On August 5, 2014 James W. Jones and Cynthia Rosenzweig (AgMIP Co-PI’s) attended a workshop hosted by the Global Agricultural Monitoring (GEOGLAM) in Beltsville, MD. The workshop brought together GEOGLAM and other agricultural research leaders to discuss both the current status of the US GEOGLAM initiative, and its future direction.
The goal of GEOGLAM is to strengthen the international community’s capacity to produce and disseminate relevant, timely and accurate forecasts of agricultural production at national, regional and global scales through the use of Earth Observations (EO), which include satellite and ground-based observations. (more…)
Today at the White House the Obama Administration invited leaders of technology and agricultural sectors to announce new public-private partnerships in order to advance the President’s Climate Data Initiative. AgMIP is pleased to announce its collaboration in several of these initiatives.
AgMIP and CIMSANS form partnership
In support of the White House Climate Data Initiative AgMIP and the Center for Integrated Modeling of Sustainable Agriculture and Nutrition Security (CIMSANS) have formed a new public-private partnership on open data and open source code modeling to enhance the climate resilience of food systems along with the International Food Policy Research Institute (IFPRI). (more…)
The objective of the initiative, co-led by Gopal Kakani and David LeBauer, is to develop protocols for intercomparison and improvement of crop models for existing and emerging biomass and bioenergy crops. Read more about the project and register for participation here.
By Mina Coutsoucos
Can current farm household models accurately simulate food security driven by climate change?
There has been considerable effort in the last 44 years by researchers to model climate change impacts on farm households, but relatively little attention have been paid to food security. Food security includes many components and modeling it requires an understanding of how agricultural systems are affected by social and economic factors. (more…)
Save the date! The 5th Annual AgMIP Global Workshop will be held February 18-20, 2015 in Gainesville, Florida. More details will be posted as the date approaches. We are looking forward to seeing you there!
AgMIP meetings and side events at the ASA Annual Meeting in Long Beach, California (November 2-5, 2014) are still being planned, including an AgMIP poster session. A complete list will be available on our website, please check if you are planning to attend.
The 6th Annual AgMIP Global Workshop – is now being planned for October 2015, location and details to come.
A joint CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and Agricultural Model Intercomparison and Improvement Project (AgMIP) meeting was held June 3-4 to kick off a USAID-CIAT (International Center for Tropical Agriculture) funded study “Increasing Productivity and Livelihoods in the Nioro du Rip Basin in Senegal” at the Earth Institute at Columbia University in New York. The meeting brought together researchers from CCAFS, the International Research Institute for Climate and Society (IRI), NASA Goddard Institute for Space Studies, University of Florida, University of Ghana, the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and the Center for Climate Systems Research. The goal of the study is to investigate how index insurance can be optimized to encourage yield-enhancing farm management choices in Senegal. (more…)
By Andrea Calderon Irazoque
According to a recent commentary “Food Security: Fertilizing hidden hunger” by Müller C. and others published in Nature Climate Change, CO2 fertilization and climate change will likely exacerbate macro and micro-nutrients deficiency in crops, jeopardizing one of the most important millennium development goals: to eradicate extreme poverty and hunger. This declining nutritional content could lead to “hidden hunger”– defined by the authors as an “insufficient supply of vitamins and minerals in diets with sufficient calorie content.” (more…)
By Nick Hudson
Crop models have been extensively tested for yields, but their validation for soil water balance, and carbon and nitrogen cycling in agricultural systems has been limited. In order to improve the use of soil data in assessments of climate change impacts on agriculture, the Agricultural Modeling Intercomparison and Improvement Project (AgMIP) and Columbia University’s Center for Climate Systems Research (CCSR), hosted a joint workshop April 9-11 funded by USAID. The workshop, part of the AgMIP GRIDded crop modeling initiative (AgGRID) brought together leaders from AgMIP soils team and AgGRID along with experts from the Gates-funded African Soil Information Service (AfSIS) project as well as other soil and Africa experts. (more…)
By Jean-Louis Durand, Institut National de la Recherche Agronomique, France
Our climate is changing and crop simulation models can project how climatic factors will affect food production in the coming decades, and what adaptations in farmers’ fields could stabilize global food security. Crop models are computer tools used in combination with present scientific knowledge to project yields under future climate. A recent publication, “How do various maize crop models vary in their responses to climate change factors?” by Bassu and others in the journal Global Change Biology addresses questions regarding our confidence in how well the maize simulation models can predict growth and yields under future climate change. (more…)
By Molly B Schneider
Recently several studies by AgMIP researchers have been released that highlight the development of improved methods for the use and management of site-specific data for agricultural research. Site-specific data consists of more detailed information about local environmental and economic variables that could impact production. By using site-specific data researchers will be able to create more accurate predictions of future trends in agricultural production. These articles highlight three updated techniques: production modeling, data sharing and yield assessments.(more…)