Decomposition rates and peat chemistry

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Appendix 7 of BD5104

Decomposition rates and peat chemistry

The purpose of this Appendix is to further describe the methods relating to decomposition rates within the peat

and aspects of peat chemistry determined by a variety of methods which are described in Sections 4.4.2 and 4.4.3

of the main body of the report for project BD5104. The methods summaries, results and discussions are not

repeated here but instead the full details of the methods are given. Additionally, the fitted polynomial surfaces

are given as 3D graphs for the relationship between soil moisture, temperature and decomposition carbon fluxes.

Peat sampling and incubation conditions

In March 2016, replicated peat cores (four each from the initially (2013) burnt and mown sub-catchment areas at

each site) were taken to a depth of approximately 20 cm using 10 cm diameter PVC tubes. These cores were

cleaned of surface vegetation (i.e. cut off shoots and removed green moss parts) and subsequently incubated in

the dark to minimise plant regrowth in temperature-controlled dark rooms under different conditions which were

a combination of three temperatures (mean of 4.5, 14.5 and 23ºC) and two water level regimes (0 cm (i.e. dry) or

6 cm water level). The water level (cores were placed inside buckets) was measured every week to ensure a

constant 6 cm high water level.

CO2 flux measurements

Soil respiration fluxes from each core were measured at regular intervals during the incubation period between

August and December 2016. As the living plant matter at the top of the cores had been cut away and the cores

were incubated in the dark, these measurements should largely represent heterotrophic respiration, i.e.

mineralisation of the peat by microbial activity. The net CO2 flux of all cores was measured using a Li-Cor 8100 soil

chamber which fitted onto the core sections. Individual collar offsets (i.e. distance from the peat surface to the

collar rim) were used to correct for the effective chamber volume in the Li-Cor software.

Measurements were made over approximately one minute on nine dates from August 2016 to January 2017. The

top 5 cm of each core was initially sliced off but the core sections were kept together and the top was removed

only for measurement purposes. Measurements were made in the order: whole core (0- 20 cm), top 5 cm and

then the bottom 15 cm section. However, the bottom sections were only measured three times and each time

validated the estimate obtained from subtracting of the flux of the top section from the total core. The top

section was removed for the duration of the top section measurement by the help of a perforated plastic sleeve

and was returned to the main core after measurement. At each measurement, the moisture content was

recorded using a Delta T SM200 handheld moisture probe (set to peat soil calibration). However, samples were

also weighed to calculate the amount of moisture loss over time. As there was a very good agreement between

the two methods for the top section and in comparison to field measurements, the SM200 values were used in

the analysis. However, the bottom section moisture content was based on the weight loss (as the 15 cm section

was much deeper than the SM200 probe length of about 6 cm and the core section visually dried out from the top

section).

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Figure A7.1 Soil respiration (means ±SE) for the across the three sites (n = 3) combined peat samples incubated at three

different temperatures (4ºC, 15ºC and 23ºC) and two managements (burnt, B vs. mown, M with brash left) for either the total

core (All), top 5 cm (Top) or the bottom 15 cm (Bottom). The overall number of replication was n = 3 (only the averages

across repeated measurements per treatment combination were used).

Temperature sensitivity

For the method of how temperature sensitivity (Q10) values and their standard errors (SE) were obtained, see

method outline in Appendix 6.

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5

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Burnt All Mown All Burnt Top Mown Top B Bottom M Bottom

So

il r

es

pir

ati

on

(C

O2

m-2

s-1

) 4C 15C 23C

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Polynomial regression and 3D surface graphs

A polynomial fit of logarithmic SR was obtained similar to Wang et al. (2010) for each site taking into account SM

changes over time and incubation temperature. The polynomial equations are shown below (Table A7.1).

Table A7.1 Polynomial equation coefficients for peat decomposition fluxes (similar to Wang et al., 2010) for each depth

section (the top 5 cm (TOP), bottom 15 cm (BOTTOM) and total 20 cm core (total depth)) for all sites and managements

combined and for all combinations of site (Mossdale, Nidderdale and Whitendale) and management (burnt or mown). The

full equation was ln(Cf) = I + T + SM + SM2, where Cf is the soil respiration carbon flux, I is the intercept, T is the soil

temperature and SM is the soil moisture. SM for the total core was either the SM of the top core (as is usually measured in

the field) or the weighted average of SM from the top and bottom (top-bottom) sections of the core.

All sites Equation I T SM SM2

Burnt and mown TOP of core ln(Cf) = -3.0860 0.067 0.0516 -0.000274

Burnt and mown BOTTOM of core ln(Cf) = -3.7441 0.103 0.0568 -0.000377

Burnt and mown total depth SM top ln(Cf) = -0.8856 0.082 0.0020 0.000035

Burnt and mown total depth SM top-bottom ln(Cf) = -0.9313 0.081 -0.0075 0.000133

Burnt TOP of core ln(Cf) = -2.5950 0.067 0.0296 -0.000099

Burnt BOTTOM of core ln(Cf) = -0.0402 0.108 -0.0427 0.000244

Burnt total depth SM top ln(Cf) = -0.6333 0.083 -0.0125 0.000156

Burnt total depth SM top-bottom ln(Cf) = 1.0683 0.081 -0.0596 0.000454

Mown TOP of core ln(Cf) = -3.5820 0.067 0.0725 -0.000438

Mown BOTTOM of core ln(Cf) = -9.6444 0.098 0.2035 -0.001252

Mown total depth SM top ln(Cf) = -1.1330 0.081 0.0152 -0.000073

Mown total depth SM top-bottom ln(Cf) = -3.6499 0.082 0.0606 -0.000277

Mossdale Equation I T SM SM2


Burnt and mown BOTTOM of core ln(Cf) = -5.1248 0.099 0.1030 -0.000667

Burnt and mown total depth SM top ln(Cf) = -0.3880 0.083 -0.0062 0.000084

Burnt and mown total depth SM top-bottom ln(Cf) = -1.4800 0.082 0.0194 -0.000069


Burnt BOTTOM of core ln(Cf) = -1.8600 0.100 0.0092 -0.000061


Burnt total depth SM top-bottom ln(Cf) = -0.4781 0.084 -0.0137 0.000155



Mown total depth SM top ln(Cf) = -0.4158 0.081 0.0025 0.000005


Nidderdale Equation I T SM SM2


Burnt and mown BOTTOM of core ln(Cf) = -1.5184 0.112 -0.0392 0.000351

Burnt and mown total depth SM top ln(Cf) = -1.3140 0.081 0.0077 0.000023

Burnt and mown total depth SM top-bottom ln(Cf) = -2.3709 0.083 0.0078 0.000125


Burnt BOTTOM of core ln(Cf) = 18.5820 0.115 -0.4911 0.002872





Mown total depth SM top ln(Cf) = -1.6630 0.082 0.0232 -0.000105


Whitendale Equation I T SM SM2


Burnt and mown BOTTOM of core ln(Cf) = 3.8837 0.104 -0.0918 0.000324

Burnt and mown total depth SM top ln(Cf) = -0.8395 0.083 -0.0019 0.000053

Burnt and mown total depth SM top-bottom ln(Cf) = 0.7188 0.081 -0.0444 0.000324


Burnt BOTTOM of core ln(Cf) = 13.3333 0.116 -0.3139 0.001588



mown TOP of core ln(Cf) = -2.9391 0.076 0.0446 -0.000237

mown BOTTOM of core ln(Cf) = -1.9134 0.094 0.0428 -0.000431

mown total depth SM top ln(Cf) = -0.9908 0.082 0.0068 -0.000019

mown total depth SM top-bottom ln(Cf) = -2.9016 0.081 0.0428 -0.000187

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The complete output of the interpolated 3D surface graphs (i.e. peat decomposition fluxes and their distances to

the fitted polynomial surface; similar method to Wang et al., 2010) is provided at the end of this Appendix (Figure

A7.4).

Statistical analysis

CO2 fluxes were also compared between management and temperatures using a 2-way ANOVA (after testing for

normal distribution and equal variance of the data and checking of the residuals).

Chemical analysis of peat samples

Two sets of peat samples (about 1 cm3 each) were taken from the same peat cores (as above) for chemical

analysis (Table A7.2). Set [I] was collected in July 2016, freeze dried and ground using a pestle and mortar, and

stored at -18°C prior to analysis. Set [II] was collected in October 2016, oven dried at 70°C for 48 hours and

ground using a pestle and mortar, and stored at 20°C prior to analysis. Samples which were still damp after oven

drying were also freeze dried in order to minimise thermal decomposition of the peat. For ease of identification

during analysis, each sample from set [I] and [II] was assigned a unique number. A 200 μm sieve was used to

fractionate milled samples; the fine fraction therefore represents particles <200 μm and the coarse fraction

particles >200 μm.

Table A7.2 Samples taken from peat cores for chemical analysis. The indicated sampling depths (cm) for either combined,

coarse or fine fractions in each set [I and II] are referred to in this report as 1 cm, 5 cm and 20 cm for brevity. The codes used

for the sample replicates are: first letter for either Mossdale (M), Nidderdale (N) or Whitendale (W), second letter for either

burnt control (C) or mown (M) catchment and the number indicating cores allocated to either the 5ºC, 14 ºC or 23 ºC

temperature incubation (5, 14, 23, respectively) with cores being kept either dry (d) at 0 cm or wet (w) at a 6 cm water level.

Either none (blank), one (1) or two (2) replicates were taken.

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Mass loss on ignition (LOI) was determined for each sample in set [II] via a method based on Ball et al. (1964).

Approximately 0.3 g of each sample was accurately weighed, dried, ground and heated in a muffle furnace at

550°C for 6 hours and the difference in mass was calculated.

A saccharification assay - which had been developed to assess the potential of plant biomass to be decomposed

into monosaccharides by commercially available enzymes (Gomez et al., 2010) - was performed to assess the

decomposability of the polysaccharide fraction of the peat. The saccharification potential of the peat samples in

set [II] was assessed using an automated assay developed by Gomez et al. (2010). 4 mg of dried and ground

sample was subjected to a weak alkaline pre-treatment (1 mol dm-3 NaOH, 90°C, 20 minutes), washed, then

treated with a commercial enzyme mix (Celluclast and Novozyme 188 in a 4:1 ratio, Bagsvaerd, Denmark) at 50°C

for 8 hours to hydrolyse digestible polysaccharides. The evolved monosaccharide content was then determined

via a colorimetric assay using 3-methyl-2-benzothiazolinone hydrazone (MBTH).

As crystalline cellulose quantification was performed on the samples following extraction of matrix

polysaccharides, the methods for both techniques are given here. However, the matrix polysaccharides are

discussed below (chromatographic separation of polysaccharide and lipid extracts). Due to their time consuming

nature, the lignin and cellulose analyses and matrix polysaccharide preparation were carried out in three batches

(samples 1-10, 11-41 and 42-72). A fourth batch (two sample replicates each of 1, 2, 3, 10, 13, 22, 28, 31, 32 and

33) was subsequently subjected to lignin and cellulose analysis only to assess the variability of these methods.

The concentrations of nine matrix polysaccharides (fucose, arabinose, rhamnose, galactose, glucose, mannose,

xylose, glucuronic acid and galacturonic acid) were determined according to Jones et al. (2003). 4 mg of dried and

ground sample was hydrolysed with 500 μL 2 mol dm-3 trifluoroacetic acid (TFA) under argon at 100°C for four

hours, then evaporated until dry (~2 hours). The dried samples were washed twice with 500 μL propan-2-ol, dried

by evaporation, then suspended in 200 μL purified (ELGA) water. The supernatant was filtered through 0.45 μm

PTFE membrane filters and stored at -20°C before analysis; the insoluble residue was dried by evaporation and

retained for crystalline cellulose quantification.

The concentrations of the monosaccharides were determined via high performance anion exchange

chromatography with integrated amperometry detection using a Dionex Carbopac PA-10 column and processed

using Chromeleon. The monosaccharides were quantified via external calibration using standard equimolar

mixtures of the nine sugars (0.0125 mmol dm-3, 0.025 mmol dm-3 and 0.035 mmol dm-3) which were treated with

TFA concurrently with the samples. To account for peak retention time drift over time, a set of standards was run

every twenty samples. The insoluble residue was heated with 1 mL of Updegraff reagent (8:1:2 v/v acetic

acid:65% nitric acid:ELGA water) for 30 minutes at 100°C to hydrolyse the lignin, hemicellulose and xylosans

(Updegraff, 1969) and the supernatant discarded. The pellet was washed once with 1.5 mL water and three times

with 1.5 mL acetone, discarding the supernatant each time, to remove any remaining matrix polysaccharides,

then air dried. The pellet was hydrolysed using 90 μL 72% H2SO4 at 25°C for four hours, followed by dilution with

1890 μL water to 3.2% H2SO4 and heating to 120°C for four hours.

The glucose content of the supernatant (equivalent to the crystalline cellulose content of the sample) was

determined using a colorimetric anthrone assay. The glucose concentration of the samples was determined using

an equation constructed from a standard curve of glucose samples of known concentration. A new calibration

curve was constructed for each batch of samples analysed to ensure that the standards were subjected to exactly

the same concentration of anthrone reagent and heating time as the samples. 400 μL of a 1 in 10 dilution of

sample supernatant or standard glucose solution was incubated in 800 μL 2 mg ml-1 anthrone/concentrated H2SO4

at 80°C for 30 minutes. 200 μL aliquots of the solution were transferred to a 96-well plate and the absorption

taken at 620 nm using a Tecan SunriseTM optical plate reader.

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For the quantification of lignin, an acetyl bromide soluble lignin protocol designed for plant materials was

followed (Fry, 1988; Fukushima and Hatfield, 2001). 4 mg dried and ground sample was incubated in 250 μL 25%

v/v acetyl bromide/75% glacial acetic acid at 50°C for three hours, then cooled and transferred to 5 mL volumetric

flask with 1 mL 2 mol dm-3 NaOH and 175 μL 0.5 mol dm-3 hydroxylamine HCl, and made up to 5 mL with glacial

acetic acid. The solution was homogenised and a 1 in 10 dilution made before measuring the absorption at 280

nm using a Varian Cary® 50 Bio UV-visible spectrophotometer. The acetyl bromide soluble lignin concentration

(ABSL) was determined using Eq.A7.1 with an extinction coefficient of 17.75, the standard coefficient for grasses,

as a peat specific coefficient was not known:

%ABSL = absorbance/(extinction coefficient*path length) x (total volume *100)/biomass weight Eq.A7.1

While using the coefficient for grasses will not give accurate absolute quantification, the error caused by the

inaccuracy of the coefficient should be the same for every sample, allowing comparison between samples.

NMR spectroscopy is a non-destructive method which gives information about the proportions of major

structural groups in samples and can be used to identify variation between samples. A molecular mixing model

was used to estimate the contributions of a range of biomolecular compound classes to the samples, allowing for

a direct comparison to the spectrophotometric quantification of lignin and cellulose.

Only 12 surface samples (one each for the top 0-1 and 1-2 cm section) from Mossdale were analysed (i.e. no

replicates) due to the relatively high cost of NMR. NMR spectra were collected for two particle sizes (greater and

less than 200 μm), two incubation temperatures (14°C and 23°C), and the two management methods (burnt and

mown). Samples were freeze dried, ground and separated into coarse (>200 μm) and fine (<200 μm) fractions

prior to analysis. 13C{1H} spectra were acquired using a 400 MHz Bruker Avance III HD spectrometer fitted with a

Bruker 4 mm H(F)/X/Y triple-resonance probe and a 9.4 T Ascend® superconducting magnet. Cross polarisation

and magic angle spinning were employed to improve the signal acquisition and minimise line broadening effects.

The spectra were compiled from 800 scans acquired using a 1 ms linearly-ramped contact pulse, a spinning rate of

12,000 ± 2 Hz, 5 second recycle delays and SPINAL-64 heteronuclear decoupling (at a νariance reduction factor of

85 kHz; see Bryce et al., 2001). Chemical shifts are reported relative to tetramethylsilane (TMS) with adamantane

(29.5 ppm) as an external secondary reference. Spectra were processed using ACD Labs; an exponential function

(line broadening = 25) was applied to the FID data to improve the signal-to-noise ratio, followed by a Fourier

transform to produce the spectra. Spectral integrations were standardised to sum to one.

The C/N ratio for bulk burnt and mown surface samples was determined using an Elementar Analysensysteme-

GmbH vario Max CN Element Analyser. For the purposes of this analysis, this ratio was converted into the molar

C:N ratio.

A molecular mixing model (MMM) was applied to the NMR spectra according to the method developed by Nelson

et al. (2005). In short, the MMM estimates the relative contributions of six biomolecular compound classes -

carbohydrate, protein, lignin, aliphatic, carbonyl and char - by simultaneously solving the contributions of each

biomolecular compound class to six regions of an NMR spectrum with the observed spectral distribution of the

sample (Table A7.3). Carbonyl is not strictly a biomolecular compound class; rather, it represents partially

oxidised material from other classes (Nelson et al., 2005).

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Table A7.3 Spectral distributions of major biomolecular compound classes for NMR spectra.

The model was adapted by using the shift regions with the greatest inter-sample variability (95-60, 45 to -10, 210-

165 and 145-110 ppm) and the molar N:C ratio, which was found to be necessary to constrain the protein content

to realistic values (Kaal et al., 2007). Although this model gave slightly negative char contents for most of the

mown samples, it was not adapted to remove char as these values were within the margin of error for the

method (Ahmad et al., 2006). Contributions smaller than ±2% were instead assumed to be zero. Spectroscopic

techniques such as FTIR and NMR present a major advantage over destructive techniques as they can be

performed on samples without any prior preparation other than drying and milling, therefore eliminating

secondary reactions associated with chemical/thermal pre-treatments and extractions (Knaber, 2000; Bellon-

Maurel and McBratney, 2011) or losses in solvent steps during sample preparation.

FTIR spectroscopy is a rapid spectroscopic technique which allows for the collection of spectra of a large number

of samples. The peaks and bands of an FTIR spectrum correspond to the vibrations of major structural

components in the sample; therefore although it is not possible to estimate the composition of complex samples

from FTIR spectra, compositional changes may be tracked through visual comparison of peaks and the calculation

of peak ratios. Spectra were acquired by averaging 16 scans between 4000-400 cm-1 at a resolution of 4 cm-1 using

a Bruker ALPHA spectrometer fitted with a Platinum diamond ATR module. Spectra were recorded to assess the

heterogeneity, fraction variability and depth trends of the burnt and mown samples (Table A7.4).

Table A7.4 FTIR spectra recorded for the Mossdale (M) samples for the different fractions (bulk, coarse or fine) from the

different peat core sampling depths (cm). “Replicates” refers to the number of sample replicates taken in each set [I:

sampled in July and II: sampled in October]. The core codes include both the burnt and mown cores at each incubation

condition. The core numbers indicate either the 5ºC, 14 ºC or 23 ºC temperature incubation (5, 14, 23, respectively) with cores

being kept either dry 0 cm (d) or wet (w) at a 6 cm water level.

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Sample replicates were recorded by taking separate subsamples from each ground and milled sample; for six

cores (MC14w, MM14w, NC14w, NM14w, WC14w, WM14w; for codes see Table A7.4) five sample replicates

were recorded at 0-1 cm to assess the variability of the material. For subsequent experiments, three sample

replicates were recorded as this was considered sufficient. Four cores (MM5w, MC5w, MM5d, MC5d) were

analysed at three depths (0-1 cm, 5-6 cm, 19-20 cm) averaging 16 scans at 2 cm-1 resolution between 3000-700

cm-1 to determine whether any additional peaks were visible at the higher resolution. Spectra were standardised

using the mean and standard deviation of all points in the spectrum in LibreOffice Calc 4.2. A correction of 1.15

was added to each data point to bring all values above 0. For comparative analysis, the average of the

standardised sample replicates was taken. Principal component analysis of the standardised spectra was

performed using the R Console.

The heights of the 2918 and 2851 cm-1 peaks were measured from the peak maximum to the tangent of the water

band (Capriel et al., 1995), which was calculated for each spectrum by constructing a straight line between the

points at 3000 cm-1 and 2800 cm-1. Unlike the aliphatic peaks, the 1800-800 cm-1 region of the spectrum has no

clearly defined “baseline” from which to measure peak heights; therefore a “peak-to-valley” method was

followed to measure peak heights representative of lignin and carbohydrate.

Figure A7.2 The lignin/carbohydrate region of the FTIR spectrum (1800-800 cm

-1; 4 cm

-1 resolution) for Mossdale (M) peat

samples at different temperatures (left) and different depths (middle). Samples were analysed when soils were dry (d)

before temperature incubation at a temperature of 5ºC (5d) and when soils were wet (w) after 8 weeks of incubation at

temperatures of 5ºC (5w), 14ºC (14w) and 23ºC (23w). Samples from three peat depths (1 cm, 5 cm and 20 cm) were analysed

for the 23ºC incubation (M23w). All lines are the average of three replicate scans for each sample. The average (± 1 standard

deviation) 2918/2851 peak height ratios are also shown for the same three depths (right). Burnt samples are orange/red;

mown samples are green.

The FTIR analysis of the peat samples across the depth range for peat cores for Mossdale clearly showed spectra

peaks in relation to specific C fractions (see Figure A7.2). There were differences between samples at different

temperature incubations, including before incubation (Figure A7.2; left), which mostly related to changes in

surface layers (Figure A7.2; middle). Although no clear overall picture emerged between mown and burnt

samples, the 2918/2851 peak ratio (Figure A7.2; right) decreased slightly with depth in almost all cores (there was

a statistically significant (p = 0.0165, α = 0.05) difference between 1 cm and 20 cm across all cores analysed).

Moreover, a principal component analysis (PCA) showed separation of the burnt and mown surface (1 & 5 cm)

peat samples, whilst all of the 20 cm layer samples lacked any clear separation (Figure A7.3). The separation at

the surface was even stronger when considering only the initial samples before any temperature changes (Figure

A7.3; 5d points). FTIR is a non-intrusive method and allows quick screening for any differences, which can then be

considered together with quantitative methods. However, more replication is needed to address the high spatial

variability in peat samples (i.e. considering sampling litter vs. peat fragments).

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Figure A7.3 Principal component analysis of the 2490-1471 cm

-1 region of the FTIR spectra for Mossdale peat core samples

analysed when soils were dry before temperature incubation at a temperature of 5ºC (5d) and when soils were wet after 8

weeks of temperature incubation at 5ºC (5w) from either the burnt (C; orange) or mown (M; green) plots from different

depths (1 cm, 5 cm and 20 cm from the surface). Each set of three sample replicates is circled to show the variation between

spectra of subsamples taken from the same core and depth. Note the separation between mown and burnt groups for the

top 1 cm and for the 5 cm depth, particularly for the non-temperature incubated samples (5d), but the very close association

for the 20 cm depth samples (which were all burnt in the past). The PC1 axis accounts for 80.0% of the total variation of the

data and the PC2 axis accounts for 16.9% of the variation.

Statistics

Unless otherwise specified, all statistical tests performed in the chemical analysis section were independent two

tailed student t-tests; the significance level was set to α = 0.05.

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Figure A7.4 Peat decomposition data and their distances to the fitted polynomial surface (see Table A7.1 above for the

parameters and statistics) for the averages of all sites (either all sites combined or individually for Mossdale, Nidderdale and

Whitendale) and the managements (either for combined or individual burnt and mown fluxes) for either the top 5 cm (top),

bottom 15 cm (bottom) and total 20 cm core, the latter either using soil moisture (SM) based on the top SM (whole core) or

the weighted top and bottom SM layers (top-bottom all). The natural log (ln) of the soil fluxes (ln Carbon flux) were plotted

against temperature (Temperature) and percentage soil moisture (Soil Moisture).

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Decomposition rates and peat chemistry