The Impact of CO2-Driven Vegetation Changes on Wildfire Risk

While wildfires are a key component of natural ecological restoration and succession, they also pose tremendous risks to human life, health, and property. Wildfire frequency is expected to increase in many regions as the radiative effects of elevated CO2 drive warmer surface air temperatures, earlier spring snow melt, and more frequent meteorological drought. However, high CO2 concentrations will also directly impact vegetation growth and physiology, potentially altering wildfire characteristics through changes in fuel amount and surface hydrology. Depending on the biome and time of year, these vegetation-driven responses may mitigate or enhance radiative-driven wildfire changes. In this study, we use a suite of earth system models from the Coupled Model Intercomparison Project 5 with active biogeophysics and biogeochemistry to understand how the vegetation response to high CO2 (CO2 quadrupling) contributes to future changes in wildfire risk across the globe. Across the models, projected CO2 fertilization enhances aboveground biomass (about a 30% leaf area index (LAI) increase averaged across the globe) during the spring and summer months, increasing the availability of wildfire fuel across all biomes. Despite greater LAI, models robustly project widespread reductions in summer season transpiration (about -15% averaged across the globe) in response to reduced stomatal conductance from CO2 physiological forcing. Reduced transpiration warms summer season near surface temperatures and lowers relative humidity across vegetated regions of the mid-to-high latitudes, heightening the risk of wildfire occurrence. However, as transpiration goes down in response to greater plant water use efficiency, a larger fraction of soil water remains in the soil, potentially halting the spread of wildfires in some regions. Given the myriad ways in which the vegetation response to CO2 may alter wildfire risk, and the robustness of the responses across models, an explicit simulation of the wildfire response to CO2-driven vegetation change with the Community Earth System Model will be presented. The results suggest that many atmosphere-centric statistical wildfire metrics do not capture the many processes that will shape future wildfire risk in a high CO2 world and highlight the need for process-based fire modeling.