BMC Ecology and Evolution
(2022) 22:12
Dibaba et al. BMC Ecology and Evolution
https://doi.org/10.1186/s12862-022-01964-4
Open Access
RESEARCH
Plant community analysis
along environmental gradients in moist
afromontane forest of Gerba Dima,
South-western Ethiopia
Abyot Dibaba1*, Teshome Soromessa2 and Bikila Warkineh3
Abstract
Background: This study was carried out in Gerba Dima Forest, South-Western Ethiopia, to determine the floristic
composition, species diversity and community types along environmental gradients. Identifying and interpreting the
structure of species assemblages is the main goal of plant community ecology. Investigation of forest community
composition and structure is very useful in understanding the status of tree population, regeneration, and diversity for
conservation purposes.
Method: Ninety sample plots having a size of 25 × 25 m (625 m2) were laid by employing stratified random sampling. Nested plots were used to sample plants of different sizes and different environmental variables. All woody
plant species with Diameter at breast height (DBH) ≥ 2.5 cm and height ≥ 1.5 m were recorded in 25 m × 25 m plots.
Hierarchical (agglomerative) cluster analysis was performed using the free statistical software R version 3.6.1 using
package cluster to classify the vegetation into plant community types. Redundancy Analysis (RDA) ordination was
used in describing the pattern of plant communities along an environmental gradient.
Result: One hundred and eighty plant species belonging to 145 genera, 69 families and comprising of 15 endemic
species were recorded. Of these, 52 species (28.9%) were trees, 6 species (3.33%) were Trees/shrubs, 31 species
(17.22%) were shrubs, 76 species (42.22%) were herbs, and 15 species (8.33%) were Lianas. Rubiaceae, Acanthaceae
and Asteraceae were the richest family each represented by 11 genera and 11 species (6.11%), 9 genera and 11 species (6.11%), 6 genera and 11 species (6.11%), respectively of total floristic composition. Cluster analysis resulted in five
different plant communities and this result was supported by the ordination result. RDA result showed altitude was
the main environmental variable in determining the plant communities. The ANOVA test indicated that the five community types differ significantly from each other with regard to Electrical Conductivity and Potassium.
Conclusions: Description of floristic diversity of species in Gerba Dima forest revealed the presence of high species
diversity and richness. The presence of endemic plant species in the study forest shows the potential of the area for
biodiversity conservation.
Keywords: Gerba Dima, Indicator species, Moist afromontane forest, Species diversity
*Correspondence: abyotdibaba77@yahoo.com
1
College of Natural Sciences, Department of Biology, Debre Berhan
University, P. O. Box 445, Debre Berhan, Ethiopia
Full list of author information is available at the end of the article
Background
Identifying and interpreting the structure of species
assemblages is the main goal of plant community ecology. Gradients in species composition vis-à-vis either
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Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
presence/absence or abundance data are commonly
employed to evaluate community structure [1]. Legendre
[2] distinguished between ‘true gradients’ in species composition, which are induced by environmental gradients,
and ‘false gradients’, which may arise even in the absence
of environmental heterogeneity as a result of biotic interactions within the community. Both true and false gradients may form distinct spatial patterns when mapped into
geographic space. According to Seabloom et al. [3], different ecological processes create distinct spatial patterns,
so that specific processes could be identified from their
spatial signature. Hence, spatial analysis of community
structure is of direct scientific interest, because spatial
structures may be critical for identifying and understanding the underlying ecological processes [4]. Biotic filters
determining limiting similarity is the assumed cause for
species dissimilarity in traits within communities. Symmetric competitive interactions might indeed lead to the
co-existence of ecologically distinct species, which minimize competition for shared resources (“symmetric competition” leading to limiting similarity [5].
The quest to explain the underlying processes for the
assembly of local communities is still a major focus in
plant community ecology, as researchers keep examining them through both observational and experimental
studies [6]. The multidimensional ecological niche space
determines the distribution of a species within a community [7]. Physiographic and edaphic factors can determine
which plant species will colonize a site since plant species
vary in their tolerance and utilization of resources site [8].
These variations have been regarded as a driving force for
the coexistence of species in a similar environment [9]
and can explain broad-scale compositional differences
among multiple resource gradients [10, 11]. The upper
storey tree density as an abiotic factor can also affect
community composition as understorey species differ in
their ability to tolerate stresses imposed by competitive
trees [12, 13]. Moreover, by increasing the abundance of
annual and biennial plants, disturbances can affect community composition via favouring stress-tolerant species
[13, 14].
Information on species composition and diversity of
tree species plays a pivotal role not only to understand
the structure of a forest community but also in planning
and implementation of conservation strategy of the community [15]. Investigation of forest community composition and structure is very useful in understanding the
status of tree population, regeneration, and diversity for
conservation purposes [16]. Quantitative information
on composition, distribution, and abundance of woody
species has paramount importance in understanding
the form and structure of a forest community and for
Page 2 of 17
planning and implementation of conservation strategy of
the community.
The recent data on forest resources of Ethiopia reported
in FAO [17] puts Ethiopia among countries with a forest
cover of 10–30%. According to this report, Ethiopia’s forest cover (FAO definition) is 12.2 million ha (11%). It further indicated that the forest cover shows a decline from
15.11 million ha in 1990 to 12.2 million ha in 2010, during which 2.65% of the forest cover was deforested. This
study was conducted in the Gerba Dima forest found in
South-Western Ethiopia with the aim of investigating the
species composition, species diversity, community types
and to relate the distribution of plant community types to
some environmental parameters.
Methods
The study area
This study was carried out in the Gerba Dima forest
found in the Illu Aba Bora zone of Oromia regional state
of Ethiopia and located between 7° 45’ to 8° 10’ North
latitude and 35° 29’ to 35° 50’ East longitude. The study
forest is bounded by Baro River to the south and west
direction whiles three other rivers, namely Bote, Hoyi
and Sor cross part of the forest in the east (Fig. 1). The
geology of the study site is characterized by the Underlying basement rock consisting of intensively folded and
faulted Precambrian rocks, overlain by Mesozoic marine
strata and Tertiary basalt types [18]. The main soil types
of the study area are red or brownish ferrisols derived
from the volcanic parent material. Other soil groups in
the area include nitosols, acrisols, vertisols, and cambisols soil types exist in the study site [19].
The rainfall data collected from the nearest Gore meteorological station to the study forest indicated that the
study area receives very high annual rainfall and characterized by unimodal rainfall pattern, which shows
low rainfall in December, January and February, gradually increasing to the peak period in August. The mean
annual rainfall of 1854 mm while the monthly mean
maximum and mean minimum temperature of the area
is 27.2 ℃ and 13.3 ℃, respectively. The mean annual temperature is 19.2 ℃ and with slight variation from year to
year [20].
The vegetation type at Gerba Dima is part of the
moist evergreen afromontane forest with characteristic
emergent species that form the upper canopy includes
Pouteria adolfi-friederici (Fig. 2). Albizia gummifera,
A. schimperiana, A. grandibracteata, Sapium ellipticum, Euphorbia ampliphylla, Ekebergia capensis, Ficus
sur, Hallea rubrostipulata, Ocotea kenyensis, Olea welwitschii, Polyscias fulva and Schefflera abyssinica are
other characteristic species of this vegetation type [21].
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 3 of 17
Fig. 1 Map of Ethiopia, Oromia region and Gerba Dima forest
Fig. 2 Photograph illustrating the forest overview
Sampling method
In this study, a stratified random sampling design was
used to collect vegetation and environmental data [1, 22].
Using Arc GIS version 10.3, the study forest was stratified
based on the altitudinal gradient and three types of strata
in the form of contour were established. Strata one was
distributed between 1500 and 1800 m altitudinal ranges
whereas strata two and three were found between 1801–
2000 m and 2001–2300 m altitudinal ranges respectively
(Fig. 1). Sample plots were assigned in each contour in
the form of Random points Using Arc GIS version 10.3
(Fig. 3).
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 4 of 17
Fig. 3 A Map showing the distribution of sample plots
Ninety sample plots having a size of 25 × 25 m
(625 m2) along each contour were laid. Nested plots
were used to sample plants of different sizes and different environmental variables. All woody plant species with Diameter at breast height (DBH) ≥ 2.5 cm
and height ≥ 1.5 m were recorded in 25 m × 25 m plots.
Within the major plots, five 3 m × 3 m subplots (9m2)
was used to collect shrubs with dbh < 2.5 cm and > 1.5 m
height. Within each 9 m2 subplots, two 1 m2 subplots
were used to collect data on the species and abundance
of herbaceous plants. Finally, the percent cover of all
plant species found within the sample plot was visually
estimated and converted to the Braun-Blanquet scale
as modified by [23]. Every plant species encountered
in each plot were recorded. Plant specimens were collected, pressed, dried and brought to the National
Herbarium (ETH), Addis Ababa University for taxonomic identification. The specimens were determined
by comparing with authenticated specimens housed at
ETH and by referring to published volumes of Flora of
Ethiopia and Eritrea [24–32].
Physiographical variables, namely altitude, geographic coordinates, slope and aspect, were recorded
for each quadrat using GPS, Clinometer and Compass
respectively. The values for aspect were codified based
on Woldu [33], where N = 0, NE = 1, E = 2, SE = 3,
S = 4, SW = 3.25, W = 2.5, NW = 1.25 before analysis.
For each sample plot, a disturbance was determined
on the basis of a five point scale following [34]. The five
scales of disturbance scores were based on visible signs
of tree cutting, grazing and presence of beehives. The
points of scale were 0 = (No disturbance), 1 = (0–20%
of the quadrat disturbed), 2 = (21–40% of the quadrat disturbed), 3 = (41–60% of the quadrat disturbed),
4 = (61- 80% of the quadrat disturbed), 5 = (81–100% of
the quadrat disturbed).
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
For analysing soil variables, soil samples were collected
with a soil core sampler from the top 40 cm depth within
1 m × 1 m subplots at the four corners and middle of the
quadrat. Composite soil samples from samples collected
from the four corners and the middle of quadrats were
brought to the soil laboratories of Addis Ababa University
(AAU). The soil samples were air-dried, rolled and passed
through a 2 mm sieve for laboratory analyses. These soil
samples were analysed for pH, electrical conductivity
(EC), sodium, potassium, organic matter, total nitrogen,
available phosphorus and texture following standard procedures outlined in [35]. The pH and EC were measured
using a pH meter and EC meter in the supernatant suspension of 1:2.5 soil–distilled water mixtures. Available
Sodium and Potassium were determined using a flame
photometer. Organic matter was determined by the ignition method. The texture was determined on the basis of
Bouycous Hydrometer method with the categories sand,
silt, and clay (expressed as % weight) while total nitrogen
was determined using Kjeldhal method. Available Phosphorus was determined by the Bray-I method and the
absorbance of the Bray-I extract is measured at 882 nm in
a spectrophotometer.
Data analysis
In this study, hierarchical (agglomerative) cluster analysis
was performed using the free statistical software R version 3.6.1 [36] using package cluster to classify the vegetation into plant community types. The similarity ratio
with Ward’s group linkage method was applied for cluster analysis i.e. to determine plots that can be classified
into the same groups based on the species abundance
data. The decision on the number of groups (clusters)
was based on objective methods of obtaining an optimal
number of clusters, the Multi Response Permutation Procedures (MRPP) technique (no-difference hypothesis)
and the ecological interpretation of the groups conducted
in R program. The T and A statistic of MRPP output were
used to obtain the number of clusters. The test statistic T
describes the separation between the groups. The more
negative T value, the stronger the separation. The P-value
associated with T is determined by numerical integration of the Pearson type III distribution. The P-value is
useful for evaluating how likely an observed difference is
due to chance [37]. The agreement statistic A describes
within-group homogeneity, compared to the random
expectation, and falls between 0 and 1. When all items
within-groups are identical A = 1 and 0 if the groups are
heterogeneous. In community ecology, A values are commonly below 0.1, and an A value greater 0.3 is fairly high
[37].
From the output of the objective method, a sharp
bend at the specific cluster in the plot could be a good
Page 5 of 17
indication of the number of clusters in the data [38].
The community types identified from the cluster analysis were further refined in a synoptic table where species
occurrences were summarized as synoptic cover-abundance values [39]. Dominant species of each community
type were identified based on their synoptic values and
community types were named after one or more dominant species. The identified groups were tested for the
hypothesis of no difference between the groups (clusters)
using nonparametric Multi-Response Permutation Procedure (MRPP). Indicator species analysis was performed
in R using package labdsv. Indicator values were tested
for statistical significance using a randomization (Monte
Carlo) technique. Species richness, evenness, Shannon
diversity and evenness indices were computed using the
free statistical software R version 3.6.1 [36]. The Shannon
diversity index (H’) was calculated from the equation:
H′ = −
s
pi lnpi
i=1
where pi, is the proportion of individuals found in the
ith species. The values of the Shannon diversity index is
usually found to fall between 1.5 and 3.5 and only rarely
surpasses 4.5 [1, 39]. The Shannon evenness index (J) was
calculated from the ratio of observed diversity to maximum diversity using the equation:
J=
H′
H′
=
H max
ln s
where Hmax is the maximum level of diversity possible
within a given population, which equals ln (number of
species). J is normal between 0 and 1, and with 1 representing a situation in which all species are equally abundant [40].
Information about endemic species, their habit, IUCN
status and geographical distributions was determined by
referring to [25–33, 42].
In this study, Redundancy Analysis (RDA) ordination
was used in describing the pattern of plant communities
along an environmental gradient since the preliminary
analysis of the vegetation data using Deterended Correspondence Analysis (DCA) revealed that the longest axis
of DCA for the dataset was less than 3 (= 2.22). Before
the application of RDA ordination, environmental variables, which were relatively more important in explaining the species data, were selected using the Monte Carlo
technique and function Adonis test for their significance.
Computation of variance inflation factor (vif ) was also
conducted to eliminate those environmental variables
that are collinear. The community types obtained were
subjected to an ANOVA based on environmental variables to find out whether there are significant variations
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
between the groups. Pearson’s product-moment correlation coefficient was calculated to evaluate the relationship between the environmental variables.
Results
Floristic composition
One hundred and eighty (180) plant species belonging to
145 genera and 69 families were recorded and identified
in the sample plots in the Gerba Dima forest (Table 1).
Of these, 52 species (28.9%) were trees, 6 species (3.33%)
were Trees/shrubs, 31 species (17.22%) were shrubs, 76
species (42.22%) were herbs, and 15 species (8.33%) were
Lianas. Angiosperms were represented by 160 species
while the rest 20 species were Pteridophytes. Among
Angiosperms, Rubiaceae, Acanthaceae and Asteraceae
were the richest family each represented by 11 genera
and 11 species (6.11%), 9 genera and 11 species (6.11%),
6 genera and 11 species (6.11%), respectively of total floristic composition, followed by Fabaceae 8 genera and
9 species (5%), Euphorbiaceae 6 genera and 7 species
(3.89%). The remaining families represented less than 3%
of species each. Eleven families, 13 genera and 20 species represented pteridophytes. Aspleniaceae, Dryopteridaceae and Pteridaceae were the richest Pteridophytes
represented by 6, 3 and 2 species respectively. The genus
Vernonia, Ficus, Asparagus, Dracaena were represented
by 5,4,3,3 species respectively and Aframomum, Albizia,
Asparagus, Cyperus, Euphorbia, Hippocratea, Hypoestes,
Justicia, Maytenus, Olea, Peperomia, Polyscias, Pteris,
Rubus, Schefflera, Solanecio, Solanum, Tacazzea, and
Zehneria were represented by 2 species each and the rest
genera contained a single species each.
Based on the information available on the published
Floras of Ethiopia a total of 15 endemic plant species in 11
families were recorded (Table 2), comprising more than
8.33% of the recorded species. Asteraceae was the first
family having three endemic species, followed by Acanthaceae and Fabaceae (two species each). The remaining
eight families have a single species each in the endemic
species list. Among the total endemic species, herb, tree,
shrub and liana growth forms were represented by 6,3,4,2
species respectively. Out of the 15 endemic species, Crotalaria rosenii and Polyscias farinosa have been included
in the IUCN red data list of Ethiopia and Eritrea qualifying for near threatened and vulnerable category respectively. In the Gerba Dima forest, at 625 m2 sample plot,
species richness varied from 26 to 59 across the study
plots. The Shannon diversity index also varied from 2.92
to 3.83 while evenness ranged from 0.89 to 0.95 in the
study plots. The overall mean Shannon diversity index,
species richness and evenness of the study area were 3.45,
41 and 0.93 respectively.
Page 6 of 17
Community types and indicator species
Five community types were derived from the hierarchical
cluster analysis in combination with Multi-response Permutation Procedures (MRPP) and objective method of
the whole data set (Fig. 4 and Table 3). From the output
of MRPP, the test statistic T value for the five groups was
−38.26 (P < 0.001) and the agreement statistic A was 0.13
while the output of objective method revealed a sharp
bend at the fifth cluster.
Community 1 (Croton macrostachyus—Bersama abyssinica community) was found in the altitudinal range of
1677–2020 m. a.s.l and slope from flat to 50%. Fourteen
plots were associated with the community and has 2 indicator species with significant indicator values (P < 0.05)
(Table 4).
Community 2 (Syzygium guineense—Olea capensis
community) was distributed from 1699 to 2240 m a.s.l.
and slope ranging from flat to 60%. It comprises of 22
plots and twenty species were associated with this community as indicator species where one of the indicator species exhibit significant indicator values (P < 0.05)
(Table 4).
Community 3 (Dracaena afromontana- Pouteria adolfi-friederici community) was found in the altitudinal
range of 1761–2000 m. a.s.l and slope from flat to 25%.
Thirteen plots were associated with the community
community and seven species were associated with this
community as indicator species while two of the indicator species showed significant indicator values (P < 0.05)
(Table 4).
Community 4 (Vepris dainellii—Schefflera abyssinica
community) was distributed in the altitude range of
1720–2060 m a.s.l. and the slope gradient varies flat to
60%. It comprised of 14 plots, eight species were associated with this community as indicator species, while four
of the indicator species exhibited significant indicator
values (P < 0.05) (Table 4).
Community 5 (Albizia gummifera—Millettia ferruginea
community) was found in the altitudinal range of 1728–
2014 m. a.s.l and slope from flat to 50%. Twenty-seven
plots were associated to the community. Eight species are
associated with this community as indicator species and
four of the indicator species exhibited significant indicator values (P < 0.05) (Table 4).
From computation of vegetation data in the study area
Shannon-Weiner diversity and evenness, indices for the
five community types showed the output in Table 5.
Relationship between community types
and environmental factors
Heterogeneity or homogeneity of vegetation data test
using DCA resulted in short length (gradient) of DCA
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 7 of 17
Table 1 List of species in Gerba Dima Forest
No
Scientific names
Family
Local namesa
Habit
Voucher No.
1
Acanthopale ethio-germanica Ensermu
Acanthaceae
Dargu
S
AD005
2
Acanthus eminens C.B.Clarke
Acanthaceae
Qosambe booyyee
S
AD107
3
Achyranthes aspera L
Amaranthaceae
Maxxane
H
AD160
4
Achyrospermum schimperi (Hochst. ex Briq.) Perkins
Lamiaceae
–
H
AD134
H
AD120
–
H
AD062
5
Adiantum poiretii Wikstr
Adiantaceae
6
Aerangis brachycarpa (A. Rich) Th Dur.& Schinz
Orchidaceae
7
Aframomum corrorima (Braun) Jansen
Zingiberaceae
Ogiiyo
H
AD045
8
Aframomum zambesiacum (Baker) K. Schum
Zingiberaceae
Ogiiyo jaldessaa
H
AD096
9
Ageratum conyzoides L
Asteraceae
–
H
AD038
10
Ajuga sp. (= Friis et al. 1456)
Lamiaceae
Gondii
H
AD118
11
Alangium chinense (Lour.) Harms
Alengeaceae
Hudu fardaa/sendo
T
AD007
12
Albizia gummifera (J.F. Gmel.) C.A. Sm.,
Fabaceae
Ambabbessa dhaltu
T
AD078
13
Albizia schimperiana Oliv
Fabaceae
Ambabbessa kormaa
T
AD009
14
Alchemilla abyssinica Fresen
Roseaceae
Korbesso
H
AD013
15
Allophyllus abyssinicus (Hochst.) Radlk
Sapindaceae
Se’o
T
AD021
16
Antrophyum mannianum Hook
Vittariaceae
Gixoo
H
AD082
17
Apodytes dimidiata E. Mey. ex Arn
Icaccinaceae
Wandabiyo
T
AD123
18
Arisaema mooneyanum Gilbert & Mayo
Araceae
Kiicu
H
AD144
19
Asparagus africanus Lam
Asparagaceae
Sariiti
H
AD165
20
Asparagus flagellaris (Kunth) Baker
Asparagaceae
Sariiti
H
AD180
21
Asparagus setaceus (Kunth) Jessop
Asparagaceae
Sariiti
H
AD174
22
Asplenium aethiopicum (Burm.f.) Bech
Aspleniaceae
–
H
AD179
24
Asplenium bugoiense Hieron
Aspleniaceae
Giixoo
H
AD143
23
Asplenium elllottii C.H.Wright,
Aspleniaceae
Giixoo
H
AD122
25
Asplenium erectum Bory ex Willd
Aspleniaceae
–
H
AD101
27
Asplenium sandersonii Hook
Aspleniaceae
Giixoo
H
AD083
26
Asplenium warnetkei Hieron
Aspleniaceae
Giixoo
H
AD042
28
Bersama abyssinica Fresen
Melianthaceae
Lolchisaa
T
AD024
29
Bothriocline schimperi Oliv. & Hiern exBenth
Asteraceae
Ilbu
S
AD129
30
Brillantaisia madagascariensis T. Anders. ex Lindau
Acanthaceae
Huxii
S
AD037
31
Brucea antidysenterica J. F. Mill
Simaroubaceae
Qomanyo
T
AD041
32
Canthium oligocarpum Hiern
Rubiaceae
Mixo
S
AD029
33
Cassipourea malosana (Baker) Alston
Rhizophoraceae
Looko
T
AD046
34
Cayratia gracilis (Guill. & Perr.) Suesseng
Vitaceae
Kalaalaa qamale
H
AD093
35
Celtis africana Burm.f
Ulmaceae
Ceeyii
T
AD015
36
Chionanthus mildbraedii (Gilg & Schellenb.) Stearn
Oleaceae
Kara waayyu
T
AD004
37
Cissampelos mucronata A.Rich
Menispermaceae
–
L
AD008
38
Clausena anisata (Wild.) Benth
Rutaceae
Ulmaayye
S
AD087
39
Clerodendrum myricoides (Hochst.) Varlee,
Lamiaceae
Maraasisaa
S
AD099
40
Clematis longicauda Steud. ex A. Rich
Ranuaculaceae
Fiitii
L
AD002
42
Coffea arabica L
Rubiaceae
Buna
T/S
AD010
41
Coleochloa abyssinica (Hochsl. ex A Rick) Gilly
Cyperaceae
Coqorsa mukaa
H
AD019
43
Combretum paniculatum Vent
Combreataceae
Bagge
L
AD177
44
Commelina diffusa Burm.f
Commelinaceae
Qorxabo
H
AD161
45
Coniogramme africana Heiron
Hemionitidaceae
–
H
AD006
46
Cordia africana Lam
Boraginaceae
Waddessa
T
AD110
47
Crotalaria rosenii (Pax) Milne-Redh. ex Polhill
Fabaceae
Ceekaa
H
AD147
48
Croton macrostachyus Del
Euphorbiaceae
Makkanisa
T
AD030
49
Cucumis dipsaceus Ehrenb. ex Spach
Cucurbitaceae
Umbaa’oo
H
AD036
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 8 of 17
Table 1 (continued)
No
Scientific names
Family
Local namesa
Habit
Voucher No.
50
Culcasia falcifolia Engl
Araceae
Qasso
H
AD077
51
Cyathea manniana Hook
Cyatheaceae
Sesino
T
AD074
52
Cyperus fischerianus A. Rich
Cyperaceae
Qunni
H
AD126
53
Cyperus longus L
Cyperaceae
–
H
AD011
54
Dalbergia lactea Vatke
Fabaceae
Sarxe dhittaa
S
AD018
55
Deinbollia kilimandscharica Taub
Sapindaceae
Qaso
T
AD017
56
Desmodium repandum (Vahl)DC
Fabaceae
Maxxanne
H
AD033
57
Didymochlaena truncatula (Sw.)J.Sm
Dryopteridaceae
–
H
AD035
58
Dombeya torrida (J.F. Gmel.) P.Bamps
Sterculiaceae
Daanisaa
S
AD034
63
Doryopteris concolor (Langsd & Fisch.) Kuhn
in von der Deck.efl
Dryopteridaceae
–
H
AD051
59
Dracaena afromontana Mildbr
Dracenaceae
Sarxe
T/S
AD072
60
Dracaena fragrans (L.) Ker Gawl
Dracenaceae
Sarxe
S
AD090
61
Dracaena steudneri Engl
Dracenaceae
Sarxe
T
AD108
62
Drynaria volkensii Hieron
Polypodiaceae
Balessa
H
AD012
64
Ehretia cymosa Thonn
Boraginaceae
Ulaagaa
T
AD026
65
Ekebergia capensis Sparrm
Meliaceae
Sombo
T
AD061
66
Elaeodendron buchananii (Loes.) Loes
Celastraceae
Waaso
T
AD167
67
Elastostema monticolum Hook.f
Urticaceae
–
H
AD162
68
Ensete ventericosum (Welw.) Cheesman
Musaceae
Eeppoo
H
AD171
69
Erythrococca trichogyne (Muell. Arg.) Prain
Euphorbiaceae
Caakkoo
T/S
AD032
70
Euphorbia ampliphylla Pax
Euphorbiaceae
Adaami
T
AD040
71
Euphorbia schimperiana Scheele
Euphorbiaceae
Ananno
S
AD064
72
Ficus exasperata Vahl
Moraceae
Baalaantaayii
T
AD068
73
Ficus ovata Vahl
Moraceae
Qilxu
T
AD065
74
Ficus sur Forssk
Moraceae
Harbu
T
AD073
75
Ficus thonningii Blume
Moraceae
Dambii
T
AD136
76
Flacourtia indica (Burm.f.) Merr
Flacourtiaceae
Akuku
T
AD139
77
Galiniera saxifraga (Hochst.) Bridson
Rubiaceae
Simararu
T
AD137
78
Glycine wightii (Wight ’& Am) Verde
Fabaceae
Kalaalaa
H
AD170
79
Gouania longispicata Engl
Rhaminaceae
Hidda reffaa
L
AD020
80
Hallea rubrostipulata (K. Schum.) J.-F. Leroy
Rubiaceae
Oobo/Bootto
T
AD016
81
Hibiscus panduriformis Burm.f
Malviaceae
Dabbasee
H
AD163
82
Hippocratea africana (Willd.) Loes
Celastraceae
Xiyo
L
AD166
83
Hippocratea pallens Planch ex Oliver
Celastraceae
Qawo
L
AD121
84
Hypoestes forskaolii (Vahl) R. Br
Acanthaceae
Dargu
H
AD124
85
Hypoestes triflora (Forssk.) Roem & Schult
Acanthaceae
Dargu
H
AD135
86
Ilex mitis (L.) Radlk
Aquifoliaceae
Qato
T
AD155
87
Ipomea indica (Burm. f ) Merrill
Convolvulaceae
Kalaalaa
H
AD148
88
Isoglossa somalensis Lindau
Acanthaceae
Ilbu
H
AD001
89
Jasminum abyssinicum Hochst. ex DC
Oleaceae
Ilchime
L
AD080
90
Justicia bizuneshiae Ensermu
Acanthaceae
-
H
AD059
91
Justicia schimperiana (Hochst. ex Nees) T. Anders
Acanthaceae
Dhumugaa
S
AD053
92
Kalanchoe petitiana A. Rich
Crassulaceae
Bosoqe mukaa
H
AD044
93
Keetia gueinzii (Sond.) Bridson
Rubiaceae
Halale
T/S
AD111
94
Lagera crispata (Vahl) Hepper & Wood
Asteracea
–
H
AD117
95
Landolphia buchananii (Hall.f.) Stapf
Apocynaceae
Geebbo
L
AD133
96
Lepidotrichilia volkensii (Gurke) Leory
Meliaceae
Haalalee
T
AD138
97
Lobelia giberroa Hemsl
Lobeliaceae
Dingiraro
S
AD169
98
Loxogramme abyssinica (Baker) MG. Price
Polypodiaceae
Giixo
H
AD175
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 9 of 17
Table 1 (continued)
No
Scientific names
Family
Local namesa
Habit
Voucher No.
99
Macaranga capensis (Baill.) Sim
Euphorbiaceae
Ongo
T
AD168
100
Maesa lanceolata Forssk
Myrsinaceae
Abbayyi
T
AD027
101
Marattia fraxinea Sm
Marattiaceae
–
H
AD028
102
Maytenus gracilipes (Welw.ex Oliv.) Exell
Celastraceae
Kombolcha
S
AD114
103
Maytenus undata (Thunb.) Blakelock
Celastraceae
Ilikke
T
AD132
104
Megalastrum lanuginosum (Willd. ex Kaulf ) Holttum
Tectariaceae
–
H
AD151
105
Microglossa pyriflolia (Lam.) O. Kuntze
Asteraceae
Nobbe
H
AD173
106
Millettia ferruginea (Hochst.) Baker
Fabaceae
Sottallo
T
AD131
107
Monothecium glandulosum Hochst
Acanthaceae
Dargu
H
AD091
108
Myrsine africana L
Myrsinaceae
–
S
AD089
109
Ocimum lamiifolium Hochst.ex Benth
Lamiaceae
Damakase
S
AD097
110
Olea capensis L
Oleaceae
Gagamaa
T
AD100
111
Olea welwitschii (Knobl.) Gilg & Schellenb
Oleaceae
Ba’aa
T
AD050
112
Oplismenus hirtellus (L.) P. Beauv
Poaceae
Sutto gogorrii
H
AD092
113
Oxyanthus speciosus DC
Rubiaceae
Abraango jaldessaa
T/S
AD079
114
Pavonia schimperiana Hochst. ex A. Rich
Malvaceae
Gajjo
H
AD084
115
Pentas schimperiana (A. Rich.) Vatke
Rubiaceae
–
H
AD031
116
Peperomia abyssinica Miq
Piperaceae
Sarxe mukaa
H
AD176
117
Peperomia retusa (L.f.) A. Dietr
Piperaceae
–
H
AD130
118
Peponium vogelii (Hook.f.) Engl
Cucurbitaceae
Tojjo
H
AD066
119
Phaulopsis imbricata (Forssk.) Sweet
Acanthaceae
Dargu
H
AD039
120
Phoenix reclinata Jacq
Araceae
Mexxi
T
AD022
121
Phyllanthus sepialis Muell. Arg
Euphorbiaceae
Qacamaa
S
AD172
122
Pilea rivularis Wedd
Urticaceae
–
H
AD153
123
Piper capense L.f
Piperaceae
Tunjo
H
AD014
124
Pittosporum viridiflorum Sims
Pittosporaceae
Soolee
T
AD070
125
Polyscias farinosa (Del.) Harms
Araliaceae
–
T
AD095
126
Polyscias fulva (Hiern) Harms
Araliaceae
Karaso
T
AD119
127
Polystachya rivae Shweinf
Orchidaceae
Capho
H
AD094
128
Polystichum wilsonii H. Christ
Dryopteridaceae
–
H
AD113
129
Pouteria adolfi-friederici (Engl.) Baehni
Sapotaceae
Qararo
T
AD152
130
Premna schimperi Engl
Verbenaceae
Urgessaa
S
AD178
131
Prunus africana (Hook. f.) Kalkm
Roseaceae
Homii
T
AD159
132
Psychotria orophila Petit
Rubiaceae
Xumaane
S
AD025
133
Pteris dentata Forssk
Pteridaceae
Giixoo
H
AD157
134
Pteris pteridioides (Hook.) ballard
Pteridaceae
Giixoo
H
AD076
135
Pterolobium stellatum (Forssk.) Brenan
Fabaceae
Harangamaa
S
AD154
136
Pupalia micrantha Haumam
Amaranthaceae
Maxxanne
H
AD128
137
Ranunculus multifidus Forssk
Ranunculaceae
–
H
AD149
138
Rhamnus prinoides L’Herit
Rhamnaceae
Gesho
S
AD067
139
Ritchiea albersii Gilg
Capparidaceae
Daqqo
T
AD140
140
Rothmannia urcelliformis (Hiern) Robyns
Rubiaceae
Diibo
T
AD069
141
Rubus apetalus Poir
Roseaceae
Goraa
S
AD075
142
Rubus steudneri Schweinf
Roseaceae
Goraa
S
AD071
143
Rytigynia neglecta (Hirn) Robyns
Rubiaceae
Mixo
S
AD112
144
Sapium ellipticum (Krauss) Pax
Euphorbiaceae
Bosoqa
T
AD109
145
Scadoxus nutans (Friis & J. Bjørnstad) Friis & Nordal
Amaryllidaceae
Qulubi jaldessaa
H
AD088
146
Schefflera abyssinica (Hochst. ex A. Rich.) Harms
Araliaceae
Gatamaa
T
AD104
147
Schefflera myriantha (Bak.) Drake
Araliaceae
Qero
L
AD086
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 10 of 17
Table 1 (continued)
No
Scientific names
Local namesa
Family
Habit
Voucher No.
148
Sericostachys scandens Gilg & Lopr
Amaranthaceae
Suddi
L
AD106
149
Setaria megaphylla (Steud.) Th. Dur. & Schinz
Poaceae
Gowaa
H
AD058
150
Solanaceo manni (Hook.f.) C. Jeffrey
Asteraceae
Rejjii caakkaa
S
AD125
151
Solanecio gigas (Vatke) C. Jeffrey
Asteraceae
Raafu boyye
S
AD054
152
Solanum adoense Hochst. ex A. Rich
Solanaceae
Hiddi- xino
S
AD102
153
Solanum giganteum Jacq
Solanaceae
Tambo arbaa
S
AD048
154
Stellaria mannii Hook.f
Caryophyllaceae
Moccoo
H
AD127
155
Syzygium guineense (Willd.) DC
Myrtaceae
Baddessaa
T
AD141
156
Tacazzea apiculata Oliv
Asclepidiaceae
Gebbo
L
AD116
157
Tacazzea conferta N.E. Br
Asclepidiaceae
Gebbo qalame
L
AD145
158
Teclea nobilis Del
Rutaceae
Mola’ee
T
AD158
159
Tectaria gemmifera (Fee) Alston
Tectariaceae
Gixoo
H
AD023
160
Thalictrum rhynchocarpum Dill. & A. Rich
Ranunculaceae
Finge
H
AD105
161
Thunbergia alata Boj. ex Sims
Acanthaceae
–
H
AD043
162
Tiliacora troupinii Cufod
Menispermaceae
Liqixi
L
AD146
163
Trema orientalis (L.) Bl
Ulmaceae
Huddu farddaa
T
AD164
164
Trichilia dregeana Sond
Meliaceae
Luyyaa
T
AD049
165
Trifolium rueppellianum Fresen
Fabaceae
Amagixa
H
AD150
166
Trilepisium madagascariense DC
Moraceae
Same’eko/ceeyii
T
AD085
167
Tristemma mauritianum J. F. Gmel
Melistostomaceae
–
H
AD052
168
Triumfetta brachyceras K. Schum
Tilaceae
Incciinii
S
AD142
169
Turraea holstii Gurke
Meliaceae
Ceekaa
S
AD003
170
Urera hypselodendron (A. Rich.) Wedd
Urticaceae
Capho
L
AD047
171
Urtica simensis Steudel
Urticaceae
Doobbii
H
AD115
172
Vangueria apiculata K. Schum
Rubiaceae
–
T
AD056
173
Vepris dainellii (Pichi-Serm.) Kokwaro
Rutaceae
Hadhessa
T
AD098
174
Vernonia amygdalina Del
Asteraceae
Eebicha
T
AD055
175
Vernonia auriculifera Hiern
Asteraceae
Rejjii
T/S
AD156
176
Vernonia hochstetteri Sch. Bip. ex Walp
Asteraceae
Soyama masango
S
AD057
177
Vernonia rueppellii Sch. Bip. ex Walp
Asteraceae
Tambo Arbaa
S
AD103
178
Vernonia wollastonii S. Moore
Asteraceae
–
H
AD060
179
Zehneria minutiflora (Cogn) C. Jeffrey
Cucurbitaceae
Kalaalaa bosonu
H
AD063
180
Zehneria scabra (Linn. f ) Sond
Cucurbitaceae
Kalaalaa bosonu
H
AD081
a
Local name = Afan Oromo
first axis i.e., < 3 (2.22) which indicate the presence of
lower species turnover or homogeneous vegetation
data due to the linear relationship between species and
environmental variables. The result of Monte Carlo test
showed that out of 14 environmental variables, seven
were found to be significant in explaining patterns of
plant community distribution. From the seven significant
environmental factors, the vif values of sand and silt were
higher than 5. Sand and Silt are highly correlated with at
least one of the other variables in the model. One solution in dealing with collinearity is to remove some of the
violating variables from the model and thus the one with
higher vif value (sand) was eliminated. The result of RDA
ordination showed that comparatively, the gradient of
altitude and potassium was highly correlated on axis one
and gradient of disturbance in axis two. The other factors
were correlated with the five axes with a different value
of correlation. The eigenvalue for axis one, two and three
were 10.65, 8.06, and 6.32 respectively. Cumulative proportion variance explained by the first five RDA axis of
the joint biplot was 93.9%. The proportion of variation
explained by five RDA axis also shows a decline towards
the successive higher axis (Table 6).
RDA ordination of the study plots of Gerba Dima
forest formed five groups or community based on the
species composition. These five community types were
segregated following the arrows of the environmental
variables. Community 3 and community 4 are found in
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 11 of 17
Table 2 Endemic species, their habit, IUCN status and geographical distributions
Species
Family
Habit
IUCN category
Altitude (m)
Acanthopale ethio germanica
Acanthaceae
Shrub
NE
2300_2600
Aframomum corrorima
Zingiberaceae
Herb
NE
1350_2000
Arisaema mooneyanum
Araceae
Herb
NE
2000_3450
Bothriocline schimperi
Asteraceae
Shrub
LC
1300_2820
Clematis longicaudata
Ranunculaceae
Liana
LC
1350_3300
Crotalaria rosenii
Fabaceae
Herb
NT
1350_2800
Justicia bizuneshiae
Acanthaceae
Herb
NE
1200_2100
Millettia ferruginea
Fabacae
Tree
LC
1000_2500
Polyscias farinosa
Araliaceae
Tree
VU
1600_2200
Scadoxus nutans
Amaryllidaceae
Herb
NE
1450_2300
Solanecio gigas
Asteraceae
Shrub
LC
1750_3350
Tiliacora troupinii
Menispermaceae
Liana
NE
1500_2100
Urtica simensis
Urticaceae
Herb
LC
1500_3400
Vepris dainellii
Rutaceae
Ttree
LC
1750_2500
Vernonia rueppellii
Asteraceae
Shrub
LC
2150_3000
Source: [24–32, 41] LC, Least Concern = A taxon is Least Concern when it has been evaluated against the criteria and does not qualify for Critically Endangered,
Endangered, Vulnerable or Near Threatened; NE, Not evaluated = A taxon is Not Evaluated when it is has not yet been evaluated against the criteria; NT, Near
Threatened=A taxon is Near Threatened when it has been evaluated against the criteria but does not qualify for Critically Endangered, Endangered or Vulnerable now,
but is close to qualifying for or is likely to qualify for a threatened category in the near future; VU, Vulnerable = A taxon is Vulnerable when the best available evidence
indicates that it meets any of the criteria, and it is therefore considered to be facing a high risk of extinction in the wild
Fig. 4 Dendrogram of the cluster analysis results of species abundance found in 90 plots
mid altitude area. Community two mostly occur at the
higher altitude while species in community 1 and community 5 are distributed at the lower altitude and higher
EC. Silt, Disturbance and potassium axes were strongly
influencing the distribution of community five. Organic
matter arrow has strongly influenced the distribution
of species in community three and four (Fig. 5). The
ANOVA test indicated that the five community types
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 12 of 17
differ significantly from each other with regard to EC
and K. The result of Tukey’s pair-wise comparison test
indicates that community 4 and 1 differ significantly
with respect to Disturbance and K while community 2
and 3 showed significant differences with respect to EC.
Table 3 Synoptic cover value of plant in Gerba Dima Forest for
species reaching ≥ 1% in at least one community
Table 3 (continued)
Cluster number
C1
C2
C3
C4
C5
Lepidotrichilia volkensii
0.57
2.59
1.23
2.43
3.30
Maytenus gracilipes
2.00
1.82
1.08
2.00
2.30
Millettia ferruginea
2.00
2.95
2.54
2.79
7.89
C1, Croton macrostachyus—Bersama abyssinica; C2, Syzygium guineense—Olea
capensis; C3, Dracaena afromontana—Pouteria adolfi-friederici; C4, Vepris dainellii
Schefflera abyssinica C5, Albizia gummifera—Millettia ferruginea community.
Values in bold indicate the synoptic value of dominant species used in naming
the plant communities
Cluster number
C1
C2
C3
C4
C5
Cluster size
14
22
13
14
27
Allophyllus abyssinicus
3.50
1.05
1.15
0.86
1.26
Bersama abyssinica
3.71
1.73
0.08
0.64
1.22
Croton macrostachyus
7.50
1.77
1.54
1.79
2.48
Cordia africana
2.79
0.55
0.00
0.00
0.63
Olea welwitschii
1.43
1.27
0.15
0.86
0.56
Name of indicator species Community Indicator value P-value
type (C)
Ehretia cymosa
2.36
2.55
1.92
0.79
1.63
Prunus Africana
1
0.528
0.018*
Polyscias fulva
1.64
1.36
1.85
0.93
1.33
Rubus apetalus
1
0.516
0.017*
Apodytes dimidiate
1.43
2.41
1.54
1.64
0.93
Flacourtia indica
2
0.521
0.02*
Olea capensis
3.14
5.59
1.54
1.93
1.04
Pilea rivularis
3
0.498
0.016*
Syzygium guineense
0.64
5.91
1.69
2.43
1.56
Elastostema monticolum
3
0.467
0.039*
Justicia schimperiana
1.29
1.68
0.85
0.36
0.93
Ritchiea albersii
4
0.861
0.001***
Canthium oligocarpum
0.29
1.05
0.62
0.50
0.52
Cassipourea malosana
0.79
1.55
1.08
0.43
0.56
Trema orientalis
4
0.677
0.001***
Combretum paniculatum
0.86
1.14
0.54
0.43
1.04
Sapium ellipticum
4
0.636
0.002**
Dracaena steudneri
1.29
3.09
0.92
1.50
1.22
Vernonia hochstetteri
4
0.538
0.014*
Elaeodendron buchananii
0.64
1.00
0.38
0.00
0.37
Zehneria scabra
5
0.581
0.002**
Oplismenus hirtellus
2.43
4.50
3.00
2.64
2.85
Zehneria minutiflora
5
0.552
0.005**
Rothmannia urcelliformis
1.14
1.95
0.77
0.86
1.15
Urera hypselodendron
5
0.478
0.017*
Sapium ellipticum
0.21
1.64
0.00
1.43
0.93
Vernonia wollastonii
5
0.423
0.045*
Table 4 Indicator species of clusters in Gerba Dima forest with
their significant P-value
C1, Croton macrostachyus-Bersama abyssinica; C2, Syzygium guineense-Olea
capensis; C3, Dracaena afromontana-Pouteria adolfi-friederici; C4, Vepris dainellii
Schefflera abyssinica C5, Albizia gummifera-Millettia ferruginea community.
* = (p < 0.5), ** =(p < 0.01), *** = (p < 0.001)
Tectaria gemmifera
0.93
1.36
1.23
1.29
0.81
Brillantaisia madagascariensis
1.43
2.73
3.00
2.79
2.48
Dracaena afromontana
1.00
3.05
7.69
0.86
0.78
Ficus sur
2.50
1.68
6.77
2.07
1.37
Galiniera saxifrage
1.00
1.05
2.31
1.43
1.56
Hallea rubrostipulata
1.07
0.00
1.31
0.00
0.00
Macaranga capensis
1.21
1.32
2.85
0.71
0.19
Table 5 Species richness, evenness and diversity indices of plant
community types
Oxyanthus speciosus
1.29
1.73
7.01
2.36
1.56
Community
Pouteria adolfi-friederici
2.21
3.05
7.31
2.07
1.26
Species
richness
Shannon diversity
index (H’)
Shannon
Evenness
Acanthopale ethio-germanica
1.36
0.77
2.08
2.43
1.96
Deinbollia kilimandscharica
0.57
1.45
2.62
4.07
1.59
1
138
4.40
0.89
Ilex mitis
0.43
0.59
1.31
4.71
0.44
2
144
4.27
0.86
Justicia bizuneshiae
0.50
1.23
1.31
1.71
1.37
3
107
3.99
0.85
Landolphia buchananii
1.00
1.32
0.85
1.43
1.19
4
104
4.05
0.87
5
140
4.19
0.85
Piper capense
1.00
0.55
0.46
1.43
1.07
Psychotria orophila
0.93
1.36
0.85
1.36
0.85
Pupalia micrantha
0.64
1.36
0.23
1.86
0.93
Schefflera abyssinica
0.50
1.73
1.38
7.29
1.33
Tiliacora troupinii
1.00
1.23
1.08
1.29
1.07
Vepris dainellii
2.21
3.36
3.00
8.43
3.59
Albizia gummifera
3.07
2.50
2.69
2.07
8.63
Clausena anisate
1.79
1.86
1.31
1.43
2.11
Hippocratea pallens
0.64
1.91
1.23
1.50
1.93
Discussion
Floristic composition and diversity of Gerba Dima forest
The existence of diversified flora of Gerba Dima forest
was in line with the general pattern of high species diversity in the tropical montane forests. According to Gentry
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Page 13 of 17
Fig. 5 RDA ordination biplot of 90 quadrats and 6 environmental variables of plant communities
Table 6 Biplot score for constraining variables and their
correlation with the RDA axis, eigenvalues and proportion of
variance explained
Environmental
variables
RDA1
RDA2
RDA3
−0.157
RDA4
RDA5
Disturbance
0.089
−0.68
Altitude
0.880
0.42
SILT
0.084
−0.40
EC
−0.053
0.31
−0.867
0.094
−0.023
OM
−0.094
0.27
−0.208 −0.357
0.844
0.703
−0.27
K
Eigenvalue
0.522
0.453
−0.054 −0.018
0.218
−0.361 −0.323 −0.370
−0.003 −0.381 −0.246
10.6445
8.0649 6.3168
5.0057 3.02318
Proportion explained
0.3024
0.2291 0.1794
0.1422 0.08588
Cumulative proportion
0.3024
0.5315 0.7109
0.8531 0.93902
[42], tropical forests are among ecosystems that harbour
high species diversity of the globe. East African montane forests of Ethiopia, Kenya, Tanzania and Uganda
are among the most diverse and richest African regions
with regard to flora composition and endemic plant taxa
[43–45]. Asteraceae, Acanthaceae, Rubiaceae, Fabaceae
and Euphorbiaceae are the five dominant families, which
contribute more than 27% of the total species in the study
forest. These dominant families were also reported as top
ten species rich families in many Neotropical forests and
Asia [42]. Except for Rubiaceae, these families are also
among the top ten species rich families in the flora area
[46]. The dominance of the above families together with
Rubiaceae was also reported in other moist afromontane
forests of southwestern Ethiopia [47–49]. Thus, the dominance of these families in the Gerba Dima forest agreed
to their general dominance in the flora area and tropical
forests. The dominance of these families in the study area
could be attributed to their successful colonization to the
landscape owing to their efficient pollination, dispersal
and germination mechanisms [50]. For instance, many
species of Asteraceae have umbrella shape structures
adapted for air dispersal and increase their opportunity
for their successful establishment [50].
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
Among the growth forms, herbs constitute more than
42% of recorded species. The prevalence of herbs could
be attributed to the presence of canopy gap because of
anthropogenic disturbance. Disturbance of forest in the
form of selective cutting of trees favours the growth
of herbaceous species in the forest understory. Under
normal circumstances, the forest floor (herbaceous
layer) of Afromontane rainforests is usually dark and
poor in species composition owing to the closed canopy of the forest that prevents light from reaching the
ground [51].
The higher value of Shannon diversity index and evenness indicates that the study forest has high species diversity with more even distribution of the species within
the study plots. Species diversity increases when the
populations have more even abundances and vice versa
[40]. High Shannon evenness in the Gerba Dima forest indicates little dominance by any single species but
the repeated coexistence of species over all the plots or
sites. Therefore, the implication of evenness values is
that, when there is a high evenness value in a given forest,
the location of conservation sites might not be of much
importance compared to when the evenness value of the
forest is low.
To give a general impression of the species richness
of Gerba Dima Forest, the results of the present study
were compared with results from other Moist Afromontane forests in Ethiopia. The species richness of Gerba
Dima forest is higher than some moist afromontane forest of Ethiopia such as Masha forest (130 species) [48],
Belete forest (157 species) [52], Gelesha forest (157 species) [53], Agama forest (162 species) [49] and more or
less similar in species richness with some other moist
afromontane forest of Ethiopia such as Komto forest
(180 species) [54] and Jibat forest (183 species) [55].
However, the species richness of Gerba Dima forest
was much lower than the values reported for few other
moist afromontane forest of Ethiopia which include
Bonga forest (243 species) [47], Yayu forest (220 species)
[56] Mana Angetu forest (212 species) [57] (Magada forest (197 species) [58] and Gesha and Sayilem forest (300
species [59].
The difference in species richness among the compared
forests could be attributed to the variations of forest sites
with regard to geographical location, altitude, anthropogenic impact, rainfall and other climatic, physiographic
and edaphic factors [60, 61]. Climatic and physiographic
factors have a wide range of effect on the diversity of
plant species across the land escape whereas suitable
environmental conditions and biotic factors influence
diversity at the site level [62, 63]. Species composition
of forests is also influenced by regeneration success and
competition among species [64].
Page 14 of 17
Plant community types in Gerba Dima forest
The output of Multi-response Permutation Procedures
(MRPP) results in T statistics having more negative value
with significant P-value (T = − 38.26, P < 0.001) and an
agreement statistic A (0.13) confirming the distinctness of clusters. The test statistic T describes the separation between the groups. The more negative T value,
the stronger the separation. From the result of this study,
the null hypothesis of no difference among groups can
be rejected. The five groups occupy different regions of
species space, as shown by the strong chance correction within the group (A) and test statistic (T) and thus
confirm the existence of 5 distinct plant communities
in the Gerba Dima forest [37]. The five plant communities showed a slight variation in their species richness,
diversity and evenness. Relatively community types 1, 2
and 5 were the richest with respect to species richness
and diversity while community types 3 and 4 the lowest.
The differences in species richness among the five communities could mainly be attributed to the dissimilarities
of the communities in terms of location, altitude, human
impact, rainfall, and other biotic and abiotic factors.
According Eilu and Obua to [65], different altitudes and
slopes influence species richness and dispersion behaviour of tree species. Altitude and climatic variables like
temperature and rainfall are also other determinant factors that affect species richness [66].
Plant community—environmental variables relationship
In the current study, the multivariate analyses (both
Ordination and cluster analysis) were consistent in showing the patterns of floristic grouping within the studied
forest and hence the two methods are complementary.
The variable with the highest score (0.88) associated
with axis one was the altitude. Therefore, altitude was
the most important variable in weighting axis one and to
interpret or explain the axis. Similar studies conducted in
other Afromontane forests of Ethiopia also confirm the
importance of altitude as a major determinant of vegetation distribution along altitudinal gradients [57, 67, 68].
Altitudinal change leads to changes in humidity, temperature, soil type, and other factors that influence the
growth and development of plants which in turn determine the patterns of vegetation distribution [69, 70].
Potassium followed by altitude was also the most
important constraining variable in weighing axis one
in the ordination. In the sandy soil, plant-soil feedback
effects were most strongly correlated with potassium.
Although most studies investigating abiotic plant-soil
interactions have focused on nitrogen and phosphorus
dynamics, in sandy soils with little clay content, potassium could be a limiting factor for plant growth [71, 72].
In particular, a growth of forbs can be highly dependent
Dibaba et al. BMC Ecology and Evolution
(2022) 22:12
on potassium [71] and hence potassium at least affects
the distribution of these species. In the same way, the
disturbance was the most important variable in weighting axis two. Disturbance affects the distribution of plant
communities by hampering natural regeneration and
seedling establishment in tropical forests [73]. Disturbance also favours the growth of herbaceous plant species by improving the availability of light conditions in
the ground layer as it widens the canopy gap [74] and
thus affects the distribution of communities with these
species. An analysis of variance (ANOVA) performed to
see any significant variation among the community types
of Gerba Dima forest with respect to non-collinear significant environmental variables indicated that the five
community types differ significantly from each other
with regard to EC and K. Similarly, result of Tukey’s pairwise comparison test indicates that community 4 and 1
differ significantly with respect to Disturbance and K
while community 2 and 3 showed significant difference
with respect to EC.
Conclusions
Description of the floristic diversity of species in the
Gerba Dima forest revealed the presence of high species diversity and richness. Of the species recorded in
this forest, 15 (8.3%) species were endemic to Ethiopia.
However, the percentage of endemic species in the study
forest is lower than the proportions generally expected in
the Afromontane forest of Ethiopia and this is attributed
to the low endemicity feature of forests in South-western
Ethiopia. In this study, five community types were identified and altitude was the major environmental variable in
determining the community types. The existence of high
species diversity and a number of endemic plant species
in the study forest shows the potential of the area for
biodiversity conservation. Thus, all Stakeholders including Oromia Forest and wildlife enterprise (OFWE) and
the regional government should work to designate the
forest as a biosphere reserve and being registered under
UNESCO.
Abbreviations
DCA: Detrended Correspondence Analysis; RDA: Redundancy Analysis; Vif:
Variance inflation factor; MRPP: Multi-response Permutation Procedures.
Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12862-022-01964-4.
Additional file 1: Dominant families with their respective species number
of Gerba Dima Forest.
Page 15 of 17
Acknowledgements
We would like to thank Addis Ababa University for providing logistics for
fieldwork and laboratory analysis.
Authors’ contributions
All authors have made substantive intellectual contributions to this manuscript. AD is made substantial contributions to conception and design, or
acquisition of data, or analysis and interpretation of data and also been
involved in drafting the manuscript or revising it critically for important intellectual content. TS is also made substantial contributions to conception and
design of data, or analysis and interpretation of data but not involved in data
collection or acquisition of data. BW has been involved in drafting the manuscript or revising it critically for important intellectual content. All authors read
and approved the final manuscript.
Funding
This study was supported by International Foundation for Science (Grant
Number D/5481-1). The funders had no role in study design, data collection
and interpretation, or the decision to submit the work for publication.
Availability of data and materials
We have also included part of the data used in this research and attached as
Additional files 1.
Declarations
Ethics approval and consent to participate
This research is mainly an ecological and study and did not involve experiment on plant species. Thus, Parts related to Ethics approval and consent to
participate is not applicable for this work. Related to this part, the collected
plant specimens in this research were deposited in the national herbarium of
Ethiopia. However, experiment was not conducted on the plant. Permissions
were needed and subsequently obtained From Oromia Forest and Wildlife
Enterprise in order to use/sample the land as described, and obtain samples.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
College of Natural Sciences, Department of Biology, Debre Berhan University,
P. O. Box 445, Debre Berhan, Ethiopia. 2 Center for Environmental Science, Addis
Ababa University, P. O. Box 1176, Addis Ababa, Ethiopia. 3 College of Natural
Sciences, Department of Plant Biology and Biodiversity Management, Addis
Ababa University, P. O. Box 3434, Addis Ababa, Ethiopia.
Received: 20 October 2021 Accepted: 18 January 2022
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