Mapping tomorrow’s coffee-growing conditions to manage climate risk in Africa
Why do farmers need tools to track changing crop hardiness zones?
The project has moved beyond describing climate risks to delivering a working tool for coffee hardiness zones mapping and data visualization through which users can explore where coffee-growing conditions are changing. Its principal achievement is making research more accessible and relevant to decisions about agricultural resilience, rather than leaving climate and crop information in separate technical datasets.
For farmers and cooperatives, the tool offers a basis for understanding exposure and exploring adaptation options. For policymakers, NGOs and supply-chain organisations, it provides a foundation for regional vulnerability assessment and more targeted resilience investment. These are intended applications: the available evidence demonstrates delivery of the prototype, not yet measured changes in farm productivity, incomes or investment decisions.
The project directly supports NCIT’s ambition to bring nature and climate considerations into decision-facing environments, connecting two of its strategic priorities:
- Food Systems: supporting more climate-resilient approaches to agricultural production and strengthening the evidence available for adaptation across food value chains.
- Digital Tech & AI: translating environmental information into an accessible digital tool designed to support informed climate action. The demonstrated output is a mapping and visualisation prototype; its value should not depend on claiming AI capabilities that have not been documented.
How does the interactive map visualize climate impacts on coffee crops?
The project translated climate and crop-growing information into an accessible, map-based tool through three connected activities:
- Defining species-specific growing conditions: distinguishing Arabica and Robusta requirements, including temperature, precipitation and elevation ranges.
- Mapping changes over time: bringing environmental data into an interactive platform that allows users to explore changes in suitable growing areas, with the published Arabica visualisation covering 2002–2024.
- Connecting research to decisions: presenting the findings around practical questions facing farmers, cooperatives and public-sector organisations, including planting locations, exposure at existing production sites and priorities for adaptation investment.
Who are the key partners involved in the Shifting Crop Hardiness Zones project?
- The University of Exeter’s Nature and Climate Impact Team (NCIT) provides research-impact and development support, with key contributions from Senior Research Impact Fellow Josh Ayers and Dr. Marcos de Oliveira Jr.
- Food Systems AI Innovation Interns contributed directly to developing and refining the mapping prototype alongside NCIT staff.
- Philanthropic support from André and Rosalie Hoffmann enables NCIT’s wider programme of research-led interventions.
What are the key results of the crop mapping prototype?
- The digital prototype maps changing growing conditions across three countries: Kenya, Ethiopia, and Uganda.
- The visualization covers two specific coffee species: Arabica and Robusta.
- The interactive mapping tool visualizes historical data for Arabica coffee growing areas from 2002 to 2024.
- The delivered output is a publicly accessible digital prototype featuring interactive mapping and growing-area visualization.
- The prototype calculates suitability using species-specific environmental inputs, including temperature, precipitation, and elevation.
Next steps
The current development pathway focuses on enriching the underlying datasets, expanding geographic coverage and exploring application to cacao. The work also establishes a platform for wider application. NCIT has identified additional datasets, expanded coffee coverage and potential extension to cacao as the next steps, creating a pathway from a focused coffee prototype towards broader climate-vulnerable crop analysis. These remain development priorities rather than completed results.