at SciVerse ScienceDirect

Soil Biology & Biochemistry 53 (2012) 112e119

Contents lists available

Soil Biology & Biochemistry

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

Soil fungi influence the distribution of microbial functional groups that mediateforest greenhouse gas emissions

David J. Burke a,b,*, Kurt A. Smemo a,c, Juan C. López-Gutiérrez a,d, Jared L. DeForest e

a The Holden Arboretum, Kirtland, OH 44094, USAb The Department of Biology, Case Western Reserve University, Cleveland, OH 44106, USAcDepartment of Biological Sciences, Kent State University, Kent, OH 44242, USAd Ecosystem Science and Management Program, University of Northern British Columbia, Prince George, British Columbia V2N 4Z9, CanadaeDepartment of Environmental and Plant Biology, Ohio University, Athens, OH 45701, USA

a r t i c l e i n f o

Article history:Received 15 December 2011Received in revised form2 May 2012Accepted 13 May 2012Available online 2 June 2012

Keywords:ArchaeaDenitrifying bacteria (DNB)Methane oxidizing bacteria (MOB)FungiNutrientsTRFLPHardwood forestExtracellular enzymes

* Corresponding author. The Holden Arboretum, 9544094, USA. Tel.: þ1 440 602 3858; fax: þ1 440 602

E-mail addresses: david.j.burke@case.edu, dburke@

0038-0717/$ e see front matter � 2012 Elsevier Ltd.doi:10.1016/j.soilbio.2012.05.008

a b s t r a c t

The distribution of microbial functional groups in soil may be governed by the interaction between thesoil environment and the presence of other microbial competitors or facilitators. In forest soils, one of themost important groups of organisms are fungi, which are vital to many ecosystem processes such asnutrient cycling and decomposition, and can form direct connections to primary producers. Neverthe-less, the overall effect of soil fungi on the structure and distribution of the other soil microbial functionalgroups has not been thoroughly investigated. We hypothesized that by altering the soil environment,fungi create favorable conditions for Archaea, methane oxidizing bacteria (MOB) and denitrifyingbacteria (DNB), thereby potentially influencing the ability of forest soils to produce or consume green-house gases. To test these hypotheses, we studied the distribution of microbial functional groups andfungi in forest soil using molecular methods and related that distribution to soil environment andextracellular enzyme activity as a measure of microbial activity and metabolic effort. Non-metricmultidimensional scaling of terminal restriction fragment length (TRFLP) profiles found that DNB andMOB largely separated within ordination space, suggesting little overlap of these bacteria in soil cores. Inaddition, DNB were significantly positively correlated with fungal biomass and with chitinase activitywhile MOB were negatively correlated with both. Most archaeal TRFs were also negatively correlatedwith fungal biomass, suggesting that forest Archaea and MOB have similar relationships to fungalbiomass. Soil chemistry including soil carbon (C), nitrogen (N) and bicarbonate extractable phosphorus(P) were not significantly correlated with DNB, MOB or Archaea. Our results suggest that soil fungi mightinfluence the spatial distribution of important prokaryotic groups in forests, including some groups thatmediate the production and consumption of important greenhouse gases.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

Soil microbes play an important role in ecosystem function andmay act as filters or valves that regulate the intra-system cycling ofsoil nutrients (Pastor et al., 1984). Important functions carried outby soil microbes include maintenance of soil fertility (i.e. nutrientcycling and organic matter decomposition), and regulating theemission and consumption of important greenhouse gases such ascarbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)(Bardgett et al., 2008; Forster et al., 2007). Changes in microbialdiversity or community structure could have dramatic impacts on

00 Sperry Road, Kirtland, OH8005.holdenarb.org (D.J. Burke).

All rights reserved.

ecosystem processes (Prosser, 2002), and the ability of microbes tomaintain soil fertility or regulate nutrient cycling may be largelydependent on the composition of soil microbial communities(Robertson et al., 2000; Singh et al., 2010). While past workaddressing the spatial structure and distribution of soil microbialcommunities has focused on assembly rules for microbial groups(e.g. Green et al., 2004; Horner-Devine et al., 2004) or environ-mental controls such as redox (e.g. Pett-Ridge and Firestone, 2005),resource availability (e.g. Zak et al., 2003), and pH (e.g. Rousk et al.,2010), less attention has been given to the spatial relationshipbetween different microbial groups as a factor that may affect theirdistribution and persistence.

For example, in temperate hardwood forests, soil fungi are a keycomponent of the soil food web acting as both decomposers (sap-rotrophs) and plant mutualists (mycorrhizas) (Rayner and Boddy,

D.J. Burke et al. / Soil Biology & Biochemistry 53 (2012) 112e119 113

1988; Leake et al., 2002; Parniske, 2008; Smith and Read, 2008). Inprevious work, we found that fungal communities associated withtree roots vary seasonally in a mature hardwood forest, and fungaldistribution is influenced by fine scale spatial variation in soilnutrient content as well as the presence of both of trees andherbaceous plants (Burke et al., 2009). Bacterial communities andspecies can also be affected by spatial changes in soil nutrientcontent (Lynch, 1988; Poly et al., 2001), fertilization of forest soil(Burke et al., 2006a), and leaf litter from different plant species(Burke and Chan, 2010). The spatial structure of fungal biomass canalso potentially create a patchy soil environment for other micro-bial groups with respect to redox, pH, and nutrient/substrateavailability (Reid, 1984; Rygiewicz et al., 1984; Linderman, 1988;Grayston et al., 1997; Smith and Read, 2008). Such heterogeneityin the soil environment could be important for the distribution andfunction of microbial functional groups in forest soil. However, theoverall influence of fungal biomass on environmental conditionsand the distribution of other microbial groups are still poorlyunderstood and additional research into spatial patterns of forestmicrobes and their interrelationships is needed.

In this study, we examined the distribution of microbial func-tional groups and fungal biomass in forest soil using molecularmethods and related that distribution to soil environment andextracellular enzyme activity as a measure of microbial activity andmetabolic effort. We chose to specifically examine how the distri-bution of fungal hyphae, that could alter soil environmentalconditions in ways important for other microbial groups, affectedthe distribution of soil Archaea, anaerobic denitrifying bacteria(DNB), and aerobic CH4-oxidizing bacteria (MOB). We chose thesegroups because factors controlling their distribution in maturehardwood forests are poorly understood (Bates et al., 2011); yet,their distribution and community structure could potentially affectwhether forest soils act as a source or a sink for CO2, CH4, and N2O(Forster et al., 2007; Bardgett et al., 2008).

Specifically, we hypothesized that 1) because many describedsoil Archaea are from groups responsible for ammonia oxidation ornitrification (Leininger et al., 2006) and CH4 production (meth-anogenesis) under anoxic conditions (Pesaro and Widmer, 2002),archaeal community structure and the relative abundance ofarchaeal taxa will be positively associated with fungal biomass dueto reduced soil redox conditions and enhanced substrate avail-ability and; 2) the community structure and relative abundance ofMOB and archaeal taxa will be positively associated with fungalbiomass in forests because MOB may be substrate-limited andtherefore prevalent near zones of active CH4 production; and 3)because DNB distribution is often explained by C availability andNO3

� pools (Wallenstein et al., 2006), we hypothesized a negativerelationship between fungal biomass and the community structureand relative abundance of DNB taxa. Specifically, we expecteda negative relationship because fungi and DNB may competedirectly for soil C and nutrients.

2. Materials and methods

2.1. Site description and sampling

We established our study site in a 80-ha section of old growthbeech-maple forest within Stebbins Gulch, a mature, 360 ha,northern hardwood forest located at The Holden Arboretum innortheastern Ohio, USA (41�360N and 81�160W) and a part of theHolden Natural Areas National Natural Landmark (http://www.nature.nps.gov/nnl/site.cfm?Site¼HOLD-OH). Total precipitationaverages around 116-cm per year, with an average of 287-cm ofsnowfall per season. The soils at the site are classified as a Mahon-ing silt loam (Aeric Epiaqualfs). These soils are characterized by

gently sloping ground (2e6% slope), somewhat poorly drained soilsthat form on till plains. Soil organic matter is concentrated in thetop 5-cm and a perched water table is common, especially in earlyspring. To capture natural variation in microbial distribution, soilcores were collected at 5-m intervals along three randomly selected100-m transects (Supplemental Fig. 1) in September of 2006 toa depth of 5-cm using a 10-cm diameter metal soil corer, trans-ported on ice to the laboratory, and subsequently sieved (2 mm) toseparate soil from root tissue. We did not collect recent leaf litterbut restricted our sampling to the Oe, Oa and A horizons. Of the 60total samples collected as part of a larger study (Burke et al., 2009),22 of those samples were chosen for a detailed analysis of microbialcommunity functional groups and fungal biomass (reported here).A portion of field fresh soil was used for analysis of pH and soilmoisture, and the remaining soil frozen and stored at �70� C forsubsequent microbial and chemical analysis. At each sample pointalong the 100-m transects, we estimated percent herbaceous plantcover within a 0.25 m radius and identified andmeasured diameterat breast height (dbh) of all overstory trees (>2 cm dbh) withina 5 m radius.

2.2. Soil chemical analyses

Field fresh soil was used to measure soil pH (1:1H2O) andgravimetric water content and is expressed here as [(g water g FWsoil�1)� 100%]. Soil for C, N and Pwas oven-dried and pulverized ina Precellys homogenizer (Bertin Technologies, Montigny-le-Bretonneux, France). Soil C and N was measured on an ECS 4010CHNSO elemental analyzer (Costech Analytical, Valencia, CA). Driedsoil was used to determine labile soil inorganic phosphorus (Pi;readily available) and organic phosphorus (Po; easily mineralizable)using colorimetric techniques. Labile soil P was extracted by adding0.5 M NaHCO3 (pH 8.5) and shaking at 100 rpm on an orbital shaker(Lab-Line, Melrose Park, IL) for 30 min (Olsen et al., 1954). Pi wasdetermined using the modified ascorbic acid method (Kuo, 1996)directly on the NaHCO3 extracts, while Po was determined by theincrease in Pi after NaHCO3 extracts were digested with 1.8 N H2SO4and (NH4)2S2O (EPA, 1971).

2.3. Enzyme assays and PLFA

Potential soil extracellular enzyme (EE) activity was measuredusing soil slurries and high throughput 96-well microplate proto-cols (Saiya-Cork et al., 2002; DeForest et al., 2004). Methyl-umbelliferone (MUF)-linked model substrates were used tofluorometrically estimate the activity of enzymes associated withthe breakdown of cellulose (b-1,4-Glucosidase (BG)), chitin (b-1,4-N-Acetylglucosaminidase (NAG)), starches (a-1,4-Glucosidase(AG)), and phosphate monoesters (acid phosphatase (AP)). Fluo-rescence was measured at 20 �C with a Synergy HT microplatereader (BioTek, Winooski, VT, USA).

Microbial biomass and abundance of broad taxonomic microbialgroups (such as bacteria, fungi, actinomycetes and arbuscularmycorrhizae) was estimated using phospholipid fatty acid (PLFA)analysis (Tunlid et al., 1989; Vestal and White, 1989; Zelles, 1999;Olsson and Wilhelmsson, 2000). Analytical recovery was deter-mined by adding phospholipid 19:0 standard (Avanti Polar Lipids,Inc., Alabaster, AL, USA). Total lipids were extracted from freeze-dried soil, and polar and nonpolar lipids were separated andquantified using an HP GC-FID (HP6890 series, Agilent Technolo-gies, Inc. Santa Clara, CA, USA) as described elsewhere (DeForestet al., 2004; DeForest and Scott, 2010). Biomarkers were identi-fied using the Sherlock System (v. 6.1, MIDI, Inc., Newark, DE, USA).We also assessed fungal biomass in each soil core by extraction andquantification of ergosterol via high-pressure liquid

D.J. Burke et al. / Soil Biology & Biochemistry 53 (2012) 112e119114

chromatography using a PerkinElmer Series 200 HPLC (Perki-nElmer Inc., Waltham, MA) following general procedures in Gonget al. (2001). In brief, 500-mg of field wet soil was shaken for 1 hat room temperature, centrifuged for 10 min at 11,000 rpm andvacuum centrifuged in the dark to completely evaporate themethanol and concentrate the ergosterol. Dried ergosterol wassuspended in 75-mL of fresh methanol and used for HPLC analysisand fungal dry weight determined as perMontgomery et al. (2000).

2.4. DNA extraction and amplification

DNA was extracted from soil using a bead beating protocol(Burke and Chan, 2010). Briefly, 500-mg fresh soil was placed ina 1.5-mL bead beating tube containing 500mg of sterile glass beads(300-mg of 400 mM glass beads [VWR,West Chester, PA, USA], 200-mg 1mm glass beads [Chemglass, Vineland, NJ, USA]) and 750 mL of2% CTAB (cetyltrimethyl-ammonium bromide). Samples were thenbeaten for 40 s in a Precellys homogenizer at 6500 rpm andapproximately 500-mL of the supernatant was removed and DNApurified by phenol/chloroform extraction and precipitation with20% polyethylene glycol 8000 in 2.5 M NaCl (Burke et al., 2005,2006b). DNA was suspended in 100 mL TE (Tris EDTA) buffer and25 mL of the DNA was further purified using a Wizard SV Gel andPCR Clean Up System (Promega, Madison,WI, USA) according to themanufacturer’s instructions. Following gel extraction, DNA wassuspended in PCR grade water and stored at �20 �C.

2.5. Molecular analysis of microbial functional groups

We targeted the 16S rRNA gene to analyze soil Archaea usinglabeled primers ARCH915-forward (6-carboxyfluorescein [6FAM])(Amann, 1995) and UNI-b-reverse (4, 7, 20, 40, 50, 70 -hexachloro-6-carboxyfluorescein [HEX]) (Brandt et al., 2001) using PCR condi-tions as described by Pesaro and Widmer (2002). PCR product wasdigested with restriction enzymes MspI and HaeIII (Promega,Madison, WI, USA). To amplify the community of DNB, we targetedthe functional gene nitrous oxide reductase (nosZ) using theprimers nosZFb-forward (6FAM) and nosZRb-reverse (HEX) (Röschand Bothe, 2005), following conditions as described in Rösch et al.(2002) and digested the product with restriction enzymesMboI andTaqI (Promega, Madison, WI, USA). Finally, we described the MOBcommunity by targeting the functional gene particulate methanemonooxygenase (pmoA) with labeled A189-forward (6FAM) andmb661-reverse primers (Costello and Lidstrom, 1999). We initiallyfollowed PCR conditions as described in Costello and Lidstrom(1999); however, these conditions resulted in the production of 2PCR bands, one approximately 585 base pairs (bp) and another 510bp in size. Subsequent cloning and sequencing revealed that thelarger band consisted of non-specific amplification productwhereas the smaller band showed high affinity to the pmoA gene.Consequently, we adjusted the PCR conditions to eliminate thelarger band and amplify only the smaller specific band. We useda touchdown PCR protocol consisting of an initial denaturation stepof 4 min at 95 �C followed by 33 cycles where the denaturation stepwas 95 �C for 1 min, the annealing step was held for 1 min, and anextension step at 72 �C for 1 min. Annealing temperaturesdecreased by 1 �C, lowering from 62 �C to 55 �C during the protocolas follows: 62 �C for 2 cycles, 61 �C for 2 cycles, 60 �C for 3 cycles,59 �C for 3 cycles, 58 �C for 4 cycles, 57 �C for 4 cycles, 56 �C for 4cycles, and 55 �C for 11 cycles. A final 5-min extension at 72 �Ccompleted the protocol. Purified pmoA PCR product was digestedwith restriction enzymes MspI and HaeIII (Promega, Madison, WI,USA).

PCR for all bacterial groups was carried out in 50 mL reactionvolumes using 1-mL of gel purified DNA, 0.2 mm of primers, 2.0 mM

MgCl, 0.2 mM dNTP, 0.25 mg Bovine Serum Albumin, and 1.0 unitTaq DNA polymerase (Promega, Madison, Wisconsin, USA) on anPTC 100 Thermal Cycler (MJ Research, Boston, USA). Terminalrestriction fragment length polymorphisms (TRFLPs) werecompleted through the Life Sciences Core Laboratories Center(Cornell University) using an Applied BioSystems 3730xl DNAAnalyzer and the GS600 LIZ size standard. Profiles were analyzedusing Peak Scanner� Software (version 1.0, Applied Biosystems2006). For our analyses, only peaks that accounted for greater than50 fluorescence units (scale of 5000) and greater than 1% of therelative peak area were included (i.e., major TRFs; Burke et al.,2008). We have found that peaks with less than 1% of totalprofile area are generally not repeatable between replicate samples(Burke et al., 2008; Burke and Chan, 2010) and although excludingthese peaks may provide a more conservative estimate of microbialdiversity and community structure, it reduces the chances thatnon-specific TRFs will be included in our analysis (Dunbar et al.,2001).

PCR was also conducted for all bacterial groups using unlabeledprimers for cloning and sequencing of the targeted groups. Cloningand sequencing was intended to confirm the specificity of therespective amplifications and provide a snapshot of the groupsmost commonly found in our forest soils. PCR conditions were asnoted above and PCR product was gel extracted prior to cloningusing the Wizard SV Gel and PCR Clean Up System (Promega,Madison, WI, USA). Gel extracted PCR product was cloned usinga pGEM-T Easy vector system (Promega, Madison, WI), followingthe manufacturer’s instructions. Randomly selected colonies wereincubated overnight at 37 �C in LB medium, and plasmids wereharvested using a Wizard Plus SV Miniprep DNA purificationsystem (Promega, Madison, WI). Sequence assignments weredetermined for Archaea using the Naive Bayesian rRNA Classifierfrom the Ribosomal Database Project (Wang et al., 2007) with theconfidence threshold set at 90%. Sequence assignments weredetermined for DNB (nosZ) and MOB (pmoA) by comparing thegenerated sequences to EMBL/GenBank/DDBJ database entriesusing the NCBI Blast tool through the European BioinformaticsInstitute (http://www.ebi.ac.uk/).

2.6. Statistical analyses

Detected TRFs were used as operational taxonomic units (OTU)and are considered proxy measures of microbial taxa, even thougheach TRF may represent many microbial species (Burke et al.,2006b, 2008; Feinstein et al., 2009; Burke and Chan, 2010). Therelative peak area of each TRF for detected Archaea and DNB andMOB was used for non-metric multidimensional scaling (NMS)analysis of community structure using PC-ORD 4 (MjM Software,OR). All peak area data was arcsine-square root transformed priorto analysis. The Sørenson distance with a random starting config-uration was used for these analyses. A maximum of 400 iterationswere used for 50 runs, with data for the Monte Carlo testrandomized. Archaea, DNB and MOB TRFs were analyzed togetherin the same ordination. We used Archaea community profilesgenerated with the HEX-labeled reverse primer using restrictionenzyme HaeIII; profiles generated with MboI and the HEX-labeledreverse primer were used to represent the DNB; and profilesgenerated with HaeIII and the 6FAM-labeled forward primer torepresent the MOB in NMS analysis. These enzymes and labeledfragments were chosen for analysis because they provided thelargest number of distinct TRFs for the respective communities.NMS analysis of microbial community structure was performed onthese three groups of soil microbes only. Soil physiochemicalconditions, enzyme activity, fungal and bacterial biomass (PLFA)and plant data were considered to be environmental features and

Table 2Phospholipid fatty acid content of microbial groups present in soil from StebbinsGulch. Means and standard errors in parenthesis.

Taxonomic group nmol PLFA g�1 soil

Total 324.9 (95.7)Bacteriaa 182.9 (65.0)Generalb 100.0 (23.8)Fungic 19.8 (2.3)Arbuscular mycorrhizad 10.6 (3.3)Actinomycete and Protozoae 11.0 (3.1)Unknownf 0.5 (0.3)

D.J. Burke et al. / Soil Biology & Biochemistry 53 (2012) 112e119 115

NMS was used to determine whether any of these environmentalfeatures was correlated with community structure determined byTRFLP. Consequently, fungal community composition was notexamined in this study or included in the ordination, but fungalbiomass was considered an environmental feature that couldinfluence archaeal, DNB and MOB community structure and taxadistribution. Significance of correlations was determined using thecritical values for correlation coefficients (Zar, 1998). For all samples(n¼ 21, excluding 1 sample outlyer), Pwas <0.05 for an r of >0.423(two-tailed test).

a Includes biomarkers i15:0, i16:0, 16:1u9c, 10Me16:0, i17:0, a17:0, cy17:0,c17:0, 18:1u7c, 18:1u7t, 18:1u5c, cy19:0a and c19:0.

b Includes biomarkers i14:0, c14:0, 16:1u7c, c16:0 and c18:0.c Includes biomarkers 18:2u6 and 18:1u9c.d Includes biomarker 16:1u5c.e Includes biomarkers 10Me18:0, 18:3u3 and 20:4u6.f Includes biomarker 20H-16:0.

2.7. Accession numbers

All sequences recovered in this study were deposited into theEMBL/GenBank/DDBJ database through the European Bio-informatics Institute. Sequence accession numbers for archaealclones are HE603013 e HE603078; DNB sequence accessionnumbers are HE602974 e HE603012; and MOB sequence accessionnumbers are HE602960 e HE602973.

3. Results

3.1. Soil chemistry and enzyme activity

Soil gravimetric water content ranged from 25 to 45% witha mean of 34.6% (Table 1). Soils were strongly acidic, with pHranging between 3.4 and 5.3 and a mean of 3.9 � 0.1. Soil N rangedfrom 2.5 to 11.2 mg N g soil�1 soil while soil C ranged from 32.1 to209.1 mg C g soil�1. Bicarbonate available inorganic P ranged from5.5 to 75.9 mg P kg�1 soil with a mean of 33.6 � 3.6 while bicar-bonate available organic P ranged from 19.5 to 128.1 mg P kg�1 soilwith a mean of 57.7 � 7.7. AP activity varied greatly in our samples,ranging between 7 and 1917 nmol h�1 g soil�1 with a mean of671 �114 nmol h�1 g soil�1. BG and NAG activity was less than thatof AP with mean rates of 322 � 63 and 157 � 51 nmol h�1 g soil�1,respectively. We generally detected very low levels of AG activity(Table 1).

3.2. PFLA analysis of soil microbial biomass

Bacterial specific PLFA biomass ranged from 30 to 1510 nmolPLFA g�1 soil with a mean of 183 � 65 nmol PLFA g�1 soil, and onaverage dominated microbial biomass and accounted for 56% of thetotal PLFA biomass (Table 2). Fungal biomass ranged between 7 and50 nmol PLFA g�1 soil, representing on average 6% of total PLFAmicrobial biomass. Biomass of AMF ranged from approximately1e75 nmol PLFA g�1 soil, and represented a relatively small portionof total biomass on average (w3.2%; Table 2). A significant portion

Table 1Soil chemical analysis and enzyme activity of forest soil samples from StebbinsGulch. Means � standard error of the mean are shown.

Soil parameter

Water content 34.6 (1.4)pH 3.9 (0.1)N (mg g�1) 4.9 (0.4)C (mg g�1) 78.3 (8.3)C:N 15.5 (0.4)Labile Pi (mg kg�1) 33.6 (3.6)Labile Po (mg kg�1) 57.7 (7.7)Acid phosphatase (nmol h�1 g�1) 671.3 (114.1)a-1,4�Glucosidase(nmol h�1 g�1) 13.1 (4.7)b-1,4�Glucosidase(nmol h�1 g�1) 322.2 (62.8)b-1,4-N-Acetylglucosaminidase (nmol h�1 g�1) 156.7 (50.9)

of the PLFA biomass was classified as “general” and is associatedwith both bacteria and fungi (Table 2).

3.3. Molecular analysis of archaeal soil communities

Using HaeIII and the reverse labeled primer, we detected a totalof 18 archaeal TRFs in our samples. The NMS ordination produceda 2-dimensional solution with a final stress of 9.94% and a cumu-lative coefficient of determination of 0.910. We did not find cleardifferences in the archaeal communities among our samples(Fig. 1). However, archaeal TRFs appeared significantly negativelycorrelated with NAG activity (r ¼ �0.509), BG activity (r ¼ �0.435),fungal PLFA biomarkers (18:1u9c) in soil (r ¼ �0.469), and fungalbiomass as measured using ergosterol (r ¼ �0.440). We found nosignificant relationships between Archaea and the AMF PLFAbiomarker (16:1u5c). Archaeal TRFs clusteredwithMOB TRFs in theordination, although some archaeal TRFs did not appear associatedwith either MOB or DNB TRFs.

Out of 75 isolated plasmids, we successfully sequenced 66archaeal clones from our soil samples. Archaeal sequences recov-ered in this study matched sequences previously described fromthe phyla Crenarchaeota and Euryarchaeota (Supplemental Table 1).13 sequences were positively identified as Euryarchaeota (%ID > 90%) and 2 other clones were putatively affiliated with Eur-yarchaeota (%ID > 85%) (Supplemental Table 1). Crenarchaeotadominated our library, and 31 sequences were positively identifiedas Crenarchaeota (%ID > 90%) and 10 other clones were putativelyaffiliated with Crenarchaeota (%ID > 85%). An additional 10sequences were most closely affiliated with the Crenarchaeota buthad low identity (%ID < 85%) (Supplemental Table 1). Most of oursequences could be positively assigned to a known class of archaea,with the Crenarchaeota class Thermoprotei and the Euryarchaeotaclass Thermoplasmata being the only class assignments oursequences could be placed. Below the class level, sequenceassignment to known groups was poor.

3.4. Molecular analysis of DNB and MOB communities

We observed 42 and 19 TRFs of DNB and MOB, respectively,among soil samples using restriction enzymes MboI and HaeIII.Although wewere able to amplify DNA from both groups, we foundevidence for spatial separation between these bacterial groups asonly 27% of samples contained both groups of bacteria. Forty-onepercent of cores contained only MOB while 32% of the cores con-tained only DNB. NMS ordination confirmed this spatial separation(Fig. 1). The analysis revealed clear separation between samplescontaining DNB and MOB although a small number of samples

-1.5 -0.5 0.5 1.5

-1.5

-0.5

0.5

Axis 1 (35.6%)

Ax

is

2 (5

5.4

%)

Fungal Biomass

(F18:1w9c)

NAGase β-Glucosidase

Beech 30-60 cm dbh

Fungal Biomass (Ergosterol)

Allium tricoccum

Fig. 1. Non-metric multidimensional scaling ordination based on the distribution of archaeal, DNB and MOB TRFs (considered OTUs based on proportional peak area). DNB TRFs arerepresented by Xs, crosses represent MOB TRFs, and filled circles represent archaeal TRFs. Soil samples are represented by open triangles and ellipses show clustering of DNB (solidellipse) and MOB (dashed ellipse). Joint plots of significant (r > 0.423) environmental variables are shown. The joint plot vector lengths indicate the strength and direction of thestrongest correlations. The proportion of variance explained by each axis is shown.

D.J. Burke et al. / Soil Biology & Biochemistry 53 (2012) 112e119116

contained both. We found that DNB TRFs and samples containingonly DNB were significantly positively correlated NAG activity(r ¼ �0.509), BG activity (r ¼ �0.435), fungal PLFA biomarkers(18:1u9c) in soil (r ¼ �0.469), and fungal biomass as measuredusing ergosterol (r ¼ �0.440), while MOB were negatively corre-lated with these same soil parameters. We found no significantrelationships between these bacterial functional groups and theAMF PLFA biomarker (16:1u5c) or with soil C, N or bicarbonateavailable P. We saw some suggestion that the distribution ofpatches of Allium tricoccum (wild leek) was positively correlatedwith MOB distribution (r ¼ �0.423).

We successfully sequenced 39 nosZ clones representing the DNBfrom our soil samples out of 48 isolated plasmids. nosZ sequencesrecovered in this study primarily matched sequences of unculturedforest denitrifying bacteria with some sequences matching uncul-tured denitrifying bacteria found in rice paddy soils (SupplementalTable 2). Successfully isolated pmoA clones showed high identity tomethanotrophic bacteria isolated from aquatic and soil environ-ments. Two clones showed high identity to species in the genusMethylocystis (Supplemental Table 3).

4. Discussion

We hypothesized that fungal biomass is an important environ-mental feature that affects the overall distribution of microbialfunctional groups in forest soil and we found evidence to supportthis concept and the idea that fungal biomass may help to structuremicrobial niches in soil and facilitate niche separation of differentgroups. Fungal biomass was negatively correlated with the distri-bution of Archaea and MOB in our forest soil, but positivelycorrelated with the distribution of DNB. This suggests that Archaeaand MOB taxa are less likely to be found in areas with high levels of

fungal biomass, whereas DNB taxa are more likely to be found inareas with high fungal biomass. This could indicate that fungi eitherfacilitate or share similar environmental preferences and mayinteract more with DNB than with either MOB or Archaea in forestsoils.

4.1. Archaea-fungal biomass relationships

We expected that soil fungi might foster conditions favorable tosoil Archaea, and therefore positive correlations might be foundbetween fungal biomass and archaeal distribution. However, fungalbiomass appeared negatively correlated with most archaeal TRFs,supporting our alternative hypothesis and suggesting that mostforest Archaea are found in soil with low levels of fungal biomass.Soil fungi can alter physicochemical conditions in soil, includingsoil oxygen (O2) status through fungal respiration, altering avail-ability of nutrients such as N and P, and altering microsite pH (Reid,1984; Rygiewicz et al., 1984; Linderman,1988; Grayston et al., 1997;Smith and Read, 2008). Fungal biomass might also serve as animportant C source as hyphae senesce and die. We expected thatfungal activity, and potentially greater soil N content in response tofungal enzyme activity, would be favorable to Archaea. However,we found that only the community structure and distribution ofDNB taxa were positively affected by fungal biomass. It is unclearwhether this pattern is driven by niche separation or substratecompetition.

Our study focused only on the distribution of Archaea in the top5-cm of the soil profile, and we found Archaea in every sampleanalyzed and had strong PCR amplification. Archaea are nowcommonly found in acidic forest soils (Pesaro and Widmer, 2002;Bomberg et al., 2010; Bates et al., 2011) with the Crenarcheotaoften dominating clone libraries as was the case in our study. We

D.J. Burke et al. / Soil Biology & Biochemistry 53 (2012) 112e119 117

also found Euryarcheota in our samples, and these clones belongedentirely to the order Thermoplasmatales, which have also beenpreviously detected in forest soils (Pesaro and Widmer, 2002).

The distribution of Crenarchaeota in anaerobic tropical peat-lands appeared correlated with deeper soil layers (>20-cm) withlow levels of enzyme activity whereas bacteria were found in moreshallow layers with higher levels of enzyme activity (Jackson et al.,2009). This is in agreement with our study since we found negativecorrelations between archaeal TRF distribution and soil enzymeactivity. Because enzyme activity is often linked to rates of organicmatter decomposition and can be considered a proxy measure ofnutrient cycling, our results suggest that most Archaea in forestsoils are associated with areas of low organic matter and nutrientcycling. This could mean that Archaea either have little effect onorganic matter turnover and nutrient cycling in forests, or that theyare more tolerant of stressful conditions where resource availabilityis low. Our results are somewhat in contrast to a large study byBates et al. (2011) that examined archaeal distribution across 146sites from North and South America and Antarctica. Only C:N ratiowas consistently correlated with archaeal abundance in soil (Bateset al., 2011). We may not have seen a positive response to C:Nbecause our study was limited to one old growth forest site, and thecombined relative effects of fungal biomass on Archaea may havebeen greater than soil chemistry alone.

Although the exact functional role Archaea may play in forestsoils is uncertain, previous studies have found that Crenarchaeotamay be an important if not the major contributor to nitrification(Wuchter et al., 2006; Bates et al., 2011) and that some possess theamoA gene for nitrification (Treusch et al., 2005). Some Archaea arealso capable of denitrification through the ANAMOX pathway(Dalsgaard et al., 2003), but whether these groups exist in forestsoil will require additional study. Overall, our understanding ofchrenarchaeal function is limited by the fact that none have yetbeen isolated in pure culture (Poplawski et al., 2007).

Euryarchaea are a ubiquitous phylum of the Archaea that areknown to produce and oxidize CH4, fix atmospheric N, reduce NO3

�,and contribute to ANAMOX, but they have not beenwidely detectedin aerobic forest soils (Poplawski et al., 2007). In two separatestudies, Bomberg et al. (2003, 2010) found that the soil aroundplant roots colonized by mycorrhizal fungi contained diversegroups of Archaea, including methanogens within the orderMethanosarcinales (Euryarcheota). Despite our cloning efforts andidentification of Euryarcheota, we did not detect any known groupsof methanogens. This does not mean that methanogens were notpresent, as many are yet undescribed, and our cloning effort wasnot exhaustive and may have missed some taxa. We also examinedsoil samples that included both mycorrhizospshere (i.e. soilimmediately around mycorrhizal roots) and bulk soil. AlthoughBomberg et al. (2003) were able to amplify Archaea from themycorrhizosphere, fungal external mycelium did not containArchaea. This suggests that archaeal distribution is highly micrositespecific, and our sampling method might have hindered our abilityto isolate methanogens that intimately associate with root surfacescolonized by mycorrhizal fungi. Additional work is needed tounderstand how microsite variability affects groups of Archaea inforest soil and the resource requirements of these different groups.

4.2. MOB-fungal biomass relationships

Although many studies have examined the taxonomic diversityand functional activity of MOB in soils including forest soils(Henckel et al., 2000; Horz et al., 2005; Singh and Tate, 2007), fewstudies have attempted to identify environmental features associ-ated with the distribution of MOB. Soil fungi can potentially alterthe environment for bacteria, includingMOB, by changing chemical

conditions including soil pH, N and P availability, and the amountand type of organic carbon found within soil (Reid, 1984; Rygiewiczet al., 1984; Linderman,1988; Grayston et al., 1997; Smith and Read,2008). In this study we attempted to discern the soil conditionsassociated with MOB and we found that MOB were negativelycorrelated with fungal biomass and enzyme activity, suggestingthat MOB are more likely found in areas with low C and nutrientcycling rates. Like Archaea, MOB appear to prefer sites with lowlevels of nutrient and organic matter decomposition and cycling,and may inhabit more mineral areas of the soil environment. Thus,the MOB are found in sites that are preferred by potential CH4producers (i.e. Euryarchaea) suggesting that spatial organizationmay be the result of substrate source. Interestingly, we saw somepositive correlation between the distribution of MOB and % cover ofthe herbaceous plant A. tricoccum (wild leek). Inwetlands, MOB areinfluenced by the presence of plant roots that alter soil O2concentration, pH, and C and N availability (Dunfield et al., 1993;King, 1996; Calhoun and King, 1997; Van der Nat and Middelburg,1998; van Bodegom et al., 2001; Bodelier and Laanbroek, 2004).Although the exact cause of the association between MOB and wildleek is uncertain, plants can have a strong affect on bacteria inmanysoil types and systems (Burke et al., 2002; Zak et al., 2003).

Although it has been thought that MOB use CH4 as their sole Cand energy source, increasing evidence suggests that MOB mayhave greater metabolic flexibility with respect to electron donorsand acceptors (Ward et al., 2004) and that different groups of MOBoccupy different niches in soil that may be governed by CH4, O2 andN concentrations (Shrestha et al., 2008). Our results suggest thatsoil fungal biomass and the activity of fungi could also affect thedistribution of this bacterial functional group in forest soils.

Previous studies have found a strong correlation between MOBand pH in forest and agricultural soil (Knief et al., 2003). However,we did not see any relationships between soil chemistry and MOB.The pH in our forest was generally more acidic, ranging narrowlybetween 3.4 and 5.3, than in the study by Knief et al. (2003) wherepH ranged from 4.3 to as high as 8.0. Effects of pH on MOB in ourstudy may therefore not be as great due to the narrow pH range.

4.3. DNB-fungal biomass relationships

Environmental factors such as pH, temperature, O2 and Cavailability may be the primary control on the distribution of DNBin soils (Wallenstein et al., 2006). Consequently, we expected fungalbiomass in surface soils to have a strong negative effect oncommunities of DNB because of their potential to compete for soil Cand N. Contrary to our expectation, DNB were positively correlatedwith both fungal biomass and C and nutrient cycling as indicated byenzyme activity. DNB were associated with BG and NAG activity,suggesting again that DNB are correlated with sites high in organicmatter and nutrient cycling and turnover.

Interestingly, DNB communities were not correlated with soil Cor N status in our study, suggesting that overall N availability maynot be important for structuring the distribution of DNB commu-nities. This observation is in contrast to other studies that reportedpositive correlations between DNB communities and C:N ratio ora lack of correlations with soil NO3

� concentrations or N supply(Mergel et al., 2001; Rich and Myrold, 2004; Haase et al., 2008).Although NO3

� concentration did not govern DNB distribution,Mergel et al. (2001) did find that DNB distribution was alwayshighest in the top 5-cm of a forest soil profile. Because fungalbiomass is often highest in the most shallow soil layers (Bååth andSöderström,1982), it may be that in terms of CN requirements fungicreate soil conditions more favorable to DNB. It is possible thereforethat organic matter quality, not overall amounts of C and N, areimportant for structuring these communities and that fungi

D.J. Burke et al. / Soil Biology & Biochemistry 53 (2012) 112e119118

positively influence organic matter quality. However, plant rootscan also control DNB distribution and activity through the excretionof substantial amounts of carbon into forest soil (Philippot et al.,2007) and more than 90% of fine root biomass at our study site isfound within the top 5-cm of soil (Burke et al., 2009). Nonetheless,we found no correlation between DNB communities and herba-ceous plant or tree distribution, indicating that fungal biomass maybe more important in structuring the distribution of the DNBcommunities than plants at our study site.

5. Conclusions

We found that soil fungi are correlated with the distribution ofimportant bacterial functional groups in forests, including somegroups that mediate the production and consumption of importantgreenhouse gases. DNB were positively correlated with fungalbiomass and enzyme activity, suggesting that both DNB and fungiare associated with each other and areas with high levels of organicC and nutrient cycling. On the other hand, MOB and Archaea werenegatively correlated with fungal biomass, suggesting that thesegroups are more likely found in areas with low organic C, nutrientavailability and organic matter turnover. Our results indicate thatniche separation may exist between these microbial groups inforest soils, and that soil fungi may be associated with somefunctional groups in forest soil, possibly due to shared preferencesfor sites with elevated levels of C and nutrient cycling.

Acknowledgements

This work was supported by funding from The Holden Arbo-retum Trust and the Corning Institute for Education and Research.

Appendix A. Supplementary material

Supplementary material associated with this article can befound, in the online version, at doi:10.1016/j.soilbio.2012.05.008.

References

Amann, R.I., 1995. Fluorescently labeled, ribosomal-rna-targeted oligonucleotideprobes in the study of microbial ecology. Molecular Ecology 4, 543e553.

Bååth, E., Söderström, B., 1982. Seasonal and spatial variation in fungal biomass ina forest soil. Soil Biology & Biochemistry 14, 353e358.

Bardgett, R.D., Freeman, C., Ostle, N.J., 2008. Microbial contributions to climatechange through carbon cycle feedbacks. ISME Journal 2, 805e814.

Bates, S.T., Berg-Lyons, D., Caporaso, J.G., Walters, W.A., Knight, R., Fierer, N., 2011.Examining the global distribution of dominant archaeal populations in soil.ISME Journal 5, 908e917.

Bodelier, P.L.E., Laanbroek, H.J., 2004. Nitrogen as a regulatory factor of methaneoxidation in soils and sediments. FEMS Microbiology Ecology 47, 265e277.

Bomberg, M., Jurgens, G., Saano, A., Sen, R., Timonen, S., 2003. Nested PCR detectionof Archaea in defined compartments of pine mycorrhizospheres developed inboreal forest humus microcosms. FEMS Microbiology Ecology 43, 163e171.

Bomberg, M., Montonen, L., Timonen, S., 2010. Anaerobic Eury- and Crenarchaeotainhabit ectomycorrhizas of boreal forest Scots pine. European Journal of SoilBiology 46, 356e364.

Brandt, K.K., Vester, F., Jensen, A.N., Ingvorsen, K., 2001. Sulfate reduction dynamicsand enumeration of sulfate-reducing bacteria in hypersaline sediments of theGreat Salt Lake (Utah, USA). Microbial Ecology 41, 1e11.

Burke, D.J., Chan, C.R., 2010. Effects of the invasive plant garlic mustard (Alliariapetiolata) on bacterial communities in a northern hardwood forest soil. Cana-dian Journal of Microbiology 56, 81e86.

Burke, D.J., Dunham, S.M., Kretzer, A.M., 2008. Molecular analysis of bacterialcommunities associated with the roots of Douglas fir (Pseudotsuga menziesii)colonized by different ectomycorrhizal fungi. FEMS Microbiology Ecology 65,299e309.

Burke, D.J., Hamerlynck, E.P., Hahn, D., 2002. Interactions among plant species andmicroorganisms in salt marsh sediments. Applied and Environmental Micro-biology 68, 1157e1164.

Burke, D.J., Kretzer, A.M., Rygiewicz, P.T., Topa, M.A., 2006a. Soil bacterial diversity ina loblolly pine plantation: influence of ectomycorrhizas and fertilization. FEMSMicrobiology Ecology 57, 409e419.

Burke, D.J., Lopez-Gutierrez, J.C., Smemo, K.A., Chan, C.R., 2009. Vegetation and soilenvironment influence the spatial distribution of root-associated fungi ina mature beech-maple forest. Applied and Environmental Microbiology 75,7639e7648.

Burke, D.J., Martin, K.J., Rygiewicz, P.T., Topa, M.A., 2005. Ectomycorrhizal fungiidentification in single and pooled root samples: terminal restriction fragmentlength polymorphism (TRFLP) and morphotyping compared. Soil Biology &Biochemistry 37, 1683e1694.

Burke, D.J., Martin, K.J., Rygiewicz, P.T., Topa, M.A., 2006b. Relative abundance ofectomycorrhizas in a managed loblolly pine (Pinus taeda) genetics plantation asdetermined through terminal restriction fragment length polymorphismprofiles. Canadian Journal of Botany-Revue Canadienne De Botanique 84,924e932.

Calhoun, A., King, G.M., 1997. Regulation of root-associated methanotrophy byoxygen availability in the rhizosphere of two aquatic macrophytes. Applied andEnvironmental Microbiology 63, 3051e3058.

Costello, A.M., Lidstrom, M.E., 1999. Molecular characterization of functional andphylogenetic genes from natural populations of methanotrophs in lake sedi-ments. Applied and Environmental Microbiology 65, 5066e5074.

Dalsgaard, T., Canfield, D.E., Petersen, J., Thamdrup, B., Acuna-Gonzalez, J., 2003. N2production by the anammox reaction in the anoxic water column of GolfoDulce, Costa Rica. Nature 422, 606e608.

DeForest, J.L., Scott, L.G., 2010. Available organic soil phosphorus has an importantinfluence on microbial community composition. Soil Science Society of AmericaJournal 74, 2059e2066.

DeForest, J.L., Zak, D.R., Pregitzer, K.S., Burton, A.J., 2004. Atmospheric nitratedeposition, microbial community composition, and enzyme activity in northernhardwood forests. Soil Science Society of America Journal 68, 132e138.

Dunbar, J., Ticknor, L.O., Kuske, C.R., 2001. Phylogenetic specificity and reproduc-ibility and new method for analysis of terminal restriction fragment profiles of16S rRNA genes from bacterial communities. Applied and EnvironmentalMicrobiology 67, 190e197.

Dunfield, P., Knowles, R., Dumont, R., Moore, T.R., 1993. Methane production andconsumption in temperate and sub-arctic peat soils e response to temperatureand pH. Soil Biology & Biochemistry 25, 321e326.

EPA, 1971. Methods of Chemical Analysis of Water and Wastes. EPA, Cincinnati, OH.Feinstein, L.M., Sul, W.J., Blackwood, C.B., 2009. Assessment of bias Associated with

incomplete extraction of microbial DNA from soil. Applied and EnvironmentalMicrobiology 75, 5428e5433.

Forster, P., Artaxo, V.R.P., Berntsen, T., Betts, R., Fahey, D.W., Haywood, J., Lean, J.,Lowe, D.C., Myhre, G., Nganga, J., Prinn, R., Raga, G., Schulz, M., Van Dorland, R.,2007. Changes in atmospheric constituents and in radiative forcing. In:Solomon, D.Q., Manning, S.M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M.,Miller, H.L. (Eds.), Climate Change 2007: The Physical Science Basis. Contribu-tion of Working Group I to the Fourth Assessment Report of the Intergovern-mental Panel on Climate Change. Cambridge University Press, Cambridge,United Kingdom and New York, NY, USA.

Gong, P., Guan, X., Witter, E., 2001. A rapid method to extract ergosterol from soil byphysical disruption. Applied Soil Ecology 17, 285e289.

Grayston, S.J., Vaughan, D., Jones, D., 1997. Rhizosphere carbon flow in trees, incomparison with annual plants: the importance of root exudation and itsimpact on microbial activity and nutrient availability. Applied Soil Ecology 5,29e56.

Green, J.L., Holmes, A.J., Westoby, M., Oliver, I., Briscoe, D., Dangerfield, M.,Gillings, M., Beattie, A.J., 2004. Spatial scaling of microbial eukaryote diversity.Nature 432, 747e750.

Haase, S., Philippot, L., Neumann, G., Marhan, S., Kandeler, E., 2008. Local responseof bacterial densities and enzyme activities to elevated atmospheric CO2 anddifferent N supply in the rhizosphere of Phaseolus vulgaris L. Soil Biology &Biochemistry 40, 1225e1234.

Henckel, T., Jackel, U., Schnell, S., Conrad, R., 2000. Molecular analyses of novelmethanotrophic communities in forest soil that oxidize atmospheric methane.Applied and Environmental Microbiology 66, 1801e1808.

Horner-Devine, M.C., Lage, M., Hughes, J.B., Bohannan, B.J.M., 2004. A taxa-arearelationship for bacteria. Nature 432, 750e753.

Horz, H.P., Rich, V., Avrahami, S., Bohannan, B.J., 2005. Methane-oxidizing bacteriain a California upland grassland soil: diversity and response to simulated globalchange. Applied and Environmental Microbiology 71, 2642e2652.

Jackson, C.R., Liew, K.C., Yule, C.M., 2009. Structural and functional changes withdepth in microbial communities in a tropical Malaysian Peat Swamp forest.Microbial Ecology 57, 402e412.

King, G.M., 1996. In situ analyses of methane oxidation associated with the rootsand rhizomes of a bur reed, Sparganium eurycarpum, in a Maine wetland.Applied and Environmental Microbiology 62, 4548e4555.

Knief, C., Lipski, A., Dunfield, P.F., 2003. Diversity and activity of methanotrophicbacteria in different upland soils. Applied and Environmental Microbiology 69,6703e6714.

Kuo, S., 1996. Phosphorus. In: Sparks, D.L. (Ed.), Methods of Soil Analysis, Part 3,Chemical Methods. SSSA and ASA, Madisoni, WI, pp. 869e919.

Leake, J.R., Donnelly, D.P., Boddy, L., 2002. Interactions between ecto-mycorrhizaland saprotrophic fungi. In: Heijden, M.G.A., Sanders, I.R. (Eds.), MycorrhizalEcology. Springer-Verlag, Berlin, pp. 345e371.

Leininger, S., Urich, T., Schloter, M., Schwark, L., Qi, J., Nicol, G.W., Prosser, J.I.,Schuster, S.C., Schleper, C., 2006. Archaea predominate among ammonia-oxidizing prokaryotes in soils. Nature 442, 806e809.

D.J. Burke et al. / Soil Biology & Biochemistry 53 (2012) 112e119 119

Linderman, R.G., 1988. Mycorrhizal interactions with the rhizosphere microflora e

the mycorrhizosphere effect. Phytopathology 78, 366e371.Lynch, J.M., 1988. The terrestrial environment. In: Lynch, J.M., Hobbie, J.E. (Eds.),

Micro-organisms in Action: Concepts and Applications in Microbial Ecology.Blackwell Scientific Publications, Inc., Palo Alto, California, USA, pp. 103e131.

Mergel, A., Schmitz, O., Mallmann, T., Bothe, H., 2001. Relative abundance of deni-trifying and dinitrogen-fixing bacteria in layers of a forest soil. FEMS Microbi-ology Ecology 36, 33e42.

Montgomery, H.J., Monreal, C.M., Young, J.C., Seifert, K.A., 2000. Determination ofsoil fungal biomass from soil ergosterol analyses. Soil Biology & Biochemistry32, 1207e1217.

Olsen, S.R., Cole, C.V., Watanabe, F.S., Dean, L.A., 1954. Estimation of AvailablePhosphorus in Soils by Extraction with Sodium Bicarbonate. U.S. GovernmentPrint Office, Washington D.C.

Olsson, P.A., Wilhelmsson, P., 2000. The growth of external AM fungal mycelium insand dunes and in experimental systems. Plant and Soil 226, 161e169.

Parniske, M., 2008. Arbuscular mycorrhiza: the mother of plant root endosymbi-oses. Nature Reviews Microbiology 6, 763e775.

Pastor, J., Aber, J.D., McClaugherty, C.A., Melillo, J.M., 1984. Above-ground produc-tion and N and P cycling along a nitrogen mineralization gradient on BlackhawkIsland, Wisconsin. Ecology 65, 256e268.

Pesaro, M., Widmer, F., 2002. Identification of novel Crenarchaeota and Eur-yarchaeota clusters associated with different depth layers of a forest soil. FEMSMicrobiology Ecology 42, 89e98.

Pett-Ridge, J., Firestone,M.K., 2005. Redox fluctuation structuresmicrobial communitiesin a wet tropical soil. Applied and Environmental Microbiology 71, 6998e7007.

Philippot, L., Hallin, S., Schloter, M., 2007. Ecology of denitrifying prokaryotes inagricultural soil. Advances in Agronomy 96, 249e305.

Poly, F., Ranjard, L., Nazaret, S., Gourbiere, F., Monrozier, L.J., 2001. Comparison ofnifH gene pools in soils and soil microenvironments with contrasting proper-ties. Applied and Environmental Microbiology 67, 2255e2262.

Poplawski, A.B., Martensson, L., Wartiainen, I., Rasmussen, U., 2007. Archaeal diversityand community structure in a Swedish barley field: specificity of the EK510R/(EURY498) 16S rDNA primer. Journal of Microbiological Methods 69, 161e173.

Prosser, J.I., 2002. Molecular and functional diversity in soil micro-organisms. Plantand Soil 244, 9e17.

Rayner, A.D.M., Boddy, L., 1988. Fungal Decomposition of Wood, its Biology andEcology. John Wiley & Sons Inc., Chichester, UK.

Reid, C.P.P., 1984. Mycorrhizae: a rootesoil interface in plant nutrition. In: Todd, R.L.,Giddens, J.E. (Eds.), ASA (American Society of Agronomy) Special Publication,No. 47. MicrobialePlant Interactions; Proceedings of a Symposium, Fort Collins,Colo., USA, Aug. 5e10, 1979. Soil Science Society of America, American Society ofAgronomy, Crop Science Society of America, Madison, Wis., USA, pp. 29e50.

Rich, J.J., Myrold, D.D., 2004. Community composition and activities of denitrifyingbacteria from adjacent agricultural soil, riparian soil, and creek sediment inOregon, USA. Soil Biology & Biochemistry 36, 1431e1441.

Robertson, G.P., Paul, E.A., Harwood, R.R., 2000. Greenhouse gases in intensiveagriculture: contributions of individual gases to the radiative forcing of theatmosphere. Science 289, 1922e1925.

Rösch, C., Bothe, H., 2005. Improved assessment of denitrifying, N-2-fixing, andtotal-community bacteria by terminal restriction fragment length poly-morphism analysis using multiple restriction enzymes. Applied and Environ-mental Microbiology 71, 2026e2035.

Rösch, C., Mergel, A., Bothe, H., 2002. Biodiversity of denitrifying and dinitrogen-fixing bacteria in an acid forest soil. Applied and Environmental Microbiology68, 3818e3829.

Rousk, J., Baath, E., Brookes, P.C., Lauber, C.L., Lozupone, C., Caporaso, J.G., Knight, R.,Fierer, N., 2010. Soil bacterial and fungal communities across a pH gradient inan arable soil. ISME Journal 4, 1340e1351.

Rygiewicz, P.T., Bledsoe, C.S., Zasoski, R.J., 1984. Effects of ectomycorrhizae andsolution ph on N-15 nitrate uptake by coniferous seedlings. Canadian Journal ofForest Research-Revue Canadienne De Recherche Forestiere 14, 893e899.

Saiya-Cork, K.R., Sinsabaugh, R.L., Zak, D.R., 2002. The effects of long term nitrogendeposition on extracellular enzyme activity in an Acer saccharum forest soil.Soil Biology & Biochemistry 34, 1309e1315.

Shrestha, M., Abraham, W.R., Shrestha, P.M., Noll, M., Conrad, R., 2008. Activity andcomposition of methanotrophic bacterial communities in planted rice soilstudied by flux measurements, analyses of pmoA gene and stable isotopeprobing of phospholipid fatty acids. Environmental Microbiology 10, 400e412.

Singh, B.K., Bardgett, R.D., Smith, P., Reay, D.S., 2010. Microorganisms and climatechange: terrestrial feedbacks and mitigation options. Nature Reviews Micro-biology 8, 779e790.

Singh, B.K., Tate, K., 2007. Biochemical and molecular characterization of meth-anotrophs in soil from a pristine New Zealand beech forest. FEMS MicrobiologyLetters 275, 89e97.

Smith, S.E., Read, D.J., 2008. Mycorrhizal Symbiosis. Academic Press Inc., London,UK.

Treusch, A.H., Leininger, S., Kletzin, A., Schuster, S.C., Klenk, H.P., Schleper, C., 2005.Novel genes for nitrite reductase and Amo-related proteins indicate a role ofuncultivated mesophilic crenarchaeota in nitrogen cycling. EnvironmentalMicrobiology 7, 1985e1995.

Tunlid, A., Ringelberg, D., Phelps, T.J., Low, C., White, D.C., 1989. Measurement ofphospholipid fatty-acids at picomolar concentrations in biofilms and deepsubsurface sediments using gas-chromatography and chemical ionizationmass-spectrometry. Journal of Microbiological Methods 10, 139e153.

van Bodegom, P., Stams, F., Mollema, L., Boeke, S., Leffelaar, P., 2001. Methaneoxidation and the competition for oxygen in the rice rhizosphere. Applied andEnvironmental Microbiology 67, 3586e3597.

Van der Nat, F., Middelburg, J.J., 1998. Effects of two common macrophytes onmethane dynamics in freshwater sediments. Biogeochemistry 43, 79e104.

Vestal, J.R., White, D.C., 1989. Lipid analysis in microbial ecology e quantitativeapproaches to the study of microbial communities. Bioscience 39, 535e541.

Wallenstein, M.D., Myrold, D.D., Firestone, M., Voytek, M., 2006. Environmentalcontrols on denitrifying communities and denitrification rates: insights frommolecular methods. Ecological Applications 16, 2143e2152.

Wang, Q., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naive Bayesian classifier forrapid assignment of rRNA sequences into the new bacterial taxonomy. Appliedand Environmental Microbiology 73, 5261e5267.

Ward, N., Larsen, O., Sakwa, J., Bruseth, L., Khouri, H., Durkin, A.S., Dimitrov, G.,Jiang, L.X., Scanlan, D., Kang, K.H., Lewis, M., Nelson, K.E., Methe, B., Wu, M.,Heidelberg, J.F., Paulsen, I.T., Fouts, D., Ravel, J., Tettelin, H., Ren, Q.H., Read, T.,DeBoy, R.T., Seshadri, R., Salzberg, S.L., Jensen, H.B., Birkeland, N.K., Nelson, W.C.,Dodson, R.J., Grindhaug, S.H., Holt, I., Eidhammer, I., Jonasen, I., Vanaken, S.,Utterback, T., Feldblyum, T.V., Fraser, C.M., Lillehaug, J.R., Eisen, J.A., 2004.Genomic insights into methanotrophy: the complete genome sequence ofMethylococcus capsulatus (Bath). PLOS Biology 2, 1616e1628.

Wuchter, C., Abbas, B., Coolen, M.J., Herfort, L., van Bleijswijk, J., Timmers, P.,Strous, M., Teira, E., Herndl, G.J., Middelburg, J.J., Schouten, S., SinningheDamste, J.S., 2006. Archaeal nitrification in the ocean. Proceedings of theNational Academy of Sciences of the United States of America 103,12317e12322.

Zak, D.R., Holmes, W.E., White, D.C., Peacock, A.D., Tilman, D., 2003. Plant diversity,soil microbial communities, and ecosystem function: are there any links?Ecology 84, 2042e2050.

Zar, J.H., 1998. Biostatistical Analysis. Prentice Hall, Upper Saddle River, NJ, 929 pp.Zelles, L., 1999. Identification of single cultured micro-organisms based on their

whole-community fatty acid profiles, using an extended extraction procedure.Chemosphere 39, 665e682.