sem image analysis in the study of a soil

SEM image analysis in the study of a soilchronosequence on fluvial terraces of the middleGuadalquivir (southern Spain)

J. CALEROa , R. DELGADO

b , G. DELGADOb & J. M. MARTIN-GARCIA

a

aDepartamento de Geologıa, Facultad de Ciencias Experimentales, Universidad de Jaen, Campus Universitario Las Lagunillas, 23071

Jaen, Spain, and bDepartamento de Edafologıa y Quımica Agrıcola, Facultad de Farmacia, Universidad de Granada, Campus

Universitario Cartuja, 18071 Granada, Spain

Summary

A Quaternary fluvial chronosequence (Guadalquivir River, southern Spain), consisting of five soil profiles

with estimated ages of 300 years (Haplic Fluvisol), 7000 years (Haplic Calcisol), 70 000 years (Cutanic

Luvisol), 300 000 years (Lixic Calcisol) and 600 000 years (Cutanic Luvisol), was studied. Increasing soil

age was associated with increases in: reddening, development of structure, clay content, dithionite-extract-

able iron (Fed) and aluminium (Ald) and strengthening of X-ray diffraction (XRD) peaks for phyllosili-

cates and iron oxides; there were also decreases in pH and percentage of carbonates in the fine earth

and lower XRD peaks for calcite and dolomite. These changes indicate that the principal pedogenic

processes were weathering, clay illuviation, rubefaction and the weathering and leaching of carbonates.

We have further characterized the pedogenetic chronosequence by quantification of ultramicrofabrics

of ped interiors using image analysis (IA) techniques on images obtained with scanning electron

microscopy (SEM). We have estimated morphometric ultramicrofabric parameters for particle clusters,

skeleton grains and pore space. These are closely related to analytical, mineralogical and macro-

morphological properties. In the principal component analysis, the first two principal components of

the combined morphological, analytical and mineralogical data accounted for 78% of the total vari-

ance. The first component (48%) is loaded by variables associated with clay illuviation, relative accu-

mulation of iron and aluminium sesquioxides and the weathering and leaching of carbonates. The

components are related to ultramicrofabric development trends. We tested several chronofunctions

derived from analytical and morphometric attributes. The logarithmic model fitted best, and we inter-

pret this as indicating pedogenetic processes that are converging towards a steady state.

Introduction

Soil chronosequences are defined as genetically related sets of

soils of different ages that have evolvedunder similar conditions,

such as vegetation, parent rock, topography and climate

(Harden, 1982). The importance of chronosequences in the

study of soil genesis has long been recognized (e.g. Jenny,

1941; Vreeken, 1975; Yaalon, 1975), and they are also of interest

to geologists and geographers, as they help in the subdivision

and correlation of unconsolidated sediments, and in paleocli-

matic and neotectonic studies (Birkeland, 1999). The timescales

involved in soil chronosequences can cover hundreds, thousands

or more than amillion years. Huggett (1998) classified soil chro-

nosequences asHistoric (fewmillennia),Holocenic (up to 10 000

years) or Quaternary (up to 1 million years).

Soil development over time implies a progressive change in

morphological, analytical and mineralogical properties

(Churchman, 1980; Harden, 1982; Birkeland, 1984; Igwe et al.,

2005). Soil fabric is closely related to field macro-

morphological properties, but more detailed conformational,

compositional and genetic aspects can provide additional

information about the types and extent of evolutionary pro-

cesses in soils. There is no universally agreed definition of soil

fabric. It has been defined either as a geometrical aspect of soil

structure (Brewer, 1964) or as a wider concept that incorpo-

rates all aspects of the spatial relationships of soil components

and their functional and genetical aspects (Bullock et al.,

1985). In our study we use ‘ultramicrofabric’ to mean the spa-

tial organization of the soil at the scanning electron microscopyCorrespondence: R. Delgado. E-mail: [email protected]

Received 10 December 2007; revised version accepted 27 January 2009

European Journal of Soil Science, June 2009, 60, 465–480 doi: 10.1111/j.1365-2389.2009.01131.x

# 2009 The Authors

Journal compilation # 2009 British Society of Soil Science 465

European Journal of Soil Science

(SEM) scale. It is expressed by the morphological character-

istics of the solid components and voids and their spatial juxta-

positions. We also consider compositional and genetic aspects,

as indicated by the types and condition of the components.

Pedologists have used SEM in studies of clay illuviation

(Walker et al., 1978), ultramicrofabric development in Entisols

(Martın-Garcıa et al., 2004), structural development in historic

garden soils (Delgado et al., 2007), and the genesis of fragipans

(Weisenborn & Schaetzl, 2005), iron-manganese concretions

(Zhang & Karathanasis, 1997) and calcic horizons (Baghernejad

& Dalrymple, 1993). Sedimentologists and geotechnicians

have used SEM to classify morphological hierarchies of fabric,

porosity and anisotropy (Barden & Sides, 1971; Yong &

Warketin, 1975; Warketin, 1980; Smart & Tovey, 1982).

Image analysis (IA) techniques have been most intensively

developed inhuman face recognition (FERET– face recognition

technology), but are useful in a wide range of fields, including

soil structure and fabric studies (Bruneau et al., 2004; Maragos

et al., 2004). Conventional soil IA procedures convert

monochromatic digital images (256 greys) from an electron

microscope into binary images by techniques of ‘thresholding’

or ‘segmentation’ (Chan et al., 1998; Gonzalez & Woods,

2002). Once the binary images have been obtained, they are

enhanced by means of morphological operators (i.e. ‘erosions’,

‘dilations’, etc.) to eliminate the noise added by features

smaller than the scale of interest (Horgan, 1998). Image seg-

mentation and enhancement permit the integration and analy-

sis of large data sets of automatically measured sizes, distances

and angles between definable and recognizable fabric features,

such as particle-cluster size and particle-size distributions

(Lamotte et al., 1997; Pieri et al., 2006), porosity (Balbino

et al., 2002), pore and particle connectivity (Ringrose-Vose,

1991) and fabric orientation and anisotropy (Shi et al., 1998).

The present study appears to be the first SEM–fabric quanti-

fication by IA of a soil chronosequence. The chronosequence

studied is located on terraces of the Guadalquivir River system.

Although the river flows into the Atlantic Ocean, its catchment

has aMediterranean climate.Mediterranean soils have been im-

portant for chronosequence studies (Harden, 1982; Harden &

Taylor, 1983). In the case of theGuadalquivirRiver,Quaternary

soil chronosequences ofmore than 1 million years durationhave

been studied in the middle (Carral et al., 1998) and lower rea-

ches (Rodrıguez-Ramırez et al., 1997). A study of iron oxides

and rubefaction in a Quaternary chronosequence in the middle

reaches found the percentages of free iron forms to be 7% or

smaller and to increase with age (Torrent et al., 1980). Gener-

ally, the mineralogical composition reflects the moderate

weathering that is typical for the xeric environment (Torrent,

1995).

None of the previous Guadalquivir chronosequence studies

included soil SEM-fabric or statistically derived chronofunc-

tions. In our paper, we quantify and integrate IA data on soil

SEM-fabric with the main macromorphological, chemical,

physical and mineralogical attributes. Statistical analysis of

the relationships enabled us to test alternative pedogenetic

chronofunctions.

Materials and methods

The site

The study area (Figure 1) is located in the middle reaches of the

Guadalquivir River, near Andujar, in southern Spain. TheGua-

dalquivir is one of the largest and oldest Iberian rivers. It drains

a catchment of 57 000 km2, and has followed, more or less, its

present course since the Plioquaternary (Fontbote, 1982). Tec-

tonically, the study area is situated on the border between the

Tertiary Guadalquivir marine depression and the Paleozoic

Hercynian Range (Sierra Morena Mountains). The source

lithology of the terrace alluvia is diverse (Fontbote, 1982;

Garcıa-Duenas et al., 1986). In the north there are Carbonifer-

ous metamorphic (shales) and igneous (granites) rocks and

Triassic sedimentary rocks (conglomerates and sandstones).

Mesozoic and Tertiary limestones, marly limestones, marls,

dolomites and gypsic marls predominate to the south and

the east.

In the study area, there are four terraces and a floodplain

along the Guadalquivir River (Table 1). The terraces are com-

posed of gravelly sediments with quartzite, limestone and shale

clasts, whichbecomemore cementedwith increasing surface age.

In some places the gravelly sediments alternate with stone-free

sandy silty layers (Santos-Garcıa et al., 1991). The Preholocene

terraces (1, 2 and 3) have undulating relief and mean gradients

of 3%, with some signs of tectonic uplift, such as fault and

Figure 1 Location of study site in the Guadalquivir terrace system,

showing sampling of profiles (P-1 to P-5) and parent material (PM).

466 J. Calero et al.

# 2009 The Authors

Journal compilation # 2009 British Society of Soil Science, European Journal of Soil Science, 60, 465–480

fractures (Santos-Garcıa et al., 1991). The Holocene surfaces

(terrace 4 and floodplain) are level and flat.

The current climate is Mediterranean, with a mean annual

temperature of 18°C, a mean annual precipitation of 650 mm

and a summer drought. The natural vegetation is profoundly

disturbed by agricultural land use (probably dating back to

the Neolithic), and the land is now predominantly under olives.

Soil sampling

Following a soil survey (Delgado et al., 1995; Calero, 2005),

one modal soil profile (P-1 to P-4) on each terrace, on the

floodplain (P-5) and parent materials (PM) from fresh point

bar deposits in the river were selected and sampled (Figure 1).

Profiles P-1 and P-3 on the Preholocene terraces are Cutanic

Luvisols but P-2 is a Lixic Calcisol. The Holocene terrace pro-

file, P-4, is a Haplic Calcisol, while the floodplain soil (P-5) is a

Haplic Fluvisol (Table 1).

Soils were sampled by all the horizons exposed in the profile,

and taken from centres in the case of undisturbed samples and

throughout the horizon for the disturbed samples. All of these

samples were air-dried in the laboratory.

Soil properties

The macromorphological features of the soil profile were

described according to the FAO (1977) and Soil Survey Staff

(1993). Soil colour was measured according to Munsell Color

(1990). The profile development index (PDI) to 1 m thickness

(Harden, 1982) was estimated for each profile.

Granulometric analysis was carried out by sieving and sedi-

mentation (Robinson pipette) for clay (< 0.002 mm), silt

(0.002–0.05 mm), fine sand (0.05–0.25 mm), coarse sand

(0.25–2 mm) and gravel (> 2 mm). Fine earth (< 2 mm) was

analysed for organic carbon (OC) by dichromate oxidation,

CaCO3 equivalent by Bernard’s calcimeter, cation exchange

capacity (CEC) and base saturation by the ammonium acetate

(pH 7)–sodium chloride method. pH was measured in a 1:1

suspension of fine earth:water, soil water release at �33 kPa

and �1500 kPa was measured on a Richard’s membrane, and

crystalline and amorphous forms of free iron and aluminium

oxides were extracted by the sodium citrate-dithionite method

(Fed and Ald) and measured by atomic absorption

spectrometry.

Soil mineralogy

X-ray diffraction (XRD) traces for disoriented crystalline powder

samples of the fine earth, and separate coarse sand, fine sand and

silt fractions, were obtained with a Siemens D5000 X-ray diffrac-

tometer (Siemens, Munich, Germany), using Cu Ka radiation,

35 kV, 15 mA, a step size of 0.05°2h, and a holder filled from

the side (Niskanen, 1964). Mineral percentages were estimated

by intensity factor methods according to the factors of Schultz

(1964), Barahona (1974) and Delgado et al. (1982).

Soil fabric

Using the morphological indices of Harden (1982), we selected the

undisturbed sample from the horizon in each profile that showed

the greatest pedogenic development (Calero, 2005). Fresh planar

sections of ped interiors were mounted on the sample holders with

colloidal silver and coated with gold that was deposited in two

orientations (20–30°), as recommended by Bohor & Huges

(1971). Soil fabric was studied with SEM, employing a Hitachi

S-510 Scanning Microscope (acceleration voltage 25 kV; Hitachi

Ltd. Scientific Instruments, Tokyo, Japan) equippedwith aRontec

energy-dispersive X-ray detector (EDX; Rontec GmbH, Berlin,

Germany).

Conventional SEM images at low magnifications of approx-

imately 300-500 were obtained, as recommended by Shi et al.

(1998) and Liu et al. (2005), to observe fabric features at the

particle-cluster level. Particle clusters (Yong & Warketin,

1975) were the most frequent and recognizable fabric units at

this magnification but there were also skeleton and porosity

features. Coarse silt and sand grains (> 20 mm) were

Table 1 Characteristics of the terraces and profiles sampled

Terrace no

Elevation above

river beda/m Ageb/years (relative age)

Soil

Profile Classificationc PDId

1 50 600 000 (Ph) P1 Cutanic Luvisol (Hypereutric, Profondic, Epiclayic, Chromic) 44.8

2 30 300 000 (Ph) P2 Lixic Calcisol (Endosiltic, Epiclayic) 44.3

3 15 70 000 (Ph) P3 Cutanic Luvisol (Profondic) 39.6

4 6 7000 (H) P4 Haplic Calcisol (Ruptic) 26.8

Flood plain — 300 (H) P5 Haplic Fluvisol (Calcaric, Hypereutric) 21.2

aThe altitude above sea level ranges from 200 to 255 m.bSantos-Garcıa (1988), Santos-Garcıa et al. (1991), Rodrıguez-Ramırez et al. (1997), Carral et al. (1998). Ph ¼ Preholocene; H ¼ Holocene.cFAO (2006).dPDI ¼ profile development index (Harden, 1982) for thickness of 1 m.

SEM image analysis in soil chronosequence studies 467

# 2009 The Authors


considered as skeleton (Brewer, 1964). The measured porosity,

at the magnifications employed, corresponded to Brewer’s

(1964) 5–30 mm microporosity.

Image analysis

The IA procedure was carried out on digital SEM images

obtained with Scan Vision Software (trade mark; Rontec

GmbH, Berlin, Germany). To isolate particle clusters, skeleton

and porosity from the background, standard segmentation pro-

cesses were used (Gonzalez & Woods, 2002), with the aid of

heuristic thresholding (Montes-H, 2005) in cases with insuffi-

cient density contrast of skeleton grains or particle clusters.

From the resulting binary images, several morphometric and

morphoscopic characteristics (Table 2) were quantified using

the Soft Imaging System GmbH (1999; Munster, Germany).

Statistical analysis

All of the analytical and mineralogical data, together with the

field macromorphological variables (i.e structure (size, grade

and type), hue (moist and dry), value (moist and dry), chroma

(moist and dry), consistency (moist and dry), stickiness, plastic-

ity, cutans (thickness, frequency,morphology) and texture class)

for all samples in each profile in the chronosequence were exam-

ined by principal component analysis (PCA).

Before PCA, the morphological data were transformed into

numerical or continuous scales by a nonlinear optimal scaling

procedure (Calero et al., 2008). The usefulness of the variables

was initially examined by means of Bartlett’s sphericity test (this

test is highly significant if the correlation matrix is not orthogo-

nal; in this case the correlation matrix is suitable for its factor-

ization) and the Kaiser-Meyer-Olkin (KMO) measure of sample

adequacy (indicating the proportion of the total correlation not

due to the partial correlation and whose values must be greater

than 0.5 and preferably close to 0.8) (Meulman & Heiser, 1999).

Only the components with eigenvalues > 1 were retained and

rotated by Varimax.

The five horizons studied by SEM-IA were grouped by hier-

archical clustering (group average method, square Euclidean

distance).

Chronofunction testing

Statistical relationships between soil age and profile develop-

ment index, principal components and selected variables (ana-

lytical and SEM-IA) were tested for linear, logarithmic and

quadratic chronofunctions.

Results and discussion

Morphological and analytical soil properties

The effects of terrace age are clearly observable in the properties

of Preholocene soils (P-1, P-2 and P-3) (Table 3). They have Bt

horizons that are relatively deep (their lower boundary is close to

Table 2 SEM features measured with Image Analysisa

SEM feature Metric name Definition Meaning

Particle

clusters

Area/mm2 Measurement of surface-particle clusters

Feret

maximum

diameter/mm

Distance between theoretical

parallel lines that are drawn

tangentially at opposing

particle-clusters borders and

perpendicular to the ocular plane

Size of the particle clusters

Shape factor Shape factor ¼ 4pa/p2;where a ¼ area, p ¼ perimeter

A measure of the ‘roundness’ of the

particle clusters, with a maximum shape

factor of 1 for a spherical particle and

decreasing values indicating greater elongation

Convexity The fraction of the particle-clusters

area and the area of its convex hull

Measure of the ‘irregularity’ or ‘sinuosity’

of the particle’s edges, being more regular and

smoother when the value approaches 1

Skeletal

grains

Feret

maximum

diameter/mm

Distance between theoretical parallel lines

that are drawn tangentially at opposing particle

borders and perpendicular to the ocular plane

Size of the skeletal grain

Total area occupied/% Percentage of the observed area

occupied by the skeletal grains

Pores Feret

maximum

diameter/mm

Distance between theoretical parallel lines that

are drawn tangentially to the pore silhouette and

perpendicular to the ocular plane

Size of the pores

Total area occupied/% Percentage of the observed area occupied by the pores

aSoft Imaging System GmbH (1999).


# 2009 The Authors


Table

3Selectedproperties

forsoilhorizonsandparentmaterial

Profile

Horizon

Depth

Texture

Cutans

Structure

Consistency

Dry

colour

Moist

colour

Gravela

Coarse

sand

Fine

sand

Clay

WR

33kPa

WR

1500kPa

OC

pH

CEC

Base

saturation

Fe d

Al d

CaCO

3

eq

/cm

%%

%%

%%

%cm

ol þkg�1

%%

%%

P-1

Ap

0–14

clvc2pl

dvh,mfr,ws,wp

7.5YR

5/6

7.5YR

4/6

10

6.3

36.1

33.4

18.32

9.35

0.51

7.9

11.1

67

2.71

0.50

0.38

Bt

14–54

cn4pf

c3abk

dvh,mfr,ws,wp

5YR

4/6

5YR

4/4

37

9.9

24.0

42.6

21.78

13.05

0.34

6.8

10.4

97

3.52

0.66

0.00

Btg1

54–90

scl

n2br

m2abk

dvh,mfr,ws,wp

5YR

4/6

5YR

4/4

29

13.3

34.2

31.2

16.03

9.41

0.25

7.6

7.9

100

2.75

0.55

1.14

Btg2

90–125

scl

n3br

m2/1abk

dvh,mfr,ws,wp

5YR

5/6

5YR

4/6

41

20.2

32.8

27.4

13.03

8.40

0.15

7.2

6.9

100

2.57

0.74

0.00

2BCtg

125–165

ln1br

0dvh/deh,mfr,ws,wp

10YR

7/4

10YR

5/8

46.1

35.2

27.0

20.93

9.27

0.13

7.5

9.1

100

2.56

0.68

2.29

3BCt

165–175

scl

n2br

f1abk

dsh/dh,mfr,wss,wps

10YR

6/6

7.5YR

4/6

30

17.8

33.0

23.6

13.60

7.13

0.12

7.3

6.8

100

2.56

0.72

0.00

4C

>175

scl

0dsh/dh,mvfr,wss,wps

10YR

7/4

10YR

5/8

96.2

50.7

20.9

14.91

6.71

0.17

7.7

7.1

99

2.05

0.68

0.00

P-2

Ap

0–26

clc2sbk

dvh,mfi,ws,wp

7.5YR

4/6

5YR

4/6

41.9

38.8

35.4

23.27

12.99

0.68

8.0

14.9

73

2.87

0.60

0.94

Btg1

26–40

cn4pf

c2abk

dvh,mfi,ws,wp

7.5YR

4/6

5YR

4/6

42.2

13.9

50.0

26.33

15.68

0.29

8.0

18.2

60

2.72

0.71

3.91

Btg2

40–50/65

cn3pf

m3sbk

dvh,mfi,ws/wvs,wp

7.5YR

4/6

5YR

4/6

10

1.9

24.3

41.7

27.74

16.59

0.40

7.8

14.7

100

2.88

0.65

4.43

Btk

50/65–89

sic

n1pf

m3sbk

dvh,mfr,ws,wp

5YR

4/4

5YR

4/6

32

2.2

8.2

41.4

26.15

11.39

0.13

7.9

16.7

93

2.00

0.45

32.01

Cmk/Bt

>89

sic

n1pf

m3sbk

dvh,mfr,ws,wp

7.5YR

8/4

7.5YR

7/6

39

1.2

8.4

46.0

24.09

10.32

0.12

7.8

10.8

100

1.88

0.46

43.30

P-3

Ap1

0–13

fsl

c3pl

dsh,mfr,wss,wps/wp

10YR

5/4

7.5YR

3/4

814.2

48.3

17.9

8.98

3.11

0.36

8.0

4.2

100

0.83

0.33

0.00

Ap2

13–30

scl

c2abk

dh,mfr,wss,wps

10YR

6/4

7.5YR

4/4

116.2

44.9

24.6

11.65

4.51

0.30

7.9

4.5

93

1.18

0.49

0.00

Bt1

30–60

scl

n2pf

m3abk

dh,mfr/m

fi,ws,wp

7.5YR

5/6

5YR

4/6

117.9

42.4

27.1

15.08

5.57

0.17

7.8

7.1

78

1.45

0.57

0.00

Bt2

60–74/90

scl

n2pf

c3abk

dvh,mfr/m

fi,ws,wp

7.5YR

5/6

7.5YR

4/6

111.9

40.7

31.9

16.21

8.11

0.23

7.7

13.5

47

1.49

0.52

0.00

Bt3

74/90–112

cln4pf

c3pr

dvh,mfi,ws/wvs,wp

7.5YR

4/6

5YR

4/6

18.8

35.6

39.9

22.93

12.25

0.28

7.3

13.5

67

1.73

0.57

0.00

Bt4

112–129

cmk4pf

c3pr

dvh,mfr/m

fi,ws,wp

5YR

4/6

5YR

4/4

29.6

23.8

42.0

24.23

10.25

0.27

7.4

29.1

35

1.94

0.36

0.00

Bt5

129–155

clmk3pf

c3abk

dvh,mfr/m

fi,wss/w

s,wps

7.5YR

5/6

5YR

4/6

615.9

28.7

34.3

20.51

10.22

0.21

7.6

9.8

82

1.66

0.56

0.00

2Bt6

155–183

scl

n1br

f2abk

dsh,mfr,wss,wps

7.5YR

5/6

5YR

4/6

43

28.6

27.8

31.0

16.65

9.28

0.08

7.4

7.5

98

1.36

0.55

0.00

3Bt7

>183

scl

n1br

f1sbk

dsh,mfr,wss,wps

5YR

4/6

5YR

4/6

47

45.9

19.2

27.7

14.42

8.49

0.12

7.7

7.5

94

1.68

0.60

0.00

P-4

Ap1

0–13

clm3gr

dvh,mfr,ws,wp

10YR

5/4

10YR

4/3

12

4.0

28.2

29.5

20.16

8.76

0.60

8.0

16.4

90

2.06

0.84

22.60

Ap2

13–35

clc2/3sbk

dh,mfr,wss,wps/wp

10YR

5/3

10YR

4/3

10

4.2

26.0

30.0

20.97

9.04

0.72

8.0

13.8

97

1.52

0.46

20.34

Bwk1

35–41/59

clc2sbk

dvh/deh,mfi,ws,wp

10YR

6/4

10YR

5/4

12

4.3

26.1

30.1

20.39

7.65

0.30

8.1

12.2

100

1.28

0.40

35.97

2Bwk2

41/59–75

scl

f2sbk

dvh,mfr,ws,wp

7.5YR

5/4

7.5YR

4/4

65

13.4

39.8

29.2

13.31

5.87

0.31

8.1

5.8

100

1.20

0.39

26.81

3C1

75–99

csl

0dl,ml,wso,wpo

7.5YR

5/4

7.5YR

4/6

72

50.1

23.5

17.6

8.63

3.66

0.16

8.1

3.2

100

1.04

0.32

24.77

4C2

>99

lcos

0dl,ml,wso,wpo

10YR

6/4

7.5YR

4/6

85

60.7

25.3

10.3

3.46

1.66

0.10

9.0

1.7

100

0.85

0.09

14.87

P-5

Ap

0–32

lc2sbk

dvh,mfr,wss,wp

10YR

6/3

10YR

4/3

30.7

41.5

23.0

20.81

7.91

0.77

7.9

12.8

100

1.08

0.27

38.39

2C1

32–83

vfsl

0dsh,mvfr/m

fr,wss,wp

10YR

6/3

10YR

4/3

20.8

52.2

19.5

16.47

6.34

0.54

8.0

6.6

100

1.00

0.23

40.08

3C2

46–83

fsl

0dl,ml,wss,wpo

10YR

6/4

10YR

4/4

82

11.4

56.2

14.4

10.27

3.93

0.45

8.0

3.4

100

0.91

0.17

36.88

4C3

83–112

l0

dsh,mfr,wss,wp

10YR

6/4

10YR

4/4

00.3

45.6

18.2

16.01

5.70

0.35

8.0

7.5

100

1.15

0.26

38.09

5C4

112–151

vfsl

0ds,mvfr,wss,wps

10YR

6/3

10YR

4/3

00.4

69.1

12.5

10.34

4.39

0.27

8.0

4.5

100

1.00

0.22

40.52

6C5

151–167

l0

dsh,mvfr,wss,wps

7.5YR

6/4

7.5YR

4/4

58

10.2

32.6

17.8

16.99

5.63

0.31

8.1

9.5

100

1.16

0.27

37.11

7C6

>167

l0

dsh,mvfr,wss,wp

7.5YR

6/4

7.5YR

5/4

20.3

44.9

17.2

17.04

5.60

0.20

8.1

4.3

100

1.15

0.24

42.01

PM

b

sl0

dl

2.5Y

7/2

2.5Y

5/3

23

45.3

21.6

16.3

11.64

4.80

1.76

8.4

8.7

100

0.63

0.15

23.49

Al d,Citrate-dithioniteextractableAlas

Al 2O

3;CaC

O3eq,calcium

carbonateequivalent;CEC,cationexchan

gecapacity;

Fe d,Citrate-dithioniteextractableFeas

Fe 2O

3;OC,organiccar-

bon;WR,waterretention.Texture:c,clay;cl,clay

loam

;csl,coarse

sandyloam

;fsl,finesandyloam

;l,loam;lcos,loam

ycoarse

sand;scl,sandyclay

loam

;sic,siltyclay;sl,sandyloam

;vfsl,

very

finesandyloam

.Cutans.Thickness:mk,moderatelythick;n,thin.Frequency:1,

few;2,

common;3,

man

y;4,

continuous.Morphology:br,bindinggrains;pf,ped

face

coatings.Struc-

ture.Size:c,coarse;f,fine;m,medium;vc,very

coarse.Grade:0,

structureless;1,weak;2,

moderate;

3,strong.

Typ

e:ab

k,an

gularblocky;gr,gran

ular;pl,platy;pr,prism

atic;sbk,sub-

angu

larblocky.

Con

sistency.When

dry:deh,extrem

elyhard;dh,hard;dl,loose;ds,soft;dsh,slightlyhard;dvh

,veryhard.When

moist:mfi,firm

;mfr,friable;ml,loose;mvfr,very

friable.

Stickiness(consistency

when

wet):ws,sticky;

wso,nonsticky;

wss,slightlysticky;wvs,verysticky.Plasticity(consistency

when

wet):wp,plastic;wpo,nonplastic;wps,slightlyplastic.

aWholesoil.

bParentmaterial:fluvialsedim

ent‘pointbar’.


# 2009 The Authors


200 cm in two of the three profiles) and clayey (often > 40%

clay). Themean profile clay contents weighted for horizon thick-

nesses were P-1 ¼ 30.2%, P-2 ¼ 42.7%, and P-3 ¼ 31.3%. The

Bt horizons had ferri-argillic cutans, angular-blocky structures

(subangular in P-2), red hues (5YR) and relatively high chroma

values (6).

The fine earth fractions of Preholocene soils had moderate

contents of Fed and Ald (mean values, weighted to the thick-

ness of the horizons, of 2.72, 2.37 and 1.52% for Fed and 0.65,

0.55 and 0.53% for Ald in P-1, P-2 and P-3, respectively) and

neutral and moderately alkaline pH values (> 6.8) in all hori-

zons. The depth distributions of carbonates in Preholocene

profiles were irregular: P-1 and P-3 were almost decarbonated,

but P-2 had carbonate accumulation within the top metre.

Properties related to clay content, such as water retention at

33 and 1500 kPa, CEC and Fed and Ald peaked in the Bt

horizons.

The Holocene soils (P-4 and P-5) had smaller clay contents

and values for clay-related properties than thePreholocene soils.

The horizon thicknessweightedmean clay contents are 22.9% in

P-4 and 17.5% in P-5. The highest clay contents were found in

the Ap and Bw horizons of P-4 and in the Ap of P-5. Compared

with Preholocene profiles, the Holocene soils had yellower hues

(10YR and 7.5YR), lower contents of Fed and Ald (horizon

thickness weighted means of 1.24 and 1.06% for Fed and 0.37

and 0.24% for Ald in P-4 and P-5, respectively), higher car-

bonate percentages (> 14% throughout) and were more alka-

line (pH > 7.9 throughout).

The contents of organic matter in the whole chronosequence

were small (OC < 1%) throughout, including all A horizons.

Soil mineralogy

The most abundant minerals found in all horizons of all profiles

and in the fresh alluvial parent material were phyllosilicates

(illite, paragonite, chlorite, smectite, kaolinite and various inter-

stratified phases), as shown by their dominance in the fine earth

(Table 4). The horizon thickness weighted means of phyllosili-

cates are 59% in P-1, 54% in P-2, 46% in P-3, 34% in P-4 and

30% in P-5, indicating that phyllosilicate contents increased

with soil age. This can also be observed by the height of the

XRD peak at 0.256 nm, which increased from P-5 to P-1

(Figure 2).

Quartz was the second most abundant mineral in the chrono-

sequence. Quartz was dominant in sand fractions (except in the

coarse sand of P-1 and P-2 where phyllosilicates and calcite

predominated, or in the fine sand of P-5 where calcite was dom-

inant). P-3 had larger feldspar contents in all the granulometric

fractions than the other soils, probably because it had developed

on somewhat different parent material. The iron oxides are

mainly goethite with minor quantities of haematite; iron oxides

percentages increased with soil age, as with the phyllosilicates.

Carbonates (calcite and dolomite) were abundant in most

granulometric fractions in the Holocene soils (e.g. in P-5, mean

profile values of calcite þ dolomite were > 30%), and there

were more than in Preholocene soils (except for the calcic Btk

and Cmk/Bt horizons of P-2). The largest proportions of dolo-

mite were found in the Holocene horizons. In the Preholocene

horizons the carbonate present was almost exclusively calcite,

with P-2 notably enriched by calcite accumulation.

The mean mineralogical composition by granulometric frac-

tions (Figure 3) shows: (i) a relative accumulation of tectosili-

cates (quartz and feldspars) and, to a lesser extent, carbonates

(calcite and dolomite) in sand fractions; (ii) an accumulation of

phyllosilicates and iron oxides in fine earth and, to a lesser

extent, in silt; and (iii) the intermediate composition of silt frac-

tion, with medium contents of phyllosilicates and iron oxides,

carbonates and tectosilicates.

The overall fine earth, and separate fine sand and silt diagrams

(Figure 3a,c,d) show a larger mean content of carbonates in the

Holocene soils (P-4 and P-5) than in the Preholocene soils (P-1,

P-2 and P-3). This differentiation is not clear in the coarse sand

diagram (Figure 3b) because of the large content of carbonates

found in Preholocene profile P-2 and the smaller content in the

Holocene profile P-4.

Figure 2 XRD diagrams, in the region 29–38°2h (CuKa), of the fine

earth fraction of selected soil horizons of the chronosequence. Cal ¼calcite; Dol ¼ dolomite; Phyll ¼ phyllosilicates (illite, paragonite,

smectite, kaolinite and interstratified phases); Qz ¼ quartz.


# 2009 The Authors


Soil SEM-fabric

Particle-cluster morphology was similar in the studied horizons

of P-1 and P-2 (Figures 4a,b and 5a,b), showing ellipsoidal

(some of which tend to be approximately isometric) and vaguely

pseudohexagonal forms, with slightly sinuous edges. IA meas-

urements confirmed the visual impressions, with a mean shape

factor of 0.70, which implies limited elongation, and mean con-

vexity of 0.90 and0.92, respectively (i.e. close to 1),which implies

smooth edges.

Skeleton grainswere hardly visible in P-1 andwere not seen at

all in P-2 because of the greater accumulation of clay particles

(as expected in argic horizons with more than 40% clay). The

grains in P-1 had a mean feret diameter of 57 mm, and were

embedded into the particle-clusters that occupied 14% of the

total area. Themineralogy of these grains was diverse (Table 4)

and included potassium feldspar, as shown by the EDX-spec-

trum (Figure 4e).

Total pore areas in P-1 and P-2 (Figures 4d and 5d) were

smaller (< 10%) than in the rest of the chronosequence

(Figures 6d–8d). Thismayhave resulted fromdense fabric pack-

ing, scarcity of skeleton grains and the importance of cementing

agents such as iron oxides. The substantial iron oxides (Fed3.52% in the Bt of P-1 and 2.72% in the Btg of P-2; Table 3),

were verified by strong Fe peaks in the EDX-spectra (e.g.

Figure 4e).

The particle-cluster morphology in the sample from the youn-

gest Preholocene profile P-3 (Figures 6a,b) differs slightly from

Table 4 Mineralogical analysis (XRD) of granulometric fractions of soil horizons and parent material (PM) (%)

Profile Horizon

Fine earth (< 2 mm) Coarse sand (0.25–2 mm) Fine sand (0.05–0.25 mm) Silt (0.002–0.05 mm)

phyll qz fd iron ox cal dol phyll qz fd iron ox cal dol phyll qz fd iron ox cal dol phyll qz fd iron ox cal dol

P-1 Ap 60 31 3 6 30 63 5 2 14 78 7 1 25 66 5 2 2

Bt 60 17 13 9 1 42 54 1 3 23 68 6 3 58 32 3 3 4

Btg1 67 24 3 3 3 70 26 2 1 1 39 55 3 2 1 61 27 4 4 4

Btg2 61 26 3 9 1 56 38 2 4 38 48 9 5 61 28 3 4 4

2BCtg 54 31 3 9 3 49 42 2 4 3 31 64 3 1 1 70 20 5 5

3BCt 55 29 3 10 3 42 52 3 2 1 28 63 5 3 1 58 38 2 2

4C 61 30 4 4 1 49 47 2 2 28 58 12 2 56 34 4 5 1

P-2 Ap 47 42 3 6 2 16 67 14 2 1 7 66 26 1 30 61 5 2 2

Btg1 68 16 4 8 4 25 14 1 3 57 20 67 5 3 5 49 43 4 2 2

Btg2 62 22 3 7 5 20 27 2 3 48 18 63 17 1 1 41 47 8 2 2

Btk 54 14 1 6 24 11 16 2 1 69 1 21 58 6 3 12 27 21 2 1 49

Cmk/Bt 50 9 2 7 32 23 14 1 1 61 22 47 4 2 25 25 17 2 2 54

P-3 Ap1 26 46 24 3 1 4 49 44 2 1 10 51 38 1 24 54 21 1

Ap2 21 48 27 3 1 14 59 26 1 4 41 53 1 1 16 68 14 2

Bt1 56 16 19 8 1 6 59 35 5 70 23 2 19 67 13 1

Bt2 41 29 24 4 1 1 3 40 56 1 5 67 28 21 64 13 1 1

Bt3 58 24 11 6 1 8 55 36 1 4 67 25 3 1 20 62 16 2

Bt4 51 23 20 5 1 8 37 50 1 4 7 58 31 1 3 30 61 9

Bt5 56 25 13 5 1 8 54 36 1 1 6 61 30 2 1 38 54 7 1

2Bt6 44 22 29 3 1 1 15 57 24 3 1 8 60 23 2 7 20 69 10 1

3Bt7 39 25 26 8 2 22 43 33 2 nd nd nd nd nd nd 45 44 8 3

P-4 Ap1 48 15 5 4 11 17 10 37 36 1 16 14 33 8 2 10 33 34 27 3 1 11 24

Ap2 51 15 5 6 14 9 9 47 30 14 8 23 10 2 10 47 31 28 4 1 12 24

Bwk1 36 17 7 8 7 25 15 51 14 17 3 11 19 4 1 13 52 17 17 1 1 36 28

2Bwk2 43 17 7 4 14 15 6 41 50 2 1 14 59 24 2 1 36 20 2 25 17

3C1 22 24 15 3 17 19 8 47 26 1 18 21 18 5 4 22 30 25 21 3 1 23 27

4C2 15 37 21 2 13 12 9 41 33 2 15 20 31 6 4 15 24 30 20 2 3 10 35

P-5 Ap 38 16 5 4 21 16 8 26 12 2 52 21 23 7 3 31 15 19 21 1 2 35 22

2C1 33 18 3 3 23 20 18 40 7 2 28 5 14 28 4 3 32 19 19 22 5 2 28 24

3C2 10 22 12 2 24 30 19 30 17 3 23 8 16 20 10 3 31 20 28 19 1 2 30 20

4C3 45 14 2 4 16 19 22 23 6 1 34 14 35 21 4 2 23 15 32 25 4 1 26 12

5C4 11 31 7 4 28 19 18 31 4 2 33 12 25 25 9 2 30 9 33 30 5 2 13 17

6C5 39 19 5 5 18 14 9 38 28 2 18 5 18 22 5 3 28 24 35 32 6 3 7 17

7C6 34 15 3 4 21 23 9 41 9 3 38 13 33 3 33 18 22 26 5 1 22 24

PM 27 30 21 3 18 1 15 53 26 6 17 30 10 3 33 7 10 18 3 2 56 11

cal, calcite; dol, dolomite; fd, feldspars; iron ox, iron oxides (hematite and goethite); nd, not determined; phyll, phyllosilicates; qz, quartz.


# 2009 The Authors


that of P-1 andP-2.Although they show similar convexity (0.90),

their shape factor reveals them to be slightly more elongated

(0.65 in P-3 compared with 0.70 in both P-1 and P-2). The P-3

sample also has larger proportions of skeleton (approximately

15%of total image area, with amean feret maximum of 41 mm),

less cemented appearance, and smaller contents of iron oxides or

other cementing agents (Fed only 1.94% and no carbonates;

Table 3) than in P-1 and P-2. This could also explain the

higher porosity (12.60% of the area occupied) and slightly

more open fabric than in P-1 and P-2.

In general terms, the ultramicrofabric of the samples from the

Holocene profiles P-4 and P-5 (Figures 7 and 8) differed sub-

stantially from those of the Preholocene profiles and were gen-

erally less well organized. They had more visible and abundant

skeletal materials with 17 and 30% out of the total image areas

occupied by mineral grains in P-4 and P-5, respectively. The

particle clusters are ill-defined with more irregular morpholo-

gies, and mean convexity is< 0.90 in both P-4 and in P-5. They

are more elongated with shape factors < 0.60 and are generally

smaller than in the older profiles P-1 and P-3.

Within the Holocene soils there are clear differences between

the Calcisol (P-4) and Fluvisol (P-5). The particle-clusters in

P-4 are less sinuous and elongated with convexity of 0.82 and

shape factor of 0.54, than in P5 where they have convexity of

0.77 and shape factor of 0.44. Furthermore, the P-4 particle-

clusters are formed by particle aggregations of skeletal and fine

fraction particles cemented by carbonates, as shown by chem-

ical analysis (Table 3) and by the Ca peak in the EDX-spectra

(Figure 7e). The total pore area in P-4 (Figure 7d) is larger than

in Preholocenic soils and the degree of packing lower. This may

be because of smaller clay content and the abundance of skeletal

elements.

The particle clusters in P-5 (Figure 8a,b) are the smallest in

the chronosequence (45 mm) and are quite irregular and elon-

gated (convexity of 0.77 and a shape factor of 0.44). They consist

of loose and ill-defined aggregates of carbonate grains and plate-

like particles of phyllosilicates of fine silt size (2–20 mm)

cemented by carbonates, as is clearly shown by the peak of cal-

cium in the EDX-spectrum (Figure 8e). Such particle clusters

seem to be deposited on skeleton grains and connected to them

Figure 3 Ternary plot of Phyllosilicates þ iron oxides – Carbonates – Tectosilicates (% from XRD analysis) in the parent material (PM) and pro-

file mean (weighted to horizon thickness) values for granulometric fractions; (a) overall fine earth (< 2 mm); (b) coarse sand (0.25–2 mm); (c) fine

sand (0.05–0.25 mm); and (d) silt (0.002–0.05 mm). Tectosilicates ¼ quartz þ feldspars; carbonates ¼ calcite þ dolomite.


# 2009 The Authors


bymeans of weak bridges, probably of carbonates. The particle-

cluster arrangement has a reticular structure. One of the out-

standing features of P-5 is the abundance of non-aggregated

skeleton grains. These occupy 30%of the image area (Figure 8c),

and have a mean feret maximum of 53 mm. Because of the

reduced cementation and abundance of skeleton grains, the total

porosity was the largest observed (32%, Figure 8b).

The P-5 sample had the least evolved SEM-fabric in the chro-

nosequence. This results from the small clay content (Bronick &

Lal, 2005), smaller and more elongated and irregular particle

clusters, larger skeleton content and higher porosity and, finally,

because themain cementing agent was carbonate. These distinc-

tive features are similar to those in the fabric of a granulated

albic Arenosol in Cameroon (Lamotte et al., 1997).

Figure 4 SEM-fabric and Image Analysis of Bt horizon from P-1: (a) SEM photography; (b) particle clusters; (c) skeleton grains; (d) porosity and

(e) EDX-spectrum (marked with * in a). SD ¼ standard deviation. (Au peak is an artefact from SEM sample preparation.)

Figure 5 SEM-fabric and Image Analysis of Btg2 horizon from P-2: (a) SEM photography; (b) particle clusters; (c) skeleton grains; and (d)

porosity. SD ¼ standard deviation.


# 2009 The Authors


The dendrogram (Figure 9) of the hierarchical clustering of

the SEM-IA variables distinguishes three morphometric types.

Type 1 (P-1 and P-3) has the most developed fabric, with large

and rounded particle clusters, few skeleton grains and low

porosity. This group is associated with Luvisols. Type 2 (P-4

and P-2), includes fabrics with particle clusters of medium size

and with medium or large values of convexity and shape factor

(Figures 5 and 7) and is associated with Calcisols. Type 3, with

the least developed ultramicrofabric, is associated with the

Fluvisol (P-5) and is characterized by the large percentages of

skeleton grains and pores, and small, irregular and elongated

particle clusters (Figure 8).

The IA measurements of soil SEM-fabric can be related to

other analytical, mineralogical and macromorphological prop-

erties (Table 5). Clay percentage correlates with particle clusters

shape factor and convexity (r ¼ 0.984 and 0.988, respectively),

and inversely with total pore area (r ¼ �0.977). Thus, a large

clay content is associated with the tendency towards increasing

roundness and smoothness of the particle clusters and decreas-

ing porosity. The texture class, after optimal scaling

Figure 6 SEM-fabric and Image Analysis of Bt4 horizon from P-3: (a) SEM photography; (b) particle clusters; (c) skeleton grains; and (d) poro-

sity. SD ¼ standard deviation.

Figure 7 SEM-fabric and Image Analysis of Bwk1 horizon from P-4: (a) SEM photography; (b) particle clusters; (c) skeleton grains; (d) porosity;

and (e) EDX-spectrum (marked with * in a). SD ¼ standard deviation. (Au peak is artefact from SEM sample preparation.)


# 2009 The Authors


transformation (Calero et al., 2008), and the XRD percentage

of phyllosilicates in fine earth (Table 5) also correlated signifi-

cantly with SEM-IA fabric attributes. The significant correla-

tion between particle clusters feret and the amount of XRD

calcite in fine earth (Table 4) (r ¼ �0.910), confirms that par-

ticle clusters size increased with decreasing calcite content.

PCA of chronosequence

The principal component analysis (PCA) gave an optimized fac-

torial model, with KMO of 0.823 and a highly significant Bar-

lett’s test (P < 0.001). The model (Table 6) yielded two

components accounting for a satisfactory 78% of the total

variance (Sondheim & Standish, 1983; Scalenghe et al., 2000;

Shaw et al., 2003). The first component accounted for 48% of

the variance and was positively related to Ald, Fed, clay, phyl-

losilicates-XRD, texture class, cutan thickness, cutan mor-

phology and moist consistency. There was a negative

relationship with all of the carbonate variables. The second

component, which accounted for 29% of the variance in the

chronosequence, was positively related to carbonate variables

such as CaCO3 eq and calcite-XRD both in fine earth and in

coarse sand.

The component scores (Figure 10a) tend to group the hori-

zons by profile taxonomy, and accord with the chronosequence.

Thus, the Preholocene soils (cutanic Luvisols P1 and P-3, and

the lixic Calcisol P-2) have positive, and the ParentMaterial has

the most negative, scores on PC1. The horizons from the less

developed Holocene soils (P-4 and P-5) are grouped in the left-

upper quadrant of the scatterplot, with negative scores for PC1

and positive scores for PC2. Projections on PC2 differentiate

between the haplic Calcisol and the haplic Fluvisol, reflecting

differences in carbonate contents. Similarly, PC2 distinguishes

the decarbonated horizons in profiles P-1 and P-3 from the Bt

carbonated horizons in P-2 in the Preholocene soils.

The location of the SEM-IA horizons in the scatterplot

(Figure 10b) shows that soil fabric morphometric type (Figure 9)

is related to the macromorphologically, mineralogically and

chemically defined PCs. Fabric type 1 horizons were closely

grouped with positive scores for PC1, those of fabric type 2 are

dispersed on PC1 but grouped on PC2, and the horizon with

Figure 9 Dendrogram of cluster analysis of SEM-fabric and IA hori-

zons. Groups: Type 1- Luvisols; Type 2- Calcisols; and Type 3-

Fluvisol.

Figure 8 SEM-fabric and Image Analysis of Ap horizon from P-5: (a) SEM photography; (b) particle clusters; (c) skeleton grains; (d) porosity;

and (e) EDX-spectrum (marked with * in a). SD ¼ standard deviation. (Au peak is artefact from SEM sample preparation.)


# 2009 The Authors


fabric type 3 has the highest score on the PC2 and is clearly sep-

arated from the other types.

Chronofunctions

In the chronofunction equations tested (Table 7), Harden’s PDI

and some important soil properties (% clay, pH and % CaCO3

eq) fit the logarithmic model better than quadratic or linear

models. However, Fed fits the linear and quadratic models bet-

ter than the logarithmic model. The first principal component

(PC1) fits both the quadratic and logarithmic models. In con-

trast, the carbonate-dominated PC2 does not adequately fit

any of the chronofunction models tested.

Although the data set is limited to five samples, some SEM-

IA-fabric morphometric attributes also fit chronofunctions

(Table 7). Porosity (total pore area in % ¼ �2.4596 ln (age in

kyear) þ 22.624; r ¼ �0.995; ***) and particle-cluster mor-

phology (mean convexity ¼ 0.0147 ln (age in kyear) þ 0.8252;

r ¼ 0.962; **; mean shape factor ¼ 0.0265 ln (age in kyear)

þ 0.5397; r ¼ 0.993; ***) fit logarithmic models. In contrast,

particle clusters size (feret) and skeleton percentage do not fit

adequately in any of the chronofunction models, possibly

because of the small size of particle clusters and the absence of

skeleton grains from profile P-2.

Pedogenetic discussion and conclusions

The soil macromorphological and analytical properties concur

with mineralogy in distinguishing between Preholocene and

Holocene soils. The data suggest that one of the main processesTable

5Linearcorrelationmatrix

forSEM-IA

andselected

soilproperties:rvalues

C.Fer

C.Sha

C.Con

Pore

Skel

Clay

CO

3¼

Fe d

Al d

Text

PhylX

RDfe

CalX

RDfe

CalX

RDfs

CalX

RDcs

DolX

RDfe

Cut.th

Cut.mo

C.w.m

.

C.Fer

0.789

0.730

�0.804

�0.428

0.820

�0.767

0.724

0.583

0.827

0.595

�0.910*

�0.840

�0.888*

�0.554

0.707

0.706

�0.012

C.Sha

0.986**

�0.996***

�0.855

0.984**

�0.933*

0.893*

0.843

0.976**

0.914*

�0.892*

�0.979**

�0.447

�0.801

0.923*

0.933*

0.260

C.Con

�0.979**

�0.871

0.988**

�0.948*

0.826

0.766

0.978**

0.914*

�0.879*

�0.967**

�0.399

�0.834

0.949*

0.953*

0.335

Pore

0.867

�0.977**

0.907*

�0.874

�0.842

�0.983**

�0.877

0.917*

0.991***

0.477

0.750

�0.893*

�0.903*

�0.311

Skel

�0.793

0.680

�0.675

�0.794

�0.832

�0.750

0.706

0.843

0.061

0.554

�0.700

�0.715

�0.624

Samplesused:Btfrom

P-1;Btg2from

P-2;Bt4

from

P-3;Bwk1from

P-4;andApfrom

P-5.N¼

5.Statisticalsignificance:*<

0.05;**<

0.01;***<

0.001.

Al d,Citrate-dithioniteextractableAlasAl 2O

3;CalX

RDcs,calcitepercentagein

coarsesand(X

RD);CalX

RDfe,calcitepercentagein

fineearth(X

RD);CalX

RDfs,calcitepercentagein

finesand(X

RD);C.Con,meanconvexityofparticle

clusters;C.Fer,meanferetmax.diam.particle

clusters;Clay,claypercentage;

CO

3¼,Calcium

carbonate

equivalentin

fineearth;

C.Sha,meanshapefactorofparticle

clusters;Cut.mo,cutansmorphology(optimalscaling);Cut.th,cutansthickness(optimalscaling);C.w.m

.,consistency

when

moist(optimalscal-

ing);DolX

RDfe,dolomitepercentagein

fineearth(X

RD);Fe d,Citrate-dithioniteextractableFeasFe 2O

3;PhylX

RDfe,phyllosilicatespercentagein

fineearth(X

RD);Pore,totalarea

ofpores;Skel,totalareaofskeleton;Text,texture

class

(optimalscaling).

Optimalscaling:qualitativevariablestransform

edto

quantitativebynonlinearprincipalcomponentanalysis(C

alero

etal.,2008).

Table 6 Principal component analysis (PCA). Soil property loadings for

the two principal components (PC-1 and PC-2)

PC-1 PC-2

Phyllosilicates in fine earth (XRD)/% 0.861 0.248

Calcite in fine earth (XRD)/% �0.759 0.586

Dolomite in fine earth (XRD)/% �0.790 0.163

Calcite in fine sand (XRD)/% �0.868 0.374

Calcite in coarse sand (XRD)/% �0.278 0.882

Fed in fine earth/% 0.808 0.153

Ald CD in fine earth/% 0.855 �0.011

Clay in fine earth/% 0.788 0.477

CaCO3 equivalent in fine earth/% �0.798 0.544

Consistency when moist (optimal scaling) 0.746 0.226

Texture class (optimal scaling) 0.847 0.278

Cutan thickness (optimal scaling) 0.780 0.288

Cutan morphology (optimal scaling) 0.777 0.315

Autovalue 6.288 3.818

% variation 48.37 29.37

Total variation 77.74

N ¼ 35 (all soil horizons and parent material).

Optimal scaling: qualitative variables transformed to quantitative by

nonlinear principal component analysis (Calero et al., 2008).


# 2009 The Authors


Table

7Chronofunctionsofthesoilproperties

y

Linear

Logarithmic

Quadratic

Equation

rEquation

requation

r

PDIa

y¼

0.0325xþ

29.0330

0.7546

y¼

2.5066Ln(x)þ

29.0800

0.9880*

y¼

�0.0001x2þ

0.1087xþ

26.1540

0.8873

Clay/%

ay¼

0.0240xþ

25.7760

0.7222

y¼

1.7929Ln(x)þ

25.9550

0.9210*

y¼

�0.0001x2þ

0.1025xþ

22.8080

0.9604*

pH

ay¼

�0.0010xþ

7.9940

�0.8302

y¼

�0.0491Ln(x)þ

7.9160

�0.9970***

y¼

�2E�06x2þ

0.0002xþ

7.9459

�0.9082

CaCO

3equivalentin

fineearth/%

ay¼

�0.0395xþ

23.8850

�0.6532

y¼

�3.4425Ln(x)þ

24.8150

�0.9392*

y¼

6E�05x2�0.0764xþ

25.2780

�0.7511

Sand/%

ay¼

�0.0252xþ

48.5010

�0.5118

y¼

�1.5075Ln(x)þ

47.3780

�0.5708

y¼

0.0002x2�0.1559xþ

53.4390

�0.8541

CEC/cmol þ

kg�1a

y¼

0.0035xþ

9.5092

0.3205

y¼

0.3549Ln(x)þ

9.2958

0.5745

y¼

�7E�05x2þ

0.0420xþ

8.0526

0.9286

Fe d

infineearth/%

ay¼

0.0032xþ

1.2286

0.9721**

y¼

0.1663Ln(x)þ

1.4390

0.8626

y¼

�4E�06x2þ

0.0053xþ

1.1501

0.9890*

WR

1500kPa/%

ay¼

0.0090xþ

6.9862

0.7660

y¼

0.5436Ln(x)þ

7.3850

0.7909

y¼

�5E�05x2þ

0.0361xþ

5.9633

0.9683*

WR

33kPa/%

ay¼

0.0074xþ

16.8780

0.4976

y¼

0.4870Ln(x)þ

17.0950

0.5741

y¼

�8E�05x2þ

0.0547xþ

15.0900

0.9182

Meanferetmaxofparticleclusters/mm

2y¼

0.0454xþ

60.3420

0.6910

y¼

3.2239Ln(x)þ

61.0970

0.8275

y¼

5E�05x2þ

0.0156xþ

61.4680

0.6997

Meanshapefactorofparticleclustersb

y¼

0.0003xþ

0.5421

0.7475

y¼

0.0265Ln(x)þ

0.5397

0.9934***

y¼

�1E�06x2þ

0.0011xþ

0.5118

0.8903

Meanconvexityofparticleclustersb

y¼

0.0002xþ

0.8308

0.6450

y¼

0.0147Ln(x)þ

0.8252

0.9619**

y¼

�1E�06x2þ

0.0007xþ

0.8099

0.8706

Totalpore

area/%

by¼

�0.0299xþ

22.2920

�0.7287

y¼

�2.4596Ln(x)þ

22.6240

�0.9949***

y¼

0.0001x2�0.1022xþ

25.0230

�0.8664

Totalskeletalarea/%

by¼

�0.0200xþ

19.1590

�0.4791

y¼

�2.0612Ln(x)þ

20.4310

�0.8322

y¼

0.0002x2�0.1427xþ

23.7960

�0.9160

PC-1

ay¼

0.0027x�0.3596

0.7870

y¼

0.1924Ln(x)�

0.3131

0.9204*

y¼

�1E�05x2þ

0.0106x�0.6576

0.9921**

PC-2

ay¼

�0.0014xþ

0.3603

�0.3783

y¼

�0.1315Ln(x)þ

0.4244

�0.5997

y¼

�5E�06x2þ

0.0017xþ

0.2462

�0.4370

x¼

agein

ka.N

¼5(P-1,P

-2,P

-3,P

-4andP-5).Statisticalsignificance:*<

0.05;**<

0.01;***<

0.001.P

DI¼

profiledevelopmentindex

(Harden,1982),forthicknessof1m;P

C-1

andPC-

2¼

principalcomponents.ForrestofvariableabbreviationsseeTable

3.

aMeanweightedto

thickness,ofprofilehorizons,upto

thicknessof1m.

bHorizonsamplesstudiedbySEM.


# 2009 The Authors


in the ageing of the soils is the increase of phyllosilicates and clay

through weathering and/or illuviation. These processes also

affect the concentrations and forms of free iron, the selective

concentration of which explains the reddening of the soil (rube-

faction). Furthermore, because of prolonged weathering and

leaching, carbonates (except in the Calcisol P-2) decreased,

and even disappeared completely, in the older soils. PCA sum-

marization of data supports these pedological trends. The first

component accounted for almost 50% of variance and encapsu-

lates the main features. This PC includes positive contibutions

from% clay,% phyllosilicates XRD, cutan thickness and cutan

morphology; its relationships with carbonates are negative.

Similar pedogenetic processes are described in other soil Qua-

ternary chronosequences in Mediterranean climates (Torrent

et al., 1980; Birkeland, 1999; Scarciglia et al., 2006) and they

are characteristic of well-developed Mediterranean soils with

clayey Bt horizons that are relatively rich in iron and alumin-

ium sesquioxides (Torrent, 1995).

The application of image analysis of SEMmicrographs shows

that the evolution of the ultramicrofabric of the interior of peds

matches the trends in other soil properties. Thus the SEM-IA-

fabric morphometric features are correlated with many of the

analytical, mineralogical and macromorphological soil proper-

ties, and the grouping of the soils by hierarchical clustering

of measured morphometric SEM-IA parameters of the fabric

parallels their taxonomy, composition and pedogenetic

development.

Logarithmic, quadratic and linear chronofunction models

have been tested for the SEM-IA-fabric morphometric data as

well as the other soil attributes. Satisfactory fits with logarithmic

and quadratic chronofunctions are interpreted as indicating

developmental convergence towards a steady state (Schaeltz

et al., 1994).

Acknowledgements

This study was partly supported by the Soil Science Investiga-

tion Group (RNM-127, Junta de Andalucıa, Spain). We thank

Robert Abrahams for translating the manuscript into English.

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sem image analysis in the study of a soil

Documents

years cutanicluvisol

amillion years

years haplic calcisol

soil development

years lixic calcisol

years haplic fluvisol

years cutanic luvisol

principal component