Integrated Forest Management Systems:
Evaluation of forest soil properties for Environmental Quality and
Agricultural Productivity
1,2CHRISTIAN TOOCHI EGBUCHE, 3SU ZHIYAO, AZUBUIKE N.O1,
I.E.DURUANYIM1, MARCELLIN ROBERTSON1, DURU I.C.1,
OKOI U. INA Jnr1
1Department of Forestry/Wildlife Technology, School of Agriculture and Agricultural
Technology, Federal University of Technology Owerri, NIGERIA
2D + C Environmental Systems Consultants Owerri/Abuja, NIGERIA,
3College of Forest Ecology, South China Agricultural University Guangzhou, CHINA
Abstract: Soil physical and chemical properties do affect forests (plant) growth and soil
management systems. Some key and important physical and chemical properties of soil are
mineral content, texture, cation exchange capacity, bulk density, structure, porosity, organic
matter content, carbon-to-ni- trogen ratio, color, depth, fertility, and pH. Sustainable forest
management and soil quality parameters may include such terrestrial functions as carbon
sequestration, land use management, erosion control, plant productivity and a soil’s capacity to
produce biomass. Sustainable forest management consistently requires enhancement of both the
chemical and physical properties of forest soil quality. Land use and change in land use as well
as forest management systems, are main indicators that may determine which soil properties
induce changes in any forest site. Forest management and crop yield are key issues of
environmental/productivity quality in addressing carbon mitigation and absorption in plant
species and agricultural productivity. Five distinct forest soils under major physical properties
and chemical properties were evaluated at the forest ecology laboratory. The results were
determined while considering regional forest management regimes. Correlation analysis in
Deqing forest soil showed that higher correlation of NMC at 25-50cm depth, BD at 0-25cm as
well as 25-50cm while EC was high on 0-40 and 0.60 At the Guangzhou site, acidic levels (pH
0-25cm) indicated minor correlation and soil salinity (EC 25-50cm) also showed minor
correlation. The trend was same the at the Changtan forest site where soil salinity showed only
minor significant relationship (0-25cm). A percentage assessment of SOC (g/kg) among the
forest sites by plot observation showed that Deqing forest site, Changtan and Nanling were well
distributed which confers best forest management regimes that yield to good forest soil chemical
and physical properties. This study gave scientific insight and boast plant functional nutrient
interaction as well as stability towards better agricultural productivity and forest management
systems. This is in agreement that good management and less disturbance in forest soils are
major component of physical and chemical properties interaction, thereby for effective integrated
forest and agricultural management systems.
Keywords: Integrated Forest management Systems, Soil Physical Properties, Soil Chemical
Properties, Environmental Quality, Agricultural Productivity and Correlation analysis of forest
soil properties.
Received: June 16, 2021. Revised: March 8, 2022. Accepted: April 1, 2022. Published: April 26, 2022.
EARTH SCIENCES AND HUMAN CONSTRUCTIONS
DOI: 10.37394/232024.2022.2.13
Christian Toochi Egbuche, Su Zhiyao,
Azubuike N. O, I. E. Duruanyim,
Marcellin Robertson, Duru I. C., Okoi U. Ina Jnr
E-ISSN: 2944-9006
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1 Introduction
Forest Inventory System (FIS) is known as
to store and process forestry information and
produces estimates of current and projected
volume and value estimates of timber and
non-timber products. The Forest Inventory
System is a component of Integrated
Forestry Management Systems and has been
developed to provide managers with up-to-
date information about their forest resources
based upon forest surveys. It is a Strategic
Planning Module formulated for the
optimum long-term forest management
strategy and reports the optimum
combination as well as the schedule of
activities, while considering constraints,
which includes wood flows, capital,
manpower, and environmental
considerations. It is based on the
environmental and ecological factors that
this study was designed to evaluate the basic
soil physical and chemical factors at a
regional scale. Over the years, the forestry
discipline as a natural science has witnessed
a paradigm shift in the approach of forest
management (sustainable utilization of
timber) to environmental stability,
biodiversity monitoring and management,
protecting ecosystem services rendered by
forests and sustained delivery of socio-
economic benefits. These goals are
enshrined in the scientific knowledge for the
management of forests towards the
provisioning of multiple ecosystem services
which includes biodiversity conservation,
water resource management and
conservation, and carbon sequestration,
adaptation, soil quality and agricultural
systems. This paper considered some
technological, scientific and laboratory
evaluation as well as analytical advances in
forest data collection and utilization. Forest
management and crop yield are key issues of
environmental/productivity quality in
addressing carbon mitigation and absorption
in plant species and agricultural
productivity. This evaluation was based on
seeking an advanced scientific knowledge to
understand the various parameters of
Integrated Forest Management System
(IFMS) and Agricultural Systems (AS) in
which soil physical and chemical properties
are of critical importance. This issue at
recent times have been considered a global
challenge in forest soil, environmental
management and agricultural productivity.
Soil constituents are of varying amounts of
silt, sand and clay and the proportion of
components determines a particular
classification. Soil texture constitutes its
implication for management towards ability
to cultivation and compaction. Soils physical
and chemical properties do affect forests
(plant) growth and soil management
systems. The key and important physical and
chemical properties of soil are mineral
content, texture, cation exchange capacity,
bulk density, structure, porosity, organic
matter content, carbon-to-ni- trogen ratio,
color, depth, fertility, and pH. In forest
management, actual applications of an
integrated approach in forest management
do not occur often but Integrated forest
management generally involves taking into
account the totality of interactions of various
sub-systems-social, economic, and
ecological-within the biosphere, together
with integration of goals set for such
management. The main thrust of this paper
is to successfully integrate field and
laboratory evaluation of forest soil chemical
and physical properties as a sub-system of
forestry and agricultural systems. The lack
of scientific knowledge regarding the effect
of physical and chemical soil properties as a
sub-system on the other, as well as lack of
information on integrated forest
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DOI: 10.37394/232024.2022.2.13
Christian Toochi Egbuche, Su Zhiyao,
Azubuike N. O, I. E. Duruanyim,
Marcellin Robertson, Duru I. C., Okoi U. Ina Jnr
E-ISSN: 2944-9006
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management and agricultural systems and
their goals, are some of the major obstacles.
Forest and land are natural resources that
have been attracting increasing utilization
within the tropical regions, thereby resulting
in degradation of soil and forest resources
(Greenland, 1981; Larson, 1986; El-Swaify,
1991; Lal, 1995; Eden, 1996, and Eswaran
et al., 1992). Using a protected forest and
cropland, carbon and nitrogen are
considered very vital in managing forest
ecosystems and soil nutrient availability for
soil fertility which physical and chemical
properties are strong influencing factors.
The evaluation of soil physical and chemical
properties as a forest management parameter
in different forest management systems as in
table 1 of various forest regimes becomes a
strategic study at this time of global change
ecology and climate change. These two
important soil factors constitute major
requirement that gives insight to forest soil
environmental quality and plant yield/
productivity. Soil properties are critical
determinant to fertility of agricultural soils,
it provides the knowledge and scientific
ability to predict and manage forest soil
nutrient dynamics and time versus space
intensity which tends to facilitate the
transition to provide sustainable model in
integrated forest management and
agricultural systems.
Soil chemical and physical properties in
forest and agricultural soils
Soil scientists and foresters in recent times
are faced with the challenge of protecting
soil health. To meet this challenge, they
must gain a better understanding of which
chemical and physical properties of soil are
important to fostering good management of
terrestrial ecosystems and sustainability. In
forest sites, soil quality is relative to forest
ecosystems functions and plant productivity.
Forest soils and forest regimes are
management and ecosystem-dependent, thus
they are an interesting aspect of
investigations. The evaluation of soil
organic carbon and chemical and physical
soil environment properties have become an
important concepts. S.H. Schoenholtz et. al.,
(2000) asserted that the concepts of soil
quality involves evaluation of soil properties
and the relationship of their functions as a
component of a forest/soil healthy
ecosystem. In the same document, soil
quality has been defined as the capacity of a
soil to function within natural or managed
ecosystem boundaries, to sustain plant and
animal productivity and maintain or enhance
water and air quality. Sustainable forest
management and soil quality parameters
may include such terrestrial functions as
carbon sequestration, land use management,
erosion control, plant productivity and a
soil’s capacity to produce biomass.
Sustainable forest management consistently
requires enhancement of both the chemical
and physical properties of forest soil quality.
Land use and change in land use as well as
forest management systems, are main
indicators that may determine which soil
properties induce changes in any forest site.
Soils in various forest management and
stand types in South China is in line with
documented studies, that soil is considered
topmost as a major component in sustainable
land management (Bouma, 1994, Scholes et
al., 1994, Swift and Sanchez, 1984).
Managing soil organic carbon in relation to
soil nutrients is a recognized challenge in
this era of climate change (Ewel, 1986;
Okigbo, 1990; Ragland and Lal, 1993;
Greenland and Szabolcs, 1994; Eger et al.,
1996), and has been characterized by
problems of spatial and temporal borders
(Fresco and Kroonenberg, 1992; Heilig,
1997). This study was designed to evaluate
soil properties in different forest
management regimes as selected field
indicators for forest management and in
relation to SOC concentrat0ion. This aspect
is in conformity that soil quality can be
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DOI: 10.37394/232024.2022.2.13
Christian Toochi Egbuche, Su Zhiyao,
Azubuike N. O, I. E. Duruanyim,
Marcellin Robertson, Duru I. C., Okoi U. Ina Jnr
E-ISSN: 2944-9006
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determined by soil chemical and physical
properties. This has posed a challenge that
can be an opportunity to advance the
knowledge of integrated sustainable forest
management and agricultural systems.
2. Methodology
Study area: This study was conducted
among five forest management regimes and
stand types in Guangdong province of
Southern China. Guangdong Province is
located in the Southeast Asian mainland and
surrounded by Fujian province to the east,
by Jiangxi and Hunan to the north, and
Guangxi province to the West. Guangdong
Province has a long coastline on the South
China Sea and the covers an area of 179,766
km2.
Sampling design and selection of
materials
Five forest management regimes in
Guangdong Province, China were selected
for this evaluation. The forest management
sites as defined in table 1 includes; Changtan
Nature Reserve (secondary forest), Deqing
Nature Reserve (pine and broad mixed
forest), Dongguan Forest Park (young
plantation for non-commercial purpose),
Guangzhou Nature Reserve (Non-
commercial ecological forest) and Nanling
National Nature Reserve (Secondary forest).
The soil samples evaluated were taken from
these forest sites while being mindful also of
each site’s forest stand type and
management systems that might have
influenced organic carbon and soil
properties.
Regional geographical distribution of vegetation regime in Guangdong province, China
Table 1 Geographical distribution of the individual forest regimes and stand types
Forest Regime
Geographic Location
Stand type
Nature Reserve
Changtan
116o03’-16o08’E,24o41’ -
24o49’N
Nature Reserve
Deqing
112o01E,- 23o26’N
Forest Park
Dongguan
22o 57’ N, 113o 47’ E
Nature Reserve
Guangzhou
113o21’E, - 23o09’N
Nature Reserve
Nangling
24 º 37 '- 24 º 57' N,
112 º 30 '- 113 º 04' E
Regional geographical location design of forest/vegetation regimes of Guangdong province:
Guangzhou – North, Changtan – East, Deqing – West, Dongguan – North and Nanling – South
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Christian Toochi Egbuche, Su Zhiyao,
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3. Determination of soil physical
and chemical properties
After establishing forest soil sites according
to stand type classification and forest
management regimes in the region, soil
samples were collected. Soil samples were
taken in all the five forest sites. A 20 x 20 m
plot was marked out at each forest site and
ten 5 x 5 m (0.025) quadrants were used, of
which five were randomly selected for
sampling. Surface (mineral) soil level was
categorized under soil below O horizon and
deep soil was adopted for sampling at
designated depths of 0 - 25 cm (surface
level) and 25 - 50 cm (deep level) using a
standard 2-cm diameter stainless steel
sampling probe. A total of 10 cores were
composite for each quadrant. Two 5 x 5 cm
cores (strata) designated for surface and
inner depth were taken per plot (forest site)
sample to determine bulk density. Soil
samples at both depth samples were
separately finely mixed, air dried, grounded,
and sieved as recommended by Nelson and
Sommers (1996). The collected soil samples
were finely mixed up, bagged in transparent
bags, labeled and transported to the
laboratory for analysis. The samples were
air-dried for 48 hours, crushed with pestle
and mortar then sieved to separate whole
soil (< 2mm). Ground floor soil aggregates,
plant/biomass materials (tree) components
(live vegetation/roots) and stones were
sieved out and removed. Soil bulk density
(Pb) was determined by the core method
(Blake and Hartge, 1986).
Soil chemical data
In reference to the laboratory method
referenced in table 2, major chemical factors
were determined according to the soil
properties analyzed. Chemical properties
include organic matter (external heating of
potassium dichromate volumetric method),
Total soil carbon content was measured
using the H2SO4 -K2 CrO, oxidation method
(Nelson and Sommers, 1982), we regarded
total soil carbon as SOC; and semi-micro
Kjeldhal method was applied for the
determination of total nitrogen. Other factors
were total phosphorous where the method of
bulk soil of 0.05 mol L-1 HCl - 0.025 mol -1
H2SO4 digestion - ammonium
paramolybdate calorimetric phosphorous
with HClO4 - H2SO4 digestion was applied
(Olson and Sommers 1982- NaOH Fusion-
flame spectrophotometry), alkali nitrogen
was determined using Alkaline hydrolysis
diffusion method, available phosphorous
was determined using 0.5 M NaHCO3
extraction- Molybdenum blue colorimetry
method, available potassium was by
NH4OAc extraction-flame
spectrophotometry.
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Christian Toochi Egbuche, Su Zhiyao,
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Table 2 Laboratory methods reference in determination of soil chemical parameters
Chemical properties
Method applied
Reference
SOM determination
Soil Survey laboratory staff.
1992 manual
SOC concentrations and
SOC density
Heating potassium dichromate
volumetric &
Walkley-Black (Cwb) method
Nelson/Sommer
1982
Metson, 1956
Total Nitrogen (Tot.N)
Semi-micro Kjeldhal
Pella. E 1990
Available Nitrogen (Av.N)
Semi-micro Kjeldhal
Pella. E 1990
Total Phosphorous (Tot.P)
Calorimetric method
Olsen & Summer
Available phosphorous (Av.P)
Calorimetric method
Olsen & Summer
1982
Available potassium (Av.K)
0.5 M NaHCO3 extraction
1992 manual
Table 3 Laboratory methods applied in determination of soil physical parameters
Physical properties
Method applied
Reference
Natural moisture content
Gravimetric method
Gardner 1986
Electrical conductivity
Conductivity method
1992 manual
pH values
Cacl2 solution by electrode/meter
McLean 1982
Bulk Density
Measured by method described
Mclean 1982
Soil physical data
Major physical properties of the forest soil
derived from all soil samples for laboratory
and field determination included pH, soil
moisture content, bulk density and electrical
conductivity. Table 3 shows the
determination reference background. Acidity
level was determined in 1: 5 (W/V)
soil/water and 0.01 mol L-1 Cacl2 solution
using a glass electrode (McLean, 1982)- (pH
meter method), electricity conductivity
(conductivity method), bulk density and soil
moisture was further determined by the
method described by McLean (1982).
4 Calculations
The dried sieved samples across the forest
sites were used to measure various soil
properties, of which organic matter (SOC)
content and concentration was determined
by loss on ignition (450 °C for 4 h). Soil
Organic Carbon was estimated by
multiplying organic matter content by 0.58
(Soil Survey Staff, 1992). Organic C
concentration/amounts (kg C m -2) were
calculated as the same in all the forest sites
within two specific depth strata. The
analysis was presented for soil organic C
data for each site in respect to forest stand
type and management regimes.
Soil Organic carbon was calculated using
the basic formula:
SOC (t ha−1) = a × D × B × C × S.
Where a was the constant to adjust for area,
D the soil depth in cm,
B the soil bulk density in g cc−1,
C the organic carbon content (%) and
S the proportion of soil mass <2 mm in the
sample which do not include stone particles.
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Soil density values were calculated
according to the equation (Post et al., 1982)
of D = 100 x c B (1 - § 2mm): Where:
D indicates Soil Organic Carbon density (kg
C m -3)
C indicates SOC content (g kg -1) for a
certain soil depth
B indicates Soil Bulk density (g cm -3)
§ 2mm indicates the content (%) of soil
particles with > 2 mm diameter.
We considered Bulk Density calculation of
the mineral soil core and was calculated by
Pb = ODW
CV - (RF/PD)
Where
Pb - Bulk density of the < 2mm fraction
(g/cm3)
ODW - Oven-dry mass of fine fraction (>
2mm) in g
CV - Core volume (cm3)
RF - Mass of course fragments (> 2mm) in g
PD - Density of rock fragments (g/cm3)
often expressed as 2.65g/cm3
The mineral soil, the amounts of carbon per
unit area are calculated by; C (t/ha) = [(soil
bulk density, (g/cm3) x soil depth (cm) x %
C)] x 100, whereby in the equation above, %
C is expressed as a decimal. In summary,
Bulk density is a measure of the weight of
the soil per unit volume (g/cc), usually given
on an oven-dry (110° C) basis, that is bulk
density is calculated by weight over the
volume, while soil porosity (%) is calculated
by 1 - bulk density divided by particle
density multiplied by 100.
Data analysis
The data analysis primarily involved and
was concentrated on the various forest soils
ranging from 0-25cm and 25-50cm.
Descriptive statistics parameters were
calculated with Microsoft Excel and
STASTICA software 6.0 versions (2001)
and SPSS software (2006). SOC
concentration and density were subjected to
tests of significance as analysis of variance
(ANOVA). The Kruskal-Wallis median test
was used at 5% probability level to evaluate
and determine differences between SOC
variations among forest sites and locations
as shown as least significant difference
(LSD). Soil Organic Carbon including bulk
density, and effects between soil depths
among forest soils were reported.
Multivariate and correlation analysis was
performed with SPSS software to evaluate
the SOC concentration, SOC by stand types
and management regimes. The physical soil
data, standard error of the differences in
mean infiltration rates and soil bulk density
were calculated for the various forest
regimes. Further descriptive statistics such
as means and coefficients of variation
(standard deviation/mean) and comparative
(ANOVA, and Turkey’s multiple
comparison) analyses were also performed
with the SPSS version (1999).
Results
Evaluation of soil bulk density
Individual soil bulk densities were evaluated
at 0-50cm correspondingly. The Dongguan
site (1.43±0.02), Deqing site (1.39±0.02),
and Guangzhou site (1.29±0.03) as shown in
table 4 were assessed in relation to forest
management system and vegetation stand
type.
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Christian Toochi Egbuche, Su Zhiyao,
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Table 4 Soil bulk density (Mg m-3) among forest management regimes (0-50cm)
Site
BD Mean
BD Sdv
Deqing
1.39±0.02
0.14
Guangzhou
1.29±0.03
0.18
Changtan
1.03±0.03
0.19
Dongguan
1.43±0.02
0.11
Nanling
1.28±0.02
0.17
Soil physical properties by multivariate
analyses
Physical soil properties at the five regional
forest sites show that natural moisture
content (NMC) in figure 5 was higher in
Changtan Nature Reserve, which is a
secondary forest. Natural moisture content is
evaluated in relationship with soil and forest
management practices and in Changtan was
400.00g*kg- at a depth of 25-50cm. The site
showed a statistical difference from other
forest depths, though with a minor
correlation to moisture content at the
Dongguan site. Deqing, Guangzhou and
Nanling showed slight correlations and there
was no correlation to the Dongguan site.
Moisture content at the Dongguan site
showed a unique result and strongly
correlated to both depths at the site. The
result in figure 5 therefore indicated that the
higher natural moisture content in Changtan,
Dongguan, and Guangzhou forest sites at
25-50cm is a prove that soil organisms and
plant stands may show higher respiration
and photosynthetic chemical processes. Bulk
densities under various forest management
systems were not similar in all forest soil
depths as in figure 6 though at the Deqing
site all depths showed the same trend and
were correlated. The bulk densities in the
secondary forest, protected (non-
commercial), young plantation as well as
pine and broad mixed leaved forest were
however, significantly higher, especially in
Deqing (1.40g*cm3-) and Guangzhou (1.42
g*cm3-).
Figure 5: Natural moisture evaluations in forest soils
NMC
e
cde
de
de
b
a
bc
bc
cd
cde
0.00
50.00
100.00
150.00
200.00
250.00
300.00
350.00
400.00
450.00
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
g.kg-1
NMC
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Figure 6: Bulk Density evaluations among forest sites
Figure 7 pH evaluations in the forest sites
Bulk density is a measure of the total mass
of a moist soil per unit volume. Topsoil and
medium depth from all the forest sites
showed a unique and classical inference of
the region’s soil acidic level irrespective of
the management practices. Figure 6
confirms this information but from a
different level in the Guangzhou Nature
Reserve (a non-commercial site) at 25-50cm
depth (6.0) showing a significant decline in
pH. pH levels of soil acidity or alkalinity
were found in the topsoil but no changes
were found in the lower horizons of all sites
(fig.7), where all were less than 7.
Electrical conductivity level in all the sites
were high as shown in figure 8. Soil salinity
is conventionally expressed in terms of EC
and is among the most useful and easily
obtained spatial properties of soil that
influences crop productivity and forest
health. Deqing and Changtan forest sites
showed highest and significantly different at
BD
bc
d
ab
a
e
f
c
d
abc
abc
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
g·cm3-
BD
pH
a
a
b
a
a
a
a
a
a
a
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
pH
pH
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surface level (0-25cm). However, the EC
evaluation in Changtan site indicated highest
in both soil levels (0-25cm and 25-50cm).
Figure 8: Electrical conductivity evaluations among the forest sites
Table 5: Correlation analysis of major physical properties in Deqing site
SOC
NMC
BD
pH
EC
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Deqing0-25
0.06
-0.20
-0.03
0.27
0.02
-0.01
-0.40*
0.60**
Deqing25-50
-0.48*
0.03
0.25
-0.39
-0.02
-0.06
0.10
0.22
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-tailed).
Based on these evaluations, further
correlation analyses for basic physical soil
properties in individual sites for the
determination of critical values was
conducted as shown in table 5. There was
minor correlation in most sites though there
was significant differences at the Deqing site
(25-50cm) on NMC and EC (-0.48 and -
0.40), with critical and significant difference
at the same site for which NMC at 25-50cm
was 0.60. At the Guangzhou site, acidic
level (pH) 0-25cm indicated minor
correlation and soil salinity (EC) 25-50cm
also showed minor correlation in table 6.
The trend was the same at the Changtan
forest site shown in table 7, where soil
salinity showed only minor significant
relationship at 0-25cm.
EC
cd
bcd
cd
d
ab
a
bcd
bc
bc
a
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
μs·cm-
EC
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Table 6: Correlation analysis of major physical properties in Guangzhou site
SOC
NMC
BD
pH
EC
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Guang0-25
-0.14
-0.09
-0.23
0.04
0.37
-0.37
-0.27
-0.42*
Guang25-50
-0.03
0.02
-0.09
-0.01
-0.42*
-0.39
0.34
-0.44*
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-tailed).
Table 7: Correlation analysis of major physical properties in Changtan site
SOC
NMC
BD
pH
EC
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Chang0-25
-0.12
-0.10
-0.14
-0.10
-0.18
-0.04
-0.03*
-0.05
Chang25-5
-0.14
0.03
-0.07
-0.33
-0.22
-0.22
-0.45*
-0.19
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-
tailed).
The fact remains that a combination of
factors influences EC measurements to
varying degrees across the region, which
may be attributed to regional forest
management practices. These factors include
soil salinity, bulk density, pH and moisture
content that has been evaluated among the
forest regimes and where EC dominated the
soil factors though the forest sites
measurements and interpretations showed no
correlation, as shown in table 8 (Dongguan
site) and table 9 (Nanling site) that NMC,
BD and EC were indicated as strongly
correlated especially at the deeper depth (25-
50cm). To use spatial measurements, these
soil properties are significantly influential
factors for vegetation stand type and
considered in management regimes.
Table 8: Correlation analysis of major physical properties in Dongguan site
SOC
NMC
BD
pH
EC
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Dong0-25
-0.09
0.19
-0.32
-0.05
-0.10
-0.05
-0.11
-0.07
Dong25-5
-0.08
0.56**
-0.24
-0.52**
-0.20
-0.12
-0.46*
-0.02
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-tailed).
Table 9: Correlation analysis of major physical properties in Nanling site
SOC
NMC
BD
pH
EC
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Nang0-25
-0.01
0.18
-0.22
-0.12
-0.02
-0.02
-0.18
-0.15
Nang25-5
-0.07
0.15
-0.26
-0.44**
-0.09
-0.07
-0.16
-0.10
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-tailed).
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Figure 9: SOM evaluations among forest soils
(Deq- Deqing, Don-Dongguan, Cha- Changtan, Gua-Guangzhou and Nan-Nanling forest sites)
Soil chemical properties by multivariate
analysis
SOM and SOC evaluation in all the forest
sites in fig. 9 and fig. 10 showed that the
density and concentration found in these
properties reflect as a strong indicator's
relationship with soil properties and forest
ecosystem function. SOM in fig. 9 showed
highest at the Deqing (Deq) forest site
(51g*kg- and 49g*kg-) at both designated
depths; Changtan (Cha) and Nanling (Nan)
sites (0-25cm) were very high (49g*kg-).
High concentration of SOC was further
observed at the Deqing forest site (30g*kg-
and 27g*kg-), exhibiting same pattern in
Changtan and Nanling at surface level
(29g*kg-), respectively, in each sites (fig 10).
Dongguan (Don) and Guangzhou (Gua)
were comparably low in all the forest soil
depths indicating no significant differences.
SOM
b
a
b
b
b
a
b
b
a
a
0.00
10.00
20.00
30.00
40.00
50.00
60.00
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
g·kg-
SOM
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Figure 10: SOC concentration among forest soils
(Deq- Deqing, Don-Dongguan, Cha- Changtan, Gua-Guangzhou and Nan-Nanling forest sites)
This skewed distribution may be as a result
of forest soil management systems and
nutrient interactions. Available nitrogen was
highest at the Deqing and the Changtan site,
available potassium was evenly distributed
at almost all the sites, though highest in
Deqing, Guangzhou, and Nanling, as shown
in fig. 11. Furthermore, available
phosphorous showed very low distribution
in all the forest sites and highest in Changtan
and Deqing (fig.11).
Figure 11: Available nutrients evaluation among the forest soils (available nitrogen,
available potassium and available phosphorous
(Deq- Deqing, Don-Dongguan, Cha- Changtan, Gua-Guangzhou and Nan-Nanling forest sites)
SOC
b
a
b
b
b
a
b
b
a
a
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
g·kg-
SOC
Available Nutrients
cd
bcd
d
d
b
a
cd
bc
bc
a
bc
b
b
ab
c
bc
c
c
ab
a
cd
bcd
d
d
ab
abc
a
ab
a
a
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
mg.kg-
AvN AvK AvP
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Figure 12: Total nutrients evaluated among forest soils (total nitrogen and total
Phosphorous (Deq- Deqing, Don-Dongguan, Cha- Changtan, Gua-Guangzhou and Nan-Nanling forest
sites)
Spatial distribution of total nitrogen was
normally distributed and high in all sites as
shown in figure 12, while total phosphorous
was comparably low at all sites. These
results seem to be in complete agreement to
the fact that overall of Soil Quality (SQ)
reflects the effects of management practices
on soil function. Correlation analyses of the
major chemical parameters to SOC
concentration further indicated at the Deqing
site (table 10) has critical correlation at
surface level (0-25cm) in total nitrogen,
available potassium, and phosphorous, but
has a minor correlation in total phosphorous.
Table 10: correlation evaluation of chemical properties in Deqing site
SOC
Vann
TotN
AvK
AvP
TotP
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Deq0-25
0.14
0.38
0.63**
-0.17
0.57**
-0.16
-0.12
-0.43*
0.14
0.50*
Deq25-50
-0.11
-0.03
0.04
0.39
-0.12
0.34
-0.03
-0.38
-0.07
0.09
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-tailed). Deq -
Deqing forest site
Total Nutrients
cd
bc
cd
cd
cd
ab
d
cd
bc
a
c
bc
c
bc
ab
a
ab
a
bc
ab
0.00
0.50
1.00
1.50
2.00
2.50
Deq0-25
Deq25-50
Don0-25
Don25-50
Cha0-25
Cha25-50
Gua0-25
Gua25-50
Nan0-25
Nan25-50
sites-depth
g.kg-
TotN TotP
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The Guangzhou site as in table 11 was
significant and critically correlated as
compared to other sites, where total
nitrogen, available P, K and total P were
critically correlated virtually at all depths
against SOC concentration. This was
attributed to the management practices from
the University forest authority and restrictive
policies. Table 12 indicated that at the
Changtan site, total N and available P in
correlation to organic carbon concentration
were significantly higher at all depths.
Table 13 and 14 showed the correlation
results in Dongguan and Nanling forest sites
where available K (25-50cm) at the
Dongguan site showed critical correlation to
SOC concentration, while at the same site,
as well in Nanling (25-50cm), available P, N
and K were minor in relation to SOC.
Table 11: Correlation evaluation of chemical properties in Guangzhou site
SOC
AvN
TotN
AvK
AvP
TotP
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Guang0-25
0.17
0.09
0.69**
0.81**
0.55**
0.47*
0.73**
0.71**
0.05
0.41*
Guang25-50
0.12
0.08
0.74**
0.81**
0.51**
0.40*
0.83**
0.77**
0.06
0.44*
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-tailed).
Guang - Guangzhou forest site
Table 12: Correlation evaluation of chemical properties in Changtan site
SOC
AvN
TotN
AvK
AvP
TotP
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Chang0-25
0.32
0.09
0.83**
0.27
0.24
-0.36
0.30
0.19
0.24
-0.14
Chang25-50
-0.06
0.00
0.39
0.57**
0.15
0.33
0.78**
0.73**
-0.07
0.19
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-
tailed). Chang - Changtan forest site
Table 13: Correlation evaluation of chemical properties in Dongguan site
SOC
AvN
TotN
AvK
AvP
TotP
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Dong0-25
-0.13
-0.02
0.05
-0.14
0.14
0.08
0.08
0.01
-0.13
-0.07
Dong25-50
0.20
-0.22
-0.16
0.38
0.08
0.55**
-0.13
0.41*
0.14
0.32
* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level (2-tailed). Dong-
Dongguan forest site
Table 14: Correlation evaluation of chemical properties in Nanling site
SOC
AvN
TotN
AvK
AvP
TotP
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
0-25
25-50
Nang0-25
-0.24
-0.19
0.15
0.19
0.22
0.34
0.15
0.21
0.00
-0.41*
Nang25-50
-
0.40*
-0.08
0.11
0.16
0.32
0.48*
0.24
0.11
0.05
-0.23
* Correlation is significant at the 0.05 level (2-tailed) ** Correlation is significant at the 0.01 level (2-
tailed). Nang- Nanling forest site
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5 Discussion
Forest soil physical properties
The assessment of soil chemical and
physical properties which is classified as
indicators for sustainable forest
management. Forest sites and soil quality is
relative to forest ecosystems functions and
plant productivity. Forest soils and forest
regimes are management and ecosystem-
dependent thus becoming an interesting
aspect of investigations. It also focuses on
the influences of soil environment factors in
the concentration and density of organic
carbon in forest soils. This study aspect is in
conformity that land use and land-use
change are major culprit in soil nutrients
negative impacts. Forest management
systems and forest soils health should be
maintained through less exploitation of soil
and forest resources. This current study has
further proved that physical and chemical
forest soil parameters are influential to soil
organic carbon concentration and density in
forest regimes.
The higher moisture content in soils
depicted the plant potential to engage in
biogeochemical processes for organic matter
density and concentration. We attributed this
evidence to the fact that the Changtan and
Nanling sites are secondary forests with
protected management practices. The
situation at the Dongguan site may be
attributed to the indirect influence of urban
and industrial activities (Oke, 1995, Mount
et al., 1999, Lee and Longhorns’ 1992, De
Miguel et al., 1977 and Meilke 1999).
However, land use and vegetation cover may
serve as an indicator of disturbance, site
history, management, and the urban
environment—factors that should
disproportionately affect surface rather than
subsurface soil properties that greatly
influence moisture content. Forests site may
be associated with lower moisture content
and correspondingly will result in
differences in organic matter composition.
We observed that in some pits roots were
absent in some parts which is commonly
found in compacted soils, and it has been
found that soil compaction is an attribute of
land use and change in land use, as well as
forest management practices that may arise,
as reported by Juang and Uehara (1971) in
sugarcane harvesting and other field
operations. The pH factor becomes
important because some plant stand types
grow better in either acidic or alkaline
conditions. pH can influence the availability
of soil nutrients in different forest types.
Acidification thus increases the
concentration of potassium (K), magnesium
(Mg), and calcium (Ca) in soil solution.
Smith, C. J et. al., (1994) documented that
nutrient cations such as zinc (Zn2+),
aluminium (Al3+), iron (Fe2+), copper (Cu2+),
cobalt (Co2+), and manganese (Mn2+) are
soluble and available for uptake by plants
below pH 5. pH levels also affect the
complex interactions among soil chemicals.
Furthermore, Wikipedia organization
(http://en.wikipedia.org/wiki/Soil_pH)
extensively reported that soil acidification
may also occur by addition of hydrogen, due
to decomposition of organic matter, acid-
forming fertilizers, and exchange of basic
cations for H+ by the roots. Certain factors
influence pH values of a soil, such as the
kinds of parent materials used for soil
formation and rainfall. Anthropogenic
pollutants do influence soil pH; this was
attributed to the Guangzhou and Dongguan
forest sites that have attracted heavy traffic
across these urban sites. Also the application
of fertilizers containing ammonium or urea
speeds up the rate at which acidity develops.
The decomposition of organic matter also
adds to soil acidity. pH and EC are
associated with the effects of salinity and
acidity that may be manifested in loss of
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stand, reduced rates of plant growth, reduced
yields, and in severe cases, total crop failure
(Rhoades and Loveday, 1990). Salinity
limits water uptake by plants by reducing the
osmotic potential and thus the total soil
water potential. In the studied forest sites,
there exists strong correlation between the
amount of salinity in the Deqing and
Changtan secondary and protected forests
measured at 0-25cm surface depth. The site-
specific relationship with all the forest sites
in South China therefore shows that
sustainable forest and land management are
based on distributive soil chemical and
physical factors. These factors also exhibit
corresponding influence on soil organic
carbon density and concentration (Smyth
and Dumanski, 1995).
Forest soil chemical properties
This study results suggests that soil chemical
properties may be spatially dependent and
that the dependence in this example
represents and reflect the soil-forming
processes and perhaps forest soil
management. Soil properties may strongly
suggest that soil management and forest
regimes are strong indicators for soil and
forest health. The major chemical
parameters evaluated in South China showed
that there was normal distribution in most of
the variables. This inference is related to the
specific forest management history and
effect of stand types in the region. This
investigation in situ therefore shows that
protected, fewer disturbances, secondary
stand types and management practices that is
classified in the Deqing, Changtan and
Nanling forest soils were positively
correlated to SOC concentration. This has
been considered also proved by the
correlation analysis in most chemical factors
in the sites. The Guangzhou forest soil and
SOC concentrations were strong and showed
positive relationship between the
parameters. This is an attribute of best forest
soil management control from the University
forest authority. Other physical and
chemical factors across the region supports
enhanced microbial dynamics, including
respiration rates (Bohlen et al., 2001; Chen
et al., 2003; Hannam and Prescott, 2003);
Changes in soil properties may continue to
change as long as the current management
strategies remain unchanged though it may
not be possible to predict at what pace such
will happen. In as much as the use of
fertilizers, encroachment to forested lands,
high emission of greenhouse gases and other
anthropogenic activities are likely to be
steadily into play in the region. These may
result to influences on organic carbon and
soil properties. Some important and general
references are such example as documented
by Hartemink, (1998), on pH buffering
capacity may increase reducing the
acidifying effects of sulphate of ammonia
which may also reduce the compatibility of
the soil by increasing resistance to
deformation (Soane, 1990). Based on the
current study, which is in conformity that
physical and chemical forest soil parameters
are influential to soil organic carbon
concentration and density in forest regimes.
This may have accounted to the various site
soil organic carbon distribution and patterns
in South China.
Correlation of forest soil properties and
SOC
Correlation analyses of the major chemical
parameters to SOC concentration further
indicated at the Deqing site (table 8) has
critical correlation at surface level (0-25cm)
in total nitrogen, available potassium, and
phosphorous, but has a minor correlation in
total phosphorous. The Guangzhou site
(fig.9) was significant and critically
correlated as compared to other sites, where
total nitrogen, available P, K and total P
were critically correlated virtually at all
depths against SOC concentration. This was
attributed to the management practices from
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the University forest authority and restrictive
policies. Table 10 indicated that at the
Changtan site total N and available P in
correlation to organic carbon concentration
were significantly higher at all depths.
Table 11 and 12 showed the correlation
results in Dongguan and Nanling forest sites
where available K (25-50cm) at the
Dongguan site showed critical correlation to
SOC concentration, while at the same site,
as well in Nanling (25-50cm), available P, N
and K were minor in relation to SOC. A
percentage assessment of SOC (g/kg) among
the forest sites by plot observation showed
that Deqing forest site, Changtan and
Nanling were well distributed which confers
best forest management regimes that yield to
good forest soil chemical and physical
properties.
SOC(g/kg
Percentage by plot observation
Deqing
-10 10 30 50 70 90 110
0%
2%
4%
6%
8%
10%
12%
14%
Guangzhou
-10 10 30 50 70 90 110
Changtan
-10 10 30 50 70 90 110
Dongguan
-10 10 30 50 70 90 110
0%
2%
4%
6%
8%
10%
12%
14%
Nanling
-10 10 30 50 70 90 110
6. Conclusions
The long and short term improved natural
management systems and regimes adapted
have significant effects on soil physical and
chemical properties in Guangdong region of
China. Soil chemical and physical properties
in both systems of management appear to be
in line with management regimes and
overtime. The dynamics of soil physical and
chemical indicators do change significantly
in both systems of management as compared
to secondary natural forest (SF). It is
observed that assessment and depth of soil
have significant effects on physical
indicators such as bulk density, porosity,
field capacity and wilting point. It is
anticipated that in both systems of
management and regimes the SOM content
at various soil depths increased with time
(periodic), however increase of SOM,
extractable P, K, and Mg, and exchangeable.
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Future research is needed to explore the
spatial impact of different vegetation stand
type and influence of climate change, soil
microbes and socio-economic services. This
study identifies the following findings:
a. Soil structure is influenced by its physical,
chemical and biological characteristics.
Good soil
structure is vital, as it can affect the
availability of air, water and nutrients for
plant growth.
b. Forestry and Agricultural practices can
significantly alter soil structure.
c. Management systems significantly
influenced total soil C and N concentrations
at the 0- to 25- cm profile in forest soil and
associated with both chemical and physical
properties.
c. Forest soil properties 0- to 25-cm soil
profile are influenced and correlations with
different
d. Relationship of forest soil (chemical and
physical) properties are influenced by
management systems and regimes at
regional and time scales.
The field and laboratory evaluation reveals
that forest soils and management systems
are key
factors of managing SOC and N in forestry
and agricultural systems. This study
recommends the
appropriate application of Soil Conditioning
Index (SDI) in the effective forest soil and
agricultural management systems. SCI can
be used to predict a positive or negative
trend in soil organic matter on agricultural
land, predict how modifications of a
management system will affect the level of
soil organic matter and evaluate
conservation management systems, when
used along with other assessment methods.
The periodic evaluation and SDI knowledge
of forest/vegetation soils, forest and
agricultural management systems will
proffer solutions to problems of integrated
forest/agricultural management system in
this era of global change ecology.
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