Economics of Community Participation in the Restoration of Bobiri Forest Reserve in Ghana

TABLE OF CONTENT

CONTENT PAGE

ABSTRACT

DEDICATION

ACKNOWLEDGEMENT

TABLE OF CONTENT

CHAPTER ONE
1.0 INTRODUCTION
1.1 Background
1.2 Statement of problem
1.3 Objectives of the study
1.4 Research questions
1.5 Significance of the study
1.6 Overview of Research Methodology
1.7 Scope of the research
1.8 Limitation of the research
1.9 The Study Area
1.10 Organization of the Study

CHAPTER TWO LITERATURE REVIEW
2.0 Introduction
2.1 Definition of Terms and Concept
2.1.1 Forest
2.1.2 Forest Reserve
2.1.3 Forest Restoration
2.2 Forest resources in Ghana
2.2.1 Forest types in Ghana
2.2.2 State of Ghana’s Forest and Factors affecting it
2.2.3 Forest Policies in Ghana
2.2.4 Economic Importance of Forests
2.3 Typologies of Community participation
2.4 Forest Restoration in Ghana
2.5 The Economics of Forest Restoration
2.5.1 Forest Growth Function
2.6 Empirical Review

CHAPTER THREE METHODOLOGY
3.0 Introduction
3.1 Data Needs
3.3 Research Design
3.4 Sampling method
3.4.1 Target Population and Sample size
3.4.2 Questionnaire design
3.5 Model Specification
3.5.3 Estimation of Total Willingness to Participate Fee
3.6 Data Presentation and Analysis

CHAPTER FOUR RESULTS PRESENTATION, ANALYSIS AND DISCUSSIONS
4.1 Introduction
4.2 Socio-economic characteristics of respondents
4.2.1 Age structure
4.2.2 Level of Educational
4.2.3 Number of year’s respondents have lived in the community
4.2.4 Occupation of people living in the community
4.2.5 Monthly Household Income
4.2.6 Household sizes and dependency burden
4.3 Contribution of the Bobiri forest to the Kubease community
4.4 Factors that influence willingness to participate in restoring of Bobiri forest reserve
4.5.1 Cross-tabulation of WTPF responses with socioeconomic characterises
4.5.2 Multivariate analysis of the determinants of WTPF
4.6 Asses the level of agreement to participate in restoring the Bobiri forest reserve
4.7 The Total Willingness to Participate fee for Bobiri forest restoration

CHAPTER FIVE FINDINGS, CONCLUSION AND RECOMMENDATION
5.1 Introduction
5.2 Summary of findings
5.3 Conclusion
5.4 Recommendations

REFERENCES

APPENDIX I

APPENDIX II

ABSTRACT

Forest restoration is not new in Ghana. The participation of community members in forest restoration has been identified as an integral factor in any successful forest restoration project. The study assessed the economics of community participation in the restoration of the Bobiri forest reserve in Kubease, in the Ashanti region of Ghana. Data was collected from a sample of 400 respondents in the community of Kubease through a simple random technique. Using an opened ended technique, it was realized that all respondents (100%) enjoy some benefit(s) from the forest reserve. The benefits range from household ones (53.75%) to commercial (19.25%), traditional or cultural (6%) and environmental protection purposes (21%). The results showed that majority (87.25%) of the respondents were willing to contribute participation fees for the restoration of the Bobiri forest reserve (BFR). About 34% of the respondents contributed a participation fee ranging from GH¢1 – GH¢4 and majority (54%) contributed a participation fee ranging from GH¢5 – GH¢100. The annual Total willingness to participate fee (TWTPF) for the restoration of the BFR for the population of Kubease (26909) was GH¢2,502,537 and the national annual TWTPF for the population of Ghana aged 18 years and above was GH¢1,267,803,807. The Ordinary Least Square (OLS) regression model revealed respondents monthly income, number of years in education and age to be significant at 5% level, number of dependents and employment status was also significant at 1% level. Using a 5 point likert scale to assess the degree of agreement to participate in the restoration of the BFR, majority (43.74%) of the respondents either strongly agreed or agreed to participate in the restoration of the BFR. It can be concluded from the study that, the sample respondents valued the BFR because majority (87.25%) were willing to contribute a participation fee for the restoration BFR. This study recommends that, community members should be informed and involved in decision making process before any restoration project is undertaken in their communities.

DEDICATION

This thesis is dedicated to my mother Mrs. Susuana Yeboah, my uncle Dr. De-Graft Owusu Manu and Linda Osei Kusi.

ACKNOWLEDGEMENT

I thank and glorify the all knowing God for his protection and abundant grace that guided me in completing this study and master’s programme successfully. My special appreciation goes to Mr. Jonathan D. Quatey of Kwame Nkrumah University of Science and Technology (KNUST) Ghana, who supervised this work. Thanks are also due to all lecturers of Department of Economics of KNUST for preparing me intellectually up to this stage.

Finally, I thank all my friends especially Barnes Evans, Amos Oppong, Justice Osei Kwabena, my family members and loved ones for their contribution towards the success of this study. May God bless them all, Amen.

LIST OF TABLES

Table 4.1: Age distribution of respondents

Table 4.2: Level of education of respondents

Table 4.3: Number of year’s respondents has lived in the community

Table 4.4: Occupation of respondents

Table 4.5: Level of income of respondents

Table 4.6: Household Size

Table 4.7: Cross-tabulation of WTPF responses with socio-economic characteristics

Table 4.8: Regressions Results of the Willingness to Participate Fee Model

Table 4.9: Frequency Distribution for willingness to participate in restoring BFR

Table 4.10: Frequency Distribution for Bobiri forest respondents

Table 4.11: Total Willingness to Participate Fee of Kubease population for restoring BFR

Table 4.12: Total Willingness to Participate Fee of Ghana’s population for restoring BFR

Table 4.13: Benefits/contribution of the Bobiri forest reserve

Table 4.14: Gender

Table 4.15: Access to household facilities

Table 3.1: Education Structure of Ghana

Table 4.16: Frequency Distribution for willingness to participate

LIST OF FIGURES

Figure 1.1: A beautiful view of Bobiri forest reserve

Figure 1.2: A map of the Bobiri forest reserve showing the Kubease community

Figure 2.2: Map of Ghana’s Forest Regions

Figure 2.3 Forestry Growth Function

Figure 4.3: Marital Status

Figure 4.4: Source of Financial support

LIST OF ABBREVIATIONS

illustration not visible in this excerpt

CHAPTER ONE

1.0 INTRODUCTION

1.1 Background

Human society and the global economy are inextricably linked to forests. Historically, forests have played a major role to influence patterns of economic development, supporting livelihoods, helping structure economic change, and promoting sustainable growth (FAO, 2010). For millennia before the industrial revolution, forests, trees, and wood were the source of land for cultivation and settlement, of construction materials, of fuel and energy, and indeed of food and nutrition as well (Williams 2002). The extended use and exploitation of forest resources even before the industrial revolution had led to efforts to conserve forested areas and plant new in specific regions of the world. In Europe, France and Germany were leaders in developing policies in the 17th and 18th centuries to regulate the use of and to protect forests (Barton 2001, Peluso and Vandergeest 2001, Troup 1940).

Forests continue today to provide the high levels of commercial benefits to households, companies, and governments that formed the initial impetus for protective statutes and policies. The FAO (2012) estimates that forest industries contribute more than US$ 450 billion to national incomes, contributing nearly 1 percent of the global GDP in 2008 and providing formal employment to 0.4% of the global labour force. Forests also provide other sources of incomes and subsistence benefits, generate informal work opportunities, and constitute reservoirs of economic values that help ameliorate shocks to household incomes – particularly in rural areas in poor countries. According to the UN (2011), over 1.6 billion people in the world depend on the forest for their livelihood.

It is impossible to overstate the importance of humankind's clearing of the forests. The transformation of forested lands by human actions represents one of the great forces in global environmental change and one of the great drivers of biodiversity loss. The impact of people has been and continues to be profound. Forests are cleared, degraded and fragmented by timber harvest, conversion to agriculture, road-building, human-caused fire, and in myriad other ways. The effort to use and subdue the forest has been a constant theme in the transformation of the earth, in many societies, in many lands, and at most times (FAO, 2010).

In the last few decades, the vast majority of deforestation has occurred in the tropics and the pace still accelerates. The removal of tropical forests in Latin America is proceeding at a pace of about 2% per year. In Africa, the pace is about 0.8% per year and in Asia it is 2% per year.

Fortunately, the twentieth century witnessed the start of “Great Restoration” of the world’s forests. Efficient farmers and foresters are learning to spare forestland by growing more food and fibre in ever-smaller areas. Although the size and wealth of the human population has shot up, the area of farm and forestland that must be dedicated to feed, heat, and house this population is shrinking. Slowly, trees can return to the liberated land (David and Jesse, 2000).

In the United States, this Great Restoration began with a big stick. Since about 1950, U.S. forest cover has increased. Studies by forest experts in Finland reveal that by the 1980s, wooded areas were increasing in all major temperate and boreal forests (David and Jesse, 2000). But the Great Restoration is far from complete. Despite major gains in some areas, the rate of deforestation according to FAO (2010) shows signs of decreasing but is still alarmingly high.

In Ghana, More than 33.7% (2,500,000 ha) of forests have been cleared since the early 1990’s (FAO, 2010). The estimated annual rate of deforestation within the period of 2005-2010 in Ghana is 2.19% per annum: this figure represents the world’s sixth highest rate of deforestation within that period (FAO, 2010).

Forestry plays a vital role in Ghana’s economy. The forestry sector, according to the Ghana Statistical Service (2014) contributes 2.2% to Ghana’s GDP. Forests also provide livelihood to 15% of Ghana’s population (3.6 million people in 2012) (Ghana Forest Commission, 2013).

Forest restoration is an inevitable exercise if natural resources especially the forest is to continue to provide its goods and services in perpetuating on a sustain yield bases. Decision makers, scientists, and the interested public now recognize that there is an urgent need to restore forest ecosystems after decades of intensive logging, fire suppression, road building, livestock grazing, mining, and invasions by exotic species (Noss and Cooperrider, 1994). Rapid deforestation and slow reforestation in Ghana is due to inadequate literature to tackle this problem. This study assesses the economics of community participation in restoration of the Bobiri forest reserve in Ghana.

1.2 Statement of problem

Forest reserves are of immense importance to the government of Ghana. As a result of this the government has established the Forest Commission to manage the country’s natural resources. Forests, according to the Ghana Forest Commission (2013) contribute 2.2% to Ghana’s GDP and provide livelihood to 15% of Ghana’s population.

Forests which are of immense importance to Ghana are under threat. Statistics indicates that, the rate of deforestation within the period of 2005 – 2010 in Ghana is estimated at 2.17% and this represents the sixth highest in the world (FAO, 2010). Immense human pressure, illegal logging and unfriendly farming activities have led to gradual degradation of the natural vegetation cover of the Bobiri forest reserve (Kusi, 2008). The continuous timber logging for about 35 years in the reserve has also resulted in canopy openings of 25m to 30m (Louis, 2008).

To help arrest this problem, in the early 1950’s the traditional taungya system was initiated to replant lost forest reserve. The Forest Service Division also initiated a reforestation programme between 1960 – 1982. Again in 1999 a Forest plantation Development Fund was established to provide funds to private investors to engage in commercial forest plantation (Ministry of Lands and Natural Resources, 2012). The Government of Ghana in November, 2012 also secured an amount of US$50million from the World Bank to embark on a forest restoration project (World Research Institute, 2014).

All these initiatives discussed above were undertaken to help restore Ghana’s forest and reduce the rate of deforestation but yet the rate of deforestation in Ghana still stand at 2.17% which is the sixth highest in the world (FAO, 2012). The depletion of the forest reserve without any restoration leads to a decline in the number of resources provided by the forest reserve. Those who rely on the forest reserve as their main source of raw material also looses their job. The income of household who depend heavily on the forest reserve is also affected. Lastly, the value of the forest reserve will also fall since it can’t continue to provide the goods and services it does. An in-depth literature review shows that economics of community participation in forest restoration is an integral factor in any successful forest restoration project (Erftemeijer and Bualuang, 2013). This study therefore seeks to examine the economics of community participation in forest restoration of the Bobiri forest reserve.

1.3 Objectives of the study

Generally, the research seeks to assess the economics of community participation in restoration of the Bobiri forest reserve in Ghana. Specifically the study seeks to:

1. Assess the contribution of the Bobiri forest to the Kubease community.
2. Identify the economic factors that influence willingness to participate fee in restoring the Bobiri forest reserve.
3. Assess the degree of agreement to participate in the restoration of the Bobiri forest reserve.

1.4 Research questions

To achieve the above stated objectives, the research questions below needed to be answered:

1. What is the contribution of Bobiri forest reserve to the Kubease community?
2. What economic factors influence household’s willingness to participate fee in the restoration Bobiri forest reserve?
3. What is the degree of agreement to participate in restoring the Bobiri forest reserve to be restored?

1.5 Significance of the study

In the development of every economy, there is always a rising or high demand for environmental goods and services. Forests in the world have been identified to provide a variety of these goods and services of which some are known to have an economic value (FAO, 2010). These goods and services do not only include timber products or only fertile soil but also ecotourism, non-timber products and an enormous environmental benefits ranging from regulation of the climate, protection of watershed and biodiversity conservation.

The primary concern of welfare economics is how resources have to be allocated within the society in order to achieve the maximum well-being. Forest products and services such as food, medicine, shelter, clean water, fuel wood and fertilizer serve as the main source of survival for hundreds of poor people in the world (Warner, 2000; Byron & Arnold, 1999).

This study assesses the economics of community participation in restoration of the Bobiri forest reserve in Ghana. The reserve provides both use and Non-use values; it provides timber and Non-timber products, fodder, ecotourism (i.e. serve as a butterfly sanctuary), the opportunity to learn more about the environment, education and the chance to learn new cultures (FORIG, 2011).

Forest restoration comes along with both economic and huge environmental rewards A promise made by the Boon Challenge indicated that, if 150 million hectares of former lost forest in the world is restored it would pump US$85billion a year into global and national economies (IUNC, 2014). Forest restoration benefits communities and society alike. Restoring degraded and deforested land to provide more provisioning services like food, fuel and timber can improve the livelihoods of poor and vulnerable people who rely acutely on the land. More broadly, restoration can reduce dangerous greenhouse emissions from land use change and fossil fuel use. In other cases, restoration can be used to produce critical ecosystem services, like clean water, at a fraction of the cost of traditional, built infrastructure (IUCN, 2006).

For economic and environmental needs, this study will provide the necessary guidelines to the government and other stakeholders or policy makers on the importance of community participation in forest restoration projects. It will also show how the contributions of the local community will assist in any forest restoration project. Future researchers can use the findings from this study as a benchmark for any forest restoration program.

1.6 Overview of Research Methodology

The main source of material for this research was Primary and secondary data. Primary data was gathered by the use of structured questionnaire and scheduled interviews and the Secondary data was extracted from relevant articles/reports, journals, textbooks, newspapers, documents and reports presented by scholars, policy makers and government agencies. The targeted population for the study was the people of Kubease. The sample size of the study was four hundred (400), this was achieved by using Sauders formula (2007); n = Abbildung in dieser Leseprobe nicht enthalten . Econometric tools were used to analyze and interpret data collected from respondents. As such, computer based data analysis tools; Microsoft Excel and Statistical Package for Social Sciences (SPSS) were used.

1.7 Scope of the research

The research was conducted primarily to assess the economics of community participation in restoration of the Bobiri forest reserve in Ghana. This study was carried out at Kubease; a town in Ashanti region of Ghana. It was limited to only one forest reserve (Bobiri) in Ghana and does not cover all forest reserves in Ghana. Therefore the results of the study was not generalised but its findings was placed in the framework of the forest under study and probably under similar forest reserve.

1.8 Limitation of the research

The limitation of the research is attributed to factors such as time, inadequate resource materials and the associated cost involved. Access to vital information on valuation of forest in Ghana and other related topics was difficult to come by. In addition to this the researcher had to combine his profession to academic work. Moreover the cost for funding this thesis was so high. The researcher had to hire trained enumerators and transport them from Kumasi to the kubease for three consecutive days. Other cost such as printing of questionnaires and the final report without sufficient funds from the government was a major constrain.

The final limitation was the difficulty in translation of certain questions into “Twi” which the local language for the people of Kubease.

1.9 The Study Area

The Bobiri forest reserve was created in 1939 when it was still an unexploited primary forest. It falls within the tropical moist semi-deciduous Forest Zone and lies between latitude 60 400 and 60 440 North of the Equator and longitudes 10 150 and 10 220 West of the Greenwich. The total area of the Reserve is 54.6 sq. km (21.1 sq. miles) and falls under the Juaso Forest Reserve District of Ashanti Region (CSIR, 2006). The reserve was named after River Bobiri which passes through the middle of the reserve. Bobiri forest reserve was created as a result of the increased demand for logs during the World War II. The reserve is endowed with variety of flora and fauna and also supports a rich fauna, most prolifically butterflies and birds. About 400 butterfly species have been recorded, but also mona, white-nosed, green and black-and-white monkeys. The reserve is administered by Forest Research Institute of Ghana and has been identified as the largest preserved parcel of land, with lush greenery and mystifying atmosphere. It is one of the most beautiful and magnificent Forest Reserves in West Africa, harbouring tall, important ancient trees (Opoku, 2012).

Ecologically, the Bibiri forest reserve fall within the tropical moist semi-deciduous forest zone and has an annual mean rainfall of 1200mm and 1750mm. The annual temperature ranges between 200C (August) and 320C (March). The distribution of rainfall patterns and temperature enhances the growth of flora and fauna in the area. It must be noted that the Bobiri forest reserve host the Bobiri arboretum and the butterfly sanctuary (FORIG, 2011).

Figure 1.1: A beautiful view of Bobiri forest reserve

Abbildung in dieser Leseprobe nicht enthalten

Source: (FORIG, 2011)

The Bobiri forest reserve is located about 35 km southeast of Kumasi the capital city of Ashanti Region of Ghana. It is about 4km off the main Kumai-Accra road at the village of Kubease. Bobiri Forest reserve is enclosed by six communities, namely; Krofrom, Kubease, Ndobom, Koforidua, Nkwankwaduan and Tsetsekaasum. Kubase was chosen as the town for the administration of the questionnaire because of its proximity and accessibility to the forest and also serving as the “gate-way” community to the reserve. Again Kubease was chosen because of its location on the main Kumasi/Accra road gives the “first impression” when approaching the reserve. Kubease’s selection was also based on its population size. The population of Kubease was estimated to be around 26,909 in 2010 (Ghana Statistical Service, 2010) and is dominated by Ashantis whose local dialect is Twi. Kubease is located at an elevation of 228M above sea level and its coordinates are 60 40’ 0” N and 10 22’ 0” E in DMS (Degree Minutes Seconds).

The predominant occupation amongst the people of Kubease is farming and foraging. Administratively, the Kubease community is under the paramouncy of the Juabeng stool. It has its own sub-chief who owes allegiance to the Juabeng paramount chief. The traditions and cultural values are being protected by the sub-chiefs and the traditional head of the community. The community also has an assembly man who is democratically elected by the people to represent them on the municipal level. In addition to this several committees have been established to see through the day-to-day administration of the community. Just to mention few; the developmental issues of the community are catered for by the Town Committee Members, the School Management Committees sees to the educational development in the community and Community Forest Committee is also responsible for the protection and management of the Bobiri forest reserve (Kusi, 2012).

Figure 1.2: A map of the Bobiri forest reserve showing the Kubease community

Abbildung in dieser Leseprobe nicht enthalten

Source: Ministry of Local Government and Rural Development and the German Technical Cooperation (2010)

1.10 Organization of the Study

This study is organized into five chapters. The first chapter is the introductory chapter and it entails the studies Background, problem statement and purpose of the study, research questions, significance of the study and the limitations of the research. Literature review is in chapter two. Chapter three entails the methodology used to place value on non-marketed goods and services. The Data analysis of the study can be found in chapter four and lastly chapter five contains the discussion, conclusion and recommendations of the study. The lists of references, tables, figures are also captured in the appendix.

CHAPTER TWO LITERATURE REVIEW

2.0 Introduction

Forest restoration have been practiced and promoted by International Tropical Timber Organization (ITTO) for many years (ITTO, 2005). In this chapter several concepts used in the study have been clearly defined, related literature on community participation in forest restoration and economics of forest restoration have also been reviewed.

2.1 Definition of Terms and Concept

Several concepts and terms used in this study is defined and explained under this section.

2.1.1 Forest

Forests according to FAO (2006) must be defined clearly by developing countries before they can host reforestation projects under the clean development mechanism (CDM) of the Kyoto protocol. Forest definition in developing countries for the CDM according to Kyoto protocol should be chosen within the parameter values from the range below;

“Forest” is a minimum area of land of 0.05-1.0 hectares with tree crown cover (or equivalent stocking level) of more than 10-30 per cent with trees with the potential to reach a minimum height of 2-5 metres at maturity in situ. All plantation and young natural stands which have yet to reach a crown density of 10-30 per cent or tree height of 2-5 meters are included under forest (FAO, 2006). Following the definition of forest by the Kyoto protocol under the CDM means that the Bobiri reserve can be described as a forest with flora of about 80-100 plants species per acre and rich in biodiversity (FORIG, 2011).

2.1.2 Forest Reserve

Forest reserve or reserved forest is a specific term for designating forests and other natural areas which enjoy judicial and/ or constitutional protection under the legal system of a country (Wikipedia, 2014). Forest history in Ghana dates back since 1906. In 1908 a Forestry department was created to control the feeling of commercial tree species. By 1939, the creation of forest reserve was largely completed and in 1948 a forest policy was then adopted. This policy was enacted to ensure the creation of permanent forest reserve or estate to help enhance the welfare of the people, protect water bodies, maintain favourable conditions for agricultural crops and aid in public education and research (Forest Commission of Ghana, 1994).

2.1.3 Forest Restoration

In simple terms forest restoration is the act or process of restoring or regaining the natural features of ecosystem that have been negatively affected due to its overuse, pollution or neglect. In 1997 Higgs said “the definition of good restoration will vary from site to site, but will always be rooted by ecological fidelity: the combination of structural replication, functional success and durability”.

Society for Ecological Restoration (SER) is one main primary authority in defining ecology restoration. Society for Ecological Restoration (2004) defines forest restoration as “the process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed.” In addition to the above, SER (2008) defines forest restoration as an “international activity that initiates or accelerates the recovery of an ecosystem with respect to its health, integrity and sustainability.

“Reforestation” is the direct human-induced conversion of non-forested land to forested land through planting, seeding and/or the human-induced promotion of natural seed sources, on land that was forested but that has been converted to non-forested land (FAO, 2006).

2.2 Forest resources in Ghana

Forest resources in Ghana are made up of goods and services. Some of these goods or services are tangible and therefore can be quantified in monetary terms, whiles others may not easily be quantified. In terms of direct economic value timber is the most important forest resource in Ghana. It contributes about 6% to GDP, employs over 75,000 of the labour force, and out of the total estimated population of 24 million it serve as a source of livelihood for about two million people (Abeney & Owusu, 1999). The forestry sector, according to the Ghana Statistical Service (2014) contributes 2.2% to Ghana’s GDP. Forests also provide livelihood to 15% of Ghana’s population (3.6 million people in 2012) (Ghana Forest Commission, 2013).

Trading in non-timber forest products (NTFs) such as fodder, chewing sticks, bush meat, nuts, pestles, canes, fruit, artefacts, medicine, etc., in Ghana are economically important within all areas of high forest zone (Ntiamoah-Baidu, 1987; Abbiw, 1990; Falconer, 1992).

2.2.1 Forest types in Ghana

The total land area of Ghana is estimated at 23.9million ha and consists of two broad ecological zones; a high forest zone (HFZ) in the south covering about 8.2million ha and the savannah zone (SZ) in north covering 15.7million ha. The savannah zone is characterized by an open canopy of shrubs and trees with a distinct ground layer of grasses (Hall & Swaine, 1981) and covered with woodland (9.4million hectares) producing mainly wood fuel and small amounts of building poles for domestic use. Livestock production and annual crops such as cotton, root crops and cereals is the predominant economic activities in this zone.

The high forest zone according to Hawthrone (1995) is approximate 82,000km3. The high forest zone is characterized by different association of species and rainfall patterns and soil conditions. This zone is father grouped into nine vegetations zones; Wet Evergreen Zone (WE), Moist Evergreen Zone (ME), Moist Semi-Deciduous North East (MSNE), Moist Semi-Deciduous South East (MSSE), Upland Evergreen (UE), Dry Semi-Deciduous Inner Zone (DSIZ), Dry Semi-Deciduous Fire Zone (DSFZ), Southern Marginal (SM) and Southern Outlier (SO).

Figure 2.2: Map of Ghana’s Forest Regions

Abbildung in dieser Leseprobe nicht enthalten

Source: UNEP-WCMC, 2004.

Most of the timber species are produced in the southwest of the evergreen and deciduous forest. The main species in the deciduous forests are Triplochitonschleroxylon (wawa), Mansoniaaltissima (Mansonia), Nesogordoniapapaverifera (Denta) and Khayaivorensis (mahogany); and in the evergreen forests Guareacedrata (Guarea), Tieghemellaheckelli (Makore), Tarrietiautils (Niangon) and Uapacaspp (Assam) (UNEP-WCMC, 2004).

2.2.2 State of Ghana’s Forest and Factors affecting it

Ghana’s forests cover was originally about 84,000km2 (36 percent) of the country’s total land area (Rice &Counsell, 1993; EU, 2006). Records do indicate the existence of relatively undisturbed forests, which harboured abundant biodiversity (Alpert, 1993), protected fragile soils (FAO, 2007; UNEP, 2002), and helps in regulating the supply of water (Katz &Glantz, 1985). The country is rapidly losing its biodiversity as a result of high rate of deforestation. Dixon et al (1996) confirms that there has been a sharp increase in the rate of forest degradation and loss of biodiversity. Forest reserve in Ghana is made up of 4,323 km² of protection forests, 11,590 km² of production forests and about 1,980 km² of game production reserves (Ghana Forestry Commission, 1995; Siaw, 2001). Ghana, like many tropical countries, is continuously losing her closed forests at an alarming rate. The area of closed forest has reduced to less than 25% of its original value and now exists in fragmented patches estimated to be about 20 to 524 km². Between1990 and 2005, the rate annual deforestation was 2.0%, this has led to an estimated forest loss of 1.9 million hectares (Mongobay, 2013).

The rate of deforestation triggered the government of Ghana to implement the plantation 20,000 ha per annum under the Ghana National Plantation Project (Domson et al., 2007; Ghana Forestry Commission, 2005; IUCN, 2006). Most of the forests have lost their pristine interior habitats that are critical for the protection of vulnerable species (FAO 2001; Forest Services Division of Ghana, 1995).

In 1992 it was estimated that the remaining closed forest was 1.5 million ha. Agricultural activities, bush fires and other human activities have depleted over 20,000 hectares of the reserve area (IUCN, 1992; Agyarko, 2001). Again, the forest reserve in Ghana is characterised by loss of biodiversity, depletion of species, excessive log harvesting, reduced standing volumes of species and a declining resource base. It should be noted that most (14%) of the permanent forest reserve in Ghana are without forest cover. The most affected zones are the South-east subtype of forest zones and moist semi deciduous North-west (Agyarko, 2001). Several factors contributes to the depletion of the forests, amongst these factors are attributed to; excessive legal and illegal logging, surface mining, annual bushfires, infrastructural development and unsustainable farming methods.

In addition, population growth and migration mostly in the forest areas also account for high of deforestation (FAO, 2000). An increase in population size comes along with higher demand for the goods and services. In order to meet the need and demand of the population, farmers start to use virgin forest to grow more crops for additional cultivation. Underlying these deforestation driving forces are failures of forest policy, external prices of timber, unrealistic forest fee regimes, population pressures and weak institutional structures (FAO, 2001).

2.2.3 Forest Policies in Ghana

An effective and a good management of Ghana’s forest depend on the availability of appropriate forest policies. Policies governing Ghana’s forest dates back to 1906 when legislation was enacted to control the felling of commercial tree species and the creation of the Forestry department in 1908 (Ministry of Lands and Forestry, 1994). By the year 1939, the demarcation and reservation of the forest estate was largely completed and the need for better government guidance and control of the forest led to the adoption of a new forest policy in 1948 (Ghana Forest Commission, 1994). Since the policy was enacted in 1948, a consistent policy of selection, demarcation, reservation, protection of water supplies, maintenance of favourable conditions for cultivation of agricultural crops and the promotion of research and public education have been vigorously pursued. Interestingly, most of the policies were cantered around the control of timber felling, and management was restricted to only the reserves (Appiah, 2001a).

Planned management of mainly the reserved forests became operational in the 1950s after adoption of Ghana’s first forest policy (Prah, 1994). In addition, a number of forest policies have been initiated by government and its agencies to regulate forest activities in the country. Amongst these policies includes; Forest and Plantation Development Act,2000.Act 583; Forestry Commision Act, 1999 Act 571; Timber Resource Management Regulations, 1998; Forest Protection (Amendment) Act, 2002.Act.624; Trees and Timber (Amendment) 1994; Timber Resource Management Act, 617 (Amendment) Act, 2002.(Ghana Forestry Commission, 2013). These policies and related laws were contained in various official documents and vested in specific ministries and state agencies for implementation. Ghana Forestry Commission is the agency responsible for forest resource management in Ghana and was established under Act 405 – Ghana Forestry Commission Act, 1980 – to coordinate the activities of the forestry sector institutions, namely: the Forestry Department, Department of Game and Wildlife, Forest Products Research Institute and Ghana Timber Marketing Board. Section 6 of the Act mandated the Commission to regulate and manage the utilization of all forestry and wildlife resources of Ghana and also coordinate the policies in relation to forest resources (Forest and Wildlife Policy, 1994).

2.2.4 Economic Importance of Forests

The importance of forests is now well understood by political decision-makers, scientists and almost all people in world (Verweij, 2002a; Goldsmith, 1998; Wagner and Cobbinah, 1993). As a result, economists, scientists and press have repeatedly hinted on the rate of deforestation and its negative impact on the environment. Studies have shown and confirmed that about 8000 years ago half of the earth was covered by the forest as compared to 30% today (FAO, 2000; Ball, 2001).

In Ghana, official statistics focuses on the role that forests play in providing raw materials for the formal timber industry. Notwithstanding this fact, forests and the savannah areas also support a variety of less formal economic activities based on wood fuel, non-timber forest products including bush meat, medicinal plants and rattan. Only wood fuel and charcoal supply about 70% of Ghana’s energy (Ghana Forest Investment Program, 2012).

According to the 2012 FIP report, as at 2010 the worth of export of timber was €140 million and the contribution of forests to GDP was estimated at 4% having fallen from a previous high of 8% a decade ago. Forest also provides livelihood to about 15% of the population and accounts for 9-12% of export earnings. Even though there is no formal record for non-timber forest products (NTFPs) due to “timberilisation” of all aspect of policy formulation and regulation it is also extremely important. Locally the economic value for non-timber forest products for both household and commercial purpose may outweigh that of timber. This area however requires further research in order to understand it properly and enable effective investment to support and enhance it.

2.3 Typologies of Community participation

The participation of community members in forest restoration makes them feel a sense of ownership and are therefore willing and prepared to offer their services for any restoration project. As used mostly in tourism literature “Host Community” is synonymous to “local people”, “public” or “citizens”, “residents” (Burn, 2004). One important feature of a host community is that they do not constitute a unified body and its constituents which involve the individuals and stakeholders are rarely homogenous (Ashley and Roe, 1998). In line with the research topic the host community for this study is the residents of Kubease which is in the Ashanti region of Ghana and the word community will be used interchangeably with Citizens.

Community participation has received significant academic interest. The seminal work of Arnstein (1969) “Ladder of Participation” is often used as the reference point. In his work Arnstein (1969) outlines eight levels of community or citizen participation: Manipulation, Therapy, Informing, Consultation, Placation, Partnership, Delegated power and Citizen Control. Under the manipulation or therapy participation, community participation is seen as a sham but the genuine participation is practiced under the citizen control. Arnstein (1969) defines citizen participation as the redistribution of power that enables have-not citizens to be deliberately included in the developmental decision-making process. As already stated above, this means that if community members are allowed to participate in a restoration project, they see their selves as partaken in the decision making of the community.

However, Arnstein’s community participation typology have been criticised as given misleading results within the context of developing countries (Chogoill, 1996) and it doesn’t specifically also deal with restoration project (Leksakundilik, 2006). Tosun (1999) classification of community participation which categories community participation into three types namely; spontaneous participation, coercive participation and induced participation is a useful framework for analyzing the extent of community participation in a forest restoration project at Bobiri reserve since it also serve as an ecotourism site.

Spontaneous participation in Tosun’s model corresponds to degrees of citizen power in Arnstein’s typology. It represents an ideal mode of community participation because it provides full managerial responsibility and authority to the host community.

2.4 Forest Restoration in Ghana

Efforts and ideas on forest restoration are not new in Ghana (IUCN, 2011). In 2004, the government of Ghana supported the establishment of a National Working Group on forest landscape. Ghana in 2006 also held the National workshop on ITTO guidelines for the restoration, management and rehabilitation of degraded and secondary tropic forest (IUCN, 2011). After the 2006 National Workshop on ITTO guidelines for forest restoration, the following assumptions were proposed for Ghana in her restoration:

- Forest resources provide the direct source of livelihoods for the majority of the rural population and that poverty reduction and wealth creation in the country are dependent upon effective management of these resources;
- However due to different anthropogenic activities the forest resources are gradually being degraded and hence need to be restored;
- Restoration requires collaboration among stakeholders;
- District Assemblies (DAs), Traditional Authorities (TAs), opinion leaders and local community groups, including women and youth groups are important actors in the restoration process;
- Restoration activities at all levels will be carried out based on effective and efficient planning and networking; and
- Capacity of communities and community structures will be developed in Forest Landscape Restoration and this will be sustained through the provision of adequate and appropriate logistic and technical support by taking into consideration their indigenous knowledge.

One typical successful forest restoration programme in Ghana was Pamu Berekum forest area located in the Brong Ahafo Region of Ghana. This was an ITTO/FORIG community collaborative restoration project. The success story of project was attributed to the participation of the local people at all levels of the restoration project (IUCN, 2011).

2.5 The Economics of Forest Restoration

Variety of discipline of study and skills are required in forestry. Foresters must have a combination of knowledge from applied sciences, biology, other natural sciences and social science such as economics. Each discipline brings on board different methodology and tools in addressing the issue of forest (Daowei, 2011). This section provides a brief overview on the economics of forest restoration. It presents a simple model on when to grow or cut down a forest. From an economic point of view forest is viewed as an economic resource because it can produce goods and services that people want to consume.

2.5.1 Forest Growth Function

A critical question about social or commercial forest economics is “when is it appropriate to cut stand of trees?” To answer this critical question, it is assumed that the land has no available alternative use. If the land has an alternative use then the concept of opportunity cost would be introduced in the model.

The critical element in forestry problem is that, Growth Function is function of Time not a function of stock.

Figure 2.5.1 Forestry Growth Function

illustration not visible in this excerpt

In the Figure above: Q(t) represents volume of timber (i.e., board feet or Cubic feet), T is the time and MSY is the Maximum Sustained Yield.

The figure depicts the growth function of a typical stand of trees. At the initial stage, the volume increases at an increasing rate for very young trees. Then, the volume of growth slows and increases at a decreasing rate. Finally, as the trees are very old, they begin to have negative growth as they rot, decay, and become subject to disease and pets.

In the figure, volume of stand of trees is maximised at time Tmax, with a volume Q(Tmax). But this volume is not the Maximum Sustained Yield (MSY). MSY occurs where the growth rate equals the Average Growth (AG) per rotation.

Recall: The motive is to re-plant new trees.

The average growth rate of a stand, at any time, t, is: Abbildung in dieser Leseprobe nicht enthalten

This can be shown by a ray through the origin.

Ray 1 shows that the average growth can be achieved by either cutting at time T1 or at time T2, but none of them gives the Maximum Average Growth.

The MSY occurs at a rotation length that maximizes the average annual growth of the stands through time. Max. {Q(t)/t} implies the FOC

Abbildung in dieser Leseprobe nicht enthalten

Applying the quotient and rearranging the terms we get: Abbildung in dieser Leseprobe nicht enthalten.

i.e. in order to harvest the MSY, the stand of trees should be cut when marginal growth equals average growth of the stand. Ray 2 shows where this condition is met, where the average growth is tangent to the growth function.

Incorporating the rate of time preference of the forester (i.e., the discount rate), it is necessary to formulate optimization problem in continuous time:

- In discrete time, Pt = [Abbildung in dieser Leseprobe nicht enthalten]

- In continuous time, ∂t 0:

As [Abbildung in dieser Leseprobe nicht enthalten]

Forest Optimization Problem:

Here, the idea is to maximize the present value of the forest stand with respect to the time period of harvest. That is to find the point is time where the NPV is maximised. To achieve this, the rotation period was divided into single and infinite rotation periods.

The Optimal Single Rotation:

Under the single rotation, there is no opportunity cost incurred by failing to plant the next stand of trees at the optimal time. Here, the major problem is to determine the optimal time of harvest. Suppose a crop is planted at time t=0 and grows in value to PQ(t) at time t. The goal is to find the harvest time that will maximize the NPV of a single rotation.

Let P = constant price per pound of the crop.

There are no harvesting costs, so that π = TR

The Objective Function is: Abbildung in dieser Leseprobe nicht enthalten [Abbildung in dieser Leseprobe nicht enthalten]

With the FOC: Abbildung in dieser Leseprobe nicht enthalten = [Abbildung in dieser Leseprobe nicht enthalten] this can be written as [Abbildung in dieser Leseprobe nicht enthalten]

Or MB of waiting (value of new growth) = MC of waiting (lost interest on TR)

NB: if the forest manager delays the harvest, she will not earn interest on revenues PQ(t).

If the forest manager delays the harvest, she will gain the value of new growth Q’(t).

The optimality condition can be rearranged to get: Abbildung in dieser Leseprobe nicht enthalten = r this implies that the percentage of growth rate in volume should equal the discount rate. Profit maximization therefore dictates that the stand should be harvested when the percentage rate of growth of crop value equals the value of alternative investments.

- If Abbildung in dieser Leseprobe nicht enthalten > r, then the crop is increasing in value quicker than market investments and the farmer should delay the harvest decision

- If Abbildung in dieser Leseprobe nicht enthalten > r, then market investments are increasing in value quicker than the growth in value of the crop (harvesting should have already occurred)

The Case of an Infinite Forest Rotation

The most relevant case for foresters is that of a continuous stand rotation over time. The concept of opportunity cost now come inn when the forester plant or replant a new forest stand immediately after cutting the old one. The opportunity cost here is the cost of future rotation.

In the infinite rotation problem, the equation below is used:

Abbildung in dieser Leseprobe nicht enthalten

Where T is the length of each rotation. The infinite rotation problem is commonly referred to as Faustmann Rotation after the German Forester in the early 1900’s (Ziberman, 1999).

Assume a constant net price (or profit) per cubic foot of timber. That is, if harvesting or replanting costs exist, then what is held constant is Net Price. Net Price = Price - per unit harvesting and replanting costs.

Let: P = the constant price per cubic foot of timber, Q = the volume of timber (in cubic feet)

The foresters profit can now be written as: π = PQ(T)Abbildung in dieser Leseprobe nicht enthalten + PQ(T)Abbildung in dieser Leseprobe nicht enthalten + PQ(T)Abbildung in dieser Leseprobe nicht enthalten + …

= PQ(T)Abbildung in dieser Leseprobe nicht enthalten + Abbildung in dieser Leseprobe nicht enthalten + Abbildung in dieser Leseprobe nicht enthalten + …]

= PQ(T)Abbildung in dieser Leseprobe nicht enthalten [1+ Abbildung in dieser Leseprobe nicht enthalten + Abbildung in dieser Leseprobe nicht enthalten + …]

= PQ(T)Abbildung in dieser Leseprobe nicht enthalten

= Abbildung in dieser Leseprobe nicht enthalten

= Abbildung in dieser Leseprobe nicht enthalten

The Optimization problem is: Abbildung in dieser Leseprobe nicht enthalten. { π = Abbildung in dieser Leseprobe nicht enthalten

With FOC: Abbildung in dieser Leseprobe nicht enthalten = Abbildung in dieser Leseprobe nicht enthalten + Abbildung in dieser Leseprobe nicht enthalten = 0

This can be re-arranged to yield: PQ’(T) = Abbildung in dieser Leseprobe nicht enthalten = Abbildung in dieser Leseprobe nicht enthalten

Cross-multiplying the optimality condition can be written as: PQ’(T) = rPQ(T) + PQ’(T)e-rt

MR of delaying = MC of waiting + MC of delaying future income stream

The first two terms are identical to those in the single stand, or cropping decision. The last term represents an additional opportunity cost of delaying the harvest. Delaying the current harvest also delays income received from future harvests. Therefore, the optimal rotation time, T, requires the forester to equate the marginal value of waiting to the marginal cost of delaying the harvest of current and future stands.

In general, T* < T* (single rotation) < Tmsy:

It is also important to analyze the effect of different parameters of the harvesting decision:

An Increase in the price of timber:

An increase in P will tend to shorten the rotation length, because higher timber prices increase the profitability of each harvest. Cutting trees earlier moves the profit of future harvests closer to the present

An Increase in the Interest Rate:

An increase in r will tend to shorten the optimal rotation length, because the forest owner is now relatively more impatient. The owner is now more eager to move profit up into the present.

An Increase in Harvesting Costs:

- Recall how harvesting costs was absorbed into the Net Price.
- Thus, an increase in c is analogous to a decrease in Price
- An increase in c will tend to increase the rotation length, because cutting trees has now become less profitable. The owner wishes to delay paying future harvesting costs.

2.6 Empirical Review

Several literatures reviewed indicates a notable number of studies on forest restoration and community participation in restoration in the world but there are limited papers on economics of community participation in a reforestation project. This section of the paper reviews existing literature on forest restoration.

An analysis of Socio-Economic Factors Influencing Forest Dwellers' Participation in Reforestation and Development of Forest Areas in west Mazandaran of Iran was conducted by Faham et al (2008). The main purpose of the study was to investigate the links between forest dwellers’ participation in reforestation and development of forest areas in west Mazandaran of Iran and a set of socio-economic variables. The statistical population included all forest dwellers living in villages, which locate in the west Mazandaran in Iran and had been covered by local forestry cooperative. A sample of 110 forest dwellers were selected by the use of proportional random sampling method. A questionnaire was used to collect data. For determining the validity of questionnaire, the content validity was used. Cronbach's alpha was used to measure reliability of the index measuring level of participation in reforestation and development of forest areas that its extent was 0.86 and showed that mentioned variable had high reliability. The data were analyzed by the use of descriptive and inferential statistics such as extent of mean, standard deviation, coefficient of variation, correlation analysis and regression analysis. The findings revealed that age, level of literacy, level of participation in extension-education courses, using level of communication channels and information resources, level of forest dependency, social participation, social solidarity, economic and social motivations are positively and significantly (p<0.01) correlated with level of forest dwellers' participation in reforestation and development of forest areas. Household size is positively and significantly (p<0.05) correlated with level of forest dwellers' participation in reforestation and development of forest areas. The result of multiple regression showed that variables of level of participation in extension-education courses, age, household size, level of economic motivation, social solidarity and level of literacy could explain 51.4% of the variation in the level of forest dwellers' participation in reforestation and development of forest areas.

Walters (1998) realised that there is relatively little social science input into the study and practice of ecological restoration. This shortcoming was examined by Walters (1998) with particular reference to restoration work in the Philippines involving the planting of native upland forest and coastal mangrove trees in a densely populated and highly degraded coastal watershed. In his study, he found that socio-economic factors were the most important factors that determine the relative success of a restoration work. He concluded that socio-economic factors or human ecological factors should be included when planning and implementing tropical restoration project.

Ishmeal and Adoto (2013) used the Bobiri forest reserve as a study area to assess community participation in ecotourism. The main objective of their study was to investigate the nature and extent of community participation in ecotourism development and management. Both probability and Non probability sampling method was used to interview a sample of 168 respondents from the community of Kubease, Krofrom and Nobewam which are in the Ashanti Region of Ghana. The data for their study was collected from residents, members of traditional councils and members of forest management committee of the three communities. The data collected from the field was analysed by using SPSS version 16.0. They concluded that, there is low level of community participation in the ecotourism program of the Bobiri forest reserve. In their recommendation they stated that, community participation should be an integral A model was developed by Egan and Estrada (2011) to assess the socioeconomic outcomes of forest restoration projects. Eleven experts in economics, social and business aspects of forest restoration were purposively selected to participate in the research. A Delphi process and post Delphi process discussion was the main methodology used in achieving their objectives. The Delphi iterative process was in four stages. The Four iterations of a Delphi process resulted in a practical, robust model capable of evaluating the social and economic effects and outcomes of a wide range of forest restoration projects. Among the most highly rated indicators in the model were those related to job creation, community stability, economic impacts, and collaborative participation in restoration processes. The relative importance of the indicators was estimated, and specific metrics were developed for each indicator in the model. Upon completion of the Delphi process, the model was discussed with forest restoration monitoring practitioners and stakeholders, who offered their perspectives from practitioners’ points of view.

Ecological restoration has recently started to adopt insights from the biodiversity-ecosystem functioning (BEF) perspective. The main focus is on restoring the relation between biodiversity and ecosystem functioning. Raf and Oliver (2011) in their study “Forest restoration, biodiversity and ecosystem function” provided an overview of important considerations related to forest restoration that can be inferred from this BEF-perspective. In their study, they attested that the restoration of multiple forest functions and stable forest functions requires multiple species. In particular in the light of global climatic change scenarios, which predict more frequent extreme disturbances and climatic events, it is important to incorporate insights from the relation between biodiversity and stability of ecosystem functioning into forest restoration projects. Rather than focussing on species per se, focussing on functional diversity of tree species assemblages seems appropriate when selecting tree species for restoration. They concluded that the BEF-approach provides a useful framework to evaluate forest restoration in an ecosystem functioning context, but it also highlights that much remains to be understood, especially regarding the relation between forest functioning on the one side and genetic diversity and above-ground-below-ground species associations on the other. The strong emphasis of the BEF-approach on functional rather than taxonomic diversity may also be the beginning of a paradigm shift in restoration ecology, increasing the tolerance towards allochthonous species.

The critical issue in this study was to assess how community members are willing to participate in a forest restoration programme. The approach upon which the issue is conceptualized provides a theoretical framework for the study. The conceptual framework of this study was built on the theories and literatures on the concept of community participation in forest restoration. Upon reviewing several typologies of community participation in forest restoration, Tosun (1999) classification of community participation which categories community participation into three types namely; spontaneous participation, coercive participation and induced participation served a useful framework for analyzing the extent of community participation in a forest restoration project at Bobiri reserve since it also serve as an ecotourism site. The conceptual framework is also built on Weber’s theory of Social Action and Durkheim’s theory of Social Solidarity (Chtamber, 1973; Tavassoli, 2006). The particiapation of community members in forest restoration may differ depending on their socio-economic characteristics (Portes, 1971). Studies have shown that level of education influence community participation in forest restoration (Lise, 2000; Glendinning, 2001; Owubah, 2001; Chowdhury, 2004). However, the influence of age on community participation is not very clear. Whiles studies have found age to be an insignificant variable that affect community participation in restoration (Thacher, 1996; Zhnag and Flick, 2001) others have found it to be significant (Atmis et al, 2007). Household’s size has also been found to influence community participation in forestry (Dolisca et al, 2006; Varamini, 2003). These variables mentioned were critically examined in this study on how they affect respondent’s willingness to participate fee in forest restoration by contributing some fraction of their income.

CHAPTER THREE METHODOLOGY

3.0 Introduction

The main objective of the research was to assess the economics of community participation in restoration of the Bobiri forest reserve in Ghana. This chapter captures the methodology employed, sources of data, sampling techniques, and data analysis methods used in achieving the objectives of this study.

3.1 Data Needs

To be able to answer the research questions and achieve the objectives for this study, data on the degree of agreement on respondent’s willingness to participate in the restoration of the Bobiri forest reserve was needed. Data on respondent’s willingness to participate fee was needed. Again data on respondent’s socio-economic characteristics such as monthly income, age, level of education, number of years that respondents have lived in Kubease, employment status and the size of respondents household was also needed. Finally, data on the benefits/contribution of the Bobiri forest reserve to the people of kubease was needed.

3.2 Data Sources

Primary and secondary data were used as the main sources materials for this study. Primary data was collected by the use of structured questionnaire and scheduled interviews. The data collection took place over a period of 5 days from 19th July, 2014 to 23rd July, 2014. The data was collected through a structured questionnaire by 5 trained enumerators with a minimum qualification of HND (Higher National Diploma). Data on respondent’s degree of agreement to willingly participate in the restoration of the Bobiri forest reserve was collected; resepondents willingness to participate fee was also collected; additionally data on contribution of the Bobiri forest reserve and socio-economic characteristics of respondents was also collected. For the respondents to get a deep understanding and a firm grip on the good or service being explained, the introductory stage of the questionnaire explained the hypothetical good in question i.e. the Bobiri forest reserve.

Secondary data was extracted from relevant journals, textbooks, articles/reports, documents and new paper bulletins presented by scholars, policy makers and government agencies.

3.3 Research Design

In answering the research questions and achieving the objectives for this study both quantitative and qualitative research strategy was adopted. Questionnaire that captures all the research questions was drafted and administered to a sample of 400 respondents in Kubease which is in the Ashanti region of Ghana. The sample size of 400 was achieved by using Sauder (2007) formula. Using a 5 point likert scale ranging from 1 =Strongly Agree, 2 = Agree, 3 = Neither Agree or Disagree, 4 = Disagree and 5 = Strongly Disagree, Respondents were being asked to indicate their degree of agreement to willingly participate in the restoration of the Bobiri forest reserve after presenting to them the good under study. Respondents were also asked their willingness to participate fee. The socio economic characteristics of respondents were also taken, this included: their age, Gender, Highest level of education, occupation, monthly income, marital status, household size and the numbers of years they have lived in Kubease. In addition to this, respondents were also asked their sources of financial support and if they have access certain household facilities (Electricity, Piped water, Flush toilet, Radio, TV, VCR/DVD, Telephone/Mobile phone and a car). The data collected from the field was then coded into SPSS and analyzed. Tables and graphs were used in presenting the socio economic characteristics of the respondent’s whiles an OLS regression model was also used in determining the factors the influence/affects people’s willingness to participate.

3.4 Sampling method

Random sampling method was used in selecting respondents for this study. According to Schuman (1996) it is the only method that can confidently be used to make generalizations from the sample to the general population. Again, probability sampling allows for generalizations from the sample to the larger study population, this makes probability sampling necessary for any community participation in a restoration study which wishes to make statistical inference (Champ, 2003).

Since the main objective of the study was to assess the economics of community participation in restoration of the Bobir forest reserve, simple random sampling was the best sampling method for this study. Simple random sampling method allows each potential respondent to have an equal likely chance or equal probability of being considered. In addition, each unit, in the entire population, has an equal chance of being included in the sample in each single drawing.

During the administration of the questionnaire every individual who had knowledge about the Bobiri forest reserve and was above the ages of 17 years in the town of Kubease as at that time was a potential respondent. With this notion in mind, every individual met in Kubease as at the time of the administration of the questionnaire was first asked of his/her age and if he/she have any knowledge about the forest reserve. Once the answers to these questions proved positive the person was a potential respondent. The respondents for this study were selected based on their availability and willingness to participate in the survey and also their age and knowledge about the forest reserve was considered.

3.4.1 Target Population and Sample size

The inhabitants of Kubease; a town near Kumasi – Ashanti Region of Ghana, is the population for this study. Kubease is located at an elevation of 228 meters above sea level and its population amounts to 26,909 (Ghana Statistical Service 2012). The inhabitants of Kubease were chosen for the study because the Bobiri forest reserve is situated on the traditional stool land of the Kubease Township. Again, given their proximity and accessibility to the forest, they were in the best position to provide the needed response for the data set. A detailed map that shows the Bobiri forest reserve and Kubease is shown under the study area.

Considering the size of the population, the cost and the time involved, a section of the population were selected to represent the sample size for the topic under study. A number of formulae have been provided for the estimation of sample size (Sauders 2007). In this study Sauders (2007) formula for estimating sample size was used; n = Abbildung in dieser Leseprobe nicht enthalten

Where n is the required sample size, N is the population size, e is the error term. This formula was used with a confidence interval of 95% and an error margin of 5%.

With the population of Kubease being 26,909, the sample size according to the formula above is n = 394.14 (N=26,909/1+ (26,909) (0.05)2. Although the estimated sample size was 394, a sample of 400 respondents was used for the study in order to have a higher response rate and reduce the problem of missing data.

3.4.2 Questionnaire design

To achieve the stated objectives, questionnaires were designed and distributed to respondents. The questionnaire was structured into three parts; the first part of the questionnaire presented the main motive for conducting the study, the next part captured questions on respondent’s willingness to participate and a monthly participation fee for the forest restoration project, the socio-economic and demographic characteristics of respondents was captured in the final part.

Hypothetical Scenario

Respondents for this study were presented were a simple scenario before they were asked their willingness to participate in the restoration project. The scenario was very simple as indicated below;

Suppose there is a programme from Kwame Nkrumah University of Science and Technology (KNUST) to embark on a restoration project in the Bobiri forest reserve. The project will involve planting of over 1000 plant species for a period of five (5) years. This plantation will help replace or depleted part of the reserve. However, the success of the project will require your input and participation by contributing a participation fee.

A 5 point likert scale was used to ask respondents degree of agreement to participate in the restoration project. An open-ended question format was used in asking respondents about their willingness to participate fee to restore the Bobiri forest reserve. This method was used by Bateman et al (1995), Lienhoop and MacMillan (2001) in their studies. Literature on forest restoration suggest respondents often find it difficult to formulate a value spontaneously for a non-marketed good, without any form of assistance, because most often they lack experience in valuing such goods (Bishop & Heberleine, 1979; Cameron & Huppert, 1989; Mitchell & Carson, 1989). As a result, respondents were being assisted and guided in valuing the good in question.

3.5 Model Specification

Economic theory identifies a number of variables that affect peoples’ willingness to participate fee in a developmental project like the restoration of the Bobiri forest reserve. In this study a cross-tabulation of households monthly willing participation fee was used to determine whether different groups of people in the same sample gave different responses to the valuation responses, a multivariate analysis of the determinants respondents preparedness to pay was also performed to give a greater insight into the factors that affect households willingness to participate in the restoration of the reserve. Following the studies of Faham et al (2008), Chowdhury (2004), Atmis el al (2007), Dolisca et al, (2006), Walters (1998), Ishmeal and Adoto (2013), Egan and Estrada (2011); age, income, education, occupation, bid amount, household size, distance to the reserve and number of years lived in or close to the reserve are some of the variables that are normally found to statistically significant effect on willingness to participate. Applying ordinary least squares methodology to the variables used by Faham et al (2008), willingness to participate fee for the forest restoration (dependent variable) was modelled linearly with age (X1), education (X2), monthly income (X3), number of dependents (X4) and employment status (X5) as the independent variables.

The general econometric models are specified as:

WTPF = f (X1, X2, X3, X4, X5) .(1)

The specific econometric models are specified as:

WTPF = ᵝ o + ᵝ 1 X1i + ᵝ 2 X2i + ᵝ 3 X3i + ᵝ 4 X4i + ᵝ 5 X5i + еi...(2)

In the equation above, WTPF is willingness to participate fee; X1 is age; X2 education; X3 income per month, X4 is number of dependents and X5 is employment status; Abbildung in dieser Leseprobe nicht enthaltenrepresent relative effect of the respective independent variable on the dependent; β0 is the intercept and i represents the i-th respondent; and е is the error term which incorporates all other variables that are not stated in the model but affect WTPF.

3.5.1 Dependent Variable:

Willingness to participate fee

Willingness to participate fee as used in the study refers to the monthly amount that households are willing to contribute for the restoration of the Bobiri forest reserve. To be able to get fair values, respondents were first presented a brief introduction of the forest and some expected benefits. Based on these facts and what the respondent already know, each tell the researcher the amount he or she is prepared to contribute. Household’s monthly willingness participation fee for the restoration of the reserve is assumed to be affected by age, education level, monthly income, household size, and length of time lived in the community.

3.5.2 Independent Variables:

Age

Data on age is a midpoint of the particular age range (i.e. 18- 24years, 25-34years, 35-44years, 45-54years and 55+) a respondent chooses. The coefficient of β2 measures the marginal impact of age on WTPF holding other independent variables (the level of education, monthly income, household size and years spent in the community) constant. It is expected that as one gets older year his or her willingness to participate fee would increase. Per economic theory, older people would be willing to contribute a higher fee (leading to a positive coefficient of β2). A positive relationship between age and WTPF then makes β2 > 0.

Level of Education

Education in equation (2) above was measured by using the number years in schooling. Ghana’s education system is divided into three parts; Basic, Secondary and tertiary but the education structure is operated on a 6-3-4-4 system (Ghana Education Service, 2005). That is primary education takes 6years, Junior high school 3years, Senior high school 4years and tertiary also takes 4 years of education. Following the Education structure of Ghana, the number of years spent in schooling started from Zero (0) for normal formation to 17 for Tertiary/University. The scale in the Table 3.1 in Appendix II was used.

Literature on labour and development economics has proved that the higher education leads to more knowledge. As a result it is expected that people with more years of schooling would have a higher propensity and willingness to participate fee greater than those with less education. The ᵝ3 parameter above; measure the marginal effect of number of years spent in schooling on willingness to participate fee; because of the knowledge they have had, people who had more years in schooling are expected to willingly contribute a higher fee; hence ᵝ3 is expected to be positive.

Monthly Income

Demand theory proposes a positive relationship between income and ability to pay for more a commodity at a given price. It is expected that households in high income brackets must be willing to contribute a higher fee than poor families. Data on monthly income for each respondent was the midpoint of the income range (i.e. Below GH¢50.00, GH¢50.00-249, GH¢250-449, GH¢450-649, GH¢650-849, GH¢849-1049 and above GH¢1049) the respondent selected. Because worthy people have much resources they have high willingness to participate fee than their poor counterparts. The ᵝ4 parameter above; measure the marginal effect of monthly income on willingness to participate fee. Because rich people are willing to contribute a higher fee; ᵝ4 is expected to be positive.

Number of Dependents

Dependency ratio analysis proposes that any household greater size (more dependants) is likely to have lower living standard. Though dependency ratio might be large willingness to participate fee would be high because members would pay for the forest to be reserved to aid their agricultural produce that spill over on improved standards of living (i.e. though large, everyone would find something doing). For any additional member to the dependency, willingness to participate fee would increase by a margin. It is expected that there would be a positive relationship between number of dependents and willingness to participate fee; hence β5 > 0. Number of depends was measured by using the number of person(s) that a respondents takes care off or supports financially.

Employment Status

Employment status is a dummy variable that take a value of 1 if the respondents is employed and zero (0) otherwise (or the controlled group). Literature on economics of labour and development has proved that employed people are more economically empowered that the unemployed. As a result it is expected that employed people would have higher willingness to participate fees than their unemployed counterpart (ie. β6 > 0). The β6 parameter above measures the extent to which the willingness to participate fee of employed people differs from the control group (unemployed).

3.5.3 Estimation of Total Willingness to Participate Fee

OECD (1994) provides a methodological approach in estimating total willingness to participate fee in forest restoration by using a frequency distribution of willingness to participate fee bids. Following the OECD’s (1994) approach, the Total willingness to participate fee (TWTPF) of the restoration of the Bobiri forest was calculated by, constructing a frequency distribution of WTPF responses and then multiplying the frequency distribution of the sample by the total population (26909) to get the estimated population in each WTPF response. The result is then multiplied by each WTPF response and summed up to arrive at the TWTPF. The value of the TWTPF is then divided by the population to get the average willingness to pay of respondents.

3.6 Data Presentation and Analysis

The data gathered from the field was carefully screened to detect any possible error or omissions. The data was then coded with an identification number for easy verification, entry and analysis of data. The main statistical packages used for the analysis was Microsoft Office Excel and SPSS (Statistical Package for Social Sciences).

For the socio-economic characteristics of the respondents, the data coded was analyzed by using graphs and tables, contribution/benefits from the Bobiri forest reserve was also presented in tables, to determine the varying willingness to participate fee within the same socio-economic group a cross tabulation was used and an OLS regression model with WTPF as the dependent variable and benefits, education, monthly income and number years respondents has lived in the community as the independent variables were run to determine the factors the influence peoples willingness to participate in the restoration of the Bobiri forest reserve.

CHAPTER FOUR RESULTS PRESENTATION, ANALYSIS AND DISCUSSIONS

4.1 Introduction

This chapter present results, analysis and discussion of data collected from community members living in Kubease. It entails facts on each of the objectives of this study starting with the socio-economic characteristics of respondents, followed by contribution of the Bobiri forest to the Kubease community, economic factors that influence willingness to participate in restoring a forest reserve, and assessing the degree of agreement to willingly participate in the restoration of the Bobiri forest reserve.

4.2 Socio-economic characteristics of respondents

4.2.1 Age structure

Although all age groups were considered (except children – below 18 years), the study turned to be skewed towards the active working age group. Table 4.1 below shows that respondents were more of youth who are actively participating in the labour market. The table shows that 89.75% of the respondents are between eighteen and fifty-four years respectively. Out of the 400 sampled respondents used for the study 20.25% are older than 18 years but younger than 24 years; 36.75% are between the ages of 25 and 34; 21.75% in the 35 to 44 years age range; 11% between 45 and 54 years; 10.25% older than 55 years. The facts shows that the sampled respondents are best fit for the study; they are all matured, can make informed decisions, and understand better the uses of the natural environment.

Table 4.1: Age distribution of respondents

illustration not visible in this excerpt

Source: Authors Field Survey, 2014.

4.2.2 Level of Educational

All else equal the more education one has the more he understands benefits of the environment. The study showed that more than four-fifth of the respondents have had some form of education. From Table 4.2 below more than two-fifth of the respondents (44.25%) had Junior High School as their highest education level.

Table 4.2: Level of education of respondents

illustration not visible in this excerpt

Source: Authors Field Survey, 2014.

This was followed by illiterates (16.25%), those who made it only to primary school (15.5%), Senior High School or Vocational or Technical school certificate holders (15%), and tertiary cum university degree holders (9.0%). Just as the age of respondents, most of the people interviewed – all things equal – were in the best position to know much about the benefits of natural reserves because almost all have some sort of education. Table 4.2 above shows that only 16.25% out of the 400 respondents have no education.

4.2.3 Number of year’s respondents have lived in the community

The number of years respondents have lived in the Kubease community was fairly enough to know much about the Bobiri forest reserve. Table 4.3 below shows that 96 out of the 400 respondents (24%) have lived in the community for less than 5 years, 65 (16.20%) for more than five years but less than 11 years, 8.5% for between 11 to 15 years, 13% for between 16 to 20 years and 38.2% for more than 20 years. These statistics show that 76% (304) of the sampled community members have lived in the community for more than five years. This put respondents in better position to tell much about forest; the benefits they enjoy from it and how much they are willing to contribute to restore it.

Table 4.3: Number of year’s respondent’s have lived in the community

illustration not visible in this excerpt

Source: Authors Field Survey, 2014.

4.2.4 Occupation of people living in the community

Facts from the study suggest that most of the Kubease people have some sort of job(s) to do. Only 14.25% of respondents were unemployed (9.75%) or in school (4.5%). Table 4.4 below shows that farming is the main occupation in the community employing almost one-third (33.25%) of the sampled respondents. This is followed by trading employing some 27% of the workforce, self-employed (13.50%) and civil servants (12.00%).

Table 4.4: Occupation of respondents

illustration not visible in this excerpt

Source: Authors Field Survey, 2014.

4.2.5 Monthly Household Income

Results from the study show typical village level characteristics. With most of them being farmers it is not surprising that their income levels are relatively low. Table 4.5 below shows that about 83.5% of respondents live on incomes less than GH¢450 per month. Approximately 26% live on incomes less than GH¢50 monthly, 40.75% on incomes between GH¢50 to GH¢249 per month and 16.75% on incomes between GH¢250 to GH¢449. Only 16.5% live on incomes more than GH¢450.

Table 4.5: Level of income of respondents

illustration not visible in this excerpt

Source: Authors Field Survey, 2014.

These low levels of income are expected to affect their willingness to participate fee and access to certain household amenities because they have relatively less to spend.

4.2.6 Household sizes and dependency burden

Theories in economics and sociology posit that rural areas tend to have a high dependency burden because high level of procreation (the end product of limited sources of entertainment). Results from the study confirm it. Table 4.6 below shows that a greater portion of the respondents interviewed have household sizes of four (4) or more dependants. The study showed that 21.25% of the respondents live in households with a size of 4, 32.25% with household size of five and 28.50% with size of six or more. From the table the least household size is one but the modal household size is five. Using data from the study to calculate the average household size, each household has on the average five dependents. These high dependency ratios have the capacity to reduce the willingness to participate fee of respondents.

Table 4.6: Household Size

illustration not visible in this excerpt

Source: Authors Field Survey, 2014.

4.3 Contribution of the Bobiri forest to the Kubease community

The environment according to economists is seen as a composite asset that provides a variety of services. The environment provides three basic functions to every economy; it serves as a source of raw material, source of amenity and a waste sink or assimilative capacity. Results from the study show that the Bobiri forest reserve as an environmental asset provides the people of Kubease with all the functions stated above. Almost everyone interviewed in a way get some benefit(s) from the functions provided by the forest. Out of the 400 respondents interviewed, 59.75% get raw materials such as firewood (14.00%), building posts (10.50%), medicinal herbs (10.50%) and traditional tools (5.25%) from the reserve, 19.25% also said the forest aids water regulation (3.00%), soil fertility (6.75%) and pollination (9.50%). Finally 21.00% enjoy other non-use values like the satisfaction of knowing that an ecosystem exist (existence value), satisfaction of knowing that other people have access to the benefits of the reserve (altruistic value) and the satisfaction of knowing that the future generation will have access to the forest reserve (bequest value). Further analysis is shown on Table 4.13 in appendix II.

4.4 Factors that influence willingness to participate in restoring of Bobiri forest reserve

In this study the amount that households are prepared to pay monthly to restore the Bobiri forest reserve is termed as household’s willingness to participate fee (WTPF). Several literature have modelled WTPF by using socio-economic factors like age, gender, occupation, monthly income, level of education, number of dependents and employment status (Carson, Flores, & Meade, 2001).

4.5.1 Cross-tabulation of WTPF responses with socioeconomic characterises.

The inference was to know how respondent’s WTPF correlate with their socioeconomic characteristics. This gives an idea of groups which were more willing to participate for the project to be undertaken in the Bobiri forest reserve. Table 4.7 below shows the relationship between respondents WTPF and selected socio-economic variables.

From Table 4.7 it is evident that the active working group are willing to contribute higher fees than the aged. Although majority of those older than 55 years are willing to contribute, the volume of the amount they could contribute is relatively low as compared to those in the 18 – 54 age groups. Out of the 41 people in the ‘55 or above’ age group, only 5 are willing to contribute GH¢20 or more per month. But the younger one is, the greater they are willing to contribute. This confirms the basic economic theory that predicts a positive relationship between age and WTPF.

Table 4.7 below also shows that respondents who are educated are willing to contribute more fees than their illiterate counterparts. Although some of the illiterates are willing to contribute a fee the magnitude of those who are not willing is relatively high. Out of the 335 people who have at least primary school education only 39 are (11.64%) not willing to contribute a fee; all 36 tertiary degree holders are willing contribute a fee for the forest restoration.

From the Table 4.7 below it could be seen that respondents with higher monthly income are willing to contribute higher participation fee than low income earners. Although majority of those whose monthly income fall below GH¢50 are willing to contribute a fee the magnitude of the amount they could pay is relatively low. Out of the 85 people who are willing to contribute a participation fee, the ‘less than GH¢50’ group (104 minus 19) 91.76% (representing 78 out of 85) are willing to contribute GH¢10 or less. But as monthly income increases, the willingness to participate fee also increases. This confirms the basic economic theory that predicts a positive relationship between income and WTPF.

From Table 4.7 below it could be seen that respondents with high household sizes and dependency burden are willing to contribute lower amount than small size families. Although majority of respondents with dependent size of three or more are willing to contribute a fee the magnitude of the amount they could pay is relatively low. Out of the 349 respondents who are willing to contribute a fee, irrespective of size of family, 55 (15.76%) of those with family size of five are willing to contribute a participation fee of GH¢5 per month. It is worth noting that the household sizes of people living in Kubease are relatively large.

Table 4.7: Cross-tabulation of WTPF responses with socio-economic characteristics

illustration not visible in this excerpt

Source: Author’s Construct, 2014.

4.5.2 Multivariate analysis of the determinants of WTPF

The main determinists of individual’s willingness to participate fee as proposed by economic theory in this study is monthly income and use and non-use value of the environmental good or service in question. As proposed in Chapter Three an econometric approach was used in determining the factors that affect people’s willingness to participate fee to restore the forest reserve. Using willingness to participate fee as the dependent variable; and age, education (number of years in schooling), monthly income, number of dependent and employment status as the independent variables yielded the following regression results.

Table 4.8: Regressions Results of the Willingness to Participate Fee Model

illustration not visible in this excerpt

Source: Author’s Construct, 2014.

Results of Model 1 above show that all the independent variables relate positively to willingness to participate fee. Age, Education (Number of years in schooling), monthly income, number of dependents and employment status all have positive coefficients but they differ in magnitude on the effect each has on willingness to participate fee.

4.5.2.1 Age

The influence of age on community participation is not very clear. Whiles studies have found age to be an insignificant variable that affect community participation in restoration (Thacher, 1996; Zhnag and Flick, 2001) others have found it to be significant (Atmis et al, 2007). In this study, Age as an independent variable is a midpoint of the age range a respondent chooses. The coefficient of 0.017 measures the marginal impact of age on WTPF holding the level of education, monthly income, number of dependents and employment status constant. It means if one gets older by a year his or her willingness to participate fee would increase by 0.017. The positive sign of the coefficient shows that there is a positive relationship between age and WTPF. Per economic theory as proposed by the basic economic models, older people must be willing to contribute a higher participation fee (leading to a positive coefficient) and the results confirm it.

4.5.2.2 Level of Education

Studies have shown that level of education influence community participation in forest restoration (Lise, 2000; Glendinning, 2001; Owubah, 2001; Chowdhury, 2004). Education level of respondents in this study was measured by using the number of year(s) in schooling. Per economic theory an educated person is assumed to have much knowledge on the usefulness of the forest reserve and must be willing to contribute higher participation fee. This assumption is confirmed by the result with a positive coefficient of 0.024 for the number of years in schooling. The coefficient of 0.024 measures the marginal impact of the number of years in schooling on WTPF holding age, monthly income, number of dependents and employment status constant. This implies that as an individual acquire an additional year in schooling his/her willingness to participate fee would increase by 0.024.

4.5.2.3 Monthly Income

People’s monthly income; as economic theory proposes, is a yardstick households use to budget for expenses to be incurred. Just as age income for each respondent is also a midpoint of the range of income the respondent selected. All else equal, the higher a person’s monthly income the higher the probability to pay to restore a natural reserve. Results from Table 4.8 above shows that there is a positive relationship between monthly income and willingness to participate fee. For any unit rise in respondents’ monthly income, they would be willing to contribute a participation fee of GH¢0.001 more. That is to say any GH¢1,000 increase in respondent’s income would result in a GH¢1 increase in their willingness to participate fee.

4.5.2.4 Number of Dependents

Number of household dependent has also been found to influence community participation in forestry (Dolisca et al, 2006; Varamini, 2003). From dependency ratio analysis any household that has a greater size is assumed to have lower living standard. The dominant occupation for the people of Kubease is farming; which the forest helps to be successful. Though a number of dependents might be large willingness to participate fee would be high because they would pay for the forest to be restored to aid their agricultural produce that spill over on improved standards of living (though large, everyone would find something doing). Results from Table 4.8 above shows that there is a positive relationship between number of dependents and willingness to participate fee. For any additional member to the dependency size, willingness to participate fee would increase by GH¢0.715.

4.5.2.5 Employment Status

Employment status as an independent variable is a dummy with value one (1) if the respondent is employed and zero (0) if otherwise. The coefficient of 0.74 measured the extent to which the average willingness to participate fee of employed people differs from the unemployed ones (the controlled group) irrespective of age, level of education, monthly income and number of dependents. The positive sign of the coefficient shows that the average willingness to participate fee of employed people is higher than that of the unemployed by approximately GH¢0.74. Per economic theory, employed people are more economically empowered to pay more that the unemployed and the results confirm it.

It is worth noting that number of years in schooling, age and monthly income are individually statistically significant at 5% level; and number of dependents and employment status are individually significantly at 1% level.

Because all independent variables used are statistically significant, the coefficient of determination (R squared) is high. The results in Table 4.8 show that approximately 79.9% of the variation in the dependent variable (willingness to participate fee) is explained jointly by the variation in the independent variables. Added, the independent variables are jointly statistically significant at 1% level with a p-value of 0.000. This p-value is significantly lower than the 1% level of significance as used in economic researches and presents enough evidence to reject the null hypothesis that the independent variables are jointly not significant.

4.6 Asses the level of agreement to participate in restoring the Bobiri forest reserve

Borrowing the ideas of Likert (1932), respondents were being asked to rank the extent to which they agreed or disagreed to participate in the restoration of the Bobiri forest reserve. A 5 point likert scale ranging from 1 = Strongly Agree, 2 = Agree, 3 = Neither agree or disagree, 4 = Disagree and 5 = Strongly Disagree was used.

Table 4.9: Frequency distribution for willingness to participate in restoring BFR

illustration not visible in this excerpt

Source: Authors own construct (2014)

Table 4.9 above shows respondents’ degree to agreement to participate in the restoration of the Bobiri forest reserve. As indicated earlier, a 5 point likert scale where 1 = Strongly Agree, 2 = Agree, 3 = Neither, 4 = Disagree and 5 = Strongly Disagree was used. 74 of the respondents constituting 18.50% of the total response strongly agreed to participate in the restoration of the Bobiri forest reserve. 25.25% (101) also agreed to participate in the restoration project. 28.25% which constituted the highest response were not certain whether they will participate or not participate in the project. However, 23.75% (95) of the respondents disagreed not to participate in the restoration project.

4.7 The Total Willingness to Participate fee for Bobiri forest restoration

As stated in Chapter Three, the Total willingness to participate fee (TWTPF) for restoring Bobiri forest is calculated by, constructing a frequency distribution of WTPF responses and then multiplying the frequency distribution of the sample by the total population (26909) to get the estimated population in each WTPF response. The result is then multiplied by each WTPF response and summed up to arrive at the TWTPF.

Table 4.10: Frequency Distribution for Bobiri forest respondents

illustration not visible in this excerpt

Source: Authors Construct, 2014

The first column in Table 4.9 shows respondents stated monthly willingness to participate fee. The second column gives details of the number of respondents who were willing to contribute the stated amount and the final column shows the percentage of responses. From Table 4.9 above majority of the respondents (25.5%) paid a monthly willingness to participate fee of GH¢5.00, followed by GH¢10.00 with a total response of 20.25%. The maximum monthly amount that respondents paid as willingness to participate fee was GH¢100.00 and the minimum contribution was GH¢1.00.

Table 4.11: Total Willingness to Participate fee (TWTPF) of Kubease population for the restoration of the Bobiri forest reserve

illustration not visible in this excerpt

Source: Author’s Construct, 2014.

In arriving at the total willingness to participate fee in restoring the Bobiri forest reserve the frequency distribution table above was constructed. The percentage of total population which is in the second column was calculated by multiplying the population (26909) by their respective frequency distribution in the first column. For example, to get the percentage of population who paid GH¢1.00, the population (26909) was multiplied by the percentage of those respondents (i.e. 5.75% * 26909 = 1547). Total willingness to participate fee which is in the fifth column was ascertained by multiplying the respective percentage of population by the amount that respondents paid as willingness to participate fee. For example, a willingness to participate fee of GH¢1.00 is multiplied by a population of 1547 to arrive at a TWTPF of 1547 (i.e. GH¢1*1547 = 1547). The summation of the willingness to participate fee gives a total willingness to participate fee of GH¢208,545 (i.e. 1547+9418+6256+2960+34309+54491+18836+33636+47091 = 208545). This implies that, the monthly total willingness to participate fee in restoring the Bobiri forest reserve is GH¢208,545 and the annual amount is GH¢2502537.

Table 4.12: Total Willingness to Participate Fee (TWTPF) of Ghana’ population for the restoration of the Bobiri forest reserve

illustration not visible in this excerpt

Source: Authors construct 2014

The stated monthly willingness to participate fee for the restoration of the Bobir forest reserve by the respondents of Kubease was used to calculate the national (Ghana) total willingness to participate fee for the bobiri forest restoration. The study used the population of people who were 18 years and above. According to the Ghana Statistical service (2010), the population of Ghanaians who were 18 and above years was 13,632,299. Following the same methodology in Table 4.11 above, it was realized that the total monthly willingness to participate fee for bobiri forest restoration for the population of Ghanaians who are 18 years and above was GH¢105,650,317. This implies an annual willingness to participate fee of GH¢1,267,803,807 for the restoration of the Bobiri forest reserve.

CHAPTER FIVE FINDINGS, CONCLUSION AND RECOMMENDATION

5.1 Introduction

This study was conducted to assess the economics of community participation in the restoration of the Bobiri forest reserve. This chapter presents a summary of all major findings, recommendation and conclusion of the entire research.

5.2 Summary of findings

Most of the literature reviewed in the study showed that community participation or involvement is an integral factor for the success of any restoration project. This study was conducted with a primary aim of assessing the economics of community participation in the restoration of the Bobiri forest reserve at Kubease in the Ashanti Region of Ghana. Other objectives were to assess the contribution of the forest to the Kubease community; identify the economic factors that influence people’s willingness to participate fee in forest restoration project and assess the degree of agreement to participate in the restoration of the Bobiri forest reserve.

Results from the study show that almost every person interviewed in a way get some benefit(s) from the forest. The benefits range from household ones to commercial, traditional or cultural, environmental protection purposes. Household get their source of energy (firewood); fruits; meat; and grazing land to farmers who rear animals. To handicraft workers and herbalist the forest serves as a source of lucrative businesses to them. As other nature reserves the forest serve as source of revenue to the community through tourist attraction. The forest also helps to protect the environment by checking soil erosion and serving as wind breaks as well to the community. It also serve as a habitat to wild animals, gods and ancestors that the community cannot live with but are very worthy to them.

In assessing factors that affect people’s willingness to participate fee in a restoration project, cross-tabulation and regression methodologies were used. The results identified number of years in schooling, household monthly income and age as the three variables that are statistically significant at the 5% level. The results also found number of dependents and employment status to be individually statistically significant at the 1% level. All the variables used were jointly statistically significant at the 1% level. The model had a strong goodness of fit with R-squared of 0.799. This means that the variables used in this study have significant effect on household’s willingness to participate for a restoration project.

Using a 5 point likert scale to assess respondent’s degree of agreement to participate in the restoration of the Bobiri forest reserve, it was realize that majority (43.75%) of the respondents either strongly agreed or agreed to participate in the restoration project. Most respondents (349 out of 400) were also eager to contribute some amount of money to restore the forest but these contributions were relatively low because their incomes are low and they have little or no education on the uses of the forest. Close to 60% of them (59.25% out of the 400) were willing to contribute amount ranging from GH¢1 to GH¢5. The highest bid price recorded was GH¢100 and the lowest was GH¢1. The annual Total willingness to participate fee (TWTPF) for the restoration of the BFR for the population of Kubease (26909) was GH¢2,502,537 and the national annual TWTPF for the population of Ghana aged 18 years and above was GH¢1,267,803,807.

5.3 Conclusion

Cost or price in the modern world is essential in making economic decisions. According to FAO (2010), from 2005 – 2010 the rate of deforestation in Ghana stood at 2.17% and it represents the sixth highest in the world. This pattern shows a continuous decline in Ghana’s forest reserve. This study was conducted with a principal aim of assessing the economics of community participation in the restoration of the Bobiri forest reserve at Kubease in the Ashanti Region of Ghana. Other objectives included: assessing the contribution of the Bobiri forest reserve and identifying the economic factors that affect people’s willingness to participate fee in a forest restoration project. Using three research questions, reviewing several literatures and adopting the appropriate methodology all objectives for this study was achieved. A sample of 400 respondents from Kubease was used in the study and it was realised that majority (43.75%) either strongly agreed or agreed to participate in the restoration of the Bobiri forest reserve. Regressing willingness to participate fee on some selected variable found age, number of years in schooling, monthly income, number of dependents and employment status as the variables that have significant effect on willingness to participate. This follows the findings of Tilahum et al (2011), Alec (2010) and Firoozan et al (2012) who all found monthly income, level of education and age as the main determinants of willingness to participate. It was also found that the forests provides raw materials such as firewood, building posts, medicinal herbs and traditional tools, amenity value and also serve as a waste sink to the Kubease community. The findings fit into the conceptual framework for the study. Some recommendations have been made to prolong the lifespan of the forest reserve.

5.4 Recommendations

One major findings of the study was; high level of community participation in the restoration of the Bobiri forest reserve. The study therefore recommends strongly that, community members should be involved in any forest restoration project. Their contributions in any decision making process in a restoration project should be considered as very important.

The study also recommends that, the government and other stakeholders should follow the findings of this study to establish a payment system that would help collect money from people to assist the restoration of forest reserves in Ghana.

Again much emphasis should be placed on the restoration of most of the lost forest reserve in Ghana since forestry was noticed in the study to be very important both on the local and international level.

Based on the findings of the study it is recommended that the Bobiri forest must be restored because most people are willing to participate to restore it. Though on average the monthly income of people living in Kubease are low, restoring the forest would be more beneficial to them than to relinquish it. The benefits they get from the forest can persist for decades to help even upcoming generations.

It is also recommended that communities closer to forest reserves must be educated well on the benefits of the reserve. Activities such as sources of firewood, source of meat, source of timber, etc. are all killing the richness of the forest. In-depth knowledge on the potential effects of such activities; which can be achieved through education, would help reduce such activities.

Lastly it is recommended that a further research should be conducted on similar forest reserve in Ghana to assess the preparedness of community members in restoration of the lost forest reserve in Ghana.

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APPENDIX I

SAMPLE QUESTIONNAIRE

I am Abaidoo Anthony an MPHIL student from Kwame Nkrumah University of Science and Technology (KNUST) and I’m here to work on a project that seeks to provide AN ECONOMICS OF COMMUNITY PARTICIPATION IN THE RESTORATION OF BOBIRI FOREST RESERVE IN GHANA. Your attention and input is very important for the success of the project and every information that you provide will be treated with strict confidentiality.

Date: [ ]

Questionnaire Number: [ ]

The market scenario for the environmental good or service

Suppose there is a programme from Kwame Nkrumah University of Science and Technology (KNUST) to embark on a restoration project in the Bobiri forest reserve. The project will involve planting of over 1000 plant species for a period of five (5) years. This plantation will help replace or depleted part of the reserve. However, the success of the project will require your input and participation by paying some amount.

WILLINGNESS TO PARTICIPATE

The project to help restore the Bobiri forest reserve for it to continue to provide goods and services will require that you willingly decide to participate.

1. Are you willing to participate in the restoration project? [ ] Yes [ ] No

2. On a scale of 5 where 1 =Strongly Agree, 2 = Agree, 3 = Neither Agree or Disagree, 4 = Disagree and 5 = Strongly Disagree. Please indicate your degree agreement to willingly participate in restoring the Bobiri forest reserve.

[1] Strongly Agree, [2] Agree, [3] Neither Agree or Disagree, [4] Disagree [5] = Strongly Disagree.

2. Kindly state your willingness to participate fee for the restoration of the Bobiri forest reserve? GH¢.

4. Please indicate the benefits you get from the functions provided by the forest

SOCIO-ECONOMIC DATA

4. Age (years)? [ ] 18 – 24 [ ] 25 – 34 [ ] 35 – 44 [ ] 45 – 54 [ ] 55 +

5. Gender? [ ] Male [ ] Female

6. What is your highest level of Education? [ ] None [ ] Primary [ ] JHS/Middle school [ ] SHS/Vocational/Technical [ ] Tertiary/University

7. From Q6, please specify the number years spent in schooling?

7. What is your occupation? [ ] Student [ ] Farmer [ ] Trader [ ] Civil Servant[ ] Unemployed [ ] Self employed

8. How much do you make per month? [ ]Below GH¢50.00 [ ] GH¢50.00 – 249 [ ] GH¢250 – 449 [ ] GH¢450 – 649 [ ] GH¢650 – 849 [ ] GH¢850 – 1049 [ ] Above GH¢1049

9. Marital Status? [ ] Married [ ] Divorced [ ] Single [ ] Widowed

10. What is the size of your household? [ ]

11. How many people do you support financially? (those who depend on you for a living) [ ]

11. Who provides monetary support for your family? [ ]Spouse/partner [ ] Children [ ] Others please specify….

12. For how long have you been living in this community? [ ] Less that 5 years [ ] 5 – 10 years [ ] 11 – 15 years [ ] 16 – 20 years [ ] More than 20 years.

13. Does your household have: (Please tick)

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APPENDIX II

TABLES AND GRAPHS

Table 4.13: Benefits/contribution of the Bobiri forest reserve

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Source: Authors field survey (2014)

Table 4.14 Gender

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Source: Authors field survey (2014)

Figure 4.3: Marital Status

Abbildung in dieser Leseprobe nicht enthalten

Source: Authors field survey (2014)

Figure 4.4: Source of Financial support

Abbildung in dieser Leseprobe nicht enthalten

Source: Authors field survey (2014)

Table 4.15: Access to household facilities

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Source: Authors field survey (2014)

Table 3.1 Education Structure of Ghana

Abbildung in dieser Leseprobe nicht enthaltenSource: Ghana Education Service (2005)

Table 4.16: Number of Dependents

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Source: Authors field survey (2014)