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SOIL ORGANIC CARBON SEQUESTRATION
POTENTIALS IN AGGREGATE FRACTIONS OF
CULTIVATED AND UNCULTIVATED SOILS OF
OKEBALAMA CHINYERE BLESSING (REG. NO: PG/M.Sc./06/41040)
A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE AWARD OF THE
DEGREE OF MASTER OF SCIENCE
(M.Sc.) IN SOIL SCIENCE
DEPARTMENT OF SOIL SCIENCE
UNIVERSITY OF NIGERIA
Okebalama, Chinyere B., a postgraduate student in the Department of Soil Science, with
the Reg. No: PG/M.Sc./06/41040 has satisfactorily completed the requirements for course and
research work for the degree of Master of Science (M.Sc.) in Soil Science.
The work embodied in this dissertation is original and has not been published or
submitted in part or full for any other diploma or degree of this or any other University.
Prof. C. A. Igwe Prof. C. L. A. Asadu
Supervisor Head of Department
This work is dedicated to Almighty God who in His infinite grace and mercy sustained
and supported me all through, having endowed me with the intellect to complete it successfully.
I also dedicate this work to my wonderful parents, Elder and Mrs S.U. Okebalama who
set the standard I strive to reach.
My sincere gratitude goes to God Almighty for the knowledge, understanding, sustenance
and grace granted to me for the successful completion of this research work.
I am very grateful to my project supervisor, Prof. C.A. Igwe for his intellectual
inspiration, guidance, encouragement, fatherly advice and provision of valuable materials used in
the course of this work. Indeed, his intuition is incisive and I am greatly privileged to have been
mentored by him thus far.
My special gratitude goes to all members (past and present) of the Department; late Prof.
J.S.C. Mbagwu of blessed memory, Prof. M.E. Obi, Prof. F.O.R. Akamigbo, Prof. C.L.A. Asadu,
Prof. N.N. Agbim, Prof. C.C. Mba, Mr M.C. Jidere, Miss I.M. Okpara, Mr S.E. Obalum and all
the laboratory staff for their directives, advice, suggestions, encouragement and knowledgeable
contributions in making this work a better one.
I also appreciate Prof. I.U. Obi, Prof. K.P. Baiyeri, and Dr P.N. Ogbonna whose
guidance, advice and encouragement were so helpful in the project facilitation. I am thankful to
Prof. O.A. Opara-Nadi of Abia State University, Uturu who allowed me source for relevant and
valuable literature from his collections.
I am particularly grateful to the members of my family, especially my parents whose
moral and financial assistance made it possible for me to enroll in this programme. Their advice
has greatly benefited me in my career development.
Finally, I appreciate all my friends: Mr Funso Fasipe, Gideon Umoh, Darlington Achonu,
Christopher Nwokocha, Chinyelu Kanemeh, Adaobi Ikeanyi, Mr and Mrs Tayo Ajayi, Emeka
Muora, Chinedu Okoro, Chimezie Nwaimo, Ozoagu Afamefuna, and Christian Nwosu for all
their inestimable support and involvement in seeing to the production of this work. May the good
Lord reward and bless you all exceedingly, Amen.
TABLE OF CONTENTS
TITLE PAGE ........................................................................................................................ i
CERTIFICATION ................................................................................................................ ii
DEDICATION ...................................................................................................................... iii
ACKNOWLEDGEMENT .................................................................................................... iv
TABLE OF CONTENTS ...................................................................................................... v
LIST OF TABLES ................................................................................................................ vii
LIST OF FIGURES .............................................................................................................. viii
LIST OF APPENDIX........................................................................................................... ix
ABSTRACT .......................................................................................................................... x
1.0 INTRODUCTION .................................................................................................... 1
2.0 LITERATURE REVIEW ......................................................................................... 4
2.1 An Overview of Global Carbon ................................................................................ 4
2.2 Soil Organic Carbon Dynamics ................................................................................ 6
2.3 Soil Organic Matter and Total Soil Nitrogen in Water Stable Aggregates ............... 10
2.4 The Concept of Soil Organic Carbon Sequestration ................................................. 12
2.4.1 Importance of Carbon Sequestration ........................................................................ 14
2.5 Influence of Soil Carbon and Total Nitrogen on Soil Properties .............................. 15
2.6 Effects of Land Use Management on Soil Carbon and Nitrogen ............................. 17
2.7 Factors Affecting Soil Organic Carbon and Total Soil Nitrogen
Pool in the Tropics ..................................................................................................... 20
3.0 MATERIALS AND METHODS .............................................................................. 26
3.1 Site Description ......................................................................................................... 26
3.2 Methods ..................................................................................................................... 27
3.2.1 Field Study ................................................................................................................. 27
3.2.2 Laboratory Study ....................................................................................................... 27
220.127.116.11 Physical Analysis ....................................................................................................... 28
18.104.22.168 Chemical Analysis ..................................................................................................... 29
3.3 Statistical Analysis ..................................................................................................... 30
4.0 RESULTS AND DISCUSSION .................................................................................. 31
4.1 Results .......................................................................................................................... 31
4.1.1 Soil Characteristics ...................................................................................................... 31
4.1.2 Microaggregate Stability Indices of the Soils .............................................................. 35
4.1.3 Water-Stable Aggregates, Mean Weight Diameter and Geometric Mean Weight
Diameter of the Soils ................................................................................................... 38
4.1.4 Soil Carbon and Nitrogen Content, and C/N Ratio in the Water-Stable Aggregates .. 40
4.1.5 Soil Organic Carbon Pool ............................................................................................ 43
4.1.6 Land Use Effect on Aggregates Size Distribution, C, and N
Contents of the Soils .................................................................................................... 46
4.1.7 Soil Texture in Relation to Soil Organic Carbon Pool ................................................ 46
4.1.8 Relationship between Aggregate Stability Indices and Soil Properties ....................... 56
4.2 Discussion .................................................................................................................... 64
5.0 SUMMARY, CONCLUSION AND RECOMMENDATION .................................... 70
LIST OF TABLES
TABLE TITLE PAGE
1 Global carbon pool and fluxes among them ............................................................. 5
2 Global soil organic carbon pool ................................................................................ 7
3 Particle size distribution and textural classification of the soils .............................. 32
4 Chemical Properties of the soils under cultivated and uncultivated land uses ........ 33
5 Microaggregate stability indices and water content at field
capacity (FC) of the soils .......................................................................................... 36
6 Soil moisture, bulk density, porosity, coefficient of linear extensibility (COLE) and volumetric shrinkage (VS) of the soils ............................ 37
7 Water stable aggregates (WSA), mean weight diameter (MWD) and geometric mean weight diameter (GMWD) of the soils. ......................................... 39
8 Carbon and nitrogen content (g kg-1), and C/N ratio in the various water- stable aggregate (WSA) fractions of cultivated and uncultivated soils ................... 41
9 Soil organic carbon (SOC) pool of cultivated and uncultivated soils
at the various soil depths. .......................................................................................... 44
10 Land use effects on water-stable aggregate (WSA) concentration at the various soil depths, and at 0-30 cm depth. ......................................................... 47
11 Land use effects on soil organic carbon (SOC) content in water-stable aggregates (WSA) at the various soil depths ........................................ 48
12 Land use effect on total soil nitrogen (TSN) content in water-stable aggregates (WSA) at the various soil depths ............................................................ 49
13 Land use effect on soil organic carbon (SOC) content in water-stable aggregates (WSA) at 0-30 cm depth .................................................... 50
14 Land use effects on total soil nitrogen (TSN) content in water-stable aggregates (WSA) at 0-30 cm depth. ....................................................................... 51
15 Land use effects on C/N ratio of water-stable aggregates (WSA)
at 0-30 cm depth........................................................................................................ 52
16 Land use effects on bulk density, > 2.00 mm water stable- aggregate (WSA), mean weight diameter (MWD) and geometric
mean weight diameter (GMWD) of the soils. .......................................................... 53
17 Soil texture effects on soil organic carbon (SOC) pool at the various sampling depths ........................................................................................... 54
18 Correlation coefficient (r) among particles sizes, aggregate indices and some selected properties of the soil under cultivated
and uncultivated land uses ....................................................................................... 59
19 Correlation coefficients (r) of the soils chemical properties and soil organic carbon (SOC) pool of cultivated and uncultivated land uses. ....... 62
20 Relationship between soil organic carbon (X) and structural stability indices (Y) in cultivated and uncultivated land uses (n = 12) ..................... 63
LIST OF FIGURES
FIGURE TITLE PAGE
1 Processes affecting soil organic carbon dynamics ................................................... 9
2 Soil depth effects on soil organic carbon (SOC) pool of cultivated and uncultivated soils ............................................................................................... 45
3 Soil texture effects on soil organic carbon (SOC) pool at
the various soil depths .............................................................................................. 55
LIST OF APPENDIX
APPENDIX TITLE PAGE
1 Final analysis of variance of a 4 x 2 x 3 factorial experiment in
CRD showing sources of variation and degree of freedom only ...................... 88
A study was carried out on soils sampled at 0-10, 10-20, and 20-30 cm depths from both
cultivated and uncultivated soils at four different locations (Awgu, Okigwe, Nsukka I, and
Nsukka II), to evaluate the potentials of various aggregate size fractions of varying soil textures
and depths to sequester carbon under different land uses. A 4 x 2 x 3 factorial experiment was
conducted in a completely randomized design (CRD). Factor A was location at four levels, while
factor B (land use) had two levels. Factor C (soil depth) comprised of three levels. Results
showed that in both land uses, soil texture varied with depth in each location and included clay,
loam, clay loam, sandy loam and sandy clay loam. Generally, all the soil properties varied with
soil depth across the locations and land uses. Land use significantly (P = 0.05) affected pH in
, CEC, 0.50-1.00 mm water stable aggregates (WSA), total soil nitrogen (TSN) in
1.00-2.00 mm WSA, and soil organic carbon (SOC) in 1.00-2.00 mm and < 0.25 mm WSA.
Cultivation at 0-30 cm depth significantly reduced SOC in 1.00-2.00 mm WSA by 19.30 %, and
TSN in 1.00-2.00 mm WSA by 2.50 %. Land use effects on SOC in WSA at 0-30 cm depth of
the various locations followed no consistent trend, except that SOC was higher in cultivated than
in uncultivated soils of Nsukka II location. The SOC pool significantly decreased with soil depth.
The SOC pool at 0-10 cm, 10-20 cm, and 20-30 cm depths averaged 17.62, 16.40 and 13.05 Mg
respectively, in cultivated soils; and 19.59, 17.86 and 12.03 Mg C ha-1
uncultivated soils. The SOC pool to the depth of 30 cm differed distinctly amongst the study sites
in both land uses; however, cultivation had no significant effect on SOC pool. The effect due to
soil texture on SOC pool indicated that C sequestration was significantly greater in clay loam >
clay > sandy loam > loam > sandy clay loam. In all, SOC pool was most secluded at 10-20 cm
depth, and least at 20-30 cm depth. Whereas SOC pool significantly correlated with dispersion
ratio (DR), aggregated silt and clay (ASC), water dispersible clay (WDC), microporosity (Pmi),
0.50-1.00 mm WSA, mean weight diameter (MWD), soil pH, K+, and C/N ratio in cultivated
soils; it correlated significantly with ASC, Na+, and CEC in uncultivated soils. Apart from Pmi,
whose variability was largely due to the effect of SOC that significantly predicted up to 76 %,
SOC significantly accounted between 34 % and 54 % of the variability in MWD, WDC, and
WSA classes of > 2.00 mm, 1.00-2.00 mm and 1.00-0.50 mm of the cultivated soils.
The fundamental basis of carbon (C) sequestration and its effect on global climate change
and agriculture have become a major concern in recent years. Emissions of greenhouse gases
(water vapour, carbon dioxide (CO2), methane, and nitrous oxide) as a result of human activities
continue to alter the atmosphere in ways that are expected to affect change in climate.
Anthropogenic activities produce CO2, which is the primary greenhouse gas that contributes to
climate change to be released to the atmosphere at rates much faster than the earths natural
processes can cycle. To help alleviate or possibly reverse the trend, a variety of means of
enhancing natural sequestration processes are being explored. Increasing CO2 sink (C
sequestration) has been acknowledged and accepted as a major possible mitigation to these
effects. This is buttressed by the report of Rice and McVay (2002) indicating that through C
sequestration, atmospheric CO2 levels are reduced as soil organic carbon (SOC) levels are
Among the three natural sinks for C (ocean, forest and soil), soils contain more C than is
contained in vegetation and the atmosphere combined (Swift, 2001). The SOC pool which forms
the largest sink after sedimentary rocks and fossil deposits however is the most vulnerable to
disturbance (Schlamadinger and Marland, 2000) especially because of the competition between
the various types of land use. Six et al. (2000) reported that tillage operations promote the loss of
SOC through macroaggregate disruption and exposure of soil organic matter (SOM) to microbial
decomposition. Also, Blum (1997) indicated that the decomposition and alteration
(mineralization and metabolization) of organic compounds produces trace gases which can be
harmful to the global atmospheric cycle.
The impact of organic carbon (OC) losses in soils may have a variety of serious
environmental consequences. Lal (2004) reported that several depletion of SOC degrades soil
quality, reduces biomass productivity, and adversely impacts water quality. Lal et al. (1998)
observed that organic matter (OM) losses from soil worldwide contribute to increased
atmospheric CO2 concentration. Lugo and Brown (1993) indicated that the net losses of SOC due
to land use changes may occur as a result of decreased organic residue inputs and changes in
litter composition, and increased rates of soil organic decomposition and soil erosion. The
contribution of soil erosion to global C emission has also been recognized by Tans et al. (1990)
as equally important to that of deforestation and fossil fuel burning. Lal (1995) estimated that the
total SOC displaced by water erosion globally as 57 Pg yr-1
[Pg = Petagram. Where, 1 Pg = 1 Gt
(Gigaton) = 1015
g = 1 billion tons]. Houghton et al. (1996) predicted that CO2 emission to the
atmosphere would increase from 7.4 Gt C yr-1
in 1997 to approximately 26 Gt C yr-1
Furthermore, the annual CO2 flux from the soil to the atmosphere (68 Pg yr-1
) is 11.3 times the
emissions from fossil fuel combustions (6 Pg yr-1
) (Raich and Schlesinger, 1992). However, the
Inter-Government Panel on Climate Change (IPCC) recognised three main options for the
mitigation of atmospheric CO2 concentrations by the agricultural sector: (i) reduction of
agriculture-related emissions, (ii) creation and strengthening of C sinks in the soil, and (iii)
production of bio-fuels to replace fossil fuels (Batjes, 1998). Hence, the need to evaluate the role
of soil as one of the natural C sinks that secludes organic C as stable humus for enhancing soil
fertility and stability of soil microaggregates. Therefore, soil C pool and its dynamics play vital
role and the knowledge of their spatial distribution is important for understanding the pedosphere
in the global C cycle for the overall management of C. It is with this background that several
attempts have been made to access the potential of cropland (Lal et al., 1999; Lal and Bruce,
1999), grazing systems (Follet et al., 2000), and forest ecosystem (Birdsey et al., 1993) to
sequester C as possible strategies to curtail the rate of increase of atmospheric concentration of
Carbon sequestration refers to the removal of C, from the atmosphere through
photosynthesis and dissolution, and storage in soil as OM or secondary carbonates (Lal, 2001).
Through this process, C storage in soil is enhanced and its loss minimized, thereby reducing the
chances of global warming by the reduction of atmospheric concentration of CO2. Recognizing
the soil as one of the important potential sinks for C requires understanding of the processes that
influence C sequestration. Soil aggregation has been observed as an important process of C
sequestration and hence a useful strategy for mitigating increase in concentration of atmospheric
CO2 (Shrestha et al., 2007). Igwe et al. (2006) stressed the importance of the study of the role of
SOC in restoration of soil fertility and stability of soil microaggregates.
The impact of C sequestration on greenhouse gases and agricultural sustainability has not
been well elucidated at regional, national or global scales. Some available statistics are generally
based on extrapolation. Lal (2004) reported that the rates of SOC sequestration in agricultural
and restored ecosystems range from 0 to 150 kg C ha-1
in dry and warm regions, and 100-
1000 kg C ha-1
in humid and cool climates. He also estimated the total potential of C
sequestration in world soils as 0.4-1.2 Gt C yr-1
, all of which were derived from national resource
inventory. Improvement in the data base on the concentration of SOC needed to be validated with
ground truth measurement/assessment, as the use of reliable data is essential for developing
techniques of soil management and identifying policy options needed for promoting appropriate
measures. Despite several studies carried out on the quantification of soil sequestered C in
different geographical regions of the world (Cruz-Rodriguez, 2004; Denef et al., 2004; Lal et al.,
1998; Lal, 2001; Shrestha et al., 2007), there are limited knowledge about SOC pool dynamics in
the tropical humid agroecosystem of southeastern Nigeria. Quantification of SOC within
aggregate size classes permits evaluation of aggregation under different soil management
systems and its contribution to the accumulation and loss of OM (Sotomayor-Ramrez et al.,
2006). The relevance of this study is to generate reliable information which is essential for
developing techniques of soil/land management systems and for recommendation of agricultural
practices that promote C sequestration for sustainable agriculture leading to advancement in food
security and consequently, mitigate global warming. The hypothesis is that SOC sequestration is
a function of soil texture and soil aggregation; and that SOC is similar between soil phases
(cultivated and uncultivated) of the same soil series. Therefore, the main objective of the study
was to assess the potentials of various aggregate size fractions of varying soil textures and depths
to sequester C in cultivated and uncultivated soils. The specific objectives included to;
(i) Determine the soil physico-chemical properties of cultivated and uncultivated soils.
(ii) Quantify SOC and total soil nitrogen (TSN) stocks and assess their distribution across
aggregate size fractions as stratified by location, land-use, soil texture and soil depth.
(iii) Determine the effect of SOC and TSN on soil aggregation and other soil properties.
(iv) Understand the SOC pool dynamics among different soil textures and depths, and
between cultivated and uncultivated soils.
2.1 An Overview of Global Carbon
Understanding the concept of carbon (C) sequestration seems to be the most reasonable point
to start a lesson, but C sequestration which is an aspect of C management cannot be absolutely
understood and appreciated as one of the identified mitigation options against global warming
and climatic change, without a critical survey of global C as documented by most researchers.
Three main reservoirs regulate the C cycle on earth (IPCC, 1990): the oceans 39000 x
g (or Pg) of C; the atmosphere ( 750 Pg C), and terrestrial systems ( 2200 Pg C). The
fourth reservoir which is a permanent sink - the geological reservoir, is estimated at 65.5 x 106 Pg
(Kempe, 1979). Table 1 shows the principal global C pools comprising of oceanic, geologic,
pedological, atmospheric, and biotic. These pools are interconnected with sizeable fluxes among
them. For example, the atmospheric pool is increasing at the rate of 3.3 Gt C yr-1
. The oceanic
pool is absorbing about 92 Gt C yr-1
and emitting 90 Gt yr-1
, with a net gain of 2 Gt yr-1
biotic pool photosynthesizes 120 Gt C plant respiration and the remaining 60 Gt C yr-1
respiration (Lal et al., 2007). Although the soil-vegetation C pool is small compared with that of
the oceans, potentially it is much more labile in the short term (Batjes, 1996). On average, the
soil contains about 2.5 times more organic carbon (OC) than the vegetation ( 650 Pg C) and
about twice as much C as is present in the atmosphere ( 750 Pg C) (Batjes, 1998). The soil is the
largest terrestrial pool of OC, with global estimates ranging from 1115 to 2200 Pg C (Batjes,
1992), 1576 Pg C (Eswaran et al., 1995), 1400 Pg C (Falloon et al., 1998) and 1220 Pg C
(Sombroek et al., 1993). Estimates of global soil C content have also been made by several
researchers including, Kimble et al. (1990), Buringh (1984), Bohn (1982), Batjes (1998), Lal
(2002), Post et al.(1990), Johnson and Kerns (1991).
World soils or the pedological pool comprises two distinct components: soil organic carbon
(SOC) and soil inorganic carbon (SIC) pools estimated at 1576 Gt and 938 Gt respectively, at 1
m depth (Post et al., 1982; Schlesinger, 1995; Eswaran et al., 1993). The SOC pool is
concentrated in soils of arctic, boreal, and temperate regions which includes highly active humus
and relatively inert charcoal C, while the SIC pool includes elemental C and carbonate minerals,
such as calcite, dolomite, and gypsum and those of arid and semiarid climates (Schnitzer, 1991;
Stevenson, 1994; Lal et al., 2000; Wagner, 1981; Paul and Clark, 1996). Lal (2004) recognized
two types of carbonates in soils: primary or lithogenic carbonates and secondary or pedogenic
carbonates. Of the global SOC pool (2500 Gt), which includes about 1550 Gt of SOC
Table 1: Global carbon pool and fluxes among them
Pool Reservoir (Gt) Flux (Gt C yr-1
Oceanic 38000 90-92 months the atmospheric
Geologic 2500 7.4 to the atmospheric pool
Pedologic 250 60 months biotic and 1 month the oceanic
Atmospheric 760 120 months the biotic pool
Biotic 560 60 months the pedological pool
(Adapted from Lal et al., 2007)
and 950 Gt of SIC therefore, the total soil C including both SOC and SIC pools in the active soil
layer of 1 m depth constitutes about 23000 Pg (Lal, 2002b) which is 3.3 times the size of the
atmospheric pool (760 Gt) and 4.5 times the size of the biotic pool (560 Gt) (Lal, 2004). Table 2
shows the global mass of SOC in the upper 30 cm, 1 m, 2 m, and 3 m of soil. The SOC pool in
the top 1 m depth of world soils ranges between 1462 and 1600 Pg, which is nearly three times
that in the aboveground biomass and approximately double that in the atmosphere; 32 % (or 506
Pg) of this is contributed by soils in the tropics (Eswaran et al., 1993; Lal et al., 1995; Batjes
1996). According to Batjes (1996) total soil C pools for the entire land area of the world,
excluding carbon held in the litter layer and charcoal, amounts to 2157 to 2293 Pg of C in the
upper 100 cm. Owning to the problem of making accurate global estimates of C, Eswaran et al.
(1993) suggested that employing the coefficient of variation (CV) which is an expression of the
variability will aid in understanding and accepting the reliability of most generalization.
Lal et al. (2007) documented the estimates of global carbon pool up to 1 m depth of the
various USDA soil orders. Another study that provided global mean of SOC estimates in soils of
the tropics reported values of 8.3 for Ultisols, 9.7 for Oxisols, and 10.4 kg m-2
among other soil orders (Lal, 2002a). These differences between soil orders in the tropics are
mainly in relation to temperature, rainfall, soil texture and land use (Batjes, 2000). Similarly,
Kimble et al. (1990) reported SOC density of principal soil orders of the world, where among
others the mean SOC density is 9.7 kg m-2
with CV of 42 % for tropical Oxisols and 8.3 kg m-2
with CV of 70 % for tropical Ultisols. About 52 % of this C pool is held in the top 30 cm of the
soil profile, the layer most susceptible to land use changes and responsive to management
practices (Lal, 2002b).
2.2 Soil Organic Carbon Dynamics
Lal (2001) noted that the SOC pool which is a function of soil characteristics and climatic
factors is a highly variable and dynamic entity. It is variable over space because its density
differs widely among soils and ecoregions; and variable over time because it changes with
change in land use and management. Lal (2002b) observed that SOC pool is in a dynamic
equilibrium with its environment, with a balance of input and output at a steady state level. Thus,
the SOC pool represents a dynamic equilibrium of gains and losses (Fig. 1). Follett (2001)
pointed out that temporal variation in SOC level results from the balance between plant biomass
input and decomposition and OC losses via leaching, oxidative, and erosional processes.
Substrate quality is one of the main factors affecting decomposition and has been linked to the
relative abundance of specific compounds such as nitrogen, lignin (Melillo et al., 1982; Tian et
al., 1993), and phenolic acids (Martens, 2000). Lal (1999) hypothesized that lack of nutrients,
especially N, could explain the low C conversion efficiency. Knops and Tilman (2000) observed
Table 2: Global soil organic carbon pool
Reference 0-30 cm 0-1 m 0-2 m 0-3 m
--------------------------SOC pool (Pg) -------------------------
Batjes (1996) 684-724 1462-1548 2376-2456 -
Eswaran et al. (1993; 2000) - 1526-1555 - -
Jobbagy and Jackson (2000) - 1502 1993 2344
Batjes and Sombrock (1997) - 1200-1600 - -
that the rate of carbon accumulation in agricultural abandoned fields was controlled by the rate of
nitrogen accumulation, which in turn depended on atmospheric nitrogen deposition and
symbiotic nitrogen fixation by legumes. More so, the turnover time of organic matter (OM)
increases with depth in the soil, ranging from several years for litter to 15-40 years in the upper
10 cm and over 100 years below a depth of about 25 cm (Harrison et al., 1990; Lobo et al.,
1990). In soils of the tropics, particle size fractionation techniques have been used to characterize
relationships between SOC and aggregation at the macro and microaggregate scale (Feller et al.,
1996). The concept is that soil organic fractions associated with different sized particles differ in
structure and function, and therefore play different roles in SOC turnover (Christensen, 1992).
The SOC pool consists of a mixture of plant and animal residues at various stages of
decomposition, of substances synthesized microbiologically and/or chemically from the
breakdown products, and of the bodies of live microorganisms and soil animals and their
decomposing products (Schnitzer, 1991). The different C pools existing in the soils have been
described in terms of the different mean residence times, ranging from years (active fraction), to
decade to hundreds of years (passive), to thousands of years (stable) (Carter et al., 2002). The C
pools are relative concepts based on the rate of decomposition of particular constituents and are
more related to biological function than to particular soil chemical C constituents. For example,
the active fraction consists of live microorganisms (microbial biomass), microbial products, and
unprotected chemical constituents such as proteins and polysaccharides with a turnover time of a
few weeks or months. The slow fractions are more resistant to decomposition due to partial
physical and chemical protection with a longer turnover time (Theng et al., 1989). The passive
organic constituents include humic substances and other macromolecules that are intrinsically
resistant against microbial attack due to chemical recalcitrance, physical protection by adsorption
on mineral surfaces, or entrapment within soil aggregates (Gregorich et al., 1997). Lal (2001)
pointed out that formation of stable microaggregates in the subsoil takes C out of circulation by
encapsulating it (physical and chemical protection from microbial activity) and is thus
sequestered. The long-term stabilization of C in temperate and tropical soils is mediated by soil
biota (e.g. fungi, bacteria, roots and earthworms), soil structure (e.g. aggregation) and their
interactions, and is influenced by agricultural management (Six et al., 2002).
In most soils, C is organic and constituents approximately 57 % of the soil organic matter
(SOM) that includes a wide spectrum of organic compounds, from labile components, such as
relatively fresh plants material and microbial biomass, to refractory components such as charcoal,
which accumulates slowly over thousands of years (Trumbore, 1993). Piccolo (1996) indicated
that the process of turning agricultural soil into sink for OC sequestration would be complete if
the stored OM were transformed into stable and recalcitrant humic substances. Accordingly,
humified OC, humic acids and humin in particular, represent the most persistent pool for SOC
Fig. 1: Processes affecting soil organic carbon dynamics.
Arrows pointed upward indicate emissions of Co2 into the atmosphere (Adapted from Lal, 2004).
accumulation with mean residence time of several hundreds of years. Spaccini et al., (2002) is of
the view that hydrophobic protection provided by humified matter may substantially reduce
decomposition of labile organic compounds in soils, thus they reported that the higher the
hydrophobicity of a humic material, the larger the sequestration of OC in soil. Bayer et al.
(2000) reported that in southern Brazil, SOC associated with sand and silt fractions was less
humified than that associated with finer-sized fractions. Nevertheless, Oades et al. (1987) and Six
et al. (2000) demonstrated that the most humified or oldest fraction is associated with silt
particles. Most of the C losses following soil disturbance such as tillage originate from the active
and slow pools, which comprise the biologically defined SOM pools described as active (labile),
slow (partially labile), and passive (stable) (Jenkinson and Rayner, 1977; Jenkinson, 1990;
Duxbury and Nkambule, 1994). Biological separation of SOC empirically separates labile from
recalcitrant forms by allowing microbes to mineralise C under controlled conditions with the
most labile C mineralised first and recalcitrant C mineralised later.
Physical fractionation of the soil according to aggregate size has been used to study the
portioning of OC in the soil (Buyanovsky et al., 1994). Fractionation using physically based
models is possible because OC is protected within and between aggregates (Cambardella and
Elliot, 1992; Six et al., 2000; Snyder and Vazquez, 2004). In its simplest case, there is a free
light fraction (LF) of labile C between the aggregates and intra-aggregate particulate OM (iPOM)
within macroaggregates (Cambardella and Elliot, 1992; Six et al., 1998). The LF may be more
related to residue input rates and soil environmental conditions and the iPOM more related to
aggregate turnover, which is strongly affected by tillage management (Six et al., 1998).
Aggregate hierarchy levels of formation occur in which the intra-macroaggregate POM
(particulate organic matter) facilitates the binding of microaggregates into macroaggregates,
which in turn affects the variation in the accessibility of soil microorganisms to SOC that leads to
pools which differ in stability and dynamics. For example, in relatively undisrupted systems such
as no-tilled agricultural and native systems, the greatest C concentration is usually found in the
small macroaggregate size class (2502000 m), with C in this fraction being most affected by
cultivation (Beare et al., 1994; Cambardella and Elliott 1994). Furthermore, a greater proportion
of the SOC pool in large microaggregates implies greater C losses to the atmosphere if
macroaggregates are broken by soil management practices (Cruz-Rodrguez, 2004). The losses of
SOC are in turn associated with losses in the POM fraction and therefore the amount of
aggregation and aggregate turnover (Six et al., 1999).
2.3 Soil Organic Matter (SOM) and Total Soil Nitrogen (TSN) in Water-Stable
Much interest has been shown in the role of OM in the formation and stabilization of both
macro- and micro- aggregates. Organic matter influences soil structure and compactibility by
binding soil mineral particles, reducing aggregate wettability, and influencing the mechanical
strength of soil aggregates, which is the measure of coherence of inter-particle bonds
(Onweremadu et al., 2007). According to Hamza and Anderson (2005), OM retains soil water
thus helping soil to rebound against compaction. Maintaining an adequate amount of OM in the
soil stabilizes soil structure and makes it more resistant to degradation (Cochrane and Aylmore,
1994; Thomas et al., 1996), and decreases bulk density and soil strength (Sparovek et al., 1999;
Carter, 2002). The following mechanisms have been identified as the most common means by
which OM influences soil structure and compactibility: (a) binding soil mineral particles (Zhang,
1994), (b) reduction of aggregate wettability (Zhang and Hartge, 1992), and (c) influencing the
mechanical strength of soil aggregates, which is the measure of coherence of inter-particle bonds
(Quirk and Panabokke, 1962). In the research carried out in Northern Appalachian, Blanco-
Canqui et al. (2007) found that SOC concentration explained 48 % of the variability in aggregate
disintegration and 86 % in aggregate wetting.
Castro et al. (2002) recognized the important role OM plays in soil particle aggregation and
consequently, reported that part of the aggregate-size variation and aggregation indices in
tropical soils can be attributed to the variation in the OM content. They further observed that a
soil that is low in OC will be poorly aggregated since the weight and the content of OC in the >
2.00 mm size class is lower than the weight and the content of OC of other classes.
Microaggregates have a lower OM concentration than macroaggregates (Dormaar, 1983) and this
OM is less labile than that associated with macroaggregates (Elliott, 1986). Moreover, reductions
in aggregate stability after cultivation are most pronounced in soil macroaggregates, while the
stability of soil microaggregates remains unchanged (Tisdall and Oades 1982; Oades, 1984).
Nwadialo and Mbagwu (1991) reported that OC does not influence microaggregate stability
greatly when the values of SOC are low and do not reach critical limits. Christensen (1985)
observed that the OM contents of macroaggregates obtained by dry-sieving were closely related
to their clay and silt contents. The findings by Christensen (1985) and Christensen and Sorensen
(1985) showed that C and N are associated with finer soil particles, and these particles may vary
among different aggregate fractions. Pikul et al. (2007) reported a significant positive
relationship (r2 = 0.79) between WSA and fPOM/SOM. Mbagwu and Piccolo (1990) reported
that on some north central Italian soils, in terms of total content, C, N and P were preferentially
concentrated in the macroaggregates. Zibilske and Bradford (2007) reported that aggregation was
significantly greater at 0-5 cm depth with no-tillage (NT) and ridge tillage, especially in the >
4750 and 500-212 m size classes, where aggregate C and N contents were as much as 60 % and
> 100 % respectively, more C and N were retained in the > 4750 and 500-212 m size classes at
0-5 cm, and most C and N were detected in the > 4750 m size fraction at the 10-15 cm depth.
Shrestha et al. (2007) showed that macroaggregates in the surface layers of Nepal soil contained
14.9 to 24.8 and 5.5 to 20.7 g kg-1
SOC in cultivated and forest soils respectively, while
microaggregates contained 12.5 to 30.8 and 11.9 to 25.4 g kg-1
2.4 The Concept of Soil Organic Carbon Sequestration
A number of definitions of C sequestration have been proposed by many researchers.
Microsoft Encarta dictionary (2008) defined sequestration as the act of going into or being in
isolation. Dick et al. (1998) described sequestration as seclusion or temporarily setting aside of
something. Carbon sequestration therefore is the term describing processes that remove CO2
from the atmosphere (Wikipedia, 2007). It is defined as the removal of CO2 from the atmosphere
to the soil where it is secluded (stored) as part of the SOM (Dick et al., 1998). Jacinthe et al.
(2002) referred to it as a process of conversion of plant-derived carbonaceous compounds into
stable SOC pools in amounts in excess of soil respiration. According to Lal (2004), soil C
sequestration means increasing SOC and SIC stocks through judicious land use and
recommended management practices (RMPs). Lal (2001) defined C sequestration as the removal
of C, as CO2, from the atmosphere through photosynthesis and dissolution, and the storage of C
in soil as OM or secondary carbonates. The Department of Energy (DOE) (2006) referred C
sequestration as the provision of long-term storage of C in the terrestrial biosphere, underground,
or the oceans so that the buildup of CO2 (the principal greenhouse gases (GHG)) concentration in
the atmosphere will reduce or slow. In contrast to SOC sequestration, however, SIC sequestration
is the immobilization of C in the form of pedogenic (secondary) carbonates, and leaching of
carbonates and bicarbonates into the ground water (Lal et al., 2000). The SIC includes elemental
C and carbonate minerals of primary and secondary origin. Primary carbonates are derived from
the parent material and secondary carbonates are found through the reaction of atmospheric CO2
(Lal and Kimble, 2000). Lal et al. (2000) is of the view that SIC
sequestration may be the significant pathway of C sequestration in arid and semi-arid regions.
Soil C sequestration is one of the important mechanisms wherein C storage in soil is
enhanced and its loss minimized, thereby reducing the rate of increase of atmospheric
concentration of CO2. Consequently, C sequestration as SOC is based on the proportion of net
primary production (NPP) returned to the soil and the conversion of biomass into humus,
whereby NPP is the difference between gross primary production by the plant and the respiration
of the plant (Macyk and Richens, 2002). Soil organic carbon sequestration depends on factors
and processes that determine the net primary productivity and its addition to the soil body, and
those that affect SOM accretion and decomposition in the soil: where changes in SOC content
reflect the net result of C input (via plant litter) and C loss (via decomposition) Akala and Lal
(2000). According to Lal et al. (2007), C sequestration process may be naturally or
anthropogenic-driven; the natural process includes terrestrial sequestration in soil (humification
and formation of secondary carbonates) and trees (biomass production and storage in
aboveground and below ground components). However, soil sink capacity and permanence are
related to clay content and mineralogy, structural stability, landscape position, moisture and
temperature regimes, and ability to form and retain stable microaggregates (Lal, 2004). For
instance, both the rate and magnitude of SOC sequestration are more in heavy-textured than
light-textured soils, on poorly drained than well-drained landscapes, in cool than warm climates,
and in humid than dry ecoregions (Lal et al., 2007). Lal (2001) identified some of the processes
leading to SOC sequestration, which include humification (conversion of biomass into humus),
aggregation (formation of organomineral complexes as secondary particles), translocation of
biomass into subsoil by deep roots and bioturbation, and by SIC leaching into groundwater as
Furthermore, the rate and magnitude of soil C sequestration also depend on the nature of
tree species; nitrogen-fixing trees usually increase soil C pool by as much as 20-50 % more than
non-N-fixers (Boring et al., 1988; Johnson and Henderson, 1995). Gerding (1991) reported a
strong correlation between SOC pool in the surface layer (30 cm depth) and the N and Ca2+
content of soils under 20-yr-old Pinus radiate D. Mkip (1995) reported an appreciable
increase of C due to fertilization from 1900 kg ha-1
(14 %) to 5530 kg ha-1
(87 %). Carbon
sequestration in humus is strongly related to soil management practices and especially to soil-
conserving practices. And the practices that increase SOM include: leaving crop residues in the
field, choosing crop rotations that include high-residue plants, using optimal nutrient and water
management practices to grow healthy plants with large amounts of roots and residues, growing
cover crops, applying manure or compost, using low-or no-till systems, and mulching to help
conserve the soil. Accordingly, addition of manure enhances SOC pool and improves soil
physical fertility (Blair et al., 2006). In addition, SOC sequestration is also caused by those
management systems that add high amounts of biomass to the soil, cause minimal soil
disturbance, conserve soil and water, improve soil structure, enhance activity and species
diversity of soil fauna, and strengthen mechanisms of elemental cycling (Lal, 2004).
2.4.1 Importance of Carbon Sequestration
In southeastern Nigeria, as in most parts of the tropics characterized by low-input
agriculture, the rate of SOM losses due to high-mineralization rate and nutrient losses to soil
erosion and leaching losses is high (Igwe, 2000). However, SOC plays an important role in
enhancing crop production (Stevenson and Cole, 1999) and also, in sustainable use of
agricultural soils (Mulongoy and Merckx, 1993). Large areas of world soils are being degraded
(Oldeman, 1994), therefore, desertification control and restoration of degraded soils is an
important strategy to sequester C in the biosphere. Because SOM is made up of the residues of
plants and microorganisms which require many elements, sequestration of C requires other
nutrients (Lal et al., 2007). For example, Hines (1997) observed on a weight basis, that the C/N
ratio of SOM was 12/1, C/P was 50/1, and C/S was 70/1. Therefore, to sequester 1 t of C, 83 kg
of N, 20 kg of P, and 14 kg of S are required. Thus, increasing SOC pool of degraded soils
increases crop yields by improving soil quality through: (i) increasing available water capacity,
(ii) improving supply of nutrients, and (iii) enhancing soil structure and other physical properties.
Blair et al. (2006) observed a strong relationship between the SOC pool and soil physical
fertility. Lal (2006) reported that increase in SOC pool by 1 t ha-1
would lead to a total
increase in food grain production of 30-50 Mt yr-1
in the developing countries. Of the total
increase, 24-39 Mt yr-1
would occur in the tropics and subtropics, composed of 4-6 Mt yr-1
Africa, 6-10 Mt yr-1
in Latin America, and 14-23 Mt yr-1
in Asia. Therefore, the importance of
SOC sequestration in achieving global food security cannot be overemphasized. In addition to
improving the quantity of food, the attendant improvement in soil quality will also alleviate the
hidden hunger affecting billions of people. Lal et al. (2007) was of the view that an increase in
the SOC pool within the root zone by 1 t C ha-1
can enhance food production in developing
countries by 30-50 Mt yr-1
including 24-40 Mt yr-1
of cereal and legumes, and 6-10 Mt yr-1
roots and tubers.
Soil organic carbon sequestration also mitigates global warming (Lal et al., 1995; Post
and Kwon, 2000) by offsetting fossil fuel emissions. No doubt, atmospheric CO2 can be
transferred into long-lived pedological pools (Lal, 2005), and once SOC is sequestered, it
remains in the soil as long as restorative land use or RMPs are followed, and sequestration rates
can continue for 30 and up to 50 yrs (Lal, 2004). The common RMPs that lead to SOC
sequestration are mulch farming, conservation tillage, agroforestry and diverse cropping systems,
cover crops (Lal, 2004). Moreover, there is a large potential for C sequestration in biomass in
forest plantations, short rotation woody perennials, and so on (Lal et al., 2007).
There are numerous benefits of sequestering SOC in soil, besides the potential of
mitigating the greenhouse effect (Rosenberg and Izaurralde, 2000). Land stewardship (Lord and
Lord, 1950) is a major benefit, because increase in SOC content enhances soil quality and
sustainability. Increase in soil quality, due to improvement in SOC content, enhances crop yield
and productivity. Lal (2002b) documented the importance of soil C sequestration in improvement
of soil quality, improvement of quality of natural water, air quality, and in reduction of silt load
and sedimentation. In their study in Thialand, Petchawee and Chaitep (1995) observed a linear
relationship between SOC and grain yield of maize (Zea mays L.). Improvements in soil
structure, in terms of both the degree and the stability of aggregation, led to a decrease in the soil
erodibility and a reduction in the risks of non-point-source pollution. The benefits in
improvements of water quality were also due to increases in soil buffering, detoxification and
biodegradation of pollutants, and increases in the retention capacity of soil to absorb ions on the
2.5 Influence of Soil Carbon and Total Nitrogen on Soil Properties
Soil organic matter is a complex mixture of organic compounds with different turnover
times (Christensen, 2001) and contains 50 to 58 % C (Nelson and Sommers, 1982). Different
pools of SOM have been conceptualized for modeling SOC dynamics (Skjemstad et al., 1998).
Particulate organic matter (Cambardella and Elliott, 1992) is an uncomplexed fraction of SOM
composed of particulate (> 0.05 mm), partially decomposed plant and animal residues, fungal
hyphae, spores, root fragments, and seeds. This fraction provides a substrate for microbial
activity and is an important agent in the formation of macroaggregates. It is a fraction that lies
intermediate between litter (fast turnover) and mineral-associated SOM (slow turnover). Soil
organic matter mediates many chemical and physical soil properties (Carter, 2002). Indirectly,
SOC and TSN affect several physical, chemical and biological processes (Bauer and Black,
1994). In the highly weathered Ultisols and Oxisols, OM is a major determinant of soil CEC, and
its reduction leads to a decrease in the nutrient and water retention capability, and lowers soil
fertility (Sotomayor-Ramrez et al., 2006). The SOM stored in the top soil contributes most
actively to nutrient cycling in the soil-water-plant system and to gaseous exchanges with the
atmosphere, but the subsoil can also be important (Nepstad et al., 1991; Davidson et al., 1993).
Depletion of SOM reduces soil fertility and degrades soil physical properties such as infiltration
rate, soil structure, and water-holding capacities (Houghton et al., 1983). Experiments have
shown that the plant available water capacity increases by 1 to 10 g for every 1 g increase in
SOM concentration (Emerson, 1995). The increase is small and usually happens only in medium-
textured soils, but is critical to sustaining crop growth between rainless periods of 5 to 15 days.
Boyle et al. (1989) reviewed the influence of SOM on soil aggregation and water infiltration and
concluded that SOM had a disproportionate effect on soil physical properties. The quantity and
quality of SOM affects WSA (Tisdall and Oades, 1982). Soils high in SOM generally have
greater available water-holding capacity than soils of similar texture with less SOM (Hudson,
1994); although Bauer and Black (1992) found that a decline in SOM did not change the
available water-holding capacity of moderately coarse-textured soils. An increase in phytomass
input to a loamy sand improved aggregate stability and water infiltration (Bruce et al., 1992).
Maintenance of SOM therefore, is a key component in sustainability of the soil resource and crop
productivity (Doran et al., 1998).
Saggar et al. (2001) found that percentage C loss differed with soil type, with Marton silt
loam (260 g kg-1
, clay) soil losing one and half times as much percentage C as Kairanga silty clay
loam (420 g kg-1
, clay) soil. Soil C accounted for about 70 to 90 % of the variability in soil
aggregate stability of a clay loam soil (Mbagwu and Bazzoffi, 1989). In long-term tillage, residue
management, and N-fertility plots, Pikul and Zuzel (1994) reported that an increase in SOM
increased the porosity of surface crusts in a silt loam soil, while on a Naff silt loam, Mulla et al.
(1992) were not able to establish a relation between SOM and physical properties of conventional
and alternatively managed farms. The alternative farm studied by Mulla et al. (1992) used a
cropping system that was more diverse than the conventional farm; however, tillage was used
on both farms.
Depletion of SOC concentration leads to reduction in aggregation, and soil structure with
attendant susceptibility to crusting, hard-setting, compaction, accelerated erosion, anaerobiosis,
drought and salt imbalance (Lal, 1991; Paustian et al., 1997; Grace et al., 1998). Generally, soil
compaction decreases with increasing SOM (Soane, 1990; Hudson, 1994). Lal (2002b) remarked
that SOC affects soil physical quality through change in soil structure, aggregation, total- and
macroporosity, susceptibility to crusting and compaction, and ease of root system development.
Degens (1997) provided a review on the function of labile organic bonding and binding agents
related to soil aggregation. Labile compounds, in the context used by Degens (1997), were
considered to be components of SOM that were readily decomposable and recently deposited by
roots and microorganisms.
2.6 Effects of Land Use Management on Soil Carbon and Nitrogen
Soils respond differently to management depending on the inherent properties of the soil
and the surrounding landscape (Andrews et al., 2006). Management choices affect the amount of
SOM, soil structure, soil depth, and water- and nutrient-holding capacities (Lal et al., 2007).
Under undisturbed natural conditions, the soil C pool is in equilibrium and the input of C (litter
fall, root biomass, C brought in by run-off, dust) is balanced by output (erosion, decomposition,
and leaching) (Lal, 2004). The reduction in C input is caused by a decline in biomass production
and reduction in the fraction returned to the soil. The increase in C output is attributed to increase
in oxidation of SOM because of change in soil moisture and temperature regimes, and increase in
losses caused by soil erosion and leaching (Lal et al., 2007). Conversion of natural ecosystems to
agriculture leads to depletion of SOC through increase in decomposition and mineralization of
biomass caused by aeration, erosion and preferential removal of SOC by erosional processes
(Lal, 1984, 1989; Tisdall, 1996), which typically reduces the amount of C input and increases the
magnitude of output. These C and N losses are caused by decreased plant OM inputs and by
increased decomposition and erosion associated with agriculture. Decomposition increases
because of a change in aggregate structure of the soil due to cultivation (Coote and Ramsey,
Anthropogenic disturbance of terrestrial biosphere can deplete the SOC pool (Schlesinger,
1993). Emission of CO2 from soil-related processes began with the onset of settled agriculture
about 10,000 years ago, and that of CH4 with the cultivation of rice paddies and domestication of
animals about 5000 years ago (Ruddiman, 2003, 2005). Tropical deforestation continues to be a
major source of CO2 (Wallace, 2007). Soil tillage, extractive farming practices, and accelerated
soil erosion cause a rapid depletion of the SOC pool (Lal et al., 2007). Many cultivated soils have
lost 50 to 75 % of their antecedent SOC pool (Lal, 2004). According to Knops and Tilman (2000)
on the average, agricultural practices resulted in a 75 % loss of soil N and an 89 % loss of soil C
at the time of abandonment, whereas recovery to 95 % of the preagricultural levels is predicted to
require 180 yr for N and 230 yr for C. Other studies suggest that losses of SOM caused by
agricultural practices range from 16-77 % (Mann, 1986), with a mean of 29 % (Schlesinger,
1986). Estimates of the historic loss of SOC pool from world soils vary widely. The loss of C
pool from world soils was estimated at 40 Gt by Houghton (1995), 55 Gt by IPCC (1995) and
Schimel (1995), and 150 Gt by Bohn (1978). The rate of C loss from world soils caused by
current land use change and soil cultivation is also variable and estimated at 0.6 to 2.6 Gt yr-1
Lashof and Hare (1999) and 1 to 2 Gt yr-1
by Bohn (1978).
Agricultural practices can cause the loss of a large fraction of SOM (Mann, 1986;
Schlesinger, 1986). Losses are influenced by soil texture with higher losses on sandy soils (Bauer
and Black, 1981; Campbell and Souster, 1982). Coote and Ramsey (1983) and Nichols (1984)
obtained a positive relationship between percentage clay and SOM. It is generally agreed that
cultivation causes a decrease of SOC content (Alvarez et al., 1998). Ellert and Gregorich (1996)
estimated that 30 to 35 % of SOC originally present in the A and B horizons of the native
temperate forest soils was lost after cultivation for 30 yr or more. In the study of the effect of
cultivation on SOC, and soil structure in soils of contrasting mineralogy, Shepherd et al. (2001)
found that soil susceptibility to structural degradation increased with years of cultivation, and
from light textured to heavier textured soils. Cultivation generally results in reduced stability and
amount of macroaggregates but does not affect microaggregate stability (Tisdall and Oades,
1982). Therefore, the SOM that binds microaggregates into macroaggregates has been suggested
to be the primary source of OM lost upon cultivation (Elliott, 1986). When soils under pasture
are brought into cultivation there is a rapid loss of OM during the first few years, reflecting, in
part, exposure of more surfaces due to soil disturbance and dry matter removed during harvesting
(Sparling et al., 1992; Shepherd et al., 2001). Farage et al. (2003) found that stocks of soil C in
Nigeria were 8-23 t ha-1
before cultivation, 6-12 t ha-1
after cultivation, and 0.05-0.01 t ha-1
with effect of conventional tillage (CT) practices.
The SOC content in cropland is strongly correlated to crop and soil management practices
which include crop species and rotation, tillage methods, fertilizer rate, manure application,
pesticide use, irrigation and drainage, and soil and water conservation (NRC, 1989; Paustian et
al., 1997). Tillage and especially bare soil conditions are the most important management
practices leading to the depletion of SOM and SOC (Lal et al., 2007). No tillage has been
proposed as an alternative to conventional cropping systems for reducing soil degradation. It
generally leads to an increase of C in the top 5-10 cm of the profile, relative to plow layer (Kern
and Johnson, 1993). Generally, organic C and N concentrations in the surface 15 cm of non-tilled
soils is greater than for tilled soils (Doran, 1980). Conversion of plow tillage to NT can increase
SOC pool by up to 10 Mg ha-1
during 5-20 yr (Paustian et al., 1997). However, CT inverts the
OM; consequently, the distribution is more uniform throughout the plow layer than in a no-till
system (Fox and Bandel, 1986). Hulugalle (2000) showed that minimum tillage decreased SOC
content in Vertisols in New South Wales, Australia. Method of tillage also influence the degree
of change in OM, [moldboard plowed tillage decreases OM more than stubble mulch tillage
which decreases it more than NT (Lamb et al., 1985)], soil texture [coarse and fine textured soils
are likely to show greater changes than medium textured soils (Bauer and Black, 1981)] and
weather conditions [(drought results in less crop residues and more soil erosion and may decrease
OM (Campbell et al., 1995)]. Denef et al. (2004) showed that total SOC as well as
microaggregate-associated C (mM-C) was greater with NT compared with CT. No tillage
increased fine particulate organic matter (fPOM)/SOM by 19 and 37 % compared with tillage
following 4 and 10 yr of NT, respectively. A 5 year diverse rotation increased fPOM/SOM by 36
% compared with monoculture. Pikul et al., (2007) demonstrated that diversity of rotation or
reduction of tillage increased fPOM and WSA and this may help to curb soil loss by maintaining
surface conditions resistant to erosion.
Adoption of RMPs has great potential for increasing the amount of C sequestered (Cole et
al., 1993; Lal et al., 1997; 1999). Whilst Watson et al. (1996) estimated that 0.4-0.8 Pg C yr-1
could be sequestered in agricultural soils globally by implementation of appropriate management
practices. Lal et al. (1995) estimated that with improved land use, cultivated and (resilient)
degraded soils can sequester 0.1-1.0 Pg C yr-1
, depending on management. Pacala and Socolow
(2004) estimated that conversion of all cropland to no-till has a potential C sink capacity of 1 Gt
. Lal (1986) pointed out that land use practices and cropping systems that do not return
residue to the soil can cause a significant decline in SOC concentration. Cropping systems to
increase SOC include the use of rotations, planting winter cover crops, and placing land into the
conservation reserve program (CRP) (Six et al., 2004). Carbon sequestering practices to enhance
SOC sequestration on cropland include improved use of crop residues; increased use of CT
(especially NT), crop residue, and other biomass management approaches; reduction of fallow;
use of organic materials and systems that enhance belowground root biomass including that from
weeds (Follett, 2001). However, Six et al. (1999) found that the greater C stabilization with NT
relative to CT is only partly explained by a greater amount of macroaggregates. Furthermore, a
reduced rate of macroaggregate turnover under NT increases the formation of microaggregates in
which C is stabilized and sequestered in the long term. Particulate organic matter is a labile
intermediate in the SOM continuum from fresh organic materials to humified SOM (Paul et al.,
2001), and is more sensitive to changes in management than total SOM (Cambardella and Elliott,
1992 and 1993; Cambardella et al., 2001). Gale et al. (2000) reported that under NT practices,
aggregate formation was directly related to root-residue decomposition and POM dynamics,
while in undisturbed soils, POM is derived primarily from roots since new microaggregates
probably form around decomposing pieces of root-derived POM inside macroaggregates. An
aggregate life cycle was proposed by Six et al. (2000) in which aggregates form and stabilize
around fPOM encrusted with microbial products, and eventually destabilize due to a cessation of
microbial activity. Six et al. (2004) identified five factors (soil fauna, microorganisms, roots,
inorganic soil components, and physical processes) that are important in the link between soil
biotic activity, SOM decomposition and stabilization, and soil aggregate dynamics. Several
reports have shown that crop residue mulch associated with NT management improves soil
aggregation and increases SOC content (Havlin et al., 1990; Carter, 1992; Cambardella and
Elliot, 1992; 1993). However, this increase is generally restricted to the surface soil (S et al.,
2001). In tropical zones, Bayer et al. (2000); Resck (1998); and S (1993) observed a significant
impact on SOC concentrations for 0-10 cm layer. Unger (1991) and Christensen et al. (1994)
demonstrated that distribution of SOC and plant nutrients changed with no-till management. No-
till resulted in increased SOC concentration near the surface even when comparing no-till with
stubble-mulch tillage, which does not invert the soil. However, tillage mixes SOC in the surface
layers, which alters the distribution and may increase decomposition (Potter et al., 1997). Other
soil management practices such as application of N fertilizer and animal manure also increased
SOC content (Paustian et al., 1997), and Potter et al. (1997) found that fallow limited C
accumulation in a dryland cropping system. Findings documenting the effectiveness of land use
and soil management practices for SOC sequestration in relation to soil and ecoregional
characteristics abound in literature (Lal et al., 1998; Batjes, 1999; IPCC, 2000; Lal, 2000).
2.7 Factors Affecting Soil Organic Carbon (SOC) and Total Soil Nitrogen (TSN) Pool in
The tropics cover 8.2 billion hectares or approximately 40 % of the world land area and are
relatively characterized by high risk of soil and environmental degradation because of harsh
climate and resource-poor farmers, and rapid decomposition of SOM because of continuously
high temperature (Lal, 2002a). The soil pool is highly reactive and dynamic, and the cultivation
of virgin soils or conversion of natural to agricultural ecosystems leads to depletion of the soil C
pool with attendant emission of GHGs into the atmosphere (Lal, 2002b). Agricultural practices
can render a soil either a sink or a source of atmospheric CO2, with direct influence on the
greenhouse effect (Lugo and Brown, 1993; Lal et al., 1995). Although cultivation of agricultural
soils is not as obvious a source of GHGs as is direct fossil fuel combustion, however, soil misuse
can lead to emissions of GHGs from soil to the atmosphere (Lal, 1999). It has been recognized
that the CO2 contribution to radiative forcing is about 50 %, and 22.9 % of total CO2 emissions to
the atmosphere is attributed to agriculture, deforestation, and land use (IPCC, 1996). The
cumulative historic loss of C by cultivation since the dawn of settled agriculture is enormous
(Lal, 2000). Total CO2-C emitted by anthropogenic activities between 1850 and 2000 is
estimated at 270 30 Gt by fossil fuel combustion and 136 55 Gt by land use change and
deforestation (IPCC, 1999; 2001). In fact, until 1970, more C came from soil cultivation and
deforestation than fossil fuel combustion (Lal, 2002b). During the 1990s, about 25 % of global
emissions came from land-use change and soil cultivation (IPCC, 1996). From 1850 to 1998, 270
30 Pg C were emitted from fossil fuel combustion and cement production (Marland et al.,
1999). During the same period, net cumulative CO2 emissions from land use change were
estimated to have been 136 55 Pg (Houghton, 1997, 1999; Houghton et al., 1999, 2000). The
emission from soil cultivation is estimated at 78 17 Pg C (Lal, 1999). Therefore, conversion to
restorative land uses (e.g. afforestation, improved pastures) and adoption of RMP can enhance
SOC and improve soil quality. Important RMP for enhancing SOC include CT, mulch farming,
cover crops, and integrated nutrient management including use of manure and compost, and
agroforestry (Lal et al., 2007). In agricultural land, techniques such as decreased tillage and
efficient use of fertilizers and irrigation have been proposed as ways to increase SOC and
decrease atmospheric CO2 (Lal et al., 1998; IPCC 2000).
It has been ascertained that the C balance of the terrestrial ecosystems can be altered
remarkably by the direct impact of human activities including deforestation, biomass burning,
land use change, and environmental pollution which release trace gases that enhance the
greenhouse effect (IPCC, 1990; Trabalka and Reichle, 1986). Six et al. (1999) stated that SOC
and SON pools may be influenced by the magnitude and quality of C inputs, disruption of
aggregates, or microclimatic changes within a relatively small area. More so, a drastic loss of
SOC during mining has been recognized by Akala and Lal (2000), and it is thus conceivable that
reclamation of mine lands can lead to recuperation and sequestration of SOC. Besides climatic
factors, the following activities that influence pools and fluxes of C are widely recognized:
1. Deforestation: Conversion of natural to agricultural ecosystems causes depletion of the SOC
pool by 75 % or more in cultivated soils of the tropics (Lal, 2004). The estimated rate of SOC
loss is 90-219 Tg C yr-1
(Tg = teragram = 1 x 1012
g) because of tropical deforestation (Lal and
Logan, 1995). In Malaysia, Andriesse and Schelhaas (1987) reported 28 Mg C ha-1
depletion of SOC pool by deforestation. Motavalli et al. (2000) showed that conversions of
secondary forest to continuous cultivation can decrease the SOM carbon by 44 % within 5 years
after cultivation. Lal and Kimble (2000) indicated that deforestation of the tropical rainforest
(TRF) accounts for about 15 % of the total global warming potential, comprising 10 % due to
CO2 and 5 % due to other trace gases (e.g., N2O, CH4 and NO), whereby estimates of CO2
release range from 400 to 2500 Tg C yr-1
. Because deforestation accounts for 20 % of the total
global GHG emissions (more than all the worlds cars, trucks, trains and airplanes combined),
world bank announced setting up a new fund (US$300 million) to subsidize developing countries
to protect and replant tropical forests for carbon sequestration (ECOS, 2008). Extensive
deforestation and intensive agricultural management have led to an increasing transfer of C from
SOM to atmospheric CO2 (Schlesinger, 1997). However, afforestation of agricultural land has
been shown by several researchers to sequester SOC in soil (Lugo and Sanchez, 1986; Johnson,
1992; Huntington, 1995; Ellert and Gregorich, 1996; Post and Kwon, 2000). Schlesinger (1999)
is of the view that a substantial sink for C in soils may derive from the application of
conservation tillage and the regrowth of native vegetation on abandoned agricultural land.
2. Fire: Lal and Kimble (2000) observed that fire has been used as a principal tool in removing
the biomass in both tropical rainforest (TRF) and tropical savanna (TS) ecosystems, which leads
to emissions of several radiatively-active gases, viz. CO2, CH4, N2O, NOx etc. Accordingly,
biomass burning in all tropical regions may account for an annual release of about 3.4 Pg of C.
Lal and Logan (1995) estimated an annual SOC loss of 112-276 Tg C yr-1
by burning of
grasslands. Both the direct effects of fire and also the overall changes to the ecosystem
encountered in a post-fire situation can lead to short-, medium- and long-term changes in the soil
which relate to soil functioning in the physical, biological and chemical sense (Chandler et al.,
1983; Neary et al., 1999; Gonzlez-Prez et al., 2004). Doerr and Cerd (2005) indicated that fire
affects the entire ecosystems their flora, fauna, the atmosphere and soil. Consequently, burning
and resulting post-fire environmental conditions can alter the functioning of soils physically (e.g.
aggregate stability, pore size, distribution, water repellency and runoff response), chemically
(e.g. nutrient availability, mineralogy, pH and C/N ratios) and biologically (e.g. biomass
productivity, microbial composition and carbon sequestration). More so, the effect of fire
decreasing the ability of soil to recover and lowering soil resilience has been recognized (Lal,
1998). However, the effects of a fire on soil characteristics will depend on the fire intensity, soil
properties and type of vegetation. On the one hand the enrichment of available nutrients in
burned soils may lead to an increase in nutrient content in the recovering plant cover, thus
enhancing primary productivity (Carter and Foster, 2004). The fire-induced increase in soil
nutrient content may also positively influence decomposition rates and nutrient cycling (De
Marco et al., 2004). On the other hand, a fire of high intensity may cause changes in soil
properties that accelerate erosion and nutrient losses (Neary et al., 1999; Thomas et al., 1999;
Gonzlez-Prez et al., 2004). For example, the complete destruction of the organic layer severely
limits soil functions, reducing infiltration and water storage (Imeson et al., 1992; Giovannini and
Lucchesi, 1997). In addition, the destruction of the vegetation cover leaves the soil exposed to
raindrop impact and water erosion. Fire, directly and indirectly, affects microorganisms
inhabiting soil surface layers. The functioning of the soil microbial community is central to
sustaining ecosystem-level processes such as decomposition of OM and nutrient cycling, which
are essential in the maintenance of soil fertility (De Marco et al., 2005). The heat generated in the
soil during a fire may kill a large or a small part of the soil microbial biomass, depending on
length of exposure to high temperatures (Neary et al., 1999).
3. Land use change and management: Cambardella and Elliot (1993, 1994) demonstrated that
land use and management practices can alter the distribution of organic C and N among labile
and stable pools with kinetically different turnover rates. For example, intensive cultivation of
grassland reduces the SOC and SON because of the destruction of soil macroaggregates by
different levels of tillage (Cambardella and Elliot, 1993). Lal and Kimble (2000) remarked that
biomass production which is an important determinant of C pool and fluxes depends on land use
and management. Consequently, conversion of natural (TRF and TS) ecosystems to agricultural
land use (plantation, pastoral and cropland) has a drastic impact on C pool and emissions of
GHGs to the atmosphere. Tillage also results in partial aggregate destruction and concomitant
OM loss (Six et al., 1999; Wright and Hons, 2005). Furthermore, a general increase in C levels
( 325 113 kg C ha-1
) was observed under NT compared with CT in tropical and temperate
soils (Six et al., 2002). However, adoption of CT practices could result in lower costs and in
improved soil quality by decreasing SOC losses (Sotomayor-Ramrez et al., 2006). Estimates of
historic SOC loss included 3.8-9.2 Tg C yr-1
by shifting cultivation and 38-92 Tg C yr-1
plowing of cropland (Lal and Logan, 1995). The rate of depletion of SOC pool was 27-38 Mg C
by shifting cultivation in eastern Africa (Woomer et al., 1994); in Australia, Dalal and
Mayer (1986) and Chan (1997) reported a decrease of 19-67 % of SOC concentration in the 0-10
cm depth by cultivation over 20-70 yrs.
Applications of agricultural input such as fertilizer also affect SOC pool. It is still observed
that addition of manure enhances SOC (Blair et al., 2006). Farage et al. (2003) reported that
additions of green manure (10 t ha-1
) or farmyard manure (1.5 t ha-1
each cropping year) to
the no-till system, lead to increases in C sequestration (0.029-0.034 t C ha-1
). On the other
hand, additions of farmyard manure and green manure both lead to marked increases in C
sequestration rates in the region of 0.18-0.25 t C ha-1
; therefore replacing inorganic fertilizer
with farmyard manure promotes C sequestration (0.22 t ha-1
) while combining the green
manure and farmyard manure applications gave the best C accrual rate, 0.29 t ha-1
Mara river valley, Catamarca province of Argentina. More so, soil C (0.1 t C ha-1
) was lost
when only inorganic fertilizers were used to maintain soil fertility in the intense systems of the
Kano closed-settlement zone in Nigeria. Replacing the manure input to this system with
inorganic fertilizer (urea 100 kg ha-1
) resulted in a large reduction in soil C, with stocks falling by
> 0.1 t C ha-1
. It was thus conclusively noted that maintaining crop yields through the
application of inorganic fertilizers alone will most likely result in substantial losses of SOM.
4. Soil factors and processes: Batjes (1998) showed that moisture status, soil temperature, O2
supply (drainage), soil acidity, soil nutrient supply, clay content and mineralogy are the major
environmental factors which control the behaviour of OM in the soil. Lal et al. (2007) reported
that change in soil moisture and temperature regimes affects oxidation of SOM. Batjes (1998)
also remarked that the soil forming factors, notably climate as well local biological activity in
which humans are often a predominating factor, control the amount of SOM that corresponds
with equilibrium conditions in a certain natural ecosystem or agro-ecosystem. Different factors
influence different SOC pools. Free OM particles and microbial biomass in soils are controlled
by residue inputs (management of crop residue and mulching) and climate, for example, the
microbial populations and activities in pasture tends to be higher compared to the corresponding
agricultural soils due to the positive imparts of the surface cover, vegetation, belowground C
allocation via roots, and lack of tillage of pasture (Acosta-Martnez et al., 2004). More so, soil
aggregation, texture and mineralogy control OM in macroaggregates. The other pools are less
influenced by agronomic factors but mainly by pedological factors - micro-aggregates, clay
composition (Feller and Beare, 1997). Furthermore, the turnover and cycling of SOC is more
rapid in the tropics than in temperate regions (Trumbore et al., 1995). Six et al. (2002) found on
the average that soil C turnover was twice as fast in tropical compared with temperate regions -
one possible reason being the continuous inputs of fresh OM in tropical soil; but no major
differences were observed in SOM quality between the two regions.
Lal and Kimble (2000) pointed out that the important soil processes influencing C pool and
dynamic include soil nutrient reserves and cycling, and soil aggregation and C sequestration.
Carbon sequestration by natural TRF was attributed to (i) CO2 fertilization effect, (ii) tree
mortality due to catastrophic events, and (iii) effect of El Nio in exacerbating tree mortality.
Other factors that have been classified as immediate causes of a decline in SOC include residue
removal, soil erosion, intensive tillage, and bare fallowing (Lal and Kimble, 2000; Paustina et al.,
2000). The various important soil factors affecting the SOC pool have been widely documented
and include texture, clay minerals, soil fertility, and plant available water capacity of the root
zone (Lal, 2001). It is generally agreed that the SOC pool increases with increase in clay content;
for the same clay content, however, soils with high activity clay have more SOC content than
those with low activity clay.
5. Landscape position: Novel understanding of the nature of the environment indicates that the
exogenous factors of climate, landscape, texture, and clay mineralogy which cannot be readily
altered are among important determinants of soil and biomass C pool (Lal, 2001). The SOC
content also depends on landscape position due to soil erosion and leaching, which are
predominant on sloping landscape. The effects of cropland management practices and landscape
position on SOC pool depend on climate, soil type and landscape morphology, and are thus site
specific (Hao et al., 2002). Increasing water content and soil deposition at lower slope position
affect SOC decomposition and crop biomass production where the SOC content would often be
higher (Pennock et al., 1994; Fahnestock et al., 1995; Gregorich et al., 1998). Hall (1983)
reported that steeper slopes contribute to greater runoff, as well as greater translocation of surface
materials downslope through surface erosion and downhill movement of soil mass.
6. Soil erosion: Decrease in the SOC pools may be caused by three often simultaneous
processes: mineralization, transport by soil erosion processes, and leaching into the ground water
or subsoil (Lal, 2000). Mokma and Sietz (1992) reported a significant reduction in SOC
concentration of the surface layer as a result of erosion on a cultivated soil. The rate of SOC
depletion by erosion was reported to be 0.4 Mg C ha-1
in Nigeria (Lal, 1976), and 0.5-1.1 Mg
in Zimbabwe (Tagwira, 1992). Lal (2001) indicated that the removal of SOC pool by
soil erosion may constitute half of the total loss of SOC pool from agricultural soils, the other
half being due to an increase in mineralization caused by climatic conditions (change in soil
temperature and moisture regimes) and properties of SOC. Accordingly, the increased loss of
SOC by accelerated erosion due to water or wind occurs because it is concentrated in the surface
area, has low density (1.2-1.5 Mg m-3
for OM compared with 2.6-2.7 Mg m-3
fraction) and the labile particulate fraction is relatively unconsolidated. Thus, soils under
agricultural crops or forest cover conserve C in greater magnitude than eroded areas (Lal, 2002b).
In conclusion therefore, three main factors namely climatic factors, soil factors
physical, chemical, biological and processes therein, and agronomic factors (land use and
management) could be responsible for losses of SOC and SON in the tropics.
MATERIALS AND METHODS
3.1 Site Description
In this research study, soils from four different locations within two agro-ecological zones
(derived savanna and secondary forest) in southeastern Nigeria were considered. Within each
sampling location, soils of similar textures were collected from both cultivated and uncultivated
soils at 0-10, 10-20, and 20-30 cm depths. The study locations included University of Nigeria
Nsukka Research Farm beside the meteorological station designated as Nsukka I (Nkpologu
series soil), and Uvuru series soil at the hills behind Miriam Babangida Auditorium designated as
Nsukka II, both in Nsukka Local Government Area of Enugu state; Awgu in Awgu Local
Government Area of Enugu state; and Ugwaku in Okigwe Local Government Area of Imo state.
Nsukka I and II are located between latitudes 6o30 and 6
o41N, and longitudes 7
7oI4E and is 400 m above sea level. On the other hand, Awgu and Ugwaku are located between
latitudes 5o43 and 6
o04N, and longitudes 7
o21 and 7
o28E. The climate is characterized by
tropical wet and dry seasons with most of the rains falling between April and October at very
high intensity, followed by the dry seasons which last from November to March (Igwe and
Okebalama, 2006). The mean annual rainfall is about 1500-1600 mm, and the relative humidity
of 70 % prevails in the study area. Temperature is uniformly high throughout the year with mean
minimum and maximum values of 26 oC and 31
The vegetation of Nsukka location is mainly derived savanna of which 60-70 % of the
vegetation is covered with grasses (Igbozurike, 1975), while that of Awgu and Okigwe fall
within the secondary forest of the humid tropics. The predominant tree species in these four
locations are oil palm (Elaeis guineensis), sweet orange (Citrus sinensis), mango (Mangifera
indica), cashew (Anacardium occidentale) and oil bean (Pentaclethra macrophllum). The major
grass species are guinea grass (Panicum maximum), elephant grass (Pennisetum purpureum),
Calapogonium species, Andropogon species, Chromolena odorantum.
Agriculture is the predominant occupation of the indigenous land owners, who are mostly
operating at the subsistence level. The common arable crops grown are cassava (Manihot
esculenta), maize (Zea mays), yam (Dioscorea species), cocoyam (Colocasia specie), local beans
(Phaseolus species), vegetables including telfairia, garden egg (Solanum species), Amaranthus
species, and plantation crops such as plantain (Musa paradisiaca), banana (Musa sapientum), and
oil palm (Elaeis guineensis).
Soils of Nsukka I and II originated from similar parent material mainly weathered
Sandstone (Ajali formation), and were classified in the early 1960s during a soil survey of the
Anambra Do River valley areas, as Nkpologu series and Uvuru series, respectively (Jungerius,
1964). The soils are deep, permeable and well-drained. The underlying geology of Awgu and
Okigwe soils is mainly Shale. The topography of the four locations is of hilly terrain.
This research work encompassed two main stages namely the field, and the laboratory
studies. The field study involved collection of samples from the four locations - Awgu, Okigwe,
Nsukka I and II. The laboratory study involved soil handling and sample preparation, including
laboratory analyses of the samples.
3.2.1 Field Study
The soils used for this study were sampled at 0-10, 10-20, and 20-30 cm depths of the
above listed locations for each of the manually-tilled cultivated and uncultivated soils of 4-5
years. The information about the land was obtained from the indigenous land owners. Additional
undisturbed core samples were collected from each site and from corresponding depths for the
determination of bulk density (BD), total porosity, macroporosity (Pma), microporosity (Pmi),
water content at field capacity (FC), and soil moisture content. A total of twenty-four samples
were collected, put in plastic bags, labeled and brought to the laboratory for proper analyses.
3.2.2 Laboratory Study
Soil handling and sample preparation
Sampled soils were air-dried and divided into two equal parts. One portion was passed
through a 4.75 mm sieve to remove rock fragments after which the fractions that passed through
the mesh were used for aggregate size separation for the determination of aggregate size
distribution of soil organic carbon (SOC) and total soil nitrogen (TSN). The second portion
passed through 2 mm sieve and was used for the determination of particle size distribution in
H2O and in calgon, soil pH, SOC, total nitrogen, available phosphorus, cation exchange capacity
(CEC), exchangeable acidity (H+, Al
3+), exchangeable bases (Na
coefficient of linear extensibility (COLE), according to standard analytical procedures as
22.214.171.124 Physical analysis
Particle size analysis of < 2 mm fine earth fractions were carried out to determine the soil
texture by the hydrometer method as described by Gee and Bauder (1986), using sodium
hydroxide as the dispersing agent, and with deionized water alone for the determination of water
dispersible clay and silt. The microaggregate stability indices of the soils including clay
dispersion index (CDI), dispersion ratio (DR), aggregated silt and clay (ASC) and clay
flocculation index (CFI) were all calculated as follows according to Igwe et al. (1999):
CDI = [% clay (water) / % clay (calgon)] x 100
DR = [% silt + % clay (water)] / [% silt + % clay (calgon)]
ASC = [% clay + % silt (calgon)] [% clay + % silt (water)]
CFI = [% clay (calgon) % clay (water)] / [% clay (calgon)] x 100
Soil moisture content was measured, and the soil water content at field capacity (FC) was
determined by using the same core sample used for bulk density, macroporosity, microporosity
and total porosity. The core samples were weighed after 24 h of complete saturation in water and
then, placed on a tension table adjusted to 60 cm of tension for 24 h, after which they were
reweighed and oven dried until constant weight was obtained. Bulk density measurement was
obtained by the cylindrical core method as described by Blake and Hartge (1986), which was
used to calculate SOC on an area basis. Total porosity was determined in undisturbed water
saturated core samples. The above parameters were calculated as follows:
Soil moisture content = [(wet weight oven dry weight) (g) / oven dry weight (g)] x 100
Water content at FC = [(60 cm tension weight oven dry weight) (g) / oven dry weight (g)] x BD
Bulk density = mass of oven dry soil (g) / volume of bulk soil (cm3)
Total porosity = volume of H2O in soil at saturation (cm3) / volume of bulk soil (cm
Macroporosity = volume of H2O drained out at 60 cm tension (cm3) / volume of bulk soil (cm
Microporosity = volume of H2O retained at 60 cm tension (cm3) / volume of bulk soil (cm
Coefficient of linear extensibility (COLE) was determined using the method described by
Schafer and Singer (1976), thus:
COLE rod = (Lm Ld)/ Ld
Where; Lm = length of moist soil
Ld = length of dry soil.
The volumetric shrinkage (VS) was also calculated using the relationship stated below:
VS = [(COLE + 1)3 1] x 100
Aggregate size separation was performed on 100 g of 4.75 mm sieved soil by wet sieving
air-dried soil through a series of sieves (Elliot 1986), after submerging the soil sample in water at
room temperature on top of 4.75 mm sieve for 5 minutes. A series of four sieves were used to
obtain five different water-stable aggregate (WSA) fractions as follows: > 2.00 mm, 1.00-2.00
mm, 0.50-1.00 mm, 0.25-0.50 mm, and < 0.25 mm. Materials retained on each sieve (WSA) were
oven dried at 40 oC to constant weight.
The mass of aggregates > 0.25 mm were calculated by subtracting the sum of the oven-
dried weights of materials retained on each sieve from the air-dried weight of the original sample.
The proportion of each class to the total sample weight was computed thus:
Wi = Mi / Mt
Where Wi = proportion of the total sample weight occurring in the corresponding size fraction.
Mi = weight of the oven-dry aggregates (uncorrected for sand) in the size class
fractions after sieving.
Mt = total weight of the initial material (100 g) before sieving.
The mean weight diameter (MWD) of each WSA fraction was calculated from the equation:
MWD = xi wi
Where xi = mean diameter of each size fraction (mm)
wi = proportion of the total sample weight occurring in the corresponding size fraction
Geometric mean weight diameter (GMWD) was calculated according to the equation:
GMWD = exp [( wi log xi )/ wi]
Where wi = the weight of aggregates
xi = average diameter
wi = total weight of the sample
126.96.36.199 Chemical analysis
Soil pH was determined in distilled water and potassium chloride solution at ratios of
1:2.5 soil/water suspension using pH meter (McLean, 1982).
Soil organic carbon content of the whole soil (< 2.00 mm) and that associated with the
various water-stable aggregate (WSA) fractions (2.00-4.75 mm, 1.00-2.00 mm, 0.50-1.00 mm,
0.25-0.50 mm, and < 0.25 mm) were quantified by Walkley and Black wet oxidation method as
described by Nelson and Sommers (1982). The SOC in WSA was expressed in g C/kg (gram
carbon per kilogram) of soil using the appropriate conversion factors. The SOM was computed
by multiplying the % OC with the conventional Van Bernmeller factor of 1.724. The SOC pool
content was calculated using the following equation (Lal et al., 1998).
Mg C ha-1
= [%C x corrected b x d x 10
-1] / 100
Where Mg C ha-1
= mega gram carbon per hectare (1 Mg = 106g)
%C = percentage of C given by laboratory results
b (Mg m
-3) = soil bulk density (Megagram per cubic meter)
d = depth in meters
Total nitrogen content of the bulk soil (< 2.00 mm) and that associated with water-stable
ggregate fractions (> 2.00, 1.00-2.00, 0.50-1.00, 0.25-0.50, and < 0.25 mm), were determined by
the macro kjeldahl digestion method using CuSO4 and Na2SO4 catalyst mixture (Bremner and
Cation exchange capacity (CEC) was determined by the NH4OAC (ammonium acetate)
pH 7 method (Thomas, 1982). Exchangeable bases were determined in 1N NH4OAC (ammonium
acetate) at pH 7 leachate using the flame photometer for sodium and potassium while
complexometric EDTA titration method was used for calcium and magnesium (Thomas, 1982).
Exchangeable acidity was determined by titration method using 1N KCI extract as described by
3.3 Statistical Analysis
The experiment was designed as 4 x 2 x 3 factorial in completely randomized design
(CRD). Factor A was location at four levels namely Awgu, Okigwe, Nsukka I, and Nsukka II.
The levels of factor B (land use) were cultivated and uncultivated soils, while factor C (soil
depth) comprised of three levels viz.: 0-10, 10-20 and 20-30 cm. The final analysis of variance
(ANOVA) table is shown in Appendix 1. The data collected on the various parameters were
analyzed using ANOVA. Separation of treatment means for statistical significance was
performed by the F-LSD procedure according to Obi (1986) to determine land use and soil type
with the highest potential of sequestering SOC. Correlation and regression analysis were
performed among WSA, SOC, TSN, and soil properties to show their relationships.
RESULTS AND DISCUSSION
4.1.1 Soil Characteristics
The particle size distribution and textural classification of the soils are presented in Table
3. The particle size fractions among the locations at 0-30 cm depth were significantly different at
P = 0.05 in both land uses. Okigwe and Awgu soils contained the highest amount of clay and silt
size particles respectively, while Nsukka I and II soils were more of sand particles than clay and
silt. The particle sizes differed with soil depth, however, the effect due to land use was not
statistically different. In both land uses, the textural classes varied with depth in each location
and included clay, loam, clay loam, sandy loam and sandy clay loam.
Table 4 presents the chemical properties of the soils. All the chemical properties differed
significantly (P = 0.05) among the locations in both land uses. Generally, the pH values of the
soils in KCl indicated that they are acid and decreased slightly with increase in soil depth. The
mean value of soil pH in KCl at 0-30 cm depth ranged from 3.87 to 4.20 and 4.00 to 4.80 in
cultivated and uncultivated land uses respectively. The OC content of the soils were generally
low and concentrated mostly at 0-10 cm depth. The mean value at 0-30 cm depth among the
locations ranged from 0.65 % to 1.47 % and 0.63 % to 1.74 % in cultivated and uncultivated land
uses respectively, with Okigwe soil having the highest value while Nsukka I had the least value
in both land uses. Available phosphorus (P) and total nitrogen (N) of the soils varied with depth
and were generally low. The mean value at 0-30 cm depth ranged from trace to 0.93 cmol/kg (P)
and 0.11-0.15 % (N) in cultivated soils, and trace to 1.73 cmol/kg (P) and 0.11 to 0.17 % (N) in
uncultivated land use. Of all the exchangeable cations (Na+, K
was mostly the same within the various soil depths among the locations, and the mean value at 0-
30 cm depth ranged from 0.10 to 0.19 cmol/kg among the locations in both land uses. The rest of
the exchangeable cations varied with soil depth except Al3+
which concentrated more at 20-30
cm depth than at 0-10 cm depth. More so, among all the exchangeable cations, Al3+
highest mean value at 0-30 cm depth in almost all the locations ranging from 2.27 to 10.53
cmol/kg and from 2.40 to 7.80 cmol/kg in both cultivated and uncultivated soils, respectively.
with mean ranging from 0.80 to 2.93 cmol/kg and from 0.60 to 10.40
cmol/kg at 0-30 cm depth among the locations in cultivated and uncultivated soils, respectively.
mean ranged from 0.27 to 3.00 cmol/kg and from 0.27 to 4.47 cmol/kg at 0-
30 cm depth among the locations in cultivated and uncultivated soils, respectively. Exchangeable
K+ mean value ranged from 0.09 to 0.18 cmol/kg, and from 0.08 to 0.22 cmol/kg at 0-30 cm
depth among the locations in cultivated and uncultivated land uses respectively. The CEC of the
Table 3: Particle size distribution and textural classification of the soils
Depth Clay Silt Fine Coarse Total Textural
Land use Location (cm) sand sand sand class --------------------------------- % ------------ ------------------
Cultivated Awgu 0-10 17 49 13 21 34 L
10-20 27 39 17 17 34 L
20-30 31 23 27 19 46 SCL
Mean 25 37 19 19 38
Okigwe 0-10 27 23 24 27 50 SCL
10-20 43 15 19 23 42 C
20-30 47 9 20 25 44 C
Mean 39 16 21 25 45 Nsukka
I 0-10 16 9 27 49 76 SL
10-20 22 7 27 44 72 SCL
20-30 22 7 25 47 72 SCL
Mean 20 8 26 47 73 Nsukka
II 0-10 26 7 34 34 68 SCL
10-20 26 9 33 32 66 SCL
20-30 30 5 44 31 66 SCL
Mean 27 7 37 32 67
LSD (0.05) 5.35* 8.20* 4.86* 6.31* 9.05*
Uncultivated Awgu 0-10 27 39 33 2 34 L
10-20 31 25 38 6 44 CL
20-30 27 29 35 9 44 L
Mean 28 31 35 6 41
Okigwe 0-10 17 25 29 29 58 SL
10-20 31 25 20 24 44 CL
20-30 43 13 20 24 44 C
Mean 30 21 23 26 49
I 0-10 14 11 25 51 76 SL
10-20 21 8 23 48 72 SCL
20-30 25 10 31 35 66 SCL
Mean 20 10 26 45 71
II 0-10 26 3 36 36 72 SCL
10-20 28 7 29 37 66 SCL
20-30 22 7 24 47 72 SCL
Mean 25 6 30 40 70
LSD (0.05) 4.31* 6.51* 3.58* 9.58* 8.53 *
Table 4: Chemical properties of the soils under cultivated land use
Depth pH pH SOC SOM Total N Avail P Na+ K
3+ CEC C/N
Land use Location (cm) H2O KCl ------------%-------------- ppm -------------------------cmol/kg-------------------------
0-10 5.70 4.30 0.88 1.52 0.11 1.19 0.19 0.15 3.00 2.20 8.80 13.60 8.00
10-20 5.60 4.10 1.03 1.78 0.14 0.40 0.19 0.10 2.80 2.40 9.20 19.60 7.36
20-30 5.50 4.10 0.96 1.66 0.11 1.19 0.19 0.15 3.00 3.60 13.60 27.60 8.73
Mean 5.60 4.17 0.96 1.65 0.12 0.93 0.19 0.13 2.93 2.73 10.53 20.27 8.03
Okigwe 0-10 5.40 4.30 1.80 3.10 0.17 trace 0.10 0.25 3.00 2.60 5.60 25.20 10.59
10-20 5.20 4.20 1.57 2.71 0.15 trace 0.10 0.20 2.00 3.00 8.20 23.60 10.47
20-30 5.20 4.10 1.03 1.78 0.14 trace 0.19 0.10 1.20 3.40 11.00 18.40 7.36
Mean 5.27 4.20 1.47 2.53 0.15 trace 0.13 0.18 2.07 3.00 8.27 22.40 9.47
0-10 4.70 3.80 0.83 1.43 0.14 2.79 0.10 0.14 1.00 0.20 4.80 19.60 5.93
10-20 4.90 3.90 0.54 0.93 0.18 trace 0.10 0.08 0.60 0.40 3.60 21.20 3.00
20-30 4.50 3.90 0.58 1.00 0.13 trace 0.10 0.06 0.80 0.20 4.80 25.60 4.46
Mean 4.70 3.87 0.65 1.12 0.15 - 0.10 0.09 0.80 0.27 4.40 22.13 4.46
0-10 5.20 4.20 1.41 2.43 0.11 trace 0.10 0.14 1.40 0.20 2.00 19.20 12.82
10-20 5.40 4.10 1.41 2.43 0.13 trace 0.10 0.11 1.00 0.60 2.00 19.20 10.85
20-30 5.50 4.10 0.93 1.60 0.10 trace 0.10 0.11 0.80 0.20 2.80 21.60 9.30
Mean 5.37 4.13 1.25 2.15 0.11 trace 0.10 0.12 1.07 0.33 2.27 20.00 10.99 Grand mean 5.23 4.09 1.08 1.86 0.13 nil 0.13 0.13 1.72 1.58 6.37 21.20 8.24
LSD (0.05) 0.21* 0.09* 0.22* 0.39* 0.01* nil 0.03* 0.03* 0.57* 0.81* 2.17* 2.21* 1.64*
Table 4 continuation: Chemical properties of the soils under uncultivated land use
Depth pH pH SOC SOM Total N Avail P Na+ K
3+ CEC C/N
Land use Location cm H2O KCl ------------%-------------- ppm ----------------------- -cmol/kg------------------------
0-10 5.90 5.30 1.34 2.31 0.13 0.80 0.19 0.25 12.40 5.60 3.60 8.00 10.31
10-20 5.60 4.70 0.84 1.45 0.11 trace 0.10 0.20 9.60 3.80 4.80 10.00 7.64
20-30 5.50 4.40 0.96 1.66 0.10 trace 0.19 0.20 9.20 4.00 4.80 8.40 9.60
Mean 5.67 4.80 1.05 1.81 0.11 - 0.16 0.22 10.40 4.47 4.40 8.80 9.18
Okigwe 0-10 5.30 4.50 2.45 4.22 0.24 trace 0.19 0.15 2.80 3.20 4.80 8.40 10.21
10-20 5.20 4.20 1.69 2.91 0.15 0.80 0.19 0.20 1.60 1.80 7.60 8.40 11.27
20-30 5.10 4.10 1.07 1.85 0.11 trace 0.19 0.10 1.20 1.60 11.00 7.20 9.73
Mean 5.20 4.27 1.74 2.99 0.17 - 0.19 0.15 1.87 2.20 7.80 8.00 10.40
0-10 5.40 4.20 0.97 1.67 0.15 3.98 0.10 0.11 1.00 0.40 2.00 11.60 6.47
10-20 5.00 4.00 0.54 0.93 0.08 0.40 0.10 0.08 0.60 0.60 2.40 11.20 6.75
20-30 4.90 3.90 0.39 0.67 0.14 0.80 0.10 0.06 0.80 0.40 2.80 13.20 2.79
Mean 5.10 4.03 0.63 1.09 0.12 1.73 0.10 0.08 0.80 0.47 2.40 12.00 5.34
0-10 5.00 4.00 1.17 2.02 0.07 0.80 0.10 0.11 0.60 0.40 2.40 8.00 16.71
10-20 4.90 4.00 0.93 1.60 0.17 2.79 0.10 0.06 0.60 0.20 3.20 8.00 5.47
20-30 5.20 4.00 0.78 1.35 0.10 1.59 0.10 0.06 0.60 0.20 2.80 11.60 7.80
Mean 5.03 4.00 0.96 1.66 0.11 1.73 0.10 0.08 0.60 0.27 2.80 9.20 9.99 Grand mean 5.25 4.28 1.09 1.89 0.13 nil 0.14 0.13 3.43 1.83 4.35 9.50 8.73
LSD (0.05) 0.18* 0.23* 0.32* 0.54* 0.03* nil 0.03* 0.04* 2.52* 1.05* 1.51* 1.12* 2.01*
Grand LSD (0.05) NS 0.13* NS NS NS nil NS NS 1.31* NS 1.36* 2.72* NS
soils varied with depth and was between 13.60 and 27.60 cmol/kg in cultivated soils with
mean ranging from 20.00 to 22.40 cmol/kg at 0-30 cm depth among the locations. In uncultivated
soils, the CEC values at the various soil depths were between 7.20 and 13.20 cmol/kg with mean
ranging from 8.00 to 12.00 cmol/kg at 0-30 cm depth among the locations. The C/N ratios of the
soils also varied with depth. The mean value at 0-30 cm depth ranged from 4.46 to 10.99 and
5.34 to 10.40 among the locations in cultivated and uncultivated land uses respectively, with
Nsukka I having the least value in both land uses. Land use had no significant effect on all the
chemical properties considered except on pH in KCl, Ca2+
, and CEC. Generally, the soils of
the four locations were low in basic cations and soil available nutrients. They suffer severe
leaching and interrill erosion as a result of high rainfall intensity (Igwe, 2005).
4.1.2 Microaggregate Stability Indices of the Soils
Microaggregate stability indices, including water content at field capacity of the soils are
presented in Table 5. All the parameters at 0-30 cm depth varied significantly (P = 0.05) among
the four locations in each of the land uses, expect that in cultivated soils, clay dispersion index
(CDI) and clay flocculation index (CFI) were not significantly affected by location. The mean
value of CDI at 0-30 cm depth among the locations ranged from 42.75 to 46.28 in cultivated and
from 30.90 to 53.72 in uncultivated land use. Dispersion ratio (DR) mean value at 0-30 cm depth
among the locations ranged from 0.56 to 0.78 and 0.61 to 0.81 in cultivated and uncultivated land
uses, respectively. Aggregated silt and clay (ASC) mean value at 0-30 cm depth ranged from
7.28 to 24.00 and 7.28 to 20.00 among the locations in cultivated and uncultivated soils,
respectively, with Okigwe soil having the highest value while Nsukka I had the least in both land
uses. The uncultivated soils had moderate CFI values with the mean range of 46.28 to 69.11.
Water dispersible clay (WDC) significantly (P = 0.05) gave higher value of 15.15 for Okigwe
soil at 0-30 cm depth in both land uses. This could be attributed to the higher value of clay
content in Okigwe soil when compared with other locations. Water dispersible silt (WDSi)
content among the locations at 0-30 cm depth mean value ranged from 11.23 to 36.61 in
cultivated soils and 11.89 to 35.95 in uncultivated soils, with Awgu soil having the highest value
while Nsukka I soil had the least value in each of the land uses. It thus follows this trend; Awgu
> Okigwe > Nsukka II > Nsukka I. Water content at field capacity of the soils ranged between 28
and 39 % among the locations in cultivated soils, and from 26 to 36 % in uncultivated soils with
Nsukka I having the least value under both land uses. Land use showed no significant difference
among all the parameters considered in Table 5.
Table 6 presents soil moisture, bulk density, porosity, COLE and VS of the soils. All the
parameters measured showed significant differences (P = 0.05) among the locations at 0-30 cm
Table 5: Microaggregate stability indices and water content at field capacity (FC) of the
Land use Location Depth CDI DR ASC CFI WDC WDSi FC
Cultivated Awgu 0-10 51.46 0.76 16.00 48.54 8.48 41.28 0.27 10-20 32.02 0.76 16.00 67.98 8.48 41.28 0.36 20-30 47.51 0.78 12.00 52.49 14.48 27.28 0.37 Mean 43.66 0.77 14.67 56.34 10.48 36.61 0.33 Okigwe 0-10 77.34 0.60 20.00 22.66 20.48 9.28 0.51 10-20 29.38 0.52 28.00 70.62 12.48 17.28 0.35 20-30 26.85 0.57 24.00 73.15 12.48 19.28 0.30 Mean 44.52 0.56 24.00 55.48 15.15 15.28 0.39
Nsukka I 0-10 41.12 0.70 7.28 58.88 6.48 10.56 0.30
10-20 48.16 0.74 7.28 51.84 10.48 10.56 0.28 20-30 38.97 0.74 7.28 61.03 8.48 12.56 0.25 Mean 42.75 0.73 7.28 57.25 8.48 11.23 0.28
Nsukka II 0-10 40.68 0.77 7.28 59.32 10.48 14.56 0.34
10-20 56.21 0.73 9.28 43.79 14.48 10.56 0.41 20-30 41.94 0.85 5.28 58.07 12.48 16.56 0.32 Mean 46.28 0.78 7.28 53.73 12.48 13.89 0.36 Grand mean 44.30 0.71 13.31 55.70 11.65 19.25 0.34 LSD (0.05) NS 0.06* 4.33* NS 2.17* 6.60* 0.04*
ated Awgu 0-10 54.68 0.79 14.00 45.32 14.48 37.28 0.39 10-20 34.38 0.82 10.00 65.62 10.48 35.28 0.35 20-30 39.58 0.82 10.00 60.42 10.48 35.28 0.33 Mean 42.88 0.81 11.33 57.12 11.81 35.95 0.36 Okigwe 0-10 63.59 0.62 16.00 36.41 10.48 15.28 0.41 10-20 54.07 0.64 20.00 45.93 16.48 19.28 0.23 20-30 43.50 0.57 24.00 56.50 18.48 13.28 0.25 Mean 53.72 0.61 20.00 46.28 15.15 15.95 0.30
Nsukka I 0-10 47.09 0.70 7.28 52.91 6.48 10.56 0.33
10-20 48.16 0.81 5.28 51.84 10.48 12.56 0.25 20-30 48.45 0.73 9.28 51.55 12.48 12.56 0.20 Mean 47.90 0.75 7.28 52.10 9.81 11.89 0.26
Nsukka II 0-10 25.16 0.74 7.28 74.85 6.48 14.56 0.35
10-20 37.75 0.67 11.28 62.25 10.48 12.56 0.32 20-30 29.78 0.60 11.28 70.22 6.48 10.56 0.36 Mean 30.90 0.67 9.95 69.11 7.81 12.56 0.34 Grand mean 43.85 0.17 12.14 56.15 11.15 19.09 0.31 LSD (0.05) 6.41* 0.05* 3.18* 6.41* 2.22* 6.02* 0.04* Grand LSD (0.05) NS NS NS NS NS NS NS
CDI = clay dispersion index; DR = dispersion ratio; ASC = aggregate silt and clay; CFI = Clay
flocculation index; WDC = water dispersible clay; WDSi = water dispersible silt.
Table 6: Soil moisture, bulk density, porosity, coefficient of linear extensibility (COLE)
and volumetric shrinkage (VS) of the soils
Soil Bulk Macro Micro Total
Depth moisture density porosity porosity porosity COLE VS
Land use Location (cm) (%) (Mg m-3
) ------------ % ------------- (%)
Cultivated Awgu 0-10 22.32 1.56 4.31 41.50 45.81 0.02 6.12 10-20 26.66 1.35 4.66 48.70 53.35 0.09 29.50 20-30 35.22 1.36 4.03 49.67 53.69 0.10 33.10 Mean 28.07 1.42 4.33 46.62 50.95 0.07 22.91 Okigwe 0-10 13.98 1.42 8.97 72.57 81.54 0.04 12.49 10-20 19.74 1.61 10.42 56.41 66.81 0.11 36.76 20-30 27.39 1.61 11.00 48.28 59.28 0.11 36.76
Mean 20.37 1.55 10.13 59.09 69.21 0.09 28.67
Nsukka I 0-10 4.25 1.36 6.65 41.30 47.95 0.01 3.03
10-20 8.53 1.52 6.91 42.08 48.99 0.02 6.12 20-30 10.49 1.56 5.90 39.15 45.05 0.04 12.49 Mean 7.76 1.48 6.49 40.84 47.33 0.02 7.21 Nsukka
II 0-10 11.59 1.41 7.95 47.38 55.33 0.03 9.27
10-20 13.72 1.29 7.91 52.14 60.06 0.02 6.12 20-30 9.82 1.45 9.64 46.33 55.97 0.02 6.12 Mean 11.71 1.38 8.50 48.62 57.12 0.02 7.17 Grand mean 16.98 1.46 7.36 48.79 56.15 0.05 16.49
LSD (0.05) 5.36* 0.06* 1.37* 5.20* 5.90* 0.02* 7.71*
ed Awgu 0-10 32.89 1.32 8.76 50.99 59.75 0.04 12.49 10-20 29.97 1.41 6.18 48.64 54.82 0.05 15.74 20-30 31.32 1.32 6.75 43.10 49.86 0.09 29.50 Mean 31.39 1.35 7.23 47.58 54.81 0.06 19.24 Okigwe 0-10 27.60 1.26 6.56 51.01 57.57 0.03 9.27 10-20 20.75 1.81 5.64 42.26 47.90 0.08 25.97 20-30 20.18 1.78 11.32 44.82 56.14 0.06 19.10 Mean 22.84 1.62 7.84 46.03 53.87 0.06 18.11
Nsukka I 0-10 6.94 1.42 7.07 46.59 53.66 0.00 0.00
10-20 8.45 1.58 7.25 39.75 47.00 0.01 3.03 20-30 9.64 1.63 1.62 32.93 34.54 0.02 6.12 Mean 8.34 1.54 5.31 39.76 45.07 0.01 3.05 Nsukka
II 0-10 10.48 1.37 6.75 48.25 55.00 0.02 6.12
10-20 10.27 1.45 6.60 46.85 53.46 0.03 9.27 20-30 12.44 1.32 6.40 47.19 53.58 0.02 6.12 Mean 11.06 1.38 6.58 47.43 54.01 0.02 7.17 Grand mean 18.41 1.47 6.74 45.20 51.94 0.04 11.89
LSD (0.05) 5.71* 0.11* 1.27* 2.97* 3.83* 0.02* 5.25*
Grand LSD (0.05) NS NS NS NS NS NS NS
depth of both land uses. Soil moisture content ranged from 7.76 to 28.07 % and 8.34 to 31.39
% in cultivated and uncultivated soils, respectively. The trend was similar to that of WDSi
content in both land uses. This could be attributed to the high proportion of total sand relative to
clay and silt size fractions in the particle size distribution. In cultivated land use, soil moisture
content increased with depth except in Nsukka II, which can be attributed to the topography of
the location (hilly) and the inclination of the direction of sunlight and rainfall. Bulk density of the
soils varied with depth. The mean ranged from 1.38 to 1.55 Mg m-3
and from 1.35 to 1.62 Mg m-3
at 0-30 cm depth in cultivated and uncultivated soils, respectively. In both land uses,
microporosity was higher than macroporosity with a mean range of 40.84 to 59.09 % and 39.76
to 47.58 % at 0-30 cm depth in cultivated and uncultivated land uses respectively, as compared to
macroporosity with mean ranging from 4.33 to 10.13 % in cultivated soils, and from 5.31 to 7.84
% in uncultivated soils. Unlike soil moisture and bulk density mean values, total porosity of the
cultivated soils was generally higher when compared with the uncultivated soils. This may be
attributed to the effect of cultivation on the physical properties of the soil as these relate to soil
structure and aggregation (Six et al., 1999). Generally, COLE values increased with soil depth
except in Nsukka II, where uniformity in the texture of the soil (Table 3) could be responsible for
the deviation from the above mentioned trend. The COLE mean values at 0-30 cm depth among
the locations ranged from 0.02 to 0.09 in cultivated soils and from 0.01 to 0.06 in uncultivated
soils. According to Schaffer and Singer (1976) outlined categories of COLE and their
corresponding shrink-swell harzard ratings, the soils of Nsukka I and II fell within the slight
shrink-swell category, whereas the Awgu and Okigwe fell within the severe shrink-swell harzard
category. The VS which reflects the absolute values of COLE followed the same trend as COLE.
In general, land use had no significant effect on any of the soil properties considered in Table 6.
4.1.3 Water-Stable Aggregates (WSA), Mean Weight Diameter (MWD) and Geometric
Mean Weight Diameter (GMWD) of the Soils
Data on WSA, MWD and GMWD of the soils are presented in Table 7. Generally, the
various aggregate sizes varied greatly across the various soil depths. Pooled over the three
depths, location significantly (P = 0.05) influenced the various aggregate size fractions in both
land uses. In Okigwe and Nsukka II soils had > 50 % of WSA > 2.00 mm at 0-30 cm depth. The
reverse was the case with Awgu and Nsukka I soils, which had about 7 to 21 % and 19 to 49 %
WSA of > 2.00 mm respectively. In Awgu location, the mean under cultivated land use were
16.80 and 27.12 % for WSA of 0.50-1.00 mm and < 0.25 mm respectively. Okigwe recorded
means of 7.44 and 53.04 % for 0.25-0.50 mm and > 2.00 mm WSA. Means of 10.65 and 30.67 %
were obtained for 0.25-0.50 mm and 1.00-2.00 mm WSA in Nsukka I. For Nsukka II, the highest
Table 7: Water-stable aggregates (WSA), mean weight diameter (MWD) and geometric
mean weight diameter (GMWD) of the soils
Depth ------------------WSA (mm) ---------------- MWD GMWD
Land use Location (cm) A B C D E (mm) (mm)
Cultivated Awgu 0-10 46.15 13.47 10.34 10.22 19.82 1.90 0.82 10-20 8.78 12.88 16.57 24.55 37.22 0.76 0.67 20-30 7.19 27.68 23.50 17.32 24.33 0.93 0.78 Mean 20.71 18.01 16.80 17.36 27.12 1.20 0.76 Okigwe 0-10 65.69 13.22 6.47 5.18 9.44 2.51 0.92 10-20 52.70 19.86 11.21 5.56 10.67 2.21 0.90 20-30 40.73 19.96 17.60 11.59 10.12 1.88 0.91 Mean 53.04 17.68 11.76 7.44 10.08 2.20 0.91 Nsukka
I 0-10 19.67 30.52 21.83 11.41 16.57 1.37 0.85 10-20 18.80 32.20 26.17 10.39 12.44 1.37 0.89 20-30 18.21 29.28 29.06 10.15 13.30 1.31 0.88 Mean 18.89 30.67 25.69 10.65 14.10 1.35 0.87 Nsukka
II 0-10 73.86 6.80 5.43 4.02 9.89 2.67 0.91 10-20 83.37 6.56 2.18 1.53 6.36 3.00 0.95 20-30 80.52 5.35 4.51 3.92 5.70 2.87 0.95 Mean 79.25 6.24 4.04 3.16 7.32 2.85 0.94
LSD (0.05) 16.34* 5.70* 5.29* 3.72* 5.15* 0.44* 0.05*
ed Awgu 0-10 3.01 7.79 11.87 19.57 56.76 0.46 0.49 10-20 2.84 22.36 21.50 11.50 41.80 0.69 0.62 20-30 14.47 21.03 20.53 14.86 29.11 1.07 0.74 Mean 6.77 17.06 17.97 15.31 42.56 0.74 0.62 Okigwe 0-10 74.40 9.96 5.23 2.61 7.80 2.71 0.93 10-20 67.35 11.19 5.85 2.95 12.66 2.50 0.88 20-30 56.47 16.32 12.78 5.35 9.08 2.29 0.92 Mean 66.07 12.49 7.95 3.64 9.85 2.50 0.91 Nsukka
I 0-10 84.11 4.46 3.65 3.41 4.37 2.96 0.96 10-20 32.89 25.26 22.56 12.59 6.70 1.72 0.94 20-30 31.15 37.58 17.21 7.67 6.39 1.78 0.95 Mean 49.38 22.43 14.47 7.89 5.82 2.15 0.95 Nsukka
II 0-10 89.16 4.96 1.20 0.92 3.76 3.13 0.96 10-20 73.46 13.12 5.42 2.24 5.76 2.81 0.95 20-30 73.92 9.10 4.78 3.37 8.83 2.69 0.92 Mean 78.85 9.06 3.80 2.18 6.12 2.88 0.94
LSD (0.05) 18.34* 5.64* 4.46* 3.46* 9.92* 0.53* 0.09*
A, B, C, D and E represent > 2.00, 1.00-2.00, 0.50-1.00, 0.25-0.50 and < 0.25 respectively.
mean was 79.25 % for > 2.00 mm WSA while the lowest was 3.16 % for 0.25-0.50 mm WSA.
For uncultivated land use, Awgu location had the highest and lowest mean of 6.77 and 42.56 %
for aggregate sizes of > 2.00 mm and < 0.25 mm, respectively. Okigwe followed the same trend
as that obtained in cultivated land use with mean values of 3.64 and 6.77 %. The lowest and
highest mean values of 5.82 and 49.38 % for WSA of < 0.25 mm and > 2.00 mm sizes were
obtained in Nsukka I. Nsukka II had a similar trend as that obtained in cultivated soils with the
lowest and highest mean values of 2.18 and 78.85 %. Both MWD and GMWD of the soils varied
with soil depth in both land uses. The MWD mean values at 0-30 cm depth ranged from 1.20 to
2.85 mm and 0.74 to 2.88 mm for cultivated and uncultivated soils, respectively. The GMWD,
which represents the absolute values of MWD, had mean values at 0-30 cm depth ranging from
0.76 to 0.94 mm and 0.62 to 0.95 mm in cultivated and uncultivated land uses respectively.
4.1.4 Soil Carbon and Nitrogen Content, and C/N ratio in the Water-Stable Aggregates
The distribution of C and N, as well as C/N ratios of the aggregate size fractions are
presented in Table 8. In all the parameters determined, effect due to location differed
significantly (P = 0.05) at 0-30 cm depth in both land uses. Generally, C and N contents varied
among the WSA sizes and across the soil depths. However, in Nsukka I, C content decreased
with soil depth in each of the land uses, except in 0.50-1.00 mm and 0.25-0.50 mm WSA of
uncultivated land use. The same trend applied to N content for the same location except in the
0.50-1.00 mm WSA of the cultivated soils, and in the 1.00-2.00 mm and < 0.25 mm WSA of the
uncultivated soils. With a few exceptions, C accumulated more in the topmost 0-10 cm depth
than the subsurface soil in both land uses. More so, the C and N contents of the soils were
generally higher in uncultivated as expected than in cultivated soils. However, the reverse was
the case with Nsukka I and II. In cultivated land use, C and N content did not vary substantially
in the various WSA sizes. Nevertheless, smaller aggregates (< 1.00 mm) contained more N than
the larger aggregates (> 1.00 mm). Highest amount of C at 0-30 cm depth was recorded in the
0.50-1.00 mm WSA for Awgu and Okigwe soils, and in the > 2.00 mm WSA for Nsukka I and II
soils. Hence, it is possible to infer that the underlying parent material of the soil could be
responsible for the differences obtained in the preferential accumulation of C in the WSA classes.
Also in cultivated land use at 0-30 cm soil depth, the < 0.25 WSA generally accumulated more N
than the rest of the aggregate fractions except in Nsukka II, where the topography of the site
could be responsible for the deviation. In all, the lowest N content was observed in 1.00-2.00 mm
and > 2.00 mm WSA. This supports other findings suggesting that N is sequestered in the
microaggregates of the soil where they are protected by a mechanism of incorporation into the
Table 8: Carbon and nitrogen content (g kg-1
), and C/N ratios in the various water-stable aggregate (WSA) fractions of cultivated soils
----------------------------------------------------WSA (mm) ---------------------------------------------------
> 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
----------------------- -------------------- ---------------------- ---------------------- ---------------------
Land use Location Depth C N C/N C N C/N C N C/N C N C/N C N C/N
Awgu 0-10 7.40 1.30 5.69 5.00 1.50 3.33 8.10 1.70 4.77 6.70 1.70 3.94 6.00 3.40 1.77
10-20 7.70 1.50 5.13 5.70 1.10 5.18 6.70 1.80 3.72 7.40 1.70 4.35 7.00 2.00 3.50
20-30 5.70 1.70 3.35 7.30 1.80 4.06 7.40 1.50 4.93 7.60 2.00 3.80 6.30 3.40 1.85
Mean 6.93 1.50 4.72 6.00 1.47 4.19 7.40 1.67 4.47 7.23 1.80 4.03 6.43 2.93 2.37
Okigwe 0-10 15.30 1.80 8.50 12.80 1.40 9.14 13.90 2.20 6.32 12.50 3.10 4.03 11.70 3.40 3.44
10-20 8.70 2.00 4.35 11.70 2.90 4.04 10.70 2.40 4.46 10.8 3.10 3.48 8.70 3.10 2.81
20-30 5.90 1.50 3.93 7.60 2.00 3.80 9.00 2.40 3.75 9.40 2.10 4.48 7.60 2.50 3.04
Mean 9.97 1.77 5.59 10.70 2.10 5.66 11.20 2.33 4.84 10.90 2.77 4.00 9.33 3.00 3.10
Nsukka I 0-10 11.40 2.00 5.7 8.00 1.50 5.33 6.40 1.40 4.57 6.00 1.50 4.00 9.10 2.80 3.25
10-20 5.70 1.40 4.07 6.40 1.30 4.92 5.70 2.10 2.71 4.60 1.40 3.29 7.60 2.50 3.04
20-30 5.70 1.40 4.07 4.00 1.10 3.64 5.30 1.10 4.82 4.60 1.30 3.54 4.60 1.70 2.71
Mean 7.60 1.60 4.75 6.13 1.30 4.63 5.80 1.53 4.03 5.07 1.40 3.61 7.10 2.33 3.00
Nsukka II 0-10 12.90 1.50 8.60 11.00 1.50 7.33 10.40 2.50 4.16 10.60 2.80 3.79 11.00 2.50 4.40
10-20 14.80 1.70 8.71 11.40 1.70 6.71 11.40 1.40 8.14 11.70 2.80 4.18 12.50 1.10 11.36
20-30 10.30 1.30 7.92 7.60 1.10 6.91 8.40 2.50 3.36 9.90 2.50 3.96 9.90 2.80 3.54
Mean 12.67 1.50 8.47 10.00 1.43 6.98 10.07 2.13 5.22 10.73 2.70 3.98 11.13 2.13 6.43
LSD (0.05) 2.07* 0.14* 1.18* 1.66* 0.29* 1.04* 1.49* 0.29* 0.83* 1.56* 0.39* 0.20* 1.40* 0.42* 1.45*
Table 8 continuation: Carbon and nitrogen content (g kg-1
), and C/N ratios in the various water-stable aggregate (WSA) fractions of
---------------------------------------------------WSA (mm) --------------------------------------------------
> 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
---------------------- -------------------- ---------------------- ---------------------- ---------------------
Land use Location Depth C N C/N C N C/N C N C/N C N C/N C N C/N
Uncultivated Awgu 0-10 20.10 2.00 10.50 18.40 2.80 6.57 15.40 1.50 10.27 9.70 1.80 5.39 5.60 2.50 2.24
10-20 14.40 2.00 7.20 9.70 2.10 4.62 8.10 1.70 4.77 6.40 1.80 3.56 4.40 2.20 2.00
20-30 9.40 3.10 3.03 9.40 1.40 6.71 6.40 2.00 3.20 5.60 1.70 3.29 3.80 1.40 2.71
Mean 14.63 2.37 6.91 12.50 2.10 5.97 9.97 1.73 6.08 7.23 1.77 4.08 4.60 2.03 2.32
Okigwe 0-10 17.40 2.10 8.29 17.40 2.00 8.70 17.00 3.60 4.72 14.10 3.40 4.15 8.70 3.60 2.42
10-20 12.20 1.70 7.18 10.40 2.10 4.95 11.80 3.10 3.81 9.50 3.40 2.79 8.10 4.80 1.69
20-30 8.70 1.10 7.91 8.30 1.80 4.61 8.70 2.00 4.35 8.10 3.10 2.61 5.70 3.10 1.84
Mean 12.77 1.63 7.79 12.03 1.97 6.09 12.50 2.90 4.29 10.57 3.30 3.18 7.50 3.83 1.98
Nsukka I 0-10 9.10 1.50 6.07 9.90 2.80 3.54 5.70 2.80 2.04 5.70 1.40 4.07 8.70 1.80 4.83
10-20 9.10 1.40 6.50 6.40 0.60 10.67 4.70 2.10 2.24 3.70 1.10 3.36 7.20 1.10 6.55
20-30 3.70 1.10 3.36 5.70 1.40 4.07 5.30 1.40 3.79 4.20 1.10 3.82 5.00 2.80 1.79
Mean 7.30 1.33 5.31 7.33 1.60 6.09 5.23 2.10 2.69 4.53 1.20 3.75 6.97 1.90 4.39
Nsukka II 0-10 8.70 1.50 5.80 11.00 2.20 5.00 9.50 2.20 4.32 9.90 1.10 9.00 10.60 3.10 3.42
10-20 8.40 1.40 6.00 6.70 1.40 4.79 6.80 2.20 3.09 8.00 3.60 2.22 10.60 3.10 3.42
20-30 8.70 1.50 5.80 8.40 1.30 6.46 5.30 1.40 3.79 6.80 2.20 3.09 8.40 2.80 3.00
Mean 8.60 1.47 5.87 8.70 1.63 5.42 7.20 1.93 3.73 8.23 2.30 4.77 9.87 3.00 3.28
LSD (0.05) 2.59* 0.32* 1.17* 2.30* 0.37* 1.20* 2.35* 0.40* 1.22* 1.67* 0.56* 1.04* 1.34* 0.58* 0.83*
hydrophobic domains present in the finest fraction (Piccolo and Mbagwu, 1999). In uncultivated
soils, the highest amount of C was observed in > 1.00 mm WSA for Awgu location at 0-30 cm
depth, while Nsukka II recorded the highest amount of C in < 0.25 mm WSA. The < 1.00 mm
WSA generally contained less C in all the locations under uncultivated land use. With the
exception of Awgu location, the < 1.00 mm WSA at 0-30 cm depth accumulated more N than the
> 1.00 mm WSA. In both land uses, the C/N ratios of the soils were generally low which explains
why there was no substantial different between C and N content of the cultivated and
uncultivated soils. The low C/N ratios may have resulted from rapid decomposition and
mineralization of SOM.
4.1.5 Soil Organic Carbon Pool
Table 9 presents SOC pool of cultivated and uncultivated soils at the various soil depths.
Soil depth significantly (P = 0.05) influenced SOC pool under both land uses. The mean value of
SOC pool at 0-30 cm depth ranged from 9.52 to 22.47 Mg ha -1
and 9.55 to 26.84 Mg ha -1
cultivated and uncultivated soils, respectively. In both land uses, SOC pool decreased with depth,
thus 0-10 cm depth sequestered more SOC and the least being 20-30 cm depth. This implies
higher accumulation of organic matter at the topmost surface layer of the soil (0-10 cm) than the
rest of the soil depths. This is graphically represented in Fig. 2. Effects of land use on SOC pool
at 0-30 cm depth showed no significant differences. Similarly, depth and land use interaction
showed no significant effect on SOC pool. Location significantly (P = 0.05) influenced SOC pool
at 0-30 cm depth in both land uses. Considering the sum of SOC at 0-30 cm depth of the
locations, the result showed that Okigwe sequestered the highest C of 67.42 Mg ha-1
, followed by
Nsukka II (51.56 Mg ha-1
), Awgu (40.70 Mg ha-1
) and the least was Nsukka I (28.55 Mg ha-1
under cultivated land use. In uncultivated land use, SOC pool at 0-30 cm depth was highest in
Okigwe (80.51 Mg ha-1
), followed by Awgu (49.20 Mg ha-1
), Nsukka II (39.82 Mg ha-1
) in the
uncultivated soils as against Okigwe > Nsukka II > Awgu > Nsukka I in the cultivated soils.
There were no significant differences in SOC pool content between the two land uses at 0-30 cm
depth. However, land use significantly affected SOC pool content of Awgu and Nsukka II
locations, and had no significant influence on Okigwe and Nsukka I locations.
4.1.6 Land Use Effect on Aggregate Size Distribution, C, and N Contents of the Soils
Table 10 presents the effects of land use on water-stable aggregate (WSA) concentration
at the various soil depths, and at 0-30 cm depth. Generally, there was no significant effect on the
concentration of WSA between the two land uses, except at 0-10 cm and 0-30 cm depths, where
Table 9: Soil organic carbon (SOC) pool of cultivated and uncultivated soils at the various
-----------Depth (cm) ------------
Land use Location 0-10 10-20 20-30 Total Mean
--------------------------- (Mg ha-1
Cultivated Awgu 13.73 13.91 13.06 40.70 13.57
Okigwe 25.56 25.28 16.58 67.42
Nsukka I 11.29 8.21 9.05 28.55
Nsukka II 19.88 18.19 13.49 51.56
Mean 17.62 16.40 13.05 15.69
Uncultivated Awgu 17.69 18.84 12.67 49.20 16.40
Okigwe 30.87 30.59 19.05 80.51
Nsukka I 13.77 8.53 6.35 28.65
Nsukka II 16.03 13.49 10.03 39.82
Mean 19.59 17.86 12.03 16.52
LSD (0.05) Location effect (cultivated) = 3.27*
LSD (0.05) Location effect (uncultivated) = 4.46*
LSD (0.05) Depth effect (cultivated) = 3.27*
LSD (0.05) Depth effect (uncultivated) = 4.46*
LSD (0.05) Land use effect at 0-30 cm depth = NS
LSD (0.05) Land use effects at various depths = NS (at all depths)
LSD (0.05) Land use effects across locations at 0-30 cm depth: Awgu = 2.13*
Okigwe = NS
Nsukka I = NS
Nsukka II = 2.86*
* = Significant at 5% alpha level; NS = Not significant at 5% alpha level.
0-10 0-20 20-30
Soil depth (cm)
Fig. 2: Soil depth effects on soil organic carbon (SOC) pool of cultivated and uncultivated
only 0.50-1.00 mm WSA were significantly (P = 0.05) not affected by cultivation. Land use
effects on SOC concentration in WSA at the various soil depths is shown in Table 11. At the
topmost 0-10 cm depth, land use significantly (P = 0.05) influenced C concentration in 1.00-2.00
mm WSA while at 20-30 cm depth, significant difference (P = 0.05) existed only in 1.00-2.00
mm and 0.25-0.50 mm WSA. Land use effects on total nitrogen content in WSA at the various
soil depths is given in Table 12. The WSA fractions of 1.00-2.00 and 0.50-1.00 mm at 0-10 cm
depth were significantly reduced by cultivation. The influence of land use on SOC content of the
various WSA at 0-30 cm depth (Table 13) showed that, only 0.50-1.00 mm and < 0.25 mm WSA
fractions were significantly influenced by land use. Whereas cultivation reduced SOC associated
with 1.00-2.00 mm WSA, the reverse was the case with < 0.25 mm WSA. Land use significantly
affected TSN associated with 1.00-2.00 mm WSA at 0-30 cm depth (Table 14). Notably, also is
the increasing trend of N with decrease in the WSA classes. As such, N accumulated more in the
microaggregates than in macroaggregates. The C/N ratios associated with WSA at 0-30 cm depth
are low and decreased with decrease in WSA classes. Land use had no significant effect on the
C/N ratio of the WSA at 0-30 cm depth (Table 15). Result of the effect of land use on BD, > 2.00
mm WSA, MWD and GMWD of the soils at the various soil depths in Table 16 showed no
significant influence on the parameters considered
4.1.7 Soil Texture in Relation to Soil Organic Carbon Pool
Since SOC sequestration process is soil specific (Lal et al., 2007), the sampling depths
relative to soil textures across the locations were also considered (Table 17). Significant
difference (P = 0.05) existed among the five soil textures (clay, loam, sandy loam, clay loam, and
sandy clay loam). Clay loam sequestered the highest amount of SOC, while sandy clay loam soil
had the lowest amount. In fact, the trend follows thus; clay loam > clay > sandy loam > loam >
sandy clay loam. The differences in SOC pool due to soil texture may be related to the clay
content of the soil relative to silt and sand particle sizes (Table 4). Effects of soil texture on SOC
pool at different sampling depths indicated that SOC pool was most secluded at 10-20 cm depth,
followed by 0-10 cm and the least was at 20-30 cm depth as shown graphically in Fig. 3.
4.1.8 Relationship between Aggregate Stability Indices and Soil Properties
Correlation coefficients (r) among the various soil particle sizes, aggregate indices and
some selected properties of the soil under cultivated and uncultivated land uses are presented in
Table 18. In cultivated soils, there was no significant correlation between BD and any of the
variables considered. The properties that correlated significantly (P 0.05) with MWD included
Table 10: Land use effects on water-stable aggregate (WSA) concentration at the various
soil depths, and at 0-30 cm depth
------------------------------WSA (mm) ----------------------------
Depth/land use > 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
(A) 0-10 cm depth
Cultivated 51.34 16.00 11.02 7.71 13.93
Uncultivated 62.67 6.79 5.49 6.63 18.17
NS NS 4.58* NS NS
(B) 10-20 cm depth
Cultivated 40.91 17.88 14.03 10.51 16.67
Uncultivated 44.14 17.98 13.83 7.32 16.73
NS NS NS NS NS
(C) 20-30 cm depth
Cultivated 36.66 20.57 18.67 10.75 13.36
Uncultivated 44.00 21.01 13.83 7.81 13.35
LSD (0.05) NS NS NS NS NS
(D) 0-30 cm depth
Cultivated 42.97 18.15 14.57 9.65 14.66
Uncultivated 50.27 15.26 11.05 7.25 16.09
LSD (0.05) NS NS 3.46* NS NS
Table 11: Land use effects on soil organic carbon (SOC) content in water-stable aggregates
(WSA) at the various soil depths
(mm) -------------------------WSA (mm) ------------------------
Depth/land use whole SOC > 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
(A) 0-10 cm depth
Cultivated 12.30 11.75 9.20 9.70 8.95 9.45
Uncultivated 14.83 13.83 14.18 11.90 9.85 8.40
NS NS 3.18* NS NS NS
(B) 10-20 cm depth
Cultivated 11.38 9.23 8.80 8.63 8.63 8.95
Uncultivated 10.00 11.03 8.30 7.85 6.90 7.58
NS NS NS NS NS NS
(C) 20-30 cm depth
Cultivated 8.75 6.90 6.63 7.53 7.88 7.10
Uncultivated 8.00 7.63 7.95 6.43 6.18 5.73
NS NS 1.20* NS 1.50* NS
Table 12: Land use effects on total soil nitrogen (TSN) content in water-stable aggregates
(WSA) at the various soil depths
(mm) ------------------------WSA (mm) -------------------------
Depth/land use whole soil > 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
(A) 0-10 cm depth
Cultivated 1.33 1.65 1.48 1.95 2.28 3.03
Uncultivated 1.48 1.78 2.45 2.53 1.93 2.75
NS NS 0.42* 0.52* NS NS
(B) 10-20 cm depth
Cultivated 1.50 1.65 1.75 1.93 2.25 2.18
Uncultivated 1.28 1.63 1.55 2.28 2.48 2.80
NS NS NS NS NS NS
(C) 20-30 cm depth
Cultivated 1.20 1.48 1.50 1.88 1.98 2.60
Uncultivated 1.13 1.70 1.48 1.70 2.03 2.53
NS NS NS NS NS NS
Table 13: Land use effects on soil organic carbon (SOC) content in water-stable aggregates
(WSA) at 0-30 cm depth
(mm) ----------------------------WSA (mm) --------------------------
Land use whole soil > 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
Cultivated 10.81 9.29 8.21 8.62 8.48 8.50
10.94 10.83 10.14 8.73 7.64 7.23
Table 14: Land use effects on total soil nitrogen (TSN) content in water-stable aggregates
(WSA) at 0-30 cm depth
(mm) -------------------------- -WSA (mm) --------------------------
Land use whole soil > 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
Cultivated 1.34 1.59 1.58 1.92 2.17 2.60
Uncultivated 1.29 1.70 1.83 2.17 2.14 2.69
Table 15: Land use effects on C/N ratio of water-stable aggregates (WSA) at 0-30 cm depth
---------------------------------WSA (mm) -------------------------------
Land use > 2.00 1.00-2.00 0.50-1.00 0.25-0.50 < 0.25
Cultivated 5.84 5.37 4.64 3.90 3.73
Uncultivated 6.47 5.89 4.20 3.95 2.99
Table 16: Land use effects on bulk density, > 2.00 mm water stable aggregate (WSA), mean
weight diameter (MWD) and geometric mean weight diameter (GMWD) of the soils
Bulk density > 2.00 WSA
Depth/land use (Mg m-3
) (mm) MWD GMWD
(A) 0-10 cm
Cultivated 1.44 51.34 2.11 0.88
Uncultivated 1.34 62.67 2.32 0.84
NS NS NS NS
(B) 10-20 cm
Cultivated 1.44 40.91 1.84 0.85
Uncultivated 1.56 44.14 1.93 0.85
NS NS NS NS
(C) 20-30 cm
Cultivated 1.50 36.66 1.75 0.88
Uncultivated 1.51 44.00 1.96 0.88
NS NS NS NS
Table 17: Soil texture effects on soil organic carbon (SOC) pool at the various sampling
No. of location Depth occurrence
Soil texture SOC pool (Mg ha-1
) occurrence (cm)
Clay 20.30 1
Loam 14.50 1
Sandy loam 18.64 2
Clay loam 24.72 2
Sandy clay loam 13.51 4
LSD (0.05) 2.70*
clay loam sandy
clay loam sandy
Fig. 3: Soil texture effects on soil organic carbon (SOC) pool at the various soil depths.
macroporosity, WSA > 2.00, 1.00-2.00, 0.50-1.00, 0.25-0.50 and < 0.25 mm, GMWD, and SOC.
Among all the variables correlated, only DR correlated significantly (P = 0.05) with TSN. The
SOC positively correlated significantly (P 0.05) with WDC, microporosity, WSA > 2.00 mm,
and MWD; while negative significant (P 0.05) correlation was obtained between SOC and
1.00-2.00 mm, and 0.50-1.00 mm WSA. Soil organic carbon pool negatively correlated
significantly (P = 0.05) with DR and 0.05-1.00 mm WSA, but positively correlated significantly
with WDC, microporosity, > 2.00 mm WSA, MWD. The > 2.00 mm WSA negatively correlated
significantly (P = 0.01) with all the other WSA classes; and positively with MWD, and GMWD.
The 1.00-2.00 mm WSA negatively correlated significantly (P 0.05) with > 2.00 mm WSA,
and MWD, and positively with 0.50-1.00 mm WSA. The WSA class of 0.50-1.00 mm correlated
significantly with WSA classes of > 2.00 mm, 1.00-2.00 mm and 0.25- 0.50 mm, MWD, and
SOC. The properties that significantly correlated with 0.25-0.50 mm WSA include WDSi, macro
porosity, WSA classes of > 2.00, 0.50-1.00 and < 0.25 mm, MWD, and GMWD. The > 0.25 mm
WSA that positively correlated significantly with silt, WDSi, and 0.25-0.50 mm WSA, also had a
negative significant correlation with macro porosity, > 2.00 mm WSA, MWD, and GMWD.
Notably, among the major three soil separates, only silt positively correlated significantly (P =
0.05) with > 0.25 mm WSA. More so, all the WSA classes correlated significantly with either or
both of their neighboring WSA classes.
In uncultivated soils, whereas positive significant (P = 0.05) correlation was obtained
between BD and clay, and WDC; BD negatively correlated significantly with fine sand and
microporosity. The MWD correlated significantly (P 0.05) with silt, coarse sand, DR, WDSi,
soil moisture, GMWD, and all WSA classes except 1.00-2.00 mm fraction. The CDI and CFI
correlated significantly (P = 0.05) with TSN. SOC showed no significant correlation with any of
the variables considered. However, SOC pool positively correlated significantly (P = 0.05) with
ASC. The properties that significantly (P 0.05) correlated with > 2.00 mm WSA included silt,
coarse sand, DR, WDSi, soil moisture, WSA classes of 0.50-1.00, 0.25-0.50 and < 0.25 mm,
MWD, and GMWD. The 1.00-2.00 mm WSA significantly (P = 0.01) correlated negatively with
microporosity and positively with WSA class 0.50-1.00 mm. The 0.50-1.00 mm WSA positively
correlated significantly (P 0.05) with DR, WSA classes of 1.00-2.00 mm, and 0.25-0.50 mm, it
significantly correlated negatively with > 2.00 mm WSA, and MWD. The 0.25-0.50 mm WSA
correlated significantly (P 0.05) with silt, coarse sand, WDSi, GMWD, and > 2.00 mm, 0.50-
1.00 mm and < 0.25 mm WSA; while < 0.25 mm WSA correlated significantly (P = 0.01) with
silt, coarse sand, WDSi, soil moisture, MWD, GMWD, < 2.00 mm, and 0.25-0.50 mm WSA.
Table 18: Correlation coefficients (r) among particle sizes, aggregate indices and some
selected properties of the soil under cultivated land use
SOC -------------------WSA (%) ------------------
Variables BD MWD TSN SOC pool A B C D E
%clay 0.40 0.18 0.07 0.38 0.49 0.17 -0.13 -0.14 -0.05 -0.21
%silt -0.02 -0.34 -0.11 0.07 0.07 -0.26 -0.16 -0.08 0.52 0.70*
%Fsand -0.42 0.51 -0.33 -0.00 -0.10 0.49 -0.30 -0.31 -0.52 -0.54
%Csand 0.00 0.00 0.24 -0.44 -0.46 -0.08 0.46 0.38 -0.31 -0.41
CDI -0.38 0.33 0.22 0.35 0.24 0.32 -0.18 -0.32 -0.36 -0.23
DR -0.46 -0.09 -0.59* -0.51 -0.63* -0.05 -0.18 0.01 0.15 0.23
ASC 0.48 0.00 0.33 0.52 0.65* 0.01 -0.04 -0.14 0.11 0.09
CFI 0.38 -0.33 -0.22 -0.35 -0.24 -0.32 0.18 0.32 0.36 0.23
WDC -0.14 0.47 0.24 0.69* 0.65* 0.46 -0.31 -0.45 -0.38 -0.38
WDSi 0.04 -0.44 -0.38 -0.17 -0.15 -0.35 -0.17 0.02 0.67* 0.78**
Soilmoist 0.07 -0.38 -0.22 0.10 0.13 -0.32 -0.02 0.09 0.57 0.55
BD 1.00 -0.03 0.17 -0.20 0.02 -0.07 0.27 0.25 -0.11 -0.25
MacroP 0.35 0.65* 0.24 0.48 0.56 0.61 -0.28 -0.42 -0.62* -0.74**
MicroP -0.16 0.39 0.38 0.87** 0.85* 0.41 -0.36 -0.50 -0.26 -0.19
COLE 0.28 -0.36 0.07 0.22 0.31 -0.33 0.14 0.20 0.47 0.36
VS 0.29 -0.35 0.07 0.21 0.31 -0.33 0.14 0.20 0.47 0.35
WSA A -0.07 0.99** -0.23 0.63* 0.60* 1.00 -0.81** -0.91** -0.86** -0.73**
WSA B 0.27 -0.73** 0.43 -0.58* -0.52 -0.81** 1.00 0.93** 0.40 0.21
WSA C 0.25 -0.86** 0.28 -0.74** -0.68* -0.91** 0.93** 1.00 0.60* 0.40
WSA D -0.11 -0.91** 0.05 -0.43 -0.44 -0.86** 0.40 0.60* 1.00 0.94**
WSA E -0.25 -0.80** -0.06 -0.27 -0.31 -0.73** 0.21 0.40 0.94** 1.00
MWD -0.03 1.00 -0.18 0.60* 0.58* 0.99** -0.73** -0.86** -0.91** -0.80**
GMWD 0.23 0.81** 0.07 0.28 0.31 0.74** -0.22 -0.41 -0.93** -1.00**
%Fsand = % fine sand, %Csand = % coarse sand, CDI = clay dispersion index; DR = dispersion
ratio; ASC = aggregated silt and clay; CFI = Clay flocculation index; WDC = water dispersible
clay; WDSi = water dispersible silt; Soilmoist = soil moisture; BD = bulk density; MacroP =
macroporosity; MicroP = microporosity; TotalP = total porosity; COLE = coefficient of linear
extensiblilty; VS = volumetric shrinkage; WSA A, B, C, D, E = water-stable aggregate > 2.00,
1.00-2.00, 0.50-1.00, 0.25-0.50 and < 0.25 mm respectively; MWD = mean weight diameter;
GMWD = geometric mean weight diameter; SOC = soil organic carbon, TSN = total soil
*, ** = Significant at 0.01 and 0.05 alpha level (2-tailed), respectively.
Table 18 continuation: Correlation coefficients (r) among particle sizes, aggregate indices
and some selected properties of the soil under uncultivated land use
SOC ------------------WSA (%) --------------------
Variables BD MWD TSN SOC pool A B C D E
%clay 0.60* -0.26 -0.33 -0.15 0.11 -0.28 0.24 0.28 0.12 0.21
%silt -0.20 -0.68* 0.28 0.49 0.52 -0.61* -0.08 0.27 0.63* 0.82**
%Fsand -0.63* -0.45 -0.14 -0.09 -0.17 -0.44 0.13 0.24 0.36 0.50
%Csand 0.11 0.76** -0.00 -0.24 -0.35 0.72** -0.10 -0.40 -0.63* -0.86**
CDI 0.17 -0.14 0.69* 0.55 0.49 -0.13 0.07 0.07 0.19 0.10
DR -0.30 -0.69** -0.42 -0.39 -0.38 -0.70* 0.36 0.64* 0.73** 0.55
ASC 0.48 0.06 0.34 0.52 0.66* 0.09 -0.18 -0.18 -0.16 0.07
CFI -0.17 0.14 -0.69* -0.55 -0.49 0.13 -0.07 -0.07 -0.19 -0.10
WDC 0.69* -0.33 0.14 0.19 0.39 -0.34 0.26 0.28 0.26 0.26
WDSi -0.31 -0.86** -0.14 0.09 0.17 -0.80** 0.07 0.49 0.78** 0.94**
Soilmoist -0.27 -0.68* 0.18 0.48 0.51 -0.61* -0.04 0.32 0.57 0.80**
BD 1.00 0.11 -0.13 -0.19 0.10 0.05 0.36 0.16 -0.18 -0.30
MacroP 0.02 -0.03 -0.17 0.23 0.24 0.03 -0.50 -0.08 0.14 0.21
MicroP -0.61* 0.05 0.22 0.58 0.48 0.17 -0.80** -0.46 -0.05 0.36
COLE 0.26 -0.39 -0.04 0.26 0.43 -0.38 0.10 0.28 0.27 0.41
VS 0.26 -0.39 -0.04 0.25 0.43 -0.37 0.10 0.29 0.27 0.40
WSA A 0.05 0.99** 0.26 0.31 0.21 1.00 -0.57 -0.86** -0.93** -0.81**
WSA B 0.36 -0.45 -0.16 -0.55 -0.45 -0.57 1.00 0.80** 0.35 0.01
WSA C 0.16 -0.79** -0.35 -0.48 -0.36 -0.86** 0.80** 1.00 0.75** 0.43
WSA D -0.18 -0.94** -0.30 -0.25 -0.25 -0.93** 0.35 0.75* 1.00 0.82**
WSA E -0.31 -0.88** -0.12 0.05 0.11 -0.81** 0.01 0.43 0.82** 1.00
MWD 0.11 1.00 0.24 0.23 0.14 0.99** -0.45 -0.79** -0.94** -0.88**
GMWD 0.31 0.87** 0.13 -0.06 -0.12 0.80** 0.01 -0.42 -0.81** -1.00**
%Fsand = % fine sand, %Csand = % coarse sand, CDI = clay dispersion index; DR = dispersion
ratio; ASC = aggregated silt and clay; CFI = Clay flocculation index; WDC = water dispersible
clay; WDSi = water dispersible silt; Soilmoist = soil moisture; BD = bulk density; MacroP =
macroporosity; MicroP = microporosity; TotalP = total porosity; COLE = coefficient of linear
extensiblilty; VS = volumetric shrinkage; WSA A, B, C, D, E = water-stable aggregate > 2.00,
1.00-2.00, 0.50-1.00, 0.25-0.50 and < 0.25 mm respectively; MWD = mean weight diameter;
GMWD = geometric mean weight diameter; SOC = soil organic carbon, TSN = total soil
*, ** = Significant at 0.01 and 0.05 alpha level (2-tailed), respectively.
Table 19 shows the correlation coefficients (r) of the soils chemical properties and SOC
pool under the two land uses. SOC content positively correlated significantly with soil pH,
exchangeable K+, and C/N ratio of the cultivated soils; but positively correlated significantly (P =
0.05) with total N, and exchangeable Na+
in uncultivated land use. Also, a negative significant
correlation was obtained between SOC and CEC in uncultivated soils. In cultivated soils,
whereas SOC pool highly correlated significantly (P = 0.01) with soil pH, SOC, exchangeable
K+, and C/N ratio; a positive significant (P 0.05) correlation was obtained with SOC, and
exchangeable Na+, and negatively with CEC of uncultivated soils.
In view of the notable contributions of some variables that correlated significantly with
SOC, regression analysis was performed on the selected structural stability indices to show their
relationship with SOC (Table 20). In cultivated land use, SOC explained significantly (P = 0.05)
39 % and 34 % of the variation in WSA classes of > 2.00 mm and 1.00-2.00 mm, and 54 % in
1.00-0.50 mm WSA. Whereas SOC significantly predicted 36 % of the variation in MWD
content, it could only explain 48 % of WDC variability. The variability in micro porosity was
largely due to the effect of SOC which predicted significantly up to 76 % of the variation. Unlike
in cultivated land use, SOC content predicted non significant low values as a measure of the
variability in the dependent variables of uncultivated soils.
Table 19: Correlation coefficients (r) of the soils chemical properties and soil organic
carbon (SOC) pool of cultivated and uncultivated land uses
Independent variables SOC SOC pool SOC SOC pool
--------------------Correlation coefficient (r) ---------------------
Soil pH 0.70* 0.73** 0.38 0.36
SOC (%) 1.00 0.97** 1.00 0.91**
Total N (%) 0.12 0.15 0.68* 0.57
(cmol/kg) -0.20 -0.18 0.66* 0.65*
(cmol/kg) 0.79** 0.80** 0.46 0.55
(cmol/kg) 0.40 0.39 0.11 0.13
(cmol/kg) 0.34 0.42 0.41 0.41
(cmol/kg) -0.07 0.01 0.32 0.54
CEC (cmol/kg) 0.11 0.10 -0.58* -0.60*
C/N ratio 0.86** 0.81** 0.53 0.51
*, ** = Significant at 0.01 and 0.05 alpha level (2-tailed) respectively.
Table 20: Relationship between soil organic carbon (X) and some structural stability indices
(Y) in cultivated and uncultivated land uses (n = 12)
----------------------Land uses --------------------------
----------Cultivated ------------ -----------Uncultivated-----------
Dependent variables (Y) Regression model R2 Regression model R
WSA: > 2.00 (mm) Y = -6.28 + 4.56X 0.39* Y = 30.76 + 1.78X 0.09ns
WSA: 1.00-2.00 (mm) Y = 34.17 1.48X 0.34* Y = 26.07 0.99X 0.31ns
WSA: 1.00-0.50 (mm) Y = 33.35 1.74X 0.54* Y = 18.51 0.68X 0.23ns
WSA: 0.05-0.25 (mm) Y = 17.37 0.71X 0.19ns
Y = 10.28 0.28X 0.06ns
WSA: < 0.25 (mm) Y = 21.40 0.62X 0.07ns
Y = 14.38 + 0.16X 0.00ns
MWD Y = 0.63 + 0.12X 0.36* Y = 1.65 + 0.04X 0.05ns
WDC Y = 4.42 + 0.67X 0.48* Y = 9.68 + 0.13X 0.04ns
Micro porosity (%) Y = 26.97 + 2.02X 0.76* Y =39.28 + 0.54X 0.33ns
* = significant at 0.05 alpha level, ns = non significant.
The clay content of the soils is moderately low when compared with the total sand
fraction. The clay distribution with depth indicated some form of eluviation and illuviation.
Among the particle size classes, sand fraction dominates with silt being the least which is more
evident in soils of Nsukka locations. Akamigbo (1984) attributed this to the nature of the parent
material and mineralogy of the soils. However, silt content of Awgu soil is relatively high when
compared with similar soil (Okigwe) of the same agroecological zone. This could have resulted
from flow of silt materials from the adjacent river because of its proximity to the sites where the
soil was sampled. Igwe et al. (1995) showed that pedologically, high silt content may be related
to mud flow and silt materials from river deposits and the underlying geological materials.
The pH of the soils was slightly acidic and as such contributed significantly to the low
OM content of the soils. This is in line with the findings of Hillel (1982), which indicated that
acidic condition incapacitates soil microorganisms from producing different kinds of OM which
enhances the aggregate stability of the soils. The low SOC contents may be attributed to leaching
and high erodibility of the soils as a result of high rainfall intensity (Igwe, 2005). Evans (1980)
pointed out that erodible soils are mainly sandy loams and loamy sands. The soil of Nsukka I,
which fell within the sandy loam textural class at 0-10 cm depth (Table 3), also recorded the
lowest SOC content showing that it is potentially erodible. Remarkably, SOC content increased
with increase in clay content and WDC. Emerson (1971) indicated that low SOC causes severe
dispersion of clay in water. Thus, low SOM enhances dispersion, and this affects the soil
potential for interrill erosion and runoff during storms. The low exchangeable cations content of
the soils could be due to excessive precipitation, which causes considerable loss of nutrient
elements through erosion and leaching.
All the parameters listed in Table 6 are estimates of soil structural stability indices.
Whereas CDI, DR, WDC, WDSi estimate the rate of dispersibility (instability) of the soils, CFI
and ASC are indices of stability for microaggregates, hence higher values of CFI and ASC imply
higher or better stability (Igwe et al., 2009), and higher values of DR and CDI imply lower
stability (Igwe et al., 1999). With CFI value of > 50 % and low DR, WDC and WDSi, the soils of
the four locations are moderately stable and less dispersive which may be attributed to their
underlying parent material. Igwe et al. (2009) reported similar observation and indicated that
soils with low to moderate DR, and low WDC and WDSi are stable and less erodible. However,
the moderate WDSi obtained in Awgu could be as a result of silt materials from river deposits. It
is worthy to note the relative contribution of % clay to aggregate stability since it follows the
same trend with WDC. Therefore, it can be deduced that increase in clay content increases the
rate of clay dispersion in water. Nikos et al. (2002) pointed out that clay is inherently more prone
to dispersion than are silts and sands. Also, Boix-Fayos et al. (2001) observed a positive
correlation between water stability of microaggregates and clay content. This is because clay
upon wetting swell, slake or disperse. This supports the argument that swelling is a precursor to
particle dispersion, which is dependent on the clay content of a soil (Emerson and Bakker, 1973).
The variation in WSA fractions obtained among the locations, soil depths and across land
uses could be due to differences in OC content (Castro et al., 2002) and the MWD of the soils.
With the exception of Okigwe and Nsukka II soils, which had comparatively moderate to high
concentration of > 2.00 mm WSA at 0-30 cm soil depth, the other two locations exhibited high
rate of macroaggregate instability in water which is also evident in the low values of MWD
obtained in both land uses. More so, a positive significant correlation was obtained between
MWD and > 2.00 mm WSA as opposed to the negative correlation between MWD and with all
other classes of WSA in both land uses (Table 18). In Table 10, only 0.50-1.00 mm WSA was
significantly influenced by land use at 0-10 cm and 0-30 cm soil depth. This suggests that
cultivation did not affect the stability of microaggregates since the amount is greater in cultivated
than in uncultivated soils. This confirms the observation that reductions in aggregate stability
after cultivation are most pronounced in soil macroaggregates, while the stability of
microaggregates remains unchanged (Tisdall and Oades, 1982; Oades, 1984).
Great variations exist in SOC and TSN associated with WSA classes and C/N ratios of
the soils. In SOC associated with WSA, whereas 1.00-2.00 mm WSA at 0-10 cm and 20-30 cm,
including the 0.25-0.50 mm WSA at 20-30 cm were significantly affected by land use, 1.00-2.00
mm and < 0.25 mm were significantly influenced at 0-30 cm soil depth. The reduction of SOC in
> 2.00 mm to 0.50-1.00 mm WSA of cultivated soils may be due to effect of tillage which
disaggregates the soil particles and increases oxidation of SOM thereby leading to C loss through
erosion, leaching or emission to the atmosphere. Research findings in confirmation to this
abound in literature (Mokma and Sietz (1992); Six et al. (1999); Lal et al. (2007); Wright and
Hons (2005); Lal and Kimble (2000); Paustina et al. (2000), and Follett (2001). The variation
may also be attributed to the quantity and quality of SOC, including the differences in soil types
(Tisdall and Oades, 1982; Saggar et al., 2001; Mbagwu and Bazzoffi, 1989). Feller and Beare
(1997) were of the view that soil aggregation, texture and mineralogy control OM in
macroaggregates. Notably, although the low C content in 1.00-2.00 mm WSA of the cultivated
soils was expected, the reverse was the case with 0.25-0.50 mm and < 0.25 mm WSA. The SOC
content generally increased in the fraction of 0.25-0.50 mm and < 0.25 mm WSA at all depths
and significantly at 20-30 cm and 0-30 cm soil depths which indicates associations such as
organo-silt complexes and organo-clay fractions (Feller, 1994), and hence more stabilization of
SOC. Although, it is generally agreed that cultivation causes a decrease of SOC (Alvarez et al.,
1998); one is uncertain why this is the case, but, a positive significant correlation was obtained
between % silt and 0.25-0.50 mm, and < 0.25 mm WSA (Table 18). Whereas Dormarr (1983)
and Mbagwu and Piccolo (1990) reported higher concentration of C in macroaggregates than
microaggregates, Christensen and Sorensen (1985) reported otherwise. Similarly, in TSN
associated WSA, 1.00-2.00 mm and 0.50-1.00 mm WSA were significantly affected by land use
at 0-10 cm soil depth, and only 1.00-2.00 mm was influenced at 0-30 cm soil depth. The results
suggest that C and N associated with 1.00-2.00 mm WSA are mostly lost may be as a result of
increased decomposition and erosion rate due to change in aggregate structure associated with
cultivation. The earlier assertions by Beare et al. (1994), Coote and Ramsey (1983), and
Cambardella and Elliott (1994) support this observation. Therefore, whereas > 1.00 mm WSA at
0-30 cm soil depth contained about 8.20 to 9.30 g kg-1
C / 1.58 to 1.59 g kg-1
N and 10.10 to
10.80 g kg-1
C / 1.70 to 1.83 g kg-1
N in cultivated and uncultivated soils respectively; < 1.00 mm
WSA contained 8.50 to 8.60 g kg-1
C / 1.92 to 2.60 g kg-1
N and 7.20 to 8.70 g kg-1
C / 2.14 to
2.69 g kg-1
N, in cultivated and uncultivated soils, respectively.
The N content of the soils was far much lower when compared with C content. The C/N
ratios of the soils were generally low, although higher at 0-10 cm when compared with the other
depths. This suggests that the availability of N in the top most surface layers is not a key
component for reducing C losses and increasing the SOC content. The decreasing trend observed
in the C/N ratio associated with the WSA from > 2.00 mm to < 0.25 mm indicated that microbial
alteration of soil OM was more associated with the microaggregates than the macroaggregates
(Monrozier et al., 1991). S et al. (2001) observed lower C/N ratios in 2- to 20- m and < 2- m
fractions than in larger sized fractions and suggested that 40 to 60 % of the microbial biomass
may be associated with the microaggregates 2- to 20- m, depending on the amount and type of
clay. More so, under tropical forest and savanna conditions, bacterial cell walls or colonies at
different stages of decomposition can be observed in fractions < 20 m. Hence, the low C/N ratio
observed in the finer-size fractions would be an indication that SOM was more stabilized and
more aromatic (Bayer et al., 2000).
The SOC pool significantly decreased with soil depth, as such, SOC pool was highest at
the topmost soil surface (0-10 cm). This could be as a result of high C input, biomass activity at
the soil surface and consequent fast C turnover rate in tropical soils. These results are in
conformity with the earlier assertions by Lal (2004), Lal et al. (2007), Six et al. (2002) and Six et
al. (1999). Resck (1998) and S (1993) observed a significant impact on SOC concentrations for
0-10 cm soil layer; also Carter (1992) reported increase in SOC content at the surface soil. From
the observation, SOC pool at 20-30 cm soil depth was higher in cultivated than in uncultivated
soils. This may be as a result of anthropogenic disturbance of soil structure during tillage in
preparation of the land for cultivation, which inverts and mixes the soil hence altering the
distribution of C by incorporating the organic materials on the soil surface to the subsoil where it
would not be easily lost (Potter et al., 1997). The reason for the higher SOC pool obtained in
cultivated soils of Nsukka II than in uncultivated land use could be attributed to the sloping
landscape position of the location due to soil erosion and leaching (Hall, 1983). Thus, whereas
cultivated soils contained an average of 15.69 Mg ha-1
C, uncultivated soils had an average of
16.52 Mg ha-1
C. The non significant difference in SOC pool obtained between both land uses is
thought to may have resulted from the following factors: (i) the low rate of biomass production,
C input and mineralization (Lal and Kimble, 2000; Lal et al., 2007); (ii) the short period of time
(4-5 yrs) the uncultivated land had been on fallow of which the rate of residue input did not
compensate the high losses of organic matter due to mineralization (S et al., 2001; Harrison et
al., 1990; Lobo et al., 1990); (iii) low C conversion efficiency due to low N content (Knops and
Tilman (2000); Lal, 1999); and (iv) increased rate of C loss through erosion (Tans et al., 1990).
Therefore, loss of C (Mg ha-1
) caused by cultivation amounted to 10 % and 9 % at 0-10 cm and
10-20 cm soil depth respectively, with an average of 5 % at 0-30 cm.
The results obtained from this study showed that across all the depths, cultivated soils as a
result of tillage disintegrated the > 1.00 mm WSA, which contained the highest amount of C
since SOC decreased with decrease in soil particle sizes (Table 13). Hence, SOC was
significantly reduced in 1.00-2.00 mm WSA at 0-10 cm and 20-30 cm soil depths (Table 11).
Therefore, the role of soil as a C sink in mitigating climatic change can only be enhanced if the
rate of macro- and micro- aggregates disruption is minimized. The practice of soil tillage as is
obtained in most parts of southeastern Nigeria should be replaced with adoption of recommended
soil management practices such as no-till or reduced tillage, increased crop rotation intensity, use
of cover crops, residue mulching, addition of organic manure, etc to promote C sequestration,
thereby reducing agriculture related CO2 emissions and consequently mitigating global warming
(Denef et al., 2004; Doran, 1980; Kern and Johnson, 1993). More so, selection of varieties and
hybrids that store more C for cultivation will strengthen C sinks in the soil.
In considering SOC pool in relation to soil texture, clay loam sequestered the highest
SOC while sandy clay loam sequestered the least. The reason for this could be related to their
clay content and possibly, the clay type which was not considered in this study. Since the
increase in SOC pool followed the same trend with clay content, it can be deduced that SOC is a
function of clay content. Hence, increase in clay content increases the rate of SOC sequestration.
Batjes (1998) showed that clay, soil acidity amidst others were among the major environmental
factors that control the behaviour of OM in the soil. Also in Table 19, soil pH positively
correlated significantly with SOC pool where r = 0.73 in cultivated soils. Coote and Ramsey
(1983), and Nichols (1984) obtained a positive relationship between % clay and SOM.
The significant correlation of SOC with WDC, micro porosity, WSA > 2.00 mm, and
MWD indicated the relative importance of SOC to these properties; hence increase in SOC
content resulted in improved rate of aggregation. Also, the significant correlation between SOC
pool and these properties, including DR, ASC, 0.50-1.00 mm WSA, and SOC confirms their
contributions to the improvement of SOC pool accumulation and stabilization. Thus, the positive
significant correlation between SOC/SOC pool and > 2.00 mm WSA is an indication that more
than 60 % SOC may be associated with > 2.00 mm WSA in cultivated soils. The SOC accounted
for about 70 to 90 % of the variability in soil aggregate stability of a clay loam soil (Mbagwu and
Bazzoffi, 1989). Therefore, decreased proportion of WSA classes of < 1.00 mm enhanced SOC
accumulation and possible stabilization in > 2.00 mm within the top soil (0-30 cm). Similarly, the
highly significant correlation between MWD and macroporosity and with all the WSA classes
indicates the relative importance of MWD to the improvement of the structural stability of the
soil. The relation between SOC and soil chemical properties indicates that, whereas soil pH,
exchangeable K+ and C/N ratio appear to be the most contributing factors to SOC improvement
in cultivated land use, total N, exchangeable Na+ and CEC could be responsible for SOC
accumulation in uncultivated land use. Gerding (1991) reported a strong correlation between
SOC pool in the surface layer (30 cm depth) and the N and Ca 2+
content of the soil.
Regression analysis showed that SOC significantly accounted for < 40 % of the
variability in > 1.00 mm WSA. This shows that although SOC is important in the aggregation of
these WSA, other cementing agents than C are equally involved in the stability of
macroaggregates of cultivated soils. Mbagwu (1989) reported that the role of SOC as an
aggregating agent diminishes in the presence of other dominating aggregating agents, such as
polyvalent metals and silicate clay. Remarkably, the non significant effect of SOC on the
variability in 0.05-0.25 mm and < 0.25 mm WSA under both land uses indicates that SOC does
not contribute to the instability of these aggregates. However, SOC became more influential and
was able to explain up to 54 % and 76 % of the variability in 1.00-0.50 mm WSA and
microporosity, respectively (Table 20).
SUMMARY, CONCLUSION AND RECOMMENDATION
The main aim of this study was to assess the potential of various aggregate size fractions
of varying soil textures and depths to sequester C under different land uses. The hypothesis was
that SOC sequestration is a function of soil texture and soil aggregation; and that SOC is similar
between soil phases (cultivated and uncultivated) of the same soil series. The data presented
support the first hypothesis, and rendered the second invalid. The results showed that great
variations exist in SOC, TSN and C/N ratio associated with WSA classes of the cultivated and
uncultivated soils. The N content of the soils was far much lower when compared with C content.
The C/N ratios of the soils were also, generally lower although higher at 0-10 cm. At 0-30 cm
soil depth, SOC content increased with increase in WSA of uncultivated soils, but in cultivated
soils, > 2.00 mm WSA sequestered the highest C, followed by 0.50-1.00 mm, 0.25-0.50 mm and
< 0.25 mm, while the least was 1.00-2.00 mm WSA. Hence, > 2.00 mm WSA contained the
highest concentration of SOC in both soil phases. Land use affected SOC concentration in 1.00-
2.00 mm and < 0.25 mm WSA at 0-30 cm depth; SOC in 1.00-2.00 mm WSA at 0-10 cm; and
SOC in 1.00-2.00 mm and 0.25-0.50 mm WSA at 20-30 cm soil depth. Unlike in SOC, TSN
associated with WSA was more in < 1.00 mm WSA than in > 1.00 mm WSA: it (generally)
increased with decrease in WSA classes at 0-30 cm depth and varied significantly in the 1.00-
2.00 mm WSA between the soil phases. The 1.00-2.00 mm and 0.50-1.00 mm WSA were
significantly affected by land use at 0-10 cm soil depth. Therefore, whereas > 1.00 mm WSA at
0-30 cm soil depth contained 8.20 to 9.30 g kg-1
C / 1.58 to 1.59 g kg-1
N and 10.10 to 10.80 g kg-
1 C / 1.70 to 1.83 g kg
-1 N in cultivated and uncultivated soils, respectively, < 1.00 mm WSA
contained 8.50 to 8.60 g kg-1
C / 1.92 to 2.60 g kg-1
N and 7.20 to 8.70 g kg-1
C / 2.14 to 2.69 g
N in cultivated and uncultivated soils, respectively.
Soil depth exerted a strong influence on the spatial distribution of SOC pool, unlike land
use that did not show any significant effect on SOC pool. In both cultivated and uncultivated
soils, SOC pool significantly decreased with soil depth; hence highest SOC pool was observed at
0-10 cm soil depth. Soil organic carbon content to the depth of 30 cm differed distinctly among
the study sites. Uncultivated soils recorded higher SOC than the cultivated soils except at 20-30
cm depth which may be due to structural alteration of C distribution resulting from anthropogenic
disturbance. Hence, loss of C caused by cultivation amounted to 10 % and 9 % at 0-10 cm and
10-20 cm soil depth respectively, with an average of 5 % at 0-30 cm.
The rate of C sequestration differed significantly (P = 0.05) with soil texture across soil
depths and land uses. The trend followed thus; clay loam > clay > sandy loam > loam > sandy
clay loam. Among the three sampled depths, soil texture effects on SOC pool indicated that SOC
was most sequestered at 10-20 cm depth, followed by 0-10 cm and the least at 20-30 cm depth.
Finally, whereas WDC, micro porosity, MWD, soil pH, K+, C/N ratio, > 2.00 mm, 1.00-2.00
mm, and 0.50-1.00 mm WSA significantly correlated with SOC concentration in cultivated soils;
only Na+, N, and CEC significantly correlated with SOC concentration in uncultivated soils thus
indicating the relative contribution of these properties to C accumulation and stabilization. Soil
organic carbon accounted for 54 % and 76 % of the variability in micro aggregates and micro
porosity (respectively) of the cultivated soil, but could not significantly account for that in
uncultivated land use.
In conclusion, SOC sequestration is a function of soil texture, depth and aggregation.
Cultivation does not affect the stability of microaggregates; however, the effect of cultivation as
a result of tillage to the depth of 30 cm promotes macroaggregate breakdown and consequent loss
of SOC to the atmosphere which could accelerate global warming. The C and N associated with
1.00-2.00 mm WSA are mostly lost as a result of increased decomposition and erosion rate due to
change in aggregate structure associated with cultivation. Notably, high proportion of clay
content in soils, and prolonged land fallow may increase the rate of carbon sequestration in soils.
Therefore, for the potentially erodible soils of southeastern Nigeria, substantial C sink might be
achieved if the rate of macro- and micro- aggregates disruption is minimized. Also, the adoption
of recommended soil management practices such as no-till or reduced tillage, use of cover crops,
residue mulching, addition of organic manure, etc will not only increase soil fertility but also will
reduce agricultural related CO2 emissions and consequently, mitigate climatic change.
Although this study has succeeded in quantifying SOC pool and understanding the
distribution of SOC and TSN across aggregate size classes as stratified by land use, soil texture,
and soil depth of some soils of southeastern Nigeria, there is still the need for more advanced
research using physical fractionation techniques of particulate organic matter to identify how
aggregation under forest vegetation or other soil management systems contribute to SOC pools
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Appendix 1: Final analysis of variance of a 4 x 2 x 3 factorial experiment in CRD showing
sources of variation and degree of freedom only
Source of Variation d.f.
Factor A (Location) 3
Factor B (Land use) 1
Factor C (Soil depth) 2
A x B 3
A x C 6
B x C 2
A x B x C 6