TREE SPECIES DIVERSITY AND THEIR CARBON SEQUESTRATION POTENTIAL
ON CULTIVATED FARMS IN AGAGO DISTRICT
BY
ODERA ALFRED
BSc WST (Mak.)
REG NO 2012/HD02/83U
STUDENT ID: 203000994
A DISSERTATION SUBMITTED TO DIRECTORATE OF RESEARCH AND
GRADUATE TRAINING IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE AWARD OF THE DEGREE OF MASTER OF SCIENCE IN
AGROFORESTRY OF MAKERERE UNIVERSITY
FEBRUARY 2021
1
DECLARATION
I, Odera Alfred, do hereby declare that the dissertation is entirely my own original work and that
it as not been submitted before to any other university or institution of higher learning for any
award.
Signature...............................................................Date......................................................................
Supervisors’ Approval
This dissertation has been submitted for examination with the approval of the following
Supervisors:
Date…………………………
Signature:
Assoc. Prof. John Bosco Lamoris Okullo
Department of Forestry, Biodiversity & Tourism.
Signature:
Date: ........................................
Dr. Daniel Waiswa
Department of Geography, Geo-Informatics and Climate Sciences.
i
DEDICATION
I dedicate this work to my late father Okello Oakley Ceaser, wife Atimango Angeline Olwoch
and my beloved children Pizzi Darah Odera and Damian Deron Odile.
ii
ACKNOWLEDGEMENT
I am indebted and grateful to my supervisors Assoc. Prof. John Bosco Lamoris Okullo and Dr.
Daniel Waiswa for their dedication and guidance throughout the process of this study.
I thank my wife Atimango Angeline Olwoch for her positive attitude towards my studies and the
financial support she offered me during this study.
I am so grateful to my friend Omara Emmanuel for offering me financial support for data
collection. I also thank Okello Kibombo Bazilio, Komakech Richard and Okidi Sunday for
assisting me in data collection.
iii
TABLE OF CONTENTS
DECLARATION ............................................................................................................................. i
DEDICATION ................................................................................................................................ ii
ACKNOWLEDGEMENT ............................................................................................................. iii
TABLE OF CONTENTS ............................................................................................................... iv
LIST OF TABLES ........................................................................................................................ vii
LIST OF FIGURES ..................................................................................................................... viii
LIST OF ACRONYMS ................................................................................................................. ix
ABSTRACT .................................................................................................................................... x
CHAPTER ONE: INTRODUCTION ......................................................................................... 1
1.1 Background ............................................................................................................................... 1
1.2 Statement of the Problem .......................................................................................................... 2
1.3 Aim and Objectives of the Study ............................................................................................. 2
1.3.1 Aim ........................................................................................................................................ 2
1.3.2 Specific Objectives ................................................................................................................ 2
1.4 Justification ............................................................................................................................... 2
1.5 Conceptual Framework ............................................................................................................. 3
CHAPTER TWO: LITERATURE REVIEW ............................................................................ 5
2.1 On-farm Tree Species Diversity ............................................................................................... 5
2.2 Factors Influencing Retention of Trees On-farm ...................................................................... 7
2.3 Amount and Variation of Carbon Sequestered by Trees On-farm............................................ 8
2.3.1 Estimation of Carbon Sequestered by Trees On Farm ......................................................... 10
2.3.2 Variation of carbon sequestered by trees on farm................................................................ 13
iv
CHAPTER THREE: STUDY AREA AND METHODS ......................................................... 15
3.1 Study Area .............................................................................................................................. 15
3.1.1 Location ............................................................................................................................... 15
3.1.2 Vegetation ............................................................................................................................ 16
3.1.3 Climate ................................................................................................................................ 16
3.1.4 Soils and Topography .......................................................................................................... 16
3.1.5 Population and Economic Activities ................................................................................... 16
3.2 Methods................................................................................................................................... 17
3.2.1 Research Design................................................................................................................... 17
3.2.2 Sampling Procedure and Size ............................................................................................. 17
3.2.3 Plot Establishment and Layout ............................................................................................ 18
3.2.4 Data Collection Procedures.................................................................................................. 18
3.2.5 Data Analysis ....................................................................................................................... 19
CHAPTER FOUR: RESULTS .................................................................................................. 24
4.1 On-farm Tree Species Diversity ............................................................................................. 24
4.1.1 On-farm Tree Species Abundance ....................................................................................... 24
4.3.2 On-farm Tree Species Diversity .......................................................................................... 26
4.2 Factors Influencing Retention of Trees On-Farms ................................................................. 29
4.3 Amount and Variation in Carbon Sequestered by Trees On Farm ......................................... 32
4.3.1 Amount of Carbon Sequestered by Trees On Farm ............................................................. 32
4.4.2 Variation in Carbon Sequestered by Trees On Farm ........................................................... 34
CHAPTER FIVE: DISCUSSION .............................................................................................. 38
5.1 On-farm Tree Species Diversity ............................................................................................. 38
5.1.1 On-farm Tree Species Abundance ....................................................................................... 38
v
5.1.2 On-farm Tree Species Diversity .......................................................................................... 39
5.2 Factors Influencing Retention of Trees On Farm ................................................................... 40
5.3 Carbon Sequestered by Trees On Farm .................................................................................. 41
5.3.1 Amount of Carbon Sequestered by On-farm Trees ............................................................. 41
5.3.2 Variation in the Amount of Carbon Sequestered by On-farm Trees ................................... 43
CHAPTER SIX : CONCLUSIONS AND RECOMMENDATIONS ..................................... 44
6.1 Conclusions ............................................................................................................................. 44
6.2 Recommendations ................................................................................................................... 45
REFERENCES ............................................................................................................................. 46
APPENDICES ............................................................................................................................. 56
Appendix 1: Tree Inventory Form ................................................................................................ 56
Appendix 2: Wood Density Values .............................................................................................. 57
Appendix 3: Retention of On-Farm Tree Species Questionnaire ................................................ 58
Appendix 4: Socio-Economic and Demographic Characteristics of the Respondents ................. 61
vi
LIST OF TABLES
Table 1: On-farm tree species (Retained during farm establishment, protected to allow natural
regeneration and planted) abundance .............................................................................. 25
Table 2: On-farm tree species (Retained during farm establishment, protected to allow natural
regeneration and planted) diversity ................................................................................. 27
Table 3: Factors influencing the retention of trees on farm (n=60) .............................................. 29
Table 4: Factors influencing retention of on-farm tree species (n=390) ...................................... 30
Table 5: Chi-Square Tests of influence of the need for biomass energy for households on
retention trees on farm ..................................................................................................... 31
Table 6: Crops integrated with trees on-farms (n=60) .................................................................. 31
Table 7: Amount of carbon sequestered by on-farm trees (tCO2/ha) ........................................... 32
Table 8: Analysis of variance for on-farm tree species carbon sequestration potential as a
function of different on-farm tree species ....................................................................... 33
Table 9: Analysis of variance for on-farm tree species carbon sequestration as a function of onfarm tree species in different Dbh categories, on-farm tree species abundance and
diversity, on-farms and geographical locations ............................................................... 36
Table 10: LSD of mean comparisons of amount of carbon sequestered by different on-farm tree
species groups.................................................................................................................. 36
Table 11: Analysis of variance for on-farm tree species carbon sequestration as a function of onfarm tree species richness and composition .................................................................... 37
vii
LIST OF FIGURES
Figure 1: Conceptual Framework showing the linkage between integration of trees on-farm to
tree species diversity and their carbon sequestration potential ........................................ 4
Figure 2: Map of the study area (Agago District, Northern Uganda) ........................................... 15
Figure 3: Farm with mature pure stands of Vitellaria paradoxa ssp. nilotica in Tekulu Village,
Lukwaongole Parish, Patongo Sub-county .................................................................... 24
Figure 4: On-farm tree species naturally regenerating in an intercropped farm in Labworyemo
South Village, Kal Parish, Patongo Sub-county ............................................................ 28
Figure 5: On-farm tree species richness, evenness and abundance .............................................. 28
Figure 6: Mean carbon sequestered by on-farm tree species (Retained during farm establishment,
protected to allow natural regeneration and planted) ..................................................... 34
Figure 7: Mean carbon sequestered by each on-farm tree species (Retained during farm
establishment, protected to allow natural regeneration and planted) ............................. 35
viii
LIST OF ACRONYMS
AGB
:
Above Ground Biomass
AGCS
:
Above Ground Carbon Sequestration
ANOVA
:
Analysis of Variance
BGB
:
Below Ground Biomass
BGCS
:
Below Ground Carbon Sequestration
C
:
Carbon
CO2
:
Carbon dioxide
Dbh
:
Diameter at Breast Height
FAO
:
Food and Agricultural Organisation
GPS
:
Global Positioning System
IAASTD
:
International Assessment of Agricultural Knowledge, Science and
IPCC
:
Intergovernmental Panel on Climate Change
LSD
:
Least- Significant Difference
NBS
:
National Biomass Study
Technology for Development
UBOS
:
Uganda Bureau of Statistics
UNDP
:
United Nation Development Programme
ix
ABSTRACT
On-farm tree species retention usually results in maintenance or increase of tree diversity and
carbon sequestration. This study evaluated the contribution of integrated on-farm trees to tree
species diversity and carbon sequestration potential in Agago District. The specific objectives
were to: assess on-farm tree species diversity, examine factors influencing retention of on-farm
tree species and determine amount and variation of carbon sequestered by trees on-farms.
Multistage sampling procedure based on administrative structure was used to select the
respondents from which 60 cultivated farms with tree species retained in them were randomly
selected. Each of the sampled cultivated farms was measured and then divided diagonally into
approximately four equal sub-units. In each sub-unit a 10 x 10 m plot was demarcated by placing
pegs at each corner. Semi structured questionnaires were used in household (HH) surveys while
checklists were used during Focus Group Discussions (FGDs) and Key Informant Interviews
(KIIs). Transect walks with counts of on-farm trees were then carried out to ascertain diversity of
trees on each farm. During on-farm tree species inventory, tree diameter at breast height, height
and crown diameter were measured on each encountered tree. HH survey data were analyzed
using SPSS statistical packages. On-farm tree species inventory was conducted and total number
of trees and each tree species encountered were recorded and used to determine on-farm tree
species abundance and diversity in MS Excel Spread Sheet. Shannon Wiener Index was used to
compute on-farm tree species diversity. Descriptive statistics were then summarized into
frequencies and One-way ANOVA conducted to examine variations. Majority of on-farm trees
were derived from retention during farm establishment and protection to allow natural
regeneration after farm establishment. On-farm tree species diversity was relatively high (2.836)
with up to 26 trees species documented. Factors which influenced retention of on-farm tree
species were need for biomass energy, food security, household income generation, farm
boundary markings/land tenure security and wind breaks. While Vitellaria paradoxa ssp. nilotica
was the main multipurpose tree species retained for provision of food/household income,
Combretum collinum and Piliostigma thonningii were retained for biomass energy. Potential onfarm tree species carbon sequestration was between 6.50tCO2/ha for Piliostigma thonningii to
183 tCO2/ha for Ficus ovata. There was a significant variation in the amount of carbon
sequestered by different individual on-farm tree species (P≤0.05). Potential carbon sequestration
varied significantly in different tree species by Dbh categories (P≤0.05). Results of such a study
would be useful in designing and developing sustainable on-farm tree-based technologies like
retention of trees in crop fields and on-farm boundaries as a way of maximizing carbon
sequestration by trees resilient to environmental changes and attaining more sustainable socioeconomic and ecological benefits of on-farm trees. Farmers should also be trained on Forestry
Business Development skills to promote marketing of on-farm fruits and associated products as
opposed to other non-fruit tree species products (Fuel wood and construction materials). This
should be done by farmers being undertaken through a process of forming forestry business
organisations and provision of forestry business management advisory services at local levels.
Key words: Carbon, diversity, Indigenous Trees, Natural Regeneration, Retention
x
CHAPTER ONE
INTRODUCTION
1.1
Background
Tree species integration on smallholder farms is a common practice in the tropics (Nobel &
Dirzo 1997; Zomer et al., 2014). Uganda is one of the countries in the tropics of Sub-saharan
Africa where trees are retained on-farms by farmers in all its regions. The process of on-farm
tree species integration by farmers involves retention of tree species before farm establishment,
tolerance of natural tree species regeneration after farm establishment (Okullo & Waithum,
2007; Ordonez et al., 2013) and active planting of selected tree species (Eswaran et al., 2006;
Okullo & Waithum, 2007; Ordonez et al., 2013).
On-farm tree species integration contributes to tree species abundance and diversity of particular
tree species on-farms (Okullo Waithum; Boffa et al., 2008; Gwali et al., 2015) and carbon
sequestration (Albrecht & Kandji, 2003; Montagnini & Nair, 2004; Nakakaawa & Vedeld,
2009). This is due to the fact that the retained trees can contribute a significant carbon pool
thereby playing a greater role in carbon sequestration (Albrecht & Kandji, 2003; Montagnini &
Nair, 2004). Carbon sequestration is a process of removing carbon from the atmosphere and
depositing it in a reservoir. It entails the transfer of atmospheric CO2 and its secure storage in
long-lived pools (Nair et al., 2009).
Integration of trees on-farms can add aboveground carbon storage capacity through a broader
diversity of living forms, including various tree species and/or perennial crops (Henry et al.,
2008). This makes understanding the relationships between tree species diversity and biomass
storage very important in attempts to maintain the carbon stocks in tree-based system over a long
term for maximization of carbon sink (Srivastava & Vellend, 2005).
Accordingly, an assessment of tree abundance/diversity and quantification of carbon sequestered
by on-farm tree species is important in the development of appropriate agricultural systems
which promotes sustainable management of on-farm tree species for carbon sequestration
(Richard et al., 2014).
1
1.2
Statement of the Problem
While retaining trees on-farm is based on farmers’ knowledge of tree management, factors
influencing their retention on-farm have not been linked to farmers’ knowledge of tree
management (Abrefa et al., 2013). Even if on-farm trees can contribute significantly to carbon
sequestration, they have been given little attention as a potential carbon sink (Albrecht & Kandji,
2003; Montagnini & Nair, 2004). Assessment of the potential of on-farm trees as a strategy for
carbon sequestration has also not been fully undertaken (Montagnini & Nair, 2004; Mng’omba &
Beedy, 2013).
On-farm tree species carbon sequestration is also far poorly understood and possibly has been
significantly underestimated due to the fact that in most countries, on-farm tree cover are ignored
in carbon sequestration estimations (Zomer et al, 2017). This study was therefore undertaken to
come out with a clear understanding tree species diversity and their carbon sequestration
potential in continuously cultivated farms in Agago District.
1.3
Aim and Objectives of the Study
1.3.1 Aim
The aim of the study was to evaluate the contribution of trees integrated on-farm to tree species
diversity and carbon sequestration potential in Agago District.
1.3.2 Specific Objectives
The specific objectives of the study were:
1. To assess on-farm tree species diversity.
2. To examine factors influencing the retention of trees on farm.
3. To determine the amount and variation of carbon sequestered by trees on-farm.
1.4
Justification
Information on on-farm tree species carbon sequestration could be used by farmers, government
and development agencies to increase on-farm tree species retention thereby contributing to onfarm tree species abundance and diversity.
2
Collection of information on farmers’ opinions and local knowledge on on-farm trees is also
paramount as it helps the government, research organisations, educational institutions and
development agencies in identification of on-farm tree species that have been lost due to land use
changes (Backes, 2001) and in the development of practices that maintain or increase tree
diversity on farms (Dawson et al., 2013, Nguyen et al., 2013).
Assembling information on carbon sequestration could also help farmers, the government,
research organisations, educational institutions and development agencies in development and
sustainable management of on-farm tree-based technologies that maximize carbon sink for
climate change mitigation and adaptation (Montagnini & Nair, 2004; Mng’omba & Beedy,
2013).
1.5
Conceptual Framework
The study was conceived as an assessment of the contribution of integrated trees to on-farm tree
species diversity and their carbon sequestration potential. To achieve the objectives of the study,
on-farm tree species diversity, factors influencing retention of on-farm tree species and their
carbon sequestration potential were analysed (Figure 1).
Since the farmers’ decision to maintain specific types of tree species on their farmland or
landholdings are influenced by their preferences for bundle of attributes or morphological
characters found in such trees (Abrefa et al., 2013), factors influencing on-farm tree species
retention were determined. (Figure1). While on-farm tree species retention can influence on-farm
tree species abundance and diversity (Okullo Waithum,2007; Boffa et al., 2008; Gwali et al.,
2015) (Figure 1); integrating trees on-farm can also influence carbon sequestration level in
agricultural systems (Luedeling et al., 2011).
3
Retention of Trees on Farms

Factors Influencing Retention of Trees
On Cultivated Far

On Farm Tree Species Diversity
Retained On-farm Tree Species

Total Number of Each Onfarm Tree Species

Total Number of All the
On-farm Tree Species
Carbon Sequestered by Trees on Farms

Diameter at Breast Height

Tree Height

Crown Diameter

Tree Biomass and Carbon
Contribution of Integrated Trees to On-farm Tree Species Diversity and their Carbon
Sequestration Potential
Figure 1: Conceptual Framework showing the linkage between integration of trees on-farm
to tree species diversity and their carbon sequestration potential
On-farm trees usually bring reductions in the buildup of atmospheric CO2 through sequestering
carbon at different level (Dossa et al., 2008; Jose, 2009). The amount and variation of carbon
sequestered by on farm trees were therefore analysed (Figure1).
Analysis of data on factors influencing retention of on-farm tree species, on-farm tree species
abundance and diversity and their carbon sequestration thus provided the focus of this study.
4
CHAPTER TWO
LITERATURE REVIEW
2.1
On-farm Tree Species Diversity
Most on-farm tree species are derived from retention of trees that were present before farms were
established, tolerance (and protection) of natural tree regeneration after farms have been
established (Ordonez et al., 2013), or active planting (Eswaran et al., 2006; Ordonez et al.,
2013). The retained on-farm tree species are deliberately managed thereby contributing to high
abundance and diversity of particular tree species on-farm (Boffa et al., 2008; Gwali et al.,
2015). On-farm tree species abundance represents the total number of trees present in a particular
farm (Boffa et al., 2008; Gwali et al., 2015) and tree species diversity refers to the number of
different tree species that can be differentiated, and to the proportions (or relative abundances) of
the number of trees that are counted in each category (Kindt & Coe, 2005).
The inclusion of trees from various tree species within farming systems has existed for a long
time among smallholder farmers in the world (Noble & Dirzo 1997; Boffa et al., 2008). As has
been reported in many studies, smallholders’ farmers in Uganda deliberately preserved trees onfarm in association with other crops (Boffa, 1990; Boffa et al., 2008, Nakakaawa & Vedeld,
2009; Gwali et al., 2015). Integration of trees with crops in farming systems is a livelihood
option that is being increasingly promoted by land-use managers and international development
agencies (Zomer et al., 2014).
Because farmers usually grow crops around and underneath some of these trees, total tree
numbers have been increasing in recent years on agricultural land throughout the world. It is
essential that this is recognized by all involved in agricultural production, planning and policy
development (Zomer et al., 2014). When an active tree-planting culture exists in rural
communities, hundreds of indigenous trees from various tree species can be found conserved in
farmland (Kindt et al., 2004). A diversity of local and exotic trees and crops therein, can thus,
improve the resilience of agricultural systems to environmental change if constituent species
respond differently to disturbances (Kindt et al., 2004).
5
Even if several indigenous trees from many tree species have been protected and managed by
farmers on farms as part of a traditional approach to land use in the tropics (Kindt et al., 2004;
Teklehaimanot, 2004); where exotic tree species have been introduced, they become the most
abundant trees thereby contributing the highest proportion of trees on-farms(Kindt et al.,
2004).The implication is that on-farm tree retention can conserve various trees from many tree
species outside native forest (Noble & Dirzo, 1997). Such retained trees are the ones that
contribute to tree species abundance (Boffa et al., 2008, Gwali et al., 2015) and diversity (Boffa
et al., 2008; Henry et al., 2008; Gwali et al., 2015).
On-farm tree species abundance is estimated by conducting tree species inventory to determine
the total number of on-farm trees (Kindt & Coe, 2005; Boffa et al.,2008; Gwali et al.,2015) or
average stem density per hectare (Boffa et al.,2008; Gwali et al.,2015). Tree diversity can be
estimated by Shannon Wiener index which indicates distribution of species and the number of
species categories. The higher the value of the index, the more diverse the farms will be in terms
of particular tree species and vice versa. The values of the index usually lie between 1.5 and 3.5,
although in exceptional cases, the values can even go beyond 4.5 (Kent & Coker, 1992). Barbour
et al., (1987) reported that values greater than 2 are indicative of medium to high diversity.
Tree species abundance and diversity can also be presented as rank-abundance. Rank curves are
conceptually the easiest method of analysing patterns of diversity. The total number of
individuals is calculated for each species and species are ranked from the most abundant to the
least abundant. Logarithm of abundance can produce better graphs when a few species are highly
dominant. Dominance of a particular tree species is when a particular tree species is more than
others in a particular area (Kindt & Coe, 2005).
The interpretation of a rank-abundance curve in terms of diversity (richness and evenness) is as
follows: On the horizontal axis, species richness is provided by the width of the curve. A wider
curve will indicate higher species richness. The shape of the rank-abundance curve is an
indication of the evenness. A completely horizontal curve is an indication of a completely evenly
distributed system. The steeper the curve, the less evenly species are distributed (Kindt & Coe,
2005).
6
The presence of reliable data on distribution of tree species abundance and diversity within the
farming systems is therefore important in determining the most endangered tree species and to
what extent land use change is potentially reducing tree diversity. Reliable data also helps in
identification of tree species being lost if specific land use strategies are altered, changed or
abandoned (Backes, 2001).
2.2
Factors Influencing Retention of Trees On-farm
According to FAO (2012), more than a billion of the world’s poorest people rely on forests and
trees on-farms to provide food, energy and cash income. Trees are also an important source of
many herbal remedies and traditional medicines. It has been estimated that more than 80% of the
rural communities in Sub-saharan Africa depend on medicinal plants for most of their health
needs and income generation (Arnold & Dewees, 1995; Garrity, 2004). In addition, trees onfarms can reduce farmers’ dependency on single staple crop and in addition to providing
significant nutritional contribution that are especially crucial during drought and famine times
(Neufeldt et al., 2009).
After an initial period of deforestation, trees on farms are remnants of previous vegetation,
followed by a gradual loss of trees retained before farms were established, tolerance (and
protection) of natural tree regeneration after farms have been established and ultimately leading
up to a phase of deliberate tree establishment by farmers. Trees on-farms are thus derived from
the combination of one or more of these processes (Eswaran et al., 2006; Ordonez et al., 2013).
The retention of on-farm tree species by smallholder farmers for various traditional uses is an
age-old practice (Noble & Dirzo 1997).This is so because rural men and women in many areas
have long been involved in the conservation and cultivation of trees on agricultural lands
(FAO,1985; Noble & Dirzo, 1997; Boffa,1999).The extent to which trees are present, cultivated
and managed depends largely on land suitability, prevention of soil erosion(Falconer &Arnold,
1991), soil fertility improvement(Boffa, 1999), patterns of agricultural land-use (FAO, 1985;
Falconer &Arnold, 1991;Boffa,1999), tenure rights, economic pressures(FAO, 1985; Falconer
&Arnold, 1991), characteristics of local ecology, cultural traditions, need for food and
fodder(Boffa, 1999), and local demands for wood and wood products (FAO, 1985). It should
however, be noted that the demand for wood from on-farm trees to supply energy for household
7
fuel is one of the key drivers of deforestation and landscape degradation in Africa (Neufeldt et
al., 2009).
Although firewood and charcoal can account for between 61 and 86% of primary energy demand
in Africa (Neufeldt et al., 2009), a farmer may only require 0.25 ha of improved fallow to
sustainably maintain their household’s primary energy demand. Since on average a family
consumes about 0.4 tons of fuel wood per year, a tree fallow as small as 0.5 ha, would provide
the firewood needed for the family to cook for one year (Sanchez & Jama, 2000).
Indeed only high quality tree species with desired attributes to provide varieties of products and
services are usually left on the farmland during the land clearing phase of farm development for
crop production (Anyonge & Roshetko, 2003; Teklehaimanot, 2004). Being an essential
component of indigenous agricultural systems, most of these on-farm tree species are preserved
or managed to meet the needs of the population such as food (Boffa, 1999; Teklehaimanot 2004),
medicines (Teklehaimanot, 2004; Boffa et al.,2008), income, fodder (Boffa, 1999;
Teklehaimanot, 2004), spices, resins, dyes, construction and agricultural materials, ecological
needs (Teklehaimanot, 2004) and fibre (FAO, 1985).
According Falconer &Arnold (1991), farmers usually protect, plant and manage trees on their
land in order to maintain supplies of sought-after products no longer readily available from the
natural forest which is degraded or is no longer accessible. This implies that tree products and
services derived from the retained on-farm trees are important for food security, health, social
and economic welfare of rural communities. In a nutshell, the above derived on-farm tree species
products and services are optimized by farmers through enhancement of tree species diversity on
their land resources (Boffa et al., 2008).
2.3
Amount and Variation of Carbon Sequestered by Trees On-farm
Global carbon is partitioned into five large pools: oceanic (42,000 billion tons); geologic (5,500
billion tons); pedologic, or soils-based (2,710 billion tons: 1,650 billion tons in Soil Organic
Carbon and 1,050 billion tons in Soil Inorganic Carbon); atmospheric (887 billion tons)
increasing at the rate of approximately 4.5 billion tons annually (IPCC, 2007a); and biotic C (606
billion tons) (Houghton, 2007). Approximately 9.9 billion tons of carbon is presently released to
8
the atmosphere each year from burning fossil fuels and industrial activity. In essence
approximately 1.7 billion tons is released from deforestation and land use change (Global Carbon
Project, 2009).
According to IPCC (2014), land use change like agriculture, forestry and livestock management
are strong contributors to climate change and accounts for approximately 24% of greenhouse gas
emissions; that also contributes to climate change. Climate change has resulted to an increase of
earth’s average surface temperature by 1.3 degrees Fahrenheit over the past century, and is
projected by the IPCC to increase by an additional 3.2 to 7.2 degrees over the 21st century (IPCC,
2007a). This has been caused due to increasing concentration of atmospheric CO2 (Conway &
Tans, 2012).
As has also been reported by IAASTD (2008), agricultural land use change and agricultural
production contributes and continue to contribute significantly to atmospheric carbon. Much as
agricultural land use results to loss of much of the above ground tree carbon, land use
alternatives such conservation-oriented land preparation and cultivation of crops in conjunction
with trees also contributes to carbon sequestration. Indeed, these latter land uses have greater
carbon sequestration potential than crop or pasture systems (Albrecht & Kandji 2003;
Montagnini & Nair, 2004; Nair et al. 2009).
Since tree species on agricultural land has the potential to make an important contribution to
climate change mitigation (Albrecht & Kandji 2003; Nair et al., 2010; Nair, 2012) agricultural
practices aimed at inclusion of tree species on agricultural systems should be promoted (Neufeldt
et al., 2009). This is so because such integration of trees would reduce greenhouse gas emissions
and vulnerability of agricultural systems to climate change.
After on-farm tree species retention, trees and woody perennials become a common feature on
farms (Neufeldt et al., 2009) and their incorporation in croplands and pastures usually results in
greater net above- and below-ground carbon sequestration (Albrecht & Kandji, 2003;
Montagnini & Nair, 2004; Nair et al. 2009). Accordingly, inclusion of trees in the agricultural
landscapes often improves the productivity of systems while providing opportunities to create
carbon sinks (Dixon, 1995). These agroeco systems formed as a result of on-farm tree retention,
9
do play a central role in the global carbon cycle and contains approximately 12% of the world
terrestrial carbon (Smith et al., 1993; Dixon, 1995).
A study by Montagnini & Nair (2004) has also shown that, atmospheric carbon can be reduced
by conservation of existing carbon pools through improved fallows and integration with trees
and substitution through biofuel and bioenergy plantations to replace fossil fuel use. Since the
global role of tree-based carbon sequestration on agricultural land is far poorly understood there
is need to quantify it in most land use systems. The ignored tree cover in most global and
regional calculations has been reported to make a major contribution to the carbon pool on
agricultural lands (Zomer et al, 2017). There has also been a proportionate increase in carbon
sequestered per hectare with increases in tree cover (Zomer et al.,2017).
Besides agricultural land use change and agricultural production, demand for biomass energy
usually reduces tree cover in many ecosystems (Neufeldt et al.,2009), but if, the trees were to be
used for construction materials only instead of biomass energy, significant amount of
atmospheric CO2 would be stored for decades or centuries thus making wood a net CO2 sinks
(Gielen, 1998).
2.3.1 Estimation of Carbon Sequestered by Trees On Farm
Estimation of carbon sequestered by on-farm trees is done using tree biomass (Ketterings et al.,
2001). The estimated tree biomass is then converted to tree carbon content and then eventually to
carbon sequestered by the tree. While West (2009), reported that as a rule of thumb it’s assumed
that 50% tree dry wood biomass corresponds to tree carbon content, Dietz& Kuyah (2011)
estimate indicate that 3.7 times the tree carbon mass would be equivalent to the sequestered
carbon for that particular tree.
Although weighing of the cut tree parts is the most accurate method of estimating tree biomass, it
is extremely time consuming and destructive. The use of allometric equations (a non-destructive
method), is thus the most common method used in tree biomass determination (Ketterings et al.,
2001).
An allometric equation is a statistical relationship between key characteristic dimension(s) of
trees that are fairly easy to measure (such as diameter at breast height-Dbh or height), and other
10
properties that are more difficult to assess (such as above ground biomass). Allometric equation
enables above ground tree biomass to be easily estimated, provided that diameter, total height,
and wood specific gravity of a tree are available, irrespective of the tree species and of the
location of the stand (Bhishma et al, 2010).
The general function of allometric equation is: y=f (xi)
(1)
Where y=Above Ground Biomass; xi=Variable such as diameter at breast height, tree height (ht),
crown area (ca), crown width (cr) and wood density (ρ)
While generic allometric equations for estimation of above ground tree biomass in different
vegetation cover types in the tropics have been developed (Brown et al., 1989; Brown, 1997;
Chave et al., 2005; Zianis, 2008), there is no available allometric equation of generic nature to
estimate above ground tree biomass on on-farm tree-based systems in the tropics.
In general, tree species-specific allometric equations are preferred because tree species may
differ greatly in tree architecture and wood gravity (Ketterings et al., 2001). Where there are
various tree species, the allometric equations used should represent variability in biomass.
Allometric equations which are country specific usually include extensive biomass field
measurement and can account for heterogeneity that is suitable for tree biomass estimation
(Avitabile et al., 2011).
Country specific allometric equations for estimation of above ground tree biomass has been
developed in some countries in the tropics, for instance, in Kenya country specific allometric
equations has been developed by Henry et al. (2010) and Dietz & Kuyah (2011) and in Uganda,
country specific allometric equations developed by National Biomass Study in year 2003 uses
tree species in different diameter categories for estimation of above ground tree biomass (Drichi,
2003).
After estimation of the above ground tree biomass, below ground tree biomass is estimated from
a known above ground tree biomass value using an allometric equation. Dietz & Kuyah (2011)
reported that below ground tree biomass is very seldom assessed although it comprises
commonly of about 20% of the total tree biomass.
11
According to IPCC (2006b), below ground tree biomass (BGB) is commonly calculated as a
ratio of the above ground tree biomass (AGB) using the equation below: BGB = AGB×R
(2)
Where
BGB =
Below Ground Biomass
AGB =
Above Ground Biomass
R
Ratio of Below Ground Tree Biomass to Above Ground Tree Biomass
=
Pearson et al., (2005), reported that belowground tree biomass can also be estimated from the
regression model below: BGB = exp (-1.0587 + 0.8836×ln (AGB))
(3)
The above regression model has been widely used and considered most practical and costeffective method of determining biomass of roots. Furthermore, it provides an accurate
assessment of belowground biomass (Pearson et al., 2005).
Since the above ground allometric models uses tree parameters such as stem diameter, height,
crown diameter, wood densities and tree biomass (Brown et al., 1989; Brown, 1997; Drichi,
2003; Chave et al., 2005; Pearson et al., 2005; Zianis, 2008; Henry et al., 2010), diameter at
breast height(Dbh) equal or greater than 5cm Dbh is measured at 1.3 metres of the tree height
(Bhishma et al., 2010, Mugasha et al., 2016). Thus, to identify the correct point to measure Dbh
on every tree, 1.3 m on the human body or a 1.3 m long stuff is used.
Diameter at breast height, are measured depending on the orientation of the trees as follows.
Usually the tree is measured on the uphill side if the tree is on a slope, perpendicular to the main
axis of the trunk (not parallel to the ground) if the tree is leaning, two trunks are measured as
separate trees if the tree is forked below 1.3 m, the main stem is measured if the tree forks is
above 1.3 m and if there is an unusual bulge right at 1.3m on the stem, Dbh is measured slightly
above 1.3m above the stem (Skole et al., 2013).
12
The total heights of trees are measured using either a clinometer or hypsometer. While
clinometer measures one of several parameters (percent, degrees, and secant), Hypsometers
measure tree height and other parameters using lasers. Tree heights are measured based on the
measurement of a known horizontal distance away from the base of the tree (Skole et al., 2013).
According to Skole et al. (2013), crown measurement is determined by using at least two crown
diameters for each tree. The first crown diameter is the maximum crown diameter (from dripline
to dripline) as determined by visual inspection of the tree and the second crown diameter is
measured at 90° to the maximum crown diameter. Studies show that variables of crown diameter
or crown area improve reliability and accuracy in biomass estimation (Henry et al., 2010; Dietz
et al., 2011).
Wood density is also used to calculate biomass when the volume of a tree is measured (mass =
volume x density). Wood density is usually measured by extracting a known volume of wood
from a tree and determining the mass. Wood samples of known volume are collected using an
increment borer or other coring/drilling device, oven-dried and the wood density calculated as
the mass of oven dried wood per unit of volume of green wood (Skole et al., 2013).
In undertaking all these, geographical locations of all measured trees for estimation of tree
biomass and carbon sequestered should be recorded with a Global Positioning System (GPS)
device. This measurement will allow for geographic information system analysis and possible
return to the site. Genus and species should be recorded for each individual tree (Skole et al.,
2013).
2.3.2 Variation of carbon sequestered by trees on farm
The carbon sequestration capacity of on-farm tree species varies considerably with tree species
composition, geographical location of the agricultural system, age (Jose, 2009) and previous land
use (Albrecht & Kandji, 2003; Montagnini& Nair, 2004; Pandey, 2002; Nair et al., 2009). It also
varies with climate, soil characteristics, crop-tree mixture, management practices (Pandey 2002;
Dossa et al. 2008), tree species biomass accumulation rates, tree species size (Mng’omba &
Beedy,2013), tree species growth rate and their life span (Mng’omba & Beedy,2013; Mayank,
2016).
13
It has also been reported that carbon sequestration capacity of tree species in established systems
varies in fast growing tree species (which sequesters and store more carbon) than slow growing
tree species (Maura-Costa, 1996; Mayank, 2016). Similarly, long-lived tree species with dense
wood can have greater carbon sequestration potential and carbon storage than tree species that
are short-lived with light wood (Maura-Costa, 1996; Mayank, 2016).
A report by Srivastava &Vellend (2005) indicates that vegetatively complex systems tend to
store more carbon and support more species, making ecologists to become more interested in the
potential functional relationships between diversity and carbon sequestration/storage. Thus,
understanding relationships between tree species diversity and biomass storage is therefore very
important in attempts to maintain the carbon stocks in tree-based system over a long term for
maximization of carbon sink (Srivastava & Vellend, 2005).
Since the conversion of forest to mixed fields usually results into loss of an enormous quantity of
above ground biomass, the different tree species left sequesters different amount of carbon
resulting to different on-farm carbon sequestration levels by on-farm trees (Maura-Costa et al.,
1996; Lamlom& Savidge, 2003).
14
CHAPTER THREE
STUDY AREA AND METHODS
3.1
Study Area
3.1.1 Location
Agago District was established by an Act of Parliament and began functioning on the 1st of July
2010 (UBOS, 2014). Prior to that date, it was part of Pader District. Agago District is located in
Northern Uganda, Acholi Sub-region (Figure 2).
Figure 2: Map of the study area (Agago District, Northern Uganda)
Agago District has a total area of 3,946.8 km2 and located at the coordinates of 02 5˚N, 33 2˚E. It
is bordered by Kitgum District to the north, Kotido District to the northeast, Abim District to the
east, Otuke District to the south and Pader District to the west. The district has 16 lower local
governments including; 3 town councils and 13 sub counties (Okaka, 2013
15
3.1.2 Vegetation
The vegetation of the district is predominantly dry savanna type comprising mainly of
Terminalia, Acacia and Vitellaria tree species (Otai, 2009; King et al.,2017). However, the
northeastern part of the district consists of mountain forest and shrubs (Otai, 2009).
3.1.3 Climate
Agago District is located in North Eastern Savannah Grassland Agro-ecological Zone with
average rainfall of 1197 mm. It has one rainy season of about 7 months (April to late October)
with the main peak in July/August and a secondary peak in May (Bwana-Simba, 2013). It also
has one long dry season of about 4 months from mid-November to late March. Driest months are
from December to February. Temperature ranges from 15 - 32.5 °C and the elevation averages
1,060 m (Bwana-Simba, 2013).
3.1.4 Soils and Topography
The soil in Agago District is generally loamy with some areas having a lot of sand and clay soil.
Agago District has generally a flat landscape with some inselbergs in the eastern side in the sub
counties of Adilang, Lapono, Lukole and Parabongo. The district has one river (Agago) which
has several streams some of which are seasonal and dry out in the dry season (Otai, 2009).
3.1.5 Population and Economic Activities
In 2014, the population of Agago District was recorded at approximately 227,486 (Male-110,095
and Female-117,391) with 43,274 households. Agriculture is the major economic activity in
Agago District.
Majority of the farmers are small holders growing both perennial and annual crops which include
bananas, coffee, tea, maize, sweet potatoes, beans, sorghum, peas, cassava and groundnuts.
Animal rearing is also practiced though on a small scale (Okaka, 2013; UBOS, 2014).
16
3.2
Methods
3.2.1 Research Design
Interviews were conducted with the help of survey questionnaires (Appendix 3). Face to face
interviews with household heads was meant to ascertain reasons for retention of on-farm tree
species (Okullo & Waithum, 2007). The socio-economic and demographic characteristics of the
respondents was determined and summarized in Appendix 4.
On-farm tree species inventory was conducted and total number of trees and each tree species
encountered were recorded and used to determine on-farm tree species abundance and diversity
(Kindt et al., 2006; Boffa et al. 2008; Gwali et al., 2015). Each tree belonging to a particular tree
species was recorded during farm walk in each household farm (Kindt et al., 2006; Okullo &
Waithum, 2007; Boffa et al. 2008). Tree parameters such as diameter at breast height (Dbh),
height (ht) and crown diameter (cr) were measured for application in allometric equations to
estimate on-farm tree species carbon sequestration potential (Drichi,2003).
3.2.2 Sampling Procedure and Size
Multistage sampling procedure based on administrative structure was used to select the
respondents (Kyarikunda, 2017). Patongo and Lukole sub-counties were randomly selected from
16 sub-counties in Agago District. Thirty villages were randomly selected from 221 villages in
Patongo and Lukole sub-counties.
From each of the thirty villages, two households were
randomly selected to make sixty respondents for the socio-economic survey.
Sixty cultivated farms with tree species retained in them were randomly selected. One cultivated
farm was randomly selected from farms of each of the sixty respondents selected during the
socio-economic survey. The cultivated fields were used to provide data on tree inventory during
farm walks (Okullo & Waithum, 2007).
17
3.2.3 Plot Establishment and Layout
Cultivated farms were measured and each of them was then divided diagonally into
approximately four equal sub-units (Okullo & Waithum, 2007). In each sub-unit a 10 x 10 m plot
was demarcated by placing pegs at each corner (Okullo & Waithum, 2007).
3.2.4 Data Collection Procedures
Both qualitative and quantitative information were collected and used to determine on-farm tree
species diversity (Kindt et al., 2006; Boffa et al. 2008; Gwali et al., 2015) and their carbon
sequestration potential (Nakakaawa & Vedeld, 2009).
a)
On-farm Tree Species Inventory
On-farm tree species inventory (Appendix I) was conducted (Kindt et al., 2006; Boffa et al.
2008). Both local and scientific names of trees belonging to different tree species were recorded
in Tree Inventory Form (Katenda et al., 1995). Assistance was sought from community members
who had knowledge in identifying tree species.
Local tree species names (Acholi) were used and later their corresponding botanical names were
recorded using Katenda et al. (1995). Digital Camera was used for photographing salient features
during the study and to indicate the presence of retained tree species on-farms (Skole et al.,
2013).
b)
Household Survey to Examine Factors Influencing Retention of Trees On Farm
A survey questionnaire was developed, pre-tested and administered to 60 respondents (Appendix
3). Data collected using the questionnaire (Appendix III) included: on-farm tree species (retained
during farm establishment, protected to allow natural regeneration and planted), factors
influencing on-farm tree species retention, duration of on-farm tree retention and long term onfarm tree species retention.
c)
Determining Amount and Variation of Carbon Sequestered by Trees On-farm
In order to determine the amount of carbon sequestered, the following tree parameters were
recorded: diameter at breast height, height and crown diameter of each on-farm tree species. A
caliper was used to measure the diameter at breast height of each encountered tree and recorded
18
in the Tree Inventory Form (Appendix 1), while distance tape was used to measure the sizes of
cultivated farms and crown diameter.
Crown measurement was determined by using at least two crown diameters for each tree. The
first crown diameter is the maximum crown diameter (from dripline to dripline) as determined by
visual inspection of the tree and the second crown diameter is measured at 90° to the maximum
crown diameter (Skole et al.,2013). Hypsometer was used to measure tree height, Global
Positioning System Device was used for tree species location determination (Skole et al., 2013).
All the variables measured for each encountered tree were recorded in the Tree Inventory Form
(Appendix I).
All trees with diameter at breast height equal or greater than 5 cm were measured for diameter at
breast height (Bhishma et al., 2013). Tree species with diameter at breast height equal or greater
than 5 cm exist in dry land vegetations of East Africa (Mugasha et al., 2016). Tree species height
and crown diameter were also measured (Drichi, 2003).
Data collected for determination of on-farm tree species carbon sequestration potential were also
used in examining variation in the carbon sequestered by different on-farm tree species. Data on
variation in the carbon sequestered by different on-farm tree species were derived from tree
biomass, carbon stored and carbon content of different tree species retained on-farms (MauraCosta, 1996; Lamlom & Savidge, 2003; Nakakaawa & Vedeld, 2009, Mng’omba & Beedy,
2013; Mayank, 2016).
3.2.5 Data Analysis
a)
Assessment of On-farm Tree Species Diversity
Tree species abundance was derived by determining the total number of trees on-farms (Kindt &
Coe, 2005; Boffa et al., 2008; Gwali et al., 2015) and average stem density per hectare (Boffa et
al., 2008; Gwali et al., 2015). All on-farm tree species were assumed to be represented in a
sample and that they were randomly sampled.
19
Shannon-Wiener's index was used to assess on-farm tree species diversity. Data on total tree
number (N) and each type of tree species number (n) were entered in MS-Excel and tree
diversity calculated using formulae in equation 4(Gotelli & Chao, 2013).
(4)
Where H
=
Shannon-Wiener's diversity index.
S
=
the number of species.
Pi
=
the proportion of individuals or the abundance of the ith species expressed
as a proportion of total number of individuals.
Log pi
=
the natural log of pi
pi =
(5)
Where
n=
number of individuals of each species (the ith species)
N=
total number of individuals
Shannon-Wiener's index is a non-parametric method widely used to indicate distribution of
species and the number of species categories (Gotelli & Chao, 2013). The higher the value of the
index, the more diverse the farms would be in terms of particular tree species and vice versa.
The values of the index usually lie between 1.5 and 3.5, although in exceptional cases, they can
exceed 4.5 (Kent & Coker, 1992).
b)
Examination of Factors Influencing Retention of Trees On Farm
Data on factors influencing retention of on-farm tree species were checked for consistency,
coded, entered in MS-Excel and Descriptive statistics was used to summarize data into
frequencies (Okullo & Waithum, 2007).
c)
Determination of the Amount/Variation in Carbon Sequestered by Trees On-farm
Tree Biomass was calculated using allometric equations developed by National Biomass Study
(NBS) in year 2003. Data collected on tree diameter at breast height, height and crown diameter
20
were entered with their actual values in MS-Excel. NBS represents an optimal reference dataset
for biomass estimation in Uganda (Avitabile et al., 2011). Tree allometry accounts for the
heterogeneity of tree diversity influenced by different management practices and climatic
conditions (Drichi, 2003).
i)
Above ground biomass
Above ground biomass was estimated using single tree weights with the following tree
parameters: diameter at breast height, height and crown diameter. According to Drichi (2003),
analysis of single tree weights is based on regression models developed from destructive
sampling of trees for the prediction of single tree weights (as the dependent variable) and tree
parameters (as independent variables) as shown in equation 6 below:
ln(PWF) = a + b*ln(d) + c*ln(ht) + d*ln(cr).
(6)
Where: a, b, c and d are regression coefficients.
ln
=
natural logarithm.
PWF =
predicted wet weight of tree.
d
=
diameter at breast height.
ht
=
tree height (from the ground).
cr
=
crown width.
In this study, the above ground biomass was calculated using diameter categories as a basis for
grouping. The equations below were used for estimating single tree weights from the tree
parameters (Drichi, 2003; Nakakaawa & Vedeld, 2009):
Category 1
Dbh < 20cm:
PWF = exp (0.5* 0.09937-0.909575 + 1.544561* (ln.d) + 0.50663 (ln.ht) + 0.33346* ln (cr) (7)
Category 2
Dbh≥20< 60cm
PWF = exp (0.5* 0.0892-1.795491 + 1.943912 * (ln.d) + 0.47371* (ln.ht) + 0.245776* ln (cr) (8)
21
Category 3
Dbh≥60cm
PWF = exp (0.5* 0.05222 -2.192612 + 2.032931*(ln.d) + 0.31292* (ln.ht) + 0.436348 * ln (cr)
(9)
Conversion of On-farm Tree Species Wet Weight to Above Ground Biomass
Aboveground biomass = PWF* wood density (ρ)
(10)
The wood density values that were used in estimation of tree above ground biomass were locally
derived (Drichi, 2003) from values in Appendix 2.
Total Above Ground Biomass
The total above ground biomass expressed as tons per hectare was obtained by summing single
on-farm tree species biomass from all the 720 plots of 0.01ha. The amount of above ground
biomass was multiplied by 100 to extrapolate 10 m x 10 m plot size to per hectare basis (Dossa
et al., 2008; Henry et al.; Nakakaawa & Vedeld, 2009; Bhishma et al., 2010; Walela et al., 2016;
Dawoe et al., 2016).
ii)
Below Ground Biomass
A regression model was applied to determine the below ground biomass from the formulae
below.
BGB = exp [-1.0587 + 0.8836 x ln (AGB)].
(11)
Where:
BGB= Belowground biomass, and
AGB = Aboveground biomass (t/ha).
The above regression model is widely used and it is the most practical and cost-effective method
of determining biomass of roots. Measurements of root biomass are simply done by inserting the
above ground biomass into the equation. Applying this equation allows an accurate assessment
of below ground biomass (Pearson et al., 2005).
22
iii)
Total Tree Biomass
Both the above- and below- ground biomass were summed up to get the total tree Species
biomass (Nakakaawa & Vedeld, 2009).
iv)
Conversion of Biomass to Carbon Content
The carbon content of each tree was calculated as the product of the dry weight biomass and an
assumed carbon content of 50% (West, 2009).
v)
Conversion of Carbon Content to the Total Carbon Sequestered by On-farm Tree
species
According to Dietz & Kuyah (2011), there is always a need for tree species carbon to be
converted to carbon sequestered as indicated in equation below:
Total Carbon Sequestered= Tree Carbon Content x 3.67
vi)
(12)
On-farm Tree Species Carbon Sequestration Potential
Average amounts of carbon sequestered per hectare by different on-farm tree species were
determine to find out the on-farm tree species which had the highest and least carbon
sequestration potential (Drichi, 2003). Analysis of Variance (ANOVA) was used to test the
variation in the amount of carbon sequestered by different tree species retained on-farm.
vii)
Variation in Carbon Sequestered by Trees On-farm
On-farm tree species of different sizes were grouped using diameter categories (Dbh < 20 cm,
Dbh ≥20< 60cm and Dbh≥60 cm) (Drichi, 2003; Nakakaawa & Vedeld, 2009). Variations of
carbon sequestration with on-farm tree species in different tree species Dbh Categories (Dbh
<20cm, Dbh ≤ 20< 60cm and Dbh ≥ 60 cm) were tested using ANOVA (Jayaraman, 1999).
Their mean comparisons were carried out using Least Significant Difference (LSD).
23
CHAPTER FOUR
RESULTS
4.1
On-farm Tree Species Diversity
4.1.1 On-farm Tree Species Abundance
A total of 390 trees belonging to 12 families and 26 species were encountered on-farms (Table
1). The average number of trees on-farms was 54 stems per hectare. Sapotaceae and
Combretaceae families contributed to 64% of the total number of trees encountered on-farms.
Average stem densities in Sapotaceae and Combretaceae families were 22 and 12 stems per
hectare respectively. All tree families except Sapotaceae, Combretaceae had an average stem
density of ≤5 stem per hectare (Table 1).
Over 90% of on-farm tree species had ≤10 individuals retained on-farms. Sixty nine and 23% of
on-farm tree species had only one and ≤5 individual/s retained on-farm respectively (Table 1).
The most abundant on-farm tree species were Vitellaria paradoxa ssp. nilotica (Figure 3) and
Combretum collinum representing 41% and 13%of the total number of trees encountered
respectively (Table 1).
Figure 3: Farm with mature pure stands of Vitellaria paradoxa ssp. nilotica in Tekulu
Village, Lukwaongole Parish, Patongo Sub-county
24
Table 1: On-farm tree species (Retained during farm establishment, protected to allow
natural regeneration and planted) abundance
Name
Local
Family
Yaa
Scientific
Vitellaria
paradoxa
nilotica(C.F.Gaertn.)
Odugu
Combretum collinum(Fressen.)
Combretaceae
Ogali
Piliostigma thonningii (Schum.) Milne-Redh
Caesalpiniaceae
Opok
Terminalia brownie (Fresen.)
Combretaceae
Anwa
Combretum fragrans F. Hoffm.
Combretaceae
Pogo
Grewia mollis(Juss.)
Muyembe
Olweto
During farm
establishment
Protected to
allow
natural
regeneration
T1
T2
TA1
Overall
Retention
Planted
TA2
T3
TA3
T
OTA
ssp.
Sapotaceae
110
15
51
7
0
0
161
22
7
1
45
6
0
0
52
7
3
0
16
2
0
0
19
3
14
2
2
0
0
0
16
2
7
1
8
1
0
0
15
2
Tiliaceae
5
1
10
1
0
0
15
2
Mangifera indica (L.)
Anarcardiaceae
0
0
0
0
14
2
14
2
Lonchocarpus laxiflorus Horchst
Umbrelliferceae
5
1
7
1
0
0
11
2
Ayuca
Lannea barteri (L.Kerstingii)
Anarcardiaceae
5
1
4
1
0
0
9
1
Olam
Ficus sycomorus Lam.
Moraceae
6
1
2
0
0
0
8
1
Olim
Combretum mole (R. Br. Ex. G. Don)
Combretaceae
6
1
1
0
0
0
7
1
Kicoro
Erythrina abyssinica (Schum.) Milne-Redh
Leguminoceae
3
0
4
1
0
0
7
1
Kworo
Ficus glumosa Del.
Moraceae
5
1
1
0
0
0
6
1
Kidit
Ficus natalensis Hochst.
Moraceae
6
1
0
0
0
0
6
1
Oywelo
Vitex doniana (Sweet.)
Verbenaceae
2
0
4
1
0
0
6
1
Lacaa
Acacia sieberiana (DC.)
Mimosaceae
5
1
0
0
0
0
5
1
Owak
Albizia grandibracteata Taub.
Mimosaceae
5
1
0
0
0
0
5
1
Pwo
Ficus ovata Vahl.
Moraceae
5
1
0
0
0
0
5
1
Oryang
Acacia hockii (De wild.)
Mimosaceae
3
0
1
0
0
0
4
1
Odwong
Gardenia ternifolia Schum.
Rubiaceae
4
1
0
0
0
0
4
1
Oduru
Ficus sur Forssk
Moraceae
3
0
0
0
0
0
3
0
Kwogo
Lannea schweinfurthii var.stuhlmannii
Anarcardiaceae
3
0
0
0
0
0
3
0
Chwa
Tamarindus indica (L.)
Caesalpiniaceae
3
0
0
0
0
0
3
0
Otoko
Acacia Senegal (L.) Willd.
Mimosaceae
0
0
2
0
0
0
2
0
Lawrewrecu
Bridelia scleroneura Mϋll. Arg.
Moraceae
2
0
0
0
0
0
2
0
Alingwalo
Strychnos innocua Lam.
Loganiaceae
2
0
0
0
0
0
2
0
Grand Total
219
30
158
22
14
2
390
T1=Total tree species number retained during farm establishment T2=Total tree species number retained after being protected to allow natural
regeneration T3 =Total tree species number retained after planting T=Total number of all the tree species retained TA1=Tree abundance of tree
species retained during farm establishment TA2=Tree abundance of tree species retained after being protected to allow natural regeneration TA3
=Tree abundance of tree species retained after planting OTA=Overall tree species abundance
Average stem densities for Vitellaria paradoxa ssp. nilotica and Combretum collinum were 22
and 7 stems per hectare respectively. All tree species except Vitellaria paradoxa ssp. nilotica had
an average stem density of <10 stem per hectare (Table 1).
25
54
4.3.2 On-farm Tree Species Diversity
A total of 26 tree species belonging to 12 families were encountered. The diversity index for onfarm tree species diversity was 2.836. On-farm tree species diversity was relatively high.
Vitellaria paradoxa ssp. nilotica and Combretum collinum contributed the highest proportion to
the diversity index (Table 2).
Ninety two percent, 58% and 4% of on-farm tree species encountered on-farms were retained
during farm establishment, protected to allow natural regeneration and planted respectively.
Indigenous tree species accounted for 96% of the total tree species encountered on-farm (Table
2).
Fifty four percent of the on-farm tree species belong to one quarter of the tree families
encountered on-farm. Moraceae was the largest family containing 24% of the tree species.
Combretaceae and Mimosaceae families had 15%of the on-farm tree species each.
Forty six percent of the tree species belong to three quarter of the encountered tree families
(Table 2). Over 55% of the families had one tree species each. All tree families except
Anarcardiaceae had only indigenous tree species (Table 2).
On-farm tree species retained during farm establishment had a diversity index of 1.557 which
was higher than for tree species retained after being protected to allow natural regeneration
(1.160) (Figure4) and planted (0.119).
26
Table 2: On-farm tree species (Retained during farm establishment, protected to allow
natural regeneration and planted) diversity
Name
Family
During farm
establishment
Protected to allow
natural
regeneration
Planted
H'
H'
H'
Local
Name
Yaa
Vitellaria paradoxa
Sapotaceae
0.357
0.266
0
Odugu
Combretum collinum
Combretaceae
0.072
0.249
0
Ogali
Piliostigma thonningii
Caesalpiniaceae
0.037
0.131
0
Opok
Terminalia brownie
Combretaceae
0.119
0.027
0
Anwa
Combretum fragrans
Combretaceae
0.072
0.08
0
Pogo
Grewia mollis
Tiliaceae
0.056
0.094
0
Muyembe
Mangifera indica
Anarcardiaceae
0
0
0.119
Olweto
Lonchocarpus laxiflorus
Umbrelliferceae
0.056
0.072
0
Ayuca
Lannea barteri
Anarcardiaceae
0.056
0.047
0
Olam
Ficus sycomorus
Moraceae
0.064
0.027
0
Olim
Combretum molle
Combretaceae
0.064
0.015
0
Kicoro
Erythrina abyssinica
Leguminoceae
0.037
0.047
0
Kworo
Ficus glumosa
Moraceae
0.056
0.015
0
Kidit
Ficus natalensis
Moraceae
0.064
0
0
Oywelo
Vitex doniana
Verbenaceae
0.027
0.047
0
Lacaa
Acacia sieberiana
Mimosaceae
0.056
0
0
Owak
Albizia grandibracteata
Mimosaceae
0.056
0
0
Pwo
Ficus ovata
Moraceae
0.056
0
0
Oryang
Acacia hockii
Mimosaceae
0.037
0.015
0
Odwong
Gardenia ternifolia
Rubiaceae
0.047
0
0
Oduru
Bridelia scleroneura
Moraceae
0.027
0
0
Kwogo
Ficus sur
Moraceae
0.037
0
0
Chwa
Lannea schweinfurthii
Anarcardiaceae
0.037
0
0
Otoko
Tamarindus indica
Caesalpiniaceae
0.037
0
0
Lawrewrecu
Acacia Senegal
Mimosaceae
0
0.027
0
Alingwalo
Strychnos innocua
Loganiaceae
0.027
0
0
1.557
1.16
0.119
In terms of on-farm tree species richness and evenness, there was high on-farm tree species
richness and less even distribution of on-farm tree species (Figure 5).
27
Figure 4: On-farm tree species naturally regenerating in an intercropped farm in
Labworyemo South Village, Kal Parish, Patongo Sub-county
Figure 5: On-farm tree species richness, evenness and abundance
28
4.2
Factors Influencing Retention of Trees On-Farms
Ninety and 78% of the respondents had trees on-farms because of the need for biomass energy
and food for households respectively (Table 3).
Table 3: Factors influencing the retention of trees on farm (n=60)
Factors
%
Biomass energy for homes
90
Food for households
78
Farm boundary markings/Land tenure security
37
Construction materials
33
Income generation
23
Wind breaks
08
Animal feeds
03
Materials for making animal traction equipments(York)
03
Performing cultural rituals
03
Shade for resting during crop production
03
Soil conservation
03
Forest habitat-based enterprise
02
Materials for making knife handle
02
Poultry feeds
02
Provision of shade for crops
02
Twenty six tree species were retained on-farms for various factors. Vitellaria paradoxa ssp.
nilotica and Combretum collinum were encountered in 72% and 58% of farms respectively.
Other factors which influenced on-farm tree retention were household income generation, need
for construction materials, farm boundary markings/land tenure security and creation of
windbreaks (Table 3).
Combretum collinum and Piliostigma thonningii were the main tree species retained for biomass
energy and Vitellaria paradoxa ssp. nilotica was the main fruit tree species retained for food and
household income generation (Table 4).
29
Table 4: Factors influencing retention of on-farm tree species (n=390)
Family
Type
Name
Factors(Frequency)
Local
Scientific
Yaa
Vitellaria paradoxa ssp nilotica
Af
Ay
Be
Ct
Fb/L
Fbe
Fo
Ig
Pcr
Pf
Ps
Sc
Sf
Wbs
Sapotaceae
FT
Farms (%)
72
0
0
29
0
0
0
149
46
0
0
0
0
0
19
Odugu
Combretum collinum
Combretaceae
NFT
58
0
0
49
3
7
2
1
0
0
0
1
0
0
0
Pogo
Grewia mollis
Tiliaceae
NFT
32
0
0
11
0
5
1
0
0
0
0
0
0
0
0
Olam
Ficus sycomorus
Moraceae
FT
18
0
0
1
5
0
0
0
0
0
0
0
2
0
0
Anwa
Combretum fragrans
Combretaceae
NFT
23
0
0
12
0
3
0
0
0
0
0
0
0
2
0
Opok
Terminalia brownie
Combretaceae
NFT
20
0
0
16
0
0
0
0
0
0
0
0
0
0
1
Olweto
Lonchocarpus laxiflorus
Umbrelliferceae
NFT
20
0
0
9
2
0
0
0
0
3
0
0
0
0
0
Muyembe
Mangifera indica
Anarcardiaceae
FT
10
4
0
4
0
0
4
10
5
0
0
0
0
0
0
Ogali
Piliostigma thonningii
Caesalpiniaceae
NFT
25
0
0
49
3
7
2
1
0
0
0
1
0
0
0
Ayuca
Lannea barteri
Anarcardiaceae
NFT
13
0
3
2
2
4
0
1
0
0
0
0
0
0
0
Olim
Combretum molle
Combretaceae
NFT
18
0
0
7
1
0
0
0
0
0
0
0
0
0
0
Owak
Albizia grandibracteata
Mimosaceae
NFT
10
0
0
4
0
0
0
0
0
0
0
0
1
0
0
Kworo
Ficus glumosa
Moraceae
FT
10
0
0
4
2
1
0
0
0
0
0
0
0
0
0
Pwo
Ficus ovata
Moraceae
FT
2
0
0
5
3
0
0
0
0
0
0
0
0
0
0
Oywelo
Vitex doniana
Verbenaceae
FT
7
0
0
0
1
0
0
5
0
0
0
0
0
0
0
Lacaa
Acacia sieberiana
Mimosaceae
NFT
7
0
0
4
1
0
0
0
0
0
0
0
0
0
0
Lawrewrecu
Bridelia scleroneura
Moraceae
FT
7
0
0
1
1
0
0
0
0
0
0
0
0
0
0
Oryang
Acacia hockii
Mimosaceae
NFT
8
0
0
1
1
2
0
0
0
0
0
0
0
0
0
Alingkwalo
Strychnos innocua
Loganiaceae
FT
3
0
0
0
0
0
0
2
0
0
0
0
0
0
0
Kicoro
Erythrina abyssinica
Leguminoceae
NFT
7
0
0
3
4
0
0
0
0
0
0
0
0
0
0
Kidit
Ficus natalensis.
Moraceae
FT
8
0
0
3
1
0
0
0
0
0
0
0
0
2
0
Otoko
Acacia Senegal
Mimosaceae
NFT
5
0
0
0
0
0
0
0
0
0
0
0
1
0
1
3
0
0
2
0
0
0
1
0
0
0
0
0
0
0
5
0
0
2
1
1
0
0
0
0
0
0
0
0
0
Chwa
Tamarindus indica
Caesalpiniaceae
FT
Kwogo
Lannea schweinfurthii
Anarcardiaceae
FT
Odwong
Gardenia ternifolia
Rubiaceae
NFT
13
0
0
4
0
1
0
0
0
0
0
0
0
0
0
Oduru
Ficus sur
Moraceae
FT
10
0
4
0
3
1
223
0
31
1
32
0
9
0
170
0
51
0
3
1
1
0
2
0
4
0
4
0
21
Total Frequency
Af=Animal feeds Ay=Animal traction equipments (York) Be=Biomass energy for homes Ct=Construction materials Fbe=Forest habitat-based enterprise Fb/L=Farm boundary marking/Land tenure
security Fo=Food for households FT=Fruit trees Ig= Income generation NFT=Non-Fruit trees Pcr= Performing cultural ritual Ps=Provision of shade for crops Pf=Poultry feeds Sc=Soil conservation
Sf=Shade for resting during crop production Wbs=Wind breaks
30
The tree species retained on-farms were less than 10, between 10-20 and above 20 years reported
by 60%, 32% and 8% of the respondents respectively. Majority of respondents (87%) said that
the need for fuel wood and biomass energy for households would not affect long term retention
of trees on farm. The need for biomass energy for households did not affect retention trees on
farm (P≤0.05) (Table 5).
Table 5: Chi-Square Tests of influence of the need for biomass energy for households on
retention trees on farm
Pearson Chi-Square
Continuity
Correctiona
Likelihood Ratio
Fisher's Exact Test
N of Valid Cases
1
Asymp. Sig.
(2-sided)
.000
371.439
1
.000
169.240
1
.000
Value
390.000b
df
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
.000
.000
390
a. Computed only for a 2x2 table5b. 1 cells (25.0%) have expected count less than 5. The
minimum expected count is 1.24.
The retained on-farm trees which would be retained for a long term were integrated with crops
such as Phaseolus vulgaris, Manihot esculenta, Gossypium hirsutum, Arachis hypogaea, Zea
mays, Eleusine coracana, Abelmoschus esculentus, Cajanus cajan, Sesanum indicum, Sorghum
vulgare, Glycine max and Helianthus annuus. Majorly cultivated crops were Zea mays and
Arachis hypogaea (Table 6).
Table 6: Crops integrated with trees on-farms (n=60)
Variables
Crops cultivated on-farm
Zea mays L.
Arachis hypogaea L.
Eleusine coracana(L.) Gaertn.
Sesanum indicum L.
Sorghum vulgare Pers.
Helianthus annuus L.
Phaseolus vulgaris L.
Glycine max(L.) Merrill.
Manihot esculenta Crantz
Gossypium hirsutum L.
Abelmoschus esculentus(L.) Moench
Cajanus cajan(L.) Millsp.
%
52
20
13
10
10
08
05
03
03
02
02
02
31
4.3 Amount and Variation in Carbon Sequestered by Trees On Farm
4.3.1 Amount of Carbon Sequestered by Trees On Farm
Twenty six on-farm tree species were measured for carbon sequestration estimation. The total
amount of carbon sequestered by trees was 18,950.89 tCO2/ha. Ficus ovata and Piliostigma
thonningii had the highest and lowest carbon sequestration potential amounting to 183 tCO2/ha
and 6.50 tCO2/ha respectively (Table 7).
Table 7: Amount of carbon sequestered by on-farm trees (tCO2/ha)
Local Name
Scientific Name
Family
Yaa
Vitellaria paradoxa
Sapotaceae
Type
FT
161
0.99
Moraceae
FT
5
11.84
Anarcardiaceae
FT
14
Combretaceae
NFT
Moraceae
FT
Moraceae
FT
Combretaceae
NFT
Combretaceae
NFT
Moraceae
FT
Tiliaceae
NFT
Combretaceae
NFT
Pwo
Mayembe
Odugu
Olam
Kidit
Anwa
Opok
Kworo
Pogo
Olim
Ficus ovata
Mangifera indica
Combretum collinum
Ficus sycomorus
Ficus natalensis
Combretum fragrans
Terminalia brownie
Ficus glumosa
Grewia mollis
Combretum molle
N
Min
Mean± SD
Max
Sum
74.82±98.71
809.88
12046.33
183.58±119.81
293.95
917.91
2.09
55.69±96.93
382.77
779.65
52
1.42
14.63±14.72
59.75
760.83
8
11.47
94.92±86.08
252.71
759.34
6
6.49
94.16±125.51
297.50
564.98
15
3.91
35.67±35.31
113.26
535.03
16
4.67
29.69±24.82
86.49
475.11
6
2.54
72.86±96.19
255.90
437.17
15
5.41
15.88±14.64
61.81
238.21
7
5.31
27.13±29.29
89.91
189.88
Ayuca
Lannea barteri
Anarcardiaceae
NFT
9
6.91
18.55±7.90
36.28
166.96
Lacaa
Acacia sieberiana
Mimosaceae
NFT
5
17.68
30.73±14.46
53.30
153.64
Verbenaceae
FT
6
8.53
23.08±10.89
34.30
138.47
Caesalpiniacaea
NFT
19
0.65
6.50±3.34
11.39
123.52
Mimosaceae
NFT
5
10.73
23.77±21.39
61.43
118.83
Umbrellifereae
NFT
12
0.82
9.63±16.42
57.99
115.54
Moraceae
FT
3
11.36
24.99±22.73
51.23
74.96
Leguminoceae
NFT
7
3.70
10.61±5.64
20.23
74.30
Caesalpiniacaea
FT
3
4.21
24.53±34.42
64.27
73.58
Rubiaceae
NFT
4
3.11
15.22±10.73
28.54
60.88
Mimosaceae
NFT
4
1.42
10.68±9.30
21.32
42.70
Loganiaceae
FT
2
12.93
17.92±7.05
22.90
35.83
Anarcardiaceae
FT
3
5.67
9.22±6.15
16.32
27.66
Mimosaceae
NFT
2
10.98
12.28±1.84
13.58
24.56
Oywelo
Ogali
Owak
Olweto
Oduru
Kicoro
Chwa
Odwong
Oryang
Alingwalo
Kwogo
Otoko
Vitex doniana
Piliostigma thonningii
Albizia grandibracteata
Lonchocarpus laxiflorus
Ficus sur
Erythrina abyssinica
Tamarindus indica
Gardenia ternifolia
Acacia hoclii
Strychnos innocua
Lannea schweinfurthii
Acacia Senegal
FT
Lawrewrecu Bridelia scleroneura
Moraceae
2
3.80 7.51±5.24
11.21
15.01
Total
18950.88
FT=Fruit Tree Max=Maximum Min=Minimum N=Number of individual trees NFT=Non-Fruit Tree SD=Standard
Deviation
32
Besides Ficus tree species, other fruit tree species such as Vitellaria paradoxa ssp. nilotica and
Mangifera indica also had high carbon sequestration potential of 74.82 tCO2/ha and 55.69
tCO2/ha respectively. Non-fruit tree species had low carbon sequestration potential with
Combretum fragrans having the highest carbon sequestration potential being of 35.67tCO2/ha
(Table 6).
Fruit trees contributed the highest proportion (84%) of total amount of carbon sequestered with
Vitellaria paradoxa ssp. nilotica contributing 64% of the total carbon sequestered by on-farm
tree species (Table 7).
There was significant variation in the amount of carbon sequestered by different on-farm tree
species (Table 8).
Table 8: Analysis of variance for on-farm tree species carbon sequestration potential as a
function of different on-farm tree species
Variables
Different individual Between
on-farm tree species Groups
Within Groups
Total
Sum of Squares
Df
Mean
Square
410895.016
24
17120.626
1989916.475
2400811.491
366
390
5436.930
F value
p value
3.149
.000
On-farm tree species retained during farm establishment and after being protected to allow
natural regeneration had the highest and lowest average carbon sequestered with each producing
65.5 tCO2/ha and 22.9tCO2/ha respectively (Figure 6).
Tree species which had the highest mean carbon sequestration potential after being retained
during farm establishment, protected to allow natural regeneration and planted were Ficus ovata,
Ficus natalensis and Mangifera indica with each sequestering 184 tCO2/ha, 50 tCO2/ha and 56
tCO2/ha respectively. All these established on-farm tree species are fruit tree species (Figure 7)
33
Figure 6: Mean carbon sequestered by on-farm tree species (Retained during farm
establishment, protected to allow natural regeneration and planted)
4.4.2 Variation in Carbon Sequestered by Trees On Farm
On-farm tree species carbon sequestration varied by different Dbh categories of Dbh <20cm,
Dbh ≤ 20< 60cm and Dbh ≥ 60 cm (P≤ 0.05). On-farm tree species carbon sequestration
potential varied with on-farm tree species abundance (P≤ 0.05), on-farm tree species diversity
(P≤ 0.05) and also by farms (P≤ 0.05) and their geographical locations (Table 9).
34
Figure 7: Mean carbon sequestered by each on-farm tree species (Retained during farm
establishment, protected to allow natural regeneration and planted)
Significant differences in the mean of on-farm tree species carbon sequestered were in the groups
of Dbh <20cm and Dbh ≤ 20< 60cm (P≤ 0.05), Dbh <20cm and Dbh ≥ 60 cm (P≤ 0.05) and Dbh
≤ 20< 60cm and Dbh ≥ 60 cm (P≤ 0.05) (Table 10).
35
Table 9: Analysis of variance for on-farm tree species carbon sequestration as a function of
on-farm tree species in different Dbh categories, on-farm tree species abundance and
diversity, on-farms and geographical locations
Variables
On-farm tree species Between
in different tree
Groups
species groups
Within Groups
Total
On-farm tree species Between
abundance
Groups
Within Groups
Total
On-farm tree species Between
diversity
Groups
Within Groups
Total
On-farms
Between
Groups
Within Groups
Total
Geographical
Between
locations
Groups
Within Groups
Total
Sum of
Squares
1306017.692
1094793.800
2400811.491
133919860.040
1240609.084
135160469.124
134604134.573
556334.551
135160469.124
Mean
Square
df
F value
2 653008.846
388
390
p value
231.429
.000
431.787
.000
190.102
.000
2.727
.000
2.617
.000
2821.634
26783972.0
08
20 62030.454
25
9614581.04
14
1
11 50575.868
25
5
785238.920
59
13309.134
1615572.571
2400811.491
331
390
4880.884
1780563.758
204
8728.254
620247.733
2400811.491
186
390
3334.665
Table 10: LSD of mean comparisons of amount of carbon sequestered by different on-farm
tree species groups
Tree Species
Groups
Dbh <20cm
Dbh ≤ 20< 60cm
Dbh ≥ 60 cm
Tree Species Groups
Dbh ≤ 20< 60cm
Dbh ≥ 60 cm
Dbh <20cm
Dbh ≥ 60 cm
Dbh <20cm
Dbh ≤ 20< 60cm
Mean
Difference Std. Error
-33.6518*
7.1211
230.3702*
19.9705
33.6518*
7.1211
196.7184*
19.6716
230.3702*
19.9705
196.7184*
19.6716
Sig.
.000
.000
.000
.000
.000
.000
95% Confidence Interval
Lower Bound Upper Bound
-47.654
-19.650
-269.638
-191.103
19.650
47.654
-235.398
-158.039
191.103
269.638
158.039
235.398
* The mean difference is significant at 0.05 level
There was no significant variation of on-farm tree carbon sequestered by on-farm tree species
richness (P>0.05) and on-farm tree species composition (P>0.05) (Table 11).
36
Table 11: Analysis of variance for on-farm tree species carbon sequestration as a function
of on-farm tree species richness and composition
Variables
On-farm tree species Between
richness
Groups
Within Groups
Total
On-farm tree species Between
composition
Groups
Within Groups
Total
Sum of
Squares
df
Mean
Square
148033.212
3
49344.404
2647527.182
2795560.394
213
216
12429.705
1
96056.593
215
216
12555.832
96056.593
2699503.801
2795560.394
37
F value
p value
3.970
.009
7.650
.006
CHAPTER FIVE
DISCUSSION
5.1
On-farm Tree Species Diversity
5.1.1 On-farm Tree Species Abundance
Many trees belonging to various tree species and families were retained on-farm for provision of
sustainable products and services. In this study, on-farm tree species abundance was higher than
on-farm tree species abundance in agricultural landscapes in some parts of the Uganda (Boffa et
al., 2008). The most abundant tree species were from Sapotaceae and Combretaceae families.
Vitellaria paradoxa ssp. nilotica (Indigenous fruit tree species) and Combretum collinum were
the most abundant and other than these tree species, rest of tree species belonging to many
families had very low abundance. Such few tree species usually contribute the highest proportion
of the total number of trees on-farm (Boffa et al., 2005; Boffa et al., 2008, Nakakaawa &
Vedeld, 2009; Gwali et al., 2015).
According to Gwali et al. (2015) and Boffa et al. (2008) findings shows that fruit trees are
among the most abundant tree species on-farm due to them having many individuals retained onfarm as compared to other tree species. The presence of many fruit trees usually contributes to a
sustainable significant amount of sequestered carbon having been retained for household food
security and income generation. The presence of large number of trees from particular tree
species which are retained for sustainable reasons such as for household food security, household
income generation, farm boundary markings/land tenure security and wind breaks do not only
promote retention of many trees on-farm but also contribute to high tree species abundance
(Boffa et al., 2008; Gwali et al., 2015) and large amount of sequestered carbon (Albrecht &
Kandji, 2003; Montagnini & Nair, 2004; Nair et al. 2009).
As has been reported by Boffa et al. (2008) and Nakakaawa & Vedeld (2009) many households
are not actively involved in on-farm tree planting but mostly concentrate on deliberate retention
of tree species during farm establishment (Figure 6). The respondents also do protect wildings to
allow natural regeneration after farm establishment (Okullo & Waithum, 2007). Retention during
38
farm establishment and protection of natural regeneration has made Vitellaria paradoxa ssp.
nilotica to be the most abundant on-farm tree species.
Vitellaria paradoxa ssp. nilotica has been declared as a protected tree species by Agago District
Local Government. The felling of this tree species is prohibited and Agago District Local
Government works together with local community members and clan leaders in identifying and
levying fines on those who contravene the law (Okaka, 2014). This implies that during farm
establishment Vitellaria paradoxa ssp. nilotica trees are retained thereby contributing to its high
abundance after the farms have been established.
5.1.2 On-farm Tree Species Diversity
Several studies have shown that, integration of trees on-farm usually result into tree species
diversity (Kindt etal., 2004, Boffa et al., 2005, Okullo & Waithum,2007; Boffa et al., 2008;
Henry etal., 2008; Gwali et al.,2015). A study conducted by Okullo & Waithum (2007) showed
that continuously cultivated dryland farms had low tree species diversity due to the fact that tree
species were not allowed to naturally regenerate as opposed to fallows. In this study, tree species
diversity was relatively high because various tree species were integrated on farms through a
combination of deliberate retention of trees during farm establishment and protection of wildings
to allow natural regeneration after farm establishment.
Even though on-farm tree species diversity was high, majority of the tree species retained onfarm belong to only one quarter of the tree family while one half of the tree family encountered
on-farms only had one tree species each. This study confirms the findings of several studies
(Okullo & Waithum, 2007; Nakakaawa & Vedeld, 2009; Gwali et al.,2015; Dawoe et al., 2016)
which noted that most tree species retained on-farm belong to very few families and most tree
families have only one tree species retained on-farms (Okullo & Waithum, 2007; Gwali et al.,
2015).
On-farm tree species integration processes such as tree species retention during farm
establishment, planting and protection to allow natural regeneration after farm establishment can
maintain and increase on-farm tree species diversity (Okullo & Waithum, 2007; Ordonez et al.;
2013).
39
Tree species retained during farm establishment are more diverse than tree species which are
planted and protected to allow natural regeneration (Okullo & Waithum, 2007). This is so as
only one naturalized tree species (Mangifera indica) is widely planted. It is also evident that onfarm tree species integration from a combination of retention during farm establishment,
protection to allow natural regeneration) and planting can promote tree species diversity (Okullo
Waithum,2007; Boffa et al., 2008; Gwali et al., 2015) and consequently sustainable tree species
carbon sequestration (Montagnini & Nair, 2004; Nakakaawa & Vedeld, 2009).
According to Ordonez et al. (2013), farm establishment reduces on-farm tree diversity due to
gradual loss of on-farm tree species. In this study, respondents reported that their land had high
on-farm tree species whose number dropped after farm establishment. This could have been due
to selective cutting and removal of unwanted trees by farmers. Indeed failure to integrate certain
tree species could lead to loss of particular on-farm tree species thereby contributing to reduction
in the diversity of tree species on-farms (Gwali et al., 2015).
Although most farms had high tree species richness, less even tree species distribution was
witnessed with majority of on-farm tree species being found in very few farms. This finding
confirms the report by Boffa et al. (2005) who noted that East African farms commonly have
very uneven number of tree species; being attributed to retention of few tree species for
provision of food, biomass energy and income generation for households.
5.2
Factors Influencing Retention of Trees On Farm
On-farm tree species integration with various crops is widely practiced in various communities
in the tropics (Noble & Dirzo, 1997; Boffa, 1999; Okullo & Waithum, 2007; Henry et al., 2008;
Luedeling et al., 2011; Zomer et al., 2014; Kyarikunda et al., 2017).Some of these tree species
are retained on-farm for the provision of various products and services (Boffa 1990; Anyonge &
Roshetko, 2003; Teklehaimanot, 2004).According to Arnold & Dewees (1995), Boffa (1990),
Garrity (2004), Teklehaimanot (2004) and FAO (2012), tree species are retained on-farms for
provision of food, energy and cash income for households.
In this study factors which highly influenced retention of on-farm tree species are needs for food
and biomass energy for households. In addition, on-farm tree species are also retained by rural
community members to meet various needs ranging from household income generation, farm
40
boundary markings/land tenure security to creation of wind breaks. These additional needs
promote sustainable utilisation of on-farm tree species thus reducing pressure on woodland or
forest (Boffa et al., 2005).
Much as the respondents’ need like fuel biomass energy usually affects the total number of trees
on-farm (Neufeldt etal., 2009; Zomer et al., 2014), in this study the demand for biomass energy
did not have a negative impact on retention of trees on-farms as most respondents reported that
on-farm tree species would be retained until maturity. The sustainable utilisation of on-farm tree
species as stated above thus can maintain or increase tree species diversity (Boffa et al., 2008;
Gwali et al., 2015) and promotes sustainable tree species carbon sequestration outside woodlands
or forests (Albrecht & Kandji 2003; Montagnini & Nair, 2004; Nair et al. 2009).
Promoting on-farm tree species retention is very critical as the loss of trees from woodlands or
forests is widespread (Kyarikunda et al., 2017).As agricultural activities intensifies the total
number of trees on-farms is also affected(Boffa 1999; Zomer et al.,2014).For instance, during
farm establishment many tree species are not retained and as crop production continues for
several years, these tree species are not either planted or protected to allow natural regeneration
because respondents usually do not have reasons for their retention. Consequently avoiding
retention of particular tree species during and after farm establishment reduces on-farm tree
species abundance and diversity (Ordonez et al., 2013; Gwali et al., 2015) and carbon
sequestration (IPCC, 2014).
5.3
Carbon Sequestered by Trees On Farm
5.3.1 Amount of Carbon Sequestered by On-farm Trees
Various on-farm tree species encountered contributed to a significant amount of sequestered
carbon. Ficus ovata and Piliostigma thonningii has the highest and least carbon sequestration
potential respectively. This implies that the inclusion of trees on-farm contribute significantly to
carbon sequestration (Albrecht & Kandji, 2003; Montagnini & Nair, 2004;2004; Henry et al.,
2008; Nair et al. 2009). In this study, tree species mainly preferred for biomass energy
sequestered the least amount of carbon. The need for biomass energy by households is one of the
factors affecting the total number of tree species (Neufeldt etal., 2009; Zomer et al., 2014) and
the amount of carbon sequestered on-farm (IPCC, 2014). Consequently sustainable utilisation of
41
particular tree species for biomass energy should be enforced as a way of promoting retention
and carbon sequestration of on-farm trees.
According to Mng’omba & Beedy (2013), on-farm fruit tree species can remove CO2 from the
atmosphere at varying levels as a result of high biomass accumulation and long life span of such
trees. In this study, on-farm fruit tree species which had been retained for sustaining some
benefits had many individual stands that contributed to an overall high proportion of total
amount of carbon sequestered on-farm with Vitellaria paradoxa ssp. nilotica contributing more
than half of the total sequestered carbon. The implication is that sustainable management and
utilisation of fruit tree species has the overall effect of promoting on-farm tree retention and
thereby contributing to long term carbon sequestration.
Long-lived tree species such Ficus, Mangifera and Vitellaria tree species can sequester more
carbon than short-lived trees such as Combretum and Grewia tree species. This study confirms
the findings of Maura-Costa et al., (1996) who noted that, long-lived tree species with dense
wood have greater carbon sequestration potential than tree species that are short-lived with light
wood. Although majority of the short lived trees are usually protected to naturally regenerate
(Okullo & Waithum, 2007), retention of both short- and long-lived tree species for sustainable
utilisation can promote and enhance an overall carbon sequestration potential on farms (MauraCosta & Aukland,1996).
As has been reported by Gielen (1998), wood harvested for construction material contains
significant amounts of stored atmospheric CO2 which can further be stored for decades or
centuries thus making wood a net CO2 sinks. In this study, retained on-farm tree species intended
for future utilization as construction materials contributed to high amount of total sequestered
carbon. The utilisation of these tree species for construction materials will therefore contribute to
long term storage of sequestered carbon in the harvested wood thereby resulting to avoidance of
the release of large amount of sequestered carbon back to the atmosphere (Gielen, 1998).
42
5.3.2 Variation in the Amount of Carbon Sequestered by On-farm Trees
The study revealed significant variation in the amount of carbon sequestered by different
individual on-farm tree species within groups of Dbh <20cm, Dbh ≤ 20< 60cm and Dbh ≥ 60 cm
and also within groups of Dbh <20cm and Dbh ≤ 20< 60cm, Dbh <20cm and Dbh ≥ 60 cm and
Dbh ≤ 20< 60cm and Dbh ≥ 60 cm. According to Maura-Costa (1996) and Lamlom & Savidge
(2003), different tree species usually sequester different amount of carbon. Such information on
variation in the amount of sequestered carbon by different tree species helps in selection and
inclusion of tree species in farming systems so as to maximise carbon sequestration on-farms.
A study conducted by Jose (2009) shows that on-farm tree carbon sequestration varies with tree
species composition, age and geographical location of the agricultural system. In this study onfarm tree species carbon sequestration varied with geographical location, on-farm tree species
abundance and on-farm tree species diversity. This is attributed to the presence of many tree
species and individuals stand with different carbon sequestration potential (Lamlom & Savidge,
2003; Mng’omba & Beedy, 2013; Mayank, 2016). However, carbon sequestration did not vary
with tree species richness and composition.
Although many farms had more than one tree species with high carbon sequestering level, few
farms had many pure stands of Vitellaria paradoxa ssp. nilotica trees which is the tree species
with the highest proportion of on-farm sequestered carbon. Ideally, information on on-farm tree
species carbon sequestration potential can helps in its promotion on-farm. Such information
could be used to guide farmers and investors who are willing to participate in carbon trading
(Kung’u et al., 2013) which is currently taking place in other parts of Uganda (Nakakaawa &
Vedeld, 2009).
43
CHAPTER SIX
CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusions
The following conclusions have been drawn from the study:
a) There was high on-farm tree species diversity with high on-farm tree species richness and
less even distribution. Vitellaria paradoxa ssp. nilotica was the most abundant tree species
(22 Stems/ha).
b) On-farm tree species were mainly retained for biomass energy and food security. Other
benefits included household income generation, farm boundary markings/land tenure security
and wind breaks. While Vitellaria paradoxa ssp. nilotica was the main multipurpose tree
species retained for provision of food for households, Combretum collinum and Piliostigma
thonningii were retained on farm for biomass energy.
c) The mean values of sequestered carbon by on-farm trees were between 6.50tCO2/ha for
Piliostigma thonningii to 183 tCO2/ha for Ficus ovata.
d) There was a significant variation in the amount of carbon sequestered by different individual
on-farm tree species (P≤0.05). Sequestered carbon varied significantly in different tree
species groups of Dbh <20cm, Dbh ≤ 20< 60cm and Dbh ≥ 60 cm (P≤0.05).
e) On-farm tree species carbon sequestration potential varied with on-farm tree species
abundance (P≤0.05), species diversity(P≤0.05) and their geographical location(P≤0.05).
44
6.2 Recommendations
The following recommendations have been made:
i) Sustainable on-farm tree-based technology like retention of trees in the crop field and onfarm boundaries should be encouraged as a way of attaining more sustainable socioeconomic and ecological benefits of on-farm trees. There is a need to promote improved
fallows to sustainably maintain household biomass energy and minimise pressure on
woodland forest and existing on-farm tree species.
ii) Farmers should also be trained on Forestry Business Development skills to promote
marketing of on-farm fruits and associated products as opposed to other non-fruit tree species
products (Fuel wood and construction materials). This should be done by farmers being
undertaken through a process of forming forestry business organisations and provision of
forestry business management advisory services at local and national levels.
iii) Establishing carbon credit markets for on-farm trees would widen the provision of
sustainable socio-economic benefits of on-farm trees. Thus, to sustainably manage existing
or develop on-farm tree-based systems which are resilient to environmental changes, the
level of carbon sequestration potential of different on-farm tree species have to be computed
and incorporated into various on-farm tree management plans.
iv) There is a need to evaluate the links between pattern of distribution, duration of retention,
abundance, diversity and carbon sequestration potential of on-farm trees verses land and
tenure security.
45
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APPENDICES
Appendix 1: Tree Inventory Form
Farm Inventory data will be used to address Objective 1: To assess on-farm tree species diversity
and Objective 3: To determine the amount and variation of carbon sequestered by trees on farms
Tree Inventory Form
Farm No…………………………………………….………...…………………………………….
Location (Sub-County/Parish/Village)...…………………/……………………/.………………....
Species Composition……………………………………………………………………………...
Tree
Tree
Number Species
Local
Tree Species
Dbh(m) Height(m) Crown
Geographical
Scientific
Diameter(m)
Coordinates
Names
NS
Northing Easting
Names
NS-North South Direction
ES-East South Direction
56
EW
Appendix 2: Wood Density Values
On-farm retained tree
On-farm Tree Species Scientific
Wood
Name
Density(g/cm3)
Serial
species (Local Name in
Number
Acholi)
1
Yaa
Vitellaria paradoxa ssp. nilotica
0.72
Drichi, P.(2003)
2
Odugu
Combretum collinum
0.79
Drichi, P.(2003)
3
Pogo
Grewia mollis
0.65
Drichi, P.(2003)
4
Olam
Ficus sycomorus
0.64
Drichi, P.(2003)
5
Anwa
Combretum fragrans
0.79
Drichi, P.(2003)
6
Opok
Terminalia brownie
0.64
Drichi, P.(2003)
7
Olweto
Lonchocarpus laxiflorus
0.58
Drichi, P.(2003)
8
Muyembe
Mangifera indica
0.60
Drichi, P.(2003)
9
Ogali
Piliostigma thonningii
0.63
Drichi, P.(2003)
10
Ayuca
Lannea
0.55
Drichi, P.(2003)
11
Olim
Combretum molle
0.74
Drichi, P.(2003)
12
Owak
Albizia grandibracteata
0.64
Drichi, P.(2003)
13
Kworo
Ficus glumosa
0.53
Drichi, P.(2003)
14
Pwo
Ficus ovata
0.53
Drichi, P.(2003)
15
Oywelo
Vitex doniana
0.48
Drichi, P.(2003)
16
Lacaa
Acacia sieberiana
0.65
Drichi, P.(2003)
17
Lawrewrecu
Bridelia scleroneura
0.75
Drichi, P.(2003)
18
Oryang
Acacia hockii
0.72
Drichi, P.(2003)
19
Alingkwalo
Strychnos innocua
0.72
Drichi, P.(2003)
20
Kicoro
Erythrina abyssinica
0.38
Drichi, P.(2003)
21
Kidit
Ficus natalensis
0.49
Drichi, P.(2003)
22
Otoko
Acacia Senegal
0.57
Drichi, P.(2003)
23
Chwa
Tamarindus indica
0.82
Drichi, P.(2003)
26
Kwogo
Lannea schweinfurthii
0.54
Drichi, P.(2003)
27
Odwong
Gardenia ternifolia
0.54
Drichi, P.(2003)
29
Oduru
Ficus sur
0.46
Drichi, P.(2003)
Source
57
Appendix 3: Retention of On-Farm Tree Species Questionnaire
I am a student of Makerere University, College of Agricultural and Environmental Sciences,
School of Forestry, Environmental and Geographical Sciences conducting research on ‘‘Tree
Species Diversity and their Carbon Sequestration Potential in cultivated farms Agago
District.’’
The goal of this study is to evaluate the contribution of integration of trees to on-farm tree
species diversity and their carbon sequestration potential in Agago District, Northern Uganda.
This questionnaire will be used to collect data to address this research objective ‘‘To Determine
Factors Influencing the Retention of Trees on Farm.’’
Based on the above background, I am therefore kindly requesting you to allocate some time and
answer the questions below.
Questionnaire No…………………………...………………………………………………………
Farmer’s Number……..…...………………………………………………………………………..
Sub-county/Parish/Village:……………………/………………………/……..……………………
PART 1: SOCIO-DEMOGRAPHIC CHARACTERISTICS OF THE RESPONDENTS
1.1 Sex:
Male [ ]
Female [ ]
1.2 Age:………………….Years
1.3 Marital status: Single [ ] Married [ ] Divorced [ ] Widowed [ ]
1.4 Level of education: None [ ] Primary [ ] Secondary [ ] College [ ]
1.5 Occupation: Farmer [ ]
Trader [ ]
Service worker [ ] Other …………………
1.6 Family size (number of people per household): < 5 [ ] 6-10 [ ] Over 10 [ ]
1.7 Annual income (Shs): < 100,000 [ ] 101,000-200,000 [ ]
201,000-300,000 [ ]
Over
301,000 [ ]
1.8 Do you own land? Yes [ ]
No [ ]
1.9 If yes, what is the size of your land? < 1 ha [ ]
1 – 3 ha [ ]
4- 6 ha [ ] Over 6 ha [ ]
PART 2: RETENTION OF ON-FARM TREE SPECIES
2.1 Which crops are found on your farm?
Currently……………………………………………………………………………………………
Last 3 Months………………………………………………………………………………………
58
Last 6 Months………………………………………………………………………………………
2.2Could you please list the tree species on your farm?...................................................................
2.3 Could you please list the reasons why you have retained the on-farm tree species (Refer to
table 1)?
Table 1: Data Sheet-Retention of On-farm Tree Species
On-farm Tree Species Reasons for On-farm Tree Species Retention
1………………….........................................................
2……………………………………………………….
3……………………………………………………….
4……………………………………………………….
5…………………………………………………….....
1………………….........................................................
2……………………………………………………….
3……………………………………………………….
4……………………………………………………….
5…………………………………………………….....
1………………….........................................................
2……………………………………………………….
3……………………………………………………….
4……………………………………………………….
5…………………………………………………….....
1………………….........................................................
2……………………………………………………….
3……………………………………………………….
4……………………………………………………….
5…………………………………………………….....
2.4. For how long have you retained the on-farm tree species?........................................................
2.5 Will you allow the retained on-farm tree species to reach maturity? Yes [ ]
No [ ]
2.6 If no then what are the reasons for not letting them reach maturity?.........................................
59
2.7. Which retained on-farm tree species were protected to allow them to grow on their own after
your farm was established?................................................................................................................
2.9 Which retained on-farm tree species were planted?..................................................................
Thank You So Much for Your Time
60
Appendix 4: Socio-Economic and Demographic Characteristics of the Respondents
Socio-Economic and Demographic Characteristics of the Respondents
Variables
Sex
Male
Female
Age
20-40
40-60
60-80
80-100
Marital Status
Divorced
Married
Widowed
Education Level
College
None
Primary
Secondary
Occupation
Civil service worker
Farmer
Local leader
Family Size
6 to 10
Below 5
Over 10
Annual Income
101,000-200,000
201,000-300,000
Below 100,000
Over 301,000
Land Ownership
Yes
No
Land Size
1-3 ha
4-6 ha
Over 6 ha
None
%
70
30
22
23
42
13
05
88
07
05
25
57
13
02
92
07
62
20
18
10
45
7
38
98
02
07
13
78
02
61