There have been incredible changes that have taken place in the land use pattern globally over the last 50 years, which resulted from environmental degradation and climate change impacts. Quantitative analysis of the LULC dynamics helps in land-use management and ecosystem degradation at large. The study was conducted in the Doyogena district, southern Ethiopia to identify LULC change dynamics, and analyze the driving forces using combined approaches: remote sensing, field observations, in-depth household interviews, key informants, and Focus Group Discussions (FGDs). A supervised maximum likelihood image cataloging method was employed in conjunction with feature extraction of satellite images to categorize and map LULC classes of the study area. Satellite image handing out, classification technique, and remotely sensed data were processed using ArcGIS map 10.6, and ERDAS Imagine 2014. Common LULC categories were identified, and a change analysis was conducted. Accordingly, seven LULC categories were determined. The result showed a considerable decline in forestland from 1756.7 ha (38.8%) in 1973 to 71.6 ha (1.6%) in 2020. Similarly, wetlands have declined successively from 16.8 in 2000–2010 to 6.3 in 1986–2020 ha/year over the last three and half decades respectively. On the other hand, cropland has increased from 34.1% in 1986–2000 to 46.3% between 1986–2020, which is linked to population growth, settlement, and expansion of farmlands. The study watershed has experienced a considerable change in LULC change over the last >3 decades. Hence, local and national regimes should implement sustainable land planning, management strategies including integrated land- use planning, and policy reform into development projects and programs.

Human settlements and swift expansion of agriculture have simplified the natural ecosystems and causing the loss of copious biological diversity. The current study was conducted in Bita district, southwestern Ethiopia to examine the pattern of land use/land cover (LULC) dynamics using multispectral satellite data for the years 1973, 1986, 2000 and 2018. The remote-sensed data were processed using ERDAS imagine 2014, ArcGIS map 10.5, and ENVI software. A supervised maximum likelihood classification algorithm was employed along with the visual interpretation of satellite images to classify each Landsat image into LULC categories. Semi-structured interviews and Focus Group Discussions were employed to identify major driving forces, impacts, and periodic LULC changes. The result revealed an alarming decrease in forestland but with an increase in the cropland. During the study periods, cropland, bareland and settlement areas have augmented by over 450% each. Conversely, grasslands and forestlands have reduced by over 45% each. The local communities perceived the population growth, and the expansion of coffee plantations and other croplands as the dominant drivers of LULC changes. The respondents also observed that the decline in forest cover triggered the loss of biodiversity, soil fertility and water availability. Decision-making on issues related to natural resource conservation, utilization and participatory resource management has to involve the engagement of the local community and other stakeholders. The deterioration in ecosystem services such as lack of benefits from medicinal plants from the forest, increase land degradation, and the decrease in water availability found to be the impacts of LULC change. This calls for a proper natural resource management plan and improvement in the livelihood of the community in the study area.

This study was aimed to determine woody species composition, diversity, and vegetation structure and to investigate major threats to Wurg forest, southwest Ethiopia. In order to collect vegetation data, 64 (400m²) sample plots from eight transect lines were employed. The distances between transect lines and plots were 400m and 200m, respectively. DBH of woody species >2.5cm and the height >2m were measured and recorded. Voucher specimens were brought to the Ethiopian Biodiversity Institute for identification and deposited there. R program version 12.5.2 software and Microsoft Excel spreadsheet were used to analyze plant community classification and structural analysis, respectively. A total of 76 woody species representing 40 families were recorded. Rubiaceae was the dominant family followed by Asteraceae. The average ShannonWiener diversity index (H) and the average evenness values of Wurg forest were 3.38 and 0.90, respectively. Four plant community types were identified by using the presence/absence values of each species. The total density of woody species with DBH>2.5cm was 1745.3ha⁻¹. The DBH and height class distributions showed an inverted J-shaped pattern, which indicates a good regeneration potential of the forest. The most frequently observed species (92) was Syzygium guineense, which contributed 46 of the total basal area. The composition of seedling, sapling, and adult trees/shrubs species was 4966.07ha⁻¹, 3125.78ha⁻¹, and 1745.27ha⁻¹, respectively. However, the major threat to the forest was selective cutting of some woody species for various purposes. Therefore, raising local community awareness on conservation and sustainable use of the forest and exploring various alternatives for local communities livelihood and promoting private and community plantations are recommendable.

In developing countries, traditional medicines occupy a central place among rural communities since they contribute to provide health care to them. However, studies on the identification and documentation of medicinal plant (MP) species used for treatment of various ailments, plants parts used, remedies, preparation and administration of herbal drugs have been scarce, especially to determine the consensus factor among local communities and evaluate the potential for new drugs of herbal origin. This paper aims to determine informant consensus factor and fidelity level of ethnomedicinal plants used in Misha Woreda, Southern Ethiopia. A total of 200 informants were selected randomly for the study. Data were collected through semi-structured interview, focus group discussions, observation and guided field walks with informants. The secondary source data were collected from previous annual reports, documented information and relevant literatures. Data were analyzed by using suitable statistical tools such as correlation coefficient, Mann-Whitney U test, informant consensus factor (ICF), Fidelity Level (FL), and various ranking methods. A total of 126MP species belonging to 110 genera and 50 families were recorded. Of the total identified species, 66 were used to treat 34 human ailment, 13 MPs to treat 28 livestock ailments, and 47 MP species were common for both human and livestock treatment. Leaves forming 41% and herbs making 52% of the total identified MPs were dominantly harvested plant parts and plant growth forms, respectively. The dominant mode of remedial preparation was crushing (44%), and most MPs (61%) were administered orally. The highest ICF values were recorded for oral & pharyngeal, and respiratory (0.95 each), depicting the agreement among informants knowledge on MPs used to treat these aliments categories. Medicinal plans species such as Datura stramonium, Prunus africana, and Ruta chalepensis had the highest fidelity level (100% each) indicating the concordance of knowledge on species of best healing potential. Preference ranking indicated that Allium sativum was ranked first and found most effective MP to cure Pneumonia. Therefore, the documented MPs can be used for future pharmacological research, and awareness creation among the traditional healers and community at large becomes vital so as to preserve the indigenous knowledge associated with MP species. Key words: Ethnobotany, Indigenous knowledge, Medicinal plant, Misha, Informant consensus.