This study was conducted in Agama Forest in Kafa Zone, Southwestern Ethiopia, to assess species diversity, vegetation structure, and regeneration status of woody species. A systematic sampling technique was employed to collect vegetation data. Sixty (60) sample plots of 25 m × 25 m were laid at 300 m intervals all along ten grids interspaced 800 m apart. Sample plots of 25 m × 25 m were used to record DBH and H of all woody plant species reaching a DBH >2.5 cm and height >2 m. For the inventory of seedling and sapling, two subplots of 2 m × 5 m were used at the beginning and the end of the baseline on opposite sides of the main quadrat. Vegetation data such as DBH, height, seedling, and sapling density of woody species were recorded in each plot. Altogether, 72 woody plant species of 65 genera and 35 families were identified. Analysis of selected tree species showed diverse population structures. This study showed that small trees and shrubs dominated the Agama Forest, which revealed its status under a secondary regeneration stage. Study on the structure and regeneration of some woody species indicated that there are species that require urgent conservation measures. Sound management and monitoring, as well as maintenance of biodiversity and cultural and economic values of the forest, require conservation activities that encourage sustainable uses of the forest and its products.

Background Unlike in the developed countries, Ethiopia does not have carbon inventories and databank to monitor and enhance carbon sequestration potential of different forests. Only small efforts have been made so far to assess the biomass and soil carbon sequestration at micro-level. This study was carried out to obtain sufficient information about the carbon stock potential of Gerba-Dima forest in south-western Ethiopia. A total of 90 sample plots were laid by employing stratified random sampling. Nested plots were used to collect data of the four carbon pools. For trees with a diameter range of 5 cm < diameter < 20 cm, the carbon stock was assessed from a plot size of 49 m 2 (7 m * 7 m). For trees with a diameter range of 20 cm < diameter < 50 cm, the carbon stock was assessed from a plot size of 625 m 2 (25 m * 25 m). For trees > 50 cm diameter, an additional larger sample of 35 * 35 m 2 was used. Litter, herb and soil data were collected from 1 m 2 subplot established at the center of each nested plot. To compute the above ground biomass carbon stock of trees and shrubs with DBH > 5 cm, their DBH and height were measured. The biomass carbon assessment of woody species having DBH < 5 cm, litter and herb were conducted by measuring their fresh weight in the field and dry weight in the laboratory. Results The mean total carbon stock density of Gerba-Dima forest was found to be 508.9 tons carbon ha −1 , out of which 243.8, 45.97, 0.03 and 219.1 tons carbon ha −1 were stored in the above ground biomass, below ground biomass, litter biomass and soil organic carbon, respectively. Conclusions The existence of high carbon stock in the study forest shows the potential of the area for climate change mitigation. Thus, all stakeholders at the local and national level should work together to implement effective conservation measures and get benefit from the biocarbon fund. Electronic supplementary material The online version of this article (10.1186/s13021-019-0116-x) contains supplementary material, which is available to authorized users.

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.

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. Ninety sample plots having a size of 25 X 25m (625m2) 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 ≥ 1.5m were recorded in 25 m X 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.

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. Ninety sample plots having a size of 25 X 25m (625m 2 ) 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 ≥ 1.5m were recorded in 25 m X 25 m plots. Within the major plots, five 3m x 3m subplots (9m 2 ) was used to collect shrubs with dbh < 2.5 cm and > 1.5m height. Within each 9m 2 subplots, two 1m 2 subplots were used to collect data on the species and abundance of herbaceous plants. 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. 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 EC and K. Conclusions: The studied forest can play a significant role in biodiversity conservation since it harbours high species diversity and richness. 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. Keyword s: Gerba Dima; Indicator species; Moist Afromontane Forest; Species diversity

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. Ninety sample plots having a size of 25 X 25m (625m2) 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 ≥ 1.5m were recorded in 25 m X 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.

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. 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 X 25 m plots. Within the major plots, five 3 m x 3 m subplots (9 m2) was used to collect shrubs with dbh < 2.5 cm and > 1.5 m height. Within each 9 m2subplots, two 1 m2 subplots were used to collect data on the species and abundance of herbaceous plants. 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. 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 EC and K. Conclusions The studied forest can play a significant role in biodiversity conservation since it harbours high species diversity and richness. 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.

This study was conducted in Gerba Dima Forest, South Western Ethiopia to formulate allometric equations for Pouteria adolfi-friederici. Prior to collecting data for tree allometry, the study forest was stratified into 3 forest strata based on altitudinal variation. By employing semi-destructive technique, 30 individuals were systematically selected and sampled for measuring biomass along the three forest strata. Based on the data collected, several equations were developed. Before establishing the allometric equation, scatter plots were used to see whether the relationship between independent and dependent variables was linear. Furthermore, several allometric relationships between independent and dependent variables were tested. The best-fit model developed was validated by testing the regression assumptions. AGB was regressed against the various forms of predictors (i.e., DBH, H and WD) and three allometric models showed significant performance (p < 0.05) on their F-test. Among the three allometric equations which showed significant performance, the selection of the best-fit model was conducted based on their P-value, adjusted r2, AIC, RMSE. The two models are nested to the third model and hence the complete model, lnAGB=1.806+1.419×lnDBH+0.628×lnWD, is selected as the best-fit model against the other two nested models since the p-values of coefficients of the complete model are significant (p < 0.05).