Thesis_Status_of_Population_Structure_Size_and_Distribution_of_Prunus_africana_in_North_and_South_Nandi_Forests

STATUS OF POPULATION STRUCTURE, SIZE AND DISTRIBUTION OF
Prunus africana (HOOK. F.) KALKMAN (ROSACEAE) IN NORTH AND
SOUTH NANDI FORESTS
HILLARY KIMUTAI KOROS
A thesis submitted in partial fulfillment for the requirements of the award of Master
of Science in Environmental Biology of Masinde Muliro University of Science and
Technology
October, 2016

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COPYRIGHT
This thesis is copyright materials protected under the Berne Convention, the
copyright Act 1999 and other international and national enactments in that behalf, on
intellectual property. It may not be reproduced by any means in full or in part except
for short extracts in fair dealing for research or private study, critical scholarly
review or discourse with acknowledgment, with written permission of the Dean
School of Graduate Studies on behalf of both the author and Masinde Muliro
University of Science and Technology.

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DEDICATION
This thesis is dedicated to my beloved parents Mr. Philip Ruto and Mrs. Ester Ruto,
for instilling the discipline and value of education in me.

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ACKNOWLEDGEMENT
I thank the almighty God for giving me the strength, good health and endurance to
carry out my studies successfully. This work was conducted under the sponsorship of
Nature Kenya in collaboration with the National Museums of Kenya (NMK) under
the ―Strengthening the Protected Area Network within the Eastern Montane Forest
Hotspot of Kenya‖ Programme.
I thank my supervisors Dr. Martha Konje and Dr. Itambo Malombe for their
immense contribution and academic guidance towards the successful completion of
this research. I could not have imagined having better advisors and tremendous
mentors for my MSc. study. I am grateful for support of Mr. Dickens Odeny and Mr.
Christopher Chesire for introducing me to data collection methods, data analysis and
GIS use for mapping. I wish to acknowledge the Faculty members of the department
of Biological Sciences at MMUST whom I constantly consulted for advice especially
while writing this thesis.
I also thank Nature Kenya (Nairobi and Kapsabet offices) who facilitated my stay
and transport during field work. I wish to thank the Community Forest Association
(CFA) (Kobujoi Office) for hosting us in their Bandas. Furthermore, I sincerely wish
to thank the Kenya Forest Service (KFS) (Kobujoi office) for providing us with
security while in the field. Many thanks also go to my fellow colleagues namely
Melly, Wambua, Mutai, Samson and Shadrack for the teamwork we had in the field.
Last but not the least, I owe an enormous debt of gratitude to my wife Peris Musitia
and daughter Verena Cherotich for their infinite patience, encouragement and
support during my fieldwork and the writing of this thesis.

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ABSTRACT
The International Union for Conservation of Nature (IUCN) documented the
conservation status of Prunus africana (Hook. F.) Kalkman as vulnerable and
showed potential distributions of the species. However, this information is at large
scale and does not provide local information on the species. The study aimed at
highlighting the status of P. africana population, ecological association with other
species, uses and conservation threats in North and South Nandi forests. Stratified
Random Sampling based on disturbance gradient, assuming higher impacts near
forest edges was used. Belt transects of two km by 400 m were established and P.
africana individuals used as reference point for establishing of five Permanent
Sampling Plots (PSP) along each transect to determine the status of P. africana
population, structure, size and distribution. The PSP was further subdivided into 20
m by 20 m subplots for detailed sampling to examine the ecological association of P.
africana with other plant species and conservation threats. Semi structured
questionnaires were used to interview the local community within 1 km buffer zone
around South Nandi Forest to determine their uses and conservation measures of P.
africana. PAleontological STatistics (PAST) (Version 4.3) was used for descriptive
and inferential statistics and statistical significance levels reported at p < 0.05 and
95% confidence level. Modeled potential distribution and mapping of P. africana
distribution was done using Maximum Entropy Modeling MaxEnt (version 3.3.3k)
and Arc GIS (version 10) respectively. Ecological association of P. africana with
other species was analyzed using Plymouth Routines In Multivariate Ecological
Research (PRIMER) (Version 5). Data from questionnaires were analysed using
Statistical Package for Social Sciences (SPSS) (version 20). The study established
that the density of P. africana was two trees/ha. The Diameter at Breast Height
(DBH) class size distribution of P. africana assumed a ‗j‘ shaped distribution with
low representation in the younger DBH class size. Other woody species had an
inverse ―j‖ shaped distribution. There was statistically significant difference in DBH
variance (F-test p<0.05) and mean DBH (T test p<0.05) between the South and
North Nandi forests. The modeled distribution showed higher density of P. africana
towards the North Eastern part of South Nandi forest around Kobujoi area. The most
utilized part of P. africana by local community is the stem whereas they use the tree
for multi-purpose functions including medicine for humans and animals, firewood,
timber and charcoal. The key forest threats were overgrazing, firewood collection,
logging and charcoal burning. The study concluded that P. africana regeneration is
high but faced with poor survival rates especially due to overgrazing. The study
recommends both in-situ and ex-situ conservation measures which includes control
of overgrazing, creation of awareness on the importance of P. africana to the locals,
encouraging planting of the tree on farms and establishment or support of the local
existing nurseries for propagation of this multipurpose tree.

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TABLE OF CONTENTS
DECLARATION .......................................................Error! Bookmark not defined.
COPYRIGHT..............................................................................................................iii
DEDICATION............................................................................................................iv
ACKNOWLEDGEMENT ...........................................................................................v
ABSTRACT................................................................................................................vi
TABLE OF CONTENTS...........................................................................................vii
LIST OF TABLES......................................................................................................xi
LIST OF FIGURES ...................................................................................................xii
ACRONYMS AND ABBREVIATIONS .................................................................xiv
CHAPTER ONE: INTRODUCTION ......................................................................1
1.1 Background to the study.....................................................................................1
1.2 Statement of the problem ...................................................................................4
1.3 Justification of the study.....................................................................................4
1.4 Objectives...........................................................................................................5
1.5 Research hypothesis ...........................................................................................5
CHAPTER TWO: LITERATURE REVIEW.........................................................6
2.1 Taxonomic description of Prunus africana........................................................6
2.2 Phenology and life cycle of Prunus africana.....................................................7
2.3 Regeneration of Prunus africana .......................................................................7
2.4 Spatial distribution and abundance of Prunus africana .....................................8
2.5 Uses and exploitation of Prunus africana..........................................................9
2.6 Conservation threats to Prunus africana..........................................................10
2.7 Application of GIS in mapping of endangered species....................................12

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CHAPTER THREE: MATERIALS AND METHODS .......................................13
3.1 Study Area........................................................................................................13
3.2 Sampling design ...............................................................................................15
3.2.1 Determination of the abundance and spatial distribution of P. africana...16
3.2.2 Determination of DBH, height and crown cover of P. africana and other
woody species.....................................................................................................16
3.2.3 Determination of the recruitment and regeneration of P. africana and other
woody species.....................................................................................................17
3.2.4 Determination of Phenology of P. africana...............................................17
3.2.5 Determination of the ecological association of P. africana with other plant
species.................................................................................................................17
3.2.6 Species identification.................................................................................18
3.2.7 Determination of conservation threats to P. africana and other species ...18
3.2.8 Determination of uses and conservation of P. africana by the locals .......19
3.3 Data analysis.....................................................................................................20
3.3.1 Population status and spatial distribution of P. africana in North and South
Nandi forests.......................................................................................................21
3.3.2 Ecological association of P. africana with other plant species in North and
South Nandi forests.............................................................................................21
3.3.3 Uses and conservation threats of P. africana by the local community
around North and South Nandi forests ...............................................................23
CHAPTER FOUR: RESULTS ...............................................................................24
4.1 Population density, size and spatial distribution of P. africana in North and
South Nandi forests ................................................................................................24
4.1.1 Population density of P. africana in North Nandi forests .........................24

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4.1.2 Density of P. africana in South Nandi forests...........................................24
4.1.3 Density distribution of P. africana in South Nandi forest and the 1 km
buffer zone..........................................................................................................26
4.1.4 DBH class size distribution of P. africana in North and South Nandi
forests..................................................................................................................27
4.1.5 DBH Class size distribution of P. africana in 1 km buffer zone of South
Nandi forest.........................................................................................................29
4.1.6 Height class distribution of P. africana in North and South Nandi forests30
4.1.7 Crown diameter class size distribution of P. africana................................31
4.1.8 DBH, Height and Crown diameter correlation ..........................................32
4.1.9 Density of Prunus africana seedlings/Saplings.........................................33
4.1.10 Phenology of Prunus africana.................................................................33
4.1.11: Priority conservation zones of P. africana in South Nandi forest..........34
4.2 Ecological association of P. africana with other plant species in North and
4.2.1 Plant growth forms.....................................................................................36
4.2.2 Floristic composition .................................................................................37
4.2.3 The general vegetation community............................................................39
4.2.4 Plant species accumulation curve ..............................................................40
4.2.5 Plant Species diversity...............................................................................41
4.2.6 Unique and rare species .............................................................................42
4.2.7 Woody tree species associated with P. africana........................................44
4.2.8 DBH class size distribution of woody species associated with P. africana44
4.2.9 Importance Values Index (IVI) of woody species.....................................45
4.2.10 Species similarity.....................................................................................48

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4.2.11 Density of woody plant seedlings............................................................49
4.3 Determination of the uses and conservation threats of P. africana by the local
communities ...........................................................................................................51
4.3.1 Study population structure.........................................................................51
4.3.2 Awareness by the local community of the population status of P. africana51
4.3.3 Sources and Uses of P. africana by the local community.........................52
4.3.4 Conservation threats of P. africana tree and other species........................54
4.3.5 Measures taken to conservation of P. africana by the locals ....................56
CHAPTER FIVE: DISCUSSION...........................................................................57
5.1 The population density, size and spatial distribution of P. africana in North and
5.2 The association of P. africana with other plant species in North and South
Nandi forests...........................................................................................................62
5.3 Uses and conservation threats of P. africana by the local community of North
and South Nandi forests .........................................................................................65
CHAPTER SIX: CONCLUSION AND RECOMMENDATIONS......................69
REFERENCES...........................................................................................................71
APPENDICES ...........................................................................................................86

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LIST OF TABLES
Table 2.1: Local names of P. africana used in some of the range countries .............. 7
Table 3.1: Indicators used to asses conservation threats to P. africana and other
species in the forest.................................................................................................... 19
Table 4.1: Density and means of DBH, height and crown length of P. africana
(≥5cm DBH) per transect (80 ha) in South Nandi forests.......................................... 24
Table 4.2: A table showing the top ten families in North and South Nandi forests.. 38
Table 4.3: Species diversity indices.......................................................................... 41
Table 4.4: Rare species recorded in North and South Nandi forests according to the
voucher specimens in the East Africa Herbarium, Nairobi........................................ 43
Table 4.5: Family, density (D) and basal area (Ba) of the principal tree species
associated with P. africana ........................................................................................ 47
Table 4.6: Density of woody plant seedlings ............................................................ 49

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LIST OF FIGURES
Figure 3.1: A map showing the study area and sampling plots. ........................................... 14
Figure 3.2: Sampling design and study plots........................................................................ 15
Figure 4.1: Density of P. africana (≥5cm DBH) per hectare (mean±SE) against distance
from the forest edge toward the interior of the forest. ........................................................... 25
Figure 4.2: Modeled potential density distribution of P. africana in South Nandi forest and 1
km buffer zone....................................................................................................................... 26
Figure 4.3: DBH frequency distribution of P. africana in North and South Nandi forests. 27
Figure 4.4: DBH distribution of P. africana in North and South Nandi forests................... 28
Figure 4.5: DBH frequency distribution of P. africana in 1 km buffer zone of South Nandi
forest. ..................................................................................................................................... 29
Figure 4.6: Height class distribution of P. africana in North and South Nandi forests........ 30
Figure 4.7: Height class distribution of P. africana in North and South Nandi forests........ 31
Figure 4.8: A linear correlation between DBH and Height of P. africana in North and South
Nandi forests.......................................................................................................................... 32
Figure 4.9: A linear correlation between DBH and Crown diameter of P. africana in North
and South Nandi forests......................................................................................................... 32
Figure 4.10: Mean density of seedlings for North and South Nandi forests......................... 33
Figure 4.11: Priority Conservation zone of P. africana in South Nandi forest .................... 34
Figure 4.12: Species diversity according to growth form in both North and South Nandi
forests..................................................................................................................................... 36
Figure 4.13: Species diversity according to growth form in Nandi forests .......................... 37
Figure 4.14: Species accumulation curve of both North and South Nandi forests ................ 41
Figure 4.15: Species diversity per plot between North and South Nandi forests ................. 42
Figure 4.16: Unique species: Nervilia bicarinata................................................................. 43
Figure 4.17: DBH class size distribution of all woody plants (≥5cm DBH) per transects in
North and South Nandi forests............................................................................................... 45
Figure 4.18: Multi-Dimensional Scaling (MDS) of plots..................................................... 48

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Figure 4.19: Top 15 plant communities in association with P. africana.............................. 50
Figure 4.20: Parts of P. africana used by the local community............................................ 53
Figure 4.21: Conservation threats of P. africana in Nandi forests ....................................... 55
Figure 4.22: Conservation threats to P. africana in North and South Nandi forests ............ 55
Figure 4.23: Steps taken to conserve P. africana by the local community........................... 56

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ACRONYMS AND ABBREVIATIONS
BIOTA Biodiversity Monitoring Transect Analysis in Africa
BPH Benign Prostate Hyperplasia
CITES Convention on International Trade in Endangered Species
E.A East Africa Herbarium
GoK Government of Kenya
GPS Global Positioning Systems
IBAs Important Bird Areas
ICRAF International Centre for Research in Agroforestry
IUCN International Union for Conservation of Nature
KIFCON Kenya Indigenous Forest Conservation
MEA Millennium Ecosystem Assessment
NEP National Environmental Policy
NMK National Museums of Kenya
NNT1 North Nandi Transect 1
NFTP Non Forest Timber Products
PAST PAleontological STatistics
PRIMER Plymouth Routines In Multivariate Ecological Research
PSP Permanent Sampling Plot
SNT1 South Nandi Transect 1
SPSS Statistical Package for Social Sciences
IVI Importance Value Index

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CHAPTER ONE
Chapter 1 INTRODUCTION
1.1 Background to the study
The Eastern afromontane biodiversity hotspot is a vast areas of Eastern Africa and
the Arabian Peninsula (Mittermeier et al., 2011). Its exceptional economic and
biodiversity values arise from this broad latitudinal and altitudinal range and a
turbulent geological history (Hitimana et al., 2004). Kenya is endowed with a rich
biodiversity and is home to some 7004 species of vascular plant of which about 500
are national endemics and 356 are threatened with extinction (GoK, 2016).
The survival of species is increasingly threatened by human activities such as habitat
loss, climate change and overexploitation (Mbatudde et al., 2013) resulting in the
dramatic transformation of the entire ecosystem on Earth. These threats to
biodiversity endanger the integrity of ecosystem services and diminish the benefits
that they provide to humans worldwide (Millennium Ecosystem Assessment [MEA],
2005).
The National Biodiversity Strategy and Action Plan (GoK, 2000), has identified the
following key challenges to successful biodiversity conservation in the country:
Adverse impacts of poverty and the rapidly increasing population has led to
encroachment into wild habitats; habitat conversion due to indiscriminate felling of
trees for wood products and energy needs and drainage of wetlands for agriculture;
insecurity in some parts of the country which are rich in biodiversity; and lack of
integration of gender concerns in planning and management of biodiversity
resources.

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The draft National Environmental Policy {NEP}(2013), notes that Kenya‘s forest
resources are being subjected to overwhelming pressure from competing land-uses
like agriculture, industry, human settlement and development of infrastructure.
Today some ecosystems are severely disturbed to the point that species diversity;
extent and quality of these habitats are severely eroded. In some cases, over 60% of
natural habitats have been lost in the last 30 years. Conservation of our threatened
flora therefore becomes urgent (MEA, 2005).
Conservation has been portrayed as a bottom-up process with a definition of species-
level targets first, from which site-level targets are developed (Garcıa et al., 2002).
Araya et al., (2009) emphasized that conservation requires detailed knowledge of the
conservation status of individual species. Given threats to biodiversity at the three
levels (species, sites and broad landscapes), targets for conservation should be set in
terms to indicate extinction avoidance, areas protected, and corridors consolidated
(Carlos et al., 2003). On the other hand, conservation outcomes are defined as the
full set of justifiable conservation targets that need to be achieved to prevent
biodiversity loss within a hotspot (Araya et al., 2009).
The IUCN Red List uses quantitative criteria in order to estimate the probability of
extinction for each species. Species classified as threatened on the Red List have a
high probability value of extinction in the medium-term future (IUCN, 2000) and
include the three IUCN categories; Critically Endangered, Endangered and
Vulnerable. Avoiding extinctions means conserving globally threatened species to
make sure that their Red List status improves or at least stabilizes. This means that
data are needed on population trends (Garcıa et al., 2002; Shii & Ashitani, 2007),
which is fundamental for species monitoring, restoration and protection.

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Although this information has been accumulating in the global Red List of
Threatened Species produced by IUCN and partners for nearly 50 years (Brooks,
2010) the knowledge of the population status of most threatened species is still
deficient (Ibisch et al., 2002). This is especially true for plants and reptiles in the
Eastern afromontane hotspot, where surveys and research on rare or threatened
species are very limited (Birdlife International, 2012).
A case in point is the conservation status of Prunus africana (Hook. F.) Kalkman
which is commercially important for its bark and has a high demand in the treatment
of Benign Prostatic Hyperplasia (BPH) (Cunningham et al., 2002; Fashing, 2004;
Jimu, 2011). Prunus africana is classified by the International Union for the
Conservation of Nature (IUCN) as vulnerable species and consequently, listed in
Appendix II of the Convention on International Trade in Endangered Species of
Fauna and Flora (CITES) (Betti, 2008; IUCN, 2013).
In Kenya, the natural populations of P. africana as a primary source of medicine and
other uses has become threatened due to over-harvesting, poor protection and
management of the protected areas (Gachie et al., 2012). Notably, the destruction of
the species in natural forests has been increasing, leading to concerns on the long-
term sustainability of harvesting and the conservation of the species (Weru, 2012;
Owiny & Malinga, 2014).

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1.2 Statement of the problem
International Union for Conservation of Nature (2012) documented the conservation
status of Prunus africana as vulnerable and showed the potential ranges of the
species. However, this information is on a global scale and does not provide
information on the local population status and conservation threats affecting the
species. It is recognized globally that the natural range of P. africana is declining and
even getting locally extinct from some of the ranges due to habitat loss and
overexploitation (Gachie et al., 2012). This has prompted a number of studies to
recommend tracking changes of the species‘ population over time. While prioritizing
species on the basis of threats and recognition by the local communities due to utility
value, P. africana was ranked highly for mapping and monitoring (Malonza et al.,
2013). This study therefore aimed at establishing the status of P. africana population,
ecological association with other species, uses and conservation threats in North and
South Nandi forests where such information is scanty.
1.3 Justification of the study
In environmental biology, without the conservation of viable populations of a
threatened species, in our case P. africana, the species could be harvested to
extinction. This has a diminishing negative effect on the social-economic livelihoods
of the local communities and narrows the options for those suffering from prostate
disorders. This study can help in providing strategies for better management and
conservation of the species and designing suitable monitoring programmes. This
information can be used to curb unsustainable exploitation of P. africana and as well
support rural development thereby contributing as an alternative source of income
when planted as a farm crop. This study therefore supports government‘s plans in the

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management of protected areas and sustainable utilization of natural resources by
influencing policy decision making process.
1.4 Objectives
The general objective was to determine the status of population structure, size and
distribution of P. africana in North and South Nandi forests.
The specific objectives were to:-
(i) Assess the population structure, size and spatial distribution of P. africana in
North and South Nandi forests
(ii) Examine the ecological association of P. africana with other plant species in
(iii) Determine the uses and conservation threats of P. africana by the local
communities in North and South Nandi forests
1.5 Research hypothesis
It was hypothesized that:-
(i) There is relatively low population density of P. africana in North and South
Nandi forest
(ii) There is no ecological association of P. africana with other plant species in
North and South Nandi forest.
(iii) There are no socio-economic uses and major conservation threats of P.
africana by the local communities in North and South Nandi forest

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CHAPTER TWO
Chapter 2 LITERATURE REVIEW
2.1 Taxonomic description of Prunus africana
Prunus africana is an evergreen canopy tree that grows to over 30 m in height (Page,
2003; Ingram et al., 2009; Mbatudde et al., 2013). The tree has a thick, black to
brown, fissured bark and straight bole that can reach a diameter of 1.5 m (Orwa et
al., 2009; Jimu, 2011).
The leaves are simple and alternately arranged and simple. The flowers are small,
white and fragrant (Orwa et al., 2009). Fruits are ellipsoid or transversely ellipsoid,
indehiscent drupe, deep red to purple-black, weighing 0.5 g, and measuring 6-7 mm
x 0.1 mm in size (Farwig, 2006). The skin (epicarp) squeezes off easily in fingers,
exposing green flesh (mesocarp) surrounding the bony endocarp. Seeds have same
shape as fruit, contained in a bony endocarp. Cotyledons are white, with a thin
papery, dry, pale yellow-brown testa. There exists one seed per fruit. Germination is
epigeal (Orwa et al., 2009).
Known under its trade name, Pygeum (Maximillian & Laughlin, 2009; Betti &
Ambara, 2013), it is the only sub-Saharan African species of more than 200 species
of the genus Prunus (Beentje 1994; Tchoundjeu et al., 2002). It grows well in the
sub-mountain and mountain forests at altitude ranging from 800 – 3000 m (Stewart,
2003; Betti & Ambara, 2013). The tree is commonly known as the African Cherry,
Red Stinkwood, or Bitter Almond (Betti, 2008; Orwa et al., 2009; Bii et al., 2010;
Weru, 2012). The local names in some of the range countries in Africa are as given
below (Table 2.1).

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Table 2.1: Local names of P. africana used in some of the range countries
Name Language Country
Bihasa Bubi Equatorial Guinea
Kumuturi Bukusu Kenya
Kwarh Muanenguba Cameroon
Mueri/muiri Kikuyu Kenya
Mueria/mweria Meru Kenya
Mueritsa/mwiritsa Luhyia Kenya
Mutimuiru/ mutimuilu Kamba Kenya
Ol-Koijuk Maasai Kenya
Omoiri Kisii Kenya
Saripaiso Bealanana Madagascar
Tenduet/tendwet Nandi/Kipsigis Kenya
Source: Adopted from Hall et al., (2002) & Weru (2012)
2.2 Phenology and life cycle of Prunus africana
Prunus africana begins flowering at an age of between 15-20 years (Simons et al.,
1998). A study in Kakamega Forest showed that flowering occurs between
November to February (Orwa et al., 2009). Pollination is by insects and seed
maturity takes 4-6 months. Fruiting is sporadic, and intensity of fruit set is variable.
The fruits are dispersed by birds and monkeys (Farwig et al., 2006). Early fruiting
seems to occur on individuals that have recently been subjected to bark removal. The
sporadic nature of fruit production has significant implications for cultivation
potential (Abebe, 2008).
2.3 Regeneration of Prunus africana
The conservation of P. africana offers a big challenge as it requires disturbance for
regeneration (Fashing, 2004). Poor establishment of the seedlings is known to be one
of the main causes of the species population decline (Orwa et al., 2009). The species
is a light demander and regeneration is best in disturbed sites or forest gaps, so it
establish well in agroforestry situations (Fashing, 2004; Farwig, 2006; Schaab, 2010;
Weru, 2012; Owiny & Malinga, 2014). However natural populations show unusual

8
size class distributions, suggesting that regeneration has been intermittent (Gachie et
al., 2012). This is mainly due to problems with longer-term establishment of young
seedlings and selective bark extraction. Cunningham & Mbenkum (1993) suggest
that, this could also be due to forest disturbance. It is light demanding and responds
well to cultivation (Weru, 2012). Since its populations are diminishing rapidly, there
is need to initiate optimum conservation strategies at both in-situ and ex-situ (Franzel
et al., 2009).
2.4 Spatial distribution and abundance of Prunus africana
Prunus africana is a medicinal tree indigenous to the montane regions of West,
Central, East and Southern Africa, including Madagascar (Jimu, 2011; Kadu et al,.
2011; Kadu et al., 2013; Mbatudde et al., 2013; Vinceti et al., 2013; Cheboiwo et al.,
2014). In Southern Africa it occurs in Angola, Lesotho, Malawi, Mozambique, South
Africa, Zambia and Zimbabwe in South Tropical Africa. In Eastern Tropical Africa,
P. africana is found in Burundi, Congo, Ethiopia, Kenya (Farwig, 2008a; Gachie et
al., 2012), Rwanda, Sudan, Tanzania (Maximillian & Laughlin, 2009) and Uganda.
The species also occurs in Cameroon, Equatorial Guinea and Nigeria of West
Tropical Africa, as well as in Madagascar (Betti & Ambara, 2013).
In Kenya, the species occurs in moist evergreen forests, riverine, often in remnants or
on forest margins between 1350-2750 m above sea level (Beentje, 1994). It is
common in Mt. Kenya, Aberdares, Kakamega, and Cherangani forests. It also occurs
in Timboroa, Nandi and western part of Mau forest (BIOTA, 2004). In south eastern
Kenya, P. africana occurs naturally in the Taita Hills cloud moist and highly
fragmented forests.

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2.5 Uses and exploitation of Prunus africana
Traditionally, P. africana has multiple uses (Ingram et al., 2009). It is valued for its
timber used for making tool handles and poles for construction and fencing, to a fuel-
wood particularly for charcoal (Stewart, 2003; Fashing, 2004). The tree bark is used
by herbalists, in treatment of prostate problems, as a remedy for stomachache and an
infusion to treat appetite, urinary and bladder infections, chest pain, malaria,
microbial infections, and kidney disease (Betti, 2008; Bii et al., 2010; Jeruto et al.,
2011; Otieno & Analo, 2012; Mwitari et al., 2013).
Internationally, P. africana bark extracts are being used medicinally to treat Benign
Prostatic Hyperplasia (BPH) that is common in older men (Briganti et al., 2009;
Betti & Ambara, 2013). This is eased through the anti-inflammatory effect of P.
africana extract on prostatic tissue and inhibition of bladder hyperactivity
(Cunningham et al., 2002). Prunus africana remedies are currently estimated at US
Dollars 220 million annually (Cunningham et al., 2002). Over the past several
decades, products from P. africana bark extracts have been the most widely exported
of any African tree species for medicinal purposes, contributing to its
overexploitation (Jimu & Ngoroyemoto, 2011).
The wild populations are currently the sole source of bark extract. In addition to local
use and trade, the collection and processing of the bark has always created economic
opportunities for rural communities (Cunningham et al., 2002; Muchugi et al., 2006;
Vinceti et al., 2013; Cunningham et al,. 2014).
Bark extracts contain fatty acids, sterols and pentacyclic terpenoids (Cunningham
and Mbenkum, 1993). The trade in dried Pygeum bark and bark extract is in the
order of 3000 to 5000 tonnes a year (Page, 2003) and the main sources being

10
Cameroon, Madagascar, Equatorial Guinea, Kenya, Uganda, and Tanzania.
Cunningham et al., (2002) pointed out that, wild populations of the P. africana in
afromontane forest were the sole source of bark and bark extract exported from
Africa and Madagascar to Europe.
Currently, P. africana products are the most commonly used medicine in France for
BPH (NTFP, 2009). Trade has grown as P. africana has emerged as the main raw
material for the international pharmaceutical trade in BPH treatments (Kadu et al.,
2012) The high demand therefore poses immediate need of ex situ and in situ
conservation strategies of P. africana populations (Mbatudde et al., 2013; Ingram et
al,. 2015). Wild-collection is no longer sustainable where harvesting adversely
affects morbidity and mortality rates of harvested populations (Stewart, 2003;
Mugaka et al., 2013).
2.6 Conservation threats to Prunus africana
According to Vinceti et al., (2013), the distribution of P. africana has been affected
by past climate change and the projected models indicate that the species is likely to
decrease in distribution by 2050. It is predicted that many regions of Africa will
suffer from temperature increases and droughts caused by range shifts along
altitudinal and moisture gradients (Jimu, 2011).
The role of legal and illegal commercial overharvesting on the decline in populations
has been clearly evident and documented (Sunderland & Tako, 1999; Ingram, 2014).
Prunus africana bark is exported dried, chipped or powdered to USA and Europe to
produce an extract used to treat benign prostrate hyperplasia (Betti et al., 2014). Bark
exploitation has caused serious damage to wild populations of P. africana including
trees inside forests of high conservation value, leading to concerns on the long term

11
sustainability of harvesting and conservation of this tree species (Navarro-cerrillo et
al., 2008; CITES, 2012).
In most parts of Africa, P. africana bark, stem and branches, roots and leaves are
used for various purposes by local people thereby threatening the populations. In
Ethiopia, the species is not threatened but local people harvest and use the bark, stem
and branches for fuel wood, charcoal production and as timber (Betti & Ambara,
2013). Both local and international market demand has therefore caused resource
depletion and an erosion of traditional resource protection practices (Stewart, 2003).
Reforestation with these species is hindered due to their recalcitrant seeds and a
higher seed predation (Farwig et al,. 2008). Preservation of the species therefore
depends on sustainable harvesting methods and on farm cultivation.
Habitat fragmentation and degradation are important drivers of biodiversity loss
(Gontier et al,. 2006). This can influence the life cycle of tropical tree species by
lowering pollination, limiting seed dispersal, increasing seed predation and therefore
affect population sizes and distribution (Farwig et al,. 2008).
Jimu and Ngoroyemoto (2011), in their study of habitat characteristics and threat
factors of the rare and endangered P. africana in Nyanga National Park, Zimbabwe,
found the major threats of P. africana to be invasive species and wild fires. Alien
plants can alter the structure of native plant communities through competition with
native plants and modification of fire regimes (Jimu and Ngoroyemoto, 2011).
Invasive plants can out-compete native annual and perennial plants (Lung, 2010;
Weru, 2012; Otieno & Analo, 2012). Some deplete soil water faster and at greater
soil depths, while others utilize increased levels of soil nutrients faster than native

12
species and thus, reduce their growth rates (Jimu, 2011). These can significantly
reduce native seedling biomass and species richness.
Fire is problematic in forests throughout Africa and the afromontane forests are
reported to be vulnerable (Betti, 2008).Wildfires mainly interfere with regeneration,
as it wipes out seedlings and saplings which cannot withstand the damage.
2.7 Application of GIS in mapping of endangered species
Geographic Information System is an important tool for monitoring biodiversity and
accommodates large varieties of spatial and aspatial data (Davis, 1994). This tool has
been adapted in determining the distribution patterns of various biodiversity
components for better management and conservation (Gontier et al,. 2006; Breugel et
al,. 2011). Any database that deals with biodiversity information has to be
geographically based, and able to predict where new populations of endangered
species with a limited known range might be expected, indicating potential hot spots
(Salem, 2003; Gontier, 2007; Lung, 2010).
Using systematic collections and GIS data to determine coverage of the target
species which are interpreted primarily through the use of maps can help in
identifying areas of high priority for conservation (Funk et al,. 1999). The results are
important for making informed decisions in conservation related issues (Pedersen et
al,. 2004).

13
CHAPTER THREE
Chapter 3 MATERIALS AND METHODS
3.1 Study Area
Nandi County falls within an agriculturally rich region of Kenya. Agriculture and
livestock keeping are the main socio-economic activities within the County. The
County has registered rapid population growth during the last four decades. The
population rose from 209,068 in 1969 to 578,751 in 1999 (GoK, 2000). The
population was estimated to be 882,086 (2014) with a growth rate of 2.9% per
annum according to the 2009 population census (GoK, 2010)
Nandi forest ecosystem is a higher altitude forests which comprises Nandi South,
Nandi North and Teressia Forest blocks, all in Nandi County. The three blocks
together with the Kakamega Forest, form part of the Western rainforest region, and
the Eastern most fragment of the Guinea Congolian phytogeographical region. The
area occupied by the forest was once extensive, but has steadily declined due to high
population pressure (Schaab et al., 2010).
Under the IUCN category of protected area, Nandi forest is a Habitat/Species
Management Area; managed mainly for conservation through management
intervention. The main value for which the area is designated is Biodiversity
conservation, water catchment, provision of forest products and cultural value.
North Nandi forest block is located between (latitudes 0˚33‗N and 0˚4‗N and
longitudes 34˚97‗E and 35˚04‗E) in Mosop and Nandi Central Sub-County (Figure
3.1). It occupies approximately 10,500 ha at an altitude of between 1,700 and 2,130
m (Kagombe et al., 2012). This is a strip of high-canopy forest on the edge of the
Nandi escarpment, above and immediately East of Kakamega Forest. It stretches for

14
more than 30 km from North to South and is 3-5 km wide for most of its length. The
mean annual rainfall varies from 1243 to 2179 mm. The highest temperature is 23ºC
while the mean minimum temperature stands at 12ºC. It is higher in altitude than
Kakamega Forest and the vegetation is floristically less diverse (Girma, 2011).
South Nandi Forest block is located (between latitudes 0˚05‗N and 0˚21‗N and
longitudes 34˚90‗E and 35˚08‗E) in South Nandi Sub-County, being a mid-elevation
forest lying west of Kapsabet town and South of the main Kapsabet-Kaimosi road
(Figure 3.1). The forest land measures approximately 16,959.5 ha, as per the
information based on forest boundaries survey carried out recently
(KWS/KFS/UNEP, 2007). Some 934.7 ha (5%) of the original forest land has been
settled. The forest elevation is between 1700 to 2000 m. It receives an annual rainfall
between 1600 and 1900 mm. The forest is drained by the Kimondi and Sirua rivers,
which merge to form the Yala River flowing into Lake Victoria.
Figure 3.1: A map showing the study area and sampling plots.
Source: Author

15
3.2 Sampling design
Stratified Random sampling was used in the sampling of P. africana based on
disturbance gradient, assuming higher impacts near forest edges (Fashing, 2004).
One and three belt transects were established in North and South Nandi forest blocks
respectively. The transects each measuring two km long and 400 m wide along an
access line was established from the forest edge towards the interior of the forest.
Prunus africana were targeted for establishing five reference points for Permanent
Sampling Plots (PSP) at an interval of 400 m along transects. The five PSP were then
subdivided into 25 smaller plots of 20 m by 20 m. The central and the four corner
sub-plots were selected for convenience of detailed vegetation sampling (Figure 3.2)
(Alder, 1992). Hand-held Global Positioning System (GPS) (Garmin etrex) devise
was used to geo-reference and take elevations of the plots.
100m
100m
20m
20m
20m
20m 20m
20m
20m
20m20m
20m
Figure 3.2: Sampling design and study plots.
Source Author

16
3.2.1 Determination of the abundance and spatial distribution of P. africana
The abundance was determined by recording the number of all mature individuals of
P. africana (≥5cm DBH) encountered in the PSP and within transects. All
individuals encountered within transect and farmlands were geo-referenced using a
hand-held GPS devise for mapping and to ensure easy location during subsequent
monitoring (Araya et al., 2009; Earle-mundil, 2010). They were also fitted with
aluminium plates with a code indicating; species name, transect number, PSP number
and species individual number. The plates were stuck to the tree trunks using
aluminium nails. Aluminium was used because it can resist rust.
Geographic Information System (GIS) was used in mapping the spatial distribution
of P. africana in South Nandi forest and the surrounding farmlands using spatial data
collected from the field. The areas with high P. africana population, high P. africana
frequency in among vegetation communities and low frequency of conservation
threats incidences were used as a basis to decide the conservation hotspots and
priority areas for conservation of P. africana. Using Arc GIS (version 10) the three
convex hull matrices were intercepted to form the four priority conservation zones in
South Nandi forest.
3.2.2 Determination of DBH, height and crown cover of P. africana and other
woody species
Diameter at Breast Height (DBH) of individuals of the P. africana and other woody
plant species measuring DBH ≥ 5 cm was recorded using a DHB meter at 1.3 m
above the ground (Abed and Stephens, 2003). Tree heights of P. africana were
determined using a clinometer (Suunto). Canopy cover of P. africana was estimated

17
in percentage relative to the plot. The crown length was determined by measurements
of the longest and the shortest diameter using a tape measure.
3.2.3 Determination of the recruitment and regeneration of P. africana and
other woody species
Seedlings/saplings of less than 1.5 m in height and with DBH below 5 cm were
counted in smaller plots of 5 m radius from the center of P. africana tree (Nzilani,
1999), and in 1 m by 1 m quadrats at the center and the four corners of the sampling
plot. Seedlings were considered as those with height of less than 30 cm and saplings
as those with DBH less or equal to 4 cm and height greater than 30 cm (Kent and
Coker, 1992). The seedlings and saplings were categorized into three strata, thus; <
0.5 m, 0.5-0.9 m and 1.0-1.49 m
3.2.4 Determination of Phenology of P. africana
To understand the effects of environmental factors on fruiting cycles and perhaps its
role in regeneration, the reproductive stages of every individual tree of P. africana
encountered in transect were recorded as flowering, fruiting or none. For the
inspection binoculars were used. Flowers and fruits dropped from the trees were
additionally used as indicators.
3.2.5 Determination of the ecological association of P. africana with other plant
species
The plots were described by recording information which included the vegetation
community, slope/gradient aspects of the landscape, drainage and habitat
disturbance. All vascular plant species in different life form categories (herbs
including grass, climbers and lianas, shrubs and trees) were recorded. The DBH and

18
vertical heights of all trees with DBH ≥ 5 cm were recorded. The forest canopy layer
was categorised using the KIFCON classification (Mutangah et al,. 1992): Tree
upper canopy (≥20m), trees middle canopy (≥10≤20m), trees lower canopy
(≥5≤10m), cover of shrub layer (1≤5), cover of herbaceous (<1m) and cover by litter.
The regeneration of all other woody species was also recorded.
3.2.6 Species identification
As much as possible plants were identified in the field by use of identification guides
(Agnew & Agnew, 2013; Beentje, 1994 and Dalitz et al., 2011). Those with
uncertain identification were collected, pressed and taken to East Africa (EA)
herbarium, Nairobi for identification with the help of botanists. Species identification
was based on Beentje (1994) and Agnew & Agnew (2013) as well as various
fascicles of Flora of Tropical East Africa (FTEA‘s). Family names followed
Angiosperm Phylogeny Group (APG III, 2009) classification.
Published literature, including Beentje (1994), Agnew & Agnew (2013), the updated
IUCN Red List of plants, as well as the List of East African Plants databases at the
E.A Herbarium and published checklist were used to identify the unique, rare,
threatened and endemic species in North and South Nandi forests.
3.2.7 Determination of conservation threats to P. africana and other species
Physical observation was used to assess and record the types of conservation threats
to P. africana and other species. This was done based on presence of conservation
threats indicators/measurable within the sub-sampling plots of 20 m by 20 m (Table
3.1).

19
Table 3.1: Indicators used to asses conservation threats to P. africana and other species in
the forest
Threat Indicators/Measurable
Logging Stumps (old and new), remaining logs, saw dust
Grazing Presence of livestock, dung, hoof marks, browsed
vegetation
Charcoal burning Active kiln, charcoal remains, burnt soil
Forest fire Burnt bushes/tree barks, chars on ground,
Resource extraction Debarking, pruning, uprooting, fire wood
Infestation Presence of pests and parasites, deformed leaves,
colouration, wounds
Invasive species Alien plants species
3.2.8 Determination of uses and conservation threats of P. africana by the local
communities in North and South Nandi forests
3.2.8.1 Sampling of sub-locations
Stratified sampling was used in this study. Google earth, under the open layer tool,
was used as a background in ArcGIS (Version 10) to generate a buffer zone of 1 km
to the outside of the South Nandi forest edge (Figure 3.1). The number of sub
locations and their area in km2
around the forest was obtained using the 2009 Kenya
data (GoK, 2010). The population of homesteads around the forests was then
estimated using the 2009 Census as the reference point. The 2009 household density
was obtained by dividing the population households‘ density of the entire sub-
location by the area (km2
) in each sub-location within the buffer zone. With a growth
rate of 2.9%, the 2015 household population density was obtained by multiplying the
density by growth rate within the buffer zone in each sub-location. A total of 9,574
households were obtained.
3.2.8.2 Sampling of Households
To determine the sample size needed to be representative of the population Krejcie &
Morgan (1970) formula was used.

20
Where S = required sample size
χ2 = the table value of chi-square for 1 degree of freedom at the desired
confidence level (3.841)
P = the population proportion (assumed to be .50 since this would provide the
maximum sample size).
N = the population size
d = degree of accuracy expressed as a proportion (.05)
A total of 370 households were obtained as the sample size of the population using
the formula and therefore 50 % (185) was targeted and interviewed in this study
which was enough as a sample size (Mugenda and Mugenda, 2003). The sample size
(185) was then divided to each sub-location based on the total household population
ratio (Appendix 3). The obtained sample from each sub-location was randomly
selected and interviewed using one semi structured questionnaires (appendix 2) per
household. In addition, three (3) case studies of herbalists were also included in the
study.
3.3 Data analysis
The data was subjected to normality test using the Shapiro-Wilk Test to check
whether the data was normally distributed. Box-plots for visualization of the
normality were also used. The data was also log, square, square root and box- Cox
transformed but the normality test was still significant. This resulted to the use of
parametric test to analyze the data at transect and forest block level. However, data at
PSP levels were analysed using non-parametric tests due to their small sample size.
All statistical significance levels were reported at 0.05 and at 95% confidence levels.

21
3.3.1 Population status and spatial distribution of P. africana in North and
South Nandi forests
The measure of central tendency, spread, normal distribution and correlation of
dependent variables of P. africana in the forest was analysed using PAST (Version
4.3) (Hammer, 2012). Data that was obtained for DBH and height was used to
generate DBH and height class size distributions respectively hence get the
population class sizes. Population structure was summarised using histograms, bar
chats and line graphs. Frequency distribution table was used to analyse the number of
incidence of the threats to P. africana at plot level. T-test was used to test for
differences in P. africana parameters among transects.
Suitability distribution models of P. africana were created using the maximum
entropy suitability mapping method (Phillips et al,. 2006; Phillips & Dudık, 2008), as
also implemented in MaxEnt (version 3.3.3k) software (Phillips et al., 2006) and
ArcGIS (version 10). The conservation hotspots and priority areas for conservation
of P. africana in the South Nandi forest was also mapped using ArcGIS (version 10).
3.3.2 Ecological association of P. africana with other plant species in North and
South Nandi forests
The basal area for each woody plant with DBH ≥ 5 cm was calculated using the
following formula;
Relative density, relative frequency and relative dominance were summed and then
divided by three (3) to calculate the relative Importance Value Index (IVI) for each

22
woody species. The following formulas were used to calculate the components of the
IVI (Kent and Coker, 1992);
Transect description of the variance and mean was analysed by one-way analysis of
variance (ANOVA) to test any significant difference in the dependent variables.
Shannon-Wiener diversity index (H‘) for each transect was computed and compared
(Shannon and Weiner, 1948). It is derived from the equation:
H‘= ∑ [pi (ln pi)]
Where; pi is the proportion of individuals found in the ith species; ln is the natural
logarithm. Species overall number (S) was obtained from the number of species in
each transect.
Pielou‘s eveness (J‘) is the ratio of observed diversity to maximum diversity (Pielou,
1966) and was calculated from the equation:
J‘= H‘/ Log (S).
Margalef species richness (Margalef, 1958) was obtained from the equation;
d= (S-1)/ Log (N).
The species-area curve based on cumulative species numbers over sampled area was
generated using PRIMER (Plymouth Routines In Multivariate Ecological Research)
(version 7) It was used to evaluate the adequacy of the sample size used for the
study.

23
Species similarity between North and South Nandi forests was compared using
Sorensen‘s and Jaccard‘s similarity index (Clarke and Robertson 2000) as shown by
the formula below;
Where a = Number of species present in both the study sites
b = Number of species present at North but not at South Nandi forest
c = Number of species present at the South but not at the North Nandi forest.
Similarity indices were based on the species information given in Appendix 1.
3.3.3 Uses and conservation threats of P. africana by the local communities in
All qualitative data from questionnaires after cleaning were coded and analysed by
use of SPSS (version 20). Frequency tables, graphs, bar charts and pie charts were
used to present the results.

24
CHAPTER FOUR
Chapter 4 RESULTS
4.1 Population density, size and spatial distribution of P. africana in North and
South Nandi forests
4.1.1 Population density of P. africana in North Nandi forests
The abundance of Prunus africana was expressed in terms of the number of
individuals observed per hectare. A total of 125 individuals of P. africana (≥5cm
DBH) were recorded in North Nandi Transect 1 (NNT1) with an average of 1.6
trees/ha. The average DBH was 66.5±32.1 with the average height of 21.4±7.1 and the
average crown length of 11.6±5.3. A maximum density of three individuals of P. africana
per Permanent Sampling Plot (PSP) was recorded. Prunus africana individuals were
also absent in some PSPs
4.1.2 Density of P. africana in South Nandi forests
The highest density of P. africana was recorded in SNT1 (n = 96), with 1.2 trees/ha
and the lowest in SNT2 (n = 12) with 0.2 trees/ha (Table 4.1).
Table 4.1: Density and means of DBH, height and crown length of P. africana (≥5cm DBH)
per transect (80 ha) in South Nandi forests
Transect Density
(Trees/Ha)
DBH
Mean ± SD
Height
Mean ± SD
Crown length
Mean ± SD
SNT1 1.2 118.6±39.3 22.7±4.4 12.9±4.1
SNT2 0.2 66.6±22.2 19.6±3.4 13.6±5.1
SNT3 0.2 118.3±39.3 24.3±4.6 14.5±5.3
There was statistically significant difference in the mean DBH among transects ( df =
2; F = 45.13; p < 0.05). The highest mean DBH of 118.6±39.3 cm was recorded in
SNT1 while the lowest mean DBH of 66.6±22.2 cm was recorded in SNT2. There
was no significant difference in mean height of the P. africana among transects (df =
2; F = 2.41; p = 0.06). The highest mean height of P. africana was recorded in SNT3

25
(n = 17), with 24.3±4.6 m and the lowest in SNT2, with 19.6±3.4 m. There was
statistically significant difference in crown length among transects (df = 2; F = 2.77;
p < 0.05). The longest mean crown diameter was recorded in SNT3 with 14.5±5.3
and the shortest in SNT1 with, 12.9±4.1.
A total of 44 individuals of P. africana were recorded in 20 Permanent Sampling
Plots (PSP) in both forests. A maximum density of 15 and three individuals of P.
africana per PSP was recorded in South Nandi and North Nandi forest respectively.
Prunus africana individuals were absent in some PSPs in both forest blocks. In all
transects, a general decrease in P. africana trees per PSP from the forest edge
towards the interior of the forest was observed (Figure 4.1).
Figure 4.1: Density of P. africana (≥5cm DBH) per hectare (mean±SE) against distance
from the forest edge toward the interior of the forest.

26
4.1.3 Density distribution of P. africana in South Nandi forest and the 1 km
buffer zone
The modeled distribution showed that a higher density of P. africana was found
towards the North Eastern part of the forest especially along the edges and the
surrounding farmlands in the 1 km buffer zone with a maximum of 4 individuals per
hectare. Conversely, a low density of P. africana was found towards the South West
parts of the forest with a probability of getting at least 1 individual per hectare
(Figure 4.2).
The study found that there was a widespread presence of P. africana on farmlands
especially towards the North Eastern part of South Nandi forest. A total of 108 (58%)
of the households with a mean of 5 acres of land per household had P. africana in
Figure 4.2: Modeled potential density distribution of P. africana in South Nandi
forest and 1 km buffer zone. The dark brown colour shows a highest probability of P.
africana up to a maximum of four trees/ha while the dark blue colour shows the
lowest probability of up to one tree/ha.

27
there farmlands ranging from 1-10 individuals. The trees on farmlands were
relatively younger and smaller in size as compared to those in the forest.
4.1.4 DBH class size distribution of P. africana in North and South Nandi forests
In North Nandi forest (n =125, Mean = 67±32) the DBH class size distribution of P.
africana was represented in all size-classes but a progressive decline of the
proportion of bigger individuals was noted resulting into a near exponential
population curve. The DBH class size 81-100 (30.4%) had a considerable higher
number of P. africana individuals than the rest of the classes. The other DBH class
sizes of 61-80, 21-40, 5-20, 41-60, 101-120, 121-140, and 141-160 contributed 20%,
13.6%, 12.8%, 9.6%, 9.6%, 3.2%, 0.8% and 0% respectively (Figure 4.3).
Figure 4.3: DBH frequency distribution of P. africana in North and South Nandi forests.
DBH class: 1 = 5-20 cm, 2 = 21-40 cm, 3 = 41-60 cm, 4 = 61-80 cm, 5 = 81-100 cm, 6 =
101-120 cm, 7 = 121-140 cm, 8 = 141-160 cm, 9 = >160 cm.

28
In South Nandi forest (n =125m Mean = 114±41) the DBH class size distribution of
P. africana showed hardly any recruitment at the lowest and subsequent DBH classes
(Figure 4.2). Majority of the individuals were found in the higher DBH class sizes of
141-160, 101-120, 81-100, 121-140 and >160 contributed to 20, 20, 15.2, 14.4 and
12% respectively. The rest of the lower DBH class sizes had a lower frequency of P.
africana individuals.
The highest DBH of 210 cm and 140 cm were found in South Nandi and North
Nandi forests respectively. Conversely, the lowest DBH of 11 cm and 7 cm was
found in North Nandi forest and South Nandi forest respectively (Figure 4.4).
There was statistically significant difference in mean DBH between North and South
Nandi forests (t = 10.14, p < 0.05). The DBH class size distribution of North Nandi
forest (n =125, Mean = 67±32) had almost a ―bell‖ shaped distribution with majority
of the individuals in the lower DBH class sizes of below 81-100cm class (86%). On
the other hand, South Nandi forest had a ‗j‘ shaped distribution with majority of the
individuals with higher DBH class size of above 81-100cm class (82%).
DBH
(cm)
South Nandi North Nandi
Figure 4.4: DBH distribution of P. africana in North and South Nandi forests

29
In both North and South Nandi forests (n = 279, Mean = 90.8±44), the DBH class
sizes of P. africana resulted in a ―bell‖ shaped distribution pattern. Twenty three
percent of the individuals were found in the middle DBH class size (81-100 cm)
while 14% and 15% accounted for DBH class size 61-80 and 101-120 respectively.
4.1.5 DBH Class size distribution of P. africana in 1 km buffer zone of South
Nandi forest
The DBH class size distribution (n = 93, mean = 40±27) exhibited a typical inverse
J-shaped curve as most of the individuals were considerably in the lower diameter
classes. The first DBH class (5 – 20 cm) contributed 26%. The second class (21 - 30
cm) accounted for 39% of the individuals while the third class (31 – 40 cm)
accounted for 16% of the individuals. The subsequent classes four, five and six
accounted for 9%, 6% and 4% respectively. The rest of the higher DBH classes had
no individual representatives (Figure 4.5).
Figure 4.5: DBH frequency distribution of P. africana in 1 km buffer zone of South Nandi
forest. DBH class: 1 = 5-20 cm, 2 = 21-40 cm, 3 = 41-60 cm, 4 = 61-80 cm, 5 = 81-100 cm,
6 = 101-120 cm, 7 = 121-140 cm, 8 = 141-160 cm, 9 = >160 cm.

30
4.1.6 Height class distribution of P. africana in North and South Nandi forests
In North Nandi forest (n =125, Mean = 21±7) the 21-25 m height class consisted
27.2% of the total individuals. The highest height class (>30m) contributed 21.6% of
the total individuals. The rest of the classes 16-21, 11-15 and 26-30m contributed
21.6%, 20, 16 and 15.2%, respectively, while the two lower classes had no
representatives (Figure 4.6).
Figure 4.6: Height class distribution of P. africana in North and South Nandi forests.
Height class: 1 = 0-5 m, 2 = 6-10 m, 3 = 11-15 m, 4 = 16-20 m, 5 = 21-25 m, 6 = 26-30 m
and 7 = >30 m
In South Nandi forest (n = 125, Mean = 23±4), the same ‗Bell‘ shaped distribution
skewed to the left was observed. Considerably high proportion (38.4%) of P.
africana individuals was observed in the height class of 26-30 m followed by 34.4%
of individuals in the height class of 21-25 m. Height classes 16-20 m, >30 and 11-15
accounted for 16.8%, 8% and 2.4% of the total individuals. The other two lower
classes had no representation.

31
There was no statistically significant difference in mean height between North and
South Nandi forests (t = 1.62, p = 0.11). A ‗Bell‘ shaped distribution of height was
observed but highly skewed to the left and non-continuous (Figure 4.7). For instance,
there was absence of any individual in the lowest two height classes. The rest of the
individuals were found to have a height more than 10 m with a large proportion of
individuals (30.8%) found in height class of 21-25 m while 26.8%, 18.4, 14.8 and
9.2% were found in the height class of 26-30, 16-20, >30 and 11-15 respectively.
Figure 4.7: Height class distribution of P. africana in North and South Nandi forests
Height class: 1 = 0-5 m, 2 = 6-10 m, 3 = 11-15 m, 4 = 16-20 m, 5 = 21-25 m, 6 = 26-
30 m and 7 = >30m.
4.1.7 Crown diameter class size distribution of P. africana
There was statistically significant difference in the mean crown diameter between
North and South Nandi forests (t = 16.55, p < 0.05). Majority of the individuals in all
the transects (38%) had a range of 11-15 m. Very few individuals (6% and 10%)
were of < 5 m and > 25 m in average crown diameter respectively. A good number
(14%) of the individuals in NNT1 as compared to other transects had less than 5 m
crown diameter.

32
4.1.8 DBH, Height and Crown diameter correlation
Pearson correlation analysis of the DBH and height of P. africana in the two forests
(n=279) showed a strong positive linear correlation (r = 0.55) (Figure 4.8).
Figure 4.8: A linear correlation between DBH and Height of P. africana in North and
South Nandi forests
In addition, the Pearson‘s correlation analysis between DBH and Crown length of P.
africana in North and South forests (n=279) showed a strong positive linear
correlation (r =0.61) (Figure 4.9).
Figure 4.9: A linear correlation between DBH and Crown diameter of P. africana in North
and South Nandi forests

33
4.1.9 Density of Prunus africana seedlings/Saplings
A total of 1989 seedlings and saplings were recorded and categorized into three strata
(< 0.5 m, 0.5-0.9 m and 1.0-1.49 m). There was statistically significant difference in
mean seedling density among the three class size categories (df = 2: F = 11.98; p <
0.05). However, 1987 (99.9%) seedlings counted were of ≤ 0.5 m in height. There
were only 2 and 1 individuals between 0.5-0.9 m and 1.0-1.49 m respectively
recorded in the two forest blocks.
North Nandi forest had the highest seedling density per transect as compared to
South Nandi forest (Figure 4.10).
There was no statistical difference in the mean density of seedlings between North
and South Nandi forests (t = 4.1; p = 0.65).
4.1.10 Phenology of Prunus africana
A total of 277 (99.3%) of the trees were not in any reproductive stage while only 2
(0.3%) was observed as flowering at the time of sampling.
North Nandi South Nandi
0
8000
16000
24000
32000
40000
48000
56000
64000
72000
SeedlingDensity
Figure 4.10: Mean density of seedlings for North and South Nandi forests

34
4.1.11: Priority conservation zones of P. africana in South Nandi forest
The convex hull matrices interception of the sites with high P. africana density,
frequency among vegetation communities and threat incidences was used to draw
conclusions on where conservation priorities would be based (Figure 4.11).
Figure 4.11: Priority Conservation zone of P. africana in South Nandi forest
Conservation Priority 1 had a high density of P. africana, high frequency vegetation
communities and high frequency in threats incidence. All the three matrices
converged at that point making it of high priority for conservation. This formed the
area of the forest between Kobujoi market and Chepkongony trading centre towards
the northern side of the forest.

35
Conservation priority 2 had a lower density of P. africana in comparison to
conservation priority 1 area. It also had relatively lower frequency of P. africana
among vegetation communities but a higher frequency of threats incidence than in
Conservation priority 1. There was an intersection of the latter two matrices and
formed the area around conservation priority 1.
Moreover, Conservation priority 3 had a lower density of P. africana, a lower
frequency in the vegetation communities and a higher incidence of conservation
threats than Conservation priority 2 hence no interception of the three matrices. It
covered a larger part of the forest than conservation priority 1 and 2.
Finally, Conservation priority 4 formed the rest of the forest block where there was
no interception of any of the matrices. It‘s important also for conservation efforts to
focus on the entire forest ecosystem as well. There is still an artificial plantation
towards the northern part of the forest as well as more conservation threats recorded
such as charcoal burning, logging and firewood collection. The Southern part is still
a natural forest but facing almost same conservation threats as the northern part as
mentioned.

36
4.2 Ecological association of P. africana with other plant species in North and
South Nandi forests
4.2.1 Plant growth forms
The plant growth form that constituted 70 different species of trees (24%), 75 species
of shrubs (26%), 48 species of climbers and lianas (16%) and 98 species of herbs
including grasses (34%) were recorded (Figure 4.12). Thus a total of 290 vascular
plants species comprising of 92 families, and 212 genera were recorded.
Figure 4.12: Species diversity according to growth form in both North and South Nandi
forests
The study showed that herbs contributed the highest number of species (34%) in
Nandi forests. It was followed by shrubs (26%), Trees (24%) and Climbers and
lianas (16%).
When the two forests were evaluated separately, it was found that in South Nandi,
herbs (35%) still contributed the highest share (Figure 4.13). Trees and shrubs had an
equal share of 24% while climbers and lianas was the lowest with 17%. In North

37
Nandi, the tree formed the highest share of 33% while Herbs and shrubs had equal
share of 25%. The lowest was climbers and lianas with 17%.
Figure 4.13: Species diversity according to growth form in Nandi forests
4.2.2 Floristic composition
The floral composition of the two forests is presented in a detailed plant checklist
(Appendix 1). The number of species, families and genera as recorded in the two
forests showed that South Nandi forest was more diverse in all aspects. In South
Nandi forest, there were 254 species which comprised of 84 families and 191 genera
while in North Nandi forest there were a total of 174 species which comprised of 75
families and 141 genera.
In both forests, Rubiaceae family was the most diverse group contributing a total of
21 species (7%). The other well represented families included Asteraceae (6%),
Euphorbiaceae (5%), Aspleniaceae (4%), Acanthaceae (4%), Apocynaceae (3%),
Vebenaceae (3%), Celestraceae (2%), Malvaceae (2%) and Cucurbitaceae (2%).

38
In South Nandi forest, Rubiaceae was the richest family with 20 species (8%), and 15
genera. The subsequent families included Asteraceae with 15 species (6%) and 11
genera, Euphorbiaceae with 14 species (6%) and 10 genera. Other well represented
families in South Nandi forest were Acanthaceae, Apocynaceae, Aspleniaceae,
Flacourtiaceae, Rosaceae and Celestraceae with more than 5 species in a family
(Table 4.2).
In North Nandi forest, Rubiaceae was the richest family with 13 species (7%) and 9
genera. It was followed by Apocynaceae with 8 species (5%) and 7 genera,
Aspleniaceae with 8 species (5%) and 1 genera. Other notable families in the top ten
included Euphorbiaceae, Acanthaceae, Asteraceae, Celestraceae, Lamiaceae,
Malvaceae and Rosaceae with more than 5 species per family.
Table 4.2: A table showing the top ten families in North and South Nandi forests
South Nandi forest North Nandi forest
Families Number
of
Species
Number
of
Genera
Families Number
of
Species
Number
of
Genera
Rubiaceae 20 15 Rubiaceae 13 9
Asteraceae 15 11 Apocynaceae 8 7
Euphorbiaceae 14 10 Aspleniaceae 8 1
Acanthaceae 11 8 Euphorbiaceae 8 6
Verbenaceae 10 3 Acanthaceae 7 6
Apocynaceae 9 8 Asteraceae 5 4
Aspleniaceae 9 1 Celestraceae 5 3
Flacourtiaceae 6 5 Lamiaceae 5 2
Rosaceae 6 3 Malvaceae 5 3
Celestraceae 5 3 Rosaceae 5 2
The top ten families in both forests formed the largest number of species. In South
Nandi forest, the top ten families comprised of 41% (105 species) of the total
recorded species. Five families were represented by 5 species (10%), 7 families were

39
represented by 4 species (14%), 9 families represented by 3 species (9%), 20 families
represented by 2 species (20%) and 34 families represented by 1 species.
In North Nandi forest, the top ten families comprised of 40% (69 species) of the
recorded species. Three families were represented by 4 species (6%), 7 families
represented by 3 species (14%), 16 families represented by 2 species (16%) and 40
families represented by 1 species (40%).
4.2.3 The general vegetation community
The general physiognomic structure and composition of the various canopy
categories was varied. The study found that the common trees included P. africana,
Croton megalocarpus Hurch., Tabernaemontana stapfiana Britten, Celtis africana
Burm.f., Polyscias fulva (Hiern) Harms, Croton macrostachyus Del., Casearia
battiscombei R.E. Fries and Macaranga kilimandscharica Pax which also formed the
most dominant communities. The trees formed a canopy cover of 31%, which was
unevenly distributed in the forest. These communities also formed the upper canopy
layer (>20 m high) with a cover of 17% and mainly dominated by P. africana.
The middle canopy layer had a cover of 36% mainly composed of T. stapfiana, as
well as the trees forming the upper canopy and other species such as M.
kilimandscharica, Diospyros abyssinica (Hiern) F. White, C. megarlocarpus, Albizia
gummifera (JF Gmel.) C.A. Sm., Neoboutonia macrocalyx Pax, C. battiscombei, C.
macrostaychus, P. fulva, Drypetes gerrardii Hurch. and Strombosia scheffleri Engl..
The lower canopy was relatively high at (39%), which was mainly composed of
Solanum mauritianum Scop., T. stapfiana, Mimulopsis arborescens C.B.Clarke,
Mimulopsis solmsii Schweinf., Heinsenia diervilloides K. Schum., M. kilimandischarica,

40
Erythrococca sp, Bersama abyssinica Fres. and C. battiscombei and intermingling
with young trees of upper and middle canopies.
The shrub layer constituted about 41% of vegetation which was almost equal to that
of the tree lower canopy cover and included; S. mauritianum, Acanthus eminens
C.B.Clarke, M. solmsii, M. arborescens, H. diervilloides, Erythrococca sp and Piper
capense L.f.. Tree saplings of Cassipourea malosana (Baker) Alston., T. stapfiana, C.
battiscombei, Strombosia scheffleri Engl., Deinbollia kilimandscharica Taub and
Trilepisium madagascariense DC. also constituted this layer.
The herbaceous layer formed 53% and included mainly Culcasia falcifolia Engl.,
Hypoestes sp, Brillantasia sp, Leucas masaiensis Oliv, Achyranthes aspera L., M.
solmsii, P. capense, Oplismenus hirtellus (L.) P. Beauv and ferns. The cover by litter
was highest with an average of 70%.
4.2.4 Plant species accumulation curve
Based on the total recorded species, an accumulation curve was generated to test the
adequacy of selected samples of 22 Permanent Sampling Plots (PSP) to estimate the
species diversity of the two forests (Figure 4.14). The study found that the number of
species first increased quickly with the sampling effort as the forest common species
were recorded then leveling off as rare species are included. However, It was
observed that new species could be recorded in the two forests although at a
decreasing rate.

41
4.2.5 Plant Species diversity
The species diversity that incorporated the species richness and evenness was
measured for comparison of the diversity among the sampling sites in the two forests
(Table 4.3). The study found that the species richness (S) for SNT1 was the highest
while North Nandi Random plots (NNR) was the least. However, there was a greater
evenness and Diversity in South Nandi Random plots (SNR) than the rest of the
Transects and random plots. The Shannon diversity indices were 4.64 and 4.81 for
North and South Nandi forests respectively.
Table 4.3: Species diversity indices
Transect NNT1 NNR SNT1 SNT2 SNT3 SNR
Species Richness (S) 145 118 165 164 141 140
Evenness (J') 0.96 1.00 0.97 0.97 0.96 1.00
Shannon-Wiener Index (H') 4.80 4.57 4.92 4.93 4.75 4.94
Simpson’s index (1-
Lambda')
1.00 1.00 1.00 1.00 1.00 1.00
Number of Permanent Sampling Plots (PSP)
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
SpeciesCount(Cumulative)
Figure 4.14: Species accumulation curve of both North and South Nandi forests

42
The study found out that there was a higher mean number of species per plot (400m2
)
in SNT1 of 63±20 followed by SNT2 with 59±18 and SNT3 with 56±19 and lowest
in NNT1 with 46±12. There was statistically significant difference in mean species
diversity among transects (Kruskal-Wallis test H=13.35, p<0.05)
There was statistically significant difference in the mean species diversity between
North and South Nandi forests (t= -5.67, p< 0.05). A higher mean number of species
per plot (400m2
) including the random plots was recorded in South Nandi forest than
in North Nandi forest (Figure 4.15). The mean number of species in South Nandi
(n=85) was 59±18 while in North Nandi (n=40) was 44±11.
Figure 4.15: Species diversity per plot between North and South Nandi forests
4.2.6 Unique and rare species
Nervilia bicarinata (Blume) Schltr (Figure 4.16) of the Orchidaceae family was
found as new record in South Nandi forest hence unique. Nervilia bicarinata is a
small erect terrestrial herb 15 – 27 cm tall. Tuber 1 - 2 x 1 – 3 x 1 – 4.7 cm, sub
spherical or ovoid with 3 – 7 nodes. The leaf is solitary appearing after flowering. It

43
is normally found in a riverine and waterfall-spray forest habitat. It is well distributed
in Africa and Arabian Peninsula.
Figure 4.16: Unique species: Nervilia bicarinata: A new record based on the database and
voucher specimens at the East Africa Herbarium, Nairobi, Kenya
The following plants were found as rare species in North and South Nandi forests.
They were very uncommon, scarce, or infrequently encountered during the study.
(Table 4.4).
Table 4.4: Rare species recorded in North and South Nandi forests according to the voucher
specimens in the East Africa Herbarium, Nairobi.
Species Conservation
status
%
frequency
NN
%
frequency
SN
Threats
Pavetta abyssinica Fresen. NA 23 48 Logging
Prunus africana (Hook.f.)
Kalkm.
VU 28 46 Medicinal
harvesting,
logging
Rubus scheffleri Engl. NA 5 13 None
Toddalia asiatica (L.) Lam. NA 13 8 None
Pouteria adolfi-friedericii
(Engl.) Robyns & Gilb.
NA 18 2 Logging
Where NN = North Nandi forest; SN = South Nandi forest; NA = Not Assessed; VU =
Vulnerable.

44
4.2.7 Woody tree species associated with P. africana
The common forest tree species in the two forest blocks based on frequency of
occurrence included: Macaranga kilimandscharica, Casearia battiscombei,
Tabernaemontana stapfiana, Croton megalocarpus, Albizia gummifera, Prunus
africana, Celtis mildbraedii Engl., Erythrococca bongensis Pax, Bersama abyssinica,
Heinsenia diervilloides, Neoboutonia macrocalyx, Strombosia scheffleri, Deinbollia
kilimandscharica and Ehretia cymosa Thonn.. Other notable tree species were
Diospyros abyssinica, Lepidotrichilia volkensii (Gürke) Leroy, Polyscias fulva,
Drypetes gerrardii, Trilepisium madagascariense and Baissea multiflora A.DC.
4.2.8 DBH class size distribution of woody species associated with P. africana
Forest structure analysis based on DBH class size of woody plant species in the two
forest blocks was performed (Figure 4.17). The DBH size classes were assigned
based on 10 cm DBH increment. The study found that 73% of the woody tree species
associated with P. africana in all transects was of smaller DBH range of 5 - 14 cm.
The other DBH class size categories in the increasing order showed a progressive
reduction of individuals respectively. Closer examination revealed differences in the
number of stems in the different size classes. SNT1 had the highest number of
individuals whose DBH was recorded followed by SNT2, SNT3 and NNT1
respectively. The NNT1 has a fewer trees stems in the size range between 5 and 14
cm but increasing number between 25 and 34 cm. DBH with greater than 85 cm were
very rare in all transects.

45
Figure 4.17: DBH class size distribution of all woody plants (≥5cm DBH) per transects in
The population structure of all woody trees in Nandi forest showed a continuous
size-class distribution with progressive decline in the proportion of individuals with
increasing DBH size. The proportions of individuals in the lower DBH classes were
higher than the remaining DBH classes and hence exhibited a typical inverse J-
shaped curve. The proportion of individuals in the successive DBH classes showed
an exponential decline (R2
= 0.97).
4.2.9 Importance Values Index (IVI) of woody species
The Importance Value Index (IVI) is an aggregate value of species relative density,
relative frequency and relative dominance (basal area). This analysis was carried out
to determine the most important woody species in the forest. Species with the highest
IVI values contributes much to the forest structure in terms of species abundance and
distribution (Table 4.5).
The study found that the most important species according to IVI values were
Solanum mauritianum (51%), Tabernaemontana stapfiana (34%), Croton
megalocarpus (16%), Macaranga kilimandscharica (14%), Heinsenia diervilloides

46
(13%), Diospyros abyssinica (10%) and Strombosia scheffleri (10%) respectively.
Prunus africana (8%) ranked at 12th
after other species such as Casearia
battiscombei, Mimulopsis arborescens, Cassipourea malosana and Cyathea
manniania Hook.
The results showed that P. africana had a low density of stems ha-1
(5.25), relative
dominance (3.68%) and relative frequency (3.28%) among the top 20 woody plant
species. However, its basal area was relatively higher. The study observed that
disturbance indicator species including S. mauritianum and T. stapfiana contribute
much to the forest structure as compared to other woody species including P.
africana.

47
Table 4.5: Family, density (D) and basal area (Ba) of the principal tree species associated with P. africana
Species Family D stem ha-1
Ba (m2
ha-1
) RD (%) RDo (%) RF (%) IVI
Solanum mauritianum Solanaceae 23.00 1870.81 21.09 25.89 4.15 51.12
Tabernaemontana stapfiana Apocynaceae 40.75 1755.01 5.96 24.28 3.71 33.95
Croton megalocarpus Euphorbiaceae 23.00 640.12 3.36 8.86 3.71 15.93
Macaranga kilimandscharica Euphorbiaceae 26.75 426.35 3.91 5.90 3.93 13.74
Heinsenia diervilloides Rubiaceae 41.00 239.76 5.99 3.32 2.84 12.15
Diospyros abyssinica Ebenaceae 21.00 348.61 3.07 4.82 2.40 10.30
Strombosia scheffleri Olacaceae 23.75 300.84 3.47 4.16 2.62 10.26
Casearia battiscombei Flacourtiaceae 20.75 149.70 3.03 2.07 3.93 9.04
Mimulopsis arborescens Acanthaceae 41.50 94.21 6.07 1.30 1.09 8.46
Cassipourea malosana Rhizophoraceae 23.50 194.21 3.44 2.69 1.97 8.09
Cyathea manniania Cyatheaceae 36.00 187.79 5.26 2.60 0.22 8.08
Prunus africana Rosaceae 5.25 264.11 0.77 3.65 3.28 7.70
Celtis mildbraedii Ulmaceae 16.75 51.99 2.45 0.72 3.28 6.44
Neoboutonia macrocalyx Euphorbiaceae 15.75 87.83 2.30 1.22 2.62 6.14
Albizia gummifera Mimosaceae 10.00 29.51 1.46 0.41 3.49 5.36
Trilepisium madagascariense Moraceae 8.50 117.90 1.24 1.63 1.97 4.84
Deinbollia kilimandscharica Sapindaceae 12.25 13.10 1.79 0.18 2.62 4.59
Erythrococca bongensis Euphorbiaceae 9.50 8.09 1.39 0.11 3.06 4.56
Bersama abyssinica Melianthaceae 7.50 19.37 1.10 0.27 3.06 4.42
Lepidotrichilia volkensii Meliaceae 11.75 18.12 1.72 0.25 2.40 4.37
IVI, Importance Value Index; RF, relative frequency; RD, relative density; RDo, relative dominance

48
4.2.10 Species similarity
Multi-Dimensional Scaling (MDS) of Permanent Sampling Plots of the four transects
and all random plots in the two forest blocks was done to provide a visual
representation of the similarity among sampling plots based on the species number
and composition (Figure 4.18). In a MDS ordination, the distances between plots on
the graph represents similarity. The results found that the degree of correspondence
between the distances among sampling plots was high (0.17).
Species diversity between North and South Nandi forests was compared to establish
the species similarity of the two forests. The study found an average of 48% common
species between the North and South Nandi forests. The average similarity indices
indicated that North and South Nandi forests are between 64% and 47% floristically
similar based on the Sorensen‘s and Jaccard‘s index respectively. This indicates that
the two forests are related by relatively high margins.
NNR
NNT1
SNR
SNT1
SNT2
SNT3
Stress: 0.17
Figure 4.18: Multi-Dimensional Scaling (MDS) of plots

49
4.2.11 Density of woody plant seedlings
Prunus africana and Diospyros abyssinica had the highest density of seedlings in all
transects respectively (Table 4.6). Allophylus rubifolius (A.Rich.) Engl. had almost
equal densities of seedlings in all transects. However, Cassipourea malosana had the
highest density of seedlings in NNT1 whereas Trilepisium madagascariense had the
highest density of seedlings in SNT2 only.
Table 4.6: Density of woody plant seedlings
Woody species NNT1
Den/ha
SNT1
Den/ha
SNT2
Den/ha
SNT3
Den/ha
Total
Den/ha
Prunus africana 5779 11545 580 936 18840
Diospyros abyssinica 4016 1247 558 508 6329
Cassipourea malosana 1673 80 89 107 1950
Allophylus rubifolius 602 523 134 615 1875
Trilepisium madagascariense * * 1718 * 1718
Strombosia scheffleri 134 402 513 * 1049
Deinbollia kilimandscharica 290 * 602 80 973
Celtis africana 268 456 * 161 884
Tabernaemontana stapfiana 245 188 45 294 772
Albizia gummifera 312 40 178 214 745
(*) Indicates only present in the random plots
The results showed that Prunus africana, Diospros abysinica, Cassipourea malosana
and Allophylus abysinica have the highest density of seedlings and hence a high
regeneration potential respectively.
4.2.12 Plant communities in association with P. africana
The study showed that there was a high frequency of P. africana in association with
Croton megalocarpus community (Figure 4.19). Other communities where P.
africana was present included; Croton macrostychyus, Polyscias fulva,
Tabernaemontana stapfiana and Solanum mauritianum among others. In most cases,
P. africana occurred with one or two more other tree species to form a community

50
Figure 4.19: Top 15 plant communities in association with P. africana
4.2.13 Plant communities where P. africana seedlings were present
Prunus africana seedlings were enumerated in a 1 m by 1 m quadrats at the centre
and the four corners of the sub-plots of 20 m by 20 m. The study showed that Prunus
africana, Croton megalocarpus, Croton macrostachyus and Albizia gumiffera
communities had a high count of P. africana seedlings. It was also found that the
communities where P. africana tree was not present recorded very low density of P.
africana seedlings. These included Solanum mauritianum and Tabernaemontana
stapfiana communities.

51
4.3 Determination of the uses and conservation threats of P. africana by the
local communities in North and South Nandi forests
4.3.1 Study population structure
A total of 188 household heads were interviewed and questionnaires administered in
this study. Among them, 129 (68.6%) were males while 59 (31.4%) were females.
The household heads were grouped into three age classes and majority (51%) were of
middle age (31-50 years) while the young (18-30 years) and the elderly (51 years and
above) formed 15% and 34% respectively. The household population had a mean of
5±2 individuals with a minimum of one and a maximum of 17.
In terms of occupation the majority 141 (75%) were farmers while the others were 22
(11.7%) self-employed, 16 (8.5%), businessmen and two (1.1%), medicine men. In
addition, majority 119 (63.3%) level of education was secondary school while 39
(20.7%) primary, 24 (12.8%) tertiary and six (3.2%) none respectively.
Majority of the household had an average land size of < 5 acres (89%) while the rest
had an average of 5-10 acres (26%), more than 10 acres (21%) and none (5%). Some
of the household head (47%) could not reveal the size of their farm. In 107 farms
(57%), P. africana was present while 73 (39%) had P. africana absent.
4.3.2 Awareness by the local community of the population status of P. africana
The study found out that 99% of the respondents were aware of the P. africana tree.
Among them, 82% agreed that their population was decreasing both in the forest and
the surrounding farmlands while 17% said that the population was increasing. The
decrease mainly was attributed by the locals to the following; charcoal burning
(49.5%), logging (47.9%), overgrazing (19.1%) and poor regeneration (13.8%)
which results from low level of recruitment into mature individuals hence reducing

52
the chances of survival, firewood collection (8%), debarking (4.3%), infestation
(3.7%), uprooting (2.7%), forest fires (1.6%) and invasive species (1.6%). On the
other hand, those who said that the population was increasing attributed it to the
following; high regeneration of the seedlings (69%) and planting of the tree on farms
(24%) among others.
Seventy four percent of the respondents were aware that P. africana is a vulnerable
species while 26% were not aware. Amongst them, 86% were aware of the
requirement of a permit to cut down P. africana as well as any indigenous tree for
the various purposes. This information, they said was obtained mainly from Kenya
Forest Service (KFS) officers (57%) such as forester, forest rangers and scouts. Other
sources of the information included; government officials especially the chiefs and
village elders (6%), Non-governmental Organizations mainly Nature Kenya (5%),
Government agencies specifically NEMA (5%), Private companies within the area
specifically Eastern Produce Kenya (4%) and local media (3%) which include
television and radio stations among others.
4.3.3 Sources and Uses of P. africana by the local community
The study established that majority of the locals (66%) acquire P. africana for use
from the forest while others (52%) acquire them from their farmlands. Other sources
of P. africana include the homesteads (9%) some of which were planted by their
forefathers for medicinal purposes and along the rivers and roads (2%). The
frequency of collection for various purposes was however not uniform. For instance,
majority of them only collect them when a need arises (92%) while others collect
them on monthly (4%), yearly (3%) and weekly (1%) basis.

53
Their main source of seedlings for planting included the forest (44%), Non-
Governmental Organizations such as Nature Kenya (34%), local tree nurseries 16%)
and Kenya Forest Service (3%).
Prunus africana is important to the local communities socially, economically and
culturally. It was established that all parts of the P. africana tree were utilized for
different purpose. The major parts of P. africana used by the locals were the stem
(95%), branches (90%), bark (67%), leaves (57%) and roots (18%) respectively
(Figure 4.20).
Figure 4.20: Parts of P. africana used by the local community
About 95% of the respondents use the stem for timber (47%), charcoal burning
(30%), wood (12%) and beams/posts (11%). In addition, about 90% of the
respondents use the branches for firewood (68%), charcoal burning (13%), fencing
(12%) and other purposes (7%) for instance, handles for axes and hoes. About 67%
of the respondents use the bark for human medicine (52%), livestock medicine (44%)
and for other uses (4%). The bark is crushed and boiled to produce a concoction that
is used to treat a wide range of illness. Furthermore, about 33% of the respondents

54
use the roots for medicinal purposes (76%) and firewood (24%). About 57% of the
respondents use the leaves as medicine both for humans and animals (39%), animal
feeds especially during droughts (36%), shade (22%) and as manure (3%) for crops.
The study found out that 74% of the respondents are aware of P. africana products in
the local market which include the furniture (96%) and beams (4%). However, 99%
were not aware of any P. africana used in the international market such as medicine
for the treatment of prostate cancer.
4.3.4 Conservation threats of P. africana tree and other species
Based on the threats incidence per sampling plots (20 x 20 m), the study found that
Grazing ranked as a major threat to conservation of P. africana based on frequency
of occurrence (Figure 4.21). Trampling ranked the second while firewood collection
and logging followed respectively. Other threats recorded though at a lower
frequency included debarking, charcoal burning and invasive species. Uncontrolled
firewood collection was recorded in most of the sampling sites and especially SNT2
while charcoal burning was recorded most frequently in SNT3. Debarking was
evident in North Nandi forest where small patches were removed hence not in a level
to cause major concern as a threat on the conservation of P. africana. The spread of
invasive shrub, Cestrum aurantiacum, especially in North Nandi forest is now
causing concerns for the conservation of the native species.

55
Figure 4.21: Conservation threats of P. africana in Nandi forests
A total of 266 (95.3%) of P. africana mature individuals were recorded without signs
of destruction. However, 11 (3.9%) individuals were found to be debarked (Figure
4.22) while two (0.7%) had an abnormal growth of the stem. There was a high
incidence of debarking in North Nandi forest (81.8%) than in South Nandi forest
(18.2%).
.
Figure 4.22: Conservation threats to P. africana in North and South Nandi forests; (a)
grazing (b) Debarked P. africana stem. Source: Author
(a) (b)

56
4.3.5 Measures taken to conservation of P. africana by the locals
The study established that some of the locals had taken measures which can help
conserve P. africana (Figure 4.23). Majority of them (70%) participated in planting
P. africana in their farms as well as in protection of the few remaining in the forest.
Some of the community members volunteered as forest scouts helping the Kenya
Forest Service (KFS) in the management of the forest. However, some were reported
not to be doing anything to conserve P. africana.
Figure 4.23: Steps taken to conserve P. africana by the local community
Some of the suggestions made by the locals toward conservation of the species in the
forest and farmland included the following; encouraging the locals to plant P.
africana in their farms (34%), creation of awareness on the importance of P. africana
to the locals (24%), protection of the already establish P. africana trees on farms
(17%), establishment/support of the existing tree nurseries (15%) and supply of P.
africana seedlings to the farmers (7%) among others (3%).

57
CHAPTER FIVE
Chapter 5 DISCUSSION
5.1 The population density, size and spatial distribution of P. africana in North
and South Nandi forests
Prunus africana was found to be present in the two forest blocks and the surrounding
farmlands. The study therefore supported the observations of other researchers that
P. africana was indigenous to afromontane forest regions (Nzilani, 1999; Njunge,
2011; Girma, 2011; Girma 2015) and occurs in moist evergreen forests in Kenya
(Beentje, 1994; BIOTA, 2004).
The high abundance of P. africana in North Nandi and the central parts of South
Nandi forest around Kobujoi forest station can be attributed to the low anthropogenic
disturbance especially from logging, charcoal burning. Similar studies have found
that logging and charcoal burning are the major threats to mature individuals of P.
africana due to their good quality charcoal and firewood they produce (Sunderland
& Tako, 1999; Fashing, 2004).
The suitability distribution modeling of P. africana in South Nandi forest showed a
high density of P. africana towards North Eastern and central parts of South Nandi
forests and surrounding farmlands. This can be attributed to its high regeneration and
establishment under various ecological conditions (Cheboiwo et al., 2014).
Conversely, North Eastern part of the forest towards Kimondi site and the Southern
part of the forest and the surrounding farmlands had low population of P. africana.
This can be attributed to ecological conditions which might not favour the
establishment of P. africana in some areas (Davis, 1994; Salem, 2003; Brummitt et
al,. 2008 and Breugel et al,. 2011). The Species distribution models allowed us to

58
forecast anthropogenic effects on patterns of P. africana at different spatial scales
(Guisan & Thuiller, 2005; Miller, 2010).
Individuals of P. africana in North Nandi forest were smaller in mean DBH than
South Nandi forest. This is an indication of a better regeneration and succession of
the species in North Nandi forest block. This could be attributed to the better
management of the forest which experienced low incidence of selective logging and
charcoal burning (Farwig et al., 2008).
Other studies have found that P. africana prefers disturbance for good regeneration
where there is low percentage canopy cover and good penetration of light for
seedlings and saplings recruitment (Hall et al., 2000; BIOTA, 2004; Fashing, 2004;
Farwig, 2006; Abebe, 2008; Farwig et al,. 2008b; Weru, 2012). This could therefore
explain why P. africana was found to be abundant along the forest edges.
However, Cestrum sp an invasive species formed a major threat to P. africana
especially in North Nandi forests. Invasive species and fire have been found as a
major threats to P. africana (Jimu & Ngoroyemoto, 2011). Furthermore, in South
Nandi forest Alchemilla kiwuensis dominated some areas and hence probably
suppressed the regeneration of other woody tree species including P. africana.
The overall diameter class distribution with a high percentage of large trees along
with few trees and saplings in lower diameter classes indicates a low regeneration
and recruitment. This is also an indication of unstable population structure of P.
africana in the two forest blocks hence threatening their survival in the future
(Cunningham, 2008; Abebe, 2008; Kleinschroth, 2010). This pattern is described by
Mligo et al., (2009) as interrupted and by Khan et al., (2015) as unsatisfactory due
to lack of replacement of the older tree and hence no structural succession.

59
The highest DBH size of P. africana was more than that recorded by Hitimana
(2000) of 1.1 m, Orwa et al., (2009) and Betti (2008) of 1.5 m. The height of the
tallest P. africana was higher than that observed by Beentje, 1994; Dalitz et al.,
2011, but concurred with the one made by Steward (2003) and Navarro-Cerrillo et
al., (2008). This indicates that P. africana is a secondary forest species and hence the
open canopy due to heavy disturbance from logging and charcoal burning in SNT3
was an important disturbance for the regeneration of P. africana (Owiny and
Malinga, 2014).
It has been reported that P. africana has a better reproductive performance indicated
by the high density of seedlings but exhibit poor survival (Fashing, 2004; Abebe,
2008). This can be attributed to seedling predation and herbivory that results into
seedlings mortality at a given seedling stage (Abebe, 2008; Tsingalia, 1989) as well
as the high and extensive level of overgrazing where P. africana seedling and
saplings are fed on by livestock (Khan et al., 2015). This has been identified as one
of the factors preventing seedlings establishment of degraded forest ecosystems
(Abebe, 2008). Enrichment of valuable tree species with supplement plantings may
be required to keep the valuable species as part of these forests (Girma & Mosandl,
2012).
Although majority of the population of P. africana had no signs of any destruction,
debarking remained as a threat especially in NNT1. This could be attributed to the
high demand for the bark used by the local herbalists and community for the
treatment of various human and animal diseases. Herbalists preferred medium sized
individuals which support the augment that they have higher level of the medicinal
compounds used for treatment (Gachie et al., 2012).

60
Although in our case debarking was low, the rate of harvesting and the technique
used was not uniform hence threatening the survival of this species (Fashing, (2004);
Jimu, 2011). Our findings are similar to those of Fashing (2004) who stated that poor
regeneration and survival of seedling and not debarking were the major causes of
population decline of P. africana.
In addition, Stewart, (2003) noted that wild-collection is no longer sustainable where
harvest adversely affects morbidity and mortality rates of harvested populations. It
has also been reported that threats varies from countries to countries and hence the
conservation strategies may be similar or different (Ingram et al., 2009; Jimu, 2011).
Preservation of the P. africana species depends on sustainable harvesting methods
and on farm cultivation (Farwig et al., 2008; Betti et al., 2014).
A high density of P. africana was found to be in SNT1 in South Nandi forest around
Kobujoi area. This area formed the Conservation Priority 1 area and should be given
a higher priority for conservation. A study in Cameroon found that such areas formed
part of in-situ conservation measures when conserved to maintain the representative
viable populations and used as seed source for on-farm production (Cunningham et
al., 2002; Freudenberger et al., 2013).
The limited resources available for conservation of biodiversity and ecosystem
services call for prioritization scheme (Brooks, 2010; Cunningham, 2002;
Freudenberger et al., 2013) indicating potential hotspots (Salem, 2003). However, in
order to ensure sustainable utilization of P. africana, there is need to conserve the
whole forest in general (Hamilton, 2004) as well as encourage on-farm tree planting
by local communities (Girma & Mosandl, 2012; Omeja, Obua, & Cunningham,
2004).

61
Tropical forest trees often show temporal variations in phenological patterns that are
associated with seasonality and environmental factors or biotic factors (Abebe,
2008). The large number of P. africana not in any reproductive stage in this study
can be attributed to the time of sampling which was done between the months of
February and May. Bentjee (1994) found the peak flowering occurred in February. A
similar study in Kakamega Forest showed that flowering occurs between November
to February (Orwa et al., 2009). Phenological differences of P. africana have been
suggested to vary from year to year as well as from area to area due to environmental
factors (Bentjee, 1994; Abebe, 2008).
Finally, the participation of the local community in monitoring of biodiversity and
management has been found to be effective in biodiversity conservation in
developing countries (Danielsen et al., 2000). The Permanent Sampling Plots set up
in North and South Nandi forests can therefore be used to monitor P. africana
population status and trends in Nandi forests, particularly the regeneration patterns
and survival rates. The information collected will help in the development of
conservation policies and examine the outcomes of management actions and guide in
decision making (Game, Edward, Kareiva & Hugh, 2013; Joseph, Field, Wilcox, &
Possingham, 2006; Kull, 2008).

62
5.2 The association of P. africana with other plant species in North and South
Nandi forests
This study recorded a total of 292 vascular plant species during the sampling period
which was less than that recorded by a previous study in Nandi forest (Girma, 2011;
Girma, 2015), which found a total of 321 vascular plants species. The difference
could be attributed to the sampling effort and time as indicated by the species
accumulation curve which did not approach an asymptote (Willott, 2001; Karl,
2003). However, the numbers rose steeply at first and then more slowly as more rare
species were found. This indicates that new species could still be identified with
increased sampling efforts (Gotelli & Colwell, 2009; Karl I. & Ugland, 2003; Olwell,
Ao, & Hang, 2004).
Solanum mauritianum was ranked as the more frequent species in the two forests.
This could be an indication of degradation of the forest mainly due to anthropogenic
disturbances. Humans caused disturbances to the forests set in motion succession
changes (Njunge, 2011). Solanum mauritianum is an invasive species and can form
dense stands that inhibit the growth of other species through overcrowding and
shading (Bosch, Ward, Clarkson, & Zealand, 2004; Olckers, 2011).
The species richness was relatively higher in SNT1. Based on other researchers
findings, this phenomenon is considered being more diverse than in the rest of the
transects (Colwell, 1988). Species richness is controlled by a combination of history
and biotic and abiotic factors (Therriault & Kolasa, 1999). The results were similar to
a study by Girma, (2015) who found that the species diversity was higher in South
Nandi forest than North Nandi forest.

63
The high evenness and diversity in SNR could be associated to the highly
heterogeneous nature of the vegetation communities encountered during sampling
(Stirling & Wilsey, 2001). A community where the relative abundances of the
species is more even than a community with the same number of species, but with
few dominants and a lot of rare species, is more diverse by a heterogeneity measure
(Althof, 2005).
The difference in species composition between the two forest blocks could also be
due to different forest management regime and anthropogenic pressures rather than
environmental conditions (KIFCON, 1994; Poorter, Hawthorne, Bongers, & Sheil,
2008). Rubiaceae family was the most dominant group because of its diverse nature
of plants ranging from herbs to trees. Biodiversity indices are therefore of
fundamental importance for environmental monitoring and conservation (Morris et
al., 2014).
Among the top six species; Solanum mauritianum, Macaranga kilimandscharica,
Casearia battiscombei, Tabernaemontana stapfiana, Croton megalocarpus and
Albizia gummifera, three (3) species were recorded among the top six in a previous
floristic survey done by Njunge, (2011). The three species are; Casearia
battiscombei, Tabernaemontana stapfiana and Croton megalocarpus. The study
agrees with Njunge, (2011) that there is succession process taking place and mainly
attributed to human activities like logging, charcoal burning and firewood collection.
Plant size is an important indicator of species position along the vertical light
gradient in the vegetation (Poorter et al., 2008).
The study on all woody plant species showed that majority were of lower DBH
ranging from 5-24 cm. The DBH class size distribution conformed to the inverse- J

64
shape which is an indication of continuous regeneration and succession process
taking place in the forest (Fashing, 2004; Hitimana et al., 2004; Abebe, 2008).
Regeneration of tree species is commonly assessed by the distributions of size-
classes measured as Diameter at Breast Height (DBH) or height (Abebe, 2008). This
can also be attributed to the high frequency of species mainly Solanum mauritianum,
Mimulopsis aborescence and Mimulopsis solmsii which formed the majority of the
woody shrubs layer. The three species are disturbance indicator species usually
frequent in forest gaps or edges of forests (KIFCON, 1994).
On the other hand, bell-shaped size-class distribution has been attributed to disturbed
forest where regeneration is hampered (Poorter et al., 2008). Population structure
gives good indication of the impact of disturbance and the forest successional trends.
Such information is critical in increasing our understanding of the conservation needs
of tropical forest ecosystems and P. africana in our case (Owiny & Malinga, 2014)).
The high stress value (0.17) of the Multidimensional Scaling may be attributed to the
greater distortion of the species composition of each sampling plots. The
dissimilarity of North and South Nandi forests could have been brought about by
fragmentation and isolation where each forest block seems to be undergoing
evolutionary changes independently (Omeja et al., 2004). The anthropogenic
pressures of the two forests influence the forest structure and composition. However,
the 47 – 68% similarity and high percentage of common species between them is an
indication that the forest blocks had a common origin (Schaab et al., 2010).

65
5.3 Uses and conservation threats of P. africana by the local community of
The study established a high awareness of P. africana by the local communities
living around South Nandi forest. This can be attributed to P. africana ecological
distribution which is widespread in mountainous forest (Stewart, 2003; Betti &
Ambara, 2013).
Majority of the respondents agreed that P. africana populations were decreasing in
the forest which was attributed to the high demand because of its multi-purpose
functions. According to other researchers, the decrease in P. africana population has
mainly been attributed to its multi-purpose function (Cunningham and Mbenkum,
1993; Cunningham, 2002; Fashing, 2004; Betti, 2008; Bii et al., 2010; Mwitari et al.,
2013 and Ingram et al., 2015). The findings therefore agreed with the global
recognition that P. africana populations is declining from its natural range, and even
getting locally extinct in some cases due to overharvesting (IUCN 2013).
The study found that P. africana was preferred by the locals because of its good
quality charcoal and timber used for construction and furniture which could also be a
reasons for the decline in population. The role of legal and illegal logging as causes
of the decline in populations of P. africana has been clearly evident and documented
(Sunderland & Tako, 1999; Cunningham et al., 2002).
In Ethiopia, the local people harvest and use the bark, stem and branches for fuel
wood, charcoal production and as timber (Betti & Ambara, 2013). Stewart (2003)
noted that P. africana is valued for its high quality timber for fuel and making tool
handles. Other use of P. africana include the use in homesteads as a shade, manure

66
for use in the farms and branches were used for fencing and construction of tool
handles (Stewart, 2003; Fashing, 2004; Betti & Ambara, 2013).
Prunus africana was used by herbalist and the locals to cure more than one ailment
depending on the part used, mode of preparation and administration. Several studies
have shown that P. africana bark is used by herbalists, in treatment of prostate
problems, as a remedy for stomachache and an infusion to treat appetite, urinary and
bladder infections, chest pain, malaria, and kidney disease (Stewart, 2003; Fashing,
2004; Addo-fordjour et al., 2008; Navarro-Cerrillo et al., 2008; Bii et al., 2010;
CITES, 2012 and Mwitari et al., 2013).
The close proximity to the forest provided easier accessibility to P. africana in the
forest by the locals. This was attributed to the increased human population which led
to more pressure on the available resources in the farmland hence the need to
supplement their demands from the forest. Prunus africana is a multipurpose tree for
the local use hence its demands is high (Jimu, 2011). It is also widely reported that
rural households rely on wild natural resources to help meet current-consumption
needs and to provide a safety net in times of hardship (Belcher et al., 2015).
Majority of the locals were aware of the furniture and beams as the main products of
P. africana in the local market. This is an indication of the good quality of the wood
attributed to P. africana (Stewart, 2003; Fashing, 2004; Betti & Ambara, 2013).
Lack of awareness of any international products of P. africana can be attributed to
lack of information and sensitization of the importance of P. africana.
Some of the community members had volunteered as forest scouts helping the Kenya
Forest Service (KFS) in the management and conservation of the forest. Planting P.
africana on farms as well as helping in protecting them in the forest by reporting any

67
illegal harvesting or any form of destruction of the forest is a good starting point
towards the conservation of the species.
However, some reported to be doing nothing to conserve P. africana which could be
due to lack of awareness on the importance of the tree. The best way to ensure the
survival and sustainable utilization of this multi-purpose tree species in the future is
planting them on farms (Hall et al., 2000; Franzel et al., 2009; Ingram et al., 2009;
Ingram et al., 2015).
The study established that the major source of P. africana seedlings was the forest.
This was due to the high germination of the seeds that fell from the mother plant and
germinate under the shade hence could be collected for free. Other sources of
seedlings to the locals included non-government agencies, local tree nurseries and
the Kenya Forest Service (KFS). In addition, they also collect the seedlings from
natural regeneration in their farms and homesteads. Prunus africana seeds are highly
dispersed by birds (Farwig et al., 2006) and therefore can be found germinating
naturally at any suitable grounds.
Overgrazing and illegal grazing in the forest have been found to be the major threat
to P. africana and other species (Ingram, 2009; Schaab et al., 2010; Khan, 2015;
Mligo 2015). Communities living near the forest keep large herds of livestock and
rely on the forest for grazing throughout the year. The livestock destroy plants
especially the seedlings and saplings. The locals attributed P. africana seedlings as
more palatable hence preferred by livestock. However, grazing was not a major
threat for mature individuals of P. africana.
Other notable causes of the decrease of P. africana by other studies were poor
regeneration (Cunnigham, 2002; Fashing, 2004; Abebe, 2008; Vincenti 2013),

68
firewood collection (Girma, 2011), debarking (CITES, 2012; Vincenti, 2013),
infestation (Orwa et al., 2009; Weru, 2012) and invasive species (MEA, 2005; Lung,
2010; Jimu, 2011). Trampling caused by animals and humans trespassing the forest
causes gullies, made worse by soil erosion which eventually destroys the forest
habitat (Girma, 2011).
On the other hand, population increase was attributed to the natural regeneration of
P. africana seedlings (Hall, 2000). However, in reality this was not the case as most
of the seedlings did not survive to maturity due to threats especially overgrazing.
Increased planting of P. africana in the farmlands due to their economic value was
seen as a major contributing factor to their increase. The cultivation of medicinal
plants on farm have been found to be a means to combine biodiversity conservation
especially the endangered species and alleviate poverty (Wiersum, 2006; Ingram,
2014).
A dense and rapidly growing human population around the forest exerts high
pressure on the forest. This has led to an increased demand for fuel wood, timber and
charcoal for both domestic and commercial purpose contributing to illegal logging
and vegetation destruction. Firewood remains the most widely used source of energy
for the local communities around the forest (Stewart, 2003; Weru, 2012).
Moreover, Illegal charcoal production and logging have led to destruction of specific
trees like P. africana, Macaranga kilimandischarica and Strombosia scheffleri
(Fashing, 2004; Althof, 2005; Farwig et al., 2008a). The fallen and dead logs being
taken out of the forests deprive many species their habitat and ultimately their
ecological role. Other tree species that debarking was evident included Fagaropsis
angolensis and Polyscias fulva.

69
CHAPTER SIX
Chapter 6 CONCLUSION AND RECOMMENDATIONS
The study showed that P. africana population in Nandi forests is relatively low,
unstable and randomly distributed in North and South Nandi forests. The saplings
and young individuals are very few therefore showing no signs of sustainable
recruitment. The lack of P. africana young individuals is majorly due to poor
survival rates to mature individuals associated with the species hence showing some
decline in the foreseeable future.
Prunus africana has a relatively good ecological association with other plant species
in the two forests. It formed one of the major plant communities in the forest with
other species, for instance, Croton megalocarpus. However, it is not among the most
dominant trees in the two forests. It terms of the overall species composition, the two
forests had unique and rich biodiversity. However, South Nandi forest was found to
be more diverse than North Nandi forest.
The most harvested and important part of P. africana to the local community was the
stem due to the high demand for timber and charcoal burning. The bark is most
commonly used as a concoction to treat several human and animal ailments. The
most notable anthropogenic activities threatening the future survival of P. africana
and the entire Nandi forest ecosystem included grazing, logging, trampling, charcoal
burning and debarking. However, the harvesting of P. africana bark in North and
South Nandi forests is not yet at a level that can cause conservation concerns.
In conclusion, it is important for urgent measures be taken in order to rehabilitate and
conserve P. africana and biodiversity of the entire ecosystems of North and South
Nandi forests.

70
Some of the recommendations are:
1. The future of P. africana lies in enhanced planting within and outside the forests.
Site specific conservation based on the developed conservation prioritization
zones should be applied for in-situ conservation of P. africana in the forest.
2. There is need to help the local community set up a propagation units and tree
nurseries of P. africana and other indigenous tree species in the forest. Moreover,
the local community needs to establish woodlots as an alternative to the high
demand for wood fuel from the forest.
3. Local communities around the forest need to diversify livestock keeping systems
that are compatible with limited grazing land to reduce the grazing pressures in
the forest. For instance, zero grazing.
4. There is need to create awareness regarding the social, economic and ecological
importance of P. africana and the entire forest at community level. This can be
done by conducting sensitization campaigns on the conservation of threatened
species and regulation of utilization.
5. The study developed a baseline inventory of the current status of P. africana
population for management planning. The Permanent Sampling Plots (PSPs)
established during the study would be valuable for periodic monitoring of P.
africana and other species of conservation concern in North and South Nandi
forest.
6. Further research: The study did not determine soil type analysis and altitudinal
difference of the two forests which could explain the observed difference in
status of P. africana population and spatial distribution.

71
REFERENCES
Abebe, G. T. (2008). Ecology of regeneration and phenology of seven indigenous
tree species in a dry tropical afromontane forest, Southern Ethiopia. PhD
Thesis, Addis Ababa University.
Abed, T. & Stephens, N. C. (2003). Tree measurement manual for farm foresters.
Practical guidelines for farm foresters undertaking basic tree measurement in
farm forest plantations. Second edition, edited M. Parsons. National forest
inventory, bureau of rural sciences, Canberra.
Addo-fordjour, P., Anning, A. K., Jeremiah, E., & Belford, D. (2008). Diversity and
conservation of medicinal plants in the Bomaa community of the Brong
Ahafo region , Ghana. Journal of Medicinal Plants Research, 2(9), 226–233.
Agnew, A. D. Q. and Agnew, S. (2013). Upland Kenya Wild Flowers. A flora of the
ferns and herbaceous flowering plants of Upland Kenya. Third Edition. East
African Natural History Society, Nairobi.
Alder., D. S. T. . (1992). Permanent Sample Plot Techniques for Mixed Tropical
Forest. Tropical Forestry Papers, 25.
Althof, A. J. (2005). Human Impact on Flora and Vegetation of Kakamega Forest,
Kenya: Structure, distribution and disturbance of plant communities in an
East African rainforest. phD Thesis; Universität Koblenz-Landau.
APG III (2009). An update of the Angiosperm Phylogeny Group classification for
the orders and families of flowering plants: APG III. Botanical Journal of
the Linnean Society 161: 105–121.
Araya, Y. N., Schmiedel, U., & Witt, C. Von. (2009). Linking ― citizen scientists ‖ to
professionals in ecological research , examples from Namibia and South
Africa. Conservation Evidence, 6, 11–17.
Beentje, H. (1994). Kenya Trees, Shrubs and Lianas. National Museums of Kenya,
Nairobi.

72
Belcher, B., Achdiawan, R., & Dewi, S. (2015). Forest-based livelihoods strategies
conditioned by market remoteness and forest proximity in Jharkhand, India.
World development, 66, 269–279.
Http://Doi.Org/10.1016/J.Worlddev.2014.08.023
Betti, J. L. (2008). Non-Detriment Findings report on Prunus africana (Rosaceae) in
Cameroon. NDF Workshop Case Studies WG1 – Trees Case Study 9, 9, 1–
41.
Betti, J. L., & Ambara, J. (2013). Mass of Prunus africana stem barks on Tchabal
Mbabo and Tchabal Gang Daba mountain forests, Cameroon. African
Journal of Environmental Science and Technology, 7(5), 204–221.
Http://Doi.Org/10.5897/Ajest11.241
Betti, J. L., Feruzi, M., Rushemeza, J., & Nzigiyimpa, L. (2014). Sustaining Prunus
africana ( Hook . F .) Kalkman (Rosaceae), A CITES listing tree species in
the Teza. International Journal of Biodiversity and Conservation, 6(9), 674–
680. Http://Doi.Org/10.5897/Ijbc2014.0721
Bii, C., Korir, K. R., Rugutt, J., & Mutai, C. (2010). The potential use of Prunus
africana for the control, treatment and management of common fungal and
bacterial infections. Journal of Medicinal Plants Research, 4(11), 995–998.
Http://Doi.Org/10.5897/Jmpr09.227
BIOTA. (2004). The influence of fragmentation and disturbance on the biodiversity
of East African highland rain forests. Final Report Phase I (2001- 2004).
Birdlife International, (2012). Critical Ecosystem Partnership Fund; Ecoststem
Profile; Eastern Afromontane Biodiversity Hotspot. Report.
Bosch, E. V., Ward, B. G., Clarkson, B. D., & Zealand, N. (2004). Woolly
Nightshade ( Solanum mauritianum ) and its allelopathic effects on New
Zealand native Hebe Stricta seed germination. Weeds of the environment,
101, 98–101.
Breugel, V., & Barnekow, J. (2011). Potential natural vegetation of Eastern Africa
(Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Uganda and Zambia) Volume
7. Projected distributions of potential natural vegetation types and two

73
important agroforestry species (Prunus africana and Warburgia sp.). Forest
& Landscape Working Papers; No. 69/2011
Briganti, A., Capitanio, U., Suardi, N., Gallina, A., Salonia, A., Bianchi, M., …
Montorsi, F. (2009). Benign Prostatic Hyperplasia and its aetiologies.
European Association of Urology, 8, 865–871.
Http://Doi.Org/10.1016/J.Eursup.2009.11.002
Brooks, T. (2010). Conservation planning and priorities. In Chapter 11; Coservation
Biology for All. Oxford University Press (Pp. 199–219).
Brummitt, N., Bachman, S. P., & Moat, J. (2008). As we see it. Applications of the
IUCN Red List : Towards a global barometer for plant diversity. Endangered
Species Research, 6, 127–135. Http://Doi.Org/10.3354/Esr00135
Carlos, J., Saiz, M., Domı, F., & Sainz, H. (2003). Recent progress in conservation of
threatened Spanish vascular flora : A critical review. Biological
Conservation, 113, 419–431. Http://Doi.Org/10.1016/S0006-
3207(03)00128-9
Cheboiwo, J. K., Mugabe, R., Langat, D., Box, P. O., Author, C., & Cheboiwo, J. K.
(2014). Review of conservation of Prunus africana and international trade
opportunities for its bark in Kenya. Journal of Emerging Trends in
Engineering and Applied Sciences, 5(6), 372–377.
CITES. (2012). Convention on International Trade in Endangered Species of Wild
Fauna and Flora. Notification to the Parties No. 2012/048.
Clarke, G.P., Vollesen, K., & Mwasumbi, L.B. (2000) Vascular plants. In: Burgess,
N.D. & Clarke, G.P. (eds.) Coastal forests of eastern Africa, pp. 129-147.
IUCN Forest Conservation Programme. Cambridge University Press,
Cambridge.
Clemente, M., Padro, E., & Kasimis, N. (2008). Forest structure in harvested sites of
afromontane forest of Prunus africana [Hook. F.] Kalkm., in Bioko
(Equatorial Guinea). African Journal of Ecology, 46, 620–630.

74
Colwell, R. K. (1988). Biodiversity: concepts, patterns, and measurement.
Biodiversity, 3(1), 257–263.
Cunningham A. B., Avana T., & Anoncho V. F. (2014). Power, profits and policy: A
reality check on the Prunus africana bark trade. Working Paper 153. Bogor,
Indonesia: CIFOR.
Cunningham, A. B. (Tony). (2008). Prunus africana : In situ conservation,
sustainable management & governance. Meeting at CITES, Geneva.
Cunningham, A. B., Ayuk, E., Franzel, S., Duguma, B. & Asanga, C. (2002). An
economic evaluation of medicinal tree cultivation: Prunus africana in
Cameroon. people and plants working paper 10. UNESCO, Paris.
Cunningham, A. B., Mbenkum, F. T., (1993). Sustainability of harvesting Prunus
africana bark in Cameroon: A medicinal plant in international trade. People
and plants. Working Paper 2, UNESCO, Paris.
Dalitz, C., Dalitz, H. Musila W., & Masinde S. (2011). Illustrated Field Guide to the
Common Woody Plants of Kakamega Forest. Institut für Lanschafts- und
Pflanzenökologie der Universität Hohenheim, Beiheft 24,Germany,
Hohenheim.
Danielsen, F., Balete, D. S., Poulsen, M. K., Enghoff, M., Nozawa, C. M., & Jensen,
A. E. (2000). A simple system for monitoring biodiversity in protected areas
of a developing country. Biodiversity and Conservation, 9, 1671–1705.
Davis, F. (1994). Mapping and monitoring terrestrial biodiversity using Geographic
Information Systems. Biodiversity and Terestrial Ecosystems, 14, 461–471.
Earle-Mundil, H. (2010). Permanent Monitoring Plots for the National Tree Pinus
Caribaea Var . Bahamensis and assessment of the distribution and
conservation status of an associated endemic species Stenandrium carolinae
in the Turks and Caicos Islands. Msc Thesis; Imperial College, London.
Farwig, N., Barbel Bleher, S., Von D. G., & Katrin-Gaese, B. (2008). Does forest
fragmentation and selective logging affect seed predators and seed predation

75
rates of Prunus africana (Rosaceae)? Biotropica, 40(2), 218–224.
Http://Doi.Org/10.1111/J.1744-7429.2007.00365.X
Farwig, N., Böhning-Gaese, K., & Bleher, B. (2006). Enhanced seed dispersal of
Prunus africana in fragmented and disturbed forests? Oecologia, 147(2),
238–52. Http://Doi.Org/10.1007/S00442-005-0288-9
Farwig, N., Braun, Æ. C., & Bo, Æ. K. (2008). Human disturbance reduces genetic
diversity of an endangered tropical tree , Prunus africana (Rosaceae).
Conservation Genetics, 9, 317–326. Http://Doi.Org/10.1007/S10592-007-
9343-X
Fashing, P. J. (2004). Mortality trends in the African Cherry (Prunus africana) and
the implications for Colobus Monkeys (Colobus Guereza) in Kakamega
forest, Kenya. Biological Conservation, 120, 449–459.
Http://Doi.Org/10.1016/J.Biocon.2004.03.018
Franzel, S., E. Ayuk, A. B. Cunningham, B. Duguma & C. Asanga (2009), Bark for
sale: The adoption potential of Prunus africana as an agroforestry tree for
small-scale farmers in Cameroon. Bark: Use, Management and Commerce in
Africa. A. B. Cunningham. 17.
Freudenberger, L., Hobson, P., Schluck, M., Kreft, S., Vohland, K., Sommer, H., …
Ibisch, P. L. (2013). Nature Conservation: Priority-Setting Needs a Global
Change. Biodiversity and Conservation, 22 (5), 1255–1281.
Http://Doi.Org/10.1007/S10531-012-0428-6
Funk, V. A., Zermoglio, M. F., & Nasir, N. (1999). Testing the use of specimen
collection data and GIS in biodiversity exploration and conservation decision
making in Guyana. Biodiversity and Conservation, 8, 727–751.
Gachie, P. K., Koech, E. K., Njunge, J. T., Simons, A. J., & Ndalut, K. (2012).
Variation in yield and composition of crude bark extracts of P . africana in
different Provenances of Kenya. Forests, Trees and Livelihoods, 21 (1), 37–
41. Http://Doi.Org/10.1080/14728028.2012.662627

76
Game T., Edward., Kareiva P., & Hugh P. (2013). Six common mistakes in
conservation priority setting. Conservation Biology, 27(3), 480–485.
Http://Doi.Org/10.1111/Cobi.1201
Garcıa, B., Gon, D., & Guzma, D. (2002). An evaluation of the status of five
threatened plant species in the Pyrenees. Biological Conservation, 103, 151–
161.
Girma, G., A. (2011). Plant Communities, Species Diversity, Seedling Bank and
Resprouting in Nandi Forests, Kenya. PhD thesis, Department of Biology,
University of Koblenz-Landau.
Girma, A., & Mosandl, R. (2012). Structure and potential regeneration of degraded
secondary stands in Munessa-Shashemene Forest , Ethiopia, 24(1), 46–53.
Girma A., Eberhard F., & Bonny D. (2015). Vascular Plant Diversity and
Community Structure of Nandi Forests, Western Kenya. Journal of East
African Natural History, 103 (2), 125-152
GoK (2000). The Kenya National Biodiversity Strategy and Action Plan. Ministry of
Environment and Natural Resources, Government of Kenya (GoK), Nairobi
GoK (2010). Kenya population and Housing Census 2009. Kenya National Bureau
of Statistics, Government of Kenya (GoK), Nairobi
GoK (2016). Ministry of Environment and Natural Resources (MENR). National
Forest Programme of Kenya. Nairobi, Kenya.
Gontier, M. (2007). Scale issues in the assessment of ecological impacts Using a
GIS-Based Habitat Model — A Case Study for the Stockholm region.
Environmental Impact Assessment Review, 27(5), 440–459.
Http://Doi.Org/10.1016/J.Eiar.2007.02.003
Gontier, M., Balfors, B., & Mörtberg, U. (2006). Biodiversity in environmental
assessment—current practice and tools for prediction. Environmental Impact
Assessment Review, 26(3), 268–286.
Http://Doi.Org/10.1016/J.Eiar.2005.09.001

77
Gotelli, N. J., & Colwell, R. K. (2009). Estimating species richness. Biological
Diversity, (2), 39–54.
Guisan, A., & Thuiller, W. (2005). Predicting species distribution : offering more
than simple habitat models. Ecology Letters, 8, 993–1009.
http://doi.org/10.1111/j.1461-0248.2005.00792.x
Hall, J.B., O‘brien, E.M., Sinclair, F. L. (2000). Prunus africana: A Monograph.
School of Agricultural and Forest Sciences Publication Number 18,
University of Wales, Bangor, India.
Hamilton, A. C. (2004). Medicinal Plants, Conservation and Livelihoods.
Biodiversity and Conservation, 13, 1477–1517.
Hammer, Ø. (2012). Past Paleontological Statistics. Version 2.17. Reference
Manual. Natural History Museum University of Oslo.
Hitimana J. (2000). Variation in structure, composition and regeneration within the
Mt. Elgon moist lower montane forest, Kenya. M. Phil. Thesis, Moi
University, Eldoret Kenya
Hitimana, J., Kiyiapi, J. L., & Njunge, J. T. (2004). Forest Structure Characteristics
in Disturbed and Undisturbed Sites of Mt . Elgon Moist Lower Montane
Forest, Western Kenya. Biological Conservation.
http://www.africanorchids.dk/higher-epidendroideae/tribe-cymbidieae/subtribe-
eulophiinae/oeceoclades/index.php?option=com_content&view=article&id=
2647:nervilia-bicarinata&catid=242:nervilia&Itemid=101
Ibisch, P. L., Nowicki, C., Müller, R., & Araujo, N. (2002) Methods for the
Assessment of Habitat and Species Conservation Status in Data-Poor
Countries- Case Study of the Pleurothallidinae (Orchidaceae) of the Andean
Rain Forests of Bolivia. Conservation of Biodiversity in the Andes and the
Amazon, 225–246.
Ingram V., Awono A., Schure J., & Ndam N. (2009). Guidance for a national
Prunus africana management plan, Cameroon. Center for International
Forestry Research, Food and Agri- culture Organization: 158. Online

78
document at: www .fao.org/forestry/20776-
0928f6e1bca7338bedfca1afabcfe2b89 .pdf. Accessed July 20, 2015.
Ingram V. J., Loo J., Barbara V., Dawson I.D., Alice M., Jérôme D., & Awono E., A.
(2015). Ensuring the Future of the Pygeum Tree (Prunus africana). Briefing
on Prunus africana Cultivation and Harvesting. Technical Report Lei
Wageningen Ur, 033 Ingram (May).
Http://Doi.Org/10.13140/Rg.2.1.4259.7280
Ingram, V. J. (2014). Win-Wins in Forest Product Value Chains? How Governance
Impacts the Sustainability of Livelihoods Based on Non-Timber Forest
Products from Cameroon. In Amsterdam Institute for Social Science
Research, Governance and Inclusive Development Group. University of
Amsterdam: Amsterdam. P. 361., 114.
IUCN (2015) Red List of Threatened Species. Version 2015-4.
<www.iucnredlist.org>. Downloaded on 30 November 2015.Date
IUCN (2013). IUCN Red List of Threatened Species. Version 2013.1. http://
www.iucnredlist.org.
IUCN. (2000). IUCN Red List Categories and Criteria: Version 3.1. Second Edition.
Gland, Switzerland and Cambridge, UK: IUCN. Iv + 32pp.
Jeruto, P., Charles, M., George, O., & Lukhoba, C. (2011). An Inventory of
Medicinal Plants That the People of Nandi Use To Treat Malaria. Journal of
Animal & Plant Sciences, 9 (3), 1192–1200.
Jimu, L. (2011). Threats and conservation strategies for the African cherry (Prunus
africana) in its natural range- A review. Journal of Ecology and the Natural
Environment, 3(4), 118–130.
Jimu, L., & Ngoroyemoto, N. (2011). Habitat Characteristics and Threat Factors of
the Rare and Endangered Prunus africana (Hook . F .) Kalkman In.
International Journal of Biodiversity and Conservation, 3(6), 230–236.
Joseph, L. N., Field, S. A., Wilcox, C., & Possingham, H. P. (2006). Presence –
Absence Versus Abundance Data for Monitoring Threatened Species.

79
Conservation Biology Volume, 20 (6), 1679–1687.
Http://Doi.Org/10.1111/J.1523-1739.2006.00529.X
Kadu, C. A. C., Konrad, H., Schueler, S., Muluvi, G. M., Eyog-Matig, O., Muchugi,
A., & Geburek, T. (2013). Divergent Pattern of Nuclear Genetic Diversity
Across the Range of the Afromontane Prunus africana Mirrors Variable
Climate of African Highlands. Annals of Botany, 111, 47–60.
Http://Doi.Org/10.1093/Aob/Mcs235
Kadu, C. A. C., Parich, A., Schueler, S., Konrad, H., Muluvi, G. M., Eyog-Matig, O.,
Kapinga, C. (2012). Bioactive Constituents in Prunus africana :
Geographical Variation Throughout Africa and Associations with
Environmental and Genetic Parameters. Phytochemistry, 83, 70–80.
Kadu, C. A. C., Schueler, S., Konrad, H., Muluvi, G. M. M., & Africa, S. (2011).
Phylogeography of the Afromontane Prunus africana Reveals a Former
Migration Corridor Between East and West African Highlands. Molecular
Ecology, 20, 165–178. Http://Doi.Org/10.1111/J.1365-294x.2010.04931.X
Kagombe J., Kimondo J., Otieno V., & Kiama S. (2012). Draft Management Plan for
Nandi Forest Ecosystem under the Strenghtening Protected Area Network
Within The Eastern Montane Forest Hotspot of Kenya. Draft report.
Karl I., Ugland, J. S. G., & Kentria. E. E., (2003). The Species–Accumulation Curve
and Estimation of Species Richness. Journal of Animal Ecology - Wiley
Online Library, 72, 888–897.
Kent, M. and Coker, P. (1992). Vegetation Description and Analysis: A Practical
Approach. John Wiley and Sons Ltd. New York.
Khan, Z., Akbar, M., Rizvi, S. M. A., Hussain, A., Ali, I., Ali, M., Hussain, J. (2015).
Assessment of Deforestation Using Diameter Size Classes Distribution of
trees in Ganji Valley Himalayan Range of Pakistan. International Journal of
Advanced Research, 3(6), 76–86.
KIFCON (1994). Kakamega Forest. The official guide. KIFCON (Kenya Indigenous
Forest Conservation programme), Nairobi, Kenya.

80
Kleinschroth, F., Cierjacks, A., Schöning, C., Kung, J. B., & Kowarik, I. (2010).
Where Are The Seedlings On These Slopes ? Regeneration of Ocotea
Usambarensis, A Key Tree Species in Montane Forests in East Africa, is
Still Inhibited 10 Years after Logging. The GFÖ 40th Anniversary Meeting
2010 - Session 3 - Poster 3.9.
KNBSAP. (2000). A Summary of the Kenya National Biodiversity Strategy and
Action Plan; Ministry of Environment & Natural Resources, (March).
Krejcie, R. V, & Morgan, D. W. (1970). Determining Sample Size for Research
Activities. Educational and Psychological Measurement, 30, 607–610.
Kull, T. (2008). Necessity and Reality of Monitoring Threatened European Vascular
Plants. Biodiversity Conservation, 17, 3383–3402.
Http://Doi.Org/10.1007/S10531-008-9432-2
KWS/KFS/UNEP, (2007). Aerial Monitoring of Forest Bounderies. A joint Kenya
Wildlife Service - Kenya Forest Service Programme, supported by United
Nations Environmental Programme. Nairobi. Vol 1. Pp. 29
Lung, T. (2010). Assessing Processes of Long-Term Land Cover Change and
Modelling their Effects on Tropical Forest Biodiversity Patterns – A Remote
Sensing and GIS-Based Approach for Three Landscapes in East Africa. PhD
Thesis, Technical University of Dresden, Germany.
Malonza P. (ed) 2013. Biodiversity monitoring and mapping of threatened species in
the Eastern Afromontane protected areas: Kakamega forest, South/North
Nandi forests, Kenya - DRAFT. National Museums of Kenya, Nairobi.
Margalef, D. R. (1958). Information theory in ecology. General Systems 3:36-71.
Maximillian, J. R., & O‘laughlin, J. (2009). Toward Sustainable Harvesting of
Africa‘s Largest Medicinal Plant Export (Prunus africana): A Case Study in
Tanzania. Southern Forests: A Journal of Forest Science, 71(4), 303–309.
Http://Doi.Org/10.2989/Sf.2009.71.4.8.1035
Mbatudde, M., Nyakaana, S., Ploß, S., & Dalitz, H. (2013). Genetic Structure of
Prunus africana Rosaceae (Hook . F .) Kalkm . In East Africa , as Inferred

81
from Nuclear and Chloroplast DNA. The African Journal of Plant Science
and Biotechnology, 7(1), 9–14.
McIntosh, R.P. (1967). An index of diversity and the relation of certain concepts to
diversity, Ecology 48: 392-404
MEA. (2005). Millenium Ecosystem Assessement. Ecosystems and Human Well-
Being: Synthesis. Island Press, Washington, DC.
Miller, J. (2010). Species Distribution Modeling. Geography Compass, 4(6), 490–
509.
Mittermeier, R. A., Turner, W. R., Larsen, F. W., Brooks, T. M., & Gascon, C.
(2011). Global Biodiversity Conservation : The Critical Role of Hotspots.
Conservation International, Arlington, USA, 3–8. http://doi.org/10.1007/978-
3-642-20992-5
Mligo, C., Lyaruu, H., Ndangalasi, H., & Marchant, R. (2009). Vegetation
Community Structure, Composition and Distribution Pattern in the
Zaraninge Forest, Bagamoyo District, Tanzania. Journal of East African
Natural History, 98(2), 223–239. Http://Doi.Org/10.2982/028.098.0204
Morris, E. K., Caruso, T., Fischer, M., Hancock, C., Obermaier, E., Prati, D., …
Nicole, W. (2014). Choosing and using diversity indices : insights for
ecological applications from the German Biodiversity Exploratories. Ecology
and Evolution, 4(18), 3514–3524. http://doi.org/10.1002/ece3.1155
Muchugi, A., Lengkeek, A. G., Kadu, C. A. C., Muluvi, G. M., Njagi, E. N. M., &
Dawson, I. K. (2006). Genetic Variation in the Threatened Medicinal Tree
Prunus africana in Cameroon and Kenya: Implications for Current
Management and Evolutionary History. South African Journal of Botany,
72(4), 498–506. Http://Doi.Org/10.1016/J.Sajb.2006.01.003
Mugaka, B. P., Erasto, P., Otieno, J. N., Mahunnah, R. A., & Kaale, E. (2013).
International Journal of Pure & Applied Bioscience Comparison of N-
Docosanol and Β - Sitosterol Content in the Leaf and Stem Bark of Prunus
africana Collected From Different Geographical Zones in Tanzania.
International Journal of Pure & Applied Bioscience, 1(6), 132–138.

82
Mugenda O.M, and Mugenda A.G, (2003). Research methods. Quantitave and
quality approaches. African Centre for Technology Studies (ACTA)
Nairobi, Kenya
Mutangah, J.G., Mwangangi, O. and Mwaura, P.K. (1992). Kakamega Forest: a
vegetation survey report. KIFCON (Kenya Indigenous Forest Conservation
programme), Nairobi, Kenya.
Mwitari, P. G., Ayeka, P. A., Ondicho, J., Matu, E. N., & Bii, C. C. (2013).
Antimicrobial Activity and Probable Mechanisms of Action of Medicinal
Plants of Kenya : Withania Somnifera , Warbugia Ugandensis, Prunus
africana and Plectrunthus Barbatus. Plos One, 8(6), 4–12.
Http://Doi.Org/10.1371/Journal.Pone.0065619
Navarro-Cerrillo RM, Clemente M, Padron E, Hernandez-Bermejo E. (2008). Forest
structure in harvested sites of Afromon-tane forest of Prunus africana
[Hook.f.] Kalkm., in Bioko (Equatorial Guinea). African J Ecol
2008;46:620–630.
NEP. (2013). National Environmental Policy; Revised Draft# 13; Ministry of
Environment and Natural Resources, (February).
Njunge, J. T. And M. J. M. (2011). Composition and Succession of the Woody Flora
of South Nandi Forest, Kenya. Research Journal of Botany, 6(3), 112–121.
NTFP. (2009). Guidance for a National Prunus africana Management Plan
Cameroon; MINISTRY OF FORESTRY AND WILDLIFE, (September 2009),
1–168.
Nzilani NJ (1999). The status of Prunus africana in Kakamega forest and the
prospects for its vegetative propagation. MPhil Thesis. Moi University
Eldoret, Kenya.
Olckers, T. (2011). Biological Control of Solanum mauritianum Scop. (Solanaceae)
in South Africa: Will perseverance pay off? African Entomology, 19(Sp),
416–426. Http://Doi.Org/10.4001/003.019.0220

83
Olwell, R. O. K. C., Ao, Chxua N. M., & Hang, J. I. N. G. C. (2004). Interpolating ,
Extrapolating , and Comparing Incidence-Based Species Accumulation
Curves. Ecology, 85(10), 2717–2727.
Omeja, P., Obua, J., & Cunningham, A. B. (2004). Regeneration , density and size
class distribution of tree species used for drum making in central Uganda.
African Journal of Ecology, 42, 129–136.
Orwa C, A Mutua, Kindt R , Jamnadass R, S Anthony. (2009). Agroforestree
Database: a tree reference and selection guide version 4.0. Nairobi, World
Agroforestry Centre (ICRAF)
(http://www.worldagroforestry.org/sites/treedbs/treedatabases.asp)
Otieno, N. E., & Analo, C. (2012). Local Indigenous Knowledge about Some
Medicinal Plants in and Around Kakamega Forest in Western Kenya [ V2 ;
Ref Status : Indexed , Http://F1000r.Es/Udnybk] Referee Status : F1000
research, 1(40), 1–17. Http://Doi.Org/10.12688/F1000 research.1-40.V1
Owiny, A. A., & Malinga, G. M. (2014). Population Structure and Regeneration
Status of Prunus africana (Hook . F .) Kalkm . After Selective and Clear
Felling in Kibale National Park, Uganda. International Journal of
Biodiversity and Conservation, 6 (December), 869–875.
Http://Doi.Org/10.5897/Ijbc2014.0750
Page, B. (2003). The Political Ecology of Prunus africana in Cameroon. Area, 35.5,
357–370.
Pedersen, Å. Ø., Nyhuus, S., Blindheim, T., & Krog, O. M. W. (2004).
Implementation of A Gis-Based Management Tool for Conservation of
Biodiversity Within the Municipality of Oslo, Norway. Landscape and
Urban Planning, 68(4), 429–438. Http://Doi.Org/10.1016/S0169-
2046(03)00148-8
Phillips, S. J., & Dudı, M. (2008). Modeling of Species Distributions With Maxent :
New Extensions and a Comprehensive Evaluation, (December 2007), 161–
175. Http://Doi.Org/10.1111/J.2007.0906-7590.05203.X

84
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum Entropy
Modeling of Species Geographic Distributions. Ecological Modelling, 190,
231–259. Http://Doi.Org/10.1016/J.Ecolmodel.2005.03.026
Pielou, E. C. (1966). Species diversity and pattern diversity in the study of ecological
succession. Journal of Theoretical Biology 10 370–383
Poorter, L., Hawthorne, W., Bongers, F., & Sheil, D. (2008). Maximum size
distributions in tropical forest communities : relationships with rainfall and
disturbance. Journal of Ecology, 96, 495–504. http://doi.org/10.1111/j.1365-
2745.2007.0
Salem, B. B. (2003). Application of GIS to Biodiversity Monitoring. Journal of Arid
Environments, 54, 91–114. Http://Doi.Org/10.1006/Jare.2001.0887
Schaab, G., Khayota, B., Eilu, G., Wägele, W. (2010). The BIOTA East Africa Atlas
– Rainforest Change over Time. Karlsruhe University of Applied Sciences,
Karlsruhe.
Shannon, C. F., & Weiner, W. (1948). The Mathematical Theory of Communication
(pp. 150). Urbana, IL: University of Il- linois Press.
Shii, J. I., & Ashitani, I. W. (2007). Habitat Analyses of Six Threatened Plant
Species in a Moist Tall Grassland Based on Hyperspectral-Remotely Sensed
Data. Global Environmental Research 11: 161–169.
Simons AJ, Dawson IK, Duguma B, Tchoundjeu Z (1998). Passing problems:
prostate and Prunus. Herbalgram 43: 49-53.
Stewart, K. M. (2003). The African Cherry (Prunus africana): Can Lessons Be
Learned From An Over-Exploited Medicinal Tree? Journal of
Ethnopharmacology, 89, 3–13. Http://Doi.Org/10.1016/J.Jep.2003.08.002
Stirling, G., & Wilsey, B. (2001). Empirical Relationships between Species Richness
, Evenness , and Proportional Diversity. The American Naturalist, 158(3),
286–299.

85
Sunderland, T. C. H., & Tako, C. (1999). The Exploitation of Prunus africana on The
Island Of Bioko , Equatorial Guinea. A report for WWF Germany and the
IUCN/SSC Medicinal Plant Specialist Group, (June).
Tchoundjeu, Z., Avana, M. L., Leakey, R. R. B., Simons, A. J., Asaah, E., Duguma,
B., & Bell, J. M. (2002). Vegetative Propagation of Prunus africana : Effects
of Rooting Medium, Auxin Concentrations and Leaf Area. Agroforestry
Systems, 54, 183–192.
Therriault, T. W., & Kolasa, J. (1999). Physical determinants of richness , diversity ,
evenness and abundance in natural aquatic microcosms. Hydrobiologia, 412,
123–130.
Tsingalia, M. H. (1989). Variation In Seedling Predation Herbivory in Prunus
africana In Kakamega Forest Kenya. African Journal of Ecology, 27, 207–
217.
Vinceti, B., Loo, J., Gaisberger, H., Zonneveld, M. J. Van, Schueler, S., Konrad, H.,
Geburek, T. (2013). Conservation Priorities for Prunus africana Defined
With the Aid of Spatial Analysis of Genetic Data and Climatic Variables.
Plos One, 8(3). Http://Doi.Org/10.1371/Journal.Pone.0059987
Weru, S. M. (2012). Distribution , Utilization and Management of Prunus africana
(Hook . F) in Gichugu Division , Kirinyaga District , Central Kenya. Msc.
Thesis, Kenyatta University, Kenya.
Whitlock, C. Michael and Schluter Dolph (2009). The Analysi of Biological Data.
Roberts and Company Publishers, Greenwood Village, Colorado
Wiersum, K. F. (2006). Cultivation of Medicinal Plants as A Tool for Biodiversity
Conservation and Poverty Alleviation in the Amatola Region, South Africa.
Medicinal and Aromatic Plants, Netherlands, Chapter 3, 43–57.
Willott, S. J. (2001). Species accumulation curves and the measure of sampling
effort. Journal of Applied Ecology, 38(2), 484–486.
http://doi.org/10.1046/j.1365-2664.2001.00589.x

86
APPENDICES
APPENDIX 1: Plant checklist of South Nandi (SN) and North Nandi (NN) forest
SN
No.
Forest
block
Family Species Life form
1 SN Acanthaceae Acanthus eminens C.B.Clarke Shrub
2 S Acanthaceae Barleria ventricosa Nees Herb
3 SN Acanthaceae Brillantasia sp Herb
4 S Acanthaceae Dicliptera laxata C.B.Clarke Herb
5 SN Acanthaceae Hypoestes forskahlii (Vahl) R.Br. Herb
6 S Acanthaceae Hypoestes sp Herb
7 S Acanthaceae Justicia flava Vahl Herb
8 SN Acanthaceae justicia sp1 Herb
9 SN Acanthaceae Mimulopsis arborescens C.B.Clarke Shrub
10 SN Acanthaceae Mimulopsis solmsii Schweinf. Shrub
11 SN Acanthaceae Thunbergia alata Sims Herb
12 S Adiantaceae Coniogramme africana Hieron Herb
13 N Adiantaceae Pellaea sp Climber
14 S Alangiaceae Alangium chinense (Lour.) Harms Tree
15 SN Amaranthaceae Achyranthes aspera L. Herb
16 S Amaranthaceae Cyathula officinalis K. C. Kuan Climber
17 S Amaranthaceae Cyathula uncinulata (Schrad.) Schinz Climber
18 SN Amaranthaceae Sericostachys scandens Gilg & Lopr. Climber
19 N Amaryllidaceae Scadoxus multiflorus (Martyn) Raf. Herb
20 N Anacardiaceae Rhus natalensis Krauss Tree
21 SN Apiaceae Peusedanum elgonense H.Wolff Herb
22 SN Apiaceae Sanicula elata D.Don Herb
23 S Apiaceae Sanicula sp Herb
24 SN Apocynaceae Baissea multiflora A.DC. Climber
25 N Apocynaceae Carrisa edulis (forssk) vahl Shrub
26 SN Apocynaceae Ceropegia meyeri-johannis Engl. Climber
27 S Apocynaceae Cycamone sp Climber
28 SN Apocynaceae Landolphia buchananii (Hall.f.) Stapf. Climber
29 S Apocynaceae Saba comorensis (Bojer) Pichon Climber
30 SN Apocynaceae Senecio syringifolia O. Hoffm. Climber
31 SN Apocynaceae Tabernaemontana stapfiana Britten Tree
32 SN Apocynaceae Tabernaemontana stapfiana Britten Tree
33 SN Apocynaceae Thylophora silvatica Decne. Herb
34 SN Araceae Culcasia falcifolia Engl. Climber
35 SN Araliaceae Polyscias fulva (Hiern) Harms Tree
36 SN Araliaceae Schefflera volkensii (Engl.) Harms Tree
37 N Asclepidiaceae Gomphocarpus stenophyllus Oliv. Shrub
38 S Asparagaceae Asparagus africana Lam Climber
39 SN Asparagaceae Asparagus sp Climber
40 SN Asparagaceae Chlorophytum silvaticum Dammer (C.
Bakeri Poelln)
Herb

87
41 N Aspleniaceae Asplenium bugoiense Hieron. Herb
42 N Aspleniaceae Asplenium ceii Pic. Serm. Herb
43 SN Aspleniaceae Asplenium aethiopicum (Burm.f.)
Becherer
Herb
44 S Aspleniaceae Asplenium angolense Bak. Herb
45 S Aspleniaceae Asplenium blastophorum Hieron. Herb
46 S Aspleniaceae Asplenium bugoiense Hieron. Herb
47 N Aspleniaceae Asplenium ceii Pic. Serm. Herb
48 S Aspleniaceae Asplenium eliottii C.H.Wright Herb
49 SN Aspleniaceae Asplenium erectum Willd. Herb
50 S Aspleniaceae Asplenium gemmifera Schrad. Herb
51 N Aspleniaceae Asplenium mossambiscensii (Oliv.) Wild Herb
52 S Aspleniaceae Asplenium protensum Schrad. Herb
53 SN Aspleniaceae Asplenium sandersonii Hook. Herb
54 N Aspleniaceae Asplenium sp Herb
55 S Asteraceae Adenostemma caffrum DC. Herb
56 S Asteraceae Ageratum conyzoides L. Herb
57 SN Asteraceae Circium buchwaldii O. Hoffm. Herb
58 N Asteraceae Conyza newii Oliv. & Hiern Herb
59 S Asteraceae Crassocephalum montuosum (S.Moore)
Milne-Redh.
Herb
60 S Asteraceae Erigeron sp Herb
61 S Asteraceae Helicrysum sp Herb
62 S Asteraceae Melanthera scandens (Schumach. &
Thonn.) Roberty
Herb
63 SN Asteraceae Microglossa pyrifolia (Lam.) Kuntze Herb
64 S Asteraceae Mikania chenopodiifolia Willd. Climber
65 S Asteraceae Solanacio manii (Hook.f.) C. Jeffrey Shrub
66 SN Asteraceae Vernonia auriculifera Hiern Shrub
67 S Asteraceae Vernonia biafrae Oliv. & Hiern Shrub
68 S Asteraceae Vernonia brachycalyx O.Hoffm. Shrub
69 S Asteraceae Vernonia hymenolepis Hochst. Ex A.
Rich.
Shrub
70 SN Asteraceae Vernonia sp Shrub
71 S Balsaminaceae Impatiens hochstetteri Warb. Herb
72 SN Balsaminaceae Impatiens sp Herb
73 S Basellaceae Basella alba L. Climber
74 S Bignoniaceae Kigelia africana (Lam.) Benth. Tree
75 S Bignoniaceae Markhamia lutea (Benth.) K.Schum. Tree
76 S Boraginaceae Cynoglossum coeruleum A.DC. Herb
77 SN Boraginaceae Ehretia cymosa Thonn. Tree
78 SN Cactaceae Rhipsalis baccifera (J. Mill.) Stearn Herb
79 SN Caesalpiniaceae Caesalpinia decapetala (Roth) Alston Shrub
80 S Caesalpiniaceae Pterolobium stellatum (Forssk.) Brenan Shrub
81 N Caesalpiniaceae Senna semptemtrionalis (Viv.) H. S. Shrub
82 SN Capparaceae Ritchiea albersii Gilg Shrub
83 SN Celestraceae Hippocratea africana (Willd.) Loes. Climber

88
84 S Celestraceae Hippocratea goetzei Loes. Climber
85 SN Celestraceae Maytenus heterophylla (Hckl. & Zeyl.)
Robson
Shrub
86 S Celestraceae Maytenus senegalensis (Lam.) Exell Shrub
87 N Celestraceae Maytenus sp Shrub
88 N Celestraceae Mytenus heterophylla (Eckl. and Zeyh.)
Robson
Tree
89 SN Celestraceae Salacio cerasifera Oliv. Climber
90 SN Colchicaceae Gloriosa superba L. Herb
91 SN Combretaceae Combretum Paniculatum Vent. Shrub
92 S Commelinaceae Commelina africana L. Herb
93 SN Commelinaceae Commelina sp Herb
94 S Convolvulaceae Ipomea tenuirostris Choisy Climber
95 SN Convolvulaceae Ipomoea wightii (Wall.) Choisy Climber
96 SN Crassulaceae Kalancoe sp Herb
97 N Cucurbitaceae Lagenaria abyssinica (Hook.f.) C.
Jeffrey
Climber
98 S Cucurbitaceae Momordica biovinii Baill. Climber
99 S Cucurbitaceae Momordica friesiorum (Harms)
C.jeffrey
Climber
100 SN Cucurbitaceae Momordica sp1 Climber
101 S Cucurbitaceae Momordica foetida Schumach. Climber
102 SN Cucurbitaceae Oreocyce africana Hook.f. Climber
103 S Cyatheaceae Cyathea manniania Hook. Tree
104 S Dennstaedtiaceae Blotiella sp Herb
105 SN Dioscoreaceae Dioscorea adoratisima Pax Climber
106 S Dracaenaceae Dracaena afromontana Mildbr Tree
107 SN Dracaenaceae Dracaena laxisimma Engl. Herb
108 SN Dracaenaceae Dracaena steudneri Engl. Tree
109 S Dryopteridaceae Didymochlaena truncatula (Sw.) J.Sm. Herb
110 S Dryopteridaceae Tectaria gemmifera (Fee) Alston Herb
111 SN Ebenaceae Diospyros abyssinica (Hiern) F. White Tree
112 S Euphorbiaceae Acalypha ornata Hochst. Ex A. Rich. Shrub
113 S Euphorbiaceae Alchornea hirtella Benth. Shrub
114 SN Euphorbiaceae Bridelia micrantha (Hochst.) Baill. Tree
115 SN Euphorbiaceae Croton macrostachyus Del. Tree
116 SN Euphorbiaceae Croton megalocarpus Hurch. Tree
117 S Euphorbiaceae Drypetes gerrardii Hurch. Tree
118 SN Euphorbiaceae Erythrococca bongensis Pax Shrub
119 SN Euphorbiaceae Erythrococca fischeri Pax Shrub
120 S Euphorbiaceae Erythrococca sp Shrub
121 S Euphorbiaceae Erythrococca trichogyne (Müll.Arg.)
Prain
Shrub
122 SN Euphorbiaceae Macaranga kilimandscharica Pax Tree
123 SN Euphorbiaceae Neoboutonia macrocalyx Pax Tree
124 S Euphorbiaceae Phyllanthus fischeri Pax Shrub
125 SN Euphorbiaceae Tragia brevipes Pax Climber
126 SN Fabaceae Dalbergia lactea Vatke Shrub

89
127 SN Fabaceae Desmodium rapandum (Vahl) DC. Herb
128 SN Flacourtiaceae Casearia battiscombei R.E. Fries Tree
129 S Flacourtiaceae Dovyalis abyssinica (A.Rich.) Warb Shrub
130 SN Flacourtiaceae Dovyalis macrocalyx (Oliv.) Warb. Shrub
131 SN Flacourtiaceae Flacourtia indica (Burm.f.) Merrill Tree
132 SN Flacourtiaceae Oncoba spinosa Forssk. Shrub
133 S Flacourtiaceae Trimeria grandifolia (Hochst.) Warb. Herb
134 S Labiataceae Plecranthus longipes Bak. Herb
135 SN Lamiaceae leucas bracteosa Gürke Herb
136 N Lamiaceae Leucas calostachys Oliv. Herb
137 SN Lamiaceae Leucas masaiensis Oliv Herb
138 N Lamiaceae Ocimum lamiifolium Hochst. ex Benth. Shrub
139 SN Lamiaceae ocimum sp Shrub
140 S Lamiaceae Plecranthus silvestris Gürke Shrub
141 S Lobeliaceae Lobellia gibberoa Hemsl. Herb
142 S Lobeliaceae Lobellia gibberoa Hemsl. Herb
143 N Lobeliaceae Lobellia gibberoa Hemsl. Herb
144 SN Loganiaceae Nuxia congesta R.Br. ex Fresen. Shrub
145 S Loranthaceae Englerina woodfordioides (Schweinf.)
Balle
Herb
146 S Loranthaceae Phragmanthera usuiensis (Oliv.) Balle Herb
147 SN Malvaceae Dombeya burgessiae Gerrard ex Harv. Shrub
148 N Malvaceae Dombeya sp Shrub
149 SN Malvaceae Dombeya torrida (J.F. Gmel.) P. Bamps Tree
150 S Malvaceae Hibiscus calyphyllus Cav. Shrub
151 SN Malvaceae Pavonia urens Cav. Shrub
152 N Malvaceae Sida sp Shrub
153 S Malvaceae Triumfetta rhomboidea Jacq. Shrub
154 N Melastomataceae Dissotis speciosa Taub. Shrub
155 SN Meliaceae Ekebergia capensis Sparrm. Tree
156 SN Meliaceae Lepidotrichilia volkensii (Gürke) Leroy Tree
157 SN Meliaceae Trichilia volkensii Gürke Shrub
158 SN Meliaceae Turraea holstii Gürke Tree
159 SN Melianthaceae Bersama abyssinica Fres. Tree
160 SN Menispermaceae Cissampelos pareira L. Herb
161 SN Menispermaceae Stephania abyssinica (Dillon & A. Rich.)
Walp.
Climber
162 SN Menispermaceae Tiliacora funifera (Miers) Oliv. Climber
163 S Mimosaceae Acacia bravespica Harms Shrub
164 N Mimosaceae Acacia nilotica (L.) Del. Tree
165 SN Mimosaceae Albizia gummifera (JF Gmel.) C.A. Sm. Tree
166 S Monimiaceae Xymalos monospora (Harv.) Warb. Tree
167 N Moraceae Dorstenia brownii Rendle Shrub
168 S Moraceae Ficus sur Forssk. Tree
169 N Moraceae Ficus thonningii Bl. Tree
170 SN Moraceae Trilepisium madagascariense DC. Tree
171 S Musaceae Musa acuminata Colla Herb

90
172 N Myrisinaceae Rapanea melanophloeos (L.) Mez. Tree
173 SN Myritaceae Syzygium guineense (Willd.) DC. Tree
174 SN Myrsinaceae Maesa lanceolata Forssk. Tree
175 S Myrtaceae Psidium guajava L. Tree
176 N Myrtaceae Syzygium guineense (Willd.) DC. Tree
177 SN Nyctasimaceae Pissonia aculeata L. Climber
178 SN Ochnaceae Ochna holstii Engl. Tree
179 SN Ochnaceae Ochna insculpta Sleumer Tree
180 SN Olacaceae Strombosia scheffleri Engl. Tree
181 SN Oleaceae Chionanthus mildbraedii (Gilg &
Schellenb.) Stearn
Tree
182 SN Oleaceae Jasminum abbysinicum Hochst. Climber
183 SN Oleaceae Jasminum sp Climber
184 SN Oleaceae Olea capensis L. Tree
185 N Oliniaceae Olinia rochetiana A. Juss. Tree
186 S Onagraceae Ludwigia stolonifera (Guill and Perr.)
raven
Herb
187 S Orchidaceae Aerangis sp Herb
188 S Orchidaceae Erygoites sp Herb
189 SN Orchidaceae Eulophia angolensis (Lindley) Reichb.f. Herb
190 S Orchidaceae Nervilia bicarinata (Blume) Schltr. Herb
191 S Oxalidaceae Oxalis sp Herb
192 S Papillionaceae Amphicarpa africana (Hook.f.) Harms Herb
193 SN Papillionaceae Crotolaria axillaris Ait. Shrub
194 N Papillionaceae Kotschya africana Endl. Shrub
195 SN Passifloraceae Adenia gummifera (Harv.) Harms Climber
196 S Passifloraceae Passiflora foetida L. Climber
197 S Periplocaceae Mondia whytei L. (Hook. F) Climber
198 S Phytollacaceae Phytolacca dodecandra L’ Hér. Shrub
199 S Piperaceae Peperomia abyssinica Miq. Herb
200 S Piperaceae Peperomia tetraphylla (Forst.) Hook.
and Arn.
Herb
201 S Piperaceae Periploca fernandopoiana C. DC. Herb
202 SN Piperaceae Piper capense L.f. Shrub
203 SN Plantaginaceae Plantago sp L. Herb
204 S Poaceae Canicum sp Herb
205 SN Poaceae Oplismenus hirtellus (L.) P. Beauv Herb
206 S Poaceae Penisetum sp Herb
207 S Poaceae Setaria poiretiana Herb
208 S Poaceae Streblochaeta longiarista (A.Rich.) Herb
209 N Podocarpaceae Podocarpus sp Tree
210 S Polypodiaceae Drynaria volkensii Hieron. Herb
211 N Polypodiaceae Lepisorus excavatus (Willd.) Moore Herb
212 SN Polypodiaceae Loxogramme abyssinica (Bak.)
M.G.Price
Herb
213 S Potamogetonaceae Potamogeton sp L. Herb
214 SN Pteridaceae Doryopteris kirkii (Hook.) Alston Herb

91
215 S Pteridaceae Pteris catoptera Kunze Herb
216 N Pteridaceae Pteris cretica L. Herb
217 S Pteridaceae Pteris dentata Forssk. Herb
218 S Pteridaceae Pteris pteridioides (Hook.) F. Ballard Herb
219 SN Ranunculaceae Clematis simensis Fresen Herb
220 S Ranunculaceae Ranunculus multifidus Forssk. Herb
221 SN Ranunculaceae Thalictrum rhynchocarpum Dillon&
A.Rich.
Herb
222 SN Rhamnaceae Gouania longispicata Engl. Climber
223 SN Rhamnaceae Scutia myrtina (Burm.f.) Kurz Climber
224 SN Rhizophoraceae Cassipourea malosana (Baker) Alston. Tree
225 S Rhizophoraceae Cassipourea ruwenzorensis (Engl.)
Alston
Tree
226 S Rosaceae Alchemilla kiwuensis Engl. Herb
227 SN Rosaceae Prunus africana (Hook.f.) Kalkm. Tree
228 SN Rosaceae Rubus apetalus Poir. Shrub
229 SN Rosaceae Rubus niveus Thunb. Shrub
230 SN Rosaceae Rubus scheffleri Engl. Shrub
231 SN Rosaceae Rubus steudneri Scheweinf. Shrub
232 SN Rubiaceae Coffea eugenioides S.Moore Tree
233 S Rubiaceae Galium chloroionanthum K. Schum. Herb
234 SN Rubiaceae Heinsenia diervilloides K. Schum. Tree
235 SN Rubiaceae Keetia gueinzii (Sond.) Bridson Climber
236 SN Rubiaceae Oxyanthus speciosus DC. Tree
237 SN Rubiaceae Pavetta abyssinica Fresen. Shrub
238 S Rubiaceae Pavetta kirkii (Hook.) Alston Shrub
239 S Rubiaceae Pentas sp Herb
240 N Rubiaceae Psychotria mahonii C.Wright Tree
241 SN Rubiaceae Psychotria orophila Petit Tree
242 SN Rubiaceae psychotria sp Tree
243 S Rubiaceae Psyndrax parviflora (Afz.) Bridson Tree
244 S Rubiaceae Rothmannia urcelliformis (Schweinf. Ex
Hiern) Bullock ex Robyns
Tree
245 S Rubiaceae Rubia cordifolia L. Herb
246 SN Rubiaceae Rutidea orientalis Bridson Climber
247 SN Rubiaceae Rytigynia acuminata (K.Schum.) Robyns Shrub
248 S Rubiaceae Rytigynia bugoyensis (K Krause) Verdic. Shrub
249 S Rubiaceae Spermacoca princeae K.Schum.) Verdc. Herb
250 SN Rubiaceae Vangueria apiculata K. Schum. Tree
251 SN Rubiaceae Vangueria madagascariensis Gmel. Tree
252 SN Rubiaceae Vangueria volkensii K. Schum. Tree
253 S Rutaceae Clausena anisata (Willd.) Benth. Shrub
254 SN Rutaceae Fagaropsis angolensis (Engl.) Dale Tree
255 SN Rutaceae Toddalia asiatica (L.) Lam. Climber
256 SN Rutaceae Vepris nobilis (Delile) Mziray Tree
257 S Rutaceae Zanthoxylum gilletti (De Wild.) Waterm. Tree
258 SN Salicaceae Rawsonia lucida Harv. & Sond. Tree

92
259 SN Sapindaceae Allophylus abyssinicus. (Hochst.) Radlk. Tree
260 SN Sapindaceae Allophylus rubifolius (A.Rich.) Engl. Shrub
261 SN Sapindaceae Deinbollia kilimandscharica Taub Tree
262 S sapotaceae Chrysophyllum sp Tree
263 N Sapotaceae Manilkara discolor (Sond.) J. H. Hemsl. Herb
264 SN Sapotaceae Pouteria adolfi-friedericii (Engl.)
Robyns & Gilb.
Tree
265 N Scrophulariaceae Halleria lucida L. Tree
266 SN Smilacaceae Smilax anceps Willd. Climber
267 N Solanaceae Cestrum aurantiacum Lindl. Shrub
268 S Solanaceae Solanum giganteum Jacq. Shrub
269 SN Solanaceae Solanum mauritianum Scop. Shrub
270 N Solanaceae Solanum nigrum L. Shrub
271 SN Solanaceae solanum sp1 Shrub
272 S Solanaceae Solanum terminale Forssk. Shrub
273 S Thelypteridaceae Christella sp A.Lev. Herb
274 SN Ulmaceae Celtis africana Burm.f. Tree
275 SN Ulmaceae Celtis gomphophylla Baker Tree
276 SN Ulmaceae Celtis mildbraedii Engl. Tree
277 S Urticaceae Laportea alatipes Hook.f. Herb
278 SN Urticaceae Pilea johnstonii Oliv. Herb
279 SN Urticaceae Urera hypselodendron (A.Rich.) Wedd. Climber
280 S Verbenaceae Clerodendrum formicarum Gürke Shrub
281 S Verbenaceae Clerodendrum johnstonii Oliv. Shrub
282 SN Verbenaceae Clerodendrum johnstonii Oliv. Shrub
283 S Verbenaceae Clerodendrum silvanum Henriq. Shrub
284 S Verbenaceae Clerodendrum sp Shrub
285 S Verbenaceae Clerodendrum volkensii K. Schum. Shrub
286 S Verbenaceae Lantana camara L. Shrub
287 S Verbenaceae Lantana trifolia L. Shrub
288 S Verbenaceae Premna angolensis Gürke Shrub
289 S Verbenaceae Premna hildebrantii Gürke Shrub
290 SN Vitaceae Cissus humbertii Robyns & Lawalree Climber
291 S Vitaceae Cyphostemma kilimandscharicum (Gilg)
Desc. ex Wild & R.B.Drumm.
Climber
292 SN Vitaceae Cyphostemma cyphopetalum (Fresen.)
et al
Climber

93
APPENDIX 2: Questionnaire for Individual Interviews
INTRODUCTION
Greetings! My name is Hillary Koros a Masters student of Environmental
Biology at Masinde Muliro University of Science and Technology
(MMUST). I am carrying out a study that seeks to find out the social-
economic uses and conservation measures of P. africana (Tenduet) by the
locals and farmers around the North and South Nandi forest. Your
participation and input will contribute greatly to the body of knowledge
which may be used for any subsequent conservation initiative for P.
africana in Nandi forests and Kenya in general. Be guaranteed that the
information collected from this interview will remain confidential and will
be used solely for the purpose of this research. The researcher therefore
requests your faithful participation. Thank you!
Instructions: Mark with an X where appropriate and elaborate where
required.
(A) PHYSICAL LOCATION AND HOUSEHOLD INFORMATION
County Sub- County
Ward Village
Respondent‘s name (optional); Age;
Gender; Male Female
Occupation; Farmer Business Employed - formal Self-
employed
Pastoralist Not employed others (specify)……………………
Number of household; Males Females
Level of Education; None Primary Secondary Tertiary
(B) LOCAL AWARENESS AND SOCIAL ECONOMIC USE OF P.
africana
1. (a) Do you know P. africana (Tenduet) tree? Yes No
(b) If yes, how is their population? Decreasing Increasing
(c) If decreasing, what do you think are the major cause of the decrease in the
forest?
Logging Overgrazing Charcoal burning induced
forest fires
Firewood collection Debarking Uprooting Pruning
Infestation
Invasive species others (specify)
2. What is the size of the land that you own? (In acres)
3. (a) Do you have any P. africana plant in your farm? Yes No
(b) If yes, how many? 1-10 11-20 20-30 31 and above
4. How is P. africana important to you? Cultural Social Economic

94
5. (a) Which part of P. africana do you use? Leaves Bark Stem
Roots Branches
(b) For what purpose do you use these parts? (Specific to plant part in use)
Leaves
Bark
Stem
Roots
Branches
(c) What other uses do the locals use P. africana parts for? (Explain)
6. Where do you/ locals acquire P africana for use? Forest Farmlands
Roadside
Homesteads Along rivers others (specify)
7. How often do you collect P. africana plant parts for use? Daily Weekly
Monthly
Yearly No specific time
8. (a) Are you aware of any P. africana products in the local or international
market? Yes No
(b) If yes, list an
(C) COSERVATION MEASURES OF P. africana BY THE LOCALS
9. What are you/ locals doing to conserve P. africana? Planting P. africana on
farm Protecting them in the forest nothing others (Specify)
10. From where do you/locals acquire P. africana seedlings?
Forest Local tree nurseries Government agencies (e.g. KFS)
(Specify) NGOs (e.g. Nature Kenya) (Specify)
Others (specify)
11. Do you know that P. africana is listed as vulnerable species and its trade is
regulated by CITES? Yes No If Yes how did you know?
12. Give your suggestion on what can be done to conserve P. africana and the
forest in general?
Thank you for your response!

95
APPENDIX 3: Sample population size and distribution in 1km buffer zone of
South Nandi forest
Sub-location
names
Household
population
Sample ratio Half of the sample
ratio
Baraton 10 0 0
Kaptobonge 24 1 0
Kamurguiwa 568 22 11
Township 962 37 19
Kapngetuny 1505 58 29
Meswo 825 32 16
Kamobo 430 17 8
Kapchorwa 645 25 12
Tindidinyo 70 3 1
Kiminda 179 7 3
Chepkumia 705 27 14
Cheboite 303 12 6
Kipsotoi 69 3 1
Mugundoi 353 14 7
Chemomi 164 6 3
Chepkongony 155 6 3
Kenyor 25 1 0
Kirondio 266 10 5
Kapkeben 197 8 4
Kapsoo 41 2 1
Soiyet 47 2 1
Kesogon 174 7 3
Kiptaruswo 198 8 4
Kamimei 74 3 1
Barasendo 118 5 2
Chepketemon 167 6 3
Mosombor 355 14 7
kapwagawat 57 2 1
Chebilat 234 9 5
Keburo 216 8 4
Koyo 125 5 2
Ndurio 130 5 3
Kapsoiyo 94 4 2
Samitui 28 1 1
Sarma 61 2 1
Total 9574 370 185

Thesis_Status_of_Population_Structure_Size_and_Distribution_of_Prunus_africana_in_North_and_South_Nandi_Forests

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