First Advisor

Andrés Holz

Term of Graduation

January 2025

Date of Publication

1-1-2025

Document Type

Thesis

Language

English

Subjects

Abies, Douglas-fir, Drought, Forest Management, Remote Sensing, Southwest Oregon

Physical Description

1 online resource ( pages)

Abstract

Increased levels of Pseudotsuga menziesii (DF) and Abies species (TF) decline throughout dry forests in the Klamath Mountains and Western Cascades ecoregions have been recorded in recent years, with preliminary evidence suggesting that factors influenced by changing climatic conditions and encroachment from fire suppression policies are primarily to blame. Yet, the physiological and environmental mechanisms of drought-driven tree decline are poorly understood across biophysical and spatial gradients. Given the complex relations that drive decline, determining the degree of influence of specific drivers is difficult, creating unique challenges for modern forest management. To elucidate the most important factors driving DF and TF decline, we trained two species-specific machine-learning models using a binary response variable generated from an annualized Landsat-based vegetation loss model (BugNet) and a variety of abiotic and biotic environmental predictor variables. Both models generalized well to the data and a had strong predictive performance, but failed to account for a significant portion of the observed deviance. Across both species classes, we found canopy height to be the strongest predictor of tree decline throughout the study area, followed closely by basal-area density. These variables showed significant interactions with the sampled growing conditions (i.e. topography, elevation, climate normals, etc.) and broadened our understanding of the drivers and covariates behind observed mortality. These results indicate that adaptive management strategies and restoration activities throughout the region should consider species and site-specific growing conditions for improving forest resilience to increasing warming and drying conditions.

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Available for download on Saturday, June 27, 2026

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