Introduction
For several decades, it was assumed that the molecular structure accounts
for the rate of decomposition of different organic compounds in soils, i.e.
compounds of high chemical recalcitrance were assumed to be selectively
preserved (Stevenson, 1994). However, the use of compound-specific isotope
analysis provided new understanding of soil organic matter (SOM) dynamics.
As an example, lignin, a compound of high chemical recalcitrance, has
shorter mean residence times (MRT) than labile compounds like sugars or
proteins (Amelung et al., 2008; Gleixner et al., 2002; Kiem and
Kögel-Knabner, 2003; Schmidt et al., 2011). The main mechanisms for the
long persistence of these labile compounds in soil are stabilization on the
one hand, i.e. protection of organic matter from mineralization either by
reduced accessibility for microorganisms caused by physical protection (by
mineral interaction or occlusion within soil aggregates) or chemical
recalcitrance (Six et al., 2002; Sollins et al., 1996; von Lützow et
al., 2006), and microbial recycling on the other, i.e. the reuse of “old”
organic compounds by microorganisms (Gleixner et al., 2002; Sauheitl et al.,
2005). The latter leads to an underestimation of the actual turnover
dynamics but overestimates the persistence of single molecules as a whole
within the SOM. Although these different underlying mechanisms were
proposed quite a while ago, their relevance in different soils and soil
horizons, especially concerning the importance of stabilization versus
microbial recycling, still remains unclear. First studies on polar membrane
lipids of microorganisms in marine sediments suggest a strong
underestimation of recycling in our current view on carbon dynamics in soils
and sediments (Takano et al., 2010). However, knowledge about soils
especially microbially active topsoils is still missing. Therefore,
assessing the importance of stabilization and recycling for the persistence
of organic matter in soil will improve the understanding of the carbon cycle
and close an important knowledge gap.
However, the pool of SOM is highly complex and intractable to analyse as a
whole. Thus, we examined the fate of sugars; an important compound class of
the SOM that is involved in almost all biological processes in soils, the
MRT of which do not match their low biochemical recalcitrance (Gleixner et
al., 2002; Derrien et al., 2006, 2007). Sugars in soils are
commonly classified according to their main origin into plant (arabinose
(ara), xylose (xyl)) or microbial-derived sugars (galactose (gal), mannose
(man), rhamnose (rha), fucose (fuc)); Oades, 1984; Moers et al., 1990).
While turnover dynamics of plant-derived sugars should mainly be governed by
stabilization processes, the turnover dynamics of microbial sugars may be
influenced by both stabilization and recycling.
The MRT of bulk and sugar carbon were examined in density fractions to
elucidate turnover dynamics in SOM pools with different degrees of
degradation and protection. While free particulate organic matter
(fPOM)
represents an only partly degraded SOM pool with fast turnover, occluded
particulate organic matter (oPOM) and mineral-associated organic matter
correspond to pools that are more preserved from microbial attacks and show
slow turnover (John et al., 2005; Golchin et al., 1994b). The study was made
on a field experiment located in Rotthalmünster with natural 13C
labelling by a vegetation change from C3 (wheat) to C4 vegetation (maize).
We hypothesize that MRT of plant and microbial sugar carbon will be
different as the mechanisms controlling their turnover dynamics are
different: turnover of microbial-derived sugars should be mainly ruled by
recycling whereas the turnover of plant-derived sugars is ruled by
stabilization.
Materials and methods
Study site
Soil samples were collected from the long-term field experiment at
“Höhere Landbauschule” Rotthalmünster, Bavaria, Germany (48∘21′47′′ N, 13∘11′46′′ E). The mean annual
temperature is 9.2 ∘C and the mean annual precipitation is 757
mm. Soil samples (Ap-horizon & E-horizon) were taken in April 2011 from
(i) a continuous maize plot (Zea mays L.) established in 1979 on a former grassland
plot until 1970 followed by wheat cultivation until 1978 and (ii) a
continuous wheat plot (Triticum aestivum L.) established in 1969. Previous vegetation on the
wheat plot was grassland. The soil at the two sites was classified as a
stagnic Luvisol (IUSS Working Group WRB, 2014), derived from loess. Soil
texture is silty loam (11 % sand, 73 % silt, 16 % clay). More details
about the soil properties can be found in John et al. (2005) and Ludwig et al. (2005).
Density fractionation
Density fractionation of soil was performed according to John et al. (2005).
Briefly, 10 g of soil was weighed into a 50 mL centrifuge tube and filled
with 40 mL 1.6 g cm-3 sodium polytungstatesolution (SPT, Sometu,
Berlin, Germany). The tube was gently shaken five times by hand and allowed to settle
for 30 min. Afterwards the solution was centrifuged for 40 min at 3700 rpm.
The supernatant including floating materials was filtered with polyamide
membrane filters (0.45 µm, Sartorius Göttingen) using vacuum and
washed with distilled water to gain the fPOM. Residual soil was re-suspended
in 25 mL SPT (1.6 g cm-3) and 18 glass pearls (4 mm diameter) were
added, the solution was then shaken for 16 h at 60 movements per minute
to break up the aggregates. Subsequently, the solution was centrifuged
40 min at 3700 rpm, vacuum filtered (0.45 µm) and washed with
distilled water to obtain the occluded particulate organic matter
(oPOM1.6). The residual soil was re-suspended with 25 mL SPT using a
density of 2 g cm-3, shaken for 10 min at 100 rpm and centrifuged (40 min at 3700 rpm). To obtain the occluded particulate organic matter with a
density of 1.6–2 g cm-3 (oPOM2), the supernatant was
vacuum-filtered and washed with distilled water. The remaining fraction
(mineral) was washed three times with 20 mL water to remove SPT. Each time
the sample was centrifuged and the supernatant discarded. All fractions were
dried at 40 ∘C.
Sugar analysis
Sugars were extracted and purified using a modified procedure based on
Amelung et al. (1996) and Amelung and Zhang (2001). For extraction,
sub-samples containing approximately 0.5–5 µg C (depending on the
availability of the respective fraction) were hydrolysed with 10 mL 4 M
Trifluoroacetic acid (TFA) at 105 ∘C for 4 h. Afterwards the
samples were filtered through a glass fibre filter (Minisart GF, Sartorius,
Göttingen, Germany) and dried by rotary evaporation (40 ∘C,
50 hPa). In contrast to Amelung et al. (1996), the pre-dried samples were
re-dissolved in 0.5 mL water and evaporated to dryness for 3 times to remove
all traces of TFA (which impedes chromatographic separation, see Basler and
Dyckmans, 2013). Then, the samples were re-dissolved in approximately 3 mL
water and passed through 4 g Dowex X8 cation exchange resin (Sigma Aldrich,
Steinheim, Germany) and 5 g Serdolit PAD IV adsorption resin (Serva
Electrophoresis GmbH, Heidelberg, Germany) for purification. Sugars were
eluted by adding 8 times 2 mL water. The eluate was freeze-dried and stored
at -18 ∘C until analysis. For HPLC-IRMS analysis the samples were
dissolved in 3 mL water and transferred into measurement vials.
The TFA extraction method is known to effectively extract hemi-cellulosic
sugars (Amelung et al., 1996) but cellulose is not cleaved by this method.
The results presented here thus only refer to non-cellulosic sugars and
substantially underestimate the total sugar contribution of plants SOM.
Isotopic analysis
Isotopic composition and total carbon content of plant material, bulk soil
and density fractions were analysed by EA-IRMS. The compound-specific isotope
analysis of the monosaccharides was performed using a high-pressure liquid
chromatography system (Sykam, Fürstenfeldbruck, Germany) coupled to an
isotope ratio mass spectrometer (Delta V Advantage, Thermo Scientific,
Bremen, Germany) via an interface (LC-Isolink, Thermo Scientific, Bremen,
Germany) as described by Basler and Dyckmans (2013). Shortly, the
chromatographic column (Carbo Pac 20, Dionex) was held at 10 ∘C
and a 0.25 mM NaOH solution was used as mobile phase at a flow rate of
250 µL min-1.
Chloroform fumigation extraction
Microbial Biomass (Cmic) was determined by the fumigation extraction
method (Brookes et al., 1985; Vance et al., 1987). K2SO4
concentrations were adapted for isotopic analysis (Engelking et al., 2008).
Briefly, a sub-sample of 20 g moist soil was separated into two portions of
10 g. One soil sub-sample was directly extracted as described below. One
portion was placed in a desiccator with ethanol free CH3Cl at 25 ∘C for 24 h. For extraction, soil samples were shaken with 60 mL
0.05 M K2SO4 for 1 h and subsequently filtered (Whatman
595 1/2, Maidstone, UK). The dissolved organic carbon was analysed using a TOC
analyser multi C / N® 2000 (Analytik Jena, Jena, Germany). For
stable isotope measurements freeze-dried aliquots were analysed by EA-IRMS.
The isotopic signature of the microbial biomass was calculated as follows:
δ13Cmic=(δ13CF⋅CF)-(δ13CnF⋅CnF)(CF-CnF)
where δ13CF and δ13CnF are the isotopic
signatures of the fumigated and non-fumigated extracts and CF and
CnF are the extracted carbon content [mg kg-1] of the fumigated
and non-fumigated soil samples. Carbon extracted from non-fumigated samples
represents the K2SO4 extractable C fraction (exC).
Estimations of maize-derived carbon and turnover times
Under the assumption that the maize and wheat sites have a similar history
and similar carbon dynamics and fractionation during decomposition is comparable
for wheat and maize plant material, the proportion of maize-derived carbon
in bulk soil and density fractions was calculated according to (Balesdent
and Mariotti, 1996; Derrien et al., 2006):
f=(δsample-δreference)(δmaize-δwheat)
where f is the relative proportion of maize-derived carbon, δsample is the δ13C value of the maize plot sample,
δrefernce presents the measured 13C value of the
corresponding wheat plot samples, and δmaize and δwheat are the 13C values of the crop residues of maize
(-13.2 ‰) and wheat (-27.5 ‰). The
resulting difference of 14.3 between wheat and maize plants was used for all
fractions (bulk material and individual sugars) because the determination
especially of mainly microbial-derived sugars in plant material was very
difficult.
The error of maize contribution percentage calculated from error propagation
was below 10 % for all samples, which is in the range of the standard
error calculated from the replications.
Assuming steady-state conditions and homogeneous soil fractions which can be
described with a single pool model (Six and Jastrow, 2002), the MRT is
calculated according to Derrien and Amelung (2011):
MRT=1k,
where the time constant k is calculated from the following equation:
f=1-exp(-kt),
where t is the time of maize cultivation.
Since conditions like fertilization and carbon contents of the soil remained
about the same after the change from C3 to C4 vegetation, and the conversion
was from other cereal crops (wheat) to maize, which are very similar with
respect to biochemical nature, soil inputs, location of soil inputs, decay
rates and decay products, the system approximates a steady-state system
(Balesdent and Mariotti, 1996) as required. It is well known that the
assumption that MRT of soil organic carbon can be described by a single pool
model is a rough simplification since it is a complex mixture of SOM with
different stability and turnover even if the isolated soil fractions are one
step towards homogeneity, especially concerning POM fractions. Therefore, we
used the term “apparent” MRT. In addition it has to be noted that we refer
to the MRT of the carbon in individual molecules and not of the intact
molecules as a whole.
Statistical analysis
Analysis of Variance (ANOVA) with ensuing post hoc test (Tukey's test) were
conducted to detect differences among the sugars within a soil fraction
(bulk soil, density fractions) and among individual sugars of different soil
fractions. Statistical analysis was made using R 3.0.2 (R Core Team, 2013).
Results
Carbon and sugar content in soil, density fractionations and plant material
Organic carbon distribution in the investigated density fractions.
Means and standard error (n= 5).
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The recovery of carbon after density fractionation of the wheat and maize
plots was about 90 % in the Ap-horizon and about 86 % in the E-horizon.
Between 79 and 89 % of total recovered carbon was found in the mineral in
the investigated soils (Fig. 1). The oPOM2 fraction accounted for 7 and
10 % of the carbon found in the Ap-horizon and for 4 and 9 % in the
E-horizon of the wheat and maize plot, respectively. Less carbon was found
in the oPOM1.6 fractions (between 3 and 5 %) and the free
particulate organic matter (fPOM; 2–3 %). The contribution of sugar carbon
to total carbon in oPOM1.6 was between 5 and 8 %. Higher
contributions were observed in the oPOM2 with 11 to 15 % (data not
shown). The general sugar distribution in the bulk soil fraction was
glc > gal > man = ara = xyl > rha>
fuc and was slightly different in the POM fractions, where ara and xyl
occurred in higher proportions than gal and man (Table 1).
In the plant, sugars were dominated by xyl with about 44
(wheat) and 30 mg C g-1 (maize), followed by ara and glc with about
8 (wheat) and 6 mg C g-1 (Table 1). The other sugars each
contributed 4 mg C g-1 or less. The extracted sugars accounted for
20 and 8 % of total carbon and in the wheat and maize plants,
respectively.
Carbon content [mg C g-1(dw)] and sugar content [mg C g-1(dw)] in bulk soil, soil density fractions and wheat and maize
plants. Latin letters (a–e) within one row indicate significant differences
(p < 0.05) among the different sugars within one fraction. Greek
letters (α-δ) within one column indicate significant
differences among different fractions for individual sugars. Means and
standard error.
Fraction
Carbon
Fuc
Rha
Ara
Xyl
Glc
Gal
Man
Continuous wheat plot (Ap)
mg Cg-1 bulk
mg Cg-1 fraction
oPOM1.6 (n= 5)
0.28 ± 0.01
0.68 ± 0.27αd
0.91 ± 0.28αcd
2.68 ± 0.6αab
6.08 ± 1.4αa
7.42 ± 1.95αa
2.24 ± 0.51αbc
2.23 ± 0.49αbcd
oPOM2 (n= 5)
0.71 ± 0.06
0.37 ± 0.03αc
1.39 ± 0.5αbc
2.70 ± 0.1αab
5.83 ± 1.01αa
6.37 ± 2.29αa
1.85 ± 0.56αab
3.19 ± 0.84αab
Mineral (n= 3)
9.51 ± 1.02
0.05 ± 0.01βd
0.09 ± 0.01βcd
0.15 ± 0.01βbc
0.15 ± 0.01βb
0.26 ± 0.03βa
0.18 ± 0.02βab
0.16 ± 0.05βb
Bulk (n= 3)
12.06 ± 0.8
0.03 ± 0.00βc
0.07 ± 0.00βc
0.13 ± 0.02βb
0.14 ± 0.01βb
0.27 ± 0.27βa
0.16 ± 0.00βab
0.14 ± 0βb
Continuous Wheat plot (E)
oPOM1.6 (n= 5)
0.25 ± 0.05
0.42 ± 0.19αb
0.60 ± 0.32αb
2.38 ± 0.91αab
3.36 ± 1.25αa
5.38 ± 1.87αa
1.93 ± 0.85αab
2.06 ± 0.66αab
oPOM2 (n= 5)
0.29 ± 0.04
0.40 ± 0.09αc
0.88 ± 0.23αbc
1.90 ± 0.42αabc
2.96 ± 0.7αab
4.39 ± 0.76αa
1.90 ± 0.37αabc
1.81 ± 0.34αabc
Mineral (n= 3)
5.90 ± 0.01
0.03 ± 0.01βd
0.08 ± 0.01βcd
0.07 ± 0.01βbc
0.07 ± 0βcd
0.14 ± 0.01βa
0.10 ± 0.01βab
0.09 ± 0.01βb
Bulk (n= 3)
7.86 ± 0.26
0.03 ± 0.00βe
0.04 ± 0.01βde
0.07 ± 0.01βbcd
0.06 ± 0.02βcd
0.16 ± 0.02βa
0.10 ± 0.02βab
0.08 ± 0.03βbc
Continuous maize plot (Ap)
oPOM1.6 (n= 5)
0.49 ± 0.02
0.76 ± 0.3αe
1.17 ± 0.28αc
3.22 ± 0.67αb
5.85 ± 1αa
8.61 ± 0.67αa
3.04 ± 0.56αa
2.90 ± 0.34αb
oPOM2 (n= 5)
1.15 ± 0.09
0.50 ± 0.02αc
0.86 ± 0.09αcd
2.61 ± 0.36αb
5.39 ± 1.17αab
6.00 ± 0.33βa
2.56 ± 0.22αb
2.28 ± 0.23αbc
Mineral (n= 3)
9.31 ± 1.51
0.03 ± 0.00βe
0.09 ± 0.02βbc
0.13 ± 0.03βabc
0.13 ± 0.02βab
0.27 ± 0.05γa
0.17 ± 0.04βab
0.16 ± 0.03βab
Bulk (n= 3)
12.51 ± 0.38
0.04 ± 0.00βf
0.09 ± 0.01βd
0.15 ± 0.01βc
0.16 ± 0.02βbc
0.36 ± 0.02γa
0.20 ± 0.01βab
0.17 ± 0.01βb
Continuous maize plot (E)
oPOM1.6 (n= 5)
0.42 ± 0.02
0.46 ± 0.09αc
0.92 ± 0.09αe
3.63 ± 0.21αbc
5.76 ± 0.93αab
9.44 ± 0.51αa
3.25 ± 0.24αcd
3.03 ± 0.17αd
oPOM2 (n= 5)
0.82 ± 0.04
0.48 ± 0.02αd
0.82 ± 0.08αc
2.48 ± 0.34βb
4.56 ± 0.9αab
5.42 ± 0.36βa
2.47 ± 0.23βb
2.09 ± 0.21βb
Mineral (n= 3)
7.75 ± 0
0.03 ± 0.00βc
0.08 ± 0.01βd
0.07 ± 0γcd
0.10 ± 0.01βdc
0.14 ± 0.01γa
0.07 ± 0.01γab
0.09 ± 0.01γbc
Bulk (n= 3)
11.10 ± 0.24
0.04 ± 0.00βd
0.07 ± 0.00βef
0.11 ± 0.01δcd
0.10 ± 0.01βdc
0.25 ± 0.02δa
0.16 ± 0.02δa
0.13 ± 0.02δbc
Plants
Wheat (n= 9)
417.09 ± 28.33
n.d.
1.07 ± 0.73
7.57 ± 0.72
44.16 ± 4.66
8.82 ± 1.18
3.66 ± 0.5
1.89 ± 0.44
Maize (n= 9)
431.93 ± 32.03
n.d.
1.14 ± 0.27
5.85 ± 0.52
29.66 ± 2.95
5.64 ± 0.41
2.88 ± 0.35
n.d.
Contribution of maize-derived carbon to the sugars in different soil
fractions
In general, the contribution of maize-derived carbon in the varying density
fractions decreased in the order fPOM > oPOM2 > mineral > oPOM1.6. The proportion of maize-derived carbon in
bulk soil was around 40 % in the Ap and 30 % in the E-horizon (Fig. 2).
The apparent MRT of carbon calculated from these data ranged between 25
(fPOM, Ap) and 119 (oPOM1.6, E) years (Table 2). The contribution of
maize to the exC was within the range of the bulk soil, whereas the
proportion of maize in Cmic was twice as high as in the bulk soil (Fig. 2).
The proportions of maize-derived carbon in individual sugars showed a
distinct pattern (Fig. 2): in the bulk soil, the highest proportion of
maize-derived carbon was observed in xyl (∼ 70 % in Ap,
56 % in E). The other sugars showed maize-derived carbon proportions in
the range of the bulk soil of about 37 in Ap and 30 % in E with the
exception of ara, fuc and gal in E with only 25 % maize contribution. Bulk
fPOM had maize contributions of 88 and 78 % in the Ap and E-horizon,
respectively. Maize contribution for all sugars in both horizons was close
to 100 % and thus the fPOM fraction was not evaluated further. In the
oPOM1.6 fraction, the proportions of maize-derived carbon of
individual sugars were two or three times higher than for total carbon in
this fraction (Fig. 2a and b). In the oPOM1.6 fraction of Ap, xyl and
man showed the highest percentages (∼ 85 %) of maize-derived
carbon, followed by glc (77 %) and ara, rha and gal (about 50 %). The
lowest percentage of maize-derived carbon was found for fuc (∼ 30 %) in the Ap-horizon. In the E horizon, all sugars contained about
55 % maize-derived C and showed no significant differences (p < 0.05), but there was still a trend towards higher percentages of
maize-derived carbon in xyl and man as compared to the other sugars.
Calculated MRT of total and individual sugar carbon in density
fractions and bulk soil. Means and standard error (n= 4).
MRT [years]
Fractions
Horizon
Bulk C
Ara
Xyl
Fuc
Rha
Gal
Man
oPOM1.6
Ap
97 ± 3
44 ± 4
17 ± 3
65 ± 24
54 ± 6
39 ± 2
17 ± 2
E
119 ± 6
48 ± 5
28 ± 4
55 ± 9
59 ± 15
51 ± 6
33 ± 3
oPOM2
Ap
37 ± 6
28 ± 4
14 ± 4
30 ± 4
43 ± 14
28 ± 4
30 ± 5
E
61 ± 8
31 ± 2
23 ± 5
28 ± 2
37 ± 12
41 ± 9
37 ± 3
Mineral
Ap
64 ± 3
57 ± 6
29 ± 2
51 ± 4
48 ± 7
47 ± 7
58 ± 10
E
98 ± 3
102 ± 11
45 ± 3
87 ± 7
60 ± 6
88 ± 7
54 ± 3
Bulk soil
Ap
68 ± 4
80 ± 13
27 ± 1
77 ± 15
77 ± 22
71 ± 2
70 ± 11
E
85 ± 4
115 ± 12
41 ± 8
104 ± 19
72 ± 8
138 ± 32
152 ± 32
In the oPOM2 fraction, the highest percentages of maize-derived carbon
in the sugars of all fractions were observed with about 77 and 65 % in
the Ap and E-horizon. In the oPOM2 fraction no significant difference
in maize contribution among the sugars was observed (p < 0.05) in
both horizons, but a trend of higher values for xyl (88 %) and lower
values for rha (58 %) were found for the Ap-horizon (Fig. 2).
In the mineral, the percentages of maize-derived carbon in the Ap-horizon
showed no significant difference to the bulk soil fraction and amounted to
about 52 % of maize-derived carbon. Xyl showed the highest values with
66 % and man and ara showed the smallest percentages (44 %). In the
mineral of the E-horizon, the maize percentages were about 37 % and showed
no significant difference to the bulk soil (Fig. 2). Xyl and man showed the
highest percentages (∼ 50 %) of maize-derived carbon,
followed by ara, glc, fuc and gal with about 25 %. The calculated MRT for
the sugar carbon in density fractions (Table 2) showed values from 14 years
(xyl in oPOM2 Ap-horizon) to 152 years (man, in bulk soil E-horizon).
Maize contribution to sugars in bulk soil, mineral, oPOM1.6
and oPOM2 fractions in the (a) Ap (0–30 cm) and (b) E-horizon (30–45 cm).
Latin letters (a–d) indicate significant differences (p < 0.05) among
the individual sugars within one fraction. Greek letters (α-γ) indicate significant differences among different fractions for individual
sugars. Means and standard error (n= 4).
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Discussion
Carbon content increased with decreasing density of the fractions
concomitant with decreasing organo-mineral associations, similar to earlier
findings on the same (John et al., 2005) and other soils (Baisden et al.,
2002; Golchin et al., 1994a). The fPOM fractions contained between 2 and
8 % of total carbon and the major part (86 %) were found in the mineral
fraction. The relative contribution of sugars to bulk carbon was 8 % in the
Ap-horizon and around 7 % in the E horizon in agreement with values
reported by Cheshire (1979), Derrien et al. (2006) and Guggenberger et al. (1994). The proportions of sugar carbon in the POM fractions decreased in
the order oPOM2> fPOM> oPOM1.6 in both
horizons. This corroborates the 13C NMR analysis on the same soil,
which revealed decreasing O-alkyl carbon content (representing e.g. sugars)
in oPOM1.6 as compared to oPOM2, whereas alky-carbon content
(representing lipids, fatty acids, plant aliphatic polymers) increased
(Helfrich et al., 2006). The ratio of alkyl to O-alkyl carbon has been
reported to provide an indicator of decomposition, as O-alkyl carbon rich
substances are more easily accessible and thus preferentially decomposed and
more recalcitrant compounds accumulate (Golchin et al., 1994b; Baldock et
al., 1997). Consequently, the higher sugar contribution in oPOM2 as
compared to oPOM1.6 probably indicates a higher degree of
decomposition in the oPOM1.6 fraction. This supports the concept of
Golchin et al. (1994a), who suggest that the fresh, carbohydrate rich POM is
utilized by microorganisms with concurrent increase of organo-mineral
associations (→ oPOM2) and the formation of aggregates. Within the
aggregates, decomposition proceeds and labile compounds become more and more
depleted. In turn, microbial activity decreases and less binding agents are
produced and binding to mineral particles is decreased (decreased density
→ oPOM1.6). Due to reduced microbial activity and decreasing
production of binding agents the aggregates become unstable and finally
disrupt, and new aggregates may develop if fresh plant or microbial debris
is available to fuel microbial activity.
In the density fractions the apparent MRT of bulk carbon increased in the
order fPOM < oPOM2 < mineral < oPOM1.6 in
both soil depths, which is in line with studies by John et al. (2005) and
Rethemeyer et al. (2005) on the same soil and corroborates the concept of
Golchin et al. (1994a) of the aggregate hierarchy described above. Although
the oPOM1.6 fraction had the highest proportion of C3 carbon, the
sugars in the oPOM1.6 fractions were much younger than the bulk
fraction, but in range with the oPOM2 fraction and the microbial
biomass. This indicates that the microbial activity leading to aggregate
formation also in the “old” oPOM1.6 fraction is fuelled from
relatively fresh assimilates and shows the importance of microbial activity
to form binding agents, as mentioned before by Oades (1984). Corroborating,
the apparent MRT of sugar carbon in both oPOM fractions is comparable to the
apparent MRT of the microbial biomass carbon in both soil horizons.
Man, as a microbial-derived sugar showed considerably higher incorporation
of maize-derived carbon similar to xyl in the oPOM fractions although the
contribution of man by plants was very little. A possible explanation could
be fungal activity, as it is known that fungi feed mainly on the recent
vegetation (Hobbie et al., 2002; Kramer and Gleixner, 2006). Additionally,
mannan, a mannose polymer, is abundant in exo-polysaccharides and cell walls
of fungi (Osaku et al., 2002; Stribley and Read, 1974; Bowman and Free,
2006) and the involvement of fungal activity in soil aggregate formation was
highlighted in several studies (Chenu, 1989; Caesar-Tonthat, 2002; Tisdall
and Oades, 1982). In the oPOM fractions of the E-horizon (especially
oPOM1.6) man was much less influenced by maize-derived carbon compared
to Ap; this may indicate a reduced importance of fungal activity to oPOM
formation in the subsoil or at least no distinct allocation of maize-derived
carbon through the hyphal network to the subsoil.
Xyl had the highest percentages of maize-derived carbon in all soil
fractions and depths, owing to the high input of xyl from plant material
(mainly from hemicellulose). Additionally, root exudates provided a further
small source of xyl as shown by Derrien et al. (2004) and, in turn, roots
and their exudates promote aggregate formation (Six et al., 2004; Oades,
1984). In contrast ara, which has also been described as mainly plant-derived (Oades, 1984), showed smaller percentages of maize-derived carbon in
all density fractions compared to xyl. One could assume that ara and xyl, as
sugars of the same origin, were subject to the same dynamics, and more
specifically, a similar mole ratio of ara to xyl in plants and oPOM was
expected. In the oPOM fractions, however, the ratio of ara to xyl increased
(as compared to the plants) and, in addition, the percentages of
maize-derived carbon of ara were not significantly different from sugars
derived mainly from microorganisms (fuc, rha and gal). This indicates that
in our soil, ara and xyl dynamics are not ruled by the same factors. It has
been shown that both sugars are highly abundant in plant material at a molar
ratio of 1:3 (ara : xyl) or higher (Boschker et al., 2008; Glaser et al.,
2000; Moers et al., 1990; Oades, 1984), however we found much less
contribution of ara than xyl by both wheat and maize plants with a molar
ratio of 1:5 (Table 1). On the other hand, both ara and xyl are produced by
microbial biomass (Muramaya, 1988; Cheshire, 1977; Coelho et al., 1988;
Basler et al., 2015) and we therefore assume that in this study, ara was much more
influenced by microbial production than xyl and its high mean age in
oPOM1.6 and oPOM2 (28 to 48 years) was considerably
influenced by microbial activity (and substrate recycling). This also
indicates that the formation of oPOM fractions is predominantly based on
microbial activity and not plant input in the first place. In contrast to
ara, the dynamics of xyl were dominated by plant input and recycling seems
to play a minor role.
Taken together the finding of substantially higher MRT for carbon of
microbial sugars (influenced by both, stabilization and substrate
recycling), compared to that of plant-derived sugars (the turnover dynamics
of which are dominated by stabilization processes) indicates that the mean
age of SOM is strongly influenced by substrate recycling and that
stabilization processes do not play a dominant role for SOM dynamics.