Streambed organic matter controls on carbon dioxide and methane

Subscriber access provided by University of Winnipeg Library

Environmental Processes

Streambed organic matter controls on carbon dioxide and methane emissions from streams Paul Romeijn, Sophie A Comer-Warner, Sami Ullah, David Hannah, and Stefan Krause Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b04243 • Publication Date (Web): 29 Jan 2019 Downloaded from http://pubs.acs.org on January 30, 2019

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 40

Environmental Science & Technology

1

Streambed organic matter controls on carbon

2

dioxide and methane emissions from streams

3

Paul Romeijn‡,*, Sophie A. Comer-Warner‡, Sami Ullah, David M. Hannah, Stefan Krause

4

University of Birmingham, School of Geography, Earth and Environmental Sciences,

5

Edgbaston, Birmingham B15 2TT, United Kingdom

6

KEYWORDS: Earth and environmental sciences; biogeochemistry; carbon cycle; ecology;

7

freshwater ecology; microbial ecology, greenhouse gas, carbon dioxide, methane.

8

Abstract art

9 10 11 12

ACS Paragon Plus Environment


13

Abstract

14

Greenhouse gas (GHG) emissions of carbon dioxide (CO2) and methane (CH4) from

15

streambeds are currently understudied. There is a paucity of research exploring organic

16

matter (OM) controls on GHG production by microbial metabolic activity in streambeds,

17

which is a major knowledge gap given the increased inputs of allochthonous carbon to

18

streams, especially in agricultural catchments. This study aims to contribute to closing this

19

knowledge gap by quantifying how contrasting OM contents in different sediments affect

20

streambed GHG production and associated microbial metabolic activity. We demonstrate, by

21

means of an incubation experiment, that streambed sediments have the potential to produce

22

substantial amounts of GHG, controlled by sediment OM quantity and quality. We observed

23

streambed CO2 production rates that can account for 35% of total stream evasion estimated in

24

previous studies, ranging between 1.4% and 86% under optimal conditions. Methane

25

production varied stronger than CO2 between different geologic backgrounds, suggesting OM

26

quality controls between streambed sediments. Moreover, our results indicate that streambed

27

sediments may produce much more CO2 than quantified to date, depending on the quantity

28

and quality of the organic matter, which has direct implications for global estimates of C

29

fluxes in stream ecosystems.

30

Introduction

31

River corridors, and in particular near the interface between groundwater and surface water,

32

provide crucial ecosystem functions such as nutrient spiralling, pollutant attenuation,

33

organism distribution and fish spawning.1–8 In terms of biogeochemical functions, freshwater

34

sediments at groundwater-surface water interfaces in streambeds have been identified as

35

significant contributors to both the global carbon (C) cycle and GHG production.9–16


Page 2 of 40

Page 3 of 40


36

Streambed and river C cycling is strongly affected by the composition and turnover of

37

organic matter (OM) in these environments.3,6,9,15,16 Despite early findings in forest streams

38

that streambed sediment OM can be an important driver in sediment respiration,9 GHG

39

production as a result of aerobic or anaerobic respiration in streambed sediments has

40

remained understudied in nutrient-rich, agricultural, lowland streams.17–22 Enhanced nutrient

41

and C loads (and often larger streambed residence time) in lowland agricultural streams offer

42

the potential to significantly alter aquatic ecosystems worldwide,23–25 most critically by

43

increasing GHG production.20,26–29

44

The drivers and controls of GHG emissions from agricultural streams less than 100 m wide,

45

and in particular those less than 10 m wide, draining nutrient-enriched catchments remain

46

unknown,30–32 despite these systems showing some of the highest CO216,22 and CH426,33

47

outgassing per surface area. One reason for this is the limited knowledge of the impacts of

48

heterogeneous spatial patterns in geologies, streambed substrates and, in turn, sediment

49

chemical conditions.34–37 Microbial communities in the streambed vary strongly between

50

different substrates,38–41 along the river length11,42 and with surrounding land use,43

51

suggesting spatially heterogeneous patterns in GHG production. Streambed CO2 production

52

is generally associated with aerobic microbial metabolic activity (MMA) as it is a product of

53

the breakdown of organic matter.10,44 CH4 production is typically associated with anaerobic

54

fermentation of organic matter by methanogenic archaea in areas with relatively finer

55

sediment types.45–47 Aerobic CO2 and anaerobic CH4 production may occur simultaneously in

56

the streambed in discrete micro-zones, therefore, CH4 production is not strictly limited to

57

completely anaerobic events if anaerobic micro-zones are present.46 Understanding the

58

relevance and spatial patterns of GHG production from lowland river streambeds requires

59

consideration of variability in OM quantity (as prime control of lowland river respiration

60

processes) as well as the quality of the OM (as control for OM turnover efficiency).



61

Sources of OM in streambed sediments range from agricultural erosion to local primary

62

production within the stream channel,48–52 all of which vary in OM quality. Therefore C

63

contents of streambed sediments are likely to reflect that of the surrounding erosional

64

surfaces.49,53 Signatures of the underlying geology are found in stream particulate organic

65

matter and dissolved organic matter from the headwater to the river mouth.39,54 There is

66

evidence that catchment geology plays an important role in river nutrient turnover55,56, and

67

ecohydrological and hydrogeological properties.57,58 The potential of microbial respiration

68

and associated GHG production in soil sediments has previously been studied in detail in

69

many contexts, investigating nutrient cycling,59–61 organic matter decomposition,62 influence

70

of water content63,64 and contaminants65 using batch incubation experiments. For streambed

71

sediments, however, incubation studies have not been widely applied,66 despite possible

72

advantages of studying respiration under controlled versus field conditions. Although thermal

73

sensitivity of streambed GHG production varies between sediments from different geologies,

74

there is poor understanding of OM controls on streambed MMA, GHG production and the

75

role of OM quantity and quality.29 Given 0.47% of the Earth’s surface area is covered by

76

streams,30 it is important to quantify the contribution of GHG production from whole stream

77

ecosystems, including under-researched streambed sediments.

78

In this context, this paper aims to quantify CO2 and CH4 (GHG) production from lowland

79

streambed sediments across a gradient of streambed OM contents and different catchment

80

geological backgrounds, focussing on sandstone and chalk. Production of CO2 and CH4 was

81

measured alongside aerobic MMA in microcosms containing six different sediment types of

82

varying OM content from UK lowland streams underlain by chalk or sandstone.


Page 4 of 40

Page 5 of 40

83 84


Materials and Methods Streambed sediments were incubated under controlled conditions. Rather than directly

85

measuring C cycling and GHG production, previous studies considered total stream

86

evasion,20,22,52 or indirectly calculated CO2 approaches,30 which may be sensitive to

87

overestimation or underestimation.70 Furthermore, field measurements are challenged by the

88

difficulty of isolating the governing processes and drivers.

89

90 91

Figure 1. Sampling location of sediments used in the microcosm incubations (left). The

92

River Tern is in a sandstone catchment and the River Lambourn in a chalk catchment. An

93

example of a microcosm is shown (right), indicating the experimental setup (photograph

94

taken by authors). Map contains data from the British Geological Survey (copyright NERC,

95

2016) and gadm.org.



96

Streambed sediments

97

Sediments used in microcosm incubations were collected from two rivers with contrasting

98

geological substrates:71 River Lambourn and River Tern (Fig. 1; Table S1). Both rivers are in

99

agricultural catchment areas with similar discharge.72 Three locations were chosen within

100

each river based on estimated OM content to achieve a gradient (fine sediment under

101

vegetation, non-vegetated armoured streambed and non-vegetated sand-dominated straight

102

channel section). The total of six field-wet sediment types (Table 1) was collected in

103

September 2015 by scooping off the top 10 cm of the streambed. Bulk sediments were

104

sieved: fine sediments from under vegetation (ChalkHigh and SandstoneHigh) at 0.8 cm to clear

105

large organic debris and the others at 1.6 cm, homogenised, and stored airtight for five weeks

106

in the dark at 4.4±0.8°C until start of the experiments. Sieving is not expected to have a major

107

influence on the results as previous studies show microbial metabolic activity is expected to

108

be similar or slightly lower after sediment disturbance such as sieving compared to in situ

109

measurements.73–75 The sieving sizes were chosen to preserve as much of the size

110

characteristics present in the field, while removing larger stones and debris that would

111

otherwise occupy a disproportionally large volume inside the mesocosms. The storage

112

temperature was monitored using a Tinytag Aquatic 2 temperature logger (Gemini Data

113

Loggers Ltd, Chichester, United Kingdom).

114 115

Table 1. OM content, carbonate content and specific ultraviolet absorption at 254 and 280

116

nm (SUVA), as measured from the bulk sediment. The new sediment name has been chosen

117

to reflect actual OM content and varies between chalk and sandstone sediments. Sediment

118

names are abbreviated in figures (abbreviations in brackets). Mean values listed with SD and

119

n=3.


Page 6 of 40

Page 7 of 40


Geological background

Sediment origin

Sediment name

%OM

%carbonate

SUVA (l mg-1 m-1)

Chalk

Under vegetation

ChalkHigh (CH)

3.625±0.069

11.620±0.499

2.098±0.180

Straight section, no vegetation

ChalkMedium (CM)

1.847±0.063

18.668±1.423

1.277±0.109

Gravel section

ChalkLow (CL)

1.409±0.047

17.170±2.259

1.498±0.092

Under vegetation

SandstoneHigh (SH)

3.616±0.116

0.357±0.017

2.642±0.511

Gravel section

SandstoneMedium (SM)

0.838±0.031

0.234±0.016

1.813±0.252

Straight section, no vegetation

SandstoneLow (SL)

0.667±0.014

0.253±0.028

3.209±0.263

Sandstone

120 121

Organic matter content was determined by loss on ignition (LOI). Samples were prepared

122

in triplicate for each sediment type (low, medium and high for both chalk and sandstone).

123

Sediment was milled, sieved (2 mm), homogenised and dried at 105°C for at least 12 hours.

124

LOI was performed using an oven at 550°C for 6 hours.76 Carbonate content was then

125

determined using the same oven at a temperature of 950°C for 6 hours.76 Weight loss relative

126

to original dry sample weight was measured immediately to prevent ambient moisture uptake

127

and then used as the fraction of OM or carbonate.

128

OM quality was measured by taking sieved sediments (2 mm) in triplicate and extracting

129

DOC from the sediments using 2M KCl.77 DOC content of sediment extracts was determined

130

using a Shimadzu TOC-L analyser (Shimadzu Corporation, Japan). The sediment extracts

131

were measured for specific ultra-violet absorption (SUVA) at 254 nm and 280 nm

132

wavelengths.78,79 Absorption was measured using a Varian Cary Eclipse UV-Vis

133

spectrophotometer (Agilent Technologies, Santa Clara, USA). A 10 mm path length quartz



134

cuvette was used, and the absorbance between 250 and 280 nm at full wavelength scanning

135

was recorded with 18.2 MΩ ultrapure water for blank correction.

136

Microcosm setup

137

Microcosms were 1 litre amber jars with 53/400 size septa-capped lids (Fisher Scientific

138

Ltd., UK). The glassware was acid-rinsed with 10% HCl before use and triple washed with

139

18.2 MΩ ultrapure water. Incubation of each sediment type was done in triplicate. Each of the

140

six sediment types were measured by wet volume using a 300 ml glass beaker and transferred

141

into the microcosms. To control for background concentrations, 500 ml ultrapure water was

142

added to the wet sediment. The headspace volume of each jar was calculated after the

143

experiment, based on total water and sediment volume. The sediments were then gently,

144

laterally shaken for 30 seconds to promote mixing of the wet sediment sample and the water

145

column. Three control treatments were prepared as three jars with 500 ml ultrapure water

146

only. The microcosms were left for 48 hours in the dark at the incubation temperature of

147

15.35±0.15°C to settle the sediment and minimise turbidity. The refrigerated incubator used

148

was a generic type with forced air circulation and no internal lights.

149

Microbial metabolic activity

150

Aerobic microbial metabolic activity (MMA) can be successfully measured using the

151

“smart” tracer resazurin. It was first used in ecohydrological applications by Haggerty et al.80

152

It proved useful in many different setups, such as reach-scale field experiments,81–85 and

153

flume-scale86 to microcosm setups.87,88 The resazurin (raz)/resorufin (rru) tracer system80 was

154

used to quantify MMA in the microcosms to be able to objectively compare activity across

155

the different sediment types. In this process, by acting as a terminal electron acceptor, raz is

156

irreversibly reduced to the strongly fluorescent rru, which can be measured using a

157

fluorometer. Two Albillia GGUN-FL30 fluorometers (Albillia SARL, Switzerland) were


Page 8 of 40

Page 9 of 40


158

used to measure rru production.89 The fluorometers were calibrated to either water extracts of

159

the sandstone or chalk at the start of the experiment to ensure best accuracy and to control for

160

variations in background fluorescence. Water extracts were sampled from the incubation jars

161

before the start of the experiment. For calibration, we used stock solutions of raz and rru

162

made up in tap water, which were diluted into final solutions of 108.67 and 95.33 ng l-1 for

163

raz and rru, using water extracts of sandstone or chalk sediments. The appropriate calibration

164

curve was applied in data analysis. The conversion of raz to rru is reported as μg rru produced

165

per μg of added raz, to normalise to slightly varying initial raz concentrations. The pH of the

166

microcosms was monitored using a handheld Hanna HI-98129 pH meter (Hanna Instruments,

167

Woonsocket, USA) to ensure pH was near 8 for accurate fluorometric detection of rru.89

168

Detection limits, calculated precision and accuracy of this type of fluorometers are listed in

169

Table S2. The target concentration of raz for the starting conditions inside the microcosms

170

was 150 ng l-1.

171

Gas sample analysis

172

Headspace gas samples were analysed on an Agilent 7890A gas chromatograph (GC),

173

equipped with a 1 ml sample loop, a platinum catalyst for CO2-to-CH4 conversion and an FID

174

for CH4 detection (Agilent Technologies, Santa Clara, USA). Samples eluted from the

175

column at: CH4 = 3.5 minutes and CO2 = 5.7 minutes, with a total run time of 7 minutes. The

176

GC was setup in splitless mode with an oven temperature of 60°C. The FID was set at 250°C,

177

H2 flow at 48 ml min-1, air flow at 500 ml min-1 and N2 make-up flow at 2 ml min-1. Samples

178

were manually injected into the sample loop using a gas-tight syringe with valve (SGE

179

Analytical Science, Australia). Detection limits, accuracy and precision for CO2 and CH4

180

were calculated by dilution of a standard gas mixture of known concentration and listed in

181

Table S3. A randomly chosen set of samples were measured twice on the GC to monitor

182

device performance as well as sampling precision.



183 184

Sampling procedure Microcosms were sampled at T = 0, 5, 10, 24 and 29 hours of the incubations to calculate

185

mean hourly rates of MMA, CO2 and CH4 production. Headspace gas concentrations were

186

measured before and after each incubation time step, to calculate the difference in

187

concentration during each time step. A 15 ml gas sample was taken using a 20 ml syringe

188

with a hypodermic needle and stopcock to pierce the septum. The syringe was purged three

189

times with ultrapure helium 5.0 (BOC Industrial gases, Manchester, UK) before each

190

sampling. The 15 ml gas sample was transferred to a 12 ml pre-evacuated Exetainer (Labco

191

Limited, Lampeter, UK), causing samples to be slightly over-pressurised. The Exetainers

192

were stored at room temperature until analysis. After headspace gas sampling the jar was

193

opened for MMA measurement.

194

Samples for fluorometric analysis of rru were extracted from the microcosms using a

195

syringe and filtered to control for turbidity using a 0.45 μm nylon syringe filter

196

(ThamesRestek, High Wycombe, UK). The filtered sample was injected directly into the

197

measurement chamber of the fluorometer and measured for at least three minutes at a 10

198

second measurement interval, which was averaged to calculate concentrations.

199

Approximately half of a randomly chosen set of samples was measured again on the second

200

fluorometer to control and correct for drift and instrument errors. Samples were transferred

201

back into the microcosm after measurement on the fluorometer to keep the volume constant

202

and the fluorometers were rinsed with ultrapure water. After fluorometric analysis the

203

headspace of the microcosm was equilibrated with ambient air, the lid was closed and a

204

headspace gas sample was taken before the microcosm was returned to the incubator. A

205

detailed description of the experimental procedure can be found in supporting information

206

text S1.


Page 10 of 40

Page 11 of 40

207 208


Statistical analysis We used descriptive statistics to compare results between sediment types. All mean values

209

listed are noted as mean±standard deviation. Error bars in figures represent one standard

210

deviation, unless stated otherwise. For bivariate analysis comparing two sediment types, data

211

were first tested for normal distribution using a Shapiro-Wilks test. A Welch’s T-test was

212

used to compare two groups of normally distributed samples and results reported as t(degrees

213

of freedom), p and sample size n. A Mann-Whitney-Wilcoxon test was used where the

214

distribution followed a nonparametric distribution with results reported as U, p and sample

215

size n. A Kruskall-Wallis test was used to compare whole geology groups, including all

216

different sediment subgroups (see supporting information). Simple linear regression was

217

applied in some cases with results reported as F(degrees of freedom), p, R2 and sample size n.

218

Experimental limitations

219

There are many variables involved in GHG production from sediment respiration. We

220

control for temperature in this experiment at 15.35±0.15°C, a temperature typical of these

221

types of streams in the UK, and hence isolate impacts of OM and geological background.

222

Although further temperature effects are out of the scope of this study, OM and geological

223

background have also been shown to affect the temperature sensitivity of streambed

224

sediments and associated GHG emissions, further underlying their importance as controls.29

225

In many natural streambed environments there will be advective processes as drivers for

226

hyporheic exchange and MMA,90–93 which we were unable to replicate in the current setup.

227

However, we acknowledge the importance of advection-driven exchange between

228

groundwater and surface water,90,91,94,95 considering that recent studies have pointed out the

229

important role of hydraulic forcing as a driver for nutrient turnover in the streambed.67,69

230

Normally, aerobic respiration starts when water enters the streambed and continues flowing

231

consistently along a flow path until dissolved oxygen is depleted, or, when water enters back



232

into the stream again.67 Therefore, the microcosm setup in this experiment best simulates a

233

stream under low flow conditions where exchange between the water column and the

234

sediment is diffusion-dominated, rather than forcing by moving water. This simplification of

235

exchange processes complicates comparison to natural streambed environments but is

236

necessary to isolate microbial activity inside the sediments itself. As we sampled undisturbed

237

headspaces of the incubated sediments, the concentration change of gases, particularly CH4,

238

represents a net flux inclusive of methanogenesis and methanotrophy, and is assumed to

239

include ebullitive events. Even under anaerobic conditions, CH4 oxidation can occur17,96 and

240

thus our measurements represent net fluxes of CH4 where positive fluxes show net emission

241

and negative fluxes show net consumption.

242

Results and Discussion

243

Sediment types are referred to by OM content (Table 1). All means are given with one

244

standard deviation, and the mean incubation temperature was 15.35±0.15°C (mean ± SD).

245

MMA was clearly detected (Fig. 2a), indicated by the conversion of raz to rru (interpreted as

246

µg rru produced per hour, normalised for initial raz concentration). CO2 and CH4 production

247

were observed in all but the control microcosms. Incubation time had no significant effect on

248

the reported rates of MMA (Fig. S1), CO2 (Fig. S2) and CH4 (Fig. S3). In general, sediments

249

with higher OM content produced more rru, CO2, and CH4, and were substantially influenced

250

by the aromaticity of the OM.

251

OM quality by aromaticity of sediment extractions varied between 1.207 and 3.469 l mg-1

252

m-1 as SUVA (Table 1). Mean aromaticity was significantly higher (t(16)=3.5546,

253

p=0.00264, n=18) in sandstone sediments (2.554±0.684 l mg-1 m-1), compared to chalk

254

sediments (1.624±0.385 l mg-1 m-1). Aromaticity and OM content were not correlated by

255

simple linear regression (F(16)=0.01309, p=0.91, R2=0.0008, n=18). This suggests that OM


Page 12 of 40

Page 13 of 40


256

in sandstone sediments is more recalcitrant and thus more difficult to metabolise by microbial

257

communities,97 while it is not simply a consequence of total OM content.

258 259

Figure 2. Mean hourly production per sediment type for a) microbial metabolic activity

260

expressed as rru production normalised for initial raz concentration, b) carbon dioxide

261

production and c) methane production. All values are mean hourly production for each

262

incubation time step. Error bars indicate standard deviation within each group (n = 12) of

263

three replicates.

264



265

MMA varied for different sediment types (Fig. 2a). Sediments with the highest OM content

266

of 3.6% were responsible for 65% of the total MMA in streambed sediments of both

267

geological backgrounds (ChalkHigh and SandstoneHigh). Overall, chalk sediments produced on

268

average 67% more rru per hour than the sandstone sediments. A generally increasing trend in

269

MMA with increasing OM content was observed (Fig. 3a). Mean hourly MMA in chalk

270

sediments was 0.00584±0.00612 µg rru hr-1 and for sandstone 0.00349±0.00492 µg rru hr-1.

271

The highest MMA was found in ChalkHigh sediments, with a mean production rate of

272

0.011±0.0078 µg rru hr-1. ChalkHigh saw 53% higher MMA than the second highest sediment

273

SandstoneHigh, which experienced production rates of 0.00721±0.0066 µg rru hr-1. ChalkHigh

274

produced 163% and 370% more rru than lower OM content sediments ChalkMedium and

275

ChalkLow, respectively. SandstoneHigh produced 262% and 463% more than SandstoneMedium

276

and SandstoneLow, respectively.

277

CO2 production followed similar patterns as observed for MMA (Fig. 2a, 2b, 3a, 3b). Mean

278

hourly CO2 production in chalk sediments was 14.97±15.54 mg C-CO2 m-2 hr-1 and for

279

sandstone 11.83±9.03 mg C-CO2 m-2 hr-1, which was 27% higher in chalk compared to

280

sandstone. Like MMA, also the highest CO2 production was found in ChalkHigh sediments,

281

with a mean of 33.40±10.55 mg C-CO2 m-2 hr-1. ChalkHigh produced 48% more CO2 than the

282

second highest sediment SandstoneHigh, which produced 22.53±7.72 mg C-CO2 m-2 hr-1.

283

ChalkHigh produced 197% more CO2 than the lower OM content sediment ChalkMedium and

284

ChalkLow produced at rates comparable to the controls (Fig. 2b). SandstoneHigh produced

285

203% and 308% more CO2 than SandstoneMedium and SandstoneLow, respectively. Sediments

286

with the highest OM content (ChalkHigh and SandstoneHigh) were responsible for 62% of total

287

CO2 production in both chalk and sandstone (Fig. 3b).


Page 14 of 40

Page 15 of 40


288 289

Figure 3. Mean hourly production per organic matter content for a) microbial metabolic

290

activity expressed as rru production normalised for initial raz concentration, b) carbon

291

dioxide production and c) methane production. Error bars indicate standard deviation within

292

each group (n = 12) of three replicates.

293 294 295

Patterns of methane production from different sediment types differed from those observed for MMA and CO2 (Fig. 2c, 3c). Overall, mean chalk sediment production was



296

0.1685±0.2503 mg C-CH4 m-2 hr-1, compared to only 0.0213±0.0365 mg C-CH4 m-2 hr-1 in

297

sandstone, 692% more CH4 in chalk compared to sandstone. Again, ChalkHigh sediment was

298

characterised by the highest CH4 production with a mean of 0.4778±0.2042 mg C-CH4 m-2 hr-

299

1.

300

produced only 0.0632±0.0369 mg C-CH4 m-2 hr-1. Compared to lower OM content sediments,

301

ChalkHigh produced 1689% more than ChalkMedium, whereas CH4 production in ChalkLow was

302

similar to that of the controls. In SandstoneMedium and SandstoneLow no difference in methane

303

production was observed compared to the controls. Sediments with the highest OM content

304

produced 95% and 100% of all methane in chalk and sandstone, respectively (Fig. 3c).

305

Methane production accounted for 1.1% of total C losses in chalk sediments, compared to

306

only 0.2% in sandstone.

ChalkHigh produced 656% more than the second highest producer SandstoneHigh, which

307

Our results highlight the substantial potential for streambed sediments from agricultural

308

lowland rivers to produce significant amounts of CO2 and CH4. We sampled only the top of

309

the streambed (see methods), although respiration can also occur at greater depths in the

310

streambed, depending on availability of OM and oxic/anoxic zonation.2,34,98,99 Especially the

311

presence of dissolved oxygen is normally driven by exchanging stream water in natural

312

streambeds (see Experimental limitations) and is an important control on MMA. Substantial

313

MMA, and CO2 and CH4 production were observed that were in a similar range to in situ

314

forest stream sediments9 and ponds,100 and lower than CO2 and CH4 production from

315

Mediterranean stream sediment incubations.66

316

MMA increased with higher OM content. Rru production was found to be linearly

317

correlated by simple linear regression with CO2 production and proved a good measure for

318

respiration (Fig. 4; F(70)=32.91, p

Streambed organic matter controls on carbon dioxide and methane

Recommend Documents