Morphometric Analysis and Prioritization of Watersheds for Soil Erosion Management in Upper Gibe Catchment

As morphometric investigation is connected to prioritization of watershed, morphometric analysis has got a significance role in light of soil and water conservation. In this study, an endeavour for the examination of point by point morphometric analyses of sub-basins was accomplished through the measurement of linear and shape parameters by using ArcGIS-9.3 software. Specifically, linear and shape morphometric parameters like stream length, stream order, drainage density, stream frequency, bifurcation ratio, Length of overland flow, basin perimeter, form factor, compactness coefficient, elongation ratio has been considered. The SRTM DEM (30 x 30 m) is processed for the delineation resulting in 61 sub-basins. The morphometric parameters which affect the soil erodibility are considered to organize the sub-basins and relegate positions on the premise of their association with erodibility to get compound parameter (Cp) esteem. Based on the value of Cp the sub-basin with the lowest Cp value was given the highest priority and then categorized the sub-basins into three classes as high, medium and low in terms of priority. Accordingly, high priority zone comprises 11 sub-basins, medium 19 and low 31 sub-basins. The sub-basins which are falling under high priority were a great deal more defenceless to soil disintegration and ought to be given high need for land preservation measures

Imaging findings and management of paediatric pulmonary hydatidiosis in an Ethiopian Referral Hospital

No Abstrac

Analysis of road traffic crashes in the State of Qatar

Road traffic crashes (RTCs) are globally acknowledged as increasing threat to society, because they can affect many lives when they result in severe injury or fatality. In the State of Qatar RTCs are getting more awareness and attention, aiming to improve the traffic safety in the country. This study is an exploratory research providing different analyses of the crash data for seven consecutive years, ranging from 2010 to 2016, which is obtained from the Traffic Department in the Ministry of Interior for the State of Qatar. The objectives aim to evaluate the trend of RTC rate over time and create understanding of the influencing factors related to RTC frequency. Time series analyses show an increasing trend of RTCs leading to severe injury and a slight decreasing trend for fatal RTCs. Secondly, different RTC severity levels are related to diverse RTC causes. Furthermore, the results revealed that crashes with severe injuries or fatality for drivers as well as pedestrians are found to be significantly affected by seasonal weather variations, with the highest vulnerability in winter and autumn season. This study therefore suggests the implementation of strategies to prioritize the traffic safety of road users during the crash-prone winter and autumn seasons. - 2019, - 2019 Informa UK Limited, trading as Taylor & Francis Group.This publication was made possible by the NPRP award [NPRP 9-360-2-150] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Treatment outcomes of patients with MDR-TB and its determinants at referral hospitals in Ethiopia.

There is limited empirical evidence in Ethiopia on the determinants of treatment outcomes of patients with multidrug-resistant tuberculosis (MDR-TB) who were enrolled to second-line anti-tuberculosis drugs. Thus, this study investigated the determinants of treatment outcomes in patients with MDR-TB at referral hospitals in Ethiopia. Design and methods This study was underpinned by a cross-sectional quantitative research design that guided both data collection and analysis. Data is collected using structured questionnaire and data analyses was performed using the Statistical Package for Social Sciences. Multi-variable logistic regression was used to control for confounders in determining the association between treatment outcomes of patients with MDR-TB and selected predictor variables, such as co-morbidity with MDR-TB and body mass index. Results From the total of 136 patients with MDR-TB included in this study, 31% had some co-morbidity with MDR-TB at baseline, and 64% of the patients had a body mass index of less than 18.5 kg/m2. At 24 months after commencing treatment, 76 (69%), n = 110), of the patients had successfully completed treatment, while 30 (27%) died of the disease. The odds of death was significantly higher among patients with low body mass index (AOR = 2.734, 95% CI: 1.01-7.395; PConclusionThe higher proportion of mortality among patients treated for MDR-TB at Adama and Nekemte Hospitals, central Ethiopia, is attributable to co-morbidities with MDR-TB, including HIV/AIDS and malnutrition. Improving socio-economic and nutritional support and provision of integrated care for MDR-TB and HIV/AIDS is recommended to mitigate the higher level of death among patients treated for MDR-TB

Exploiting genetic variation from unadapted germplasm—An example from improvement of sorghum in Ethiopia

Societal Impact Statement The productivity of sorghum in Ethiopia has been largely limited by rain-fed condi- tions because farmers tend to use local drought-tolerant but low-yielding landraces, as high-yielding and late-maturing landrace cultivars risk failure due to drought. Addressing such issues often requires a far-reaching approach to identify and incorporate new traits into a gene pool, followed by a period of selection to re-establish an overall adaptive phenotype. The sorghum backcross nested association mapping (BC-NAM) population developed in this study increases the genetic diversity available in Ethiopian elite adapted sorghum germplasm, providing new scope to improve food security in a region known for periodic devastating droughts. Summary • As the center of diversity for sorghum, Sorghum bicolor (L.) Moench, elite cultivars selected in Ethiopia are of central importance to sub-Saharan food security. Despite being presumably well adapted to their center of diversity, elite Ethiopian sorghums nonetheless experience constraints to productivity, for example, associ- ated with shifting rainfall patterns associated with climate change. • A sorghum backcross nested association mapping (BC-NAM) population developed by crossing 13 diverse lines preidentified to have various drought resilience mechanisms with an Ethiopian elite cultivar, Teshale, was tested under three rainfed environments in Ethiopia. • Twenty-seven, 15, and 15 quantitative trait loci (QTLs) with predominantly small additive effects were identified for days to flowering, days to maturity, and plant height, respectively. Many associations detected in this study corresponded closely to known or candidate genes or previously mapped QTLs, supporting their validity. • The expectation that genotypes such as Teshale from the center of diversity tend to have a history of strong balancing selection, with novel variations more likely to persist in small marginal populations, was strongly supported in that for these three traits, nearly equal numbers of alleles from the donor lines conferred increases and decreases in phenotype relative to the Teshale allele. Such rich variation provides a foundation for selection to arrive at a new “adaptive peak,” exemplifying the nature of efforts that may be necessary to adapt many crops to new climate extremes

Restoring Rangelands for Nutrition and Health for Humans and Livestock

Drylands cover 40% of the global land area and host 2 billion people, of which 90% live in low- or middleincome countries. Drylands often face severe land degradation, low agricultural productivity, rapid population growth, widespread poverty, and poor health. Governance structures and institutions are often eroded. Livestock-based livelihoods, largely depending on seasonal migration are common. Pastoralist communities and their land are highly vulnerable to climate shocks, while there are also changes in land tenure, insecurity/conflicts and rapid infrastructure development. Drylands Transform is an interdisciplinary research project revolving around the UN Sustainable Development Goals (SDGs). The project aim is to contribute new knowledge to a transformative change and sustainable development of drylands in East Africa to help escape the ongoing negative spiral of land, livestock and livelihood degradation. We investigate the links between land health, livelihoods, human well-being, and land management and governance with several study sites along the Kenya-Uganda border. Through strong stakeholder engagement we will explore challenges and pathways towards a social-ecological transformation in these drylands. The entry point is the urgent need to identify and enhance synergies between food and nutrition security (SDG2), land and ecosystem health (SDG15) and governance and justice (SDG16) for sustainable dryland development, aiming to improve health and equity (SDGs 3 and 5), while minimizing trade-offs between agricultural productivity, natural resources management and climate change. We are using innovative field research approaches focusing on livelihood improvement through rangeland (grazing areas) restoration and governance interventions. We will present results from the initial work to assess land health using the Land Degradation Surveillance Framework and explore the links with human health and well-being through household survey data. We will also show how we will co-develop sustainable dryland management options (e.g., field experiments with fodder grasses and shrubs) with local communities and set-up knowledge sharing hubs

Least concern to endangered: applying climate change projections profoundly influences the extinction risk assessment for wild Arabica coffee

Arabica coffee (Coffea arabica) is a key crop in many tropical countries and globally provides an export value of over US$13 billion per year. Wild Arabica coffee is of fundamental importance for the global coffee sector and of direct importance within Ethiopia, as a source of harvestable income and planting stock. Published studies show that climate change is projected to have a substantial negative influence on the current suitable growing areas for indigenous Arabica in Ethiopia and South Sudan. Here we use all available future projections for the species based on multiple general circulation models (GCMs), emission scenarios and migration scenarios, to predict changes in Extent of Occurrence (EOO), Area of Occupancy (AOO) and population numbers for wild Arabica coffee. Under climate change alone, our results show that population numbers could reduce by 50% or more (with a few models showing over 80%) by 2088. EOO and AOO are projected to decline by around 30% in many cases. Furthermore, present-day models compared to the near future (2038), show a reduction for EOO of over 40% (with a few cases over 50%), although EOO should be treated with caution due to its sensitivity to outlying occurrences. When applying these metrics to extinction risk, we show that the determination of generation length is critical. When applying the International Union for Conservation of Nature’s Red list of Threatened Species (IUCN Red List) criteria, even with a very conservative generation length of 21 years, wild Arabica coffee is assessed as Threatened with extinction (placed in the Endangered category) under a broad range of climate change projections, if no interventions are made. Importantly, if we do not include climate change in our assessment, Arabica coffee is assessed as Least Concern (Non-threatened) when applying the IUCN Red List criteri

Gridded daily 2-m air temperature dataset for Ethiopia derived by debiasing and downscaling ERA5-Land for the period 1981–2010

A gridded maximum and minimum (Tx and Tn) daily temperature dataset derived by spatial downscaling and bias correction of the ERA5-Land (ERA5L) for the period 1981–2010 is presented. Observed daily Tx and Tn at 154 stations in Ethiopia covering record lengths of 5–30 years were used as a reference. The statistics that define the Gaussian distribution (mean and standard deviation) of Tx and Tn from the station observations were interpolated in space to create a monthly climatology and interannual statistics at 0.05° × 0.05° resolution using a hybrid interpolation approach that combines linear regression with topographic and location attributes, and non-Euclidean inverse distance weighting interpolation. The interpolated monthly and interannual statistics were then used to debias the ERA5L Tx and Tn using a quantile mapping approach. Leave-one-out cross-validation showed that the mean absolute errors in the corrected and downscaled daily temperatures are about 0.7 °C for Tx and 1.1 °C for Tn, reducing the statistical biases in the ERA5L Tx and Tn by 68% and 25% respectively. For monthly climatology, 40–64% of the biases were removed for Tx while for Tn the reductions range from 19% to 32%. The correction also improved commonly used indices for extremes like the probability of warm days, cold days, and warm nights, but overestimated the probability of cold nights. The presented open-access Tx and Tn dataset is a substantial improvement over existing gridded temperature datasets for Ethiopia, such as ERA5L and the Climate Hazards Infrared Temperature with Station (CHIRTS), and we suggest it is suitable for a wide range of environmental applications, e.g. in the fields of hydrology, agriculture, and ecology.ISSN:2352-340