i
GODSON CHINONYEREM ASUOHA
PG/M.Sc/08/48968
THE IMPACT OF AGRICULTURAL LANDUSE PRACTICES
ON BIODIVERSITY IN ISIALA NGWA NORTH L.G.A. OF
ABIA STATE, NIGERIA
Department of Geography
Faculty of Social Sciences
Odimba Rita
Digitally Signed by: Content manager’s Name
DN : CN = Weabmaster’s name
O= University of Nigeria, Nsukka
OU = Innovation Centre
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THE IMPACT OF AGRICULTURAL LANDUSE PRACTICES
ON BIODIVERSITY IN ISIALA NGWA NORTH L.G.A. OF
ABIA STATE, NIGERIA
BY
Godson Chinonyerem ASUOHA
B.Sc. (Nig.)
PG/M.Sc/08/48968
A project submitted to the school of postgraduate studies and
the Department of Geography, University of Nigeria, Nsukka
in partial fulfillment of the requirements for the Degree of
Master of Science
Department of Geography
University of Nigeria,
Nsukka.
MARCH, 2014
iii
CERTIFICATION
Mr. Godson Chinonyerem Asuoha, a postgraduate student in the Department of
Geography, specializing in Biogeography, has satisfactorily completed the requirements
of the research work for the degree of Master of Science (M.Sc.) in Geography.
The work embodied in this project is original and has not been submitted in part
or full for any other diploma or degree of this or any other University.
………………………………
PROF. P.O. PHIL-EZE
(Supervisor)
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PROF. F. E. BISONG
(External Examiner)
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PROF. I.A. MADU
(Head, Department of Geography)
……………………………..
PROF. C.O.T. UGWU
(Dean, Faculty of the Social Sciences)
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DEDICATION
To Almighty God and my beloved wife, Mrs. Gloria O. Asuoha for their love and
unwavering support.
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TABLE OF CONTENTS
Title Page
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Certification -
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Dedication
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Table of Contents
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Acknowledgement
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List of Figures -
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List of Tables -
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List of Plates -
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List of Acronyms
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Glossary
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Abstract
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CHAPTER ONE: INTRODUCTION
1.1
Background to the Study
1.2
Statement of the Research Problem
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1.3
Aim and the Objectives of the Study
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1.4
The Study Area
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1.4.1
Relief
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1.4.2
Drainage
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1.4.3
Climate
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1.4.4
Soil
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1.4.5
Vegetation
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1.4.6
Wildlife
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1.4.7
Economic Activities
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1.5
Literature Review
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1.6
Conceptual Framework
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1.6.1
Millennium Ecosystem Assessment -
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1.6.2
The Japan Ecosystem Assessment
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1.7
Methodology
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1.7.1
Types and Sources of Data
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1.7.2
Sample Selection
1.7.3
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Sampling Technique and Data Collection
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1.7.4
Soil Sampling -
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1.7.5
Laboratory Analysis of Soil Samples -
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1.7.6
Techniques of Data Analysis -
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1.8
Plan of the Project
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CHAPTER TWO: THE NATURE OF BIODIVERSITY IN THE STUDY AREA
2.1
The Inventory and Check list of the plant species found in the
study area
2.2
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The Inventory and Check list of the animal species found in the
study area
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CHAPTER THREE: THE TYPES AND SPATIAL DISTRIBUTION OF
AGRICULTURAL LAND USE PRACTICES IN THE
STUDY AREA
3.1
Types of Identified Agricultural Land use practices in the
Study Area 56
3.2
3.3
3.4
The spatial Distribution of the Agricultural land use practices
in the Area
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Factors that determine the choice and location of agricultural
land use types in the study area
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Analysis of the relative strength of the factors of land use types
in Isiala Ngwa L.G.A. -
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CHAPTER FOUR: AGRICULTURAL LAND USE PRACTICES THAT
IMPACT BIODIVERSITY IN THE STUDY AREA
4.1
4.2
The relationship between agricultural land use practices
and biodiversity in the study are
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Determination of the diversity and biodiversity indices from the
land use types in the study area -
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4.3
The diversity indices of the animal species in the study area
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4.4
The biodiversity indices of the species in the study area
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4.5
The Key informant interviews (KIIs) and focus group discussion
with some farmers in the study area - -
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4.6
Hunting and Biodiversity in the study area in the study area
4.7
Farmer’s perception on biodiversity -
4.8
Soil characteristics and biodiversity in the area
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CHAPTER FIVE: MEASURES THAT WILL ENCOURAGE SUSTAINABLE
AGRICULTURAL LAND USE AND CONSERVATION
OF BIODVIVEISTY IN THE STUDY AREA
5.1
Modification of the farming system -
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5.2
The Role of the Government in modifying sustainable agricultural
land use and biodiversity conservation in the area 126
5.3
The role of non-governmental organizations in modifying
sustainable agricultural production in the area
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CHAPTER SIX: SUMMARY OF FINDINGS, RECOMMENDATIONS AND
CONCLUSION
6.1
Summary of Findings
6.2
Recommendations
6.3
Conclusion
REFERENCES
APPENDICES
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ACKNOWLEDGEMENT
I wish to express my profound gratitude to the Almighty God, for guiding me
throughout the duration of this study. I am also very grateful to my supervisor, Prof. P.O.
Phil-Eze for his priceless suggestions and guidance in the course of this research. My
thanks also go to my Head of Department, Prof. I.A. Madu for encouraging me.
I am equally grateful to Mr. D.M.O. Ebere, Rev. Fr. Paulinus M. Nwachukwu and
the staff of Isiala Ngwa North L.G.A., for their assistance. My sincere gratitude goes to
Dr. and Mrs. C.K. Ajaero for their invaluable support right from the beginning of this
study. I also thank Dr/Mrs. T.C. Nzeadibe, Dr/Mrs. G.C. Nji and Dr. Reginald Njokuocha
for assisting me in various ways. I also wish to thank Mrs. Philomena Ochiobi for her
financial and moral support.
I am also indebted to Dr/Mrs. Edward Ngozi Nwaogu for both their moral and
financial support. I also thank the management and staff of the soil science department of
National Root Crop Research Institute Umudike, Umuahia, for analyzing my soil samples
in their laboratory. I am indeed very grateful to Dr. Luke Nwaokeonu Onuoha for his
financial and moral support. My colleague, Mrs Daicy N. Ezeokpube assisted me during
my data analysis. To her I say thank you.
I also wish to express my heart-felt gratitude to my parents, Ezinna/Ezinne L.C.
Asuoha, my brothers, Mr. C.C., Asuoha, Mr. C.V. Asuoha, Mr. P.O. Asuoha and other
members of my family. Let me at this juncture appreciate my beloved wife, Mrs. Gloria
O. Asuoha, for alwayss being there for me through thick and thin. To other friends, too
numerous to mention, I thank you all for your support.
March, 2014
Godson Chinonyerem Asuoha
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LIST OF FIGURES
FIGURES
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Figure 1:
Abia State showing the study area
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Figure 2:
Isiala Ngwa North L.G.A showing the communities -
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Figure 3:
Millennium Ecosystem Assessment -
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Figure 4:
the Japan Ecosystem Assessment (JSSA)
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Figure 5:
Percentage of the plant species in the area
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Figure 6:
Percentage of different wildlife in the area
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Figure 7:
Isiala Ngwa North showing the spatial distribution of
intercropping -
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Isiala Ngwa North showing the spatial distribution of
mixed farming in the area
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Isiala Ngwa North showing the spatial distribution of
plantation agriculture in the area.
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Isiala Ngwa North showing the spatial distribution bush
fallowing in the area. -
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Map of Isiala Ngwa North showing the spatial distribution of
animal husbandry in the area. -
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Isiala Ngwa North showing the spatial distribution of the five
agricultural land use practices in the area
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Pie charts showing the farmers’ perception on biodiversity in the
area. -
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Figure 8:
Figure 9:
Figure 10:
Figure 11:
Figure 12:
Figure 13:
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LIST OF TABLES
Table 1:
Table 2:
Table 3:
Table 4:
Table 5:
Table 6:
Table 7:
Table 8:
Table 9:
Table 10:
Table 11:
Table 12:
Table 13:
Table 14:
Table 15:
Table 16:
Table 17:
Table 18:
Table 19:
Table 20:
Table 21:
Table 21:
The checklist of the plant species found in the study area 36
The inventory of the plant species found in the study area 42
The checklist of the animal species found in the study area 50
The inventory of the animal species found in the study area 52
Rotated component matrix of the factors that determine the
farmers’ choice of agricultural land use types in the study area
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The diversity indices of the plant species in the study area 82
Correlation matrix of the impact of Agricultural land use practices
on plant species in the study area.
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Rotated component matrix of the impact of agricultural land use
practices on plant species diversity in the study area.
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Relative contributions of the impact of agricultural land use
practices on plant species diversity. 88
The Diversity indices of the animal species in Isiala Ngwa
North L.G.A 89
Correlation matrix of the Impact of Agricultural land use practices
on the animal species diversity in the study area.
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The Rotated component matrix of the impact of agricultural land
use practices on the animal species diversity in the study area.
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Relative contributions of the impact of agricultural land use practices
on animal species
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Biodiversity indices from Agricultural land use types in
Isiala Ngwa North
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Correlation Matrix of the Impact of Agricultural Land use practices
on Biodiversity in the study area
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The Rotated Component Matrix of the impact of Agricultural land
use practices on Biodiversity in the study area
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The Results of the Key Informant Interviews and Focus Groups
Discussion with Farmers in the Area 101
Soil/Biodiversity relationship in the study area
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Rotated Component Matrix of the Soil Properties and Plant
Diversity Index in the Study Area 113
Rotated Component Matrix of the Soil Properties and Animal
Diversity Index in the Study Area 115
Rotated Component Matrix of Soil Properties and Biodiversity Index
in the Study Area.
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Rotated Component Matrix of Soil properties and Biodiversity Index
in the Study Area
119
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LIST OF PLATES
PLATE
Plate 1:
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A Section of the Vegetation of the Study Area from Amaorji
and Amapu Umuoha Community
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Plate 2:
One of the Quadrats being mapped out in Agburuke Community
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Plate 3:
Some of the Plant Species in the Area
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Plate 4:
One of the Plant Species in the Area -
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Plate 5:
Some Grazing Animals in Uratta Umuoha Community
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Plate 6:
Some Grazing Animals tied to Stakes in Amapu Umuoha
Community -
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Plate 7:
FGD with some Farmers in Uratta Umuoha Community
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Plate 8:
FGD with some Hunters in Ntigha community
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xii
LIST OF ACRONYMS
ANOVA:
Analysis of Variance
C.B.D.
Convention on Biological Diversity
CAP:
Common Agricultural Policy
CBM:
Community Biodiversity Management
CI
Conservation International
cT:
Tropical Continental Air mass
EEA:
European Environment Agency
EENRD/EC: European Evaluation Network for Rural Development of the
European community
FAO/UNEP: Food and Agriculture Organization/United Nations’ Environment
Programme
FAO:
Food and Agriculture Organization
FGD:
Focus Group Discussion
FGN:
Federal Government of Nigeria
HNV:
High Nature Value (associated with areas with a great diversity
of species).
ICU:
International Conservation Union
ITD:
Inter-tropical Discontinuity
KIIS:
Key Informant Interviews
LGA:
Local Government Area
MEA:
Millennium Ecosystem Assessment
mT:
Tropical Maritime Air mass
NBSAP:
National Biodiversity Strategy and Action Plan.
NGOs:
Non Governmental Organization.
TFT:
The Forest Trust
TNC:
The Nature Conservancy
WCS:
World Conservation Society
WWF:
World Wildlife Fund
xiii
GLOSSARY
1. Animal husbandry:
is a branch of agriculture concerned with the care and
breeding of domestic animals such as cattle, hogs, sheep
and horses.
2. Biodiversity:
the variety of life on earth-all the species of plants, animals
as well as microorganism, their genetic make up, where
they live and how they interact with themselves and their
surroundings.
3. Biodiversity index:
an expression used to describe the amount of species
diversity in a given area. It is given as:
Biodiversity index = the number of species in the area
The number of individuals in the area
4. Biogeochemical cycles:
the cyclical services of transformation of a chemical element
through the organism in a biotic community and their
physical environment.
5. Bush fallowing:
a type of subsistence agriculture where land is cultivated
for a period of time and then left uncultivated for several
years so that its fertility will be restored.
6. Coefficient of variation (cv)- the ratio of the standard deviation to the mean. It shows
the extent of variability in relation to the mean of the
population.
7. Cover:
the area covered by the above-ground parts of plants of a
species.
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8. Inter Croping:
the process of growing crops ie non-animal species or
variety to be harvested as food, livestock fodder, fuel or for
any other economic purpose.
9. Counting flock:
Counting birds directly from a suitable vantage point.
10. Diversity index (DI):
a statistic which is used to measure the differences among
number of a set consisting of various species. It is
calculated using Shannon Wiener’s diversity index, which
is given as:
H1
Where N
=
NLnN-
∑ (ni ln ni )
N
is the total number of individuals of all species, ni is the number of
individuals of species i, ln is natural logarithm
11. Direct count:
counting directly the number of individuals in a study
population.
12. Grazing land-
a field covered with grass or herbage and suitable for
grazing by livestock.
13. Mixed farming:
the use of a single farm for multiple purposes such as the
growing of cash crops and annual crops or the raising of
livestock.
14. Plantation agriculture:
an agricultural system generally a monoculture, for the
production of tropical and sub-tropical crops.
15. Physicochemical soil properties: soil chemical, physical and biological properties.
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16. Point count:
a count undertaken from a fixed location for fixed time
period.
17. Species diversity:
a measure of the diversity within an ecological community
that incorporates both species richness (the number of
species in a community) and the evenness of species.
18. Species richness:
a simple count of species in a community.
19. Grass:
a low green plant which grows naturally over a lot of the
earth’s surface
20. Shrub:
a woody perennial plant smaller than a tree.
21. Tree:
a large plant with a woody trunk and branches.
22. Wildlife corridor:
an area of habitat connecting wildlife populations separated
by human activities
xvi
ABSTRACT
This work examined the impact of agricultural land use practices on biodiversity in Isiala
Ngwa North L.G.A of Abia State, Nigeria. The study undertook biodiversity inventory in
terms of the types, species richness, diversity and distribution with respect to the effect of
agricultural land use on them. Data were collected via questionnaire survey. Copies of
questionnaire were administered on 400 purposively selected respondents. Key informant
interviews and focus group discussion were conducted with knowledgeable respondents
amongst the population of the study area. Primary data were further collected form field
observation. Soil data were collected and analyzed in the laboratory. Secondary data were
elicited and used to prepare the foundation of this study. Shannon Wiener’s Diversity
Index, Spearman’s rank correlation coefficient and Principal Component Analysis were
applied to the body of data. Shannon Wiener’s Diversity Index indicated the impact of
agricultural land use practices on biodiversity. Spearman’s rank correlation coefficient
indicated the relationship between soil characteristics and biodiversity. P.C.A. identified
the main effects of agricultural land use practices on biodiversity. They are: Loss of
biodiversity, habitat disturbance and simplification of diversity. The three components
together explained 64.296% of the total variance. Based on the results, the
recommendations on how to improve on the farming system in favour of biodiversity
include increased fallow periods, application of organic fertilizer, rotational grazing,
controlled burning, improved land tenure system, selective instead of outright clearing of
the plantation farms among others.
1
CHAPTER ONE
Introduction
1.1
Background to the Study
Land use is the human use of land. It involves the management and modification
of natural environment or wilderness into built environment such as fields, pastures and
settlement. According to Guttenberg (1959), land use is a key term in the language of city
planning. Land use and land management practices have a major impact on natural
resources including water, soil nutrients, plants and animals. Agricultural land use
denotes the land used for agricultural production, including both crops and livestock
(F.A.O., 1997a, F.A.O. 1999)
The standard classification used by FAO (1997a), divides agricultural land into
the following components:
Arable Land -
Land under annual crops, such as cereals, cotton, other
technical crops- potatoes, vegetables and melons.
Orchards and Vineyards - Land under permanent crops eg fruit plantations and
Meadows and Pastures –
Areas for natural grasses and grazing of livestock.
All these practices have different ways of impacting biodiversity.
Biodiversity according to Flint (1991), is the variety and variability of all plants,
animals and microorganisms on earth. Wilson (1992), defined biodiversity as variety of
living organisms at all levels – from genetic variants belonging to the same species,
through arrays of species, families and genera, and through population, community,
habitat and even ecosystems levels, and went further to depose that it is the diversity of
life itself. The convention on Biodiversity (CBD) at the 1991 Earth Summit in Rio de
2
Janeiro, Brazil, defined biodiversity as the variability among living organisms from all
sources, inter alia, terrestrial, marine, and other aquatic ecosystems and the ecological
complexes of which they are part. This includes diversity within species, between
species, and of ecosystems (CBD, 1992). Biodiversity according to Gaston (1996) is the
variety of life on earth at all its levels, from genes to ecosystems and the ecological and
evolutionary processes that sustain it. Also, Phil-Eze (2001), defined biodiversity as the
variety and variability of plant and animal genes and species and ecosystems found on the
surface of the earth. In other words, biodiversity is the variation among living organisms,
which includes species diversity (the number of different species), genetic diversity
(genetic variety within species) and ecosystem diversity (the vaiety of interaction among
living things in natural communities). Among all the definitions above, the most popular
is that given by the Convention on Biodiversity in 1992. However, for the purposes of
this study, biodiversity is operationally defined as the variety and variability of all plants
and animals on earth with particular reference to species richness and species diversity in
the terrestrial ecosystem.
The link between farming practices and biodiversity has been established since
the early nineties in works by Baldock et al (1993) and Beaufoy et al (1994). Mapping
efforts to identify High Nature Value (HNV) farmland have been carried out more
recently (European Environment Agency EEA, 2004; Pointereau et al 2007; Paracchini et
al, 2008). The HNV farmland concept has also been embedded in the Common
Agricultural Policy (CAP); to protect and enhance the European Union’s natural
resources and landscapes in rural areas. Agriculture thus continues to play a crucial role
both in the maintenance and the loss of biodiversity in rural areas.
3
In Nigeria, there are several agricultural land use practices that have the potential
to impact on biodiversity. Some of such practices include the nomadic herding which
involves movement of large number of ruminants, mainly cattle, according to seasonal
variations in browse and water availability in the dry savanna. The assumption is that
nomadic herding impacts negatively on the biota by the extensive grazing; through the
use of fire to suppress undesirable plant species, and soil compaction due to regular
trampling by animals on the move. Major factors involved in this nomadic herding are
grazing pressure that results in accelerated dispersal of seeds of trees through cattle
manure; cattle dung that provides a favourable micro-environment for tree growth,
especially by enriched soil fertility and above all, fire management regimes that favour
trees (Bassett and Boutrais, 1996).
Shifting cultivation conserves biodiversity through any of the following practices
such as controlled use of fire to clear vegetation on a selective basis, use of chopped nonburnt vegetation for mulching, minimal tillage, use of environmentally low-impact tools,
agro-forestry involving inter cropping among the trees left in situ and integration of
domestic animals. These practices could usefully inform policy, even though shifting
cultivation is unsustainable because of the reduced per capita agricultural land (Nye et al,
1996). Bush fallowing is a direct offshoot of shifting cultivation. It proceeds on a
rotational basis in plots around fixed settlements.
In Isiala Ngwa North L.G.A. of Abia State, some of these practices take place
with their attendant impact on biodiversity. In the study area, these practices are under
taken by the people with little or no knowledge of their likely consequences. A number of
studies on the impact of agricultural landuse practices on biodiversity have been done in
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various parts of Nigeria like Anikwe (2010) and Raufu (2010) among others. Biodiversity
harbours a great diversity of plant and animal species that have medicinal, aesthetic and
other values; and thus provides services that enhance and sustain human livelihood. As
some of the agricultural landuse practices have ways of exerting their impacts, which are
often negative on biodiversity, and there is no knowledge of the extent of these impact on
biodiversity; it is only necessary therefore that people be armed with the knowledge of
the consequences of their farming practices on biodiversity.
1.2
Statement of the Research Problem
Isiala Ngwa North Local Government Area of Abia State is essentially an
agricultural settlement .The economic activities and means of livelihood there are
dominated by agricultural production. Following the rich soils and vegetation covers
which favour farming activities, the people engage in various types of agricultural land
use practices. The area is well endowed with great diversity of plant and animal species.
As population increased, virgin lands were cleared for either human settlement or
agricultural production, thereby loosing the original forest vegetation. This is in line with
Okafor (1991), who noted that the growing agricultural land use intensification especially
in the densely settled parts of Nigeria, will have a negative impact on biodiversity in the
long run. The lost vegetation usually housed various plant species and wildlife. Due to
uncontrolled bush clearing and hunting, most of the keystone species like the Khaya
ivorensis, Milicia excelsa, Elephas maximus (giant elephants) and Python sabae
(pythons), which lived in the area, especially the sacred forests are no longer in existence.
This view is supported by the study done by Buchmann and Nabhan (1996), in which
they noted that agriculture fragments the landscape, breaking formerly contiguous wild
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species populations into small units that are more vulnerable to extirpation. The more the
population grows, the more virgin lands are being cleared with the notion that the
biodiversity resources are limitless and inexhaustible. Thus, Phil-Eze (2001), rightly
observed that we know very little about the richness of our biodiversity and most
importantly, the biodiversity in Nigeria is being depleted at rates greater than their rate of
turnover which spells doom to the ignorant populace.
It is quite certain or possible that the different agricultural land use practices
within the study area impact differently on biodiversity species. However, the extent of
the impact is not known, especially by the indigeninous or local farmers. Enormous
pressure is currently placed on the earth’s biodiversity by uncontrolled and poorly
managed human activities including agricultural land use practices. Many of these
organisms disappear before we have the opportunity to study, understand, or document
them, especially their medicinal and other values (SPDC, 2007).
Research in Nigeria on agricultural land use and biodiversity risk has been scanty,
and has seemingly not emphasized the issue of agricultural land use practices that support
biodiversity. This agrees with the claim by Lichtenberg (2002), that quantitative studies
that estimate the impact of agriculture on environmental quality are surprisingly scanty.
Some of the works done so far in this regard include those done by Donald et al, (2001),
Donald, (2004), Adinna (2001) and Anikwe (2010). The various agricultural land use
practices that operate in the local government area, individually and collectively have
ways of affecting the environment. These effects may be imperceptible initially, but as
time progresses, they may become apparent. Agricultural land use practices cause habitat
changes that transform a balanced diversified natural ecosystem to a simplified man-
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made ecosystem. This in turn affects species richness in Isiala Ngwa North L.G.A. in
ways yet to be determined. The paucity of research in this line shows either neglect or
lack of interest on the part of researchers in an all important aspect of the environment. It
is this neglected aspect of the environment that necessitated this research, as the total
livelihood and wellbeing of man revolve around biodiversity. It is against this
background therefore, that the researcher decided to carry out the research. This study is
considered important because it is necessary to know to what extent the various
agricultural land use practices that operate in the area have affected biodiversity in terms
of species richness and species diversity.
The Nigeria Biodiversity Strategy and Action Plan (NBSAP, 2008) is a policy by
the Nigerian government which encourages agriculture in one hand and protection of
biodiversity on the other hand. Whereas agriculture has negative impact on biodiversity,
how both agricultural production and biodiversity conservation can thrive has not been
studied in Isiala Ngwa North, the study area. This is the gap that this study attempts to
fill.
1.3
Aim and Objectives of the Research
This research project is aimed at examining the impact of agricultural land use
practices on biodiversity in Isiala Ngwa North L.G.A of Abia state. To achieve this aim,
the following objectives will be pursued:
1. To make an inventory of the nature of biodiversity in the study area in terms of
species richness and species diversity;
2. To identify the types and spatial distribution of agricultural land use practices in the
area;
7
3. To examine the effects of agricultural land use practices on biodiversity in the area
4. To suggest measures that will encourage sustainable agricultural land use and
conservation of biodiversity in the area.
1.4
The Study Area
Isiala Ngwa North L.G.A is located between latitudes 05021′N and 0529′N and
longitudes 07018′E and 07022′E. It is bounded to the north, south and east by Umuahia
south, Isiala Ngwa South and Ikwuano Local Government Areas respectively. It is also
bounded to the west by the Imo River in Imo state. Isiala Ngwa North L.G.A. has a total
of forty (40) communities. The study area has a land area of about 83.5 square kilometers
and population of about 154, 083 people by the 2006 population census [FGN, 2007].
The position of the study area in relation to Abia state is shown in Fig1, while the actual
map containing the forty (40) communities is shown in Fig 2.
8
Fig. 1: Abia State showing the study Area
Source: Department of Geography, UNN (2012)
9
Fig 2: Isiala Ngwa North LGA showing the communities
Source: Department of Geography, UNN (2012)
9
10
1.4.1 Relief:
The relief of Isiala Ngwa falls under plains and lowlands. The trend of the
topography of the study area is that of a gradual ascent which extends from Osisioma
Ngwa (Aba) LGA, through Isiala Ngwa south (Mbutu) L.G.A. up to the study area.
Hence the gradual ascent stems from plains from 50-100 metres above sea levels (Aba) to
plains from 100-200 metres above sea levels (Ntigha) near Umuahia (Ofomata 2002). In
other words, Isiala Ngwa is dominated by plains under 200 metres above sea levels.
1.4.2
Drainage
Isiala Ngwa is dominated by the Imo River drainage system (Wigwe, 1975). The
Imo drainage system has a total drainage area of about 8,288 km2 with the Imo as the
most important river. The Imo River is one of the largest independent streams,-that is
those which reach the sea, without joining one of the large rivers. The Imo River changes
its direction and consequently receives some major tributaries: the Otamiri and the Aba
rivers (Ofomata, 2002). However, there are smaller water bodies in the study area. They
include the Etu-Amapu stream in Amapu Umuoha, Nwaohia, Okpomiri, Mmiri Nkuma,
Nwaolighili and Agbamboro streams in Uratta. It is note worthy to mention that the Imo
river and its tributaries flow in the South-Western direction, while the Umuala river and
its tributaries flow in the South-Eastern direction. The Imo River has a total length of
about 220km and enters the sea at Opobo (Wigwe, 1975).
1.4.3
Climate
The climate of the study area falls under the Af climate of Koppen’s
classification, with two distinct seasons namely the rainy and dry seasons. The months of
April to October witness heavy rainfall while from November to March is the period for
11
dry season in some parts of the study area. Isiala Ngwa North experiences a total annual
rainfall of 2250-2500mm, with a relative humidity that ranges from 75-100% and
temperature range of 250C to 320C (Anyadike, 2002).
The Tropical maritime air mass (mT) brings wet conditions during the period of
high sun, being drawn in from across the Atlantic. It contains plenty of moisture and its
relative humidity always approaches 100 percent. The Tropical continental air mass (cT),
on the other hand brings dry condition from November to March (that is during the period
of low sun). These air masses are manifested as the South-west trade wind (or Monsoon)
and North-East Trade wind (or Harmattan) respectively. The two air-streams meet at the
Inter-Tropical Discontinuity (ITD) where the mT air is overrun by the cT air. (Anyadike,
2002). These seasonal oscillations and alternations of the two air masses caused by the
pole ward and equator ward migrations of the trough determine the incidence of wet and
dry seasons. So, the effects of the inter-tropical discontinuity control rainfall over the
study area, just as it does over the rest of the south eastern Nigeria (Ali, 1975). There is
normally a long rainy season from April to October, with a break in-between the rainfall
regime. This break is mostly in July or August and it is known as the August Break or the
little dry season (llesanmi, 1972). The dry season proper lasts between November and
March (Ali, 1975).
1.4.4
Soil
The soil of Isiala Ngwa is classified under the ferrallitic soils. The soils however
are derived from sand, where they are further subdivided according to dominant soil
colour, and from various complexes of sandstones and shales where they occupy the well
drained sites. The soil of Isiala Ngwa therefore is sandy-loam with the dominant colour
12
being yellowish-brown and on which agriculture is based usually upon production of
subsistence crops (Ofomata, 2010).
1.4.5
Vegetation
The study area is located in the rain forest belt. The soil characteristics and
climatic condition indicate that the natural climax vegetation around the area has been
tropical rain forest. Due to human activities, the original vegetation has been largely
degraded. The degradation is attributable to such human activities as grazing, cultivation,
bush burning and logging over a long period of time. As population increased, virgin
lands were cleared, thereby loosing the original vegetation. However, the vegetation
type in the area today is mainly lowland rain forest (Igbozurike, 1975). The study area
may be termed an oil palm bush from the ubiquitousness of oil palms (Elaeis guineensis)
and raphia palms (Raphia vinifera) (Udo, 1978). The vegetation in the area is
characterized by an abundance of plant species, which sometimes exceed 150 different
species per hectare (Igbozuruike, 1975), and it is this great diversity which makes the
rainforest the richest of all terrestrial ecosystems in terms of biomass productivity. A
storeyed sequence of the canopies may be observed in some parts of the area. The
number of easily discernible strata is neither regionally constant nor temporally regular,
and anywhere from three to six canopy layers may be delimited. Some of the plant
species in the area include Khaya ivorensis, (mahogany), Milicia excelsa (Iroko)
Pentaclethra macrophyla (oil bean) and Cnestis feruginea (Anyadike, 2002).
However, it is pertinent to mention that some parts of the study area are
dominated by Chromolaena odorata (Siam weed) interspersed with some grass species
such as Pennisetum purpureum, Andropogon spp, Geophillia and Costus spp (Igbozurike,
13
1975; Anyadike, 2002). Plate 1 shows the picture of a cross section of the vegetation of
the study area
A: Amaorji
B: Amaapu Umuoha
Plate 1: A section of the vegetation of the study area from Amaorji and Amapu Umuoha communities
1.4.6 Wildlife
In Isiala Ngwa North Local Government Area, there is a history of a diversity of
wildlife. In the olden days, there were tick forests in the area. Forests are closely
associated with wildlife. For instance, in the early twentieth century, there were a variety
of wild animals in some parts of the study area like Ntigha, where we had animals like
Python sabae (Pythons), Tragelaphus scriptus, Neotragus pygmaeus (antelopes), Hyena
stirata (hyena), birds of different species like Ploceus cucullatus (weaver birds), Milvus
migrans (Kites), and others. These animals were found in large numbers. (Arungwa,
2011).
Furthermore, in other parts of the study area, like Okporo in Amorji, there used to
be all sorts of snakes (eg the green snakes) Natrix sp, Echis carinatus, Botheopthalmus
14
lineatus. With the increase in demand for land due to population growth, coupled with
uncontrolled hunting activities, some of these animals either disappeared or decreased in
their numbers.
Nowadays, the predominant wildlife in the area comprises of Thryonomis
swinderianus (grass cutters), Philantomba maxwelli (Maxwell’s duiker), Hyena stirata
(Hyena), Protoxerus strangeri (squirrels), Cricetomys gambianus (African giant rats) and
Guttera edouardi (guinea fowl). Others include Atherurus africana (porcupines), snails
of different species like Achachatina magmata (African land snail) and Achatina
achatina, earthworms of different species like Nsukkadrilus mbae and Lumbricus
terrestris. Also, there are birds of different kinds like the Ptilopsis leucotis (owl), Milvus
migrans (Kites) and Ploceus cucullatus (weaver birds). In places like Umuosu Nsulu,
there are few Python sabeae that are rarely seen and other kinds of snakes that are also
seen once in a while. For instance, in the Mkpokoro stream in Umuosu Nsulu, Python
sabae and Natrix spp are seen occasionally. Other animals in this community also include
the Guttera edouardi, (Guinea fowl), pachybolus ligulatus (Millipedes), Lumbricus
terrestris, Achatina achatina and others. It is also pertinent to mention that in the wetter
parts of the study area, there are frogs of different species as well as Bufo regularis
(Toad) and Agama agama (Rainbow lizard). (Fieldwork 2011).
1.4.7 Economic Activities
The study area has agriculture as one of the dominant economic activities. It is
dominated by food-cropping (Uzozie, 1975, Hayward and Oguntoyinbo, 1987). Examples
of the food-crops are Manihot utilissima (cassava), Dioscorea spp (yam eg white yam-
Dioscorea rotundata, yellow yam-Dioscorea cayensis, water yam-dioscorea alata etc,
15
Zea Mays (maize), and Colocasia esculenta (cocoyam). There are also tree crops like
Elaeis guineensis (oil palm), Theobroma cacao (cocoa). The wetter parts of the area
which are fresh water swamp forest have a lot of economic trees such as Symphonia
globulifera (which is a tall straight tree), Gmelina aboreal (gmelina), Milicia excelsa
(Iroko), Khaya ivorensis (mahogany), Pentaclethra macrophyla (oil bean) and various
others where lumbering takes place.
It is pertinent to mention that some rural households keep a few livestock like
sheep, cattle, goats, as well as pigs. Poultry farming is also practiced there.
The system of cultivation in Isiala Ngwa North falls under subsistence and small scale
commercial farming. Subsistence agriculture is concerned mainly with the provision of
the basic needs of the farming family, while small scale commercial farming is designed
to make money from the crop production. The farm sizes are generally small, about 3-5
hectares. Plantation commercial farming is also practiced in the area though in a small
scale. For instance, there are some households that have large areas of land devoted to oil
palm and plantain plantations although with a mixture of some food crops like Manihot
utilissima and Dioscorea species.
1.5 Literature Review
Great deal of studies have been carried out both in the developed and developing
countries on the impact of agricultural land use practices on biodiversity. Evidence
abound about how farming practices influence species richness and abundance of taxa
(Vickery et al. 2001; Firbank et al. 2003; Fuller 2005), about the threats posed by
agricultural change to biodiversity (Tucker and Evans 1997; Krebs et al. 1999; Petit et al,
2001; Tilman 2001), and how farming practices can be modified to mitigate these threats
16
and generate benefits (McNeely and Scherr 2003). The biophysical processes relating
agriculture and biodiversity are so numerous and interacting that it is difficult to ascribe a
particular biodiversity response to an individual agricultural cause. Rather, most
biodiversity changes are responses to a suite of agricultural changes that can be regarded
together as agricultural intensification (Chamberlain et al. 2000) on the one hand, or
habitat restoration or abandonment on the other.
The need to reconcile agricultural production and production-dependent rural
livelihoods with healthy ecosystems has prompted widespread innovation to coordinate
landscape and policy action (Brechwoldt, 1983, Acharya, 2006). Hence, the link between
farming practices and biodiversity has been established since the early nineties in works
by Baldock et al, (1993) and Beaufoy et al, (1994). In their work, they observed that
there is hardly any farming practice without its attendant impact on biodiversity. In the
same way, mapping efforts to identify High Nature Value (HNV) farmland have been
carried out more recently (EEA, 2004, Pointereau et al, 2007, Paracchini et al, 2008,
EENRD/EC-2009).
The Millennium Ecosystem Assessment documented the dominant impact of
agriculture on terrestrial land and freshwater use, and the critical importance of
agricultural landscapes in providing products for human sustenance, supporting wild
species, biodiversity and maintaining ecosystem services (MEA, 2005).
According to Cincotta and Engelman (2000), more than 1.1 billion people, most
agriculture-dependent, now live within the world’s 25 biodiversity ‘hotspots’; areas
described by ecologists as the most threatened species-rich regions on earth. Angelsen
and Kaimowitz (2001), in their studies observed that both extensive lower- yield and
17
intensive higher-yield agricultural systems, have profound ecological effects. According
to them, millions of hectares of forests and natural vegetation have been cleared for
agricultural use and for harvesting timber and wood fuels. They concluded that empirical
evidence suggests that intensification rarely results in saving land for nature. Supporting
this view, Jenkins (2003) and Thomas et al (2004) indicated that one of the major
pressures on biodiversity on a global scale, remains the transformations of natural
habitats to agriculture, especially through forest clearance, both alone and interactively
with climate change. Some transformation between agricultural land and habitats for
biodiversity are conceptual, rather than reflect changes in land management. Hence, this
historic farming practice is conserved for their aesthetic, cultural and ecological interest,
although the crops are possibly harvested for human consumption, thus transforming
natural ecosystems into agricultural ones. (MEA, 2005 b).
The ‘human footprint’ analysis of Sanderson et al (2002) estimated that 80-90%
of lands habitable by humans are affected by some form of productive activity. Ngailo et
al (2001) in their study observed that each time, the growth per unit area in number of
animal and human population in the district of Arumeru in Tanzania, has contributed to
decreased size of the average farm size for both cropping and grazing. According to
them, there has been a change in biodiversity as some of the cropping systems have
become extinct whereas others have emerged, adding that the negative aspect of the
changes has been the reduction of species diversity due to degradation and over
exploitation.
According to Donald, et al., (2001) and Donald (2004), a number of studies
document the measurable adverse impact of agricultural intensification on farmland bird
18
populations in Europe and elsewhere. They concluded that as a result of agricultural
intensification on farmlands, some bird populations are forced to either die off or migrate
to other environments that are uncondusive, thereby reducing their populations or even
driving them to extinction.
In addition, Buchmann and Nabhan (1996) discovered in their study that
agriculture fragments the landscape, breaking formerly contiguous wild species
populations into small units that are more vulnerable to extirpation. Farmers generally
have sought to eliminate wild species from their lands in order to reduce the negative
effects of pests, predators and weeds. They added that these practices however often harm
beneficial wild species that prey on agricultural pests. Hence, they concluded that these
threats posed by agriculture to conservation have been a key motivator for
conservationists to develop protected areas where agricultural activity is officially
excluded or seriously circumscribed.
Tilman et al (2002), indicated that agriculture remains a predominant activity
through which humans interact with the natural world. Hence, Millennium Ecosystem
Assessment report, added that total cultivated systems covered 25% of earth’s terrestrial
surface in 2000, with their attendant impact on biodiversity (MEA, 2005). According to
Heal and Small (2002), agriculture is an activity that extracts renewable resources from a
biological base. Thus, Pagiola et al (1998), opined that sustainable agriculture must be
embedded in sustainable ecosystems and the protection of our stock of biodiversity. In
addition, some researches have been done about the use of inorganic fertilizer and
biodiversity by Pagiola et al (1998), In their study, they observed that inorganic fertilizer
use in agriculture changes the energy and nutrient cycling and storage that lead to the
disruption of normal ecosystem functioning. Lichtenberg (2002) noted that investigating
19
the impact of inorganic fertilizer use is important due to recent massive increases in
nutrient pollution that have occurred over the last several decades. The scale of nitrogen
and phosphorus deposition in the world’s agricultural soil from inorganic fertilizer use is
quite different and may have very different impact on biodiversity.
Accordingly, Carpenter et al (1998), observed that in the United States and
Europe, only 30% of the phosphorus input in fertilizer is available in farm produce,
leaving an average accumulation of 22kg/ha/year while only 18 percent of the nitrogen
input in fertilizer goes back to farm produce and accumulating a surplus of 147kg/ha/year
in the soil. Similarly, Ingham (1998), observed that while adding inorganic fertilizer in
the soil may improve plant growth in the short term, it may lead to environmental
degradation over longer time frames. Thus, soils play a crucial role in maintaining the
terrestrial food chain and represent a very important component of any nation’s natural
capital and take hundreds of years to be built (Daily et al, 1997). With the use of
inorganic fertilizer, biodiversity loss occurs because some economic agent perceives that
the additional return from the use, or increased intensity of inorganic fertilizer exceed the
returns from conserving the natural productivity of soil. This gap creates the difference
between private and social return from conserving biodiversity. Institutional
arrangements that facilitate significant subsidy for inorganic fertilizer worsen this gap
(MEA, 2005).
Furthermore, Paul et al (1997), observed in their study that a well documented
impact of agricultural intensification is the loss of soil organic matter that provides soil
structure and its nutrient and water holding capacity. However, conversion of land to
cultivation under conventional tillage system may result in a decline in organic matter.
Farming system that utilizes mechanical tillage can promote soil carbon loss by many
20
processes, such as disintegration of soil aggregates which usually protect soil organic
matter from decomposition; they may increase microbial activity aeration thereby
increasing the level of CO2 in the atmosphere. This agrees with the findings of Karlen
and Cambardella (1996), Six et al (1999), Kladivko (2000) and Bayer et al (2006 and
2009).
In their study on the impact of agricultural practices on biodiversity, McLaughlin
and Mineaub (1995), reported that farming practices must prevent to a larger degree
impacts which cause a simplification of floristic diversity, fragmentation of habitats,
decrease in soil quality, etc. They concluded that high fertilization doses, short crop
rotations or monoculture combined with chemical plant protection measures cause
depletion of species richness and species diversity. Also, McLaughlin (2000) and
Mineaub (2000) in their study indicates that agricultural activities such as tillage,
drainage, inter-cropping, rotation, grazing and extensive usage of pesticides and
fertilizers have significant implication for wild species of flora and fauna. According to
them, species capable of adapting to the agricultural landscape may be limited directly by
the disturbance regimes of grazing, planting and harvesting, and indirectly by the
abundance of plant and insect foods available. They also stress that some management
techniques, such as drainage, create such fundamental habitat changes that there are
significant shifts in species composition. They however, concluded that chemical
fertilizer loadings must be better budgeted not to exceed local needs, and those pesticides
inputs should be reduced to a minimum; and that the types and regimes of disturbance
due to mechanical operations associated with agricultural activity may also be modified
to help reduce negative impact on particular groups of species, such as birds.
21
According to Lal (2000), tillage could stimulate the process of soil erosion,
resulting in further loss of soil carbon. Similarly, Bossio et al (2004), in their study
observe that meeting food needs and economic demand by widespread resource
degradation is already either reducing supply or increasing costs of production. They
however, concluded that up to 50% of the globe’s agricultural land and 60% of ecosystem
services are now affected by some degree of degradation, with agricultural land use: the
chief cause of land degradation.
Furthermore, Bassett and Boutrais (1996), noted that nomadic herding necessarily
impact negatively on the biota by extensive grazing and the use of fire to suppress
undesirable plant species, while it degrades soils by regular trampling by animals on the
move. In a similar study on carbon storage in soils of southeastern Nigeria, Anikwe
(2010) came up with the result that the highest carbon stocks of 7906-97,510gcm-2, were
found at the sites representing natural forest, artificial forest and artificial grassland
ecosystems. Continuously cropped and conventionally tilled soils according to him, had
about 75% lower carbon stock (1979-2822gcm-2). Thus, the soil carbon stock in a 45-year
old Gmelina forest was 8987gcm-2, whereas the parts of this forest, that were cleared and
continuously cultivated for 15years, had 75% lower carbon stock (1978gcm-2). The
carbon stock of continuously cropped and conventionally tilled soils was also 25% lower
carbon than the carbon stock of the soil cultivated by use of conservation tillage.
Soil carbon enhances the growth of plants which in turn provides food and shelter
for animal species. Hence, soils in agro-ecosystems lose 25 to 75 percent of their organic
carbon during the initial conversion of these ecosystems from natural to agricultural due
to such soil degradation processes as erosion, salinization and nutrient depletion. This is
22
equivalent to a global loss of carbon (286000 ± 44000 MtCo2e per year) through historic
land use and soil degradation (Lal, 2011). It is pertinent to mention that it is estimated
that increasing the soil carbon pool by 1 tonne of carbon hectare per year (3.7 t
CO2e/Ha/yr) in developing countries can enhance agronomic production by 32 ± 11
million metric tones per year (Mt/yr) of cereals and pulses and 9 ± 2 Mt/yr of roots and
tubers (Lal, 2011).
According to Pimm et al. (1995) and MEA (2005), there are persistent concerns
and accumulating evidence of rapid losses in biodiversity as a result of certain
agricultural land use practices. According to these researchers, biodiversity is critical to
the provision of ecosystem services and human wellbeing crucially depends on ecosystem
services (MEA, 2005). The ecosystem services include production of food, fibre,
medicine, water, air, formation and retention of soil fertility, hosting of the genetic
library, pest and disease control, crop pollination, climate regulation, flood control, water
filtration and cleaning, maintaining and balancing biogeochemical cycles, recreational,
cultural and aesthetic benefits etc. (Heal and Small 2002, Armsworth et al. 2004, Heal
2004).
In addition, Okafor (1991) reported that the growing agricultural land use
intensification especially in the densely settled southeastern Nigeria, has a negative
impact on biodiversity in the long run. He therefore noted however, that while
intensification appears to simulate crop-biodiversity, it evidently evokes an opposite
effect on composition of ‘native’ forest species.
In his study, Adinna (2001) revealed that over-cultivation, which is the continuous
use of the same land for food or cash crop production due to land scarcity, impacts
23
negatively on biodiversity. He noted that in Amazon, the perception of limitless
resources, prompted the farmers to ‘mine’ their soils and push into virgin forests. He also
notes that land scarcity due to population increase, land fragmentation, ignorance of
conservation measures, and lack of alternative land for particular crops are among the
factors of over cultivation. Back here in Africa, Adinna (2001) also observed that
common practice in the African rotational bush fallow system of subsistence economy is
slash and burn and burning before clearing approach without providing adequate
fireguards. He therefore observed that such leads to unwanted bush burning, forest
destruction and loss of biodiversity. He concluded that although this burning method
makes land clearing easy, reduces bacteria in the soil, introduces ash to the soil and
makes for positive farm waste management, yet the disadvantages of net destruction, loss
of biodiversity and retardation of the rate of forest recovery outweigh the benefits
Emphasizing the negative impact of some agricultural land use practices on
biodiversity, Adinna (2001), also opined that bush burning for grazing and cultivation,
overgrazing, clearing for farm settlements, plantation agriculture and agro forestry play
major role in biodiversity loss. He therefore, pointed out that they introduce novel plants
into, and force same on the natural environment thereby disrupting the natural ecosystem.
Rich Islands of forests around villages characterize the forest-savanna mosaic zone of
West Africa. A common view is that they are relics of a once thick forest in a process of
transformation to a forest-savanna mosaic and other formations increasingly deprived of
forest species by grazing, arable farming and other forms of human pressure. A counter
view holds that the forest islands actually represent an enrichment of a basically savanna
vegetation by special management practices including nurturing of trees, as part and
24
parcel of agriculture and also in the past, as a military defense strategy (Fairhead &
Leach, 1996).
Gyasi (1996b), stated that the introduction of the exotic plantation system in the
18th century, has transformed vast areas of diversified humid forest ecosystems, most
especially in Cote d’Ivoire, Liberia, Nigeria and Ghana, into mono-cultural ones focused
on the oil palm (Elaeis guineensis), rubber (Havea brasiliensis), and cocoa (Theobroma
cocao). On the effects of oil palm plantations in Ghana, Gyasi (1996b) observed that the
resilient, diversified indigenous agriculture, modeled on the forest ecosystem and based
on eco-farming principles borne out of the peasants’ intimate knowledge of the natural
environment, is being replaced by the risk-prone mono-cultural system, with devastating
consequences for the forest ecosystem (Gyasi, 1996b: 352). A similar effect is reported of
the Rison palm nucleus estate in Nigeria (Gyasi, 1987). To this, Okafor (1991) added that
this process of agro-ecological erosion is fuelled by external demand, profit maximization
and pressures of production exerted by the expanding population.
Concerning modern horticulture or market gardening that evidently enhances
agricultural biodiversity, examples are the studies done by Gyasi (1997), Dzokoto, (2000)
etc on the Shallot-centered farming developed in an area marked by insufficient rainfall
and humus deficient sandy soils in Anloga in Ghana’s southeastern coastal savanna
plains. It is an indigenous system that integrates modern techniques and methods. It’s
development started in the 1930s through reclamation of marshy depressions within an
area then dominated by grass and coconuts. It is characterized by labour intensive
multiple cropping, focused primarily on Shallot (Allium ascalonium), inter cropping of
the shallots by various crops, including leguminous and nitrogen-fixing ones on small
25
sandy beds, often with maize (Zea mays) in the alleys’ strict adherence to uniform
planting periods among the farmers as a pest and disease minimization strategy. It also
involved mulching and hoeing-under of weeds and crop residues, manual and small
mechanical pump irrigation and soil fertility creation and regeneration by externally
sourced inorganic artificial chemical fertilizers, green manure, fish residue and most
especially by externally sourced material, whose use is encouraged by official policy, and
which benefits soil structure and soil moisture holding capacity, reduces the need for
chemical fertilizers and helps to increase the efficiency with which these are used by the
plants (Ghana, Republic of 1990, Gyasi, 1997, Dzokoto, 2000).
Concerning the potential positive impact of some agricultural land use practices
on biodiversity, Hole et al (2005), concluded that organic farming increases biodiversity
at every level of food chain. They also indicate in their study that degraded soil could also
be restored through improved agricultural practices, adding that such evidence supports
the promotion of alternative agricultural practices to achieve sustainable food supplies. In
support of this view, Pimentel (1997), pointed out that these basic environmental
resources (e.g. biological resources, land, water and energy) that sustain agriculture must
be conserved to meet the critical need of augmented food production for the world
population.
Similarly, Mader et al (2002), posited that long-term agro-ecosystem experiments
show that organic manures and fertilizers offer increased diversity among soil microbial
communities that transform carbon more efficiently from organic debris and build up a
higher microbial biomass. To this, Matson et al (1997), added that sustainable
agricultural land use management strategies that advocate replacing the use of inorganic
26
fertilizer by organic manure not only increase soil organic matter, but also provide an
increasingly important service of sinking carbon dioxide into the soil.
Generally, it has been established from the foregoing, as argued by a variety of
sources, that failure to take action to protect biodiversity undermines human wellbeing
and poses serious threats to sustainable development (Daily, 1997, Faith, 2005).
This therefore necessitated the research as it is important to examine the impact of
agricultural land use practices on biodiversity in Isiala Ngwa North L.G.A of Abia state,
so as to maximize agricultural production and also protect biodiversity in order to achieve
a sustainable development in the area.
Having gone through what has been done on the research topic at global ( Donald
et al.,2001 and Donald, 2004), continental (Adinna,2001), regional (Fairhead & Leach,
1996) and national scale (Anikwe, 2010, Okafor, 1991, & Gyasi, 1987) the researcher
still deems it necessary to replicate the work at a local level so as to know if the result
will be the same with the previous works done or if there are generalizations above that
do not actually apply in a local setting like the study area. In other words, global,
continental, regional and national scale studies are more of generalization. Hence, a study
at local level will be more detailed.
1.6
Conceptual Framework
In emaining the impact fo agricultural land use practices on biodiversity in the
study area, two conceptual framework were used. These are the Millennium ecosystem
assessment (MEA) and the Japan ecosystem assessment (JSSA).
27
1.6.1
Millennium Ecosystem Assessment
The conceptual framework of the Millenium Ecosystem Assessemnt (fig 3) was
launched in 2001 and the primary assessment reports was relaeased in 2005. The
Millenium Assessment focuses on how humans have altered ecosystems and how
changes in ecosystem services have affected human well-being. It also involves how
ecosystem changes may affect people in future decades and what types of responses can
be adopted at local, national or global scales to imrpvoe ecosystem management and
thereby contribute to human well-being and povertyalleviation.
Fig. 3: Millennium Ecosystem Assessment
Soruce: Millennium Ecosystem Assessemnt (MEA 2005).
28
In relation to the study area, the dominat agricultural land use practices have
altered the ecosystems especially the terrestrial ecosystem. This alteraction has also
effected change in the ecosystem services. This change in the ecosystem services has in
turn affected human well-being. As such, certain species of plants and animals have gone
into extinction rendering their services inaccessible.
1.6.2
The Japan Ecosystem Assessment
The Japan Satoyama – Satoumi Assessment (JSSA), conceptural framework was
developed in 2011 (Fig 4). It was developed to obtain a better understanding of the key
indirect and direct drivers of biodiversity and ecosystem servies change across urbanrural landscapes called Satoyama in Japan. JSSA used the Millennium Ecosystem
Assessment conceptual framework as a basis. As the focus of the assessment was on
understanding landscape ecology nd the mosaic of ecosystem types required to produce a
set of ecosystem services. For human wellbing, the landscope module was introduced
into the Millenium Ecosystem Assessment Framework (Duranappah et al 2012).
Indirect drivers
Land-use change
Climate change
Invasive species
Over-exploitation
Pollution
Under-use
Demographic change
Economic change
Cultural change
Science and technology
Sociopolitical change
Provisioning
services
Regulating
services
Cultural
services
Security
Basic
materials
Health
Social
relations
Freedom of
choice & action
Supporting
services
Satoyama
& Satoumi
Direct drivers
Fig. 4: The Japan Ecosystem assessment (JSSA)
Soruce: Duraiappah et al 2012.
29
Related to the study area, which is a rural setting, the farming activities of the
populace have affected the ecosystem services derivable therefrom. This is as a result of
the dirvers of biodiversity and ecosystem services change both directly and indirectly as
shown in Fig 4. Some of these drivers are land use change, climate change, overexploitation, pollution, cultural change, economic change, demographic change among
others. These changes due to anthropogenic activities like farming methods have affected
the services provided by the ecosystems. Hence most of the species in the area have
either reduced in numbers or gone into extinction, to the detriment of human wellbeing.
1.7
1.7.1
Methodology
Types and Sources of Data
The types of data used in the study include primary and secondary data. Primary
data were sourced from field observation, key informant interviews, focus group
discussion and questionnaire survey. The data on diversity inventory of plant and animal
species were collected via quadrat analysis. Identification of species, and their scientific
names were done with the help of experts (research assistants) and the internet. That of
the diversity indices were generated from the diversity inventory via Shannon Wiener’s
Diversity Index. Secondary data were collected from the internet, books, magazines and
Isiala Ngwa North L.G.A. secretariat. Data on the physical and chemical properties of the
soil were collected from the soil samples that were collected from the study area.
1.7.2
Sample Selection
The study area is made up of forty communities (Fig. 2). A 20m x 20m frame
quadrat was laid on selected sites of each of the five predominant agricultural land use
types in each community. Also 400 elderly farmers (respondents) were selected to whom
30
copies of questionnaire were administered. The method of selection was purposive
sampling in which 10 farmers were selected from each community. The reason for choice
of 10 farmers per community was convenience. The justification for the selection was
knowledgeability on the subject matter.The criteria for selection were willingness and
availability during field work. These farmers were visited.
1.7.3
Sampling Technique and Data Collection
The period of the field work for this research was from January 2011 to October
2011. Purposive sampling technique was used in data collection to sample some quadrats
from the forty communities of the study area. This was done on the selected sites of the
prevalent agricultural land use types. In that way a representation of the study area was
achieved. Also, data were collected through questionnaire survey. A 20 x 20m frame
quadrat was used to sample biodiversity in the land use types in each of the 40
communities according to Sutherland (1996). In each quadrat sampled, enumeration and
recording of biodiversity in the area in terms of species richness and species diversity
were undertaken. For the plants, direct count was adopted to estimate number while
diversity index was used to determine the species abundance. The enumeration and
recording of species enabled the determination of the species diversity by noting the
number of different species in each quadrat for later analysis
The study for wildlife was restricted to mammals, birds, reptiles and amphibians.
This was because these are the major indicators of biodiversity in an area. For mammals,
use of direct count was also adopted. In addition, the number of animals caught by
hunters was also used as an index of animal population (Sutherland, 1996). This was
done by Focus Group Discussions with experienced hunters. In estimating the population
31
of birds, a number of techniques were combined. They included point counts, counting
of flocks, and counting of occupied nests on tree colonies. In addition, with the aid of
some hunters in the area, the remains of animals like their skulls, bones, evidence of
moulted skin, moulted feathers, droppings, etc. were examined to determine the presence
of certain animal species in the quadrats.
Also the relationship between agricultural land use practices and biodiversity was
examined in detail. This was done through Focus Group discussions, and key informant
interviews. For the farmers there was a two single-gender FGD sessions, comprising of
six (6) elderly male farmers and six (6) elderly female farmers. This was done to elicit
information on the impact of agricultural land use practices on biodiversity in the study
area. The method of selection was purposive sampling and selection criteria are
availability at the time of the fieldwork, knowledge of the subject as shown by many
years of farming experience and willingness to participate in the FGD. A single gender
FGD session involving a group of twelve (12) hunters was done. The procedure was the
same as that of the farmers.
Also, two key informants were interviewed. One of them was a retired senior
Agricultural Science teacher and now a farmer. The other one was an experienced farmer
and the Chairman of Isiala Ngwa North and South Hunters’ Association. The criteria for
selection were the same as those of the FGDs. The field work also enabled the direct
observation of the problems confronting biodiversity in the face of increasing demand for
food and other land conversions activities.
32
1.7.4 Soil Sampling
Eighteen (18) soil samples were also collected from the study area for laboratory
analysis. The samples were coellcted using auger at depths of 10 – 20cm. The samples
were collected from three different locations of each agricultural land use type. Three
other samples were also collected from three different uncultivated locations to serve as
control. The method used in the collection was purposive sampling. Hence the samples
were only taken from selected sites of the dominant agricultural land use types. The
parameters of the soil tested were practicle size distribution and texture, pH, Nitrogen,
organic carbon, (organic matter), exchangeable bases (calcium, magnesium, sodium),
phosphorus and exchangeable aluminum contents of the soil.
1.7.5
Laboraroty Analysis of Soil Samples
The soil slamples collected were analyzed in the laboratory. The analysis was
done in the soil sciene Department of National Root Crop Research Institute Umudike,
Umuahia (Appendix 3).
1.7.6 Techniques of Data Analysis
The data collected were subjected to descriptive statistics such as tables to analyze
the inventory of biodiversity indices. Principal Component Analysis was also used to
analyze the impact of agricultural land use types on biodiversity. Shannon Wiener’s
Diversity index after Ian and Peter (2003) was used to obtain the diversity Indices of the
species. The choice of Shannon-Wiener’s diversity index was informed by the fact that it
is considered appropriate and widely used in the interpretation of species diversity. The
value of Shannon diversity is usually found to fall between 1.5 and 3.5 and only rarely it
surpasses 4.5 (Khan, 2013). The value of the DI is a reflection of the impact of
33
Agricultural Land use practice on biodiversity. The Shannon-Wiener’s Diversity index is
given as:
Hi
=
N ln N − ∑ (ni ln ni )
N
−−−−−−−−−−−−−−−−−−−−−−
(1)
Where N is the total number of individuals of all species, ni is the number of individuals
of species i, and ln is natural logarithm. See Appendix 7 for illustration.
The calculation of biodiversity indices for the species in the area was done using the
formular after Hill (1973). Biodiversity index is given as:
Biodiversity Index =
the number of species in the area
the number of individual s in the area
− − − ( 2)
The results of the soil analysis, were further subjected to ANOVA to know if the land use
types have any impact on biodiversity from the purview of the soil.
1.8
Plan of the Project
The project has six chapters. Chapter one is the introductory chapter and includes
the background to the study, research problem, aim and objectives of the study, the study
area, literature review, research methodology and the plan of the project.
Chapter two dwells on the nature of biodiversity in the study area in terms of
species richness and species diversity. Chapter three deals with the identification of
types and the analysis of the spatial distribution of agricultural land use practices in the
area.
Chapter four focuses on determining how agricultural land use practices impact
biodiversity in the area. While Chapter five deals with measures that will encourage
sustainable agricultural land use and conservation of biodiversity in the area, Chapter
six is devoted to the summary, recommendations and conclusion of the study.
34
CHAPTER TWO
THE NATURE OF BIODIVERSITY IN THE STUDY AREA
As reported in Table 1 and Appendix 2, biodiversity in the study area vary greatly
in terms of plant and animal species. The plants species, are of different types, ranging
from herbs (H), grasses (G), shrubs (S), Climbers(C) to trees (T) and others. There are
herbs like Ageratum conyzoides, Aspilia africana, Chromolaena odorata, etc. We have
species of grass like the Peperomia pellucida, (shinny bush), Eleusine indica (Indian
goose grass). Also found werew shrubs like Alchornea cordifolia, Afromomam
melegueta, Anacardium occidentale, Cnestis feruginea, etc. The climbers include some
legumes like Calopogonium mucunoides, Mucuna pruriens, Andropogon tectorium,
Commelina erecta, among others. Some of the tree species include Pentaclethra
macrophylla (Oil bean), Khaya ivorensis (Mahogany), Alstonia boonei (Alstonia
cheesewood) etc. Some of the species are evergreen (retain green leaves all year round)
while others are deciduous (shed their leaves in the dry season). Example of deciduous
trees includes Penthaclethra macrophylla (Oil bean). In terms of number, some of the
plant species appear in large numbers in one place while they may be relatively scarce in
other places. An example is the Chromolaena odorata (siam weed), which dominates
some parts of the area like Ngwaukwu, Agburuke and Amapu Umuoha communities. In
terms of colour, they are mainly green. Some of them are flowering plants (Eg.
Napoleona imperialis, Costus afer, Cnestis feruginea, etc). Others are non-flowering
plants such as Pteridium aquilinum, Peperomia pellucida, Polystichum munitum, etc.
In the study area, some of the plant species attain a maximum height of 100m and
above at full maturity. Examples include the Khaya ivorensis, Millicia excelsa,
Pentaclethra macrophylla, etc. The plants are the primary producers. They also provide
ecosystem services such as food, fibre, water, air, pest and disease control, flood control,
etc. They also provide construction and medicinal services. Typical plant species used for
35
construction services include Khaya ivorensis, Millicia exelsa and Pentaclethra
macrophylla. Some of the plant species also play religious roles. For instance,
biodiversity utilization in the religion of the people of the study area is common with
reverence to kolanut (Cola nitida), in marriage rites, burial rites, title taking, etc. (PhilEze, 2010).
Some of the plants species are used as vegetables. Examples include Amaranthus
hybridus (smooth pigweed/Green), Vernonia amygdalina (bitter leaf) etc. On the other
hand, others are used as medicines. For instance, Acanthus montanus (False thistle) is
used with other species for the treatment of hepatitis. Most of these plant species have the
rainy season as their growing period. While some bear fruit in the rainy seasons, (Carica
papaya, Mangifera indica), others bear their fruit towards the beginning of the dry
season, ie November. Examples include Penthaclethra macrophylla, Gambeya albida,
Dacryodes edulis etc.The percentage occurrence of these plant species is presented in a
pie chart in Fig 3
In terms of the animal species, there are a lot of animal species of different kinds
in the area. They include the reptiles, amphibians, mammals, birds, molluscs etc. Some of
them are used as food. Examples include the Echis carinatus (saw scaled viper), Crocuta
crocuta (spotted hyena), Achatina achatina and Achachatina magmata, Artherurus
africana, Ploceus cucullatus, Cricetomys gambianus, etc.The percentage occurrence of
different wildlife in the is shown as pie chart in Fig 4.
In most parts of the study area, a storeyed sequence of canopies may be observed.
The number of easily discernible strata is not regular; anywhere from three to six canopy
layers may be delimited (Anyadike, 2002). Such canopy layers are mainly found in the
36
forest areas located around the community shrines and along the river banks. Example of
such areas include Amapu Umuoha and Uratta Umuoha communities.
2.1
The inventory and checklist of the plant species found in the study area
From the study, Isiala Ngwa North has a total of one hundred and thirty-two (132)
plant species. These plant species are classified under fifty-nine (59) families and one
hundred and twelve (112) genera as shown on the checklist. The checklist of the plant
species found in Isiala Ngwa North is presented in Table I.
Table 1: The Check List of the Plant Species Found In the Study Area
S/NO
1
FAMILY
Acanthaceae
SCIENTIFIC NAME
Acanthus montanus
ENGLISH NAME
3
NAME
TYPE
Inyinye ogwu/ H
Agamevu
H
Anwirinwa
Agaonidae
Ficus exasperate
Sand paper leaf
Amaranthaceae
Amaranthus spinosus
Spiny amaranth
H
Amaranthus hybridus
H
Amaranthus viridis
Smooth
pigweed/green
Slender amaranth
Spondias mombin
Yellow mombin
Anacardim occidentale
Anacardiaceae
H
S
Cashew
Mangifera indica
Mango
Ugiribekee
T
Finger root/bush
banana
Swizzle stick
Annonaceae
Uvaria chamae
5
Apoccynaceae
Rauvolfia vomitoria
Gongronema latifolium
Araceae
T
Uvuru/tutu
uvuru
Kanshu
4
6
SPECIES
False thistle
Acanthus arboreus
2
IGBO
S
C
Mgbugba
ogiri
Utazi/utabazi
S
C
Alstonia boonei
Alstonia cheesewood
Egbu
T
Anchomanes difformis
Forest anchomanes
Uto
H
37
Table 1: The Check List of the Plant Species Found In the Study Area Contd.
Colocasia esculenta
Cocoyam
Ede
7
Araliaceae
Centrum spp
8
Asteraceace
Emilia praetermissa
Milne/red head
Chromolaena odorata
Siam weed
Vernonia amygdalina
Bitter leaf
Synedrella nodiflora
Yellow starwort
Ageratum conyzoides
Goat weed
Emilia sonchifolia
H
9
Bignoniaceae
Newbouldia laevis
10
Bromeliaceae
Ananas comosus
Yellow tassel flower
stop death
West African border
tree
Pineapple
11
Burseraceae
Dacryoides edulis
Native pear
12
Capparidaceae
Pterocarpus mildbreadii
13
Caricaceae
Carica papaya
Pawpaw
Centrocema arenicola
Sand butterfly pear
Garcinia kola
Bitter cola
14
Clusiaceae
H
Awolowo/
Owolowo
Olugbu/
Onugbu
H
H
H
Ula njula/
ora njula
Ogburnizu/
Ahu mmuo
Ari
H
Nkugbo/
Nkwuaba
Ube
H
Oha/ora
T
Popo/okworo
nkita
H
H
T
T
C
Akuilu/
Agbiilu
T
T
Symphonia globulifera
15
Colchicaceae
Gloriosa superba
Flame lily/Glory lily
16
Combretaceae
Combretum micranthum
African bush willow
Commelinaceae
Combretum
dolichopetalum
Palisota hirsute
17
H
C
Ubi
S
G
Thumb
Commelina erecta
Aneilema umbrosum
Ikpereaturu
H
Agwo
anwuanwu
Nsansa
G
Azuuzu
H
H
18
Compositae
Aspilia Africana
African marigold
19
Convolvulaceae
Ipomoea involucrate
Morning glory weed
20
Cucurbiaceae
Telfairia occidentalis
Fluted pumpkin
Ugu
C
21
Cucurbitaceae
Lagenaria siceraria
Molina
Ugbooro
mmuo
C
C
38
Table 1: The Check List of the Plant Species Found In the Study Area Contd.
Cucurbita pepo
Pumpkin
Ugbooro/
ugbogoro
22
Cyperaceae
Cyperus difformis
Small
flower/umbrella plant
Mariscus alternifolius
Umbrella flatsedge
Cyperus distans
Piedmont flatsedge
C
H
G
G
23
Dennstaedtiaceae
Pteridium aquilinum
Bracken fern
Ebelebe
F
24
Dioscoreaceae
Dioscorea rotundata
White yam
H
25
Dryopteridaceae
Polystichum munitum
Sword fern
Jiagbaka/
jiocha
Ebelebe nkwu
Diplazium esculentum
Consumed fern
Manihot utilissima
Cassava (reddish)
26
Euphorbiaceae
Alchornia castaneaefolia
27
Fabaceae
F
F
Akpu/jiapu
S
Okpokai
S
Uvuvu
S
Alchornea cordifolia
Christmas bush
Euphorbia heterophylla
Spurge weed
H
Acalypha ciliate
Coper leaf plant
H
Havea brasilliensis
Para rubber
T
Euphorbia hirta
H
Ricinus communis
Garden spurge/hairy
spurge
Castor oil bean
Acalypha hispida
Chenille plant
Manihot esculenta
Cassava (yellowish
green)
Butterfuly pear
Centrocema pubescens
Pterocarupus
santalinoides
Anthonatha macrophylla
Baphia nitida
Camwood
Pentaclethra
macrophylla
Calopognium
mucunoides
Dialum guineense
Oil bean
Albizia samanea
Ogirisi
H
S
Akpu/jiapu
S
C
Nturukpa
T
Ububa
ubakiriba
Avosi/
Abosi
Ugba/ukpaka
S
Rattlesnake
S
T
C
Itikirinkwa/N
kwa
Avu
S
T
39
Table 1: The Check List of the Plant Species Found In the Study Area Contd.
Pueraria lobata
Kudzu vine
28
Gnetaceae
C
Pterocarpus soyauxii
Oha/ora
S
Gnetum africanum
Okazi/ukazi
C
Gnetum buchholzianum
Okazi/ukazi
C
29
Icacinaceae
Icacina trichanta
False yam
Ezeocha
S
30
Irvingiaceae
Irvingia gabonensis
Ugiri/ogbono/
ogbolo
T
31
Laminaceae
Platostoma africanum
African mango/wild
mango
Wild tea bush
Ocimum gratissimum
Scent leaf
Nchanwu
H
Avocado pear
Ube bekee
T
Mkpidi
H
H
32
Lauraceae
Persea americana
33
Lecythidaceae
Napoleona imperialis
34
Leguminosae
Mucuna pruriens
Mucuna beans
Agbara
C
35
Malvaceae
Cola pachyarpa
Colanut
Oji
T
Sida acuta
Wire weed/twelve
o’clock weed
Rose mallow weed
Nwokoadaghi
beyalaka
H
Hibiscus surrattensis
Urena lobata
Caesar weed
Ukukuru/oji
mbe
Udo
Cola nitida
Colanut
Oji
T
Triumfetta cordifolia
Cordleaf burbark
S
Corchorus olitorius
Vegetable jute
Akuba/Akugb
a
Ahihiara
Thaumatoccus danielli
Miracle fruit/sweet
Akwukwo
H
prayer plant
etere
Cola hispida
36
Marantaceae
H
T
H
H
37
Melastomataceae
Dissotis rotundifolia
Pinklady
Nri Ntekwuru
H
38
Meliaceae
Khaya ivorensis
Mahogany
Ono
T
Azadirachta indica
Neem/dogoyaro
Akum shorop
T
Nkwukwo
C
39
Menispermaceae
Synclisia scabrida
40
Mimosoideae
Mimosa pudica
41
Moraceae
Ebiaka anwu
G
Musanga cecropioides
Sleeping/sensitive
grass
Umbrella tree
Uru
T
Milicia excels
Iroko/African teak
Oji
T
40
Table 1: The Check List of the Plant Species Found In the Study Area Contd.
Myrianthus arboreus
Corkwood
Ujuju
42
Musaceae
H
Artocarpus altilis
Bread fruit
Ukwa
T
Musa parasidiaca
Plantain
Abirika
H
Musa acuminata
Banana
Unere
H
43
Myrtaceae
Psidium guajava
Guava
Gova
T
44
Palmae
Raffia vinifera
Raffia palm
Ngwo
T
Elaeis guineensis
Oil palm
Nkwu/Akwu
T
Cocos nucifera
Coconut
T
Citrus sinensis
Sweet orange
Aki
oyibo/Aku
bekee
Epe/Nde/oro
ma
45
Papilionidae
G
Combretum aculeatum
46
47
Piperaceae
Poaceae
Piper guineense
Black pepper fruit
Peperomia pellucida
Shinny bush
Bambusa bambos
Indian bamboo
Dactyloctenium
aegyptium
Andropogon tectorum
Crowfoot grass
Pennisetum purpureum
Pennisetum polystachion
Elephant/Napier
grass
Spear grass/congo
grass
Mission grass
Panicum maximum
Guinea grass
Eleusine indica
Indian goose grass
Ichita/ichite
G
Cymbopogon citratus
Lemon grass
Achara tii
G
Water leaf
Imperata cylindrical
48
Portulacaceae
Talinum triangulare
49
Rubiaceae
Sarcocephalus latifolius
Nauclea latifolia
50
Ruscaceae
T
Giant blue stem
African peach
Uziza
C
H
Acharaji
T
G
Achara
oghommiri
Achara ehi
G
Achara nkam
G
Achara nri
G
G
G
H
Uvuru
ilu/ubulu inu
Opikokoro
S
T
Diodia scandens
Onaedi/unaedi H
Dracaena manii
Ukpo
T
41
Table 1: The Check List of the Plant Species Found In the Study Area Contd.
51
Rutaceae
Citrus aurantifolia
Lime
Oroma
nkirisi/ Epe
ntiti
Citrus limon
Lemon
S
52
Sapotaceae
Gambeya albida
53
Solanaceae
Cnestis feruginea
S
White star apple
Udara
T
S
Capsicum frutescens
Sweet or bell pepper
Ijimbe/okpun
kita
Ose nkiri
Capsicum annum
Cayenne/red pepper
Ose
S
D
54
Sterculiaceae
Theobroma cacao
Cocoa
T
55
Tiliaceae
Glyphaea brevis
Masquerade stick
56
Urticaceae
Fleurya aestuans
Tropical netlle weed
57
Verbenaceae
Gmelina arborea
Gmelina
Melaina,
T
Blue porter weed
Anyannunu
H
58
Zingiberaceae
Stachytarpheta
cayennensis
Afromomum melegueta
Alligator pepper
Ose oji
S
59
Zomgoberaceae
Costus afer
Bush cane
Opete/okpete
H
Anyasu/
Anyachu
H
Source: Field work 2011
In the inventory of the plant species, (1) denotes present while (0) denotes absent. The
inventory of plant species according to the sampled quadrats in the communities is
presented in Table 2 as follows:
S
40
Umakwu
Amaekpu
Amachi
Umuosonyike
Umuomainta
A. montanus
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
0
1 1 1 1 1 1
1 0 1 1
1 1 1 1
1 1 0
1
1 1
1 1
0
1
Usaka
Umuala
0
Amaasaa
0
Umuatu Nsulu
0 0
Amachara
1 0
Ohuhu nsulu
0
Ubaha
0 0 0
Mbubo
0 0 0 0
Umuosu
0 1 0 0
Umuode
0 0 0 0 0 0
Ikputu
0
Umuezeukwu
0 0 0 0 0
Umuogu
0
Umuodeche
0 0
Umuezegu
0
Umuomaiukwu
Ntigha
0
Agburuke
Eziala
0
Nsulu
Amapu umuoha
0
Osusu
Umurandu
0
Obikabia
Ahiaba ubi
1
Amaoji
Ihie
0
Uratta umuoha
Abayi
A. arboreus
Scientific
Ahiaba okpuala
Eziama
Acanthaceae
Ngwa Ukwu
1
Name
Eziama Ntigha
Family
Amapu Ntigha
S/N
Umuogele
Table 2: The Inventory of Plant Species in Isiala-Ngwa North L.G.A.
2
Agaonidae
F. exasperata
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 0 0 0 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 0
1
1
3
Amaranthaceae
A. spinosus
0
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 0
0 1
1
1
A. hybridus
0
0
0
1
0
0
0
1 0
0
0 0 0 1 1
1
0 0 0 1 0 1
1 0 1 1
0 1 0 1
1 1 1
0
1 0
1 1
0
1
A. viridis
0
0
0
0
1
1
1
1 1
0
0 1 0 1 1
1
1 1 1 1 1 0
0 1 1 1
0 1 1 1
1 1 1
0
0 1
0 1
1
1
A. occidentale
1
0
1
0
0
0
0
0 0
0
0 1 0 0 1
1
1 0 0 0 0 1
1 0 1 0
1 0 0 0
0 1 0
1
0 0
0 1
1
0
S. mombin
1
1
1
1
1
1
0
1 0
1
1 1 1 1 1
1
1 1 1 0 1 0
0 0 1 1
1 1 0 1
1 1 1
1
1 1
0 0
1
0
M. indica
0
0
0
0
0
0
0
1 1
1
1 0 1 1 1
1
1 1 0 0 1 0
1 1 1 1
0 1 0 1
0 1 0
1
1 0
0 1
1
1
4
Anacardiaceae
5
Annonaceae
U. chamae
0
0
0
0
1
0
0
0 0
0
0 0 0 0 0
0
0 0 1 0 0 0
0 1 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
6
Apoccynaceae
R. vomitoria
1
1
1
1
1
1
1
1 1
1
1 0 1 1 1
0
1 0 1 0 1 1
0 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
7
Apocynaceae
G. latifolium
0
0
0
1
1
1
0
1 0
1
1 1 0 1 0
1
1 0 1 0 1 0
0 0 0 1
0 0 1 0
0 0 1
1
0 0
0 0
1
0
8
Apocynaceae
A. boonei
0
0
0
0
0
0
0
1 1
1
1 1 0 0 1
1
1 0 1 1 0 1
1 1 0 1
1 1 1 1
1 1 0
1
1 1
1 1
1
0
9
Araceae
A. difformis
1
0
1
1
1
1
0
1 1
1
1 1 1 1 1
0
0 0 1 1 1 0
0 1 1 0
1 0 1 0
0 1 0
0
1 1
1 0
0
0
C. esculenta
0
1
1
1
0
1
1
0 1
1
1 1 1 0 1
0
1 1 1 0 1 0
0 1 1 1
1 0 1 1
1 1 1
1
1 1
1 0
1
1
10
Araliaceae
Centrum spp
0
1
1
0
0
1
1
1 0
0
0 0 0 1 0
0
0 0 0 1 1 0
0 0 0 0
0 0 0 0
0 0 0
0
1 0
0 0
0
0
11
Arecaceae
E. guineensis
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
C. nucifera
0
0
0
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 1 0
1 0 1 0
1 0 1
1
0 0
0 0
0
1
C. odorata
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
12
Asteraceae
42
41
Table 2: The Inventory of Plant Species in Isiala-Ngwa North L.G.A. Contd
V. amygdalina
1
0
1
1
1
1
1
1 1
1
1 1 1 0 1
1
1 1 1 0 1 1
1 1 1 1
0 1 1 1
0 0 0
1
1 0
0 1
1
1
S. nodiflora
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
A. conyzoides
1
0
1
0
0
1
0
0 1
1
1 1 0 0 0
1
1 1 0 0 0 1
1 0 1 0
1 1 1 1
1 1 0
1
1 1
1 1
1
1
E. sonchifolia
0
1
1
1
1
1
1
0 1
1
1 1 0 1 0
1
1 0 1 1 1 1
1 1 1 0
1 1 1 0
1 0 1
1
1 1
1 1
1
1
E. praetermissa
0
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 0 1
1
1 0
0 0
1
1
13
Bignoniacea
N. laevis
1
0
0
1
1
1
0
1 1
0
0 1 1 1 0
1
0 0 1 0 1 1
0 0 1 0
0 1 1 0
0 1 1
0
1 1
1 1
0
1
14
Bromeliaceae
A. comosus
0
0
0
0
0
0
0
0 0
0
1 0 1 0 0
0
0 0 0 0 0 0
1 1 1 0
1 1 0 0
0 1 1
1
1 0
1 0
0
1
15
Burseraceae
D. edulis
0
1
1
0
0
1
1
1 0
1
1 1 1 1 1
1
0 1 1 1 1 1
1 0 1 0
1 1 0 1
0 1 1
1
1 1
1 0
1
0
16
Capparidaceae
P. mildbreadii
1
1
1
1
1
1
1
1 1
0
0 1 1 0 1
0
1 1 1 1 1 1
1 1 1 1
1 1 0 1
1 1 1
1
0 1
1 0
1
1
17
Caricaceae
C. papaya
0
0
0
0
0
0
0
0 0
0
1 0 1 0 0
1
0 0 0 0 0 1
0 0 0 0
0 0 1 0
0 0 0
0
1 0
1 0
0
0
18
Caucaceae
C. arenicola
0
0
0
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 1 1
0 0 0 0
0 0 0
0
0 0
0 0
0
0
19
Clusiaceae
Garcinia kola
1
0
0
0
0
0
0
0 0
0
0 1 0 1 1
1
0 0 0 0 0 1
1 1 1 0
1 0 0 0
0 0 0
0
0 0
0 1
1
1
S. globulifera
0
0
0
0
0
0
0
0 0
0
0 0 0 0 1
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
20
Colchicaceae
G. superba
0
0
0
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 1 0 1 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
21
Combretaceae
C. micranthum
0
1
0
0
0
0
0
0 0
0
0 0 0 0 1
0
0 0 0 0 0 0
1 1 1 1
0 0 0 1
0 0 0
0
0 1
1 1
1
0
Combretaceae
C. dolichopetalum
0
0
0
1
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
Commelinaceae
P. hirsuta
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
C. erecta
1
1
1
0
1
1
1
1 1
1
0 0 0 1 1
1
1 0 1 1 1 0
1 1 1 1
1 1 1 1
1 1 1
1
1 1
0 1
0
0
A. umbrosum
0
1
0
1
1
1
1
1 1
0
1 0 1 1 1
1
0 1 1 0 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
22
23
Compositae
A. africana
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
24
Convolvulaceae
I. involucrata
0
1
0
0
0
0
0
0 0
0
0 0 0 1 1
0
0 0 0 0 0 0
0 0 0 0
1 0 0 0
0 0 0
0
0 0
0 0
0
0
25
Cucurbitaceae
L. siceraria
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 0 1 1 1 1
0 0 1 0
1 1 0 1
1 1 1
1
1 0
1 1
1
1
C. pepo
0
0
0
0
1
0
0
0 1
0
0 0 0 0 0
0
0 0 0 0 0 0
0 1 0 0
0 0 0 0
0 0 0
0
0 1
0 0
0
0
T. occidentalis
0
0
0
0
0
0
0
0 0
1
1 1 1 1 1
0
1 1 0 0 0 1
0 0 0 0
0 1 0 1
0 0 0
1
0 1
0 0
0
0
C. difformis
0
1
0
0
0
0
1
0 0
0
1 1 1 1 1
0
0 0 0 0 0 1
0 0 0 1
1 1 1 1
1 1 1
1
1 1
1 0
1
0
26
Cyperaceae
43
42
Table 2: The Inventory of Plant Species in Isiala-Ngwa North L.G.A. Contd
M. alternifolius
0
1
1
0
1
1
0
1 1
1
0 0 1 1 1
1
0 1 1 1 1 0
0 1 0 1
0 0 1 1
0 1 0
0
0 0
1 0
0
0
C. distans
0
0
0
1
0
0
0
0 0
1
0 0 0 0 1
0
0 0 0 0 0 0
0 0 0 0
0 0 1 0
0 0 0
0
0 0
0 0
0
0
27
Dennstaedtiaceae
P. aquilinum
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 0 1 1 1 0
1 1 1 1
1 1 0 1
1 1 1
1
1 1
1 1
1
1
28
Dioscoreaceae
D. rotundata
0
0
0
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 1
1 0 0 0
0 0 0
0
0 0
0 0
0
1
29
Dryopteridacea
P. munitum
1
1
1
1
1
1
1
0 0
1
1 0 1 0 0
1
1 0 1 0 1 0
1 1 1 1
1 0 1 1
1 0 1
1
1 1
0 1
1
0
D. esculentum
0
0
0
0
0
0
0
0 0
0
1 0 0 0 0
0
0 0 0 0 0 0
0 0 0 1
0 0 0 1
1 0 0
0
0 1
0 0
0
0
M. utilissima
1
1
1
1
1
1
0
1 1
1
1 1 1 1 1
1
1 1 1 1 1 0
1 1 1 1
1 1 1 1
1 1 1
1
0 1
1 1
1
0
A. castaneaefolia
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
0 1 0 1
0 0 0
1
1 0
1 1
0
0
A. cordifolia
1
1
1
1
1
0
1
1 1
0
1 1 1 1 1
1
1 1 0 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
E. heterophylla
0
1
1
1
1
1
1
1 0
0
0 1 1 0 0
1
1 0 1 1 1 1
1 0 1 0
0 1 1 1
1 0 0
0
1 0
1 1
0
1
A. ciliata
0
1
1
1
0
0
1
1 0
1
0 0 1 0 0
1
1 0 0 0 0 0
0 0 0 1
0 1 1 0
1 1 0
1
1 1
1 1
1
1
H. brasiliensis
0
0
1
1
1
1
0
1 1
0
1 0 0 1 0
1
1 0 1 1 1 1
0 1 1 1
0 1 0 1
0 0 1
0
1 0
1 1
0
0
E. hirta
0
0
1
0
1
1
1
1 1
1
1 0 0 0 1
1
0 1 1 1 1 1
0 1 0 0
0 0 0 1
0 0 0
0
0 0
0 0
0
1
R. communis
0
0
0
1
0
0
1
0 0
0
1 1 1 0 1
1
1 1 0 1 0 1
0 1 1 1
1 0 1 1
1 0 1
1
0 0
0 1
1
0
D. scandens
0
0
0
0
0
0
0
0 0
0
0 0 1 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
M. esculenta
0
0
0
0
0
0
0
0 0
0
0 0 0 0 1
1
1 0 0 0 0 0
1 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
P. santalinoides
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 0
1
1
A. macrophylla
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
0 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
B. nitida
1
1
1
1
0
1
0
1 1
1
1 0 1 1 0
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
0
1 1
0 1
1
1
P. macrophylla
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
0 1
1 1
0
1
C. pubescens
0
1
0
0
1
0
0
0 0
0
0 1 0 0 0
0
0 0 0 0 0 1
1 0 0 0
0 0 1 0
0 0 1
1
1 1
0 0
1
0
C. mucunoides
0
1
1
0
1
1
1
1 1
0
0 0 1 0 0
1
1 1 1 1 0 1
1 1 0 0
1 1 1 1
1 1 1
1
1 1
0 1
1
1
D. guineense
0
1
1
0
1
1
1
1 0
1
1 1 0 1 1
1
1 1 1 1 1 1
1 0 1 1
1 1 0 1
1 1 1
1
1 1
0 1
1
1
A. samanea
0
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
0 0 1 1 1 1
0 1 0 1
0 1 0 1
1 1 0
0
1 1
1 0
1
0
P. lobata
0
0
1
0
0
0
0
0 0
0
1 0 0 0 0
0
1 1 0 0 0 1
0 0 0 0
1 1 0 0
0 0 1
0
0 0
1 1
0
0
P. soyauxii
0
0
0
0
0
0
0
0 0
1
1 0 0 1 0
1
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
G. africanum
1
1
1
1
1
1
0
1 1
0
0 1 0 1 1
1
1 1 1 1 1 1
1 1 1 1
1 0 0 1
0 1 0
0
0 1
0 1
1
0
30
31
32
Euphorbiaceae
Fabaceae
Gnetaceae
44
43
Table 2: The Inventory of Plant Species in Isiala-Ngwa North L.G.A. Contd
G. buchholzianum
0
0
0
0
0
0
1
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
33
Icacinaceae
I. trichanta
1
0
0
1
1
0
1
0 1
1
1 1 1 1 0
0
0 0 0 0 0 0
0 1 1 0
1 1 1 1
1 1 1
1
1 1
1 0
0
1
34
Irvingiaceae
I. gabonensis
0
0
1
1
0
1
1
1 1
0
0 0 0 1 1
0
0 0 0 1 0 0
1 1 1 0
0 0 0 0
1 0 0
0
0 1
0 0
1
1
35
Lamiaceae
P. africanum
0
1
0
0
1
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 1
0 0 0
0
0 0
0 0
0
0
O. gratissimum
0
0
1
1
0
0
1
1 1
0
1 0 1 0 1
0
0 0 0 0 0 1
0 1 0 0
0 0 1 0
1 1 1
1
0 1
0 0
1
0
36
Lauraceae
P. americana
0
0
0
0
0
0
0
0 1
0
0 0 1 0 0
0
1 0 0 0 0 1
1 1 1 0
1 1 1 1
1 1 1
1
1 0
1 0
1
1
37
Lecythidaceae
N. imperialis
1
1
1
1
1
1
1
0 1
1
1 1 0 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 0 0
0 0 1
0
1 1
1 1
1
1
38
Leguminosae
M. pruriens
1
1
1
1
1
1
1
1 1
0
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
39
Malvaceae
C. pachycarpa
1
0
0
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 1 0 0 0
1 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
S. acuta
1
1
1
1
1
1
1
1 1
1
1 1 0 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 0 0
0 1 1
0
1 1
0 1
1
1
H. surattensis
1
1
1
0
1
1
1
0 1
1
0 0 0 1 0
1
1 1 1 1 1 1
1 0 0 0
1 0 0 1
1 0 0
0
1 1
0 1
1
1
C. hispida
1
0
1
1
1
1
1
1 1
1
1 1 1 1 1
0
0 0 1 0 1 1
1 1 1 1
0 1 1 0
1 1 0
1
0 0
1 1
1
0
U. lobata
1
1
1
1
1
1
0
1 1
1
1 1 1 1 1
1
1 1 0 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 0
1 1
1
1
C. nitida
0
0
1
0
1
0
0
1 1
0
1 0 0 1 0
0
0 0 0 0 0 0
0 1 0 0
1 0 0 0
1 0 0
0
0 0
0 0
1
0
T. cordifolia
0
0
0
1
0
0
0
1 1
0
1 0 0 1 1
1
0 0 0 0 0 0
0 1 1 0
0 0 0 1
0 1 0
1
0 0
0 0
1
0
C. olitorius
0
0
0
0
0
0
0
0 0
1
0 0 0 0 1
1
1 1 0 0 1 1
0 0 1 0
0 1 1 1
1 1 1
1
1 1
1 1
0
1
40
Marantaceae
T. danielli
0
0
0
1
0
1
1
0 1
0
1 1 0 0 0
1
0 1 1 1 1 1
0 1 1 0
0 0 0 0
1 1 0
0
0 0
0 0
1
1
41
Melastomataceae
D. rotundifolia
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
0 0 0 1 1 1
1 1 1 0
1 0 1 1
0 0 1
0
0 1
0 1
1
1
42
Meliaceae
K. ivorensis
1
1
1
1
0
1
0
1 1
1
1 0 1 1 1
1
0 0 1 1 1 1
0 1 1 1
1 1 1 0
1 1 1
1
1 1
1 1
0
1
A. indica
0
0
0
0
0
0
0
0 0
0
0 0 0 0 0
0
0 1 0 0 0 1
0 1 1 0
1 0 0 0
1 0 0
1
0 1
0 1
0
1
43
Menispermaceae
S. scabrida
0
0
1
0
0
0
0
0 0
0
0 1 0 1 1
1
1 0 1 0 1 1
1 0 0 1
1 1 0 0
1 1 0
0
0 1
0 0
1
0
44
Mimosoideae
M. pudica
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
45
Moraceae
M. cecropioides
1
0
1
1
1
1
1
1 1
1
1 1 0 1 1
0
0 0 1 0 1 0
0 1 1 0
0 0 0 0
1 0 0
0
0 1
0 0
1
0
M. excelsa
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
M. arboreus
1
1
1
1
1
1
1
1 1
1
1 0 1 1 1
1
1 1 1 1 1 0
1 1 1 1
0 1 0 0
1 1 1
0
1 1
1 1
1
0
A. altilis
1
0
1
1
1
1
1
0 1
1
1 1 0 1 1
1
0 1 1 1 1 1
0 1 0 1
1 1 1 1
1 1 0
1
1 1
1 0
1
1
M. parasidiaca
0
0
0
0
0
0
0
0 0
1
1 1 0 1 1
1
1 1 0 0 1 0
1 1 1 1
0 0 1 0
0 1 1
1
1 1
1 0
1
1
46
Musaceae
45
44
Table 2: The Inventory of Plant Species in Isiala-Ngwa North L.G.A. Contd
M. acuminta
0
0
0
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
1
0
47
Myrtaceae
P. guajava
1
1
1
1
1
1
1
1 0
1
1 1 1 1 0
0
0 0 1 0 1 1
0 0 1 0
1 0 1 0
0 0 1
1
1 1
1 0
0
0
48
Palmae
R. vinifera
1
1
1
1
1
1
1
1 1
1
1 1 0 0 1
1
1 1 1 1 1 1
1 1 1 1
1 1 0 1
0 0 0
0
1 0
1 1
0
1
49
Papilionidae
C. sinensis
0
0
0
0
1
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
1 1 1 0
0 0 0 1
0 1 0
1
0 0
0 0
0
0
50
Phytoseiidae
C. aculeatum
0
0
0
0
1
0
1
0 1
1
1 1 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
51
Piperaceae
P. guineense
1
0
0
0
1
0
0
0 0
1
0 0 0 1 1
1
0 1 0 1 0 1
0 0 0 0
0 0 0 1
0 0 0
0
0 1
0 0
0
0
P. pellucida
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 0
1
1
B. bambos
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
0 1 1 1
1 1 1
1
0 1
1 1
1
1
D. aegyptium
1
1
0
1
1
1
0
1 1
1
0 0 0 1 1
0
0 1 1 1 1 0
1 1 1 1
1 0 0 1
1 1 0
0
0 1
0 1
1
1
A. tectorum
1
1
1
1
1
1
1
1 1
1
1 1 0 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
P. purpureum
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
I. cylindrical
1
1
1
1
1
1
1
1 0
1
0 0 1 1 1
1
1 1 1 1 1 1
0 0 1 1
1 0 1 1
1 0 1
1
1 1
1 1
1
1
P. polystachion
1
1
1
1
1
1
1
1 1
0
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 0
0 0 1 1
0 0 0
1
1 1
0 1
1
0
P. maximum
0
1
1
0
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 0
1 1 1
1
1 0
1 1
1
1
E. indica
0
1
0
0
0
0
0
1 0
0
1 1 1 1 1
1
1 1 0 1 0 1
1 0 1 1
1 1 1 1
1 1 1
0
1 0
1 1
1
1
C. citratus
0
0
1
0
0
0
0
0 0
0
0 0 0 0 0
1
1 1 0 0 0 0
0 0 0 0
1 0 0 0
0 0 0
1
0 1
0 1
0
0
52
Poaceae
53
Portulacaceae
T. triangulare
1
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 1
1
1
54
Rubiaceae
S. latifolius
1
1
1
1
1
1
1
1 1
0
1 1 1 1 1
0
0 1 1 1 1 1
1 1 1 1
0 1 1 1
0 1 1
1
1 0
1 1
1
1
N. latifolia
1
1
1
1
1
1
1
0 0
0
0 1 1 1 1
1
0 0 1 0 1 0
0 0 1 0
1 0 0 0
0 1 0
0
0 0
1 0
1
0
D. scandens
0
0
0
0
0
0
0
0 0
0
0 1 0 0 0
0
1 0 0 0 0 1
0 0 1 0
1 0 0 0
1 0 1
1
0 1
0 0
0
1
55
Ruscaceae
D. manii
1
1
1
1
1
1
0
0 0
1
0 1 1 1 1
1
0 1 0 1 1 0
1 1 1 1
1 1 1 1
1 1 1
1
1 1
1 0
1
1
56
Rutaceae
C. aurantifolia
0
0
0
1
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
1 0 0 0
1 0 0 0
0 0 0
0
0 0
0 0
0
0
C. limon
0
0
0
0
0
0
1
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
57
Sapotaceae
G. albida
0
0
0
0
1
1
0
0 1
0
0 0 1 0 0
0
1 1 0 1 0 1
1 1 1 0
1 1 0 1
1 1 1
1
1 0
1 1
1
1
58
Solanaceae
C. feruginea
1
1
1
1
1
1
1
1 1
1
1 1 0 1 1
0
1 1 1 1 1 1
1 1 1 1
1 1 1 1
1 1 0
1
1 1
1 1
1
1
C. frutescens
0
0
1
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
1
C. annum
0
0
0
1
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0
0
0 0
0 0
0
0
46
45
Table 2: The Inventory of Plant Species in Isiala-Ngwa North L.G.A. Contd
59
Sterculiaceae
T. cacao
0
0
1
0
0
0
0
0 0
0
0 0 0 0 0
0
0 0 0 0 0 0
0 0 1 0
0 0 0 0
0 0 0
0
0 0
1 0
0
0
60
Tiliaceae
G. brevis
1
0
0
1
1
0
1
1 1
1
0 0 1 1 1
1
0 0 0 0 0 1
0 0 0 1
1 0 1 0
0 1 1
0
1 1
0 0
1
0
61
Urticaceae
F. aestuans
0
1
0
1
1
1
1
1 1
1
0 0 0 0 1
1
1 1 1 0 1 1
1 1 1 1
0 0 0 1
1 0 0
0
1 0
1 0
1
0
62
Verbenaceae
G. arborea
1
0
1
1
1
1
1
1 0
1
0 0 0 1 1
1
0 1 1 1 1 0
0 1 1 1
1 1 1 1
0 1 1
1
1 0
1 0
1
1
S. cayennensis
0
1
1
1
1
1
1
1 1
1
1 1 1 1 1
1
1 0 1 1 1 1
0 1 1 0
0 1 0 1
1 0 1
1
1 1
0 0
1
1
C. afer
1
1
1
1
1
1
1
0 0
1
1 1 1 1 1
1
1 1 1 1 1 1
1 0 1 1
1 0 1 1
1 1 0
0
1 1
1 1
1
1
A. melegueta
0
0
1
0
0
0
0
0 0
0
0 0 0 0 0
0
0 1 0 0 0 1
0 0 0 0
1 0 0 0
1 0 0
1
0 1
0 0
0
0
63
Zingiberaceae
Source: Fieldwork 2011
NB:
1
=
present
0
=
Absent
47
48
Plate 2 shows one of the sampled quadrats being mapped out, while plate 3
shows some of the plant species in the area.
Plate 2: One of the quadrats being mapped out in Agburuke Community
Plate 3: Some of the plants species in the area: Aspilia africana, Chromolaena
odorata, Pteriduim aquilinum and Pennisetum purpureum.
The plant species in the study area are divided into six groups viz ferns,
climbers, grasses, herbs, shrubs, and trees. The inventory shows that there are three
(3) species of ferns, fourteen (14) species of climbers and the grasses also have
49
fourteen (14) species. There are also forty-six (46) species of herbs and twenty-three
(23) species of shrubs. The inventory equally included thirty-five (35) species of trees.
(See Appendix 2A). Their frequency of occurrence shows that they are 2766 in
number. The ferns are sixty-seven (67), representing 2.64% of the total population.
The climbers are one hundred and seventy-two (172), which is 6.79% of the
population. While the grasses are three hundred and three (303) representing 11.96%,
there are seven hundred and fifty-five (755) herbs (29.79%). The shrubs are four
hundred and one (401) which is 15.82% of the population of the plant species.
Finally, the trees are eight hundred and thirty-six (836) representing 32.99% of the
population. This is represented with a pie chart in Fig 5.
Fig 5: Percentage of the plant species in the area.
2.2 The Inventory and Checklist of the animal species found in the study area.
As can be seen in Table 3 and Appendix 2B, the checklist of the animal
species shows a great diversity of animal species. They range from reptiles (R),
amphibians (A), other lower animals to larger mammals (M) and others (O) that do
not fall under any of the categories above. From the study, it is evident that Isiala
50
Ngwa North has a total of sixty- two (62) species of animals. They are classified
under forty-eight (48) families and sixty (60) genera as can be seen on the checklist.
Table 3: The Checklist of the Animal Species Found In the Study Area
S/N FAMILY
SCIENTIFIC NAME
ENGLISH NAME
IGBO NAME
1.
Milvus migrans
Kite
Egbe
SPECIES
TYPE
B
Leptodon cayanensis
Gray-headed kite
Egbe
B
Elanus leucurus
White-tailed kite
Egbe
B
Buteo nitidus
Gray hawk
Otinkwu
B
Accipitridae
2
Achatinidae
Achatina achatina
African Land snail
Eju/Ejula
O
3
Aegypiinae
Aegyius monachus
Vulture
Udele
B
4
Agamidae
Agama agama
Rainbow lizard
R
5
Alaudidae
Galerida malabarica
Malabar-lark
Oketikpo/oke
ngwere
Okuruekwe
6
Apodidae
Apus apus
Swift
Ebelebe ntiogu
B
7.
Archachatinidae
Archachatina magmata
African land snail
Eju/Ejula
O
8
Ardeidae
Bulbulcus ibis
Cattle Egret
Shekeleke
B
9
Bovidae
Philantomba maxwelli
Maxwell’s duiker
Nwanzu
M
Neotragus pygmaeus
Antelope
Ele
M
Bos primigenius
Cattle
Ehi/Efi
M
Bos Taurus
Cow
Nnama/Efi
M
B
10
Bufonidae
Bufo regularis
Toad
Awo/Awoli
A
11.
Canidae
Vulpes zerda
Pale-fox
Ufu
M
12.
Cisticolidae
Cisticola carruthersi
Carruthers Cisticola
13.
Colubridae
Oxybelis fulgidus
Green-vine snake
Agwoaka
R
Opheodrys aestivus
Rough Green snake
Nsuali
R
B
14.
Columbidae
Columbina passerina
Dove
Nduru/Nduri
B
15.
Cuculidae
Centropus senegalensis
Senegal coucal
Ovo
B
Cuculus canorus
Common cuckoo
Nwankwo
oringwere/Nkwo
B
16.
Dicruridae
Dicrurus leucophaeus
Drongos/black bird
B
17.
Emberizidae
Emberiza citrinella
Yellow Hammer
B
18.
Estrildidae
Lagonosticta senegala
Red-billed fire finches
B
19.
Eudrilidae
Nsukkadrilus mbae
Earthworm
Udude/idide
O
20.
Gekkonidae
Hemitheconyx caudinunctus
African fat-tailed
gecko
Yellow-headed day
Gecko
Ncheke
R
Phelsuma klemmeri
R
51
Table 2: The Checklist of the Animal Species Found In the Study Area Contd.
21.
Heteromyidae
Perognathus longimembris
Mouse
Oke
M
22.
Hyaenidae
Crocuta crocuta
Spotted hyena
Nkita ohia
M
Hyena stirata
Hyena
Ediabali/Edi
M
23.
Hystricidae
Atherurus africana
Porcupine
Ebiogwu
M
24.
Lumbricidae
Lumbricus terrestris
Earthworm
Ududu/idide
O
25.
Malapteruvidae
Bothropthalmus lineatus
Eke/Akogwe
R
26.
Muridae
Rattus norvegicus
Red and black stripped
snake
Rat
Oke
M
Pseudomys postvittana
Hasting’s river mouse
Oke
M
Lemniscomys barbarus
Stripped grass mouse
Oke
M
27.
Muscicapidae
Muscicapella hodgsoni
Pygmyfly catcher
Nkelu
B
28.
Nesomyidae
Cricetomys gambianus
African giant rat
Ewi/Ewita/Eyi
M
29.
Nimaviridae
Epihyas postvittana
Nnunu
B
30.
Numididae
Guttera edouardi
Light Brown Apple
moth
Guinea fowl
Ogazi
B
31.
Pachybolidae
Pachybolus ligulatus
Millipede
Esu/Ariri
O
32.
Palmeae
Thryonomis swinderianus
Grass cutter/cane rat
Ebinchi/Nchi
M
33.
Phyllostomidae
Desmodus rotundus
Bat
Usu
B
34.
Plocedidae
Ploceus cucullatus
Weaver bird
Ahia/Asha
B
35.
Psittacidae
Psittacus erithacus
African grey parrot
Iche/iche okwe
B
36.
Pycnonotidae
Pycnonotus atriceps
Bulbuls/song bird
37.
Pythonidae
Python sabae
African rock python
Eke
R
38.
Ranidae
Rana hexadactyla
Frog
Akiri
R
Rana arvalis
Frog
Akiri
R
B
39.
Remizidae
Anthoscopus minutus
Southern penduline-tit
B
40.
Sciuridae
Xerus erythropus
Stripped ground squirrel
Uze
M
Heliosciuru gambianus
Gambian sun squirrel
Osa
M
41.
Sphaerodactylidae Gonalodes albogularis
Yellow-headed Gecko
Ngwere Ubi
R
42.
Sphenodontidae
Sphenodon punctatus
Tuatara
Ngwere
A
43.
Strigidae
Ptilopsis leucotis
Owl
Ududu/Nkwu
B
44.
Suidae
Sus scrofa
Eziohia
M
45.
Thraupidae
Tachyphonus luctuosus
46.
Timaliidae
Turdoides gularis
Wild pig/wild boa/feral
pig
White-shouldered
Tanager
White-throated babbler
47.
Viperidae
Echis carinatus
Saw-scaled viper
Ajuala
48.
Xantusidae
Lepidophyma flavimacuatum
Yellow-spotted lizard
Source: Field work 2011
B
B
R
R
45
The inventory of the animal species taken from the sampled quadrats is presented in Table 4 as follows.
Abayi
Ihie
Ahiaba ubi
Ahiaba okpuala
Umurandu
Amapu umuoha
Uratta umuoha
Amaoji
Obikabia
Osusu
Eziala
Ntigha
Nsulu
Agburuke
Umuomaiukwu
Umuezegu
Umuodeche
Umuogu
Umuezeukwu
Ikputu
Umuode
Umuosu
Mbubo
Ubaha
Ohuhu nsulu
Amachara
Umuatu Nsulu
Amaasaa
Umuala
Umakwu
Amaekpu
Amachi
Usaka
Umuosonyike
Umuomainta
Accipitridae
Eziama
1.
Name
Ngwa Ukwu
Family
Eziama Ntigha
S/N
Umuogele
Amapu Ntigha
Table 4: The Inventory of the Animal Species in Isiala Ngwa North L.G.A.
M. migrans
0 0
0
0
0
0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
0
0
0
L. cayanensis
1 0
0
0
0
0 0 1 0
0 0 1 1 1 1 0 1 0 0 1 0 0 1 1 0 0 1 1 0 1 1 0 0 1 0 0 1
0
0
0
E. leucurus
1 1
1
1
1
1 1 1 0
1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 1 0 0 0 1 1
0
0
0
Scientific
2
Accipitridae
B. nitidus
1 1
1
1
1
1 1 1 1
0 1 1 1 0 0 0 0 0 0 1 1 1 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0
0
0
0
3
4
Achatinidae
Aegypiinae
A. achatina
A. monachus
0 0
1 0
0
1
0
1
0
1
0 0 0 0
1 1 1 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 1 0 0 0 1 0 1 0 1 1 1 0 1 0 0 0 0 0 1 1 1 0 0 1 1 1
0
0
0
1
0
0
5
Agamidae
A. agama
1 1
1
1
1
1 1 1 1
1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1
1
1
1
6
Alaudidae
G. malabarica
1 0
1
0
0
0 0 1 1
1 1 0 0 1 1 1 1 1 1 0 0 1 1 1 0 1 0 0 1 1 1 1 1 0 1 0 1
1
1
1
A. apus
0 0
1
1
1
0 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 0 1 1 0
1
0
1
7
Archachatinidae
A. magmata
0 0
0
0
0
0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
0
0
8
Ardeidae
B. ibis
1 0
0
0
1
1 1 0 0
0 1 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0
0
1
1
9
Bovidae
P. maxwelli
0 1
0
1
0
0 0 0 1
0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1
1
0
0
N. pygmaeus
0 0
0
0
0
0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
0
0
10
Bufonidae
B. regularis
1 1
1
1
1
1 0 1 1
1 1 1 1 1 0 0 1 1
0 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1
1
1
1
11
Canidae
V. zerda
0 0
1
0
0
0 1 0 0
0 0 1 0 1 1 1 1 0 1 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0
1
1
0
12
Cisticolidae
C. carruthersi
0 0
0
0
1
0 0 1 1
1 1 0 1 0 0 0 1 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 1 0 1 1 0
0
0
1
13
Colubridae
O. fulgidus
1 1
1
1
1
1 1 1 0
1 0 1 1 1 1 0 1 0 1 1 0 1 1 1 1 1 0 1 1 1 0 0 0 0 1 1 1
1
1
0
52
46
Table 4: The Inventory of the Animal Species in Isiala Ngwa North L.G.A.
O. aestivus
0
0
0
0
0
0 0 0 0
1 1 1 0 0 1 0 1 1 0 1 0 1 0 1 1 1 1 0 1 0 1 0 1 0 0 0 0 1 1
0
C. passerine
0
0
0
0
0
0 0 1 1 1 0 1 1 1 1 0 0 1 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 1 0 0 1 0
1
14
Cuculidae
C. senegalensis
0
0
1
0
1
0 0 0 0 0 1 1 1 1 1 0 1 0 1 1 1 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1
1
15
16
Cuculidae
Dicruridae
C. canorus
D. leucophaeus
0
1
1
1
1
0
1
0
1
0
1 0 0 0 0 1 1 1 1 1 0 0 0 0 1 0 1 0 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1
1 0 1 1 1 0 1 1 1 1 1 1 1 0 1 1 0 0 0 1 1 1 1 1 1 1 0 0 1 0 0 0 1 1
1
1
17
Emberizidae
E. citrinella
1
1
1
0
1
0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1
0
18
Estrildidae
L. senegala
0
0
0
0
0
0 0 1 0 1 0 1 1 0 1 0 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1
1
19
Eudrilidae
N. mbae
0
0
0
0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
20
Gekkonidae
H. caudinunctus
1
1
1
1
1
1 0 0 1 0 1 1 1 1 0 0 0 1 1 0 0 1 1 0 1 0 0 1 1 1 0 1 1 0 1 1 0 1 1
0
21
22
Heteromyidae
Hyaenidae
P. Klemmeri
P. longimembris
C. crocuta
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 0 0 1 0 0 1 1 0 1 1 1 0 1 0 0 0 1 0 0 0 1 0 1 0 1 0 1 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
1
0
23
Hystricidae
H. stirata
A. africana
0
0
1
0
1
1
1
0
1
0
1 1 1 1 1 0 1 1 1 0 1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0
0 0 1 0 1 1 0 1 1 0 1 0 1 0 1 1 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 1
0
0
24
Lumbricidae
L. terrestris
0
0
0
0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
25
Malapteruridae
B. lineatus
0
0
1
1
0
0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0
26
Muridae
R. norvegicus
1
1
1
1
1
1 0 1 1 1 1 0 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 1 0 0
0
P. postvittana
0
0
0
0
0
0 0 1 1 1 0 0 0 1 0 1 1 1 1 1 0 1 0 0 0 0 0 0 1 1 0 1 0 1 1 1 1 0 1
1
L. barbarus
1
1
0
1
0
0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 0 1 1 1 0 1 1 1 1 0 0 1 0 1 1
0
27
Muscicapidae
M. hodgsoni
1
1
1
0
1
1 1 1 0 1 1 0 0 1 0 1 1 1 1 1 0 1 0 0 1 0 1 0 1 1 0 0 1 0 0 0 1 0 0
1
28
Nesomyidae
C. gambianus
1
1
1
1
1
1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 1 1 1 0 1 0 1 0 1 1 1 1 1 1 0 1 0
0
29
Nimaviridae
E. postvittana
0
0
0
0
0
0 0 1 1 0 1 1 1 0 0 0 1 0 1 1 0 0 0 0 1 1 0 0 1 0 1 0 1 0 1 1 0 0 1
1
30
Numididae
G. edouardi
1
1
0
1
1
1 1 1 1 1 1 1 0 1 1 1 0 0 1 1 1 1 1 0 0 1 0 0 0 0 1 1 1 1 0 1 1 0 0
0
53
47
Table 4: The Inventory of the Animal Species in Isiala Ngwa North L.G.A.
P. ligulatus
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
31
Pachybolidae
32
Palmeae
T.
1 1
1
1
1
1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0
swinderianus
33
Phyllostomidae
D. rotundus
1 1
1
1
1
1 0 1 0 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 0 1 1 0 1 1 1 1
34
Ploceidae
P. cucullatus
1 1
1
1
1
1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 0 1 0 1 0 1 1 1 1 1 1 1 1 0 1 0
35
Psittacidae
P. erithacus
0 0
1
0
0
0 0 0 1 0 1 0 0 0 0 1 0 1 0 1 1 0 0 1 0 1 0 0 0 1 1 1 1 1 0 0 1 0 1 0
36
Pycononotidae
P. atriceps
0 0
1
1
0
1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 0 1 1 1 0 1 0
37
Pythonidae
P. sabae
0 0
0
0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
38
Ranidae
R. hexadactyla
1 0
0
1
1
0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 0 1 1 0 0 0
R. arvalis
0 1
1
0
0
1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 0 0 1 0 1 0 1 0 0 0 1 0 0 1 1 1
39
Remizidae
A. minutus
0 0
0
0
0
0 0 0 1 1 1 1 0 0 1 0 1 0 1 0 1 1 1 0 0 1 1 0 1 1 0 0 1 0 1 0 1 0 0
40
Sciuridae
X. erythropus
0 1
1
1
1
1 0 0 1 1 1 0 1 1 1 0 1 1 0 1 1 1 0 0 0 1 1 1 1 0 1 0 0 1 0 0 1 0 1 0
H. gambianus
1 1
1
1
1
1 1 1 1 1 0 1 1 0 1 1 1 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 1 1 1 0 0 1 0 1
41
Sphaerodactylidae
G. albogularis
1 1
1
0
1
1 0 1 0 1 0 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 0 0 1 1
42
Sphenodontidae
S. punctatus
0 1
0
0
0
0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0
43
Strigidae
P. leucotis
1 1
1
1
1
1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0
44
Suidae
S. scrofa
0 0
0
0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
45
Thraupidae
T. luctosus
0 0
0
0
0
0 0 0 1 1 0 1 1 1 0 0 1 1 0 0 1 1 0 1 1 1 1 1 1 1 1 0 1 0 1 0 0 1 0 1
46
Timaliidae
T. gularis
0 0
0
0
0
0 0 0 0 0 1 1 0 0 1 0 1 1 0 1 0 1 1 1 1 1 0 0 1 0 0 0 1 0 0 0 1 0 1 0
47
Viperidae
E. carinatus
1 1
1
1
1
1 0 0 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 0 1 1 0 1 0 1
48
Xantusidae
L. flavimaculatum
0 1
Source: Field work, 2011
0
0
0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
54
55
The animal species are divided into four main groups viz: birds, reptiles,
amphibians, mammals and others. From the inventory, there are 26 species of birds, 11
species of reptiles, 15 species of mammals, and 4 species of amphibians. See appendix 2.
In their frequency of occurrence, there are 469 birds (42.75%), 158 reptiles (14.40%),
304 mammals (27.72%) and 92 others (8.392%). This is represented with a pie chart in
Fig 6.
Fig 6: Percentage of different wildlife of the area
56
CHAPTER THREE
THE TYPES AND SPATIAL DISTRIBUTION OF AGRICULTURAL LAND USE
PRACTICES IN ISIALA NGWA NORTH
3.1
Types of Identified Agricultural Land Use Practices in the Study Area
Data on the different typses of agricultural land use practices within the area is
shown/presented on figures 5 to 10. Agriculture is the main economic activity in Isiala
Ngwa North LGA. The agricultural activities in the area are dominated by food cropping.
Hence, there are a number of ways in which the people of the area carry out their
agricultural, activities for food production.
The agricultural land use types that are practiced in the area include bush
fallowing/shifting cultivation, intercropping, crop rotation, mixed farming, monocropping/plantation agriculture and animal husbandry. Although these agricultural land
use types are practiced in the study area, the degree of practice varies among the
communities.
3.1.1
Bush fallowing/shifting cultivation
Bush fallowing is a type of agricultural land use for subsistence agriculture where
land is cultivated for a period of time and then left uncultivated for several years so that
its fertility will be restored. In bush fallowing or shifting cultivation, a farmer crops an
area for 2 or 3 years and then leaves the land fallow for a period of five to twelve years.
During the fallow period, the farmer uses other plots of land. The fallow period varies
from place to place and is mainly determined by the size of the population in relation to
the available land mass. For instance, many decades ago in the study area, the fallow
period of 5 – 12 years was obtainable. But nowadays, it has reduced due to population
growth, to two or three years. Shifting cultivation can be said to have two versions. The
57
first is the bush rotation which is the clearing and cultivation of an area of virgin bush for
2-3 years after which the farmer moves to another area and repeats the process. Farmers
generally return to the old site after several years. The second is the village rotation
which involves the total population of a community. After clearing and cultivating the
area, they move to settle elsewhere. This is relatively easy when the population of the
community is low. It is bush rotation that is practiced in the study area. Even at that, the
practice is mainly among the communities with villages that have communal land
ownership. In that case, during the farming season, a day is set aside by the elders, when
an area of land would be divided into plots among taxable adults. Otherwise, individual
farmers acquire land on lease from those that have more. There are some people who
have other people’s land on pledge in addition to their own land. Such people do lease to
interested farmers just for a planting season. For economic reasons, when somebody
takes land on lease, he maximizes the profit. This has a negative impact on biodiversity,
as the farmer tends to reduce the fallow period. This reduction is in order to cultivate the
land for many years.
3.1.2
Intercroping
Intercroping is the process of growing crops ie non-animal species or variety to be
harvested as food, livestock fodder, fuel or any other economic purpose. Major world
crops include sugar cane, pumpkin, maize (corn), wheat, rice, cassava, yam, soya beans,
hay, potatoes and cotton (F.A.O. UN, 2009).
Intercroping involves planting of different crops on the same piece of land. Crop
rotation is related to intercroping since it is a system where by different crops are grown
continually on the same piece of land in such a way that they follow a definite sequence
58
or cycle. The selection of the crops grown and the kind of rotation used, differs from
place to place and environmental conditions play a significant role here. In the study area,
this practice is mainly associated with communities with limited parcels of land. It is also
practised by public schools with high staff strength and very little arable farm land.
3.1.3
Mixed farming
Mixed farming is the use of a single farm for multiple purposes such as the
growing of cash crops and annual crops or the raising of livestock. In other words, mixed
farming is a system in which animal husbandry is combined with crop production. There
are two main versions of mixed farming. In the first, a farmer may keep livestock on his
farm and also cultivates crops such as maize and rice. The animals are fed with some of
these cereals. The second is where a farmer does not keep his own animals; he may allow
the animals of other farmers to graze on his farm after harvesting his crops, so that he will
gain the advantage of their manure through their droppings in improving the fertility of
his soil (Adeleye 2003, Amechi, 2004). The first version of the mixed farming is
operational in the study area. Here the farmer feeds his livestock with the plant residue,
while he improves the soil fertility with the animal dung.
3.1.4
Mono-cropping/plantation agriculture:
This is an agricultural system, generally a monoculture, for the production of
tropical and sub tropical crops especially bananas, coffee, cocoa, cotton, oil palm, rubber
etc. In the study area, plantation agriculture is practised by some farmers with crops such
as oil palm, rubber, orange, plantain among others. The practice is not done on a large
scale as it is required because farmers prefer to concentrate on food crops. Another
reason is that the available and arable lands have drastically reduced due to increase in
59
the population size in the study area. Plate 4 shows an Oil palm plantation located in
Amapu Umuoha one of the communities of in the study area
Plate 4: One of the Oil palm (Elaeis guineenisis) plantations in Amapu Umuoha community
3.1.5
Animal Husbandry:
Animal husbandry is the agricultural practice of breeding and raising livestock.
Grazing is the process in which the farmer keeps his livestock on a designated field for
grazing. In the study area, such livestock include cattle, cows, sheep, and goat. The
farmer either takes them out to the field in the morning and brings them back in the
evening, or stays with them in the field till he is ready to bring them back. Some of the
areas where grazing takes place are located near the compound. Sometimes school fields
are also used for this purpose. The types of livestock that graze on school fields are sheep
and cattle that are tied to sticks in the morning and taken home in the evening.
Grazing of livestock in the study area however is mostly done in such a way that
the farmer uses his own parcel of land. Hence, nobody allows anybody to use his land for
grazing. Plates 5-6 show some of the grazing animals in the area.
60
Plate 5: Some grazing animals (Cows: Bos taurus)in
Uratta Umuoha Community
Plate 6: Some grazing animals
(Cattle: Bos primigenius) tied to stakes
in Amapu Umuoha Community
3.2 The Spatial Distribution of the Agricultural Land Use Practices in the Area
In the study area, five dominant agricultural land use types were identified. They
are intercropping/crop rotation, mixed farming, plantation agriculture/mono-cropping,
bush fallowing/shifting cultivation and animal husbandry. Even though these agricultural
land use types operate in the study area, their intensity are not evenly distributed over the
study area. Fig 10 presents the spatial spread of the respective agric land use types
practiced. Based on field survey, intercropping/crop rotation is practiced in all the
communities at varying degrees. The first groups are the communities in the NorthEastern part of the study area. Notable among them are Agburuke, Umuezeukwu,
Umuode among others. Among this group, the rate itensity is high.
61
The second group are the communities in the South-Eastern part of the area. They
include Amasaa, Usaka, Amachara among others. Here the itensity is moderate. The third
group comprises of the communities in the North Central. This group also includes those
communities in the South-Western part. In this group, there is a low itensity of the
practice of intercroping. Some of the communities in this group are Umuezegu, Osusu
and Amaekpu communities among others. This is shown in Fig 5 presents the spatial
spread of the practice. For mixed farming, there is a high intensity of the practice in the
communities in the North-Central part of the area. Hence, these communities had 37.8
percent of the respondents. Here the notable communities include Ntigha, Umuezegu and
Eziama. As you move down to the communities in the South-East, there is a moderate
intensity of practice of the land use type. This group of communities had 28.8 percent of
the respondents. The communities here includes Amasaa, Umuatu, Amachi among
others. The next group with about 21.6 percent are those communities in the NorthEastern part of the area. There is generally low intensity of practice of the land use type
in other part of the area. This is shown in Fig 7.
62
Fig 7: Isiala Ngwa North showing the spatial distribution of Intercropping in the area.
Source: Field work 2011
62
63
Fig 8: Isiala Ngwa North showing the spatial distribution of mixed farming in the area.
Source: Field work, 2011.
63
64
Concerning plantation agriculture, the plantations are mainly found at the
periphery of the area. In these areas, there is a high intensity of the practice. Some of the
communities here include Eziama Ntigha, Amapu Umuoha, Umuezeukwu, Amaasaa,
Amachara, etc. There is a low intensity of the practice within the Central part of the study
area. This spatial dimension is presented in Fig 9.
Bush fallowing is practiced by two main categories of communities. The first
category are those in the North-East and North-West. The rest of the area fall under the
second category of communities. The communities in the first group have high intensity
of this practice. Examples include Umuogele (NW), and Umuogu (NE), among others.
There is a low intensity of the practice in the second category of communities. They
include Ntigha and Umuala, etc. This is shown in Fig 10.
As for animal husbandry, the practice is evenly distributed in the area. In other
words there is no place mostly associated with it. There is generally a low intensity of the
practices among the communities. Hence a few individuals undertake animal husbandry.
The spatial distribution of animal husbandry is shown in Fig 11.
65
Fig 9: Isiala Ngwa North showing the spatial distribution of plantation
agriculture in the area:
Source: Fieldwork 2011
65
66
Fig 10: Isiala Ngwa North showing the spatial distribution of bush fallowing in the area:
Source: Fireldwork, 2011
66
67
Fig 11: Isiala Ngwa North showing the spatial distribution of animal husbandry in the area.
Source: Field work 2011
67
68
Fig 12: Isiala Ngwa North showing the spatial distribution of the five agricultural land use practices in the area.
Source: Fieldwork, 2011.
68
69
Fig 12 shows the different agricultural land use practices found in the various
communities of the study area. It also shows the intensity of the agricultural land use
practices.
3.3
Factors that determine the choice and location of Agricultural land use types
in the study area
The spatial distribution of the agricultural land use practices in the area is a
function of some factors. Those factors include land availability, type of crops to be
planted, type of soil, land ownership, soil fertility, price affordability for land
procurement, access to good roads for evacuation of products, topography, loss of farm
produce to thieves, slope angle and size of land.
3.3.1
Land availability:
In the study area, land availability is one of the factors that determine the people’s
choice of agricultural land use types. If one does not have land, he may not embark on
any agricultural land use practice. However, those without enough land do lease from
others. Sixty-seven (67) out of the four hundred (400) respondents agreed that land
availability is a major factor in the choice of agricultural land use types. In other words,
only 16.85 of the respondents regard land availability as a factor of choice of land use
type. Hence, the remaining 83.2 percent have land and so do not see it as a strong factor
in this regard.
3.3.2
Type of crops to be planted:
This factor attracted sixty-nine (69) respondents. This number takes care of 17.3 per
cent of the respondents. It means that only 17.3 per cent of the four hundred respondents
regard type of crops to be planted as a factor in the choice of land use type. This agrees
70
with our findings during the Key Informant Interviews (KIIs) session. One of the key
informants stressed that he considers the type of crop he intends to plant in relation to
both land use type and site. According to him, if a crop like yam is planted on an
unsuitable land, it would not yield much. For this reason, the farmers’ tend to consider
their intended crop in their choice of agricultural land use types
3.3.3
Type of soil:
The type of soil is another factor that determines the choice and location of
farming systems to be adopted. If the farmer does not consider the type of soil in his
choice of agricultural land use type, he may end up wasting his efforts, crops and other
imput. Bearing this in mind, it becomes necessary that the farmer chooses the type of soil
that would suit his crops, so as to ensure a good harvest. However, twenty-three (23)
respondents from seventeen communities agreed to this fact. Therefore 13.5%. regard soil
type as a factor that affects the choice of agricultural land use types in Isiala Ngwa North.
3.3.4
Land ownership:
This is also another factor in the farmers’ choice of agricultural land use types. In
the study area, some communities are blessed with more land than others. Those farmers
with lesser portions of land and may not have other people’s land on pledge resort to
leasing land from others. This type of land ownership does not favour biodiversity. Also,
communities that operate communal land ownership share their land among taxable
adults. For such communities, it is only those portions that have been left fallow that they
share among those taxable adults. However, twenty-one (21) respondents consider land
ownership a factor in the choice of agricultural land use type. This is equivalent to 5.8 per
71
cent of the respondents. This means that it is not a popular opinion as the proponents are
not many.
3.3.5
Soil fertility:
From the result of the research, it is evident that soil fertility remains a factor that
influences people’s choice of land use types. It is generally known that no farmer chooses
to cultivate an unfertile soil. So the farmers tend to consider soil fertility when choosing
their proposed farmland and land use types. Our questionnaire survey shows that sixtytwo (62) respondents agreed to this. In other words, this is the opinion of 15.5% of the
total number of respondents.
3.3.6
Price affordability for farmland:
The study shows that twenty-three (23) respondents agreed that price affordability
is one of the factors that influence the choice of farming systems. This number of
respondents make up about 5.8% of the respondents. This percentage of the respondents
believe that the price for leasing of land must be affordable for people to acquire land for
farming. From our field survey, some people indicated that the price of land in some parts
of the study area is not pocket-friendly. This affects their choice as they tend to look for
where they can afford.
3.3.7
Access to good roads for evacuation of produce:
Only six (6) respondents from the population sampled ticked the factor above as a
determinant of the farmers’ choice of agricultural land use type. This number represents
about 1.5 per cent of the respondents. This implies that a majority of the people do not
consider it as such. The reason for this is that they believe they would always find a way
of evacuating their farm produce. To buttress this point, one of the key informants in
72
Ntigha community, said that since the area is mainly known for subsistence agriculture,
presence or lack of good roads is not so much considered in the choice of farming
system. It is only in the areas where mechanized farming operates, that good roads are
considered a determining factor.
3.4
Analysis of the Relative Strength of the Factors of Land Use Types in Isiala
Ngwa North L.G.A.
In order to further analyze the relative strength of the factors of land use types in
Isiala Ngwa north L.G.A., the Principal Component Analysis (PCA).
Table 5 shows the component matrix.
Table 5: Rotated component matrix of the factors that determine the farmers’ choice of
agricultural land use types in the study areas.
Component
Variables
1
2
3
4
5
6
7
X1
Land availability
.666*
-.217
.114
-.021
-.081
-.081
-.081
X2
.142
-.027
-.054
-.891*
-.082
-.082
-.082
X3
Types of crops to
be planted
Type of soil
-.653*
-.092
.000
.284
-.276
-.276
-.276
X4
Land ownership
-.026
.746*
.051
.047
-.044
-.044
-.044
X5
Soil fertility
.634*
.274
-.037
-.046
-.129
-.129
-.129
X6
Price affordability
for land
Access to good
roads
Topography
-420
-.109
-.665*
.356
-.065
-.065
-.065
.239
-.038
.789*
.242
-.039
-.039
-.39
-.075
-.030
-.001
.075
-.047
.959*
-.047
.044
.792*
-.030
-.039
.024
-.024
.024
-.075
-.030
-.001
.075
.959*
-.047
-.047
X7
X8
X9
X10
Loss of farm
produce
Slope angle
73
X11
Size of land
-.075
-.030
-.001
.075
-.047
-.047
.959*
Eigen value
1.574
1.332
1.086
1.084
1.039
1.039
1.039
% of variance
14.309
12.112
9.870
9.851
9.446
9.446
9.446
Cumulative %
14.309
26.421
36.292
46.143
55.589
65.036
74.482
* Significant Loadings ≥ +/– 0.60
The result of the P.C.A. above shows that seven components were extracted from
the eleven variables. Component I has significant loadings on three variables ie X1 (.666)
meaning that land availability is a strong factor in the farmers’ choice of agricultural land
use types. Therefore, if there is no available land, it would be difficult for any farmer to
practice any agricultural land use type. The second variable is X3 (-.653), implying that
the farmers consider the soil type in terms of suitability for intended crops. Hence no
farmer wants to invest his resources on a poor soil, knowing that there would be minimal
output eventually. In other words, type of soil is an important factor in the farmers’
choice of agricultural land use types. The last variable in this component is X5 (.634),
meaning that soil fertility plays an important role in the farmers’ choice of land use types.
It implies that no farmer would willingly choose an infertile soil during farming. If not,
the crops, man hours and other resources invested there would be a waste. The underlying
component here becomes the nature of available soil. The component has an eigen value
of 1.574 and explains 14.309% of the total variance. Component 11 has significant
loadings on two variables, has an eigen value of 1.332 and contributes 12.112% of the
total variance. The variables with significant loadings are X4 (.746), which means that
land ownership is an important factor in the farmers’ choice of agricultural land use type.
Hence, the farmer has to own a piece of land through any of the land ownership systems,
74
before he can do farm work. The second variable is X9 (.792). This means that the farmer
considers the safety of his farm in choosing his farm site. It therefore means that the
farmer would not want to lose his farm output, and so must make his choice bearing that
in mind. The underlying dimension here is farmland security.
Component III is significantly loaded on two variables, they are X6 (-.665) and X7
(.789). The loading on variable X6 implies that price for land can be a limiting factor in
the choice of land use type. This is because a farmer may not acquire land for farming if
he cannot afford it. For variable X7 it means that the farmers consider the nature of the
roads leading to their proposed farm lands. If the roads are not easily passable, they tend
to make alternative choice of land use type where they can easily evacuate their farm
produce during harvest. The underlying factor here becomes accessibility. The eigen
value is 1.086 and it accounts for 9.87% of the total variance.
Component IV has significant loading on one variable ie X2 (-.891). the
implication is that the types of crops to be planted are considered by the farmer when
choosing his agricultural land use type. Every crop has a suitable farm land considering
its nutrient requirements. If the farmer does not have this in mind, he may end up wasting
his resources. But if he considers this, he would have a desired yield, all other conditions
being equal. The underlying component here is impact of suitable conditions for crop
yield. The component has an eigen value of 1.084 and explains 9.44% of the total
variance.
Component V has significant loadings on one variable X10 (.959). This means that
the slope angle of the intended farm land should be critically examined while making his
choice. If such slope angle cannot be managed, he should avoid the site. Otherwise, he
75
may risk loosing his crops to erosion. This is more so if the area is prone to flooding. The
underlying factor is suitability of farmland. It has an eigen value of 1.039 and explains
9.446% of the total variance.
Component VI has significant loadings on one variable The variable is X8
(.959).It means that the farmer considers the terrain of the intended farmland. Hence, if it
is susceptible to soil erosion, he would be guided in his choice of land use type and its
location. The underlying factor is favourable farmland. The component has an eigen
value of 1.039 and accounts for 9.446% of the total variance.
Component VII has significant loading only on variable X11 (.959). This means
that the size of farmland is considered a factor that determines the farmers’ choice of land
use type. If the farmer wishes to engage in plantation agriculture for instance, he
considers size of land. The reason is that plantation agriculture requires a large expanse
of land. The underlying component is crop requirement. The component has an eigen
value of 1.039 and explains 9.446% of the total variance.
76
CHAPTER FOUR
AGRICULTURAL LAND USE PRACTICES AND THEIR IMPACT ON
BIODIVERSITY IN THE STUDY AREA
4.1
The relationship between various agricultural land use practices and
biodiversity in the study area:
The agricultural land use practices in the study area as identified in chapter three
have their various relationship with biodiversity. In other words, the relationship of bush
fallowing with biodiversity may vary from that of intercropping or the other agricultural
land use practices that operate in Isiala Ngwa North. `The dominant agricultural land use
practices in the study area are intercropping, mixed farming, plantation agriculture, bush
fallowing and animal husbandry.Their relationship with biodiversity in Isiala Ngwa
North is discussed in what follows;
a.
Intercropping:
This is the process of growing crops to be harvested as food, livestock fodder, and
fuel or for any other economic purpose. In the study area, this farming system seems to
impact biodiversity in terms of species abundance. This is due to the clearing of the bush
for the crop farm. As the crop farm is cleared, it reduces the abundance of plant and
animal species since every species growing there including both plants and animals are
removed to make way for the desired crop to be planted. The crops so planted cover
everywhere, giving no room for species diversity. Even when the crops are planted they
are weeded from time to time, while inorganic fertilizer is applied on the crops. This in
turn leads to disruption of the normal ecosystem as well as environmental degradation
with subsequent application of inorganic fertilizer. Hence, Pagiola et al (1998), observed
that inorganic fertilizer use in agriculture changes the energy and nutrient cycling and
77
storage that lead to the disruption of normal ecosystem functioning. Similarly, Ingham
(1998), observed that while adding inorganic fertilizer in the soil may improve plant
growth in the short term, it may lead to environmental degradation over longer time
frames. In the course of preparing the land for crop planting, the soil is tilled, and this
also leads to loss of carbon. In line with this Bayer et al (2006 & 2009), said that soil
tillage can promote soil carbon loss by many processes, such as disintegration of soil
aggregates which usually protect soil organic matter from decomposition. We know that
plant species need soil organic matter for their growth.
b.
Mixed farming:
Mixed farming is the use of a single farm for multiple purposes such as the
growing of cash crops or annual crops and raising of livestock. This agricultural land use
type from observation also appears to impact biodiversity both positively and negatively.
In the study area, you can find mixed farming that involves crop planting and raising of
livestock. The farmer uses the animal droppings to improve the soil for the raising of
crops. However, it is likely to affect biodiversity since the animals also eat up the young
vegetal cover in such areas as the plant species regenerate. In areas where mixed farming
involves growing of cash crops and annual crops, we found out that some of these
plantations (cash crops) mainly oil palm have grown to the extent of giving no room for a
good harvest from the annual crops inter cropped with the cash crops. This could be
attributable to the over shadowing nature of the cash crops, which makes it difficult for
other plants in the area to experience the direct rays of the sun and we know that
photosynthesis is aided by the sun. However, Mclaughlin (2000) and Mineaub (2000)
supported this view in their study in which they indicated that agricultural activities such
78
as tillage, inter-cropping and grazing have signiicnat implication for wild species of flora
and fauna as species capable of adapting to the agricultural landscape may be limited
directly by the disturbance regimes of grazing, planting and harvesting.
c.
Plantation agriculture:
Plantation agriculture is an agricultural system, generally a monoculture, for the
production of tropical and sub-tropical crops. In the study area, plantation agriculture is
largely dominated by oil palms (Elaeis guineensis). Some of them are at the growing
stage while others have attained maturity stage. Those at the growing stage still
accommodate inter-cropping while those at the climax stage of maturity no longer give
room for other annual crops as the soil no longer supports their growth.
As these plantations are maintained, the farmer clears other plant species while
sparing the desired crops. This may lead to species depletion. The process is such that
when these unwanted plant species are cleared, they also go with the animal species that
usually lived there. To this end, Mclaughlin and Mineaub. (1995) noted in their study,
that farming practices must prevent to a larger degree impacts which cause a
simplification of floristic diversity, fragmentation of habitats and decrease in soil quality
etc. They concluded that high fertilization doses, short rotations or monoculture
combined with chemical plant protection measures cause depletion of species richness
and species diversity.
Similarly, Gyasi (1996) stated that the introduction of the exotic plantation system
in the 18th century, has transformed vast areas of diversified humid forest ecosystems,
most especially in cote d’lvoire, Liberia, Nigeria and Ghana, into mono-cultural ones
focused on the oil palm (Elaeis guineensis), rubber (Havea brasiliensis), and cocoa
79
(Theobroma cacao). He added that the resilient, diversified indigenous agriculture,
modeled on the forest ecosystem and based on eco-farming principles borne out of
peasants’ intimate knowledge of the natural environment, is being replaced by the riskprone monocultural system, with devastating consequences for the forest ecosystem.
d.
Bush fallowing:
Bush fallowing is a type of subsistence agriculture where land is cultivated for a
period of time and then left uncultivated for several years so that its fertility will be
restored. This practice in the study area is mainly characterized by short fallow periods of
two to three years.
In the study area, the fallow periods which used to range from five to twelve years,
have decreased to two or three years. This is due to land scarcity as a result of population
growth. This short fallow period could be traced to forest disappearance, together with
some animal species. It may also lead to yearly application of inorganic fertilizers on the
crops. All these generally may have ways of disrupting normal ecosystem functioning,
habitat fragmentation, decrease in soil quality and above all, depletion of species richness
and species diversity. However, from observation, there may be a low impact of bush
fallowing in areas like Amapu Umuoha and Agburuke, where fallow periods is about
three years. Sometimes as the bush is cleared for farming, the dried grasses are burnt.
Some people often set the bush ablaze without clearing it. This is followed by tilling of
the soil. This soil tillage according to Lal (2000), could stimulate the process of soil
erosion resulting in further loss of soil carbon. Concerning short fallow periods and bush
burning, Adinna (2001) stated that common practice in the African rotational bush fallow
system of subsistence economy is slash and burn and burning without providing adequate
80
fire guards. He observed that such leads to unwanted bush burning, forest destruction and
loss of biodiversity.
e.
Animal Husbandry:
Animal husbandry is the agricultural practice of breeding and raising livestock. In the
study area, some farmers engage in animal husbandry. The livestock involved are mainly
ruminants like goats, sheep, cattle and cows. Some of these animals are kept at home
while others are left to roam about. Either ways, the practice seems to affect biodiversity
adversely. Those that are kept in the house are fed with fodder gathered by the farmer
from the bush-a practice that causes biodiversity destruction. Those that are semi-free
ranged also cause harm to biodiversity. This is because both gathering of folder and
grazing activities take place in the bush at the expense of biodiversity. When they are also
left to roam about for sometimes, the animals go about eating up people’s crops on their
farmlands or even enter the nearby bush to feed on plant species. So, from any angle it is
considered, biodiversity is at the receiving end in this practice. In the case of the cows,
they are seen to roam about, although accompanied by their rearers. However, as they
move about, they eat up the plant species along their pathways and also trample others
underfoot thereby destroying them. But the cattle are stationed at specific points, while
the farmer relocates them later when they would have eaten up everything around their
radii. For instance in some parts of Amapu Umuoha and Uratta Umuoha `communities,
such areas that are regularly under grazing have gone bare and as such, there are traces of
soil erosion therein. This is supported by Bassett and Boutrais (1996) when they
remarked that nomadic herding impacts negatively on the biota by extensive grazing and
81
the use of fire to suppress undesirable plant species. They also observed that such
practice degrades soils by regular trampling by animals on the move.
The relationship between agricultural land use practices and biodiversity is shown
from the value of the biodiversity indices as obtained from the quadrats of the various
agricultural land use types. Hence, the lower the index, the more adverse the effect of the
agricultural land use practice on biodiversity and vice versa. The data for this expression
is presented in table 14.
4.2 Determination of the diversity and biodiversity indices from the land use types
in the study area
From the study, the diversity indices (DI) of the plant and animal species, as well
as the biodiversity indices were generated from the inventory taken from the study area.
Shannon-Wiener’s diversity index was adopted in generating the diversity indices for
plant species and animal species as reported under data collection. After obtaining the
diversity indices for both plant and animal species, a combination of the diversity
inventory (actual number) for the plant and animal species was done.This was used to get
the biodiversity indices as equally reported in chapter 1. `The diversity indices of the
plant species are shown in Table 6 below:
82
Table 6: The Diversity Indices of the plant species in the study area
Land use practices
S/N Communities
1.
Umuogele
Intercropping Mixed
Plantation Bush
Animal
Mean
farming agriculture fallowing Husbandry
2.27
3.82
2.23
2.70
2.72
2.75
2.
Amapu Ntigha
2.27
2.77
3.16
2.57
2.44
2.73
3.
Eziama Ntigha
3.03
2.86
3.28
2.46
3.72
3.07
4.
Ngwaukwu
2.24
2.23
2.95
2.74
2.61
2.55
5.
Eziama
2.77
2.83
2.90
2.90
1.74
2.63
6.
Abayi
3.09
3.37
2.92
2.70
3.17
3.25
7.
Ihie
3.01
3.06
2.68
3.14
2.97
2.97
8.
Ahiabaubi
2.91
3.04
2.32
3.02
2.90
2.94
9.
Ahiabaokpuala
2.95
2.85
2.90
2.84
2.84
2.88
10.
Umurandu
2.38
2.63
3.02
2.90
2.70
2.67
11.
3.08
4.91
3.02
3.35
3.36
12.
Amapu
2.64
Umuoha
Uratta Umuoha 2.85
3.50
2.53
4.91
2.84
3.55
13.
Amaorji
2.89
2.62
2.62
2.78
2.74
2.73
14.
Obikabia
2.78
2.50
2.34
2.53
2.98
2.63
15.
Osusu
2.98
2.93
3.05
2.92
2.83
2.94
16.
Eziala
2.44
1.10
2.92
3.11
2.67
2.45
17.
Ntigha
2.42
2.73
2.69
2.53
2.57
2.59
18.
Nsulu
2.88
2.69
2.50
2.55
2.80
2.68
19.
Agburuke
3.16
3.06
2.19
2.65
3.24
3.00
20.
Umuomainkwu 2.56
3.14
3.08
3.11
2.81
2.94
83
21.
Umuezegu
3.01
3.19
2.79
1.98
3.16
2.83
22.
Umuodeche
2.77
2.68
2.65
2.30
2.68
2.62
23.
Umuogu
2.49
2.93
2.67
2.94
2.58
2.72
24.
Umuezeukwu
2.55
2.78
2.23
3.22
0.24
2.82
25.
Ikputu
2.34
2.59
2.63
2.78
2.61
2.59
26.
Umuode
2.68
2.80
2.80
2.66
2.68
2.72
27.
Umuosu
2.49
2.86
2.44
2.74
2.86
2.68
28.
Mbubo
2.92
2.62
2.84
2.47
3.55
2.68
29.
Ubaha
2.43
2.85
2.68
2.12
2.74
2.56
30.
Ohuhu Nsulu
2.78
2.78
2.71
2.84
2.65
2.75
31.
Amachara
3.03
2.75
2.89
2.98
2.78
2.89
32.
Umuatu-Nsulu
2.85
2.49
2.78
2.75
2.77
2.73
33.
Amasaa
2.99
2.66
2.73
2.76
2.94
2.82
34.
Umuala
2.92
3.73
2.59
2.95
2.67
2.97
35.
Umuakwu
2.77
2.55
2.90
2.89
2.79
2.78
36.
Amaekpu
2.70
2.86
2.70
2.19
2.69
2.63
37.
Amachi
2.56
2.46
2.50
2.77
2.69
2.60
38.
Usaka
2.86
2.17
2.79
2.92
2.93
2.84
39.
Umuosonyike
2.83
3.42
2.82
2.90
2.87
2.97
40.
Umuomainta
2.60
2.88
2.94
2.93
2.92
2.85
Mean
2.74
2.84
2.80
2.69
2.81
Soruce: Field work, 2011
84
From the result, it is evident that in Umuogele community, the highest diversity index
(DI) of 2.23 was obtained from a quadrat sited on a plantation farm (Oil palm plantation).
It is pertinent to mention here that the higher the value, the more diverse the plant species
are in a plot. Generally, the DI across the communities range from 0.24 in Umuezeukwu
community (animal husbandry) to 4.91 in Uratta Umuoha (plantation agriculture plot)
community.
It is note worthy to state here that the results show that how these agricultural
land use practices are managed, affects the diversity indices of the plant species there in.
In other words, the intensity of practice of the agrucltural land use types vary from
community to community. Hence, the agricultural land use type that produces the highest
DI in one community may also have the least else where. For instance, in Eziama Ntigha,
animal husbandry had the highest DI (3.72) whereas in Umuezeukwu, the same land use
type had the lowest DI of 0.24.
However, the impact of agricultural land use practices on plant species was
ranked, while the communities were grouped according to their diversity ranking. The
diversity indices were ranked Very High, High, Moderate and Low. This was done for
each of the five land use types as shown in Appendix 6. For example, Under Mixed
farming, the communities with Very High diversity ranking include Umuogele, Abayi,
Amapu Umuoha, Uratta Umuoha, Agburuke, Umuezegu, Amachara, Umuala, and
Umuosonyeike. The rest fall under High DI ranking. For bush fallowing, Ihie, Ahiabaubi,
Uratta Umuoha, Eziala, and Umuezeukwu ranked Very High. The rest except Umuezegu
ranked High. Umuezegu had Moderate ranking. In the case of plantation agriculture, the
communities ranked High and Very High. This means that the practice favours plant
diversity in the area. For animal husbandry, six communities ranked Very High. They are
Eziama Ntigha, Abayi, Amapu Umuoha, Agburuke, Umuezegu and Umuezeukwu. The
85
remaining communities fall under High DI ranking, apart from Eziama which falls under
Moderate DI ranking (Appendix 6).
P.C.A. of the impact of agricultural land use practices on plant species
The diversity indices generated above, were analyzed using Principal Component
Analysis (P.C.A). The various degrees of DI among the communities is as a result of
the intensity of practice across the study area. For this reason, the analysis was done
in order to ascertain the underlying factors of the observed variation in DI among the
Agricultural land use practices in Isiala Ngwa North. The correlation matrix is shown in
Table 7.
Table 7: Correlation Matrix of the Impact of Agricultural Land Use Practices on
Plant Species Diversity in the Study Area
Crop farming
Mixed
Plantation Bush
Animal
farming
agriculture fallowing husbandry
Intercroping
1.000
Mixed farming
.237
1.000
Plantation agriculture
-.050
-.058
1.000
Bush fallowing
.007
-.044
.005
1.000
Animal husbandry
.394
.176
.167
-.043
1.000
Table 7 shows a low relationship between the agricultural land use types, and
plant species diversity in the area. For example, Mixed farming (0.237) and Animal
husbandry (0.394). The others showed no relationship with plant species diversity. For
this reason, the correlation matrix could not explain the factors behind the variation.
Hence we used PCA to isolate the underlying factors as shown in Table 8.
86
Table 8: Rotated Component Matrix of the impact of agricultural land use
practices on plant species diversity in the study area
Component
Variables
I
II
III
XI
Crop farming
.805*
-.020
. 088
X2
Mixed farming
.619*
-. 276
-. 123
X3
Plantation agriculture
-.049
.916*
-.010
X4
Bush fallowing
-.015
-.009
.991*
X5
Animal husbandry
.713*
.430
-.034
Eigen value
1.541
1.101
1.007
% of variance
30.818
22.014
20.137
Cumulative %
30.818
52.832
72.969
* Significant loadings ≥ + /-0.60
From the PCA results in Table 8, three orthogonal components were extracted to
explain a total variance of 72.969%. Component 1 has significant loadings on three
variables. The variables are X1, X2 and X5. For X1 (crop farming), it implies that increase
in crop farming, increases the rate of loss of plant species. The reason is that other plant
species are cleared during farming thereby making room for only the desired crops. The
loading on X2 (mixed farming), means that as long as there is increase in the frequency of
mixed farming, more plant species will regenerate as the animal droppings aid plant
growth through improved soil fertility. Variable X5 (animal husbandry), indicates that as
grazing increases, there is also an increase in the rate at which plant species are lost. In
mixed farming therefore, it follows that as the animals are either tied to stick to graze or
allowed to move freely, their droppings aid plant growth, while the grazing pressure
impacts negatively on the plant species in the area. Variables X1, X2, and X5 together
87
explain 30.8 per cent of the total variance. The underlying factor here becomes general
suppression of plant species diversity. This component has an eigeavalue of 1.541 and
accounts for 30.818 of the total variance.
Component II has an eigenvalue of 1.101 and accounts for 22.014% of the total
variance. It has a significant loading on only one variable. The variable is X3 (plantation
agriculture), implying that the higher the rate of this practise, the lower the regeneration
rate of plant species. It means that for oil palm plantation, for instance as they grow,
other plant species are completely removed in favour of Oil palm trees, thereby reducing
the rate at which plant species regenerate. Variable X3 accounts for 22.014 per cent of
the total variance. Hence, the underlying dimension is the limitation of diversity of plant
species.
Component III has a significant loading on only one variable, X4 (bush
fallowing), meaning that the higher the fallow lengths, the more the plant species
flourish. If the fallow periods are increased, it will enable more plant species to
regenerate thereby enhancing species diversity and richness. The variable has an eigen
value of 1.007 and accounts for 20.137% of the total variance. The underlying dimension
therefore, is the opportunity for re-growth. Table 9 shows relative contributions of the
impact of agricultural land use practices on plant species diversity.
88
Table 9: Relative Contributions of the impact of agricultural land use practices on
plant species in the study area.
Component Underlying dimension
Relative
Cumulative
contribution
contribution
(%)
( %)
I
General suppression of plant species diversity
30.818
30.818
II
Limitation of diversity of plant species
22.014
52.832
III
Opportunity for re-growth
20.137
72.969
It could be inferred from the results that “general suppression of plant species”
has the greatest impact on plant species diversity in Isiala Ngwa North L.G.A, as it
accounts for 30.818% of the total variance. This is followed by “limitation of diversity of
plant species” which accounts for 22.014% of the total variance (72.969%). Relatively,
bush fallowing accounts for the least impact on plant species, as it accounts for 20.137%
of the total variance. This implies that bush fallowing with long fallow periods favour
plant species, thereby reducing the negative impact on biodiversity.
4.3 The diversity indices of the animal species in the study area.
The diversity indices of the animal species are presented in Table 10.
89
Table 10: The Diversity Indiceis of the Animal Speices in Isiala Ngwa North L.G.A.
Land use practices
S/N Communities
1.
Umuogele
Intercropping Mixed
Plantation Bush
Animal
Mean
farming farming
fallowing Husbandry
1.52
2.38
1.97
1.76
1.17
1.87
2.
Amapu Ntigha
2.21
2.08
1.77
2.12
1.62
1.96
3.
Eziama Ntigha
1.61
1.80
1.82
1.81
158
1.92
4.
Ngwaukwu
2.23
1.73
2.05
1.85
2.44
2.06
5.
Eziama
2.30
1.87
2.13
2.23
1.18
1.94
6.
Abayi
1.68
1.87
2.19
1.21
2.31
1.85
7.
Ihie
2.01
1.78
2.28
1.50
1.86
1.89
8.
Ahiabaubi
2.03
1.75
1.95
2.09
1.81
1.93
9.
Ahiabaokpuala
1.62
1.53
1.91
2.05
1.84
1.79
10.
Umurandu
1.95
1.79
2.10
1.30
1.81
1.79
11.
1.47
2.13
1.16
1.81
1.72
12.
Amapu
2.02
Umuoha
Uratta Umuoha 2.14
1.51
1.08
1.91
1.85
1.70
13.
Amaorji
1.23
2.02
1.37
1.36
1.64
1.52
14.
Obikabia
1.67
1.46
1.34
2.08
1.83
1.68
15.
Osusu
1.91
1.78
1.26
1.77
1.70
1.68
16.
Eziala
1.91
1.62
1.45
1.99
1.52
1.70
17.
Ntigha
1.82
1.94
0.65
1.18
1.92
1.50
18.
Nsulu
1.77
1.47
1.79
1.97
1.20
1.64
19.
Agburuke
1.84
1.50
1.67
2.21
1.61
1.77
20.
Umuomainkwu 1.92
1.52
1.89
1.79
1.98
082
90
21.
Umuezegu
1.81
1.41
1.80
1.30
1.52
1.57
22.
Umuodeche
1.80
1.99
2.07
1.96
1.62
1.69
23.
Umuogu
1.66
1.66
1.34
1.87
1.04
1.51
24.
Umuezeukwu
1.77
1.23
1.19
1.56
0.24
1.20
25.
Ikputu
1.60
1.93
1.48
1.47
1.42
1.58
26.
Umuode
1.53
1.50
1.22
1.55
1.57
1.47
27.
Umuosu
1.75
1.58
1.37
1.62
1.56
1.58
28.
Mbubo
2.03
1.75
1.40
1.74
1.45
1.67
29.
Ubaha
1.76
1.48
1.95
1.71
1.52
1.68
30.
Ohuhu Nsulu
1.76
1.67
1.23
1.42
1.82
1.58
31.
Amachara
2.08
1.74
1.95
1.97
0.91
1.73
32.
Umuatu-Nsulu
1.67
1.60
1.36
1.39
1.36
1.48
33.
Amasaa
1.52
1.49
1.93
0.99
1.52
1.49
34.
Umuala
1.80
0.93
1.89
0.57
1.73
1.38
35.
Umuakwu
1.60
1.56
1.37
1.94
1.47
1.59
36.
Amaekpu
1.79
1.45
2.03
1.87
0.77
1.58
37.
Amachi
1.55
1.32
1.54
1.61
1.61
1.53
38.
Usaka
1.33
1.65
1.15
1.52
1.68
1.50
39.
Umuosonyike
1.78
3.42
1.37
1.43
1.71
1.61
40.
Umuomainta
1.24
1.40
1.15
1.47
1.12
1.28
Mean
1.78
1.65
1.65
1.66
1.60
Source: Field work, 2011
91
Results on Table 10 show how the DIs are spread across the communities in the
area. The overall lowest DI of 0.65 was obtained from plantation agriculture in Ntigha
community. On the other hand the highest (3.42) was derived from mixed farming in
Umuosonyike community. This could be as a result of the management system.
However, it is note worthy to state here that in almost all the communities in the
NE part of the study area, the lowest diversity indices were recorded from quadrats
located in sites used for grazing. The reason is obvious as during grazing, the vegetation
that harbours most of the animals is cleared by the grazing activities of the domestic
animals. This therefore leads to the displacement and exposure of the animals to threats,
thereby decreasing their diversity indices. It is also pertinent to mention that any quadrat
from which a low diversity index was obtained, will be deemed to have been adversely
affected by the agricultural land usse type taking place there.
From the DI ranking scale, it could be observed that in terms of crop farming, the animal
index ranked from moderate to high, with no community ranking either very high or low.
This is shown also in Appendix 6.
Concerning mixed farming, the DI ranking ranges from low to high, although it is
only Umuala community that ranks low. In other words, the practice generally has a
moderate impact on animal diversity as in the case of plantation agriculture. It is only
Ntigha that ranked low on the scale for bush fallowing. The diversity indices range from
moderate to high. In the case of low diversity index ranking, there are only two
communities-viz Amasaa and Umuala. This generally implies that there is a moderate
impact on diversity.
92
Finally, under animal husbandry, the diversity indices range from low to high as can be
seen in Appendix 6. However, three communities ranked high. They are Eziama Ntigha,
Ngwaukwu, and Abayi, while three others ranked low viz-Umuezeukwu, Amachara and
Amaekpu. The rest ranked moderate.
P.C.A of the impact of agricultural land use practices on animal species
The correlation between agricultural land use practices and animal speices diversity
indices was established. The result is shown in Table 11.
Table 11: Correlation Matrix of the Impact of Agricultural Land Use Practices On
the Animal Species Diversity in the Study Area
Variables
Intercropping Mixed
Plantation Bush
Animal
farming
agriculture fallowing husbandry
Intercropping
1.000
Mixed
.089
1.000
.361
.107
1.000
Bush fallow
.330
.257
0.760
1.000
Animal
.082
.278
.189
-.123
farming
Plantation
agriculture
1.000
husbandry
Source: Field work, 2011
From Table 11, it could be seen that there is a weak relationship between the agricultural
land use types and animal species diversity. For instance, plantation agriculture (0.361)
and bush fallowing (0.330) have weak positive correlation with animal species diversity.
The rest have poor correlation. For this reason, P.C.A was used to determine the
underlying factors as shown in Table 12.
93
Table 12: The Rotated Component Matrix of the impact of agricultural land use
practices on the animal species diversity in the study area.
Variables
I
II
III
XI
Intercropping
.719*
-.305
-.340
X2
Mixed farming
.557
.285
.662*
X3
Plantation Agriculture
.633*
.135
-.562
X4
Bush fallowing
.555
-.601*
.028
X5
Animal husbandry
.387
.799*
1.029
Eigen value
1.686
1.193
1.029
% of variance
33.712
23.851
20.586
Cumulative %
33.712
57.564
78.150
* significant loadings exceeding ≥ +/-0.60
The results of the rotated P.C.A above, shows that three components were
extracted from the variables which explain the total variance of 78.150 per cent.
Component I has significant loadings on two variables ie X1 (crop farming), meaning that
if crop farming practice goes on frequently, there will be loss of animal species. This loss
of animal species implies depletion of species diversity. Therefore, an increase in the rate
of crop farming, increases the chances of habitat loss to the detriment of the animal
species. Hence, species richness and species diversity will continue to decline.
The second variable is X3 (plantation agriculture), meaning that when plantation
agriculture increases, the animal species decrease in number. The reason is that when
there is loss of plant species, the animals living within the vegetal cover are exposed to
danger, thereby forcing them to move away in search of sanctuary. In this component,
94
variables X1 and X3 jointly explain 33.7% of the total variance. The underlying factor
here is habitat change for the animal species. The component has an eigeavalue of 1.686
and explains 30.81% of the total variance.
Component II has significant loadings on two variables, and contributes 23.851%
of the total variance and has an eigenvalue of 1.193. One of the variables with significant
loadings is X4 (bush fallowing). This indicates that when bush fallowing increases in
frequency with short fallow periods, the animal species decrease in number, thereby
impacting negatively on biodiversity. The second variable is X5 (animal husbandry). This
means that with a high rate of loss of plant species through grazing or collection of
fodder, animal species are affected. In other words, when the animals feed regularly in an
area, the animals therein are exposed to habitat loss and other hazards. This is true most
especially for those larger animals that can not hide under the grasses. Variable X4 and X5
together explain 23.851 percent of the total variance. Consequently, the underlying factor
is loss of habitat.
Component III has an eigenvalue of 1.029 and accounts for 20.586% of the total
variance. Only one variable has significant loading, namely X2 (mixed farming). This
means that increase in mixed farming, increases the tendency for the animal species not
to re-populate the area. Variable X2 in this component accounts for 20.586% percent of
the total variance. Hence, the underlying factor here becomes habitat relocation.
95
Table 13: Relative contributions of the impact of agricultural land use practices on
animal species.
Component
Underlying dimension
Relative
Cumulative contribution
Contribution in %
I
Habitat change for the animal species
33.712
33.712
II
Loss of habitat and species
23.815
57.564
III
Habitat relocation
20.586
78.150
It could be seen from table 11 above, that the greatest impact of agricultural land
use practices on animal species is contributed by “habitat change for the animal species”.
It accounts for 33.712% of the total variance. The next is loss of habitat and species ”,
which accounts for 23.815% and this is followed by habitat relocation which accounts
for 20.586% and it is relatively the least. This implies that the longer the fallow periods,
the more the animal species are attracted to the area in search of sanctuary.
4.4
The biodiversity indices of the species in the study area.
The result of the biodiversity indices is presented in Table14.
96
Table 14: Biodiversity Indices from Agricultural Land Use Types in Isiala Ngwa
North
Land use practices
S/N Communities
Intercropping Mixed
Plantation Bush
Animal
farming farming
fallowing Husbandry
1.
Umuogele
0.04
0.05
0.05
0.04
0.04
2.
Amapu Ntigha
0.05
0.08
0.10
0.07
0.02
3.
Eziama Ntigha
0.08
0.08
0.06
0.07
0.05
4.
Ngwaukwu
0.05
0.04
0.05
0.08
0.06
5.
Eziama
0.08
0.04
0.06
0.09
0.07
6.
Abayi
0.06
0.08
0.08
0.05
0.07
7.
Ihie
0.08
0.06
0.08
0.05
0.07
8.
Ahiabaubi
0.04
0.05
0.06
0.07
0.06
9.
Ahiabaokpuala
0.07
0.07
0.08
0.06
0.07
10.
Umurandu
0.44
0.03
0.05
0.04
0.04
11.
0.08
0.07
0.04
0.05
0.08
12.
Amapu
Umuoha
Uratta Umuoha
0.07
0.06
0.06
0.07
0.06
13.
Amaorji
0.08
0.12
0.08
0.06
0.06
14.
Obikabia
0.04
0.04
0.03
0.06
0.03
15.
Osusu
0.06
0.05
0.04
0.08
0.06
16.
Eziala
0.04
0.08
0.06
0.07
0.03
17.
Ntigha
0.05
0.04
0.09
0.04
0.03
18.
Nsulu
0.07
0.08
0.06
0.05
0.05
19.
Agburuke
0.06
0.06
0.08
0.06
0.06
97
20.
Umuomainkwu 0.05
0.05
0.11
0.09
0.03
21.
Umuezegu
0.06
0.06
0.08
0.05
0.06
22.
Umuodeche
0.10
0.04
0.04
0.04
0.04
23.
Umuogu
0.05
0.04
0.07
0.05
0.03
24.
Umuezeukwu
0.05
0.06
0.06
0.06
0.07
25.
Ikputu
0.07
0.05
0.07
0.04
0.07
26.
Umuode
0.06
0.06
0.07
0.04
0.05
27.
Umuosu
0.08
0.08
0.07
0.05
0.05
28.
Mbubo
0.10
0.05
0.09
0.04
0.05
29.
Ubaha
0.05
0.06
0.06
0.05
0.04
30.
Ohuhu Nsulu
0.08
0.07
0.04
0.06
0.04
31.
Amachara
0.09
0.04
0.10
0.05
0.04
32.
Umuatu-Nsulu
0.08
0.06
0.07
0.04
0.05
33.
Amasaa
0.11
0.05
0.07
0.06
0.06
34.
Umuala
0.18
0.07
0.09
0.06
0.08
35.
Umuakwu
0.14
0.05
0.11
0.08
0.05
36.
Amaekpu
0.09
0.06
0.06
0.04
0.03
37.
Amachi
0.11
0.06
0.11
0.06
0.05
38.
Usaka
0.07
0.05
0.07
0.06
0.06
39.
Umuosonyike
0.11
0.06
0.10
0.06
0.06
40.
Umuomainta
0.08
0.07
0.08
0.07
0.06
Source: Field work, 2011
98
The results on table 14 show generally, that the biodiversity indices of the species
in the study area, are very low. They however range from 0.02 to 0.44. In other words,
the highest biodiversity index of 0.44, was obtained from a quadrat sited in a crop farm in
Umurandu. Contrarily, the least biodiversity index of 0.02, was obtained from a quadrat
located in grazing land for animal husbandry in Amapu-Ntigha community. It would
appear that the management system of these agricultural land use practices affects the
biodiversity indices of species in the area. Hence, the lowest index of 0.02 was recorded
from animal husbandry in Amapu-Ntigha, while the highest, though not high enough was
0.44, which was obtained from a crop farm in Umurandu community. However, the
biodiversity indices obtained were also analyzed using Principal Component Analysis to
ascertain the factors responsible for this variation.
P.C.A. of the impact of agricultural land use practices on biodiversity.
We subjected the biodiversity indices to further analysis using P.C.A, to ascertain
the impact of agricultural land use practices on biodiversity in Isiala Ngwa North. Hence,
the correlation matrix of the analysis is shown in Table 15 as follows:
Table 15: Correlation Matrix of the Impact of Agricultural land use Practices on
Biodiversity in the Study Area
Variables
Intercropping Mixed
Plantation
Bush
Animal
Farming Agriculture Fallowing
Husbandry
Intercropping
1.000
Mixed farming
-.222
1.000
Plantation agriculture
.019
.134
1.000
Bush fallowing
-.191
.058
.136
1.000
Animal Husbandry
.034
.186
-.021
.138
1.000
99
The result on Table 15 shows that crop farming and mixed farming are not
friendly to biodiversity. Hence there is a very low relationship between the agruciutral
land use practices and biodiversity. Thus, the raw data was subjected to P.C.A to find out
the underlying factors in the observed variation. The P.C.A. is shown in Table 16.
Table 16: The Rotated Component Matrix of the Impact of Agricultural Land Use
Practices on Biodiversity in the Study Area
Component
Variables
I
II
III
XI
Intercropping
-.775*
.060
.227
X2
Mixed farming
.511
.156
.430
X3
Plantation agriculture
.208
.841*
.040
X4
Bush fallowing
.618*
-.053
-.174
X5
Animal husbandry
-.008
-.053
.923*
Eigenvalue
1.380
1.355
1.123
% of variance
22.996
22.577
18.723
Cumulative %
22.996
45.573
64.296
*significant loadings ≥ + /− 0.60
The results of the P.C.A in Table 16 show that out of the five variables, three
components were extracted explaining a total variance of 64.296%.
Component I has significant loadings on two variables (X1, and X4). The variables
are XI (crop farming (-.775), meaning that it impacts negatively on biodiversity. The
second variable is X4 (bush fallowing (.618) which implies that bush fallowing with long
100
fallow periods leads to the capability of plants to regenerate after being burnt or cleared
for farming. Variable X1 and X4 explain 22.996 of the total variance. The underlying
factor therefore becomes the impact of plant clearance on biodiversity. The eigen value is
1.380.
Component II has significant loading on only one variable. The variable is X3
(Plantation Agriculture), which means that increase in the rate of Plantation Agriculture,
increases the depletion of biodiversity and diminishes the chances of regeneration of the
vegetal cover. This also affects the entire elements of biodiversity. The eigen value is
1.355 and it accounts for 22.577% of the total variance. Thus, the underlying dimension
becomes effect of mono cropping on biodiversity.
Component III has significant loading on one variable, and contributes 18.723%.
The variable is X5 (Animal Husbandry). This indicates that with a high frequency of
plantation agriculture, there will be an increase in the destruction of biodiversity. As the
farmers allow animals to graze in the area, it will eventually lead to the death of plant
species. This in turn causes the exposure of the animal species living there to either death
or other hazards or both. When these animals are exposed to such threats, they either die
or migrate to other areas that may not be conducive for them. The underlying component
here becomes “effect of habitat disturbance on biodiversity”.
4.5
The Key Informant Interviews (KIIs) and Focus Group Discussion with
some Farmers in the Study Area
The summary of the focus group discussion together with the key informant
interviews is presented in Table 17
101
Table 17: The results of the Key Informant Interviews and Focus Group Discussions
with farmers in the Area
Questions Raised
Responses from Respondents
Researcher’s comments
Concerning the farming
Farming system is mainly peasant or
Short fallow periods do not
systems practiced
subsistence farming. The major practice
favour biodiversity
is bush fallowing, with fallow period 2 – conservation.
3 years
About farm tools used
Farm tools are hoes, knives, and spades.
Farming systems determine
and type of crops
The type of crops planted are cassava,
the tools used. Hence
planted
yam, garden eggs and vegetables, yield
simple farm tools used for
determined by soil fertility
subsistence farming.
What type of animals
They include ruminants e.g. goats,
Leaving the livestock to
are kept in the area
sheep, cows and cattle. Some livestock
roam about leads to
roam about on free range while others
biodiversity depletion
are on semi-free range – partially
housed and sometimes left or their own.
Concerning the effect of
They agreed that it has negative impacts
Most mammals that require
constant bush clearing
on wildlife and plant species in the area
forest areas for habitation
on biodiversity
are now absent. Hence this
practice causes loss of
habitat.
As to whether there are
There are informal protected areas. E.g.
More of these protected
protected areas in the
waste lands around shrines, along
areas are advocated
area
ancestral bush tracks.
Concerning sustainable
They suggested controlled burning i.e.
If organic farming is
agricultural production
gathering the grasses together and
practiced, biodiversity
and biodiversity
burning them. So, organic farming is
conservation is rest
conservation
advised.
assured.
In terms of the use of
It was obtainable in the past due to long
This does not aid
inorganic fertilizer
fallow periods. But population growth
biodiversity recuperation.
has resulted in land scarcity, leading to
102
short fallow periods.
About continuous
This is mostly done at the back of
Over time, this may lead to
cropping
people’s houses, school farms etc.
perpetual loss of soil
fertility
About hunting and bush
Some hunters set the bush ablaze so as
Bush burning is very
burning in relation to
to catch some animals. Some widows do
detrimental to the wildlife
biodiversity
same in order to clear their land for
and vegetation and should
farming as they have nobody to help
be discouraged.
them.
Source: Field work, 2011
Plate 6 shows the FGD section with some farmers in the area.
Plate7: FGD. With some farmers in Uratta Umuoha Community
4.6
Hunting and Biodiversity in the Area.
In the course of the FGDs, the discussants open-heartedly participated in the
discussion, bringing their many years of hunting experience to bear. According to their
103
responses, hunting in Isiala Ngwa started right from their ancestral period. In the present
times, some have hunted for about twenty-five (25) years. Hunting takes place on agreed
dates/days. It takes place once or twice a week, especially on Wednesdays and Saturdays.
The significance of long period of hunting is the reduction in the population of the animal
species. Hunting does not take place on Eke market days as a tradition. Even when
attempted, there would be no catch. This hunting frequency implies that the animals are
killed every week, this means that in time to come, there would be nothing to hunt for in
the area. Hence, this would result in depletion of biodiversity. The animal species hunted
in the area include hyenas, guinea fowls, African giant rats, cane rats, Maxwell’s Duikas,
etc. There are no animals forbidden by custom from hunting. This implies that the area is
free for hunting. Their kill rate per hunting expedition ranges form twenty-five to fifty
animal species. Hunting involves both the young and the old as they shoot the animals at
sight. The implication is that some species may totally disappear with time, leaving
nothing for future generations. Also, it means that with the killing of the old and young,
there is no room for re-population in the area. They adopt different hunting methods. For
instance one could see an animal asleep or in defenseless mood and kills it with a knife.
Traps, guns and snares are also used.
Their hunting grounds include Ntigha, Uratta-Umuoha, Ihie, Amapu-Umuoha,
Amaekpu all of which are in the study area. Animals mostly killed in farm lands include
cane rates, porcupines, Maxwell’s Duikas, etc. These are killed more than other species.
This is a sign that these species are the most common and will soon disappear from the
bush. Animal species caught in the past, which are no longer seen presently include
crocodiles, lions, wild pigs, pythons, etc. It means that they have gone into extinction,
104
and as such, there is nothing kept for posterity. They have ways of identifying the
presence of certain animal species in the bush. For instance, the eating habit of the cane
rats differs from that of African giant rats. They also have different foot prints along their
pathways. They unanimously said that bush burning is prohibited while defaulters are
liable to fines.They have ready market for their catch, no matter how many. Their
customers are hoteliers, bush bars and even some of the hunters themselves. The
monetary value encourages regular hunting and eventual loss of species diversity in the
area.
Plate 7: Focus group discussion session with some hunters in Ntigha
Community
4.7
Farmers’ Perception of Biodiversity in the Study Area
105
Fig 13a: Controlled burning stimulates the
growth of biodiversity
Fig 13c: Farming practices have been modified
in favour of biodiversity
Fig 13e: Major threat to biodiversity is habitat
transformation
Fig 13b: Mixed farming conserves biodiversity.
Fig 13d: Most forests have been cleared for
agriculture
Fig 13f: Degradation & overexploitation of
vegetation reduce species diversity
106
Fig 13g: Intensive farming leads to death/out
migration of birds.
Fig 13h: Agriculture fragments habitats
leading to biodiversity loss.
Fig 13i: To conserve biodiversity, there should be
protected areas.
Fig 13j: Inorganic fertilizer use changes the
energy and nutrient cycle.
Fig 13k:
Inorganic fertilizer use disrupts normal
ecosystem functioning
Fig 13l: Impact of inorganic fertilizer use on
biodiversity should be investigated
.
107
107
Fig 13m: Inorganic fertilizer usage causes loss of
biodiversity.
Fig 13o: Continuous cropping impacts
biodiversity negatively
Fig 13n: chemical plant control
Fig 13p: Organic farming increases biodiversity
Fig 13q: Absence of corridors alters the movement and interaction of wildlife.
108
The pie charts in Fig 13 show the farmers’ perception of biodiversity in the area.
Most of them (58%) agreed that controlled burning favours biodiversity. Some strongly
(38%) agreed that mixed farming conserves biodiversity. While 36% strongly agreed that
some farming systems have been modified in favour of biodiversity, others have no
opinion on that. This shows their level of biodiversity awareness. Generally, they have
varying opinions on the impact of agricultural land use practices on biodiversity. This
calls for a massive community biodiversity awareness campaign in the study area.
109
4.8
Soil Chratercitices and Biodiversity in the Area.
Table 18: Soil/Biodiversity Relationship in the Study Area
S/N
Sample
%
Sand
%
Silt
%
Clay
PH
H2O
P
mg/kg
%N
%
Oc
%
OM
%
Ca
Mg
Cmol
%
Na
%
Ex.A1
Plants
Animals
Biodiversity
1
Intercropping
81.60
6.20
12.00
4.10
13.30
0.126
1.147
1.977
3.20
1.60
1.973
0.68
2.73
1.85
IC=0.089
2
Mixed
farming
Plantation
agriculture
Bush
fallowing
Animal
husbandry
79.80
9.70
10.33
13.90
0.154
1.437
2.477
3.00
2.00
2.773
1.00
2.82
1.67
MF=0.059
73.80
18.20
8.00
4.a2
7
4.57
23.80
0.105
0.880
1.700
5.00
2.20
0.480
0.12
2.78
1.66
PA=0.071
78.80
12.20
9.00
4.30
19.50
0.088
0.717
1.230
4.13
2.20
1.280
0.80
2.75
1.67
B.F=0.058
74.80
13.70
11.50
4.30
16.10
0.126
1.167
2.010
4.40
1.40
0.760
0.66
2.81
1.60
A.H=0.053
3
4
5
Source: Field work, 2011
110
From the result, a soil/biodiversity relationship table was generated as shown in
table 18. Data on physical and chemical properties of soil in the area is given in
Appendix 3; while correlation result between soil and biodiversity are presented in
Appendix 4. The raw data is also given as Appendix 3.
The spearman’s rank correlation coefficient was run to generate correlation matrix
for the properties and plant diversity index, animal diversity index, plant and animal
diversity index and biodiversity index. (Appendix 4). In the correlation between soil
properties and plant diversity index, there is correlation between soil and plant species
diversity index. Hence, there is correlation between plant index and sand, as well as plant
index and clay, although the coefficient is negative. The negative coefficient between
plant index and sand implies that where sand is high, there will be less plant species
diversity. That of plant index and clay means that where the clay content of the soil is
high, it would adversely affect plant growth. The reason is that the water may not
penetrate the clay and reach the roots of certain plant species. It is only those plants
whose roots are within the clayey part that would thrive well. There is a positive
correlation between plant index and silt, same applies to plant index and water pH.
The positive correlation between plant diversity index and silt means that high silt
content favours plant growth. On the other than, when the water pH is high, there would
be less plant diversity. In the correlation between soil properties and animal diversity
index, it could be seen that there is relationship between animal index and sand (0.671),
animal index and silt (-.0.671) though with a negative correlation coefficient. This means
that where sand content is high, there would be more animal diversity, and vice versa. For
animal index and silt, where there is high silt content, there would be low animal
111
diversity. The same also applies to animal index and water pH (-0.574). This indicates
that less water pH entails high animal diversity. When the water pH is high, there would
be less plant diversity, which in turn affects wildlife negatively.
For the correlation between soil properties and plant and animal diversity indices,
there is also correlation between soil and plant and animal diversity indices. The
implication is that the more the soil properties in the right proportions, the more the
diversity of plant and animal species. Hence, the coefficient for plant index and sand is 0.564. This means that more sand content in the soil implies less plant diversity. The
reason is that all the soil properties must be in the right proportions for plants to grow
well. That of plant index and silt is 0.564, while the coefficient for plant index and clay is
-0.616. It means that silt content if high, does not favour plant growth. Similarly, as clay
retains moisture, the smaller plants whose roots do not penetrate beyond the level of clay
may not do well. It is only those with stronger roots that penetrate beyond this level that
would flourish. The correlation coefficient between plant index and water pH is 0.526. As
for that between plant diversity index and water pH, the higher the water pH, the less
diverse the plant species in an area. On the other hand the correlation coefficient between
animal index and sand is 0.671. This however implies that the more the sand content, the
less the animal diversity. That of animal index and silt is -0.671. It implies that the less
the silt, the more the animal diversity. While that between animal index and water pH is 0.574, that between animal index and nitrogen is 0.000. This entails that the higher the
water pH, the lower the animal diversity in an area. There is no relationship between
animal diversity index and nitrogen.
112
Surprisingly in the correlation between soil properties and biodiversity, there was
no relationship between sand and biodiversity. The same thing applies to that between silt
and biodiversity. However, there was weak correlation between clay and biodiversity.
The same thing applies to Exchangeable Aluminium (Ex.Al) and biodiversity. There was
also moderate correlation between Mg and biodiversity, but it was not encouraging.
Furthermore, to ascertain the underlying factors responsible for the observed relationship
between the soil properties and biodiversity, the soil test result was subjected to P.C.A.
The first analysis was run between soil properties and plant index. The second was
between soil and animal index. The third was run between soil and plant and animal
index, while the fourth was between soil and biodiversity index. The PCA of the soil and
plant index is shown in Table 19.
113
Table 19: Rotated Component Matrix of the Soil Properties and Plant Diversity
Index in the Study Area
Component
Variables
1
2
3
X1
% of sand
-.984*
-.027
-.097
X2
% of silt
.904*
-.084
.404
X3
% of clay
-.413
.252
-.875*
X4
% of soil pH
.807*
.006
.589
X5
% of potassium
.704*
-.418
.569
X6
% of Nitrogen
-.297
.919*
-.242
X7
% of OC
-.299
.903*
-.305
X8
% of OM
-.187
.941*
-.237
X9
% of Ca
.907*
-.385
.158
X10
% of Mg
-.010
-.218
.974*
X11
% of Na
-.868*
488
.082
X12
% of Ex. Al
-.788*
.277
-.117
Plant index
.618
.705
.300
Eigen value
5.893
3.800
2.902
% of variance
45.333
29.233
22.322
Cumulative %
45.333
74.566
96.888
* significant loadings ≥ + /− 0.70
The results of the rotated component matrix above, show that three components
were extracted from the twelve variables. Component 1 has significant loadings on seven
variables. The variables with negative signs are XI (% of sand), XII (% of Na), and X12
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(Ex. Al). This means that the more agricultural land use practices adversely affect these
soil properties, the less the soil quality. This in turn implies that such soil would not
support more plant diversity index. The variables with positive signs are X2 (% of silt),
X4 (% of water pH), X5 (% of potassium), and X9 (% of Ca). It mans that as long as these
practices do not have adverse effects on the soil, there is bound to be more plant species
diversity. The underlying factor becomes effect of soil physico-chemical properties.
The component has an eigen value of 5.893 and explains 45.333% of the total variance.
Component II has significant loadings on three variables viz X6 (% of Nitrogen),
X7 (% of OC), and X8 (% of OM). The heavy loadings on these variables denote that if
the land use practices do not impact negatively on nitrogen, organic carbon and organic
matter, there would be diversity of plant species and vise versa. This is because these
properties of the soil favour plant growth in an area. In other words the plant diversity
index (705*) is in agreement with variables X6, X7 and X8. The underlying factor here is
carbon – nitrogen ratio. The component has an eigen value of 3.800 and explains
29.233% of the total variance.
Component III loads heavily on two variables. They are X3 (-0.875) and X10
(0.974). Variable X3 has a negative loading (-0.875) although high, which means that the
more the soil lacks clay, the more it supports plant species diversity. This is because clay
retains water and does not allow it to permeate. This adversely affect plant diversity.
Variable X10 which loads with a positive sign implies that as long as the quantity of
magnesium is not affected adversely by the farming practices, there is bound to be plant
diversity in such area. Hence, the component has an eigen value of 2.902 and contributes
22.322% of the total variance. The underlying factor here becomes index of soil fertility.
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PCA was used to ascertain the major factors responsible for the observed variation in the
correlation between soil properties and animal diversity index. The rotated component
matrix is presented in Table 20.
Table 20: Rotated Component Matrix of the Soil Properties and Animal Diversity
Index in the Study Area
Component
Variables
I
II
III
X1
% of sand
.991*
.124
-.028
X2
% of silt
-.913*
-.227
.339
X3
% of clay
.425
.330
-.842*
X4
% of soil pH
-.826*
-.141
.527
X5
% of potassium
-.654
-.543
.513
X6
% of Nitrogen
-.175
.946*
-.222
X7
% of OC
.180
.934*
-.284
X8
% of OM
.071
.942*
-.227
X9
% of Ca
-.846*
-.525
.090
X10
% of Mg
-.018
-.232
.971*
X11
% of Na
.772*
.618*
.145
X12
% of Ex. Al
.673*
.458
-.044
Plant index
.723
.-.208
-.203
Eigen value
5.463
4.111
2.561
% of variance
42.024
31.625
19.698
Cumulative %
42.024
73.650
93.347
* significant loadings ≥ + /− 0.70
Table 20 shows three components. Component I has significant loadings on six
variables. Variables XI (% of sand), and XII (% of Na) have positive sings and load high.
This means that if the agricultural land use practices have low negative impact on these
116
soil properties, the soil would support plant growth; which in turn encourages animal
diversity in the area. Variables X2 (% of silt, X4 (% of soil pH), and X9 (% of Ca), have
high negative loadings, meaning that animal diversity would be discouraged, if such soil
properties are adversely impacted as a result of agricultural land use practices in the area.
The component has an eigen value of 5.463 and explains 42.024% of the total variance.
The underlying factor is general disposition of soil properties towards animal species
diversity.
For component II, there are significant loadings on variable X6(% of Nitrogen),
X7(% of OC), X8(% of OM) and X11(% of Na). The positive significant loadings here
imply that these soil properties denote soil fertility in an area and as such would
encourage plant growth. This plant growth would aid animal diversity especially for
those larger animals that cannot hide under the grasses. Even those that burrow in the soil
are also favoured. So any farming systems that favour these soil properties in turn favour
animal species diversity. The component has an eigen value of 4.111 and explains
31.625% of the total variance. The underlying factor here is favourable habitat.
Component III has heavy loadings on two variables viz: X3(% of clay) and
X10(% of Mg). Variable X3 has a high negative loading, meaning that when the
percentage of clay is negatively impacted by land use practices, the life of certain animals
there is endangered. This is more so in the case of burrowing animals. Like the Rattus
rattus. Variable X10 has a positively high loading, meaning that when the percentage of
Magnesium in the soil diminishes due to farming systems, animal diversity is limited.
The component has an eigen value of 2.561 and explains 19.698% of the total variance. .
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The underlying factor here is clay mineral impact. The three components together explain
93.347% of the observed variation, leaving the remaining 6.653% unexplained
The rotated component matrix of the soil properties with plant diversity index and
animal diversity index is shown in Table 21.
Table 21: Rotated Component Matrix of the Soil Properties, Plant and Animal
Index in the Study Area
Component
Variables
I
II
III
X1
% of sand
-.983*
.180
-.004
X2
% of silt
.908*
-.270
.319
X3
% of clay
-.430
.332
-.838*
X4
% of soil pH
.831*
-.176
.506
X5
% of potassium
.637
-.568
.509
X6
% of Nitrogen
-.128
.948*
-.244
X7
% of OC
-.136
.935*
-.305
X8
% of OM
-.026
.937*
-.252
X9
% of Ca
.818*
-.570
.083
X10
% of Mg
.033
-.208
.976*
X11
% of Na
-.732*
.665
.149
X12
% of Ex. Al
-.644
.499
-.035
Plant index
.796
.564
.220
Animal index
-.742
-.176
-.179
Eigen value
5.911
4.626
2.597
% of variance
42.223
33.045
18.553
Cumulative
42.223
75.268
93.821
* significant loadings ≥ + /− 0.70
Table 21 shows that there are three components resulting from the twelve
variables. Component 1 has significant loadings on five variables. Variables XI (% of
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sand) and XII (% of Na) have highly negative loadings. This means that as these soil
components are impacted negatively by the farming system in the area, animal diversity
tends to be suppressed. Variables X2 (% of silt), X4 (% of soil pH) and X9 (% of Ca) have
significant loadings, meaning that the more these properties of the soil are moderately
impacted by agricultural land use practices, the more the plant diversity index. The
component has an eigen value of 5.911 and explains 42.223% of the total variance. The
underlying factor here is soil conditions for species diversity.
Component II has three variables with significant loadings. They are X6 (% of
Nitrogen), X7 (% of OC) and X8 (% of OM). This implies that as long as Nitrogen,
organic carbon and organic matter are favoured by the farming systems in an area, the
plant species would flourish. Hence, these are soil nutrients that enhance plant growth.
The component has an eigen value of 4.626 and represents 33.045% of the total variance.
The underlying dimension is favourable conditions for plant species diversity.
Component III has significant loadings on two variables viz: X3 (% of clay) and
X10 (% of Mg). For variable X3, the more the % of clay the less the animal species
diversity. Whereas the more the magnesium content in the soil the more the plant species
diversity. The component has an eigen value of 2.597 and explains 18.553% of the total
variance. The underlying factor here is the impact of soil minerals on biodiversity.
However, the three components jointly explain 93.821% of the variation on the input
data, leaving 6.1792 unexplained.
The table for the PCA on soil properties and biodiversity index is shown in Table
22.
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Table 22: Rotated Component Matrix of Soil Properties and Biodiversity Index in
the Study Area
Component
Variables
I
II
III
X1
% of sand
-.961*
-.078
-.028
X2
% of silt
.889*
-.189
.338
X3
% of clay
-.423
.316
-.842*
X4
% of soil pH
.823*
-.074
.549
X5
% of potassium
.701*
-.474
.532
X6
% of Nitrogen
-.240
.950*
-.199
X7
% of OC
-.249
.930*
-.266
X8
% of OM
-.121
.974*
-.190
X9
% of Ca
.874*
-.465
.096
X10
% of Mg
.015
-.247
.968*
X11
% of Na
-.825*
.547
.137
X12
% of Ex. Al
-.835*
.240
-.146
Plant index
.759
-.038
.494
Eigen value
5.915
3.723
2.786
% of variance
45.504
28.640
21.428
Cumulative %
45.504
74.144
95.572
* significant loadings ≥ + /− 0.70
Table 22 shows that three components were extracted from the twelve variables.
Component I has significant loadings on seven variables. The variables with negative
signs are XI (% of sand), XII (% of Na) and X12 (% of Ex. Al), meaning that the more
negatively these soil properties are impacted, the less the biodiversity index. For the four
variables X2 (% of silt), X4 (% of soil pH), X5 (% of Potassium) and X9 (% of Ca), the
heavy loadings imply that increase in these soil properties, increases biodiversity index.
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The underlying component here is conditions for biodiversity enhancement. The
component has an eigen value of 5.915 and accounts for 45.504% of the total variance.
In the case of component II, only three variables are significantly loaded. They
are X6 (% of Nitrogen), X7 (of OC) and X8 (% of OM). Their high loadings imply that the
more these properties in the soil, the more the biodiversity index. This is because these
three elements favour plant growth, which in turn encourages biodiversity. The
component has an eigen value of 3.723 and explains 28.640% of the total variance. The
underlying dimension is impact of favourable soil properties on biodiversity.
Component III has two variables with significant loadings. They are X3 (% of
clay) and X10 (% of Mg). This means that while high clay content in the soil impacts
negatively on the biodiversity index, high Mg content impacts positively on biodiversity.
In terms of X10, more Mg in the soil attracts more biodiversity. This is because Mg is an
essential nutrient for plant growth. The component has an eigen value of 2.786 and
accounts for 21.428% of the total variance. The underlying factor here is effect of
clay/Mg relationship on biodiversity. The three components therefore account for
95.572% of the observed variation leaving 4.428% unexplained.
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CHAPTER FIVE
MEASURES TO ENCOURAGE SUSTAINABLE AGRICULTURAL LAND USE
AND CONSERVATION OF BIODIVERSITY IN THE AREA
5.1 Modification of the farming system
From the study, it is evident that apart from bush fallowing, the other identified
various agricultural land use practices undertaken by man have adverse effects on
biodiversity in the study area. Sequel to this, it becomes imperative that some measures
be taken to mitigate the impact of these practices on biodiversity. These measures include
among other things, the adoption of modified farming systems that favour biodiversity
and also sustain food production. Prominent among them is organic agriculture or organic
farming.
Organic agriculture is a system of agriculture that relies on ecosystem
management rather than external inputs. It is a system that begins to consider potential
environmental and social impacts by eliminating the use of synthetic inputs, such as
synthetic fertilizers and pesticides, veterinary drugs, genetically modified seeds and
breeds and preservatives, additives and irradiatives. These are replaced with site-specific
management practices that maintain and increase long-term soil fertility and prevent pest
and diseases. For instance, in the case of intercropping, it was discovered that it destroys
biodiversity. This is due to the fact that other plant species in a proposed crop farm are
cleared in favour of the desired crops. Intercropping could be modified by employing
agro-forestry (agriculture incorporating the cultivation of trees). Such trees include
Penthaclethra macrophylla and Elaeis guineensis among others. These tree crops provide
habitat for certain animal species. As these animal species inhabit there, their droppings
would aid soil fertility. This in turn enhances plant growth. This combines agricultural
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and forestry technology to create more diverse, productive, profitable, healthy and
sustainable land-use system. An example is parkland in Burkina Faso where sorghum
was grown under Faidherbia albida and Borassus akeassii (Wojtkowski, 2002).
From our findings, burning after clearing should be done earlier before the first
rains. This enables the ashes and other humus contents to be mixed up as the first rains
fall. In terms of burning, it should be pile burning, which is gathering up the slash into
piles before burning. Our findings show that as a result of crop farm management system,
Umuogele had a biodiversity index of 0.04 which is very low. Ahiaba Ubi and Obikabia
also had 0.04 among others. The application of compost manure should be prefered to
inorganic fertilizer. If these modifications are adopted, it would make a difference.
Organic agriculture is a holistic production management system which promotes and
enhances agro-ecosystem health including biodiversity, biological cycles, and soil
biological activity. In this system of farming, organic manure and fertilizers offer
increased diversity among soil microbial communities that transform carbon more
efficiently from organic debris and build the microbial biomass. Hence, Matson et al
(1997), observed that sustainable agricultural land use management strategies that
advocate replacing the use of inorganic fertilizer by organic manure, increase soil organic
matter and therefore support biodiversity conservation be adopted.
Organic agriculture is one of several approaches to sustainable agriculture and
many of the techniques used (eg inter-cropping, rotation of crops, mulching, integration
of crops and livestock) are practiced under various agricultural systems. What makes
organic agriculture unique, as regulated under various laws and certification programmes
is that almost all synthetic inputs are prohibited and soil building crop rotations are
123
mandated. Crop rotations encourage a diversity of food crops, fodder and under-utilized
plants. Apart from improving overall farm production, soil fertility may assist in the
conservation of plant genetic resources.
Tree crops and non-farm forestry integrated into the system provide shade and
wind-breaks while providing food, incomes, fuel and wood. Economic objectives are not
the only motivation of organic farmers, their intent is often to optimize land, animal and
plant interactions, preserve and enhance biodiversity, all of which contribute to the
overall objective of sustainable agriculture to preserve natural resources and ecosystem
for future generations. In mixed farming, the animals eat up the young vegetal cover in
such areas as the plant species regenerate. In the area where mixed farming involves
growing of cash crops among annual crops, it can also be modified. We obtained low
biodiversity indices in Ngwankwu (0.04), Eziama (0.04) etc. The cash crops for instance
rubber or Oil palms cover the annual crops. There should be proper planning here. The
areas mapped out for mixed farming should be divided into plots. They should be
managed in such a way that the animals are not allowed to destroy the re-vegetated plots.
As for cash and annual crops, the cash crops should be slightly pruned to enable the
annual crops receive sun rays. This is supported by Fuhlendorf and Engle (2004).
Plantation agriculture could also be modified in favour of biodiversity. In the
study area, where some plantation farms were at the growing stage, others had already
attained maturity. We discovered that some of the plantation farms were totally cleared of
other plant species, such that one can find no other plant species except the cash crops.
Hence the biodiversity indices derived there from ranges from 0.03 (in Obikabia) to 0.10
(in Amapu Ntigha). The areas with plantations at the growing stage should be managed in
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order to abate the negative impact of the practice on biodiversity. In this case, there
should be selective clearing of plant species. This involves clearing only the plant species
within the immediate surroundings of individual stands and not outright clearing of the
whole plantation site. For the plantations at full maturity, the same should also apply.
These ones could be pruned once in a while. This could help the other species therein to
flourish. This is supported by F.A.O. (2002).
Concerning animal husbandry, we found biodiversity indices as low as 0.02
(Amapu Ntigha). Other communities with low biodiversity indices include Umuogele
(0.04), Obikabia (0.03), Eziala (0.03), Ntigha (0.03). It means that this practice has a
negative impact on biodiversity. However, there could be some modifications. As we
know that animal husbandry leads to overgrazing, this could be managed in order to also
abate the impact on biodiversity. If there are areas designated for animal husbandry, it
could be helpful. When the areas are also divided into plots, such that rotational grazing
is adopted it could make a difference. This is preferable to indiscriminate grazing.
Other things that could be done under the modified farming systems include
improved bush fallowing system. This involves increasing the fallow period from two to
at least six years. This will enable the soil to regain its fertility as well as conserve
biodiversity; thereby encourage sustainable food production and species diversity. In
bush fallowing, we discovered that biodiversity has moderate impact from the practice.
From the study, we recorded low biodiversity indices in some communities. These
include Umuogele (0.04), Ntigha (0.04), Umurandu (0.04), etc. This means that the
practice also has negative impact on biodiversity. However, if the fallow period is
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increased, to about six years, it would enable biodiversity recuperation in the area. Those
disappeared animal species might begin to come back.
Controlled burning or prescribed burning instead of indiscriminate bush burning
should be adopted. This is also known as hazard reduction burning and it is a technique
sometimes used in forest management, farming or greenhouse gas abatement. Fire is a
natural part of both forest and grassland ecology and controlled fire can be a tool for
foresters. Hazard reduction or controlled burning is conducted during the cooler months
to reduce fuel build up and decrease the likelihood of serious hotter fires. Controlled
burning stimulates the germination of some desirable forest trees, thus renewing the
forest (Julie et al. 2004). They furthermore reported that controlled burning is of two
types: broadcast burning, which is the burning of scattered slash over a wide area. The
other one is pile burning, which is gathering up the slash into piles before burning. These
burning piles may be referred to as bonfires. Controlled burning reduces fuels, may
improve wildlife habitat, controls competing vegetation, improves short term forage for
grazing, improves accessibility, helps control tree disease and perpetuates fire dependent
species.
In our research, we discovered that there are some people who practice
continuous cropping behind their compounds. This is due to poor land tenure system. If
the land tenure system is arranged in such a way that people have more than two portions
of land, it would help. Otherwise a farmer that has just one portion of land, would be
forced to continuously cultivate the area. This could lead to perpetual soil
impoverishment and eventual biodiversity loss.
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5.2
The role of the Government in Modifying Sustainable Agricultural Land Use
and Biodiversity Conservation in the Area.
The modifications highlighted above may be difficult to implement if the
government does not intervene. The government may put some modalities in place to
ensure sustainable agricultural land use and biodiversity conservation. Such modalities
include legislation and public awareness campaign that will enforce the implementation.
The government in the developed countries has departments that are responsible for the
implementation. For instance, in the U.K., it is known as the Department for
Environment, Food and Rural Affairs (DEFRA). This department covers the following
areas:
The natural environment, biodiversity-plants and animals.
Sustainable development and the green economy.
Food, farming and fisheries
Animal health and welfare
Environmental protection and pollution control
Rural communities and issues
The government believes that we need to protect the environment for future
generations, make our economy more environmentally sustainable and improve our
quality of life and well-being. We also believe that much more needs to be done to
support the farming industry, protect biodiversity and encourage sustainable food
production. In the case of the study area, the Federal government through the Federal
Ministry of Environment, should borrow a leaf from those countries and replicate same at
the state, local government and community levels.
127
In addition, protected areas should be established from the state, local government
to the local communities including the study area. However, the Convention on
Biodiversity (CBD) is the most important international legal instrument addressing
protected areas. The term protected area is defined in article 2 of the convention as a
geographically defined area, which is designated or regulated and managed to achieve
specific conservation objectives. Protected areas are areas where special measures are
taken to conserve biological diversity. Protected areas are the dominant approach to
protecting biodiversity and the supply of ecosystem services (MEA, 2005).
Protected areas might push local economies out of poverty traps, by providing
tourism business opportunities, improved infrastructure or enhanced supply of ecosystem
services. For example, evidence from Costa Rica (Central America) and Thailand (South
East Asia) suggests that protected areas in these two countries have on average, reduced
local poverty (Andam, et al, 2010, Sims, 2010). If these protected areas, where
agricultural activities are totally prohibited are established at the state, local government
and community levels, with close monitoring, they will no doubt achieve the desired
goal.
Apart from the above, the government should also evolve other policies that are
geared towards sustainable agricultural production and biodiversity conservation. An
example of such policies in Nigeria is the Nigeria National Biodiversity Strategy and
Action Plan (NBSAP, 2008). This policy by the Nigerian government is aimed at
encouraging sustainable agricultural production and protection of biodiversity.
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5.3
The Role of Non-Governmental Organizations in Modifying Sustainable
Agricultural Production in the Area.
In the war against biodiversity depletion as a result of certain agricultural land use
practices, all hands should be on deck. Everything should not be left for the government
alone. Therefore, the non-governmental organizations have a role to play in this regard.
There are a number of such NGOs and in cooperation with international partners,
they could be reached. Some of the NGOs include the Community Biodiversity
Management (CBM). This NGO has offices in Ethiopia, France, Brazil, and India.
C.B.M. is a methodology guiding practices that contribute to the conservation and
sustainable use of biodiversity at the local level, with emphasis on agro-biodiversity. The
C.B.M. distinguishes itself from other conservation strategies because of its focus on the
process of enabling communities to secure their access to and control over genetic
resources through increased decision-making power. This NGO, organizes community
symposia, workshops, awareness campaigns at the local levels. So, if their presence is
attracted in the study area, it will make a difference in the orientation of local farmers in
terms of biodiversity conservation. The CBM is a subsidiary of the global community
Biodiversity management study with the main objective to compare different local
practices and realities of community based management of biodiversity.
We also have the Rainforest Alliance, this is an NGO with the published aims of
working to conserve biodiversity and ensure sustainable livelihoods by transforming
agricultural land use practices, business practices and consumer behaviour. It is based in
New York City and has offices worldwide. The Rainforest Alliance sustainable Forestry
is another NGO. This NGO launched the world’s first sustainable forestry certification
129
programme in 1989 to encourage market- driven and environmentally and socially
responsible management of forests, tree farms and forest resources.
Agricultural expansion is responsible for 70% of global deforestation and is the
single greatest threat to tropical forests. In these biodiversity-rich regions, farms are often
responsible for soil erosion, water pollution and wildlife habitat destruction. Hence,
Rainforest Alliance Certification encourages farmers to grow crops and manage
ranchlands sustainably. The certification system is built on the three pillars of
sustainability-environmental protection, social equity and economic viability and no
single pillar can support long-term success on its own, and so local farmers are helped to
improve in all three areas.
Other NGOs in this regard include: International Conservation Union (ICU), The
Forest Trust (TFT), Conservation International (CI), The Wildlife Conservation Society
(WCS), The Nature Conservancy (TNC) and the World Wildlife Fund for Nature
(WWF). They all act as mediator between various development interest, policy makers,
local peoples, scientists and activist groups in promoting conservation. These NGOs
initiate and support a broad range of conservation-related activities from arranging
international conferences to establishing community-based conservation projects to
maintaining parks and reserves.
In view of the above, the services of these NGOs are advocated so as to encourage
sustainable agricultural production and conservation of biodiversity in the study area.
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CHAPTER SIX
SUMMARY OF FINDINGS, RECOMMENDATIONS AND CONCLUSION
6.1
Summary of Findings
This study examined the impact of agricultural land use practices on biodiversity
in Isiala North L.G.A of Abia State. The study was carried out using all the forty
communities of the L.G.A. Biodiversity inventory of the species was undertaken from
each of the five dominant agricultural land use types in the study area, through
purposively selecting one quadrat from each community. With the aid of Shannon
Wienner’s diversity index, the diversity indices of the plant and animal species were
determined. From the biodiversity inventory, we also determined the biodiversity indices
of the species in the area. We also identified five main agricultural land use types in the
area. They include crop farming, mixed farming, plantation agriculture, bush fallowing
and animal husbandry.
The study shows how the various agricultural land use types affected biodiversity
in the study area. From the results, soil tillage led to decline in organic matter content of
the soil, as it disintegrates the soil aggregates that protect soil organic matter from
decomposition. Bush burning had adverse effect on biodiversity as it led to the depletion
of plant and animal species. This is due to forest clearing, which forces unique fauna
species to migrate due to the destruction of their habitat, and therefore exposes them to
predators. Animal husbandry encouraged to overgrazing, which in turn resulted to
depletion of biodiversity. Field observation revealed that due to regular grazing, some
areas have almost become bare soils. Traces of erosion were apparent in such areas. In
the case of mixed farming,
131
it was discovered that as the animals feed on the grass, their droppings help improve soil
fertility and re-growth, although it does not allow for vegetation regeneration as the
animals also eat the re-growth as they regenerate. Weed control measures practiced in the
area are unfavourable to biodiversity. This is due to regular weeding, chemical weed
control etc, which impact negatively on biodiversity in the area.
Similarly, the measures used in controlling the animals that invade farmlands are
also harmful to biodiversity. These include mainly trapping, hunting, poisoning etc. All
these are not in favour of biodiversity conservation. Concerning bush fallowing, the short
fallow periods as shown from the study, cause depletion of biodiversity. Plantation
agriculture in the same vein limits species richness and diversity as plantation fields are
cleared of other plant species in favour of only the desired tree crop. The same thing
applies to crop farming as the plant and animal species are cleared during the pre-farming
preparation.
The data on biodiversity indices were subjected to PCA together with the
agricultural land use types, to ascertain their impact on biodiversity. The PCA results
showed that the five variables were reduced to three underlying components. These three
components together explained 64.296% total cumulative variance in the original data
and were identified as impact of plant clearance on biodiversity, effect of habitat
disturbance on biodiversity and effect of mono-cropping on biodiversity.
The FGD sessions with the farmers and hunters were in agreement with the
findings of the research. Thus the farmers agreed that intercropping leads to the depletion
of biodiversity. On their own part, the hunters also agreed that they hunt on weekly basis.
This certainly takes its toll on biodiversity. Even the key informants during the interviews
132
disclosed some of their farming activities that threaten biodiversity conservation. Such
include constant clearing of the bush, encroachment into the informal protected areas by
farmers, application of inorganic fertilizers, etc.
Furthermore, during the study, 18 soil samples were collected from various
locations of different agricultural land use types that dominate the area, for laboratory
analysis. The result indicates that agricultural land use practices have significant negative
effect on the soil properties which in turn affects biodiversity as shown in appendix 2.
6.2
Recommendations
Having studied the impact of agricultural land use practices on biodiversity and
analyzed the various aspects of these practices and how they affect biodiversity in the
area, it was discovered that these agricultural land use type have varied impacts on
biodiversity. Hence, intercroping has the greatest negative impact. It destroys every other
plant species in the area. The next is mixed farming. This also leads to the depletion of
plant species and eventual habitat disturbance. This is followed by animal husbandry as it
leads to overgrazing. It is note worthy to mention that this practice has both positive and
negative impacts. While it leads to overgrazing, the animal droppings aid soil fertility.
The agricultural land use type with the least negative impact is bush fallowing, implying
that with long fallow periods, there would be biodiversity conservation.
Following the findings on the impact of agricultural land use practices on
biodiversity in Isiala Ngwa North Local Government Area, the following are therefore
recommended to ensure sustainable agricultural land use and biodiversity conservation:
133
a)
Extension of fallow periods.
Farmers should extend the fallow periods to ensure the recovery of soil fertility. If the
fallow periods are increased from three to about six years, it will go a long way to
restoring the soil fertility. This in turn will also restore the wildlife corridors which are
lost due to forest clearance. For instance, Amapu-Umuoha community, which is one of
the few communities that have up to three year-fallow periods in some cases, should be
encouraged to increase the fallow periods, while other communities should also do
likewise. This will invariably give the plant and animal species in the area enough time to
regenerate. This is in line with Adinma (2001) who stated that common practice in the
African rotational bush fallow system of subsistence economy is slash and burn and
burning without providing adequate fire guards. This leads to unwanted bush burning,
forest destruction and loss of biodiversity.
b)
Enlightenment of the public on sustainable land use practices
With respect to the findings, there is urgent need for the awareness campaign to
be carried out especially at the grassroots on sustainable land use practices. A situation
where a farmer does not even know if there are consequences associated with
indiscriminate bush burning, regular application of inorganic fertilizer etc, spells doom to
the biodiversity in the area. Therefore we recommended pile burning which is gathering
up the slash into piles before burning. This is preferable to indiscriminate bush burning as
suggested by Julie et al (2004). Application of organic fertilizer is recommended in
preference to inorganic fertilizer.
Therefore, the government in collaboration with the community leaders, should
embark on massive awareness campaign on the impact of unsustainable farming methods.
134
This will help drive home the message of sustainable farming practices that encourage
protection of biodiversity. This could be done through television, radio jingles and
workshops.
c)
Reinforcing the policy on the protection of farmlands
There is a policy passed into law to protect farmlands against bush burning in the
study area. Such policy is dormant and needs to be fully reinforced. It was discovered
during our interviews that some farmers resort to bush burning as a way of clearing the
bush for farming. We also found out that some farmers allow their livestock to roam
about, thereby destroying peoples’ crops.
In view of the above, it becomes imperative that a policy be put in place with adequate
sanctions to defaulters. If there are fines to pay for bush burning, leaving animals to roam
about, it will serve as a deterrent to intending defaulters, thereby ensuring biodiversity
conservation.
d)
Establishment of Protected areas, parks and reserves
Even though there are informal protected areas in the area, they are not enough.
There should be more of these informal protected areas, reserves, parks etc, where
farming and hunting are strictly prohibited. Our study reveals that there are no formally
designated protected areas, reserves, parks etc, where farming and hunting activities are
restricted. Hence, the hunters do their hunting expeditions everywhere and every week,
killing both the young and old animals. We also discovered that some farmers have
gradually started to encroach into the sacred forests where still-births are disposed of and
community shrines are housed. This is supported by Buchman and Nabhan (1996).
135
The community leaders should reawaken the customary sanctions associated with
such encroachment. This will help to forestall further encroachment into such areas. And
if this is achieved, the aesthetic value and other ecosystem services will be enjoyed by all,
especially the future generations.
e)
Agricultural Extension Services
The government at all levels should engage in massive agricultural extension
services, to keep the farming communities abreast of healthy and sustainable farming
practices. These agricultural extension services such as teaching farmers new farming
methods, giving them improved varieties of crops, birds and other farm inputs at
subsidized rates, will help improve food security as well as conserve biodiversity in the
study area.
In other words, if the government at all levels and community leaders see this as a
challenge and face it as such, the extension services will no doubt permeate the local
communities and ensure a turn-around in the farming systems that operate in the area.
f)
Involvement of non-governmental organizations (NGOs)
Finally, there should be a serious involvement of non-governmental organizations
in the crusade against biodiversity depletion as a result of certain agricultural land use
practices in the area.
As we said earlier in section 3.3, there are a good number of NGOs out there, that
could be involved in this matter. This could be possible through the government in
collaboration with well-meaning and public-spirited individuals in the society. If these
NGOs are consulted, they could play a role that will also intensify the efforts towards
achieving sustainable agricultural production and biodiversity conservation for posterity
if not for anything else.
136
g).
Rotational grazing
Instead of indiscriminate grazing, we advocate for rotational grazing. There
should be areas designated for grazing by farmers who practice animal husbandry. Such
areas should be divided in plots, such that while the animals graze in plot A, the plant
species in B would be spared. This is better than indiscriminate grazing. Rotational
grazing involves dividing the range into several pastures and then grazing each in
sequence throughout the grazing period. This can improve livestock distribution while
incorporating rest period for new forage. Another prescribed form of grazing is Patch-
burn grazing. This involves burning of a third of a pasture each year. This burned patch
is used for grazing because of the fresh grasses that grow therein. The other patches
receive little or no grazing. During the next two years, the next two patches burn
consecutively and then the cycle begins a new. In this way, patches receive two years of
rest and recovery of the heavy grazing. (Fuhlendorf and Engle, 2004).
6.3
Conclusion
On the basis of the major findings, inferences were made. It was discovered that
all the five identified prevalent agricultural land use practices had negative impact on
biodiversity, except bush fallowing. Intercropping, mixed farming, plantation agriculture
and animal husbandry had negative impact on biodiversity. These practices led to the
destruction of plant species and loss of habitat for the animal species. They further led to
exposure of the animal species to threat and eventual death. Bush fallowing had
moderately negative impact on biodiversity due to short fallow periods. Among the
agricultural land use practices that operate in the area, intercropping had the most
negative impact on biodiversity.
137
Descriptive analyses were carried out on the indices and the agricultural land use
types to ascertain the impact of these practices on biodiversity in the area. In addition,
P.C.A was used to further analyze the data obtained. The results showed that the
agricultural land use practices were reduced to three (3) underlying components that
explained a total variance of 64.296% of the agricultural land use types. The result further
shows that “the suppression of biodiversity” was the greatest negative impact on
biodiversity as it accounts for 22.996% of the total variance. This is followed by “effect
of mono-cropping on biodiversity”, which accounts for 22.577% of the total variance. In
other words, crop farming has the greatest negative impact on biodiversity in the area.
This is because crop farming does not permit the sustenance of biodiversity. This is
followed by mixed farming. This is due to the fact that during mixed farming, animals eat
up the plant species in the area thereby exposing the fauna to danger.
Based on these findings, suggestions were made on how to achieve sustainable food
production and at the same time promote biodiversity conservation in the study area. If
these recommendations are properly implemented, they will help to stem the tide of the
impact of agricultural land use practices in the area, thereby increase food production,
conservation of biodiversity and ensure sustainable, development in the area.
138
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146
APPENDIX 2
CLASSIFICATION OF THE PLANT SPECIES IN THE AREA
Herbs
Grasses
1. Crowfoot
grass 21
2. Giant Blue
stem 30
3. Elepaht grass
38
Shrubs
1. Cnestis
feniginea 30
2. Manihot
utilissima 37
3. Yellow
mombin 28
Trees
1. Indian
bamboo 35
2. Guava 20
3. False thistle
28
4. Umbrella
tree 16
5. Napoleona
Imperialis 33
6. Palisota
hursuta 37
7. BNitterleaf
26
8. Swizzle stick
28
9. Corkwood
31
4. Coumelina
erecta 28
5. Sleeping
grass 38
6. Spear grass
26
7. Mission grass
25
8. Guinea grass
37
9. Indian goose
grass 21
10. Umbrella
fletsedge 15
4. Alchornea c.
32
5. Christmas
bush 33
6. Pterocarpus
m 38
7. Anthonatha
m. 35
8. Cashew 13
4. Sand paper
leaf 35
5. Bitter cola
12
6. Oil bean 36
10. Forest
anchomanes 20
11. Pinklady 25
11. Lemon grass
7
12. Combretum
dohchopetalum
13
13. Piedmont
flatsedge 3
14. Combretum
aculeatum 1
1. Siam weed
380
2. Bush cane 32
12. Yellow Star
worth 38
13. African
manigold 35
14. Goat weed
25
15. Wive weed
30
16. Rose
mallow weed
22
17. Water leaf
35
18. Caesar
weed 32
19. Shinny
bush 38
20. Centrum
spp 5
21. spurge
weed 38
303
9. Camwood
30
10.
Masquerade
stick 15
11. False yam
21
12.
Sarcocephalus
l. 29
13. Afrcian
peach 18
14. African
bush willow 13
15. Dialum
guineense 31
16. Sweet/bell
pepper 1
17. Alligator
pepper 7
3. Iroko 18
7. Gmelina 28
8. Bread fruit
29
9. Cola P. 11
4. Rattlesnake
26
5. Morning
glory weed 1
6. Synclisia s.
12
7. Kudzu vine
8
8. Pumpkin 4
10. W/African
border tree 15
9. Fingerroot
1
10. Gnetum b.
27
11. D. manii
198
Manhogany
24
11. Fluted
pumpkin 11
12. Flame lily
1
Albizia s.
13. Sand
butterfly 1
157
B. mango
(Irvingia g.)
20
Cocoa 3
Rubber 21
Sweet orange
5
18. Cordleaf
burbark 13
19. Lime 2
White star
apple 18
M. indica 20
20.
Cayenne/red
pepper 1
21. Lemon 1
Alstonea b. 23
22. Pterocarpus
s. 35
Climbers
1. Mucina
beans 33
2. Lagenana
siceraria 29
3. Butterfly
pear 6
Avocado pear
15
Symphonia g.
1
Palms
1. Oil
palm 38
2. Raffia
plam 38
3.
Coconut
plam 6
82
Ferns
1. Sword
fern 25
2. Bracken
fern 37
3.
Consumed
fern 5
67
147
22. yellow
tassel flower 30
23.
Milne/redhead
33
24. Tropical
netle weed 23
25. Blue porter
weed 23
26. Cocoyam
28
27. Coper leaf
plant 17
28. Spiny
amaranth 32
29. Acanthus
Arboreus 1
30. Small
flower 20
31. Wild tee
bush 2
Aneclema
umbrosum 31
Garden spurge
17
Scent leaf 13
Miracle fruit 15
Gongronema l.
15
Castor oil bean
21
Smooth
pigweed 17
Slender
amaranth 22
Plantain 19
Vegetable juite
20
Pineapple 12
Pawpaw 8
Diodia
scandens 1
White yam 2
Banana 1
1046
23. Chenille
plant 1
464
Neem 8
647
148
APPENDIX 2B
CLASSIFICATION OF ANIMAL SPECIES IN THE AREA
Mammals
1. African giant rat 25
2. Grass cutter 29
3. Porcupine 13
Reptiles
1. Red & black stripped snake
1
2. Rainbow lizards 33
3. Saw-scaled vipers 26
4. Rat 17
4. Green-vine snakes 20
5. Pale fox 15
5. Rough green snakes 20
6. Hasting’s river mouse
18
7. Stripped grass mouse
21
8. Stripped ground
squirrel 22
9. Hyena 6
6. Yellow-headed geckos 22
5. African gray
parrots 13
6. Cattle egrets 11
7. African fat-tailed gecko 22
7. Vultures 23
8. Yellow-spotted lizards 1
8. Gray hawk 17
9. Yellow-headed day geckos
13
158
9. White-tailed kites
15
10. Senegal coucals
27
11. Bats 31
12. Doves 23
13. White-tailed
bablers 10
14. Light brown
apple moths 11
15. Red-billed fire
finches 13
16. Malabar-larks 19
17. Bulbuls/song
birds 28
18. Pygmy fly catcher
19
19. Southern
pendulinetit 17
20. Drougos/black
bird 18
21. Yellow hammer
22
22. White-sholdered
tanager 18
23. Swifts 29
24. Common cuckoo
23
25. Carruthers
cisticola 16
10. Mouse 13
11. Cattle 45
12. Cow 70
304
Amphibians
1. Toads 55
Birds
1. Weaver birds 22
2. Tuataras 6
3. Frogs (Rana h)
20
4. Frogs (Rana a)
15
74
2. Kites 1
3. Guinea fowls 12
4. Owls 31