The Effects of Catastrophic Wildfires on Vegetation and Fuel Loads in the Sierra Nevada of California
In recent years, a number of catastrophic wildfires have fundamentally changed species composition and structure across a large area of the Sierra Nevada of California. These fires leave behind many large, severely burned patches of land where the majority of trees have died. To make informed management decisions, forest managers need to understand the long-term effects of these fires on vegetation recovery and fuel loading. Large patches without trees might not reforest on their own which can cause forest loss; and, high-severity fires may lead to other high-severity fires by increasing the amount of fuel available to burn. Such repeat fires could lower the odds of any postfire forest recovery.
By including data from older fires, this project expands on an ongoing project that has been documenting conditions shortly after wildfires. Using these data, the project team will develop models to predict how vegetation and fuel levels change over time after fire. Such models can predict where forests are unlikely to recover, and where and when fuel levels could become dangerous. Management partners can use this information to make informed decisions about whether intervention is needed, where and when it is needed, and how to intervene (for example, through fuels reduction treatments or the planting of tree seedlings).
- Source: USGS Sciencebase (id: 654dbf4cd34ee4b6e05c312e)
In recent years, a number of catastrophic wildfires have fundamentally changed species composition and structure across a large area of the Sierra Nevada of California. These fires leave behind many large, severely burned patches of land where the majority of trees have died. To make informed management decisions, forest managers need to understand the long-term effects of these fires on vegetation recovery and fuel loading. Large patches without trees might not reforest on their own which can cause forest loss; and, high-severity fires may lead to other high-severity fires by increasing the amount of fuel available to burn. Such repeat fires could lower the odds of any postfire forest recovery.
By including data from older fires, this project expands on an ongoing project that has been documenting conditions shortly after wildfires. Using these data, the project team will develop models to predict how vegetation and fuel levels change over time after fire. Such models can predict where forests are unlikely to recover, and where and when fuel levels could become dangerous. Management partners can use this information to make informed decisions about whether intervention is needed, where and when it is needed, and how to intervene (for example, through fuels reduction treatments or the planting of tree seedlings).
- Source: USGS Sciencebase (id: 654dbf4cd34ee4b6e05c312e)