities have also displayed a range of
2014), increase Bradyrhizobiacea and Hyphomicrobiaceae responses, including fluctuations in arbuscular mycor-
populations in short-term pot experiment on ryegrass rhizalfungi(AMF)colonizationandabundance(Warnock
(Andersonet al.,2011)andincreasednitrification(amoA, et al. 2010; Elmer & Pignatello 2011), decreased diversity
amoB), nitrogen fixing (nifH) and nitrite reduction (nirS, (Huet al.,2014),increasedfungalgrowth(Sunet al.2013),
nirK and nosZ) gene abundances (Ducey et al., 2013). A decreased fungal growth (Quilliam et al. 2012) and
126-day pot experiment studying the effects of biochar decreasesintheabundanceoffungi(Amelootet al.2014).
applicationonSandPmobilizingbacteriainLoliumper- Studies of fungi have indicated a decline in alpha (a)
enne indicated increased abundance of Rhizobacteria diversity due to the inability of fungal taxa to adapt to
associatedwiththemineralizationofSandPinnutrient rapid variation in the soil environment (Hu et al., 2014)
limited soils (Fox et al., 2014). However, previous stud- and shifts in community composition (Chen et al., 2013).
ies have been undertaken over short time scales and in Increased abundance of Trichloderma and Paecilomyces in
microcosm experiments, thus their relevance to long- biochar samples has also been noted (Hu et al., 2014),
termfieldimpactsremainsunknown. knowntoimprovesoilsandpromoteplantgrowth.
Observed effects of biochar on edaphic microbial pro- Using the 16S rRNA subunit gene and the ribosomal
cesses are often conflicting. Different studies have internal transcribed spacer region (ITS), surveys of the
observed increases in soil respiration (Kolb et al., 2009; relative abundance of bacterial and fungal operational
Zavalloni et al., 2011; Belyaeva & Haynes, 2011; Castaldi taxonomic units (OTUs) within a sample can be under-
et al., 2011; Quilliam et al. 2012; Ventura et al., 2014); taken without the need for culturing. These methods
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.,9,591–612
BIOCHAR ALTERS SOIL MICROBIOME AND FUNCTION 593
have the added advantage of detecting changes even in Field sites
unidentified species such that we can now begin to
Three field sites (Fig.1) were established across Europe. The
unravel complex ecological processes with the aid of
siteswerepartoftheEuroCharproject(www.eurochar.eu)and
molecular approaches. For example, 16S amplicon sur-
were located in West Sussex (UK), Prato Sesia (IT) and Lusig-
veys comparing existing agricultural practises with low
nan(FR)(Table2).
andhighapplicationsofbiocharenhancedwith chicken At all sites, biochar was added to the soil as previously
manure and rock phosphate indicated significant differ- described(Venturaetal.,2015).Asinglebiocharapplicationof
ences between high biochar and control bacterial diver- 30tha(cid:1)1 (65kg of biochar fresh weight, equivalent to
sity. This was due to decreased abundance of the 5.5kgm(cid:1)2dryweight,45%watercontent)wasappliedateach
Bacteroidete families Flavobacteriaceae and Saprospiraceae, siteinJune2012toadepthof15cm.IntheUK,thisapplication
the Planctomycete genus Planctomyes, the Alphaproteobac- was carried out using hand tools to minimize damage to the
pre-established Salix crop, whilst a rotary hoe was used for
teria families Hyphomonadaceae and Rhodobacteraceae and
application in IT and FR. Biochar was shipped to each site in
two Verrucomicrobia genera, Rubritalea and Roseibacillus
sealed plasticbags within weeksof its production, in order to
(Nielsen et al., 2014). However, this utilized enriched
maintainitssterility.Biocharwasnotsterilizedafterproduction,
biochars at a single field site, and so whilst representa-
as this would not be representative of real-world application
tive of the changes under those conditions, it is likely
scenarios. Treated and control plots were arranged in a com-
variation in response will occur in taxa treated with pletely randomized design, with four replicates per treatment.
nonenriched biochars. Furthermore, to date, next-gen- Plots were 4.392.75m, 599m and 594m at UK, IT and
eration sequencing (NGS) ITS amplicon surveys have FRsites,respectively.Differenceinplotsizereflectedthediffer-
not been used to study shifts in fungal abundance after entcroppingmethodsappliedateachsite.However,onlythree
biocharapplicationinafieldtrial. replicatesweresampledformicrobialcommunityanalysis.
It therefore remains unclear how biochar application
will effect bacterial and fungal populations within the Sampling
soil. Furthermore, it is uncertain whether the disparate
findingsofpreviousstudiesareduetodifferencesinthe Themicrobialcommunitywasassessedateachsite1yearafter
biochar application (July 2013). An additional intensive time
biochar used, the nature ofbiodiversity assessment, dif-
seriesexperimentwascarriedoutattheUKsite,withsamples
ferences inenvironments/communities studied or some
collected pretreatment during March 2012, 1month after bio-
combination of these factors. In this study, we applied
char amendment during July 2012 and 1year after biochar
16S rRNA and ITS short read amplicon sequencing to
applicationinJuly2013.Atallsites,biochar-treatedplotswere
assess detailed taxonomic changes in both bacterial and
referred to as B, whilst control was denoted C. A total of 130
fungal microbiomes as a result of field-scale treatment soil samples were collected from biochar amended plots and
using a standardized biochar, applied at three contrast- controlplotsusingasystematicsamplingdesign,with30sam-
ing sites across Europe and attempted to link our find- ples from FR, IT, UK 1month and UK 1year (5 samples93
ings in the UK to assessment of soil chemistry using replicates92treatments).Tensampleswerecollectedpriorto
measures of enzymatic activity and nutrient leachate. It biochar addition from UK pretreatment. Samples were col-
was hypothesized that in time series data for the UK, a lectedata1.5mradiusfromthecentreofeachplot.Consider-
able effort was maintained throughout sampling to ensure
short-termincreaseincopiotrophictaxawouldoccur,as
clean,uncontaminatedsamples,includinguseofglovesduring
labile portions of biochar become available as microbial
substrates. In addition, increases in the proportion of
Table1 Physico-chemical properties of AGT biochar applied
Actinobacteria and Acidobacteria were expected across all
inUK,FRandIT
sites, as these have been associated with carbon cycling
and the decomposition of complex carbon molecules Parameter Value Units
(Lehmannet al.,2011;Nielsenet al.,2014). BulkDensity 0.65 gcm(cid:1)3
pH(HO) 11.6 –
2
Salinity 758 mSm(cid:1)1
Materials and methods
H 2.3 %
H/C 0.5 –
Biochar characterization C 56.1 %
N 1.35 %
Biochar was produced by AdvancedGasificationTechnologies C:N 42.9 –
(AGTs.r.l.,Cremona,Italy),usingZeamaysfeedstockinafixed Ca 38.1 gkg(cid:1)1
bed, open core, down draft gasifier as previously described K 32.3 gkg(cid:1)1
(Venturaetal.,2015).Detailedchemicalcharacterizationofbio- P 8.56 gkg(cid:1)1
char produced by the gasification process can be found in S 1.32 gkg(cid:1)1
Wiedneretal.(2013)(Table1).
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.,9,591–612
594 J. R. JENKINS et al.
(a)
(b)
(c)
Fig.1 Details of each of the three field sites sampled(a) West Sussex UK (Grey), (b) Lusignan FR (Orange) and (c) Prato Sesia IT
(Purple).Tablesincludemeanannualtemperatureandrainfall,cropspecies,sitecoordinatesandsoildata.
Table2 SitepropertiesforUK,ITandFR
Meanannual
temperature
Locationandsitename andrainfall Soiltype pH Altitude Crop
WestSussex(UK) 10°C Permeable, 6.04 33ma.s.l. Salixsp.SRC
50°58038″N;0°27033″W 742.3mm seasonallywet,
clayandloam
PratoSesia,Novara(IT) 12°C Sandy 5.4 279ma.s.l. PopulusxcandadensisM€onch,
45°39032.27″N;8°21016.83″E 1200mm clone‘Oudemberg’,SRF
Lusignan(FR) 10.5°C Loamycambisol 6.8 153ma.s.l. Festucaarundinaceaand
46°25012.91″N; 600mm Dactylisglomeratagrassland
0°07029.35″E
sample collection and decontamination of equipment prior to extraction, a 50-ml sterile falcon tube was then filled with a
andduringsampling.Collectionwascarriedoutusingasteril- homogenizedportionofthesievedsample,priortofreezingin
izedstainlesssteelsoilcorer(15cm92.5cm).Oncecollected, liquid nitrogen. Samples were transported back to the labora-
soil samples were passed through sterilized stainless steel tory at (cid:1)80°C by cryoshipper. Between the sampling at each
sieves (mesh size 2mm) and homogenized. For DNA site,previouslycollectedsampleswerestoredat(cid:1)80°C.
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.,9,591–612
BIOCHAR ALTERS SOIL MICROBIOME AND FUNCTION 595
Extraction protocol reads disagree on a basecall, the programme utilizes the base
with the highest quality score. Combined reads were then
DNA extraction used MoBio Powersoil Extraction kits (MO
renamed and preprocessed using BESPOKE software (SeqSuite,
BIOLaboratories,Carlsbad,CA,USA).Briefly,0.5g(increased
http://bioware.soton.ac.uk), which renamed each read and
fromtherecommended0.25g,asaresultofexperimentaltest-
ensured names were compatible with QIIME. Formatted files
ingofmethodstoincreaseDNAyield)ofhomogenizedfrozen
wererunthroughtheQuantitativeInsightsintoMicrobialEcol-
soil was placed into a PowerSoil Bead Tube, before following
ogy(QIIME v1.8)pipeline(Caporasoetal.,2010b).Unlessother-
manufacturer’s specifications. DNA quality and concentration
wisestated,namedpythonscriptsarefromtheQIIMEpackage.
were assessed using a NanoDrop 1000 (Thermo Scientific,
ReadswereclusteredintoOTUsusingthepick_denovo_otus.py
Waltham, MA, USA) ensuring all samples had a minimum
workflow, clustering all reads at 97% identity using UCLUST
260/280 ratio of 1.8. Extracted samples were stored at (cid:1)80°C
(Edgar, 2010), prior to alignment using PyNAST (Caporaso
until all extractions were complete and ready for transport to
etal.,2010a).Classificationofsequenceswasundertakenusing
LGCGenomics(Berlin,Germany).
theRDPClassifier(Wangetal.,2007),trainedbytheGREENGENES
13.5 database (DeSantis etal., 2006). Phylogenetic trees were
Amplification and sequencing produced using the make_phylogeny.py command using
FastTree2 (Price etal., 2010). Filtering of errant sequences
IsolatedDNAfromeachsamplewasamplifiedusingthebacte- was undertaken through use offilter_otus_from_otu_table.py,
rial 16S rRNA gene primers 341F (50-TCC TAC GGG NGG removing singletons from the data set, before sorting samples
CWG CAG-30) and 785R (50-GAC TAC HVG GGT ATC TAA bytreatmentutilizingsort_otu_table.py.Taxonomicsummaries
KCC-30) (Klindworthetal., 2013)and the fungal primers fITS7 were generated using the summarize_taxa_through_plots.py
(50-TGTGARTCATCGAATCTTTG-30) and ITS4 (50-TTCCTCC script, generating bar charts showing the raw relative abun-
GCTTATTGATATGC-30) (Ihrmark etal., 2012). In the case of danceoutputofthepipeline,andmeanvaluesbytreatment.
the 16S region, these primers were chosen as they provide
approximately 470bp of sequence and are suitable for a wide ITS pipeline. Initial QC and read combination of ITS reads
range of bacterial taxa, amplifying the hypervariable V3-V4 werecarriedoutidenticallytothemethodsoutlinedinthe16S
regionandhavetheadditionalabilitytodetectasmallrangeof pipeline above. OTUs were picked using the open reference
archaea.TheITSprimerswerechosenastheyamplifytheITS2 pipeline which clusters reads against a reference sequence
region and include a portion of the 5.8S region. This primer database(inthiscase,theUNITEITSdatabase12.11;Ko~ljalgetal.,
pair has been shown to increase the diversity of fungi identi- 2013). Reads failing to match any within the database were
fied,whilstdecreasingmisrepresentationincommunities.Each groupedwiththeclosestmatchingcluster.
samplewastaggedwithanindividualeightnucleotidebarcode
toallowdemultiplexingofpooledsequencesintotheiroriginal
samples. Tagged samples were randomly pooled prior to Nutrientleaching, pH, respiration and soil enzymatic
library construction, to ensure a mix of treatments in each activities
sequencing lane (Carlsen etal., 2012). Amplification was car-
To coincidewiththe time seriesamplicondataat the UKsite,
ried out using 15 pmol of each forward and reverse primer,
added to 20ll of MyTaqbuffer,including 1.5 units of MyTaq further detailed analyses were undertaken to link soil micro-
DNA polymerase and 2ll of BiostabII PCR Enhancer. Thirty biometofunctionalattributesofthesoil.pHwasmeasuredfor
cyclesofPCRwereundertakenfor2minat96°C,followedby eachsample,usinga1:5watersoil:waterdilution(weight:vol-
96°C for 15s, 50°C for 30s and 72°C for 60s, and gel elec- ume) method in deionized water. Samples were agitated and
left to equilibrate for 1h before measurement using a Jenway
trophoresis was utilized to assess concentration. Finally,
3510 pH meter. Total and heterotrophic soil respirations were
approximately 20ng of PCR product was pooled prior to
monitoredonsiteaspartofapreviousworkduring2012–2013
purification using preparative gel electrophoresis. Purified
(Ventura etal., 2015). These used an automaticsoil respiration
amplicon, barcode and primer complexes were sequenced on
(SR) system to collect soil respiration data from control and
an Illumina MiSeq, using V3 reagent chemistry, producing
29300-bp paired-end reads. Reads were demultiplexed and biochar plots every 4h. Furthermore, heterotrophic and total
respirations were measured in each plot through the installa-
separated by their sample-specific barcodes. These steps were
tion of two SR chambersper plot, one unconstrained chamber
undertakenatLGCGenomics(Gmbh),Berlin,Germany.
measuringtotalSRandanothersurroundedbyarootexclusion
cylinder,measuringheterotrophicSRonly(forfurtherdetailed
SequenceAnalysisPipeline methodologyseeDelleVedoveetal.,2007;Venturaetal.,2014).
Samples were checked for curvature and rejected if the rela-
16S pipeline. Foreachsite,paired-endreadswerefirstquality tionshipbetweencumulativefluxandtimewasconcave,orifa
controlledandcombinedusingPandaSeq(Masellaetal.,2012). difference of <3ppm was detected between initial and final
PandaSeqcombinespaired-endreadsthroughareasofoverlap- flux measurements (Ventura etal., 2015).If this occurred, data
ping sequence, converting 29300bp reads into a single read was gapfilled using a model based on soil temperature and
of approximately 500bp in length and clips adapters and pri- moisture content (Qi & Xu, 2001; Delle Vedove etal., 2007).
mers from each read. Using .fastq input, PandaSeq is able to Mean daily flux was calculated during the period of the time
determine the quality score of each base, and in cases where seriessampling(19June2012–18June2013)foreachtreatment
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.,9,591–612
596 J. R. JENKINS et al.
group: total biochar, heterotrophic (root excluded) biochar, at the level of OTU. Due to difficulties in aligning the
totalcontrolandheterotrophic(rootexcluded)control. ITS sequences, nonphylogenetic measures (Chao1 or
Duringthesametimeperiod,resinlysimeterswereinstalled Bray–Curtis distance) were used to analyse a and beta
inbiocharandcontrolplotstoassessconcentrationsofammo- (b) diversity of fungal samples. Each sample was ran-
nium(NHþ),phosphates(PO3(cid:1) )andnitrate(NO(cid:1) )presentin
4 4 3 domly subsampled to 90% of the smallest sample at
leachateaftertreatment.Lysimeterswerepositionedtocapture
each site, to ensure that each sample was directly com-
leachatefromwithintherowandfrombetweenadjacentrows.
parable. Reported values represent the mean for each
Lysimeters consisted of a mixed ion-exchange resin (16.2g,
rarefied metric per treatment at each site (Table S1).
Amberlite MB-150, Sigma-Aldrich, Dorset, UK) held within
These rarefied values represent a normalized mean for
PVC pipe sections with a height of 3cm and a diameter of
5cm. To prevent direct contact with soil, a section of glass the samplesateach site. Speciesrichnesswasmeasured
beads (2mm diam.) was placedat either end of the resin and through use of a diversity metrics (observed species:
held in place using 125lm nylon mesh (Scubla s.n.c., Reman- OBS, Chao1 and phylogenetic diversity: PD), indicating
zacco,UD,Italy;Venturaetal.,2013).Installationoflysimeters whether a change in the number of different OTUs
wascarriedoutonthe10July2012.Threelysimeterswerebur- betweentreatmentsoccurred.Significanceofdifferences
iedverticallyatadepthof20cmineachplot.Thesewerecol- between sites and treatments used two-sample t-tests
lected during July 2013, approximately 1year after their
adjusted with Monte Carlo methods (using QIIME’s
placement.Oncecollected,lysimeterswereopenedinthelabo-
compare_alpha_diversity.pyscript).
ratory prior to washing of resin with 100mL of 2M KCl solu-
b diversity, the similarity between the identities of
tionwithin500mLErlenmeyerflasks.Thesewerethenshaken
taxa and their abundances by treatment, was assessed
at 100rpm for 1h using an orbital shaker before filtration
(Whatman no. 42 filters). NO(cid:1) and NHþ concentrations were through pairwise UNIFRAC distances (Lozupone &
3 4
detected in the washing solution through a continuous flow Knight, 2005) prior to plotting using EMPeror
automatic analyser (AxFlow AA3, Bran+Luebbe, Norderstedt, (V(cid:2)azquez-Baezaet al.,2013)orbespokeRscripts.Again,
Germany). Ammonium was detected using a combination of a single rarefaction of 90% of the smallest sample in
salicylate and dichloro-isocyanuric acid (ISO 11732:2005), each site was used to normalize samples. Unweighted
whilst sulphanilamide-NEDD [N-(1-Naphthyl)ethylenedia- UNIFRAC methods determine whether the identities of
mine] was used for nitrate (ISO 13395:2006) (Ventura etal., taxa within communities change, whilst weighted UNI-
2013).PO3(cid:1)analysisofextractswascarriedoutusinganinduc-
4 FRACrepresentstheidentitiesofthetaxa,andtheirrel-
tivelycoupledplasmaopticalemissionspectrometer(ICP-OES,
ative abundances. Using both metrics, we determined
SpectroArcos,Ametek,Germany).
whether community structure varied due to changes in
During the campaign to collect soil material for sequenc-
taxonomic abundance or shifts in the identities of taxa
ing, additional samples were collected for soil enzymatic
present due to treatment. To statistically assess the
activity (EA) analysis. Samples were collected using the same
method as the amplicon samples, prior to analysis. dsDNA differences between a diversities, a nonparametric two-
was extracted from soil samples following the procedure sample t-test was utilized using the compare_alpha_
from Fornasier etal. (2014). Briefly, DNA was extracted with diversity.py script within QIIME. b diversities at the
a 0.12M, pH 8 Na2HPO4 buffer using bead beating; dsDNA level of OTU in treated and control samples were anal-
was quantified in a crude (not purified) extract using the ysed through use of principle coordinate analysis
PicoGreen reagent. Soil EAs quantified were as follows: aryl- (PCoA), prior to ADONIS statistical testing for signifi-
sulfatase, b-glucosidase, acid and alkaline phosphatase, phos-
cance(999permutations)(Oksanenet al.,2016).Tocom-
phodiesterase, esterase and leucine aminopeptidase. EA
pensate forthe multiple ADONIS tests carried out (four
substrates were determined after treating soil subsamples
unweighted UNIFRAC tests for 16S – UK 1 month, UK
with an extraction/desorption procedure (Fornasier & Mar-
1 year, FR and IT, 4 weighted UNIFRAC tests for 16S
gon, 2007). Extracts were obtained using 400mg of soil and
1.2mL of extractant (3% lysozyme, Cowie etal., 2013) in and 4 ITS tests of Bray–Curtis distances = 12 in total), a
2mL Eppendorf tubes containing 0.4mL of 1mm diameter Benjamini–Hochberg correction was applied to an FDR
ceramic beads and 0.4mL of 100 micron glass beads. Tubes of 0.05 (Benjamini & Hochberg, 1995). As a result, each
were shaken for 3min at 30 strokes s(cid:1)1 using a Retsch 400 q-score which passed the threshold set for significance
beating mill then centrifuged at 15000g for 3min. Aliquots representsonlya5%chanceofafalsepositive.
of supernatants were dispensed in 384-well microplates with Finally, differential abundance testing of each taxo-
appropriate buffer to determine EA using fluorescent nomic level (from phylum to genus) was carried out
4-methylumbelliferyl substrates.
using STAMP (Parks & Beiko, 2010), using two-sided
Whites nonparametric t-tests (White et al., 2009), with
Benjamini–HochbergFDRcorrectionformultipletesting
Statisticalmethods
(Benjamini&Hochberg,1995).Theseanalyseswerecar-
To understand the impacts of biochar on the number of ried out to compare the differences between treatments
taxa present in each samples, a diversity was calculated at each site and to compare temporal differences within
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.,9,591–612
BIOCHAR ALTERS SOIL MICROBIOME AND FUNCTION 597
treatments in UK time series samples. Statistically sig- 1 year after treatment. FR samples contained 581 030
nificant results were filtered to include only OTUs reads (l = 19367.667, r = 7074.381), whilst IT contained
which had >5 sequences, where the difference between a total of 832 375 reads (l = 27745.833, r = 10757.089).
proportions was >0.5% or the ratio of proportions >2. A After rarefaction of data (to 90% of the reads from the
q-value of 0.05 was used, representative of a 95% confi- smallest sample), downstream analysis used 7619 (UK
dencethatasignificantresultisnotafalsediscovery. 1 month), 1827 (UK 1 year) and 3354 (FR) 2940 (IT)
In addition, to detect the differences between the ini- reads,respectively.
tialcommunitycompositionsofeachsite,afurthercom-
parison of the control samples from each site at 1 year
Bacterialcommunitystructureanddiversity
was undertaken using the same methods described
above. The effect of site on initial community structure. Compar-
To assess correlation between taxonomic and pH dis- ison of the sites prior to treatment showed significant
tance matrices, Mantel tests were conducted for each differences in community structure. a diversity analysis
site using QIIME (compare_distance_matrices.py) to revealed significant differences between UK and conti-
determine whether there was a significant correlation nental Europe for bacterial richness regardless of the
between biochar induced pH change and community metric used. UK samples displayed lower richness than
structure. Additionally, a two-way analysis of variance the continental samples, although both FR and IT com-
(ANOVA)lookingattheeffectofsite(IT,FRandUK)and munitieshadsimilaradiversities(Fig. 2).
treatment (biochar and control) on soil pH was con- bdiversity ofthe sitesrevealed significant differences
ductedinR. in bacterial community structure and abundance.
For respiration measurements, ANOVA was carried out Results ofboth weighted UNIFRAC PCoA revealed sig-
using SPSS (IBM SPSS Statistics for Windows, Version nificant clustering of samples (Fig. 3a) by site (ADONIS
22.0. Armonk, NY, USA: IBM Corp) using a between R2 = 0.16, P = 0.001). Therefore, we conclude that there
subjectsdesign,factoringthetreatment(biocharvs.con- were substantial differences between the bacterial taxa
trol), the partitioning of respiration (total vs. hetero- present, and their abundances within the communities
trophic)andtheinteractionbetweenthetwofactors. presentateachofthethreesites.
To test for differences in the leachate in the UK, a a diversity analysis of fungal communities revealed
(cid:1) þ
two-wayANOVAwasusedforeachchemical(NO3,NH4 no significant differences in fungal richness by site.
and PO3(cid:1)) extracted from the lysimeters. Homogeneity However, fungal b diversity analysis by site revealed a
4
of variance was checked using Levene’s test. When similar pattern to that observed inthe bacterial samples
homogeneity of variants was not respected, Mood’s (Fig. 3b), in that distinct clusters formed based on the
median test was carried out to identify divergences site of origin of each sample (ADONIS: R2 = 0.56,
betweentreatments.Normalityofdatawasnotchecked, P = 0.001). Therefore, it appears that there are signifi-
due to the relatively low number of replicates. Treat- cant differences in the taxa present and in their relative
ment (control vs. biochar) and position of lysimeter proportionsateachsite.
(outside left, within row, outside right) were indepen-
dent variables. STATGRAPHICS software (Statpoint Inc., The effect of biochar treatment on community struc-
Warrenton,VA,USA)wasusedforstatisticalanalysis. ture. Biochar treatments had no significant effect
Finally, to detect changes taking place in enzymatic detectedforanyofthemetricsusedtoassessbacteriala
activities, ANOVA for dsDNA and EAs was performed in diversity at any of the sites 1 year after treatment
SPSS (IBM SPSS Statistics for Windows, Version 22.0: (Table S1). The impact of biochar on bacterial b diver-
IBM Corp) using a one-way ANOVA. ANOVAs were per- sity was significant but differed depending on site.
formed including soil treatment (biochar vs. control) as PCoAforbiocharsamplescollectedafter1 yearshowed
fixedfactor. a significant difference in weighted (ADONIS:
R2 = 0.12, q = 0.004) and unweighted (ADONIS:
R2 = 0.06, q = 0.004) UNIFRAC distances between UK
Results
controlandbiocharsamples(Fig. 4a).ITresultsshowed
significant clustering by treatment on weighted
Sequencedata
(ADONIS: R2 = 0.08, q = 0.013) and unweighted
A total of 2 453 023 reads were produced, of which (ADONIS: R2 = 0.06, q = 0.004) UNIFRAC distance
299 593 (l = 19972.867, r = 3859.847) were from UK (Fig. 4b). Finally, results for FR showed no significant
pretreatment, 502 318 (l = 16743.933, r = 5414.146) clusteringbytreatmentintheweightedUNIFRACanal-
were from UK samples 1 month after treatment, and ysis (Fig. 4c) although unweighted (ADONIS: R2 = 0.04,
237 707 (l = 7923.567, r = 3832.652) were from the UK q = 0.004) UNIFRAC showed significant differences
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.,9,591–612
598 J. R. JENKINS et al.
Fig.2 adiversitymetricsshowing(a)Observedspecies,(b)Chao1and(c)PhylogeneticdiversitymetricdataforUKpretreatment,
UKafter1month,UKafter1year,ITandFR(ITandFRarelabelledtoindicatethatsamplesweretaken1yearaftertreatment).ITS
analysisofObservedspeciesandChao1isshownin(d)and(e).Eachplotshowsaveragevaluesforbiocharinred,controlinblue
andpretreatmentingreen.
between treatments, indicating a shift in OTUs present revealedasignificantlinearpositivecorrelation(Mantel:
betweentreatmenttypes(Fig.S1). R = 0.15, P = 0.001; Fig. S2). This reflects an increasing
Mantel tests comparing bacterial unweighted diversity of taxa as pH increased, as a consequence of
UNIFRAC b diversity with pH distance matrices thebiochartreatment.
Fig.3 Principle coordinate analysis of bacterial (left hand column) and fungal (right hand column) OTU weighted UNIFRAC dis-
tancesforcontrolsamplesatUK(greycircles),IT(purplesquares)andFR(yellowtriangles)sites.Samplesarefromthesummerof
2013,1yearafterbiocharapplicationateachsite.
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BIOCHAR ALTERS SOIL MICROBIOME AND FUNCTION 599
©2016TheAuthorsGlobalChangeBiologyBioenergyPublishedbyJohnWiley&SonsLtd.,9,591–612