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Agricultural development must integrate multiple objectives at the same time, including food security, income, and environmental sustainability. To help achieve these objectives, development practitioners need to prioritize concrete livelihood practices to promote to rural households. But trade-offs between objectives can lead to dilemmas in selecting practices. In addition, heterogeneity among farming households requires targeting different strategies to different types of households. Existing diversity of household resources and activities, however, may also bear solutions. We explored a new, empirical research method that identifies promising options for multi-objective development by focusing on existing cases of strong multi-dimensional household performance. The “Positive Deviance” approach signifies identifying locally viable livelihood practices from diverse households that achieve stronger performance than comparable households in the same area. These practices are promising for other local households in comparable resource contexts. The approach has been used in other domains, such as child nutrition, but has not yet been fully implemented for agricultural development with a focus on the simultaneous achievement of multiple objectives. To test our adapted version of the Positive Deviance approach, we used a quantitative survey of over 500 rural households in South-Eastern Tanzania. We identified 54 households with outstanding relative performance regarding five key development dimensions (food security, income, nutrition, environmental sustainability, and social equity). We found that, compared to other households with similar resource levels, these “positive deviants” performed strongest for food security, but only slightly better for social equity. We then re-visited a diverse sub-sample for qualitative interviews, and identified 14 uncommon, “deviant” practices that plausibly contributed to the households’ superior outcomes. We illustrate how these practices can inform specific recommendations of practices for other local households in comparable resource contexts. The study demonstrates how, with the Positive Deviance approach, empirical observations of individual, outstanding households can inform discussions about locally viable agricultural development solutions in diverse household context. [ABSTRACT FROM AUTHOR]

To target food security interventions for smallholder households, decision makers need large-scale information, such as maps on poverty, food security and key livelihood activities. Such information is often based on expert knowledge or aggregated data, despite the fact that food security and poverty are driven largely by processes at the household level. At present, it is unclear if and how household level information can contribute to the spatial prediction of such welfare indicators or to what extent local variability is ignored by current mapping efforts. A combination of geo-referenced household level information with spatially continuous information is an underused approach to quantify local and large-scale variation, while it can provide a direct estimate of the variability of welfare indicators at the most relevant scale. We applied a stepwise regression kriging procedure to translate point information to spatially explicit patterns and create country-wide predictions with associated uncertainty estimates for indicators on food availability and related livelihood activities using household survey data from Uganda. With few exceptions, predictions of the indicators were weak, highlighting the difficulty in capturing variability at larger scale. Household explanatory variables identified little additional variation compared to environmental explanatory variables alone. Spatial predictability was strongest for indicators whose distribution was determined by environmental gradients. In contrast, indicators of crops that were more ubiquitously present across agroecological zones showed large local variation, which often overruled large-scale patterns. Our procedure adds to existing approaches that often only show large-scale patterns by revealing that local variation in welfare is large. Interventions that aim to target the poor must recognise that diversity in livelihood activities for income generation within any given area often overrides the variability of livelihood activities between distant regions in the country. [ABSTRACT FROM AUTHOR]

Abstract: The APSIM model was used to assess the impact of legumes on sorghum grown in rotation in a nutrient-limited system under dry conditions in south-western Zimbabwe. An experiment was conducted at Lucydale, Matopos Research Station, between 2002 and 2005. The model was used to simulate soil and plant responses in the experiment. Sequences of cowpea (Vigna unguiculata), pigeonpea (Cajanus cajan), groundnut (Arachis hypogaea) and sorghum (Sorghum bicolor) were used in the rotations. Legumes accumulated up to 130kg of Nha−1 which was potentially available for uptake by sorghum in the following season. The APSIM model predicted total biomass, grain and N yields of the legume phase within the experimental error and performed well in predicting sorghum yield and N supplied in the rotation after cowpea and groundnut. The model generally under-predicted sorghum total biomass and grain yield after pigeonpea. Observed patterns of crop water use, evaporative losses during the dry season and re-charge of soil profile at the start of the rainy season were generally well predicted by the model. An assessment of output on sorghum N and water stresses in the rotation indicated that the legume–cereal rotation is more driven by soil nitrogen availability than water availability even under semi-arid conditions. Further legume–cereal rotation analysis using the model will assist in the understanding of other processes in the rotations in dry environments. [Copyright &y& Elsevier]