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Understanding household diversity in rural eastern and southern Africa

Monograph Series No. 205
women and men listening to a speaker near a plot of beans

Increasing agricultural productivity, sustainability and resilience through technological innovation is a key mandate of ACIAR. Since 1982, ACIAR has organised and funded research to inform agricultural development programs that are applied to the wide range of cultures, resources, growing conditions, political climates, food and
livelihood needs of our partner countries. This book highlights the role of diversity in agricultural development efforts in southern and eastern Africa.

The food and nutrition security of more than half a billion smallholder farmers in Africa depends on their capacity to scale efficient and effective innovations that increase productivity and build resilience in their food and livelihood systems. The Sustainable Intensification of Maize-Legume Systems for Food Security in eastern and southern Africa (SIMLESA) program aimed to create more productive, resilient, profitable and sustainable maize-legume farming systems to overcome food insecurity and help reverse soil fertility decline, particularly in the context of climate risk and change.

This monograph, produced by the SIMLESA program, aims to identify the agroecological and socioeconomic patterns that define the diversity of opportunities to sustainably intensify eastern and southern Africa’s food and livelihood systems. It describes differences and similarities within and across five countries, and the various types of disparities that contribute to generating poverty traps and opportunities for economic and social growth.

A copy of this publication may be downloaded from this page or you may order a hardcopy by sending a request to publishing [at] aciar.gov.au (subject: Publication%20order, body: Please%20send%20me%20a%20hard%20copy%20of%20MN205%20Understanding%20household%20diversity%20in%20rural%20eastern%20and%20southern%20Africa%0A%0AName%3A%0AOrganisation%3A%09%0AStreet%20Address%3A%09%0APostal%20Address%3A%09%0ASuburb%2FCity%3A%09%0AState%3A%09%0APostcode%3A%09%0ACountry%3A%0A)

The R script code described in this publication is available, see details at right.