Spatio-temporal dynamics of pastoral grazing resources influences the pastoral production system. Obtaining timely and reliable information on the status of these resources will support planning and early response to climatic variability. This study in Karamoja pastoral sub-region of Uganda identified herbaceous and woody forage species in different grazing land cover types, quantified forage in different grazing land covers, analyzed long-term land use/cover change (from 1986 to 2013) and determined the relationship between Normalized Difference Vegetation Index (NDVI) and herbaceous biomass. Results showed that the sub-region has over 30 grass species that provide forage. During the wet season, woodlands, grasslands and thickets and shrublands recorded a wet weight of 1,342.5 ± 104.5 kg/ha, 857.5 ± 29.4 kg/ha and 501 ± 43.9 kg/ha, respectively. In the dry season, 542.5 ± 57.6 kg/ha, 273 ± 6.4 kg/ha and 140 ± 9.2 kg/ha were realized in the woodlands, grasslands and thickets and shrublands, respectively. However, in the transitionary season, 276, 512.5 and 529.2 kg/ha were obtained in the woodlands, grasslands and thickets and shrublands accordingly. Similar trends were observed in dry matter biomass in the respective land cover type. Seasonality, land cover type and location accounted for the variations in the observed forage quantities. Analysis of land cover and land use change revealed a tenfold increase in croplands in the last 13 years. The expansion of crop cultivation is attributed to interventions by the Government of Uganda and development partners to promote food security in the sub-region. Heightened bushland encroachment was similarly observed in the last 13 years. The study also found a significant positive relationship between NDVI and herbaceous biomass, indicating that remote sensing offers reliable resource assessment and monitoring options for informing planning and interventions in semi-arid areas.

Climate-smart agriculture (CSA) is one of the innovative approaches for sustainably increasing the agricultural productivity, improving livelihoods and incomes of farmers, while at the same time improving resilience and contributing to climate change mitigation. In spite of the fact that there is neither explicit policy nor practices branded as CSA in Democratic Republic of Congo (DRC), farmers are utilizing an array of farming practices whose attributes meet the CSA criteria. However, the intensity, distribution, efficiency, and dynamics of use as well as the sources of these technologies are not sufficiently documented. Therefore, this review paper provides a comprehensive evidence of CSA-associated farming practices in DRC, public and private efforts to promote CSA practices, and the associated benefits accruing from the practices as deployed by farmers in the DRC. We find evidence of progress among farming communities in the use of practices that can be classified as CSA. Communities using these practices are building on the traditional knowledge systems and adaptation of introduced technologies to suit the local conditions. Reported returns on use of these practices are promising, pointing to their potential continued use into the future. While progressive returns on investment are reported, they are relatively lower than those reported from other areas in sub-Saharan Africa deploying similar approaches. We recommend for strategic support for capacity building at various levels, including public institutions for policy development and guidance, extension and community level to support uptake of technologies and higher education institutions for mainstreaming CSA into curricula and training a generation of CSA sensitive human resources.

Long-term trend analysis at local scale for rainfall and temperature is critical for detecting climate change patterns. This study analysed historical (1980–2009), near future (2010–2039), mid- (1940–2069) and end-century (2070–2099) rainfall and temperature over Karamoja sub-region. The Modern Era-Retrospective Analysis for Research and Applications (MERRA) daily climate data provided by the Agricultural Model Inter-comparison and Improvement Project (AgMIP) was used. The AgMIP delta method analysis protocol was used for an ensemble of 20 models under two representative concentration pathways (RCPs 4.5 and 8.5). Historical mean rainfall was 920.1 ± 118.9 mm and minimum, maximum and mean temperature were 16.8 ± 0.5 °C, 30.6 ± 0.4 °C and 32.0 ± 0.7 °C, respectively. Minimum temperature over the historical period significantly rose between 2000 and 2008. Near future rainfall varied by scenario with 1012.9 ± 146.3 mm and 997.5 ± 144.7 mm for RCP4.5 and RCP8.5 respectively; with a sharp rise predicted in 2017. In the mid-century, mean annual rainfall will be 1084.7 ± 137.4 mm and 1205.5 ± 164.9 mm under RCP4.5 and RCP8.5 respectively. The districts of Kaabong and Kotido are projected to experience low rainfall total under RCP4.5 (mid-century) and RCP8.5 (end-century). The minimum temperature is projected to increase by 1.8 °C (RCP4.5) and 2.1 °C (RCP8.5) in mid-century, and by 2.2 °C (RCP4.5) and 4.0 °C (RCP8.5) in end-century.

Concerns have been raised on the effectiveness and sustainability of Soil and Water Conservation (SWC) practices as adaptation options to climate change and high intra– and inter–annual rainfall variabilities in eastern Democratic Republic of Congo (DRC). This study was conducted in the Ruzizi Plain, a dryland area, to assess the performance of maize (Zea mays L.) under two Representative Concentration Pathways (RCP 4.5 and 8.5) and two SWC practices (tied ridges and conventional tillage). The AgMIP’s Regional Integrated Assessment (RIA) approach was used to simulate Water Use Efficiency (WUE) under the Cropping System Model–Crop Environment Resource Synthesis (CSM–CERES–Maize) of the Decision Support System for Agro–technology Transfer (DSSAT). The model was calibrated using experimental data from nine cropping seasons (2011–2018) and 100 farms. The model sensitivity was assessed as a function of temperature, water, and SWC practices for the same environments. Initial conditions of crop management practices were used as input data for CSM–CERES–Maize. Current climate data were extracted from AgMERRA datasets corrected with local data for the period of 1980 to 2021. Future climate projections (2022–2099) were obtained after down−scaling the data from the 29 General Circulation Models (GCMS) of Coupled Model Intercomparison Project 5 (CMIP5) and subsetted to five GCMs based on climate regimes. GCMS results were a strong indicator that climate change in this DRC dryland will result in an increase in average annual temperatures for both RCP 4.5 and 8.5, with the highest increase (3.05 °C) under hot/dry conditions for RCP8.5 and the lowest (1.04 °C) under cool/dry conditions for RCP 4.5. All the models selected for five climate regimes for 2022–2099 showed no change in the rainfall trends for RCP 4.5 (p > 0.05). The models projected yield declines of 5–25%, with less yield losses under tied ridges as an adaptation practice. The use of efficient SWC practices could therefore be a promising strategy in reducing potential losses from climate change in drylands of eastern DRC.

Background: COVID-19 continues to wreak havoc in different countries across the world, claiming thousands of lives, increasing morbidity and disrupting lifestyles. The global scientific community is in urgent need of relevant evidence, to understand the challenges and knowledge gaps, as well as the opportunities to contain the spread of the virus. Considering the unique socio-economic, demographic, political, ecological and climatic contexts in Africa, the responses which may prove to be successful in other regions may not be appropriate on the continent. This paper aims to provide insight for scientists, policy makers and international agencies to contain the virus and to mitigate its impact at all levels. Methods: The Affiliates of the African Academy of Sciences (AAS), came together to synthesize the current evidence, identify the challenges and opportunities to enhance the understanding of the disease. We assess the potential impact of this pandemic and the unique challenges of the disease on African nations. We examine the state of Africa’s preparedness and make recommendations for steps needed to win the war against this pandemic and combat potential resurgence. Results: We identified gaps and opportunities among cross-cutting issues which is recommended to be addressed or harnessed in this pandemic. Factors such as the nature of the virus and the opportunities for drug targeting, point of care diagnostics, health surveillance systems, food security, mental health, xenophobia and gender-based violence, shelter for the homeless, water and sanitation, telecommunications challenges, domestic regional coordination and financing. Conclusion: Based on our synthesis of the current evidence, while there are plans for preparedness in several African countries, there are significant limitations. Multi-sectoral efforts from the science, education, medical, technological, communication, business and industry sectors as well as local communities is required in order to win this fight.

Land degradation and discontinuation of ecosystem services (ES) are a common phenomenon that causes socio-economic and environmental problems in Ethiopia. However, a dearth of information is known about how ES are changing from the past to the future with regard to land use land cover (LULC) changes. This study aimed at estimating the values of ES based on the past and future LULC changes in central Ethiopia. Maximum likelihood classifier and cellular automata-artificial neuron network (CA-ANN) models that integrate the module for land use change evaluation (MOLUSE) were used to classify and predict LULC. The CA-ANN model learning and validation was employed to predict LULC of 2031 and 2051. Following LULC change detection and prediction, the total ES values were estimated using the benefit transfer method. Results revealed that forests, wetlands, grazing lands, shrub-bush-woodlands, and water bodies were reduced by 9755 ha (37%), 4092 ha (38.4%), 21,263 ha (81%), 63,161 ha (25.7%), and 905 ha (1%), respectively, between 1986 and 2021. Similarly, forests, wetlands, grazing lands, shrub-bush lands, and water bodies will experience a decline of 1.5%, 0.5%, 2.6%, 19.6%, and 0.1%, respectively. Meanwhile, cultivated lands, bare-lands, and built-up areas will experience an increase between 1986 and 2051. The estimated total ES values were reduced by US$58.3 and 85.4 million in the period 1986–2021 and 1986–2051. Food production and biological control value increased while 15 other ES decreased throughout the study periods. Proper land use policy with strategic actions, including enforcement laws for natural ecosystems protection, afforestation, ecosystems restoration, and conservation practices, are recommended to be undertaken to enhance multiple ES provision.