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EFFECTS OF CLIMATE VARIABILITY ON MAIZE YIELD IN MATUNGULU WEST, MACHAKOS COUNTY KENYA

By

EURRY S. MABONGA (LL.B)

Reg. No.: N50/CTY/PT/21538/2010

DEPARTMENT OF ENVIRONMENTAL EDUCATION

A RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE MASTER OF ENVIRONMENTAL STUDIES (CLIMATE VARIABILITY AND SUSTAINABILITY) DEGREE IN THE

SCHOOL OF ENVIRONMENTAL STUDIES, KENYATTA UNIVERSITY

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DECLARATION Declaration by the candidate

This project is my original research work and has not been presented for a degree or any other award in any other University. Appropriate credit has been given where reference has been made to the work of others. No part of this work should be reproduced without prior permission of the author and/or Kenyatta University.

Signed: ……….Date:………..

Eurry S. Mabonga (N50/CTY/PT/21538/10 Department of Environmental Education

Declaration by Supervisors

We confirm that the work reported in this project was carried out by the candidate under our supervision.

Signed:………... Date:………

Dr. Daniel G. Manguriu

Department of Environmental Education Kenyatta University

Signed:……….. Date:………

Dr. Richard Kerich

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DEDICATION

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ACKNOWLEDGEMENT

First and foremost, I would like to thank my Father in Heaven. He is my strength and my Joy. Secondly, I am indebted to my supervisors, Dr. Daniel G. Manguriu and Dr. Richard Kerich. They remained committed to serve me and guided me along the difficult path travelled by scholars. It shall be scholarly blander not to mention my family; Dad, mum, siblings and my wife who prayed for and with me along this academic sojourn. They hold a special place in my success.

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Table of Contents

Declaration ... ii

Dedication.. ... iii

Acknowledgement ... iv

Table of Contents ... v

List of Figures ... viii

List of Tables ... ix

List of Acronyms and Abbreviations ... x

Abstract ... xii

CHAPTER ONE: INTRODUCTION ... 1

1.1 Background Information ... 1

1.2 Statement of the Problem ... 3

1.3 Research Questions ... 5

1.4 Objectives of the Study ... 5

1.4.1 General Objective ... 5

1.4.2 Specific Objectives ... 6

1.5 Hypotheses ... 6

1.6 Significance of the Study ... 6

1.7 Conceptual Framework ... 7

1.8 Definition of Terms... 9

CHAPTER TWO: LIRATURE REVIEW ... 9

2.1 The Mean Annual Rainfall and Mean Annual Temperature ... 11

2.1.1 Climate Variability and Agriculture ... 10

2.2 The Extent Inter-Annual Climate Variability Influences Maize Yield ... 14

2.2.1 Drought with Respect to Plant Growth and Yield ... 17

2.2.2 Changes in Temperature ... 18

2.2.3 Changes in Rainfall ... 19

2.3 The Maize Crop Requirements ... 20

2.3.1 Soils... 21

2.3.2 Soil Moisture ... 21

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2.3.4 Germination ... 22

2.3.5 Effects of Rise in Mean Temperature During the Reproductive Phase ... 22

2.4 Adaptations Measures and Coping Strategies to Climate Variability ... 23

2.4.1 Adaptive Measures ... 24

2.4.2 Coping Strategies ... 26

2.5 Knowledge Gaps ... 27

CHAPTER THREE: METHODOLOGY ... 28

3.1 Study Area ... 28

3.2 Research Design... 30

3.3 Target Population ... 30

3.4 Sample Size ... 30

3.5 Sampling Procedure ... 31

3.5.1 Systematic Random Sampling ... 31

3.5.2 Purposive Sampling ... 32

3.6 Data Collection Research Instruments ... 32

3.6.1 Primary Data ... 32

3.6.2 Secondary Data ... 33

3.7 Validity and Reliability of Research Instruments ... 33

3.7.1 Validity ... 33

3.7.2 Reliability ... 34

3.8 Data Analysis and Presentation ... 34

CHAPTER FOUR: RESULTS AND DISCUSSIONS ... 34

4.1 Background Information of the Respondent Farmers ... 34

4.1.1 Age Distribution of the Respondent Farmers ... 34

4.1.2 Education Levels of the Respondent Farmers ... 36

4.1.3 Respondent Farmers Duration of Stay in Matungulu West ... 37

4.1.4 Farmers Perception of the Effects of Temperatures on Maize Yield ... 38

4.1.5 Climatic Conditions Known by Farmers ... 39

4.1.6 Climatic Variations Experienced by Farmers in the Last 30 Years ... 40

4.1.7 Level of Knowledge on Climate Variability in Matungulu West ... 42

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4.2 Changes in Mean Annual Rainfall and Temperature in Matungulu West ... 43

4.3 Changes in Mean Annual Rainfall in Matungulu West ... 45

4.4 Changes in Mean Annual Temperature in Matungulu West ... 46

4.4.1 First Hypothesis ... 47

4.5 Effects of Inter-annual Climate Variability on Maize Yield ... 48

4.6 Farmers Perception of the Effects of Rainfall on Maize Yield ... 50

4.7 Effects of Temperature on Maize Yield ... 50

4.7 Effects of Temperature on Maize Yield ... 40

4.8 Coefficients of Variation (CV) of Rainfall and Temperature on Maize Yield ... 52

4.8.1 Second Hypothesis ... 53

4.9 Coping Strategies to Climate Variability in Matungulu West ... 54

4.10 Adaptive Measures to Climate Variability in Matungulu West ... 55

4.11 Hindrances to Adaptation Measures and Coping Strategies ... 56

4.11.1 Third Hypothesis ... 57

CHAPTER FIVE: SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS ... 58

5.1 Summary ... 60

5.2 Conclusions ... 60

5.3 Recommendations ... 61

5.4 Areas for Further Study ... 62

REFERENCES ... 64

APPENDICES ... 74

Appendix I: Field Photographs ... 74

Appendix II: Questionnaire for Households ... 77

Appendix III: Key Respondents Interview schedule ... 80

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viii List of Figures

Figure 1.1: Conceptual Framework ... 7

Figure 3.1: Map of Matungulu West ... 28

Figure 4.1: Mean Annual Rainfall and Temperature in Matungulu West ... 44

Figure 4.2: Changes in Mean Annual Rainfall in Matungulu West ... 45

Figure 4.3: Changes in Mean Annual Temperature in Matungulu West ... 46

Figure 4.4: Effects of Rainfall on Maize Yield ... 49

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ix List of Tables

Table 4.1: Sub-Locations of Matungulu West ... 34

Table 4.2: Age Distribution of Respondent Farmers ... 36

Table 4.3: Education Level of the Respondent Farmers ... 38

Table 4.4: Respondents Duration of Stay in Matungulu West ... 39

Table 4.5: Farmers Perception of the Effects of Rainfall on Maize Yield ... 40

Table 4.6: Climatic Conditions Known to Farmers ... 40

Table 4.7: Climatic Variation Experienced by Farmers in the Last 30 Years ... 42

Table 4.8: Level of Knowledge on Climate Variability in Matungulu West ... 43

Table 4.9: Household Farm Size in Acres in Matungulu West ... 47

Table 4.10 Difference Between the Annual Means of Rainfall and Temperature: ... 50

Table 4.11: Farmers Perception of the Effects of Rainfall on Maize Yield ... 52

Table 4:12: Correlation between Inter-Annual Climate Variability and Maize Yield ... 53

Table 4.13: Copping Strategies to Climate Variability in Matungulu West ... 55

Table 4.14: Adaptive Measures to Climate Variability in Matungulu West ... 55

Table 4.15: Hindrances to Adaptation Measures and Copping Strategies ... 56

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LIST OF ACRONYMS AND ABBREVIATIONS

ASALs Arid and Semi-arid Lands

CDKN Climate and Development Knowledge Network CIMMYT International Maize and Wheat Improvement Centre CV Climate Variability

DEFRA Department for Environment, Food and Rural Affairs ESRC Economic and Social Research Council

FAO Food and Agriculture Organization GHGs Greenhouse Gases

GCMs Global Climate Models GoK Government of Kenya

IFPRI International Food Policy Research Institute IPCC Intergovernmental Panel on Climate variability IITA International Institute of Topical Agriculture

KIPPRA Kenya Institute for Public Policy Research and Analysis KNBS Kenya National Bureau of Statistics

KMD Kenya Meteorological Department

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SPSS Statistical Package for Social Sciences

USAID United States Agency for International Development UNEP United Nations Environment Programme

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xii ABSTRACT

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CHAPTER ONE: INTRODUCTION 1.1 Background to the Study

IPCC (2012) attributes climate variability to anthropogenic causes. Records from the Kenya Metrological Department indicate that the country is warming. The available metrological records attest to the fact that the African content has severely been affected by the changing climate. It is approximated that the continent has been experiencing approximately 0.05°C. The climatic patterns have continued to change and a trend that is currently worrying. The warmest years in the 21st century have are cited as including 1988 and 1995. This warming of the African content was also experienced across the globe (IPCC, 2012). A study by Alexander et al., (2008) and Schnoor, (2010) demonstrated how climate variability impacted on rainfall patterns, the ecosystem, biodiversity and water towers across the globe.

Climate variability is a phenomenal challenge to the citizens of the globe. It is noticeable from many documented studies that climate variability is taking place at an alarming rate (Lobell et al., 2011; Wheeler and Braun 2013; IPCC 2007). According to Hansen et al., (2006) the globe has experienced an increase in temperature of approximately ≈ 0.20 C after every ten years for the last three decades. Such drastic increase in temperature has had a negative impact on maize yield especially in areas that predominantly arid and semi-arid. The total sum of such extremes is a terribly affected livelihood in particular those living below the dollar

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Kenya’s crop production is predominantly rain-fed (98%) and the remaining 2% is

through irrigation and mostly done for crops for export (Jayne et al., 2005). Research has established that an estimated 15% of the country gets adequate rainfall to sustain the growth of maize and 13% of the land across the country is apt for special dry farming or irrigated agriculture (Wambui, 2008). Dependence on rainfall to grow crops especially in ASALs has a very high risk of crop failure (25-75% in semi-arid, and 75-100% in arid areas) which makes agriculture extremely vulnerable to climate variability (Wambui, 2008).

It is estimated that maize is cultivated on about 100 million hectares in developing world. FAOSTAT (2010), observed that an estimated 70% of total maize yield realized is in this countries comes from the middle and lower income earners. Despite climate variability affecting maize yield in some areas, other areas are likely to realize more yields by 2050. It is estimated that with the ever increasing human population, there will be high demand for maize by 2050 (Rosegrant et al., 2008). Maize is consumed by a vast majority of the African countries. It is projected that the amount of calories being consumed will double the current amount in parts of Eastern and Southern Africa. Heisey and Edmeades (1999) have established whereas the demand for maize continues to rise and climate keeps affecting its production, some regions will have plenty of maize.

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There is no doubt that Kenya has not yet achieved self-sufficiency in maize production. The main issue occasioned by such struggles includes extreme weather conditions, shifting climatic patterns and negative effects depleting soil nutrients (Nyoro et al., 2007). These are factors that have continually affected the amount of maize yield and the tonnage per hectare is estimated to have dropped from 1.5 and 2.6 (FAOSTAT, 2010). This explains the reason why Kenya has in the last one decade has exceedingly imported maize for local consumption (GoK, 2010).

The Kenya’s natural resources continue to be affected negatively due to climate

variability (UNFCCC, 2007). This is likely to affect agriculture which happens to dependent on the climate. Dinar and Mendelsohn (2009) have indicated that by all indications climate variability is having serious effects on agriculture. Drought stress for instance has a serious effect to the grain yield more especially when the crop is beginning to develop and fill the grains (Heisey and Edmeades, 1999). When the maize crop begins to extend its stem the all other parts of the plant develop very fast a stage that will demand sufficient water and incase the crop is exposed to water stress then sum effect will be a total crop failure (Heisey and Edmeades, 1999). The effects of water stress on maize yield are severe if it occurs during flowering stage. The maize crop drops approximately two more times than when it occurs during other developmental stages (Grant et al., 1989).

1.2 Statement of the Problem

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that rainfall will become erratic and less predictable. Even the slightest increase in frequency of droughts will present major challenges for crop production which essentially affects the yields.

Kenya experiences major droughts every after a decade and moderate droughts within a span of every three to four years with devastating results (Guha-Sapir et al., (2013). The same study made a finding that droughts have affected more people and had the greatest economic impact (8% of GDP every five years). It is alarming to note that in the last 100 years, the country has experienced approximately 28 droughts Guha-Sapir et al., (2013). This trend appears to be taking an upward trend every year and more lives are becoming more vulnerable every single day.

There is enough literature on the climate variability across the globe. The effects that climate variability has had on agriculture are well documented. However it is not clear how maize yield are affected due to inter-annual climate variability. There is scanty information regarding the impact of both temperature fluctuation and rainfall unpredictability on maize yield. This paper sought to address the identified gap and explore the extend temperature and precipitation are correlated with maize yield.

To address this problem, the study focused on the effects of inter-annual climate variability on maize yield in Matungulu West in Machakos County for the period 1984-2014.

1.3Research Questions

1. How has the mean annual rainfall and mean annual temperature of Matungulu West in Machakos County varied for the period 1984 to 2014.

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3. What are the adaptation mechanisms and coping strategies?

1.4 Objectives of the Study 1.4.1 General Objective

The general objective of this study was to assess the potential effects of climate variability on maize yield in Matungulu West in Machakos County for the period 1984-2014.

1.4.2 Specific Objectives

1. To examine the mean annual rainfall and mean annual temperature of Matungulu West in Machakos County between 1984 and 2014.

2. To establish the extent inter-annual climate variability has influenced maize yield in Matungulu West in Machakos County for the period 1984 to 2014.

3. To determine adaptation measures and coping strategies being practiced by households in Matungulu West in Machakos County in addressing climate variability.

1.5 Hypotheses

HO1 There is no significant difference between the annual means of rainfall and temperature for the period 1984 to 2014.

HO2 There is no a correlation between inter-annual climate variability and maize yields in Matungulu West.

HO3 The adaptation measures and coping strategies to climate variability devised by households in Matungulu West, in Machakos County are not effective.

1.6 Significance of the Study

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on the findings, households could adopt the best strategies without aggravating the effects of climate variability.

The study could be of significance to policy makers like the Ministry of Agriculture Livestock and Fisheries, development agencies and local organizations in that the study generated information that could guide and enable effective adaptation policies to be appropriately targeted.

The study findings could assist the Kenyan Government comply with Articles 4.1.b and 4.8 of the United Nations Framework Convention on Climate variability (UNFCCC) that demands all parties to formulate and implement national or regional programmes containing measures to facilitate adequate adaptation to climate variability.

The general public could benefit from the study in that adoption of the best adaptation practices would lead to increase in agricultural production in a sustainable way, thereby leading to food sufficiency and improved health status of the community. The study also seeks to contribute to existing body of knowledge on effects of climate variability on dry-land agriculture, and generates ideas for further research.

1.7 Conceptual Framework

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Water stress during floral initiation, differentiation of the inflorescence, male and female meiosis, development of pollen and embryo sac, pollination, fertilization and seed development decreases the grain yield drastically (Diallo et al., 2001) and (Olaoye et al., 2009). Consequently, it is expected that there will be a decrease in household income, non-employment, raised food grain prices, low land productivity, increased cost of cultivation and increased poverty. Adaptation to climate variability and extremes events serves as a basis for reducing vulnerability to long term climate variability. It is understood that the patterns or trends of the past climate can tell us something about future climate. Strategies developed to manage year-to-year climate variability can go a long way towards building resilience and managing the risks of climate variability and variability.

Figure 1.1 Conceptual Framework. Source: Adapted from Portier et al., (2010)

The conceptual framework shows that climate drivers will accelerate the severe climatic events consequently reducing maize yield. Effective adaptation and coping strategies will lead to outcome of higher maize yield, drought resistant crops and increased farm income

Climate Drivers -Anthropogenic -Natural

Climate variability Temperature &

precipitation

(Independent variables)

Adaptation Strategies

Crop production systems

(Intervening variables)

Maize yield

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9 1.8 Definition of Terms

Adaptation: it is appreciating that climate is changing and formulating measures and strategies to reduce or eliminate the damages and or utilizing the presented opportunities presented by the climate variability (Hansen et al., 2013).

Adverse effects of climate variability: These are a range of changes as a result of climate variability which pose serious challenges on the productivity of the ecosystem or the well-being of humanity socially and economically (FAOSTAT, 2010).

Climate variability: It is a change of climate ascribed either due to anthropogenic actions or natural causes and its net effect is altering the composition of atmosphere and normally observed over a period of time. The change can be in terms of rainfall, temperature, wind speed, raising sea level among other variables (IPCC, 2012).

Rainfall Variability: It is degree at which the changing amount of rainfall is experienced across the globe over a period of time (Faramarzi et al., 2013).

Greenhouse gases: These are gases that are emitted into the atmosphere through anthropogenic actions or natural causes and they absorb and remit the infrared radiation to the earth (IPCC, 2017).

Global Warming: This is an increase in the concentration of greenhouse gases as a consequence of anthropogenic actions, where the consequence is an increase in the concentration thus absorbing more emitted gases which are remitted back to the earth leading to adverse climatic phenomenon (UNFCCC, 2007).

Mitigation: is the measure taken to minimize the effects of climate variability to avoid undesired climate risks (EPA, 2013).

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CHAPTER TWO: LITERATURE REVIEW

2.1 Mean Annual Rainfall and Mean Annual Temperature in Matungulu West It has already been established that Kenya as a country is facing serious ramifications of climate variability with current projections suggesting an enormous increase in temperature of close to 2.5ºC between 2000 and 2050 (Republic of Kenya, 2013). Another study by (Parry et al., 2012), makes an alarming finding that rainfall will become more erratic and less predictable. For every increase in frequency of droughts serious challenges are bound to be accessioned more especially for crop yields and water availability. The net outcome of this trend of events is total crop failure.

According to (Republic of Kenya, 2013), Kenya ranks 155 out of 178 countries in the Notre Dame Global Adaptation Initiative (ND-GAIN) index (2013). This ranking indicates a worsening situation compared to 2010 when the country was ranked at position 145. The Countries vulnerability ranks stands at 33rd and 155th on readiness meaning that the countries vulnerability is exceedingly high and much unprepared to deal with challenges posed by the changing climate (Republic of Kenya, 2013). It is explained further by (Waithaka et al., 2013), that the ability of a country already exposed to adverse effects of climate variability hazards is by accounting for the social and economic well-being of the people in the affected places. The people must strategize their readiness to combat such climatic effects.

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between April – June and most during which time farmers could plant their maize crops. This could be followed by cool dry season between July – September then short wet season between October – December when some farmers could plant maize crops and other varieties of crops that takes a shorter period to mature and warm dry season January – March. However, due to climate variability, such normality has shifted drastically and

farmers are never sure when to expect rains and when to plant their crops.

The amount of rainfall in Kenya is not constant, especially in ASALs. For the last decade the country has experienced fluctuating rainfalls which were characterized by El Nino and La Nino (Parry et al., 2013). It is established that first rains of the long wet season normally experienced between Aprils - June have become unreliable and the amount received keeps going down. These rains are now becoming insufficient to support a harvest or even livestock rearing, especially in the east of the country (CDKN, 2014).

It has been established that while the average number of rainy days during the short wet season has reduced from 60 to 30, rainfall has become erratic and unpredictable a situations that often prolongs the short rain season into January and February, leading to higher total rainfall for this season (CDKN, 2014). This is a clear indication of the changing rainfall trends which are even shifting the planting seasons. Rainfall intensity has generally increased all over the country, but with special interest is the coastal area. Statistics from the metrological department affirm that some regions in Kenya that were receiving about 500 mm of rain or more per year from 1960 are now receiving lesser rains and this is likely to keep shrinking over the next 30 years. Contrary to rainfall, temperature appears to be increasing annually from what it was in 9160. The current trend of temperature increase is averaged at 0.2ºC per decade (Republic of Kenya, 2013).

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disasters of which half concerned climate and the other half hydrological events (Parry et al., (2012).

Whenever the country experiences droughts, the ramifications are often nation-wide, but normally have the most severe effects in ASALs. According to Huho and Mugalavai, (2010) Kenya vast land falls within what is described as ASALs. Whereas it is true that droughts affect most people, it is also correct to mention that floods have caused the greatest losses of human lives. They are more localized than droughts, seasonally affecting almost all parts of the country. Most of the ASALs periodically experience flash floods with severe ramifications. Study shows that between 1950 and 2014, the country experienced six serious floods. The floods have been contributing to an estimated loss of about 5.5% of GDP every seven years (Huho and Mugalavai, 2010). Researchers have placed their concern on alarming glacial melt at Mount Kenya. It is stated that the mountain had 18 glaciers in 1900, but in 2008. It is shocking that only seven of them are remaining.

It is widely expected that the world at large and Kenya in particular will continue to experience extreme climatic conditions that will alter normal patterns. Rainfall forecasts vary, depending on which model is used. Although IPCC models for East Africa predict general rainfall increases, some models applied to the national level predict decreases of 50-150 mm between 2000 and 2025 for most of Kenya Parry et al., (2012). Regardless of which model is used, projections suggest that changes will be different according to location and season (Parry et al., (2012).

2.1.1 Climate Variability and Agriculture

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The mean annual temperature is on a rise according to the fifth assessment report of the IPCC Working Group (2007). It is dangerously increasing and unless the trend is curtailed then the 21st century is posed to experience an increase by at least 2°C. This will be more disastrous to Africa due to its vast land receiving rainfall below 700mm per year. It is also projected that Africa will continue to have a faster rise in temperature. According to Kang (2013) a rise in temperature is likely to affect water supply and its availability will become a problem because the water resources will decrease in the semi-arid areas. Kenya practices rain-fed agriculture thus crop production will be adversely affected. Hulme et al. (2001) and Faramarzi et al. (2013) projects a wetter climate for whole of East Africa in general. But due to regional differences the prediction for Matungulu West is still a temperature rise of 3°C. It is also projected that rainfall will decrease by 10-24% (Faramarzi et al., 2013).

Climate variability will also interact with non-climate drivers and stressors. The Fifth IPCC Report predicts that semi-arid areas, where the land is used for agricultural purposes vulnerability will increase (UNEP, 2010, IPCC, 2014). Kenya’s agricultural

sector in high farming potential areas and semi arid areas is already experiencing erratic and extreme weather events (UNEP, 2010). These unpredictable climatic conditions are said to contribute heavily to crop failure. Several report have highlighted some of these weather events as prolonged drought, shifting weather patterns like the short rains coming late or earlier than expected and serious floods that wipe away crops.

2.2 The Extent Inter-Annual Climate Variability Influences Maize Yield

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dry with over 200 million people staying in the affected region (Recha et al., 2008). This is alarming since the number of people affected continues to as the region continues to experience the adverse effects of climate variability.

According to a study by Guha-Sapir et al., (2013), the Kenya experiences major droughts after every decadal and moderate drought within a span of every three to four years with devastating results. It is noted that with such unpredictability then more droughts are likely to be experienced which will lead to diminished maize yield and increased poverty to households in the ASALs. The same study made a finding that droughts have affected more people and had the greatest economic impact (8% of GDP every five years). It is alarming to note that in the last 100 years, Kenya has experienced approximately 28 droughts (Guha-Sapir et al., 2013). This trend appears to be taking an upward trend every year and more lives are becoming more vulnerable every single day.

The challenges posed by climate variability include erratic weather patterns shifting seasons and prolonged drought at different stages of maize development. Maize yield will continue to suffer a decrease as already established due to erratic climatic conditions (Bals et al., 2008). Maize crop for instance over relies on the climate effect and it is understood that this crop is posed to drop significantly by between 10-20% within the next two decades. The study states further that the burden of climate variability will be massive to the poor and those confined in the ASALs. Adamgbe and Ujoh (2013) established that extreme climatic events and climate factors influencing crop production due to the changing and erratic climate conditions like fluctuating rainfall, unpredictable floods and extreme increase in temperature have an adverse effect on maize crop. The study makes a finding that if maize is properly evaluated as to how it adjusts itself to the changes brought about by the climate then it is likely that proper adaptations measures will be formulated.

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2007, 58% in 2008 and 44% in 2009 (Cadoni & Angeluci, 2013). This study states further that in 2010 estimated corn production in Nigeria was about 8,800 metric tons with growth rate of 1.68% which rose in 2012, to about 9,410 metric tons putting the growth rate at 1.73%.

A study by (Ojo, 2000) to identify factors that affect maize production in Nigeria, found out that there are many factors affect maize production in Nigeria. He however noted that one other major factor is climate especially rainfall. Another study carried out by (Chi-chung and Mccarl, 2004) confirmed that climate limits the production area of maize and lack of rainfall (drought) or too much of it (flood) can result in 100% loss of maize output.

Many African countries suffer the epidemic food security and alarming level of poverty as a consequence of erratic climate. The ramifications are always manifested through reduced agricultural productivity. The activities of human being continue to acerbate climate variability thus affecting agriculture on a daily basis. The effects of climate variability are felt universally but the most affected part of the globe shall be the African content due to its vulnerability to climate variability and inadequate capacity to reduce its impact. (Ohajianya and Osuji, 2012 and Ellen and Barry, 2005).

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Nyoro et al., (2007) research finding estimated that 1.1 tones of maize in Kenya are realized in every one acre of land. He states further that this kind of yields is common in the ever dry regions. Beside the direct effects of climate variability, other factors such as pests and diseases and outdated technologies, maize yield are also likely to be affected (Government of Kenya, 2009). These factors have been identified as some of reason why maize yield is lower than expected. This scenario continues to affect the rural households since they have to purchase more maize to cater for their daily food. Parry et al. (2010) affirms that maize yield is extremely sensitive to climate variability. He states further that these effects of climate variability become extremely disastrous when it occurs at developments stage of maize more especially when the crops begins to fill the grains and produce flowers (Parry et al., 2010).

2.2.1 Drought With Respect to Plant Growth and Yield

Abiotic and biotic constrains contributes significantly to the production of Maize crop. The production level of maize crop is dependent on availability or lack of insect pests, parasitic weeds and leaf and ear diseases which in this case study is referred to as biotic constrains. On the other side, the abiotic constraints are normally categorized as low soil fertility, drought, soil toxicity, high temperatures, flooding and soil salinity (Diallo et al., 2001).

The most affected regions by the changing climate are those located at subtropical and lowland areas of the continent. It is estimated 20 and 25% respectively of these regions experience serious climate variability ramifications every year (Heisey and Edmeades, 1999). This study was confirmed by a separate study by (Diallo et al., 2001) and (Olaoye et al., 2009) which stated that drought occurring at vegetative stage mainly causes delay in silking than a subsequent reduction in grain yield, drought stress at flowering and post flowering can cause up to 17-37% yield loss .

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temperatures surpasses the required degree, the maize yield tends to drop significantly. When it occurs at these stages, the maize yields are expected to be adversely affected (Diallo et al., 2001; and Olaoye et al., 2009).

Maize tends to experience a total crop failure whenever a dry spell sets in at the early stages of its growth. In many occasions this mid-season droughts are rare to occur but in cases where they do occur the effects are normally far reaching (Guelloub et al., 2003). Every stage of maize growth requires a specific amount of rainfall and temperature. However, at this stage it is normally disastrous since the maize is developing flowers that will eventually determine how much yield is realized.

It is therefore apparent that when drought occurs in mid-season, the ramifications are dire. The reason is that at this stage of the crop development the maize crop is more vulnerable and nothing short of enough water shall sustain its development. Guelloub et al., (2003) made a finding that most that Kenya is 82% dry thus getting even the salty/brackish water for irrigation then liming the soils after some time by itself is challenging. This is also a scenario faced by most Kenyan farmer whose majority are living below the dollar and they cannot afford irrigation. Guelloub et al. (2003) affirms that drought leads to reduced leaf surface area, delayed silk emergence, reduced stem internodes, fewer roots and slow grain expansion in that order. Leaf senescence is accelerated starting with older leaves at the bottom of the plant but at severe drought levels, the top leaves are also affected. This is ultimately leads to reduced yields or no yields at all.

2.2.2 Changes in Temperature and its Effects on Maize growth

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changes in temperature may not be enormous but its timing during development of the crop has serious ramifications. Climate variability is characterized by unpredictability of the temperatures and that explains the reason maize is highly affected.

High temperature during the day shortens the phenological phase. According to Chi-chung (2004), the rate of evapo-transpiration is determined by daytime temperatures thus making it vital to plant growth. The global climate model has projected that most of the Sub-Sahara Africa (SSA) will continue to experience this enormous increase in temperature in the next few years. Due to the rising temperatures, it is expected that there will be a high rate of evaporation of water from river basins, dams and from the soil and if the same is not equated to the amount of rainfall, then crops will be adversely affected.

2.2.3 Changes in rainfall

Whereas the total rainfall received in a region is important, crop producers in the distribution of the rains from the start of planting season to the harvest is considered extremely important. Rainfall remains the most vital resources in any agricultural region. Water for agricultural activities is received from rivers, dams and the soil which acts as reservoirs of the rain water. Crops are able to grow and develop well as a result of constant replenishing of the soil, by the rain. Arnetzen et al. (1996) made an observation that rainfall is one of the most vital requirements for maize growth. He states further that the occurrence of rainfall, magnitude and spread determines the amount of yield to be realized. The amount of rainfall received will determine the amount being absorbed by the soil and the amount evaporating in the atmosphere. All these are events that have far reaching effects on maize growth which eventually determines the amount of yields realized (Arnetzen et al., 1996).

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adversely affected by moisture deficit as a result of shortened season. This is critical and the effect on the crop production is enormous.

2.3 The Maize Crop Requirements

Maize is now the most grown cereal across the world in a range of agro-ecological environments (FAO, 2013). A study (Ojo, 2000) estimated that there are approximately 50 species of maize exist and consist of different colors, textures, grains, shapes and size. Maize crop was introduced in Africa over a century and half ago. Maize is one of the crops that have been grown in Africa for a very long time. That is the reason why maize has become the main food crop in every most of the African households (FAO, 2013).

In developing world and Kenya in particular maize has been established to form part of the staple foods. The crop forms approximately 80%-90% of the total calorie intake of the rural population (Ayoola, 2001). Maize in its entirety has both economic and nutritional value that is critical for a better livelihood. IITA (2009) states that the grain, leaves, stalk, tassel and cob of a maize crop are vital in animal and human feeds which just explains the importance of the maize crop.

Having established the economic importance of maize, it emerges that several factors have been noted to have an effect on its production in Kenya. Ojo (2000) avers that there are many factors that affects maize yield. The study by (Ojo, 2000) made a finding that inadequate rainfall, fluctuating temperatures, post-harvest management poor marketing strategies, serious crop diseases and inefficiency of resources utilization are the main factors reducing maize and/or affecting maize yields. Climate variability has been identified as a major factor affecting maize yield especially rainfall.

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becomes highly vulnerable due to the unpredictability of the weather. It is clear that whereas climate variability is having a serious effect on maize crop, there are also several factors that contribute to poor yield.

It is without doubt that fluctuation in the amount of rainfall and ever increasing temperatures are hurting agriculture across Africa (Ajetumobi et al., 2010). That being the onset, it follows therefore that agriculture is the most affected sector more especially rain-fed. Climate variability is largely as a result of anthropogenic actions and to a lesser extent through natural cause. It is therefore true that the effects it has on agriculture can be reduced if the human action on climate can be controlled.

It has been established that to climate variability is a tragedy that is being felt by all humanity. It has had severe impact on the livelihoods of the global citizens but with devastating effects on Africa. The reason Africa is adversely affected is because most of it is extremely dry and human activities like poor soil management, resource depletion, overgrazing and deforestation continues to happen at an alarming level (Ohajianya and Osuji, 2012).

2.3.1 Soils

According to Keeffe (2009), maize grows well in different types of soil. Temperate podzols are soils that support maize growth well. It is also established that leached red soils of the tropics are suitable for maize growth. These kinds of soil are good for maize growth but not the best. It is recommended that for maximum maize yield to be realized, the soils must be rich in nutrients, deep without soil compaction mostly found in the sub-tropics (Keeffe, 2009).

2.3.2 Soil Moisture

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which according to Zhao et al., (2013) is extremely vulnerable to water stress. Maize yields reduce potentially when the amount of water in the soil is lost more than the amount being absorbed. This process is commonly referred to as evapotranspiration. When amount of water lost is enormous, the maize crop will be unable to absorb nutrients from the soil which eventually will lead to the weakening of the plant and making it susceptible to pests and diseases. The total sum of this is either a total crop failure or reduced maize yield (Sheng et al., 2014). It was also established by (Hejnak, 2009) that the stem and cell expansion are affected due to insufficient moisture in the soil. This the study states that will lead to the shortening of the maize crop below its expected height. Such moisture stress is likely to cause an up to 50% reduced yield which is extremely alarming.

2.3.3 Temperature

Maize yield is determined by the amount of temperature during its life cycle. The soil moisture is dependent on the amount of temperature received which when not favorable may cause yield loss of between 20%–100% (Yi et al., 2014). Most favorable temperatures for the growth of maize occur at 24 to 30 °C. On the other hand temperatures above 38 °C, will increases evapotranspiration resulting to senescence and drastic yield reduction (Pingali, 2001). High temperature during seedling, silking and tasselling is detrimental to the maize yield (Shaw, 1983).

2.3.4 Germination

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2.3.5 Effects of Rise in Mean Temperature During the Reproductive Phase

Typical florets of a maize plant are initiated at shorter time intervals than leaves. Maize grown in tropical regions, the interval between the initiations of successive leaf primordial is between 1.2 and 1.8 days but between 600 and 800 florets may be formed on a single ear in a space of 20 to 40 days. This according to Goldsworthy and Fisher, (1984) is subject to temperature and radiation. Study shows that higher temperatures cut down the duration of floret initiation thus diminishing the number formed. Temperature is also important in the setting of kernels. According to Carberry et al., (1989) higher mean temperatures during the plant season reduces the number of grain per plant resulting in a lower final yield.

2.4 Adaptation Measures and Coping Strategies to Climate Variability

Climate variability is a well know phenomenon to majority of the farmers. Each household is on trial to strategize the best way to deal with such changing climate. This explains the measures taken by these farmers in establishing ways to combat the effects of climate variability on their crops (Hansen et al., 2013). The measures being employed by the farmers can either be couched to address the adverse effects or to capitalize on the opportunities presented by the changing climate (EPA, 2013). It is stated further that most of the regions and people affected by climate variability have generally been able to come up with very effective way of addressing the climate variability challenges.

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There are several ways of categorizing adaptation responses which is subject to the effectiveness of the chosen adaptation strategy. Autonomous or Separate strategy are categorized as reactionary to climatic stimuli (Smit et al., 2001). Leary (1999) study shows that this mode of adaptation is an initiative by classified actors rather than by communal usually prompted by market or welfare changes induced by definite or predictable climate variability.

Osman-Elasha (2010) and Pittock and Jones (2000) have analyzed another adaptation mode called Policy-driven or planned adaptation. According to their studies, policy driven adaptation is a thoughtful and firm policy formulation supported by the fact that climate is changing drastically and there must be change of events and activities positively address the adverse effects of climate variability.

Farmers in arid and semi-arid regions have established their own measures and strategies to address the effects posed by climate variability. Some have chosen to plant diverse crops especially those that resistant to drought, while other have chosen to practice water harvesting for usage during the dry spell. Irrigation has not been exhaustively utilized due to the amount of money required to set up the unit (Ngigi, 2009). It is established that incase farmers can be enabled to harvest and manage rain water; this can be an answer to the effects brought about by climate variability. This according to his study, Water management can be enhanced through a multiplicity of alternatives such as shallow wells, boreholes and rainwater storage. However, the ecological effects of these options need to be scrutinized.

2.4.1 Adaptive Strategies

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small scale farmers, who happen to be at the center of this disastrous climate hazard, are to involve government agencies in addressing climate variability. This will is likely to expand the capacity of the small scale farmers to adapt to the changing climate.

The concept of adaptive capacity was well established through a study carried out (Bantilan and Anupama, 2002). This study established that several parts of India like Aurepalle and Dokur were persistently being affected by the changing climate and they had not employed any meaningful strategy to address these disastrous impacts of climate variability. Most of the wells dug by people in the study area were completely dry and even those areas that practiced irrigation could no longer access water. The study made a finding that the effects of such adverse weather conditions affected households severely. The study made an interesting finding that climate variability also affects income either positively or negatively. In the year the study was carried out, the selected region posed negative results in terms of income having a decline having declined from 91% overall to 41%. This is a significant decline in terms of income and it clear that many households were and continue to feel the effects of climate variability.

Bantilan and Anupama (2002) made a critical finding that as a result of the posted climate variability ramifications many families were diversifying their activities from the once predominantly agriculture based to other off farm activities like seeking employment and or engaging in business. This, it was found out families that adapted to the erratic weather conditions increased their income significantly as opposed to those that maintained their conventional way of doing agriculture. This was concluded by the researchers to mean that families in the two targeted villages had actually higher adaptive capacity.

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agriculture. The best way to address such shortcomings is for the concerned stakeholders to come up with innovative alternatives that are easily accessible and readily available. There are glaring gaps that must be filled with best alternatives. Water management especially the water harvested from the rains improves maize seeds that are resistant to harsh climatic conditions and proper land management to reduce soil degradation shall be paramount to combating climate variability. These are alternatives that are achievable and less expensive and upon its implementation there shall be a significant reduction in climate variability effects.

2.4.2 Copping Strategies

These are efforts that are put in place by small scale farmers to tolerate, reduce and minimize the effects of climate variability. Different copping strategies are normally employed by different households. According to (Bantilan and Anupama 2002), these strategies have kept on changing to catch up with the changing climate. There are many factors that affect maize yield as already established. The soil keeps on losing its fertility through serous soil degradation occasioned by overstocking, over cultivation and deforestation. On the other side the land is facing population pressure which means the land is reducing at an alarming rate. These factors capped with crop diseases and lack of a viable market for the few agricultural products realized slowly changing the viability of the agricultural sector (Jayne et al. 2003).

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climate variability effects. This in essence calls for proper formulation of coping strategies that are modern in nature to address the current and future climatic trends.

2.5 Knowledge Gaps

Based on the literature reviewed in this chapter, it emerges that much concentration of climate variability and its effect has and continues to be done on a lager perspective. This kind of study is on a general perspective. There is over concentration of research on the effects of climate variability on the developing countries than the real culprits who are majorly responsible for causing climate variability. For climate variability to be conclusively addressed, the research must be done across all countries regardless of whether they are industrialized or developing. This is the sure way to identify the best alternatives to deal with climate variability equitably.

There is an extensive research being done in the areas that are climate related and agricultural based. This is said to be a way that has been strategized to deal with food insecurity in the world having threatened many livelihoods. However, the research has not optimally appreciated the various stresses that are indirectly related to climate variability but heavily impact on agriculture. This explains the reason why despite having so many studies relating to climate variability on agriculture, very little Is documented as a tangible research addressing the extend of vulnerability occasioned by factors not directly related to climate variability. It is time real research in this area was commissioned to be able to address the vulnerabilities level of communities especially those in arid and semi-arid regions. This will eventually give these to proper adaptation measures by these communities to combat the effects of climate variability.

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CHAPTER THREE: RESEARCH METHODOLOGY 3.1 Study Area

The study was undertaken in Matungulu West Sub-Location, Machakos County (Fig 3.1). The area stretches from latitudes 0º 45’ south to 1º 31’ South and longitudes 36° 45’ East to 37° 45’ East; and covers an area of 6,208 square Km (GoK, 2009).

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Matungulu west Sub-County is made up of nine administrative Sub-Locations namely; Komarock, Kithuani, Nguluni, Kwangii, Kithimani, Kalandini, Matuu, Mukengesya, and Mbuni in Machakos County. Matungulu west is boadered by several constituencies including Mwala to the North, Mbooni to the south, Kathiani to the west, Yatta to the East and Mwala to the North West. Matungulu west covers an area of 246.90 Sq. km most of which is semi-arid. The Sub-County receives low, unevenly distributed and unreliable rainfall ranging between 250mm-1300mm per year. The area’s population is estimated to be 33,808 with 7792 households (KNBS, 2010).

The major part of Matungulu West is regarded as semi arid (KNBS, 2010). It is estimated that less than 40% supports agricultural activities and water mass occupies 15sq. km, mostly perennial rivers and dams (GoK, 2009). The sub-county receives low, unevenly distributed and unreliable rainfall ranging between 250mm-1300mm per year. The study area experiences regular crop failure and due to erratic weather conditions. The Sub-Location is predominately rural with most of the population engaged in agricultural activities especially in high potential areas.

The rainfall distribution of the study area occurs in two models. The area experiences both long and short rains spread across the year. Between March and May, Matungulu West experiences long rains and shot rains are normally between October and December. The Machakos County Metrological Department has also corroborated this report by affirming that the annual average rainfall of the Matungulu West sub-county is between 250 mm and 1300 mm. it is established that this trends is not constant since it keeps changing every year. The area lies in agro-climatic zone Lower Midland Zones LM4 and LM5. These are zones characterized by short to medium and short cropping seasons respectively. The main economic activities in the area are trade and small scale farming (GoK, 2009).

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significantly dropped (GoK, 2009). Even though rainfall amounts and distribution have often been below the required amount to support maize growing, rain-fed agriculture constitutes 70% of rural employment and economic activities (GoK 2009). The main issue in Matungulu area has been revealed to be how to deal with the unpredictability or rainfall and unprecedented drought.

3.2 Research Design

Research design is a plan of action to be carried out in connection with a proposed research work. Mugenda and Mugenda (2003) argue that research design can be classified based on the purpose, method of analysis and research type. The study used an exploratory survey design that enabled a visit to the region in search for responses from the target population. According to Russell (2005), exploratory research aids in establishing the best research design, data collection method and selection of subjects. The survey research design identified the respondents by selecting the appropriate stakeholders in the study area. The essential plan behind research design was to gauge variables by asking the respondents questions and then to scrutinize interactions among the variables. The research design endeavor was to capture the manner or prototype of the questions being sought.

3.3 Target Population

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According to Mugenda and Mugenda (2003) sample population is a representative population selected from the accessible population to act as a representative. The researcher applied the formulae designed by Yamane, (1967) in determining the sample size.

N

n = ______________ 1+N( )2

Where n= Sample size N= Population size

e=level of precision which is 0.05%

The study area has 7792 household thus using the above formula, the sample size will be calculated as follow:

7792

n = ______________ 1+7792(0.05)2

From the calculation above, the required sample size is 380 households.

3.5 Sampling Procedure

Kothari (2004) defines sampling procedure as a definite plan for obtaining a sample from a given population. The study employed the sampling techniques explained below:

3.5.1 Systematic Random Sampling

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Purposive sampling was used to sample the key informants from the relevant institutions for instance, Machakos County Meteorological Department and National Cereals and Produce Board Machakos Depot.

3.6 Data Collection Research Instruments

Different types of data collection tools were used to allow for triangulation. Research instruments are the techniques and materials used by the study to collect information (Gillham, 2000). The study used questionnaires, interview schedules and observation to collect required data. Both quantitative and qualitative data was collected in the study. Questionnaires were used to collect qualitative data from households of the study area. The questions that were asked were identical in order to solicit homogeneous information from all households. Qualitative data was collected using interview schedules to gather firsthand information from the key informants. The interviews followed a semi-structured format, with an in-depth focus in regards to the area of expertise of the informant. According to Yin (2004), interviews are important to assist the research to get more information on a particular area of interest in the study. Additionally, observation was used and results included illustrative pictures taken in the field.

3.6.1 Primary Data

Key Informant and Personal Interviews

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The study formulated an open ended questionnaire so that reliable information could be collected. The questions were asked in a way that their responses would answer the objectives of the research.

3.6.2 Secondary Data

Secondary data was obtained from desk top research conducted. This focused on publications by the Ministry of Agriculture as then was, books and articles that have information on maize production in Matungulu West in Machakos County for the past thirty years, climatic conditions and how it is affecting maize production and different theories on the adaptation and coping measures employed by different household in the study area.

Maize yield data was sourced from the National Cereal and Produce Board Machakos Depot. Climate data for the study was obtained from Machakos County Metrological Department.

3.7 Validity and Reliability of Research Instruments 3.7.1 Validity

Mugenda & Mugenda, (2003), defined validity as the degree to which results obtained from analysis of the data actually represents the phenomenon under the study. If the data is true reflection of the variables, then inferences based on the data will be accurate and meaningful. For the study to be rated as bearing the desired quality, the data collection procedures must be proper which in turn rely on the validity of the instruments used.

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Reliability of research instruments has been defined by a study carried out by (Mugenda & Mugenda, 2003), as the measure of the degree to which a research instrument yields consistent results. The study states further that to maintain the consistent results the researcher will employ the test- reset technique and the split- half technique to ensure the instruments used will be free of random errors.

Short Note on SPSS was used to test the reliability of research tools. A pilot test was used to collect data from 20 respondents from Matungulu West not included in the sample. The data collected was analyzed using Statistical Package for Social Sciences.

3.8 Data Analysis and Presentation

The data collected from the field was analyzed qualitatively and quantitatively. The data collected was screened to identify omissions and removal of non-answered questions. For qualitative data analysis, coding and entry was done using an electronic spreadsheet with the aid of Statistical Package for Social Sciences. The data generated was analyzed using descriptive and inferential statistics. Qualitative data from interview schedules was analyzed through content analysis. Leedy and Ormrod (2013) confirm that content analysis is a meticulous methodological evaluation of the content of a specific form of material with an intention to identify preconceived notion. The responses from the key informants’ interviews was analyzed and presented in a narrative form according to

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CHAPTER FOUR: RESULTS AND DISCUSSIONS

4.1 Background Information of the Respondent Farmers 4.1.1 Age Distribution of the Respondent Farmers

An overwhelming (80.5%) of the respondents interviewed were male and (19.5%) were female respondents (Table 4.1). Male dominance in farming is attributed to the fact that men are predominantly presumed to be household heads and holders of land and that’s

why they embark on farming to feed their families. Whereas it is true that women are mostly the ones working in the farms, this study revealed that men in Matungulu West take pride in farming. That explains the high percentage of of male participating in farming.

Table 4.1: Age Distribution of Respondents

MALE FEMALE TOTAL

___________ ___________ ______________

Age F % F % F %

________________________________________________________________________ 25-35 29 7.6 2 0.5 31 8.1

36-45 80 21.1 16 4.2 96 25.3

46-55 101 26.6 56 14.7 157 41.3

Over 55 63 16.6 33 8.7 33 25.3

TOTAL 273 80.5 104 19.5 380 100

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The study also established that both men and women participated in maize farming during the study period. This corroborates the study by Ndegwa et al., (2010) and Ndungu et al., (2004) which established that men and women equally participate in farming with differences only in the farming activities engaged in. Minority of the respondents (8.1%) were young people of between 25-35 years. Involvement of younger people in farming appears to be taking an upward surge and this confirms a finding that placed the younger people unemployment rate in Kenya at (12.7%) in the year 2006 (KNBS, 2007) and at 40 percent in the year 2009 (Krishnamurthy & Dejan, 2009). The finding of this study places the involvement of younger people in farming at (8.1%). This is a high rating as compared to the national rating considering that the study was focused on Matungulu West Sub County alone.

4.1.2 Education Levels of the Respondent Farmers

The researcher established that (52.1%) had attended primary school education which indicates that majority of the respondents are literate (Table 4.2).

Table 4.2: Education Level Attained by Respondents in Matungulu West.

MALE FEMALE TOTAL

____________ ____________ ______________ Education level F % F % F %

_______________________________________________________________________ Primary 97 25.5 101 26.6 198 52.1

secondary 60 15.8 59 15.5 119 31.0

Collage 32 8.4 12 3.2 44 11.6

University 12 3.2 7 1.8 19 5.0

TOTAL 201 52.9 179 47.1 380 100

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appeal to the educated leading to their migration elsewhere. This study therefore can conclude that the reason most farmers are of low education is because most the educated consider farming an odd job.

Matungulu West proximity to Nairobi appears to be affecting education. Most of the people have migrated to Nairobi in search of better education. The less fortunate who remain in the village, can only afford education up to primary level due to extreme poverty. The findings in this study confirm similar findings by Sifuna, (2005), which established that most parts of Kenya especially rural areas have not posted good results in terms of education. It is clear that most of the rural consider primary education as a major achievement and also considering that they are poor, they don’t bother pursuing further

education beyond basic education.

The education level of individuals is a factor that indicates awareness levels informing the type of farming and adaptation measures. According to Gardner et al., (2001), highly educated people have the ability to analyze information critically. This will enable them to apply the necessary knowledge to implement new farming technology and realize the expected results.

The study also established that a mere 5% of the respondents with university degree practiced maize farming. This will pose a challenge to adaptation measures and coping strategies since proper knowledge is key in dealing with climate variability. This study reveals that very few graduates, who are regarded as knowledgeable enough to understand climate variability, are engaging in farming.

4.1.3 Respondent Farmers’ Duration of Stay in Matungulu West

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which defined Climate variability as the sum total of all the climate variables like rainfall, temperature and wind which are measured on timescale ranging from weeks to decades.

Table 4.3: Respondents’ Duration of Stay in Matungulu West.

MALE FEMALE TOTAL

___________ ____________ ______________ Period Stayed F % F % F %

________________________________________________________________________ Below 5yrs 21 5.5 8 2.1 29 7.6

5-10 yrs 10 2.6 6 1.6 16 4.2

10-15 yrs 21 5.5 20 5.3 41 10.8

15-20 yrs 38 10.0 31 8.2 69 18.2

Over 20 yrs 124 32.6 101 26.6 225 59.2

TOTAL 214 56.2 166 43.8 380 100

It is therefore paramount that for this study to conclusively observe a change in climate, these variables must have been present for a considerable period of time. The duration of stay of the respondent farmers in the study area revealed that there has been considerable climate variability. The study established that young people (7.6%) comprised the number of farmers with few years of stay in the study area. They had little to say about these climate variables considering that some had stayed in Matungulu West for a period of less than one year.

4.1.4 Farmers Perception of the Effects of Temperatures on Maize Yield

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Table 4.4: Farmers Perception of the Effects of Temperatures on Maize Yield ________________________________________________________________________

MALE FEMALE TOTAL

Effects of Temperature ___________ __________ ________ F % F % F %

________________________________________________________________________ Adverse 31 8.2 12 3.1 29 11.3

minimal 123 32.4 97 25.5 16 57.9

None 52 13.7 39 10.3 41 24.0

Not sure 12 3.1 14 3.7 69 6.8

TOTAL 218 57.5 162 42.7 380 100

It is worth noting that temperatures of between 240C – 300 C are within range and its effects may not be necessarily high. The (11.3%) of the respondents who indicated that temperature has had adverse effect on their maize yield are likely to be in the category of farmers whose maize were affected by high temperatures during seedling, silking and tasselling. maize crop is highly vulnerable to temperature during seedling, silking and tasselling (shaw, 1983). The study by (Shaw 1983) states further that the net effect of temperature at this stage is likely to decrease maize yield by between 50%-90%.

4.1.5 Climatic Conditions known by the Farmers

The results in (Table 4.5) imply that for most farmers in Matungulu West, climate variability was a reality, characterized by erratic rainfall, floods, drought and raising temperatures.

Figure

Figure 1.1 Source: Conceptual Framework.  Adapted from Portier et al., (2010)
Figure 3.1: Map of Matungulu West.
Table 4.1:
Table 4.2: Education Level Attained by Respondents in Matungulu West.
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References

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