Forest Sciences Commons^™

A Comparison Of Wildfire Adaptive Traits In Juvenile Conifers Of The Northern Rockies, Andie Sonnen

Undergraduate Theses, Professional Papers, and Capstone Artifacts

Wildfire is an importance disturbance that continues to shape the ecosystems of the northern Rockies through varying patterns of frequency and intensity. Due to historical fire suppression and the hotter and drier conditions brought upon by anthropogenic climate change, wildfire frequency and intensity is increasing. These increases will alter vegetation structure and composition, but the degree to which is unknown.

Individual plant traits can offer insight into how these vegetation communities will shift, especially the particular traits that reduce fire-related mortality. To survive wildfires, juvenile northern conifers employ two strategies: increasing their bark thickness and increasing their crown height. To …

Ecological Effects Of Prescribed Burning, Mechanical Cutting, And Post-Treatment Wildfire For Restoration Of Pinus Albicaulis, Enzo Paolo Martelli Moya

Graduate Student Theses, Dissertations, & Professional Papers

The field of ecological restoration is growing rapidly, increasing the need for reliable and generalizable information on the impacts of management interventions aimed to be restorative. Prescribed burning and mechanical cutting have been proposed as primary strategies for restoration. However, there is limited information on their efficacy and effects in subalpine forest types, suggesting that monitoring to inform adaptive management is a priority need. I used data from a 15-year, replicated before-after-control-impact (BACI) study on Pinus albicaulis (whitebark pine) restoration to assess the ecological effects of prescribed burning and mechanical cutting, with and without subsequent unplanned wildfire, as well as …

Lidar-Landsat Covariance For Predicting Canopy Fuels, Margaret D. Epstein

Graduate Student Theses, Dissertations, & Professional Papers

Managing wildfires in the western United States is becoming increasingly complex. Visualizing and quantifying canopy structures allows fire managers to both plan for fire and track recovery. Light detecting and ranging, or LiDAR can measure forests in three dimensions, but has limited spatial and temporal coverage. LiDAR-Landsat covariance uses machine learning to fill in the spatial and temporal gaps of LiDAR coverage with supplemental Landsat imagery. However, in order to capture real forest dynamics, a model needs to be stable enough to detect long term trends, sensitive to episodic disturbance, and general enough to work on multiple landcovers. The purpose …