This study investigated the effect of resilience components and indicators on households' welfare distribution in the study area, using the data collected from households' surveys. Respondents were drawn from the study area through the multistage random sampling technique; while the data obtained from 363 sampled respondents were analyzed and described through the use of descriptive statistics (frequency distribution, percentages, and cross tabulation technique). The resilience tool of the Food and Agriculture Organization of the United Nations (UN-FAO) was adopted to measure the resilience pillars through their corresponding components/indicators. Similarly, a quantile regression econometric model was used to estimate the effect of the resilience pillars vis-à-vis the indicators on welfare distribution in the study area. The results indicated that the majority of the respondents fall within the low quintiles of households' welfare, while women were found to be disproportionately vulnerable to shocks, as many of them fall within the low welfare class. The resilience pillars/components were found to have varying degrees of significance and direction of movement with quintiles of households' welfare status. This was observed across all the quintiles (0.1, 0.25, 0.50, 0.75, and 0.90; that is, 10, 25, 50, 75, and 90th quintiles), respectively. The study recommended proper and transparent implementation of functional social protection programs to reduce households' vulnerability to shock and stressors. There is also the need for investments to be made across all pillars and indicators of resilience to build sustained households' resilience capacity and welfare status.

Recently, many developing nations are disproportionately experiencing the impact of shocks and stressors compared to the rest of the world due to increasing inadequate capability and capacity to withstand the shocks. In particular, farmers and farming households are faced with diverse repeated and unanticipated shocks, which may be socio-economic, ecological and/or environmental in nature. All these shocks become unbearable and worsen in terms of food insecurity. The welfare costs associated with the shocks are significant, attracting humanitarian and development policy experts’ attention to developing suitable interventions to build a resilient food system and society. Consequently, this study analyzed the correlates of farmers’ resilience to food insecurity in South-West Nigeria. Drawing on the data collected from 472 smallholder farmers randomly sampled, descriptive statistics, the United States Department of Agriculture (USDA)’s food insecurity experience scale approach, composite score technique, principal component analysis (PCA) and Structural equation modeling (SEM) were used to analyze the data. The findings indicated that more than half (55.3%) of the respondents were inadequate in almost all the resilience indicators and components, had low resilience capacity, and were vulnerable to food shocks and food insecurity. In comparison, only 7.8% have a high resilience capacity to be a buffer against food shocks. 54% of the respondents fall into a high food insecurity category, while only 1.9% fall into a very-low food insecurity continuum. The SEM analysis also revealed that social safety net (p<0.01), climate extreme events (p<0.01), access to essential services (p<0.01), presence of enabling institutional environment (p<0.01), and technical level (p<0.05) made direct impacts on the farmers’ food insecurity status. Conversely, possession of assets (p<0.01), and social capital/neighborhood effect (p<0.1) had inverse impacts on the farmers’ food insecurity status. The study recommended transparently implementing a social protection program to assist the farmer in building buffers against shocks. There is also a greater need for sustained investments across the resilience pillars and indicators to build farmers’ resilience capacity to food insecurity and other shocks.

Background: Practicing the unsustainable system of farming contributes in no small way to soil deterioration which in turn affects agricultural productivity. Even though one of the important requirements for embracing any agrarian practice is the financial viability of the process, it is believed that the differences in the benefits obtained from both conventional farming and conservation agriculture are not well articulated. While general inference can be made, it is also important to make a thorough evaluation of the benefits that can be derived from conservation agriculture and conventional agriculture.Methods: The study was conducted in Okhahlamba Local Municipality, which is situated in-between Lesotho, Free State Province, Alfred Duma and the Inkosi Langalibalele Local Municipality. Secondary data were retrieved from the Mahlathini Organics dataset collected from three different seasons, such as 2012/2013 to 2014/2015 and 2016/2017 seasons. The farmers under study practiced conservation agriculture (0.8ha) and conventional agriculture (0.8ha). Result: Using Gross Margin in addition to indicators like Benefit-Cost Ratio, Internal Rate of Returns and Net Present Value, this research identified that the advantages of using the conservation system of farming are enormous when matched with conventional agriculture. Consequently, this research suggests the advancement and encouragement of conservation agriculture as it provides more incentives in the long run.

The impacts of livelihood shocks on agrarian population especially the natural resource-dependent smallholder farmers in Nigeria cannot be over-emphasized, as this devastating event renders many farmers vulnerable because of limited adaptive capacity. Therefore, this study examined the vulnerability of agrarian households to livelihood shocks using a sample size of 368 farmers selected from Oyo State, Nigeria, through a multistage sampling technique, and from whom relevant data were elicited. This study applied the livelihood vulnerability index approach, and composite score technique to decipher the vulnerability space of the respondents, and for the ordinal categorization of the respondents into different vulnerability categories, respectively. The study also used proportional odds model to investigate the determinants of livelihood vulnerability from the perspective of adaptive capacity vis-à-vis the livelihood capital assets of the farmers. Findings from the study indicated that farmers suffered heavily from crime and economic related shocks due to the farmers-herdsmen conflict, while covariate and idiosyncratic related stressors were also reported by the farmers. Findings also indicated a high level of farmers’ exposure to shocks, with a moderate sensitivity to shocks, and a low adaptive capacity, which apparently pre-dispose the farmers to a serious vulnerable position. The farmers’ adaptive capacity linkage of the livelihood capital assets were also found to contribute significantly to farmers’ vulnerability status in the study area. The study recommended strengthening of physical, human, natural, social, and financial capital assets in building a sustained adaptive capacity of the farming population.

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