Date of Award

Spring 1-1-2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Geography

First Advisor

Thomas T. Veblen

Second Advisor

Waleed Abdalati

Third Advisor

Tania Schoennagel

Fourth Advisor

Stefan Leyk

Fifth Advisor

Nichole Barger

Abstract

Forests characterized by mixed-severity fire regimes (MSFR) exhibit high spatio-temporal variability of fire frequency and severity. These forests comprise much of western North America, but their ecological dynamics, spatial ecology, resilience mechanisms, and biophysical drivers are poorly understood. MSFR forests provide rich spatio-temporal data that predate landscape changes and alterations to disturbance regimes that have occurred since Euro-American colonization. However, the relative scarcity of large historical datasets and some persistent methodological limitations have impeded robust reconstructions of historical MSFRs, creating substantial debate and confusion. We address these problems by developing an extensive dataset of dendroecological records and geospatial maps of historical forest conditions for MSFR forests in seven watersheds across two distinct study regions in the northern U.S. Rockies. We develop a framework for scaling dendroecological reconstruction methods along the fire regime gradient that accounts for the increasing loss and spatial bias of historical data that occurs for MSFRs. We use this approach to reconstruct spatio-temporal patterns of fire severity-mediated dynamics for a subset of forest patches throughout each watershed. These data reveal novel landscape dynamics and a resilience mechanism to high severity fire that has not been previously documented. Finally, we use the dendroecological records as a validation dataset to develop a calibrated structure-based fire severity model based on the photo-interpreted structural attributes and patch boundaries in our geospatial maps. The resulting model reveals complex relationships between forest structures and fire severity history, but provides a relatively strong method for reconstructing spatial patterns of fire-severity-mediated dynamics across a range of scales, from plots to patches to landscapes. This model represents one of the most robust and unique tools for examining spatio-temporal patterns of historical MSFR forests to date.

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