MINISTRY OF NATURAL RESOURCES AND TOURISM

TANZANIA FOREST SERVICES (TFS) AGENCY

BACK TO OFFICE REPORT

Enhancing the Forest Nature Reserves Network for Biodiversity Conservation in Tanzania

To:Project Coordinator

(Attention: Gerald Kamwenda)

Copied to:

Director of Resources Development

From:Mathias Lema July, 2017: Research & Risk Coordinator

Details of Activity /Trip

BIODIVERSITY SURVEY IN MOUNT HANANG NATURE FOREST RESERVE (NFR)

TFS & COSTEC staff involved in the survey

William Kindekete Florian MkeyaMathias LemaEvarist NashandaGerald KamwendaKazumari MkwavillaAhazi Luponelo ShayoVitalis BuraKatebalilo BituroHassan KmartAlly HemedJoseph MdumaMoses MwangokaKusaga Mukama

OBJECTIVES AND LINKAGE TO THE WORK PLAN The Tanzania Forest Services (TFS) Agency, is implementing a Global Environmental Facility (GEF) funded project. Under The Project, “Enhancing the Forest Nature Reserves Network for Biodiversity Conservation in Tanzania” one of its component has a key result area planned for Capacity Building of TFS Staff working in targeted Proposed Nature Forest Reserves (NFRs). This activity is specifically meant for biodiversity assessments

OUTPUT/DELIVERABLESa. Biodiversity assessments of Mount Hanang Nature Forest Reserveb. Hands on training to Key TFS Staff

Recommendations/Action points and persons responsibleThe biodiversity assessment report to be included in the Mount Hanang Nature Forest Reserve

Responsible persons:Conservator Mount Hanang Nature Forest Reserve

1. SUMMARY OF THE ASSESSMENT

In Mount Hanang Forest Reserve (MHFR) Six distinct vegetation types were identified and mapped,

including the Dense forest, Open forest, Woodland, Bushland, Heathland on rock outcrops,

Grassland and glades. The study revealed that, the MHFR is dominated by the Bushland and

Grassland, Dense forest being the least. The dense forest is characterized by a high percentage tree

cover with tall trees up to 30 m tall and canopy cover of more than 80%. The key tree species found

include: Albizia gummifera, Cassipourea malosana, Ekebergia capensis, Cussonia spicata, Celtis

african, Podocarpus falcatus and Prunus africana as top canopy tree species. The under storey

canopy is dominated with tree species such as Turrea holstii, Paveta sp, Vangurea madagascarensis

and Vepris simplisifolia.This dominant vegetation type provides the main habitat for wildlife

especially during dry seasons due to presence cool and favorable conditions.

A total of 171 plant species were encountered and enumerated. The large compositions of species

were from the herbs (48%), trees (28%), shrubs (18%), lianas (4%), grasses (3%), ferns (3%) and

sedges (1%). A total of 49 birds, 27 insects and 4 mammals’ species were encountered and

enumerated respectively.

Also, the analysis revealed that only few products were harvested for use and/or sell; firewood being

the major product taking 51.1% of the total value of forest products from MHFR. Other products

with their percentage contribution in brackets include fodder (13.8%), wild vegetables/leaves (6.2%),

timber (4.9%), honey (3.9%) and thatching material (2.6%).

The overall total present value for all forest related products is TZS 87.8 billion, which is equivalent

to USD 40 million. On the other hand there are equally important products from forests which didn't

come out from respondents such as edible ants, edible grasshoppers, gums and cosmetics. This could

probably be that they are harvested by very few members of the village and little is used.

Despite the high biodiversity and value of the MHFR, the reserve is threatened by increasing

encroachment due to human activities such as cultivation along the buffer zones, cattle grazing,

illegal harvesting of timber, wild fires incidences and low awareness of the communities on

sustainable natural resource conservation.

Strategic promotion of the biodiversity and ecological richness of the MHFR could significantly

increase awareness and possibly attract government attention, tourists and potential investors. This

should go hand in hand with design of trails/routes to various attractions found to attract tourists.

Given the diverse nature of challenges facing the MHFR, coordinated strategic intervention by all

relevant sectors and stakeholders is required in order to reduce human disturbance and conserve the

biodiversity richness.

2. ASSESSMENTS

2.1. Biodiversity Assessment

The biodiversity assessment concentrated on investigations of the flora, fauna and natural resource-

use, employing methods used by Frontier-Tanzania (2004). Information on plant species collected

were on names, their species abundance, importance/main use and areas of concentration. The

botanist and ecologist in the team with help of local people helped to classify, identify and map

various vegetation types occurring in the study area. Also they identified key plant species as well as

assessing the biological value of each vegetation unit classified. The key plant species identified

include; IUCN threatened plant species categories, CITES listed plant species appendices, Endemic,

Rare and species with socio economic importance such as medicinal, timber, food and building

poles. The above information will help to justify the biological value of the habitats and answering

the question why they should be conserved and being protected. Also the information will help to

make decision on the utilization of species and habitats.

For fauna, the main methods used were detailed field surveys and species inventory using a

combination of mist netting and observations (for birds), trapping (small mammals, reptiles and

amphibians) and opportunistic sighting and capture by hand (mammals, birds, reptiles and

amphibians). Location of flagship wildlife species was done with help of the local communities.

Indirect methods of detection (use of sign, transects, informal discussions with local residents) were

also used.

2.2. Assessment of Flora

The study area was stratified into relatively small homogenous classes/strata through classification

technique. Stratified sampling technique based on vegetation cover classification was performed in

ERDAS Imagine software. The vegetation cover was stratified into approximately homogeneous

classes on the basis of the forest types, stocking density of trees and tree species. Landsat image of

2015 was used as the focal scene for classification since it is the closest to the study start date. Based

on image classification results, the vegetation cover was identified, stratified and mapped.

2.3. Vegetation Inventory

The resultant vegetation cover map was used to set up (design) transects, which were laid on the

ground using Global Positioning System (GPS) devices. A sampling intensity that maximizes the

number of plots so as to capture as much as large plant variation in the MHFR was adopted for flora.

Sampling plots (20m x 20m) within MHFR was established systematically along transects.

Plot location was recorded using GPS for future monitoring. All trees with diameter at breast height

(1.3m) ≥5cm, from both the canopy and sub canopy layers, were recorded, counted and identified.

Moreover, the frequency of encounter of each species and its abundance will also be counted and

recorded to enable determination of species diversity, dominance and distribution. Regeneration plot

(2m x 2m) was laid out at the centre of each 20m x 20m plot so as to record, count and identify tree

sampling, seedlings and non-woody species such as grasses and herbs. Opportunistic observations of

grass, shrub and tree floras were made throughout the survey to supplement plots data. For plant

species that was difficult to identify in the field voucher specimens were collected for further

identification.

Human disturbances, special grazing grass for wild animals and wild fire incidences were recorded.

Wild fires have ecological effects on plants especially the woodland and montane type which is

dominant in the study area. Special habitats for wildlife were recorded as these may be points for

eco-tourism. Non Timber forest Products (NTFP) such as thatch, medicines, vegetables, fruits and

mushrooms harvested from the MHFR were assessed.

2.4. Assessment of Fauna

The fauna assessment focused on the following taxonomic groups, taxa chosen for this survey were

large mammals, small mammals, birds, bats, reptiles and butterflies. These wildlife categories cover

a wide cross-section of the ecological niches in the ecosystem and they are relatively well known and

easy to observe or collect. Information was compiled through a combination of literature reviews,

field data collection and local knowledge. The order, family, common name, genus and species are

presented along with the ecological type, endemic and conservation status. Combinations of methods

were used to collect data on fauna, including: Line Transects Method, Point count method, Mist

netting, Sweep netting and Opportunistic collection, observation, literature reviews and from local

knowledge.

Plate 1. Assessment of fauna

2.5.Assessment of Bird Species

Line Transects Method for Birds

Total of 4 transects of different lengths were established in the MHFR. Selection of transects was

based on vegetation types and accessibility. Observers walked along transect and stop where

necessary to record bird species spotted or heard on either side of transect. Vegetation survey

transects established were adopted during birds sampling.

Point Count Method for Birds

Data on fauna were collected at sampling sites established (abbreviated ‘plot’); 11 plots were

established in the MHFR. Plots were chosen to cover the largest range of habitats pre-identified;

Dense forest, Open forest, Woodland and Grassland.

Birds were counted using a standard “point count” method (Pomeroy, 1992; Pomeroy and Dranzoa,

1997; Dranzoa, 2001, Nkwabi et al., 2011; 2014) to determine the abundance and distribution of

birds in the study areas. The method consists of standing at a particular point, or walking slowly so

as to detect cryptic and skulking species in the areas. Identification of the species was aided with a

pair of binoculars and field guidebooks. During surveys, a 20 minute count was made at each

sampling plot. Surveys started around 06:40 AM and continued to late morning (11:00 AM) or the

transect end point. Total number of birds seen or heard during the 20 minute counts were recorded

and distance from the observer were also estimated. GPS position was recorded for each sampling

point and transects.

Mist Netting for Birds

Mist nets were used to capture birds so as to allow identification and to allow data to be collected on

reproductive status, especially the presence or absence of a brood patch. Mist-netting were also

conducted for cryptic and skulking species for building species list. The nets were erected at each

site along clear-cut runs about 1 m wide at each site. After being set, the nets were checked more

frequently during the morning and evening hours for 12 daylight hours. Birds captured were placed

in cloth “bird-bags” for identification and photographing. Birds were identified with the aid of birds’

field guidebook. GPS readings were taken near each mist net site.

Search for Nests

Systematic physical searches for breeding birds was carried out. The search for breeding individuals

was carried out in areas where there are active breeding activities. Breeding birds were randomly

searched in the sampling plots immediate after counting hours (10.30 hrs). During the search for

nesting birds, the size of the plot varied depending on availability of breeding bird activities.

2.6. Butterfly Assessment

Survey methods for butterflies vary depending on the site conditions and the stages of life cycle. To

obtain representative information, the survey was conducted during daytime and under fine weather

when most butterflies are active as recommended by Kielland (1990) and Larsen (1996). The

following method was used during the survey.

Transect Method for Butterfly

Visual observation as explained by Sinclair et al. (2014) was made and recorded for those species of

butterflies that are common and easy to identify to avoid over collection. The method involved

counting the number of flying butterflies that crossed a strip of known length (somewhere between

40 and 80 m) and 20 m wide for 10 minutes in the middle of the day when the insects are flying; this

was a ‘visual’ method. Butterflies were sampled starting from the morning once it is warm enough

for butterflies to fly; then in the noon time, from 12.00 noon to 02:00 PM and in the evening from

03:00 PM to 05:00 PM. The observer used a convenient tree as the end marker and recorded

individuals that crossed the strip of transect established by the observer, noting the types as whites,

yellows, reds or individual species if they will be easily identifiable. Distance to the end marker was

measured later after ten minutes of count.

Photo plate 2. Assessment of butterflies

Use of Sweep-nets for Butterfly Sampling

This method sampled butterflies in the miombo, forest under-story/scrub/thicket and around ground

herbs and grasses. Timed sweep netting was conducted within each vegetation plot. Data on the

taxonomy and sex, as well as habitat notes and associated vegetation types were recorded on

standardized data sheets. If not taken for specimens identification, captured butterflies were released

unmarked. Collected butterfly individuals were preserved in an envelope and identified to species

level by the aid of field guide book by Kielland (1990) and Larsen (1996). This method

supplemented the above method by establishing species list of butterfly in the study area.

2.7. Assessment of Small Mammals and Reptiles

Small mammals and reptiles were assessed using standard techniques shown to have been effective

elsewhere in East Africa (Davies and Howell, 2002; Howell, 2002) including Sherman, a drift fence

array with bucket pitfall traps and snap (break back) traps. Sherman traps were used to record and

sample small rodent and insectivorous mammals (diurnal, crepuscular, and nocturnal), while Hand

Capturing method was used to assess reptiles. This approach was done by searching in potential

shelter sites, including turning over rocks and logs and striping bark from trees. A hand held rake

can be useful in searching for small lizards and snake that may have crawled under the leaf litter,

however, small sticks may as well be used. Data on the taxonomy, sex, breeding status and

biometrics of each animal captured, as well as habitat notes and associated vegetation types, were

recorded on standardized data sheets.

2.8. Assessment of Large Mammal Species

Assessment of mammal species in the MHFR was accomplished by the line transect count method as

described by Jachman (1991). Transect lines were established along the vegetation assessment

transects. The crew moved slowly and scan quietly along the established transects and record all

encountered species along the same. Whenever an observation is encountered, up to 5 minutes or

until visual contact is lost, was spent recording data using a standardized recording sheet. In addition,

local knowledge on the presence of particular species was used, along with identification of presence

signs such as footprints, droppings and vocalization. For transect counts, the line transects was used

to collate data on the population estimate, size and spatial distribution. The number of individuals

counted within a given distance at a set speed under standard conditions was used to give an index of

relative abundance. Further, the density of droppings was also used to give an index of relative

abundance for a given species. The line transect count method was complimented by semi-structured

questionnaire that was administered to the game officers at the Hanang District and opinionsfrom the

community leaders and VNRCs. The GPSdevices were used to record observation coordinates.

Photo Plate 3. Assessment of mammal species

2.9. Identification and Mapping of Natural and Cultural Sites

Key natural and cultural sites such caves and rituals areas within the MHFR were identified and

mapped.This was possible through literature review and guidance from the knowledgeable

community leaders and key informants. In addition to heritage sites, other important tourism

attractions like view points were recorded using GPS and cameras.

Photo plate 1. Ritual areas along Jorodom route

Photo Plate 4: Worshipping site along river, ca 2km north east of entrance of Jerodom route

2.10. Data Processing and Analysis

Data processing involved all the steps and procedures necessary for the generation of required

information from the sets of data collected. In this study, data processing involved field data entry

into computer programs, processing, analysis, and validation, creation of maps and compilation of

report.

Following the field work task, all data collected were entered into computer programs, summarized

and analyzed. Subsequently processing and analysis of socio-economic data was done using

Microsoft Excel, Statistical Package for Social Sciences (SPSS),Species Diversity and Richness

(SDR); while spatial data, ArcGIS and ERDAS Imagine software were used. Results of the analysis

are organized into statistical tables and graphs for presentation.

2.11. Assessment of VegetationCover

The recent remotely sensed data (multi-spectral Landsat image) was used for vegetation mapping.

Image classification technique was applied to infer existing vegetation classes from Landsat image,

dated September, 2015.

2.12. Image classification

Pixel based image classification was applied to categorize characteristics of pixel groups on acquired

image to real world classes/objects. For efficient output, a combination of supervised and

unsupervised classification technique i.e. Hybrid classification approach was used to perform image

classification.

2.13. The Accuracy Assessment of Classification Results

Success of image classification is measured during accuracy assessment in thematic mapping from

remotely sensed data, and the term classification accuracy is typically taken to mean the degree of

‘correctness’ of a map or classification. Accuracy assessment determines the correctness of a

classified image based on pixel groupings i.e. the categories of real world features presented. The

classification results were compared with ground truth data (test set), and tabulated in a table to

determine accuracy of each class and overall accuracy, which was found to 96%.

3. QUANTIFICATION OF BIOMASS AND CARBON STOCKS

3.1. Estimating Biomass from Forest Inventory

All trees Diameter at breast Height (DBH)≥5cm within 20m x 20m were measured and recorded.

Additionally, height was measured for sample trees (Largest, Medium and Smallest). The allometric

equations developed by Masota et al., 2015 for montane forest with DBHand height as input

parameters was used to estimate the individual tree above ground biomass. Then, biomass of each

individual tree was converted into carbon in tons per hectare by multiplying biomass by 0.49

(percentage forest default value of aboveground carbon dry mass) (IPCC, 2006). Apart from field

based forest inventory estimation of biomass the consultant employed remote sensing techniques to

estimate tree above ground biomass and later integrate field based forest inventory and remote

sensing data (Landsat images) to produce carbon maps for 2004, 2010 and 2015.

3.2. Estimating Biomass from Landsat Images

3.2.1. Computation of Vegetation Indices

Regression analysis of Biomass and Spectral Indices were performed involving various vegetation

indices to test the correlation of field estimated biomass with spectral data from the multi-spectral

satellite scenes. The regression equation developed was based on Vegetation Indices (VIs) which

relates to optical measures of vegetation canopy ‘greenness’ resulting from the composite property of

total leaf chlorophyll, leaf area, canopy cover, and structure. The following indices were tested for

relationship between biomass and spectral data: -

Normalized Difference Vegetation Index (NDVI)

The NDVI is perhaps the most well-known and often used vegetation index. The NDVI is a simple,

but effective VI for quantifying green vegetation. The NDVI normalizes green leaf scattering in the

near-infrared wavelength and chlorophyll absorption in the red wavelength.

NDVI = (NIR–RED)/(NIR+RED)

The value range of an NDVI is -1 to 1 where healthy vegetation generally falls between values of

0.20 to 0.80.

Enhanced Vegetation Index (EVI)

In areas of dense canopy where the leaf area index (LAI) is high, the NDVI values can be improved

by leveraging information in the blue wavelength. Information in this portion of the spectrum can

help correct for soil background signals and atmospheric influences. 

EVI = 2.5[(NIR – RED) / ((NIR) + (6RED) - (7.5BLUE) + 1)]

The range of values for the EVI is -1 to 1, where healthy vegetation generally falls between values of

0.20 to 0.80.

Atmospherically Resistant Vegetation Index (ARVI)

The ARVI is an enhancement to the NDVI that is relatively resistant to atmospheric factors such as

aerosol. It works by using reflectance measurements in the blue wavelengths to correct for

atmospheric scattering effects that register in the red reflectance spectrum. The ARVI is most useful

in regions of high atmospheric aerosol content.

ARVI=((NIR)-(2RED-BLUE)/(NIR)+(2RED-BLUE))

The range for an ARVI is -1 to 1 where green vegetation generally falls between values of 0.20 to

0.80.

Optimized Soil Adjusted Vegetation Index (OSAVI)

This index is based on the Optimized Soil Adjusted Vegetation Index (SAVI). It uses a standard

value of 0.16 for the canopy background adjustment factor. This value provides greater soil variation

than SAVI for low vegetation cover, while demonstrating increased sensitivity to vegetation cover

greater than 50%. This index is best used in areas with relatively sparse vegetation where soil is

visible through the canopy.

Four VIs were tested i.e. NDVI, EVI, ARVI and OSAVI three out of these showed a good

linear relationship and hence these VIs were used to develop the aboveground tree biomass

equation.

3.2.2.Integration of Forest Inventory Data and Image Data

Following completion of computation of the Vegetation indices (VIs) per pixel, the next step was to

integrate field data with satellite data (VIs). Since each sample data had known coordinate, it was

necessary to reduce miss location error, therefore a window of 3 by 3 was used to extract (i.e.

extracting pixels corresponding to plots using the shape file of the plots) the mean value of the centre

of the pixel where the coordinates of the sample were located. These values were then linked with

field measured biomass data using empirical analysis employing the Ordinary Least Square (OLS)

regression to study the relationship between per plot above ground biomass and Vegetation indices.

The ordinary least square (OLS) regression, empirical approach, was used in modeling the

relationship between two observed variables, X and Y (Cohen et al., 2003). The form of the OLS

regression is in form of

Y = β0 + β1X + εi …………………………………………………………………(3.7)

Where,

Y = Variable to be predicted (dependent variable)

X= the variable to be predicted from (explanatory or independent variable),

β0 = Intercept

β1 = Slope of explanatory variables.

εi = Error term

Cohen et al. (2003) suggested that data for the analysis in OLS regression should be supplied from

paired observation of the two variables (dependent and explanatory variable). Commonly one

variable is difficult or costly to measure (e.g. Forest or vegetation parameters from field sampling)

and the other is relatively easy or inexpensive to observe (e.g. Vegetation indices).

The above OLS regression model was rewritten in the form of;

AGB = β0 + β1X1 + β2X2 + β3X3 + εi

Where,

AGB = Above-ground biomassβ0 = Interceptβ1…….. β4 = Slopes of respective explanatory variables.X1-X3=Image valuesεi = Error termX1 = ARVIX2 = NDVIX3 = OSAVI

The model was;

AGB = 1.1612ARVI - 4.9772 NDVI - 0.1749 OSAVI + 4.56 (R2 =72.01% SE = 2.66)

The resulting regression model from the analysis was used to predict Total Above-Ground tree

Biomass (TAGB) for the entire study area.

3.0. Results and Findings of the Assessments

3.1.Biodiversity Assets

The section is divided into sub sections to present flora (vegetation species) and fauna (large

mammals, small mammals, birds, butterflies and reptiles).

3.1.1. The FloraFrom the survey findings it has been noted that due to presence of high diversity of vegetation

categories classified from the study area, there is also high diversity of species as well as life forms

(Appendix 3).

3.1.2. Vegetation Types and Plant Communities of MHFR

The vegetation types of the study area were heterogeneous mosaic with patchy distribution recurring

without any defined pattern. A total number of six vegetation types were classified; Dense forest,

Open forest, Woodland, Bushland, Heathland and rock outcrop, and Grassland and glades as listed in

figure 4 and 5.

0.0

500.0

1000.0

1500.0

Area(Ha)

Classes

Vegetation covers,2015

HL&OR

Bushland

GR&GL

Woodland

Open forest

Dense forest

Ha 668.9 1222.6 1221.9 1024.5 1101.2 644.3

HL&OR Bushla GR&GL Woodla Open Dense

Figure 1. MHFR vegetation distribution

Key:HL and OR=Heathland and Outcrop Rocks, GR and GL=Grasslnd and Glades

Figure 2. MHFR vegetation map

Bushland

This is the first vegetation category (20.78 %) in the study area with tall shrubs up to 2 m tall and

canopy cover not more than 20 %. It is dominated by tree species of Abutilon longicuspe and

Vernonia myriantha as shown on photo plate 15 below. This vegetation category is common and

mostly found in Eastern part of the mountain. The vegetation is having high biological value of

insects (Appendix 8).

Photo plate 22: Patches of Vernonia myriantha Bushland within the forest

Grassland and glades

This is the second largest vegetation category (20.77 %) in the study area with abundant Exotheca

aabyssinicaand Setaria pumila, and outcrop rocks as shown on photo plate 16 below. This

vegetation category is common and mostly found along Jorodom tourist route and at the top of the

mountain. The vegetation is having high biological value of insects and butterflies.

Photo plate 13: Grassland and glades

Open Forest

This is the thirdvegetation category (18.72 %) in the study area with tall trees up to 20m tall and

canopy cover more than 60%. It is dominated by tree species of Olinia rochetiana, Calodendrum

capense, Nuxia congesta, Juniperus procera, Olea europaea and Euclea divinorumas top canopy

tree species. The understorey canopy is dominated with tree species such as,Rytignia uhilgii,

Vangueria madagascariensis and Paveta sp as shown on photo plate 13 below. This vegetation

category is common and mostly found in western part of the mountain. The vegetation is having high

biological value of birds and insects (Appendix 8 and 9) national reserved tree species like Juniperus

procera, Olea europea.

Photo plate 34: Open forest in the Western part of the Mountain

Woodland

This the fourthvegetation category (17.41 %) in the study area with tall trees up to 15m tall and

canopy cover not more than 50%. It is dominated by tree species of Acacia tortilis, Dodonea viscosa

as top canopy tree species, as shown on photo plate 14 below. This vegetation category is common

and mostly found in western part of the mountain. The vegetation is having high biological value of

birds (Appendix 8 and 9).

Photo plate 45: Woodland in the Western part of the Mountain

Heathland and Outcrop rocks

This is the fifth vegetation category (11.37 %)in the study area with tall shrubs up to 2.5m tall and

canopy cover not more than 20%. It is dominated by Erica arborea and Exotheca abyssinica and

outcrop rocksas shown on photo plate 16 below. This vegetation category is common and mostly

found at the top of the mountain. The vegetation is having high biological value of insects, birds and

butterflies (Appendix 8 and 9).

Photo plate 5: Heath vegetation and outcrop rocks at the top of the mountain

Dense Forest

This is sixth (smallest) vegetation category (10.95 %) in the study area (Figure 3), with tall trees up

to 30m tall and canopy cover more than 80 %. It is dominated by tree species of Albizia gummifera,

Cassipourea malosana Ekebergia capensis, Cussonia spicata Celtis africana, Podocarpus falcatus

and Prunus africana as top canopy tree species. The understorey canopy is dominated with tree

species such as Turraea holstii, Pavetta sp, Vangurea madagascarensis and Vepris simplisifolia as

shown on photo plate 12 below. This vegetation category is common and mostly found in East and

Northern part of the mountain. The vegetation is having high biological value of birds and insects

(Appendix 8 and 9) and tree species Prunus africana recognized by IUCN as endangered and

national reserved tree species like Podocarpus falcatus and Prunus africana.

Photo plate 67: Dense forest in the Northern part of the Mountain

3.1.1.2.Forest Stand Parameters

Overall stand parameters for MHFR showed mean stocking of 652±164 SPH, basal area of

55.54±17.45 m2/ha, mean volume of 38.67±12.67 m3/ha and mean above ground tree biomass of

21.49±6.66 tons/ha (Appendix 1). The higher stocking of lower Dbh classes is a good indication that

the forest has a potential for growth since these are going to be future trees of high volume as

evidenced by the growing volume per ha with increase along the diameter at the breast height (Dbh)

classes. The basal area for montane rainforest ranges between 24-30 m2/ha that means montane

forest, having basal area of 55 m2/ha is still a very good forest. Thus more effort should be put on

protection to main its status (Table 1).

Table 1: Values of stand parameters by diameter classes in MHFR

DBHclass

DBH range(Cm)

Stocking(SPH)

Basal area(m2/ha)

Standing volume(m3/ha)

Above Ground

Tree Biomass(tons/ha)

Below Ground

Tree Biomass(tons/ha)

1 5-15 3925 21.05 9.93 9.12 13.182 15-25 925 22.44 11.95 9.37 7.903 25-35 525 34.75 20.32 14.11 8.104 35-45 375 47.77 29.70 19.06 8.515 45-55 125 24.72 16.02 9.74 3.676 55.1 625 404.75 298.88 153.57 35.43

Forest Stocking with Respect to Diameter Classes

There is a general decreasing number of stems/ha as diameter class increases, giving almost an

inverted “J” shape (Figure 2.). This is always the case in natural forests where there is active

regeneration and a mixture of trees of all age class. In this particular case it seems there was

excessive harvesting of large trees, giving way to regeneration. The fairly small amount of trees with

large diameter might mean that the few trees left are now protected so they continue to grow.

Diameter class 35-45 and 45-55 cm show lowest stocking, it can be assumed this is a result of over-

exploitation since this is the size class which could be easily handled by poachers.

Photo plate 18: Distribution of number of stems per hectare of standing stemsby diameter classes (cm) in MHFR

According to Lowore et al., (1994) basal area is linearly related to volume. This is confirmed by

findings of this study that, basal area and standing volume manifest linear relationship with the

increase in diameter classes (Figures 7 and 8).

Figure 3: Distribution of basal area per hectare of standing crop by diameter classes (cm) in MHFR

Figure 4: Distribution of volume per hectare of standing crop by diameter classes (cm) in MHFR

Forest Stocking with Respect to Species

Stocking assessment showed that, Euclea divinorum, Olinia rochetiana, Nuxia congests, Gnidia

glauca, Catha edulis, Ficus thonningii, Olea europaea, Ekebergia capensis, Dodonaea viscosa,

Sclopia rhymniphylla and Cassipourea malosanahave highest stocking in terms of stems per hectare

ranging from 150 to 100 SPH (Appendix 2). The least stocked valuable timber species include Albizia

gummifera,Celtis africana, Podocarpus falcatus, Fagaropsis angolensis and Juniperus procera which have

40 stems/ha, 50 stems/ha, 50 stems/ha 25 stems/ha, 25 stems/ha respectively (Appendix 2). The low

stocking for these species is associated to the illegal harvesting took place in the past before the JFM.

This was evidenced by the presence old cuts observed during the taking of forest inventory.

Moreover, these species occur in a very limited area as such they need protection as well as measures

to encourage regeneration especially Podocarpus falcatus and Fagaropsis angolensis. There was

little evidence of natural regeneration of these species in the field thus artificial regeneration should

be established.

Stems Density of Regenerants

Moreover, the results show that, mean total density of regenerants was 17 ± 7 stems per hectare

(Appendix 3). Figure 5 shows the distribution of regenerants in the montane forest MHFR. It shows

that, Juniperus procera(39%), Euclea divinorum(15%), Abutilon longicuspe(6%) Olinia

rochetiana(5%), Nuxia congests(4%), Psychotria sp. (4%), Morella salicifolia(3%) Rhamnus

staddo(3%), Ekebergia capensis (2%) and Vernonia myriantha(2%) are among the most regenerating

species in MHFR (Appendix 4). From these results it suffices to conclude that, the most regenerating

species are plausibly the most exploited species by local communities in their daily livelihood

activities. Regeneration in montane is mainly by recruitment from old stunted seedlings already

present in soil.

Figure 5: Distribution of regenerants species in MHFR

3.1.1.3.Plant Diversity

Tree Species Composition and Richness

A total of 171 species were encountered and the large composition of species were from the herbs

(48%), trees (28%), shrubs (18%), lianas (4%), grasses (3%), ferns (3%) and sedges (1%) (Figure 10

and Appendix 3).

Figure 6: Species richness and composition in MHFR

Tree Species Diversity

The study revealed Shannon-Wiener Index of Diversity of 3.30 for the Montane forest of MHFR

(Figure 11). This index tells about species richness (number of species) and evenness (species

distribution) (Magurran, 1988), the larger the value of H’ the greater the species diversity and vice

versa. An ecosystemwith H’ value > 2 was regarded as medium to high diversity in terms of species

(Barbour et al., 1999). Thus, MHFR has reasonably high tree species diversity. Species noted to have

contribution to high species diversity include:- (Euclea divinorum (0.29),Olinia rochetiana (0.22),

Nuxia congests (0.22), Gnidia glauca (0.21), Catha edulis (0.13),Ficus thonningii, (0.12), Olea

europaea (0.12), Ekebergia capensis (0.11), Dodonaea viscosa (0.11), Sclopia rhymniphylla (0.10)

and Cassipourea malosana (0.09) (Figure 7).

Figure 7: Tree species according to diversity index

Index of Dominance

According to Misra (1989), the greater the value of Index of Dominance (ID) the lower the species

diversity and vice versa (in the scale of 0 to 1). The study came up with ID of 0.061 for montane

forest of MHFR (Appendix 6). This result indicates that there is higher species richness in that forest

reserve. Species noted to be relative dominant include:- Olinia rochetiana (0.009), Nuxia congesta

(0.008), Gnidia glauca (0.007) and Euclea divinorum (0.023).

Figure 8: Tree species according to index of dominance

3.1.1.4.Tree Species Exploitation

Results show that, mean total density of stems was 3 ± 2 stems per hectare were cut (Appendix 5).

The species found to be highly harvested were Juniperus procera (18%), Fagaropsis angolensis

(18%), Podocarpus falcatus (16%), Prunus africana (11%), Cassipourea malosana (9%), Nuxia

congesta(9%), Albizia gummifera (7%), Ekebergia capensis (8%) and Celtis africana (5%)(Figure

9). These species were harvested for timber, firewood, poles, hoe handle, bee hives, and poles.

Juniperus procera, Fagaropsis angolensis, Podocarpus falcatus and Prunus africanaare the prime

timbers in montane forests others are Cassipourea malosana, Albizia gummifera and Celtis africana.

Nuxia congests and Ekebergia capensis are the best for hoe handle, poles and beehives.

Figure 9: Tree cut by species

3.1.1.5.Remote Sensing Based Results

Aboveground Tree Biomass Maps

Overall results on carbon assessment revealed that Aboveground Tree Biomass (AGB) of the MHFR

in the past 24 years have been increasing linearly. During this period AGB increase by 31.08%

between 1992 to 2015. The mean biomass for year 1992, 2004 and 2015 scenes was 117.32t/ha,

158.13t/ha and 170.24t/ha respectively (Figure 14, 15 and 16). From the above observation, it is clear

that the mean biomass is relatively higher than the one from ground based assessment. This implies

that the two methods gave nearly same biomass estimation per hectare. This is because the ground

based information to feed remote sensing was collected with high accuracy and precision.

Figure 10:Aboveground Tree Biomass in year 1992

Figure 11:Aboveground Tree Biomass in year 2004

Figure 12:Aboveground Tree Biomass in year 2015

3.1.2.The Fauna: Wildlife Abundance and Distribution

3.1.2.1. Birds

The MHFR consists of high bird species diversity that beautifies the area. The study revealed 49

species of birds, counting 291, mean of 5.9, diversity index (H’) of 3.38. The large H’ entails high

species diversity of birds (Table 2). The common birds were Colius striatus (Speckled mousebird)

(36) with H’ 0.26 and Apus affinis (Little swift) (30) with H’ of 0.23 (Appendix 8).

3.1.2.2. Insects

Insects including butterflies imply suitable natural environment for wildlife. The study revealed 27

species revealing relatively high species of insects counting 329, mean count of 12.19, H’ of 2.04

(Table 2), an implication of high species of insects of which most of them were butterflies (Appendix

9). Most common insects were Stomaxy calcitrans (105) and Crematogaster peringueyi (100)

(Appendix 9).

Table 2: Fauna species richness, diversity and abundance

Group of fauna Total species Total count Mean countDiversity Index

(H')Bird 49 291 5.9 3.38Insect 27 329 12.19 2.04Mammal 4 38 9.5 0.67

3.1.2.3.Mammals

A total of 4 species of mammals were identified. The recorded mammals were Papio anubis,

Oreotragus oreotragus, and Heliophobius argenteocinereus(Table 3) while the Madoque kirikii

(Kirk’s dikdik) was revealed through seeing a dung. Of those, Papio Anubis (Olive baboons) were

the most common (30) (Table 3).

Table 3: Fauna species richness, diversity and abundance

S/N Family Order Scientific name Common name Red List Category Count

1 Bathyergidae RodentiaHeliophobius argenteocinereus Silky blesmol

-1

2 ArtiodactylaEven-toed ungulate

Oreotragus oreotragus Klipspringer

-1

3 Cercopithecidae Passerfomes Papio anubis Olive baboon - 304 Cercopithecidae primates Papio sp. Blue monkey - 6

5 Suidae CetartiodactylaPotamochoerus larvatus Pushpig

Least Concern ver 3.14

6 Hyaenidae Carnivora Crocuta crocuta Spotted hyena Least Concern ver 3.1 27 Felidae Carnivora Panthera pardus Leopard Near Threatened ver 3.1 18 Pythonidae - Pythonidae Python - 1

Total 46

Photo plate 7: Oreotragus

3.1.2.4.Endemism

The MHFR comprises of few East African endemic fauna species including endemic species to the

area, while most of the found butterflies and birds were common (Table 4). The revealed endemic

fauna was a type of bird called Turraco hartlaubi (Hartlaubas turraco), and Bradypterus

cinnamomeus (Cinnamon branken warbler).

Intra African Migrants

These included the African migrant butterflies, such as Catopsilia florella (Table 4).

Table 4: African migrant butterly and East African Endemic birds

Family Order Scientific name Common name Category Migrants

Pieridae Lepidoptera Catopsilia florella Butterfly

African migrant

butterfly

Musophagidae Passeriformes Tauraco hartlaubi Hartlaubas turraco Bird

East African

endemic

Sylviidae Passeriformes

Bradypterus

cinnamomeus

Cinnamon branken

warbler Bird

East African

endemic

3.2. Ecological, Cultural and Heritage Attractions

The study results indicate that in addition to the vegetation and wildlife resources, there are several

ecological, cultural and heritage sites within the MHFR and among the communities which could

provide valuable opportunities for eco and cultural tourism as well as income generation prospects.

The MHFR provides opportunities for nature and cultural based adventure tourism.

3.2.1. Ecological Attractions

The MHFR has numerous flora and fauna species, attributed to diversity of habitats and

landforms.The ecological potential of the MHFR makes an area ideal place for tourism and,

therefore, offering another economic opportunity for communities to increase their household

income and reduce poverty. Some of these attractions and opportunities are presented hereunder.

The high diversity of assets is mainly a function of areas’ diverse habitats including forests and

woodlands. These habitats are characterised by a variety of common wildlife species.

3.2.1.1. The Flora

Flora encompasses a diverse of plant species existing in any vegetation, ranging from lower to higher

growing taxa. The foothills and peaks of mountains comprise of the most interesting floristic areas in

tropical Africa (Cribb and Leedal, 1982). A variety of plant species viewed as the tourists climb the

mountain may look marvelous to them.

Berberisholstii [Berberidaceae]

Gloriosa superba

One of attractive mountain grasslands of Tanzania flowering herb [Kniphofia thomsonii]

Gladiolus newii

Proteakilimandscharica observed blooming in February

Senecio angulatus

Osteospermum vaillantii

Lagenari abyssinica along tourist trail from Gocho to the top

Young Lobelia deckenii

Parchycarpus eximius

Orchid

Disafragrans(An attractive bulbous herb growing on well drained grasslands with rock outcrop in MHFR)

Liverworts

Dryopteris schimperiana [a fern near second cave entrance]

Epiphytic plants:

Fern

Lepisorus excavates on Dombeyarotundifolia trunk

Loxogramme abyssinica on Agaristasalicifolia trunk

Moss:

Moss

Parasitic plants:

Viscum tuberculatum

This is a parasitic shrub with yellowish green stems, shedding to grey mature stems [see inside circled part]

Viscum tuberculatum

Landscapes/vegetation types:

Dry forest

Grassland patches:

Grassland patch with a flat plain viewed from Jorodom tourist route just above dry forest [eastern side as the tourist ascends from entrance].

Shrubland

Acanthospermum hispidum shrubland

Erica arborea shrubland

Nice looking shrub woodland dominated with Erica arborea around the summit point with red pink to mauve petals

Kotschyarecuvifoliaand Acanthospermum hispidum shrubland

Kotschya shrubland along Jorodom route with nice looking spurs/valley slopes.

3.2.1.2.The Fauna

Insects

Insects form an important component of biodiversity and are the spectacularly diverse scenery in our

ecosystem. The protected vegetation is a home of a variety of biological species, of which insects are

among them (Woodhall, 2005).

Common name: Kipepeo in Kiswahili.

Scientific name: Papiliodardanus

Matting Green-banded swallowtail

Common name: Kipepeo in Kiswahili

Scientific name: Antanartiadimorphicadimorphica

Northern short-tailed Admiral on fingers

Common name: Brown veined white, Kipepeo in Kiswahili.

Scientific name:Belenoisaurotaaurota

Was observed at gentle-flatland of Nangwa village site. Habitat; hillsides, flatlands, parks, gardens,

forest edges, coast and mountains (Woodhall, 2005).

Brown veined white

Common name: Moth in English; Nondo in Kiswahili

Scientific name: Caenurginasp.

Usually found in moist forest. Was found in Gitting Moist montane forest, with abundant Vernoniamyriantha.

Moth on leaf of V. myriantha

Ground Beetle:

This was on foot truck side along Jorodom tourist route, with massive offsprings.

Ground beetle with massive offspring

Caterpillar

This is a larva stage of a butterfly which starts its life as an egg. The larva (caterpillar) hatches from

an egg and eats leaves or flowers almost constantly. The caterpillar molts (loses its old skin) many

times as it grows. The caterpillar is a feeding stage. It then turns into a pupa

(chrysalis); this is a resting stage. Then the chrysalis turns into a butterfly, a stage or reproductive.

All these are among tourist attractions viewed easily as someone ascends or descends the MHFR.

Caterpillars

Common name: Millipede [English], Jongoo [Kiswahili].

Scientific name: Eurymerodesmus spp.

Milepede

Grasshopper

Grasshopper (English}: Family: Caelifera [Phyullum: Arthropoda; Order: Orthoptera]

Matting grasshoppers [Panzi in Kiswahili]

3.2.2. Cultural and Heritage Attractions

Besides flora, fauna and historical sites, the MHFR also offers a number of attractions that amplifies

the value of the area as a tourist destination.

Several cultural, heritage and historical sites and attractions exist within the communities around the

MHFR. These sites portray very important cultural and historical aspects of the indigenous tribes

living around the communities. They also provide opportunities for diversification of tourism

products for MHFR and provide additional value and benefits directly to the communities. Some of

these attractions include caves, view points, Mountain summit, waterfalls, rocks etc.

Caves

The first cave at 764864 [E] and 9507954 [N], with elevation of 3,138 m above seas level, eastern

side of Jorodom route

Second cave [E: 766282 and N: 9509616. Alt: 3,222 m above sea level], Eastern side of Jorodom route

Cultural site [near water intake], at Himit river valley, north east of Jorodom route entry point to forest reserve.

The tree is Ficusthonningii, Fig tree in English and MkuyuJamii in Kiswahili. The place where Barbaigs elders conduct worshiping/rituals regularly, asking their spirits to help them whenever there is a

prolonged drought.

View point of Great Rift Valley from the Mountain Summit

View point of Lake Balangida and Gedawarifrom Gabadaw village side of the Mountain

View Point of Gedawari Lake from Gabadaw village

Ridges of MHFR with nice looking slopes

Spurs

Spurs viewed to the eastern side of the Jorodom route when ascending and to the left when descending.

Picnic site

Picnic site along Jorodom route within grassland patch above wooded grassland ridge

Campsite

Suitable site for camping along Jorodom route

Distant view of campsite as someone descends from summit

Nice bending trees along Jorodom route

Nice looking bending Agaristasalicifolia

Undulating hills

These are beautiful rolling parts of MHFR that strike any person climbing or viewing the mountain

from and visible direction or point.

Undulating hills viewed from woodland above Gabadaw village.

Steep slope rock along Himit river north of water intake

Impressive undulating rock hills and ridge slopes as viewed from cave two. Erica arboreashrubland

in the north of Himit valley, forest in valleys can be viewed clearly.

Rock hills to the summit

Arrangement of small hills as the tourist ascends to and descends from summit through Jorodom route

Summit

Summit point at 3,423 m above sea level

Fog

Fog ascending from mountain hills valley bottom

These attractions range from a summary of key cultural, heritage and historical sites in and around

MHFR and their significance to eco and cultural tourism is presented in Table 5 below.

Table 5: Summary of cultural, historical and heritage sites and their significance to eco and cultural tourism

Cultural &

heritage site

Location Significance to

culture of the

communities

Significance for eco

and cultural tourism

Mount Hanang summit

At the peak of the Mountain(E:0766442 N: 95009780. Alt. 3,423 m. a.s.l.

Natural phenomenon.

Potential for eco and photographic tourism.

A natural phenomenon with some historical attachment. Significant for eco and cultural tourism.

A nice view point of lake Balangida Lelu and Gedawari.

It presents a broad view of the underlying plains all the way to Babati, Mbulu, Kondoa, Chemba districts and part of districs in Singida region.

Worshiping area,

An old Butress fig. tree called “Mkuyu’’ found near water source

Along Jorodom route

(E:766150,N:9504672, Alt. 2,067ma.s.l.)

This is seen as a sacred place and therefore used for rituals and sites for communication with the ancestors.

As a sacred site it has very significant impacts on the beliefs and culture of the communities. It could be a potential site for eco and cultural tourism.

Gabadaw view point

Fitsa- Gabadaw village

(E:0761223,N:9506409,Alt.1,880m. a.s.l.)

Nature attractions

Potential for eco and photographic tourism.

A nice view point of lake Balangida Lelu and Gedawari. It presents a broad view of the underlying plains all the way to Kondoa, Chemba districts and part of districs in Singida region.

Water falls of Himit River

Along Jorodom route Nature attractions.

Potential for eco and photographic tourism.

Caves Along eastern side of Jorodom route

Cave 1 :(E:764864, N:9507954, Alt. 3,138 m a.s.l.),

Cave 2: (E:766282, N: 9509616], Alt: 3,222 m a.s.l.)

Historical site.

Nature attractions.

Potential for eco and photographic tourism.

3.3. Water Sources

MHFR is the major source of water in Hanang District. The following are important rivers and

streams that emanate from the forest reserve:

i. Himit–The Himit supplies water to Katesh Township and the Southern Barabaig, with water flowing

throughout the year.

ii. Nangwa–This flows its water to Nangwa trade centre and the lower plains.

iii. Gitting-Also called Endagek, which flows on the North Eastern side of the reserve.

iv. Shishie Barjomot-A stream which supplies water to the Eastern side of the reserve. Currently the

stream is seasonal compared to the past five years where by the supply of water to the Eastern side

of the plains was throughout the year.

v. Dumanang: Supply water to Hanang wheat complex which used to be a subsidiary supply of National

Agriculture and Food Corporation (NAFCO). It also supplies water to the villages of Gendabi, Dawar

and Gidagamowd.

The forest reserve has also a number of seasonal streams such as Bagara, Endemyo, Endage on the

Eastern part while, Bayayi, Endarbu, Shishiekati and Endari are on the Northern part of the

reserve.These water source contain varieties aquatic life, and provide water for the wildlife.

Water source in Jorodom side of the Mountain

Appendix 2: Stocking per Species (Refine the name of table)

SN Scientific nameN G V AGB BGB(SPH) (m2/ha) (m3/ha) (tons/ha) (tons/ha)

1 Abutilon longicuspe 50 0.120 0.051 0.053 0.1112 Acacia tortilis 75 0.687 0.341 0.293 0.3413 Albizia gummifera 50 19.368 13.679 7.445 2.0504 Allophyllus abyssinicus 50 0.397 0.190 0.171 0.2235 Apodytes dimidiata 75 6.536 3.959 2.628 1.3276 Buddleia polystachya 100 0.813 0.408 0.346 0.4057 Calodendrum capense 75 7.667 4.836 3.046 1.3108 Casearia battiscombei 25 1.227 0.696 0.503 0.3259 Cassipourea malosana 150 22.881 14.827 9.020 3.52410 Catha edulis 275 5.453 2.994 2.259 1.83411 Celtis africana 50 29.484 21.624 11.207 2.63712 Clematis simensis 50 0.245 0.114 0.107 0.16113 Cussonia holstii 25 0.283 0.140 0.121 0.13814 Cussonia spicata 50 1.541 0.842 0.639 0.48915 Dodonaea viscosa 175 0.387 0.164 0.173 0.37116 Dombeya rotundifolia 75 0.342 0.157 0.149 0.23517 Ehretia cymosa 125 0.868 0.427 0.371 0.46618 Ekebergia capensis 225 75.437 53.582 28.966 8.10719 Euclea divinorum 1000 13.368 7.834 5.456 4.41820 Fagaropsis angolensis 25 0.283 0.140 0.121 0.13821 Ficus thonningii 275 93.325 69.777 35.304 8.28622 Gnidia glauca 550 3.806 1.823 1.640 2.18523 Grewia similis 125 2.376 1.293 0.987 0.82324 Heteromorpha trifoliolata 25 0.049 0.021 0.022 0.05025 Ilex mitis 25 23.758 17.864 8.960 1.83726 Juniperus procera 25 0.049 0.021 0.022 0.05027 Maesa lanceolata 50 0.622 0.311 0.265 0.29028 Nuxia congests 600 68.542 45.381 26.859 9.80729 Olea europaea 275 13.540 8.023 5.483 3.17530 Olinia rochetiana 625 12.887 7.091 5.334 4.25231 Pavetta abyssinica 50 0.638 0.321 0.271 0.29132 Pavetta sp. 25 0.196 0.094 0.085 0.11233 Podocarpus falcatus 50 0.120 0.051 0.053 0.11134 Prunus africana 100 47.469 34.644 18.080 4.48635 Rhus longipes 125 0.522 0.236 0.229 0.38136 Rhus natalensis 75 0.169 0.072 0.075 0.16137 Rothecca myricoides 75 0.169 0.072 0.075 0.16138 Rytignia uhilgii 25 0.503 0.262 0.211 0.19339 Salacia madagascariensis 50 0.322 0.151 0.140 0.19840 Sclopia rhymniphylla 200 2.490 1.280 1.051 1.07241 Scutia myrtina 25 0.283 0.140 0.121 0.13842 Solanecio mannii 100 1.174 0.625 0.491 0.46643 Toddalia asiatica 25 0.071 0.031 0.031 0.061

44 Turraea holstii 25 0.567 0.299 0.238 0.20745 Turraea robusta 75 0.389 0.179 0.169 0.25946 Urera hypselodendron 25 0.442 0.227 0.186 0.179

47Vangueria madgascariensis 100 0.852 0.433 0.361 0.406

48 Vepris simplicifolia 75 0.905 0.478 0.379 0.362

Appendix 3: Species Composition, Richness and Diversity

Scientific name Abundance Density Index of dominance Shanon indexAbutilon longicuspe 2 50 0.00 0.0373Acacia tortilis 3 75 0.00 0.0513Albizia gummifera 2 50 0.00 0.0373Allophyllus abyssinicus 2 50 0.00 0.0373Apodytes dimidiata 3 75 0.00 0.0513Buddleia polystachya 4 100 0.00 0.0640Calodendrum capense 3 75 0.00 0.0513Casearia battiscombei 1 25 0.00 0.0213Cassipourea malosana 6 150 0.00 0.0867Catha edulis 11 275 0.00 0.1335Celtis africana 2 50 0.00 0.0373Clematis simensis 2 50 0.00 0.0373Cussonia holstii 1 25 0.00 0.0213Cussonia spicata 2 50 0.00 0.0373Dodonaea viscosa 8 200 0.00 0.1068Dombeya rotundifolia 3 75 0.00 0.0513Ehretia cymosa 5 125 0.00 0.0758Ekebergia capensis 9 225 0.00 0.1161Euclea divinorum 40 1000 0.02 0.2875Fagaropsis angolensis 1 25 0.00 0.0213Ficus thonningii 11 275 0.00 0.1335Gnidia glauca 22 550 0.01 0.2085Grewia similis 5 125 0.00 0.0758Heteromorpha trifoliolata 1 25 0.00 0.0213Ilex mitis 1 25 0.00 0.0213Juniperus procera 1 25 0.00 0.0213Maesa lanceolata 2 50 0.00 0.0373Nuxia congests 24 600 0.01 0.2194Olea europaea 10 250 0.00 0.1250Olinia rochetiana 25 625 0.01 0.2247Pavetta abyssinica 2 50 0.00 0.0373Pavetta sp. 1 25 0.00 0.0213Podocarpus falcatus 2 50 0.00 0.0373Prunus africana 5 125 0.00 0.0758Rhus longipes 5 125 0.00 0.0758Rhus natalensis 3 75 0.00 0.0513Rothecca myricoides 3 75 0.00 0.0513Rytignia uhilgii 1 25 0.00 0.0213Salacia madagascariensis 2 50 0.00 0.0373Sclopia rhymniphylla 7 175 0.00 0.0971Scutia myrtina 1 25 0.00 0.0213Solanecio mannii 4 100 0.00 0.0640Toddalia asiatica 1 25 0.00 0.0213Turraea holstii 1 25 0.00 0.0213Turraea robusta 3 75 0.00 0.0513

Urera hypselodendron 1 25 0.00 0.0213Vangueria madagascariensis 4 100 0.00 0.0640Vepris simplicifolia 3 75 0.00 0.0513Total 258 6450 0.06 3.2736

Appendix 4: Density of Regenerants (Refine the name of table)

SN Scientific name Density Rel. density1 Abutilon longicuspe 45 5.562 Acacia tortilis 1 0.123 Albizia gummifera 3 0.374 Allophyllus africanus 2 0.255 Apodytes dimidiata 1 0.126 Cassipourea malosana 9 1.117 Catha edulis 2 0.258 Celtis africana 3 0.379 Clematis simensis 4 0.4910 Clerodendrum johnstonnii 3 0.3711 Dodonaea viscosa 8 0.9947 Ekebergia capensis 18 2.2212 Erythrococca fischeri 8 0.9943 Euclea divinorum 122 15.0614 Fagaropsis angolensis 1 0.1215 Juniperus procera 319 39.3816 Lantana trifolia 1 0.1217 Maytenus heterophylla 2 0.2518 Morella salicifolia 25 3.0945 Nuxia congests 32 3.9546 Olea europaea 12 1.4844 Olinia rochetiana 44 5.4319 Osyris lanceolata 1 0.1220 Pavetta sp. 6 0.7421 Pavonia urens 10 1.2322 Periplocca linearifolia 1 0.1223 Podocarpus falcatus 2 0.2524 Psychotria sp. 30 3.7025 Pterolobium stellatum 10 1.2326 Pytolacca dodecandra 1 0.1227 Rhamnus staddo 21 2.5928 Rhus longipes 2 0.2529 Rhus natalensis 3 0.3730 Rothecca myricoides 3 0.3731 Rytignia uhilgii 4 0.4932 Schrebera alata 1 0.1233 Sclopia rhymniphylla 7 0.8634 Solanum aculeastrum 3 0.3735 Sparmannia ricinocarpa 9 1.1136 Turraea holstii 1 0.1237 Turraea robusta 1 0.1238 Urera hypselodendron 4 0.4939 Vangueria infausta 1 0.1240 Vernonia brachycalyx 2 0.2541 Vernonia lasiopus 6 0.74

42 Vernonia myriantha 16 1.98

Appendix 5: Trees Removal

SN Scientific name Local name Count Status of stump

1 Juniperus procera Dukuu 8 Old cut2 Fagaropsis angolensis Grintuwa 8 Old cut3 Podocarpus falcatus Nokii 7 Old cut4 Prunus africana Gwami 5 Old cut5 Cassipourea malosana Funtsari 4 Old cut6 Nuxia congests Aftsii 4 Old cut7 Albizia gummifera Sori 3 Old cut8 Ekebergia capensis Tewi 3 Old cut9 Celtis africana Diwili 2 Old cut

10 Apodytes dimidiata Khatsimoo 1 New cut11 Olea europaea Saatii 1 New cut12 Turraea robusta Daatenii 1 New cut13 Ehretia amoena Bormo 1 New cut14 Maytenus heterophylla   1 New cut

  TOTAL 49  

Appendix 6: Fauna Species Richness, Diversity and Abundance (Refine the table name)

S/N Family Order Scientific nameCommon name

Red List Category

Count

1 Bathyergidae Rodentia

Heliophobius argenteocinereus Silky blesmol

-

1

2 ArtiodactylaEven-toed ungulate

Oreotragus oreotragus Klipspringer

-1

3Cercopithecidae Passerfomes Papio anubis Olive baboon

-30

4Cercopithecidae primates Papio sp. Blue monkey

-6

5 SuidaeCetartiodactyla

Potamochoerus larvatus Pushpig

Least Concern ver 3.1 4

6 Hyaenidae Carnivora Crocuta crocuta Spotted hyenaLeast Concern ver 3.1 2

7 Felidae Carnivora Panthera pardus Leopard

Near Threatened ver 3.1 1

8 Pythonidae - Pythonidae Python - 1Total 46

Appendix 8: Birds identified at Mount Hanang’ Forest Reserve (Refine the name of table)

S/No. Family Order Scientific name Common name Count H' D

1 Sylviidae passeriformesAndropaclus nigriceps mountain green bul 11 0.12

0.001429

2 Platysteiridae Passeriformes Apalis flavida Yellow breasted Apalis 3 0.050.00010

6

3 passeridae passeriformes Apalis thoracica Bar-throated Apalis 3 0.050.00010

6

4 pycnonotidae passeriformes Apus barbatus Africa black swift 6 0.080.00042

5

5 Platysteiridae Passeriformes Apus affinis Little swift 30 0.230.01062

8

6 Muscicapidae Passeriformes Apus caffer white rumped swift 2 0.030.00004

7

7 Sylviidae Passeriformes Aquila verreauxii verreaux's Eagle 4 0.060.00018

9

8 Pcononotidae Passeriformes Batis molitor Chin spot batis 5 0.070.00029

5

9 Ploceidae passeriformesBradypterus cinnamomeus

Cinnamon branken warbler 7 0.09

0.000579

10 coliidae passeriformes Buteo augur Augur buzard 2 0.030.00004

7

11 Sylviidae passeriformesCamaroptera brachyura

Grey backey camaroptera 11 0.12

0.001429

12 pycnonotidae PasseriformesChalcomitra amethystina Amethyst sunbird 2 0.03

0.000047

13 Apodidae PasseriformesChloropeta natalensis

Dark-capped yellow warbler 1 0.02

0.000012

14Maloconitidae Passeriformes

Chrysococcyx klaas Klaas's cuckoo 2 0.03

0.000047

15 Accipitridae Falconiformes Cinnyris mediocrisEastern double collared sunbird 2 0.03

0.000047

16 Phasianidae Passeriformes Cinnyris venusta Variable sunbird 12 0.130.00170

0

17 Nectariniidae passeriformes Colius striatus Speckled mousebird 36 0.260.01530

4

18 Nectariniidae passeriformes Columba arquatrix Olive pigeon 2 0.030.00004

7

19 Nectariniidae Passerformes Corvus albicollis White nacked raven 6 0.080.00042

5

20 ColumbidaeColumbiformes Cosspha heuglini White browed robin chat 4 0.06

0.000189

21 Sylviidae Passerformes Dryoscops cubla Black backed puff back 14 0.150.00231

5

22Musophagidae Passerformes

Francolinus sephaena Crested francolin 1 0.02

0.000012

23 Nectariniidae Passerformes Hedydipna collaris Collared sunbird 2 0.030.00004

7

63

24 Columbidae Passerformes Hirundo fulugula Rock martin 2 0.030.00004

7

25 Zosteropidae PasserformesHirundo senegalensis Mosque swallow 2 0.03

0.000047

26 Muscicapidae PasserformesLaniarius aethiopcus Tropical bou bou 13 0.14

0.001996

27 Coliidae passeriformesMelaenornis fischeri

White eyed slaty flycatcher 2 0.03

0.000047

28 Pycnonotidae passeriformes Muscicapa adusta Africa dusky flycatcher 1 0.020.00001

2

29 Sylviidae passeriformesMuscicapa caerulescens Ashy flycatcher 1 0.02

0.000012

30Malaconotidae passeriformes

Nectarinia kilimensis Bronze sunbird 4 0.06

0.000189

31 Accipitridae FalconiformesOnychognathus morio Red winged starling 20 0.18

0.004724

32 Nectariniidae passeriformes Parisoma boehmi Banded parisoma 1 0.020.00001

2

33 Sylviidae passeriformes Passer griseus Grey headed sparrow 2 0.030.00004

7

34 ploceidae passeriformes passeriformes White browed robin chat 1 0.020.00001

2

35 Nectariniidae passeriformesPloceus baglafecht Baglafetch weaver 9 0.11

0.000957

36Malaconotidae Passeriformes Ploceus ocularis Spectacled weaver 4 0.06

0.000189

37 Sylviidae PasseriformesPogonocichla stellata White starred robin 2 0.03

0.000047

38 Nectariniidae PasseriformesPsalidoprocne albiceps white headed swallow 7 0.09

0.000579

39 Turdidae PasseriformesPycnonotus barbatus Yellow vented bulbul 15 0.15

0.002657

40 Apodidae PasseriformesSchoutedenapus myptilus Scarce swift 2 0.03

0.000047

41 Hirundinidae PasseriformesSerinus citrineloids African citril 2 0.03

0.000047

42 Corvidae Passeriformessmithornis capensis Africa broadbill 4 0.06

0.000189

43 Pycnonotidae PasseriformesStreptopelia semitorquata Red eyed dove 4 0.06

0.000189

44 Plocidae Passeriformes Sylvia atricapilla Black cap warbler 1 0.020.00001

2

45 Muscicapidae Passeriformes Tauraco hartlaubi Hartlaub's turaco 10 0.120.00118

1

46 Nectariinadae Passeriformes Tchagra australis Brown crowed tchagra 1 0.020.00001

2

47 Sylviidae Passeriformes Turdus oliveceus Olive Thrush 1 0.020.00001

2

48 Musophagie PasseriformesTurtur tympanistria Tambourine dove 2 0.03

0.000047

64

49 Zosteropidae PasseriformesZosterops poliogaster Montane white eye 10 0.12

0.001181

291 3.380.04996

4

Appendix 9: Insects identified at Mount Hanang’ Forest Reserve (Refine the table name)

S/No. Family Order Scientific name Common nameCount H' D

1 Culicidae Diptera Aedes sp Bush mosquitoes 6 0.07 0.0000554

2 Nymphalidae LepidopteraAntanantia d.dimorphica

Short tailed Admiral butterfly,photo 4 0.05 0.0000370

3 Lycaenidae Lepidoptera Anthene definita Common hairtail butterfly 1 0.02 0.0000092

4 Pieridae Lepidoptera Belenois a.aurotaBrown-veined white butterfly 2 0.03 0.0000185

5 Nymphalidae LepidopteraBelenois creona severina

African common white butterfly 1 0.02 0.0000092

6 Pieridae Lepidoptera Catapsilia florellaAfrican migrant butterfly 5 0.06 0.0000462

7 Pieridae Lepioptera Colotis auxoSulphur orange tip butterfly 4 0.05 0.0000370

8 FormicideHymenoptera

Crematogaster peringueyi Cocktail ants trail 100 0.36 0.0009239

9 Pieridae Lepioptera Dixeia c. charinaAfrican small white butterfly 3 0.04 0.0000277

10 Pieridae Lepioptera Eronia ledaautumn-leaf vagrant butterfly 2 0.03 0.0000185

11 Nymphalidae LepiopteraEuraytela dryope angulata Pied piper butterfly 2 0.03 0.0000185

12 Pieridae LepidopteraEurema hecabe solifera

Common grass yellow butterfly 5 0.06 0.0000462

13 Nymphalidae LepidopteraEurytela hiarbas angustata Pied piper butterfly 1 0.02 0.0000092

14 Nymphalidae Lepidoptera Hyalites eponinaSmall orange acraea butterfly 1 0.02 0.0000092

15 Nymphalidae LepidopteraHypolimnas misippus

Common diadem butterfly 2 0.03 0.0000185

16 Pieridae Lepioptera Nepheronia Cambridge vagrant 4 0.05 0.0000370

65

thalassina sinalata butterfly

17 Papilionidae LepidopteraPapilio d. demodocus

citrus swallowtail butterfly 2 0.03 0.0000185

18 papilionidae LepidopteraPapilio e. echerrioides

white banded swallowtail 3 0.04 0.0000277

19 Papiliondae LepidopteraPapilio nireus lyaeus

Green banded swallowed butterfly 5 0.06 0.0000462

20 Papilionidae LepiopteraPapilion e. echeriodes

White banded swallow butterfly 1 0.02 0.0000092

21 Nymphalidae Lepidopteraphalanta p aethiopica

common leopard butterfly 2 0.03 0.0000185

22 Pipilionidae LepidopteraPipilio nireus lyaeus

Green bunded swallowtail butterfly 1 0.02 0.0000092

23 Pieridae Lepidoptera Pontia helice helice meadow white butterfly 4 0.05 0.000037024 Muscidae Lepidoptera Stomoxys calcitrans Stable fly 105 0.36 0.000970125 Nymphalidae Lepidoptera Vanessa cardui Painted lady butterfly 41 0.26 0.0003788

26Anthophoridae

Hymenoptera Xylocopa Carpenter bee 2 0.03 0.0000185

27 InsectsHymenoptera Apis mellifera Stinging honey bee 20 0.17 0.0001848

Total 329 2.04 0.0030395

66