Vegetation Ecology and Land Use/ Land Cover Changes in
Selected Afromontane Forests Along Gibe–Omo Watershed,
Southwest Ethiopia
Abreham Assefa Madebo
ADDIS ABABA UNIVERSITY
June 2017
Addis Ababa, Ethiopia
Vegetation Ecology and Land Use/ Land Cover Changes in
Selected Afromontane Forests Along Gibe–Omo Watershed,
Southwest Ethiopia
By: Abreham Assefa Madebo
Supervisors:
Prof. Sebsebe Demissew (PhD)
Prof. Zerihun Woldu (PhD)
Dr. Feyera Senbeta (PhD)
PhD Dissertation Submitted to the Department of Plant Biology and
Biodiversity Management, Addis Ababa University, in fulfillment of the
requirement for the Degree of Doctor of Philosophy in Biology
(Botanical Science)
ADDIS ABABA UNIVERSITY
June 2017
Addis Ababa, Ethiopia
Vegetation Ecology and Land use/ Land cover Changes in
Selected Afromontane Forests along Gibe–Omo Watershed,
Southwest Ethiopia
Abreham Assefa
Addis Ababa University, 2017
Abstract
This study was aimed to investigate plant diversity and community analyses of the
Afromontane forests at Tiro Boter Becho (TBB) and Chebera Churchura National Park
(CCNP) and analyze LU/LC changes of the two study areas. Systematic sampling
technique was applied to vegetation and environmental data collection. Vascular plants
encountered in each plot were recorded and identified. In addition, soil samples were
taken from each plot and analyzed for pH, organic matter, cation exchange capacity,
total nitrogen, available phosphorus and texture. Land use land cover changes of the
two study sites were analyzed from the period 1984–2015 using geographic
information system and remote sensing techniques. 204 and 144 plant species were
recorded from TBB and CCNP respectively. Five and four plant communities were
identified at the Afromontane forests of TBB and CCNP respectively. The density of
woody species was 1902 stems.ha–1 in TBB and 1562 stems.ha–1 in CCNP. Whereas,
the Basal area of woody species was 72.98 m2ha–1 in TBB and 73.81 m2ha–1 in CCNP.
Four LU/LC types were identified in TBB and five LU/LC types were identified in
CCNP. In the period of 1984–2000, Forest and Agriculture & Settlement showed
increasing trends in TBB. But Woodland and Shrub/Bushland showed decreasing
trends. In the period 2000–2015, Agriculture & Settlement and Shrub/Bushland showed
increasing trends. But Forest and Woodland showed a remarkable loss. In CCNP,
Forest, Grassland and Agriculture & Settlement showed increasing trends in the period
of 1984–2000. But Woodland and Water body showed decreasing trends. In the period
2000–2015, Agriculture & Settlement, Grassland and Water body showed increasing
trends. Whereas Forest and Woodland showed decreasing trends. A decreasing trend
in vegetation and increasing trend in Agriculture and Settlement is an indication of
high demand of land for cultivation and settlement. Integrated watershed management
approach should be in place to manage the entire watershed. Furthermore, effective
enforcement of forest laws/policies, fair involvement of local communities in forest
management, delineation of the forest buffer zone and improve the use of modern
stoves for efficient energy consumption must be carried out at a local level to ensure
the sustainability of natural forest.
Key Words/phrases: Afromontane forest, Chebera Churchura National Park, Land
use/Land cover change, Plant Community and Diversity, and Tiro-BoterBecho
iii
Acknowledgements
I would like to thank my supervisors: Prof Sebsebe Demissew, Prof. Zerihun Woldu
and Dr. Feyera Senbeta for their guidance during this research work. I would also like
to thank all colleagues and friends, who contributed to the success of this work. This
research has been conducted with financial support from thematic research project
“Restoration of upper Awash and Gibe watershed and western escarpment of the
central Rift valley: mechanisms for re-establishment of biodiversity, ecosystem
functions and livelihood” at AAU, and International Foundation for Science (IFS).
Oromiya Forest and Wildlife Enterprise and Chebera Churchura National Park are
acknowledged for their cooperation during data collection. The National Herbarium,
AAU is also acknowledged for provision of facilities during plant identification.
iv
Table of Contents
Contents
Page
List of Tables ............................................................................................................. viii
List of Figures ................................................................................................................x
List of Annexes ........................................................................................................... xii
ACRONYMS............................................................................................................. xiii
CHAPTER ONE ............................................................................................................1
1. Introduction................................................................................................................1
1.1 Background of the Study......................................................................................1
1.2 Statement of the Problem .....................................................................................2
1.3 Objective of the Study..........................................................................................4
1.3.1 General Objective ..........................................................................................4
1.3.2 Specific Objectives ........................................................................................4
1.4 Research Questions ..............................................................................................4
CHAPTER TWO ...........................................................................................................5
2. LITERATURE REVIEW ..........................................................................................5
2.1 Afromontane Forests of Ethiopia .........................................................................5
2.2 Moist Evergreen Afromontane Forest..................................................................8
2.3 Diversity and Composition of Moist Afromontane Forest.................................11
2.4 Importance of the Forest of Ethiopia..................................................................14
2.5 Threats to Afromontane Forests.........................................................................15
2.6 Conservation Status of Forest Resources ...........................................................17
2.7 Vegetation Ecology and Plant Communities .....................................................19
2.8 Influence of Environmental Gradients on Plant Communities ..........................23
2.9 Remote Sensing and Land Use /Land Cover Change ........................................25
v
2.10 Trends of LU/LC Change in Ethiopia and its Drivers .....................................26
CHAPTER THREE .....................................................................................................29
3. MATERIALS AND METHODS.............................................................................29
3.1 Description of Study Areas ................................................................................29
3.1.1 Tiro Boter Becho .........................................................................................29
3.1.2 Chebera Churchura National Park ...............................................................33
3.2 Preliminary Survey.............................................................................................37
3.3 Methods of Data collection ................................................................................37
3.3.1 Vegetation Sampling ...................................................................................37
3.3.2 Environmental Data.....................................................................................38
3.3.3 Land Use Land Cover Data .........................................................................39
3.4 Data Analysis .....................................................................................................40
3.4.1 Plant Diversity analysis ...............................................................................40
3.4.2 Vegetation and Plant Community Structural Analysis................................41
3.4.3 LU/LC Detection and Analysis ...................................................................45
CHAPTER FOUR........................................................................................................50
4. RESULTS ................................................................................................................50
4.1 Plant Diversity and Species Composition of Afromontane forest of
TBB and CCNP .................................................................................................50
4.2 Vegetation Structure...........................................................................................53
4.2.1 Plant Community Structure of the Afromontane forest of TBB
and CCNP ..................................................................................................53
4.2.2 Diversity of Plant Communities ..................................................................68
4.2.3 Plant Population Structure of the Afromontane forest of TBB
and CCNP ..................................................................................................69
vi
4.2.5 Regeneration Status of Montane Forests at TBB and CCNP ......................82
4.3 Land use/Land cover Change .............................................................................83
4.4 Change Detection of LU/LC ..............................................................................88
4.5 Rate of LC/LC Changes .....................................................................................96
4.6 Summary of Results of Key Informant Interviews and Focus Group
Discussions........................................................................................................98
4.7 Causes of LU/LC Changes.................................................................................98
CHAPTER FIVE .......................................................................................................103
5. DISCUSSION ........................................................................................................103
5.1 Floristic Diversity and Composition ................................................................103
5.2 Community Structure .......................................................................................105
5.3 Population Structure.........................................................................................107
5.4 LU/LC Changes at TBB and CCNP.................................................................116
CHAPTER SIX..........................................................................................................121
6. CONCLUSION AND RECOMMENDATIONS ..................................................121
6.1 Conclusion........................................................................................................121
6.2 Recommendations ............................................................................................123
REFERENCES ..........................................................................................................124
ANNEXES.................................................................................................................144
vii
List of Tables
Tables
Page
Table 1. Description of Landsat Images used and their Sources .................................. 39
Table 2. Modified Braun-Blanquet Scale for cover abundance values ........................ 42
Table 3. Description of LU Classes Identified.............................................................. 46
Table 4. Distribution of species according to growth–form/habit of plants at the
Afromontane forest of TBB with their corresponding number species .......... 50
Table 5. Distribution of species according to growth–form/habit of plants at the
Afromontane forest of CCNP with their corresponding number species........ 51
Table 6. List of top five plant families with their number of genera and species
encountered at the Afromontane forest of TBB .............................................. 51
Table 7. List of top five plant families with their number of genera and species
encountered at the Afromontane forest of CCNP ........................................... 52
Table 8. Endemic species and their habit at the Afromontane forests of TBB and
CCNP............................................................................................................... 52
Table 9. Result of permutation test of environmental variables at TBB ...................... 65
Table 10. Result of permutation test of environmental variables at CCNP.................. 66
Table 11. Biplot scores for constraining variables at TBB ........................................... 67
Table 12. Biplot scores for constraining variables at CCNP ........................................ 68
Table 13. Species richness, evenness, and diversity of the five plant communities
of the Afromontane forest of TBB .................................................................. 69
Table 14. Species richness, evenness, and diversity in the three plant
communities of the Afromontane forest of CCNP .......................................... 69
Table 15. Importance Value Index of woody species with DBH ≥2.5 cm at TBB ..... 78
Table 16. Importance Value Index of woody species with DBH ≥2.5 cm at
CCNP............................................................................................................... 79
Table 17. Density, number of species, and ratios of individuals to species by
storey at the Afromontane forest of TBB ........................................................ 81
Table 18. Density, number of species, and ratios of individuals to species by
storey at the Afromontane forest of CCNP ..................................................... 82
Table 19. Classification accuracy for 2015 classified images of TBB. ........................ 87
Table 20. Classification accuracy for 2015 classified images of CCNP ...................... 88
viii
Table 21. LU/LC change at TBB from the year 1984 to 2000 ..................................... 89
Table 22. LU/LC change at TBB from the year 2000 to 2015 ..................................... 90
Table 23. LULC change at TBB from the year 1984 to 2015 ...................................... 91
Table 24. LULC change at CCNP from the year 1984 to 2000.................................... 93
Table 25. LULC change at CCNP from the year 2000 to 2015.................................... 94
Table 26. LULC change at CCNP from the year 1984 to 2015.................................... 95
Table 27. The ratio of tree densities of DBH > 10 cm and DBH > 20 cm at the
Afromontane forests of TBB, CCNP and other selected Afromontane
forests ............................................................................................................ 110
Table 28. Structural characteristics of the Afromontane forests of TBB, CCNP
and other selected Afromontane forests in the country................................. 112
Table 29. Regeneration status of some selected montane forests ............................... 113
Table 30. Phytogeographical Comparison of Afromontane forest of TBB
(altitudinal range of 1682 – 2339 and mean annual rainfall 1431 mm)
with other five similar Afromontane forests in southwest Ethiopia.............. 114
Table 31. Phytogeographical Comparison of Afromontane forest of CCNP with
other five similar Afromontane forests in southwest Ethiopia...................... 114
ix
List of Figures
Figures
Page
Figure 1. Map of Ethiopia, Oromiya Regional State, and the study area (TBB).......... 30
Figure 2. Climadiagram for Boter Becho Station ........................................................ 31
Figure 3. Partial view of Moist Afromontane forest of TBB........................................ 32
Figure 4. Map of Ethiopia, SNNPRS, and the study area (CCNP)............................... 34
Figure 5. Climadiagram for Ameya Station ................................................................. 35
Figure 6. Partial view of Moist Afromontane forest of CCNP (own Photo) ................ 36
Figure 7. Flowchart showing the steps followed during LU/LC evaluation ................ 49
Figure 8. Dendrogram showing clusters of plots obtained from the
Afromontane forest of TBB ........................................................................... 53
Figure 9. Partial view of Podocarpus falcatus dominated Afromontane forest
of TBB ........................................................................................................... 54
Figure 10. Partial view of Pouteria adolfi-friedrici dominated Afromontane
forest of TBB ................................................................................................. 55
Figure 11. Partial view of area where species belongs to community 5 at the
Afromontane forest of TBB exist ................................................................. 58
Figure 12. Dendrogram showing clusters of plots obtained from the
Afromontane forest at CCNP......................................................................... 59
Figure 13. Partial view of Cyathea maniana dominated area at the
Afromontane forest of CCNP ........................................................................ 61
Figure 14. Constrained RDA for the plant communities at the Afromontane
forest of TBB, showing the relationships of environmental variables
correlated with sites ....................................................................................... 63
Figure 15. Constrained RDA for the plant communities at the Afromontane
forest of CCNP showing the relationships of environmental variables
correlated with sites ....................................................................................... 64
Figure 16. Distribution of individuals of woody species across DBH Class at
the Afromontane forest of TBB. .................................................................... 70
Figure 21. Distribution of individuals of woody species across Height Class at
the Afromontane forest of TBB . ................................................................... 71
x
Figure 18. Distribution of individuals of woody species across DBH Class at
the Afromontane forest of CCNP .................................................................. 72
Figure 19. Distribution of individuals of woody species across Height Class at
the Afromontane forest of CCNP .................................................................. 72
Figure 20. Structure of selected woody species with regard to DBH at the
Afromontane forest of TBB ........................................................................... 74
Figure 21. Structure of selected woody species with regard to DBH at the
Afromontane forest of CCNP ........................................................................ 75
Figure 22. Structure of selected woody species with regard to Height at the
Afromontane forest of TBB ........................................................................... 76
Figure 23. Structure of selected woody species with regard to Height at the
Afromontane forest of CCNP ........................................................................ 77
Figure 24. Distribution of Basal area across DBH classes at the Afromontane
forest of TBB ................................................................................................. 80
Figure 25. Distribution of Basal area across DBH classes at the Afromontane
forest of CCNP............................................................................................... 80
Figure 26. LU/LC map of TBB for the year 1984, 2000, and 2015 ............................. 84
Figure 27. LU/LC map of CCNP for the year 1984, 2000, and 2015........................... 86
Figure 28. Annual Rate of Land Use/Land Cover change in TBB from 1984 to
2000, from 2000 to 2015, and from 1984 to 2015 ......................................... 96
Figure 29. Annual Rate of Land Use/Land Cover change in CCNP from 1984
to 2000, from 2000 to 2015, and from 1984 to 2015..................................... 97
Figure 30. Partial view of threat to the Afromontane forest of TBB.......................... 100
Figure 31. Partial view of threat to the Afromontane forest of CCNP ....................... 101
Figure 32. Partial view Nursery site and plantation of Cupresus as a buffer ............. 102
xi
List of Annexes
Annex
Page
Annex 1. List of plant species recorded at the Afromontane forests of TBB
and CCNP .................................................................................................... 144
Annex 2. List of plant families with their number of genera and species
encountered at the afromontane forest of TBB............................................ 154
Annex 3. List of plant families with their number of genera and species
encountered at the afromontane forest of CCNP ......................................... 156
Annex 4. Species indicator values for plant species at the Afromontane forest
of TBB. ........................................................................................................ 158
Annex 5. Species indicator values for plant species at the Afromontane forest
of CCNP....................................................................................................... 160
Annex 6. Density of woody species along DBH-classes at the Afromontane
forest of TBB ............................................................................................... 162
Annex 7. Density of woody species along height-classes at the Afromontane
forest of TBB ............................................................................................... 165
Annex 9. Density of woody species along height-classes at the Afromontane
forest of CCNP............................................................................................. 171
Annex 10. Frequency, Density, Basal Area and Important value indices of
Woody species at the Afromontane forest of TBB ...................................... 174
Annex 11. Frequency, Density, Basal area and Important value indices of
Woody species at the Afromontane forest of CCNP ................................... 177
Annex 12. Seedling and Saplings at the Afromontane forest of TBB ........................ 180
Annex 13. Density of Seedlings and Saplings of the Afromontane forest of
CCNP ........................................................................................................... 182
xii
ACRONYMS
a.s.l.
BA
CCA
CCNP
CEC
CRGE
DBH
DCA
EFAP
FAO
FDRE
GIS
GPS
ha
IBC
IUFRO
IVI
km
LU/LC
NCS
NDVI
NFPAs
NMA
OFWE
OM
PGR
pH
QGIS
ROI
TBB
UNDP
USGS
UTM
WGS
above sea level
Basal Area
Canonical Correspondence Analysis
Chebera Churchura National Park
Cation Exchange Capacity
Climate Resilient Green Economy
Diameter at Breast Height
Redundancy analysis
Ethiopian Forestry Action Program
Food and Agriculture Organization
Federal Democratic Republic of Ethiopia
Geographic Information System
Global Positioning System
Hectare
Institute of Biodiversity Conservation
International Union for Forestry Research Organization
Important Value Index
Kilometer
Land Use/Land Cover
National Conservation Strategy
Normalized Difference Vegetation Index
National Forest Priority Areas
National Meteorological Agency
Oromiya Forest and Wildlife Enterprise
Organic Matter
Plant Genetic Resources
Measure of Hydrogen ion
Quantum Geographic Information System
Region of Interest
Tiro Boter Becho
United Nations Development Programme
United States Geographical Survey
Universal Transverse Mercator
World Geodetic System
xiii
CHAPTER ONE
1. Introduction
1.1 Background of the Study
Ethiopia, a country with a total area of 1.1 million km2 is located in the northeastern
part of Africa. Ethiopia’s topographical diversity encompasses high and rugged
mountains, plateaus, and deep gorges with rivers and rolling plains (PGR, 1995;
Zerihun Woldu, 1999). The altitudes ranges from 110 meter below sea level at the
Danakil depression, in the northeast to 4530 m.a.s.l, to the Simien Mountains in the
north.
Tropical forests are the most diverse ecosystems and are reservoirs of biodiversity
(Fangliang et al., 1996). Ethiopia possesses the fifth largest floral composition in
tropical Africa (Eshetu Yirdaw, 2001). The topographic and altitudinal diversity have
made the country to have diverse ecological conditions, which in turn contributed for
its diverse biological resources with endemic elements (PGR, 1995; Zerihun Woldu,
1999). Hedberg (2009) and Ensermu Kelbessa and Sebsebe Demissew (2014)
indicated that, the current estimate of higher plants is about 6,000 species with 10%
endemism.
Forests are among main resources of the country and having wider range of
biodiversity, and are often vital to livelihood strategies of local communities through
provision of environmental services and socioeconomic benefits. Pearce and Pearce
(2001); Tadesse Woldemariam, (2003); World Bank (2004); and Feyera Senbeta
(2006) stated that, the forests of the country are providing several ecosystem services
1
including regulation of rainwater runoff and drought, control of pests and disease,
purification of air and water, plant pollination, soil formation and maintenance, seed
dispersal and nutrient cycling, maintaining biodiversity, provide ecological and
ethno–botanical uses, climate stabilization (through carbon sequestration), and
regulating extremes of temperature and wind.
As part of the Gibe–Omo watershed, the Afromontane forests of Tiro Boter Becho
state forest and Chebera Churchura National Park play great roles in serving as
sources of water for Gibe and Omo Rivers, flood retention and ground water recharge.
Today, forests worldwide is facing unprecedented pressures (FAO, 2015). World
Bank (2004) also reported that forest ecosystems are being converted to other land
uses; freshwater resources are over utilized affecting the normal flow rates and
recharge; and pasturelands are overused and agricultural soils are being degraded.
Similarly, the natural forests in Ethiopia are under high pressure due to ever
increasing human population despite the services they provide (Kumelachew
Yeshitela, 2008).
Forest inventory and examination of land use/land cover changes are vital tools for
forest management (Maureen and Andrew, 2004). Therefore, this study will bring
information required to design strategies needed for sustainable forest management
(including restoration, reforestation, and combat forest degradation) in the area.
1.2 Statement of the Problem
Rapid increase in global temperatures may cause regional and global changes in
climate that could have significant impacts on human and natural systems. Forests
play both ecological and regulatory roles supportive to overcome the effect of climate
2
change. Several small rivers, which drain into Gibe and Omo Rivers, originate from
mountains covered by the Afromontane forests at TBB and CCNP respectively. These
forests play important regulatory role in hydrological processes of the area. The
Afromontane forests in the area capture and store rainfall and moisture, maintain
water quality, regulate river flow, reduce erosion, and protect against landslides. More
specifically, the Afromontane forests of TBB and CCNP are draining water to Gibe
and Omo rivers where dams are constructed for hydroelectric power generation.
These forests have a great use in reducing soil erosion that induces heavy silt loads
into the dam. In the absence of these forests, Gibe and Omo rivers may gradually
change into intermittent rivers and progressively into dry river beds. In addition, the
role of Afromontane forests at TBB and CCNP in climate change regulations could
not be underestimated since the forests in the country have tremendous roles in
building climate–resilient green economy. The vegetation studies and LU/LC changes
taking place in these Afromontane forests have not been carried out.
One of the vital tools for forest management is forest inventory (Maureen and
Andrew, 2004). According to Kershaw (1973), vegetation studies promote designing
and employment of appropriate conservation and management plan for sustainable
use of resources. Careful analysis of vegetation provides relevant information about
its present situation and ecological status (Goldsmith et al., 1986). It also helps for
monitoring future changes in species composition. Changes in land cover have caused
most pressing environmental issue in recent decades (FAO, 2015). Factors that cause
changes in LULC are essential for predicting future changes or development of
management strategies and policies to ameliorate or prevent further decline of natural
resources. This study aims to investigate the diversity of the Afromontane forests of
TBB and CCNP, and analyzing the LU/LC changes of these area.
3
1.3 Objective of the Study
1.3.1 General Objective
The main objective of this study is to study on floristic, structure, and plant diversity
of the Afromontane forests of Tiro-Boter-Becho (TBB) and Chebera Churchura
National Park (CCNP); and land use/land cover changes in the two study areas.
1.3.2 Specific Objectives
The specific objectives are:
•
to study the plant diversity and composition of the Afromontane forests of
TBB and CCNP
•
to describe vegetation structure of the Afromontane forests of TBB and CCNP
•
to study the land use/land cover changes of the study areas
1.4 Research Questions
In order to realize the aforementioned research objectives, the following research
questions were raised:
•
What are the plant species existing at the Afromontane forests of TBB and
CCNP?
•
What plant communities are identified at the two Afromontane forests?
•
Which environmental factors significantly affect the distribution of plant
communities at the Afromontane forests of TBB and CCNP?
•
What is the regeneration status of the Afromontane forests of TBB and
CCNP?
•
What does the land use/land cover change of the study areas look like?
4
CHAPTER TWO
2. LITERATURE REVIEW
2.1 Afromontane Forests of Ethiopia
Edwards and Ensermu Kelbessa (1999) expressed that Ethiopia is an important
regional center of biodiversity. Studies by EFAP (1994), Demel Teketay (1999),
Zerihun Woldu (1999), and IBC (2005) show that, varied topography, the rift valley,
and the surrounding lowlands have given Ethiopia a wide spectrum of habitats, plant
diversity, and large number of endemics. The Afromontane forests of Ethiopia are
part of Eastern Afromontane Biodiversity Hotspots, one of the 34 regions globally
important for biodiversity conservation (Conservation International, 2009). Most
Afromontane communities are found above 2000 m, but they can occur as low as
1200m above sea level in some places (White, 1983). The Ethiopian highlands (land
areas above 1500 m.a.s.l. with associated valleys) comprise over 50% of the Eastern
Afromontane Hotspot and over 40% of the Horn of Africa Hotspot (Tamirat Bekele,
1994; Yalden, 1983) are however, among the most threatened Hotspot areas in the
world. Afromontane forests of Ethiopian highlands contain the only forest ecosystem
with wild Coffea arabica populations worldwide. Despite its importance, the
Afromontane forests of Ethiopia are being cleared and degraded at an alarming rate
due to several social, economic, and political factors (Feyerea Senbeta and Manfred,
2006).
Many species common in Afromontane forests such as trees of the genera Podocarpus
and Juniperus have economic importance (Tamirat Bekele, 1993). Historical records
show that 35–40% of the total land area of the country might have once been covered
5
with natural forest (von Breitenbach, 1961, 1962; and EFAP, 1994). However, this
forest resource was later reduced to 4.8 % in 1973 (Reusing, 1998), 4.4% by 1960
(von Breitenbach, 1962), and 4 % in 2000 (Earth Trends (2003). Although a forest
resource assessment estimated Ethiopia’s forest cover at 11% (FAO, 2010), the
Ethiopian government claims to reach 15 % due to the various multifaceted natural
resource conservation, reforestation and other related activities carried out during the
past decades (Sara Shibeshi, 2015).
Destruction of the remnant high forests continues at an estimated rate of 150,000 200,000 ha per year (EFAP, 1994; Reusing, 1998). As evidence, in the highlands of
northern Ethiopia, remnants of the original Afromontane forest vegetation are largely
restricted to church yards and other sacred groves in a matrix of cropland and
semiarid degraded savanna (Aerts, 2006). This is because highlands of Ethiopia, in
contrast to most mountain systems outside Africa, are very suitable for human
inhabitation/settlement. This population pressure on the highlands accompanied by
sedentary agriculture, extensive cattle herding activities and socio-political instability,
has resulted in heavy deforestation, forest fragmentation, and loss of biodiversity and
impoverishment of ecosystems in general (Eshetu Yirdaw, 2002).
Many scholars have classified the Ethiopian vegetation into various categories which
can even split into smaller units (Logan,1946; Pichi-Sermolli,1957; von Breitenbach,
1963; White,1983; Friis, 1986; Friis,1992; Sebsebe Demissew et al., 1996; Zerihun
Woldu, 1999; and Friis and Sebsebe Demissew, 2001). Pichi-Sermolli (1957)
recognized 24 vegetation units for the whole country and von Breitenbach (1963)
proposed seven broadly defined units, which were further subdivided into smaller
associations. Gilbert (1986) argued that some vegetation types described by
6
Pichi- Sermolli hardly differed from each other, while others have been
oversimplified. Friis et al. (1982) pointed out that von Breitenbach's associations lack
essential information on localities and distribution. According to White (1983)
vegetation classification, the country has four of the regional centres of endemism:
Sudanian Regional Centre, Somalia-Maasai Regional Centre, Afromontane Regional
Centre and Afroalpine Regional Centre. These are very broad categorizations of the
vegetation of Ethiopia with ‘centers of endemism’ as the main emphasis.
Moreover, Sebsebe Demissew et al. (1996) broadly categorized the vegetation of
Ethiopia into nine major groups. These include Afroalpine and Sub-Afroalpine
vegetation, dry evergreen montane forest, moist evergreen montane forest, wetlands,
evergreen scrub, Combretum-Terminalia woodland, Acacia-Commiphora woodland,
lowland dry forest, and lowland semi-desert and desert areas. Similarly, Zerihun
Woldu (1999) also categorized the Ethiopian vegetation into nine broad vegetation
types. These are Afroalpine and Sub–Afroalpine, dry evergreen montane forest and
grassland complex, moist evergreen montane forest, Acacia – Commiphora woodland,
Combretum – Terminalia woodland, lowland semi–evergreen forest, desert and semi–
desert scrubland, and wetlands and riparian vegetation. These attempts have all
contributed considerably towards the understanding of the vegetation types of
Ethiopia.
Very recently, the Atlas of the Potential Vegetation Map of Ethiopia (Friis et al.,
2011) shows the distribution of twelve potential vegetation types that was mapped
using environmental parameters and GIS-methodology at the scale of 1:2,000,000.
These vegetation types have been described and further divided into a number of
subtypes, including desert, semi-desert, deciduous bush-lands and woodlands,
7
evergreen Afromontane forests and grasslands, transitional rainforest, Ericaceous and
Afroalpine vegetations, riverine vegetation, various types of freshwater lake- and
swamp-vegetation, as well as salt-lakes and salt-pans. The vegetation types classified
here are based on information from previous literature and field experience of the
authors as they have life-long work experience on Ethiopian vegetation. An analysis
of the information for about 1300 species of woody plants in the Flora of Ethiopia and
Eritrea have been made by the authors. Accordingly, of the vegetation types and
subtypes described in the text, fifteen units that have large enough extension are
mapped and defined in relation to topographic features such as altitude, rivers and
lakes and rainfall.
Among the general vegetation studies mentioned above, some are giving a particular
emphasis in forests and forest types. Both Logan (1946) and Pichi-Sermolli (1957)
provided a general outline of Ethiopian forest vegetation, comprising three distinct
forest types: Montane Dry Evergreen Forest, Montane Moist Evergreen Forest and
Bamboo Forest. Von Breitenbach (1963) recognized more forest types according to
their dominant species and grouped them into two very broad categories such as
Lower and Upper-Highland Forests. The most important surveys of Ethiopian forests
are those by Friis et al. (1982) and Friis (1992).
2.2 Moist Evergreen Afromontane Forest
The Afromontane forests on the Ethiopian highlands can be broadly divided into dry
montane forests and moist montane forests. The dry montane forests are dominated by
hard leaved evergreens, such as Juniperus procera, Podocarpus falcatus, and Olea
europaea subsp. cuspidata. While the moist montane forests are characterized by
large broad leaved and soft leaved species like Aningeria adolfi-friederici, Olea
8
welwitschii, Olea hochsteterii, and Croton macrostachyus (Sebsebe Demissew et al.,
1996; Tamirat Bekele, 1994). Arundinaria alpina stands are also found at humid
highland elevation areas.
Moist Evergreen afromontane forest (MAF) is the major remnant forest in the
country. Different authors have given different names for this forest vegetation;
(Afro) montane rainforest (Friis, 1992), moist montane forest or moist montane
evergreen forest (Friis, 1986; Sebsebe Demissew et al., 1996; Zerihun Woldu, 1999).
According to Sebsebe Demissew and Friis (2009), this forest type was considered to
consist of two subtypes: Subtype I (Afromontane Rainforest, where wild coffee are
found between 1500 and 2600 m a.s.l) and Subtype II (Transitional Rainforest
between 450 and 1500 m a.s.l bordering the Combretum-Terminalia woodlands on the
western escarpments of the Ethiopian highlands in the floristic regions of IL and KF).
Recent quantitative assessments demonstrate the presence of different regional moist
forest assemblages and question whether the general altitudinal cut-off level at 1500
m a.s.l. is the most decisive factor for floristic variations (Tadesse Woldemariam,
2003; Feyera Senbeta, 2006; Schmitt et al., 2010). The moist evergreen Afromontane
forests remaining are mainly found at altitudes between 500 and 3000 m in the
southwest and southeast of the country and are characterized by steep slopes and
rugged topography (Friis et al., 2011).
The Ethiopian Afromontane forests are belong to the least explored and least
protected eco-regions in Africa (Tadesse Woldemariam et al., 2008). This is
surprising given the fact that these areas in Ethiopia have been recognized as global
biodiversity conservation priority areas and centers for plant diversity (Barthlott et al.,
9
1999) but also for other groups of organisms such as Endemic Bird Areas (ICBP,
1992).
According to vegetation classification of White (1983), Moist Evergreen
Afromontane forest was named as Afromontane Rainforest which is very similar in
structure and physiognomy to certain types of Guineo-Congolian lowland rainforest.
At the species level, however, it is almost completely different but many of its species
are closely related to Guineo-Congolian species or have their closest relatives
elsewhere in the lowland tropics (Chapman & White, 1970). In Ethiopia, the montane
moist forest ecosystem comprises high forests of the country mainly the southwest
forests, which are the wettest, and also the humid forest on the southeastern plateau
known as the Harenna forest. The highlands in the southwest of the country form the
upper catchments of several important rivers such as the Baro and Akobo (tributaries
of the Nile) and the Omo iver. The forests in this region do not only play a major role
in water regulation of these rivers but are also of significance for conserving
biodiversity. They are floristically related to other Afromontane forests, especially in
eastern Africa, and harbour unique plants (Friis et al., 1982).
Floristically, MAF is a moderately diverse vegetation type, with a low number of
unique woody species, subspecies, and varieties. The highest number of woody
species, subspecies and varieties are shared with dry evergreen Afromontane forest
and grassland complex (DAF), Riverine vegetation, and transitional rainforest (Friis et
al., 2011). Several authors (Mooney, 1963; Chaffey, 1979; Mesfin Tadesse, 1986;
Friis, 1986 and 1992; Lisanework Nigatu and Mesfin Tadesse, 1989; Zerihun Woldu
et al., 1989; Kumlachew Yeshitila, 1997; and Abreham Assefa et al., 2014) studied
the composition and population structure of this type of forest vegetation and
10
described them on floristic basis. According to Friis (1992), it occurs in the
southwestern part of the Ethiopian highlands at altitudes between 1500 and 2600 m, at
annual rainfall between 700 and 1500 mm. However, as to White (1983), the mean
annual rainfall lies mostly between 1250 and 2500 mm, but is sometimes higher.
There is usually a dry season lasting from one to five months, but dry season mists are
frequent. This may explain the fact that upland rainforest is often much less deciduous
than lowland semi-evergreen rainforest experiencing a similar rainfall. Apart from
secondary species, only a few of the larger tree species such as Pouteria adolfifriederici and Entandrophragma excelsum lose their leaves and then only for few
days.
2.3 Diversity and Composition of Moist Afromontane Forest
This forest is home to various endemic and indigenous plants though poor in
endemicity compared to DAF. Low diversity in endemic plant species, however, is a
common feature of all montane moist forests of Ethiopia (Friis and Sebsebe
Demissew, 2001) rather they are important wild gene pools of few important plants
for food and agriculture as well some of them are Coffea arabica, Piper capense,
Aframomum corrorima. For instance, Yayu forest is poor in the number of plant
species endemic to Ethiopia. Only three endemic species namely: M. ferruginea,
Phyllanthus limuensis, and Vepris dainelli were recorded in the area (Tadesse
Woldemariam et al., 2008). Moreover, Ensermu Kelbessa and Teshome Soromessa
(2008) listed a total of 243 plant species belonging to 85 families from the Bonga
forest. Of these, 66 families were angiosperms, 2 were gymnosperms, and 17
monilophytes (ferns). The region is recognized as biodiversity hotspot of global
interest with Coffea arabica as flagship species (Tadesse Woldemariam et al., 2000).
11
It is reputed as the area of origin for this species, and there is a long history of forest
coffee providing an environmental income to local people (Schmitt, 2006; Wiersum,
2010).
The structural diversity in the forest also allows both animals and plants to occupy
different ecological niche. The high forests are not only diverse in their composition
but hold also important genetic components and populations of wild coffee and
several associated economic plant species. Previous study of the montane moist
forests in southwest by Kumlachew Yeshitila (1997) had shown that more than 160
vascular plant species were recorded. This forest vegetation was stratified into four
different layers namely; upper canopy, middle canopy, shrub layer and the ground
layer. The upper canopy is occupied the spectacular emergent trees of Pouteria adolfifriederici (Friis, 1992). Other characteristic species in the canopy include Olea
capensis subsp. welweitschii and subsp hochestetteri, Prunus africana, Albizia
schimperiana, Milletia ferruginea and Celtis africana. Moreover, species such as
Polyscias fulva, Schefflera volkensii, Schefflera abyssinica, Bersama abyssinica,
Mimusops kummel are also associated to it. Middle canopy species include Croton
macrostachyus, Cordia africana, Dracaena steudneri, Syzygium guineense subsp.
afromontanum, Sapium ellipticum, Ilex mitis, Erythrina brucei, and Rothmannia
urcelliformis. The shrub layer consists of species of Coffee arabica, Galiniera
saxifraga, Teclea nobilis, Ocotea kenyensis, Clausena anisata, Maesa lanceolata and
Maytenus spp.
The Woody climbers are Urera hypselodendron, Landolphia owarensis, Embelia
schimperi, and Jasminum spp. The ground cover is comparatively lush, and rich in
ferns, grasses and herbaceous plants such as Acanthus, Justicia, Peperomia,
12
Galinsoga, Impatiens, and Urtica. Lianas are present and about several species have
been recorded and Arundinaria alpina is not uncommon at higher altitudes in this area
(Friis, 1992). The montane moist forest ecosystem is distinguished also by supporting
luxuriant growing epiphytes Canarina, Orchids, Scadoxus, and fern plants such as
Platycerium and Drynaria. Mosses also occur in the wettest portion of forests
associated to major branches and barks of trees. Podocarpus is never a single
dominant and becomes gradually more infrequent towards the southwest in Kaffa and
Ilubabor as the rainfall increases, while the Pouteria adolfi-friederici becomes more
prominent in the same direction. The drier parts of these forests are floristically very
similar to those in the humid parts of the central highlands. The more or less
continuous canopy consists of medium sized trees 10-30 m tall. The smaller trees and
large shrubs form a discontinuous stratum. The most humid forests have dense stands
of tree ferns (Cyathea) in the ravines.
In general, the southwestern receives the highest amount of rainfall in the country.
Some of the good examples of the moist forests literally included in high forests of
Ethiopia include: Tiro-Boter-Becho forest, Belete-Gera, Yayu, Sigmo-Gatira,
Harenna-Kokosa in Oromia Region and the Masha-Anderacha, Bonga, Godere
forests in Southern Regions. These forests are recognized as high forests with closed
continuous canopy cover. Most of the forests in the southwestern plateau which seem
to be intact from above canopy are Coffee managed forests highly encroached by
humans. The trees have been selectively felled for timber, construction, expansion of
agriculture as well as Coffee and Tea plantations (Feyera Senbeta, 2006; Tadesse
Woldemariam et al., 2008).
13
2.4 Importance of the Forest of Ethiopia
Forests also sustain a range of economic activities in the world and act as a source of
food, medicine and fuel for more than a billion people (FAO, 2015). Forest
ecosystems and biodiversity more generally, are being considered for a wide variety
of useful services they provide for human wellbeing (MEA, 2003). The services
provided by the natural forest include provisioning services (e.g. food, fiber, fuel,
water), regulating services (e.g. climate, floods, disease, waste and water quality),
cultural services (e.g. recreation, aesthetic enjoyment, tourism, spiritual and ethical
values), and supporting services necessary for the production of all other ecosystem
services (e.g. soil formation, photosynthesis and carbon sequestration, nutrient
cycling). Supporting services are services that provide benefits outside the forest
ecosystem itself. For examples watershed protection and natural water filtration
benefits people in downstream and carbon sequestration benefits the entire global
community by reducing climate change (Bishop, 1999). However, the extent to which
human beings depend upon the natural forests for ranges of biological and chemical
processes is not well accounted.
Forestry is as one of the economic sectors in Ethiopia, and is closely linked to
economic growth and wellbeing of local communities. It is the one among four pillars
in the Climate Resilient Green Economy (CRGE) strategy (FDRE, 2011; UNDP,
2014). However, the value of forest ecosystem service is currently not adequately
captured under system of national account and its contribution to the national
economy is not estimated (UNDP, 2016). Moreover, only commercial timber is
accounting for Ethiopian economy (UNDP, 2016).
14
2.5 Threats to Afromontane Forests
Human beings are demanding more goods and services from natural forest beyond
their capacity to meet their need. Human induced disturbances such as fragmentation
and habitat loss are strongly influencing the regeneration success of plant species, and
determine the vegetation structure and composition of forests (Cabin et al., 2002;
Cotler and Ortega–Larrocea, 2006). According to Demel Teketay (1992) and Tamrat
Bekele (1994), growth in human populations and prosperity in Ethiopia translates into
increased conversions of natural forest to agricultural, industrial, or residential use.
The forest cover of Ethiopia in the past was expected to be much larger than the
present. Major deforestation incidents took place all over Ethiopia towards the
beginning of the twentieth century (Melaku Bekele, 2003; EFAP, 1994). Statistical
figures regarding Ethiopian forests indicate a continuous decline from the original
35% forest cover in 1950 (von Breitenbach, 1961, 1962; and EFAP, 1994) to 2.4% in
1992 (NCS, 1990; Sayer et al., 1992). FAO (2002) estimates the annual rate of
deforestation to be between 150,000ha – 200,000ha. From 1990 – 2010 alone, 2.65%
of the forest cover of the country was deforested (FAO, 2010). Deforestation affects
biodiversity and natural habitats and degrades natural resources. Von Breitenbach
(1963) stated that, the greatest threat to montane forest is the destruction caused by
deforestation, fire, expansion of agriculture and overgrazing which leads to depletion
of standing stock.
Growing population is one of the reason for increasing deforestation, which is leading
the country to lose its forest resources (Zewdu Eshetu and Yitebitu Moges, 2010). As
the population continues to grow, demand for agricultural land increases. This results
in permanent change of forest to other land uses such as agriculture, grazing, new
15
settlements, and infrastructure. This alarming rate of deforestation will results in fuel
wood crisis, loss of flora and fauna, loss of genetic diversity, loss of fertile soil and
reduced agricultural productivity.
Even though the depletion of forest stocks of the country is not well captured, the
natural forests are vanishing at an alarming rate due to extensive deforestation (Hurni
et al., 1987; Mulugeta Lemenih and Demel Teketay, 2006; and Shibru Tedla, 1995).
Often the decisions made on the forests do not take due consideration of the interests
of stakeholders, especially communities who are dependent on the local resources. As
a result, uncontrolled expansion of agriculture and grazing coupled with the illegal
harvesting of the forest and other forest products has been threatening normal
ecological functions of the forest ecosystems in many parts of the country (Chaffey,
1980; and Shibru Tedla, 1995). Moreover, lack of integration of the local people
living around the conservation areas in the conservation efforts, and absence of law
enforcement system triggers change that results in decline of diversity and abundance
of natural vegetation (Mulugeta Lemenih and Demel Teketay, 2006; Demel Teketay,
1999).
Similar to other forested areas of the country, the remaining high natural and coffee
forests in the southwest of Ethiopia are continuously threatened by anthropogenic
activities such as agricultural encroachment, extraction of timber and fire (Melaku
Bekele, 1992; and Feyera Senbeta, 2006). For instance, according to Gatzweiler
(2007), coffee forest cover in southwest Ethiopia was reduced by 11% from 1973–
1987. This period was characterized by resettlement program and the expansion of
state farms. It was also indicated that, 24 % forest loss was due to conversion of
10,128 ha of high forests into coffee plantations. In later periods, forests continued to
16
be converted to agro-forestry systems, agricultural land and settlement areas. There
were migration and settlement of landless people from densely populated and drought
affected parts of the country in areas covered by forest in search of agricultural land.
In addition, investment activities in forested areas and conversion of natural forests
into commercial plantations such as coffee and tea plantations in southwest Ethiopia
have contributed to the destruction of forests (Kumelachew Yeshitela, 2001). These
incidences have accelerated the rate of deforestation in the area. The major reason for
the failure to conserve natural forest is that their vulnerability and their values are not
fully realized (World Bank, 2004; United Nations, 2013).
2.6 Conservation Status of Forest Resources
Afromontane forests are very important and well known for maintaining threatened
species such as Prunus africana and Canarina abyssinica, and for other ecosystem
services. Very recently, increasing demand for land is in conflict with biodiversity
conservation in the country (Shibru Tedla and Kifle Lemma, 1998; Young, 2012).
Even though the natural forests of the country are under enormous pressure from the
growing demands of resources, the Government of Ethiopia has made an effort to
manage forests. Among the attempts done for conservation are establishment of
number of protected areas that may or may not incorporate the montane forests (parks,
NFPAs, wildlife sanctuaries, reserves, community conservation areas) covering about
2.7% of the country (with main focus on larger fauna). These protected areas however
have been suffered severe damage during the war or during its immediate aftermath.
The parks have not been legally gazetted except very few which was established very
earlier.
17
In addition, 58 most important natural forests were identified and established as
National forest priority areas (NFPAs), within the high forest areas with the objective
to implement an integrated forest management system (i.e. production, protection and
biological conservation services) (EFAP, 1994; Zerihun Woldu, 1999; and FAO,
2002). The NFPAs were established in 1988 comprising of natural forests,
plantations, and non-forested lands. Among the NFPAs designated for protection the
moist evergreen montane forest ecosystem include Harenna-Kokossa, Godare
(Gambella), Gebre Dima, Setema, Sigmo-Geba, Yayu, Babya-Folla, Belete-Gera,
Tiro-Boter-Becho, Masha-Anderacha, Bonga and Sheko forests. In some of the
NFPAs there was no natural forests remain and the forest stands have been partly
deforested or severely degraded in quality and quantity (Reusing, 1998). The present
management of the high forest fails to achieve its conservation objective due to
absence of effective forest policy, lack of appropriate institutional setup, and lack of
legal status of NFPAs. For example, none of the National Forest Protection Areas
(NFPAs) have legal protection any more. At present, except for the Menagesha Suba
Forest, all Forests designated under NFPAs are under Regional Governments.
Moreover, lack of accountability and commitment from government and expansion of
investment in forested areas have aggravated the decline of forests in the country.
The land tenure system is a major factor behind the poor adoption of forest
conservation and management practices. Repeated studies have confirmed that land
security enhances proper land management and increased productivity. When the state
administers the land, farmers may not feel secure enough to spend their time in soil
protection and land improvement activities. Moreover, with growing population
pressure, the degree of land fragmentation continuously increases; this aggravates
18
tenure insecurity as well as land degradation, with consequent degradation in
environmental resources and productivity such as forest degradation.
On the other hand, the most important of the conservation areas in Ethiopia is the Bale
Mountains National Park, a formal national park and it is yet to be officially gazetted.
This Key Biodiversity Area harbors the finest and most intact remnants of the
highlands' original vegetation (Young, 2012). These mountains are also home to four
threatened endemic species, and to more than half of the global population of the
Ethiopian wolf (Conservation International, 2009; Young, 2012).
Reforestation programs resulted in the planting of millions of seedlings in community
forests throughout Ethiopia. A number of NGOs, which had to organize their
activities through local associations, supplemented government efforts to rehabilitate
Ethiopia's forests. However, critics maintain that both systems caused communal
resources to be developed at the expense of private needs. As a result, reforestation
programs did not perform well throughout the country. Seedling survival rates were as
slow as 10 percent in some areas, largely because of inadequate care and premature
cutting by nearby residents (McKee, 2007).
2.7 Vegetation Ecology and Plant Communities
Vegetation Studies
Vegetation of an area can be described by its physiognomy and floristic
characteristics. Kuchler and Zonneveld (1988) express physiognomy as the overall
appearance or morphological characteristics of vegetation. The broad features of the
vegetation such as the growth forms and/or the life form of dominant species within a
plant community are described using the physiognomy of that particular vegetation.
19
Physiognomic characterization is a means to describe and characterize vegetation
fastly, as it does not require much floristic detail about the vegetation. It is mainly
used for conducting a reconnaissance type of vegetation survey to cover large
geographical areas in a limited period. Physiognomic characterization is not effective
in detecting spatial and temporal changes of vegetation.
A very important characteristic of vegetation is its life form and is used in many
vegetation classification systems (Raunkaer, 1934). Floristic characterization of a
vegetation focuses on analysis and synthesis of the floristic composition of plant
communities. The floristic characterization of vegetation include description of
floristic composition and quantitative measurements of certain parameters of
individual species. Functionally, according to Greig–Smith (1964, 1983), vegetation
is an organized and an integrated whole than the individual species and possess
properties which are not necessarily found in the species themselves. This shows that
vegetation is a holistic system by itself and is the most obvious feature of earth’s
surface that forms the immediate environment of human being. During floristic
analysis, whole assemblage of the constituent species are equally weighed and
examined. However, most plant communities consist of so many species that it is not
practical to discover all species within a community. It is common to use dominant
species in naming plant communities.
Kershaw (1973) agrees that the study of floristic composition enables us to build a
mental picture of an area under investigation and permit the comparison as well as the
ultimate classification of different units of vegetation. Shimwell (1984) pointed out
that vegetation analysis has five main objectives. The plant communities of an area,
the relationship that exists within communities, how plant communities related to the
20
environment and express their environment, how the individual plant species are
distributed within these communities, and how the communities develop and function
as organized living system.
Plant Community Structure
Plants are associated in communities, which have a definite structure and often a
regular specific composition (Poore, 1962). The community is one of the key concepts
in vegetation ecology (Poore, 1962; Braun–Blanquet, 1965). Communities may be
large or small and the number of species and/or population abundance in communities
may vary greatly. According to Callaway (1997), a community is the product of
several ecological processes, which include competition of species to limited
resources and facilitation of environment by pioneer species to other species. Plant
community can also be used in the sense of describing a group of the individuals of
different plant species occupying the area under study. Mueller–Dombois and
Ellenberg (1974) explained plant community structure as the horizontal and vertical
distribution of the abundances of plants in the community. Moreover, Larsen and
Bliss (1998) refined the concept as the vertical and spatial organization of species in a
community as the outcome of the processes of recruitment, growth, and competition
in a physical landscape. Plant communities involve many species and environmental
factors with complex relationship. Vegetation covering an area has a definite structure
and composition developed because of long-term interaction with biotic and a biotic
factors, and any change in the status of these factors disturbs the floristic composition
of the environment. Multivariate techniques are normally employed to study the
complex nature of plant communities summarizing large complex data sets obtained
from community samples (Gauch and Whittaker, 1972, 1981; Gauch, 1982).
21
Multivariate data consist of sets of attributes or scores for each of a number of
variables, this number being greater than two and sometimes large (Jeffers, 1978).
Multivariate techniques are being applied to study plant communities (Mueller–
Dombois and Ellenberg, 1974). Ordination and classification are the two widely used
multivariate methods used to study plant communities. These methods are essentially
structuring techniques, in that both are aimed at seeking a simpler structure than that
of the original raw data. In classification, sites/quadrates with species sharing certain
properties are arranged in groups. Whereas in ordination, sites or species are arranged
on axes, where their properties are determining by their positions (Lambert and Dale,
1964).
Cluster Analysis
Cluster analysis in this study involves grouping of plots/sites based on their similarity
and difference in species they commonly share (Jeffers, 1978). Clusters could be
generated using either divisive or agglomerative method (Lambert and Dale, 1964;
Greig–Smith, 1983; Digby and Kempton, 1987; Jeffers, 1978). Divisive begins with
dividing whole population of sites successively to produce a hierarchy in to smaller
groups. Each group is being examined independently for possible further subdivision
as it was extracted. Agglomerative begins with combining individual sites in a
hierarchy until all individuals are eventually united in a single population. Thus,
divisive method concentrate essentially on differences and start from maximal
information obtained over the whole population, while agglomerative method seeks
similarities and start from single units of minimal information.
22
Ordination
Vegetation is determined by number of environmental factors. Distribution of plant
species in a particular forest as well as in certain region is also determined by number
of environmental factors. Ordination is a means of analyzing the relationship between
species and environmental variables aiming at description through the arrangement of
samples and stands in order of similarity or difference in response to environmental
gradients (Mueller–Dombois and Ellenberg, 1974). Ordination helps ecologists to
understand the environmental patterns underlying vegetation composition. Ordination
is used to arrange sample sites along axes based on the data on species composition. It
also arranges points in such a way that sample quadrates which are located close
together are similar in species composition (Goodall, 1954). In ordination, sites are
arranged in small possible number of dimensions, in such a way that information
available on the data is retained (Jeffers, 1978). Ordination axes are constrained to
optimize their relation with a set of environmental variables. The ordination technique
offers a framework within which pattern of species distribution can be correlated with
a number of environmental factors there by demonstrating their relationships
(Anderson, 1966).
2.8 Influence of Environmental Gradients on Plant Communities
Vegetation is not a random assemblage of individuals of species (Whittaker, 1975).
Species may be found together in certain environment more frequently than would be
expected by chance. Plants require limited range of or optimum environmental
conditions such as light, temperature, water/moisture, nutrient, salinity, soil structure,
elevation, aspect, etc in which it can survive and reproduce. These environmental
conditions alter their adaptation, distribution, and assemblage. Plant species are
23
associated in certain manner and form communities, which have a definite structure
and often a regular specific composition (Poore, 1962). These plant communities
exhibit various structures or recognizable patterns in spatial arrangements of their
members. Smith (1990) indicated that horizontal heterogeneity in plant species results
from an array of environmental influences. Plant community distribution is the
manifestation of elevation, soil heterogeneity, microclimate, and disturbances (Urban
et al., 2000). For every combination of soil, climate, altitude, slope and aspect there
will be one species that grows better than any other does, so that it produces more
seeds or occupies more space by vegetative spread (Crawley, 1997). Austin et al.
(1996) also discovered that, altitude, topography, soil nutrient, moisture, and climate
influence the growth and development of plants and distribution patterns of plant
communities. Of these complex variables, which are difficult to separate, temperature
and other climatic variables seem to be most important for describing species richness
or community through the altitudinal gradient (Woodward, 1987).
Environmental parameters can be categorized in to three gradients. The first category
is named as ‘indirect environmental gradients’, in which the environmental variable
does not have a direct physiological influence on plant growth. It rather creates impact
on correlation of other influencing environmental variables. Elevation and aspect are
examples of such gradient; the secondly one is called ‘direct environmental
gradients’, where the environmental factor has a physiological influence on plant
growth but is not a resource for plant growth for which exploitative competition might
take place. pH is an example; and the third is known as ‘resource gradients’, where
the environmental variable is actually an essential resource for plant growth. Nutrients
are examples.
24
In the same way as abiotic variables determine species distributions, biotic
interactions constrain individual species ranges and, thus, the spatial variation in
species assemblages (Wisz et al., 2013). Thus, plant community assembly considers
both the ecological interactions that shape local communities and the evolutionary and
biogeographic processes that lead to variation in the diversity and its composition
(Kraft and Ackerly, 2014).
2.9 Remote Sensing and Land Use /Land Cover Change
According to Sohl and Sleeter (2012), land use (LU) refers to how land is used by
humans. In other words, it refers to the economic use to which land is put. Whereas
land cover (LC) refers to the actual surface cover for a given location. Unlike land
cover, which can be directly observed and monitored from remote sensing data, land
use typically must be inferred through a combination of remote sensing observation,
regional and local knowledge (including field observation), and other ancillary
information that links a given land use with land cover in a region. Remote sensing
data have great contributions for LU/LC modeling and is widely used to analyze
landscape patterns (Sohl and Sleeter, 2012).
Remote sensing is the acquisition of information about an object or phenomenon
without making physical contact to the object and thus in contrast to on site
observation. In modern usage, the term remote sensing generally refers to the use of
aerial sensor technologies to detect and classify objects on Earth (both on the surface,
and in the atmosphere and oceans) by means of propagated signals. Typically, LU/LC
is mapped from remote sensing data and then processed using appropriate software,
with the help of information on current and historical landscape patterns and the
driving forces behind.
25
According to Petit et al. (2001), monitoring and characterizing spatial patterns of
LU/LC change are vital for understanding and predicting LU/LC change. Mertens and
Lambin (1999) and Rindfuss et al. (2004) stated that spatial patterns of LU/LC change
represent the coupled human–environment changes of an area or a landscape and is
dependent on both physical and cultural factors. LU/LC modeling highly relies on
both historical and current land–cover maps coupled with data representing the
driving forces of change. Direct observation and mapping of land cover through
remote sensing analysis are very important for identifying and quantifying the major
processes of change.
As indicated by Mertens and Lambin (1999), empirical diagnostic models of LU/LC
change can be developed from the site-based observations. To understand the driving
forces of those observed changes, site-based observation data are used to be linked to
historical and socioeconomic data. However, Parker et al. (2002) and Tayyebi et al.
(2008) found that the availability of spatially and temporally consistent data
representing the driving forces is a primary challenge for LU/LC modeling.
2.10 Trends of LU/LC Change in Ethiopia and its Drivers
Biophysical processes and socioeconomic drivers are among the major factors
contributing for LU/LC changes occurring over time and space dimensions (FAO,
2006). Over the past century, agricultural lands have doubled worldwide (Etter et al.,
2006). In Sub–Sahara Africa, high population growth contributed for overexploitation
of natural resources. In these areas productivity of land is low, and the extent and rate
of LU/LC change is high (Bassett and Bi Zueli, 2000). These LU/LC changes have
implications for changes in land management practices in the landscape, hydrological
cycles, biodiversity, microclimates, and ground water (Lambin and Geist, 2003).
26
Forests are the major natural resources that are greatly affected by the LU/LC
changes, and are converted to agricultural lands.
According to Tsehaye Gebrelibanos and Mohammed Assen (2015), regional and local
landscapes of the country have been changing because of human–induced LU/LC
changes. Studies conducted by Gete Zeleke (2000), Kebrom Tekle and Hedlund
(2000), Gete Zeleke and Hurni (2001), Fikir Alemayehu et al. (2009), and
Mohammed Assen (2011) showed that, high rate of LU/LC has been experienced in
many parts of Ethiopian highlands. Agriculture and settlement has increased in the
expense of forest resources. Despite the fact that the rate, extent, and consequences of
forest loss have been documented in Ethiopia by EFAP (1994) and FAO (2010),
relationships between demographic, economic, and institutional factors that cause
LU/LC changes at local level are not well documented.
Studies by Woldeamlak Bewket and Sterk (2005) in Chemoga showed that, decrease
in vegetative cover at the watershed area resulted in generation of high surface runoff
in rainy seasons. The same study further explained that, the stream flow of the
watershed was affected by shortage of rainfall, and degradation of the watershed
because of LU/LC changes.
According to Woldeamlak Bewket and Ermiyas Teferi (2009), soil erosion caused due
to LU/LC, is a major contributor to the prevailing food insecurity in the country by
removing the fertile soil, as a result the area became degraded. Unsustainable
exploitation of the land resource, manifested by extensive removal of vegetation for
fuelwood, expansion of cultivation and grazing in steep land areas are the underlying
cause for the excessive rate of soil loss and food insecurity (Gete Zeleke, 2000;
27
Kebrom Tekle and Hedlund, 2000; Weldeamlak Bewket, 2002; Aklilu Amsalu et al.,
2007).
Underlying causes and associated consequences of LU/LC changes are explained in
terms of major events such as socio–ecological, environmental, policy and
development intervention (Teshome Abate and Ayana Angassa, 2016). Climate
change–related events (such as rainfall variability, recurrent drought, and
temperature), development intervention related events (i.e., promotion of crop
production, construction of water point), policy related events (i.e., ban of fire,
promotion of crop production, settlement) are influencing the LU/LC changes.
Climate change is affecting LU/LC and vegetation changes within individual
landscapes directly or indirectly. Bloesch (1999) suggested that, climate change is
affecting all types of land use and ecosystem services, as well as the behavior of
humans. Demographic factors related to population growth are the major among the
underlying causes for LU/LC changes in the country (Diress Tsegaye et al., 2010).
Population pressure together with other anthropogenic factors has significantly
contributed to the changes in LU/LC through expansion of cultivation, settlements,
and intensive exploitation of existing forest resources. Government policies on forest
management and use–right, expansion of cropland and settlement were also reported
to be the main causes for LU/LC changes. In addition, both natural and manmade fire
were affecting vegetation in various parts of the country, and regulating the normal
functioning of rangeland ecosystems (Bloesch, 1999; Laris, 2002; Angassa and Oba,
2008; and Diress Tsegaye et al., 2010).
28
CHAPTER THREE
3. MATERIALS AND METHODS
3.1 Description of Study Areas
This study was carried out at the Afromontane forests of Tiro Boter Becho (TBB)
state forest and Chebera Churchura National Park (CCNP).
3.1.1 Tiro Boter Becho
The first study site, TBB (Figure 1) is located between Tiro Afeta and Chora Boter
Weredas of Jimma Zone, Oromia Regional State. It is situated between 08001' –
08028' N latitude and 037009' – 037020' E longitude, covering an area of 40,528ha.
TBB lies along a volcanic mountain ridge, running almost north to south, and rising to
a series of small peaks of 3030 m.a.s.l. It is possible to reach to the forest in two ways.
One is through Boter Becho, which is located at about 73 km southwest of Welkite
town, which in turn is 150km from Addis Ababa. The other route is through Tiro,
which is located at about 55 km northwest of Asendabo town, which in turn is 300 km
from Addis Ababa. There are several streams flowing out of the Afromontane forest
of TBB to Gilgel Gibe, which forms a wide valley supporting the lower parts of the
forest.
29
Figure 1. Map of Ethiopia, Oromiya Regional State, and the study area (TBB)
30
Temperature and Rainfall
According to the rainfall data obtained from National Meteorological Agency for the
period 2001 – 2015, the mean annual temperature of Boter Becho is about 14.3 oC
with maximum (26.6 oC) from January to March and minimum (1.0 oC) from
November to December. The mean annual rainfall is 1434 mm year–1, with high
variation from year to year, ranging from about 1088 – 1703 mm year–1 (SD =
182.94). The rainfall pattern is unimodal, with a dry season from November to
February and then gradually increasing to the rainy season from March to October.
July is the month where the area gets the highest rainfall (Figure 2).
Figure 2. Climadiagram for Boter Becho Station (Data source: NMA)
31
Topography and Soil
The landform changes from flat surface on top of plateau to very steep slopes and
valley bottoms. The altitude of the area ranges from 1650 to 3030 m.a.s.l. The soils in
TBB where the Afromontane forest exists are acidic with pH value ranging between
pH of 3.94 and 6.43 (own data). According to the soil classification system by
FAO/UNESCO (1990), the soil association of TBB is Eutric Nitosols.
Vegetation
TBB forest is composed of Moist Afromontane forest (Figure 3) at higher altitude and
Combretum–Terminalia woodland in its lower altitude. The montane forest
characteristically contains a mixture of Podocarpus falcatus and broad–leaved species
as emergent trees in the canopy including Pouteria adolfi–friederici. There are also a
number of medium–sized trees, and large shrubs. In addition, Juniperus procera,
Hagenia abyssinica and other small trees that grade into an open Erica arborea zone
around 2900 m are also present. There are some patches of Arundinaria alpina in wet,
sheltered valleys.
Figure 3. Partial view of Moist Afromontane forest of TBB (own photo)
32
3.1.2 Chebera Churchura National Park
The second study site is the Afromontane forest of Chebera Churchura National Park
(CCNP). CCNP is one of the recently established parks in the Southern Nations
Nationalities and Peoples Regional State (SSNPRS), with the primary objective of
protecting wildlife (especially the African Elephants and Buffaloes). The park lies
within the western side of the central Gibe–Omo Basin, between Dawro
Administrative Zone and Konta Special Woreda, situated between 06040' – 07009' N
latitude and 036030' – 036058' E longitude, covering an area of 121 km2 (Figure 4).
The park is located at about 580 km southwest of Addis Ababa. In addition to existing
wildlife resource, the park is also known by its small crater lakes and major rivers.
There are also several hot springs and waterfalls in the park. Omo River is bordering
the park to the South, to which all the major rivers from the park are draining.
33
Figure 4. Map of Ethiopia, SNNPRS, and the study area (CCNP)
34
Temperature and Rainfall
The rainfall data obtained from NMA for the period 2005 – 2013 shows that the mean
annual temperature at Ameya, the nearest town to CCNP (21 km air distance), is about
18.1 oC with maximum (25.1 oC) from December to April and minimum (12.1 oC) from
June to October. The mean annual rainfall is 2082 mm year–1, with high variation from
year to year, ranging from about 1810–2375 mm year–1 (SD = 198.69). The rainfall
pattern is bimodal, with a dry season from December to February and then gradually
increasing to the rainy seasons between March and November. July is the month, where
the area gets the highest rainfall (Figure 5).
Figure 5. Climadiagram for Ameya Station (Data source: NMA)
35
Topography and soil
The park is characterized by its undulating heterogeneous hilly terrain with various
sized valleys and gorges. The altitude of the park ranges from 550 to 2800 m.a.s.l. The
soils of CCNP, where the Afromontane forest is situated, are slightly acidic with pH
value ranging between pH of 5.32 and 6.36 (own data). According to the soil
classification system by FAO/UNESCO (1990), the largest portion of the park consists
of Eutric Cambisols and small portion of the northern and western part of the park has a
soil type of Eutric Nitosols.
Vegetation
There are different vegetations types in Chebera Churchura National Park: Moist
Afromontane Rainforest (Figure 6), Riverine vegetation, Combretum–Terminalia
woodland and Wooded Grassland.
Figure 6. Partial view of Moist Afromontane forest of CCNP (own Photo)
36
The largest portion of the park is grassland with scattered trees, where grass reach up to
3 m tall. Fire is taking place every year in the park during the dry season in the lowland
areas occupied by grasses. Some broad–leaved emergent trees species in the canopy
include Pouteria adolfi–friederici and Polyscias fulva. There are also a number of
medium–sized trees and shrubs at the Afromontane forests of the area.
3.2 Preliminary Survey
Reconnaissance survey was carried out to both TBB and CCNP prior to data collection.
This overview was important for the selection of the representative sites for data
collection.
3.3 Methods of Data collection
3.3.1 Vegetation Sampling
Transects were laid along gradients in the Afromontane part of TBB and CCNP for the
collection of vegetation and environmental data following Muller–Dombois and
Ellenberg (1974) and Kent and Coker (1992). Vegetation data were collected in each
sampling sites using plot area of 30 m x 30 m (900 m2). Because of high canopy
closure, the herbaceous cover in the area was sparse. Therefore, within each main plot a
5 m x 5 m sub–plot was used for recording herbaceous species. A total of 118 and 61
plots were taken from the Afromontane forests of TBB and CCNP respectively,
depending on the size of the Afromontane forests of the areas. The plots were
established at 300 m along line transects. 32 and 14 transects were laid in TBB and
CCNP respectively. Transects were spread at 500 m from one another.
Each of the vascular plant species encountered in each plot of the Afromontane forests
TBB and CCNP were recorded. Height measurements were taken for each woody plant
37
with height ≥2 m and diameter measurements were taken for each woody plant with
DBH ≥2.5 cm. Plants with a height of less than 2 m and DBH less than 2.5 cm were
treated as seedlings and saplings respectively. Moreover, percentage of canopy cover of
each plant species in the sampling plots was visually estimated. Species occurring
outside the plots were also recorded for enriching the diversity of the flora of the study
area. Voucher specimens were collected, pressed, and brought to the National
Herbarium (ETH), Addis Ababa University, for identification using published volumes
of Flora of Ethiopia and Eritrea (Hedberg and Edwards, 1989; Hedberg and Edwards,
1995; Edwards et al., 1995; Edwards et al., 1997; Edwards et al., 2000; Hedberg et al.,
2003; Hedberg et al., 2004; Hedberg et al., 2006; and Hedberg et al., 2009), other
taxonomic works and comparing them with specimens already deposited in the
National Herbarium.
3.3.2 Environmental Data
Geographic coordinate and elevation for each main plot was recorded using Garmin
Global Positioning System (GPS). Slope of each main plot was taken using Sunto
Clinometer. In addition, soil samples were collected from each main plot from the
depth of 0–10 cm, 10–20 cm and 20–50 cm at four corners of the main plot and
composite samples were made for each layer.
Disturbance on the forest resources were estimated and rated as “Low (when the
number of seedlings trampled in a sampling plot were less than 10 and no trees cut
down)”, “Medium (when the number of seedlings trampled in a sampling plot were
between 10 and 20, and/or one tree is cut down)”, and/or “High (when the number of
seedlings trampled in a sampling plot were higher than 20, and/or more than one trees
are cut down)” based on number of seedling trampled, footpaths, and extent of grazing.
38
3.3.3 Land Use Land Cover Data
Landsat images of the three selected years within the past thirty years (Table 1) were
obtained from United States Geological Survey (USGS) (an open source) are used to
analyze the land use/land cover in the study areas.
Table 1. Description of Landsat Images used and their Sources
No
Image
Resolution
Sensor
or scale
Year of
image
Source
acquisition
1
Landsat 8 Operational Land Imager (OLI)
30m
2015
USGS
2
Landsat 7 Enhanced Thematic Mapper
30m
2000
USGS
30m
1984
USGS
Plus (ETM+)
3
Landsat 5 Thematic Mapper (TM)
Field observations and GPS ground truthing points were taken from the actual field,
and assisted with Google Earth and topographic maps of 1972 of the area for the
purpose of land cover classification. Data regarding the major driving forces of the
LU/LC changes and threats on the vegetation in the study area were collected using
focus group discussions, and interview with key informants from local people residing
near the forests. Two focus group discussions were carried out at each study site. Each
focus group had fifteen individuals composed of elders, youths, and administrative
officials. Key informants, who lived in the area for more than thirty years were selected
purposefully.
39
During the key informant interviews and focus group discussions, issues regarding the
main economic activity/activities practiced in this area, land ownership and agricultural
practice of local communities, the benefit(s) that the local communities are obtaining
from the natural forest in the area in a rank order, the main source(s) of energy for your
household, source of wood/timber for community’s for firewood and house
construction, trends of population change, trends of change of natural forest and
agricultural lands in the area, factors contributing to changes to forest and agricultural
lands, and suggested forest management approaches were raised.
3.4 Data Analysis
3.4.1 Plant Diversity analysis
According to Whittaker (1975), the description of vegetation involves the analysis of
species diversity, evenness, and similarity. Shannon and Wiener (1949) index of
diversity analysis, was applied to quantify the species diversity and evenness of the
Afromontane forests of TBB and CCNP.
s
H ' = −∑ pi ln pi,
The diversity was calculated as:
i =1
Where: Pi= the proportion of individuals or the abundance of ith species as a proportion
of total cover in the sample.
Evenness was calculated using the formula: J =
H'
,
ln(S )
Where: J = evenness; H’ = Shannon–Wiener diversity index; and S = total number of
species in the sample.
40
The value of evenness index falls between zero and one. The higher the value of
evenness index the more evenly distributed the species are within the given area (Kent
and Coker, 1992).
Floristic Similarity
The floristic similarity of the two forests under study and other similar forest in the
country was assessed in terms of species composition using the Sorensen’s coefficient
of similarity (Ss) shown in Kent and Coker (1992). Sorensen’s coefficient of similarity
value ranges from zero (complete dissimilarity) to one (total similarity).
Floristic similarity of forests was calculated using the formula: Ss =
2a
,
( 2a + b + c )
Where: Ss = Sorenson Similarity coefficient; a = the number of species common to
both forests compared; b = the number of species in one of the forest to be compared;
and c = the number of species in present in other forest.
Density
The density of woody species at the Afromontane forests of TBB and CCNP was
computed in stems per hectare (stems.ha-1) basis. The density of individuals with DBH
> 10 cm and DBH > 20 cm was computed and the ratio of these two was taken as a
measure of the proportion of small– and large–sized individuals (Grubb et al. 1963).
3.4.2 Vegetation and Plant Community Structural Analysis
The percentage cover values for trees, shrubs, herbs and grasses estimated in each
sample plots was converted into cover abundance values using 1 - 9 modified BraunBlanquet scale (Table 2) as modified by van der Maarel (1979).
41
Table 2. Modified Braun-Blanquet scale for cover abundance values
Scale
Cover abundance values
1
Rare, generally one individual
2
Occasional, less than 5 % cover of the total
3
Abundant, with less than 5% cover of the total
4
Very abundant, with less than 5% cover of the total
5
Cover 5-12.5% of the total area
6
Cover 12.5- 25% of the total area
7
Cover 25-50% of the total area
8
Cover 50-75% of the total area
9
Cover >75% of the total area
Source: van der Maarel, 1979
Plots were further grouped into clusters with the aid of Multivariate methods using R
(Zerihun Woldu, in press). Using similarity Ratio as resemblance index and Wards
method of amalgamation technique.
1−
(∑ x
∑(x *x )
+∑x
)− ∑(x
k ,i
2
2
k ,i
k, j
k, j
x
*
k ,i
k, j )
The dissimilarities between the clusters are the squared Euclidean distances between
cluster means. The vertical axis of the dendrogram represents the dissimilarity or
distance between clusters. The horizontal axis represents the main plots and clusters.
Each joining (fusion) of two clusters is represented on the graph by the splitting of a
vertical line into two vertical lines. The vertical position of the split, shown by the short
horizontal bar, gives the dissimilarity (distance) between the two clusters.
The communities distinguished were further refined in an indicator species table.
Indicator species is a species that characterizes of a cluster of samples. Indicator Value
42
of each species was calculates as the product of its relative frequency and its relative
abundance. Indicator values range from 0 to1. The significance of indicator values were
tested through permutation test. Relationship of plant communities and environmental
variables was presented in a multivariate method that expresses relationships between
samples, species and environmental variables in a low–dimensional space called
ordination diagrams (McCune and Grace, 2002). For this study, constrained RDA
(Redundancy analysis) is used instead of CCA (the most popular ordination methods in
community ecology when the length of the axis of DCA is shorter then 3SD) (ter Braak
& Šmilauer, 2002; Lepš & Šmilauer, 2003). All environmental variables were
subjected to ANOVA and Adonis test prior to DCA for their significance at P=0.05.
Regarding the structure of the Afromontane forests of the study areas, analyses were
carried out in terms of tree density, girth diameter, height, and basal area in hectare
basis. The diameter at breast height (DBH) was grouped into eleven diameter classes
and the percentage distributions of woody species in each class were computed to
indicate plant population structure of the area. Tree height was also grouped into seven
height-classes and the percentage distributions of woody species in each height-class
were calculated. Structural comparison of the two Afromontane forests under
investigation to other forests in Ethiopia was carried out.
Basal Area
According to Barbour et al. (1987), basal area (BA) is the cross–sectional area of tree
stems at breast height. And it is a measure of dominance, where the term dominance
refers to the degree of coverage of species as an expression of the space it occupies.
43
Basal Area was calculated as: BA =
πd
2
4
, Where: BA= basal area in m2 per hectare;
d = diameter of tree stem at breast height; and π = 3.14.
Importance value Index (IVI)
The ecological significance of a species in a forest was compared using Importance
Value (IV) of a species (Lamprecht, 1989). Important values Index (IVI) of woody
species (Mueller–Dombois and Ellenberg 1974) was computed by summing up their
relative density (RD), relative dominance (RDO) and relative frequency (RF). i.e. IVI =
RD+RDO+RF, Where,
The number of individuals of a species
Relative density =
The total number of all individuals
X 100;
The number of plots where a species occur
Relative frequency =
X 100; and
The total plots used during the study
Dominance of a species
Relative dominance =
X 100
Dominance of all species in the study area
Dominance: area a species occupies in a stand (or basal area for trees) on a unit area
basis
Basal area of individual species in the sample (m 2 )
Dominance (Do) =
Total area of the sample (m 2 )
or
Dominance = mean basal area of a species multiplied by number of trees of a
species per hectare.
Frequency (F) was calculated as the number of plots in which a species recorded
divided by total plots
44
In order to describe the effects of environment on the distribution of plant species, pH,
organic matter, Cation Exchange Capacity (CEC), total Nitrogen, available Phosphorus
and soil textures only were analyzed from composite soil samples collected from each
layer of the main plot.
Vertical Structure of the Forest
The vertical structures of woody species in the two Afromontane forests under study
were described following the IUFRO (International Union for Forestry Research
Organization) classification scheme (Lamprecht, 1989). Three vertical structures were
distinguished as: upper storey (tree height higher than 2/3 of highest height), middle
storey (tree height between 1/3 and 2/3 of highest height) and lower storey (tree height
lower than 1/3 of the highest height).
3.4.3 LU/LC Detection and Analysis
LU/LC of the study area were monitored by analyzing the satellite imageries at a
resolution of 30 m from the year 1984, 2000, and 2015. The boundary of the study area
was obtained from the CCNP Head Quarter and Oromia Forest and Wildlife Enterprise
(OFWE), TBB District Office.
Landsat image processing, spatial analysis, and change detection were carried out using
Quantum Geographic Information System QGIS (Lyon–version 2.12.3). Automatic
Classification Plug-in (Congedo et al., 2013) was used for image processing and
LU/LC classification and analysis. In addition, Microsoft Office Excel was used to
create charts and graphs. Supervised digital image classification technique was
employed using spectral angle mapping algorithm and complemented with 25 ground
points from each LU/LC types. The images were projected, to the spatial reference
45
coordinate systems of Adindan / UTM zone 37N, prior to image processing and
classification. The sub-setting of satellite images were performed for extracting study
area from both images by taking geo-referenced outline boundary of the study area map
as AOI (Area of Interest). For better classification results, normalized difference
vegetation index (NDVI) was created to classify the Landsat images.
Three LU/LC maps corresponding to the three reference years were finally produced
based on reflectance characteristics and color features of the various LU/LC types. The
trends and extents of each LU/LC change were determined for the respective years of
the study. Field visit and focus group discussions were carried out to obtain additional
information on the long year practice regarding the LU/LC changes in the study areas.
Descriptions to land use classes obtained from classification of Landsat images through
the methodology described in Congedo et al., (2013) are given in Table 3.
Table 3. Description of LU Classes Identified
LU Class
Forest
Woodland
Shrub/Bushland
Grassland
Agriculture and
Settlement
Water body
Description
Areas covered mainly with natural forest and plantations, whose
pixels had higher NDVI values (between 0.61 – 1.00)
Areas covered with woodland and sparse vegetation, whose pixels
had medium NDVI values (between 0.41 – 0.60)
Areas covered with shrub/bushes, whose pixels had NDVI values
between 0.31 – 0.40
Areas covered with open grasses and bushes used for grazing
(pixels had NDVI values between 0.21 – 0.30)
Plain and slightly undulating landscapes that are cultivated; land
surface features devoid of any type of vegetation cover including
settlement areas, abandoned land, roads, gullies and waterways
(pixels with NDVI value between 0.10 – 0.20)
Surface water such as lakes and flood plains covered with water
(pixels with NDVI value less than or equal to 0.1)
46
LU/LC change for 1984 to 2000, 2000 to 2015, and 1984 to 2015 were analyzed using
transformation matrices from the three LU/LC maps of the study area with an overlay
analysis technique.
The extent of LU/LC change at TBB and CCNP are given in matrix. The change
detection was carried out using images of LU/LC analysis from two different years and
reported in hectare. The land use land cover change matrix depicts LU/LC classes,
LU/LC classes remain unchanged, and direction of changes of the LU/LC classes.
Classification accuracy
Classification accuracy of LU/LC classification is presented using matrix known as
confusion matrix. LU/LC classification is usually carried out using the reference and
classified data. The classified data represent the location of the spectrally classified
pixel in the classified image. Whereas, the reference data denote the actual location of
the pixel on the ground, which is obtained from the ground truthing. The matrix
presents the numbers of correctly classified and misclassified pixels of a classified
image. The total numbers of pixels that exactly match both the reference and classified
data in the cell array are the correct classifications, and are shown in bold diagonally in
error matrices. The overall classification accuracy shows that how accurate the
classification was. It is provided as the ratio of the sum of correct classifications and
total randomly generated reference pixels used for the assessment.
Kappa value of classification accounts for the off–diagonal elements as a product of the
row and column marginal and not just the diagonal values in the estimation of
accuracy. Kappa coefficient is used to determine if the accuracy presented in the error
matrix is significantly better than a random result. It also accounts for the random
accuracy of a given classification.
47
N ∑ X −∑ (X * X
N −∑ (X * X )
r
Kappa (K) is calculated using the formula: K =
i =1
2
r
ii
r
i =1
i+
i =1
i+
+i
)
,
+i
Where, r = number of rows in the error matrix; Xii = number of observations in row i
and column i (on the major diagonal); Xi+ = total of observations in row i (shown as
marginal total to right of the matrix); X+i = total of observations in column i (shown as
marginal total at bottom of the matrix); and N = total number of observations included
in matrix
Kappa value ranges from zero to one. Kappa of one indicates perfect match between
the reference and classified data and zero indicates that any match is totally due to
chance.
Rate of land use and land cover changes in the study area
The rate of LU/LC change (RC) in ha.year–1 basis was calculated using the formula:
RC =
( A − B)
,
t
Where: RC = rate of LU/LC change; A = recent area of LU/LC in ha; B = previous area
of LU/LC in ha; and t = time interval between A and B in year
Overall steps followed for LU/LC study is presented in the flowchart (Figure 7).
48
Figure 7. Flowchart showing the steps followed during LU/LC evaluation
(own sketch)
49
CHAPTER FOUR
4. RESULTS
4.1 Plant Diversity and Species Composition of Afromontane forest of TBB and
CCNP
Two hundred and four plant species belonging to 168 genera, and 72 families were
recorded from sample plots and their vicinity at the Afromontane forest of TBB.
Whereas one hundred and forty four plant species belonging to 131 genera and 66
families were recorded from sample plots and their vicinity at the Afromontane forest
of CCNP. The complete list of plant species identified in the two study areas is given in
Annex 1.
Plant species identified from the study areas were grouped based on their habit
according to plant habit classification of the Flora books (Table 4 and Table 5).
Table 4. Distribution of species according to growth–form/habit of plants at the
Afromontane forest of TBB with their corresponding number species
Habit
Number of Species
Percent (%)
Tree/Shrub
55
27.0
Herb
58
28.4
Tree
28
13.7
Shrub
31
15.2
Liana (Woody climber)
17
8.3
Herbaceous climber
6
2.9
Fern
5
2.5
Grass
4
2.0
50
Table 5. Distribution of species according to growth–form/habit of plants at the
Afromontane forest of CCNP with their corresponding number species
Habit
Number of Species
Percent (%)
Tree/Shrub
43
29.9
Herb
39
27.1
Tree
26
18.1
Shrub
12
8.3
Liana (Woody climber)
15
10.4
Herbaceous climber
5
3.5
Fern
3
2.1
Grass
1
0.7
From total families identified at the Afromontane forest of TBB and CCNP (Annex and
Annex 3 respectively), the top five families with regard to their species composition are
provided in Table 6 and Table 7 respectively, in descending order. In TBB, family
Asteraceae has the highest number of species, followed by family Acanthaceae.
Whereas In CCNP, family Fabaceae has the highest number of species followed by
family Acanthaceae and Asteraceae.
Table 6. List of top five plant families with their number of genera and species
encountered at the Afromontane forest of TBB
Family
No. of Species
%
No. of Genera
%
Asteraceae
19
9.3
15
9.0
Acanthaceae
12
5.9
9
5.4
Fabaceae
11
5.4
9
5.4
Lamiaceae
11
5.4
9
5.4
Rubiaceae
9
4.4
8
4.8
51
Table 7. List of top five plant families with their number of genera and species
encountered at the Afromontane forest of CCNP
Family
No. of Species
%
No. of Genera
%
Fabaceae
8
5.56
7
5.51
Acanthaceae
7
4.86
6
4.72
Asteraceae
7
4.86
7
5.51
Euphorbiaceae
6
4.17
6
4.72
Rubiaceae
6
4.17
6
4.72
The Shannon diversity index of Afromontane forest of TBB was 3.45 and CCNP was
3.32 with their evenness value of 0.80 and 0.84 respectively. Based on the information
available on the published books of Flora of Ethiopia and Eritrea, 12 endemic plant
species were recorded from the Afromontane forest of TBB and 6 endemic plant
species from the Afromontane forest of CCNP (Table 8).
Table 8. Endemic species and their habit at the Afromontane forests of TBB and CCNP
Scientific Name
Acanthus sennii Chiov.
Cissampelos pareira L.
Clematis longicauda Steud.ex A. Rich.
Erythrina brucei Schweinf.
Lippia adoensis Hochst. ex Walp.
Maytenus addat (Loes.) Sebsebe
Millettia ferruginea (Hochst.) Bak.
subsp. darassana (Cuf.) Gillett
Pittosporum viridiflorum Sims.
Plectocephalus varians (A. Rich.) C.
Jeffrey ex Cufod.
Solanecio gigas (Vatke) C. Jeffrey
Tiliachora troupinii Cufod.
Vepris dainellii (Pichi–serm.) Kokwaro
Family
Acanthaceae
Menispermaceae
Ranunculaceae
Fabaceae
Verbenaceae
Celastraceae
Habit
Sh
Li
Cl
T
Sh
T
Occurrence
TBB
TBB
CCNP and TBB
CCNP and TBB
TBB
TBB
Fabaceae
Pittosporaceae
T
T/Sh
CCNP and TBB
CCNP and TBB
Asteraceae
Asteraceae
Menispermaceae
Rutaceae
H
T/Sh
Li
T/Sh
TBB
TBB
CCNP and TBB
CCNP and TBB
52
4.2 Vegetation Structure
4.2.1 Plant Community Structure of the Afromontane forest of TBB and CCNP
4.2.1.1 Cluster Analysis
Result from the cluster analysis shows that the plant species recorded from one hundred
eighteen plots of the Afromontane forest at TBB were clustered in to five plant
communities (Figure 8).
Figure 8. Dendrogram showing clusters of plots obtained from the Afromontane forest
of TBB
53
Cluster numbers in the dendrogram corresponds to the communities in the subsequent
discussion. These clusters were designated as local plant communities and given names
after two indicator species with higher species indicator value (Annex 4).
Community 1: Apodytes dimidiata - Podocarpus falcatus community
This plant community was distributed at altitudes between 2335 and 2685 m.a.s.l. with
mean altitude of 2488 m.a.s.l. This community is dominated by Podocarpus falcatus
and Apodytes dimidiata (Figure 9). Grazing and tree cutting is common in this
community.
Figure 9. Partial view of Podocarpus falcatus dominated Afromontane forest of TBB
(own photo)
54
Species in upper storey in this community include Syzygium guineense subsp.
afromontanum, Olea capensis subsp. macrocarpa, Podocarpus falcatus, and Prunus
africana. Species in middle storey in this community include Apodytes dimidiata,
Chionanthus mildbraedii, Bersama abyssinica, Olinia rochetiana, Ficus sur,
Allophylus abyssinicus, Ilex mitis and Polyscias fulva. Species in lower storey include
Psychotria orophila, Oxyanthus speciosus, Maytenus gracilipes subsp. arguta, Vepris
dainellii. Understory species in this community includes Oplismenus hirtellus, Setaria
megaphylla, Acanthopale pubescens and Acanthus eminens.
Community 2: Croton macrostachyus - Pouteria adolfi-friederici community
This community was distributed at altitudes between 2105 and 2550 m.a.s.l. with mean
altitude of 2341 m.a.s.l. This community is distant from settlement areas disturbance
resulting from human and grazing in this community is very unlikely compared to other
communities. This area is known by its high density of emergent tree species of
Pouteria adolfi-friedrici, Croton macrostachyus and Prunus africanus (Figure 10).
Figure 10. Partial view of Pouteria adolfi-friedrici dominated Afromontane forest of
TBB (own photo)
55
Species in upper storey in this community include Olea capensis subsp. macrocarpa,
Syzygium guineense subsp. afromontanum, Prunus africana, Podocarpus falcatus,
Croton macrostachyus and Pouteria adolfi–friederici. Species in middle storey in this
community include Macaranga capensis, Celtis africana, Olinia rochetiana, Polyscias
fulva, Ficus sur, Allophylus abyssinicus, Apodytes dimidiata and Millettia ferruginea
subsp. darassana. Species in lower storey include Bersama abyssinica, Vepris dainellii,
Psychotria orophila and Chionanthus mildbraedii. Understory species in this
community includes Oplismenus hirtellus, Acanthus eminens, Acanthopale pubescens
and Setaria megaphylla.
Community 3: Macaranga capensis - Lepidotrichilia volkensii community
This community was distributed at altitudes between 2165 and 2616 m.a.s.l. with mean
altitude of 2261 m.a.s.l. Species in upper storey in this community include Olea
capensis subsp. macrocarpa, Syzygium guineense subsp. afromontanum, Podocarpus
falcatus, Pouteria adolfi–friederici and Prunus africana. Species in middle storey in
this community include Olinia rochetiana, Millettia ferruginea subsp. darassana,
Albizia gummifera, Schefflera abyssinica, Celtis africana, Ilex mitis, Polyscias fulva,
Allophylus abyssinicus and Schefflera volkensii. Species in lower storey include
Dracaena afromontana, Ehretia cymosa, Chionanthus mildbraedii, Bersama
abyssinica, Psychotria orophila, Oxyanthus speciosus, Vepris dainellii, Teclea nobilis,
Pittosporum viridiflorum, Clausena anisata, Canthium oligocarpum and Rytigynia
neglecta. Understory species in this community includes Acanthus eminens,
Oplismenus hirtellus, Acanthopale pubescens and Setaria megaphylla.
56
Community 4: Clausena anisata - Pittosporum viridiflorum community
This community was distributed at altitudes between 2141 and 2585 m.a.s.l. with mean
altitude of 2307 m.a.s.l. Species in upper storey in this community include Olea
capensis subsp. macrocarpa, Syzygium guineense subsp. afromontanum, Podocarpus
falcatus and Pouteria adolfi–friederici. Species in middle storey in this community
include Macaranga capensis, Olinia rochetiana, Ilex mitis, Millettia ferruginea subsp.
darassana, Ficus sur, Allophylus abyssinicus, Schefflera abyssinica and Lepidotrichilia
volkensii. Species in lower storey include Dracaena afromontana, Psychotria orophila,
Maytenus gracilipes subsp. arguta and Oxyanthus speciosus. Understory species in this
community includes Setaria megaphylla, Oplismenus hirtellus, Acanthus eminens and
Desmodium repandum.
Community 5: Myrsine melanophloes - Hagenia abyssinica community
This community was distributed at altitudes between 2753 and 2932 m.a.s.l. with mean
altitude of 2847 m.a.s.l. This community is restricted to mountainous area locally
known as ‘bore’. Erica arborea, Osyris quadripartita, Myrsine melanophloes were
dominant plant species in this area (Figure 11). Arundinaria alpina is located in the
wetter western side of the mountain. The diversity of this community is very low
compared to the other four communities. Disturbance is relatively high in this
community. Grazing, clearing the forest for agriculture and wood extraction is common
in this area. People in this area are collecting Erica arborea for firewood, bamboo for
house construction.
57
Figure 11. Partial view of area where species belongs to community 5 at the
Afromontane forest of TBB exist (own photo)
Species in upper storey in this community include Olea capensis subsp. macrocarpa
and Juniperus procera. Species in middle storey in this community include
Arundinaria alpina, Myrsine melanophloes, Hagenia abyssinica, Olinia rochetiana and
Ilex mitis. Species in lower storey include Erica arborea and Maytenus addat.
Understory species in this community includes Setaria megaphylla, Acanthus eminens,
Acanthopale pubescens and Oplismenus hirtellus.
58
Result from the cluster analysis shows that plants from the sample plots at the
Afromontane forest of CCNP were grouped into three plant communities (Figure 12).
Figure 12. Dendrogram showing clusters of plots obtained from the Afromontane forest
at CCNP
Cluster numbers in the dendrogram corresponds to the communities in the subsequent
discussion. These clusters were designated as local plant communities and given names
after two indicator species with higher species indicator value (Annex 5).
59
Community 1: Olea capensis subsp. macrocarpa - Macaranga capensis community
This community was distributed at altitudes between 1737 and 2339 m.a.s.l. with an
average altitude of 2007 m.a.s.l. Species in upper storey in this community include
Syzygium guineense subsp. afromontanum, Prunus africana, Albizia gummifera and
Olea capensis subsp. macrocarpa. Species in the middle storey include Lepidotrichilia
volkensii, Ficus sur, Apodytes dimidiata, Macaranga capensis, Millettia ferruginea
subsp. darassana, Polyscias fulva, Pouteria adolfi–friederici, Ilex mitis, Croton
macrostachyus, Dombeya torrida, Vepris dainellii, Schefflera abyssinica and
Allophylus abyssinicus. Species in lower storey include Psychotria orophila,
Chionanthus mildbraedii, Oxyanthus speciosus, Dracaena afromontana, Maytenus
gracilipes subsp. arguta, Pittosporum viridiflorum, Rytigynia neglecta and Galiniera
saxifraga. Understory species in this community includes Desmodium repandum,
Oplismenus hirtellus and Piper capense.
Community 2. Cyathea manniana - Lepidotrichilia volkensii community
This community was distributed at altitudes between 1682 and 2173 m.a.s.l. with an
average altitude of 1950 m.a.s.l. This community was formed along valleys in more
wetter areas. It was dominated by Cyathea maniana, a tree fern (Figure 13).
60
Figure 13. Partial view of Cyathea maniana dominated area at the Afromontane forest
of CCNP (own photo)
Species in upper storey in this community include Syzygium guineense subsp.
afromontanum and Prunus africana. Species in middle storey in this community
include Dracaena afromontana, Lepidotrichilia volkensii, Ficus sur, Polyscias fulva,
Schefflera abyssinica, Millettia ferruginea subsp. darassana, Croton macrostachyus,
Celtis africana, Allophylus abyssinicus, Ilex mitis, and Vepris dainellii. Species in
lower storey include Chionanthus mildbraedii, Oxyanthus speciosus, Cyathea
manniana, Psychotria orophila, Galiniera saxifraga, Rytigynia neglecta, Pittosporum
viridiflorum, Maytenus gracilipes subsp. arguta, and Canthium oligocarpum.
Understory species in this community includes Piper capense and Oplismenus hirtellus.
61
Community 3. Coffea arabica - Nuxia congesta community
This community was distributed at altitudes between 1614 and 1852 m.a.s.l. with an
average altitude of 1702 m.a.s.l. This community is composed of plots dominated by
wild Coffea arabica and Nuxia congesta and Agarista salicifolia. The latter two species
were highly dominant in relatively open area of the Afromontane forest at the park .
Species in upper storey in this community include Syzygium guineense subsp.
afromontanum and Ilex mitis. Species in middle storey in this community include
Agarista salicifolia, Croton macrostachyus, Nuxia congesta, Schefflera volkensii,
Millettia ferruginea subsp. darassana, Apodytes dimidiata, Allophylus abyssinicus,
Ficus sur, Celtis africana, Macaranga capensis and Schefflera abyssinica. Species in
lower storey include Oxyanthus speciosus, Chionanthus mildbraedii, Coffea arabica,
Dracaena afromontana, Psychotria orophila, Maytenus gracilipes subsp. arguta,
Galiniera saxifrage, Maesa lanceolata, Rytigynia neglecta and Vepris dainellii.
Understory species in this community includes Oplismenus hirtellus, Setaria
megaphylla, Acanthopale pubescens, and Achyranthes aspera.
62
4.2.1.2 Ordination
Ordination describes environmental variable that control distribution of species in the
forest (Jongman et al., 1987). RDA was applied to determine environmental variables
which are responsible for the distribution of plant species in the forest and Adonis
permutation test to determine the statistical significance of the variables. RDA was
plotted using cover abundance values of plant species and significant (P ≤ 0.05)
environmental variables (Figure 14 and 15). Direction of arrow shows the gradient of
the environmental variable, and the length of the arrow shows its importance.
Figure 14. Constrained RDA for the plant communities at the Afromontane forest of
TBB, showing the relationships of environmental variables correlated (P ≤
0.05) with sites [numbers associated with environmental variables refer to the soil layer,
where, 1 is for top layer which ranges from 0 – 10 cm, 2 is for middle layer which ranges
from 10 – 20 cm and 3 is for lower layer which ranges from 20 – 50 cm]
63
Figure 15. Constrained RDA for the plant communities at the Afromontane forest of
CCNP showing the relationships of environmental variables correlated (P ≤
0.05) with sites
According to the result obtained from RDA analysis variables that showed significance
at p=0.05 at TBB are Elevation, P, OC, Silt, Na, pH, Clay, CEC, K, and N. Whereas
variables that showed significance at p=0.05 at CCNP are P, CEC, pH, Na, Elevation,
Clay, and OC. The significance of environmental variables at P=0.05 is given in Table
9 and Table 10 for TBB and CCNP respectively.
64
Table 9. Result of permutation test of environmental variables at TBB
Variable
Df Sums of Sqs.
PH.1
1
0.0668
PH.2
1
0.4245
PH.3
1
0.3882
OC.1
1
0.3278
OC.2
1
0.2496
OC.3
1
1.0173
N.1
1
0.4763
N.2
1
0.2368
N.3
1
0.0864
P.1
1
0.1408
P.2
1
0.6235
P.3
1
0.2022
CEC.1
1
0.1877
CEC.2
1
0.1675
CEC.3
1
0.1285
Na.1
1
0.0891
Na.2
1
0.0967
Na.3
1
0.2771
K.1
1
0.3687
K.2
1
0.1296
K.3
1
0.0964
Clay.1
1
0.1678
Clay.2
1
0.1098
Clay.3
1
0.2243
Sand.1
1
0.0955
Sand.2
1
0.1599
Sand.3
1
0.1444
Silt.2
1
0.1082
Silt.3
1
0.2461
Elevation
1
0.3234
Slope
1
0.1329
Aspect
1
0.1226
Disturbance
1
0.1646
Residuals
84 8.2824
Total
117 16.0631
Significance codes: ‘***’ 0.001
Mean Sqs.
0.06675
0.4245
0.38816
0.32776
0.24961
1.01731
0.47628
0.23683
0.08639
0.14078
0.62352
0.20222
0.18772
0.16748
0.12846
0.08909
0.09674
0.27712
0.36865
0.12963
0.09635
0.16777
0.1098
0.22427
0.09547
0.15991
0.14436
0.10816
0.24606
0.32343
0.13287
0.12264
0.16463
0.0986
F. Model
0.677
4.3053
3.9367
3.3241
2.5316
10.3176
4.8304
2.402
0.8762
1.4278
6.3238
2.0509
1.9039
1.6986
1.3029
0.9036
0.9811
2.8105
3.7389
1.3148
0.9772
1.7015
1.1136
2.2745
0.9683
1.6219
1.4641
1.0969
2.4956
3.2802
1.3476
1.2438
1.6697
R2
0.00416
0.02643
0.02416
0.0204
0.01554
0.06333
0.02965
0.01474
0.00538
0.00876
0.03882
0.01259
0.01169
0.01043
0.008
0.00555
0.00602
0.01725
0.02295
0.00807
0.006
0.01044
0.00684
0.01396
0.00594
0.00996
0.00899
0.00673
0.01532
0.02013
0.00827
0.00763
0.01025
0.51561
1
‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1
65
Pr(>F)
0.8
0.001 ***
0.001 ***
0.004 **
0.006 **
0.001 ***
0.001 ***
0.009 **
0.562
0.111
0.001 ***
0.019 *
0.039 *
0.079 .
0.196
0.537
0.444
0.004 **
0.001 ***
0.224
0.441
0.056 .
0.341
0.017 *
0.463
0.079 .
0.142
0.327
0.009 **
0.001 ***
0.185
0.253
0.052 .
Table 10. Result of permutation test of environmental variables at CCNP
Variable
Df Sums of Sqs.
PH.1
1 0.1757
PH.2
1 0.4033
PH.3
1 0.2257
OC.1
1 0.1826
OC.2
1 0.0705
OC.3
1 0.2854
N.1
1 0.1157
N.2
1 0.0838
N.3
1 0.1042
P.1
1 0.5355
P.2
1 0.0945
P.3
1 0.1592
CEC.1
1 0.2046
CEC.2
1 0.0972
CEC.3
1 0.1019
Na.1
1 0.2409
Na.2
1 0.1761
Na.3
1 0.0945
K.1
1 0.149
K.2
1 0.1227
K.3
1 0.1009
Clay.1
1 0.0309
Clay.2
1 0.1304
Clay.3
1 0.1858
Sand.1
1 0.0914
Sand.2
1 0.1272
Sand.3
1 0.0606
Elevation
1 0.3046
Slope
1 0.0303
Aspect
1 0.1605
Disturbance
1 0.0802
Residuals
29 2.2247
Total
60 7.1505
Significance codes: ‘***’ 0.001
Mean Sqs.
0.17572
0.40335
0.22568
0.18265
0.07048
0.2854
0.11569
0.08376
0.10418
0.53554
0.09446
0.15921
0.20457
0.09717
0.10187
0.24094
0.17612
0.09448
0.14895
0.12273
0.1009
0.0309
0.13039
0.18585
0.09138
0.12716
0.06065
0.30464
0.03034
0.16049
0.08023
0.07671
F. Model
2.2906
5.2579
2.9419
2.3809
0.9187
3.7203
1.5081
1.0918
1.3581
6.9812
1.2314
2.0754
2.6667
1.2667
1.3279
3.1408
2.2959
1.2316
1.9417
1.5998
1.3153
0.4027
1.6997
2.4226
1.1912
1.6576
0.7906
3.9712
0.3955
2.0921
1.0458
R2
0.02457
0.05641
0.03156
0.02554
0.00986
0.03991
0.01618
0.01171
0.01457
0.0749
0.01321
0.02227
0.02861
0.01359
0.01425
0.0337
0.02463
0.01321
0.02083
0.01716
0.01411
0.00432
0.01823
0.02599
0.01278
0.01778
0.00848
0.0426
0.00424
0.02244
0.01122
0.31112
1
‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1
66
Pr(>F)
0.047 *
0.002 **
0.017 *
0.038 *
0.435
0.003 **
0.176
0.325
0.191
0.001 ***
0.232
0.061 .
0.018 *
0.226
0.215
0.016 *
0.043 *
0.263
0.068 .
0.136
0.202
0.921
0.109
0.040 *
0.238
0.127
0.575
0.005 **
0.937
0.055 .
0.366
Importance of the constraining variables with their corresponding scores where axis
one is the most important in explaining variation of patterns in species composition,
and then variation explained by higher axes decreases successively (Kent and Cooker,
1992). Cumulative proportion of variance explained by the first six axes of the joint
plot in the constraining biplot at TBB and CCNP were 66.9 % and 47.1 % respectively.
From the cumulative proportion of variance explained by the first six axes, the
proportion of variation explained by the first two axes at TBB and CCNP were 60.68 %
and 66.94 % respectively. Constraining variables highly correlated with axis one
contributed more eigenvalues indicating that more variation was explained by these
constraining variables. The eigenvalue for axis one was the highest than the
eigenvalues of the remaining five axes. The constraining variables of all the significant
variables (p=0.05) are given in Table 11 and Table 12.
Table 11. Biplot scores for constraining variables at TBB
Variable
PH.2
PH.3
OC.1
OC.2
OC.3
N.1
N.2
P.2
P.3
CEC.1
Na.3
K.1
Clay.3
Silt.3
Elevation
Eigenvalue
Proportion Explained
Cumulative Proportion
RDA1
RDA2 RDA3 RDA4 RDA5 RDA6
0.399 -0.196 -0.056 -0.003 0.000 -0.126
0.110 -0.417 -0.180
0.274 -0.053 0.188
-0.133 0.001 -0.405 -0.196 0.198 -0.272
-0.084 0.343
0.015 -0.112 0.049 0.344
0.548 0.355
0.013
0.064 0.137 0.086
-0.469 0.019 -0.079 -0.078 -0.056 0.143
-0.315 0.095 -0.085
0.115 0.187 0.341
-0.142 0.659 -0.211
0.234 0.087 0.169
-0.134 0.635 -0.218
0.268 -0.030 0.281
-0.504 -0.112
0.033 -0.207 0.056 0.036
0.385 -0.057
0.215
0.171 -0.216 0.203
-0.767 -0.039
0.187
0.070 -0.100 0.014
-0.259 -0.245
0.443 -0.326 -0.254 -0.035
0.586 0.134 -0.287
0.305 0.022 0.113
0.364 0.739
0.058 -0.123 0.268 0.174
13.688 9.380
4.760
3.902 3.365 2.946
0.241 0.165
0.084
0.069 0.059 0.052
0.241 0.406
0.489
0.558 0.617 0.669
67
Table 12. Biplot scores for constraining variables at CCNP
Variable
PH.1
PH.2
PH.3
OC.1
OC.3
P.1
CEC.1
Na.1
Na.2
Clay.3
Elevation
Eigenvalue
Proportion Explained
Cumulative Proportion
RDA1 RDA2
0.074 -0.362
-0.356 -0.393
-0.061 -0.449
0.014 0.724
-0.032 0.378
-0.547 0.316
-0.295 -0.214
-0.247 -0.433
-0.098 -0.479
0.180 0.321
0.763 -0.073
32.573 11.882
0.231 0.084
0.231 0.315
RDA3
-0.156
-0.120
-0.025
0.098
0.221
-0.047
0.366
-0.084
-0.524
0.055
0.152
7.518
0.053
0.368
RDA4
-0.021
0.128
0.080
-0.161
0.029
-0.203
-0.147
0.016
0.280
-0.315
-0.136
5.769
0.041
0.409
RDA5
0.130
0.199
0.011
-0.296
-0.013
0.017
0.383
-0.036
0.210
0.206
-0.085
4.876
0.035
0.443
RDA6
-0.252
0.203
0.060
-0.041
0.120
0.077
-0.208
0.015
0.160
0.121
0.315
3.882
0.027
0.471
The constraining variable with the highest score associated to the first axes was
potassium (0.767) and elevation (0.763) in TBB and CCNP respectively. Potassium and
elevation were the most important variable in weighing axis one of the ordination at the
respective forests. Similarly, elevation was the most important constraining variable in
weighing axis two in TBB and Organic Carbon in CCNP with the biplot score of 0.739
0.724 respectively.
4.2.2 Diversity of Plant Communities
The Shannon–Wiener diversity indices of species for communities at the Afromontane
forest of TBB (Table 13) showed that, community 4 had the highest diversity followed
by communities 3, community 2 and community 1. Whereas, community 5 had the
lowest diversity compared to other communities in this Afromontane forest. The
species richness values among communities at the Afromontane forest of TBB were
almost comparable except for community 5, which had the least evenness value.
68
Table 13. Species richness, evenness, and diversity of the five plant communities of the
Afromontane forest of TBB
Communities
Richness (N)
Diversity (H’)
Evenness (E)
1
45
2.91
0.76
2
53
3.13
0.79
3
47
3.36
0.87
4
49
3.43
0.88
5
25
1.94
0.60
On the other hand, the Shannon–Wiener diversity indices of communities at the
Afromontane forest of CCNP (Table 14) showed that, community 1 had the highest
diversity followed by community 2. Whereas community 3 had, the least diversity
compared to the other two communities in this forest. Similarly, the species richness
values among communities at the Afromontane forest of CCNP were almost
comparable.
Table 14. Species richness, evenness, and diversity in the three plant communities of
the Afromontane forest of CCNP
Community
Richness (N)
Diversity (H’)
Evenness (E)
1
45
3.21
0.84
2
46
3.16
0.83
3
44
3.12
0.82
4.2.3 Plant Population Structure of the Afromontane forest of TBB and CCNP
Diameter and Height Class Distributions
The highest DBH recorded at the Afromontane forest of TBB was 239 cm for
Schefflera abyssinica followed by 191 cm and 182 cm for Prunus africana and
69
Juniperus procera respectively. Regarding the height measurement, the highest height
of a tree was recorded for Olea capensis subsp. macrocarpa (40 m) followed by
Pouteria adolfi–friederici (30 m) and Albizia gummifera (28 m).
In the patterns of distribution of individuals to DBH classes at the Afromontane forests
of TBB, the density of individuals of woody species gradually decreased from DBHclass 1 to DBH-class 10 and increased at DBH-class 11. The height-class distribution
of this forest showed similar pattern with DBH-classes distribution with slight
increment at height-class 8. Both the DBH-class (Figure 16) and Height-class (Figure
17) distributions of the forest showed an inverted J – shape pattern indicating that the
forest has a healthy growth pattern. Densities of each woody species to their DBH- and
Height-classes are presented in Annex 6 and Annex 7 respectively.
Figure 16. Distribution of individuals of woody species across DBH Class at the
Afromontane forest of TBB. (DBH-class 1 = 2.5 cm – 6 cm, 2 = 6 cm – 10 cm, 3 =
10 cm – 15 cm, 4 = 15 cm – 20 cm, 5 = 20 cm – 25 cm, 6 = 25 cm – 30 cm, 7 = 30 cm –
35 cm, 8 = 35 cm – 40 cm, 9 = 40 cm – 45 cm, 10 = 45 cm – 50 cm and 11 = > 50 cm).
70
Figure 17. Distribution of individuals of woody species across Height Class at the
Afromontane forest of TBB (height-class 1 = 2 m – 5 m, 2 = 5 m – 8 m, 3 = 8 m – 11
m, 4 = 11 m – 14 m, 5 = 14 m – 17 m, 6 = 17 m – 20 m, 7 = > 20 m).
On the other hand, the highest DBH recorded in CCNP was for Albizia gummifera,
which was 223 cm, followed by Olea capensis subsp. macrocarpa (105 cm) and
Pouteria adolfi-friederici (74 cm). Regarding height measurement, the highest height
was recorded for Albizia gummifera (35 m) followed by Apodytes dimidiata (28 m) and
Ilex mitis (20 m). Both the DBH-class (Figure 18) and Height-class (Figure 19)
distributions of the Afromontane forest of CCNP showed an inverted J – shape pattern
with the density of varies at each DBH- and Height- classes.
71
Figure 18. Distribution of individuals of woody species across DBH Class at the
Afromontane forest of CCNP
Figure 19. Distribution of individuals of woody species across Height Class at the
Afromontane forest of CCNP
The density of individuals of woody species along DBH class gradually decreased from
DBH-class 1 to DBH-class 10 and gradually increased at DBH-class 11 showing an
inverted J– shape type. Similarly the pattern in height-class distribution was an inverted
72
J– shape with slight increment at height-class 8. Densities of woody species with
respect to DBH- and Height-classes of the Afromontane forest of CCNP are given in
Annex 8 and Annex 9 respectively.
Patterns of Population Structure of the Afromontane forests of TBB and CCNP
The diameter and height-class distribution patterns show trends of population change
and recruitment processes of plants in a forest (Larsen and Bliss, 1998). Three and four
main patterns of population structures of woody plant species were obtained from
diameter-class distribution at the Afromontane forest of TBB (Figure 20) and CCNP
(Figure 21) respectively.
The first pattern of population structure of woody species at the Afromontane forest of
TBB is represented by Podocarpus falcatus. It approaches an inverted J–shape pattern.
In this distribution pattern, species density distribution was the highest in the lower
diameter classes and showed gradual decrease towards the higher diameter classes with
further increase at diameter-class 11. Species included in this group are Ilex mitis,
Psychotria orophila, and Pouteria adolfi–friedrici. The second pattern is represented
by Olea capensis subsp. macrocarpa. In this pattern, species density distribution was
becoming increasing from diameter-class 1 to diameter-class 2 and then decreases with
increasing diameter up to diameter-class 10. It showed further increase at diameterclass 11. Ficus sur, Syzygium guineense, and Olinia rochetiana are species with the
same distribution pattern. The third pattern is an undulating pattern, in which species
density distribution shows alternation of increase and decrease in consecutive diameter
classes. This pattern is represented by Macaranga capensis.
73
Figure 20. Structure of selected woody species with regard to DBH at the Afromontane
forest of TBB
However, the first pattern of population structure of woody species at the Afromontane
forest of TBB is represented by Albizia gummifera. It showed an inverted–J shaped pattern
interrupted at diameter-class 4. In this pattern, density of woody species at DBH-class 4
showed remarkable decrease from its neighboring diameter classes. The second diameterclass distribution pattern is represented by Agarista salicifolia. It showed a bell–shaped
pattern interrapted at diameter-class 4, 6 and 8. In these diameter classes density of woody
species showed remarkable decrease from their neighboring diameter classes. The third
diameter-class distribution pattern is represented by Syzygium guineense. In this pattern,
species density distribution increased from diameter-class 1 to diameter-class 2 and then
decreases with increasing diameter up to diameter-class 9. In addition, a further increase
was observed at diameter-class 11. The forth diameter-class distribution pattern is
74
represented by Prunus africana. It is U–shaped pattern having high density at diameterclass 1 and 11, with slight interruption in middle diameter-classes.
Figure 21. Structure of selected woody species with regard to DBH at the Afromontane
forest of CCNP
On the other hand, the distribution of woody species at the Afromontane forest of TBB
(Figure 22) and CCNP (Figure 23) showed two and four types of height-class
distribution patterns respectively. The first pattern at the Afromontane forest of TBB,
represented by Syzygium guineense, showed an inverted J–shape pattern. In this pattern,
density of species at the first height-class was the highest and it decreases in the
subsequent height-classes. Chionanthus mildbraedii, Pouteria adolfi-friederici and
Podocarpus falcatus showed this pattern. The second pattern is represented by
Macaranga capensis, where the species density distribution was becoming increasing
75
from height-class 1 to height-class 2 and then decreases gradually in subsequent heightclasses. Ficus sur, Olea capensis subsp. macrocarpa and Macaranga capensis are
species showing this distribution pattern.
Figure 22. Structure of selected woody species with regard to Height at the
Afromontane forest of TBB
Whereas the pattern at the Afromontane forest of CCNP, a bell–shaped pattern is
represented by Croton macrostachyus. In this pattern, species density distribution
showed increases from height-class 1 to height-class 3 and showed gradual decrease to
height-class 5. The second height-class distribution pattern, an inverted–J pattern is
represented by Albizia gummifera. In this pattern density of species was highest at the
first height-class and decreasing in the subsequent height-classes. The third height-class
distribution pattern, a zigzag height-class distribution pattern is represented by Pouteria
adolfi–friedricii. In this pattern, density of species showed gradual decreases from
height-class 1 to height-class 4. It then showed an increase in density in height-class 5
and showed gradual decrease afterwards. The forth height-class distribution pattern, an
irregular height-class distribution pattern is represented by Ilex mitis. In this pattern,
density of species showed an increase in density from height-class 1 to height-class 2. It
then showed decrease in density at height-class 3 followed by slight increase at height-
76
class 4. The density was then decreased at height-class 5 followed by slight decreases at
consecutive height-classes.
Figure 23. Structure of selected woody species with regard to Height at the
Afromontane forest of CCNP
Density of Woody Species
Density of woody species at the Afromontane forest of TBB and CCNP were 1902
stems.ha–1 and 1562 stems.ha–1 respectively. The density of woody species at the
Afromontane forest of TBB with DBH higher than 10 cm (a) and DBH higher than 20
cm (b) were 678 stems.ha–1 and 366 stems.ha–1 respectively with the ratio (a/b) of 1.9.
Whereas the density of woody species at the Afromontane forest of CCNP with DBH
higher than 10 cm (a) and DBH higher than 20 cm (b) were 570 stems.ha–1 and 269
77
stems.ha–1 respectively, and their ratio (a/b) is 2.1. Density, Basal area, Frequency, and
IVI for woody species recorded at the Afromontane forest of TBB and CCNP are given
in Annex 10 and 11 respectively.
Importance Value Index (IVI)
Ten most important woody species with IVI higher than 8 at the Afromontane forest of
TBB is presented in Table 15.
Table 15. Importance Value Index of woody species with DBH ≥2.5 cm at TBB
No.
Plant Species
IVI
%
1
Olea capensis subsp. macrocarpa
28.63
9.54
2
Syzygium guineense subsp. afromontanum
28.43
9.48
3
Pouteria adolfi–friederici
16.54
5.51
4
Podocarpus falcatus
14.07
4.69
5
Chionanthus mildbraedii
13.81
4.60
6
Olinia rochetiana
11.16
3.72
7
Macaranga capensis
9.75
3.25
8
Ficus sur
9.39
3.13
9
Psychotria orophila
8.88
2.96
10
Ilex mitis
8.73
2.91
149.39
49.80
Sum
Olea capensis subsp. macrocarpa had the highest IVI followed by Syzygium guineense
subsp. afromontanum. Those ten species totally account for 49.80 % of the total IVI.
Similarly, ten most important woody species of the Afromontane forest of CCNP with
IVI higher than 10 was presented in Table 16. Syzygium guineense subsp.
afromontanum had the highest IVI followed by prunus africana and Oxyanthus
speciosus. Those ten species totally account for 49.2 % of the total IVI.
78
Table 16. Importance Value Index of woody species with DBH ≥2.5 cm at CCNP
No.
Plant Species
IVI
%
1
Syzygium guineense subsp. afromontanum
24.31
8.10
2
Prunus africana
15.84
5.28
3
Oxyanthus speciosus
15.05
5.02
4
Chionanthus mildbraedii
14.88
4.96
5
Ilex mitis
14.48
4.83
6
Schefflera abyssinica
14.31
4.77
7
Dracaena afromontana
14.18
4.73
8
Ficus sur
12.73
4.24
9
Psychotria orophila
11.09
3.70
10
Pouteria adolfi–friederici
10.74
3.58
Sum 147.61
49.20
Basal area
Basal area of woody species at the Afromontane forests of TBB and CCNP are 72.98
m2ha–1 and 73.81 m2ha–1 respectively. From the total individuals of woody species
obtained from the Afromontane forest of TBB, 4.46 % attained DBH greater than 50
cm. The higher DBH-class was occupied by 25 woody plant species, of which
Syzygium guineense had the highest density (20.67 %) followed by Olea capensis
subsp. macrocarpa (16.56 %) and Pouteria adolfi–friedrici (9.44 %). The remaining 22
woody plant species were accounting for 53.33 % of the total density at DBH-class 11.
These species showed low recruitments and their contribution of total density was
minimal.
On the other hand, only 6.22 % individuals of woody species attained DBH greater
than 50 cm at the Afromontane forest of CCNP. The higher DBH-class was occupied
by 20 woody plant species of which Prunus africana had the highest density (15.38 %)
79
followed by Ilex mitis (13.13 %), Syzygium guineense (12.57 %) and Ficus sur (11.26).
The remaining 16 woody plant species together accounted for 47.65 % of the total
density at DBH-class 11. The 16 woody plant species accounting for 47.65 % of the
total density at DBH-class 11 had low recruitments and low contribution to the total
density in the forest. Distribution of basal area across DBH-classes for TBB and CCNP
are presented in Figure 24 and Figure 25 respectively.
Figure 24. Distribution of Basal area across DBH classes at the Afromontane forest of
TBB
Figure 25. Distribution of Basal area across DBH classes at the Afromontane forest of
CCNP
80
Vertical Structure of the Forest
Since the tallest tree at the Afromontane forest of TBB was Olea capensis subsp.
macrocarpa (40 m), trees with height higher than 26.6 m were grouped into the upper
storey, between 13.3 m and 26.6 m were grouped into middle storey and trees with
height lower than 13.3 m were grouped into lower storey (Table 17). The three species
occupying the upper storey at TBB were Albizia gummifera (7.69 %), Olea capensis
subsp. macrocarpa (38.46 %), and Pouteria adolfi–friederici (53.85 %).
Table 17. Density, number of species, and ratios of individuals to species by storey at
the Afromontane forest of TBB
Density
Ratio of ind. ha–1
No of
(Ind. ha–1)
%
species
%
to species
Upper
1.22
0.06
3
4.00
0.41:1
Middle
94.73
4.98
25
33.33
3.79:1
Lower
1805.84
94.95
74
98.67
24.40:1
Story
Whereas the tallest tree at the Afromontane forest of CCNP was Albizia gummifera (35
m). Trees with height higher than 23.3 m were grouped into upper storey, trees with
height between 11.6 m and 23.3 m were grouped into middle storey and trees with
height lower than 11.6 m were grouped into lower storey (Table 18). The highest
density of stems was measured from the lower storey and the lowest density of stems
was measured from the upper storey. Similarly, more species were found in the lower
storey followed by the middle storey. The upper story had a least number of species
when compared to the middle story and the lower storey. The two species occupying
the upper storey at the Afromontane forest of CCNP were Albizia gummifera (97.30 %)
and Apodytes dimidiata (2.70 %).
81
Table 18. Density, number of species, and ratios of individuals to species by storey at
the Afromontane forest of CCNP
Density
Ratio of ind. ha–1
No of
(Ind. ha–1)
%
species
%
to species
6.73
0.43
2
7.41
3.37:1
Middle
105.84
6.78
7
25.93
15.12:1
Lower
1449.36
92.79
27
100
53.68:1
Story
Upper
4.2.5 Regeneration Status of Montane Forests at TBB and CCNP
54 and 58 species were recorded at the Afromontane forest of TBB as seedlings and
saplings respectively with their corresponding density of 735.3 stems.ha–1 and 1558.4
stems.ha–1. On the other hand, 41 species were recorded at the Afromontane forest of
CCNP as both seedlings and saplings with seedlings and saplings density of 1005.3
stems.ha–1 and 755.7 stems.ha–1 respectively. A complete record of seedlings and
saplings recorded at the Afromontane forests of TBB and CCNP are presented in
Annex 12 and Annex 13.
82
4.3 Land use/Land cover Change
Landsat satellite images of the year 1984, 2000, and 2015 were used for the
applications of image processing and classification at both TBB and CCNP. Four major
LU/LC types were identified in TBB. These are (i) Forest, (ii) Woodland, (iii)
Shrub/Bushland, and (iv) Agriculture and settlement (Figure 26).
The LU/LC classification of the year 1984 at TBB indicates that the greatest share of
the total LU/LC area was from forest, which covered an area of 26384.40 ha (65.10 %).
The land covered by Shrub/Bushland and Woodland were 6470.19 ha (15.97 %) and
5300.01 ha (13.08 %) respectively. Whereas, land covered by Agriculture and
settlement was 2373.48 ha (5.86 %).
For the LU/LC of the year 2000 at TBB, the highest share of the total LU/LC area was
from Forest, which was 29461.14 ha (72.69 %) followed by Agriculture and settlement
which covered 4228.02 ha (10.43 %). Land covered by Woodland and Shrub/Bushland
were 3703.50 ha (9.14 %) and 3135.42 ha (7.74 %) respectively.
Result from the LU/LC classification at TBB for the year 2015 shows that the greatest
portion of the total LU/LC area was covered by Forest, an area of 21070.44 ha (51.99
%) followed by Agriculture and settlement which was 8623.62 ha (21.28 %). LU/LC
area for Shrub/Bushland and Woodland were 7950.06 ha (19.62 %) and 2883.96 ha
(7.12 %) respectively.
83
Figure 26. LU/LC map of TBB for the year 1984, 2000, and 2015
84
Regarding CCNP, five major LU/LC types were identified. These are: (i) Forest, (ii)
Woodland, (iii) Grassland, (iv) Agriculture and Settlement, and (v) Water body
(Figure 27).
LU/LC classification from the year 1984 indicates that the greatest portion of the total
LU/LC area was from Woodland, which covered an area of 46912.00 ha (38.61 %).
Grassland and Forest covered an area of 37688.22 ha (31.02 %) and 36114.56 ha
(29.72 %) respectively, whereas land covered by Agriculture and Settlement was
335.01 ha (0.28 %) and land covered by Water body was 457.32 ha (0.38 %).
Unlike the LU/LC of the year 1984 at CCNP, the LU/LC classification at CCNP for
the year 2000 showed that the greatest share of the total LU/LC area was from
Grassland, which covered an area of 45814.43 ha (37.71 %) followed by Woodland,
covering an area of 39012.11 ha (32.11 %). The Forest cover of the area was
35412.68 ha (29.14 %) and that of Agriculture and Settlement was 809.18 ha (0.67 %)
of the total area. Whereas land covered by Water body was 458.80 ha (0.38 %).
Similarly, results from the LU/LC classification of the year 2015 shows that the
greatest share of the total LU/LC area was from Grassland, which covered an area of
53896.93 ha (44.36%) followed by Forest, covering an area 34038.23 ha (28.01 %) of
the total land of the study area. Woodland covered an area of 25302.75 ha (20.82 %).
Agriculture and Settlement covered an area of 7809.14 ha (6.43 %). Whereas, land
covered by Water body was 460.15 ha (0.38 %).
85
Figure 27. LU/LC map of CCNP for the year 1984, 2000, and 2015
86
Classification Accuracy
Classification accuracy assessment results for the 2015 classified images of TBB and
CCNP are given in Table 19 and Table 20 respectively. The matrices indicate the nature
of the classification error made during the assignment of LU/LC classes. The accuracy
assessment was done based on pixel–by–pixel comparison and the data/number presented
in the matrices is a pixel count assigned to the corresponding LU/LC class. Hence, the
overall accuracy of the LU/LC classification at TBB was 96.09 % while the kappa
coefficient of the classification was 0.90. Whereas the overall accuracy of the LU/LC
classification at CCNP was 90.66 % while the kappa coefficient of the classification was
0.92.
Table 19. Classification accuracy for 2015 classified images of TBB.
LU/LC Class
Fr
Wd
Sh/Bu
Ag & Se
Class Total
Fr
4014
2
4
0
4020
Wd
8
157
11
0
176
147
36
922
1
1106
0
0
3
116
119
4169
195
940
117
5421
Sh/Bu
Ag & Se
Class Total
Fr= Forest, Wd= Woodland, Sh/Bu= Shrub/Bushland, Ag & Se= Agriculture & Settlement
87
Table 20. Classification accuracy for 2015 classified images of CCNP
Class
Fr
Wd
Gr
Ag & Se
Wa
Class Total
Fr
15505
10
228
0
0
15743
Wd
40
875
562
8
0
1485
Gr
2
2
28889
1
0
28894
Ag & Se
3
62
161
30
0
256
Wa
0
0
34
0
90
124
15550
949
29874
39
90
46502
Class Total
Fr= Forest, Wd= Woodland, Gr= Grassland, Ag & Se= Agriculture & Settlement, Wa= Water body
4.4 Change Detection of LU/LC
The change detection given in Table 21, Table 22, and Table 23 show area of both
unchanged and changed LU/LC types in TBB from the year 1984 to 2000, 2000 to 2015,
and 1984 to 2015 respectively.
88
Table 21. LU/LC change at TBB from the year 1984 to 2000
2000
LULC Class
Area
Fr
1984
ha
Wd
Sh/Bu
Ag & Se
Class Total
%
ha
%
ha
%
ha
%
ha
%
Fr
23456.16 88.90
1310.76
4.97
1182.51
4.48
434.97
1.65
26384.4
65.10
Wd
2847.78 53.73
1227.69 23.16
607.77 11.47
616.77 11.64
5300.01
13.08
Sh/Bu
2381.31 36.80
964.71 14.91
1043.19 16.12
2080.98 32.16
6470.19
15.96
301.95 12.72
1095.3 46.15
2373.48
5.86
Ag & Se
Class Total
775.89 32.69
200.34
8.44
29461.14 72.69
3703.5
9.14
Class change
6004.98 20.38
Image difference
3076.74
3135.42
2475.81 66.85
-1596.51
7.74
4228.02 10.43
2092.23 66.73
3132.72 74.09
-3334.77
Fr= Forest, Wd= Woodland, Sh/Bu= Shrub/Bushland, Ag & Se= Agriculture & Settlement
89
1854.54
40528.1 100.00
0.00
0.00
Table 22. LU/LC change at TBB from the year 2000 to 2015
2015
LULC Class
Area
Fr
ha
Sh/Bu
%
ha
%
19142.64 64.98
2340.36
Wd
818.46 22.10
Sh/Bu
875.43 27.92
Ag & Se
233.91
Fr
2000
Wd
Class Total
Class Total
%
ha
%
ha
%
7.94
5303.25 18.00
2674.89
9.08
29461.1
72.69
328.5
8.87
1195.2 32.27
1361.34 36.76
3703.5
9.14
142.47
4.54
728.1 23.22
1389.42 44.31
3135.42
7.74
5.53
72.63
1.72
723.51 17.11
3197.97 75.64
4228.02
10.43
21070.44 51.99
2883.96
7.12
7950.06 19.62
8623.62 21.28
40528.1 100.00
2555.46 88.61
7221.96 90.84
5425.65 62.92
-819.54
4814.64
Class change
1927.8
Image change
-8390.7
9.15
ha
Ag & Se
Fr= Forest, Wd= Woodland, Sh/Bu= Shrub/Bushland, Ag & Se= Agriculture & Settlement
90
4395.6
0.00
0.00
Table 23. LULC change at TBB from the year 1984 to 2015
2015
Area
LULC Class
Fr
1984
ha
Wd
Sh/Bu
%
ha
%
Fr
19108.6 72.42
1913.58
Wd
1126.89 21.26
Sh/Bu
Ag & Se
Class Total
Class change
Image difference
Class Total
%
ha
%
ha
%
7.25
3658.68 13.87
1703.52
6.46
26384.4
65.10
530.28 10.01
1727.91 32.60
1914.93 36.13
5300.01
13.08
371.25
5.74
1895.49 29.30
3552.12 54.90
6470.19
15.96
7.74
68.85
2.90
667.98 28.14
1453.05 61.22
2373.48
5.86
21070.4 51.99
2883.96
7.12
7950.06 19.62
8623.62 21.28
40528.1 100.00
2353.68 81.61
6054.57 76.16
7170.57 83.15
1479.87
6250.14
651.33 10.07
183.6
1961.8
-5314
9.31
ha
Ag & Se
-2416.05
Fr= Forest, Wd= Woodland, Sh/Bu= Shrub/Bushland, Ag & Se= Agriculture & Settlement
91
0.00
0.00
Area of changed and unchanged LU/LC types in CCNP from the year 1984 to 2000,
2000 to 2015, and 1984 to 2015 are given in Table 24, Table 25, and Table 26
respectively.
92
Table 24. LULC change at CCNP from the year 1984 to 2000
2000
LULC Class
Area
Fr
Ha
1984
Fr
Wd
Gr
Ag & Se
Wa
Class Total
%
Ha
%
ha
%
ha
%
ha
%
ha
%
35285.94 97.71
510
1.41
127.02
0.35
191.69
0.53
0
0.00
36,114.65
29.72
8129.3 17.33
312.01
0.67
0
0.00
46,912.00
38.61
37538.48 99.60
3.1
0.01
1.48
0.00
37,689.22
31.02
302.38 90.26
0
0.00
335.01
0.28
457.32
0.38
Wd
65.48
0.14
Gr
50.26
0.13
95.9
0.25
11
3.28
2
0.60
19.63
5.86
0
0.00
0
0.00
0
0.00
0
0.00
457.32 100.00
45,814.43 37.70
809.18
0.67
458.80
0.38
8,275.95 18.06
506.80 62.63
1.48
0.32
8,125.21
474.17
1.48
Ag & Se
Wa
Class Total
35,412.68 29.14
Class change
126.74
Image change
-701.97
0.36
38405.21 81.87
39,013.11 32.11
607.90
-7,898.89
1.56
Fr= Forest, Wd= Woodland, Gr= Grassland, Ag & Se= Agriculture & Settlement, Wa= Water body
93
121,508.20 100.00
0.00
0.00
Table 25. LULC change at CCNP from the year 2000 to 2015
2015
LULC Class
Area
Fr
Ha
2000
Fr
Wd
Gr
Ag & Se
Wa
Class Total
%
Ha
%
ha
%
ha
%
ha
%
ha
%
34013.76 96.05
115.48
0.33
180
0.51
1103.44
3.12
0
0.00
35,412.68
29.14
5871.02 15.05
0
0.00
39,012.11
32.11
0.08
1.35
0.00
45,814.43
37.71
797.61 98.57
0
0.00
809.18
0.67
458.8 100.00
458.8
0.38
Wd
16.03
0.04
Gr
5.24
0.01
10.56
0.02
3.2
0.40
1.45
0.18
6.92
0.86
0
0.00
0
0.00
0
0.00
0
0.00
53,896.93 44.36
7,809.14
6.43
460.15
0.38
8,136.81 15.10
7,011.53 89.79
1.35
0.29
8,082.50
6,999.96
1.35
Ag & Se
Wa
Class Total 34,038.23 28.01
Class change
Image change
24.47
-1,374.45
0.07
25175.17 64.53
25,302.66 20.82
127.49
-13,709.45
0.50
7949.89 20.38
45760.12 99.88
Fr= Forest, Wd= Woodland, Gr= Grassland, Ag & Se= Agriculture & Settlement, Wa= Water body
94
37.07
121,507.20 100.00
0.00
0.00
Table 26. LULC change at CCNP from the year 1984 to 2015
2015
LULC Class
Area
Fr
Ha
1984
Fr
Wd
Gr
Ag & Se
Wa
Class Total
%
Ha
%
ha
%
ha
%
ha
%
ha
%
34005.23 94.16
203.70
0.56
111.81
0.31
1793.91
4.97
0.00
0.00
36114.65
29.72
5671.02 12.09
0.00
0.00
46912.00
38.61
0.07
2.83
0.01
37688.22
31.02
315.99 94.32
0.00
0.00
335.01
0.28
457.32
0.38
Wd
20.43
0.04
Gr
7.35
0.02
4.20
0.01
Ag, & Se
5.22
1.56
2.10
0.63
11.70
3.49
Wa
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
457.32 100.00
53896.93 44.36
7809.14
6.43
460.15
0.38
16,251.31 30.15
7,493.15 95.95
2.83
0.62
16,208.71
7,474.13
2.83
Class Total
Class change
Image change
34038.23 28.01
33.00
-2,076.42
0.10
25092.75 53.49
25302.75 20.82
210.00
-21,609.25
0.83
16127.80 34.38
37645.62 99.89
Fr= Forest, Wd= Woodland, Gr= Grassland, Ag & Se= Agriculture & Settlement, Wa= Water body
95
28.22
121507.20 100.00
0.00
0.00
4.5 Rate of LC/LC Changes
There were variations among the rate of changes in the LU/LC types at TBB and
CCNP in various periods under study. In the entire study period (from year 1984 to
2015), Forest cover was changed from 26384.40 ha to 21070.44 ha at a rate of 171.42
ha per year. Woodland cover was also changed from 5300.01 ha to 2883.96 ha at a
rate of 77.94 ha per year. However, Shrub/Bushland cover was changed from 6470.19
ha to 7950.06 ha at a rate of 47.74 ha per year. Agriculture and Settlement were
changed from 2373.48 ha to 8623.62 ha at a rate of 201.62 ha per year. The rate of
change of LU/LC types at TBB is given in Figure 28.
Figure 28. Annual Rate of Land Use/Land Cover change in TBB from 1984 to 2000,
from 2000 to 2015, and from 1984 to 2015
96
In CCNP, Forest cover was changed from 36114.65 ha to 34038.23 ha from year 1984
to 2015, at a rate of -66.98 ha per year. Woodland cover was changed from 46912.00
ha to 253.2.75 ha at a rate of -697.07 ha per year. Grassland cover was changed from
37688.22 ha to 45814.43 ha at a rate of 522.86 ha per year. Agriculture Settlement
were changed increased from 335.01 ha to 7809.14 ha at a rate of 241.10 ha per year.
Change in the water body was also detected from 457.32 ha in 1984 to 460.15 ha in
2015 at a rate of 0.09 ha per year. The rate of change of LU/LC types at CCNP is
given in Figure 29.
Figure 29. Annual Rate of Land Use/Land Cover change in CCNP from 1984 to 2000,
from 2000 to 2015, and from 1984 to 2015
97
4.6 Summary of Results of Key Informant Interviews and Focus Group
Discussions
Among the main economic activities in TBB and CCNP, Agriculture was the first
followed by petty trade and employment (permanent employment in OFWE and
contract as daily laborer). In addition, some people living around the park hunt small
wild animals for food. It was reported that human population of local community
around forest in both study areas were increasing from time to time. As a result the
demand for agriculture and land for house construction is increasing. This demand
was usually fulfilled through conversion of forested areas. Most households living in
the study area own land used for agriculture and house construction. Only few
households in TBB, who own land were planted woodlots in their plots. None of the
households living inside or around CCNP were planted trees for their consumption.
They simply collect from the forest inside or around the park.
People living adjacent to the forest uses the forest as source of firewood, timber for
house construction, source of non timber products such as honey, spices and Rhamnus
prinoides. It was also mentioned that the forest is serving as important source water
for the communities. Some individuals also benefit from employment in OFWE and
CCNP as guard/scout. The local people were claimed that the natural forest cover in
the study area was decreased comparing to the condition of 30 years ago.
There was no direct involvement of community in forest ownership, management, and
legal utilization of forest timber products. They suggested participatory or joint forest
management as an option for better forest nagement.
98
4.7 Causes of LU/LC Changes
According to the data obtained from focus group discussions (FGDs) carried out in
Tiro and Boter Becho, farmlands and settlement areas has been increasing from time
to time because of growing population in the area. Oromia Forest and Wildlife
Enterprise (OFWE), governmental owned enterprise, was engaged in production and
sale of timber from plantations in Tiro and Boter Becho District Offices. The
enterprise was planting seedlings of exotic plant species such as Cupressus and Pinus
trees for commercial use. Timber was produced from these plant species to satisfy
timber demand of the country.
Frequent fire hazard has been recognized in TBB as a factor that caused forest
destruction in forest located at both higher and lower altitude of the study area taking
forest fire incidents occurred in 2008 and 2012 as evidence. These fire incidences
caused damage on natural forest. As forest fire in TBB was human induced element,
effort has been made to distinguish the origin of the incident during the focus group
discussion. They pointed out that honey collection in forest and sudden fire from
farmlands was the main causes for forest fire incidence. The local communities living
in the area adjacent to the forest are solely dependent on biomass energy for their
energy source (for cooking and heating). As a result, they extract fuelwood and make
charcoal from nearby forest. In addition, forest clearance for agricultural purpose,
wood extraction, cutting of trees to extract honey, and debarking of few trees of
Ekebergia capensis beehive fumigation, and cattle grazing inside the forest were
observed (Figure 30 and 31).
99
Figure 30. Partial view of threat to the Afromontane forest of TBB
Based on data obtained during FGD carried out with local communities living
adjacent to CCNP and KII with park authorities, settlements have taken place outside
the park boundary (i.e. in 1996 and 2002 before the establishment of the park). This
settlement resulted in increase in human population in the area, and now causing
impacts on the park (farmland expansion, setting fire to the grass in the park, and
hunting wild animals for food, hide, and Elephant tusks). During dry season, both
natural and manmade fire was common phenomenon, taking place in the lowland
areas of CCNP. Manmade fire was an intentional activity takes place almost every
year to initiate the emergence of new grass for their livestock. Similar to communities
in TBB, the local communities living adjacent to the forest in CCNP are solely
dependent on biomass energy for their energy consumption in the form of fuel–wood
and charcoal. In addition, it was observed that cattle are grazing inside the park. Trees
100
were cut down for their timber and fuelwood, and small area of woodland in the park
was cleared for agriculture (Figure 31).
Figure 31. Partial view of threat to the Afromontane forest of CCNP
Efforts have been made by OFWE to conserve the remaining natural forest of
Afromontane forest of TBB thorough nursery establishment, seedling plantation, and
buffer zone establishment around to the natural forest (Figure 32).
101
Figure 32. Partial view Nursery site and plantation of Cupresus as a buffer to the
natural forest in TBB
Similarly, some conservation measures were carried out to protect the forest and wild
animals of the CCNP. Undertaking regular education (awareness creation) programs
to people inside and around the park to improve attitude of the local people residing
the CCNP could be mentioned as evidence. The park management has also started
negotiation to voluntarily relocate people who are living inside the park.
102
CHAPTER FIVE
5. DISCUSSION
5.1 Floristic Diversity and Composition
Afromontane forests are home for wide range of plant species. Floristically the
Afromontane forests of TBB and CCNP are rich in plant species. Several studies on
Afromontane forests have been conducted in different parts of the country to
determine the floristic composition and diversity of plant. Although comparison of the
species richness in various studies using statistical analyses is not feasible due to
differences in size of the forests, survey methods, and objectives of the study.
However, the overall species richness of the forests may give a general impression of
their floristic diversity (Tadesse Woldemariam, 2003). Hence, one can understand
that, with 204 plant species, Afromontane forest of TBB excels other similar
rainforests like Harenna forest in southeast Ethiopia (160 species; Kumlachew
Yeshitila, 1997), Komto forest in east Wellega (180 species; Fekadu Gurmessa et al.,
2013), Guraferda in southwestern Ethiopia (196 species; Dereje Denu, 2007), Sigmo–
Setema in southwestern Ethiopia (196 species; Alemu Abebe, 2007), and Gara Ades
forest in southeastern Ethiopia (124 species; Uhlig and Uhlig, 1990). Whereas the
Afromontane forest of TBB had lower species record than those reported for the
vegetation of the Gambella region in southwestern Ethiopia. i.e. 220 species (Tesfaye
Awas et al., 2001), Bonga forest in southwest Ethiopia (243 species; Ensermu
Kelbessa and Teshome Soromessa (2008), and Yayu forest in southwest Ethiopia (220
species; Tadesse Woldemariam et al., 2008). However, floristically, the Afromontane
forest of CCNP had lower species record than the Afromontane forests mentioned
earlier.
103
From plant families recorded in the study area, family Asteraceae had the highest
species record compared to other families in the study areas. This might be due to the
evolutionary characteristics of the family. It is known that family Asteraceae is an
exceedingly large and widespread family of flowering plants. It exhibit extensive
morphological and ecological diversity. Asteraceae was the family with highest
number of species in studies of Ermias Lulekal et al. (2008) and Haile Yineger et al.
(2008). Regarding habits of species identified, largest number of species was
described as tree/shrub, followed by herbs, trees and shrubs. Whereas in CCNP,
shrubs were the highest followed by herbs.
Afromontane rain forests of Ethiopia are known to be home for various endemic and
indigenous plant species (Mesfin Tadesse, 1991). In addition to the diversity in plant
species, the Afromontane forests of TBB and CCNP are important forests with respect
to their endemicity. Comparing the endemicity to Dry Afromontane forests and other
Moist Afromontane forests in Ethiopia, 29 endemic species were recorded at Wof–
Washa forest (Demel Teketay and Tamrat Bekele, 1995), 14 endemic species were
recorded at Sheko forest (Feyera Senbeta et al., 2007), 17 endemic species were
recorded at Harenna forest, 14 endemic species were recorded at Berhane–Kontir, 14
endemic species were recorded at Bonga, 7 endemic species were recorded at Yayu,
and 4 endemic species were recorded at Maji (Feyera Senbeta, 2006). The current
study areas have 12 and 6 endemic plant species respectively.
Compared to endemicity to above mentioned forests, TBB had more endemic plant
species than Maji, Yayu and CCNP. Whereas the Afromontane forest of CCNP had
more endemic plant species diversity than Maji forest. The Afromontane forest of
TBB had less endemic plant species diversity when compared to Wofwasha, Harenna,
104
Bonga, Berhane–Kontir and Sheko forests. Similarly, the Afromontane forest of
CCNP had less endemic plant species than Wofwasha, Harenna, Bonga, Berhane–
Kontir, Yayu and Sheko forests. Friis et al. (2001) described that, low diversity of
endemic plant species is a common feature of moist montane rain forests of southwest
Ethiopia. Endemism is high in dry Afromontane forests and grassland complex than
moist Afromontane forests (Sebsebe Demissew et al., 1996). Low endemicity in a
given forest also associated to low diversity of environmental gradients and associated
vegetation isolation (Kruckeberg and Rabinowitz, 1985).
5.2 Plant Community Structure
Plant species tend to occur together share certain environmental requirements (Keddy,
1982; Snow and Vince, 1984; Ellison et al., 2000). Variations in environmental
conditions of the area might to be responsible for plant species richness and changes
in plant species composition of vegetation. In cluster analysis, five and three plant
communities were identified in TBB and CCNP respectively.
Plant communities are collections of the plant species that are growing together in a
particular location and show definite association or affinity with each other (Kent and
Cooker, 1992). According to Snow and Vince (1984), distribution of plant species
along environmental gradient arises as a result of physiological restriction of species
to different portion of gradients. Environmental variables show strong correlation
with species performance in some areas and none in others depending on a change in
the limiting factor for plant growth or altering the correlation of the limiting factor
with other environmental variables. Accordingly, from RDA analysis, the
constraining variable highly correlated with axis one in TBB was potassium. Silt and
Organic Carbon to a lesser extent were correlated to axis one. In CCNP, Elevation
105
was the most constraining variable followed by Phosphorus and pH. Among the
constraining variables, Potassium and Elevation in particular, contributed significantly
in explaining pattern of variation in the species distribution and type of plant
community formation in TBB and CCNP respectively. Potassium might have a major
impact on plant growth through certain physio–chemical processes. Whereas,
elevation might alters the correlation of the limiting factor with other environmental
variables. Tadesse Woldemariam (2003) has found that, environmental factors such as
altitude, slope, and landforms characterized the communities in Yayu forest. One
important measure of the structural heterogeneity of a community is its diversity.
Diversity in a community can be expressed in terms of number (richness) of species,
degree of dominance by one or a few species, relative abundance of all species
(evenness), number of rare species, vertical stratification of species, horizontal
patchiness, number of growth or life forms, and so on.
Diversity measurements are used to interpret mechanisms operating in the
community. High diversity in a given forest enhances community stability,
community productivity
and
maintains
niche
structure
(McIntosh,
1967).
Accordingly, community 4 in TBB had highest diversity compared to the other four
communities. Whereas community 5 had the least diversity compared to the other
four communities. Similarly, community 1 in CCNP had the highest diversity than the
other two communities, and community 3 had the least diversity. In TBB, community
5 was known by its lowest species richness. This might be due to its existence at
highest elevated area. Habitats with extreme environmental conditions generally
support few species and relatively few individuals of a species (Putman, 1994). The
area where community 5 is located was highly affected by humans, so that the level of
disturbance in that particular area was found to be high.
106
5.3 Population Structure
The general pattern of plant population structure that was emerged at both TBB and
CCNP is an inverted – J shape, which had higher stems in the lower size classes and
few individuals in the higher size classes. Afromontane forests studied by Tamrat
Bekele (1993), Feyera Senbeta (2006), and Abreham Assefa et al. (2014) also showed
inverted – J shape pattern of population structure. This pattern of plant population
structure is an indication of a normal population distribution (Tamrat Bekele, 1993;
Feyera Senbeta, 2006; Feyera Senbeta et al., 2007). However, the general pattern of a
population structure is a cumulative result of all woody plants subjected to DBH and
height measurement.
Various major types of patterns of plant population structure were identified at the
Afromontane forests of TBB and CCNP. From these patterns, inverted J – shaped
patterns show healthy regeneration pattern, where higher densities available at lower
DBH and height classes followed by gradual decrease in densities to the higher DBH
and height class. This kind of pattern with respect to DBH was exhibited by
Podocarpus falcatus. The reason for the this kind of pattern might be due to the
consumption of those woody species at the middle and higher DBH and height classes
by local communities for various purposes. In the pattern of population structure
represented by Olea capensis subsp. macrocarpa, the density if woody species at the
first DBH class is lower than the second DBH class. It further gradually reduced to
the tenth DBH class. In this pattern selective cutting at the first DBH class and
between DBH class four and ten there might also be carried out. However, in the third
pattern, which is represented by Macaranga capensis, zigzag pattern was observed
indicating that no uniform variation at each DBH classes. This plant was seen to be
107
consumed by browsers and also collected by the local people for firewood. In CCNP,
Syzygium guineense stands from fivth to tenth DBH classes were expected to be
logged for its timber value. the situation to Prunus africana in TBB is more serious
than other plant species. this is because higher density was observed only at the first
and last DBH classes forming a U – shapped pattern of population structure. Prunus
africana is known by its timber quality in the area.
Generally, most population structures for specific plant species do not investigate a
healthy structure for the fact that there might be selective logging at a particular DBH
class. The probable effect on one species in a given DBH class might be compensated
by another species when the entire forest is considered for population structure.
Hence, it would be difficult to evaluate healthiness of a forest by only looking at the
entire population structure without considering the population structure of some major
plant species.
Diversity, Density and Basal Area of Vegetation
Diversity can be measured using one or more indices combining species richness and
relative abundance within an area. Richness and diversity have commonly been
described as a characteristic property of a putative homogeneous community and
indicative of its organization (Macintosh, 1967). The two study areas had high
diversity (H’) of 3.45 for TBB and 3.32 for CCNP. This might be associated with the
protection and conservation efforts made by OFWE in BB and the Park in CCNP.
However, TBB had highest species richness compared to CCNP. This might be due to
the existence of larger area coverage of Afromontane forest in TBB compared to
CCNP. The second reason for higher diversity in TBB might be due to the fact that
108
the forest is located adjacent to Central highlands of Ethiopia and shares some species
with its neighboring Dry afromontane forests to the eastern side of the forest.
Total density of woody species encountered in TBB and CCNP was 1902 stems.ha–1
and 1562 stems.ha–1 respectively. Comparisons of densities for DBH > 10 cm and
DBH > 20 cm of the Afromontane forests of TBB and CCNP along with other
Afromontane forests of the country are given in Table 27 to identify proportion of
small–sized to large–sized individuals in those forests. Pattern of density distribution
of vegetation might be altered by one or more major environmental factors (Kershaw,
1973). The ratio of DBH > 10 cm to DBH > 20 cm was 1.9 for TBB and 2.1 for
CCNP, which indicates slight variability of proportion between small–sized and
large–sized individuals. The comparison of density of the present study areas with
Afromontane forests of the central plateau of Shewa (Tamrat Bekele, 1993) and
Masha–Anderacha forest (Kumelachew Yeshitela and Taye Bekele, 2003) showed
that, TBB and CCNP were the first and the fourth respectively in density of woody
species with DBH > 10 cm and the first and the third respectively in density of woody
species with DBH > 20 cm. Like Chilimo and Menagesha forests and Masha–
Anderacha forest, the ratio of density of species with DBH > 10cm to DBH > 20cm
was very high indicating the predominance of small sized tree individuals. The former
two forests, described by Tamrat Bekele (1993), were subjected to excessive cutting
took place long time ago. But in Masha–Anderacha forest this was due to high density
of Cyathea maniana. The situation in Both TBB and CCNP was due to high density
of Dracaena afromontana and Chionanthus mildbraedii, small sized woody species in
the forest.
109
Table 27. The ratio of tree densities of DBH > 10 cm and DBH > 20 cm at the
Afromontane forests of TBB, CCNP and other selected Afromontane forests
Forest
DBH > 10 cm (a)
DBH > 20 cm (b)
a/b
Chilimo foresta
638
250
2.6
Menagesha foresta
484
208
2.3
Wof–Washa foresta
329
215
1.5
Masha forestb
633
286
2.2
TBB
678
366
1.9
570
269
2.1
CCNP
a
b
Tamrat Bekele (1993); Abreham Assefa (2009)
In contrast to simple count, basal area provides a better measure of the relative
importance of woody species (Cain and Castro, 1959). According to Tamrat Bekele
(1993), species with higher measure of basal area have higher contribution to the total
basal area of a forest. Thus, these species can be considered as the most important
species in a forest. In Afromontane forest of TBB, 69% of the total basal area was
contributed by nine woody species. Those plant species which had much contributed
for the total basal area in TBB are Syzygium guineense subsp. afromontana, Olea
capensis subsp. macrocarpa, Pouteria adolfi-friederici, Schefflera abyssinica,
Macaranga capensis, Olinia rochetiana, Ficus sur, Podocarpus falcatus and Croton
macrostachyus. Similarly, nine woody species, namely: Syzygium guineense subsp.
afromontanum, Schefflera abyssinica, Prunus africana, Ficus sur, Ilex mitis, Pouteria
adolfi–friederici, Schefflera volkensii, Olea capensis subsp. macrocarpa, and
Apodytes dimidiata contributed for 73% of the total basal area of the Afromontane
forest of CCNP. Species which have greater contribution to the total basal of a given
forest are considered as the most important species for that particular forest (Abreham
Assefa et al., 2014).
110
Gradual increase in basal area as increase in DBH class was seen from the
Afromontane forests of TBB and CCNP. The highest basal area was obtained from
plant species at DBH class 11. Most of trees at the Afromontane forests of TBB and
CCNP were small sized. However, trees belonging to DBH class 11 (DBH higher
than 50 cm) were fewer, but contribute much to the total basal area. For those woody
plant species which are represented by few individuals (low density), recruitments and
contribution of density for that particular DBH class was very low.
Comparison of basal area and densities in diameter classes in the study area indicates
that there were more individuals in the first diameter classes both in TBB and CCNP,
though their contribution to the basal area was very low. Majority of trees in study
areas were small sized. Trees belonging to the highest DBH-class were fewer in
number/density. However, these trees in highest DBH-class contributed much to the
total basal areas of forests under study.
The basal areas in the current two study areas are almost alike (72.98 for TBB and
73.81 for CCNP), and higher than basal areas of the forests of Chilimo (30.1 m2 ha–1)
and Menagesha (36.1 m2 ha–1) (Tamrat Bekele, 1993). However, the basal areas are
lower than Wof–Washa forest (101.8 m2 ha–1) (Tamrat Bekele, 1993) and Masha
forest (147 m2 ha–1) (Abreham Assefa et al., 2014). Low basal areas in the former two
forests were due to the fact that these forests have been under heavy exploitation for
their timber (Tamrat Bekele, 1993). On the other hand, the Wof–Washa forest had
been free from such abuse.
Furthermore, comparison of the basal area and densities of the current study area with
other Afromontane forests in Central Plateau of Ethiopia (Tamrat Bekele, 1993) and
Masha–Anderacha forest (Kumelachew Yeshitela and Taye Bekele, 2003) (Table 28)
111
revealed that, for trees with DBH higher than 10 cm the current study area had higher
basal area than Masha–Anderacha, Jibat and Chilimo forest. For trees with DBH
lower than 10 cm, the current study area had higher densities than Masha–Anderacha
forests, but lower densities than Jibat, Chilimo and Menagesha forests. For trees with
DBH between 10 and 20 cm, the current study area had higher densities than Jibat,
and Menagesha, but lower densities than Chilimo and Masha–Anderacha forests.
Similarly, for trees with DBH higher than 20 cm, the current study area had higher
densities than Central Plateau forests and Masha–Anderacha forest, which could be
attributed to the predominance of few species such as Pouteria adolfi-friederici in the
current study area.
Table 28. Structural characteristics of the Afromontane forests of TBB, CCNP and
other selected Afromontane forests in the country
Jibat
Masha–
Masha
CCNP
Anderacha
TBB
Characteristic
Chilimo Menagesha
Basal area DBH > 10 cm
47.5
27.3
32.4
65.2
139
70
71
Density DBH< 10 cm
1254 1606
2010
574
1048
1223 992
a
Forest Forest
a
Forest
a
Forest
b
Forestc
Density 10 cm < DBH < 20 cm 275
388
276
987.7
347
312
302
285
250
208
150.8
286
366
269
Density DBH > 20 cm
Source: aTamrat Bekele (1993);
(2009)
b
Kumelachew Yeshitela and Taye Bekele (2003), cAbreham Assefa
Important Value Indices (IVI)
It is difficult to make a census of all inhabitants of diversified natural vegetation and
to discover the role of each species in a complicated ecosystem (Clarke, 1954). Such
tasks require the combined efforts of several taxonomists and ecologists competent to
deal with detailed studies of the inhabitants of specific habitats/area. Thus, ecological
112
significance of a species in a forest is compared using Importance Value (IV) of a
species (Lamprecht, 1989).
Olea capensis subsp. macrocarpa, Syzygium guineense subsp. afromontanum and
Pouteria adolfi–friederici were the top three plant species at the Afromontane forest
of TBB that are indexed with respect to their importance. Similarly, Syzygium
guineense subsp. afromontanum and Prunus africana woody species that had higher
importance to the Afromontane forest of CCNP. Only few species in both study areas
had higher IVI value. Majority of species in both TBB and CCNP had importance
value indices of less than 10 indicating that attention should be given to conserve
those species.
Density of Seedling and Sapling
The regeneration of Afromontane forest of TBB and CCNP was found to be low
comparing to the regeneration status of Sheko forest, Yayu forest, Godere forest,
Belete–Gera forest, Bonga forest, Setema forest, Sigmo forest (Elias Taye and
Getachew Berhan, 2002) and Masha forest (Abreham Assefa et al., 2014) (Table 29).
Table 29. Regeneration status of some selected montane forests
Montane forests
Sheko forest b
Yayu forest b
Godere forest b
Belete–Gera forest b
Bonga forest b
Setema forest b
Sigmo forest b
Masha forestc
TBB
CCNP
Regeneration densities (stems.ha–1)
7277
6818
6676
6630
5656
5528
5226
5289
2294
1761
Source: b Elias Taye and Getachew Berhan (2002), cAbreham Assefa et al. (2014)
113
Phytogeographical comparison
Most characteristic tree species of Afromontane rainforest (Friis, 1992) recorded from
TBB and CCNP are Pouteria adolfi-friederici, Prunus africana, Polyscias fulva,
Dracaena afromontana, and Syzygium guineense subsp. afromontanum. Comparison
of species composition of the two study areas each other and with four other moist
Afromontane forests in southwest Ethiopia was carried out using Sorenson’s
similarity index (Table 30 and Table 31).
Table 30. Phytogeographical Comparison of Afromontane forest of TBB (altitudinal
range of 1682 – 2339 and mean annual rainfall 1431 mm) with other five
similar Afromontane forests in southwest Ethiopia
Forest
Agama1
Belete2
Guraferda3
Komto4
Masha5
CCNP
Mean annual rainfall
(mm)
Altitudinal
range (m)
1830
1800-2300
2067
2192
2082
1700 – 2370
1300 – 3000
2100 – 2482
1700 – 2321
1682 – 2339
a
b
c
Ss
57
56
58
69
62
91
86
87
81
74
81
52
22
29
17
28
17
13
0.51
0.49
0.54
0.58
0.56
0.74
1
Admassu Addi et al. (2016); 2Kflay Gebrehiwot and Kitessa Hundera (2014); 3Dereje Denu (2007);
Fekadu Gurmessa et al. (2012); and 5Abreham Assefa et al. (2014)
4
Table 31. Phytogeographical Comparison of Afromontane forest of CCNP with other
five similar Afromontane forests in southwest Ethiopia.
Forest
Agama1
Belete2
Guraferda3
Komto4
Masha5
Mean annual rainfall
(mm)
1830
1800-2300
Altitudinal
range (m)
1700 – 2370
1300 – 3000
2067
2192
2100 – 2482
1700 – 2321
a
B
c
Ss
55
49
57
63
64
49
55
47
41
40
24
36
54
34
15
0.60
0.52
0.53
0.63
0.70
1
Admassu Addi et al. (2016); 2Kflay Gebrehiwot and Kitessa Hundera (2014); 3Dereje Denu (2007);
Fekadu Gurmessa et al. (2012); and 5Abreham Assefa et al. (2014)
4
‘a’ is number of common species to forest under comparison, ‘b’ is number of species
found in present study area, ‘c’ is number of species found in vegetation of other sites in
comparison with present study area and ‘‘Ss’’ is Sorenson’s similarity index.
114
As a result, the highest similarity was observed between the two forests under study
than any other Afromontane forest under comparison. Both the range of altitude and
geographical location of Afromontane forest of TBB are very similar to Afromontane
forest of CCNP as stated in Abreham Assefa et al., (2014). These two forests are
belongs to Gibe–Omo watershed. The highest floristic similarity between these two
forests might be due to environmental factors and/or their proximity.
Afromontane forest of TBB showed higher similarity to Komto followed by Masha
and Guraferda forests. These forests are located in the same agro–climatic region and
obtain high annual rainfall. The Afromontane forest of TBB showed the least
similarity to Belete forest. Similarly, Afromontane forest of CCNP showed higher
similarity to Masha followed by Agama and Komto. The Afromontane forest of
CCNP showed the least similarity to Belete forest. The possible explanations for the
overall low floristic similarities between the current study areas and Afromontane
rainforests under comparison might be due to their distance, variation in geographical
location, and environmental determinism. Relation between geographical distance and
floristic similarity can largely be explained by the fact that environmental variables
change with geographical distance, which lead to the floristic dissimilarity (Tuomisto
et al., 2003).
115
5.4 LU/LC Changes at TBB and CCNP
LULC class in CCNP varies both in TBB and in CCNP in all the three study periods.
The largest area of TBB and CCNP park were occupied by Forest woodlad and
respectively. The area of forest cover in TBB increased from the year 1984 to 2000.
This increase was due to the mass plantation events carried out several times in the
period. However this forest cover was declined in 2015 as a result of harvesting of
plantations by OFWE for timber production. The decrease in forest area was also
associated with conversion of some forested area to farmland. Clearance of forested
area particularly for timber resulted in envision of the cleared area by herbaceous
cover and grasses, which led to increased grassland cover.
Agriculture and settlement was covering small area in 1984, which gradually
increased in 2015 mainly as the expense of both forest and woodland. In CCNP,
unlike other land use/land cover types, large area of Woodland was converted to
grasslands, agricultural and settlement in all the three study period. Forest was the
next land use/land cover type which was converted to Agriculture and settlement land
use type. The area of conversion of woodland to grassland, agriculture and settlement
became increased from the initial period to the last study period. This indicates that
woodland was being harvested for timber and other wood products and the area was
cleared for expansion of farmlands. Several people were settled at lower altitudinal
areas within the park and its periphery than the highland areas.
Several LU/LC studies conducted in different parts of the country indicated the level
of loss of natural vegetation cover, expansion of cultivated land and increase in land
degradation occurred in the areas where these studies were conducted. Most studies
conducted in Ethiopia indicated that LU/LC changes have resulted in undesirable
116
biophysical and socioeconomic impacts. For instance decrease in shrub lands, forests
and riverine vegetation was reported to have occurred in Kalu area of south Wollo
(Ethiopia) between1958 and 1986 by Kebrom Tekle and Hedlund (2000), substantial
increase of cultivated lands between 1957 and 1995 was reported in Dembecha area,
northwestern Ethiopia by Gete Zeleke (2000), remarkable increase of grassland at the
cost of cropland and bare land was reported to have occurred in Beressa watershed,
central highlands of Ethiopia, between 1957 and 2000 by Aklilu Amsalu (2006), a
considerable loss of wetland, forest, grass and shrubland was reported to have
occurred in Alemaya area of eastern Ethiopia between 1965 and 2007 by Mohammed
Assen (2011). On the other hand, study conducted by Woldeamlak Bewket (2003)
showed an increase in forestland in Chemoga watershed northwestern highlands of
Ethiopia between 1957 and 1998. Study conducted by Asmamaw Legesse et al.,
(2011) also showed the increase in forestland in Gerado catchment of northeastern
Ethiopia between 1958 and 2006.
The overall pattern of LU/LC change at TBB and CCNP show that there was decrease
in the vegetation cover (forest and woodland), while area cover of Agriculture and
Settlement have progressively increased from the year 1984 to 2015. Whereas forest
cover in CCNP showed small change when compared to woodland, grassland and
agriculture. In CCNP, the establishment of the park and associated activities such as
relocation/resettlement of some settlers inside the park and adjacent to it, recruitment
of guards/scouts, and frequent awareness raising programs might have reduced the
conversion of forest into other land use/land cover type. for In addition, some people
living inside CCNP (in both lowland and highland areas) were found to convert
forested areas in to agricultural land as a result of high demand of agricultural
production due to increasing population over time. There was high rate of change of
117
forest cover in TBB between the year 2000 and 2015 compared to other land use/land
cover types. Following forest there was high rate change of woodland cover between
the year 1984 and 2015. Similarly, there was high rate of conversion of woodland
cover into other land use/land cover types in CCNP between the year 2000 and 2015.
Factors Contributing for LU/LC Changes at TBB and CCNP
Similar to other parts of the country, agriculture was reported as the main source of
income to the local communities in both TBB and CCNP. Because of increase in
population, households living in forested areas need more land for agricultural
production. These demands were being satisfied through conversion of forest or
woodland into agricultural lands. The forests were benefiting local communities in
several ways. The forest serve as source of firewood, timber for house construction,
source of non timber products, and source of water. In addition, both OFWE and
CCNP were serving the communities by creating job opportunity to the local
communities.
Study of LU/LC change at local scales is important to understand drivers of the
changes and seek for viable land management options. Drivers of LU/LC change and
level of influence by drivers of change vary in space and time depending on location–
specific factors (Qasim et al., 2013). The result of LU/LC changes at both TBB and
CCNP implies that there might be some sort of socioeconomic changes taken place
between the year 1984 and 2015 that altered the LU/LC of those areas. Results from
focus group discussions showed that population pressure, poverty, timber production,
firewood collection and charcoal making, and fire were the major causes for the
LU/LC change in the two study areas. Cattle grazing inside the forest might result in
trampling and browsing of seedlings and saplings of some plant species. Studies
118
carried out in different parts of Ethiopia also have similar findings for the contribution
of LU/LC changes. For instance, in Kebrom Tekle and Hedlund (2000), Woldeamlak
Bewket (2002), Belay Tegene (2002) and Messay Mulugeta (2011), population
increase, expansion of farmlands, fuel wood collection, charcoal making, and
expansion of settlements were reported to be the major factors of LU/LC changes in
various parts of Ethiopia. In Aklilu Amsalu (2006), Fikir Alemayehu et al. (2009),
Gete Zeleke and Hurni (2001) and Hurni (1993), population pressure was indicated to
be the largest factor causing LU/LC changes in many parts of Ethiopia. Population
growth in the current study areas depicted that pressure on the land resources was
high in the area, which in turn could have claimed more agricultural and settlement
land and fuel wood consumption. This has led to the expansion of cultivated and
settlement lands. Expansion of agricultural land and increase in settlements areas are
an apparent indicators of impacts of a continuous increase in population density on
the LU/LC of the area.
Conversion of other LU/LC for fresh agriculture has been takes place as the farmland
become less productive, which caused expansion of cultivated lands. Thus, high
dependence of the local community on agriculture caused LU/LC changes in the study
area. Due to tree plantation and timber production at TBB by OFWE, the LU/LC was
changing from grass/shrub land to shrub land and then to forest and back to shrub
land after the forest has been harvested. Expansion of settlements in the area was also
being carried out in the expense of forest. This finding is similar to the finding by
Aerts et al. (2009). However, increase in forest cover in TBB was mainly associated
to trees planted for timber production by OFWE.
119
Lack of community involvement in forest management was mentioned as one of the
cause for forest degradation. Community based forest management or joint forest
management approach were the options raised by the communities as an option for
sustainable forest management.
120
CHAPTER SIX
6. CONCLUSION AND RECOMMENDATIONS
6.1 Conclusion
Afromontane forests of TBB and CCNP are diverse with respect to their
species composition and existence of several endemic plant species. The
overall population structure forest in the two study areas have similar pattern
showing healthy regeneration pattern. Similarly, the plant communities
identified at the two study sites also showed the same pattern as the
population structure does. In contrary, the two forests are threatened as a
result of human activities demanding the existing forest recourses. Dealing
with the healthiness of the regeneration pattern of a forest by looking at the
overall population structure as well as description of structures of plant
communities identified from that forest would be misleading. Because, some
species are highly threatened than the other and the effect was compensated
by another species that are not under threat.
These Moist Afromontane forests are home for emergent trees species such
as Pouteria adolfi-friedrici, Olea welwitschii, and Prunus africanus. However,
these plant species are under severe threat as a result of selective logging
and grazing taking place inside the forest. In addition, the overall regeneration
status (i.e. seedling and sapling) of the forests can be taken as poor, so that it
needs attention for conservation. Different environmental variables are
responsible for distribution and assemblage of plants in different area/forest.
Due to the existence of high density of Pouteria adolfi-friederici at the Afromontane
121
forest of TBB, the area can be taken as an in-situ conservation site in the for Pouteria
adolfi-friederici. This in turn helps to conserve the gene pool of other species in the
area and maintain plant communities with high species diversity.
The local communities of the forested areas of the two study areas were mainly
dependent on agriculture. They also rely on the forest resources various uses. LU/LC
of the two study areas were changing from time to time. Decrease in vegetation cover
and increase in agriculture and settlement in the study area is an indication of
conversion of forest and other land use types because of demand for land for
agriculture and settlement. The change from reduction of more natural vegetation
(natural forest and woodland) to expanded cultivated land was more of conversion
and high change of this type was observed between 2000 and 2015. This change
might alter both ecological and economical values of the Afromontane forests of the
study areas, and Gibe–Omo watershed subsequently.
OFWE and CCNP were serving as the main actors of the protection and conservation
of natural resources especially forest resources in the respective study areas.
However, due to rapid population growth, resulted in increase in Agriculture and
settlement cover and contributed for decrease in forest and woodland cover. The
existing forest management system in the area was not allowing the local
communities in management and utilization of the forest resources owned by the
government. This situation was contributed for the conversion of the forest and
woodlands into other land use/land cover types.
122
6.2 Recommendations
To maintain ecological and economical benefit of the Afromontane forests of TBB and
CCNP, the government should allow the local communities to involve in
conservation, management, and utilization (as participatory or joint forest
management) for sustainable management of the existing forests. This will in
turn help to conserve the gene pool of those plant species under threat and
maintain original plant community with large species diversity.
The concerning bodies such as local governments and the Ministry of Environment,
Forest and Climate Change (MEFCC) in collaboration of Ministry of Agriculture and
Natural Resource should introduce alternative means of income generation to avoid
further conversion of forest to other land use/land cover type. The management options
should include reducing livestock pressure on forest, limiting further expansion of
farmlands and providing farmers/community with tree species as alternative to their
wood/timber need. Introduction of participatory forest management will allow the local
communities living around the forest to participate in forest management for a better
conservation and utilization of the resources in the area.
In addition, the local communities should be supported to increase household income
through certain activities such as agricultural intensification and improved (or SMART)
agricultural practices, and off–farm economic activities. In addition, improve the use of
modern stoves for efficient energy consumption might help the sustainability of natural
forest. Moreover, effective enforcement of forest laws/policies should also be there.
123
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ANNEXES
Annex 1. List of plant species recorded at the Afromontane forests of TBB and CCNP
S. No
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Scientific Name
Abutilon longicuspe Hochst. ex A. Rich.
Acalypha psilostachya Hochst.
Acanthopale pubescens (Lindau ex Engl.) C.B. Clarke
Acanthus eminens C. B. Clarke
Acanthus sennii Chiov.
Achyranthes aspera L.
Achyrospermum schimperi (Hochst. ex Briq.) Perkins
Adenostemma mauritianum DC.
Adiantum thalictroides Wild.
Aframomum corrorima (Braun) Jansen
Agarista salicifolia (Comm. ex Lam.) Hook.
Ageratum conyzoides L.
Albizia gummifera (J. F. Gmel.) C. A. Sm
Albizia schimperiana Oliv.
Alchemilla abyssinica Fresen.
Alchemilla pedata A. Rich.
Allophylus abyssinicus (Hochst.) Radlkofer
Anthemis tigreensis J.Gay ex A. Rich.
Apodytes dimidiata E. Mey. ex Arn.
Aristea abyssinica Pax
144
Family
Malvaceae
Euphorbiaceae
Acanthaceae
Acanthaceae
Acanthaceae
Amaranthaceae
Lamiaceae
Asteraceae
Adiantaceae
Zingeberaceae
Ericaceae
Asteraceae
Fabaceae
Fabaceae
Rosaceae
Rosaceae
Sapindaceae
Asteraceae
Icacinaceae
Iridaceae
Habit
H/Sh
H/Sh
H
Sh
Sh
H
H/Sh
H
F
H
T/Sh
H
T
T
H
H
T
H
T
H
TBB
CCNP
S. No
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
Scientific Name
Arundinaria alpina K. Schum.
Asparagus africanus Lam.
Aspilia mossambicensis (Oliv.) Wild
Asystasia mysorensi (Roth) T. Anders.
Athrixia rosmarinifolia (Sch. Bip. ex Walp.) Oliv. & Hiern
Cyperus dereilema Steud.
Barleria ventricosa Hochst. ex Nees
Bersama abyssinica Fresen.
Brucea antidysenterica J. F. Mill.
Buddleja polystachya Fresen.
Calpurnia aurea (Ait.) Benth.
Canthium oligocarpum Hiern
Carduus leptacanthus Fresen.
Carissa spinarum L.
Cassipourea malosana (Baker) Alston
Celtis africana Burm. f.
Chionanthus mildbraedii (Gig & Schellenb.) Stearn
Cirsium vulgare (Savi.) Ten.
Cissampelos pareira L.
Clausena anisata (Willd.) Benth.
Clematis hirsuta Perro & Guill
Clematis longicauda Steud.ex A. Rich.
Clematis simensis Fresen.
Clerodendrum myricoides (Hochst.) Vatke
145
Family
Poaceae
Asparagaceae
Asteraceae
Acanthaceae
Asteraceae
Cyperaceae
Acanthaceae
Melianthaceae
Simarubaceae
Loganiaceae
Fabaceae
Rubiaceae
Asteraceae
Apocynaceae
Rhizophoraceae
Ulmaceae
Oleaceae
Asteraceae
Menispermaceae
Rutaceae
Ranunculaceae
Ranunculaceae
Ranunculaceae
Lamiaceae
Habit
T
Sh/Li
H/Sh
H
H/Sh
H
H
T/Sh
T/Sh
T/Sh
T/Sh
T/Sh
H
Sh/Li
T
T
T/Sh
H
Li
T/Sh
Sh
Cl
Li
H/Sh
TBB
CCNP
S. No
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
Scientific Name
Clutia abyssinica Jaub. & Spach.
Coffea arabica L.
Combretum paniculatum Vent.
Commelina foliacea Chiov.
Conyza hypoleuca A. Rich
Cordia africana Lam.
Crepis rueppellii Sch. Bip.
Crotalaria alexandri Bak. f.
Croton macrostachyus Del.
Cyathea manniana Hook.
Cyathula cylindrica Moq.
Cynoglossum amplifolium Hochst. ex A. DC. in DC.
Cynoglossum lanceolatum Forssk.
Cyperus fischerianus A. Rich.
Cyphostemma adenocaule (Steud. ex A. Rich.) Descoings ex Wild & Drummond
Cyphostemma cyphopetalum (Fresen.) Descoings ex Wild & Drummond
Desmodium repandum (Vahl) DC.
Dicliptera laxata C. B. Clarke
Discopodium penninervium Hochst.
Dissotis senegambiensis (GuilL. & Perr.) Triana
Dodonaea angustifolia L. f.
Dombeya torrida (J. F. Gmel.) P. Bamps
Dovyalis abyssinica (A. Rich.) Warb
Dovyalis verrucosa (Hochat.) Warb.
146
Family
Euphorbiaceae
Rubiaceae
Combretaceae
Commelinaceae
Asteraceae
Boraginaceae
Asteraceae
Fabaceae
Euphorbiaceae
Cyatheaceae
Amaranthaceae
Boraginaceae
Boraginaceae
Cyperaceae
Vitaceae
Vitaceae
Fabaceae
Acanthaceae
Solanaceae
Melastomataceae
Sapindaceae
Sterculariaceae
Flacourtiaceae
Flacourtiaceae
Habit
H/Sh
T/Sh
Sh/Li
H
T/Sh
T
H
H
T/Sh
T
H
H
H
H
Cl
Cl
H/Sh
H
T
H
Sh
T
T/Sh
T/Sh
TBB
CCNP
S. No
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
Scientific Name
Dracaena afromontana Mildbr.
Dracaena steudneri Engl.
Dumasia villosa DC.
Ehretia cymosa Thonn.
Ekebergia capensis Spamn.
Elaeodendron buchananii (Loes.) Loes.
Embelia schimperi Vatke
Englerina woodfordioides (Schweinf.) M. Gilbert
Ensete ventricosum (Welw.) Cheesman
Erica arborea L.
Erythrina abyssinica Lam. ex DC.
Erythrina brucei Schweinf.
Erythrococca trichogyne (Muell. Arg) Prain.
Euphorbia schimperiana Scheele
Ficus lutea Vahl
Ficus sur Forssk.
Flacoutia indica (Burm.f) Merr.
Galiniera saxifraga (Hochst.) Bridson
Galium aparinoides Forssk.
Garcinia budlananii Baker
Geranium arabicum Forssk.
Gomphocarpus semilunatus A. Rich.
Gouania longispicta Engl.
Guizotia scabra (Vis.) Chiov.
147
Family
Dracaenaceae
Dracaenaceae
Fabaceae
Boraginaceae
Meliaceae
Celastraceae
Myrsinaceae
Loranthaceae
Musaceae
Ericaceae
Fabaceae
Fabaceae
Euphorbiaceae
Euphorbiaceae
Moraceae
Moraceae
Flacourtiaceae
Rubiaceae
Rubiaceae
Clusiaceae
Geraniaceae
Asclepiadaceae
Rhamnaceae
Asteraceae
Habit
T/Sh
T/Sh
Cl
T/Sh
T
T/Sh
Sh/Li/T
H
H
T/Sh
T/Sh
T
T/Sh
H
T
T
T/Sh
T/Sh
H
T/Sh
H
H/Sh
Sh/Li
H
TBB
CCNP
S. No
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
Scientific Name
Hagenia abyssinica (Bruce) J. F. Gmel.
Hebenstretia angolensis Rolfe
Helichrysum forsskahlii (J. F. Gmel.) Hilliard & Burtt
Helichrysum splendidum (Thunb.) Less.
Helinus mystacinus (Ait.) E. Mey. ex Steud.
Hibiscus macranthus Hochst. ex A. Rich.
Hippocratea africana (Willd.) Loes.
Hippocratea goetzei Loes.
Hydrocotyle mannii Hook.f
Hypericum peplidifolium A. Rich.
Hypericum quartinianum A. Rich.
Hypericum revolutum Vahl.
Hypoestes forskaolii (Vahl) R. Br.
Hypoestes triflora (Forssk.) Roem & Schult.
Ilex mitis (L.) Radlk.
Isoglossa somalensis Lindau
Jasminum abyssinicum Hochst. ex DC.
Juniperus procera Hochst. ex Endl.
Justicia ladanoides Lam.
Justicia schimperiana (Hochst. ex Nees) T. Anders.
Kalanchoe petitiana A. Rich.
Kosteletzkya begoniifolia (Ulbr.) Ulbr.
Landolphia buchananii (Hall. F.) Stapf
Leonotis ocymifolia (Burm. f.) Iwarsson
148
Family
Rosaceae
Scrophulariaceae
Asteraceae
Asteraceae
Rhamnaceae
Malvaceae
Celastraceae
Celastraceae
Apiaceae
Clusiaceae
Clusiaceae
Clusiaceae
Acanthaceae
Acanthaceae
Aquifoliaceae
Acanthaceae
Oleaceae
Cuppressaceae
Acanthaceae
Acanthaceae
Crassulaceae
Malvaceae
Apocynaceae
Lamiaceae
Habit
T
H/Sh
H
H/Sh
Li
H/Sh
Sh/Li
Sh/Li
H
H
T/Sh
T/Sh
H
H
T/Sh
Sh
Li
T
H
Sh
H
H
Sh/Li
Sh
TBB
CCNP
S. No
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
Scientific Name
Lepidotrichilia volkensii (Gilrke) Leroy
Leucas deflexa Hook. f.
Leucas martinicensis (Jacq.) R. Br.
Lippia adoensis Hochst. ex Walp.
Lobelia giberroa Hemsl.
Macaranga capensis (Baill.) Sim.
Maesa lanceolata Forssk.
Maytenus addat (Loes.) Sebsebe
Maytenus arbutifolia (A. Rich.) Wilczek
Maytenus gracilipes (Welw. ex Oliv.) Exell subsp. arguta (Loes.) Sebsebe
Maytenus undata (Thunb.) Blakelock
Micractis bojeri DC
Microglossa pyrifolia (Lam.) Kuntze
Millettia ferruginea (Hochst.) Bak. subsp. darassana (Cuf.) Gillett
Mimulopsis solmsii Schweinf.
Momordica foetida Schumach.
Monothecium glandulosum Hochst.
Myrica salicifolia A. Rich
Myrsine africana L.
Myrsine melanophloes (L.) R. Br.
Nuxia congesta R. Br. ex Fresen.
Ocimum lamiifolium Hochst. ex Benth.
Oldenlandia monanthos L.
Olea capensis L. subsp. macrocarpa (C. H. Wright) Verdc.
149
Family
Meliaceae
Lamiaceae
Lamiaceae
Verbenaceae
Lobeliaceae
Euphorbiaceae
Myrsinaceae
Celastraceae
Celastraceae
Celastraceae
Celastraceae
Asteraceae
Asteraceae
Fabaceae
Acanthaceae
Cucurbitaceae
Acanthaceae
Myricaceae
Myrsinaceae
Myrsinaceae
Loganiaceae
Lamiaceae
Rubiaceae
Oleaceae
Habit
T
H
H
Sh
T/Sh
T
T/Sh
T
T/Sh
T/Sh
T/Sh
H
Sh
T
Sh
Cl
H
T/Sh
T/Sh
T/Sh
T/Sh
Sh
H
T
TBB
CCNP
S. No
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
Scientific Name
Olea europaea L. subsp. cuspidata (Wall. ex G. Don) Cif
Olea welwitschii (Knobl.) Gilg & Schellenb.
Olinia rochetiana A. Juss.
Oncoba spinosa Forssk.
Oplismenus hirtellus (L.) P. Beauv.
Osyris quadripartita Decn.
Paveta abyssinica Fresen.
Pavonia kilimandscharica Gürke
Pegolettia senegalensis Cass.
Pennisetum thunbergii Kunth
Pentas lanceolata (Forssk.) Deflers
Pentas schimperiana (A. Rich.) Vatke subsp. schimperiana
Peperomia abyssinica Miq.
Peperomia molleri C. DC.
Peperomia tetraphylla (Forster) Hook. & Arn.
Peponium vogelii (Hook.f) Engl.
Periploca linearifolia Quart. –Dill. & A. Rich
Phoenix reclinata Jacq.
Phyllanthus fischeri Pax
Phyllanthus ovalifolius Forssk.
Phytolacca dodecandra L’Herit
Pilea bambuseti Engl. subsp. aethiopica Friis
Piper capense L.f.
Pittosporum viridiflorum Sims
150
Family
Oleaceae
Oleaceae
Oliniaceae
Flacourtiaceae
Poaceae
Santalaceae
Rubiaceae
Malvaceae
Asteraceae
Poaceae
Rubiaceae
Rubiaceae
Piperaceae
Piperaceae
Piperaceae
Cucurbitaceae
Asclepiadaceae
Arecaceae
Euphorbiaceae
Euphorbiaceae
Phytolaccaceae
Urticaceae
Piperaceae
Pittosporaceae
Habit
T/Sh
T
T/Sh
T/Sh
G
T/Sh
T/Sh
Sh
H
G
H/Sh
H/Sh
H
H
H
Cl
Li
T
H
T/Sh
Sh
H
H
T/Sh
TBB
CCNP
S. No
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
Scientific Name
Plantago lanceolata L.
Plantago palmata Hook. f.
Plectocephalus varians (A. Rich.) C. Jeffrey ex Cufod.
Plectranthus alpinus (Vatke) Ryding
Podocarpus falcatus (Thunb.) R.B. ex Mirb.
Polyscias fulva (Hiern) Harms
Pouteria adolfi–friederici (Engl.) Baehni
Premna schimperi Engl.
Prunus africana (Hook. F.) Kalkm
Pseudognaphalium richardianum (Cufod.) Hilliard & Burtt
Psychotria orophila Petit
Pteridium aquilinum (L.) Kuhn
Pteris cretica L.
Pteris pteroides (Hook.)
Pteris quadriaurita Retz.
Pycnostachys eminii Gurke
Rhamnus prinoides L'Herit.
Rhus glutinosa A. Rich.
Rhus vulgaris Meikle
Ritchiea albersii Gilg
Rosa abyssinica Lindley
Rothmannia urcelliformis (Hiern) Robyns
Rubus steudneri Schweinf.
Rytigynia neglecta (Hiern) Robyns
151
Family
Plantaginaceae
Plantaginaceae
Asteraceae
Lamiaceae
Podocarpaceae
Araliaceae
Sapotaceae
Lamiaceae
Rosaceae
Asteraceae
Rubiaceae
Dennstaedtiaceae
Pteridaceae
Pteridaceae
Pteridaceae
Lamiaceae
Rhamnaceae
Anacardiaceae
Anacardiaceae
Capparidaceae
Rosaceae
Rubiaceae
Rosaceae
Rubiaceae
Habit
H
H
H
H
T
T
T
T/Sh
T
H
T/Sh
F
F
F
F
H/Sh
T/Sh
T/Sh
T/Sh
T/Sh
Sh/Li/T
T/Sh
Sh
Sh
TBB
CCNP
S. No
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
Scientific Name
Salvia nilotica Jacq.
Sanicula elata Buch.–Ham. ex D. Don
Sapium ellipticum (Krauss) Pax
Satureja punctata (Benth.) Briq.
Satureja simensis (Benth.) Briq.
Scabiosa columbaria L.
Scadoxus multiflorus (Martyn) Raf.
Schefflera abyssinica (Hochst. ex. A. Rich) Harms
Schefflera volkensii (Engl.) Harms
Schrebera alata (Hochst.) Welw.
Senna petersiana (Bolle) Lock
Setaria megaphylla (Steud.) Th. Dur. & Schinz
Sida schimperiana Hochst. ex A. Rich.
Smilax anceps Willd
Smilax aspera L.
Solanecio gigas (Vatke) C. Jeffrey
Solanecio mannii (Hook. f.) C. Jeffrey
Solanum anguivi Lam.
Solanum giganteum Jacq.
Solanum nigrum L.
Sonchus bipontini Asch.
Sonchus oleraceus L.
Sparmannia ricinocarpa Eckl. & Zeyh.) O. Ktze.
Stachys aculeolata Hook.f
152
Family
Lamiaceae
Apiaceae
Euphorbiaceae
Lamiaceae
Lamiaceae
Dipsacaceae
Amarylidaceae
Araliaceae
Araliaceae
Oleaceae
Fabaceae
Poaceae
Malvaceae
Smilacaceae
Smilacaceae
Asteraceae
Asteraceae
Solanaceae
Solanaceae
Solanaceae
Asteraceae
Asteraceae
Tiliaceae
Lamiaceae
Habit
H
H
T/Sh
Sh
H
H
H
T
Sh/Li/T
T/Sh
T/Sh
G
Sh
Li
Li
T/Sh
T/Sh
H
T/Sh
H
H
H
Sh
Cl
TBB
CCNP
S. No
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
Scientific Name
Stephania abyssinica (Dillon & A. Rich.) Walp.
Streblochaete longiarista (A. Rich.) Pilg.
Swertia tetrandra Hochst.
Syzygium guineense (Wild.) DC. subsp. afromontanum F. White
Tacazzea apiculata Oliv.
Tacazzea conferta N. E. Br.
Tapinanthus heteromorphus (A. Rich.) Danser
Teclea nobilis Del.
Tephrosia interrupta Hoechst. & Steud ex Engl.
Tiliachora troupinii Cufod.
Toddalia asiatica (L.) Lam.
Tragia brevipes Pax
Trema orientalis (L.) Bl.
Trichilia dregena Sond.
Triumfetta brachyceras K. Schum.
Triumfetta rhomboidea Jacq.
Turraea holstii Gurke
Urera hypselodendron (A. Rich.) Weed.
Vepris dainellii (Pichi–serm.) Kokwaro
Verbascum sinaiticum Benth.
Vernonia amygdalina Del.
Vernonia bipontini Vatke
153
Family
Menispermaceae
Poaceae
Gentianaceae
Myrtaceae
Asclepiadaceae
Asclepiadaceae
Loranthaceae
Rutaceae
Fabaceae
Menispermaceae
Rutaceae
Euphorbiaceae
Ulmaceae
Meliaceae
Tiliaceae
Tiliaceae
Meliaceae
Urticaceae
Rutaceae
Scrophulariaceae
Asteraceae
Asteraceae
Habit
H
G
H
T
Li
Li
Sh
T/Sh
H/Sh
Li
H
H/Sh
T/Sh
T
H/Sh
H
T/Sh
Li
T/Sh
H
T/Sh
H/Sh
TBB
CCNP
Annex 2. List of plant families with their number of genera and species encountered at
the afromontane forest of TBB
Family
Asteraceae
Acanthaceae
Fabaceae
Lamiaceae
Rubiaceae
Euphorbiaceae
Celastraceae
Oleaceae
Rosaceae
Poaceae
Asclepiadaceae
Clusiaceae
Flacourtiaceae
Malvaceae
Meliaceae
Myrsinaceae
Rutaceae
Araliaceae
Boraginaceae
Menispermaceae
Pteridaceae
Rhamnaceae
Solanaceae
Tiliaceae
Amaranthaceae
Anacardiaceae
Apocynaceae
Cyperaceae
Dracaenaceae
Loranthaceae
Piperaceae
Plantaginaceae
Ranunculaceae
Sapindaceae
Scrophulariaceae
Smilacaceae
Ulmaceae
Vitaceae
Adiantaceae
No. of Species
19
12
11
11
9
8
7
6
6
5
4
4
4
4
4
4
4
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
%
9.31
5.88
5.39
5.39
4.41
3.92
3.43
2.94
2.94
2.45
1.96
1.96
1.96
1.96
1.96
1.96
1.96
1.47
1.47
1.47
1.47
1.47
1.47
1.47
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.49
154
No. of Genera
15
9
9
9
8
8
3
4
5
5
3
2
3
4
4
3
4
2
2
3
1
3
2
2
2
1
2
1
1
2
1
1
1
2
2
1
2
1
1
%
9.04
5.42
5.42
5.42
4.82
4.82
1.81
2.41
3.01
3.01
1.81
1.20
1.81
2.41
2.41
1.81
2.41
1.20
1.20
1.81
0.60
1.81
1.20
1.20
1.20
0.60
1.20
0.60
0.60
1.20
0.60
0.60
0.60
1.20
1.20
0.60
1.20
0.60
0.60
Family
Amarylidaceae
Apiaceae
Aquifoliaceae
Arecaceae
Asparagaceae
Capparidaceae
Combretaceae
Crassulaceae
Cucurbitaceae
Cuppressaceae
Dennstaedtiaceae
Dipsacaceae
Ericaceae
Gentianaceae
Icacinaceae
Iridaceae
Loganiaceae
Melianthaceae
Moraceae
Myricaceae
Myrtaceae
Oliniaceae
Phytolaccaceae
Pittosporaceae
Podocarpaceae
Rhizophoraceae
Santalaceae
Sapotaceae
Simarubaceae
Sterculariaceae
Urticaceae
Verbenaceae
No. of Species
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
%
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
155
No. of Genera
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
%
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
Annex 3. List of plant families with their number of genera and species encountered at
the afromontane forest of CCNP
Family
Fabaceae
Acanthaceae
Asteraceae
Euphorbiaceae
Rubiaceae
Celastraceae
Oleaceae
Rosaceae
Myrsinaceae
Rutaceae
Araliaceae
Boraginaceae
Lamiaceae
Piperaceae
Ranunculaceae
Anacardiaceae
Apiaceae
Apocynaceae
Asclepiadaceae
Clusiaceae
Cucurbitaceae
Cyperaceae
Dracaenaceae
Flacourtiaceae
Loganiaceae
Malvaceae
Meliaceae
Menispermaceae
Moraceae
Poaceae
Pteridaceae
Rhamnaceae
Sapindaceae
Smilacaceae
Ulmaceae
Urticaceae
Amaranthaceae
Aquifoliaceae
No. of Species
8
7
7
6
6
5
5
5
4
4
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
156
%
5.56
4.86
4.86
4.17
4.17
3.47
3.47
3.47
2.78
2.78
2.08
2.08
2.08
2.08
2.08
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
1.39
0.69
0.69
No. of Genera
7
6
7
6
6
3
4
5
3
4
2
3
3
2
1
1
2
2
2
1
2
1
1
2
2
2
2
2
1
2
1
2
2
1
2
2
1
1
%
5.51
4.72
5.51
4.72
4.72
2.36
3.15
3.94
2.36
3.15
1.57
2.36
2.36
1.57
0.79
0.79
1.57
1.57
1.57
0.79
1.57
0.79
0.79
1.57
1.57
1.57
1.57
1.57
0.79
1.57
0.79
1.57
1.57
0.79
1.57
1.57
0.79
0.79
Family
Arecaceae
Asparagaceae
Capparidaceae
Combretaceae
Commelinaceae
Cyatheaceae
Dennstaedtiaceae
Ericaceae
Geraniaceae
Icacinaceae
Lobeliaceae
Melastomataceae
Melianthaceae
Musaceae
Myricaceae
Myrtaceae
Oliniaceae
Phytolaccaceae
Pittosporaceae
Plantaginaceae
Rhizophoraceae
Sapotaceae
Simarubaceae
Solanaceae
Sterculariaceae
Tiliaceae
Vitaceae
Zingeberaceae
No. of Species
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
157
%
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
0.69
No. of Genera
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
%
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
0.79
Annex 4. Species indicator values for plant species at the Afromontane forest of TBB.
Values in bold refer to species used for naming the plant communities.
Plant Name
Apodytes dimidiata
Podocarpus falcatus
Syzygium guineense subsp.
afromontanum
Olea capensis subsp.
macrocarpa
Acanthus sennii
Maytenus undata
Embelia schimperi
Phoenix reclinata
Maesa lanceolata
Hypoestes triflora
Premna schimperi
Croton macrostachyus
Pouteria adolfi-friederici
Chionanthus mildbraedii
Allophylus abyssinicus
Setaria megaphylla
Calpurnia aurea
Landolphia buchananii
Solanecio mannii
Clutia abyssinica
Carissa spinarum
Rhus glutinosa
Macaranga capensis
Lepidotrichilia volkensii
Oxyanthus speciosus
Dracaena afromontana
Millettia ferruginea subsp.
darassana
Maytenus gracilipes subsp.
arguta
Desmodium repandum
Psychotria orophila
Cassipourea malosana
Elaeodendron buchananii
Olinia rochetiana
Ficus sur
Dombeya torrida
Sapium ellipticum
Comm. 1 Comm. 2
Comm. 3
Comm. 4 Comm. 5 P. value
0.35
0.34
0.13
0.26
0.12
0.15
0.03
0.17
0.03
0.00
0.005
0.002
0.33
0.23
0.21
0.19
0.00
0.001
0.26
0.24
0.22
0.10
0.09
0.08
0.06
0.06
0.01
0.04
0.23
0.08
0.17
0.01
0.01
0.00
0.00
0.00
0.00
0.03
0.00
0.07
0.05
0.19
0.23
0.02
0.00
0.00
0.00
0.05
0.02
0.54
0.31
0.26
0.19
0.17
0.17
0.03
0.03
0.03
0.03
0.03
0.17
0.00
0.03
0.03
0.22
0.08
0.00
0.00
0.00
0.00
0.03
0.00
0.06
0.09
0.26
0.17
0.07
0.03
0.00
0.00
0.00
0.00
0.00
0.55
0.46
0.43
0.41
0.18
0.24
0.00
0.02
0.00
0.01
0.04
0.00
0.05
0.25
0.23
0.14
0.16
0.14
0.02
0.00
0.00
0.00
0.00
0.00
0.24
0.33
0.39
0.08
0.22
0.00
0.00
0.00
0.07
0.01
0.00
0.00
0.00
0.00
0.00
0.08
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.003
0.141
0.025
0.142
0.135
0.319
0.894
0.330
0.001
0.016
0.018
0.299
0.694
0.182
0.757
1.000
1.000
1.000
1.000
0.001
0.001
0.001
0.001
0.00
0.14
0.40
0.27
0.00
0.001
0.15
0.01
0.15
0.00
0.00
0.24
0.06
0.00
0.00
0.06
0.01
0.14
0.03
0.00
0.02
0.17
0.03
0.00
0.37
0.35
0.30
0.30
0.28
0.26
0.24
0.24
0.23
0.12
0.01
0.21
0.04
0.11
0.18
0.13
0.02
0.06
0.00
0.01
0.00
0.00
0.00
0.15
0.00
0.06
0.00
0.001
0.009
0.017
0.017
0.008
0.059
0.122
0.023
0.026
158
Plant Name
Oplismenus hirtellus
Ritchiea albersii
Hippocratea goetzei
Dracaena steudneri
Rhamnus prinoides
Clausena anisata
Pittosporum viridiflorum
Rytigynia neglecta
Albizia gummifera
Teclea nobilis
Vepris dainellii
Schefflera abyssinica
Ehretia cymosa
Canthium oligocarpum
Prunus africana
Celtis africana
Brucea antidysenterica
Ekebergia capensis
Bersama abyssinica
Galiniera saxifraga
Oncoba spinosa
Polyscias fulva
Schefflera volkensii
Myrsine melanophloes
Hagenia abyssinica
Erica arborea
Maytenus addat
Arundinaria alpina
Ilex mitis
Acanthopale pubescens
Juniperus procera
Nuxia congesta
Hypericum revolutum
Myrica salicifolia
Osyris quadripartita
Myrsine africana
Comm. 1 Comm. 2
0.18
0.00
0.02
0.00
0.01
0.01
0.00
0.02
0.00
0.05
0.21
0.00
0.00
0.11
0.07
0.01
0.00
0.00
0.16
0.04
0.00
0.14
0.00
0.00
0.01
0.00
0.01
0.00
0.05
0.12
0.04
0.07
0.00
0.00
0.00
0.03
0.20
0.00
0.08
0.00
0.02
0.02
0.00
0.08
0.05
0.10
0.05
0.00
0.02
0.05
0.09
0.09
0.00
0.00
0.21
0.00
0.03
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.07
0.00
0.01
0.00
0.00
0.00
0.03
159
Comm. 3
0.21
0.16
0.15
0.14
0.03
0.08
0.12
0.38
0.12
0.30
0.33
0.28
0.03
0.09
0.07
0.03
0.20
0.08
0.06
0.19
0.14
0.10
0.05
0.02
0.00
0.00
0.00
0.00
0.24
0.02
0.00
0.03
0.00
0.00
0.00
0.01
Comm. 4 Comm. 5 P. value
0.18
0.09
0.08
0.08
0.02
0.50
0.46
0.40
0.36
0.35
0.34
0.31
0.31
0.30
0.29
0.28
0.26
0.22
0.21
0.21
0.20
0.16
0.13
0.04
0.00
0.00
0.00
0.00
0.11
0.18
0.00
0.08
0.00
0.00
0.00
0.04
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.03
0.01
0.00
0.00
0.06
0.66
0.58
0.50
0.45
0.33
0.32
0.30
0.26
0.23
0.17
0.17
0.16
0.14
0.654
0.044
0.227
0.111
1.000
0.001
0.003
0.001
0.006
0.002
0.001
0.005
0.009
0.016
0.021
0.023
0.025
0.025
0.259
0.102
0.079
0.493
0.161
0.001
0.001
0.002
0.001
0.004
0.018
0.018
0.006
0.039
0.052
0.049
0.027
0.145
Annex 5. Species indicator values for plant species at the Afromontane forest of CCNP.
Values in bold refer to the species used for naming the plant communities.
Plant Name
Olea capensis subsp. macrocarpa
Macaranga capensis
Desmodium repandum
Apodytes dimidiata
Pouteria adolfi-friederici
Millettia ferruginea subsp. darassana
Vepris dainellii
Prunus africana
Oxyanthus speciosus
Psychotria orophila
Piper capense
Rothmannia urcelliformis
Bersama abyssinica
Albizia gummifera
Dombeya torrida
Teclea nobilis
Oncoba spinosa
Ehretia cymosa
Phoenix reclinata
Olea welwitschii
Cordia africana
Aframomum corrorima
Ritchiea albersii
Justicia schimperiana
Hypoestes triflora
Cyathea maniana
Lepidotrichilia volkensii
Polyscias fulva
Pittosporum viridiflorum
Hippocratea africana
Dracaena afromontana
Hippocratea goetzei
Galiniera saxifraga
Syzygium guineense subsp.
afromontanum
Ficus sur
Schefflera abyssinica
Chionanthus mildbraedii
Canthium oligocarpum
Clausena anisata
Comm. 1 Comm. 2 Comm. 3
0.00
0.00
0.70
0.04
0.08
0.51
0.48
0.02
0.00
0.45
0.00
0.16
0.40
0.02
0.01
0.39
0.38
0.24
0.38
0.23
0.28
0.38
0.34
0.00
0.35
0.33
0.33
0.33
0.32
0.27
0.32
0.10
0.00
0.32
0.10
0.00
0.29
0.23
0.01
0.26
0.09
0.04
0.22
0.01
0.12
0.21
0.10
0.19
0.18
0.08
0.04
0.18
0.07
0.02
0.18
0.07
0.02
0.18
0.04
0.00
0.18
0.04
0.00
0.13
0.00
0.00
0.12
0.00
0.02
0.04
0.02
0.02
0.03
0.00
0.00
0.01
0.00
0.84
0.45
0.01
0.49
0.31
0.47
0.01
0.32
0.45
0.02
0.12
0.43
0.00
0.36
0.42
0.16
0.16
0.37
0.01
0.29
0.36
0.05
0.30
0.33
0.13
0.31
0.19
0.16
160
0.35
0.35
0.34
0.34
0.30
0.30
0.35
0.09
0.04
0.33
0.20
0.14
P. value
0.001
0.001
0.002
0.002
0.001
0.054
0.131
0.020
0.549
0.776
0.026
0.016
0.134
0.154
0.156
0.699
0.375
0.218
0.278
0.124
0.127
0.134
0.271
1.000
1.000
0.001
0.001
0.003
0.005
0.002
0.001
0.018
0.055
0.252
0.180
0.024
0.875
0.408
0.253
Plant Name
Myrsine melanophloes
Celtis africana
Brucea antidysenterica
Allophylus abyssinicus
Coffea arabica
Nuxia congesta
Agarista salicifolia
Acanthopale pubescens
Oplismenus hirtellus
Ilex mitis
Schefflera volkensii
Setaria megaphylla
Maesa lanceolata
Maytenus gracilipes subsp. arguta
Croton macrostachyus
Calpurnia aurea
Rytigynia neglecta
Achyranthes aspera
Landolphia buchananii
Dracaena steudneri
Cassipourea malosana
Ekebergia capensis
Vernonia amygdalina
Comm. 1 Comm. 2 Comm. 3
0.00
0.27
0.00
0.05
0.26
0.12
0.14
0.25
0.03
0.20
0.24
0.17
0.00
0.00
1.00
0.00
0.00
1.00
0.00
0.00
0.94
0.08
0.06
0.80
0.11
0.09
0.67
0.12
0.04
0.65
0.00
0.00
0.63
0.04
0.07
0.54
0.01
0.00
0.50
0.28
0.24
0.43
0.07
0.29
0.38
0.00
0.00
0.38
0.23
0.35
0.37
0.00
0.00
0.28
0.18
0.00
0.19
0.16
0.05
0.17
0.10
0.11
0.14
0.04
0.00
0.07
0.00
0.00
0.06
161
P. value
0.002
0.103
0.126
0.796
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.002
0.001
0.008
0.037
0.001
0.258
0.007
0.341
0.714
0.829
0.565
0.525
Annex 6. Density of woody species along DBH-classes at the Afromontane forest of TBB
Scientific Name
Acanthus sennii
Albizia gummifera
Allophylus abyssinicus
Apodytes dimidiata
Arundinaria alpina
Bersama abyssinica
Brucea antidysenterica
Calpurnia aurea
Canthium oligocarpum
Carissa spinarum
Cassipourea malosana
Celtis africana
Chionanthus mildbraedii
Clausena anisata
Clutia abyssinica
Croton macrostachyus
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
Ehretia cymosa
Ekebergia capensis
Elaeodendron buchananii
1
1.8
4.7
3.1
6.2
36.5
25.6
4.0
12.8
11.9
0.6
3.2
3.3
117.9
18.5
0.4
0.4
0.4
22.2
0.0
0.8
0.1
0.4
162
2
0.1
3.0
5.3
5.7
11.7
13.5
1.0
8.2
3.1
0.2
1.0
1.2
40.0
2.4
0.0
0.6
0.7
20.2
0.0
1.1
0.2
0.3
3
0.0
1.8
4.6
5.1
0.0
4.3
0.0
3.7
1.5
0.2
1.7
2.3
6.5
0.5
0.0
2.7
0.8
7.3
0.1
1.8
0.0
0.6
4
0.0
1.4
3.3
3.0
0.0
1.6
0.0
0.4
0.7
0.0
0.3
1.0
1.1
0.0
0.0
2.4
0.4
2.3
0.6
1.5
0.2
0.2
DBH Classes
5
6
0.0
0.0
1.4
1.9
2.7
2.1
1.4
1.5
0.0
0.0
0.3
0.0
0.0
0.0
0.2
0.0
0.3
0.0
0.0
0.0
0.2
0.2
0.8
1.2
0.2
0.0
0.0
0.0
0.0
0.0
3.6
5.4
0.5
0.8
1.0
0.0
0.4
0.3
0.5
0.1
0.3
0.2
0.2
0.3
7
0.0
0.6
2.1
1.7
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.7
0.0
0.0
0.0
3.4
0.4
0.0
0.1
0.0
0.0
0.2
8
0.0
0.7
0.8
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.7
0.0
0.0
0.0
4.4
0.0
0.0
0.1
0.0
0.1
0.1
9
0.0
0.2
1.4
1.7
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.8
0.0
0.0
0.0
2.1
0.1
0.0
0.0
0.0
0.2
0.2
10
0.0
0.7
0.9
2.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
1.1
0.4
0.0
0.0
0.0
0.0
0.0
11
0.0
1.6
1.6
1.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.2
0.0
0.0
0.0
2.9
0.0
0.0
0.0
0.0
0.5
0.4
Total density
1.9
17.9
27.9
31.3
48.2
45.6
5.1
25.3
17.4
0.9
6.7
13.2
165.7
21.4
0.4
28.9
4.4
53.0
1.5
5.8
1.7
2.7
Scientific Name
Erica arborea
Ficus sur
Galiniera saxifraga
Hagenia abyssinica
Hypericum revolutum
Ilex mitis
Juniperus procera
Justicia schimperiana
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus addat
Maytenus gracilipes subsp. arguta
Maytenus undata
Millettia ferruginea
Myrica salicifolia
Myrsine africana
Myrsine melanophloes
Nuxia congesta
Olea capensis subsp. macrocarpa
Olinia rochetiana
Oncoba spinosa
Osyris quadripartita
Oxyanthus speciosus
1
30.2
3.3
3.6
0.2
0.0
11.5
0.1
0.3
3.8
4.2
0.4
1.0
51.2
3.0
13.9
0.2
6.0
16.5
2.7
42.5
6.1
2.5
0.3
36.0
163
2
9.0
5.7
3.6
0.3
0.2
10.6
0.0
0.0
3.3
6.3
1.4
0.2
2.1
1.0
15.7
0.1
0.0
12.8
2.8
53.5
7.7
2.0
1.1
19.0
3
2.0
4.3
3.5
0.6
0.6
10.3
0.0
0.0
3.5
5.2
1.0
0.3
0.5
1.1
13.3
0.1
0.0
3.1
1.9
33.7
8.4
0.0
0.0
4.3
4
0.1
4.7
0.8
1.0
0.0
5.6
0.0
0.0
1.3
4.0
0.4
0.1
0.0
0.9
6.2
0.0
0.0
1.5
0.6
12.4
7.0
0.0
0.0
1.6
DBH Classes
5
6
0.0
0.0
3.9
3.0
0.3
0.1
0.8
0.5
0.0
0.0
4.3
4.2
0.3
0.3
0.0
0.0
0.3
0.2
5.9
4.0
0.0
0.2
0.1
0.1
0.0
0.0
0.7
0.7
4.4
2.4
0.0
0.0
0.0
0.0
1.5
0.8
0.2
0.3
7.3
8.8
7.0
2.5
0.0
0.0
0.0
0.0
0.6
0.3
7
0.0
2.1
0.0
0.5
0.0
2.7
0.5
0.0
0.0
4.3
0.0
0.0
0.0
0.0
1.3
0.0
0.0
1.6
0.0
5.6
4.7
0.0
0.0
0.0
8
0.0
1.2
0.0
0.6
0.0
2.1
0.3
0.0
0.1
3.7
0.0
0.7
0.0
0.3
0.8
0.0
0.0
0.9
0.5
4.7
3.3
0.0
0.0
0.0
9
0.0
1.7
0.0
0.4
0.0
1.0
0.1
0.0
0.0
4.8
0.0
0.3
0.0
0.4
0.5
0.0
0.0
0.4
0.0
3.0
1.9
0.0
0.0
0.0
10
0.0
2.0
0.0
0.8
0.0
0.7
0.1
0.0
0.0
2.4
0.0
0.4
0.0
0.1
0.0
0.0
0.0
0.2
0.1
2.9
1.7
0.0
0.0
0.0
11
0.0
5.6
0.0
0.4
0.0
2.4
1.7
0.0
0.0
3.5
0.0
0.3
0.0
0.2
0.1
0.0
0.0
0.0
0.0
14.0
4.5
0.0
0.0
0.0
Total density
41.3
37.5
11.8
6.0
0.8
55.5
3.3
0.3
12.4
48.3
3.4
3.4
53.8
8.4
58.8
0.4
6.0
39.3
9.0
188.5
54.8
4.5
1.4
61.8
Scientific Name
Phoenix reclinata
Pittosporum viridiflorum
Podocarpus falcatus
Polyscias fulva
Pouteria adolfi–friederici
Premna schimperi
Prunus africana
Psychotria orophila
Rhamnus prinoides
Rhus glutinosa
Ritchiea albersii
Rytigynia neglecta
Sapium ellipticum
Schefflera abyssinica
Schefflera volkensii
Solanecio mannii
Syzygium guineense subsp.
afromontanum
Teclea nobilis
Vepris dainelli
Vernonia amygdalina
Total
1
0.0
1.5
39.4
0.8
21.3
0.1
7.9
66.2
0.2
0.2
0.1
52.5
0.0
0.0
0.3
0.1
2
0.0
2.4
22.7
1.4
11.5
0.5
1.8
24.7
0.0
0.0
1.6
10.6
0.0
0.2
0.0
0.0
3
0.1
0.9
13.2
1.2
8.2
0.4
2.3
4.9
0.0
0.0
0.4
0.6
0.0
0.0
0.1
0.0
4
0.4
0.3
6.6
1.7
3.9
0.0
0.6
0.2
0.0
0.0
0.3
0.0
0.0
0.1
0.3
0.0
DBH Classes
5
6
0.0
0.0
0.2
0.0
5.6
5.5
1.5
0.2
4.0
3.1
0.0
0.0
1.4
1.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.2
0.4
0.1
0.3
0.0
0.0
32.2
33.9
31.5
0.4
802.9
33.0
9.0
23.2
0.1
420.6
22.2
1.9
13.9
0.2
213.4
11.1
0.1
4.8
0.2
98.9
6.1
0.0
1.8
0.0
72.4
164
6.8
0.0
0.5
0.0
60.9
7
0.0
0.0
1.8
1.6
2.2
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.5
0.2
0.1
0.0
8
0.0
0.0
2.3
1.6
2.7
0.0
2.3
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
9
0.0
0.0
3.2
1.1
2.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.2
0.0
10
0.0
0.0
1.5
1.8
0.8
0.0
0.5
0.0
0.0
0.0
0.0
0.6
0.0
0.2
0.3
0.0
11
0.0
0.0
3.7
4.1
8.0
0.0
3.2
0.0
0.0
0.0
0.0
0.0
0.1
3.8
1.6
0.0
Total density
0.5
5.3
105.3
17.1
67.6
0.9
23.3
96.0
0.2
0.2
2.4
64.3
1.4
5.1
3.2
0.1
7.6
0.0
0.3
0.0
47.7
5.0
0.0
0.1
0.0
41.3
3.7
0.0
0.0
0.0
32.0
4.6
0.0
0.0
0.0
26.8
17.5
0.0
0.0
0.0
84.7
149.8
44.9
76.0
0.8
1901.8
Annex 7. Density of woody species along height-classes at the Afromontane forest of TBB
Scientific Name
Acanthus sennii
Albizia gummifera
Allophylus abyssinicus
Apodytes dimidiata
Arundinaria alpina
Bersama abyssinica
Brucea antidysenterica
Calpurnia aurea
Canthium oligocarpum
Carissa spinarum
Cassipourea malosana
Celtis africana
Chionanthus mildbraedii
Clausena anisata
Clutia abyssinica
Croton macrostachyus
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
Ehretia cymosa
Ekebergia capensis
Elaeodendron buchananii
1
1.9
5.4
7.0
8.8
11.5
33.5
4.7
13.2
14.3
0.4
4.3
3.7
145.3
18.8
0.4
1.1
0.8
52.4
0.0
2.7
0.2
0.3
165
2
0.0
3.8
9.1
10.1
27.8
11.2
0.4
11.1
2.7
0.6
1.6
2.9
19.6
2.5
0.0
7.5
2.2
0.6
1.0
2.0
0.4
0.8
3
0.0
2.9
7.3
6.5
8.9
0.8
0.0
1.0
0.4
0.0
0.8
2.2
0.8
0.0
0.0
9.3
1.4
0.0
0.4
1.1
0.3
0.9
Height Classes
4
0.0
2.2
3.7
4.3
0.0
0.1
0.0
0.0
0.0
0.0
0.0
3.8
0.0
0.0
0.0
8.3
0.0
0.0
0.1
0.0
0.4
0.4
5
0.0
1.8
0.8
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
2.3
0.0
0.0
0.0
0.0
0.4
0.3
6
0.0
1.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.1
0.0
7
0.0
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Total density
1.9
17.9
27.9
31.3
48.2
45.6
5.1
25.3
17.4
0.9
6.7
13.2
165.7
21.4
0.4
28.9
4.4
53.0
1.5
5.8
1.7
2.7
Scientific Name
Erica arborea
Ficus sur
Galiniera saxifraga
Hagenia abyssinica
Hypericum revolutum
Ilex mitis
Juniperus procera
Justicia schimperiana
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus addat
Maytenus gracilipes subsp. arguta
Maytenus undata
Millettia ferruginea subsp. darassana
Myrica salicifolia
Myrsine africana
Myrsine melanophloes
Nuxia congesta
Olea capensis subsp. macrocarpa
Olinia rochetiana
Oncoba spinosa
Osyris quadripartita
Oxyanthus speciosus
1
41.0
6.9
10.4
0.5
0.6
23.5
0.1
0.3
6.8
6.5
2.5
0.8
53.7
4.8
19.1
0.2
6.0
22.1
4.7
64.6
9.8
2.5
1.4
52.9
166
2
0.4
10.3
1.4
2.2
0.2
18.0
0.2
0.0
5.6
17.0
0.8
1.2
0.1
2.8
24.3
0.2
0.0
12.1
4.3
77.2
23.4
1.9
0.0
8.9
3
0.0
8.4
0.0
1.8
0.0
8.0
0.7
0.0
0.1
15.5
0.0
1.0
0.0
0.7
11.9
0.0
0.0
3.1
0.0
25.3
10.5
0.1
0.0
0.0
Height Classes
4
0.0
7.1
0.0
1.5
0.0
4.4
1.0
0.0
0.0
7.2
0.1
0.3
0.0
0.1
2.9
0.0
0.0
1.8
0.0
14.1
8.9
0.0
0.0
0.0
5
0.0
3.2
0.0
0.1
0.0
1.0
0.5
0.0
0.0
1.7
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.1
0.0
5.0
2.0
0.0
0.0
0.0
6
0.0
1.5
0.0
0.0
0.0
0.3
0.5
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.7
0.2
0.0
0.0
0.0
7
0.0
0.2
0.0
0.0
0.0
0.2
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
Total density
41.3
37.5
11.8
6.0
0.8
55.5
3.3
0.3
12.4
48.3
3.4
3.4
53.8
8.4
58.8
0.4
6.0
39.3
9.0
188.5
54.8
4.5
1.4
61.8
Scientific Name
Phoenix reclinata
Pittosporum viridiflorum
Podocarpus falcatus
Polyscias fulva
Pouteria adolfi–friederici
Premna schimperi
Prunus africana
Psychotria orophila
Rhamnus prinoides
Rhus glutinosa
Ritchiea albersii
Rytigynia neglecta
Sapium ellipticum
Schefflera abyssinica
Schefflera volkensii
Solanecio mannii
Syzygium guineense subsp. afromontanum
Teclea nobilis
Vepris dainelli
Vernonia amygdalina
Total density
167
1
0.1
4.2
47.5
0.4
25.1
0.6
9.3
90.1
0.2
0.2
2.0
58.4
0.0
0.2
0.5
0.1
50.9
41.3
51.8
0.5
1055.7
2
0.2
1.0
32.7
6.0
16.6
0.4
4.7
5.8
0.0
0.0
0.4
5.1
0.3
0.5
1.0
0.0
44.8
3.6
23.1
0.4
476.8
Height Classes
3
4
0.2
0.0
0.0
0.0
12.1
8.6
5.1
3.1
9.5
8.6
0.0
0.0
3.3
3.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.8
0.4
2.4
0.7
1.0
0.2
0.0
0.0
25.4
17.5
0.0
0.0
1.1
0.0
0.0
0.0
193.3
115.2
5
0.0
0.0
3.3
1.8
4.1
0.0
2.1
0.0
0.0
0.0
0.0
0.6
0.0
1.2
0.5
0.0
8.0
0.0
0.0
0.0
42.9
6
0.0
0.0
1.0
0.6
1.9
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
2.8
0.0
0.0
0.0
13.2
7
0.0
0.0
0.2
0.2
1.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
4.6
Total density
0.5
5.3
105.3
17.1
67.6
0.9
23.3
96.0
0.2
0.2
2.4
64.3
1.4
5.1
3.2
0.1
149.8
44.9
76.0
0.8
1901.8
Annex 8. Density of woody species along DBH-classes at the Afromontane forest of CCNP
Scientific Name
Agarista salicifolia
Albizia gummifera
Allophylus abyssinicus
Apodytes dimidiata
Bersama abyssinica
Brucea antidysenterica
Calpurnia aurea
Canthium oligocarpum
Cassipourea malosana
Celtis africana
Chionanthus mildbraedii
Clausena anisata
Coffea arabica
Cordia africana
Croton macrostachyus
Cyathea maniana
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
Ehretia cymosa
Ekebergia capensis
1
0.9
3.3
3.8
3.1
8.7
7.5
2.6
14.8
3.8
4.0
108.6
13.7
8.4
1.5
0.4
0.4
0.5
26.8
0.0
0.5
0.2
168
2
2.0
2.7
3.3
3.3
3.5
2.0
0.7
3.8
1.5
1.8
48.5
2.9
5.5
0.5
0.4
3.6
1.3
51.7
0.0
1.1
0.2
3
2.4
1.8
2.0
4.4
0.5
0.0
0.7
1.5
1.6
2.7
4.4
0.5
0.7
0.2
1.5
16.0
1.5
37.5
0.4
1.3
0.0
4
0.9
0.4
0.2
2.2
0.0
0.0
0.2
0.7
0.4
0.7
1.5
0.0
0.0
0.7
0.9
1.5
0.7
10.7
2.2
2.7
0.0
DBH Classes
5
6
7
3.3
1.1
1.8
1.1
0.7
0.5
1.5
0.5
1.3
1.1
0.4
1.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.2
0.2
0.0
0.7
1.5
0.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
2.0
2.6
3.1
0.0
0.0
0.0
0.7
1.3
0.5
6.4
0.4
0.0
1.5
1.1
0.4
0.4
0.2
0.0
0.0
0.2
0.0
8
0.7
0.2
0.4
1.5
0.0
0.0
0.0
0.0
0.2
1.1
0.0
0.0
0.0
0.4
2.2
0.0
0.0
0.0
0.4
0.0
0.0
9
0.9
0.4
1.1
2.4
0.0
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.0
0.0
0.9
0.0
0.2
0.0
0.0
0.0
0.0
10
0.5
0.2
0.9
2.2
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.2
0.7
0.0
0.5
0.0
0.0
0.0
0.0
11
0.5
0.7
1.5
5.8
0.0
0.0
0.0
0.0
0.0
1.5
0.0
0.0
0.0
0.0
2.6
0.0
0.0
0.0
0.0
0.0
0.5
Total density
15.1
12.0
16.4
28.1
12.8
9.5
4.2
21.3
7.8
15.7
162.8
17.1
14.6
3.6
17.1
21.5
7.3
133.5
5.8
6.2
1.1
Scientific Name
Ficus sur
Galiniera saxifraga
Ilex mitis
Landolphia buchananii
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus gracilipes subsp. arguta
Millettia ferruginea
Myrsine melanophloes
Nuxia congesta
Olea capensis subsp. macrocarpa
Olea welwitschii
Oncoba spinosa
Oxyanthus speciosus
Phoenix reclinata
Pittosporum viridiflorum
Polyscias fulva
Pouteria adolfi–friederici
Prunus africana
Psychotria orophila
Ritchiea albersii
Rothmannia urcelliformis
Rytigynia neglecta
1
0.5
17.9
4.7
0.9
18.0
3.1
0.4
66.3
11.7
1.8
5.8
1.1
1.5
3.6
90.3
0.5
12.9
1.3
1.1
14.6
63.4
0.0
1.3
40.8
169
2
3.3
8.6
5.8
0.5
14.0
5.8
1.5
3.6
12.8
1.6
9.7
2.2
0.5
2.6
52.5
1.1
6.4
2.2
0.5
2.9
38.4
1.3
4.2
8.9
3
0.9
32.2
7.5
1.3
13.7
4.7
2.9
0.7
11.7
0.2
4.9
0.2
0.2
0.0
11.5
1.3
2.2
2.0
0.4
1.6
7.5
0.0
2.0
0.5
4
1.5
6.9
2.9
0.4
4.7
3.8
0.5
0.0
6.9
0.0
1.5
0.0
0.7
0.0
3.8
2.7
0.4
2.4
0.0
0.4
0.2
0.0
0.5
0.0
DBH Classes
5
6
7
1.5
0.9
0.4
0.0
0.4
0.0
1.1
2.0
0.9
0.4
0.5
0.4
1.3
0.7
0.0
3.1
4.4
2.9
0.0
0.4
0.0
0.0
0.0
0.0
5.8
2.6
1.5
0.0
0.0
0.5
0.0
0.7
0.0
0.0
0.2
0.4
0.0
0.2
0.0
0.0
0.0
0.0
1.3
0.5
0.0
0.4
0.2
0.0
0.0
0.0
0.0
0.4
0.4
1.3
0.2
0.4
0.0
2.7
1.1
1.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
8
0.2
0.0
1.1
0.2
0.4
2.6
0.0
0.0
0.7
0.2
1.6
0.0
0.4
0.0
0.0
0.0
0.0
0.7
0.2
2.0
0.0
0.0
0.0
0.0
9
0.9
0.0
2.6
0.4
0.5
4.4
0.0
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.0
0.0
0.0
1.3
0.0
2.0
0.0
0.0
0.0
0.0
10
0.7
0.0
1.8
0.0
0.5
1.3
0.0
0.0
0.0
0.0
0.0
1.5
0.2
0.0
0.0
0.0
0.0
1.3
0.5
1.8
0.0
0.0
0.0
0.4
11
10.9
0.0
12.8
0.7
2.2
2.2
0.0
0.0
0.2
0.0
0.0
7.5
0.0
0.0
0.0
0.0
0.0
4.4
4.9
14.9
0.0
0.0
0.0
0.0
Total density
21.7
65.9
43.2
5.6
56.1
38.3
5.6
70.7
53.7
4.4
24.2
13.7
3.6
6.2
159.9
6.2
21.9
17.5
8.2
45.4
109.5
1.3
8.0
50.6
Scientific Name
Schefflera abyssinica
Schefflera volkensii
Syzygium guineense subsp.
afromontanum
Teclea nobilis
Vepris dainellii
Vernonia amygdalina
Total
1
0.0
0.5
2
0.5
0.2
3
0.0
0.2
4
0.0
0.2
DBH Classes
5
6
7
0.5
0.4
0.5
0.2
0.5
0.4
20.6
6.4
15.3
0.4
620.0
24.8
2.9
12.0
0.0
371.6
22.0
0.9
6.4
0.0
221.1
11.1
0.0
2.4
0.0
80.5
5.5
0.0
0.4
0.0
43.9
170
6.6
0.0
0.2
0.0
33.3
6.2
0.0
0.2
0.0
27.0
8
0.4
0.0
9
0.2
0.2
10
0.4
0.9
11
7.7
3.5
Total density
10.6
6.7
4.0
0.0
0.0
0.0
21.5
3.6
0.0
0.0
0.0
23.3
5.8
0.0
0.0
0.0
22.6
12.2
0.0
0.0
0.0
97.1
122.4
10.2
36.8
0.4
1561.9
Annex 9. Density of woody species along height-classes at the Afromontane forest of CCNP
Scientific Name
Agarista salicifolia
Albizia gummifera
Allophylus abyssinicus
Apodytes dimidiata
Bersama abyssinica
Brucea antidysenterica
Calpurnia aurea
Canthium oligocarpum
Cassipourea malosana
Celtis africana
Chionanthus mildbraedii
Clausena anisata
Coffea arabica
Cordia africana
Croton macrostachyus
Cyathea maniana
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
Ehretia cymosa
Ekebergia capensis
Ficus sur
1
2.7
4.0
5.8
6.4
10.6
8.9
1.6
17.7
5.3
4.7
140.3
14.9
14.6
1.5
0.4
13.1
1.5
133.3
0.0
3.1
0.4
2.6
171
2
6.9
2.4
3.1
5.8
2.0
0.5
2.2
3.3
1.6
3.6
21.9
2.2
0.0
0.9
3.6
7.8
3.6
0.2
4.0
2.2
0.2
5.8
3
5.5
1.6
4.9
4.2
0.2
0.0
0.4
0.4
0.9
2.4
0.7
0.0
0.0
0.5
6.9
0.5
2.2
0.0
1.5
0.9
0.0
6.4
Height Classes
4
0.0
1.6
2.2
4.9
0.0
0.0
0.0
0.0
0.0
4.2
0.0
0.0
0.0
0.5
5.3
0.0
0.0
0.0
0.4
0.0
0.2
3.8
5
0.0
1.1
0.4
3.1
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.9
0.0
0.0
0.0
0.0
0.0
0.2
1.6
6
0.0
0.7
0.0
1.1
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.4
7
0.0
0.5
0.0
2.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.1
Total density
15.1
12.0
16.4
28.1
12.8
9.5
4.2
21.3
7.8
15.7
162.8
17.1
14.6
3.6
17.1
21.5
7.3
133.5
5.8
6.2
1.1
21.7
Scientific Name
Galiniera saxifraga
Ilex mitis
Landolphia buchananii
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus gracilipes subsp. arguta
Millettia ferruginea
Myrsine melanophloes
Nuxia congesta
Olea capensis subsp. macrocarpa
Olea welwitschii
Oncoba spinosa
Oxyanthus speciosus
Phoenix reclinata
Pittosporum viridiflorum
Polyscias fulva
Pouteria adolfi–friederici
Prunus africana
Psychotria orophila
Ritchiea albersii
Rothmannia urcelliformis
Rytigynia neglecta
Schefflera abyssinica
1
65.9
12.6
0.7
31.0
4.6
4.6
70.5
14.9
2.4
10.7
1.1
1.5
3.6
142.4
3.1
20.2
0.7
1.6
17.1
103.5
1.3
5.8
43.5
0.5
172
2
0.0
14.9
1.6
21.3
12.4
1.1
0.2
23.1
1.6
13.5
5.3
0.9
2.6
17.5
2.2
1.6
6.9
1.5
10.2
6.0
0.0
2.2
6.2
0.9
Height Classes
3
4
0.0
0.0
6.7
7.3
2.0
0.7
0.7
1.1
14.9
4.2
0.0
0.0
0.0
0.0
14.6
0.5
0.2
0.2
0.0
0.0
4.9
1.5
0.5
0.5
0.0
0.0
0.0
0.0
0.9
0.0
0.0
0.0
6.0
1.6
1.1
0.7
6.0
6.9
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
5.1
1.1
5
0.0
0.9
0.5
0.5
2.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.6
1.5
3.6
0.0
0.0
0.0
0.4
2.7
6
0.0
0.5
0.0
0.4
0.2
0.0
0.0
0.0
0.0
0.0
0.9
0.2
0.0
0.0
0.0
0.0
0.4
1.1
0.7
0.0
0.0
0.0
0.0
0.2
7
0.0
0.2
0.0
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.7
0.7
0.0
0.0
0.0
0.0
0.0
Total density
65.9
43.2
5.6
56.1
38.3
5.6
70.7
53.7
4.4
24.2
13.7
3.6
6.2
159.9
6.2
21.9
17.5
8.2
45.4
109.5
1.3
8.0
50.6
10.6
Scientific Name
Schefflera volkensii
Syzygium guineense subsp. afromontanum
Teclea nobilis
Vepris dainellii
Vernonia amygdalina
Total density
173
1
1.1
35.9
9.1
24.0
0.4
1027.7
2
1.6
39.2
1.1
12.6
0.0
292.2
Height Classes
3
4
5
2.4
0.5
1.1
22.6
16.0
6.2
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
129.5
66.1
29.5
6
0.0
2.2
0.0
0.0
0.0
9.5
7
0.0
0.4
0.0
0.0
0.0
7.5
Total density
6.7
122.4
10.2
36.8
0.4
1561.9
Annex 10. Frequency, Density, Basal Area and Important value indices of Woody species at the Afromontane forest of TBB
Where: P=Number of plot where a species was present, F=Frequency, N=Number/count of individuals, D=Density, BA=Basal Area,
Av.BA=Average BA, DO=Dominance, RF=Relative Frequency, RD=Relative Density, RDO=Relative dominance and IVI=Importance value
index.
Scientific Name
Acanthus sennii
Albizia gummifera
Allophylus abyssinicus
Apodytes dimidiata
Arundinaria alpina
Bersama abyssinica
Brucea antidysenterica
Calpurnia aurea
Canthium oligocarpum
Carissa spinarum
Cassipourea malosana
Celtis africana
Chionanthus mildbraedii
Clausena anisata
Clutia abyssinica
Croton macrostachyus
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
Ehretia cymosa
P
7
38
66
71
2
80
28
34
56
1
26
35
111
41
1
60
19
73
11
23
F
0.0593
0.3220
0.5593
0.6017
0.0169
0.6780
0.2373
0.2881
0.4746
0.0085
0.2203
0.2966
0.9407
0.3475
0.0085
0.5085
0.1610
0.6186
0.0932
0.1949
174
N
20
190
296
332
512
484
54
269
185
10
71
140
1760
227
4
307
47
563
16
62
D
1.8832
17.8908
27.8719
31.2618
48.2109
45.5744
5.0847
25.3296
17.4200
0.9416
6.6855
13.1827
165.7250
21.3748
0.3766
28.9077
4.4256
53.0132
1.5066
5.8380
BA
0.0022
1.1529
1.8143
1.8181
0.0946
0.2395
0.0094
0.1214
0.0690
0.0037
0.0652
0.7750
0.4437
0.0377
0.0002
2.6504
0.1990
0.3028
0.0615
0.0863
Av. BA
0.0001
0.0061
0.0061
0.0055
0.0002
0.0005
0.0002
0.0005
0.0004
0.0004
0.0009
0.0055
0.0003
0.0002
0.0000
0.0086
0.0042
0.0005
0.0038
0.0014
DO
0.0022
1.1529
1.8143
1.8181
0.0946
0.2395
0.0094
0.1214
0.0690
0.0037
0.0652
0.7750
0.4437
0.0377
0.0002
2.6504
0.1990
0.3028
0.0615
0.0863
RF
0.2828
1.5354
2.6667
2.8687
0.0808
3.2323
1.1313
1.3737
2.2626
0.0404
1.0505
1.4141
4.4848
1.6566
0.0404
2.4242
0.7677
2.9495
0.4444
0.9293
RD
0.0990
0.9407
1.4656
1.6438
2.5350
2.3964
0.2674
1.3319
0.9160
0.0495
0.3515
0.6932
8.7142
1.1239
0.0198
1.5200
0.2327
2.7875
0.0792
0.3070
RDO
0.0030
1.5796
2.4859
2.4911
0.1297
0.3281
0.0129
0.1664
0.0946
0.0050
0.0894
1.0619
0.6080
0.0517
0.0003
3.6314
0.2727
0.4149
0.0843
0.1183
IVI
0.3849
4.0557
6.6181
7.0036
2.7455
5.9569
1.4115
2.8720
3.2732
0.0949
1.4914
3.1692
13.8070
2.8321
0.0605
7.5757
1.2731
6.1519
0.6080
1.3545
Scientific Name
Ekebergia capensis
Elaeodendron buchananii
Erica arborea
Ficus sur
Galiniera saxifraga
Hagenia abyssinica
Hypericum revolutum
Ilex mitis
Juniperus procera
Justicia schimperiana
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus addat
Maytenus gracilipes subsp.
arguta
Maytenus undata
Millettia ferruginea subsp.
darassana
Myrica salicifolia
Myrsine africana
Myrsine melanophloes
Nuxia congesta
Olea capensis subsp.
macrocarpa
Olinia rochetiana
P
15
18
3
65
35
6
1
65
6
2
35
54
10
6
F
0.1271
0.1525
0.0254
0.5508
0.2966
0.0508
0.0085
0.5508
0.0508
0.0169
0.2966
0.4576
0.0847
0.0508
N
18
29
439
398
125
64
8
589
35
3
132
513
36
36
D
1.6949
2.7307
41.3371
37.4765
11.7702
6.0264
0.7533
55.4614
3.2957
0.2825
12.4294
48.3051
3.3898
3.3898
BA
0.2750
0.2517
0.1071
3.5005
0.1027
0.5173
0.0096
2.3266
1.1177
0.0004
0.1186
3.6700
0.0373
0.2814
Av. BA
0.0153
0.0087
0.0002
0.0088
0.0008
0.0081
0.0012
0.0040
0.0319
0.0001
0.0009
0.0072
0.0010
0.0078
DO
0.2750
0.2517
0.1071
3.5005
0.1027
0.5173
0.0096
2.3266
1.1177
0.0004
0.1186
3.6700
0.0373
0.2814
RF
0.6061
0.7273
0.1212
2.6263
1.4141
0.2424
0.0404
2.6263
0.2424
0.0808
1.4141
2.1818
0.4040
0.2424
RD
0.0891
0.1436
2.1736
1.9706
0.6189
0.3169
0.0396
2.9163
0.1733
0.0149
0.6536
2.5400
0.1782
0.1782
RDO
0.3768
0.3448
0.1468
4.7962
0.1407
0.7088
0.0131
3.1878
1.5315
0.0005
0.1625
5.0285
0.0512
0.3855
IVI
1.0720
1.2157
2.4416
9.3931
2.1737
1.2681
0.0931
8.7303
1.9472
0.0962
2.2302
9.7503
0.6334
0.8062
72
8
0.6102
0.0678
571
89
53.7665
8.3804
0.0624
0.2576
0.0001
0.0029
0.0624
0.2576
2.9091
0.3232
2.8272
0.4407
0.0856
0.3530
5.8218
1.1169
75
1
13
25
33
0.6356
0.0085
0.1102
0.2119
0.2797
624
4
64
417
96
58.7571
0.3766
6.0264
39.2655
9.0395
1.0101
0.0018
0.0052
0.5792
0.1419
0.0016
0.0005
0.0001
0.0014
0.0015
1.0101
0.0018
0.0052
0.5792
0.1419
3.0303
0.0404
0.5253
1.0101
1.3333
3.0896
0.0198
0.3169
2.0647
0.4753
1.3840
0.0025
0.0071
0.7936
0.1944
7.5039
0.0627
0.8493
3.8683
2.0030
112
83
0.9492
0.7034
2002
582
188.5122
54.8023
10.3587
3.5978
0.0052
0.0062
10.3587
3.5978
4.5253
3.3535
9.9124
2.8816
14.1931
4.9295
28.6307
11.1647
175
Scientific Name
Oncoba spinosa
Osyris quadripartita
Oxyanthus speciosus
Phoenix reclinata
Pittosporum viridiflorum
Podocarpus falcatus
Polyscias fulva
Pouteria adolfi-friederici
Premna schimperi
Prunus africana
Psychotria orophila
Rhamnus prinoides
Rhus glutinosa
Ritchiea albersii
Rytigynia neglecta
Sapium ellipticum
Schefflera abyssinica
Schefflera volkensii
Solanecio mannii
Syzygium guineense subsp.
afromontanum
Teclea nobilis
Vepris dainelli
Vernonia amygdalina
P
27
2
72
2
27
103
57
74
4
54
86
1
1
14
78
14
33
14
1
F
0.2288
0.0169
0.6102
0.0169
0.2288
0.8729
0.4831
0.6271
0.0339
0.4576
0.7288
0.0085
0.0085
0.1186
0.6610
0.1186
0.2797
0.1186
0.0085
N
48
15
656
5
56
1118
182
718
10
247
1019
2
2
25
683
15
54
34
1
D
4.5198
1.4124
61.7702
0.4708
5.2731
105.2731
17.1375
67.6083
0.9416
23.2580
95.9510
0.1883
0.1883
2.3540
64.3126
1.4124
5.0847
3.2015
0.0942
BA
0.0145
0.0051
0.2665
0.0106
0.0388
3.1887
2.4413
7.2932
0.0070
2.2771
0.2655
0.0001
0.0004
0.0160
0.2147
0.1593
4.2480
1.7161
0.0012
Av. BA
0.0003
0.0003
0.0004
0.0021
0.0007
0.0029
0.0134
0.0102
0.0007
0.0092
0.0003
0.0001
0.0002
0.0006
0.0003
0.0106
0.0787
0.0505
0.0012
DO
0.0145
0.0051
0.2665
0.0106
0.0388
3.1887
2.4413
7.2932
0.0070
2.2771
0.2655
0.0001
0.0004
0.0160
0.2147
0.1593
4.2480
1.7161
0.0012
RF
1.0909
0.0808
2.9091
0.0808
1.0909
4.1616
2.3030
2.9899
0.1616
2.1818
3.4747
0.0404
0.0404
0.5657
3.1515
0.5657
1.3333
0.5657
0.0404
RD
0.2377
0.0743
3.2480
0.0248
0.2773
5.5355
0.9011
3.5550
0.0495
1.2230
5.0453
0.0099
0.0099
0.1238
3.3817
0.0743
0.2674
0.1683
0.0050
RDO
0.0199
0.0069
0.3651
0.0145
0.0532
4.3690
3.3449
9.9928
0.0096
3.1200
0.3638
0.0002
0.0006
0.0219
0.2942
0.2183
5.8204
2.3513
0.0016
IVI
1.3484
0.1620
6.5222
0.1200
1.4214
14.0661
6.5491
16.5377
0.2207
6.5247
8.8838
0.0505
0.0509
0.7114
6.8274
0.8582
7.4211
3.0853
0.0470
106
79
93
7
0.8983
0.6695
0.7881
0.0593
1591
477
807
9
149.8117
44.9153
75.9887
0.8475
11.8748
0.1072
0.5533
0.0076
0.0075
0.0002
0.0007
0.0008
11.8748
0.1072
0.5533
0.0076
4.2828
3.1919
3.7576
0.2828
7.8774
2.3617
3.9956
0.0446
16.2703
0.1469
0.7580
0.0104
28.4305
5.7005
8.5113
0.3378
176
Annex 11. Frequency, Density, Basal area and Important value indices of Woody species at the Afromontane forest of CCNP
Where: P=Number of plot where a species was present, F=Frequency, N=Number/count of individuals, D=Density, BA=Basal Area,
Av.BA=Average BA, DO=Dominance, RF=Relative Frequency, RD=Relative Density, RDO=Relative dominance and IVI=Importance value
index.
Scientific Name
Albizia gummifera
Allophylus abyssinicus
Agarista salicifolia
Apodytes dimidiata
Bersama abyssinica
Brucea antidysenterica
Calpurnia aurea
Canthium oligocarpum
Cassipourea malosana
Celtis africana
Chionanthus mildbraedii
Clausena anisata
Coffea arabica
Cordia africana
Croton macrostachyus
Cyathea maniana
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
P
24
38
18
28
28
23
6
40
20
21
60
35
16
10
38
17
18
61
23
F
0.3934
0.6230
0.2951
0.4590
0.4590
0.3770
0.0984
0.6557
0.3279
0.3443
0.9836
0.5738
0.2623
0.1639
0.6230
0.2787
0.2951
1.0000
0.3770
177
N
66
90
83
154
70
52
23
117
43
86
894
94
80
20
94
118
40
733
32
D
12.0219
16.3934
15.1184
28.0510
12.7505
9.4718
4.1894
21.3115
7.8324
15.6648
162.8415
17.1220
14.5719
3.6430
17.1220
21.4936
7.2860
133.5155
5.8288
BA
0.8722
1.4615
0.8406
3.2368
0.0327
0.0180
0.0207
0.0863
0.0794
0.9234
0.4560
0.0362
0.0425
0.1040
1.9406
0.2401
0.3083
1.2802
0.2381
Av. BA
0.0132
0.0162
0.0101
0.0210
0.0005
0.0003
0.0009
0.0007
0.0018
0.0107
0.0005
0.0004
0.0005
0.0052
0.0206
0.0020
0.0077
0.0017
0.0074
DO
0.8722
1.4615
0.8406
3.2368
0.0327
0.0180
0.0207
0.0863
0.0794
0.9234
0.4560
0.0362
0.0425
0.1040
1.9406
0.2401
0.3083
1.2802
0.2381
RF
1.5335
2.4281
1.1502
1.7891
1.7891
1.4696
0.3834
2.5559
1.2780
1.3419
3.8339
2.2364
1.0224
0.6390
2.4281
1.0863
1.1502
3.8978
1.4696
RD
0.7697
1.0496
0.9679
1.7959
0.8163
0.6064
0.2682
1.3644
0.5015
1.0029
10.4257
1.0962
0.9329
0.2332
1.0962
1.3761
0.4665
8.5481
0.3732
RDO
1.1817
1.9802
1.1388
4.3854
0.0444
0.0244
0.0280
0.1170
0.1076
1.2511
0.6178
0.0491
0.0576
0.1409
2.6293
0.3253
0.4177
1.7345
0.3226
IVI
3.4849
5.4578
3.2569
7.9705
2.6498
2.1005
0.6797
4.0373
1.8870
3.5959
14.8773
3.3817
2.0129
1.0131
6.1536
2.7877
2.0343
14.1804
2.1654
Scientific Name
Ehretia cymosa
Ekebergia capensis
Ficus sur
Galiniera saxifraga
Ilex mitis
Landolphia buchananii
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus gracilipes subsp.
arguta
Millettia ferruginea subsp.
darassana
Myrsine melanophloes
Nuxia congesta
Olea capensis subsp.
macrocarpa
Olea welwitschii
Oncoba spinosa
Oxyanthus speciosus
Phoenix reclinata
Pittosporum viridiflorum
Polyscias fulva
Pouteria adolfi–friederici
P
15
5
45
39
61
20
46
34
11
F
0.2459
0.0820
0.7377
0.6393
1.0000
0.3279
0.7541
0.5574
0.1803
N
34
6
119
362
237
31
308
210
31
D
6.1931
1.0929
21.6758
65.9381
43.1694
5.6466
56.1020
38.2514
5.6466
BA
0.1084
0.3125
6.2457
0.6160
5.7740
0.4900
1.2635
2.6910
0.0713
Av. BA
0.0032
0.0521
0.0525
0.0017
0.0244
0.0158
0.0041
0.0128
0.0023
DO
0.1084
0.3125
6.2457
0.6160
5.7740
0.4900
1.2635
2.6910
0.0713
RF
0.9585
0.3195
2.8754
2.4920
3.8978
1.2780
2.9393
2.1725
0.7029
RD
0.3965
0.0700
1.3878
4.2216
2.7638
0.3615
3.5918
2.4490
0.3615
RDO
0.1468
0.4234
8.4622
0.8346
7.8231
0.6639
1.7118
3.6460
0.0967
IVI
1.5018
0.8129
12.7253
7.5482
14.4847
2.3033
8.2430
8.2675
1.1611
58
0.9508
388
70.6740
0.0876
0.0002
0.0876
3.7061
4.5248
0.1186
8.3495
61
4
16
1.0000
0.0656
0.2623
295
24
133
53.7341
4.3716
24.2259
1.0243
0.0773
0.3605
0.0035
0.0032
0.0027
1.0243
0.0773
0.3605
3.8978
0.2556
1.0224
3.4402
0.2799
1.5510
1.3877
0.1047
0.4885
8.7257
0.6402
3.0618
25
10
18
61
15
41
39
61
0.4098
0.1639
0.2951
1.0000
0.2459
0.6721
0.6393
1.0000
75
20
34
878
34
120
96
45
13.6612
3.6430
6.1931
159.9271
6.1931
21.8579
17.4863
8.1967
3.5379
0.1040
0.0197
0.6755
0.1084
0.0838
2.1427
4.6607
0.0472
0.0052
0.0006
0.0008
0.0032
0.0007
0.0223
0.1036
3.5379
0.1040
0.0197
0.6755
0.1084
0.0838
2.1427
4.6607
1.5974
0.6390
1.1502
3.8978
0.9585
2.6198
2.4920
3.8978
0.8746
0.2332
0.3965
10.2391
0.3965
1.3994
1.1195
0.5248
4.7934
0.1409
0.0267
0.9152
0.1468
0.1136
2.9031
6.3147
7.2655
1.0131
1.5734
15.0521
1.5018
4.1328
6.5146
10.7372
178
Scientific Name
Prunus africana
Psychotria orophila
Ritchiea albersii
Rothmannia urcelliformis
Rytigynia neglecta
Schefflera abyssinica
Schefflera volkensii
Syzygium guineense subsp.
afromontanum
Teclea nobilis
Vepris dainellii
Vernonia amygdalina
P
33
56
6
19
57
27
10
F
0.5410
0.9180
0.0984
0.3115
0.9344
0.4426
0.1639
N
249
601
7
44
278
58
37
D
45.3552
109.4718
1.2750
8.0146
50.6375
10.5647
6.7395
BA
7.9936
0.3705
0.0057
0.0612
0.1627
8.7906
4.1978
Av. BA
0.0321
0.0006
0.0008
0.0014
0.0006
0.1516
0.1135
DO
7.9936
0.3705
0.0057
0.0612
0.1627
8.7906
4.1978
RF
2.1086
3.5783
0.3834
1.2141
3.6422
1.7252
0.6390
RD
2.9038
7.0087
0.0816
0.5131
3.2420
0.6764
0.4315
RDO
10.8304
0.5020
0.0077
0.0829
0.2204
11.9102
5.6875
IVI
15.8428
11.0891
0.4727
1.8100
7.1045
14.3118
6.7580
61
31
55
1
1.0000
0.5082
0.9016
0.0164
672
56
202
2
122.4044
10.2004
36.7942
0.3643
9.2791
0.0324
0.2408
0.0004
0.0138
0.0006
0.0012
0.0002
9.2791
0.0324
0.2408
0.0004
3.8978
1.9808
3.5144
0.0639
7.8367
0.6531
2.3557
0.0233
12.5721
0.0439
0.3262
0.0006
24.3066
2.6778
6.1963
0.0878
179
Annex 12. Seedling and Saplings at the Afromontane forest of TBB
Plant Name
Acanthus sennii
Albizia gummifera
Allophylus abyssinicus
Apodytes dimidiata
Arundinaria alpina
Bersama abyssinica
Brucea antidysenterica
Calpurnia aurea
Canthium oligocarpum
Carissa spinarum
Cassipourea malosana
Celtis africana
Chionanthus mildbraedii
Clausena anisata
Clutia abyssinica
Croton macrostachyus
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
Ehretia cymosa
Embelia schimperi
Erica arborea
Erythrococca trichogyne
Ficus sur
Flacortia indica
Galiniera saxifraga
Hagenia abyssinica
Ilex mitis
Juniperus procera
Justicia schimperiana
Landolphia buchananii
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus gracilipes subsp. arguta
Maytenus undata
Millettia ferruginea subsp.
darassana
Myrsine africana
Seedling
Sapling
Seedling Sapling Density
Density
Count
Count
(stem ha-1)
(stem ha-1)
13
187
1.22
17.61
153
143
14.41
13.47
40
47
3.77
4.43
20
65
1.88
6.12
5
111
0.47
10.45
401
554
37.76
52.17
11
44
1.04
4.14
118
179
11.11
16.85
17
75
1.60
7.06
0
1
0.00
0.09
8
30
0.75
2.82
15
82
1.41
7.72
252
356
23.73
33.52
75
504
7.06
47.46
2
12
0.19
1.13
3
14
0.28
1.32
12
14
1.13
1.32
137
448
12.90
42.18
291
95
27.40
8.95
0
1
0.00
0.09
64
111
6.03
10.45
10
16
0.94
1.51
283
107
26.65
10.08
6
23
0.56
2.17
2
5
0.19
0.47
206
198
19.40
18.64
3
5
0.28
0.47
11
98
1.04
9.23
17
11
1.60
1.04
39
56
3.67
5.27
78
142
7.34
13.37
54
64
5.08
6.03
18
48
1.69
4.52
15
23
1.41
2.17
1941
4240
182.77
399.25
4
20
0.38
1.88
49
426
180
79
1600
4.61
40.11
7.44
150.66
Seedling
Density
Plant Name
Myrsine melanophloes
Nuxia congesta
Olea capensis subsp. macrocarpa
Olinia rochetiana
Osyris quadripartita
Oxyanthus speciosus
Phoenix reclinata
Pittosporum viridiflorum
Podocarpus falcatus
Polyscias fulva
Pouteria adolfi-friederici
Prmnia schimperi
Prunus africana
Psychotria orophila
Rhamnus prinoides
Rytigynia neglecta
Syzygium guineense subsp.
afromontanum
Teclea nobilis
Trichilia dregeana
Vepris dainellii
Sapling
Density
Seedling Sapling
Count
Count
(stem ha-1)
(stem ha-1)
66
320
6.21
30.13
3
24
0.28
2.26
321
841
30.23
79.19
0
38
0.00
3.58
1
4
0.09
0.38
296
551
27.87
51.88
2
9
0.19
0.85
13
35
1.22
3.30
111
482
10.45
45.39
15
44
1.41
4.14
118
212
11.11
19.96
0
2
0.00
0.19
36
125
3.39
11.77
559
1441
52.64
135.69
5
18
0.47
1.69
278
1284
26.18
120.90
597
125
27
437
181
315
251
109
637
56.21
11.77
2.54
41.15
29.66
23.63
10.26
59.98
Annex 13. Density of Seedlings and Saplings of the Afromontane forest of CCNP
Plant Name
Albizia gummifera
Allophylus abyssinicus
Apodytes dimidiata
Bersama abyssinica
Brucea antidysenterica
Canthium oligocarpum
Cassipourea malosana
Chionanthus mildbraedii
Clausena anisata
Coffea arabica
Croton macrostachyus
Cyathea manniana
Dombeya torrida
Dracaena afromontana
Dracaena steudneri
Erythrococca trichogyne
Ficus sur
Galiniera saxifraga
Ilex mitis
Justicia schimperiana
Landolphia buchananii
Lepidotrichilia volkensii
Macaranga capensis
Maesa lanceolata
Maytenus gracilipes subsp. arguta
Millettia ferruginea subsp. darassana
Olea capensis subsp. macrocarpa
Olea welwitschii
Oxyanthus speciosus
Phoenix reclinata
Pittosporum viridiflorum
Polyscias fulva
Pouteria adolfi-friederici
prunus africana
Psychotria orophila
Rothmannia urcelliformis
Rytigynia neglecta
Syzygium guineense subsp. afromontanum
Teclea nobilis
Vepris dainellii
Seedling
Sapling
Seedling Sapling Density
Density
Count
Count
(stem ha-1) (stem ha-1)
127
77
23.13
14.03
38
17
6.92
3.10
19
22
3.46
4.01
3
19
0.55
3.46
3
10
0.55
1.82
27
42
4.92
7.65
53
45
9.65
8.20
637
480
116.03
87.43
94
263
17.12
47.91
363
167
66.12
30.42
19
43
3.46
7.83
109
75
19.85
13.66
1
6
0.18
1.09
122
109
22.22
19.85
306
98
55.74
17.85
361
166
65.76
30.24
2
4
0.36
0.73
461
292
83.97
53.19
98
70
17.85
12.75
116
39
21.13
7.10
17
16
3.10
2.91
371
273
67.58
49.73
10
10
1.82
1.82
28
23
5.10
4.19
161
121
29.33
22.04
43
34
7.83
6.19
13
53
2.37
9.65
14
11
2.55
2.00
458
369
83.42
67.21
31
34
5.65
6.19
82
88
14.94
16.03
41
25
7.47
4.55
222
42
40.44
7.65
123
106
22.40
19.31
246
374
44.81
68.12
156
186
28.42
33.88
17
16
3.10
2.91
11
13
2.00
2.37
40
13
7.29
2.37
476
298
86.70
54.28
182
Abreham Assefa