Type of Document	Master's Thesis
Author	Slyder, Jacob Brake
Author's Email Address	slyder@vt.edu
URN	etd-05072012-142254
Title	Population Structure and Biophysical Density Correlates of Whitebark Pine (Pinus albicaulis) at Two Treelines in the Northern Rocky Mountains
Degree	Master of Science
Department	Geography
Advisory Committee	Advisor Name Title Resler, Lynn M. Committee Chair Kennedy, Lisa M. Committee Member Thomas, Valerie A. Committee Member
Keywords	regeneration alpine treeline ecotone Pinus albicaulis white pine blister rust population structure
Date of Defense	2012-04-27
Availability	restricted
Abstract This study analyzes the structure and biophysical correlates of density of two whitebark pine (Pinus albicaulis) populations in the northern Rocky Mountains. Whitebark pine is a keystone species and an important component of treeline ecosystem dynamics; however, subalpine populations have declined nearly rangewide in recent decades. Though declines in subalpine forests have been well documented in the literature, few studies have assessed population structure and habitat requirements at treeline. Various disturbances have combined to impact whitebark pine populations across its range, but the primary threat at treeline sites in the northern Rocky Mountains is white pine blister rust, caused by the exotic fungal pathogen Cronartium ribicola. In this study, I aim to: 1) assess population structure and regeneration within two geographically different treelines experiencing contrasting levels of infection, and 2) examine associations among several biophysical variables and whitebark pine density to better understand treeline habitat variability and regeneration patterns. I used density-diameter curves and non-parametric Kruskal-Wallis tests to compare population structure between sites, and developed generalized linear mixed models to assess correlations between whitebark pine density and biophysical site variables. The results demonstrate that despite very different ecosystems and blister rust infection rates, our two study sites have similar population structure. Our model results highlight marked differences between populations in terms of biophysical correlates of density. While correlations are similar within site, seedlings and saplings have stronger correlations with biophysical variables than established trees.
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