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The vegetation composition, structure and regeneration status of Gole Natural Forest, West Arsi Zone, Oromia Regional State, Ethiopia

Cite this dataset

Belete, Mesfin; Demsis, Tamru (2020). The vegetation composition, structure and regeneration status of Gole Natural Forest, West Arsi Zone, Oromia Regional State, Ethiopia [Dataset]. Dryad.


This study was conducted in Gole natural forest (Dodola) West Arsi Zone of Oromia Regional State, Ethiopia. The study was intended to investigate the vegetation composition, structure, community types and the regeneration status. To collect the vegetation data, systematically 62 plots 20 m × 20 m (400 m2) were established at 100 m interval, starting from the top of the mountain. Tree and shrub species were counted and their cover abundance value was estimated. The data for herbaceous species were collected from five 2 m × 2 m sub-plots laid at the four corners each and one at the centre of the main plot. Height and diameter at breast height (DBH) of all woody species taller than 1.5 m and thicker than 2 cm were measured. R package was applied for cluster analysis. Indicator species analysis was performed in R Interpolated species accumulation curves. Estimate S 8.2 Software and Microsoft Excel were used to analyze the data. Rarefaction was applied to compare the species richness of the plant communities in the study area. Sorensen’s similarity coefficient was used to detect similarities and dissimilarities among communities.

A total of 114 plant species belonging to 57 families and 94 genera were identified. The most dominant families were Asteraceae, followed by Acanthaceae and Lamiaceaae. Out of 114 species 17 were endemic to Ethiopia. The study showed that high density was seen at lower height and DBH classes. Five plant community types were identified. The rarefaction revealed that there is difference in species richness among communities. The Sorensen’s similarity index showed that, there was a difference in the distribution of plant species composition among the five plant communities.


Systematically, quadrats of 20 m x 20 m (400 m2) were established. The first plot was established randomly starting from the top of the mountain to the lower side, and then the remaining plots were established 100 m interval along transect lines. A total of 62 quadrats were laid for vegetation data collection. Trees and shrubs were collected from the main plots. Five subplots of 2 x 2 m one at the center and four at the corner of the main (20x20m) plot were laid to collect data of herbaceous plants (Hailemariam MB. and Temam TD., 2018). Voucher specimens were collected for all plant species and were identified at National Herbarium (ETH). Environmental factors (altitude) and geographical coordinates were measured using Garmin GPS in the middle of the main plots.  The types of disturbance were recorded for each plot. Disturbance could be grazing, number of trees and shrubs cut, number of foot trails, and number of seedlings trampled. The intensity of anthropogenic disturbance (grazing) in each plot was estimated as a sum (cumulative effect) of the following scale: 0 = no disturbance, 1 = slightly disturbed, 2 = moderately disturbed, 3 = highly disturbed and 4 = destructive. Cover-abundance values were estimated using the modified Braun Blanquet scales (Van der Maarel E., 2005).

Classification and ordination methods were used to describe vegetation types and to examine the relationship between vegetation types and environmental variables. R statistical package (R Development Core Team, 2009), was used for cluster and ordination analysis. Indicator species analysis was performed to find indicator species characterizing the communities. Indicator species analysis was performed in R using package labdsv (Roberts DW., 2012). Box plots and One-way analysis of variance (ANOVA) were used to assess the relationships between plant communities and elevation as well as plant communities with disturbance intensity. Tukey’s test was performed to detect significant differences among the different means of the environmental parameters of each community types. Sorenson's index of similarity (Ss) was computed to assess the floristic similarity between communities.