In the face of the fact that climatic change could increase the frequency and severity of droughts or rainy seasons, exposing farmers to adverse climates that would cause severe damage to crops, the Crop and Climate modeling team of CIAT’s Decision and Policy Analysis (DAPA) Research Area supports the Center’s research processes through the development and implementation of agro-climatic models.
The work of this team of professionals from CIAT has largely focused on the analysis of the responses of productive systems to climate conditions, which includes variations in rainfall patterns and other meteorological parameters (temperature, relative humidity). Some of the most important weather events are El Niño and La Niña, because of their environmental, social, and economic impacts.
Within this framework, the objective is to devise new solutions to counteract the effects of these factors, and actions are being defined under the concept of Climate-Smart Agriculture (CSA). This term includes many of the real and proven measures that form the backbone of sustainable agriculture: conservation of soil fertility; protection of watersheds; enhanced access to knowledge, supplies and markets for producers to have better livelihoods and food security.
CSA introduces a new point of view to help farmers, governments, companies, associations, and NGOs to better understand and manage the risks posed by climate change, as well as to be more resilient.* For CSA efforts to be significant for a large number of stakeholders, it becomes necessary to convene meetings with multiple actors, so they can understand site-specific projections regarding the impact of climate change and develop appropriate responses.
To start developing appropriate responses to climate variations, the Crop and Climate modeling team has focused on following:
Crop modeling consists of the implementation and operational improvement of crop models based on niches and processes. The team uses these tools to provide support for land-use planning, climate change adaptation, responses to climate variability, and to facilitate a better management of productive systems. It also conducts fundamental research of certain physiological processes (e.g., heat stress). The team collaborates with other modeling research groups ( AgMIP, University of Leeds, Embrapa).
This modeling is focused on assessing and adapting existing methodologies for weather and climate prediction for crops in specific contexts, understanding the impacts of climate variability on productivity, and providing key information for decision making at farm level (e.g., when to sow?, which varieties?).
Socio-economic modeling and the ex-ante impact assessment is focused on understanding the economic impact of climate change and variability on productive systems, improving decision-making in the economics-agriculture interface, and assessing the potential impact of agricultural technologies and/or policies.
In addition, the team is working in collaboration with CIAT’s Big Data team to develop software and design platforms to analyze and perform modeling tasks.
“We are a team of fourteen people with different backgrounds and with our ideas we strengthen our daily research work. We want to be in line with other areas with which we have shared interests and work with them as a team to meet our goals”.Julián Ramirez-Villegas
Projects and key collaborations
The Crop and Climate modeling team leads one of the main projects in the portfolio of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) in Latin America on agro-climatic forecasts for decision-making in agriculture. Likewise, it is carrying out a series of projects on modeling, climate change, and climate-smart agriculture in Latin America, Africa and Asia.
Publication of scientific papers
In relation to scientific output, the team has published over 50 scientific papers on topics such as modeling and climate change impact in the last 5 years, in a variety of international journals. Some of the journals where the team has published research results include Nature Climate Change (Rippke et al., 2016; Warren et al., 2013), European Journal of Agronomy (Ramírez-Villegas et al., 2016), Journal of Experimental Botany (Ramírez-Villegas et al., 2015; Heinemann et al., 2015), among others.
Four future challenges
- To ensure the integration of different modeling activities and work teams in the area of Decision and Policy Analysis at CIAT.
- To work as a team with CIAT’s research programs.
- To increase the number of publications.
- To learn from the experience and knowledge exchange with agricultural research experts, such as the emeriti scientists from CIAT and program leaders.
Four examples of joint collaboration
- The team supports the preparation of CSA country profiles in Africa and Latin America, and at a subnational level in Kenya, through the analysis of climate scenarios and potential impacts on productive systems.
- The team collaborates withand CIAT-Africa in modeling climate risks and CSA practices under the Risks, Households and Options (RHO) work scheme in the “Partnerships for Scaling Climate-Smart Agriculture” project led by ICRAF and CIAT within the CCAFS portfolio.
- It also collaborated with the CCAFS project and theBig Data team on ten-year predictions of CSA practices.
- Finally, the team is getting involved in the work of climate-smart value chains (with the Linking Farmers to Markets unit), by mapping adaptive gradients in cocoa and coffee.
The modeling team at CIAT is formed by:
- Steven Prager: Expert Integrated Modeling Scientist
- Julian Ramírez: Expert Climate Impact Scientist
- Carlos Eduardo Navarro Racines: Agricultural Engineer
- Diana Carolina Giraldo Méndez: Master in Agrometeorology
- Patricia Moreno Cadena: Agricultural Engineer
- David Arango Londoño: Statistics Specialist, Master in Applied Economics
- Camilo Barrios Pérez: Agricultural Engineer
- Patricia Álvarez Toro: Agricultural Engineer
- Lizeth Llanos Herrera: Statistics Specialist
- Jefferson Rodríguez Espinosa: Environmental Engineer
- Jaime Eduardo Tarapues Montenegro: Topographical Engineer
- Diego Agudelo: Statistics Specialist
- Carlos Eduardo González: Economist
- Jesús José Rodríguez de Luque: Economist
- Harold Armando Achicanoy Estrella: Statistics Specialist
- Diego Obando Bonilla: Master in Plant Physiology
*Resilience is defined as the capacity of a social-ecological system to cope with disturbance, responding or reorganizing in ways that it maintain its essential function, identity and structure, whilst also maintaining the capacity for adaptation, learning and transformation (Arctic Council, 2013).
Arctic Council, 2013: Glossary of terms. In: Arctic Resilience Interim Report 2013. Stockholm Environment Institute and Stockholm Resilience Centre, Stockholm, Sweden.