Relating Fire-Caused Change in Forest Structure to Remotely Sensed Estimates of Fire Severity

摘要

Fire severity maps are an important tool for understanding fire effects on a landscape. The relative differenced normalized burn ratio (RdNBR) is a commonly used severity index in California forests, and is typically divided into four categories: unchanged, low, moderate, and high. RdNBR is often calculated twice—from images collected the year of the fire (initial assessment) and during the summer of the year after the fire (extended assessment). Both collection times have been calibrated to field measurements, but field data with both pre-fire and post-fire observations of matched plots are typically not available. This study uses a large network of field plots (n = 175) that was surveyed the year of and one year after a large wildfire in the central Sierra Nevada, USA, to quantify forest structure, mortality, and fire effects within fire severity categories from both the initial and extended RdNBR assessments. Most plots were classified in the same severity category in both assessments, particularly when mortality was high. Comparing initial and extended assessments, plots with lower pre-fire basal area were more likely to be classified at lower severity in the extended assessment, while plots with greater tree density were more likely to be classified at higher severity. High-severity plots had significantly greater pre-fire density of small trees. The high-severity category clearly captured stand-replacing fire effects (95% basal area mortality, 99% tree density mortality), with typically all trees exhibiting high levels of crown consumption and scorching. In other severity categories, most large-sized and intermediate-sized trees survived, and moderate-severity fire favored survival of shade-intolerant species. Results suggest that both the initial and extended RdNBR assessments give an accurate representation of forest structural change in mixed-conifer forests following fire, particularly those of high severity.