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An abstract of the Rockefeller Foundation supported Project under the Climate Smart for Rural
                                           Development Initiative
Project Title: Prioritizing Investments in Food Security under a Changing Climate
Grant number 2008 CLI 301
Name of the Organization: Stanford University
Country: USA
Name of the Contact Person: David Lobell
Email: dlobell@stanford.edu
Telephone: +1-650-721-6207

Key Objectives

   1. Assessing climate threats to staple crops by 2030, at a country level.
   2. Determining the relative importance of climate and crop models as a source of uncertainty.
   3. Determining “climate-agriculture analogues” in 2050 and 2100.
   4. Getting data on agricultural production and consumption in an easily usable and publicly available
      form.
   5. Translating crop productivity impacts into food security and/or poverty impacts.

Key Activities

   1. Work with organizations in Africa to compile data on past crop production at various scales,
      including field, state, and country level
   2. Apply statistical modeling techniques to these datasets to understand crop responses to climate
   3. Use process-based crop models as a comparison with statistical models
   4. Access climate projections for Africa and apply crop models to identify impacts and associated
      adaptation needs over the next few decades
   5. Work with economic models to translate impacts into poverty or food security measures.

Key Deliverables

   1. Country-level information on impacts for main crops, and existing analogues in different parts of
      Africa, and other parts of the world where possible and appropriate.
   2. Finer scale projections where possible.
   3. Peer-reviewed scientific publications that give a clear description of the methods, results, and
      sources of uncertainties.

Expected Outcomes

   1. A more robust and quantitative understanding of how climate change will affect agriculture in
      Africa over the next few decades.
   2. Identification of key regions in need of rapid adaptation efforts.
   3. Where possible, insights into which adaptation measures are likely to be most effective.

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Stanford university

  • 1. An abstract of the Rockefeller Foundation supported Project under the Climate Smart for Rural Development Initiative Project Title: Prioritizing Investments in Food Security under a Changing Climate Grant number 2008 CLI 301 Name of the Organization: Stanford University Country: USA Name of the Contact Person: David Lobell Email: dlobell@stanford.edu Telephone: +1-650-721-6207 Key Objectives 1. Assessing climate threats to staple crops by 2030, at a country level. 2. Determining the relative importance of climate and crop models as a source of uncertainty. 3. Determining “climate-agriculture analogues” in 2050 and 2100. 4. Getting data on agricultural production and consumption in an easily usable and publicly available form. 5. Translating crop productivity impacts into food security and/or poverty impacts. Key Activities 1. Work with organizations in Africa to compile data on past crop production at various scales, including field, state, and country level 2. Apply statistical modeling techniques to these datasets to understand crop responses to climate 3. Use process-based crop models as a comparison with statistical models 4. Access climate projections for Africa and apply crop models to identify impacts and associated adaptation needs over the next few decades 5. Work with economic models to translate impacts into poverty or food security measures. Key Deliverables 1. Country-level information on impacts for main crops, and existing analogues in different parts of Africa, and other parts of the world where possible and appropriate. 2. Finer scale projections where possible. 3. Peer-reviewed scientific publications that give a clear description of the methods, results, and sources of uncertainties. Expected Outcomes 1. A more robust and quantitative understanding of how climate change will affect agriculture in Africa over the next few decades. 2. Identification of key regions in need of rapid adaptation efforts. 3. Where possible, insights into which adaptation measures are likely to be most effective.