dependence on environmental income by …dependence on environmental income by households around...
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Dependence on environmental income by households around Rwenzori Mountain National Park, Western Uganda
David Mwesigye Tumusiime
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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 programmes) and assignments.
The Noragric Master theses are the final theses submitted by students in order to fulfil
the requirements under the Noragric Master programme “Management of Natural
Resources and Sustainable Agriculture” (MNRSA), “Development Studies” and other
Master programmes.
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.
© David Mwesigye Tumusiime, May 2006 [email protected] 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
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DECLARATION
I, David Mwesigye Tumusiime declare that this is my original work, and the sources
of materials are acknowledged. This work has not been submitted before for any
academic award.
Signature…………………
Date………………………
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ACKNOWLEDGEMENT
Sincere thanks go to NORAD for funding my study and fieldwork. My supervisor Prof. Pål Vedeld, thank you for being such a great teacher. I particularly admire and appreciate the way we have systematically moved this work from one level to the next. It has been an enjoyable learning experience. To Liv and Ingeborg, I will always remember your willingness to help me whenever I popped in. I thank my supervisor in Uganda, Prof. William Gombya-Ssembajjwe for the many useful suggestions and practical assistance in the field. Special thanks go to my teachers and colleagues at the Faculty of Forestry who have honestly been there for me. My hearty thanks to Ronnie for introducing me to stata. I thank Svein Erik of WWF Norway for introducing to WWF Uganda office and for his continued support in Norway. WWF Uganda office is acknowledged for my orientation in the study area Sincere thanks to my research assistants Vincent, Seth and Masereka, who endured long walks in the rough terrain of the Rwenzoris. The friendship of Teshome, Justine, Ashaba, Roselyn, Daniel, Steven, Maria, Mzee, Amigo, Aslaug, Amiga, Esther, Trine, Antenne, Camilla and my classmates has been exceptional. Friends, I do appreciate. Meeting you here in Norway has been a sweet bonus. Also, special mention is here made of Arijol, Chipo, Ivan, Frank, Raf, Oscar, Eddie, the Solos, Sam plus Becky, Bella, Naome, and Peggy. To my ever loving parents, Mr. and Mrs. Mwesigye, may the good Lord bless you in a special way!
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ABSTRACT
With the transition of 6 major forest reserves in Uganda to National parks, several million people were deprived of access to forest resources. This study analyses one of the areas and how people at present make a living partly based on environmental resources. This study was carried out in communities surrounding Rwenzori National Park in Western Uganda. A major motivation was that while other National parks in Uganda have made agreements with their neighbours to sustainably utilise Park resources, Rwenzori has not and illegal use of park resources is rife. The research sought to examine household dependence on park environmental incomes through household survey. The interviews were augmented by focus group discussions. Household livelihoods are assessed and factors constraining livelihoods mapped. Dependency on environmental income is measured by share of total income that is environmental in origin. The two steps method of Heckman is used to estimate factors influencing dependency on park environmental income. The relationship between park and non-park environmental income is investigated using simple linear regression. Effects of environmental incomes on income inequality are estimated using Gini coefficient and Atkinson index and Forster-Greer-Thorbecke poverty measures are used to estimate the effect on poverty. Results indicate a general low access to assets. Households pursue a wide range of activities, but agriculture contributes most (70%) to total incomes. Off-farm income is low due to lack of opportunities. On average environmental income contributes 18.6% to total income; and a third of this income comes from the national park contributes much more to the welfare of the poor. The park income reduces income inequality, incidence, depth and severity of poverty by 2.8, 3.4, 4.7, and 3.6 percentage points, respectively. Households’ persistent illegal access to park resources despite heavy penalties is indicative of the central role the resources play in their livelihood. Increased law enforcement alone is unlikely to protect the park because it provides no alternatives. Provision of opportunities for off-farm employment and signing of resource use agreements will provide for better planned and managed use of the park resources, directly benefiting the people and the park. It is important that the local peoples get involved and that their rights are respected.
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TABLE OF CONTENTS
DECLARATION .................................................................................................................... II
ACKNOWLEDGEMENT ....................................................................................................III
ABSTRACT ........................................................................................................................... IV
ACRONYMS AND ABBREVIATIONS ............................................................................. IX
CHAPTER I: INTRODUCTION........................................................................................... 1
1.1 BACKGROUND .......................................................................................................... 1 1.2 RESEARCH OBJECTIVES AND QUESTIONS ................................................................. 4 1.3 JUSTIFICATION.......................................................................................................... 5 1.4 THESIS STRUCTURE .................................................................................................. 6
CHAPTER II: CONCEPTUAL FRAMEWORK AND LITERATURE REVIEW.......... 7
2.1 MANAGEMENT OF RWENZORI MOUNTAIN NATIONAL PARK................................... 7 2.1.1 Management under the Forest Department............................................................. 7 2.1.2 Management under Uganda Wildlife Authority................................................... 8
2.2 CONCEPTUAL FRAMEWORK ..................................................................................... 9 2.3 RURAL LIVELIHOODS ............................................................................................. 11
2.3.1 Access to assets.................................................................................................. 12 2.3.2 Livelihood activities........................................................................................... 12 2.3.3 Income contribution from different livelihood activities ................................... 13
2.4 HOUSEHOLD CONSTRAINTS .................................................................................... 14 2.4.1 Main constraints ................................................................................................ 14 2.4.2 Costs related to living close to the park ............................................................ 14
2.5 DEPENDENCY ON ENVIRONMENTAL INCOME ......................................................... 16 2.5.1 Total household income..................................................................................... 16 2.5.2 Environmental incomes and total household incomes....................................... 16 2.5.3 Household internal factors impacting on collection of forest products ............ 17 2.5.4 Household external factors................................................................................ 20
2.6 DISTRIBUTION OF PARK INCOME ............................................................................ 22 2.6.1 Wealth categories .............................................................................................. 22 2.6.2 Location ............................................................................................................. 23 2.6.3 Gender ............................................................................................................... 23
2.7 IMPORTANCE OF PARK PRODUCTS.......................................................................... 23
CHAPTER III: STUDY AREA AND METHODS............................................................. 26
3.1 STUDY AREA.................................................................................................................. 26 3.1.1 Physical and climatic conditions ....................................................................... 26 3.1.2 Flora and fauna ................................................................................................. 26 3.1.3 The People ......................................................................................................... 26
3.2 DATA COLLECTION, HANDLING AND ESTIMATION PROCEDURES ........................... 28 3.3 EMPIRICAL MODELS ............................................................................................... 29
3.3.1 Collection of park products ............................................................................... 29 3.3.2 Extent of collection ................................................................................................ 30
3.4 PARK INCOME AND INCOME INEQUALITY AND POVERTY....................................... 31 3.5 MEASUREMENT OF THE DEPENDENT VARIABLES................................................... 33
3.5.1 Environmental income....................................................................................... 33 3.5.2 Absolute and relative environmental income..................................................... 34 3.5.3 Income from agriculture .................................................................................... 34 3.5.4 Income from off-farm activities ......................................................................... 34
3.6 DEFINITION AND MEASUREMENT OF THE INDEPENDENT VARIABLES .................... 34 3.6.1 Household internal factors ................................................................................ 35 3.6.2 Household external factors................................................................................ 38
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3.6.3 Proxies and their expected signs ........................................................................... 39 3.7 DATA ANALYSIS ..................................................................................................... 40
3.7.1 Present livelihoods of communities adjacent RMNP......................................... 41 3.7.2 Household constraints ....................................................................................... 41 3.7.3 Estimating household dependency on environmental income ........................... 41 3.7.4 Estimating dependency on park environmental income .................................... 41 3.7.5 Relationship between park and non-park environmental income...................... 42 3.7.6 Effects of park income on income inequality and poverty ................................. 42 3.8.1 Representativity ................................................................................................. 42 3.8.2 Validity and reliability ........................................................................................... 43
CHAPTER IV: RESULTS AND DISCUSSIONS .............................................................. 44
4.1 PRESENT LIVELIHOODS OF THE COMMUNITIES ADJACENT RMNP................................ 44 4.1.1 Household access to assets .................................................................................... 44 4.1.2 Household livelihood activities.............................................................................. 52 4.1.3 Incomes from the livelihood activities ................................................................... 54 4.1.4 Relationship between household income and assets.......................................... 56
4.2 HOUSEHOLD CONSTRAINTS TO IMPROVED LIVELIHOOD ............................................... 64 4.2.1 Main constraints to improved livelihoods ............................................................. 65 4.2.2 Constraints associated with living close to the national park ........................... 68
4.3 TOTAL ENVIRONMENTAL INCOME.......................................................................... 70 4.3.1 Contribution of environmental income to total household income.................... 70 4.3.2 Effect of household income on dependency on environmental income.............. 71
4.4 A MORE DETAILED ANALYSIS OF DEPENDENCE ON PARK ENVIRONMENTAL INCOME 73
4.4.1 Modelling dependency on park income ............................................................. 73 4.4.1 Distribution pattern of park income ...................................................................... 80 4.3.2 Gender differentiation of collection of park products ........................................... 82
4.5 RELATIONSHIP BETWEEN PARK AND NON-PARK ENVIRONMENTAL INCOMES ....... 86 4.6 ENVIRONMENTAL INCOME, POVERTY AND INCOME INEQUALITY .......................... 87
4.6.1 Effect on poverty ................................................................................................ 87 4.6.2 Effect on income inequality ............................................................................... 88
CHAPTER V: CONCLUSIONS AND POLICY RELATED SUGGESTIONS .............. 90
5.1 CONCLUSIONS ............................................................................................................ 90 5.2 POLICY SUGGESTIONS ............................................................................................ 93
REFERENCES ...................................................................................................................... 96
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LIST OF TABLES
Table 1: OECD Adult equivalency scales ...................................................................36 Table 2: Livestock conversion factors .........................................................................37 Table 3: Proxies used in the regression models and their expected signs ...................39 Table 4: Average land access by district, survey, Western Uganda 2005 ...................45 Table 5: Livestock keeping by communities around RMNP (Std. Err. in parentheses), survey, Western Uganda 2005 .....................................................................................46 Table 6: Correlation between some proxies of access to assets, survey, Western Uganda, 2005 ...............................................................................................................51 Table 7: Reported household head occupations, survey, Western Uganda 2005 ........52 Table 8: Average share contribution of livelihood activities to total household income, survey, Western Uganda 2005 .....................................................................................54 Table 9: Sources of agricultural income, survey, Western Uganda 2005....................54 Table 10: Determinants of household per capita income, survey, Western Uganda 2005..............................................................................................................................57 Table 11: Household factors by wealth category, survey, Western Uganda 2005 ......63 Table 12: Techniques used to fight crop raiding, survey, Western Uganda 2005 .......69 Table 13: Factors determining collection of forest products, survey, Western Uganda, 2005..............................................................................................................................74 Table 14: Sources of household park income, survey, Western Uganda 2005............83 Table 15: Collection of park products by location, survey, Western Uganda 2005 ....84 Table 16: Comparison of poverty indices with and without environmental income, survey, Western Uganda 2005 .....................................................................................88 Table 17: Comparison of income inequality with and without environmental income, survey, Western Uganda 2005 .....................................................................................89
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LIST OF FIGURES
Figure 1: A modified household economic model (Based on Vedeld, 1995)..............10 Figure 2 Map of Uganda showing Rwenzori Mountain National Park and study area27 Figure 3: Different forms of collateral reportedly used to obtain credit, survey, Western Uganda 2005..................................................................................................47 Figure 4: Percentage membership to associations, survey, Western Uganda 2005.....49 Figure 5: Differences in household dependence on income sources, survey, Western Uganda 2005 ................................................................................................................64 Figure 6: Relationship between total environmental income and total household income, survey, Western Uganda 2005 .......................................................................71 Figure 7: The relationship between relative environmental income and household total income, survey, Western Uganda 2005 .......................................................................72 Figure 8: Relationship between total park income and total household non-park income, survey, Western Uganda 2005 .......................................................................81 Figure 9: Relationship between relative park income and total household income, survey, Western Uganda 2005 .....................................................................................82 Figure 10: Park income by income type for locations, survey, Western Uganda 2005......................................................................................................................................85 Figure 11: Relationship between park and non-park environmental incomes, survey, Western Uganda 2005..................................................................................................86
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ACRONYMS AND ABBREVIATIONS
CBNRM Community Based Natural Resource Management
CFR Central Forest Reserve
DRC Democratic Republic of Congo
FD Forestry Department
Fpc Finite population correction
OECD Organisation for Economic Co-operation and Development
PSU Primary sampling unit
RMCEMP Rwenzori Mountain Conservation and Environmental Management
Project
RMNP Rwenzori Mountain National Park
TLU Tropical Livestock Unit
UBOS Uganda National Bureau of Statistics
UNESCO United Nations Educational, Scientific and Cultural Organisation
UWA Uganda Wildlife Authority
WWF Wild Wide Fund for Nature
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CHAPTER I: INTRODUCTION
1.1 Background
Two reinforcing arguments are commonly advanced about communities living
adjacent to forested areas. The first is that access to forest products is a primary
source of livelihood that provides cash and/or subsistence income to residents of rural
households (Cavendish, 2003; Vedeld et al., 2004). The second is that park income is
important to poor households and may reduce income disparities at micro levels
(Fisher, 2002; Katto, 2004); though this rarely has a comparative advantage for
reducing poverty, particularly at national levels (Wunder, 2001). However, park
incomes provide micro level benefits depending on how much products rural
households can access. Therefore creating conducive frameworks that offer rural
households access to park products may help generate higher revenues and create
stronger incentives for communities to take on increasing responsibility for park and/
or forest management. This may further promote better maintenance and efficient
utilisation of park resources with positive impacts on both intra and inter-generational
equity and resource sustainability for the future generations.
Access to park forest products has over time been changing mostly in line with
international changes in ideas regarding conservation. For example, the belief that
biodiversity was threatened by consumptive uses ushered in attempts to separate
people from areas rich in biodiversity. This approach to conservation is known as
“fortress conservation” and dominated much of the 20th century thinking (Hutton et
al., 2005). The hegemony of fortress conservation also led to a management paradigm
shift that in many cases led to elevation of the protection status of forested areas to
national parks (Bruner et al., 2001; Brockington & Schmidt-Soltau, 2004; Hutton et
al., 2005). This reduced local collection of what became park products as collection of
several previously accessible products suddenly became illegal (cf. Bruner et al.,
2001; Vedeld, 2002).
In Uganda, Rwenzori Mountain National Park (referred to as RMNP, hereafter) is one
of six major forest reserves that were converted into national parks in 1993. Though
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this could be justifiable as these were significant bastions of biodiversity threatened
by anthropogenic influences (Plumptre et al., 2003), it is almost ironical that the
conversion took place at a time when the dominant approach of fortress conservation
was no longer hegemonic (Adams & Hulme, 2001), and elsewhere efforts were
increasingly being made to involve local people (Hutton et. al., 2005). RMNP is
surrounded by communities of high population density approximated at (150-430
persons/km2); while the three districts of Kabarole, Kasese and Bundibugyo in which
the park is located, have been experiencing high annual population growth rates
estimated at 1.6, 3.8 and 5.2 respectively (UBOS, 2002). This has resulted in high
demand for park resources, threatening one of the continent’s most valuable natural
heritages (RMCEMP, 2003). Under such circumstances, fortress conservation
typically prescribes minimisation of all forms of human impact. This is exactly what
happened when the area was declared a national park. Management became more
restrictive on resource use and emphasised non-consumptive uses (Ditiro, 2003).
The creation of national parks from forest reserves in Uganda in 1991-1993 was a
return to fortress conservation. It happened at a time when the mainstream had
accepted community conservation, established by such processes as the World
Conservation Strategies and acknowledged by the 1987 publication of our common
future by the World Commission on Environment and Development (Salomons,
2000). Community Based Natural Resource Management (CBNRM) had become
popular in southern Africa in the 1980s and 1990s. Notable here is the popular
CAMPFIRE in Zimbabwe (Adams & Hulme, 2001). As Wilshusen et al. (2002) and
Hutton et al. (2005) show, a return to the fortress approach is now considered
necessary by actors such as conservation biologists and sections of the donor
community, especially the US Agency for International Development (USAID)
(Hutton et al., 2005). USAID support for the return to fortress conservation is evident
in its role in the conversion of Uganda’s forest reserves to national parks (Ditiro,
2003).
Despite the return to fortress conservation in Uganda, in some national parks such as
the Mt. Elgon National park, collaborative resource agreements that allow some
communities access to some park products have been made and seen to be beneficial
(Katto, 2004; Namugwanya, 2005). RMNP however has no such agreements, though
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efforts have been made to benefit the local people. A case in point is the Rwenzori
Mountains Conservation and Environmental Management Project (RMCEMP),
funded by USAID in its earlier phases, but now funded by NORAD and implemented
by the World Wide Fund for Nature (WWF). The project started in 1992 and has
several targets. Notable among them is reducing pressure on the park by helping
sustain livelihoods of adjacent communities through alternative means such as soil
conservation, agro forestry and conservation education.
However, efforts towards alternative livelihoods, as suggested by RMCEMP, often do
not achieve much because they do not usually match the local peoples’ needs and
expectations. The alternatives suggested should address those people that have been
collecting park products and also provide substitutes that are considered important by
the concerned. Parks resources, though often obtained illegally are primary sources of
livelihood (Godoy et al., 2000) providing in some extreme cases up to 99% of the
communities’ requirements for some products (Stræde et al., 2002). Generation of
alternative livelihood sources is thus often necessary to reduce park dependence and
resource use conflicts. This, however, requires an understanding of the factors
influencing collection of the particular park products and the micro level importance
of the income in reducing income inequality and poverty. The Rwenzori Mountain
National Park was added to UNESCO’s World Heritage List in 1994. This is
testimony to the area’s international importance. The park is “one of continent’s most
valuable natural heritages whose breathe taking scenic beauty, exceptional scientific
value and inestimable ecological and economic worth spans local, national and
international boundaries” (RMNP project proposal, 2003). That loss of this park’s
biodiversity is a grave problem thus requires little justification but “protection-by-
any-means-necessary” at best gives limited short-term benefits (Brechin et al., 2002).
The importance of the park resources to the surrounding communities therefore needs
to be appreciated and should be factored in the making of RMNP conservation
policies. Specifically, not much analytical work has been done to quantify the local
importance of the park resources to the adjacent communities. Further, there is a
dearth of studies in Uganda detailing in social-economic terms the behavioural
underpinnings that compel rural households to depend on park and forest resources
and the impact of dependence on park income to the general rural economy. Most of
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the previous research has broadly focussed on biological and ecological aspects
(Herberg, 1963; Howard, 1991; Butynski, 1992; Lush, 1993; and Plumptre et al.,
2003). On the other hand, most of the socio-economic studies were conducted before
the area was converted to a national park and mostly took the form of inquiries and
recommendations for park establishment (Yeoman et al., 1990). Little is known about
the current livelihood strategies of the communities around the park, how much park
income is obtained, by who, how important the income is to the local economy and
what constraints the people face.
The resource use agreements and other collaborative schemes that have been made in
many other national parks are still missing in RMNP. This could partly be due to the
disruption of management by rebel activities in the area. The rebel activities that
started in mid nineties led to park closure in 1999 and its inscription on the list of
world heritage in danger in the same year. Following the opening of the park in 2001,
RMCEMP has resumed its operations with an objective that conservation of the
Rwenzori Mountains ecosystem is enhanced and its biodiversity and water
catchment’s values are maintained in harmony with sustainable utilisation of
resources for the benefit of Uganda and the international communities (RMCEMP,
2003). A task such as this calls for, among others, first understanding the collection
and importance of collection of forest products from the park by adjacent
communities.
1.2 Research objectives and questions
The research objectives and questions are:
1. To estimate present livelihoods of communities adjacent to RMNP
i. What are households’ accesses to assets?
ii. Which livelihood activities do households pursue?
iii. How much does each activity contribute to households’ total income?
iv. What is the relationship between household income and access to assets?
2. To estimate household constraints
i. What constrains households’ attainment of better economic livelihoods?
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ii. What problems do households face as a result of living close to a national park?
3. To estimate household dependency on environmental income
i. What share of the income is environmental income?
ii. How much of the environmental income is park environmental income?
iii. How does dependency on environmental income vary with household income?
4. To estimate dependency on park environmental income
i. Which factors influence household dependency on park environmental income?
ii. What is the distribution pattern of the forest income among different groups of
households?
5. To establish the relationship between park and non-park environmental
income
i. Does park income substitute or complement non-park environmental income?
6. To estimate the effect of park income on income inequality and poverty
i. Do park incomes diminish income inequality?
ii. How do park incomes impact on poverty;
a) Incidence?
a) Severity?
b) Depth?
1.3 Justification
It is increasingly accepted that many biodiversity hotspots are also important to local
communities’ livelihoods. Given the unique biodiversity of RMNP, its conservation
has benefits beyond national boundaries. However, as a source of park income,
RMNP is important to local development. Both conservationist and development
work around RMNP thus needs a clearer understanding of the collection and
importance of the park products to adjacent communities. This is particularly so,
given that conservation is a social and political process (Brechin et al., 2002) and
development programmes are better when combined with conservation (Sanderson
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and Redford, 2003). The study thus helps to visualise the impacts of the establishment
of parks on rural livelihoods, as a basis for making policies for conservation and
development of the area. It also feeds into current debates such as the one on effects
of biodiversity conservation on local economies (e.g. Shylajan and Mythili, 2003;
Brockington & Schmidt-Soltau, 2004).
Potentially, given that no resource use agreements have been made in RMNP (despite
earlier efforts), the study may help guide future negotiations to establish these
agreements. It could also provide a basis for comparison of the effects of resource use
agreements on dependence on park incomes; by either comparing the observed
dependence with dependence in areas with resource use agreements or comparing the
observed dependence with future dependence when resource use agreements are
signed.
1.4 Thesis structure
The thesis is sectioned into five chapters. Chapter 2 gives a brief on management of
RMNP under the forest department and Uganda Wildlife Authority, and reviews the
empirical and theoretical literature linking activity choice with household internal and
external factors. A modified household economic model forms the basis of the review.
Chapter three is divided into two sections; one describing the study area and the other,
the methodology. Chapter four presents a discussion of the major research findings,
while chapter five presents the conclusions and recommendations respectively.
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CHAPTER II: CONCEPTUAL FRAMEWORK AND LITERATURE REVIEW
This chapter gives a brief of the two management regimes of RMNP, a presentation of
the conceptual framework used in the thesis and a review of literature on the
importance of forest products.
2.1 Management of Rwenzori Mountain National Park
Like the other five forest reserves that were converted to national parks for the period
1991-1993 in Uganda, the historical management of RMNP can be separated into two
distinct phases; the management as a forest reserve under the Forest Department (FD),
and the management as a national park under Uganda Wildlife Authority (UWA).
2.1.1 Management under the Forest Department
Prior to 1991, RMNP was managed as a Central Forest Reserve (CFR), under the
jurisdiction of the FD. The FD managed CFRs based on forest policies and forest
management plans that were revised (where necessary) to reflect change(s) in
management objectives such as community-based management and resource
exploitation to meet demands of the increasing human population.
The first Forest policy was enacted in 1929, but revised in 1948, 1988 and 2001. The
1929 policy emphasised both exploitation and the environmental roles of forests.
Population increase led to the 1948 review that somewhat departed from conservation
by encouraging both agriculture and exploitation of forests. This was in response to
the increased human population that needed land for agriculture and forest products
such as timber to support the growing construction industry.
When Uganda became independent in 1962, it maintained and continued the 1948
policy, which it later reviewed in 1988. A revision in 1988 addressed the degradation
that had taken place in the turbulent years before 1986. It thus emphasised protective
forestry in opposition to the “double production” campaign that had encouraged
people to clear forests for agriculture. Using pedagogic tools, well planned forest
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exploitation was promoted and private land owners were encouraged to plant and
manage trees on their own lands. The current policy, enacted in 2001 (MWLE, 2001),
allows for among others, collaborative natural resource management; largely because
of the increasing importance attached to community conservation.
Until 1991, RMNP was a forest reserve and the management strategies thus changed
with changes in forest policies. However, when changes were made in forest policies,
communities adjacent to the forests were always granted access and; use of
commercially less important forest products (e.g. fire wood) and non-consumptive
uses such as recreation and concessional harvesting of commercial products such as
timber. When management of the forest was transferred to UWA changes in access
and use occurred.
2.1.2 Management under Uganda Wildlife Authority
The transition from forest reserve to national park raised the conservation status of the
area, and exploitative use of the park resources was declared illegal. The use of park
roads that connect different villages was also prohibited. Further, people were denied
access to areas of cultural values such as hunters’ shrines and human burial sites. As
with other converted forest reserves no compensation was given or considered (Ditiro,
2003).
UWA was established in 1986 as a governmental parastatal to manage game reserves.
The Uganda National Park, a predecessor to UWA, used a rather militaristic approach
that alienated local people from the adjacent resources. With the formation of UWA,
efforts were made to reduce the confrontational approaches. Efforts have been made
to include people in the management of national parks for example the establishment
of resource-use zones in Bwindi Impenetrable National Park and the resource user
groups in Mt. Elgon National Park. However, national parks are still more restrictive
and local people cannot easily access them as it previously was with forest reserves
(Ditito, 2003).
Management under UWA has so far had low levels of community participation.
However, as a step towards addressing the negative outcomes to communities of
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converting the forest reserve into a national park, Rwenzori Mountains Conservation
and Development Project was established. It can be categorised in three phases. That
is, phase I (1990-1994), phase II (1995-1998), and phase III (2004-to date). It aims at
enhancing conservation of RMNP biodiversity and sustainable use of RMNP
resources to benefit Ugandans and the international community (RMCEMP, 2003).
As RMCEMP (2004) notes, under UWA’s management, the importance of the park as
a natural heritage was recognised and it was inscribed on the UNESCO World
Heritage List in 1994. However, occupation of the park by rebels in 1997 halted
conservation work and, this combined with pressures from the increasing population
led to declaration of the area as a ‘World Heritage in Danger’ in 1999 . The park was
however removed from the list five years later by the World Heritage Committee at its
28th
session on 4th July 2004 in Suzhou, China.
2.2 Conceptual framework
A household economic model (Fig. 1) is used to investigate collection of forest
products for different groups of households in the study area. A household is defined
by sharing the same abode and eating together. A household is an appropriate unit for
economic analysis because a household typically pools its resources, makes joint
decisions and shares incomes. Intra-household resource allocation is not taken into
account given the limitations in time and budget for data collection. A household
often has to make choice regarding which income generating activities to pursue.
Choice of combination activities to pursue is determined partly by the household’s
internal factors, mainly access to assets and partly by household external factors
(Barrett et al., 2001; Damite & Negatu, 2004). Assets can be categorised differently
(cf: Reardon & Vosti, 1995, Barrett & Reardon, 2000; Ellis, 2000). Here the assets are
categorised into: (1) physical; (2) human; (3) social; (4) financial; and (5) natural
capital (Figure 1). These assets and the activities to which they are put define the
household livelihood (Chambers & Conway, 1992; Ellis, 2000) and any factor
limiting the attainment of improved livelihood can be seen as a constraint. The
constraints may thus be limited access to various assets, adverse household external
factors that affect household ability to convert assets into outputs.
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Based on the decisions made, a household undertakes a given set of activities. These
define the household’s livelihood and following Ellis (2000) can thus be referred to as
livelihood activities. Often farm and non-farm activities are combined (Reardon,
1997; Arnold & Townson, 1998; Vedeld et al., 2004). For households in the vicinity
of forest resources, a considerable share of the latter is from collection of forest
products for subsistence and/or commercial use (Fearnside, 1989; Peters et al., 1989;
FAO, 1993; Vedeld et al., 2004).
Figure 1: A modified household economic model (Based on Vedeld, 1995).
The selected activities generate income for the household, in form of goods, and
services in kind or in cash. The income is either consumed to contribute to the
material wellbeing of the household or invested to enhance the household asset base
and future incomes. Through its consumption and/or investment, the income so
generated has implications beyond the economics of a single household. Which
EXTERNAL FACTORS Natural vagaries
Access to markets
Distance to national park
Ethnicity
ASSETS (CAPITAL)
Human Physical Social Financial Natural
Household
LIVELIHOOD ACTIVITIES
Crop and animal husbandry
Off-farm activities Collection of forest products
Consumption Investments/savings
Access to forest resources
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household gets how much income will impact on income distribution, poverty and has
policy implications.
For example, if an activity such as the collection of forest products from the park
contributes to the incomes of the poor members of a community, the income reduces
the concentration of incomes to a smaller section of the community (income
inequality). Also, the welfare of the recipients improves; they will be more able to
access a socially acceptable standard of nutrition, other necessities and will thus be
less poor. Such an activity will have reduced (1) the proportion of the poor (poverty
incidence), (2) the average distance separating the poor from the poverty line (poverty
depth) and (3) thus poverty severity in that community. All these have policy
implications for rural development, poverty alleviation and in case of park income, on
park dependence as well.
The next section reviews literature on livelihoods, collection, and importance of
collection of forest products from the national park. This is done within the
framework of the above conceptual framework.
2.3 Rural livelihoods
A livelihood is defined to consist of “… the assets (natural, physical, human, financial
and social capital), the activities, and the access to these (mediated by institutions and
social relations) that together determine the living gained by the individual” (Ellis,
2000). The activities generate corresponding incomes. For example, park activities
generate park income and the sum of the incomes from all the activities defines the
“living” gained by the individual or household. However, as shown in the above
framework, choice of activities depends on access to assets. Understanding activity
choice for any community thus demands first a look at access to assets, followed by
the activities to which the assets are put and then the incomes arising from the
selected activities.
12
2.3.1 Access to assets
Households’ access to assets can be expressed variously and despite the various
categorizations of assets (e.g. Reardon & Vosti, 1995, Barrett & Reardon, 2000; Ellis,
2000), the consensus is that households with better resource access typically have
more profitable choices of household activities to pursue. Able to access a variety of
income strategies and having a higher opportunity cost of time, households with better
access to assets may often disregard environmental incomes such as park income;
often considered “employment of the last resort” (Gunatilake, 1998; Angelsen and
Wunder, 2003).
Wealthier households both own productive assets (such as land, better quality labour)
and have better access to financial to markets, in particular financial markets
(Schwarze, 2004). They are thus able to invest in off-farm agricultural activities and
also often employ poor people on their farms. Poor households are on the other hand
“pushed” into selling their labour and pursuing activities that require little or no asset
possession. Often, these return low benefits. In this way, different households pursue
different diversification patterns.
2.3.2 Livelihood activities
Traditional rural development approaches have focused on agricultural growth,
ignoring the heterogeneity of rural households and livelihoods (Damite & Negatu,
2004). Rural households are however, typically heterogeneous, possess different sets
of assets and pursue a variety of livelihood strategies. They may be seen to seek to
maximise their utility given their resources at disposal and under particular constraints
associated with each livelihood activity. As a general rule, each household pursues at
least two livelihood activities, due to either “pull” or “push” factors (Ellis, 2000).
In many rural areas of developing countries, agriculture (more often in subsistence
form) is the primary livelihood activity. This is often combined for example with
either off-farm activities or dependence on forested areas. Although the latter does not
provide a major way out of poverty, it often attracts many households, particularly the
poor (Vedeld et al., 2004).
13
Forest product activities continue to generate incomes for many households in rural
areas (Arnold & Townson, 1998; Vedeld et al., 2004) though many continue to be
referred to as subsistence farmers (Reardon, 1997). A rural household is not
automatically equivalent to a farm household. Households typically have a diversified
portfolio of livelihood activities. The reasons for diversification are varied but as
Kinsey et al. (1998) noted, diversification can be an important means of addressing
the risk associated with agriculture for subsistence farmers.
2.3.3 Income contribution from different livelihood activities
Agricultural activities typically provide the bulk of household incomes for many rural
households. For example, households around Mt. Elgon national park earn an
estimated 65% of their incomes from agriculture (Katto, 2004). Off-farm activities
tend to be less important as they often require asset investment and many rural
households have poor access to assets. Forest activities are often important to such
households.
Forest activities provide timber and non-timber forest products, the latter are often the
most common, and in many instance the most important. The products are important
for; cash generation, construction (e.g. building poles), food security (e.g. honey and
mushrooms), and health (medicinal plants). For example, the National Wilderness
Area of Knuckles in Sri Lanka provides 16.2% worth of household total income,
through non wood forest products alone. And for the poorest group, this accounts for
an estimated 31% of total income (Gunatilake et al., 1993 in Stræde et al., 2002).
Around Mt. Elgon National Park, environmental incomes provide 19% of total
incomes, 80% of which is park income (Katto, 2004).
Literature indicates that total household income is but a pool of incomes from
different livelihood activities. On-farm agricultural activities are not the sole sources
of income for rural households. For example, from a 3 decades’ extensive analysis of
household surveys starting in 1970s, Reardon et al. (1998) noted that non-farm
incomes contribute considerably to average total incomes; Africa (42%), Latin
America (40%), and Asia (32%). A considerable share of these non-farm incomes has
14
been found to be forest income (Fearnside, 1989; Peters et al., 1989; FAO, 1993;
Vedeld et al., 2004).
2.4 Household constraints
Households typically face constraints to achieving better livelihoods. Households face
main constraints that are general in nature and are mainly external to the household
but for those close to forested areas such as national parks, some of the constraints are
often related to proximity to the forest. These constraints are often referred to as costs
for living close to the park.
2.4.1 Main constraints
Rural households are limited in their quest for better economic livelihoods by limited
access to assets. They lack access to land and when accessible it is often of poor
quality-either naturally such as the rocky areas not suitable for agriculture or has been
degraded- and/or fragmented. Land fragmentation results from land partitioning
through inheritance.
Households often lack access to financial services; the available human capital is
often of low quality because of the usual minimal investments in education. Some
areas are infested with pests and diseases and are not conducive for keeping livestock.
Other constraints emanate from factors external to the household. Such factors include
the occurrence of natural vagaries and various ecological conditions, legal institutions
that deny people access to some assets and insufficient access to markets and market
imperfections of various kinds.
2.4.2 Costs related to living close to the park
Long-term integrity of national parks, wherever they have been established, depends
on the essential support of rural adjacent communities (Tweheyo et al., 2005).
However, empirical evidence from field observations suggests that the existence of
national parks has substantial negative effects on local livelihoods. Communities
living close to the park face varied problems and opportunity costs of conservation.
These are important sources of people-park conflicts (Hill, 1997; Hill, 2000; and
15
Tweheyo et al., 2005). The problems can generally be categorised into (i) competing
land uses and (ii) human-wildlife conflicts. The costs are unevenly distributed across
households around the park and dent the support for conservation by the affected
households (Ferraro, 2001).
By virtue of its existence, the park occupies land that is consequently not available for
other uses such as agriculture and that the communities often would prefer. The
implications of this cost are exacerbated by restriction of local people to access the
park, which in their view is on their land. For example in a study by Mbogha (2000),
over a third of the respondents considered restricted access to RMNP as a major cause
of people-park conflicts.
Human-wildlife conflicts have been a cause of concern to conservation and have thus
been widely studied (e.g. Hill, 1997; Hill, 2000; and Tweheyo et al., 2005). The
conflicts usually arise from crop raiding and attack of humans and their livestock by
wild animals from the park. For example, in Uganda’s Budongo forest reserve,
wildlife conflicts stemming from crop raiding are reportedly undermining
conservation efforts (Tweheyo et al., 2005).
As such, there is a high opportunity cost for conservation. For example, Norton-
Griffiths and Southey (1995) estimate that Kenya annually foregoes 2.8% of her GDP
to conserve biodiversity through the use of protected areas such as national parks,
forests and nature reserves. Around Madagascar’s Ranomafana National Park, Ferraro
(2001) estimates the opportunity costs of conservation at $3.37 million. The estimated
costs per household in the four zones adjacent the park are estimated to be between
$353 to $1,316, which amounts to annual costs per average household of $19 to $70
over a sixty-year time period.
Because of costs such as the above, there are overwhelmingly negative attitudes
toward protected areas by adjacent communities that often live in abject poverty. Such
communities often strongly favour degazetting protected areas to allow for example
agricultural production for subsistence cultivation.
16
2.5 Dependency on environmental income
Rural households typically depend on the environment for products such as firewood,
fodder, vegetables and medicinal plants. Households that are adjacent to forested
areas such as national parks additionally collect products from the national park and
thus exhibit some dependency on both park and non-park environmental income.
Gazetting areas as national parks may not hinder adjacent communities from
collecting forest products from the park (Bruner et al., 2001). Such “biodiversity
hotspots” are also often social “hotbeds”’ (Brechin et al., 2002). People may continue
to collect park resources, even where buffer zones are in place, particularly because
alternative areas are inferior sources to national parks (Stræde et al., 2002). The park
income so obtained complements income from other sources to make up total
household income.
2.5.1 Total household income
Total household income is related to park income in two ways. In instances where
collection of park products needs investment such as buying concessions, employing
other persons to do the exploitation or purchase of equipment such as power saws for
cutting timber, it is typically households with good access to assets that will benefit
from the park income. In such cases, the extent of collection of park products might
increase with increase in total incomes.
On the other hand, if the accessible park products are mainly for subsistence, poorer
households will often be more involved in the collection of the products. The park
activities in this case are incomes of last resort, attractive to mostly those short of
options. And park dependence will increase with decrease in total household income.
Poor households are forced to include park activities in their diversification portfolio.
2.5.2 Environmental incomes and total household incomes
Every household in the vicinity of the national park makes a decision as whether to
collect or not to collect park products. Once a household has decided to collect forest
17
products, it has to decide on the extent of collection. For example, should forest
income provide most, much or just some of the income? Participants do not access
equal amounts of products. Collection intensity for various products and proportion
contributed to total income often varies between locations, communities, and also for
households within communities.
Collection and extent of collection of park products are influenced, among others, by
socio-economic and cultural factors (Stræde et al., 2002). Culturally, some tribes may
depend heavily on park products while others selectively use the products. In other
instances, some tribes may require small or large amounts of a given product, while
others may be completely disassociated from park products (e.g. immigrants from
non-forest environments). These and other factors affecting collection of park
products are considered next.
2.5.3 Household internal factors impacting on collection of forest products
The important household internal factors are in the form of access to assets. From the
modified household economic model presented in the framework, assets can be
categorised in form of capital as physical, human, social, financial and natural capital.
1. Physical capital
Physical capital is defined as assets such as land and livestock and other physical
assets owned by the household and that are useful in the process of production. Land
is the most important asset for agrarian communities. Their primary occupation is
agriculture which even at its very basic; needs land. Access to land thus influences
ability to farm. The lesser the land access, the more a household is pushed into other
livelihood activities. Thus households with little or no access to land are more likely
to engage in such activities as collection of forest products. Wealthy households, with
good access to land, may also diversify but for them it is often due to pull factors.
They are attracted by better paying alternatives unlike the households with poor
access to land that because of limited choice are “pushed” into alternatives of the last
resort.
18
Rural households in developing countries face risk and often need to quickly and
efficiently generate some cash to meet financial needs in order to mitigate such risks.
For this they need access to assets that can easily be converted to cash when
necessary. Near liquid assets such as livestock which can easily be converted into
cash may thus lead to more stable livelihoods. Lack of ability to accumulate livestock
as a form of livelihoods security or capital may lead to a greater dependence on other
resources such as forests.
2. Human capital
Human capital is embodied in people’s knowledge and skills such as labour,
education, age and gender. It influences needs and abilities to undertake particular
income activities. Labour is important in terms of its quality and quantity. Quantity
relates to the household size, gender and age composition; and quality to the skills
possessed, often developed through education and as they age. With more education,
households may access a broad variety of livelihood activities and disregard less
profitable activities such as the collection of forest products. Households with
sufficient access to labour can afford to allocate some labour units even into last resort
activities.
The influence of age on engaging in forest activities may be very variable but one
possible relationship between age and dependence on park activities is an inverted U-
shaped curve. The young may use the park in multiple ways, collect multiple products
and/or accumulate assets that are invested in other activities at later ages (Baikuntha,
2002). And, at old age, individuals may lack energy and/or time to carry out park
activities yet also young people may under look park activities and/or lack essential
skills (Vedeld et al., 2004). In general, different age groups are often found to use
forests in different ways (Cavendish, 1999).
Traditionally, men and women collect and control the use of different products. Forest
activities such as collection of firewood for cooking and medicinal plants combine
well with the females’ family and household tasks (Arnold, 2001) whereas activities
for strictly earning cash are often the domain of men. The sex of the household head
19
often shapes household activity choice (Murphy et al., 1997), particularly in forest
based activities. Female-headed households often depend on forest environmental
income. As Vedeld et al. (2004) note, this could be because in most cultures female-
headed households have smaller adult labour force as their husbands are often
working far away, if not divorced or widowed.
3. Social capital
Social capital is based on reciprocity within the community and between households.
It connects to social institutions; that directly or indirectly condition economic
decisions. Social capital can refer to vertical or horizontal relations (Coleman, 1988).
Vertical relations refer to links with people beyond the village level; for example
relations with politicians and park authorities. Horizontal relations are limited to links
with members of the same village.
The household’s access to social capital can be influenced by such factors as
ethnicity, duration of stay in the village and whether or not the household is an
immigrant. Links that facilitate pursuit of better paying activities may discourage
pursuit of park activities whereas links with park authorities may facilitate pursuit of
park activities.
4. Financial capital
Financial capital tends to be least available to the rural poor, and when available, it is
still inaccessible because the low return activities undertaken may not finance the
associated interest rates. With constrained access to credit, poor households have
limited ability to invest and may thus depend on such activities as collection of forest
products. They become forest dependent because they are poor (Vedeld et al., 2004),
and not the other way around.
Household total income can be seen as a proxy for household welfare. Whereas it may
be difficult to ascertain whether the poor or the rich are more forest dependent, the
poor often rely on forest products for subsistence whereas the rich use forests to
broaden their cash income bases. The role of wealth in influencing involvement in
collection of park products is important to the promotion of sustainable resource
utilisation and poverty reduction (Barham et al., 1999).
20
5. Natural capital
Natural capital consists of the stock of both resources and living systems from which
flows resource harvest and extraction, in addition to the essential ecosystem services.
Land and forest resources are two of the most popular natural capitals, though land is
often categorised a physical capital, as has been done here. Forests provide for both
consumptive and non consumptive uses, the former being the most important,
especially for its tangibility, to the rural people.
In general, forest activities and the resulting income play three different functions; as
safety nets, support to current consumption, and as a pathway out of poverty
(Cavendish, 2003). The safety net function relates to the role the income plays in
unpredicted and irregular times of hardship such as crop failure due to drought. Park
income may be used as a coping strategy to support current consumption and prevent
households sinking into deeper poverty but may also serve as a pathway out of
poverty by contributing to accumulation of assets (see vedeld et al., 2004).
2.5.4 Household external factors
From the modified household economic model, a number of household external
factors are hypothesised to influence choice of livelihood activities. For park
activities, important factors could be distance to the park, social institutions such as
ethnicity, duration of stay in an area, natural given vagaries such as adverse climate
leading to crop failures, and access to markets.
1. Distance to the park
The effect of distance to the park on household participation in the collection of park
products is variable. Logically, households living far away from the park should find
it more costly to collect park products due to travel time requirements but some
evidence suggests otherwise. For example, in Tanzania’s Nanguruwe village, women
regularly walk 8 to 16 km to gather a wild yam ming'oko (Dioscorea sp.), which is an
important component of their diet (Missano, 1994). And in Ban Moh village in
Thailand, households continue to move long distances to collect natural products from
a village forest even after its closure (Sastri, 1994). In general, the effect of distance
21
on park dependence is variable and may depend on how important the collected
products are as a means of either subsistence or source of cash.
2. Ethnicity and duration of stay
Cultural factors such as ethnicity often influence dependence on park income (Stræde
et al., 2002). Culturally, some tribes may be heavily dependent on park products
while others selectively use few products. In other instances, some tribes may require
small or large amounts of a given product, while others may be completely
disassociated from park products. This may be related to the duration of stay in the
area. Having stayed near the park for a shorter period of time, immigrant tribes may
have no much interest or knowledge in the park products and may lack essential skills
or experience, especially if they come from non-forest environments. An opposite
situation might arise where immigrants do not have sufficient access to assets. They
are poor and attracted by park activities, especially where the parks are not managed
based on customary rights as these would again deny immigrants access.
However, tribes that have lived close to the park for long may have associations with
the park and use its products in particular ways that are often sustainable. For example
they may have taboos prohibiting usage of some products at least in some periods.
Immigrant tribes may have no associations with the park and no respect for such
customs. Ethnicity and duration of stay thus have varied influence on collection of
park products.
3. Natural vagaries
Natural vagaries such as adverse weather conditions increase risks for agrarian
communities. Rural households often insure themselves against such risks by
engaging in more than one livelihood activity (Kinsey et al., 1998). Whether a
household engages in collection of park products as a way of insuring against such
risk depends to a large extent on what other options the household has.
4. Access to markets
The effect of access to markets on park incomes varies with the importance of other
factors correlated with access to markets (Vedeld et al., 2004). For example, whereas
22
better access may be expected to favour park income, a remote area with no market
access may show greater dependence on park income primarily because of the
abundance of the park resources. Also remoteness might mean reduced alternative
livelihood activities. Access to markets may have no effect especially if the park
products are primarily sources of subsistence income as opposed to cash.
2.6 Distribution of park income
There is great variation in extent of collection of park products and in types of
products collected. The variation might be within and between wealth categories,
locations, and differential access to markets and by gender. However, many of these
variables are composite, which complicates accounting for the observed differences.
For example embedded within the differences in distribution between locations could
be differences in ecology, ethnicity, market access just to mention but a few. More
complicated is if the interaction terms of these differences are also important. Despite
their drawbacks, it is often worth to consider these differences, albeit with the caveats
in mind.
2.6.1 Wealth categories
Households are typically heterogeneous in levels and types of assets held. They also
have varied wealth levels, the opportunity cost of time varies between them and their
utility functions may also vary differently. This variation conditions both
participation, extent of participation in any given income strategy and thus the
proportionate contribution of any given strategy. As Barham et al. (1999) noted, even
the often over looked small wealth differences can significantly affect dependence on
forest income.
Wealthier households tend to prefer more stable income strategies (Gunatilake, 1998),
whereas with their limited access to credit for example, poor households have limited
ability to invest in non-agricultural activities. This results into dependence on
activities such as collection of forest products.
23
2.6.2 Location
Locations vary in terms of both internal and external household specific factors. For
example, households in different regions have different access to assets, are exposed
to different external factors and/or different means of responding to the external
factors. The combination of livelihood activities pursued and the proportionate
contributions of incomes from each activity thus vary between locations.
2.6.3 Gender
Collection of park forest products is often differentiated by gender. Typically men and
women collect different forest products, although there can be an overlap on some
products. Gender differentiation of collection of forest products is embedded in social,
cultural and historical contexts of many African communities and has been the norm
since the hunting and gathering era. Whereas it is common for men to pursue those
products than have the potential of earning some cash for the household, the tendency
is for women to collect for home use. Women thus commonly collect such products as
firewood, medicinal plants, fruits whereas men may collect products such as timber
and bush meat. Quite apart from the domestic role that men and women play, the
other conditioning factor as to which products to collect is the labour requirement and
the risks involved in collection. The tendency is for men to collect more labour
requiring products and where it is more risky.
2.7 Importance of park products
Collection of forest products plays three key roles: as safety nets, support to current
consumption, and/or pathway out of poverty (Cavendish, 2003). These roles tend to
fit neatly into the livelihoods of the poor. The three roles may not always be separable
and some forest products might serve at least two if not all the three roles.
The safety net function is related with events that are irregular in nature and thus
unpredictable. Such events as natural disasters, family illness or death bring
hardships. The safety net role of forests refers to their provision of income in such
times so as to prevent extreme hardship. How important forest income is to the
household will depend on how susceptible the household is to such events and what
24
alternative safety nets the household has. More vulnerable households with fewer
safety net alternatives will find the forest income more useful for its safety net
function.
By supporting current consumption, forest income can be used to overcome seasonal
shortfalls, as a regular means to subsistence, and as a low return activity, attractive to
the poor. Forest income helps fill gaps resulting from seasonal shortfalls. For example
some households living adjacent forest areas collect wild fruits and foods from the
forest in the months before harvest of staple crops. This tends to occur in rather
anticipated times, which differentiates this role from the safety role. Regular means of
subsistence refers to uses made of the forest more or less through out the year. For
purposes such as firewood collection, forest adjacent communities often depend on
the adjacent forests. This is not to imply that forests are only about facilitating direct
consumption. They can also be used as means of economic production, albeit with
low returns.
Poverty alleviation is on Uganda’s national agenda. Considering that many of the
poor live adjacent forest areas, it is important to understand the relevance of forest
income for poverty alleviation. To what extent does forest income help lift poor
people out of poverty? The importance of collection of park products, particularly to
the local economy, can be estimated through the effect of the resulting income on
income inequality and poverty.
Income inequality relates to how much income goes to each household percentage. In
situations of perfectly equal income distribution, every household has as much income
as the other. The bottom a% household will have a% income. The exact opposite is
where one household has 100% of the income and all the others have 0%. This gives
the perfect inequality curve. The Gini coefficient as a rule lies between 0 and 1.
From the household economic model, total household income reflects the assets a
household accesses and the returns to these assets. In this respect, poverty is but an
expression of inadequate levels of access to assets and/or return to the assets, resulting
in lowered household welfare. Poverty exists when at least one individual is not able
25
to attain what his or her society deems minimum for material well-being (Ravallion,
1992). Poverty can be measured in absolute or relative terms. Absolute poverty is
when the individual income is below a fixed measure regarded a minimal material
necessity for healthy survival whereas relative poverty is when the individual’s
income is significantly below average societal incomes and thus un able to enjoy fully
all that other members enjoy. This study uses absolute poverty.
Both consumption and income are used as proxy measures of welfare. In some
instances, consumption indicators are superior (e.g. Ravallion, 1988) whereas in
others income measures are better where households smoothen income instead of
consumption. Showing the effect of an income activity on poverty requires setting a
poverty line that separates the ‘poor’ from the ‘non-poor’. It is computed basing on
the cost of basic necessities of life. This is then used as threshold expenditure deemed
necessary to buy a minimum or socially acceptable standard of nutrition and other
necessities (World Bank, 1993). By default, this varies between countries.
The absolute poverty line for Uganda is equivalent to the cost of obtaining the
recommended 2283 calories per capita. After adjusting household size for the number
of people of different ages and correcting for inflation, Uganda’s national poverty line
was projected at 23,430 Ugandan shillings (U Shs) per capita per month by January
2002 (UBOS, 2001). This gives a national income poverty line of 281,160 Ugshs per
year. Households whose per capita income is less than 281,160 U Shs (154.5 USD)
per year are thus considered poor.
Park income contributes to poverty reduction in rural areas. A household might
collect a diversity of park products or specialise in one product. Either way, by
providing either cash or subsistence income, the pursued activity may contribute to
reducing the occurrence of poor people in the population (i.e. reducing poverty
incidence), bringing those below poverty line close to the line (i.e. diminishing the
poverty depth) and/or reducing the severity of poverty in the population.
26
CHAPTER III: STUDY AREA AND METHODS
3.1 Study area
3.1.1 Physical and climatic conditions
Rwenzori Mountain National Park is located in the Rwenzori mountain ranges,
covering a total area of 100,000 ha. Its location within these ranges gives it unique
physical and climatic conditions. The Rwenzori Mountains are located 30o east of the
Greenwich and less than 1o north of the equator, with an attitudinal range between
1,700 m and 5,109 m, at the convergence zone of the south east monsoon and north
east trade winds. This gives the mountain substantial aerographic effects, thus unique
hydrological, ecological and geographical characteristics; a recipe for unique flora
and fauna (Howard, 1991; Tukahirwa, 1998).
3.1.2 Flora and fauna
The Rwenzori mountains are well known for their unusual flora, many endemic to the
Albertine Rift as elaborated by Herberg (1963), Howard (1991) Butynski (1992), and
Lush (1993) among others. Faunal knowledge is skewed in favour of the higher
altitude species. Overall, the mountains contain at least 89 species of forest bird 19 of
which are Albertine Rift endemics (Howard, 1991). The area has a high level of sub-
specific endemism; Rwenzori colobus monkey (Colobus angolenis rwenzorii),
Rwenzori hyrax (Dendrohyrax arboreus rwenzorii) and Rwenzori leopard (Panthera
pardus rwenzorii). The park is home to a number of globally threatened species, albeit
in low numbers; elephant (Loxodonta Africana), chimpanzee (Pan troglodytes),
l'hoests monkey (Cercopithecus l'hoesti).
3.1.3 The People
The Bakonjo is the dominant tribe around RMNP. They belong to Bayira, a Bantu
speaking people, most of whom live on the DRC side under the name Banande
(Magezi et al., 2004). The other major ethnic groups are Bamba Batuku, Batoro and
Banyabindi. The Bakonjo and Bamba live on the higher altitudes. The majority (80%)
of local people, like in many other rural areas of Uganda, depend on subsistence
27
agriculture, but with a considerable forest-based share of the total income.
Agricultural crops grown are augmented by collection of a variety of products from
the park; bamboo, fibres for weaving, and medicinal plants, for example.
Figure 2 Map of Uganda showing Rwenzori Mountain National Park and study area
(Source; Rwenzori Mountains Conservation and Environmental Management Project)
28
3.2 Data collection, handling and estimation procedures
Collection of information on household characteristics, asset ownership and collection
of park products used a survey approach carried out from October to December 2005.
Six sub-counties that border with the park were randomly chosen (Figure 1) and from
each sub-county, two sample villages were randomly chosen. Focus group discussions
were also held in each sample village, with a group of 4-6 people. The target population
for the study were all households that use RMNP. The observation unit was the
household. Sample households were chosen using one stage stratified random sampling
technique.
The observation units were stratified basing on the assumption that various income
groups use the forest resources in different ways. For each sample village, participatory
wealth ranking categorised all the households into three wealth categories and five
households were randomly selected from each. The total number of households in each
village and wealth category was recorded for purposes of weighting the observations.
Stratification displays the varying levels of household dependence on the forest to
maintain their livelihood and also ensures full coverage of the range of existent
livelihood circumstances for each sample village. The total sample is thus made up of
three strata based on wealth; Rich, medium and poor. The assumption here is that there
is less variation within a given wealth category across villages than between wealth
categories within a village.
Random selection of villages and households within strata was attained by assigning
numbers to all population units of the organisation group. Then pieces of paper with the
corresponding numbers were made and shuffled within a small box. Depending on the
required number of units, an equal number of papers were randomly drawn from the
box and the units with the corresponding numbers selected as sample units. As a result
of the above process, 12 villages were visited and a total of 180 households were
interviewed.
29
Present livelihoods of the communities around RMNP, the constraints they face and the
proportionate contribution of the park income to their total incomes are estimated by
analysing (see section 3.7) the data collected as above. Model estimations are used to
determine factors for collection and extent of collection of park products. The effect of
park income on income inequality and poverty is estimated by comparing the Foster-
Greer-Thorbecke (FGT) class of poverty measures for observed household income
distribution with counterfactual income distribution without park income. .
3.3 Empirical models
From the conceptual framework, at any particular moment, the household selects a
mix of strategies that maximizes its utility. The available income strategies can be
classified as below;
1. Purely subsistence agriculture
2. Combining strategy (1) with collection of park products
3. Combining strategy (1) with an off-farm activity
4. A mixed strategy, combining the above 3 in all possible combinations.
However, based on collection of park products, two income strategies are discerned; a
strategy that involves collection of park products, and one that does not involve any
collection of park products, strategy.
3.3.1 Collection of park products
Collection of park products is first treated as a binary response, with only two
possible outcomes; one either collects or not. Following from the conceptual
framework, decision to collect park products is specified in terms of household
characteristics and asset ownership and the outcomes labelled 1 and 0, respectively. A
model can then be specified for the decision to collect and extent of collection of park
products.
In order to identify factors influencing decisions to collect or not, use of a binary
choice model may be useful. Possible models are Linear Probability, Logit and Probit
models. Linear Probability Model is least used because of its associated problems;
30
variance of the error term is not constant since it depends on the explanatory
variables, and the probabilities do not lie between 0 and 1. Commonly used is either a
Logit or Probit model. Both give similar parametric coefficients and thus, decision
concerning which of the two to use is often made arbitrarily (Aldrich and Nelson,
1984). The estimations here thus use a Probit model. The Probit model computes
estimates using the Maximum-Likelihood function (Heckman, 1979). Following (), if
participation is denoted by yi the probability that a household with characteristics xi
collects park products (yi=1) is given by;
P(yi=1/xi)= Ф (α + βxi) …………………………………………………….....(1)
where Ф (.) is the cumulative distribution function for the normal distribution
Higher estimated values of the coefficients denote higher participation probabilities.
3.3.2 Extent of collection
The extent of collection of park products is estimated in this study as the amount of
income obtained from the collection. Park income is not observable for non-collecting
households and all estimates based on it will exclude the non-collecting households.
Observations on the latter households are censored yet they have information on
explanatory variables (in terms of household characteristics and asset ownership).
Estimates based for example on Ordinary Least Squares (OLS) under such
circumstances violate the essential assumptions of unbiasedness and consistency of
the estimators. However, the Heckman selection model can test and control such
selection biases (Wooldridge, 2004), in a two stage least square estimation method.
The model is specified as
E(Y1 | X, Y2 =0) = ßo + ßi Xi + γ1λ(.) + εI ……………………………….(2)
Where Y1 is observed value, Y2 is unobservable value, and λ(.)1 is Inverse Mills Ratio
(IMR) meant to control selection bias. The equation can be estimated using
Heckman’s two-stage least square estimation. In the model, one identifies a variable
1 Calculated as the ratio of normal density distribution to cumulative normal distribution
31
that can strongly affect the chances of observation but not the outcome under study, in
this case, extent of collection of park products. Unlike OLS or Tobit estimates that
omit the term γ1λ(.), estimates from the above equation are consistent (Wooldridge,
2004). The coefficient γ1 tests for the existence of selection bias.
The two stages of the Heckit model, as applied here, are thus; first, Probit regression
to identify factors that influence participation in collection of park products and
second, the OLS regression to identify the factors determining the extent of
participation. In the second OLS regression the IMR generated from the first step is
included. This corrects for the bias that would otherwise result from censoring non
participating households.
3.4 Park income and income inequality and poverty
The impact of park income on inequality is estimated by measuring and comparing
the Gini coefficients in the absence and presence of park income. Human beings
prefer higher status and thus like any change that moves them up relative to others but
they dislike inequality (e.g. Bolton and Ockenfels, 2000). The Atkinson inequality
aversion parameter (Atkinson, 1970) is incorporated in the estimation of the income
inequality with and without park income to measure household inequality intolerance.
The measure takes values ranging from zero to infinity. Increases in the parameter
signal increased household intolerance to inequality and that the households attach
more weight to income transfers at the lower end of the distribution and less weight to
transfers at the top. The effect of park income on poverty is measured by the Foster-
Greer-Thorbecke (FGT) class of poverty measures Pα (Foster et al., 1984).
The Foster- Greer-Thorbecke (FGT) class of poverty measures is denoted by:
α
α ∑=
−=
q
i
i
z
yz
nP
1
1 ……………………………………………………………… (3)
were α = Poverty aversion parameter
n= Total number of individuals in the population
q= Total number of poor individuals
z= Poverty line
iy = Income of individuals below poverty line, and i=1, 2,…q
32
The FGT is made up of three basic measures; when α=0, 1, and 2 and these are the
head count poverty measure, poverty gap index, and the measure of poverty severity,
respectively.
Head count poverty measure: Head count poverty measure )( 0P is a head count
ratio index, expressing the proportion of total population lying below the poverty line.
By showing the proportion population that is poor, the ratio measures poverty
incidence. The ratio is presented as;
If 0=α ; Then n
qP =0 ………………...……………………………. (4)
However, 0P is only sensitive to the number of the poor in the population and thus
only reflects the prevalence of poverty but is totally insensitive to differences in the
depth and severity of poverty.
Poverty Gap Index: The poverty gap index )( 1P measures the depth (extent or
intensity) of poverty in a population by estimating the average distance separating the
poor from the poverty line. It can thus indicate, under perfect targeting, how much
income should be transferred to the poor so as to close the poverty gap and eradicate
poverty. The index is presented as;
If α= 1; Then [ ]∑=
−=
q
i
iyznz
P1
1
1 ………………………..…………………….. (5)
However, P1 may not convincingly capture differences in the severity of poverty. It is
insensitive to income distribution among the poor. An index that reflects this must
attach greater weight to the poorest units and this can be achieved by setting α= 2.
Measure of Poverty Severity ( 2P ): 2P is additive and weights the poverty gaps
when aggregating poverty. It shows how severe poverty is by assigning each
household a weight equal to its distance from the poverty line. In this way, 2P
33
accounts for both the distance separating the poor from the poverty line and the
inequality among the poor. It reflects the degree of inequality among the poor; the
greater the income inequality among the poor (and thus the greater poverty severity
is), the higher is P2. It is presented as;
If α=2; 2P = [ ]∑=
−
q
i
iyznz 1
2
2.
1 …………………………………………….. (6)
3.5 Measurement of the dependent variables
The main dependent variable in this study is park income and its share of total
income. Evaluation of park income involves three aspects: decision to collect forest
products from the park, extent of collection, and impact of the income so earned on
both income inequality and on poverty. By definition, a household collects forest
products if the park income (measured in Uganda shillings) arising from the
collection, is different from zero. The extent of collection and effect of the earned
income on income inequality and poverty are based on amount of income earned.
However, park income is a component of the household’s environmental income. The
sum of environmental income, incomes from agriculture and off-farm activities
constitute the total household income. This total income defines the livelihood gained
by the household. To understand the relative contribution of the park income, all
income sources are measured and the total income is estimated.
3.5.1 Environmental income
Environmental income is calculated to include park environmental income and non-
park environmental income. Park environmental income is estimated by summing the
value of all products collected from the park for the year 2005, based on a recall
method. Goods sold by a household are valued using the respective selling price while
those consumed at home are valued at reported market prices. The latter goods are
also considered as income as they provide utility that would have otherwise been
provided by income from elsewhere. The value of each good is calculated as the
product of quantity collected and the price. Non-park environmental income is
34
estimated and the sum of the two incomes categories gives total environmental
income.
3.5.2 Absolute and relative environmental income
Absolute environmental income is here defined to refer to the sum of park and non-
park environmental income as defined above. Relative environmental income refers to
the share of environmental income over total household income.
3.5.3 Income from agriculture
Total income from agriculture is calculated as the sum of the value of agricultural
crops, livestock and associated (waste) products. All the outputs are valued at the
market producer price irrespective of whether they are sold or consumed at home.
Incomes are calculated by multiplying the quantities of commodity produced by its
market price, less the estimated production costs such as cost of seed.
3.5.4 Income from off-farm activities
Income from off-farm activities is here defined to include both the (i) non-farm
income that some household members earn by working as casual labourers both on
other peoples’ farms and other non-regular casual work for others; and (ii) income
earned by members who either have some form of business or earn some regular
wage. Income from case (i) is obtained as an aggregate of the pay the household
recalls to have earned from such kind for the year 2005 while for case (ii) is derived
from the average monthly earning.
3.6 Definition and measurement of the independent variables
Independent variables are estimated and used in the Heckman model. The model uses
a number of independent variables, reflecting the heterogeneity of opportunities and
constraints facing households in their income generating strategies. The modified
household economic model presented in the conceptual framework categorises these
35
variables into household internal factors and household external factors. Following
the model, these factors are empirically measured using proxies as follows.
3.6.1 Household internal factors
Household internal factors are factors within the direct control of the household and
are in form of access to assets; human, social, physical and financial capital. All are
measured by use of proxies, with different logics for inclusion in the models and
different expectations of signs for their correlations. The basic assumption made is
that park incomes are incomes of the last resort. It is thus hypothesized that
households with limited access to assets have low per capita incomes, limited ability
to invest in alternative income sources and are thus forced to depend on park income.
Human capital: To qualify and quantify human capital, the age categories are
distinguished: less than 14 years of age, 14-64 and above 64 years of age. The number
of productive age adults (14-64) is further split by gender. Human capital like all
other variables dependent on household size can not be measured by a simple head
count of the household members. Two households with an equal number of residents
may access very different amounts of labour based on the differences in sex and age
compositions of the members. Commonly used is an equivalence scale that measures
the number of adult males to which the household is deemed to be equivalent. Each
household member counts as a fraction of an adult male. Effectively, household size
is the sum of these fractions, referred to as adult equivalents. This study uses modified
Organisation for Economic Co-operation and Development (OECD) scales (Table 1),
and all per capita measurements are estimated with adult equivalents as the household
size.
Differences between the qualities of labour accessed by households are measured
using the number of years spent in school by the household head, and the education
levels of the male and female adult household members. Households with better
educated household heads and higher number of adult members with higher education
levels are expected to have higher per capita incomes and thus lower probability and
36
extent of collection of forest products. Differences in quantities of labour accessed by
households are expressed by the respective total adult equivalents for each household
and household age composition.
Table 1: OECD Adult equivalency scales
Modified OECD Scales Adult equivalents First adult 1.0 Spouse 0.5 Other second adult 0.5 Subsequent adults 0.5 Children aged 14yrs and over 0.5 Children aged below 14yrs 0.3 Source: OECD, 2003/4
Household composition by sex affects both the quality and quantity of labour. As
Murphy et al. (1997) note, disaggregation between male and female workers controls
for the effect of gender in shaping household activity choice. Male and female-headed
households are thus identified and when measuring access to labour, the education
levels are disaggregated based on gender. The general hypothesis here is higher
education levels are associated with higher per capita incomes and reduced likelihood
for collection of forest products, whereas the effect of gender is variable.
Sex of the household head is input as a dummy variable. Since inputting two dummy
variables would result in one being dropped due to collinearity, only one household
head sex dummy is used in the regression analysis. It is one if the household head is
female and zero otherwise. In general, female-headed households in the rural areas are
often poorer than the male-headed. The former are thus more likely to resort to
collection of forest products as “employment of last resort”.
Membership to associations: Membership in various associations is used as a proxy
for access to informal social networks. Membership is used as a dummy variable;
which is “one” for households that belong to at least one association and “zero”
otherwise. Membership to associations provides mutual help and is expected to be
positively correlated with per capita income. Its correlation with collection of park
products is variable.
37
Physical capital: Access is estimated for two physical assets; land and livestock.
Land is measured by total land area, land area squared, per capita land area. Land area
is hypothesized to increase per capita incomes and to reduce the likelihood and extent
of collection of forest products.
Households own different kinds of livestock. For meaningful comparisons, a
conversion factor is used to calculate a single indicator for livestock ownership (Table
2). The number of units obtained after a given livestock species is multiplied by the
appropriate conversion factors is the Tropical Livestock Units (TLU) for that species.
Household access to livestock assets is thus measured by the sum of TLU owned.
Livestock relieves the household of liquidity constraints and livestock or its products
are sold, the household gets cash. It is thus hypothesised that larger TLU increase
household per capita incomes and reduce the likelihood and extent of collection of
forest products.
Table 2: Livestock conversion factors
Type of animal Conversion factor
Cattle 0.70
Pigs 0.30
Goats 0.10
Poultry 0.02
Source: Taylor and Turner (2000)
Financial capital: Due to the difficulties associated with measuring access to credit,
participation in credit markets is input using a dummy variable; which is “one” for
households that have received credit in the previous four years and “zero” otherwise.
Credit solves liquidity constraints and facilitates pursuance of off-farm businesses. It
is thus hypothesized that access to credit increases household per capita income but
reduces the likelihood and extent of collection of forest products.
38
3.6.2 Household external factors
Important external factors beyond the control of the household are location, distance
to the park, ethnicity, duration of stay in the area, natural vagaries, and access to
markets. These largely shape the extent to which the household envisions the resource
value of its surrounding environment. They are broader scale issues whose
consideration is necessary so as to contextualise household adaptations and usage of
the environment.
Location: Locations vary in several aspects such as ethnic composition, geology, and
hydrology. Such variations provide opportunities and challenges and the location
effect on per capita income and dependency on the environment is variable. But one
generalisation is that where the combination of local conditions is conducive for good
income generating alternatives, per capita is high and there is little interest in such
“employment of last resort” as collection of forest products.
Distance to the park: Distance to the park is estimated in Kilometers. Distance
increases the cost of transportation of forest products and communities near the park
are away from many social and economic services such as good roads and markets.
Distance is thus hypothesized to reduce per capita income and the likelihood and
extent of collection of forest products.
Ethnicity: The tribe of the household head and duration of stay are specified in the
Heckman model. A dummy variable, “one” for immigrant households and “zero”
otherwise is input. The effect of tribe is not straight forward. Its effect depends on
differences in access to opportunities by the different tribes.
Natural vagaries: Natural vagaries are captured through the number of failed crop
seasons within the last four years. Crop failure directly reduces household incomes
and the higher the number of failed the more likely the household is to resort to
collection of park forest products as an “employment of last resort”.
Market access: Access to market estimated by distances to the nearest rural market,
town and trading centre. The effect of market on collection of park forest products is
39
ambiguous. Specialisation in high-value forest products needs good access to market,
but since most of the forest products from RMNP are collected for subsistence, it is
here hypothesized that good market access makes alternative income sources more
profitable as compared to collection of forest products.
3.6.3 Proxies and their expected signs
The proxies for household internal and external factors are input into the models and
because of the variation in their effect, different signs are expected for their effect on
household per capita income and collection of park products (Table 3).
Table 3: Proxies used in the regression models and their expected signs
Expected sign Proxy
Per capita income Collection of park forest products
Household internal factors
Total land accessed by household (in Acres) + -
Total land accessed by household squared (in Acres) + -
Total Livestock Units + -
Household head age in years + +/-
Household head age in years squared + -
Household head education in years + -
Household head has above secondary level of education + -
Number of females with primary level of education + -
Number of males with primary level of education + -
Number of females with secondary level of education + -
Number of males with secondary level of education + -
Number of females with above secondary level of education + -
Number of males with above secondary level of education + -
Household size - +
Household number of males + +/-
Household number of dependants - +
Household consumer worker ratio + +/-
Household headed by female (1=Yes) - +
Household head has a secondary occupation (1=Yes) + -
Household is a member to at least one association (1=Yes) + +/-
Household primary occupation (1=Subsistence agriculture) - ?
Household has received credit within the last 4 years + ?
Household collects park forest products (1=Yes) -
Household external factors
Location dummy: Kasese (1=Yes) ? ?
Location dummy: Kabarole (1=Yes) ? ?
Duration of stay in the area + +/-
Household received remittances (1=Yes) - +
Number of failed crop seasons - +
Distance to the park boundary + -
40
3.7 Data analysis
Since the data were collected using a one stage stratified random sampling procedure,
not every household in the population of interest had exactly the same probability of
being chosen during sample. Rather, households in the randomly selected villages
were stratified by wealth to ensure a balanced number of respondents for each wealth
category since wealth categories differ in access to assets and livelihood activities.
The villages are thus the Primary Sampling Units (PSU), have three strata; the rich,
medium and poor households and the total number of households in each wealth
category constitutes that strata’s finite population correction (fpc) (Levy and
Lemeshow, 1999; Thompson, 2002).
However these categories have different proportions in each village and thus,
households have different probabilities of being included in the sample. To account
for this difference, sample weights (pweights) are used. The weights denote the
inverse of the probability that a household is included in the sample as a result of the
sampling design. Thus if five households are selected from a wealth category with a
population of thirty households, the pweight is thirty divided by five, which is six.
Observations from a single household in such a wealth category represent
observations for six households. The psu, fpc, and pweights are all set using Stata
8.0’s svyset command and the analysis combines descriptive analyses and
econometric estimations using svy commands. The estimated coefficients are thus
robust. Survey commands use fpc to compute population size and fpc is used to
calculate the standard error of the estimates ((Levy and Lemeshow, 1999). Thus,
variability is reported in terms of standard error instead of the standard deviation.
Standard deviation measures the variability of the data about the mean but having
used a stratified sampling procedure, the variability of importance is the standard
error, which measures the standard deviation of the sample mean based on the
population mean; how likely is it to get the same estimate if we were to repeat the
same type of measurement again and again on different samples of the same
population?
41
3.7.1 Present livelihoods of communities adjacent RMNP
Descriptive statistics are used to estimate present livelihoods of communities adjacent
RMNP. Households’ accesses to assets (land, labour and capital), livelihood activities
pursued by households pursue and the contribution of each activity to household total
income are estimated using descriptive statistics and presented using n-way tables.
The correlation between access to the different assets is estimated using pair wise
correlation. (Hamilton, 2003). The relationship between household income and access
to assets is examined using a log-lin model (Wooldridge, 2004). Local heterogeneity
is captured by comparing household factors across wealth categories. For continous
variables, Analysis of Variance is used whereas the chi square is used with the
dummies to show statistical significance of the heterogeneity (Hamilton, 2003).
3.7.2 Household constraints
Household constraints in form the main constraints to better economic livelihoods and
the specific problems faced because of living close to a national park are analysed as
frequencies and presented descriptively.
3.7.3 Estimating household dependency on environmental income
The average proportionate contribution of environmental income to total household
income is estimated and the percentage contribution computed. Variation in
dependency on environmental income by households with different income levels is
examined by regressing environmental income and relative environmental income
against total household income.
3.7.4 Estimating dependency on park environmental income
Factors that influence dependency on park environmental income are estimated by
factors for collection and extent of collection of forest products. The latter are
estimated using a two step Heckman model. The distribution pattern of the forest
income between the districts is estimated by the average contribution of park income
to their total incomes. The distribution pattern by gender is examined through the
42
products collected by men and women. Variation in dependency on park
environmental income by households with different income levels is examined by
regressing park environmental income and relative park environmental income
against household income.
3.7.5 Relationship between park and non-park environmental income
The relationship between park and non-park environmental income is investigated by
regressing park income against non-park environmental income and observing how
the two incomes co-vary.
3.7.6 Effects of park income on income inequality and poverty
The Gini coefficient and Atkinson index are used to show income inequality
household intolerance to inequality, respectively. A comparison of the coefficients
and indices for household incomes without environmental incomes is made with total
incomes to show if environmental incomes contribute towards diminishing income
inequality. Effect of park income on poverty is measured using the Foster-Greer-
Thorbecke (FGT) class of poverty measures at 0=α , 1, and 2.
3.8.1 Representativity
A total of 180 sample households were interviewed from a population of 1423
households in the 12 villages visited. Stratification of the households in each village,
based on participatory wealth ranking ensures full coverage of the range of existent
livelihood circumstances for each sample village and the use of stata’s survey
commands helps to account for the differences in the probability of selection of
households in the different wealth strata in the sample villages. This makes the data
representative of the sample villages. However, the random selection of sample
villages was made in a population of villages near the park, within a radius of utmost
6 Km. The findings can thus be generalised but only to the villages within this radius.
43
3.8.2 Validity and reliability
Validity and reliability of sample data are two of the virtues of good quality research.
Validity measures the presence and extent of systematic errors whereas reliability
assesses the study for random errors. Lower the errors mean higher validity and
reliability (Bryman, 2001). In effort to collect valid and reliable data, it was clarified
that the research is for scientific and academic purposes and has no legal implications
whatsoever. This assurance was necessary since collection of park products is illegal
in Uganda. Also, the research assistants were recruited locally and were fluent in
English and the local language so that there was equal understanding between them of
the questionnaire and knowledge of the local language meant no interpreter was
required which reduced distortion of information that is otherwise likely.
44
CHAPTER IV: RESULTS AND DISCUSSIONS
The first section of this chapter estimates present livelihoods of the communities
adjacent RMNP as measured by their access to assets, the livelihood activities they
pursue and the income contribution from each activity, relationship between
household income and assets, and local heterogeneity and diversification. The
second section presents the main constraints to households’ attainment of better
economic livelihoods and the particular constraints related to living close to the
park. The third section examines household dependence on environmental income
whereas the fourth closely looks at the dependence on park environmental income.
The fifth section examines the nature of the relationship between park and non park
environmental income and the last section estimates the effect of park income on
income inequality and poverty.
4.1 Present livelihoods of the communities adjacent RMNP
Conditions that influence a rural household’s livelihood depend to a large extent on
its access to assets as they influence which activities a household can pursue and thus
also the levels of income it can obtain. Therefore households’ asset portfolios are
important in order to estimate dependency on park resources since increased access
to these resources is expected to increase a household’s income, which may reduce
the household’s dependency on park resources.
4.1.1 Household access to assets
Also from the focus group discussions and insights in the field, it emerges that
household access to assets is important in shaping their economic and social
environments. It impacts on their choice of livelihood activities, levels of income and
general welfare. Assets are in the form of physical, human, social, financial and
natural capital.
Access to physical capital; Access to land and livestock were the two major forms
of physical capital commonly highlighted from the focus group discussions.
45
Access to land: Typically, all sample households have access to land. Most of the
land is privately owned, while some parcels are communally owned by the clan. All
clan members have access to such parcels. Households that privately own larger
areas of land have much access to land as they can also access the lands owned by
the clan. On average, each household has access to 2.8 hectares, but with substantial
variations between districts (Table 4). On average, households in Kasese access less
land compared to households in Kabarole while households in Bundibugyo have the
best access. This may impact on how households in the different districts depend on
environmental resources as an alternative source of income.
Table 4: Average land access by district, survey, Western Uganda 2005
Pweight: Pw Number of obs 179 Strata: Wealth Number of strata 3 PSU: Village Number of PSUs 36
FPC: Fpc Population size 1413.4
District Mean estimate (Ha) Std. Err. 95% Conf. Interval Deff
Kasese 1.606 0.273 1.051 2.161 3.299
Kabarole 3.284 0.240 2.795 3.773 1.893 Bundibugyo 3.693 0.527 2.621 4.766 3.402
Average 2.839 0.255 2.319 3.359 3.654
Sixty three percent of the households report to inherit all their land holdings, while
only 36.7 percent purchased at least one of the parcels owned. Inheritance as the
main form of land ownership not only perpetuates land fragmentation but also
indicates low land turnover in the area.
Summing up access to land; Each household in the sample area access on average 2.8
hectares of land. On the other hand, households in Kasese district have the least
access and the main form of land acquisition is through inheritance.
Access to livestock: Among the non-land physical assets that also impact on the
state of household’s incomes and welfare, is their livestock portfolios. A majority of
households (96 percent) keep some type of livestock. The number of animals kept is
here converted to Tropical Livestock Units (TLUs) to compare across livestock
species. The average TLU is 0.84 but there is variation in the numbers of livestock
kept by livestock type and by district (Table 5). The most common livestock kept by
46
most households (81 percent) is poultry, although it has a low average TLU (0.066).
In comparison, cattle are kept by 23 percent households, but average 0.447 TLU.
Many households own poultry because it is easy to acquire and keep but also is more
readily converted into cash, as compared to the others. It also provides important diet
sources of egg proteins and meat.
Table 5: Livestock keeping by communities around RMNP (Std. Err. in
parentheses), survey, Western Uganda 2005
Pweight: pw Number of obs = 179 Strata: wealth Number of strata = 3
PSU: village Number of PSUs = 36 FPC: fpc Population size = 1413.4
District Type of livestock Kasese Kabarole Bundibugyo Average
Goats 0.217 0.298 0.226 0.249 (0.020) (0.072) (0.035) (0.029) Sheep 0.016 0.052 0.028 0.033
(0.006) (0.015) (0.012) (0.008) Pig 0.061 0.019 0.061 0.046 (0.024) (0.010) (0.036) (0.014) Cattle 0.071 0.406 0.920 0.447
(0.051) (0.204) (0.288) (0.108) Poultry 0.057 0.065 0.077 0.066 (0.006) (0.008) (0.008) (0.004) Average 0.422 0.839 1.313 0.840
(0.066) (0.206) (0.295) (0.109)
However, compared to other areas of Uganda, this area keeps low numbers of
livestock. The poor households attribute their low numbers to the lack of capital to
invest in livestock whereas the better off households report limitations from the
rugged nature of the terrain and inadequate land holdings.
Summing up livestock ownership; A majority of households own some type of
livestock, and the most common is poultry. On average, Bundibugyo district keeps
more livestock than Kabarole and Kasese has the least number of livestock.
Access to credit; Conditions that influence households’ incomes and wealth patterns
are also to a large extent reflected in their access to credit. However, due to
imperfections in credit markets, high levels of poverty and the strongly subsistence
oriented nature of present production; poor farmers usually find it extremely difficult
47
to access funds through formal leading institutions. Therefore, the use of credit is low
in these rural areas, leaving informal credit markets as the main source of credit.
Most respondents interviewed during the focus group discussions attribute this low
borrowing to unavailability of lending institutions but households are also reported to
have fear of failure to pay back due to high levels of poverty, and that their land has
to be used as collateral.
From the descriptive evidence, an estimated 53 percent households have received
credit within the last four years. Of these, only 5 percent obtained credit from formal
institutions, while 95 percent borrowed money from other households. Generally,
households are found to get credit independently of their wealth category (Pearson
chi2 = 0.7460 Pr = 0.689). Households use different forms of collateral to access
credit (Figure 3).
32.1
2018
16.8
8.4
4.7
0
5
10
15
20
25
30
35
Crops in field Agreements No collateral Livestock Other assets Land
Type of collateral
Perc
enta
ge u
se
Figure 3: Different forms of collateral reportedly used to obtain credit, survey,
Western Uganda 2005
Noticeably, crops in the field, mainly cassava and coffee, are the most important
collateral used. Land is mainly used with formal lending and lenders reportedly
prefer privately owned parcels as collateral. Communal land owned by the clans is
least preferred as collateral. Households that sign agreements, only promise to pay
back on a specified date while those that use no collateral just promise to keep their
word. These two forms combined account for 38 percent of collateral usage and these
48
households report it is because they are trusted by the lenders that they can use these
forms of collateral.
“Trust is the poor man’s asset. If my friend trusts
me, he will lend me without my provision of
collateral” Male household head (52 years).
Among the livestock categories, goats are the main livestock assets used as collateral.
The goats are preferred because they can readily be converted to money and the
amount of money usually borrowed amounts to the value of a goat on average. This
is reportedly because households mainly borrow to finance some consumption needs,
which normally does not require large sums of money.
Summing up access to credit; The main sources of credit to households are fellow
households especially from neighbours and friends, borrowing is largely to finance
consumption, we find that most households draw on networks of trust for collateral.
Access to social networks; The social and economic environment of the poor also
largely depends on trust and social networks as assets embedded in social capital. In
the analysis, social capital is measured through membership to organisations as a
proxy for access to social network. Measured this way, most sample households have
low access to social networks. Only 20 percent of the households belong to at least
one association, and majority belong to farmer associations (Figure 4). Households
benefit from farmer associations especially garlic farmers who often jointly secure
markets and borrow money from amongst themselves. This lending often requires no
collateral and at its most formal, an agreement is signed specifying the amount
borrowed and when to pay back. Bee keepers, especially in Kabarole district pool
their honey collections and sell it as a group, and benefit from higher prices usually
offered by customers requiring large amount supplies. Savings and credit
associations pool money into revolving funds and lend it to themselves.
49
76
19
5
Farmer associations
Bee keeping
Savings and credit
Figure 4: Percentage membership to associations, survey, Western Uganda 2005
Summing up access to credit; Membership to associations is very low. The most
important associations are farmer associations, as would be expected in agrarian
communities. Membership in savings and credit associations is also very low,
especially given the scarcity of money lending institutions.
Access to human capital; Rural peasant farming economies have labour intensive
operations. Labour can limit attainment of better economic livelihoods. As such,
“access to labour, rather than land is the basis of economic and political power”
(Upton, 1987). Households have different access to labour depending on household
size and composition. The average household size is 7.3 members. The household
size is thus larger than in many other forested areas of Uganda. For example around
Budongo forest reserve in Western Uganda, the household size is 5.1 members on
average (Baikuntha, 2002) and around Mt. Elgon National park, it is estimated at 6.5
persons (Katto, 2004).
Whether the large household sizes are assets or liabilities to the households can be
examined by looking at the household consumer worker ratio. The ratio indicates the
relationship between consumers and workers. The lower it is, the higher the number
of workers compared to the number of consumers. Thus the lower the ratio, the more
likely the household will meet its consumption needs. The average consumer worker
50
ratio is 1.6 (St. Err.: 0.03). This means on average every worker fends for 1.6
consumers. The households thus have a high dependency burden.
The level of education acquired improves skills of the household members and adds
value to their labour units. However, education levels in the study area are generally
low. Taking the household heads, the average number of years spent in school is six
years. This is primary level education which intrinsically adds less value to the
households’ family labour. Only 3 percent of the household heads have post
secondary education. Like in many other forested areas, low levels of education are
expected to increase the dependence on park products. The dependence is likely to be
reinforced by large household sizes particularly if other livelihood options are
limited. In terms of alternative employment opportunities, only the 3 percent with
post secondary education are able to get gainful employment, and especially so in
formal sectors of the economy. Primary and secondary levels of education are no
longer enough to ensure access to better paid employment.
The majority of the households (92%) in the sample area are male headed. Only 8%
households are headed by females. The latter are widowed and divorced women with
no mature sons to head the households. From literature, such households are often
resource poor and are thus expected to exhibit more dependency on environmental
income.
Summing up on access to human capital; most households have large families with
high dependence ratios as depicted by the consumer worker ratio that is greater than
unity. Households have low education levels and are thus likely to have low access to
alternative sources of income.
Access to natural capital; In this analysis access to natural capital is measured
through the environmental income, which combines both the park and non-park
environmental income. Environmental income is the focus of much of the following
sections and is therefore briefly assessed here. Access to park resources is in
principle illegal and most resources used are non park resources collected from both
privately and clan held parcels. Some households are found to illegally access
51
resources also on parcels that privately belong to other households. The product often
accessed in this way is wood fuel.
Summing up on access to assets; There are variations in access to assets between
households in the different districts and within households in the same district. All
households do have access to land. The access to livestock is lower compared to
other areas in Uganda. The area has large family sizes with many dependants. Access
to credit is largely through informal sources and household membership to
associations is very low. A pair wise correlation shows significant correlation
between proxies for access to the assets (Table 6).
Ownership of land and livestock significantly increase with age of the household
head whereas access to credit decreases with age. Male headed households are
significantly bigger in size and have more livestock units. Households with large land
areas have significantly larger TLUs, are more likely to be members to associations
Kabarole and Bundibugyo districts have significantly better access to land than
Kasese. Bundibugyo district has better access to resources than Kabarole while
Kasese has the least.
Table 6: Correlation between some proxies of access to assets, survey, Western
Uganda, 2005
Variables Headage Size Land (Ha) TLU Network credit Male head Head age 1.000 Size 0.116 1.000 (0.121) Land (Ha) 0.222*** 0.303 1.000 (0.003) (0.000) TLU 0.141* 0.282*** 0.602*** 1.000 (0.060) (0.000) (0.000) Network 0.100 0.168 0.067 0.008 1.000 (0.185) (0.025) (0.374)** (0.914)** Credit -0.374*** -0.101 0.042 -0.048 0.111 1.000 (0.000) (0.180) (0.581) (0.528) (0.139) Male head -0.299*** 0.403*** 0.155** 0.167** -0.116 0.072 1.000 (0.000) (0.000) (0.039) (0.026) (0.121) (0.336) Kasese 0.113 -0.154 -0.507 -0.277 0.029 -0.123 -0.127 (0.133) (0.040) (0.000) (0.000) (0.704) (0.102) (0.090) Kabarole 0.109 0.199*** 0.215*** 0.013 0.249*** -0.158** 0.083 (0.148) (0.008) (0.004) (0.866) (0.001) (0.034) (0.267) Bundibugyo -0.221*** -0.044 0.293*** 0.264*** -0.277*** 0.280*** 0.044 (0.003) (0.555) (0.000) (0.000) (0.000) (0.000) (0.560) *** = significant at P < 0.01, ** = significant at p < 0.05, * = significant at P < 0.1
52
4.1.2 Household livelihood activities
It is not enough to know what assets households control. It is important to study how
they put them to use. The conditions that determine households’ welfare status and
patterns of production are reflected in household production and labour allocation
decisions; and thus the livelihood activities pursued. Possible livelihood activities
include agriculture, various off-farm activities and dependence on environmental
incomes. This study categorises livelihood activities into primary and secondary
activities (Table 7). A primary activity is one deemed as the household’s main source
of income whereas secondary activities play supplementary roles. The sample
households pursue a number of activities, consistent with observations in other rural
areas of Africa (Ellis, 2000).
Table 7: Reported household head occupations, survey, Western Uganda 2005 Household head occupation Frequency Percent
Primary Production/sale of crops 171 95.0 Crafts and Arts 2 1.1
Salary employment by government 5 2.8 Casual labourer 2 1.1
Secondary Trading in agricultural output 31 54.4
Production/sale of crops 7 12.3 Casual labourer 6 10.5 Beer brewing 4 7.0 Trading and services provision 4 7.0
Trading in agricultural inputs 1 1.8 Crafts and Arts 1 1.8 Charcoal burning 1 1.8 Salary employment (by government and NGO) 2 3.6
Agriculture combines both animal and crop husbandry and is the primary activity of
majority households reported by 95% of the sample households. Other activities
considered primary are off-farm activities which stand at 5% while no household
considers dependence on environmental income as a primary activity. Typically, all
households engage in subsistence form of agricultural production. The main staple
crops are cassava, maize, millet, potatoes and banana for all three districts. In
Bundibugyo we also find vanilla and cocoa as cash crops, in Kasese we find,
53
sorghum and passion fruits in Kabarole tea and coffee. These relate to variation in
agroecological conditions.
The crops are supplemented by livestock farming and despite the subsistence nature
of production; farmers in all the three districts often have some surplus that is sold to
both internal and external markets. There is a lot of on-farm diversification.
Households typically grow a variety of food and cash crops. Nearly every household
reports to grow beans, maize, cassava, bananas, potatoes and coffee. Coffee, vanilla,
tea, and cocoa where grown are strictly for cash income generation.
The important off-farm activities are self employment in trading of agricultural
produce; regular salaried jobs, beer brewing, selling labour on other peoples’ farms,
making crafts and providing services such as bar services. Trading in agricultural
produce is considered an indicator of wealth and is one of the main criteria used by
households in the participatory wealth ranking. Households trading in agricultural
produce usually have some cash and are reported to benefit from distress sales.
Households with no household member with a regular salary report distress sales. For
example one household head commented
“We never have cash except just after the harvest yet there are
times when one is in serious need of cash for example for medical
care, school fees or an emergency situation. Then one is forced to
sell one’s crops when still in the field. At such times, one is at the
mercy of the buyer who knows one has no choice but to sell at
whatever price is offered” (40 Years household head in
Kinyampanika village)
Households also report to collect forest products from the national park. A total of
34.4% households collect forest products from the park, even if no household deems
the collection of these products “an occupation”. Households collect both wood and
non-wood products and the collection is done by both men and women.
54
4.1.3 Incomes from the livelihood activities
The pursued livelihood activities contribute in different ways to total household cash
and subsistence income. On average, agriculture contributes the largest amount to
household total incomes (Table 8), which is a typical feature of rural livelihoods. The
share of off-farm activities is rather low in this area (cf Reardon et al., 1998). From
focus group discussions, we learned that opportunities for off-farm activities are
scarce in the area. Apart from trading in agricultural produce, the other common off-
farm activity is working as casual labour. Focus group discussions in the study area
revealed that some household members engage in food for work by working on other
peoples’ lands for food, although this appears to be under-reported. Households feel
embarrassed to report this, and the percentage share reported here thus needs to be
used with caution.
Table 8: Average share contribution of livelihood activities to total household
income, survey, Western Uganda 2005
Livelihood activity Average total
income (U Shs)
% share of
total income
Agriculture 1,101,335 74.3 Environmental 274,941 18.6 Off-farm 102,668 6.9 Remittances 3,014 0.2
Further looking at income from agricultural activities, the main sources of
agricultural income are starchy crops, vegetables, cash crops, fruits, seed crops and
livestock (Table 9).
Table 9: Sources of agricultural income, survey, Western Uganda 2005
Income source Average income
(U Shs)
% share of
agricultural income
Starchy crops 515,223 46.8 Vegetables 254,711 23.1 Cash crops 98,100 8.9 Fruits 92,542 8.4 Seed crops 77,732 7.1 Livestock 63,025 5.7
55
The most important starchy crops are cassava and banana, which are typically
consumed at home but in some instances also sold to get some cash. On average,
cash crops provide 8.9 percent of the total household income. This also indicates the
households have cash constraints. The vegetables are mainly consumed at home. The
most frequently sold fruit is passion fruit and sales of seed crops such as beans and
maize are made in the periods following harvests, only for the households to buy
them again at higher prices later in the year.
Livestock is on average the least important income source and is mostly owned by
the more wealthy households. Although agriculture is by far the major source of
income for the communities adjacent RMNP, environmental goods also provide
substantial cash and subsistence income. Environmental income combines both park
and non-park environmental incomes and its share contribution to household total
income is 18.6 percent.
Examples of products collected are bush meat, medicinal plants, firewood, timber,
mushroom, and honey. The major source of environmental income from both the
park and non park area is firewood, which is mainly collected by the women.
Medicinal plants collected from the park are also regarded important. All respondents
report environmental income as they all use wood fuel, 34.4 percent get their
environmental income from the national park. Park income contributes a third of the
environmental income and two thirds of the environmental income is from outside
the park. The environmental income is covered in greater detail in section 4.3.
The two main sources of off-farm income are trading and working as casual labour.
Trading is mainly in terms of agricultural produce and is typically pursued by
members of better off households that also report access to some kind of financial
capital. Asset poor households are limited in the kind of activities they can pursue
and are the only households selling their labour. Working as casual labour is largely
the domain of men, but in some instances women also sell their labour. From
informal field observations and discussions, women sale of labour indicates poor
households. Women tend to shun such odd jobs and their pursuance of such activities
signals a lack of alternatives.
56
The other sources of income are remittances often sent by relatives not living with
the household. The remittances are either in form of cash or even material items.
However, only a few households received remittances. The main reason advanced for
low remittances in the region is that few households have close relatives in better off
positions so as to give a helping hand. It is mainly the better off households that
receive remittances because they manage to have some of their members educated
and thus pursue better paid jobs in towns.
Summing up livelihood activities; Typical of rural livelihoods, households pursue a
diversity of activities. However, agriculture contributes most to households’ total
incomes. The percentage contribution of off-farm income to households’ total
incomes is low due to lack of opportunities for off-farm activities but also probably
due to under reporting of income from off-farm activities as households are not very
willing to admit working as casual labourers. Agricultural income is mainly from
starchy crops. Households also depend on environmental income and two thirds of
this income is from outside the national park. The national park provides only a third
of the environmental income but it is from a diversity of sources as compared to non-
park environmental income that is almost exclusively from wood products. The park
is especially important for medicinal plants, some of which are reportedly not
available outside the park.
4.1.4 Relationship between household income and assets
Households in the study area have an average annual per capita income of 302530 U
Shs (166 USD). This is less than 0.5 USD/per capita/per day. However, there are
great income variations among households. The household with the highest annual
income has a per capita income of 1,280,027 U Shs (703 USD) whereas the least
earns U Shs 55,961 (31USD). We tested how total household per capita income is
correlated with a number of factors. Following the modified household economic
model (see Figure 1), the factors are categorised into household internal and external
factors (Table 10).
57
Table 10: Determinants of household per capita income, survey, Western
Uganda 2005
Explanatory variables Coefficient t P>t
Household internal factors
Total land accessed by household (in Acres) 0.005 0.42 0.679
Total Livestock Units 0.084 2.44 0.020**
Household head age in years 0.027 0.86 0.394
Household head age in years squared -0.001 -2.34 0.026**
Household head education in years -0.018 -0.92 0.366
Household head has above secondary education 0.707 2.01 0.053*
Number of females with primary level of education 0.009 0.13 0.896
Number of males with primary level of education 0.068 1.10 0.280
Number of females with secondary level of education -0.015 -0.18 0.858
Number of males with secondary level of education 0.103 1.39 0.175
Number of females with above secondary level of education -0.081 -0.66 0.514
Number of males with above secondary level of education -0.192 -0.97 0.341
Household size -0.630 -2.86 0.007***
Household number of males -0.107 -1.94 0.061*
Household number of dependants -0.058 -0.78 0.440
Household consumer worker ratio 0.615 4.38 0.000***
Household adult equivalents 0.946 2.85 0.007***
Household headed by female (1=Yes) -0.556 -3.55 0.001***
Household head has a secondary occupation (1=Yes) 0.269 2.61 0.014**
Household is a member to at least one association (1=Yes) -0.074 -0.95 0.351
Household primary occupation (1=Subsistence agriculture) 0.286 1.66 0.106
Household has received credit within the last 4 years 0.166 2.13 0.040***
Household collects park forest products (1=Yes) -0.255 -3.53 0.001***
Household external factors
Location dummy: Kasese (1=Yes) 0.004 0.04 0.971
Location dummy: Kabarole (1=Yes) 0.133 1.29 0.206
Duration of stay in the area 0.046 3.51 0.001***
Household received remittances (1=Yes) -0.096 -0.91 0.370
Number of failed crop seasons 0.009 0.29 0.771
Distance to the park boundary 0.008 0.15 0.879
Constant 10.308 13.81 0.000***
Number of observations 148
Number of strata 3
Number of Primary Sampling Units 36
Population size 1187.8
F( 29, 5) 5.21
Prob > F 0.037**
R-squared 0.565
*** = significant at P < 0.01, ** = significant at p < 0.05, * = significant at P < 0.1
58
4.1.4.1 Household internal factors
Household per capita income is positively correlated with household access to
physical assets, which is consistent with the general observation that access to
physical assets enhances wealth accumulation. Access to land has a positive, but not
significant correlation with total income. Most likely this is because households do
not put to use all the land units to which they have access. Some land parcels have
been degraded and are not suitable for agriculture, whereas others are rocky and
hence not suitable for farming. Fields with stunted annual crops, beans with empty
pods are a common sight on many fragmented fields. Farmers report close to zero
yields in some instances.
Livestock ownership is positively and significantly correlated with total income.
Whereas livestock in theory could be used to generate wealth particularly by the poor
households that can depend on livestock to solve liquidity constraints, it appears to
be different around RMNP. Rather, livestock ownership seems to be more a result of
accumulation of assets. It is better off households that report access to livestock. Poor
households keep chicken and wealthier households keep goats and cattle.
Human capital embedded in household skills is correlated with total income in
various ways. Household head age has a positive but non significant correlation.
However, the quadratic term in the square of the age of the household head age has a
significant negative correlation with household per capita income. This suggests that
household per capita income increases with household head age before falling. For
many households, the household head is normally the principal earner and thus his or
her attributes are normally important in household decisions on activities undertaken
and the income accruing from the undertakings. Around RMNP, the main sources of
income are agriculture and some off-farm activities, which for most households is
through selling labour. Both activities are demanding and thus suitability for them
increases with age up to a certain level and then level off as the individuals grow
older.
The sign on the estimated effect for household head education in years is counter-
intuitive. Theory on access to assets suggests that education of household members is
59
positively correlated with income as education imparts skills that facilitate flexibility
in choosing livelihood activities. This assumes that such opportunities are available.
In areas such as around RMNP, the opportunities available are shunned by people
with higher levels of education. The most common off-farm activity is selling labour
and this is often not attractive to individuals with higher education levels, and could
thus partly explain the negative correlation observed between household per capita
income and household head education in years.
The effect of education on household per capita income is gender specific. Whereas
the education of male household members is positively correlated with household per
capita income, for females it is only primary education that is positively correlated
with total income. Secondary and post secondary levels of education have a negative
correlation. This could again be due to the nature of income opportunities available.
The main occupation is subsistence agriculture and main off-farm activities are
trading in agricultural produce and selling labour to other peoples’ farms as casual
labour. As females get increasing levels of education, these employment options
become less attractive, save for trading. Trading is, however, also limited by its
financial needs and it tends to favour men because the middlemen often have to
move around the villages buying the produce from the farm gates. This requires use
of bicycles, and it is men who do the cycling. This may also explain the positive
correlation observed between male education and income.
Another important dimension of human capital can be seen by looking at the amount
of labour force available for production. The household number of “adult
equivalents” measures the household’s access to labour. Households with more
labour are in a better position to diversify to more income generating options,
especially in slack periods when there are less agricultural activities. This explains
the positive correlation observed in Table 10 between household adult equivalents
and per capita income. Related to the household adult equivalents is its “consumer to
worker ratio” which measures the number of consumers a worker fends for in a
household. Households with more workers and less dependants will be expected to
have higher per capita incomes and we do observe a positive correlation between
consumer worker ratio and income. In the same vein, household number of
dependants is negatively correlated with household per capita incomes.
60
From field observations, the sex of the household head also has an impact on labour
access and consequently on production. Female headed households tend to have poor
access to assets, they often have large families with many dependants and even
where small, the household head is still the major income earner. Female headed
households usually have low per capita incomes whether small or large in family
size, and this explains the negative correlation observed in Table 10.
Households with few workers seem to limit themselves to subsistence agriculture.
Further, they do seem not to have sufficient labour to invest in alternative income
sources. However, in other instances, households fail to pursue other occupations
because of the special requirements of the alternatives; financial capital in case of
trading or enough stamina to work for long hours doing hard work as casual labour.
Pursuance of other occupations often increases total income earnings of the
household. We do find a positive and significant correlation for households that have
a secondary occupation (see Table 10). This is not to say that subsistence farming
automatically means low total incomes. Pursuance of subsistence agriculture as the
main occupation has a positive correlation with per capita income in the study area.
However, the positive correlation is due to the fact that household heads that have
subsistence agriculture as the main occupation might pursue some secondary
occupation whereas those with other occupations as the main occupation, seldom
have other income generating activities.
As we have seen, 34.4% of the households report to collect park forest products. The
collection of park forest products as an alternative source of income has however, a
significant negative correlation with household per capita income. Households that
collect park forest products are thus more likely to have low per capita incomes.
Membership in village associations normally provides mechanisms for mutual aid
among members. Associations are often established to secure labour, skills, credit as
well as group marketing of agricultural produce. Intuitively, membership in such
associations is expected to have a positive correlation with per capita incomes.
However, results from this study suggest otherwise. This is possibly because the
membership in many of these organisations for various reasons is biased towards the
poor. The poor households join the organisations because they are poor. They hope to
61
have improved economic livelihoods through the tapping of opportunities arising
from membership.
In line with the evidence from previous studies and also emanating from theory,
Table 10 indicates that there is a positive relationship between access to credit and
per capita income; although much of the informal discussions with respondents in
focus group discussions indicated that a substantial part of the borrowed capital is
used to finance consumption and does not go to production and potential wealth
generation.
4.1.4.2 Household external factors
The important household external factors that can influence household per capita
income include location, duration of stay by the household in that area, natural
vagaries resulting in crop failures, and since these households live adjacent to the
park, the distance to the park boundary could also be important. All these factors,
save for duration of stay, have positive but statistically insignificant effects on
household per capita income. The duration of stay in the area is an important factor
that relates to the household’s social capital and ability to access assets such as
financial capital. The longer a household stays in an area the more information and
practical skills it acquires about the surrounding environment placing it in a better
situation to exploit the environment to its benefit.
Summing up on household total income; As regards households’ internal factors, this
analysis has revealed that a household’s income is positively correlated with access
to physical assets, notably land, human capital and livestock portfolios. Access to
credit which households often use during adverse periods for consumption and
production smoothing is also positively correlated with households’ per capital
incomes. On the other hand, factors that are considered external to the household but
which are positive correlates to the households’ per capital income levels include
location, natural vagaries resulting in crop failures and the distance to the park
boundary.
62
4.1.5 A closer look at local heterogeneity and diversification
Communities are typically heterogeneous entities. Households vary in terms of both
internal and external factors. Various income groups use forest resources in different
ways and display varying levels of dependence on the forest. Participatory wealth
ranking and the resulting stratification aimed at capturing this local heterogeneity.
Here the households are divided into three terciles corresponding to the poor,
medium and rich categories that emerged from participatory wealth ranking. The
section then takes a closer look at heterogeneity in terms of household internal and
external factors, and diversification in terms of share income from different
livelihood activities for each wealthy category.
4.1.5.1 Local heterogeneity
Wealth categories differ in terms of household internal and external factors (Table
11).
Household internal factors; Access to land, livestock ownership, education level of
the household head, and the probability for the household head to have a secondary
occupation all show significant increase with wealth. Wealthier households have
significantly larger families but also significantly larger number of workers, and thus
their lower consumer worker ratio observed. On the other hand, the probability for a
household to be headed by a female is significantly lower for wealthier households.
Thus, wealthier households have a better access to assets and are in a better position
to pursue alternative income generating activities. As such, they are more likely to
disregard collection of park forest products which is usually “employment of last
resort”.
Household external factors; There is no significant difference between wealth
categories with respect to membership in associations, receipt of remittances,
number of failed crop seasons, duration of stay and the immigration status. The
overall probability for a household being an immigrant is very low (0.01). Only one
in a hundred households is an immigrant. On the other hand, there is a significant
difference in distance to park boundary. Poorer households live closer to the park.
63
Table 11: Household factors by wealth category, survey, Western Uganda 2005
Wealth category
Household factor Poor Medium Rich Probability Household internal factors Total land accessed in Ha 1.9604 2.983 3.5807 0.000*** Total Livestock Units 0.2976 0.674 1.366 0.000*** Head age 40.327 43.287 42.84 0.239 Household head education in years 4.8464 6.33345 6.46 0.0474** Household size 6.44358 7.4291 8.107 0.000*** Household number of workers 2.7121 3.107 3.49315 0.0011*** Consumer worker ratio 1.6 1.592 1.5263 0.2656 Household head has a secondary occupation (1=Yes) 0.071 0.0952 0.1382 0.0074*** Household got credit within last 4 years (1=Yes) 0.1677 0.2292 0.1533 0.6363 Household headed by female (1=Yes) 0.0535 0.0235 0.0042 0.0105** Household external factors
Household is a member to at least one association (1=Yes) 0.0534 0.0783 0.0832 0.3428 Household received remittance (1=Yes) 0.0205 .0412 .0295 0.544 Number of failed crop seasons within last 4 years 3.4 3.2778 3.198 0.129 Duration of stay 40.121 43.28 42.695 0.1907 Distance to park boundary 1.939 2.193 2.383 0.0118** Household is immigrant (1= Yes) 0.0067 0 0.0042 0.3001
*** = significant at P < 0.01, ** = significant at p < 0.05
Summing up on local heterogeneity; Wealthier households have better access to
assets, lower probability of being headed by females and are more distant from the
park boundary.
4.1.5.2 Income diversification
Wealth categories differ in income sources pursued (Figure 5). Agriculture is the
main source of income for all wealth categories. Remittances contribute the least to
household incomes. On average, environmental incomes contribute more to the
incomes of the poor than the medium while the least contribution is to the incomes of
the rich households. Wealthier households are thus less dependent on the
environment. On the other hand, off-farm incomes contribute more to the incomes of
the rich households than the medium whereas poor households get the least
contribution. As we have seen, wealthier households have better access to assets and
are thus more able to pursue off-farm activities, for which access to assets is usually
a prerequisite. Remittances are not shown on the graph because of very low
64
contribution. Remittances contribute 0.3 percent to the incomes of the poor, and 0.2
percent to the incomes of both medium and rich category households.
74.8 76.5 72.7
23.6 18.317.0
10.11.3 5.0
0%
20%
40%
60%
80%
100%
Poor Medium Rich
Wealth category
Con
trib
utio
n to
tota
l inc
ome
Agricultural Environmental Off-farm
Figure 5: Differences in household dependence on income sources, survey,
Western Uganda 2005
Summing up on diversification; Agriculture is the most important source of income
for the three wealth categories, the importance of environmental incomes decreases
from poorer to wealthier households while the importance of off-farm increases.
4.2 Household constraints to improved livelihood
Household income is often used as a proxy for the household’s livelihood. The above
section has shown household per capita income to be a function of both internal and
external household factors. Any factor that limits the household’s attainment of
higher incomes can be seen as constraining household attainment of better economic
livelihoods. This section looks closer at some of these constraints; the main
constraints and the particular constraints related to households’ proximity to the
national park.
65
4.2.1 Main constraints to improved livelihoods
The major constraints faced by households in their decreasing order of importance
are: land access problems, access to financial capital, access to forest products from
the park and low market prices. Following the household economic model, these are
divided into internal and external household factors.
4.2.1.1 Household internal factors
Land; Land is a primary asset that supports rural livelihoods. From this study, we
see that households derive over 70 percent of their total incomes from agriculture.
Thus land plays a central role in their livelihoods. From the above section, we find
that land is positively correlated with per capita income. In the study area land is
limiting in terms of both quality and quantity. The inherent land shortage problems
are accelerated by the large household sizes indicating high population growth. From
focus group discussions, households with larger families depend more on clan held
lands than do the smaller. Some parcels owned by the clan have suffered from the
“tragedy of the commons” and been degraded. Some are merely kept as scanty
bushes that only provide firewood. There is no restriction as to what amounts of
firewood a household can collect from such lands.
The main way of accessing land is through inheritance. The sub division of land at
inheritance fragments the privately owned land parcels. As a result, households own
scattered parcels of land and acknowledge spending a lot of otherwise productive
time walking to and from gardens and different plots.
The quality of both private and clan owned land parcels has deteriorated due to the
increasing continuous cultivation without fallowing. A majority of the households
(60%) stated that crop yields are declining. Because of the increased population and
the resulting increased food needs, fallowing land is a luxury many households no
longer can afford. Given that many are too poor to buy inorganic fertilisers,
application of organic materials and manure seems the only option. However, people
have little livestock and many of the crops grown do not give much waste. For
example, cassava, the main food and cash crop for many households, has its leaves
66
fed to livestock, the tubers eaten by people and stems used as firewood. The soils are
continuously mined of nutrients. As RMCEMP (2004) notes, the anthropogenic
causes of decline in soil fertility are compounded by unsuitability of the soils for
agriculture. The soils in the area are less fertile than other East African highlands
because they are not volcanic. Given these limitations, people are willing to plant
trees on such lands and in the villages where WWF is piloting landscape restoration,
the response has been positive.
Access to credit; Formal lending institutions are often inaccessible in rural areas.
The main sources of credit are thus often intra and inter-household lending.
Households typically borrow from other households and though some form of
collateral might be required, more often social networks of trust and reciprocity are
more important. Even in instances where a household is asked to provide collateral,
trust is more important as it is only trusted members that will be lent money.
However, the household to household lending is limited by the general shortage of
cash. None of the households sampled reports access to financial capital all year
around. There is thus no assured source of credit throughout all seasons. Lenders are
often relatively wealthy households involved in non-agricultural activities. This
category includes mainly people with some business, regular salary or some park
based activities. The lenders themselves do not have much capital at their disposal,
which limits the amounts of money they can give out and the length of the pay back
period.
Borrowing is mainly done by those households that are solely dependent on
agriculture, but the common feature of all borrowing is that it is often to finance
consumption. Sometimes the borrowed money is spent on paying school fees for the
young members of the household, or to pay for medical bills. Whereas this could be
seen as a form of investment in human capital development, particularly the payment
for education, the benefits are long term and continuously demand money for a
longer period of time. Education as an investment best pays back when one achieves
higher levels of education. Many household members are educated, but only to some
primary level of education. This is only good in the sense that such members can
read and write, but it will rarely afford them better paid jobs.
67
The poor rural households are often caught in a vicious cycle of poverty especially
when they are forced to sell surplus produce at the time of harvest often at low prices
to finance other needs such as medical care, debt repayments or even to buy some
other market products. These households often buy the same produce they sold later
in the season, at much higher prices.
4.2.1.2 Household external factors
Access to park forest products; Local people are formally not allowed to access
national park products. The national park is however an important source of basic
resources such as medicinal plants, many of which are reportedly not available from
outside the national park. Medicinal plants in particular are collected by individual
households for use both at home and by the medicine men for sale as a source of
income. According to UWA regulations, local people are allowed to collect some
resources for subsistence use. However, the local people are not aware of which
products they are allowed to collect and those that they are prohibited. They take it
that they are not allowed to collect any forest product from the park and they regard
whatever they access as illegal. Some households reported that accessibility to some
park products often becomes easier after they have made friends with the park
rangers. It therefore seems important that the local people get to know exactly what
they are allowed to access. This will go a long way in reducing the current people
park conflicts and perhaps ensuring responsible use of the valued resources.
Problems associated with markets; Crops grown for cash generation are coffee,
vanilla, passion fruits, cocoa and garlic. These are bought by middlemen who come
to farmers’ homes. Market for these commodities is always available but the prices
offered are low. Farmers have to take prices given by the middlemen. For some food
crops such as cassava, any surplus is sold at village markets which are accessible, at
an average distance of 4 km, but the prices offered are also usually low. The
government encouraged households to plant Moringa oleifera. Households in
Kasese, Kabarole and Bundibugyo district planted the crop but are now stuck with it,
with no market. The market price for vanilla has also gone down.
68
Summing up on main constraints; Land is a primary asset that supports rural
livelihoods and it is found to be a limiting factor in production, both in terms of low
quality and insufficient quantities. The inherent land shortage problems are
accelerated by the large household sizes and tragedy of the commons problems
associated with clan owned land parcels. The poor are also faced with fragmented
and imperfect output markets leading to low prices for their commodities. The
insecurity that results from prohibiting use of park resources equally makes access to
such resources unpredictable and less economically rewarding.
4.2.2 Constraints associated with living close to the national park
The problems reported by local people associated with living close to the national
park can be divided into three categories based on whether they affect crops,
livestock or people.
The most common problem is crop raiding which is reported by about 96 percent of
the households. Monkeys are reported to be the most damaging crop raider (93
percent) compared to other common crop raiders such as the baboon (26 percent).
Crop raiding is perhaps the most serious conservation cost normally covered by the
local people. It normally takes a big share of the household labour both through the
measures taken to fight crop raiding and the crop losses suffered. The households
report different frequencies of usage for different techniques to fight crop raiders
(Table 11). The use of scare crows is the most frequently reported technique because
the technique saves time. The most time consuming technique is crop guarding.
Guarding is mainly carried out by children but when crops near harvest, even adults
get involved because this is when crop raiding peaks. Crop raiding is a particular
problem as people cultivate up to the park boundary. This increases the crops’
susceptibility to crop raiding, resulting into a people-park conflict which according to
RMCEMP (2003) is responsible for perhaps over 90 percent of the negative attitudes
that people have towards the park. About 18 percent of the households also attribute
some crop diseases to their proximity to the park.
69
Table 12: Techniques used to fight crop raiding, survey, Western Uganda 2005
Technique Frequency % usage
Scare crows 140 45.8 Chasing with stones and/or dogs 93 30.3 Guarding 47 15.4 Traps 19 6.2 Poisoning 7 2.3
The problems for domestic animals are not frequently reported. This could be
because the households do not have much livestock. However, some problems exist.
Most important are ticks (13 percent) from park animals to domestic animals. It is
also believed by 8 percent of the households that park animals are the cause of
animal diseases, 3.9 percent report their domestic animals being attacked by animals
from the park and 0.6 percent lack grazing land. Also, about 14 percent households
report people being attacked by wild animals from the park. This is particularly when
cultivating the parcels adjacent the park and the main victims are women and
children. Culprit animals are baboons and monkeys.
It proved difficult to assess the scale of costs involved but experience from other
studies indicate costs as high as 20 percent of total incomes (Vedeld et al., 2004;
Tweheyo et al., 2005).
Summing up on constraints; Crop raiding is perhaps the main problem faced by most
farm households adjacent to parks with about 96 percent of the households reportedly
being affected. The monkey is reported to be the main raider of crops and farm
households usually spend most of their productive time guarding their gardens from
this vermin. Other problems associated with close proximity to the park include
transmission of diseases from wild animals to domestic animals, while some people
also report attacks from wild animals.
70
4.3 Total environmental income
This section considers the importance of the environmental income to total household
income and how dependency on environmental income varies with total household
income.
4.3.1 Contribution of environmental income to total household income
Agriculture is the main source of income for the rural households around RMNP but
as Table 8 shows, the households also depend on the environmental income, which
contributes 18.6 per cent of total household income. The environmental income is in
form of both cash and subsistence income. The non-park environmental income
constitutes 69.8 percent (191,797 U Shs) of average annual environmental income
and the park environmental income constitutes 30.2 percent (83,145 U Shs). Over 90
percent of the non-park environmental income is from wood fuel where as the park
income is from a diversity of sources. The products from the park are collected
illegally and households in focus group discussions never willingly revealed that they
collect park products. However, when contacted through individual interviews, they
are more willing to discuss these issues.
On the other hand, the non park environmental income includes wood collected from
privately owned land parcels and those parcels owned by the clan. Fire wood
collection is primarily a women’s activity and from this extrapolation one can be
made to conclude that most of the non-park environmental income goes to the
women.
From field observations, medicinal plants are wide spread on peoples’ own lands but
they seem to disregard their importance. Households reportedly depend on the park
for medicinal plants while little efforts seem to be taken to plant the medicinal plant
species from the park to their own land parcels. However, there are variations
expected in patterns of distribution for environmental income between households
with different incomes, due to the inherent variations in the opportunities and
constraints faced.
71
4.3.2 Effect of household income on dependency on environmental income
Literature holds environmental resources as income of the last resort typically
particularly attractive to the poor (e.g. Vedeld et al., 2004; Angelsen and Wunder,
2003). Consequently, dependency on environmental income is expected to decrease
with increasing household total incomes. This is investigated by the relationship
between total environmental income and total household income (Figure 6).
The relationship between total household environmental income and total income is
statistically insignificant (R-sq (Adj) = 0%, p = 0.47; Appendix ii). Removing the
outliers has no significant effect. This means that the total environment income is not
different across income quintiles. But before concluding that income quintiles are
indifferent in dependence on environmental income, let us look at dependence in
relative terms (Figure 7).
Total household income (U Shs)
Tot
al e
nviro
nmen
tal i
ncom
e (U
Shs
)
500000040000003000000200000010000000
700000
600000
500000
400000
300000
200000
100000
0
Figure 6: Relationship between total environmental income and total household
income, survey, Western Uganda 2005
72
Total household income (U Shs)
Rel
ativ
e en
viro
nmen
tal i
ncom
e (U
Shs
)
500000040000003000000200000010000000
70
60
50
40
30
20
10
0
-10
-20
Figure 7: The relationship between relative environmental income and household total income,
survey, Western Uganda 2005
We do find a significant negative relationship between environmental income and
total household income (R-sq (Adj) = 21.7, p = 0.000; appendix ii). Removing the
outliers has no significant effect. The contribution of environmental income to total
household income decreases with increasing total household income. We thus find
that poorer households derive a greater share of their total income from
environmental income compared to “wealthier” households.
Summing up dependency on environmental income; On average, environmental
income contributes 18.6 percent of total household income and two thirds of this
income is from outside the national park. The environmental income contributes
more to the incomes of the poor, although there is no evidence that the poor
households get more environmental income than the wealthier households. This is
also in line with findings from other areas (see Vedeld et al., 2004).
73
4.4 A more detailed analysis of dependence on park environmental income
Section 4.1.4 showed that access to assets together with favourable external
household factors yield higher household per capita incomes. The next section looks
at the collection of park forest products. As noted earlier in the analysis, collection of
these products is considered an illegal activity. From field observations, it is
observed that most of the products collected are for subsistence, which makes their
collection less attractive to households with access to alternative sources of income.
The assumption is that it is the poor households with little access to assets that will
collect park products. This section considers the factors for dependency on park
income, and the distribution of the resulting income by income groups, gender and
location.
4.4.1 Modelling dependency on park income
We analyse factors that impact on collection of park products as a step-wise
procedure using a two step Heckman model (Heckman, 1979). The model recursively
estimates the first step as the probability for a household to participate in the
collection of park products whereas the second step determines factors that impact on
the extent of collection (Table 13) Following the modified household economic
model (Figure 1), the factors are categorised into household internal and external
factors.
4.4.1.1 Household internal factors
The per capita income of the household as earlier mentioned has a significant
negative correlation with the probability of collection of park products. The
probability of collection of park products is thus higher for lower income households.
Access to majority of the national park products is illegal and although UWA
regulations and guidelines allow some consumptive use, local people are not aware
of which products they are allowed to access and not. Collection of any park products
is done clandestine, mainly by those without alternative income opportunities and
also from focus group discussions and interviews this is evident.
“We go to the park because we do not have much choice” was a common
phrase among the respondents.
74
Table 13: Factors determining collection of forest products, survey, Western
Uganda, 2005
Probability of collection
of park forest products Extent of collection of park forest products
Explanatory variables Coefficient T P>t Coefficient t P>t Household internal factors Household per capita income -3.33E-06 -2.11 0.043** 0.000 -1.63 0.113 Total land accessed by household (in Acres)
-0.298 -1.83 0.076* -1.195 -2.98 0.005***
Total land accessed by household squared (in Acres)
0.013 1.59 0.122 0.052 3.72 0.001***
Total Livestock Units -0.204 -1.27 0.212 -0.918 -2.30 0.028** Household head age in years -0.144 -1.59 0.121 -0.394 -1.03 0.311 Household head age in years squared
0.001 1.28 0.210 0.005 1.60 0.119
Household head education in years -0.193 -2.31 0.027** -0.854 -2.46 0.019* Number of females with primary level of education
-0.918 -2.22 0.034** -4.081 -2.79 0.009***
Number of males with primary level of education
0.049 0.16 0.875 -0.150 -0.16 0.872
Number of females with secondary level of education
-1.030 -3.56 0.001*** -4.451 -3.42 0.002***
Number of males with secondary level of education
0.630 1.70 0.099* 2.802 2.04 0.049**
Number of females with above secondary level of education
-1.008 -1.53 0.136 -5.769 -2.46 0.019**
Number of males with above secondary level of education
2.243 1.99 0.055* 9.108 2.38 0.023**
Household size 0.725 1.92 0.064* 2.863 3.78 0.001*** Household number of males -1.001 -3.18 0.003*** -4.436 -3.65 0.001*** Household number of dependants 0.007 0.02 0.985 0.786 0.68 0.501 Household consumer worker ratio -0.971 -0.98 0.332 -5.834 -1.60 0.118 Household headed by female (1=Yes)
0.779 0.86 0.396 4.828 1.67 0.104
Household head has a secondary occupation (1=Yes)
0.169 0.64 0.526 0.806 0.96 0.344
Household is a member to at least one association (1=Yes)
0.063 0.15 0.885 0.723 0.59 0.562
Household primary occupation (1=Subsistence agriculture)
0.286 0.55 0.588 -0.052 -0.03 0.973
Household has received credit within the last 4 years
0.207 0.53 0.600
Household trades (1=Yes) -0.242 -0.46 0.651 -1.278 -0.87 0.393 Household external factors Location dummy: Kasese (1=Yes) 0.066 0.15 0.884 0.671 0.58 0.566 Location dummy: Kabarole (1=Yes) 0.443 1.08 0.289 1.756 1.13 0.266 Duration of stay in the area 0.034 0.44 0.661 0.103 0.48 0.632 Household received remittances (1=Yes)
-0.193 -0.35 0.726 -0.487 -0.36 0.720
Number of failed crop seasons -0.220 -1.19 0.244 -0.604 -1.01 0.318 Distance to the park boundary -0.036 -0.14 0.886 -0.442 -0.69 0.497 Inverse Mills Ratio (IMR) 2.863 1.31 0.200 Constant 5.939 1.63 0.113 30.272 2.11 0.042** Number of observations 148 148 Number of strata 3 3 Number of Primary Sampling Units 36 36 Population size 1187.8 1187.8 F( 29, 5) 342.53 F(29, 5) 72.04 Prob > F 0.000 0.00 R-squared 0.3504 *** = significant at P < 0.01, ** = significant at p < 0.05, * = significant at P < 0.1
75
RMNP is at present managed based on the “fortress approach” and trespassers are
fined heavily. This, however, has not stopped households with low incomes from
collecting the products. However, per capita income is not correlated with the extent
of collection from the park. Once a household has made a decision to collect park
forest products, how much it collects is found to be independent of the household
income. It could be that other factors become much more important than the
household’s per capita income in relation to the park related incomes.
That collection of park forest products is an activity of last resort, pursued by poor
households is further emphasised by the negative correlation between access to
physical assets and extent of collection of park products. Access to land has a
significant negative correlation with both the probability and extent of collection of
park products. Households with poor access to land are more likely to collect park
products and they acquire more park incomes. The probability and extent of
collection of park products do not decline linearly with increasing access to land as
shown by the quadratic function expressing the impact of the square of the land area
accessed by the household.
The total livestock units owned by a household indicate a significant negative
relationship with both the probability and extent of collection of park products. The
extent of collection of park products has a significant negative correlation with
household ownership of livestock. Inferring from the positive and significant
correlation observed between household livestock ownership and household total per
capita income, an extension is made to conclude that households with more livestock
have higher incomes and are thus less dependent on collection of park products.
The age of head of household is negatively correlated with both the probability and
extent of collection of park products. This seems to support what emerged from the
focus group discussions; where it was reported that relatively younger and more
dynamic household heads prefer to engage in alternative employment such as off-
farm work, with some migrating to urban centres for causal or informal employment.
However, the relationship between household age and collection of park products is
not linear as shown by the negative correlation with the square of the household head
age. This may mean that at later stages as the capacity to engage in alternative
76
employment falls, the probability of the household collecting the forest products
increases.
Also, older household heads, up to a certain age, tend to have larger family sizes. The
families are usually extended and many of the household members are grandchildren
and other young relatives who constitute a high dependency burden to the working
members of the household. Lacking alternatives, the household may be forced to
depend more on park resources. Also, it is mainly the old people who collect
medicinal plants from the park as it requires knowledge and experience, which
usually accumulate with age. Medicinal plants are the second most important forest
product collected, after firewood. The high number of households collecting
medicinal pants, many of them headed by old heads could explain this observation.
Medicinal plants are collected both for sale and use at home. As a product for sale, it
is the older household members who know which plant treats which ailment and are
thus the dominant groups collecting plants.
The relationship between education and collection of park products is also gender
specific. Whereas the household’s number of females with primary, secondary and
post secondary education is negatively and significantly correlated with collection of
park products, male education is positively correlated. Female education is
negatively correlated because educated women are more likely to avoid collection of
park products and opt for other alternatives, even in instances where the latter
alternatives might not be as profitable as the collection of park products. Pursuance
of other alternatives is enhanced by the fear especially among women of being
arrested and penalised for collecting park products. On the other hand, the number of
educated male household members is positively correlated with collection of park
products. While this could be attributed to the general lack of alternatives forms of
employment, still with more education, the males are more able to manoeuvre their
way and more easily make connections with park rangers, which could facilitate the
illegal exploitation of park products.
As indicated in Table 13 above, household size has a positive and significant
relationship with the collection of forest products. As earlier discussed, large
households tend to have low incomes and often lack alternatives to feed the usually
77
large numbers of dependants. From field observations, many members in large sized
households were noted to be dependants, constituting a dependency burden.
A household headed by a female increases both its probability and extent of
collection of park products, but the increase is not significant. It could be attributed
to the general lack of alternative sources of income, and low consumer worker ratios
that are more common in female headed than male headed households.
Whether a household’s primary occupation is subsistence agriculture or other does
not have a significant correlation with the probability of the household to collect park
products. However, the relationship is positive for subsistence farmers but negative
with respect to the extent of collection. Subsistence agriculture has some periods of
redundancy and during such periods collection of park products might be utilised.
Membership in associations also increases both the probability and extent of
collection of park products but not significantly. This is contrary to what could be
expected. Membership in associations is expected to be negatively correlated with
collection of park products since membership to associations such as farmer
associations is expected to increase households’ access to better paid alternatives.
However, the most important associations were farmer associations encouraging
subsistence agriculture yet pursuance of subsistence agriculture as the primary
occupation does not significantly change the probability of one collecting forest
products.
Further, access to credit is normally expected to increase household earning
possibilities and thus in this case to be negatively correlated with collection of park
products. However, though not significant, the observed correlation is positive. This
could be because of the nature of the credit received. Credit predominantly finances
consumption and not investment. And it is mainly poor households with low per
capita incomes that get this kind of credit, and it s thus not surprising under these
circumstances that credit access is correlated with collection of park products.
78
4.4.1.2 Household external factors
All household external factors show insignificant correlation but the signs of their
coefficients could be important.
Using dummy location variables, Kasese and Kabarole districts have a positive
correlation with collection of park products whereas Bundibugyo is negatively
correlated. This could be due to the variation in household access to assets in the
three districts. As Table 6 shows, households in Bundibugyo district have better
access to assets that are shown to be positively correlated with per capita incomes.
For example the district has the best access to land (Table 4) and to livestock (Table
5). This could explain Bundibugyo negative relationship, while the lower levels of
access to assets could account for the positive correlation observed for Kasese and
Kabarole districts.
How long households have lived in the area or “the duration of stay adjacent to the
national park” shows a positive correlation with collection of park products.
However, the correlation is not significant. The positive correlation was expected
because the duration of stay is correlated with more experience-based knowledge
about the environment. Households that have lived adjacent the park for long would
more often know which products are useful, where they are located and how best to
collect them with out being seen by the park rangers.
Households were categorised into two categories based on whether or not the
household have received remittances in 2005. Households that receive remittances
are found to be less likely to collect forest products and if they do, they will not
collect as much as the households that do not. This could be because as it turned out,
it is mainly households that are better off that receive remittances. Better off
households manage to educate their members and when away, these members send
money back home. As such, it is households already with high per capita income that
receive remittances and hence the negative correlation observed.
One of the essential roles that forest products are expected to play for rural
livelihoods is gap-filling, especially given that for many rural communities living
79
adjacent to forested areas, insurance and credit markets are seldom available and
when available, there are a lot of variations in households’ access to them. In the
event of natural vagaries such as bad weather that causes crop failure, the rural
households often find themselves short of alternatives.2This suggests a positive
relationship between crop failure and collection of park forest products. To the
contrary, a negative correlation is observed. This suggests that households are
dealing with food shortages in a different way mainly by pursuance of off-farm
activities for cash to buy food. The other explanation could be the restricted access
because the park resources are guarded.
The distance that household members have to walk to and from the park and
especially when loaded with the collected park products, is a factor external to the
household, but might influence the decision to collect forest products. Once the
decision has been made to collect, the distance might influence how much of the
products are collected. Distance increases the cost of transportation. The sample
households live adjacent to the park with an average distance of 2.5 km and
maximum of 6 km. We observe a negative correlation between collection of forest
products and distance is observed. Households living closer to the park have a higher
probability of collecting larger amounts of forest products.
Distances to the markets are usually hypothesised to influence forest dependency.
The hypothesis normally runs that good market access avails better alternative
income opportunities, lowering forest dependency. A notable exception to this is
when households specialise in high-value products, because these as well require
good market access. However, sample villages collect products mainly for
subsistence and there is no much variation in their access to markets. All households
have access to markets. Every village has access to a market place, managed by
individuals who are themselves subsistence farmers. They are open in the evenings
and most of the merchandise is agricultural produce. Also, the agricultural produce is
bought by middlemen who move around the villages on bicycles. Indeed trading in
agricultural produce and selling labour on other peoples’ farms were the most
common off-farm activities pursued. As such, access to markets is omitted from
2 Several studies (e.g. Pattanayak and Sills, 2001) have shown households to make use of the “natural insurance” value forests and collect such products as fruits
80
analyses, because the important market factor is the price. The farmers have no say
on the price of their produce and are in many instances exploited by the middlemen.
However, the lack of significance for household external factors could be explained
by the importance of the park income to the households. As already seen, the park
only provides a third of household environmental income. Two thirds come from
areas outside the park.
Summing up on factors for collection of park products; Park income is mainly
important to large sized households that have low access to land, livestock, low
education, and with low consumer worker ratios.
4.4.1 Distribution pattern of park income
There is a difference in the type and amount of products collected by households
with different incomes by different locations, because of the differences in the
opportunities and constraints at play in the different regions. Also, there is
differentiation in type of products collected by men and women. This section looks
closer at the distribution pattern of park income across these groups.
4.4.3.1 Effect of household income on dependency on park income
From previous studies and theory, poor households depend more on forest incomes
than do wealthier households (e.g. Botha, 2003; Vedeld et al., 2004). This is
investigated in the relationship between total park income and total household non-
park income (Figure 8).
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Total household non-park income (U Shs)
Hou
seho
ld p
ark
inco
me
(U S
hs)
500000040000003000000200000010000000
700000
600000
500000
400000
300000
200000
100000
0
-100000
-200000
Figure 8: Relationship between total park income and total household non-park
income, survey, Western Uganda 2005
There is a significant negative relationship between total household park income and
total household non-park income (R-Sq(adj) = 12.8%, p = 0.000; Appendix iii).
Poorer households thus get more absolute park income than wealthier households.
But before concluding that income quintiles are indifferent in dependence on park
environmental income, let us look at dependence in relative terms (Figure 9).
A linear regression analysis shows a significant negative relationship between
household total income and dependency on park income (R-Sq(adj) = 11.3%, p =
0.000; Appendix iii). Wealthier households do have a lower share of their total
incomes from park income compared to poorer households.
82
Total household income (U Shs)
Rel
ativ
e pa
rk in
com
e
500000040000003000000200000010000000
70
60
50
40
30
20
10
0
-10
-20
Figure 9: Relationship between relative park income and total household
income, survey, Western Uganda 2005
This relationship can be viewed as an egg-chicken problem in that; (i) households
that collect park products are poor because of their dependency on park forest
products, and/or (ii) households collect forest products because they are poor. The
latter seems to be more likely because collection of park forest products in itself does
not cause poverty. Rather, poor households resort to collection of the products as “an
employment of last resort”. In many instances, especially where access is not as
restricted as in national parks, poor households with low or no access to the assets
required to pursue other alternatives often resort to collection of forest products.
Collection of forest products is usually a low-return activity, attractive only to the
poorest households. These findings were also mainly revealed by the respondents in
the informal and focus group discussions.
4.3.2 Gender differentiation of collection of park products
Households typically collect a number of forest products, which contribute
differently to household income (Table 13). Wood products, particularly firewood
contribute most to household income. Collection of the park forest products is
however, often gendered.
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Table 14: Sources of household park income, survey, Western Uganda 2005 Park product Average income (U Shs) % share of
park income
Wood products 35,337 42.5 Mushroom and honey 22,283 26.8 Fruits and handicrafts 12,472 15.0 Medicinal plants 8,481 10.2 Bush meat 4,573 5.5
For communities around RMNP, some products are collected by men and others by
women. At least from the sampled households, collection of firewood is exclusively
by women whereas the collection of timber, bamboo, bush meat and charcoal are
exclusively by men. Honey, mushroom, fibre, fruits and rattan are collected by both
sexes. Collection of medicine and mushroom is to a larger extent by women.
Men dominate the hunting of wild game, collection of timber, bamboo and charcoal
making. Male bias in hunting is not unique to RMNP but a more or less universal
feature across cultures. The reasons are varied but around RMNP, it is reported that
since hunting is illegal, extra care has to be taken so that no word leaks about a
hunting ground. Men say women cannot be trusted with such “classified”
information. The same view is shared by men in Guinea (Leach, 1999). However,
literature shows some rare exceptions where women are part of the hunting party. In
DRC’s Ituri forest, Mbuti men hunt with their women and the benefits are shared
equally (Tshombe et al, 2000). Also, women collect mopane worms in most of the
southern African countries.
Gender differentiation in collection of forest products has been the norm in most
cultures since the hunting and gathering era. Whereas women have continued to
collect products that match their family and household duties, men as the household
heads have tended to pursue those products that generate cash. Firewood, a product
exclusively collected by women, is exclusively used at home whereas the products
collected by men are both consumed at home and sold to earn some cash. This is not
to say that all products collected by women are for use at home. Some are sold and
interestingly, where the products collected by women are sold, 90 percent of the sales
are made by women, 2 percent by men and 8 percent by either. However, decision on
how to use proceeds from such sales are largely made by both the man and woman
84
(54.6 percent). The frequency for women to make decisions on how to use such
monies is reported at a low 6.8 percent whereas for men alone is at 38.6 percent.
4.4.1 Collection of park products by location
The 12 sample villages are from the three administrative districts of Kasese,
Kabarole and Bundibugyo. District boundaries were often made arbitrarily. However,
people in the three districts do show different levels of dependency on the
environment (Table 14). Kabarole derives the largest share of the income from the
environment, followed by Kasese and Bundibugyo. This is true both in absolute
amounts of environmental income earned and in terms of relative environmental
income.
However, in terms of park percentage share of the environmental income, Kasese has
a much higher share than the rest. Park income contributes over half of Kasese’s
environmental income. Despite its highest dependency on environmental income,
Kabarole has the least dependence on the park because of its more fertile soils. With
its poor soils, Kasese households have to depend on the park for most of its
environmental income needs. Bundibugyo reports the least park income most likely
because the main park product is fuel wood and Bundibugyo has more wood tree
cash crops and trees on private lands than Kasese and Kabarole. However, the other
possible explanation for the variation in park dependency is the variation in the
degree of control of access to park resources in the different districts. Where
management is stricter with monitoring and penalising trespassers, less dependency
on park income should be expected.
Table 15: Collection of park products by location, survey, Western Uganda 2005 Location
Income (in Uganda shillings) Kasese Kabarole Bundibugyo
Total income 79,015,000 116,430,000 78,972,900
Environmental income (EI) 12,208,800 23,230,800 10,235,000
EI share (%) of total income 15.5 20.0 13.0
Park income 6,748,800 3,920,800 2,123,000
Park income share(%) of EI 55.3 16.9 20.7
85
A comparison of the products collected reveals the districts to differ in the nature of
products collected (Figure 9). Kasese collects more fire wood than the other two
districts combined. However, Kasese and Kabarole get about the same amount of
non-wood income from the park whereas Bundibugyo collects the least of both
incomes. Bundibugyo collects the least wood income because grows more tree cash
crops, which provide fuel wood, the main wood product collected from the park.
Kasese collects most wood income from the park because it grows fewer tree cash
crops and has less trees on agricultural land whereas Kabarole is able to meet a high
percentage of its wood needs from private lands outside the park because of its fairly
larger share of tree cash crops and trees on private lands, especially those owned by
the clans.
Figure 10: Park income by income type for locations, survey, Western Uganda
2005
Summing up on park dependency; Poor households, who predominantly use park
resources as a safety net, report higher dependence on park products compared to
more wealthy households. Collection of Park Forest products is also found to be
gender specific, for example collection of firewood is exclusively done by women
whereas the collection of timber, bamboo, bush meat and charcoal are exclusively
0
10,000
20,000
30,000
40,000
Kasese Kabarole Bundibugyo Non-wood Wood
Income type
Inco
me
(U S
hs)
86
done by men. Other factors external to the household but which are important for
access to park products include location as measured by the proximity to the park in
relation to the three districts of Kasese, Kabarole and Bundibugyo.
4.5 Relationship between park and non-park environmental incomes
This section investigates the complementary or substitute nature of the relationship
between park environmental income and non-park environmental income.
The environmental income accounts for some essential requirements, although
largely for subsistence, such as firewood. Firewood is collected from both outside
and inside the park. The question is then; do the park environmental incomes
substitute for non-park environmental income or do the two incomes complement
each other?
Non-park environmental income (U Shs)
Park
env
ironm
enta
l inc
ome
4000003000002000001000000
700000
600000
500000
400000
300000
200000
100000
0
Figure 11: Relationship between park and non-park environmental incomes, survey,
Western Uganda 2005
As Figure 11 shows, there is a significant negative correlation between park
environmental income and non-park environmental income(R-Sq(adj) = 7.7%, p =
0.000; Appendix iv). Households that have low non-park environmental income thus
87
depend more on the park income. By extension, the two incomes are substitutes,
which means that availability of non-park environmental income may reduce the
need for households to collect the illegal park products.
The substitute nature of the relationship between dependency on park and non park
environmental incomes means there is a possibility for reduced dependency on the
park if alternative sources of non park environmental income are provided. Emphasis
could be placed on planting of trees, since as we have seen above firewood is the
most important source of environmental income.
Summing up the relationship between the environmental incomes; Households
depend on park income as a substitute when non-park environmental incomes are
less available.
4.6 Environmental income, poverty and income inequality
This section examines the impact of environmental income on poverty and income
inequality. The FGT classes of poverty measures, Gini coefficient and Atkinson index
are first estimated with the total income in order to document poverty and income
inequality levels for the communities. Estimates are then made first without the park
income and second without environmental income. Estimates from the three
procedures are compared.
4.6.1 Effect on poverty
As measured by household per capita income, collection of park products improves
the average income. Using a poverty line of 281,160 U Shs, collection of park forest
products is seen to reduce all the poverty indices (Table 15). The environmental
income as a whole reduces the poverty indices even more than the park income.
Park income leads to a 3.4 percent decline in the incidence of poverty, 4.7 percent
decline in poverty depth and 3.6 percent decline in the severity of poverty. The
respective declines due to environmental income are 13.1%, 10.2% and 6.9%. Since
88
poverty severity attaches higher weights to incomes from the poorest units, the
observed reductions suggest that dependency on park and environmental incomes
improves the well-being of the poorest disproportionately; that is, the gain in poverty
reduction due to dependency on these incomes goes disproportionately to the poorest
households. The relatively stronger impact on poverty depth suggests the dependency
on these incomes to reduce the income gap among the poor whereas a decline in
poverty incidence suggests that the incomes reduce the incidence of household
poverty.
Table 16: Comparison of poverty indices with and without environmental
income, survey, Western Uganda 2005
Pweight: pw Number of observations 180
Strata: wealth Number of strata 3 PSU: village Number of PSUs 36 FPC: fpc Population size 1423
Poverty indices Mean estimate Std Err. 95% Conf. Interval Deff
with environmental income
Poverty incidence 0.552 0.038 0.475 0.629 1.187
Poverty depth 0.147 0.019 0.108 0.186 1.927
Poverty severity 0.061 0.012 0.036 0.860 2.027
without park income
Poverty incidence 0.586 0.044 0.675 1.645 0.496 Poverty depth 0.194 0.028 0.137 0.252 2.796
Poverty severity 0.097 0.022 0.051 0.142 3.547
Without environmental income
Poverty incidence 0.683 0.035 0.613 0.753 1.189
Poverty depth 0.249 0.020 0.210 0.289 1.212
Poverty severity 0.130 0.015 0.100 0.159 1.228
Summing up effect on poverty; Park income and total environmental income reduce
poverty. The welfare of the households could thus be improved by increasing access
to the environmental income.
4.6.2 Effect on income inequality
The Gini coefficient with park income is lower than that of the income distribution
without park income (Table 16). This directly suggests that collection of park
products reduces income inequality. Omission of the park income increases income
inequality by 2.8 percentage points.
89
Table 17: Comparison of income inequality with and without environmental
income, survey, Western Uganda 2005
Inequality Gini coefficient Inequality aversion
e(0.5)
With environmental income 0.377 0.142 Without park incomes 0.405 0.159 Without environmental income 0.373 0.139
Atkinson inequality aversion parameter (e) is incorporated in the estimation of the
income inequality with and without park income. Increases in the parameter as seen
without park income signals increased household intolerance to inequality and the
households attach more weight to income transfers at the lower end of the
distribution and less weight to transfers at the top. However, the increase in the
aversion parameter without park income is low because not many households are
acquiring park income and for those who get, the income is low.
Environmental income as a whole has no significant effect on income inequality and
household intolerance to inequality. This lack of significance is traceable from Figure
6 that shows no evidence for differences on dependency on environmental income
between poor and wealthier households. All households equally depend on the
environmental incomes and thus removal of the income proportionately reduces the
incomes of the poor and the rich, unlike the absence of park income that
disproportionately reduces the incomes of the poor who figure 7 shows to be more
dependent on park income.
Summing up effect on income inequality; Park income reduces income inequality
because it mostly goes to the poor, as compared to the total environmental income for
which there is no evidence for difference on dependency between the poor and
wealthy households.
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CHAPTER V: CONCLUSIONS AND POLICY RELATED SUGGESTIONS
5.1 Conclusions
The underlying objectives of this research have been; to estimate the present
livelihoods for communities adjacent RMNP, examine the constraints faced by
these households in accessing park resources, estimate both household dependence
on, and the relationship between, park and non park environmental income, the
relationship between park and non park environmental income and lastly to
examine the effect of park income on income inequality and general rural poverty.
From the analysis, the results indicate great variations in asset endowments among
communities adjacent to RMNP and we also find that the observed livelihoods
patterns are strongly correlated with the assets. As expected, the majority of wealthy
households have better access to physical and financial capital compared to the poorer
ones. This further accentuates the problem of income inequality driving the very poor
to depend more on environmental and in particular park resources as a safety net and
as a resource of “the last resort”. Access to credit is also very low in the studied area
signalling a binding problem of liquidity constraints in the households’ production
choices. Households in the study area have a mean family size of 4.6 and the average
consumer work ratio is found to be 1.6. School attendance is found to be six years, on
average. This is low and implies low human capital values in terms of skills and
training.
Many of the households have diversified their livelihoods although the majority of
people in the area still largely depend on subsistence production as their main source
of income, contributing up to seventy percent of their incomes.
Households’ attainment of improved economic livelihoods is further constrained by
several factors, some of which are general in nature while others are related to their
proximity to the park. They include crop raiding by the park’s resident fauna which
destroys crops disrupting households’ output levels further worsening their poverty
91
levels. The park’s fauna is also reported to attack domestic animals, children and
women and spread diseases to livestock and humans. The other constraints include the
decline in quality of land due to over-cultivation, poor access to assets especially
financial capital, low market prices of agricultural produce, and the denial of access to
park forest products. All these constraints combine to make the poor rural households’
livelihoods less viable, at times leading to park-people conflicts that of recent have
become quite frequent among the communities adjacent RMNP.
As regards the indicators of rural poverty levels in the study area, the average per
capita income is estimated 302,530 U Shs which is above the adjusted national
poverty line of 281,160 U Shs. This could suggest good household well being, which
is far from the truth, given the high income inequality of 37.7 percent. Poverty is high
and 55 percent of the population live below the national poverty line. This is higher
than the estimated national rural poverty level of 41.1 percent. Regression results on
income versus household factors indicate that the per capita income is positively
correlated with ownership of livestock, education, and consumer worker ratio, access
to credit, household adult equivalents and pursuance of a secondary occupation. It is
however; negatively correlated with household head age, household size, number of
dependants, female headed households and collection of park forest products.
In areas of high poverty incidence, households tend to rely on environmental incomes
as a survival strategy of last resort. Despite the restricted access to the park, the poor
households still engage in collection of park products and their per capita incomes
show a high correlation with park and forest activities. Additionally, their share of per
capita park income is found to be decreasing from the lowest to highest total per
capita incomes. On average, park income contributes 8.6 percent to household per
capita income and it is mainly important to large sized households that have low
access to land, livestock, low education, and with low consumer worker ratios.
Household per capita income decreases as one gets closer to the park. Park boundary
households are thus poorer.
92
In terms of gender, location and income levels, the study reveals that collection of
park forest products is gender specific, location determined and categorically different
among income groups. For example, collection of firewood is exclusively by women
and collection of bush meat, timber, bamboo and charcoal making are the domain of
the males. Honey, mushroom, fibres and rattan are however collected by both sexes.
On the other hand, households headed by females are more likely to collect park
products possibly because of their usual lack of alternative sources of income and the
low consumer worker ratio. The district of Kasese collects more park products than
the rest and the most important products collected are wood products, particularly
firewood by the women. The poor display a greater level of dependence on park
income than the rich but there is no evidence for difference in dependence on the
environmental income between the poor and wealthy households. Park income and
non-park environmental income are used as substitutes.
In its role as a source of income to the poor, park income impacts on income
inequality and poverty. As measured by the Gini coefficient, park income reduces
income inequality by 2.8 percentage points and as measured by the Atkinson index,
park income reduces household intolerance to inequality by 1.7 percentage points.
The income reduces the incidence of poverty by 3.4 percent, the depth by 4.7 percent
and severity by 3.6 percent. It is evident that collection of these products diminishes
poverty as measured by FGT class of poverty measures and the income inequality as
shown by the Gini coefficient and Atkinson’s index. However, the impacts are small
as shown by the small percentage changes. Park incomes can thus hardily provide for
any pathway out of poverty. They are as such not as important for poverty reduction
as for prevention. They may, however, help prevent households from falling deeper
into poverty. This does not make a general case for all forest environmental incomes
because the limited contribution of the park products could in this respect be due to
the restricted access. In light of the above, policy interventions are necessary in
relation to poverty alleviation, park dependence and rural development.
93
5.2 Policy suggestions
From the above, we see that the poverty levels in the communities adjacent RMNP
are high. Especially the poor households depend on the park income as an
“employment of last resort”. Rural development if steered has the potential to remove
households from the poverty levels seen, reduce their dependence on the national park
and thus contribute towards conservation of the Rwenzoris. Poverty reduction,
reduced dependency on the park and thus its conservation are thus three interrelated
goals that could be jointly pursued and the following suggestions are made.
Since households inherently have low access to assets and off farm employment
opportunities, efforts could be made to improve on this. Particularly, putting in place
policies that would help ameliorate the constraints that hinder the proper functioning
of labour and land markets may go along way in enhancing households’ levels of
productivity and incomes. Access to credit could further be improved by
establishment of micro credit institutions and loan schemes that are tailored to
benefiting the rural people. The approach by Uganda’s Plan for Modernisation of
Agriculture that requires the local people to demand for themselves the services they
need, seem not to be appropriate in such areas where the local farmers have numerous
limitations and may not actually discern exactly what to demand for. From a policy
standpoint, this approach could be modified in lieu of the existing problems and
escalating poverty so as to target the core rural poor population in this study area and
else where in the country with similar problems. This would further contribute to
poverty reduction in rural areas by creating clear path ways out of poverty and capital
accumulation.
The poverty alleviation gains from park activities are minimal. Park incomes can thus
hardly provide pathways out of poverty. Since they are the only incomes of last resort
pursued by the poor, creation of alternative sources of income will not only help
alleviate poverty but will also reduce park dependence. The area around the park
seems conducive for fruit growing, especially passion fruits as evidenced from current
production, which is at present only threatened by diseases. The local people could be
organised into groups and assisted with inputs to grow crops such as fruits and also be
94
assisted with market procurement since low market prices are already a big constraint
to improved economic livelihoods in the area.
Although RMCEMP is still at the trial phase of its land restoration programme, efforts
could be made now and in the future to focus more on tree planting in Kasese district
because the district is much more dependent on the park for wood products than other
areas. Up to 50 percent of the park income in Kasese is wood income. Since fuel
wood is the most sought after product, preference could be given to fast growing trees
and care be taken to involve women because they are the most affected as they have
to collect firewood. Since female headed households are more likely to result into low
per capita incomes and high dependency on park products, gender specific policies
that target women would be warranted in order to reduce their heavy dependence on
park resources by enabling them other alternative forms of energy and income
generation.
Collection of park products is mainly carried out by the poor. Efforts to reduce park
dependency could thus be biased towards the poor. Since these will often be poverty
alleviating, this is appealing even from an ethical view point. Present restoration
programmes by RMCEMP could thus be biased towards the poor by providing them
some more facilitation to afford them caring for the trees. Tree growing is an
expensive venture, with high immediate costs and benefits in the future. With the poor
people’s preference of current consumption to future consumption, the poor will not
plant trees unless assisted, and will continue to exert pressure on the park.
Crop raiding could be addressed by planting the lands adjacent the park with crops
that are not palatable to the park’s fauna. Explorations could be made so as to identify
such crops. It should be ensured that the crops are useful to the people as a source of
income. This could be a welcome idea because the communities adjacent to the park
currently have limited access to sources of cash income. Transparent sharing of
benefits with the local people should be effected and some education campaigns could
be started to discourage usage of traps and poison in the fighting of crop raiding.
95
Households’ persistent illegal access to park resources despite heavy penalties is
indicative of the central role the resources play in their livelihood. Increased
patrolling, more severe penalties, and law enforcement alone are unlikely to protect
the park because they provide no alternative sources of essential resources such as
firewood and medicinal plants. The signing of resource use agreements will provide
for managed and planned use of the park resources, directly benefiting the people and
the park. Besides, efforts need to be made to communicate to the people what they are
allowed to access and what they are not allowed.
With regard to the ongoing Rwenzori Mountains Conservation and Environmental
Management Project, from this study it is suggested that;
• The project enhances sources of non park environmental incomes; for example
through encouraging on-farm planting of trees and medicinal plants.
• In liaison with UWA, the project could discourage usage of traps and poison
to fight crop raiding and effect compensation schemes.
• The piloted landscape restoration programme could consider multipurpose
trees that can contribute towards land restoration and provision of forest
products.
• The planting of trees could concentrate more in Kasese, and target the poor
households who seem to be more dependent on the park.
• The project’s proposed training of the community on proper agronomic
practices could start as soon as possible.
• Efforts could be made to avail opportunities for off-farm incomes
96
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Appendix I: Household questionnaire
Questionnaire number …………. Date of interview ……… Name of interviewer …………… Village …………………. Parish …………………………… Sub-county …………….. Wealth class ……………………. Tribe …………………… I. Basic household information
HH members
Sex Relationship with hh heada
Age Educationb Primary occupationc
Secondary occupationc
Other occupation(s)c
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11. aRelationship with hh head codes 1=hh head; 2= wife; 3=Child; 4=Dependant; 6=Labourer; 7=Others (specify) bEducation: formal education in years, or fill in the level cOccupation codes: 1 = prodn/sale of crops; 2 = prodn/sale of livestock & its products; 3 = Beer brewing; 4 = Agricultural input trading; 5 = Carpentry/lumbering; 6 = Crafts & arts; 7 = trading in agricultural output; 8 = shop keeper; 9 = Brick making/stone quarrying; 10 = service provider (e.g bar); 11 = charcoal burning; 12 = Salary employment by gov’t; 13 = Salary employment by NGO, CBO; 14 = Sell bushmeat; 15 = Casual labourer; 16 = Remittance income; 17 = Tourist guide;
1.2 How long has your family lived here? 1.3 Where did your family live before
a) Within the park c) Else where (specify) b) With in the district
1.4 If question 1.3 applies, why did you move to here? In search for; a) Land for cultivation c) Fertile soils b) Pastures for grazing d) Others specify
1.5 Observe the main house & tick as appropriate Roofing materials: Iron sheets ……. Grass ….. Others specify ………. Walls: Bricks ………… Mud & wattle ….. Others specify …..
Floor: Cement ………. Mud ……… Others specify …… II. Park/Forest products
2.1 How far is it from your home to the park boundary? 2.2 Do you or any member of the household collect any product(s) from the park?
a) Yes b) No 2.3 If yes do you face any problem(s) collecting the products from the park?
a) Yes b) No If no, go to 2.8 2.4 If yes, which problems?
…………………………………………………………………………………Do you collect any similar products from outside the park? a) Yes b) No
2.5 And do you face any problems collecting those products?
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a) Yes b) No 2.6 If yes, which problems?
…………………………………………………………………………………What do you do in times when you cannot access park products? …………………………………………………………………………………Apart from collecting forest products, do you get any other benefit from the park?
2.7 If yes, which one(s)? …………………………………………………………………………………Could you please recall the amounts of forest products you have collected from and outside the park and how they have been utilized? (Refer to tables 2.1 & 2.2 below).
Table 2.1: Forest products collected from the park during 2005 and how they were disposed
Item Local Unit
Own harvested units sold annually
Own harvested units consumed weekly
Price/ unit
Where sold a
How far from home
Rank b
Yams Heap Bamboo shoot
Bundle
Mushrooms Basket Wild honey Litre Afromamum Heap Passion fruit Heap Guava Heap Mango Heap Jackfruit Head Pawpaw Head Palm nut (oil) Basket Wild Coffee Kg Small wild animals:
Rats Piece Rabbits Piece Duiker Piece Primates Piece Snakes Piece Porcupine Piece Guinea fowl Piece Francolin Piece Other Large wild animals:
Big Antelope Piece Hippo Piece Buffalo Piece Other products:
Building Poles
Piece
Timber from forest
Grass for thatching
Bundle
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Rattan Bundle Bamboo Bundle Sand Heap Clay Heap Stones Heap Other Large carpentry items
Item
Small carpentry items
Item
Medicinal plants
Kg
Mats/woven goods
Item
Handicrafts Item Firewood Bundle Charcoal Sac a1= Onfarm; 2 = Nearest trading centre; 3= Rural market; 4= Nearest town market; 5= Local buyer; 6 = on roadside; 7= Retail shop bHow do you rank the above products in order of importance (1 being the most important)
2.10 In this household, which products are collected by
Men …………………………………………………………………………. Women ………………………………………………………………………
2.11 Who sells the products collected by the women? …………………………... 2.12 Who makes decision on how to use money from such sales? ……………… 2.13 How do products fluctuate within and between years?
………………………………………………………………………………… 2.14 What do you do in times when you cannot access those products?
………………………………………………………………………………… III: Information on land tenure, use and productivity
3.1 Do you have access to land? 3.2 If yes, how many parcels and what are their particulars? Household land assets Parcel #
1 Parcel # 2
Parcel # 3
Parcel # 4
Parcel # 5
Parcel # 6
Size Year acquired How acquireda Have formal title to parcel
Land rights statusb A land parcel is here defined as a contigous piece of land that has a common owner, land rights and tenure status. a Acquisition codes: 1= Purchase 2= leased in for fixed payment 3 = sharecropped in 4 = Borrowed 5 = Received
as a gift/inheritance 6 = others specify b 1= freehold (mailo); 2= Unregistered freehold; 3 = Freehold with formal title; 4 = Leasehold; 5 = Customary
(freehold); 6 = Customary (public); 7 = Squatter; 8= others specify
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3.3 What problems did you have with your crops last season? a) Drought d) Landslides b) Vermin e) others (specify) c) Diseases
3.4 How many seasons have you had poor yield in the last 4 years? …………. 3.5 In the table below, please fill the livestock and poultry assets as indicated Livestock and Poultry assets
Animal type
# begin of yr
Total value
Sold Died Slaughtered Given out
Bought Received End of yr #
Total value end of yr
Cows Bulls Calves Goats Sheep Pigs Chicken Turkey Duck Others
3.6 What were the different associated costs of production? Livestock Associated cost Cost value 1. …………….. ……………………………………. ……………… 2. …………….. ……………………………………. ……………… 3. …………….. ……………………………………. ………………. 4. …………….. ……………………………………. ……………… 5. …………….. ……………………………………. ………………. 3.7 In the table below, please fill products’ information as indicated
Average production of livestock products in 2005
Product amount Unit Value Costs Net income
Milk from cows
Milk from goats
Eggs from chicken
Animal Manure *
Others *Is it sold, used on own farm or battered? If bartered, what is the value of the good bartered with?
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3.10 In the table below, please fill details relating to production as indicated
Crops and agricultural products produced during 2005 and how they were disposed
Item Annual income from own produce/ labour
Weekly consumption of own produce
Where sold a
Local Unit
Total annual harvest
Units Sold/received
Units Consumed
Average Price per unit
Crop Income Coffee Tin Tea Kg Cocoa Kg Tobacco Beans (dry) Kg Staple Food (starches, maize matooke etc):
1 2 3 4 Vegetables: 1 2 3 4 5 Fruits: 1 2 3 4 5 Tree Crop Income 1 2 3 4 Woodlot poles: 1 2 3 4 Charcoal Sac Moringa Kg Honey Kg Medicine Wage Labour Unskilled Agricultural/seasonal labour
Other employment Skilled/regular employment
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Crafts and small scale enterprise
Beer Jerry can
Waragi Litre Sale of crafts Item Trading goods Miscellaneous cash income
Private Cash gifts/donations received
Private non cash gifts received
Total gifts received
a 1= Onfarm; 2 = Nearest trading centre; 3= Rural market; 4= Nearest town market; 5= Local buyer; 6 = on roadside; 7= Retail shop ** Make sure you get information on vegetables usually grown close to the homestead
What were the different associated costs of production? Crop Associated cost Cost value 1. …………….. ……………………………………. ……………… 2. …………….. ……………………………………. ……………… 3. …………….. ……………………………………. ………………. 4. …………….. ……………………………………. ……………… IV: Constraints to the local people
4.1 What problems do you face because of living close to the park, in relation to Crops ………………………………………………………………………………… Animals ……………………………………………………………………………… People ………………………………………………………………………………… 4.2 If crop raiding is a problem, what are the frequent raiders? ………………………………………………………………………………… 4.3 What crops do they raid? ………………………………………………………………………………… 4.4 How do you fight crop raiding? ………………………………………………………………………………… 4.5 What impact has the conversion from forest reserve to national park had on
the above problems? ………………………………………………………………………………… 4.6 What constraints do you face in relation to improving your livelihood and how
would you rank them in importance
Constraint Tick if applicable Rank Capital Access to resources Market access Market prices Labour Political insecurity Others
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4.7 Have you received any formal credit in the last 4 years?........... 4.8 If yes, from who and what did you use as collateral?..................................... 4.9 Name 4 most important association(s) that the household belongs to and show its involvement in decision making regarding the affairs of the association?
Association activity Involvement a
a 1= Very active 2 = somewhat active 3 = not very active V: Remittances 5.1 Do you have children or relatives not living with you? ...….. 5.2 If Yes, do they send money to you?....... 5.3 If yes, how much do they send each month? For retired officers, ask if they get pension funds and indicate the amount each month
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Appendix II: Variation in dependence on environmental income by total
household income
Regression Analysis: Relative environmental income versus Total household income The regression equation is
Relative env. income = 31.83 - 0.000011 Total household income
S = 11.7033 R-Sq = 22.2% R-Sq(adj) = 21.7%
Analysis of Variance
Source DF SS MS F P
Regression 1 6781.3 6781.25 49.51 0.000
Error 174 23832.4 136.97
Total 175 30613.6
Regression Analysis: Total environmental income versus Total household income The regression equation is
Total environmental income = 184078 + 0.01089 Total household income
S = 116818 R-Sq = 0.3% R-Sq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 1 7.16377E+09 7.16377E+09 0.52 0.470
Error 174 2.37447E+12 1.36464E+10
Total 175 2.38164E+12
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Appendix III: Variation in dependence on park income by total household
income
Regression Analysis: Relative park income versus Total household income The regression equation is
Relative park income = 17.55 - 0.000008 Total household income
S = 12.2884 R-Sq = 11.9% R-Sq(adj) = 11.3%
Analysis of Variance
Source DF SS MS F P
Regression 1 3534.1 3534.11 23.40 0.000
Error 174 26275.0 151.01
Total 175 29809.2
Regression Analysis: Total park income versus Total non-park income The regression equation is
Total park income = 157030 - 0.06898 Total non-park income
S = 109305 R-Sq = 13.3% R-Sq(adj) = 12.8%
Analysis of Variance
Source DF SS MS F P
Regression 1 3.20181E+11 3.20181E+11 26.80 0.000
Error 174 2.07889E+12 1.19476E+10
Total 175 2.39907E+12
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Appendix IV: Relationship between park and non-park environmental income Regression Analysis: Park environmental income versus non-park environmental income The regression equation is
Park env. income = 136877 - 0.5115 non-park env. income
S = 112460 R-Sq = 8.3% R-Sq(adj) = 7.7%
Analysis of Variance
Source DF SS MS F P
Regression 1 1.98448E+11 1.98448E+11 15.69 0.000
Error 174 2.20062E+12 1.26472E+10
Total 175 2.39907E+12