There is an ongoing debate on what constitutes sustainable intensification of agriculture (SIA). In this paper, we propose that a paradigm for sustainable intensification can be defined and translated into an operational framework for agricultural development. We argue that this paradigm must now be defined—at all scales—in the context of rapidly rising global environmental changes in the Anthropocene, while focusing on eradicating poverty and hunger and contributing to human wellbeing.

Given limited resources, adaptation strategies must target those populations most vulnerable to global change and equip those unable to adapt—generally the poorest—with the tools and incentives that will enable them to do so. ASARECA has recently carried out a study to enhance the understanding of climate change in the 10 ASARECA member countries. This report profiles the available climate change–related datasets and their accessibility and procurement details in the 10 ASARECA member countries.

Climate change is a hazard to the food security of a growing world population since it affects agriculture and likewise, agriculture and natural resource management affect the climate system. The relationships between all these factors including polices, political conditions, economical management and pest and diseases, and how they interact are not currently well-understood, nor are the advantages and disadvantages of different responses to climate change.

Extensive land degradation in the Ethiopian Highlands jeopardizes rural livelihood. Intensified by increasing population pressure, farmers are forced to expand their arable land by deforestation and thus worsening the soil erosion problem. Through the application of various soil conservation measures, farmers and authorities try to prevent against further land degradation.

Much of the native forest in the highlands of western Kenya has been converted to agricultural land in order to feed the growing population, and more land is being cleared. In tropical Africa, this land use change results in progressive soil degradation, as the period of cultivation increases. Both rates and variation in infiltration, soil carbon concentration and other soil parameters are influenced by management within agricultural systems, but they have rarely been well documented in East Africa.

Bhutan is least developed, mountainous and landlocked country in the eastern Himalayan range with a population of over 600,000. However its population and ecosystems are vulnerable to climate change. Despite a high level of environmental protection and awareness, Bhutan has become a victim of the global impacts of climate change caused by emissions in other countries. There is little historical climate data available in Bhutan; current records date back only to 1994. Consequently, the future climate scenario for Bhutan is uncertain.

Long-term investments in agricultural water management (AWM) interventions in the Volta and Limpopo river basins have aimed at improving water availability and quality for smallholder farming systems. However, sustained and wider uptake of AWM technologies and approaches has not been as successful. We need to learn from successful AWM interventions, those interventions that have led to a sustained or increased uptake of AWM technologies or approaches, and which have led to improved well-being of farmers and livestock keepers in the rural development context of sub-Sahara Africa.

Engagement platforms are variously known as multi-stakeholder platforms or innovation platforms. In general terms, an engagement platform is an opportunity for individuals and people representing organizations with different backgrounds and interests to come together to diagnose problems, identify opportunities and implement solutions. They may engage in design and implementation as a platform, in smaller groups, or individually.

Measurements of nutrient stocks and greenhouse gas (GHG) fluxes are typically collected at very local scales (<1 to 30 m2) and then extrapolated to estimate impacts at larger spatial extents (farms, landscapes, or even countries). Translating point measurements to higher levels of aggregation is called scaling. Scaling fundamentally involves conversion of data through integration or interpolation and/or simplifying or nesting models. Model and data manipulation techniques to scale estimates are referred to as scaling methods.