SU+ @ Strathmore 

University Library 
 

  
 

Electronic Theses and Dissertations 

 

 

This work is availed for free and open access by Strathmore University Library.  

It has been accepted for digital distribution by an authorized administrator of SU+ @Strathmore University. 

For more information, please contact library@strathmore.edu 

 

 
2025 

 

Moderating effect of biodiversity 

conservation on the relationship between 

agroforestry practices and productivity of 

smallholder farmers in Mt. Elgon, Kenya. 

 
 
Loyatum, Antonious 
Strathmore Business School 
Strathmore University 

 

 

Recommended Citation 

Loyatum, A. (2025). Moderating effect of biodiversity conservation on the relationship between agroforestry 

practices and productivity of smallholder farmers in Mt. Elgon, Kenya [Strathmore University]. 

http://hdl.handle.net/11071/15997 

 
 
 
 

Follow this and additional works at: http://hdl.handle.net/11071/15997 

https://su-plus.strathmore.edu/
https://su-plus.strathmore.edu/
http://hdl.handle.net/11071/2474
mailto:library@strathmore.edu
http://hdl.handle.net/11071/15997
http://hdl.handle.net/11071/15997


MODERATING EFFECT OF BIODIVERSITY CONSERVATION ON THE 

RELATIONSHIP BETWEEN AGROFORESTRY PRACTICES AND 

PRODUCTIVITY OF SMALLHOLDER FARMERS IN MT. ELGON, 

KENYA  

 

 

 

 

 

 

ANTONIOUS LOYATUM 

MDF/152484/2022 

 

A Research Project Submitted to the Strathmore Business School in Partial 

Fulfilment for the Master of Science in Development Finance of Strathmore 

University 

 

 

 

MAY, 2025 

 



ii 

 

DECLARATION 

DECLARATION 

I declare that this work has not been previously submitted and approved for the award of a degree 

by this or any other University. To the best of my knowledge and belief, the thesis contains no 

material previously published or written by another person except where due reference is made in 

the thesis itself.  

Antonious Cherop Loyatum 

 

Approval  

The thesis of Antonious Cherop Loyatum was reviewed and approved by the following:  

Prof. Simon Wagura Ndiritu  

Director and Associate Professor  

Strathmore University Business School/ Strathmore Agri-Food Innovation Center 

 

  



iii 

 

ABSTRACT  

Agroforestry, practiced on over 1 billion hectares globally, represents 28% of agricultural land area 

and offers potential solutions to smallholder farmers’ challenges, including soil degradation, low 

productivity and climate variability. Despite its extensive adoption, there is limited statistical 

evidence quantifying the impact of agroforestry practices and biodiversity conservation on farm 

productivity. This study sought to address this gap by examining the relationship between 

agroforestry practices, biodiversity conservation and productivity in Mt. Elgon Sub-County, 

Kenya. Specifically, the study aimed to analyze the effects of agroforestry types, implementation 

scale and utilization of extension services on productivity. Additionally, it evaluated how 

biodiversity conservation moderated the relationship between agroforestry practices and 

productivity. The research was underpinned by three theories: the Theory of Agroforestry Systems, 

which explains the ecological and economic synergies of integrated farming systems; the Resource 

Dependence Theory, emphasizing farmers’ reliance on external and natural resources; and the 

Theory of Planned Behavior, which accounts for farmers’ attitudes and intentions in adopting 

agroforestry. A pragmatist research philosophy guided the study, focusing on actionable insights 

for addressing real-world challenges. A concurrent triangulation research design was employed, 

combining qualitative and quantitative methods to ensure robust findings. The study targeted 

smallholder farmers practicing agroforestry in Mt. Elgon Sub-County, Kenya, estimated at 16,283 

households. A sample size of 384 farmers was determined using Fisher’s formula, with participants 

selected through stratified random sampling across geographical zones and purposive sampling 

for key informants to ensure comprehensive representation of agroforestry practices. Data was 

collected through questionnaires and key informant interviews from a stratified random sample of 

smallholder farmers in Mt. Elgon Sub-County. Quantitative data was analyzed using SPSS Version 

27, employing descriptive statistics and multiple linear regression, while qualitative data 

underwent content analysis. The findings revealed that the type of agroforestry system 

significantly influenced farm productivity, with more diverse systems showing greater benefits. 

Expanding the scale of agroforestry implementation had the strongest positive impact on 

productivity, demonstrating the advantages of wider adoption. Access to extension services 

contributed moderately to productivity gains, particularly when combined with other factors. Most 

notably, biodiversity conservation played a crucial moderating role, enhancing the positive 

relationship between agroforestry practices and productivity, especially when implemented at 

larger scales and supported by extension services. The research recommended that farmers should 

be supported with targeted interventions to enhance the scale and effectiveness of agroforestry 

implementation. This study contributes to policy frameworks and extension programs, supporting 

sustainable agricultural practices and biodiversity management in the region. 

Keywords: Agroforestry Practices, Biodiversity Conservation, Smallholder Productivity, 

Sustainable Agriculture, Mt. Elgon Kenya. 

  



iv 

 

TABLE OF CONTENTS 

DECLARATION ........................................................................................................................... ii 

DECLARATION ........................................................................................................................... ii 

ABSTRACT .................................................................................................................................. iii 

TABLE OF CONTENTS ............................................................................................................. iv 

LIST OF TABLES ...................................................................................................................... viii 

LIST OF FIGURES ..................................................................................................................... ix 

ABBREVIATIONS AND ACRONYMS ..................................................................................... x 

DEFINITION OF TERMS .......................................................................................................... xi 

DEDICATION ............................................................................................................................ xiii 

ACKNOWLEDGEMENT ......................................................................................................... xiv 

CHAPTER ONE ............................................................................................................................. 1 

INTRODUCTION .......................................................................................................................... 1 

1.1 Background of the Study ....................................................................................................... 1 

1.1.1 Agroforestry Practices .................................................................................................... 1 

1.1.2 Productivity of Smallholder Farmers ............................................................................. 3 

1.1.3 Biodiversity Conservation .............................................................................................. 4 

1.1.4 Study Context and Justification ...................................................................................... 6 

1.2 Statement of the Problem ...................................................................................................... 6 

1.3 Research Objectives .............................................................................................................. 7 

1.3.1 General Objective ........................................................................................................... 7 

1.3.2 Specific Objectives ......................................................................................................... 8 

1.4 Research Questions ............................................................................................................... 8 

1.5 Scope of the Study ................................................................................................................. 8 

1.6 Significance of the Study ...................................................................................................... 9 

1.6.1 Policy Makers and Regulators ........................................................................................ 9 

1.6.2 Academicians and Researchers ....................................................................................... 9 

1.6.3 Community ................................................................................................................... 10 

1.7 Chapter Summary ................................................................................................................ 10 

CHAPTER TWO .......................................................................................................................... 12 

LITERATURE REVIEW .............................................................................................................. 12 



v 

 

2.1 Introduction ......................................................................................................................... 12 

2.2 Theoretical Review ............................................................................................................. 12 

2.2.1 Theory of Agroforestry Systems ................................................................................... 12 

2.2.2 Resource Dependence Theory ...................................................................................... 14 

2.2.3 Theory of Planned Behaviour ....................................................................................... 15 

2.3 Empirical Literature Review ............................................................................................... 16 

2.3.1 Type of Agroforestry and Productivity ......................................................................... 16 

2.3.2 Scale of Implementation and Productivity ................................................................... 18 

2.3.3 Extension Services and Productivity ............................................................................ 19 

2.3.4 Moderating Effect of Biodiversity Conservation on Relationship between Agroforestry 

Practices and Productivity ..................................................................................................... 21 

2.4 Summary of Literature and Gap .......................................................................................... 23 

2.5 Conceptual Framework ....................................................................................................... 27 

2.6 Operationalization of Variables ........................................................................................... 28 

2.7 Chapter Summary ................................................................................................................ 29 

CHAPTER THREE ...................................................................................................................... 30 

RESEARCH METHODOLOGY.................................................................................................. 30 

3.1 Introduction ......................................................................................................................... 30 

3.2 Research Philosophy ........................................................................................................... 30 

3.3 Research Design .................................................................................................................. 31 

3.4 Target Population ................................................................................................................ 32 

3.5 Sampling and Sample Size .................................................................................................. 33 

3.6 Data Collection .................................................................................................................... 34 

3.6.1 Instrument Validity ....................................................................................................... 35 

3.6.1 Validity .......................................................................................................................... 35 

3.6.2 Reliability of the Instruments ....................................................................................... 35 

3.6.3 Pilot Testing .................................................................................................................. 36 

3.7 Data Analysis....................................................................................................................... 36 

3.8 Ethical Considerations......................................................................................................... 38 

3.9 Chapter Summary ................................................................................................................ 38 

CHAPTER FOUR ......................................................................................................................... 39 



vi 

 

RESULTS ...................................................................................................................................... 39 

4.1 Introduction ......................................................................................................................... 39 

4.2 Response Rate ..................................................................................................................... 39 

4.3 Demographic Information of Respondents ......................................................................... 40 

4.4 Descriptive Analysis of the Independent Variables ............................................................. 41 

4.4.1 Descriptive Findings on Type of Agroforestry ............................................................. 41 

4.4.2 Descriptive Findings on Scale of Implementation ....................................................... 44 

4.4.3 Descriptive Findings on Extension Services ................................................................ 47 

4.4.4 Descriptive Statistics on Biodiversity Conservation .................................................... 51 

4.4.5 Descriptive Statistics on Productivity........................................................................... 54 

4.5 Regression Analysis Findings ............................................................................................. 63 

4.5.1 Regression Analysis Model without Moderator ........................................................... 63 

4.5.2 Regression Analysis with Moderation Effect ............................................................... 65 

CHAPTER FIVE .......................................................................................................................... 68 

DISCUSSIONS, CONCLUSIONS AND RECOMMENDATIONS ............................................ 68 

5.1 Introduction ......................................................................................................................... 68 

5.2 Discussions .......................................................................................................................... 68 

5.2.1 Type of Agroforestry and Productivity ......................................................................... 68 

5.2.2 Scale of Implementation and Productivity ................................................................... 71 

5.2.3 Extension Services and Productivity ............................................................................ 75 

5.2.4 Biodiversity Conservation and Productivity................................................................. 77 

5.3 Conclusions ......................................................................................................................... 80 

5.3.1 Type of Agroforestry and Productivity ......................................................................... 80 

5.3.2 Scale of Implementation and Productivity ................................................................... 80 

5.3.3 Extension Services and Productivity ............................................................................ 81 

5.3.4 Biodiversity Conservation and Productivity................................................................. 82 

5.4 Recommendations ............................................................................................................... 83 

5.4.1 Type of Agroforestry and Productivity ......................................................................... 83 

5.4.2 Scale of Implementation and Productivity ................................................................... 83 

5.4.3 Extension Services and Productivity ............................................................................ 84 

5.4.4 Biodiversity Conservation and Productivity................................................................. 84 



vii 

 

5.5 Limitations and Areas for Further Research ....................................................................... 84 

REFERENCES ............................................................................................................................. 86 

APPENDICES .............................................................................................................................. 91 

Appendix 1: Questionnaire........................................................................................................ 91 

Appendix 2: Key Informant Interview Guide ......................................................................... 101 

Appendix 3: Ethical Review Clearance .................................................................................. 104 

Appendix 4: Research Permit from NACOSTI....................................................................... 105 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  



viii 

 

LIST OF TABLES 

Table 2.1 Summary of Literature Review...................................................................................... 23 

Table 2.2 Operationalization of Variables ..................................................................................... 28 

Table 3.1: Reliability Results ........................................................................................................ 36 

Table 4.1 Descriptive Statistics on Demographic Data ................................................................ 41 

Table 4.2 Descriptive Findings on Agroforestry Practices ........................................................... 43 

Table 4.3 Number of Trees in the Respondent’s Farm .................................................................. 44 

Table 4.4 Scale of Respondent’s Agroforestry Implementation ................................................... 45 

Table 4.5 Descriptive Statistics on  Agroforestry Practices .......................................................... 46 

Table 4.6 Accesses to Extension Services Related to Agroforestry .............................................. 47 

Table 4.7 Descriptive Findings on Extension Services ................................................................. 50 

Table 4.8 Changes in Biodiversity on the Farm for the Last 5 Years ........................................... 51 

Table 4.9 Presence of Specific Actions to Conserve Biodiversity on their Farm ......................... 52 

Table 4.10 Descriptive Findings on Biodiversity Conservation ................................................... 54 

Table 4.11 Respondent’s Total Annual Income from Agricultural Sales ...................................... 55 

Table 4.12 Percentage of Respondent’s Farm Area Allocated to Agroforestry ............................ 56 

Table 4.13 Descriptive Statistics on Productivity ......................................................................... 57 

Table 4.14 Proportion of Respondent’s Total Income Coming from Agroforestry Products ....... 57 

Table 4.15 Respondent’s Average Annual Income Generated from Agroforestry Products ......... 59 

Table 4.16 Impact of Agroforestry on Respondent’s Access to On-farm Resources .................... 59 

Table 4.17 How Agroforestry Affected Overall Farm Productivity.............................................. 60 

Table 4.18 Descriptive Findings on Environmental Productivity ................................................. 61 

Table 4.19 Seasonal Differences in Productivity Due to Agroforestry Practices ......................... 62 

Table 4.20 Regression Model Summary ....................................................................................... 63 

Table 4.21 Regression ANOVA .................................................................................................... 64 

Table 4.22 Regression Coefficients .............................................................................................. 65 

Table 4.23 Moderated Regression Model Summary ..................................................................... 65 

Table 4.24 Moderated Regression ANOVA Results ..................................................................... 66 

Table 4.25 Moderated Regression Coefficients ............................................................................ 67 

  



ix 

 

LIST OF FIGURES 

Figure 2.1 Conceptual Framework ............................................................................................... 27 

Figure 4.1 Response Rate ............................................................................................................. 39 

Figure 4.2 Gender of the Respondents .......................................................................................... 40 

Figure 4.3 Agroforestry Practices Implemented on Farm ............................................................. 42 

Figure 4.4:Main Reasons for Practicing Agroforestry .................................................................. 42 

Figure 4.5: Challenges in Implementing Agroforestry Practices .................................................. 45 

Figure 4.6 Frequency of Receiving Calls if Yes ........................................................................... 48 

Figure 4.7 Type of Support the Respondents Receive from Extension Services .......................... 49 

Figure 4.8 Types of Biodiversity Changes Respondents Observed .............................................. 52 

Figure 4.9 Actions Taken by Respondents .................................................................................... 53 

Figure 4.10 Types of Crops Grown by the Respondents .............................................................. 55 

Figure 4.11 Types of Products the Respondents Harvest from Agroforestry Practices ................ 58 

Figure 4.12 Main Challenges in Improving Productivity through Agroforestry .......................... 61 

  



x 

 

ABBREVIATIONS AND ACRONYMS 

ASALs   Arid and Semi-Arid Areas  

FAO    Food and Agriculture Organization  

IRB    Institutional Review Board  

KACP    Kenya Agricultural Carbon Project  

NACOSTI   National Commission for Science, Technology and Innovation 

RDT    Resource Dependence Theory  

SBS    Strathmore Business School  

SDGs    Sustainable Development Goals  

TPB    Theory of Planned Behaviour  

 

  



xi 

 

DEFINITION OF TERMS 

Agroforestry Practices:     Agroforestry practices involve integration of trees and shrubs into 

agricultural landscapes to enhance productivity, sustainability and 

environmental benefits. These practices include alley cropping, 

silvopasture, riparian buffer strips and windbreaks, aiming to 

create diverse, multi-functional landscapes that support both 

agricultural production and ecosystem services (Ahmad et al., 

2023). 

Biodiversity Conservation: Biodiversity conservation refers to the management and protection 

of ecosystems, species and genetic diversity to prevent the loss of 

biological resources. This includes strategies and practices 

designed to maintain and restore the variety of life forms, their 

habitats and their ecological functions (Swallow et al., 2020). 

Extension Services:  Extension services are support systems that provide education, 

resources and assistance to farmers to improve their agricultural 

practices. These services aim to disseminate knowledge, promote 

innovative practices and increase the general productivity and 

sustainability of farming systems, including agroforestry (Kinyili 

et al., 2020). 

Productivity:  Productivity in the context of agroforestry refers to the output or 

yield of agricultural and forestry products per unit of land. It 

encompasses both the quantity and quality of produce generated 

from agroforestry systems, focusing on sustainable and efficient 

production and improved household income (Castle et al., 2021). 

Scale of Agroforestry Implementation: The scale of agroforestry implementation refers to the 

extent and intensity at which agroforestry practices are adopted 

and practiced, ranging from small-scale individual farm plots to 

large-scale, landscape-level interventions. The scale of 

implementation can significantly influence the effectiveness and 



xii 

 

sustainability of agroforestry practices (Telwala, 2023). 

Smallholder Farmers:  Smallholder farmers are individuals or families that farm small 

plots of land, typically less than 5 acres and rely primarily on 

family labour for production. These farmers typically practice 

subsistence agriculture but may also produce crops for local 

markets. Their farming activities are often characterized by low 

input and output levels and significant reliance on agroecological 

principles (Duffy et al., 2021). 

Type of Agroforestry:  Types of agroforestry include silvopastoral (livestock and trees), 

agrosilvicultural (crops and trees) and agrosilvopastoral (crops, 

livestock and trees) systems. Each type integrates different 

components of agriculture and forestry to optimize land use and 

resource efficiency (Korir et al., 2022). 

 

 

 

 

 

 

 

 

 

 

  



xiii 

 

 

DEDICATION 

I dedicate this research project to my family for their encouragement and unwavering support 

throughout my journey. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



xiv 

 

 

ACKNOWLEDGEMENT 

I extend my heartfelt gratitude to God for His constant guidance and blessings throughout this 

journey. I am deeply thankful to my mother and sister for their unwavering support, encouragement 

and sacrifices that have shaped my path. Special appreciation goes to my husband and son, whose 

companionship and positivity have been a source of strength and motivation. I am indebted to my 

esteemed colleagues at Strathmore Business School for their valuable insights and collaborative 

spirit. Additionally, I would like to express my sincere thanks to my university supervisor for their 

guidance and expertise, which have been instrumental in shaping this work. Lastly, I appreciate 

my classmates for their solidarity and shared learning experiences, which have enriched my 

academic journey.



1 

 

CHAPTER ONE  

INTRODUCTION 

1.1 Background of the Study 

Smallholder agriculture is critical to global food security, yet it faces persistent productivity 

challenges. Worldwide, smallholders manage approximately 500 million farms, producing over 

50% of the global food supply, but many operate on degraded land with limited access to resources 

(Kassa, 2022). Globally, agricultural productivity among smallholders has stagnated or declined 

in many regions due to unsustainable practices, soil degradation and climate change. Studies 

estimate that yield gaps, which are the difference between actual and potential productivity, 

average between 20% and 60% for key crops like maize and rice (Mukhlis et al., 2022). This crisis 

disproportionately affects vulnerable populations, with an estimated 80% of people living in 

extreme poverty residing in rural areas dependent on agriculture (Homann-Kee et al., 2023; Kassa, 

2022). 

1.1.1 Agroforestry Practices 

Agroforestry practices, which involve the deliberate integration of trees with crops and/or livestock 

on the same land unit, are globally recognized for their ecological and economic benefits. Around 

the world, agroforestry has gained attention as a sustainable land-use system capable of improving 

food production, enhancing biodiversity and addressing the adverse effects of climate change. 

Research by Alifa et al. (2024) highlights how integrating trees with crops and livestock enhances 

soil fertility, water retention and microclimate regulation, leading to yield increases of up to 30% 

in some regions. In Latin America, agroforestry has been successfully deployed to reduce 

deforestation and sequester carbon while maintaining food output (Willmott et al., 2023). In 

Southeast Asia, particularly in Indonesia and the Philippines, agroforestry has enabled farmers to 

adopt climate-smart practices that build resilience to extreme weather and sustain livelihoods in 

ecologically fragile zones (Alifa et al., 2024). Despite these successes, the global uptake of 

agroforestry remains uneven due to differences in policy environments, land tenure systems and 

technical knowledge. 

Regionally, in Sub-Saharan Africa, where over 70% of the population depends on smallholder 

farming for food and income (Homann-Kee et al., 2023), agroforestry plays a vital role in 

enhancing productivity and ecological resilience. Countries like Zimbabwe and Burkina Faso have 



2 

 

recorded higher household incomes, improved food security and healthier ecosystems among 

smallholders who integrate trees into their farming systems (Kinyili et al., 2020). In arid and semi-

arid lands (ASALs) of the region, agroforestry is increasingly viewed as a tool for reversing land 

degradation and combating desertification (Kassa, 2022). However, the pace of adoption is still 

constrained by challenges such as inadequate extension services, lack of financing and cultural 

preferences for conventional cropping systems. 

In Kenya, where smallholder farmers constitute approximately 75% of the agricultural workforce, 

agroforestry has been promoted as a key strategy for sustainable agriculture and rural development. 

The government, through institutions such as the Kenya Forestry Research Institute (KEFRI), has 

supported the dissemination of agroforestry technologies including tree planting on farms, alley 

cropping and boundary planting. These efforts have targeted regions experiencing soil depletion, 

erratic rainfall and declining farm productivity. Nevertheless, the adoption of agroforestry in 

Kenya is often hindered by insecure land tenure, fragmented extension systems and limited farmer 

awareness about long-term benefits (Korir et al., 2022). 

Locally, Mt. Elgon in Bungoma County provides a compelling context for agroforestry 

implementation due to its highland ecosystem, fertile volcanic soils and historical reliance on 

agriculture. The region is ecologically rich but vulnerable to soil erosion, deforestation and 

unsustainable land-use practices. Several agroforestry interventions have been piloted in Mt. 

Elgon, focusing on the use of nitrogen-fixing species such as Sesbania, Calliandra and Grevillea 

robusta to improve soil health and provide fodder and fuelwood. Despite observable benefits in 

certain areas, the adoption of agroforestry remains uneven. Factors such as limited technical 

support, lack of coordinated community participation and insufficient integration of indigenous 

knowledge systems have constrained its widespread application. There is a critical need to 

investigate how context-specific agroforestry practices can be scaled up to improve productivity 

and support biodiversity conservation in Mt. Elgon. 

Despite the growing body of literature on agroforestry, several critical research gaps persist, 

particularly concerning smallholder farmers in specific regions like Mount Elgon, Kenya. 

Globally, agroforestry has been recognized as a sustainable land management strategy, yet much 

of the research has focused on its environmental benefits, such as carbon sequestration and soil 

fertility improvement, with less emphasis on its direct impact on smallholder productivity (FAO, 



3 

 

2020; Homann-Kee et al., 2023). While studies from regions such as Southeast Asia and Latin 

America highlight the role of agroforestry in improving rural livelihoods (Alifa et al., 2024; 

Willmott et al., 2023), localized studies in African contexts, particularly in Kenya, remain limited. 

The lack of region-specific data creates a significant gap in understanding how diverse agroforestry 

systems interact with local ecological, social and economic factors to affect productivity. 

1.1.2 Productivity of Smallholder Farmers 

Globally, smallholder farmers, those cultivating less than two hectares, produce over one-third of 

the world’s food supply, yet their productivity remains significantly constrained (FAO, 2021). 

Productivity, defined as output per unit of land or input, varies widely due to factors such as soil 

degradation, limited access to inputs, climate variability and inadequate extension services. In 

regions like South Asia and Latin America, innovations including the use of nitrogen-fixing trees 

such as Sesbania and Calliandra have improved soil fertility, thereby boosting crop yields by over 

25% (Mukhlis et al., 2022). Despite these advances, yield gaps persist due to fragmented 

landholdings, poor infrastructure and weak policy support. 

In Africa, where approximately 33 million smallholder farms contribute up to 80% of the 

continent’s food production, low productivity remains a pressing concern. These farmers typically 

face challenges such as nutrient-depleted soils, unpredictable rainfall, pests and limited market 

access. Agroecological approaches, including agroforestry, have shown promise in improving 

productivity while conserving the environment. For instance, in countries such as Malawi and 

Ghana, the integration of multipurpose tree species into farming systems has enhanced crop output 

and soil quality. However, adoption remains patchy due to the absence of scalable financing 

models, inadequate research-extension linkages and socio-cultural barriers (Homann-Kee et al., 

2023). 

In Kenya, smallholder farmers form the backbone of the agricultural sector, contributing over 75% 

of total agricultural output. Yet, their productivity remains below both regional and global 

benchmarks (Korir et al., 2022). Key challenges include low input use, poor soil health, fragmented 

land tenure systems and limited adoption of sustainable practices. While government and non-

governmental efforts have promoted agroforestry and conservation agriculture, the impact has 

been uneven, partly due to limited outreach and inconsistent policy implementation. As a result, 



4 

 

staple crops such as maize, beans and potatoes still yield below their potential, affecting food 

security and income generation at the household level. 

Locally, in Mt. Elgon, Bungoma County, smallholder farmers dominate the agricultural landscape, 

relying heavily on crops like maize, beans and potatoes. The region is characterized by fertile 

volcanic soils and high rainfall, which offer significant potential for enhanced agricultural 

productivity. However, local farmers grapple with a range of challenges including deforestation, 

soil erosion, limited access to quality seeds and fertilizers and inadequate agricultural extension 

services. Although agroforestry interventions have been introduced to improve soil fertility and 

reduce land degradation, their uptake remains limited. Addressing these constraints through 

context-specific productivity-enhancing strategies such as the incorporation of nitrogen-fixing 

trees, improved extension support and local seed systems could significantly improve yields and 

strengthen household food security in Mt. Elgon. 

Empirical studies underscore the potential of agroforestry to enhance smallholder productivity. For 

example, Korir et al. (2022) report that the incorporation of nitrogen-fixing trees in Kenyan 

smallholder farms increased maize yields by 20-50%, while Kinyili et al. (2020) highlight the role 

of agroforestry in improving soil fertility and water retention, particularly in arid and semi-arid 

regions of sub-Saharan Africa. Similarly, a study by Mukhlis et al. (2022) in Zimbabwe showed 

that smallholder farmers practicing agroforestry experienced a 30% rise in overall farm 

productivity compared to those relying on monoculture systems. However, the variability in these 

results points to the importance of local ecological and socio-economic conditions, necessitating 

more targeted research to understand the full potential of agroforestry in specific regions. 

1.1.3 Biodiversity Conservation 

Globally, biodiversity conservation, the protection, sustainable management and restoration of 

biological diversity, is critical for maintaining ecosystem resilience, food security and climate 

stability. The loss of biodiversity has accelerated over recent decades due to habitat destruction, 

pollution, overexploitation and climate change. The Intergovernmental Science-Policy Platform 

on Biodiversity and Ecosystem Services (IPBES, 2019) warns that over one million species face 

extinction, undermining ecosystem services like pollination, water regulation and disease control. 

Agroforestry systems, which combine tree cover with agriculture, are increasingly recognized as 

a nature-based solution that enhances biodiversity while sustaining agricultural livelihoods. 



5 

 

Studies in Latin America and Southeast Asia have shown that such systems support greater species 

richness and habitat connectivity compared to conventional agriculture (Willmott et al., 2023). 

In Africa, where biodiversity hotspots such as the Congo Basin and the Eastern Afromontane 

region are under growing pressure, biodiversity conservation is both a challenge and a necessity. 

Land-use changes driven by agricultural expansion, charcoal production and logging have 

contributed to forest fragmentation and species decline. However, evidence from countries like 

Uganda, Ethiopia and Cameroon shows that agroforestry can mitigate biodiversity loss by creating 

ecological corridors, preserving soil organisms and enhancing carbon storage (Kassa, 2022). These 

landscapes support both endemic and migratory species, which are vital for ecological balance and 

local economies. Yet, the success of such interventions depends on supportive policy 

environments, community participation and long-term incentives. 

In Kenya, biodiversity conservation is enshrined in national policy frameworks such as the 

National Biodiversity Strategy and Action Plan and Vision 2030. Kenya hosts diverse ecosystems, 

from coastal wetlands to montane forests, which are under pressure from land conversion, 

overgrazing and unsustainable harvesting. Agroforestry has gained prominence as a strategy for 

reconciling conservation and development goals. Initiatives in areas such as Kakamega Forest and 

the Mau Complex have demonstrated how integrating trees into farming systems can protect 

critical habitats and enhance resilience. Nonetheless, gaps in enforcement, weak local institutions 

and competing land uses continue to hamper biodiversity conservation efforts at scale. 

Locally, Mt. Elgon represents a vital ecological zone with high endemism and rich forest 

biodiversity. The region supports numerous plant and animal species, some of which are threatened 

due to deforestation, land degradation and agricultural encroachment. Agroforestry offers a 

promising pathway to conserve biodiversity in Mt. Elgon by reducing dependence on native forests 

for fuelwood and timber, while promoting habitat diversity on farmland. Studies show that 

agroforestry systems in this area can act as biological corridors, supporting species movement and 

enhancing ecosystem services like pollination, soil stabilization and pest control (Kinyili et al., 

2020). As deforestation intensifies in Mt. Elgon, integrated approaches that combine biodiversity 

conservation with smallholder livelihoods are increasingly essential. This study, therefore, aimed 

to investigate how agroforestry can serve as a dual-purpose strategy, enhancing agricultural 



6 

 

productivity while conserving the ecological integrity of one of Kenya’s most critical biodiversity 

landscapes. 

1.1.4 Study Context and Justification 

Mt. Elgon was selected for this study due to its ecological significance and the unique challenges 

faced by smallholder farmers in the region. As a globally recognized biodiversity hotspot, Mt. 

Elgon hosts diverse flora and fauna, including several endemic and threatened species (Willmott 

et al., 2023). This makes it an ideal location for examining how biodiversity conservation 

moderates the relationship between agroforestry practices and farm productivity. Furthermore, the 

region has witnessed significant environmental challenges, such as deforestation, soil erosion and 

habitat degradation, which impact both agricultural productivity and ecosystem health (Kinyili et 

al., 2020). The study aims to provide actionable insights for promoting sustainable practices that 

balance productivity with conservation. Additionally, Mt. Elgon is predominantly home to 

smallholder farmers who rely on agriculture for their livelihoods. These farmers face challenges 

such as declining soil fertility, unpredictable rainfall and limited access to extension services 

(Willmott et al., 2023). Agroforestry is widely practiced in the region as a means of addressing 

these challenges, providing a relevant context for analyzing its effectiveness. The selection of Mt. 

Elgon ensures that the study’s findings was directly applicable to a population that stands to benefit 

significantly from evidence-based policy and practice recommendations, thereby enhancing 

agricultural sustainability and biodiversity conservation in the region. 

1.2 Statement of the Problem 

Despite the recognized potential of agroforestry practices and biodiversity conservation to improve 

the productivity of smallholder farmers, a significant gap exists in empirical data quantifying their 

impact, especially in specific contexts. Globally, agroforestry is practiced on over 1 billion hectares 

of land, constituting approximately 28% of the agricultural land area (FAO, 2020). However, there 

is insufficient statistical evidence to comprehensively link agroforestry to key indicators such as 

agricultural productivity, carbon sequestration, biodiversity conservation and poverty alleviation. 

This lack of precise data hinders the ability of policymakers, researchers and practitioners to 

prioritize agroforestry as a transformative solution to global challenges like food insecurity, 

climate change and rural poverty (Homann-Kee et al., 2023; Willmott et al., 2023). 



7 

 

In Mount Elgon, Kenya, a region known for its ecological diversity and agricultural heritage, 

contextual gaps exist as localized research on agroforestry remains scarce. While studies in other 

parts of Kenya have demonstrated agroforestry’s benefits, such as increased crop yields and 

improved livelihoods (Korir et al., 2022), the unique challenges and opportunities within Mount 

Elgon have not been adequately explored. The region faces distinct issues like deforestation, soil 

erosion and biodiversity loss, which complicate sustainable land management efforts. 

Furthermore, the interplay between agroforestry practices, biodiversity conservation and 

smallholder productivity in Mount Elgon has not been sufficiently examined, leaving critical 

knowledge gaps that impede the development of tailored interventions. 

Furthermore, limited research exists on the role of biodiversity conservation in moderating the 

relationship between agroforestry practices and productivity. Agroforestry systems are inherently 

multifunctional, yet most studies fail to comprehensively examine how the integration of 

biodiversity conservation within these systems influences agricultural productivity and ecological 

sustainability (Kassa, 2022). This knowledge gap is particularly critical for regions like Mount 

Elgon, where biodiversity plays a pivotal role in ecosystem services, such as pollination and pest 

control, that directly impact agricultural outcomes. 

Additionally, existing research often focuses on either qualitative or quantitative methodologies, 

rarely integrating the two to provide a holistic understanding of agroforestry systems. This 

methodological gap limits the depth and breadth of insights that can inform policies and 

interventions tailored to the unique needs of smallholder farmers in Mount Elgon. Addressing these 

research gaps is essential to unlocking the full potential of agroforestry as a sustainable 

development strategy and enhancing the livelihoods of smallholder farmers while conserving the 

region’s biodiversity. This study aims to fill these gaps by analyzing agroforestry practices, 

biodiversity conservation and productivity in Mount Elgon Sub-County, Kenya, thereby providing 

evidence-based insights to inform policy and practice. 

1.3 Research Objectives 

1.3.1 General Objective 

The main objective of the study is to determine the relationship between agroforestry practices, 

biodiversity conservation and productivity in Mt. Elgon Sub-County, Kenya.  



8 

 

1.3.2 Specific Objectives 

The specific objectives were as follows; 

i. To analyze the effect of type of agroforestry on productivity in Mt. Elgon Sub-County, 

Kenya. 

ii. To investigate the effect of scale of agroforestry implementation on productivity in Mt. 

Elgon Sub-County, Kenya. 

iii. To examine the effect of utilization of extension services on productivity in Mt. Elgon Sub-

County, Kenya. 

iv. To evaluate the moderating effect of biodiversity conservation on the relationship between 

agroforestry practices and productivity in Mt. Elgon Sub-County, Kenya. 

1.4 Research Questions 

The study was guided by the following research questions: 

i. What is the effect of type of agroforestry on productivity in Mt. Elgon Sub-County, Kenya? 

ii. How does the scale of agroforestry implementation affect productivity in Mt. Elgon Sub-

County, Kenya? 

iii. What is the effect of utilization of extension services on productivity in Mt. Elgon Sub-

County, Kenya? 

iv. What is the moderating effect of biodiversity conservation on the relationship between 

agroforestry practices and productivity in Mt. Elgon Sub-County, Kenya? 

1.5 Scope of the Study 

The study focused on Mount Elgon Sub-County in north-western Kenya, an area spanning 

approximately 35,000 hectares and home to a population of about 135,000 people (Nyberg et al., 

2020). The region is characterized by a savanna climate, fertile soils and a predominantly 

smallholder farming system. These smallholders engage in subsistence farming, cash crop 

cultivation and dairy production, forming the backbone of the local agricultural economy. 

However, challenges such as deforestation, soil degradation and unsustainable farming practices 

have significantly affected agricultural productivity, reduced household incomes and contributed 



9 

 

to environmental degradation. The study targeted smallholder farmers practicing agroforestry in 

Mt. Elgon Sub-County, Kenya, estimated at 16,283 households. A sample size of 384 farmers was 

determined using Fisher’s formula. It analyzed three key dimensions of agroforestry practices: the 

types of agroforestry systems employed, the scale of implementation and the role of extension 

services in promoting these practices. Additionally, it evaluated the moderating effect of 

biodiversity conservation on the relationship between agroforestry practices and productivity. 

A mixed-methods approach was employed, integrating both qualitative and quantitative research 

methodologies. This involved the collection of primary data through surveys, interviews and focus 

group discussions, as well as the analysis of secondary data from relevant reports and studies. The 

study aimed to provide a comprehensive understanding of agroforestry practices in the region, 

contributing to evidence-based policy formulation and sustainable development initiatives in 

Mount Elgon Sub-County. The study was conducted between September 2024 and April 2025. 

1.6 Significance of the Study 

The study was beneficial to the following: 

1.6.1 Policy Makers and Regulators 

This research is of great significance for regulators and policymakers, especially in the context of 

Mount Elgon, Kenya, where smallholder agroforestry plays a major role. Policymakers and 

regulators obtained vital insights into the potential of smallholder agroforestry techniques in 

fostering sustainable development and livelihood improvement by exploring the environmental 

benefits of this type of farming. Comprehending the distinct advantages of agroforestry, such as 

better conservation of soil, preservation of biodiversity, heightened crop productivity and 

augmented household income, empowers policymakers to customize policies and regulations that 

facilitate and encourage the implementation of agroforestry among smallholders in Mount Elgon. 

Furthermore, policymakers coordinated their policies with more general objectives for 

environmental conservation and development by acknowledging the socioeconomic and 

environmental benefits of agroforestry. 

1.6.2 Academicians and Researchers 



10 

 

The study provided a foundational framework for future academicians and researchers interested 

in investigating the benefits of smallholder agroforestry in the context of Mount Elgon, Kenya. 

Comprehensive insights into the environmental and socioeconomic benefits of agroforestry 

practices in this region served as a valuable foundation for further research endeavours. Future 

academicians and researchers will leverage the findings of this study to explore additional 

dimensions of smallholder agroforestry, such as its long-term impacts, scalability and specific 

mechanisms underlying its effectiveness. Moreover, the methodology and analytical approach 

employed in this study served as a guide for designing similar research studies in the future, 

thereby contributing to the advancement of knowledge in the field of agroforestry and sustainable 

land management. 

1.6.3 Community 

Local communities in the Mount Elgon region of Kenya also benefited from this study. Uncovering 

the environmental and socioeconomic benefits of smallholder agroforestry, the findings informed 

community members about the potential advantages of adopting such practices. Understanding the 

benefits of agroforestry on soil conservation, biodiversity conservation, crop yields and household 

income empowered communities to make informed decisions regarding land management and 

agricultural practices. Additionally, the study highlighted opportunities for community 

engagement and participation in agroforestry initiatives, fostering a sense of accountability and 

ownership among locals. 

1.7 Chapter Summary 

The first chapter offers a synopsis of the research, outlining the key elements to be explored. It 

begins by providing a background of the study, offering insights into the concept and context of 

smallholder agroforestry, as well as identifying research gaps. Following this, the statement of the 

problem highlights the specific gap addressed by the study and its incremental contribution to 

existing knowledge. Subsequently, the research objectives are presented, comprising both the 

general objective, which mirrors the study’s title and specific objectives aimed at guiding the 

research process. These objectives are complemented by research questions, formulated to further 

elucidate the study’s focus and guide data collection and analysis. The scope of the study is then 

discussed, delineating the specific parameters and boundaries within which the research operated, 

including the geographical and temporal dimensions. Finally, the significance of the study is 



11 

 

outlined, detailing the various stakeholders and beneficiaries who stand to gain from the research 

findings, ranging from policymakers and regulators to local communities and academia. 

Chapter two offers a comprehensive review of the body of research on agroforestry practices, 

biodiversity conservation and productivity of smallholder farmers. It begins with a theoretical 

review, exploring the foundational theories that inform the study. This is followed by an empirical 

literature review, which examines existing research findings related to the key variables of the 

study. The chapter then identifies gaps in the current literature and concludes with a summary of 

the literature reviewed, a conceptual framework illustrating the relationships between the study 

variables and the operationalization of these variables. Chapter three outlines the methodology to 

be employed in the study, detailing the philosophical underpinnings, research design, population 

selection, sampling methods, procedures for data collection, reliability and validity of instruments, 

data analysis techniques, ethical considerations and a summary of the chapter.  

 

 

 

  



12 

 

CHAPTER TWO  

LITERATURE REVIEW 

2.1 Introduction 

This chapter offers a comprehensive review of the body of research on agroforestry practices, 

biodiversity conservation and productivity of smallholder farmers. It begins with a theoretical 

review, exploring the foundational theories that inform the study. This is followed by an empirical 

literature review, which examines existing research findings related to the key variables of the 

study. The chapter then identifies gaps in the current literature and concludes with a summary of 

the literature reviewed, a conceptual framework illustrating the relationships between the study 

variables and the operationalization of these variables. 

2.2 Theoretical Review 

This study drew upon three foundational theories. Firstly, the theory of agroforestry systems 

elucidates the integration of trees with crops and/or livestock, highlighting how this amalgamation 

can boost agricultural productivity and fortify ecosystem resilience. Secondly, resource 

dependence theory was employed to analyze the relationships between stakeholders involved in 

agroforestry initiatives, emphasizing how the control and access to resources such as knowledge, 

funding and support affect the implementation and sustainability of agroforestry practices. The 

theory of planned behaviour delved into the determinants of farmers’ adoption of agroforestry 

practices, emphasizing the impact of perceived behavioural control, subjective norms and attitudes 

on their decision-making processes. These theoretical foundations collectively provide an in-depth 

understanding of the multifaceted benefits, adoption dynamics and resource management 

implications of agroforestry practices. 

2.2.1 Theory of Agroforestry Systems 

The Theory of Agroforestry Systems has been advanced by proponents such as Nair (1993) and 

Jose et al. (2009), who emphasize the strategic integration of trees within agricultural landscapes 

to enhance overall productivity and ecological resilience. This theory posits that by combining 

trees with crops and/or livestock, agroforestry systems can diversify agricultural production, 

improve soil fertility, mitigate environmental degradation and contribute to sustainable land use 

practices (Jose et al., 2009). Scholars have further developed this theory to incorporate a variety 



13 

 

of agroforestry techniques such as silvopasture, alley cropping and home gardens, each tailored to 

specific ecological and socio-economic contexts (Nair, 1993). 

The theory of agroforestry systems explores several key arguments and concepts essential to its 

application. Central to this theory is the notion that trees in agroecosystems serve multiple 

functions beyond mere timber production, including providing shade, improving microclimatic 

conditions and contributing to biodiversity conservation (Jose et al., 2009). Moreover, agroforestry 

systems are viewed as sustainable alternatives to conventional agriculture by promoting resource-

use efficiency, reducing greenhouse gas emissions and enhancing socio-economic resilience 

among smallholder farmers (Nair, 1993). 

In the context of this study on agroforestry practices, the theory aligns closely with the identified 

objectives and variables. The theory’s emphasis on different types of agroforestry systems (such 

as silvopasture and alley cropping), scales of implementation and the integration of extension 

services resonates with the study’s focus on understanding how these factors influence productivity 

and biodiversity conservation in Mount Elgon, Kenya. 

In the Kenyan context, particularly in Mount Elgon, smallholder farmers often operate on 

fragmented and degraded lands, making the adoption of agroforestry critical for enhancing 

productivity. The theory’s focus on tailored systems resonates with the region’s specific ecological 

and socio-economic challenges, such as deforestation and declining soil fertility. By incorporating 

extension services, the theory emphasizes the importance of technical support to optimize 

agroforestry outcomes, which is vital for smallholders lacking resources and expertise. 

Furthermore, the theory’s advocacy for biodiversity conservation aligns with Mount Elgon’s 

urgent need to address habitat loss and ecosystem degradation, reinforcing agroforestry as a 

sustainable solution for balancing productivity and environmental stewardship. While the theory 

of agroforestry systems effectively addresses ecological integration and productivity, it does not 

fully account for the institutional and behavioural drivers influencing farmer decisions. Resource 

dependence theory and the theory of planned behaviour complement this gap by offering insights 

into how access to resources and individual intentions shape agroforestry adoption and outcomes. 

 

 



14 

 

2.2.2 Resource Dependence Theory 

Pfeffer and Salancik (1978) developed the Resource Dependence Theory (RDT), which posits that 

organizations strategically manage their external dependencies on resources to ensure 

sustainability and effectiveness. Applied to smallholder agroforestry in Mount Elgon, Kenya, RDT 

emphasizes how farmers rely on natural resources and external support systems to enhance 

agricultural practices and livelihoods. In this context, farmers integrate trees with crops and 

livestock to diversify their resource base, mitigating risks associated with climate variability, 

enhancing soil fertility and supporting biodiversity conservation efforts (Pfeffer & Salancik, 1978). 

RDT argues that farmers engage in agroforestry practices to reduce dependency on external inputs 

and optimize resource use efficiency (Kalamkar & Acharya, 2024). The theory suggests that 

farmers strategically choose agroforestry systems based on their resource dependencies, such as 

soil nutrient levels and water availability (Sheppard et al., 2020). This choice influences indicators 

such as tree species diversity, crop diversity and the integration of livestock, reflecting how farmers 

manage their resource dependencies to improve productivity and sustainability. Moreover, RDT 

highlights the role of external dependencies in shaping farmers’ decisions regarding the scale of 

agroforestry implementation, including landholding size and allocation for agroforestry practices. 

The RDT is highly applicable to the study’s variables in Mount Elgon. Firstly, regarding type of 

agroforestry, the theory predicts that farmers will select systems that minimize external 

dependencies while maximizing resource efficiency, influencing tree-crop-livestock integration. 

Secondly, for Scale of Implementation, RDT suggests that farmers adjust agroforestry practices 

based on their landholding size and resource availability, influencing the extent and allocation of 

agroforestry land. Thirdly, concerning extension services, RDT posits that farmers utilize services 

to mitigate external dependencies, affecting accessibility, training opportunities and market access. 

Finally, for Productivity and Biodiversity Conservation, the theory underscores how agroforestry 

practices optimize resource use and reduce external dependencies, enhancing soil conservation, 

crop yields, income and biodiversity. 

In the context of Mount Elgon, where smallholder farmers face challenges like declining soil 

fertility and climate variability, RDT explains the adoption of specific agroforestry systems, such 

as integrating trees with crops and livestock, to diversify resource use and mitigate risks. The 

theory aligns with study variables by suggesting that the type of agroforestry is determined by 



15 

 

farmers’ efforts to minimize reliance on external inputs and maximize efficiency, while the scale 

of implementation reflects resource availability, such as land size. Furthermore, RDT highlights 

the critical role of extension services in reducing farmers’ external dependencies, influencing 

training, access to markets and agroforestry adoption. Ultimately, the theory underscores how 

optimizing resource use through agroforestry practices directly enhances productivity and 

promotes biodiversity conservation, crucial for sustainable livelihoods in Mount Elgon. While 

resource dependence theory effectively explains how farmers adapt agroforestry practices to 

manage limited resources, it overlooks individual behavioural intentions and attitudes that drive 

adoption. The theory of planned behaviour complements this gap by focusing on farmers’ 

motivations, perceived control and social norms influencing agroforestry decisions. 

2.2.3 Theory of Planned Behaviour 

The Theory of Planned Behaviour (TPB), proposed by Ajzen (1991), is a widely recognized 

psychological theory that explains human behaviour through the lens of attitudes, individual 

beliefs, perceived behavioural control and subjective norms. Applied to the context of smallholder 

agroforestry in Mount Elgon, Kenya, TPB suggests that farmers’ intentions to adopt agroforestry 

practices are influenced by their attitudes towards agroforestry, subjective norms within their social 

networks and perceived control over implementing these practices effectively (Ajzen, 1991). 

TPB argues that individuals’ behavioural intentions are shaped by their attitudes towards the 

behavior (whether positive or negative), subjective norms (whether they feel social pressure to 

engage or not) and perceived behavioural control (whether they believe they can carry out the 

behavior) (Ajzen, 2020). In the case of smallholder farmers in Mount Elgon, TPB posits that 

favourable attitudes towards agroforestry (e.g., perceived benefits such as increased crop yield and 

income), supportive subjective norms (e.g., encouragement from family, neighbours and 

community leaders) and perceived behavioural control (e.g., access to extension services and 

technical knowledge) are critical determinants of their intention to adopt agroforestry practices. 

TPB provides a robust framework for understanding the study’s variables in Mount Elgon. Firstly, 

for Type of Agroforestry, TPB predicts that farmers’ attitudes towards specific agroforestry 

systems (e.g., tree-crop integration, agroforestry with livestock) influence their adoption decisions, 

shaping indicators such as tree species diversity and crop variety. Secondly, concerning Scale of 

Implementation, TPB suggests that farmers’ intentions are influenced by subjective norms and 



16 

 

perceived control over landholding extent and agroforestry plot size, impacting the scale and 

allocation of agroforestry practices. Thirdly, regarding Extension Services, TPB underscores the 

role of perceived behavioural control in accessing services, training opportunities and market 

accessibility, influencing farmers’ adoption and implementation of agroforestry. Finally, for 

productivity and biodiversity conservation, TPB suggests that farmers’ intentions to engage in 

agroforestry are driven by perceived benefits, social pressures and confidence in achieving 

environmental and economic outcomes. 

The type of agroforestry adopted, such as integrating trees with crops or livestock, is influenced 

by farmers’ positive attitudes toward specific systems and the encouragement of social networks. 

The scale of implementation is determined by perceived behavioural control, including access to 

resources and landholding size, which affects the extent of agroforestry adoption. TPB also 

highlights the importance of extension services, as access to training and support enhances farmers’ 

confidence in implementing agroforestry practices effectively. Lastly, the theory links behavioural 

intentions to outcomes, suggesting that favourable attitudes and strong social support drive higher 

productivity and biodiversity conservation in agroforestry systems, addressing both ecological and 

economic challenges in Mount Elgon. While the theory of planned behaviour effectively captures 

the psychological and social factors influencing agroforestry adoption, it does not fully account 

for the structural and resource-based constraints faced by farmers. Resource dependence theory 

complements this by emphasizing the external resource limitations and strategic decisions that 

shape agroforestry implementation. 

2.3 Empirical Literature Review 

2.3.1 Type of Agroforestry and Productivity  

Telwala (2023) and Araya et al. (2023) offer compelling evidence from India and Malawi 

respectively, emphasizing agroforestry as a nature-based solution to enhance resilience in drought-

prone and climate-stressed areas. Both studies highlight specific systems such as alley cropping, 

silvopasture and macadamia-based agroforestry, demonstrating how these enhance soil fertility, 

biodiversity and income stability. While Telwala provides a diversified system-level analysis 

incorporating home gardens and livestock integration, Araya et al. take a more crop-specific 

approach, focused on macadamia. Their emphasis on local knowledge and community 

involvement is echoed in Yasin et al. (2023), who explore traditional agroforestry in Pakistan. 



17 

 

However, while Araya et al. centre on modern climate-smart practices, Yasin et al. stress the 

significance of indigenous knowledge in sustaining semi-arid systems. This comparison highlights 

a key tension in agroforestry discourse: the need to balance modern innovations with traditional 

ecological practices to ensure long-term sustainability. 

Studies such as De Giusti et al. (2019) and Miller et al. (2020) bring in empirical and systematic 

review approaches respectively, linking agroforestry directly to measurable climate benefits such 

as greenhouse gas reduction and increased carbon sequestration. De Giusti et al., working with 

smallholder farmers in Kenya, underscore the synergistic effects of tree-crop-livestock integration 

on productivity and resilience. However, the systemic review by Miller et al. identifies a lack of 

region-specific outcomes and long-term assessments, highlighting a broader issue in agroforestry 

research: generalizability across socio-ecological contexts remains weak due to a reliance on cross-

sectional or generalized findings. 

Furthering this critique, Lehmann et al. (2020) and Alifa et al. (2024) both emphasize the economic 

and ecological sustainability of agroforestry, but from different angles. Lehmann focuses on the 

profitability and scaling challenges of diversified agroforestry systems, revealing structural 

barriers such as lack of initial investment and policy support. Alifa et al., using sustainability 

theory, similarly highlight agroforestry’s promise in mitigating ecological trade-offs but warn 

against overreliance on secondary data. Both studies call for empirical, locally grounded research 

to validate theoretical claims, an appeal particularly relevant to under-studied areas like Mount 

Elgon. 

Willmott et al. (2023) add another dimension by applying ecological theory to analyze the socio-

ecological benefits of agroforestry, particularly in terms of ecosystem services and biodiversity. 

However, their findings, like those of Miller et al., suffer from a lack of contextualization, limiting 

their practical applicability. Kassa (2022) identifies agroforestry as a climate-smart agribusiness 

model but does not account for underlying variables influencing its adoption, such as socio-

economic or institutional dynamics. 

In the Kenyan context, while Korir et al. (2022) and Kinyili et al. (2020) affirm the role of 

agroforestry in addressing food insecurity and land degradation, these studies are geographically 

concentrated in central and eastern regions. This creates a significant knowledge gap for areas such 

as Mount Elgon, which, despite its ecological richness and socio-economic vulnerability, remains 



18 

 

underexplored. The region’s specific agroecological dynamics including steep terrain, shifting 

rainfall patterns and high biodiversity, require tailored agroforestry strategies that may differ 

significantly from those in other Kenyan regions. Moreover, the existing studies have not 

sufficiently disaggregated the types and scales of agroforestry systems or linked them to 

measurable productivity outcomes for smallholder farmers in this region. 

2.3.2 Scale of Implementation and Productivity 

Nyberg et al. (2020), within the Kenya Agricultural Carbon Project, provided context-specific 

evidence from sub-Saharan Africa, showing that larger agroforestry plots and broader land 

allocation enhanced soil fertility and overall productivity. This study offers a detailed empirical 

basis for linking scale to both ecological restoration and farm-level gains, particularly in 

smallholder settings. In contrast, Castle et al. (2022) conducted a systematic review primarily 

focused on high-income countries, yet arrived at similar conclusions. Their synthesis found that 

well-allocated agroforestry plots improve ecosystem services, including soil health and food 

security. The consistency of these findings across distinct socio-economic and ecological contexts 

suggests that the relationship between scale and productivity is generalizable, although its 

expression may vary depending on the enabling environment and institutional support. 

Both studies operationalized scale using comparable indicators such as landholding size, 

proportion of land under agroforestry and relative plot size, allowing for meaningful comparison. 

However, while Nyberg et al. grounded their work in field data, Castle et al. synthesized existing 

studies, thus potentially inheriting methodological inconsistencies from the underlying literature. 

This contrast highlights a methodological gap: the need for more cross-contextual, field-based 

studies that validate systematic review findings under diverse agroecological conditions. 

Duffy et al. (2021) extended the conversation by linking scale of implementation to food security 

outcomes among smallholders in Indonesia. Like Nyberg et al., they confirmed that larger, more 

diversified agroforestry systems support household resilience and income stability. However, 

Duffy et al. placed stronger emphasis on diversification within agroforestry systems as a buffer 

against climate and market risks, suggesting that scale alone is not sufficient, system complexity 

also matters. This adds a layer of nuance to prior findings, revealing that the quality and diversity 

of agroforestry interventions must accompany scale for optimal productivity outcomes. 



19 

 

Economic dimensions were explored by Cialdella et al. (2023), who analyzed how the extent of 

land under agroforestry affects profitability and sustainability. Their study aligns with earlier 

findings by confirming that larger plots can deliver both ecological and economic returns. 

However, their focus on cost-effectiveness and financial incentives introduces a critical dimension 

often underexplored in biophysical studies: the role of market integration and economic viability 

in scaling agroforestry. By doing so, they identify a gap in earlier work (e.g., Nyberg et al., Duffy 

et al.), which often emphasizes environmental or food security benefits without fully addressing 

financial sustainability. 

Notably, Gosling et al. (2021) took a different approach by using modelling to assess the viability 

of silvopasture systems in less productive regions. While their findings confirmed the productivity 

potential of agroforestry, they did not directly investigate the scale of implementation. This 

omission limits the applicability of their results to real-world planning and underscores a recurring 

gap in theoretical modelling studies, the lack of empirical validation concerning how plot size and 

land allocation impact productivity in practice. Their identification of labour intensity as a barrier, 

however, introduces a socio-economic variable absent in most of the other studies, suggesting that 

implementation scale must be evaluated not only in spatial but also in labour and institutional 

terms. 

2.3.3 Extension Services and Productivity 

Castle et al. (2021) conducted a systematic review that broadly concluded that extension services, 

particularly those providing training and technical support play a pivotal role in enhancing 

agroforestry adoption and productivity through improved soil health, crop yields and income 

diversification. Their meta-analysis presents extension services as a vital knowledge transfer tool. 

However, the review’s breadth limits its ability to examine how variations in local governance 

structures, resource allocation and community engagement mediate this effectiveness. The lack of 

localized empirical insights points to a methodological gap in understanding how and under what 

conditions extension services drive productivity gains. 

Complementing Castle et al., Mukhlis et al. (2022) take a more community-focused lens, 

emphasizing the socio-economic and environmental impacts of agroforestry and the facilitative 

role of extension services. While they reinforce the centrality of knowledge dissemination, their 

findings go further by highlighting the need for institutional backing and targeted policies. This 



20 

 

underscores a key contrast: whereas Castle et al. focus on extension as a technical tool, Mukhlis et 

al. present it as an institutional mechanism embedded within broader development strategies. Yet, 

both studies leave unexplored the role of farmer feedback in tailoring extension content to local 

needs, signalling a practical gap in adaptive service design. 

Ahmad et al. (2023) shift attention to individual-level adoption, revealing how farmers’ 

perceptions and socio-economic factors such as land tenure, access to credit and institutional trust, 

interact with extension services to influence agroforestry uptake. Unlike the previous two studies 

that emphasize the provision of services, Ahmad et al. question their accessibility and relevance. 

This contrast exposes a recurring oversight in the literature: few studies interrogate the equity and 

inclusivity of extension models, particularly in marginalized or resource-poor farming contexts. 

A more systems-oriented perspective is offered by Pédelahore et al. (2023), who frame extension 

services not just as conveyors of information, but as dynamic facilitators of market linkages, policy 

feedback and adaptive socio-economic transformation. Their methodological approach integrates 

agroforestry within a complex system of stakeholders and institutional interactions. This broader 

framing challenges the relatively static conception of extension found in earlier studies and calls 

for a shift toward participatory, co-designed service models. However, empirical testing of this 

adaptive framework in rural African contexts remains limited, highlighting a theoretical and 

application gap. 

In contrast to the conceptual richness of Pédelahore et al., Sheppard et al. (2020) return to a 

practical orientation, examining case studies in Southern Africa. They reinforce the critical role of 

extension services in climate adaptation through agroforestry but recommend stronger stakeholder 

coordination and policy integration. Unlike Castle et al., they identify extension not merely as a 

farm-level input but as a critical link between local resilience and national climate strategies. This 

reframing brings attention to a gap in scale integration how national policy goals translate into 

actionable, context-specific extension programs remains underexplored. 

Kenyan studies by Kinyili et al. (2020) and Korir et al. (2022) add regional specificity, showing 

that despite relatively high adoption rates of agroforestry practices in ASALs and parts of Kericho 

County, extension services remain under-resourced and inconsistently linked to productivity 

outcomes. Kinyili et al. highlight the absence of triangulated data on adoption drivers, while Korir 

et al. note a lack of direct connection between extension efforts and productivity metrics. Together, 



21 

 

they point to an empirical gap in measurement: many studies assume rather than demonstrate 

causality between extension services and productivity. 

2.3.4 Moderating Effect of Biodiversity Conservation on Relationship between Agroforestry 

Practices and Productivity 

The literature widely recognizes biodiversity conservation as a key moderating factor that 

strengthens the positive relationship between agroforestry practices and agricultural productivity. 

However, across the reviewed studies, there is notable variation in how this moderating effect is 

conceptualized, measured and integrated into agroforestry models, indicating both theoretical and 

empirical gaps. Swallow et al. (2020) offer a foundational synthesis by positioning biodiversity as 

a central component of productive and resilient agroforestry systems. They emphasize the role of 

agrobiodiversity in supporting critical ecosystem services such as pest regulation, pollination and 

nutrient cycling that directly contribute to higher and more stable yields. Their review highlights 

that agroforestry systems outperform monoculture in generating biodiversity co-benefits, 

especially when implemented within integrated landscape management frameworks. However, 

while they propose that biodiversity enhances productivity through ecosystem functioning, their 

evidence remains primarily conceptual and synthesized from diverse contexts. This broad 

approach, while informative, lacks region-specific empirical validation, particularly in African 

highland ecosystems like Mount Elgon, leaving a gap in practical applicability. 

Klie (2018) narrows the focus by examining biodiversity’s moderating role through a case study 

in Brazil’s Atlantic Forest, linking agroforestry adoption to habitat provision for endemic species 

and improved ecosystem services. Unlike Swallow et al., Klie’s study incorporates farmer 

perspectives, revealing that income diversification and increased productivity are perceived 

benefits of biodiversity-enhancing agroforestry systems. However, the findings also expose 

barriers such as lack of knowledge and technical support that hinder full realization of 

biodiversity’s productivity benefits. This contrast highlights an implementation gap: while 

biodiversity is acknowledged as beneficial, systemic obstacles limit its integration into smallholder 

practices. Moreover, the species-specific conservation lens, while important ecologically, offers 

limited insight into broader agro-ecological productivity metrics. 

Mulatu and Hunde (2019) extend the discourse by framing biodiversity conservation within the 

context of climate change mitigation and adaptation. Their review connects biodiversity-enhancing 



22 

 

agroforestry systems with resilience to climate variability and improved carbon sequestration, 

further strengthening the case for biodiversity as a productivity moderator. Unlike Klie and 

Swallow et al., their focus is on ecosystem-wide resilience rather than species conservation or 

income effects. This systemic framing adds conceptual depth but lacks a direct quantification of 

productivity improvements, revealing a measurement gap in linking biodiversity with tangible 

yield or income outcomes in agroforestry contexts. 

Liliane (2021) provides empirical clarity by analyzing the influence of biodiversity-conserving 

agroforestry technologies on farmer livelihoods in Rwanda. Her study is distinct in employing 

both qualitative and quantitative analyses, demonstrating that biodiversity benefits such as reduced 

soil erosion and improved fertility directly contribute to enhanced productivity and income. 

Liliane’s work offers one of the few studies that explicitly ties biodiversity’s moderating role to 

measurable economic outcomes, thereby partially addressing the empirical and attribution gaps 

identified in earlier literature. However, the study also notes that household and farm-level 

variables mediate these outcomes, suggesting that biodiversity’s effect is not uniform but 

contingent on socio-economic and agro-ecological factors. This reveals a contextual gap: 

biodiversity’s moderating effect must be understood not as a constant, but as one shaped by local 

conditions and resource endowments. 



23 

 

2.4 Summary of Literature and Gap 

Table 2.1 Summary of Literature Review 

Author 

and year of 

study 

Study focus Sector of 

study 

Theories 

applied 

Methodology 

applied 

Summary of findings Research Gap(s) 

Alifa et al. 

(2024) 

Socioeconomic 

and ecological 

sustainability of 

agroforestry 

Agriculture, 

Environmental 

Science 

Sustainability 

theory 

Literature 

review 

The study emphasizes the 

need to understand the 

extent to which 

agroforestry can minimize 

economic and ecological 

trade-offs, optimizing 

benefits for both people 

and the environment.  

The study does 

not use primary 

data to arrive at 

findings, a 

weakness in its 

methodology 

Gosling et 

al. (2021) 

Socio-economic 

conditions 

driving the 

selection of 

agroforestry at 

the forest frontier 

Agriculture, 

Environmental 

Management 

Modern 

Portfolio 

Theory 

Modelling 

approach, 

Robust 

optimization 

Silvopasture emerges as a 

promising land use, 

especially for farms with 

less productive soils. 

Although the higher 

labour demands compared 

to conventional pasture 

may hinder adoption for 

farms with labour 

shortages.  

The study fails 

to look at the 

scale of 

implementation 

of agroforestry 

and its linkage 

to productivity 

Kassa 

(2022) 

Agroforestry as a 

pathway to 

climate-smart 

agribusiness: 

challenges and 

opportunities to 

smallholder 

farmers Agriculture No theory used 

Literature 

review 

Agroforestry systems 

offer new commercial 

opportunities to 

smallholder farmers and 

are gaining popularity as 

eco-friendly and climate-

smart practices.  

No theory or 

moderating 

variables used, a 

weakness in its 

approach 



24 

 

Willmott 

et al. 

(2023) 

Harnessing the 

socio-ecological 

benefits of 

agroforestry 

diversification  

Agriculture, 

Forestry, 

Environmental 

Management 

Ecological 

theory 

Literature 

review, 

Questionnaire 

Agroforestry is 

recognized for providing 

multiple ecosystem 

services, biodiversity 

habitat and socio-

economic development 

opportunities.  

The study 

findings were 

general and not 

contextualized 

to a specific 

region or area 

Kinyili et 

al. (2020) 

Socio-economic 

and institutional 

factors 

influencing 

adoption of 

agroforestry in 

ASALs 

Agriculture, 

Rural 

Development 

in Sub 

Saharan 

Africa None used Survey research 

The study revealed that 

82% of respondents had 

adopted agroforestry, with 

boundary planting, 

hedgerow, woodlots, 

scattered planting and 

alley cropping being the 

main practices.  

No triangulation 

of data was done 

Mukhlis et 

al. (2022) 

Understanding 

socio-economic 

and 

environmental 

impacts of 

agroforestry on 

rural 

communities 

Agriculture, 

Rural 

Development 

Socioeconomic 

theory 

Literature 

review 

Agroforestry is 

recognized for its 

potential to increase food 

security, improve 

smallholders’ income, 

promote gender equality 

and stimulate cultural 

activities in rural areas. 

Additionally, it enhances 

ecosystem services 

through improved soil 

structure, increased 

carbon sequestration and 

higher water retention.  

Secondary data 

was used and 

the farmers 

responses were 

not included 

Korir et al. 

(2022) 

Classification 

and socio-

economic 

Agriculture, 

Rural 

Development 

Agroforestry 

classification 

theory  

Qualitative 

research 

Four classes of 

agroforestry systems were 

identified: 

The study did 

not link 

agroforestry 



25 

 

benefits of 

agroforestry 

systems  

in Soin Ward, 

Kericho 

County, 

Kenya 

agrosilvopastoral, 

agrosilvicultural, 

silvopastoral and 

integrated farm-based 

agroforestry. Respondents 

predominantly preferred 

Grevillea tree species for 

blending with sugarcane 

in agroforestry systems.  

practices to 

productivity  

Telwala 

(2023) 

Unlocking the 

potential of 

agroforestry as a 

nature-based 

solution for 

SDGs. 

Agriculture, 

Environmental 

Science 

Sustainability 

theory 

Case study, 

field 

observations 

Agroforestry’s role in 

achieving SDGs, 

emphasizing its potential 

in sustainable 

development in drought-

prone regions. 

Limited data on 

long-term 

impacts of 

agroforestry. 

De Giusti 

et al. 

(2019) 

Agroforestry as a 

climate change 

mitigation 

practice in 

smallholder 

farming. 

Agriculture, 

Climate 

Science 

None Quantitative 

analysis, field 

data collection 

Agroforestry systems 

effectively sequester 

carbon, providing 

mitigation benefits in 

smallholder farming 

systems. 

Lack of 

comparative 

studies with 

other mitigation 

practices. 

Yasin et al. 

(2023) 

Traditional 

agroforestry 

systems in 

climate change 

mitigation. 

Agriculture, 

Climate 

Science 

None Quantitative 

survey, carbon 

measurement 

Traditional agroforestry 

practices in semi-arid 

regions contribute 

significantly to carbon 

sequestration. 

Need for 

broader regional 

studies to 

validate 

findings. 

Nyberg et 

al. (2020) 

Effects of 

agroforestry in 

the Kenya 

Agricultural 

Agriculture, 

Environmental 

Science 

None Quantitative 

analysis, site 

comparison 

Agroforestry enhances 

soil fertility, biodiversity 

and resilience to climate 

change in Kenya. 

Need for long-

term impact 

studies on 

different land 

types. 



26 

 

Carbon Project 

(KACP). 

Ahmad et 

al. (2023) 

Socioeconomic 

determinants and 

perceptions of 

agroforestry 

adoption. 

Agriculture None Survey research Key socio-economic 

factors influence 

agroforestry adoption in 

northern Pakistan, with 

variations in perceptions. 

No triangulation 

of data in the 

study. 

Pédelahore 

et al. 

(2023) 

Identifying 

socio-economic 

determinants in 

agroforestry 

transformations. 

Agriculture, 

Rural 

Development 

None Qualitative 

research 

Four agroforestry system 

classes identified, 

focusing on tree species 

preferences in Kenya. 

Lack of link 

between 

practices and 

productivity. 

 

 



27 

 

2.5 Conceptual Framework 

Independent variables encompass various dimensions of agroforestry practices, including the type 

of agroforestry, scale of implementation and extension service variables, such as availability, 

accessibility and training opportunities. The dependent variable encompasses productivity 

benefits, including improved soil conservation, enhanced crop yields and increased household 

income. Biodiversity conservation forms the moderating variable. 

                                      Dependent Variable 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Independent Variables       

Figure 2.1 Conceptual Framework 

 

 

 

 

 

Productivity 

 

• Improved 

agricultural 

output 

• Increased 

household 

income 

Scale of implementation 

• Landholding extent for 

smallholder agroforestry 

• Number of trees in the farm 

• Agroforestry land allocation 

extent 

Extension Services 

• Availability and accessibility  

• Training and capacity-

building opportunities 

• Accessibility of markets  

Type of agroforestry 

• Tree species diversity 

• Crop diversity 

• Livestock integration 

Moderating Variable  

• Biodiversity 

conservation 

 

Control variables 

• Level of education 

• Soil health   



28 

 

The conceptual framework is grounded in the theory of agroforestry systems, which links 

agroforestry practices (independent variable) to improved productivity (dependent variable) 

through ecological benefits. The resource dependence theory supports the role of extension 

services by highlighting the importance of access to resources for effective implementation. The 

theory of planned behaviour explains how farmers’ attitudes, norms and perceived control 

influence adoption. Biodiversity conservation moderates the agroforestry–productivity 

relationship by enhancing ecosystem services, reinforcing the interconnectedness of the 

framework. 

2.6 Operationalization of Variables 

Table 2.2 Operationalization of Variables 

Variable Definition Indicators Measurement 

Method 

Type of 

Agroforestry 

Different 

agroforestry 

systems used 

• Tree species diversity 

• Crop diversity 

• Livestock integration 

Continuous or/and 

ordinal 

Scale of 

Implementation 

Extent of 

agroforestry 

practice adoption 

• Landholding extent for 

smallholder agroforestry 

• Number of trees in the farm 

• Agroforestry land allocation 

extent 

Continuous or/and 

ordinal 

Extension 

Services 

Support and 

training provided 

to farmers 

• Availability and accessibility  

• Training and capacity-

building opportunities 

• Accessibility of markets 

Continuous or/and 

ordinal 

Productivity Agricultural 

outputs and 

benefits 

• Improved agricultural output 

• Increased household income 

Continuous or/and 

ordinal 

Biodiversity 

Conservation 

Conservation 

efforts within 

agroforestry 

practices 

• Species diversity 

• Habitat quality 

Continuous or/and 

ordinal 



29 

 

 

2.7 Chapter Summary 

This chapter reviewed the theoretical and empirical literature relevant to agroforestry practices, 

biodiversity conservation and productivity. It highlighted the gaps in existing research, particularly 

in the context of Mount Elgon, Kenya. The chapter concluded with a conceptual framework 

outlining the relationships between the study variables and the operationalization of these 

variables, setting the stage for the subsequent chapters. 

  



30 

 

CHAPTER THREE 

RESEARCH METHODOLOGY 

3.1 Introduction 

This chapter outlines the methodology employed in the study, detailing the philosophical 

underpinnings, research design, population selection, sampling methods, procedures for data 

collection, reliability and validity of instruments, data analysis techniques, ethical considerations 

and a summary of the chapter. Each section is meticulously crafted to ensure the robustness and 

rigor of the research, aiming to provide comprehensive insights into the relationships between 

agroforestry practices, biodiversity conservation and productivity among smallholder farmers in 

Mount Elgon, Kenya. 

3.2 Research Philosophy 

The research philosophy serves as the foundation that underpins the researcher’s assumptions 

about the nature of knowledge and reality, guiding decisions on how data was collected, interpreted 

and applied (Cuthbertson et al., 2020). Several philosophies were considered for this research, 

including positivism, interpretivism, critical realism and pragmatism. Positivism assumed that 

reality is objective and can be observed and measured through empirical evidence. This philosophy 

emphasizes quantitative methods and is suitable for studies seeking to establish causal 

relationships or test hypotheses, such as examining the impact of agroforestry practices on 

productivity. However, its rigid focus on observable phenomena may limit exploration of 

subjective experiences and contextual factors. 

Interpretivism, on the other hand, is rooted in the belief that reality is socially constructed and 

subjective. It focuses on understanding meanings and perspectives, making it ideal for qualitative 

research exploring farmers’ experiences, attitudes and social norms related to agroforestry 

practices. However, interpretivism may lack the structured framework required for measuring 

outcomes like productivity and biodiversity conservation (Nair, 1993). Critical Realism bridges 

the gap between positivism and interpretivism by recognizing the existence of an objective reality 

while acknowledging that our understanding is influenced by social, cultural and historical 

contexts. It is well-suited for studies investigating underlying mechanisms driving observed 

phenomena, such as socioeconomic or institutional factors affecting agroforestry adoption. 

However, it may require more nuanced data collection and analysis, which can be resource-



31 

 

intensive. Pragmatism, the chosen philosophy for this study, integrates the strengths of both 

positivism and interpretivism, emphasizing practical solutions and the relevance of findings in 

real-world contexts. Pragmatism is particularly appropriate for mixed-methods research, as it 

accommodates quantitative analysis to measure productivity and biodiversity outcomes while 

allowing qualitative insights into farmers’ perceptions, attitudes and challenges (Cuthbertson et 

al., 2020). 

This study sought to address the multifaceted interactions between agroforestry practices, 

biodiversity conservation and productivity among smallholder farmers in Mount Elgon. 

Pragmatism aligns with the research objectives by enabling the use of both quantitative methods 

for example statistical analysis of productivity data and qualitative approaches for example 

interviews to capture farmers’ experiences (Telwala, 2023). This philosophy ensures a holistic 

understanding of the research problem while maintaining practical applicability for designing 

targeted interventions to improve livelihoods and promote sustainable practices in the Kenyan 

context. 

 

3.3 Research Design  

The research design acts as the structural framework guiding a study, detailing the methodological 

strategies and approaches used to address research questions and objectives (Bell et al., 2018). 

Research designs encompass various types, such as experimental, correlational, descriptive and 

exploratory, each serving distinct purposes and methodological methodologies. The study 

employed a concurrent triangulation research design to simultaneously integrate qualitative and 

quantitative data collection and analysis methods. This approach aimed to provide a 

comprehensive exploration and validation of the research findings by triangulating different data 

sources and methods. Qualitative methods including interviews were used to investigate the 

experiences, perceptions and attitudes of farmers and stakeholders regarding agroforestry practices 

and biodiversity conservation. These qualitative insights helped to contextualize the quantitative 

data and provide deeper insights into the underlying mechanisms and dynamics at play (Kalamkar 

& Acharya, 2024).  

Quantitative methods, involving use of questionnaires, were employed to measure and quantify 

variables such as the type of agroforestry, scale of implementation, productivity outcomes and 



32 

 

biodiversity indicators. These quantitative measures allowed for the assessment of correlations, 

trends and statistical significance among the variables studied. The concurrent triangulation design 

is particularly suited to this study as it facilitates the integration of diverse data sources and 

methods, thereby enhancing the reliability and validity of the findings. This design ensures that 

both qualitative richness and quantitative rigor are maintained throughout the research process, 

enabling a comprehensive examination of the complex relationships within the context of 

smallholder agroforestry in Mt. Elgon, Kenya. 

The choice of a concurrent triangulation research design was justified as it allows for a 

comprehensive and multi-faceted exploration of the complex dynamics surrounding agroforestry 

practices and biodiversity conservation in Mount Elgon, Kenya. Through a combination of both 

qualitative and quantitative methods, this design enhances the richness and depth of the study. 

Qualitative methods such as interviews enable an in-depth understanding of the farmers’ 

experiences, perceptions and attitudes, which is essential for contextualizing the quantitative data. 

Meanwhile, quantitative methods including use of questionnaires provide empirical measurements 

of key variables such as agroforestry type, scale of implementation, productivity outcomes and 

biodiversity indicators. The simultaneous integration of these methods allows for cross-validation, 

ensuring more robust, reliable and valid findings and offering a comprehensive view of how 

agroforestry practices can enhance productivity and biodiversity conservation in smallholder 

farming systems (Nair, 1993). This mixed-method approach was therefore best suited for 

addressing the research objectives and answering the study’s research questions effectively. 

3.4 Target Population  

The target population for this study was smallholder farmers practicing agroforestry in Mt. Elgon 

Sub-County, Bungoma Co