Next Generation Fire Modeling to Inform the Management of Climate and Fire Driven Ecological Transformations in the Rio Grande Basin
The warming climate combined with a century of fuel build up (i.e. burnable plant materials found in the forest) due to fire suppression are driving megafires that threaten life and property and are severely altering ecosystems. Many of these fires are converting large areas of forest to shrub fields or grasslands, termed “ecological transformations.” Although uncharacteristically severe fires are contributing to these changes, lower intensity fire is a key ecological process that sustains native ecosystems, increases ecological resilience, and guides climate change adaptation. Planned fires (e.g., prescribed fire) are the most efficient management activity that can be performed at scales large enough to address the problem of megafires and related ecological transformations. A better understanding of the range of current and potential future fire behaviors is necessary to safely and effectively increase the scale and desired outcomes of prescribed fire. Unfortunately, commonly available fire simulation models are overwhelmed by uncertainty in novel fire environments.
The goal of the project is to apply advanced, mechanistic fire modeling to increase understanding of ecological transformations in the Rio Grande Basin and identify pathways for managing these changes through proactive fire management. This project combines high-resolution 3D vegetation inputs with physics-based coupled-fire-atmosphere modeling to predict fire behavior and fire effects in forests vulnerable to ecological transformation. The resulting information on the amount of plant materials burned and damage to trees can then be incorporated into decisions related to future fire and vegetation management.
It is anticipated that results from this project will provide safer ranges of conditions for prescribed fire and predictions of fire behavior in novel fuels, like shrub fields created by high-severity fire. Smoke and embers, both crucial to safe prescribed fire application, are inherent to these advanced models. These results will enhance the use of fire to meet management objectives and promote resilience to climate change.
- Source: USGS Sciencebase (id: 625ed404d34e85fa62b7f7c6)
The warming climate combined with a century of fuel build up (i.e. burnable plant materials found in the forest) due to fire suppression are driving megafires that threaten life and property and are severely altering ecosystems. Many of these fires are converting large areas of forest to shrub fields or grasslands, termed “ecological transformations.” Although uncharacteristically severe fires are contributing to these changes, lower intensity fire is a key ecological process that sustains native ecosystems, increases ecological resilience, and guides climate change adaptation. Planned fires (e.g., prescribed fire) are the most efficient management activity that can be performed at scales large enough to address the problem of megafires and related ecological transformations. A better understanding of the range of current and potential future fire behaviors is necessary to safely and effectively increase the scale and desired outcomes of prescribed fire. Unfortunately, commonly available fire simulation models are overwhelmed by uncertainty in novel fire environments.
The goal of the project is to apply advanced, mechanistic fire modeling to increase understanding of ecological transformations in the Rio Grande Basin and identify pathways for managing these changes through proactive fire management. This project combines high-resolution 3D vegetation inputs with physics-based coupled-fire-atmosphere modeling to predict fire behavior and fire effects in forests vulnerable to ecological transformation. The resulting information on the amount of plant materials burned and damage to trees can then be incorporated into decisions related to future fire and vegetation management.
It is anticipated that results from this project will provide safer ranges of conditions for prescribed fire and predictions of fire behavior in novel fuels, like shrub fields created by high-severity fire. Smoke and embers, both crucial to safe prescribed fire application, are inherent to these advanced models. These results will enhance the use of fire to meet management objectives and promote resilience to climate change.
- Source: USGS Sciencebase (id: 625ed404d34e85fa62b7f7c6)