Poverty dynamics and the determining factors among East African smallholder farmers.

Context: Rapid economic development in East Africa is matched by extremely dynamic smallholder livelihoods.

Objective: To quantify the changes in poverty of smallholder farmers, to evaluate the potential of farm and off-farm activities to alleviate poverty, and to evaluate the potential barriers to poverty alleviation.

Methods: The analyses were based on a panel survey of 600 households undertaken in 2012 and re-visited approximately four years later in four sites in East Africa.

Prioritizing options for multi-objective agricultural development through the Positive Deviance approach.

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.

Using household survey data to identify large-scale food security patterns across Uganda.

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.

Agricultural diversification as an important strategy for achieving food security in Africa.

Farmers in Africa have long adapted to climatic and other risks by diversifying their farming activities. Using a multi-scale approach, we explore the relationship between farming diversity and food security and the diversification potential of African agriculture and its limits on the household and continental scale. On the household scale, we use agricultural surveys from more than 28,000 households located in 18 African countries.

Climate smart agriculture, farm household typologies and food security: An assessment from Eastern India.

One of the great challenges in agricultural development and sustainable intensification is the assurance of social equity in food security oriented interventions. Development practitioners, researchers, and policy makers alike could benefit from prior insight into what interventions or environmental shocks might differentially affect farmers' food security status, in order to move towards more informed and equitable development. We examined the food security status and livelihood activities of 269 smallholder farm households (HHs) in Bihar, India.

Drivers of household food availability in sub-Saharan Africa based on big data from small farms.

We calculated a simple indicator of food availability using data from 93 sites in 17 countries across contrasted agroecologies in sub-Saharan Africa (>13,000 farm households) and analyzed the drivers of variations in food availability. Crop production was the major source of energy, contributing 60% of food availability. The off-farm income contribution to food availability ranged from 12% for households without enough food available (18% of the total sample) to 27% for the 58% of households with sufficient food available.

Climate change and maize yield in southern Africa: what can farm management do?

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates.

Incident radiation and the allocation of nitrogen within Arctic plant canopies: implications for predicting gross primary productivity.

Arctic vegetation is characterized by high spatial variability in plant functional type (PFT) composition and gross primary productivity (P). Despite this variability, the two main drivers of P in sub-Arctic tundra are leaf area index (LT ) and total foliar nitrogen (NT ). LT and NT have been shown to be tightly coupled across PFTs in sub-Arctic tundra vegetation, which simplifies up-scaling by allowing quantification of the main drivers of P from remotely sensed LT .

Tight coupling between leaf area index and foliage N content in arctic plant communities.

The large spatial heterogeneity of arctic landscapes complicates efforts to quantify key processes of these ecosystems, for example productivity, at the landscape level. Robust relationships that help to simplify and explain observed patterns, are thus powerful tools for understanding and predicting vegetation distribution and dynamics. Here we present the same linear relationship between Leaf area index (LAI) and Total foliar nitrogen (TFN), the two factors determining the photosynthetic capacity of vegetation, across a wide range of tundra vegetation types in both northern Sweden and Alaska between leaf area indices of 0 and 1 m2 m(-2), which is essentially the entire range of leaf area index values for the Arctic as a whole.