The RShiny application powered by these data enables communities to assess key aspects of food system resilience and empowers changemakers to invest in places that face outsized challenges to resilience, with a particular focus on communities of color. It is a preliminary tool that brings together diverse data sets on climate hazards, agricultural production, food security and access, and racial equity, that we aspire to build in future work through researcher and community feedback. The tool includes:

A “national map” tab, which shows areas with elevated climate hazards and food systems challenges. These maps look at the intersection of climate hazards that have strong impacts on local food systems, including wildfires, droughts, and floods and food security and agricultural production. This tab is useful for exploring where climate and food systems risks intersect and which counties face cumulative disadvantages in food system resilience.

A “county level data” tab, which shows data on food security and access, demographics, agricultural production, and climate hazards at the county-level. Users can toggle between looking at raw values or their county’s percentile rank relative to other counties. This tab is useful for exploring county-level data on factors that shape food system resilience to climate hazards and seeing how your county compares with all U.S. counties.

A “race-disaggregated data” tab, which shows county-level data on factors that shape food system resilience, disaggregated by race. Specifically, this tab includes data for differences in demographics, social ties, home values, homeownership, employment, poverty, agricultural production, and income by race and ethnicity. This tab is valuable for exploring differences within counties between populations to illustrate the landscape of varied risks by race and ethnicity.

The code is available for review in the public GitHub repository. See the technical appendix below for more information about the data and methodology.