anaerobic oxidation of methane in northern peatlands · 2012. 11. 1. · 4.1.3 anaerobic ch 4...

Anaerobic Oxidation of Methane in Northern Peatlands

by

Mr. Varun Gupta

A thesis submitted in conformity with the requirements for the degree of Master of Science

Department of Geography University of Toronto

© Copyright by Varun Gupta, 2011

ii

Anaerobic Oxidation of Methane in Northern Peatlands

Varun Gupta

Master of Science

Department of Geography

University of Toronto

2011

Abstract

Anaerobic oxidation of methane (AOM) in peatlands was investigated using 13

carbon isotope

tracers. Existence of AOM in marine and freshwater ecosystems is well known, but only recently

has solid evidence for this process been demonstrated in northern peat accumulating wetland

ecosystems. The primary objective of this thesis research was to characterize rates of AOM in

peatlands across site types (bogs and fens with varying physicochemical properties) and

latitudinal gradients. It was found that AOM was ubiquitous process across North American sites

and dominant in fens over bogs, however carbon derived from methane was similar in both types

of peatlands. None of the proposed electron acceptors hypothesized to support AOM stimulated

AOM. AOM had a combined, average rate of 2.9 nmol CH4 kg-1

s-1

, which would translate to an

approximate global consumption of 24 Tg CH4 annually. This mass of CH4 is equivalent to

almost 7% of all annual anthropogenic CO2 emissions.

iii

Acknowledgments

I would like to thank Dr. Nathan Basiliko, my thesis supervisor for providing me guidance,

support and encouragement for last 4 years. I would also like to thank Dr. Kurt Smemo and Dr.

Joseph Yavitt for providing their insight into this project.

Many people have helped me throughout my Masters. In particular I thank Carolyn Winsborough

and Derek Przybycien for helping me in the lab, Professor Sasa Stefanovic for use of a

centrifuge, Michael Preston for advice on statistical analyses, and Tom Ulanowski for providing

me information about the vegetation communities at the James Bay Lowland sites. I was

supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) CGS-M

Fellowship and awards from the University of Toronto and the Department of Geography.

Project funding also came from a NSERC Discovery Grant to my research supervisor.

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Table of Contents

Abstract ........................................................................................................................................... ii

Acknowledgments ........................................................................................................................... ii

Table of Contents ........................................................................................................................... iv

List of Tables ................................................................................................................................ vii

List of Figures .............................................................................................................................. viii

Chapter 1 : Introduction and literature review ................................................................................ 1

1.1 General introduction to the thesis ....................................................................................... 1

1.2 An introduction to global wetlands and northern peatland (fen and bog) ecosystems ....... 3

1.3 Methane biogeochemistry of northern peatlands ................................................................ 5

1.4 Anaerobic CH4 oxidation .................................................................................................... 8

1.4.1 Anaerobic oxidation of CH4 in marine ecosystems ................................................ 9

1.4.2 Anaerobic oxidation of CH4 in freshwater ecosystems: Lake sediments ............. 15

1.4.3 Anaerobic oxidation of CH4 in peatlands ............................................................. 17

Chapter 2: Objective and hypothesis ............................................................................................ 19

2.1 Objectives ......................................................................................................................... 19

2.2 Hypothesis ......................................................................................................................... 20

Chapter 3: Methodology ............................................................................................................... 21

3.1 Characterization of AOM across sites .............................................................................. 21

3.1.1 Study sites ............................................................................................................. 21

3.1.2 Sampling procedure .............................................................................................. 29

3.1.3 AOM 13

C tracer incubations ................................................................................. 29

3.1.4 Site chemical analysis ........................................................................................... 32

3.1.5 Calculations and numerical analyses .................................................................... 32

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3.1.6 Statistical analysis ................................................................................................. 35

3.2 Potential electron acceptor addition study ........................................................................ 36

3.2.1 Study site and field sampling ................................................................................ 36

3.2.2 Anaerobic incubations, gas sampling and analysis ............................................... 36

Chapter 4: Results ......................................................................................................................... 38

4.1 Characterization of CH4 dynamics and AOM across sites ............................................... 38

4.1.1 Net CH4 production under 13

CH4 and N2 .............................................................. 38

4.1.2 12

CH4 vs N2 treatments: impacts on fractionation of natural abundance 13

C ....... 41

4.1.3 Anaerobic CH4 oxidation ...................................................................................... 45

4.1.4 Solid phase analysis .............................................................................................. 51

4.1.5 AOM in relation to gross CH4 production ............................................................ 56

4.1.6 Potential chemical/ substrate controls of AOM .................................................... 58

4.2 Potential electron acceptor addition study ........................................................................ 61

4.2.1 Net CH4 production ............................................................................................... 61

4.2.2 Headspace 13

C enrichment and AOM calculations ............................................... 61

Chapter 5: Discussion ................................................................................................................... 64

5.1 Evidence of AOM ............................................................................................................. 64

5.2 Anaerobic CH4 oxidation to CO2 ...................................................................................... 66

5.3 13C assimilation in peat ..................................................................................................... 69

5.4 Potential chemical/substrate control on AOM .................................................................. 72

5.5 Relevance of AOM in peatlands ....................................................................................... 76

Chapter 6: Conclusions and future studies .................................................................................... 78

6.1 Conclusions ....................................................................................................................... 78

6.2 Future studies .................................................................................................................... 79

References ..................................................................................................................................... 81

Appendix 1: Carbonates solutions ................................................................................................ 91

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Appendix 2: Electron acceptor solutions ...................................................................................... 92

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List of Tables

Table 3.1-1: Study sites characteristics…………………………………………………………..25

Table 4.1-1: Summary table for all 15 peatlands. Mean rates (±SD) are shown, where n = 3. NSD

was placed when there were no significant difference (p > 0.05) between N2 and 13

CH4 treatment.

Mclean Bog, Time 20 net AOM rate was not calculated due to the loss of samples. Gross CH4

production rate was calculated by addition of Net CH4 production rate under 20000 ppm, Net

AOM rate and Net 13

C assimilation in solid phase. Study sites are arranged from high pH (fen

type) to low pH (bog). ................................................................................................................... 40

Table 4.1-2: Percent of gross CH4 consumed by AOM (headspace) ............................................ 57

Table 4.1-3: Percent of gross CH4 consumed by AOM and solid phase ...................................... 57

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List of Figures

Figure 3.1-1: Location of fifteen study sites……………………………………………………..24

Figure 4.1-1: Mean methane production rate for bogs (n=18) and fens (n=27) for N2 and 13

CH4

treatments. pH 4.2 was chosen as a indicator to differentiate between bog and fen. Rates are

shown for two treatments, over two intervals, Time 20 (solid black) and Time 40 (solid grey). . 39

Figure 4.1-2: Headspace 13

C atom percent from three treatments, over three time interval (Time

3, 20, 40). N2 addition (red square), 12

CH4 addition (green triangle) and 13

CH4 addition (blue

diamond). Compared to the natural fractionation (N2 treatment), no artificial fractionation of

13CO2 occurred when methane (

12CH4) was added to the headspace. Error bars represents the

standard deviation of triplicate incubations. The small inlet is closer view of two control

treatments. ..................................................................................................................................... 44


CO2 atom percent (AP) and net AOM amount for 15 peatlands over

the three time interval. On the primary y-axis, increase in 13

C AP of CO2 for 13

CH4 addition (blue

diamond) and N2 control addition (red square) were plotted. On the secondary y-axis, net CH4

oxidized (green triangle) via AOM was plotted. Graphs are arranged from high pH (fen type) to

low pH (bog). Error bars for all points are ± SD, where n = 3. Note: 5A` Fen have different y-

axis scale (*). ................................................................................................................................ 50

Figure 4.1-4: Solid phase 13

C assimilation in peat for 9 peatlands. On primary y-axis, 13

C atom

percent were plotted for 13

CH4 (diamond) and N2 additions (square) over two time interval (Time

20 and 40). On secondary y-axis, net 13

C assimilation (triangle) assimilation was plotted. Graphs

are arranged from high pH (fen type) to low pH (bog). Error bars for net CH4 oxidation points (±

SD), where n = 3. Note: Channel Fen, Bog Lake Fen and S1 Bog have different y-axis scale (*).

....................................................................................................................................................... 55

Figure 4.1-5: Time interval vs maximum rate of AOM. Fens and bogs were separated based on

pH. Bogs (gray cone) AOM either peaked at Time 3, or stayed constant, while fens (black cone)

AOM peaked at Time 20/40. ........................................................................................................ 59

Figure 4.1-6: Correlation between average rate of AOM with porewater ion concentration….. . 60

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Figure 4.2-1: CH4 flux (12

C additions) 0 to 25d. Flux values are means in mg CH4 per flask with

7g wet peat or ca. 1g dry peat each. Bars are standard deviations of 3 replicates ........................ 62

Figure 4.2-2: 13

C AP enrichment of incubations amended with addition of electron acceptor (grey

bars). Amount of net CH4 oxidized over 21 days period in these treatment (secondary y-axis,

dashed line), where N2 treatment AP value was assumed as fractionation control for electron

acceptor study. .............................................................................................................................. 63







1

Chapter 1 : Introduction and literature review

1.1 General introduction to the thesis

Methane (CH4) is an important global atmospheric trace greenhouse gas that contributes to the

greenhouse effect and global climate change (IPPC, 2007). Terrestrial and shallow water wetland

sources of CH4 to the atmosphere are the largest, and conceptually, CH4 is produced as a product

of organic matter decomposition under strictly anoxic conditions by archaeal communities when

all the available inorganic electron acceptors (e.g. O2, NO3-, Fe(III), Mn(IV)) are utilized and/or

not biologically available (Valentine, 2002). It is under these situations that carbon dioxide or

organic molecules are utilized by methanogens as electron acceptors, and where the by-product

is CH4 (Valentine, 2002).

In soils and sediments, microbial CH4 oxidation above the water table can potentially greatly

reduce net CH4 emissions; and in certain cases, as much as 100% of all CH4 produced

anaerobically can be oxidized (Bodelier et al., 2005). Aerobic CH4 oxidation in soils and

sediments has been moderately well studied and is known to be carried out by members of two

classes of bacteria in the phylum Proteobacteria and in many wetland soils respond to substrate

availability with first-order kinetics (Hansen and Hansen 1996). However, there have been new

recent discoveries related to CH4 oxidation and methanotrophic microorganisms, including

uncovering of a new bacterial phylum of bacterial methanotrophs (the Verrucomicrobia,

Dunfield et al., 2007), facultative use of non-CH4 redox and C substrates by methanotrophic

bacteria (Dedysh et al., 2005), that archaea might be involved in aerobic C and CH4 cycling in

peatlands (Gupta et al., in press) and that anaerobic oxidation of CH4 (AOM) in wetlands might

represent a key CH4 sink and internal C cycling mechanism in shallow freshwater aquatic

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systems (Raghoebarsing et al., 2006) and in peatlands (Smemo and Yavitt 2007). This thesis

focuses on the latter issue.

Anaerobic oxidation of CH4 has been reported in marine sediments and water column since the

late 1970s (Barnes and Goldberg, 1976; Reeburgh, 1976) and appears to be mediated by a

consortium of microorganisms that includes methanogenic archaea operating “in reverse” and

sulphate reducing bacteria (Hoehler et al., 1994). The process of AOM in marine environments,

although not conclusively yet linked to microorganisms, has been quantified and reported to

remove a substantial portion of CH4 before it would otherwise be emitted to the atmosphere

(Valentine, 2002). Because of the partial known linkage to sulphur (S) reduction and that in

marine environments S is abundant, and cycling between reduced and oxidized forms can be

very rapid, until recently it has been assumed that AOM is only globally relevant in these

systems. However recently in a polluted shallow freshwater system in the Netherlands, AOM

has been reported and linked to denitrification (Raghoebarsing et al., 2006). In peatlands, the

predominant wetland classes by area worldwide, AOM has recently been proven to occur and

linked to reduction of inorganic electron acceptors under anoxic conditions by Smemo and

Yavitt (2007), however this seminal study used indirect techniques for detecting and quantifying

AOM including isotope dilution assays and selective methanogenic antibiotics

(bromoethanesulfonic acid target methyl coenzyme reductase A; Zinder et al., 1984) that have

known limitations, such as incomplete inhibition of methanogens. Direct use of stable isotope

tracers (i.e. 13

CH4) to investigate rates of and controls on AOM in peatlands would represent a

key milestone in our understanding of this process and thus forms the cornerstone of MSc.

research and thesis.

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1.2 An introduction to global wetlands and northern peatland (fen and bog) ecosystems

There are five distinct wetland classes as recognized by The Canadian Wetland Classification

System: namely, bog, fen, marsh, swamp, and shallow open water (Warner and Rubec, 1997).

The Northern peatlands (also called mires) are defined by the presence of organic soils (peat),

consist of bogs and fens and are found notably in Canada, Russia, Finland, Poland, Germany,

and Scotland covering about 3% of global land mass (Gorham, 1991). Canada has about 127.2

million hectares of wetlands, out of which 111.3 hectares is peatland (Environment Canada,

1993).

Peatlands can be classified using five different features, namely topography, hydrology, water

chemistry, nutrition and vegetation (Warner and Rubec, 1997), though fundamentally isolation

from groundwater or connectivity to groundwater defines a bog versus a fen. Minerotrophic

peatlands are neutral pH (5-7) fens that are more typically dominated by herbaceous plants such

as sedges (Warner and Rubec, 1997). Fens are nutrient rich (higher base cation concentrations)

because in addition to atmospheric inputs of water and nutrients, they receive inputs from

groundwater and surface runoff (Warner and Rubec, 1997). Ombrotrophic Peatlands are true

raised bogs that are nutrient-poor, low pH ecosystems, dominated by Sphagnum mosses and

receive water and nutrients from atmospheric inputs only (Warner and Rubec, 1997).

Mesotrophic Peatlands are intermediate between the two, and are sometime called poor fens

(Mitsch and Gosselink, 2000).

Many bogs and fens in North America have formed in old lake basins after the last glaciation,

and peatlands are considered to be a late stage of a “filling-in” process, particularly in temperate

and southern boreal biomes (Mitsch and Gosselink, 2000). However river and stream channels

4

also can contain peatlands, and thereby would technically be classified as fens. Permafrost also

serves as an impervious basin in many northern boreal, sub-arctic, and arctic peatlands, and there

have been a number of studies that have shown that the ecology and biogeochemistry of

permafrost peatlands can be quite unique from even nearby non-permafrost sites (e.g. Yavitt et

al., 2006, Turetsky et al., 2004).

In terms of biogeochemistry, peatlands are the only ecosystems that are fundamentally “out of

balance” over long periods of time regarding C inputs and C outputs. Even in cases where rates

of net primary productivity are slow, microbial decomposition is even slower, resulting in the

seemingly perpetual buildup of soil organic matter. Despite that early models predicted

peatlands to cease to sequester C between 10-15k y of age (Clymo, 1984), there is evidence that

even very old peatlands with deep peat profiles still sequester C (Roulet et al., 2007).

Nevertheless, globally peatlands are still „young‟ (ca. 4-5k y) based on the initial predictions of

constraints on C accumulation by Clymo (1984), and have accumulated somewhere between

about 200 to more than 400 Gt of C, a sizable global pool (Turunen et al., 2002; Gorham, 1991).

There are a number of key reasons why decomposition of deep peat is slow allowing this

accumulation. The overriding control is predominantly linked to hydrology where both anoxia

caused by perpetual flooding, and very slow turnover time in humified peat with slow hydraulic

conductivity allows accumulation of decomposition end products that slow rates and limited to

no oxidation and „recharge‟ of electron acceptors (e.g. Morris and Waddington 2011; Beer et al.,

2008). However, other aspects including the unique and unfavourable chemistry and physical

environment of peat soil, particularly when composed of Sphagnum moss remains, low

temperatures, and low nutrient availability also play key roles in slow to seemingly nil rates (at

low depths) of decomposition (Moore and Basiliko, 2006).

5

1.3 Methane biogeochemistry of northern peatlands

One of the consequences of peat accumulation through slow, anaerobic decomposition is the

production of the greenhouse gas CH4 (Moore and Basiliko, 2006). Wetlands are the largest

global natural source of atmospheric CH4 with an estimated emission of 55-150Tg/year (Prather

et al., 1995). Considering the fact that CH4 is 25 times more effective as a greenhouse gas than

CO2 per molecule in the atmosphere over 100 years (IPCC, 2007), this molecule contributes to

22% of total climate forcing (Lai, 2009). The role that peatlands play in global climate and

climate change is balanced between a net C sink, and net CH4 source. Although over 100-year

timescales, it appears that peatlands are slightly mitigating contemporary climate change, slight

global-scale changes in their CH4 dynamics could change this role (Roulet, 2000). This point

provides a key rational for the present work, a study that involves a fundamentally new

understanding of CH4 dynamic in northern peatlands.

Methanogenesis is the process in which CH4 is produced by methanogens, using simple

compounds such as CO2 + H2 and acetate. This is one of the key terminal steps in the anaerobic

degradation of organic matter (Ferry, 2010). Methanogens belong to the domain Archaea and

phylum Euryarchaeota, where 26 genera and more than 60 species of methanogens are known to

exist (Ferry, 2010); however, they have been notoriously difficult to cultivate in isolation (Bräuer

et al., 2006). Although methanogens can collectively utilize more than 10 different C and redox

substrates, two metabolic pathways predominate in peatlands (Conrad, 2007). When

methanogens utilized CO2 + H2 for CH4 production, it is known as CO2 reduction; when acetate

is utilized, it is known as acetotrophy or acetoclastic methanogenesis. Although the former is

more energetically profitable, acetoclastic methanogenesis has been shown to be the predominant

pathway in nutrient rich sites, particularly when sedges are present (Hines et al., 2008; Galand et

6

al., 2005), although others have reported abundant obligate acetotrophic and CO2-reducing

methanogens in both poor and rich sites (Basiliko et al., 2003).

Organic substrate supply from vascular plant roots, particularly sedges, has been shown to be an

important C source for methanogens (Marinier et al., 2004). In principle, methanogens in

peatlands cannot compete for C sources with organisms capable of carrying out anaerobic

respiration (particularly sulphate, iron, and manganese reducing bacteria and ammonia oxidizers)

and therefore would only be active when all of the alternative electron acceptors have been

reduced following prolonged anoxia (e.g. Gaucci et al., 2004; Frenzel, 1999; Roy and Conrad,

1999). However, the same chemical species can also serve as anabolic nutrients for methanogens

(Basiliko and Yavitt, 2001; Jarrell and Kalmokoff, 1988), and it is increasingly common that

idealized thermodynamic competition does not play out as strongly in soils as in sediments, the

former where niche separation is likely quite common over very small spatial scales (Moore and

Basiliko, 2006).

Generally, in peatlands, water table level is typically or at least assumed to be the boundary

between aerobic and anaerobic processes (Lai, 2009; LeMer and Roger, 2001; Bubier and

Moore, 1994). Until recently it has been understood and accepted that CH4 is only produced

below the water table under anoxic conditions and oxidized above the water table under aerobic

conditions (AOM is dealt with below). Aerobic methanotrophs typically conduct aerobic CH4

oxidation by utilizing CH4 as a carbon and energy source (Hanson and Hanson, 1996). Known

methanotrophs belong to the phyla Proteobacteria and Verrucomicrobia, and are quite diverse in

terms of their carbon assimilation pathways, phylogenetic affiliation, and intracellular membrane

arrangement (Dunfield et al., 2007; Hanson and Hanson, 1996). Whether methanotrophs are

ecologically diverse in peat soils is unclear, and previously the diversity of active

7

methanotrophic bacteria across peatland types has been investigated using nucleic acid stable-

isotope probing (Gupta et al., in press). Aerobic CH4-oxidizing bacteria in peatlands or other

wetland environments are capable of very fast rates of CH4 oxidation, and these rates typically

follow first-order kinetics where higher concentrations of CH4 (with adequate O2) lead to faster

rates. When water table positions are low enough, peatlands can even be net sinks of

atmospheric CH4 even though CH4 production still occurs rapidly at depth; this is due to the

activity of methanotrophs (Godin et al., in review). Therefore it is possible for aerobic CH4

oxidation to filter all CH4 before reaching the atmosphere in some sites, although this is not

common, as water table positions are variable and can be close to the surface, restricting the zone

of aerobic CH4 oxidation (and explaining why peatlands are important net CH4 sources to the

atmosphere).

Other factors play roles in CH4 emissions to the atmosphere from peatlands beyond just

competing rates of production and aerobic oxidation as dictated by the water table. Of note are

the means of CH4 transport to the atmosphere: CH4 is released via three main pathways, namely

ebullition, plant-mediated transport and diffusion (Lai, 2009). Ebullition is a transfer of CH4 as

bubble flux and it is the dominant pathway in unvegetated surfaces and during winter months.

Aerenchyma in certain vascular plants serve as gas conduits to facilitate CH4 flux from the

anaerobic zone straight to the atmosphere. However, aerenchyma can also transport O2 beneath

the water table to sustain aerobic autotrophic respiration and inhibit the obligately anaerobic

methanogens. Lastly, molecular diffusion of CH4 is a function of the CH4 concentration gradient

in the peat. It is slower in the saturated zone than in the unsaturated zone of the peat profile; it is

through this process that methanotrophic communities come in contact with CH4, hence

controlling the rate of CH4 flux (Lai, 2009)

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1.4 Anaerobic CH4 oxidation

Anaerobic methane oxidation (AOM) is a process where methane is oxidized anoxically

(Hoehler et al., 1994). Although until recently it has been largely disregarded as an important

control on CH4 dynamics in peatlands (Smemo and Yavitt, 2011), it is estimated that 70 Tg to

300 Tg of CH4 is consumed by AOM in marine sediments annually (Valentine, 2002). Very little

is known about AOM in peatlands, where it could represent a large “internal” sink for CH4. Even

in marine and freshwater aquatic environments the exact organisms and mechanisms involved

are poorly understood. AOM occurs in marine and the freshwater aquatic environment, mediated

by archaeal and/or bacterial communities working solo or as a consortium (Boetius et al., 2000;

Raghoebarsing et al., 2006; Ettwig et al., 2010).

Though existence of AOM in the marine and the freshwater environment, such as lakes, is now

widely accepted, the pathway through which CH4 is oxidized and the electron acceptor it utilizes

is still fiercely debated. Nevertheless, AOM in peatlands has been regarded as an insignificant or

non-existent process (Nedwell and Watson, 1995), but strong evidence against this long held

understanding has been challenged by Smemo and Yavitt (2007).

Below I provide a brief history of AOM as a process, while discussing how our knowledge of

AOM has developed over the last three decades and why there still is no universal agreement

over the pathway and the microbes responsible for it. I begin by introducing AOM in marine

ecosystems where the most work has been done, freshwater aquatic systems where a limited

number of studies have been conducted, and finally the recent study by Smemo and Yavitt

(2007) providing evidence for AOM in northern peatlands.

9

1.4.1 Anaerobic oxidation of CH4 in marine ecosystems

Barnes and Goldberg (1976) and Reeburgh (1976) were among the first researchers that studied

and provided evidence of AOM in marine environments. Barnes and Goldberg (1976) studied

geochemical gradients in the sediment profile of the Santa Barbara basin, where they found that

there was a zone of overlap between diminishing CH4 concentration and increasing sulfate (SO4)

reduction, which led them to conclude that CH4 is oxidized with the help of SO4 reducers.

Zehnder and Brock (1980) reported the presence of AOM in freshwater lake sediments. They

found that AOM was inhibited by SO4, whereas both acetate and hydrogen (H2) stimulated

AOM. They also noted a striking similarity between AOM patterns with that of methanogenesis,

which led them to conclude that methanogens are responsible for AOM. However, their finding

was opposed by Alperin and Reeburgh (1985), who noted that when they tried to inhibit AOM

using molybdate (a specific inhibitor for SO4 reduction), inhibition did not occur. They also

noted that 2-bromoethanesulfonic acid (BES), a methanogenesis inhibitor, failed to inhibit AOM.

This led them to conclude that AOM cannot directly be carried out by sulfate-reducing bacteria

(SRB) or methanogenic bacteria. Instead, they hypothesized that AOM is conducted by a

consortium of unknown anaerobic methane oxidizers and SRB .

Hoehler et al. (1994) proposed an intriguing pathway through which AOM could be conducted in

marine environments. They proposed that CO2 reducers (methanogens) reversed their

biochemical pathway, and started to oxidize CH4 using water as an electron acceptor (eq 1),

where CO2 and H2 were the by-products. Subsequently, H2 was utilized by SRB (eq 2) in a

syntrophic association, yielding -25 kJ mol-1

. They called this process “reverse methanogenesis”

and cautioned that net CH4 oxidization was only feasible when H2 concentrations were below

0.84nM. In their laboratory sediment studies, they noted that AOM did not occur when SO4 was

abundant; rather it occurred in SO4 depleted sediments. Nevertheless, net consumption of CH4

10

did not occur in an absence of SO4 in any of the field or laboratory studies, suggesting that SO4

was necessary for net oxidation. In order to explain this contrasting effect of SO4 on AOM, they

reckoned that perhaps there might be two modes of CH4 oxidation, where the SO4 concentration

is the most critical factor. They hypothesized competition-exclusion of methane oxidizing

bacteria (MOB) by SRB, competing for the same substrate, in this case, acetate and H2.

However, in the SO4 depleted sediments, MOB and SRB could work in a syntrophic association,

where H2 acted as an intermediate. Furthermore, since both SRB and methanogens can utilize

acetate and H2, along with the fact that AOM is partially inhibited by BES (contrary to Alperin

and Reeburgh, 1985), it suggested that methanogens working in reverse are responsible for AOM

(Hoehler et al., 1994). Hansen et al. (1998) further supported the consortium hypothesis, where

they also found that AOM was directly proportional to CH4 concentration, however addition of

molybate (a SRB inhibitor) caused an uncoupling of AOM with CH4 concentrations after a lag of

3 days. This further confirms the fact that one functional group of microorganisms alone does not

conduct AOM.

CH4 + 2H2O CO2 + 4H2 (1)

SO42-

+ 4H2 + H+ HS

- + 4H2O (2)

SO42-

+ CH4 HCO3- + HS

- + H2O (3, net)

(∆G°‟ = -25 kJ mol-1

)

Subsequently, Hinrichs et al. (1999) discovered a new archaeal group and coined the name

anaerobic methanotrophic Archaea (ANME-1 cluster). ANME-1 cluster 16s rRNA sequences

were phylogenetically related to the methanogenic orders Methanomicrobiales and

Methanosarcinales. In addition, Boetius et al. (2000) provided microscopic evidence of archaeal

11

and SRB consortia conducting AOM from a marine hydrate using a fluorescence in situ

hybridization (FISH) technique. They also noted physical manifestation of two by-products of

AOM according to the stoichiometric reaction (eq 3), namely sulfides and bicarbonates near

marine hydrate ridges. However, FISH probes for ANME-1 organisms failed and instead a new

group of Archaea was shown to be actively taking part, which they named EelMS932.

Additionally, Desulfosarcina/Desulfococcus were the SRB actively taking part in AOM (Boetius

et al., 2000). Furthermore, using phylogenetic analysis of 16S rDNA, it was concluded that

ANME-1, ANME-2, ANME-3, and SRB are the most dominant archaeal and bacterial groups,

respectively, involved in these consortia (Strous and Jetten, 2004; Heijs et al., 2007; Girguis et

al., 2003). Heijs et al. (2007) noted that members of the ANME-2 cluster were closely related to

the methylotrophic methanogens, known as Methanosarcinales. Moreover, some species within

the Methanosarcinales group are capable of performing methanogenesis through CO2 reduction

(Heijs et al., 2007).

To summarize, the Hoehler et al. (1994) reverse methanogenesis hypothesis as a putative AOM

mechanism has received considerable support from other researchers, but it was still far from

getting full acceptance as noted by Valentine and Reeburg (2000). First, such low concentrations

of H2 are rarely maintained for extended periods of time in marine sediments or lower water

columns, and attempts to conduct AOM in a pure culture using methanogens that are able to

produce H2 under high CH4 concentration failed (Valentine et al., 2000). Valentine et al. (2000)

assumed that if methanogens simply reversed their biochemical pathway to oxidize CH4, then

given enough lag time, they should have observed AOM. They created a H2 removal technique,

so that no syntrophic association with SRB was required. Regardless of this, no CH4 oxidation

was observed. Second, AOM only yields about -25 kJ mol-1

of energy, which then must be

shared between the archaeal and SRB partners. However, for a syntrophic association to be

12

favorable, the accepted biological energy quantum is -20 kJ mol-1

per organism (Schink, 1997).

Furthermore, Moran et al. (2008) found that an increase in the H2 concentration did not affect the

rate of AOM, thereby concluding that H2 does not play interspecies role between Archaea and

SRB. Moran et al. (2008) then postulated a new model for AOM, where methyl sulfide (H3CSH)

plays the interspecies role, which is reduced by SRB. In addition to that, acetate and formate

have been suggested to play interspecies role between Archaea and SRB (Valentine and

Reeburg, 2000), but Nauhaus et al. (2005) failed to find evidence to support their involvement in

AOM. Therefore by the early to mid parts of the 2000‟s, one aspect of AOM was confirmed: that

it is conducted in a consortium of Archaea and SRB. Interspecies electron carrier debate was still

wide open and no further details about microorganisms responsible for AOM was known.

Then, in 2003, Hallam et al. reported an enzyme used by members of ANME-1 and ANME-2

clusters that was potentially conducting AOM. Methyl coenzyme M reductase (MCR) is an

enzyme that is associated with all known methanogens, since it catalyzes the terminal step in

CH4 production (Hallam et al., 2003). Due to functional constraints, MCR amino acid sequences

are conserved, even between phylogenetically distant methanogenic lineages (Hallam et al.,

2003). They speculated that if the CH4-oxidizing Archaea (MOA) did reverse their pathway to

conduct AOM, the mcrA gene should be present, but there must be some variation in the

sequence. The authors cloned mcrA genes from marine sediments, and found that four out of five

novel mcrA types were associated with the ANME-1 and ANME-2 groups. This provided a more

definitive link between methanogenic and methanotrophic Archaea.

Concomitantly, Girguis et al. (2003) developed a novel method to study AOM via continuous-

flow anaerobic CH4 incubation system (AMIS). This system supported the metabolism and

growth of MOA and SRB by simulating most of the in situ conditions. Girguis et al. (2003)

13

collected sediments from within, and nearby a CH4 cold seep and a non-seep sample and

incubated them for a period of 24 weeks in the AMIS. The authors found that the sediments from

the seep demonstrated no significant difference between AOM rate before and after the

incubation, indicating that the AMIS was successful in keeping the methanotrophic community

alive. Whereas, for the non-seep sediment samples, AOM was non-existent prior to the

incubation, but after 24 weeks incubation, AOM was evident. This suggested that the AMIS

provided an environment where AOM was preferred. Furthermore, phylogenetic analysis of 16

SSU rRNA sequence was conducted to identify Archaea in the samples. They found that in the

seep samples, organisms belonging to ANME-2c were the most abundant before and after the

incubation. However, in the non-seep sample, organisms belonging to ANME-2c were not

present before the incubation, but were present after the incubation, and represented the majority

of unique sequences/taxa detected (55% of total sequences analyzed). In addition, they

conducted FISH on the AOM consortia for the seep samples, and found that the consortium

significantly increased in sized after the incubation and there were more physical/spatial

interactions between the Archaea and the SRB. (Girguis et al., 2003)

With these keys findings, the enigma behind this elusive process in marine environments was

coming in the grasp of researchers. However that perception was short lived. In 2008, Ettwig et

al. started to publish a series of findings that threaten to dismantle the whole dogma of AOM.

Ettwig et al. (2008) conducted a bioreactor study, like Girguis et al. (2003), where they found

that AOM is linked with denitrification, similar to Raghoebarsing et al. (2006) findings, but

without the help of Archaea. In addition, contrary to Hallam et al. (2003), mcrA genes were not

modified in the ANME-2 cluster. In fact, they also reported that there was no inhibition effect of

BES (a methanogenesis inhibitor) on AOM. This lack of inhibition had also been earlier noted by

Alperin and Reeburg (1985) and Iverson et al. (1987). They also disputed Girguis‟ et al. (2003)

14

finding of increased abundance of organisms belonging to ANME-2c. Ettwig et al. (2008) found

that when they ran their incubation for 1 year, instead of 24 weeks as Girguis et al. (2003) did,

the archaeal population disappeared after an initial enrichment. Moreover, organisms termed

„NC 10‟ were the dominant bacterial group, and possibly solely responsible for AOM. They

indicated that Archaea might only have been methanogenic. Methanogens have been known to

oxidize very small portions of CH4 during methanogenesis (Zehnder and Brock, 1979), which

could have explained their initial enrichment observed by Ettwig et al. (2008) in their

incubations.

Subsequently Ettwig et al. (2010) concluded that AOM is conducted by an oxygenic bacterium,

which they named Candidatus Methylomirabilis oxyfera (NC10 phylotype). M. oxyfera is an

anaerobic, denitrifying bacterium, which encodes the well-known aerobic pathway for CH4

oxidation (CH4 is first converted to methanol, then formaldehyde and formate to CO2).

Therefore, this represents only the fourth known biological pathway known to produce molecular

oxygen (O2). Equation 4 is the overall reaction of CH4 with nitrite (NO2) and illustrates the

thermodynamic feasibility (Raghoebarsing et al., 2006). However, Ettwig et al. (2010) found that

M. oxyfera lacks some necessary genes for complete denitrification, such as, nosZDFY, a gene

responsible for catalyzing the last step (eq 5), dinitrogen production; hence, this pathway was not

feasible in this bacteria. They suggested a new enzyme „NO dismutase‟ that produces N2 and O2

from 2NO. Then, this intra-produced O2 was utilized in the oxidation of CH4 via the aerobic

pathway. In conclusion, their research challenges decade‟s long research on the AOM pathway

and microbes responsible, while proposing a paradoxical pathway, where CH4 was oxidized

under anaerobic environment, using an aerobic pathway.

15

3CH4 + NO2- + 8H

+ 3CO2 + 4N2 + 10H2O

(∆G°‟ = -928 kJ mol-1

) (4)

2NO3- 2NO2

- 2NO

N2O

N2

(5)

1.4.2 Anaerobic oxidation of CH4 in freshwater ecosystems: Lake sediments

Panganiban et al. (1979) studied Lake Mendota in Madison, Wisconsin and were the first

researchers to report the occurrence of AOM in freshwater ecosystems. They performed

incubation experiments where they found that acetate assimilation increased by 100 fold when

CH4 was present. SO4, acetate and CH4 were all required for growth of the enrichment. Acetate

was not oxidized to CO2, but assimilated by the cells, while CH4 was not assimilated, but was

oxidized to CO2. Zehnder and Brock (1980) also studied Lake Mendota and found that in the

presence of iron and SO4, the ratio of CH4 oxidized to CH4 formed substantially increased. They

also noted that acetate, H2 and manganese dioxide all stimulated AOM, whereas NO3 addition

inhibited AOM. Iverson et al. (1987) tested if SRB took part in AOM in freshwater ecosystems

by adding tungsten, which inhibits sulfate reduction, but no effect on AOM was apparent. Hence,

they concluded that in the freshwater environments, AOM is not coupled with SRB. They

reported CH4 consumption via AOM to occur at a rate of 1.36-mmol m-2

d-1

, and that AOM was

faster than CH4 production at all the depths. Smith et al. (1991) presented indirect evidence of

AOM in groundwater, where it was apparently fastest in the zone of abundant NO3. Furthermore,

Miura et al. (1992) linked AOM with Fe (III) reduction, where ferrous iron was oxidized to ferric

hydroxide (eq 6).

16

CH4 + 8Fe3+

+ 3H2O HCO3 + 8Fe2+

+ 9H+

(6)

In 2004, Islas-Lima et al. provided conclusive evidence of AOM coupled to denitrification in a

culture study using sludge water. CH4 was used as the sole electron donor for denitrification and

there was a 1:1 ratio between denitrification and N2 gas production (eq 7), as expected by the

stoichiometric calculation. However, they did not elude to or uncover potential microbes

responsible for AOM linked with denitrification.

5CH4 + 8NO3- 5CO2 + 4N2 + OH

- + 6H2O

(∆G°‟ = -960 kJ mol-1

) (7)

Subsequently, Raghoebarsing et al. (2006) investigated fresh water sediments that receive large

amount of NO3 via agricultural runoff and reported AOM linked with denitrification. However,

NO2 was preferred over NO3 in their enrichment experiments (eq 8), but when NO2 was

depleted, AOM resumed using NO3 as an electron acceptor after a lag time of 10-20 hours.

Biomarker analysis indicated that a consortium of Archaea (distantly related to known marine

ANME-2) and bacteria were responsible for AOM, but ruled out the presence of SRB.

Additionally they noted that their sequences were more related to the sequences from NO3

contaminated groundwater from United States, and contaminated soils from Japan, suggesting

that the AOM linked with denitrification is a wide spread phenomenon.

3CH4 + 8NO2- + 8H

+ 3CO2 + 4N2 + 10H2O

(∆G°‟ = -928 kJ mol-1

) (8)

Recently, radiotracer experiments were conducted using sediments of an oligotrophic freshwater

lake, where the researchers provided 14

CH4 to the headspace and tracked the formation of 14

CO2

17

(Deutzmann and Schink, 2011). They also provided these incubations with electron acceptors,

such as, NO3, NO2, and SO4 and found that SO4 has negligible effect on AOM, whereas, NO3

significantly increased the formation of 14

CO2 (reported rate of AOM: 1.8 to 3.6 nmol day-1

ml

sediment-1

). They also found the presence of M. oyxfera while using NC10-specific pmoA

primers. This was the first paper that has reported the presence of M. oyxfera in a freshwater

ecosystem, and putatively taking part in AOM linked with denitrification.

1.4.3 Anaerobic oxidation of CH4 in peatlands

Recently, Smemo and Yavitt (2007) presented evidence for AOM in freshwater peatlands. Even

though extensive research on marine AOM has been conducted, very little is known about it in

these important terrestrial wetlands. This lack of knowledge primarily stemmed from most

researchers considering AOM quantitatively insignificant and/or non-existent. The reason why

AOM in peatlands is a controversial topic is because there is no clear indication as to which

inorganic chemical species acts as the terminal electron acceptor, with for example, low SO4

concentrations, thereby making it thermodynamically unviable. In addition, AOM linked with

denitrification is unlikely because it requires abundant NO3 (nitrification would be constrained

by low pH and low O2 levels) and well-developed denitrifying bacterial communities, which are

also absent in most peatlands.

Smemo and Yavitt (2007) presented three types of experimental evidence to support their

findings that AOM is important in peatlands: first, by adding methanogenic inhibitors, second

by stable isotope enrichment (13

C-CH4), and third by natural abundance stable isotope (13

C-CH4)

analysis. They aimed to separate net vs. gross CH4 production to determine the rate of AOM.

First by using methanogenic inhibitors, such as BES and NO3, resulted in net CH4 oxidation

18

when compared to their CH4 production control. Addition of BES resulted in significant mean

net CH4 oxidation rate (-1.85 nmol kg-1

s-1

in Carex-derived peat to -4.15 nmol kg-1

s-1

in Typha-

derived peat), suggesting that AOM does occur in at least fen systems. Second, stable isotope

enrichments also confirmed the inhibition experiment conclusion, where it was calculated that up

to 65% of gross CH4 production is consumed by AOM.

They also conducted an electron acceptor study by providing incubations with either, SO42-

, NO3-

, or Fe (III). They found that in a minerotrophic fen (local name Michigan Hollow), SO42-

additions increased net CH4 consumption, whereas in Sphagnum-derived peat, NO3- additions

increased AOM. However, they concluded that increased AOM rate in NO3- additions were due

to its ability to inhibit methanogenesis.

Smemo and Yavitt (2007) also studied peatlands from Sweden and found that net AOM was

faster in minerotrophic fens than intermediate and ombrotrophic sites. Interestingly, they also

found that AOM is faster in deeper peat of the minerotrophic site.

19

2

Chapter 2: Objective and hypothesis

2.1 Objectives

The primary objective of this study was to investigate AOM with novel isotope tracer techniques

using an ecologically and spatially diverse and globally relevant set of peatland ecosystems and

by revisiting one of the sites where Smemo and Yavitt (2007) first reported AOM to occur for an

in-depth exploration of controls on this process. Specific objectives and research milestones were

to:

1) Quantify the rates and biogeochemical significance of AOM across 15 peatlands in North

America.

2) Determine if AOM involves anabolic assimilation of CH4-C in microbial biomass

3) Identify potential controls on the process using correlations with latitude/climate, site

type and trophic status, and site physicochemical properties

4) Identify the electron acceptor(s) sustaining AOM in a rich fen where Smemo and Yavitt

(2007) worked prior through the addition of potential electron acceptors under controlled

conditions.

20

2.2 Hypothesis

It was hypothesized that:

1) AOM exists and is a ubiquitous process across the latitudinal gradient based on the initial

report across 4 sites in the USA and Sweden by Smemo and Yavitt (2007).

2) Microbial communities responsible for AOM would assimilate some 13

C from oxidizing

13CH4 in their biomass, similar to marine environment (Hinrichs et al., 1999; Pancost et

al., 2000; Nauhaus et al., 2007) and freshwater environment (Raghoebarsing et al., 2006)

where bacterial and archaeal lipid biomarkers were indicative of these microbes

assimilating C from AOM.

3) Fens have faster rates of AOM than bogs due to potentially higher nutrient (base cations)

availability and thus supply of potential alternative electron acceptors to sustain this

anaerobic process.

4) Nitrate and/or ferrous iron are most likely to be the key electron acceptor driving fast

rates, as per Raghoebarsing et al. (2006) and Smemo and Yavitt (2007), and this would

be apparent both in correlations observed through objective 3 and manipulation

experiments through objective 4.

21

3 Chapter 3: Methodology

3.1 Characterization of AOM across sites

3.1.1 Study sites

Fifteen peatlands were selected for this study from Canada and United States (Figure 3.1-1). In

most cases (except for James Bay), other biogeochemical and ecological characteristic of the

sites have been studied and published. Samples were collected between June 2009 – July 2009

for Michigan Hollow, Big Run Bog, Buckles Bog, Mclean Bog, Dryden Bog and White River

fens (Rich, Intermediate and Poor); October 2009 for James Bay Lowlands sites (5A‟ Fen, Bog

on Permafrost, SA460 Fen, Channel Fen) and between July 2010 – August 2010 from Marcell

Experimental Forest (S1 Bog, S2 Bog, Bog Lake Fen) (see Table 3.1-1).

Big Run bog: is a 15 hectare minerotrophic fen, located in West Virginia, USA, within the

Monogahela National Forest. Sphagnum and Polytrichum mosses were the dominant bryophyte

and cover 85% of the wetland, while sedges (Eriophorum vaginatum L. and Carex spp), rushes

(Juncus effusus L) were the dominant vascular plant species. Mean annual temperature (MAT) is

7.9 °C and mean annual precipitation (MAP) is 133 cm (Weider, 1985; Basiliko and Yavitt,

2001).

Buckles Bog: is an open low-shrub bog located in the northeast-southwest trending valley and

ridge topography of the Allegheny plateau (Maxwell and Davis, 1972). Sphagnum fallax was the

dominant bryophyte species. Andromeda glaucophylla, Kalmia latifolia and Gaultheria

hispudula were the dominant vascular species (Basiliko and Yavitt, 2001). MAT = 7.9 °C and

MAP = 133 cm

22

Michigan Hollow: is a 15 hectare minerotrophic fen, located near Ithaca, NY, USA, and is

managed by the New York State Department of Environmental Conservation. There are three

dominant plant species at this site, which are Carex lacustris L., Typha latifolia L. and Juncus

effusus L. In addition to hydrological input from rainfall, the fen receives groundwater and

surface water flow from the surrounding upland forests (Smemo and Yavitt, 2007)

Mclean Bog: is a 70 meter across, ombrotrophic, kettle hole bog, located southwest of Cortland,

NY, USA. Sphagnum angustifolium and S. magellanicum were the dominant bryophyte species.

Andromeda glaucophylla, Chamaedaphne calyculata and Carex lacustris L. were the dominant

vascular species (Basiliko et al., 2003; Basiliko and Yavitt, 2003). MAT = 13.1 °C and MAP =

89.9 cm

Dryden Bog: is a poor fen, kettle hole depression, located southwest Cortland, NY, USA. Ledum

groenlandicum and Sphagnum angustifolium were the dominant vegetation (Cox, 1959). MAT =

13.1 °C and MAP = 89.9 cm

Bog Lake Fen: is a poor fen, located in North-central Minnesota, USA and is part of Marcell

Experimental Forest. Sphagnum sp, and Carex sp. are the dominant plant species. MAT = 3.0 °C

and MAP = 76.6 cm (Smemo and Yavitt, 2007).

S1 Bog and S2 Bog: is a perched bog, located in North-central Minnesota, USA and is part of

Marcell Experimental Forest. Dominant plant species are Picea mariana, Ledum groenlandicum,

Carex trisperma, Spahgnum magellanicum, and S. angustifolium (Kolka et al., 1999).

White River fens are part of the White River Experimental Watershed Study, located within the

catchment of White River basin. MAT = 2.1 °C and MAP = 98.0 cm. White River Rich Fen is a

2.1 ha, sedge fen, dominated by Eriophorum vaginatum L. and Carex sp. White River

23

Intermediate Fen is a 10.2 ha, dominated by Carex lacustris L, shrubs (Myrica gale L.,

Chamaedaphne calyculata, Ledum groenlandicum) and Sphagnum mosses. White River Poor fen

is 4.5 ha, dominated by Carex lacustris L, shrubs, Sphagnum mosses and trees (Picea mariana

and Larix laricina) (Webster and McLaughlin, 2010, Myers et al., in revision).

James Bay Lowland is a part of one of the world‟s largest continuous complex of peatlands, an

ecoregion that extends from James Bay in Quebec to Attawapiskat River in Northern Ontario

(Ecological framework of Canada). Four peatlands were chosen from this region, around the

Victor mine, which is located 90 km west of Attawapiskat, where MAP = 65.0 cm and average

temperature slightly above freezing (Hattori et al., 2009). Channel Fen is a riparian fen,

dominated by sedges (such as Carex lacustris L,), ericaceous shrubs (such as Ledum

groenlandicum), Betula nana, Alnus rugosa and Myrica gale. Bog on Permafrost is a pasla bog,

dominated by Picea mariana, Sphagnum, and Ledum groenlandicum. SA460 Fen is a floating

mat fen, dominated by Scorpidium limpr moss and Carex lacustris L. 5A‟ Fen is a shrub rich

treed fen, dominated by Scorpidium limpr moss, sedges (such as Carex lacustris L,), and Larix

laricina.

24

Figure: 3.1- 1: Location of fifteen study sites

25

Table: 3.1-1: Study sites characteristics

Sitea Location Site type

pHb

Dominant Vegetation

Surface pore water

chemistry

(μeq.L-1

)

Referencec

Big Run

Bog

West Virginia,

USA

39° 07‟N

79° 35‟ W

Chemically: True

ombrotrophic bogs.

Physiographically:

minerotrophic fen.

4.72

Sphagnum and

Polytrichum mosses

Vascular flora:

Eriophorum

vaginatum L., Carex

spp and Juncus

effusus L

Ca2+

: 39

Mg2+

: 18

K+: 10

NO-3 + NO

-2: 2

Cl-: 24

SO2-

4: 139

Na+: 8

Fe2+

: 22

Weider 1985.

Biogeochemistry 1: 277 –

302.

Buckles

Bog

Maryland, USA

39° 34‟N

79° 16‟ W

Open low-shrub bog 4.05

Sphagnum fallax.

Vasular: Andromeda

glaucophylla, Kalmia

latifolia, Gaultheria

hispudula

Ca2+

: 405

Mg2+

: 148

K+: 50

Na+:144

Fe2+

: 109

Basiliko and Yavitt

(2001). Biogeochemistry,

52: 133-153

Michigan

Hollow

New York, USA

42° 21‟N

76° 28‟ W

Minerotrophic sedge

fen 5.86

Carex lacustris,

Typha latifolia,and

Juncus effusus

Ca2+

: 4421

Mg2+

: 840

K+: 68

NO-3: 3

Cl-: 127

SO2-

4: 60

Na+:161

Fe2+

: 11460

Smemo and Yavitt (2007).

Geomicrobiology Journal.

24: 583-597. Iron data

only,

converted to (μeq.L-1

)

Other ions data: This

study

Mclean Bog

New York, USA

42° 45‟N

76° 01‟ W

Ombrotrophic kettle

hole bog 3.83

Sphagnum

angustifolium, S.

magellanicum, and

ericaceous shrubs

(Andromeda

glaucophylla,

Chamaedapne

calyculata and

Eriophorum

virgicum).

Ca2+

: 149

Mg2+

: 44

K+: 12

Na+: 151

Fe2+

: 9

Basiliko and Yavitt

(2003). Geomicrobiology

Journal, 20: 6, 563-577

26


pHb

Dominant Vegetation

Surface pore water

chemistry

(μeq.L-1

)

Referencec

Dryden Bog

New York, USA

42° 45‟N

76° 01‟ W

Poor fen

Kettle Hole

Depression

3.72

Ledum

groenlandicum,

Sphagnum

angustifolium

Ca2+

: 180

Mg2+

: 29

K+: 38

Cl-: 134

SO2-

4: 27

Na+: 298

Cox DD (1959). NewYork

State Museum and Science

Service Bulletin Number

377

Ions data: This study

Bog Lake

Fen

Minnesota, USA

47° 32‟N

93° 28‟ W

Poor fen 4.42 Sphagnum sp.,

Carex spp.

Ca2+

: 223

Mg2+

: 77

K+: 37

NO-3: 2

Cl-: 3

SO2-

4: 85

Na+: 28

Fe2+

: 1669

Smemo and Yavitt (2007).

Geomicrobiology Journal.

24: 583-597. Iron data

only,

converted to (μeq.L-1

)

Ions data: This study

S1 Bog

Minnesota, USA

47° 32‟N

93° 28‟ W

Perched Bog,

Young forested bog 3.6

Picea mariana, Ledum

groenlandicum, Carex

trisperma, Spahgnum

magellanicum,

S. angustifolium

Ca2+

: 240

Mg2+

: 160

Cl-: 3

SO2-

4:20

Na+:192

Fe2+

: 97

Kolka et al. (1999)- JEQ

28:766-775.

Kolka, R.K., Sebestyen,

S.D., Verry, E.S., and

Brooks, K.N. , editors.

(2010)

S2 Bog

Minnesota, USA

47° 32‟N

93° 28‟ W

Perched Bog,

Old forested bog 3.6

Picea mariana, Ledum

groenlandicum, Carex

trisperma, Spahgnum

magellanicum,

S. angustifolium

Ca2+

: 240

Mg2+

: 160

Cl-: 3

SO2-

4:20

Na+:192

Fe2+

: 97

Kolka et al. (1999)- JEQ

28:766-775.

Kolka, R.K., Sebestyen,

S.D., Verry, E.S., and

Brooks, K.N., editors.

(2010)

27


pHb

Dominant Vegetation

Surface pore water

chemistry

(μeq.L-1

)

Referencec

White River

Rich Fen

Northern Ontario,

Canada

48° 21‟N

85° 21‟ W

Rich sedge fen 5.76

Sedges

(Eriophorum

vaginatum

L. and Carex spp.)

Ca2+

: 1347

Mg2+

: 362

K+: 4

NO-3 + NO

-2: 11

Cl-: 6

SO2-

4: 192

Na+: 87

Webster and McLaughlin

(2010). Soil. Sci. Am. J.

74 (6)

doi:10.2136

Ions data converted to

(μeq.L-1

)

White River

Int. Fen

Northern Ontario,

Canada

48° 21‟N

85° 21‟ W

Intermediate sedge

and shrub fen 5.40

Sedges

(Eriophorum

vaginatum

L. and Carex sp.)

Shrubs (Myrica gale

L. and Chamaedaphne

calyculata).

Sphagnum moss.

Ca2+

: 559

Mg2+

: 198

K+: 5

NO-3 + NO

-2: 11

Cl-: 8

SO2-

4: 162

Na+: 83



74 (6)

doi:10.2136


(μeq.L-1

)

White River

Poor Fen

Northern Ontario,

Canada

48° 21‟N

85° 21‟ W

Poor fen 4.25

Shrubs (Myrica gale

L. and Chamaedaphne

calyculata).

Sphagnum moss.

Picea mariana and

Larix laricina

Ca2+

: 289

Mg2+

: 82

K+: 6

NO-3 + NO

-2: 16

Cl-: 9

SO2-

4: 137

Na+: 100



74 (6)

doi:10.2136


(μeq.L-1

)

Channel

Fen

James Bay

Lowland

52° 49‟N

83° 53‟W

Riparian channel

Fen 5.38

Eriophorum

vaginatum L,

Betula nana, Alnus

rugosa, and Myrica

gale

Ca2+

: 516

Mg2+

: 170

K+: 17

NO-3: 3

Cl-: 35

SO2-

4: 33

Na+:94

This study

28


pHb

Dominant Vegetation

Surface pore water

chemistry

(μeq.L-1

)

Referencec

Bog on

Permafrost

James Bay

Lowland

52° 49‟N

83° 53‟W

Paasla bog 3.95

Picea mariana,

Sphagnum and Ledum

groenlandicum

Ca2+

: 216

Mg2+

: 16

K+: 13

NO-3: 2

Cl-: 22

SO2-

4: 33

Na+:80

This study

SA 460 Fen

James Bay

Lowland

UTM ZONE

17N

301603 E

5845271 N

Floating

Matt/Shallow

Pond/Fen

4.40 Scorpidium limpr

moss and Carex spp.

Ca2+

: 176

Mg2+

: 16

K+: 16

Cl-: 43

SO2-

4: 49

Na+: 62

This study

5A‟ Fen

James Bay

Lowland

UTM ZONE

17N

300415 E

5843095 N

Shrub Rich Treed

Fen 4.28

Scorpidium limpr

moss, Carex spp. And

Larix laricina

Ca2+

: 190

Mg2+

: 16

K+: 279

NO-3: 2

Cl-: 18

SO2-

4: 407

Na+: 23

This study

a: Peatlands are arranged according to their latitudinal position.

b: Average pH of peat from all the incubations (n=18 or n=27) was calculated.

c: Unless explicitly stated, above stated site characteristics (except for pH) for each sites was gathered from published literature.

29

3.1.2 Sampling procedure

At each sites, anoxic peat samples were collected by hand at five different locations (minimum

10 meters apart) and 15 cm below the ambient water table. This depth was chosen because the

water table in peatlands is known to fluctuate (Webster and McLaughlin, 2010), but it not too

deep that highly decomposed peat was collected. Peat samples were stored and sealed in 750 ml

Mason vials and over filled with porewater to keep them anoxic. All samples were transported

the same day via car and/ or plane on ice to the University of Toronto Mississauga, where they

were stored at -20 °C. Peat was thawed at room temperature prior to incubation. Porewater was

also collected, filtered and stored at -20 °C. These samples were thawed and analyzed for

calcium, magnesium, potassium, nitrate, chloride, sulfate and sodium for sites whose ion data

was not previously published (see the Table 3.1-1 for more detail).

3.1.3 AOM 13C tracer incubations

Each study site had a minimum of two treatments, “N2 addition” incubation and “13

CH4 addition”

incubation at three different time intervals (day 3, 20, 40). All treatments were in triplicate, n = 9

(three replicates at three time intervals) and all sampling for C measurements were „destructive‟.

In addition, fractionation control “12

CH4 addition” incubation was also set up for seven sites to

confirm that the CH4 concentration did not affect rates of gross methanogenesis and associated C

fractionation in the controls, where n = 9. So, each site had a total of 18 or 27 incubations. The

seven sites chosen for this additional treatment were 5A‟ Fen, SA460 Fen, Channel Fen, Bog on

Permafrost, Bog Lake Fen, S1 Bog and S2 Bog.

Peat samples from different within-site locations were mixed and homogenized into a composite

sample. Approximately 35 grams of moist peat was added to 500 ml serum vials along with 70

30

ml distilled water. Each container was sealed using thick rubber septa (Geo-Microbial

Technologies, Ocheleta OK, USA; Cat. # 1313l), and covered with two layers of Parafilm M

(Pechiney Plastic Packaging Company, Chicago IL, USA). Following that, air in each vial was

evacuated using a vacuum pump for 5 minutes and back flushed with N2 gas (Linde, grade 4.8,

99.998% purity) for 2 minutes. This process was repeated four times, and during the last round,

each vial was equilibrated to the atmospheric pressure using a 20G needle, until very slight

positive pressure was noted in an attached syringe. Rubber septa were again covered with a layer

of Parafilm. Furthermore, to ensure that the conditions in the vials were anoxic prior to the

addition of 13

CH4, vials were kept in a dark (to minimize potential photosynthesis) at room

temperature for 4 days, so that any remaining oxygen was consumed by heterotrophs.

After 4 days, 10 ml of N2, 12

CH4 (Cambridge Isotopes, Cambridge MA, USA, 99.99% isotope

purity, less than 10ppm chemical impurity confirmed not to be O2 by the manufacturer), or 13

CH4

(Cambridge Isotopes 99.99% isotope purity, less than 10ppm chemical impurity confirmed not to

be O2 by the manufacturer) was added to the respective incubations. Headspace gas was mixed

(using the same syringe) and 10 ml of headspace was removed and the stopcock was closed prior

to the removal of the syringe. Headspace CH4 and CO2 concentration were determined using a

gas chromatograph (GC) equipped with a flame ionization detector and in-line methanizer (SRI

Intruments, Torrance, CA, USA). Volumetric concentration of CH4 and CO2 were determined

relative to the commercial standards and then converted to part per million (ppm). This point

signified “Time zero”.

At days 3, 20 and 40, a set of three incubations was destructively sampled to analyze the

headspace CH4 and CO2 concentration, the isotopic signatures of the headspace CO2, and

31

isotopic signature of organic carbon in peat. First, the headspace gas was gently mixed and 10 ml

of gas was removed for GC analysis.

Second, remaining headspace gas was evacuated using 60 ml syringe and bubbled through 5ml

of 0.2 M sodium hydroxide solution at a rate of 1ml/sec (this rate was empirically optimized,

data not shown) in a 15ml falcon tube. Once all the headspace gas was captured, 5ml of 0.2M

barium chloride solution was added to the tubes; white precipitate (barium carbonate)

immediately started to precipitate (see appendix 1 for calculations). Tubes were stored at room

temperature until they were centrifuge, or if that was not possible (> 2 days), stored at 4 °C. All

tubes were centrifuged at 4000G for 30 min at room temperature. After the centrifugation,

barium carbonate precipitate formed at the bottom of the tube. Without disturbing the pellet, the

supernatant was gently removed using a 10 ml pipette. Then, 7ml of DDI water was added to

each tube and mixed for a few seconds. The tubes were centrifuged at the same setting and the

supernatant was gently removed. This process was repeated three times. In the end, all tubes

were oven dried at 45 °C and shipped to Keck Paleoenvironmental & Environmental Stable

Isotope Laboratory at the University of Kansas, Lawrence, KS. Samples were analysed using a

Kiel Carbonate Device III + Finnigan MAT253 isotope ratio mass spectrometer

(ThermoFinnigan, Germany). Samples were reacted with 100% prepared phosphoric acid at 75

°C for 3 min (carbon of calcite) and 12 min (carbon of dolomite) to release CO2, which was

trapped cryogenically. CO2 was then measured versus a CO2 reference tank, whereby raw δ 13

C

was determined, calibrated using commercial standards and reported as δ13

C VPDB. Sample

measurement precision was better than ±0.10‰.

Third, the incubation vials were opened, peat was extracted using a spatula, pH was recorded and

subsequently 2N hydrochloric acid was added to acidify peat to approximately pH 2. Thereafter,

32

the peat was dried at 60 °C and ground using a Wiley Mill (Thomas Instruments Swedesboro,

NJ, USA). Ground peat samples were then shipped to Keck Paleoenvironmental &

Environmental Stable Isotope Laboratory at the University of Kansas, Lawrence, KS. Samples

were analyzed using a Costech 4010 elemental analyzer (EA) in conjunction with a Thermo

Finnigan MAT 253 IRMS (ThermoFinnigan, Germany). Samples were flash combusted at

roughly 1800 °C to produce various carbon compounds, such as CO2. CO2 was then measured

versus a CO2 reference tank, whereby raw δ 13

C was determined, calibrated using commercial

standards and reported as δ13

C VPDB. Sample measurement precision was better than ±0.22‰.

3.1.4 Site chemical analysis

For many sites, pore water ion chemistry was available from previous studies (Table 3.1-1).

Otherwise pore water was analyzed for Ca2+

, Mg2+

, K+, NO3

- + NO2

-, Cl

-, SO2

4, Na

+, Fe

2+ using a

Dionex 1600 ion chromatograph (Dionex Corporation, Sunnyvale, CA USA). For all sites peat

pH was measured in this study using a Ag/glass electrode and meter.

3.1.5 Calculations and numerical analyses

3.1.5.1 Net CH4 production rate

Time Zero CH4 concentration was subtracted from each respective incubation. This eliminated

any CH4 that was produced prior to Time Zero, and it normalized CH4 concentration in 13

CH4

addition incubations that received 20000 ppm CH4. Methane concentrations were corrected for

the 10ml of headspace gas extracted for GC analysis. The GC reports in peak areas that were

converted to PPMV relative to commercial standards and then converted to mass CH4 per jar

33

using the ideal gas law. Using the determined moisture content of each peat (though oven

drying a sub sample), values were then converted to nmol CH4-C/ kgdried peat sec-1

3.1.5.2 Anaerobic oxidation of CH4

δ13

C VPDB values were converted to 13

C fractional abundance (13

F), where RStandard = 0.0118

13F = δ13C VPDB + 1000

δ13C VPDB + 1000 + (1000/ RStandard)

13F was multiplied by 100 to obtain

13C atom percent (

13AP). The three replicates were averaged

of 13

AP for each treatment, per time interval and the average 13

AP of the N2 addition was

subtracted from 13

C-CH4 addition. This provided net gain in 13

C AP over that time interval.

For the AOM calculation, CO2 concentrations from the N2 addition were used, which provided a

conservative value of total inorganic C in each flask (i.e. because CO2 production from AOM

was not accounted for). For each incubation, CO2 concentration at `Time zero` was subtracted

from its corresponding concentration at the respective subsequent days (3, 20, 40). This

represented the amount of CO2 that was produced during that particular period. CO2

concentrations were then corrected as per Henry`s Law to account for dissolved inorganic C. For

each time interval, CO2 concentration was averaged and multiplied by the net gain in 13

AP. Then,

to calculate the net gain in 13

CO2 (in μg C g-1

dried peat), the ideal gas law was solved for „n‟,

where temperature is 293K and atmospheric pressure was assumed to be 1atm. The amount of

AOM was expressed per gram dried peat and values were converted to nmol C kg dried peat-1

sec-1

34

3.1.5.3 Determining 12CH4 and N2 treatments C fractionation

Channel Fen, Bog Lake Fen, SA460 Fen, 5A‟ Fen, Bog on Permafrost, S2 Bog and S1 Bog were

chosen to be tested with 12

CH4 at the same concentration as 13

CH4 addition. This would

determine if the addition of 20000 ppm CH4 resulted in higher 13

CO2 fractionation versus the N2

addition. One explanation for this would be that CO2-reducing methanogens are known to

discriminate against 13

C and if rates of methanogenesis were dependent on CH4 concentrations, a

correction would have to be made (though CH4 production is typically known to not be product

concentration dependent). The average 13

C AP of the 12

CH4 addition over the three time intervals

were calculated as above. Then, average 13

C AP of the N2 addition were compared with 13

C AP

of the 12

CH4 addition using student t-test.

3.1.5.4 Assimilation of CH4 derived C in solid phase

Detection of tracer 13

C following acidification in peat would indicate that microorganisms were

assimilating C. Using the solid (acidified, dried peat) phase C isotope data, the net gain in 13

AP

over each time interval was calculated as above for the gas phase. The total mass of organic C in

peat was calculated by multiplying organic C% (provided by Keck Paleoenvironmental &

Environmental Stable Isotope Laboratory, method shown above) by the mass of dried peat. The

resulting value was then multiplied by net gain in 13

AP, which provided net gain in 13

C content in

peat. This value was divided by mass of dried peat to provide net gain in 13

C per grams of dried

peat. These values represented total CH4-derived organic C per mass of peat.

35

3.1.5.5 Gross CH4 production

The gross CH4 production rate under 20000 ppm CH4 was calculated by adding the net CH4

production rate under 20000 ppm CH4 plus net AOM plus net 13

C assimilation in solid phase.

3.1.6 Statistical analysis

Production, oxidation, and assimilation values were tested to confirm that the data had a normal

distribution. Then, student t-tests were conducted to determine if the 12

CH4 addition values

differed from N2 additions (at P < 0.05). If no significant differences were noted between the two

treatments (i.e. CH4 concentration did not affect natural abundance C fractionation in the

treatment), and therefore student t-tests were performed between N2 addition and 13-CH4

additions. If significant differences were observed in the 13

AP values, they were disregarded

from further analysis. Variability is expressed as standard deviation calculated using each set of

three replicates from each sampling time. Repeated measures ANOVAs were not required as

each sampling time involved an independent set of samples. Correlations between site

characteristics and measured rates were explored and correlation coefficients and resulting P

values calculated using Microsoft Excel. Single t-tests were also used to characterize the

differences between categorical sets of sites (e.g. bog and fen).

36

3.2 Potential electron acceptor addition study

A smaller scale manipulative study was conducted involving additions of potential electron

acceptors involved in AOM was carried out using Michigan Hollow peat.

3.2.1 Study site and field sampling

Michigan Hollow, described above, was sampled in July, 2008 and at the time of sampling the

water table was at or just above the soil surface. Anoxic peat samples were collected by hand at

the three locations because the water table was above the surface and the peat profile is <1m.

Peat samples were stored and sealed in 750 ml Mason vials and over filled with porewater to

keep them anoxic. All samples were transported the same day via car to the University of

Toronto Mississauga and were stored at room temperature until incubations were set up a few

days later.

3.2.2 Anaerobic incubations, gas sampling and analysis

The experimental design of in vitro incubation consisted of 12 vials; 3 incubations with no

electron acceptor (control), 3 incubations with SO42-

, 3 incubations with NO3- and 3 incubations

with Fe (III) as a potential electron acceptor. Anoxic samples were mixed and homogenized in a

zip-lock bag using sterile scissors. Approximately 7 grams of moist peat was added to 100ml

serum vials along with 14 ml of pore-water deoxygenated with N2 gas. 1 ml of electron

acceptors (deoxygenated with N2 gas) were added to the respective incubations, where SO42-

was

added in the form of Na2SO4 (final concentration of 100 µM SO4-), NO3

- was added in the form

of Ca(NO3)2 (final concentration of 100 µM NO3-) and Fe (III) in the form of Fe(OH)3 (final

37

concentration 200 µM). 1ml of deoxygenated, de-ionized water was added in the control

incubations (see appendix 2 for calculation).

Each container was sealed with rubber septa (Geo-Microbial Technologies; Cat. # 1313) and

covered with an aluminum cover (Wheaton Science products) using a Wheaton E-Z crimper.

Following that, all incubations were made anoxic, as described above in section 3.1.3

After three days, 1 ml of 12

CH4 was added to all 12 vials, and briefly mixed. A headspace gas

sample was immediately extracted and analyzed on the GC for CH4 concentration. After 25 days,

headspace CH4 concentration was measured again on the GC. Subsequently, all incubations were

evacuated and filled with N2 as above and 1ml of each electron acceptor was added to the

respective vials to revitalize the peat samples. After a three days period, 1 ml of 13

CH4

(Cambridge Isotope 99.99%) was added to all 12 incubations. This set of incubations ran for 21

days, after which headspace CO2 was trapped as barium carbonate for isotopic analysis as per

section 3.1.3, except that the samples were shipped to University of Georgia for 13

C isotope

analysis on a solid phase C analyzer with an isotope ratio mass spectrometer. However, there

was not enough carbonate for analyses of individual samples; replicates were combined for

Michigan Hollow.

38

4 Chapter 4: Results

4.1 Characterization of CH4 dynamics and AOM across sites

4.1.1 Net CH4 production under 13CH4 and N2

When CH4 production rates were compared within each headspace condition, interesting patterns

were evident. In the N2 addition, CH4 production rate between Time 20 and Time 40 either

stayed constant (7 peatlands) or increased (7 peatlands) (Table 4.1-1). This indicates that there

was enough substrate for methanogenesis. In comparison, the CH4 production rate stayed

constant in nine peatlands, increased in two peatlands, and decreased in four peatlands in the

13CH4 addition (Table 4.1-1). Furthermore, on average, fens produced more CH4 than bogs at

both time intervals, and in both treatments, though only N2 treatment values were significant

(Figure 4.1-1).

39

Figure 4.1-1-1: Mean methane production rate for bogs (n=18) and fens (n=27) for

N2 and 13

CH4 treatments. pH 4.2 was chosen as an indicator to differentiate between

bog and fen. Rates are shown for two treatments, over two intervals, Time 20 (solid

black) and Time 40 (solid grey).

40

Table 4.1-1: Summary table for all 15 peatlands. Mean rates (±SD) are shown, where n = 3. NSD was placed

when there were no significant difference (p > 0.05) between N2 and 13

CH4 treatment. Mclean Bog, Time 20

net AOM rate was not calculated due to the loss of samples. Gross CH4 production rate was calculated by

addition of Net CH4 production rate under 20000 ppm, Net AOM rate and Net 13

C assimilation in solid

phase. Study sites are arranged from high pH (fen type) to low pH (bog).

41

4.1.2 12CH4 vs N2 treatments: impacts on fractionation of natural abundance 13C

Seven sites were tested with 12

CH4 to determine if the addition of 20000 ppm CH4 results in

higher 13

CO2 fractionation versus the N2 addition (beginning at 0 ppm CH4). The logic behind

this test was that methanogens discriminate against isotopically heavier CO2 (12

CO2 vs 13

CO2),

thereby enriching headspace with 13

CO2, and potentially leading to overestimation of AOM.

Although methanogenesis is not generally understood to be product concentration dependent, I

wanted to confirm that this was the case between 0 ppm CH4 vs ~ 20000 ppm CH4. In all the

seven sites, 13

CO2 atom percent of both addition treatments, 12

CH4 and N2, were not statistically

different from each other (Figure 4.1-2). Hence, using 13

C fraction from N2 addition to account

for fractionation of natural abundance C for all sites is a valid assumption.

42

- N2 addition - 12

CH4 addition

- 13

CH4 addition

addaaaddaddition

43

- N2 addition - 12

CH4 addition

- 13

CH4 addition

- N2 addition - 12

CH4 addition - 13

CH4 addition

44


C atom percent from three treatments, over three time interval

(Time 3, 20, 40). N2 addition (red square), 12

CH4 addition (green triangle) and 13

CH4

addition (blue diamond). Compared to the natural fractionation (N2 treatment), no artificial

fractionation of 13

CO2 occurred when methane (12

CH4) was added to the headspace. Error

bars represents the standard deviation of triplicate incubations. The small inlet is closer

view of N2 and 12

CH4 additions.

45

4.1.3 Anaerobic CH4 oxidation

The first objective of this research was to quantity the rates and to determine biogeochemical

significance of AOM across 15 different peatlands in North America. There was a significant

increase in the headspace 13

CO2 atom percent (AP) of 13

CH4 treatment during the course of 40

days incubation in all the peatlands except in the Bog on Permafrost (Figure 4.1-3; blue

diamond). This indicated that labelled 13

CH4 added to these incubations was anaerobically

oxidized, thereby causing an increase in the headspace 13

CO2 signature. On the other hand, no

significant increase in the 13

CO2 AP of N2 treatment was noted (Figure 4.1-3; red square), which

indicated that natural fractionation, presumably due to methonogenesis had little impact over the

course of the experiment, and that natural 13

CO2 signature (CO2 produced by decomposer and

other anaerobic microbes) does not change over the course of the experiment.

Furthermore, net amount of AOM increased during the 40 days incubation in all the peatlands

(Figure 4.1-3; green pyramid). The 5A‟ Fen had the highest amount of AOM (16.38 ± 1.68

μmole CH4), while the Bog on Permafrost had the least amount of AOM (0.92 ± 0.66 μmole

CH4). Overall, fens consumed more CH4 over the 40 day period (range of 3.99 – 16.38 μmole

CH4) than bogs (range of 0.92 – 3.68 μmole CH4).

AOM rates were also calculated, where day 20 had marginally higher rate than day 40 (Table

4.1-1). AOM rate was fastest in 5A‟ fen at both day 20 (7.09 ± 5.16 nmol CH4 kg peat-1

sec-1

)

and at day 40 (4.74 ± 0.49 nmol CH4 kg peat-1

sec-1

) (Table 4.1-1). It should be noted that all

AOM rates were corrected for background changes in 13

C. All three replicates for Mclean Bog,

day 20 interval were lost due to tube breakage in the centrifuge.

46

- N2 addition

- 13

CH4 addition - Net CH4 oxidized

- N2 addition - 12

CH4 addition - 13

CH4 addition

47

- N2 addition

- 13


- N2 addition - 12

CH4 addition - 13

CH4 addition

48

- N2 addition

- 13


- N2 addition - 12

CH4 addition - 13

CH4 addition

49

- N2 addition

- 13


- N2 addition - 12

CH4 addition - 13

CH4 addition

50


CO2 atom percent (AP) and net AOM amount for 15 peatlands

over the three time interval. On the primary y-axis, increase in 13

C AP of CO2 for 13

CH4

addition (blue diamond) and N2 control addition (red square) were plotted. On the

secondary y-axis, net CH4 oxidized (green triangle) via AOM was plotted. Graphs are

arranged from high pH (fen type) to low pH (bog). Error bars for all points are ± SD,

where n = 3. Note: 5A` Fen has a different y-axis scale (*).

51

4.1.4 Solid phase analysis

4.1.4.1 12CH4 vs N2 treatments and C fractionation

Of the seven sites tested, there were no significant differences between the solid phase 13

C AP of

N2 and 12

CH4 additions headspace conditions (data not shown). Hence, it is assumed that the N2

addition samples served as an appropriate control for all the sites to determine the net 13

C

assimilation in the peat.

4.1.4.2 13C assimilation in the peat

The second objective of this research was to determine if AOM involves anabolic assimilation of

C derived from CH4 oxidized in microbial biomass. At day 3 in comparison to the N2 addition,

there was no significant enrichment in 13

C of peat under the 13

CH4 headspace. Furthermore,

when compared to the N2 addition, two fens (5A‟ Fen and Big Run Bog) and four bogs (Buckles

Bog, Bog on Permafrost, White River Poor Fen and S2 bog) did not have significant 13

C

enrichment over the day 20 and day 40 intervals (Table 4.1-1). A total of nine sites (six fens and

three bogs) showed small, yet significant 13

C enrichment in peat by the day 20 and/or day 40

interval (Figure 4.1-4 and Table 4.1-1). Of these sites, Michigan Hollow had the least amount of

assimilation (~31 nmol C g dried peat-1

), while Bog Lake Fen had the highest amount of

assimilation (~1713 nmol C g dried peat-1

) (Figure 4.1-4). Fens were more likely to assimilate

significant 13

C in the peat than bogs, but there was no clear relationship between the amount of

13C assimilated and the peatland type, unlike with AOM as determined by net

13CO2 production

above.

52

In the terms of 13

C assimilation rate, three peatlands showed a much higher rate of assimilation

than others. These were, Channel Fen (3.45 ± 1.35 nmol CH-C kg peat-1

sec-1

), Bog Lake Fen

(5.96 ± 3.37 nmol CH-C kg peat-1

sec-1

) and S1 Bog (4.55 ± 3.08 nmol CH-C kg peat-1

sec-1

)

(Table 4.1-1).

53

- N2 addition

- 13

CH4 addition - Net 13

C assimilated

- N2 addition - 12

CH4 addition - 13

CH4 addition

54

- N2 addition

- 13

CH4 addition - Net 13

C assimilated

- N2 addition - 12

CH4 addition - 13

CH4 addition

55

Figure 4.1-4: Solid phase 13

C assimilation in peat for 9 peatlands. On primary y-axis, 13

C atom

percent were plotted for 13

CH4 (diamond) and N2 additions (square) over two time interval

(Time 20 and 40). On secondary y-axis, net 13

C assimilation (triangle) assimilation was plotted.

Graphs are arranged from high pH (fen type) to low pH (bog). Error bars for net CH4 oxidation

points (± SD), where n = 3. Note: Channel Fen, Bog Lake Fen and S1 Bog have different y-

axis scale (*).

56

4.1.5 AOM in relation to gross CH4 production

When AOM rate was divided by the gross CH4 production rate, the importance of the magnitude

of AOM in peatlands became clearer. At day 20, AOM consumed anywhere from 2.5% to

115.6% of the amount of gross CH4 produced over the same time period by the same peat (Table

4.1-2). At day 40, AOM could consume anywhere from 2.5% to 38.5%. Overall, day 20 interval

had higher percent consumption than day 40 interval, which was due to reduced AOM.

Additionally, AOM was perceived to be a slightly more important process in bogs than fens at

day 20 and at day 40, but this was due to decreased CH4 production in bogs.

When AOM measured as 13

CO2, was combined with solid phase 13

C assimilation, and divided by

the gross CH4 production rate, AOM could consume anywhere from 3% to 289% of gross CH4

production. Once again, day 20 interval had overall higher percent consumption than Time 40

interval, which was due to reduced AOM rate at day 40. While, total AOM was more dominant

in bogs than fens at day 20 and at day 40, which was due to increased 13

C assimilation in the peat

at day 20 and decreased CH4 production at day 40 in bogs (Table 4.1-3).

57

Table 4.1-3: Percent of gross CH4 consumed by AOM and solid phase

Table 4.1-2: Percent of gross CH4 consumed by AOM (headspace)

58

4.1.6 Potential chemical/ substrate controls of AOM

The third objective of this research was to identify potential control on this process using

correlations with latitude, site type, trophic status and physiochemical properties. There was a

quite robust relationship between the maximum rate of AOM and peatland type (fens vs. bogs).

When peatlands were divided into two categories, bogs and fens, where pH 4.2 was chosen as

the cut off, interesting patterns were noted. Peatlands who achieved their maximum rate of

AOM at Time 3, were always bogs (two sites), whereas, those who achieved their maximum rate

at Time 20/Time 40 were always fens (eight sites). However, there were four peatland (3 bogs

and 1 fen) whose AOM rate stayed constant throughout the experiment, though at the lower rate

(Figure 4.1-5)

Correlation analysis was conducted with average rates of AOM over the 40 days period and ions

concentrations in porewater, such as sulfate, magnesium, nitrate, sodium and chloride, and

overall ionic strength. Except for SO4, no strong or significant correlation was present between

any ion concentration and rate of AOM (Figure 4.1-6)

59

Figure 4.1-5: Time interval vs maximum rate of AOM. Fens and bogs were separated based on

pH. Bogs (gray cone) AOM either peaked at Time 3, or stayed constant, while fens (black cone)

AOM peaked at Time 20/40.

60

Figure 4.1-6: Correlation between average rate of AOM with porewater ion concentration.

61

4.2 Potential electron acceptor addition study

4.2.1 Net CH4 production

In the Michigan Hollow incubations, the treatment that received no addition showed the smallest

mean net CH4 production, while the incubations that received potential electron acceptors (Fe

(III), NO3, or SO4) had higher mean net CH4 production after 25 days (Figure 4.2-1). However,

among the three electron acceptors treatments there were no significant difference in net CH4

production rates (Figure 4.2-1).

4.2.2 Headspace 13C enrichment and AOM calculations

The fourth objective of this research was to identify the electron acceptor(s) sustaining AOM in a

rich fen. Headspace CO2 in the Michigan Hollow samples were highly enriched with 13

C, with

the control having the most enriched sample, 1.199 δ13

C AP, while the treatment receiving the

electron acceptors SO4, NO3 or Fe (III) had an enrichment of 1.181 δ13

C AP, 1.184 δ13

C AP and

1.185 δ13

C AP, respectively (Figure 4.2-2). This is in comparison to the N2 treatment value from

Michigan Hollow of 1.144 δ13

C AP. This resulted in net methane oxidation of 3.94 μmole CH4 in

the no electron acceptor addition treatments, while treatment receiving electron acceptors

oxidized 2.75 μmole CH4 (SO4 amendment) 2.99 μmole CH4 (NO3 amendment) and 2.97 μmole

CH4 (Fe (III) amendment), respectively (Figure 4.2-2).

62

Figure 4.2-1: CH4 flux (12

C additions) 0 to 25d. Flux values are means in mg CH4 per flask

with 7g wet peat or ca. 1g dry peat each. Bars are standard deviations of 3 replicates

63

Figure 4.2-2: 13

C AP enrichment of incubations amended with addition of electron acceptor (grey

bars). Amount of net CH4 oxidized over 21 days period in these treatment (secondary y-axis, dashed

line), where N2 treatment AP value was assumed as fractionation control for electron acceptor study.

64

5 Chapter 5: Discussion

5.1 Evidence of AOM

My thesis work represents, to my knowledge, the first characterization of AOM in peatlands

using stable isotope tracer techniques. In marine sediments, AOM is considered to be a very

quantitatively important control on CH4 emissions, and it was estimated to consume about 70 to

300 Tg of CH4 annually (Valentine, 2000). Numerous studies of marine sediment and water

column environments have eluded to AOM being carried out by a consortium of archaea

(ANME-1,2,3 cluster) and SRB (Hoehler et al., 1994; Hinrichs et al., 1999; Pancost et al., 2000;

Hallam et al., 2004), while more recently Ettwig et al. (2008 and 2010) reported that an

anaerobic denitrifying bacterium was solely responsible for AOM. In addition to this, potential

terminal electron acceptors and interspecies electron transfer between the consortium members

has been another hotly debated topic. Hence, it should come to no surprise that so far no

organisms responsible for AOM have been isolated in a pure culture, though researchers have

been studying this for more than three decades.

Knowledge about the existence of AOM in freshwater environments also dates back three

decades, but comparatively speaking, our understanding of AOM in freshwater systems, at best,

is rudimentary. Evidence of AOM in freshwater lakes potentially utilizing SO4 as an electron

acceptor (Panganiban et al., 1979; Iverson et al., 1987; Smith et al., 1993), and in groundwater

potentially using NO3 as an electron acceptor (Smith et al., 1991) has been reported. Islas-Lima

et al. (2004) conclusively linked implicated NO3- in AOM and , Raghoebarsing et al. (2006)

confirmed AOM can be driven via denitrification and carried out by a consortium consisting of

an archeaon similar to the ANME cluster member and a bacterium (likely a denitrifier).

65

In peatlands, AOM has been largely ignored, partly due to Nedwell and Watson (1985), who

concluded that AOM is not feasible in peatlands or at least is not a significant process in these

types of ecosystem. However their conclusion was not based on any experimental evidence.

Nevertheless, due to this, researchers ignored this process and since most studies of anaerobic

CH4 fluxes are studied in vitro in incubations without added CH4, where this was not readily

apparent (not possible to differentiate from CH4 production rate). However, what is consistent

with this process being ignored/undiscovered is the very poor correlations between rates of CH4

production and aerobic oxidization (i.e. as governed by the water table position) and CH4

emissions. Smemo and Yavitt (2007) were the first to present evidence of AOM in peatlands,

where they reported a mean AOM rate of 17 ± 2.6 nmol kg-1

s-1

based primarily on data collected

from 4 sites using isotope dilution techniques and methanogenic inhibitors. Later in a

perspectives paper they conservatively estimated that AOM in peatlands is responsible for

consuming 41 Tg of CH4 per year globally (Smemo and Yavitt, 2011); almost equalling the net

global CH4 efflux estimates of 38 Tg CH4 per year from wetlands (Bartlett and Harriss, 1993).

However, the stable isotope dilution technique utilized, was still a very indirect way of

measuring AOM and has some key limitations (von Fischer and Hedin, 2002). My work used a

more direct approach (13

CH4 conversion to 13

CO2, and assimilation of 13

C in peat) to study and

measure rates of AOM. This combined with having studied 15 peatlands representing different

site types and spanning across ~1500 km greatly increases the potential to accurately determine

the rates and the significance of AOM in reducing the net atmospheric CH4 burden of these sites.

66

5.2 Anaerobic CH4 oxidation to CO2

The first objective of this research was to quantity rates and to determine the biogeochemical

significance of AOM across 15 different peatlands in North America. It was hypothesized that

AOM is a ubiquitous process across the latitudinal gradient.

I was able to demonstrate the occurrence of AOM along with some characteristics of the

temporal variability of AOM rates over the 40 day incubation. As hypothesized, AOM was

indeed a ubiquitous process across the latitudinal gradient, and this observation was in agreement

with Smemo and Yavitt (2007). However, AOM rates did not correlate with latitude or coarse-

level climate attributes. I expected to observe a negative relationship with increasing latitude and

AOM rate, based on the affect of the climatic (temperature) gradient on microbial activity.

Smemo (2003) and Hoehler et al. (1994) have reported that AOM is temperature sensitive, with

~ 25 oC as the optimum temperature. Perhaps the reason I failed to see any relationship in this

study was because all of the incubations were conducted at the room temperature (~20 oC), and

either microbial communities responsible for AOM do not differ latitudinally or they had time to

adjust and respond to standardized conditions over the course of the incubations. However, it

should be taken into account that samples were collected during different seasons, for example,

samples from Southern peatlands were collected during the summer, while samples from

Northern peatlands (James Bay Lowlands) were collected during the fall. This could cause

changes in the “starting” community composition, which could then affect AOM rate.

The logic behind using stable C isotope tracer techniques, to measure AOM was as follows: if

AOM was occurring in peat, then microbes responsible for the process would utilize labelled

13CH4, and produce

13CO2.

13CO2 would then be trapped as barium carbonate and analyzed for

13C/

12C ratio (written as

13C AP). However, there were two other possible ways through which

67

13CO2 could have accumulated in the headspace, where AOM was not the source process. First,

bacteria decomposing peat could have produced isotopically heavier 13

CO2 through selective

breakdown of naturally abundant 13

C compounds. However this is generally not observed in

heterotrophic mineralization of soil organic matter. Second, isotopic fractionation, also known as

Rayleigh distillation (Hoefs, 1997), where heavier isotopes accumulate over time due to

preferential utilization of the lighter isotope could occur. It is generally known that methanogens

in particular discriminate against 13

C over 12

C compounds, including the reduction of CO2. CO2-

reducing methanogens are known to occupy at least 6 of the sites studied (Basiliko et al., 2003;

Dettling et al., 2006; Godin et al., in review). Although changes in this background 13

CO2

signature were accounted for by subtracting 13

C AP values from the N2 addition flasks on a “site

at a given measurement time” basis, no statistically significant selective isotopic fractionation

was observed between the 13

CO2 AP of the incubations that received 12

CH4 or N2 as headspace

gas (Figure 4.1-2). Therefore, increased 13

CO2 in the headspace of the incubations that received

13CH4 additions, could have come from the oxidation of CH4 under anaerobic conditions.

Furthermore, 13

CO2 AP of 13

CH4 addition incubation increased over the 40 day period (Figure

4.1-3), illustrating that the process was real and could be sustained over moderate periods of

time.

Per my initial hypothesis, I found that quantitatively, AOM was a far more rapid process in fens

than bogs, which suggests that greater base cation availability and supply of nutrients from

groundwater could lead to a greater supply of elements that could potentially serve as an electron

acceptors and perhaps sustain AOM at higher rates in fens. However, when rich fens vs

intermediate/poor fens were compared, my hypothesis involving greater nutrient availability did

not hold true. For instance, by day 20, the 5A‟ Fen had the fastest rate of AOM. This site had a

pH of 4.28, dominated by Scorpidium limpr, Larix laricina and Carex lacustris L, while its

68

trophic status would be classified as an intermediate fen. Michigan Hollow, with the highest

measured pH (up to 7.5 in other publications) which would clearly be classified as a rich fen

(Smemo and Yavitt, 2007) had rates of AOM of only ~1/10th

those of 5A‟ Fen.

Interestingly, Smemo and Yaviit (2007) arrived at a similar conclusion from their study of four

peatlands using 13

CH4 dilution techniques: where AOM was more important in minerotrophic

systems than oligotrophic systems, but also did not find linear patterns regarding peatland trophic

status or nutrient availability and AOM rates. There was significant difference between the AOM

rate calculated in this study and by Smemo and Yavitt (2007). On average, I reported AOM rates

of ~1.5 nmol C kg-1

s-1

, with a maximum rate of 7.09 nmol C kg-1

s-1

, compared to average rates

reported by Smemo and Yavitt (2007) of 17 nmol C kg-1

s-1

, with a maximum rate of up to 176

nmol C kg-1

s-1

.

This “order of magnitude” difference in reported AOM rates (including between 2 of the same

sites) might have occurred for several reasons. First, as noted by Smemo and Yavitt (2007), there

were important differences in AOM rates depending on when and where peat samples were

collected (summer vs fall; depth; proximity to groundwater and nutrient source). In addition,

they utilized stable isotope dilution techniques to calculate AOM rates. This technique was

created to calculate aerobic CH4 oxidation, not AOM, as it assumes a first order kinetic principle

and could not account for AOM being conducted via syntrophic association (as likely occurs in

marine systems). Syntrophic associations require a multitude of conditions (such as common

substrate limitation by H2, SO4, etc) that allow multiple microbial taxa to work together in a

consortium. Such situations are very hard to take into account due to dynamic and heterogeneous

environment of peatlands. Furthermore, this model assumes a 1:1 correlation with amount of

CH4 present, and the amount of CH4 consumed through AOM; which has yet to be

69

experimentally confirmed. Another point to note is that, I did study their most active

minerotrophic peatland, Michigan Hollow, on two separate occasions, but I did not observe

AOM rates in the range of their reported rates (Figure 4.1-3 and Figure 4.2-2). However, this

difference could stem from spatial and temporal variability, where two sampling times were most

likely not sufficient to conclude that there are inherent differences between the two techniques.

Nevertheless, I believe that the technique which I am utilizing is an improvement over Smemo

and Yavitt‟s technique, and rates reported here better reflect the true magnitude of AOM.

5.3 13

C assimilation in peat

The second objective of this research was to determine if AOM involves anabolic assimilation of

C derived from CH4 oxidized in microbial biomass, where it was hypothesized that microbial

communities responsible for AOM would assimilate some 13

C from oxidizing 13

CH4 in their

biomass.

The 13

C content of peat was measured at all three time intervals. Literature from studies in

marine environments have reported that bacterial and archaeal communities responsible for

AOM have a tendency to assimilate some C derived from oxidized CH4 to build their biomass.

There were two main ways through which researchers have measured this. First by analyzing

naturally depleted 13

C bacterial and archaeal lipid biomarkers (in un-13

C-amended environments)

or 13

C enriched lipid biomarkers (in lab based, manipulated experiments). Isotopically (13

C)

depleted lipid biomarkers have been extensively studied to support AOM since CH4 is

isotopically light (highly enriched with 12

CH4), with values ranging from δ 13

C -50‰ to δ -90‰

relative to the VPDB standard (Valentine and Reeburgh. 2000). Consequently, mechanisms that

were involved in CH4 oxidation yielded catabolic and anabolic products that were also depleted

70

in 13

C (Valentine and Reeburgh. 2000). Therefore, if the observed lipids were isotopically light,

it has been inferred that the CH4-derived C was assimilated by organisms involved in AOM,

which then produced these lipids. These lipid biomarkers were depleted in 13

C in a range from

δ13

C -65‰ (Pancost et al., 2000) to δ13

C -110‰ (Hinrichs et al., 1999). Second, in the laboratory

experiments, when 13

CH4 was provided, those same bacterial and archaeal lipids were highly

enriched, some up to δ +4400 ‰ (Raghoebarsing et al., 2006), a clear confirmation that they

were utilizing C derived from CH4.

However considering that there had been no prior precedent of investigating microbes

responsible for AOM in peatlands, and that only indirect techniques had been used to calculate

the first reports of AOM rates , it was premature to delve into a a biomarker SIP study. Despite

having prior experience with SIP techniques for phylogenetically identifying active organisms

involved in peatland CH4 cycling (Gupta et al., in press), I decided to investigate bulk

assimilation of 13

C in organic matter (which presumably could only enter through the microbial

community) derived from 13

CH4 by measuring total 13

C content in the organic C of peat.

However, since this technique tracked changes in the 13

C content of all the peat, not just the

microbial biomass, even a small difference (δ -26‰ vs δ -18‰ VPDB) represented significant

enrichment, consistent with the microbial biomass C pool making up only a small fraction of the

total organic C in peat, and presumably the community responsible for AOM making up a small

fraction of the total microbial biomass.

Given that AOM consortia have a growth rate of 0.003 day-1

or doubling time of approximately 7

months (Nauhaus et al., 2007), it was not surprising that peat did not show significant 13

C

enrichment in the peat organic phase by day 3, and that peat from six sites never showed

significant enrichment during the course of a 40 day incubation. Nevertheless, nine peatlands

71

did show small, but significant 13

C enrichment (up to 5.96 ± 3.37 nmol C/kg-1

sec-1

in Bog Lake

Fen at day 40). In contrast to 13

CO2 produced through AOM, bogs and fens were equally likely

to assimilate some 13

C and had similar rate of 13

C assimilation in the biomass. This suggested

that microbial communities in bogs preferred to assimilate C from CH4 oxidized to build their

biomass, indicating that in bogs, which have known nutrient limitations, microbial communities

are starved and hence are more likely to utilize C to repair and build their biomass, and then use

remaining C to gain energy. Therefore microbial communities in fens and bogs might have

different strategies to utilize with C derived from AOM.

Given the gap in the data with 6 sites not illustrating significant assimilation over the 40 day

incubations, no further correlation analyses were conducted. Regardless of this, my initial

hypothesis of anabolic assimilation in the microbial biomass stands, and this was a significant

achievement, since this represents the first study to conclude that the assimilation pathway does

exist in peatlands. Consequently, this opens up a plethora of future research, possibly leading to

identification of microbial communities responsible for AOM in peatland using DNA-SIP, a

technique that was recently used to identify active aerobic methanotrophs in N. American

peatlands (Gupta et al., in press).

72

5.4 Potential chemical/substrate control on AOM

The third objective of this research was to identify potential control on this process using

correlations with latitude, site type, trophic status and physiochemical properties, where it was

hypothesized that fens would have faster AOM than bogs.

Many variables were tested as potential controls on AOM in peatlands such as inorganic ion

concentrations and pH in pore water, latitude and trophic status as indicated by vegetation and

physicochemical properties. My initial hypothesis stated that there would be a positive

correlation with certain ion concentrations, especially NO3 and Fe (III); the two main purported

electron acceptors for AOM in freshwater ecosystems. However, I found that there was no strong

relationship between ion concentrations and AOM rates (Figure 4.1-6). SO4 showed some

correlation with AOM rate (r2 = 0.4383), that indicated that it might be involved, however it

seemed to be driven by one site in particular (p-value = 0.13), namely 5A‟ Fen, that had highest

AOM rate and highest SO4 concentration in porewater. Furthermore, it should be accounted that

ion concentrations for some peatlands were obtained from previously published literature, and

that the concentrations could be affected by temporal and spatial variability of porewater

collection. The reason I did not measure porewater ion concentrations for all sites myself was

because this objective was conceived after I had collected peat samples from some sites.

In addition, no general pattern of AOM rates changing with trophic status in peatlands was

evident. Nevertheless, AOM rates clustered with pH, where acidic pH (< 4.2) led to earlier

peaking of AOM rates over the course of the incubations, while higher pH (> 4.2) led to AOM

rates that peaked later (at day 20 or 40). This was perplexing since high and low pH generally

relates to fen versus bog and nutrient/ion-rich versus nutrient/ion-poor ecosystems; but I failed to

see a direct relationship with the latter two. Given the number of pathways suggested for AOM

73

and particularly that the pathways appear to differ from one ecosystem type to another, it is

possible that AOM in peatlands utilizes a unique pathway, such as oxidized humic acids as redox

substrate, which can be readily available in this ecosystem and have been shown to play a key

but poorly known role in anaerobic respiration through the recycling of inorganic electron

acceptors (Keller et al., 2009). This deserves further attention where differences in humic acids

availability should be studied in bogs and fens, along with the affect of pH on the availability in

peatlands.

This leads into the fourth objective of this research, which was to identify the electron

acceptor(s) sustaining AOM in a rich fen. To further substantiate the above claim, the electron

acceptor amendments using Michigan Hollow peat, also pointed to the same conclusion. I

initially hypothesized that the addition of NO3 or Fe (III) would stimulate AOM in peatlands.

However, addition of potential electron acceptors inhibited AOM and stimulated net CH4

production. Addition of SO4, NO3 and Fe (III) resulted in less enrichment of 13

CO2 in the

headspace, while the control treatment (no electron acceptor) had the highest amount of 13

CO2 in

the headspace. This finding was contrary to numerous studies from marine and freshwater

aquatic environments. In marine systems, AOM is strongly linked with SO4 reduction, so

availability of SO4 is essential (Valentine, 2002), while in freshwater lake sediments, AOM has

been linked with NO2 and NO3 (Raghoebarsing et al., 2006), and recently Beal et al. (2009)

linked AOM with Fe in marine systems. In addition, Smemo and Yavitt (2007 and 2011) also

suggested NO3 and Fe (III) could act as the electron acceptor in peatlands supporting AOM.

Thermodynamically, all of the above electron acceptors are energetically favourable, but perhaps

the correct question to ask was, were these electron acceptors even available in peatlands?

74

SO4 dependant AOM (in consortium with SRB) was the least energetically profitable potential

electron acceptor. SO4 is present in some peatlands where acid deposition acts as a major input

(Gauci et al., 2005; Wieder et al., 1992), and even in the present study, thirteen out of fifteen

peatlands had some SO4 (ranging from 20 – 407 μeq.L-1

) present in porewaters. Theoretically,

SO4 concentrations in most peatlands were deemed to be insufficient for SRB to be fully

functional (Wieder and Lang, 1988). In addition, when SO4 was added to a microcosm

experiment, significant reduction in net CH4 flux was noted (Smemo and Yavitt, 2007), however

this could have been a result of methanogenesis inhibition by SRB though competition for

substrate, though I did not notice any reduction in net CH4 flux in my amendment studies (Figure

4.2-1). Nevertheless, Smemo and Yavitt (2007) speculated that even a small amount of SO4

could conduct significant AOM by repeated oxidation and reduction between near oxic/anoxic

interfaces. Essentially, reduced S could be oxidized in aerobic conditions and then reduced in

anaerobic conditions, the latter while driving AOM.

Peatlands are generally very low in NO3 concentrations and vegetation is typically N limited in

oligotrophic sites, due to slow nitrification rates under acidic conditions or low NH4+ availability

(Westbrook et al., 2006) because available NO3 is quickly utilized for denitrification (Gorham et

al., 1985). Seasonal increases in NO3 concentration have been noted in peatlands

(Schmalenberger et al., 2007), but often this is short lived even under aerobic conditions in

surface peat as NO3 is also readily used by plants (Moore et al., 2005). Even in this study, nine

peatlands showed detectable levels of NO3/NO2with concentrations ranging from 2 – 16 μeq.L-1

.

A sizable quantity of Fe does exist in peatlands, but the readily useable form for anaerobic

metabolism, amorphous Fe (III) oxide, exists in very small concentrations (Blodau et al., 2002).

75

Michigan Hollow was a rare exception, where Fe often flocculates in the surface water, but in

this site, potential electron acceptor amendments did not cause AOM to increase.

I reckon that the situation of AOM in peatlands and proposed electron acceptor(s) represent a

“Catch-22”: CH4 production typically occurs in environments where other electron acceptors

(SO4, NO3, Fe(III)) have become reduced. However, if AOM also requires those same electron

acceptor(s), AOM would be limited by lack of CH4 substrate, since presence of those electron

acceptors would exclude CH4 production. The reason SO4, NO3, and/or Fe (III) could support

AOM in marine/freshwater lake environments is that there exists a large spatial divide between

where CH4 is produced and oxidized. CH4 is produced in the deeper sediments and subsequently

it starts to diffuse upwards in the sediment column where availability of electron acceptors in the

upper portion of the sediment column also increases (near the sediment-water interface). This

therefore provide microbes a spatial and temporal divide to act on CH4. Now, comparing this

scenario with peatlands, CH4 is produced below the water table, which then starts to diffuse

upwards, and eventually reaches the aerobic phase of the peatland and is consumed via aerobic

methane oxidation. The spatial and temporal divide in peatlands is not well defined and is quite

dynamic over time. Therefore, in peatlands, AOM and methanogenesis must coexist, and

according to Smemo and Yavitt (2007), this is feasible. Hence, using this logic, one can argue

that in peatlands, SO4, NO3 and Fe might not be the terminal electron acceptors driving AOM.

Also since no correlation with these ions was observed and the electron acceptor amendment

study did not stimulate AOM this leads me to speculate that humic acids or other organic

electron acceptors might be responsible for AOM in peatlands and this opens a new avenue of

future research.

76

5.5 Relevance of AOM in peatlands

AOM can consume a significant proportion of the amount of gross CH4 production in peatlands.

At day 20, AOM consumed anywhere from 2.5% to 115.6% of gross CH4 production over the

same time period by the same peat (Table 4.1-2), and overall averaged ~17%. Day 40 was

considerably lower, but that could have been due to substrate limitation (incubations remained

anoxic during the course of the incubation which could have led to a depletion in electron

acceptors). This represents a significant portion of gross CH4 production that is virtually always

underestimated in other studies; and which could be released to the atmosphere if environmental

factors change and lead to reduction in rates. AOM has been a known CH4 sink in marine

environments, consuming about 70 Tg to 300 Tg CH4 per year. Therefore, to truly appreciate

AOM in peatlands, one must be able to characterize its role on global scales. However, scaling

up is very tricky and potentially inaccurate, since most laboratory experiments do not reflect real

environmental conditions and changes in microbial communities have been known to occur

under these conditions (Liesack et al., 2000). Keeping this in mind, I followed Smemo and

Yavitt‟s (2011) exercise in calculating annual CH4 consumption by AOM. By averaging day 20

and day 40 AOM rates from both headspace and 13

C solid phase assimilation, an AOM rate of

2.9 nmol kg-1

s-1

was calculated. This rate was assumed to be an average for peatlands between 50

and 70o N (area = 2.65 x 10

12 m

2), a peat bulk density of 0.1 g cm

-3, and 3 months of AOM active

period each year in 50% of the top 50 cm of peat (Smemo and Yavitt, 2011). According to this

calculation, northern peatlands could consume ~24 Tg of CH4 on average each year via AOM.

Though this number is smaller than Smemo and Yavitt (2011), where they estimated about 41 Tg

of CH4, the present study much better reflects the true impact of AOM due to more appropriate

and direct methodological approaches and a broader and more representative set of peatlands

studied.

77

Nevertheless there were some methodological considerations that must be noted. First,

composite peat samples, for each site were used in the experiment in controlled in vitro

conditions that likely do not represent in situ conditions. Furthermore, it is possible that AOM

might be limited by CH4 diffusion across the gas to liquid/peat interface. Were this true, the cross

sectional area of the incubation vessel could influence observed rates of AOM. Nevertheless,

conditions were standardized across all samples/sites so this does not deter from my main

conclusions, and this implication could, in principle, only lead to the underestimation of the

reported AOM rates

6

78

Chapter 6: Conclusions and future studies

6.1 Conclusions

This thesis furthers our understanding of the importance of AOM in peatlands with isotope tracer

techniques using an ecologically and spatially diverse and globally relevant set of sites. The

following section summarizes the findings for each of the four objectives set out in the thesis and

then directs key future research.

Objective 1: Quantify the rates and biogeochemical significance of AOM across 15 peatlands in

N America.

It was determined that AOM was a ubiquitous process in N American peatlands. AOM rates

ranged from 0.28 ± 0.03 to 7.09 ± 5.16 nmol C kg-1

s-1

, with fens being faster than bogs. On a

global scale, AOM can consume up to ~24 Tg of CH4 annually in peatlands, which has a global

warming potential equivalent to more than 0.5Gt of CO2 in the atmosphere over 100 years,

clearly signifying the importance of this process.

Objective 2: Determine if AOM involves anabolic assimilation of CH4-C in microbial biomass

Nine peatlands showed significant enrichment in the organic C of the bulk peat, which indicated

that microbes responsible for AOM can assimilate at least some C from CH4 they oxidize. Rates

of assimilation ranged from 0.21 ± 0.04 to 5.96 ± 3.37 nmol C kg-1

s-1

, almost on par with AOM

rates calculated from the headspace calculation.

79

Objective 3: Identify potential controls on the process using correlations with latitude/climate,

site type and trophic statue, and site physicochemical properties

AOM rates only broadly correlated with site type: fens vs bogs, where fens had faster rates.

Other than this, no correlations with latitude, trophic state, or porewater ion concentrations were

observed.

Objective 4: Identify the electron acceptor(s) sustaining AOM in a rich fen where Smemo and

Yavitt (2007) worked prior through the addition of potential electron acceptors under controlled

conditions.

I failed to determine which electron acceptor was potentially facilitating AOM. All three electron

acceptor studied, SO4, NO3, and Fe (III) actually suppressed AOM, compared to the incubations

that received no potential electron acceptors. This led me to formulate the hypothesis to test in

the future that an internal electron acceptor, possibly humic acids are involved in AOM.

6.2 Future studies

In many aspects, this study lays groundwork for expanding research of AOM in peatlands. I

recommend that two peatlands should be studied more closely to better understand AOM: 5A‟

Fen and Bog Lake Fen, since they had the fastest AOM rate and the fastest 13

C assimilation in

peat, respectively. In addition, humic acids should be tested as potential electron acceptors in

controlled microcosm experiments and dissolved organic carbon (DOC) and DOC chemistry

should be measured as a physiochemical indicator and potential control on AOM.

80

Experiments simulating different temperatures and samples from varying depth also should be

carried out. My work has demonstrated the potential importance of AOM, but controlling

variables do need to be established (beyond just knowing average rates of a large mixed horizon

of peat under strict anoxia and at laboratory temperatures) that could be used to improve process-

based CH4 emission models (which are notoriously inaccurate by orders of magnitude (Mathews

2000), perhaps in part due to a lack of inclusion of AOM processes).

Lastly, since I established that 13

C assimilation from CH4 was occurring, subsequent studies

using DNA-SIP or RNA-SIP to label and identify putative microbes responsible for AOM should

be carried out, followed by targeted cultivation, enrichment, and isolation of organism(s)

involved.

81

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Appendix 1: Carbonates solutions

Calculation for:

0.1 M NaOH

FW = 40 g/mol

40 g/mol X 0.1 mol/L X 0.25 L = 1.00 grams

Add 1.00 grams of NaOH in 200 ml DDI water, mix, and then fill the water up to 250 ml mark.

0.1 M BaCl2

FW = 244.28 g/mol

244.28 g/mol X 0.1 mol/L X 0.25 L = 6.107 grams

Add 6.107 grams of BaCl2 in 200 ml DDI water, mix, and then fill the water up to 250 ml mark.

For 0.2 M solutions, twice the calculated amount of NaOH and BaCl2 was used.

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Appendix 2: Electron acceptor solutions

Calculation for:

For Nitrate

Calcium nitrate: Ca(NO3)2 . H2O

F.W. = 236.15 g/mol

Concentration = 2.1 mM of NO3

Volume = 0.5 L

236.15 g/mol X 2.1 mM X 0.5 L

= 0.24785 grams

Per mol of NO3 = 0.24785 grams / 2

= 0.12397 grams

Add 0.12397 grams to 300 ml of DDI water and bring the final volume to 500ml

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For Sulfate

Sodium Sulfate anhydrous: Na2SO4

F.W. = 142.04 g/mol

Concentration = 2.1 mM of SO3

Volume = 0.5 L

142.04 g/mol X 2.1 mM X 0.5 L

= 0.14914 grams

Add 0.14914 grams to 300 ml of DDI water and bring the final volume to 500ml

For Iron

Ferric hydroxide: Fe(OH)3

F.W. = 106.869 g/mol

Concentration = 4.2 mM of Fe

Volume = 0.1 L

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106.869 g/mol X 4.2 mM X 0.1L = 0.044884 grams of dried Fe(OH)3

Need to know the wet weight of Fe(OH)3 to be added:

Dried 0.0205g of liquid Fe(OH)3 in oven

Dry weight = 0.0008 grams

0.0205/0.0008 = X/0.044884

X = 1.1501 grams

Thus, add 1.11501 grams of liquid Fe(OH)3 and raise the volume to 100ml with DDI water.