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Clay Dispersibility and Soil
Friability
—
Tes ng the Soil
Clay-to-Carbon Satura on Concept
Soil organic carbon (OC) in
fl
uences clay dispersibility, which a
ff
ects soil lth condi ons
and the risk of ver cal migra on of clay colloids. No universal lower threshold of OC has
been iden
fi
ed for sa sfactory stabiliza on of soil structure. We tested the concept of clay
satura on with OC as a predictor of clay dispersibility and soil friability. Soil was sampled 3
yr in a
fi
eld varying in clay content (
?
100 to
?
220 g kg
−
1
soil) and grown with di
ff
erent crop
rota ons. Clay dispersibility was measured a er end-over-end shaking of
fi
eld-moist soil
and 1- to 2-mm sized aggregates either air-dried or rewe ed to
−
100 hPa matric poten al.
Tensile strength of 1- to 2-, 2- to 4-, 4- to 8-, and 8- to 16-mm air-dried aggregates was
calculated from their compressive strength, and soil friability es mated from the strength–
volume rela on. Crop rota on characteris cs gave only minor e
ff
ects on clay dispersibility
and no detectable e
ff
ects on soil friability. Dispersed clay correlated to soil content of
clay, but the correla on increased if subtrac ng a frac on assumed protected by OC. This
trend was less convincing for soil tensile strength and friability. Increased clay dispersibility
and reduced soil friability for 1 yr of measurements could be ascribed to wet condi ons
for potato (
Solanum tuberosum
L.) harvest and llage the preceding year. Literature data
indicate soils’ content of clay and silt (Fines20) to be a be er predictor of speci
fi
c surface
area than clay. We conclude that a clay/OC ra o of 10 and a Fines20/OC ra o of 20 may
serve as corresponding thresholds for clay dispersibility, the la er probably best re
fl
ec ng
organo-mineral interac ons of importance to the soil physical proper es.
Abbrevia ons: C, catch crop; CB, conven onal beans; CC, complexed clay; COC, complexed organic carbon;
EGME, ethylene glycol monoethyl ether; F, fer lizer; Fines20, mineral par cles <20
μ
m; M, manure; NCC,
noncomplexed clay; NCOC, noncomplexed organic carbon; OB, organic beans; OC, organic carbon; OG,
organic grass; SA, speci
fi
c surface area; SOM, soil organic ma er.
Ver cal migra on
of clay particles is a natural pedogenic process in humid areas,
where many soils show increased contents of clay with depth in the proi le and have devel-
oped argillic horizons from clay colloids eluviated from the surface soil. Clay skins formed
in macropores in subsoil horizons have also been attributed to clay particles eluviated from
surface soil (Kjaergaard et al., 2004). Intensive arable cropping on drained land with fre-
quent and intensive tillage leads to reduced soil organic matter (SOM) levels and inferior
soil physical properties. Reduced SOM contents and high energy inputs in tillage increase
the formation of free clay particles (e.g., Watts et al., 1996; Watts and Dexter, 1998) that
can be eluviated to deeper layers of the vadose zone. In drying, dispersed clay may form
mechanically strong aggregates and clods (e.g., Kay and Dexter, 1992), causing poor tilth
conditions. h
is in turn may require larger energy inputs in tillage, creating a vicious circle
of soil tilth degradation (Kay and Munkholm, 2004). h
e overall outcome may be a dra-
matically accelerated eluviation of clay colloids, and surface soil structure may deteriorate,
leading to reduced retention of plant-available water and nutrients and increased water and
wind erosion potentials. Further, migrating clay colloids may carry phosphorus, pesticides,
and otherwise immobile pollutants toward groundwater reservoirs and the aquatic envi-
ronment (de Jonge et al., 2004; Laegdsmand et al., 2007).
Studies of SOM gradients indicated satisfactory soil friability for a loamy sand (Askov
long-term fertilization experiments;
?
13% clay) at a SOM content of
?
21 g kg
−1
, while
similar levels of friability for a loamy soil at Rothamsted with
?
24% clay required SOM
contents about 36 g kg
−1
(Watts and Dexter, 1997; Munkholm et al., 2002). Loveland
and Webb (2003) reviewed the literature but failed to identify a universal critical lower
threshold of SOM for sustainable soil functions of British soils. A group of scientists
gathered for the same task during the European Union work on a Soil h
ematic Strategy
suggested target SOM values for numerous combinations of climate and soil types (van
Based on analyses using soils with
gradients in soil texture and carbon
management, the concept of clay sat-
ura on with organic carbon (OC) as
a predictor of soil physical behavior
was con
fi
rmed for clay dispersibil-
ity. A clay/OC ra o of 10 and a (clay
+
fi
ne silt)/OC ra o of 20 may serve
as corresponding thresholds for clay
dispersibility.
P. Schjønning, L.W. de Jonge, L.J. Munkholm,
B.T. Christensen, and J.E. Olesen, Aarhus
Univ., Dep. of Agroecology, Blichers Allé
20, P.O. Box 50, DK-8830 Tjele, Denmark;
P.
Moldrup,
Aalborg
Univ.,
Dep.
of
Biotechnology, Chemistry and Environmental
Engineering, Sohngaardsholmsvej 57,
DK-9000 Aalborg, Denmark. *Corresponding
author (Per.Schjonning@agrsci.dk).
Vadose Zone J.
doi:10.2136/vzj2011.0067
Received 16 June 2011.
Special Section:
Soil Architecture and Function
P. Schjønning*
L.W. de Jonge
L.J. Munkholm
P. Moldrup
B.T. Christensen
J.E. Olesen
© Soil Science Society of America
5585 Guilford Rd., Madison, WI 53711 USA.
All rights reserved. No part of this periodical may
be reproduced or transmi ed in any form or by any
means, electronic or mechanical, including pho-
tocopying, recording, or any informa on storage
and retrieval system, without permission in wri ng
from the publisher.
Published February, 2012
Page 2
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Camp et al., 2004). Such an approach rel ects that the state of
knowledge of SOM interaction with mineral particles is rather
limited and not yet sui
ciently developed to be implemented in an
ef ective strategy for soil conservation. Dexter et al. (2008) recently
found that SOM ef ects on clay dispersibility could be related
to properties of the clay-sized soil fraction. Work on Polish and
French soil data sets indicated that OC was complexed with clay
for clay/OC ratios higher than 10 oft en observed for soils under
continuous arable cropping. For pasture soils considered as having
passed their protective capacity for carbon sequestration (Hassink,
1997), clay/OC ratios were typically below 10.
We have previously addressed the implications of the soil clay-
to-carbon saturation concept for selected soil physical properties
(de Jonge et al., 2009). Here we examine how the clay/OC
= 10 “saturation” threshold relates to measurements of clay
dispersibility and soil friability for a Danish arable sandy loam
soil. Soil was sampled in a i eld experiment with dif erent cropping
systems, allowing for identii cation of management ef ects. h
e
experimental i eld displays a natural gradient in soil clay content
and thus also provides a gradient in the clay/OC ratio. We further
examined the saturation concept in a wider context by evaluating
the relationship between the content of soil particles <20
μ
m
and measurements of soil surface area extracted from previously
published studies.
6
Materials and Methods
h is study was based on (i) new experimental data from a i eld
experiment with a natural gradient in soil clay content and (ii)
previously published data on soil specii c surface area.
Field Experiment
Soil Type and Experimental Treatments
h
e i eld experiment is situated at Research Centre Flakkebjerg
(55
°
19
′
N, 11
°
23
′
E), Aarhus University, Denmark. Average annual
temperature and precipitation are 7.8
°
C and 626 mm. h
e soil is
a sandy loam, freely drained and is classii ed as a Mollic Luvisol
according to the WRB (FAO) system (Krogh and Greve, 1999).
h
e area of the experimental i eld is 3.4 ha with a clay content
in the topsoil ranging from
?
100 to
?
220 g kg
−1
soil (Table 1).
h
e i eld has been in arable farming for centuries and now has a
SOM content of
?
16 g kg
−1
soil. Figure 1 shows the topography
of the i eld, the content of clay and OC in the topsoil, and the
corresponding clay/OC ratios. h
e concentration gradients in clay
and OC are probably af ected by long-term tillage erosion: the
elevated area in the southeastern part of the i eld is low in OC
content, perhaps due to B horizon soil being mixed into the topsoil
by tillage operations. Soil properties of the site have been detailed
by Djurhuus and Olesen (2000).
h
e experimental crop rotations were initiated in 1997 (Olesen et
al., 2000). h
e factorial design comprises three factors within two
replicate blocks. h
e factors are (i) the proportion of N
2
–i xing
crops in the rotation, (ii) the use of a catch crop undersown in
the spring in the cereal or pulse crop (with: +C, without: −C),
and (iii) the application of pig slurry (with: +M, without: −M)
or mineral fertilizer (+F). Further details on the i rst and second
course (1997–2004) of the crop rotations are given by Olesen et al.
(2000). From 2005, the organically grown crop rotation, −C−M,
was converted to conventional management, and mineral fertilizers
and pesticides were introduced (Askegaard et al., 2011).
From 2005 the organic rotations included grass–clover (organic
grass, OG) or faba beans (
Vicia faba
L.) (organic beans, OB) as
N
2
–i xing crop, while the conventional rotations included faba
beans (conventional beans, CB). Two of the organic rotations were
Table 1. Soil textural composition and cation-exchange capacity for the
0- to 25-cm layer of the experimental i eld as summarized for all 64
experimental plots.
Soil parameter
Unit
Mean
Median SD
Min. Max.
Soil organic matter
g kg
−1
16.0
16.2
1.73
8.8
20.2
Clay, <2
μ
m
143
139
23.3
103
217
Silt, 2–20
μ
m
134
135
10.5
102
153
Sand I, 20–63
μ
m
94
96
19.8
60
130
Sand II, 63–2000
μ
m
611
615
38.9
496
710
CEC†
mmol
c
kg
−1
106
15.1
† Cation-exchange capacity aft er Kalra and Maynard (1991) (data from
Djurhuus and Olesen, 2000).
Fig. 1. Map of the experimental i eld with individual plots shown with
(a) isolines of elevation (topography), (b) isolines of clay, (c) isolines
of organic carbon (OC), and (d) isolines of clay/OC. h
e i eld
experiment included 64 of the total of 72 plots.
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without slurry application but included catch crops (Table 2). h
e
complete crop rotations were: (i) spring barley (
Hordeum vulgare
L.), (ii) grass–clover (a mixture of
Lolium perenne
L.,
Trifolium
repens
L., and
Trifolium pratense
L.) (OG) or faba beans (OB and
CB), (iii) potato, and (iv) winter wheat (
Triticum aestivum
L.). All
crops were grown every year, yielding a total of 64 experimental
plots (8 cropping systems × 4 crops × 2 replicates). Primary tillage
for all cropping systems was moldboard plowing. Secondary
tillage including preparation of seedbed was accomplished by
dif erent tine cultivators. Wheeling was restricted to permanent
tracks except during tine cultivation where twin wheels on
tractors reduced the compaction impact. Harvest of potatoes was
performed by machinery (1-row ASA-lift ) that accomplished a
rather intensive disturbance of the upper
?
15 cm soil layer.
Soil Sampling and Measurements
In spring 2007, 2008, and 2009, we collected minimally disturbed
cubes (
?
700 cm
3
) from the 6- to 13-cm soil layer as described by
Schjønning et al. (2002). Sampling took place in the winter wheat
plots (16 plots; 8 cropping systems
×
2 replicate plots) at water
contents close to i eld capacity. h
e cubes were sampled in three
subplots (1 by 1 m
2
) within each experimental plot to account for
within-plot variation. In addition, larger blocks of soil (7 by 20 by
15 cm
3
) were retrieved from the same soil depth. Sampling and
transportation procedures avoided subsequent compaction and
smearing of the i eld-moist soil cubes and blocks, and the cubes
were stored at 2
°
C until analyses. h
e soil blocks were spread out
and left to air-dry in a ventilated room at 25
°
C. h
e drying soil was
inspected daily, and individual clods were carefully fragmented by
hand along natural planes of weakness when reaching their state
of maximum friability. We then used a nest of sieves to obtain air-
dried aggregates in four size classes 1 to 2, 2 to 4, 4 to 8, and 8 to
16 mm, as detailed by Elmholt et al. (2008).
Aft er temperature equilibration at 20
°
C, soil was subsampled
from the moist undisturbed soil cubes using a small corer (12-mm
diam.). h
e subsample was gently fractionated by hand to pass an
8-mm sieve. Subsamples of approximately 10 g of soil were taken
for determination of clay dispersibility as outlined by Pojasok and
Kay (1990). Cylindrical plastic bottles with the soil subsample and
80 mL distilled water were rotated end-over-end (33 rpm, 23-cm
diam. rotation) for 2 min and then left to stand for 3 h 50 min,
allowing particles >2
μ
m to settle. Subsequently, the suspension
containing particles
≤
2
μ
m, i.e., the dispersed clay, was siphoned
of by pipette. h
e dispersed clay was determined aft er oven-drying
the suspension at 105
°
C. Stones >2 mm in the residual soil aft er
shaking were quantii ed to relate the dispersed clay to stone-free
soil. A soil subsample was taken for determination of water content
allowing results to be presented on a dry-weight basis.
Air-dry aggregates of 1- to 2-mm size were treated similarly for
determination of clay dispersibility. One portion of the aggregates
was submitted directly to the dispersion test, while another portion
was adjusted to a matric water potential of −100 hPa. h
e rewetting
included capillary wetting on tension tables, initially with a
suction of 100 hPa. h
e aggregates while being held in a metal
ring underlined a synthetic cloth were gradually (over a period of
1 wk) exposed to reduced suctions until i nally equilibrated at 3
hPa. Next, the aggregates were equilibrated at −100 hPa suction by
gradually increasing the suction. h
e water contents of the air-dry
as well as rewetted aggregates were determined.
Tensile strength of air-dry aggregates of all four size classes was
measured as detailed by Munkholm et al. (2001). In brief, the
aggregates were crushed individually between two parallel plates in
an indirect tension test. We tested 15 individual aggregates for each
combination of sampling year, aggregate size class, and experimental
plot (2 yr × 4 size fractions × 16 plots × 15 aggregates = 1920 tests).
h
e aggregate tensile strength (
Y
) was calculated from the equation
(Dexter and Watts, 2000):
Y
= 0.576
F
/
d
2
[1]
where
F
(N) is the polar force required to fracture the aggregate
and
d
(m) is the mean aggregate diameter. In this study
d
was
estimated from:
d
= (
o
1
+
o
2
)/2
[2]
where
o
1
and
o
2
are the openings of the upper and lower sieves
for the specii c size-class. h
e rupture energy,
E
, was derived by
calculating the area under the stress-strain curve (Vomocil and
Chancellor, 1969):
Table 2. Cropping systems investigated. Cuttings of grass–clover in the
organic grass (OG) systems were removed in the +M treatments and an
equivalent amount of total N was applied as manure in the rotation.
Cropping system
acronym†
N i xing crop
OG/OB/CB
Nutrient source‡
± M/F
Catch crops§
± C
OG−M+C
grass-clover
none
present
OG+M−C
grass-clover
pig slurry stored
absent
OG+M+C
grass-clover
pig slurry stored
present
OB−M+C
faba bean
none
present
OB+M−C
faba bean
pig slurry stored
absent
OB+M+C
faba bean
pig slurry stored
present
CB+F−C¶
faba bean
mineral fertilizer
absent
CB+F+C¶
faba bean
mineral fertilizer
present
† C, catch crop; CB, conventional beans; F, fertilizer; M, manure; OB, organic
beans; OG, organic grass.
‡ Average level of N application in manure or fertilizer for each system during
third course (2005–2008): 72, 71, and 102 kg ha
−1
yr
−1
for the OG, OB,
and CB systems, respectively.
§ Dif erent catch crop mixtures were used throughout the experimental period;
please consult Askegaard et al. (2011) for details.
¶ First and second course (1997–2004) grown without any supply of nutrient.
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E
≈
Σ
i
F
(
s
i
)
Δ
s
i
[3]
where
F
(
s
i
) is the mean force at the
i
th subinterval and
Δ
s
i
is
the displacement length of the
i
th subinterval. h
e mass-specii c
rupture energy,
E
sp
, was calculated as:
E
sp
= E
/
m
[4]
where
m
is the mass of the aggregate. For the aggregate size classes 4
to 8 and 8 to 16 mm, we measured
m
for each individual aggregate
tested for tensile strength. For the two smallest aggregate size
classes, mean
m
values were estimated by weighing a collection
of 160 aggregates for each combination of sampling year and
aggregate size class.
Soil friability was calculated for each experimental plot based on
average test data from aggregate crushing tests. Friability based on
tensile strength data,
k
Y
, was estimated from the equation (Utomo
and Dexter, 1981):
log
e
(
Y
) = −
k
Y
log
e
(
V
) +
A
Y
[5]
where log
e
is the natural logarithm,
A
Y
is the predicted log
e
strength of 1 m
3
soil, and
V
(m
3
) is the estimated aggregate volume.
An estimate of soil friability based on aggregate specii c rupture
energy,
k
E
, was similarly calculated as:
log
e
(
E
sp
) = −
k
E
log
e
(
V
) +
A
E
[6]
where
A
E
is the predicted log
e
specii c rupture energy of 1 m
3
soil.
In 2008, soil from the 0- to 25-cm depth was collected from
all individual experimental plots by merging a total of 16 auger
samples taken randomly across each
plot. h
e soil content of clay (<2
μ
m)
and silt (2–20
μ
m) was determined
by the hydrometer method based on
air-dried soil crushed to pass a 2-mm
sieve. Soil carbon was determined on
ball-milled subsamples using a LECO
CNS-1000 analyzer with IR detector
(LECO Corporation, St. Joseph, MI).
h
e soil was tested for free carbonates,
and soil OC was calculated as the
dif erence between total carbon and
carbonate-carbon. Only two of the
64 plots contained carbonates. We
calculated the change in soil content of
carbon from 1996 to 2008 (three full
rotations) by comparing the measured
data for each plot to those reported for
1996 by Djurhuus and Olesen (2000).
Sta s cs
The change in soil OC (difference between 1996 and 2008
measurements) were treated by a mixed model with crop rotation
as i xed ef ect and block and “i eld” within each rotation as random
effects. In these tests, the Kenward–Roger method was used for
calculating degrees of freedom. Clay dispersibility, tensile strength
and rupture energy of aggregates, and soil friability estimated for
each individual year of measurement were tested in a mixed model
excluding block as a factor but including soil clay content as a covariate.
Tests across years of measurement included year as a random ef ect.
Speci
fi
c Surface Area Data
We collected data on soil specific surface area (SA) from the
literature (Table 3). All SA values were determined using the
ethylene glycol monoethyl ether (EGME) method (Petersen et al.,
1996; Pennell, 2002). h
e SA of organic soils of dif erent origin
measured by EGME was found to be similar to SA measured
by CO
2
(de Jonge et al., 2000). Cihacek and Bremner (1979)
investigated the effect of removing organic matter on surface
area measured by the EGME method and found no dif erence on
overall SA for samples with and without pretreatment. Further, de
Jonge et al. (2000) found that the microporous structure of more
rigid organic soil materials was not strongly af ected by EGME
penetration. It is likely that organic matter partially covers clay
surfaces when forming organo-mineral complexes, hereby reducing
the effective surface area measured using the EGME method.
On these bases, the literature soils used in this study were not
pretreated to remove organic matter nor saturated with Ca
2+
.
A total of 63 soils were included, 35 from topsoils and 28 from
subsoil layers. None of the data sources provided information
on soil mineralogy. h
e data sets included soils from a range of
European countries with 16 to 276 g clay kg
−1
, 9 to 273 g silt (2–20
μ
m) kg
−1
, and 1.7 to 28.3 g OC kg
−1
soil (Table 3).
Table 3. Selected properties of soils from literature with data on specii c surface area (SA). For all soils, SA
was determined by the ethylene glycol monoethyl ether (EGME) method described by Petersen et al. (1996).
Soil label
Country
Number
of soils
Clay
(<2
μ
m)
Silt
(2–20
μ
m) Organic C
Surface area
Symbol in
Fig. 12–13
Source†
—————— g kg
−1
———————— m
2
g
−1
Bad L.
Germany
6
256–266 254–273
15.3–23.7
47.2–54.3
diamond
A
Aarup
Denmark
9
111–233 102–247
12.6–21.5
12.2–62.3
square B
Lib-DK
Denmark
3
69–202
91–248
12.5–16.3
10.4–37.3
triangle
C
IFA
Austria
1
247
163
18.4
40.2
inverted triangle C
Kettering
U.K.
1
245
145
20.9
52.3
hexagon
C
Kübel
Austria
1
201
326
28.3
85.0
black inverted
triangle
C
P2
Spain
1
203
78
5.6
19.1
black hexagon
C
DSL‡, topsoil Denmark
13
37–163
38–228
9.3–19.1
5.0–52.7
circle
D
DSL‡, subsoil Denmark
28
16–276
9–244
1.7–23.8
3.9–111.3
gray circle
D
† Source: A: Vendelboe et al. (2012); B: Vendelboe et al. (2011); C: de Jonge et al. (2008); D: Petersen et al. (1996)
and Resurreccion et al. (2011).
‡ DSL: Danish Soil Library (Hansen, 1976).
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6
Results and Discussion
Soil Clay and Soil Organic Carbon
Figure 2 shows the content of clay and OC in the top 25 cm
soil of all 64 experimental plots. h
e 48 plots sampled for clay
dispersibility during 3 yr are shown by open symbols, while the
remaining plots are in gray. h
e soil OC content is relatively small
and unaf ected by soil clay content. h is is in accordance with
other studies of clay gradients (Schjønning et al., 1999; Arthur
et al., 2012). h
e clay content across the plots ranges from around
10 to 22%. h
e lines with arrows and labels refer to the division of
clay and OC suggested by Dexter et al. (2008):
CC = (
n
OC) if (
n
OC < clay), else CC = clay
[7]
NCC = (clay-CC) if (clay-CC) > 0, else NCC = 0
[8]
COC = OC if OC < (clay/
n
), else COC = (clay/
n
) [9]
NCOC = OC-COC if (OC-COC) > 0, else NCOC = 0 [10]
where CC is complexed clay, NCC is noncomplexed clay, COC is
complexed OC, NCOC is noncomplexed OC, and
n
is an (integer)
number. We have inserted the line
n
= clay/OC = 10 as suggested
by Dexter et al. (2008) for “saturation” of clay with OC. Following
this terminology, the soil for all 64 plots is “unsaturated” with OC.
We note that the soil’s content of NCC will be determined partly
by the soil clay content but also by OC; i.e., the data set of NCC
will not be a simple mirror of the data set of clay.
Crop Rota on E
ff
ects on Soil Organic Carbon
h
e large variation across the i eld in soil OC (Table 1, Fig. 1 and
2) prevents evaluation of management effects from the 2008
measurements of OC. Instead we used the dif erence between OC
measured in 1996 and in 2008 and observed a decrease in soil OC
for nearly all crop rotations (Fig. 3). Given the long arable history
of this site (and hence the relatively small OC contents at the start
of the i eld experiment), we expected an absolute increase in soil
OC at least for the rotations with animal manure and catch crops.
When considering the relative changes in the soil OC between
1996 and 2008, we observed that OC accumulation was largest
in the OG+M+C rotation and dif ered signii cantly from the OB
and CB rotations. For the cropping systems OG, OB, and CB,
inclusion of a catch crop tended to increase soil OC. h
e trend
was not statistically signii cant for individual rotations but when
averaged across the two organic systems (OG and OB, where catch
crops had been used throughout the 12-yr period), catch crops gave
an excess OC content of 0.688 g kg
−1
(
P
= 0.023; analyses not
shown). h
e use of grass–clover in the OG rotations as compared
to faba bean in the OB rotations gave a signii cantly higher OC
content of 1.224 g kg
−1
(
P
= 0.001; analyses not shown).
Assuming an average bulk density of 1500 kg m
−3
and a plowing
depth of 25 cm, the use of catch crops caused an average increase
of
?
0.2 Mg OC ha
−1
yr
−1
. Compared to the faba beans, the
grass–clover crop provided an excess input of
?
0.38 Mg OC ha
−1
yr
−1
. However, since grass–clover was only grown every fourth year
in the rotation, the estimated increase from each year of grass–clover
is 1.5 Mg OC ha
−1
yr
−1
. h is may be compared with an annual
increase of 1.1 Mg OC ha
−1
yr
−1
estimated for a 6-yr grass-only ley
in Denmark (Christensen et al., 2009) and 0.6 Mg OC ha
−1
yr
−1
for long-term pastures in Europe (Soussana et al., 2004). h
e higher
carbon accumulation in the present experiment may be attributed
to the fact that the grass–clover cuttings were mostly mulched and
thus contributed to soil OC, whereas the aboveground biomass in
the other experiments was either cut and removed or grazed. Catch
crops were on average grown every second year, giving an estimated
sequestration of
?
0.4 Mg OC ha
−1
yr
−1
. h
is may be compared
Fig. 2. Topsoil organic carbon (OC) plotted versus clay for the 64
experimental plots. h
e plots used for studies of clay dispersibility are
with white symbols and the rest with gray. (COC, complexed organic
carbon; NCOC, noncomplexed organic carbon; CC, complexed
clay; NCC, noncomplexed clay; please consult text for quantitative
dei nitions. h
e square symbol is a hypothetical soil inserted to display
the NCOC term.)
Fig. 3. Changes in topsoil (0–25 cm) content of organic carbon (OC)
from start of experimentation in 1996 to 2008. Please consult Table 2
for explanation of crop rotation legends. Bars labeled with the same
letter are not signii cantly dif erent (
P
= 0.05).
15391663, 2012, 1, Downloaded from https://acsess.onlinelibrary.wiley.com/doi/10.2136/vzj2011.0067 by Hayley Peter-Contesse , Wiley Online Library on [18/10/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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with annual carbon increases of 0.2 Mg ha
−1
yr
−1
estimated in a
long-term experiment in Denmark with perennial ryegrass (
Lolium
perenne
L.) as catch crop (h
omsen and Christensen, 2004). h
us
the carbon sequestration provided by catch crops appears to be less
than half of that obtained by full-year grassland crops.
Crop Rota on E
ff
ects on Clay Dispersibility
Clay dispersibility measured for bulk soil as well as aggregates
is shown in Table 4. Dispersion from the field-moist soil was
considerably greater than from aggregates, even when these
were rewetted and drained to −100 hPa matric potential. h is
is ascribed to interaggregate soil material being more vulnerable
to slaking than soil within discrete aggregates that survived the
fragmentation process in the laboratory. It may, however, also
rel ect a time dimension in soil structural stability. Dexter et al.
(2011) showed that rewetting of dried soil did not immediately
return soil dispersibility to original levels. The dispersibility
of i eld-moist soil was signii cantly greater in 2008 than in the
other years (analyses not shown). In contrast, the dispersibility of
rewetted aggregates was smallest in 2008. For dry aggregates, the
dispersibility was greater in 2008 than in 2009 (no data available
for 2007).
Ef ects of crop rotation on clay dispersibility were not found for
the 2007 and 2008 measurements. Neither did an analysis across
the 3 yr reveal statistically signii cant ef ects. h
is was true for i eld-
moist bulk soil (from cubes) as well as for 1- to 2-mm aggregates.
In 2009, however, signii cant ef ects were found for all three tests
(Fig. 4). For aggregates (rewetted as well as dry), the use of catch
crops reduced clay dispersibility in the OG system (OG+M−C
vs. OG+M+C). A similar trend was observed for i eld-moist soil.
h
e most consistent ef ect was a smaller dispersion of clay in the
CB+F+C rotation than in the other rotations (although not
signii cantly dif erently from all). h
e ef ect was found for moist
bulk soil as well as aggregates. h
is is remarkable as this rotation
was grown without any manure or fertilizers during the i rst 8
yr of the i eld experiment (Olesen et al., 2000). Please consult
Schjønning et al. (2007) for a detailed study of the nutrient- and
carbon-exhausted soil of this rotation as compared to systems
including catch crops and manure. In 2009, the CB plots examined
in this study had received mineral fertilizers in the previous 3 yr
only, suggesting that mineral fertilizers combined with catch crops
may reduce clay dispersibility. h
is could be due to formation of
labile OC fractions active in stabilization of soil structure. We have
previously shown that the clay dispersibility of an OC-depleted soil
was correlated to hot-water extractable OC (Elmholt et al., 2008).
Clay Dispersibility and the Clay/Organic
Carbon Ra o
According to the concept proposed by Dexter et al. (2008), the
fraction of clay “complexed” to OC (CC, Eq. [7]) should be
protected from dispersion in water, and the noncomplexed
fraction (NCC, Eq. [8]) should be a better predictor of clay
dispersibility than the total clay content. Figure 5 shows the
amount of clay dispersed from rewetted and dry aggregates
plotted versus the content of total clay and versus NCC. We note
that clay dispersibility increases with increase in total clay as well
as with NCC. h
e correlation of dispersible clay to total clay is
in accordance with other studies (e.g., Kjaergaard et al., 2004;
Vendelboe et al., 2012). h
e scatter around the regression lines
actually diminishes when dispersed clay is plotted against NCC
instead of total clay (Fig. 5), supporting the concept of Dexter et al.
(2008). We quantii ed this observation by regressing the dispersed
clay against NCC using dif erent
n
values. For an
n
value of 0 in
Eq. [7], NCC equals total clay and increasing
n
values represents
an increasing fraction of the total clay being complexed with OC.
h
e coei
cient of determination,
R
2
, increases with
n
supporting
the clay saturation hypothesis (Fig. 6). For dry aggregates, the
maximum
R
2
was found for
n
= 12 in both years with observations.
For rewetted aggregates, the maximum
R
2
was found for
n
ranging
from 7 to 10. h
is is in close agreement with Dexter et al. (2008),
who found
n
to vary in the range 8 to 11, thus suggesting
n
= 10 as
a general threshold. h
e pattern was much less clear for the i eld-
moist soil cubes, where
R
2
for each individual year varied less with
n
and displayed a maximum at
n
?
6 for 2008 and 2009 and
n
=
14 for 2007 (Fig. 7). h
e scatter in the
R
2
values for high
n
values,
especially for rewetted aggregates, may rel ect an increase in the
number of plots with NCC values of 0, giving a “jump” in the
R
2
value. However, this does not necessarily disqualify that better
regression models are obtained for
n
values higher than 0. Dexter et
al. (2008) used a slightly dif erent approach to estimate the
n
value
in Eq. [7] with respect to readily dispersible clay for a total of 210
Polish soils. Our data do not allow us to estimate a quantitatively
exact value of
n
, but the pattern in the dispersibility data (Fig. 5
and 6) tends to support
n
values close to 10.
Soil Aggregate Strength and Soil Friability
Several studies have shown that large amounts of readily dispersible
clay may increase the tensile strength of dry aggregates (Kay and
Dexter, 1992; Watts and Dexter, 1997; Elmholt et al., 2008).
h
is is probably due to dispersed clay forming internal crusts and
“cemented” surfaces when the soil dries up. Soil organic matter
may play a double role here. Soil organic matter is not only a
crucial component in aggregation (e.g., Tisdall and Oades, 1982)
but also affects the proportion of clay (NCC), which in turn
inl uences clay dispersibility and hence the risk of cementation
in drying. A structural hierarchy of soil (Hadas, 1987; Dexter,
1988; Oades and Waters, 1991) implies that the structure of
soil in situ is made up of large macroaggregates, which in turn
are composed of microaggregates formed by associations of
dif erently sized primary organo-mineral particles. A diversity
of SOM components is involved in creating and stabilizing the
dif erent levels of the structural hierarchy. h
e strength of bonds
between the components of any hierarchical level may be measured
by the tensile strength of components associated with the next
higher level in the structural hierarchy (Dexter, 1988). Aggregate
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Table 4. Soil content of clay and organic carbon, and clay dispersibility measured from i eld-moist soil (cubes) as well as aggregates either air-dry or
rewetted and drained to −100 hPa.
Year
Cropping system† Plot
Clay
Organic
carbon
Clay/
organic
carbon
Dispersed clay
Field moist whole soil‡
Aggregates, rewetted§
Aggregates, air-dry¶
——— g kg
−1
soil ———
———————————————— g kg
−1
soil ————————————————
2007
OG−M+C
18
197
9.0
21.9
25.0
(0.6)
4.81
(0.08)
–
–
69
119
8.6
13.8
22.2
(1.3)
2.16
–
–
–
OG+M−C
33
132
9.8
13.5
16.0
(1.5)
2.16
–
–
–
68
124
8.5
14.5
11.3
(0.3)
2.40
–
–
–
OG+M+C
35
120
10.4
11.5
15.0
(1.7)
2.08
–
–
–
70
147
9.5
15.4
22.6
(1.3)
2.51
(0.02)
–
–
OB−M+C
12
127
9.8
13.0
14.4
(0.6)
2.28
–
–
–
63
174
9.0
19.3
33.1
(3.3)
4.76
(0.06)
–
–
OB+M−C
2
134
9.2
14.6
18.7
(1.2)
2.40
(0.00)
–
–
51
147
8.3
17.7
20.3
(3.7)
2.76
.
–
–
OB+M+C
28
132
8.9
14.8
19.0
(1.7)
2.40
–
–
–
52
139
10.5
13.2
19.2
(2.3)
2.59
–
–
–
CB+F−C
20
159
7.8
20.4
32.6
(1.5)
4.35
(0.22)
–
–
41
139
8.5
16.3
19.6
(2.8)
3.49
–
–
–
CB+F+C
3
126
9.9
12.8
18.1
(1.7)
2.56
(0.01)
–
–
50
153
9.6
16.0
16.9
(0.9)
2.90
(0.02)
–
–
2008
OG−M+C
29
132
9.6
13.8
28.8
(0.6)
2.00
(0.00)
1.92
(0.04)
64
139
9.7
14.3
26.4
(1.2)
2.41
(0.00)
2.18
(0.02)
OG+M−C
8
207
8.4
24.6
40.1
(1.2)
4.31
(0.04)
2.87
(0.02)
55
132
8.7
15.2
26.8
(4.8)
2.10
(0.02)
2.02
(0.02)
OG+M+C
26
113
9.0
12.5
29.5
(0.9)
1.54
(0.10)
1.88
(0.24)
47
148
10.7
13.8
32.3
(0.3)
2.07
(0.02)
1.88
(0.00)
OB−M+C
25
113
9.4
12.0
21.2
(0.6)
1.42
(0.06)
1.66
(0.02)
37
140
10.4
13.4
21.6
(0.9)
1.95
(0.02)
1.91
(0.22)
OB+M−C
24
116
8.9
13.1
25.7
(0.4)
1.58
(0.14)
1.72
(0.00)
61
126
10.1
12.5
24.9
(1.0)
1.86
(0.02)
1.68
(0.00)
OB+M+C
7
197
8.6
22.9
36.4
(1.9)
5.67
(0.20)
3.66
(0.00)
40
132
9.8
13.5
26.9
(1.2)
1.98
(0.02)
1.90
(0.06)
CB+F−C
19
186
7.9
23.6
37.8
(4.3)
3.82
(0.06)
2.77
(0.04)
65
131
7.7
17.0
24.4
(0.3)
2.86
(0.10)
2.36
(0.04)
CB+F+C
27
120
9.1
13.1
27.0
(1.4)
2.14
(0.06)
2.14
(0.02)
59
148
9.8
15.1
26.1
(1.3)
2.65
(0.08)
2.28
(0.12)
2009
OG−M+C
31
152
9.7
15.7
13.4
(0.8)
3.08
(0.15)
1.90
(0.02)
44
159
9.8
16.2
18.2
(3.1)
3.19
(0.02)
2.07
(0.02)
OG+M−C
5
217
9.1
23.8
39.8
(1.8)
5.81
(0.07)
2.80
(0.02)
66
111
8.4
13.2
9.7
(1.5)
2.56
(0.00)
1.80
(0.00)
OG+M+C
13
120
10.8
11.2
9.7
(0.9)
1.91
(0.14)
1.44
(0.00)
38
141
10.4
13.5
15.4
(1.6)
2.69
(0.08)
1.59
(0.02)
OB−M+C
15
167
8.2
20.3
26.9
(1.3)
3.94
(0.04)
2.03
(0.06)
39
140
9.4
14.9
19.0
(3.8)
2.75
(0.14)
1.73
(0.04)
OB+M−C
36
133
9.9
13.4
13.2
(1.4)
2.01
(0.00)
1.37
(0.04)
46
148
10.2
14.5
18.5
(1.6)
3.15
(0.02)
1.85
(0.12)
OB+M+C
30
146
8.9
16.4
13.8
(0.9)
3.17
(0.03)
2.06
(0.02)
54
146
9.2
15.8
18.8
(1.0)
3.21
(0.00)
1.92
(0.00)
CB+F−C
16
175
8.3
21.0
25.2
(3.1)
4.79
(0.07)
2.25
(0.08)
57
132
8.5
15.5
15.5
(1.6
3.07
(0.02)
1.88
(0.00)
CB+F+C
10
152
9.7
15.7
15.2
(0.6)
2.87
(0.22)
1.67
(0.02)
60
133
11.7
11.4
9.3
(0.2)
2.09
(0.16)
1.33
(0.00)
† Abbreviations: C, catch crop; CB, conventional beans; F, fertilizer; M, manure; OB, organic beans; OG, organic grass.
‡ Standard error rel ects i eld subareas for sampling (
n
= 3).
§ Standard errors refer to laboratory replicates (
n
= 2). No standard error means only measurement on one sample.
¶ No data indicates there was insui
cient quantity of soil material for tests.
15391663, 2012, 1, Downloaded from https://acsess.onlinelibrary.wiley.com/doi/10.2136/vzj2011.0067 by Hayley Peter-Contesse , Wiley Online Library on [18/10/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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tensile strength of natural or well-managed soils decreases with
increasing aggregate size (e.g., Braunack et al., 1979; Munkholm
et al., 2001). Utomo and Dexter (1981) dei ned soil friability as the
tendency of an unconi ned soil to break down and crumble under
applied stress into a particular size range of smaller fragments.
Friability may hence be quantii ed by relating the tensile strength
of aggregates to their size (volume) (Dexter and Kroesbergen,
1985). We hypothesize that the quantity of NCC in a soil is a key
determinant for soil friability.
Analyses of variance showed no statistically signii cant ef ect of crop
rotation on tensile strength and rupture energy of aggregates, nor
on the friability of soil (analyses not shown). h
is is ascribed to the
large variation in texture and SOM across the experimental i eld,
although we did use clay as a covariate in our statistical analyses.
The tensile strength as well as the specific rupture energy of
aggregates increased with NCC (Fig. 7). In contrast to clay
dispersibility, NCC was not a better predictor of tensile strength
and rupture energy than was the content of total clay. h
us we
found approximately the same relationship between aggregate
strength expressions and total clay as shown for NCC. We choose,
however, to use NCC in Fig. 7 as our data for clay dispersibility
suggest that NCC relates better to the mechanisms involved and
therefore may be a superior determinant. Although Fig. 7 is based
on geometric means across all four size classes, similar trends were
observed for individual aggregate size classes. Rupture energy
has been suggested for expressing aggregate strength rather than
tensile strength since no assumptions on mode of failure have to
be taken for rupture energy (Perfect and Kay, 1994). Our data
indicate that both expressions relate similarly to NCC. Please note
that both expressions of aggregate strength showed higher values in
2008 than in 2007, especially for smaller values of NCC.
Figure 8 shows the relation between aggregate tensile strength and
volume for four selected experimental plots. In accordance with
Fig. 4. Crop rotation ef ects on dispersible clay
from either i eld-moist soil, aggregates at −100
hPa matric potential, and air-dry aggregates
for experimental plots sampled in 2009. Please
consult Table 2 for explanation of crop rotation
legends. Bars marked with the same letter are not
signii cantly dif erent (
P
= 0.05).
Fig. 5. Dispersed clay from 1- to 2-mm aggregates either air-dried or rewetted and equilibrated
at −100 hPa matric potential and shown for each individual experimental plot. Results are
plotted and regressed vs. soil content of total clay (left ) or noncomplexed clay (NCC) (right;
n
= 10 in Eq. [7]).
15391663, 2012, 1, Downloaded from https://acsess.onlinelibrary.wiley.com/doi/10.2136/vzj2011.0067 by Hayley Peter-Contesse , Wiley Online Library on [18/10/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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Fig. 7, the high-NCC Plot 18 showed higher tensile strengths for
all four aggregate size classes than Plot 3 low in NCC (Fig. 8a).
In addition, the slope of the regressed relation between aggregate
volume and strength (
k
Y
, i.e., the soil friability) was lower for the
high-NCC Plot 18 than Plot 3 (see inserted values). In accordance
with the observations presented in Fig. 7, Fig. 8b shows that for
two plots with comparable contents of NCC, the plot sampled in
2008 had the highest tensile strength and the smallest friability.
h
is is discussed below.
Soil friability across all experimental plots tended to decrease with
an increase in NCC (Fig. 9). However, the trend was signii cant
only in 2008. As seen for the experimental plot in Fig. 8b, soil
friability generally was much lower in 2008 than in 2007. h
e
simple regression model with NCC as descriptor of friability
explained much less of the variation in data than was the case for
clay dispersibility (Fig. 5 and 6). For 2007, the
R
2
increased from
0.054 to 0.144 (Fig. 9). Using NCC with dif erent
n
values (Eq.
[7–8]) in the regression between NCC and friability showed a
maximum
R
2
at
n
= 11 in 2007, whereas no clear maximum was
detected in 2008 (analyses not shown).
Friability may be based on tensile strength data as well as on specii c
rupture energy. Figure 10 shows that these two independent
measures of friability correlate quite well.
k
E
= 1.09
***
k
Y
− 0.05
**
, SE = 0.034,
R
2
= 0.738
[11]
Stars denote level of signii cance: *:
P
< 0.05, **:
P
< 0.01, **:
P
<
0.001, and SE indicate standard error of estimate for this equation
and following. A few of the plots in 2008 displayed negative
k
E
values, which carries no physical meaning. In mathematical terms,
Fig. 6. Coei
cient of determination,
R
2
, in regression analyses of
dispersed clay vs. noncomplexed clay (NCC) with dif erent
n
value in
calculations (Eq. [7–8]). Regressions for
n
= 0 and
n
= 10 are shown
for aggregates in Fig. 5.
Fig. 7. Tensile strength and specii c rupture energy of air-dry aggregates calculated as geometric
means across the four aggregate size classes. h
e results are plotted vs. noncomplexed clay
(NCC) for each individual experimental plot. It should be mentioned that NCC did not
yield a better correlation than total content of clay.
Fig. 8. Log
e
aggregate strength,
Y
, (kPa) as a function of log
e
aggregate volume,
V
, (m
3
) for air-dry aggregates. Soil friability index,
k
Y
, determined as the slope of the regression equation is shown for
each selected experimental plot. (a) Two experimental plots with
contrasting content of non-complexed clay (NCC) both sampled in
2007. (b) One experimental plot each from 2007 and 2008 but with
similar contents of NCC.
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it expresses higher specii c rupture energy levels of
large than of small aggregates (analog to positive
slopes in the plots in Fig. 8). We note that for
negative
k
E
values corresponding to
k
Y
values below
?
0.06 (Fig. 10), there is no signii cant dif erence
between the specii c rupture energy of dif erently
sized aggregates. h
is rel ects a collapse of the soil
structural hierarchy. Such soils can be regarded as
a homogeneous material across the bulk mass of
soil to the size of the largest aggregates. Watts and
Dexter (1998) formed
?
10 mm balls by molding
natural moist aggregates by hand, whereby the
indigenous soil structure was destroyed. h
e balls
were subsequently used for establishing reference
tensile strength and friability estimates as compared
to natural aggregates. h
eir friability estimates (here
called F1) obtained with another approach than
used in this study were in the range F1 = 0.06–0.12
(dependent on origin). Dexter (2004) showed that
F1
?
2
k
Y
. Based on this, we expect
k
Y
values in
the range
?
0.03 to 0.06 to rel ect soils with a
destroyed structure. We note that this is exactly
the
k
Y
range for which
k
E
was negative (Fig. 10).
h
e soils in these experimental plots may thus
be characterized as having lost their structural
hierarchy.
Figure 9 showed a tendency of reduced friability with increased
NCC or total clay (signii cant only in 2008). h
e range in total clay
as well as in NCC was about identical for the 2 yr of investigation,
and the soil samples were from plots located randomly across the
experimental i eld for both years. h
e question then is: what can have
caused the poor friability in 2008 as compared to 2007? Weather
conditions for potato harvest (the crop preceding winter wheat) and
for the tillage preceding winter wheat planting were very poor in
2007 (i.e., for the plots sampled in 2008), while conditions were
near optimal in 2006. h
us the plots sampled in spring 2008 had
been exposed to intensive mechanical treatment during the previous
potato harvesting under wet conditions. In addition, the plots were
not plowed in the autumn 2007 but instead cultivated with a stubble
cultivator before sowing the winter wheat. Our results thus seem to
indicate that the impact of day-to-day management may be at least
as decisive for soil structural strength and friability as dif erences
in NCC derived from long-term depletion of SOM. In a previous
study on a texturally comparable soil we found puddling of the soil
by intensive rotary cultivation and compaction by wheel trai
c at
wet conditions to increase the tensile strength of aggregates but not
soil friability (Munkholm and Schjønning, 2004).
As stated above, clay dispersibility of field-moist soil was
signii cantly higher in 2008 than in 2007 (Table 4). h
e very poor
friability of soil sampled in 2008 was rel ected in much readily
dispersible clay (Fig. 11), but clay dispersibility could also feed
back on soil friability (Chan, 1989; Kay and Munkholm, 2004).
It should be noted that the tendency line in Fig. 11 derives from the
dif erences between years only (no signii cant correlation between
clay dispersibility and friability within each experimental year).
Interestingly, the 1- to 2-mm aggregates that were resaturated
and drained to −100 hPa had signii cantly
lower
dispersibility in
2008 than in 2007. h is may be due to cementation during the
Fig. 10. Indices of friability based on either aggregate tensile strength,
k
Y
, or specii c rupture energy,
k
E
, for each individual experimental plot
in 2007 and 2008. Regression model relating the two parameters is
given in Eq. [11].
Fig. 9. Friability index,
k
Y
, calculated from the relation between log
e
tensile strength and log
e
aggregate volume (Fig. 8) for each individual experimental plot. h
e results are plotted vs.
soil content of clay (top) or vs. noncomplexed clay (bottom).
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air-drying of dispersed clay particles that are not again released
during the dispersion that follows short-term resaturation (Dexter
et al., 2011).
Mineral Surface Coverage with Organic Carbon
This study does not address the physicochemical mechanisms
involved in the interactions between soil minerals and SOM. It
is logical, however, to hypothesize that in some way the SA of soil
particles most likely relate to the ability of soil to interact with
organic substances. In Fig. 12 we relate the EGME-estimated SA
of a range of soils (Table 3) to the content of clay (Fig. 12a) and
clay plus silt here labeled Fines20 (Fig. 12b). We found a reasonable
correlation between SA and clay, with subsoils generally being
higher in SA than topsoils. Regression analyses indicated that the
intercept on the SA axis was not signii cantly dif erent from zero,
and the regression line was forced through (0,0):
Topsoils: SA = 0.20*
×
clay, SE = 10.6,
R
2
= 0.675
[12]
Subsoils: SA = 0.35*
×
clay, SE = 11.2,
R
2
= 0.875
[13]
where SA is in units of meters squared per gram, and clay in grams
per kilogram soil.
For Fines20 we found the correlations:
Topsoils: SA = 0.10*
×
Fines20, SE = 8.8,
R
2
= 0.778
[14]
Subsoils: SA = 0.19*
×
Fines20, SE = 11.3,
R
2
= 0.874
[15]
It is interesting to note that for topsoils
R
2
increased from 0.675 to
0.778 when substituting clay with Fines20, and the standard error
of SA estimates decreased from 10.6 to 8.8 m
2
g
−1
. h
is indicates
that the silt fraction (2–20
μ
m) contributes to the SA of soils, and
is in accordance with de Jonge et al. (2000), who found that the
silt fraction was responsible for approximately 20% of the total
SA. A clear indication of this is found by comparing the SA of the
Kübel soil (see Table 3) i tted to the regression models in Fig. 12a
and b (black triangle symbol). h
is soil is relatively high in i ne
silt (Table 3), and the improved i t to the regression model when
using Fines20 as the predictor clearly indicates that the i ne silt-
sized particles contribute to SA. Similarly, the P2 soil from Spain
(black hexagon symbol) appeared as an outlier with
lower
SA when
relating SA and clay but i tted well to the regression model when
Fines20 was used as predictor.
It is well established that SOM is associated with silt-sized organo-
mineral particles (Christensen, 1992). Hassink (1997) observed
that although a range of Dutch arable soils contained less OC than
corresponding grassland soils, the amounts of OC associated with
clay and silt particles were similar, suggesting that the amount of
carbon associated with this fraction had reached a maximum.
Fig. 11. Dispersible clay from i eld-moist soil (cubes) plotted vs. index
of friability,
k
Y
, for each individual experimental plot in 2007 and
2008. h
e regression line only rel ects dif erences between years (no
signii cant trends within each individual year).
Fig. 12. Specii c surface area, SA (m
2
g
−1
), for topsoils plotted vs.
soil content of (a) clay or (b) clay plus silt (<20
μ
m) for a range of
data in the literature. Please consult Table 3 for details of and legends
for the soils. h
e correlations are given in Eq. [12] and [14]. Subsoil
correlations (data not shown) are found in Eq. [13] and [15].
15391663, 2012, 1, Downloaded from https://acsess.onlinelibrary.wiley.com/doi/10.2136/vzj2011.0067 by Hayley Peter-Contesse , Wiley Online Library on [18/10/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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A close positive relationship between
the proportion of Fines20 in a soil and
the amount of OC associated with this
fraction has previously been reported
(Christensen, 1992; Hassink, 1997),
substantiating that the content of Fines20
in soil determines the capacity of a soil to
preserve OC rather than the content of
clay only. In Fig. 13, we have plotted the
SOM coverage against the clay/OC ratio
(Fig. 13a) and the Fines20/OC ratio (Fig.
13b). h
e SOM coverage was calculated
as SOM/SA. Assuming a SOM density
of 1 g cm
−3
, the SOM equivalent layer
thickness was calculated to range from
?
0.1 to 6 nm (right-hand ordinate axis in
Fig. 13b). We note that the Dexter clay/
OC ratio of
n
= 10 approximates a 1-nm equivalent SOM coverage
of EGME-accessible surfaces and that a distinct increase in SOM
per unit area of the mineral surface occurs at a clay/OC ratio of
about 10 (Fig. 13a). However, this also occurs for a Fines20/OC
ratio of about 20 (Fig. 13b). We found a close correlation between
(Fines20/OC) and (clay/OC), especially for topsoils:
Fines20/OC = 2.06
***
×
(clay/OC), SE = 2.35,
R
2
= 0.988 [16]
h
is indicates that a clay/OC ratio of 10 as suggested by Dexter et
al. (2008) for our topsoil data corresponds to a Fines20/OC ratio
of 20.6. In the regression presented in Eq. [16], we omitted the P2
soil (Table 3) because it was an outlier compared to the 34 other
topsoils in the data set.
h
e i tting lines in Fig. 13 were derived from linear regression of a
double-logarithmic presentation of data:
log
10
(SOM/SA) = −1.19
***
×
log
10
(clay/OC) + 1.09
***
,
SE = 0.160,
R
2
= 0.897
[17]
log
10
(SOM/SA) = −1.23
***
×
log
10
[(clay + silt)/OC] + 1.50
***
,
SE = 0.163,
R
2
= 0.894
[18]
We note that OC is included in the numerator of the ordinate
and in the denominator of the abscissa, which probably causes the
hyperbola-like appearance of the curve. Nevertheless, the point of
steep increase in SOM per unit soil surface indirectly supports the
concept of OC saturation (Hassink, 1997). h is point coincides
with a clay/OC ratio of 10, for which a change in physical behavior
was observed by Dexter et al. (2008) and also in this study. h
e
improved correlation between SA and mineral fraction when using
Fines20 instead of clay (Fig. 12) suggests that a Fines20/OC ratio
of 20 may serve as a similar threshold for soil physical behavior.
6
Conclusions and Perspec ves
Our results support the concept that clay dispersibility is
determined by the degree to which fine mineral particles are
saturated with OC, while the experimental evidence for aggregate
tensile strength and soil friability was less convincing. We conclude
that soil particles <20
μ
m may be a better predictor than clay for
soil surface area and the adsorption of SOM. Dexter et al. (2008)
found that approximately 10 g of clay was able to complex with 1
g of OC and that clay dispersibility increased with the amount of
noncomplexed clay. Our results indicate that the clay/OC ratio of
10 can be regarded mainly as an index and that the suggested (i nes
<20
μ
m)/OC ratio of 20 probably provides a better mechanistic
approach to explain the observed changes in soil physical behavior.
The concept of OC saturation of clay particles forwarded by
Hassink (1997) and later Dexter et al. (2008) does not cover all soil
types. It is most likely that soil mineralogy inl uences the capacity
of soil to complex with SOM and hence the (clay+silt)/OC
threshold ratio for changes in soil physical behavior. On the other
hand, Hassink (1997) included a range of soils with contrasting
mineralogy across the world. The only exception not obeying
the i nes <20
μ
m as a predictor of the capacity to preserve OC
in Hassink’s study was an Australian soil. Future studies should
relate the "i nes saturation" concept to terminology used in other
soil science research areas. Six et al. (2002) suggested SOM to be
dif erentiated into four fractions: 1. clay and silt protected OC, 2.
microaggregate protected OC, 3. biochemically protected OC, 4.
nonprotected OC. We consider that Fractions 1 and 2 correspond
to complexed OC in the saturation concepts of Hassink and Dexter
et al. Fractions 3 and 4 should then correspond to noncomplexed
OC in Dexter’s terminology. Because Fraction 4 may include labile
fractions, especially active in soil aggregation and hence structural
stabilization (e.g., Elmholt et al., 2008) and Fraction 3 may include
Fig. 13. Soil organic matter (SOM) relative to the specii c surface area (SA) (SOM coverage/layer
thickness) plotted against (a) the clay/organic carbon (OC) ratio and (b) the (clay+silt)/OC ratio
for the soils shown in Table 3 and Fig. 12
.
h
e i tting curves were derived by linear regression of log-
transformed abscissa and ordinate values and are given in Eq. [17] and [18].
15391663, 2012, 1, Downloaded from https://acsess.onlinelibrary.wiley.com/doi/10.2136/vzj2011.0067 by Hayley Peter-Contesse , Wiley Online Library on [18/10/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
Page 13
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resistant OC not actively involved in soil aggregation (h
omsen et
al., 2009), it remains a challenge to reveal how the quality of OC
links to the i nes/OC ratio threshold for soil physical behavior.
Fraction 4 may also include particulate organic matter, which
further calls for a rei nement of the terms used.
Our study indicates that tillage events may dominate over
noncomplexed clay as determinant of soil structural conditions.
We found greater OC storage in rotations with catch crops, while
grass–clover leys in the rotation stored an additional
?
380 kg OC
ha
−1
yr
−1
compared to faba beans. h is dif erence corresponds to
0.1 g OC kg
−1
soil yr
−1
, a quantity that would “complex” only 1 g
clay kg
−1
soil. In comparison, the NCC across the experimental
i eld ranged from 10 to 130 g kg
−1
(e.g., Fig. 9). It is hence a slow
process to change the structural conditions of a soil severely
depleted in OC. h is may be why the crop rotations had only a
small ef ect on clay dispersibility and no ef ect on soil friability.
Acknowledgments
We thank S.T. Rasmussen, J.M. Nielsen, P. Jørgensen, B.B. Christensen, and M.
Koppelgaard for technical assistance in sampling and laboratory measurements and
E. Driessen for managing the experimental i eld. Dr. K. Kristensen provided valuable
assistance in identii cation of statistical models. h
is study was i nanced partly by the
Danish Ministry of Agriculture and Fisheries (ICROF project “CROPSYS”) and
partly by the Danish Research Council for Technology and Production Sciences
(Soil-it-is project), and contributes to the EU supported project “SmartSoil.”
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