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Field experiment was conducted for two consecutive years (2015 and 2016) in north western Ethiopia to test the effect of Integrated Nutrient Management (INM) on soil nutrient status, nutrient uptake, protein content and yield of chickpea. The experiment comprised of 6 levels of INM treatments (unfertilized, 100% recommended-1 dose of chemical fertilizer (RDF), 6 t compost ha alone or combined with: 75, 50 and 25% RDF). The treatments were arranged in randomized complete block design with three replications. The result showed that application of full recommended dose of chemical fertilizer (RDF) or integrated application of compost along with 25, 50 or 75% RDF appreciably enhanced soil N and P status, seed and biomass yield, protein content and nutrient uptake of chickpea. Compared to the unfertilized treatment, application of 100% RDF alone;-1 combined application of 6 t compost ha along with 75, 50 and 25% RDF improved seed yield by 44, 38, 37.5, and 38% and seed protein content by 63, 61, 69 and 60%, respectively. All INM treatments produced statistically the same yield to that of RDF. Therefore, INM can be recommended as sustainable nutrient management option for production of chickpea by poor small holder farmers who cannot afford direct monetary expenditure in cash for chemical fertilizers and to maintain the soil health

Teff (Eragrostis tef (Zucc.) Trotter) is a staple, ancient food crop in Ethiopia. Its growth is affected by climate change, so it is essential to understand climatic effects on its habitat suitability in order to design countermeasures to ensure food security. Based on the four Representative Concentration Pathway emission scenarios (i.e., RCP2.6, RCP4.5, RCP6.0 and RCP8.5) set by the Intergovernmental Panel on Climate Change (IPCC), we predicted the potential distribution of teff under current and future scenarios using a maximum entropy model (Maxent). Eleven variables were selected out of 19, according to correlation analysis combined with their contribution rates to the distribution. Simulated accuracy results validated by the area under the curve (AUC) had strong predictability with values of 0.83–0.85 for current and RCP scenarios. Our results demonstrated that mean temperature in the coldest season, precipitation seasonality, precipitation in the cold season and slope are the dominant factors driving potential teff distribution. Proportions of suitable teff area, relative to the total study area were 58% in current climate condition, 58.8% in RCP2.6, 57.6% in RCP4.5, 59.2% in RCP6.0, and 57.4% in RCP8.5, respectively. We found that warmer conditions are correlated with decreased land suitability. As expected, bioclimatic variables related to temperature and precipitation were the best predictors for teff suitability. Additionally, there were geographic shifts in land suitability, which need to be accounted for when assessing overall susceptibility to climate change. The ability to adapt to climate change will be critical for Ethiopia’s agricultural strategy and food security. A robust climate model is necessary for developing primary adaptive strategies and policy to minimize the harmful impact of climate change on teff.