Which options fit best? Operationalizing the socio-ecological niche concept

Article Purchased; Published: 1st August 2016The large diversity of farms and farming systems in sub-Saharan Africa calls for agricultural improvement options that are adapted to the context in which smallholder farmers operate. The socio-ecological niche concept incorporates the agro-ecological, socio-cultural, economic and institutional dimensions and the multiple levels of this context in order to identify which options fit best. In this paper, we illustrate how farming systems analysis, following the DEED cycle of Describe, Explain, Explore and Design, and embedding co-learning amongst researchers, farmers and other stakeholders, helps to operationalize the socio-ecological niche concept. Examples illustrate how farm typologies, detailed farm characterization and on-farm experimental work, in combination with modelling and participatory approaches inform the matching of options to the context at regional, village, farm and field level. Recommendation domains at these gradually finer levels form the basis for gradually more detailed baskets of options from which farmers and other stakeholders may choose, test and adjust to their specific needs. Tailored options identified through the DEED cycle proof to be more relevant, feasible and performant as compared to blanket recommendations in terms of both researcher and farmer-identified criteria. As part of DEED, on-farm experiments are particularly useful in revealing constraints and risks faced by farmers. We show that targeting options to the niches in which they perform best, helps to reduce this risk. Whereas the conclusions of our work about the potential for improving smallholders’ livelihoods are often sobering, farming systems analysis allows substantiating the limitations of technological options, thus highlighting the need for enabling policies and institutions that may improve the larger-scale context and increase the uptake potential of options

Vulnerability and adaptation options to climate change for rural livelihoods – a country-wide analysis for Uganda

Open Access Article; Published online: 15 July 2019Rural households in sub-Saharan Africa earn a substantial part of their living from rain-fed smallholder agriculture, which is highly sensitive to climate change. There is a growing number of multi-level assessments on impacts and adaptation options for African smallholder systems under climate change, yet few studies translate impacts at the individual crop level to vulnerability at the household level, at which other livelihood activities need to be considered. Further, these assessments often use representative household types rather than considering the diversity of households for the identification of larger-scale patterns at sub-national and national levels. We developed a framework that combines crop suitability maps with a household food availability analysis to quantify household vulnerability to climate-related impacts on crop production and effects of adaptation options. The framework was tested for Uganda, identifying four hotspots of household vulnerability across the country. Hotspots were visually identified as areas with a relatively high concentration of vulnerable households, experiencing a decline in household crop suitability. About 30% of the households in the hotspots in (central) southwest were vulnerable to a combination of 3 °C temperature increase and 10% rainfall decline through declining suitability for several key crops (including highland banana, cassava, maize and sorghum). In contrast only 10% of the households in West Nile and central northern Uganda were negatively affected, and these were mainly affected by declining suitability of common beans. Households that depended on common beans and lived at lower elevations in West Nile and central north were vulnerable to a 2 to 3 °C temperature increase, while households located at higher elevations (above 1100–2000 m.a.s.l. depending on the crop) benefited from such an increase. Options for adaptation to increasing temperatures were most beneficial in northern Uganda, while drought-related adaptation options were more beneficial in the southwest. This framework provides a basis for decision makers who need information on where the vulnerable households are, what crops drive the vulnerability at household level and which intervention efforts are most beneficial in which regions

What works where and for whom? Farm Household Strategies for Food Security across Uganda

East Africa's smallholder agriculture is expected to be strongly affected by climate change, which, together with a growing population and pressure on natural resources, will result in an increasing challenge to achieve food security for households and regions. Policy makers need information on what works where for which farmers in order to guide their decision making and prioritise investment for agricultural interventions to increase food security. For this, we must better understand how smallholder farm strategies for achieving food security differ across regions and farm types and what drives these strategies. In this study we present new analyses at country and farm household level that quantify drivers of productivity and food security, and that can be used to prioritise agricultural interventions. Uganda was chosen as a case study because of data availability but the approach can be applied to other countries in sub-Saharan Africa. First, we quantified how food security and farm types varied across Uganda, and which key factors drive this variability. We used household level data from the Living Standard Measurement Study – Integrated Survey on Agriculture (LSMS-ISA) of the World Bank and developed an approach to map and quantitatively explain food security and agricultural land use across Uganda. The resulting maps showed where which crops and livestock activities are important for which types of farm households. Subsequently, the effects of agricultural interventions on food security of different farm types were assessed. Second, we used this information to select contrasting sites and farm households for detailed interviews, which aimed at identifying drivers of farmers' decision making, assessing farmers' vulnerability to climate change and how proposed interventions match with the farmers' socio-ecological niche. The spatial approach we developed is a novel way to use farm household level information to generate country-wide patterns in farming systems and their productivity. It generates useful information for a quantitative assessment of what might happen to the food security of smallholder farmers in Uganda under climate change and for a country-wide targeting of agricultural interventions that aim at mitigating the effects of climate change

Making the most of imperfect data: A critical evaluation of standard information collected in farm household surveys

Household surveys are one of the most commonly used tools for generating insight into rural communities. Despite their prevalence, few studies comprehensively evaluate the quality of data derived from farm household surveys. We critically evaluated a series of standard reported values and indicators that are captured in multiple farm household surveys, and then quantified their credibility, consistency and, thus, their reliability. Surprisingly, even variables which might be considered ‘easy to estimate’ had instances of non-credible observations. In addition, measurements of maize yields and land owned were found to be less reliable than other stationary variables. This lack of reliability has implications for monitoring food security status, poverty status and the land productivity of households. Despite this rather bleak picture, our analysis also shows that if the same farm households are followed over time, the sample sizes needed to detect substantial changes are in the order of hundreds of surveys, and not in the thousands. Our research highlights the value of targeted and systematised household surveys and the importance of ongoing efforts to improve data quality. Improvements must be based on the foundations of robust survey design, transparency of experimental design and effective training. The quality and usability of such data can be further enhanced by improving coordination between agencies, incorporating mixed modes of data collection and continuing systematic validation programmes

The Rural Household Multiple Indicator Survey, data from 13,310 farm households in 21 countries

The Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 758 variables covering household demographics, farm area, crops grown and their production, livestock holdings and their production, agricultural product use and variables underlying standard socio-economic and food security indicators such as the Probability of Poverty Index, the Household Food Insecurity Access Scale, and household dietary diversity. These variables are used to quantify more than 40 different indicators on farm and household characteristics, welfare, productivity, and economic performance. Between 2015 and the beginning of 2018, the survey instrument was applied in 21 countries in Central America, sub-Saharan Africa and Asia. The data presented here include the raw survey response data, the indicator calculation code, and the resulting indicator values. These data can be used to quantify on- and off-farm pathways to food security, diverse diets, and changes in poverty for rural smallholder farm households

Food security in a changing world : disentangling the diversity of rural livelihood strategies across Uganda

Climate change increasingly challenges smallholder farming and our ability to achieve Sustainable Development Goal 2 (Zero Hunger) in sub-Saharan Africa. Agricultural interventions are needed that aim at improving the food insecurity of the most vulnerable rural households. Interventions must fit the local context of a diverse population of rural households, and a key challenge is to identify which kinds of interventions work in which regions and for which households. Micro-level information can account for this diversity, but is an underused source of information for planning of interventions at national and sub-national levels. In this thesis, I explored how micro-level information from cross-country household survey data can be used for effective planning of interventions. A further research aim was to understand within-country patterns of livelihood strategies in relation to food security and vulnerability to climate change of rural households in Uganda. Cross-country household data from the World Bank Living Standard Measurement Survey – Integrated Surveys on Agriculture (LSMS-ISA) were used to 1) aggregate household level information to higher levels (e.g. districts, regions, livelihood zones), 2) spatially interpolate household level information and 3) identify hotspot areas of household vulnerability. I used data that I collected from two sites in Uganda for an in-depth analysis on current coping strategies of households for climate and price variability. Household food security was approximated using a food availability indicator that quantified the contribution of livelihood activities to household food availability. Livelihood strategies of rural households across Uganda varied with household food availability. They changed from subsistence-oriented on-farm activities to market-oriented on-farm and off-farm activities as household food availability increased. Aggregation revealed spatial differences in food availability and livelihood activities. However, a geostatistical interpolation approach showed that local variability in food availability and livelihood activities was often larger than variability across larger areas. These findings stress that the large diversity in livelihood activities within any given area must be recognised in decision making at higher levels. Climate change scenarios were linked to the household livelihood activities to identify hotspot areas of vulnerable households in a country-wide assessment of climate change impacts on crop suitability. Groups of crop-related adaptation options were determined per hotspot area. Adaptation options related to temperature were suitable in the north, while drought-related adaptation options were more suitable in the southwest of Uganda. An in-depth analysis indicated that few ex-ante coping strategies were applied under current climate and price variability. Such coping strategies mostly required little financial investment such as switching crops, which was common for households with more land available. Households tended to react to shocks rather than taking preventive action. Better-off households compensated for crop losses by selling livestock or relying more on off-farm income, while the poor and food insecure lacked the resources to do so. These findings suggest that lack of resources can prevent households from adapting to climate change, even when adaptation options are useful from an agronomic perspective. Therefore, contextualised research is needed to understand local barriers to adoption, so that adaptation options can be tailored to local contexts and underpinned by enabling policies and institutional arrangements. Current top-down approaches to planning interventions ignore local diversity of livelihood strategies and food security. However, my results demonstrate that food security and vulnerability tend to be locally driven with large variability at small scale. Therefore, I propose a three-step approach for using micro-level information for multi-level planning. Step 1 disentangles livelihood diversity using cross-country household surveys. Step 2 locates important production activities (Pathway 2a) or vulnerable households and suitable adaptation options (Pathway 2b). Step 3 uses site-specific household surveys to assess which interventions work for which groups of households in the local context. This approach adds to existing approaches by generating spatially-explicit and quantitative information on livelihood activities for food availability and on household vulnerability, while accounting for the diversity of households within and across areas. It enables the exploration and tailoring of intervention options under different future scenarios. In this way, my work contributes to identifying pathways to achieve zero hunger by 2030 in sub-Saharan Africa.</p

Production variability and adaptation strategies of Ugandan smallholders in the face of climate variability and market shocks

Climate-related variability in crop production and market price variability affect food and income security of Uganda's rural households. We used household surveys from two contrasting sites in Uganda to quantify the relationships between crop production variability, adaptation strategies and household resource characteristics. Variability of production was large for all crops with almost doubling of yields under good conditions and halving of yields in bad years. Ex-post adaptation strategies were common, and the most frequent were relying on off-farm income, selling livestock, and reducing food consumption. Using off-farm income or selling livestock to compensate for crop damage were not feasible for 25–50% of the population. Few households applied ex-ante adaptation strategies, and those who did used strategies that required little financial investment, such as switching crops. The restricted application of ex-ante adaptation strategies and the fact that major ex-post adaptation strategies were inaccessible for large parts of the population is alarming considering that climate change studies show that weather variability and extreme weather events are expected to worsen and to jeopardize crop production. Interventions must aim to reduce households’ sensitivity to variability in crop production and prices by increased preparedness to shocks, strengthening the asset base, and diversifying the livelihood portfolio. Social protection programmes are important for the poor who have no means to cushion effects from climate or price variability

The contribution of integrated crop–livestock systems in combatting climate change and improving resilience in agricultural production to achieve food security

This chapter illustrates through a contrasting set of examples how current crop–livestock systems contribute to the food security and diverse diets of smallholder livelihoods. It also highlights how farmers use these systems to cope with a variable climate. The chapter provides a short overview of analyses and approaches focusing on climate change and mixed crop–livestock systems in recent scientific literature. It also presents analyses that quantify how in crop–livestock systems food security and dietary diversity are being shaped. The chapter then reviews analyses of short-term climate variability coping strategies that farmers currently apply in mixed crop–livestock systems, as well as highlighting adaptation options to climate change in mixed farming systems. It concludes by consolidating these findings to provide a review of the resilience of mixed crop–livestock systems in the face of existing and future climate variability