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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]

Bamboos provide a number of ecosystem services, including the provision of a permanent carbon (C) sink. The present study was undertaken in the Sheka forest, currently recognized as a UNESCO Biosphere Reserve. The objectives of this study were to: (1) develop species- and site-specific allometric models for biomass estimation and (2) quantify the carbon storage capacity of highland bamboo stands. A total of 12 plots each measuring 10 m x 10 m were established at a distance of 200 m in the forest. 96 culms were harvested for the development of biomass estimation equations. Litter samples were collected in 1 m x 1 m subplots, while soil samples were collected at 0–10, 10–20, 20–40, and 40–60 cm soil depths for determination of soil organic carbon (SOC) contents. The estimated mean DBH, basal area and plant height were 7.0 cm, 53.2 m2 ha−1 and 12.9 m, respectively. The study has established allometric scaling of plant height with stem diameter in highland bamboo. It has also established that the allometric model is superior to commonly used non-linear H-DBH models. Aboveground biomass was estimated at 93 Mg ha−1 with mean C stocks of 43.7 Mg ha−1. The estimated below-ground biomass was 18.6 Mg ha−1 with C stocks of 8.7 Mg ha−1. The C stocks in the litter layer were estimated at 1.57 Mg ha−1. Average soil C storage was estimated at 388.12 Mg ha−1 within the 0–60 cm soil depth. In total, the natural highland bamboo stands store approximately 442.1 Mg C ha−1. The estimated C stocks were comparable with values reported for bamboos in Ethiopia and elsewhere. It is concluded that natural highland bamboo stands play a significant role as carbon sinks. The insights gained in this study are expected to be applicable to Afromontane ecosystems where highland bamboo occurs in Africa. Highland bamboo (Oldeania alpina) is a conspicuous element of Afromontane vegetation in Africa We developed models for estimating biomass carbon (C) stocks in highland bamboo stands We estimated biomass C stock of highland bamboo stands at 52.5 Mg ha−1 and litter C at 1.6 Mg ha−1 Soil organic C stock of highland bamboo stands was 388.1 Mg ha−1 Total system C in highland bamboo stands was over 442 Mg ha−1 [ABSTRACT FROM AUTHOR]

East Africa is an underrepresented region in respect of monitoring the stable isotopic composition of precipitation (δ18Oprec and δ2Hprec). In 2017, we collected precipitation samples from ten weather stations located along an altitudinal transect ranging from 1304 to 4375 m a.s.l. The δ18Oprec and δ2Hprec values varied from –8.7 to +3.7 ‰ and –38 to +29 ‰, respectively. The local meteoric water line is characterised by a lower slope, a higher intercept and more positive d-excess values (δ2H = 5.3 ± 0.2 * δ18O + 14.9 ± 0.9) compared to the global meteoric water line. Both altitude and amount of precipitation clearly correlate with our isotope data. However, the δ18Oprec and δ2Hprec values show at the same time a seasonal pattern reflecting rainy versus dry season. More enriched isotope values prevailed shortly after the end of the dry season; more depleted isotope values coincided with high precipitation amounts recorded in May, August and September. Moreover, HYSPLIT trajectories reveal that during the dry season water vapour originates primarily from the Arabian Sea, whereas during the wet season it originates primarily from the Southern Indian Ocean. These findings challenge the traditional amount effect interpretation of paleoclimate isotope records from East Africa and rather point to a previously underestimated source effect. [ABSTRACT FROM AUTHOR]

One hundred and thirty-nine taxa of mosses are reported from the montane forest zone of southwest Ethiopia. Of these, 53 taxa are new country records andMeteoriopsis reclinata(Müll.Hal.) M.Fleisch.exBroth. is, in addition, new to Africa. Most of the new records are of species also found in Uganda, Kenya or Tanzania, but there are some surprises, such asFabronia perciliataMüll.Hal. with the closest location in South Africa and Namibia,Entodontella cameruniaeBroth. previously known only from West Africa andBryomaltaea obtusifolia(Hook.) Goffinet, otherwise reported only from the Democratic Republic of the Congo. We list all taxa and give a short account of their frequency and in which habitat and on which substrate they grow. That such a large proportion of the species are new to the country suggests that Ethiopia is bryologically very under-explored, and that further exploration will reveal many additional species. In particular, the remnant forests of southwest Ethiopia are likely to be of great importance as bryophyte hotspots. [ABSTRACT FROM PUBLISHER]

Ethiopia has diverse topographic features and climatic conditions with a diverse flora. The liverwort flora of southwest Ethiopia is practically unknown, despite a favourable climate and the occurrence of suitable ecosystems such as montane rainforests. During an ecological study of diversity patterns of bryophytes and vascular plants in relation to land use, we recorded many bryophyte species. In this paper we report the finding of 89 species of liverworts, and give short ecological notes and describe the distribution (locally and in Africa) for each species. Of these, 51 species are newly reported from Ethiopia. It is thus obvious that Ethiopia is considerably richer in liverworts than might be expected from previous checklists. [ABSTRACT FROM AUTHOR]