August,2017 Adama,Ethiopia

ADAMA SCIENCE AND TECHNOLOGY UNIVERSITY

SCHOOL OF HUMANITIES AND LAW DEPARTMENT OF GEOGRAPHY AND ENVIRONMENTAL STUDIES

THE NEXUS BETWEEN POPULATION GROWTH AND DEFORESTATION IN THE CASE OF MEKO WOREDA, SOUTH WESTERN OF ETHIOPIA

By: MULUGETA ADDISU

AUGUST,2017 ADAMA,ETHIOPIA

ADAMA SCIENCE AND TECHNOLOGY UNIVERSITY

SCHOOL OF HUMANITIES AND LAW DEPARTMENT OF GEOGRAPHY AND ENVIRONMENTAL STUDIES

THE NEXUS BETWEEN POPULATION GROWTH AND DEFORESTATION IN THE CASE OF MEKO WOREDA, SOUTH WESTERN OF ETHIOPIA

By: MULUGETA ADDISU

A THESIS SUBMITTED TO DEPARTMENT OF GEOGRAPHY ANDENVIRONMENTAL STUDIES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ART IN GEOGRAPHY AND ENVIRONMENTALSTUDIES

ADVISOR: TSETADIRGACHEW LEGESSE (PhD)

AUGUST, 2017 ADAMA, ETHIOPIA

Declaration

By my signature below, I declare and affirm that this thesis is my own work. I have followed all ethical principles of scholarship in the preparation, data collection, data analysis and completion of this thesis. All scholarly matter that is included in the thesis has been given recognition through citation. I affirm that I have cited and referenced all sources used in this document. Every serious effort has been made to avoid any plagiarism in the preparation of this thesis.

Name: ______

Signature: ______

Date: ______

Place: Adama Science and Technology University

AKNOWLEGEMENT

First and for most, I would like to thank my God for his overall gifts. Moreover, the success of this research work is the cumulative output of the contributions of different individuals, who must be acknowledged. I am grateful to thank my advisor D/r Tsetadirgachew for his comfortable academic advisor and constructive comment. He patiently tolerated my ignorance; and my open and lively discussion with him cleared my confusion about the issue to be researched. I would like to thank Meko secondary school which helped me to complete this work by giving permission and by supporting different material like paper, pen and printing. To all the respondents in Dembely Sophe and Mainty Selgen kebeles, Kebele managers and natural resources expert of Meko Woreda I am very grateful to you for giving me the much needed information that contributed tremendously to making this study. I am also very grateful to those individual who tirelessly assisted me in the translating questionnaire into Afan Oromo and GIS operating. Last but not least, my wife Emebet Taye Gegesa deserves my deepest appreciation for her unreserved care, love and encouragements throughout my study.

Table of Contents Contents Page

Acknowledgment…………………………………………………………………………I

Table of Contents……………………………………………………………………….II

List of Figures…………………………………………………………………………...V

List of Tables…………………………………………………………………………….V

Acronyms……………………………………………………………………………….VI I

Abstract……………………………………………………………………………….VIII

CHAPTER ONE: INTRODUCTION………………………………………………………………………...1

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

1.2 Statement of the Problem…...... 2

1.3 Objectives of the Study…………………………………………………………….3

1.3.1 General Objective……………………………………………………………..3

1.3.2 Specific Objectives……………………………………………………………3

1.4 Research Questions………………………………………………………………..4

1.5 Significance of the Study………………………………………………………….4

1.6 The Scope and Limitations of the Study…………………………………………..4

1.7 Organization of the Paper………………………………………………………….5

1.8 List of Operational Terms………………………………………………………….5

CHAPTER TWO: REVIEW OF RELATED LITERATURE……………………………6

2.1 Concept of Forest…………………………………………………………………..6

2.1.1 Definition of Forest ……………………………………………………………6

2.1.2 Uses of Forest………………………………………………………………….6

2.2 Deforestation ……………………………………………………………………....7

2.2.1 Definition of Deforestation……………………………………………………..7

2.2.2 Deforestation in Ethiopia……………………………………………………….7

2.2.3 Causes of Deforestation and Forest Degradation. ……………………………..8

2.2.4 Consequence of Deforestation………………………………………………...10

2.2.5 Possible Conservation Measures ……………………………………………...12

2.3 Theoretical Literature and Empirical Evidences ………………………………….15

2.4 Conceptual Frameworks…………………………………………………………..16

CHAPTER THREE: BRIEF DESCRIPTIONS OF THE STUDY AREA AND RESEARCH METHODS AND MATERIALS………………………………………………..18

3.1 Brief Description of the Study Area………………………………………………18

3.1.1 Location and Physical background of the Study Area ………………………..18

3.1.2 Population and Socio economic Characteristics of the Study Area…………...20

3.2 Research Method and Materials…………………………………………………...22

3.2.1 Research Design and Approach………………………………………………..22

3.2.2 Data Types……………………………………………………………………..22

3.2.3 Sampling Technique and Sample Size Determination…………………………23

3.2.4 Methods of Data Collection……………………………………………………24

3.2.5 Method of Data Analysis………………………………………………………27

3.2.6 Data Validity and Reliability…………………………………………………..30 CHAPTER FOUR: RESULT AND DISCUSSION…………………………………… 31

4.1 Socio Economic Characteristics of Respondents ...... 31 4.2 Patterns and Extent of the Major LULC in the Selected Kebeles of Meko Woreda During 1986- 2016 ...... 34 4.2.1: Analysis of LULC Change in the Selected Kebeles During1986-2016……...36

4.3 Causes of Deforestation ...... 43

4.4 Consequences of Deforestation in the Study Area ...... 49

4.5 Forest Conservation Mechanisms in the Study Area ...... 51 4.6 Part of Inferential Statistical Analysis ...... 54 CHAPTER FIVE: CONCLUSION AND RECOMMENDATIONS……………………66

5.1 Conclusion…………………………………………………………………………66

5.2 Recommendations…………………………………………………………………67

References ...... 69

Appendices ...... 74

List of figures Figures page Figure 2.1 Conceptual Framework ...... 17 Figure 3.1: Map of the Study Area ...... 19 Figure 3.2: Mean Monthly Temperature and Rainfall in Meko Woreda (1979 - 2014) ...20 Figure 4.1: LULC map of Manity Selgen and Dembely Sophe kebeles in 1986, 2000 and 2016 ...... 35 Figure 4.2: LULC Change in Hectare between 1986 and 2000 ...... 40 Figure 4.3: LULC Change in Hectare between 2000-2016 ...... 41 Figure 4.4: LULC change in Hectare between 1986-2016 ...... 42 Figure 4.5: Source of Grazing land for Household Head‟s livestock ...... 44 Figure 4.6: Extensive Soil Erosion in the Study Area ...... 50

List of Table Tables page Table 3.1: Population Size of the Study area ...... 21 Table 3.2: Land use Land Cover Pattern of Meko woreda ...... 22 Table 3.3: Sample Size of the Study: ...... 24 Table 3.4: Classification of LULC of Mainty Selegen and Dembely Sophe kebeles of Meko Woreda ...... 29 Table 4.1: Age Structure of Respondents ...... 32 Table 4.2: Land Holding Size of the Respondents ...... 33 Table 4.3: Household size of the Respondents ...... 34 Table 4.4: Educational Status of Household Heads ...... 34 Table 4.5: Percentages of Land use/Land cover in Manity Selgen & Dembely Kebeles of Meko Woreda during the period 1986 – 2016 ...... 36 Table 4.6: Land use/Land Cover Change Matrix in Manity Selgen & Dembely Kebeles of Meko Woreda during the Period 1986 – 2000 ...... 37 Table 4.7: Land use/Land Cover Change Matrix in Manity Selgen & Dembely Kebeles of Meko Woreda during the Period 2000 – 2016...... 38 Table 4.8: Land Use/Land Cover Change Matrix in Manity Selgen & Dembely Sophe Kebeles of Meko Woreda during the period 1986- 2016 ...... 39 Table 4.9: Land Use/Land Cover Change during 1986-2000 ...... 39 Table 4.10: Land Use/Land Cover change during 2000-2016 ...... 41 Table 4.11: Land Use/Land Cover change during 1986 – 2016 ...... 42 Table 4.12: Source of Additional Land for household heads between 2005 and 2016 .....45 Table 4.13: Source of Dominant Cash Income for household heads ...... 46 Table 4.14: Mean Clearing Forest between 2005 and 2016 by In-migrants and Native Household heads ...... 48 Table 4.15: Mean of Clearing Forest size at Household Head Level in Dembely Sophe and Mainty Selgen kebele: ...... 55 Table 4.16: T- test for Equality of Means of Clearing Forest in hectare at Household Head Level of Dembely Sophe and Mainty selgen kebele ...... 55

Table 4.17: Mean and Standard Deviation of Clearing Forest by Two Genders ...... 56 Table 4.18: Independent Samples t- test of Clearing forest Size in Hectare at Household heads level in two gender...... 57 Table 4.19: Descriptive Statistics of Clearing Forest Size at Household Head Level in Different Marital Status between 2005 and 2016 for Different Land Uses ...... 58 Table 4.20: ANOVA ...... 58 Table 4.21: Post Hoc Tests ...... 59 Table 4.22: Descriptive Statistics of Clearing Forest Size in Hectare at Household Head Level at Different Age Group ...... 60 Table 4.23: ANOVA ...... 61 Table 4.24: Post Hoc Tests ...... 61 Table 4.25: Descriptive Statistics of Clearing forest Size in hectare between 2005 and 2016 at Household Head Level at Different Age Group ...... 62 Table 4.26: ANOVA ...... 63 Table 4.27: Post Hoc Tests ...... 63 Table 4.28: Correlation matrix ...... 65

Acronyms ANOVA Analysis of variance CSA Central statistical Authority EFAP Ethiopia Forestry Action Program EMA Ethiopia Map Authority ESHH Education Status of house hold heads ETB Ethiopian Birr ETM Enhanced Thematic Mapper FAO Food and Agriculture Organization FAO SOTER Food and Agriculture organization of Soil Organization of Tropical Eastern Region FCC False Color Composite FGD Focus Group Discussion GDP Gross Domestic Product LULC Land use/ Land cover MoARD Ministry of Agriculture and Rural Development NDVI Normalized Digital Vegetation Index REDD Reducing Emission from Deforestation and Degradation SNNP South Nation Nationalities and Peoples TM Thematic Mapper UN United Nations UNEP United Nations Environmental Program US United states USGS United States Geological Survey

WB World Bank WWF World Wide Fund

Abstract The purpose of this thesis was to understand the nexus between population growth and deforestation in the case of Meko woreda, Buno Bedele Zone, southwestern Ethiopia. In order to achieve the main objective of the study the necessary data were drawn from primary and secondary data sources. Questionnaire, key informant interview, focus group discussion, field observation and satellite imagery were the main means of data collection techniques from primary sources. To this study 224 household heads were taken from a total of 616 household heads of the two sample kebeles by systematic sampling technique. The collected data were analyzed by qualitative and quantitative techniques. In 1986, 2000 and 2016 the study area covered by forest was about 26%, 18% and 13% of the study area respectively. This indicates high deforestation rate in the study area. Major direct causes of deforestation drought on by humans include, fuel wood, expansion of agricultural land, house construction, resettlement, low level of education and training about forest , overgrazing, and population growth. All causes of deforestation are either directly or indirectly derived from high population growth of the study area. Demographic change and deforestation have cause and effect relationship. Due to deforestation the climate of the study area has been changing, the extent of biodiversity trends to minimize, agriculture productivity has been declining and other consequences are occurred. To minimize the rate of deforestation due to high population growth the government should provide alternative source of energy for house hold heads and give training about forest resources to maximize the participation of local people in the forest conservation program; Meko Woreda health office should create awareness about advantage family planning for rural household head and supply different family planning techniques, and also local communities should participate in the forest conservation mechanism by considering as their asset.

Key term: population, deforestation, conservation, Household heads, nexus

CHAPTER ONE: INTRODUCTION

1.1 Background of the Study

The twentieth century has been a century of uncontrolled population growth, economic development and environmental change. From 1900 to 2000 the world population is grown from 1.6 billion peoples to 6 billion. About 80% of the increased population has been occurred since 1980. This rapid population growth is facilitated by dramatic reduction of mortality especially in the less developed region. As a result, world population has been increased since 1950, with global rate of growth peaking 2.04% per year (UN, 2012). UN suggested that annual net addition of world population was 77 million peoples (UN, 2013a).

More than four billion hectares of the world were covered by forest in 2010. This represents 0.6 hectares per person. There is a wide variation in the global, regional and local distribution of forest resources (FAO, 2010).While, forest area in developed countries has established and is slightly increasing overall, deforestation has continued in developing countries. Around 7.3 million hectares of forest, which is roughly the size the country Panama, are lost in each year. About 36 football fields‟ worth of trees lost every minute in the world (FAO, 2010).

Deforestation is closely related to demographic expansion and the conversion of forest land to other land uses. Major causes of deforestation brought on by humans include over harvesting of industrial wood, fuel wood and other forest products, and overgrazing (FAO, 2001).

Ethiopia is one of the most severely deforested countries in sub- Saharan African countries. In relation to the causes of deforestation in Ethiopia several causes have been mentioned. The increasing demand of farming land, fuel wood, construction, unlawful settlement in the forest and unlawful logging are the main causes of deforestation of Ethiopia (MoARD and WB, 2007 and Behailu, 2006).

1.2 Statement of the problem

The world population is estimated to increase to 8.1 billion by 2025 and to 9.6 billion by 2050. Most of this growth is going to the developing countries. Population growth is the major cause of world poverty and environmental degradation (Ehrich, 2001 and Dietz, 2007).

Deforestation in Africa was observed to be higher. For instance, between 1990 and 2000 the continent lost about 52 million hectares of the forest which account 56% of the global reduction of forest cover. There is considerable variation of forest cover loss among the countries in Africa (FAO, 2010).

According to FAO reports, the total forest coverage of Ethiopian was approximately 40% of the land in 1900 but in 2007 it has been declined into less than 3 %. Rate of deforestation have been more difficult to estimate in the context country level. For example according Gurmesa (2015), the annual loss of natural high forest area has been estimated to between 150,000 and 200,000 hectares. And also according to FAO (2010), between 1990 and 2010 Ethiopia lost an average of 140,900 hectare or 0.93% per year.

The Oromia region represents approximately 70% of the forest resources of Ethiopia. However, its closed high forest are diminishing 50,000 hectare to 100,000 hectare per year due to agriculture land expansion, fuel wood collection, illegal settlers, urbanization, forest fires and poor logging practice( MoARD &WB,2007).

The study area is found one of the areas which known for its richest in forest resource but deforestation is the major issue in the local area. In the study area a new settlement in forest was increasing and had resulted in conversion of forests land into agricultural and other land use systems. According to Meko woreda Agriculture and rural development office 2015 report around 1000 resettles were exist in the study area and the population of the study area has been grown by 2.68. Moreover, high population pressure together and expansion of crop land were some of the key factors which were being aggravated deforestation in the study area. One of the challenges in the study area was that conversion of natural forests into cultivated land. According to Meko Woreda natural

15 resource office 2016 report more than 170 hectare of forest is cleared in every year in the study area due to expansion of crop land and other population growth related factors.

In light of this, this research work was conducted to fulfill the research gap by identifying the necessary information about the nexus between population growth and deforestation. Different researches were conducted in different parts of Ethiopia and elsewhere in the world about deforestation. But the nexus between population growth and deforestation that concluded by other researchers in other area may be different from the study area due to variation of the study area in terms of socio-economically, culturally and demographically from other areas. And when the researcher reviewed some researcher‟s work he had seen some methodological gap. For instance, Bijendra, Gurmesa and Mulugeta were utilized qualitative method of data analysis and some descriptive statistics. To fill this gap, the researcher applied both quantitative and qualitative data analysis methods.

1.3 Objectives of the study

1.3.1 General objective

The overriding objective of this study is to understand the nexus between population growth and deforestation in the case of Meko woreda, Buno Bedele zone, Southwestern part of Ethiopia.

1.3.2 Specific Objectives

More specifically, the study is aspired to

1. Investigate the trends of forest coverage and other LULC of the study area 2. spot the main human made causes of deforestation 3. look into the relationship between household size change and deforestation 4. Identify the main environmental and economic consequences of deforestation 5. Explore the possible mechanisms which helpful to minimize the rate of deforestation

1.4 Research Questions

So as to attaining these specific objectives, the following research questions that need addressing were formulated.

1. How are the change of forest coverage and other LULC of the study area? 2. What are the major human related causes of deforestation? 3. How is the relation relationship between household size change and deforestation? 4. What are the main environmental and economic consequences of deforestation? 5. What are the possible mechanisms which helpful to minimize the impact of population growth towards forest resources?

1.5 Significances of the Study

The purpose of this research was conducted to examine the relationship between population growth and deforestation. The study is providing further knowledge for local communities about causes and consequences of deforestation. It also provides inputs to policy makers‟ insights into resource management options. It uses for peoples, government, NGO as input to maintain forest resources from different human activities which results high population growth. And also it serves as a base for other researcher who wants to make further investigation about deforestation and related problems.

1.6 The Scope and limitation of the Study

The scope of this research was to study the relationship between population growth and deforestation in the case of Meko Woreda. However, due to time, money and labor constraint it is tedious and out of reach of to include all kebeles, the study was done on two kebeles from the rural area of the woreda. These are Manity Selgen and Dembely Sophe. The researcher tried to assess the relationship between population growth and deforestation between 2005 and 2016. The researcher also tried to assess trends of land use land cover changes, causes of deforestation, the relationship between household size change and deforestation, consequences of deforestation and methods of forest conservation practice in the context of study area.

In addition to financial and time limitations, the study is constrained by the following limitations:

 There is no prior study in the study area to be used as a springboard,  Lack of organized secondary data due to the absence of documentation and organized database system in the study area,  Absence of officials and some experts from office during data collection, and  Some household head were not willingness to give response during household survey.

However, utmost effort was made to minimize the negative impact of such constraints on the result of the study.

1.7 Organizations of the Paper

This thesis is about the nexus between demographic changes and deforestation in Meko woreda. The thesis is organized in to five chapters. The first chapter deals with background of the study, statement of the problem, objective of the study and significance of the study. The second chapter deals with review of conceptual as well as empirical literatures related to the objective of the study. Chapter three exclusively deals with study area and general methodology which encompasses decryption of the study area, research design, sample size and sampling technique, data sources, method of data collection and analysis. Chapter four, deals with the finding of the study. Chapter five presents conclusion and the main recommendations of the research work.

1.8 List of Operational Terms

Kebele: lowest administrative unit in Ethiopia

Household: the people who are living under one roof

Woreda: an administrative unit which equivalent to district

Zone: the second largest administrative unit after region in Ethiopia

CHAPTER TWO: REVIEW OF THE RELATED LITERATURE

2.1 Concept of Forest

2.1.1 Definition of Forest

The definition of forest is still ambiguous. According to FAO (2006), forest is a minimum land area of 0.05-1 hectare with tree grown cover more than 10-30 % and tree height of 2-5 m at maturity. Purnomo (2003) who defines forest as an ecosystem characterized by more or less dense and extensive tree cover, often consisting of stands that vary in species composition, structure, age, class, and associated processes. According to Carle and Holmgren cited in FAO (2007), a forest are defined as tree covered areas not predominantly used for purposes other than forestry and is thus distinguished into natural forests and planted secondary or plantation forests. The former is explained as forests regenerated naturally without human intervention, while the latter is defined as forests planted or seeded with human intervention, where the main land use is for production, protection of soil, water and other environmental values, conservation of biological diversity, socio-economic.

2.1.2 Uses of Forest

Historically, forests have played a major role to influence patterns of economic development, supporting livelihoods, helping structure of economic change, and promoting sustainable growth. FAO estimates that forest industries contribute more than US$450 billion to national income, contributing nearly 1 percent of global GDP in 2008 and providing formal employment to 0.45% of the global labor force (FAO, 2012). And other socio-economic and ecological uses of forest are the following:

A. Domestic consumption of fuel wood: More than 80% of the world forest resources harvested in developing countries is used as fuel wood, compared with less than 20% in developed countries. More than 90% of households in sub-Saharan Africa use wood-fuel as the staple source of energy (UNEP, 2006 & Fuller, 2008).

B. To keep earth cool: trees have another way to minimize the heat by absorb CO2. Plants always need some CO2 for photosynthesis, but earth`s air is know so thick with extra emissions that forests fight global warming just by breathing. Carbon dioxide stored in wood, leaves and soil often for centuries (UNEP, 2006).

C .To makes it rain: large forest can influence regional weather pattern and even create their own micro climate. The Amazon for example generates atmospheric condition that not only promote regular rainfall there and in nearby farm land, but potentially as far away as the great plains of North America (FAO, 2010).

D. They fight flooding: trees root are key allies in heavy rain, especially for low lying areas like river plain. They help the ground absorb more of flood, reducing soil loss and property damage by slowing the flow (FAO, 2002).

E. They block wind: farming near a forest has lots of benefits, like bats and songbirds that eat insects or owls and foxes that eat rates. But groups of trees can also serve as a wind break, providing a buffer for wind sensitive crops (Fuller, 2008). Etc

2.2 Deforestation

2.2.1 Definition of Deforestation

Deforestation defined broadly can include not only conversion of forest land into non- forest (FAO, 2005). According to Fearnside which cited in Gurmesa (2015), deforestation is the loss of original forest for temporary or permanently clearance of forest for other purpose. FAO (2006) defines deforestation as the conversion of forest to another land use or the long –term reduction of the tree canopy cover below a minimum 10% threshold.

2.2.2 Deforestation in Ethiopia

Altitude and topographic location have favored Ethiopia to have numerous or varying agro-climatic zone. This has given rise to the presence of a botanical treasure house containing 6000 different flowering plants in Ethiopia. Out of these flowering plants, 12% are probably endemic (FAO, 2007).

As Reusing (2001) stated that high forest cover of Ethiopia decreased from 50,410 km2 to 45,055 km2 or from 4.75 % to 3.93% of the total land area from 1973-1990. He calculated deforestation rate of 1,630 km2 per year. The FAO (2006) estimated a deforestation rate of 1,410km2 per year which relatively equal to Reusing estimation.

2.2.3 Causes of Deforestation and Forest Degradation

According to Williams (2006), the causes of deforestation are complex and often differ in each forest and country. It may be difficult to determine the cause of deforestation in a particular forest and noted that there are three schools of thought with regards to the cause of deforestation. One is the Impoverishment school, which believes that the major cause of deforestation is the growing number of poor. The second school of thought is Neoclassical which believes that the major causes of deforestation are open-access property rights. The third school of thought which believes that the major cause of deforestation is that capitalist investor‟s crowd out peasants is called political-ecology. This school sees capitalist entrepreneurs as the major agents of deforestation.

The causes of deforestation may be categorized broadly into anthropogenic and natural. According to Mahapatra and Kant (2003), the anthropogenic factors are believed to originate from six sectors and these include forest (e.g. extent of forest area), demographic (e.g. population growth), macroeconomic (e.g. economic growth and debt service growth), agriculture (e.g. agricultural growth), infrastructure (e.g. development of road) and political (e.g. level of democracy). For the anthropogenic factors, mining and quarrying, resettlement, increased wood fuel collection, clearing of forests for agriculture land, illegal and poorly regulated timber extraction, social and environmental conflicts, increasing urbanization and industrialization are the primary known causes for the loss of forests and woodlands. For the natural factors, the impacts of drought and natural forest fires have been highlighted in the cause (FAO, 2002).

The role of increased population growth, population density and urbanization are major factors currently exerting immense pressure on forest resources in major towns and cities in developing countries. Poverty and overpopulation are believed to be the main causes of forest loss according to the international agencies such as FAO and intergovernmental

21 bodies. However there is good evidence that rapid population growth is a major indirect and over-arching cause of deforestation. More people require more food and space which requires more land for agriculture and habitation. This in turn results in more clearing of forests. The growing populations in rich industrialized nations are therefore responsible for much of the exploitation of the earth and there is a clear link between the overconsumption in rich countries and deforestation in the tropics (Sands, 2005).

There are different causes of forest degradation and deforestation in Ethiopia. Almost all causes of deforestation and forest degradation are related to high population growth. Some causes of deforestation in Ethiopia are the following:

1.Agriculture expansion: Ethiopia`s economy is primarily based on agriculture, which accounts for 50% GDP and employs about 80% of labor force, shares 90% of total foreign exchange income and provides about 70% of the raw material for food processing, beverage and textile industry. So to get agricultural land peoples of Ethiopia invite to destruct forest resources. This leads to deforestation and forest degradation (MoARD and WB, 2007).

2. Harvesting or extraction of wood: as we know Ethiopia is one of the world`s most fuel wood reliant nation. Fuel wood is the most important forest product in Ethiopia. More than 85% of Ethiopian population lives in rural areas. The vast majority of these populations are dependent on the traditional fuels of wood, cow dung and crop. The annual demand of fuel wood (45million m3) is close to twenty times the demand of other forest products combined. The traditional fuel sources (woody biomass, crop residues, dung and charcoal) put together are reported 95.3 % of the total domestic energy consumption in Ethiopia. Whereas the modern sources such as petroleum and electricity accounted only 4.7% in 1990/91. The demand of fuel wood energy has been increasing from time to time due to high population growth rate (Mekete, 2006).

3. House construction: wood and wood products are the prominent materials for house construction in Ethiopia. About 74 % of housing unit in the rural and 72 % in the urban areas were reported to be ordinary houses with wall made of wood and mud. The annual demand for construction wood is estimated to be 2.1 million m3. Demand is projected to

22 increase with population growth and therefore doubles to 4.3 million m3 per year in 2020 (Mekete, 2006).

4. Expansion of infrastructure: Infrastructure development is another issues often underestimated as a cause of deforestation. Some infrastructures like mining, hydropower and road construction are facilitating deforestation and forest degradation in Ethiopia. During road construction flat lands are selected to build road as that time deforestation is mandatory (Mulugeta, 2007).

5. Resettlement pattern: in some regions resettlement is a major cause of forest degradation and deforestation (Behailu, 2006). The objective of resettlement program is to assist food insecure households‟ gets access to productive farmland. The strategy of resettlement program in most cases taking place through the clearing of forest. For instance, between 2000 and 2004 about 220,000 household heads or 1.2 million people were resettled in Amhara, Oromia, SNNP and Tigray. These households carved out crop land and made settlement housing by clearing areas of their natural vegetation and using woody resources unsustainably (Mulugeta, 2007).

6. Over grazing: Ethiopian forest also faced by frequent grazing. As FAO (2003) indicated, Ethiopia has more than 80 million livestock heads. Ethiopia has one of the largest livestock populations in Africa. It is estimated that over 80% of the livestock are found in the high land with an estimated stocking rate of 360 livestock head per km2, causing widespread over grazing and degradation on both arable, grazing land and forestland( Behailu, 2006).

2.2.4 Consequence of Deforestation

The process of deforestation may produce many negative effects such as global warming, biodiversity loss and soil degradation which are often identified (Mahapatra and Kant, 2003). The main consequences of deforestation are the following:

1. Soil degradation and flooding: Soil degradation particularly loss of soil fertility is a known effect of the loss of forests and grasslands. It is realized forest vegetation and biodiversity have become indispensable in soil nutrients maintenance. This is because as

23 the leaves, flowers and branches fall to the ground or as roots die, the numerous soil- dwelling animals and bacteria act on them, transforming the forest litter into organic matter, which is a reliable supply of soil fertility (Gabler, 2007).

Deforestation can result to watersheds that no longer able to sustain and regulate water flow from rivers and streams. The forest also serves as a cover against erosion. Once they gone, too much water can result to downstream flooding. Many of which have caused disaster in many part of the world. As fertile topsoil is eroded and flooded into the lower regions, many of coastal fisheries and coral reef suffer from sedimentation brought by flooding. This results to negative effects in the economic viability of many businesses and fatalities in wildlife population (FAO, 2010).

2. None-suitability of deforested areas for cultivation: most of areas that have undergone deforestation are actually unsuitable for long-term agricultural use such as ranching and farming. Once deprived of their forest cover the lands rapidly degrade in quality, losing their fertility and arability. The soil in many deforested areas is also unsuitable for supporting annual crops (FAO, 2010).

3. The displacement of indigenous communities and their traditional way of life (FAO, 2006).

4. The loss in number of biodiversity: this is probably the most serious consequence of deforestation and forest degradation. It means the destruction of and extinction of many plant animal species, many of whom remain unknown and whose benefit will be left undiscovered (WWF, 2012).

5.Climate change: deforestation can change the global heat energy not only through micrometeorological process but also by increasing the concentration of carbon die oxide in the atmosphere because carbon die oxide absorb thermal infrared radiation in the atmosphere (Pinker,2000). Deforestation disrupts normal weather condition by creating hotter and drier weather condition thus increasing drought and desertification, crop failure, melting of polar icecaps, coastal flooding and displacement of major vegetation regimes (Dregen, 2003). There is an established relationship between deforestation and global warming because forests, notably tropical forests are major carbon sinks. The loss

24 of tropical forests in many countries means the collapse of major carbon sinks and generation of more carbon dioxide which is a serious threat to global climate and atmospheric temperature distribution. On the part of global warming, it is noted that deforestation and forest degradation in developing countries are held to account about 18% to 20% of increased emission of GHGs that are responsible for global warming and climate change (Gorte and Sheikh, 2010).

6. Disturbance of water cycle: Deforestation also disrupts the global water cycle. With removal of part of the forest, the area cannot hold as much water creating a drier climate. Water resources affected by deforestation include drinking water, fisheries and aquatic habitats, flood/drought control, waterways and dams affected by siltation, less appealing water- related recreation, and damage to crops and irrigation systems from erosion and turbidity (FAO, 2010).

2.2.5 Possible Conservation Measures

The problem of deforestation can be reduced through the application of different forest- conservation measures. These measures include reforestation, afforestation, agro-forestry, social forestry, family planning and area enclosure (FAO, 2010). Let see one by one:

1. Reforestation: is planting trees in areas where the original forest cover has been removed. It is done to replace the trees that have been cut by humans for different purposes. Small-scale plantations mainly on degraded lands have become important forest conservation practice in Ethiopia particularly since the mid-1990s. In Ethiopia up to 2006 more than 300,000 hectare of land covered by planted trees through reforestation program (Mulugeta, 2007).

2. Afforestation: is planting trees in areas where there was no original forest cover. Afforestation is appropriate for areas where the land is left empty and exposed to erosion. Planting trees is often the quickest and most effective way of producing new biomass, thus helping to offset the loss of carbon resulting from deforestation or forest degradation on another plot of land (FAO, 2010). The government of Ethiopia continues to encourage industrial plantation to meet national industrial, construction and fuel wood demands through afforestation program. Until

2007 around 200,000 hectares of bare land in Ethiopia were planted through afforestation program. Eucalyptus species are the dominant plantation species (Mulugeta, 2014). 3. Agro-forestry: is forestry combined with farming. It is practices of integrating the planting of trees into farming to provide fuel, fruit, forage, shelter for animals or crops, and other benefits. From the total agricultural land of the world only10 percent is covered by agro-forestry. Farm forestry contributes up to 40 percent of farm income through the harvesting of wood, fruits, oils and medicines from trees. Trees can also provide fodder for livestock, help enhance soil fertility, and provide environmental benefits such as clean water, soil health, carbon sequestration and biodiversity (FAO, 2012).

4. Social forestry: refers to planting trees in urban areas in association with human settlements. Social forestry in cities, they provide ecosystem services like shade from heat, shelter from wind, absorption of pollution, and creation of urban biodiversity. Social forestry programs were aimed primarily at helping small farmers and the landless to meet their consumption and income needs. The strategic objectives embedded in the very concept of social forestry are to encourage large numbers of people to plant trees; to promote the kind of tree growing that will best supply fuel wood, small timber, grasses, to the small producers themselves; to increase the income and benefits to poor people from tree growing and forest products and to improve environmental protection (Micheal,2002).

5. Area enclosure: The minimum area of forest to be protected is generally considered to be 10 per cent of total forest area. It is reported that 12.4 per cent of the world‟s forest are located within protected areas. Tropical and temperate forests have the highest proportions of their forests in protected areas and boreal forests have the least. The Americans have the greatest proportion while Europe the least proportion of protected areas (Anonymous, 2010). It is the dominant type of re-greening practice in Ethiopia which promoted by NGOs, as well as by multilateral and bilateral donors, on degraded land. Recently, the government has also begun promoting area enclosure activities across the country. These activities seek primarily to rehabilitate degraded forest land and its biodiversity, and ensure a continued supply of forest products and services (Mulugeta, 2014).

6. Reduce population growth by applying different family planning techniques: this method is used balance population number with carrying capacity of environment. As we know the main causes of deforestation are related to rapid growth rate of the world population. So to minimize high rate of deforestation the best solution is minimize population growth by using different family planning techniques. Reduction of population growth is pivotal in reducing deforestation in the developing countries. Consequent of reduced population, increase in per capita income will occur as a consequence of increased incomes and literacy rates which will reduce pressure on the remaining forests for new human settlement and land use change (UN, 2012).

7. Expansion of research and education about forest: Training and education of stakeholder‟s helps people understand how to prevent and reduce adverse environmental effects associated with deforestation and forestry activities and take appropriate action when it is possible. Research helps to understand the problem, its cause and mitigation (Anonymous, 2010). Adequate forestry and natural resource education, research, and extension service are needed to meet the demand for and challenges of managing natural resources on a sustainable basis. All professionals concerned with agriculture, forestry, and natural resources should come together and work toward developing strategies for sustainable agro forestry and natural resource management that will ensure food security for the rural poor and long term sustainability of the resource base upon which other development sectors depend (Badege, 2001).

8. Adequate forest policy: Strong and stable government are essential to slow down the rate of deforestation. Half of the current tropical deforestation could be stopped if the governments of deforesting countries were determined to do so (Anonymous, 2010).

Ethiopia is owner of an environmental policy that identifies issues like integration of gender, social and cultural issues and public awareness and promoting understanding of the essential relation between environment and development as important agents of promoting conservation of resources. Badege (2001) indicated that without clear policy, it is difficult to adopt forest conservation practices. Forest conservation system requires long duration tenure system that guarantees continued ownership of land. Land in

Ethiopia is under government control and redistributed to individual farmers. Therefore, without clear policy, it is difficult to adopt forest conservation practices (Badege, 2001).

9. Participatory forest management: In order to forest management to be succeed all parties with an interest in the fate of the forest should be communally involved in planning, management and rehabilitee program (Chomitz, 2007)

2.3 Theoretical Literature and Empirical Evidences

There is debate on the role of the demographic changes in forest degradation and deforestation continuous with one group considering population growth as the main cause of deforestation while the other group is opposite of it. Former group include Mather, Robertson, William, Harrison, Palo, Litho. While the latter group Agrawal, Lohamann, Ghimire are prominent. Former studies were conducted on the Scottish high lands. Robertson and his advocators argued that human population is adversary effect to forest resources (Mather, 2000).

The assumption that population growth adversely affects economic growth and natural resource came under fire beginning in the late 1970s with the work of Juliin Simon. Simon‟s view was that moderate population growth is beneficial, not detrimental, because it brings technical innovation .While, Malthus argued with growing population, resource depletion is accelerated resulting in wide spread deforestation, overgrazing, biodiversity loss, etc. The ultimate destination of which is poverty and starvation (Mulugeta, 2014).

The most important demographic pattern which could impact on forest and forestry include population size and growth, population distribution and population structure (Bijendera, 2008). According his study, which concerning about impact of demographic change on forests and forestry in the Asia and the pacific, demographic change has its impact on forest land. As he stated that the impact of population change on forest land is related to level of education, need of agricultural land, level of technology, rapid rate of urbanization and expansion of infrastructure.

And also Temesgen & Wondie (2013) concluded that in their research, which concerns about threats of woody plant species diversity and conservation techniques in Ethiopia, forest of Ethiopia are mainly affected by expansion agricultural activity and settlement, land fragmentation, deforestation and invasive species introduction. These factors are related to high population growth.

Boserupian theory focused on the relationship between these three variables population, environment and technology. There is an emergent more neutral view that considers population growth neither strongly positive nor negatively impacting on environment and suggests that the environment and agricultural problem have social, political or economic causes (Mulugeta, 2007).

As Meyer who cited in Bijendera (2008) stated that the influence of population growth on forest can be considered as two effects. One is the consuming destructive effect. Population growths can inevitable result in increasing demand for life necessities. To meet these demands, large areas with good forest cover will be exploited for construction of house, roads, factories and shops. Another is the planting construction effect. Vegetation is an essential element for human development and it can help improve living environment as well as providing productive material and sources of energy for humans. With the population growth, the demand of ecological function provide by forest will increase. To full fill these demands some constructive actions such as forest protection, reforestation and soon will be carried out which resulting in a forest cover increase (Fuller, 2008).

2.4 Conceptual Frameworks

There is different cause‟s deforestation. Generally, causes of deforestation can be grouped into human made causes and natural causes. And there are different consequences. To minimize the deforestation rate different techniques has been taken. Generally, the causes and consequences of deforestation are presented in the following form.

Deforestation

Human made causes Natural causes -Demographic changes -Expansion of agriculture - Drought land - Desertification -Construction - Diseases - Over grazing - Forest fire - Resettlement - Expansion of infra structure -Extraction of fuel wood and Charcoal

Consequences of deforestation

- Loss of biodiversity - displacement of wildlife - Climate change -decline agriculture productivity

- Soil erosion - flooding

Measurement techniques

Afforestation social forestry Reforestation reduce population growth Agro-forestry participatory forest management Area enclosures

Figure 2.1 conceptual framework (Source: Developed by the researcher based on FAO, 2010, Mulugeta, 2007 and UN, 2012 )

CHAPTER THREE: BRIEF DESCRIPTION OF THE STUDY AREA AND RESEARCH METHODS AND MATERIALS

3.1 Brief Description of the Study Area

3.1.1 Location and Physical Background of the Study Area

Location

Meko woreda is one of the woredas categorized under newly formed zone, Buno Bedele. Meko woreda is sub-divided into 13 kebele administrative entities. Out of these kebeles, one is urban kebele others are rural kebeles. Its total area is around 29,000 hectare (Meko woreda agriculture and rural development office‟s report, 2015).

The study area is situated in southwestern part of Ethiopia which far 555km southwest from Addis Ababa, and Northwest of the capital city of Bunno Bedele zone which is known as Bedele and far 86km from Bedele town. It is surrounded by six neighboring woredas. It locates northeast of Algie Sachi woreda, west of Dabo Hana, northwest Dega woreda, east of Nole Kaba, south of Haru woreda and southwest of Chewaqa woreda (CSA, 2007).

Geographically the study area is located between 08037ˈ00ˈˈN to 08053ˈ00ˈˈN latitude and 35052ˈ00ˈˈE to 360 08ˈ00ˈˈE longitude.

Figure 3.1: Map of the study area (Source: ArcGIS and EthioGIS from CSA (2007))

Climate

According to Meko woreda agriculture and rural development office report (2015), total area of Meko woreda is divided into three agro-climate zones. These are temperate (dega), sub-tropical (woyina dega) and tropical (kolla) traditional climate zones. Temperate climate zone covers 15,466 hectare; sub-tropical climate zone covers 6,767 hectares and tropical climate zone covers 6,767 hectares of its total area.

The temperature of the study area ranges from 110c at minimum to 31.330c at maximum. It gets rainfall from the moisture laden south westerly (Guinea Monsoon) winds blowing over the area during summer. The total annual rainfall raining over the Woreda ranges between 1500 and 2500mm. The rainy month of the district is august (Meko woreda agriculture and rural development office‟s report, 2015 and explore from global weather server).

50.00

45.00

40.00

35.00 fall(cm) 30.00 Rainfall (cm) 25.00 Minimum Temperature 20.00 (oC) 15.00 Maximum Temperature (oC)

10.00 Tempreture(0c)and rain 5.00 0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month of a year Figure 3.2 Mean Monthly temperature and Rainfall in Meko Woreda (1979 - 2014) (Source: explorer from global weather server)

Topography and Soil Type

MekoWoreda is situated on landscapes having elevation ranging between 1490 m amsl in the east of Meko Woreda which contains part of Dembely Sophe Kebele and 2430m amsl in the western end of the woreda.

According to FAO SOTER (1997) soil map of East Africa, Meko woreda is subdivided into three landscapes. The woreda is dominated by plateaus, hilly landscape and escarpments. The geology of the plateaus and escarpments in the central part is dominated by acidic rocks. The southern part hills and escarpments are formed on ultra- basic rocks and pyroclastic rocks. And the main soil types which existing in the study area are vertic nitosols which covers 15% of the woreda and umberic nitosol which covers 85 % of the woreda.

3.1.2 Population and Socio-economic Characteristics of the Study Area

Population

Population number of the study area was 30,421. Out of this, 15,971 were males and 14,450 were females. When we see the population distribution, 27,331 peoples were settled in rural area and 3,090 peoples were settled in urban area (Oromia urban planning institute western branch, 2017)

Table 3.1: population size of the study area

Household size

Temperate Sub tropical Tropical Total population

M F T M F T M F T M F T

1046 115 1161 2203 223 2426 579 80 659 15,971 14,450 30,421

Source: Oromia urban planning institute western branch, 2017

The average family size for the study area household head is more than 4 and 5 persons for urban and rural families respectively. Out of the total population residing in the woreda, which were consider economically active (15-64 age group) were accounted 49.7 %. Whereas the dependent population accounted for 50.28%, out of which the youth age group (0-14 age group) comprised 46.8%. While the old age dependents (above 65 years old) comprised only 3.48%. Generally we can conclude that about 50.28% of the total populations are economically dependent on 49.7% of the general population (Oromia urban planning institute western branch, 2017)

Land Use Pattern

When we see its land use and land cover pattern, around 15,900 hectares are crop land. Forest land covers 2,920 hectares of the study area. Grass land and shrub land covers 6,650 hectares of its total area. And 2,330 hectares are bare land. The remaining 1,200 hectares are covered by other land uses (Oromia urban planning institute western branch, 2017)

Table 3.2: land use land cover pattern of Meko woreda

Land use land cover Coverage in hectare Percentage share Cropland 15,900 54.8 Grass and shrub land 6,650 23 Forest land 2,920 10 Bare land 2,330 8 Others 1,200 4.2 Total 29,000 100 Source: Oromia urban planning institute western branch, 2017

When we see the forest coverage of Meko woreda, it covers 2,920 hectares. Of this, 2,116 hectares are covered by natural forest. The remaining 804 hectares are covered by planted forest. Forest coverage of the study area is unevenly distributed in kebele level. Highest forest coverage is exist in Qode Gasi, Busano Gnagno, Dembely Sophe, Manity Selgen and Dora Abo kebeles (Meko woreda agriculture and rural development office‟s, 2015).

Economic Activities

The main ways of life of peoples in the study area are agriculture and service sector. More than 92.4% of peoples of the study area are engage in agriculture like crop cultivation and animal rearing. Less than 8% of peoples of the study area engage their life based on shopping, government employment, wood work and other service sectors. And its agriculture is mainly depending on rainfall and traditional farming system. The dominant crop which produced in the study area is teff which shares more than 93% of agriculture product. The livestock production is the second livelihood of the study area population, mostly rural community. More than 90% of livestock are cattle. It also practiced by urban dweller in the traditional way (Meko woreda agriculture and rural development office‟s report, 2015 and Oromia urban planning institute western branch, 2017).

3.2 Research Methods and Materials

3.2.1 Research Design and Approach

There are different types of research approaches which applied in social science research to choose from them. However, for the purpose of this study mixed research approach was selected. The purpose of this research approach is to include both quantitative and qualitative approaches in one research simultaneously. For this research cross-sectional survey design was selected. In a cross sectional survey collects data to make inferences about population of interests at one point in time.

3.2.2 Data Types

In this research both qualitative and quantitative data were under taken. These data were obtained from primary and secondary data sources. Household heads, field, natural resource expert and satellite images of 1986, 2000 and 2016 were the primary sources of data for this work. The main data collection techniques which applied to collect data from primary sources were questionnaire from household heads, interview with natural resource expert and household heads, FGD of household heads, field observation and satellite imageries. And also the researcher was tried to collect data from secondary sources like reports, published and unpublished materials.

3.2.3 Sampling Technique and Sample Size Determination

A two stage sampling technique was employed in this study to collect primary data. Firstly, two kebeles were selected from thirteen kebeles by purposive sampling technique. The main purpose to select two kebeles form other kebeles, the two kebels which under taken in this study are known by high rate of deforestation. Secondly, to collect data by using questionnaire, the sample household heads were selected from each kebele by using systematic sampling technique. By using Yamane (1973) sample size determination formula, 243 household heads were selected from 616 household heads of two kebeles with proportional to their numbers of household heads. In this study sample frames would be divided into male and female sex groups. Household heads of each kebele in different sex group were recorded alphabetically. The sample respondents were taken by three

36 intervals from prepared list of household heads living in each kebele. The specific interval was calculated by number of household heads divided by number of samples. The starting number was selected by using day-coding method.

Yamane (1973) sample size determination formula

n=N / (1+N (e) 2)

n=sample size

N=study population or sample frame

e=95% accuracy or 5% error

So sample size of the study area

n= 616/ (1+616(0.05)2)

=243

Table 3.3: sample size of the study

Kebele Household heads size Sample size Male Female Total Male Female Total Dembely Sophe 368 35 403 145 14 159 Manity Selgen 187 26 213 74 10 84

Total 555 61 616 219 24 243 Source: Computed based on Meko woreda agriculture and rural development office‟s report in 2015

3.2.4 Methods of Data Collection

As in the above stated both primary and secondary data sources were considered in this research. Primary data of this study were collected by using observation, questionnaire, key informant interview, focus group discussion and satellite imagery. Let see the data collection techniques from primary sources one by one:

A. Observation

By using this method of data collection, data which related to the present level of forest coverage, different activities of society which affects the forest resources, consequences of deforestation and forestation, afforestion practice of the community etc were collected from two kebele( Appendex IV).

B. Questionnaire

The questionnaires were distributed to 243 household heads. When we see sex distribution of sample size, the researcher distributed questionnaire for 215 male household heads and 28 female household heads. The main data which gathered through questionnaire were age of household heads, marital status of house hold heads, household size of household heads, landholding size of household heads , sources of additional farm land for household heads, sources of energy for household heads, livestock size of household heads, education level of household heads, agriculture product of household heads per ha, source of grazing land for livestock‟s of household heads, sources of the dominant cash incomes for household hold heads etc. To collect data through questionnaire the researcher used four enumerators.

C. Key Informant Interview

The researcher interviewed with natural resources management expert of Meko woreda, Meko woreda health office administer, two kebele`s managers and seven elders. Through interview the researcher was get information about the previous and present forest coverage, causes and consequences of deforestation, mechanism of forest conservation, the pattern of population growth and its impact on forest coverage and other issues from elders. From kebele managers and natural resource experts information which related to current forest situation, the relationship between population and deforestation, causes and consequences of deforestation, and the pattern of forest conservation in the study area were collected. The main target to select elders from other household heads for key informant interview was elders have more know-how about the previous forest coverage of their locality than others. The researcher passed 20 minute with each key informant interview.

D. Focus Group Discussion

And also the researcher discussed with two focus groups. Each focus group was included ten peoples. Totally, 14 male household heads and 6 female household heads were involved in FGD. The researcher discussed with each focus group for one hour in two times. The main information which collected through focus discussion were about causes and consequences of deforestation, the impact of population growth towards forest resources and method of forest resources conservation.

E. Satellite Imageries

The study of the long term (1986 – 2016) land use/ land cover patterns and changes and thus the detection of symptoms of land degradation (deforestation, conversion to bare land) in the woreda was carried out based on satellite imageries and base maps of 2016 obtained from USGS . The land use land cover maps of the area at different times were depicted based on the Land Sat imageries of Land Sat TM 7 (1986) and Land Sat ETM+ (2000, 2016). All of the imageries were taken on a bright day in March 1986, February 2000 and January 2016. A full scene (7 bands for Land sat TM 1986, 8 bands for Land sat ETM+ 2000 and 2016) of each of Land sat imageries contained in the path 171 and row 053 was taken from internet sources of Earth Explorer (a USGS server for land sat imageries). A very high resolution and a recent (2016) imagery from Google Earth were used to improve the accuracy of the classification made on the 1986, 2000 and 2016 Land sat imageries.

Parallel with primary sources of data, secondary data sources from Meko Woreda Agriculture and rural development office 2015 report and Oromia urban planning institute western branch 2017 published paper were undertaken. From secondary source of data the researcher was got climate data, the dominant crop type and other socioeconomic issues of the study area.

3.2.5 Method of Data Analysis

A. Analysis of Survey Data

Since the collected data were quantitative and qualitative data, this study was relied on qualitative and quantitative data analysis. Qualitative data like consequences of deforestation and forest conservation mechanisms that were generated through key informant interview, FGD, field observation and other secondary sources were analyzed by using description method of analysis such as summarization, categorization, restating etc. Quantitative data which collected through questionnaire were coded and entered into computer for analysis by using computer software of SPSS (Statistical Package for Social science). By using this software, correlation coefficient, t-test and ANOVA were applied to analysis the quantitative data. To explore the relationship between household size changes, change of agriculture productivity in quintal per hectare, clearing forest size in hectare and frequency of training which household heads have got at household head level between 2005 and 2016 were analyzed by using Pearson correlation. One way ANOVA was applied to compare mean clearing forest in hectare by household heads in different age group, marital status and education status. And also t-test was used to compare mean clearing forest size in hectare between male and female house hold heads.

The main dependent and independent variables which under taken in this study are the following.

Independent Variables

 Sex of household heads  Source of energy for household heads  Source of income for household heads  Land holding size for household  Age of household heads  Marital status of household heads  Education status of household heads  Chang household size between 2005 and 2016 at household head level

 Number of times which household heads have got training about forest between 2005 and 2016 Dependent variable  Clearing forest size in hectare between 2005 and 2016 at household head level And also descriptive statistics such as mean, percentage and frequency were applied for some statistics. Tables, graphs and figures were also applied to organize, analyze and interpret the study.

B. Analysis of Land Use Land Cover Change of Satellite Images

Having looked at the false color composites in detail, the varying texture, intensity of the reddish color tells that the vegetation in the area is composed of grassland, shrub land and forest land. Having looked at a high resolution and recent imagery of the area, the bright/darker cyan covered area consists of scattered plots of cropland and dominantly bare land. The central and northern parts of the 2016 imagery is dominated by red color and seems that the vegetation in this area has increased. However the high resolution imagery from Google earth has showed that area is dominated by grassland and scrubland. That is Google Earth Imagery was used to improve the accuracy of classification or to differentiate the natural forest which is normally found along rivers from grass, scrub or weed covers.

Unsupervised classification on NDVI derived for the image. This resulted in three classes (vegetation, bare soil and water bodies). Based on supervised classification the areas classified into vegetation were reclassified in to forest, shrub and grass land. Whereas the areas classified into bare land was reclassified into crop land and bare land. The later was supplemented with very high resolution satellite imageries. So that the crop land was distinctively differentiated from bare lands based on regular pattern of crop lands have. The area occupied water bodies along the streams reclassified as independent LULC category rather there were generalized shrub land.

The classification and interpretation of the satellite imageries into a certain LULC cover categories was done by image enhancement (by applying smoothing, sharpening, contract and stretching), displaying bands in false color composition and natural color

41 composition, and deriving NDVI (normalized vegetation index) applied on land sat imageries were the main tasks carried out. A false color composite display of green, red and near Infrared bands of the Imageries Land Sat TM 7 (March, 1986), Land Sat ETM+ (February, 2000) and Land Sat ETM+ (January, 2016) of the area was displayed. The main intention behind using a false color display of these bands was to differentiate water bodies, vegetation (grassland, shrub land, and forestland) and bare soils (exposed surface, cultivated and built up areas) distinctively. As shown in the imageries of the area displayed above, an agglomeration of cyan (light blue) colored areas were identified as cultivated land. Besides the brighter red tone area in the central and eastern parts of the Meko woreda were clearly differentiated to be vegetation area (grassland, shrub land and forestland). Together with the author‟s knowledge about the area, the dark and rough red tone along the rivers in the area were identified and classified to be forestland. Google earth which displaying the current image of the area at a very high resolution allowed the author to classify the bare land area as barren land and as cropland.

The enhanced FCC display of the Land sat imageries of the area combined with the very high resolution imageries from Google Earth, Manity Selgen and Dembely sophe Kebeles of Meko woreda was classified into five major land use categories (Forest land, Shrub land, grassland, bare land and cropland) based on the USGS level I land use/land cover classification (Mc Cloy, 1995).

Table 3.4 classification of LULC of Mainty Selegen and Dembely Sophe kebeles

Lu/Lc Type Description Forestland Areas covered with dense trees/woods, shrubs, and grasses – spatially not differentiable pattern- which appears to be a dark, or a bright red continuum in FCC display of land Sat imageries Shrub land Scattered patches covered with trees, which appears to be a mix of dark and light red color in a FCC display of Land Sat Imageries. Grassland Areas covered with normally irregular shapes/strips in the cropland and rectangular inside built up areas with a smooth light red color on a FCC display of dry season Land Sat imageries.

Cropland Areas covered with normally regular shapes/patterns of land lots with a smooth darker cyan color (but also reddish irrigated farms or perennial crops) on a FCC display of a dry season Land Sat imageries. Bare land Exposed areas probably covered by sandy soils appear to be brighter cyan and they are a continuum of amorphous shaped areas and dominantly found on hilly and valley landscapes along Sudan border.

Source: extracted from land sat images of 1986, 2000 and 2016 and USGS server Once generated the land use/land cover maps of Manity Selgen and Dembely sophe Kebeles of Meko woreda for the years 1986, 2000 and 2016, Arc GIS version 10.5 and Excell 2010 was used to map expansion cropland and diminishing vegetation covered areas over the past 30 years, derive change matrices and create graphs showing which land use/land cover has remained persistence, gain or lost its areal extent.

3.2.6 Data Validity and Reliability

One of the main requirements of any scientific research is the validity and reliability of the data and finding. Reliability deals with the consistency and dependability of the result which obtained from a piece of research. Validity is concerned with the meaningfulness, truthfulness and acceptability of research components (Nunan, 1999).

In order to assure the validity of the research, adequate related conceptual and empirical literatures were reviewed to the problem under study. And also the researcher tried to refer different methodological aspect of the previous research results and other published reference books. And also to achieve the maximum validity and reliability of the data, triangulation method of data collection and analyze were employed. By different method of data collection the researcher was cross checked data which collected by one technique data collection to another technique.

Before presenting the result of the land use/land cover interpretation made for each year, 1986, 2000 and 2016, accuracy of the resulting maps were assessed using Kappa index based on GPS data collected at 58 sample points in the field and the corresponding sites

43 on the 2016 Google Earth Image of the area. The samples were taken at the spectral signatures representing the main land use/land cover categories defined above.

About 85.8% of the sample points matches were secured between the field recorded land use/land cover categories with that of the land use/land cover categories detected in the 2016 very high resolution satellite imagery obtained from Google Earth of the area. How accurate the interpretation of the 1986 and 2000 land sat imageries was assessed based on matching the color patterns (signatures) of the false color composite display of the Land Sat 2016 with the very high resolution of the 2016 Google earth imagery. The signatures for Forestland, shrub land, grassland, bare land and urban/built up area taken from the FCC display of the 2016 Land sat imagery were then compared to the same/similar signatures found on the corresponding FCC display of the 1986 and 2000 Land Sat imageries of Manity selgen and Dembely Sophe Kebeles of Meko Woreda. Above all the basic photogrammetric principles (smoothing- to remove dusts or noises and vegetation index allowing to discriminate vegetation from water body and bare soils, elements of visual interpretation like tone, texture, shape, size, structures, shadows, slope, etc. were strictly considered while differentiating patterns of signatures for vegetation (Forest, scrubland, grassland), and bare land areas (bare land and cropland).

CHAPTER FOUR: RESULT AND DISCUSSION

4.1 Socio-economic Characteristics of the Respondents

A. Sex and Age Structure of the Respondents

From distributed questionnaire by researcher for 243 household heads, only 224 household heads fill the questionnaires and returned to the researcher. Out of 224 household heads, 200 were males and 24 were females. When we see the distribution of respondents in kebele level, 129 male and 14 female household heads were participated from Dembely Sophe and 71 male and 10 female household heads from Mainty Selgen were participated.

Table 4.1 Age structure of Respondents

Age of HHH Frequency Percent 24-43 106 48.7 44-63 94 41.9 64-82 24 9.4 Total 224 100.0 Source: household head survey at 2017 As in the table 4.1 indicated that about 106 ( 48.7%) respondents were 24-43 years old and (41.9%) and 24 ( 9.4%) of respondents were grouped into between 44 and 63 years old and between 64-82 years old age group respectively. Most of respondents have 24 up to 63 years old age. The maximum and minimum age of the respondent is 24 and 82 respectively. The effect of age and sex of household heads towards clearing forest size in the study area is described in the inferential statistics part.

B. Marital Status of Respondents When we see marital statuses of the respondents, 175 respondents were married, 12 respondents were unmarried, 12 respondents were divorced and 25 respondents were widower and widowed. So most of respondents in this study were married household heads.

C. Land Holding Size of the respondent According to household survey, land holding size in hectare of the respondent is represented in the table 4.2. Table 4.2: land holding size of the respondents

Land holding size in ha Frequency Percentage

0.5-2.2 82 36.6 2.21-3.9 81 36.2

3.91-5.61 46 20.5

5.62-7.32 13 5.8 7.33- 9 2 0.8

Total 224 100 Source: household head survey at 2017

As in the table 4.2 indicated that , about 82( 36.6%) of respondents have 0.5-2.2 hectare land holding size , about 81(36.2%) respondents have between 2.21-3.9 hectare land , about 46 (20.5%) respondents have between 3.91-5.61 hectare land,13(5.8%) respondents have between 5.62 and 7.32 hectare land and 2(0.8%) respondent have 7.33 up to 9 hectare land. The maximum and the minimum land holding size of the respondents is 0.5 and 9 hectare respectively. Mean land holding size of the respondents is 2.82 hectare. More than 72% of the respondents have less than four hectare land. According to natural resources expert, even around 25% of respondents have more than 4 hectare land, only 2 or three hectare can used for crop cultivation because of its fertility is poor which resulted to intensive erosion.

D. Household size of the Respondent

As in the table 4.3 indicated that about 32 respondents have 1 up to 3 household size; about 143 respondents have four up to six household size. The remaining 48 respondents have 7 up to 9 family sizes. More than 175 (85 %) of respondents have more than 4 house hold size. The mean household size of the respondent is 5.16. The maximum and

46 minimum house hold size of the respondent is 1 and 9 respectively. The standard deviation of house hold size is 1.959.

Table 4.3: Household Size of the Respondents

House hold size Frequency Percentage 1-3 32 14.2 4-6 143 63.9 7-9 48 21.4 Total 224 100 Source: Household head survey at 2017

E. Education Status of the Respondents

According to household head survey most of household heads are uneducated. The education status of the respondent could be grouped in three groups these are 0-class, elementary and secondary and above.

Table 4.4: Education status of household heads

Grade level Frequency Percent Not literate 111 49.6 Elementary grade level 101 45 9 and above 12 5.4 Source: household head survey

As in the Table 4.4 indicated that most of respondent were uneducated (0-class) which shares 111 (49.6%) of the respondents. The remaining (101)45% and 12 (5.4 %) of respondents were stopped education in elementary and secondary school level respectively.

4.2 Patterns and Extent of the Major LULC in the Selected Kebeles of Meko Woreda during 1986- 2016 The Land use/land cover map of the two kebeles in 1986, 2000 & 2016 is portrayed in the figure 4.1 as one image so that visually comparison of the LULC patterns in the area can

47 be done easily. The dark green representing the natural forest or river in vegetation has been decreasing over the last 30 years on average at a rate of about 60 hectares a year. The decline was very high in south western part spatially compared to other areas in the study area. Unlike these both grassland and scrubland have been increasing in the last 30 years at a rate of about 40 and 100 hectare a year respectively. The increase was dominantly happening on eastern plains where this area used to be exposed surface. The brown color representing cropland has been increasing from 1986 to 2016 at a rate of about 40 hectare a year. The increase of cropland was along the western border and the central part of the selected kebeles (Manity selgen and Dembely Sophe) of Meko woreda. A large extent of land used to be barren has been declining at the highest rate of about 126 hectares per year. Viewed the entire images (land use/land cover maps of all years), the northern-eastern part appear to be still vegetated – though largely swallowed by grass land and scrubland. The spatial trend of cropland in the south western part obviously appears to be expanding.

Figure 4.1 LULC changes of Mainty Selgen and Dembely Sophe kebeles in1986, 2000 and 2016 (source: satellite images from www.USGS.com) In the table 4.5 to see the extent of each land use/land cover in 1986, 2000 and 2016 and their trends in the last three decades. In 1986, 2000 and 2016 the area covered by forest was about 26%, 18% and 13% of the area respectively. Unlike this the areal extent of

48 scrubland has been increasing from 1,723 hectare (~13%) in 1986, through 2,551 hectare (~19%) in 2000 to 4,774 hectare (~35%) in 2016. In a similar pattern the area covered by grassland was also increasing. The area covered by the grass land was about 655 hectares (~5%) in 1986 and has almost doubled to be 1,211 hectares (9%) in 2000 and this in turn has increased to be 1913 hectares (14%) in 2016. The reason for the increase of grassland and shrub land to such extent which understand from field observation could be associated with the infestation of the north eastern by a weed like elephant grass which in turn due to the changing climate in the area and increasing human activities like expansion of agricultural land, cutting of wood plant for fuel wood consumption and over grazing. The areal extent of cropland has been increasing in the first decade and second decade. The areal extent of cropland in 1986 was only about 2,757 hectares (20%) of the selected kebeles. But this extent has increased by about 856 to become 3,613 hectares (~26%) in 2000 and by 1,327 hectare to become 3,940 hectares (~29%) in 2016. Table 4.5: Percentages of Land use/Land cover in Manity Selgen & Dembely Kebeles of Meko Woreda during the period 1986 – 2016

1986 2000 2016 LULC type Ha. % Ha. % Ha. % Forestland 3528.8 25.8 2497.9 18.3 1811.6 13.2 Shrub land 1723.0 12.6 2550.9 18.6 4773.9 34.9 Grassland 654.6 4.8 1211.5 8.9 1912.9 14.0 Bare land 5019.0 36.7 3809.1 27.8 1244.2 9.1 Cropland 2756.9 20.1 3613.0 26.4 3939.8 28.8 Total 13682 100.0 13682 100.0 13682 100.0 (Source: Computed based on land sat images of 1986, 2000 and 2016)

4.2.1: Analysis of LULC Change in the Selected Kebeles during1986-2016 The matrices tables in the below indicates which land use/land cover category is transformed in each period over the last 30 years. In the first period (1986 – 2000), which indicated in the table 4.6, about 693 hectare (20%) and 143 hectare (4%) of forest land was deforested to be a shrub land and grassland respectively. The transition from shrub land to grassland during the first period (1986-2000) was about 70 hectare which accounts for 4% of the area. The conversion was not only from the natural forest to shrub

49 land or grassland or from shrub land to grassland there was also a regeneration of grassland to shrub land or forest or shrub land to forest land observed in this period. About 308 hectares of shrub land and 47 hectares of grassland were regenerated to forest land and 87 hectare of crop land transformed into forest land through reforestation and afforestation mechanisms. About 727 hectares or 20.6% of the forest land 43.2 ha (2.5%) of shrub land, was cleared for a cropland between 1986 and 2000. About 209 hectares of forestland and 553hectares of shrub and 174 hectares of grass land were cleared for nothing (bare land) and this much of area was left barren and left exposed for erosion. According to 65 years old elder large forest size of the study area was changed into cropland around 1980s because of the population number of the study area increased by number in-migrants and birth. During this time large amount of forestland were cleared to source of wood to house construction and fuel wood consumption for in-migrants and changed into shrub and bare land.

Table 4.6: Land use/Land cover change matrix in Manity Selgen & Dembely Kebeles of Meko Woreda during the period 1986 – 2000

Land use/Land cover types 1986

LULC type Forestland Shrub land Grassland Bare land Cropland Total

Ha. % Ha. % Ha. % Ha. % Ha. % Ha. %

175 Forest land 49.8 308 17.9 47.3 7.2 298 5.9 86.9 3.2 2498 18.3 8 Shrub land 693 19.6 749 43.5 0.0 0.0 1109 22.1 0.0 0.0 2551 18.6 Grassland 143 4.0 70 4.0 433 66.1 566.4 11.3 0.0 0.0 1212 8.9

Bare land 209 5.9 553 32.1 174 26.6 2872 57.2 0.0 0.0 3809 27.8 crop land 727 20.6 43.0 2.5 0.0 0.0 174.3 3.5 2670 96.8 3613 26.4 352 172 1368 Total 100 100 655 100 5019 100 2757 100 100

9 3 2

Lu/lc2000 types Source: Computed based on satellite images of 1986, 2000 and 2016 During the second period (2000-2016), which indicated in the table 4.7, the land use/land cover dynamics in the area was more or less the same to the first period regardless of the percentage difference. The areas covered by forest and bare land were declining and the area covered by grass and shrub vegetation and cropland were increasing as it happened in the first period (1986-2000). About 739 hectare (30%) and 215 hectare (9%) of

50 forestland was converted to shrub land and grassland respectively. About 58 hectare (2.3%) and 212.5 hectare (8.5%) of the forestland in 2000 was converted to bare land and crop land respectively. About 233 hectare of grass land and 191hectare of shrub land were changed into crop land. About 58 hectare of forest land, 390 hectare of shrub land and 84hectare of grass land were changed into bare land. And also about 270 hectare of shrub land and 43 hectare of grass land were regenerated into forest land between 2000 and 2016 by naturally and reforestation and afforestation mechanisms. During this period large amount of forestland was deforested due to different factors like expansion of crop land and change of forestland into shrub land and grassland which results to high population growth. Table 4.7: Land use/Land cover change matrix in Manity Selgen & Dembely Kebeles of Meko Woreda during the period 2000 – 2016 Land use/Land cover types 2000

LULC Forestland Shrub land Grassland Bare land Cropland Total type Ha. % Ha. % Ha. % Ha. % Ha. % Ha. % Forestland 1274 51.0 270 10.6 43 3.5 144 3.8 81 2.2 1812 13.2 Shrubland 739 29.6 1436 56.3 454 37.5 1888 49.6 257 7.1 4774 34.9 Grassland 215 8.6 258 10.1 397 32.8 896 23.5 147 4.1 1913 14.0 Bare land 58 2.3 396 15.5 84 6.9 706 18.5 0 0.0 1244 9.1

crop land 212 8.5 191 7.5 233 19.3 175 4.6 3128 86.6 3940 28.8

Total 2498 100 2551 100 1211 100 3809 100 3613 100 13682 100

use/LandLand types cover 2016 Source: Computed based on satellite images of 1986, 2000 and 2016 The matrix table in table 4.8 shows the 30 years (1986-2016) land use /land cover change in Manity Selgen and Dembely Sophe kebeles of Meko woreda. Forestland or the natural vegetation along the streams in the area have declined sharply and is expected to decline in the next 30 years most likely being transited to shrub land, grassland, cropland and bare land. About 1,240 hectare forest land and 227 hectare grass land were changed into shrub land. About 213 hectare forest land and 218 shrub land changed into grassland between 1986 and 2016. Shrub land and grassland were increasing in the last 30 years and this mainly due to the transition of forestland into one of this vegetation and the rehabilitation of degraded bare land. About 815 hectare of forest land, 152 hectare of shrub land and 126 hectare of grassland were changed into crop land between 1986 and

2016. Cropland has been increasing in the last 30 years and would be expected as long shrub land and grassland and even forestland with suitable topography and soils is available. Cropland is inevitably expected to increase mainly due to the ever increasing population of the area and the consequent shortage of land that would be created. Table 4.8: Land use/Land cover change matrix in Manity Selgen & Dembely Sophe Kebeles of Meko Woreda during the period 1986- 2016 Land use/Land cover types 1986

LULC type Forestland Shrub land Grassland Bare land Cropland Total

Ha. % Ha. % Ha. % Ha. % Ha. % Ha. %

Forestland 1051 29.8 232 13.4 23 3.6 428 8.5 78 2.8 1812 13.2

Shrubland 1240 35.1 859 49.8 227 34.7 2289 45.6 159 5.8 4774 34.9

Grassland 213 6.0 218 12.7 203 31.0 1187 23.7 92 3.3 1913 14.0

Bare land 210 6.0 262 15.2 75 11.5 696 13.9 0 0.0 1244 9.1

Cropland 815 23.1 152 8.8 126 19.2 418 8.3 2429 88.1 3940 28.8

Total 3529 100 1723 100 655 100 5019 100 2757 100 13682 100 LU LCtypes 2016 LULCtypes Source: Computed from satellite images of 1986, 2000 and 2016

To determine what areal extent each LULC has persisted, gained or lost, the following tables and graphs were produced for each period.

Table 4.9: Land use/Land cover change during 1986-2000

Persistence Gains Losses Net Change LULC Type Ha % Gains % Losses % Ha % (ha) (ha)

Forestland 1758.4 49.8 739.4 14.22 -1770.4 -34.0 -1031.0 -19.8

Shrub land 749.3 43.5 1801.5 34.65 -973.6 -18.7 827.9 15.9

Grassland 432.8 66.1 778.7 14.98 -221.8 -4.3 556.9 10.7

Bare land 2872.2 57.2 936.9 18.02 -2146.9 -41.3 -1210.0 -23.3

Cropland 2670.0 96.8 942.9 18.14 -86.8 -1.7 856.1 16.5

Total 8482.8 62 5199.5 100 -5199.5 -100 0.0 0.0

Cropland

Bareland Gains (ha) Grassland Losses (ha) Shrubland

Forestland

-3000.0 -2000.0lulc(hectare)-1000.0 0.0 19861000.0-20002000.0

Figure 4.2: LULC change in hectare between 1986 and 2000 (Source: computed based on land sat images of 1986 and 2000)

In the first period (1986-2000), which indicated in the table 4.9, almost all of crop land about 2670 hectare (97%), about 432 hectare (66%) of grassland, about 2872hectare (57%) of bare land, about 1758.4 hectare (50%) of forestland and about 749hectare (44%) of shrub land in 1986 were found in 2000 unchanged. About 739 hectare of grassland and shrub land was regenerated to a forestland. About 1801 hectares of shrub land have been gained from forest, grassland or bare land areas in 1986. A big mass of bare land (about 2147 hectares) and forestland (about 1770 hectare) were transformed either to crop land, grassland or shrub land (plantation). Generally, forest land and bare land has been declined between 1986 and 2000 by 1031 hectare and 1210 hectare respectively. But crop land, shrub land and grass land has been increased by 856 hectare, 830 hectare and 557 hectare respectively. Generally the net change of forest land and bare land were negative between 1986 and 2000. Whereas the net change of shrub land, grass land and crop land were positive. This indicated that there was high rate of deforestation between 1986 and 2000 in Dembely Sophe and Manity Selgen kebeles. The decline of forest land during this period was resulted expansion of crop land due to high population growth and other population growth related factors.

Table 4.10: Land use/Land cover change during 2000-2016

Persistence Gains Losses Net Change LULC Ha % Gains % Losses % Ha % Type (ha) (ha) Forestland 1273.6 51.0 538.0 10.35 -1224.3 -23.5 -686.3 -13.2 Shrub land 1435.8 56.3 3338.1 64.2 -1115.1 -21.4 2223.0 42.8 Grassland 396.9 32.8 1516.0 29.16 -814.6 -15.7 701.4 13.5 Bare land 706.2 18.5 537.9 10.35 -3102.8 -59.7 -2564.9 -49.3 Cropland 3128.4 86.6 811.4 15.6 -484.6 -9.3 326.8 6.3 Total 6940.9 50.73 6741.4 129.7 -6741.4 -130 0.0 0.0 Source: Computed from land sat images of 2000 and 2006

Cropland

Bareland

Gains (ha) Grassland Losses (ha) Shrubland

Forestland

-4000.0 -2000.0 0.0 2000.0 4000.0

Land use/Land cover Change (Hectare) 2000 - 2016

Figure 4.3: LULC change in hectare between 2000-2016(Source: Computed from land sat images of 2000and 2006)

In the second period (2000 – 2016), which indicated in the table 4.10, more than 50% of forestland, shrub land and cropland were not in the dynamics, that is, not changed to any other land us/land cover category. Whereas as it was about 396 hectare(33%) of grassland and about 706 hectare (19%) of bare land which were unchanged to any other land use/land cover categories. Though to a varied extent, the net change on forestland and bare land was negative and the net change on shrub land, grassland and cropland was positive. While the highest net decline was happened on bare land the highest net

54 increase was on shrub land. About 686 hectare of forest land was changed into shrub land, crop land, grass land and bare land between 2000 and 2016.

Table 4.11: Land use/Land cover change during 1986 – 2016

Persistence Gains Losses Net Change LULC Type Ha % Gains % Losses % Ha % (ha) (ha) Forestland 1050.8 29.8 760.8 14.63 -2478.0 -47.7 -1717.2 -33.0 Shrub land 858.6 49.8 3915.3 75.3 -864.4 -16.6 3050.9 58.7 Grassland 202.7 31.0 1710.2 32.89 -451.9 -8.7 1258.3 24.2 Bare land 696.1 13.9 548.1 10.54 -4323.0 -83.1 -3774.9 -72.6 Cropland 2429.0 88.1 1510.7 29.06 -327.9 -6.3 1182.9 22.7 Total 5237 38.28 8445 162.4 -8445.1 -162 0.0 0.0 Source: Computed from land sat images of 1986 and 2016

Cropland

Bareland

Gains (ha) Grassland Losses (ha) Shrubland

Forestland

-6000.0 -4000.0 -2000.0 0.0 2000.0 4000.0

Figure 4.4 LULC change between 1986 and 2016 (Source: Constructed based on land sat images of 1986, 2000 and 2006)

Summarized the land use/land cover dynamics in the last 30 years, which indicated in the table 4.11, all of the land use/land cover categories were in the dynamics. The net change of forestland and bare land was negative (about -1717 hectares and -3774 hectares respectively). Whereas the net change in the other land use categories was positive. The

55 decline of forest land and bare land could be associated to the activities like deforestation and conversion of bare land of the ever increasing population of the area. The increase of scrubland and grassland could be due to human activities but also due to changes that happens beyond the control of the local people. The change of forest to grass or the shrub to grass, the infestation of the area by weed like grasses and harvesting of large amount of wood for fuel and house construction from forest land.

From the above analysis the researcher concludes that large amount of forest land was cleared between 1986 and 2016. But the size of cultivated land, grass land and shrub land had been increased. This indicates that there is high rate of deforestation in the study area which results high population growth of the study area.

4.3 Causes of Deforestation in the study area

There are different causes of deforestation in the study area. As the data gathered from the study area by different techniques the main cause of deforestation in the study area are sources of energy, overgrazing, expansion of cultivated land, high population growth, low level of education etc. 1. Extraction of Fuel Wood and Charcoal: Most of household heads of the study area are depend on fuel wood and charcoal. According to household head survey the main source of energy for 220(98.4%) respondent is fuel energy and charcoal. And the remaining 4(1.6%) respondents are getting energy from solar energy, petroleum and hydro electric power. From focus group discussion the researcher understands that the main source of fuel wood and charcoal is natural forests because of there is no enough planted trees to satisfy the demand of energy. The demand of fuel wood and charcoal has been increasing due to change of population size of the study area. This leads to clearing forest to get fuel wood and charcoal. But as one elder said that most of rural household heads are get energy from fuel wood. They sell charcoal for urban residence. And also most of time urban residences are get fuel wood from forests of Demebely Sophe and Mainty Selgen kebeles by travelling up to one o‟clock. The overall result of data indicates that extraction of fuel wood and charcoal is one of the main causes of deforestation in the study area.

2. Over Grazing: The main way of life people in the study area is agriculture which includes crop cultivation and livestock breading. Crop cultivation is the mainly way of life peoples of the study area. The second main primary economic activity in which peoples of the study area are engaging their life is animal rearing. The dominant livestock which rearing in the study area are cattle which shares more 90% of livestock size of the study area (Meko woreda agriculture and rural development, 2015). According to household survey the mean of livestock (cattle) size of household heads during 2005 was 5 but the mean of livestock size for household heads was raised into 11 in 2016. There are different sources of grazing for livestock of household heads in the study area. According to household survey, the main source of grazing land for livestock of household heads describe in terms of the following pie chart.

Figure 4.5 source of grazing land for household head‟s livestock (source: constructed based on household heads survey at 2017) Figure 4.5 represents the dominant source of grazing land for 102 (45.5%) respondent‟s livestock is public forest land. And about 43 (19.2%), 41 ( 18.3%) and 36 (16.1%) of respondent‟s are getting grazing land for their livestock from private grass land, both public forest land and grass land and public grass land respectively. According to focus group discussion and interviewed with kebele managers, most of household heads are getting grazing land from natural forests in permanently and the natural forests are greatly affected by overgrazing. When the live stock size of household heads has been increasing from time to time, pressure on the forest land has been increasing. And the content of forest size in study area has been declining due to overgrazing with other

57 factors. So, one of the main causes of deforestation in the study area is over grazing which resulted to increase the number of livestock of the household heads. 3. Expansion of Agricultural Land: The population size of the study area has been increasing from time to time. This leads to increase the demand of some resources such as agricultural land, water, energy, etc. In LULC analysis we understand that the size of forest land trends to decline but the size of crop land trends to increase. According to household survey the mean of land holding size for household heads was 2.3 hectare in 2005 and rise up into 2.82 hectare in 2016. This indicates the land holding size of house hold heads has been increasing. There are different sources of additional agricultural land for household heads of the study area. As the researcher interviewed with kebele mangers, elders and natural resource management expert of Meko woreda, one of the main causes of deforestation is clearing of forest to get additional cultivated land (expansion of agricultural land). Table 4.12: Source of additional land for household heads between 2005 and 2016 Source of additional land Frequency Percent Inheritance 20 8.9 Contract 15 6.7 clearing forest 101 45.1 Government 1 0.4 both inheritance and 22 9.8 by clearing forest None 65 29.0 Total 224 100.0 Source: household head survey at 2017 According to household heads survey which indicated in the table 4.12 the main source of additional agricultural land in hectare between 2005 and 2016 was clearing forest for 101 respondents, contract for 15 respondents, government for one respondent and both inheritance and clearing forest for 22 respondents. Only 65 respondent‟s cultivated land was stagnant between 2005 and 2016. This indicates that most of household heads which were added their agricultural land between 2005 and 2016 was derived from clearing forest land. According LULC analysis, about 727 hectare between1986-2000 and 212

58 hectare between 2000 and 2016 forest land was cleared for crop land. So due to expansion of crop land large amount forest land has been clearing in the study area. According to natural resource expert of Meko Worda, most of time agriculture land which derived through clearing forest is not productive for long period of time due to this some household heads of the study area follow shifting agriculture by clearing forest. This is one of the causes of deforestation in the study area. 4. Clearing Forest to Get Cash Income: forest is one of the major sources cash incomes for peoples of the study area. When the researcher interviewed with elders the researcher understand that some peoples who have not enough land and livestock to engaging their life, they gets cash income by selling charcoal, fuel wood, timber and other forest products. Every morning time of Saturday and Wednesday we can observe large numbers of household heads those sell charcoal, fuel wood and timbers for urban residences and get cash income. Data gathered through household survey is support the above idea. As in the table 4.13 indicated that out 224 respondents the dominant source of cash income for 61 (27.2%) household head‟s are derived from selling forest product, 78 (34.8%) of respondents are get from selling crop product and 83 (37.1%) respondents are get cash income from selling livestock. According to household head survey, household heads those getting cash income from selling forest product are got 800 up to 10,000 ETB per year. Table 4.13: Source of the dominant cash income for household heads of the study area Source of cash income Frequency Percent selling crops 78 34.8 selling livestock 83 37.1 Selling forest products 61 27.2 Total 222 99.1 Source: household head survey at 2017 According to natural resource expert of Meko worda, due to lack of coordination between government and local communities until large amount of forest are clear by illegal timber extractor. Based on the above stated data, the researcher concludes that cutting of trees by household head to get cash income is contributed to decline forest coverage in the study area.

5. House Construction: There are different sources of raw material for house construction like metal, wood, cement etc. The dominant source of house construction in both rural and urban kebele’s household heads in the study area are wood and mud. According to household survey almost all respondent‟s the dominant source of raw material house construction is wood. According to one kebele manager, most household heads in the study area are prefers natural forest wood than planted forest wood in aspect of strength like woyira and Tikur Enchet. Due to this hard wood trees are clearing for house construction in different time. According to 70 years old elder, during 1980s large amount of hard trees were cleared by in-migrants for wood to house construction and get land to made house. So house construction is one of the main causes of deforestation in the study area.

6. Low level of Education and Training about Forest: education and training are bases for resource conservation. But according to household head survey, 60% of respondents have not got any training about forest between 2005 and 2016. And 50% of household heads are uneducated (0-class). According to natural resource expert of Meko woreda, due to lack of education farmers of Meko woreda till large amount of crop land without use modern inputs of agriculture. Due to this most of house hold heads of the study area are prefer expanding agricultural land by clearing forest rather than application of modern inputs like fertilizer to increase their agriculture product. The researcher concludes that most of household heads have not know-how about impacts of deforestation and method of forest conservation and they clear forest by considering the short run advantages.

7. Resettlement Program: Migration is the movement of people from their residential place into another place due to ecological, political, social and economical reasons. Due to ecological problem peoples of northern and eastern part of Ethiopia were traveled in southwestern Ethiopia through resettlement program. Most of time resettles are settled in the forest land and they clear forests for different land use purpose like to house construction and to get agricultural land. The study area is known by resettlement programs in different times. The well known resettlement program was conducted in 1985 by Derge regime from Wello and Harerghe zone (Meko agriculture and rural development, 2015).

Table 4.14: Mean clearing forest between 2005 and 2016 by in-migrants and native household heads

Residential Mean clearing forest in N Std. status HHH hectare between 2005 & Deviation 2016 In- migrant 1.0238 63 0.81036 Native peoples 0.4494 161 0.58060 Total 0.6109 224 0.70103 Sources: Household heads survey at 2017 According to household survey, which indicated that in the table 4.14, about 63 respondents are in-migrants and 163 respondents are native peoples. From focus group discussion the researcher understand that most of in-migrants are clear forest carelessly. As in the table 4.14 indicated that in-migrants were clear forest for different land uses between 2005 and 2016 more than native household heads in the study area. That means mean clearing forest size in hectare between 2005 and 2016 by in-migrant respondents (1.023hectare) was greater than mean clearing forest size by native peoples (0.4494ha). Based on the above results the researcher concludes that resettlement program is one of the main causes of deforestation in the study area. 8. Low Level of Family Planning and High Population Growth: as the researcher interviewed with Meko worda health office administer, the stage of using family planning still now is poor in the study area. Due to lack education, most of rural household heads counts their children as asset. Due to this, the population of the study area has been growing alarmingly. The population size of Dembely Sophe and Mainty Selgen kebeles were 2500 in 2010, 2800 in 2011,3300 in 2012, 3673 in 2013, 4260 in 2014, 4561 in 2015 and 4983 ( Oromia urban planning institute western branch, 2017).This indicates the population number of the study area has been increasing. More population needs more resources to satisfy their basic needs and wants. According to household head survey, 182 respondents are believed that high population growth is the main cause of deforestation in the study area. According to natural resources expert, the first and the basic causes of deforestation in the study area is high population growth which resulted low level of family planning and resettlement program. Household size change and

61 clearing forest size in hectare, which indicated in the table 4.28, have moderately positive relationship. The researcher concludes that population growth is the main cause and source of other causes of deforestation in the study area. Due to high population growth in the study area, the demand of fuel wood, wood to construction, additional agricultural land has been increasing from time to time. This leads to increasing deforestation in the study area. 4.4 Consequences of Deforestation in the Study Area There are different consequences of deforestation in the study area. Some of consequences are climate change, soil erosion, decline biodiversity, minimize, agriculture productive etc. 1. Climate Change: large forest can influence regional weather pattern and even create own micro climate. When the forest size is decline, the concentration of CO2 in the atmosphere is increase. And the climate condition the deforested and surrounded area can be changed (FAO, 2010). As stated in the LULC analysis the forest coverage of the study area has been declining, this leads to climate change of the study area. According to household head survey, almost all 219(97.8%) respondents‟ responded that there is a climate change in their locality. As key informant interview with elders, during past time the temperature of the study area was cold but now the temperature has been increasing. And also there was large amount of rainfall during past time but now the amount of rainfall trends to minimizing and the characteristics‟ of seasons has been changed. The data which gets from the national metrological station from Jimma branch and global weather is supports the above idea. The mean annual temperature of the study area was 21oc in 2005 and increased into 22.90c in 2016. And the total annual rainfall of the study area was 2200mm in 2005 and declined into 1990mm in 2016. Based on the above data the researcher conclude that the climate of the study area has been changing due deforestation. Because of when forest coverage had been declined the concentration of CO2 in the atmosphere is increased. 2. Soil Erosion: Trees are highly effective in absorbing water quantities and keeping the amount of water in watershed to a manageable level. The forest also serves as a cover of soil against erosion. When the forest is cleared, the soil is vulnerable to erosion (FAO, 2010). From group discussion the researcher understand that the soil of the study area

62 was fertile, but now the soil especially soils of the steep slope area has been eroded by running water. When the researcher observed the study area, the previous forest area but now deforested is greatly affected by intense soil erosion up to make gorge and cliff. And some part of household head‟s agricultural land is become too bare land. The part of the study area which indicated in the figure 4.6, which captured during observation time, was covered by dense forest before 10 years, but due to expansion of agricultural land which results to high population growth the forest is cleared and the land is greatly affected by intensive running water erosion.

Figure 4.6: Extensive soil erosion in the study area (source, field survey at 2017)

According to interview with elders, the soil of the study area was favorable to grow crops without any fertilizer but now some part of the study area is not effective to crop cultivation without fertilizer. This indicates that decline soil fertility due to erosion. And also the Meko woreda‟s natural resource expert stated that most of agricultural lands which derived through clearing forest are not effective for long run agriculture activity due to it is vulnerable for erosion. 3. Decline Agriculture Productivity: due to climate change and soil erosion which results deforestation, agriculture productivity of the study area is trends to decline. According to household head survey, during 2005 average product of crop per hectare at household level was 8.3quintal but in 2016 it decline into 7.56 quintal. According to

63 natural resources expert of Meko Woreda the soil fertility of the study area has been declining because of soil erosion which resulted decline of forest coverage. This leads to decline agriculture productivity. 4. Loss of Biodiversity: Most of plant and animal species are exist in the forest land. When forest land is cleared wild animals and plant sizes are minimized. According to household head survey, about 17 respondents responded that biodiversity in their locality trends to increasing, 14 respondent‟s response were constant and 187 respondents were responded that biodiversity in their locality trends to minimizing. According to household head survey, the biodiversity situation of the study area is trends to minimize due to deforestation. From focus group discussion the researcher understand that the same to household heads survey. According to interviewed with one elder, some plants like tide, Tikur enchet and woyira were existed during past time but now they trends to extinct in the study area for house construction. And also some wildlife like lion and cheetah are extinct in the study area due to minimizing of forest coverage. As interviewed with one kebele manager, the study area was the habitat of different wild life but now due to deforestation most of wild life are leave out from the study area to neighboring woredas. According to field observation, large amount of tree species are destroyed in everyday for charcoal, house construction and fuel wood etc. During evening time of winter season the researcher observed large amount of forest land are clearing by using fire to expansion agricultural land. As that time large amount of plant and animal life are died. So the researcher concludes that the amount of biodiversity in the study area has been diminishing due to high rate of deforestation. 4.5 Forest Conservation Mechanisms in the Study Area There are different forest conservation mechanisms which applied in over the entire world. Some of forest conservation mechanisms are reforestation, afforestation, agro- forestry, training household heads about forest, conducting research about forest, family planning, etc. let us see the forest conservation mechanisms condition of the study area. 1. Reforestation, afforestation and agro forestry: reforestation and afforestation are the main ways of forest conservation techniques. According to household survey, about 152 respondents responded that there is no afforestation and reforestation program in their locality. The remaining 72 respondents responded that there is reforestation and

64 afforestation in the study area. Even there is some afforestion and reforestation practice but household heads cannot manage planted tree. According to one elder, most of peoples in the study area prefer clearing forest rather than planting forest. According to 65 years old elder, there were reforestation and afforestation during Derg regime but planted trees during Derg regime are cleared for source of income of the present government and local communities. During field observation the researcher has not seen any recently reforested and afforested area. But in some area the researcher observed reforested and afforested area which planted during Ethiopian millennium and the Derg government. The dominant planted tree which planted in the study area is eucalyptus. And also according to household survey, only 20(8.9%) household heads are exercise agro-forestry in their crop land. And 114(91.1%) respondents responded that their no agro forestry practice in their crop land. According to Meko woreda natural resources expert, some peoples have been planting some garden like coffee, banana and mango which used for economy and environmental protection. But it is not enough when compare to the potential of land. Based on the collected data by household heads survey, field observation and interviewed with kebele manager; the researcher concludes that there is no enough reforestation, afforestation and agro-forestry practices in the study area when we compare the rate of deforestation. 2. Participation of local communities in the forest conservation. Local community participation is necessary to conserve and rehabilitee forest resources. But according to Meko woreda natural resource expert, elders and kebele managers, it is so difficult to say there is local community participation in the forest conservation practice in the study area. Household head‟s survey is supports interviewed with kebele managers; natural resource expert and elder‟s idea. According to household head survey, 130 respondents are poor participant in forest conservation; 81 respondents are medium participant and 13 respondents are strong participant in the forest conservation. This indicates most of local communities are poor participants in forest conservation in the study area. According to Meko woreda natural resource expert, there was relatively medium community participation during the beginning of Ethiopian millennium otherwise the community participation to plant trees and managing forest is poor in the study area. The overall idea indicates that there is poor

65 community participation in the forest conservation program in the study area because of most of household head have not got any training about forest and uneducated. 3. Area enclosure: area enclosure is one of the forest conservation mechanisms in the most deforested area. But according to household head survey and interviewed with elders, there is no so much protected forest area from animal and human contact in the study area . According to natural resource expert of Meko woreda, protect forest resource from human and animal contact is the better conservation mechanism of forest resources and wild life but it needs a long period of time to applied in the study area because of forest resource is one of the main source of grazing land and the main source of energy. As the researcher observed the study area forest land are vulnerable for destruction due to day to day interaction with human and animal life. According to household survey, about 31(13 %) of the respondent responded that there is enclosure area in their locality and 192(85.7%) household heads responded that there is no protected forest area from animal and human contact. Based on the household head survey, focus group discussion and interview, the researcher concluded that there is no enough protected forest area from domestic animal and human contact in the study area. 4. Good government action to forest management: is one of the minimize techniques of deforestation. As a policy Ethiopia formulated environmental policy to protect natural resources from different human activities. But according to Meko woreda natural resource management expert and kebele managers, the implication of environmental policy is not effective in the study area. As the researcher observed the study area and understands from group discussion still now there is high rate of deforestation and the government action to protect forest resource is not tangible. According to household head survey, about105 (46.9%) of the respondents responded that the government action to protect forest resource is poor in their locality, about 102 (45.5%) of the respondents responded that the government action is medium. The remaining 17 (7.6%) respondents were responded that the government action towards protecting forest resources is strong. Additionally, as one kebele manager and natural resource expert stated that during interviewed with them the natural resources management office cannot motivate experts

66 to conduct research relating to forest resources. Due to this, there is no research conducted towards forest resource in the study area. And also one kebele manager stated that there is no enough training which given to household heads to conserve forest resources. As natural resources expert of Meko woreda stated the government must give training for household heads in every time, but due lack of human resources until most of peoples could not get any training. The only NGO which supported to give training in 2015 and 2016 was REDD. This training was facilitated by Meko woreda administers office and natural resource management office. But it includes only some household heads. Generally good government action is necessary to give training, managing the existing forest, facilitating afforestation and reforestation. The researcher conclude that the government action to give training about forest, to take punishment peoples those clear forest for different purpose, in forest conservation mechanism, implication of the environmental policy, etc is poor in the study area which resulted due lack of trained manpower. 4.6 Part of inferential Statistical analysis 1. T-test Analysis A. T-test Analysis to Compare Mean of Clearing Forest in Hectare between 2005 and 2016 in Two kebeles at Household Head Level H0: The mean of clearing forest size in hectare in Dembely sophe and Mainty selgen kebele at household head level are equal ( ).

H1: The mean of clearing forest size in hectare in Dembely sophe and Mainty selgen kebele at household head level are not equal ( ).

Table 4.15: Mean of Clearing Forest size in Hectare at Household Head Level in Dembely Sophe and Mainty selgen kebeles

Household head's N Mean Std. Std. Error kebele Deviation Mean clearing forest size Dembely Sophe 143 0.696 0.68953 0.05768 at household head Mainty selgen 81 0.459 0.69984 0.0776 level

Source: Household heads survey at 2017 As in the table 4.15 indicated, the mean of clearing forest size in hectare at household head level between 2005 and 2016 for different land uses were 0.6965 and 0.4599 of Dembely sophe and Mainty selgen kebele with standard deviation 0.68953 and 0.69984 are respectively. Table 4.16: t- test for Equality of Means of Clearing Forest in Hectare between 2005 and 2016 at Household Head level of Dembely Sophe and Mainty selgen kebele.

Levene's Test for t-test for Equality of Means Equality of Variances F Sig. T Df Sig. (2- Mean Std. Error 95% Confidence tailed) Difference Difference Interval of the Difference Lower Upper Equal clearing variances 0.895 0.345 2.454 222 0.015 0.23663 0.09641 0.4664 0.42662 forest size assumed

Source: SPSS output of household survey at 2017 Table 4.16 indicates, there is a significance evidence to reject null hypothesis of the mean of clearing forest size in hectare at household head level in Dembely sophe and Mainty selgen kebele are equal and accept alternative hypothesis. There is statistically significant different the mean of clearing forest size at household head level of two kebele at 5% level of significant (p-value = 0.015 < 0.05). Or when t-calculate is greater than t-tabulate

H0 is rejected (0.345>0.015). So household heads in Dembely Sophe were clear more forest land in hectare for different land use between 2005 and 2016 than household heads in Manity Selgen Kebele. During field observation the researcher understand that the rate of deforestation is higher in Dembely sophe than Manity selgen. According to meko woreda agriculture and rural development (2015), Dembely sophe is known by about 200 household head in-migrant and high rate of natural increase. This is the main causes of deforestion is higher in Dembely sophe than Manity Selgen kebele.

B. T-test Analysis to Compare Mean of Clearing Forest in Hectare between 2005 and 2016 in Male and Female Household Heads

H0: The mean of clearing forest size in between 2005 and 2016 at male and female of household head level are equal ( ).

H1: The mean of clearing forest size between 2005 and 2016 at male and female household heads level are not equal ( ).

Table 4.17: Mean and Standard deviation clearing forest by Two Gender

Sex of house hold N Mean Std. Deviation head

Clearing forest Female 24 0.6071 0.78595 size at household head level Male 200 0.6115 0.69027 Source: SPSS output of household heads survey

The mean of clearing forest size at household head level between 2005 and 2016 for different land uses which indicated in the table 4.17 were 0.6071 hectare and 0.6115 hectare of male and female of household head with 0.78595 and 0.69027 standard deviation are respectively

Table 4.18: independent Samples t- test of clearing forest size in hectare at household heads level in gender Source: SPSS out of household survey at 2017

Table 4.18 indicates at the 5% level of significance, there is no enough evidence to conclude that the mean of clearing forest size between 2005 and 2016 at household head

Levene's Test t-test for Equality of Means for Equality of Variances F Sig. T Df Sig. Mean Std. Error 95% Confidence Interval of the (2- Differen Differenc Difference tailed ce e Lower Upper ) Equal Clearing variances 0.163 0.687 -0.031 222 0.976 -0.00434 0.14195 -0.28407 0.27540 forest assumed size level of male and female household heads are the different ( p-value= 0.687 > 0.05) due to this H0 is accepted. From this test we can understand that sex is not a factor for the clearing forest in hectare at household head level in the study area.

2. One way ANOVA

In this research mean clearing forest size in hectare between 2005 and 2016 at household head level in different marital status, education status and age group were compared by using one way ANOVA.

A. One –way ANOVA of Clearing Forest Size at Household Head Level in Different Marital status

One way ANOVA of clearing forest at household head level indifferent marital status can express in the following mechanisms. Table 4.19 indicated that the mean clearing forest size in hectare between 2005 and 2016 for different land use by married, unmarried, divorced, widower or widow household

70 heads were 0.714, 0.1458, 0.4167 and 0.2 hectare respectively. The maximum and minimum clearing forest size by married household head was 0 and 3 hectare, by unmarried was 0 and 0.5 hectare, by divorced was 0 and 1and by widower or widowed was 0 and 1.5 respectively. Table 4.19: Descriptive statistics of clearing forest size at household head level in different marital status

Marital status N Mean Std. Minimu Maximum Deviatio m n Married 175 0.7149 0.73287 0.00 3.00 Unmarried 12 0.1458 0.22508 0.00 0.50 Divorced 12 0.4167 0.46872 0.00 1.00

widower or 25 0.2000 0.40825 0.00 1.50 widowed

Total 224 0.6109 0.70103 0.00 3.00

Source: SPSS output of household head survey at 2017 Table 4.20: ANOVA

Sum of Squares Df Mean Square F Sig.

Between Groups 9.160 3 3.053 6.689 0.000 Within Groups 100.430 220 0.457 Total 109.591 223

Source: computed based on household survey 2017 From the table 4.20, we understand that there is a significance difference of mean clearing forest between household heads due to marital status difference because of p- value=0.000<0.05 at two tailed significance level. We can enter post Hoch-test to multiple comparisons clearing forest size between different marital statuses of the respondent

Table 4.21 Post Hoc Tests: Multiple Comparisons of clearing forest size at household level of marital status Dependent Variable: clearing forest size in hectare at household level between 2005and 2016 for different land uses (I) Marital status (J) Marital status of Mean Std. Error Sig. 95% Confidence Interval Difference HHH HHH Lower Bound Upper (I-J) Bound Unmarried 0.56902* 0.20162 0.005 0.1717 0.9664 Married Divorced 0.29819 0.20162 0.141 -0.0992 0.6955 widower or widowed 0.51486* 0.14446 0.000 0.2302 0.7996 Married -0.56902* 0.20162 0.005 -0.9664 -0.1717

Unmarried Divorced -0.27083 0.27583 0.327 -0.8144 0.2728 widower or widowed -0.05417 0.23728 0.820 -0.5218 0.4135 Married -0.29819 0.20162 0.141 -0.6955 0.0992 Divorced Unmarried 0.27083 0.27583 0.327 -0.2728 0.8144 Widower or widowed 0.21667 0.23728 0.362 -0.2510 0.6843 Married -0.51486* 0.14446 0.000 -0.7996 -0.2302 widower or Unmarried 0.05417 0.23728 0.820 -0.4135 0.5218 widowed Divorced -0.21667 0.23728 0.362 -0.6843 0.2510 *. The mean difference is significant at the 0.05 level Source: SPSS output of household head survey at 2017 A one-way between groups analysis of variance is conducted to explore the effect of marital status on clearing forest size at household head level. Participants are divided into four groups according to their marital status (Married; Unmarried; Divorced; and widower or widowed). There is a statistically significant difference at the p < 0.000 level in clearing forest size at household level for four marital status groups F (3, 220) = 6.689, p < 0.000. Post-hoc comparisons using the LSD test indicated that the mean of clearing forest size in hectare between 2005 and 2016 for married household heads (Mean = 0.7149, SD = 0.73287) is significantly different from unmarried household heads (Mean = 0.1458, SD = 0.22508) and widower or widowed household heads (Mean = 0.2000, SD = 0.40825). There is no statistically significant difference in mean clearing forest size between unmarried household head and divorced household head (p=0.327>0.05). And

72 also, there is no statistically significant difference in mean of clearing forest size in hectare between 2005 and 2016 between unmarried household head and widower or widowed household head (P-value=0.82>0.05). The researcher concludes that married household head are clear more forest land in hectare to different land use than other household head to satisfy the increasing demand of land and forest resources which results of high household size growth in the study area. The main reason is the household size of married household head is relatively dynamic than other marital status. Due to change of household size married household heads are need more agricultural land and clear more forest land.

B. One- ways of Analysis of variance of clearing forest size at household head level in different age group

A one-way between groups analysis of variance was conducted to explore the effect of age on clearing forest size at household heads level. Participants are divided into three groups according to age (age<30, between 30 and 50 age group and above 50 years old).

Table 4.22: descriptive statistics of clearing forest size in hectare between 2005 and 2016 at household head level at different age group

Age of household head Mean N Std. Deviation Low level 0.2310 21 0.40015 30-50 0.7759 145 0.71427 High level 0.3362 58 0.61514 Total 0.6109 224 0.70103 Source: household heads survey at 2017 The mean clearing forest size of the respondent between 2005 and 2016 in hectare which indicated the table 4.22 at age below 30, between 30 and 50, and above 50 years old household heads were 0.231hectare, 0.776 hectare and 0.336 hectare at standard deviation of 0.40015, 0.71427 and 0.61514 respectively. Less variability recorded in household heads whose age under 30 years old.

Table 4.23: ANOVA Sum of Squares Df Mean Square F Sig.

Between Groups 11.354 2 5.677 12.771 0.000

Within Groups 98.237 221 0.445

Total 109.591 223

Source: household head survey at 2017 As in the table 4.23 indicated that p-value is 0.000 which less than 0.05. This indicated that there was a significance difference of mean clearing forest in hectare due to variation of age. So we can analyze by using post hoc test to multiple comparison mean clearing forest in hectare between 2005 and 2016 at household head level in different age group. Table 4.24: Post Hoc Tests: Multiple Comparisons of clearing forest size at household level of different age group. Dependent Variable: clearing forest size in hectare at household head level between 2005 and 2016 for different land uses LSD

(I) age of house hold head (J) age of house Mean Std. Sig. 95% Confidence hold head Difference Error Interval (I-J) Lower Upper Bound Bound 30-50 -0.54491* 0.15567 0.001 -0.8517 -0.2381 Low level High level -0.10525 0.16980 0.536 -0.4399 0.2294 Low level 0.54491* 0.15567 0.001 0.2381 0.8517 30-50 High level 0.43966* 0.10358 0.000 0.2355 0.6438 Low level 0.10525 0.16980 0.536 -0.2294 0.4399 High level 30-50 -0.43966* 0.10358 0.000 0-.6438 -0.2355 *. The mean difference is significant at the 0.05 level. Source : household head survey at 2017 Post-hoc comparisons using the LSD test indicated table 4.24 the mean of clearing forest size in hectare at household head level between 2005 and 2016 for age group of between 30 and 50 years old (Mean = 0.7759, SD = 0.71425) is significantly different from age group below 30 years old (Mean = 0.231, SD = 0.40015) at p-value =0.001 and high level

74 age group (Mean = 0.3362, SD = 0.61514) at p-value=0.000. There is no statistically significant difference in mean of clearing forest size in hectare at household head level between 2005 and 2016 between age group of low level age group and high level age group at p-value=0.536 which greater than 0.05. So household heads those ages under grouped between 30 and 50 years old are clear more forest than household heads whose age under grouped below 30 and above 50 years old. This age group is known is known by large number of house hold size because of they are exist in the most reproductive age group. And most of household heads which less than 30 year years old are relatively educated than household heads whose ages are between 30 and 50. And also household heads whose age is above 50 are less powerful to clear forest land than others. Due to these factors household heads whose age is between 30 and 50 are clear more forest to expansion agricultural land and to satisfy other needs and wants. C. One- ways of ANOVA of clearing forest size at household head level in different education status

Table 4.25: Descriptive statistics of clearing forest size in hectare at household head level in different education status

ESHH Mean N Std. Deviation 0 0.8874 111 0.76183 1-8 0.3738 101 0.52515 ≥9 0.0500 12 0.14460 Total 0.6109 224 0.70103

Source: house hold head survey at 2017 Table 4.25 indicates that the mean clearing forest size in hectare between 2005 and 2016 at household heave level in the education level of 0-calss, 1-8 and above 9 grade levels were 0.887 hectare, 0.373 hectare and 0.05 hectare at standard deviation of 0.76183, 0.525 and 0.1446 respectively. We can check whether statistical significance difference of mean clearing forest size among household heads due to difference of education status or not by using ANOVA test.

Table 4.26 ANOVA test Dependent variable: Clearing forest size in hectare at household level between 2005 and 2016 for different land uses

Sum of Df Mean F Sig. Squares Square Between Groups 17.940 2 8.970 21.63 0.000 Within Groups 91.650 221 0.415 Total 109.591 223 Source: household head survey at 2017 ANOVA test in the table 4.26 indicates, there is a significance mean difference of clearing forest size in hectare between 2005 and 2016 among household heads due to variation of education status. Because of p-value =0.000 is less than 0.05 at two-tailed significance level. Table 4.27: Post Hoc Tests: Multiple Comparisons of clearing forest size at household level of different age group Dependent Variable: clearing forest size in hectare at household head level between 2005 and 2016 for different land uses LSD

(I) (J) Mean Std. Error Sig. 95% Confidence ESH ESHH Difference (I- Interval H J) Lower Upper Bound Bound 1-8 0.51363* 0.08856 0.000 0.3391 0.6881 0 ≥ 9 0.83739* 0.19569 0.000 0.4517 1.2230 0 -0.51363* 0.08856 0.000 -0.6881 -0.3391 1-8 ≥9 0.32376 0.19663 0.101 -0.0638 0.7113 0 -0.83739* 0.19569 0.000 -1.2230 -0.4517 ≥9 1-8 -0.32376 0.19663 0.101 -0.7113 0.0638 *. The mean difference is significant at the 0.05 level. Source: household head survey at 2017 Post-hoc comparisons using the LSD test which displayed in the table 4.27 indicated that the mean clearing forest size at household head of education status 0-class (Mean = 0.887, SD = 0.762) is significantly different from education status of households at elementary school level (Mean = 0.374, SD = 0.525) at p- value of 0.000 and education

76 status of households at 9 and above school level (Mean = 0.051, SD = 0.61514) at p- value of 0.000. There is no statistically significant difference in mean clearing forest size in hectare between household heads at elementary school education level and household heads at secondary and above education level at p-value=0.101. Household heads whose education status is uneducated are clear more forest than other household heads in the study area. Generally, the mean clearing forest size in hectare in the study area by household heads is decline when the education status of household heads is increase because educated household heads have more Know-how about advantages of forest and forest conservation mechanism than uneducated household heads. 3. Correlation analysis In this part the relationship between house hold size change between 2005 and 2016, clearing forest size in hectare at household head level between 2005 And 2016 , the change of agriculture product in quintal per hectare between 2005 and 2016, number of time which house hold heads were get training about forest between 2005 and 2016 were analyzed. As in the table 4.28 indicated that Pearson correlation for the clearing forest size in hectare at household head level between 2005 and 2016 for different land uses with change of agriculture product in quintal per hectare between 2005 and 2016 at household level (r= -0.493) and Number of times which household heads have got training about forest conservation between 2005 and 2016 (r= -0.384) show moderately negative an weak negative relationship respectively. Pearson correlation for the clearing forest size in hectare at household head level between 2005 and 2016 for different land uses with household size change between 2005 and 2016 at household head level(r=0.501) show a moderate positive relationship. The relationship between the clearing forest size in hectare at household head level with change of agriculture product in quintal per hectare at household level and number of times which household heads have got training about forest conservation is negative or indirect relationship which means as value of one variable increase the value of the other variable is decrease. The clearing forest size at household level is positive relationship with household size change which means when household size change is decrease the amount clearing forest size at household level is decrease. The researcher conclude that population growth and deforestation have positive

77 relationship. The results indicates that the three variables are statistically significant at 5% level of two-tailed significant (p- value <0.05). The above correlation indicated that household size changes, low level of training about forest conservation for household heads are the causes of deforestation in the study area. And also decline agriculture productivity is one of the consequences of deforestation in the study area. Table 4.28: Correlation Matrix

clearing forest change of agriculture Number of times household size size in hectare product in quintal per which HHH have got change at HHH at HHH level hectare training level

clearing forest Pearson Correlation 1 size in hectare Sig. (2-tailed) at HHH level N 224 change of ** Pearson Correlation - 0.493 1 agriculture Sig. (2-tailed) 0.000 product in quintal per ha N 214 214

Number of ** ** Pearson Correlation -0.384 0.324 1 times which Sig. (2-tailed) 0.000 0.000 HHH have got training N 224 214 224

Pearson Correlation 0.501** -0.234** -0.315** 1 household size change at HHH Sig. (2-tailed) 0.000 0.001 0.000 level N 223 213 223 223

**correlation is significant at the 0.05 level.

Source: household head survey at 2017

CHAPTER FIVE: CONCLUSION AND RECOMMENDATIONS

5.1 Conclusion

By using primary data which gathered through questionnaire, interview, focus group discussion, field observation and satellite imageries from household heads, kebele managers, natural resource management office expert, field and satellite images and also secondary sources the researcher conclude the results in terms of the following way.

In 1986, 2000 and 2016 the study area covered by forest was about 26%, 18% and 13% of the area respectively. Unlike this the areal extent of shrub land has been increasing from 13% in 1986, 19% in 2000, and 35% in 2016. The area covered by the grass land was about 5% in 1986 and has almost doubled to be 9% in 2000 and this in turn has increased to be 14% in 2016. The reason for the increase of grassland and shrub land to such extent which understand from field observation could be associated with the infestation of the north eastern by a weed like elephant grass which in turn due to the changing climate in the area and increasing human activities like expansion of agricultural land, cutting of wood plant for fuel wood consumption and over grazing. The areal extent of cropland has been increasing in the first decade and second decade. The areal extent of cropland in 1986 was only about 2757 hectares (20%) of the selected kebeles. But this extent has increased into become 3613 hectares (~26%) in 2000 and by 1300 hectare to become 3940 hectares (~29%) in 2016. Forest resource of the study area is exposed to high rate of deforestation which is caused by different factors. The main cause of deforestation in the study area are expansion of cultivated land, poor forest management, low participation of local communities towards forest management, over grazing in the forest land, poor afforestion and reforestation practice of local communities, low level of accessibility of training about forest for house hold heads, resettlement and high population growth. The correlation coefficient between clearing forest size in hectare and household size change between 2005 and 2016 is 0.51 at two tailed sig < 0.05. This indicates household size change and deforestation have moderately positive relationship.

Due to high deforestation rate in the study area some ecological and economical effects have been observed in the study area within ten years. Some consequence of deforestation which have been observed in the study area are decline soil fertility, increasing temperature, declining annual rainfall, decline agricultural product, minimizing amount of biodiversity and extinct of some tree species.

Household heads in Dembely Sophe were cleared more forest than household heads in Mainty Selgen kebele between 2005 and 2016 because of high concentration of in - migrants. Sex difference is not factor for clearing forest size for different land uses in the study area. There is a significance difference of clearing forest among household heads due to difference of marital status. Married household heads are clear more forest than other household heads because the house hold size of married household heads has been increasing from time to time and they needs large amount of agricultural land. Household heads whose age are between 30 and 50 years old are clear more forest land for agricultural land than household heads whose age are above 50 and below 30 years old.

There is no effective forest resources conservation mechanism in the study area. There is no enough non-governmental organization involved in the conservation of forest resources in the study area. The participation of local community to protect forest resource is poor. The government action to protect forest resource in the study area is weak.

5.2 Recommendations

Based on the finding of the study, the following recommendation points are forwarded to minimize the rate of deforestation

1. Since forest resource is the lung of the people, Meko woreda natural management office should give more attention about forest resource of the study area. And should motivate and invite researcher (experts) who wants to study about deforestation.

2. To minimize deforestation which results due to resettlement program the federal government should give attention where migrant peoples are resettling through resettlement program.

3. The Meko woreda health offices should create awareness about advantages different family planning mechanisms for rural household heads to minimize the population growth and provide different family planning techniques for household heads to balance population growth with the carrying capacity of environment.

4. The Meko worda micro and small enterprise, natural resource management and mineral and energy offices should create other job opportunities for peoples who engaged their life by selling forest product like charcoal, fuel wood and timber.

5. The Meko woreda mineral and energy offices must be create awareness about different sources of energy for household heads like solar energy and hydroelectric power and distribute for household heads up to rural area to minimize fuel wood and charcoal consumption.

6. Local communities should participate in different forest conservation mechanism like in afforestation, reforestation and agro-forestry program and also the management of planted trees by considering as their asset.

7. None-governmental organization and private sectors should participate to give training about forest resources management and family planning techniques.

8. Most of household heads are clearing forest to increase their crop product by expansion crop land. So, Meko Woreda agriculture and rural development office must supply modern inputs of agriculture like fertilizer for rural household heads to minimize deforestation by increase productivity of the land.

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Appendixes

Appendix I: questionnaire

Adama Science and Technology University

School of Humanities and law

Department of Geography and Environmental studies

Questionnaire to be filled by household heads

The main purpose of this questionnaire is to gather relevant data to understand the nexus between demographic changes and deforestation in the case of Meko woreda, Buno Bedele zone, southwestern Ethiopia. The response you provide will have a constructive and paramount important for the accomplishment of this study. So you are kindly requested to your genuine response.

Instruction: please circle the choice or fill the blank space of your response

1. Sex ______

2. Age______

3. kebele______

4. Education level______

5. Marital status A. Married

B. Unmarried

C. Divorced

D. Widowed/ widower

6. Household size in 2005______in 2016______

7. Do you believe high population growth is the main cause of deforestation in your locality? A. yes B. no

8. What is your main source of energy? A. Fuel wood and charcoal

B. Electricity

C. Petroleum

D. Solar Energy

9. How many sack of charcoal you use within a year in a household level? ______

10. Livestock size in 2005______In 2016______

11. What is your dominant source of grazing land?

A. Public forestland C. Public forest land and grass land

B. Public grass land D. Private grass land

12. Land holding size in 2005______in 2016______

13. What is the main source of additional agricultural land between 2005 and 2016? A. by inheritance C. by clearing forest B. Contract D. from government 14. How many hectares of forest land you have clearing for different land use from 2005 up to 2016? ______

15. What is your dominant source of cash income? A. Selling crop

B. Selling cattle

C. Selling forest product (charcoal, fuel wood, timber, etc)

16. How many birr you have get by selling forest products within a year at household level? ______

17. What is your most source of raw material for house construction? A. Wood B. Metals C. Cement

18. Are you resettled from other place? A. Yes B. No

19. How long have you stayed in this community? ______

20. Is there a strong forest administration in your locality? A. yes B. no

21. If you have thought other causes of deforestation in your locality, please list them.

______

22. What you observe agriculture productivity in a hectare within the previous ten years?

A, increased B, constant /stagnant C, Decreased

23. How money average quintal of crops you produce from one hectare cultivated land per year in 2005 and 2016? 2005______2016______

24. Do you observe any climate change within ten years? A. yes B. no

25. What you observe the extent of biodiversity in your locality within 10 years? A. Increased B. constant C. minimized

26. If you observe other consequences of deforestation which are not included in the above questions, please them. ______27. Have you got any training/education which regarding forest between 2005 and 2016? A. yes B. no

28. if you say „yes‟ for question 27, how many times you have got training about forest conservation?

29. Is there reforestation and afforestation program in your locality? A. yes B. No

30. Have you seen a research which conducts about forest by any person in your locality? A .yes B. no

31. Are you apply agro-forestry practice in your agricultural land? A. yes B. no

32. What seems like governments action to protect forest resources? A. weak

B. medium C. Strong

33. What seems like your participation to protect forest resources? A. Weak B. Medium C. Strong

34. Is there any protected forest area from animals and human being contact in your locality? A. yes B. no

35. If you observe any forest conservation mechanism which has been applied in your locality, please list them. ______Thank You!!!

Unka Gaafannoo Abbaa Warraan Guutamu Yaada deebii laattotaa, kaayyoon gaaffiiwwan kanaa odeeffannoo yookaan ragaa qo‟annoo fi qorannoo mata-dureen isaa“hariiroo baayinni uummataa dabaluu fi manca‟ina bosonaa akka Aanaa Makko, Godina Buunno Badallee, Bulchiinsa Mootummaa Naannoo Oromiyaatti ta‟a”. Kanaafuu deebii keessan gati-qabeessa ta‟e akka nuuf kennitan kabajaan gaafatamtaniittu. Haaluma kanaan deebiin keessan qo‟annoo barnootaaf malee kaayyoo kan biraaf akka hin taane asumaan akka beektan haa ta‟u. Ajaja:qubee debii keessaniif filattanitti maraa, akkasumas yaada bakka duwwaa kenname irratti barreessuudhaan guutaa. 1. saala ______2. Umrii______3. Ganda______4. Sadarkaa barnootaa______5. Haala fuudhaa fi heerumaa A. kan fuudhe B. Kan hin fuunee C. Kan wal hiike D. Kan abbaan mana lubbuun hin jirree ykn kan haati mana lubbuun hin jiree 6. Baayina maatii Bara 1998______Bara 2009______7. Baayinni nama ganda keesssani dabaluun isaa manca‟uu bosonaatiif sababa jettani yaadduu?A. Eeyyee B. lakki 8. Maddi humna annisaa keessani maalidha? A.Muka /Qoraan fi cilee irraa C. Gaazii uumamaa B. Elektrika irraa D. Ifa Aduu/solaari irraa 9. Akka maatii keessaniitti waggaa tokko keessatti cilee kuntaala meeqa fayyadamtu? 10. Baayina horii Qabdanii Bara 1998______Bara 2009______11. Madda dheedicha horii keessanii maalidha? A.Lafa bosona hawaasa C. Lafa Bosona fi Dheedicha ummataa B. Lafa Dheedicha ummataa D. Lafa Dheedicha dhuunfaa 12. Lafa heektara meeqa qabdu? bara 1998______Bara 2009______13. Maalli lafa qonnaa addaa addaa keessanii ittiin baballifattan Bara 1998 hanga 2009tti argamee maalidha?

A.Dhaalaanii /kennaadhaan B. Kontiraataan/kirayidhaan C.Bosona Mancaasun D. Mootumma irraa 14. Lafa Bosonaa heektara meeqatu faayidaa adda addaa irra ooluu irraa kan ka’e bara 1998 hanga 2009tti manca’e ? ______15. Maddi galii keessan harki caalaan maalidhaa? A.Gurgurtaa Midhaanii irraa B.Gurgurtaa Horii irraa C. Gurgurta Bu‟aa bosonaa irraa argamu (cilee,Qoraanii,Xaawulaa k.k.f) 16. Akka Maatii keessaniitti gurgurtaa Bu‟aa Bosonaa irraa waggaatti Qarshii meeqa argattu?______17. Ijaarsa manaatiif Baayinaan Maddii Meeshaa keessanii Maalidha? A. Muka B. sibila C. simintoo 18. Iddoo Biraa irraa dhuftanii kan Qubattanii dha ? A. Eeyyee B. Lakkii 19. Hawaasa kana keessa waggaa meeqa jiraattanii?______20. Ganda keessan keessa Bulchiinsi cimaan bosonaa jiraayii? A. Eeyyee B. Lakkii 21. Ganda keessan keessa manca‟uu bosonaatiif sababa adda addaa jira jettanii kan yaaddan yoo jiratee nuu tarreessaa. ______22. Waggaa kudhan(10) keessatti Bu‟aa Qonna heektara irraa akkamitti ilaaltani ? A. Dabalaa jira B. Dhaabbataa dha /jijjiirama hin qabu c. gadi bu‟aa dha 23. Lafa Hektaara tokko (1) irratti qonna qotan irraa kuntaala meeqa waggaatti argattu bara 1998 fi 2009? Bara 1998______Bara 2009______24. Waggaa kudhan (10) giddutti jijjiirama qilleensaa argitan qabduu? A. Eeyyee B .Lakkii 25. Waggaa kudhan keessatti haalli Baayodaayiversiiti (Bineensota fi biqiltoota) akkamii?A.Dabaleera B.Dhaabbataa dha C.Gadi bu‟aa dha 26. Taateewwan biroo bosona mancaasuu irraa argamee yoo jiratee nuu tarreessaa. ______

27. Waa‟ee bosonaa irrattii leenjii fudhattanii beektuu? A. Eeyyee B. lakkii 28. Gaaffii 27 irratti deebiin keessan eyyee yoo ta‟e, yeroo meeqa leenjitanii ?______29. Ganda keessan keessa tti sagantaa bosona deebisanii misoomsu fi kanaan dura lafa bosonni hin jirree bosonesuun jiraayii? A.Eyye B. Lakkii 30. Namni kanaan dura ganda keessani keessaatti qorannoo bosona kana geggeese jira? A. Eeyyee B.Lakkii 31. Lafa keessan irraatti biqiloota nyaataa oolan akkasumas akka bosonaatti kan fayyadani dhaabuu yaaltanii beektu ? A.Eeyyee B. Lakkii 32. Mootumman bosona eguu irraatti hojii inni hojjetuu maal fakkataa?A. Laafaa dha B. Giddu galessaa C.Cimaadha 33. Bosona eeguu irraatti hirmannaan keessan maal fakkata?A.Laafaa dha B. Giddu galeessaa C. Cimaadha 34. Ganda keessan keessaa bosoni namaa fi bineensottan hin tuttuqamne /kan tuttuqaa irraa daangeeffame / jiraa? A.Eeyyee B.Lakkii 35. Ganda keessan keessatti maloota egumsa bosonaatiif kan hojjira oolaa jiran yoo jiraate nu tarreessa. ______Galatooma!!!

Appendix III

Data Collection Technique: Semi-structured interviewing

This interview guide is prepared to direct the interviews to be conducted with household heads in the selected kebele. The purpose of this guide is to secure additional data that may not be clearly secured through questionnaires to be filled by household heads.

1. What seems like the population size of your locality during the previous ten years and present?

2. To what extent deforestation has been witnessed in your locality?

3. What are the major population growths related causes of deforestation in your locality?

4. How deforestation rates compare in the past 10 years? Is that rapidly increased or not?

5. What are the consequences of deforestation in the area?

6. What is your opinion about the current forest resource condition in the area?

7. Are there reforestation and afforestation scheme in your locality?

8. Have there any support organizations to improve forest resource management activities in the area?

9. What solutions do you propose to mitigate the major causes and consequence of deforestation in area? Explain.

Appendix IV: Key Informant Interview Guide for Experts and kebele managers

This interview guide is prepared to direct the interviews to be conducted with natural resource expert of Meko woreda agricultural Office and kebele managers in the selected kebele. The purpose of this guide is to secure additional data that may not be clearly secured through questionnaires to be filled by household heads.

1. What are you considered as a major activities leading to forest destruction in Meko woreda?

2. Do you believe that high population growth has own impact towards forest resources?

3. What are the main consequences of deforestation in the context of Meko Woreda?

4. What contribute Meko woreda natural resource management office to initiate experts to conduct research about forest resource related problems?

5. What are the government actions to minimize the rate of deforestation and to manage up its impacts?

6. To what extent the local people‟s participation plant trees for household need and forest conservation?

7. To what extent different training are provided to the rural people in related to forest resource conservation?

8. What solutions generally you proposed for sustainable conservation of forest resources?

Appendix IV: Summary of Observation Checklist

1. In what extent the study area is deforested?

2. What extent to biological diversity is affected the study area?

3. Extent of forest lands cleared for crop land

4. For what purposes are mainly forests are cut in the area study area?

Appendix V. Checklist for Focus Group Discussion

1. What are the major human made causes of deforestation?

2. What are the consequences of deforestation?

3. How to minimize the rate of deforestation and consequences of deforestation?

4. What are the major responsibilities of local communities to protect forest resources?

Appendix table-1 kappa index

LULC (Field Observed)

Forestland Shrub land Grassland Cropland Bare land Total Co Co % of C un % of Cou % of un % of Cou Tota Co % of ou % of t Total nt Total t Total nt l unt Total nt Total LULC Forestland 8 13.8 0 0.0 1 1.7 1 1.7 0 0.0 10 17.2 (office Shrubland 0 0.0 8 13.8 1 1.7 0 0.0 0 0.0 9 15.4 interp Grassland 0 0.0 1 1.7 10 17.2 0 0.0 0 0.0 11 18.9 reted) Cropland 0 0.0 0 0 1 1.7 14 23.8 0 0.0 15 25.5 Bare land 0 0.0 0 0.0 0 0.0 3 51.1 10 17.2 13 22.9 Total 8 13.8 9 15.5 13 22.4 18 31.0 10 17.2 58 100.0 Source: Field survey used GPS and interpretation of satellite imageries in the office Overall accuracy = 85.8%.