The Risks and Consequences of Catastrophic Wildfires on the Conifer Forests of the Sierra Nevada of California

Forests in California’s Sierra Nevada have become increasingly vulnerable to wildfires due to fire suppression practices, elevated tree mortality and warming temperatures. With these fires growing in severity, these forests are struggling to recover on their own, creating landscapes that are more susceptible to future fires and increased forest loss. Researchers supported by this Southwest CASC project will create resources that will estimate fuel amounts and accumulation rates as well as identify areas where forests are least likely to recover. These efforts will inform decision makers in the most effective intervention methods to protect the future of the forests.  

As a consequence of fire suppression practices, elevated tree mortality, and warming temperatures, forests in the Sierra Nevada of California have become increasingly vulnerable to wildfires of a size and severity well outside the historical norm. Such fires can fundamentally alter the vegetation on the landscape, leaving behind many large, severely burned patches where the majority of trees have died and where forests may not recover on their own. Furthermore, due to the numerous trees killed by fire, fuels can quickly re-accumulate, leading to future high severity fires that further increase the risk of forest loss. 

Faced with both the risks and the consequences of these wildfires, forest managers are tasked not only with attempting to minimize their probability of their occurrence but also with managing the substantially altered landscapes that remain when they do occur. To make informed decisions about where to target treatments, forest managers need landscape-level fuels maps that are also accurate at a management-relevant scale. And, in areas where these fires have already burned, they need information on how rapidly fuels will re-accumulate and where natural forest recovery is least likely. 

This project will create a growing plot network that encompasses both unburned forests and areas that have burned in large wildfires over the course of the last two decades. Using data from these plots, the project team will develop empirical models that estimate fuels at landscape scales; predict the rate at which fuels re-accumulate after wildfire; and identify areas on the landscape where forests are least likely to recover. This will allow forest managers to make informed decisions about whether intervention is needed, where and when it is needed, and the most effective intervention methods to use.