Climate-smart agriculture

Quick and easy to read, the Climate-Smart Agriculture (CSA) country profiles give an overview of the agricultural challenges in 12 countries, and how CSA can help them adapt to and mitigate climate change. Developed by CIAT and CCAFS, in partnership with the World Bank, Costa Rica’s CATIE, and USAID’s Bureau for Food Security, the majority cover Latin America, as well as part of Africa and South Asia.

The following profiles are now available: Argentina, Colombia, Costa Rica, El Salvador, Grenada, Mexico, Peru, Nicaragua,  Uruguay, Kenya, Rwanda, Senegal, Sri Lanka, and Moldova. Scientists are currently developing profiles about: Ethiopia, Ghana, Mali, Niger, and Uganda.

Using one or more global climate models, the analogues tool takes climate and rainfall predictions for a particular site and searches for places with similar conditions at present. Armed with the knowledge of what they may face in future, farmers, researchers and policy makers can determine their adaptation options based on real models. The tool can also track historical data to learn how communities have adapted – or have failed to adapt – to climate change over time. Importantly, it helps capture the real world capacity of farmers to adapt, which is too often not taken into account in catastrophic climate models. Users of the tool can include variables such as crops, soils and socio-economic indicators in their searches.

The CSA Implementer platform is a crowdsourcing tool used to collect and share relevant data for monitoring and scaling out promising climate-smart agricultural practices. A mobile phone application supports knowledge exchange. For example, farmers can ask extension workers questions and be connected to national and international CSA experts. Lessons learned, spatial observations, and issues can be documented by local experts and attended to by experts through the interactive platform. Best practices of CSA implementation are spatially documented and can be out scaled to other similar regions.

CSA-Plan is a guide for CSA planning, programming and implementation. Sitting within each component of CSA-Plan are information, tools, and approaches to enable action. Engagement and capacity building are key crosscutting elements of CSA-Plan. Developed in cooperation with the World Agroforestry Center and CIAT, CSA-Plan can be applied across levels of decision making and allows for exchange of information between levels to maximinze alignment and integration of information and planning.

The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and the International Center for Tropical Agriculture (CIAT) have taken on the challenge of developing a framework for prioritizing investment in CSA that is evidence-based, yet realistic in that it can move forward in the face of data and resource constraints. The prioritization framework uses a four-phase approach to guide stakeholders through the process of filtering a long list of applicable CSA practices into portfolios of priority practices. The phases are additive, with each refining the previous outputs. The process generally takes between 4-8 months, and can be simplified and still provide valuable inputs into investment decision-making.

Based on satellite information from NASA, Terra-i is smart enough to distinguish between natural losses and those caused by human activity – and can also monitor habitat change in non-forested areas, such as savannahs and deserts. The cost-effective system is based on the premise that natural vegetation follows a predictable pattern of changes in greenness from one date to the next brought about by site-specific land and climatic conditions over the same period. A computational neural network is ‘trained’ to understand the normal pattern of changes in vegetation greenness in relation to terrain and rainfall for a site and then marks areas as changed where the greenness suddenly changes well beyond these normal limits. This analysis is refreshed with new imagery every 16 days and for every 250m square of land.

The portal produces and makes high-resolution climate data available to the public. It now contains about 14 terabytes of easy to use, open access datasets of climate projections that will help researchers make climate change impact assessments. The portal can support research in a variety of fields related to biodiversity and agriculture, particularly crop modelling and agro-climatology. Applications include assessing ecosystem functioning, options for policy-making, and food security and adaptation planning.