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Detailed information on plant community types, distribution, and their relationships with various environmental gradients is crucial for understanding forest dynamics and sustainable forest management because plant community types are influenced by various environmental factors. Thus, this study was conducted to investigate plant community types and species diversity in relation to various environmental gradients in Geramo Forest, which is a remnant forest in the western escarpment of the Rift Valley of Ethiopia. Vegetation data were collected in 96 nested plots (20 × 20 m2 and five 1 ×1 m2) laid systematically at a distance of 250 m along 16 line transects, which were laid 300 m apart. Environmental and disturbance variables were also collected from each main plot. Agglomerative hierarchical cluster analysis and Canonical correspondence analysis (CCA) with R software were used to identify plant community types and analyze the relationship between plant community types and environmental variables, respectively. The Shannon Wiener diversity index was used to compute species diversity among community types. Five significantly different (p ≤ 0.001) plant community types were identified. The CCA results showed that species diversity and community composition among different community types were significantly influenced by altitude, disturbance, soil organic carbon, slope, soil available phosphorus, and pH, which revealed the compounded effect of various environmental factors on species richness, diversity, and evenness among plant community types. The study also identified a significant level of anthropogenic disturbance and a strong reliance of the local community on the forest in the research area. Therefore, it is recommended that sustainable forest conservation interventions be implemented through awareness creation and the promotion of community-based approaches., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Getaneh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Forest vulnerability to drought is expected to increase under anthropogenic climate change, and drought-induced mortality and community dynamics following drought have major ecological and societal impacts. Here, we show that tree mortality concomitant with drought has led to short-term (mean 5 y, range 1 to 23 y after mortality) vegetation-type conversion in multiple biomes across the world (131 sites). Self-replacement of the dominant tree species was only prevalent in 21% of the examined cases and forests and woodlands shifted to nonwoody vegetation in 10% of them. The ultimate temporal persistence of such changes remains unknown but, given the key role of biological legacies in long-term ecological succession, this emerging picture of postdrought ecological trajectories highlights the potential for major ecosystem reorganization in the coming decades. Community changes were less pronounced under wetter postmortality conditions. Replacement was also influenced by management intensity, and postdrought shrub dominance was higher when pathogens acted as codrivers of tree mortality. Early change in community composition indicates that forests dominated by mesic species generally shifted toward more xeric communities, with replacing tree and shrub species exhibiting drier bioclimatic optima and distribution ranges. However, shifts toward more mesic communities also occurred and multiple pathways of forest replacement were observed for some species. Drought characteristics, species-specific environmental preferences, plant traits, and ecosystem legacies govern postdrought species turnover and subsequent ecological trajectories, with potential far-reaching implications for forest biodiversity and ecosystem services.

We evaluated the applicability of the Visible and Near Infrared bands (15 m spatial resolution) of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery in mapping land use/cover in the drylands of northern Ethiopia. Ground Control Points were collected from the field using Geographic Positioning System in which half of them were used for classification and the remaining for accuracy assessment. The image was classified into four dominant land use/cover types that represent the major habitats of the study site. Image classification was done using pixel-based supervised classification with the Maximum Likelihood Classification algorithm. The accuracy of classification was evaluated using error matrix and Kappa statistics. Finally, we found an overall classification accuracy of 80% and this implies that ASTER imagery can be used as a good source of data in mapping biodiversity at habitat scale in data scarce drylands of northern Ethiopia. [ABSTRACT FROM AUTHOR]

We investigated arbuscular mycorrhizal fungi (AMF) spore density and root colonization in three distinct dry Afromontane forest plant communities, representing differing levels of disturbance and soil properties. Soil and root samples were collected from sixty-five 50 × 50-m plots from four plant communities. We collected data for AMF spore density, AMF root colonization and soil organic carbon stocks in 0–25 and 25–50 cm soil depth ranges. AMF spore density, and root colonization differed significantly among plant communities. The least disturbed Juniperus procera–Maytenus senegalensis (Jupr-Mase) plant community, which contained high tree and shrub density, had the highest AMF spore density, root colonization and soil carbon stocks. The most disturbed Cadia purpurea–Opuntia ficus-indica (Capu-Opfi) community which contained the lowest tree and shrub density supported the lowest AMF spore density, root colonization and soil carbon stocks. There was no significant difference in spore density between the two soil depths, but AMF root colonization was significantly higher in the upper soil than in the subsoil (p < 0.001). The difference in soil properties was not uniform between plant communities. Conserving remnant dry Afromontane forests and restoring the degraded forests are critical to improve and maintain forest ecosystem functioning and sustain ecosystem services. [ABSTRACT FROM AUTHOR]

Forest management, agroforestry and tree planting are some of the key approaches to sustainable rural development, and climate change adaptation and mitigation in West African savannas. However, the planning of land management interventions is hindered by the lack of information at relevant spatial resolution. We examined predictive models for mapping various tree, soil and species diversity attributes with a comparison of RapidEye and Landsat imagery. The field data was collected in the vicinity of the community-managed forest in southern Burkina Faso, where the main environmental threats are agricultural expansion and fuelwood extraction. The modelling was done using Random Forest algorithm. According to our results, tree crown cover and correlated attributes, such as basal area and tree species richness, were predicted most accurately. High spatial resolution RapidEye imagery provided the best accuracy but difference to medium resolution Landsat imagery was negligible for most attributes. Burn scar masked Landsat time series performed similar to dry season single date Landsat imagery, but the former avoids image selection and mosaicking, and could be less sensitive to artifacts due to the burn scars. The presented approach provides valuable information on important tree, soil and species diversity attributes for spatial planning of land management interventions. [ABSTRACT FROM AUTHOR]