University of Ghana http://ugspace.ug.edu.gh REGIONAL INSTITUTE FOR POPULATION STUDIES AT THE UNIVERSITY OF GHANA CLIMATE-RELATED VULNERABILITY AND MIGRATION: A COMPARATIVE STUDY OF BUOKU AND BOFIE-BANDA COMMUNITIES IN THE WENCHI DISTRICT BY ABU MUMUNI THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE AWARD OF MPHIL POPULATION STUDIES DEGREE JUNE 2010 University of Ghana http://ugspace.ug.edu.gh ACCEPTANCE Accepted by the Faculty of Social Studies, University of Ghana, Legon, in Partial Fulfilment of the Requirement for the Award of M.Phil Population Studies degree. Date _'c-L3-+t...:....::d/- :......1(~g..o~, _0_ _ ~,~ I V- Dr. Samuel N.A. Codjoe Date 13 }' 2.. ( ;to I 0 University of Ghana http://ugspace.ug.edu.gh DECLARATION I hereby declare that, except for the duly acknowledged references to other people's work, this work is the result of my own research and that it has neither in part nor in whole been presented elsewhere for another degree. Signed: ~ Abu Mumuni (Candidate) Date: __/ _S+[_'_~-+-/_~_~_f7_ I I ii University of Ghana http://ugspace.ug.edu.gh DEDICATION This work is dedicated to my wife, Asana Mohammed and my son, Salman-Faris Mumuni. iii University of Ghana http://ugspace.ug.edu.gh ACKNOWLEDGEMENTS I would like to express my profound gratitude to all personalities who have, in diverse ways, made this study a success. Firstly, lowe a great deal of gratitude to my supervisors, Dr. S. O. Kwankye and Dr. S. N. A. Codjoe, whose invaluable criticisms, suggestions and direction have actually brought this study into fruition. To them, I express my sincere thanks. I would also like to acknowledge the substantial contribution of Dr. Philomena Nyarko and all other lecturers whose comments, suggestions and guidance I could not do without. I would also like to thank all the team members on the Climate Change Collective Learning and Observatory Network Ghana (CCLONG) Project; Dr. Petra Tchakert, Prof. Samuel Adiku, Prof. K. Abekoe, Mrs. Regina Sagoe, Mr. Emmanuel Tachie, Mr. Samuel Kumahor, Mrs. Gifty Ofori Darko and Ms. Lucy Atidoh. I wish to also express my sincere gratitude to all my colleagues for their support, encouragement and love. I fmally give glory to the Almighty Allah, whose love, sustenance and leadership have earned me such an achievement. Abu Mumuni iv University of Ghana http://ugspace.ug.edu.gh TABLE OF CONTENTS ACCEPTANCE ............. .......... ·.············· .. ·. ......... · ................... . .............. i DECLARATION ...................................... . .. .......... .ii DEDICATION .............................. ...... · .. · .. .. ................. .iii ACKNOWLEDGEMENTS ............... ... .. .. .... ...... .. ............ .iv TABLE OF CONTENTS ...................... . .. ............................. v LIST OF TABLES ..................................... . viii LIST OF FIGURES .......................................... .. . ........................ x ABSTRACT ................................................... . . .................. xi CHAPTER ONE: INTRODUCTION ................ ... ....... . .. ................ 1 1.1 Background to the Study ................ .. .. .. ........ .... .......... . .. ....................... 1 1.2 Statement of the Problem .................................................. . .. ................ .............. 3 1.3 Rationale of the Study................. .................................. . ...................... 6 1.4 Objectives of the Study .......... ... ............................ .... ............... ............ .. ............. 9 1.5 Literature Review ....................................... .......... ............................................ 10 1.5.1 Climate change and human mobility ........................................................... 10 1.5.2 Climate-related environmental events and migration ..................................... 13 1.5.3 Summary of literature ........................................................... .. ........................ 16 1.6 Conceptual Framework .......................................................... .... ................. .. .... 16 1.7 Methodology ........................... ........... .............................. ...... . .................. 20 1.7.1 Sources of Data.................... .... .......... .... ..... . ............. .. .......... ..... 20 1.7.2 Method of Data Analysis ....... ........... .. ............ ...... ......... 22 1.8 Limitations of the Study .................................................................................. 24 1.9 Definition of some Concepts ...................... ........................... ... ... ............. ......... 26 1.10 Organisation ofthe Study ................. .. ...................................... . .... ... ............. 26 CHAPTER TWO: THE GEOGRAPHY OF THE STUDY AREA .................................. 27 2.1 Introduction ................................. .. ........ .. ...... ....................... ...... .......... .. ........... 27 2.2 Description of the Study Area .................................. ..... ............................ .. ...... 27 2.3 The Ecology of the Study Area ......................................................................... 29 2.4 Climate Related Environmental Events of the Study Area .................... .. ......... 30 v University of Ghana http://ugspace.ug.edu.gh 2.5 Trend in the Degradation of the Vegetation ......................... ··················· .......... 32 2.6 Change in land cover types .............................................................................. 34 2.7 Major drivers of Land Use Land Cover (LULC) change, future trends and interventions ............................................................ ... ....................................... 35 2.8 Analysis of rainfall and temperature data in the Wenchi District.. .................. 36 2.9 Modelling of Rainfall Pattern for the forest savanna transition zone - 1960 to 2004 .... .. .................................................................... .... ............. ... ... ........... ....... 40 2.10 Historical evidence of environmental events in the study communities .......... .45 CHAPTER THREE: INTERNAL MIGRATION IN BRONG AHAFO AND SOCIO- DEMOGRAPHIC CHARACTERITICS OF HOUSEHOLD HEADS ........... .49 3.1 Introduction ................................................ ................................ ... ................. .. . 49 3.2 Patterns and Trends oflnter-Regional Migration ...... ...................................... .49 3.3 Migration Streams ................................................................... ··.·· .···················· 51 3.4 Socio-Demographic Characteristics of Respondents ........................................ 54 3.4.1 Age and Sex Composition of Household Heads ........................ ................. 54 3.4.2 Marital Status of Household Heads ............................................................. 55 3.4.3 Educational Attainment of Heads of Household ........................ ................ 56 3.4.4 Household Size and Composition ................................................................ 57 3.4.5 Characteristics of households by migration status ....................... .... .......... 58 3.5 Stressors in the study communities ............................................. ...................... 60 3.6 Place of destination of climate-related migrants ............................................... 60 3.7 Relationship between explanatory variables and the intention to migrate ........ 61 3.7.1 Experience of Environmental Events .......................................................... 61 3.7.2 Distribution of Household Heads by Age and Intention to migrate ............ 63 3.7.3 Educational Attainment of Household Heads and Intention to Migrate ..... 64 3.7.4 Marital Status of Household Heads and the Intention to Migrate ............... 65 3.7.5 Sex of Household Heads and the Intention to Migrate ............. ........... ... ..... 66 3.7.6 Household Income and the Intention to Migrate ......................................... 67 3.7.7 Household Size and Intention to Migrate .................................................... 68 CHAPTER FOUR: CLIMATE VARIABILITY, MIGRATION INTENTION AND THE FUTURE OF RURAL HOUSEHOLDS ..................... ...................................... 69 4.1 Introduction .......... .......................................... ..... ............................................. 69 vi University of Ghana http://ugspace.ug.edu.gh 4.2 Causes and Consequences of Climate Change and Migration .. ... .. ......... .. ........ 69 4.3 Community Adaptation Strategies to Extreme Climatic conditions .... .... ... ...... 70 4.4 The Impact of Climate Change on Migration ... ........ ..... .. .... .... ..... ... .... ...... ....... 71 4.5 Future Implications of climate change on the livelihood of the people .... ... ..... 82 CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDAT rONS ...... ... 84 5.1 Summary .. ... ....... ..... .. ...... ..... .................. .... .... .... .. ...... .. ..... .... ..... ... .. ..... ... ... ..... .. 84 5.2 Conclusion ... ...... ... ... .......... .... .... .. ............. ..... ............. ..... ...... ... ... .... .... ........ ... .. 86 5.3 Recommendations ... ... ... .. .. ... . . ... .. ......... ... .. ..... ... .... ..... .... ........ .. .... ... 87 REFERENCES ............. .... .... ... ... ... .... ... ... ............ . . ..... ..... .... ... ....... 91 Appendix A: Survey Questionnaire .......... ... ... .... ... ... . . ... ..... .... . 96 Appendix B: Mental Models .. ..... ... ... ..... .. .. ... .. . . ...... ..... .. ...... . 109 vii University of Ghana http://ugspace.ug.edu.gh LIST OF TABLES Page Table 2.1: Total %~: ~~~;~ ~~~O~~~ .~~~~~. ~~~. .~ ~.~~~. ~~~~~. .~ ~. ~~~.~.~~ .~~.~~~~. ..... ... .... .. 34 2.2: Present and Previous Pattern of Rainfall in the Buoku and Bofie-Banda Communities ... ... ... ... .. ... .... .... ... .. ..... ...... ... .. .... ...... .. ... ... .... .... ..... ... ... ... ........... .. .46 3.1: Inter-Regional Migration Rates of Ghanaian Residence by Region, 1984- 2000 .... ... .. ..... .. ........... ... ... .... ..... .. .......... ..... .. ... ... .... ......... .. ..... .... .. .. .. ... ... ... ....... 50 3.2: Migration Streams of Ghanaian Residents to and from Brong Ahafo by region, 2000 .... ... ..... ...... .... .. ... .... ...... ... ..... .. ........ .... .......... .. ....... ... ......... ... .. ...... 51 3.3 : Life-Time Intra Regional Migration Rates (%) of Ghana by Birth and by Districts, 2000 (Brong Ahafo ) ...... .. ........ .. ............ ...... .... .. ... .. .. ... ... .. .... .. .. ............ .... ..... 54 3.4: Percentage distribution of respondents by Sex and Age Group .... .. .... .. ... ............. 55 3.5: Percentage distribution of respondents by Current Marital Status .. .. ..... .... .. ..... ....... 56 3.6: Percentage distribution of respondent by Sex and Educational Attainment .. .. .... .... 57 3.7: Percentage distribution of household heads by age group, Sex and Migration Status .... ... .... .... ... ... .. ...... ... .. ..... .. ....... ..... ... ..... .. .... .. ....... ... ..... .... ..... ... .... ..... .... ... 59 3.8: Percentage distribution of Community Stressors .... .. .. .. .. ............ .. .. ... .......... .... ........ 60 3.9: Percentage distribution of respondents by place migrated to and the number of years lived away .... .. .. .. .. .. ....... .......... ... ...... ... ........ ..... ... .............. ...... ... .. ..... .... 61 3.1 0: Percen~ge di~tributio~ of experience of environmental events by households by Intention to mIgrate .. ...... ... ....... ..... .... .... ..... ... .. ..... ... .. ..... .. ... ..... .... ... .. .. ........ 62 3.11: Percentage distribution of age of household heads by intention to migrate ...... .... .. 64 3.12: Percentage distribution oflevel of education of household head by intention to migrate .. .. ... ....... ... ..... ...... ..... ... ... ..... .. ... ... ... .......... ... .... .... .. .... .. ... ..... ..... .. .. ... .. ... .6 5 3.13: Percentage distribution of marital status of household heads by intention to Migrate ..... ........ ... .. ... ....... ...... ........... ... ... .... ......... ........ .... .... ..... .... ..... .... .... .... 66 viii University of Ghana http://ugspace.ug.edu.gh 3.14: Percentage distribution of sex of household heads by intention to migrate ....... .. .. .. ... .. .......... ... .......... ............ .... .. .............. .. ...... .... .... .. ... .. ........ 67 3.15: Percentage distribution of income of household by intention to migrate ... ......... .. . 67 3.16: Percentage distribution of size of household by intention to migrate ........... .. ..... ... 68 4.1: Percentage distribution of community responses to environmental stress by sex .... .... .... ............ ..... ........ .. .. .......... .. ... ...... ......... .. .. ....... ... ........ .. ...... .... .. ....... 71 4.2: Analysis of variance of the effect of climate related environmental events and other explanatory variables on the Inclination to Migrate - Buoku. .... . 72 4.3 : Relationship between climate related environmental events and other explanatory variables on the inclination to migrate - Buoku. ............ .... .. .. .... ....... ........ ...... 73 4.4: Analysis of variance of the effect of climate related environmental events and other explanatory variables on the Inclination to Migrate - Bofie-Banda. . .. 78 4.5 : Relationship between climate related environmental events and other explanatory variables on the inclination to migrate - Bofie-Banda. . .. ..... ....... .... ............... 80 ix University of Ghana http://ugspace.ug.edu.gh LIST OF FIGURES Page Figure 1.1: A conceptual framework showing the relationship between climate change and migration ....................................................... ··· .. ········· ······· .. ················ .18 2.1: Agro-Ecological Map of Ghana ............................................................................ 30 2.2: Land use and land cover maps of Wenchi District in 1972, 1985, 2000 and 2050 in the forest savanna transition zone ................................................. 33 2.3: Changes (km2) of cover types between 1972 and 2000 in Forest-Savanna Transition zone ... .. ......................... ....................... ...... ..... ........................... .35 2.4: Future land covers in 2000 and 2050 under business as usual (BaU) and policy intervention (PI) in forest savanna transition zone .................................... .36 2.5: Trend in annual rainfall in the forest savanna transition zone from 1960- 2005 ....... ............................................................................. ... ..... .................. .37 2.6: Annual number of rain days in the forest savanna transition zone from 1960- 2005 ............................................. ................................................................. 38 2.7: Trend in annual rainfall from 1960-2004 - Bui Station ............. .. .... .... ... .. .... .. ...... 39 2.8: Trend in number of rainy days from 1960 - 2004 - Bui Station ............................ .40 2.9: Pattern of rainfall variation in the forest savanna transition zone 1960- 2007 ........... .. ... ........ ............................................................ .'. ................. ........ .41 2.10: Wenchi Seasonal Cycle, 1961- 2000 and 2046 - 2065 ........ ................ .. .............. .42 2.11: Trend in annual maximum temperature, 1960 - 2004 .......................................... .44 2.12: Trend in annual minimum temperature, 1960 - 2004 ...................... .. ..... ..... .......... 44 3.1: Population pyramid of household members by age and sex ..................... .. ............. 58 x University of Ghana http://ugspace.ug.edu.gh ABSTRACT The population mobility and environment nexus has received a lot of attention in the field of population-environment studies in recent times. Increasing concerns about consequences of climate change for human population have further fueled the interest in the subject. The interest has not, however, resolved the debate on exactly what constitutes climate-induced movement, how to explain it, or what the magnitude is. The study examines the extent to which migration has been used as a livelihood strategy in response to climatic changes. The study uses a mixed method approach of both qualitative and quantitative instruments. Twenty four households were involved in the qualitative study whilst 100 households were interviewed in Bouku and Bofie-Banda respectively in the Wenchi District in the Brong Ahafo Region in the quantitative survey. Data were analysed using analytic and descriptive statistics to examine the direct and indirect influences of climate change on the decision to migrate at the household level. The results indicate that, the mean deviation of the mean of experience of only flood or drought is positive in the savanna zone when other independent variables and covariates are controlled whilst that of the forest zone is negative. People, consciously or unconsciously, either adapt to situations or migrate to other communities when they have no alternative choices. Farmers in Bofie-Banda presently cultivate cassava and cashew which, they say, is able to do well under the current rainfall regime in the area. Farmers in Bouku have started cultivating tiger nuts as an additional crop that is able to bring income to the family no matter the weather situation. Among other things, it is recommended that sustainable adaptation strategies to climate related environmental events should be promoted in rural communities in Ghana. xi University of Ghana http://ugspace.ug.edu.gh CHAPTER ONE INTRODUCTION 1.1 Background to the Study Population mobility is probably the demographic process that has received the most attention within the field of population-environment studies in recent times (Adamo, 2008). Increasing concerns about consequences of climate variability for human population have further fueled the interest in the subject. The interest has not, however, resolved the debate on exactly what constitutes climate-induced movement, how to explain it, or what the magnitude is. Climate change is usually confused with climate variability. There is a thin line between the two concepts. The United Nations Framework Convention on Climate Change (UNFCCC) defines climate change to clearly distinguish between natural variations in climate and climate change caused by humans (UNFCCC, 1992). Extreme environmental events such as periods without rainfall or with heavy rainfall and strong winds are part of natural variations whilst climate change is expected to completely alter these patterns. However, the form and the extent of these expected changes are still largely unknown and as a result make it difficult to accurately predict the impact of future climate change on migration (Schmidt-Verkerk, 2007). The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) in 2007 found out that the impacts of climate change are already being felt around the world. The report further indicates that the concentrations of most of the greenhouse gases (GHGs) are increasing at rates higher than reported in the Third Assessment Report (TAR) of the IPCC in 2001. University of Ghana http://ugspace.ug.edu.gh Historically, industrialised countries account for roughly 80% of the carbon dioxide build-up in the atmosphere. According to a US Department of Energy study in 2000, annually, more than 60% of global industrial carbon dioxide emissions originate in industrialised countries, where only 20% of the world's population resides. Emissions from sub-Saharan Africa contributed 0.8 metric tons to greenhouse gas emissions but it is the region noted to suffer most from the consequences of climate change (U.S Department of Energy, 2000). The most direct effects of climate change, according to the TAR of the IPCC in 2001, are on temperature and precipitation patterns. Scientists have also estimated that a warming of just 2°C will put as high as 30% of the world's species at risk of extinction (IPCC, 2007). The impact of climate on the world has no limits or boundaries. Industrialised countries have better adaptive capacity to climate conditions than developing countries. Most sub-Saharan African (SSA) countries are finding it difficult to cope with the existing climate stress and future climate change and variability. The United Nations (UN) Conference on Climate Change held in Accra, Ghana from the 21 to 27th sl August, 2008 focused on adaptive mechanisms to climate variability within the sub-region. The inability of people to cope with environmental stress as a result of climate change could contribute directly to migration by pushing people out of uninhabitable areas. Environmental events such as floods and droughts can serve as an immediate push whilst long-term changes such as desertification can lead to a decline in living standards that increases the cost of staying versus leaving (Adamo, 2003). Even though countries like China and Brazil in particular, have been making progress towards cleaner and more efficient technologies, there is still the need to do more in order to reduce the occurrence of climate events. As Flannery (2005) 2 University of Ghana http://ugspace.ug.edu.gh puts it, "non-adaptation to climate change is equivalent to genocide and that if we pursue business as usual for the next 50 years, the collapse of civilisation due to climate change is inevitable". The study, therefore, seeks to examine the extent to which migration has been used as a livelihood strategy in response to climatic changes and contributes to the adaptation portfolios for rural communities. 1.2 Statement of the Problem Today, environmental change, including climate change presents a new threat to human security and a new situation for migration (Adger, 2001). Mayers (1994) estimated that there were 25 million environmental refugees in the world compared to the 17 million traditional political refugees. He suggested that the number would reach 50 million in 2010 and 250 million by the next century in a greenhouse warmed world. The Fourth Assessment Report of the IPee described the estimates of numbers of environmental migrants as at best, guesswork, because of a host of intervening factors that influence both climate change impacts, and migration pattern (IPee, 2007), suggesting the need for extreme caution in the use of such statistics. There are three basic responses to climate variability. They are: 1) people will adapt to the climate conditions or 2) migrate to different environments or 3) die. These responses have some consequences but usually migration appears to be the main option in Africa because of limited adaptation strategies to climate change (Henry et al" 2005). It is, however, generally difficult to predict people's reaction with regard to the type of migration that would be undertaken as a result of climate change. A study by Munshi (2003) in Southwest Mexico found a correlation between declining rainfall and rising migration to the United States, since many rural communities depend on rain-fed agriculture. However, findings from studies in Burkina Faso 3 University of Ghana http://ugspace.ug.edu.gh (Schoumaker and Beauchemin, 2005) and Mali (Findley, 1994) revealed that droughts in the 1970s and 1980s were associated with decreases in international, long-distance migration. Short- distance migration to larger agglomerations, however, increased during drought years. Over the years, migration as a result of social and economic reasons has had serious consequences for the place of origin and of destination. Migration resulting from climate-related environmental events will, therefore, exacerbate the situation in Ghana where challenges of urbanisation such as sanitation, crime, inadequate health facilities and poor housing conditions are putting a lot of pressure on city authorities. It has been estimated that many regions will face severe water shortage in a warmer world, creating the potential for conflicts (lPCC, 2007). These climate-related environmental events are likely to considerably have impact on water resources, with a reduction in river flows and reduced groundwater availability. They are also projected to negatively affect agricultural yields, particularly in the central and northern parts of the country (Environmental Protection Agency (EPA), 2000). This will exacerbate the already high level of poverty in the northern parts of Ghana and also create food insecurity. The already high flow of migration from the north to the south could increase as a result of exposure to climate-related environmental events. This will put pressure on resources in receiving communities and also create high unemployment in such areas. The consequences of these are usually increased social vices and increased pressure on government to expand infrastructure in receiving communities mostly to the detriment of sending communities. In addition, the volume of migration from sending communities to receiving communities could aggravate accommodation problems in receiving communities and lead to the development of slums and squatter settlements with their attendant anomic activities. 4 University of Ghana http://ugspace.ug.edu.gh It has also been observed that cocoa, which is a major export product in Ghana, is highly susceptible to drought and the pattern of cropping of the crop is related to rainfall distribution (EPA, 2009). Further, black pod disease is closely related to weather and climate and this will have a major impact on the output from cocoa farms. A reduction in cocoa production will have serious consequences on Ghana's economy and increase the dependency of the national budget on donor supports and, therefore, create problems for growth in the economy. Also, farmers in cocoa producing communities will be faced with the problem of looking for alternative economic activities and many of them are likely to end up in urban communities. The characteristics of rural agricultural communities in Ghana make them more vulnerable to climate change and increase the desire of people to migrate. Climate related environmental events will increase rural-urban migration and leave most rural areas with the aged and children who do not have the capacity to go into large scale agriculture, the resultant effect being shortages and high cost of food. Even though, arguments in Tschakert et al. (2010) suggest that migration as a result of the impact of climate change may not be that phenomenal, it is important to examine the consequences of migration due to climate change and the number of people that will migrate as a result of climate-related environmental events. From the foregoing, the study seeks to answer the following questions: i. What is the trend in climate variables (rainfall and temperature) in Buoku and Bofie-Banda communities in the Wenchi District? ii. What type of environmental events may trigger migration? 5 University of Ghana http://ugspace.ug.edu.gh iii. What is the difference in female and male-headed households' response to climate related environmental events? iv. What is the contribution of climate change to migration in the study communities? v. What adaptation strategies do climate-change-affected communities adopt for their livelihood? 1.3 Rationale of the Study Rural populations in Africa depend largely on natural resources as their source of livelihood. Climate change presents major stumbling blocks to efforts made at reducing poverty and improving living standards of rural populations in Ghana. It is, therefore, imperative to examine the complex nature of climate change and how it affects all aspects of the social and economic life of the people. Ghana is fast urbani sing and the estimates suggest that 52 percent of the population will be in urban areas by 2010 (GSS, 2005). Migration still plays a major role in urbanisation in Ghana. Poverty, particularly extreme poverty remains largely a rural phenomenon with few exceptions in urban slums (World Bank, 2007). According to the World Bank in 2007, in some cases, urban poverty could be more serious than rural poverty. The urban environment cannot, therefore, serve as a safety net for rural migrants. In Ghana, about 70 percent of the poor people live in rural areas where they have limited access to basic social services, safe drinking water, good roads, electricity and telephone services (International Fund for Agricultural Development (IF AD), 2007). Thus, the very nature of rural life makes it unattractive and so if there is any environmental event that affects natural resources 6 University of Ghana http://ugspace.ug.edu.gh on which the rural population depends for their livelihood, one of the possible options that would be considered for survival will be migration. Speakers at the Sixteenth Session of the Commission for Sustainable Development held in May, 2008 in New York, asserted that climate change is the most urgent challenge faced by African countries whose economies are dependent on activities affected by climate. There is inadequate scientific research, education, data collection and monitoring as well as capacity building in developing countries aimed at addressing the issue of climate variability (Commission for Sustainable Development, 2008). This poses a lot of constraints to developing countries since building resilience to climate variability requires in-depth knowledge of local area ecosystems, weather patterns, land use and demographic patterns. There is the need to help developing countries to device adaptation strategies through financial assistance, technology transfer, drawing upon experience and capacity building. Environmental migration has been identified by researchers as one of the difficult interrelationships to measure as a result of the number of factors that influence migration. It is usually difficult to isolate the effect of climate variability and shock from other factors in the measurement of migration. Stem (2006) argues that measuring the impact of climate variability on migration in Africa could be done by identifying the existing migration patterns and examining how demographic trends and climate change may affect the drivers of these specific migrations. Over the past three decades, a lot of interest has been shown by policy makers and academic communities in the study of environmental refugees. Some of the studies that 7 University of Ghana http://ugspace.ug.edu.gh described environmental effects on human mobility included Adamo's (2008) study on "environmentally induced population displacements", Black's (2008) study on the "demographics and climate change" and Henry et al. (2003) study on "modelling inter-provincial migration in Burkina Faso". Apart from a few studies done by some researchers such as Van der Geest (2004, 2008) on North - South migration in Ghana and the role of the environment, there are not many studies on the relationship between the environment and migration in Ghana. The present study is new in the field of social science research in Ghana and will serve as the foundation for further larger scale studies in the area of climate change and migration. The study will also serve as an empirical guide to policy makers on how to integrate climate events at various development levels to the benefit of the population. This study has further been deemed necessary because of the recent trends in the changes in cropping patterns in the country as a result of climate conditions. The agricultural sector is the dominant sector in Ghana's economy in terms of its share of Gross Domestic Product (GOP), employment and foreign exchange earnings. In 2003, the sector contributed about 39.2% to GOP and accounted for about 46.1 % of foreign exchange earnings (Institute of Statistical Social and Economic Research (lSSER), 2004). This makes the Ghanaian economy very vulnerable to climate-related environmental events because any change in environmental conditions such as rainfall affects the entire economy either positively or negatively. Agricultural technologies developed to solve farmers' problems are not in many cases applicable to their particular circumstances and farming systems. Variability in rainfall, inaccessibility to market and low price paid for most agricultural produce do not encourage the use of mineral fertilizers (Adjei- Nsiah, 2006). 8 University of Ghana http://ugspace.ug.edu.gh The study would assess the social vulnerability of the study communities and examine how households have coped with the situation over the years. The study would also assess how migration features in the adaptation strategies at the household level in order to contribute to presenting better adaptation options for communities. It is hoped that if better adaptation strategies to environmental events in rural communities are encouraged, it will help improve the economic livelihood of rural dwellers and eventually reduce rural-urban migration and poverty. 1.4 Objectives of the Study The overall objective of the study is to provide empirical evidence on how the different drivers of vulnerability in rural households caused by climate variability might influence the decision to migrate. Specifically, the study seeks to: i. Examine the drivers of vulnerability to climate related environmental events in the study communities. ii . Examine the demographic and socio-economic factors affected by climate change and how these may trigger migration. iii. Analyse the extent to which climate change contributes to migration at place of origin as a push factor. iv. Examine climate-related environmental events that may trigger migration from the study communities. v. Make recommendations to policy makers on how to develop plausible adaptation strategies for vulnerable communities in the country. 9 University of Ghana http://ugspace.ug.edu.gh 1.5 Literature Review 1.5.1 Climate change and human mobility Earlier studies on the relationship between climate change and migration focused on the issue of environmental refugees which assumes that migration was caused by one single event. Yet, there is a consensus in the migration studies literature that migration can only rarely be explained by one single reason alone (Kritz et ai., 1992; Castles and Miller, 1993; Boyle et ai., 1998; Wood, 2001). Also the Geneva Convention's definition of "Refugees" as people who are outside the country of their nationality "owing to a well-founded fear of being persecuted for reasons of race, religion, nationality, membership of a particular social group or political opinion" (UNHCR, 2006: 16) makes it inappropriate to use the term environmental refugees. This definition, therefore, makes the issue of environmental refugees currently legally meaningless. On the basis of the legality of the term environmental refugees, Hugo (1996) suggested the use of the concept "environmental migrant" instead, although he acknowledges that environmental change is a factor that drives involuntary migration and should be recognized academically and politically as such. Migration is usually considered an inevitable option when there is adverse environmental change (Henry, 2006). The concept of environmental change, however, encompasses (among others) natural disasters (including drought) and the gradual deterioration of environmental conditions as a result of human activities. The challenge here is that most of the literature on environment and migration inter-relationship classify both situations as push factors of migration. Henry (2006) further argues that because land degradation and drought occur by different means with the former being human-induced and the latter being natural, the responses 10 University of Ghana http://ugspace.ug.edu.gh to these events will not be the same. He noted that in the fonner, the individual household is involved in the act and so has a big role to play in deciding on how to address the issue whilst with the latter, even though households will be the victims, the reactions to it usually come from policy makers. In countries where agriculture is the main source of livelihood, environmental changes can seriously trigger migration. Migration is more likely incorporated by low-income rural households, mostly if their incomes are drought-sensitive. Since the 1990s, the nexus between climate change and migration has been addressed both empirically and theoretically. The release of the Summary for Policymakers of the Working Group II Document on Impacts, Adaptation, and Vulnerability, which is part of the Fourth Assessment Report of the IPCC, has generated interest in the relationship between climate change and migration. The report assessed the potential of population migration in some areas as a result of drought and an increase in tropical cyclone activities (Parry et al., 2007: 16). It revealed that such climatic events tend to destroy the natural resource base of the population and, therefore, give rise to migration into areas where people may feel secure to carry out their activities. The 2009 state of the world population report indicates that climate change and its adverse consequences for livelihood, public health, food security, and water availability will have a major impact on human mobility likely leading to substantial increase in the scale of migration and displacement (United Nations Population Fund (UNFPA), 2009). While environmental change triggers popUlation movement on one hand, migration may take a toll on the environment in areas of origin, destination and travelling routes in between. The report further showed that there is a two-way connection between the migration and the environment relationship which 11 University of Ghana http://ugspace.ug.edu.gh results in a vicious circle: population movement contributes to environmental degradation in areas of destination, which may in tum provoke further migration and displacement (UNFP A, 2009). A fairly recent development in the migration literature has been the emphasis on family and family strategies as crucial elements in migration decisions. Migration by one person can be due to, fully consistent with, or undertaken by a group of persons, such as the family (Krokfors 1995). The family is conceptualised as a coalition vis-a-vis the rest of the world, family members share costs of and rewards of migration. Consistent with more recent 'livelihood' approaches, migration is seen as a form of portfolio diversification by families, in which they enter into chosen contractual arrangements, and remittances exemplify the 'inter-temporal contractual arrangement' between migrant and family, with families investing in migrants, migrants in families, and both expecting returns from that (Krokfors 1995). The existence of family ties at place of destination facilitates the process of migration for most potential migrants in sub-Sahara Africa. Networks can provide information on migration opportunities, facilitate finding employment, and support migrants while looking for work, thus lowering the costs and risks of migration. In a 1995 survey, 23.5 percent of Ghanaian migrants stated that they emigrated because of the presence of relatives and friends (Anarfi and others 2003). Ghanaian diaspora associations, such as Pentecostal churches, assist new migrants in the United States, the United Kingdom, Canada and other countries (Quartey 2006). The existence of relations has contributed to the migration of a number of family members and this also influences the direction of remittances to place of origin. In Ghana for instance, the Ashanti and 12 University of Ghana http://ugspace.ug.edu.gh greater Accra regI·O ns account for most .mtern.atlO na I rem!· ttances (Kabki and ot~I'S" 2004, Mazzucato and others 2005). 1.5.2 Climate-related environmental events and migration Findley (1994) in research on migration from rural Mali during the 1983-1985 drought found that long-distance migration - notably of male household members to France - decreased during drought periods. She noted that this could be explained by the fact that food scarcity leads to increased prices, forcing people to spend more money on their basic needs rather than long-distance migration. She further indicated that, short-distance migration to larger agglomerations increased during drought years as women and children left in search of work to contribute to household incomes. In addition, this strategy reduced the number of persons in a household and consequently, the amount of food needed. The focus of Findley's study was on drought and the argument then was as to whether drought alone could trigger migration. Meze-Hausken (2004) in a study in Ethiopia in which she surveyed more than 100 peasant farmers, found that people in marginal regions have developed adaptation mechanisms such as the cultivation of drought tolerant crops which strengthened their ability to cope with climatic events. It is, therefore, difficult to limit the relationship between climate change and migration to just one environmental event. The consequences that an environmental event such as drought has on livelihood decisions, including migration, largely depended on the socio-economic situation of the people concerned (Haug, 2002). It is, therefore, important to consider these socio-economic issues such as income and the occupation of the people in analysing the impact of an environmental event on migration. 13 University of Ghana http://ugspace.ug.edu.gh Further, a study by Henry et aI., (2004) on the effect of changing rainfall patterns and migration in Burkina Faso, using historical analysis found no relationship when they did not distinguish between the different types of migration by destination and duration. When the research was repeated by factoring in the different types of migration, the analysis revealed that people living in areas with scarce rainfall are more likely to engage in short distance moves than people living in other regions. The researchers also concluded that long-term migration seems to be less related to environmental conditions than short term moves. Literature on other climatic events and their impacts on migration have revealed that the reaction of human population with regard to climate issues varies from one event to the other. For instance, a study by Paul (2005) on the effect of tornados on migration behaviour in two village communities in north-central Bangladesh concluded that there was no link between the tornado and migration behaviour at all. It indicated that the 2004 tornado in the region did not cause higher rates of out-migration in the affected villages. Earlier studies on Hurricane Andrew that hit parts of Florida in 1994 found that people who lived in the wealthier southern part of the country migrated in much larger numbers than people who lived in the poorer northern parts (Smith and McCarty, 1996). The question here, however, is whether the severity of the hurricane in the southern part is what contributed to the larger migration in the area or if it is as a result of the distribution of wealth in the region. The emergence of such technical questions in the analysis of the relationship between climate change and migration, therefore, calls for the employment of various methods to help draw conclusions. University of Ghana http://ugspace.ug.edu.gh There is so much debate about estimates of climate-induced migration because climate variability may not necessarily lead to migration as people may still be tied to their homes as a result of lack of social connection outside their communities. There are a number of issues that are taken into consideration before deciding on whether to migrate or not. Even if migration is triggered by climate change, it will be inter-related with the existing migration flow because of the importance of social networks and capital constraints in determining people's ability to migrate (Development Research Centre, 2008). That is to say that, there is the possibility of an increase in migration in the future but as to whether these migrations would be triggered by climatic factors is a question yet to be answered. For instance, prior to Hurricane Katrina, up to 70,000 inhabitants of New Orleans, most of whom were living in poverty, were unable to flee the city before the storm hit. Around 1.3 million people did leave the city to other metropolitan areas in the US, and 60 percent of these people had since not returned to the city by 2007 (Development Research Centre, 2008). In this instance, even though there were significant environmental 'push' factors encouraging residents to leave affected areas, people's mobility was mediated by a host of other factors that had more to do with socio-economic conditions than the devastation itself. It is, however, difficult to distinguish these socio-economic factors from environmental factors as a result of the inter-dependence of a lot of these socio-economic factors with the environment. Migration has a long standing tradition in Ghana. Every Ethnic group in Ghana claims to have migrated from somewhere else (Anarfi et. a1., 2003). The reasons behind most of these migrations are usually linked to struggles for better environment for survival and also for economic activities. Studies of migration have always focused on the economic aspect of it with little attention on other factor that contributes to migration. Migration, caused by an 15 University of Ghana http://ugspace.ug.edu.gh environmental event, can be considered in most instances as forced migration because people usually do this against their wish. Such movements are usually involuntary and in such cases push factors at place of origin seem to be more of a concern than pull factors at place of destination (Adamo, 2008). According to Izazola et al. (1998) and Hunter (2005), the deterioration of local environmental conditions with its direct impact on quality of life in general could serve as a push factor from a community. 1.5.3 Summary of literature The review of literature on climate change and migration indicates that the impact of climate change would be felt more in developing countries because of the limited capacity to adapt to climate situations. It is, however, difficult to tell whether people in such affected places in the world will embark on migration as a survival strategy. The literature also reveals that migration will be a key adaptation strategy in the event of climate change but the challenge will be how to justify whether such migration was triggered by climate change and not other socio- economic factors. Further, there is also the issue of how to identify the threshold of climate- related environmental events that could trigger migration and even the type of migration that will be embarked on. These gaps in the literature are what this study aspires to fill. 1.6 Conceptual Framework The framework shown in Figure 1.1 examines the relationship between climate-related vulnerability and migration at the household level. The framework for the study is based on three approaches, namely the risks hazard approach, the livelihood driven approach and the psychological driven approach. It shows that an interaction between climate-related 16 University of Ghana http://ugspace.ug.edu.gh environmental events and social vulnerability exposes households to some forms of risk from climate change impact. Climate-related environmental events in the study are the intensity and duration of floods and droughts in the study area. These are determined through the analysis of rainfall data from the Wenchi and Bui sites of the Ghana Meteorological Services Department from 1960 to 2005. Temperature in the district is also examined from 1960 to 2004 to ascertain the trend of minimum and maximum temperatures in the district and their implications for the livelihood of the people. Social vulnerability, on the other hand, looks at the socio-demographic characteristics of the households, household livelihood, individual characteristics and income status. Specific variables that were used in assessing social vulnerability are age and sex of household members, sex of head of household, educational level of head of household, marital status of head of household, migration status of household, occupation of head of household, activity status of household members and household income. 17 University of Ghana http://ugspace.ug.edu.gh Figure 1.1: A conceptual framework showing the relationship between climate cbange and ~~rati~n /---Eii~ate Relat;f~ / Environmental Events~ - Floods .F,,,.;.,D':::,ght , SOCial VUlnerabil~ ~ '~;:i; •. Risk of being affected by Climate Change Impact = Environmental Hazards -t;Social Vulnerability of Population Experience and Perception Adaptation Strategy F==::;:*",:::::====I of Environmental Hardship Migration Inclination J Source: Based on Hewitt (1997), Blaikie et al. (1994), Meze-Hausken (2000), Adamo (2003). Climate-related environmental events such as flood and drought have serious implications for the health of children and the aged. These climate related environmental events lead to food insecurity and breeding grounds for mosquitoes. The sex of the head of a household gives one some privilege with regard to ownership of land. Usually, male-headed households tend to have access to larger land than female-headed households. The vulnerability of female- headed households will, therefore, be exacerbated with the occurrence of climate-related environmental events. Further, the ability to adapt to climate-related environmental events depends on one's income level and social circumstances. Households with good income standing will be able to adapt easily to climate events whilst the vulnerability of poorer households will be exacerbated. Education is expected to add value to every individual's life and 18 University of Ghana http://ugspace.ug.edu.gh household heads with higher educational background are in a better position to take advantage of good opportunities than their counterparts with lower or no education background. In a nutshell. the risk of being affected by climate impact as indicated in Figure 1.1 is the interaction between climate-related environmental events and vulnerability of the population. The framework further indicates that the decision of households at risk of climate change impact to migrate or not to migrate is determined by households' adaptation mechanisms and perceptions as well as experiences of environmental hardships. Generally, people will adopt various strategies as ways of living under a condition. Some of the adaptation strategies include cultivation of drought/flood tolerant crops, construction of fire belts, dependence on support from relatives and migration. This, therefore, indicates that environmental factors rarely act alone. Lonergan (1998) affirmed that environmental factors cannot be easily disentangled from the rest of the social, economic and political factors and processes leading to out-migration. Except in cases of sudden environmental disasters, migration is just one among several possible responses and adaptations to environmental changes (Adger et al. 2007). Also, people's subjective view and perception of climate hazard and their own vulnerability to climate variability is emerging as yet another important factor (Izazola, 1998; Hunter, 2005). Psychologically, people who have experienced a particular event over a long period of time may tend to perceive it as a normal event without necessarily having a solution to it. They tend to develop a psychological thinking that endures them to cope with environmental hardships which may be difficult for households that have not ever been exposed to similar events to bear. 19 University of Ghana http://ugspace.ug.edu.gh Generally, the inclination to migrate arises when people have challenges with their present place of residence and have the perception that they could get a better satisfaction of life from elsewhere. The circumstances that may lead one to have such inclination may be economical, social, political, environmental, or a combination of two or three of the factors or even all the factors put together. It is therefore, difficult to just speculate that the migration of people from the study communities is as a result of environmental events without taking cognisance of other explanatory factors. 1. 7 Methodology 1.7.1 Sources of Data Data for the study are drawn from both primary and secondary sources. Secondary sources of data are drawn from the national censuses and meteorological data from the Ghana Meteorological Services Department. The primary data are collected by members of the Climate Change Collective Learning and Observatory Network Ghana (CCLONG) project and a household survey in the two communities. The CCLONG Project collected a range of both qualitative and quantitative data from twelve (12) households in each of the study communities. Selection of households for the study was done by taking into consideration different socio- economic backgrounds of the people in the study communities including migrants and non- migrants, women and men and old and young people. The aim was to gain a holistic understanding of people's livelihood and how they react to climatic events. They were asked how they perceive their natural environment, how it affects their lives and what they did to maintain themselves during past environmental events like droughts and floods. Also, 20 University of Ghana http://ugspace.ug.edu.gh information on household assets, household members and major occupation of households were collected. There was also questionnaire administration to migrant and non-migrant fanners in the two study communities. Both communities have about 50 percent of the population being migrants mostly from the Upper West region and other close by communities who have migrated to the communities for fanning purposes. In all, 100 questionnaires were administered in 100 households in each of the two study communities. A sample size of 100 households per community was chosen because it represented more than half of the households in the communities. Also, the households in the study communities are homogenous in character with about 98 percent of them being fanners. The sampling of the households was done randomly using a household listing that was done by students of the University for Development Studies in 2008 in the study communities. The main issues in the questionnaire are the background of the respondent, household information, migration patterns and environmental challenges in the communities. The questionnaire was administered to heads of household (See a copy of questionnaire in Appendix A). There were also participant observations in the communities to find out what people discuss and this involved living with families for about a month over the entire study period of two years. Analysis of very wet periods, normal periods and dry periods which are used as indicators for examining the climate was done by examining the rainfall and temperature data of the Meteorological Services Department over a period of 45 years. Also, data from the 1970, 1984 and 2000 population censuses are used to examine in-migration as well as inter-censal 21 University of Ghana http://ugspace.ug.edu.gh migration among districts in the Brong-Ahafo Region. The purpose of this is to provide a general idea of the migration flows to the region and within the region. 1.7.2 Method of Data Analysis The following approaches were employed to examine the extent to which migration could playa role as an adaptation strategy in the event of climate change. Computation of migration streams to and from the Brong-Ahafo Region for 1970, 1984 and 2000 and intra-regional migration rates for 1970, 1984 and 2000 was carried out. The 1970 and 1984 censuses used Local Authority to represent places of birth while the 2000 census used the administrative districts. The place of birth was used as the unit of analysis to examine information on migration from the census data. Estimation for in-migration and inter-censal migration for each of the districts was based on the National Growth Rate method of estimation. The following formula is employed in the computation: Mi = [pit+n-pl t PT+N-PT] X 100 pIt PT Where: Mi = Intercensal rate for the ith district pi t = Population of the ith district at first census pit+n= Population of the ith district at second census PT = Total Regional Population at first census PT+N= Total Regional Population at second census. The purpose of these migration computations from the census data is to assist in drawing some conclusions from the historical data gathered from the communities in relation to the trend 22 University of Ghana http://ugspace.ug.edu.gh of migration in the district. In addition, descriptive statistics in the form of percentages are employed to examine the demographic and socio-economic characteristics of the respondents, perception of migrants and non-migrants to environmental events, types of migration embarked on in the study areas, causes of migration in the study areas and causes of vulnerability with regard to climatic events. A mental model technique was used to assess how the people in the communities understand climate change in their own local sense, the causes of climate change and its effects. The technique involves meeting with community members in groups and allowing them to discuss among themselves as to what they understand by climate change, its causes and consequences. Participants are allowed to look at both the positive and negative impact of climate change on people and the environment. Because most of the participants were illiterates, they were allowed to express their views on a piece of paper in the form of a drawing that is understandable to all the participants (see Appendix B for details). This encouraged all the participants to contribute effectively to the discussion. To examine the influence of climate related environmental events on the intention to migrate, a Hierarchical Analysis of Variance (ANOVA) and Multiple Classification Analysis (MCA) were employed. Multiple Classification Analysis is a technique for examining the interrelationship between several predictor variables and one dependent variable in the context of an additive model. The main advantage of the MCA technique is that it provides the grand mean of the dependent variable as its constant term and a set of category means for each factor expressed as deviations from the grand mean as main effects. Expressed in deviation form, category means reflect the magnitude of each category of a factor. 23 University of Ghana http://ugspace.ug.edu.gh Migration is influenced by socio-demographic and economic factors such as age, level of education, marital status, sex, size of household and income. Climate-related environmental events of interest in the study are floods, droughts or experience of both events. It is also important to note that the intention to migrate is also determined considerably by the household perception of climate-related environmental events in the community and the migration status of the household, i.e., whether the household is a migrant household or a non-migrant household. In order to measure the impact of climate change on the intention to migrate, the socio- demographic and economic factors that influence the decision to migrate were considered in the model. The level of significance for interpreting the results is p25 trees/he) ~Kllometers _ Wildely Open Cultivated woodland «20 treeslha) o 5 10 20 30 40 Source: Centre for International Forestry Research (CIFOR), 2008 A critical look at the land cover image in 1985, however, indicates a drastic depletion of the vegetation. Further, the image shown in 2000 is an indication that both the forest and savanna areas of the district are getting depleted. It is projected that if the situation continues as it is today, by 2050, the entire forest-savanna transition would be reduced to open cultivated woodland vegetation and this will have serious implications for farmers in the region. The location of Bofie-Banda and Buoku in the Wenchi District is an indication that farmers in the communities will be faced with environmental challenges that may come up as a result of the depletion of the vegetation in the future. 33 University of Ghana http://ugspace.ug.edu.gh 2.6 Change in land cover types Table 2.1 shows Land use/land cover (LULC) class types in 1972, 1985 and 2000 as mapped from the Landsat satellite images. It indicates that open forest in the transitional zone reduced from 1,629 km2 to 243 km2 between 1972 and 2000. It is also anticipated that only 59 km2 of the open forest would be available by 2050 under "business as usual" scenarios, representing 96.4% loss. Again, the 3,000 km2 closed savanna woodland was converted to only 1,927 km2 representing 21.2% loss between 1972 and 2000 and a total loss of70% by 2050. It is also worth noting that 505 km2 representing 10% of the total land area is threatened by desertification as indicated in Figure 2.3. The challenge here is how the population in the district is going to cope with the situation as the years go by. Table 2.1: Total areas of land use/ land cover per class, change and rate of changes from 1972-2050 Chan!!e Area Annual Rate of Land UselLand 1972 1985 2000 2050 Chanee Cover Class kml % kml % kml % kml % kml % Open forest «60 % canopy) 1629 32.3 684 13.5 243 4.8 59 1.2 -51 -1 Closed savanna woodland (>25 3000 59.4 2608 51.7 1927 38.2 898 17.8 -38 -1 treeslha) Open cultivated savanna (20-25 419 8.3 1757 34.8 2880 57 3588 71.1 89 1.8 trees/ha) Widely Open Cultivated Savanna «20 505 10 - - trees/ba) Total 5,049 100 5,049 100 5,049 100 5049 100 59 1.2 Note: The annual rate of change was calculated based on the observed land use/land cover change. Source: Centre for International Forestry Research (CIFOR), 2008. 34 University of Ghana http://ugspace.ug.edu.gh Figure 2.3: Changes (kml) of land cover types between 1972 and 2050 in Forest-savanna transitional zone 4000 3500 3000 • Open forest «60% canopYI E 2500 .>C ~ 2000 • Closed savanna woodland (>25 3 trees/hal 1500 iii Open cultivated savanna (20-25 1000 trees/hal 500 • Widely Open Cultivated Savanna «20 treees/hal 1972 1982 2000 2050 Years Source: Centre for International Forestry Research (CIFOR), 2008 2.7 Major drivers of Land Use Land Cover (LVLC) change, future trends and interventions Major drivers of LULC in the Forest-savanna transitional zone are: bushfires, traditional slash and bum fanning method, widespread burning of rangeland by herdsmen, decline in soil fertility, illegal exploitation of resources and increased population density. The Wenchi District which lies within the forest-savanna zone has lost its forest cover giving way to savanna woodland and grassland (CIFOR, 2008). Wood harvesting for domestic and commercial purposes is a common practice in the district. Charcoal production, extensive cultivation, inappropriate fanning methods and the use of fire as a major domestic energy source will continue to deplete the vegetation and reduce the soil fertility, if appropriate measures are not taken to regulate the situation. The long term effect of all this may be irregular rainfall which will have serious implications on the livelihood of the people who are predominantly fanners. 35 University of Ghana http://ugspace.ug.edu.gh The CIFOR report, 2008 proposed the establishment of woodlots purposely for meeting fuel wood demand, promote agro-forestry and educate farmers on the use of fire in farming. It noted that if the proposed forest management practices are encouraged from now to 2050, 49.5% and 33% of the open forest and closed savanna respectively could be restored (see Figure 2.4). Figure 2.4: usual (BaU) and 4000 3500 3000 • Open forest «60% canopy) N 2500 ..E.: ~ 2000 • Closed savanna woodland (>25 3 trees/hal 1500 II Open cultivated savanna (20-25 1000 trees/hal • Widely Open Cultivated 500 Savanna «20 treees/ha) 0 2000 Years Source: Centre for International Forestry Research (CIFOR), 2008. 2.8 Analysis of rainfall and temperature data in the Wenchi District Rainfall and temperature playa very important role in defining the ecology of an area. The two study communities are farming communities that depend heavily on rainfall for their livelihood. The district has two main seasons - rainy and dry seasons. The rainy season occurs between April to October with short dry spell in August whilst the dry season is from November to March. The district experiences an average of five months of rain. Figure 2.5 indicates that the trend in annual rainfall in the Wenchi District for the period 1960 to 2005 did not show any significant changes. What this implies is that, approximately the same amount of rainfall is 36 University of Ghana http://ugspace.ug.edu.gh of the number of rainy days required for optimum crop yield of 100 days is anything to go by, then 1983, 1988, 1992, 1993, 1994, 1998 and 2001 could further be described as drought years with all of them occurring in the last three decades. The slight reduction in annual rainfall and the steep decline in the number of rainy days is an indication of intensive rains in recent times. Changes in rainfall within the period (1960-2005) was 7.1% (100mm) while the change in number of rainy days was 18% (22 days) (Figures 2.5 & 2.6). The trend in annual rate of change for rainfall and number of rainy days were 0.16% (2.2mm) and 0.4% (O.5day) respectively. Figure 2.6: Annual number of rainy days in the forest-savanna transition zone from 1960- 2005 r 180 r I 160 i 140 ~ 120 "C I <: .~ 100 '0 OJ 80 .0 E :s z 60 40 20 0 Source: Computed from rainfall data from Ghana Meteorological Service Department (GMSD). Analysis of rainfall data from the Bui Meteorological Station depicts a slight decline in the amount of annual rainfall over the period 1960 - 2004 (Figure 2.7). The data, however, show 38 University of Ghana http://ugspace.ug.edu.gh a sharp decline in the number of rainy days as shown in Figure 2.8. The data from Bui Meteorological Station better explain the rainfall pattern in the Bofie-Banda community than the data from the Wenchi Meteorological Sub-station. Figure 2.7 shows that if rainfall required for an optimum crop yield is estimated at 1,100mm, then 1961, 1967, 1970, 1973, 1975, 1977, 1981, 1983, 1984, 1984, 1985, 1988, 1992, 1994, 1998 and 2004 could be described as drought years within the 44-year period. Figure 2.8, on the other hand, shows that if the number of rainy days required for optimum crop yield is 100 days, then apart from 1962, 1963, 1966, 1968, 1974 and 1979, all the other years could be described as drought years with 1983 being the most severe. Analysis of the rainfall data from Wenchi and Bui Meteorological sub-stations suggests that Bofie-Banda is experiencing more drought spells than Bouku. Accordingly, Bouku experiences more wet periods than Bofie-Banda. r·ll! e 2.7: Trend in Annual Rainfall from 1960-2004 -~!!~t!!ion -2000 -- i 1800 t---t-------------------"I-'~~~-+-l,14(~ 1600 t-_tt-__• ____________- --:-__- --.:R.:....Z..::.=.::.0.::.0:.:.1::53~_ 1400 -r-----tf--t"----,r-t--------A--------.-----I\-------- E 1200 E. :f 1000 c ·iii 800 III: 600 400 +---------------------------- 200 o ~-------------------------------------------- Years Source: Computed from Rainfall Data from Ghana Meteorological Service Department (GMSD) 39 University of Ghana http://ugspace.ug.edu.gh "~uU. re 2.8: Trend in Number of Rainy days from 1960-2004 - Bui station f 140 ---------- 120 ~ 100 "t:I 0ci! 80 '0 ~ 60 -'I E :::J 40 Z 20 0 0 N o;t U) co 0,.. N oU) U) U) U) U) .. ,.... ,..;.t. U,...). ,0..0.. 0 N o;t U) 00 0 N o;t U) 00 0 N <:t 00 00 co 00 co 0 0 0 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ '~" '~" '~" '~" '~" ~ 0 0 N N Years Source: Computed from Rainfall Data from Ghana Meteorological Service Department (GMSD). 2.9 Modelling of Rainfall Pattern for the forest savanna transition zone - 1960 to 2004 The forest savanna transition zone is one of the food production baskets of Ghana. Agriculture in the forest-savanna transition zone relies solely on rainfall and it is the main source of livelihood for the people in the transition zone. Modelling of rainfall pattern in the forest savanna transition zone for a period of 47 years indicates that the pattern of rainfall in the transition zone has been changing over the years. Figure 2.9 shows that when the graph is divided into three parts, the events experienced in each of the parts vary from one period to the other. There were more very wet periods in the first 15 year period compared to the other two later periods. The figure also indicates that whilst the highest very wet year was experienced in the first period - 1968, the driest year was experienced in the second period - 1983. The figure further shows that whilst there were very wet years following one another in the first period, there was nothing of that in the second period. There were, however, several normal rainfalls in 40 University of Ghana http://ugspace.ug.edu.gh the second period. The third period shown in the graph experienced more dry periods during that period and there was a continuous dry period in 1998 and 1999. It also indicates that the period experienced continuous wet years from 2002 to 2005. Fi ore 2.9: Pattern of rainfall variation in the forest savanna transition- z-on-e - 1960-2007 , • Very Wet i .---J . Normal I 600 ----------- ---- . Dry 8e5 00 .....- --....... - -; 400 __- ._- __11--- .~ 300 ---...-- -...-- .";: 200 __~ ._-__1__=_ __ Q,I ~ 100 e__.....-.JI---_____. ... ~c 0 ~NI~~~~~~. .~ ~. .~ ,.~~,.~~~~~~~~~~. .~ ~-I 00 1IAI; ....- --1m1<~-I-<.,,1- -200 .--------- -300 -400 -500 ~---------!----- Year Source: Computed from rainfall data from GMSD for the savanna trahsition zone The implication is that over the last IS years, there has been an experience of more dry years as well as very wet periods and this makes it very difficult for farmers to plan. It is also revealing from Figure 2.9 that even though there were continuous dry periods in 1998 and 1999, the event that was easily recollected by most of the people in the communities was the 1983 drought. The last period presented in Figure 2.9 also indicates a drastic decline in the intensity of the wet years compared to the first and second periods. However, the same thing cannot be said of the dry years. The graph indicates that there have been very significant dry years in the last period. Apart from 1983, 1995 was the second driest year in the whole 47 -year period. 41 University of Ghana http://ugspace.ug.edu.gh Generally, the trend of annual rainfall in the last period is an indication that yearly prediction of rainfall pattern is becoming more difticult. The last seven years in the graph assumed a different trend all together where very wet years are experienced more often. This is usually not good for farmers because farming activities rather do well under normal rainfall conditions. Further, very wet periods could result in floods and this will have serious implications on the well-being of the people. The future trend of climate change is very important for the discussions in this study. Figure 2.10 is the climate change projection for the forest-savanna transition zone as estimated by the CCLONG Project in collaboration with the Alliance for Earth Science, Engineering and Development in Africa (AESEDA). The blue is the observed rainfall in the forest-savanna transition during 1961-2000 and the red line is the projected rainfall for 2046 to 2065. The projection starts from 2046 because predicting future climate change is made possible after looking at the situation after 40-45 years. Figure 2.10: Wenchi Seasonal Cycle, 1961-2000 and 2046-2065 ,--------------------------------------- Wenchi, Ghana: Seasonal Cycle (CCMA, CSIRO 3.5, MPI, MRI) -1961-2000 -2046-2065 ,nu. III ~~~~~~~~5~~~§~~~~~~~~~~~~ Day of the Year change = 13.7%increase Source: CCLONG, AESEDA, 2009 42 University of Ghana http://ugspace.ug.edu.gh The graph indicates that the forest-savanna transition zone experienced two rainfall seasons during the period 1961 to 2000. Rainfall in the transition zone begins slowly in January, has a broad peak from April to June, experiences a decline in July and begins to increase again in August. The zone then experiences a sharp peak of rainfall in September and begins to decline thereafter to December. The projections, however, indicate an increased rainfall in the transition zone throughout the year. The amount of rainfall experienced in each month presently is expected to increase in the future with peaks expected in May, July and September. The projections indicate the likelihood of some 13.7 percent increase in the amount of rainfall in the transition zone. There is also an indication that the broad peak that used to exist will change to two peaks in the future which is an indication of more rainfall in such months and the resultant consequences could be floods. Analysis of the temperature data collected from the meteorological services presents an overall increase in temperature from 1960 to 2004. Figures 2.11 and 2.12 indicate that both maximum and minimum temperatures have been increasing over the period. The highest temperature within the 1960-2004 period was recorded in the last decade as 32.3°C in 1998 (Figure 2.11). 43 University of Ghana http://ugspace.ug.edu.gh Fi ure 2.11: Trend in annual maximum tem erature, 1960-2004 Mean annual maximum temperature 1960-2004 over Forest/Savanna Transitional study area ::::: ~~ -~ --~--------~----H--- ~ .!: 31.50 2! :::I 1ii 31.00 +.A------Hr-:c- :u D- E ~ v = 0.0242x + 30.427 RZ =0 .4788 30.00 -1-- I 29.50 I 0 N <0 00 0 N 0 N <0 00 <0 <0 <""0 <0 <0 ,.... ,.... ",..".. ~ ~ 00 00 "0"0 00 00 Years ~ ~ e..n.. ~ ~ .e.n.. ~ ~ ~ ~ ~ ~ .e.n.. ~ ~ Source: Computed from temperature data from Ghana Meteorological Service Department (GMSD). Figure 2.12: Trend in Annual Minimum Temperature, 1960-2004 Figure 2.12: Trend in Annual Minimum Temperature, 1960-2004 22.50 22.00 ~ .!: 2! 21.50 ~ I.'! QI 21.00 D- E ~ 20.50 20.00 Y =0 .024Sx + 20.68 Z 19.50 R =0 .406 0 N "" <0 00 ,0<0 <0 <0 <0 <0 .. .. ,N... . ",..".. ,<..0.. 0,..0.. 0 N "" <0 00 0 N 00 00 00 00 00 en en e"n" <0 00 0 N en en 0 0 0 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ "" ~ ~ ~ ~ 0 0 N N Years Source: Computed from temperature data from Ghana Meteorological Service Department (GMSD). 44 University of Ghana http://ugspace.ug.edu.gh 2.10 Historical evidence of environmental events in the study communities A qualitative survey among 12 households in each of the communities revealed the following pattern of environmental conditions experienced by the people. In Bouku, the participating households noted that the hottest month of the year used to be February some three decades ago but this has changed to March within the last 10 years. They also noted that the heat that they experience in the month of March is more severe than what they used to experience previously in the month of February. They further revealed that the coolest months of the year used to be December and January formerly but of late the month of December is not as cool as it used to be. They noted, however, that the cold dry wind that usually brings the harmattan occurs in the month of December. In contrast, the data gathered in Bofie-Banda indicate that the hottest month in the community has been February over the past four decades. It also showed that the severity of the heat is higher presently than what pertained previously. The pattern of rainfall in the Bouku and Bofie-Banda communities as indicated by the households is shown in Table 2.2. The table indicates that previously, normal rains began in Buoku in the month of February and continued to March and then heavy rains in April. This is contrary to the present situation where slight rains are experienced in March and then followed by heavy rains in April. Also, whilst previously slight rains were experienced from June to August, the present pattern shows slight rains in June, no rain in July and normal rains in August. There is also slight rainfall in November and sometimes two separate rainfalls in December previously. Presently, there is no rain in November and December. 45 University of Ghana http://ugspace.ug.edu.gh Table 2.2: Present and Previous pattern of rainfall in the Buoku and Bofie-Banda commuD'lfle s Community Month I Jan Feb Mar Apr May Jun Jul Au!!: Sept Oct Nov Dec Current Buoku Pattern NR NR R* HR R R* NR R HR R NR NR Previous Pattern NR R R HR R R* R* R* HR R R* NR** Current Bofie- Pattern NR NR R R NR R* R* NR HR NR NR NR Banda Previous Pattern NR R HR R NR HR R NR R R NR NR Notes: NR= No ram, R= normal ram, HR= heavy ram or peak penod, R*- shght mtermlttent rain, NR * * - sometimes 2 rains Source: CCLONG Field data, 2007/2008 The present pattern of rainfall in Bofie-Banda on the other hand, is different from what pertained previously. Table 2.2 indicates that previously the rain used to begin in February with heavy rains experienced in March and normal rains in April. The present pattern of rainfall indicates that the community experiences normal rains in March and April and there is no rain in May just as it happened previously. Also, whilst heavy rains are experienced in June and normal rains in July previously, slight rains are experienced in June and July presently. Further, whilst normal rainfall was experienced in September and October previously, heavy rains are experienced in September and October presently. The table also shows that there is an early onset of rainfall in February in both communities presently which used to occur in the month of March previously. Further, heavy rainfalls were experienced in Buoku in April and September previously and the same thing is happening in the community presently. In Bofie-Banda on the other hand, heavy rainfalls were experienced in September previously but the current pattern shows that heavy rainfalls are experienced in March and June. The Bouku community experienced a number of environmental events and an interaction with households in the community revealed the following events. The most mentioned 46 University of Ghana http://ugspace.ug.edu.gh environmental event among the households visited was the 1983 drought. They indicated that the drought was very severe because there were no rains in October and November in 1982; the forest got burnt on 7th February, 1983; food crops in the field got burnt and access to drinking water was difficult. Subsequently, part of the forest in the area got burnt again in 1987 and in 1988 the entire forest was burnt when the community experienced a short drought. The 1988 burning of the forest prevented cars from passing through the town as a result of the burning flames. A number of houses got burnt and one person lost his life in it. A number of households had to relocate to the nearby villages to seek shelter. The participating households from Bouku noted that the severity of the damage of the 1988 burning of the forest was more widespread than that of 1983. Notwithstanding this, the forest got burnt again in 1995 but this time round it was not severe. In 1997, the community experienced a three-day continuous rainfall in the month of August which led to flooding. A number of houses collapsed as a result of the rain, roof. . got ripped off and streams and rivers overflowed their banks. The community also experienced another flood in 2006 due to a one-day stormy rainfall which also destroyed buildings. The major environmental events that were mentioned in the Bofie-Banda community are the 198211983 drought and the 1986 flooding in the month of September and October. They indicated that there were very poor rains in 1982 which led to very poor crop yields. As a result, the impact of the 1983 drought became very severe because they did not get enough food crops from the previous year to enable them stand the challenges of the drought. The drought led to severe hunger, drying up of wells, streams and rivers and they had to walk for long distances in search of water. They further narrated that the floods in 1986 took two months and most of their 47 University of Ghana http://ugspace.ug.edu.gh crops were destroyed as a result of that. They also noted that crops like yam and cassava were destroyed in the flood and they lost some animals such as cattle and poultry due to diseases that affected them after the flood. Some buildings in the community also collapsed as a result of the flood. The discussions above indicate that the forest-savanna transition zone is experiencing drastic changes with respect to rainfall, temperature and vegetation in general. It is important to note that, the vegetation cover of an area plays a very important role in determining the kind of rainfall pattern that will be experienced in such areas. Even though the forest savanna transition zone is noted to have a bi-modal rainfall pattern some years back, this is gradually turning into a uni-modal event. Communities that lie closer to the savanna belt of the district experience almost the same environmental consequences like those in the northern regions of Ghana. Being farming communities, addressing the issue of environmental events on the livelihood of the people is paramount in the era of climate change. It is obvious that the impact of climate variability is already being felt in these communities and it is important to understand how people have coped with the situation and how to harness the best adaptation strategies for the benefit of the communities and the district as a whole. 48 University of Ghana http://ugspace.ug.edu.gh CHAPTER THREE INTERNAL MIGRAT lON IN BRONG AHAFO AND SOCIO-DEMOGRAPHIC CHARACTERITlCS OF HOUSEHOLD HEADS 3.1 Introduction This chapter examines inter-regional migration to assess the flow of migration to and from Brong-Ahafo Region. Also, the pattern and trend of migration within the districts in Brong- Ahafo Region are discussed. It further examines the socio-demographic characteristics of the respondents in order to know the composition of the sampled population for the study. Other issues discussed in this chapter are age and sex distribution of household heads, marital status, educational attainment, the size and composition of households. The chapter further discusses the activity status of household members, migration status of household heads, stressors in the communities and the relationship between the independent variables and the dependent variable. 3.2 Patterns and Trends of Inter-Regional Migration Table 3.1 shows that apart from Central and Ashanti regions which had one of the highest proportions of non-migrants in 1984 and 2000 respectively, the three northern regions in Ghana, namely, Northern, Upper West and Upper East regions had the highest number of non-migrants for 1984 and 2000. This is an indication of the perceived low economic opportunities the three regions offer to the population in other regions. While the percentage of non-migrants in the three northern regions ranged from a minimum of 67 percent in 1984 to a maximum of 84 percent in 2000, the percentage of in-migrants into the three regions ranged from a minimum of 5.4 percent in 1984 to a maximum of six percent in 2000. All the three northern regions showed a decrease in the proportion of the population reported as in-migrants between 1984 and 2000. This could be attributed to the ethnic conflicts and the chieftaincy disputes that have been 49 University of Ghana http://ugspace.ug.edu.gh occurring in the three northern regions over the past three decades. In contrast, the Greater Accra Region is the highest recipient of in-migrants in Ghana: 36 percent in 1984 and 37 percent in 2000. The Greater Accra Region is, therefore, the most preferred destination of most migrants in Ghana, followed by the Western Region with an in-migrant figure of 29 percent and 26 percent respectively in 1984 and 2000. Next in line is the Brong Ahafo Region with the proportion of in-migrants standing at 25 percent and 20 percent respectively in 1984 and 2000. Table 3.1: Inter-Regional Migration Rates of Ghanaian Residence by Re2ion, 198 4-2000 Intra- Non- Regional In- Out- Region Mi2rants Migrants Mi2rants Mi2rants Net-Migrants 1984 2000 1984 2000 1984 2000 1984 2000 1984 2000 Western 54.1 56.0 16.9 9.2 28.6 26.1 24.5 8.8 4.1 17.3 Central 68.1 66.5 19.5 13.3 12.1 18.8 19.0 30.0 -6.9 -18.1 Greater Accra 55.3 48.1 7.9 6.0 36.1 37 24.8 7.0 11.3 30.0 Volta 65.9 71.4 24.1 17.0 9.0 6.7 17.5 32.6 -8.5 -25.9 Eastern 57.4 63.5 25.3 15.2 17.0 14.8 21.8 26.0 -4.8 -11.2 Ashanti 34.1 80.6 19.7 11.5 16.4 15.9 17.8 12.1 -1.4 3.9 Brong Ahafo 57.7 66.4 17.5 7.1 24.6 20.0 20.1 11.4 4.5 8.5 Northern 67.1 80.9 23.7 8.3 8.6 6.0 7.7 14.1 0.9 -8.1 Upper East 74.1 84.2 19.2 2.4 5.6 5.4 8.3 27.8 -2.7 -22.4 Upper West 68.7 78.9 23.7 10.0 6.2 5.8 6.9 39.5 -0.7 -33.7 Source: 1984 figures were extracted from Ghana MIgration Research Study 10 1991, GSS 1995; 2000 figures from 2000 Population Census The Brong Ahafo Region, like the other regions that received a lot of in-migrants also experienced substantial amounts of out-migration in 1984. This could partly be explained by the 1983 drought which had serious implications for farming communities across the country. It is, however, important to note that the Greater Accra and Western regions experienced a drastic decline in the volume of out-migration in 2000 compared to what pertained in the Brong Ahafo Region in the same year. Also, there was a drop in the percentage of in-migrants into the Brong 50 University of Ghana http://ugspace.ug.edu.gh Ahafo Region from 25 percent in 1984 to 20 percent in 2000 even though the region had one of the highest inflow of in-migrants compared to other regions. The question then is what is causing the reduction of the proportion of in-migrants in the region? One reason is that migrant cocoa farmers and farm labourers are increasingly moving to the Western Region where new frontier areas exist for cash crop farming activities compared to the Srong Ahafo Region. A study by Asiamah et al. (2000) has also shown gradual changes in the soil fertility and rainfall pattern in the forest-savanna transition zone which used to be a major detenninant of migration into the area. The net migration rate for the Srong Ahafo Region increased from five percent in 1984 to nine percent in 2000 due to a sharp decline in out-migration from Srong-Ahafo Region from 20.1 percent in 1984 to 11.4 percent in 2000. This is an indication that the Srong Ahafo Region has a net increase in the number of migrants, meaning the number of people migrating into the region exceeds those moving out of the region. The Greater Accra Region has the highest population of net-migrants of 11 percent in 1984 and 30 percent in 2000. This is followed by the Western Region with four percent in 1984 and 17 percent in 2000. In sum, the three regions (Greater Accra, Western and Srong Ahafo) have received more in-migrants than non-migrants indicating the potential economic opportunities the three regions are perceived to have that attract migrants. 3.3 Migration Streams Migration to and from the Srong Ahafo Region is very important to the study because it provides answers as to which region's population are attracted to the Srong Ahafo Region and which regions are the people of Srong Ahafo most attracted to. Five percent of the in-migrant population in the region are from the Upper West region. There is equally a substantial out- 51 University of Ghana http://ugspace.ug.edu.gh migration from Brong-Ahafo Region into the Upper West Region, constituting six percent of the population of out-migrants in the region. On the other hand, the Ashanti Region receives the highest number of out-migrants from the Brong Ahafo Region, constituting 13.5 percent of out- migration from the region. Generally, the destination of most migrants from the Brong Ahafo Region is the Ashanti Region with a net migration rate of -12.9 percent (Table 3.2). Table 3.2: Migration Streams of Ghanaian Residents To and From the Brong Ahafo by regI.O n, 20 00 Brong Ahafo (% of Brong Ahafo resident population) In- Out- Gross Migration Migration Net-Mil! ration Interchange Regions Volumes % Volumes 0/0 Volumes 0/0 Volumes % Western 15,315 0.8 63,511 3.5 -48,196 -2.7 78,826 4.3 Central 13,645 0.8 7,969 0.4 5,676 0.3 21,614 1.2 Greater Accra 28,995 1.6 33,772 1.9 -4,777 -0.3 62,767 3.5 Volta 18,762 1.0 4,906 0.3 13,856 0.8 23,668 1.3 Eastern 69,930 3.9 10,783 0.6 59,147 3.3 80,713 4.4 Ashanti 11,939 0.7 245,681 13.5 -233,742 -12.9 257,620 14.2 Northern 59,696 3.3 132,919 7.3 -73,223 -4.0 192,615 10.6 Upper East 54,580 3.0 77,288 4.3 -22,708 -1.3 131,868 7.3 Upper West 90,397 5.0 108,974 6.0 -18,577 -1.0 199,371 1.1 Source: Computed from the 2000 PopulatIOn and Housmg Census of Ghana The movement of people from the Brong Ahafo Region to the Greater Accra, Ashanti and Western regions could be as a result of the availability of economic opportunities in these regions compared to the Brong Ahafo Region. With regard to the flow of migrants from Brong Ahafo Region to the three northern regions, the arong Ahafo Region is strategically closer to the 52 University of Ghana http://ugspace.ug.edu.gh three northern regions and with this proximity; it facilitates inter-marriages and economic activities among the three regions. Analysis of life-time intra-regional migration in the Brong Ahafo Region shows that the volume of in-migrants that entered the Wenchi District is slightly more than the volume of people that migrated out of the district into other districts. Thus, the net flow of migration from the Wenchi District is 0.1 percent as indicated in Table 3.3. Table 3.3: Life-Time Intra-Regional Migration Rates (%)by and Migration flows, 2000 (Brong Abafo) In- Out- Net- Native migrants Rates migration Rates migration Rates Region Population Volume (%) Volume (%) Volume (%) Asunafo 143,095 1,971 1.4 2,052 1.4 (81) 0.1 Asutifi 70,952 1,813 2.6 1,550 2.2 263 0.4 Tanoso 104,519 2,492 2.4 1,543 1.5 949 0.9 Sunyani 156,030 3,309 2.1 3,017 1.9 292 0.2 Dormaa 129,089 1,800 1.4 2,163 1.7 (363) -0.3 Jaman 126,060 1,182 0.9 1,239 0.9 (57) 0.0 Berekum 79,099 1,386 1.8 2,334 3.0 (948) -1.2 Wencbi 140,204 2,422 1.7 2,328 1.7 94 0.1 Tecbiman 148,616 3,044 2.0 2,372 1.6 672 0.4 Nkoranza 108,388 1,868 1.7 2,972 2.7 (111) -1.0 Kintampo 121,472 1,413 1.2 2,073 1.7 (660) -0.5 Atebubu 135,394 2,075 1.5 1,458 1.0 617 0.4 Sene 67,726 951 1.4 818 1.2 133 0.2 Source. Computed from PopulatlOn and Housmg Census, 2000 53 University of Ghana http://ugspace.ug.edu.gh 3.4 Socio-Demographic Characteristics of Respondents 3.4.1 Age and Sex Composition of Household Heads There were more male-headed households in the study communities than female-headed households as indicated in Table 3.4. In all, 65 percent of the respondents from Bouku and 61 percent of those from Bofie-Banda were males. This compares with 35 percent from Buoku and 39 percent from Bofie-Banda who were females. Sixteen percent of the male-headed households in Buoku were of ages 25-29 years, 13 percent were aged 40-44 years, 11 percent were 30-34 years and the remaining age groups each was represented by less than 10 percent. In Bofie- Banda on the other hand, 13 percent of the male-headed households were aged 25-29 years, 11 percent were aged 30-34 years and the remaining age groups recorded less than 10 percent each. Female-headed households in both communities constituted less than 10 percent of respondents across all the age groups. Further, more than half (59 percent) of household heads in Bouku and 44 percent of their counterparts in Bofie-Banda were less than 40 years of age. This indicates that, the responsibility of most of the households lies in the hands of young adults. 54 University of Ghana http://ugspace.ug.edu.gh Table 3.4: Percentage distribution of respondents by sex and ~e gouJ!. Age Bouku Bofie-Banda group Male Female Total Male Female Total 20-24 - 3 3 1 2 3 25-29 16 7 23 13 1 14 30-34 11 9 20 11 5 16 35-39 8 5 13 8 3 11 40-44 13 2 15 6 3 9 45-49 9 2 11 5 5 10 50-54 5 5 10 8 7 15 55-59 - 1 1 2 3 5 60-64 - 1 1 3 1 4 65-69 1 1 2 70+ 3 3 3 8 11 Total 65 35 100 61 39 100 N 65 35 100 61 39 100 Source: CCLONG, 2009 3.4.2 Marital Status of Household Heads Table 3.5 indicates that more than half (58 percent) of the respondents from Bouku and 59 percent of the respondents from Bofie-Banda were currently married whilst 26 percent of the respondents in both communities had r.ever married. It further indicates that four percent of the respondents from Buoku were divorced, seven percent were widowed, four percent reported to be separated and one percent were cohabiting whilst 13 percent of the respondents from Bofie- Banda were widowed and two percent were divorced. These characteristics of the individual households have implications for the welfare of the family and their responses to social challenges. People who are single are more likely to have the liberty to take certain decision on their own without having to seek for the concern of anybody. This makes such people very mobile at the least opportunity. Married people on the other hand, would have to seek the consent of a partner before embarking on migration. In this sense, it could be one of the couples 55 University of Ghana http://ugspace.ug.edu.gh migrating or both migrating at the same time. In some instance, the entry into marital union will demand that one member of the couple migrates to join the other. T able 3.5: Percenta2e distribution of respondents b) y curren marl't a I status Buoku Bofie-Banda Marital Status % % Single 26 26 Married 58 59 Separated 4 0 Divorced 4 2 Widowed 7 13 Cohabiting 1 0 Total % 100 100 N 100 100 Source: CCLONG, 2009 3.4.3 Educational Attainment of Heads of Household The educational level of an individual determines hislher ability to take certain decisions and also the possibility of being able to secure employment in another environment. The educational level of individuals, therefore, plays important roles in migration studies. Analysis of the educational attainment of respondents from Bouku indicates that a little over half (51 percent) of the males and 37 percent of the females had attained Middle/JSS education (Table 3.6). It also indicates that 46 percent of the females and 40 percent of the males had not had any fonn of education. This is different from what pertained at Bofie-Banda where 80 percent of the females and 61 percent of the males had never had any form of education. Also, only 21 percent of the males and 10 percent of the females in Bofie-Banda had attained Middle/JSS education in comparison with Bouku. 56 University of Ghana http://ugspace.ug.edu.gh Table 3.6: Percentage distribution of respon d ents b) y sex an d e d ucaf Jo nal attainment Bouku Bofie-Banda Marital Status Male Female Total Male Female Total None 40 45.7 42 60.7 79.5 68 Primary 6.2 8.6 7 11.5 7.7 10 Middle/JSS 50.8 37.1 46 21.3 10.3 17 Secondary/SSS 1.5 5.7 3 6.6 2.6 5 Higher 1.5 2.9 2 - - - Total % 100.0 100.0 100.0 100.0 100.0 100.0 N 65 35 100 61 39 100 Source: Survey Data, 2009 3.4.4 Household Size and Composition The average household size for Bouku is 4.4 whilst that of Bofie-Banda is 5.5. There were 337 household members (other than the heads) constituting the 100 households that were sampled from Bouku whilst that of Bofie-Banda recorded 446 household members. More than half of the household members in both Bouku (70 percent) and Bofie-Banda (57 percent) were less than 20 years of age. Less than five percent of the respondents were 60 years and above for both Bouku and Bofie-Banda communities. In both communities, there were more males in the households than females. Males constituted more than half of household members in Bouku (54 percent) and Bofie-Banda (51 percent) whilst females constituted 46 percent and 49 percent of household members respectively in Bouku and Bofie-Banda. 57 University of Ghana http://ugspace.ug.edu.gh Figure 3.1: Population pyramid of household members by age and sel' Buoku Bohe-Banda 3.4.5 Characteristics of households by migration status Household heads playa very significant role in the decision to migrate at the household level. The head of a household is in most cases the controller of household resources and is the most important figure when it comes to making decisions concerning household resources. Access to resources is also determined by the sex of the head of the household. In most cultures in Ghana, community resources are usually owned and controlled by males. Further, access to community resources depends on whether one is a migrant or a native. Table 3.7 shows that 48 percent of the household heads from Buoku and 49 percent from Bofie-Banda were migrants whilst 52 percent of the household heads from Buoku and 51 percent from Bofie-Banda were non-migrants. Among the female migrants in Buoku, more than half (58.8 perent) were below age 40 compared to their counterparts in Bofie-Banda among whom 40 percent were below age 40. With regard to the male migrants in Buoku, more than half (58.1 percent) were below age 40 whilst 50 percent of the male migrants in Bofie-Banda were below age 40. Forty-nine percent of 58 University of Ghana http://ugspace.ug.edu.gh the non-migrants from Bofie-Banda were aged 50 years and above compared to 13.5 percent in Buoku. Table 3.7: Percentage distribution of household heads by age group, sex and migration status Migration Total Community Status 20-29 30-39 40-49 50+ % N Buoku Migrant Male 22.6 35.5 29.0 12.9 100.0 31 Female 23.5 35.3 17.6 23 .5 100.0 17 Total 22.9 35.4 25 .0 16.7 100.0 48 Non-migrant Male 26.5 23.5 38.2 11 .8 100.0 34 Female 33.3 44.4 5.6 16.7 100.0 18 Total 28.8 30.8 26.9 13 .5 100.0 52 Bofie-Banda Migrant Male 29.4 41.2 11.8 17.6 100.0 34 Female 0.0 40.0 20.0 40.0 100.0 15 Total 20.4 40.8 14.3 24.5 100.0 49 Non-migrant Male 14.8 18.5 25.9 40.7 100.0 27 Female 12.5 8.3 20.8 58.3 100.0 24 Total 13.7 13.7 23.5 49.0 100.0 51 Source: CCLONG, 2009 The movement of people from their current place of residence to another community is partly explained by whether they are natives or migrants in their present community. In most instances, natives would develop some level of attachment to their communities and so may not migrate in the event of an environmental impact which may have implication on their source of livelihood. On the other hand, even if they migrate, most of them will embark on a short distance migration and return to the community in a short period of time. However, migrants are deemed to immediately migrate from the community in the event of climate related environmental event that impacts on their livelihood because, they may have little or no attachment to the community. 59 University of Ghana http://ugspace.ug.edu.gh 3.5 Stressors in the study communities Table 3.8 presents the stressors in the communities as reported by respondents. In Bofie- Banda for instance, 84 percent of the respondents mentioned irregular rainfall as a major stress to their livelihood whilst 54 percent of the respondents in Buoku mentioned irregular rainfall as a stress to their livelihood. Seventy three percent of the respondents in Buoku indicated that unemployment and poverty are a stress to their livelihood whilst 27 percent and 57 percent of the respondents in Bofie-Banda respectively indicated that unemployment and poverty affected their livelihood. Also, while 23 percent of the respondents in Bofie-Banda indicated that bushfire was a stress to their livelihood, only two percent of the respondents in Buoku indicated that bushfire was a stress to their livelihood. Generally, the stressors in the study communities range from socio-economic to environmental issues. Table 3.8: Percentae:e distribution of community stressors by study a rea Bofie-Banda Buoku Conununity Stressors Yes No Total % Yes No Total % Irregular rainfall 84 16 100 54 46 100 Bushfire 23 77 100 2 98 100 Poor soil fertility 8 92 100 2 98 100 Poor heath service 53 47 100 16 84 100 Unemployment 27 73 100 73 27 100 Education 10 90 100 9 91 100 Poverty 57 43 100 73 27 100 Other 7 93 100 12 88 100 Source: CCLONG, 2009 3.6 Place of destination of climate-related migrants Generally, only a few of respondents migrated as a result of experience of climatic events in the past. In Table 3.9, nine respondents from Buoku and five from Bofie-Banda migrated 60 University of Ghana http://ugspace.ug.edu.gh during past extreme climatic events. In Buoku Clor 'I nstance, the m'l gra1 "1 0 n that was embarked on by the respondents was internal and they lived away for one to three years. However, in Bofie- Banda, 60 percent of the migrations were internal and 40 percent were international. Buoku is closer to Wenchi, Techiman and Kurnasi and that reflected in the direction of the migrants from Buoku whilst Bofie-Banda is closer to the northern part of Cote d'Ivoire. Table 3.9: Percentage distribution of respondents by place migrated to Buoku Bofie-Banda Place migrated to % % Accra 11.1 0.0 Kumasi 66.7 60.0 Techiman 11.1 0.0 Wenchi 11.1 0.0 Cote d'Ivoire 0.0 40.0 Total % 100.0 100.0 N 9 5 Source: CCLONO, 2009 3.7 Relationship between explanatory variables and the intention to migrate 3.7.1 Experience of Environmental Events Table 3.10 indicates that among the households that experienced some form of environmental events and had the intention to migrate in Buoku, 35.1 percent of them were those who experienced both flood and drought whilst in Bofie-Banda 30 percent of those who experienced both had the intention to migrate. It further revealed that among household that experienced drought in Bofie-Banda, 60 percent of them had the intention to migrate whilst 52.4 percent of the households that experienced drought in Buoku had the intention to migrate. Apart 61 University of Ghana http://ugspace.ug.edu.gh from the exposure to drought which may trigger more households to migrate from Bofie-Banda than Bouku, the experience of only flood or both flood and drought will trigger more people to migrate from Bouku than Bofie-Banda. This may be explained by the fact that, the Bofie-Banda community has a savanna characteristics and the impact of a drought will be more felt than Buoku which has a forest characteristics. The Buoku community on the other hand has recent history of climate-related environmental events such as flood events in 1997 and 2006 and burning of the community forest in 1983, 1988 and 2005. The damage caused by these events might have influenced the response of the community with regards to exposure to flood and frequent experience of both flood and drought. Table 3.10: Percentage distribution of experience of environmental events by households by I.D t enh. on t o mi.g rate Intention to migrate Environmental Event Buoku Bofie-Banda Yes No Total N Yes No Total N Flood 68.2 31.8 100.0 22.0 30.4 69.6 100.0 23 Drought 52.4 47.6 100.0 21.0 60.0 40.0 100.0 35 Flood and Drought 35.1 64.9 100.0 57.0 28.6 71.4 100.0 42 Total 46.0 54.0 100.0 100 40.0 60.0 100.0 100 x2 =7.434 Sig.O.024 l =8.996 Sig.O.Oll Source: CCLONG, 2009 There is a statistical association (Buoku: X2 =7.434 Sig. 0.024 and Bofie-Banda: X2 =8.996 Sig. 0.011) between experience of an environmental event and the intention to migrate in both communities. This is an indication that environmental events playa role in the decision to migrate in the study communities. 62 University of Ghana http://ugspace.ug.edu.gh 3.7.2 Distribution of Household Heads by Age and Intention to migrate Age of household head plays a very significant role in the decision to migrate in both study communities as presented in Table 3.11 (Buoku: X2 =16.941 Sig. 0.000 and Bofie- Banda: ./ =26.260 Sig. 0.000). The age of the migrant is also important to be able to take advantage of the opportunities at place of destination. Hence, migration selectivity in terms of productive capacity, age composition can have significant demographic, social and economic impacts on both the source and destination areas (GSS, 2005). Table 3.11 further reveals that more than two-thirds of the household heads in both communities (67.4 percent in Buoku and 75.8 percent in Bofie-Banda) who had the intention to migrate were aged 20-34 years. The intention to migrate decreases as the age of the household head increases in Bofie-Banda whilst that of Buoku fluctuates from one age group to the other. For instance, among household heads who were aged 50 years and above, 40 percent had the intention to migrate in Buoku while 21.6 percent had the intention to migrate in Bofie-Banda. Usually, household heads, who are 50 years and above would wish to have most of the economically active members of the household around them to support them in their economic activities. Younger adults are however, more likely to migrate because they have the strength to withstand the challenges that migrants go through at place of destination. The following are the views of the youth in Buoku and Bofie- Banda communities on whether they will migrate from the community in the event of climate- related environmental events. "Why should we spend all our youthful life in this community if there is nothing to show for it? Life in this community is about how much money you have to take care of your family. We do not earn much from farming these days and it will be unwise to live here and let our family starve. The elders in this community will insult you if you are not able to care for your family." (Focus group discussion with the youth of Buoku). "The. only economic activity here is farming and the current trend of rainfall is making farmmg unprofitable. As young men, we cannot continue to live is such a situation when 63 University of Ghana http://ugspace.ug.edu.gh we know that there are opportunities in other places we can take ad~antage of. The elderly in this community can continue to live here but we need to ~I1Igrat.e and. make some money and corne and develop the community." (Focus group dIscuSSIOn wIth the youth of Bofie-Banda). Table 3.11: Percentae;e distribution of Al?;e of Household heads bv Intention to ml' grate Intention to migrate Age of Head of Bofie-Banda Household Buoku Yes No Total N Yes No Total N 20-34 67.4 32.6 100.0 46 75 .8 24.2 100.0 33 35-49 23.1 76.9 100.0 39 23.3 76.7 100.0 30 50+ 40.0 60.0 100.0 15 21.6 78.4 100.0 37 Total 46.0 54.0 100.0 100 40.0 60.0 100.0 100 x2 =16.941 Sig. O.OOO x2 =26.260 Sig. 0.000 Source: CCLONG, 2009 3.7.3 Educational Attainment of Household Heads and the Intention to Migrate Table 3.12 presents the educational attainment of household heads and their intention to migrate. Among the household heads in Buoku who had JHS/Higher education, 47.1 percent had the intention to migrate whilst 50 percent of household heads in Bofie-Banda with JHSlHigher education had the intention to migrate. Among household heads with PrimarylNo education in Buoku, 44.9 percent had the intention to migrate as compared to 37.2 percent of their counterparts in Bofie-Banda. There is no statistically significant association between level of education of household head and the intention to migrate at alpha level of 0.05 . This could be explained by the relatively low level of education among the sample population even though some literature have indicated a statistically significant association between level of education of household head and the intention to migrate. 64 University of Ghana http://ugspace.ug.edu.gh Table 3.12: Percentage distribution of Household Head Level of Education by Intention to Mie:rate Intention to migrate Level of Buoku Bofie-Banda Education Yes No Total % N Yes No Total % N Primary/No Education 44.9 55.1 100.0 49 37.2 62.8 100.0 78 JHSlHigher 47.1 52.9 100.0 51 50.0 50.0 100.0 22 Total 46.0 54.0 100.0 100 40.0 60.0 100.0 100 x2 2 =0.047 Sig. 0.828 x =1.175 Sig. 0.278 Source: CCLONG, 2009 3.7.4 Marital Status of Household Heads and the Intention to Migrate The percentage distribution of household heads by their current marital status and intention to migrate is presented in Table 3.13. Marital union has its own social norms which demand that couples live together. People who are married/cohabiting do not easily migrate compared to those who are not in union. Table 3.13 indicates that among household heads who are married/cohabiting in Buoku, 30.5 percent had the intention to ; the same percentage of married/cohabiting households in Bofie-Banda had the intention to migrate. With regard to households that are not in union, 68.3 percent of those in Buoku had the intention to migrate as compared to 53.7 percent of their counterparts in Bofie-Banda. There is statistical association (Buoku: X2 =13.903 Sig. 0.000 and Bofie-Banda: X2 =5.402 Sig. 0.020) between marital status of household head and the intention to migrate. This indicates that the decision to migrate at the household level in the event of a climate-related environmental event in both communities depends on the marital status of the household head. 65 University of Ghana http://ugspace.ug.edu.gh Table 3.13: Percentage distribution of marital Status of household heads by Intention to mi2rate Intention to migrate Marital status Buoku Bofie-Banda Yes No Total % N Yes No Total % N Married/cohabiting 30.5 69.5 100.0 59 30.5 69.5 100.0 59 Not in union 68.3 31.7 100.0 41 53.7 46.3 100.0 41 Total 46.0 54.0 100.0 100 40.0 60.0 100.0 100 x2 =13 .903 Sig.O.OOO x2 =5.402 Sig.0.020 Source: CCLONG, 2009 3.7.5 Sex of Household Heads and the Intention to Migrate The sex of a person plays a very important role in decision making at the household level. In most Ghanaian societies the male is usually given preferences in telms of family inheritance and access to opportunities. Whilst there is no statistical association (X2 =2.692 Sig. 0.101 ) between sex of household head and the intention to migrate in Buoku, there is a statistical association (X2 =7.629 Sig. 0.006) between the sex of the household head and the intention to migrate in Bofie-Banda. Table 3.14 shows that among the male headed households in Buoku. 40 percent of them had the intention to migrate as against 50.8 percent of their counterparts in Bofie-Banda. More than half (57.1 percent) of female headed households in Buoku had the intention to migrate whilst 23.1 percent of female headed households in Bofie-Banda had the intention to migrate. Whilst more male headed households in Bofie-Banda expressed their interest to migrate, more females in Buoku expressed their interest to migrate. 66 University of Ghana http://ugspace.ug.edu.gh Table 3.14: Percentage distribution of sex of bousebold beads by Intention to migrate Intention to migrate Bofie-Banda Sex of Household Buoku Head Yes No Total % N Yes No Total N Male 40.0 60.0 100.0 65 50.8 49.2 100.0 61 Female 57.1 42.9 100.0 35 23.1 76.9 100.0 39 Total 46.0 54.0 100.0 100 40.0 60.0 100.0 100 x2 x2 =2.692 Sig.0.l01 =7.629 Sig. 0.006 Source: CCLONG, 2009 3.7.6 Housebold Income and the Intention to Migrate Table 3.15 presents the relationship between income of household and the intention to migrate. Income of household plays a significant role (X2 =8.550 Sig. 0.003 ) in the decision to migrate in Buoku whilst it does not playa significant role (X2 =1.648 Sig. 0.199) in Bofie-Banda. Buoku is located on the highway to Sunyani, the capital of Brong Ahafo Region and it is also closer to Kumasi, the capital of Ashanti Region. Majority of potential migrants in Buoku expressed the interest in migrating to place where they will begin something new in their life and this requires some capital to be able to do so. In Bofie-Banda on the other hand migration from the community is just moving from one farming environment to another. Migration from the community, therefore, does not require much income. Table 3.15: Percentage distribution of household Income by Intention to migrate Intention to migrate Income of Buoku Bofie-Banda Household Yes No Total % N Yes No Total N <2000 67.7 32.3 100.0 31 35.4 64.6 100.0 65 2000+ 36.2 63.8 100.0 69 48.6 51.4 100.0 35 Total 46.0 54.0 100.0 100 40.0 60.0 100.0 100 x2 =8.550 Sig. 0.003 x2 =1.648 Sig. 0.199 Source: CCLONG, 2009 67 University of Ghana http://ugspace.ug.edu.gh 3.7.7 Household Size and Intention to Migrate 2 There is a statistically significant association (Buoku: X ==14.966 Sig. 0.001 and Bofie- Banda: X2 =14.282 Sig. 0.001 ) between size of household and the intention to migrate in both communities. Table 3.16 indicates that among households with less than three members in Buoku, 75.9 percent had the intention to migrate as against 69 percent of their counterparts in Bofie-Banda. Table 3.16 further indicates that the percentage of households with the intention to migrate decreases with the increase in size of the household in both communities. This may be explained by the fact that an increase in household size will lead to an increase in household expenditure. Therefore, an increase in household size will make it impossible for households to save enough money to be able to support an individual to migrate. Table 3.16: Percentage distribution of household size by Intention to migrate Intention to migrate Household Size Buoku Bofie-Banda Yes No Total N Yes No Total N <3 75.9 24.1 100.0 29 69.0 31.0 100.0 29 3-5 36.6 63.4 100.0 41 28.6 71.4 100.0 28 6+ 30.0 70.0 100.0 30 27.9 72.1 100.0 43 Total 46.0 54.0 100.0 100 40.0 60.0 100.0 100 X2 =14.966 Sig.O.OOl X2 =14.282 Sig.0.001 Source: CCLONG, 2009 68 University of Ghana http://ugspace.ug.edu.gh CHAPTER FOUR CLIMATE VARIABILITY, MIGRATION INTENTION AND THE FUTURE OF RURAL HOUSEHOLDS 4.1 Introduction This chapter discusses the drivers of migration and of climate change, and the relationship between climate-related environmental events and migration. Also, the chapter discusses some of the adaptation strategies the study communities used in previous climatic events and how efficient these strategies may be in the future if a similar event were to happen. Further, the chapter draws some conclusions from the climate change projection that was done by the CCLONG Project and its implications for the livelihood of the study population. 4.2 Causes and Consequences of Climate Change and Migration Climate change manifests itself in a number of ways depending on the geographical location of an area. In the two study communities, climate change manifests itself in the form of floods and droughts. The drivers of climate change as mentioned by the people of Buoku are continuous cropping, land degradation, logging for timber, bush burning, over population, land disputes, and degraded land whilst those mentioned in Bofie-Banda are charcoal production, bush burning, non-observance of local taboos, the making of God or gods. With regard to the effects of climate change, the following were mentioned in Buoku: flood, hunger, poor yield, poverty, no drinking water, and poor rainfall. The effects of climate change as mentioned by the people of Bofie-Banda are poor yields, drying of streams, poor soil, death of livestock, hunger and sickness. 69 University of Ghana http://ugspace.ug.edu.gh The causes of migration as mentioned in both communities are economic, social, political and environmental. In the study communities, most of the respondents who had the intention to migrate in future if the situation did not change were all fanners and their main source of livelihood depended on nature. Thus, if the rains fail, fanners in the communities will not be able to do anything because there are no irrigation facilities in the study communities. 4.3 Community Adaptation Strategies to Extreme Climatic conditions Communities were asked about how they coped with past extreme climate events in their community and their views on the efficiency of the coping strategy if a similar event were to occur in the future. Table 4.1 shows that about 77 percent of the respondents from Buoku depended on family/friends compared with 19 percent of the respondents from Bofie-Banda. Creation of fire belts to protect fann produce from being destroyed by fire was done in Bofie- Banda. Ten percent of the male respondents from Bofie-Banda and 16 percent of their female counterparts traded in shea butter in Cote d'Ivoire during the 1983 drought. Further, 16.3 percent of the respondents from Bofie-Banda and 11 percent of those from Buoku prayed to God to intervene for them and some of them did practically nothing about it. 70 University of Ghana http://ugspace.ug.edu.gh Ta ble 4.1: Percentage distribution of communityresponses to envlronmen tal stress by sex Bofie-Banda Buoku Response to sex of respondent environmental stress Male Female Total Male Female Total Migrated 5.0 2.6 4.1 12.2 12.5 12.3 Went into different employment 3.3 2.6 3.1 0.0 0.0 0.0 Depended on support from family/friends 8.3 36.8 19.4 81.6 66.7 76.7 Create fire belt 43.3 21.1 34.7 0.0 0.0 0.0 Traded in shea butter in cote d'Ivoire 10.0 15.8 12.2 0.0 0.0 0.0 Travel long distance for water 5.0 5.3 5.1 0.0 0.0 0.0 Depended on cassava 5.0 5.3 5.1 0.0 0.0 0.0 Other 20.0 10.5 16.3 6.1 20.8 11.0 Total % 100.0 100.0 100.0 100.0 100.0 100.0 N 60 38 98 49 24 73 Source: CCLONG, 2009 4.4 The Impact of Climate Change on Migration Table 4.2 presents the results of the hierarchical analysis of variance of the intention to migrate by household members in Bouku, with household perception of current coping strategies in the future and migration status as covariates and the other variables as explanatory variables. The hierarchical analysis of variance show which of the independent variables are significant predictors in explaining the differences in the dependent variable. It indicates that the age of the household head explains a significant variation in the intention of a household member to migrate. It seems that climate related environmental events are also an important predictor explaining differences in the intention to migrate by a household member. The analysis reveals that household size and sex of head of household are significant predictors of intention to migrate at the household level whilst income of household, level of education of the head of 71 University of Ghana http://ugspace.ug.edu.gh household and hislher marital status are not important predictors in explaining the variations in the intention to migrate at the household level. Table 4.2: Analysis of variance of the effects of climate-related environmental events and other ex~lanato!]': variables on the inclination to migrate, Bouku Hierarchical Method Sum of Mean Significance Source of Variation Sguares DF Sguare F ofF Main Effects (Combined) 8.475 12 0.706 3.754 0.000 climate related environmental events 1.847 2 0.923 4.909 0.010 age of household head 2.963 2 1.482 7.876 0.001 size of household 1.216 2 0.608 3.232 0.044 income of household 0.590 0.590 3.139 0.080 level of education head of household 0.105 0.105 0.557 0.457 sex of household head 0.775 0.775 4.120 0.045 marital status of head of household 0.067 0.067 0.354 0.554 Covariates perception of current coping strategy in the future 0.527 0.527 2.799 0.098 migration status 0.385 0.385 2.048 0.156 Model 8.475 12 0.706 3.754 0.000 Residual 16.365 87 0.188 Total 24.840 99 0.251 Source: Computed from CCLONG, 2009 The MCA results for Buoku community in Table 4.3 indicates that about 30 percent of the variation in the intention to migrate is explained by the additive effects of climate related environmental events, income of household, age of head of household, level of education, marital status, sex of head of household and the size of the household. However, 34 percent of the variation in the intention to migrate is explained by the additive effect of all factors and covariates. It further shows that the effect of climate related environmental events on the 72 University of Ghana http://ugspace.ug.edu.gh intention to migrate is reflected by the fact that households that have been exposed to only flood or drought have a negative mean deviation of -0.017 and -0.035 respectively after controlling for the effects of income, age of household head, level of education of household head, marital status of household head, sex of household head, size of household and the covariates (perception of current coping strategy in the future and migration status). Table 4.3: Relationship between climate related environmental events and other explanatory variables and the inclination to migrate, Buoku Deviation from the Grand Mean Adjusted for independents Adjusted for and Variable + Category Unadjusted independents covariates Climate related environmental events: Flood - 0.222 - 0.117 - 0.017 Drought - 0.064 -0.019 - 0.035 Flood and Drought +0.109 +0.052 +0.019 (Eta and beta) (0.273) (0.137) (0.046) Income: < 2,000 - 0.217 - 0.094 - 0.053 2,000+ +0.098 +0.042 +0.024 (Eta and beta) (0.292) (0.127) (0.071) Age of head of household: 20-34 -0.214 - 0.147 - 0.150 35-49 +0.229 +0.145 +0.180 50+ +0.060 +0.075 - 0.006 (Eta and beta) (0.412) (0.277) (0.304) Level of education of head of household: Primary/lower +0.011 - 0.031 +0.007 JHSfHigher - 0.011 +0.029 - 0.006 73 University of Ghana http://ugspace.ug.edu.gh (0.022) (0.060) (0.013) (Eta and beta) Marital status of head of household: Married/cohabiting +0.155 +0.043 +0.034 Not in union - 0.223 - 0.062 - 0.049 (Eta and beta) (0.373) (0.104) (0.175) Sex of household head: Male +0.060 +0.055 +0.064 Female - 0.111 - 0.102 - 0.119 (Eta and beta) (0.164) (0.150) (0.175) Size of household: <3 - 0.299 -0.114 -0.149 3 - 5 +0.094 +0.103 +0.111 6+ +0.160 - 0.031 - 0.008 (Eta and beta) (0.387) (0.184) (0.215) MultipleR 0.547 0.584 R2 0.299 0.341 Source: Computed from CCONG, 2009 On the other hand, households that have been exposed to both floods and droughts have a positive deviation (+0.019) after controlling for other explanatory variables and covariates. As the results indicate, households that have been exposed to both floods and droughts are those who may have the intention to migrate among people who live in an environment that is typical of forest vegetation. Thus, in such an environment, exposure to only floods or droughts will not trigger people to migrate because there will always be some other alternative ways of adjusting to the situation. 74 University of Ghana http://ugspace.ug.edu.gh It is also observed from Table 4.3 that the betas decrease from 0.273 to 0.137 after controlling for other explanatory variables and further to 0.048 after controlling for other explanatory variables and covariates. A focus group discussion with elders in the community to discuss slow changes in the climate on July 4th, 2009, indicates that members in the community are able to deal easily with just one climate related environmental event like either flood or drought. It was realised that climate related environmental events become difficult to address when communities are not able to predict its occurrence. A 57-year old maize farmer in the community noted: "We experience at least one climate-related environmental event in this community after every five years some four decades ago. What happened was that when we experience flood in a particular year, then we expect to experience drought in the next five years after that. This trend of events made it possible for us to plan the type of crops to cultivate. The situation has been different over the past decade where floods and droughts occurred in this community unexpectedly. This is really making farming a very difficult business". The results also show a very interesting relation between income and the intention to migrate and again between age of the head of the household and the intention to migrate. Households with annual income of less than GH¢2,000 had a negative mean deviation (-0.053) while households with annual income of GH¢2,000 and above had a positive mean deviation (+0.024). This implies that migration is not just embarked upon by those who are poor but those who have the means to support themselves for the first few weeks at place of destination. Even though most of those in the lower income bracket will be willing to migrate, they cannot do so easily because they need some money to take care of themselves for the first few days at place of destination before probably getting a job. Households with heads aged 20-34 have a negative mean deviation (-0.150) whilst households with heads who are 35-49 years old have a positive mean deviation (+0.180) after controlling for other explanatory variables and covariates. Most of 75 University of Ghana http://ugspace.ug.edu.gh those in the age category 20-34 are single households and as a result may not feel the difficulty of the economic challenges that may have come about as a result of climate related environmental events in the community because they have fewer or no family members to cater for. The Buoku community has a number of quarry companies that provide employment to some youth in the community. Those in the age group 35-49 years old are either married or ever been in a union and so will be faced with the responsibility of large household sizes. In such situations, the temptation may be that, the household head will encourage members to migrate to other places first; to reduce the number of mouths to feed in the household and also to work and send some remittances to the family back home. Other significant explanatory variables such as sex of the head of the household and the size of the household also have varying effects on the intention to migrate. In terms of sex, males have a positive mean deviation (+0.064) whilst females have a negative mean deviation (-0.119). A focus group discussion with elders in the community indicated that the community encourages male migration more than that of females . An elderly woman noted: "Women are very fragile and they cannot just sleep at any place when they move out of this community without actually knowing who they are going to live with. Men are able to do hard work like construction works when they get to the city and they are able to support families here". Results on size of household indicate that households with a size of less than three have a negative mean deviation (-0.149); households with a size of 3-5 have a positive mean deviation (+0.111) compared to households with a size of six and above which has a negative mean deviation (-0.008). Thus, households with a size of less than three will not be encouraged to migrate because the economic burden of having to cater for the family may be less than household with more than three members. Households with large sizes might not migrate 76 University of Ghana http://ugspace.ug.edu.gh because it will be difficult to move all members. However, households with a size of 3-5 members may migrate because such numbers are manageable than larger ones. Table 4.4 presents the results of the hierarchical analysis of variance of the intention to migrate by household members in Bofie-Banda, with household perception of current coping strategy in the future and migration status as covariates and the other variables as explanatory variables. Similar to what pertained in Buoku, the results from Table 4.4 indicate that the age of the head of the household explains a statistically significant variation in the intention to migrate by a household member. Also, climate related environmental event is a significant predictor explaining the differences in the intention to migrate by a household member. Table 4.4 further indicates that the level of education of the head of the household, income, size of the household, sex of the head of household intention and marital status of the head of the household were not significant predictors on the intention to migrate at the household level. Further, whilst household size, the sex of head of household and income of the household are significant predictors on the intention to migrate in Buoku community, they were not significant predictors of intention to migrate at the household level in Bofie-Banda. 77 University of Ghana http://ugspace.ug.edu.gh Table 4.4: Analysis of variance of the effects of climate related environmental events and other ex(!lanato!), variables on the inclination to migrate, Bofie-Banda Hierarchical Method Sum of Mean Significance Source of Variation Sguares DF Sguare F ofF Main Effects (Combined) 9.364 12 0.780 4.639 0.000 climate related environmental event 2.159 2 1.080 6.417 0.003 13.25 age of household head 4.458 2 2.229 0 0.000 size of household 0.324 2 0.162 0.964 0.385 income of household 0.166 0.166 0.985 0.324 level of education head of household 0.634 0.634 3.771 0.055 sex of household head 0.423 0.423 2.517 0.116 marital status of head of household 0.058 0.058 0.346 0.558 Covariates perception of current coping strategy in the future 0.074 0.074 0.438 0.510 migration status 1.067 1.067 6.345 0.014 Model 9.364 12 0.780 4.639 0.000 Residual 14.636 87 0.168 Total 24.000 99 0.242 Source: Computed from Survey data, 2009 The proportion of the variation in the intention to migrate explained by the additive effects of climate related environmental events, income of household, age of head of household, level of education, marital status and sex of head of household, and size of household is 0.343. However, climate related environmental events together with the other explanatory variables explain 39 percent of the variance in the intention to migrate from Bofie-Banda as shown in Table 4.5. Table 4.5 further indicates that households in Bofie-Banda that have experienced flood have a positive mean deviation (+0.017) just as households that experienced drought (+0.071) after controlling for the effects of income, age of household head, level of education, marital 78 University of Ghana http://ugspace.ug.edu.gh status of household head and sex of household head, size of household and the covariates (perception of current coping strategy in the future and migration status). This is contrary to what pertained in Buoku where exposure to only flood or drought is negative mean deviation. Generally, the weather conditions in the savanna zone are at the extreme and so exposure to any climate related environmental event is more likely to trigger households to have the intention to migrate. On the other hand, households exposed to both floods and droughts have negative mean deviation (-0.069) after controlling for other explanatory variables and covariates. This is true because the ability to live within one extreme environmental event in the savanna zone strengthens households to deal with subsequent issues that may come up and so will not consider migration as an immediate solution. This scenario is also contrary to what pertained in Buoku where exposure to both flood and drought is more likely to trigger households to have the intention to migrate. The two communities fall into different ecological zones and so respond to climate related environmental events differently. While climate related environmental events are common phenomena in the savanna zone, it is not the same in the forest zone. As a result, any household that is able to stand the pressure of one climate related environmental event in the savanna zone may be in a better position to address other future climate related environmental events and so may not migrate. 79 University of Ghana http://ugspace.ug.edu.gh Table 4.5: Relationship between climate related environmental events and other explanatory variables and the inclination to migrate, Bofie-Banda Deviation from the Grand Mean Adjusted for independents Adjusted for and Variable + Category Unadjusted independents covariates Climate related environmental events: Flood +0.096 +0.065 +0.017 Drought - 0.200 - 0.059 +0.071 Flood and Drought +0.114 +0.013 - 0.069 (Eta and beta) (0.300) (0.097) (0.126) Income: < 2,000 +0.046 +0.051 +0.038 2,000+ - 0.086 -0.094 - 0.071 (Eta and beta) (0.128) (0.141) (0.107) Age of head of household: 20-34 - 0.358 - 0.331 - 0.308 35-49 +0.167 +0.170 +0.147 50+ +0.184 +0.157 +0.155 (Eta and beta) (0.512) (0.474) (0.441) Level of education of head of household: Primary/lower +0.020 - 0.053 - 0.043 JHSlHigher - 0.100 +0.188 +0.045 (Eta and beta) (0.108) (0.203) (0.167) Marital status of head of household: Married/cohabiting +0.095 +0.024 - 0.043 Not in union - 0.137 - 0.035 +0.154 (Eta and beta) (0.232) (0.060) (0.167) 80 University of Ghana http://ugspace.ug.edu.gh Sex of household head: Male - 0.108 - 0.062 - 0.056 Female +0.169 +0.097 +0.087 (Eta and beta) (0.276) (0.159) (0.143) Size of household: <3 - 0.290 - 0.042 - 0.042 3-5 +0.114 +0.060 +0.065 6+ +0.121 - 0.011 - 0.014 (Eta and beta) (0.378) (0.081) (0.086) MultipleR 0.585 0.625 R2 0.343 0.390 Source: Computed from CCLONO, 2009 Age of household head also plays a very important role in the decision to migrate by a household member. Table 4.5 indicates that household heads of age 20-34 have negative mean deviation (-0.308) after controlling for other explanatory variables and covariates. Household heads aged 35-49 years have positive mean deviation (+0.147) just as household heads aged 50 years and above (+0.155). Further, Table 4.5 shows that level of education of head of household has a positive effect on the intention to migrate. Household heads with primary or lower education have negative mean deviation (-0.043) whilst their counterparts with Junior High School or higher education have positive mean deviation (+0.154) when exposed to either flood or drought or both. This is so because education gives people the skill to explore other environments for alternative job opportunities whilst households with lower education will have to rely on the only available opportunity within their environment. A focus group discussion among the youth in 81 University of Ghana http://ugspace.ug.edu.gh the community revealed that migration among young girls who have just completed Junior High School is on the increase in the community because of a perception in the community that educated female migrants easily get jobs when they get to the city. 4.5 Future Implications of climate change on the livelihood of the people Climate change will pose a serious threat to the livelihood of the people in the study communities because of their primary reliance on environment as their source of livelihood. The major crops that are cultivated in the forest-savanna transition zone are maize, cassava, yam and millet. These crops do not require excessive rainfall to do well and increases in the volume of rainfall will have serious consequences for such crops. Water-loving crops such as taro and rice are not currently cultivated in these communities and farmers will have the challenging task of adjusting to the situation in the future. The income levels of the people in the communities are already very low with majority of them living below the minimum wage. The impact of climate related environmental events like flood in the future will exacerbate the situation and push majority of the people away from their present location in search of a more favourable environment. The vegetation of the transition zone is already under serious threat due to deforestation and frequent bushfires. The fertility of the soil in the transition zone cannot support the cultivation of certain crops that the people used to cultivate. Even though some communities have begun cultivating new crops that are able to do well with little rainfall, the situation will be different in the near future because predictions are that there will be more rainfall in the future and this will not favour the type of crops cultivated presently. Most of the traditional crops will 82 University of Ghana http://ugspace.ug.edu.gh not be able to do well under the heavy rainfall that will be experienced in the future and farmers generally will need some time to adjust to the situation. Further, because most of these farmers are poor, their homes are likely to also be seriously affected by continuous heavy rainfall episodes. There will also be increase in malaria cases since there will be stagnant water that may be breeding grounds for mosquitoes. Women, children and the aged may suffer most in the future and there is the need to find ways of addressing the situation from today before it gets out of hand in future. 83 University of Ghana http://ugspace.ug.edu.gh CHAPTER FIVE SUMMARY, CONCLUSION AND RECOMMENDATIONS 5.1 Summary The study examined climate related vulnerability and how this triggers the intention to migrate in the forest-savanna transition zone with specific reference to Buoku and Bofie-Banda communities in the Wenchi District in the Brong Ahafo Region of Ghana. The ultimate objective of the study was to provide empirical evidence as to how different drivers of vulnerability in rural households caused by climate change might influence the decision to migrate. To achieve the study objectives, the study addressed the question on the trend of rainfall and temperature as well as the type of climate related environmental event that triggers the intention to migrate among household members in Buoku and Bofie-Banda. Further, the study responded to the question on the type of migration people embark on as a result of perceived or real climate change or variability in the study communities and how female-headed households and male-headed households deal with climate related environmental events. Finally, the study addressed the question on the contribution of climate change to the intention to migrate in the study communities. The forest-savanna transition zone is experiencing drastic changes in the area of rainfall, temperature and vegetation. The bi-modal pattern of rainfall that used to exist in the entire forest-savanna transition zone is gradually giving way to a uni-modal pattern of rainfall especially in communities that are located close to the savanna belt of the Wenchi District. Analysis of the trend of rainfall in Buoku and Bofie-Banda showed that there has not been any significant change in the amount of annual rainfall in the two communities from 1960 to 2004. It was, however, evident in the data that there was a significant reduction in the number of rain 84 University of Ghana http://ugspace.ug.edu.gh days from 1960 to 2004. Rainfalls are more erratic in the two communities in recent times and this is reflected in the frequent experience of very wet years in the last 15 years in the forest- savanna transition zone. The application of Multiple Classification Analysis (MCA) on the contribution of climate related environmental events to the intention to migrate indicates that exposure to flood have positive deviation (+0.017) for households in Bofie-Banda. In contrast, it has a negative deviation (-0.017) for households in Buoku after controlling for the effects of income, age, level of education, marital status and sex of household head, and the size of household and the covariates (perception of current coping strategy in the future and migration status). Also, exposure to drought have a positive mean deviation (+0.071) for households in Bofie-Banda whilst it has a negative mean deviation (-0.035) for households in Buoku after controlling for other explanatory variables and covariates. Further, exposure to frequent occurrence of both flood and drought has a negative mean deviation (-0.069) for households in Bofie-Banda whilst it has a positive mean deviation (+0.019) for households in Buoku after controlling for other explanatory variables and covariates. In addition, while the households headed by females have a positive mean deviation (+0.087), households headed by males have a negative mean deviation (-0.056) in Bofie-Banda. This compares differently to what pertains in Buoku where households headed by females have a negative mean deviation (-0.119) and households headed by males have a positive mean deviation (+0.064). The differences could be the result of the value people in these two communities attached to migration as influenced by the sex of their head of household. While female migration is encouraged in Bofie-Banda because of the perception that females easily get 85 University of Ghana http://ugspace.ug.edu.gh jobs in cities, it is rather male migration that is encouraged in Buoku for the reason that males are able to work harder and send some remittances home when they migrate. The proportion of the variation in the intention to migrate explained by the additive effect of all factors and covariates is 0.341 for Buoku and 0.390 for Bofie-Banda. Thus, 34 percent of the variations in the intention to migrate in Buoku is explained by the additive effect of all factors and covariates whilst 39 percent of the variation in the intention to migrate in Bofie- Banda is explained by the additive effect of all factors and covariates. Thus, the intention to migrate from the community is not explained by just one single event. Climate-related environmental events alone may not trigger people to migrate but when it is linked to other socio-demographic and economic issues the impact is usually obvious. 5.2 Conclusion Climate change is a development issue that needs the attention of all stakeholders. The impact of climate change will exacerbate the already challenging economic, social and health issues confronting the people in the forest-savanna transition zone and makes it difficult for government to achieve the Millennium Development Goal (MDG) target of reducing poverty by half by the year 2015. According to the EPA report on Climate Change Impacts, Vulnerability and Adaptation in Assessment, 2008, cocoa production will be seriously affected by the impact of climate change and the ramification of this on the social and economic life of individuals, communities and Ghana as a whole will be very significant. The projection of future scenarios of rainfall in the forest-savanna transition zone indicates that the current rainfall will increase substantially by about 14 percent. This has its own advantages and disadvantages depending on how the population of an area is able to prepare 86 University of Ghana http://ugspace.ug.edu.gh itself for such events. Bofie-Banda is already experiencing out-migration of young females and also the experience of flood in the community is 0.017 times more likely to trigger the people in the community to migrate. Future increase in rainfall will therefore, increase the flow of migration from the Bofie-Banda community into other communities and urban settlements. The future composition of most households in the community will be the aged and children and this will have serious implications on the economic activities of the household. Migration is, however, a survival strategy and the contribution of migrants to the development of their communities have been very significant. Families benefit from the remittances migrants send home and communities benefit from the small and medium-scale enterprises that some migrants set up in their communities. The future movement of people from Bofie-Banda as a result of increased rainfall in the community could equally be beneficial to the community when migrants begin to send remittances home. 5.3 Recommendations A focus group discussion with farmers in the study communities revealed that the impact of climate change is already having serious effects on the livelihood of farmers with majority of them having to complain about frequent failure of crops in the past decade as a result of poor rainfall. Analyses of rainfall pattern in the forest-savanna transition zone indicate that the pattern of rainfall in the zone has changed with the most significant changes being experienced in the past 15 years. It was mentioned in both study communities that migration is usually the last option that people will consider when affected by climate-related environmental events. The household survey data, however, indicate that exposure to climate-related environmental events is one of the major reasons why people may have the intention to migrate from a particular place. 87 University of Ghana http://ugspace.ug.edu.gh The study recommends the following in the forest-savanna transition zone in this era of climate change. There is the need to educate farmers on issues of climate change and how it manifests itself within any geographical location. In many instances, farmers are confused with regard to distinguishing between weather, climate and climate change. Educating farmers on the causes of climate change will enable them to adopt a more friendly environmental way of cultivating their crops thereby, contributing in their own small way to reducing green house gasses in the atmosphere. Information on climate change is also paramount to farmers and there is the need to ensure proper collaboration between the Meteorological Services Department and agricultural extension officers to ensure that seasonal weather forecasts are made available and also explained to farmers to enable them to plan the timing of their farming activities. Secondly, there is the need for agricultural extension officers in the study communities to educate farmers in the area to begin to cultivate water loving crops such as rice because projections of future rainfall in the area indicate higher rainfall pattern which will not be conducive for crops that do not need much water. It is also important to educate farmers to cultivate their crops on uplands and create water ways within their farms to ensure easy passage of water. Further, government needs to commit funds to support the construction of drainage systems in the study communities to ensure easy passage of water and also protect the buildings in the communities from collapsing as a result of heavy rainfall events in the future. In addition, efforts should be made at helping people in rural communities to embrace small-scale 88 University of Ghana http://ugspace.ug.edu.gh mecham·s ed agn.cultu.re sm ce the current meth d f Co • Wl'll not be sustainable in the future 0 0 larrmng where the impact of climate change will be most felt. It is also important to embrace climate change as a development issue and all sectors should be brought on board in addressing it. The population issues in climate change such as its impact on migration, the aged, women and children should be given priority by government. It will be prudent to integrate climate change issues into all aspects of the development process and this could be made possible if all sectors of the economy are brought on board. Adaptation to climate change is a major concern that government has to consider in addressing the issue of climate change in rural agricultural communities in Ghana. Being a developing country, there is usually a major challenge with regard to adaptive capacity mostly as a result of low level of development, inadequate resources, and inadequate scientific and technical capacity. However, adaptation in the form of better education, training and awareness of climate change and more technical measures like promotion of water loving crops, diversification of livelihood options and community-based natural resource management to prevent over-exploitation of marginal lands and replanting depleted forests could be done with support from industrialised countries. Finally, there is the need to incorporate climate-related environmental events into census questionnaire and other nationally representative surveys like the Ghana Living Standards Survey and also improve on migration data collection. This makes it possible to use census data to undertake comprehensive studies with respect to the impact of climate related environmental events on migration within any geographical region in the country. This is very important for 89 University of Ghana http://ugspace.ug.edu.gh national planning as it would help - improve on the mechanisms for effective allocation of resources to regions that are mostly affected by climate related environmental events thereby, providing alternative economic opportunities to affected populations instead of consigning them to migration as the only available option that is open to them. 90 University of Ghana http://ugspace.ug.edu.gh REFERENCES Adamo, S. 2008. 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Washington: Woodrow Wilson International Centre for Scholars, pp. 5-15. 93 University of Ghana http://ugspace.ug.edu.gh Lozan, J L, GraBI, H and Hupfer, P. 1998. Warnsignal Klima. Mehr Klimaschutz - weniger Risikenfor die ZukunJt. J L Lozan in co-operation with GEO, Hamburg. Mazzucato, Valentina, Bart van den Boom, and N. N. N. Nsowah-Nuamah. ~005. "Th~ im,Pact of international remittances on local living standards: Evidence for households In Ghana. Mlmeo. Ghana Transnational Networks Research Program. Meze-Hausken, E. 2000. "Migration caused by climate change: how vulnerable are people in dryland areas? A case study in Northern Ethiopia " Mitigation and Adaptation Strategies for Global Change. 5:379-406. Munshi, K. 2003. 'Networks in the Modem Economy: Mexican Migrants in the U.S. Labour Market'. In: Quarterly Journal of Economics 118(2): 549-599. Myers, N. 2002: Environmental refugees: a growing phenomenon of the 21st century. In:Philosophical Transactions of The Royal Society B. vol. 357, pp. 609-613. Myers, N. 2005. Environmental Refugees: An Emergent Security Issue. 13th Economic Forum, Prague, 23-27 May. Parry, M.L., O.F. Canziani, J.P. Palutikof, and co-authors 2007 Technical Summary, Climate Change 2007: Impacts, Adaptation and Vulnerability, in M.L. Parry, O.F. Canziani, J.P. Palutikof, PJ. van der Linden, and C.E. Hanson (eds), Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 23-78. Paul, B. K. 2005. Evidence against disaster-induced migration: The 2004 Tornado in North-Central Bangladesh. Disasters 29(4): 370-385. Quartey, Peter. 2006. "Migration and Development: Challenges and Opportunities for Sending Countries Ghana Country Case Study." Report prepared for German Marshall Fund of the USA. Washington, D.C. July 22-26. Tschakert, P., Sagoe, R., Ofori-Darko, G. and S. N. Codjoe (2010). Floods in the Sahel: An Analysis of Anomalies, Memory and Anticipatory Learning. Climate change, Vol. 103: 471-502. Roeckner, E, Bengtsson, L, Feichter, J, Lelieveld, J and Rodhe, H 1998. Transient Climate Change Simulations with a Coupled Atmosphere-ocean GCM Including the Tropospheric Sulfor Cycle. (MPI) Max Planck Institute for Meteorology,Hamburg. Ropelewski, C.F. and M.S. Halpert 1987 "Global and regional scale precipitation patterns associated with the EI-Nino Southern Oscillation", Monthly Weather Review, 115(8): 1606-1626. Stem, N., 2006. Stern Review on the Economics of Climate Change, HM treasury, London. 94 University of Ghana http://ugspace.ug.edu.gh Tim Flannery Now or Never: A Sustainable Future for Australia? Quarterly Essay Issue 31. 2000. United Nations Framework Convention on Climate Change (UNFCCC) 1992. United Nations Framework on Climate Change. United Nations Department of Economics and Social Affairs, Population Division 2009. World Population 2008. Wallchart (United Nations Publications, Sales No. E.09.xm.2). United Nations High Commissioner for Refugees (UNHCR) 2006 Convention and Protocol Relating to the Status of Refugees, Geneva, United Nations High Commissioner for Refugees. United States Department of Energy, 2000. United Nations Population Fund. 2009. State of World Population 2009. Facing a changing world: women, population and climate. Wood, W. B. 2001. Ecomigration: linkages between environmental change and migration. In Global migrants and global refugees: Problems and solutions. eds. A. R. Van der Geest K. 2004. "We are managing! " Climate Change and Livelihood Vulnerability in Northwest Ghana. Leiden: Afrika-Studie Centrum. Van der Geest, K. 2008. EACH-FOR Case study Report: Ghana. (www.each-for.eu) 95 University of Ghana http://ugspace.ug.edu.gh Appendix A: Survey Questionnaire Climate Related Vulnerability and Migration: A Comparative Study of Bouku and Bofie-Banda Communities in the Wenchi District. NOTE: Interviewer, enquire from the respondent to make sure that he/she is not one of the households that were interviewed in the community on the same project. Information on Hometown Name of Respondents Hometown Region of Respondents Hometown District of Respondents Hometown J Interviewer visits Date visited: Name of interviewer: Identification no: 96 University of Ghana http://ugspace.ug.edu.gh 2. HOUSEHOLD INFORMATION No Question Coding classification 1. BACKGROUND INFORMATION 101 Sex 1 Male 2 Female 102 How old are you? [age in completed Years: vearsl 103 What is the highest level of school you 1 None have attended? 2 Primary 3 Middle/JSS 4 Secondary/SSS 5 Higher 9 other (Specify) I 104 What is your religion? 01 No religion 02 Catholic 03 Protestant 04 Spiritual/Pentecostal 05 Other Christian 06 Moslem 07 Traditional 09 Other (specify) ___ I -- 105 To which ethnic group do you belong? 01 Akan 02 GalDangme 03 Ewe 04 Guan 05 Mole Dagbani 06 Grussi 07 Gruma 08 Hausa 09 Other (speCify) ___ 106 What is your marital status? 1 Single 2 Married 3 Separated 4 Divorced 5 Widowed 6 Cohabiting 9 Other (specify) ___ --- ~---- 97 University of Ghana http://ugspace.ug.edu.gh 202 203 204 201 What is his/her Sex What is his/her Pers Please indicate the first name of relation to you? age? No all the persons who belong to your household. 1 male Interviewer: See 2 female codes be/ow. 01 [ 1 [ 1 --- 02 [ 1 [ 1 --- 03 [ 1 [ 1 - - - 04 [ 1 [ 1 --- os [ 1 [ 1 --- 06 [ ) [ ) Codes for 202 : 01 Spouse of head of household 02 Child of reference person and/or of his/her spouse 03 Father or mother of head of household 04 Brother or sister of head of household (with at least one parent in common) 05 Father- or mother-in-law of head of household 06 Brother- or sister-in-law of reference person 07 Son- or daughter-in-law of head of household and/or of his/her spouse 08 (Great) grandchild of head of household and/or of his/her spouse 09 Other relatives of head of household and/or of his/her spouse 10 Employer 11 No family ties 98 University of Ghana http://ugspace.ug.edu.gh 205 206 207 208 Which district does Is he/she currently Pers In which country If Ghana, which No does he/she region does he/she live living in this town? live? he/she live in? in? 1 Yes [skip to 210 I I Interviewer: Write Interviewer: Write Interviewer: Write 2 No down the down the down the country of residence. name of the region. name of the district. 01 [ I 02 [ I 03 [ ----- 1 I 04 [ 1 os [ 1 06 [ I Codes for 206: 01 Ashanti Region 02 Central Region 03 Greater Accra Region 04 Brong Ahafo Region OS Volta Region 06 Eastern Region 07 Western Region 08 Northern Region 09 Upper East 10 Upper West i -- I 99 University of Ghana http://ugspace.ug.edu.gh 209 210 211 Pers If no, why is he/she not What level of school is he/she What is his/her activity status? No in this town with you? currently attending? Interviewer: See codes below. 1 Migrated 1 None 2 Living in my home 2 Non-formal town 3 Primary 3 Gone to school 4 Middle/JSS 9 Other 5 Secondary/SSS (specify) 6 Higher 7 Completed school -~ I 01 [ 1 [ 1 [ 1 I 02 [ 1 [ 1 [ 1 03 [ 1 [ J [ 1 I 04 [ i [ [ I J 1 I 05 [ 1 I [ J I [ 1 06 [ 1 [ 1 [ 1 Codes for 211: 01 Working for pay 02 Working in unpaid family business or farm 03 Looking for work/unemployed 04 Student 05 Doing housework 06 Unable to work because of disability 07 Retired 08 National service 09 Other (specify) I 100 University of Ghana http://ugspace.ug.edu.gh 3. Migration Pat te rn 301 Is your current place of residence different 1 Yes from your hometown? 2 No [skip to 309] 302 Were you born in, or came to your current place of residence on your own? a) Born in place of 1 Yes [skip to 308] residence: 2 No 1 Yes b) Came on my 2 No own: 303 Just before you moved here, did you live in 1 City a city, town, or village? 2 Town 3 Village 304 Why did you move to (CURRENT PLACE 1 Poor soil at place of origin OF RESIDENCE)? Note: Can choose 2 Look for employment more than one response 3 Lack of Education 4 Joining immediate family 5 Poor rains at place of origin I I 6 To get Married 9 Other (specify): ___ I i 305 What year did you move to your ! (CURRENT PLACE OF RESIDENCE)? Year:- -- 306 Has your expectations for migrating to this 1 Yes place been met? 2 No [Skip to 307a] i 307 If yes, what do you think made it possible 1 Good soil for agriculture for you to realise your dream? 2 Lavailability of jobs 1 Note: Can choose more than one response 3 Got good Education 4 JOining immediate family 5 Good rains for farming I I 6 joining other relatives I 9 Other (specify):_ __ I I 307a Do you think your household is better here 1 Same than your place of origin? 2 Well-off 3 In okay conditions I I 4 Barely surviving ---,-----, 307b Have you regretted migrating here? 1 Yes 2 No -~ 101 University of Ghana http://ugspace.ug.edu.gh 307c Would you recommend to other families at your place of origin to migrate to this place? 1 Yes 2 No 308 Do you intend to go back to your home 1 Yes town? 2 No 309 What are the major problems faced by you 1 Poor health services 2 Unemployment in this community? 3 Lack of Education 4 Irregular rainfall 5 Note: Can choose more than one response Bush fire 6 Poverty 7 Poor soil fertility 9 Other (specify): ___ 0 - 310 Which of these problems would you say 1 Poor health services affects you most? 2 Unemployment 3 Lack of Education l 4 Irregular rainfall I 5 Bush fire 6 Poverty 7 Poor soil fertility 9 Other (specify):_ __ 0 - 310a How would you score the effect of these 1 Poor health services problems on your livelihood? 2 Unemployment Note: Use scores below: 3 Lack of Education I 1 = Negligible 4 Irregular rainfall 2 = Manageable 5 Bush fire 3 = Fairly manageable 6 Poverty 4 = Difficult to deal with 7 Poor soil fertility 5 = Can kill 9 Other (specify):_ __ 311 Why does this affect you most? 312 For how long have you been living under this condition? Years: 313 How did you cope under this condition over 1 Labour for food the years? 2 Depended on aid 3 Migrated 4 Use irrigation 5 Cultivate different crops 9 Other (specify) :_ __ '---- 102 University of Ghana http://ugspace.ug.edu.gh 314 How do you think this condition will be in 1 It will be better the future? 2 It will be worse 3 It will be the same 9 Other (specify): ___ 314a Give reasons for you response in question 315? 315 Do you think your current coping strategies 1 Yes will work in the future? 2 No [Skip to 217) 316 If yes, why do you think it will work? 317 If no, why do think it will not work? 318 What do you think should be done to address thes issues in the future? 319 What kind of crops do you cultivate here? 1 Maize 2 Yam 3 cassava 4 cowpea 5 Groundnut 9 Other (specify):_ __ I 320 Are these the crops you have been 1 Yes cultivating here over the years? 2 No I 321 If no, why the change in crops cultivated? 1 Changes in rainfall pattern 2 Changes in soil fertility 3 Some crops don't do well 4 It is expensive cultivating it now 5 Poor market/low prices 9 Other (specify):_ __ 322 Do you intend to migrate out of this 1 Yes community? 2 No [skip to 325) !1 103 University of Ghana http://ugspace.ug.edu.gh 323 If yes, why do you want to leave this 1 Poor crop yield community? 2 Lack of employment 3 Education 4 Joining immediate family 5 Poor rains 6 Joining other relatives 9 Other (specify): ___ 324 Where do you intend to go? 325 Do you know of any member of your family 1 Yes who migrated out of this community? 2 No [skip to 401) 326 If yes, what was the reason for migrating? 1 Poor crop yield 2 Lack of employment 3 Education 4 Joining immediate family 5 Poor rains 6 joining other relatives 9 Other (specify):_ __ 4. Income 401 How much was your income for last year? I I Note: Probe well to be able to estimate the A month: household income for the year. 402 How do yo compare your last year income 1 More than previous years 2 Less than to previous years? prevoius years 403 How does your household consider itself? 1 Well-off 2 In okay conditions 3 Barely surviving I 5. Environment I 501 What are some of the environmental 1 Flood I stresses that you have gone through in this 2 Drought community over the past 40 years? Note: 9 Other (specify):_ __ Can choose more than one response I 502 Which year did this occur? I 503 Are these different from what you 1 Yes encountered at place of origin? 2 No =-rJ 104 University of Ghana http://ugspace.ug.edu.gh 504 Are the strategies you used at place of 1 Yes origin applicable here? 2 No 504a If yes, why? 504b If no, why not? 505 How did you respond to this environmental 1 Migrated stress? 2 Went into different employment 3 Depended on support from family/friends 9 Other (specify) :_ __ 506 If migrated, where did you go to? 507 How long did you stay away? 508 What should we expect for the next farming season? 105 University of Ghana http://ugspace.ug.edu.gh Appendix B: Mental Models CONCEPT MAP FOR BUOKU -L~~k-~f~~~~-i ----------------- I _~~~~:~~~_~~~t~~_ :~~~~I~~~~~~~~~\ l" -L~~~i~~ -i~r------1 :- ~lll~~ _~I~~i~-~ J\ : timber: 'It --,"---~ ,--------- --- - - --- - ~ CLIMATE i-------------.------~ CHANGE : Over populatIOn : /' :------l----------~-L~d di~~~t~f--1 :~;~~;~::: c-.~~~~~I~~~~-_~~: L~~~~~~_I~.!'_cl_ _ j Key Causes of climate change Negative consequences of climate change Positive consequences of climate change 109 University of Ghana http://ugspace.ug.edu.gh CONCEPT MAP FOR BOFIE BANDA --------- - -- - - --- - -- - -----. L_~i~~ _b.~I! ~9!1~!~~c..ti':!~ _____ j \~~I~;~i;~~~~ ~ I RII~h hllminl1 l_'_~ ~~_ I::'~~I::'~~~~~!.' ___ ~ n~for~~tlltion ' .oI1Pinl1 K~y . . --, Chllrcolli VIews ofagnc extensIOn officer: Causes of climate change - - - - - -- === • Consequences of climate change Views of community members Causes of climate change __ Consequences of climate change 110