This study develops a micro-level Ricardian model to assess how long-run climate patterns affect agricultural land values across the urban-rural gradient in the Chesapeake Bay Watershed. Using an 8-km gridded dataset that combines farmland prices, high-resolution climate data, and urban land cover, the analysis shows that seasonal temperature and precipitation affect land values nonlinearly, and urbanization significantly moderates the effects of precipitation. A climate simulation suggests heterogeneous impacts across urban grids. Our findings highlight the critical role of urban land cover in shaping climate adaptation strategies, offering new insights into how transitional urban-agricultural regions respond to climate stress. These results provide actionable guidance for policymakers seeking to enhance agricultural resilience in the face of continued urban expansion.
Urban areas change local climates by trapping heat, altering rainfall, and changing how water moves. These changes can affect nearby farms, influencing crops, soil moisture, and land value. We studied farmland in the Chesapeake Bay region to see how long‐term temperature and rainfall affect land prices, and how these effects change near cities. Using detailed data and models, we found that farmland values rise with warm growing seasons and summer/fall rain but drop with extreme heat, warm winters, or heavy winter rain. Near cities, spring rain helps less, but winter rain is less harmful, likely due to changes in water drainage. In a scenario with 3°F warming and more rain, only 15% of areas gained value, while most lost value. Our results show climate change impacts farmland differently depending on urbanization, offering insights for better policies to protect agriculture in growing cities.
© 2025 The Author(s). Journal of Environmental Quality © 2025 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.