Insights into Fire Severity and Post-Fire Recovery from an Integrated Analysis of Forestry Inventory Data and Long-Term Fire Mapping Datasets
Location
USU Eccles Conference Center
Event Website
http://www.restoringthewest.org
Abstract
Plot data from the Forest Inventory and Analysis (FIA) Program can be combined with spatially explicit polygon data from the Monitoring Trends in Burn Severity (MTBS) Program to provide insights into fire effects, fire severity, and long-term recovery in forested areas. MTBS delineates two main products: burned-area polygons that provide a census of large fires from 1984 to the present, and severity layers with 30-m resolution, where each pixel is classified into one of four major severity classes, ranging from very low or unburned to high-severity fire. We spatially intersected FIA’s plot data with both MTBS datasets to quantify fire effects in three ways. First, a characterization of burned areas throughout our 8-state study area showed that 41% of the acreage of large fires since 1984 burned on forest land, and the most commonly burned stands were in ponderosa pine, lodgepole pine, and Douglas-fir forest types. Nearly 35% of post-fire plots had no live basal area of trees ≥5” diameter remaining. Second, we examined the relationship between time since fire and basal area, seedling density, and sapling density at FIA plots. Survivor trees experienced low post-fire mortality rates, and almost half of post-fire dead basal area persisted for up to 25 years after fire. Seedling density peaked 5 to 10 years after fire, while sapling density increased steadily for at least 25 years post-fire. Third, we identified FIA plots that were measured both pre-fire and post-fire, and then compared mean post-fire reductions in live basal area by MTBS severity class. Plots that experienced high-severity fire had higher pre-fire basal area than plots that burned at lower intensities. At a regional scale, post-fire reductions in live basal area were significantly different across the four MTBS severity classes, although severity classes were less distinguishable for individual forest types.
Insights into Fire Severity and Post-Fire Recovery from an Integrated Analysis of Forestry Inventory Data and Long-Term Fire Mapping Datasets
USU Eccles Conference Center
Plot data from the Forest Inventory and Analysis (FIA) Program can be combined with spatially explicit polygon data from the Monitoring Trends in Burn Severity (MTBS) Program to provide insights into fire effects, fire severity, and long-term recovery in forested areas. MTBS delineates two main products: burned-area polygons that provide a census of large fires from 1984 to the present, and severity layers with 30-m resolution, where each pixel is classified into one of four major severity classes, ranging from very low or unburned to high-severity fire. We spatially intersected FIA’s plot data with both MTBS datasets to quantify fire effects in three ways. First, a characterization of burned areas throughout our 8-state study area showed that 41% of the acreage of large fires since 1984 burned on forest land, and the most commonly burned stands were in ponderosa pine, lodgepole pine, and Douglas-fir forest types. Nearly 35% of post-fire plots had no live basal area of trees ≥5” diameter remaining. Second, we examined the relationship between time since fire and basal area, seedling density, and sapling density at FIA plots. Survivor trees experienced low post-fire mortality rates, and almost half of post-fire dead basal area persisted for up to 25 years after fire. Seedling density peaked 5 to 10 years after fire, while sapling density increased steadily for at least 25 years post-fire. Third, we identified FIA plots that were measured both pre-fire and post-fire, and then compared mean post-fire reductions in live basal area by MTBS severity class. Plots that experienced high-severity fire had higher pre-fire basal area than plots that burned at lower intensities. At a regional scale, post-fire reductions in live basal area were significantly different across the four MTBS severity classes, although severity classes were less distinguishable for individual forest types.
https://digitalcommons.usu.edu/rtw/2015/Oct29/7
Comments
Sara Goeking is a Biological Scientist, Forest Service, Rocky Mountain Research Station, Inventory and Monitoring Program.