Examining Drivers of Post-Wildfire Vegetation Dynamics Across Multiple Scales Using Time-Series Remote Sensing
AuthorCasady, Grant M.
AdvisorMarsh, Stuart E.
Committee ChairMarsh, Stuart E.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractEcosystem response to disturbance is a function of environmental factors interacting at a number of spatio-temporal scales. This research explored ecosystem response to wildfire as a function of local and broad-scale environmental factors using satellite based time-series remote sensing data. This topic was explored as a series of three independent but related studies. The first study focused on the evaluation of techniques for the analysis of time-series satellite data for describing post-fire vegetation trends at sites in the US, Spain, and Israel. Time-series data effectively described post-fire trends, and reference sites were valuable for differentiating between post-fire effects and other environmental factors. The use of phenological indicators derived from the time-series shows promise as a monitoring tool, but requires further investigation. The next study evaluated the influence of broad-scale climate factors on rates of post-fire vegetation regeneration across the western US. Rates of post-fire regeneration were higher with increased precipitation and higher minimum temperatures. Changes in climate are likely to result in shifts in post-fire vegetation dynamics, leading to important feedbacks into the climate system. The use of time-series data was a valuable tool in measuring trends in post-fire vegetation across a large area and over an extended period. The final study used time-series vegetation data to measure variations in post-fire vegetation response across an extensive 2002 wildfire. Regression tree analysis related post-fire regeneration to local environmental factors such as burn severity, soil properties, vegetation, and topography. Residuals from modeled rates of post-fire regeneration were evaluated in the context of management activities and site characteristics using expert knowledge. Post-fire rates of regeneration were a function of water availability, pre-burn vegetation, and burn severity. Management activities, soil differences, and shifts in vegetation community composition resulted in deviations from the modeled post-fire regeneration rates. The results of these three research studies indicate that remotely sensed time-series vegetation data provide a useful tool for measuring post-fire vegetation dynamics. Both broad-scale and local environmental factors play important roles in defining post-fire vegetation response, and the use of remote sensing and geospatial data sets can be useful in integrating these factors and enhancing management decisions.
Degree ProgramArid Lands Resource Sciences