The ratio of methanogens to methanotrophs and water-level ... · Tamarack zone, close to saturation, and the lowest values in the restored zone. While the CH4 ﬂuxes and pore-water

Biogeosciences 16 3207ndash3231 2019httpsdoiorg105194bg-16-3207-2019copy Author(s) 2019 This work is distributed underthe Creative Commons Attribution 40 License

The ratio of methanogens to methanotrophs and water-leveldynamics drive methane transfer velocity in a temperatekettle-hole peat bogCamilo Rey-Sanchez1a Gil Bohrer1 Julie Slater2 Yueh-Fen Li3 Roger Grau-Andreacutes2 Yushan Hao2Virginia I Rich3 and G Matt Davies2

1Department of Civil Environmental and Geodetic EngineeringThe Ohio State University Columbus Ohio 43210 USA2School of Environment and Natural Resources The Ohio State University Columbus Ohio 43210 USA3Department of Microbiology The Ohio State University Columbus Ohio 43210 USAacurrent address Department of Environmental Science Policy and ManagementUniversity of California Berkeley California 94720 USA

Correspondence Camilo Rey-Sanchez (rey1berkeleyedu)

Received 28 March 2019 ndash Discussion started 23 April 2019Revised 20 July 2019 ndash Accepted 31 July 2019 ndash Published 29 August 2019

Abstract Peatlands are a large source of methane (CH4)to the atmosphere yet the uncertainty around the estimatesof CH4 flux from peatlands is large To better understandthe spatial heterogeneity in temperate peatland CH4 emis-sions and their response to physical and biological driverswe studied CH4 dynamics throughout the growing seasonsof 2017 and 2018 in Flatiron Lake Bog a kettle-hole peatbog in Ohio The site is composed of six different hydro-biological zones an open water zone four concentric veg-etation zones surrounding the open water and a restoredzone connected to the main bog by a narrow channel Ateach of these locations we monitored water level (WL) CH4pore-water concentration at different peat depths CH4 fluxesfrom the ground and from representative plant species us-ing chambers and microbial community composition with afocus here on known methanogens and methanotrophs In-tegrated CH4 emissions for the growing season were esti-mated as 3154plusmn 166 mgCH4 mminus2 dminus1 in 2017 and 3623plusmn687 mgCH4 mminus2 dminus1 in 2018 Median CH4 emission washighest in the open water then it decreased and became morevariable through the concentric vegetation zones as the WLdropped with extreme emission hotspots observed in thetamarack mixed woodlands (Tamarack) and low emissionsin the restored zone (188ndash303 mgCH4 mminus2 dminus1) GenerallyCH4 flux from above-ground vegetation was negligible com-pared to ground flux (lt 04 ) although blueberry plants

were a small CH4 sink Pore-water CH4 concentrations var-ied significantly among zones with the highest values in theTamarack zone close to saturation and the lowest valuesin the restored zone While the CH4 fluxes and pore-waterconcentrations were not correlated with methanogen relativeabundance the ratio of methanogens to methanotrophs in theupper portion of the peat was significantly correlated to CH4transfer velocity (the CH4 flux divided by the difference inCH4 pore-water concentration between the top of the peatprofile and the concentration in equilibrium with the atmo-sphere) Since ebullition and plant-mediated transport werenot important sources of CH4 and the peat structure andporosity were similar across the different zones in the bogwe conclude that the differences in CH4 transfer velocitiesand thus the flux are driven by the ratio of methanogen tomethanotroph relative abundance close to the surface Thisstudy illustrates the importance of the interactions betweenwater-level and microbial composition to better understandCH4 fluxes from bogs and wetlands in general

Published by Copernicus Publications on behalf of the European Geosciences Union

3208 C Rey-Sanchez et al Ratio of methanogens to methanotrophs drive methane transfer velocity

1 Introduction

Methane (CH4) fluxes from natural and anthropogenicsources play a significant role in determining atmosphericclimate forcing (Ciais et al 2013) Changes to CH4 fluxesfrom natural systems are of significant concern due to theirpotential to drive positive feedback cycles in the global cli-mate system (Bridgham et al 2013 Dean et al 2018) Nat-ural wetlands emit approximately 30 of all the methane(CH4) released into the atmosphere (Kirschke et al 2013)yet the uncertainty around wetland CH4 flux is the highestof all the components of the global CH4 budget (Kirschke etal 2013) This uncertainty partly arises from the complex-ity of physical and biological interactions that result in theproduction and oxidation of CH4 and its eventual release tothe atmosphere (Lai 2009) Generally water level (WL) isthe most important driver of CH4 emissions from wetlandsand especially peatlands as its position in the soil or peatprofile defines the boundary between anaerobic CH4 produc-tion (methanogenesis) in the catotelm (ie the lower anoxicportion of the peat) and aerobic CH4 oxidation (methanotro-phy) in the acrotelm (the upper oxic peat Kettunen 2003White et al 2008) However a plethora of environmentalvariables can also influence CH4 fluxes in peatlands includ-ing temperature (Bohn et al 2007 Kim et al 1999 Segers1998) peat origin (eg Sphagnum woody peat and fen andreed peat Bridgham and Richardson 1992) degree of humi-fication (Glatzel et al 2004) availability of labile carbon inthe peat (Updegraff et al 1995) concentrations of ligninlong-chain fatty acids and polysaccharides along the peatprofile (Hoyos-Santillan et al 2016) phosphorous contentwhich regulates anaerobic decomposition of organic matter(Basiliko et al 2007) the abundance of other electron ac-ceptors especially Fe (Chamberlain et al 2018) and pHas methanogens occur at greater abundances in neutral toslightly alkaline conditions (Wang et al 1993) It is also im-portant to be cognisant of reports of CH4 production in aer-obic soil (Angle et al 2017) and an increased awareness ofthe importance of anaerobic oxidation of CH4 (Smemo andYavitt 2011)

The microbiota of a site can have complex interactionswith WL and other physical conditions which result in vari-able CH4 fluxes Despite the increasingly complex pictureemerging of peatland CH4 cycling it has been estimatedthat methanotrophy can oxidize 60 ndash90 of the CH4 pro-duced in wetlands before it can escape to the atmosphere (LeMer and Roger 2001) Research has also shown that wa-ter table drawdowns reduce the abundance of methanogens(Kim et al 2008) and that changes in ecosystem vegetationand structure can affect microbial community compositionand in turn the CH4 biochemistry of wetlands (McCalley etal 2014) Generally peat bogs are nutrient-poor sites domi-nated by hydrogenotrophic methanogenesis but when distur-bance occurs a change from hydrogenotrophic to acetoclas-tic methanogenesis can occur due to an increase in pH and

nutrients (Kelly et al 1992 Kim et al 2008 Kotsyurbenkoet al 2004)

Kettle-hole peat bogs are peatlands created by the accu-mulation of peat in areas previously occupied by kettle lakesKettle-hole peat bogs which are frequently found in east-ern North America (Cai and Yu 2011 Moore 2002) oftenconsist of water bodies surrounded by different vegetationzones Closest to the open water there is often a mat of float-ing vegetation followed by concentrically organized vege-tation zones that ultimately support shrubs and trees (Vittand Slack 1975) This vegetation heterogeneity can be animportant driver of CH4 fluxes (Lai et al 2014) particu-larly in ombrotrophic peat bogs where vegetation commu-nities and water levels are strongly associated (Malhotra etal 2016) Measurements of CH4 flux in different vegeta-tion zones are important in understanding site-level flux esti-mates at the bog scale that are affected by the relative coverand arrangement of different vegetation zones (Nadeau et al2013) Most importantly a better understanding of the bio-logical chemical and physical processes controlling fluxesat these low resolutions is necessary to scale up CH4 fluxesat the ecosystem level (Bridgham et al 2013) The objec-tives of this study were to (1) calculate the growing-seasonCH4 budget of a kettle-hole peat bog in Ohio by upscalingflux measurements from different vegetation zones (2) quan-tify the effects of biotic and abiotic controls on below-groundvertical profiles of CH4 pore-water concentration and relatedfluxes and (3) determine the links between microbial com-munity structure and associated CH4 dynamics Brief com-parisons of CH4 dynamics between restored and undisturbedsection are discussed but not in detail as the evaluation ofthe effect of restoration on CH4 fluxes is not the objective ofthis paper

2 Methods

21 Study site

We studied Flatiron Lake Bog a ca 144 ha kettle-holepeat bog located in northeastern Ohio (4102prime4067primeprime N8121prime5981primeprimeW Fig 1) The site is a state nature pre-serve and has been owned by The Nature Conservancy(TNC) since 1984 The greater part of the site typifies thecharacteristic abiotic and biotic zonation found in simi-lar sites throughout eastern North America A small area(ca 1120 m2) of open water (Water) is located at the cen-ter of the site and is surrounded by a series of concentri-cally organized vegetation zones The vegetation commu-nity of the site including the bog vegetation and uplandzones was described in detail by Colwell (2009) The clos-est zone to the open water hereafter called the Sphagnum-leatherleaf mat (Mat) consists of a floating mat of Sphag-num fallax (H Klinggr) with abundant cover of swamploosestrife (Decodon verticillatus (L) Elliot) and leather-

Biogeosciences 16 3207ndash3231 2019 wwwbiogeosciencesnet1632072019

C Rey-Sanchez et al Ratio of methanogens to methanotrophs drive methane transfer velocity 3209

Figure 1 Map of the study site showing the different hydro-biological zones and the sampling locations The map was cre-ated with QGIS and the image was downloaded from the OhioGeographically Referenced Information Program (OGRIP) (httpgis5oitohiogovgeodatadownload last access 2 February 2018image reference number N2280505 and N2280500)

leaf (Chamaedaphne calyculata (L) Moench) Further awayfrom the open water and surrounding the Mat is a narrowband of tamarack mixed woodland (Tamarack) The Tama-rack zone is characterized by tamarack (Larix laricina (DuRoi) K Koch) and yellow birch (Betula alleghaniensis Brit-ton) with a ground layer dominated by S fallax Further to-wards the bogrsquos periphery one can find a large area of mixedericaceous shrubs (Shrubs) dominated by highbush blueberry(Vaccinium corymbosum L) and huckleberry (Gaylussaciabaccata (Wangenh) K Koch) with a ground layer of Sphag-num and scattered sedges ferns and forbs The Shrubs zonealso includes occasional patches dominated by winterberry(Ilex glabra (L) A Gray) or mature hardwoods such as redmaple (Acer rubrum L) and yellow birch Finally the outer-most area consists of a lagg or moat hereafter called the win-terberry lagg (Lagg) The Lagg is typically inundated duringthe first half of the growing season but dry during extendedperiods of the year The dominant vegetation on the Lagg in-cludes winterberry (I glabra) and buttonbush (Cephalanthusoccidentalis L) The Water Mat and Tamarack zones gener-ally present water levels that are always at (Water and Mat)or near (Tamarack) the surface and together they are here-after referred to as the permanently wetted area In contrastthe Shrubs and Lagg zones have deeper water tables withmore pronounced fluctuations in water level and are here-after referred to as the intermittently wetted area Peat coringand manual depth probing revealed a gradient in peat depthsfrom the margin of the site to the interior Measured peat

depths varied from gt 03 m in the Lagg areas to gt 10 m closethe center of the site The immediate upland area surround-ing the bog is mostly forested with dominant tree speciesincluding the American beech (Fagus grandifolia L) blackoak (Quercus velutina Lam) and red maple (Acer rubrumL) The width of this forested buffer varies and some partsof the site are in proximity to areas under arable productionroads or buildings (Fig 1)

In addition to this relatively unaltered core area of thesite there is a restored section (Res) in the southern part ofthe bog which is connected to the main area by a narrowchannel (Fig 1) and comprises 19 of the total peatland(ca 23 430 m2) During the 1950s this area was disturbedand drained to provide water for gravel- and sand-mining ac-tivities in adjacent areas Peat coring in this area has revealedevidence of fire disturbance with significant deposits of char-coal and char layers Between 2001 and 2003 TNC imple-mented a few restoration interventions in this area This in-cluded opening of the channel to reconnect the two sectionsof the bog and the installation of a water-control structureto raise the water table at the restored section Elevated wa-ter tables suppressed red maple trees that had colonized thesite since the disturbance and enabled the establishment ofbog vegetation The latter process was aided by the transferof Sphagnum diaspores and the planting of Vaccinium sppThe current vegetation community for the restored section isdominated by winterberry (I glabra) buttonbush (C occi-dentalis) invasive glossy buckthorn (Frangula alnus Mill)and a remnant population of red maple trees Thin discon-tinuous mats of Sphagnum spp and Carex spp dominatedthe ground layer Due to its limited connection to the coreof the site and its history of modification degradation andrestoration we consider the Res zone to be a distinct hydro-biological zone and due to its large variation in water levelwe consider this zone to be part of the intermittently wettedarea as well

22 Experimental design

Across the site we established multiple sampling locationsto assess ecosystem carbon fluxes CH4 pore-water concen-trations peat properties water table dynamics and micro-bial community composition Monitoring included locationswithin both the undisturbed and restored sections of the bogIn the permanently wetted area we initiated two transectswith their start points located to the north and south of theopen water in the center of the bog (Fig 1) Each transectincluded three sampling locations each associated with avegetation zone Water Mat and Tamarack In the intermit-tently wetted area sampling locations for Shrubs and Laggwere selected as shown in Fig 1 Most locations were es-tablished in summer 2017 but the Tamarack location on thenorth transect and the Lagg location were added in the springof 2018 For the restored section two randomly selected loca-tions were sampled a northern location towards the center of

wwwbiogeosciencesnet1632072019 Biogeosciences 16 3207ndash3231 2019

the restored section (Res-N) and a southern location near theedge (Res-S) Fewer sampling locations in the restored sec-tion were justified by the more homogenous vegetation com-position at the section scale and the sectionrsquos smaller area

23 Surface CH4 flux chamber measurements

In 2017 CH4 gas transfer at the peat surface was measuredmonthly between June and October using non-steady-statechambers We sampled two to four chambers monthly in eachsampling location at each zone Chambers were deployed ontop of semi-permanent collars that were installed 3 monthsprior to the first round of sampling The collars in the Wa-ter Tamarack Shrubs and Res zones were made of rect-angular high-density polyethylene (HDPE) boxes with di-mensions of 38cmtimes 56cm and a height of 26 cm Duringsampling the collars and the chambers had a foam seal andwere held together with clamps For the open-water cham-bers closed-cell polyethylene pipe insulation (13 cm inter-nal diameter) was attached to the bottom edge of the chamberto facilitate flotation and create a seal with the water surface(Rey-Sanchez et al 2018) For the Mat zone we used tallchambers with a volume of 121 L (height 82 cm and radius28 cm) with circular collars with a 28 cm radius and a heightof 59 cm that were inserted ca 30 cm into the mat for a to-tal chamber height of ca 121 cm The height of the cham-bers was necessary to fit the tall and abundant loosestrife andleatherleaf plants Due to their larger volume these chambersincluded fans at 30 and 85 cm above the surface to improveair mixing within the chamber during sampling The volumeof the plants within the chamber was considered negligible

All chambers included a thermometer to measure air tem-perature a 3 m long Tygon tube (16 mm internal diameter)used as a vent for stabilizing pressure and a 20 mm graybutyl stopper that served as a sampling port In 2017 gassamples were extracted from the chambers using a syringe(30 mL) Here 20 mL of the gas sample was introduced intoevacuated 10 mL vials to keep it over-pressurized We useda closure time of 30 min for each chamber and extracted asample every 5 min for a total of seven samples per cham-ber The gas extracted from the chamber was transported tothe laboratory to be analyzed on a gas chromatograph (Shi-madzu GC-2014 Shimadzu Scientific Instruments KyotoJapan) Fluxes were calculated from the slope of the lin-ear regression of the molar density of the greenhouse gasvs time We incorporated selection criteria for rejecting out-liers from individual chamber measurements as described inMorin et al (2017) Specifically if the r2 value of the lin-ear regression of molar density vs time was not sufficientlyhigh (r2

ge 085) and the p value was higher than 005 weremoved one outlier point (identified as the point with thehighest residual value) from the regression This was doneup to twice per chamber and if the accumulation rate regres-sion still did not meet the selection requirements the entirechamber observation was rejected This approach leads to the

exclusion of cases where ebullition events occur during thesampling creating a non-linear change in concentration Theprocedure for calibration of the gas chromatograph is basedon previous studies at the same facility (Nahlik and Mitsch2010 Sha et al 2011) and was fully described in Morin etal (2017)

In 2018 surface fluxes were measured monthly and atthe same locations as in 2017 and the additional Lagg andTamarack locations We used a portable infrared gas ana-lyzer (Picarro GasScouter G4301 Picarro Inc Santa ClaraCA) adapted to sample the same chambers as used in 2017Given the higher sampling rate of the Picarro (one point persecond) the fluxes were calculated based on a linear regres-sion of the molar density of CH4 over 2ndash4 min depending onthe volume of the chamber and the strength of the responseof gas concentration vs time Due to the higher number ofpoints (146ndash293 per regression) a stricter p value was im-plemented (p lt 0001) to determine the significance of theregression A lack of a significant correlation within a cham-ber measurement set was assumed to equal a zero flux

Diurnal patterns of CH4 emissions for the four main zonesin the bog (Open Mat Tamarack and Shrubs) were mea-sured in September in O-S Mat-S Tamarack-S and Shrubslocations (Fig 1) Four individual chamber measurementsper location were completed throughout a full 24 h cycle witha frequency of approximately 3 h Chamber measurementswere accompanied by measurements of surface or water tem-perature when appropriate

24 CH4 flux from plants

To estimate potential emission of CH4 through the plant tis-sues of larger sub-canopy and canopy trees and shrubs whichwould be missed by chambers we measured plant fluxes indominant vascular species near the location of the surfacemeasurements Fluxes from plants were sampled monthly inJune July and September 2018 using the Picarro gas scouterwith chambers adapted to fit individual leaves or branch sec-tions Measurements were taken at multiple times during theday in June July and September while a full diurnal patternwas performed in September

To measure fluxes coming directly through the plant tis-sue in the Mat zone we used small chambers on loosestrifestems the most abundant plant species in this zone Thesechambers had a small opening in the corner of one of thesections to allow the stem to sit uncompressed The spacesaround the stem hole were sealed with putty This loosestrife-stem chamber enclosure had dimensions of 34cmtimes 21cmtimes124cm and a volume of 114 L

We used fully mature and healthy-looking loosestrifestems with more than 200 cm2 of area for plant-flux calcula-tions Stems were measured five times throughout the day inJune and twice in July and September adding up to nine ob-servations throughout the season After 2ndash3 min of measure-ments the stem was cut wrapped in a moist paper towel and

put in a cooler for calculation of leaf area The leaves weredetached from the stem and petioles arranged on a sheet ofpaper and put on a scanner with a reference scale The im-ages were analyzed with the software ImageJ (Schneider etal 2012) for calculation of total leaf area

Plant-flux measurements at the Tamarack zone were con-ducted on stems and trunk sections of Tamarack while fluxesat the Shrubs were measured from blueberry stems To mea-sure fluxes coming from trunk sections we used an adaptationof the chambers used by Pangala et al (2013) for tropicalwetlands These chambers had two sections that were sealedwith insulation foam that closed around the trunk and thatwere held together tightly with clips When holes around thetrunk were present additional layers of insulation foam wereadded to guarantee a good seal The volume of the trunk in-side the chamber was measured to subtract from the total vol-ume of the chamber which was 106 L The dimensions of allthe enclosures were 76cmtimes112cmtimes52cm The understoryfluxes from the low stems of the Tamarack as well as blue-berry the most abundant plant in the understory in the Tama-rack and Shrubs zones were measured using stem chambersTrunk fluxes were measured six times in the months of Mayand July For stem flux calculation we used fully mature andhealthy tamarack stems growing at a reachable height Stemswere measured twice in May seven times in June five timesin July and twice in September Blueberry twigs were sam-pled at multiple locations within the Shrubs zones four timesin June four times in July and twice in September

25 Upscaling of CH4 fluxes

To scale up the fluxes from each of the zones we extrap-olated monthly mean chamber measurements to the entirearea of each zone We then integrated the monthly observedflux to calculate the total seasonal CH4 budget for eachzone and added the contribution of all the zones for the to-tal seasonal site total When fluxes from plants were sig-nificant we calculated the total contributions by first mul-tiplying the per-leaf-area rate observed by the plant cham-ber measurement by the leaf-area index then multiplyingby the area of the zone and finally integrating in time forthe whole season The leaf-area index (LAI) was calcu-lated based on the MODIS LAI product (image collectionID MODIS006MCD15A3H available through the GoogleEarth Engine) for the period of study Due to the low resolu-tion of the imagery with respect to the site (500 m) we cal-culated the average LAI of the two images intersecting thesite which comprised similar areas

Due to the lack of strength in the signal of the diurnal pat-tern we did not correct the monthly measurements by timeof day The measurements in 2017 encompassed a total of122 d for which the integration of fluxes was performed Thelength of this period was higher in 2018 and was equal to149 d

26 Vertical profiles of CH4 pore-water concentrationand methane transfer velocity

We used in situ dialysis pore-water samplers (ldquopeepersrdquoAngle et al 2017 MacDonald et al 2013) to measurevertical pore-water concentration profiles of dissolved CH4In total seven peepers were installed throughout the sitefive in the undisturbed section and two in the restored sec-tion Peepers were placed adjacent to the gas flux chambersEach peeper had 10 sampling windows located at depthsfrom 14 to 518 cm and spaced every 56 cm Each window(889 cmtimes228 cm area and 302 cm depth) which was filledwith deionized water that equilibrates with the surroundingpore water through a semi-permeable membrane (pore size02 microm Sterlitech Corporation Kent WA) was connectedto two UV-resistant Tygon tubes that extended to the sur-face When one tube water was suctioned using a syringethe other was connected to a nitrogen bag to replace the vol-ume of water extracted Extracted samples were stored in10 mL glass vials each containing 100 microL of hydrochloricacid (2 M) to prevent any biological reactions Samples werekept in a cooler at low temperatures (ca 4 C) for no longerthan 2 d before processing

Samples were processed with the goal of measuring theconcentration of dissolved gases in the water 5 mL of thewater sample was extracted from each vial and placed in asyringe pre-filled with 20 mL of N2 gas The syringes wereshaken vigorously for 15 min and 20 mL of the headspacewas extracted into a new 10 mL glass vial The pore-waterconcentrations of the samples were calculated based on theheadspace concentration of the gas in equilibrium with theliquid sample according to Henryrsquos law of equilibrium ofgases in a liquidndashair interface The coefficient of equilibriumfor CH4 was 6713 LMPamolminus1 The gas samples were ana-lyzed in a gas chromatograph with a flame ionization detector(FID Shimadzu GC-2014 Shimadzu Scientific InstrumentsKyoto Japan)

By combining pore-water concentration at the surface withthe associated fluxes estimations of methane transfer veloc-ity were obtained as in previous studies in forested pondsand lakes (Holgerson et al 2017 Schilder et al 2016 Wan-ninkhof 2014) Through this approach the flux at the waterndashair interface can be calculated using the bulk formulation

FCH4 = k(CwminusCeq) (1)

where FCH4 is the diffusive CH4 flux (molmminus2 sminus1) k isthe CH4 transfer velocity (msminus1) Cw is the concentrationof methane in the pore water at the surface (molmminus3) andCeq is the concentration of CH4 in equilibrium with the at-mosphere (molmminus3) Ceq is calculated by multiplying themixing ratio of CH4 in the atmosphere (r in molmolminus1)by the atmospheric pressure (P in MPa) and dividing byHenryrsquos law coefficient of equilibrium for CH4 (KH) of

0067 m3 MPamolminus1 as in Eq (2)

Ceq =rP

KH (2)

Ceq was calculated first with a constant r (2 micromolmolminus1) andsecond with the value of the average of the initial r of thechamber measurements associated with each flux calcula-tion These two methods produced nearly identical results inCeq when compared to the much higher values of Cw Theconstant mixing ratio was chosen for the rest of the analysesgiven the uncertainty associated with the initial concentrationfrom the chambers In the case of our peat bog Cw can becalculated by multiplying pore-water concentration ([CH4])by peat porosity (8 see ancillary measurements below)

Cw = [CH4]8 (3)

where [CH4] was calculated in the top stratigraphic layer ofthe peat (ca 10 cm) Finally methane transfer velocity canbe calculated as

k =FCH4

CwminusCeq (4)

We focus on the top 10 cm because first this is the sectionwhere the atmospheric exchange occurs Secondly this sec-tion should be the most active one for both methanogens andmethanotrophs (Angle et al 2017) since it includes the moreaerobic acrotelm as well as less well-humified peat (greaterlabile C availability)

27 Core sampling DNA extraction and 16S rRNAamplicon sequencing and analysis

We analyzed the microbial composition of peat cores ad-jacent to the peepers Three cores were extracted in Au-gust 2017 from within 5 m of the peepers located in theMat-S Tamarack-S Shrubs Res-N and Res-S zones Thecores were extracted using a rectangular Wardenaar peatcorer with an aperture area of 12 cmtimes12 cm and gt 50 cmlength Core horizons were sampled in the field accordingto obvious stratigraphy (by color texture and von Post hu-mification) Representative ca 10 cm long samples of eachhorizon were stored at 4 C and processed the next day formicrobial analyses Processing involved dividing each sec-tion vertically into three sub-samples which were homoge-nized before a 025 g sub-sample was extracted from eachA fourth 025 g sub-sample was taken following homoge-nization of all the remaining material from a given sectionAll sub-samples were stored at minus20 C for no more than3 months until DNA extraction DNA was extracted usingDNeasy PowerSoil Kit (Qiagen Hilden Germany) followingthe manufacturerrsquos protocol Extracted DNA was quantifiedwith NanoDrop 8000 (Thermo Fisher Scientific WalthamWA) The 16S rRNA V4 region was then amplified andsequenced on the Illumina MiSeq platform (Illumina San

Diego CA) at Argonne National Labs via the Earth Mi-crobiome Project (httpwwwearthmicrobiomeorg last ac-cess 3 January 2019) post-2015 barcoded primer set Theseprimers (515F Parada et al 2016 CGTGYCAGCMGC-CGCGGTAA ndash 806R April GGACTACNVGGGTWTC-TAAT forward-barcoded Parada et al 2016 and Apprill etal 2015) are adapted for Illumina HiSeq2000 and MiSeqby the addition to the forward primer of a 5 ft Illuminaadapter to support paired-end sequencing a 12-base bar-code sequence to support sample pooling in each lane andforward pad and linker sequences and the addition to thereverse primer of a 3 ft Illumina adapter and reverse padand linker sequences (Caporaso et al 2010 redesigned byWalters et al 2016) Each 25 microL polymerase chain reac-tion (PCR) contained 12 microL of MO BIO PCR water (certi-fied DNA-free) 10 microL of 5PRIME HotMasterMix (1times) 1 microLof forward primer (5 microM concentration 200 pM final) 1 microLGolay barcode-tagged reverse primer (5 microM concentration200 pM final) and 1 microL of template DNA The conditions forPCR were as follows 94 C for 3 min to denature the DNAwith 35 cycles at 94 C for 45 s 50 C for 60 s and 72 C for90 s with a final extension at 72 C for 10 min to ensure com-plete amplification The PCR amplicons were quantified us-ing PicoGreen (Invitrogen Carlsbad CA) and a plate readerOnce quantified various volumes of each of the ampliconswere pooled into a single tube for equal representation ofeach sample This pool was then cleaned using UltraCleanPCR Clean-Up Kit (MO BIO Laboratories Inc) and quanti-fied using the Qubit (Invitrogen Carlsbad CA) After quan-tification the molarity of the pool was determined and di-luted to 2 nM denatured and then diluted to a final concen-tration of 40 pM with a 10 PhiX spike for sequencing onthe Illumina MiSeq via the protocol with 2times 150 base pairs

Sequence data were processed with the bioinformatic soft-ware QIIME 191 (Caporaso et al 2010) using a 16S RDSpipeline (Nelson et al 2014) with slight modifications Thesubset of amplicon-based lineages identified as genera ofknown methanogens and methanotrophs (Appendix A Ta-ble A1) were then further profiled for this study Sub-sampleswere averaged to obtain one mean value for each sectionwithin each core

28 Ancillary measurements

Data from nearby NOAA meteorological stationsWBAN14813 and WBAN14985 (httpswwwncdcnoaagovcdr last access 8 November 2018) were used toobtain hourly and daily averages of air temperature precip-itation and atmospheric pressure Eight dip wells adjacentto the peepers (Mat-N Mat-S Tamarack-N Tamarack-SShrubs Lagg Res-N and Res-S) were used for monthlymeasurements of water level Water level was measuredcontinuously between June 2017 and October 2018 in fourof the eight dip wells (Mat-S Tamarack-S Shrubs Res-S)Water levels at other locations were estimated based on an

offset between manual readings of water level To calcu-late water levels we used HOBO pressure sensors (OnsetComputer Corporation Bourne MA) that were correctedusing atmospheric pressure data from the NOAA stationsAdjacent to each peeper we measured vertical profiles ofdissolved oxygen two to four times a year using a probeequipped with a fiber-optic sensor and a temperature sensor(PreSens Precision Sensing GmbH Regensburg Germany)The probe was inserted to a depth of 80 cm and allowed tostabilize for ca 30 min The probe was then moved upwardsin 10ndash20 cm increments to complete a profile up to the levelof the water table

Water from the eight dip wells was sampled for chemi-cal analysis roughly monthly between 27 June and 3 Octo-ber 2017 in four sampling events All dip wells were perfo-rated at 60ndash90 cm below ground level to ensure that watersamples were collected from a consistent depth Before col-lecting water samples dip wells were emptied completelyusing a vacuum syringe and allowed to refill When it wasimpossible to completely empty a dip well due to rapidrecharge a volume of water equivalent to the volume of thedip well was removed before collecting samples Electricalconductivity (EC) and pH were measured in the field us-ing a YSI Pro1030 pH conductivity and salinity instrumentWhen dip-well recharge was insufficient for EC and pH mea-surements in the field these measurements were made within48 h in the lab using a YSI EcoSense EC30A conductivityand TDS pen tester and a YSI EcoSense EH10A pH andtemperature pen tester Water samples were then filtered us-ing Whatman binder-free glass microfiber 07 microm filters thathad been combusted at 500 C to remove organic contamina-tion Water samples were stored in HDPE-coated bottles andfrozen atminus22 C for 10 months prior to analysis Inductivelycoupled plasmandashoptical emission spectrometry (ICP-OESUS EPA 2015b) was carried out using a Varian Vista-MPXto measure concentration of Al Ca Fe K Mg Mn Na PS and Zn Concentrations of NO3+NO2 nitrogen (measuredas a combined value) and NH4 nitrogen were determined bycolorimetry using Lachatrsquos QuikChemreg 8500 Series 2 FlowInjection Analysis System (US EPA 2015a) Quality assur-ance and quality control protocols were followed for boththe ICP-OES and flow injection analyses Recoveries of ma-trix spikes and serial dilutions were at least 75 and 90 respectively The reporting limit (RL) for each batch of sam-ples was the lowest concentration in the calibration curveThe RL for NH4-N was 01 mgLminus1 and the RL for all otheranalytes was 001ndash005 mgLminus1 Where concentrations werebelow the reporting limit the measured concentration wassubstituted with one-half the reporting limit Check standardsand blanks were analyzed every 10 samples Check standardrecoveries did not exceed plusmn10 error and blanks did notexceed reporting limits No blanks were allowed to exceedthe reporting limits Accuracy of pH and EC measurementswas ensured through regular calibration of equipment

In 27 June 2017 one core from the Shrubs zone and onefrom the Res zone were extracted for analysis of peat bulkdensity and porosity The core was sliced every 25 cm toa depth of 50 cm Samples were packed and sealed in plas-tic bags and taken to the laboratory to measure wet weightSamples were then dried in an oven at 60 C for 2ndash3 duntil the weight was stable Peat bulk density was calcu-lated based on the weight of dry soil occupied by slicesof 25 cmtimes12 cmtimes12 cm Porosity was calculated as 1 mi-nus the ratio of peat bulk density to soil particle densitywhich was estimated as 145 Mgmminus3 for Sphagnum peatsoils (Oleszczuk and Truba 2013)

29 Data analysis

Data preparation was completed in MATLAB (R2017bMathworks) and statistical analyses were completed in Rversion 351 (R Development Core Team 2018) Differ-ences in CH4 fluxes between hydro-biological zones wereevaluated using a linear mixed-effect model (lmm) throughthe function ldquolmerrdquo implemented in R in the packageldquolmerTestrdquo version 30-1 (Kuznetsova et al 2017) Trans-formation of CH4 flux data to their logarithm base 10 wasapplied to improve the normality of the data and the nor-mality of the residuals of the model The fixed effects in themodel were Zone (Water Mat Tamarack Shrubs and Res)a categorical value for year (Year) a categorical value for themonth of measurements (Month) temperature 10 cm belowthe surface (Tsurf) mean water level for a month before theflux measurements (WLm) and a continuous variable rep-resenting the time to noon in hours (t2noon) The transect(north or south) was specified as a random effect We alsotested for the interactions between Zone and Month Zoneand WLm and Zone and Tsurf but they were not significantThe final statistical model for both CH4 flux is described inEq (5)

Fluxsim Zone+ Tsurf+WLm+Year+Month

+ t2noon+ (1|Transect) (5)

Pair-wise differences in emissions among the zones wereevaluated through testing differences in the marginal meansof the reference grid of the mixed model using the packageldquoemmeansrdquo in R (Lenth et al 2018) The overall effect ofthe factors within the model was evaluated with an ANOVAof the model Significance in the model was defined with ap value of 005 To evaluate if plant fluxes were significantlydifferent from zero we used a one-sample Wilcoxon test

Pore-water concentrations of CH4 were evaluated usinga linear mixed model We used a similar model to evaluatepore-water CH4 concentrations except that we added depth tothe surface (Depth) as a fixed effect (see Eq 6) We deletedthe interaction between depth and zone because it was notsignificant The final model for pore-water concentrations of

CH4 is described in Eq (6)

CH4 Pore-water concsim Zone+Depth+WLm+ Tsurf

+Year+Month+ (1|Transect) (6)

Pair-wise differences in pore-water concentrations betweenzones were tested by evaluating differences in the marginalmeans in the same way as for the model of CH4 flux Theoverall effect of the factors in the model was evaluated withan ANOVA

Chemical analyses were not included in the model aschemistry data were only available for 2017 Instead a prin-cipal component analyses was run on the chemical variables(12 chemical species plus EC and pH Appendix A Ta-ble A2) at the eight sampling locations and the scores ofthe first principal component were correlated to mean CH4fluxes mean CH4 pore-water concentration and mean CH4transfer velocity Differences in element concentrations be-tween different vegetation zones and between different loca-tions were evaluated using ANOVA Pair-wise comparisonswere evaluated using a Tukey HSD (honestly significant dif-ference) post hoc test Differences in peat bulk density wereevaluated using an ANCOVA of zone and depth The rela-tionship between microbiota and methane fluxes was evalu-ated through a correlation of the ratio of the relative abun-dance of methanogens to the relative abundance of methan-otrophs versus CH4 flux mean CH4 pore-water concentrationand CH4 transfer velocity

3 Results

31 Inter- and intra-annual variation in abioticconditions

The mean air temperature during the growing season (1 Mayto 31 October) was 204 C in 2017 and 225 C in 2018 asmeasured by standard meteorological stations In 2017 and2018 total precipitation for the growing season was 196 and356 mm respectively (Fig 2) The water level ranged fromminus454 to 197 cm in 2017 and minus551 to 273 cm in 2018where negative levels indicate a water table below the groundsurface (Fig 2) As expected the intermittently wetted area(Shrubs Lagg and Res zones) experienced substantial fluc-tuations in water level while in the permanently wetted area(Tamarack) the water level remained at or close to the surface(Fig 2) Fluctuations were smaller in the Tamarack zonewith the water table drawing down to a maximum depthof 12 cm compared to a maximum of 53 cm in the Shrubs(Fig 2)

pH was similar throughout the bog with higher values oc-curring in the restored (Res) zone than in the undisturbedzone (Appendix A Table A2) but with no significant dif-ferences among the hydro-biological zones (F = 098 p =

043) The Lagg zone had significantly higher concentra-tions of Fe Ca Mg and Mn when compared to other hydro-

biological zones (p lt 005 for all paired relationships) Therestored section had significantly higher concentration of Mn(F = 380 p = 001) and Na (F = 378 p = 001) Concen-trations of Ca and P tended to be higher in the restored sec-tion as well however the differences were not significantwhen comparing all hydro-biological zones (F = 288 247p = 005 007 respectively) Interestingly concentrations ofammonia (NH+4 ) were significantly higher in the Tamarackzone (F = 106 p lt 0001) than in all the other zones whileconcentrations of nitrate (NOminus3 ) were generally low and didnot significantly differ among zones (F = 005 p = 091)

The northern section of the bog collected runoff from adja-cent agricultural fields and consequentially had higher pHelectrical conductivity and concentration of elements includ-ing S Na Mn Mg Fe and Ca than the rest of the bogNotably when considering location-wise comparisons theconcentrations of S Ca and Mn were significantly higherin Tamarack-N than in all other locations of the undisturbedbog (Appendix A Table A2) Location differences also oc-curred in the restored section pH was significantly higher inthe Res-N location (p lt 005) and P was significantly higherin the Res-S location (p lt 005)

Vertical profiles of dissolved oxygen confirmed the exis-tence of anoxic conditions below the water level Dissolvedoxygen concentrations below the water level were alwaysless than 01 mgLminus1 whereas above the water level the con-centration increased sharply The only exception was the pro-files taken at the Mat which had an average dissolved oxygenconcentration of 027 mgLminus1

Peat bulk density was significantly lower in the Shrubsthan in the Res zone (F = 345 p lt 0001) with aver-ages plusmnSD of 008plusmn 002 and 012plusmn 003 gmminus3 respec-tively Calculated porosities assuming a peat particle den-sity of 145 gmminus3 (Oleszczuk and Truba 2013) were equalto 945 and 918 Because the peat was saturated at thetime of extraction this porosity is equivalent to the volumet-ric water content There was not a significant effect of depthon peat bulk density (F = 005 p = 082)

32 The effect of different hydro-biological zones andwater level on CH4 emissions

There were higher CH4 emissions towards the central per-manently wetted part of the bog (Table 1) The fluxes fromthe Lagg zone were not significantly different than zero(t test p = 0185) and were therefore excluded for futurecomparisons among zones Mean CH4 fluxes were signifi-cantly different between hydro-biological zones (F = 114p lt 0001) The fluxes from the Water zone were not signif-icantly higher than the fluxes from the other units within thepermanently wetted area (t ratio=minus145 p = 059 and t ra-tio= 127 p = 070 for Mat and Tamarack respectively)but they were significantly higher than fluxes in the intermit-tently wetted area (Shrubs zone t ratio= 583 p lt 0001Res zone t ratio= 653 p lt 0001) CH4 emissions from

Figure 2 Water-level (WL) fluctuations in the tamarack mixed woodland (Tam) zone the mixed ericaceous shrub (Shrubs) zone and therestored (Res) zone of the bog Vertical dashed lines indicated the 10 times of pore-water sampling and the solid lines indicate the two timesof core sampling gray for Tam Shrubs and Res-S and teal for Mat and Res-N The secondary axis shows daily values of precipitation

Table 1 CH4 fluxes for the different hydro-biological zones in Flatiron Lake Bog Integrated fluxes are based on a 122 d period for 2017 and149 d period for 2018 Values in parenthesis for mean fluxes are the standard error and for the subsequent rows the propagated standard error

Area Median flux Mean flux Daily normalized Daily normalized(m2) (nmolmminus2 sminus1) (nmolmminus2 sminus1) emissions 2017 emissions 2018

(mgCH4 mminus2 dminus1) (mgCH4 mminus2 dminus1)

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Tamarack 14 577 105 6022 686 24785(minus86ndash27 186) (3421) (828) (38195)

Shrubs 85 539 31 625 4410 85(minus08ndash624) (2262) (1627) (90)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

BBa 12 3546 minus04 minus11 minus39 minus38(minus38 to minus384) (047) (18) (13)

Total 125 592 na na 3154b 3623b

(166) (687)

a BB blueberry leaves occupy the area of the Tamarack Shrubs and Res zones Fluxes from other plant species and from the Lagg zonewere not significantly different from zerob Total emissions per zone (mg CH4 dminus1) were added and divided by the area of the bog (excluding the Lagg zone) to produce the finalresult of 3154plusmn 166 mg CH4 mminus2 dminus1 in 2017 and 3623plusmn 687 mg CH4 mminus2 dminus1 in 2018na not applicable

the restored section were significantly lower than the emis-sions from units in the permanently wetted area and theMat (t ratio=minus46 p lt 0001) and Tamarack zones (t ra-tio=minus61 p lt 0001) However CH4 emissions from therestored section were not significantly different from theemissions from the Shrubs zone (t ratio=minus017 p = 099)

Mean water level (WLm) had a significant effect on CH4flux (F = 849 p = 0003) with higher emissions occurringwhen WLm was more positive (higher WLm) The effectof water level on CH4 fluxes was not significant when con-sidering instantaneous water levels at the time of the mea-surements but was significant when considering the averagewater-level data throughout the 30 d prior to the flux mea-

surement The effect of temperature (Tsurf) was not signifi-cant (F = 071 p = 040)

33 Temporal variations in CH4 fluxes

There was a substantial temporal variability in CH4 fluxesThe open water zone was the only zone that had a distinct andconsistent seasonal cycle where the fluxes increased fromMay to the middle of the growing season peaking in earlySeptember and declining in October (Fig 3) In the Tama-rack zone fluxes declined over the growing season in 2017but in 2018 the flux peaked in early September where therewere two extremely high flux measurements at the north-ern transect of 27 180 and 8605 nmolmminus2 sminus1 that skewed

Figure 3 Monthly fluxes of methane for each of the five hydro-biological zones of the study Fluxes from the Lagg were not sig-nificantly different than zero and are therefore not shown Standarderrors are for all sample locations within the same month and zone(variable number see Sect 23)

Figure 4 Diurnal patterns of CH4 emission measured over a 24 hperiod in September 2018 Note a smaller y axis maximum in theShrubs zone Error bars represent the standard error of four individ-ual chamber measurements within the same 30 min period at eachlocation Secondary axis (and black lines) shows the temperature at10 cm below the surface either in the open water (Water) or in thepeat (Mat Tamarack and Shrubs) The Res zone was not sampled

the average to a total of 6748 nmolmminus2 sminus1 There was nosignificant relationship between month of measurement andCH4 flux (F = 221 p = 005) Across all hydro-biologicalzones CH4 fluxes were not significantly different in 2017and 2018 (F = 259 p = 011)

Although the relationship of CH4 emissions with time tonoon was significant (F = 131 p lt 0001) the diurnal mea-surements from September 2018 (Fig 4) did not indicatestrong diurnal patterns of CH4 emissions In the open wa-ter zone CH4 emissions decreased during the late afternoonto early evening which approximately coincided with a peakin water surface temperature (Fig 4) In the Tamarack zoneemissions increased with warmer temperatures in the after-noon In the Mat zone there was a peak in the middle of themorning but there was no apparent relationship with surfacetemperature There was no clear diurnal pattern of CH4 emis-

Figure 5 Plant-mediated CH4 fluxes from loosestrife leaves (Matzone) tamarack leaves tamarack Stems and blueberry leaves(Tamarack and Shrubs zone) Only fluxes from the blueberry weresignificantly different from zero (p = 001)

sions in the Shrubs zone likely a consequence of very lowCH4 emissions during the time of measurements

34 Plants fluxes and upscaling of CH4 emissions

Fluxes from plant tissues were negligible compared to thefluxes from the peat or open water surfaces (Fig 5) Mea-surements from loosestrife the most abundant vascular plantin the Mat and from tamarack stems and stems were notsignificantly different from zero (p = 083 p = 048 andp = 006 respectively) Fluxes from the blueberry leaveswere significantly different than zero (p = 001) and aver-aged at minus111 nmolmminus2 sminus1 indicating net uptake of CH4by or through blueberry plants (Fig 5)

The peat bog emitted a total of 48plusmn19 and 55plusmn84 t ofCH4 during the growing seasons of 2017 and 2018 respec-tively The high uncertainty in 2018 was due to the largervariation in fluxes produced by high fluxes in the Tamarackzone which emitted a total of 012plusmn 014 t of CH4 in 2017but a much higher 54plusmn 82 t of CH4 in 2018

Blueberry leaves acted as a slight sink of atmosphericCH4 with a mean flux ofminus111 nmolmminus2 sminus1 The total sinkof CH4 from blueberry bushes was equal to minus469plusmn 20 andminus574plusmn24 kg of CH4 for 2017 and 2018 respectively Thesevalues were equal to a small offset of the total daily emissionsby 037 for 2017 and 014 for 2018

Because the length of the measurement periods in thegrowing seasons was not equal among years total emis-sions (Table 1) were divided by the length of the mea-surement period to produce estimates of mean total fluxper day These values were then divided by the area ofthe bog (excluding the Lagg zone) to produce the final re-sult of 3154plusmn 166 mgCH4 mminus2 dminus1 in 2017 and 3623plusmn687 mgCH4 mminus2 dminus1 in 2018

Figure 6 Vertical profiles of CH4 pore-water concentrations byzone The error bars represent the standard deviation of the monthlymeasurements for 2017 and 2018 combined A minor y-axis jitterhas been added to more clearly distinguish zone patterns Note thatthe concentrations in the Tamarack zone at depth approach satura-tion (144 mM at 20 C CH4)

35 Dissolved CH4 pore-water concentrations andmethane transfer velocity

Excluding the Mat zone the mean CH4 pore-water concen-tration per zone followed a pattern similar to the fluxes withhigher concentrations in the Tamarack zone followed byShrubs Res and Lagg zones (Fig 6) Pore-water CH4 con-centrations were significantly higher in the Tamarack zonethan in the Mat zone (t ratio= 33 p = 0003) and in theShrubs zone (t ratio= 64 p lt 0001) Pore-water CH4 con-centrations were significantly lower in the Res zone than inthe Mat zone (t ratio=minus72 p lt 0001) the Tamarack zone(t ratio=minus171 p lt 0001) and the Shrubs zone (t ratio=minus68 p lt 0001) but not significantly different from concen-trations in the Lagg (t ratio= 028 p = 077 Fig 6) Dif-ferences in CH4 pore-water concentration between Mat andShrubs zones were not significant (t ratio= 198 p = 019)It is important to note that times for which the water tablewas below the level of a certain peeper sampling windowwere considered to be missing values because there was nopore water at that given height

There was a significant relationship between CH4 con-centration and depth (F = 853 p lt 0001) with pore-waterconcentrations of CH4 increasing with depth CH4 pore-water increased significantly with increasing temperature10 cm below the surface at the time of measurement (Tsurf)(F = 209 p lt 0001) and with the average water level dur-ing the month preceding the measurement (WLm F = 162p lt 0001) Higher water tables were associated with in-creased CH4 pore-water concentration throughout the wholeprofile

Per location average (meanplusmnSD) CH4 pore-water con-centration in the top 50 cm of the peat was the highestin Tamarack-S (086plusmn 062 mM) followed by Tamarack-N(076plusmn036 mM) Shrubs (030plusmn026 mM) Mat-N (021plusmn012 mM) Mat-S (019plusmn012 mM) Res-N (014plusmn013 mM)Lagg (010plusmn008 mM) and Res-S (009plusmn008 mM) Ammo-nium concentration was positively correlated with CH4 pore-water concentration averaged for the whole profile (r2

070 p = 0005) and for the top peat layer (r2= 083 p lt

001)CH4 pore-water concentrations were significantly differ-

ent among months with concentrations always lower in May(p lt 0001 for all paired relationships) and June (p lt 0001for all paired relationships) and higher in August around thepeak of the growing season and October at the end of thegrowing season CH4 pore-water concentrations were signif-icantly higher in 2018 than in 2017 (F = 249 p lt 0001)

Overall there was no significant relationship between av-erage concentration and surface fluxes (r2 lt 001 p = 095)even when considering only the top layers of the peat col-umn where a better relationship was expected (r2

= 008p = 011 Fig 7a) The lack of a relationship was surprisingas the values included only those times at which the top strati-graphic layer of the peat was saturated Methane transfer ve-locity was calculated from these data (Fig 7b) and from thetimes when the microbiology data were available for com-parison (Fig 7c)

The first principal component (PC1) of the chemical ana-lytes explained 376 of the variation in the dataset whilethe second explained 285 (Appendix B Fig B1) The10 variables that contributed the most to PC1 were in or-der Mn Ca Mg S P Al EC NA NO3 and K There wasno significant relationship between PC1 and CH4 flux (r2

017 p = 017) CH4 pore-water concentration (r2= 015

p = 080) or CH4 transfer velocity (r2= 012 p = 065)

36 Both methanogens and methanotrophs were moreabundant in permanently wetted zones

Overall both methanogens and methanotrophs were athigher relative abundances (as a portion of the overall mi-crobial communities) in the permanently wetted zones Mat-S and Tamarack-S (where they accounted for 18 and20 of the microbial communities respectively by am-plicon percentages) than in the intermittently wetted zonesShrubs Res-N and Res-S (02 01 and 01 respec-tively Fig 8) In addition hydrogenotrophic methanogens(Methanobacterium and Methanoregula) were much moreabundant than acetoclastic methanogens (Methanosaeta andMethanosarcina) at all sites (Fig 8) Among the hy-drogenotrophs Methanobacterium was broadly presentwhile Methanoregula was generally a larger component ofthe methanogen community in saturated undisturbed peat(Mat-S Tamarack-S and deep Shrubs) Among the aceto-clastic methanogens Methanosaeta was observed only in the

Figure 7 (a) Relationship between CH4 pore-water concentrationand CH4 flux for times where the WL was high and within the topstratigraphic layer of the peat (b) CH4 transfer velocity calculatedfrom the upper plot (c) same as previous but with the data relevantfor microbial analysis only Note that microbial samples for Tam-N Mat-S and Lagg are not available and therefore not used in thefollowing comparisons of CH4 transfer velocity against microbialactivity The error bars are the standard error

permanently wetted zone Mat-S and Tamarack-S and ac-counted for a small proportion of total methanogens exceptat 50 cm in Mat-S In the restored zones where acetoclas-tic methanogens had higher relative abundances the genusMethanosarcina was predominant

Methanotrophs were mostly present in the permanentlyflooded zones Mat-S and Tamarack-S and were particu-larly abundant in peat strata closer to the surface (0ndash20 cm)Methylomonas accounted for most of the methanotroph se-quences found in this study and dominated the methan-otrophs of the Mat-S and Tamarack-S zones while Methy-losinus was a much larger portion of the methanotrophs inthe Shrubs and Res zones (Fig 8) even as overall methan-otroph relative abundance dropped to less than 005 of themicrobial community

Methane fluxes were not correlated to the relative abun-dance of methanogens (r2

= 001 p = 074) or methan-otrophs (r2

= 001 p = 078) In addition mean CH4 con-centrations were also not correlated to the relative abun-dance of methanogens (r2

= 001 p = 070) However for the principal co-ordinates analysis of sites based on geochemistry PC1 wassignificantly negatively correlated to methanogensrsquo relativeabundance (r2

= 090 p lt 001) As indicated above mostof the variation in PC1 was driven by Mn Ca Mg andS and there was a significant relationship between mean

methanogen relative abundance and manganese (r2= 090

p = 0007) and sulfur concentrations (r2= 074 p = 003)

When considering only the bottom 25 cm of the peat pro-file the layer from which pore water was taken for chemi-cal analyses methanogen relative abundance was negativelycorrelated to electrical conductivity (r2

= 085 p = 001) Inthe top layer of the peat where methanotrophs are more ac-tive there was a negative correlation between methanotrophrelative abundance and magnesium concentration (r2

= 079p = 003)

4 Discussion

41 The CH4 budget and its heterogeneity amonghydro-biological zones

There were relatively high CH4 emissions in FlatironLake Bog compared to previously reported fluxes in othernorthern peatlands Average daily CH4 emissions wereequal to 3154plusmn 166 mgCH4 mminus2 dminus1 in 2017 and 3623plusmn687 mgCH4 mminus2 dminus1 in 2018 These values were higherthan emissions in ombrotrophic peat bogs in Minnesota(monthly average range 27ndash240 mgCH4 mminus2 dminus1 Chasar etal 2000 117 mgCH4 mminus2 dminus1 Dise 1993) and Michigan(06ndash209 mgCH4 mminus2 dminus1 Shannon and White 1994) andin a boreal bog in northern Quebec (57 mgCH4 mminus2 dminus1Nadeau et al 2013) Higher CH4 fluxes compared to otherbogs are likely the result of the higher temperatures experi-enced in Ohio which are at the southern limit of northernpeatland distribution

Methane fluxes were highly heterogeneous with a vari-ation of over 4 orders of magnitude and with a skeweddistribution due to extreme events of CH4 flux (median337 nmolmminus2 sminus1 range minus122ndash27 186 nmolmminus2 sminus1)The skewed distribution of CH4 fluxes and heterogene-ity has also been found by Christen et al (2016) in aCanadian undisturbed scrub-pine Sphagnum bog (median42 nmolmminus2 sminus1 range 5ndash3500 nmolmminus2 sminus1) and byTreat et al (2007) in temperate fen in New Hampshire(range 63ndash2772 nmolmminus2 sminus1) We found higher emis-sions in the open water (mean 122 median 619 range014ndash1823 nmolmminus2 sminus1) than in the other hydro-biologicalzones This pattern was also found by Christen et al (2016)who found that fluxes from open waters or ponds hadan average of 3336 nmolmminus2 sminus1 and a median value of2670 nmolmminus2 sminus1 compared to collars on the groundcontaining vegetation that had mean and median valuesof 986 and 47 nmolmminus2 sminus1 respectively In an analysisof a variety in peatlands in Minnesota Crill et al (1988)also found that mean CH4 emissions were 294 mgmminus2 dminus1

in open bogs while in forested bogs the mean was equalto 77 mgmminus2 dminus1 This result agrees with our calcula-tions where we find daily normalized fluxes averaged

Figure 8 Relative abundances of methanogens and methanotrophs in the Mat-S Tam-S Shrubs Res-N and Res-S zones of the bog atdifferent depths in the peat column with the mean water level from June 2017 through August 2017 (mean WL) and the water level attime of sampling (core WL in Mat-S these were both at 0 cm in Tam-S the mean WL was at 0 cm) Panel (a) shows overall methanogen(Mgens) and methanotroph (Mtrophs) abundances along with the average dissolved oxygen profile over the preceding month (from coringsee Methods) The observed genera of methanogens and methanotrophs are shown in panels (b) and (c) respectively with variable x axesMethanobacterium (Mbac) and Methanoregula (Mreg) are hydrogenotrophic methanogens and Methanosaeta (Msaet) and Methanosarcina(Msarc) are acetoclastic methanogens Methylomonas (Mmonas) and Methylosinus (Msinus) are methanotrophs

for both years of 279 mgCH4 mminus2 dminus1 in open water and22472 mgCH4 mminus2 dminus1 in the mixed ericaceous shrub units

There were extremely high CH4 flux measurements fromthe northern transect of the Tamarack zone in Septem-ber 2018 (27 180 and 8605 nmolmminus2 sminus1) and in Octo-ber 2018 (2808 and 6609 nmolmminus2 sminus1) These measure-ments were not ebullition events since the increase in con-centration with time was steady (Appendix B Fig B2) andthe coefficient of correlation for both flux events was higherthan 097 They were not localized events either since thetwo collars were about 15 m apart from each other Unfor-tunately a core was not taken at the northern transect wherethis event occurred so the abundance of methanogens andmethanotrophs could not be tested Interestingly the concen-

tration of sulfur was significantly higher in this zone indi-cating that the Tamarack-N possesses an environment that ishighly reduced where both methanogenesis and sulfate re-duction take place at extremely high rates This was corrob-orated by the detection of a potent smell of hydrogen sul-fide while measuring these extremely high CH4 fluxes It isalso possible that specific plantndashsoil relationships such ashigher polysaccharides in the form of tree-root exudates (Lai2009) have enhanced CH4 production in the Tamarack zoneHowever more research on the characteristics of the peat atthis site is needed to reach conclusions about these extremeevents

Although higher heterogeneity in CH4 fluxes within peatbogs can be encountered it is likely that the same patterns

of CH4 flux along hydro-biological zones occur in otherkettle-hole peat bogs due to the tight relationships betweenwater-level fluctuations and vegetation composition in theseecosystems (Malhotra et al 2016) It is also possible thatthe higher rates of CH4 emission in this Ohio peat bog arereplicated in similar peat bogs located at lower latitudeswhere warmer temperatures have the potential to not onlydrive much higher productivity (Cai and Yu 2011) but alsoincrease methane emissions due to the effect of higher tem-peratures on CH4 emissions in peatlands (Moore and Dalva1993 Pugh et al 2018)

42 The role of plants in the CH4 cycle in peat bogs

The presence of different plant species was strongly associ-ated with variations in CH4 emissions in peatlands For ex-ample the presence of sedges such as Eriophorum vagina-tum L in ombrotrophic peat bogs was observed to be animportant transport of CH4 to the atmosphere (Greenup etal 2000) In our study site however there was no activeplant transport of CH4 This lack of plant transport in om-brotrophic peat bogs has also been reported by Chasar etal (2000) and can be likely attributed to a low abundanceof sedges

Lai et al (2014) found that fluxes varied signifi-cantly among plant communities at the ombrotrophic MerBleue bog in Canada In this bog low fluxes werefound in Chamaedaphne (32ndash22 mgCH4 mminus2 dminus1) and Ma-ianthemum and Ledum (83ndash53 mgCH4 mminus2 dminus1) communi-ties whereas the highest were found in the Eriophorum-dominated community (122ndash124 mgCH4 mminus2 dminus1) Themagnitude of these fluxes was much lower than the aver-age daily emissions from the mixed ericaceous shrubs of22472 mgCH4 mminus2 dminus1

Interestingly we found that blueberry plants were slightbut statistically significant sinks of CH4 This result wasalso reported by Sundqvist et al (2012) who found that bo-real plants of spruce (Picea abies) birch (Betula pubescens)rowan (Sorbus aucuparia) and pine (Pinus sylvestris)showed a net uptake of CH4 The values found by Sundqvistet al (2012) fluctuated between 1 and 2 nmolmminus2 sminus1 whichis similar to the values found in this study The mechanismbehind this process is still uncertain but it has been reportedthat this process could be mediated by epiphytic bacteriacapable of consuming CH4 (Raghoebarsing et al 2005)Sundqvist et al (2012) believe that the response is medi-ated by gross primary productivity and stomatal conductancethrough mechanisms not yet understood

We did not find a clear diurnal pattern of CH4 emissionsin the bog Similarly summer season measurements of eddycovariance in an ombrotrophic bog did not find clear diur-nal patterns either (Nadeau et al 2013) In contrast studiesin other wetlands have found a mid-morning peak in CH4emissions in fen (Whiting and Chanton 1992) and marshes(Kim et al 1999 Rey-Sanchez et al 2018 Van der Nat

et al 1998) This discrepancy is likely due to the fact thatCH4 emissions in marshes (Chu et al 2014 Hatala et al2012 Morin et al 2014 2017) and in fen (Chasar et al2000 Treat et al 2007 Waddington and Day 2007) arelargely dominated by plants that transport CH4 through theiraerenchyma

43 Fluctuations in water level explain variability inCH4 emissions

Methane fluxes were different among hydro-biologicalzones but given that plants were not a pathway of CH4 fluxthe reported differences were most likely driven by the water-level differences among hydro-biological zones The lengthof dry conditions preceding permanently wetted conditionshas important consequences for the magnitude of CH4 fluxes(Turetsky et al 2014) While the highest CH4 flux occursafter a period of 30 d of antecedent wet conditions (Turet-sky et al 2014) longer dry periods reduce the capacityof methanogens to acclimate to stable environmental condi-tions therefore reducing methanogenesis Indeed we foundthat the average water-level data throughout the 30 d prior tothe flux measurement not the instantaneous water level hada significant effect in CH4 fluxes We hypothesize that this isa general ecological response by which community compo-sition lags behind environmental change In our case it maytake several weeks for methanogens to acclimate to new wa-ter levels after the water level has been raised therefore notresponding to instantaneous changes in water level Both Resand Shrubs zones were characterized by high fluctuations inwater level which was likely the cause of lower CH4 emis-sions in these zones when compared to the more permanentlywetted Tamarack Mat and Water zones Higher WL fluctua-tions in the Shrubs zones in 2018 (rangeminus404ndash61 cm) thanin 2017 (range minus316ndash80 cm) could also explain the higherCH4 emissions in 2017 than in 2018 in the Shrubs zone

Our conclusion is that methanogen inhibition associatedwith longer dry periods in the Shrubs and Res zones is likelythe cause of lower CH4 emissions However reduced CH4emissions are also the result of an increase in the amount ofmethanotrophy in the upper oxic layers We can confirm thisas we observed pore-water concentrations of CH4 that weremuch higher in the Shrubs zone than in the Res zone despitesimilar WL fluctuation Yet the fluxes were not significantlydifferent between these two zones indicating higher levels ofmethanotrophy in the Shrubs zones Indeed methanotrophrelative abundance in the top section was twice as much inthe Shrubs zone than in the Res zone

We did not find a significant correlation between CH4 fluxand surface temperature This is partially explained by thefact that the effect of temperature on peatland CH4 emissionsis significant when the water table is near the surface (Strackand Zuback 2013) and our site had significant water-levelfluctuations For example Lai et al (2014) found that the re-lationship between temperature and CH4 flux was only sig-

nificant when the water table was less than 30 cm depth inaverage It is possible that due to monthly variations in thewater level in the Shrubs and Tamarack sites the response ofCH4 emissions to temperature was confounded The tempo-ral resolution of the measurements was also a reason for thelack of correlation At a higher temporal resolution such asthe measurements of the diurnal pattern the effect of temper-ature on CH4 emissions may be more easily discerned

44 Pore-water CH4 concentrations were higher in theundisturbed section

Pore-water CH4 concentration was high throughout theundisturbed section of the bog and significantly lower inthe restored section Although concentrations of key elec-tron acceptors such as nitrates or sulfates were low and notsignificantly different among zones we found that the re-stored section had significantly higher concentration of Mn(F = 380 p = 001) and Na (F = 378 p = 001) sug-gesting that bacterial manganese reduction could competeagainst methanogens in the restored zone

Excluding the Mat zone pore-water CH4 concentrationfollowed a similar pattern of variation to the fluxes withhigher concentrations in the Tamarack zone followed byShrubs Res and Lagg zones Low concentrations but higherfluxes in the Mat zones indicate a higher CH4 transfer ve-locity This could be the consequence of different porositiesin the peat that affect the rate of transfer However becausethe porosity throughout the peat bog was uniform it is likelythat CH4 transfer velocity is being driven by microbial activ-ity rather than physical properties (see Sect 46)

Pore-water CH4 concentration was the highest in theTamarack zone with concentration at deeper levels close tothe saturation point (12 mM) Similarly in a study in an om-brotrophic peat bog in Minnesota Chasar et al (2000) re-ported high CH4 pore-water concentrations in bogs of 12and 15 mM for pore water at about 1 m of depth for June andJuly respectively Chasar et al (2000) also reported muchhigher pore-water CH4 concentrations in bogs than in fen andsuggested that this is related to negligible plant transport inpeat bogs that causes CH4 to accumulate in the pore waterdiffuse upwards and be oxidized in the top layers of the peatMethanotrophy in the shallow layers of the peat was also re-ported by Chasar et al (2000) where analysis of isotopes inshallow pore water versus associated fluxes indicated oxida-tion of CH4 in the pore water before diffusive transport to theatmosphere

Concurrent measurements of pore-water CO2 concentra-tions indicated that the CH4 CO2 ratio was similar at the topof the profiles while at the bottom of the profiles there was aclear difference between restored and undisturbed sites (Ap-pendix B Fig B3) This difference could indicate that thereis a higher competition for respiratory processes in the dis-turbed section while methanogenesis is more favored in theundisturbed section The analysis of CO2 fluxes is not how-

ever within the scope of this paper and is presented here onlyas a preamble for future studies

45 Methane-cycler abundance depends on vegetationzone and water level

Consistent with expectations based on their anaero-bic lifestyle we found higher relative abundances ofmethanogens in the permanently wetted areas Mat and Tama-rack than in the intermittently wetted areas (Shrubs Res-N and Res-S) Hydrogenotrophic methanogens which aretypically dominant in nutrient-poor sites (Kelly et al 1992Kim et al 2008 Kotsyurbenko et al 2004) and are typicalof Sphagnum-dominated bogs (Chasar et al 2000 Kelly etal 1992 Lansdown et al 1992) dominated both the undis-turbed and restored sections while acetoclastic methanogenswere rare and only slightly more common in the restored sec-tion We hypothesized that the restored section had gainedmore nutrients due to higher degree of mineralization how-ever the dominance of hydrogenotrophic methanogens sug-gests that the restored section may still be nutrient-poor de-spite the disturbance and apparent mineralization of the soilThis is also evident in the low concentration of key con-stituents such as nitrates iron ammonium phosphorousand magnesium (although note relatively higher concentra-tions of manganese and calcium in the restored section Ap-pendix A Table A2) It is possible that 15 years of restora-tion efforts have effectively restored this sectionrsquos trophicstatus and that acetoclastic methanogenesis was higher therein the past Alternately the original disturbance may havehad minimal impact on the microbial composition such thatthe restored section retains a community similar to its pre-disturbance state when it was part of the Shrubs zone ofthe then-undisturbed section Basiliko et al (2013) similarlyfound that mining-based disturbance and subsequent restora-tion of Canadian peatlands did not affect archaeal microbialcommunity composition

At the genus level however there were differences inmethanogen composition between the undisturbed and re-stored sections While hydrogenotrophic genera stronglydominated both there was a shift from Methanoregula-dominated communities in the undisturbed sections tostrongly Methanobacterium-dominated communities in therestored sections Based on our prediction of a higher nutrientstatus in the restored site we would have expected the oppo-site trend in Methanoregula dominance since Methanomi-crobiales (the order containing Methanoregula) have beenobserved as preferring nutrient-rich sites (Godin et al 2012)their dominance is further indication that the restored sec-tion is not as high in nutrients as we expected In contrast tothe hydrogenotrophs the acetoclastic methanogens did notshow genus-level differences from undisturbed to restoredzones but rather from inundated (Mat-S and Tamarack-S)to intermittently flooded (Shrubs Res-N and Res-S) onesWhen acetoclastic methanogens were present Methanosaeta

dominated their community consistent with observations ofMethanosaeta in nutrient-poor acidic sites (Godin et al2012) However in the inundated zones Methanosarcinawas also present This is actually the opposite pattern wewould have expected based purely on likely oxygen concen-trations as Methanosaeta typically dominates anaerobic en-vironments while Methanosarcina can produce methane un-der partially oxic conditions (Angel et al 2011) We there-fore interpret Methanosaetarsquos presence in FSL-S and TMW-Sto arise from its greater metabolic versatility ndash in addition toacetate it can also use CO2 or methylated compounds (Liuand Whitman 2008) ndash and thus conclude that these sites mayhave distinct substrate profiles

Methanotrophic lineages like methanogens were at thehighest relative abundances in the undisturbed inundatedsites where they primarily occurred near the peat surfaceThe higher abundance of methanotrophs in inundated zonesmay be related to the presence of Sphagnum mosses in thesezones as methanotrophs are a common abundant memberof the Sphagnum microbiome (Dedysh 2011 Kostka et al2016) the DNA extraction method may have accessed mi-crobiota on and within the moss as well as from the bulk peatAlternatively the higher methanotrophs in the inundated sec-tions may have been in the bulk peat and may simply be dueto the higher supply of methane in those areas

46 Microbiota drive CH4 transfer velocity

While methanogens control the production of CH4 throughthe peat column methanotrophs interact with plants andphysical processes to mediate the portion of produced CH4that is oxidized before being emitted to atmosphere Wetherefore examined the relationship between resident CH4cyclers and the CH4 transfer velocity in the top stratigraphiclayer of the peat Generally when the water level is near thesurface CH4 diffuses directly from the surface pore water tothe overlying air and can also be transported via plant tis-sue However at our site we measured no significant CH4transport through vascular plants (see Sect 42) Thereforethe transport pathway at the upper layers of the soil in allzones (except Water) should occur through the ubiquitousSphagnum mat and thus have similar resistance throughoutthe site We also found no significant correlation betweenCH4 pore-water concentration at the top soil layers and sur-face CH4 flux (Fig 7a) Thus with all zones expected to besimilar in their physical transport processes observed differ-ences in CH4 transfer velocity among zones should repre-sent differences in microbial processes Indeed we found asignificant correlation between CH4 transfer velocity and theratio of total methanogens to total methanotrophs (r2

= 033p = 003 based on the relative abundances of lineages ineach functional guild see Methods Fig 9) A related re-sult was reported in a rice paddy system where the ratioof the gene expression of the two diagnostic marker genesfor methanogenesis and methanotrophy mcrA and pmoA in

Figure 9 Relationship between the ratio of the relative abundanceof methanogenicndashmethanotrophic lineages (MgenMtroph) and theCH4 transfer velocity in the top stratigraphic layer of the peat pro-file 0ndash67 cm for Mat and 0ndash125 cm for the other zones CH4 trans-fer velocity was calculated as the average for the 3 months prior tocoring during which the water level was within or above the topstratigraphic layer

the upper 10 cm of the soil was highly correlated to CH4flux (Lee et al 2014) However in our site this correla-tion was not significant when using CH4 flux data alone(r2= 001 p = 075) or pore-water data alone (r2

= 003p = 057) It is intriguing that despite the fact that presencedoes not necessarily imply activity and relative abundancesdo not represent absolute abundances in our study we seethis relationship between the 16S rRNA gene amplicons ofknown methanogenic and methanotrophic lineages and theCH4 fluxes in both undisturbed and restored peatlands Thisresult illustrates the utility of examining microbiota to ex-plain differences between CH4 production and emissions tothe atmosphere

5 Conclusions

Flatiron Lake Bog had high rates of CH4 emission thatincluded several extreme fluxes from the Tamarack mixedwoodland zone that were not driven by ebullition CH4 emis-sions decreased with distance from the center of the bogfrom regularly wetted sections to those that had higher water-level fluctuations Pore-water concentrations followed a sim-ilar pattern of increase with depth except for the Mat zonewhich is adjacent to the open water and thus has bettervertical mixing Longer dry periods in the Shrubs and Res

zone likely inhibited methanogens lowering their abundanceand thus decreasing CH4 accumulation in the pore waterand associated emissions Although pore-water chemistryexplained some of the variation in pore-water CH4 concen-tration water level explained the largest component of vari-ation in CH4 fluxes due to its effects on methanogenesis andmethanotrophy at the top soil levels Given that plants werenot an appreciable pathway of CH4 flux the reported dif-ferences in CH4 transfer velocity when the water level washigh were explained by the ratio of the relative abundance ofmethanogens to methanotrophs in the top layer

Why would two locations with similar near-surface CH4concentrations have different fluxes if they also have simi-lar diffusivities and negligible ebullition and plant transportOur results show that the answer is that they have differenttransfer velocities for CH4 Transfer velocities are normallya function of wind speed but beneath the shrub and treecanopy of peat bogs wind speeds are very low so somethingelse is affecting this transfer velocity The upper layer of thebogrsquos peat mass is a dynamic region with both methanotrophsand methanogens living within the oxic layer (Angle et al2017) Within this layer higher abundance of methanogensdrives higher transfer velocities if the concentration of CH4is assumed to be at a quasi-steady state At the same timehowever methanotrophs consume much of the methane pro-duced Therefore methanogen abundance when normalizedby methanotroph abundance can explain CH4 transfer veloc-ity differences in a peat bog where diffusive transport frompore water in saturated layers is dominant We conclude thatmicrobial communities and their control by variation in wa-ter table depth are the key drivers of variability in CH4 fluxesacross multiple hydro-biological zones in kettle-hole peatbogs Future research should examine whether such patternscan be confirmed in other ecosystems where plant-mediatedtransport of CH4 is low

Code and data availability The data and the code used in this pa-per are available upon request

Appendix A

Table A1 Subset of amplicon-based lineages identified as genera of known methanogens and methanotrophs The genera found in the studyare shown in bold letters

Methanogens Methanotrophs

Methanobacterium MethylocystisMethanobrevibacter MethylosinusMethanocalculus MethylocellaMethanocaldococcus MethylocapsaMethanocella MethyloferulaMethanococcoides MethylococcusMethanococcus MethylocaldumMethanocorpusculum MethylomicrobiumMethanoculleus MethylosphaeraMethanofollis MethylomonasMethanogenium MethylobacterMethanohalobium MethylosarcinaMethanohalophilus MethylothermusMethanolacinia MethylohalobiusMethanolineaMethanolobusMethanomassiliicoccusMethanomethylovoransMethanomicrobiumMethanomicrococcusMethanoplanusMethanopyrusMethanoregulaMethanosaetaMethanosalsumMethanosarcinaMethanosphaeraMethanosphaerulaMethanospirillumMethanothermobacterMethanothermococcusMethanothermusMethanotorrisMethermicoccusMethanoflorensMethanomassilliicoccusMethanospaerulaMethanospirillumMethanothrix

Table A2 Water chemistry of the pore water in the eight locations of the study The means (SD) are averages of four measurements takenthroughout the growing season of 2017 Asterisks indicate means that are significantly higher than at least one other mean

Variable Mat-N Mat-S Tam-N Tam-S Shrubs Lagg Res-N Res-S

NH4 (mgLminus1) 053 (024) 047 (009) 35 (075) 285 (013) 122 (042) 054 (055) 162 (165) 136 (017)NO3 (mgLminus1) 006 (003) 003 (001) 008 (004) 003 (0) 008 (009) 004 (001) 007 (008) 005 (003)pH 41 (036) 47 (043) 426 (019) 488 (05) 475 (058) 432 (03) 538 (082) 442 (042)EC (dSmminus1) 004 (0) 004 (0) 008 (0) 008 (003) 006 (0) 007 (002) 009 (004) 008 (001)Al (mgLminus1) 057 (007) 047 (007) 064 (008) 018 (007) 027 (011) 107 (028) 034 (025) 079 (035)Ca (mgLminus1) 31 (036) 315 (103) 44 (062) 146 (05) 255 (065) 452 (117) 439 (145) 416 (159)Fe (mgLminus1) 132 (014) 128 (016) 142 (013) 076 (067) 146 (091) 201 (078) 097 (059) 082 (027)K (mgLminus1) 156 (027) 205 (051) 238 (045) 242 (028) 238 (025) 941 (1083) 206 (062) 929 (1263)Mg (mgLminus1) 091 (009) 085 (01) 138 (011) 053 (011) 091 (008) 124 (027) 109 (044) 089 (027)Mn (mgLminus1) 005 (0) 005 (0) 011 (001) 004 (001) 007 (001) 009 (003) 01 (001) 01 (003)Na (mgLminus1) 107 (033) 11 (031) 155 (021) 169 (028) 155 (017) 2 (077) 25 (164) 209 (034)P (mgLminus1) 007 (002) 004 (001) 016 (004) 004 (002) 006 (006) 01 (006) 007 (005) 033 (016)S (mgLminus1) 184 (043) 164 (027) 495 (047) 171 (037) 192 (043) 231 (053) 237 (128) 282 (059)Zn (mgLminus1) 012 (007) 023 (02) 026 (032) 406 (776) 47 (461) 031 (021) 1138 (1257) 404 (603)

Level of significance p lt 005

Appendix B

Figure B1 Principal component analysis of the 14 variables listed in Table A2

Figure B2 Chamber measurement during the September hotspot in the Tam-N location Note the steady increase in concentration thatindicates that ebullition was not the reason for the high magnitude of the flux at this location

Figure B3 Vertical profiles of CH4 and CO2 pore-water concentrations (a b) and the resulting CH4 CO2 ratios (c)

Author contributions CRS GB and GMD designed the experi-ments CRS JS RGA and YH conducted field and laboratory ob-servations VIR and YFL generated the microbial analyses CRSprepared the paper with contributions from all co-authors

Competing interests The authors declare that they have no conflictof interest

Acknowledgements We thank Bryan Cassidy Dominique HadadAnna Thompson Julio Quevedo Austin Rechner andAlexa Baratucci for their assistance in the field in 2017 andTasmina Uddin Tim Becker Charles Davis Jorge Villa There-sia Yasbeck Taylor Stephen Yang Ju and Cassandra Rey fortheir assistance in the field in 2018 We thank Julian Deventer forinsights on the analysis of the data We also thank Karen Seidel andThe Nature Conservancy for granting access to the site

Financial support This research has been supported by the OhioState University Presidential Fellowship to Camilo Rey-Sanchezthe Ohio Water Resources Center (grant no G16AP00076) and theOhio Agricultural Research and Development Center Ohio StateUniversity (grant no SEEDS 2016-055)

Review statement This paper was edited by Tina Treude and re-viewed by two anonymous referees

References

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Apprill A McNally S Parsons R and Weber L Minor revi-sion to V4 region SSU rRNA 806R gene primer greatly increasesdetection of SAR11 bacterioplankton Aquat Microb Ecol 75129ndash137 httpsdoiorg103354ame01753 2015

Basiliko N Blodau C Roehm C Bengtson P and Moore TR Regulation of decomposition and methane dynamics acrossnatural commercially mined and restored northern peatlandsEcosystems 10 1148ndash1165 httpsdoiorg101007s10021-007-9083-2 2007

Basiliko N Henry K Gupta V Moore T R Driscoll B Tand Dunfield P F Controls on bacterial and archaeal commu-nity structure and greenhouse gas production in natural minedand restored Canadian peatlands Front Microbiol 4 215httpsdoiorg103389fmicb201300215 2013

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Chu H S Chen J Q Gottgens J F Ouyang Z T John RCzajkowski K and Becker R Net ecosystem methane andcarbon dioxide exchanges in a Lake Erie coastal marsh anda nearby cropland J Geophys Res-Biogeo 119 722ndash740httpsdoiorg1010022013jg002520 2014

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Colwell S R Characterization of UplandWetland CommunityTypes Changes to Flatiron Lake Bog over a 24-Year PeriodThe Ohio State University available at httpsetdohiolinkedupg_100NO10P10_ETD_SUBID68741 (last access 23 Au-gust 2019) 2009

Crill P M Bartlett K B Harriss R C Gorham E Verry ES Sebacherl D I Madsar L and Sanner W Methane flux

from minnesota peatlands Glob Biogeochem Cy 2 371ndash384httpsdoiorg101029GB002i004p00371 1988

Dean J F Middelburg J J Roumlckmann T Aerts R BlauwL G Egger M Jetten M S M Jong A E E deMeisel O H Rasigraf O Slomp C P inrsquot Zandt M Hand Dolman A J Methane Feedbacks to the Global Cli-mate System in a Warmer World Rev Geophys 56 207ndash250httpsdoiorg1010022017RG000559 2018

Dedysh S N Cultivating Uncultured Bacteria from Northern Wet-lands Knowledge Gained and Remaining Gaps Front Micro-biol 2 184 httpsdoiorg103389fmicb201100184 2011

Dise N B Methane emission from minnesota peatlands ndash spa-tial and seasonal variability Glob Biogeochem Cy 7 123ndash142httpsdoiorg10102992gb02299 1993

Glatzel S Basiliko N and Moore T Carbon dioxideand methane production potentials of peats from natu-ral harvested and restored sites eastern Quebec CanadaWetlands 24 261ndash267 httpsdoiorg1016720277-5212(2004)024[0261cdampp]20co2 2004

Godin A McLaughlin J W Webster K L Packalen M andBasiliko N Methane and methanogen community dynamicsacross a boreal peatland nutrient gradient Soil Biol Biochem48 96ndash105 httpsdoiorg101016jsoilbio201201018 2012

Greenup A L Bradford M A McNamara N P Ineson Pand Lee J A The role of Eriophorum vaginatum in CH4flux from an ombrotrophic peatland Plant Soil 227 265ndash272httpsdoiorg101023a1026573727311 2000

Hatala J A Detto M and Baldocchi D D Gross ecosys-tem photosynthesis causes a diurnal pattern in methaneemission from rice Geophys Res Lett 39 L06409httpsdoiorg1010292012gl051303 2012

Holgerson M A Farr E R and Raymond P A Gas transfer ve-locities in small forested ponds J Geophys Res-Biogeo 1221011ndash1021 httpsdoiorg1010022016JG003734 2017

Hoyos-Santillan J Lomax B H Large D Turner B L BoomA Lopez O R and Sjogersten S Quality not quantityOrganic matter composition controls of CO2 and CH4 fluxesin neotropical peat profiles Soil Biol Biochem 103 86ndash96httpsdoiorg101016jsoilbio201608017 2016

Kelly C A Dise N B and Martens C S Temporal variationsin the stable carbon isotopic composmon of methane emittedfrom minnesota peatlands Glob Biogeochem Cy 6 263ndash269httpsdoiorg10102992gb01478 1992

Kettunen A Connecting methane fluxes to vegetationcover and water table fluctuations at microsite levelA modeling study Glob Biogeochem Cy 17 1051httpsdoiorg1010292002gb001958 2003

Kim J Verma S B and Billesbach D P Seasonal variationin methane emission from a temperate Phragmites-dominatedmarsh effect of growth stage and plant-mediated transportGlob Change Biol 5 433ndash440 httpsdoiorg101046j1365-2486199900237x 1999

Kim S Y Lee S H Freeman C Fenner N and KangH Comparative analysis of soil microbial communitiesand their responses to the short-term drought in bog fenand riparian wetlands Soil Biol Biochem 40 2874ndash2880httpsdoiorg101016jsoilbio200808004 2008

Kirschke S Bousquet P Ciais P Saunois M Canadell J GDlugokencky E J Bergamaschi P Bergmann D Blake D

R Bruhwiler L Cameron-Smith P Castaldi S ChevallierF Feng L Fraser A Heimann M Hodson E L Houwel-ing S Josse B Fraser P J Krummel P B Lamarque JF Langenfelds R L Le Quere C Naik V OrsquoDoherty SPalmer P I Pison I Plummer D Poulter B Prinn R GRigby M Ringeval B Santini M Schmidt M Shindell DT Simpson I J Spahni R Steele L P Strode S A SudoK Szopa S van der Werf G R Voulgarakis A van WeeleM Weiss R F Williams J E and Zeng G Three decadesof global methane sources and sinks Nat Geosci 6 813ndash823httpsdoiorg101038ngeo1955 2013

Kostka J E Weston D J Glass J B Lilleskov E A ShawA J and Turetsky M R The Sphagnum microbiome new in-sights from an ancient plant lineage New Phytol 211 57ndash64httpsdoiorg101111nph13993 2016

Kotsyurbenko O R Chin K J Glagolev M V Stub-ner S Simankova M V Nozhevnikova A N andConrad R Acetoclastic and hydrogenotrophic methaneproduction and methanogenic populations in an acidicWest-Siberian peat bog Environ Microbiol 6 1159ndash1173httpsdoiorg101111j1462-2920200400634x 2004

Kuznetsova A Brockhoff P B and Christensen R H BlmerTest Package Tests in Linear Mixed Effects Models J StatSoftw 82 1ndash26 httpsdoiorg1018637jssv082i13 2017

Lai D Y F Methane Dynamics in Northern Peatlands A ReviewPedosphere 19 409ndash421 2009

Lai D Y F Moore T R and Roulet N T Spatial and tem-poral variations of methane flux measured by autochambers ina temperate ombrotrophic peatland J Geophys Res-Biogeo119 864ndash880 httpsdoiorg1010022013jg002410 2014

Lansdown J M Quay P D and King S L CH4 produc-tion via CO2 reduction in a temperate bog A source of 13C-depIeted CH4 Geochim Cosmochim Ac 56 3493ndash3503httpsdoiorg1010160016-7037(92)90393-W 1992

Lee H J Kim S Y Kim P J Madsen E L andJeon C O Methane emission and dynamics of methan-otrophic and methanogenic communities in a flooded ricefield ecosystem FEMS Microbiol Ecol 88 195ndash212httpsdoiorg1011111574-694112282 2014

Le Mer J and Roger P Production oxidation emission and con-sumption of methane by soils A review Eur J Soil Biol 3725ndash50 httpsdoiorg101016s1164-5563(01)01067-6 2001

Lenth R Singmann H Love J Buerkner P and Herve M em-means Estimated Marginal Means aka Least-Squares Meansavailable at httpsCRANR-projectorgpackage=emmeanslast access 24 December 2018

Liu Y C and Whitman W B Metabolic phylogenetic and eco-logical diversity of the methanogenic archaea in IncredibleAnaerobes From Physiology to Genomics to Fuels vol 1125edited by Wiegel J Maier R J and Adams M W W pp171ndash189 2008

MacDonald L H Paull J S and Jaffe P R Enhanced semiper-manent dialysis samplers for long-term environmental monitor-ing in saturated sediments Environ Monit Assess 185 3613ndash3624 httpsdoiorg101007s10661-012-2813-8 2013

Malhotra A Roulet N T Wilson P Giroux-Bougard Xand Harris L I Ecohydrological feedbacks in peatlandsan empirical test of the relationship among vegetation mi-

crotopography and water table Ecohydrology 9 1346ndash1357httpsdoiorg101002eco1731 2016

McCalley C K Woodcroft B J Hodgkins S B Wehr R AKim E-H Mondav R Crill P M Chanton J P Rich V ITyson G W and Saleska S R Methane dynamics regulated bymicrobial community response to permafrost thaw Nature 514478ndash481 httpsdoiorg101038nature13798 2014

Moore P D The future of cool temperate bogs Environ Conserv29 3ndash20 httpsdoiorg101017s0376892902000024 2002

Moore T R and Dalva M The influence of temperature andwater-table position on carbon-dioxide and methane emissionsfrom laboratory columns of peatland soils J Soil Sci 44 651ndash664 1993

Morin T H Bohrer G Naor-Azrieli L Mesi S Kenny W TMitsch W J and Schaefer K V R The seasonal and diurnaldynamics of methane flux at a created urban wetland Ecol Eng72 74ndash83 httpsdoiorg101016jecoleng201402002 2014

Morin T H Bohrer G Stefanik K C Rey-Sanchez AC Matheny A M and Mitsch W J Combining eddy-covariance and chamber measurements to determine themethane budget from a small heterogeneous urban flood-plain wetland park Agric Forest Meteorol 237 160ndash170httpsdoiorg101016jagrformet201701022 2017

Nadeau D F Rousseau A N Coursolle C Margolis HA and Parlange M B Summer methane fluxes froma boreal bog in northern Quebec Canada using eddycovariance measurements Atmos Environ 81 464ndash474httpsdoiorg101016jatmosenv201309044 2013

Nahlik A M and Mitsch W J Methane EmissionsFrom Created Riverine Wetlands Wetlands 30 783ndash793httpsdoiorg101007s13157-010-0038-6 2010

Nelson M C Morrison H G Benjamino J Grim S L andGraf J Analysis Optimization and Verification of Illumina-Generated 16S rRNA Gene Amplicon Surveys PLOS ONE 9e94249 httpsdoiorg101371journalpone0094249 2014

Oleszczuk R and Truba M The analysis of some phys-ical properties of drained peat-moorsh soil layers AnnWars Univ Life Sci 00 SGGW Land Reclam 45 41ndash48httpsdoiorg102478sggw-2013-0004 2013

Pangala S R Moore S Hornibrook E R C and GauciV Trees are major conduits for methane egress fromtropical forested wetlands New Phytol 197 524ndash531httpsdoiorg101111nph12031 2013

Parada A E Needham D M and Fuhrman J A Everybase matters assessing small subunit rRNA primers for ma-rine microbiomes with mock communities time series andglobal field samples Environ Microbiol 18 1403ndash1414httpsdoiorg1011111462-292013023 2016

Pugh C A Reed D E Desai A R and Sulman B NWetland flux controls how does interacting water table lev-els and temperature influence carbon dioxide and methanefluxes in northern Wisconsin Biogeochemistry 137 15ndash25httpsdoiorg101007s10533-017-0414-x 2018

Raghoebarsing A A Smolders A J P Schmid M C Rijp-stra W I C Wolters-Arts M Derksen J Jetten M S MSchouten S Damste J S S Lamers L P M Roelofs J GM den Camp H and Strous M Methanotrophic symbiontsprovide carbon for photosynthesis in peat bogs Nature 4361153ndash1156 httpsdoiorg101038nature03802 2005

R Development Core Team R A language and environment for sta-tistical computing available at httpwwwR-projectorg (lastaccess 7 January 2019) 2018

Rey-Sanchez A C Morin T H Stefanik K C Wrighton Kand Bohrer G Determining total emissions and environmentaldrivers of methane flux in a Lake Erie estuarine marsh EcolEng 114 7ndash15 httpsdoiorg101016jecoleng2017060422018

Schilder J Bastviken D Hardenbroek M and van and HeiriO Spatiotemporal patterns in methane flux and gas transfervelocity at low wind speeds Implications for upscaling stud-ies on small lakes J Geophys Res-Biogeo 121 1456ndash1467httpsdoiorg1010022016JG003346 2016

Schneider C A Rasband W S and Eliceiri K W NIH Image toImageJ 25 years of image analysis Nat Methods 9 671ndash675httpsdoiorg101038nmeth2089 2012

Segers R Methane production and methane consumption a re-view of processes underlying wetland methane fluxes Biogeo-chemistry 41 23ndash51 httpsdoiorg101023a10059290327641998

Sha C Mitsch W J Mander U Lu J J Batson JZhang L and He W S Methane emissions fromfreshwater riverine wetlands Ecol Eng 37 16ndash24httpsdoiorg101016jecoleng201007022 2011

Shannon R D and White J R 3-year study of controls onmethane emissions from 2 Michigan peatlands Biogeochem-istry 27 35ndash60 1994

Smemo K A and Yavitt J B Anaerobic oxidation of methane anunderappreciated aspect of methane cycling in peatland ecosys-tems Biogeosciences 8 779ndash793 httpsdoiorg105194bg-8-779-2011 2011

Strack M and Zuback Y C A Annual carbon balance of a peat-land 10 yr following restoration Biogeosciences 10 2885ndash2896httpsdoiorg105194bg-10-2885-2013 2013

Sundqvist E Crill P Molder M Vestin P and Lindroth AAtmospheric methane removal by boreal plants Geophys ResLett 39 L21806 httpsdoiorg1010292012gl053592 2012

Treat C C Bubier J L Varner R K and Crill P M Timescaledependence of environmental and plant-mediated controls onCH4 flux in a temperate fen J Geophys Res-Biogeo 112G01014 httpsdoiorg1010292006jg000210 2007

Turetsky M R Kotowska A Bubier J Dise N B CrillP Hornibrook E R C Minkkinen K Moore T RMyers-Smith I H Nykanen H Olefeldt D Rinne JSaarnio S Shurpali N Tuittila E S Waddington J MWhite J R Wickland K P and Wilmking M A syn-thesis of methane emissions from 71 northern temperateand subtropical wetlands Glob Change Biol 20 2183ndash2197httpsdoiorg101111gcb12580 2014

Updegraff K Pastor J Bridgham S D and Johnston C AEnvironmental and substrate controls over carbon and nitrogenmineralization in northern wetlands Ecol Appl 5 151ndash163httpsdoiorg1023071942060 1995

US EPA O EPA Method 3501 Determination of Ammonia Ni-trogen by Semi-Automated Colorimetry US EPA available athttpswwwepagovhomeland-security-researchepa-method-3501-determination-ammonia-nitrogen-semi-automated-colorimetry (last access 5 March 2019) 2015a

US EPA O SW-846 Test Method 6010D Inductively Cou-pled Plasma-Optical Emission Spectrometry (ICP-OES) USEPA available at httpswwwepagovhw-sw846sw-846-test-method-6010d-inductively-coupled-plasma-optical-emission-spectrometry-icp-oes (last access 5 March 2019) 2015b

Van der Nat F Middelburg J J Van Meteren D and Wiele-makers A Diel methane emission patterns from Scirpus la-custris and Phragmites australis Biogeochemistry 41 1ndash22httpsdoiorg101023a1005933100905 1998

Vitt D H and Slack N G An analysis of the veg-etation of Sphagnum-dominated kettle-hole bogs in rela-tion to environmental gradients Can J Bot 53 332ndash359httpsdoiorg101139b75-042 1975

Waddington J M and Day S M Methane emissions from a peat-land following restoration J Geophys Res-Biogeo 112 112httpsdoiorg1010292007jg000400 2007

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Wang Z P Delaune R D Masscheleyn P H and Patrick WH Soil redox and ph effects on methane production in a floodedrice soil Soil Sci Soc Am J 57 382ndash385 1993

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White J R Shannon R D Weltzin J F Pastor J andBridgham S D Effects of soil warming and drying on methanecycling in a northern peatland mesocosm study J Geophys Res-Biogeo 113 G00A06 httpsdoiorg1010292007jg0006092008

Whiting G J and Chanton J P Plant-dependent CH4 emissionin a subarctic canadian fen Glob Biogeochem Cy 6 225ndash231httpsdoiorg101029926b00710 1992

Abstract

Introduction

Methods

Study site

Experimental design

Surface CH4 flux chamber measurements

CH4 flux from plants

Upscaling of CH4 fluxes

Vertical profiles of CH4 pore-water concentration and methane transfer velocity

Core sampling DNA extraction and 16S rRNA amplicon sequencing and analysis

Ancillary measurements

Data analysis

Results

Inter- and intra-annual variation in abiotic conditions

The effect of different hydro-biological zones and water level on CH4 emissions

Temporal variations in CH4 fluxes

Plants fluxes and upscaling of CH4 emissions

Dissolved CH4 pore-water concentrations and methane transfer velocity

Both methanogens and methanotrophs were more abundant in permanently wetted zones

Discussion

The CH4 budget and its heterogeneity among hydro-biological zones

The role of plants in the CH4 cycle in peat bogs

Fluctuations in water level explain variability in CH4 emissions

Pore-water CH4 concentrations were higher in the undisturbed section

Methane-cycler abundance depends on vegetation zone and water level

Microbiota drive CH4 transfer velocity

Conclusions

Code and data availability

Appendix A

Appendix B

Author contributions

Competing interests

Acknowledgements

Financial support

Review statement

References

1 Introduction

Methane (CH4) fluxes from natural and anthropogenicsources play a significant role in determining atmosphericclimate forcing (Ciais et al 2013) Changes to CH4 fluxesfrom natural systems are of significant concern due to theirpotential to drive positive feedback cycles in the global cli-mate system (Bridgham et al 2013 Dean et al 2018) Nat-ural wetlands emit approximately 30 of all the methane(CH4) released into the atmosphere (Kirschke et al 2013)yet the uncertainty around wetland CH4 flux is the highestof all the components of the global CH4 budget (Kirschke etal 2013) This uncertainty partly arises from the complex-ity of physical and biological interactions that result in theproduction and oxidation of CH4 and its eventual release tothe atmosphere (Lai 2009) Generally water level (WL) isthe most important driver of CH4 emissions from wetlandsand especially peatlands as its position in the soil or peatprofile defines the boundary between anaerobic CH4 produc-tion (methanogenesis) in the catotelm (ie the lower anoxicportion of the peat) and aerobic CH4 oxidation (methanotro-phy) in the acrotelm (the upper oxic peat Kettunen 2003White et al 2008) However a plethora of environmentalvariables can also influence CH4 fluxes in peatlands includ-ing temperature (Bohn et al 2007 Kim et al 1999 Segers1998) peat origin (eg Sphagnum woody peat and fen andreed peat Bridgham and Richardson 1992) degree of humi-fication (Glatzel et al 2004) availability of labile carbon inthe peat (Updegraff et al 1995) concentrations of ligninlong-chain fatty acids and polysaccharides along the peatprofile (Hoyos-Santillan et al 2016) phosphorous contentwhich regulates anaerobic decomposition of organic matter(Basiliko et al 2007) the abundance of other electron ac-ceptors especially Fe (Chamberlain et al 2018) and pHas methanogens occur at greater abundances in neutral toslightly alkaline conditions (Wang et al 1993) It is also im-portant to be cognisant of reports of CH4 production in aer-obic soil (Angle et al 2017) and an increased awareness ofthe importance of anaerobic oxidation of CH4 (Smemo andYavitt 2011)

The microbiota of a site can have complex interactionswith WL and other physical conditions which result in vari-able CH4 fluxes Despite the increasingly complex pictureemerging of peatland CH4 cycling it has been estimatedthat methanotrophy can oxidize 60 ndash90 of the CH4 pro-duced in wetlands before it can escape to the atmosphere (LeMer and Roger 2001) Research has also shown that wa-ter table drawdowns reduce the abundance of methanogens(Kim et al 2008) and that changes in ecosystem vegetationand structure can affect microbial community compositionand in turn the CH4 biochemistry of wetlands (McCalley etal 2014) Generally peat bogs are nutrient-poor sites domi-nated by hydrogenotrophic methanogenesis but when distur-bance occurs a change from hydrogenotrophic to acetoclas-tic methanogenesis can occur due to an increase in pH and

nutrients (Kelly et al 1992 Kim et al 2008 Kotsyurbenkoet al 2004)

Kettle-hole peat bogs are peatlands created by the accu-mulation of peat in areas previously occupied by kettle lakesKettle-hole peat bogs which are frequently found in east-ern North America (Cai and Yu 2011 Moore 2002) oftenconsist of water bodies surrounded by different vegetationzones Closest to the open water there is often a mat of float-ing vegetation followed by concentrically organized vege-tation zones that ultimately support shrubs and trees (Vittand Slack 1975) This vegetation heterogeneity can be animportant driver of CH4 fluxes (Lai et al 2014) particu-larly in ombrotrophic peat bogs where vegetation commu-nities and water levels are strongly associated (Malhotra etal 2016) Measurements of CH4 flux in different vegeta-tion zones are important in understanding site-level flux esti-mates at the bog scale that are affected by the relative coverand arrangement of different vegetation zones (Nadeau et al2013) Most importantly a better understanding of the bio-logical chemical and physical processes controlling fluxesat these low resolutions is necessary to scale up CH4 fluxesat the ecosystem level (Bridgham et al 2013) The objec-tives of this study were to (1) calculate the growing-seasonCH4 budget of a kettle-hole peat bog in Ohio by upscalingflux measurements from different vegetation zones (2) quan-tify the effects of biotic and abiotic controls on below-groundvertical profiles of CH4 pore-water concentration and relatedfluxes and (3) determine the links between microbial com-munity structure and associated CH4 dynamics Brief com-parisons of CH4 dynamics between restored and undisturbedsection are discussed but not in detail as the evaluation ofthe effect of restoration on CH4 fluxes is not the objective ofthis paper

2 Methods

21 Study site

We studied Flatiron Lake Bog a ca 144 ha kettle-holepeat bog located in northeastern Ohio (4102prime4067primeprime N8121prime5981primeprimeW Fig 1) The site is a state nature pre-serve and has been owned by The Nature Conservancy(TNC) since 1984 The greater part of the site typifies thecharacteristic abiotic and biotic zonation found in simi-lar sites throughout eastern North America A small area(ca 1120 m2) of open water (Water) is located at the cen-ter of the site and is surrounded by a series of concentri-cally organized vegetation zones The vegetation commu-nity of the site including the bog vegetation and uplandzones was described in detail by Colwell (2009) The clos-est zone to the open water hereafter called the Sphagnum-leatherleaf mat (Mat) consists of a floating mat of Sphag-num fallax (H Klinggr) with abundant cover of swamploosestrife (Decodon verticillatus (L) Elliot) and leather-

Ceq =rP

KH (2)

Cw = [CH4]8 (3)

k =FCH4

CwminusCeq (4)

29 Data analysis

3 Results

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Ceq =rP

KH (2)

Cw = [CH4]8 (3)

k =FCH4

CwminusCeq (4)

29 Data analysis

3 Results

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Ceq =rP

KH (2)

Cw = [CH4]8 (3)

k =FCH4

CwminusCeq (4)

29 Data analysis

3 Results

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Ceq =rP

KH (2)

Cw = [CH4]8 (3)

k =FCH4

CwminusCeq (4)

29 Data analysis

3 Results

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Ceq =rP

KH (2)

Cw = [CH4]8 (3)

k =FCH4

CwminusCeq (4)

29 Data analysis

3 Results

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

29 Data analysis

3 Results

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

3 Results

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Water 1119 619 1226 3492 2107(01ndash1823) (245) (4025) (1698)

Mat 927 395 825 1541 832(minus122ndash753) (207) (869) (485)

Res 23 430 07 215 303 188(minus114ndash2799) (818) (508) (275)

Total 125 592 na na 3154b 3623b

(166) (687)

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

= 079p = 003)

4 Discussion

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

5 Conclusions

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Appendix A

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Appendix B

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

Results







Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Appendix B

References

Abstract

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Methods

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Data analysis

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Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

References

Abstract

Introduction

Methods

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Data analysis

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Discussion







Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

References

Abstract

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Methods

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Data analysis

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Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Abstract

Introduction

Methods

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Data analysis

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Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Abstract

Introduction

Methods

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Data analysis

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Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

Abstract

Introduction

Methods

Study site

Experimental design







Data analysis

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Conclusions


Appendix A

Appendix B


Competing interests

Acknowledgements

Financial support

Review statement

References

The ratio of methanogens to methanotrophs and water-level ... · Tamarack zone, close to saturation, and the lowest values in the restored zone. While the CH4 ﬂuxes and pore-water

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