University of Nigeria · as losses of soil organic matter (SOM) and aggregate stability. However,...

University of Nigeria Research Publications

Aut

hor

OGUIKE, Paul chukwudi

PG/PhD/98/25998

Title

Aggregate Stability of Soils of Coastal Plain sand in Owerri, Southeastern Nigeria in Relation to their

Contents of Carbohydrates and Human Substances

Facu

lty

Agriculture

Dep

artm

ent

Soil Science

Dat

e

March, 2008

Sign

atur

e

AGGREGATE STABILITY OF SOILS OF COASTAL PLAIN '

SAND IN OWERRI, SOUTHEASTERN NIGERIA, IN I

RELATION TO THEIR CONTENTS OF CARBOHYDRATES AND HUMlC SUBSTANCES.

OGUIKE, PAUL CHUKWDI PG/Ph.D/98/25998

A THESIS SUBMITTED TO THE DEPARTMENT OF SOIL SCIENCE, FACULTY OF AGRICULTURE, UNIVERSITY OF NIGERIA, NSUKKA,

IN PARTLAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF DOCTOR OF PHILOSOPHY (Ph.D) IN

SOIL PHYSICS/CONSERVATION.

MARCH, 2008.

CERTIFICATION

OGUIKE, PAUL CHUKWUDI, a Ph.D Student in the Department of Soil

Science with registration number PG/Ph.D/98/25998, has completed the

requirements for the degree of Doctor of Philosophy (Ph.D) in Soil Science.

The work embodied in this thesis 'is original and has not been

published or submitted in part or in full for the degre? of this or any other

University.

~ r o f ; / ~ . S. C. Mbagwu (Supervisor) ('JAead of Department)

DEDICATION

To the memories o f Anthony A. Oguike, Emma 0. H. Oguike, other departed

members of the Oguike extended family, and also, Pa Jonathan Nwaorgu

and his son, Emma C. Nwaorgu.

ACKNOWLEDGEMENT

I am grateful to all those who, in any way, contributed to the successful

completion of this work.

I n no way will I be able to pay Prof. J. S. C. Mbagwu for his kindness

towards me. "Prof." was very patient with me and this was an invaluable

experience. "Prof." I pray God to bless you, your wife and children. You

supervised this work and every success in it is due to you while all the errors

are mine.

I immensely thank Prof. C. A. Igwe and Mr. C. J. Onyirioha who led me

through the field and laboratory works, respectively. I owe a lot of gratitude

to all the other Professors and Lecturers in the Department of Soil Science

for their individual and collective contributions to this work. They include

Professors F. 0. R. Akamigbo, M. E. Obi, N. N. Agbim, C. L. A. Asadu, C. C.

Mba and Mr. C. Jidere. The list did not follow,any particular order.

G. 0. Oko-Ibom deserves a special mention here because, in addition to

academic discussions we held, he made my stay in Nsukka comfortable.

P. 3 . Nwaorgu and his brother, Felix-George are wonderful people who must

be acknowledged for their views during the course of this work.

I am indebted to my mother, Mrs. Janet N. Oguike and my other sisters,

Ndaa Julie, Rev. Sr . Dl-. Mary Anthony Oguike and Lucy, for their moral and

financial supports.

I thank my wife, Lynda, and my children, Chioma, Okechukwu and Chisom

for understanding that I needed time to complete this work. Above all, I am

grateful to God.

TABLE OF CONTENTS

TITLE PAGE ... ... ... ...

CERTIFICATION ... ... ...

DEDICATION ... ... ...

ACKNOWLEDGEMENT ... ...

TABLE OF CONTENTS ...

LIST Of TABLES ... ...

ABSTRACT ... ... ...

CHAPTER ONE

Introduction ...

CHAPTER TWO

Literature Review ...

Soils of Coastal Plains

I Distribution and Land Use

2.1.2 Effect of Land Use on Soil Properties ...

2.1.3 Characteristics of Soils of Coastal Plains ...

2.1.3.1 Texture ... ... ... ... ... ...

... 2.1.3.2 Structure ... ... ... ... ...

2.1.3.3 Water Retention ... ... ... ...

2 .I . 3.4 Hydraulic Conductivity ... ... ...

2.1.3.5 Exchange Properties ... ... ... ...

2.1.3.6 Organic Matter, Nitrogen and Phosphorus

... ... ... ... 2.2 Soil Degradation

2.2.1 Types and Causes of Degradation ... ...

2.2.1.1 Erosion ... ... ... ... ... ...

2.2.1.2 Structural Degradation ... ... ...

2.2.1.3 Loss of Organic Matter and Nutrients ...

PAGE

i . . I i

... I i i

iv

v 1

IX

xii

1

5

6

6

10

12

12

12

13

14

15

16

17

18

18

19

22

2.2. I . 4 Accumulation of Toxicities (Salinization and

Acidification) . . . . . . ... ... ... ... ... 23

2.3 Soil Organic Matter ...... ... ... ... ... ... 25

... 2.3.1 ComponentsofSoilOrganicMatter ... ... 26

2.3.1.1 Carbohydrate and their Role in Aggregate Stability ... 27

2.3.1.2 Humic Substances ...... ... ... ... ... ... 30

... 2.3.1.2.1 Characteristics of Humic Substances ... ... 30

... 2.3.1.2.2 Humic Substances and Soil Aggregation ... 33

2.4 Need for further studies ... ... ... ... ... 36

CHAPTER THREE

3.0 Materials and Methods ... ... ... ... ... ... 37

... ... 3.1 The Physical Environment ... ... ... 37

3.2 Field and Laboratory Studies ... ... ... ... ... 39

3.2.1 Top Soil Samples ... ... ... ... ... ... ... 39

3.2.2 Profilesamples ... ... ... ... ... ... ... 40

... ... ... ... ... Statistical Analysis ... ... 46

CHAPTER FOUR

Results and Discussions ... ... ... ... ... ... 47

Particle Size Distribution ... ... ... ... ... 47

Aggregate Stability Indices ... ... ... ... ... 5 1

Water Retention Characteristics ... ... ... ... 55

Bulk Density. Porosity Characteristics and Saturated

Hydraulic Conductivity ... ... ... ... ... ... 57

Exchange Properties of Topsoil from Different land Use

... ... Types ... ... ... ... ... ... ... 60

pH, Organic Matter, Total Nitrogen and Available Phosphorus

of Top soils Sampled ... ... ... ... ... ... 63

... ... ... Organic Matter Fractions ... ... 66

... V l l l

4.8 Correlation between Aggregate Stability Indices and some

Physico-Chemical Properties of Soils under Different Land

Use Types ... . . . ... . . . ... ... . . . ...

4.9 Principal Component Analysis of Soil Properties Influencing

Aggregate Stability under Different Land Use Types ...

4.9.1 Principal Component Analysis of Soil under the four year

bush fallow land ... . . . . . . ... . . . ... ... ...

4.9.2 Principal Component Analysis of Soil under grass vegetation

land ... ... . . . ... ... . . . ... ... ... ...

4.9.3 Principal Component Analysis of Soil under continuously

cultivated land ... ... ... . . . . . . . . . ... . . .

4.9.4 Principal Component Analysis of Soil under forest vegetation

land ... . . . ... ... ... .-. ... ... ... . . .

4.9.5 Principal Component Analysis of'Soil under one-year cassava

farm land ... . . . . . . . . . ... ...

CHAPTER FIVE

5.0 Summary, Conclusions and recommendations

5 . 1 Summary ... ... ... ... ...

5.2 Conclusions . . . . . . . . . ... ...

5.3 Recommendations ... . . . . . . . . .

REFERENCES . . . -. - . . . -.. . . .

APPENDIX ... ... ... ... ...

LIST OF TABLES

TABLE PAGE

Some physical properties of profiles under different land use types

Some chemical properties of profiles under different land use types

Mean values of particle size distribution of top(0-20)soil - -

Aggregate stability indices - - - - - -

Water retention characteristics

Bulk density, porosity characteristics and saturated hydraulic

conductivity - - - -

Mean values of exchange properties of top(0-20cm)soil - -

Mean values of OM, pH, total N, Avail. P. of top(0-20cm)soil -

Organic matter fractions - - . - - - -

Simple correlation analysis between aggregate stability indices and

some physico-chemical properties of soil under four-year fallow land(FY)

Simple correlation analysis between aggregate stability indices and some

pliysico-chemical properties of soil under grass vegetation land(GV) -

Simple correlation analysis between aggregate stability ind:ces and some

physico-chemical properties of soil under continuously cultivated land(CC)


physico-chemical properties of soil under forest vegetation land (FV) -


physico-chemical properties of soil under one-year cassava farm land(CF)

Principal component analysis of soil properties influencing mean weight

diameter under FY - - - - - - - -

Principal component analysis of soil properties influencing dispersion

ratio under FY- - -

15c Principal component analysis of soil properties influencing clay

dispersion index under FY - - - - - - 81

15d Principal component analysis of soil properties influencing aggregated

silt + clay under FY - - - - - - - 8 3

15e Principal component analysis of soil properties influencing clay flocculation

index under PI - - - - - - - - 8 5

16a Principal component analysis of soil properties influencing mean weight

diameter under GV - - - - - - - 87

16b Principal component analysis of soil properties influencing dispersion ratio I

under GV - - - - - - - - - 89

16c Principal component analysis of soil properties influencing clay dispersion

index under GV - - - - - 9 1


silt + clay under GV- - - - - - - - 93


index under GV - - - - - - - 9 5

17a Principal component analysis of soil properties influencing mean weight

diameter under CC - - - - - - - - 97

17b Principal component analysis of soil properties influencing dispersion ratio

under CC - - - - - - 9 9

17c Principal component analysis of soil properties influencing clay dispersion

index under CC - - - - - - - - 101


silt + clay under CC - - - - - 103


index under CC - - - - - - - - 105


d~ameter under FV - - - - - - - -

Principal component analysis of soil properties ;influencing dispersion ratio

under FV - - - - - - - - -

Principal component analysis of soil properties influencing clay dispersion

ir,dex under FV - - - -

Principal component analysis of soil properties influencing aggregated

silt + clay under FV - - - - - - -

Principal component analysis of soil properties influencing clay flocculation

index under FV - - - - - - -


diameter under CF - - _ I - -

Principal component analysis of soil properties influencing dispersion ratio

under CF - - - - -

Principal component analysis of soil properties influencing clay dispersion

index under CF - - - - - -

PI incipal component analysis of soil properties influencing aggregated

silt + clay under CF - - - - -

Principal component analysis of soil properties influencing clay flocculation

index under CF - - -

xii

ABSTRACT

Profile soil samples and 25 additional top(0-20cm)soil samples from

five land use types from Owerri, Southeastern .Nigeria, were used to study

the role of carbohydrates (R-CHO) and humic substances (HS) including

fulvic (FA) and humic (HA) acids in aggregate stability of soils of coastal

plain sands. The land use types were four year fallow (FY), grass vegetation

(GV), continuously cultivated (CC), forest vegetation (FV) and one year

cassava farm (CF) lands. Aggregate stability was measured at the macro

level by mean weight diameter (MWD) of water stable aggregates (WSA)

and at the micro level by dispersion. ratio (DR), clay dispersion index (CDI),

aggregated silt plus clay (ASC) and clay flocculation index (CFI). The topsoils

were sandy loam to loamy sand. Clay content increased with depth while

sand decreased. Saturated hydraulic conductivity (Ksat) showed an inverse

relationship with bulk density (BD) with the former. decreasing as the later

increased with depth. Values for the Ksat were fairly rdpid (0.96 to 1.95 cm

min-l) except for the GV where BD values were higher (1.5 to 1.589 cm3).

Topsoil BD were moderate, varying from 1.20 to 1.50 g cm-3 while the

subsoil values where higher, starting from 1.41 in one horizon to 1.58 g cm-3

in another. Except for the exchangeable Al, which was fairly high, the soils

were low in exchangeable cations. The exchangeable cations and CEC, with

the exception of Na did not influence aggregate stability to any appreciable

extent. Comparatively, HS, FA and HA influenced aggregate stability both at

. . . Xll l

the macro and micro levels, whereas, R-CHO did not. As far as organic

matter (OM) fractions were concerned, FA exerted a stabilizing influence on

soil aggregates under CC while for soil under FV, FA together with HA

influenced aggregate stability. Humic substance (HS) showed its influence on

aggregation of soil under CF and FY whereas no OM fraction was involved in

aggregate stability of soil under GV. For the soils studied, humic substances

(FA and HA) rather than R-CHO were implicated in aggregate stability, as

revealed by the Kaiser Varimax Rotated Components of all the properties of

the land use types.

CHAPTER ONE

INTRODUCTION

Organic matter (OM) exerts some influence on soil structural

stability. I t is a significant component of soil, fundamentally

contributing to the overall soil quality. Spaccini e t a/. (2002)

reported that changes in land use, for example, conversion of

natural forest to crop land, contributed to land degradations such

as losses of soil organic matter (SOM) and aggregate stability.

However, the authors could not relate contents of carbohydrates

to aggregate stability in the forested and cultivated soils,

suggesting that the aggregate stability was mediated by such

other aggregating agents as humic substances (HS) and iron and

aluminum oxides. Continuous cultivation degrades soil structural

properties due to the diminished OM content. Nevertheless, in

such arable lands, inputs of organic residues ameliorate soil

physical properties as much as OM accumulation does in forest,

grass or planted fallow lands. Assessment of changes in soil

properties which are associated with different land use systems

is vital to conclusions on appropriate soil conservation and

management practices to be adopted.

Information on components of SOM influencing flocculation and

dispersion is required to understand which component in

pdrticular affects stability of the aggregates. Despite the use of

several indices for the characterization of soil structural stability,

i t is still doubtful whether or not the components of OM have the

same and equal influence on such indices. Therefore, a

knowledge of these components and their effects on aggregation

will be necessary in deciding which is more useful as soil

amendment.

It has been reported that fractions of SOM rather than the total

alnount per se, are more important in modifying the structural

stability of soils (Hamblin and Greenland, 1977; Dormaar, 1983;

Dutarte et a/., 1993; Piccolo, 1996). Humic substances (HS),

namely, humic acid (HA), fulvic acid (FA) and humin (H) as well

as non-humic substances, for example, carbohydrates, peptides,

resins and waxes are major SOM components involved in soil

aggregate stability (Tisdall and Oades, 1982; Piccolo and

Mbagwu, 1999). At the macroaggregate level, some organic

biopolymers, for example, polysaccharides and proteins cover

the soil particle surfaces, transiently forming physical linkages

between them and hence temporarily acting as binding agents.

However, Adesodu et a/. (2001), had shown that carbohydrate

pools were not very effective in stabilizing soil aggregates

whereas Mbagwu and Piccolo (1998) and Piccolo and Mbagwu

(1990) had reported that HS, at the colloidal level of soil

aggregation, binds the particles together through formation of

hydrogen bridges, covalent linkages and complexes between clay

particles and polyvalent metals.

Most of the studies with HS and R-CHO were carried out in the

temperate regions (Kerndorff and Schnitzer, 1979; Senesi,

1992; Hanschmann et a/., 1997; Markarov, et a/., 1997) mainly

focusing on their chemistry and structure ( ~ e r d e n and Berggren,

1991; Ricca et a/., 1993; Piccolo, 1997). I n the tropical region,

the studies were, however, focused on exogen0u.s applications of

HS and R-CHO as amendments to soils to improve their physico-

chemical properties and productivity (Mbagwu e: a/., 1993;

Piccolo and Mbagwu, 1994; Ekeh et a/.' 1997). There is therefore,

the need for further research on tropical soils involving the role

of endogenous HS and R-CHO fractions of SOM in structural

stability. Hence. this study, which is generally an investigation

into the relative contributions of R-CHO a'nd HS to structural

stability of soils under different vegetation and management

systems. It is also an attempt to harmonize the controversial

results from studies on the role and actual fractions of OM

implicated in soil aggregate stability.

It is expected that adding high molecular weight organic

materials, such as HS and R-CHO, to structurally fragile soils

would be a useful management practice for improving their

aggregate stability.

The specific objectives of the study include:

1) Identification of variations in physico-chemical properties of

soils under different land use types,) and

2) Evaluation of the relative and/or complementary roles of HS

and R-CHO in aggregate stability of these soils in Owerri,

Southeastern Nigeria.

CHAPTER TWO

2.0 LITERATURE REVIEW

Food shortages, together with population increase across tropical

Africa, have forced more people into arable farming, thereby

putting the existing lands under continuous cultivation, and also

depleting reserved forest lands. The result of these phenomena

is soil degradation due to little or no input which reflects low

levels of plant nutrients in such soils.

Deforestation, intense cultivation of vulnerable land, over

grazing and poor soil and water management reduce the

productive capacity of soils and pose constraints to food, forage

and energy production. Wild food, 'such as mushroom and

certain fruits, come from forest while crop plants and animal

products are from agricultural systems. Forests as sink for COz

play a crucial role in reduction of global warming. Deforestation

begets bad effects such as erosion and silting up of rivers and

streams.

However, with proper management,, land can be cropped

continuously without reduction in yield so that we can have

forests and other vegetation types for biodiversity and

environmental health.

2.1 SOILS OF COASTAL PLAINS

2.1.1 DISTRIBUTION AND LAND USE

Within Southeastern Nigeria, soils of the coastal plains are

among the "acid sands", derived from unconsolidated sand

deposits formed over coastal plain sands and sedimentary rocks

in the humid zone of Nigeria where high incidence of rainfall

promotes leaching. I n this region, these soils constitute about

35% of the land area, stretching from the River Niger down to

Imo River Basin (Obigbesan e t a/., 1981). The "acid sands" are

not restricted to the rainforest zone of the country. They also

occupy the area stretching towards the northern Savanna around I

Nsukka.

The land area covered by the soils of the coastal plains is

densely populated. Due to their coarse nature, the sandy soils of

the coastal plains are referred to as unproductive (Babalola and

Obi, 1981). These soils are cultivated extensively for arable

crops under the bush fallow system or shifting cultivation. Small-

holder farmers in the area, who arei resourcefully poor, grow

such food crops as cassava, maize, various vegetables, etc.

under mixed cropping. Such soils are not suitable for continuous

monoculture of cereals that will demand high nutrients (Juo,

1981).

Soils of coastal plains are among the most important soil

resources of Nigeria in terms of agricultural potential and

utilization. I n some places, plantation agriculture among which

include oil palm, raphia palm, co~onuts, kolanuts, rubber,

cashew, plantain and banana, is practiced. I n the 1950s and

early 1960s, produce from the plantations, including timber from

the forests, accounted for substantial percentage of the country's

total export earnings (Ataga et at., 1981).

For many years, soils of coastal plains have sustained arable

cropping due to the management system adopted by the

farmers. Some of the systems include land rotation, land

clearing and bush burning, fertilizer use and OM and waste

management.

Under the system of land rotation, land is cropped for a year (or

two in some places) and then left to fallow for four to five years

I ITA, 1979). However, the slash-and-burn system has

considerable effects on soils' physico-chemical properties. For

instance, burning which increases temperature of sandy soils

that are low in heat-conducting, affects germination emergence

and overall development of seedlinqs. Other bad effects of

burning are loss of OM, erosion and leaching of bases under

heavy rainfall.

Nutrient losses through leaching are rampant in the sandy acid

soils of the coastal plains. I n other to supplement nutrient lost in

these soils, there is need to add fertilizers. Split application, at

periods of maximum demand by the crops, improves their

utilization efficiency. Fertilizer applicdtion, however, should be

based on soil test results.

Low levels of SOM compounded by leaching losses make

nitrogen one of the most limiting factors for crop production in

acid sands. Resource - poor farmers in the coastal plains of

Southeastern Nigeria apply house-hold and kitchen wastes to

their farms and gardens. Of late, pqultry manure has gained

prominence as a source of organic manure.

2.1.2 EFFECT OF LAND USE ON SOIL PROPERTIES

Multi-nutrient deficiencies and high acidity are common

features of soils of the coastal plains. Thus, in addition to

liming, fertilizers containing the deficient nutrients should be

applied. However, acid-forming fertilizers such as ammonium

sulphate should be avoided.

Forests with deeply rooted large and tall trees return nutrients

to soil surface through leaf and litter falls, thereby maintaining

nutrient cycling. However, disturbances such as lumbering,

clearing for agricultural and recreational uses reduce the

fertility and productive capacity of forest soils.

Once a forest is cleared for agricultural practice, soil

degradation ensues due to erosion of topsoil. Soil organic

matter (SOM) depletes as a result of removal of trees and

crops, with consequent stoppage of recycling. Basic cations are

lost through leaching, encourage

rainfall. With washing off of topsoi

exerca bates.

!d by tillage under severe

1 during erosion, soil acidity

Land use significantly influences soil physical properties,

especially structure. Clearing a land and leaving it bare fallow for

sometime can reduce the total porosity as well as water stable

aggregates (WSA), especially on sandy soils. Bulk density (BD)

reduces when sandy soil is ploughed either with machinery or

hand hoe to a depth not exceeding 30cm (Babalola and Obi,

1981). Under continuous pasture soil properties such as percent

water stable aggregates (WSA), BD, and total porosity (Pt) are

enhanced compared to bush fallow and continuous cultivation of

sandy soils of the coastal plains. Land use system can influence

hydraulic conductivity (Ksat). For example, use of heavy farm

machinery can induce compaction thereby causing a reduction in

Ksat of the sandy soils. Also, construction activities, such as

buildings and roads linked to urbanization, are capable of

adversely affecting Ksat.

During periods of grazing, infiltration rates are reduced due to

increased soil compaction and BD as a result of trampling by

cattle.

2.1.3 CHARACTERISTICS OF SOILS OF COASTAL PLAINS

2.1.3.1 TEXTURE

Soils derived from coastal plain sands are deep and vary from

sand to loamy sand in subsoil texture (Lekwa and Whiteside,

1986). They are generally coarse - textured with koalinite as

the predominant clay mineral (Lekwa and Whiteside, 1986;

Juo, 1981). Other classes present to a lesser extent among

the "acid sands" are sandy loam and sandy clay loam. Due to

their location in high rainfall area and coupled with their loose

nature, they are susceptible to water erosion.

2.1.3.2 STRUCTURE

Devoid of cementing agents such as organic and inorganic

colloids, soils of coastal plains are non cohesive. They may

remain as single grains and therefore, generally referred to as

"structureless". However, depending on the amount of clay

and OM, the sandy loams have variable structures ranging

from weak crumb and crumb to grahular.,

Lack of OM as a binding agent makes the particles to lie in close

contact, thereby increasing their BD as a result of reduction in

volume. Continuous cultivation, compared to grass fallow,

increases the BD. High BD of sandy soils is a reflection of their

low Pt which ranges from 38 - 50% (Babalola and Obi, 1981).

These soils are generally referred to as "porous" due to the

preponderance of macro pores. Total pore space decreases with

cultivation.

Stability of aggregates in water is better under grass fallow than

under bush fallow and arable cultivation. Clearing a sandy soil

and leaving it bare fallow for sometime reduced the total

porosity and water stable aggregates (Ba balola and Obi, 1981).

Continuous cropping destroys percent water stable aggregates.

Since cultivation reduces Pt and WSA while increasing BD,

fallowing brings about improved soil structural conditions.

2.1.3.3 WATER RETENTION

Where crops depend primarily on precipitation, a large storage

capacity for soil is needed. Sandy soils are "droughty", having

low water retention capacity. This is attributed to their low

content of colloidal materials and high percentage of macro-

pores. For these soils, difference between field capacity and

permanent witting point is small. Thus, they have a narrow

range of available water. This has implication for the method and

frequency of irrigation. I n the United States of America, it is

recommended that an irrigable soil should have available water

capacity of 6 cmm-' of soil (Massoud, 1973). However, for soils

that hold small amount of available hater, such as the coastal

plain sandy soils of Southeastern Nigeria, it is important that

field capacity be accurately determined. ' For such soils, it has

been recognized that the moisture equilibrium at -1OOcm matric

potential on pressure plates underestimates the field capacity

(Rivers and Shipp, 1971). Hence, Babalola (1978) recommended

equilibrium moisture contents at matric potentials between -80

and -1OOcm for the field capacity of sandy soils and some

tropical soils with kaolinite as their predominant clay mineral.

2.1.3.4 HYDRAULIC CONDUCTIVITY

Under saturated and unsaturated conditions, respectively, water

movement through sandy soils will be both rapid and slow. This

has a link with the pore size distribution and moisture

retentivity. The high and low values of saturated and

unsaturated hydraulic conductivity, respectively of sandy soils,

are due to the high proportion of macropores in these soils.

These facts have implications for infiltration of water into the

soils, redistribution of water, availability of water to plant roots

and leaching losses (Babalola and Obi, 1981). Saturated

hydraulic conductivity (KSat) values of 20.1 cmhr-' and 15.9

cmhr-' for loamy sand and sandy loam, respectively, have been

recorded (Babalola and Obi, 1981). For some "acid sand"

profiles, values ranging from 7.1 to 55.4 cmhr-' have been

recorded (Obi and Asiegbu, 1980) and are considered

moderately rapid to very rapid.

2.1.3.5 EXCHANGE PROPERTIES

Location of the soils in the high rainfall area, in addition to their

coarse-texture, make them susceptible to strong leaching and

water erosion. They are thus deprived of the Basic cations. I n

these soils, the cation exchange capaoity (CEC) is generally low.

Except in some top soils with high OM content, the effective

cation exchange capacity (ECEC) value rarely measures up to

lOcmol/kg but may be as low as 2cmol/kg (Enwezor e l a/.,

1981). The low values may be attributed to the predominance of

kaolinite. Also, Enwezor e t a/., (1981) reported as follows; "that

the magnitude of the total exchangeable bases is low relative to

ECEC, and that the base saturation is therefore low, being below

50% in most cases." Furthermore, they reported that the

exchange acidity is on the other hand, relatively high,

contributing generally over 50% to the ECEC while exchangeable

AI is high and usually contributes over 60% to the total

exchange acidity.

Depletion of OM, the source of exchangeable ions, further

accentuates the deficiency of the exchangeable cations.

2.1.3.6 ORGANIC MATTER, NITROGEN AND PHOSPHORUS

Organic matter content is generally low in the soils. For some

surface soils, values ranging from 0.74 to 4.63% OM have been

recorded (Enwezor et a/., 1981). Under intensive cultivation,

depletion of OM in these soils is high. Udo et a/., (1981) reported

that OM is more related to the ECEC, exchangeable Ca, base

saturation, total N and extractable Fe and Mn in some "Acid I

Sands".

Organic matter content of the soils can be used as a measure of

its nitrogen, phosphorus and potassium status. The soils of

coastal plain sands require considerable NPK fertilization on

account of low OM content and heavy rainfall and leaching. It is

essential to apply fertilizer during the period of maximum

demand for growth, for efficient utilization by crops on these

soils. 1

The soils are low in both total and available phosphorus. Most of

the inorganic phosphorus are in the occluded form and not

readily available to plants. Enwezer e t a/., (1981) attributes this

to the strong weathering and low pH values of the soils.

SOIL DEGRADATION

This may be explained as decline in soil quality resulting in loss

of actual and potential productivity through its improper use by

man. This situation has become a major global concern, being

one of the main problems confronting agriculture.

Soils can degrade without loss of their particles but always due

to cultural practices. It implies that erosion is not the only form

of soil degradation. During ploughing, the soil looses OM and

changes its composition. During irrigation, soil can accumulate

salts and eventually become unproductive.

2.2.1 TYPES AND CAUSES OF DEGRADATION

Various forms of soil degradation includ-e erosion, structural

decline, loss of OM and nutrients, accumulation of toxicities,

salinization, acidification, etc. These forms of soil degradation

may be grouped into physical, chemical and biological. For

example, physical degradation may be due to deterioration of

physical properties by compaction or 'surface crusting. Chemical

degradation takes the form of acidification or salinization,

whereas biological degradation reflects depletion of OM and

mineral content (Mbagwu, 2003).

2.2.1.1 EROSION

"Erosion" covers all forms of soil erosion by water and wind,

including interrill, rill and gully. Also, human-induced land

sliding due to deforestation, construction of roads and

railways is included. Erosion refers to transportation of

detached soil particles. While water erosion is rampant in the

humid tropics, wind erosion occurs primarily in dry regions.

Erosion results in loss of topsoil, terrain deformation, flooding,

reservoir sedimentation and silting up of streams and rivers.

Major causes of erosion according to UNECE (2001) are

unsustainable agricultural practices, large-scale farming and

over-grazing, poor water and irrigation management.

Increased wood cutting for fire wood and forest fires have

also been implicated as drivers of soil erosion (UNEP, 2002;

EEA, 2002).

2.2.1.2 STRUCTURAL DEGRADATION

The main forms of structural degradation are soil crusting,

sealing and compaction whereby soil particles are pressed

together and the pore spaces between them reduce.

Deterioration of soil structure is rare under natural conditions.

However, it occurs along tracks used by foraging animals and

where vegetation is removed, by fire. With agricultural

practice, changes in soil structure are common. Negative

impacts on agricultural productivity have been reported in

.places affected (EEA, 1995a; Nolte and Fausey, 2000; Van

Lynden, 2000). Structural decline occurs when the soil is

physically disturbed. Structure is lost i f soil is churned to a

significant depth, for instance, during construction work,

ploughing or compaction by agricultural machinery. Stability

of soil structure is determined by the strength of the bonds

holding the solid particles together. The relevance of structure

to agriculture lies in the key role played ,by soil pores. Crops

naturally rely on the spaces betweep soil particles to establish

root systems. Also, water will not percolate through heavily

compacted soil but will instead move quickly across the soil

surface carrying with it, the particles and nutrients.

Compaction also changes the quality and quantity of

biochemical and microbiological activity in the soil.

Compaction may be limited to the surface horizon, but after a

long term use of heavy machinery, subsoil may be affected to I

depths of 60 - 70cm (~ut i lek , 2005) and may become

irreversible (EEA, 1995b). Hebert (2002) had observed that

deep soils with less than 25% clay are most sensitive to

subsoil compaction.

Soil sealing changes the nature of surface soil, making it

impermeable. It affects the ecological function of the soil,

such as storage of carbon and habitat for biota. When soil

sealing occurs, surface run off increases significantly in

amount and velocity resulting in flood control problems (Pik,

Breakdown of aggregates at the soil surface causes crusting,

which inhibits infiltration and prevents seedling emergence.

Under continuous cultivation, the productivity of strongly

weathered, kaolinitic soils reduces rapidly because of crusting

and erosion (Lal, 1976; Kooistra e l a/., 1990; Van der Watt

and Valentin, 1992). Gijsman (1996) also repnrted low water-

stable aggregates under continuous rice cultivation. This was

attributed to frequent soil disturbance by ploughing and,

reduction in OM content. Golchin eta/., (1995) suggested that

only a part of soil carbon or carbohydrate is involved in

aggregate stability. They also observed that cultivation was

not a dominant factor influencing ,water-dispersible day but

structural collapse occurred more in cultivated than in fallow

soils and that intensive tillage practices degrade soil

aggregates. Tisdall and Oades (1980) had earlier reported

that cropping systems have a strong influence on the

structural characteristics of soil aggregates, particularly water

stable aggregates.

Instability of soil structure may result in surface crusting and

hard-setting due to inability to withstand ~ is rupt ive forces

occurring upon rapid wetting. The surface aggregates slake

and on drying they form a compact matrix. This phenomenon

creates a problem during tillage, culminating in restricted

infiltration of water, aeration, root penetration and seed

germination (Golchin et a/., 1995). Under conventional tillage

practices, poorly structured soils are prone to increased water

erosion (Chisci and Zanchi, 1981).

2.2.1.3 LOSS OF ORGANIC MATTER AND NUTRIEhTS

These constitute an integral part of soil degradation. Zech and

Guggenberger (1996) have reported that decrease in soil OM,

together with removal of the above-ground biomass,

accompanies soil quality degradation. Ctmversion of forest to

arable land reduces the OM content (Withbread et a/., 1998;

Caravaca et a/., 2002). Soil orgariic matter is important in

sustainable agriculture. Recognition of this fact in the tropics

has shifted increased attention to improved farming options

that will maintain adequate soil organic matter levels

(Fernandes et a/., 1997).

Soil application of OM improves structural stability through

enhancements in aggregate stability, porosity and reduction I

of bulk density (Mbagwu, 1989; Oades, 1984). These

parameters play a role in reduciion of water erosion by

improving the infiltration capacity and hydral~lic conductivity

of soils (Withbread et a/ . , 1998).

Soil organic matter can be lost through erosion (USDA,

1996). This process detaches and transports topsoil particles

which contain organic matter. Soil organic matter diminishes

as soil microorganisms utilize them ,as energy and nutrients to

support their own life processes. Decomposition of OM

becomes faster with tillage because of changes in water,

aeration and temperature conditions (USDA, 1996). Amount

of OM lost after clearing forested land or tilling native

grassland varies with the kind of soil. However most of the

OM is lost within the first 10 years (USDA; 1996).

I

2.2.1.4 ACCUMULATION OF TOXICITIES (SALINIZATION AND

ACIDIFICATION)

Application of pesticides, sewage sludge, fertilizer and even

manures which may contain heavy metals can accumulate to

toxic levels in the soil. Also, atmospheric deposition of

acidifying compounds, improper municipal and industrial

waste disposal, can become toxic to soil environment. Major

pollutants include organic contaminant such as chlorinated

hydrocarbon, mineral oil, and heavy metals.

The soil functions most affected by co~~taminants are

buffering, infiltration and transforming capacities.

Contaminated sites can pose serious threat to health as a

result of release of harmful substances to the ground or

surface waters, uptake by plants and direct contact by

humans.

I

Salinization, which is the accumulation of salts on soil surface,

results in unproductive soils. I t is caused by improper

irrigation methods, evaporation of saline ground water and

also by industrial activities (European Commission, 2000).

Dry land salinity may be due to over grazing, clearing for

agricultural activities and any measure that reduces

vegetation cover and water absorption. Gardner (1997)

estimated that salinization reduced cotton yields from 280 to

230tkm-* in the '70s and '80s in the Central Asian Republics,

despite increased use of fertilizers. Above certain thresholds,

restoration of saline soil is quite expensive. Remediation of

salinity focuses on improvements of irrigation systems and

water use efficiency and also by improved drainage systems.

Where drainage is expensive, salt-resistant plants are used to

stabilize the soil and reduce erosion (Mainguet and Letolle,

2000).

I n acidic soils, there is an abundance of alur,iinum, which is

not necessary for plant growth but can be toxic.

Acidity also affects vital bacteria in the roots of legumes,

most of which thrive in neutral or slightly alkaline soils. Soil

acidification goes hand in hand with nutrient leaching, which

leaves the soils with low base and pH values.

2.3 SOIL ORGANIC MATTER

This is made up of the decaying remains of plants and

animals. It therefore, originated from the product of primary

producers which becomes decomposed by soil organisms.

I n most soils, the OM accounts for less than 5% of the I

volume (USDA, 1996). It is therefore, a relatively small

component of the soils mass, but has a disproportionately

important role in controlling the physico-chemical character of

the soil, including its fertility and aggregate stability. I t

thereby, retains and provides nutrients for plants by

enhancing cation exchange capacity of soils while reducing

the hazards of erosion.

By improving the soil's ability to store and transmit water and

air, OM aids the growth of crops as well as maintaining soil in

an uncompacted condition with reduced bulk density (BD).

Soil OM is a source as well as a sink of atmospheric COz and

contributes to plant growth through its effect on physical,

chemical and biological properties of the soil (Duxbury e t a/.,

1989).

2.3.1 COMPONENTS OF SOIL ORGANIC MATTER

Soil OM can be separated into two components. There is a

smaller labile fraction consisting of plant, microbial and

animal products, easily decomposed, playing a vital role in

nutrient cycling. A second fraction is the stable component.

I t is a complex material referred to as humus which

decomposes very slowly. Humus includes humic substances

and identifiable biomolecules, which are less resistant to

decomposition.

2.3.1.1 CARBOHYDRATES AND THEIR ROLE I N AGGREGATE

STABILITY

Soil carbohydrates are representatives of labile, non- humic

substances. They constitute 5 - 25% of SOM in most soils

(Steven-son, 1994). Plant remains, contribute R-CHO in the

form of simple sugars, hemicellulose and cellulose. These are

easily decomposed by bacteria, actinomycetes and fungi

which in turn synthesize polysaccharides and other R-CHO on

their own.

The significance of R-CHOs in soils arises largely from the

ability of complex polysaccharide to bind inorganic soil

particles into stable aggregates. Carbohydrates also form

complexes with metal ions and they serve as building blocks

for humus synthesis.

Golchin e t a/ . (1995) reported that m l y a part of SOM or R-

CHO is involved in aggregate stability. Earlier, Tisdall and

Oades (1982) and Lynch and Bregg (1985) had suggested

that R-CHO was involved in aggregation especially in soils low

in OM. Adesodu et a/., (2001) on the other hand, observed

very poor correlation of aggregate stability with R-CHOs,

suggesting that i t was not contributing to aggregate

stabilization of the soil particles. Earlier, Oades (1984) had

reported that R-CHO fraction of SOM is as important as glues.

Other researchers, Chaney and Swift (1986), Angers and

Mehuys (1989), Haynes and Swift (1990) and Angers e t a/.,

(1993) have posited that soil dmendment with glucose

produced stable aggregates. Nacro e t a/., (2005),

corroborated this when they reported that monosaccharides

play an important role in soil quality involving in formation

and stabilization of soil aggregates. However, Insam (1996)

insisted that R-CHOs cannot participate in long term

stabilization of aggregates since they are easily degradable by

microorganisms. This was confirmed by Piccolo and Mbagwu

(1999) when they suggested that hydrophobic humic acid has

longer lasting effect on aggregate stability than hydrophilic R-

CHOs which are rapidly biodegraded. These diverging reports

may be due to the sources of the R-CHOs and the residence

time of the organic materials producing them in the soil.

Organic matter from diverse sources behave differently in

different soils while their tenure in soils relate to intensity of

cultivation, soil type, texture, temperature, microbial

activities and the chemical composition (Piccolo, 1996;

Mbagwu and Piccolo, 1998; Watts et at., 2001).

Transient nature of polysaccharides in soils may contribute to

poor correlation of such R-CHOs with aggregate stability

(Adesodu et at., 2001). Earlier, Guggenberger et a/., (1999)

had reported temporary stabilization of soil aggregates by

root exudates, mucilages and extracellular gums from I

rhizosphere activity. Carbohydrates in conjunction with

humified SOM, get involved in aggregate stab~lization (Angers

and Mehuys, 1989; Caron et at., 1992). Spaccini et a/.,

(2002) observed that R-CHOs alone did not explain much of

the variability in mean weight diameter (MWD) of the soils,

confirming that other components of OM such as HS may be

acting in concert with the R-CHOs to stabilize the aggregates.

Dutarte et a/., (1993) reported sim'ilar findings, showing that

humin and HAS were mainly responsible for the aggregate

stability of continuously cultivated soils in the tropics.

Nacro e t a/., (2005) observed that, although tropical forest

soils were higher in OM than savanna soils, their R-CHO

content was higher under savanna than under forest soils.

They also reported generally low content of R-CHOs,

attributing these to rapid decomposition of surface plant

debris under tropical climate. Earlier, Mbagwu and Piccolo

(1998) had observed that in Nigeria, soil R-CHO content

decreased with decreasing wet aggregate size in the humid

South, whereas Adamu, et a/., (1997) noted that with dry

aggregates, the opposite was the case in the cool Plateau of

the North.

Most abundant extractable monosaccharides in soils include

qlucose, ribose, mannose, xylose and galactose which are

also derived from microbial biomass (Nacro e t a/., 2005),

indicating intense microbial activities in the soil.

2.3.1.2 HUMIC SUBSTANCES

2.3.1.2.1 CHARACTERISTICS OF HUMIC SUBSTANCES

Humic substances are stable components of SOM that are

resistant to microbial attack. hey constitute 60 - 80% of

SOM (Mbagwu and Piccolo, 1989). They are amorphous,

characterized by aromatic ringed structures which include

polyphenols and polyquinones. Humic substances are dark

coloured with molecular weights ranging from 2000 to

300,000 gmol-I (Brady and Neil, 1999).

There are three classes of HS based on their solubility. These

include fulvic acid, humic acid and humin. Fulvic acid has the

lowest molecular weight. I t is also lightest in colour and

soluble both in acid and alkaline media. Of the three classes

of humic substances, it is the most susceptible to microbial

attack.

Humic acid has higher molecular weight than fulvic acid but

lower than humin. I t is soluble in alkali but not in acid. I t is

intermediate in colour and in resistance to biodegradation.

Humin has the highest molecular weight, darkest in colour

and insoluble both in acidic and alkaline media. I t is also the

most resistant to microbial attack.

Humic and fulvic acids extracted from a soil differ in quality

and chemical composition, depending on parent material and

climate (Garcia e t a/., 1985; Sarmah and Bardoloi, 1993).

Altitude and vegetation type (Singhal and Sharma, 1983;

Sarmah and Bordoloi, 1993) and soil management (Miglierina

and Rosell, 1995) are also factors influencing the composition

of humic substances. Arshad and Schnitzer (1989) have also

reported the dominant effect of rainfall and vegetation on the

composition of HA. Functional groups and molecular weights

have also been reported to be influenced by cultivation and

vegetation type (Dormaar, 1979; Mukhopadhyay and

Banerjee 1985; Zhang etal., 1988):

Martin e t al., (1998), characterizing HS extracted from

cultivated and forested soils, observed that the elements C, H

and N were higher in HA than in FA but that FA contained

more 0. This corroborated an earlier report by Sarmah and

Bordoloi (1993). Martin et al., (1998) also reported that

cultivation decreased the contents ,of C, and H but increased

that of 0 in both humic and fulvic acids, I n HA, N contents

decreased with cultivation while i t increased in FA, whereas

the highest C and lowest 0 contents were observed in humic

and fulvic acids extracted from natural forested soils (Martin

e t al., 1998).

Sarmah and Bordoloi (1993) observed higher total acidity and

alcoholic hydroxyl group in fulvic than in humic acids which

was confirmed by Martin et a/., (1998). Dormaar (1979) had

also earlier observed an increase in )the total acidity of HS due

to cultivation.

2.3.1.2.2 HUMIC SUBSTANCES AND SOIL AGGREGATION

I n many agricultural soils, exposure can reduce aggregate

stability. Within the tropics, one of the most natural processes

affecting structural stability is the degree of wetting and

drying cycles the soils are exposed to (Piccolo et a/., 1997). 1

I n their study on aggregate stability, Chaney and Swift

(1986) observed higher relative improvement with application

of HA than with the less stable R-CHOs. This was supported

by the findings of Fortune et a/., (1989) that HS extracted

from farm yard manure improved and prolonged aggregate

stability more than the bulk manure. Further studies on soil

aggregation by Piccolo and Mbagwu (1990) revealed, in

addition to high correlation of stability with HS, that the larger

the molecular size of the HS, the larger the stability of

mircoaggregates. Piccolo and Mbagwu (1990) also suggested

that microaggregate stability correlated with the relative

content of HS. They further observed that microaggregates

decreased with reduced HA whereas FA alone was not

significantly related to aggregate stability. Shanmuganathan

and Oades (1983) had earlier made similar observations and

reported that FA rather increased clay dispersibility. Earlier,

Dell' Agnola and Ferran (1971) found that the more stable

macroaggregates related well with the higher molecular

weight HS. Later, studies by Chakraborty et a/., (1979 and

1982) revealed that HA of low molecular weight were mainly

responsible for stabilizing large size aggregates. However,

Tisdall and Oades (1982) believed that HS exerted their

binding actions more in the microaggregates. At the

macroaggregate level, Piccolo et a/., (1996), studying

Mediterranean soils, observed that HA rates.increased mean

weight diameter (MWD) relative to a control. Meanwhile,

Piccolo and Mbagwu (1989, 1994) and Mbagwu et a/., (1993)

,reported slight decrease in MWD at larger rates of HA on

some Italian and Nigerian soils. Earlier, Visser and Caillier

(1988) also showed that HA applications on a Quebec soil

increased the amount of water-dispersible clay, implying a I

reduction in stability. These reports indicate the dual role of

HS as aggregating and disaggregating agents (Emerson,

1983; Oades, 1984).

The mechanism of soil aggregation by HS was explained by

Stevenson (1994), Theng

involves both hydrophilic

acting simultaneously at

aggregation levels. The

(1982) and Greenland (1971). This

and hydrophobic functional groups

the micro-aggregation and macro- 1

acidic functional groups dissociate

(Stevenson, 1994) and upon contact with soil materials, they

quickly react with polyvalent cations on the surfaces of the

clay parties forming strong humus-polyvalent metal-clay

complex (Greenland, 1971; Then, 1982). During this complex

formation, the hydrophobic functional groups of the HS are

orientated towards the outside of the soil particles, thus

increasing the soil solid-liquid interfhcial forces. This enhances

the water repellency as the surface tension is increased,

thereby preventing immediate water infiltration and slaking.

Theng (1982) again explained the dispersive mechanism of

HS stating that when high concentrations were added to some

soils, low molecular size components penetrated the clay

domains. These formed complex chalates with polyvalent

cations involved in holding clay particles together. This

resulted in clay dispersion in water.'

The implication of these aggregating and dispersing roles of

HS is to identify the optimum rate for use in improving

structural stability of specific soils.

2.4 NEED FOR FURTHER STUDIES

Once forests are cleared for agricultural practices, soil

degradation ensues due to loss of SOM. There is therefore,

the need for intensive soil conservation programmes to

maintain the productivity of tropical soils under sustainable

agricultural practices. Considering extensive researches into

soil amendments, improvements with HS that are

spontanuous, long lasting and not biologically mediated

indicate that these materials could be especially beneficial on

degraded troplicaI soils with little biological activities as

depicted in soils derived from coastal plain sal\ds. However, a

lot of study need to be undertaken to relate the endogenous

HS and R-CHO to soil productivity.

CHAPTER THREE

3.0 MATERIALS AND METHODS

3.1 THE PHYSICAL ENVIRONMENT

The study area is located within latitddes 5'14'N to 5O18'N and

longitudes 7'5'E to 7'10'E in Owerri North Local Government

Area of I m o State, Southeastern Nigeria. Tropical wet and dry

climates prevail in the area. Mean annual rainfall is 2000 mm.

Wet season extends from March to October with peaks in

June/July and September. Intensities of rainfall may be as high

as 50 to > I 0 0 mmhi l . (NRCRI, 2003)

I n some years, rainfall may be prolonged while there may be

delayed onset in some other years. Annual mean maximum

temperature is 28OC, while 21°C is the annual mean minimum.

(NRCRI, 2003). Throughout the year, insolation is high.

The area is geomorphologically plain. Topography is nearly flat

with gentle slope, while dominant vegetation types are tropical

rainforest and derived savanna of the guinea type. The tree

species are varied, including Dialium guineense, Anthonotha sp.

The grass species are mainly guinea grass (Panicum sp),

Ba hama (Cynodon dactylon), feathery lovegrass (Eragrostis

tenella), etc.

The main occupation of the population is subsistent farming.

Food crop cultivation dominates the agricultural landscape. Major

crops grown in the area include cassaba, maize, melon, telfaria,

and pepper, with only a few farmers cr~ltivating yam.

PlantainIBanana and cocoyam are grow around the homestead

where refuse is dumped.

Such conservation practices as low planting densities and

organic manuring are adopted. The main conservation practices

include shifting cultivation, necessitatipg one - season cropping

and bush fallow system; multiple cropping; cover cropping;

mulching; and organic manuring, with application of wood ash

from burnt wood used as fuel. Inorganic fertilizer application has

not gained ground due to financial constraints and sociological

behaviour of the resource - poor farmers.

3.2 FIELD AND LABORATORY STUDIES

These included digging and description of one profile pit each in

five land use type areas. Samples for laboratory analyses were

collected from the profile horizons and randomly from top (0-20

cm) soils around each profile pit. The soil samples were

collected with auger, trowel and core samplers.

3.2.1 TOP (0 - 2 0 cm) SOIL SAMPLES

The following properties were determined using standard

methods:

(i) Particle size distribution by ~ o u ~ o u c o s hydrometer method as

described by Gee and Bauder (1986).

(ii) Organic matter, determined as organic carbon (OC) by the

Walkley and Black method (Nelson and Sommers 1982).

Organic matter was derived by mult'iplying OC by 1.724.

(iii)Total Nitrogen by the micro-kjeldahl digestion method of

Bremmer and Mulvaney (1982).

(iv) Available Phosphorus was calorimetrically determined using

Bray 2 method as described by Olsen and Sommers (1982).

(v) Exchangeable Ca, Mg, Na and K were extracted with neutral

ammonium acetate. The Ca and Mg in the leachate were

determined by EDTA titration (Lanyon and Heald, 1984)

whereas Na and K were by flame photometry. (Kundsen et

a/., 1982).

(vi) Exchangeable acidity (H+ + A I ~ + ) wa; by the KC1

displacement method of Mclean (1982).

(vii) Cation Exchange capacity was determined by the sodium

acetate technique (Rhoades, 1982).

(viii) pH was measured electrometrically with pH meter in water

and in KC1 using soil: water or KC1 ratio of 1 :2.5.

3.2.2 PROFILE SAMPLES

I n addition to the above determinations the following parameters

were also measured.

(i) Aggregate Stability: Texture was determined by Bouyoucos

hydrometer method described by Gee and Bauder (1986) with

calgon (sadium hexametaphospHate) as dispersing agent.

Also, profile samples were dispersed in water to enable the

determination of such aggregate stability indices as DR, ASC,

CFI and CDI as follows:

[% silt + clay (H20)] DR = x 100

[% silt + clay (calgon)]

ASC = [% clay + silt (calgon)] - [% clay + silt (H20)] ...( 2)

[% clay (calgon) - O/O clay (H20)] . CFI = x 100 ...( 3)

[% clay (calgon)] I

O/O clay (HzO) CDI = x 100 ...( 4)

O/O clay (calgon)

(ii) Water - Stable Aggregates: This was by the wet - sieving

method of Kemper and Rosenau (1986). I n this method, 259

of the < 4.75mm soil sample was put in the topmost of a nest

of four sieves of 2.00, 1.00, 0.50 and 0.25mm sizes. I t was

presoaked in water for l0min: Then, the nest of sieves with

the soil sample was oscillated vertically 20 times in water,

using a 4cm amplitude, at the rate of one oscillation per

second. Soil particles at the topmost sieve were always below

the water surface during each oscillation. At the .end of wet-

sieving, resistant aggregates on each sieve were oven-dried

and recorded as percentages of the original mass as shown:

WSA = (Mr/Mt) x 100 ...( 5)

Where Mr is mass of resistant aggregates and Mt is the total

mass of wet-sieved soil. The water - stable aggregates (WSA)

were then categorized into 4.75 - 2.00, 2.00 - 1.00, 1.00 -

0.50, 0.50 - 0.25 and < 0.25mm. Mean weight diameter

(MWD) of WSA was calculated as:

n MWD = XiWi

i= 1

Where Xi is the mean diameter of the ith sieve size and Wi is

the proportion of the total aggregates in the it11 fraction.

(iii) Saturated Hydraulic Conductivity: Saturated hydraulic

conductivity (KSat) was done by the constant head

permeameter method. Triplicate determinations were made

per sample. Darcy's equation, as explained by Youngs (2001),

was used for the computation of K& I n this procedure, the

core sample was trimmed at both ends and a cheese cloth

was fastened at the base using a rubber band to hold it in

place. This was saturated in water for 48hr. Thereafter, an

empty core of same diameter was placed on top and held in

place with wax to ensure no leakage of water. This way, a

constant head of water above the sample was obtained. The

rate of water flow was observed and recorded when constant I

for three consecutive runs.

I

KSat was calculated thus:

Where Q is water discharge (cm3), L is the length of soil

column (cm), A is the cross-sectional area of the soil column

(cm2), AH is the head pressure difference causing the flow

(dimensionless), T is the time of flow (sec.).

(iv) Water Retention: Water retained at field capacity (FC)

and permanent wilting point (PWP) were determined using

the saturation water percentage based - estimation models of

Mbagwu and Mbah (1998). Total available water capacity

(TAWC) was computed as the difference between moisture

retained at FC and WP. The models are: I

FC = 0.79 (SP) - 6.22 ( r = 0.972) . . . (8)

WP = 0.51 (SP) - 8.65 (r = 0.949) . . . (9)

where FC and WP are the field capacity (%) and permanent

wilting point (%), respectively, and SP is the saturation water

percentage.

For the determination of SP, ceramic crucibles with perforated I

bottom were used. Duplicate determinations were made per

sample. Portions of the air-dried soil sample were transferred

into the crucible, a little a t a time, with intermittent gentle

tappings on the work bench, to consolid.ate the mixture. The

process was continued until the crucible was about four-fifth

full. The crucible, with air-dry sample, was weighed. It was

then transferred into a basin and water was added into the

basin up to a depth of about two-third of the height of the

crucible. I t was allowed to stand for 24hr to saturate. I t was

then dried in the oven for 24hr at 10S0C, after which the

mass of crucible with oven-dry soil sample was recorded. SP

was then calculated as follows:

Me + (Msa - Mso) SP = 100 x ...( 10)

Msa Where Mso = 100 x

I n equations 10 and 11, is the air-dry (residual) moisture

percentage, Me is the mass of water absorbed (g), Msa is

mass of air-dry soil (g) and Mso is mass of over-dry soil.

(v) Bulk Density and Porosity: Bulk density (BD) was

determined using the core method as described by Anderson

and Ingram (1993).

Total porosity (Pt), the percentage of bulk volume not

occupied by solids, was calculated from BD values assuming a

particle density (PD) of 2.65 g ~ m - ~

Macroporosity (P,,,,) was computed from volumetric moisture

content at FC as described by Mbagwu (1991) using the

equation shown below:

. Pma = PI- - FC

Where FC is volumetric moisture content at FC.

Microporosity was calculated as the difference between Pt and

Pma (Mbagwu, 1991).

(vi) Carbohydrates: Total carbohydrate (R-CHO) fractions in

the soil samples were determined in dilute acid extracts using

the method outlined by Adesodu et a/. (2001).

(vii) Humic Substances: These were extracted using the

method described by Castagnoli etal . (1990). I n this method,

HS as humified carbon, was determined, after extraction with

sodium hydroxide (NaOH), by wet oxidation with K2Cr207 in

acid medium. Acidification (pH1 or 2) of an aliquot of the

extract with NaOH precipitated HA while FA remained in

solution and was determined by the same method of wet

oxidation with K2Cr207 in acid medium.

3.3 STATISTICAL ANALYSES

Principal component analysis (PCA) and simple correlation

analysis were used. Least significant difference was also used

to detect differences between means.

I

CHAPTER FOUR

4.0 RESULTS AND DISCUSSION

4.1 PARTICLE SIZE DISTRIBUTION

The distribution of the soil separates in the five land use types

studied are shown in Tables 1 and 3. Results indicated that the

cassava farm land (CF), forest vegetation land (FV) and

continuously cultivated land (CC) had significantly (PS0.05)

higher sand fractions than the four year fallow land (FY) and

grass vegetation land (GV). The last two land use types were not

statistically different (Table 3). The CF was highest followed by

FV and CC in that order.

For the silt fraction, FV and FY contained more than the rest and

were statistically (PS0.05) different from GV and CC.

I

The land use types were significantly different from each other in

clay content, except for FV and CF which were statistically

similar.

The high sand content in all the soils ssmpled could be attributed

to their being derived from unconsolidated sand deposits, formed

over coastal plain sands and sedimentary rocks (Obigbesan et

a/. , 1981). The texture of the soils are related to their parent

materials (Akamigbo and Asadu 1983) which accounted for the

similarity of particle size distribution obtained Igwe et a/. (1999)

made similar observations when they reported that soils derived

from different geologic formations varied in particle size

distributions.

Table 1. Some pHysical properties of profiles under different land use types.

~ o r i z o n Depth %clay %silt %sand K,,, %P, ~ , (g-crn-~) TAWC% I

- - _ C c m L _ - -- . - _ -- -(L cm - min-'1 FYP(1)

AP AB

B A I

B A 2

B

GVP(2)

AP ABx

B t l

B t 2

CCP(3)

AP AB

BA

B

FVP(4)

Ah AB

B A I

B A 2

B

CFP(5)

AP AB

B A I

B A 2

4

6 4

6

6

4

Trace

Trace

Trace

3 4

4

4

6 4

4

2

2

4

2 4

4

B ... . 74 - 111 17 2 81 1.17 46.60 1.33 12.24 NP(1) = Profile pit in a four-year bush fallow land GVP(2) = CCP(3) = FVP(4) = CFP (5) = Ksat

- -

pt - -

BD - -

TAWC =

Profile pit in a grass vegetation land Profile pit in a continuously cultivated land Profile pit in a forest vegetation land Profile pit in a one-year cassava farm land Saturated hydraulic conductivity Total porosity bulk density Total available water capacity

Table 2. Some chemical properties of profiles under different

land use types. -- -- - -. I

Depth(cm) pH(H,O) pH(Kcl) Na K Ca Mg CEC Al H

FYP(l), GVP(2), CCP(3), FVP(4) and CFP (5) are as stated under Table 1.

Table 3. Mean values of particle size distribution of top - 20cm) soil. - - - - -- ( 0 . - -- - --

Properties Landuse Types LSD(0.05)

O/O sand 79.2 77.2 82.0 84.2 86.6 2.2

O/O silt 5.6 3.2 2.8 6.4 4.8 2.2

O/O clay 15.2 19.6 15.2 9.4 8.6 1.9

FY = four year fallow land; GV = grass vegetation land;

CC = continuously cultivated land; FV = forest vegetation land;

CF = one year cassava farm land; SL = sandy loam;

LS = loamy sand.

4.2 AGGREGATE STABILITY INDICES

The percent water stable aggregates (WSA) varied between land

use types (Table 4). The highest value for the 4.75 - 2.00mm

aggregate size was observed under FY while the lowest was

under the GV. Also, for the 2.00 - 1.QOmm aggregate size, the

FY was highest while CF was lowest. Towards the

microaggregate sizes, (0.50 - 0.25) GV had the highest values,

while the FV had the highest for the <0,25mm aggregate size.

This implied low stability. With the exception of 1.00 - 0.50mm

aggregate size, significant (P10.05) differences in WSA were

observed between most of the land use types. Comparing FV and

CC, the results obtained for the microaggregate size fractions

were contrary to the observation reported by Spaccini e t a/.,

(2001), but supported those of Spaccini et a/., (2002) both at

the macro and micro levels, except for the <0.25mm size

fractions. However, at the macroaggregatior, size (4.75 -

2.0mm) level soil under the FV was better aggregated than that

of CC.

Table 4. Aggregate stability indices. -- - - - - - - - -

Properties Landuse Types , LsD(o.05)

FY = four year fallow; GV = grass vegetation;

CC = continuously cultivated land; FV = forest vegetation;

CF = one year cassava farm land; WSA = water stable aggregates;

MWD = mean weight diameter; DR = dispersion ration;

CDI = clay dispersion index; ASC = aggregated silt + clay;

CFI = clay flocculation index.

The WSA under the FY consistently reduced with decreasing

aggregate sizes while the contrary was observed under GV. For

the other land use types there was no consistent pattern. This

observation indicated that different factors may oe affecting the

WSA under different land use types.

At the macroaggregation level measured by mean weight

diameter (MWD), the FY performed better than the other land

use types, closely followed by CF. Contrary to expectation, GV

and FV showed less stability of their aggregates. Comparing FV

and CC, the results supported the observations of Spaccini e t a1

( 2002 ) who reported reduction in MWD when forested land was

converted to arable land. However, the difference in the values

between the FY and the FV was significant (PSO.05). Tillage with

traditional hoeing and clean weeding may explain the low value

of MWD observed under CC while low levels of SOM explained

low aggregate stability under GV. 1

At the micro level, measured by DR, CDI, ASC, and CFI (Table 4)

the stability of the aggregates under the different land use types

was irregular. For DR, significant difference was observed

between CC, which had the highest value, and CF with the

lowest value, whereas none was observed between CC and the

other three land use types. These other three land use types

(FV, GV and FY) were not statistically different from CF. Also CC

recorded the highest value for CDI while GV had the lowest I

value. Considering ASC and CFI, CC performed poorly. The

values obtained with these indices of microag~regate stability

under CC showed that its stability was lower than the other land

use types. This may be connected with lowest organic matter

content observed under CC which supported the report by Igwe

et a/ . , (1999) and Gijsman (1996). Although no significant

differences existed between the land use types, except for DR,

GV appeared to be best a t the microaggregation level

irrespective of the higher values of OM and OM fractions

observed in soils under the FY and FV. I t may, therefore, mean

that other factors, apart from OM and OM fractions influenced

aggregate stability of the soils studied.

4.3 WATER RETENTION CHARACTERISTICS

The saturation water percentage (SP), field capacity (FC),

permanent wilting point (PWP) and available water capacity

(AWC) of the studied land use types are shown (m Table 5). The

trend observed indicated that OM and OM fractions influenced

these parameters. I n all these parameters, FV performed best,

reflecting its content of OM and OM fractions. The high moisture

retained at FC, PWP and AWC under FV was a manifestation of

the affinity of OM for water (Oguike and Mbagwu, 2004; Mbagwu

et a/., 1994). Differences between FV and the other land use

types in these properties were significant (P50.05).

Table 5. Water retention characteristics. --

Properties Landuse Types LsD(o.05)


CC = continuously cultivated land; FV = forest vegetation;

CF = one year cassava farm land; SP = saturation moisture

percentage; FC = field capacity; PWP = permanent wilting point;

TAWC = total available water capacity.

4.4 BULK DENSITY, POROSITY CHARACTERISTICS AND

SATURATED HYDRAULIC CONDUCTIVITY

Variations in bulk density (BD), porosity and saturated hydraulic

conductivity (KSat) are shown in (Table 6). I n all the parameters

measured, FV performed best with the lowest BD, highest total

porosity (Pt), macroporosity (P,,) and the most rapid KSat. These

results may be due to the high content of OM which reduces BD

and increases porosity and K,,t. Although, with regard to BD,

there were significant differences between the land use types, no

regular pattern of relationship between BD and OM content was

observed. This, however, negated decreases in BD due to

increases in OM, and was not consistent with the reports of other

researchers (Igwe et a/., 1995; Mbagwu et a/., 1983; Oguike et

Significant differences in Pt were observed between the land use

types but not between FY and GV. FV recorded slightly more

than 50% Pt, while CC recorded just above 37%. With respect to

FV, GV and CC, OM could be inferred to have played a role in the

Pt of the soils. As OM decreased in these land use types, from FV

to CC the Pt reduced (Table 5). This is consistent with the

observations of Oguike et a/., (2006). Also, Ekeh et a/., (1997)

observed enhancements in both Pt and P,, with improved OM

status. I n this study, Pt and P,, followed the same trend while

microporosity (Pmi) was highest under the GV.

The KSat observed was fairly rapid, possibly as a result of the

coarse texture of the soils. Values ranged from 0.4lcmmin-I to

1.67 under GV and FV, respectively. The most likely explanation

would be the percent sand content which was highest under the

FV and lowest under the GV. Also, P,, was highest under FV

explaining further, the rapid KsaL. This observation agreed with

those of Ekeh e t a/., (1997), and Oguike e t a/. (2006, 2007). No

significant differences were observed between FV, CF and FY but I

these were statistically different from GV and CC.

Table 6. Bulk density, porosity characteristics and saturated

hydraulic conductivity. -- -

Properties Landuse Types LSD(0.05)



CF = one year- cassava farm land; Bo = bulk density;

PC = total porosity; P,, = macroporosity; Pmi = microporosity; I

K,,c = saturated hydraulic conductivity.

4.5 EXCHANGE PROPERTIES OF TOPSOILS FROM DIFFERENT

LAND USE TYPES I

Mean values of exchange properties of top soils (0 - 20cm)

sampled from each land use type are shown in Table 7. The

values ranged from very low to moderate, indicative of degraded

soils. Variations in Na contents under the different land use

types were significant (P10.05), with FY ranking highest. The

CF, with the lowest value of 0.16 was not statistically different

from the FV (0.22). I

There was no significant difference in K in all the land use types,

with FY having the lowest value. The highest value was recorded

in CC. With respect to Ca, CC, where the highest value was

recorded, was statistically different from GV. The other land use

types, though, statistically not different from CC, showed no

significant difference from GV, which was lowest.

Highest value of 0.524 for Mg was observed 'n FY while the

lowest of 0.062 was recorded in CF. The PI was significantly

different from all the other land use types with respect to Mg,

whereas, GV, FV and CF were not statistically different. The FV

recorded the highest value of 9.60 for CEC while CC recorded the

lowest ( 7 .00 ) . There was significant difference between these

two land use types, while none was observed between the other

land use types.

Table7. Mean values of exchange properties of top m- 20cm) soil. - -. . - - - . . -. - -- - . . - . ~ . -

Properties LanduseTypes LSD(0.05)


CC =.continuously cultivated land; FV = forest vegetation land;

CF = one year cassava farm land.

1

Soil acidity was generally high with exchangeable A13+

contributing more to the low pH values. However, exchangeable

H ' contributed more under CF. There was no significant

difference observed between GV and FV in terms of

exchangeable A13+ but these two land use types significantly

differed from the rest. Also, FY was statistically different from I

CF. Exchangeable H+ contributed minimally. to exchange acidity

and contributed nothing under CC. The FV and CF were not

statistically different, but both differed significantly from the

other land use types, which were statistically not different from

one another.

The low values in the exchange properties may be as a result of

the climatic condition of high rainfall and insolation which hasten

organic matter decomposition and permit deep leaching of

nutrients. Ogui ke et a/., (2007) made similar observation.

Ultimately, soils under this climatic condition develop high acidity

(Igwe et a/., 1999; Enwezor e t a/., 1981).

4.6 pH, ORGANIC MATTER, TOTAL NITROGEN AND AVAILABLE

PHOSPHORUS OF TOPSOILS SAMPLED

Table 8 shows the mean values of pH (both in H20 and Kcl), OM,

TN and avail P of soils under the different land use types. The pH

(HzO) ranged from extremely acid to very strongly acid, while pH

(IW) were all extremely acid (Onwueme and Sinha, 1991).

Oguike e t al., (2006, 2007) and Igwe e t al., (1999) reported

similar observations while studying soils from the same agro-

ecological zone. I n all cases, soil under FV was more acidic than

the other land use types (Table 8). Differences in acidity under

the land use types were significant (PS0.05). The high acidity

observed may be connected with heavy leaching due to the

climate and the coarse nature of the soils (Igwe etal., 1999).

Values for OM in all the land use types were very high. The FV

recorded the highest values while CC had the lowest OM value.

There were significant differences between the OM under FV, GV

and CC. The high OM values recorded in FV and FY may be as a

result of plant materials abundantly returned to the soil in these

environments. Although, CC was comparatively lowest in OM

content, the value was high (Onwueme and Sinha, 1991),

probably due to the organic wastes which peasant farmers in the

area continually used as soil amendment. For CF, the relatively

high value could be as a result of the leaf litter (Carsky and

Toukourou, 2003). The values recorded for OM under these land

use types drastically differed from observations of some

researchers (Igwe et a/., 1999; Igwe et a/., 1995; Piccolo et a/.,

1997; Mbagwu and Piccolo, 1997) while confirming the results

reported by Machado and Gerzabek (1993).'

Values for TN ranged from 0.128 under CC to 0.280 under CF,

indicating medium to high contents (Onwueme and Sinha,

1991). No significant differences wdre observed among the

different land use types. These values contradicted the results

reported by Oguike et a/., (2006) and were probably due to the

high contents of OM (Table 8), which typically contains about 5%

nitrogen (Brady and Weil, 1999). However, these values were

expected to be lower than observed because the coarse nature

of the soils permit downward leaching of NO3- with drainage

water. Also, the negative charge on No3- would not allow it to be I

adsorbed by the negatively charged colloids dominating most

soils. The lowest value observed under CC may be due to

excessive removal in crop harvesting (Ipinmoroti et a/. , 2005).

Available P. in all land use types were high (Onwueme and

Sinha, 1991), ranging from 25.2gkg-I in FV to 58.1 in CC. With

the exception of GV, all the land use types were statistically

different from FV, but, were not significantly different from one

another. These results were totally different from the

observations of Ipinmoroti et a/., (2005) who reported lower

values, with virgin forest and fallowed soils ha\-ing the highest

values. Earlier, Enwezor (1977) had reported that soils of

Eastern Nigeria were generally low in avail P., probably due to

complexing with Fe as a result of acidic nature of the soils. Johns

and McCouchie (1994) had also reported possibility of P-fixation

when soil pH is low. However, when OM is high, as was the case

in the soils studied, especially with dumping of organic wastes in

the CC, redox reaction may ensue. Under this condition,

microorganisms may reduce Fe3+, during respiration, to Fe2+

which has higher mobility. Phosphorus, hitherto bound to ~ e ~ ' ,

will become available in the soil. This phenomenon may account

for the high avail P values in the CC and in all the other land use

types.

Table 8. Mean values of OM, PHI total N, avail. P. of top

(0 - 20cm) soil.

Properties Land use Types LsD(o.05)

Avail. P. (g/kg) 45.50 43.90 58.10 25.20 14.80 19.02



CF = one year cassava farm land.

4.7 ORGANIC MATTER FRACTIONS

The organic matter fractions including carbohydrates (R-CHO),

humic substances (HS), fulvic acids (FA) and humic acids (HA)

are shown in Table 9. Value for R-CHO under the FV was highest

followed by the CF. Although, these were not statistically

different from each other, they were significantly (P50.05)

different from the other three land use types, which were

statistically the same. Values ranged from 2.83gkg-I under GV to

1

S.85gkg ' under FV. The result from this study confirmed the

observation of Spaccini et a/., (2001) who reported that R-CHO's I

were reduced when tropical forested soils were cultivated. Later,

Spacci ni et a/. , (2002), reported discrepancies in R-CHO contents

between forested and cultivated soils, but showing that in most

cases, the forested soil contained more R-CHO's.

The HS and FA were highest in the FV, whereas the CC had the

highest concentration of HA. These values, expected to reflect

the OM status in the different land use types, did not follow any

regular pattern. This indicated that concentrations of OM

fractions under the different land use types did not depend on

the total soil organic matter (SOM). However, the results

confirmed the report of Machado and Gerzabek (1993) who

stated that HS was higher for forested soil while HA was higher

for cultivated soil. The low value of FA under CC, compared to FV

(Table 9), may be due to the presumption that soil cultivation I

promotes its mineralization (Machado and Gerzabek, 1993).

Earlier, Gerzabek et a/., (1991) had reported that smaller

molecules such as FA, in comparison with higher molecular

weight fractions like HA, decomposed faster with cultivation. This

explains the higher value of HA obtained under CC. However, in

consideration of predominance of FA and HA, the results of this

study partially contradicts those of Sarmah and Bordoloi (1993)

who reported predominance of FA and HA in tropical soils of

Assam, India.

Table 9. Organic matter fractions.

Properties Land use Types LsD(o.0~)

FY = four year fallow; GV = grass vegetation; ,

CC = continuously cultivated; FV = forest vegetation;

CF = one year cassava farm land; R-CHO = carbohydrate;

HS = humic substance; FA = fulvic acid; HA = humic acid.

4.8 CORRELATION BETWEEN AGGREGATE STABILITY INDICES

AND SOME PHYSICO-CHEMICAL PROPERTIES OF SOILS

UNDER DIFFERENT LAND USE TYPES.

Under the FY (Table 1 0 HS, negatively and positively,

correlated significantly (P50.05) with CDI and CFI, respectively,

while R-CHO, FA, HA, OM, KSat, BD and PL, significantly correlated

with MWD only. At the macro-level bt was more important in

aggregate stability, while HS played a leading role in

microaggregate stability than the other properties.

Table 10. Simple correlation analysis between aggregate stability indices and some physico-chemical

. --- . -- . - properties .- of soil under f o u r e a r fallow -- land [FY). - -. R-CHO HS FA HA OM Ksat BD pt

C D I (%) -0.18NS -0.91" 0.18NS -0.13NS -0.15NS 0.16 0.21NS O.06NS

ASC (%) -0.41NS 0.46NS -0.72NS -0.41NS -0.39NS -0.67NS -0.49NS 0.36NS

C F I (%) 0.19NS 0.91" -0.17NS 0.13NS 0.15NS -0.15NS -0.21NS -0.O6NS

x Significant at 5%

** Highly significant at 1% NS = Not significant N value = 5

MWD = Mean weight diameter DR = Dispersion ratio CDI = Clay dispersion index ASC = Aggregated silt + clay CFI = Clay flocculation index

With respect to GV (Table ll), R-CMO significantly correlated

positively with CDI and negatively with CFI. The HS had a

significant positive correlation with Mw'D, and CDI, and a

significant negative correlation with CFI. The FA had significant

relationship only with MWD but not with any of the

microaggregate stability indices. The HA correlated significantly

with MWD, CDI and CFI, while OM, only correlated significantly

with ASC. The Ksat and BD significantly correlated with CDI and

CFI, while Pt did not significantly correlate with any of the indices

of aggregation. The HS, HA and OM were more important in

structural stability of soils under the GV.

Table 1 1 Simple correlation analysis between aggregate stability indices and some physico-chemical . -

properties of soil under grass vegetation land (GV). ,

R-CHO HS FA HA OM Ksat BD Pt

MWD 0.88~s 0.97** 0.92% 0.95* 0.67 NS 0.88 NS -0.82 NS -0.57 NS

( m m ) I

D R (Yo) 0 . 0 1 ~ s 0.08 N S -0.08 NS 0.09 NS 0.66 NS -0.11 NS -0.21 NS -0.04 NS

C D I ( % ) 0.95* 0.98** 0.73 NS 0.98** 0.89 NS b.91* -0.96** -0.75 NS

ASC ( % ) - 0 . 7 0 ~ ~ -0.74 NS -0.42 NS -0.75 NS -0.99** -0.62 NS -0.83 NS 0.67 NS

C F I ("10) -0.97** -0.99** -0.75 NS -0.99** -0.83 NS -0.95" 0.97** 0.78 NS

x Significant at 5%

* Significant at 1% NS = Not significant N value = 4


Considering CC (Table 1 2 only FA and BD did not have

significant relationship with all the aggregate stability indices

measured, whereas OM, OM components, KSat and Pt related

significantly with MWD and ASC but not with DR, CDI and CFI.

HA and OM played more prominent !ole in aggregation of the

CC.

Table 12. Simple correlation analysis between aggregate stability indices and some physico-chemical properties of soil under continuously cultivated I

land (CC). - - - - -. - - - -- - - - - R-CHO HS FA HA OM Ksat BD Pt

MWD 0.99"" 0.99** -0.82 NS 1.00** 0.98** 0.94* -0.78 NS 1.00**

CDI (Ole) 0.69 NS 0.79 NS -0.38 NS 0.75 NS 0.68 NS 0.52 NS -0.31 NS 0.73 NS

ASC (%) -0.92 * -0.98** 0.62 NS -0.95* -0.98** 0.54* 0.57 NS -0.98**

C F I (%) -0.69 NS -0.79 NS 0.38 NS -0.75 NS -0.68 NS 0.52 NS 0.31 NS -0.73 NS

* Significant a t 5%

** Significant a t 1% NS = Not significant N value = 4


For the FV shown in (Table 13), R-CHO, HS and OM were

significantly correlated with MWD only, while Pt significantly

correlated with DR. The other soil properties showed no

significant relationship with the indices of aggregation. The OM,

R-CHO, Pt and HS were of importance in structural stability of

the soils under FV. I

Table 13.

R-CHO

I

Simple correlation analysis between aggregate stability indices and some pHysico-chemical properties of soil under forest vegeta2ion land (FV). I - - -- - -- - -- - - --

HS FA HA OM Ksat BD Pt

M W D 0.93* 0.95* 0.39 NS 0.88 NS 0.96* 0.65 NS -0.88 NS 0.34 NS

(mm)

D R ( % ) -0.18~s -0 .06~s -0 .70~s 0 . 1 8 ~ s -0 .10~s -0 .67~s 0 .24~s -0.90*

C D I (%) 0.75 NS 0.83 NS -0.01 NS 0.89 NS 0.82 NS 0.43 NS -0.71 NS 0.14 NS

ASC (%) -0.30 NS 0.40 NS 0.42 NS -0.58 NS -0.36 NS 0.25 NS 0.27 NS 0.64 NS

C F I (%) -0.78 NS 0.81 NS -0.32 NS -0.75 NS -0.81 NS -0.71 NS 0.74 NS 0.57 NS

* Significant at 5%

* * Significant a t 1% NS = Not significant N value = 5


I

With regard to CF (Table 14), FA and KSat significantly correlated

with MWD alone, while R-CHO significantly correlAed with all the

indices of aggregate stability. The HS, OM and Pt did not

correlate significantly with MWD but with all the other indices.

The HA correlated significantly with only CDI and CFI while BD

significantly correlated negatively and positively with MW D and

ASC, respectively. FA and K t are important in macro

I

aggregation, but are less important than the other properties in

micro aggregation of soil under CF.

Table 14. Simple correlation analysis between aggregate stability indices and some physico-chemical properties of soil under one year cassava farm

- . (CF). R-CHO HS FA HA OM Ksat BD Pt

..

M W D 0.97** 0.89~s 0.91* 0.66~s 0.87~s 0.97** -0.99** 0.89 NS (mm) DR ( O h ) 0.93* 0.95* 0.81 NS 0.85 NS 0.90* 0.77 NS -0.86~s 0.94"

C D I ( O 1 0 ) 0.93* 0.98** 0.81 NS 0.91* 0.99** 0.81 NS -0.88 NS -0.95"

ASC ('10) -0.98** -0.99"" -0.85 NS -0.88 NS 0.99** 0.81 NS -0.94" -0.97**

C F I (010) -0.93* -0.98** -0.81 NS -0.91* -0.99** -0.81 NS -0.88 NS -0.95" . . --

% Significant at 5%

* Significant at 1% NS = Not significant N value = 5


The negative sign for Bu was due to the inverse relationship

existing between it and MWD. These results partially supported

the findings of Piccolo and Mbagwu (1990) who reported no

significant correlation between FA and OM with DR, but observed

significant correlation between HA and HS with DR. A holistic

view of the land use types indicated inconsistencies in the

correlation analyses, especially at the microaggregation level.

Perhaps, at this level, OM and its fr8ctions increased clay

dispersibility, indicating the dual function of OM as an

aggregating as well as a disaggregatin,g agent (Oades, 1984). I t

is probable that some other soil chemical properties such as

oxides of Fe, All Mg and Mn may be operating in conjunction

with OM and its fractions to effectively aggregate and stabilize

the soil particles. However, the influence of these oxides on

aggregate stability was not within the scope of this study.

4.9 PRINCIPAL COMPONENT ANALYSIS OF SOIL PROPERTIES

INFLUENCING AGGREGATE STABILITY UNDER DIFFERENT

LAND USE TYPES

Exception for the GV and CC whose variables were reduced to

three components each, variables in the land use types were

decomposed to four orthogonal components after Kaiser-

Varimax rotation of the PCA. I n all cases, the eigenvalues were

>l. Values 2 * 0.50 are significant. The variables with the

highest loadings in the components ar;e the component defining

variables (CDV).

4.9.1 PRINCIPLE COMPONENT ANALYSIS OF SOILS UNDER THE FOUR

YEAR BUSH FALLOW LAND (FY) (Tables 15a to 15e)

Table 15a shows the PCA of soil properties influencing mean

weight diameter (MWD). The 4 components accounted for the

total variance within the variables. Component 1 explained

55.4% of the total variance, with significant loadings on %clay,

Pt, %sand, Al, PI,-,,, Pn,i, AWC, FC, PWP, SP, HI HA, BD, &at, OM, I

FA, R-CHO, Mg, CEC and avail P. The size of the loads indicated

that this component referred to the influence of soil physical

properties on MWD. Component 2 had significant loadings on

KSat, OM, R-CHO, Na, Ca, K, CEC, TN, avail. PI and pH(H20),

explaining 24.7% of the variance and empHasizing the

contribution of exchange properties to macroaggregate stability.

Component 3, with significant loadings on FA, TN, pH(H20),

pH(Kcl), explained 10.0% of the variance and showed the

negative effect of pH on aggregate stability. Component 4 had

only %silt and HS with significant loadings and explained only

9.9% of the total variance. I t showed that increasing silt content

reduced MWD. The component defining variables (CDV) were

%clay, Na, pH (H20) and %silt.

Table 15a . Principal component analysis of soil properties influencing MWD under FY. - -

Variable .

Factor 1 Factor 2 Factor 3 Factor 4

MWD

%clay

pt %sand

A1

P",,

Pmi TAWC

FC

PWP

SP H

HA

f3 D

Ksat Vo 0 M

FA

R-CHO

Mg Na

Ca

K

CEC TN

Avail. P.

pH(H20)

pH(Kcl) %silt

HS Eig. Value

010 of Expl. Variances

Cumulative 90

P, = - ~ o t a l porosity, P,,,, = Macroporosity, P,, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, 1-1s = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

With regard to DR under FY shown in (Table 15b). Component 1

explained 53.3% of the variance with significant loadings on KSat,

R-CHO, FA, HA, OM, Mg, CEC, Al, H, avail. P, SP, FC, WP, AWC, Pt, P,,,

P,,,il Bo, %clay and %sand. The second component explained 25.2% of I

the total variance with significant loadings on KSat, R-CHO, HS, OM, TN,

Na, K, Ca, Mg, CEC and avail. P, while component 3, with significant

loadings on two variables, HS and %silt, explained 11.9% of the

variance. Component 4 explained 9.7% of the total variance and had

significant loadings on FA, pH(H20), pH(Kcl), TN. The CDV were

%clay, Na, %silt, and pH(H20).

Table 15b. Principal component analysis ' of soil properties influencing DR under FY

Variable Factor 1 Factor 2 Factor 3 Factor 4

K s a t

R-CHO

HS

FA

HA

pH(H20) pH(Kcl) O/o 0 M TN

Na

K

Ca

Mg CEC

Al

H

Avail. P

SP

FC PWP

TAWC

pt

pma

Pnri

BD %clay

%silt

%sand

Eig. Value .


Cumulative O/O

P, = Total porosity, PI,,, = Macroporosity, P,,, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

I

For CDI under FYI component 1 had significant loadings on 20 out of

the 28 variables and accounted for 53.99% of the variance. The sizes

of the significant loadings suggested the effect of texture, structure

and water retention properties on CDI. Also, R-CHO, FA, HA, and OM

influenced CDI. Component 2 explained 23.57% of the variances and

the variables with significant loadings above *0.80 included Na, K, Ca,

CEC. TN and avail P had significant loadings barely + 0.70, while KSat.,

R-CHO, and OM had significant loadings just above + 0.50. The

indication here was that the exchange' properties of the soil

contributed more to the CDI. The third component showed that HS

and %silt were the only variables influencing CDI, with %silt having a

diminishing effect. This component accounted for 12.75% of the total

variance. I n the fourth component, FA, pH (both in water and in Kcl)

and TN had significant loadings and this component accounted for only

9.69% of the variance. The magnitude of the loadings suggested that

pH had the strongest influence on CDI, even though, this influence

was negative. The CDV were %clay, Na, HS and pH(H20).

Table 15c. Principal component analysis of soil properties influencing CDI - under - - - --- FY - -- - -

Variable actor 1 Factor 2 Factor 3 Factor 4 a

CD I .I22

Ksat

R-CHO HS

FA

HA

PH(H20)

pH(Kcl) O/o 0 M

TN

Na K

Ca

Mg CEC A l H Avail. P

SP

FC

PWP

TAWC

pt

P"1,

Pmi

BD %clay

%silt

%sand

Eig. Value


Cumulative 010 - -. -- -

P, = Total porosity, P,,,,, = Macroporosity, P,,,, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

I n consideration of ASC under FYI component 1 alone accounted for

67.95% of the variance and the variables with significant loadings

included %clay and %sand, closely followed by the porosity

parameters and then, by water retention parameters. These

observations suggested the greater influence of texture, porosity and

water retention properties of the soil on AS^ than the BD, Ksatl R-CHO,

FA, HA, OM, Mg, CEC, All HI and avail. P. I n component 2, which

accounted for 13.80% of the variance, the exchange properties mostly

influenced ASC. Other chemical factors influencing the ASC were R-

CHO, HS, HA, OM, TN and avail PI while Ksat was the only pHysical

factor influencing ASC. Component 3 accounted for 10.31% of the

variance. Variables with significant loadings were HS, FA, pH(H20), TN

and avail P. The magnitude of the loadings showed that these

variables weakly influenced ASC with the exception of pH(H20)

exerting strong negative influence. The 4th component accounted for

only 7.88% of the variance with HS, pH(Kc1) and %silt as the only

variables with significant loadings. pH(Kc1) and %silt showed strong

negative influence. The CDV were %clay, Na, pH(H20) and pH(Kc1).

Table 15d. Principal component analysis of soil properties influencing ASC under FY

variable'-- -- Factor 1 Factor 2 Factor 3 Factor 4 . ASC

Ksat R-CHO HS

FA

HA

pH(H20) pH(Kcl) O/o O M

TN

Na K

Ca

Mg CEC A l H Avail. P SP

FC

PWP

TAWC

pt

P",, Pmi B D

%clay %silt

%sand

Eig. Value O/O o f Expl. Variances Cumulat ive O/O

P, = Total porosity, P,,,, = Macroporosity, P,,li = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

Table 15e shows the PCA of soil properties influencing CFI under PI.

I n component 1, 53.97% of the variance was accounted for. The I

physical properties including texture, porosity, water retention

characteristics and structural properties influenced CFi more than the

chemical properties which included R-CHO, FA, HA, OM, Mg, CEC, Al, H

and avail. P. Component 2 which explained 23.57% of the total

variance had significant loadings on KSat, R-CHO, OM, TN, Na, K, Ca,

CEC and avail P. The size of the loadings indicated that the exchange

properties influenced CFI mostly. Component 3 explained 12.77% of

the variance with significant loadings 6nly on HS and %silt.

Component 4, accounting for just 9.69% of the variance, had

significant loadings on FA, pH(H20 and Kcl) and TN with pH exerting

most of the influence. The CDV were %clay, Na, HS and pH(H2O).

Table 15e. Principal component analysis of soil properties influencinq CFI under FY

Variable Factor 1 Factor 2 Factor 3 Factor 4 . CFI

Ksat R-CHO

HS

FA

HA

pH(H20)

pH(Kcl) 010 0 M

TN

Na

K

Ca

Mg CEC

Al

H

Avail. P

SP

FC

PWP

TAWC

p t

P"1, Pllli

B D

%clay

%silt

%sand

Eig. Value

O/O of Expl. Variances

Cumulative O/o

P, = Total porosity, P,,,, = Macroporosity, P,, = ~icroporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

4.9.2 PRINCIPAL COMPONENT ANALYSIS OF SOILS UNDER GRASS

VEGETATION LAND (GV) (TABLES 16a - 16e).

The PCA in respect of MWD of soil under GV is shown in (Table

16a). The variables with significant loadings in component 1

were Ks,tl R-CHO, HS, FA, HA, pH(H20), Na and CEC. The others

were All BD, %clay, %silt and %sand. This component accounted

for 39.42% of the variance. I n the second component, which

accounted for 37.45% of the explained variance, KSat, R-CHO, Kt

Ca, Mg, avail PI SP, FC, WP, AWC, Pt, Pm,, Pmi and BD had

significant loadings. Following the magnitude of the loadings,

some of the exchange properties (Kt Ca and Mg), the water

retention and porosity characteristics influenced aggregate

stability more than the R-CHO fraction of OM. For component 3,

accounting for 23.13% of the variance, pH(Kcl), OM, TN, CEC, HI

avail. P, P,,i and BD, having significant loadings, were responsible

for aggregate stability. The sizes of the loadings indicated that

OM, TN, H and avail P contributed more. However, the

component defining variables were Na, SP and H.

Table 16a. Principal component analysis of soil properties influencinq MWD under grass veqetation land (GV)

Variable Factor 1 Factor 2 Factor 3

MWD .944 - . lo5 .312

Ksat .781 -. 548 -.300 R-CHO .742 -.536 .403

HS .837 -. 265. .478 FA .920 .302 .250 HA .811 -.318 .492

pH(H20) -.929 .204 -. 308

pH(Kcl) -.439 .430 -. 789 O/o 0 M .401 - .I12 .909 TN .334 0.64 .940 Na .973 -.079 -.218 K -.060 -.994 .090 Ca .060 .994 .090

Mg -.060 1.994 .090 CEC ,757 -.028 ,653 A 1 ,920 .302 .250 H . I91 -.262 .946

Avail. P .I82 .53 1 ,828

SP .036 .996 -.081 FC -.099 .993 -.067 PWP -.lo1 .992 -.069 TAWC -.094 .993 ' -0.064

P t -.390 .853 -.347

Pma -.322 .942 .093

Pmi -.464 .SO9 -.725

B D -.617 .538 -.574

O/~clay -.948 . l o 1 -.302 O/osilt .920 !302 .250 %sand .880 -.361 ,310

Eig. Value ' 11.431 10.860 6.708 010 of Expl. Variances 39.419 37.450 23.132 Cumulative 010 39.419 76.868 100.000

P, = Total porosity, P,,,, = Macroporosity, P,, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O h of Expl. Variances = Percent of explained variances.

With regards to DR under GV shown in (Table 16b), component 1

accounted for 40.35% of the total variance. The soil separates (i.e.

texture), contributed more to DR. The other variables with significant

loadings were KSat, R-CHO, HS, FA, HA, pH(M20, Kcl), Na, CEC, Al, Pmi

and BD. HS, FA and HA performed better than the R-CHO. I n

component 2, which accounted for 37.80% of the variance, Ksat,

R-CHO, K and Mg, having significant loadings, exerted negative

influences on DR, while the water retention parameters (SP, FC, WP

and AWC) together with Pt, Pmi and Ca had enormous positive

influence on DR. Component 3 accounted for 21.85% of the variance

with only 7 variables having significant loadings. These included

pH(Kcl), OM, TN, CEC, HI avail P and Pmi. The magnitude of the

loadings showed that HI TN and avail P contributed more than the

other variables in influencing DR. The CDV were %clay, SP and H.

Table 16b. Principal component analysis of soil properties influencing DR under grass vegetation land (GV)

-. ~ a - r i a b l e Factor 1 Factor 2 Factor 3

DR -.287 . I13 .951

Ksat .810 -.552 .I99 R-CHO .782 -.543 .307 HS ,884 -.274 .380 FA .940 , .300 .I62 HA .859 -.328 .394

P H ( H ~ O ) -.957 -.328 .394

pH(Kcl) -.521 .207 -.202

010 0 M .494 -.I37 ,858

TN -431 .038 .902 Na .945 -.066 -.321 K -.047 -.997 .064

Ca .047 .997 -.064

M!3 -.047 -.997 ,064 CEC -821 -.043 .569

A l .940 .300 .I62 H .290 -. 290 ,912 Avail. P .266 ,506 ,821

SP .024 .998 -.059

FC -. 108 I .994 -.025

PWP -.I11 .993 -.027 TAWC -.I03 .994 -.023

Pt -.427 .861 -. 277

Pma -.313 .937 ,156

Pmi -.539 .528 -. 656

BD -.676 .55 1 -.490

%clay -.975 ,104 -. 198 %silt .940 .300 .I62 %sand .909 .364 .204 Eig. Value 11.701 10.963 6.336

010 of Expl. Variances 40.349 37.803 2.848 Cumulative 010 40.349 78.152 100.000

P, = Total porosity, P,, = Macroporosity, P,,,i = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

Table 16c shows the PCA for CDI under GV. The first component

accounted for 37.50% of the explained variance. The water retention

properties accounted more for the reduction in CDI. Also, the porosity

of the soil significantly influenced the reduction in CDI. However, K

and Mg showed direct relationship with the CDI, which reduced as

these exchangeable cations decreased. Other variables with significant

loadings included, KSat, R-CHO, Ca, avail P and BD. The variables with

significant loadings in the second component, which explained 37.41%

of the variance were Ksat, R-CHO, HS, FA, HA, pH(H20), Na CEC, All

BD, %clay, %silt and %sand. I n the third component, which accounted

for 25.09% of the variances, the influence of HI TN, and OM on CDI

were highlighted. Other variables that affected CDI were HA, pH(kcl),

CEC, avail PI Pimi and BD. The CDV were SP, Na and H.

Table 16c.

variable

CDI

Ksat R-CHO

HS

FA

HA

pH(H20)

pH(Kc1) O/o 0 M

TN

Na K

Ca

Mg CEC

A l

H

Avail. P

SP

FC

PWP

TAWC

p t

Pnia

Pnii

B D

%clay %silt

%sand Eig. Value

Principal component analysis of soil properties influencing CDI under grass vegetation land (GV)

1

Factor 1 Factor 2 Factor 3

010 of Expl. Variances 37.500 37.408 25.072

Cumulative O/O 37.500 74.908 100.000

P, = Total porosity, P,,,, = Macroporosity, Pmi = Microporosity, TAWC - Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

The PCA for ASC under GV is shown in a able 16d). Component 1,

explained 37.32% of the variance. 13 variables in the component had

significant loadings on ASC. Regarding the magnitude of the loadings,

the water retention characteristics, some exchangeable cations (Kt Ca

and Mg) and porosity, especially P,,,, influenced ASC more than KSat,

R-CHO, avail P and BD. Component 2, which accounted for 35.47% of

the total variance, showed the influence of particle size and stabilized,

humified C on ASC. pH(H20), Na and All with very high loadings, also

influenced ASC. I n component 3, 27.21% of the total variance was

explained by the variables. OM, TN and H influenced ASC more than

the other variables which included HS, HA, pH(Kcl), CEC, avail PI Pmi

and BD. The CDV were SP, Na and H.

Table 16d. Principal component analysis of soil properties influencing ASC under grass vegetation land (GV)

2 . - - - .. - -- --


-- ASC

Ksat R-CHO

HS

FA

HA

pH(H20)

pH(Kcl) 010 0 M

TN

Na

K

Ca

Mg CEC

A l

H

Avail. P

SP

FC

PWP

TAWC

pt Pill,

Pnri

B D

%clay

%silt

%sand

Eig. Value


Cumulative 010

P, = Total porosity, P,,,, = Macroporosity, P,,,i = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent o f explained variances. I

Table 16e showed PCA of CFI under GV.' Component 1 explained

38.32O/0 of the variance. It was shown that the OM f rx t i ons reduced

aggregate stability since their increase reduced CFI. But increase in

pH(H20) increased CFI meaning that aggregate stability enhanced with

reduction in acidity. Also, with increase in the Na content (which

causes clay dispersion), flocculation was reduced, indicating reduced

aggregate stability. Reduction in %clay resulted in reduction in CFI,

indicating reduce aggregate stability. Hoyvever, O/osilt and %sand

showed an inverse relationship with CFI and, together with %clay,

indicated the influence of particle size on CFI. Component 2, explaining

37.58% of the total variance, showed the influence of the water

retention properties, on CFI. Also, K, Ca and Mg influenced CFI with K

and Mg exerting negative influences. Other variables with significant

loadings included KSat, R-CHO, avail P, PI., P,,, Pmi and BD. Component

3 accounted for 24.10% of the variances. The OM, but not its

fractions, affected CFI. Also, TN and H influenced the CFI more than

the other variables with significant loadings which ir,cluded pH(Kcl),

CEC, avail P, P ,,,, and BD. The CDV were Na, SP and H.

Table 16e. Principal component analysis of soil properties influencing CFI under grass vegetation land (GV)

L


CFI

Ksat R-CHO

HS

FA

HA

pH(H20)

pH(Kcl) 010 0 M

TN

Na

K

Ca

Mg CEC

Al

H

Avail. P

SP

F C

PWP

TAWC

p t

pma

Pmi

B D

%clay

%silt

%sand

Eig. Value


Cumulative 010 - - - - -- - -. - . . . . --

P, = Total porosity, P ,,,,, = Macroporosity, P ,,,, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent w~l t ing point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

4.9.3 Principal component analysis of soils under continuously

cultivated land (CC) (Tables 17a to 17e).

The PCA of MWD under CC is shown in (Table 17a). Component 1

explained 59.61% of the total variance. Variables with significant

loadings were Ksatl R-CHO, HS, FA, HA, pH(l$cl), OM, TN, Ca and CEC.

The others were SP, FC, WP, AWC, Pt, P,,, BD, %clay, %silt and

%sand. Component 2, accounting for 23.87% of the total variance,

indicated the influence of the exchange properties on MWD. Also, HS,

pH(Kcl) and PIlli influenced MWD. Component 3 explained 16.52% of

the total variance with avail PI pH(H20), All HI K and %silt having

significant loadings. The CDV were FA, Na and avail P.

Table 17a. Principal component analysis of soil properties influencing MWD under continuously cultivated

1 -- land - (CC). ---- Variable Factor 1 Factor 2 Factor 3

MWD .910 .406 -.083

CEC A l H Avail. P

SP

FC

PWP .969 .226 -.096

TAWC .970 .229 . -.083

Eig. Value 17.287 6.922 4.791

010 of Expl. Variances 59.610 23.870 16.515

Cuniulative O/O 59.610 83.481 100.000 - . . -- ---- - - -- -. - - . - -- P, = Total porosity, P,,,, = Macroporosily, P,, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

Table 17b showed the PCA of soil properties influencing DR under CC.

Component 1 explained 56.34% of the total variance. Variables with

significant loadings were Ksat, R-CHO, HS, FA, 'HA, pH(Kcl), OM, TN,

Ca, CEC, SP, FC, WP and AWC. The others included Pt, P,,, BD, O/~clay,

%silt and %sand. The magnitude of the loadings revealed that the

water retention properties, texture, especially signified by %sand and

%clay, structural properties represented by BD and P,,, and OM

fractions (R-CHO, FA) influenced DR. component 2 explained 26.24%

of the total variance. Variables with significant loadings were HS,

pH(Kcl), Na, K, Ca, Mg, CEC, H and Pmi. The exchangeable cations

appear to be the influencing chemical properties even though, HS and

pH(Kcl) had some influence on the DR. I n component 3, the variables

explained 17.42% of the variance. Those with significant loadings were

pH(H20), K, Al, H, avail P, %silt. The sizes of the loads showed that

pH(H20) and avail P exerted the greatest negative influence on DR.

The CDV were FA, Na, pH(H20) and avail P.

Table 17b. Principal component analysis of soil properties influencing DR under continuously cultivated land

- -- w--- Variable Factor 1 Factor 2 Factor 3

DR

KS,,

R-CHO

HS

FA

HA

pH(H20)

pH(Kc1) O/o 0 M

TN

Na

K C a

Mg CEC

Al

H Avail. P

SP

F C

PWP

TAWC

pt

pma

Pnli

BD %clay

%silt

%sand

Eig. Value

Vo of Expl. Variances

Cuniulative 010 -- ---a-

P, = Total porosity, P,,, = Macroporosity, P,,i = Micr oporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

The influence of the variables on CDI for soil under CC is shown in

(Table 17c). Component I explained 55.75% of the total variance. FA,

with the highest loading exerted the greatest negative influence on the

CDI. With the negative sign on this variable, its decrease meant an

increase in CDI and since higher values for CDI means less stability,

FA enhanced aggregate stability. However, in this component,

following the pattern of loadings, the water retention parameters, total

and macro porosities, KSat, BD, texture, OM and its fractions and some

other soil chemical properties, all influenced CDI either adversely or

favourably. I n component 2, the variables explained 26.69% of the

total variance. Since increasing value of CDI means disaggregation,

therefore, pH(Kcl) and Mg, favoured aggregate stability. Contrarily,

variables with significant loadings, and without negative signs,

adversely affected CDI, thereby reducing aggregation when tney

increased. Na with the highest positive loading adversely exerted the

greatest influence on aggregate stability. The othel variables with

significant loadings were HS, K, Ca, CEC and Pmi. For component 3, the

variables explained 17.56% of the variations. pH(H20), K, Al, H, avail

P and %silt had significant loadings. The CDV were FA, Na and avail P.

Table 17c. Principal component analysis of soil properties influencing C D I under continuously cultivated land -

. (CC) Variable Factor 1

-- Factor 2 Factor 3

- - - - -- -- CDI .457 .821 ,343

R-CHO .933 .351 -.080

Mg CEC

Avail. P -.024 ' -.I95 .980 SP

F C

PWP

TAWC

pt

pn,,

Pn,i

B D

%clay

O/~silt

%sand

Eig. Value


Cumulative 010 55.748 - - - - - -- - - - - - - - - - - - - ,82.436

-- - -- 100.000

P, = Total porosity, P,,,,, = Macroporosity, P,,,, = Microporosity, TAWC - Total available water capacity, FC = Field capacity, PWP = Permanent w ~ l t ~ n g point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Var~ances = Percent of explained variances.

Principal component analysis of ASC of soil under CC is shown in

(Table 17d). Twenty out of the 28 variables in component 1 had

significant loadings. Of these 20, only FA, pH(Kcl), BD, %clay and %silt

favourably influenced ASC. FA, with the highest loading, exerted the

greatest influence. Component 1 explained 57.66% of the total

variances. I n component 2, only 9 variables had significant loadings.

This component explained 25.76% of the total variance. The 9

variables included HS, pH(Kcl), Na, K, Ca, Mg, C'K, H and Pmi.

Component 3 explained 16.58% of the total variance. I n this

component, the only physical parameter influencing ASC is %silt

whereas pH(H20), K, Al, H and avail P, were the chemical properties

exerting influence on ASC. Avail P had the greatest favourable

influence on ASC. The CDV were FA, Na and avail P.

Table 17d. Principal component analysis of soil properties influencing ASC under continuously cultivated land (CC)

.-

Variable Factor 1 ~actor-2 Factor 3

ASC

Ksat

R-CHO

HS

FA

HA

pH(H20)

pH(Kc1) O/o 0 M TN

Na

K

Ca

Mg CEC Al

H

Avail. P

SP FC

PWP

TAWC

pt

P",,

Pnli

BD O/~clay -.919 -.390 -.053

%silt -.691 -.258 .675

%sand ,922 .388 -.017

Eig. Value 16.723 7.467 4.808

O/O of Expl. Variances 57.665 35.756 16.579

Cumulative O/o 57.665 83.421 100.000

P, = Total porosity, PI,,, = Macroporosity, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Hurnic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

Table 17e shows PCA of CFI for soil under CC. Component 1 explained

55.75% of the total variance. Of the 20 variables with significant

loadings, FA exerted the greatest influence, while Ca exerted the least.

Increasing values of CFI implies, increasing stability. Therefore, FA

exerted the greatest favourable influence on CFI. Also, pH(Kcl), BD,

%clay and %silt exerted favourable influence on CFI. With the

exception of FA, OM and its other fractions adversely affected CFI,

causing disaggregation. All other chemical parameters with significant

loadings unfavourably influenced CFI. Physical parameters with

significant loadings having unfavourable influence on CFI included the

water retention parameters, KSat, Pt and P,,. Component 2 explained

26.69% of the variances. Na with the highest s i~ni f icant loading

exerted the greatest influence but induced disaggregation due to its

dispersive function. Other variables with significant loadings were HS,

pH(Kcl), Na, K, Ca, Mg, CEC and Pfmi. I n component 3, variables with

significant loadings were only 6 namely, pH(H20), K, Al, HI avail P and

%silt. This component accounted for 17.56% of the explained total

variance. The CDV were FA, Na and avail P. ,

Table 17e. Principal component analysis of soil properties influencing CFI under continuously cultivated land

- K S L Variable Factor 1 Factor 2 Factor 3

CFI

KS.3,

R-CHO

HS

FA

HA

pH(H20)

pH(Kcl) 010 0 M

TN

Na

K

C a

M g CEC

A l

H

Avail. P

SP

FC

PWP

TAWC

pt

P",,

Pmi

BD %clay

O/osilt .

%sand

Eig. Value

O/o of Expl. Variances

Cumulative O/O --- 1 P, = Total porosity, P,,,,, = Macroporosity, P,,,i = Mtcroporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point', HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigeli value, O/O of Expl. Variances = Percent o f explained variances.

4.9.4 Principal component analysis of soils under Forest

vegetation land (FV) (Tables 18a to 18e).

Table 18a shows the principal component analysis of MWD of

soils under FV. Component I explained 41.5% of the total

variance and had significant loadings on Ksatr R-CHO, FA,

pH(H20), TN, Na, Ca, CEC, H, SP WP, AWC, Pt, P,,, BD, %clay,

?/osilt and %sand. The magnitude of the loadings showed that I

this component refers to the influence of FA, Na and porosity on

MWD. Component 2 explained 38.6% of the variance having

significant loadings on R-CHO, HS, HA, pH(H20), OM, TN, K,

avail PI SP, WP, AWC, Pmi, BD, %clay, %silt and %sand.

Component 3, with significant loadings on Ca, Mg, FC and Pmi,

explained 11.2% of the total variance. The fourth component

which explained only 8.7% of the variance had significant

loadings on TN, All and H. The CDV were FA, HA, Mg and Al.

Table 18a. Principal component analysis of soil properties influencing MWD under forest vegetation land (FV)

Variable Factor 1 Factor 2 F ~ c t o r 3 Factor 4

MWD

Ksat R-CHO

HS

FA

HA /

pH(H20)

pH(Kcl) 010 0 M

TN

Na

K

Ca

Mg CEC Al H

Avail. P

SP

FC

PWP

TAWC

pt

pma

Pmi

B D

%clay

O/osilt

%sand

Eig. Value

O/O of Expl. Variances Cumulative 010

P, = Total porosity, P,, = Macroporosity, P,, = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

Principal component analysis of DR of soils under FV is shown in (Table

18b). component 1 explained 40.5% of the variance with significant

loadings on Ksat, R-CHO, FA, pH(H20), TN, Na, Ca, CEC, HI SP, WP,

AWC, Pt, Pm,, BD, %clay, %silt and %shnd. Component 2, with

significant loadings on R-CHO, HS, HA, pH(H20), pH(Kcl), OM, TN, Kt,,

avail PI SP, WP, AWC, P,il BD, %clay, %silt and %sand, accounted for

37.4% of the total variance. Component 3, which explained 13.1% of

the total variance, had significant loadings on Ca, Mg, FC, and Pmi,

while component 4, which accounted for only 9.0% of the total

variance had significant loadings on TN and Al. The CDV were FA, Na,

HA, Mg and Al. 1

Table 18b. Principal component analysis of soil properties influencing DR under forest vegetation land (FV).

a


Ksat R-CHO

HS

FA

HA

pH(H20)

pH(Kcl) O/o 0 M TN

Na

K

Ca

M g CEC

A l H

Avail. P SP

FC

PWP

TAWC

pt

pma

Pmi

B D

%clay ,

%silt

%sand

Eig. Value


Cumulative O/o

P, = Total porosity, P,, = Macroporosity, Pmi = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA t Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

The PCA of CDI for soils under FV is shown i m (Table 18c). Component

1 explained 43.4% of the total variance and had significant loadings on

Ksatl R-CHO, FA, pH(H20), TN, Na, Ca, CEC, HI SP, WP, AWC, Pt, Pma,

BD, %clay, %silt and %sand. Component 2 had significant loadings

on R-CHO, HS, HA, pH(H20), pH(Kcl), OM, TN, K, avail PI Pmil BD,

%clay, %silt and %sand and explained 37.0% of the total variance.

Component 3, which accounted for 11.5% of the total variance, had

significant loadings on Ca, Mg, FC and Pmi, while component 4, I

explaining just 8.0% of the total variance had significant loadings only

on TN, All and H. The CDV include Na, HA, Mg and Al.

Table 18c. Principal component analysis of soil properties influencing C D I under forest vegetation land (FV). .


I

CDI .011 .937 -.239 .255

Ksat R-CHO HS

FA

HA

pH(H20) PH(KCI)'

O1o 0 M

TN

Na

K

Ca

M g CEC

Al

H Avail. P

Sf'

FC

PWP

TAWC

pt

pma Pmi

BD %clay . %silt

%sand

Eig. Value

010 of Expl. Variances 43.448 36.987

Cumulative 010 43.448 80.435

P, = Total porosity, P,, = Macroporosity, Pmi = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

The Kaiser-Varimax rotated PCA of ASC for soils under FV is shown in

(Table 18d). Component 1 explained 42.0% of the total variance.

Significant loadings in this component were observed on Ksat, R-CHO,

FA, pH(H20), TN, Na, CAI CEC, HI SP, WP, AWC, Pt, P,,, BD, %clay,

%silt and %sand. Component 2 explained 35.9% of the total variance I

with significant loadings on R-CHO, HS, HA, pH(H20), pH(Kcl), OM, TN,

Kt avail PI SP, WP, AWC, Pmi, BD, %clay, %silt, and Ohsand. The third

component account for only 13.4% of the total variance, having

significant loadings on Cat Mg, FC and Pmi while component 4,

explaining just 8.6O/0 of the total variance had significant loadings on

TN, Al, and H. The CDV were Na, HA, Mg and Al.

Table 1Sd. Principal component analysis of soil properties influencinq ASC under forest veqetatim land (FV) -

Variable Factor 1 Factor 2 Factor 3 Factor 4 . ASC

Ksat R-CHO HS

FA HA

pH(H20)

pH(Kcl) %OM ' TN

Na

K

Ca

M g CEC

Al

H

Avail. P

SP

FC

PWP

TAWC

p t pma

Pmi

B D

%clay

%silt

%sand

Eig. Value


Cumulative O/O


The PCA of CFI for soils under FV is shown in (Table 18e). Component

I accounted for 41.0% of the total variance with significant loadings

on Ksat, R-CHO, FA, pH(H20), TN, Na, Ca, CEC, H, SP, WP, AWC, P,,

P,,, BD, %clay, %silt and %sand. The second component explained

37.8% of the total variance, with significant loadings R-CHO, HS, HA,

pH(H20), pH(Kcl), OM, TN, K, avail P, SP, PWP, TAWC, Pmi, BD, O/oclay,

%silt,and %sand. The third component explained 12.5% of the total

variance, having significant loadings on Ca, Mg, FC and Pmi, while

component 4, with significant loadings on TN, Al and HI explained

8.6% of the total variance. The CDV included Na, HA, Mg and Al.

Table 18e. Principal component analysis of soil properties influencing C F I under forest vegetation land (FV).


C F I

Ksat

R-CHO HS FA HA

pli(H20) pH(Kcl)' O/o 0 M TN Na K Ca

Mg CEC Al H Avail. P SP FC PWP TAWC

pt

pma Pmi f3 D

%clay %silt %sand Eig. Value 010 of Expl. Variances Cumulative O/O

P, = Total porosity, P,, = Macroporosity, Pmi = Microporosity, TAWC = Total available water capacity, FC = Field capacity, ?WP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

4.9.5 PRINCIPAL COMPONENT ANALYSIS (PCA) OF SOIL

UNDER ONE-YEAR CASSAVA FARM LAND (CF). TABLES 19a

to 19e).

The PCA of MWD for soil under CF is shown in (Table 19a).

Component 1 accounted for 53.2% of the total variance, with

significant loadings on KSat, R-CHO, HS, FA, HA, pH(Kcl), OM, TN,

SP, FC, WP AWC, Pt, P,,, BD, %clay and %sand. Component 2

explained 21.4% of the total variance, having significant

loadings on Ca, Mg, CEC, HI avail P and Pmi. Component 3, with

significant loadings on pH(H20), Na, Kt All HI %clay and %silt,

explained 16.5% of the total variance, while component 4

explained 8.9% of the total variance and had significant loadings

only on Na, and K. The CDV were HS, Pmi, %silt and K.

Table 19a. Principal component analysis of soil properties influencing MWD under one-year cassava farm land (CF)


MWD

Ksat

R-CHO

HS

FA

HA

pH(H20) ' pH(Kcl) O/o 0 M

TN

Na K

Ca

Mg CEC A1

H

Avail. P

SP

FC PWP

TAWC

pt

pma

pmi

B D

%clay

%silt

%sand

Eig. Value


Cumulative O/O


The PCA of DR for soils under CF is shown in (Table 19b). The first

component explained 52.8% of the total variance with significant

loadings on KSat, R-CHO, HS, FA, HA, p ~ ( ~ h ) , OM TN, SP, FC, PWP,

TAWC, Pt, Pma, BD, %clay and %sand. The secmd component

explained 21.4% of the total variance. Significant loadings were

observed on KSat, Ca, Mg, CEC, H, avail P and Pmi. The third component

accounted for 16.8% of the total variance, having significant loadings

on pH(H20), Na, K, At, H and %silt. The fourth component had

significant loadings on FA, Na, and K and explained only 9.0% of the

total variance. The CDV included HS, Pmi, %silt and K.

Table 19b. Principal component analysis of soil properties influencing DR under one-year cassava farm land .

-. (CF )


DR

&at

R-CHO

HS

FA

HA

pH(H20)

P H W W O/o 0 M

TN

Na

K

Ca

Mg CEC

A1

H

Avail. P

SP

FC

PWP

TAWC

pt

Pma

Pmi

B D

%clay

%silt

%sand

Eig. Value


Cumulative O/O


Table 19c showed the PCA of soil properties influencing CDI under CF.

Component 1 explained 52.8% of the total variance. Significant

loadings were observed on KSat, R-CHO, HS, FA, Pt, P,,, BD, %clay and

%sand. Component 2 accounted for 21.0% of the total variance and

had significant loadings on KSat, Ca, Mg, CEC, HI avail P and Pmi. The

third component, which explained 16.0% of the total variance, had

significant loadings on pH(H20), All H and %silt. Component 4

accounted for 9.8% of the total variance with signific3nt loadings on

FA, Na and K. The CDV were HS, Pmi, %silt and K.

Table 19c. Principal component analysis of soil properties influencing C D I under one-year cassava farm land (CF) .

Variable Factor 1 Factor 2 F a d o r 3 Factor 4

- - - C D I .901 .I11 .418 -.027

Ksat R-CHO

HS

FA

HA

pH(H20)

pH(Kcl3 O/o 0 M

TN Na

K

Ca

M g CEC Al

H

Avail. P

SP

FC

PWP TAWC

pt

pma

Pmi

BD %clay

O/osiIt

%sand

Eig. Value


Cumulative %


Table 19d showed PCA of ASC for soils under CF. Component 1

explained 53.3% of the total variance. Significant loadings were

observed on 17 out of the 28 variables. These were Ksat, R-CHO, HS,

FA, HA, pH(Kcl), OM and TN. The other were SP, FC, WP, AWC, Pt, P,,,

BD, %clay and %sand. Component 2 explained 20.9% of the total

variance, with significant loadings on KSat, Ca, Mg, CEC H, avail P and

Pmi. Component 3, explaining 16.3% of the total variance, had

significant loadings on pH(H20), Na, Al, H and O/osilt. The fourth

component explained 9.5% of the total variance, having significant

loadings on FA, Na, and K. The CDV were HS, Pmi, %silt and K.

Table 19d. Principal component analysis of soil properties influencing ASC under one-year cassava farm land (W


ASC -.971 -.I92 -.I42 -.024

Ksat

R-CHO

HS FA HA ,

Na

K

Ca

Mg CEC Al

H

Avail. P

SP

PWP .904 .288 .216 .232

TAWC .903 .291 .217 .230

Eig. Value 15.464 6.068 4.710 2.752

010 of Expl. Variances 53.325 20.924 16.262 9.489

Cumulative 010 53.325 74.249 90.511 100.000 -

P, = Total porosity, P,, = Macroporosity, P,,i = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent of explained variances.

The PCA of CFI for soils under CF is shown in (Table 13e). Component

1 accounted for 52.8% of the total variance and significant loadings

were observed on 17 out of the 28 variances. These variables were

Ksat, R-CHO, HS, FA, HA, pH(Kcl), OM TN, SP, FC, PWP, TAWC, Pt, P,,,

BD, %clay and %sand. For the second component, significant loadings

were observed on KSat, Ca, Mg, CEC, HI avail P and Pmi. These,

together with the other variables in this component, explained 21.1%

of the total variance. Component 3 accounted for 16.3% of the total

variance and had significant loadings on pH(H20), Al, H and %silt.

Component 4 which explained 9.8% of the total variance had

significant loadings on FA, Na and K. The CDV were HS, Pmi, O/osilt and

K.

Table 19e. Principal component analysis of soil properties influencing C F I under on'e-year cassava farm land (CF)


Ksat

R-CHO

HS

FA

CEC . I 2 5

Avail. P .388

PWP ,902 TAWC .902

pt

pma

Pmi

BD %clay %silt %sand Eig. Value 010 of Expl. Variances

Cumulative 010 52.766

P, = Total porosity, P,, = Macroporosity, Pmi = Microporosity, TAWC = Total available water capacity, FC = Field capacity, PWP = Permanent wilting point, SP = Saturation percentage point, HA = Humic acid, FA = Fulvic acid, R-CHO = Carbohydrate, HS = Humic substance, Eig.Value = Eigen value, O/O of Expl. Variances = Percent o f explained variances.

I n totality, the component defining variables cut across the physical

and chemical properties of the soils studied. The physical properties

included %clay, %silt, SP and Pmi. The chemical properties were Na,

pH, HS, H, FA, avail P, HA, Mg, Al and K.

The influence of these physical properties on aggregate stability

appeared to be complementary. Under GV, FV and CF, where the clay

fraction of soil separates exhibited negative relationship with MWD, the

silt fraction showed a positive relationship. Therefore, the relative

proportions of these particles influenced macro aggregate stability in

these land use types. However, under PY and CC, clay exerted

negative influence compared to the influence of SP and microporosity

on MWD. It also means that the effect of clay depended on those of

SP and microporosity. Where these physical properties exerted

negative effects on the macroaggregate or microaggregate stability

indices, their influences appeared diminishing since their increase or

decrease would mean reduced aggregate stability. Mbagwu e t a/ . ,

(2004), Mbagwu (1990) and Bruce-Okine and Lal (1975) observed

similar effects of silt on aggregate stability.

Using MWD to measure aggregate stability in all the land use types did

not show Na as a dispersant (Tables 15a, 16a, 17a, 18a and 19a).

However, under CC, and with regard to microaggregate stability

indices, Na was shown to be a dispersant. This is in agreement with

Igwe e t a/., (1999) who reported negative correlation of clay with

exchangeable sodium percent. Mbagwu e t a/., (1993) had earlier

reported displacement of polyvalent cation bridges by Na which led to I

clay dispersion.

I n all, but GV land use types, HS, FA and HA influenced aggregate

stability at both the macro and micro levels. R-CHO did not influence

aggregate stability. This confirms the result of the study by Spaccini et

a/., (2002). While studying the influence of organic' residues on

carbohydrate contents and structural stability of tropical soils, they

reported that aggregate stability was correlated with OM content but

not with carbohydrate. Similar observations had earlier been reported

by Dutarte et a/., (1993).

Regarding the PCA, R-CHO had significant loadings but never was a

CDV in any case (Tables 15a to 19e). This means that the R-CHO

exerted some influence on aggregate stability but suggested that its

role in aggregation

Mbagwu, 1999) as

degraded by soil

may be transient (Piccolo, 1996; Piccolo and l

it is a labile fraction of SOM which is rapidly

organisms (Insam, 1996). Possibly, physical

protection of easily biodegradable compounds, such as the R-CHO was

not favoured by the sandy texture of the soils studied, explaining why

this labile OM fraction could not be effective in aggregate stability.

Perhaps, carbohydrate takes part in aggregation only when it acts in

concert with HS.

At the microlevel, HS, FA and HA played prominent roles in stabilizing

the aggregates (Tables 15c - e; 17a - e; 18a - e; 19a - e). Piccolo

and Mbagwu (1990) and Mbagwu and Piccolo (1998) had earlier made

similar observations, reporting a significantly greater positive

correlation between microaggregate stability and humic acid than

carbohydrate contents. However, with respect to FA, this study

partially agrees with the observations of Piccolo and Mbagwu (1990)

who reported non-significant correlation of FA with aggregate stability.

Also, the result of this study contraditted the observation of

Shanmuganathan and Oades (1983) who reported increased clay

dispersion with FA.

At the macrolevel, Adesodu et a/., (2001) observed that R-CHO was

not very effective in stabilizing soil aggregates. This may mean that

other factors such as HS, FA and HA were required for effective

aggregate stability. This observation is in conformity with results

obtained from the study. Also, Piccolo and Mbagwu (1999) noted a

limited aggregating capacity of R-CHO under' natural conditions. This is

supported by the observation that, although, R-CHO had significant

loadings in all cases of the PCA, it was never a CDV.

The action of HS, FA and HA in aggregate stability may be that of soil

watet: repellency which is probably due to the formation of a

hydrophobic complex film on soil (Piccolo and Mbagwu, 1999). This

phenomenon is capable of reducing entry of water into the aggregates,

thus enhancing their stability in water. The reason for the longer

lasting aggregate stabilization action of HS, FA and HA than that of the

labile R-CHO is that the R-CHO is hydrophilic, preferring to reside in

the soil solution where they are rapidly biodegraded. This is likely the

case in this study, explaining further why the R-CHO was unable to

exert considerable influence on aggregate stability. Humic substances

have the advantage of a refractory chemical structure which makes

them more resistant to microbial attack. It had been reported that

humic substances improved and prolonged aggregate stability (Fortune

e t a/., 1989) hence, the observed influence on the soils studied.

CHAPTER FIVE

5.0 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

5.1 SUMMARY

The soils of the coastal plain sands in'south eastern Nigeria are

extensively cultivated for arable crops under 'he bush fallow

system or shifting cultivation. The resourcefully-poor, small-

holder farmers in the area grow such food crops as cassava,

maize, various vegetables, etc. under mixed cropping. These

soils are therefore among the most important soil resources of

Nigeria in terms of agricultural potential and utilization.

However, multinutrient deficiencies and high acidity, revealed by

the results of the physico-chemical analysis, are common

features of these soils necessitating the search for appropriate

soil amendment and conservation practices.

Aggregate stability of the soils has been

use types using both macro and micro

The land use type studied are four year

vegetation (GV), continuously cultivated

(FV) and one-year cassava farm (CF)

studied under five land

indices of aggregation.

bush fallow (FY), grass

(CC), forest vegetation

lands. The indices of

aggregation include mean weight diameter (MWD) for the

macro, while dispersion ratio (DR), clay dispersion index (CDI),

13 1

aggregated silt + clay (ASC) and clay flocculation index (CFI) are

used for the micro indices in each land use type, relationship

between aggregate stability and carbohydrate (R-CHO) and

humic substances in (HS) contents of the soils were established.

Observations

,stability with

I

indicated very poor correlation of aggregate

R-CHO suggesting that it was only transiently

contributing to aggregation of the soil particles. On the other

hand, humic substances (HS) including fulvic (FA) and humic

(HA) acids, correlated highly with aggregate stability. As

revealed by the Kaiser - Varimax rotated principal component

analysis (PCA), the humic substances were involved in soil

aggregation as they were found to be among the component

defining variables (CDV).

Improvement of soil properties with HS that are spontaneous,

long lasting and not biologically mediated indicate that these

materials could be especially beneficial on degraded tropical soils

with little bioactivity as depicted in soils derived from coastal

plain sands. There is therefore the need for further studies to

relate the endogenous HS and R-CHO to soil productivity.

I

5.2. CONCLUSIONS

Land use significantly influenced soil physical properties,

especially structure. Changes in land use such as conversion of

natural forest to crop land contributed to land degradation that

manifested in losses of soil organic matter (SOM) and reduced

stability of the soil aggregates. Aggregate stability was

/transiently medicated by carbohydrates and more permanently

by humic substances.

Continuous cultivation degraded soil structural properties due to

the diminished organic matter (OM) content. Such structural

degradation can be reversed with inputs of organic residues

which ameliorate soil physical properties as OM accumulation

does in forest, grass or bush fallow lands.

I

Humic substances including fulivc acids (FA) and humic acids

(HA) played a dominant and more important role than

carbohydrates (R-CHO) and organic matter (OM) in both the

micro and macroaggregate stability of these soils under the

different land use types. Under tropical conditions, the aggregate

stabilizing action of R-CHO appears to be transient because

it is easily biodegradable. I

Other physico - chemical soil properties are involved in

aggregate stability of these soils, especially under the grass

vegetation where aggregate stability was influenced by other soil

factors than the humified organic matter fraction. The physico -

chemical properties of the soils under the land use types varied,

and, in several instances, the variations were significant,

indicating that the results of this study were land use type -

specific. Sodium was found to behave both as a dispersing and I

flocculating agent, contrary to common knowledge.

RECOMMENDATIONS

The objectives of this study having been met, recommendations

are therefore, based on the results obtained. Due to the location

of these soils in the high rainfall and high temperature area, and

coupled with their loose nature, the rate of chemical

decomposition is fast and, leaching of hutrients out of root zone,

is significant. The maintenance of a stable structure for these

soils is a major problem due to structural decline under

cultivation. Hence, they are susceptible to erosion. Therefore,

mechanization, which can induce erosion, it not recommended

since the owners of the lands are resource - poor farmers.

For improved crop production in these locations, the

management practices recommended include:

Minimum tillage, which reduces loss of aggregate

stabilizing OM. Hoeing at the planting spots reduces the

overall soil disturbance.

Addition of crop residues, compost and animal manures,

which will be effective in stimulating microbial activities

and enhancing decomposition products such as HS, HA,

FA, etc. that help to stabilize soil aggregates. These

components, in addition to liming, improve the CEC which

sustains continuous cultivation without degradation of the I

physical and chemical soil properties.

Crop rotation, with inclusion of grass crops in rotation

helps to maintain soil organic matter (SOM) under

continuous cultivation providing aggregating influence of

plant roots.

Cover cropping and green manuring are recommended as

these improve aggregation and reduce raindrop impact on

soils, with resultant reduction of water erosion.

Supplementary fertilizer application, especially the split -

application method, is required. This will boost biomass for

soil surface cover to prevent erosion. However, acid-

forming fertilizers are to be avoided so that the H" does

not replace cations at the exchange sites to reduce pH,

and

(vi) Since low soil pH negatively influences availability of plant

nutrients, as well as activities of microorganisms, liming is

required in these soils and will also aid in stabilizing

M surface aggregates of the acid sands.

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I

APPENDIX

PROFILE PIT DESCRIPTION

One profile pit was dug in each of the five land use types. The

land use types are four-year bush fallow (FY), grassland (GV),

continuously cultivated land (CC), forest land (FV) and one-

year cassava farm land (CF). The profile designations are

- FYP(1) for FYI GVP(2) for GV, CCP(3) for CC, FVP(4) for FV and

CFP(5) for CF. The descriptive features of the pedons studied

are given below:

FYP(1):

Well drained four-year bush fallow sdil on 1% slope with dense

canopy cover. Termite mounds and earth-worm castes abound.

Ap (0 - 1Ocm): Dark reddish brown (5YR 2.512) moist, sandy

loam; medium subangular blocky; friable, slightly plastic and

slightly sticky; many fine, medium and coarse roots; insect

burrows are common; gradual smooth boundary.

I

AB (10 - 15cm): Dark reddish brown (5YR 3/') moist, loamy

sand; medium subangular blocky; friable, slightly plastic and

slightly sticky; many fine, medium and coarse roots; insect

burrows are common; gradual smooth boundary.

B A l (15 - 30cm): Reddish brown (5YR 414) moist, sandy

loam; medium subangular blocky; friable, plastic and sticky;

many fine, medium and few coarse roots; few insect burrows; I

' gradual smooth boundary.

BA2 (30 - 79cm): Yellowish red (5YR 416) moist, sandy loam;

medium su bangular blocky; friable, plastic and sticky; few fine

roots, diffuse boundary.

B (79 - 120cm): Yellowish red (5YR 418) moist, sandy loam;

medium subangular blocky; plastic and sticky.

GVP(2):

Moderately drained, on l0/0 slope, under grass vegetation.

Termite mounds abound.

Ap (0 - l l c m ) : Dark brown (7.5YR 312) moist, loamy sand;

medium crumb, friable, slightly plastic and slightly sticky; many

fibrous roots; diffuse smooth boundary'.

I

ABx (I1 - 21cm): Dark brown (7.5YR 3/2) moist, sandy loam;

strong subangular blocky; firm, slightly plas~ic and slightly

sticky; many fibrous roots; diffuse wavy boundary.

Bt l (21 - 61cm): Dark reddish brown (7.5YR 3/4) moist, sandy

, clay loam; medium subangular, blocky; slightly firm, plastic and

sticky; diffuse smooth boundary.

Bt2 (61 - IOIcm): Reddish brown (5YR 4/4) moist, sandy clay

loam; medium subangular, blocky; slightly firm, slightly plastic

and slightly sticky.

CCP (3):

Well drained, on 2% slope, under continuous cultivation for more

than thirty-five years. Earthworm castes are few. I

Ap (0 - l lcm): Dark brown (7.5YR 312) moist, loamy sand;

medium crumb; friable, many fine roots, diffuse, smooth

boundary.

AB (11 - 20cm): Reddish brown (5YR 414) moist, loamy sand;

medium subangular blocky; friable, slightly plastic and sticky;

many fine roots; insect burrows present; diffuse smooth I

boundary.

BA (20 - 88cm): Yellowish red (5YR 416) moist, sandy loam;

medium subangular blocky; friable, slightly plastic and slightly /

sticky; few fine roots; insect burrows present; diffuse smooth

boundary.

B (88 - 140cm): Yellowish red (5YR 418) moist, sandy loam; I

medium subangular blocky; friable, slightly plastic and sticky;

many fine roots; few insect burrows.

FVP(4):

Well drained, on flat topography, under forest vegetation with

unidentified tall and large tree species with very dense canopy

covers; termite mounds and earthworm castes are many.

I

Ah (0 - 13cm): Dark reddish brown (5YR 2.512) moist, loamy

sand; moderate medium crumb; friable, fine, medium and

coarse roots a bound; insect burrows common; diffuse smooth

boundary.

AB (13 - 29cm): Dark reddish brown (5YR 3/3) moist, loamy

sand; medium subangular blocky; friable, slightly plastic and

slightly sticky; many fine, medium and coarse roots abound;

many insect burrows; gradual smooth boundary. I

BAA (29 - 48cm): Reddish brown (5YR 4/4) moist, loamy

sand; subangular blocky; friable, slightly plastic and slightly

sticky; many fine and coarse roots; insect burrows common;

difus smooth boundary.

BA2 (48 - 126cm): Reddish brown (5YR 4/4) moist, sandy

loam; medium subangular blocky; firm, plastic and sticky; many

fine and coarse roots; insect burrows few; diffuse smooth

boundary.

B (126+): Yellowish red (SYR 4/6) moist, sandy loam; medium

subangular blocky; firm, plastic and sticky; fine and coarse roots

common.

Well drained, on 2% slope, under cassava crop.

Ap (0 - l lcm): Dark reddish brown (SYR 314) moist, loamy

sand; weak crumb, loose, non-plastic, non-sticky; many fine,

medium and coarse roots; insect burrows common; gradual

smooth boundary.

AB (11 - 27cm): Dark reddish brown (5YR 313) moist, loamy / I

sand; weak, medium subangular blocky; friable, slightly sticky;

medium and coarse roots common; few insect burrows; gradual

smooth boundary.

BAl (27 - 48cm): Yellowish red (5YR 416) moist, loamy sand;

weak medium subangular blocky; slightly firm, slightly sticky;

few coarse root; few insect burrows; gradual smooth boundary.

I

BA2 (48 - 74cm): Yellowish red (5YR 418) moist, sandy loam;

moderate, medium subangular blocky; firm, slightly plastic and

slightly sticky; diffuse smooth boundary.

B (74 - l l l c m ) : Yellowish red (SYR 518) moist, sandy loam;

moderate, medium subangular blocky; slightly plastic and

slightly sticky. I

University of Nigeria · as losses of soil organic matter (SOM) and aggregate stability. However,...

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