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SOIL DEVELOPMENT, PLANT COLONIZATION AND LANDSCAPE FUNCTION ANALYSIS FOR
DISTURBED LANDS UNDER NATURAL AND ASSISTED REHABILITATION
By
DWI SETYAWAN Sarjana in Agriculture (BSc Hons.) Bogor Agricultural University, Indonesia
MSc(Agric) The University of Western Australia
This thesis is presented for the degree of Doctor of Philosophy of The University of Western Australia
SCHOOL OF EARTH AND GEOGRAPHICAL SCIENCES FACULTY OF NATURAL AND AGRICULTURAL SCIENCES
2004
In loving memory of
Habibah Nur Amaliah
(30/6/1992 – 3/11/1996)
i
Soil development, plant colonization and landscape function analysis for disturbed lands under natural and assisted rehabilitation
Dwi Setyawan
ABSTRACT
Spontaneous plant growth and soil development occur at disturbed sites with
their extent and nature being variously affected by soil fertility status, local climate and
topographic conditions. Soil-plant interactions can be diverse and site-specific within a
disturbed landscape. The main purpose of the present study is to evaluate soil
characteristics and landscape indices in relation to natural plant growth and soil
development under different conditions and for diverse materials. A comprehensive
study has been carried out to evaluate spontaneous soil development and plant
colonization on various regolith materials at a railway cutting near Jarrahdale bauxite
mine and on various substrates comprising waste rock, weathered regolith and replaced
topsoil at Scotia (Norseman, Western Australia) and Kelian (East Kalimantan,
Indonesia).
At Jarrahdale soil development has occurred slowly over 36 years in relation to
morphological changes in surface horizons. Soils at several locations exhibit substantial
changes in color, texture and structure. The slow soil development is primarily due to
low biomass and litter contributions (~1 Mg/ha) from colonizing plants (e.g. Dryandra
sessilis, Eucalyptus marginata and low shrubs) on the cutting shelf and slow litter
decomposition. Nutrient accumulation is up to 5 kg N/ha, and 0.5 kg/ha for P and K.
Surface soil samples from Jarrahdale are generally acidic (pH < 5.1) and contain low
concentrations of total soil carbon (20 g/kg) and nutrients of total nitrogen (0.73 g/kg),
bicarbonate-extractable phosphorus (bic-P) (< 2 mg/kg), bic-K (37 mg/kg) and total
exchangeable bases (<1.1 cmol/kg, with 24 % base saturation).
Soil properties at the Scotia waste dump are mainly associated with alkaline
(mean pH = 9) and saline conditions (EC1:5 = 1.01 dS/m). Exchangeable base values
are high with average concentrations of exchangeable Ca of 18 cmol/kg and exchange-
able Mg of 6 cmol/kg, thus these elements are not a limiting factor for plant nutrition.
Patchy plant growth on the waste dump is mostly related to differences in water
availability in the arid region and to salinity such that halophytes (saltbushes Maireana
ii
and Atriplex) colonize many parts of the waste dump together with some Melaleuca and
Eucalyptus species.
Soil development and vegetation growth occurs rapidly on rehabilitated mine sites
at Kelian (East Kalimantan). Ripping and piled-dumping during topsoil replacement
have been used to prepare rehabilitated sites in which topsoil serves as a cover material
over waste rocks. Vigorous plant growth, mainly local species of meranti (Shorea sp)
exists across the rehabilitated mine sites due to high annual rainfall (up to 4000 mm),
thus abundant soil moisture is available for plant growth. Abundant litterfall is evident
at the surface of older rehabilitated sites providing a large increase in total soil carbon
(TC) in the topsoil from 5 g/kg (3-month sites) to 95 g/kg (7-year sites). The average
concentration of potentially mineralizable nitrogen (PMN) also increased from 12 to 50
mg/kg. Soil respiration varies greatly (200 to 800 mg CO2/m2/hr) across the sites and
field infiltration also shows much variation (10 to >1000 mm/hr).
For all three sites, Landscape Function Analysis (LFA) has been employed to
assess soil surface conditions in comparison to neighbouring undisturbed (analogue)
sites. The bare soil zone comprises the largest part of Jarrahdale and Scotia sites and
contributes substantially to low values of LFA indices. In general values of LFA indices
are in the order of stability > infiltration > nutrient cycling with values ranging from 50
to 65 % for stability and infiltration indices and up to 20 % for nutrient cycling index
(NCI). For Kelian, LFA indices of 7-year sites are close to values for primary forest, in
particular NCI values which increased to 50 % compared with 70 % for analogue sites.
Variations in these indices are due to local conditions which are driven by vegetation
and litter cover, biophysical entrapment and micro-topographic situation, and soil
texture.
The present study demonstrates that successful plant growth under natural
conditions and associated soil development on disturbed sites are related to a number of
soil and environmental factors including properties of regolith materials, fringing
vegetation, water availability and variations in micro-relief.
iii
TABLE OF CONTENTS
ABSTRACT iLIST OF TABLES viiLIST OF FIGURES ixLIST OF APPENDICES xivACKNOWLEDGMENT xvGLOSSARY OF TERMS xvi Chapter 1. Introduction 11.1. Research background 11.2. Overview of key issues in the study 1 1.2.1. General principles of rehabilitation of degraded lands, particularly minesites
1
1.2.2. Soil development/formation processes in lateritic (Jarrahdale), saline-sodic (Scotia) and tropical (Kelian) soil profiles
3
1.2.3. LFA and its underlying ecological principles, and the methods for implementing it in the field
3
1.3. Research aim 41.4. Research approach 51.5. Thesis outline 6 Part 1. Soil development and plant growth on several regolith materials derived from granite at Jarrahdale, Western Australia
9
Chapter 2. Parent material, micro-relief and plant colonization on the railway cutting shelf near Jarrahdale bauxite mine, Western Australia
11
2.1. Introduction 112.2. Materials and methods 13 2.2.1. Study sites 13 2.2.2. Sampling plots 15 2.2.3. Micro-scale mapping 18 2.2.4. Biomass prediction 18 2.2.5. Plant and litter analyses 192.3. Results and discussion 19 2.3.1. Parent materials of the cutting shelf soils 19 2.3.2. Micro-geomorphic units 23 2.3.3. Soil surface morphology 27 2.3.4. Plant colonization and standing biomass 30 2.3.5. Nutrient concentrations of plant and litter samples 38 2.3.6. General discussion 43Chapter 3. Properties of lateritic regolith 36 years after exposure in the Jarrahdale railway cutting
45
3.1. Introduction 453.2. Materials and methods 45 3.2.1. Field technique 46 3.2.2. Soil sampling 46 3.2.3. Soil analyses 47 3.2.4. Statistical analysis 48
iv
3.3. Results and discussion 49 3.3.1. Gravel content and particle size distribution 49 3.3.2. Bulk density, aggregate stability and hydraulic conductivity 53 3.3.3. Soil acidity and salinity 55 3.3.4. Total carbon and total nitrogen 57 3.3.5. NaHCO3-extractable phosphorus 60 3.3.6. NaHCO3-extractable potassium 62 3.3.7. Exchangeable base cations and CEC 64 3.3.8. Multivariate analysis 71 3.3.9. Clay mineral composition 73 3.3.10. General discussion 75Chapter 4. The assessment of soil surface conditions on the Jarrahdale cutting shelf using Landscape Function Analysis
79
4.1. Introduction 794.2. Materials and methods 80 4.2.1. The basic of landscape function analysis 80 4.2.2. Observation transects 864.3. Results and discussion 88 4.3.1. Landscape organization and indices in horizontal direction 88 4.3.2. Down-slope variation in landscape parameters 91
4.3.3. LFA infiltration index in relation to unsaturated hydraulic conductivity
94
Part 2. Natural rehabilitation of a gold mine waste dump in an arid region of Western Australia
97
Chapter 5. Integrating landscape indices and soil properties for assessing spontaneous soil and ecosystem development on a waste dump at the Scotia gold mine, Western Australia
99
5.1. Introduction 995.2. Materials and methods 100 5.2.1. Study area 100 5.2.2. Sampling method 102 5.2.3. Analytical methods 104 5.2.4. Statistical analysis 1055.3. Results and discussion 105 5.3.1. Landscape organization and soil surface conditions 105 5.3.2. Soil properties 108
5.3.3. Relationships between soil properties 110 5.3.4. Multivariate analysis 112 5.3.5. Vegetation pattern and plant sample analysis 114 5.3.6. General discussion 119 Part 3. Land rehabilitation and the LFA method at a gold mine site in the tropical climate of East Kalimantan
123
Chapter 6. Soil properties of a rehabilitated mine site at Kelian, East Kalimantan Indonesia
125
6.1. Introduction 1256.2. Materials and methods 126 6.2.1. Study area 126
v
6.2.2. Soil sampling 127 6.2.3. Analytical methods 129 6.2.4. Statistical analysis 1296.3. Results and discussion 130 6.3.1. Physical properties of Kelian soils 130 6.3.2. Chemical properties of Kelian soils 134 6.3.3. General discussion of analytical data 139Chapter 7. Landscape Function Analysis for the assessment of mine site rehabilitation under a tropical climate
143
7.1. Introduction 1437.2. Materials and methods 144 7.2.1. Assessment of soil surface conditions 144 7.2.2. Measurement of soil respiration and field infiltration 145 7.2.3. Statistical analysis 1477.3. Results and discussion 147 7.3.1. Landscape indices of rehabilitated mine sites 147 7.3.2. Relationship of stability index to MWD of water-stable aggregates and soil carbon
148
7.3.3. Relationship of infiltration index to soil attributes and field infiltration
150
7.3.4. Relationship of nutrient cycling index to soil attributes including soil respiration
153
7.3.5. Effect of sampling depth on relationships of calculated indices to soil parameters
155
7.3.6. General discussion 157 Chapter 8. Summary, limitations and contributions of this study 1618.1. Main research findings 161 8.1.1. Jarrahdale site 162 8.1.2. Scotia site 163 8.1.3. Kelian site 164 8.1.4. Comparisons between study sites 1658.2. Limitations of this study and suggestions for future work 1658.3. Contribution of the present study 166 References 169
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LIST OF TABLES
Table Title Page
2.1 Parent materials of soils on the Jarrahdale railway cutting shelf. 21
2.2 The occurrence (m2) of micro-geomorphic units for individual plots at the Jarrahdale railway cutting shelf with the relative area (% plot size) shown in brackets. D/E indicates coincident depositional and erosional surfaces.
27
2.3 Soil processes and related indicators of soil surface horizon development at the Jarrahdale railway cutting shelf.
29
2.4 Plant species occurrence (++dominant species, + present, − absent) on the Jarrahdale cutting shelf. Annual species are common during winter and spring. Species identification is courtesy of Dr John Koch (ALCOA).
31
2.5 Equations for predicting biomass of several species obtained from previous work in the region. All fit a power function (or natural log-transformed function) incorporating plant attributes. The abbreviations are as follows: DW, dry weight (kg); FW, fresh weight (kg); bbh, basal area at breast height (cm2); dgl, diameter at ground level (cm); dbh, diameter at breast height (cm).
33
2.6 Element concentrations (single measurement of bulk composite sample) of different parts of the major plant species at the Jarrahdale cutting shelf (60 °C basis).
39
2.7 Element concentrations of litter samples. 403.1 Particle size distribution of < 2 mm fraction (mean± standard deviation)
and gravel content of the Jarrahdale shelf and jarrah forest soils. Number of soils used for measuring gravel content are shown in parenthesis.
50
3.2 Bulk density, saturated hydraulic conductivity (Ksat), water-stable aggregate size (MWD, mean-weight diameter), and macro-aggregate (> 0.250 mm) representing the shelf and jarrah forest soils.
53
3.3 Parameters derived from the single field measurement of unsaturated hydraulic conductivity (Kunsat) at –30 mm tension for the Jarrahdale shelf plots (P3-P7) and for jarrah forest soils, and bulk density.
54
3.4 The pHw and EC (1:5) of the Jarrahdale shelf and the jarrah forest soils. For individual soil horizons, mean values followed by the same letters are not significantly different (p > 0.05).
56
3.5 Total carbon and total nitrogen (mean ± standard deviation) of surface and subsurface soils of the Jarrahdale shelf cutting and native jarrah forest.
58
3.6 Sodium bicarbonate-extractable phosphorus (mg/kg) for the shelf and jarrah forest soil samples.
60
3.7 Bicarbonate-extractable potassium (mg/kg) for shelf and jarrah forest soils.
62
3.8 Exchangeable cations, CEC and base saturation (BS) for surface and subsurface soils from shelf and jarrah forest sites.
64
3.9 Latent vectors of the principal component analysis for shelf and forest soil samples from the Jarrahdale sites.
72
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Table Title Page
4.1 Soil surface features used for the assessment of soil surface condition in Landscape Function Analysis and landscape indices derived from these features (Tongway and Hindley, 1995).
82
4.2 Landscape parameters in a horizontal direction. 884.3 Mean values of soil surface zones identified for the horizontal transect. 894.4 Landscape parameters and land surface zones on down-slope transects
on the shelf compared with jarrah forest at Jarrahdale sites. 92
4.5 LFA indices for Jarrahdale shelf and mine sites in Australia. 945.1 Summary of landscape properties and major zones for each transect
(SW waste dump; NW native woodland). Abbreviations: BSR, bare soil surface with significant amounts of rock fragments; SLC, soil-log complex. Obstruction index is the total length of obstruction (sink) divided by transect length and indicates the proportion of sink and the potential retention of resources.
106
5.2 Site information and values of LFA indices (%) for the Scotia waste dump and analogue sites.
107
5.3 Soil physical properties of topsoils from the Scotia waste dump and native forest (mean ± standard deviation). The difference between mean values for waste dump and woodland topsoil is significant if the probability (p-value) is less than 0.05.
108
5.4 Mean value (± standard deviation) of textural and chemical properties of soils from the Scotia waste dump (n=25) and native woodland soils (n=12 for each depth).
109
5.5 Six principal components (PC) for Scotia soils samples having a latent root larger than unity.
112
5.6 Element concentrations of plant and litter samples from Scotia waste dump and native woodland sites.
117
6.1 Site information, particle size distribution, bulk density (BD) and mean-weight diameter (MWD) for rehabilitated mine sites and analogue forest soils at Kelian, East Kalimantan. Summary of ANOVA is included (ns, not significant; * and ** significant at 5 % and 1 % probability respectively).
132
6.2 Site and sampling information, mean values and standard deviation of chemical properties for rehabilitated mine sites and analogue (forest) soils at Kelian. Bic-P and Bic-K, bicarbonate-extractable P and K. Summary of ANOVA is presented (ns, not significant; * and ** significant at 5 % and 1 % probability).
137
8.1 Soil respiration values representing a wide range of ecosystems from around the world.
164
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LIST OF FIGURES
Figure Title Page
2.1 a) Locality map of the Jarrahdale railway cutting near Darling Scarp, Western Australia (Sadleir and Gilkes, 1976) and b) schematic diagram of laterite profile (McArthur, 1991).
14
2.2 Average monthly rainfall and evaporation (1963-2001) from a nearby climate station at Karnet (32º26´S, 116º04´E, altitude 286 m above sea level) (Bureau of Meteorology).
14
2.3 Aerial view of the Jarrahdale railway cutting (left) at the early phase of mine operation in 1969 and (right) in 1990 (Source: ALCOA World Alumina).
15
2.4 Cross-sectional view of the railway cutting (not to scale). 152.5 Geology of the Jarrahdale railway cutting, Western Australia (modified
from Sadleir and Gilkes, 1976) showing parent materials and locations of sampling plots in this study (P1-P7).
16
2.6 General view of sampling plots at the Jarrahdale shelf (P1-P7), and the adjacent jarrah forest (BP).
17
2.7 General front view of underlying materials (lower slope) below several sampling plots. Pallid-mottled zone (PMZ) materials are prevalent at the location of plots P1, P4 and P7. Granitoid rocks are exposed at plot P5. See Table 2.1 for more information.
22
2.8 Micro-geomorphic units of the pallid mottled zone (PMZ) plots. Depositional surfaces are distinguished by the deposited materials (i.e. sand, gravel, litter). Depositional/erosional surface indicates a simultaneous occurrence of the two processes.
24
2.9 Micro-geomorphic units of the granite/saprolite plots. Erosional surface is particularly prominent at plot P6 due to the gentle slope.
25
2.10 Equations for predicting the biomass of dominant plant species colonizing the Jarrahdale cutting shelf derived from the present study.
33
2.11 Standing biomass in gram/unit area (25cm x 25 cm = 0.062 m2) for several plots. Large contributions are due to sedge (P1), shrubs (P3) or banksia (P4). Points indicate locations of plants used for determination of biomass estimation, except for Plot 4 showing Banksia.
34
2.12 Litter cover area as a percentage of the unit area (25 cm x 25 cm = 0.062 m2) for pallid-mottled zone (PMZ) plots.
35
2.13 Litter cover area as a percentage of the unit area (25 cm x 25 cm = 0.062 m2) for granite/ saprolite plots.
36
2.14 Litter weight increases with percentage surface cover for a mixed sample from plots P1, P2 and P3.
37
2.15 Bivariate plots for nitrogen, phosphorus, potassium and calcium concentrations of equivalent plant materials from plants growing on the cutting shelf and adjacent jarrah forest. Lines indicate 1:1 slope.
41
2.16 Litter versus biomass nutrient concentrations. Lines indicate 1:1 slope. 422.17 Concentrations of aluminium (Al) of litter samples are closely and
linearly related to silica (Si). 43
2.18 Relationship between C/N value and total N for various parts of plant species and litter.
43
x
Figure Title Page
3.1 Frequency distribution of gravel contents for the Jarrahdale shelf and jarrah forest soils.
49
3.2 Different forms of gravel. Rock fragments on plot P2 (left) and lateritic gravel on plot P3 (right).
50
3.3 Ternary diagram of texture for the fine earth (< 2 mm) of soils from the Jarrahdale cutting site (shelf and jarrah forest) and data from McCrea et al. (1990) representing dolerite pallid zone (DPZ) and granite pallid zone (GPZ). For this presentation, the sand fraction is 0.02-2 mm, silt 0.002-0.02 mm and clay < 0.002 mm.
51
3.4 Silt to clay ratio for the Jarrahdale cutting soil samples. 523.5 Relative changes (delta = surface value minus subsurface value) of sand
and clay for the Jarrahdale shelf soils. 52
3.6 Bivariate plot of saturated hydraulic conductivity (Ksat) versus bulk density for the Jarrahdale shelf and jarrah forest soils.
54
3.7 Bivariate plots of surface versus subsurface values for soil pH and EC values for the Jarrahdale shelf soils and jarrah forest soils.
57
3.8 Bivariate plots for surface and subsurface concentrations of total carbon and total nitrogen of Jarrahdale shelf and jarrah forest soils.
58
3.9 a) Log total nitrogen is linearly related to log total carbon for all of the shelf and the jarrah forest soils, b) C/N values tend to increase with total soil carbon.
59
3.10 Litter accumulation consisting mostly of jarrah leaves on plot P7 (left) and litter from a mixed population of marri and jarrah near plot P4 (right).
60
3.11 Bivariate plot of bicarbonate-P concentrations in surface and subsurface layers of Jarrahdale shelf and jarrah forest soils.
61
3.12 Bivariate plot of values for log bic-P (mg/kg) versus log total carbon (g/kg) of pallid-mottled zone (PMZ), granitic saprolite, and jarrah forest soils.
61
3.13 Bivariate plot of surface versus subsurface values for bicarbonate-extractable potassium for the Jarrahdale shelf and jarrah forest soils.
63
3.14 Bivariate plots for exchangeable potassium versus NaHCO3-extractable potassium for surface soils (left) and for subsurface soils (right). Lines indicate 1:1 slope.
63
3.15 Exchangeable cations, CEC and base saturation (BS) for surface and subsurface soils from shelf and jarrah forest sites.
65
3.16 Bivariate plot for base saturation and soil pH for shelf and jarrah forest soils.
66
3.17 Scatter diagrams for exchangeable cations versus clay content for subsets of soils on pallid-mottled zone (left) and granite (right). Lines are fitted for P4 and P7 data.
67
3.18 Scatter diagrams for exchangeable cations versus soil carbon content for subsets of soils on pallid-mottled zone (left) where the data are log-transformed and granite saprolite (right). Regression lines for plot P7 data.
68
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Figure Title Page
3.19 Cation exchange capacity is not simply related to clay concentration of soils on PMZ and granite plots (left), and tends to increase with total soil carbon concentration (right) excluding samples with CEC < 1 cmol/kg and total carbon < 1 g/kg. Relationships for data for southwestern Australia soils are also shown (McArthur, 1991).
69
3.20 CEC versus total soil carbon for surface soil samples, there is no evident relationship.
70
3.21 Scores for the first and second PCA dimensions for the Jarrahdale soil samples grouped into PMZ, granite and jarrah forest soils.
72
3.22 XRD patterns of basally oriented clay fraction of Jarrahdale samples. The symbols are as follows: K, kaolin; V, vermiculite; I, illite (mica); G, gibbsite; B, boehmite; Go, goethite; H, hematite; Q, quartz. Clay-size quartz may be present but the peaks are masked by the peaks from the supporting ceramic plates.
74
3.23 Ternary diagram of clay fraction mineralogical composition normalized to 100 % for the five minerals indicated on the axes for Jarrahdale samples. Amounts of iron oxides, quartz, anatase, etc were mostly relatively minor and have been omitted.
75
4.1 An example of LFA transect observation showing a sink-source pattern (Tongway and Hindley, 2000).
81
4.2 Transect layout in a horizontal direction along the bench showing vegetation and soil patches, and locations of sampling plots used for describing lateritic regolith properties.
87
4.3 View of the plots for vertical transect observation across slope and shelf surface.
87
4.4 The values of stability, infiltration and nutrient cycling (NCI) indices for 50-m intervals of the shelf compared with values for the jarrah forest.
90
4.5 Diagram of vertical transects parallel to steep slopes and across nearly flat surface of the cutting shelf.
91
4.6 LFA indices down-slope across three plots compared with indices for jarrah forest.
93
4.7 Bivariate plot for LFA infiltration index and values of unsaturated hydraulic conductivity (steady-state flow rate) for Jarrahdale soils.
95
5.1 Site map of Scotia waste dump showing transect lines crossing the main drainage.
100
5.2 Geological map of Scotia waste dump showing the location access road to the site (from McGoldrick, 1993).
101
5.3 Monthly rainfall, temperatures and evaporation representing Norseman station (Bureau of Meteorology; Luke et al., 1988).
102
5.4 General view of the Scotia waste dump and adjacent woodland showing (rocky) drainage structure, soil surface and plant growth conditions.
103
5.5 Relationships between nutrient cycling index (NCI) and both organic carbon and total nitrogen for the Scotia topsoils.
110
5.6 For all waste dump and woodland soils, organic carbon is significantly (linearly) related to total nitrogen, exchangeable calcium and CEC, but not to bic-P.
111
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Figure Title Page
5.7 Soil pH (left) and EC (right) are weakly (positively) related to exchangeable sodium. Highly saline conditions occur for a few samples at the waste dump (right) and data points these very saline samples do not conform to the linear relationship.
111
5.8 Plots of loading scores the first two dimensions of the principal component analysis.
113
5.9 Canonical variate analysis for Scotia soils. 1145.10 Graphics presenting a function of mean distance (i.e. average distance
to four nearest plants) along PCQ transect on waste dump (top and middle) and from native forest/woodland (lower graphs). The horizontal line shows the overall mean distance for individual transects. These plots imply some banding may be present.
115
6.1 Geographical location of the Kelian mine in East Kalimantan (Simmons and Browne, 1990).
127
6.2 Pictures showing a general view of native (analogue) forest and rehabilitated mine sites at Kelian.
128
6.3 Ternary diagram of soil texture for native forest and rehabilitated mine sites at Kelian comprising all sampling depth. Ellipse shows the clouds of data for individual sites (two for the 7-year sites).
131
6.4 Bivariate plot for values of mean-weight diameter (MWD) versus clay content for three sampling depths for Kelian soils.
133
6.5 Bivariate plot for values of bulk density versus clay content for three sampling depths for Kelian soils.
133
6.6 Mean values of total soil carbon for various micro-topographic zones for rehabilitated mine sites and forest soils.
135
6.7 Mean values of total nitrogen and mineralizable nitrogen for various micro-topographic zones for rehabilitated mine site and forest soils.
136
6.8 Total nitrogen is strongly related to total carbon for Kelian soils. 1386.9 Potentially mineralizable N (PMN) is linearly related to total N for
Kelian soils. 138
6.10 Bivariate plots showing values for bicarbonate extractable-P (left) and bicarbonate extractable-K (right) in relation to soil total carbon for Kelian soils.
139
7.1 Soil respiration gear consisting of Perspex lid, ring and petri dish containing 20 ml of 0.5 M KOH (left) and when the apparatus is fully installed and secured (right) (photos by David Tongway).
146
7.2 The apparatus for measuring field infiltration (photos by David Tongway).
146
7.3 Mean values of LFA indices for rehabilitated mine sites and analogue site in Kelian (Indonesia).
148
7.4 LFA stability index versus values of mean-weight diameter (MWD) of soil aggregates obtained by wet sieving for the 0-1 cm and 1-3 cm depth. Regression lines are fitted to data for 1-year, 7 year and analogue sites.
149
7.5 Bivariate plots for stability index versus total soil carbon for the 0-1 cm and 1-3 cm soil layers.
149
7.6 Relationships between infiltration index and bulk density for different soil depths.
151
7.7 Infiltration index versus clay content for 0-1 cm and 1-3 cm soil depths. 151
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Figure Title Page
7.8 Infiltration index versus total carbon for 0-1 cm and 1-3 cm soil depths. 1527.9 Bivariate plot for LFA infiltration index versus field infiltration rate for
Kelian soils. 152
7.10 Nutrient cycling index (NCI) is not simply related to potentially mineralizable nitrogen (PMN) for 0-1 cm and 1-3 cm soil depths.
153
7.11 Nutrient cycling index (NCI) is logarithmically related to total soil carbon for 0-1 and 1-3 cm soil depths.
154
7.12 Bivariate plot for nutrient cycling index (NCI) versus soil respiration for all samples of Kelian soils (left) and the plot for mean values for micro-topographic zones (right).
155
7.13 Nutrient cycling index (NCI) versus potentially mineralizable nitrogen (PMN) (left) and total carbon (right) calculated for 0-3, 0-5 and 0-10 cm depths. Bulk density for the 5-10 depth was assumed to be the same as for the 3-5 cm depth.
156
8.1 A flowchart showing the inter-connectivity between land degradation, site rehabilitation, indices of soil development and monitoring of progress towards sustainability.
161
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LIST OF APPENDICES
Appendix Title Page
1 Site information, physical and chemical properties of Jarrahdale soil samples. Notes: Csilt (coarse silt, 0.02-0.05 mm), Fsilt (fine silt, 0.002-0.02 mm), bic-P (bicarbonate-extractable P), bic-K (bicarbonate-extractable K), BSP (base saturation percentage) are consistently used in the following appendices.
183
2 Site information, physical and chemical properties of Scotia soil samples. Notes: SW, waste dump soils; woodland soils (BS bare soil, EUC eucalypt, SLC Melaleuca, and ATR Atriplex); FC, field capacity; PWP, permanent wilting point; AW, available water.
189
3 Site information, landscape indices (STA stability, INF infiltration, NCI nutrient cycling index) and properties of Kelian soil samples.
193
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ACKNOWLEDGMENT
I would like to thank my supervisors Professor R.J. Gilkes and Associate
Professor David Jasper who have put much time, effort and patience into supervising
my study and shared constructive ideas and criticisms during thesis writing.
A scholarship from Australian Agency for International Development (AusAID)
that enabled me to undertake PhD studies is gratefully acknowledged as is the assistance
of its staff in particular Mr. Keith Chambers and Mrs Rhonda Haskell. Funding was
also provided by Central Norseman Gold Corporation (CNGC) and valuable assistance
by Ms Roberta Sellecks for a fieldwork at Scotia goldmine waste dump. ACMER
Project 31 Stage 2 (verification of indicators and transfer of monitoring technology) and
staff at PT Kelian Equatorial Mining (KEM) assisted fieldwork at Kelian (East
Kalimantan).
I am also grateful to the Government of Indonesia, Rector Sriwijaya University,
Dean Faculty of Agriculture and Head Department of Soil Science of the Sriwijaya
University for granting me leave to pursue this degree.
My special thanks are extended to Mr David Tongway and Mr Norman Hindley
from CSIRO Sustainable Ecosystems in Canberra for teaching me the basis of
Landscape Function Analysis which was used widely in this study, and to Dr John Koch
from ALCOA for access to resources and plant species identification. I am indebted to
members of SEGS, The University of Western Australia for their technical and
administrative assistance, in particular to Michael Smirk for training on various
instruments for analytical work, Guy Boggs, Adam Pratt and Faron Mengler for
ArcView GIS tutorials, Garry Cass and Liz Halladin from the Faculty Student Lab,
Barbara Millar, Janet King, Susie Cass and Vicki Wallis from the SEGS office.
Finally, I wish to thank my wife, Herlina Hanum and our children Chairunnisa
Rizkiah, Muhammad Yusuf Herwansyah and Jasmine Ausssie Azzahra who have
endured this hard time with patience, understanding, constant support and prayer.
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GLOSSARY OF TERMS
AW : available water (i.e. FC-PWP)
Bic-P : sodium bicarbonate-extractable phosphorus
Bic-K : sodium bicarbonate-extractable potassium
CEC : cation exchange capacity
CVA : canonical variate analysis
EC : electrical conductivity
EFA : Ecosystem Function Analysis
ESP : exchangeable sodium percentage
FC : field capacity (i.e. water retention at –10 kPa)
LFA : Landscape Function Analysis
Mottled zone : reddish yellow spots within the soil profile due to precipitation of Fe3+
compounds
MWD : mean-weight diameter
NCI : nutrient cycling index
OC : organic carbon
Pallid zone : soil horizon characterised by white to greyish colour and abundant in
kaolinite
PCA : principal component analysis
Pixel : unit area (i.e. 25cm x 25cm) used in spatial analysis involving micro-
scale mapping
PMN : potentially mineralizable nitrogen
PMZ : pallid-mottled zone (see above)
Plot : sampling area for micro-scale mapping
PWP : permanent wilting point (i.e. water retention at –1500 kPa)
TC : total soil carbon
TN : total nitrogen
WSA : water stable aggregate
XRD : X-ray diffractometer
XRF : X-ray fluorescence
1
CHAPTER 1. INTRODUCTION
1.1. Research background
Disturbance to ecosystems may occur in any place around the world as a result of
various activities or events, some of them are unavoidable such as a natural disaster.
Site disturbance can be caused by natural causes including landslides (Zarin and
Johnson, 1995; Mather et al., 2002) and volcanic eruptions (Thornton et al., 2002), or
by impacts of human activities including mining operations (Ward, 2000) and site
clearing (Ludwig et al., 1997), and over-grazing by native animals and stock (Tongway
and Ludwig, 1996). These disturbances may lead to land degradation when impacts of
the disturbance exceed inherent capacity of the disturbed landscape to recovery.
Nevertheless, the disturbance itself might be considered as the time-zero of rejuvenation
process for disturbed lands with the extent of site development depending upon many
factors, such as. climatic regime and soil conditions.
Site disturbance often causes major changes in soil properties and productive
potential conditions. Problems of disturbed lands are generally related to the soil
quality of affected areas which mostly declines, as is revealed by poor fertility
(McKissock and Gilkes, 1991; Rate and Sawada, 2000; Jasper, 2002), restricted plant
growth (Skousen et al., 1994; Francescato et al., 2001), or increased pollution (Johnson
et al., 1994). This study is mainly concerned with soil and plant development after
disturbance in several mine sites. The central concept of this thesis is that for disturbed
sites plant colonization and growth, soil development and reduction of offsite impacts
on the environment can occur spontaneously and that even minimal site preparation can
materially facilitate these natural processes.
1.2. Overview of key issues in the study
1.2.1. General principles of rehabilitation of degraded lands, particularly minesites
There is a need to restore disturbed sites, either naturally or by active
rehabilitation programs but the mechanisms and relative benefits of these two options
are often poorly understood. The passive approach basically removes the disturbing
influence and waits for nature to provide a remedy, whereas the active approach may
2
involve various measures of re-establishing vegetation community, arresting erosion
and ameliorating soil. These approaches have their own limitations and benefits in terms
of rate of development, expenses and ecosystem stability (Tongway and Ludwig,
2002).
In the case of mine sites, the ultimate goal of rehabilitation is to imitate the pre-
mining condition and create a new sustainable ecosystem. Increasingly stringent
requirements for rehabilitation are imposed upon miners by local or national
governments (Johnson et al., 1994; Danielson and Nixon, 2000; Sassoon, 2000).
However, sufficient resources might not be available in all cases to carry out the
optimum rehabilitation practices. Sites are sometimes left without rehabilitation due to
a lack of funding or inadequate regulation.
Natural revegetation occurs on disturbed sites. At such sites plant colonization
and growth can only take place naturally. However, the rate of spontaneous
colonization and growth is highly variable and can take many decades (Skousen et al.,
1994; Francescato et al., 2001). Colonization of disturbed and abandoned sites by
pioneer plant species varies with species, location, substrate and climate (Kamijo et al.,
2002; del Moral and Jones, 2002). Spontaneous plant growth and soil development at
disturbed sites depend partially on initial soil qualities and are strongly related to local
climate conditions. Mine sites may face problems in these respects that inhibit
achievement of a sustainable ecosystem. The quality of surface materials is a key factor
for successful mine site rehabilitation and in some instances only inferior materials are
available. Where active rehabilitation is not practical, spontaneous plant and soil
development will also depend greatly on materials exposed on the mine floor or waste
dump (Williams, 1997; Bradshaw, 1997; 2000). In essence the seedbed is simply what
is left on the site.
The available seed-bank and soil fertility are commonly minimal or poorly
distributed on disturbed sites. Patchy growth of particular plant species may also reflect
the diversity of properties of underlying materials with extreme conditions being
unsuitable for some species. Soil-plant interactions can be site-specific across a
disturbed landscape with variability operating at various scales. Pasture and native
plant species have been used for revegetation of shallow or infertile soils on coal mine
wastes (McKissock and Gilkes, 1991; Loch and Orange, 1997), whereas other native
species (e.g. Maireana brevifolia, Atriplex undulata, Phragmites australis) grow well in
very saline or alkaline/acid conditions of gold mine wastes (Osborne, 1996; Neel et al.,
3
2003). Vegetative remediation at mine sites is often considered as a basis for
landscaping, site stabilization and pollution/dust control (Johnson et al., 1994). It is
therefore essential that soil (surface material) properties are identified as
hospitable/inhospitable for plant growth and soil development on sites, where
spontaneous revegetation by local plant species is to be considered as a suitable
management option.
1.2.2. Soil development/formation processes in lateritic (Jarrahdale), saline-sodic
(Scotia) and tropical (Kelian) soil profiles
The extent and direction of soil formation from certain parent materials are often
dictated by climatic regimes and controlled by topographic and biotic factors (Buol et
al., 1989; Birkeland, 1999). Many lateritic soils in the Darling Plateau area of Western
Australia including Jarrahdale have derived from advanced in situ weathering of granite
(Mulcahy, 1960; Gilkes et al., 1973). Most of exchangeable cations have been depleted
from exchange sites which results in the low fertility status of these soils. McArthur
(1991) has done extensive work describing major soil types in the south-western
Australia. Soil development in Jarrahdale is mostly related to the formation of an iron
concretion layer (also known as duricrust) and gravelly-sandy topsoil. Intensive
weathering has produced a deep profile that may reach up to 50 m depth in which
kaolinite is the dominant clay mineral and aluminium and/or iron oxide have been
concentrated in soils (McCrea et al., 1990).
In contrast, soil development in Scotia in more recent times has experienced very
dry conditions, thus leaching of exchangeable cations may be lower compared with soils
at Jarrahdale and Kelian. Salt deposition by wind erosion is common. Many soils
exhibit saline or sodic conditions or have formed directly on salt-lake beds (McArthur,
1991).
Soil development in the wet tropical conditions of Kelian (or East Kalimantan in
general) has been associated with much higher annual rainfall in the region. Many soil
profiles have shown horizons of a mature soil in which surface soil is often
characterized by dark color of humified organic matter, and subsoil horizons indicate a
structural development and clay accumulation (Ohta and Effendi, 1992).
4
1.2.3. LFA and its underlying ecological principles, and the methods for implementing
it in the field.
There is a need to monitor the progress of ecosystem development for both
spontaneous and actively rehabilitated land. Several methods have been developed for
the assessment of post-mining landscape ecology, each with their advantages and
limitations. None is claimed to be the most comprehensive, acknowledging the
complex nature of ecosystem development (Bradshaw and Hütl, 2001). In this study,
Ecosystem Function Analysis (EFA) (Tongway and Hindley, 1995) is introduced as a
tool for landscape evaluation of disturbed (mined) land due to its simplicity and utility.
Tongway and Ludwig (1997) formalized the conceptual framework underlying the LFA
procedure, called trigger-transfer-reserve-pulse. This framework takes into account the
spatial patterning in terms of resources regulation processes. Four important points can
be suggested related to rehabilitation of disturbed lands (Tongway and Ludwig, 2002),
these are 1) advance plans for specified end land use, 2) understanding the current
functional status of degraded lands, 3) establishment of edaphic habitat, 4)
comprehensive approaches to reduce time for rehabilitation. The core module of EFA is
the assessment of soil surface conditions using Landscape Function Analysis (LFA).
The results of LFA can be used as a base line (or current status) for monitoring site
evolution and to help establish action plans for accelerated/assisted rehabilitation if
necessary.
1.3. Research aim
This research is primarily based on the idea or hypothesis that the type and rate of
spontaneous growth of local plant species and soil development at disturbed sites are
mostly determined by the surficial materials properties, local relief (topography and
micro-topography) and climate. Plant colonization is indicative of soil support and
landscape function. Lack of plant colonization also needs to be examined in the same
context and provides a threshold to look for. It is impossible to use a single soil
parameter for evaluating plant and soil development, hence an integrated approach is
required to provide an understanding of soil-landscape-plant interactions for various
surficial materials (e.g. mine floors, waste dumps, contaminated land). Therefore, the
central aim of this research is to evaluate soil characteristics and landscape indices in
5
relation to natural plant growth and soil development under different conditions and for
diverse materials.
1.4. Research approach
To achieve the research aim, fieldwork has been conducted in three locations, each
with a specific focus. The objective of studying three sites with different parent
material, soil condition and climatic regime is possibly to derive generic solutions for
disturbed land by working on diverse sites. In order of presentation, the following topics
will be addressed.
Properties of soils developed from lateritic regolith materials formed from granite
and dolerite and exposed by excavation of a railway cutting. The different materials
and soil evolution subsequent to excavation have resulted in different rates of
colonization by local plant species. Soil development will be minimal in the areas
subject to erosion and run off. Conversely, soil development may be rapid in
resource accumulation zones. Micro-relief of local landscape (at cm-m scales) may
control the distribution and nature of zones and thus the loss and gain of soil
resources “within the hillslope” scale. This subproject is a micro-scale study which
explores interactions between the diverse soil parent materials and micro-topography
within a narrow landscape. The specific purpose was to establish a picture of the
relationships between micro-relief, soil properties and plant associations in a micro-
scale study where other factors such as climate are mostly constant. The research
focuses on soil and plant development on artificially exposed surfaces in a lateritic
landscape.
Natural rehabilitation of waste dumps on mines has been shown to sometimes be as
effective as induced (man-made) rehabilitation even though it may take a long time
to achieve satisfactory vegetation growth under natural conditions. For waste dumps
that comprise a closed system (i.e. plateau) such as the Scotia gold mine near
Norseman, Western Australia, plant colonization depends primarily on the properties
of soil materials used to build the waste dump, and the existence of very local sites
on the dump where soil, water, nutrients, seeds, etc accumulate. Water availability
in space and time is crucial in this very dry (arid) region. The colonization and
distribution of vegetation on a mine dump again should resemble the pre-mining
condition although the dump landform is quite discordant with local natural
6
landforms. In general, it would be economically beneficial for mining companies if
natural rehabilitation can be implemented as an acceptable practice in mining
rehabilitation as the high cost of major engineering and other works to rehabilitate
dumps can be minimized. An integrated approach using LFA and soil analysis may
provide a basis for interpreting the processes involved in the spontaneous
revegetation of mine dumps, and for predicting long-term outcomes.
Climate is an important factor affecting soil stability and plant growth. High annual
rainfall and a constant warm temperature are typical of tropical climates. Mine site
rehabilitation in the humid tropics will experience different conditions from those
operating in temperate and dry regions. The LFA procedure has been used
successfully at mine sites in Australia but its reliability as a monitoring tool for
tropical mine sites is still open to question. Fieldwork was conducted at the Kelian
Equatorial Mining in East Kalimantan, which is currently the largest gold mine
operating in Indonesia and which experiences a very wet (4000 mm per annum),
warm tropical environment and where the local native vegetation is rainforest. The
specific purpose of this sub-study was to evaluate the calculated values (landscape
function indices) against direct measurements in the field of site and soil properties
for rehabilitating land, comparing them with an unmined reference site.
1.5. Thesis outline
As the thesis relates to three discrete research locations, the thesis is written in three
parts comprising seven chapters in total, with contents as follows:
Chapter 1. Introduction
The first chapter contains research background, main hypothesis, aims of this
study, research approach and thesis outline.
Part 1. Soil development and plant growth on several regolith materials derived
from granite at Jarrahdale, Western Australia
This part contains results of fieldwork conducted on the shelf of railway cutting
near Jarrahdale, Western Australia. This site which is about 55 km south of Perth has
been mined for bauxite since 1963 when the cutting was excavated. The mining
operation was closed in 1999. The distinctive nature of this cutting is that we are able
7
to observe soil variation and vegetation growing on different substrates (these are
various types of granite and dolerite lateritic regolith). There are three chapters
addressing particular topics for the Jarrahdale site as follows:
Chapter 2. Parent material, micro-relief and plant colonization on the railway
cutting shelf near Jarrahdale bauxite mine, Western Australia
This chapter discusses results of micro-scale mapping of the shelf regarding
micro-relief, parent materials, biomass, and soil. Micro-scale mapping may be
extrapolated into larger areas using the principal of systematic soil-environment
interaction. Maps produced in this section are used to assist interpretation of soil
analyses. Biomass production is estimated by a series of predictive equations for major
plant species.
Chapter 3. Properties of lateritic regolith 36 years after exposure in the
Jarrahdale railway cutting
This chapter consists of analytical results for chemical, physical and mineralogical
properties of samples from mini plots on the shelf, and reference comparison samples
from native jarrah (Eucalytus marginata) forest adjacent to the cutting.
Chapter 4. The assessment of soil surface conditions on the Jarrahdale cutting
shelf using Landscape Function Analysis
Landscape Function Analysis (LFA) has been used to provide values of landscape
indices for the site. The LFA procedure initially records the landscape organization
from which we can evaluate the pattern of soil resource accumulation. Field
observation was carried out along a transect which was subdivided into 50-m intervals
and positioned parallel to the shelf surface (horizontal direction). The observation was
also conducted on transects established parallel to slope direction (vertical direction).
Index values of stability, infiltration and nutrient cycling are calculated from scores
representing soil surface conditions.
Part 2. Natural rehabilitation of a gold mine waste dump in an arid region of
Western Australia
8
Chapter 5. Integrating landscape indices and soil properties for assessing
spontaneous soil and ecosystem development on a waste dump at the Scotia gold
mine, Western Australia
This chapter contains results of fieldwork at the Scotia waste dump, a gold mine
site administered by the Central Norseman Gold Corporation. The dump was about 15
years of age when the study was done. Parallel field sampling of reference woodland
sites was carried out and soil samples were analysed for various chemical and physical
properties.
Part 3. Land rehabilitation and the LFA method at a gold mine in the tropical
climate of East Kalimantan
Chapter 6. Soil properties of a rehabilitated mine site at Kelian, East Kalimantan
Indonesia
This chapter will discuss analytical results for soil samples from the Kelian
Equatorial Mining (gold mine). These samples were collected from sites representing
three ages of rehabilitation and also from analogue sites (native rainforest).
Chapter 7. Landscape Function Analysis for the assessment of mine site
rehabilitation under a tropical climate
This chapter will discuss soil surface assessment conducted by LFA procedures
and direct field measurement for infiltration and soil respiration (an estimate of nutrient
cycling index). The field determined stability index is compared with laboratory
measurements of aggregate stability.
Chapter 8. Summary, limitations and contributions of this study
The final chapter provides a summary of main findings of this study which are
related to the nature and limitations of spontaneous soil development and vegetation
growth, and the merit of using LFA as an approach to understanding land/plant
resources and functions for a disturbed landscape.
9
Part 1. Soil development and plant growth on several regolith
materials derived from granite at Jarrahdale, Western Australia
The first part of thesis presents results of fieldwork undertaken on a railway
cutting shelf at Jarrahdale, Western Australia. The surrounding area was formerly a
bauxite mine operated by ALCOA World Alumina which was opened in 1963 and
decommissioned in 1999. The railway cutting exposes a deep profile of regolith formed
by in situ lateritic weathering of mostly granitoid rocks. Following the excavation with
no initial or subsequent site treatments, a new niche was established to host plant
colonization and soil development. Consequently plant colonization and soil formation
has occurred spontaneously under natural conditions and reflects variations and
contributions by local micro-relief, fringing vegetation and parent materials. Thus the
focus of this research is to compare spontaneous formation of soils and colonization by
vegetation on diverse regolith materials exposed on a near-horizontal bench cut into the
wall of a deep railway cutting approximately 36 years before this study was undertaken.
The following three chapters discuss the results of Jarrahdale fieldwork particularly the
relationship between parent material, micro-landform and plant growth on the shelf
(Chapter 2), properties of soils on the shelf (Chapter 3), and the use of landscape
function analysis to assess soil surface conditions (Chapter 4).
10
Chapter 2. Parent material, micro-relief and plant colonization on the
railway cutting shelf near Jarrahdale bauxite mine, Western Australia
2.1. Introduction
Soil formation is a complex process involving several factors including parent
material, relief (landform), climate and hydrology, vegetation and fauna within a period
of time (Jenny, 1941; Tille et al., 1998). One or two factors may be dominant in the
early phase of soil development and others are more significant in the next stage. There
is an inter-dependence between these factors so that it is common, for example, to have
different soils derived from similar parent materials under different climate conditions,
topography or vegetation (Buol et al., 1989).
Soil development occurs naturally or as an assisted rejuvenation process after land
disturbance (Bradshaw, 2000). The degree of land and vegetation disturbance varies
from little damage with some surviving species (secondary succession) to complete
destruction of soil profiles and few if any biological remnants (primary succession)
(McCook, 1994; Grishin et al., 1996). The construction in 1963 of a railway track at the
ALCOA Jarrahdale bauxite mine (Western Australia) exposed a deep lateritic
weathering profile on a cutting through Rhodes Ridge. Regolith has formed mainly
from complex granitoid basement rocks with several dolerite intrusions and minor aplite
and quartz veins. The geology of these rocks has been investigated by several workers
(Johnstone et al., 1973; Sadleir and Gilkes, 1976). This cutting provides an excellent
site for regolith studies and there are several theses (Sadleir, 1974; Suddhiprakarn,
1978; Anand, 1984; McCrea, 1987) and many publications dealing with the nature and
origin of regolith at this site, including micro-morphology and mineralogical aspect of
parent materials and weathering products (e.g. Sadleir and Gilkes, 1976; Gilkes and
Suddhiprakarn, 1979; Anand et al. 1985, McCrea et al. 1990). However, little or no
research has been conducted on these materials in relation to plant colonization and
growth and soil development.
The cutting also provides an excellent site for investigating spontaneous
restoration more than three decades after excavation as considerable soil and plant
development has occurred. The present parent materials and soils are very different
from the original soils. Newly exposed substrates have undergone several processes
11
including humus addition, erosion and deposition that have resulted in various soil
conditions for supporting plant growth.
A patchy growth of colonizing species commonly occurs at disturbed sites.
Diverse properties of parent materials (types, composition, depth), soil nutrient status,
and viable seed may create (uneven) patches or niches for plant growth (Ludwig and
Tongway, 1996; Berendse et al., 1998; Paniagua et al., 1999; Jim, 2001). Plant
colonization at the beginning of vegetation development often occurs slowly until a
homogenous, sustainable plant community is achieved (Odland and del Moral, 2002).
Soil resource movement is broadly controlled by local landscape topography and
partly by micro-relief. In general soil particles and litter are more easily mobilized from
a steep slope. Soil resources may accumulate on flat or gentle slopes and in depressions
(Tongway and Ludwig, 1996; Todd et al., 2000b; Kapolka and Dollhopf, 2001). The
railway cutting at Jarrahdale comprises steep slopes (~35°) at the upper and lower parts,
and a nearly flat bench between the sloping elements. The bench is an engineering
device to control the stability of the cutting. Transportation of soil materials and litter
along and across the shelf is affected by micro-relief and biophysical entrapment.
Resource interception by various means (e.g. grass clump, stem, rock fragment) creates
a source-sink structure that provides primary sites for colonization by local plant
species.
Soil properties (e.g. organic carbon, nitrogen and phosphorus concentrations) may
vary over short distances (Webster, 1985; Jackson and Caldwell, 1993; Todd et al.,
2000b). To quantify this variation, micro-scale mapping has a practical value for
relating micro-topography, parent material, biomass and litter distribution. The
information obtained by this procedure may be extended to larger locations to explore
soil-plant relationships at a landscape scale.
The objective of this study is to assess soil morphology and plant colonization
after land disturbance. It examines parent materials and micro-relief in relation to the
growth of native plant species that have colonized the railway cutting shelf, including
biomass contribution and litter distribution on the shelf. It is expected that the results
can be utilized as a basis for understanding and studying other types of land disturbance
in the region.
12
2.2. Materials and Methods
2.2.1. Study sites
The Jarrahdale railway cutting is about 55 km south of Perth, Western Australia
(32º17´S, 116º05´E) near the margin of the Darling Range (Figure 2.1a). The study was
focused on the southern side of the cutting, and a reference site from the adjacent jarrah
forest was included for comparison. Annual rainfall in the Darling Range region ranges
from 900-1300 mm, and annual evaporation is about 1500 mm. There is a surplus of
water from May to September and a deficit occurs during November to March (Figure
2.2). Mean daily maximum temperatures are nearly 30 ºC in summer and 15 ºC in
winter; the minimum temperature ranges from 12 ºC in summer to 6 ºC in winter. Soils
have developed primarily from various granitoid rocks and meta-quartz dolerite to
generate a lateritic soil-landscape system (Gilkes et al., 1973, Sadleir and Gilkes, 1976).
Sandy topsoils with shallow laterite (duricrust) or mottled zone are typical in the region.
Clayey topsoils only occur in a small area but clayey deep subsoils are dominant (Figure
2.1b). The landscape changes to the Swan Coastal Plain system to the west of the
Darling Fault Scarp, and is characterized by alluvium and deep-sandy soils of coastal
dune origin (McArthur, 1991).
At Jarrahdale the railway cuts through laterite profiles on Rhodes Ridge which is a
major structural feature, and exposes a series of lateritic deep weathering profiles
mostly developed from granite with dolerite intrusions (dykes) being parent materials at
some parts of the cutting (Sadleir and Gilkes, 1976). Granitoid rocks are exposed at
various depths in the railway cutting where the weathering zone-rock interface can be
observed but at many positions weathering extends below the base of the cutting.
Aerial photos show a patchy white (bare pallid zone) area around the cutting and other
open spaces including roads and pits (Figure 2.3). Mined locations adjacent to the
cutting were rehabilitated several years before decommissioning of the Jarrahdale mine
and railway in 1999.
Landform elements of the railway cutting are crest (jarrah forest), (simple) upper
slope, flat surface (shelf), depression, ridge (embankment) and (simple) lower slope
(Figure 2.4) following the classification of McDonald et al. (1990). A berm on the edge
of the cutting is designed to capture eroding surface materials to prevent their transport
onto the upper slope. Lateral (horizontal) flow of surface water may remove material
13
from the shelf and deposit it onto the lower slope although a small berm (ridge) at the
edge of the shelf partly protects the lower slope.
Figure 2.1. a) Locality map of the Jarrahdale railway cutting near Darling Scarp, Western Australia (Sadleir and Gilkes, 1976) and b) schematic diagram of laterite profile (McArthur, 1991).
Figure 2.2. Average monthly rainfall and evaporation (1963-2001) from a nearby climate station at Karnet (32º26´S, 116º04´E, altitude 286 m above sea level) (Bureau of Meteorology).
0
50
100
150
200
250
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Mea
n m
onth
ly ra
infa
ll (m
m)
0
50
100
150
200
250
Mea
n m
onth
ly e
vapo
ratio
n (m
m)
rainfall
evaporation
a) b)
14
Figure 2.3. Aerial view of the Jarrahdale railway cutting (left) at the early phase of mine operation in 1969 and (right) in 1990 (Source: ALCOA World Alumina).
Figure 2.4. Cross-sectional view of the railway cutting (not to scale).
2.2.2. Sampling plots
To investigate soil development after disturbance on various regolith materials,
seven observation plots were located on the cutting shelf for mapping of micro-
geomorphic unit, litter distribution and standing biomass. Fieldwork was initially
conducted to obtain information regarding soil surface condition and substrate variation
along the cutting shelf. These plots were delineated simply following the local variation
in surface micro relief and resource accumulation pattern which takes roughly a
rectangular shape. Plot size ranges from 12 to 40 m2 depending upon the shelf width
(1.5 to 4 m). The shelf is nearly flat with only gentle slopes. Plot boundaries were
marked by galvanized nails and nylon string.
Jarrah forest Berm
Upper slope
ShelfRidge (berm)
Lower slope
Base of cutting
Run-offErosion
Flow direction on shelf
Slopes mostly ~35-40°.Almost vertical (cliff) at granite exposure in cutting.Ridges (berms) vary in size.
15
The plots were established to represent different parts of the shelf colonized by
low shrubs (Leucopon nutans and Hypocalymma angustifolium) (i.e. plots P1 and P3)
growing on pallid-mottled zone (PMZ); by Banksia grandis (P4) on loamy-clayey pallid
zone; Dryandra sessilis (plots P5 and P6) on weathered granite and saprolite; and mixed
sedge (P7) on PMZ, and plot P2 (on granite) represents minimum colonization by moss
and lichen (Figure 2.5) with the general view of these sampling plots shown in Figure
2.6. Notes that other species, e.g. jarrah (Eucalyptus marginata), marri (Corymbia
macrophylla) and sheoak (Allocasuarina fraseriana) also colonize the shelf. In addition
to the micro-scale mapping, soil samples were collected for analysis of basic properties.
Soil properties of regolith materials are discussed in Chapter 3.
Figure 2.5. Geology of the Jarrahdale railway cutting, Western Australia (modified from Sadleir and Gilkes, 1976) showing parent material and location of sampling plots in this study (P1-P7).
Plant communities in the region are dominated by jarrah interstratified with marri.
Small-tree component consists of bull banksia (Banksia grandis), sheoak, snottygobbles
(Persoonia longifolia), and woody pear (Xylomelum occidentale). The understorey
comprises many shrubs species up to 3 m height mainly from families Myrtaceae,
Proteaceae, Leguminosae, and Epacridaceae (Koch, 1987). Adjacent mined areas had
been ripped and contoured then rehabilitated with hand planted seedlings of eucalypts
(E. resinifera, E. wandoo) and some experimental plots of hand planted pinus species
(P. pinaster, P. halepensis). Most areas had also been seeded with a mixture of legume
16
species as groundcover and understorey vegetation. However, plant colonization at the
shelf and slopes has occurred under natural conditions with no site preparation, seeding
or fertilization.
Figure 2.6. General view of sampling plots at the Jarrahdale shelf (P1-P7), and the adjacent jarrah forest (BP).
17
2.2.3. Micro-scale mapping
Micro-scale maps were produced by drawing sketches (1:25 scale) on a graph pad.
The sketches comprise maps of micro-geomorphic units and record erosional and
depositional surfaces, ridge/embankment, rock outcrops; maps of litter distribution, and
locations of major plant species for estimation of standing biomass. Parent materials
(i.e. substrates on which plants develop) were presented as a simplified cross-sectional
diagram. The field observations used for making sketch maps were guided by pilot
points marked on a metal frame (1m x 1m).
Micro-geomorphic maps were transferred into a digitized form using ArcView
GIS software (version 3.1). Litter cover and standing biomass were reproduced as
raster maps based on a 25cm x 25cm pixel using the spatial analysis extension of the
ArcView GIS software. Litter cover is categorized into five classes for this mapping
purpose (nil, <25, 25-50, 50-75 and >75% cover of the pixel). Standing biomass was
interpolated using an IDW (inverse distance weighted) option to create a map based on
class intervals.
2.2.4. Biomass prediction
Total standing biomass of shrubs and woody species can be estimated by
regression relationships with other simply measured plant attributes. Stem diameter at
breast height (dbh) is the common explanatory parameter for trees (Ward and
Pickersgill, 1985; Koch, 1987; Ketterings et al., 2001; Rayachhetry et al., 2001).
Weight of plant samples (aboveground part) is usually obtained from a destructive
sampling, in which tree is cut down, segmented, oven-dried and weighed. Another
method is the estimation of total biomass using allometric regression (generalized
equation) which is developed initially from the destructive procedure, and then the
models are expanded through use of several best-fit models for other areas. This
allometric approach has advantages in reducing the number of plant samples and time
required and is very useful for plants that grow under similar conditions, especially
large-scale commercial plantations, for estimating timber production (Verwijst and
Telenius, 1999; Nelson et al., 1999; Zianis and Mencuccini, 2004).
Standing biomass was calculated from measurements using several equations
available for specific plant species found on the cutting shelf. Representatives of a few
18
plant species were sampled for biomass estimation. Total biomass was estimated by
measuring stem diameter at the ground level (dgl) and plant height of Dryandra sessilis.
For low shrubs, total biomass was estimated from the height (Hypocalymma) and
canopy size (Leucopogon) respectively. For sedges, the biomass was estimated from
the clump diameter and height. To calibrate these measurements all plant samples were
collected by destructive sampling by cutting the aboveground biomass which was oven-
dried at 60 ºC for several days until the weight was constant. Dry weight was related to
the particular plant parameters measured for each species with the data generally
conforming to a power equation. For other plant species, the equations for biomass
prediction were obtained from the literature (Glossop, 1978; Ward and Pickersgill,
1985; Koch, 1987).
2.2.5. Plant and litter analyses
Nutrient uptake may indicate the response of plant species to soil fertility. Site
disturbance often decreases nutrient content, so that plant species need to adjust to the
marginal conditions by utilizing the available nutrient more efficiently. This plant
analysis is aimed to identify whether nutrient concentration differs between plant
samples collected from the cutting shelf and the jarrah forest. Total nutrient
concentration was determined for P, S, Ca, Mg, K, Na, Si, Al, Cu, Zn, Fe and Mn using
the X-ray fluorescence method (Philips PW1400) for plant materials and litter samples.
These plant and litter samples were oven-dried (60 ºC) for a few days to achieve
constant weight and finely ground. The biomass and litter samples were prepared as a
pressed-pellet using boric acid as binder (Norrish and Hutton, 1977). Total carbon and
total nitrogen were measured using a high-temperature induction furnace (LECO
CHN1000) (Nelson and Sommers, 1982; Bremner and Mulvaney, 1982).
2.3. Results and discussion
2.3.1. Parent material of the cutting shelf soils
There are three major materials from which soils on the cutting shelf have
developed, these are granitic pallid zone, granitic mottled zone and weathered granite
(saprolite), variously associated with lateritic debris including gravel (Table 2.1). The
19
sketch of the vertical section only shows the lower embankment to the base of cutting.
Please also refer to Figure 4.5 for a full vertical section of the cutting . However, no
historical information is available from published articles on how the cutting was
excavated and prepared for a railway track. Blasting and excavation were presumably
the main site preparation. The excavation removed all materials up to 10 m depth and
exposed a deep soil profile that had formed in situ over millions of years by lateritic
weathering of Archaean granitoid rocks and meta-quartz dolerite. The depth of
weathering varies up to a maximum of about 30-40 m (Sadleir and Gilkes 1976).
Granitoid boulders are exposed at two places along the railway cutting where plots P2
and P5 are located representing a relatively shallow depth of weathering as is discussed
by Sadleir and Gilkes (1976). To reduce the slope length along the cutting, a bench
(shelf) was constructed about 6 m above the cutting base and thus varies in depth (1-6
m) below the original soil surface of Rhodes Ridge. Therefore, ‘parent materials’ of the
shelf soils are basically the various subsoil horizons of the original laterite profiles.
Granitoids and meta-quartz dolerite are the major parent rocks of soils in the
region. Following the excavation, it is now possible to examine complete profiles of
soil materials above the parent rock at some positions. At other positions the excavation
has not exposed rock which drilling has located at depth of >40 m below ground
surface. Weathered granite (saprolite) is at a quite shallow depth (less than 50 cm) on
the shelf, mainly near plots P5 and P6, where massive unweathered granite occurs 2 m
below the original surface soil. Fractures in the exposed granite are evident some of
which are original and others may be due to blasting but soil formation is considered to
be minimum on the freshly exposed granitoid rocks.
Pallid zone is exposed in the central part of the cutting and extends in a SE
direction on the shelf. This zone occurs as a distinctive white horizon (10YR 7/1-8/1).
The pallid zone is rich in kaolinitic, porous clay as a result of isovolumetric chemical
weathering of primary minerals in granite (e.g. mainly feldspar) (Sadleir and Gilkes
1976; Gilkes and Suddhiprakarn, 1979; McCrea et al., 1990). The color may have
become slightly gray with reddish spots (7.5YR 6/8) after exposure.
20
Table 2.1. Parent materials of soils on the Jarrahdale railway cutting shelf.
Plots P7 P6 P5 P4 P3 P2 P1 Surface materials
Mottled zone, colluvium
Saprolite (eroded) and colluvium (lateritic gravel)
Colluvium and saprolite
Mottled (upper slope) and pallid zones
Colluvium on granitic saprolite
Debris & rock fragments
Laterite and mottled zone
Underlying materials
Mottled and pallid zone
Weathered granite (saprolite)
Fractured granite Pallid zone (deep) Saprolite and granite Granite Weathered dolerite & granite
Other features Caprock (duricrust) Quartz vein Cracks Spill way (outlet), dissected
Ant mound (part), depression
Crack/depression filled with moss
Hard surface
Simplified vertical section of parent materials (lower slope)
21
Figure 2.7. General front view of underlying materials (lower slope) below several sampling plots. Pallid-mottled zone (PMZ) materials are prevalent at the location of plots P1, P4 and P7. Granitoid rocks are exposed at plot P5. See Table 2.1 for more information.
The mottled zone usually occurs quite close to the original soil surface (< 2 m
depth) depending upon the thickness of the gravel and duricrust layers. Its presence and
depth varies across Rhodes Ridge. A mottled zone of variable depth underlain by a
pallid zone is a common feature of laterite profiles in the Western Australian landscape
(Gilkes et al., 1973; McArthur, 1991). The fabric of the mottled zone broadly
resembles that of the pallid zone but translocation of clay has occurred and much kaolin
has been replaced by gibbsite (Gilkes et al., 1973; McCrea et al, 1990; Tille et al.,
1998). Mottles are dominant and may indicate ancient movements of the groundwater
table with mobilization of iron (as Fe2+) by flow and diffusion, which is subsequently
oxidized and precipitated as Fe3+ minerals under aerobic conditions. Mottles may be
brittle (i.e. friable mottled zone) and hard (i.e. hard mottled zone). The mottle colors
range from reddish brown (5YR 4/3) to yellowish red (5YR 5/8). For practical reasons
in presenting these results these materials are collectively denoted as pallid-mottled
zone (PMZ) materials.
The subsurface horizon of the original lateritic soil is characterized by hard-
cemented gravel or massive layer (duricrust). The duricrust layer has a variable
thickness in the primary bauxite deposit and is removed as economic bauxite due to its
high gibbsite content (Ward, 2000). The lateritic gravel above the duricrust may be
unconsolidated in a sandy soil matrix. Loose gravel and sand particles from the soil
horizon may be detached and removed from the upper slope and accumulate along the
toe slope.
22
Diverse underlying substrates exposed in the cutting appear to have created a wide
range of soil conditions for plant colonization. For example, plant growth appears to be
much greater on porous PMZ materials compared to the shallow soils on granite. This
situation reflects a need for sufficient soil depth for establishment, and water/nutrient
storage and plant root function. Nevertheless, local variability in soil conditions may not
be simply associated with differences in soil depth. The slope above the shelf has been
eroded as indicated by the presence of rills and channels on the surface. This corrugated
slope surface, and also cracks in massive granite also provide niches to support plants,
as shown by the parrot bush (Dryandra), fern and jarrah seedlings in Figure 2.7 (plot
P5). This also supports the proposition that these plant species are plastic in their
edaphic needs.
2.3.2. Micro-geomorphic units
Micro-geomorphic units on the cutting shelf were broadly distinguished into
erosional surface, depositional surface, ridge (berm) and outcrop based on visual
observation (McDonald et al., 1990). Depositional/erosional surface indicates that both
deposition and erosion processes may take place at that site. The distribution of these
micro-geomorphic units is presented for pallid mottled zone (PMZ) plots (Figure 2.8)
and for granite/saprolite plots (Figure 2.9). Depositional surface occurs mostly along the
slope boundary (toe slope, south side) and extends to a mid-distance position on the
shelf and it is described by its accumulated materials (i.e. sand, gravel, litter). The
erosional surface on the other hand is mostly present near the shelf embankment (berm)
adjacent to the lower slope. This occurrence is probably associated with the lateral
surface flow that is partly confined by the embankment (berm). The berm may be a soil-
gravel fragment mixture, which is distinguished from a berm which is a rock outcrop.
The occurrence of these micro-geomorphic/depositional units varied within and
across sampling plots (Table 2.2). Depositional surfaces occupy larger areas as do
erosional surfaces for both PMZ and granite plots, which indicates that these two
processes will strongly determine soil surface conditions. There is no distinct pattern of
micro-geomorphic units associated with features of the underlying parent materials.
Variation in micro-geomorphic units on the shelf are mostly related to local micro-relief
and location on the shelf.
23
Figure 2.8. Micro-geomorphic units of the pallid mottled zone (PMZ) plots. Depositional surfaces are distinguished by the deposited materials (i.e. sand, gravel, litter). Depositional/erosional surface indicates a simultaneous occurrence of the two processes.
24
Figure 2.9. Micro-geomorphic units of the granite/saprolite plots. Erosional surface is particularly prominent at plot P6 due to the gentle slope.
25
Table 2.2. The occurrence (m2) of micro-geomorphic units for individual plots at the Jarrahdale railway cutting shelf with the relative area (% plot size) shown in brackets. D/E indicates coincident depositional and erosional surfaces.
Plots Depositional surface
Erosional surface
D/E Berm Outcrop Total (m2)
P1 16.1 (90) 1.6 (9) 0.3 (1) 18
P2 4.8 (16) 2.5 (8) 8.3 (28) 3.5 (12) 10.9 (36) 30
P3 11.0 (69) 5.0 (31) 16
P4 17.7 (71) 2.1 (8) 5.2 (21) 25
P5 24.0 (60) 6.4 (16) 3.1 (8) 4.0 (10) 2.5 (6) 40
P6 22.3 (55) 17.5 (44) 0.2 (1) 40
P7 11.1 (93) 0.9 (7) 12
A difficulty may arise in the field when locating the boundary between erosional
and depositional surfaces since erosional and depositional processes ebb and flow rather
than being strictly located in specific positions. In addition, these geomorphic units
might be active or passive depending upon the intensity of the driving force (i.e.
rainfall). As a practical guide, an erosional surface is usually characterized by the
presence of features including lag-gravel, pedestal and scald. Depositional surfaces are
indicated by the presence of a fine to coarse sand fraction and litter trapped behind
sedge clumps, fallen twigs, stumps, roots or rock fragments, etc. In general, materials
tend to move across the shelf up to the edge (berm). This process is similar to the
formation of an alluvial fan or floodplain deposit but at a much smaller scale.
Micro-relief may play an important role in regulating movement of soil particles
associated with water erosion. Water containment occurs mostly in the area of jarrah-
banksia-sedge association between plots P3 and P4, where micro-relief is highly
functioning (i.e. water is ponded). Past events of water erosion are evident at lower-
slope and some upper-slope positions of the cutting shelf leading to formation of gullies
to about 30 cm depth at a spillway near the Banksia-pallid zone site (plot P4) and plot
P7, with rills occurring at many parts of the lower slope. A spillway outlet is likely to
have formed through a long process of detachment, slaking and dispersion of easily
eroded materials, which gradually created a channel for run-off water. Erosion was
presumably greater at the early stage of soil development due to the lack of vegetation
cover, coupled with steep slopes and high annual rainfall in excess of 1,000 mm in the
26
region. These three factors (i.e. slope, soil cover, and rainfall) are most influential on
erosion at most locations (Wischmeier and Smith, 1978; Coles and Moore, 1998).
Under natural spontaneous growth, natural mechanisms for reducing soil erosion
involve biophysical mechanisms, which can take the simple form of clumps of grass and
sedge, fallen branches of trees, and litter-bridges across plant roots. These structures
form a slightly rough surface that is beneficial for soil particle retention.
2.3.3. Soil surface morphology
Soil surface horizon development occurs as a result of several processes and the
extent of development may be indicated by a wide range of soil attributes. Primary
attention is particularly given to morphological changes of the surface horizon (Table
2.3) due to the relatively short time (~35 years after disturbance) for soil development.
Within this period new parent materials of the shelf have undergone soil forming
process which vary in nature and biological effectiveness across the shelf.
Natural processes of soil development on degraded lands are generally slow
(Bradshaw, 1997; Neel et al., 2003), thus in a short-term one may expect biological
development (e.g. accumulation of soil organic matter, fixation of atmospheric nitrogen
and nutrient cycling) to dominate while pedological development can take a much
longer time. The pedogenic formation of an A horizon is considered to be a key
indicator of soil forming processes (Birkeland, 1999; Neel et al., 2003). In this study
the depth of the pedogenic A horizon varies across the shelf from very thin (< 1 cm) and
up to 5 cm with the A horizon being indicated mainly by a darker color (e.g. dark
brown) and the presence of fine roots. The presence of a distinct A horizon indicates
that soil development has occurred as the initial surface of the shelf would not have
contained this horizon, being exposed deep regolith and rock with a variable cover of
diverse detritus from excavation of cutting.
The development of an A horizon can be impeded on an erosional surface due to
constant disturbance (i.e. soil loss by water erosion). For example, the surface horizons
of the granite/saprolite plots (P5 and P6) remain similar to underlying substrates (i.e.
‘fresh’ saprolite) and are only distinguished by a thin-greenish layer (mosses and lichens
with 1-5 mm thick) as the surface horizon. In contrast, soils on the depositional surface
may show a greater soil development as the substrate of the original surface interacts
with deposited materials. This condition is particularly evident near the slope boundary.
27
For example, the surface layer (0-2 cm) of plot P4 differs from the underlying pallid
zone in color and texture. The color changes from light gray (10YR7/1) or white (10YR
8/1) to very dark gray (10YR3/1) or dark brown (10YR3/3) due to organic matter
accumulation and humification.
Structure development within deposited and subsurface parent materials is
assisted by fine roots, which are evident in the top 1-2 cm depth for example, in the
surface layer of plots P3, P4 and P7. The structure of surface soils ranges from fine to
medium, moderately stable crumb or granular to fine sub-angular blocky.
Surface stabilization is required for soil development at disturbed sites
(Bradshaw, 2000). This is particularly important to minimize detachment of soil
particles in erosion events. Stabilization may result from soil particle-root binding and
soil surface colonization by lichens and mosses (cryptogamic crusts). Bresson and
Boiffin (1990) summarized that crust development generally follows two successive
stages, these are 1) sealing of the soil surface by s structural crust and 2) development of
a depositional crust. Gaskin and Gardner (2001) found a reduction up to 50 % in run-off
and soil loss for plots covered with cryptogam. There is evidence of this type of surface
stabilization across the shelf although this occurs in a patchy pattern. Both lichens and
mosses grow on various substrates ranging from rock to clayey-mottled surfaces.
Surface cover by cryptogamic crusts is more critical for stabilization of disturbed sites
mainly due to lack of vegetation cover compared with forest floor of established
woodland with extensive roots and massive canopy. Soil enrichment occurs through
biomass contribution of fringing vegetation on the crest of the railway cutting or plant
species colonizing the shelf, along with sand and fine-size particles deposition from the
upper slope. Soil resource movement, retention and utilization on the shelf should
therefore be viewed as a holistic process at a hillslope scale.
28
Table 2.3. Soil processes and related indicators of soil surface horizon development at the Jarrahdale railway cutting shelf.
Parameter Sampling plot P1 P2 P3 P4 P5 P6 P7 Soil process Root action (sedge)
into hard surface (bioturbation), deposition
Lichen and moss colonization on rock surface, debris erosion
Erosion, sand deposition, fauna activity (ant)
Erosion, deposition, particle sorting
Erosion, Deposition, particle sorting
Erosion , Deposition, particle sorting
Deposition, erosion, fauna activity
Surface indicator of soil process
Moss cover, surface break-up by root penetration (sedge), stem deposition
Moss and lichen colonization
Litter and organic matter enrichment, biopore formation
Fine material and litter accumulation, lichen growth
Eroded sloping parts, cryptogam cover around stem, litter accumulation behind rock
Eroded and scoured surface, thin bio-crust formation
Litter accumulation surface darkening, root binding
Depth of A horizon
Localized (sedge tussock) <5 cm wide and <10 cm depth, limited over duricrust layer
<1cm depth on debris material (limited to depression), mostly eroded
3-5 cm depth, dark brown to yellowish brown
3-10 cm depth, lighter (sandier) texture
Vary (<1cm near embankment/edge), 1-3 cm around ridge, some are gravelly
Very thin (<1cm) 1-5 cm thick, evidence of organic matter incorporation, varies in colour to dark brown
Soil structure development
Developed mostly around sedge and toe-slope (material deposition), granular to sub-angular blocky
Becomes stable, fine-coarse granular to sub-angular blocky to weakly structured (debris materials)
Fine-medium sub angular blocky or crumb (fine root binding over blocky and platy subsurface horizon
Fine-medium blocky (litter and root affected soil), slightly platy or sub-blocky (sand deposition)
Weakly structured (saprolite) to slightly crumb or fine-medium sub angular blocky near toe-slope
Massive to slight crumb (as saprolite structure)
Developed structure, crumb to sub-angular blocky, 5-10 mm in size.
Surface crusting Moss and lichen prominent in winter (wet) season
Moss and lichen on debris materials
Cryptogamic crust around shrub stems
Present along toe slope, cryptogam at upper slope, not significant on shelf
Cryptogamic crust around Dryandra stems and gently sloping surface
Cryptogamic crust around Dryandra stems
Limited near plot boundary, not favorable under litter cover
29
2.3.4. Plant colonization and standing biomass
Plant colonization varied considerably (i.e. sites rich in vital resources) across the
cutting shelf. Plant growth could be related to both parent materials and micro-
geomorphic units. In general plant growth is more favored on deep substrates, behind
embankments or in depressions. Two or three species are variously dominant and the
species differ between plots (Table 2.4). A few woody species have colonized the shelf
and slopes, while other parts of the cutting shelf are still sparsely occupied. Successful
site colonization is not solely dependent upon parent material and local relief, but it also
requires a variety of source plants. Fringing vegetation is an important source of seed
and seedling (Booth et al., 1999; Honnay et al., 1999; Roelle and Gladwin, 1999; Craft
et al., 2002). In many examples, plant succession on degraded lands, including those
due to mining operations, is associated with immigration and establishment via
transported seeds (Tucker and Murphy, 1997; Bradshaw, 2000). Seedlings of Dryandra
sessilis are very common and represent an extensive colonization (i.e. the primary
colonizer) of the cutting including the sloping area. The high occurrence of this
volunteer species might indicate its adaptation to poor soil conditions.
Site occupation by local plant species is more vigorous on flat to gentle slopes
than on steep slopes. Despite the hard-cemented surface of plot P1, a few sedge, heath,
sheoak and mosses have successfully colonized the site. Low shrubs are less than 50
cm height. The embankment of this plot is colonized by several plant species (sheoak,
marri) taller than 2 m. Site colonization is minimal at plot P2 (granite substrate) due to
the very shallow ‘soil’ depth directly on massive granite. In general, jarrah, marri and
banksia trees grow well on the shelf where the soil is relatively deep (>2-4 m) and
without root-restricting layers. The absence of a non-limiting layer is also a key
criterion for rehabilitated mine sites (Nichols et al., 1985; Osborne, 1996). Several
groundcover species grow on the slopes, mostly being located in micro-depressions (e.g.
plots P3 and P4). Although the vegetation on the shelf is quite sparse, it must be
recalled that rates of natural recovery are generally very slow. The process may take
50-300 years for plant cover and biomass turnover to reach equilibrium, and over 3000
years for complete ecosystem recovery (Bradshaw, 1997; Lovich and Bainbridge,
1999).
30
Table 2.4. Plant species occurrence (++dominant species, + present, − absent) on the Jarrahdale cutting shelf. Annual species are common during
winter and spring. Species identification is courtesy of Dr John Koch (ALCOA).
Plots Plant species Common name P1 P2 P3 P4 P5 P6 P7
Allocasuarina fraseriana Sheoak ++ − + − − − − Banksia grandis Bull-banksia + + + ++ + + + Eucalyptus marginata Jarrah + − + + + + + Dryandra sessilis Parrot bush + − + + ++ ++ + Corymbia macrophylla Marri + − + + + + + Leucopogon nutans Drooping heath + + ++ + + + + Hypocalymma angustifolium White myrtle + + ++ + + + + Cyathochaeta avenacea Grass sedge + + + + + + ++ Conostylis setosa / C. setigera White/Bristly
cottonhead + + + + + + +
Daveisia decurrans Prickly bitter-pea − − + − + − − Pentapeltis peltigera - + − − − − − + Gompholobium marginatum - + − − − − − + Pterochaeta paniculata (annual)
Dwarf daisy + + + + + + +
Stylidium hispidum (annual) White butterfly triggerplant
+ + + + + + +
Briza maxima (annual) Blowfly grass + + + − + − −
31
Plant growth appears to be better on the deep-clayey substrate (that is pallid zone)
probably due to its higher available moisture content. McCrea et al. (1990) found that
saturated and available water contents of dolerite and granite pallid zone materials of
the Jarrahdale cutting has a positive relationship with clay content. Surface cracks (1-2
cm width) form in the clay substrate during dry months and are beneficial for down-
profile water movement, thus reducing run-off. This part of the cutting shelf is thus
more drought resistant and may be better able to support plant growth, especially soils
adjacent to the Banksia plot (P4). At this location jarrah trees up to 10 m height and
Banksia up to 2.5-3 m height have established. Thus, this simple niche (micro-
depression and embankment) and a suitable substrate represent an effective soil patch
for plants.
Total dry weight of above-ground parts is closely related to various plant
attributes for several plant species on the Jarrahdale cutting shelf. The dry weight of an
entire parrot bush (Dryandra sessilis) is sufficiently predicted by both stem diameter
and plant height. For sedge (Cyathochaeta avenacea), the biomass is adequately
predicted by clump circumference (or diameter). Biomass of two species of low shrubs
typical of the area (Hypocalymma angustifolium, Leucopogon nutans) is highly related
to plant height and canopy depending on growth form (Figure 2.10). Bull banksia
(Banksia grandis) is also common on the shelf, and equations for biomass prediction in
this study are from other work (Glossop, 1978). The biomass prediction equations for
some species and corresponding references are in Table 2.5.
Standing biomass varied considerably across the shelf which is due partly to the
patchy occurrence and size (quantity) of plants and the several plant species (diversity).
Figure 2.11 shows standing biomass for several plots that indicates a wide range of
biomass values for different types of vegetation. Early colonizers also include annual
species (herbs) and grasses. The annual species were abundant in winter (rainy) (June-
August). Total biomass contributions by annual herb species may be minor due to their
small size, however fine roots of these plant species may contribute significantly in
stabilizing soil materials.
32
Figure 2.10. Equations for predicting the biomass of dominant plant species colonizing the Jarrahdale cutting shelf derived from the present study.
Table 2.5. Equations for predicting biomass of several species obtained from previous work in the region. All fit a power function (or natural log-transformed function) incorporating plant attributes. The abbreviations are as follows: DW, dry weight (kg); FW, fresh weight (kg); bbh, basal area at breast height (cm2); dgl, diameter at ground level (cm); dbh, diameter at breast height (cm). Species Biomass equation N r2 References
E. marginata DW = 0.0353 (bbh)1.42 10 0.995 Glossop (1978)
Ln (DW) = 2.84 ln(dbh) – 3.68 10 0.994 Hingston et al. (1981)
E. calophylla DW = 0.146 (bbh)1.15 10 0.938 Glossop (1978)
Ln (DW) =2.74ln(dbh) – 3.37 10 0.982 Hingston et al. (1981)
Ln (DW) = 2.04 ln (dbh) – 1.54 9 0.99 Ward and Pickersgill (1985)
B. grandis DW = 0.132(dbh)2.28 11 0.959 Glossop (1978)
A. saligna DW = 2.24 ln(dgl) – 2.94 10 0.933 Koch (1987)
Dryandra sessilis
y = 34.8 x 2.12
r2 = 0.973
0
50
100
150
200
250
300
0 1 2 3Stem diameter (cm)
Dry
wei
ght (
gram
)
Leucopogon nutans
y = 0.043xr2 = 0.996
0
2040
60
80
100120
140
0 1000 2000 3000 4000canopy size (cm2)
Dry
wei
ght (
gram
)
Hypocalymma angustifolium
y = 0.00041 x 2.85
r2 = 0.881
0
2
4
6
8
10
12
0 10 20 30 40Height (cm)
Dry
wei
ght (
gram
)
Sedge (Cyathochaeta avenacea )
y = 9.02 x1.30
r2 = 0.981
0
20
40
60
80
100
0 1 2 3 4 5 6Clump diameter (cm)
Dry
wei
ght (
gram
)
33
Figure 2.11. Standing biomass in gram/unit area (0.25 m x 0.25 m = 0.062 m2) for several plots. Large contributions are due to sedge (P1), shrubs (P3) or banksia (P4). Points indicate locations of plants used for determination of biomass estimation, except for Plot 4 showing Banksia.
34
Figure 2.12. Litter cover area as a percentage of the unit area (0.25 m x 0.25 m = 0.062 m2) for pallid-mottled zone (PMZ) plots.
35
Figure 2.13. Litter cover area as a percentage of the unit area (0.25 m x 0.25 m = 0.062 m2) for granite/saprolite plots.
The average amount of standing biomass (dry weight) was less than 0.05 kg/m2
for plot P2; 0.05 to 0.10 kg/m2 for plots P1 and P3; 0.10-0.25 kg/m2 for plots P5, P6 and
P7; and >1.10 kg/m2 for plot P4 (Banksia). Except for plot P4, the biomass for other
plots is equivalent to values of up to 1 Mg/ha. For comparison, literature indicates
36
values of standing biomass of about 1.7 Mg/ha for shrubs (<1.5 m height) in a mature
jarrah forest, 2.8 Mg/ha for understorey (Banksia grandis and others > 1.5 m height),
out of a total biomass of 262 Mg/ha (Hingston et al., 1981). A total biomass of 1.23
Mg/ha was recorded for E. calophylla plantations in rehabilitatated bauxite mine sites
3.5 years after establishment which increased to 24 Mg/ha after 7.5 years (Ward and
Pickersgill, 1985). The biomass reached about 1.22 kg/m2 (~12.3 Mg/ha) for vascular
and woody species (mainly Oxycoccus macrocarpos, Salix repens, Erica tetralix) on a
coastal dune in the Netherlands over 35 years of succession (Berendse et al., 1998).
Standing biomass is mostly contributed by perennial species. Jarrah and marri
contribute largely to total biomass due to their long lifespan (>30 years) and vigorous
growth form (broadleaf, large tree).
Standing biomass can be used as an indicator of litter production. However, litter
accumulates on the cutting shelf from both local and transported sources. There is also
a distinct pattern of litter deposited along the toe slope or near the source plants for plot
P4 (Figure 2.12). A very low cover of litter was noted for plot P2 as a consequence of
the very low biomass and almost nil litter transport onto the plot due to the position of
this plot near the top of the embankment of the cutting shelf. Granite outcrop and rock
fragments are beneficial to retaining the litter of the standing biomass on the site of plot
P5 (Figure 2.13).
Figure 2.14. Litter weight increases with percentage surface cover for a mixed litter from plots P1, P2 and P3.
There is a strong positive relationship between litter weight and surface cover of
mixed plant residues (sheoak needle, jarrah leaf) from plots P1, P2 and P3 (Figure 2.14).
The litter amount is quite low but is still appreciable for these bare soil sites with
y = 2.80 x (r2 = 0.99)
0
50
100
150
200
250
300
350
0 25 50 75 100Surface cover (%)
Litte
r wei
ght (
g/m
2 )
37
volunteer vegetation where plant growth is much less than for assisted rehabilitation and
mature forest sites. For a rehabilitated bauxite mine site after 9 years, the average
amount of standing biomass was 7.2 Mg/ha and the maximum litter amount in a unit
area (0.6 m by 0.6 m) was 1.5 kg (~4.2 Mg/ha) (Todd et al., 2000b). The amounts of
litter on rehabilitated sites is also affected by the density of understorey species and
ranged from 1.8 Mg/ha (low density of understorey for 7.5 year old rehabilitated bauxite
mine sites) and was up to 8.9 Mg/ha for a younger site (3.5 years) sown with various
legume species (Ward and Pickersgill, 1985). In the mature jarrah forest, the amounts
of litter are also high (11.1 Mg/ha) (Hingston et al., 1981).
2.3.5. Nutrient concentrations of plant and litter samples
Nutrient concentrations varied considerably for various parts of plant species
growing on the cutting shelf (Table 2.6). The concentration of nitrogen was mostly
more than 1 % occuring in leaves relative to woody parts of plants. Total N was lower
(0.7 %) for dryandra leaf than for leaves of other species. Low shrubs (heath and
myrtle) contained about 1.5 % N and the N concentration decreased to about 0.4 % for
other parts of these plant species. These results are comparable to published results for
jarrah leaves (mean concentration of about 1.0 % N) and other parts of jarrah trees (less
than 0.3 % N) (Hingston et al. 1981) and for plantation eucalypts (Ward and Pickersgill,
1985). However, the nitrogen capital for these forest and plantations soils is largely
determined by the total biomass and litter mass, which is much lower for the Jarrahdale
shelf being less than about 1 Mg/ha for low shrubs. Consequently, the potential for N
contribution from plants to soil on the shelf is low (approximately 10 kg N/ha).
Other nutrients also varied considerably in concentration. Phosphorus (P)
concentration is low (less than 0.05 %) and P is mostly contained in leaves; the average
concentration was about 0.02 % in the other parts of plants. The low concentration of P
in plant samples reflects the low concentration of soil P, and the adaptation of these
plants to gross infertility (Bell and Ward, 1984; Majer et al., 1992; Ward and Koch,
1996; Lambers et al., 2002). Potassium (K) concentrations ranged from 0.08 − 0.63 %
for the various plant samples. For NPK the concentrations in equivalent plant samples
from the shelf and the adjacent jarrah forest are similar (Figure 2.15).
38
Table 2.6. Element concentrations (single measurement of bulk composite sample) of different parts of the major plant species at the Jarrahdale cutting shelf (60 °C basis).
Plant species Sample C N P K Ca Mg Na S Cl Si Al Zn Cu Fe Mn (%) (mg/kg) Jarrah Leaf 55.9 1.13 0.039 0.34 0.30 0.33 0.18 0.10 0.46 0.01 0.07 6 2 135 185 Fruit 52.5 0.26 0.019 0.08 0.20 0.23 0.11 0.06 0.01 0.20 0.22 7 1 449 93 Bark 52.8 0.40 0.009 < 0.17 0.10 0.04 0.05 < 0.08 0.22 4 < 943 45 Marri Leaf 54.5 1.24 0.050 0.63 0.68 0.31 0.21 0.11 0.55 < 0.08 12 3 129 73 Fruit 49.8 0.29 0.009 0.58 0.14 0.16 0.21 0.04 0.08 1.42* 0.99* 5 1 1254* 33 Twig 51.6 0.40 0.022 0.28 1.86 0.24 0.11 0.05 0.23 < 0.05 14 8 133 103 Banksia Leaf 51.3 1.01 0.054 0.33 0.27 0.14 0.27 0.15 0.29 < 0.30 8 2 66 508 Fruit 44.5 0.25 0.008 < 0.15 0.09 0.03 0.04 < 2.45* 3.42* 9 5 6811* 83 Flower 48.5 0.38 0.001 0.09 0.06 0.08 0.13 0.02 < 0.01 0.10 4 < 834 17 Dryandra Leaf 49.4 0.69 0.015 0.25 0.60 0.14 0.21 0.23 0.21 < 0.05 6 < 113 365 Stem 48.0 0.24 0.008 0.35 0.57 0.31 0.54 0.20 0.61 0.02 0.11 19 < 256 596 Hypocalymma Leaf 54.2 1.51 0.046 0.46 0.50 0.12 0.06 0.14 0.11 < 0.01 33 7 42 345 Stem 52.1 0.40 0.017 0.17 0.73 0.09 0.04 0.07 0.15 0.01 0.08 75 5 98 895 Leucopogon All 55.0 1.53 0.043 0.41 0.44 0.18 0.11 0.17 0.27 0.15 0.34 15 5 519 287 Sheoak Needle 51.5 0.81 0.022 0.38 0.65 0.24 0.14 0.11 0.39 < 0.07 61 4 75 83 Sedge Leaf 46.2 0.35 0.008 0.25 0.15 0.11 0.03 0.11 0.14 2.14 0.20 19 1 245 178
Note: < = less than the lower limit of detection *) The very high concentrations of these elements are probably due to contamination by soil.
39
Table 2.7. Element concentrations of litter samples. Species Sample C N P K Ca Mg Na S Cl Si Al Zn Cu Fe Mn (%) (mg/kg) Shelf Animal faeces 46.8 1.36 0.076 0.039 0.46 0.08 0.029 0.144 0.020 2.31 1.00 18 2 4094 204 Sheoak needle 52.6 0.62 0.004 < 0.52 0.15 0.039 0.056 < 0.10 0.36 19 2 720 72 Banksia leaf 51.9 0.56 0.011 < 0.56 0.17 0.039 0.102 0.002 0.03 0.20 4 < 197 76 flower 41.9 0.36 0.005 0.066 0.23 0.10 0.058 0.030 < 0.82 1.64 6 < 6227 44 bark 49.6 0.50 0.029 0.016 0.28 0.11 0.040 0.086 < 0.49 1.12 5 < 1588 26 Jarrah leaf 57.1 0.59 0.006 0.001 0.90 0.14 0.039 0.060 0.057 0.20 0.41 8 1 853 179 fruit 52.7 0.52 0.013 < 0.33 0.27 0.037 0.056 0.011 0.04 0.17 7 1 280 150 twig 50.1 0.35 0.003 < 0.64 0.13 0.032 0.042 < 0.11 0.28 6 2 1080 149 Marri leaf 54.5 0.54 0.003 < 1.15 0.14 0.038 0.054 0.029 0.29 0.56 11 < 623 103 Heath stem 49.4 0.69 0.015 0.011 0.18 0.06 0.026 0.073 0.001 0.48 0.96 15 < 3755 24 Jarrah forest Acacia leaf 52.8 0.53 0.007 < 0.34 0.10 0.035 0.119 < 0.08 0.19 5 < 547 64 pod 52.4 0.79 0.008 < 0.75 0.16 0.035 0.046 0.033 0.05 0.19 8 < 797 180 Jarrah leaf 57.1 0.63 0.006 < 0.87 0.17 0.040 0.063 0.038 0.10 0.16 7 1 565 252
Note: < = less than the lower limit of detection
40
Figure 2.15. Bivariate plots for nitrogen, phosphorus, potassium and calcium concentrations of equivalent plant materials from plants growing on the cutting shelf and adjacent jarrah forest. Lines indicate 1:1 slope.
Concentrations of metals generally have the following order of concentrations:
Fe > Mn > Zn > Cu. The largest concentration of Fe (> 1200 mg/kg) was in the fruit of
banksia and marri. Literature indicates that for a mature jarrah forest, average
concentrations of Mn ranged from 2 to 144 mg/kg, Cu and Zn concentrations are less
than 12 mg/kg for various jarrah forest plant materials (Hingston et al., 1981). Foliage
samples of Banksia grandis contained higher concentrations of Mn (208-549 mg/kg)
than for other metals (less than 71 mg/kg) (Barrick, 2003). With an assumed total
biomass of 2 Mg/ha, the amounts of metals are mostly less than 1 kg Fe, 0.5 kg Mn,
0.04 kg Zn and 0.01 kg Cu per hectare. Total contribution of metals for eucalypts in
rehabilitated bauxite mined area varied from 1.9 to 5.2 kg Mn/ha and less than 0.5 kg/ha
for Cu and Zn (Ward and Pickersgill, 1985) which were similar to values for jarrah and
marri in a mature forest (Hingston et al., 1981).
The concentrations of C, Ca and Mg in litter were broadly similar to those in
living biomass. Litter mostly had much lower concentrations of P and K relative to
biomass (Table 2.7; Figure 2.16). Concentrations of aluminium and silica are strongly
related for litter samples (Figure 2.17) presumably representing contamination by soil
0
0.4
0.8
1.2
1.6
0 0.6 1.2 1.8Forest N (%)
Shel
f N (%
)
Leafother partsLitter
0
0.01
0.02
0.03
0.04
0.05
0.06
0 0.02 0.04 0.06 0.08Forest P (%)
Shel
f P (%
)
0
0.2
0.4
0.6
0.8
0 0.3 0.6 0.9 1.2Forest K (%)
She
lf K
(%)
0
0.5
1
1.5
2
0 0.5 1 1.5Forest Ca (%)
She
lf C
a (%
)
41
constituents. The dominant constituent of the clay fraction of shelf soils is gibbsite
followed kaolin which is consistent with this material contaminating litter. Element
concentrations of litter samples in this study are comparable with published results
including nitrogen (0.33 to 0.46 % ), phosphorus (0.01-0.02 %) and metals (100-300
mg/kg of Mn and less than 10 mg/kg of Cu and Zn), and are mostly lower for K
concentration (0.051-0.094%) (Hingston et al., 1981; Ward and Pickersgill, 1985).
Since litter production is low at the cutting shelf (~1 Mg/ha), the nutrient contribution to
soil from litter is low (less than 5 kg of N, 0.5 kg of both P and K per hectare).
Microbial decomposition of litter may be slow due to the high C/N ratio of these
materials (Figure 2.18) (Hingston et al., 1981; O’Connell and Menage, 1983; Ward et
al., 1991).
Figure 2.16. Litter versus biomass nutrient concentrations. Lines indicate 1:1 slope.
40
45
50
55
60
40 45 50 55 60Biomass C (%)
Litte
r C (%
)
0
0.2
0.4
0.6
0.8
1
0 0.5 1 1.5 2Biomass N (%)
Litte
r N (%
)
0
0.5
1
1.5
0 0.5 1 1.5Biomass Ca (%)
Litte
r Ca
(%)
0
0.01
0.02
0 0.02 0.04 0.06Biomass P (%)
Litte
r P (%
)
0
0.02
0.04
0.06
0.08
0 0.2 0.4 0.6 0.8Biomass K (%)
Litte
r K (%
)
0
0.1
0.2
0.3
0 0.1 0.2 0.3 0.4Biomass Mg (%)
Litte
r Mg
(%)
42
Figure 2.17. Concentrations of aluminium (Al) of litter samples are closely and linearly related to silica (Si).
Figure 2.18. Relationship between C/N value and total N for various parts of plant species and litter.
2.3.6. General discussion
Complex relationships exist between vegetation, parent material and topography.
This study demonstrates that the slow soil development of exposed subsoil materials is
partly due to the low extent of plant colonization of the cutting shelf. Litter
accumulation is low and patchy across the shelf. Under natural conditions, plant
biomass production is the key source of litter and litter decomposition is essential for
nutrient cycling. Litter of jarrah trees is relatively slowly decomposed due to the high
values of the C/N ratio (Hingston et al., 1981; Ward and Pickersgill, 1985; Ward and
Koch, 1996). The poor plant colonization of the shelf presumably reflects the low
fertility status of the exposed subsoil materials which limits the initial growth of
0
50
100
150
200
250
0 0.5 1 1.5 2Total N (%)
C/N
val
ue
Littershelf biomassforest biomass
y = 1.92 x + 0.076r2 = 0.98
0.0
0.3
0.6
0.9
1.2
1.5
1.8
0.0 0.2 0.4 0.6 0.8 1.0Litter Si (%)
Litte
r Al (
%)
43
recruited plants. Litter from vegetation on plots is not always retained by soil within
plots and may be transported to other parts of the shelf by lateral movement of water
including water derived from the upper slope. Significant litter retention only occurs
over less than 8 % of the shelf total length (~300 m), particularly in depressions. These
findings suggest that retention and utilization of nutrients and organic matter in litter are
very important in establishing soil fertility on the shelf.
Initial processes of soil development are also related to the accumulation or loss of
fine size mineral particles in the topsoil, in addition to increased soil organic matter
derived by litter decomposition. Massive clayey substrates (e.g. sandy clay) may
gradually change into lighter textured materials (clay loam or sandy loam) as a result of
particle size sorting and sand accumulation. Organic substances interact with soil
particles and this process is important for promoting soil structure, porosity and
aggregate stability (Chaney and Swift, 1984; Uchida et al., 2000; Gaskin and Gardner,
2001). Aggregate stability is also enhanced by the presence of fine roots and fungal
hyphae (Oades, 1993; Eldridge and Koen, 1998; Eldridge et al., 2000). All of these
effect may occur within a thin layer (~1 cm) in the surface layer of shelf soils.
Soil development can take a long time to reach a mature stage. This study
however records some development of biological and physical properties of the shelf
soils over 36 years after disturbance. In particular establishment of several plant
volunteer species, topsoil development and organic matter enrichment of topsoil on
various regolith materials has occurred on the cutting shelf.
44
Chapter 3. Properties of lateritic regolith 36 years after exposure in
the Jarrahdale railway cutting
3.1. Introduction
Soil development occurs spontaneously after land disturbance. The rate and
direction of soil development vary considerably in relation to the plant community
composition and soil properties. Recovery of a site may be relatively fast in achieving a
new sustainable ecosystem under suitable conditions, whereas it may be very slow
under unfavorable conditions (Zarin and Johnson, 1995; Pillans, 1997; Francescato et
al., 2001). Several factors are responsible for the variation in the rate and nature of soil
and plant development including parent material, landform, climate and colonizing plant
species (Honnay et al., 1999; Ward, 2000; Odland and del Moral, 2002; Néel et al.,
2003).
Soil characteristics are usually strongly influenced by the properties of parent
materials. For example, mafic and felsic rocks produce soils with very different
chemical, physical and mineralogical properties due to the different mineral
compositions of these rock types (Knapp, 1979; White, 1987; Buol et al., 1989;
Birkeland, 1999). Many soils in the Darling Range region (Western Australia) are
derived from the advanced weathering of granitoid rocks which resulted in extensive
leaching of alkalis (i.e. K, Na, Ca, Mg). Consequently soils were acidic and deficient
for these elements, and kaolinite and gibbsite are dominant in the clay fraction (Gilkes
et al., 1973; Sadleir and Gilkes, 1976; Siradz, 1985; McArthur, 1991).
Changes in soil properties may occur naturally or as an impact of human activity.
The latter includes pre-mining engineering work and effects of mining operations. Soil
properties may improve, deteriorate or even fluctuate during the course of soil
development depending upon environmental factors. Initial changes in soil properties at
disturbed sites are commonly associated with the accumulation of litter and fine earth
materials and decomposition of organic matter (i.e. from exogenous sources), that
increases soil nitrogen, plant-available P and K, exchangeable bases and CEC (Zarin
and Johnson, 1995; Cox and Whelan, 2000; Schwenke et al., 2000; Ward, 2000). The
contribution of endogenous material is mostly from the weathering and transformation
of soil minerals (Knapp, 1979; Birkeland, 1999).
45
Spontaneous plant growth and soil development have occurred on a bench of the
Jarrahdale railway cutting within three decades after disturbance. The extent of soil
development may be determined by comparing properties of newly developed topsoil
relative to values for subsurface horizons of original soils. This chapter describes soil
properties 36 years after excavation of the Jarrahdale railway cutting through an
investigation of several sites exposed on a bench in the cutting for several contrasting
rock and regolith materials. This work deals with physical, chemical and mineralogical
properties of shelf soils.
3.2. Materials and Methods
3.2.1. Field technique
Soil samples were collected from seven small plots established along the cutting
shelf. The description and parent materials of these plots are presented in Chapter 2
(Section 2.2.2). These plots were delineated purposely so that they represent much of
the variation of soil surface and parent material along the cutting shelf. Plots dimension
ranges from 1.5-4 m (width) by 6-10 m (length). These plots were selected to
adequately represent variations in soil development and plant colonization on the shelf.
These plots vary in their underlying materials comprising pallid zone, mottled zone,
granite saprolite with some colluviation of lateritic gravel and other detritus to the
surface at each plot. The shelf soil samples were categorized into two groups: a) pallid-
mottled zone (PMZ) comprising plots P1, P3, P4 and P7, and b) granite saprolite
consisting of plots P2, P5 and P6. Soil from the adjacent jarrah forest was also sampled
for reference purposes. These groups of samples are utilized in this thesis as the basis
for result presentation and multivariate analysis.
Some soils on the shelf show substantial changes in their morphology relative to
parent materials including development of moderately well-developed structure which
is sub-blocky or weakly granular (crumbling with pressure), darkening of surface
horizon to dark grayish brown (10YR 4/3), brown (10YR 5/3), dark yellowish brown
(10YR 4/4) or reddish yellow (7.5YR 6/6). Soil color is darker on sites under
decomposing litter becoming very dark grayish brown (10YR 3/3).
46
3.2.2. Soil sampling
Soil samples were collected from each plot with the sampling strategy reflecting
the various soil materials present in individual sampling plots. Depth of soil sampling
varied from one point to another due to variations in underlying materials, and
sometimes included several shallow soil layers (<10 cm depth). Particular attention was
given to the 0-1 cm surface layer as an indicator of soil forming processes. Another set
of soil samples was collected from the nearby jarrah forest (upper-slope site) at 0-10 cm
and 10-20 cm depth. The difference in sampling between the cutting shelf and the
jarrah forest is because no clear horizon was observed in 0-20 cm depth. The jarrah
forest had not been disturbed by mining, thus it represents the pre-disturbance condition
of the sites. Soil core samples (7 cm height, 7.2 cm diameter) were also collected from
the shelf and the jarrah forest for measurement of bulk density, saturated hydraulic
conductivity, and aggregate stability.
3.2.3. Soil analyses
Soil permeability (hydraulic conductivity HC) was measured under a saturated
condition in the laboratory using intact (diameter 7.2 cm) core samples and the constant-
head method (Klute, 1965). It is well known that it is very difficult to measure soil
permeability in the laboratory due to problems of obtaining undisturbed/intact cores, so
it would have been preferable for HC measurements under both saturated and
unsaturated conditions to have been done in the field using the disc permeameter
developed by White et al. (1992). For several samples, soil permeability was also
measured under an unsaturated condition in the field which gave values of soil
sorptivity, steady-state flow rate and hydraulic conductivity (McKenzie et al., 2002).
Water-stable aggregates were determined by the Yoder (1936) wet sieving method for
8-mm or smaller aggregates on a set of sieves with 4.75, 2.0, 1.0, 0.5 and 0.250 mm
apertures, with shaking for 20 min with up and down strokes (19 mm amplitude) at a
rate of 38 strokes per minute. The result is usually expressed by mean-weight diameter
or MWD (Kemper and Chepil, 1965; Chaney and Swift, 1984). Bulk density was
determined using a corer-gravimetric procedure (Blake, 1965).
Soils were passed through a 2-mm sieve prior to analysis of basic soil properties.
Particle size distribution was determined using the pipette method after organic matter
47
removal using hydrogen peroxide (Van Reeuwijk, 1987). Soil pH and electrical
conductivity (EC) were measured on a 1:5 soil to water suspension. Soil samples were
extracted with 0.5 M NaHCO3 pH 8.5 (Colwell, 1963) to measure plant-available
phosphorus and potassium. The LECO CHN1000 combustion method was used to
measure total carbon (Nelson and Sommers, 1982) and total nitrogen (Bremner and
Mulvaney, 1982) after the removal of (mostly) macro-organic material. Exchangeable
base cations and cation exchange capacity (CEC) were determined using the silver
thiourea exchange method (0.01 M AgTU) and were measured using an atomic
absorption spectrometer (Rayment and Higginson, 1992). Clay mineral composition
was determined by X-ray diffraction (Philips PW1380) after preparing oriented-clay
suspensions on ceramic plates, saturated with 2 M MgCl2 and further saturation with
50% aqueous glycerol if there were diffraction peaks at low angles (~1.4 nm), which
indicate the presence of swelling 2:1 type clay minerals, particularly smectite and
vermiculite. The approximate relative abundance of clay minerals was calculated by
measuring the relative areas under first order basal reflections after background
correction and normalized to give a total of 100 % (Brown and Brindley, 1980).
3.2.4. Statistical analysis
A simple correlation matrix with non-transformed data was used to identify
bivariate relationships between soil properties using the StatView® (Abacus Concepts,
1996) statistical package. The principle component analysis (PCA) was done using the
GenStat program based on a correlation matrix as an option to reduce variability in
measurement scales of original variables, which automatically standardized soil
attributes to have a mean of 0 and variance of 1 (Digby et al. 1989; Lawes Agricultural
Trust, 2002). The values of original variables were transformed into new dimensions
(components) with each principle component representing a linear combination of
original variables. The greatest variation between samples is accounted for by the first
dimension and the amount of variation explained decreases for subsequent dimensions.
The PCA components with latent roots (eigenvalues) higher than 1 were retained for
further analysis. Variation in properties of soil samples was presented as a bivariate
plot of two components showing loading scores.
48
3.3. Results and Discussion
This study examined surface and subsurface samples of the shelf soils. The
purpose was to contrast properties of soil layers to provide an indication of the soil
development being achieved after land disturbance at the Jarrahdale site. To achieve
this purpose, the results are presented mainly as bivariate plots for physical and
chemical properties of surface and subsurface samples.
3.3.1. Gravel content and particle size distribution
Gravel content of topsoil (<10 cm depth) varied considerably within and between
sites ranging from 20 to 97 % (mean 55 %). Gravel is partly due to deposition
(colluviation) of lateritic gravel from upslope and partly to residual rock fragments. The
colluvium collects where the slope changes sharply from gentle-steep to nearly flat. For
all soils, more than half the samples had gravel contents ranging from 30-60 % by
weight (Figure 3.1). Subsoil horizons also contained much gravel comprising 15 to
65% (mean 43 %). The jarrah forest contained more gravel in subsoil (10-20 cm)
(Table 3.1).
Figure 3.1. Frequency distribution of gravel contents for the Jarrahdale shelf and jarrah forest soils.
Gravel-size material in these soils is mainly in the form of rock fragments or
colluvial and in situ lateritic gravel (Figure 3.2). Some rock fragments may have been
generated by blasting activity during engineering works. In contrast, lateritic gravel is a
common constituent of the upper horizons of lateritic soils. Some of the shelf sites were
on exposed lateritic mottled zone materials that contain lateritic gravel in the form of
hardened mottles (Gilkes et al., 1973). Lateritic gravel is transported by colluviation and
Surface soils
012345678
15 25 35 45 55 65 75 85 95Mid-class of gravel content (%)
Cou
nt
Subsurface soils
0
2
4
6
8
10
12
15 25 35 45 55 65Mid-class of gravel content (%)
Cou
nt
49
deposited in micro-depressions, troughs or around ridge/embankment (berm) situations
on the shelf sites.
Table 3.1. Particle size distribution of < 2 mm fraction (mean± standard deviation) and gravel content of the Jarrahdale shelf and jarrah forest soils. Number of soils used for measuring gravel content are shown in parenthesis.
Soil parent Samples N Particle size (%) Gravel material > 50 µm 2-50 µm < 2 µm (%) PMZ Surface 17(18) 76±15 12±7 11±8 52±23
Subsurface 25(19) 62±22 18±10 20±14 45±16
Granite Surface 13(14) 80±6 11±2 9±4 55±22
Subsurface 16(16) 79±5 12±2 10±3 43±13
Jarrah forest Surface 4(4) 81±2 12±2 7±1 38±19
Subsurface 4(4) 83±3 11±2 6±1 51±15
Figure 3.2. Different forms of gravel. Rock fragments on plot P2 (left) and lateritic gravel on plot P3 (right).
Diverse granitoid and dolerite rocks are parent materials of the lateritic soils at
Jarrahdale and various laterite horizons are exposed resulting in a wide range of particle
size distributions and soil texture classes for shelf samples (Table 3.1). Complete
results of particle size analysis and other properties are given in Appendix 1. Two
50
definitions of silt and sand fractions are commonly used, i.e. 2-20 µm and 20-2000 µm
respectively (widely used in Australian classification systems) and 2-50 µm and 50-
2000 µm respectively (USDA Soil Taxonomy, widely used in Indonesia). As the author
is most familiar with the USDA classes, this report selects 50-µm as the lower size limit
for sand. The 20-50 µm size fraction is also available in this work which enables
comparison with the results from McCrea et al. (1990) from the same site and the
results of other Australian authors (Figure 3.3). Soil texture was mostly loamy sand or
sandy loam, while a few samples were sandy clay loam, loam, clay loam, or clay. Sand
was dominant for most of samples (70 % of total soil samples) with average contents of
70-90 %. Plot P4 soil had a high clay content (30+ %) due to its position on the shelf
which represents exposed kaolin-rich pallid zone (Sadleir and Gilkes, 1976; McCrea et
al., 1990). Values for surface layers of the shelf soils were mostly clustered around 75
% sand, 15% silt and 10 % clay presumably reflecting the dominant effect of colluvium
as materials approximately represent the weighted average composition of the various
lateritic materials exposed on the shelf. Sub-surface layers were more variable in their
particle size distributions (Figure 3.3).
Figure 3.3. Ternary diagram of texture for the fine earth (< 2 mm) of soils from the Jarrahdale cutting site (shelf and jarrah forest) and data from McCrea et al. (1990)
51
representing dolerite pallid zone (DPZ) and granite pallid zone (GPZ). For this presentation, the sand fraction is 0.02-2 mm, silt 0.002-0.02 mm and clay < 0.002 mm.
Differences in the silt to clay ratio shown in Figure 3.4 may be original or due to
relative movement (translocation) of fine particle within a soil profile or during
transportation (colluviation). The ratio tends to decrease as clay content increases. The
large variations in sand, silt and clay contents can be related to the different quartz
contents of the granitic and doleritic rocks which are major parent materials of lateritic
soils in the region. Soils developed from granite contain more sand and less clay than
those derived from dolerite (McCrea et al. 1990).
Figure 3.4. Silt to clay ratio for the Jarrahdale cutting soil samples.
y = 4.2 x-0.53
r2 = 0.59
0
1
2
3
4
0 20 40 60Clay (%)
silt/
clay
PMZGraniteForest
52
Figure 3.5. Relative difference between horizons (delta = surface value minus subsurface value) of sand and clay for the Jarrahdale shelf soils.
Differences in soil properties between soil horizon can be useful as indicators of
soil development. By comparing properties of surface and subsurface layers,
pedogenetic processes can be identified. For example, there is generally more sand and
less clay in soil materials that have been colluviated or strongly eluviated. The
increments/ decrements in clay and sand contents for topsoil versus subsoil are
illustrated in Figure 3.5. The large differences in soil texture between surface and
subsurface soil materials for PMZ profiles demonstrated in Figure 3.5 are evidence of
the operation of particle size sorting occurring by colluviation (surface transport). Run-
off water has washed away finer size particles (clay and silt) and left sand behind
resulting in coarser textured surface horizons. This process has operated on both PMZ
and granite soil materials.
3.3.2. Bulk density, aggregate stability and hydraulic conductivity
Undisturbed core samples (0-7 cm) were taken from shelf and forest soils to
determine several soil physical properties (Table 3.2). Saturated hydraulic conductivity
(Ksat) varied greatly between shelf samples with a mean value of 19.1 cm/hr and a range
of 0.9-65.9 cm/hr. This large range reflects the heterogeneity of surface materials on
the shelf. The great variation is partly due to the large differences in texture between
the clay-rich (P4) and the sandy or loamy soils (the others) (Figure 3.6). Hydraulic
-20
-15
-10
-5
0
5
10
15
-20 -10 0 10 20 30
Delta sand (%)
Delta clay (%) PMZ
Granite
53
conductivity was significantly higher (p<0.01) for the jarrah forest soils which reflects
the quite different soil conditions (lower density, high organic matter in surface layers,
crumb or sub-angular blocky structure and smaller aggregates, coupled with a sandy
loam texture). Unsaturated hydraulic conductivity (Kunsat) is a useful predictor of water
movement through the soil to plant roots (Purdie, 1998). The Kunsat (at –30 mm tension)
values differed considerably between substrates on the shelf and the Kunsat values for
forest soil were much larger (Table 3.3). At a tension of -30 m, water flow is mainly
through finer soil pores, which are largely determined by soil texture, and not by
organic matter/fine roots. Therefore, in Table 3.3, the higher values of Kunsat for the
forest soils (compared to the shelf soils) are probably due to their higher sand/lower clay
content.
Table 3.2. Bulk density, saturated hydraulic conductivity (Ksat), water-stable aggregate size (MWD, mean-weight diameter), and macro-aggregate (> 0.250 mm) representing the shelf and jarrah forest soils.
Properties Shelf (n=10) Jarrah forest (n=6) Mean ± sd range Mean ± sd range Bulk density (g/cm3) 1.36 ± 0.16 1.10-1.60 0.90 ± 0.08 0.82-1.03
Ksat (cm/hr) 19.1 ± 23.1 0.9-65.9 70.4 ± 53.7 9.2-167.2
MWD (mm) by wet sieving
1.56 ± 0.35 1.14-2.02 1.21 ± 0.57 0.60-2.13
Macro-aggregate (%) by wet sieving
30 ± 27 1-87 30 ± 11 20-42
54
Figure 3.6. Bivariate plot of saturated hydraulic conductivity (Ksat) versus bulk density for the Jarrahdale shelf and jarrah forest soils.
Table 3.3. Parameters derived from the single field measurement of unsaturated hydraulic conductivity (Kunsat) at –30 mm tension for the Jarrahdale shelf plots (P3-P7) and for jarrah forest soils, and bulk density.
Sampling plot Bulk density
(g/cm3)
Sorptivity (mm/hr0.5)
Steady-state flow (mm/hr)
Kunsat (mm/hr) at –30 mm tension
P3 1.50 15.2 20.2 17.5
P4 1.51 11.0 8.4 6.1
P5 1.37 17.4 25.9 18.8
P6 1.42 23.1 21.8 11.6
P7 1.50 15.8 15.4 10.8
Jarrah forest 0.71 8.5 42.9 37.9
Bulk density (BD) of shelf soils (0-7 cm depth ) was significantly higher (p<0.01)
(mean 1.36 g/cm3) compared with forest soils (mean 0.90 g/cm3). The difference was at
least partly due to abundant organic matter and plant roots in the forest soils. The shelf
soils essentially consist of exposed laterite subsoil materials (i.e. mottled zone, pallid
zone, saprolite, rock) (Sadleir and Gilkes, 1976; McCrea et al., 1990) and unlike the
jarrah forest soils do not have mature topsoils. The BD values for shelf soils are
0
30
60
90
120
150
180
0 0.5 1 1.5 2Bulk density (g/cm3)
Ksa
t (cm
/hr)
shelfforest
55
comparable to the values for dolerite pallid zone (DPZ) (ranging from 1.14-1.50 g/cm3)
and lower than those for granite pallid zone (1.62-1.85 g/cm3) (McCrea et al. 1990).
There is no systematic relationship between values of Ksat and bulk density (Figure 3.6).
As the Ksat value is not simply related to BD alone it is likely to also reflect soil texture,
pore structure, presence of impermeable layers, and/or the non-wetting property of
surface soil (Klute, 1965; Moore et al., 1998; McKenzie et al., 2002).
Mean-weight diameter (MWD) of soil aggregates is similar for shelf and forest
soils (1.56 mm and 1.21 mm respectively) despite a wider range of MWD for the forest
soils (Table 3.2). The (unexpectedly) higher MWD value of the shelf soil compared
with the forest soil is probably mainly due to the higher gravel content of the shelf soil
(Table 3.1), and not largely related to any improved aggregation of the shelf soils as a
result of fine roots. The exposed subsoils in the railway cutting exhibit some structural
development including aggregate stabilization in which soil particles are bound together
by fine roots of annual and other plants. The proportion of macro-aggregate (i.e.
aggregates larger than 0.250 mm) that are stable during wet sieving (WSA) varied
widely for the shelf soils (1-87 %) compared with the forest soils (20-42 %), however
mean values were similar for the two types of site (30 %). The wide range of values for
shelf soils indicates the diverse conditions on the shelf.
The different underlying parent materials are primarily responsible for the wide
range of physical properties for shelf soils. These properties may be used as soil quality
indicators for site management and rehabilitation. In general low BD values, high
values of Ksat, MWD and WSA and a loamy texture are preferable soil conditions (Lal,
1994; Shukla et al., 2004). Furthermore, these soil attributes are important in
determining plant species recruitment and ecosystem development in general and at the
Jarrahdale cutting site in particular. The soils with low Ksat values are associated with
plants that favor a seasonally wet soil environment particularly the sedge Cyathochaeta
avenacea on deep-clayey substrates, which are also favored by deep-rooted plants
including bull-banksia (Banksia grandis), jarrah (Eucalyptus marginata, and marri
(Corymbia macrophylla). Some shrubs including parrot bush (Dryandra sessilis) are
able to grow on various substrates.
56
3.3.3. Soil acidity and salinity
All soil samples from the Jarrahdale shelf were acidic and more than 80 % of total
shelf soil samples had pH 4.6-5.2. For PMZ soils, pHw (measured in a 1:5 soil to water
suspension) significantly (p < 0.05) decreased in subsurface layers relative to surface
layers. The pH values were similar (p > 0.05) between surface and subsurface soils for
granite plots (Figure 3.7). Surface horizons of shelf soils were more acidic than for the
jarrah forest soils (Table 3.4). For comparison, soil pHw (1:5) for soils from adjacent
rehabilitated bauxite mine sites (7-27 years old) ranged from 5.9-6.3 (Todd et al.,
2000a) and pH values for local native forest and virgin soils were 6.0-6.2 (McArthur,
1991; Todd et al., 2000a). Soil acidity develops naturally due to a number of processes
includes leaching of alkalis and nitrate (Moore et al. 1998). Local species (i.e. mostly
eucalypts, Banksia, Dryandra, sedges and low shrubs) are adapted to these conditions
(Hingston et al., 1981; Ward and Pickersgill, 1985). Several species of low shrubs (e.g.
Leucopon, Hypocalymma) are commonly present in the heathlands across Australia
which exhibits their tolerance of low nutrient status of the soils (Groves, 1981).
Table 3.4. The pHw and EC (1:5) of the Jarrahdale shelf and the jarrah forest soils. For individual soil horizons, mean values followed by the same letters are not significantly different (p > 0.05).
Samples Soil pHw (1:5) EC (1:5) dS/m surface subsurface surface subsurface PMZ 5.13±0.34b 4.91±0.29a 0.053±0.014a 0.053±0.018b
Granite 4.83±0.16a 5.01±0.36ab 0.056±0.013a 0.044±0.013a
Native forest 5.81±0.21c 5.36±0.24b 0.052±0.015a 0.090±0.003c
Soil salinity is not a problem in soils of the study sites as indicated by electrical
conductivity (EC1:5) values less than 0.1 dS/m. Most samples (72 % of total samples)
had EC values between 0.032 and 0.065 dS/m. The EC values were similar for surface
soil samples of different sampling groups (Table 3.4). EC values were mostly slightly
57
higher in surface than subsurface horizons of shelf soils with the reverse trend for jarrah
forest soils (Figure 3.7). In general, soil salinity does not affect plants if EC1:5 values
are less than 0.2 dS/m (Hunt and Gilkes, 1992; Moore, 1998). Soils in the Darling
Plateau region mostly have EC values less than 0.1 dS/m, thus growth of local species is
unaffected by these low EC values (McArthur, 1991).
The low soil salinity of soils in the Jarrahdale region is due to high annual rainfall
(>1100 mm) and excellent internal drainage of the forest soils (Moore, 1998). Minimal
salt accumulation following temporary water-logging and evaporation may occur on
some parts of the shelf but these soluble salts are probably removed in run-off water
during high rainfall events.
Figure 3.7. Bivariate plots of surface versus subsurface values for soil pH and EC values for the Jarrahdale shelf soils and jarrah forest soils.
3.3.4. Total carbon and total nitrogen
The concentration of total soil carbon (TC) for shelf soils differed greatly between
sites and with soil depth (0.87 to 106 g/kg). The very high TC concentration for plot P7
is an outlier as at plot P7 abundant litter (mainly from jarrah) has moderately
decomposed and become mixed with the surface soil. To minimize the effect of macro
fragments of organic material, surface soils containing much litter were initially sieved
(< 0.5 mm) before grinding and analysis with the LECO instrument. Total carbon
obtained in the analysis is likely representing the humified carbon in soil samples.
4.0
4.5
5.0
5.5
6.0
6.5
4.0 5.0 6.0 7.0
Surface pH
Subs
urfa
ce p
H PMZGranite
Forest
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.00 0.02 0.04 0.06 0.08 0.10Surface EC (dS/m)
Subs
urfa
ce E
C (d
S/m
)
1:1 line
1:1 line
58
There was also a large difference in TC between the shelf and the forest soils (mean
values 9.36 and 56.9 g/kg respectively). The bivariate plot shows a nearly 2:1 ratio in
TC between surface and subsurface layers for shelf soils and about 4:1 for forest soils
(Figure 3.8). The large differences in TC between plots is a consequence of different
amounts of plant growth and litter production which is the primary source of soil
carbon. Carbon accumulation in PMZ soils was more abundant probably due to both
higher biomass contributions and less erosion. On the other hand, the granite plot is
situated on gently sloping shelf that was more susceptible to run-off and erosion. It also
supported a relatively low biomass. Todd et al. (2000b) found that total soil carbon
content in an adjacent 9-year old rehabilitated bauxite mine site soil (0-5 cm depth)
varied with sampling time with mean values of 18.6 g/kg for winter and 38.2 g/kg for
summer. The difference in TC values between the sampling times is probably due to
higher rate of soil biomass decomposition induced by warm temperature in the spring
and summer seasons.
Table 3.5. Total carbon and total nitrogen (mean ± standard deviation) of surface and subsurface soils of the Jarrahdale shelf cutting and native jarrah forest.
Samples Total carbon (g/kg) Total nitrogen (g/kg) surface subsurface surface subsurface PMZ 19.7±25.2 7.8±9.5 0.73±0.64 0.40±0.22
Granite 5.6±4.0 3.7±3.6 0.39±0.29 0.24±0.16
Jarrah forest 88.2±61.4 25.6±3.9 3.16±2.26 0.81±0.15
59
Figure 3.8. Bivariate plots for surface and subsurface concentrations of total carbon and total nitrogen of Jarrahdale shelf and jarrah forest soils.
Total nitrogen (TN) was significantly lower for the shelf soils (mean 0.44 g/kg
and range 0.02-2.80 g/kg) compared with forest soils (mean 1.98 g/kg and range 0.64-
6.42 g/kg). Similar to the distribution of total soil carbon, the total nitrogen in PMZ
soils was significantly higher than the value for soils of granite plots. Pre-mining soils
of the jarrah forest typically contain 1.45-1.80 g/kg total nitrogen in topsoil (0-5 cm),
and about 0.5 g/kg in subsoil (20-30 cm) (Ward, 2000). Native forest soils may contain
less total N than soils from adjacent rehabilitated bauxite mine sites, for example Todd
et al. (2000a) found that surface soils of the jarrah forest contained about 1 g/kg of TN
and soils of rehabilitated mine sites contained 1-5 g/kg.
Total nitrogen is related to total carbon by a log/log relationship with a slope of
0.60 showing that the C/N ratio inceases as per cent carbon increases (Figure 3.9).
Values of the C/N ratio of shelf soils are significantly smaller (p<0.01) (PMZ 21±10,
granite 16±7) than the value for forest soils (28±6). For comparison, most topsoils of
WA virgin soils have a C/N ratio of 16-25 (McArthur, 1991); native jarrah forest soils
(0-5 cm) 35-40 and rehabilitated bauxite mine sites 22-39 (Todd et al., 2002a). The
lower C/N for shelf soils relative to forest soils presumably reflects the youth (relatively
less old carbon) of the shelf soils. Carbon tends to accumulate relative to nitrogen in
old soils which is largely related to a higher utilization of nitrogen by plant and biota in
mature soils (Zarin and Johnson, 1995; Berendse et al., 1998).
0
10
20
30
40
50
0 50 100 150 200Surface total C (g/kg)
Subs
urfa
ce to
tal C
(g/k
g)
PMZ
GraniteForest
0
0.3
0.6
0.9
1.2
1.5
0 2 4 6 8Surface total N (g/kg)
Subs
urfa
ce to
tal N
(g/k
g)
1:2 line1:2 line
60
Figure 3.9. a) Log total nitrogen is linearly related to log total carbon for all of the shelf and the jarrah forest soils, b) C/N values tend to increase with total soil carbon.
The results indicate that accumulation of C and N in soils on the shelf is slow with
values being much lower (~25 %) than those of forest soils despite 36 years of litter
accumulation and soil development. If we assume that initial levels of C and N were nil
immediately after excavation, for 5-cm depth soil and bulk density 1 g/cm3, the average
rates of accumulation over 36 years are 0.38 g/kg (~190 kg/ha) of carbon and 0.016
g/kg (8 kg/ha) of nitrogen per annum. In contrast the introduction of mixed species
including legumes to rehabilitated mine sites combined with fertilization rapidly
increases soil carbon and nitrogen levels (Koch, 1987). For the shelf soils, litter in
colluvium from upslope adjacent forest is the dominant source of nitrogen, with some
contribution from volunteer legumes. Unless litter is retained on the shelf, incorporated
into the soil and N released and utilized by plants, spontaneous growth and development
of vegetation will be limited by N availability. There is a diverse occurrence of
volunteer jarrah, marri, Banksia, Dryandra, Acacia (N-fixing legume), heath, myrtle
and sedge colonizing the cutting shelf. Litter from very local sources (Figure 3.10) will
be supplemented by transported litter from adjacent forest as a secondary source of soil
carbon and nitrogen.
a)
y = 0.60 x - 0.88r2 = 0.77
-1.5
-1
-0.5
0
0.5
1
-1 0 1 2 3 Log total carbon
Log total nitrogen
PMZGraniteForest
b)
0
10
20
30
40
50
0 50 100 150 200
Total soil carbon (g/kg)
C/N
PMZGraniteForest
61
Figure 3.10. Litter accumulation consisting mostly of jarrah leaves on plot P7 (left) and litter from a mixed population of marri and jarrah near plot P4 (right).
3.3.5. NaHCO3-extractable phosphorus
Plant-available phosphorus (sodium bicarbonate-extractable P henceforth referred
to as bic-P) is very low for the shelf soils. For shelf surface soils, the average bic-P
concentration was less than 2 mg/kg for both PMZ and granite soils. The mean values
decreased to about 1 mg P/kg for subsurface samples (Table 3.6). The average bic-P
concentration was similar for surface and subsurface layers for granite plots and was
considerably higher in the surface soil for PMZ plots. The surface horizon of jarrah
forest soils contains much higher concentrations of bic-P than subsurface soil due
presumably to greater organic matter inputs and biological activity (Figure 3.11).
Table 3.6. Sodium bicarbonate-extractable phosphorus (mg/kg) for the shelf and jarrah forest soil samples.
Samples N Surface (mg P/kg) N Subsurface (mg P/kg) mean±sd range mean±sd range PMZ 18 1.6±1.0 0.3-4.6 25 0.7±0.3 0.2-1.5
Granite 14 1.1±0.6 0.3-2.3 16 0.9±0.4 0.4-1.6
Jarrah forest 4 4.8±2.6 0.9-6.7 4 1.6±0.8 0.9-2.3
62
Most of soil samples (78 % of total samples) contained < 1.5 mg/kg of bic-P.
Low levels of bic-P are inherent to soils in the region but the values for the shelf are
particularly low. The bic-P concentration of rehabilitated bauxite mines which had
received P-fertiliser was 38 mg/kg (ripline trough, 0-5 cm) 3.5 years after rehabilitation
and values were lower at the ripline crest (ca. 8 mg/kg). The higher bic-P content in
topsoil of rehabilitated bauxite mines is largely related to the application of P fertilizer
in site preparation (Ward, 2000). The bic-P concentration of virgin Darling Range soils
was mostly less than 6 mg/kg in topsoil and less than 2 mg/kg in subsoil (McArthur,
1991).
Figure 3.11. Bivariate plot of bicarbonate-P concentrations in surface and subsurface layers of Jarrahdale shelf and jarrah forest soils.
0
1
2
3
0 2 4 6 8
Surface bic-P (mg/kg)
Subs
urfa
ce b
ic-P
(mg/
kg)
1:1 line
63
Figure 3.12. Bivariate plot of values for log bic-P (mg/kg) versus log total carbon (g/kg) of pallid-mottled zone (PMZ), granitic saprolite, and jarrah forest soils.
The bic-P concentration does not increase systematically with increasing total soil
carbon (Figure 3.12). Logarithmic transformation of data is necessary to reduce data
skewness and create a normal distribution but did not improve the relationship between
bic-P and total soil carbon. For a subset of Darling Plateau soils (n = 19) (McArthur,
1991) comprising topsoil and subsoil horizons, bic-P was closely related to organic
carbon as follows: bic-P (mg/kg)= 0.74 OC (%) + 0.05 (r2 = 0.93). Low phosphorus
availability in lateritic soils is common and thus needs much attention for ensuring
optimum plant growth and production. The problem is primarily due to fixation by Al
and Fe (hydrous)oxides which are major constituents of lateritic soils (Siradz, 1985;
McArthur, 1991).
3.3.6. NaHCO3-extractable potassium
NaHCO3-extractable potassium (bic-K) varied beween PMZ and granite plots but
was mostly similar to values for jarrah forest soils. Mean values of bic-K concentration
for shelf soils were low (< 70 mg/kg) and lower than the bic-K value for many WA soils
(McArthur, 1991; Purdie, 1998). The majority (92 % of total shelf soil samples) had
bic-K values less than 68 mg/kg. Two subsurface samples from granite plots contained
much higher concentrations of bic-K (>120 mg/kg). There are similar mean values of
-1
-0.5
0
0.5
1
-0.5 0 0.5 1 1.5 2 2.5 Log TC (g/kg)
Log bic-P (mg/kg)
PMZGraniteForest
64
bic-K for surface soils of granite and PMZ plots (Table 3.7). The bic-K values were
about 65 % higher for subsurface soils of granite plots than for PMZ plots. The bic-K
concentrations were higher in surface horizons for jarrah forest soils and a few shelf
soils with a reverse trend for most granite and PMZ soils (Figure 3.13).
Table 3.7. Bicarbonate-extractable potassium (mg/kg) for shelf and jarrah forest soils.
Soil parent N Surface (mg K/kg) N Subsurface (mg K/kg) material mean±sd range mean±sd range PMZ 18 33±23 7-93 25 32±13 10-54
Granite 14 37±21 8-84 16 53±50 11-210
Forest 4 57±5 54-65 4 42±18 20-64
Potassium in the soils probably originated in potassium-feldspar and mica (i.e.
mainly from granite) but these minerals are now minor constituents of most soils at
Jarrahdale (Sadleir and Gilkes 1976; McCrea et al. 1990). The low concentration of
potassium in shelf and forest soils is simply a consequence of almost complete
replacement of K-containing primary minerals in these highly weathered materials.
Samples with highest bic-K concentrations represent the subsurface of weathered
granite from plots P2 and P6 where these primary K minerals are abundant. The low
concentration of bic-K in most of the shelf soils may contribute to the poor recruitment
of native plant species on these substrates. There is apparently more bic-K in forest
soils which is presumably a consequence of biocycling under the extensive canopy of
jarrah and other species (Ward et al., 1991; Ward, 2000). The topsoils (0-5 cm) of pre-
mining laterite soils have bic-K concentrations ranging from 85-101 mg/kg, and around
30 mg/kg at 20-30 cm depth (Ward 2000). A large proportion (41 %) of surface samples
of virgin soils in Western Australia contained < 35 mg bic-K/kg (Pal et al., 1999).
65
Figure 3.13. Bivariate plot of surface versus subsurface values for bicarbonate-extractable potassium for the Jarrahdale shelf and jarrah forest soils.
Figure 3.14. Bivariate plots for exchangeable potassium versus NaHCO3-extractable potassium for surface soils (left) and for subsurface soils (right). Lines indicate 1:1 slope.
For non-saline virgin Western Australian soils, the value of bic-K is about equal
to exchangeable K extracted using 1 M NH4OAC (McArthur, 1991; Pal et al., 1999).
Even though some of the present soil samples have a ratio of exch-K/bic-K of about 1,
most soil samples for granite plots in particular have much higher bic-K values than
exchangeable-K values for both surface and subsurface soils (Figure 3.14). The
discrepancy might be attributed to different cations in the extracting solutions (i.e.
AgTU complex for exch-K and Na+ for bic-K) and different displacement of interlayer
0
20
40
60
80
100
0 20 40 60 80 100
Surface bic-K (mg/kg)
Subs
urfa
ce b
ic-K
(mg/
kg)
PMZ
Granite
Forest
1:1 line
surface
0
10
20
3040
50
60
70
80
0 20 40 60 80 100Bic-K (mg/kg)
Exc
h-K
(mg/
kg)
PMZGraniteForest
subsurface
0
10
20
30
40
50
60
70
80
0 50 100 150 200 250Bic-K (mg/kg)
Exc
h-K
(mg/
kg)
66
K from vermiculite and partially weathered mica by these cations. Other workers have
shown that exchangeable K values determined by extraction with NH4OAC and AgTU
methods (Pleysier and Juo, 1980; Searle, 1986) were only moderately well related (r =
0.68-0.73) with mean values of exchangeable K mostly being smaller for the AgTU
method as is reported here.
3.3.7. Exchangeable base cations and CEC
Concentrations of exchangeable cations were classified as low (Moore, 1998) for
most shelf soils. Average concentrations of exchangeable Ca and Mg were
considerably higher for soils on PMZ plots than for soils on granite plots for both
surface and subsurface soil samples (Figure 3.16). Exchangeable K and Na
concentrations were similar for soils from PMZ and granite plots (Table 3.8). Some
surface soil samples of PMZ plots contained relatively elevated concentrations of
exchangeable Ca > 1.2 cmol/kg, Mg > 0.6 cmol/kg, K > 0.12 cmol/kg and Na > 0.2
cmol/kg. The relatively high concentration of exchangeable cations in these samples
might be due to enrichment from inputs such as organic matter, ash and animal waste.
In general, the shelf soils contained much lower concentrations of exchangeable cations
and lower CEC than the forest soils (Table 3.8).
Table 3.8. Exchangeable cations, CEC and base saturation (BS) for surface and subsurface soils from shelf and jarrah forest sites.
Layers Samples Ca Mg K Na CEC BS (cmol/kg) % Surface PMZ 0.61±1.06 0.35±0.32 0.05±0.04 0.08±0.06 4.14±1.83 24±24
Granite 0.11±0.09 0.29±0.17 0.04±0.03 0.09±0.06 3.87±2.80 23±18
Forest 5.06±3.62 1.30±0.80 0.16±0.03 0.25±0.14 9.36±3.87 68±20
Subsurface PMZ 0.22±0.15 0.39±0.33 0.05±0.04 0.06±0.04 3.14±1.20 25±21
Granite 0.13±0.13 0.23±0.13 0.04±0.04 0.06±0.09 2.04±1.22 27±15
Forest 1.16±0.72 0.46±0.13 0.08±0.04 0.06±0.01 7.82±0.96 22±9
67
Exchangeable cation concentrations in the forest soils are comparable with
published values for soils on rehabilitated bauxite mines. For examples, topsoil (0-5
cm) contained concentrations of exchangeable Ca ranging from 1.8 and 1.9 cmol/kg,
and the concentration decreased sharply at 30-35 cm depth. The other base cations (Mg,
K and Na) were at concentrations less than 0.5 cmol/kg for the Jarrahdale and Del Park
bauxite mine sites (Ward and Pickersgill, 1985). The sum of exchangeable bases varied
slightly with the age of rehabilitation ranging from 6.7 cmol/kg (7-year rehabilitated
site) to 7.8 cmol/kg (22-year site) and decreased slightly to 5.2 cmol/kg for the oldest
site (27 year) which was comparable with the native forest at Jarrahdale (5.7-6.6
cmol/kg) (Todd et al., 2000a).
68
Figure 3.15. Bivariate plots of subsurface versus surface values for exchangeable cations, CEC and base saturation of shelf and forest soils. Lines indicate 1:1 slope. Exchangeable Ca data were log-transformed to reduce the effect of a tadpole distribution (highly skewed) of data.
The very low values of base saturation indicate that most exchange sites are
occupied by acidic cations (Al3+ and H+) as is commonly associated with an acidic soil
reaction. There is no systematic increase in base saturation with increasing soil pH for
all shelf soil samples (Figure 3.16). The low concentrations of exchangeable bases,
0
0.2
0.4
0.6
0.8
1
0 1 2 3Surface exch Mg (cmol/kg)
Subs
urfa
ce e
xch
Mg
(cm
ol/k
g)
0
0.05
0.1
0.15
0.2
0 0.05 0.1 0.15 0.2
Surface exch K (cmol/kg)
Subs
urfa
ce e
xch
K (c
mol
/kg)
0
0.05
0.1
0.15
0 0.1 0.2 0.3 0.4 0.5
Surface exch Na (cmol/kg)Su
bsur
face
exc
h N
a (c
mol
/kg)
0
2
4
6
8
10
12
0 2 4 6 8 10 12 14 16
Surface CEC (cmol/kg)
Subs
urfa
ce C
EC (c
mol
/kg)
0
10
20
30
40
50
60
0 20 40 60 80 100
Surface BS (%)
Subs
urfa
ce B
S (%
)
0.01
0.1
1
10
0.01 0.1 1 10 100
Surface exch Ca (cmol/kg)
Subs
urfa
ce e
xch
Ca
(cm
ol/k
g)PMZGraniteForest
69
coupled with acidic reaction may affect the availability of alkali elements to plants and
may inhibit plant colonization.
Figure 3.16. Bivariate plot for base saturation and soil pH for shelf and jarrah forest soils.
Exchangeable base concentration is commonly closely related to other soil
properties, such as organic carbon content (Zarin and Johnson, 1995). However for the
present soils there are different relationships for different sites but mostly these data
show that exchangeable cations are not simply related to clay content (Figure 3.17) or to
soil carbon (Figure 3.18). Generally exchangeable cations increase in quantity with
increasing clay content and increasing soil carbon (McArthur, 1991; Zarin and Johnson,
1995).
For all shelf soils, CEC values ranged from 1 to 9 cmol/kg. The CEC values were
higher for surface soils than for subsurface soils (Table 3.8; Figure 3.15). Two
dominant factors affect CEC, these are clay (content and mineral type) and organic
matter (abundance and composition) (Thompson et al., 1989; Parfitt, et al., 1995; Curtin
and Rostad, 1997). For all shelf and jarrah forest soils, CEC values do not increase with
increasing clay content (Figure 3.19). Soil CEC is low if the clay fraction is dominated
by kaolin (CEC < 15 cmol/kg clay) and by non-clay minerals (Al-Fe oxides/hydroxides)
primarily gibbsite and goethite (Bohn et al., 1979; Tan, 1982). These latter constituents
are dominant in the clay fraction of many soils at Jarrahdale (Sadleir and Gilkes, 1976;
McCrea et al. 1990). Consequently, the CEC is not simply related to clay content.
0
20
40
60
80
100
4 5 6 7Soil pH (1:5)
Base
sat
urat
ion
(%) PMZ
Granite
Forest
70
Figure 3.17. Scatter diagrams for exchangeable cations versus clay content for subsets of soils on pallid-mottled zone (left) and granite (right). Lines are fitted for P4 and P7 data.
y = 0.0085x - 0.0087r2 = 0.62 P4
y = 0.15x - 0.51r2 = 0.66 P7
0
1
2
3
4
5
0 20 40 60
Exc
h C
a (c
mol
/kg)
P1
P3
P4
P7
0
0.2
0.4
0.6
0 5 10 15 20
P2
P5P6
y = 0.024x - 0.096r2 = 0.91 P4
y = 0.042x - 0.0012r2 = 0.64 P7
0
0.3
0.6
0.9
1.2
1.5
0 20 40 60
Exch
Mg
(cm
ol/k
g)
0
0.2
0.4
0.6
0.8
0 5 10 15 20
y = 0.0020x + 0.015r2 = 0.40 P4
y = 0.0050x + 0.00033r2 = 0.88 P7
0
0.05
0.1
0.15
0.2
0 20 40 60
Exch
K (c
mol
/kg)
0
0.05
0.1
0.15
0 5 10 15 20
y = 0.0016x + 0.035r2 = 0.24 P4
y = 0.0084x - 0.0027r2 = 0.90 P7
0
0.1
0.2
0.3
0 20 40 60Clay (%)
Exch
Na
(cm
ol/k
g)
0
0.1
0.2
0.3
0.4
0 5 10 15 20Clay (%)
71
Figure 3.18. Scatter diagrams for exchangeable cations versus soil carbon content for subsets of soils on pallid-mottled zone (left) where the data are log-transformed and granite saprolite (right). Regression lines for plot P7 data.
y = 1.71x - 2.85r2 = 0.81
-2
-1.5
-1
-0.5
0
0.5
1
0 1 2 3
Log
exch
-Ca
P1
P3P4
P7
0
0.2
0.4
0.6
0 5 10 15 20
Exc
h C
a (c
mol
/kg)
P2
P5P6
y = 0.91x - 1.82r2 = 0.83
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0 1 2 3
Log
exch
-Mg
y = 0.69x - 2.37r2 = 0.66
-2.5
-2
-1.5
-1
-0.5
0
0 1 2 3
Log
exch
-K
y = 0.68x - 2.14r2 = 0.73
-3
-2.5
-2
-1.5
-1
-0.5
0
0 1 2 3Log total carbon
Log
exch
-Na
0
0.2
0.4
0.6
0.8
0 5 10 15 20E
xch
Mg
(cm
ol/k
g)
0
0.05
0.1
0.15
0 5 10 15 20
Exc
h K
(cm
ol/k
g)
0
0.1
0.2
0.3
0.4
0 5 10 15 20Total carbon (g/kg)
Exc
h N
a (c
mol
/kg)
72
The contribution of soil organic matter to CEC in soils at the cutting is likely to be
significant. Organic matter is one of main sources of negative charge providing cation
exchange sites in sandy kaolin or sesquioxide dominated soils (Lieffering and McLay,
1996; Fernandez Marcos et al., 1998; Emerson and McGarry, 2003). The higher CEC
value for topsoil is probably related to the higher concentration of organic matter in
surface layers. For all surface soils containing total carbon > 1 g/kg and CEC > 1
cmol/kg, log CEC is linearly related to log total carbon (n = 32) as follows:
Log CEC (mol/kg) = 0.34 log TC (g/kg) + 0.22 (r2 = 0.47). Log-transformation is
required to reduce the effect of data skewness.
Figure 3.19. Cation exchange capacity is not simply related to clay concentration of soils on PMZ and granite plots (left), and tends to increase with total soil carbon concentration (right) excluding samples with CEC < 1 cmol/kg and total carbon < 1
y = 0.059x + 2.95r2 = 0.35
02468
1012141618
0 50 100 150 200Total soil carbon (g/kg)
CE
C (c
mol
/kg)
0
2
4
6
8
10
12
14
16
0 20 40 60Clay (%)
CE
C (c
mol
/kg)
PMZgraniteforest
(McArthur 1991, topsoil n=118)
y = 0.28x + 0.30r2 = 0.36
0
0.3
0.6
0.9
1.2
1.5
0 0.5 1 1.5 2 2.5Log total soil carbon (g/kg)
Log
CE
C (c
mol
/kg)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 0.5 1 1.5 2Log clay (%)
Log
CE
C (c
mol
/kg)
PMZgraniteforest
(McArthur 1991, topsoil n=118)
73
g/kg. Relationships for data for southwestern Australia soils are also shown (McArthur, 1991).
It may be necessary to replenish these deficient cationic nutrients for the shelf
soils so that soil conditions become more favorable for plant growth. Nutrients once
utilized by plant uptake can be returned into soil through biocycling. The higher
concentrations of exchangeable bases and higher CEC of the forest soils are partly
attributable to the higher organic matter content of the forest surface soil (Figure 3.20).
Previous work found that the CEC varied from 6.9 to 7.4 cmol/kg in the topsoil (0-5
cm) of rehabilitated bauxite mines (Ward and Pickersgill 1985). Low CEC values may
reduce the soils capacity to retain added or recycled nutrients so that there is loss of
nutrients by leaching from the nutrient pool (McKissock and Gilkes 1991; Zarin and
Johnson, 1995; Ludwig et al., 1997). An increase in soil CEC for rehabilitated land
such as the railway cutting is therefore a highly desirable objective for improving
retention of cationic nutrients by the soil.
Multiple regression statistical analysis has been utilized to explain variations in
exchangeable bases and CEC. In general, CEC increases consistently with soil carbon
and inclusion of clay concentration as a predictive variable does not significantly
improve the prediction. Indeed in the regression equation CEC is negatively related to
clay and positively to total carbon (TC) as follows:
CEC = (3.54±0.41) + (0.057±0.009) TC − (0.040±0.023) clay (R2 = 0.38).
In contrast, total exchangeable bases is more precisely predicted by a combination of
these factors as follows:
Total base (cmol/kg) = 0.030 clay (%) + 0.066 TC (g/kg) − 0.25 (R2 = 0.87).
74
Figure 3.20. CEC versus total soil carbon for surface soil samples, there is no evident relationship.
Rapid establishment of a vigorous plant community on the shelf is necessary to
quickly increase soil organic carbon and to participate in the recycling of cations and
other plant nutrients. However, the low inherent fertility status of shelf soils limits
initial development of a vigorous native species community. Based on Figure 3.20, a
possible critical threshold for soil carbon is assumed to be 40 g/kg and for CEC is 7
cmol/kg for supporting sustainable plant growth on the shelf. As the initial chemical
and physical conditions of the soil need to be favorable for seedling growth,
management of rehabilitation sites aims to establish site conditions that minimize losses
of soil by erosion, while optimizing retention of litter and water.
3.3.8. Multivariate Analysis
Principal component analysis (PCA) was used to investigate differences in soil
properties between the shelf soils and the forest soils. The analysis utilized soil texture
and chemical analysis data. Twelve soil attributes were utilized, recognizing that
possible co-linearity should be avoided. Therefore, silt is excluded when sand and clay
are considered more important in the analysis (Manly, 1986). Likewise, the analysis
includes total carbon and excludes total nitrogen due to high correlation between these
surface soils
024
68
1012
1416
0 50 100 150 200
Total carbon (g/kg)
CE
C (c
mol
/kg)
PMZGraniteForest
75
two properties. The PCA is based on a correlation matrix, thus automatically
standardizing raw data.
There are four dimensions (components) which have latent roots (Eigenvalues)
larger than unity accounting for 85 % of total variation in soil samples (Table 3.9). The
first dimension is characterized by negative coefficients for all of the variables except
sand, and is dominated by total carbon and exchangeable Ca and Mg. The first
dimension may be related to potential chemical fertility. Forest soils dominate the left
side (negative) due to their higher concentrations of total carbon, bicarbonate-
extractable P and exchangeable Ca, and this situation might be interpreted as being due
to the inter-related nature of these attributes (Figure 3.21). Soil samples from the shelf
are clustered around the origin showing low to moderate concentrations of these
attributes.
The next components of the PCA are related to different soil attributes. The
second dimension is dominated by soil texture. This component is indicative of
physical fertility, water retention and infiltration rate in particular. Some samples of
PMZ soils have high negative scores of PC2 and are clearly separated from the other
PMZ, granite and forest soils. Since the second dimension is confined to particle size
data with opposite signs between the two attributes, it is evident that the positive end is
for soil samples of clayey texture and the negative end is for sandy texture. The third
dimension is indicated by the positive loading of bicarbonate-extractable potassium
(bic-K) and the fourth component by the positive loading of electrical conductivity
(EC). These last two components explain 19 % of the variation in soil samples.
Table 3.9. Latent vectors of the principal component analysis for shelf and forest soil samples from the Jarrahdale sites.
Variable Latent vectors (Eigenvector) 1 2 3 4 sand 0.045 -0.601 -0.040 0.212 clay -0.013 0.593 0.034 -0.266 pH(H2O) -0.189 -0.240 0.418 -0.451 EC (1:5) -0.180 0.247 -0.211 0.662 NaHCO3-P -0.310 -0.185 -0.212 -0.107 NaHCO3-K -0.182 -0.031 0.741 0.305 Total carbon -0.373 -0.118 -0.219 -0.153 Ca -0.389 -0.090 -0.191 -0.206
76
Mg -0.384 0.222 -0.086 -0.122 K -0.359 0.162 0.177 0.101 Na -0.375 0.052 0.176 0.143 CEC -0.304 -0.179 -0.172 0.168 Latent root 5.409 2.520 1.164 1.092 Coefficient of variation (%) 45.1 21.0 9.7 9.1
Figure 3.21. Scores for the first and second PCA dimensions for the Jarrahdale soil samples grouped into PMZ, granite and jarrah forest soils.
In conclusion soil samples on the shelf mostly have similar texture to forest soils
while soil fertility is much lower for the shelf soils. Soil samples from the pallid
mottled zone (PMZ) on the shelf have a wide range of textures compared with samples
from other sites. A large part of the variation between soil samples is thus related to the
various measures of chemical and physical fertility.
-3
-2
-1
0
1
2
3
4
5
6
7
-15 -10 -5 0 5PC1 (45%)
-(TC,Ca,Mg)
PC2 (21%) +clay,-sandPMZ
GraniteForest
77
3.3.9. Clay mineral composition
The clay and non-clay minerals in the clay fraction of samples from Jarrahdale
sites were determined by semi-quantitative XRD analysis using a Philips X-ray
diffractometer (XRD) (Figure 3.22). Major diffraction peaks of basally oriented clays
show the presence of gibbsite (peak 0.485 nm) in many samples and kaolin (peak 0.71-
0.72 nm) for the shelf P4 samples. Relative amounts of clay minerals, boehmite and
gibbsite in each clay sample have been normalized to a total of 100 % based on the peak
areas of major reflections of these minerals and omitting quartz, anatase, goethite,
hematite which are also significant components in some clay fractions (Figure 3.23).
Gibbsite (expressed together with boehmite) is dominant for most samples with a
relative amount ranging from 50-95 % of the clay fraction. Kaolinite is abundant in
samples from P4 (soils on clay-rich pallid zone) reaching 90 % or more. Mostly clay
samples contain less than 30 % kaolinite. A 2:1 clay mineral (vermiculite) is mostly
absent (or present in trace amounts) in the shelf soils, and there is little (< 10 %) in the
jarrah forest soils (Figure 3.24). Illite (mica) was detected in soils on granite plots (P2,
P5 and P6) with various amounts (1-20 %) being present, and it is mostly absent from
the forest soils.
Despite the limited depth of sampling in the present work compared with the
approximately 15-m depth of the weathering profile, the mineralogy is in conformity
with previous work at the same site by McCrea et al. (1990) who found that weathering
of granite produced gibbsite and quartz in the duricrust (ironstone gravel) layer and
mottled zone. Kaolin was abundant in the pallid zone, while quartz was ubiquitous.
Soil profiles derived from dolerite had dominant gibbsite and goethite in both topsoil
and mottled zone, with kaolinite increasing substantially in the pallid zone. Hydrated
(1.0 nm) halloysite and dehydrated (0.72 nm) halloysite were also present in various
amounts in the pallid zone. The abundances of kaolin and gibbsite are reflected by the
low CEC values, especially for soils with low organic matter and clay contents.
78
Figure 3.22. XRD patterns of basally oriented clay fraction of Jarrahdale samples. The symbols are as follows: K, kaolin; V, vermiculite; I, illite (mica); G, gibbsite; B, boehmite; Go, goethite; H, hematite; Q, quartz. Clay-size quartz may be present but the peaks are masked by the peaks from the supporting ceramic plates.
79
Figure 3.23. Ternary diagram of clay fraction mineralogical composition normalized to 100 % for the five minerals indicated on the axes for Jarrahdale samples. Amounts of iron oxides, quartz, anatase, etc were mostly relatively minor and have been omitted.
Iron oxides (primarily goethite with lesser hematite) are present in mottled and
duricrust horizons (Sadleir and Gilkes 1976; McCrea et al., 1990). These minerals were
quite abundant in forest soil samples (BP4) and some shelf soil samples (P43, P51, P62,
P72). These results indicate a greater variability in clay mineralogy of shelf soils
compared with forest soils, which may have contributed to the somewhat different
properties of the shelf soils. To fully investigate phosphorus forms, a Hedley P
fractionation would be needed.
3.3.10. General discussion
Soils on the railway cutting shelf remains low in NPK after 36 years in a non-
rehabilitated, unfertilized condition. Phosphorus is probably the most critical limitation
with an average bic-P concentration of less than 2 mg/kg in 0-5 cm depth soil and about
1 mg P/kg in 5-10 cm depth soil. In general, soils in the region are highly deficient in
phosphorus but the average bic-P concentration is about 5 mg/kg in the surface horizon
of virgin soils of Western Australia (McArthur, 1991). Jarrah forest soils adjacent to
Gibbsite+boehmite
0
10
20
30
40
50
60
70
80
90
100
Kaolinite
0
10
20
30
40
50
60
70
80
90
100
Vermiculite+illite
0102030405060708090100
shelfforest
80
Jarrahdale bauxite mines contain around 3 mg P/kg in the topsoil layers and the P
concentration decreases to 2 mg/kg in the subsurface layers (Ward, 2000). Soil
disturbance due to bauxite mining activity in Queensland altered the distribution of P
between soil fractions and severely reduced plant-available P (Short et al., 1999). It is
possible to supply additional P as fertilizer, but under unfertilized conditions an increase
of plant-available P pool is only achieved through biomass turnover including
introduction of litter.
Soils on the shelf are mostly also deficient in both nitrogen and potassium. Soils
developed on PMZ materials contain more total N (0.7 g/kg) than those on granite (0.4
g/kg). These values are comparable to soils of newly rehabilitated bauxite mines (0.5
g/kg) and are much lower than for old rehabilitated sites (1.5 g/kg) (Ward, 2000) where
nitrogen is provided by N-fixation by native legumes species. Previous work has shown
that the average rate of nitrogen accumulation 12 years after bauxite mine rehabilitation
is about 117 kg/ha per annum (Ward and Pickersgill, 1985; Ward and Koch, 1996)
which can be compared to 7 kg/ha per annum in native jarrah forest (Hingston, 1981).
While litter decomposition is apparent on the soil surface and contributes nutrients to
topsoil, nutrient enrichment in subsoil may also come from root residues (Ward, 2000).
For example, total nitrogen in shallow soils on granite (plot P2) increased from 0.2-0.4
g/kg (subsurface) to 0.4-1.1 g/kg (surface) probably due to moss and lichen
colonization. Similarly, plant-available potassium (bic-K) is deficient in most of the
soil samples on the shelf with an average concentration of less than 70 mg/kg. In
contrast, granite saprolite contains much higher amounts of bic-K with values up to 200
mg/kg. As for phosphorus and nitrogen, biomass cycling is a primary source of soil
potassium except for the soils on granite that contain abundant primary K minerals.
Litter contributes up to 40 % of the potassium-nutrient pool in jarrah forest soils
(O’Connell and Grove, 1996). Therefore, biomass retention and recycling should be
enhanced on the cutting shelf to improve soil fertility status.
Soil texture is the soil property which is most closely related to other soil
properties. Cation exchange capacity (CEC) is mostly low (less than 5 cmol/kg) in shelf
soils and is significantly less than the value for native forest soils in south Western
Australia (up to 10 cmol/kg) (McArthur, 1991). The low CEC of these soils is partly
related to the low clay content which is dominated by Fe-Al oxides and kaolin as the
case at Jarrahdale (Sadleir and Gilkes, 1976; McCrea et al. 1990) and low carbon
concentration in topsoils (less than 30 g/kg). As a result of the advanced weathering
81
status, exchangeable cations and base saturation are low in shelf soils. Texture also
relates directly to soil structure, porosity and drainage as is reflected by highly variable
values of unsaturated hydraulic conductivity (range 6 to 19 mm/hr at -30mm suction)
and saturated hydraulic conductivity (range 1 to 66 cm/hr). Water retention and
available water are smaller for sandy soils than for well structured clayey soils so that
plant survival over dry periods may be reduced for sandy soils. For the railway cutting
regolith, McCrea et al. (1990) found that total water content at saturation (pF 0) ranged
from 18-32 % (w/w) for granite pallid zone (GPZ) and 34-51 % (w/w) for dolerite pallid
zone (DPZ). Much water is retained in micropores less than 0.1 µm diameter and is
unavailable to plants. The average value of plant-available moisture (pF range 2.5-4.2)
was only 4 % (w/w) of saturated water content for GPZ and 7 % (w/w) for DPZ
materials. Therefore, patchy plant growth on the Jarrahdale cutting shelf may be
primarily related to the variability in texture of the substrates and associated variation in
supply of plant available water. Soil texture is however not the sole factor affecting site
colonization by plants.
Soil profile development occurs at rates ranging from decades (Zarin and Johnson,
1995; Néel et al, 2003) to millions of year (Pillans, 1997). For disturbed sites rates of
soil development are highly dependent upon parent materials, environmental conditions
and management practices. Soil recovery is considered to be very slow for non-
rehabilitated sites on the Jarrahdale cutting shelf. Compared with the adjacent
undisturbed jarrah forest soil fertility has shown little recovery over three decades since
excavation. Variability in soil properties is mostly related to underlying parent
materials and is also affected by local relief, vegetation cover and sediment inputs.
Overall results indicate that probably the soil and its biota in the cutting shelf are
below critical thresholds for self-improvement. A critical threshold represents
conceptually a range of values of an index for sustainability, that is the ecosystem does
not require inputs of nutrients, seed, water or other management measures in order to be
self-sustaining (Kearns and Barnett, 1999; Tongway and Hindley, 2000). We can use
any (sensitive) indicator(s) to investigate sustainability. If we put results in a projection
(i.e. trajectory analysis) with time, we can consider an ecosystem evolving towards a
sustainable condition if values of the indicator are above the threshold. For this
particular study a critical value may be defined after regular measurements within a
period of time.
82
Chapter 4. The assessment of soil surface conditions on the Jarrahdale
cutting shelf using Landscape Function Analysis
4.1. Introduction
Soil development on disturbed sites is often initiated by surface stabilization
which is partly due to binding of soil particles by fine roots of annual species, together
with growth of lichens and mosses which may lead to biocrust (cryptogam) formation.
Extensive root interaction often only occurs in the top 10-mm depth of soil (Perez,
1997). Biocrust formation may be inhibited for soils constantly exposed to degrading
processes (e.g. soil erosion). Previous work has shown that disturbances may lead to
changes in composition of soil crust communities. Eldridge and Koen (1998) found that
some lichens and bryophytes were consistently associated with stable sites (e.g.
Xanthoparmelia sp), while others species are associated with unstable sites (e.g.
Heterodea beaugleholei).
Protection against rain-splash erosion is necessary to minimize losses of soil
particles, nutrients, viable seeds and water. The protection may come from rock
fragment, logs and branches, or low shrubs and perennial grasses (i.e. less than 0.5 m
height). A simple technique of placing piles of branches proved useful in providing
multiple benefits including soil protection against rain-splash erosion, promotion of
water infiltration, retention of soil particles, seeds and nutrients, and moderation of soil
temperature (Tongway and Ludwig, 1996). Spatial soil resource control is essential to
ensure that nutrients are retained and utilized for plant growth and that soil particles and
water are conserved. Resource regulation may be controlled by micro-relief and
vegetation (Tongway and Ludwig, 1998). This is particularly beneficial for soils in a
high rainfall area such as Jarrahdale, Western Australia.
Soil conditions on disturbed sites change with time at a variable rate. The
improvement of conditions can be expressed by a substantial increase in the nutrient
pool (e.g. total nitrogen, available phosphorus), or by other soil indicators. Changes in
these soil properties can be related to soil surface and landscape attributes. Therefore,
an assessment of soil surface conditions is an important step in describing the extent of
soil recovery that might have occurred at disturbed sites.
83
Various methods have been developed as tools for assessing ecosystem recovery
and soil conditions after disturbance. Various parameters are used by each method as
indicators of soil and habitat recovery including ants (Folgarait, 1998; Majer and
Nichols, 1998; Bisevac and Majer, 1999), avifauna (Whitford et al., 1998; Armstrong
and Nichols, 2000; Passell, 2000), amphibians and invertebrates (Galan, 1997; Zaady
and Bouskila, 2002), and soil surface conditions (Tongway and Hindley, 1995). Despite
a wide range of parameters used in the analysis, interpretation and prediction of site
evolution, the common ground is to assess whether the present landscape condition is
progressing toward a sustainable ecosystem. Re-establishment of a sustainable
ecosystem needs vegetative diversity and productivity that are suitable for the
prescribed final use. This requirement is equally applicable for mine site and
agricultural land (Jasper, 2002).
Developed initially for tropical grasslands in Australia, the procedure of
Landscape Function Analysis (LFA) (Tongway and Hindley, 1995) has been adapted
for the assessment of disturbed sites representing a wide range of mine types, climates
and soil types across the Nation and overseas (Kearns and Barnett, 1999; Palmer et al.,
2001; Rezaei, 2003; Tongway et al., 2003). The method has a strong ecological basis
and it is quite simple, practical and reliable. The LFA module records 11 soil surface
features and the surface soil is used in assessment ranging from soil cover to slake test
and texture. Three landscape indices (stability, infiltration and nutrient cycling) can be
derived by combining several features. Data accession in the field follows the “nested
spatial hierarchy” that consists of hillslope scale and patch scale.
This chapter particularly investigates the spatial variation in soil surface indicators
measured by the landscape function analysis (LFA) method over a range of sites
representing both a horizontal transect (i.e. along the shelf) and a vertical direction (i.e.
up slope on the embankment) of the railway cutting near Jarrahdale Western Australia.
4.2. Materials and method
4.2.1. The basic of landscape function analysis
Ecosystem function analysis (EFA) consists of three modules, i.e. landscape
function analysis (LFA), vegetation analysis and habitat complexity. Landscape
Function Analysis was originally developed from chenopod shrublands, mulga
84
woodlands and arid grasslands (Tongway, 1994), then expanded with a fuller
explanation on the calculation of landscape indices (Tongway and Hindley, 1995).
Observation is primarily focused on the LFA module for each transect. All modules
may be used in a landscape observation if the interest is also to investigate plant
development with time and the extent of environmental niches for fauna development
(Tongway and Hindley, 2000). The LFA procedure consists of three steps. The first
step is to define site characteristics which focus on landform (shape and slope) and soil
texture profile providing a broad pattern of resource retention and soil cover. The
second step is to characterize landscape organization. This is done by establishing
transects orientated along the maximum slope so that it is possible to capture maximum
variation in soil resources. However, for particular purposes the transect direction
might be established arbitrarily depending upon slope characteristic. Observation starts
with recognizing soil surface zones which are distinguished broadly into sink (run-on)
and source (run-off) patches and named according to the constituents, e.g. shrub/litter
complex or bare soil (Figure 4.1). There is no rigid rule for naming such a zone. The
purpose of naming is to be able to distinguish between different patches and/or
interpatches.
Sink zone Length
Sink zone Width
Start
50 metresshown
Biological sink zones canbe grass, trees, shrubs, logsor any combination.
Litter accumulationaffects sink zone size
10
20
30
40Observation line
Runoffzonelength
Figure 4.1. An example of LFA transect observation showing a sink-source pattern (Tongway and Hindley, 2000).
85
The third step is to assess soil surface indicators using the standard scoring
procedure as set out in the manual (Tongway and Hindley, 1995). The scores for litter
cover, origin and decomposition have been modified in the 2004 edition/revision
(Tongway and Hindley, 2004). Surface features range from soil cover against rain-
splash erosion (e.g. rocks, logs) to soil surface texture (4 classes as related to relative
infiltration rate) which can be combined to produce three landscape indices namely
stability, infiltration and nutrient cycling (Table 4.1). Certain features may be absent
and are recorded as nil (not applicable). Any features with a “not applicable” score will
be excluded automatically from the calculation of landscape indices. Sufficient
replicates, at least three, of each identified zone, are required to enable statistical
interpretation.
Table 4.1. Soil surface features used for the assessment of soil surface condition in Landscape Function Analysis and landscape indices derived from these features (Tongway and Hindley, 1995). Surface features Score Stability Infiltration Nutrient
cycling Soil cover 1-5 √ Basal cover of perennial grass or canopy density of trees and shrubs
1-4 √ √
Litter cover (simple) 1-10 √ √ Litter cover, origin and decomposition
1-30 √
Cryptogam cover 1-4 √ √ Crust brokenness 1-4 √ Erosion severity 1-4 √ Deposited materials 1-4 √ Surface roughness 1-5 √ √ Surface nature 1-5 √ Slake test 1-4 √ √ Soil surface texture 1-4 √ Total score 8-40 5-27 4-43
Following is the detail of keys to assessment of soil surface conditions as developed by
Tongway and Hindley (1995).
1. Soil cover is used to assess soil surface vulnerability to rain-splash erosion. Soil
surface protection is by rocks, logs and other stable structures and excludes soft
ephemeral herbage, foliage >0.5m height, and litter.
86
Projected cover (%) Rating Class < 1 insignificant 1
1-15 low 2 15-30 medium 3 30-50 high 4 > 50 very high 5
2. Basal and canopy cover is used to assess the contribution of root biomass to
nutrient cycling processes. The value is estimated by basal cover of perennial grass
or canopy cover of shrubs and trees.
Basal/canopy cover (%) Rating Class
< 1 insignificant 1 1-10 slight 2 10-20 moderate 3 > 20 high 4
3. Litter cover is used to assess the availability of surface organic matter for
decomposition and nutrient cycling. The score for nutrient cycling index (NCI) is
obtained using weighting factors for litter source (1 for transported; 1.5 for local
source) and degree of incorporation ranging through nil (N=1), slight (S=1.3)
medium (M=1.7) and extensive (E=2). For example, a surface zone with 4LM
notation means that the litter cover is 50-75 % from local sources and moderately
incorporated into the soil, and the score for NCI is (4x1.5x1.7) = 10.2.
Litter cover (%) Class Litter cover (%) Class < 10 1 100, < 2cm thick 6
10-25 2 100, < 7cm thick 7 25-50 3 100, < 12cm thick 8 50-75 4 100, < 17cm thick 9 75-100 5 100, > 17cm thick 10
4. Cryptogam cover is used as an indicator of surface stability, resistance to erosion
and nutrient availability. It excludes self-mulching clay, and thick litter bed (noted
as not applicable and scored as zero).
87
Cryptogam cover (%) Rating Class < 1 insignificant 1
1-10 slight 2 10-50 moderate 3 > 50 extensive 4
5. Crust brokenness is used to assess the unconsolidated (loose) crusted materials
susceptible to wind and water erosion. It excludes >75% eroded material, self-
mulching soil, loose sand, tracks (noted as not applicable).
Crust brokenness Class Extensively broken 1 Moderately broken 2 Slightly broken 3 Intact 4
6. Soil erosion severity is used to assess the nature and severity of current soil erosion
features compared with reference pictures. This indicator is used to infer instability
on the study transect. Forms of erosion include rill and gully, terracette, sheet,
scalding, hummock, and pedestal. If there is a sign of soil erosion developing, the
obtained score reduced by 1 unit showing an unstable condition.
Erosion severity Class Extensive 1 Moderate 2 Slight 3 Insignificant 4
7. Deposited material is used to estimate the quantity of alluvial deposits on the study
transect. This indicator is used to infer instability upslope. The forms include
alluvial fan and hummock on landscape. Accumulated materials may progress
toward stabilization.
88
Eroded material (%) Rating Class
>50 extensive 1 20-50 moderate 2 5-20 slight 3 < 5 insignificant 4
8. Surface roughness is used to assess micro-relief features for water infiltration, flow
disruption and seed retention. The forms include gilgai, cracking clays, sink hole,
depression (micro-relief ). Surface obstructions such as densely growing tufted
grass plants also qualify.
Surface roughness Micro-relief (mm) Class Smooth (e.g. scald surface) < 3 1 Shallow depressions 3-8 2 Deeper depressions 8-25 3 Deep visible base 25-100 4 Very deep, extensive features (e.g. gilgai, sink-holes, deep cracks)
> 100 5
9. Surface nature is used to assess surface resistance against mechanical impact and
erodibility. It is best determined using dry soil and recorded as crust flexibility,
brittleness and hardness including subsurface crusting. Root abundance is also
noted.
Surface nature Class
Loose-sand over non-coherent sand 1 Easy broken crust (finger) over non-coherent subsurface 2 Moderate crust (plastic tool), brittle over coherent subsurface 3 Very hard crust (metal tool), brittle over hard-coherent subsurface (a typical scald surface)
4
Non-brittle, some flexible or self mulching, over sub-coherent or strong crumb; highly organic
5
10. Slake test is used to assess soil stability and dispersion under wet conditions
(simulating rainy days). It is conducted by immersing replicates samples of dry soil
aggregate (ca. 1-2 cm) into a container filled with deionised (rain) water. The result
may be compared with reference pictures. This is a simplification of the Emerson
dispersion index.
89
Slake test result Class Collapse <5sec, shapeless (very unstable) 1 Collapse (5-10sec), 50% slumps (unstable) 2 Crust surface intact, subsurface aggregate slumps < 50% 3 Whole intact > 5 min 4
11. Soil surface texture is measured using the hand-texture method and the result is
related to soil permeability. Please note that self-mulching, cracking clay soils have
a class 3 due to their moderate infiltration rate. Surface texture is related to
infiltration and water storage.
Surface texture Infiltration Class Silty clay to heavy clay Very slow 1 Sandy clay loam to sandy clay Slow 2 Sandy loam to silt loam Moderate 3 Sandy to clayey sand High 4
4.2.2. Observation transects
The study was undertaken at a railway cutting shelf near Jarrahdale bauxite mine,
Western Australia. To capture variation in soil surface conditions in a horizontal
direction, a single 300-m transect was established along the cutting shelf. The transect
was divided into 50-m intervals for continuous observation (Figure 4.2). Soil surface
condition was assessed for each zone according to the manual (Tongway and Hindley,
1995). Resources movement on the shelf occurs predominantly due to slope gradient
and is facilitated by the ridge (embankment) along the shelf margin. Resource
movement in a horizontal direction is limited on the nearly flat surface of the cutting
shelf but movement down the embankment is significant.
90
Figure 4.2. Transect layout in a horizontal direction along the bench showing vegetation and soil patches, and locations of sampling plots used for describing lateritic regolith properties.
In addition three short transects (15-25 m long) were also established parallel to
the slope for the granite plot (P2), pallid-mottle zone (PMZ) with low shrub (P3) and
PMZ colonized by Banksia grandis (P4); general view of these plots is presented in
Figure 4.3 showing the upper slope and the bench (shelf). These transects are utilized to
describe soil resource regulation in the ‘vertical’ direction (down-slope). The upper and
lower slopes of the shelf are steep (~35-40 degrees) with the slope length varying from
4 to 15 m. Soil resources movement on the sloping surface is active which limits
resource accumulation on the shelf.
Figure 4.3. View of the plots for vertical transect observation across slope and shelf surface.
Another transect located in the upslope jarrah forest was treated as analogue site.
Comparison with an analogue is recommended to obtain a reference value, representing
a long-term target value for the assessment of trend or trajectory analysis (Tongway et
al., 1997). The reference site is usually an undisturbed ecosystem within local
landscape which is assumed or agreed to be the state achieved at the end of natural or
managed rehabilitation.
0 m 50 100 150 200 250 300P1 P3 P4 P5 P6 P7
Low shrubs, sedgeduricrust surface
GranitoidP2
Low shrubs,sheoak litter
Jarrah interstratifiedwith banksia
Banksia
Marri
sedge Sedge patch,a few < 1 m jarrah
Dryandra on saprolitegranite, gently slope
Mixed treeson embankment
Bare soil, gravelcolluvium, jarrahseedling
Sedge,litterTrough
NE
91
4.3. Results and Discussion
4.3.1. Landscape organization and indices in horizontal direction
Resource regulation in the field reflects the landscapes capability to intercept,
retain and utilize soil resources. This is shown by several landscape parameters related
to surface zones (Table 4.2). The focus is emphasized on the number and dimension of
zones able to retain the resources. Therefore, parameters related to the number and
dimension of sink (run-on) zones are the key in assessing landscape functionality. The
current LFA methods have standardized on patch (= run-on, sink) and inter-patch (=
run-off, source).
Table 4.2. Landscape parameters in a horizontal direction.
Transect section (m)
Number of sink /10 m
Total sink width
(m/10m)
Obstruction index (%)
Number of inter-patch zone/10m
Mean inter-patch length (m)
0-50 3.6 2.08 13.6 3.8 2.27
50-100 4.2 3.02 48.5 3.6 1.43
100-150 1.6 1.73 47.6 1.4 3.74
150-200 1.8 1.64 34.8 1.8 3.62
200-250 1.4 2.18 50.0 1.8 2.78
250-300 2.0 2.26 29.9 1.6 4.38
Obstruction index (i.e. the proportion of sink (run-on) zone to total length of
observation) provides an estimate of a transect covered by surface zones able in some
way to retain soil resources. Potential resource retention increases with increasing
values of the obstruction index, which is high in the 50-150 m and 200-250 m sections
of the horizontal transect. A trough created by a ripping process is also considered as a
sink irrespective of whether it is vegetated or barren as long as it has the capacity to
capture passing resources. Surface ripping as practiced in rehabilitated mine sites
provides a high obstruction index due to the rip-lines. There is a trend of more sinks
over the 0-100 m interval and fewer in the 100-300 m interval. The higher number of
sink is related to the presence of low shrubs and woody species (trees). Total sink width
92
may not be linearly related to obstruction index or to the number of sinks. For example,
the less abundance of sinks (1.6/10 m) with higher obstruction index (47.6 %) at the
100-150 m section may indicate a better resource regulation than for the 250-300 m
section (obstruction index 29.9 %). Values of mean inter-patch length (run-off zone)
indicate the average size of void surface and the value depends on the number of
interpatch zones. It is suggested that obstruction index and interpatch attributes should
be utilized in assessing soil surface condition. By combining these parameters for
example, it can be deduced that resources are unlikely to be well retained in the 0-50 m
and 250-300 m sections.
Soil surface zones of the cutting shelf are simply grouped into six types (Table
4.3). Bare soil is invariably the largest zone of the shelf ranging from 44 to 86 % of
each transect interval. The bare soil zone may vary from simply bare surface soil
exposed by excavation of the cutting to a surface covered by colluvial gravel or litter.
Therefore, the soil surface of a bare soil zone may be protected against rain-splash
erosion if there is a significant cover of stable materials (e.g. rock fragments, branches).
A bare soil zone simply indicates a lack of vegetation cover. The tree/shrub-litter
complex varied widely in occurrence and it was substantial for the 50-100-m section
where jarrah and Banksia are growing well. Sedge tussock commonly occurs on pallid-
mottled zone presumably reflecting the soil water status of these sites. In general
resource regulation is confined to limited parts of the shelf and a large proportion of the
shelf is poor in resources.
Table 4.3. Mean values of soil surface zones identified for the horizontal transect.
Mean values (%) of coverage Transect section (m) Bare soil Tree/shrub
litter Sedge
tussock Log-litter Ridge/
bank Depression/
trough 0-50 86.4 6.0 4.2 3.4 - -
50-100 51.5 48.5 - - - -
100-150 52.4 32.2 15.4 - - -
150-200 65.2 4.6 30.2 - - -
200-250 44.2 28.6 - - 5.8 21.4
250-300 70.1 - 9.5 20.4 - -
Individual values of landscape indices are combined using the proportion of these
zones to produce the indices for the whole shelf landscape. There is an S-form pattern
93
of landscape indices observed along the cutting shelf. The S-form shows an increase in
an index value at the 50-150-m section, then the value decreases at the 150-250-m
section, and finally the index returns to a similar level at the 250-300 m section of
transect (Figure 4.4).
The values of individual indices vary by up to 10 % between the transect
intervals, which reflects characteristics of the dominant surface zones, i.e. bare soil,
tree/shrub-litter complex and sedge tussock for the whole shelf landscape. For newly
disturbed land, minimum values of LFA indices estimated using scores of Table 4.1
would be about 20 % for soil stability, 18 % or higher for infiltration and 9 % for
nutrient cycling index (NCI). Taking these presumed minimum values, recovery of the
site is nearly concurrent for these indices. The large range in NCI values is likely to be
due to the poor quality of the bare soil zone dominating the landscape.
Figure 4.4. The values of stability, infiltration and nutrient cycling (NCI) indices for 50-m intervals of the shelf compared with values for the jarrah forest.
The Landscape Stability Index (LSI) for the shelf (mean 61 %) is quite close to
the value for jarrah forest sites (75 %). It means that soil surface at the shelf is more
protected and more resistant to disrupting force (e.g. rainfall). Infiltration (mean 49 %)
and nutrient cycling indices (mean 28 %) for the shelf are considerably lower than
values for the jarrah forest site (infiltration 68 %, NCI 49 %) largely due to differences
in litter abundance and vegetation cover. The cutting shelf has gradually evolved to the
functionality of the benchmark state (e.g. jarrah forest). Spontaneous recovery at
disturbed sites is improved by a suitable geotechnical preparation at the beginning that
sets a favorable-baseline condition for soil and plant development. This strategy should
0
10
20
30
40
50
60
70
80
0-50 50-100 100-150 150-200 200-250 250-300 ForestShelf position (metre)
LFA
indi
ces
(%)
stabilityinfiltrationNCI
94
promote ground cover and plant growth and minimize erosion, for example use of
perennial grasses, low shrubs and plant residues together with ripping the soil surface to
create micro-relief which enhances interception of surface run-off water and provides
greater infiltration, and prevents nett export of resources from site.
4.3.2. Down-slope variation in landscape parameters
Resource movement across a landscape is closely controlled by topography. For
this purpose, soil surface assessment was also conducted in a vertical direction in order
to capture down-slope variation in landscape parameters. Three short transects were
located across the granite plot (P2, 12 m), lateritic gravel (P3, 15 m) and pallid-mottled
zone (P4, 25 m) (Figure 4.5). The assessment of soil surface condition is similar to that
used for the horizontal transect.
Figure 4.5. Diagram of vertical transects parallel to steep slopes and across nearly flat surface of the cutting shelf.
Landscape parameters indicate different conditions of resource retention in a
vertical direction between the shelf transects and in comparison with jarrah forest (Table
4.4). A smaller number of sinks (1.7/10 m transect) was observed for the P4 site
showing a lack of vegetation cover and accumulation zone relative to the transect
Rhodes Ridge
Base of cutting
Lower slope ~35º
Upper slope ~35º
Nearly flat shelf surface
Granitoidvertical
P4 P3 P2
transect
embankmenttransect
transect
95
length. Values of mean interpatch length also suggest similar conditions. Due to its
shape and position, the cutting shelf is also considered as a sink and thus affects the
value of obstruction index. Total sink width is mostly determined by the shelf
dimension. Low values of obstruction index (14-30 %) suggest a potential loss of soil
resources in major rainfall events.
Table 4.4. Landscape parameters and land surface zones on down-slope transects on the shelf compared with jarrah forest at Jarrahdale sites.
Down-slope transect Parameter P2 granite P3 heath P4 Banksia Jarrah forest
Number of sinks /10 m 3.3 3.3 1.7 2.4 Total sink width (m/10 m) 7.46 2.87 6.64 4.98 Number of interpatch/10 m 4.9 4.7 2.5 1.0 Mean interpatch length (m) 1.43 1.61 3.37 3.16 Obstruction index (%) 29.5 24.7 14.0 68.4 Land surface zones: Bare soil (%) 55.7 62.7 82.6 31.6 Tree/shrub litter complex 13.1 10.7 4.7 25.2 Sedge tussock - - - 34.8 Log-litter - - - 8.4 Ridge/embankment 14.8 12.7 3.4 - Depression/shelf 16.4 14.0 9.4 -
Plant-associated (i.e. tree/shrub litter) zones are minor for the down-slope
direction comprising 13 % or less of transect length; the bare soil zone is dominant on
the slope consisting of 56 % or more of transect length. These values indicate that the
cutting shelf is still experiencing poor resource regulation due to the steep slope of the
local landscape, particularly if the condition is compared with the nearby jarrah forest.
The jarrah forest has much better resource regulation as indicated by a high value
of obstruction index (68.4 %) due to the higher occurrence of plant-associated zones
comprising up to 60 % of the transect length with a significant contribution of
understorey species. Tussock represents either sedge clumps alone or in association
with creepers. The jarrah forest floor has some open space with bare soil although the
zone is under a dense canopy of tall jarrah trees and other woody perennial species.
Low resource regulation results in low values of landscape indices on the shelf
relative to jarrah forest. The values are significantly lower for the slope transects on the
96
shelf compared with LFA indices for jarrah forest. For the stability index, the difference
is about 20-30 % (Figure 4.6). A lower value of stability index may indicate a condition
that is more vulnerable to erosion. The data also show a large difference in infiltration
index (about 30-40%) between the shelf and the forest sites. The contrast is due to
differences in litter abundance and soil texture. The infiltration index provides an
estimate of the soils capability to infiltrate rainfall and store water. Nutrient cycling
index (NCI) is much lower (less than 20 %) for the shelf. The NCI value is largely
affected by litter characteristics. The litter has been slightly to moderately decomposed
in the jarrah forest compared with that on the cutting shelf. Litter distribution is very
limited on the bench and is mostly along the foot slope. Biomass contribution to the
slope is from colonizing plant species or has been transported from the upper slope
vegetation.
Figure 4.6. LFA indices down-slope across three plots compared with indices for jarrah forest.
There is no absolute numerical category for site classification into poor, moderate
or good condition solely that is based on landscape indices. Values for analogue sites
may differ for different mine sites as affected by local climate and vegetation type. For
example the following data (Table 4.5) are a summary of LFA observations conducted
at a rehabilitated nickel mine sites in Kambalda, Western Australia with annual rainfall
260 mm (Kearns and Barnett, 1999) and rehabilitated coal mine sites in Bowen Basin,
in central Queensland with annual rainfall 625 mm (Tongway et al., 1998). Bauxite
mine sites at Jarrahdale have much higher annual rainfall (1000-1200 mm) and support
a dense forest compared with mine sites in arid and semi-arid regions. Consequently
0
10
20
30
40
50
60
70
80
P2 granite P3 heath P4 Banksia forest
LFA
indi
ces
(%)
stabilityinfiltrationNCI
97
the LFA indices are significantly higher for the Jarrahdale analogue site than the
Kambalda and Bowen Basin sites. The values for the cutting shelf are however similar
to those for the nickel mine site at Kambalda and analogue and new rehabilitation sites
in the Bowen Basin. The significance of the numerical values is site-restricted, thus a
direct comparison between sites should be exercised with precaution.
Table 4.5. LFA indices for Jarrahdale shelf and mine sites in Australia.
Location Sites LFA indices (%) Stability Infiltration NCI Kambalda Rehabilitation 47 45 19
Analogue 53 40 20
Bowen Basin New rehabilitation 40 40 15
Old rehabilitation 70 50 35
Analogue 55 45 25
Jarrahdale Jarrah forest (analogue) 75 68 49
Shelf (horizontal) 61 49 28
Shelf (vertical) 49 34 17
4.3.3. LFA infiltration index in relation to unsaturated hydraulic conductivity
There is a need to use indicators as surrogates for environmental variables that are
impossible or difficult to measure. A reliable indicator should have a predictive capacity
over a wide range of soil conditions. However, for extreme conditions the prediction
may fail. Thus it is valuable to know if infiltration index calculated by the LFA
procedure is closely related to actual soil infiltration. For this purpose, unsaturated
hydraulic conductivity was measured in the field following the procedure of McKenzie
et al. (2002) and soil surface condition was assessed according to Tongway and Hindley
(1995). The use of unsaturated flow for infiltration assessment should mimic what
happens in nature. For combined shelf and jarrah forest data (n=6), LFA infiltration
index tends to increase with higher values of unsaturated hydraulic conductivity in the
field (Figure 4.7) but there is not a close relationship. It is not surprising that a poor
correlation exists between LFA infiltration index and Kunsat, as the infiltration index is
determined by a range of surface soil factors (such as cover, cryptogams, micro-
98
topography, texture), whereas Kunsat is mainly related to texture. It would have been
better to relate LFA infiltration index to field measurements of Kunsat done with the disc
permeameter. The surface of jarrah forest soils exhibits a favorable condition for water
infiltration as shown by relatively high values for these infiltration attributes that is
mainly due to porous and granular soil structure. To confirm this result for the whole
landscape, an extensive measurement is required across various soil surface conditions.
Nevertheless, LFA is intended for use across the full range (32-72 here), not for looking
at close correlations between similar sites.
Figure 4.7. Bivariate plot for LFA infiltration index and values of unsaturated hydraulic conductivity (steady-state flow rate) for Jarrahdale soils.
Ecosystem recovery is an ultimate goal in both naturally and assisted
rehabilitation after disturbance. The extent of recovery to prescribed land end-uses can
be evaluated and monitored using various methods and indicators. It is suggested here
that landscape function analysis is quite simple, practical and ‘reliable’ for assessing
soil surface conditions. Resource regulation is easily captured by field observations and
the indices produced from a set of surface zones may be used as estimates of landscape
integrity. Parts of the cutting shelf are developing toward a more sustainable condition
while other parts are still under-resourced.
0
20
40
60
80
0 10 20 30 40Kunsat (mm/hr) at -30mm tension
LFA
infil
trat
ion
inde
x (%
)
Shelf
Forest
99
Part 2. Natural rehabilitation of a gold mine waste dump in an arid
region of Western Australia
The second part of this thesis describes fieldwork which evaluates a natural
rehabilitation process at a gold mine waste dump at Scotia (near Norseman), Western
Australia. This site is an example of mine site rehabilitation under arid conditions
where pioneer plant growth relies on the quality of materials used to prepare the waste
dump. Two factors are considered particularly important in determining successful
spontaneous recovery at Scotia; these are salinity and available water. Consequently
plant colonization reflects species tolerance of these limiting factors.
Rainfall harvesting is most crucial to ensure water availability for plant growth
under an arid environment. Therefore, the mining company built a geotechnical
measure in the form of a semi-radial internal drain structure across the dump. The
structure was made mainly from various rock fragments. Spontaneous site colonisation
by several local species occurs mostly near and along the drain structure. A number of
salt-tolerant species occupy many parts of the dump.
Soil development was assessed by analysing basic soil properties along with
landscape indices that provide a baseline for assessing natural rehabilitation. Soil
conditions at the dump were compared with adjacent woodland soils. The focus of this
research is thus to examine the extent of rehabilitation success of a gold mine waste
dump under a natural condition. The results are presented in Chapter 5.
100
Chapter 5. Integrating landscape indices and soil properties for
assessing spontaneous soil and ecosystem development on a waste
dump at the Scotia gold mine, Western Australia
5.1. Introduction
Spontaneous growth of native plant species and soil development on disturbed
sites, especially on mine sites, has been little studied, in contrast to responses to active
rehabilitation techniques that have been intensively studied on many disturbed sites.
Revegetation of disturbed sites using a mixture of a large number of plant species is a
common practice. Plant species for site rehabilitation may be indigenous to the locality
or introduced, as for example the rehabilitation of a gold mine spoil (Osborne, 1996),
bauxite mines (Ward and Koch, 1996; Ward, 2000), and a lignite mine (Schulz and
Wiegleb, 2000). Various cultural practices including fertilizing are usually employed.
In contrast, natural (spontaneous) rehabilitation may also provide quite
satisfactory remediation of disturbed sites although establishment of plant cover by this
method may take a considerably longer period and outcomes may not be easily
predicted due to exposure to risk of failure during the long slow development
(Schmeisky and Podlacha, 2000). Williams (1997) reviewed disturbed sites around the
world and found that natural rehabilitation induces a more stable landscape, owing
partly to less compaction by machinery and provides more favorable niches for species
diversity on abandoned sites.
Another issue in mine spoil rehabilitation is how to monitor progress. Procedures
to be used in monitoring should be practical, quick, unambiguous, and repetitive.
Tongway and Hindley (1995) originally developed the Landscape Function Analysis
(LFA) technique for rangelands in Australia, but now it has been revised for use on
mine sites (Tongway and Hindley, 2004). Although the analysis is quite reliable,
examples of its application to mine sites are still limited, and more fieldwork is required
to validate the technique.
I studied natural rehabilitation of a 15-year old waste dump at the Scotia gold
mine (Norseman, Western Australia), as an example of spontaneous growth and soil
development in an arid environment. The main purpose of this study is to evaluate soil
properties, vegetation patterns and landscape indices of the waste dump using LFA
101
indicators. The results are compared with analogue sites in the adjacent (unmined)
native eucalypt woodland which had been grazed previously by native animals.
5.2. Materials and Methods
5.2.1. Study area
The study site is located at the Scotia gold mine waste dump near Norseman,
Western Australia, approximately 760 km south-east of Perth. The site has been left
undisturbed in the mining modified landscape for about 15 years. The waste dump and
pit lie between 121°47′ to 121°48′ E and 32°28′ to 32°29′ S (approximately AMG
Reference 386000mE/ 6406000mN Zone 51) (Figure 5.1.).
Figure 5.1. Site map of Scotia waste dump showing transect lines crossing the main drainage.
The waste dump consists of diverse mixtures of weathered and fresh mafic and
felsic rocks with particle sizes ranging from clay to boulder from the mine pit. The
dump extends over several hectares and is approximately flat topped with steeply
sloping sides. The Scotia waste dump is thus in the form of a plateau with an almost flat
surface. The top of the dump has been colonized by several volunteer perennial and
annual plant species. However, these species are distributed in a patchy pattern that
102
may reflect spatial variations in soil fertility at the site. Because of its high position in
the landscape, the top of the waste dump does not receive inputs of sediment and relies
on its inherent fertility to support plant growth. Thus it is an essentially closed system
receiving little inputs, but erosion from the dump may contribute considerably to the
surrounding sites, especially on the sloping sides of the dump.
The Norseman region comprises the eastern border of the Yilgarn Block, a major
geological feature. This Archaean Craton mainly consists of a greenstone belt within
extensive granitoids and various grade of gneiss (Swager et al., 1995). The oldest rocks
form a thick sequence of sandstones, quartzites, mudstones and conglomerates with
some interlayered basaltic lavas and intrusive dolerites (mainly sills). This formation is
overlain by a great thickness of Archaean basaltic rocks and the rocks have been
multiply folded and fractured to present a complex subsurface geology. Gold occurs in
several of these rock types. Some of these rocks and their saprolites are represented by
the materials in waste dump (Figure 5.2).
Figure 5.2. Geological map of Scotia waste dump showing the location access road to the site (from McGoldrick, 1993).
103
Salt lake chains within broad valleys of low relief characterize the present
landform. Two large salt lakes set a natural boundary to the region, namely Lake
Cowan to the north-west and Lake Dundas in the east (Campbell, 1990). These salt
lakes occupy old river valleys that are now partly filled with Tertiary terrestrial and
marine sediments and more recent aeolian and lacustrine deposits. The adjacent gentle
slopes are mostly mantled by regolith and associated colluvium and aeolian deposits.
The mine sites and reference site occur on such a sloping area.
The analogue undisturbed site is under native woodland on soils developed from
quaternary calcareous materials resulting from wind-drifted erosion (Doepel, 1973).
Soils in the native woodland have similar properties to that of reference profile SG2
(McArthur, 1991) which was classified as Brown Calcareous Soil (Gc 1.22) or Typic
Eutrochrept and which may have formed from aeolian materials originating from
extensive salt lake beds.
Local climate is typically Mediterranean with mostly winter rainfall and a hot dry
summer. Annual rainfall is 288 mm and potential evaporation is 2445 mm, which
clearly shows a very strong deficit of water for the year. The highest monthly average
of maximum temperature occurs in January (32.5 °C), and the lowest average minimum
is 5.2 °C in July (Figure 5.3).
Figure 5.3. Monthly rainfall, temperatures and evaporation representing Norseman station (Bureau of Meteorology; Luke et al., 1988).
5.2.2. Sampling methods
Fieldwork was conducted from November to December 1999 and in February
2000. Four 100-m transects were established on the waste dump, approximately 25 to
50 m apart. In addition, two transects were set up at the analogue site (undisturbed
0
5
10
15
20
25
30
35
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Rai
nfal
l (m
m)
0
5
10
15
20
25
30
35
Tem
pera
ture
(deg
C)
rainfall min temp max temp
0
50
100
150
200
250
300
350
400
Jan
Feb Mar Apr May Jun Ju
lAug Sep Oct
Nov Dec
Evap
orat
ion
(mm
)
104
native Eucalyptus and Melaleuca woodland about 300 m to the west of the dump).
Different zones were recorded and named to represent soil surface condition. A zone
may be a patch (sink) which retains resources or an interpatch (source) from which
resources are lost (Tongway and Hindley, 1995; 2000). The typical zones at the Scotia
mine were mostly bare soil (with abundant gravel and rock fragments, and physical
crusts), shrub and tree associations, and also a man-made bank-trough series installed to
manage surface drainage (Figure 5.4). A combination of soil characteristics were used
to calculate indices of stability, infiltration and nutrient cycling (see Section 4.2.1 and
Table 4.1 presented earlier for details). The concept was developed by Tongway (1994)
and completed later by Tongway and Hindley (1995) for monitoring shrublands,
woodlands, and grasslands, but is being verified by the author for application to mine
sites. Absent or non-applicable features as specified in Tongway and Hindley (1995)
were given a zero score and automatically excluded from the calculation.
Figure 5.4. General view of the Scotia waste dump and adjacent woodland showing
(rocky) drainage structure, soil surface and plant growth conditions.
105
Soil depths on waste dumps are variable and it is difficult to obtain consistent
depths for sampling because the soils often contain large rock fragments. For this
reason, soil samples from the mine waste dump were collected from 0-10 cm depth
along the transects (total 25 samples) that represent major zones as identified by the
LFA assessment. Under native woodland, soils have fewer rock fragments so that soil
samples were collected from 0-15 cm and 15-30 cm depths (each of 12 samples) that
represent bare soil, low shrub (Atriplex) and litter-tree association zones.
Vegetation density and cover was recorded using the point-centred quarter (PCQ)
method which is suitable for sparsely vegetated (low density) sites. Observation was
carried out along the same transect as for LFA measurement (Bonham, 1989; Tongway
and Hindley, 2000). The transect was divided into 10-m intervals, thus there are four
quarters relative to the centre point. At each point, the nearest plant was recorded
(distance, species, height). The same plant can only be sampled once. The average
distance (X) can be used to estimate plant density per hectare (Y) using a simple
formula: Y = (10000/X2).
Plant samples were collected representing major native species that were present
for both the waste dump and native woodland. Several litter samples were also obtained
from both sites. All plant and litter tissues were analyzed for total nutrient content.
5.2.3. Analytical methods
Unless specified otherwise, the detail of soil analyses used in this study can be
found in Section 3.2.3. Soil chemical analyses include pH and EC (1:5 ratio),
bicarbonate-extractable (P) and potassium (K), total carbon and total nitrogen. Organic
carbon was measured using the Walkley-Black method (Walkley, 1947). Exchangeable
cations and CEC were extracted using 0.01 M silver thiourea and measured by AAS.
Soil physical analyses include water retention using a pressure plate apparatus at 10 and
1500 kPa. Particle size analysis was determined using the pipette procedure (Van
Reeuwijk, 1987). Aggregate stability was determined using the Yoder method (Chaney
and Swift, 1984). Soil strength of surface soil in the field was determined using a
pocket penetrometer. For bulk density measurement, samples were taken with a brass
corer (7.2 cm inner diameter and 7 cm height) and values were calculated for oven-dried
(105 °C) soil.
106
Total nutrient element concentration for plant and litter samples was measured
using X-ray fluorescence spectrometry (Philips PW1400). Samples were oven-dried
(60 ºC) for a few days and finely ground. A pressed-pellet was prepared using boric
acid as binder (Norrish and Hutton, 1977). The XRF analysis measured total
concentrations of P, S, Ca, Mg, K, Na, Si, Cu, and Zn. In addition, total carbon and
total nitrogen concentrations were measured using a high-temperature induction furnace
(LECO CHN1000).
5.2.4. Statistical Analysis
A simple correlation matrix with non-transformed data was used to identify
bivariate relationships between soil properties, and multivariate methods were used to
determine the most diagnostic combination of soil attributes to explain differences
between the waste dump and native woodland soils. These methods include principle
component and canonical variate analysis using the GENSTAT program (Digby et al.,
1989).
5.3. Results and discussion
5.3.1. Landscape organization and soil surface conditions
There are four major zones on the dump which are associated with particular soil
surface conditions and vegetation, and which may primarily reflect fertility status. The
main zone on the dump is bare soil (with abundant rock fragments), with smaller zones
of low shrub of Melaleuca species, saltbush species or trees (Eucalyptus), and ridge
zone (Table 5.1). A semi-radial drainage structure of tilled rock runs across the dump.
This structure retains water and transported soil particles, and has enabled growth of
several species. Major plant species on the waste dump are Eucalyptus torquata, E.
diptera and E. terebra, Melaleuca lanceolata, Maireana apppresa, and annual species
(including Angianthus sp). Saltbush species (e.g. Maireana, Atriplex) are present and
adapted to highly saline condition of the waste dump.
The analogue site showed two strata of native vegetation namely Melaleuca spp.
(paper-bark trees) as low and middle-storey and Eucalyptus spp. as the upper-storey.
Major soil surface zones are bare soil, saltbush, Melaleuca spp, or Eucalyptus
107
woodland, mostly with abundant litter accumulation and decomposition. At both sites,
fallen branches, and on the dump, scrap metal, pipe and tyres have acted as
erosion/transport traps retaining soil resources (i.e. fine soil, litter).
108
Table 5.1. Summary of landscape properties and major zones for each transect (SW waste dump; NW native woodland). Abbreviations: BSR, bare soil surface with significant amounts of rock fragments; SLC, soil-log complex. Obstruction index is the total length of obstruction (sink) divided by transect length and indicates the proportion of sink and the potential retention of resources.
Zone LFA indices (%) Transect
Number of sink /10m
Total sink width
(m/10m)
Mean interpatch length (m)
Obstruction index Major Length (m) % Stability Infiltration Nutrient
cycling
SW 1 2.7 5.13 2.77 0.33 BSR 2.77 66.5 46.0 30.9 12.2 Ridge 2.08 16.7 49.5 39.4 19.4 Maireana 0.84 11.7 61.6 51.9 34.3 SW 2 2.8 8.26 3.62 0.42 BSR 3.62 57.9 52.5 38.2 18.4 Ridge 2.25 15.8 43.6 43.2 22.7 Melaleuca 1.07 10.7 61.0 51.3 36.6 SW 3 2.6 7.95 3.12 0.34 BSR 3.51 49.2 51.8 41.7 24.4 Ridge 1.08 17.3 47.8 36.8 22.3 Bare soil 2.34 16.4 62.0 42.1 28.9 SW 4 2.9 12.4 3.27 0.35 BSR 3.27 65.9 49.8 29.5 18.9 Ridge 1.19 17.9 49.4 44.6 27.3 Trees 3.38 10.2 48.4 53.5 37.8 NW 1 1.5 4.67 4.89 0.32 Bare soil 4.89 68.4 66.3 53.1 37.8 Melaleuca 2.62 23.6 72.5 69.6 61.6 SLC 1.33 8.0 55.4 48.2 36.0 NW 2 2.3 8.36 3.38 0.36 Bare soil 3.38 64.3 63.1 51.9 33.1 Trees 4.16 16.7 71.7 71.6 59.7 SLC 1.06 10.6 61.3 50.0 32.0
109
Initial values of landscape indices for the Scotia waste dump are unknown. The data
collected represent whatever degree of self improvement that has occurred. Therefore the
values obtained in this study may be considered as “current status values” for monitoring
purposes. For all transects, the bare soil zone contributes the largest portion for each index
(58-68 %). Shrub or trees zones provide a smaller contribution to the whole landscape,
being less than 25 % (Table 5.1). The higher obstruction index on the dump was associated
with the man-made ridge (drain) structure.
Landscape indices vary between transects on the dump (Table 5.2). The average
values of each landscape index after 15 years are as follows: stability 51%, infiltration 39
%, and nutrient cycling 22 %. If the mean values of indices from the waste dump and
native sites are compared and expressed as proportions, the stability index for the dump is
approximately 0.78 that of the native woodland, and the infiltration index is about 0.68.
Litter accumulation substantially increases the nutrient cycling index. The much lower
nutrient cycling index for the waste dump (0.54 of the native woodland) may indicate a
slow process of soil enrichment due to biological activity on the new land surface. In this
case, litter production by living plants and its decomposition by a variety of organisms is
the key factor that enhances the nutrient cycling index. The nutrient cycling index
increases as plant biomass increases, and cryptogams become established.
Table 5.2. Site information and values of LFA indices (%) for the Scotia waste dump and analogue sites. Landscape elements Stability Infiltration Nutrient
cycling Analogue transects 1. NW1 (Atriplex-Melaleuca site) 66.9 ± 3.7 56.6 ± 2.2 43.3 ± 6.0 2. NW2 (Melaleuca-Eucalyptus site) 64.3 ± 0.8 56.5 ± 1.7 39.2 ± 2.2 Mean 65.6 56.6 41.2 Waste dump transects 1. SW1 (Western side) 49.0 ± 0.7 35.8 ± 5.4 17.2 ± 1.4 2. SW2 (Mid-west) 52.2 ± 1.9 40.9 ± 3.0 22.0 ± 1.9 3. SW3 (Mid-east) 54.4 ± 3.3 42.5 ± 5.1 27.1 ± 2.4 4. SW4 (Eastern side) 49.7 ± 3.3 35.5 ± 3.7 22.7 ± 2.1 Mean 51.3 38.7 22.2
110
5.3.2. Soil properties
Surface soils from several sites on the Scotia waste dump show lower hydraulic
conductivity, higher bulk density (BD), higher soil strength, and larger soil aggregates than
for the native topsoils (Table 5.3). The higher BD values for the dump are partly associated
with a higher gravel content. Soil crusting associated with clay dispersion also affects the
measured physical properties, especially as it inhibits water movement through the profile
and generates a hard layer. Mean weight-diameter (MWD) values for aggregate stability
were higher for the waste dump. However, the ratio of MWD values measured by wet and
dry sieving indicates a more stable condition for the native samples (ratio 0.59) than for the
waste dump samples (ratio 0.42).
Soils on the waste dump are mostly (gravelly) sandy loam in texture with a clay
content of less than 10% and 60% or more sand (Table 5.4). There is a slight difference in
water retention characteristics between the two sites. Volumetric water content at field
capacity is approximately 30 %, and 12-15 % at wilting point.The average value of
available water is 14 % (by volume). Rainfall may be retained and is available to plants for
a limited period (winter rain from May to July). Therefore, the most adapted plants are
drought-tolerant species.
Table 5.3. Soil physical properties of topsoils from the Scotia waste dump and native forest (mean ± standard deviation). The difference between mean values for waste dump and woodland topsoil is significant if the probability (p-value) is less than 0.05.
Waste dump Native topsoil p-value Physical properties mean ± sd n mean ± sd n Hydraulic conductivity (mm/hr) 32.7 ± 19.5 5 80.8 ± 28.2 5 0.014 Bulk density (g/cm3) 1.21 ± 0.19 5 0.99 ± 0.13 5 0.072 Soil strength (MPa) • Bare soil sites 2.56 ± 1.78 10 0.64 ± 0.28 10 0.004 • Trees/eucalypt sites 2.84 ± 1.43 10 0.44 ± 0.19 10 <0.001 • Melaleuca sites 3.87 ± 1.50 10 0.28 ± 0.12 10 <0.001 • Saltbush sites 4.82 ± 1.42 10 0.63 ± 0.24 10 <0.001 Mean weight diameter (mm) • Dry sieving 2.11 ± 0.67 8 0.84 ± 0.18 5 0.002 • Wet sieving 0.89 ± 0.40 8 0.49 ± 0.06 5 0.053
111
Table 5.4. Mean value (± standard deviation) of textural and chemical properties of soils from the Scotia waste dump (n=25) and native woodland soils (n=12 for each depth). Soil properties Waste dump Native woodland 0-10 cm 0-15 cm 15-30 cm Physical properties Field capacity (% v/v) 30.8 ± 8.1 28.3 ± 3.9 33.5 ± 4.7 Wilting point (% v/v) 15.1 ± 2.2 12.3 ± 0.7 13.9 ± 1.1 Sand (2mm-50µm) % 62.4 ± 5.1 65.4 ± 2.5 64.1 ± 2.9 Silt (2-50µm) % 27.4 ± 5.1 25.2 ± 3.4 25.0 ± 1.5 Clay (0-2µm) % 10.2 ± 4.3 9.4 ± 1.3 10.9 ± 2.5 Gravel (%) 35 ± 15 12± 5 14± 5 Chemical properties EC 1:5 (dS/m) 1.01 ± 1.23 0.44 ± 0.34 0.81 ± 0.38 Soil pH (1:5) 9.0 ± 0.4 8.5 ± 0.3 9.5 ± 0.5 Available P (mg/kg) 6.1 ± 3.8 8.7 ± 4.5 6.2 ± 4.3 Available K (mg/kg) 567 ± 213 620 ± 192 503 ± 140 Total N (g/kg) 1.43 ± 0.29 1.78 ± 0.46 1.29 ± 0.25 Total carbon (g/kg) 40.8 ± 7.2 31.1 ± 7.1 28.4 ± 3.4 Organic carbon (g/kg) 16.6 ± 3.9 23.9 ± 8.3 17.3 ± 6.0 Exch Ca (cmol/kg) 18.5 ± 1.9 20.2 ± 1.3 18.5 ± 1.2 Exch Mg (cmol/kg) 6.01 ± 0.93 6.30 ± 1.15 8.10 ± 1.29 Exch K (cmol/kg) 1.00 ± 0.30 0.99 ± 0.25 0.89 ± 0.18 Exch Na (cmol/kg) 2.40 ± 1.75 1.29 ± 0.68 2.89 ± 1.20 Sum of base cations (cmol/kg) 27.9 ± 2.6 28.8 ± 2.0 30.4 ± 2.0 CEC (cmol/kg) 28.4 ± 3.5 30.3 ± 2.3 31.3 ± 2.1 ESP (%) 8.6 ± 6.5 4.2 ± 2.3 9.3 ± 3.8
Soils on the waste dump are mostly alkaline (pH > 9) and saline (EC > 0.4 dS/m)
which make these soils suitable only for those plant species that are tolerant of these
extreme conditions, especially saltbush (Atriplex and Maireana). Woodland subsoils
exhibit more saline conditions, higher pH and higher exchangeable Na values than
associated topsoils. These soil properties resemble those of soils of the Dundas series
(McArthur, 1991).
Other chemical properties of topsoils of waste dump and analogue sites are quite
similar except for higher levels of organic carbon (OC) and plant-available P (Table 5.4) in
analogue sites. It should be noted that these difference between woodland and dump sites
mostly reflect the role of plants but might be partly related to sampling depths at the two
localities. For the native woodland, values of these properties were systematically higher
for topsoils than for subsoils. The soil properties reflect the higher potential fertility of
112
woodland soils relative to dump soils due to the well-established woodland ecosystem
containing substantial plant biomass. Nutrient cycling index increases with soil organic
matter and total nitrogen (Figure 5.5).
Figure 5.5. Relationships between nutrient cycling index (NCI) and both organic carbon and total nitrogen for the Scotia topsoils.
5.3.3. Relationships between soil properties
Several close relationships exist between soil properties when all soil samples are
considered together. In particular, organic carbon (OC) is positively related to total
nitrogen (r = 0.89), exchangeable Ca (r = 0.71), and CEC (r = 0.64) (Figure 5.6). Soil pH is
positively related to Na (r = 0.57) (Figure 5.7). Using the stepwise regression technique,
we can identify several relationships between soil attributes. The CEC value is highly
predicted by OC and total exchangeable bases which together account for 78 % of the total
variance in CEC. There is no strong prediction for bicarbonate-extractable phosphorus
(bic-P), with clay, EC and soil pH together only explaining 27 % of total variation in bic-P.
Exchangeable K only accounts for 44 % of total variance in bicarbonate-extractable
potassium (bic-K).
In some cases relationships between soil properties are improved if soils from each
site are considered separately. The relationship between CEC and organic carbon (OC)
increases in significance (r = 0.81) for waste dump soils but is reduced for native sites (r =
0.59). Exchangeable Ca is the best predictor for CEC for the dump soils (r = 0.83) but not
for the analogue sites (r = 0.42) whereas exchangeable Mg is more predictive of CEC for
analogue soils (r = 0.61). Total N is accurately predicted by OC for the native soils
accounting for 86 % of variation. The accuracy of prediction increases by 6 % if silt and
CEC are included into the regression equation. For the waste dump soils, OC accounts for
010
20304050
6070
0 10 20 30 40Organic carbon (g/kg)
NC
I (%
)
waste dumpwoodland topsoil
010
2030
4050
6070
0 1 2 3Total nitrogen (g/kg)
NC
I (%
)
113
70 % of the variation in total N. The juvenile nature of dump soils may be responsible for
the absence of the close relationships between properties that exist for soils under mature
bush vegetation.
Figure 5.6. For all waste dump and woodland soils, organic carbon is significantly (linearly) related to total nitrogen, exchangeable calcium and CEC, but not to bic-P.
Figure 5.7. Soil pH (left) and EC (right) are weakly (positively) related to exchangeable sodium. Highly saline conditions occur for a few samples at the waste dump (right) and data points these very saline samples do not conform to the linear relationship.
y = 0.052 x + 0.52R2 = 0.79
0
0.5
1
1.5
2
2.5
3
0 10 20 30 40Organic carbon (g/kg)
Tota
l nitr
ogen
(g/k
g)
waste dump
native topsoilnative subsoil
0
5
10
15
20
25
0 10 20 30 40Organic carbon (g/kg)
Bic-
P (m
g/kg
)
y = 0.19 x + 15.3R2 = 0.50
10
14
18
22
26
30
0 10 20 30 40Organic carbon (g/kg)
Exch
Ca
(cm
ol/k
g)
y = 0.318 x + 23.7R2 = 0.41
15
20
25
30
35
40
0 10 20 30 40Organic carbon (g/kg)
CEC
(cm
ol/k
g)
y = 0.195 x + 8.56r = 0.57
6
7
8
9
10
11
0 1 2 3 4 5 6 7Exch Na (cmol/kg)
Soi
l pH
waste dumpnative topsoilnative subsoil
y = 0.187 x + 0.21r = 0.57
0
1
2
3
0 1 2 3 4 5 6 7Exch Na (cmol/kg)
EC
1:5 (
dS/m
)
114
5.3.4. Multivariate analysis
Principal component analysis (PCA) was carried out on a correlation matrix in which
the original data were standardized to have a variance of 1 and mean of zero. This option is
important to reduce the effect of variables having large values and variances. The PCA
technique is helpful in reducing a large number of variables to ease data interpretation
(Leclerc et al., 2001; Bailey et al., 2002; Shukla et al., 2004). For the Scotia sites, PCA
using 16 variables provides six new components with latent roots greater than unity. The
first component which accounts for 22.3 % of the total variance contains positive loading
values (>0.4) for organic carbon, exchangeable Ca and CEC (Table 5.5).
Table 5.5. Six principal components (PC) for Scotia soils samples having a latent root larger than unity. Variable Loading of latent vectors 1 2 3 4 5 6Field capacity 0.056 0.066 0.471 0.112 0.072 0.087Permanent wilting point 0.101 0.476 -0.054 0.105 0.006 -0.142Sand -0.259 -0.419 -0.059 -0.255 -0.102 -0.028Silt 0.104 0.293 -0.278 0.339 0.461 -0.009Clay 0.197 0.164 0.423 -0.103 -0.451 0.048Gravel -0.019 0.332 -0.017 0.375 -0.302 -0.109EC -0.117 0.123 -0.183 -0.180 -0.275 -0.719pH -0.240 0.292 0.180 -0.306 0.245 0.334Bic-P 0.150 -0.149 0.411 0.281 -0.120 -0.054Bic-K 0.264 0.062 -0.360 -0.290 -0.267 0.273Organic carbon 0.440 -0.170 -0.129 0.001 0.082 -0.147Ca 0.429 -0.180 0.062 0.075 -0.001 -0.070Mg 0.159 0.104 0.218 -0.418 0.399 -0.341K 0.311 0.144 -0.245 -0.126 -0.216 0.324Na -0.146 0.387 0.097 -0.287 -0.140 0.003CEC 0.430 0.047 0.116 -0.278 0.154 -0.065 Latent roots 3.565 2.931 1.881 1.626 1.538 1.106Variance (%) 22.28 18.32 11.75 10.16 9.61 6.91
We can simply summarise this outcome by considering that the first component
relates to potential fertility. The second component of the PCA which explains 18.3 % of
the total variance contains positive loadings for water retention at wilting point (PWP) and
negative loadings for sand. The second component thus incorporates the influence of soil
texture and water retention. The inclusion of water retention and texture properties together
with bic-P increases the prediction by 12 %. The inclusion of EC values improve
115
prediction by 7 %. Shukla et al. (2004) found that soil quality indicators for reclaimed
mine soils in southeastern Ohio are closely related to bulk density, water infiltration,
aggregate size and soil carbon/nitrogen. As a new ecosystem develops, different attributes
become important. The changes in these attributes may indicate changing conditions (i.e. an
orderly succession) as soils develop, thus providing an approach for site monitoring.
The dump and native topsoils are separated along the first axis (Figure 5.8), although
separation is diffuse for some native subsoils. The first two components only explain 41 %
of total variance, with soil fertility status having a key role in discriminating between the
sites. It is sometimes difficult to interpret the results directly from the principal
components and other techniques, for example factor analysis may be used to assist data
analysis, in which variables of the original principal components are rotated (Manly 1986;
Brejda et al. 2000).
Figure 5.8. Plots of loading scores the first two dimensions of the principal component analysis.
The PCA method is used to describe variation between individuals within a data
population. If the interest is for recognizing differences between groups of samples,
canonical variate analysis (CVA) may be used (Manly, 1986). The CVA shows a strong
separation between groups of soil samples (Figure 5.9). Soil fertility status, as expressed by
positive values for pH and CEC, together with a negative loading for gravel content
accounted for 62 % of total variance along the first axis. Waste dump soils are effectively
separated from the woodland soils by the CV1 axis that includes these soil fertility and
-4-3-2-101
23456
-6 -4 -2 0 2 4 6 PC1(OC,Ca,CEC)
PC2 (PWP,-sand)waste dump
native topsoil
native subsoil
116
gravel attributes. The waste dump soils contain more gravel than do woodland soils. The
CV2 axis explains 38 % in total variance which is also characterized by pH, CEC and
gravel, with additional contributions from exchangeable Ca and Na. Waste dump soils are
similar to woodland subsoils which are clearly separated from woodland topsoils along the
CV2 axis.
Figure 5.9. Canonical variate analysis for Scotia soils.
5.3.5. Vegetation pattern and plant sample analysis
Many parts of the waste dump, including the slopes and benches, have been colonized
by a number of local native species. Vegetation stands on waste dump are very different
from those of adjacent native woodland. The average height of Melaleuca and Maireana is
about 1.5 m; up to 3 m for Eucalyptus, and mostly less than 1 m for Atriplex on the waste
dump; by contrast in the native forest Eucalyptus trees can reach 10-15 m in height and 3 m
for Melaleuca. In addition the poor groundcover on the waste dump may indicate poor
seedling recruitment.
Mean distance (i.e. the average distance of four nearest plants to a center point within
individual intervals) of shrub and trees species plotted together with overall mean value
along the PCQ transects showed uneven distributions of vegetation on the sites (Figure
5.10). The common pattern is that plants tend to clump near the edge of the waste dump
and becomes patchy in the middle of transects. The eastern corridor of the waste dump is
characterized by sparsely distributed vegetation on the southern end and a higher density of
-5
-4
-3
-2
-1
0
1
2
3
4
-4 -2 0 2 4 6 CV1 (pH,CEC)-gravel
CV2 -(Ca,Na)
waste dumpnative topsoilnative subsoil
117
vegetation on the northern end. Plant distribution is likely to be a function of soil water
content over time and soil quality, for example soils with high salinity tend to have fewer
species (as few as two) and a lower plant density. Plant density however varies
considerably across the waste dump. Plants tend to cluster along the western side and
around the drainage channel, while their occurrence is relatively low at the eastern side.
The average distance of nearest individual plant to centre point of 10-m interval transect
ranges from 2.27 to 3.44 m. The vegetation density is estimated to reach about 1463
plant/ha for the waste dump and 998 plant/ha for the native woodland.
Figure 5.10. Graphics presenting a function of mean distance (i.e. average distance to four nearest plants) along PCQ transect on waste dump (top and middle) and from native forest/woodland (lower graphs). The horizontal line shows the overall mean distance for individual transects. These plots imply some banding may be present.
SWD-1 (West)
0
1
2
3
4
5
6
0 20 40 60 80 100
SWD-2 (Central)
0
1
2
3
4
5
0 20 40 60 80 100
SWD-3 (Central)
0
1
2
3
4
5
6
0 20 40 60 80 100
SWD-4 (East)
0
1
2
3
4
5
6
7
8
9
0 20 40 60 80 100
SNB-1
0
1
2
3
4
5
6
0 20 40 60 80 100
SNB-2
0
1
2
3
4
5
0 20 40 60 80 100
Distance from starting point (m)
Mea
n di
stan
ce (m
)
118
Nutrient element concentrations differ considerably between different parts of plant
biomass and litter (Table 5.6). Calcium (Ca) is the most abundant plant nutrient in litter,
eucalypt and Melaleuca. Saltbushes (Atriplex and Maireana) contain much higher levels
for sodium (Na) and chloride (Cl) in their biomass. This reflects the nature of salt-tolerance
of these species which enables them to accumulate salt. These plant species also
accumulate salt even in low EC systems.
The results of chemical analysis indicate that metal toxicity due to Zn, Cu, Fe and Mn
is absent for Eucalyptus samples (fresh biomass) growing on this mine waste which
contains some elevated concentrations of metals; Fe concentrations tend to increase in litter
(decomposing tissue) and animal waste and (digested biomass). These results may provide
an estimation of nutrient contribution to soils from litter and plant biomass in the waste
dump and analogue sites. A sufficient supply from in situ nutrient cycling will improve soil
fertility towards supporting a sustainable natural rehabilitation.
Nutrient enrichment from litter decomposition varies between nutrients and the values
are greatly affected by litter abundance. Assuming 1 % of total nitrogen in plant material
and that annual litter production on the dump is 100 kg/ha, then annual contribution of plant
biomass for nitrogen (N) is less than 1 kg/ha, and it is much lower for phosphorus (P) and
potassium (K). This simple calculation illustrates a serious problem for the soil fertility
status of the dump. Although the nutrient content of plants is quite satisfactory, the patchy/
unvegetated parts of the dump need more attention to improve water infiltration and
storage. In particular unless water availability is increased during the most critical early
growth period of pioneer species, the prolonged dry season will severely hinder plant
development. In turn, recovery of plant biomass will be slow, particularly due to low
density of trees (e.g. Eucalyptus) growing on the waste dump.
Maireana and Atriplex are commonly associated with high salinity soils. These
species have well adapted to saline condition on the dump. Halophytes are able to survive
high salt concentrations, either by excluding salt or accumulating salt as in the saltbushes
(Condon and Sippel, 1990; Osborne, 1996). The nitrogen concentration was twice as high
in Atriplex and nearly four times in Maireana than for eucalypt leaves. The concentrations
of P and K were also higher for saltbushes than for eucalypt leaves for the dump. For the
same plant parts, nutrient contents vary considerably between three Eucalyptus species
colonizing the waste dump. The average contents of major elements in this study are
within published ranges and are comparable with results from other workers (e.g. Judd et
al., 1996).
119
Table 5.6. Element concentrations of plant and litter samples from Scotia waste dump and native woodland sites. Samples Parts C N P K Ca Mg Na S Cl Zn Cu Fe Mn (%) (mg/kg) Waste dump Litter Bark 52.6 0.20 0.002 0.027 1.32 0.15 0.055 0.031 0.005 14 2 353 76 Leaf 56.5 0.54 0.011 0.11 2.10 0.18 0.28 0.14 0.072 78 9 876 240 Twig 50.6 0.32 0.008 0.076 2.55 0.25 0.12 0.067 0.079 65 2 1615 128 E. diptera Leaf 58.7 0.96 0.035 0.47 0.80 0.11 0.35 0.19 0.39 65 14 111 125 Nut 55.5 0.54 0.059 0.61 0.71 0.13 0.45 0.070 0.56 42 8 43 107 E. terebra Leaf 59.2 0.83 0.027 0.33 1.20 0.067 0.68 0.21 0.38 88 3 44 171 Bark 55.6 0.21 0.004 0.051 0.90 0.15 0.13 0.032 0.20 16 3 46 35 Twig 53.7 0.69 0.016 0.12 2.24 0.12 0.41 0.051 0.39 78 < 40 70 Nut 53.9 0.73 0.080 0.38 0.98 0.092 0.47 0.093 0.52 63 4 35 109 E. torquata Leaf 59.1 1.07 0.052 0.46 0.73 0.11 0.32 0.12 0.31 56 6 59 198 Twig 55.0 0.41 0.047 0.28 0.77 0.098 0.29 0.048 0.28 83 17 21 285 Nut 58.6 0.67 0.072 0.57 0.61 0.12 0.46 0.076 0.48 50 6 25 161 Melaleuca All 55 1.05 0.056 0.58 0.63 0.17 0.54 0.19 0.93 30 5 311 7 Angianthus All 48.2 0.95 0.020 0.46 0.90 0.11 0.29 0.16 0.22 24 13 1630 47 Mairena All 41.7 3.85 0.12 1.12 0.42 0.15 2.50 0.25 1.68 47 16 335 160 Atriplex All 40.6 1.45 0.035 1.27 1.04 0.22 3.45 0.22 5.36 59 16 465 98 Note: < = less than the lowest limit of detection
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Table 5.6 (continued). Samples Parts C N P K Ca Mg Na S Cl Zn Cu Fe Mn (%) (mg/kg) Native forest Litter Melaleuca Twig 52.2 0.40 0.016 0.079 1.25 0.11 0.11 0.081 0.10 13 8 450 44 Eucalyptus Bark 51.6 0.35 0.012 0.23 0.72 0.11 0.10 0.055 0.056 12 4 1002 48 Leaf 60.9 0.64 0.014 0.070 1.57 0.12 0.059 0.091 0.043 13 < 372 75 Fruit 50.5 0.32 0.017 0.16 0.95 0.15 0.21 0.056 0.035 14 7 217 30 Animal waste Faeces 37.8 1.44 0.048 0.25 1.46 0.50 0.076 0.17 < 22 13 5264 273 Biomass Eucalyptus Leaf 60.6 0.87 0.042 0.54 0.66 0.15 0.24 0.091 0.57 14 1 47 17 Twig 56.6 0.57 0.051 0.38 0.97 0.12 0.22 0.047 0.49 18 < 30 32 Fruit 56.8 0.42 0.030 0.30 0.81 0.20 0.47 0.070 0.73 12 3 38 18 Bark 52.2 0.17 0.002 0.17 0.46 0.051 0.16 0.024 0.043 4 < 38 8 Melaleuca All 53.3 1.26 0.034 0.36 1.36 0.22 0.72 0.42 1.31 20 3 321 11 Atriplex All 40.1 1.76 0.040 0.69 0.81 0.17 5.45 0.19 6.11 22 8 165 57 Note: < = less than the lowest limit of detection
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5.3.6. General discussion
Spontaneous plant growth and soil development on the Scotia waste dump has
been relatively slow. Plant density of mixed species at the waste dump varies from 845
to 1940 plant per hectare. Shrubs and trees mostly colonize the western part of the
dump. The average height of trees and shrubs is much lower at the waste dump than for
the mature stands of vegetation in undisturbed woodland. In contrast to the spontaneous
plant colonization described here, seeding of mixed local species (4.5 kg/ha) was
sufficient for extensive development of vegetation during rehabilitation of waste dumps
at the Westonia (Western Australia) gold mine. Plant densities were similar between
both sites after 5 years with a total density of 16,978 plant/ha for the waste dump and
14,874 plant/ha for the nearby woodland. Indigenous species of saltbushes (chenopods)
are well adapted to drought and saline conditions (Osborne, 1996) and thus highly
suitable for revegetation. At a micro-scale, spontaneous plant development on the
Scotia waste dump is affected by the nature of the waste materials used to build the
dump. Soils in the region are associated with materials from ancient salt lakes, thus
salinity is significant. It is clearly important that soil materials used in rehabilitation
contain a seed bank of native species (Koch et al., 1996; Osborne, 1996). To ensure
successful revegetation, mining companies when preparing a waste dump should
carefully manage and separate waste materials from topsoil.
Early growth of native species mainly starts from an area where soil resources are
retained or accumulate. This condition may have been established by a drain structure
(semi-radial form) on the top of Scotia waste dump. Paper-bark trees (Melaleuca sp)
occupy most of the north-western part of the dump (average height < 1.2 m) and extend
to the central part of the dump. Eucalyptus sp are less abundant and are mostly
distributed in the central and eastern parts (average height of 2.5 m). The drain
structure intercepts and traps surface water (run-off), and also retain soil particles, litter
and seeds. Physical obstructions of this type are essential for restoring soil patchiness
and local zones of soil fertility. For example, piles of branches were effective as a
means for intercepting water and other soil resources in restoring soil function in a
mulga (Acacia aneura) woodland (Tongway and Ludwig, 1996). Ripping of the topsoil
is also important as it increases water infiltration and reduce the effect of traffic
compacted layers in rehabilitated gold mines (Osborne, 1996) and bauxite mines (Ward
2000). For a plateau-like waste dump, installation of a drain structure may be beneficial
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for controlling and retaining of vital resources on the dump, and thus supporting plant
growth. However, it might be the source of an excessive loss of water too if it is badly
planned and executed.
The nutrient cycling index (NCI) for the waste dump is considerably smaller than
the value for the analogue site. In this study, the analogue site is in a nearby
Eucalyptus-Melaleuca woodland. This index may reflect a dynamic process in a
productive soil patch (Tongway and Hindley, 1995). The values of NCI depends
largely upon the score of litter abundance and its incorporation into soils. For the waste
dump, the score is mostly 1 or 2 and nil for decomposition compared with the analogue
sites (average score of 5 for litter and slightly to moderately incorporated). In addition
the score for cryptogam is mostly 1 or not applicable for the dump. The value for Scotia
waste dump is slightly higher than the NCI value for the nearby Kambalda nickel mine
(18.8 %) partly due to minimum topsoil being available for rehabilitation at the nickel
mine site (Tongway et al., 1997). The largest proportion of NCI (70 %) is determined
by scores for litter, and reflect the abundance, origin and decomposition (incorporation)
of litter into soils. The low density of trees on the dump will have contributed to the
low litter production. Amendment of topsoils using organic materials should increase
the nutrient cycling index. However, production of biomass from growing trees and
shrubs is essential for sustainable soil development on the site. The present conditions
support a quite satisfactory growth of local trees although establishment and growth are
slow under the natural rehabilitation process at the dump. The proportions of bare soil
for both dump and native bush sites are similar (66 %), while NCI for the dump is about
one third that for the native site (Table 5.2). Establishment of trees substantially
reduces the bare soil zone, and contributes a significant increase of plant biomass. A
suitable niche for plant growth must be promoted to stimulate a rapid increase in
nutrient cycling index.
Differences in infiltration index reflect different surface conditions between the
waste dump and the analogue site. Water infiltration has been promoted by application
of geotechnical measures to the dump (ripping and drainage), while in the woodland it
is much influenced by biophysical traps such as fallen branches and logs. Ripping
substantially increased infiltration index for waste dumps at the Kambalda nickel mine
(44.8 %) to values that were slightly larger than for analogue sites (39.6 %) (Tongway
et al., 1997). The presence of trees will increase the infiltration index as shown by the
difference between bare soil and tree zones (Table 5.1). The value of infiltration index
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is much influenced by plant canopy and litter cover. The largest contributor of litter is
expected to be eucalypt trees, mainly as leaf, bark and twig, while paperbark (Melaleuca
sp) trees mostly contribute twig and branch material due to the small size of their leaves
and indication of decomposition. Litter accumulation at the dump is estimated to be
less than 100 kg/ha, and mostly occurs around plant stems and within drainage
channels. Increasing plant cover is likely to substantially improve the infiltration index.
The current stability index of the Scotia waste dump approaches the value for
reference woodland with vegetated zones of the dump having higher index values
(Table 5.2). In most cases of mine rehabilitation, the stability index is likely to increase
rapidly in the first years of plant establishment (Tongway et al., 1997). Cryptogam
cover can be used as one indicator of stable surface in the field (Tongway and Hindley
1995; Osborne, 2000). The increasing value of stability index indicates that the soil
surface has become more stable against external disruptive force, primarily rainfall and
overland flow. For a salt-affected surface like the Scotia waste dump, surface crusting
due to excessive salt content is subject to two different conditions: 1) crust brokenness
may be more severe resulting in a lower score, 2) a hard, cemented surface leading to
high resistance to pressure that gives a higher score. Plants with extensive rooting
systems may help stabilize the soil surface (Oades, 1984; 1993).
The current LFA indices may be used as the representative current values for
further site monitoring. There are two points that need to be addressed when using LFA
for this purpose. First, LFA does not automatically classify a site as poor, moderate or
good. It is necessary to compare index values from rehabilitated sites with appropriate
analogue sites and also the values expressed in “fresh” rehabilitation in order to draw
any inference from a particular numerical value. There are no generic values to indicate
that a functional state is acceptable across landscape types. Type of biome affects the
values, for example a nutrient cycling index of 25 may indicate a highly functional
grassland, but it may indicate a dysfunctional woodland (Tongway and Hindley, 2000).
Second, LFA measurements are ideally conducted in a time series spanning from the
early stage of site rehabilitation to its state at decommissioning. However, it is
generally not possible to find rehabilitation sites of different ages that have been
established using a single practice. . At some stage the S-shape (i.e. sigmoid) response
curve may be used as an approach for predicting the possibility of a new ecosystem will
sustain any disturbance (Tongway and Hindley, 2000). This approach is only possible
when we know the initial and limiting indicator values (y0 and y0+a) that fit the model.
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In the present case, the Scotia waste dump provides an only single unit of observation,
consequently a time trajectory analysis using the sigmoid curve can not be performed
Completion criteria may also be derived from soil sample analyses. The selection
of appropriate soil properties is dependent on plant and environmental variables. For
salt-affected soils under arid conditions such as exist at Scotia, electrical conductivity
(EC), exchangeable sodium saturation (ESP), and soil pH may be highly important
criteria. The analytical results show that soil properties of the waste dump are quite
similar to those of the analogue sites, except for the lower organic carbon concentration
(Table 5.4). These soil properties together with associated vegetation parameters (plant
density, vegetation cover, and species richness) have been used to satisfactorily define
stages of mine site rehabilitation at Laverton, Western Australia (Osborne, 1999).
However, physical properties of the Scotia waste dump may ultimately limit plant
growth and soil development. Soil compaction is present in some parts of the dump as a
result of the mechanical work during site preparation. Plant growth and root penetration
may help break encrusted and compacted hard layers providing they are not
impenetrable. The existence of such layers at the soil surface creates temporary water-
logging on the dump during high rainfall events and reduced infiltration.
It may be impossible to set final conditions for completion of rehabilitation based
solely on soil analysis due to the natural heterogeneity in soil materials. A combination
of several parameters may be more appropriate for evaluating current conditions at
rehabilitated mine sites. Landscape indices (LFA module) may be used to estimate the
temporal trend of rehabilitation. It appears that the nutrient cycling index is closely
related to the concentration of soil organic carbon (Figure 5.5). This relationship can be
used to compare the waste dump with the reference sites. Increased organic carbon is
indicative of increased soil development as also suggested by the landscape index. This
example shows that integrating both landscape indices and soil analysis provides a
better understanding of soil and plant development at disturbed sites.
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Part 3. Land rehabilitation and the LFA method at a gold mine in the
tropical climate of East Kalimantan
The third part of this thesis presents results of fieldwork at the Kelian Equatorial
Mining (KEM) mine in East Kalimantan, Indonesia. This site is included in the study
primarily to evaluate the assisted rehabilitation of disturbed sites using as an example a
gold mining operation in a tropical region. This management contrasts with the natural
rehabilitation existing at the other sites (i.e. Jarrahdale and Scotia) investigated in this
research. A site in Indonesia rather than in Western Australia was chosen to provide the
author (DS) with an experience that will be directly applicable to his future work. This
study applied ecosystem function analysis (EFA) based on the hypothesis that the
protocol can be used under tropical conditions thus extending the range of application of
the concept. The method has been tested mostly under temperate to arid conditions so
that this application represents an innovative use of EFA. The high rainfall and
consistently high ambient temperatures in this tropical region is believed to be the main
driving force of the fast vegetation recovery compared with the arid and semi-arid
locations where EFA has mostly been applied. The focus of this component of the
research is to evaluate changes in soil properties and landscape indices associated with
the rehabilitation process which are presented in Chapter 6 (soil properties of a
rehabilitated mine site) and Chapter 7 (landscape function analysis).
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Chapter 6. Soil properties of a rehabilitated mine site at Kelian, East
Kalimantan Indonesia
6.1. Introduction
Rehabilitation of land disturbed by mining and mineral processing has become an
integral part and key issue in mining operations (Bradshaw, 2000). Mine site
rehabilitation is considered satisfactory when plant density and species diversity are
close to the pre-mining condition, also soil quality should be improved to a condition
that will continue to support plant growth (Osborne, 1996; Tordoff et al., 2000). Poor
vegetation growth and low species abundance on mine spoils may be due to various soil
condition including low nutrient status and low water availability (Jochimsen, 2001).
During mine planning it is important to design an acceptable final environment for
when the operation is completed. Kelian Equatorial Mining (KEM) has operated an
open-cut gold mine in East Kalimantan province (Indonesia) since 1990 using
conventional drill and blast, load and haul techniques. The mining company processes
31 million tons per year (Mta) comprising 7.5 Mta ore and 23.5 Mta waste rock, and
generates 7.5 Mta of tailings from the processing plant to produce 14 ton/year of gold
and 11 ton/year of silver. The company discharges tailings from the processing plant
into the Namuk Dam, while waste rock is stock-piled at the Nakan Dam (commonly
referred to as the lower and upper dumps) (Eaglen et al. 1998).
Land rehabilitation is being implemented under a Forestry Agreement whereby
KEM is required to reintroduce native species into degraded forest sites affected by
mining activities, and to install permanent (constructed) wetlands where such
revegetation is impossible. An integrated land rehabilitation program was initiated just
prior to 1994 by establishing a plant nursery at the Lingau area, which supplies local
and commercial tree species. Tree species for rehabilitation include fast growing
pioneers, members of the slower growing primary Dipterocarpaceae family and fruit
trees. A major species is Shorea sp (locally known as meranti). The local plant species
including meranti (Shorea sp), kapur (Dryobalanops sp) and keruing (Dipterocarpus
sp) are valuable for the regional development of East Kalimantan (Uuttera et al., 2000).
As at many locations, preserving fertile topsoil is essential to the land
rehabilitation program (Dykstra et al., 2000; Rokich et al., 2000; Parrotta and Knowles,
2001) but often little topsoil is available. Consequently, mine site rehabilitation often
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uses materials of low quality (Brown and Grant, 2000). Preserved surface (and
subsurface) soil materials might not suffice to cover large areas with a minimum
required thickness (e.g. 20 cm). Hence, mixtures with waste rock (overburden)
materials are also commonly used. The mixtures have diverse properties and these
properties will change at various rates as soils develop and plant growth proceeds.
Unfortunately, methods used for mine site rehabilitation sometimes need to be adjusted
to local conditions and circumstances which results in variations in rehabilitation
practice. Techniques used for site preparation at the Kelian sites changed from
spreading and ripping of topsoil in 1994 to piled-dumping of topsoil (’pimple-dumping’
or paddock dumping) without ripping in more recent years (2000/2001). For both
methods of handling topsoils, it is important to determine how soil properties change
with time under a tropical climate.
The purpose of this study was to assess soil properties of rehabilitated mine sites
at Kelian and relate measured soil properties to EFA assessment. Physical and chemical
properties are examined in a pseudo-time series (a space for time substitution) that
represents different age of rehabilitation (3 month, 1 year and 7 year) and sites are
compared to a primary forest (analogue site) as reference.
6.2. Materials and Methods
6.2.1. Study area
The KEM mine site is located about 180 km north-west of Samarinda, the capital
city of East Kalimantan Province and is about 3 km south of the Equator (approximately
0°05′S, 115°30′E). The name originates from the nearby Kelian River, a tributary of the
Mahakam River. Altitude is around 250 m above sea level. The area has a typically
tropical environment with rainfall in excess of 3500 mm/year occurring mostly in
September to March. Seasonal variations in rainfall cause a high variability in the flow
rate of the Kelian River ranging from 2 to 400 m3/s. Local relief is mainly deeply
dissected sloping areas with steep-sided ridges and valleys and flat lands adjacent to the
riverbed (Eaglen et al. 1998). Mining operations are focused at the Prampus hill
prospect near the Kelian River (Figure 6.1). Gold mineralisation occurs with
disseminated sulphides and carbonate in an epithermal style deposit (van Leeuwen et
al., 1990).
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Figure 6.1. Geographical location of the Kelian mine in East Kalimantan (Simmons and Browne, 1990).
6.2.2. Soil sampling
Soils in the study area derived from various volcanic rocks comprising the Lingau
Plateau formation (e.g. granite, tuff, andesite and rhyolite) and various Tertiary
sedimentary rocks (lithified sandstone, claystone and mudstone of the Pliocene and
Miocene). The geological structure of the East Kalimantan province has been subjected
to strong compression and folding forming a low mountain and rugged hill topography
characterized by steep slopes (~30 %) and broad ridges (Ohta and Effendi, 1992). The
surface horizon (0-5 cm) of primary forest soils is highly characterized by organic
matter and a dark color (dark brown to black) caused by the accumulation of litterfall
and its incorporation into soil materials. The subsurface horizon is yellowish or reddish
yellow in color and is underlain by yellowish gray materials. The major soil types
under primary and secondary forest in East Kalimantan are red yellow podsolic and
lateritic soils (Paleudults and Hapludults). Texture of these soils ranges widely from
sandy loam to clay loam for surface horizons, and sandy clay loam to clay for
subsurface horizons (Ohta and Effendi, 1992; Uutera et al. 2000).
Fieldwork was undertaken in June 2001. Three locations were selected from the
mine sites that were rehabilitated in 1994 (7 years old), in 2000 (1 year old) and in 2001
(rehabilitation 3 month prior to the study) and a reference site in adjacent native forest
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was also included (Figure 6.2). These sites represent a wide range of soil surface
conditions as materials and rehabilitation practice have not been uniform over 7 years.
The native forest is characterized by a thick and continuous litter bed. A bank-trough
micro-topography was formed at the 7-year site by ripping. Soil surface indicates the
abundant accumulation of decomposed litter from several tree species growing on the 7-
year site. The pimple-dumping technique (a mound-depression or moonscaping
arrangement) created islands of topsoil for both the 1-year and the 3-month sites. This
dumping technique forms a very uneven surface of 2-3 m relief but is relatively
effective for the interception and retention of run-off water and use of stock-piled
topsoil. Due to low plant and topsoil cover, the 3-month site is initially susceptible to
erosion. For this site surface zones are simply denoted as steep slope and gentle slope.
At every site the soil surface conditions were assessed and sampling points were located
along a down-slope transect. The number of sampling points differs between sites and in
total there are 26 sampling points. From each sampling point, soil samples were
collected from four depths (0-1, 1-3, 3-5 and 5-10 cm) that gives a total number of 104
samples. In addition, 26 core samples were collected and divided into 0-1, 1-3 and 3-5
cm subsamples for measurement of bulk density and aggregate size distribution.
Figure 6.2. Pictures showing a general view of native (analogue) forest and rehabilitated mine sites at Kelian.
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6.2.3. Analytical methods
Due to quarantine restriction, all soil samples from Kelian had been sterilized by
gamma ray irradiation on their arrival in Australia as required by the Australian
Quarantine Service. This treatment is unlikely to affect the measured properties. Soil
physical analyses include water-stable aggregate (Yoder, 1936; Chaney and Swift,1984;
Six et al., 2000; Shukla et al., 2004), bulk density, and particle size analysis by the
pipette method after organic matter removal. Chemical properties include soil pHw and
EC (1:5 soil to water extract), total soil carbon and total nitrogen, plant-available
phosphorus was and extractable-potassium. The detail of these analyses was provided
in Section 3.2.3.
Potentially available (mineralizable) nitrogen was determined following the
modified chemical procedure of Gianello and Bremner (1986) ( methodNo. 4 in that
publication). This chemical procedure is quite rapid for measuring available N for
routine analysis. The author found that even though the average concentration of
ammonium-N obtained by the chemical method is only about 32 % of the N
concentration produced by incubation of soil at 40 °C for 7 days, both methods are
closely related (r = 0.95). Published work also shows close relationships for
ammonium-N obtained by the chemical extraction and incubation methods (Zhang et
al., 2002; Picone et al., 2002). For this analysis, a batch of 3 grams of 2-mm sieved
soil was mixed with 20 ml of 2 M KCl in a digestion tube. The mixture was transferred
into AIM500 block digester and heated for 16 hours at 95 °C. An aliquot was filtered
through Whatman 42 filter paper (pre-moistened with Milli-Q water). Ammonium-N
was measured with a SKALAR autoanalyser. Another set of samples was
simultaneously prepared for ‘cold’ extraction to measure mineral-N in which the soil
mixture was shaken occasionally and kept at room temperature for 16 hours. Potentially
mineralisable-N is calculated as the difference between values for the hot extraction (i.e.
mineral plus mineralizable N) and the cold extraction (mineral N).
6.2.4. Statistical analysis
Analysis of variance (ANOVA) was done using a factorial design without
blocking structure due to unequal sample numbers between these sites (5-8 pseudo-
replicates). Two factors are considered, i.e. sites (analogue, 7 year, 1 year and 3 month)
130
and soil depth (0-1, 1-3, 3-5, and 5-10 cm). The objective was to evaluate trends at a
particular site over four depths and to compare sites for certain soil depth. The statistical
analysis was conducted using the StatView (Abacus Concepts, 1996) and the GenStat
(Digby et al., 1989). Simple regression and correlation procedures were used to
describe relationships between soil properties.
6.3. Results and discussion
6.3.1. Physical properties of Kelian soils
Materials used for rehabilitation belong to a wide range of texture classes. Soil
texture differs widely between locations. Forest soils have a very low variability in
texture. The variability increases in the following order of rehabilitated sites: 1-year <
3-month < 7-year. Soil texture shows two populations of samples (Figure 6.3). The
analogue forest soils are mostly sandy loam whereas the soils of the rehabilitated sites
have sandy clay loam to sandy clay texture. The values for particle size distribution are
relatively homogenous over soil depth. The 3-month site however shows an increase of
clay content with depth (Table 6.1). For individual depths, sand was significantly
higher for the native forest soils (mean ~60 %) than for rehabilitated mine soils (mean
30-45 %). Consequently a reverse trend exists for the clay fraction where the clay
content was invariably much higher for rehabilitated soils (ranging from 30-52 %) than
for native forest soils (mean ~20%). This was because the soil was stripped from a
valley floor. Soils at the 3-month site show significant differences in sand and clay
fractions with depth. This is probably due to particle sorting produced by soil erosion in
which clay from the 0-1 cm layer has been removed and deposited further down-slope
leaving a thin sandy layer at the surface. This large difference in particle size
distribution between sites affects some other soil properties which differ substantially
between soils. The large variation in texture between sites occurs quite commonly in
rehabilitated areas since in practice it is impossible to obtain soil materials with
homogeneous properties for restoration of the large areas affected by mining activity.
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Figure 6.3. Ternary diagram of soil texture for native forest and rehabilitated mine sites at Kelian comprising data for all sampling depths. Ellipse shows the clouds of data for individual sites (two for the 7-year sites).
Soil aggregates were less stable for the recently rehabilitated sites (3-month, 1-
year) than for the 7 year and forest sites as shown by smaller mean-aggregate size (1.4-
1.7 mm) as a consequence of the lower extent of aggregation of the young soils. The
differences in MWD values with depth for the 3-month and the 1-year sites are not
significant (Table 6.1). Thus there is a tendency of increasing MWD value with age of
rehabilitation (mean 2.1-2.7 mm for the 7-year site and 0.9-1.7 mm for younger soils).
This trend may indicate the increased stabilization of peds due to increased soil particle
binding by increased amounts of organic matter including plant roots in 7-year old and
forest soils. Aggregate stabilization is an important soil process as it assists soil
development and soil conservation of degraded land in regions such as Kelian which
have significant slopes and receive in excess of 3500 mm rainfall annually, thus soils
may be at risk of severe erosion under these conditions. MWD values are not simply
related to clay content presumably due to the strong influence of organic matter (Figure
6.4).
Mean values of bulk density (BD) increase with depth (forest and the 7-and 1-year
sites) and the values are similar throughout the sampled depth for the 3-month soils
(Table 6.1). The coefficient of variation (i.e. standard deviation divided by mean
132
values) tends to be higher for surface soils (0-3 cm) than for the 3-5 cm depth. The
smaller values of BD for the 0-1 cm depth is partly due to the dilution effect of soil
organic matter (average contents of soil total carbon 14-108 g/kg). The BD values vary
considerably and can be as low as 0.2 g/cm3 for the 0-1 cm and 1.22 g/cm3 for 3-5 cm
depth. These values indicate that the soil surface is highly porous, is not compact and is
therefore physically favorable for seedling emergence and water infiltration. The
variation in BD values is not directly related to clay content (Figure 6.5).
Table 6.1. Site information, particle size distribution, bulk density (BD) and mean-weight diameter (MWD) for rehabilitated mine sites and analogue forest soils at Kelian, East Kalimantan. Summary of ANOVA is included (ns, not significant; * and ** significant at 5 % and 1 % probability respectively). Sites Depth Sand Silt Clay BD MWD (cm) % (g/cm3) (mm) Forest 0-1 59.6±8.4 18.0±4.7 22.3±6.2 0.48±0.19 3.41±0.61 (n=5) 1-3 62.7±6.1 17.8±3.1 19.5±3.9 0.74±0.21 2.68±0.74 3-5 64.5±4.8 17.2±2.2 18.3±2.8 0.83±0.24 2.30±0.86 5-10 63.3±2.5 18.1±1.5 18.7±2.3 7 year 0-1 30.1±14.0 29.8±11.6 40.0±16.1 0.38±0.24 2.74±1.38 (n=8) 1-3 33.0±17.5 29.0±14.6 38.0±20.2 0.63±0.20 2.16±1.08 3-5 31.8±14.2 30.1±14.5 38.1±19.5 0.92±0.13 1.61±0.98 5-10 35.2±20.8 25.0±9.5 39.8±23.0 1 year 0-1 41.0±17.5 28.1±8.4 30.9±9.6 0.92±0.41 1.31±0.44 (n=6) 1-3 42.8±16.9 27.6±9.1 29.7±9.6 1.00±0.30 1.05±0.36 3-5 41.9±9.5 27.0±5.9 31.0±7.6 1.22±0.13 0.91±0.43 5-10 41.2±9.0 27.2±6.5 31.6±7.1 3 month 0-1 45.4±9.9 15.7±5.6 38.8±7.4 1.02±0.10 1.42±0.37 (n=7) 1-3 33.5±11.3 19.4±4.3 47.0±11.3 0.93±0.14 1.73±0.65 3-5 32.9±10.7 19.2±5.6 47.9±10.1 0.96±0.10 1.66±0.57 5-10 28.7±7.9 19.7±4.7 51.6±9.6 Sites ** ** ** ** ** Depth ns ns ns ** * S x D ns ns ns * ns LSD 5% 14.7 9.7 14.8 0.24 0.43
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Figure 6.4. Bivariate plots for values of mean-weight diameter (MWD) of soil aggregates versus clay content for three sampling depths for Kelian soils.
Figure 6.5. Bivariate plots for values of bulk density versus clay content for three sampling depths for Kelian soils.
0-1 cm
0
1
2
3
4
5
0 20 40 60 80Clay (%)
MW
D (m
m)
1-3 cm
0
1
2
3
4
0 20 40 60 80Clay (%)
MW
D (m
m)
3-5 cm
0
1
2
3
4
0 20 40 60 80Clay (%)
MW
D (m
m) Analogue
7 year1 year3 month
0-1 cm
0
0.3
0.6
0.9
1.2
1.5
0 20 40 60 80Clay (%)
Bul
k de
nsity
(g/c
m3 ) 1-3 cm
0
0.3
0.6
0.9
1.2
1.5
0 20 40 60 80Clay (%)
Bul
k de
nsity
(g/c
m3 )
3-5 cm
0
0.3
0.6
0.9
1.2
1.5
0 20 40 60 80Clay (%)
Bul
k de
nsity
(g/c
m3 )
Analogue7 year1 year3 month
134
6.3.2. Chemical properties of Kelian soils
Mature tropical soils have commonly undergone intensive leaching and
pedogenesis due to high rainfall (in excess of 2500 mm per annum) coupled with warm
temperatures throughout the year. Soil acidification occurs relatively quickly even for
soils formed from non-acidic parent materials (Birkeland, 1999; Fageria and Baligar,
2001; Idowu, 2003). This study shows that soils at the Kelian site were more acidic
under native forest condition (pHw values 4.0-4.3) than for rehabilitated soils (mean 5.3-
5.8). The pHw values were similar within the sample depth (0-10 cm) for individual
sites (Table 6.2). Lime was applied as dolomite (3 ton/ha) during site preparation for
rehabilitation of 3 month and 1 year sites which is presumably partly responsible for the
higher pH of rehabilitated sites relative to forest sites. Soil pH of the 7 year sites was
also as high as limed sites but the 7-year site was not limed and was prepared by
replacing topsoil from the Lingau area (near nursery) at 4000 m3/ha (approximately
equivalent to a 40-cm thick layer). This topsoil was presumably less acidic than soils of
the analogue site. Soil pH may also have been affected by the decomposition of the
dense legume cover crop used initially at the rehabilitated site.
Soil samples from the Kelian sites mostly contained low levels of soluble salt as
shown by the low values of electrical conductivity (EC 1:5) < 0.2 dS/m, however a few
samples had EC values higher than 0.3 dS/m. Thus in general salinity is not a problem
for plant growth on rehabilitated mine sites at Kelian. In contrast, goldmine waste
dump in Western Australia often have EC values higher than 2 dS/m due to very saline
native soils in this region (Chapter 5; Osborne, 1999). At Kelian the salt content of
soils at gold mine sites is sometimes associated with sulfate due to oxidation of pyrite
where gold mineralisation occurs in pyrite bearing host rocks. High salinity as soluble
sulfate occurs at some locations on the KEM site adjacent to stockpiles of sulphidic
rocks and which corresponds to acid mine drainage. This local hazard must be managed
to minimize the impact on the surrounding area (Tongway et al., 1997; Eaglen et al.
1998).
Total soil carbon (TC) increased systematically with age of rehabilitation and
consistently decreased with depth (Table 6.2). Mean concentration of TC was about 5
g/kg for the recently rehabilitated sites, and increased up to 95 g/kg for the 7- year sites
for the 0-1 cm depth. The average concentrations of TC in the bank and trough zones of
the 7-year site were comparable to that of the native forest (Figure 6.6). It is very likely
135
that finely divided macro-organic matter,, was included in the sample due to its intimate
mixture with mineral soil. This is unavoidable. The trough zone generally contains
higher TC (85 g/kg, 0-1 cm depth) as was found for ripping lines of a rehabilitated
bauxite mine at Jarrahdale, Western Australia (Ward, 2000). The ripping of surface soil
was only used for early rehabilitation (1994) in Kelian. Contour ripping is made across
slopes so that the structure can intercept overland flow. Field experience at that time
however showed a very strong impact of running water during high rainfall events that
flooded riplines on the newly rehabilitated land and which caused severe damage to
riplines. Subsequently ripping was carried out parallel to slopes and the use of fast
growing creepers (legume cover crops) helps minimize the impact of rain splash erosion
and surface run-off which occurs in the trough zone which is protected by this
vegetation. This is probably the reason why the bank soils (ripline crest) contains
higher organic matter than in the trough soils (ripline bottom) due to erosion of organic
matter from troughs (i.e. the reverse of the Western Australian observation) (Ward,
2000). Organic matter (total carbon) in soils at the 7 year site is already approaching the
level of soil carbon under the native forest. However, soil carbon values are relatively
low (< 20 g/kg) for soils in the recently rehabilitated sites (i.e. mound and depression
for the 1 year site; steep and gentle slopes for the 3 month site) (Figure 6.6).
Figure 6.6. Mean values of total soil carbon for various micro-topographic zones for rehabilitated mine sites and forest soils.
Values of total nitrogen (TN) and potentially mineralizable N (PMN) increased
with age of rehabilitation and significantly differed between the micro-topographic
zones (Figure 6.7). Total N was estimated to have an average value about 6.3 % of the
value for total carbon for all sites with the equation: TN = 0.063 TC + 0.54 (r2 = 0.87).
0
20
40
60
80
100
120
Forest Bank Trough Mound Depres Steepslope
Gentleslope
7 year 1 year 3 month
Tota
l car
bon
(g/k
g)
0-1cm
1-3cm
3-5cm
5-10cm
136
The slope of this relationship was larger for rehabilitated sites (0.080) than the value for
forest soils (0.046) (Figure 6.8). For all soil samples, the PMN value is approximately
0.98 % of total nitrogen (Figure 6.9). For 0-5 cm depth and assumed BD 1 g/cm3, the
average amounts of PMN range from about 6 kg/ha (3-month sites) to 28 kg/ha (7-year
sites). For rehabilitated bauxite mine sites in Western Australia, mean amounts of
ammonium-N are about 4 kg/ha and the mean rate of N mineralization is 42±11 kg/ha
per annum (7-year old site) which is significantly higher than the rate for native jarrah
forest sites (26±13 kg/ha per annum) (Todd et al., 2000a).
Mineralizable N is of significance in relation to the N fertility management of
soils and the value may be used to indicate N supplying power of the soil for plant
uptake (Gianello and Bremner, 1986; Picone et al., 2002; Zhang et al., 2002) and as an
indicator of the long-term nitrogen pool (Sanchez et al., 2001). Soil nitrogen is made
available for plant uptake through ammonification and nitrification of organic N
compounds, both processes are affected by microorganisms. Increased mineralizable N
indicates improved biological fertility and increases may occur for 5-10 years after
rehabilitation (Todd et al., 2000a). It needs to be noted that nutrient decomposition and
uptake in the wet tropics is often via fungi linking litter with vascular plant roots and
short-circuiting the soil. Fungi were clearly active in the forested analogue sites as were
fine plant roots; which had ramified throughout the body of the litter.
Figure 6.7. Mean values of total nitrogen and mineralizable nitrogen for various micro- topographic zones for rehabilitated mine site and forest soils.
01
2345
678
910
Forest Bank Trough Mound Depres Steepslope
Gentleslope
7 year 1 year 3 month
Tota
l N (g
/kg)
0-1cm
1-3cm
3-5cm
5-10cm
0
10
20
30
40
50
60
70
80
Forest Bank Trough Mound Depres Steepslope
Gentleslope
7 year 1 year 3 month
Min
eral
izab
le N
(mg/
kg)
137
Table 6.2. Site and sampling information, mean values and standard deviation of chemical properties for rehabilitated mine sites and analogue (forest) soils at Kelian. Bic-P and Bic-K, bicarbonate-extractable P and K. Summary of ANOVA is presented (ns, not significant; * and ** significant at 5 % and 1 % probability). Sites Depth pHw (1:5) EC (1:5) Bic-P Bic-K Total C Total N Mineralizable N (cm) (dS/m) (mg/kg) (g/kg) (mg/kg)
Forest 0-1 3.94±0.36 0.218±0.073 11.9±4.3 139±44 108 ±32.8 5.55±1.34 57±13 (n=5) 1-3 3.99±0.09 0.140±0.014 4.9±1.1 80±17 61.3±9.4 3.62±0.44 39±18 3-5 4.12±0.11 0.107±0.016 5.1±2.0 52±14 39.6±11.7 2.43±0.57 26±17 5-10 4.32±0.07 0.084±0.012 5.0±2.5 45±18 26.3±6.4 1.77±0.37 17±11 7 year 0-1 5.73±0.53 0.317±0.052 22.6±11.7 226±76 94.8±27.5 7.88±1.75 50±29 (n=8) 1-3 5.57±0.60 0.130±0.017 8.1±2.5 104±41 36.4±9.6 3.79±0.83 56±22 3-5 5.44±0.56 0.097±0.017 8.1±4.8 79±37 23.2±8.6 2.64±0.63 34±21 5-10 5.24±0.54 0.085±0.024 7.9±5.3 63±28 17.4±9.6 1.91±0.74 28±19 1 year 0-1 5.87±1.13 0.098±0.041 10.9±3.1 73±21 14.4±8.4 1.82±0.97 26±11 (n=6) 1-3 5.84±1.40 0.083±0.053 8.1±2.9 55±17 7.1±2.1 1.05±0.46 11±7 3-5 5.84±1.41 0.085±0.078 10.3±7.1 48±16 5.2±1.5 1.04±0.39 16±6 5-10 5.88±1.46 0.080±0.079 7.3±4.0 48±14 5.3±2.3 0.82±0.30 12±6 3 month 0-1 5.33±0.55 0.034±0.028 18.3±14.0 24±10 5.4±1.5 0.51±0.21 12±7 (n=7) 1-3 5.56±0.94 0.055±0.057 22.2±24.3 28±22 5.3±1.4 0.54±0.19 15±9 3-5 5.48±0.97 0.048±0.046 20.9±16.8 23±12 5.6±1.6 0.45±0.15 16±5 5-10 5.40±0.99 0.054±0.077 18.8±13.9 21±14 5.8±1.7 0.42±0.25 11±8 Sites ** ** ** ** ** ** ** Depth ns ** ns ** ** ** ** S x D ns ** ns ** ** ** * LSD 5% 0.49 0.055 5.9 36 13.8 0.86 17
138
Figure 6.8. Total nitrogen is strongly related to total carbon for Kelian soils.
Figure 6.9. Potentially mineralizable N (PMN) is linearly related to total N for Kelian soils.
Bicarbonate-extractable phosphorus (bic-P) varied widely for the Kelian soils with
average concentrations ranging from about 12 mg/kg in the native forest soils (0-1 cm
depth) to above 70 mg/kg in the newly rehabilitated sites. The bic-P concentration
decreased with depth for the native forest soils and the 7-year site soils (Table 6.2).
Topsoil of the 7-year sites contained twice the bic-P present in topsoil of the primary
forest.
The bic-P values tend to increase with increasing concentration of soil carbon,
particularly for the 7-year site and the native forest sites (Figure 6.10). The much
higher bic-P concentrations in soils for the 3-month and 1-year rehabilitation sites is due
to the application of P-fertilizer which did not occur for the 7-year site, thus the effect of
biomass contribution to bic-P is confounded to some extent by P-fertilizer application.
Furthermore the increases in biomass and soil carbon may be responses to greater soil
fertility (bic-P). Phosphorus is known to be relatively immobile in soil but is lost by
erosion. Loss of soil P due to erosion is greater when ground cover is low (Kaihura et
y = 9.77 x + 7.02r2 = 0.70
0
20
40
60
80
100
0 2 4 6 8 10Total N (g/kg)
PMN
(mg/
kg)
Forest
7 year
1 year
3 month
y = 0.046 x + 0.67r2 = 0.99forest
y = 0.080 x + 0.40r2 = 0.96rehab sites
0
2
4
6
8
10
12
0 50 100 150 200Total carbon (g/kg)
Tota
l N (g
/kg)
Analogue7 year1 year3 month
139
al., 1999; Le Bayon and Binet, 1999; Bationo and Buerket, 2001). Therefore, the
legume cover crop (creeper) introduced in the early stage of mine site rehabilitation at
Kelian provides benefits for soil fertility by both reducing rain splash-induced erosion
and increasing soil biomass which increases organic P reserves in the soil.
Bicarbonate extractable-potassium (bic-K) was much higher in old rehabilitated
site (7-year site) soils relative to native forest soils. A large proportion of bic-K is
accumulated in the 0-3 cm depth (Table 6.2). Biomass cycling may play an important
role in restoring the K pool in the mature rehabilitated sites (Paniagua et al., 1999). For
the Kelian sites, there are strong relationships between extractable-K and total carbon
for the 7-year old sites (r2 = 0.75) and for the primary forest sites (r2 = 0.89) (Figure
6.10).
Figure 6.10. Bivariate plots showing values for bicarbonate extractable-P (left) and bicarbonate extractable-K (right) in relation to soil total carbon for Kelian soils.
6.3.3. General discussion of analytical data
Provision of optimum soil conditions together with the establishment of
sustainable plant communities are prime objectives of mine rehabilitation. Techniques
for mine site rehabilitation sometimes change during the course of mining activities.
This variation dealing with hazard like pyrite and salt includes site preparation, topsoil
application, fertilizer usage, plant species selection and maintenance work. Due to this
non-uniformity of treatment, direct comparisons between sites of different age might not
be reliable owing to various initial conditions. This situation is anticipated for the
Kelian sites where topsoil handling has changed from spreading and ripping to ‘pimple-
dumping’. This latter practice alters local terrain so that slope angle and length are
reduced considerably. This pimple-dumping method increases retention of transported
particles, litter (organic matter) and water. Rough terrains generally have the potential
to retain soil resources including water (Tongway and Ludwig, 1997). Field visual
y = 1.18x + 10r2 = 0.89Analogue
y = 1.99x + 32 r2 = 0.757 year
0
50
100
150
200
250
300
350
0 50 100 150 200Total carbon (g/kg)
Bic
-K (m
g/kg
)
Analogue7 year1 year3 month
y = 0.090x + 1.4r2 = 0.66Analogue
y = 0.16x + 4.6r2 = 0.387 year
0
20
40
60
80
0 50 100 150 200Total carbon (g/kg)
Bic
-P (m
g/kg
)
140
observations show that soils remain moist in depressions between topsoil dumps
(pimples) at the recent rehabilitated sites.
Soil properties are often monitored in a ‘pseudo-time series’ that basically use a
set of plots of different ages. Rapid changes in soil properties seems to occur
concurrently with vegetation development. At Kelian planted trees have reached 10 m
height or more within 7 years. This rapid growth might reflect the high rainfall as the
dominant driving force in a tropical region, in contrast to much slower growth under
much less rainfall in semi-arid environments (Hodgkinson and Freudenberger, 1997;
Ludwig and Tongway, 1997; Bell, 2001). Litter abundance has increased substantially
in the older plots. Understorey species or ground cover are almost absent in old
rehabilitated sites due to senescence and high canopy cover. The use of fast growing
pioneer species provided rapid surface stabilization and retention of soil resources.
Organic matter from these species may have contributed considerably to nutrient pools.
Increasing soil carbon may lead to the improvement of other soil properties
including compaction, porosity and aggregate stability (Loch and Orange, 1997).
Changes in physical properties of topsoils are partly due to the mechanical impact of
rainfall. At Kelian newly replaced topsoil has (fine-medium) granular to sub-angular
blocky structure and is relatively friable. It is noted that soil aggregates slake easily for
recently rehabilitated sites and that aggregate stability is much higher for the 7-year
sites due to much higher organic matter and the many roots of strongly established
vegetation. Previous studies have shown that soil aggregate stability is closely related
to either organic matter and/or other cementing agents (e.g. sesquioxides) (Garcia-
Olivia et al., 1999; Neufeldt et al., 1999; Six et al., 2000; Zhang and Horn, 2001).
Different components of organic matter may have different impacts on aggregate
stability (Piccolo and Mbagwu, 1999). In general, soil structure stabilization occurs
naturally under established vegetation.
Increased organic matter in rehabilitated mine soils in the long-term is indicative
of the improved nutrient pool. This was noticed particularly for the 7-year rehabilitated
sites where residual direct effects of previously applied fertilizers might have been
reduced or even become negligible. Long-term effects of organic amendments
significantly improve mine soil quality in addition to the increase in soil organic matter
(Schwenke et al., 2000). Mineralizable nitrogen, extractable phosphorus and aggregate
stability commonly increase (Bendfeldt et al., 2001). Under natural systems, this
improvement mostly happens through plant production as appears to be the case at
141
Kelian. A question to be resolved is whether the current vegetation at rehabilitated sites
is functioning optimally and is sustainable in the long-term, as occurs in the primary
forest. Vegetation monitoring is necessary to ensure the rehabilitation is progressing
satisfactory and whether additional amelioration is necessary.
142
Chapter 7. Landscape Function Analysis for the assessment of mine
site rehabilitation under a tropical climate
7.1. Introduction
Mine site rehabilitation is implemented primarily to improve soil quality for the
post-mining environment and to ensure that rehabilitation is in compliance with the
imposed regulations (Bradfield et al., 1996; Brooks et al., 1996). Open-cut mining
operations often generate extreme disturbance as topsoil is either removed entirely, or
removed and then replaced. As a consequence of considerable land clearing and
disturbance associated with open-cut mine, careful design is required for immediate and
long-term site management (Farrell and Kratzing, 1996). Mining and processing
operations may result in the creation of massive amounts of waste rock and regolith
(overburden) and tailings (Osborne, 1996; Tordoff et al., 2000). Derelict landscapes are
created and need to be rehabilitated. Substantial improvement in land resource quality
may occur over short or long periods depending inter alia upon mine types, materials
and technology for rehabilitation, together with environmental factors (Bell, 1996;
White et al., 1996).
Mining operations are often of short duration relative to the time required for
complete rehabilitation. Hence, there is a need for assessment criteria that provide
confidence to mining companies and regulators on whether rehabilitated sites are
advancing or declining in self-sustainability, so that appropriate and timely remedial
actions may be identified. This assessment may be provided by indicators generated
through systematic monitoring of key parameters. Along with other important factors
such as the monitoring of water quality and aquatic biodiversity, the progress in mine
site rehabilitation towards sustainability may be monitored or reflected by vegetation
growth indicators such as abundance, diversity, height and diameter of trees and shrubs.
A typical ‘successful’ rehabilitation is commonly indicated by optimum plant density,
species richness, soil cover and biomass accumulation. Restored habitat in rehabilitated
mine sites also provides a niche for returning birds (Armstrong and Nichols, 2000;
Passell, 2000), ants (Majer, 1996; Folgarait, 1998; Majer and Nichols, 1998; Bisevac
and Majer, 1999), amphibians and reptiles (Galan, 1997). These biota can be monitored
as indicators of rehabilitation success.
143
Monitoring the progress of a rehabilitation program is a classical problem, i.e.
how to predict expected outcomes based on the current values; whether mature
rehabilitated sites are functioning well and exhibiting sustainable development or
whether they are in need of treatment. A number of monitoring techniques have been
developed, each with its own benefits and limitations but most follow similar
methodology. In this study, a single procedure known as Ecosystem Function Analysis
(EFA) (Tongway and Hindley, 1995; 2004) is introduced as a tool for the assessment of
soil conditions in the field. The basic of EFA procedure has been presented earlier in
Chapter 4 (Section 4.2.1). This technique has a strong background concept in ecology
and resource control (Bell, 2001; Jasper, 2002) and has potential for assessing soil
conditions at rehabilitated mine sites in arid and semi-arid environments (Tongway et
al. 1997). Testing the concept in a tropical forest is challenging owing to the much
greater rainfall, warm climate, different soil conditions and different biota in the tropics.
The main purpose of this chapter is to evaluate the reliability of the landscape
function analysis (LFA) protocol for the assessment of soil conditions at a rehabilitated
mine site at Kelian (Indonesia). It relates the indicator-based values to the laboratory
and field measurements discussed earlier (Chapter 6) in order to assess if the LFA
indicators adequately represent site and soil properties for a wet tropical environment.
7.2. Materials and Methods
7.2.1. Assessment of soil surface conditions
The total area affected by mining activities is about 1285 ha. By the end of 2001,
a total of 1021 ha (79.5 %) had been replanted with native trees (KEM fact sheet).
Three mine sites were selected to represent land rehabilitation implemented in 1994 (7
year), 2000 (1 year) and 2001 (3 month) prior to the fieldwork. The observation
includes an analogue site (i.e. a primary forest near the Namuk tailing dam) as a
reference.
At each site a transect was set up down-slope and soil surface conditions were
recorded. The soil surface assessment was conducted to characterize individual
landscape zones. The procedure for soil surface assessment is presented in Section
4.2.1 (Chapter 4). The native forest comprises a single zone simply noted as litter bed
reflecting the continuous litter cover and its role as a “patch”. The 7-year site consist of
two zones (bank and trough) due to ripping. The 1-year site is characterized by mound
144
and depression zones as a result of islands of topsoil being dumped. The 3-month site
also had topsoil spread in a similar way to the 1-year site, and mostly consisted of run-
off zones on coalescing dumps. The run-off zones at the 3-month site have been
subdivided into steep and gentle slopes.
There are 26 observation points representing the above seven land surface zones.
From the soil surface assessment, three landscape indices were calculated, i.e. stability,
infiltration and nutrient cycling (see Table 4.1 for reference of surface indicators used
for these indices). Subsequently, soil samples were collected from 0-1, 1-3, 3-5 and 5-
10 cm depths for individual zones. Details of soil sampling, laboratory analytical
methods for the following physical and chemical properties have been presented earlier
in Chapter 6 (Sections 6.2.2 and 6.2.3). To relate landscape-based to soil properties, the
nutrient cycling index has been related to total soil carbon, potentially mineralizable
nitrogen, and soil respiration; stability index to aggregate stability; and infiltration index
to bulk density and field infiltration.
7.2.2. Measurement of soil respiration and field infiltration
Soil respiration estimates soil microbial and root activity and was measured by
entrapping carbon dioxide (CO2) released as a product of metabolism. This may be
conducted in the field using a simple apparatus (inverted box) which retains evolving
gas in a closed system (Figure 7.1). Values of soil respiration are related to the LFA
nutrient cycling index. The released CO2 reacts with an alkali solution (0.5 M KOH)
(Hartigan, 1980; Tongway and Ludwig, 1996). The rate of soil respiration is estimated
by measuring electrical conductivity (EC) of the alkali solution after 24 hours (Wollum-
II and Gomez, 1969). The duration for field incubation may vary depending on soil
conditions. For example, soils containing high amounts of biological activity, such as
Kelian soils, may only need 8 hours for a sufficient reading due to the high activity of
soil biota. The respiration rates exceeded the capacity of our apparatus, and we
resolved on 8-hour runs to avoid saturating the KOH and losing data. We have since
used larger volumes of KOH, keeping its concentration constant and retaining 24-hour
as the standard measurement period. The EC reading is related to a calibration curve
developed for fresh and CO2-saturated KOH. For a 20-cm diameter ring and 20 ml of
0.5 M KOH, soil respiration can be calculated from the formula:
145
t1
31410000
xxx)220(x nRespiratio
12
2 ××−−
=
where:
respiration is expressed as mg CO2/m2/hr
x = sample EC (mS/cm)
x1 = EC of CO2-saturated KOH (45.74 mS/cm)
x2 = EC of fresh KOH (vary slightly, approximately 114.6 mS/cm)
t = time required for measurement (hour).
Figure 7.1. Soil respiration gear consisting of Perspex lid, ring and petri dish containing 20 ml of 0.5 M KOH (left) and when the apparatus is fully installed and secured (right) (photos by David Tongway).
Field infiltration was measured at a saturated condition using a Mariotte-type
permeameter (Figure 7.2), with a positive pressure head of 10 mm. The measurement
was undertaken by taking a record of the drop in water level inside the main (reservoir)
cylinder at constant time intervals until a constant rate is obtained (White et al., 1992).
Field infiltration rate can be related to the LFA infiltration index.
Figure 7.2. The apparatus for measuring field infiltration (photos by David Tongway).
146
7.2.3. Statistical analysis
Simple linear and non-linear regression and correlation analyses were employed
to describe relationships between landscape indices and soil attributes obtained from the
field measurements (infiltration and soil respiration) and laboratory analyses.
7.3. Results and discussion
7.3.1. Landscape indices of rehabilitated mine sites
Newly rehabilitated sites at the Kelian mine sites had low to middle values for
three landscape indices-stability, infiltration and nutrient cycling, while the analogue
site had very high values (Figure 7.3). The indices for the 7-year site were somewhat
lower but were close to the values recorded in the analogue site. This is to be expected,
as the analogue site is almost a mature system with a high density of tall trees, shorter
trees and shrubs, with highly abundant litter. If rehabilitation is successful, EFA indices
increase in numerical value over time to eventually achieve an equilibrium value. The
rate of change and the numerical values achieved are used to indicate how functional the
rehabilitated land has become.
A rapid development takes place after rehabilitation is initiated and therefore more
observations in the early years of rehabilitation are useful in defining the ecosystem
development curve. The values for stability index increased from 38 % (the 3-month
site) to 68 % (the 1-year site); infiltration index 26 to 39 % and nutrient cycling index
14 to 36 %. The gradient is much lower over the period of 1 and 7 year sites (2-3 %
annual increment). This result implies that the initial conditions are critical in ensuring
a functional and sustainable environmental for landscape development. Overall the
current status of the Kelian rehabilitated mine sites, landscape recovery is satisfactory
and potentially sustainable. If there are sufficient data points, a critical threshold for
self-sustainability can be identified using a sigmoid curve (Graetz and Ludwig, 1978;
Noy-Meir, 1981). At least 6 points, including both ‘fresh’ rehabilitation and a mature
analogue are required. It is possible to undertake long-term ecological research that
enables one to follow the gradient of landscape development for a single site, but this
kind of study is constrained by time and location. Therefore, a ‘pseudo-time series’
using a space for time substitution, is more commonly used by sampling different sites
147
created at different times, as has been done for the Kelian sites. With the KEM mine
closure commencing in 2004, much attention is now being directed towards
rehabilitation work. Providing a sufficient training for Kelian environmental staff in the
use of EFA method is therefore beneficial so that site monitoring can be carried out
until final mine closure is achieved in 2007.
Figure 7.3. Mean values of LFA indices for rehabilitated mine sites and analogue site in Kelian (Indonesia).
7.3.2. Relationships of stability index to MWD of water-stable aggregates and soil carbon
Rehabilitated mine sites at Kelian show a considerable increase in soil stability
index over time. It is expected that stability index is related to other soil attributes
defining soil stability. For this purpose, water-stable aggregate (WSA) expressed as
mean-weight diameter (MWD) of aggregates obtained by wet sieving is utilized as an
estimate. It is noted that for the youngest location (3-month site) the soil surface is still
undergoing natural consolidation processes and scores obtained for the calculation of
stability index are mostly 1 or 2 which are quite low values. This low stability index
should be anticipated for newly constructed sites partly due to the low soil cover, lack of
bio-crust, low biomass and high erosion (Tongway et al., 1997 and 1998; Kearns and
Barnett, 1999). Stability index is not simply related to the MWD of water-stable
aggregates for both the 0 - 1 cm and 1-3 cm soil layers if data for all sites are
considered. For the 3-month site, it is the values for stability index that are low, not the
values for MWD. However, for a subset of data excluding the 3-month site, values of
stability index tend to increase with increasing MWD values (Figure 7.4). For mature
0
20
40
60
80
100
3 month 1 year 7 year Analogue
Sites
LFA
inde
x (%
) StabilityInfiltrationNutrient cycling
148
sites (7-year and analogue) the stability index is essentially constant irrespective of the
large variation in MWD.
The importance of soil organic matter to the soil stability index is demonstrated
by the positive exponential relationship of this index to total soil carbon (Figure 7.5).
The value for the index appears to reach a near maximum when the surface soil reached
levels of about 50 g/kg soil carbon for 0-1 cm depth and 20 g/kg soil for 1-3 cm depth.
Figure 7.4. LFA stability index versus values of mean-weight diameter (MWD) of soil aggregates obtained by wet sieving for the 0-1 cm and 1-3 cm depth. Regression lines are fitted to data for 1-year, 7 year and analogue sites.
Figure 7.5. Bivariate plots for stability index versus total soil carbon for the 0-1 cm and 1-3 cm soil layers.
Variation in values of the stability index (Y) is mostly explained by values of soil
total carbon (X1); addition of WSA (X2) improves the prediction by 20 % although the
coefficient is negative. The multivariate linear equation can be written as follows:
Y = 50.9 + 0.47 X1 − 2.90 X2 (R2 = 0.73).
0-1 cmy = 6.25 x + 63.4r = 0.749
0
20
40
60
80
100
0 1 2 3 4 5MWD wet sieve (mm)
Sta
bilit
y in
dex
(%)
Analogue7 year1 year3 month
1-3 cmy = 5.52 x + 68.1r = 0.625
0
20
40
60
80
100
0 1 2 3 4MWD wet sieve (mm)
Stab
ility
inde
x (%
)
0-1 cm
y = 12.6 Ln(x) + 26.8r2 = 0.79
0
20
40
60
80
100
0 50 100 150 200Total carbon (g/kg)
Stab
ility
inde
x (%
)
Analogue7 year
1 year3 month
1-3 cm
y = 15.0 Ln(x) + 26.9r2 = 0.69
0
20
40
60
80
100
0 20 40 60 80Total carbon (g/kg)
Stab
ility
inde
x (%
)
149
The negative coefficient of WSA has a large value of standard error (4.17) which is
partly related to values for the 3-month site. For the 1- and 7-year rehabilitated mine
sites and analogue soils, the prediction using these two variables provides a positive
coefficient for WSA as follows: Y = 64.0 + 0.20 X1 + 0.81 X2 (R2 = 0.77). The 3-
month site used freshly stripped topsoil, which was “ecologically mature” in itself, but
its physical presentation with low plant cover and high slake lowered its LFA values.
7.3.3. Relationships of infiltration index to soil attributes and field infiltration
Infiltration index provides an estimate of the capability of soil to retain and utilize
surface water (rainfall). It does not measure the amount of water intake nor soil
permeability. Three soil properties are considered in relation to movement and
retention of water through the surface soil, thus influencing the calculated infiltration
index, i.e. bulk density, clay content and soil carbon. Values of infiltration index
increased with age of rehabilitation, however soil bulk density (BD) varied substantially
for each rehabilitation site for different depths so close relationships with infiltration
index do not exist. The infiltration index tends to decrease with increasing values of BD
for particular soil depths. The prediction is weak irrespective of soil depth used for
providing BD values (Figure 7.6).
Soil texture is one of the surface soil attributes used to calculate infiltration index.
Scores generally decrease for soils with more clayey texture as was observed in this
research (Figure 7.7).
The infiltration index was positively related to total carbon by an exponential
relationship (Figure 7.8). As with other indices, the interpretation of this relationship is
restricted due to the nature of the data distribution for the 7-year sites. Since the index
is largely affected by scores of litter abundance and to a lesser extent by canopy cover,
there is a higher index for sites with mature and dense vegetation. Litter decomposition
and activities by microorganisms and soil fauna create abundant, stable pores which are
important for water movement within the profile and for aggregate stability (Oades,
1984). This vegetation effect is most evident for locations with similar site preparation,
micro-geomorphology and soil materials, where infiltration index is primarily
associated with changes in litter production and soil organic constituents.
150
Using multivariate linear regression, values of infiltration index (Y) are adequately
predicted by concentrations of soil total carbon (X1) and clay content (X2) by the
equation: Y = 48.5 + 0.25 X1 − 0.49 X2 (R2 = 0.81).
Figure 7.6. Relationships between infiltration index and bulk density for different soil depths.
Figure 7.7. Infiltration index versus clay content for 0-1 cm and 1-3 cm soil depths.
0-1 cm
y = -19 Ln(x) + 112 (r2 = 0.20)0
20
40
60
80
0 20 40 60 80
Clay (%)
Infil
tratio
n in
dex
(%)
Analogue7 year1 year3 month
1-3 cm
y = -20 Ln(x) + 115 (r2 = 0.37)0
20
40
60
80
0 20 40 60 80
Clay (%)
Infil
tratio
n in
dex
(%)
0-1 cm
y = -25 x + 63 r2 = 0.36
0
20
40
60
80
0 0.3 0.6 0.9 1.2 1.5Bulk density (g/cm3)
Infil
tratio
n in
dex
(%)
0-3 cm
y = -27 x + 67r2 = 0.24
0
20
40
60
80
0 0.3 0.6 0.9 1.2 1.5Bulk density (g/cm3)
Infil
tratio
n in
dex
(%)
0-5 cm
y = -33 x + 74r2 = 0.23
0
20
40
60
80
0 0.3 0.6 0.9 1.2 1.5Bulk density (g/cm3)
Infil
tratio
n in
dex
(%)
Analogue7 year1 year3 month
151
Figure 7.8. Infiltration index versus total carbon for 0-1 cm and 1-3 cm soil depths.
In an attempt to verify that the infiltration index serves as a reliable indicator of
field conditions, values of water infiltration were also measured under a saturated
condition. Infiltration measurement produced the surprising finding that some soil
samples have an extremely high rate of infiltration (> 1000 mm/hr) which is very poorly
predicted by the infiltration index. A weak positive linear relationship occurred for soils
with an infiltration rate less than 400 mm/hr (Figure 7.9). Exceptions were soils on
recent rehabilitation (1-year sites) or soils with extensive plant root mats (the analogue
site). This is partly due to high porosity of less compacted soils or where extensive bio-
pores and roots exist as in the mature vegetation site. Infiltration measurements
indicated extremely high values in “new” soils. These appeared to behave like deep
gravel beds. Several published works (Gillman et al., 1989; Gillman and Bristow,
1990) reported this phenomenon in Atherton tableland soils in Queensland. LFA
infiltration index fails on soils with these properties.
Figure 7.9. Bivariate plot for LFA infiltration index versus field infiltration rate for Kelian soils.
0-1 cm
y = 10.1 Ln(x) + 12.2r2 = 0.79
0
20
40
60
80
0 50 100 150 200
Total carbon (g/kg)
Infil
tratio
n in
dex
(%)
Analogue7 year1 year3 month
1-3 cm
y = 12.7 Ln(x) + 10.5r2 = 0.77
0
20
40
60
80
0 20 40 60 80
Total carbon (g/kg)
Infil
tratio
n in
dex
(%)
20
30
40
50
60
70
80
0 1000 2000 3000 4000
Infiltration rate (mm/hr)
Infil
tratio
n in
dex
(%)
Analogue
7 year
1 yeary = 0.054 x + 46.7r2 = 0.48
20
30
40
50
60
70
80
0 100 200 300 400
Infiltration rate (mm/hr)
Infil
tratio
n in
dex
(%)
152
In Figure 7.9 the extremely high infiltration rates that are measured are probably
due to incorrect values of the surface area for infiltration (i.e. the radius of the confining
ring, 10 cm in this study). In some soils such as the tropical soils of Kelian, with very
high levels of organic matter, root materials, and microtopography, the surface area
through which water can flow is probably a lot greater than the present value. To cope
with the technical difficulty of measuring infiltration in extensively rooted soils, the
height of the infiltration ring needs to be adjusted (e.g. to 20-25 cm height) so that the
ring can be inserted into a greater depth which may prevent lateral seepage. The deeper
insertion of the confining ring may not affect the calculation because the infiltration rate
is largely determined by water volume (reading)and surface area. As forest soils show
no signs of erosion, they clearly exhibit rapid infiltration and the measured high
infiltration rate is consistent with the behavior of soils.
7.3.4. Relationships of nutrient cycling index to soil attributes including soil respiration
The nutrient cycling index (NCI) increases considerably with age of rehabilitation.
The NCI values tend to increase with increasing values of potentially mineralizable
nitrogen (PMN) but the trend is quite weak and diffuse for both 0-1 cm and 1-3 cm
depth (Figure 7.10). The weak relationships are partly due to data for the 7- year site
for which the NCI values are almost constant despite a wide range of PMN values. The
largest variation occurs between bank (69±20 mg/kg) and trough zones (31±24 mg/kg).
There is no conclusive evidence that increased nitrogen mineralization is always
reflected in higher values of the nutrient cycling index.
Figure 7.10. Nutrient cycling index (NCI) is not simply related to potentially mineralizable nitrogen (PMN) for 0-1 cm and 1-3 cm soil depths.
0-1 cm
y = 15.4 Ln(x) - 7.9r2 = 0.52
0
20
40
60
80
0 20 40 60 80 100Mineralizable N (mg/kg)
NC
I (%
)
Analogue7 year1 year3 month
1-3 cm
y = 12.3 Ln(x) + 4.2r2 = 0.36
0
20
40
60
80
0 20 40 60 80 100Mineralizable N (mg/kg)
NC
I (%
)
153
The nutrient cycling index has a strong relationship with soil total carbon and the
prediction is consistent for different soil depths (Figure 7.11). Soil carbon is probably
the best single predictor for all landscape indices. The NCI value is largely (70 %)
attributed to litter components (i.e. abundance, origin and degree of incorporation) and
soil carbon concentration is also affected by litter conditions. Thus a high NCI value is
expected for mature soils with abundant organic matter. However, it should be noted
here that a non-linear relationship exists. For the 0-1 cm depth, the NCI increased
rapidly with increasing soil carbon up to 25 g/kg. Beyond this point, subsequent small
increases in NCI (i.e. the plateau area) are not related to increasing soil carbon. Using
multiple linear regression, NCI values (Y) are adequately predicted by soil total carbon
(X1) and potentially mineralizable nitrogen (X2) by the equation:
Y = 19.8 + 0.24 X1 + 0.25 X2 (R2 = 0.72).
Figure 7.11. Nutrient cycling index (NCI) is logarithmically related to total soil carbon for 0-1 and 1-3 cm soil depths.
Soil respiration was measured at the same sites used for the assessment of nutrient
cycling index. This measurement is used as an estimate of biological fertility. The
result shows a similar range of respiration rates (200 to 800 mg CO2/m2/hr) between
rehabilitated mine sites and analogue site. Soil microorganisms are probably equally
active in soils at rehabilitated sites and analogue forest soils. The increment in NCI
values is not always associated with higher soil respiration (Figure 7.12). The result
suggests a highly dynamic soil condition in these tropical soils. Values of soil
respiration are much higher than soil respiration in the mulga soils in arid and semi-arid
areas of New South Wales which had mean values of 128 to 221 mg CO2/m2/hr for
different treatments of bare soil rehabilitation (Tongway and Ludwig, 1996). The high
respiration rates at Kelian were due to high levels of activity in litter break-down and
0-1 cm
y = 13.4 Ln(x) - 2.4r2 = 0.82
0
20
40
60
80
0 50 100 150 200Total carbon (g/kg)
NC
I (%
)
Analogue7 year1 year3 month
1-3 cm
y = 16.2 Ln(x) - 3.0r2 = 0.74
0
20
40
60
80
0 20 40 60 80Total carbon (g/kg)
NC
I (%
)
154
root activity on the surface. It is noted that quite large roots ran along the soil surface,
with fine roots being very dense and in contact with the litter layer. There was
also a massive fungal infection of the litter. Probably nutrient uptake was directly into
the roots from fungal symbiosis. Available soil moisture all years simply elevated all of
the biological activity rates. The Mulga, on the other hand, has slowly decomposing
litter and is only rarely moist, slowing the rate of respiration. The mulga litter may also
be more resistant to decomposition, due to the protective chemistry (tannins) in the
leaves.
Measuring soil respiration in the wet tropics area of Kelian in East Kalimantan has
exposed some technical problems. This is due to the complex plant litter and the
presence of a root system above the mineral soil horizons. In this situation, the thick
litter cover and a dense mat of near surface roots need to be removed for securing the
respiration chamber in place. As a consequence, the measurement might have severely
under-sampled and hence under-estimated the real values of soil respiration in these
litter-rich soils.
Figure 7.12. Bivariate plot for nutrient cycling index (NCI) versus soil respiration for all samples of Kelian soils (left) and the plot for mean values for micro-topographic zones (right).
7.3.5. Effect of sampling depth on relationships of calculated indices to soil parameters
It is apparent from the current results for Kelian sites that the three indices
calculated in the LFA process are most closely related to measured values for surface
soils (i.e. 0-1 cm). This is not unexpected for 'young' soils, in which the recovery of all
aspects of fertility will be driven by plant productivity and organic matter inputs.
y = 0.053 x + 19.7r2 = 0.15
0
20
40
60
80
100
0 250 500 750 1000Soil respiration (mg CO2/m2/hr)
NC
I (%
)
Analogue7 year1 year3 month
y = 0.17 x - 46.8r2 = 0.57
0
20
40
60
80
100
300 400 500 600 700Soil respiration (mg CO2/m2/hr)
NC
I (%
)
155
However, most soil sampling protocols are based on taking samples to a greater depth,
typically 0-5 cm or 0-10 cm, especially in agriculture systems where mature yet deeply
cultivated soils exist. Therefore it is of interest to determine the relationships between
LFA indices and 'whole' soil profiles to these depths. These relationships were
calculated for two measured parameters, potentially mineralizable nitrogen (PMN) and
soil total carbon (Figure 7.13).
Figure 7.13. Nutrient cycling index (NCI) versus potentially mineralizable nitrogen (PMN) (left) and total carbon (right) calculated for 0-3, 0-5 and 0-10 cm depths. Bulk density for the 5-10 depth was assumed to be the same as for the 3-5 cm depth.
0-3 cm
y = 15.7 Ln(x) - 8.2r2 = 0.41
0
15
30
45
60
75
90
0 20 40 60 80
NC
I (%
)
0-5 cm
y = 16.1 Ln(x) - 10.7r2 = 0.31
0
15
30
45
60
75
90
0 20 40 60 80
NC
I (%
)
0-10 cm
y = 13.7 Ln(x) + 2.3r2 = 0.21
0
15
30
45
60
75
90
0 20 40 60 80PMN (mg/kg)
NC
I (%
)
0-3 cm
y = 15.7 Ln(x) - 3.9r2 = 0.81
0
15
30
45
60
75
90
0 20 40 60 80 100
Analogue7 year1 year
3 month
0-5 cm
y = 16.6 Ln(x) - 3.4r2 = 0.76
0
15
30
45
60
75
90
0 20 40 60 80
0-10 cm
y = 17.7 Ln(x) - 2.7r2 = 0.67
0
15
30
45
60
75
90
0 15 30 45 60Total carbon (g/kg)
156
The LFA nutrient cycling index was positively, but weakly related to PMN for the
0-3 cm depth; this relationship was weaker for the 0-5 cm, and 0-10 cm soil depths.
These data support nutrient uptake directly or in combination with fungi, by a dense
network of fine vascular plant roots. The soil is “short-circuited”. Mineralizable
nitrogen is a very labile pool and hence represents N that is readily available for plant
uptake (Keeney, 1982). Relationships are better for NCI value versus total soil carbon
for all three depths of sampling. This relationship also decreased in reliability (r2) for
greater depths of sampling (i.e. 0-5 and 0-10 cm). Measured total carbon includes pre-
existing carbon in the soil since the ignition method of determining carbon can not
discriminate between new and old carbon including charcoal. In humid regions where
soils have undergone extensive leaching and oxidation, organic C comprises most of
total C for non calcareous soils (Nelson and Sommers, 1982).
This approach should be taken with precaution particularly for ‘young’ soils
undergoing rehabilitation. Diluting the effect of topsoil development by incorporating
subsoil values can obscure the effect of surface development. The nutrient cycling
index indicates carbon cycling and not carbon content. Cycling activity is expected to
be highest at the surface where litter is usually abundant in this environment. In
essence, this LFA index is based purely on surface features. Such features are
sometimes controlled by factors within the profile - roots, crumb-structured clay and the
like which can result in ‘anomalous’ (extreme) values. The indicators are designed to
identify problems relating to surface stability, water availability and nutrient availability
within landscape framework so that immediate actions may be taken if there is a sign of
landscape dysfunction.
7.3.6. General discussion
Landscape indices increased rapidly within 7 years in this pseudo-time series
study. The stability index at 7 years is approaching the values for the analogue site (i.e.
native forest). Values of landscape indices are in the order stability > infiltration >
nutrient cycling. The use of an appropriate analogue site is central to the LFA
procedure although the final configuration of rehabilitated mine sites is not necessarily
the same as for the primary forest (Tongway and Hindley, 2000). LFA is only a guide
to the extent to which the natural function of the restored landscape has returned. The
rapid change of landscape indices after rehabilitation is related to the fast growing
157
legume cover crop that quickly changed scores from 1 to 5, or 1 to 4, or 1 to 10, or 1 to
30 in the first years of rehabilitation. Fast establishment of pioneer vegetation as a soil
surface cover induces more and better niches for soil and plant development. Mine
waste stabilization by vegetation is highly desirable due to root systems binding of soil
particles and its multiplying effects for nutrient utilization, transpiration and landscape
shape recovery (Tordoff et al., 2000). In contrast to revegetated disturbed sites where
diverse species are introduced, the natural recovery of degraded lands is usually
associated with a few pioneer species that withstand harsh or poor conditions (Chapters
2 and 5; Mueller-Dombois, 2000).
Rapid changes of landscape indices in this tropical environment seem to be related
to the high and reliable rainfall in the high temperature region. This is in contrast to
mine rehabilitation in arid or semi-arid regions (less than 250 mm per annum) where the
occurrence of rainfall is the main trigger for the development of vegetation and soil
resources (Ludwig and Tongway, 1997). Limited available water significantly restricts
establishment of vegetation communities at rehabilitated mine sites and commonly
sparse vegetation evolves. In contrast for the well watered Kelian sites, fast growing
broadleaf species have rapidly increased litter abundance and soil organic matter. This
process is important for nutrient cycling. For example, the NCI value for the Kelian
waste dump after 1 year rehabilitation (30-50 %) is considerably higher than the NCI
(18.8 %) for rehabilitated land at the Kambalda nickel mine in semi-arid Western
Australia (Tongway et al. 1997). Unfortunately, there is no information available to
enable direct comparison with results for other tropical regions due to limited use of the
LFA protocol outside Australia or for mined land in tropical Australia.
This evaluation of the use of LFA indices in this tropical area has provided
valuable outcomes. Firstly, the ecosystem function analysis (EFA) protocol is practical
and useful for the assessment of land surface conditions and for monitoring progress of
site rehabilitation, despite the unexpectedly very high infiltration rate, thick litter cover,
and highly variable soil respiration values which are used to assess LFA indices. The
stability index was evaluated by measuring aggregate stability (MWD) in laboratory.
The relationship between the field and laboratory measures of soil stability is weak for
the 0-1 cm depth. It should be noted that this layer may comprise solely litter or be an
entirely mineral layer at rehabilitated sites so that simple relationships would not be
anticipated. Secondly, the high rate and highly variable values of soil respiration are
associated with a small range of values of nutrient cycling index at individual sites. It
158
seems that we need to re-evaluate the prominent contribution of litter in the
determination of NCI. It is possible to introduce other surface features (e.g. evidence of
fungal decomposition of litter) to accommodate soil biological activity. Thirdly, the
infiltration index is unable to evaluate extremely high values of infiltration rate. In this
study, the infiltration index is only a reliable predictor for actual infiltration rates less
than 400 mm/hr. Infiltration rate is highly sensitive to the condition of the soil surface.
For example infiltration rate was increased for restored productive soil patches of
rehabilitated grazed paddock from 12 to 118 mm/hr simply by placing branches to
provide water interception (Tongway and Ludwig, 1996). The dense vegetative cover
and litter on mature soils at Kelian presumably achieves the same effect. The overall
results show that the EFA protocol has the potential to be used in the tropical region but
should be modified. Furthermore, we need to address micro-scale variability so as to
improve the reliability of the EFA protocol for tropical areas.
159
Chapter 8. Summary, limitations and contributions of this study
8.1. Main research findings
This chapter identifies the major findings of the research. The detailed results and
discussion on each topic are presented within the relevant chapters. Figure 8.1 shows
the inter-relationships between research interests in which both natural and assisted
rehabilitation for disturbed lands are viewed as a dynamic process in relation to a
number of limiting factors and the monitoring of landscape quality. For this study,
three sites were selected which represent a wide range of soil conditions related to land
disturbance by mining activities under different climate conditions. Soil and niche
development occurring on these disturbed lands reflect the complex nature of soil-plant-
environment relationships. This research has identified and quantified some of the
processes and interactions represented within this figure.
Figure 8.1. A flowchart showing the inter-connectivity between land disturbance/ degradation, site rehabilitation, indices of soil development and monitoring of progress towards sustainability.
Disturbed/degraded lands(origin, property, land use)
Socio-culture
Legislation
Bio-geochemistry
Local climate
Natural and assisted rehabilitation
Native plant colonization
Biologicaldevelopment
Pedologicaldevelopment
Physical-chemicaldevelopment
Landscape indices andmonitoring systems
Dysfunctional ecosystem Functional ecosystem
Remedial actions
Micro-reliefResources
160
8.1.1. Jarrahdale site
The relatively slow rate of soil development on several regolith materials at the
Jarrahdale railway cutting shelf is partly due to both the patchy plant growth and
depositional/erosional processes. The average rate for the development of an A horizon
36 years after excavation ranges from 0.3-1.4 mm/year. The formation of A-C horizons
on a gold mine tailing in France after 35 years was much faster and occurred at rates of
2.5 to 7.0 mm/year (Neel et al., 2003). There is evidence that nutrient enrichment at the
surface horizons of PMZ soils is greater than for soils on granite plots. Overall soils at
the Jarrahdale shelf are considerably deficient in major nutrients for plants with the
average concentrations of total nitrogen of 0.73 g/kg (PMZ plots) and 0.39 g/kg (granite
plots); the extractable phosphorus is less than 2 mg/kg for all soil samples, and
exchangeable bases are 1.1 cmol/kg or less. These are all very low values. A few
samples have elevated concentrations of soil carbon, nitrogen, exchangeable bases and
CEC presumably reflecting the contribution of greater amounts of litter and its
decomposition. Soils on several landslides in Puerto Rico exhibited significant
increases in soil organic matter (1 to 9 %) and exchangeable bases (0.06 to 2.5
cmol/kg) within 55 years which were associated with early pedogenesis of the soils
(Zarin and Johnson, 1995). For reclaimed bauxite mines in China, organic matter had
increased substantially after 4 years (from 2.2 to 9.9 g/kg) as had total nitrogen (0.3 to
0.7 g/kg) (Miao and Marrs, 2000).
Site colonization by a number of volunteer local species was greatest on the
relatively deep soils on PMZ materials and less abundant on granite/saprolite materials.
Seeds probably originate in the fringing vegetation along the upper ridge and the
adjacent jarrah forest where a colonization front is evident. This condition is similar to
the pattern species recruitment along the exploitation roads in a Belgian forest (Honnay
et al, 1999). Overall the patchy growth of volunteer plants at the Jarrahdale cutting
shelf has resulted in a low production and accumulation of plant biomass and litter. A
quite similar situation to the Jarrahdale cutting shelf occurs at a rehabilitated granite
quarry in Hong Kong where shallow soil, high stone content and limited available
moisture greatly restrict plant colonization and growth (Jim, 2001). Plant seedling
recruitment has benefited from the construction of ridge (berm) and depression on the
shelf, which retain and concentrate fine material, seed and litter. This surface
topography greatly assists colonization and to some extent resembles the riplines used
161
in the rehabilitation of bauxite mines in Australia (Schwenke et al., 2000; Ward, 2000)
and other mining, agricultural and forestry sites around the world (Hart et al., 1999;
Moffat and Bending, 2000; Montalvo et al., 2002; Close and Davidson, 2003).
The patchy soil and vegetation conditions are reflected in the relatively low values
of landscape indices determined by Landscape Function Analysis (LFA), in particular
the value for nutrient cycling index being much lower than for the adjacent jarrah forest.
Differences in the LFA indices are mostly related to variations in local micro-relief,
litter abundance and vegetation occurrence.
8.1.2. Scotia site
Natural rehabilitation at the Scotia waste dump (over ca. 15 years) is characterized
by the patchy occurrence of a number of salt-tolerance species (Maireana, Atriplex,
Melaleuca) and several eucalypts. Soil properties are mostly similar to those in the
adjacent native woodland except for the more saline condition of the waste dump soils
(EC1:5 > 1 dS/m). Natural saline conditions are commonly encountered at many
locations surrounding gold mine operations in the arid and semi-arid regions of Western
Australia and generally significantly limit plant establishment (Osborne, 1999). In
contrast native species recruitment following the closure of a gold mine in Brazil
occurred quite rapidly (18 months after site preparation) under tropical rain forest
conditions with annual rainfall exceeding 2000 mm. In this instance several species
such as Trema micrantha, Schizolobium amazonicum were abundant colonizers of the
abandoned mine site (Rodrigues et al., 2004). Clearly the arid, saline conditions at
Scotia greatly limit plant establishment as indicated by species composition and rates of
colonization.
Native species colonizing various parts of the Scotia waste dump have partly
improved soil surface conditions and may have contributed to soil stabilization, water
retention and nutrient enrichment. These conditions lead to some moderation of
measured LFA indices across the waste dump with average values being comparable to
those for several mine sites in Western Australia (Tongway et al., 1997; Kearns and
Barnett, 1999) and elsewhere in Australia (Tongway et al., 2003). An integrated use of
the LFA technique and soil analysis (using a minimum dataset) provided a better
approach for understanding the extent of soil and plant development at the Scotia waste
dump.
162
8.1.3. Kelian site
Soil and plant development occurred much more rapidly in actively rehabilitated
mine sites at Kelian (East Kalimantan) under tropical humid conditions. Vigorous plant
growth with +10-m height of vegetation has been achieved within 7 years with average
stands closely resembling forest conditions of analogue sites. It is a quite common to
observe a rapid vegetation recruitment in tropical regions across several continents;
including North Queensland (Tucker and Murphy, 1997) and Brazil (Parrotta et al.,
1997). The growth of various tree species and legume cover crops for rehabilitation at
Kelian has contributed a large amount of plant biomass and abundant soil organic
matter. The large increases in total soil carbon for 0-1 cm depth from 5.4 g/kg (3-month
site) to 95 g/kg (7-year site) and in total nitrogen (0.5 to 7.9 g/kg) reflect the greatly
improved fertility status of the soil as plants and soils have developed over this time.
Table 8.1. Soil respiration values representing a wide range of ecosystems from around the world. Locality Ecosystem Soil respiration
(mg CO2/m2/hr) References
Lake Mere, New South Wales Australia
Improved paddock grassland
140-221 Tongway and Ludwig (1996)
Weipa, North Queensland Australia
Rehabilitated bauxite mine
30-86 Schwenke et al. (2000)
Kyushu, Japan Cedar forest (thinned and intact stands)
209-349 Ohashi et al. (1999)
Yakutsk, Russia Siberian taiga (various fire histories)
65-1429 Sawamoto et al. (2000)
Florida, USA Pine plantation (seasonal variation)
313-781 Fang et al. (1998)
Arizona, USA Ponderosa pine-bunch grass restoration
13-146 Kaye and Hart (1998)
Hawaii Tropical forest 237-354 Townsend et al. (1995)
Bavaria, Germany Norway spruce stands 40-253 Buchmann (2000) Kelian, Indonesia Rehabilitated gold mine 220-862 This study Native forest 425-612 This study
Improved soil and plant conditions may be reflected by rapid increments in
landscape indices (stability, infiltration and nutrient cycling) in the first years to achieve
levels close to those for the native forest. LFA indices at Kelian exhibit mostly non-
linear relationships with soil attributes, of which total soil carbon is most predictive.
163
The wide range of soil respiration values obtained at Kelian sites may indicate diverse
soil conditions which are not strongly predicted by the nutrient cycling index. The
values of soil respiration for Kelian soils are comparable to values for several other
locations around the world irrespective the methods used for measuring evolved carbon
dioxide (Table 8.1). Nutrient cycling in the tropical forest of Kelian is favorable in the
context of litter/fungi/plant root connectivity, whereas organic matter can be more easily
decomposed under this condition.
8.1.4. Comparisons between study sites
It is quite difficult to draw a common conclusionfor these study sites, owing to
very different environmental conditions. In terms of soil variation in soil properties, it
is clear that nature and properties of parent materials determine the current soil fertility
status. Having granite as the primary parent rocks for two sites, soils from the cutting
shelf in Jarrahdale basically have properties close to those from Kelian, except for the
occurrence of iron gravel and sandier texture. However, surface soils from Kelian show
superior quality than Jarrahdale soils. Derived largely from mafic rocks results in soils
having very high levels of exchangeable cations and CEC for Scotia samples, that are
very contrast to the other sites in the study. Soil development in these sites has
underlying factors which are mostly driven by the capacity of each site for biomass
production, subsequently its accumulation and decomposition. Rapid vegetative
recovery in Kelian has benefited from nutrient cycling from waste materials and soil
improvement.
Indices of landscape quality exhibit similar pattern in which massive litter
production and subsequently moderately to highly decomposed has significantly
contributed to the rapid increase in LFA indices for Kelian soils compared with two
other sites. However, this discrepancy should be viewed with a holistic approach
providing that soils under temperate (or sub-humid) and arid conditions to some extent
be able to achieve such levels of pre-disturbance conditions within a relatively short
time of rehabilitation.
164
8.2. Limitations of this study and suggestions for future work
There are certainly a number of deficiencies in this study, some of which were
anticipated, others became evident during the research. Plant colonization was observed
at a general level in this study as an indicator of soil recovery. However details of
species richness, seedbank and other vegetation parameters were not determined;
observations of these data are desirable to provide a comprehensive understanding of
colonization. This was not possible within the present study due to time constraints.
The lack of information regarding initial soil conditions of degraded lands often limits
interpretation and quantification of actual soil development when data are only for the
current condition. Soils on mines are often very difficult to sample and for in situ
measurements. In addition the procedures followed including a non-uniform sampling
depth for sample collection from different sites at Scotia partly restrict a direct
comparison between the dump and woodland soils. The use of various analytical
methods for the measurement of soil chemical and physical properties may not allow a
direct comparison of the results across quite different mine sites or localities; or with
literature values. For soils that are developing under similar conditions (e.g. similar
parent material, topography and climate), the results of the present study may be
extended with some confidence to enable comparisons and predictions of outcomes.
Due to the stringent regulations that operate in most countries, disturbed lands
resulting from mining operations must be restored to an acceptable condition as quickly
as possible. Thus natural rehabilitation is not commonly selected as a practice and may
only exist for historical mining sites (orphan mines). For spontaneously rehabilitated
sites trajectory analysis over time is often not possible, neither are paired comparisons
with equivalent rehabilitated sites. These matters would deserve close investigation in
future work.
Highly variable soil conditions at rehabilitated mine sites at Kelian are sometimes
poorly predicted by LFA indices, in particular the measurements of soil respiration and
field infiltration, especially in extremely high rate circumstances. A rapid field
assessment might be more preferred for well-structured clays. Adjustment of sampling
instruments and procedures for local conditions may be necessary for laboratory
analysis to evaluate LFA measurements. Progressive rehabilitation allows us to monitor
the rate of progress of rehabilitation from the beginning of a mining operation but only
providing that similar techniques for rehabilitation and monitoring have been employed
165
throughout (this rarely occurs in practice). Factors affecting soil respiration and actual
infiltration and their effects on soil quality are topics of potential research interest which
may enable the refinement of the LFA technique for tropical environments.
8.3. Contribution of the present study
This work has demonstrated that natural rehabilitation occurs on disturbed lands
in which some native local species colonize the sites spontaneously and soil fertility
develops considerably within a quite short period of time with little or no external
inputs (see also Tongway and Ludwig, 2002). Species richness of natural rehabilitation
is much lower than for assisted rehabilitation where all or most of the original species
are introduced. A main difference between these two approaches is that natural
rehabilitation generally requires a much longer period to achieve a sustainably
functioning ecosystem than does an assisted rehabilitation. It is important to determine
a critical threshold as guidelines for defining management strategies so that the
rehabilitated ecosystems sustain. However it is possible to accelerate soil and plant
development of disturbed lands even using minimum inputs and inexpensive site
preparation, such as the construction of man-made drain structure at the Scotia waste
dump which is beneficial for retention of rainfall and seedlings, and the ridge (berm) at
the Jarrahdale cutting shelf. This study has utilised the LFA technique for the
assessment of soil surface conditions. The use of this technique is a valuable tool for
assessing the status of rehabilitation. It is a simple and practical technique for assessing
and monitoring soil surface and plant habitat conditions for rehabilitated land in both
subhumid and arid regions in Western Australia. This work has provided a first
application of the LFA technique to a tropical region of Indonesia and indicates that it
will be a valuable tool for this and similar environments but with some limitations.
166
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Appendix 1. Site information, physical and chemical properties of Jarrahdale soil samples. Notes: Csilt (coarse silt, 0.02-0.05 mm), Fsilt (fine silt, 0.002-0.02 mm), bic-P (bicarbonate-extractable P), bic-K (bicarbonate-extractable K), BSP (base saturation percentage) are consistently used in the following appendices. No. Sample Depth Gravel Sand Csilt Fsilt Clay silt/clay (cm) % Shelf 1 P1.1 0-5 20 80.2 3.3 7.3 9.1 1.16 2 P1.2 0-8 37 71.2 4.1 8.7 16.1 0.80 3 P1.3A 0-3 44 79.7 4.4 6.2 9.8 1.08 4 P1.3B 3-7 43 70.7 2.0 9.6 17.7 0.66 5 P1.4A 0-7 26 69.8 4.9 6.6 18.7 0.61 6 P1.4B 7-35 46 64.0 3.3 9.3 23.4 0.54 7 P1.5A 0-11 27 82.5 2.8 5.3 9.4 0.86 8 P1.5B 11-40 66 79.5 3.3 7.1 10.1 1.03 9 P2.1A 0-2 87 75.7 3.6 8.4 12.3 0.98 10 P2.1B 2-7 43 78.6 2.3 7.6 11.4 0.87 11 P2.2A 0-2 50 81.7 7.0 6.2 5.2 2.54 12 P2.2B 2-5 51 83.7 5.0 6.0 5.3 2.08 13 P2.3A 0-5 28 77.5 4.0 7.8 10.6 1.11 14 P2.3B 5-12 50 79.1 4.0 6.6 10.3 1.03 15 P2.3C 12-18 50 83.3 4.7 6.7 5.2 2.19 16 P2.4A 0-4 25 81.7 3.4 7.9 6.9 1.64 17 P2.4B 4-10 60 80.1 3.8 6.9 9.2 1.16 18 P3.1A 0-3 66 90.6 3.0 3.0 3.3 1.82 19 P3.1B 3-23 51 88.2 3.8 3.8 4.1 1.85 20 P3.2A 0-1 75 79.7 4.7 8.2 7.4 1.74 21 P3.2B 1-6 17 81.5 4.1 5.4 9.0 1.06 22 P3.2C 6-18 15 67.9 3.3 9.3 19.6 0.64 23 P3.3A 0-4 81 87.6 3.4 4.9 4.1 2.02 24 P3.3B 4-9 63 79.2 3.6 8.7 8.5 1.45 25 P3.3C 9-13 50 75.8 3.5 7.1 13.6 0.78 26 P3.4A 0-3 79 89.0 2.0 4.3 4.6 1.37 27 P3.4B 3-7 64 88.0 1.0 4.4 6.7 0.81 28 P3.4C 7-33 32 71.1 2.0 3.8 23.1 0.25 29 P4.1A 0-12 31 84.3 2.5 5.5 7.7 1.04 30 P4.1B 12-30 52 57.4 2.3 16.8 23.5 0.81 31 P4.1C 30-53 40.0 4.2 22.8 33.0 0.82 32 P4.2A 0-3 32 77.0 1.0 7.8 14.1 0.62 33 P4.2B 3-15 18 77.5 0.5 8.1 13.9 0.62 34 P4.2C 15-55 22.8 4.6 33.1 39.5 0.95 35 P4.3A 0-1 56 54.5 5.6 17.1 22.7 1.00 36 P4.3B 1-4 55 48.0 5.4 19.0 27.7 0.88 37 P4.3C 4-25 57.4 1.2 14.4 26.9 0.58 38 P4.3D 25-50 42.9 0.3 26.3 30.6 0.87 39 P4.4A 0-3 66 46.7 3.3 19.2 30.8 0.73 40 P4.4B 3-12 69 25.8 2.0 27.2 45.0 0.65 41 P4.4C 12-25 21.4 5.7 32.1 40.8 0.93 42 P4.4D 25-50 15.2 2.5 30.6 51.7 0.64 43 P5.1A 0-1 97 44 P5.1B 1-4 60 85.7 3.3 5.4 5.6 1.55 45 P5.1C 4-12 42 73.8 1.8 10.8 13.6 0.93 46 P5.1D 12-27 22 73.9 2.3 12.5 11.3 1.31 47 P5.2A 0-2 41 81.2 3.0 7.2 8.7 1.17
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No. Sample Depth Gravel Sand Csilt Fsilt Clay silt/clay (cm) % 48 P5.2B 2-12 15 79.3 2.2 9.0 9.5 1.18 49 P5.3A 0-4 39 74.0 3.8 10.4 11.9 1.19 50 P5.3B 4-15 32 73.4 2.5 11.1 12.9 1.05 51 P5.4A 0-4 48 75.3 3.5 9.3 11.9 1.08 52 P5.4B 4-25 38 73.2 3.0 10.4 13.4 1.00 53 P5.5A 0-2 48 80.3 3.8 8.3 7.6 1.59 54 P5.5B 2-10 33 79.7 3.3 8.3 8.8 1.32 55 P5.6A 0-8 49 69.8 3.2 11.1 15.9 0.90 56 P5.6B 8-23 36 70.1 3.5 11.8 14.6 1.05 57 P6.1A 0-1 90 81.2 5.1 5.1 8.6 1.19 58 P6.1B 1-11 53 76.9 4.1 8.2 10.8 1.14 59 P6.2A 0-1 61 90.3 2.6 3.3 3.8 1.55 60 P6.2B 1-4 59 87.2 3.3 4.1 5.4 1.37 61 P6.2C 4-15 42 82.6 2.8 9.1 5.4 2.20 62 P6.3SP 0-5 57 78.9 2.3 9.2 9.7 1.19 63 P6.4SR 0-5 56 90.6 2.8 5.4 1.3 6.31 64 P7.1A 0-1 44 88.8 3.7 4.4 3.1 2.61 65 P7.1B 1-9 39 64.4 12.0 14.3 9.2 2.86 66 P7.1C 9-38 43 83.7 5.0 5.0 6.3 1.59 67 P7.2A 0-1 27 43.5 7.7 24.4 24.4 1.32 68 P7.2B 1-4 54 57.7 8.0 19.1 15.3 1.77 69 P7.2C 4-15 43 81.6 5.1 6.8 6.6 1.80 70 P7.3A 0-1 68 86.1 3.5 5.6 4.8 1.90 71 P7.3B 1-10 44 84.3 5.6 5.6 4.4 2.55 72 P7.4 0-8 69 84.9 6.1 5.3 3.6 3.17 73 P7.5 0-5 95 Forest 74 BP1.1 0-10 14 80.2 4.7 6.7 8.5 1.34 75 BP1.2 10-20 36 81.3 6.1 6.3 6.3 1.97 76 BP2.1 0-10 33 78.5 4.9 10.1 6.5 2.31 77 BP2.2 10-20 40 84.4 3.0 8.1 4.6 2.41 78 BP3.1 0-10 44 81.7 5.7 4.7 8.0 1.30 79 BP3.2 10-20 65 86.3 3.5 4.0 6.2 1.21 80 BP4.1 0-10 60 83.8 4.6 6.0 5.7 1.86 81 BP4.2 10-20 63 81.3 4.1 8.9 5.7 2.28
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Appendix 1. continued No. Sample pH EC Bic-P Bic-K Total C Total N C/N (dS/m) (mg/kg) (g/kg) Shelf 1 P1.1 5.78 0.025 1.39 26.8 10.2 0.44 23 2 P1.2 6.00 0.025 0.52 93.1 7.48 0.28 27 3 P1.3A 4.87 0.056 2.93 39.0 10.7 0.59 18 4 P1.3B 4.81 0.039 0.83 13.2 4.25 0.38 11 5 P1.4A 5.20 0.060 1.08 28.2 9.11 0.50 18 6 P1.4B 4.89 0.040 1.30 47.9 2.29 0.34 7 7 P1.5A 5.06 0.051 2.01 7.3 7.23 0.42 17 8 P1.5B 4.80 0.038 1.47 27.0 3.87 0.27 14 9 P2.1A 4.87 0.052 1.04 27.3 6.29 0.48 13 10 P2.1B 5.12 0.039 1.14 44.6 2.55 0.32 8 11 P2.2A 4.79 0.039 2.18 27.0 8.67 0.75 12 12 P2.2B 5.09 0.029 1.26 56.3 2.43 0.19 13 13 P2.3A 5.19 0.057 0.77 41.3 3.56 0.38 9 14 P2.3B 5.85 0.040 0.70 71.9 1.94 0.21 9 15 P2.3C 5.80 0.038 0.63 123.3 0.87 0.29 3 16 P2.4A 4.68 0.086 2.34 59.1 15.3 1.17 13 17 P2.4B 4.94 0.040 1.52 58.6 4.87 0.42 12 18 P3.1A 4.91 0.057 2.12 18.8 11.9 0.64 19 19 P3.1B 5.56 0.020 0.90 24.9 11.6 0.54 21 20 P3.2A 5.13 0.074 4.56 60.1 54.8 1.89 29 21 P3.2B 4.75 0.050 0.65 40.5 12.3 0.54 23 22 P3.2C 4.73 0.058 0.73 23.5 2.18 0.18 12 23 P3.3A 5.13 0.065 1.12 28.9 12.3 0.60 21 24 P3.3B 5.29 0.053 0.62 39.5 12.4 0.63 20 25 P3.3C 5.05 0.045 0.25 32.1 4.75 0.25 19 26 P3.4A 5.06 0.057 1.06 24.9 12.9 0.64 20 27 P3.4B 5.02 0.058 0.84 36.5 9.31 0.44 21 28 P3.4C 5.44 0.016 0.56 22.7 3.06 0.23 13 29 P4.1A 4.80 0.037 1.66 24.9 2.20 0.21 10 30 P4.1B 4.71 0.053 0.60 25.4 1.72 0.37 5 31 P4.1C 4.96 0.058 0.42 28.6 1.65 0.19 9 32 P4.2A 4.77 0.048 2.42 17.8 3.97 0.26 15 33 P4.2B 4.63 0.051 0.42 12.2 2.02 0.22 9 34 P4.2C 4.66 0.068 0.68 14.2 1.52 0.24 6 35 P4.3A 5.34 0.049 0.80 35.8 9.27 0.62 15 36 P4.3B 4.63 0.098 0.45 33.0 7.26 0.47 15 37 P4.3C 4.70 0.074 0.90 53.0 7.73 0.38 20 38 P4.3D 4.74 0.069 0.46 51.7 2.57 0.27 10 39 P4.4A 4.95 0.060 1.81 11.4 4.65 0.46 10 40 P4.4B 5.04 0.054 1.47 41.3 2.61 0.28 9 41 P4.4C 4.94 0.083 0.74 53.8 2.03 0.37 5 42 P4.4D 4.99 0.070 0.60 35.7 2.06 0.75 3 43 P5.1A 0.74 27.3 9.71 0.50 19 44 P5.1B 4.91 0.061 1.26 34.0 13.2 0.65 20 45 P5.1C 4.83 0.042 0.67 34.2 2.26 0.16 14 46 P5.1D 5.06 0.040 0.82 17.5 1.01 0.09 11 47 P5.2A 5.00 0.037 0.91 8.4 2.19 0.19 12 48 P5.2B 4.98 0.028 0.81 11.2 1.29 0.17 8 49 P5.3A 4.88 0.054 0.88 43.6 2.94 0.13 23 50 P5.3B 5.06 0.040 0.79 21.9 1.86 0.14 13
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No. Sample pH EC Bic-P Bic-K Total C Total N C/N (dS/m) (mg/kg) (g/kg) 51 P5.4A 4.82 0.062 0.28 83.7 4.09 0.19 22 52 P5.4B 4.92 0.044 0.48 26.8 1.73 0.10 17 53 P5.5A 4.69 0.056 0.28 13.2 4.68 0.12 39 54 P5.5B 4.94 0.032 0.45 25.7 1.81 0.09 20 55 P5.6A 4.60 0.078 0.79 23.1 12.3 0.52 24 56 P5.6B 4.43 0.043 0.46 24.0 3.21 0.20 16 57 P6.1A 4.66 0.050 1.74 24.9 8.13 0.36 23 58 P6.1B 4.74 0.048 1.55 36.7 4.97 0.31 16 59 P6.2A 4.82 0.047 1.35 22.6 4.76 0.29 16 60 P6.2B 4.73 0.046 1.29 51.1 4.51 0.27 17 61 P6.2C 5.12 0.066 1.52 210.3 1.39 0.02 70 62 P6.3SP 4.66 0.065 1.49 55.4 1.66 0.33 5 63 P6.4SR 4.94 0.064 0.84 60.9 0.92 0.18 5 64 P7.1A 4.83 0.063 0.91 32.0 15.6 0.47 33 65 P7.1B 4.48 0.073 0.75 39.0 23.1 0.66 35 66 P7.1C 4.57 0.037 0.74 21.1 7.17 0.26 28 67 P7.2A 5.09 0.068 1.87 83.3 106 2.80 38 68 P7.2B 5.40 0.045 0.79 31.6 46.2 1.15 40 69 P7.2C 4.65 0.045 0.91 10.1 9.45 0.20 47 70 P7.3A 5.45 0.034 1.53 21.0 38.9 1.10 35 71 P7.3B 5.24 0.043 0.35 39.9 11.1 0.41 27 72 P7.4 5.09 0.061 0.76 12.5 24.4 0.71 34 73 P7.5 4.82 0.067 0.34 24.3 12.0 0.57 21 Forest 74 BP1.1 5.83 0.042 6.71 55.6 43.1 1.95 22 75 BP1.2 5.30 0.086 2.11 20.2 22.7 0.90 25 76 BP2.1 5.65 0.061 5.92 65.2 104 2.86 36 77 BP2.2 5.53 0.088 0.88 45.8 23.1 0.64 36 78 BP3.1 5.66 0.069 5.58 54.0 168 6.42 26 79 BP3.2 5.51 0.092 2.33 63.7 25.4 0.96 26 80 BP4.1 6.11 0.038 0.89 55.2 37.5 1.40 27 81 BP4.2 5.11 0.093 0.94 37.1 31.3 0.73 43
183
Appendix 1. continued No. Sample Ca Mg K Na Sum CEC BSP (cmol/kg) % Shelf 1 P1.1 0.22 0.18 0.06 0.04 0.50 3.27 15.1 2 P1.2 0.18 0.24 0.04 0.05 0.50 4.76 10.6 3 P1.3A 0.17 0.20 0.05 0.04 0.46 5.15 8.9 4 P1.3B 0.13 0.18 0.03 0.01 0.35 3.61 9.6 5 P1.4A 0.32 0.38 0.04 0.04 0.77 5.43 14.2 6 P1.4B 0.15 0.22 0.03 0.01 0.41 3.43 12.0 7 P1.5A 0.20 0.15 0.02 0.02 0.39 3.29 11.9 8 P1.5B 0.07 0.08 0.01 0.00 0.17 2.95 5.7 9 P2.1A 0.10 0.21 0.02 0.03 0.36 3.06 11.8 10 P2.1B 0.12 0.18 0.01 0.01 0.33 1.09 29.8 11 P2.2A 0.08 0.14 0.02 0.03 0.27 3.68 7.3 12 P2.2B 0.04 0.08 0.00 0.01 0.14 2.59 5.3 13 P2.3A 0.15 0.20 0.02 0.06 0.42 3.35 12.7 14 P2.3B 0.23 0.20 0.05 0.02 0.50 3.71 13.6 15 P2.3C 0.19 0.13 0.07 0.04 0.43 2.93 14.8 16 P2.4A 0.28 0.32 0.11 0.09 0.80 3.16 25.2 17 P2.4B 0.13 0.17 0.03 0.02 0.35 2.66 13.2 18 P3.1A 0.18 0.14 0.02 0.05 0.39 2.55 15.3 19 P3.1B 0.20 0.10 0.02 0.03 0.35 3.82 9.1 20 P3.2A 2.52 0.97 0.18 0.25 3.93 6.19 63.4 21 P3.2B 0.20 0.12 0.04 0.04 0.40 4.16 9.6 22 P3.2C 0.14 0.18 0.02 0.03 0.36 2.24 16.3 23 P3.3A 0.32 0.18 0.03 0.09 0.62 3.69 16.7 24 P3.3B 0.27 0.16 0.02 0.07 0.52 2.33 22.3 25 P3.3C 0.17 0.13 0.01 0.04 0.35 3.58 9.7 26 P3.4A 0.20 0.14 0.02 0.05 0.41 5.07 8.0 27 P3.4B 0.12 0.14 0.01 0.04 0.31 1.62 19.2 28 P3.4C 0.04 0.11 0.01 0.03 0.19 1.83 10.2 29 P4.1A 0.04 0.10 0.02 0.04 0.20 1.56 12.6 30 P4.1B 0.17 0.50 0.05 0.06 0.78 1.70 45.9 31 P4.1C 0.27 0.82 0.07 0.11 1.27 2.54 50.2 32 P4.2A 0.07 0.21 0.03 0.06 0.37 1.87 19.9 33 P4.2B 0.06 0.18 0.02 0.02 0.27 1.91 14.3 34 P4.2C 0.24 0.82 0.05 0.06 1.17 2.34 50.2 35 P4.3A 0.25 0.50 0.09 0.14 0.98 2.40 40.8 36 P4.3B 0.22 0.56 0.10 0.08 0.96 3.15 30.4 37 P4.3C 0.20 0.56 0.15 0.09 0.99 3.41 29.1 38 P4.3D 0.51 0.69 0.08 0.08 1.36 6.74 20.1 39 P4.4A 0.22 0.51 0.05 0.06 0.85 3.50 24.2 40 P4.4B 0.37 0.91 0.08 0.06 1.41 3.32 42.5 41 P4.4C 0.37 1.12 0.12 0.17 1.77 2.94 60.3 42 P4.4D 0.37 1.06 0.12 0.12 1.68 1.90 88.1 43 P5.1A 0.31 0.44 0.07 0.23 1.05 2.07 50.8 44 P5.1B 0.09 0.16 0.03 0.06 0.34 0.90 38.0 45 P5.1C 0.04 0.19 0.02 0.02 0.26 0.68 38.6 46 P5.1D 0.04 0.18 0.10 0.02 0.35 0.69 50.4 47 P5.2A 0.02 0.11 0.01 0.04 0.18 1.39 13.1 48 P5.2B 0.02 0.11 0.01 0.04 0.17 0.87 19.7 49 P5.3A 0.15 0.35 0.04 0.11 0.65 2.23 29.0 50 P5.3B 0.13 0.29 0.03 0.05 0.51 0.92 54.8
184
No. Sample Ca Mg K Na Sum CEC BSP (cmol/kg) % 51 P5.4A 0.06 0.21 0.03 0.12 0.42 0.73 58.1 52 P5.4B 0.08 0.27 0.02 0.07 0.44 1.46 29.9 53 P5.5A 0.03 0.14 0.03 0.07 0.27 0.82 32.6 54 P5.5B 0.03 0.13 0.01 0.02 0.19 0.41 47.2 55 P5.6A 0.58 0.49 0.04 0.07 1.18 2.36 50.0 56 P5.6B 0.12 0.24 0.04 0.04 0.44 3.10 14.2 57 P6.1A 0.12 0.27 0.03 0.06 0.48 6.59 7.2 58 P6.1B 0.11 0.30 0.05 0.06 0.51 3.03 16.9 59 P6.2A 0.04 0.17 0.02 0.06 0.29 5.32 5.5 60 P6.2B 0.05 0.21 0.04 0.06 0.37 3.19 11.5 61 P6.2C 0.17 0.55 0.14 0.39 1.25 4.15 30.2 62 P6.3SP 0.10 0.43 0.05 0.09 0.67 8.96 7.5 63 P6.4SR 0.02 0.73 0.07 0.15 0.97 8.95 10.9 64 P7.1A 0.14 0.15 0.02 0.04 0.35 8.83 4.0 65 P7.1B 0.14 0.17 0.03 0.05 0.40 3.40 11.7 66 P7.1C 0.02 0.09 0.03 0.03 0.17 2.66 6.3 67 P7.2A 4.15 1.25 0.13 0.22 5.75 3.19 100* 68 P7.2B 0.63 0.40 0.07 0.12 1.22 5.21 23.4 69 P7.2C 0.10 0.12 0.01 0.03 0.26 2.76 9.4 70 P7.3A 1.28 0.60 0.04 0.06 1.98 5.04 39.3 71 P7.3B 0.33 0.28 0.03 0.03 0.67 4.88 13.6 72 P7.4 0.53 0.23 0.03 0.04 0.84 6.07 13.8 73 P7.5 0.06 0.12 0.04 0.09 0.31 2.73 11.2 Forest 74 BP1.1 4.14 0.94 0.12 0.18 5.38 7.40 72.6 75 BP1.2 0.75 0.47 0.05 0.07 1.33 8.63 15.4 76 BP2.1 3.65 1.03 0.16 0.27 5.10 7.11 71.8 77 BP2.2 0.76 0.38 0.07 0.07 1.28 7.48 17.1 78 BP3.1 10.33 2.49 0.19 0.43 13.45 15.15 88.7 79 BP3.2 2.23 0.64 0.07 0.05 2.99 8.56 34.9 80 BP4.1 2.10 0.73 0.17 0.11 3.11 7.80 39.9 81 BP4.2 0.88 0.35 0.15 0.07 1.45 6.61 21.9 *) measured CEC < sum of bases
185
Appendix 2. Site information, physical and chemical properties of Scotia soil samples. Notes: SW, waste dump soils; woodland soils (BS bare soil, EUC eucalypt, SLC Melaleuca, and ATR Atriplex zones); FC, field capacity; PWP, permanent wilting point; AW, available water. No. Sample FC PWP AW Gravel Sand Csilt Fsilt Clay %(v/v) % 1 SW 1 20.3 15.2 5.1 33 65.1 5.8 24.6 4.4 2 SW 2 21.9 15.6 6.3 41 64.1 5.5 27.7 2.8 3 SW 3 28.6 20.3 8.3 42 51.2 4.0 32.1 12.7 4 SW 4 30.7 11.6 19.1 57 66.1 9.9 14.4 9.6 5 SW 5 29.9 13.8 16.1 29 62.0 5.6 18.4 14.0 6 SW 6 48.4 13.9 34.6 46 66.4 5.4 14.7 13.5 7 SW 7 39.7 14.7 25.0 60 57.9 5.2 20.3 16.6 8 SW 8 29.9 13.9 16.0 18 66.0 4.3 17.2 12.6 9 SW 9 29.4 17.6 11.8 26 65.5 4.9 18.3 11.4 10 SW 10 19.5 14.1 5.4 55 60.9 7.4 21.9 9.8 11 SW 11 25.9 16.0 9.9 58 62.7 6.0 19.5 11.8 12 SW 12 42.4 14.7 27.7 14 56.5 6.2 31.2 6.2 13 SW 13 30.5 13.1 17.4 37 63.0 3.0 29.2 4.9 14 SW 14 27.0 17.8 9.2 45 58.4 7.8 18.0 15.8 15 SW 15 27.1 16.7 10.4 24 62.8 5.7 18.9 12.6 16 SW 16 41.7 18.7 23.0 64 52.4 7.2 21.9 18.6 17 SW 17 26.5 17.0 9.5 29 61.4 6.4 21.1 11.1 18 SW 18 29.0 13.6 15.4 22 66.5 4.6 17.5 11.4 19 SW 19 40.4 13.7 26.8 27 60.0 4.9 21.8 13.4 20 SW 20 40.1 15.5 24.5 34 54.8 5.5 32.5 7.2 21 SW 21 30.7 13.9 16.7 25 64.6 6.7 17.7 11.0 22 SW 22 21.9 18.4 3.6 33 62.6 5.9 25.8 5.6 23 SW 23 19.6 13.8 5.8 20 70.2 5.6 20.6 3.5 24 SW 24 25.8 11.2 14.6 22 71.8 4.9 13.8 9.5 25 SW 25 42.3 14.1 28.2 15 68.0 5.6 21.7 4.7 26 BS1-1 26.1 11.8 14.3 10 64.2 6.8 20.5 8.5 27 BS1-2 29.5 14.0 15.4 24 69.7 5.1 18.8 6.5 28 SLC1-1 24.2 13.8 10.4 16 59.3 5.6 28.8 6.4 29 SLC1-2 26.9 13.9 13.0 21 62.7 5.2 18.7 13.5 30 EUC1-1 22.3 12.0 10.4 12 64.8 4.8 19.4 10.9 31 EUC1-2 25.3 14.2 11.1 10 65.4 4.7 18.1 11.8 32 BS3-1 32.9 12.5 20.3 3 65.9 3.7 20.5 9.9 33 BS3-2 37.3 15.9 21.4 19 63.9 4.0 19.5 12.7 34 SLC3-1 23.5 12.3 11.2 14 65.4 4.9 18.9 10.9 35 SLC3-2 34.9 12.7 22.2 10 61.5 5.1 20.9 12.5 36 ATR2-1 31.9 12.4 19.5 12 67.9 4.7 17.6 9.7 37 ATR2-2 41.5 13.8 27.7 9 62.8 5.0 20.7 11.5 38 BS2-1 26.0 11.5 14.5 10 64.1 5.4 20.2 10.3 39 BS2-2 30.5 12.3 18.2 15 62.0 5.0 20.1 12.9 40 SLC2-1 29.5 12.2 17.3 10 66.7 4.1 19.1 10.1 41 SLC2-2 34.0 14.5 19.5 9 61.8 4.8 21.3 12.1 42 EUC2-1 27.1 13.2 13.9 10 66.0 4.5 19.9 9.6 43 EUC2-2 34.5 13.9 20.6 15 60.1 5.0 22.3 12.7 44 EUC3-1 32.5 12.5 20.0 12 66.1 4.4 19.0 10.5 45 EUC3-2 37.8 15.3 22.5 8 64.5 5.2 21.2 9.2 46 ATR1-1 33.4 11.1 22.4 22 69.8 4.8 16.7 8.7 47 ATR1-2 33.1 12.1 21.0 16 67.5 4.4 18.6 9.6 48 ATR3-1 30.8 12.3 18.6 8 64.5 6.2 21.3 8.1 49 ATR3-2 36.8 14.4 22.4 14 67.8 6.3 19.9 6.0
186
Appendix 2. continued No. Sample EC pH Bic-P Bic-K Total-C Org-C Total-N (dS/m) (mg/kg) (g/kg) 1 SW 1 0.403 9.24 3.2 672 36.7 15.3 1.24 2 SW 2 0.425 9.53 0.7 546 35.9 15.0 1.28 3 SW 3 0.485 9.28 11.1 610 58.3 18.6 1.65 4 SW 4 2.260 9.12 6.4 322 19.8 6.5 0.66 5 SW 5 2.190 9.06 4.1 620 44.4 15.6 1.42 6 SW 6 1.460 8.72 14.4 348 43.6 12.7 1.3 7 SW 7 0.149 8.47 8.6 690 33.0 20.8 1.51 8 SW 8 0.374 9.48 5.3 427 39.1 18.1 1.43 9 SW 9 1.326 8.82 12.6 553 39.2 18.7 1.45 10 SW 10 0.321 9.08 7.3 497 33.9 21.1 1.43 11 SW 11 0.894 9.47 7.2 285 36.7 14.3 1.26 12 SW 12 0.508 8.97 6.6 561 49.8 20.9 1.86 13 SW 13 0.167 8.60 7.4 324 43.0 18.4 1.59 14 SW 14 0.587 9.45 2.2 1397 38.0 22.1 1.84 15 SW 15 0.721 9.47 8.3 682 39.6 14.1 1.3 16 SW 16 0.368 9.10 8.4 554 49.6 20.7 1.96 17 SW 17 0.180 8.71 5.8 452 45.4 19.7 1.73 18 SW 18 3.375 8.43 3.5 775 42.0 14.9 1.55 19 SW 19 0.329 8.88 4.0 550 44.1 10.4 1.06 20 SW 20 0.209 8.59 1.2 544 43.6 19.8 1.41 21 SW 21 2.620 8.20 5.4 445 41.1 17.0 1.79 22 SW 22 5.150 8.58 0.3 620 44.0 16.7 1.48 23 SW 23 0.487 9.51 0.3 550 37.2 11.4 0.97 24 SW 24 0.197 9.02 6.0 638 35.5 13.1 1.22 25 SW 25 0.187 8.83 11.6 512 46.1 20.1 1.38 26 BS1-1 0.366 8.83 6.1 620 26.5 17.6 1.54 27 BS1-2 1.340 9.31 0.6 478 27.1 16.7 1.43 28 SLC1-1 0.762 8.75 8.2 665 41.5 34.4 2.43 29 SLC1-2 1.084 8.45 10.5 620 35.7 31.9 1.84 30 EUC1-1 0.299 8.92 6.5 435 24.7 15.6 1.13 31 EUC1-2 0.945 9.90 1.6 330 25.1 14.5 1.16 32 BS3-1 0.159 8.34 20.5 351 24.5 16.4 1.63 33 BS3-2 1.027 9.93 12.2 287 29.6 13.1 1.04 34 SLC3-1 1.067 7.77 8.7 1046 42.0 35.5 2.45 35 SLC3-2 0.781 9.44 2.6 623 27.5 16.8 1.3 36 ATR2-1 0.265 8.40 9.1 675 27.6 21.2 1.72 37 ATR2-2 0.383 9.62 4.6 718 31.3 22.2 1.52 38 BS2-1 0.139 8.97 6.3 599 23.7 12.4 1.14 39 BS2-2 0.563 9.75 9.8 524 23.1 9.2 0.97 40 SLC2-1 1.079 8.58 8.0 837 31.2 23.2 1.85 41 SLC2-2 1.501 8.96 5.6 482 32.0 19.9 1.46 42 EUC2-1 0.243 8.14 14.7 414 41.0 37.9 2.36 43 EUC2-2 0.277 9.33 13.6 466 28.8 21.6 1.36 44 EUC3-1 0.250 8.24 6.4 534 32.3 25.8 1.67 45 EUC3-2 0.593 10.09 5.5 300 27.0 12.0 1.11 46 ATR1-1 0.262 8.60 4.4 551 23.8 22.9 1.46 47 ATR1-2 0.761 9.46 5.2 582 25.4 14.7 1.23 48 ATR3-1 0.341 8.63 5.8 716 33.8 23.7 2.02 49 ATR3-2 0.458 9.91 2.2 620 28.0 14.9 1.07
187
Appendix 2. continued No. Sample Ca Mg K Na Sum of bases CEC ESP (cmol/kg) (%) 1 SW 1 17.5 6.06 1.04 1.37 26.0 25.3 5.4 2 SW 2 18.0 5.49 0.59 3.12 27.2 25.2 12.4 3 SW 3 16.7 7.96 1.41 4.08 30.2 29.3 13.9 4 SW 4 15.4 3.72 0.55 6.00 25.7 22.1 27.1 5 SW 5 18.0 7.40 0.76 4.94 31.1 29.4 16.8 6 SW 6 17.2 6.65 0.67 1.99 26.5 21.1 9.4 7 SW 7 24.7 6.64 0.86 0.53 32.7 35.7 1.5 8 SW 8 19.2 5.48 1.03 2.42 28.1 28.8 8.4 9 SW 9 18.3 6.06 1.16 2.28 27.8 29.6 7.7 10 SW 10 20.4 5.65 1.00 1.38 28.4 31.4 4.4 11 SW 11 17.6 5.30 0.54 5.56 29.0 29.1 19.1 12 SW 12 18.4 6.24 1.41 2.47 28.5 29.3 8.4 13 SW 13 20.2 5.70 0.70 0.37 27.0 29.5 1.3 14 SW 14 20.1 5.26 1.61 5.54 32.5 33.7 16.4 15 SW 15 16.6 4.51 1.52 3.66 26.3 26.8 13.7 16 SW 16 21.4 7.18 1.45 3.51 33.5 35.5 9.9 17 SW 17 20.0 6.43 1.03 0.56 28.0 29.5 1.9 18 SW 18 18.8 5.89 1.20 1.66 27.6 29.6 5.6 19 SW 19 16.5 5.18 0.81 0.71 23.2 24.9 2.9 20 SW 20 18.0 6.27 0.91 0.64 25.8 27.8 2.3 21 SW 21 18.5 5.86 1.05 1.17 26.6 28.0 4.2 22 SW 22 18.0 7.55 0.95 2.62 29.1 27.7 9.5 23 SW 23 16.7 6.01 0.93 2.09 25.7 25.1 8.3 24 SW 24 16.9 5.54 1.02 0.67 24.1 25.5 2.6 25 SW 25 19.2 6.23 0.90 0.55 26.9 29.6 1.9 26 BS1-1 18.6 5.81 0.77 2.97 28.2 28.9 10.3 27 BS1-2 17.8 6.10 0.70 2.43 27.0 28.9 8.4 28 SLC1-1 20.3 7.38 1.11 1.13 29.9 34.0 3.3 29 SLC1-2 20.1 8.75 1.19 1.68 31.7 34.6 4.9 30 EUC1-1 19.5 7.13 0.73 0.70 28.1 27.8 2.5 31 EUC1-2 18.2 8.25 0.77 1.58 28.8 30.3 5.2 32 BS3-1 19.4 5.46 0.70 1.11 26.7 27.5 4.0 33 BS3-2 17.4 9.21 0.62 2.64 29.9 29.3 9.0 34 SLC3-1 21.4 8.61 1.24 1.69 32.9 33.3 5.1 35 SLC3-2 18.0 8.83 0.93 2.81 30.6 32.0 8.8 36 ATR2-1 18.4 4.64 1.36 0.80 25.2 27.2 2.9 37 ATR2-2 20.5 7.39 1.21 1.85 31.0 33.0 5.6 38 BS2-1 20.0 5.17 0.88 1.12 27.2 29.2 3.8 39 BS2-2 18.6 5.75 0.91 3.48 28.7 28.4 12.3 40 SLC2-1 20.2 6.82 1.08 2.23 30.3 31.7 7.0 41 SLC2-2 19.0 8.93 1.03 3.99 33.0 33.2 12.0 42 EUC2-1 23.0 5.42 0.89 0.83 30.1 32.1 2.6 43 EUC2-2 20.2 8.96 0.77 1.92 31.9 33.0 5.8 44 EUC3-1 21.3 5.67 0.82 0.72 28.5 31.3 2.3 45 EUC3-2 17.3 8.47 0.82 5.80 32.4 32.0 18.1 46 ATR1-1 20.0 6.16 0.91 1.01 28.1 31.1 3.2 47 ATR1-2 17.2 6.75 0.92 2.91 27.8 28.6 10.2 48 ATR3-1 20.0 7.29 1.44 1.18 29.9 30.0 3.9 49 ATR3-2 18.3 9.77 0.76 3.55 32.4 32.7 10.9
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Appendix 3. Site information, landscape indices (STA stability, INF infiltration, NCI nutrient cycling index) and properties of Kelian soil samples. No Zone Rep Depth STA INF NCI WSA BD sand csilt fsilt clay (cm) (%) (mm) g/cm3 (%) 1 Forest 1 0-1 90.6 71.2 71.8 0.16 47.5 7.4 12.8 32.3 2 Forest 1 1-3 3.21 0.42 54.7 7.9 12.7 24.7 3 Forest 1 3-5 3.25 0.51 59.5 7.6 12.2 20.8 4 Forest 1 5-10 59.3 7.5 11.5 21.8 5 Forest 2 0-1 87.5 64.2 61.5 2.56 0.55 56.7 12.0 12.6 18.7 6 Forest 2 1-3 2.55 0.80 60.0 10.1 10.1 19.7 7 Forest 2 3-5 2.01 0.86 60.2 7.3 12.3 20.2 8 Forest 2 5-10 62.5 8.2 10.6 18.7 9 Forest 3 0-1 87.5 64.2 61.5 3.55 0.54 60.3 6.6 11.1 22.0 10 Forest 3 1-3 2.45 0.85 63.5 8.6 10.8 17.0 11 Forest 3 3-5 2.23 1.01 66.1 5.9 9.9 18.0 12 Forest 3 5-10 64.2 7.1 9.5 19.2 13 Forest 4 0-1 90.6 71.2 71.8 4.03 0.48 63.7 3.7 9.8 22.9 14 Forest 4 1-3 3.53 0.66 63.7 5.5 9.6 21.2 15 Forest 4 3-5 2.94 0.67 65.4 6.4 9.6 18.6 16 Forest 4 5-10 65.7 6.0 10.3 18.0 17 Forest 5 0-1 90.6 69.5 69.2 3.53 0.68 70.1 4.4 9.5 16.0 18 Forest 5 1-3 1.64 0.96 71.4 4.9 9.0 14.7 19 Forest 5 3-5 1.06 1.08 71.2 5.3 9.8 13.8 20 Forest 5 5-10 64.7 7.0 12.9 15.5 21 Bank 1 0-1 81.3 51.3 53.7 2.96 0.50 37.7 3.0 20.7 38.7 22 Bank 1 1-3 2.81 0.72 48.4 3.3 16.3 32.0 23 Bank 1 3-5 2.02 0.81 34.7 4.4 17.1 43.7 24 Bank 1 5-10 16.7 4.8 17.2 61.3 25 Bank 2 0-1 81.3 51.3 53.7 3.58 0.66 30.5 3.7 21.6 44.2 26 Bank 2 1-3 3.28 0.47 14.2 5.1 16.5 64.3 27 Bank 2 3-5 2.72 0.87 17.8 4.1 16.0 62.1 28 Bank 2 5-10 9.9 5.2 15.1 69.8 29 Bank 3 0-1 78.1 46.9 47.3 0.12 17.2 3.3 23.3 56.1 30 Bank 3 1-3 2.29 0.43 14.1 3.4 15.5 67.1 31 Bank 3 3-5 2.27 0.70 13.2 3.8 16.0 67.0 32 Bank 3 5-10 10.4 4.8 15.5 69.3 33 Bank 4 0-1 81.3 51.3 53.7 3.68 0.46 14.3 3.3 14.0 68.4 34 Bank 4 1-3 3.66 0.81 32.9 2.8 12.4 51.9 35 Bank 4 3-5 2.90 0.94 37.3 3.8 13.1 45.8 36 Bank 4 5-10 51.5 4.3 10.9 33.3 37 Trough 1 0-1 75.0 51.3 53.7 0.20 47.4 7.4 22.8 22.3 38 Trough 1 1-3 0.94 0.48 54.3 6.4 21.9 17.4 39 Trough 1 3-5 0.49 1.02 52.6 8.2 23.2 16.0 40 Trough 1 5-10 60.3 4.7 20.1 14.9 41 Trough 2 0-1 84.4 57.1 53.7 0.17 47.8 5.2 24.4 22.6 42 Trough 2 1-3 2.04 0.48 53.7 5.5 23.1 17.6 43 Trough 2 3-5 1.02 0.86 35.1 9.6 34.6 20.6 44 Trough 2 5-10 42.3 8.5 26.4 22.8 45 Trough 3 0-1 81.3 57.1 53.7 0.73 0.75 13.3 10.7 45.9 30.2 46 Trough 3 1-3 0.57 0.99 15.4 15.8 43.5 25.2 47 Trough 3 3-5 0.61 1.05 17.9 16.3 42.3 23.4 48 Trough 3 5-10 33.3 11.3 32.3 23.1 49 Trough 4 0-1 75.0 51.3 53.7 0.21 32.9 3.2 26.4 37.6 50 Trough 4 1-3 1.69 0.71 30.8 8.7 32.1 28.3 51 Trough 4 3-5 0.86 1.09 45.9 6.7 21.2 26.1
190
No Zone Rep Depth STA INF NCI WSA BD sand csilt fsilt clay (cm) (%) (mm) g/cm3 (%) 52 Trough 4 5-10 57.2 3.1 15.6 24.1 53 Mound 1 0-1 68.8 42.6 41.0 0.15 53.3 4.7 21.3 20.7 54 Mound 1 1-3 1.34 0.51 46.9 8.7 24.0 20.4 55 Mound 1 3-5 0.86 1.18 42.4 8.7 27.1 21.8 56 Mound 1 5-10 40.8 8.2 29.2 21.8 57 Depression 1 0-1 71.9 48.7 49.9 2.03 1.04 9.7 7.7 36.3 46.3 58 Depression 1 1-3 1.09 1.15 13.1 7.2 33.5 46.1 59 Depression 1 3-5 0.91 1.33 31.9 5.8 24.9 37.5 60 Depression 1 5-10 34.0 7.4 23.2 35.4 61 Mound 2 0-1 75.0 40.8 38.4 0.96 1.01 34.1 7.9 20.7 37.3 62 Mound 2 1-3 1.26 1.03 34.2 7.6 22.5 35.7 63 Mound 2 3-5 1.41 1.28 35.1 5.4 21.2 38.3 64 Mound 2 5-10 33.6 5.9 22.0 38.5 65 Depression 2 0-1 56.3 32.1 28.2 1.19 1.21 47.3 8.0 15.5 29.1 66 Depression 2 1-3 0.79 1.12 57.8 4.3 10.7 27.2 67 Depression 2 3-5 0.78 1.35 47.1 7.2 13.6 32.2 68 Depression 2 5-10 39.6 6.7 17.7 36.1 69 Depression 3 0-1 68.8 44.3 43.5 0.96 1.29 58.3 7.2 12.4 22.1 70 Depression 3 1-3 0.44 1.35 57.1 6.5 14.0 22.5 71 Depression 3 3-5 0.21 1.21 58.0 6.3 14.3 21.4 72 Depression 3 5-10 58.4 5.0 13.1 23.5 73 Mound 3 0-1 71.9 35.6 30.7 1.40 0.81 43.8 8.9 17.7 29.7 74 Mound 3 1-3 1.36 0.82 47.5 9.2 17.3 26.0 75 Mound 3 3-5 1.32 1.00 37.4 7.3 20.2 35.1 76 Mound 3 5-10 41.1 4.9 19.8 34.2 77 Steep 1 0-1 37.5 29.8 10.3 0.77 0.99 42.2 2.4 11.7 43.6 78 Steep 1 1-3 1.88 0.82 28.6 1.8 14.0 55.7 79 Steep 1 3-5 1.25 0.87 28.5 3.5 11.9 56.1 80 Steep 1 5-10 18.8 3.2 12.3 65.7 81 Steep 2 0-1 34.4 22.1 10.3 1.51 1.04 58.1 1.8 8.3 31.8 82 Steep 2 1-3 1.71 0.90 13.5 3.0 19.7 63.8 83 Steep 2 3-5 2.16 0.90 24.2 2.7 14.3 58.9 84 Steep 2 5-10 37.2 2.5 13.3 47.0 85 Gentle 1 0-1 37.5 29.8 10.3 1.16 1.05 47.5 2.6 9.5 40.4 86 Gentle 1 1-3 0.78 0.95 33.7 3.5 13.2 49.7 87 Gentle 1 3-5 0.98 1.08 43.2 2.0 12.0 42.8 88 Gentle 1 5-10 30.5 4.1 13.7 51.7 89 Steep 3 0-1 36.1 27.4 20.9 1.95 0.91 49.6 3.2 11.5 35.7 90 Steep 3 1-3 2.44 0.90 30.0 3.1 16.1 50.9 91 Steep 3 3-5 2.15 0.87 17.3 4.3 17.9 60.4 92 Steep 3 5-10 16.2 4.5 16.7 62.6 93 Gentle 2 0-1 41.7 23.9 14.0 1.48 0.92 26.2 3.7 18.1 52.0 94 Gentle 2 1-3 0.92 1.23 36.5 4.2 19.0 40.3 95 Gentle 2 3-5 1.26 1.07 32.8 5.8 20.6 40.9 96 Gentle 2 5-10 31.7 4.8 20.2 43.4 97 Gentle 3 0-1 50.0 23.3 20.5 1.56 1.20 44.1 5.3 19.9 30.6 98 Gentle 3 1-3 2.09 0.87 45.0 4.9 20.0 30.1 99 Gentle 3 3-5 1.38 1.05 36.3 5.7 20.4 37.6 100 Gentle 3 5-10 33.5 5.9 21.0 39.7 101 Steep 4 0-1 43.8 27.4 12.8 1.51 1.03 50.0 2.3 9.8 37.9 102 Steep 4 1-3 2.32 0.86 47.5 3.1 10.5 39.0 103 Steep 4 3-5 2.43 0.91 48.2 2.5 10.7 38.6 104 Steep 4 5-10 33.0 4.1 12.0 50.9
191
Appendix 3. continued
No. pH EC Bic-P Bic-K Total C Total N PMN (dS/m) (mg/kg) (g/kg) (mg/kg) 1 3.62 0.305 19.6 199 161.4 7.82 72.3 2 3.93 0.140 5.7 79 70.2 4.15 28.4 3 3.95 0.106 3.9 59 47.2 2.84 4.6 4 4.28 0.090 6.9 54 32.6 2.01 9.4 5 3.84 0.197 10.2 127 83.0 4.55 58.2 6 3.88 0.163 4.8 107 66.7 3.72 67.7 7 4.09 0.128 5.7 73 53.3 3.10 29.7 8 4.36 0.093 8.3 71 28.5 1.96 14.3 9 3.80 0.248 9.1 167 109.5 5.54 35.4
10 4.12 0.141 3.9 84 51.2 3.20 33.0 11 4.23 0.108 7.8 47 37.9 2.43 43.4 12 4.37 0.081 4.2 38 30.0 2.02 27.4 13 3.90 0.231 10.7 114 105.8 5.32 62.4 14 4.00 0.131 3.7 69 67.7 3.89 46.8 15 4.19 0.109 2.6 46 37.2 2.09 40.5 16 4.22 0.092 2.0 41 24.2 1.68 28.6 17 4.55 0.108 10.1 86 79.1 4.54 54.9 18 4.04 0.126 6.5 64 50.9 3.15 21.8 19 4.16 0.083 5.5 35 22.6 1.67 14.5 20 4.38 0.064 3.7 22 16.2 1.16 4.8 21 5.70 0.377 19.7 240 96.2 8.06 87.9 22 5.71 0.126 11.4 125 38.9 3.56 76.3 23 5.41 0.092 7.1 96 27.8 2.82 48.7 24 4.95 0.117 9.3 65 27.3 2.35 36.7 25 5.56 0.286 12.8 254 95.3 7.69 72.7 26 5.26 0.130 8.5 145 40.8 3.95 63.7 27 5.00 0.113 3.8 119 30.9 3.04 47.4 28 4.84 0.106 9.5 81 25.2 2.26 33.4 29 5.08 0.340 13.8 303 136.5 11.22 40.7 30 4.72 0.155 7.5 75 52.7 5.42 84.6 31 4.87 0.101 7.2 56 34.8 3.64 70.2 32 4.95 0.103 9.7 46 26.7 2.89 61.1 33 5.02 0.303 13.8 293 89.6 8.17 74.5 34 4.91 0.133 9.5 171 42.6 4.35 69.1 35 4.84 0.116 19.3 144 30.0 2.98 42.6 36 4.81 0.094 18.8 121 25.7 2.75 43.7 37 6.50 0.316 22.5 129 65.4 5.79 25.3 38 6.30 0.105 4.2 70 21.4 2.65 34.1 39 5.74 0.078 9.1 63 11.2 1.59 16.7 40 5.17 0.058 3.1 67 6.2 1.27 8.1 41 6.34 0.398 43.8 251 64.2 6.64 17.7 42 6.10 0.154 10.9 106 29.4 3.46 18.3 43 6.24 0.103 5.6 65 17.4 2.46 13.1 44 6.12 0.079 4.2 46 9.7 1.55 4.1 45 5.93 0.275 16.7 91 77.9 6.32 66.0 46 6.17 0.119 6.7 53 29.9 3.14 55.9 47 6.16 0.109 6.9 52 18.4 2.5 18.5 48 6.06 0.079 2.8 36 11.3 1.06 23.7 49 5.75 0.244 37.5 248 133.0 9.18 14.9 50 5.38 0.120 5.8 87 35.5 3.81 46.4 51 5.23 0.067 6.0 38 15.4 2.09 16.2 52 5.03 0.047 5.6 40 7.2 1.16 15.3
192
No. pH EC Bic-P Bic-K Total C Total N PMN (dS/m) (mg/kg) (g/kg) (mg/kg)
53 5.28 0.095 13.3 82 16.8 2.28 33.6 54 4.99 0.045 13.2 55 6.2 1.26 20.5 55 4.91 0.037 23.6 64 4.6 1.23 25.1 56 4.87 0.019 11.2 56 2.8 1.01 15.4 57 5.00 0.088 8.4 93 28.8 3.31 33.1 58 4.90 0.061 5.3 72 6.5 1.44 10.4 59 4.96 0.051 7.7 52 5.6 1.38 22.6 60 5.05 0.053 5.1 59 5.4 1.15 15.4 61 4.93 0.025 11.5 64 4.8 1.35 19.0 62 4.96 0.040 9.3 77 10.8 1.48 1.5 63 4.85 0.023 3.4 44 3.7 0.96 12.8 64 4.80 0.020 1.6 33 4.0 1.01 20.2 65 5.56 0.110 10.2 85 16.5 2.24 27.9 66 5.17 0.062 7.6 44 6.5 1.13 17.1 67 5.07 0.059 6.4 36 6.2 1.48 12.9 68 5.12 0.049 6.5 46 6.2 0.55 11.4 69 6.72 0.125 6.9 34 8.7 0.73 34.9 70 6.73 0.115 6.2 30 4.6 0.29 10.5 71 7.15 0.108 8.9 24 3.6 0.53 14.8 72 7.23 0.114 7.3 29 4.0 0.36 5.8 73 7.76 0.144 15.3 82 10.7 1.01 6.0 74 8.32 0.176 7.1 54 7.8 0.73 4.7 75 8.09 0.232 11.9 66 7.5 0.67 9.1 76 8.21 0.225 12.4 63 9.3 0.85 2.9 77 4.90 0.031 7.8 23 6.6 0.86 17.7 78 4.85 0.022 5.6 14 6.5 0.73 10.9 79 4.85 0.029 9.3 13 7.3 0.70 21.9 80 4.85 0.027 11.1 10 7.9 0.88 27.0 81 5.03 0.015 4.7 7 3.2 0.50 12.1 82 5.01 0.012 3.6 9 3.0 0.43 13.4 83 4.91 0.011 5.5 7 2.7 0.30 17.4 84 4.99 0.015 6.3 7 3.1 0.49 1.4 85 5.34 0.021 9.8 29 4.3 0.52 24.7 86 5.32 0.023 11.2 28 4.8 0.56 9.6 87 5.32 0.030 14.0 32 4.9 0.55 13.0 88 5.37 0.027 14.6 26 4.9 0.57 5.4 89 5.27 0.030 23.6 36 6.2 0.52 2.0 90 6.24 0.138 19.1 27 6.3 0.81 32.9 91 5.61 0.074 18.4 20 7.0 0.44 24.3 92 5.10 0.037 13.9 16 6.9 0.38 10.8 93 6.53 0.097 26.4 36 6.0 0.43 10.3 94 7.43 0.137 34.0 76 5.8 0.47 17.3 95 7.60 0.142 39.5 44 6.2 0.33 12.9 96 7.62 0.228 33.9 50 7.4 0.29 12.2 97 5.13 0.018 44.4 20 4.2 0.14 8.0 98 4.98 0.025 72.1 22 4.4 0.25 13.2 99 4.93 0.024 49.3 25 4.7 0.31 9.5 100 4.88 0.022 42.9 21 5.3 0.15 8.7 101 5.08 0.028 11.6 21 7.5 0.57 6.4 102 5.11 0.028 9.6 21 6.7 0.55 5.7 103 5.15 0.029 10.3 23 6.7 0.54 16.1 104 4.99 0.020 8.9 16 5.3 0.21 13.6