Clare Sullivan

Identifying potential synergies and trade-offs for meeting food security and climate change objectives in sub-Saharan Africa

Potential interactions between food production and climate mitigation are explored for two situations in sub-Saharan Africa, where deforestation and land degradation overlap with hunger and poverty. Three agriculture intensification scenarios for supplying nitrogen to increase crop production (mineral fertilizer, herbaceous legume cover crops—green manures—and agroforestry—legume improved tree fallows) are compared to baseline food production, land requirements to meet basic caloric requirements, and greenhouse gas emissions. At low population densities and high land availability, food security and climate mitigation goals are met with all intensification scenarios, resulting in surplus crop area for reforestation. In contrast, for high population density and small farm sizes, attaining food security and reducing greenhouse gas emissions require mineral fertilizers to make land available for reforestation; green manure or improved tree fallows do not provide sufficient increases in yields to permit reforestation. Tree fallows sequester significant carbon on cropland, but green manures result in net carbon dioxide equivalent emissions because of nitrogen additions. Although these results are encouraging, agricultural intensification in sub-Saharan Africa with mineral fertilizers, green manures, or improved tree fallows will remain low without policies that address access, costs, and lack of incentives. Carbon financing for small-holder agriculture could increase the likelihood of success of Reducing Emissions from Deforestation and Forest Degradation in Developing Countries programs and climate change mitigation but also promote food security in the region.

Assessing Nutritional Diversity of Cropping Systems in African Villages

Background In Sub-Saharan Africa, 40% of children under five years in age are chronically undernourished. As new investments and attention galvanize action on African agriculture to reduce hunger, there is an urgent need for metrics that monitor agricultural progress beyond calories produced per capita and address nutritional diversity essential for human health. In this study we demonstrate how an ecological tool, functional diversity (FD), has potential to address this need and provide new insights on nutritional diversity of cropping systems in rural Africa. Methods and Findings Data on edible plant species diversity, food security and diet diversity were collected for 170 farms in three rural settings in Sub-Saharan Africa. Nutritional FD metrics were calculated based on farm species composition and species nutritional composition. Iron and vitamin A deficiency were determined from blood samples of 90 adult women. Nutritional FD metrics summarized the diversity of nutrients provided by the farm and showed variability between farms and villages. Regression of nutritional FD against species richness and expected FD enabled identification of key species that add nutrient diversity to the system and assessed the degree of redundancy for nutrient traits. Nutritional FD analysis demonstrated that depending on the original composition of species on farm or village, adding or removing individual species can have radically different outcomes for nutritional diversity. While correlations between nutritional FD, food and nutrition indicators were not significant at household level, associations between these variables were observed at village level. Conclusion This study provides novel metrics to address nutritional diversity in farming systems and examples of how these metrics can help guide agricultural interventions towards adequate nutrient diversity. New hypotheses on the link between agro-diversity, food security and human nutrition are generated and strategies for future research are suggested calling for integration of agriculture, ecology, nutrition, and socio-economics.

An operational framework for object-based land use classification of heterogeneous rural landscapes

Abstract The characteristics of very high resolution (VHR) satellite data are encouraging development agencies to investigate its use in monitoring and evaluation programmes. VHR data pose challenges for land use classification of heterogeneous rural landscapes as it is not possible to develop generalised and transferable land use classification definitions and algorithms. We present an operational framework for classifying VHR satellite data in heterogeneous rural landscapes using an object-based and random forest classifier. The framework overcomes the challenges of classifying VHR data in anthropogenic landscapes. It does this by using an image stack of RGB-NIR, Normalised Difference Vegetation Index (NDVI) and textural bands in a two-phase object-based classification. The framework can be applied to data acquired by different sensors, with different view and illumination geometries, at different times of the year. Even with these complex input data the framework can produce classification results that are comparable across time. Here we describe the framework and present an example of its application using data from QuickBird (2 images) and GeoEye (1 image) sensors.

Monitoring and evaluation to support adaptive co-management: Lessons learned from the Millennium Villages Project

This article focuses attention on monitoring and evaluation approaches that will help resource managers to manage for change and uncertainty in adaptive co-management (ACM). ACM is a learning-by-doing approach that aims to build flexible community-based natural resource governance systems through collaborative or otherwise participatory means. We describe the framework for monitoring and evaluation that we developed and applied in ten African countries, which includes fixed indicators and measures for co-management performance monitoring, a process evaluation element, a platform for repeat ecological surveillance, and a longitudinal household survey. We comment on the usefulness of this framework, and its applicability to a wide range of geographic contexts. We then present a four step model to assist managers in applying the framework to specific co-management problems. The model suggests a cascade approach to defining key evaluations questions at a systems, network, individual and synthesis level. We illustrate the application of our model and framework by means of a case study of a co-managed agroforestry program in western Kenya.