JUSTIN

Typewritten Text

IMPACTS OF BWINDI IMPENETRABLE NATIONAL PARK ON LOCAL PEOPLES’

LIVELIHOODS

KENNETH BALIKOOWA

May 2008

Department of international Environment and Development Studies (Noragric)

Norwegian University of Life Sciences (UMB)

A thesis submitted in partial fulfillment of the requirements for the award of a degree of Masters

of Science in Natural Resource Management and Sustainable Agriculture

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The Department of International Environment and Development Studies, Noragric, is the

international gateway for the Norwegian University of Life Sciences (UMB). Eight departments,

associated research institutions and the Norwegian College of Veterinary Medicine in Oslo.

Established in 1986, Noragric’s contribution to international development lies in the interface

between research, education (Bachelor, Master and PhD programs) and assignments.

The Noragric Master theses are the final theses submitted by students in order to fulfill the

requirements under the Noragric Master program “Management of Natural Resources and

Sustainable Agriculture” (MNRSA), “Development Studies” and other Master programs.

The findings in this thesis do not necessarily reflect the views of Noragric. Extracts from this

publication may only be reproduced after prior consultation with the author and on condition that

the source is indicated. For rights of reproduction or translation contact Noragric.

© Kenneth Balikoowa, May 2008 balikeny@yahoo.com Noragric Department of International Environment and Development Studies P.O. Box 5003 N-1432 Ås Norway Tel.: +47 64 96 52 00 Fax: +47 64 96 52 01 Internet: http://www.umb.no/noragric

DECLARATION

I, Kenneth Balikoowa, declare that this thesis is a result of my research investigations and

findings. Sources of information other than my own have been acknowledged and a reference

list has been appended. This work has not been previously submitted to any other university for

award of any type of academic degree.

Signature……………………………….........

Date…………………………………………

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DEDICATION

This thesis is dedicated to my girlfriend Irene; I love you so much and always will.

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ACKNOWLEDGEMENT

I am very grateful to my supervisor Assoc Professor Espen Sjastaad for the guidance in preparing

the proposal and the final report. Also Professor Paul Vedeld was very much involved in the

inception of this research and Doctor Buyinza Mukadasi whose help while in the field is

invaluable.

I am grateful to NORAD for having sponsored my master’s degree studies, and all staff at

Noragric for being such good teachers. Doctor Goretti Nabanoga of Faculty of Forestry, you were

very helpful. Ingeborg and Liv at Noragric library, you have been so helpful and always willing

to help with literature search.

I also thank in a special way Herbert Ainembabazi for the unconditional help during data

analysis. I am indebted to all my classmates and friends at UMB, Patrick, David, Justin, Gloria,

Linn Marie, Sandy, Henry, Bjonnar Rebekka and Christina you all deserve the best in life. To all

of you I say thank you and may God bless you.

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ABSTRACT

There is debate on whether protected areas like national parks can help in poverty alleviation or are instead poverty traps. In this study, the impact of Bwindi impenetrable national park in south-western Uganda on local incomes and livelihoods is assessed. The study also seeks local perceptions on collaborative natural resource management scheme. Data was collected from a stratified random sample. Stratification was based on proximity to the park boundary with strata at 0-2 km, 3-6 km and above 6 km from the park boundary. Another stratum also 0-2 km from the park boundary but with some access to park resources was created. The four strata were compared with respect to total household income, asset endowment, income diversification and income distribution. Results showed that households nearest to the park earned higher income but no differences in land and livestock ownership. Proximity to the park negatively affected access to social services. Dependence on park income was not influenced not by proximity but by membership to a resource user group. Dependence on park income had a negative effect on total household income and due to the small allowable quotas of park resources, park income had a small income equalising effect. Local people expressed concern over damage of crops done by park animals and inability of park management to either curb the problem or offer compensation for the damage. However, there is satisfaction with the management approach but less appreciation of the manner in which tourist revenue sharing money was being handled. As a result it is concluded that BINP has enormous potential to benefit local people but real local benefits remain a distant reality yet the costs associated with the existence of the park are having a heavy toll on local people.

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TABLE OF CONTENTS

DECLARATION -------------------------------------------------------------------------------------------- i

DEDICATION ---------------------------------------------------------------------------------------------- ii

ACKNOWLEDGEMENT ------------------------------------------------------------------------------- iii

ABSTRACT -------------------------------------------------------------------------------------------------- iv

TABLE OF CONTENTS ---------------------------------------------------------------------------------- v

LIST OF TABLES ----------------------------------------------------------------------------------------- vii

LIST OF FIGURES -------------------------------------------------------------------------------------- viii

ACRONYMS AND ABBREVIATIONS --------------------------------------------------------------- ix

CHAPTER I: INTRODUCTION ------------------------------------------------------------------------ 1 1.1 Background -------------------------------------------------------------------------------------------- 1

1.2 Problem statement ------------------------------------------------------------------------------------ 3

1.3 Goals, objectives and hypotheses ------------------------------------------------------------------- 4

CHAPTER II: ANALYTICAL FRAMEWORK AND LITERATURE REVIEW ------------ 6

2.1 Analytical framework -------------------------------------------------------------------------------- 6 2.1.1 Key terms and concepts ------------------------------------------------------------------------- 6 2.1.2 Household economic model -------------------------------------------------------------------- 6

2.2 Rural livelihoods -------------------------------------------------------------------------------------- 9 2.2.1 Characteristics of rural households ------------------------------------------------------------ 9 2.2.2 Rural income diversification ------------------------------------------------------------------- 9 2.2.3 Rural household dependence on natural resources ----------------------------------------- 10 2.2.4 Rural household income distribution -------------------------------------------------------- 10 2.2.5 Community based natural resource management------------------------------------------- 10 2.2.6 A case for community involvement in conservation --------------------------------------- 12 2.2.7 A case against community involvement in conservation ---------------------------------- 13

CHAPTER III: STUDY AREA AND METHODOLOGY ---------------------------------------- 15

3.1 Study area --------------------------------------------------------------------------------------------- 15 3.1.1 Location, physical and demographic characteristics --------------------------------------- 15 3.1.2 Management of Bwindi forest prior to becoming a national park ------------------------ 16 3.1.3 Management of Bwindi forest as a national park ------------------------------------------- 17

3.2 Methodology ------------------------------------------------------------------------------------------ 19 3.2.1 Site selection ------------------------------------------------------------------------------------ 19 3.2.2 Data collection ---------------------------------------------------------------------------------- 19 3.2.3 Data handling, estimation and analysis ------------------------------------------------------ 20

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3.3 Proxies for internal household factors ------------------------------------------------------------ 22 3.3.1 Human capital ----------------------------------------------------------------------------------- 22 3.3.2 Physical capital --------------------------------------------------------------------------------- 23

CHAPTER IV: RESULTS AND DISCUSSION ----------------------------------------------------- 25

4.1 Basic household characteristics ------------------------------------------------------------------- 25

4.2 Access to infrastructure and social services ----------------------------------------------------- 29

4.3 Household income and income dependence ------------------------------------------------------ 32 4.3.1 Household income sources -------------------------------------------------------------------- 32 4.3.2 Household dependence ------------------------------------------------------------------------ 34

4.4 Determinants of total household income --------------------------------------------------------- 37

4.5 Effect of proximity to the park on total household incomes ------------------------------------ 40

4.6 Household total income diversification ----------------------------------------------------------- 40

4.7 Distribution of income ------------------------------------------------------------------------------ 43 4.7.1 Income inequality ------------------------------------------------------------------------------- 43 4.7.2 Effect of park income on income inequality ------------------------------------------------ 43

4.8 Performance under the collaborative management scheme------------------------------------ 45 4.8.1 People-park relations --------------------------------------------------------------------------- 45 4.8.2 Perceived benefits of staying close to the park --------------------------------------------- 45 4.8.3 Local people participation in management of BINP --------------------------------------- 46 4.8.4 The tourist revenue sharing scheme ---------------------------------------------------------- 47 4.8.5 Resource use in BINP -------------------------------------------------------------------------- 48 4.8.6 Local opinions on how the park can benefit local people --------------------------------- 48

CHAPTER V: CONCLUSIONS ------------------------------------------------------------------------ 50

REFERENCES --------------------------------------------------------------------------------------------- 52

APPENDICES ---------------------------------------------------------------------------------------------- 60

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LIST OF TABLES Table 1: Adult equivalent scales ................................................................................................... 23 

Table 2: Livestock conversion factors ........................................................................................... 23 

Table 3: Socio-economic and demographic characteristics of the four strata and whole sample .. 26 

Table 4: Main occupations of household heads ............................................................................ 28 

Table 5: Household income (UGX) .............................................................................................. 33 

Table 6: Contribution of livelihood activities to household income .............................................. 35 

Table 7: Household subsistence and cash income ........................................................................ 36 

Table 8: Ordinary linear regression of log total household income against household

characteristics ......................................................................................................................... 38 

Table 9: Weighted least squares regression of total income diversity and household socio

economic fators ...................................................................................................................... 41 

Table 10: Comparison of income inequality in the four strata ....................................................... 43 

Table 11: Comparing Gini coefficient for Karangara with and without park income ................... 44 

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LIST OF FIGURES Figure 1 Modified household economic model (Based on Tumusiime (2006)) ---------------------- 8 

Figure 2 Map of Uganda showing location of Bwindi Impenetrable National Park ---------------- 16 

Figure 3: Selected endowments by stratum -------------------------------------------------------------- 31 

Figure 4: Selected asset endowments showing aggregated strata ------------------------------------- 32 

Figure 5: Relationship between dependence on off-farm income and total household income --- 40 

Figure 6: Relationship between total household income and income diversification -------------- 42 

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ACRONYMS AND ABBREVIATIONS

AEU Adult Equivalent Units BCHC Buhoma Community Health Centre BINP Bwindi Impenetrable National Park CEU Cattle Equivalent Units CPAC Community-Protected Areas Committees CPI Community Protected Area Institutions DANIDA Danish International Development Agency DTC Development Through Conservation GEF Global Environment Facility HuGo Human-Gorilla Conflict Resolution ICDP Integrated Community Development Projects ITFC Institute Of Tropical Forest Conservation LIRDP Luangwa Integrated Resource Development Project MBIFCT Mgahinga and Bwindi Impenetrable Forest Conservation Trust MoU Memorandum of Understanding MUZ Multiple Use-Zones NEMA National Environmental Management Authority PEC Production and Environment Committees PMI Poverty Measurement Index RUG Resource User Agreements UWA Uganda Wildlife Authority WHS World Heritage Site

CHAPTER I: INTRODUCTION

1.1 Background

The increase in the extent of protected area coverage highlights the attention that biodiversity

conservation has received in the past few decades. But conserving biodiversity by setting aside

large tracts of land for strict protection necessitates that other land use options are sidelined

(Johannesen 2007), which affects land based livelihoods. Over the years, global conservation

strategies have shifted in nature (Tumusiime 2006), mainly to respond to pressures that natural

resources face in an ever dynamic world. Earlier, challenges such as declining biodiversity

populations and habitat transformation (Adams, William M. et al. 2004), attracted attention and

support to the creation of protected areas that separated humans from nature (Adams, W. M.

2004). It appears however to have been only a quick fix to the problem. While protected areas

have proved to be largely effective in stemming species extinction (Hutton et al. 2005), evidence

suggests that they may be negatively affecting human survival (de Sherbinin 2008).

Rural people in developing countries depend heavily on natural resources and derive a significant

portion of their income and livelihoods from them (e.g Cavendish 2000; Escobal & Aldana 2003;

Ghate 2002; Mamo et al. 2007; Vedeld, Pal et al. 2004). This has increased global attention

towards biodiversity management in the last decades (Ferraro 2001). Some believe the “fortress

approach” to managing natural resources is no longer tenable, due to its disadvantages especially

in relation to human cost (Brockington & Schmidt-Soltau 2004) but also the difficulty in

enforcing established protected areas in face of growing local opposition (Hutton et al. 2005;

Wells, P. M. & McShane 2004). A new “community conservation” paradigm (Hulme &

Murphree 2001) later emerged that emphasized conserving biodiversity hand in hand with

satisfaction of human needs (e.g. Adams, M. William & Hulme 2001; Adams, William M. &

Infield 2003; Hutton et al. 2005).

The costs and benefits of conservation accrue unequally at local, national and international levels

(Balmford & Whitten 2003; Wells, M. 1992). Unfortunately, the marginalized and impoverished

local people foot the bigger part of the conservation bill (see Ferraro 2001; IUCN 2005; Roe &

Elliott 2004; Wells, M. 1992) and receive the least of the benefits (Adams, William M. & Infield

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2003). Yet local people are indispensable for the long term integrity of protected areas (Wells, P.

M. & McShane 2004). It is now commonplace that management of protected areas be consistent

with overall socio economic goals of society (Adams, William M. et al. 2004).

The negative effects of protected areas on people’s livelihoods undermine local support

(e.g.Adams, William M. et al. 2004; Kiss 1990; Wells, P. M. & McShane 2004). Most notable of

these negative effects arise from crop raiding and foregone access to resources (Adams,

M.William & Hutton 2007; Archabald & Naughton-Treves 2002; Cernea, M Michael 2006).

Incompatibility of the development aspirations of local populations and the preservationist

objectives of park authorities is usually a breeding ground for animosity and serves to increase

the challenge of conservation. According to Scherl, Wilson et al. (2004 :2), “ to survive,

protected areas in the poorer nations must be seen as a land-use option that contributes as

positively to sustainable development as other types of land use”.

To counteract the negative effects of protected areas, a number of approaches have been

formulated to reduce tensions between local communities and protected areas management.

Allowing for access to the park has to be incorporated into park management plans to cater for

the interests of local communities. Legal extraction of park resources, revenue sharing (for

instance of tourist gate fees) and community representation on park management advisory

committees were observed for instance in Uganda (Adams, William M. & Infield 2003), to

enable benefits of managing protected areas to be realized by both government agencies and local

communities (Mugisha 2002).

While reduction of poverty is a secondary goal of protected areas with respect to conservation of

biological diversity and provision of ecosystem services (Scherl et al. 2004), examination of the

linkages between protected areas and issues of poverty is not only a practical issue but an ethical

necessity. The participants in the Workshop Stream on Building Broader Support for Protected

Areas stated that “protected areas should not exist as islands, divorced from the social, cultural

and economic context in which they are located” (Recommendation V.29, Vth IUCN World Parks

Congress) (IUCN 2005). This has further emphasized the need for an increased role for local

people in management of national parks (Inamdar et al. 1999; Namara 2006).

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1.2 Problem statement

National parks like Bwindi Impenetrable National Park (BINP) can provide various goods and

services to local communities around it, and therefore contribute to improvement of livelihoods;

this is true for all protected areas (Blom 2001; Kibirige 2003; Scherl et al. 2004). Parks do not

only provide food, medicine, fodder, building poles etc to local communities but also parks offer

job opportunities, educative programs, and other community services (Blom 2000; Kibirige

2003). A gorilla park like BINP can have enormous money streams due to the appeal gorillas

have on tourists (Adams, William M. & Infield 2003). While there is a general change in

conservation doctrine to involve communities more as a means of soliciting their cooperation and

support (Wells, P. M. & McShane 2004), local communities are allocated large responsibilities

under the resource-use programs (Namara 2006) yet reciprocal benefits remain minimal (Wilkie

et al. 2006).

As a source of fuelwood, medicinal herbs, forest foods, fish, building poles and other subsistence

products (Archabald & Naughton-Treves 2002), BINP had always been important in the

livelihoods of the local communities, till its elevation to park status which henceforth

disenfranchised local people by making access illegal.

Without doubt, the change in the status of the park greatly changed the way local people relate

with the park and the resources therein. Whether or not the change has been to the advantage of

local people is uncertain. This study seeks to find some answers by investigation the effect that

park proximity has on people’s livelihoods. In addition, revenue sharing and direct funding has

been implemented in BINP (Archabald & Naughton-Treves 2002; Kazoora 2002), to increase

benefit flow from the park. The park is also expected to have multiplier effects that will

positively affect people’s incomes and therefore livelihoods. It is important to make an

assessment if BINP actually contributes to the livelihoods of the local people surrounding it.

Involvement and support of local people is paramount in natural resource management (Ferraro

2001). Variants of collaborative management are being used in Uganda to boost local

involvement in park management (Mutebi 2003; Namara 2006). As with any other change, there

are winners and losers. Community-based natural resource management is intended to cater for

both the needs of the national government or its conservation agency and the local people. The

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benefits to the government include lower administrative costs by reduction in work force used in

conservation. The effect of adopting community-based natural resource management on local

people needs to be investigated by assessing their level of involvement, their attitude towards

park management and their perceived effect of the park on their livelihoods compared to the pre

community-based management era.

1.3 Goals, objectives and hypotheses The study seeks to examine park-poverty relations in terms of how livelihoods around BINP are

affected by the park and if the management approach has improved local people’s attitudes

towards the park.

Objective 1: To assess the implications of park proximity on local livelihoods in terms of

natural resource dependence, livelihood diversification and income distribution

Hypotheses

1. Households nearer the park have higher total incomes.

The park is expected to offer job opportunities to local people for instance as tourist guides

and market for local goods and curios. These are expected to positively affect local

household income.

2. Households nearer the park have greater asset endowments.

People use household income to accumulate assets. With expected high incomes, it is

assumed that households will have more assets like more land, livestock, or more educated

household members.

3. Households nearer the park depend more on park income.

Common-pool resources like forests provide cheap alternatives to private assets. People close

to forest resources are expected to make use of these resources for household consumption

and income generation. In many cases the only cost to forest resource extraction is time; both

to and from the park. Being close to the park lowers the amount of time spent on resource

extraction and this should serve as an incentive to extract more park resources.

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4. Households nearer the park have more diversified incomes.

Tourism is expected to attract a lot of other business opportunities like sale of agricultural

products, sale of curios and cultural exhibitions. In addition many local people will be

expected to take up park jobs. This should result in more diversified income for the

participating households in comparison with distant households which may not be able to tap

into the additional income possibilities.

5. Total income increases with park income.

Environmental income has been found to make significant contribution to total household

income by some studies on rural livelihoods. As a supplement to other income activities, park

income is expected to increase total household income for households participating in

resource extraction.

6. The park contributes to income equality.

Income inequality exists due to differences among households with respect to access to

private assets. Common-pool resources like park resources provide cheap alternatives to asset

poor households and hence have a potential to reduce income inequality.

Objective 2: To investigate the local people’s attitudes and perceptions on the current

management approach of BINP.

The research questions are:

1. Has the current management approach reduced animosity between local people and park

management?

2. Do local people realize and appreciate benefits from the park?

3. Is money from tourist revenue sharing scheme used to benefit people affected by the

park?

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CHAPTER II: ANALYTICAL FRAMEWORK AND LITERATURE REVIEW

2.1 Analytical framework

2.1.1 Key terms and concepts

The definition of livelihoods follows that by Ellis (2000 : 10) “…the assets (natural, physical,

human, financial, and social capital), the activities, and the access to these (mediated by

institutional and social relations) that together determine the living gained by the individual or

household”.

Poverty is usually taken to describe a situation of failure to meet the “one dollar a day” yardstick.

However, there is more to it than the simplicity that the yardstick represents. It can include

deprivation of capabilities (Sen 1999). I adopt the definition of poverty as “ a pronounced

deprivation of well-being related to lack of material income or consumption, low levels of

education and health, vulnerability and exposure to risk, lack of opportunity to be heard and

powerlessness”(WorldBank 2001 pg 15). Poverty alleviation is looked at as the reduction in

deprivation of well-being.

2.1.2 Household economic model

The household economic model (Figure 1) gives insights into the conditions under which

households make choices about which economic activities to pursue. The model summarizes the

assets available to the household, the options to which the assets can be put to use in order to

generate income and the fate of the income generated from adopted livelihood activities. A

household is herein taken to be a group of individuals making joint decisions, staying in the same

residence and usually sharing meals (Ellis, Frank 1998). A household is used as the unit of

analysis because individual household choices have implications on the welfare of the whole

society due to interconnections that exist in communities; moreover household members pool

resources and make joint decisions and also share incomes (Tumusiime 2006).

Factors both internal and external to the household influence choice of activities to pursue

(Barrett, C. B. et al. 2001). External factors are those to which the household has little control and

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include policies, natural vagaries and availability of social services, while internal factors are the

various types of assets owned by the household. These assets can be broadly categorized as

capitals; social, human, natural, financial and physical capital (Scoones 1998). The assets and the

various uses to which they are put to use to produce outputs constitute the livelihood (Ellis, Frank

2000).

Both external and internal factors affect the household but also work in synergy to each other to

create an even bigger influence on the household. The quality and quantity of assets owned

enables a household to pursue livelihood activities not possible to another household with

different asset endowment. For instance, a household rich in human capital i.e. with more

educated household members is better placed to tap into employment opportunities than a less

educated household and a household with more land is better placed to engage in extensive

agriculture than a land deficient household. Household assets are important because they are

useful inputs into production but can also be finished products in themselves. Family labor

represents human capital as an input, but when a household member offers labor to other

households, human capital is then a finished product. The choice on how to use family labor will

reflect the opportunity cost of either alternative.

External factors affect internal factors and subsequently livelihood activities, i.e. the types and

blend of assets a household owns and/or has access to, is determined in part by external factors.

The status of a forest as either a forest reserve or a national park can influence what type of

natural resources local households can access; where status dictates the level of restriction

imposed on the type of resources local people can get from the forest. In addition, incidents of

crop raiding may affect what types of crops local people can grow on their land. Yet some parks

can be important sources of financial capital and off-farm income activities. Therefore the effect

can be either to enhance or constrain a livelihood. Of particular importance in a rural context will

be how access to resources is constrained by external factors. Access to resources is fundamental

as a pathway out of poverty.

Households earn income when assets are allocated to activities (Barrett, C. B. et al. 2001) and the

different activities generate different incomes to the household. In order for the household to

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maximize income, a good mix of assets and an enabling external environment are important to

choose the most profitable livelihood activities. This is because access to assets has to be coupled

with the ability to put resources to productive use and also possibility of meaningful asset

accumulation in a direction that ultimately leads to more productive assets (Ellis, Frank &

Bahiigwa 2003; Ellis, Frank & Freeman 2004).

Therefore in using the household economic model, I investigate the effect park proximity has on

the assets owned by a household and the various ways in which the assets are put to use.

EXTERNAL FACTORS

Insecurity Policies Social services

Natural vagaries

Market access

Park proximity

ASSETS (CAPITAL)

Figure 1 Modified household economic model (Based on Tumusiime (2006))

Physical Human Natural Financial Social

Household

LIVELIHOOD ACTIVITIES Crop and animal husbandry, off-farm employment, collection of forest products

Consumption Investment

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2.2 Rural livelihoods

2.2.1 Characteristics of rural households

Rural people typically have low education and possess little of economically significant assets.

They struggle with little land and livestock. Financial capital is also low (Ellis, Frank &

Bahiigwa 2003; Ellis, Frank & Ntengua 2003). Further, they are located far from basic

infrastructure and find themselves in situations where markets are more less unfunctional

(Holland et al. 2003). Labor intensive and subsistence production is symptomatic of their

predicament. Social capital in terms of social interconnections (Wu & Pretty 2004), enabling the

ability to undertake collective action, and natural capital i.e. the bulk of all common pool land

resources (Narain et al. 2005), form the backbone of their livelihoods (Pretty & Smith 2004;

Vedeld, Paul et al. 2007).

2.2.2 Rural income diversification

An important feature of rural livelihoods is livelihood diversification defined as “the process by

which rural families construct a diverse portfolio of activities and social support capabilities in

their struggle for survival and in order to improve their standards of living” (Ellis, Frank 1998).

The reasons for livelihood diversification range from push factors like high transaction costs and

failures in credit markets (Reardon 1997) to coping strategy and safety net in case of adverse

shocks (Blaikie 1994; Davies 1996). But households can also voluntarily take up diversification

(Ellis, Frank 1998; Stark 1991) as a means of increasing current consumption and for the richer

households, diversification offers an opportunity for accumulation (Hart 1994). Barrett et al

(2001) also argue that diversification of livelihoods may due to complementarity of livelihood

activities, for instance livestock offering manure for crops and crop residues acting as fodder for

livestock.

It is important to highlight that the choice to diversify livelihoods presents a major disconnect

from common economic reasoning since it negates the advantages otherwise realized with

specialization, the least of which being increased incomes (Vedeld, Pal et al. 2004). Whether

rural people diversify livelihoods as a survival mechanism against failure in one activity,

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implying a sense of desperation or as a means to increase current consumption, implying

proactive choice is subject to discussion (Ellis, Frank 1998; Vedeld, Paul et al. 2007).

2.2.3 Rural household dependence on natural resources

Several studies have illustrated that poor rural people depend on common-pool natural resources

for their livelihoods (e.g see Mamo et al. 2007; Narain et al. 2005; Reddy & Chakravarty 1999;

Tumusiime 2006; Upton et al. 2007). Common-pool resources like national park are a source of

food, fodder, medicines for local use (Mugisha 2002) but local people also need these common-

pool resources as a means of off-farm employment (Cernea, M. Micheal & Schmidt-Soltau 2006)

and as gap fillers during times of financial hardship or famine (Scherl et al. 2004). Studies have

shown that generally dependence on natural resources declines with income (Fisher 2004; Narain

et al. 2005). Poorer households depend more on natural resources although their extraction is

usually lower than that for wealthier households (cf Vedeld, Paul et al. 2007).

2.2.4 Rural household income distribution

Rural households can exhibit differences in incomes due to differences in asset endowments and

livelihood activities pursued. Environmental incomes from forest resources can reduce income

inequalities in rural communities by offering a source of income for asset-poor families

(Cavendish 2000; Fisher 2004; Tumusiime 2006).

2.2.5 Community based natural resource management

A lot of debate has recently emerged on the subject of biodiversity conservation and how to

reconcile the costs of conservation with the needs and aspirations of rural people dwelling near

biodiversity rich ecosystems (e.g Scherl et al. 2004). Early conservation efforts supported the

separation of humans from natural resources under a strict protectionist strategy code named

“fortress conservation” or the fines and fences approach (Adams, M. William & Hulme 2001;

Namara 2006; Wells, M. 1992). Criticisms later emerged about the disregard for human rights

and wellbeing in pursuit of more protection for nature as it became clearer that protectionist

approaches deprived rural people of resources they so much depended on for their livelihoods.

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The highlight of the people-parks debate has been the birth of two opposing schools of thought;

for and against the establishment of protected areas to conserve nature, with each enjoying

hegemony at different times in the recent past. Establishment of protected areas was a popular

strategy in nineteenth century and was based on the American notion of parks as pristine areas of

biodiversity (Adams, M. William & Hulme 2001). This was quickly adopted especially in sub-

Saharan Africa with the creation of so many parks.

Studies on rural livelihoods have shown that rural people depend on natural resources (Fisher

2004; Narain et al. 2005; Upton et al. 2007; Vedeld, Pal et al. 2004). Establishment of national

parks with strict protection may therefore deprive local people of livelihood options and impose

significant local costs (Ferraro 2001). Deprivation will usually result into conflict and animosity

between local people and protected area managers (Hayes 2006) and local people will usually

take up illegal activities like arson, poaching and poisoning wildlife to show resentment to the

park (Mutebi 2003).

Parks do not only limit access to resources but also can limit the range of livelihood options

available to the local people. Cases of crop raiding are reported almost wherever a park exists

(e.g Gillingham & Lee 2003; Lepp 2007; Plumptre et al. 2004). Communities affected by wildlife

raiding may have to forfeit growing some crops or livestock or otherwise take up labor intensive

means of reducing crop and livestock damage.

Generally, it’s well known that local people bear the biggest part of conservation costs (Balmford

& Whitten 2003). This is especially in cases where large tracts of land are set aside for protection

of nature. The costs may be attributed to loss of access to resources (Cernea, M. Micheal &

Schmidt-Soltau 2006; West & Brockington 2006) displacement and dispossession of people

(Cernea, M Michael 2006; Maisel et al. 2007), creation of criminal spaces (West & Brockington

2006) and rising prices where tourism activities occur (Lepp 2007). Successive World Parks

Conferences have acknowledged this fact and since the Bali conference in 1982, there have been

increasing calls to reconcile conservation with human needs (McNeely and Miller (1984) in

Scherl et al. 2004).

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The preceding presentation shows that parks and local people are in direct conflict with each

other. This is not universal truth. There are several cases where local people have embraced parks

and reported significant benefits. Under such cases, conservation agencies have maintained some

degree of access to resources from the park by local people and/or instituted other transfer

mechanisms to ensure that local costs are transferred to national and international levels

(Balmford & Whitten 2003). These approaches range from revenue sharing like in Uganda

(Archabald & Naughton-Treves 2002) and implementation of other types of integrated

community development projects (ICPD) (Barrett & Arcese 1995; Brandon & Wells 1992;

Johannesen & Skonhoft 2005). Implementation of ICDPs may include infrastructural

developments like local schools and health centers (Lepp 2007; Makombo 2003). Such

infrastructural developments improve local attitudes towards the park. More telling success

stories can be found in southern Africa like the Luangwa Integrated Resource Development

Project (LIRDP) in Zambia (Child & Dalal-Clayton 2004). Several debates arise about the

effectiveness of any conservation strategy with some researchers stating that parks are the most

effective way to conserve biodiversity (Bruner et al. 2001).

2.2.6 A case for community involvement in conservation

The main argument is that community based resource management is characterized by

empowerment and control of forest resources by the community, which in turn leads to efficient,

effective, equitable and sustainable forest management (Namara & Nsabagasani 2003).

One of the strengths of community conservation is its ability to instill cultural pride and identity

(Roe et al. 2000) of the communities surrounding the park. The communities apply and

rediscover indigenous knowledge of controlling, monitoring and managing the parks. They feel

responsible for the management of the protected as they get involved in management decision

making. This however in some schools of thoughts is seen as the weakness of the discourse

because in most cases traditional methods fail to define issues beyond the wildlife and its habitat.

The socio-economic value of the resource is rarely known due to technical incapabilities. Kiss

(1990) observed that ‘….wildlife management and utilization (beyond informal hunting) may

require various types of knowledge, skills and capabilities which the people do not have, and

12

investment which they cannot make….They also may not be aware of the real value of wildlife ..

particularly the recreational values…’

The fortress approach creates conflict and animosity between local populations and protected

area managers, with activities such as local communities setting sections of protected areas

ablaze or poisoning wildlife in protest (Mutebi 2003). Community based conservation on the

other hand meant to reduce animosity between communities and protected area authorities and

extend benefits to local communities as incentives for them to assume responsibilities to support

conservation (Namara & Nsabagasani 2003).

In addition, most governments have neither the financial, human or institutional capacity to affect

protectionist approaches to natural resource management. Conservation agencies manpower

resources are already over stretched and cannot cope with the task of managing all protected

areas (Wells, P. M. & McShane 2004). This is exacerbated by the poor enumeration of staff and

corruption. The use of the local communities who live nearest the protected area resources and on

which their livelihoods is based can be enlisted and could be a better alternative.

There are other benefits from the parks under community management. Community members get

paid employment for scouting or general management work especially when some special

projects are done in the area. For instance the people around Bwindi national park in Uganda and

also direct benefits the community gets from gate collection fees. Roe, Mayers et al. (2000)

reported that the Sankuno protected area of Botswana employs about 16% of the local people

under a joint venture agreement with other stakeholders on tourism.

2.2.7 A case against community involvement in conservation

Critics have raised concerns about the over simplification of community participation in natural

resource management as a sustainable mechanism (Ribot 2002). The main arguments arising

from this discourse include: concern that without adequate and appropriate institutional forms

and powers, community participation may not deliver expected benefits such as efficiency,

equity, improved service provision and development (Ribot 2002) secondly, due to the

13

differentiated nature of the communities, community involvement may benefit certain elite, social

classes and ethnic groups while other resource users are marginalized thus ruling out equitable

benefits, as communities are more dynamic and highly differentiated than assumed (Leach 1999

cited in (Namara & Nsabagasani 2003). As noted by Mutebi (2003) there is a danger of capture

by influential or elite groups who can further disenfranchise the weak and poor. According to

Barrow and Murphree’s (2001) the strength of a collaborative management agreement is subject

to the level of benefits derived from resource use and the contribution to local livelihoods that

such resources make. Since community members do not equally benefit, the community will be

stratified in terms of motivation and enthusiasm to fulfill their obligation and may also result into

intercommunity tensions (Namara 2006).

14

CHAPTER III: STUDY AREA AND METHODOLOGY

3.1 Study area

3.1.1 Location, physical and demographic characteristics

Bwindi impenetrable national park is located in southwestern Uganda between latitude 0031`-

108`S and longitude 39035`-29050`E (Mwima & McNeilage 2003), and about 540 km from the

capital city; Kampala. It covers the districts of Kisoro, Kanungu and Kabale. It is among the

largest of Afromontane forests covering a total area of 330.8 km2 (Babaasa et al. 2004). The

topography is extremely rugged with narrow steep sided valleys running in various direction with

hills of between 1400 and 2500 meters above sea level (Harcourt 1981). Mean annual

temperature is 130 C and annual mean rainfall of 1440 mm, ranging between 1130 and 2390 mm

(Kamugisha et al. 1997) the wettest months are March- April and August- November.

BINP is an enclave for at least twelve species known to be threatened with global extinction and

is home to half the world population of the critically endangered mountain gorilla (Gorilla gorilla

beringei) (Archabald & Naughton-Treves 2002; Hamilton et al. 2000; Namara 2006). The area is

extremely rich in biodiversity with 120 species of mammals documented including the red-tailed

or white-nosed monkey Cercopithecus ascanius, blue monkey Cercopithecus mitis, L'Hoest's

monkey (Cercopithecus L 'Hoestii), black and white colobus (Colobus guereza), , chimpanzees

(Pan troglodytes) olive baboons (Papio cynocephalus anubis) and mountain gorilla (Gorilla

beringei beringei) (Harcourt 1981; Kamugisha et al. 1997).

The park is surrounded by some of the most densely populated areas in Uganda, district average

population densities of Kisoro, Kanungu and Kabale are 324, 163, 281 respectively all of which

are well above the national average of 122.8/km2 (Uganda Bureau of Statistics 2002b). The dense

population implies increased pressure on resources both inside and outside the park.

The areas around the park have a multi ethnic composition but the Bakiga, Bafumbira are the

biggest tribes (Korbee 2007). The area is also home to the Batwa one of the poorest, heavily

forest dependent people who live in small communities previously inside the forest and detached

from the general populace. The Batwa pygmies are indigenous to the area.

15

Low input subsistence agriculture is the main economic activity among the local people (Korbee

2007). Crops grown include bananas, sorghum, millet sweet potatoes and beans. Tea is also

grown as the major cash crop for sale at Kayonza tea factory. Tourism is the most vibrant

economic activity and BINP is one of the leading tourist areas in Uganda largely due to the

mountain gorillas in the forest.

Figure 2 Map of Uganda showing location of Bwindi Impenetrable National Park

3.1.2 Management of Bwindi forest prior to becoming a national park

The area occupied by BINP was first gazetted as two separate forests in 1932 by the colonial

government due to its economic and ecological importance. In 1942, the two forests were

combined and gazetted as impenetrable central crown forest. In 1961, it was declared a game

sanctuary with the aim of protecting the Bwindi population of the mountain gorillas (Gorilla

16

gorilla beringei) (Makombo 2003). Hence, management of the forest reserve was vested with the

colonial government and communities had to seek permission to access forest resources in the

reserve (Mutebi 2003).

From 1964 to 1991 Bwindi impenetrable forest was managed as both a forest reserve under the

forest department and a game sanctuary under the game department (Mutebi 2003).

3.1.3 Management of Bwindi forest as a national park

The impenetrable forest came under national park status by the resolution of the National

Resistance Council (Parliament) in 1991, to be known as Bwindi impenetrable national park

BINP. The park was declared a world heritage site (WHS) in 1994 (Namara & Nsabagasani

2003). The purpose of conserving Bwindi as park can be summarized as conservation of high

value and high biodiversity ecological resources, protection of important economic resources, and

protection of the Bwindi mountain gorillas as a gateway to increased tourism revenues.

Traditionally, the forest department allowed free extraction of non-timber products from the

forest. With the uplifting of the forest status to a national park level in 1991, all activities in the

park like entrance to the park without permission from the park management and use or

extraction of any forest resources by community members was henceforth illegal. The improved

protection accorded to the forest resources, coupled with the costs incurred from wildlife crop

raiding on community land and livestock loss to wild animals that contributed to poverty, was

marked by heightening hostility between the park staff and the local communities who resented

the escalating loss of access to traditional resources (Makombo 2003). Due to this, a new

management approach was introduced in BINP.

The management of BINP as from 1991 falls under the wider decentralization strategy and can

be described as comprising of collaborative management, under which the government has

devolved some powers and responsibilities to the local authorities including those governing

management of natural resources (Namara & Nsabagasani 2003). The collaborative-management

approach recognizes that interested parties have to work together on a mutual basis in order to

17

meet their various interests. To enlist community participation in the management of the park,

Community Protected Area Institutions (CPIs) which are supported by the Community Protected

Area Institutions Policy have been instituted to represent the interests of all parishes bordering

particular protected areas (Namara 2006). CPIs comprise of Community Protected Areas

Committees (CPAC), operate at the community and protected area level of organization and are

linked to the local governments system through the Production and Environment Committees

(PECs) (Makombo 2003). Its membership is drawn directly from parish-level local government

of the three districts that surround the park (Namara 2006). This management approach ensures

that there is representation of local community, local government, national and international

community interests (Infield & Adams 1999). International interests are represented through

organizations such as DANIDA funded CARE-Development Through Conservation (DTC)

Project., Mgahinga and Bwindi Impenetrable Forest Conservation Trust (MBIFCT) which is a

World Bank-GEF initiative. National interests represented by the Uganda Wildlife Authority

(UWA) mandated by the Wildlife Statute to manage wildlife in the country on behalf of the

people of Uganda and National Environmental Management Authority (NEMA) which deals

with all matters related to natural resource management.

The CPIs are an avenue of communication and advocacy between the local communities and park

management and also roles such screening and selecting parish-level projects for funding under

the UWA revenue sharing program and to identify any excessive conduct of the park staff and

report this to park management (Namara 2006).

Communities are allowed to use the park through resource user agreements (RUAs) signed

between resource user groups (RUGs) and UWA to allow use of specific resources from the park

in what was called the multiple use-zones (MUZs). Resources considered under this arrangement

are medicinal plants, craft materials, seed collection for on-farm planting outside the park, and

also the utilization of the park for placement of bee hives for honey collection (Makombo 2003),

but also forbidding some other uses like hunting, timber extraction which are assumed to have a

negative effect to the park. The memorandum of understanding specified the roles of the

communities and those of the park in ensuring that sustainable extraction of the resources is

18

maintained. The program has created a sense of ownership of the park by the communities,

enabled dialogue between the communities and the park management (Makombo 2003).

Under the resource-use program, resource user groups were expected to voluntarily monitor

illegal activities within their respective multiple-use areas, and to report to relevant authorities if

they detected any (Namara 2006).

3.2 Methodology

3.2.1 Site selection

The park is chosen because was one of the first parks in Uganda to start collaborative

management approach to park management (Namara & Nsabagasani 2003), and also as Namara

(2006) observes, BINP was among the first parks to institutionalize a framework for local

government participation in park management and decision making. Being a gorilla park, it is one

of the parks with the highest income (Kazoora 2002), this represents a greater potential to have a

contribution to the incomes of local communities. The park is also a wise selection because there

is general satisfaction from the community with the management approach and there are calls for

the program to continue (Ibid).

3.2.2 Data collection

Collection of data was done from October to December 2007. It involved both qualitative and

quantitative methods; to address issues of institutional arrangements enforced by park

management and collect data on income, activities and assets possessed by households

respectively. Data was collected using a seven page pre-tested questionnaire (Appendix viii).

Also focused group discussions with community opinion leaders were held to gauge community

attitudes and perceptions about the management strategy in place.

The survey units were stratified based on their proximity to the nearest park boundary. The strata

were at distances of less than two kilometers, between three and six kilometers and more than six

kilometers. In addition, 30 more households were selected from a list of 53 resource users of

Karangara resource users group. This is one of the few villages around the park were the local

19

community members have entered into an agreement with park management for the permission to

access selected resources from the park under agreed conditions. Karangara village is also located

at distance of less than two kilometers from the park. It was expected that survey units at

different distances to the park would show variation in key livelihood gradients as a result of

difference in benefits accruing at different distances from the park (Howard 1995). The sampling

frame was a list of households in villages at distances as stated in the stratification procedure; 0-2

km (Buhoma, Mukono, Nkwenda), 3-6 km (Kanyashade, Kimbugushu), 6+ km (Rugando) and 0-

2 km with resource user agreement (Karangara).

The four strata have been named as follows: - 0-2 km - Buhoma, 3-6 km - Kanyashande, 6+ km -

Rugando and 0-2 km with resource user agreement – Karangara.

From each of Buhoma, Kanyashande and Rugando, 40 households were randomly selected from

a list of village households to be interviewed. Together with the 30 members of Karangara

resource user group, these comprised the total sample of 150 households. Household head were

interviewed or in their absence the oldest family member. The household was used as the

smallest unit from which to measure income flows and stocks.

Some of the livelihood gradients used were similar but not restricted to those by Ellis and

Bihiigwa (2003). In order to do poverty level comparisons of the different strata, poverty

indicators similar to those suggested in the Poverty Measurement Index (PMI) by Hayati et al.

(2006) are adopted. These have undisputable relevance and validity (Hayati et al. 2006).

3.2.3 Data handling, estimation and analysis

Quantitative and qualitative data from the survey were analyzed using Stata10 and SPSS

respectively. Descriptive statistics are used to present household socio-economic characteristics

and relative incomes are used to show dependence on income sources. Like other studies in the

field, e.g Vedeld, Pal et al. (2004), relative income from park resources is used as a proxy for

measuring household dependence in park income.

Generally

20

RPI = relative park income =

TI

API

Whereby

API = absolute park income; TI = absolute total income

Diversity will is shown by the Simpson diversification index

DITI = Diversification index, total income =

∑=

⎟⎠⎞⎜

⎝⎛−

n

i

iTI

I1

2

1

Whereby

Ii is the income from the ith source in a set of n sources

and TI is the total income.

The Gini coefficient for total income is used to show income inequality (Cheong 1999).

The Gini coefficient for total income is calculated as

GTI =

μ2

1 1

2n

TITIn

i

n

iji∑∑

= =

−

Whereby

µ = Mean household income

n = Total population

TIi= Share on individual i of total household income

TIj = share of individual j of total household income

Further, a Gini coefficient is obtained for Karangara with park income excluded from total

income to reveal if park income has an income equalizing effect.

The contribution of the park to livelihood is estimated by using park income, which is the value

of all the products collected from the park. Value is obtained by multiplication of quantity of

21

products by selling price (for products sold in the market) or reported market price (for products

consumed by the household). Income from agriculture is measured using the reported price of

agricultural products.

Ordinary linear regression OLS analysis is used to estimate determinants of total household

income. In the analysis, total household income is transformed using natural logarithms to control

for variance and to ensure normality. A graphical presentation of the results for total household

income transformation is provided in Appendix ii.

Weighted least square regression was used to estimate the determinants of household income

diversity. Weighted least square regression was used because one of the variables (dependence on

off-farm income) was heteroscedastic. Weighting was done using the squared fitted value type

(xb2). The residual versus dependence on off-farm income and residual versus fitted values plots

are shown in Appendix iii and Appendix iv respectively.

3.3 Proxies for internal household factors

All household internal factors (access to human, social, physical and financial capital) are

measured by use of proxies.

3.3.1 Human capital

Human labor often offers the only other input aside from land that can be used to increase

productivity. In order to approximate human capital, it’s important not to use head count numbers

without adjusting them for age and sex characteristics of each household member. Age and sex

will affect the quality and quantity of human capital (Murphy et al. 1997). To adjust household

head count for age and sex, equivalent scales are used. Adult equivalence scales such as those

developed by the World Health Organization (Table 1) factor in the differences in households

caused by differences in age and sex of each household member (Cavendish 2002). The scales

used are similar to scales developed from elsewhere for instance adult scales in the TCH model

by Tedford, Capps et al (1986). The use of equivalent scales brings more accurate analysis than

22

using unadjusted household size in income analysis (Lanjouw & Ravallion 1995) despite their

many shortcoming as those discussed by Cavendish (2002).

The quality of human capital for each household is estimated using the number of years spent in

school by the head of the household. Only the household head is used because in most rural

areas, it is only the household head that is involved in gainful employment. Therefore the

household head education level can give a good indication of the quality of labor available to the

household.

Table 1: Adult equivalent scales Age Adult equivalents

Male Female 0-2 0.40 3-4 0.48 5-6 0.56 7-8 0.64 9-10 0.76 11-12 0.80 0.88 13-14 1.00 1.00 15-18 1.20 1.00 19-59 1.00 0.88 60+ 0.88 0.72 Source: Cavendish (2000)

3.3.2 Physical capital

Physical capital available is estimated by considering land and livestock assets. Different types of

livestock are kept ranging from cattle to poultry. In order to make comparisons, all livestock were

converted into a single unit; cattle equivalent units which express livestock in terms of price

ratios compared to cattle price. Such conversions have been done in other studies e.g. Ellis and

Ntengua (2003). Cattle equivalent units are presented in Table 2.

Table 2: Livestock conversion factors

23

Type of animal

Cattle equivalent

Cattle 1

Goats 0.12

Sheep 0.10

Pigs 0.14

Poultry 0.02

Source: (Ellis, Frank & Bahiigwa 2003)

Land assets were measured in total land owned (hectares). Another factor that has been included

to analyze land assess relates to land fragmentation, since fragmentation affects the productivity

and returns to land (Jha et al. 2005; Niroula & Thapa 2005). The number of parcels of land

owned was recorded. More number of parcels represents more fragmentation.

24

CHAPTER IV: RESULTS AND DISCUSSION

4.1 Basic household characteristics

The average household size for the whole sample was found to be 5.37 persons. Household size

is similar to other forested areas in Uganda for instance around Mount Elgon National park,

family size is estimated at 6.5 persons (Katto 2004). Household size in the study area is much

higher than the national average of 4.7 and also higher than 4.8 persons for most rural areas in

Uganda (UBoS 2002). Large households require more resources to meet their livelihood needs;

this increases demand for resources. It is expected that this will increase pressure on common-

pool resources like the park since most rural people like around BINP have few private assets.

The four strata did not differ significantly in respect to household size (p= 0.01). However, there

is a significant difference (p< 0.01) in adult equivalent units (AEU). Buhoma had the largest

family size probably because it covers Nkwenda and Buhoma that are bigger trading centers

being located closest to the tourist camp at Buhoma. Closeness to the tourist camp is expected to

offer employment opportunities that will attract many young people. Younger household heads

often have younger household members. In this study, the correlation between age of the

household head and adult equivalent units is significant (p<0.01), this can explain why Buhoma

did not have the highest adult equivalent units. On the other hand, Karangara had the highest

adult equivalent units probably because it has the highest average age for household head, which

was 49.3 years.

Male-headed households were 87.3% while female-headed households were 12.7%. Age of the

household head varied from 20 years to 90 years. There was a significant difference (p< 0.01) in

the age of the family head among the four strata.

25

Table 3: Socio-economic and demographic characteristics of the four strata and whole sample

Variable Buhoma Kanyashande Rugando Karangara Whole sample

n = 40 n = 40 n = 40 n = 30 N = 150

Mean (std.dev)

Mean (std.dev)

Mean (std.dev)

Mean (std.dev)

Mean (std.dev)

F statistic

p-value

Adult equivalent

units

4.823

(1.55)

3.81

(1.41)

3.82

(1.56)

5.16

(1.96)

4.35

(1.70) 6.58 0.0003***

Age of household

head (years)

43.7

(13.19)

38.58

(14.37)

34.38

(13.18)

49.33

(16.03)

40.97

(14.98) 7.31 0.0001***

Cattle equivalent

units

0.514

(0.49)

0.77

(1.13)

1.21

(1.78)

1.25

(1.74)

0.92

(1.38) 2.53 0.0598

Consumer worker

ratio

1.2058

(0.71)

1.04

(0.63)

1.11

(0.96)

0.81

(0.52)

1.06

(0.74) 1.72 0.166

Distance from

nearest dispensary

(km)

1.2625

(0.54)

3.40

(2.08)

8.78

(1.61)

3.40

(2.50)

4.26

(3.37) 129.08 0.0000***

Distance from

nearest hospital

(km)

62.875

(0.5352629)

57.93

(1.91)

53.45

(1.69)

41.73

(3.20)

54.81

(7.71) 596.14 0.0000***

Distance from

nearest market

centre (km)

19.675

(2.246222)

19.30

(3.22)

10.30

(1.87)

5.70

(1.01)

14.28

(6.23) 318.01 0.0000***

Distance from

nearest primary

school (km)

1.57

(1.57)

1.01

(0.76)

0.51

(0.49)

1.29

(0.79)

1.08

(1.07) 8.03 0.0001***

Distance from

nearest secondary

school (km)

19.80

(2.41)

17.75

(3.05)

14.28

(2.67)

3.20

(1.24)

14.46

(6.50) 286.76 0.0000***

Distance from

nearest tertiary

school (km)

47.40

(2.58)

46.40

(3.64)

32.00

(7.88)

34.07

(6.18)

40.36

(8.87) 83.87 0.0000***

Household head

count

5.88

(1.62)

4.98

(1.61)

4.83

(1.72)

5.93

(2.23)

5.37

(1.83) 3.92 0.0100**

Household head

education (years)

4.88

(2.85)

4.63

(2.87)

5.43

(3.37)

4.53

(3.49)

4.89

(3.12) 0.61 0.6075

26

Number of parcels

of land

2.45

(0.88)

2.28

1.11 ()

2.55

(1.22)

2.23

(1.14)

2.39

(1.09) 0.68 0.5635

Total land owned

(hectares)

1.68

(0.68)

0.94

(0.38)

1.49

(0.60)

2.16

(2.01)

1.46

(1.53) 4.39 0.0055***

F statistic and p-value show differences between the four strata: Buhoma (0-2 km), Kanyashande (3-6 km), Rugando (>6 km) and Karangara (0-2 km), from the park boundary. Karangara households are members of Karangara resource user group. *** = significant at p<0.01, ** = significant at p<0.05

Large families struggle with available incomes (Mamo et al. 2007), but families with a large

proportion of working members can pool incomes to obtain increase household income. The

consumer/workers ratio is computed for all strata and the whole sample, ANOVA reveals no

significant difference among the strata. This means that the effect of one unit of income from a

working household member on household welfare is similar among the strata since the

dependence ratio is the same.

The average number of years in school by the household head was found to be 4.89 for the whole

sample and there were no significant differences among the four strata. This falls under the

primary level of education. This is very characteristic of most of rural Uganda (Uganda Bureau of

Statistics 2002a). With such low levels of education, there is reduced ability and capacity to get

involved in off- farm employment.

With such low levels of education, the occupations of family heads were almost predictable. 83

percent of all household heads reported farming as their primary occupation. Peasant farmers

were understood to be those people who carry out own land cultivation as a means of livelihood.

The recent national census in 2002 reported that around 90 percent of people in western Uganda

report crop farming as the main economic activity (Uganda Bureau of Statistics 2002a). Regular

employment is not common in the area due to remoteness. Working as casual labor is not

common either in the area due to prohibitively low wages of labor which make it unattractive to

offer own labor for casual employment.

There were differences in number of household heads involved in different occupations

especially salaried employment. The most remote of the four strata i.e. Karangara reported no

salaried employment.

27

Park related employment such as tourist rangers or working in tourist camps was reported only in

Buhoma because it covered villages nearest to the tourist camps at Buhoma. While the randomly

selected sample did not reflect salaried employment in Buhoma, there are a number of

households whose members are employed as park staff.

Table 4: Main occupations of household heads Occupation Frequency Percent

Peasant 124 82.7

Student 1 0.7

Casual laborer 2 1.3

Salary employment 7 4.7

Service provider 3 2.0

None 10 6.7

Ranger 3 2.0

Total 150 100.0

All households had access to land. On average, the whole sample shows total land owned of 1.46

hectares. There were significant differences (p< 0.01) among the four strata. Karangara had the

largest amount of land owned, followed by Buhoma. Kanyashande had the smallest amount of

land owned. Remoteness of Karangara relative to other strata can explain why they possessed

more land. The reason for more land owned in Karangara could be the fact that they households

interviewed had older family heads.

There is usually a relationship between the age of the family head and the amount of land owned.

In this study, age of the family head was found to be positively correlated with amount of land

owned (p< 0.01). Most of the household perceived their land as being fertile. None of the

respondents had a land title; it was not considered important to get a land title. The cost of getting

a land title may also be prohibitively high especially in rural areas where land markets are so

poor. This may have implications on the ability to access financial credit in conventional lending

institutions like banks since only titled land is used as collateral. While the study did not probe

28

much on access to financial credit due to sensitivity of the matter and the possibility of none

responses, many rural household can still access financial credit using social ties as security.

There was a lot of fragmentation of land with most households reporting more than two parcels

of land (Table 3). Fragmentation may hinder productivity (Niroula & Thapa 2005) due to travel

time between land parcels and the fact that the parcels are usually too small to facilitate any

intensive agriculture or may have desirable effects on households by enabling to schedule costs

and to ease labor bottlenecks. It was not in the scope of this study to detail the effects of

fragmentation on productivity. Fragmentation in the study areas is due to the practice of

inheritance whereby the father apportions land among all male children. When family size is big,

each male child inherits just a small portion of the land and may have to purchase more land to

increase own land holding. A major feature of the landscape in southwestern Uganda; the field

mosaic is evident in the study area. Field mosaic describes the patterns made by small fields of

crops on the gentle slopes. Acquisition of land was mainly by purchase and inheritance. Most of

the respondents reported to have acquired at least one of the parcels by inheritance.

The other important asset noted was livestock. There was a large profile of different livestock

kept by households, almost every household owned poultry. The reason being the ease with

which poultry is converted into cash and low investment. Reasons for owning livestock were

reported provision of meat and milk and also status symbol especially cows. On average,

households possessed 0.92 cattle equivalent units (CEU) of livestock. There was no significant

difference among the strata but Karangara households owned more livestock compared to the rest

(1.25 CEU). The respondents in Karangara are members of a resource user group that at one time

was provided with goats under a program to provide bush meat substitutes to households that

previously hunted bush meat in the park.

4.2 Access to infrastructure and social services

Rural livelihoods are constrained by poor road infrastructure and long distances from basic social

services like schools and health centers. Long distances from schools may hinder attainment of

education and improvement of human skills, distant health facilities may exacerbate prevalence

29

of disease and high mortality. This study revealed that households were located at average

distances of 1.08 kilometers from a primary school, 14.46 kilometers from a secondary school,

and 4.26 kilometers from the nearest dispensary. Distance from a general hospital was even

greater at 54.81 kilometers. The four strata differed significantly in their closeness to primary,

secondary, tertiary, dispensary, and hospital (p< 0.01). Households closest to the park boundary

were located furthest from schools and the main hospital. These results however have to be

treated with caution. Like Maisel et al (2007) argue, “protected areas are often established in

remote regions where resources may be less abundant or productive, where households rarely

have access to markets, and are last to be provided with government or NGO-sponsored social

services.” Hence the difference here may not show the effect of the park on local welfare.

Households in Buhoma were located close to the dispensary due to the presence of Buhoma

community health centre BCHC, a community dispensary set up by Doctor Scott Kellermann a

volunteer doctor to offer health services to poor batwa pygmies. The center now offers medical

services to the whole community.

Access to the market may also affect rural livelihoods. Cash income especially from the sale of

agricultural produce can be a major contributor to total household income. This study shows a

strong positive correlation between total crop cash income and total household income (p<0.01).

This is obvious since agriculture forms a backbone of most of rural Uganda.

In order to sell their crops; there is need for a market to be available at a reasonable distance,

which will enable transportation of produce with the available transport means. The results

showed negative significant correlation (p<0.01), though weak, between distance to the market

and income from sale of crops. The weak strength of the correlation may be because rural people

sometimes have other ways of having farm produce sold other than taking it to the market, for

instance on-farm sales. The survey subjects were located at an average of 14.28 km from the

nearby market center at Butogota. The four strata differed significantly in their distance from the

market (p<0.01). Karangara was located nearest to the market center (5.70 km) and Buhoma the

furthest (19.68 km).

30

A radial graph is drawn to compare the strata in terms of the reported four basic assets.

Household annual percapita income was included as the fifth variable and the results are shown

below in Figure 4. Of the four five categories of assets used in the radio graph, it is only adult

equivalent units and total hand where the four strata were significantly different and in these two

Karangara was the best followed by Buhoma. There is not enough grounds to confirm the

hypothesis that households nearer the park have greater asset endowment.

Buhoma (0-2 km), Kanyashande (3-6 km), Rugando (>6 km) and Karangara (0-2 km), from the park boundary. Karangara households are members of Karangara resource user group.

Figure 3: Selected endowments by stratum

Aggregating Buhoma and Karangara also Kanyashande and Rugando to investigate further the

effect of proximity on access to assets gave a more elaborate superiority of households nearer the

park in terms of the chosen asset categories.

31

Buhoma (0-2 km), Kanyashande (3-6 km), Rugando (>6 km) and Karangara (0-2 km), from the park boundary. Karangara households are members of Karangara resource user group.

Figure 4: Selected asset endowments showing aggregated strata

4.3 Household income and income dependence

4.3.1 Household income sources

Households had mainly agriculture-based incomes. Cash and subsistence income from sale of

crops, livestock and livestock products formed the backbone of household income. Seldom also,

households got income from non-farm based sources like off-farm employment. Households in

Karangara also reported income from park products like from sale of crafts and honey.

32

Table 5: Household income (UGX) Variable Buhoma

n=40

Mean

(std dev)

Kanyashande

n=40

Mean

(std dev)

Rugando

n=40

Mean

(std dev)

Karangara

n=30

Mean

(std dev)

Whole

sample

N=150

Mean

(std dev)

F-

statistic p-value

Crop

income

1031775

(691456.4)

753760

(477936)

787935

(698760.3)

2126947

(2181730)

1111648

(1229205) 10.67 0.000***

Livestock

income

42075

(76133.28)

78175

(115658.8)

38081.25

(184139.9)

80818.33

(112496)

58385.33

(129403.6) 1.16 0.3287

Off-farm

income

490500

(800832.7)

409125

(769738.5)

690000

(1201076)

45466.67

(157695.4)

432993.3

(868555.2) 3.38 0.0200**

Park

income

0.000

(0.000)

0.000

(0.000)

0.000

(0.000)

13833.33

(18465.41)

(0 01)

2766.667

(9857.337) 22.6 0.000***

Total

household

1564350

(999067.20)

1241060

(764542.10)

1516016

(1702951)

2267065

(2167611)

1488014

(1605793) 2.95 0.0035***

income (0 01)F statistic and p-value show differences between the four strata; Buhoma (0-2 km), Kanyashande (3-6 km), Rugando (>6 km) and Karangara (0-2 km), from the park boundary. Karangara households are members of Karangara resource user group. *** = significant at p<0.01, ** = significant at p<0.05

As Table 5 shows, there were significant differences (p<0.05) in total household income, crop

income, off-farm income and park income. Karangara households received the highest crop

income probably due to the popularity of tea growing in the area. Tea is a popular crop in

Karangara because it is one of the crops encouraged under the Human-Gorilla Conflict

Resolution (HuGo) scheme because it is not palatable to gorillas. While taking up tea growing

due to its being unpalatable to gorillas has brought benefits of increased income, it cannot be

considered an advantage of being close to the park because the households in the areas most

affected by crop raiding have to buy food crops they cannot grow on their own land. Price

fluctuation in the price of tea, a major source of income in such areas, may make these people

vulnerable. Low crop income in Kanyashande may be because of low land acreage among

households, while involvement in off-farm employment for instance in as medical officers and/or

teachers among some household members in Rugando may have reduced crop income since off-

farm employment is more attractive than farming.

33

Households from Rugando received the highest off-farm income, followed by households in

Buhoma. A number of households in Rugando had a member working at Buhoma community

health center BCHC or teaching at a local primary school. This increased the average income

from off-farm activities for Rugando. Buhoma also had some household members working in the

park as support staff.

Predictably, due to the resource user agreement (RUA) scheme, only Karangara households

obtained park related income. Households from the other strata could not access park products

since they did not have a memorandum of understanding MoU with the park.

The four strata did not differ with respect to livestock income. Generally the area is not very ideal

for livestock husbandry due to heavy rains and shortage of land. Though some households owned

livestock, it is not a major livelihood activity.

Households closest to the park (Buhoma and Karangara) received higher total household income

than those further away (Kanyashande and Rugando). Karangara households received the highest

followed by Buhoma. Kanyashande households received the lowest household income. These

results can be used to confirm the hypothesis that households nearer to the park have higher total

incomes.

4.3.2 Household dependence

The different livelihood activities contributed differently to total household income. The

contribution of each source of income to total household income was computed. This has been

expressed relative to total household income to show dependence of the household in a given

income activity. The results are presented in Table 6.

34

Table 6: Contribution of livelihood activities to household income Variable Buhoma

n=40

Mean

(std dev)

Kanyashande

n=40

Mean

(std dev)

Rugando

n=40

Mean

(std dev)

Karangara

n=30

Mean

(std dev)

Whole

sample

N=150

Mean

(std

F-

statistic p-value

Dependence on

agriculture

0.80

(0.31)

0.77

(0.34)

0.78

(0.33)

0.96

(0.08)

0.82

(0.30) 3.11 0.0284**

Dependence on

off-farm income

0.20

(0.31)

0.23

(0.34)

0.22

(0.33)

0.03

(0.08)

0.18

(0.30) 3.42 0.0191**

Dependence on

park income

0.00

(0.00)

0.00

(0.00)

0.00

(0.00)

0.01

(0.01)

0.00

(0.01) 25.72 0.0000***

F statistic and p-value show differences between the four strata; Buhoma (0-2 km), Kanyashande (3-6 km), Rugando (>6 km) and Karangara (0-2 km), from the park boundary. Karangara households are members of Karangara resource user group. *** = significant at p<0.01, ** = significant at p<0.05

There is a significant difference (p<0.05) among the four strata in relation to dependence on the

main livelihood activities (see Table 6). Generally, agriculture provided the bulk of household

income; more than 70 percent. This has been found in other studies on rural households

(Tumusiime 2006). Households in Karangara were the most dependent on agriculture (96%). The

other three strata show almost similar dependence of agriculture. The high dependence on

agriculture on Karangara is likely because there were no other important available means of

livelihood due to remoteness.

Off-farm employment opportunities were very few in Karangara. Much as Karangara much is

located as close to the park as Buhoma, it’s located very far from any important park activity sites

like gorrrila tracks or tourist camp. Other sources of off-farm income like casual labor are not

attractive due to the very low wages. Respondents reported that a casual laborer in the area is

paid 1500 UGX for a day’s work. This is a disincentive to engage in offering casual labor. As a

result off-farm income contributed only eight percent of total household income.

Only Karangara households showed any dependence on park income because they have a

memorandum of understanding to harvest park products. The strict protection and restrictions

over access to park resources make analysis of factors determining dependence on park income

35

difficult. All members of Karangara resource user group are allocated equal harvestable quotas of

basketry materials. The resource user agreement stipulates beneficiaries, the quantities to harvest

and the frequency of entry into the park. Based on that, the conditions under which park products

from BINP are accessed by local people make rejecting the hypothesis that household nearer the

park depend more on park income inevitable.

Household income from agricultural production has been calculated as a sum of both cash and

subsistence income. Therefore the figures do not show a very true picture of how much money

households have available to invest in asset accumulation. Poor food commodity markets make

rural people use up a large portion of crop production consumption. In the household economic

model (Figure 1), a block arrow from the consumption box has been used show the proportion of

returns from livelihood activities used up in household consumption. The table below shows the

proportion of crop income used for either subsistence or cash.

Table 7: Household subsistence and cash income Variable Buhoma

n=40

Mean

(std dev)

Kanyashande

n=40

Mean

(std dev)

Rugando

n=40

Mean

(std dev)

Karangara

n=30

Mean

(std dev)

Whole

sample

N=150

( td

F-

statistic

p-value

Relative

cash income

0.22

(0.17)

0.21

(0.19)

0.09

(0.17)

0.38

(0.24)

0.22

(0.21) 14.04 0.0000***

Relative

subsistence

income

0.76

(0.17)

0.76

(0.20)

0.91

(0.18)

0.56

(0.22)

0.76

(0.22) 18.79 0.0000***

F statistic and p-value show differences between the four strata; Buhoma (0-2 km), Kanyashande (3-6 km), Rugando (>6 km) and Karangara (0-2 km), from the park boundary. Karangara households are members of Karangara resource user group. *** = significant at p<0.01, ** = significant at p<0.05

Table 7 shows that most of the income from agriculture is subsistence income. The whole sample

showed 76 percent of income being subsistence. The four strata differ significantly (p<0.01) in

the share of subsistence and cash income from agriculture. Karangara shows the highest share of

cash income. Because of its location relative to a market center at Butogota, households in

Karangara revealed the highest total crop cash income of 1,196,575 UGX. The high crop cash

36

income in Karangara may also be because the area is prone to crop raiding by gorillas from the

park and can only grow crops that are less palatable to gorillas. Due to that, almost all households

in Karangara grow tea which is not destroyed by gorillas. Tea income is only reflected as cash

income since it is not consumed at home.

4.4 Determinants of total household income

In order to assess the effect of household level factors on total household incomes, I ran an

ordinary linear regression analysis of total household income against household characteristics.

The results are presented in Table 8. Among the characteristics, total land owned (*** p<0.01),

adult equivalent units (*** p<0.01), education of household head (* p<0.1), dependence on off-

farm income (*** p<0.01), cattle equivalent units (* p<0.1) and location of the household in

Karangara were found to be significant and with positive signs of the coefficient.

The size of land holding determines the returns to agriculture based livelihoods (Karugia et al.

2005). Together with labor, land is important in rural productivity and usually may represent the

only variable input into agriculture production. Therefore households with more land are likely to

have higher incomes especially so because the study area revealed a high dependence on

agricultural incomes. This is well in line with a study by Karugia et al. (2005) in rural Kenya that

concluded that increase in land holding was positively correlated with percapita income.

Higher adult equivalent units positively affected household income because households with

more adults have more labor for both on-farm and off-farm employment. This increased

household agriculture productivity since family labor is an important input in agriculture in rural

areas. Having more adult equivalent units in a household also increased chances of engaging in

off-farm employment which led to higher household income due to high returns from off-farm

employment (Karugia et al. 2005).

Dependence on park income was found to be significant (p<0.1) but together with household

head being female (p<0.1) had negative coefficients. Engaging in forest products extraction may

be the only means for the household to make use of excess family labor, but it is clearly a less

productive use of labor, hence may reduce total household income. In Karangara offtake quotas

37

for Marantochloa mannii and Smilax anceps for basketry are low. These are also not very

valuable resources. Yet resource user group members are allocated large responsibilities like

boundary monitoring which require time and compromise involvement in other income

generating activities. This could be counterproductive as indeed Table 8 shows, hence rejecting

the hypothesis that total income increases with park income.

Female household heads negatively affected household income. This may be explained by the

fact that most of female household heads were widowed and old women who may be less

productive than their male counterparts.

Table 8: Ordinary linear regression of log total household income against household characteristics

Number of observations= 150 F( 15, 134) = 12.23 Prob > F = 0.0000

R-squared = 0.5779 Adj R-squared = 0.5307

Root MSE = .561 Log Total household income Coefficient. t P>|t|

Sex of household head (1= Male) -0.26778 -1.8 0.074*

Age of household head 0.00213 0.51 0.611

Occupation of household head (1= peasant) 0.255008 1.29 0.199

Distance from the market 0.010206 0.49 0.623

Total land owned 0.069366 4.39 0.000***

Cattle equivalent units 0.098457 2.37 0.019**

Dependence on off-farm income 1.111351 5.04 0.000***

Dependence on park income -18.456 -1.94 0.054*

Consumer Worker ratio 0.04722 0.71 0.477

Diversity index of total income -0.00176 -0.01 0.996

Adult equivalent units 0.097691 3.01 0.003*** Kanyashande (1= Buhoma) -0.00505 -0.04 0.971 Rugando (1= Buhoma) -0.20192 -0.85 0.395 Karangara (1= Buhoma) 0.590443 1.76 0.08*

Household education (years) 0.036572 1.92 0.056*

Constant 12.49586 26.22 0.000*** Breusch-Pagan / Cook-Weisberg test for heteroskedasticity: Prob > chi2 = 0.9785. Buhoma and Karangara (0-2 km), Kanyashande (2-6 km), Rugando (>6 km) from the park boundary *** = significant at p<0.01, ** = significant at p<0.05, * = significant at p<0.1

38

Using dummies for location of the household in either of the strata, the regression revealed that

only being located in Karangara had a significant (p<0.1) effect on total household income. This

result however has to be used with caution; Karangara has many other desirable attributes that

may be responsible for the high incomes. These include its location near the market and the fact

that a lot of household engaged in the highly income generating tea growing. The relationship

between dependence on off-farm income and total household income is graphically presented in

Figure 5

The graph shows that many households did not earn any off-farm income. However, for those

who did, increased dependence on off-farm income tends to increase household income. Apart

from being a supplement to other income activities like agriculture, off-farm income can also be

used to boost income from other livelihood activities like hire farm labor, which may ultimately

increase agricultural income. Households that showed zero dependence on off-farm income were

also able to obtain high households income. The study area in not known for a lot of off-farm

employment opportunities. Households with no access to off-farm income concentrated on other

livelihood sources to get equally high household income. This is especially true for Karangara

households that specialized in tea growing.

log Total household incomeFitted values

1.8.4 .6Dependence on off-farm

.20

16

15

14

13

12

39

Figure 5: Relationship between dependence on off-farm income and total household income

Age and occupation of the household head did not affect total household incomes. This is a rather

unexpected result but it may be due to the size of the sample. The effect of occupation being

insignificant may also be due to the low variation in occupation; most of the respondents were

peasants (see Table 4).

4.5 Effect of proximity to the park on total household incomes

The results in Table 8 show that location of the household relative to the park had no significant

effect on total household income at 5% level of significance. The reason for this result may be

caused by the level protection imposed on BINP, which makes it different from other forest

resources. Use of park resources is strictly forbidden unless under very special circumstances.

Even then, the resources allowed to be taken out are too little to make any significant impact on

household incomes. Tourist camps and lodges can potentially provide market for locally

produced goods. This is not true in BINP because tourist camps offer foreign dishes to guests and

are not too involved purchase of local agricultural goods. Most food commodities are purchased

from Kampala. Differences in household incomes among the four strata are likely to emanate

from other influences for instance distance relative to market and the type of crops grown in

households.

4.6 Household total income diversification

A major characteristic of rural livelihoods is livelihood diversification whereby a large profile of

livelihood activities is adapted (Barrett, Christopher B. et al. 2001). Table 5 showed a large

profile of livelihood activities pursued by households in the different strata. The reasons for this

are numerous as noted by Ellis (1998). It can be argued that rural people take up many livelihood

activities as a means is spreading out risk in case of failure in any one of the activities, but also

due to the fact that rural income activities generate meager incomes, a large profile of activities is

needed to build up current consumption (Vedeld, Paul et al. 2007) .

40

Simpson’s diversification index is used to measure the level of diversification. The index

expresses diversification in terms of the number of activities. It can range from zero showing no

diversification at all (a single income source) to value 1 showing maximum diversification (c.f

Vedeld, Pal et al. 2004).

Households’ income diversification depends on the various assets owned by a household.

Weighted least squares regression shows that the amount of livestock owned has an influence on

income diversification (p< 0.01). Livestock especially goats can be easily sold and provide a

good supplement to other household income, therefore will increase sources of household

income. Consumer/worker ratio has a negative effect on diversification index (p<0.01) (Table 9).

Total household income is a summation of all income for each member of the household. Where

individual household members specialize in different activities, more working household

members will increase the number of available income sources. This means that while each

member specializes in one activity, data for the whole household may show diversification of

household income when individual incomes are pooled together.

The household dependence on off-farm income will positively affect diversity of household

income (p<0.01). Off-farm income has been calculated as a sum of a number of off-farm related

income sources, the more the number of sources, the higher the income diversity.

Table 9: Weighted least squares regression of total income diversity and household socio economic fators

Number of observation = 150 F( 11, 138) = 12.75 Prob > F = 0.0000

R-squared = 0.5040 Adj R-squared = 0.4645 Root MSE = .02202

Diversity index of total income Coefficient t P>|t| Sex of household head (1= Male) 0.106281 2.2 0.029** Age of household head -0.00174 -1.87 0.063* Occupation of household head (1= peasant )

-0.01462 -0.18 0.858

Distance from the market 0.004077 2.47 0.015** Total land owned 0.015814 3.46 0.001*** Cattle equivalent units 0.06718 3.63 0.000*** Consumer Worker ratio -0.05765 -3.5 0.001*** Adult equivalent units 0.003322 0.68 0.498

41

Household head education (years) -0.00206 -0.56 0.578 Log Total household income 0.037262 4.31 0.000*** Dependence on off-farm income 0.517854 3.56 0.001*** Constant -0.46696 -4.38 0.000***

Total income diversity increases with total income (p<0.01); wealthier families with higher

incomes usually have the resources to engage in more than one income activity. One of such

sources is land, which is necessary for livestock husbandry. Wealthier families can also afford to

hire labor for agricultural activities while family members engage in other off-farm activities.

Figure 6 shows the relationship between the log of total household income and income diversity

index. From the figure, it is apparent that some households show total specialization while others

highly diversify their income. The majority of households showed low diversification with

average at 0.177. While a few households obtained high incomes with total specialization, the

majority of high incomes earning households are ones that showed high tendency to diversify

income. While diversification is believed to have a negative effect on income (see Vedeld, Pal et

al. 2004), it can be used to increase current consumption and in the short run may have a positive

effect on household income.

Total income Diversification indexFitted values

161514Log Total household income

1312

.8

.6

.4

.2

0

Figure 6: Relationship between total household income and income diversification

42

43

4.7 Distribution of income

4.7.1 Income inequality It is not enough to know average total incomes for a particular society. The way income is

distributed among the different households is important to give the overall picture of inequality

and wellbeing. High levels of inequality reflect lower wellbeing. Gini coefficient is used to

indicate the level of income inequality in the four strata. The results are shown in Table 10. The

Lorenz curves for each stratum is shown in Appendix i

Table 10: Comparison of income inequality in the four strata Stratum Gini coefficient

1 0.3508

2 0.3358

3 0.5347

4 0.4683

Whole sample 0.4389

Buhoma (0-2 km), Kanyashande (3-6 km), Rugando (>6 km) and Karangara (0-2 km), from the park boundary. Karangara households are members of Karangara resource user group.

The Gini coefficient for Rugando is highest which clearly shows that there is more inequality in

Rugando. The reason for the high Gini coefficient is likely due to the number of household heads

with salary employment. 86 percent of household heads in the whole sample with salary

employment were located in Rugando. This may have caused the high Gini coefficient having

high earning households in a stratum with the second worst total household income. Generally,

Kanyashande and Buhoma show the least inequality. The low inequality in Kanyashande can be

attributed to the fact that all household heads had similar occupation and therefore likely to have

similar income.

4.7.2 Effect of park income on income inequality

To understand the effect of park income on income inequality, the Gini coefficient for Karangara

with park income was compared with the Gini coefficient without park income, the results are

shown in Table 11. They reveal that Gini coefficient without park income is lower than park

Gini coefficient without park income. The difference is however too small to warrant a

conclusion that park income reduces income inequality in places where community members are

allowed to access park products.

Table 11: Comparing Gini coefficient for Karangara with and without park income

Inequality Gini

coefficient

Total household income of Karangara with park income 0.4683

Total household income of Karangara without park income 0.4698

44

4.8 Performance under the collaborative management scheme

4.8.1 People-park relations

Focus group discussions revealed that salient tentions exist between the park and the aspirations

of local pepole. It is a well held view that the park is a constraint in the pursuit of better

livelihoods. Having been established recently in 1991, local people were still bitter about the loss

of access to park resources especially timber and mineral resources, which they considered to be

good sources of income. Loss of access to resources accentuated by strict protection within

national parks has been widely reported (e.g. Cernea, M. Micheal & Schmidt-Soltau 2006;

Kawuki 2007; West & Brockington 2006). None the less, local people still held the view that

change of status of the forest from forest reserve to national park was a good development and

are still optimistic that the park will generate benefits. Good attitude towards the park has also

been reported in an earlier study by Wild and Mutebi (1996). The optimism can be an example of

what Kremen et al. (1999) describe as social engineering whereby rhetoric about park benefits

creates expectations within local people which are hardly met (West & Brockington 2006). Local

people reported that the park is beneficial to them but further probing revealed that the positive

opinion about park is a mere expression of what they have been made to believe.

4.8.2 Perceived benefits of staying close to the park

The question about the percieved benefits of being close to the park generated mixed responses

with half of the group agreeing that being close to the park was beneficial while the other half

disagreed. The people who reported being close to the park as beneficial were those located

nearest to the tourist camp because they could get additional income from working as tourist

guides and also selling currio. Among other benefits reported were tourism revenue sharing

which according to members ensured that more people benefited from the park as opposed to

when only people involved in timber business would benefit when the forest was still a forest

reserve with timber extraction permitted. There were however strong reservations about the

allocation of the tourism revenue sharing funds.

45

Local people also pointed out a number of intergrated community development projects

established in recent times that are believed to be beneficial to the community. These included

Buhoma community rest camp offering budget tourist accomodation. It is managed by Buhoma

Community Development Association (BCDA) on behalf of local communities in Mukono parish

and was established with the help of Institute of Tropical Forest Conservation ITFC with the help

of UWA.

Focus group participants also reported increased security as a benefit from the park. The study

area is located on the Uganda-Congo border and has been an area ridden with rebel insurgency, a

common occurance in many protected areas (West & Brockington 2006). However, due to the

importance attached to tourism activity in the area, the military has beefed up security, the area

now benefits from 24 hour patrols by military permanetly based in the park. Such benefits have

also been reported in other parks where security has been tightened. For instance local people

around Mt Elgon national park also reported increased security against cattle rustlers as a benefit

attributable to park security (Kawuki 2007).

4.8.3 Local people participation in management of BINP

The community conservation model considers local people participation as indispensable in

successful management of protected areas (Hayes 2006). The push towards the community

conservation model in Uganda has also been catalysed by economic reforms in the late 1980s

especially the structural adjustment program, which sought to reduce government spending

(Namara 2006). Exercising community conservation has seen the creation of structures such as

Community Protected Area Institutions (CPI) to represent local interests. In view of this, focus

group participants were asked if they considered themselves actively involved in park

management.

There was consensus within focus group participants that local people were more involved in the

management of the park due to the work of the community conservation warden. But local people

did not feel that they were being taken as equal partners in the management of the park and in

decision making. This agrees with what Goldman (2003) noted that in most of Africa, local

communities “remain peripheral to defining the ways in which conservation is viewed and nature

46

managed.” Power relations between local people and conservation agency are a contentious

subject. Conservation agencies prefer to keep local people at a distance (Wells, P. M. & McShane

2004) and as a resullt, power devolution is still a distant reality (Agrawal & Ribot 1999). Also

according to Ribot (2002) “reforms are characterized by insufficient transfer of powers to local

institutions under tight central government oversight”. Studies in other parks in Uganda have

highlighted the level of emphasis UWA has placed on patnerships. Recruitment data of park

rangers shows that in Mt Elgon national park and Kibale national park, the ratio of law

enforcement rangers to community conservation rangers is 6:1 which shows that higher prioroty

is given to protection than to collaboration (Chhetri et al. 2003).

4.8.4 The tourist revenue sharing scheme

Tourism revenue sharing was implemented in BINP in 1994 as one of three pilot parks. Under

the scheme, local people were mandated to obtain part of tourism money for use in community

development projects. This scheme has since been made manadatory for all ten parks in Uganda

(Archabald & Naughton-Treves 2002). The enabling policy for the scheme was changed in 1996

and currently allows sharing of 20 percent of park gate fees. The change in policy had negative

effects on gorrila based parks like BINP because it excludes gorrila permit and viewing fees

(Archabald & Naughton-Treves 2002) which make the biggest bulk of tourism revenue.

None the less, the money has been used to finance local projects (Makombo 2003). The study

sought local people’s attitudes about the management of the scheme.

A common disgust was noted about the fact that the money is sent to the local government for

allocation. Participants echoed that the costs of proximity to the park particulary wildlife crop

raiding were incurred by individual households but the tourism revenue sharing money was being

enjoyed by people far away, who are not in any way affected by the park. Asked how best they

would like funds from tourism revenue to be handled, focus group members suggested that they

would rather the money be sent to the village level which would then decide on how to best use

the money for the benefit of the real people affected by park proximity. A minority of participants

suggested that money be given to individual households, but this was rejected on grounds of

impractability and montoring difficulties.

47

4.8.5 Resource use in BINP

In 1994, BINP has implemented schemes to provide benefits to local communities (Hamilton et

al. 2000). One of the schemes was the creation of multiple-user zones in the park in which local

people could be allowed to extract some resources. This was however to be done on condition

that a group of resource users signs a memorandum of understanding with park management on

behalf of UWA. The first memoranda of understanding were signed in three pilot parishes and

they permitted use of speicified quantities of resources in multiple use zones (Wild & Mutebi

1996). The allowed resources in Bwindi are medicinal plants, basketry materials and placemet of

bee hives.This has since expanded and now covers over 20 parishes around the park .

Only Karangara had a memorandum of understanding with the park for use of resources and

discusion with group members revealed disatisfaction with the quantities of resources and

frequency of entry into the park. Low quantities under these resource user agreements have also

been repoted in an earlier study by Wild and Mutebi (1996). The economic analysis showed that

park resources contributed very little to household income.

There were also sentiments on the fact that these agreements were signed with groups of users of

specific resources and not the whole community. If access to resources was being allowed as

compensation for the damage done by wildlife, then the agreements should be more inclusive

since wildlife did not selectively damage property of resource use group members.

4.8.6 Local opinions on how the park can benefit local people

Generally sustainable resource use was not seen as the best method of compensating for costs of

being close to the park. Discussion group members from villages nearest to the park suggested

that they were more interested in park mamagement doing more to reduce crop damange while

those further away were more intersted in collaborative resource management. This clearly shows

the importance local people attach to having some power over the management of resources in

their midst. Like Mac Chapin (2004) reports, most partnerships with local people represent the

agenda of conservationsists, which is not in the spirit of equal rights between conservationists

and local people. For people nearest to the park and who are victims of crop raiding, park

48

management should put more effort in reducing crop damage or compensate for crop damage.

Currently the park has no obligation to compensate for crops damaged and communities have to

organise themselves to errect barries against gorrila entering private land. Barriers used have

included trenches, planting thorny fences between farmers fileds and the park and also growing

buffer crops such as tea.

49

CHAPTER V: CONCLUSIONS

The study revealed that differences in household income. Income in Karangara is high, Buhoma

and Rugando are intermediate and Kanyashande low. High household incomes in Buhoma can be

attributed to park related activities like park jobs, selling curios, and petty businesses that flourish

at the entrance of the park. High incomes for households in Karangara are due to tea growing.

The danger of crop raiding makes tea growing the best income generating activity. However, this

may make households in Karangara vulnerable to income failures in case the price of tea

fluctuates or they may be susceptible to monopsonist exploitation, given the fact that there is only

one tea buyer in the area.

The study showed that proximity to the park did not significantly affect asset endowment among

households. There was no significant difference in livestock, education level of the household

head, and household adult equivalents among the strata. There were however significant

differences on amount of land owned with Karangara recording the highest land owned, followed

by Buhoma.

Regarding the effect of proximity to the park on dependence on park income, the study does not

provide enough grounds to conclude that households nearer to the park depended more on park

income. The reason for this is that access to park resources in not guaranteed by closeness to the

park but by signing a memorandum of understanding with the park management. Members of

resource user groups upon signing a memorandum of understanding are given identification cards

and its only then that they can be allowed to enter the forest on a given date usually twice a year

and in the company of a park ranger to collect park products. The resource user agreements

allocate harvestable offtake quotas according to what is considered as being sustainable ensuring

that the forest retains its natural state as much as possible. Both Buhoma and Karangara are

located within the same distance from the park but only Karangara households could access park

resources and therefore only Karangara reported park income.

50

Proximity to the park did not influence income diversification because the park does not offer so

many other sources of income to the local people as do other parks where resource extraction is

permitted or in parks with mass tourism and more visitor numbers

While total household income is expected to increase with environmental income like forest

income wherever local people are allowed to access forest products, the study revealed that

dependence on park income in Karangara was associated with low household income. Park

income in Karangara also reduced income inequality but only slightly. On the one hand, this

suggests that targeting of groups for user agreements has been relatively accurate and successful.

On the other hand, the actual benefits realized by beneficiaries are extremely modest. Park

resources clearly have the potential to bring about increased income equality by serving as

substitutes for private assets among asset-poor households. However, the scale of these programs

and the permitted extractive activities are today too limited to generate significant improvements

in local livelihoods.

From the focus group discussion it is safe to conclude that local people are generally happy with

the management scheme in place. They acknowledge the fact that the park offers a lot of

community benefits in terms of integrated community development projects like gravity water

schemes and funding construction of local schools. However there is dissatisfaction with tourist

revenue sharing. Locals believe the money should be used to benefit directly the people most

affected by proximity to the park. Instead, the money is sent to local government as used

according to local government plans which may not directly benefit the affected households.

The rhetoric about tourist revenue sharing compensating lost access to resources within local

communities near BINP does not make up for the loss to crop raiding. For victims of crop

raiding, the only reasonable compensation should be directly proportional to the damage made by

park wildlife. Park management has failed to commit on crop raiding neither as compensation nor

putting in place control measures like park boundary to stop wildlife attacks.

51

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APPENDICES Appendix i: Lorenz curves showing income inequality

Whole sample (Gini 0.4389)

Cum

ulat

ive

Frac

tion

of T

HI

Lorenz Curve--THICumulative Fraction of base

FPOP2 FDIST

0 .5 1

0

.5

1

Buhoma (Gini = 0.3508 )

Cum

ulat

ive

Frac

tion

of T

HI

Lorenz Curve--THICumulative Fraction of base

FPOP2 FDIST

0 .5 1

0

.5

1

Kanyashande (Gini = 0.3358)

60

C

umul

ativ

e Fr

actio

n of

TH

I

Lorenz Curve--THICumulative Fraction of base

FPOP2 FDIST

0 .5 1

0

.5

1

Rugando (Gini = 0.5547)

Cum

ulat

ive

Frac

tion

of T

HI

Lorenz Curve--THICumulative Fraction of base

FPOP2 FDIST

0 .5 1

0

.5

1

Karangara (Gini 0.4683)

61

C

umul

ativ

e Fr

actio

n of

TH

I

Lorenz Curve--THICumulative Fraction of base

FPOP2 FDIST

0 .5 1

0

.5

1

Karangara without park income (Gini 0.4698)

Cum

ulat

ive

Frac

tion

of T

HP

Lorenz Curve--THPCumulative Fraction of base

FPOP2 FDIST

0 .5 1

0

.5

1

62

Appendix ii

Histograms of transformation for total household income 02.

0e-2

14.

0e-2

16.

0e-2

18.

0e-2

11.

0e-2

0

0 5.00e+20 1.00e+21

cubic

02.0e

-14

4.0e

-14

6.0e

-14

8.0e

-14

1.0e

-13

02.00e+134.00e+136.00e+138.00e+131.00e+14

square

02.

0e-0

74.

0e-0

76.

0e-0

7

0 20000004000000600000080000001.00e+07

identity

02.0e

-04

4.0e

-04

6.0e

-04

8.0e

-04

.001

500 10001500200025003000

sqrt0

.2.4

.6

12 13 14 15 16

log

050

010

00

-.002 -.0015 -.001 -.0005 0

1/sqrt

02.0e

+05

4.0e

+05

6.0e

+05

8.0e

+05

-5.00e-06-4.00e-06-3.00e-06-2.00e-06-1.00e-06 0

inverse

01.0e

+11

2.0e

+11

3.0e

+11

4.0e

+11

-2.50e-11-2.00e-11-1.50e-11-1.00e-11-5.00e-12 0

1/square

02.0e

+16

4.0e

+16

6.0e

+16

8.0e

+16

1.0e

+17

-1.00e-16 -5.00e-17 0

1/cubic

Den

sity

Total household incomeHistograms by transformation

Appendix iii

The residual versus dependence on off-farm income plot

1

2

34

5

6

7

8

9

10

11

12

13

14

15

161718

19

20

21

22 23

24

25

26

27

28

29

30

31323334

353637

38

39

4041

4243

44

45

46

47

48

49

5051

52 5354

5556

57

5859

60

61

6263

64

6566

676869

70

71

72

73

74

75 76

7778

79

80

81

82

838485

86

8788

89

90

91 92

93

94

9596

97

9899

100

101

102103

104

105

106

107

108109110111112

113

114115

116

117118119

120

121

122

123124

125

126

127128

129

130

131132133

134

135

136

137138

139

140

141

142

143

144145

146

147

148

149

150

-.4-.2

0.2

.4R

esid

uals

0 .2 .4 .6 .8 1Dependance on off farm income

63

Appendix iv

Weighted residuals versus fitted values for dependence on off-farm income

-200

0-1

000

010

0020

00w

ls re

sidu

als

0 .5 1Fitted values

64

Appendix v

Gini coefficient for different strata

THI | 1.0e+06 9.6e+05 1.4e+06 0.9267 0.8468 0.4389 1.2e+05 544.17%--------|---------------------------------------------------------------------variable| Mean Median MeanDif CV CD Gini SEMean % Dev. | Mean Dev. about Max.

Measures of Absolute and Relative Dispersion (or Inequality):. rspread THI

THI | 1.5e+06 1.4e+06 2.1e+06 0.9561 0.9389 0.4683 4.0e+05 356.27%--------|---------------------------------------------------------------------variable| Mean Median MeanDif CV CD Gini SEMean % Dev. | Mean Dev. about Max.

Measures of Absolute and Relative Dispersion (or Inequality):. rspread THI if stratum==4, gr

THI | 1.3e+06 1.1e+06 1.6e+06 1.1233 1.2735 0.5347 2.7e+05 434.91%--------|---------------------------------------------------------------------variable| Mean Median MeanDif CV CD Gini SEMean % Dev. | Mean Dev. about Max.

Measures of Absolute and Relative Dispersion (or Inequality):. rspread THI if stratum==3, gr

THI | 5.7e+05 5.7e+05 8.3e+05 0.6160 0.4733 0.3358 1.2e+05 178.79%--------|---------------------------------------------------------------------variable| Mean Median MeanDif CV CD Gini SEMean % Dev. | Mean Dev. about Max.

Measures of Absolute and Relative Dispersion (or Inequality):. rspread THI if stratum==2, gr

THI | 8.2e+05 7.8e+05 1.1e+06 0.6386 0.6203 0.3508 1.6e+05 174.68%--------|---------------------------------------------------------------------variable| Mean Median MeanDif CV CD Gini SEMean % Dev. | Mean Dev. about Max.

Measures of Absolute and Relative Dispersion (or Inequality):. rspread THI if stratum==1, gr

.

THP | 1.5e+06 1.4e+06 2.1e+06 0.9605 0.9386 0.4698 4.0e+05 358.19%--------|---------------------------------------------------------------------variable| Mean Median MeanDif CV CD Gini SEMean % Dev. | Mean Dev. about Max.

Measures of Absolute and Relative Dispersion (or Inequality):. rspread THP if stratum==4, gr

65

Appendix vi Weighted least square regression for diversity index of total income

_cons -.4669643 .1066008 -4.38 0.000 -.6777465 -.2561821 DOFI .517854 .1456142 3.56 0.001 .2299305 .8057775 lgTHI .0372622 .0086439 4.31 0.000 .0201707 .0543538 hheduc -.0020573 .0036864 -0.56 0.578 -.0093464 .0052319 aeu .0033221 .0048914 0.68 0.498 -.0063496 .0129938 CWratio -.057647 .0164925 -3.50 0.001 -.0902576 -.0250363 ceu .0671801 .01849 3.63 0.000 .0306198 .1037405 total_land .0158138 .0045767 3.46 0.001 .0067643 .0248634 market .0040769 .0016522 2.47 0.015 .0008099 .0073438 _Ioccupn_2 -.0146203 .0815562 -0.18 0.858 -.1758817 .1466411 age1 -.0017368 .0009263 -1.87 0.063 -.0035683 .0000948 _IHHHsex_2 .1062808 .0482166 2.20 0.029 .0109421 .2016196 DIITI Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total .134870379 149 .00090517 Root MSE = .02202 Adj R-squared = 0.4645 Residual .066893347 138 .000484734 R-squared = 0.5040 Model .067977032 11 .00617973 Prob > F = 0.0000 F( 11, 138) = 12.75 Source SS df MS Number of obs = 150

(sum of wgt is 7.5145e+05)

WLS regression - type: proportional to xb^2

i.occupn _Ioccupn_1-2 (naturally coded; _Ioccupn_1 omitted)i.HHHsex _IHHHsex_1-2 (naturally coded; _IHHHsex_1 omitted)> I, wvar(DOFI) type(xb2) noconst gr. xi:wls0 DIITI i.HHHsex age1 i.occupn market total_land ceu CWratio aeu hheduc lgTHI DO

66

Appendix vii OLS regression for log total household income

_cons 12.49586 .4766279 26.22 0.000 11.55318 13.43855 hheduc .0365717 .019 1.92 0.056 -.001007 .0741503 _Istratum_4 .5904426 .3351922 1.76 0.080 -.0725092 1.253394 _Istratum_3 -.2019163 .236383 -0.85 0.395 -.6694406 .2656081 _Istratum_2 -.0050519 .1380349 -0.04 0.971 -.2780609 .2679572 aeu .0976905 .0324385 3.01 0.003 .0335328 .1618482 DIITI -.0017634 .3270748 -0.01 0.996 -.6486603 .6451335 CWratio .0472197 .0662095 0.71 0.477 -.0837312 .1781707 DPARK -18.45598 9.513125 -1.94 0.054 -37.27128 .3593225 DOFI 1.111351 .2202972 5.04 0.000 .6756418 1.547061 ceu .0984567 .0415064 2.37 0.019 .0163643 .1805491 total_land .0693661 .0158081 4.39 0.000 .0381005 .1006317 market .0102064 .0206955 0.49 0.623 -.0307257 .0511384 _Ioccupn_2 .2550081 .1976572 1.29 0.199 -.1359234 .6459397 age1 .0021298 .0041718 0.51 0.611 -.0061213 .0103809 _IHHHsex_2 -.2677831 .1486845 -1.80 0.074 -.5618551 .0262889 lgTHI Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 99.9154846 149 .670573722 Root MSE = .561 Adj R-squared = 0.5307 Residual 42.1731219 134 .31472479 R-squared = 0.5779 Model 57.7423627 15 3.84949085 Prob > F = 0.0000 F( 15, 134) = 12.23 Source SS df MS Number of obs = 150

i.stratum _Istratum_1-4 (naturally coded; _Istratum_1 omitted)i.occupn _Ioccupn_1-2 (naturally coded; _Ioccupn_1 omitted)i.HHHsex _IHHHsex_1-2 (naturally coded; _IHHHsex_1 omitted)> i.stratum hheduc. xi:reg lgTHI i.HHHsex age1 i.occupn market total_land ceu DOFI DPARK CWratio DIITI ae

67

Appendix viii Questionnaire This is research being done as part of my studies in Msc Management of Natural Resources and sustainable Agriculture at the Norwegian University of Life Sciences in Aas, Norway. It seeks to assess the effect that BINP has on local people’s livelihoods. You have been randomly chosen from this community to be a respondent. Confidentiality is key in the survey and for this reason you will not be asked for any indentifying information. While there is no wrong and right answer, I will be grateful if provided with honest answers. 1.1 How far is your homestead from the park boundary? ................................................. Basic household information 1.2 1.3 1.4 1.5 1.6 1.7 HH members

Sex Age Relationship with HH head

Education level

Primary occupation

Other occupation(s)

1 2 3 4 5 6 7 8 9 10 11 12 1.8 What is the distance between your homestead and the nearest..?

a) Primary sch ……….…b) Secondary sch……………… c) Tertiary sch ………… 1.9 What is the distance between your homestead and the nearest..?

a) Hospital …………. b) Dispensary………………….. c) Local clinic …………… 1.10 What is the distance between your homestead and the nearest market place………………………….… 1.11 What are the walls of the main house made of? (tick appropriate)

a) Brick walls b) Mud and wattle walls

2.0 Land ownership and farming 2.1 Does this household own land in this village? Y /N 2.2 How many parcels of land do you own?……………………

68

Land particulars (all land currently used for agricultural production) Description Parcel 1 Parcel 2 Parcel 3 Parcel 4 Parcel 5 Parcel 6 Size of parcel (ha)

Year acquired

Mode of

acquisition*

Land

quality#

Land title *Acquisition codes: 1= purchase, 2= leased, 3= sharecropping, 4= borrowed, 5= inherited/gift, 6= specify any other # Land quality codes 1= fertile 2= medium 3= poor 3.0 Livestock, poultry assets 3.1 3.2 Livestock type Number owned Units sold last 12

months Price/unit

Cows Sheep Goats Oxen Chicken Pigs Rabbits Ducks 4.0 Livestock, poultry products 4.1 4.2 Product Unit Quantity for

own use Quantity sold last 12 months

Unit cost

Milk products

Eggs Hides Animal manure

Others specify

69

5.0 Details of agricultural production 5.1 What land size do you use for crop production?............................................... 5.2 5.3 5.4 5.5 Crop type Quantity

harvested kg/yr

Quantity consumed by HH kg/yr

Quantity sold kg/yr

Unit price (Ushs)

Maize Beans Irish potatoes

Sweet potatoes

Coffee Cassava G. nuts Banana Sorghum Millet Wheat Tea Peas Yams 5.8 What crop production costs did you incur in the last 12 months? Type of input

Unit of measurement

Quantity Unit price (Ugsh)

Total costs incurred

Fertilizer Seed Pesticide Labour Land rent

What livestock production costs did you incur in the last 12 months?

Type of input Unit of measurement

Quantity Unit price (Ugsh)

Total costs incurred

Medicine Fodder Concentrates Pesticides

70

6.0 Park/forest products 6.1 Do you or any members of the household collect products from the park? Y/N 6.2 If yes, do you face any problems collecting these products from the park?....................................................................................................................................................................................................................................................................................... Could you recall the amounts of forest products and how they have been utilized? 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10

Item Local unit

Quantity/ month from park

Quantity/ month out of park

Time (hours) spent to and from collecting

Quantity used monthly

Quantity sold monthly

Price/unit

Included in RUA? Amount allowed

Rank#

Firewood Bundles Fodder Bundles Timber M3 Bamboo stems

Bundles

Honey Liters Rope stems Bundles Vegetables Baskets Salt lick kgs Charcoal Bags Medicinal plants

Bags

Clay Heaps Thatching grass

Bundles

Wild meat kgs Building poles

Sticks

Rattan Bundles Stones/minerals

Heaps

Fruits Baskets Mushrooms Bags Others specify

# How would you rank the above products in order of importance (1 being the most important)

71

72

6.10 What is the most important constrain in accessing park resources? ................................................................................................................................................................................................................................................................................................ 6.11 Non farm related income sources Activity Income /month Costs /month Net income Remittances Retail trading Salary employment Brick making Arts and crafts Pitsawing Honey collection Mining Fishing

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