The Rural Household Multi-Indicator Survey (RHoMIS) for rapid characterisation of households to inform climate smart agriculture interventions: Description and applications in East Africa and Central America

Abstract

Achieving climate smart agriculture depends on understanding the links between farming and livelihood practices, other possible adaptation options, and the effects on farm performance, which is conceptualised by farmers as wider than yields. Reliable indicators of farm performance are needed in order to model these links, and to therefore be able to design interventions which meet the differing needs of specific user groups. However, the lack of standardization of performance indicators has led to a wide array of tools and ad-hoc indicators which limit our ability to compare across studies and to draw general conclusions on relationships and trade-offs whereby performance indicators are shaped by farm management and the wider socialenvironmental context. RHoMIS is a household survey tool designed to rapidly characterise a series of standardised indicators across the spectrum of agricultural production and market integration, nutrition, food security, poverty and GHG emissions. The survey tool takes 40-60 minutes to administer per household using a digital implementation platform. This is linked to a set of automated analysis procedures that enable immediate cross-site benchmarking and intra-site characterisation. We trialled the survey in two contrasting agro-ecosystems, in Lushoto district of Tanzania (n=151) and in the Trifinio border region of Guatemala, El Salvador and Honduras (n=285). The tool rapidly characterised variability between farming systems at landscape scales in both locations identifying key differences across the population of farm households that would be critical for targeting CSA interventions. Our results suggest that at both sites the climate smartness of different farm strategies is clearly determined by an interaction between the characteristics of the farm household and the farm strategy. In general strategies that enabled production intensification contributed more towards the goals of climate smart agriculture on smaller farms, whereas increased market orientation was more successful on larger farms. On small farms off-farm income needs to be in place before interventions can be promoted successfully, whereas on the larger farms a choice is made between investing labour in off-farm incomes, or investing that the labour into the farm, resulting in a negative association between off-farm labour and intensification, market orientation and crop diversity on the larger farms, which is in complete opposition to the associations found for the smaller farms. The balance of indicators selected gave an adequate snap shot picture of the two sites, and allowed us to appraise the 'CSA-ness' of different existing farm strategies, within the context of other major development objectives.

Identifying Climate-smart agriculture research needs

“…However, food security in itself is a complex concept depending on various conditions (access, availability, utilization, stability) which all need to be taken into account (Richardson, 2010). Some authors are consequently using food security indicators such as the Household Food Insecurity Access Scale or Dietary Diversity with indicators of social resilience and CO 2 emissions to assess the climate smartness of farming systems (Hammond et al 2017).…”

Food availability and livelihood strategies among rural households across Uganda

“…Hammond et al (2016) correlated the food availability indicator with other food security indicators, including the Household Dietary Diversity Score (HDDS) and the Household Food Insecurity Access Scale (HFIAS). These food security indicators improved up to a food availability indicator value of 5000 kcal cap −1 day −1 , but not beyond (Hammond et al 2016). …”

“…Frelat et al (2016) developed a simple food availability indicator using information on household on-and off-farm activities of smallholders. This food availability indicator closely correlates to well-established indicators such as the Household Dietary Diversity Score (HDDS) and the Household Food Insecurity Access Scale (HFIAS) (Hammond et al 2016). Frelat et al (2016) observed that household food availability improved with increasing dependency on off-farm activities, suggesting diverse strategies among rural households.…”

Experiences and Drivers of Food Insecurity in Guatemala's Dry Corridor: Insights From the Integration of Ethnographic and Household Survey Data

“…There is a drive toward standardization of surveys on food security (Nicholson et al, 2019), for example in the application of the Rural Household Multi-Indicator Survey (RHoMIS), which is increasingly used by CGIAR research institutes and their partners. RHoMIS has been designed to enable a more holistic assessment of progress toward the SDGs, specifically around goals 1, 2, 5, and 13 in recognition of the interdependence of issues of poverty, food insecurity and gender equality (Frelat et al, 2016;Hammond et al, 2017). It provides a standardized framework-based on best practice-which aims to improve consistency and comparability of data across sectors, organizations and regions, and provides a basis for regression modeling to determine household-level causes and correlates of food security.…”