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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 113, B11102, doi:10.1029/2008JB005669, 2008
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Direct estimates of pedogenic magnetite as a tool to reconstruct
past climates from buried soils
Christoph E. Geiss,1 Ramon Egli,2 and C. William Zanner3
Received 4 March 2008; revised 4 July 2008; accepted 21 August 2008; published 7 November 2008.
[1] Variations in magnetic properties of buried soils can be used to reconstruct past
climatic conditions during paleosol formation. Most methods, however, are based on
comparisons between the magnetically enriched upper soil horizons and the magnetically
unaltered parent material. In thin loess-paleosol sequences such a comparison can be
problematic because all horizons, soil and underlying loess, may be affected to varying
degrees by pedogenesis. We propose two direct estimates of pedogenic magnetite based on
the analysis of anhysteretic remanent magnetization ratios (cARM/isothermal remanent
magnetization) and coercivity distributions. These estimates are independent of any
information regarding the parent material and are possible if pedogenic minerals have
similar magnetic properties throughout the study region. This condition seems to be met
throughout the Midwestern United States and a few loessic soils elsewhere. The
remanence-carrying part of pedogenic magnetite is composed of single-domain particles
with consistent, well-constrained magnetic properties. These particles are extremely well
dispersed in the soil matrix as indicated by the absence of noticeable magnetostatic
interaction effects. Our analyses of over 70 modern loessic soil profiles demonstrate that
the abundance of pedogenic magnetite correlates well with modern climate and that the
method is suited for reconstruction of past climates from paleosols.
Citation: Geiss, C. E., R. Egli, and C. W. Zanner (2008), Direct estimates of pedogenic magnetite as a tool to reconstruct past
climates from buried soils, J. Geophys. Res., 113, B11102, doi:10.1029/2008JB005669.
1. Introduction
[2] Many modern and buried soils are characterized by an
increased abundance of ferrimagnetic minerals (most likely
maghemite) in their upper soil horizons. This magnetic
enhancement of the topsoil can be detected through simple
rock-magnetic measurements, and the magnetic properties
of soils have long been used to quantify soil development.
Early studies [e.g., Heller and Liu, 1986; Kukla et al., 1988]
focused on changes in magnetic susceptibility (c) to reconstruct variations in climate and correlate the Chinese loesspaleosol sequence with the marine isotope record. Later,
Maher and coworkers [Maher and Hu, 2006; Maher and
Thompson, 1992, 1995; Maher et al., 1994] studied the
differences in susceptibility between the topsoil and the
unaltered parent material. They called this difference pedogenic susceptibility (cped = cBhorizon cparent material) and
used it to quantify past variations in rainfall across the
Chinese loess plateau. Similar reconstructions of past climates for the Chinese loess plateau include the work of Han
et al. [1996], who analyzed the magnetic susceptibility of
1
Department of Physics, Trinity College, Hartford, Connecticut, USA.
Department of Earth and Environmental Sciences, Ludwig-Maximilians-Universität, Munich, Germany.
3
Department of Soil, Water, and Climate, University of Minnesota,
St. Paul, Minnesota, USA.
2
Copyright 2008 by the American Geophysical Union.
0148-0227/08/2008JB005669$09.00
modern soils across China to reconstruct paleoclimatic
variations at Louchuan for the past 130 ka, and Heller et
al. [1993], who used a combination of geochemical and
magnetic methods.
[3] The use of soil magnetic properties as a paleoclimate
proxy [e.g., Heller and Evans, 1995; Maher, 1998] seems
justified because the observed changes in soil magnetic
properties are in most cases due to the neoformation of finegrained, single-domain (SD) or even finer, superparamagnetic (SP) ferrimagnetic particles [e.g., Geiss and Zanner,
2007; Maher, 1986; Mishima et al., 2001]. Though it is
possible to produce such particles in the laboratory or by
subjecting soils to a series of repeated wetting and drying
cycles [Le Borgne, 1960; Maher and Taylor, 1988; Taylor et
al., 1987], it is very likely that the formation of most
pedogenic ferrimagnetic material is aided by the presence
of iron-reducing bacteria [Dearing et al., 2001; Guyodo et
al., 2006; Maher and Thompson, 1999], whose activities are
highly dependent on available soil moisture, organic matter
content, and, to a lesser degree, temperature.
[4] While pedogenic susceptibility (cped) appears to be a
suitable paleorainfall proxy for the Chinese loess plateau,
Geiss and Zanner [2007] found a poor relationship between
cped and mean annual precipitation for approximately 75
modern loessic soils from the Midwestern United States,
which they attribute to the variability of the underlying
parent material [e.g., Muhs et al., 2008] or recent additions
of Eolian dust during the Holocene and their incorporation
into the soil profile [Jacobs and Mason, 2007; Mason and
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Jacobs, 1998]. Geiss and Zanner [2006] suggested that
simple ratios of magnetic parameters (e.g., ctopsoil/cparent
material) are better suited to compensate for parent material
heterogeneities. Since a large fraction of ferromagnetic and
remanence-carrying pedogenic magnetic minerals are in the
SD grain size range, Geiss and Zanner [2007] also proposed
magnetic proxies that are highly selective to this grain size
fraction of the pedogenic component, such as anhysteretic
remanent magnetization (ARM) or its normalized equivalent, susceptibility of ARM (cARM).
[5] All these techniques rely on a comparison between
the magnetically enhanced soil horizons and the (presumably) unaltered parent material. Such an approach is problematic if buried soils are separated by only a thin layer of
loess, which may be affected by pedogenesis, or if small
dust additions have been incorporated into a soil horizon. In
this study we explore the use of two-component mixing
models [e.g., Dunlop, 2002; Evans and Heller, 1994;
Mishima et al., 2001] to quantify the abundance of pedogenic magnetite in a soil sample without comparison to its
original parent material. Such an approach is possible
because for many loessic soils the pedogenic magnetic
component appears to have very similar magnetic properties
[Evans and Heller, 1994; Geiss and Zanner, 2006]. Here we
focus on the use of simple remanence ratios and the
coercivity analysis of magnetization curves [Egli, 2004a;
Geiss and Zanner, 2006; Robertson and France, 1994;
Stockhausen, 1998] to quantify the abundance of pedogenically produced ferrimagnetic minerals and their use as a
climate proxy.
2. Methods
2.1. Site Selection and Magnetic Analyses
[6] All soil profiles presented in this study have formed in
Peoria loess and were sampled from well-drained, stable
upland positions (Figure 1). To avoid anthropogenic influences we sampled old prairie cemeteries that have remained
unaffected by agricultural activity for at least a century. The
top 5 cm of the soil profile were not used for analyses
because of possible contamination through fly ash from
coal-burning power plants. Soil profiles were sampled using
a hydraulic soil probe. The 3 inch diameter cores were
described in the field using standard soil terminology [Soil
Survey Division Staff, 1993] and subsampled into small
plastic bags. The sampling interval was 5 cm for the magnetically enhanced portion of the soil profile and 10 cm
thereafter. All samples were air-dried in the laboratory, gently
crushed by hand, passed through a 2 mm sieve to remove
root fragments (no gravel was present in any of the samples)
and filled into weakly diamagnetic plastic boxes of 5.3 cm3
volume. Sample masses ranged between 5 and 7 g. Lowfield magnetic susceptibility (c) was measured using a
AGICO Kappabridge KLY 4S.
[7] Anhysteretic remanent magnetization (ARM) was
acquired using a Magnon International AFD300 or a D-Tech
2000 alternating-field demagnetizer. For both instruments
the peak AF field was 100 mT with a bias field Hbias = 50 mT.
Susceptibility of ARM (cARM) was calculated by dividing
the mass-normalized ARM values by the bias field (Hbias)
applied during ARM acquisition (cARM = ARM/Hbias).
Isothermal remanent magnetization (IRM) was acquired
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through three (to compensate for viscous effects during
IRM acquisition in a pulsed field) pulses of 100 mT using a
ASC-Scientific pulse magnetizer. All remanence parameters
were measured either in a cryogenic (2G – Model 760) or a
spinner (AGICO, JR-6) magnetometer.
[8] Coercivity distributions for most samples (except for
samples shown in Figures 2 – 4) were calculated from
alternating field (AF) demagnetization curves of an IRM
acquired in a pulsed magnetic field of 2.8 T. Stepwise
AF-demagnetization of the IRM up to a peak field of 300 mT
was performed with a Magnon International AFD300 alternating field demagnetizer. The data were fitted using two
cumulative lognormal distributions as described by Geiss
and Zanner [2006] to model the coercivity distributions of
pedogenic magnetite, a second component which represents
the magnetic contribution of the parent material, and all
high-coercivity minerals with switching fields <300 mT.
The model function of each coercivity distribution is controlled by three parameters: (1) the magnitude M
corresponding to the total magnetization of the specific
component, (2) the median coercivity Bh, and (3) the
dispersion parameter Dp corresponding to the width of the
distribution on a log10 scale. A total of six parameters are
needed to model a magnetization curve according to this
model without a priori assumptions (unconstrained fit). On
the basis of numerous unconstrained analyses, Geiss and
Zanner [2006] noted that the pedogenic component in the
magnetically enhanced horizons of loessic soils in the
Midwestern United States is characterized by very consistent parameters given by Bh 20 mT and Dp 0.3, while
the detrital component was rather heterogeneous. A different
procedure [Egli, 2003] was used for the coercivity analysis
of very detailed AF demagnetization curves of ARM and
IRM shown in Figure 2. The demagnetization curves are
obtained from the average of three identical experiments
where a remanent magnetization (ARM or IRM) was given,
and the sample was then stepwise demagnetized up to
200 mT in a total of 105 steps, equally spaced on a
logarithmic scale. To ensure exact reproducibility of the
experiments and avoid any viscous effect, AF demagnetization was started 3 min after the acquisition of a remanence, and a 10 s waiting time occurred between each AF
demagnetization step and measurement with a 2G cryogenic magnetometer. The high-precision experiments allowed
us to model the AF demagnetization curves using a generalization of the lognormal distribution, called SGG [Egli,
2003] that accommodates for the asymmetry of coercivity
distributions studied by Egli [2004b] The shape of a SGG
function is controlled by an additional skewness parameter,
so that a total of four parameters were used to model
each coercivity distribution. This approach gives Bh = 18 mT,
Dp = 0.3 for the ARM of pedogenic magnetite in a Chinese
paleosol [Egli, 2004a], and Bh = 21 mT, Dp = 0.32 for the
sample shown in Figure 2. The model parameters for
pedogenic magnetite are consistent throughout the entire
set of soil samples when analyzed with an unconstrained
fit, independently of the method used for coercivity
analysis. Since unconstrained fits require a large number
of precisely measured demagnetization steps, one can utilize
the constancy of the model parameters for the pedogenic
component, and constrain the fit algorithm to predetermined
values of Bh and Dp, while freely adjusting M and the
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Figure 1. Location of all soil profiles analyzed for this study. All sites are located in loess, well drained,
undisturbed by recent human activity, and located in stable upland positions.
parameters of the other component. In this study we used
Bh = 1.3 and Dp = 0.3, for the constrained analyses.
[9] In this study we use several magnetic parameters to
quantify magnetic enhancement of soils. They are listed in
Table 1 and can be calculated from the measurements
described above.
2.2. Characterization of SD Pedogenic Magnetite
[10] In contrast to the parent material, pedogenic magnetite particles that are blocked at room temperature are
mostly single domain. Unlike SD magnetic particles produced by magnetotactic bacteria, the size and shape of
pedogenic magnetite particles is not well constrained. Coercivity analysis has been successfully employed to characterize the SD fraction of pedogenic magnetite in loessic soils
[Egli, 2004a; Evans and Heller, 1994; Geiss and Zanner,
2006]. In all topsoil and paleosol samples investigated until
now, the coercivity distribution of the pedogenic component
was found to have strongly consistent properties Bh = 20 mT,
and Dp = 0.3 as discussed in the previous section. Through
the analysis of AF demagnetization curves of ARM and IRM
(Figure 2) it is possible to calculate the ratio cARM/IRM
(ARM ratio) for the pedogenic component [Egli, 2004a].
The ARM ratio is strongly grain size dependent and reaches
its maximum for particles whose size coincides with the
upper limit for coherent moment reversal. This limit has
been calculated for magnetite and corresponds to a grain
diameter of d = 5 nm for equidimensional particles [Newell
and Merrill, 1999]. Between this limit and the SP/SD
threshold of 20 nm (calculated for magnetite particles with
a microcoercivity of 80 mT), the ARM ratio is /d2, where d
is the grain diameter [Egli and Lowrie, 2002]. Using the
expression for ARM of Egli and Lowrie [2002], cARM/IRM =
1 3 103 m/A for noninteracting magnetite particles. For
comparison, the pedogenic component is characterized by
cARM/IRM = 0.8 2 103 m/A.
[11] Methods for pedogenic magnetite quantification
based on room temperature experiments rely on the SD
fraction, and the constancy of the corresponding magnetic
properties is of primary importance. ARM is a good
candidate for such methods, since it is naturally selective
toward the SD fraction; however, it is also extremely
sensitive to magnetostatic interactions [Egli, 2006b]. Effective volume concentrations as low as 1% are sufficient to
reduce the ARM by a factor of 2. Therefore, it is important
to establish if pedogenic particles are magnetically interacting, and if the interaction effects are eventually the same in
all soils. Quantitative methods for the analysis of interactions in SD particles have been developed recently [Chen et
al., 2007; Egli, 2006a]. Therefore, we present here a first
evaluation of interactions in pedogenic magnetite, based on
two samples, STP 18 and STP 70, of a soil developed on
glacial till in St. Paul, Minnesota (Waukegan silt loam). The
two samples were taken from the soil profile at depths of
18 cm and 70 cm, respectively. These two depths correspond
to horizons of maximum magnetic enhancement (18 cm) and
no enhancement (70 cm). The coercivity distributions calculated from AF demagnetization curves of ARM and IRM are
shown in Figure 2 for the enhanced. Unlike loessic soils, the
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Figure 2. Coercivity analysis of the 18 cm soil sample
from St. Paul, obtained from alternating field (AF)
demagnetization curves of (a) anhysteretic remanent
magnetization (ARM) susceptibility and (b) isothermal
remanent magnetization (IRM). Dots represent the coercivity distribution calculated by taking the first derivative of
the demagnetization curve according to Egli [2003],
whereby each dot represents a demagnetization step. In
both plots the upper coercivity distribution corresponds to
the bulk sample, and the lower curve was measured on the
same sample after coarse multidomain (MD) magnetite was
removed with a hand magnet. The dashed curves are model
functions used to fit the coercivity distribution, whereby the
fit is shown as a solid curve. Each model function represents
the coercivity distribution of a magnetic component. The
low-coercivity component is interpreted as arising from
pedogenic magnetite or maghemite particles in the singledomain (SD) range, while the high-coercivity component is
probably hematite. The coercivity distribution of MD
magnetite from the parent material is similar to that of the
pedogenic component and could not be resolved by
coercivity analysis. The magnetic contribution of MD
magnetite, however, is clearly shown by the difference
between the IRM coercivity distribution measured before
and after removing a coarse magnetic fraction with the hand
magnet. As expected, ARM is only marginally affected by
the removal of coarse magnetic particles. The area under the
model function for the pedogenic component (shaded) is
equal to the contribution of this component to the total
ARM and IRM, respectively. The ratio of the two gives
cARM/IRM = 1 103 m/A.
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parent material was found to contain coarse MD magnetite
and the background material is characterized by a coercivity
distribution that is unfortunately similar to that of pedogenic
magnetite. Therefore, component analysis on the bulk samples does not provide reliable data in this case. In order to
solve this problem, large magnetite particles have been
extracted from the finely dispersed powder samples using a
strong permanent magnet. The magnetic extraction has been
carried out until the remaining soil material did not show any
further decrease in magnetic susceptibility. The second pair
of curves in Figure 2 shows the coercivity distributions
measured after magnetic extraction. While ARM remained
relatively unaffected by the treatment, IRM was reduced by
almost a factor 2. Since ARM is strongly selective to SD
particles, we conclude that we were incapable of extracting
the SD fraction. This is probably due to the fact that fine
magnetite particles are strongly bonded to large, nonmagnetic
minerals (probably clays). The extracted material has hysteresis and low-temperature properties consistent with those of
MD magnetite.
[12] Coercivity analysis performed after magnetic extraction is consistent with previous results obtained on loessic
samples, whereby cARM/IRM = 1 103 m3kg1. Firstorder reversal curves (FORC) have been measured on both
samples using a Micromag Alternating Force Magnetometer
(AGM). Because of the weakness of the samples, nine
identical measurements have been stacked. Data have been
analyzed using the Forcobello Matlab code [Winklhofer and
Zimanyi, 2006], whereby a smoothing factor SF = 3 was
chosen to preserve resolution (Figure 3). The FORC diagrams of the two samples show clear differences that can be
interpreted as the overlap of three distinct components: (1) a
positive ridge along Hc = 0, which is related to reversible
magnetization changes [Pike, 2003], not of further interest
here; (2) a FORC distribution characterized by contour lines
that are spreading out toward Hc = 0, which is characteristic
for coarse magnetite in the PSD-MD range [e.g., Roberts,
2000, Figure 7]; and (3) a narrow FORC distribution concentrated along the Hc axis [e.g., Roberts, 2000, Figure 3].
Component 2 is particularly evident in the 70 cm sample,
while component 3 occurs only in the 18 cm sample. The
superposition of the latter two components was analyzed
quantitatively on a Hu profile of the FORC diagram
(Figure 4a), obtained by integrating the FORC function
with respect to Hc, between Hc = 5 mT and Hc = 27 mT
(dashed lines in Figure 3). Integration was necessary to
increase the signal-to-noise ratio, especially for the 70 cm
sample. Component 2 is clearly represented by a broad
distribution of Hu fields, which is identical in the two
samples. We interpret this component as the signature of
lithogenic magnetic particles from the soil parent material.
Superimposed to this contribution, a narrow distribution of
Hu fields can be clearly seen in the 18 cm sample, although
faintly recognizable in the 70 cm sample as well. Since this
latter distribution is an unquestionable signature of SD
particles that occurs with highest concentration in the
magnetically enhanced horizon, we can directly interpret it
as a distribution of interaction fields acting between the
pedogenic magnetite particles. The narrowness of the distribution already suggests that magnetostatic interactions, if
present, are weak. Egli [2006a] calculated the theoretical
FORC distribution of weakly interacting SD particles and
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Figure 3. First-order reversal curves (FORC) diagrams for two samples from the St. Paul soil profile
taken at (a) 70 cm depth and (b) 18 cm depth. The dashed lines represent the range considered for
calculating the Hu profile shown in Figure 4.
concluded that Hu profiles taken for Hc < Bh coincide with
the interaction field distribution, which can be fitted with
appropriate model functions to obtain the effective packing
fraction of the particles. Another source of a small spreading
of Hu profiles is related to the thermal activation of viscous
particles [Egli, 2006a], as observed in goethite samples
[Roberts et al., 2006]. This source cannot be excluded in
our samples, since soils can contain significant amounts of
fine-grained goethite. Neglecting thermal activation effects
will overestimate magnetostatic interactions, meaning that
we can obtain only an upper limit for the interaction field
distribution. We used the method described by Egli [2006a]
and Chen et al. [2007] to fit the FORC profile with two
model curves, one that accounts for the contribution of the
parent material, which will not be interpreted further, and
the second for pedogenic magnetite. FORC data processing
introduces smoothing effects that broaden narrow FORC
profiles. This effect was taken into account by calculating
the FORC of noninteracting, rectangular hysterons and
processing the data with the same parameters used for the
samples. The smoothing effect related to data processing
was then subtracted from the pedogenic contribution to
obtain a ‘‘smoothing-free’’ profile (Figure 4a), from which
we obtain an upper estimate of p = 0.0059 for the effective
packing fraction of pedogenic magnetite. We can now
compare this limit with an independent estimate of magnetostatic interactions obtained by comparing the theoretical
ARM calculated by Egli [2006b] for interacting SD particles
with the ARM ratio measured for the pedogenic component in STP18 (Figure 4). A relatively precise estimate of
cARM/IRM for noninteracting pedogenic magnetite or
maghemite particles can be obtained by integrating
equation (32) in the work of Egli and Lowrie [2002]
over the SD range of the pedogenic grain size distribution
estimated by Liu et al. [2007]. This operation gives an upper
limit of cARM/IRM 1.2 103 m/A for magnetite and
cARM/IRM 1.4 103 m/A for maghemite, using a microcoercivity of 80 mT (corresponding to 2 Bh) as estimated
from the coercivity analysis of soil samples. The experimental value cARM/IRM = 1.0 103 m/A obtained for
the pedogenic coercivity component of the 18 cm sample
(Figure 2) corresponds to 70– 80% of the theoretical value
calculated for noninteracting particles. Considering all the
uncertainties involved in modeling the ARM and in the
coercivity analysis, this difference might simply be
accounted for by calculation errors. On the other hand,
assuming the cARM/IRM estimates to be error free, and
assuming that the difference between the experimental value
and the predicted value for noninteracting particles is
entirely produced by magnetostatic interactions, we can
obtain an upper limit for the packing fraction of the
particles. For this purpose we compare the ratio of the
interacting versus noninteracting ARM predicted by Egli
[2006b] for a range of packing fractions with the value of
0.7– 0.8 obtained above (Figure 4b), and find that this ratio
can be explained by assuming a packing fraction between
0.002 and 0.005. This value is somewhat smaller than the
estimate obtained from the FORC measurement. Considering
the uncertainties contained both in the measurements and in
the theories of ARM, magnetostatic interactions, and
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Figure 4. (a) Hu profile (dots and circles) of the FORC diagrams shown in Figure 3, obtained by
integrating the FORC distribution with respect to Hc in the range between Hc = 5 and Hc = 27 mT. The
profile of the 18 cm sample has been fitted with a combination of two model functions (dashed curves)
representing theoretical interaction field distributions as calculated by Egli [2006b]. The model,
consisting of the sum of the two functions (solid curve), fits the experimental data well. The narrow
model function is corrected for the smoothing effect introduced by data processing (small dashed curve)
and interpreted as the interaction field distribution of pedogenic magnetite or maghemite with a packing
fraction p = 0.0059. (b) Diagram showing the effect of magnetostatic interaction on the ARM of SD
particles as a function of the packing fraction p for two grain sizes (25 nm and 40 nm) representing the
lower bound of the SD range and the size that is characterized by the highest cARM/IRM, respectively.
The vertical dashed line represents the upper limit for the packing fraction of the pedogenic component
estimated in Figure 4a. The two horizontal dashed lines represent the ratio between cARM/IRM measured
on the pedogenic component (Figure 2) and the theoretical cARM/IRM predicted for noninteracting
magnetite or maghemite SD particles. The solid and dashed lines define the range of packing fractions
(shaded area) that is compatible with experimental data from FORC measurements and from arm/IRM.
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Table 1. Magnetic Enhancement Parameters
Parameter
Pedogenic
susceptibility cped
Description
Absolute Enhancement Parametera
cped = cBhorizon cChorizon
[Maher et al., 1994]
Relative Enhancement Parametersb
quantifies relative change of all magnetic
minerals (dominated by changes in
ferrimagnetic minerals)
quantifies relative change of remanenceIRMenh/IRMparent
carrying minerals (dominated by changes
in ferrimagnetic minerals)
similar to IRMenh/IRMparent but heavily
ARMenh/ARMparent
biased toward fine-grained (single-domain)
ferrimagnetic minerals
quantifies changes in magnetic grain size,
ARM/IRMenh/
ARM/IRMparent
especially abundance of fine (SD)
magnetic particles
cenh/cparent
c
Direct Estimates of the Pedogenic Component
cARM/IRM, or ARM/IRM can be directly linked to abundance of
(of enhanced horizon)
pedogenic component via two-component
mixing model [Geiss and Zanner, 2006].
estimates the relative abundance of the
IRMped/IRMtotal
pedogenic component through the
analysis of magnetic coercivity distributions
a
Quantifies the absolute difference between the magnetically enhanced
soil horizons and the unaltered parent material.
b
Give the relative change between the magnetically enhanced soil
horizons and the parent material.
c
Estimate the abundance of pedogenic magnetite from one sample
without comparison to parent material.
FORC, this is a good agreement. We therefore conclude that
pedogenic magnetite is only weakly interacting, whereby
the interaction effects observed, if any, are explained by a
volume concentration <0.3%. This concentration corre-
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sponds to a mean distance between particles of >5 times
their diameter, which excludes the presence of dense particle
aggregates as often observed in synthetic samples of SP/SD
ferromagnetic particles. The interaction effects of such a
small concentration on the ARM are negligible, and in any
case much smaller than the scatter observed in soil susceptibility. The effect of interactions on all other magnetic
parameters, such as susceptibility, is even smaller. Since
the high ARM ratio of other soils analyzed suggests the
same conclusions, we can confidently exclude that magnetostatic interactions represent a disturbing factor when using
magnetic parameters to estimate the concentration of pedogenic magnetite.
3. Results and Discussion
3.1. Absolute Enhancement Parameters: Pedogenic
Susceptibility
[13] Figure 5 shows the correlation between pedogenic
susceptibility (cped = cB horizon cparent material) and mean
annual precipitation for modern loessic soils from the
Chinese loess plateau [Maher et al., 1994; Porter et al.,
2001], Alaska [Sharpe, 1996], the Czech Republic [Oches
and Banerjee, 1996], various sites from the Northern
Hemisphere [Maher and Thompson, 1995], and the Midwestern United States (this study and that of Geiss and
Zanner [2007]). The best fit calibration between cped and
mean annual precipitation, established by Maher et al.
[1994] from an initial set of less than a dozen modern soils
from the Chinese loess plateau, is also shown. cped correlates well with mean annual precipitation for Maher et al.’s
[1994] initial data and reasonably well with other magnetic
data from the Chinese loess plateau [Porter et al., 2001] and
the Russian steppe [Alekseev et al., 2003], though the
resulting slope of the best fit line (not shown) is a bit
shallower.
Figure 5. Semilogarithmic plot of pedogenic susceptibility cped = cBhorizon cparent with mean
annual precipitation for modern loessic soils. Solid line is the best fit line given by Maher et al. [1994] to
describe the relationship between cped and mean annual precipitation for modern soils from the Chinese
loess plateau.
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Figure 6. (a– d) Scatterplots of relative enhancement parameters and mean annual precipitation.
[14] The poor fit with other Northern Hemisphere loess
data [Maher and Thompson, 1995] may be due to regional
differences in the degree of magnetic enhancement, though
the slope of a best fit line through these considerably
scattered data would be rather shallow (decreasing its value
as a paleoprecipitation proxy). Our data from the Midwestern
United States fall below all other previously published sites,
and any correlation between cped and mean annual precipitation is rather poor (r2 = 0.28, n = 72). Our compilation of
pedogenic susceptibility data shows that cped may be useful
for regional climate reconstructions as long as regional
transfer functions have been established. The large scatter
in the data may also be caused by climatic influences other
than precipitation as suggested by Han et al. [1996].
3.2. Relative Enhancement Parameters
[15] Pedogenic susceptibility, defined as the difference in
susceptibility between the maximum enhanced horizon and
the background, is an example of absolute enhancement
parameter. On the other hand, a relative enhancement
parameter might be defined as the ratio between a given
magnetic parameter measured for the maximally enhanced
horizon and at a depth where no enhancement can be
recognized. Accordingly, a relative susceptibility enhancement would be defined as cenhanced/cparent. Absolute enhancement parameters are most effective in describing a
formation process for pedogenic minerals that is completely
independent from the magnetic minerals present in the parent
material. A relative enhancement parameter, on the other
hand, works under the assumption that the concentration of
pedogenic magnetite is proportional with the magnetic minerals of the parent materials.
[16] The correlations between various relative magnetic
enhancement parameters and modern mean annual precipitation for approximately 80 modern loessic soil profiles
from the Midwestern United States are shown in Figure 6.
Magnetic susceptibility (c, Figure 6a) and isothermal remanent magnetization (IRM, Figure 6b) represent the total
magnetic signal produced by a wide range of magnetic
particles and the correlation between these magnetic parameters and precipitation is rather poor (r2 = 0.43 for c and r2 =
0.34 for IRM). Anhysteretic remanent magnetization
(ARM, Figure 6c) is heavily biased toward fine singledomain (SD) grains. Since the in situ production of such
small magnetic particles is the cause of magnetic enhancement in these soil profiles and the occurrence of SD
particles in the parent loess is negligible, an ARM-based
magnetic enhancement parameter yields slightly better
results (r2 = 0.53). Results improve further if the concentration independent ratio ARM/IRM is used to calculate
magnetic enhancement (r2 = 0.59, Figure 6d).
[17] All the relative enhancement parameters shown in
Figure 6 outperform pedogenic susceptibility cped for our
sites in the Midwestern United States (Figure 5). The poor
performance of cped for Midwestern soils may be due to (1)
variations in the underlying parent material and (2) additional
dust input during the Holocene. Peoria loess, which is the
parent material for our soil profiles, is relatively homogenous, but various studies [e.g., Mason et al., 1994; Muhs and
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Figure 7. Average ARM ratio (cARM/IRM) of the magnetically enhanced soil horizon versus mean
annual precipitation. Since cARM/IRM depends directly on the relative abundance of pedogenic
magnetite, it can be used to estimate the degree of magnetic enhancement and, if measured for buried
soils, to estimate past climatic conditions.
Bettis, 2000; Muhs et al., 2008; Winspear and Pye, 1995]
have identified several dust sources and transport paths.
Geiss and Zanner [2007] have found significant variations
in the magnetic properties of unaltered Peoria loess. These
variations are at least partially due to the variability of ironbearing magnetic minerals in the underlying parent material, which influences the degree of magnetic enhancement
[Dearing et al., 1996]. Furthermore, Jacobs and Mason
[2005, 2007] have shown that additions of dust during the
Holocene have significantly modified many soil profiles on
the Great Plains. Given the variable sources of Peoria loess,
these later additions may have different magnetic properties
than Pleistocene Peoria loess. Therefore, magnetic proxies
that rely on a comparison between topsoil and parent
material (i.e., all the ones shown in Figures 5 and 6) may
be seriously affected by such additions of loess because the
underlying pedogenic model of downward soil development
is now invalidated. Such later dust additions and the
resulting upward growth of soils in stable upland positions
(the preferred landscape position for our and similar studies)
likely add to the scatter observed in Figures 5 and 6. We
therefore interpret the partial success of relative enhancement parameters as due to their partial ability to account for
site-to-site variations of the parent material. However, depth
variations due for example to weathering, and later dust
input, are not accounted by relative enhancement parameters either, and this represent the limit that prevents a further
improvement of the correlation with climate.
[18] Upward soil growth and the eventual modification or
loss of magnetic minerals in the lower parts of the soil
profile represent strong arguments in favor of a direct
estimate of pedogenic magnetite concentration that will be
discussed in the remainder of this paper.
3.3. Direct Estimates of Pedogenic Fraction From One
Sample
[19] Geiss and Zanner [2006] as well as Evans and Heller
[1994] have shown that the pedogenic component of loessic
soils from the Midwestern United States has remarkably
homogenous magnetic properties. Knowledge of these
magnetic properties allows us to directly estimate the
amount of pedogenic magnetite present in a soil sample
without the need for a comparison with the unaltered parent
material.
3.3.1. ARM/IRM
[20] Geiss and Zanner [2006] presented a simple linear
mixing model to estimate the abundance of pedogenic
magnetite (fped) from ARM/IRM ratios. Since ARM/IRM
(or cARM/IRM) depends directly on fped it is not necessary
to calculate fped explicitly, and the average cARM/IRM of the
magnetically enhanced soil horizons can be used directly as
a paleoprecipitation proxy. Figure 7 shows a correlation
between average cARM/IRM for the magnetically enhanced
soil horizons with mean annual precipitation for loessic
soils in the Midwestern United States. The correlation with
mean annual precipitation is rather good (r2 = 0.70, n = 76).
Furthermore, the scatter affecting all relative enhancement
parameters at the wet end of our data is now greatly
reduced.
[21] Aside from the good correlation with mean annual
precipitation the method is an attractive parameter because
it requires relatively few measurements. At least in theory it
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Figure 8. Logarithm of the median coercivity (log Bh) and distribution width (Dp) for the two magnetic
components identified in magnetically enhanced soil horizons and parent material for soil profiles from
the Midwestern United States, Alaska, and Connecticut.
is not necessary to measure an entire soil profile, but one
can focus solely of the modern or buried soils, which one
should be able to identify through a careful soil profile
description during field sampling. In addition, the measurement of only two remanence parameters can be carried out
extremely rapidly, even when using spinner magnetometers
with characteristic measurement times of a minute or so.
Using cARM/IRM as a paleoprecipitation proxy will allow
even small laboratories to analyze a large number of sites to
obtain regional climate estimates. On the downside, the
reduction of an entire soil profile into one ratio results in a
large loss of information, and there is little hope to extract
any secondary climatic information from the data. Using
IRM acquired in a magnetic field of 100 mT rather than
saturation IRM (SIRM) to normalize for changes in the
concentration of magnetic minerals ensures that ARM and
IRM are affected by the same coercivity components and
minimizes the effects of mineralogical changes on the
cARM/IRM proxy. Unfortunately, most published studies
present ARM/SIRM ratios which makes comparisons between sites difficult unless IRM acquisition curves are also
published. A comparison of our enhancement data with data
from the Russian steppe [Alekseev et al., 2003], Alaska
[Sharpe, 1996], and the Czech Republic [Oches and
Banerjee, 1996] show that loessic soils from the Midwestern United States appear to be less magnetically enhanced
than loessic soils elsewhere, stressing the need for regional
transfer functions between magnetic proxies and climate.
3.3.2. Analysis of Magnetic Coercivity Distributions
[22] The initial analysis of magnetization curves of Midwestern soils showed that the pedogenic magnetic component is characterized by a well-constrained coercivity
distribution [Geiss and Zanner, 2006]. Figure 8 is an
extension of this original data set and shows that this holds
true for a variety of modern loessic soils from Alaska and
Illinois, soils that formed in glacial outwash (J. A. Tauer
Prairie State Natural Area, MN, Dickman sandy loam), and
even some hydric soils that formed in extremely stony till in
Connecticut (Trinity College Field Station, Ashford, CT,
Ridgebury series). The pedogenic component of all soils is
characterized by a very narrow range of distribution parameters Bh and Dp. Analyzing the coercivity distributions of
paleosols using CLGs or more complicated generalized
distribution functions [Egli, 2004a] allows us to quantitatively estimate the amount of pedogenic magnetite directly
from one sample, without the need for a ‘‘background’’
estimate. It is possible to use unconstrained CLG fits, but
often better results are obtained by fitting the data to a
predetermined pedogenic component and a freely adjustable
background component [Geiss and Zanner, 2006]. Figure 9
shows the results of such an analysis for 15 soil profiles
from the Midwestern United States using a predetermined
pedogenic component (Bh = 1.3, Dp = 0.3). The degree of
correlation with mean annual precipitation is similar to
ARM/IRM (r2 = 0.74, n = 15).
[23] Estimates of fped using either ARM/IRM ratios or
coercivity distributions yield similar results. The much
greater time commitment required to measure a magnetic
coercivity distribution at high resolution may be rewarded
by additional climatic information, such as temperature, that
can be gained from the data. The scatter that is observed in
the magnetic properties of the pedogenic component may be
just that, or it may prove to yield additional climatic
information. On the other hand, loessic soils from Alaska
display consistently lower Bh values than samples from the
Midwestern United States. In the Midwestern sites, the
scatter in the data is most pronounced toward the humid
end of our sample area where sites follow the roughly northsouth trending Iowa loess bluffs along the Missouri river.
The variations in present-day mean annual temperatures are
more pronounced along this part of the transect than for
other sample sites. This suggests that other climate variables
may well influence soil magnetic properties in a systematic
way, and the analysis of magnetic coercivity distributions
may provide a means to extract these variables from soils.
Unfortunately, at present, our data set does not span a
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Figure 9. Relative IRM contributions of the pedogenic magnetic component versus mean annual
precipitation.
significant enough combined precipitation and temperature
range to test this hypothesis.
[24] The direct estimates of pedogenic magnetite as outlined above avoid some of the shortfalls of previous
methods. Since they do not require the identification and
analysis of magnetically unaltered parent material, they can
be successful when analyzing thin loess-paleosol sequences
or soils that aggraded upward through additions of windblown dust that were not significant enough to interrupt soil
development. However, the method may run into difficulties
if later additions of dust already contain a significant
amount of pedogenic magnetite, which might lead to an
overestimate of the magnetic component formed in situ
through pedogenic processes.
enhanced modern soil horizon. This component is absent
between 50 –80 cm depth (Bt2 horizon), the assumed top of
the buried soil. Despite possible pedogenic overprints the
similarities of the pedogenic components in both the modern
and the buried soil may allow us to interpret the magnetic
record. Figure 10c shows our analyses of magnetic coercivity
spectra where the pedogenic component was constrained to
log Bh = 1.3 and Dp = 0.3. The resulting abundance estimates
for the pedogenic component suggest that the buried soil
formed under slightly wetter climatic conditions. Further
analyses of similar, but better preserved, paleosols are currently under way and will show whether it is possible to
extract climatic information from such poorly separated
paleosol horizons.
3.4. Application to a Welded Soil Profile
[25] Figure 10 shows some of our magnetic analyses for
North Lutheran Cemetery in central Nebraska (40.421°N,
97.426°W). The profile contains the modern soil, a typical
prairie soil (Crete silty clay loam), and a buried soil between
55 cm and 150 cm depth, identifiable through changes in
soil color and structure and otherwise incorporated into the
modern soil. The lower part of this buried soil (90 – 120 cm,
interpreted as a B horizon with former E horizon characteristics) is magnetically enhanced leading to increased values
in all concentration-dependent magnetic parameters (c
shown in Figure 10a). ARM ratios (Figure 10b) show a
general increase in fine-grained SD material throughout the
upper 150 cm of the soil profile indicating that magnetic
enhancement processes were active throughout the deposition of approximately 50 cm of Holocene loess. An unconstrained analysis of magnetic coercivity distributions
(Figure 10d) shows that the magnetically enhanced buried
soil horizon is enriched in a pedogenic component (solid
black curves) similar to the ones found in the magnetically
3.5. Inherited Pedogenic Magnetic Components
[26] Holocene (Bignell) loess in Nebraska and elsewhere
in the Midwestern United States is often darker in color,
possibly because it has been derived from a mixture of
floodplain deposits and older reworked loess and soil
[Mason and Kuzila, 2000]. We analyzed the magnetic
coercivity distributions of two samples of Bignell and
Peoria loess to test for the presence of a pedogenic component in Bignell loess. The samples were supplied to us by
Mark Kuzila and are from the Mirdan Canal section in
central Nebraska [Mason and Kuzila, 2000]. The results are
shown in Figure 11. Both loess units contain a magnetic
component that could be of pedogenic origin, but their
abundance varies little between the two samples. This
component can be an intrinsic part of the parent material
(as is the case for the sample analyzed in Figure 2) or is
evidence for continued pedogenesis during periods of loess
deposition. In either case, the magnetic properties of both
loess units are sufficiently similar to allow for meaningful
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Figure 10. Magnetic analyses of a soil profile obtained from North Lutheran Cemetery, Nebraska
(40.421°N, 97.426°W). (a) Variations in magnetic susceptibility (c) reflect changes in the abundance of
all iron-bearing minerals but are heavily biased by changes in ferrimagnetic maghemite or magnetite.
(b) The ratio of cARM/IRM serves as a proxy for the relative abundance of fine-grained (SD) magnetic
particles. (c) Estimate of the relative abundance of pedogenic magnetite based on the analysis of
coercivity distributions. (d) Unconstrained analyses of magnetic coercivity distributions for selected
samples from North Lutheran Cemetery showing the presence of a pedogenic magnetic component (solid
curves) in the magnetically enhanced horizons as well as a magnetic background component (dashed
curves). No pedogenic component was detected in samples below 150 cm depth, and both coercivity
components were classified as background components. Abbreviations used in soil profile description:
str, strong; mod, moderate; gran, granular; abk, angular blocky; sbk, subangular blocky; prism, prismatic;
f, fine; med, medium; c, coarse; sil, silt loam; sicl, silty clay loam; h, heavy.
direct estimates of pedogenically formed magnetite in soil
profiles that received later additions of Bignell loess.
4. Conclusions
[27] Both ARM ratios (cARM/IRM) and magnetic coercivity distributions reflect climatic conditions during soil
formation and can be used as a paleoclimate proxy. For
modern soils from the Midwestern United States the correlation between these two magnetic proxies and paleoclimate
is better than for any other previously studied magnetic
proxy (cped in Figure 5 and various magnetic ratios in
Figure 6) and independent of our knowledge of the original,
unaltered parent material. The latter fact allows it to be
applicable to the analysis of thin loess-paleosol sequences,
where no unaltered parent material may be available.
[28] Our analyses of the various magnetic enhancement
parameters show that the correlation between magnetic
proxies and climate is only of regional value. This may
not be a problem as long as a regional transfer function can
be established from modern soils. However, it is possible
that these transfer functions change not only in space but
also in time, making their application to older soils difficult
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Figure 11. Coercivity distributions and coercivity component analyses for a sample of (a) Bignell loess
and (b) Peoria loess. Dashed curves show individual coercivity components, solid curve shows the sum
of the two individual coercivity components, and dots show measured coercivity data.
if not impossible. More research regarding the processes
that influence magnetic enhancement is clearly necessary.
[29] Our study limited itself to modern soils that formed
within the last few thousand years. Some authors [e.g.,
Maher and Thompson, 1999, and references therein] argue
that magnetic enhancement proceeds relatively quickly and
reaches saturation within a few hundred or thousand years
in loessic soils. This view is not shared by several other
authors [e.g., Grimley et al., 2003; Singer et al., 1992; Vidic
and Lobnik, 1997; Vidic et al., 2004] whose research
suggests that the magnetic signal builds up more slowly
over time. In light of such uncertainties, it might be best,
when using a transfer function, to limit oneself to paleosols
that are thought to have formed for similar lengths of time
as the modern soils on which the function is based.
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[30] Despite these limitations, magnetic analyses of buried soils can provide quantitative information on past
precipitation gradients, though more work is clearly necessary to constrain the pathways of magnetic enhancement
and their link to biologically driven processes in the upper
soil horizons.
[31] Acknowledgments. We are grateful to all landowners, funeral
homes, and land managers for access to the numerous sites across
Nebraska, Iowa, Missouri, Illinois, and Minnesota. Jim Bisbee, Dan
Scollan, Alex Masi, and Saroj Aryal helped with field sampling and
magnetic analyses at Trinity College. Mark Kuzila (University of Nebraska
at Lincoln) generously supported this project throughout the years by
supplying a probe truck and by supplying samples from the Mirdan Canal
section. Most of C. E. G.’s work was supported through faculty and student
research grants from Trinity College. R. E. is grateful to Amy Chen for
measuring FORC diagrams of soil samples. Some of the magnetic measurements were conducted at the Institute for Rock Magnetism (IRM). The IRM
is funded by the W.M. Keck Foundation, the National Science Foundation’s
Earth Science Division’s Instrumentation and Facilities Program, and the
University of Minnesota.
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R. Egli, Department of Earth and Environmental Sciences, LudwigMaximilians-Universität, Geophysics Theresienstrasse 41, Munich D-80333,
Germany.
C. E. Geiss, Department of Physics, Trinity College, 300 Summit Street,
McCook 105, Hartford, CT 06106, USA. ([email protected])
C. W. Zanner, Department of Soil, Water, and Climate, University of
Minnesota, St. Paul, MN 55108, USA.
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