Gender assessment for women’s economic empowerment in Doyogena climate-smart landscape in Southern Ethiopia

Agricultural production systems in Ethiopia depend on seasonal rains, which are increasingly becoming variable, affecting the livelihoods of many farmers. Women in rural areas are more vulnerable to climate change and climaterelated risks due to existing social norms and gender inequalities (limited ownership and control over productive assets/resources, decision-making power, access to information, extension services, market etc.) and multidimensional social factors. These gender inequalities affect the ability of women to adapt to climate change. On the other hand, women have unique knowledge and skills that can help create effective and sustainable responses to climate change (Habtezion 2013)

Building soil carbon stocks to enhance adaptation and mitigate climate change in climate-smart landscapes, Southern Ethiopia

Climate change is a major challenge, particularly for Ethiopia’s rural populations who depend on rainfall for subsistence farming and are therefore more vulnerable to climate-related risks. Agriculture accounts for more than 40% of Ethiopia’s gross domestic product (GDP) (UNDP, 2015), and contributes significantly to greenhouse gas (GHG) emissions (FDRE, 2015). In Ethiopia, annual GHG emissions were estimated to be 150 Mt CO2e in 2010, with 50% of emissions coming from agriculture, and another 37% from forestry sectors — mainly agriculture related deforestation (FAO, 2016). Furthermore, the capacity of Ethiopia’s agricultural, forest, and grassland sectors to act as carbon sinks is decreasing rapidly due to unsustainable agricultural practices. Since 2011, the federal government of Ethiopia has embarked on implementing the Climate Resilient Green Economy (CRGE) strategy. CRGE has ambitious commitments in its Nationally Determined Contribution (NDC) submitted to the United Nations Framework Convention on Climate Change (UNFCCC), to "climate-proof" Ethiopia’s Growth and Transformation Plan (GTP) by curbing its GHG emissions by more than half by 2030, while also building resilience against climate risks and future climate change. As set forth in the second GTP, reaching this goal will require boosting agricultural productivity by introducing climate-smart technologies and practices that include integrated watershed management, conservation agriculture, as well as nutrient and crop management across agroecosystems and landscapes with the potential to reduce GHG emissions by 40 Mt CO2e in 2030 (CRGE, 2011)

The effect of climate-smart agriculture on soil fertility, crop yield, and soil carbon in Southern Ethiopia

It is critical to develop technologies that simultaneously improve agricultural production,offset impacts of climate change, and ensure food security in a changing climate. Within this context,considerable attention has been given to climate-smart agricultural practices (CSA). This study wasconducted to investigate the effects of integrating different CSA practices on crop production, soilfertility, and carbon sequestration after being practiced continuously for up to 10 years. The CSApractices include use of soil and water conservation (SWC) structures combined with biologicalmeasures, hedgerow planting, crop residue management, grazing management, crop rotation, andperennial crop-based agroforestry systems. The landscapes with CSA interventions were comparedto farmers’ business-as-usual practices (i.e., control). Wheat (Triticumsp.) yield was quantified from245 households.The results demonstrated that yield was 30–45% higher under CSA practices than thecontrol (p< 0.05). The total carbon stored at a soil depth of 1 m was three- to seven-fold higher underCSA landscapes than the control. CSA interventions slightly increased the soil pH and exhibited2.2–2.6 and 1.7–2.7 times more total nitrogen and plant-available phosphorus content, respectively,than the control. The time series Normalized Difference Water Index (NDWI) revealed higher soilmoisture content under CSA. The findings illustrated the substantial opportunity of integrating CSApractices to build climate change resilience of resource-poor farmers through improving crop yield,reducing nutrient depletion, and mitigating GHG emissions through soil carbon sequestratiom

Legume CHOICE - a participatory tool to fit multi-purpose legumes to appropriate niches in mixed crop-livestock farming systems

German Federal Ministry for Economic Cooperation and DevelopmentDeutsche Gesellschaft für Internationale Zusammenarbei

Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0

Up-to-date digital soil resource information and its comprehensive understanding are crucial to supporting crop production and sustainable agricultural development. Generating such information through conventional approaches consumes time and resources, and is difficult for developing countries. In Ethiopia, the soil resource map that was in use is qualitative, dated (since 1984), and small scaled (1 : 2 M), which limit its practical applicability. Yet, a large legacy soil profile dataset accumulated over time and the emerging machine-learning modeling approaches can help in generating a high-quality quantitative digital soil map that can provide better soil information. Thus, a group of researchers formed a Coalition of the Willing for soil and agronomy data-sharing and collated about 20 000 soil profile data and stored them in a central database. The data were cleaned and harmonized using the latest soil profile data template and 14 681 profile data were prepared for modeling. Random forest was used to develop a continuous quantitative digital map of 18 World Reference Base (WRB) soil groups at 250 m resolution by integrating environmental covariates representing major soil-forming factors. The map was validated by experts through a rigorous process involving senior soil specialists or pedologists checking the map based on purposely selected district-level geographic windows across Ethiopia. The map is expected to be of tremendous value for soil management and other land-based development planning, given its improved spatial resolution and quantitative digital representation.</p

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic