Digitally Signed by: Content manager’s Name

DN : CN = Weabmaster’s name

O= University of Nigeria, Nsukka

OU = Innovation Centre

Elvis-Ozoadibe Christiana

Faculty of Agriculture

DEPARTMENT OF AGRICULTURAL ECONOMICS

FACTORS INFLUENCING FARMERS’ WILLINGNESS TO ENGAGE IN AGROFORESTRY PRACTICE IN EKITI STATE,

NIGERIA

ONI, FELIX OLUMIDE PG/M.Sc/08/49213

PG/MSC/08/48435

TITLE PAGE

FACTORS INFLUENCING FARMERS’ WILLINGNESS TO ENGAGE IN

AGROFORESTRY PRACTICE IN EKITI STATE, NIGERIA

A DISSERTATION SUBMITTED TO THE DEPARTMENT OF AGRICULTURAL

ECONOMICS, UNIVERSITY OF NIGERIA, NSUKKA IN PARTIAL

FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF MASTERS OF

SCIENCE (M.Sc) DEGREE IN AGRICULTURAL ECONOMICS

BY

ONI, FELIX OLUMIDE

PG/M.Sc/08/49213

JANUARY, 2015.

i

CERTIFICATION

ONI, Felix Olumide, a postgraduate student in the Department of Agricultural Economics, with

registration number PG/M.Sc/08/49213 has satisfactorily completed the requirements for course

and research work for the award of the degree of Masters of Science (M.Sc) in Agricultural

Economics. The work embodied in this dissertation, except where duly acknowledged, is the

product of my original work and has not been previously published in part or full for any other

diploma or degree of this or any other University.

----------------------------- ---------------- ---------------------------------- ---------------

Prof. E.C. Okorji Date Prof. S.A.N.D Chidebelu Date

(Supervisor) (Head of Department)

-------------------------- ------------------

External Examiner Date

ii

DEDICATION

This work is dedicated to Almighty God, the author and finisher of my faith.

iii

ACKNOWLEDGEMENT

I indeed owe a lot of gratitude, thanks and praises to God Almighty who has kept me

from the very beginning to the present moment. May His name be highly praised. My profound

gratitude goes to my supervisor Prof. E.C. Okorji for his patience, encouragement and

constructive criticisms at different stages of the work. I sincerely appreciate you Prof. I jealously

cherish Professors S.A.N.D Chidebelu; A.I Achike; N. J. Nweze; C.J. Arene; C.U Okoye and

Doctors A. A. Enete; F.U. Agbo, N. Chukwuone; Ben Okpupara; Ebele Amaechina and other

academic staff of the Department of Agricultural Economics, UNN who have contributed so

immensely in the course of this research work, I thank you all for your unalloyed cooperation

and support.

I am indeed very appreciative of Doctors Amusa Taofeeq and Otitoju Adebanjo who

have immensely contributed to the successful completion of this work. You are indeed

wonderful people, may the Almighty God bless you all. On a very important note, I wish to

register my genuine appreciation to my parents Chief and Chief Mrs. Oni Adeniyi; and my

lovely wife Mrs. Omowumi Oni (Wumine) for all their encouragement, moral, spiritual and

financial supports during the course of this study. God bless you all.

Oni, F.O.

iv

TABLE OF CONTENTS

Title Page i

Certification ii

Dedication iii

Acknowledgement iv

Table of Contents v

List of Tables vii

Abstract viii

CHAPTER ONE: INTRODUCTION 1

1.1 Background Information 1

1.2 Problem statement 5

1.3 Objectives of the study 7

1.4 Research hypotheses 8

1.5 Justification of the study 8

CHAPTER TWO: LITERATURE REVIEW 11

2.1 Conceptual Framework 11

2.2 Socioeconomic Characteristics of Agroforestry farmers 15

2.3 Land Tenure System and other Agroforestry Practices 18

2.4 Factors Influencing Farmers’ Willingness to Plant Agroforestry Trees 22

2.5 Attitudinal and Behavioral Pattern of Farmers towards Agroforestry Practice 28

2.6 Constraints to wider agroforestry tree planting in Nigeria 29

2.6.1 Lack of widespread understanding of the benefits

of agroforestry 29

2.6.2 Mass agriculture’s focus on using fertilizer and pesticide 30

2.6.3 Lack of Tree seed supply 31

2.6.4 Land tenure insecurity among smallholder farmers 31

2.6.5 Market constraints 32

2.6.6 Lack of sufficient Extension work 33

2.6.7 Policy constraints 33

2.7 Theoretical framework 34

2.8 Analytical framework 35

2.8.1 The Probit model 35

2.8.2 Likert scale rating technique 37

2.8.3 Exploratory Factor Analysis 39

v

CHAPTER THREE: METHODOLOGY 41

3.1 The Study Area 41

3.2 Sampling procedure 42

3.3 Data Collection 42

3.4 Method of Data Analysis 43

3.4.1 Probit Model 43

3.4.2 Likert scale Rating Technique 44

3.4.3 Factor Analysis model 45

3.5 Testing of Hypotheses 46

CHAPTER FOUR: RESULTS AND DISCUSSION 47

4.1 Social-economic characteristics of the respondents 47

4.2 Associated land tenure systems and other agroforestry practices

engaged in by farmers in Ekiti State 53

4.3 Factors influencing farmers’ willingness to plant agroforestry trees

in Ekiti State 57

4.4 Farmers’ attitude towards agroforestry tree planting and other

agroforestry practices in Ekiti State 61

4.5 Constraints to agroforestry tree planting by farmers in Ekiti State 65

CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATIONS 69

5.1 Summary 69

5.2 Conclusion 71

5.3 Recommendations 72

REFERENCES 74

APPENDIX A: Questionnaire for Data Collection 85

vi

LIST OF TABLES

Table 4.1: Frequency Distribution of the Respondents according to their

socio-economic characteristics. 52

Table 4.2: Frequency Distribution of respondents by their major land tenurial

systems practiced in Ekiti State. 54

Table 4.3: Frequency Distribution of the Respondents according to

agroforestry practices 57

Table 4.4: Factors Influencing Farmers’ Willingness to Plant Agroforestry

Trees in Ekiti State 60

Table 4.5: Farmers’ attitude towards agroforestry tree planting and engagement

in other agroforestry practices in Ekiti State. 64

Table 4.6: Farmers’ Constraints to Agroforestry tree planting and engagement in

other agroforestry practices in Ekiti State. 68

vii

Abstract

This study examined the factors influencing farmers’ willingness to engage in agroforestry

practice in Ekiti State, Nigeria using cross-section data. Multi-stage and random sampling

techniques were used to select 180 respondents. The analytical techniques involved descriptive

and inferential statistics. It was shown that majority (50.60%) of the respondents were within

26-50 years age bracket while the average age of the farmers was 51 years. Majority of the

sampled farmers (92.20%) were male. The greatest percentage of 83.30% of the farmers were

married while 15%, 1.10% and 0.60% were single, widow and divorced, respectively. Also,

majority (83.30%) of the farmers had formal education, while 16.70% of them never attended

school. Out of those that had formal education, 35.60% of them attended primary school,

26.10% attended secondary school or its equivalent, while 21.70% had one form of higher

education certificate. The average years of schooling of the farmers was 9 years. The study also

shown that majority (66.70%) of the respondents had farming as their primary occupation, while

33.30% had farming as their secondary occupation. Out of 66.70% of them that had farming as

their secondary education, 16.10%, 9.40% and 7.20% were civil servants, traders and artisans,

respectively. The probit model result indicates that education (years of schooling), farm distance

to farmers’ residents, farming status, and land ownership positively influenced farmers’

willingness to plant agroforestry trees in the study area. Information on the agroforestry systems

or practices adopted by the farmers showed that majority (46.10%) of the respondents were

willing to combine agroforest tree species with cocoa and 80% of those willing to plant

agroforestry trees were to practice cocoa agroforest. About 28% of the respondents were willing

to combine agroforestry tree species with arable crops and 53.20% of those that were willing to

plant agroforestry trees were willing to plant it with arable crops. The mean scores and

standard deviations of farmers’ attitude towards agroforestry tree planting and engagement in

other agroforestry practices showed that the farmers expressed positive attitude toward 15

statements out of the 16 statements bordering on agroforestry practices. However, only one

statement “farmers do not loose their benefits of participating in other agricultural programmes

if engaging in agroforestry practice” was perceived by the farmers negatively. In this study,

specific issue which elicited most favourable positive attitude from the farmers is “engaging in

agroforestry practice is necessary to achieve increased agricultural productivity”. However, the

negative statement that farmers disagree with most on their attitude towards engaging in

agroforestry practices is “most farmers are not willing to plant agroforestry trees due to lack of

fund”. The factor analysis revealed that the constraints faced by farmers in planting

agroforestry trees and engaging in other agroforestry practices are techno-information, cost and

public policies constraint, technical/institutional support constraint, land, belief and risk taking

constraint and agricultural extension/planting materials constraint. As verified through this

study, farmers must be properly given needed attention through extension activities on

agroforestry practices that can encourage them to engage in agroforestry practice.

Promulgations on land use should be farmers’ friendly enough in order to encourage them to

plant agroforestry trees and make them have the confidence to reap the benefits of planting trees

that may still come to them several years later. Other technical supports such as credit must be

given by government agencies and non-governmental organizations (NGOs) in other to

encourage farmers to engage in agroforestry practices because of the benefits that can be

derived from this both by the farmers and the society at large.

viii

CHAPTER ONE

INTRODUCTION

1.1 Background Information

Tree planting was conceived as a potential strategy to meet the needs of local people and

protect the environment in the 1970s (Abegunde, 1999). The worldwide interest in tree planting

and management gave birth to several popular terms with “forestry” endings such as social

forestry, community forestry and agroforestry (Tamale, 1995; Nair, 1993; Foley and Barnard,

1984). Although these terms are new names for age-old practices, specialists maintained the

distinctions among them defining a precise technical meaning (Barraclough & Ghimire, 1995).

Social forestry as an umbrella term includes the practice of planting or using trees to pursue

social objectives through delivery of benefit to the local people. Community forestry, farm

forestry and agroforestry are all forms of social forestry (Hobley, 1996; Nair, 1993; Tamale,

1995). Community forestry refers either to portion of national forestland handed over to

communities or to the use of public or communal land for tree growing which is later handed

over to the community for the purpose of management (Hobley, 1996; Nair, 1993; Tamale,

1995)

On the other hand, agroforestry is a collective name for all land-use systems and

practices where woody perennial plants are deliberately grown on the same land management

unit as agricultural crops and/or animals, either in spatial mixture or in temporal sequence

(Lundgren, 1987). There must be both ecological and economic interactions between the woody

and non-woody components to qualify as agroforestry (Rocheleau, 1989).

More simply put, Agroforestry is any land-use involving planting of trees or deliberate

retention of trees by farmers within the farm or homestead for a variety of purposes which

include wood, fodder, fruits, medicine, shade, soil improvement, water conservation etc

(Aturamu, 2005). Agroforestry is more than intercropping trees with food crops; it combines

crop and livestock production with forestry activities to improve or prevent further degradation

of ecosystems. Agroforestry systems normally involve two or more species of plants (or plants

and animals), at least one of which is a woody perennial and hence,two or more outputs.

Growing trees along with crops and livestock enhances crop yields, conserves soil and recycles

nutrients while producing fuelwood, fodder, fruit and timber {International Centre for Research

in Agroforestry (ICRAF), 1993}. Agroforestry can help mitigate deforestation because it

addresses in general, the issues of tree planting; combat land depletion because of its potential

for soil conservation and as a result contribute to the alleviation of rural poverty (ICRAF, 1993).

Agroforestry practices in Ekiti state can be described in two broad categories: farm -

based and forest-based. The farm-based practices deals with tree planting on and around

agricultural fields, tree wood lots and commercial crop under shade trees or food crops inter-

planted with commercial trees (Olajide, 2003). The forest-based practices involve specific

agricultural practices associated with forests where farmers collect food, fruits and gums (Tejani

& Lai, 1992). In this study, agroforestry is referred to as farm-based practices. Agroforestry trees

therefore involve those trees planted in and within home gardens, agricultural fields and

commercial trees interplanted with food crops. This does not exclude 'fruit trees' which are

limited to those that provide fruit for human food such as mangoes, citrus, as well as some nut-

bearing trees, such as walnuts. Agroforestry trees do not only yield useful products but also play

vital role as more permanent elements in the landscape, sustaining the capacity of the land to

feed people. Thus, agroforestry trees in this study also include large perennials such as

banana/plantain.

Several studies have indicated that access to agroforestry fruit trees reduces impact of

food shortage during the hunger periods of the year (Akinnifesi, Leakey, Ajayi, Sileshi,

Tchoundjeu, Matakala & Kwesiga,2008; Jones 2009; Mithofer, 2006; Williams 2009). An ex

ante impact analysis in western Nigeria indicated that agroforestry fruits can reduce vulnerability

of rural households to income poverty by 33% (Mithofer, Waibel & Akinnifesi., 2006).

Therefore, investment in agroforestry tree planting, conservation and commercialization

constitute a safety-net during the periods of famine, and provide income to women and children

(Ramadhani, 2002). White and Robinson (2000) indicated that most female headed households

tend to seek small-scale income generating activities like selling agroforestry fruits for raising

cash. Agroforestry also help to address some of the complex and challenging environmental

problems suchas marginal economics of rural resource management, disruption of the soil and

hydrologic cycles, air quality problems, loss of rare and endangered ecosystems, species and

populations, andhealth issues. As a result, research has been intensified on domestication

strategies: selection of priority species, germplasm collection and tree genetic improvement,

propagation systems and field management, harvesting and post-harvest technology, economic

analysis and market research (Akinnifesi et al., 2006, 2008). Agroforestry tree domestication is

aimed at promoting the cultivation of indigenous trees with economic potential as new cash

crops.

Despite the important role that agroforestry practices play in the food security and

livelihood of households in Nigeria, especially in Ekiti state, investments in the cultivation and

conservation of the trees by farm communities is quite low (Bello, 2003). In the literature, this

has been attributed to several reasons to include socio-economic factors, institutional factors (the

insecure tenure rights on trees and land), changes in demand for tree

products,biophysicalenvironmentalfactors and change of resource endowment. In his own

contribution, Adekanye (2002) hypothesized that land characteristics such as land and tree

tenure, as well as tenure rights; social economic and demographic characteristics; and cultural

norms affect farmers’ willingness to cultivate agroforestry trees. Benneh, (1987); Akinnifesi,

(2005) added that the institutional arrangements under which a person gains access to land

largely determines, among other things, what crops he can grow, how long he can till a particular

piece of land, his rights over the trees and fruits of his labour and his ability to undertake long-

term improvements on the land. Rogers (2003) also noted that family household power structure

(matrilineal and patrilineal system) and other socioeconomic characteristics have some

significant implication for farm enterprise choice. The cultivation and management of forest

trees is an important farm enterprise in the Southern Nigeria and in particular, Ekiti State.

According to Ramadhani (2002), tree tenure is a form of tree ownership belonging to the

state while communal tenure was defined as trees owned by the community as opposed to group

tree tenure defined as trees owned by a group of individuals having common interest, such as

fruit processing groups or tobacco growing farmers. Individual tree tenure was defined as the

sole or exclusive user rights on those trees that an individual household have planted, inherited

or managed. Aturamu (2008) added that under private user rights, farmers are expected to be

more willing to invest in the cultivation of fruit trees because they retain exclusive rights to the

benefits of such investments. They may however be less willing to invest in the development of

common property resources. This study was undertaken to investigate factors affecting farmer’s

willingness to plant and domesticate Agroforestry trees.

1.2 Problem Statement

Concerns over the food security situation in Nigeria are reflected in the Millennium

Development Goals (MDGs) to reduce the number of food insecure by half by 2015 (Aturamu,

2005). Given that land plays an important role in the livelihoods of the majority of Nigerians,

food security and poverty reduction cannot be achieved unless issues of access to land, security

of tenure and the capacity to engage in agroforestry practices in a sustainable manner are

addressed (Olu, 2004). Agroforestry practices can help in sustainability of land, especially tree

planting. Agroforestry is an important tool that can bridge up the gap between demand and

supply of wood and non-wood products (Denning, 2001). The overall agricultural situation has

deteriorated, creating a wide gap between the supply and demand for food locally (Alabi, 2003),

with consequent importation of food items that could as well be produced in Nigeria. Production

of some major crops that used to earn the country considerable foreign exchange has greatly

declined to such a level, causing a lot of embarrassment to the nation (Salako, 2009). For

instance, the production of cocoa as an important agroforestry crop in Nigeria had witnessed a

downward trend, thereby reducing the country’s world market share to about 6% and its rank to

5th world largest cocoa producer till 2005 (Folayan, Daramola & Oguntade, 2006; Kwanashie,

Ajilima & Garba, 1998).

In addition, rural (wood fuel) supplies appear to be steadily collapsing in south west, especially

in Ekiti State. The situation has been worsening such that (wood fuel tonnage) shortfalls were

3.4, 6.8 and 8.0 in 1995, 2000 and 2003 respectively. The report of Ekiti State Ministry of

Environment (2004) projected the shortfalls to be 17.6 by the year 2015. In the quest to provide

food and fibre to an expanding human population, the provision of agriculture-based ecosystem

services that help to moderate climate change is increasingly under threat (FAO, 2007). As high

potential land becomes less available and the rural human population increases, farming is

extending into more fragile lands, undermining the natural resource capital base (Salako, 2009).

The damage to landbased ecosystems is exacerbated as agriculture is expanded to marginal and

environmentally fragile areas.To address this ugly trend, there have been supports by Ekiti state

Government to provide tree seedlings through agroforestry and afforestation programmes. To

buttress this fact, the State government in 2007 distributed about 200, 000 major tree crop

seedlings with other chemicals to farmers at highly subsidized rate (Ekiti State Government,

2007). Despite this effort, not much was achieved by the government in terms of improved

agroforestry farming and production in the State. Oriloye (2005) however confirmed that,

farmers irrespective of the support accorded to them have negatively responded to agroforestry

tree planting.

A lot of factors could be responsible for this. For instance, Adebayo (2006) observed that

access to land for permanent cropping is extremely limited in Ekiti due to land tenure structure

and current population growth rates. Moreover, Dairo (2006) stated that high degrees of

uncertainty over tenure security prevail in Ekiti state, and this according to the author reduces

incentives of farmers to involve in tree conservation and management practices. In addition,

Arnold (1991) observed that there is increasing evidence that property rights regimes play a

central role in the use and management of natural resources.

However, the fact that tenure security and other socio-economic attributes of smallholders

can influence their willingness to involve in soil conservation practice such as agroforestry

farming is often neglected by both researchers and development practitioners (Usman,

2003).Many researchers have devoted considerable time to the issue of tenure and its effects on

agroforestry tree production, for example those by Kohlin & Parks (2001); German (2009), their

studies focused on domestication, conservation and management of community wood lots. It is

imperative to state that none of these studies had attempted to ascertain the factors influencing

farmers’ willingness to engage in agroforestry practice. Therefore, it is of a particular interest to

understand the determinants of farmers’ willingness to plant agroforestry trees in the area, their

attitudes toward agroforestry tree cultivation and engagement in other agroforestry practices and

major constraints to agroforestry tree planting in the area.Therefore, this study aims to fill these

gaps in knowledge.

1.3 Objectives of the Study

The broad objective of this research is to determine the factors that influence farmers’

willingness to engage in agroforestry practices in the study area. Specifically, the study sought

to:

(i) describe the socioeconomic characteristics of farmers in the study area;

(ii) describe the associated land tenure systems and other agroforestry practices used by the

farmers in the study area;

(iii) examine the factors influencing farmers’ willingness to engage inagroforestry practice in

the study area;

(iv) determine farmers’ attitudes toward agroforestry tree planting and engagement in

other agroforestry practices in the study area;

(v) determine farmers’ constraints to agroforestry tree planting and engagement in

other agroforestry practices in the study area; and

(vi) make recommendations based on the findings.

1.4 Research Hypotheses

Based on the stated objectives of the study, the following hypotheses were tested:

(i) socio-economic characteristics of the farmers have no significant influence on

their willingness-to-plant agroforestry trees in the study area.

(ii) farm-specific and institutional factors do not influence the willingness of the

farmers to engage in agroforestry practice in the study area.

1.5 Justification of the Study

Increasing pressure on limited land resources is a problem facing rural communities in

Ekiti State (Adekanye 2002). Subsistence farmers in these areas practice traditional bush fallow,

clearing and burning bush at short intervals to grow annual food crops. The problem of

population growth coupled with economic pressure has resulted in a high rate of deforestation of

the state’s Agroforestry trees (Bello 2006). Deforestation has also been on the increase due to the

increasing demand for fuelwood, tree fodder, timber, poles and agricultural land. Soil erosion,

shortage of fuelwood, land degradation, siltation of water bodies and lowering of agricultural

production usually result from deforestation. Over-cropping by farmers has also resulted in loss

of vegetation, which allows for easy soil erosion with its consequent depletion of soil fertility.

This goes a long way to result in wood and non wood products decline and thus leads to poverty

and / or hunger (Gouyon 1992).

Currently in Ekiti state, the area of closed forest is declining by an estimated 0.4% per

year and the area of savanna woodland is shrinking by 0.5% a year (Adekanye, 2002).

Approximately 4 ha of tree cover are lost yearly through improper farming practices and over

exploitation of wood resources (Adekanye, 2002). Due to the small land area owned by most

farmers in these forest areas, there has been a problem of encroachment on forest reserves by

farmers for agricultural activities which may result in excessive destruction of tree cover or

vegetation. The traditional farming system is shifting cultivation and its productivity depends

largely on the fertility of the soil, which is usually maintained by long fallow periods (Bello,

2003). With the depletion of communal forests and increasing pressures on the forest reserves, a

better management system has to be found to reduce degradation even further, and guarantee the

future of the existing forest reserve and it is for this reason that agroforestry as a better land use

system has been suggested. The result of this study would therefore serve to improve the system

as well as pave way for future research works and serve as a reference point or benchmark for

further studies in agroforestry and the study area in particular.

The result of the study will also be able to shape the context in which farmers make

decisions about where and when to invest time and resources in planting and managing trees.

Finally, the study will come up with suggestions on how farmers will be encouraged to protect

existing vegetation and invest in new agroforestry systems when they have secure rights to the

products generated by the trees.

The rationale behind ‘Willingness-to-engage’ studies is that they indicate the value that

individuals attach to a good or service, which in turn predicts their likely contribution to its

sustenance (Boadu, 1993). By understanding the factors that have direct impact on the farmers’

decision to engage in agroforestry practice, as described by the farmers themselves, this study

will provide information that could be used to help decide the appropriate technology, and more

so provide considerable assurance of its maintenance and sustainability.

CHAPTER TWO

LITERATURE REVIEW

2.1 Conceptual Framework

(i) Agroforestry

The main objectives of agroforestry activities are to plant and protect trees and forests,

and to ensure the continued provision of the services and economic products they provide

(Adekunle, 2002). Although there are numerous definitions of agroforestry, one that reflects the

nature of existing Ekiti state agroforestry system is the one defined by Lundgren, (1982). He

defined Agroforestry as “a collective name for all land-use systems and practices where woody

perennial (trees, shrubs, palms, bamboos etc.) are deliberately grown on the same land

management unit as agricultural crops and/or animals, either in spatial mixture or in temporal

sequence”. Lundgren stated that there must be significant ecological and economic interactions

between the woody and non-woody components.

Leakey (1996) also defined agroforestry as “a dynamic, ecologically based, natural

resource management system that through the integration of trees in farm-and rangeland,

diversifies and sustains small holder production for increased social, economic and

environmental benefits”. Agroforestry is practiced for a variety of objectives and represents an

interface between agriculture and forestry and encompasses mixed land use practices (Nair,

1993). These practices have been developed primarily in response to the special needs and

conditions in Nigeria that have not been satisfactorily addressed by advances in conventional

agriculture or forestry (Nair, 1993). Nair further added that, the term agroforestry is used to

denote practices ranging from simple forms of shifting cultivation to complex hedgerow

intercropping systems; systems including varying densities of tree stands ranging from widely-

scattered trees, to the high-density multistoried home gardens; and systems in which trees play a

predominantly service role (e.g. windbreaks) to those in which they provide the main

commercial product (e.g., intercropping with plantation crops). It needs to be re-emphasized that

one concept is common to all these diverse agroforestry systems: the purposeful growing or

deliberate retention of trees with crops and / or animals in interacting combinations for multiple

products or benefits from the same management unit. This is the essence of agroforestry (Nair.

1993). Examples of these agroforestry trees are Mangifera indica, Anacardium occidentale,

Citrus species, Psidium guajava, Tamarindus indica, and some indigenous species such as

Parkia biglobosa, Vitellaria paradoxa, Adansonia digitata, Elaise guineensis, Azadirachta

indica and irvinga gabonenesis(Atolagbe, 2002).

Importance of Agroforestry

Agroforestry combines production and service roles (Daily, 2007). Agroforestry leads to

the production of some economic products such as food, fodder, fuelwood, medicinal

substances, gums and resins, tannins, essential oils, fibres and waxes (Meinzen-Dick, Knox,

Place & Swallow, 2002). Oram (1993) reported that agroforestry provides a wider range of

products, more secure subsistence or more cash income from wood products to enable the farmer

to buy food. Nair (1993) indicated that the combination of several types of products which are

both subsistence and income generating, helps farmers to meet their basic needs and minimizes

the risk of the production system’s total failure. In Ekiti State, agroforestry home gardens play

an essential role in producing foodstuffs and other subsistence or commercial products and also

meeting most of the requirements for sustainability (Torquebiau, 1992). Nair (1993) found that

in tree home gardens, the production is for home consumption, but any marketable surplus can

provide a safe guard against future crop failures and security for interval between the harvests.

Some important service roles of agroforestry are: soil conservation, either erosion control

(presence of a permanent soil cover, barrier effect against run-off), soil fertility maintenance

(incorporation of organic matter into the soil, nutrient pumping from the deep layers of the soil

through the tree’s roots, these nutrients then improve the crops through litter and mulch, nitrogen

fixation) or soil physical properties maintenance (Young, 2000). He indicated that the creation of

a microclimate, which can be beneficial to certain plants or animals, for example modifications

of light, temperature, humidity or wind, can also help fight weed proliferation.

(ii). Agrisilviculture

Agrisilviculture is the intercropping of timber and fuelwood species and/or fruit and

other useful trees with vegetables and other crops in a common space, at the same time

(Lungren, 1982). In agrisilviculture, some of the components of the field are cultivated through

practices like weeding and thinning.Agrisilviculture is examined as a solution to the increasing

degradation of soils in the humid tropics, which has resulted from increasing pressures from

shifting cultivations. Agrisilviculture is the simultaneous husbandry of forest tree crops and food

crops (Rogers, 2000).

(iii). Taungya System

The Taungya system is a system of agriculture whereby villagers and sometimes forest

plantation workers are given the right to cultivate agricultural crops during the early stages of

forest plantation establishment. Cultivation is often allowed to continue until trees shade crops

due to canopy closure (Caveness and Kurtz, 2006). During the early stage of forest plantation

establishment, intercropping of young trees with food crops is beneficial in terms of tree

survival, food crop production, financial income to the peasant farmers and reduction of forest

plantation establishment costs. The system is therefore suitable and should be sustained (Salako,

1982).

(iv). Community Forestry

Community forestry is an evolving branch of forestry whereby the local community

plays a significant role in forest management and land use decision making by themselves in

the facilitating support of government as well as change agents (Byron, Curtis, and Mackay,

2005). It involves the participation and collaboration of various stakeholders including

Community, Government and Non-government Organisations (NGO’s). The level of

involvement of each of these groups is dependent on the specific community forest project, the

management system in use and the region (Scherr and Frankel 2002).

(v). Farm Forestry

Farm forestry is defined as the combination of forestry activities with cropping and/or

livestock production. The focus of the forestry activity is primarily commercial, although there

may also be other objectives including shade and shelter for stock or crops, natural resources

management including soil and water protection(Benneh, 1987). Ayling (1999) added that a

broad definition of farm forestry includes any tree on farm land which are managed to produce

saleable products such as timber, oil, tannin, charcoal or carbon credits. The main objectives of

farm forestry are to increase the total productivity of the land by producing timber products; help

in controlling soil erosion; reduce salinity and provide shelter for livestock;improved natural

resource management - by controlling rising groundwater, wind- and water induced soil erosion.

(vi). Farmers’ Willingness

‘Willingness’ is defined as the voluntary decision to make full use of an innovation

(engage in agroforestry practice) as the best course of action available (Rogers, 2000). The

reverse ‘Unwillingness’ is the decision not to engage.The decision to adopt or to reject occurs as

a process, the innovation-decision process. This process begins when individuals (or any other

decision-making unit) first learn about the existence of the technology, forming an attitude

towards it, deciding to accept or reject, to implement or use it, and finally to confirm their

decision (Adekunle & Bakare, 2004).

2.2 Socio-economic characteristics of Agroforestry Farmers

Raintree (1991) pointed out that the degree of socio-economic stratification, which exists

within a locality, is important in determining the adoption of a new technology particularly if it

is highly attached to factors, which govern access to resources. The stratification of a community

can be on the basis of wealth, landholding size, gender, age, ethnicity, religion, education etc.

For example, results of studies by Lundgren (1987) and Nweke (1990) as quoted by Njoku

(1991) indicated that the level of tree planting adoption on smallholder farms is influenced by

the farmers’ age, literacy rate, access to material inputs of technology and food security needs.

Eckman (1992) deduced from his studies that individuals within a household may have different

rights depending on gender, birth or intra-family status.

Age

The age of farmers is often considered to be an indicator of willingness to plant

agroforestry trees, with the assumption that younger farmers are more likely to adapt to change.

However, there is conflicting evidence on this relationship, with some researchers finding no

significant relationship between age and tree planting decisions (Guerin, 1994; Curtis et al.,

2000; Cary et al., 2002; Lockie, Lawrence, Dale and Taylor, 2002). To further confound the

matter, Duriappah (1996) found a converse relationship between age and willingness to plant

agroforestry trees, revealing that the age group most likely to identify stage of life as a constraint

was those under 30 due to emerging family commitments, savings and debt.

However, others have found a more direct relationship between agroforestry tree planting

decisions and age. Denning (2001) found that younger farmers were more likely to adopt new

technologies, while a Belgian study (Vanslembrouck, 2002) investigating the willingness of

farmers to participate in agri-environmental measures, found that as the age of farmers

increased, there was a corresponding decrease in their willingness to participate in

environmental schemes. Moreover, while Eckman (1992) found no significant relationship

between farmers’ age and their decision to domesticate fruit trees, he did find significant

relationships between age and the adoption of tree planting and actions to treat erosion. It was

found that adoption rates increased for tree planting to a maximum adoption rate at ages 45-55,

and then decreased for age cohorts beyond this.

A study conducted in the Burdekin Dry Tropics region also found age to be correlated

with land manager’ willingness to adopt innovative practices, with the older the manager, the

less likely is adoption (Greiner, Stoeckl, Stokes, Herr and Bachmaier, 2003). Further,

Chukwuebuka, Rashid & Alfrad (2004) found that people over the age of 65 are significantly

more likely to identify their stage of life as an important factor affecting their decision-making

about changing management practices. It is believed that the long-term commitment necessary to

implement changed practices, combined with short-term economic costs, provides little incentive

for land managers approaching retirement. Under this argument, as changed land management

practices often require a huge knowledge and attitudinal shift, the ‘age barrier’ may become a

significant constraint to encouraging widespread change. So, the relationship is unclear,

however, as Cary et al. (2002) argue whatever relationship does exist is unlikely to be linear, and

will likely be confounded by other factors.

Gender

The relationship between gender and the adoption of change practices is also unclear.

There is certainly evidence that women are a driving force for natural resource management

(Davidson and Stratford, 2000). Additionally, Okyere et al (2000) argued that rural women are

under-represented in formal arenas of power, with the implication that women’s real

contribution to natural resource management is underplayed. Indeed, Vanclay (2004) suggests

that the complexity of modern farm management partnerships, where women play a major role,

is often ignored by extension programs that are targeted predominantly towards male farmers.

Certainly if extension or incentive programs are to be successful their proponents need to be

cognisant of the changing role of women and the emerging issues (Vanclay, 2004).

Education

It has been assumed that formal educational levels are directly correlated with

willingness to plant agroforestry trees. However, some evidence suggests that there is little direct

relationship and that the possession of formal education qualifications does not increase the

likelihood of an individual adopting agroforestry practices (Curtis, MacKay, van Nouhuys,

Lockwood, Byron and Graham, 2000; Cary & Barr., 2002). Alternatively, some studies have

found that willingness to participate in tree planting is influenced by education, with the higher

the education level, the more likelihood of participation in some practices (Vanslembrouck,

2002). Finlay (2004) further found that the likelihood of participating in Land care is associated

with education levels, so where it can be assumed that Land care membership is correlated with

an increased adoption of new practices, then the influence of education is strong. Further,

participation in training courses and field days does appear to increase adoption of natural

resource management practices (Cary et al., 2002). Indirectly, education may be important in

enabling farmers to seek off-farm income, and may therefore increase their financial capacity to

invest in changed practices (Cary et al., 2002).

2.3 land Tenure system and other agroforestry practices

One of the critical factors that have been given consideration in determining the potential

acceptability and viability of agroforestry is land tenure systems and tree ownership. Adekunle

(2002) defined land tenure, or land tenure system as a set of rules defining the customary and

legal rights which govern the social relations between individuals or groups in their access and

use of natural resources. Tenure (Kessler, 2006) encompasses land and all those natural

resources which are directly related to it (water, trees, pastures etc.).

Francis (2009) gave the assertion that patterns of tree planting adoption will be shaped by

the structure of opportunities and constraints presented by the rules of tenure. Caveness and

Kurtz (2006) found out that land ownership was one of the two predominant factors (the other

was labour) affecting the adoption of agroforestry practices. Raintree (1991) has also found that

if a ‘would be user’ does not have security over the intended planting location; adoption of the

tree planting innovation may be quite out of question. Kolade (2007) also noted that in vast

agricultural lands of Tropical Africa, agroforestry has yet to make a break through. The reason is

largely due to the flexible system of land tenure as well as its attendant insecurity.

Land tenure reforms in Nigeria has been advocated by Benneh (1987) on the grounds that

the old system does not provide security of tenure; that it discourages the investment of natural

resources and does not encourage investments which bring about development in the land.

Miniature farm sizes and the manner in which they are fragmented and scattered, he argues,

constitute an obstacle to farm improvement for they do not enable farmers to take advantage of

economies of scale in production. The old system, he claims prevent the use of farmland as

collateral for credit, also it discourages the adoption of innovations and individual initiative in

farming.

Governments in many states in Nigeria are aware of the need for tenure reformation. For

example in Ondo state, the government among others prohibited ejection of tenants without

governmental approval (Arhin, 2008). Okyere, Charter & Blench (2010) pointed out that many

government interventions at tenure reformation have given rise to clashes between landowners

and tenants. They pointed out that despite attempts by government to intervene by legislature;

the bulk of statutory law relating to rural land has remained migratory. Most land matters are

handed by linage elders and local chiefs in accordance with their interpretation of indigenous

land laws.

Leach and Mearns (1988) asserted that tenure issues in agroforestry do not relate to land

tenure only but also to tree tenure. The distinction between land and tree tenure is crucial to the

participation of rural communities in projects involving tree growing. Fortmann (1990) has listed

four major categories of rights that make the bundle, which comprises tree tenure: the right to

plant, the right to use, the right to dispose and the right to own or inherit. Each of these

categories or combinations of any, Fortmann emphasizes, have restrictions on community

participation in agroforestry projects in several African countries. He also points out that tree

tenure issues in the community intended for the project needs careful examination to avoid

problems like the loss of rights, particularly to other uses of land or the trees on it and loss of

gathering rights among others. The complexity of tenure issues is believed to have discouraged

many tenants from growing trees. Francis (2009) said that in areas where land pressure is more

intense and other terms of tenancy are more definite, permanent tenants, many of whom grow

food crops under tenancy leases, may be disallowed from planting tree.

Tenure insecurity and its characteristics

Tenure insecurity is a characteristic of many farmers in many parts of the less developed

countries. It arises from a number of sources, depending on the historical pattern of land

acquisition and settlement (Meinzen-Dick et al., 2002). According to Adams (2000), tenure

insecurity is viewed as the landholders’ perception of the probability of loosing land within some

future time period. More broadly it can be defined as the landholders’ perception of the

likelihood of losing a specific right in land such as the right to cultivate, graze, fallow, transfer or

mortgage. Parallel with that, according to Place & Otsuka (2000), land tenure security exists

when an individual perceives that he or she has rights to a piece of land on a continuous basis,

free from imposition or interference from outside sources, as well as the ability to reap the

benefits of labour and capital investment in the land, either in use or upon transfer to another

holder. The definitions show that duration of tenure is an important and necessary component of

tenure security. Duration of tenure refers to the temporal extent of one’s right. Secure tenure is

created when one holds a sufficient time horizon to collect the benefits of one’s investments

(Meinzen-Dick, 2002).

Trends in land and tree tenures

The land tenure system is one of the most important components of any land use or

farming system. The institutional arrangements under which a person gains access to land

largely determines, among other things, what crops he can grow, how long he can till a particular

piece of land, his rights over the fruits of his labour and his ability to undertake long-term

improvements on the land (Benneh, 1987; Atolagbe, 2002). A land tenure system is the body of

rights and duties which regulates the use and control of land. It is the terms and conditions under

which land is held, used and transacted (Adams, 2000). These customary property systems often

distinguish between tree and the land on which they grow, and may vary between regions and

countries, and areas within the country (Alabi, 2006). Land tenure, which refers to land user

rights and security are among the cited land related factors affecting agroforestry tree

domestication. Tchale and Lunduka (2000) observed that land user rights, which are temporal,

create insecurity and therefore a disincentive to farmers to domesticate or plant fruit trees.

2.4 Factors Influencing Farmers’ Willingness to Plant Agroforestry Trees

Generally, the factors influencing agroforestry tree planting decision may not be much

different from those influencing the adoption of agricultural innovations (Arnold, 1987). There

are several factors that influence the decision to plant, retain or take care of trees planted on

farmlands. Some of them are characteristics of the innovation (agroforestry) itself, while others

accrue from the potential adopters (the agroforestry tree farmers). In their own view, Burley &

Steward (1982) as quoted by FAO (1986) suggested that the major conditions which must be

satisfied before rural people will be willing to plant trees are economic, social/cultural and

environmental.

Economic: - There must be sufficient land, capital and labour resources available to make tree

growing possible and to cover the expenses of planting, cultivating, harvesting and marketing

trees and their products. The benefits of tree cultivation and management, both in economic and

financial terms, must exceed the net benefits from alternative resources and agricultural

management, strategies as well as costs of production.

Social/ Cultural: -Changes in productive relationships and in the pattern of resource ownership

which might be brought about by tree cultivation must fall within culturally accepted strategies

for resource distribution. Further, appropriate and culturally sensitive technical expertise must be

available.

Environmental: - Interventions or adaptive strategies must be responsive to the availability of

water, to temperature regimes, to soil types and to other characteristics of the natural

environment.In contrast to the broad categorization of factors that influence tree growing above,

Agyemang (1991) concluded that the specific factors that should receive prominent attention of

farmer’s willingness to plant agroforestry trees are: land tenure and tree ownership, institutional

support systems, labour requirement, management complexity for traditional farmers, long term

nature of benefits and social security and equity.

Like other innovation adoptions, the incorporation of trees on- farm in the form of

agroforestry is a complicated process that is influenced not only by physical factors but also by a

number of socio-economic factors (Malla, 2000). There had been high socio-economic

inequalities in farming communities in the developing countries and level of participation in any

production activity is influenced by the absence of convergent interests located in the socio-

economic structure of the community (Agarwal, 2002).

Agroforestry as a science is in its infancy and it is argued that agriculture and forestry

have the same clientele, farmers. So forestry has to take lessons from agriculture where study of

social structure has proved helpful in designing socially desirable agricultural technologies and

their implementation (Ayling, 1999). If the goal is to convince people to grow trees, then the

study of socio-economic aspects becomes important to identify the motivation and de-motivation

to grow trees (Daily, 2007; Oke &Odebiyi, 2007). Rocheleau and Raintree, (1986) contributed

that socio-economic considerations are increasingly becoming important in technology diffusion

and adoption processes. This is more so for agricultural, forestry, agroforestry and related

innovations, which are meant for the diverse environments and circumstances of rural people.

The need to examine socio-economic factors influencing the decision to adopt

agroforestry tree planting has also been highlighted by Raintree (1991) in his evaluation of the

storm over Eucalyptus in social forestry programmes in India. Among his findings he stated that:

“On closer examination of the issues, it appears that while most of the debate has been couched

on ecological terms, many of the underlying issues are social and economic in nature. The

debate demonstrated how important the socio-economic context of the intended user can be in

determining whether or not he or she will be able to make effective use of a particular tree

planting practice.

Again, Hoskin (1987) gives a partial list of socio-economic issues that must be taken into

consideration if farm families are to involve in agroforestry tree planting as: local uses and

knowledge of trees, tenure, organization, conservation, landlessness, enterprises and marketing,

labour, nutrition, gender and age. In his analysis on socio-economic context and development

strategy for tree growing, Raintree (1991) pointed out that factors that are relevant to consider

under the broad heading of socio-economic will vary from place to place. Among the most

important are: degree of local socio-economic stratification (by wealth, land holding size,

gender, ethnic group etc.); access to resources (land and tenure); overall economic development

strategy; general approach to tree planting programmes, opportunity for relocation of resources;

access to credit; processing technology and marketing assistance etc. It could be seen from the

above discourse that the socio-economic factors that affect the decision to plant agroforestry

trees are many and differ from place to place and it is time specific. In his own view, Kelechi

(2007) opined that in spite of these variations, the major socio-economic factors that are

necessary in agroforestry tree planting decision by individuals are land tenure and ownership

issues, socio-economic stratification, and labour availability.

Also an analysis on farmer adoption of agroforestry technologies by Adedire (2004)

draws a direct relationship between empirical studies on adoption of green revolution in

developing countries and that of agroforestry and lists the following as the major factors that

influence agroforestry tree planting: Labour requirements, Capital, Market, and Institutions.

(i) Labour Requirements

One of the major factors influencing farmers’ decision to plant agroforestry trees is

labour requirement (Arnold, 1987). He stated that a farmer’s decision to grow trees can be

influenced by two main factors: one is the high cost of labour and capital and the other is the

potential of income to be generated from tree as distinct from food production in farmers’

production objectives. Njoku (1991) in his studies on adoption of improved oil palm production

found that a major constraint was high cost of labour. He concluded that many new technologies

require intense labour use, which contrasts greatly with the limited amount of labour expended

in the traditional wild oil palm groves and that smallholder farmers must hire expensive labour

to implement the improved technologies. The strong competition for household labour with

other activities in the farming system particularly during critical periods in the agricultural

season would obviously influence farmers’ decision about adopting agroforestry. This has been

found for example to be true of alley farming (Kang and Wilson, 2009).

(ii) Capital

One of the captivating arguments about capital requirements and tree growing decision

has been put forward by Arnold (1987) as; “It is widely argued that the lengthy production

period and the incidence of most of the costs at the time of establishment, create financial

problems for farmers in adopting practices involving tree growing”. It is this argument that

underlies the widespread provision of planting stock, either free or at subsidized prices in

programmes to support tree growing. However, the evidence that tree systems are favoured by

farmers when capital is scarce because trees require less investment than alternative crops and/

or provide substitutes for purchased inputs example fertilizer and herbicides suggests that

improved access to capital would not necessarily increase adoption of agroforestry tree planting.

In support of Arnold argument, Hyman (2000) in his investigation on pulpwood production in

the Philippines concluded that capital could be an impediment to investment in larger rotation

timber species grown as cash crops. In this situation however, the constraint seems to be not the

capital cost of establishment but lengthy period that elapses before there is any return. Oke et al

(2007) argued that adoptions of scale-neutral innovations are not necessarily inhibited by credit

constraints. They stated that the profitability of innovations often induces small-scale farmers to

find the cash required for adoption from their relatively meagre resources.

Contrary to the above discourse, capital in the form of savings and credit is required in order to

form many agricultural and agroforestry innovations. Therefore differential access to capital is

frequently cited as a major factor determining adoption rates (Mercer and Hyde, 1992). For

example, Owusu-Sekyere (1991) concluded that participating farmers in an agroforestry project

complained that they needed credit in the form of cash to pay for extra labour required to

maintain their agroforestry plots and that without attending to farmers cash needs project

implementation can be very slow.

(iii) Markets

Marketing of products could serve as a great incentive or disincentive to virtually all

productive ventures. According to Cukwuebuka et al (1990), the important criteria for farmers to

grow any new tree species, depend among others on assured demand for the produce and really

market outlets, minimum support price, at which tree growing is profitable; and generation of

cash surplus as the most powerful incentive for most farmers.

(iv) Institutions

Policy analysis defines institutions as rules, norms and values that shape our behaviour.

Sometimes known as the rules of the game; institutions can be:

• Both formal (example, laws that govern land tenure, market transactions or civil rights)

and informal (example, social customs and conventions);

• Created (example, as a result of deliberate political or policy decisions) or may evolve

overtime;

• Present at local, organizational, national, and international levels.

In many developing countries, policies and institutions discriminate against those with few

assets and disadvantage poor people. Such discriminatory policies and institutions undermine

development efforts to eradicate poverty. It is now generally accepted that significant and

sustainable gains in poverty reduction cannot be achieved unless accompanied by pro-poor

reforms to domestic and international policies and institutions (Ashley and Carney, 1999).

2.5 Attitudinal and behavioural pattern of Farmers toward Agroforestry practice

Many different variables may be responsible for farmers’ attitude or behaviour toward

agroforestry practice (Hoskin, 1987). Age is a variable with mixed results, positive and negative

effects onagroforestry. Education level has also been widely regarded as having a positive

relationshipwith adoption of agroforestry practices (Raintree, 1991). Other factors associated

with a positive relationship includeinvolvement in local organizations, farm size, income, land

ownership or tenure, familysize, and familiarity with conservation practices.Boadu (1993)

pointed out that illiteracy was the mainreason for non-adoption of agroforestry practice by

farmers.The farmers considered this practice harmful for their agricultural crops due to lack of

education andawareness. Nweke (1990) also reported that educationwas the main and vital

weapon for bringing a positivechange in the behavioural pattern of individual farmer,

whichdevelops knowledge and other desirable qualities ofmind and general competence. Hence,

thelevel of illiteracy among the farmers is much influencing theirbehaviour to adopt agroforestry

practices. It is one ofthe main hindrances because it creates ignorance andunawareness among

the individuals.

Attitude like knowledge and skill, determine the decision to practice agroforestry

(Campbell 1992). Farmers’ attitudes aremore likely to correspond with their

behaviours.Therefore, transforming factors such as youth and women participation in

agriculturalproduction, extension contact, training and practical demonstration of technologies,

knowledgeas well as access to micro-credit facilities are required to serve as opportunity to

change farmers’ attitude towards agroforestry practice in the study area.

2.6 Constraints to wider Agroforestry tree planting in Nigeria

Despite the concentration of agroforestry research in Nigeria and the presence of

empirical data confirming its benefits, agroforestry practices among smallholder farmers have

not expanded accordingly (Nweke, 1990). Food insecurity, soil erosion, shortages of fuelwood

and fodder and environmental degradation are still widespread. The following is an attempt to

assess the reasons why agroforestry in Nigeria has been unable to expand to meet its full

potential and to identify mechanisms for its promotion.

2.6.1 Lack of Widespread Understanding of the Benefits of Agroforestry

Agroforestry from the 1970s through the early 1990s was focused primarily on empirical

research (Akinnifesi, 2005). While this empirical work has generated a significant body of

scientific literature on agroforestry in Nigeria, it has been conducted primarily at research

stations or on plots leaving the farmers involved geographically isolated, preventing the

generation of collective initiatives (Adams, 2000).

This empirical focus has also meant that there is a lack of comprehensive, robust, and

widely applicable methodology for realistically assessing the benefits and impacts of

agroforestry practices (Nair, 1993). Although an increased emphasis on working with farmers’

groups has increased farmer-to-famer learning and opportunities to spread agroforestry, as of the

early 1990s only a few extension projects in Nigeria had evaluated the financial impact of

agroforestry or attempted to quantify its contribution to household income, food security and

welfare (Franzel and Scherr, 2002). These few projects, have demonstrated that agroforestry

increases household incomes, generates environmental benefits, and is particularly well suited to

poor and female farmers, but success stories are localized. Because case studies of these

successes have not been written-up or widely published, funders and governments have not been

presented with evidence of the broader applicability of agroforestry (Scherr, 2008).

2.6.2 Mass Agriculture’s Focus on Using Fertilizer and Pesticides

Demonstrating agroforestry’s large scale applicability is particularly important because

since the 1960s the focus of agricultural development has been “mass outreach agriculture.”

Mass agriculture includes methods to increase productivity and yields which can be widely

applied on millions of farms and across diverse regions. As a result, donors and governments

have prioritized agricultural development programs to increase access to fertilizers and

pesticides at the expense of methods like agroforestry and eco-agriculture (Scherr, 2008).

Despite their popularity, mass agriculture programmes face serious limitations. While

chemical fertilizers increase yields, overtime they contribute to soil degradation; in contrast,

agroforestry systems do not only increase yields but also restore soil fertility through the use of

nitrogen fixing species (Oriloye, 2005). In addition, chemical or petroleum based fertilizers are

often too expensive for smallholder farmers to purchase, with the rising price of fuel

exacerbating the problem (Franzel and Scherr, 2002). From a donor perspective, subsidized

fertilizer and programmes to increase yields demand on-going funding and can cost millions of

naira whereas agroforestry has the potential to be a sustainable, self-replicating investment.

World Agroforestry Centre economists have estimated the cost of training and equipping one

farm family to practice agroforestry to be about $2.50 (Akinnifesi, 2005).

2.6.3 Lack of Tree Seed Supply

A lack of tree seed is considered essential to the expansion of agroforestry tree planting

system. Even though there is demand for seeds from farmers, they are often unable to obtain

them because of cost or inadequate supply (Usman, 2003). Olu (2004) added that a reliable seed

supply and distribution system on a much greater scale is required to increase adoption of

agroforestry tree planting. At the moment there are few incentives for private sector investment

in this area. Some tree species require many years before they produce seeds, delaying

investment returns and locking producers into selected products. This time lag is particularly

detrimental when future markets for the variety of trees species are uncertain (Scherr and

Franzel, 2002).

2.6.4 Land Tenure insecurity among Smallholder Farmers

At the farm scale, the most important institutional arrangement affecting agroforestry tree

planting is property rights. Property rights shape farmers’ expectations of whether and how they

will be able to appropriate long-term benefits from investing in tree management and planting

(Meinzen-Dick, 2002). Property rights are particularly significant for smallholder farmers who

tend to be risk averse. Studies in Cameroon, Kenya, Mali, Uganda and Zambia have found that

tenants without long-term land rights are restricted in their ability to plant or harvest from trees

because of insecurity of tenure (Place, 1994a).

The literature also tends to suggest that incomplete property rights reinforce the poverty-

environment vicious circle (Duriappah, 1996; Scherr, 2008). This line of argument proposes that

insecure tenure rights to land and the imperfect functioning of land markets tend to reduce

incentives for smaller rural farmers to invest in long-term conservation measures such as

planting trees, and soil conservation structures.

Surprisingly, despite the well-thought-out theoretical links, the results from studies that link

tenure security and investment in conservation activities are contradictory and inconclusive. For

instance, some studies argued that tenure security is not important for conservation (Migot-

Adholla et al., 1991; Brasselle et al., 2002), while others argued that it is (Shiferaw & Holden,

1999; Place & Otsuka, 2000; Gabremedhin & Swinton, 2003; Kabubo, 2003). These different

findings are the result of differences either in the way tenure security is measured or in the way

the relationship between investments and tenure rights is empirically conceptualized (Kabubo

2003).

2.6.5 Market Constraints

Market constraints also play a significant role in hindering the scaling up of agroforestry.

Agroforestry extension and research has tended to emphasize increasing production levels of

trees and crops but these efforts have been undertaken with little regard for demand or price.

Recent work has shown that market conditions and institutions play a critical role in farmers’

decision to plant agroforestry trees (Place, 1994b).

For example, Scherr (2008) found that when the price of maize in Ondo state decreased,

farmers were more likely to use improved fallows to reduce the area under maize cultivation

allowing them to increase production of higher value cash crops on other fields. Market

instability also affects agroforestry strategies. In addition, Scherr and Frankel (2002) found that,

the price of fuelwood had a strong effect on the popularity of agroforestry in Western Nigeria.

Hence, if agroforestry is to be adopted on a scale that has meaningful economic, social and

environmental impacts, it is crucial that markets for agroforestry tree products are expanded. For

this to occur there must be stronger links between tree domestication and product

commercialization (Leakey 2006).

2.6.6 Lack of Sufficient Extension Work

The issue of appropriate extension work for increasing the scale of agroforestry is of

particular importance because agroforestry is a relatively ‘knowledge intensive’ practice,

reducing the likelihood that knowledge will spread easily on its own. Several researchers have

cited national extension systems in many sub-Saharan African countries as a major barrier to

scaling-up agroforestry (Scherr et al 2002). They note a lack of rigorous, organized and locally

adapted extension messages, the general weakness and limited resources of government

extension systems, lack of agroforestry training for extension workers, and the unclear

assignment of responsibility for agroforestry between agricultural and forestry extension

institutions. Research on agroforestry adoption in Central America indicates that particular

attention must be paid to improving institutional structures that provide information and

extension work (Nair, 1993).

2.6.7 Policy Constraints

There are significant policy based constraints to the expansion of agroforestry tree

planting in Nigeria. Experts in agroforestry are clear that an enabling policy environment that

favours smallholder rural development is an essential condition for the success of agroforestry

(Scherr et al 2002). They are equally clear in their belief that the lack of institutional support for

agroforestry is a major policy related constraint to agroforestry development in Africa and an

issue which has not been adequately addressed in agroforestry research.

2.7 Theoretical Framework

The theory reviewed in this work is utility theory. Utility theory is concerned with

people’s choices and decisions. It is concerned also with preferences and with judgments of

preferability, worth, value, goodness or any of a number of similar concepts (Fishburn, 1968).

This theory provides a methodological framework for the evaluation of alternative choices made

by individuals, firms and organizations. Utility refers to the satisfaction that each choice

provides to the decision maker. Thus, this theory assumes that any decision is made on the basis

of the utility maximization principle according to which the best choice is the one that provides

the highest utility (satisfaction) to the decision maker. This work hinges on this theory. To

measure the willingness of farmers to plant agroforestry trees in Ekiti State, which have the

potentials to meet their needs in terms of food, fibre, financial provision, environmental

protection and soil fertility improvement will be mostly preferred and these are the ones the

farmers will be willing to plant.

Utility theory is often used to explain the behaviour of individual consumers. In this case the

farmer plays the role of the decision maker that must decide whether to engage in agroforestry

practice or not. Farmer’s willingness may be subject to level of total utility subject to his or her

available income, prices, and other factors.

Different models have been suggested to explain the decision and willingness to adopt

new technologies(Tolman, 1967; Rogers, 2000). Akinnifesiet al(2006) have argued that there is

no single theory of causation that can embrace all aspects of adoption and explain the traditional

attitude of small farmers towards technologies in developing countries. According to Tolman

(1967), the adoption behaviour of an individual is a function of socioeconomic and

environmental factors and the adoption is endogenous to the sum of the interacting forces of

his/her situation. Following Tolman (1967), Aturamu (2005) adds that adoption behaviour is a

mental process governed by a set of intervening variables: individual needs, knowledge about

the technology, and individual perceptions about methods used in meeting those needs in a

specific environment. Nonetheless, these intervening variables are shown to depend on a set of

socioeconomic variables. Following Rogers (2000), willingness is defined as a decision to make

full use of an innovation as the best course of action, and rejection or non-adoption as a decision

not to adopt an innovation. In this study, it is therefore assumed that agroforestry tree planting is

ecologically feasible, economically efficient, and socially compatible in the study area. It will be

also assumed that for resource poor farmers, practicing agroforestry tree planting technology is a

better option and expect that farmers who adopt this technology will continue to adopt in the

future.

2.8 Analytical Framework

The framework of analysis of this work is reviewed under the following tools of analysis;

Probit model, Likert scale rating, and exploratory factor analysis.

2.8.1 The Probit Model

The probit model is a statistical probability model with two categories in the dependent

variable (Liao, 1994). Probit analysis is based on the cumulative normal probability distribution.

The binary dependent variable, y, takes on the values of zero and one. The outcomes of y are

mutually exclusive and exhaustive. The dependent variable, y, depends on k observable

variables xk where k=1,…,K (Aldrich & Nelson, 1984). While the values of zero and one were

observed for the dependent variable in the probit model, there was a latent, unobserved

continuous variable, y*.

k

k kk xy1

* ………………………………………..(1)

ε is IN (0, σ2)

The dummy variable, y, was observed and was determined by y* as follows.

y = { 1 if y* > 0, 0 otherwise ………………………………..(2)

The point of interest relates to the probability that y equals one. From the above equations, we

see that:

Prob (y=1) = Prob ( kk

k

k x1 > 0)

= Prob (ε > - kk

k

k x 1

= 1 – Φ (- )1 kk

k

k x …………………………………………(3)

Where Φ was the cumulative distribution function of ε (Liao, 1994). The probit model assumed

that the data will generate from a random sample of size N with a sample observation denoted by

i, i = 1,…,N. Thus the observations of y must be statistically independent of each other to rule

out serial correlation. Additionally, it is assumed that the independent variables (the responses to

the farmers’ willingness-to-plant agroforestry trees survey questions) were random variables.

The Maximum Likelihood Estimation (MLE) technique will be used to estimate probit model

parameters. MLE focused on choosing parameter estimates that give the highest probability or

likelihood of obtaining the observed sample y. The main principle of MLE is to choose as an

estimate of β the set of K numbers that would maximize the likelihood of having observed this

particular y (Aldrich & Nelson, 1984).

Ogar (2008) in his study of determining the factors influencing the perception of local

people as regard the use of forest management committee in management of community forest

used probit model. In the same vein, (Ali Chebil, Hafedh Nasr and Lokman Zaibet, 2009) used

probit regression to ascertain the factors affecting farmers’ willingness to adopt salt-tolerant

forage crops.

In this study, probit model will be used to determine the factors that influence farmers’

willingness to plant agroforestry tree. The explanatory variables to include in the probit model

are: level of education, annual income, gender, farm household head, age, household size,

extension contact, group membership, and marital status etc.

2.8.2 Likert Scale Rating Technique

A 4-point rating scale was employed to determine the attitude of the farmers towards

agroforestry tree planting and engagement in other agroforestry practices in the area. A rating

scale is a psychometric scale and bipolar scaling method (Wuensch, 2005) and a set of

categorized response items used in survey research to elicit information about a quantitative or a

qualitative attribute from respondents. In the social sciences, common examples are the Likert

scale and 1-10 rating scales in which a respondent selects the number which is considered to be a

true reflection of the perceived quality or opinion of the respondent on an item statement

(Andrich, 1978).

All the rating scales can be classified into one of the following four classifications: the

nominal, interval, ordinal and ratio levels (Andrich, 1978). Sometimes a four-point scale is used;

this is a forced choice method (Wuensch, 2005). In the case of this study where some of the

major interests are to determine the effects of land tenure system and property right on

agroforestry tree planting; and the attitude of the farmers towards agroforestry tree planting, an

ordinal level 4-point rating scale will be adopted. At the ordinal level, numbers indicate the

relative position of items rather than the magnitude of difference as in the case of nominal,

interval and ratio levels. The 4-point rating scale indicating attitudes of the farmers in this study

is used and named as follows: Strongly Agree (SA) = 4, Agree (A) = 3, Disagree (D) = 2 and

Strongly Disagree (SD) =1.

A 4-point rating scale was used by Otitoju (2008) to measure the constraints faced by soybeans

farmers in Benue States in Nigeria where the author categorized the constraints as Very Serious

(4), Serious (3), Less Serious (2) and Not Serious (1). Ezeibe (2009) also in the same vein used

likert scale to determine and analyse the constraints facing female farmers in crop production in

Abia state. Similarly, Abah (2011) on a study to determine the constraints facing farmers in the

use of organic solid waste in tomatoes gardening in FCT Abuja used 4-point rating scale. The

rating scale in Aba’s study was categorised into Very Important (4), Important (3), Less

Important (2) and Not Important (1). In this research, 4-point rating scale was framed in the

questionnaire to elicit information for establishing the existing constraints facing farmers in

planting agroforestry tree and engagement in other agroforestry practices using factor analysis.

2.8.3: Exploratory Factor Analysis

The ultimate goal of factor analysis is to explain the covariance relationships among the

variables in terms of some unobservable and non – measurable random factors. A wide range of

dimension or multivariate variables may exist; therefore factor analysis aims at reducing the

dimensionality or multi-variate data set to an orderly structure (Ashley, Amber and Anthony,

2006; Ledyard and Robert, 1997). Factor analysis is a means of describing groups of highly

correlated variables by a single underlying construct or factor that is responsible for the observed

correlations (Ashley et al, 2006), and once the groups of correlated variable are identified, they

are interpreted and labeled.

There are methods of factor analysis which include common and principal component

analysis. As reported by Wilkinson, Blank and Gruber (1996), most data sets under both

methods of analysis lead to similar conclusion. Exploratory factor analysis procedure using the

principal component model with iteration and varimax rotation will be employed in grouping the

constraints to Agroforestry tree planting decision into major components. In this analysis, the

factor loading under each constraint (beta weight) represent a correlation of the variables

(constraint areas) to the identified constraint factor and has the same interpretation as any

correlation coefficient. However, only variables with factor loading of 0.30 and above will be

used in naming the factor (Ashley et.al 2006 and Madukwe , 2004). Also, variable that loaded in

more than one factor will not be used.

High reliability of factor analysis models in social science studies has widely been

explored by several authors. Ashley et al, (2006) employed factors analysis to analyse education

systems of 64 countries around the world; Okorji and Chukwuone (2002) applied factor analysis

to determine constraining factors to community seed project in Enugu State, Nigeria; Agwu

(2000) analysed his data on extracting cowpea technology diffusion in Northeast Savanna Zone

of Nigeria using Factor analysis; Kessler (2006) applied factor analysis in determining the

decisive key factors influencing farm households soil and water conservation investments in

Netherlands. Also Enete and Amusa (2010) employed factor analysis to identify factor

constraints militating against women in making contributions to farming decision among cocoa-

based agroforestry households in Ekiti State, Nigeria.

CHAPTER THREE

METHODOLOGY

3.1 The study Area

The study was carried out in Ekiti State, Nigeria. Ekiti State was created on 1st October

1996. The State which was carved out of the former Ondo state has its headquarters located in

Ado Ekiti and situated entirely within the tropics. It is located between Longitude 40 45’ to 50

45’ East of the Greenwich meridian and Latitudes 70 15’-80 5’ North of the Equator. It lies South

of Kwara and Kogi States as well as bounded in the East and in the South by Ondo State. It is an

agrarian state with sixteen (16) Local Government Areas (Ekiti State Government, 2007).

In the 1991 Census, Ekiti State population was 1,647,822 while the estimated population

on creation of the State on October 1, 1996 was about 1.75 million. The 2006 population Census

by the National Population Commission puts the population of Ekiti State at 2,384,212. The

State enjoys tropical climate with two distinct seasons. These are the rainy season (April-

October) and the dry season (November - March). Temperature ranges between 210C and 280C

with high humidity. The South-West winds and the North-East Trade winds blow in the rainy

and dry seasons respectively. Tropical Forest exists in the South, while Guinea Savanna

occupies the Northern peripheries (Ekiti State Government, 2011).

Agriculture is the main occupation of the people and it is the major source of income for

many in the State. Agriculture provides income and employment for more than 75% of the

population of Ekiti State. The main cash crops are Cocoa, Coffee, Kola nut, Cashew and Oil

palm. Other tree crops include Citrus fruits, Coconut, Mango and Guava. The State can also

boast of various species of timber that provide raw material for wood- based industries. Food

Crops that abound in the State include yam, cocoyam, cassava, maize, plantain/banana, rice,

tomatoes and varieties of vegetables (Olaitan and Austin, 2006).

3.2 Sampling Procedure

Multi-stage and random sampling techniques were used for selecting the respondents for

the study. The two agricultural zones in the study area were involved in the study. Each zone

was made up of 8 Local Government Areas (LGAs). Three (3) local government areas were

randomly selected from each agricultural zone making 6 LGAs and from the selected LGAs;

three communities were randomly selected from each LGA making 18 communities for the

study. Random sampling procedure was also used to select ten (10) respondents from each

sampled farming communities to give a total of 180 respondents. Consequently, the set of

questionnaire was administered to 180 respondents.

3.3 Data Collection

Data for this study were obtained from primary source. The primary data were obtained

through the use of structured questionnaire to gather information on the respondents’ socio-

economic characteristics such as age, sex, level of education, household size etc. Other

information that were gathered from the respondents include the determinants of farmers’

willingness to plant agroforestry trees (availability of planting materials, extension contact, land

ownership, etc.), the attitudes of the farmers towards agroforestry tree planting and engagement

in other agroforestry practices), and possible constraints facing the farmers in planting

agroforestry trees and engagement in other agroforestry practices in the study area. The

questionnaire was validated by three lecturers from the Department of Agricultural Economics,

University of Nigeria, Nsukka. To ascertain the reliability of the questionnaire, 15 copies were

trial tested on farmers from Ondo State and a reliability coefficient of 0.77 was obtained using

Cronbach alpha method. Data generated were analyzed using factor analysis and probit model.

3.4 Method of Data Analysis

In order to realise the specific objectives of the study, relevant analytical tools were

employed. Objectives (i) and (ii) were achieved using frequency distribution, percentages and

mean. Objective (iv) was realised with the use of mean and standard deviation. Objective (iii)

was realised using binary probit model while Objective (v) was achieved using principal

component factor analysis

The models used in realising these specific objectives are stated below:

3.4.1 Probit model

Probit model was employed to analyse the factors influencing the farmers’ willingness to

plant agroforestry trees. The dependent variable here was the farmers’ willingness to plant while

the factors influencing their willingness to plant agroforestry trees were the independent

variables. Here, the dependent variable takes on the value of one 1 if the farmer is willing to

plant agroforestry trees (Y=1), and 0 otherwise i.e. if the farmer was not willing to plant

agroforestry trees (Y=0).

Yi = 1 = Xiʹβi + ei,

The explicit form of the model is

Pr(Y=1) =β0 + β1X1 + β2x2 + β3X3 + β4X4 + β5 X5 + β6X6 + β7X7 + β8X8 + e.

Where;

Y = conditional probability with 1 as farmers willing to engage in agroforestry practice, 0 if

otherwise.

β0 = intercept

β1 – β8 = coefficients of independent variables.

e = stochastic error term.

The hypothesised factors influencing the farmers’ willingness to engage in agroforestry practice

include;

X1 = age of farmer (in years)

X2 = Gender of Household head (1 if male, 0 if otherwise)

X3 = Education level (years in schooling)

X4 = Availability of planting materials (1 if available, 0 otherwise)

X5 = Extension Contact (Number of visit (s) per annum)

X6 = Farm distance to farmer’s residential areas (in kilometre)

X7 = Farming status (1 if farming is primary occupation, 0 otherwise)

X8 = Land ownership (1 if farmer owns land, 0 otherwise)

3.4.2: Likert Scale Rating Technique

A likert scale is a psychometric scale commonly used in questionnaires, and is the most

widely used scale in survey research. When responding to a Likert questionnaire item,

respondents specify their level of agreement or disagreement on a symmetric agree-disagree

scale for a series of item statements. Thus, the scale captures the intensity of their feelings. A 4-

point rating scale was used in this work to describe farmers’ attitudes to agroforestry tree

planting and engage in other agroforestry practices in the area while the scaling was graded as;

Strongly Agree (SA), Agree (A), Disagree (D) and Strongly Disagree (SD) with corresponding

values of 4, 3, 2 and 1 respectively, was used to determine each respondent’s level of agreement

or disagreement with the statements. Rating scales with a pool of positive and negative

statements were framed through review of literature on agroforestry practices.

The mean score of respondents based on the 4-point rating scale was computed as;

4 + 3 + 2 + 1 = 10 = 2.50 cut off point

A cut-off mark of 2.5 was used to select statements which were perceived favourable by

the respondents. For all the positive statements a mean score (MS) of ≥ 2.5 depicts a favourable

statement with regard to attitude of farmers towards agroforestry tree planting and engagement

in other agroforestry practices. Also for all negative statements (scoring of all negative

statements used to ascertain the attitude of farmers towards agroforestry tree planting and

engagement in other agroforestry practices were reversed) a mean score of ≤ 2.5

4 4

showsunfavourable statement with regard to the attitude of the farmers towards agroforestry tree

planting and engagement in other agroforestry practices.

3.4.3: Factor analysis model

Principal component factor analysis model used in achieving objective (v) is given as:

Y1 = a11X1 + a12X2 + * * *+ a1nXn

Y2 = a21X1 + a22X2 + * * * + a2nXn

* = *

* = *

Yn= an1X1 + an2X2 + * * + annXn

Where:

Y1, Y2 …Yn = observed variables/constraints facing farmers in planting agroforestry

trees and engaging in other agroforestry practices in the study area.

a1 – an = factor loadings or correlation coefficients.

X1, X2, … Xn = unobserved underlying factors constraining farmers in planting

agroforestry trees and engaging in other agroforestry practices in the

study area.

3.5. Testing of Hypotheses

Hypotheses (i) and (ii) were tested using z-test statistic as inherent in the probit model.

CHAPTER FOUR

RESULTS AND DISCUSSION

4.1 SOCIO-ECONOMIC CHARACTERISTICS OF THE RESPONDENTS

The socio-economic characteristics of respondents discussed in this section include age,

gender, marital status, level of education, occupation, extension contact/service, household size,

land ownership, access to credit, membership of farm association, and farming experience. The

frequency distribution of respondents according to their socio-economic characteristics is

presented in Table 4.1.

Age of Respondents

From Table 4.1, it is shown that majority (50.60%) of the respondents fell within 26 – 50

years age bracket while 46.10% fell within 51 -75 years of age bracket.2.20% of the respondents

had age of 75 years and above while 1.10% were of 25 years and below. The average age of the

respondents is 51 years. This result suggests that farmers in the area are within economically

active age range. This agrees with the study of Kolade (2007) that found out that Ondo

Statecocoa farmers were of average age of 51 years. This positively influences the decision of

the respondents to practicing agroforestry.

Gender of Respondents

Table 4.1 shows that majority of the respondents (92.20%) were male and 7.80% were

female. This implies that agroforestry practice in the study area is still dominated by men.

Marital Status of Respondents

Table 4.1 shows that majority of the respondents (83.30%) were married while 15%,

1.10% and 0.60% were single, widow and divorced, respectively. This suggests that

agroforestry practice in the study area is still dominated by married men and women.

Level of Education of Respondents

As shown in Table 4.1, majority (83.30%) of the respondents had formal education,

while 16.70% of them never attended school. Out of those that had formal education, 35.60% of

them attended primary school, 26.10% attended secondary school or its equivalent, while

21.70% had acquired a certain form of higher education certificate. The average years of

schooling of the respondents as estimated by this study is about 9 years. This implies that

majority of them only attempted secondary school or its equivalent. This agrees with the finding

of Nwaru and Onuoha (2010) that a greater percentage of smallholder food crop farmers (both

credit using farmers and non-credit farmers) in Imo state, Nigeria, only attempted secondary

school or its equivalent with average years of schooling of about 10 years and also agrees with

the findings of Ogundari (2008) that rainfed rice farmers in Nigeria had the average age of

schooling of 10 years. This suggests that majority of the agroforestry farmers in the study area

were at least lettered (they could read and write).

Primary Occupation of respondents

In Table 4.1, majority (66.70%) of the respondents had farming as their primary

occupation, while 33.30% had farming as their secondary occupation. Out of the 33.30% that

had farming as their secondary occupation, 16.10%, 9.40% and 8.20% were civil servants,

traders and artisans, respectively. This finding suggests that majority of the sampled respondents

practice agroforestry.

Household size of Respondents

As shown in Table 4.1, 48.90% of the respondents had household size of five persons

and below, 40% of them had household size that fell within 6 – 10 persons range, 7.80% of them

had household size that fell within 11- 15 persons and 2.20% of them had household size that

fell between 21 – 25 persons. The average household size as estimated is 6.5 (about 7 persons).

This result agrees with the finding of Otitoju and Arene (2010) that majority of the respondents

(medium-scale soybean farmers in Benue State Nigeria) had the average household size of about

7 people. This implies that more people will be involved in agroforestry.

Other related characteristics of the respondents

Extension Contact/Service

Table 4.1 shows that majority (77.70%) of the respondents did not have any extension

contact during the cropping season, while 22.80% of them had extension contact. Out of those

that had extension contact, 63.40% of them had one or two extension contacts, 9.80% of them

had three or four contacts, 7.30% of them had between seven and ten contacts, 4.90% of them

had five or six contacts. The average extension contact during the tree planting season is 0.64.

This implies that the agricultural extension programmes and services in the study area is not yet

as obtainable in other agroforestry economies of the world especially the emerging ones where

agricultural development has improved greatly. It is established in the literature that the more

number of contactsagroforestry farmers have with extension personnel and services, the better

their engagement in the practice, and the more efficient the farmers in the use of limited

resources, and invariably the more the farm’s income from agroforestry practice.

Land ownership

From Table 4.1, majority (77.20%) of the respondents were land owners, that is they own

the plots of land on which they are carrying out their farming activities, while 22.80% were

tenants. This implies that respondents in the study area are land secured. Tenants can be assumed

less likely than landowners to adopt new technological innovations, as the benefits may not

necessarily flow to them, while land ownership influences the farmers’ decisions. It is assumed

that land security has the tendency of influencing farmers’ willingness to plant agroforestry trees

in the study area.

Access to credit by the Respondents

As shown in table 4.1, majority of the respondents had no access to credit especially

formal credit, while 22.20% of them had access to informal credit. Respondents that have access

to credit can be assumed more likely to adopt new technologies than those without access to

credit. This might serve as a strong impediment to farmers’ willingness to plant agroforestry

trees in Ekiti State.

Membership of farmers’ or cooperative association(s)

It is expected that social participation i.e. membership of farmers’ or cooperative

associations should enhance farmers’ decisions. As seen in Table 4.1, 77.80% of the respondents

did not belong to any agroforestry association and/or cooperative societies, while 22.20% belong

to farmers association (s) or cooperative societies. Of those that belong to farmers’ association,

majority (75%) of them belong to one or two associations, 15% of them belong to 3 or 4

associations, and 10% belong to five associations. This implies that lesser participation in social

or cooperative associations might not enhance the decision of the respondents to engage in

agroforestry practice.

Farming experience of respondents

As shown in Table 4.1, 16.10% of the respondents had between 11 – 15 years of farming

experience, 14.50% of them had within 16 – 20 years, 14.40% of them had farming experience

of 41 years and above, 13.30% of them had farming experience of five years and below. About

12% of them had farming experience that fell between 6 and 10 years, 8.90% of them had

farming experience that fell within 26 – 30 years. The estimated average of farming experience

of the farmers is 23.3 years. This shows that quite a number of the respondents had being in

business of farming for many years. The managerial ability of a farmer reflects on his rate of

success in the farm. This could as well be a function of number of years the farmers had actively

stayed in farming. Farming involves a lot of risks and uncertainties, therefore to be competent

enough to handle all the vagaries of agriculture, farmers must have stayed in the farm for quite

some time (Ogundele and Okoruwa, 2006). The age of a farmer may not necessarily be a strong

factor in his years of farming experience. This is because some farmers who are from farming

households start participating in farming very early in their lives as children while some join

farming business at middle age or even after retirement from public services. Those respondents

with longer farming experience will be more willing to engage in agroforestry practice in the

study area.

Table 4.1: Frequency distribution of the respondents according to their Socio-economic

characteristics Variables Frequency Percentage (%)

Age (Years) Mean = 51 years

≤ 25 2 1.1

26 – 50 91 50.6

51 – 75 83 46.1

˃ 75 4 2.2

Total 180 100.0

Gender

Male 166 92.2

Female 14 7.8

Total 180 100.0

Marital status (Number)

Single 27 15.0

Married 150 83.3

Widow/widowed 2 1.1

Divorced 1 0.6

Total 180 100.0

Level of education Mean = 8.54 years

Never attended school 30 16.7

Attended primary school 64 35.6

Attended secondary school 47 26.1

Attended any higher institution 39 21.7

Total 180 100.0

Farming as occupation

Primary occupation 120 66.7

Secondary occupation 60 33.3

Total 180 100.0

Farming 120 66.7

Artisanship/craftsmanship 13 7.2

Civil service 29 16.1

Trading 17 9.4

Private Sector (Banking) 1 0.6

Total 180 100.0

Average income (N) Mean = N145,400.00

< 10,000.00 1 0.5

10,000.00 – 49,999.00 29 16.1

50,000.00 – 99,999.00 46 25.6

100,00.00 - 149,999.00 29 16.1

150,000.00 – 199,999.00 16 8.9

200,000.00 – 249,999.00 20 11.1

250,000.00 - 299,999.00 10 5.6

≥ 300,000.00 29 16.1

Total 180 100.0

Extension Contact/Services

No Extension visit/contact 139 77.2

Extension visit/contact 41 22.8

Total 180 100.0

No of visit(s)

1-2 (at most 2 visits) 26 63.4

3-4 10 24.4

5- 6 2 4.9

7 – 10 3 7.3

Total 41 100.0

Household size Mean = 6.5

≤ 5 88 48.9

6 – 10 72 40.0

11 – 15 14 7.8

16 – 20 2 1.1

21 – 25 4 2.2

Total 180 100.0

Land Ownership (Number)

Land owners 139 77.2

Land tenants 41 22.8

Total 180 100.0

Access to credit

Access 40 22.2

No access 140 77.8

Total 180 100.0

Membership of farm association(s), farmers’

coop, etc

Yes 40 22.2

No 140 77.8

Total 180 100.0

Number of association(s)

1 – 2 30 75.0

3 – 4 6 15.0

5 4 10.0

Total 40 100.0

Farming experience (Years) Mean = 23.3 years

≤ 5 24 13.3

6 – 10 21 11.7

11 – 15 29 16.1

16 – 20 26 14.5

21 – 25 14 7.8

26 – 30 16 8.9

31 – 35 9 5.0

36 – 40 15 8.3

≥ 41 26 14.4

Total 40 100.0

Source: Computed from field data, 2013

4.2: ASSOCIATED LAND TENURE SYSTEMS AND OTHER AGROFORESTRY

PRACTICES ENGAGED IN BY FARMERS IN EKITI STATE

This section describes the associated land tenure systemsand other agroforestry practices

being practiced by the farmers in the study area.

Land tenure systems

Land tenure is the method by which individuals or groups acquire, hold, transfer or

transmit property rights in land (Ogundari, 2008). Such property rights may include rights to use,

cultivate, transfer, build, alienate and so on. It is the body of rules and practices that regulate

peoples’ rights and obligations in relation to land, including any conditions and time limits to the

use of land resources(Usman, 2003). Hence, land tenure is that bundle of rights which a person

or group of persons holds in land. It determines how land as a resource may be owned and used,

and it involves any socio-cultural regulations which govern the use of such land.

Table 4.2 shown that majority (57.80%) of the respondents inherited the plots of lands

they used in farming. 17.80% of them got their land by leasehold system of land acquisition,

12.20% of them got through gift, 7.20% of them purchased their lands for farming, and 5% of

them were practicing agroforestry on government approved lands. This agrees with the finding

of Manyong and Houndekon (2000) that divided inheritance is the dominant tenurial

arrangement for the access to land (about 52 percent for all the fields in the Savannas of West

Africa).

Table 4.2: Frequency distribution of respondents by their major land tenurial systems

practiced in Ekiti State

Land tenure system Frequency Percentage

Inheritance 104 57.8

Gift 22 12.2

Purchased 13 7.2

Leased 32 17.8

Government land (or

Approved tungya system)

9 5.0

Total 180 100.0

Source: Computed from field data, 2013.

Agroforestry practices or systems engaged in by the respondents

Agroforestry systems or practices adopted by respondents in the study area are presented

in Table 4.3. Cocoa agroforest is the combination of tree species with cocoa. This is the

commonest agroforestry practice in the study area. Majority (46.10%) of the respondents were

willing to combine agroforest tree species with cocoa and 80% of those willing to plant

agroforestry trees were to practice cocoa agroforest. About 28% of the respondents were willing

to combine agroforestry tree species with arable crops and 53.2% of those that were willing to

plant agroforestry trees were willing to plant it with arable crops, this agroforestry system is

done in order for the trees planted to provide shade for the arable crops and also reduce their

expenses on weeding. Deliberately retaining trees on farmland during land preparation was also

practiced by 26.10% of the respondents and 50% of those that were willing to plant agroforestry

trees were willing to retain different agroforestry species in the study area. According to the

farmers, these species are retained to provide shade for crops, control soil erosion, and to supply

edible fruits, timber and herbs. About 18% of the total respondents were willing to combine

planting of agroforestry tree species with rearing of livestock and 35.10% of the farmers that

were willing to plant agroforestry trees adopted this combination. Mulching with agroforestry

species is also a system practiced by those farmers willing to plant agroforestry trees, 15% of the

total respondents were willing to mulch with agroforestry species and 28.70% of those that were

willing to plant agroforestry trees adopted mulching with agroforestry species in the study area.

Approved taungya system was practiced by 8.30% of the respondents and 15.90% of those

willing to plant agroforestry trees in the study area.

Alley farming is an agroforestry system in which food or forage crops are grown in the

“alleys” between hedgerows of trees or shrubs. The trees or shrubs are established in hedgerows

usually 4-meters apart (Whitttome, 1994). The trees are periodically pruned and managed during

the cropping phase to prevent shading of the companion crops. The pruning of foliage and young

stems are incorporated into the soil as green manure or used as mulch. Some portions of the tree

foliage can be harvested and fed to livestock. Alley farming is designed to be a sustainable

alternative to traditional bush fallow systems (shifting cultivation). It is a low input, improved

bush-fallow system that can be sustained even under conditions of land scarcity (Kang, 1993). It

offers opportunity to reduce deforestation and land degradation. The woody hedgerow

component of the alley farming system helps in soil protection, nutrient recycling; weed

suppression and provision of staking materials and fuel wood. Results of on-station and on-farm

trials have shown consistently that alley farming is efficient in reducing soil erosion, improving

soil organic matter and nutrient status, and sustaining crop yield under continuous cropping

(Kang, Osiname and Larbi, 1995). Alley faming was practiced by 6.70% of the respondents and

12.80% of those willing to plant agroforestry trees in the study area.

The scarcity of land prevented the majority of respondents from having woodlots for

timber production. About 6% of the total respondents were willing to adopt woodlot as an

agroforestry system in the area and 15.90% of those willing to plant agroforestry trees were

willing to engage in woodlot.

Table 4.3: Frequency distribution of respondents according to agroforestry practices

Agroforestry

practice

Frequency Percentage based on

total respondents

(N= 180)

Percentage based on

respondents WTP

agroforestry trees (N=94)

Govt approved taungya

system

15 8.3 15.9

Retaining trees on

farmlands

47 26.1 50.0

Cocoa agroforest 83 46.1 88.3

Mulching with

agroforestry species

27 15.0 28.7

Woodlot 10 5.6 10.6

Alley farming 12 6.7 12.8

Planting agroforesry

trees and livestock

rearing

33 18.3 35.1

Planting agroforestry

trees with arable crops

50 27.8 53.2

Source: Computed from field data, 2013.

4.3: FACTORS INFLUENCING FARMERS’ WILLINGNESS TO ENGAGE IN

AGROFORESTRY PRACTICE IN EKITI STATE

The result of the probit model indicates that different factors (education, farm distance to

farmers’ residents, farming status, and land ownership) influence farmers’ willingness to engage

in agroforestry practice in the study area. The likelihood ratio statistics as indicated by χ2

statistics are highly significant (P < 0.05), suggesting the model has a strong explanatory power.

In terms of consistency with a priori expectations on the relationship between the dependent

variable and the explanatory variables, the model seems to have behaved well. Table 4.4

presents the parameter estimates, standard error, and the z-ratios from the probit model.

Education

The human capital of the farmer is also assumed to have a significant bearing on the

decision to adopt new technologies. Most adoption studies have attempted to measure human

capital through education or farming experience. Table 4.4 shows that education of the farmers

has direct and significant (p<0.01) relationship with the probability of farmers’ willingness to

plant agroforestry trees in the study area. This implies that a one-unit increase in education (i.e.

years of schooling) would lead to 0.0569 (5.69%) increase in the probability of being willing to

plant agroforestry trees in Ekiti State (Table 4.4). This agrees with a priori expectation. This

means that educated farmers were more willing to plant agroforestry trees than less educated

farmers and illiterates. This is because they are more aware of the positive benefits associated

with agroforestry tree planting (reduce deforestation and land degradation; soil protection,

nutrient recycling; weed suppression and provision of staking materials and fuel wood; reducing

soil erosion, improving soil organic matter and nutrient status, and sustaining crop yield under

continuous cropping) and also show a positive attitude towards agroforestry practices in Ekiti

State. This finding agrees with the study of Keelan, Thorne, Flanagan, Newman and Mullins

(2009) which confirmed a positive relationship between Irish farmers willingness to adopt

Genetically Modified technology. Education of the farmer has been found to have a positive

effect on adoption of Genetically Modified oilseed rape in Germany (Breustedt, Muller-Scheesel

and Latacz-Lohmann, 2008) and on Bt and HT corn adoption in the United States (Fernandez-

Cornejo and McBride, 2002).

Farm Distance to Respondents’ residence

Table 4.4 shows that farm distance has positive and significant (p<0.1) relationship with

the probability of the respondents being willing to plant agroforestry trees in the study area. This

means that a unit increase in farm distance increases the willingness to engage in agroforestry

practice by 0.0849 (8.49%). This is probably because of the availability of more area of land in

distant farms than in nearby farms. Also, forest is usually located or found far away from

people’s residence.

Farming status (i.e. farming as primary occupation)

Respondents that are primarily into farming may take adoption of new technologies more

serious than others that do it on secondary basis. From Table 4.4, it is shown that farming status

has direct and significant (p< 0.05) relationship with the probability of farmers willingness to

engage in agroforestry practice in Ekiti State. This implies that a unit increase in farming as

primary occupation increases the willingness to engage in agroforestry practice by 0.534

(53.4%).

Land ownership

Land ownership is widely believed to encourage the adoption of new technologies

(Daberkow and McBride, 2003). Tenants can be assumed less likely than landowners to adopt

new technological innovations, as the benefits may not necessarily flow to them, while land

ownership is likely to influence the adoption decision. Table 4.4 shows that land ownership has a

positive and significant (p<0.05) correlation with the probability of farmers’ willingness to plant

agroforestry trees in Ekiti State. This implies that a-unit increase in farm/land ownership

increases the willingness to engage in agroforestry practice by 0.541 (54.1%).

Table 4.4 Factors influencing farmers’ willingness to engage in agroforestry practice in

Ekiti State

Variable Coefficient Standard error z-ratio

Socio-economic variables:

Age of farmer (years) 0.00530

0.00831 0.60

Gender (1 if male, 0

otherwise)

-0.495

0.3797 -1.30

Education (years of

schooling)

0.0569

0.0222 2.55***

Farm-specific and institutional variables:

Availability of planting

materials(1 if available, 0

otherwise)

-0.1602

0.2420 -0.66

Extension contact (Number

of visits)

0.0331

0.0655 0.51

Farm distance to resident

(Kilometre)

0.0849

0.0481 1.76*

Farming Status (1 if farming

is primary occupation, 0

otherwise)

0.534

0.244 2.18**

Land ownership (1 if farmer

owns land, 0 otherwise)

0.541

0.248 2.18**

Constant -1.321

0.6749 -1.96**

Number of observation = 180

Log likelihood ratio chi2 (8) = 15.58**

Prob ˃ chi2 = 0.0048

Pseudo R2 = 0.625

* stands for 10% significance level; ** stands for 5% significance level

*** stands for 1% significance level.

Source: Computed from field data, 2013.

4.4 FARMERS’ ATTITUDE TOWARDS AGROFORESTRY TREE PLANTING AND

OTHER AGROFORESTRY PRACTICES IN EKTIT STATE

Table 4.5 shows the distribution of the mean scores and standard deviations of farmers’

attitude towards agroforestry practices in Ekiti State. The result shows that the farmers expressed

positive attitude towards 15 statements out of the 16 statements bordering on the importance of

agroforestry practices. However, only one statement “farmers do not loose their benefits of

participating in other agricultural programmes if engaging in agroforestry practice (Mean Score=

2.43)” was perceived by the farmers negatively. Specifically, the following positive statements

elicited favourable attitude from the farmers: engaging in agroforestry practice is necessary to

achieve increased agricultural productivity (Mean Score = 3.56); engaging in agroforestry

practice is necessary to enhance farmers income generation (Mean Score = 3.36); planting and

retention of agroforestry trees makes extension workers to provide better services to farmers

(Mean Score = 2.57); engaging in agroforestry practice makes farmers to benefits more from

donor assisted agroforestry programmes (Mean Score = 3.02); engaging in agroforestry practice

enhance the farmers’ access to agroforestry tree products (AFTPs) (Mean Score = 3.18);

engaging in agroforestry practice enhance the nutritional status of the farmers households (Mean

Score = 2.99); farmers engage in agroforestry practices because it helps farmers to benefit from

other donor assisted agricultural and rural development programme in the state (Mean Score =

3.29); engaging in agroforestry practice reduces land degradation due to deforestation (Mean

Score = 3.20); engaging in agroforestry practice helps in the improvement of soil fertility (Mean

Score = 3.48); planting and retention of agroforestry trees to improve environmental

sustainability (Mean Score = 3.41) and engaging in agroforestry tree planting has increased the

farmers’ use of tree products for local medicinal purposes (Mean Score = 3.43). However, the

farmers disagree with the following negative statements on their attitude towards engaging in

agroforestry practices in the study area; most farmers are not willing to plant agroforestry trees

due to lack of fund (Mean Score = 3.38); planting and nurturing of agroforestry trees is not

encouraging because it affects other farm activities negatively (e.g paying little attention to the

other farm activities) (Mean Score = 2.57) and planting and nurturing of agroforestry trees don’t

allow expansion of food crop farm areas (Mean Score =2.52).

These findings show that the majority of the farmers have strong positive attitude

towards agroforestry tree planting and engaging in other agroforestry practices in Ekiti State.

More so, the low standard deviations from the mean for the responses, is an indication that the

farmers’ individual scores as regards their attitude towards the planting of agroforestry trees and

engaging in other agroforestry practices did not differ from their mean score. This finding agrees

with Ozor, Agwu, Chuckwuone, Madukwe and Gartorth (2007) who noted in their study that

farmers shown positive attitude in favour agricultural technology in Nigeria. This also confirms

the work of Agwu and Abah (2009) who noted that farmers showed positive attitude towards

National Fadama Development Project (NFDP- II) in Kogi State. From the foregoing, it is

clearly revealed that farmers always show positive attitude towards programmes, projects,

agricultural practices that hold great benefits for them. The positive attitude of the farmers

towards agroforestry tree planting and engagement in other agroforestry practices is because

they are more aware of the positive benefits associated with agroforestry tree planting e.g.

reduced deforestation and land degradation; soil protection, nutrient recycling; weed suppression

and provision of staking materials and fuel wood; reducing soil erosion, improving soil organic

matter and nutrient status, and sustaining crop yield under continuous cropping. In this study,

specific issues which elicited most favourable attitude from the farmers include engaging in

agroforestry practice is necessary to achieve increased agricultural productivity and engaging in

agroforestry practice helps in the improvement of soil fertility. This implies that the farmers are

aware that agroforestry tree planting and engagement in other agroforestry practices can improve

their socio-economic status and sustain their soil for improved agricultural productivity.

Table 4.5: Farmers’ attitude towards agroforestry tree planting and engagement in other

agroforestry practices in Ekiti State

S/No. Items Mean

Score

Standard

Deviation

Remarks

1. Engaging in agroforestry practice is necessary to

achieve increased agricultural productivity

3.56 0.609 Agree

2. Engaging in agroforestry practice is necessary to

enhance farmers income generation

3.36 0.715 Agree

3.* Most farmers are not willing to plant agroforestry

trees due to lack of fund

3.38 0.734 Agree

4.* Planting and nurturing of agroforestry trees is not

encouraging because it affects other farm activities

negatively (e.g paying little attention to the other

farm activities)

2.57 1.009 Agree

5. Planting and retention of agroforestry trees makes

extension workers to provide better services to

farmers

2.57 1.009 Agree

6. Engaging in agroforestry practice has made

governments to be more responsive to farmers’ needs

2.67 0.818 Agree

7.* Farmers do not loose their benefits of participating in

other agricultural programmes if engaging in

agroforestry practice

2.43 0.963 Disagree

8. Engaging in agroforestry practice makes farmers to

benefits more from donor assisted agroforestry

programmes

3.02 0.776 Agree

9. Engaging in agroforestry practice enhance the

farmers’ access to agroforestry tree products (AFTPs)

3.18 0.627 Agree

10. Engaging in agroforestry practice enhance the

nutritional status of the farmers households

2.99 0.832 Agree

11. Farmers engage in agroforestry practices because it

helps farmers to benefit from other donor assisted

agricultural and rural development programme in the

state

3.29 0.674 Agree

12.* Planting and nurturing of agroforestry trees don’t

allow expansion of food crop farm areas

2.52 1.091 Agree

13. Engaging in agroforestry practice reduces land

degradation due to deforestation

3.20 0.822 Agree

14. Engaging in agroforestry practice helps in the

improvement of soil fertility

3.48 0.705 Agree

15. Planting and retention of agroforestry trees to

improve environmental sustainability

3.41 0.632 Agree

16. Engaging in agroforestry tree planting has increased

the farmers’ use of tree products for local medicinal

purposes

3.43 0.608 Agree

* Negative statements

Source: Computed from field data, 2013.

4.5: CONSTRAINTS TO AGROFORESTRY TREE PLANTING BY FARMERS IN

EKITI STATE

Table 4.6 shows the varimax-rotated principal component factor analysis of major factors

constraining farmers in planting agroforestry trees and engaging in other agroforestry practices

in the study area. From result in the table, four (4) factors were extracted based on the responses

of the respondents (farmers). The Kaiser criterion (1960) was used for selecting the number of

underlying factors or principal components explaining the data. In this study, the number was

decided by leaving out components with corresponding Eigen values (a measure of explained

variance) of less than one. Only variables with factor loadings of /0.40/ and above at 10%

overlapping variance were used in naming the factors. Variables that have factor loading of less

than /0.40/ were not used while variables that loaded in more than one constraints were also

discarded (Madukwe, 2004). The communalities represent the relation between the variable and

all other variables (i.e., the squared multiple correlation between the item and all other items).

These factors are; factor 1(Techno-information and public policies factor), factor 2

(Technical/Institutional support factor), factor 3 (Land, belief and risk taking factor) and factor 4

(Agricultural extension/planting materials factor).

Under factor 1 (Techno-information and public policies factor), the specific constraining

variable against agroforeststry tree planting and engagement in other agroforestry practices

include: high cost of fertilizers and other inputs (0.764); poor access to agroforestry tree planting

information by the farmers (0.691); lack of adequate access to agroforestry practices/

technologies (0.680); lack of adequate extension programmes directed towards agroforestry

practice (0.589); inadequate government policies to encourage farmers in agroforestry practices

(0.540) and high cost of farmland (0.427).

Variables that loaded under factor 2 (Technical/Institutional support factor) include:

Insufficient knowledge of credit source to support farm work (0.790); Lack of adequate access to

supporting institutional facilities e.g, cooperative, tree planting education programme (0.678);

Limited Government responsiveness to agroforestry tree management and programme (0.637);

Lack of access to and awareness about NGOs programme for agroforestry tree planting (0.614);

Illiteracy of the farmers (0.560); Poor technical know-how of the farmers in relation to

agroforestry tree planting technology (0.439).

The constraints as perceived by the respondents (farmers) constraining farmers’

willingness to plant agroforestry trees and engage in other agroforestry practices under factor 3

(Land, belief and risk taking factor) include: involvement of the farmers in some off farm jobs,

e.g. trading, artisans, teaching, etc. (0.749); inherited system of land ownership (0.685); religious

belief of the farmers about tree planting (0.643) and unwillingness of the farmers to take risks

involved in planting, retaining and nurturing agroforestry trees (0.522).

Under factor 4 (Agricultural extension/planting materials factor) the specific constraining

variable against agroforestry tree planting and engagement in other agroforestry practices

include: high cost of improved agroforestry tree planting materials (-0.747) and poor agricultural

extension service delivery (0.439).

Adekunle (2009) reported that on some of the reasons why some respondents are not willing to

plant trees to include non-availability of land as the majority has a small landholding, problems

with land tenure, long gestation period of trees, lack of planting materials (seeds and seedlings),

lack of technical expertise, lack of incentive and poor government policies.

Table 4.6: Farmers’ Constraints to Agroforestry tree planting and engagement in their

agroforestry practices in Ekiti State

Constraints Factor

1

Factor

2

Factor

3

Factor

4

Commonalit

y

High cost of fertilizers and other inputs 0.764 0.615

Poor access to agroforestry tree planting

information by the farmers

0.691 0.584

Lack of adequate access to agroforestry

practices/ technologies

0.680 0.519

Lack of adequate extension programmes

directed towards agroforestry practice

0.589 0.462

Inadequate government policies to

encourage farmers in agroforestry practices

0.540 0.557

High cost of farmland 0.427 0.360

Insufficient knowledge of credit source to

support farm work. 0.790 0.650

Lack of adequate access to supporting

institutional facilities e.g, cooperative, tree

planting education programme.

0.678 0.524

Limited Government responsiveness to

agroforestry tree management and

programme

0.637 0.534

Lack of access to and awareness about

NGOs programme for agroforestry tree

planting

0.614 0.424

Illiteracy of the farmers 0.560 0.442

Poor technical know-how of the farmers in

relation to agroforestry tree planting

technology

0.439

0.401

Involvement of the farmers in some off farm

jobs, e.g. trading, artisans, teaching, etc. 0.749 0.568

Inherited system of land ownership 0.685 0.476

Religious belief of the farmers about tree

planting

0.643

0.512

Unwillingness of the farmers to take risks

involved in planting, retaining and nurturing

agroforestry trees

0.522

0.450

High cost of improved agroforestry tree

planting materials -0.747 0.602

Poor agricultural extension service delivery 0.439 0.407

Percentage (%) of variance 15.397 14.836 11.049 8.136 49.418

Factor 1(Techno-information, cost and public policies factor), factor 2 (Technical/institutional

support factor), factor 3 (Land, belief and risk taking factor) and factor 4 (Agricultural

extension/planting materials factor).

Source: Computed from field data, 2013.

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

5.1 SUMMARY

This study examined the factors influencing farmers’ willingness to engage in

agroforestry practices in Ekiti State, Nigeria. The study was conducted using survey design.

Multistage random sampling technique was adopted to select the respondents from a population

of 1,215 registered farmers from Ekiti State. The two agricultural zones (Zone I and Zone II) in

the state were used. Each zone was made up of 8 local government areas (LGAs). Three LGAs

were randomly selected from each agricultural zone making 6 LGAs and from each of the

selected LGAs; three communities were randomly selected making 18 communities. Random

sampling procedure was also used to select ten farmers from each sampled farming communities

to give a total of 180 respondents. Primary data were collected using structured questionnaire.

The questionnaire was structured into five sections. Sections A, B and C were used to

obtain data on socio-economic characteristics of the farmers, associated land tenure system and

factors influencing farmers’ willingness to plant agroforestry trees respectively. Sections D and

E were structured into four-point rating scale to obtain data on farmers’ attitudes toward

agroforestry tree planting and constraints facing farmers in planting agroforestry trees

respectively. The questionnaire was validated by three lecturers from the Department of

Agricultural Economics, University of Nigeria, Nsukka. To ascertain the reliability of the

questionnaire, 15 copies were trial tested on farmers from Ondo State and a reliability coefficient

of 0.77 was obtained using Cronbach alpha method. Data generated were analyzed using factor

analysis and probit model.

Based on the data analyzed, the study found that majority (50.60%) of the respondents

were within 26 – 50 years age bracket while the average age of the farmers was 51 years.

Majority of the farmers (92.20%) were male. The greatest percentage (83.30%) were married

while 15%, 1.10% and 0.60% were single, widow and divorced, respectively. Majority (83.30%)

had formal education, while 16.70% never attended school. Out of those that had formal

education, 35.60% had primary education, 26.10% had secondary school education, while

21.70% had one form of higher education or the other. The average years of schooling of the

farmers was nine years. Majority (66.70%) of the respondents had farming as their primary

occupation while the remaining 33.30% had farming as their secondary occupation. Education

(years of schooling), farm distance to farmers’ residents, farming status and land ownership were

positive and significantly (p<0.05) influenced farmers’ willingness to plant agroforestry trees.

About 80% of the respondents were willing to intercrop agroforestry tree species with

cocoa while about 53.20% were willing to intercrop agroforestry tree species with arable crops.

Farmers expressed positive attitude towards 15 out of the 16 items bordering on planting of

agroforestry trees with mean values ranging between 2.68 and 3.73 on a four-point rating scale.

The constraints the farmers faced in planting agroforestry trees were lack of appropriate

technology, inadequate information, high cost of inputs, institutional neglect, land tenure system,

cultural barriers, inadequate agricultural extension visits and lack of improved planting materials

with mean values ranging between 2.75 and 3.58 on a 4-point rating scale.

5.2 CONCLUSION

This study examined the factors influencing farmers’ willingness to engage in

agroforestry practices in Ekiti State, Nigeria. The probit model result indicates that education

(years of schooling), farm distance to farmers’ residents, farming status, and land ownership

positively influenced farmers’ willingness to plant agroforestry trees in the study area. In this

study, specific issue which elicited most favourable positive attitude from the farmers is

“engaging in agroforestry practice is necessary to achieve increased agricultural productivity”

while the negative statement that farmers disagree with most on their attitude towards planting

agroforestry trees and engaging in other agroforestry practices is“most farmers are not willing to

plant agroforestry trees due to lack of fund”. The study also revealed that the constraints faced

by farmers in planting agroforestry trees and engaging in other agroforestry practices are techno-

information, cost and public policies constraint, technical/institutional support constraints, land,

belief and risk taking constraint and agricultural extension/planting materials constraint. As

verified through this study, farmers must be properly given needed attention through extension

activities on agroforestry practices that can encourage them to plant agroforestry trees.

Promulgations on land use should be farmers’ friendly enough in order to encourage them to

plant agroforestry trees and make them have the confidence to reap the benefits of planting trees

that may still come to them several years later. Other technical supports such as credit must be

given by government agencies and non-governmental organizations (NGOs) in other to

encourage farmers to engage in agroforestry practices because of the benefits that can be derived

from this both by the farmers and the society at large.

5.3 RECOMMENDATIONS

The findings of the study have some important policy implications for enhancing the

willingness to engage in agroforestry practices especially in agroforestry tree planting. The

following recommendations are presented which have policy implications.

i. Government should consider making promulgations on land tenure arrangements

that give farmers sense of belongings on lands (i.e. to own more lands of theirs),

which have the potentials to make the farmers more willing to plant agroforestry

trees in the area. Tenants are less likely than landowners to engage in agroforestry

practices, because the benefits may not necessarily flow to them. Land ownership

has the potential to influence farmers’ decision on agroforestry tree planting.

ii. Farmers that are on full time farming should be encouraged to participate more in

agroforestry programmes by the governments and donor-assisted agencies at all

levels in the study area.

iii. Educated farmers should be encouraged to participate more in agroforestry

programmes, especially tree planting programmes or agricultural and/or rural

development programmes or projects that has tree planting as a component and

who will invariably help their neighbouring farmers, especially the illiterates to

be willing to plant agroforestry trees (i.e. farmer-to-farmer extension paradigm).

iv. Proactive measures should be taken in the extension programmes of the Ministry

of Agriculture and Ekiti State Agricultural Development Programme (EKADEP)

to involve farmers in their tree planting programmes and campaigns. Farmers

should be co-opted to participate in the planning, implementation and execution

of agroforestry programmes. Farmers should be enlightened by agroforestry

extension personnels that participation in other agricultural programmes or

projects do not make them to loose their benefits when they engage in

agroforestry practices.

v. Technical and institutional support constraints should be addressed through

provision of more credit through public policies and even creating more

awareness of non-governmental organizations (NGOs) interested in agroforestry

programmes. Farmers should even be made to be aware of relevant credit support

for tree planting and NGOs that are involved in supporting agroforestry

programmes in the study area.

References

Abegunde C. K.(1999). Land Tenure and Administration in Nigeria and the Cameroons. Ibadan:

University Press.

Adams, M.E. (2000). Agricultural Extension in Developing Countries. Macmillan Press Ltd.,

London.

Adebayo, W. O, (2006). Waste Generation, Disposal and Management Techniques in an

Urbanizing Environment: A case study of Ado- Ekiti, Nigerian Research Journal of

Applied Science. 1 (1): 63–66.

Adedire, M.O. (2004). Environmental protection: the Agroforestry option. Nigerian journal of

Forestry 34 (1):1-6.

Adekanye, J.A. (2002). Once Upon a Forest: A Masterpiece of Creation. UNAAB Inaugural

Lecture Series No. 1, 29 p.

Adekunle, V.A.J. (2002). Inventory Techniques and Models for Yield and Tree Species

Diversity Assessment in Ala and Omo Forest Reserves, S. W. Nigeria.Ph. D. Thesis,

Federal University of Technology, Dept of Forestry and Wood Technology, Akure,

Nigeria.

Adekunle, V.A.J. & Bakare, Y. (2004).Rural Livelihood Benefits from Participation in Taungya

Agroforestry System in Ondo State Nigeria. Journal of Small-Scale Forest Economic,

Management and Policy 3(1): 131- 138.

Adekunle, V.A. (2009). Contributions of agroforestry practice in Ondo State, Nigeria, to

environmental sustainability and sustainable agricultural production. Afrika Focus 22 (2):

27- 40.

Agarwal H (2002). Coconut harvesting practices in Indonesia. Pemberitean-Lembaga Penelitian

Tanaman Industri 36, p. 58-73.

Agwu, A.E. & Abah, H. O. (2009). Attitutde of farmers towards cost-sharing in the second

National Fadama Development Project (NFDP-II): the case of Kogi State of Nigeria.

Journal of Agricultural Extension, 13(2): 92-106.

Agwu, A.E. (2000). “Diffusion of Improved Cowpea Technology Among Farmers in the North

East Savanna Zone of Nigeria.” An UnpublishedPh.D Thesis Submitted to the

Department of Agricultural Extension University of Nigeria, Nsukka.

Agyemang, K.O., (1991). Socio-Economic/Cultural Issues in alley farming research and

development. Paper prepared for the AFNETA Training Course for Eastern and Southern

Africa English speaking countries, KEFRI, Nairobi, Kenya.

Akinnifesi F.K, F. Kwesiga, J. Mhango, T. Chilanga, A. Mkonda, C.A.C Kadu, I. Kadzere, D.

Mithofer, J.D.K Saka, G. Sileshi, T. Ramadhani, P. Dhliwayo (2006). Towards the

development of miombo fruit trees as commercial tree crops in southern Africa.For.Trees

Livelihood 16: 103-121.

Akinnifesi F.K, R.R.B Leakey, O.C Ajayi, G. Sileshi, Z. Tchoundjeu, P. Matakala, F.R Kwesiga

(2008). Indigenous Fruit Trees in the Tropics: Domestication, Utilization and

Commercialization. World Agroforestry Centre: Nairobi. CAB International Publishing,

Walling-ford, UK.p. 438.

Akkinnifesi, F. (2005) Formalizing Agroforestry in Malawi: Trees Take Root in Government

Policy,” World Agroforestry Center, Southern Africa Regional Programme, 2005.

http://www.worldagroforestrycentre.org/downloads/5%20Formalizing%20agroforestry.p

df

Alabi, R.A. (2003). “Human Capital as Determinant of Technical Inefficiency of Cocoa-based

Agroforestry System”.Journal of Food, Agriculture and Environment Vol. 1 (3 & 4): 277

– 281.

Alabi, T. (2006).Challenges of Sustainable Forest Management in Ondo State: Community

Based Forest Management System as a Panacea. In: Research for development in

forestry, forest products and natural resources management, Onyekwelu, J.C., Adekunle,

V.A.J. and Oke, D.O. (Eds.), Proceedings of the 1st National Conference of the Forest

and Forest Products Society held at the Federal University of Technology, Akure,

Nigeria, 16th – 18th April, 2008, 242-247.

Aldrich, J. H. & Nelson, F. D. (1984).Linear Probability, Logit, and Probit Models. Newbury

Park, CA: Sage Publications, Inc.

Andrich, D. (1978). A Rating Formulation for Ordered Response Categories.Psychometrika,

4(3),357-374.

Arhin, K. (2008). The expansion of cocoa production: The working condition of migrant cocoa

farmers in the Western and the Central Regions. Institute of Africa Studies, University of

Ghana, Legon.

Arnold, J.E. M. (1991). Community forestry ten years in review.Forest, Trees and People.

Community Forestry Note 7: 20-23.

Arnold, J.E.M. (1987). “Economic considerations in agroforestry” in steppler, H.A. and Nair,

P.K. (1998). Agroforesty: A Decade of Development. ICRAF, Nairobi, pp. 174-190.

Ashley, B., S. Amber and F. Anthony. (2006). “Education by Nation: Multivariate analysis”.

Retrieved September 22, 2011, from http://www.users.muohio.edu/porterbm/

Ashley, C. and D. Carney. (1999). Sustainable livelihood: Lessons from early experience DFID,

London, UK.

Aturamu, D. (2005). Agroforestry policy options for Nigeria: A simulation study.

Food,Agriculture and Environment 3:1.

Aturamu, M.O. (2008). Environmental Protection: The Agroforestry Option. Nigerian Journal of

Forestry 34 (1): 1-6.

Ayling, K.G.(1999). The possible cause of Lethal Yellowing disease of coconut. FAO Plant

Protection Bulletin 20, 3, p. 58-68.

Barraclough, S. L. and K .B.Ghimire. (1995). Forest and livelihoods: The social dimension of

deforestation in developing countries. Macmillan Press LTD, UK.

Bello K.A. (2006).Traditional cocoa-based agroforestry and forest species conservation in

Ondo State, Nigeria.Agriculture, Ecosystems and Environment, 122: 305-311.

Bello, D.O. (2003). The Changing Cocoa Agroforests of Ondo State, Nigeria: Implications for

Environmental Stability, Food Security and Biodiversity Conservation. In: Research for

development in forestry, forest products and natural resources management, Onyekwelu,

J.C., Adekunle, V.A.J. and Oke, D.O. (Eds.), Proceedings of the 1st National Conference

of the Forest and Forest Products Society held at the Federal University of Technology,

Akure, Nigeria, 16th – 18th April, 2008, 60-63.

Benneh G (1987). Land tenure and agroforestry land use systems in Ghana. In: Raintree, JB (ed)

Trees and tenure. Proc. Int. Workshop on Tenure Issues in Agroforestry, Land Tenure

Centre, Wisconsin, USA.

Boadu, F.O. (1993). Contingent valuation for household water in rural Ghana.Journal of

Economics, 43(3), 458-65.

Brasselle A.S, F. Gaspart and J.P Platteau, (2002). Land tenure security and investment

incentives: Puzzling evidence from Burkina Faso. Journal of Development Economics

67, 373–418.

Breustedt, G., Muller-Scheesel, J., & Latacz-Lohmann, U. (2008).Forecasting the adoption of

GM oilseed rape: Evidence from a discreet choice experiment in Germany.Journal of

Agricultural Economics, 59(2), 237-256.

Burley, J. and J.L. Steward (eds). 1982. Increasing productivity of Multipurpose species. Publ.

by IUFRO, Vienna, pp. 560.

Byron I., A. Curtis, and J. MacKay (2005).Draft: Providing social and economic data to support

regional natural resource management in the BurnettMary,Bureau of Rural Sciences,

Canberra.

Campbell, A. (1992). Taking the long view in tough times… Landcare in Australia, National Soil

Conservation Program, ACT.

Cary J., T. Webb and N. Barr. (2002). Understanding land managers’ capacity to change to

sustainable practices: insights about practice adoption and social capacity for change,

Bureau of Rural Sciences, Canberra.

Caveness, F.A and W.B Kurtz (2006) Agroforestry adoption and risk perception by farmers in

Senegal. Agroforestry Systems (21): 11-25.

Chavanapoonphol, Y., Battese, G.E. & Chang, H.C. (2005, February 9 – 11). The impact of rural

financial services on the technical efficiency of rice farmers in the Upper North of

Thailand. Paper presented at the Annual Conference of the Australian Agricultural and

Resource Economics Society at Coffs Harbour.

Curtis A, J. MacKay, M. Van Nouhuys, M. Lockwood, I Byron, and M. Graham. (2000).

Exploring land manager willingness and capacity to manage dryland salinity: the

Goulburn Broken Catchment, Charles Sturt University, Albury.

Dairo A.M.O. (2006). Architecture in Nigeria and the practice for sustainable development: A

comparative study of modern and indigenous housing strategy. AARCHES Journal 2 (1):

61-65.

Davidson, J. and E.Stratford (2000).Building the knowledge base of the social and institutional

dimensions of natural resource management, a University of Tasmania report for Land

and Water Resources Research and Development Corporation, Tasmania.

Denning, G. L. (2001).Realizing the potential of agro-forestry: Integrating research and

Development to achieve greater impact.Development in Practice 11:4.

Duriappah, A, (1996). Poverty and environmental degradation: A literature review and analysis

of the nexus. World Development 26(12), 2169–79.

Eckman H.C(1992). The evolution, dissemination and classification of Cocos nucifera L. The

Botanical Review 44, 3, p. 265-319.

Ekiti State Government (2007).“The People of Ekiti State”. Retrieved August 13, 2007 from

http://www.ekitinigeria.net/

Enete, A. A and Amusa, T. A (2010).Determinants of Women’s Contribution to Farming

Decisions in Cocoa-Based Agroforestry Households of Ekiti State, Nigeria.Journal

ofField Actions Science Reports (FACTS),Vol. 4/1, pp 1-6. Retrieved 23 September,

2011 from http://www.factsreports.revues.org/

Fernandez-Cornejo, J., & McBride, W. (2002).Adoption of bioengineered crops (Agricultural

Economics Report No. 810). Washington, DC: US Department of Agriculture Economic

Research Service (USDA ERS).

Finlay, R. A., (2004). Understanding Land Managers Attitudes Using Focus Groups,Proceedings

of Refereed Papers, AFBMNetwork Conference 2004.

Fishburn, P.C. (1968). “Utility theory”.Management sciences, 14(5): 335-378. (Theory series)

(January). Retrieved June 1, 2011 from http://www.jstor.org/stable/2628674

Folayan, J.A., G.A, Daramola and A.E, Oguntade. (2006). “Structure and Performance

Evaluation of Cocoa Marketing Institutions in South -Western Nigeria: An Economic

Analysis”. Journal of Food, Agriculture and Environment.4 92: 125 – 128.

Foley, G. and G.Barnard. (1984). Farm and community forestry. Earthscan- International

Institute for Environment and Development (IIED). London.

Food and Agriculture Organisation (FAO), (1986). Tree growing by rural people. Food and

Agricultural Organization of the UN, Rome.pp 26-29.

Food and Agriculture Organisation (FAO), (1989). Food loss prevention in perishable crops.

Agricultural Services Bulletin 43. FAO of the UN, Rome, XIV. Pp 32.

Fortman, L. (1990). The Tree Tenure Factor in Agroforestry with Particular Reference to Africa.

Agroforestry Systems 2: 229 – 251.

Francis, P.A (2009) Sociological and ecological factors in technology adoption: fodder trees in

southeast Nigeria. Experimental Agriculture (25): 1-10.

Franzel S, and S.J Scherr (2002) Assessing the adoption potential of Agroforestry practices:

ICRAF’s experiences in sub-saharan Africa. In: Sinclair F (ed) Process-based Research

in Sustainable Agricultural Development: Integrating Social, Economic, and Ecological

Perspectives. Proceedings of a joint meeting between the International Union of Forestry

Research Organizations Research Group and the Association for Farming Systems

Research-Extension, 29 Nov–4 Dec 1998, Pretoria, South Africa (In press).

Gabremedhin B and S.M Swinton (2003). Investment in soil conservation in Northern Ethiopia:

The role of land tenure security and public programs. Agricultural Economics 29, 69–84.

German E.M (2009). Conservation of Tree Species Diversity in Tropical Rainforest Ecosystem

of Southwest Nigeria. Journal of Tropical Forest Science (Malaysia) 18(2): 91-101.

Gouyon, A.T. (1992). Vegetation Modification and Man-induced Environmental Change in

Rural Southwestern Nigeria. Agriculture, Ecosystem and Environment, 70: 159-167.

Greiner R., N. Stoeckl, C. Stokes, A. Herr, and J. Bachmaier. (2003). Natural resource

management in the Burdekin Dry Tropics: social and economic issues, a report for the

Burdekin Dry Tropics NRM Board, CSIRO, Townsville.

Guerin, L. (1994). Constraints to the adoption of innovations in Agricultural Research and

environmental management, Australian Journal of Experimental Agriculture, 34, 549-

571.

Hobley, M. (1996). Why participatory forestry. In participatory forestry: The process of change

in India and Nepal. M. Hobley (ed.). Rural development forestry study guide 3. ODI,

London.

Hoskins, M.W (1987) Agroforestry and the social milieu. In: Steppler HA and Nair PKR (eds)

Agroforestry: A Decade of Development, 191-203. ICRAF, Nairobi, Kenya.

Hyman, E.L (2000). Loan financing of smallholder tree farming in the provinces of llocos Norte

and llocos Sur, Philippines. Agroforestry Systems (1): 225-243.

International Center for Research in Agroforestry (ICRAF), (1993). Strategy to the year 2000.

Mimeo, Nairobi: ICRAF.pp 78.

Jones, V.A.J. (2009). Inventory Techniques and Models for Yield and Tree Species Diversity

Assessment in Ala and Omo Forest Reserves, S. W. Nigeria. Ph. D. Thesis, Federal

University of Technology, Dept of Forestry and Wood Technology, Akure, Nigeria, 179

p.

Kabubo-Mariara, J, (2003). The linkages between property rights, migration and productivity:

The case of Kajiado District, Kenya. Environment and Development Economics 8(4),

621–36.

Kang ,B.T, Osiname, O.A., Larbi, A. (1995): Alley farming research and Development. In:

Proceedings ofthe International Conference on Alley Farming Held at IITA. 14th–

18thSept., Ibadan, Nigeria.

Kang B.T. (1993): Alley Cropping: Past achievements and future directions. Agroforestry

system, 23 (2–3): 141–156.

Kang, B.T. and G.F Wilson, (2009). The Development of Alley cropping as a promising

Agroforestry Technology. In: Steppler, H.A. and Nair, P.K. eds. Agroforestry: A decade

of development. ICRAF, Nairobi. Pp. 174 – 190.

Keelan, C., Thorne, F.S., Flanagan, P., Newman, C. & Mullins, E. (2009). Predicted willingness

of Irish farmers to adopt GM technology, AgbioForum, 12 (3&4), 394-403.

Kessler M C (2006). The Challenge of Sustainable Forests: Forest resource policy in Malaysia,

Sydney: Allen & Unwin and University of Hawaii Press, Honolulu.

Kohlin, G., and P.J. Parks. (2001). Spatial Variability and Disincentives to Harvest:

Deforestation and Fuelwood Collection in South Asia. Land Economics 77(2): 206–218.

Kolade, A.S. (2007). “Some Tenurial and Legal Aspects of Agroforestry” in Jackson, J.K. ed

Social, Economic and Institutional Aspects of Agroforestry. The United Nation

University Tokyo, Japan. Pp 20 – 25.

Kwanashie, M., I. Ajilima and A.G, Garba. (1998). “The Nigerian Economy: Response of

Agriculture to Adjustment Policies”. AERC Research Paper 78. African Economic

Research Consortium, Nairobi, Kenya.

Leach, G., and R. Mearns, (1988). Beyond the wood fuel crisis. People, Land and tree in Africa,

Earthscan Publications Ltd., London.

Leakey, (1996). Agroforestry Today: Vol. 8 No. 1: ICRAF, Nairobi, Kenya.

Leakey, R. (2006). Definition of Agroforestry revisited. Agroforestry Today 8(1): 5-7.

Ledyard, R.T and C.M, Robert. (1997). Exploratory Factor Analysis. Ohio: Ohio State

University Press.

Liao, T. F. (1994). Interpreting Probability Models: Logit, Probit, and Other Generalized Linear

Models. Thousand Oaks, CA: Sage Publications, Inc.

Lockie, S., G. Lawrence, A. Dale, and B. Taylor. (2002). Capacity for change: testing a model

for the inclusion of social indicators in Australia’s National Land and Water Resources

Audit, Journal of Environmental Planning and Management, 45(6) November, 813-826.

Lungren, B. O. (1982). What is Agroforestry? Agroforestry Systems 1:7-12.

Lungren, B. O. (1987). ICRAF’s first ten years. Agroforestry systems 5: 197-217.

Madukwe, M.C. (2004)."Multivariate Analysis for Agricultural Extension Research”. In Olowu,

T. A. (Ed) Research Methods in Agricultural Extension. pp 206 – 236.

Malla S A, (2000). Development as Freedom. Alfred A. Knopf, New York.

Manyong, V.M. & Houndekon, V. A. (2000). Land tenurial systems and the adoption of Mucuna

palnted fallow in the Derived Savannas of West Africa, CAPRi Working paper N0. 4,

International Food Policy Research Institute (IFPRI), Washington, D.C. , U.S.A.

Meinzen-Dick, R., A. Knox, F. Place and B. Swallow (eds) (2002). Innovation in Natural

Resource Management: The Role of Property Rights and Collective Action in

Developing Countries. Johns Hopkins University Press, Baltimore, USA.

Mercer, D.E. and F. Hyde, (1992). The Economics of land-use systems. Paper presentation at a

course on ICRAF’s multi-disciplinary approach to diagnose land-use problems and the

potentials and design of Agroforestry Technologies to overcome identified constraints.

ICRAF, Nairobi, Kenya.

Migot-Adholla S.E, P.Hazell,B. Blarel, & F.Place, (1991). Indigenous land rights systems in

sub-Saharan Africa: A constraint on productivity? World Bank Economic Review 5(1),

155–75.

Mithofer D. (2006). Income and labour productivity of collection and use of indigenous fruit tree

products in Zimbabwe. Agroforestry Systems 59: 295–305.

Mithofer D, H. Waibel, F.K Akinnifesi. (2006). The role of food from natural resources in

reducing vulnerability to poverty: a case study from Zimbabwe Proc. 26th Conf. Int.

Assoc. Agr. Economists (IAAE), Queensland, Australia.

Nair, P.K. (1993). An introduction to Agroforestry. pp 13-155, ICRAF/Kluwers Academic

Publishers, Dordrecht, Netherlands.

Njoku, J.E., (1991). Determinants of Adoption of improved Oil palm production technologies in

Imo State, Nigeria. In: Doss, C.R., and Olson, C. (eds). Issues in African rural

development. Winrock International Institute for Agricultural Development. Arlington,

USA.

Nwaru, J.C. & Onuoha, R.E. (2010). Credit use and technical change in smallholder food crop

production in Imo State, Nigeria. New York Science Journal, 3(11), 144-151.

Nweke, P.R. (1990) “Directions in Tropical Agroforestry Research: Past, Present and Future,”

Agroforestry Systems, Vol. 38, No. 1-3 (July 1997) 223-245.

Ogundari, K. (2008). Reesource-productivity, allocative efficiency and determinants of technical

efficiency of rainfed rice farmers: A guide for food security in Nigeria. Journal of

Sustainable Development in Agriculture & Environment, 3(2), 20-33.

Ogundele, O. O. & Okoruwa, V.O. (2006). Technical efficiency differentials in rice production

technologies in Nigeria (AERC Research Paper 154). Nairobi, Kenya: African

Economic Research Consortium. Retrieved October 10, 2006, from

http://www.aecrafrica.org/documents/rp154.pdf.

Okorji, E.C and N.A, Chukwuone. (2002). “Assessment of Farmers Under the Community Seed

Project: Implications for Agricultural Development and Poverty Eradication in Nigeria”,

In Iloeje, M.U and Osuji, G.E (Eds), Agriculture: A Basis for Poverty Eradication and

Conflict Management; Proceedings of the 36th Annual Conference of Agricultural

Society of Nigeria. Held at the Federal University of Technology Owerri, Nigeria. pp 138

– 142.

Okyere, E.O., S.Charter, and R.Blench (2010). Traditional farming systems in the sub-humid

zone of Africa. University Press, London. Pp. 110 – 140.

Olu A .A (2004). Technology Characteristics, Farmers’ Perceptions and Adoption Decisions: A

Tobit Model Application in Sierra Leone. Agric. Econ., 9: 297-311.

Oram, P. (1993). Global Perspective on Population, Resources and Agricultural Production.

Keynote Paper, proceedings of the 7th Australian Agronomy Conference, Carlton, Pp 37.

Oriloye A L. (2005). Land Management in Nigeria: Issues, Opportunities and Threats”, Paper

presented at the National Conference on Land Management and Taxation, Department of

Estate Management, University of Lagos.

Otitoju, M. A. and Arene, C. J. (2010). Constraints and determinants of technical efficiency in

medium-scale soybean production in Benue State, Nigeria. African Journal of

Agricultural Research, 5(17), 2276-2280. Available online at

http://www.academicjournals.org/AJAR

Owusu-Sekyere, E. (1991). The Socio-cultural Problems in Agroforestry Development in Ghana

(Case study) in Koen J.H. ed. Africa Agroforestry Emphasis on Southern Africa.

Environmental Forum Report.

Ozor, N. Agwu, A.E, Chukwuone, N.A., Madukwe, M.C. & Garforth, C.J. (2007). Cost-sharing

of agricultural technology transfer in Nigeria: perceptions of farmers and extension

professionals, Journal of Agricultural Education and Extension, 13 (1), 23-37.

Place F (1994a). Policies and incentives for the adoption of improved fallows. Agroforestry

Systems (this issue)

Place F (1994b). The Role of Land and Tree Tenure on the Adoption of Agroforestry.

Place, F. and K. Otsuka (2000). Tenure and tree management in Uganda and Malawi. In:

Meinzen-Dick, R., A. Knox, F. Place and B. Swallow (eds) Innovation in Natural Re-

source Management: The Role of Property Rights and Collective Action in Developing

Countries. Johns Hopkins University Press, Baltimore, USA.

Raintree, J.B., (1991). Socio – economic attributes of trees and tree planting practices.

Community Forestry Note 9. Food and Agricultural Organization of the UN, Rome.

Ramadhani T. (2002). Marketing of Indigenous Fruits in Zimbabwe. Socio-economic

Studies on Rural Development, Vol 129. Wissenschaftsverlag Vauk. Kiel, Germany.

Rocheleau, D and J.D Raintree (1986). Agroforestry and the future of food production in

developing countries. Impact of Science and Society 142: 127 – 141.

Rocheleau, D and J.D. Raintree, (1986). Agroforestry and the future of food production in

developing countries. Impact of Science and Society 142: 127 – 141.

Rogers, E.M. (2003). Diffusion of innovations. New York: The Free Press.

Salako, Y. (1982). Rural Livelihood Benefits from Participation in Taungya Agroforestry

System in Ondo State Nigeria. Journal of Small-Scale Forest Economic, Management

and Policy 3(1): 131- 138.

Scherr SJ, and E.U Frankel (2002). Technology impact evaluation in agroforestry projects.

Agrofor. Syst., 13: 235–257.

Scherr, S. J. (2008). Meeting household needs : Farmer-tree growing strategies in western

Kenya. In farms, trees and farmers: Responses to agricultural intensification. J. E. M.

Arnold and P. A.. Dewees (eds.). pp 141-173.

Scherr, S. J., B. Swallow, and D. Russell, (2002). Talk given at USAID Biodiversity and

Forestry Seminar, December 4, 2002.

Shiferaw, B & S. Holden (1999). Soil erosion and smallholders’ conservation decisions in the

highlands of Ethiopia. World Development 27(4), 739–52.

Tamale, E., Jones, N. Riddihough, I. P. (1995). Participatory forestry in tropical and sub tropical

countries. World Bank forestry series. Technical paper number 299.

Tejwani, K. G. And C.K Lai, (1992). Asia-pacific agroforestry profiles, agroforestry systems

research and development in the Asia-Pacific region. Asia pacific agroforestry network

(APAN) field document no. 1. Bogor, Indonesia. pp. 34-40.

Tolman A C. (1967). Tree Seeds for Farmers: A Tool Kit and Reference Source. Nairobi.

World Agroforestry Center.

Torquebiau, E. (1992). Are tropical agroforestry homegardens sustainable? Agriculture

Ecosystems and Environment, 41: 189-207.

Usman A.T. (2003). Vegetation Modification and Man-induced Environmental Change in Rural

Southwestern Nigeria. Agriculture, Ecosystem and Environment, 70: 159-167.

Vanclay, F. (2004). Social principles for agricultural extension to assist in the promotion of

natural resource management, Australian Journal of Experimental Agriculture 44(3):

213–222.

Vanslembrouck. I, (2002). Determinants of the willingness of Belgian farmers to participate in

agri-environmental measures, Journal of Agricultural Economics, 53 (3), 489-511.

White J, and E. Robinson. (2000). HIV/AIDS and rural livelihoods in Sub-Saharan Africa.

Policy Series No. 6, Natural Resource Institute. University of Greenwich p.63.

Whittome, M. (1994). The Adoption of Alley Farming in Nigeria and Benin: The on-farm

experience of IITA and ILCA. (Ph.D Thesis) Department of Geography, University of

Cambridge, UK.

Wilkinson, L.G and C, Gruber. (1996). “Desktop Data Analysis with SYSTAT.” Upper Saddle River,

NJ: Prentice Hall.

Williams, Y.L. (2009) “Land and Tree Tenure in Nigeria” in World Bank, Population,

Agriculture and Environment, World Bank Study, pp54.

Wuensch, K. L. (2005). "What is a Likert Scale? and How Do You Pronounce 'Likert? Retrieved

September 30, 2011 from http://www.core.ecu.edu/psyc/.

Young, A. (2000). Agroforestry for soil conservation. Science and practice of Agroforestry, 4

Wallingford, UK: CAB International and Nairobi: ICRAF, 276pp.

APPENDIX A

Questionnaire/ Interview Schedule

A. Location

1. Zone……………………………………………………………………

2. Local Government Area……………………………………………….

3. Village /Town……………………………………………………………

B. Socio-economic, institutional and farm-specific characteristics of farmers

1. Name (optional)………………………………………………………………..

2. Age in years……………………………………………………………………

3. Marital Status: Single Married Widow Divorced

4. Sex of the house head: Male Female

5. Level of Education:

i. Never attended school ii. Attended primary school

iii. Attended secondary school iv. Attended any higher institution

6. How many years did you totally spend in school…………………………

7. Number of people in your farming household…………………………….

8. Is farming your primary occupation? Yes No If No, which of the

following? (i). Craftsman (ii). Civil servant (iii). Trading

Specify, if others………………………………………………..

9. What is the average distance to your farm(s) in kilometers from your

homestead?………………..

10. Do you belong to any civil, local and farm association(s): Yes No If

yes, how many………………………….

11. For how long have you been farming? …………………………………….

12. What is your average income from farming in the last cropping season?

………………………………… (in Naira).

13. Did you have access to credit in the last cropping season? Yes No

……………………………..

14. Did extension workers or agents visit your farm in the last cropping season? Yes

No If yes, how many times………………………….

15. Do you own the land you use in farming? Yes No

16. Are agroforestry tree planting materials available to you? Yes

No

C. Agroforestry practices observed by the farmers in the study area

17. Are you willing to plant agroforestry trees? Yes No

18. Which of the following agroforestry practices do you engage in?

(i). Approved tungya system (ii). Retaining trees on farmlands

(iii). Cocoa agroforestry (iv). Mulching with agrofoestry species

(v). Woodlot (vi). Alley farming (vii). Planting and retaining of

trees with livestock rearing (viii). Planting and retaining of trees with

planting of arable crops

D. Land Tenurial systems practiced by the farmers in the study area

19. Which of the following land tenurial systems do you practice in association with

agroforestry tree planting?

(i). Inheritance (ii). Gift (iii). Purchasing

(iv). Renting/Leasing (v). Government land (Approved Taungya

system)

E. Farmers’ attitude towards agroforestry tree planting and engagement in other

agroforestry practices in the area

Please tick the appropriate most column (√) below

S/No Items Strongl

y Agree

Agre

e

Disagre

e

Strongly

Disagre

e

1. Engaging in agroforestry practice is

necessary to achieve increased agricultural

productivity

2. Engaging in agroforestry practice is

necessary to enhance farmers income

generation

3. Most farmers are not willing to plant

agroforestry trees due to lack of fund

4. Planting and nurturing of agroforestry trees

is not encouraging because it affects other

farm activities negatively (e.g paying little

attention to the other farm activities)

5. Planting and retention of agroforestry trees

makes extension workers to provide better

services to farmers

6. Engaging in agroforestry practice has made

governments to be more responsive to

farmers’ needs

7. Farmers stand to loose their benefits of

participating in other agricultural

programmes if engaging in agroforestry

practice

8. Engaging in agroforestry practice makes

farmers to benefits more from donor

assisted agroforestry programmes

9. Engaging in agroforestry practice enhance

the farmers’ access to agroforestry tree

products (AFTPs)

10. Engagnig in agroforestry practice enhance

the nutritional status of the farmers

households

11. Farmers engage in agroforestry practices

because it helps farmers to benefit from

other donor assisted agricultural and rural

development programme in the state

12. Planting and nurturing of agroforestry trees

don’t allow expansion of food crop farm

areas

13. Engaging in agroforestry practice reduces

land degradation due to deforestation

14. Engaging in agroforestry practice helps in

the improvement of soil fertility

15. Planting and retention of agroforestry trees

to improve environmental sustainability

16. Engaging in agroforestry tree planting has

increased the farmers’ use of tree products

for local medicinal purposes

F. Farmers’ Constraints to Agroforestry tree planting and engagement in other agroforestry

practices in the study area

Please tick the most appropriate column (√) below

S/No Items Very

Serious

Serious Less

Serious

Not

Serious

1. Illiteracy of the farmers

2. Lack of adequate extension programmes directed

towards agroforestry practice

3. Poor access to agroforestry tree planting information

by the farmers

4. Limited Government responsiveness to agroforestry

tree management and programme

5. Insufficient funds/finance

6. Lack of adequate access to agroforestry practices/

technologies

7. Lack of adequate access to supporting institutional

facilities e.g, cooperative, tree planting education

programme.

8. High cost of improved agroforestry tree planting

materials

9. Poor agricultural extension service delivery

10. Inherited system of land ownership

11. Non-availability of farm labour

12. High cost of fertilizers and other inputs

13. High cost of farmland

14. Involvement of the farmers in some off farm jobs,

e.g. trading, artisans, teaching, etc.

15. Insufficient knowledge of credit source to support

farm work.

16. Inadequate government policies to encourage

farmers in agroforestry practices

17. Unwillingness of the farmers to take risks involved

in planting, retaining and nurturing agroforestry trees

18. Lack of access to and awareness about NGOs

programme for agroforestry tree planting

19. Religious belief of the farmers about tree planting

20. Poor technical know-how of the farmers in relation

to agroforestry tree planting technology