Characterizing 30-years of conifer regeneration patterns in high-severity wildfires: a snow-cover remote sensing approach - Menick, Casey, author; Hoffman, Chad M., advisor; Tinkham, Wade T., advisor; Vanderhoof, Melanie K., committee member; Vogeler, Jody C., committee member (Colorado State University. Libraries, 2023)
The number of large, high-severity wildfires has been increasing across the Western United States. It is not fully understood how wildfire intensification may impact conifer forests of the West, whose resilience is dependent on successful seedling regeneration. It is important to understand how conifer-dominated forests are able to recolonize high-severity burn patches and subsequently respond to shifting disturbance regimes. The goal of our research is to characterize patterns of conifer recolonization within high-severity burn patches over a 30-year study period. We investigate 34 high-severity wildfire complexes that occurred between 1988 and 1991 in conifer-dominated ecosystems of the northern Rocky Mountains. Composite snow-cover Landsat imagery was utilized to isolate conifer-specific vegetation by diminishing spectral contributions from soil and deciduous vegetation. Conifer regeneration was determined to be detectable by Landsat 11-19 years post-fire across forest types and at >10% canopy cover using snow-cover imagery. The trajectory of snow-cover Landsat NDVI was utilized to project future recovery time to pre-fire conifer vegetation levels for lodgepole pine (29.5 years), Douglas-fir (36.9 years), and fir-spruce forests (48.7 years). The presence of conifer regeneration was then modeled at 3-year intervals post-fire to characterize the progression of recolonization. Conifer recolonization analysis showed that 65% of the total high-severity burn area was reforested after 30 years. Across all high-severity patches, median patch recolonization was 100% within lodgepole pine, 91.1% within Douglas-fir, and 41.3% within fir-spruce. Patch fragmentation occurred across all size classes and forest types, with the majority of the remaining unforested area in Douglas fir (76%), lodgepole pine (61%), and fir-spruce (50%) transitioning to smaller unforested patch size classes. While we identified overall patterns of conifer resilience, high-severity burn patches with lower likelihoods of 30-year conifer recovery had lower edge-densities, drier climates, steeper slopes, higher elevations, and fir-spruce forests. These findings have implications for climate change resilience and may be applied to support forest restoration decision-making following high-severity wildfire. Future analyses should be conducted using snow-cover remote sensing imagery to identify patterns of post-disturbance conifer recovery over a wider spatial and temporal extent.
Keywords: landsat; remote sensing; forest; wildfire; regeneration