Fire is a complicated process that affects forests in diverse ways. Current methods for predicting fire effects on forests still largely rely on past observations rather than a deep understanding of how fire interacts with a forest environment.
In order to more fully understand fire’s effect on an ecosystem, wildland fire must be viewed as a biophysical process – a process that directly links fire’s transfer of energy to impacts on organisms and the environment.
Recent technological advances have enabled the study of wildland fire in a biophysical sense. USDA Forest Service research ecologist Joseph O’Brien, along with collaborator Louise Loudermilk and others, reviewed new technology and highlighted its most pressing applications to fire ecology. The review was published in the journal Current Forestry Reports.
“You can think of the energy released by a fire as a dose. If you don’t measure the dose of energy, it’s hard to predict what the fire’s effects will be,” says O’Brien, who argues that the field of fire ecology must embrace fire as a complicated physical process – not an event. “Especially in prescribed burns, what we’ve learned is that a fire’s heterogeneity matters. If you do not capture the details, you cannot solve any complicated problems.”
The effects of wildland fires are often predicted using modeling software. Traditionally, the field of fire ecology has used predictive empirical models – models that use known outcomes of similar past fires to forecast a result.
O’Brien argues that the field must move toward the use of mechanistic models – those that consider physical processes of fire to calculate a result. Examples of physical processes include the movement of buoyant smoke and the consumption of fuel in the complex structure of a forest.
New insights derived from considerations of physical mechanisms can help scientists understand how and why a forest ecosystem will be affected by a fire.
Tools such as LiDAR can capture 3D characteristics of a forest across a variety of scales. Other tools like infrared thermal imagery can help track the movement of heat and heated tissue throughout a forest. These tools, only recently introduced to the field of fire ecology, are critical to the mechanistic study of forest fires – they capture highly precise, detailed data. When studying things like the movement of heat through a forest, having a good understanding of the fine-scale forest structure is critical.
These tools, combined with mechanistic models, can enable fire ecologists to understand the effects of fires in targeted locations of a forest. One example is the movement of heat through soils, where it is extremely difficult to make useful measurements.
Another is fire-atmosphere dynamics in the crown area of a canopy – now possible to study using LiDAR modeling. Study of fire’s effects on specific parts of trees improves fire ecologists’ understanding of how fire contributes to tree mortality.
“We eventually want to predict how fire affects forests in a meaningful way,” says O’Brien. He has worked on research teams to create mechanistic models such as QUIC-fire – a model that is “useful for looking at ignition patterns and key fire behaviors to expect.” These newer models will allow forest managers to effectively use fire to manage both forest health and public safety.
Being able to predict tree mortality pre- and post-fire is primary goal for fire managers. This will require a widespread shift to physics-based models that carefully predict movements of fire and energy throughout a forest – and this shift will not be easy. The future of fire ecology lies in interdisciplinary research teams combining knowledge of ecology with physics expertise.
For more information, email Joseph O’Brien at email@example.com