High-resolution global maps of yield potential with local relevance for targeted crop production improvement.

Identifying untapped opportunities for crop production improvement in current cropland is crucial to guide food availability interventions. Here we integrated an agronomically robust bottom-up approach with machine learning to generate global maps of yield potential of high resolution (ca. 1 km at the Equator) and accuracy for maize, wheat and rice.

Daily bias-corrected weather data and daily simulated growth data of maize, millet, sorghum, and wheat in the changing climate of sub-Saharan Africa.

Crop models are the primary means by which agricultural scientists assess climate change impacts on crop production. Site-based and high-quality weather and climate data is essential for agronomically and physiologically sound crop simulations under historical and future climate scenarios. Here, we describe a bias-corrected dataset of daily agro-meteorological data for 109 reference weather stations distributed across key production areas of maize, millet, sorghum, and wheat in ten sub-Saharan African countries.

Costs and benefits of synthetic nitrogen for global cereal production in 2015 and in 2050 under contrasting scenarios.

Cereals are the most important global staple crop and use more than half of global cropland and synthetic nitrogen (N) fertilizer. While this synthetic N may feed half of the current global population, it has led to a massive increase in reactive N loss to the environment, causing a suite of impacts, offsetting the benefits of N fertilizers for food security and agricultural economy. To address these complex issues, the NBCalCer model was developed to quantify the global effects of N input on crop yields, N budgets and environmental impacts and to assess the associated social benefits and costs.

Spatial frameworks for robust estimation of yield gaps.

Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used 'top-down' gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative 'bottom-up' approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales.

Impacts of intensifying or expanding cereal cropping in sub-Saharan Africa on greenhouse gas emissions and food security.

Cropping is responsible for substantial emissions of greenhouse gasses (GHGs) worldwide through the use of fertilizers and through expansion of agricultural land and associated carbon losses. Especially in sub-Saharan Africa (SSA), GHG emissions from these processes might increase steeply in coming decades, due to tripling demand for food until 2050 to match the steep population growth. This study assesses the impact of achieving cereal self-sufficiency by the year 2050 for 10 SSA countries on GHG emissions related to different scenarios of increasing cereal production, ranging from intensifying production to agricultural area expansion.

Can sub-Saharan Africa feed itself?

Although global food demand is expected to increase 60% by 2050 compared with 2005/2007, the rise will be much greater in sub-Saharan Africa (SSA). Indeed, SSA is the region at greatest food security risk because by 2050 its population will increase 2.5-fold and demand for cereals approximately triple, whereas current levels of cereal consumption already depend on substantial imports.

Plant-plant interactions mediate the plastic and genotypic response of Plantago asiatica to CO2: an experiment with plant populations from naturally high CO2 areas.

Background And Aims: The rising atmospheric CO2 concentration ([CO2]) is a ubiquitous selective force that may strongly impact species distribution and vegetation functioning. Plant-plant interactions could mediate the trajectory of vegetation responses to elevated [CO2], because some plants may benefit more from [CO2] elevation than others. The relative contribution of plastic (within the plant's lifetime) and genotypic (over several generations) responses to elevated [CO2] on plant performance was investigated and how these patterns are modified by plant-plant interactions was analysed.

How light competition between plants affects their response to climate change.

How plants respond to climate change is of major concern, as plants will strongly impact future ecosystem functioning, food production and climate. Here, we investigated how vegetation structure and functioning may be influenced by predicted increases in annual temperatures and atmospheric CO2 concentration, and modeled the extent to which local plant-plant interactions may modify these effects. A canopy model was developed, which calculates photosynthesis as a function of light, nitrogen, temperature, CO2 and water availability, and considers different degrees of light competition between neighboring plants through canopy mixing; soybean (Glycine max) was used as a reference system.