This thesis quantifies the economic values of East Mau forest ecosystem using Market based, Contingent Valuation and Benefit Transfer techniques. Data was collected from households, sawmills and forest product traders within and adjacent to East Mau forest. Additional data were obtained from published and unpublished sources. Descriptive statistics and parametric tests were applied to describe forest ecosystem values. Difference in forest incomes across locations; ethnicity and wealth classes were tested using comparison of means and ANOVA. A multiple regression model was used to identify determinants of forest dependence with relative forest income and socio-economic characteristics as dependent and independent variables respectively. The total economic value (TEV) of East Mau forest ecosystem was KES 24billion (US$266million) per annum and indirect use values formed the bulk of TEV at KES 19.7billion (US$219 million) (82.4%), direct use values was KES 4.2billion (US$ 46million) (17.5%), and non-use values was KES 31million (US$ 347, 000 (0.1%). The bulk (96%) of direct use values were appropriated by local communities. Carbon sequestration and oxygen generation contributed 79% of indirect use values and 65% of the TEV. The local community and government of Kenya are subsidizing conservation of East Mau by KES 650million (US$7.2million) per annum. The bulk of ecosystems values (65%) accrue to global community and only 35% are appropriated by local communities and government of Kenya. Forest income contributed 33% of household income and poor households are more dependent on forests resources. However, in absolute terms, the wealthy derived greater monetary benefits from forest resources. The key determinants of forest dependence are off- farm income and number of cattle. These results provide valuable information on the types and magnitude of values that could be relevant in decision-making concerning conservation and management of East Mau forest ecosystem for enhanced ecosystem services and livelihoods.

Background to the Study
Forests cover about 25% of the world’s land mass and are critical in provisioning of various commodities and services such as water, food, medicine, fuel wood, fodder and timber. Forests also provide a wide range of environmental services that support biodiversity conservation, watershed protection, protection of soil and mitigate global climate change (Landell-Mills and Porras, 2002). However, there is unprecedented increase in deforestation globally. According to the Food and Agriculture Organization (FAO) about 13million hectares of world’s forests are cut down and converted to other land uses every year (FAO, 2006). For instance, in the period 1990 to 2000, the world lost about 3% of its forest cover to alternative land uses (UNEP, FAO and UNFF, 2009). This raises serious concerns about the sustainability of the various ecosystem services provided by the forest ecosystems.

Africa is endowed with diverse, rich natural and plantation forests which cover 23 percent of the land area of the continent. These forests provide a wide range of goods and services that create opportunities for development, and support the livelihoods of millions of people, living in and around the forest. For example, forest resources contribute about 6 per cent of the Gross Domestic Product (GDP) of the national and local economies in the region but this value exclude fuel wood energy which account for about 90 per cent of domestic energy and subsistence forest uses (Barrow et al., 2009). African forest constitute 21 per cent of global total of carbon stock in forest biomass and have the capacity to sequester up to 680kg of carbon per hectare per year, thereby providing critical buffer against global climate change (Katerere et al., 2009). Despite the importance of forests in Africa’s socio-economic development and sustainable development, the forest estate is declining at a faster rate due to increasing deforestation, land degradation and poor forest management practices. From 2000 to 2010, Africa recorded an annual loss of about 3.4million hectares making it second largest net forest loser in the world (ECA et al., 2012).

Forest resources in Kenya are undergoing tremendous degradation through sanctioned excisions, illegal encroachments and illegal extraction.

The rate of deforestation is currently between 0.4% and 1.2% per annum (Mogaka, 2005). Decades of anthropogenic activities have resulted in degraded forests resulting in loss of biodiversity, impaired ecosystem functions and less availability of important wood and non- wood forest products (KEFRI, 2005).The majority of Kenya’s 3million forest people depend on forest resources and agricultural activities for their livelihoods (Chao, 2012). The direct forest use and indirect use values contribute 1% and 13% to GDP respectively (World Bank, 2000; UNEP, 2012).

The Forestry sector provides linkages with agriculture and livestock sectors, which are the backbone of Kenya’s economy. The sector supports agriculture through soil and water conservation and amelioration of environment and provides economic benefits such as generation of jobs in the rural areas in small and medium-scale forest products processing industries. The regulating services of Kenya’s natural ecosystems are important production factors to the agriculture, forest and fishing sectors, the energy and water sectors, tourism , the public administration and security sectors, and sustain a large proportion of the country’s population (SEI, 2009; UNEP, 2012). These sectors, together, contributed between 33% and 39% in Gross Domestic Product (GDP) between 2000 and 2010 (UNEP, 2012). In addition, these sectors have a significant multiplier effect on the rest of the economy’s GDP. For example, more than 90% of the country’s domestic energy requirements are met by fuel wood. One of the highest sources of foreign income is wildlife tourism, which is highly dependent on forest ecosystem (MENR, 1994). Forest ecosystems minimize risks to the economy through the provision of regulatory functions (climate and disease control) and thus provide insurance values to the economy, during times of market volatilities and when security and exports of goods in certain sectors may be a challenge (UNEP, 2012). This insurance value is critical for maintenance of economic resilience in the face of unpredictable variability of environment and economic conditions and also minimizes long-term economic hazards like climate change (UNEP, 2012).

Despite its critical importance in ensuring environmental stability and economic development, forests ecosystems in Kenya are facing unprecedented challenges because of burgeoning population, poverty and accelerated conversion to other land uses (Allaway and Cox, 1989; SEI, 2009). This problem is partly explained by the lack of appreciation of total economic values and the costs of forest degradation (Allaway and Cox, 1989; Emerton, 1996; Emerton, 2001; Mogaka, 2001).

Most policy decisions concerning management and conservation of forest resources do not consider the non-market benefits of the forest ecosystem and therefore a large part of economic costs of forest degradation is ignored in natural resources decisions by policy makers (Emerton, 2001; Mogaka, 2005; Kipkoech et al., 2011). This leads to inappropriate allocation of resources and less investment in forest ecosystems. The role played by forests in the provision of ecosystems services such as biodiversity conservation, amenity reservation and aesthetic values are positive externalities which accrue to the public at local, regional, national and global levels. Most ecosystems services unlike conventional goods and services have no developed markets and their prices are not easily determined (Pearce et al., 2002). This has consequently resulted in forest degradation and subsequent negative impacts on hydrological functions such as irregular rainfall, reduction in water levels in rivers and lakes and increased flushness of medium-sized storm flows due to decreased base flows (Mogaka, 2005; Otuoma et al., 2011). The impacts of forest clearance has exacerbated flooding and mitigation costs for irrigation, flood control and hydropower generation. For example, by 2011 human activities in upper catchment of Masinga dam had resulted in the loss of water storage capacity of the dam by 215.26m3 (13.59 %) of its design storage capacity to sedimentation (Bunyasi et al., 2013). Forest resource degradation is costing the national economy about KES 175million (US$ 3.5million) per annum due to flush floods, health hazards and crop failures (Mogaka, 2005). Moreover, the country has wood products deficit (fuel wood, timber, pulp and paper and poles).The situation will be exacerbated by further deforestation and environmental degradation that will negatively impact on the livelihoods of the local people (Mogaka, 2005). If natural forests are not restored and the process of deforestation halted, it may reduce land productivity and exacerbate vulnerability to climate change (ACTS and ACC 2011). It is, therefore, important that decisions about forest resources take account of all costs and benefits to ensure their optimal uses.

The Mau complex forms the largest closed-canopy montane forest ecosystem in East Africa covering approximately 400,000ha. It is situated at 0°30’ South, 35°20’ East within the Rift Valley Region and spans seven counties: Baringo, Bomet, Keiyo-Marakwet, Kericho, Nakuru, Nandi, and Narok. The area is thus the largest water tower in the region, being the main catchment area for 12 rivers draining into Lake Baringo, Lake Nakuru, Lake Turkana, Lake Natron and the Trans-boundary Lake Victoria (Kipkoech et al., 2011). East Mau forest is one of the critical forest blocks of the Mau Forest Complex (MFC).

It is a source of river Njoro and river Makalia that support Lake Nakuru ecosystems, the largest bird sanctuary in the world and important tourism destination. Additionally, it is the source of Mara River, which is a source of water for the wildlife and livestock in the extensive Mara River Basin and ecosystem–world famous site for spectacular wild beast migration and tourism destination and thriving livestock sector. The forest block was originally about 66,000 ha of contiguous forest and formed one-fifth of the MFC. However, it lost 50% of its size due to excisions for human settlement in late 1990’s and early 2000 (UNEP et al., 2006). The encroachment and excisions have led to drastic and rapid land fragmentation, deforestation of watershed and destruction of wetlands in fertile upstream areas (Olang and Kundu, 2011).

The government of Kenya (GoK) recognizes the important role the environment plays in supporting the productive sectors of the economy and this is amplified in the Vision 2030 (GoK, 2007a). To achieve the noble objectives of Vision 2030, the Government of Kenya (GoK) is committed to enhance the protection of critical “water towers" in the country including Mau Forest Complex (MFC). The government of Kenya has initiated a series of reforms in Forestry and Environmental Sectors through policies and legislations (MENR, 1994; GoK, 2005; GoK, 2007b; GoK 2015a). The draft new Forest Policy 2015 proposes to integrate all forest values into the national development processes (GoK, 2015) and recognizes the important role the forest ecosystems play in socioeconomic development of the nation.

The National Forest Policy of Kenya, (GoK, 2015a) and the revised Forest Conservation and Management bill 2015(GoK, 2015b), recognizes and support the active participation of local communities in forest management. The Participatory Forest Management (PFM) approach seeks to develop partnerships between Kenya Forest Service (KFS) and local communities as co-managers for sustainable forest management. However, KFS has not developed a benefit sharing framework suitable for reconciling conservation and livelihoods of the local people (Mariara and Gachoki, 2008). In this context, it is important to know the extent of forest use and level of community’s forest dependence and identify factors that influence forest dependence. Many studies in other parts of the world continue to define the crucial role forest resources may play in poverty alleviation and minimizing income inequalities (Mamo et al., 2007; Kamanga et al., 2009).

In addition, it has been shown that the forest extractive activities of households are, in fact, quite diverse both within and across communities (Coomes, 1995; Coomes and Barham, 1997, Mariara and Gachoki, 2008; Heubach, 2011). This diversity or heterogeneity means that whereas forest products may represent major sources of income for some households, others in the same community may rely primarily on other sources such as agriculture for their livelihoods. Thus, the factors that influence household participation in forest activities are critical in designing appropriate conservation strategies. Despite the increasing knowledge on forest-livelihood links in developing countries (Cavendish, 2000; Angelsen and Wunder, 2003; Fisher, 2004; Adhikari et al., 2004, Vedeld et al., 2004; Angelsen et al., 2014), there are few studies on forest –livelihood dependence in Kenya. Although, it is known that forests in Kenya support forest adjacent communities, there is little quantitative data on the extent of forest use and contribution of forest income to household welfare. Most of the information on contribution of forest resources to households is descriptive, and often location specific (MENR, 1994; Emerton 1996; Emerton, 2001; Mogaka, 2001; Langat, et al., 2005; Langat and Cheboiwo, 2010 b). The net effect is poor understanding of the role of forests in local livelihoods. Most studies of forest valuation in Kenya have largely relied on direct use values for few selected forests (Mogaka, 2001; Emerton, 1996, 2001; Langat and Cheboiwo, 2010(b) but do not include quantitative information on household-level use or activities that cover a complete range of forest products and the importance of forest resources in local livelihoods and the wider economy. What is important in designing a win- win strategy for forest conservation and household welfare is a clear understanding of all forest values, households’ forest dependence on products and services, factors influencing household’s forest dependence, distribution of costs and benefits of conservation to different stakeholders and the potential linkages between conservation and livelihoods.

Statement of the Problem
In the last three decades, the East Mau forest area in Kenya has declined primarily due to anthropogenic activities. Central to the anthropogenic activities is the dependence of the people on forest products and services for livelihoods. These human perturbations threaten biodiversity and future ecosystems functions of this forest and thus livelihoods. The full values of the ecosystem benefits have not been adequately quantified, and their role in socioeconomic development has not been examined.

Moreover, most natural ecosystems services are not traded in the market and therefore often true values of forest ecosystems are obscured. Consequently, the total economic values of forest ecosystems are incomplete and undervalued (Babulo et al., 2006; Kipkoech et al., 2011). Such undervaluation has resulted in marginalization of forest ecosystems in budget allocations, land-use change decisions, leading to excisions and degradation.

Despite its importance as a resource for local livelihoods, there is hardly quantitative information on direct use values and the role of the forest to the household and the wider economy. Studies have found that the relationship between socio-economic and external factors on forest resource dependence are contestable and can vary between locations, product types, or specific forest (Adhikari et al., 2004; Kamanga et al., 2009; Kalaba et al., 2013). However, there are few studies in Kenya which have analysed the role of socioeconomic and external factors on household dependence on forest resources. To address the information gaps articulated above economic, Economic valuation of forest ecosystems services was undertaken in East Mau forest.

Research Objectives
Broad Objective
To determine the total economic value of ecosystem services and its implications on conservation strategies in East Mau forest

Specific Objectives
1. To determine the magnitude of provisioning services from East Mau forest ecosystem to the local community and other stakeholders;

2. To determine the soil conservation functions, carbon sequestration, oxygen cycling, watershed functions, (indirect use values) and bequest, option (non-use values) values to local community and other stakeholders;

3. To determine the TEV distribution of benefits and costs of forest resources and implications to community livelihood needs and conservation;

4. To determine the level of forest dependence by forest adjacent households and examine the socioeconomic factors that influence dependence.

Research Questions
Objective 1
i. What are the quantities of forest products collected by households in study locations?

ii. What is the monetary value of forest products obtained by households across the study locations?

iii. What is the economic value of forest product trade among small scale forest product traders and saw millers

iv. What is the total revenue collected from products and services to Kenya Forest Service from East Mau?

Objective 2
i. What are the cultural and spiritual use values of East Mau forest ecosystem by the local community?

ii. What are the potential carbon sequestration and oxygen generation values of vegetation types of East Mau forest ecosystem?

iii. What are the monetary values of water flow and quality regulations functions (watershed) of East Mau forest Ecosystem?

iv. What are the monetary value of soil protection and nutrient cycling functions (soil functions) of East Mau forest Ecosystem?

v. What is the pharmaceutical potential value of East Mau biodiversity?

vi. What is the bequest value of East Mau forest ecosystem?

Objective 3
i. What is the total economic value of the forest ecosystem?

ii. How are the costs and benefits distributed among different stakeholders?

Objective 4
i. What are livelihood activities of households in the study locations?

ii. How much does forest income contribute to household’s income portfolios in the study locations?

iii. How does reliance on forest income vary with different levels of income and ethnicity?

iv. What socioeconomic characteristics affect the magnitude and relative importance of forest income?

Justification of the Study
East Mau Forest has undergone tremendous degradation and conversion to other land uses. One reason is the lack of appreciation of the varied values from the forest ecosystem. Most of the benefits have received little attention due to lack of knowledge or difficulty in monetary quantification. Primary amongst these benefits are the ecological services provided by the forests, including: the benefits to agricultural production, climate regulation; regulation of water flow; and soil protection, pollution control, biodiversity; aesthetic value; existence value, option and bequest value. To make optimal choices between the conservation and the continuation and expansion of human activities in forest ecosystems there is need to fully recognize the total economic values of the ecosystem goods and services so that they can be compared with the economic values of activities that may compromise them.

Significance of the Study
A proper understanding of the economic values and contributions of East Mau forest ecosystem to all stakeholders at all levels will provide clear signals to policy makers and resource managers to appreciate the importance of forest resources to household wellbeing and the wider society and therefore make optimal decisions regarding this important forest ecosystem. A comprehensive determination and appreciation of all forest values will provide justification for fair allocation of scarce public resources into its conservation. Furthermore, information on forest total economic values is important in identifying the costs and benefits of conservation and how the benefits accrued from forest conservation are appropriated by different stakeholders. Such information is critical for developing incentives for effective community participation and may contribute to shaping policies for mainstreaming forestry in local livelihoods and poverty alleviation (Campbell and Luckert, 2002; Mariara and Gachoki 2008) and may provide a key step towards sustainable use and management of this forest ecosystem.

Moreover, a clear understanding of the factors influencing household forest dependence can enable the resources managers to identify and focus conservation programs on the categories of local populations that are most dependent on forest resources (Gavin and Anderson, 2007). The information generated from this study may assist the government and other stakeholders in developing conservation strategies for optimizing forest resources to achieve economic and social objectives in tandem with national aspirations contained in Vision 2030.

Scope and Limitations of the Study
The study focus was on the East Mau forest blocks of Kiptunga, Mariashoni, Teret, Nessuit and Baraget. It was undertaken in four administrative locations of Mariashioni, Teret, Nessuit, Kapsimbeiywo and Silibwet, covering households in the location inside the forest (Mariashioni) and households within 5km from the forest reserve Teret, Nessuit, Kapsimbeiywo and Silibwet. The study also covered small scale, medium and large sized wood industries, small scale forest users, traders adjacent to East Mau forest and traders in major urban centres of Nakuru, Molo, Elburgon, Njoro, Keringet and Olenguorone. Data collection concentrated on the use of East Mau for extractive and non-extractive uses within the one year using cross-sectional design. The study focused on use (local) and non-use values (national and global) of East Mau forest, contribution of forest resources to local people and other stakeholders, household’s socioeconomic factors and contextual factors such as distance to the forest, ethnicity, and distance to markets and access to credit), costs and benefits of conservation.

The data collected for the study had some limitations. The data collected relied on recall of the respondents and because some forest use /products are continuously collected throughout the year, or harvested seasonally, it was a challenge for respondents to recall with ease. Another problem experienced during data collection was because some products were collected by local communities illegally and most likely the respondents might have concealed the actual quantities of products extracted.

The main objective of this thesis was to estimate the total economic value of East Mau forest ecosystem. It is however, important to note that the economic values derived from this study are not exhaustive. For example, the carbon sequestration value did not take into account the below ground biomass.

In addition, the estimates of non-use values only considered local bequest values and did not account for bequest values by the international community. Furthermore, the study did not take into account existence and recreation values for the local and international communities. The economic values derived from this study are largely conservative and need to be treated as indicative values in the complex arena of forest ecosystems valuation. However, the estimated values are based on the best available primary and secondary sources.

Definition of Terms
The following terms are defined in the context of this study.

Forest adjacent households - These are households bordering the forest reserve and are located within 5km from the forest boundary (Wass, 1995).

Household head - Household head refers to the member of a household who is the primary sole decision maker of the household (KNBS, 2010).

Livelihood - A livelihood refers to income-generating activities determined by natural, social, human, financial and physical assets and their access such as farming, livestock keeping and business (Ellis, 2000).

Forest income - Monetary value of all products obtained from forest activities for home consumption and sale (Wollenberg, 2000).

Forest dependence - This is a level of forest reliance for subsistence and cash income (Wollenberg, 2000).

Direct use - This is use of forest ecosystem through extractive use or enjoyment of services from the forest (Pearce et al., 2002), for example the collection of firewood for home consumption and sale.

Indirect use - This is the positive influence of the forest on productive sectors which have a direct bearing on human welfare; such as improving quality and quantity of water for domestic use and for industry, soil protection, flood control, climate amelioration and carbon sequestration (Pearce et al., 2002).

Ecosystem services - This is defined as the benefits people obtain from ecosystems (Pearce et al. 2002; MEA, 2005), for instance, provisioning services including timber, firewood etc.

Economic value - This is the expression of value of forest products or services in monetary terms (Pearce et al., 2002).

Consumer surplus-An economic measure of consumer satisfaction, which is calculated by analyzing the difference between what consumers are willing to pay for a good or service relative to its market price. A consumer surplus occurs when the consumer is willing to pay more for a given product than the current market price. (

Total Economic Value - This is the sum total of all economic values and includes direct use, indirect use (use) and non-use values (Pearce et al., 2002).

Non use value is the value that people assign to economic goods (including public goods) even if they never have and never will use it. Non-use value as a category may include: option value, bequest value and existence value (Pearce et al., 2002).

Option value –The value placed on individual willingness to pay for maintaining an asset or resource even if there is little or no likelihood of the individual actually ever using it (Pearce et al., 2002).

Bequest value- This is the value placed on individual willingness to pay for maintaining or preserving an asset or resource that has no use now, so that it is available for future generations (Pearce et al., 2002).

Existence value- This the value people derive from knowing that a unique environment or species exists (Pearce et al., 2002).

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