The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector.
The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, crop model, economics, and information technology protocols are presented to guide coordinated AgMIP research activities around the world, along with cross-cutting themes that address aggregation, uncertainty, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones.
The worldwide agricultural sector faces the significant challenge of increasing production to provide food security for a population projected to rise to 9 billion by mid-century while protecting the environment and the functioning of ecosystems. This challenge is compounded by the need to adapt to climate change by taking advantage of potential benefits and by minimizing the potentially negative impacts to agricultural production. The Agricultural Model Intercomparison and Improvement Project (AgMIP) seeks to improve substantially the characterization of world food security under climate change and to enhance adaptation capacity in both developing and developed countries.
To examine the full range of climate change impacts on agriculture, both biophysical and economic aspects need to be considered and combined (Hillel and Rosenzweig, 2011). Methodologies for assessing the biophysical effects of climate on crop yield include statistical models (e.g., Schlenker et al., 2006; Lobell and Burke, 2010) and process-based dynamic crop growth models (e.g., Keating et al., 2003; Brisson et al., 2003; Jones et al., 2003; van Ittersum and Donatelli, 2003; Challinor et al., 2004). For simulating the combined biophysical and economic effects of climate change on agriculture, reduced form statistical models have been used (e.g., Mendelsohn et al., 1994) as well as internally or externally coupled biophysical and economic simulation models designed for integrated assessment of economic, technological, policy, and environmental changes at regional or global scales (e.g., Rosenzweig and Parry, 1994; Fischer et al., 2002; Hermans et al., 2010; Nelson et al, 2010).
AgMIP aims to utilize intercomparisons of these various types of methods to improve crop and economic models and ensemble projections and to produce enhanced assessments by the crop and economic modeling communities researching climate change agricultural impacts and adaptation.
The following map shows the locations of AgMIP participants.