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.

Characterizing patterns of seasonal drought stress for use in common bean breeding in East Africa under present and future climates.

Common bean ( L.) is the second most important source of dietary protein and the third most important source of calories in Africa, especially for the poor. In East Africa, drought is an important constraint to bean production.

Data-driven approaches can harness crop diversity to address heterogeneous needs for breeding products.

This perspective describes the opportunities and challenges of data-driven approaches for crop diversity management (genebanks and breeding) in the context of agricultural research for sustainable development in the Global South. Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. This can lead to more information-rich management of crop diversity, which can address the complex interactions between crop diversity, production environments, and socioeconomic heterogeneity and help to deliver more suitable portfolios of crop diversity to users with highly diverse demands.

The determinants of common bean variety selection and diversification in Colombia.

Variety selection and diversification are climate change adaptation practices pursued by Colombian common bean producers. We investigate the drivers behind common bean variety selection and diversification in one of the most important common bean production regions in Colombia -Santander. The effects of climate change on this region are expected to be elevation driven.

Modeling growth, development and yield of cassava: A review.

Cassava is an important crop in the developing world. The goal of this study was to review published cassava models (18) for their capability to simulate storage root biomass and to categorize them into static and dynamic models. The majority (14) are dynamic and capture within season growth dynamics.

One CGIAR and the Integrated Agri-food Systems Initiative: From short-termism to transformation of the world's food systems.

Agri-food systems are besieged by malnutrition, yield gaps, and climate vulnerability, but integrated, research-based responses in public policy, agricultural, value chains, and finance are constrained by short-termism and zero sum thinking. As they respond to current and emerging agri-food system challenges, decision makers need new tools that steer toward multi-sector, evidence-based collaboration. To support national agri-food system policy processes, the Integrated Agri-food System Initiative (IASI) methodology was developed and validated through case studies in Mexico and Colombia.

Understanding the complexity of disease-climate interactions for rice bacterial panicle blight under tropical conditions.

Bacterial panicle blight (BPB) caused by Burkholderia glumae is one of the main concerns for rice production in the Americas since bacterial infection can interfere with the grain-filling process and under severe conditions can result in high sterility. B. glumae has been detected in several rice-growing areas of Colombia and other countries of Central and Andean regions in Latin America, although evidence of its involvement in decreasing yield under these conditions is lacking.

South India projected to be susceptible to high future groundnut failure rates for future climate change and geo-engineered scenarios.

With an increase in global mean temperature predicted for this century accompanied by more frequent extremes, will farming communities need to brace for increased crop failures and hardship? Solar dimming climate geoengineering has been proposed as a possible solution to combat rising global temperature but what effect will it or other climate related adaptation have on crop failures? We performed a crop modelling study using future climate and geoengineering projections to investigate these questions. Our results indicate that groundnut crop failure rates in Southern India are very sensitive to climate change, and project an increase of approximately a factor of two on average over this century, affecting one out of every two to three years instead of one in every five years. We also project that solar dimming geoengineering will have little impact on reducing these failure rates.

Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model.

We identified the most sensitive genotype-specific parameters (GSPs) and their contribution to the uncertainty of the MANIHOT simulation model. We applied a global sensitivity and uncertainty analysis (GSUA) of the GSPs to the simulation outputs for the cassava development, growth, and yield in contrasting environments. We compared enhanced Sampling for Uniformity, a qualitative screening method new to crop simulation modeling, and Sobol, a quantitative, variance-based method.

High-resolution and bias-corrected CMIP5 projections for climate change impact assessments.

Projections of climate change are available at coarse scales (70-400 km). But agricultural and species models typically require finer scale climate data to model climate change impacts. Here, we present a global database of future climates developed by applying the delta method -a method for climate model bias correction.

Black Sigatoka in bananas: Ecoclimatic suitability and disease pressure assessments.

Black leaf streak disease, or black Sigatoka, is caused by the fungus Pseudocercospora fijiensis, and has been identified as a major constraint to global production of banana and plantain. We fitted a climatic niche model (CLIMEX) for P. fijiensis to gain an understanding of the patterns of climate suitability, and hence hazard from this disease.

Emergence of robust precipitation changes across crop production areas in the 21st century.

A warming climate will affect regional precipitation and hence food supply. However, only a few regions around the world are currently undergoing precipitation changes that can be attributed to climate change. Knowing when such changes are projected to emerge outside natural variability-the time of emergence (TOE)-is critical for taking effective adaptation measures.

Data for the calculation of an indicator of the comprehensiveness of conservation of useful wild plants.

The datasets and code presented in this article are related to the research article entitled "Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets". The indicator methodology includes five main steps, each requiring and producing data, which are fully described and available here. These data include: species taxonomy, uses, and general geographic information (dataset 1); species occurrence data (dataset 2); global administrative areas data (dataset 3); eco-geographic predictors used in species distribution modeling (dataset 4); a world map raster file (dataset 5); species spatial distribution modeling outputs (dataset 6); ecoregion spatial data used in conservation analyses (dataset 7); protected area spatial data used in conservation analyses (dataset 8); and countries, sub-regions, and regions classifications data (dataset 9).

Reduction in nutritional quality and growing area suitability of common bean under climate change induced drought stress in Africa.

Climate change impacts on food security will involve negative impacts on crop yields, and potentially on the nutritional quality of staple crops. Common bean is the most important grain legume staple crop for human diets and nutrition worldwide. We demonstrate by crop modeling that the majority of current common bean growing areas in southeastern Africa will become unsuitable for bean cultivation by the year 2050.

Breeding implications of drought stress under future climate for upland rice in Brazil.

Rice is the most important food crop in the developing world. For rice production systems to address the challenges of increasing demand and climate change, potential and on-farm yield increases must be increased. Breeding is one of the main strategies toward such aim.

Improving the use of crop models for risk assessment and climate change adaptation.

Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk.

Integrating Plant Science and Crop Modeling: Assessment of the Impact of Climate Change on Soybean and Maize Production.

Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world. Crop model inter-comparison studies have identified large uncertainties and biases associated with climate change.

Potential negative consequences of geoengineering on crop production: A study of Indian groundnut.

Geoengineering has been proposed to stabilize global temperature, but its impacts on crop production and stability are not fully understood. A few case studies suggest that certain crops are likely to benefit from solar dimming geoengineering, yet we show that geoengineering is projected to have detrimental effects for groundnut. Using an ensemble of crop-climate model simulations, we illustrate that groundnut yields in India undergo a statistically significant decrease of up to 20% as a result of solar dimming geoengineering relative to RCP4.

Global conservation priorities for crop wild relatives.

The wild relatives of domesticated crops possess genetic diversity useful for developing more productive, nutritious and resilient crop varieties. However, their conservation status and availability for utilization are a concern, and have not been quantified globally. Here, we model the global distribution of 1,076 taxa related to 81 crops, using occurrence information collected from biodiversity, herbarium and gene bank databases.

Variation and impact of drought-stress patterns across upland rice target population of environments in Brazil.

The upland rice (UR) cropped area in Brazil has decreased in the last decade. Importantly, a portion of this decrease can be attributed to the current UR breeding programme strategy, according to which direct grain yield selection is targeted primarily to the most favourable areas. New strategies for more-efficient crop breeding under non-optimal conditions are needed for Brazil's UR regions.

Identifying traits for genotypic adaptation using crop models.

Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts.

Crop yield response to climate change varies with cropping intensity.

Projections of the response of crop yield to climate change at different spatial scales are known to vary. However, understanding of the causes of systematic differences across scale is limited. Here, we hypothesize that heterogeneous cropping intensity is one source of scale dependency.