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Erica is a dominant vegetation type in many sub-afroalpine ecosystems, such as the Bale Mountains in Ethiopia. However, the past extent of Erica is not well known and climate versus anthropogenic influence on altitudinal shifts are difficult to assign unambiguously, especially during the Holocene. The main objective of the present study is to chemotaxonomically characterize the dominant plant species occurring in the Bale Mountains using lignin phenols and n -alkane biomarkers and to examine the potential of those biomarkers for reconstructing vegetation history. Fresh plant material, organic layer and mineral topsoil samples were collected along a northeastern and a southwestern altitudinal transect (4134–3870 and 4377–2550 m a.s.l., respectively). Lignin-derived vanillyl, syringyl and cinnamyl phenols were analyzed using the cupric oxide oxidation method. Leaf-wax-derived n -alkanes were extracted and purified using Soxhlet and aminopropyl columns. Individual lignin phenols and n -alkanes were separated by gas-chromatography and detected by mass spectrometry and flame ionization detection, respectively. We found that the relative contributions of vanillyl, syringyl and cinnamyl phenols allow us to chemotaxonomically distinguish contemporary plant species of the Bale Mountains. Erica in particular is characterized by relatively high cinnamyl contributions of >40 %. However, litter degradation strongly decreases the lignin phenol concentrations and completely changes the lignin phenol patterns. Relative cinnamyl contributions in soils under Erica were <40 %, while soils that developed under Poaceae (Festuca abyssinica) exhibited relative cinnamyl contributions of >40 %. Similarly, long-chain n -alkanes extracted from the leaf waxes allowed for differentiation between Erica versus Festuca abyssinica and Alchemilla , based on lower C 31 / C 29 ratios in Erica. However, this characteristic plant pattern was also lost due to degradation in the respective O layers and A h horizons. In conclusion, although in modern-day plant samples a chemotaxonomic differentiation is possible, soil degradation processes seem to render the proxies unusable for the reconstruction of the past extent of Erica on the Sanetti Plateau, Bale Mountains, Ethiopia. This finding is of high relevance beyond our case study. Kurzfassung: Erica prägt als dominante Pflanzengattung viele Subafro-alpine Ökosysteme, so auch die Bale Berge in Äthiopien. Das Ausmaß der flächenhaften Ausdehnung von Erica in der Vergangenheit ist jedoch unklar, genauso wie die klimatische versus menschliche Verursachung solcher Vegetationsänderungen insbesondere im Holozän. Das Ziel dieser Studie war es herauszufinden (i) ob sich die dominante Vegetation in den Bale Bergen anhand von ligninbürtigen Phenolen und blattwachsbürtigen n -Alkanbiomarkern chemotaxonomisch unterscheiden lässt und (ii) ob diese Biomarker das Potential haben zur Vegetationsrekonstruktion im Untersuchungsgebiet beizutragen. In einem Begleitartikel (Mekonnen et al., 2019) verfolgen wir dasselbe Ziel, jedoch anhand von Stabilkohlenstoff- und Stickstoffisotopen sowie Zuckerbiomarkern. Untersucht wurden Pflanzenproben, O-Lagen und A h Horizonte entlang eines Nord- und eines Südwest-Höhentransektes (3870–4134 m bzw. 2550–4377 m ü. NN). Die ligninbürtigen Phenoleinheiten Vannilly, Syringyl und Cinnamyl wurden mittels der Kupferoxidationsmethode gewonnen; die n -Alkane wurden mittels Soxhlet extrahiert und über Aminopropylsäulen aufgereinigt. Die Quantifizierung der Ligninphenole und n -Alkane erfolgte mittels Gaschromatographie – Massenspektrometrie bzw. Gaschromatographie – Flammenionisationsdetektion. Die Ergebnisse zeigen, dass sich die dominanten Pflanzenarten in den Bale Bergen anhand ihrer Vanillyl, Syringyl und Cinnamyl Einheiten chemotaxonomisch unterscheiden lassen. So weist insbesondere Erica charakteristischerweise relativ hohe Cinnamyl-Anteile von >40 % auf. Vermutlich degradationsbedingt nimmt jedoch in der Reihe Pflanze – O-Lage – A h Horizont nicht nur die Ligninkonzentration stark ab, sondern auch die Ligninmuster ändern sich völlig. Dadurch weisen Böden unter Erica Cinnamyl-Anteile <40 % auf, während Böden die sich unter der dominanten Grasart Festuca abyssinica entwickelt haben Cinnamyl-Anteile von >40 % aufweisen. Auch anhand der Alkanbiomarker ist eine chemotaxonomische Unterscheidung zumindest zwischen Erica versus Festuca abyssinica und Alchemilla möglich. Als Proxy dient hier das Verhältnis von C 31 zu C 29. Allerdings führt auch hier Degradation in der Reihe Pflanze – O-Lage – A h Horizont zum Verlust des charakteristischen Alkanmusters. Obwohl sich rezentes Pflanzenmaterial chemotaxonomisch unterscheiden lässt, zwingt dies zur Schlussfolgerung, dass Degradationseffekte bei der Rekonstruktion von Erica im Untersuchungsgebiet der Bale Berge in Äthiopien anhand von ligninbürtigen Phenolen und blattwachsbürtigen Alkanbiomarkern nicht unberücksichtigt bleiben dürfen. Dieser Befund ist über unsere Fallstudie hinaus von hoher Relevanz. [ABSTRACT FROM AUTHOR]

Vast areas of forests in North-eastern Ethiopia have been replaced by cropland, shrub land or grazing areas. Thus, information about how vegetation composition and structure varies with disturbance is fundamental to conservation of such areas. This study aimed to investigate the effects of disturbance on the population structure and regeneration potential of five dominant woody species within forest where local communities harvest wood and graze livestock. Vegetation structure and environmental variables were assessed in 50 quadrats (20 m × 20 m). In most of both disturbed and undisturbed treatments, Juniperus procera was the highest contributor to the basal area of the forest, while that of Olinia rochetiana was the lowest. Analysis of population structure showed high density at lower Diameter at Breast Height ( DBH) and low density at higher DBH classes. Undisturbed forest treatments had 84% canopy cover, 22 m mean vegetation height and a density of 1320 trees of dominant species and 1024 seedlings/saplings ha−1. In disturbed habitats, canopy cover (73%), mean vegetation height (18 m) and density of dominant trees and saplings were significantly lower than in undisturbed habitats. Thus, to ensure species, survival and maintain species diversity managed use of the protected area is essential. [ABSTRACT FROM AUTHOR]

Background: Ethiopia is endowed with much plant diversity. The insignificant number of studies on wild edible plants with their ethnobotanical perspectives indicated that this plant diversity comprised only hundreds of wild edible plants used to supplement food sources for the local community under different conditions. There still need to be further investigations throughout the country when compared to the total area and cultural diversity of the country. However, they are seriously under pressure due to different natural and human influences. Therefore, the study was conducted to document underutilized wild edible plants along with their associated indigenous knowledge and explore threats to them in Midakegn District. Methods: A questionnaire survey, semi-structured interviews, a market survey, score ranking, and focused group discussions were employed for data collection. Statistical analysis of ethnobotanical knowledge mean variation between different informant groups was computed by using one-way ANOVA in the IBM SPSS Statics version 24 package. Results: A total of fifty underutilized wild edible plants belonging to 39 genera and 30 families were collected, recorded, and documented. The families Moraceae (four), Fabaceae, Flacourtaceae, Myrtaceae, Rosaceae, and Tiliaceae (each three) represented the highest number of species. It comprised shrubs (44%), trees (36%), herbs (18%), and epiphytes (2%). Fruits (62.3%) were found to be the most frequently used and mostly taken raw, fresh, or dried. These edible resources were consumed to supplement staple foods (67.3%), whereas 25% were used as emergency foods. The majority of species (96%) had multiple uses in addition to their edibility. A significantly higher (P < 0.05) number of underutilized wild edible plants were cited by males than females, by key informants than generals, elders than youngsters, illiterate than literate, and poorer than other wealth class groups of the community. Priority rankings indicate that agricultural expansion, fuel wood harvest, overgrazing, and selective harvesting are the most threatening factors to underutilized wild edible plants. Conclusions: Fifty underutilized wild edible plants, along with their associated indigenous knowledge, were recorded. Local people utilize them for supplementing staple food, as emergency food, to get relief, trust, and chew during drought. But they are mainly threatened by different human activities in the study area. [ABSTRACT FROM AUTHOR]

Abstract: The composition of coffee shade tree species and density of arbuscular mycorrhizal fungi (AMF) spores in Bonga natural coffee forest of southwestern Ethiopia were investigated. This study is the first report on AMF populations of Ethiopian natural coffee forests. The main purposes were to systematically identify the dominant coffee shade tree species, evaluate their densities and quantify and characterize populations of arbuscular mycorrhizal fungi particularly in the rhizosphere of coffee plants. Sample plots of 400m2 with coffee plants and dominant shade tree species were selected. Sampling of soil was carried out at a depth of 0–15cm from the rooting areas of shaded and unshaded coffee plants for analysis of some soil parameters and quantification of AMF spores. Nineteen dominant shade tree species belonging to 14 plant families were identified in considered 10 quadrates. In terms of their stand dominance, Millettia ferruginea (Hochst.) Baker had the highest frequency of occurrence (22.3%) followed by O. welwitschii Friis & P.S. Green (15.5%). High density (503stems/ha) and/or percentage (66%) of Coffea arabica L. were recorded. All soil samples yielded AMF spores and the counts ranged from 4 to 67 spores 100g−1 of dry soil. Notably higher mean counts of AMF spores were found under leguminous shade trees compared to non-leguminous ones. AMF spore counts were significantly positively correlated with coffee counts and available soil P content. Five genera of AMF were identified based on spore morphology. Glomus dominated members of Glomeromycota. The other genera found were Gigaspora, Acaulospora, Entrophospora and Scutellospora in order of occurrence. The present investigation has documented species richness among dominant coffee shade tree species along with a fair distribution of relevant numbers and types (genera) of AMF to stimulate coffee growth. Thus, Bonga natural coffee forest seems to be an ideal focal forest for in situ coffee genetic resources conservation and promotion of organic coffee production. [Copyright &y& Elsevier]

Societal Impact Statement Summary Arabica coffee grows in the forests and woodlands of Ethiopia. These Arabica coffee populations contain a reservoir of the highest genetic variation of this species, which is extremely valuable from a biodiversity conservation and coffee breeding point of view. Knowledge about the distribution of these populations, including how and to what extent they have been managed by local communities now and in the past, is limited. We reveal insights into the history, distribution, and management of Arabica coffee populations in the remaining forests of Ethiopia, which is essential for developing effective conservation policies for this globally important resource. To guide conservation of forest biodiversity in a broad sense, we need to understand the landscape‐level variation in current and historical management practices of agroforestry systems. We collected data on coffee management practices across a large forested landscape in Ethiopia within Arabica coffee's indigenous distribution, using interviews in 11 villages and field surveys and interviews at 78 coffee sites in the forest. There was a gradient in coffee density (higher), liana cover (lower), and canopy cover (lower) from sites with high management intensity to sites without management. Recently, management intensity has increased in the forest edges. Interviews suggest that substantial areas of currently unmanaged coffee forests are a legacy of reforestation of abandoned (semi‐) open landscapes in the late 19th century. Despite a dynamic history of coffee cultivation across these areas, the conservation of forest biodiversity, including unmanaged populations of genetically diverse Arabica coffee, should be a priority, given the few such remaining areas in Ethiopia and elsewhere in the world. [ABSTRACT FROM AUTHOR]

Background: The study aimed at documenting the indigenous and local knowledge and use of traditional medicinal plants for treating human and livestock ailments in Dawuro Zone of Ethiopia. Methods: A survey was conducted among traditional healers and native administrators through discussion, interviews, and field observations. The snowball sampling technique was used to select 384 traditional healers in purposefully selected 50 villages spanning seven districts for face-to-face individual interviews. The chi-square test was applied to establish associations between traditional healers' demographics, the distance between the village site and the nearest natural forest and a health center, and SPSS V.20 software was used for the analysis. Results: The traditional healers of the study area reported the use of 274 traditional medicinal plant species belonging to 217 genera and 82 families. Asteraceae (11.68%), Fabaceae (9.49%), and Lamiaceae (9.12%) were the foremost frequently used families. Herb species (54.8%) and leaves (65%) were predominantly sourced from the wild environment. The quantity of medicinal plants used (x2 = 278.368, df = 20, P = 0.000) and years of (experience in) traditional healing using herbs (x2 = 76.358, df = 10, P = 0.000) varied with distance from the natural forests. The service charge for healing had strong positive association (x2 = 24.349, df = 5, P = 0.000) with healer's age (x2 = 309.119, df = 184, P = 0.000) and educational level (x2 = 851.230, df = 598, P = 0.000) with distance of traditional healer's residence from the medical institution. The agricultural activities, urbanization, low or no charge for the healing service, the secrecy and oral transfer of the knowledge, and the demand for medicinal and other multiple purposes species were some of the factors threatening the resource and the associated knowledge as well as the service in the study area. Conclusion: There are diversified traditional medicinal plants applied for healthcare of the community and domestic animals of the study area. The source of remedies mostly depends on herbs of natural forests, and the leaf was the most frequently used plant part. Developing conservation intervention and sustainable systems of utilization is needed for multipurpose medicinal plants. Finally, integrating with modern system and formalizing, legalizing, and capacitating the traditional medicine practitioners are needed for access of primary healthcare systems to rural communities. [ABSTRACT FROM AUTHOR]

Recent advances in the application of spectral bands from satellite observations and machine learning algorithms (MLA) in the Google Earth Engine (GEE) cloud-computing platform have been demonstrated to enhance the accuracy of mapping forest resources. This study presents a novel method for mapping the natural distribution of highland bamboo (Oldeania alpina) using spectral bands and three machine learning algorithms, namely random forest, gradient tree boosting, and classification and regression tree. First, spectral bands, vegetation indices and textural features including contrast, entropy and inverse difference moment were derived from the Sentinel-2 elevation data. Second, observations were categorized as the dry season (December-February), short rainy season (March-May), main (long) rainy season (June-August), wet season (September-November) and annual composite. Third, the machine learning algorithms were tested using 1882 ground control points collected from field and high spatial resolution images. Finally, the best-performing machine learning algorithm was used to classify and map bamboo forests. The five land cover categories identified were bamboo stands, natural forest, other vegetation, non-vegetated areas and water bodies. The result shows that the random forest classifier is a robust algorithm with an overall accuracy of 94% considering all the annual composite's spectral, vegetation and textural variables. The highland bamboo coverage (91 km2) in the Andracha district provided valuable insights. Bamboo stands were mostly distributed in the southern and southeastern parts of the district. Here, we show that image compositing and multiple input parameters using machine learning techniques can overcome challenges facing land cover classification, which can hinder accurate mapping of Afromontane forests. We conclude that the incorporation of vegetation indices and textural features in land cover classification increases accuracy of mapping natural highland bamboo coverage and distribution. The application of this new method is a promising prospect not only in Ethiopia but also in Afromontane forests elsewhere in Africa. [ABSTRACT FROM AUTHOR]

Despite the fact that the vegetation pattern and history of the Bale Mountains in Ethiopia were reconstructed using pollen, little is known about the former extent of Erica species. The main objective of the present study is to identify unambiguous chemical proxies from plant-derived phenolic compounds to characterize Erica and other keystone species. Mild alkaline CuO oxidation has been used to extract sixteen phenolic compounds. After removal of undesired impurities, individual phenols were separated by gas chromatography and were detected by mass spectrometry. While conventional phenol ratios such as syringyl vs. vanillyl and cinnamyl vs. vanillyl and hierarchical cluster analysis of phenols failed for unambiguous Erica identification, the relative abundance of coumaryl phenols (>0.20) and benzoic acids (0.05—0.12) can be used as a proxy to distinguish Erica from other plant species. Moreover, a Random Forest decision tree based on syringyl phenols, benzoic acids (>0.06), coumaryl phenols (<0.21), hydroxybenzoic acids, and vanillyl phenols (>0.3) could be established for unambiguous Erica identification. In conclusion, serious caution should be given before interpreting this calibration study in paleovegetation reconstruction in respect of degradation and underground inputs of soil organic matter. [ABSTRACT FROM AUTHOR]