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Increased concentration of atmospheric nitrous oxide (N2O), a potent greenhouse gas (GHG), is of great concern due to its impact on ozone layer depletion leading to climate change. Ozone layer depletion allows penetration of ultraviolet radiations, which are hazardous to human health. Climate change culminates in reduced food productivity. Limited empirical studies have been conducted in Sub-Saharan Africa (SSA) to quantify and understand the dynamics of soil N2O fluxes from smallholder cropping systems. The available literature on soil N2O fluxes in SSA is limited; hence, there is a pressing need to consolidate it to ease mitigation targeting and policy formulation initiatives. We reviewed the state of N2O emissions from selected cropping systems, drivers that significantly influence N2O emissions, and probable soil N2O emissions mitigation options from 30 studies in SSA cropping systems have been elucidated here. The review outcome indicates that coffee, tea, maize, and vegetables emit N2O ranging from 1 to 1.9, 0.4 to 3.9, 0.1 to 4.26, and 48 to 113.4 kg N2O-N ha-1 yr−1, respectively. The yield-scaled and N2O emissions factors ranged between 0.08 and 67 g N2O-N kg−1 and 0.01 and 4.1%, respectively, across cropping systems. Soil characteristics, farm management practices, and climatic and environmental conditions were significant drivers influencing N2O emissions across SSA cropping systems. We found that site-specific soil N2O emissions mitigation measures are required due to high variations in N2O drivers across SSA. We conclude that appropriate fertilizer and organic input management combined with improved soil management practices are potential approaches in N2O emissions mitigation in SSA. We recommend that (i) while formulating soil N2O emissions mitigation approaches, in SSA, policymakers should consider site-specific targeting approaches, and (ii) more empirical studies need to be conducted in diverse agroecological zones of SSA to qualify various mitigation options on N2O emissions, yield-scaled N2O emissions, and N2O emission factors which are essential in improving national and regional GHG inventories.

Aims: To identify the most appropriate drought indices for the identification and monitoring of historical meteorological and agricultural drought incidences and to explore the spatial characteristics of these droughts. Study design: GIS-based empirical research design. Place and Duration of Study: Upper Tana River Watershed, Kenya drought analysis covering a period of 1981 to 2013. Methodology: National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) provided raster maps for Normalized Difference Vegetation Index (NDVI) agricultural drought index, while GeoClim databased through Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) was used for retrieval of raster maps for Standardized Precipitation Index (SPI) meteorological drought index. ArcGIS version 10.3.1 facilitated image enhancement and correction for better visualization and interpretation. Results: Agricultural drought years were in 1983, 1987, 1993, 1996, 2000, 2004, 2005, 2008, and 2009 while meteorological drought years were in 1983, 1984, 1992, 1996, 1999, 2002, 2003, and 2011. Conclusion: Meteorological drought triggered events of agricultural drought. Both droughts showed a widespread pattern and were found to manifest at relatively same intervals during the study period.

Farmer adoption of soil technologies has been commonly explored in the literature using binary models, which significantly simplifies the multi-dimensional nature of technology adoption by farmers. Therefore, it is necessary to fill this gap to improve soil technology adoption models to enhance small-scale farmers' soil fertility management practices. We investigated patterns of multiple soil technology adoption using multivariate analysis and regression modeling in Central Kenya. We used a cross-sectional survey design to sample 300 small-scale farmers in Tharaka-Nithi County and employed a multi-stage sampling design. We found that soil nutrient applications and soil fertility management patterns were linked to crop enterprises, driven by socioeconomic farm characteristics. Our findings showed that farmers applied higher N inputs and soil fertility management technologies on crops with high economic and staple use-values. Farmers in high potential agro-ecozones and those with higher incomes and TLU (Tropical Livestock Units) intensity applied higher fertilizer N intensities than farmers with lower incomes and TLU intensity. Farmers in high potential agro-ecozones applied higher fertilizer and manure rates than their counterparts in low potential agro-ecozones of Tharaka-Nithi County. Farm size was inversely related to nitrogen fertilizer application intensity, while farmers had a lower propensity to restore fields undergoing degradation. We obtained five significant sets of soil fertility management technologies that farmers practiced due to the complementary nature of their benefits. We found that farmer perceptions of soil fertility, income distribution, site, education qualifications, credit access, labor availability, and access to extension services influenced their technology adoption patterns. We recommend that farmer sensitization about the fertility of their soils is needed to enhance soil fertility management strategies in small-scale farming systems.

Climate variability in recent decades has intensified in the SSA region, which makes it imperative to explore adequate adaptation and mitigation strategies to offset its current and future adverse impacts. Farmers' perception of climate variability can significantly influence their coping, mitigation, and adaptation potential. This study assessed farmers' perceptions of indicators and consequences of climate variability and explored factors influencing their perception of climate variability and adoption of climate coping strategies. A cross-sectional survey design was used to sample 300 farmers in the Central Highlands of Kenya. Binary logistic regression models were used to determine factors that influenced the perception of climate variability, adaptation, and mitigation strategies based on three predictor sets, including socioeconomic, institutional, and environmental dimensions. Three climate adaptation and mitigation strategy groups adopted by farmers, including crop adjustment, nutrient management, and soil and water management practices, were subjected to binary logistic regression models. The core determinants of farmers' perception of climate variability included tropical livestock unit (TLU, p = 0.008), access to agricultural training (p = 0.022), change in agricultural production (p = 0.005), change in forest cover (p = 0.014), soil fertility status (p = 0.039), and perceptions of soil erosion (p = 0.001). Most farmers reported changes in all climatic indicators during the decade preceding the survey, including increasing temperature (80%), reduced precipitation (78%), and declining season lengths (76%). There were significant relationships between climate variability perceptions and coping strategies, with the soil and water management set showing stronger links with climate perceptions compared to crop adjustment and nutrient management strategies. Critical mitigation and adaptation strategies to cope with climate variability implemented by farmers included the use of fertilizer and manure in combination (71%), terracing (66%), and crop rotation (60%). Farmers' perceptions significantly determined the adoption of climate-smart agriculture technologies, and environmental determinants strongly influenced climate variability coping strategies. Therefore, while formulating climate sustainability-related policies, farmers' perceptions should be considered.

Most sub-Saharan Africa smallholder farming systems are highly heterogeneous. Direct quantification of greenhouse gas emissions from these farming systems is hampered by diversity at farm-level. Each farm contributes differently to greenhouse gas (GHG) emissions and consequently GHG inventories. Typologies can be used as a mechanism of addressing farming systems’ heterogeneity by grouping them into specific farm types. With the GHG quantification simplification initiatives in mind, we developed smallholder farm typologies based on soil fertility inputs. We assessed nitrogen application rate, soil fertility management technologies and the socio-economic factors diversity among the farm typologies in the central highlands of Kenya. We used data from a cross-sectional household survey with a sample size of 300 smallholder farmers. We characterized the farm types using principal component analysis (PCA). To develop farm typologies, we subjected the PCA-derived typologies related factors to cluster analysis (CA). The results showed six farm types: Type 1, comprising cash crop and hybrid cattle farmers; Type 2, comprising food crop farmers; Type 3, composed of coffee-maize farmers; Type 4, comprising millet-livestock farmers; Type 5, comprising highly diversified farmers, and Type 6, comprising tobacco farmers. Land size owned, total tropical livestock unit, the proportion of land and nitrogen applied to different cropping systems were significant in the construction of farm typologies. Univariate analysis showed the household head's level of education, hired labour, group membership, access to extension services, and proportion of income from cropping activities as critical factors influencing farm typologies in the study area. This study demonstrates the importance of smallholder farm typologies in identifying greenhouse gas emissions hotspots, designing quantification experiment and policy framing. We concluded that policies and intervention measures targeting climate-smart agriculture at smallholder farms should consider not only farm-level soil fertility management technologies but also socio-economic characteristics that influence their adoption.

Monitoring and assessment of drought is key to modelling, impact assessment, mitigation and prediction of occurrence. The Upper Tana River watershed hosts two of Kenya's main water towers, Mt. Kenya and Aberdare Ranges, and is increasingly under threat from reduced water levels in the river basins due to unsustainable anthropogenic activities. The occurrence of drought in the region often exacerbates the impact of such activities on the natural resource-base. The study evaluated temporal and spatial characteristics of meteorological drought in Upper Tana Watershed using remotely sensed data from 1981 to 2018. Climate Hazard Group InfraRed Precipitation with Station (CHIRPS) and Modern-Era Retro-Analysis for Research and Applications-Assimilation Model (MERRA) products provided precipitation and temperature data via Google Earth Engine platform. GeoClim was used in the retrieval of Standardised Precipitation Index (SPI), while Standardised Precipitation and Evapotranspiration Index (SPEI) data were downloaded from SPEI Global Drought Monitor. Values for these datasets were plotted against time to facilitate temporal analysis of the drought. Spatially, the most intense meteorological drought period was from 2007 to 2009 in that the years were hit by severe drought for three consecutive years that covered the entire watershed. Temporally, drought incidences were observed in 1982, 1989, 1994, 2000, 2006, and 2011 and 2017. Both SPI and SPEI indices showed similar drought years. Drought mitigation measures should be implemented across the watershed. The findings provide insights that can be used by natural resource management practitioners in; drought forecasting, early warning systems, and in planning and management of water resources within the watershed. We recommend characterisation of the other types of droughts, agricultural and socio-economic droughts, for a holistic understanding of their spatial-temporal manifestations and the impact on the livelihoods of the watershed. Keywords: Meteorological drought, SPI, SPEI, Time-series, Remote sensing, Geospatial tools

The prevailing low food production in sub-Saharan Africa is an issue of great concern especially since Africa south of the Sahara is the only remaining region of the world where per capita food production has remained stagnant. This chapter reviews long-term experiments in Africa in the context of shifting paradigms related to tropical soil fertility management from first external input paradigm right through to the current Integrated Soil Fertility Management (ISFM) approach, which is a culmination of the participatory methods developed along the paradigm shift. Long term experiments (LTE) are an important source of evidence for soil fertility decline and provide crucial datasets for the development of sustainable management practices for tropical land-use systems and the amelioration of global climatic and environmental change impacts. A survey was undertaken to identify some ongoing long-term trials distributed across east, south and western Africa and in different agro-ecological zones. A long-term Experiment was defined as that extending over a period of over 5 years and more. Results from these trials are discussed in detail. Inference has been drawn from these findings and includes the following key findings: a) All long term trials showed yield decline, often with a relatively rapid fall to a low level equilibrium; b) At all sites, there were positive yield responses to one or more nutrients added as mineral fertilizers, which were consistent for the duration of the experiments highlighting the effectiveness of mine­ral fertilizers in increasing yield in arable farming systems in Africa; c) Soil organic matter (SOM) also declines significantly when land is cultivated; d) Prolonged treatments using only inputs of organic matter also showed yield declines, although the positive impact were sustained longer than for inorganic fertilizers alone in most cases; e) Rotational treatments, including sequences with legume crops and fallow periods had lower yield declines than monocultures; f) The best results invariably were those treatments that combined inorganic and organic inputs.