Document: CHA-3-40-22

Montane and subalpine meadows of the Three Sisters Wilderness Area/Biosphere Reserve, Oregon: A community classification and gradient analysis.

HALPERN, C.B.*

University of Washington, Seattle, WA 98195-2100 USA 1

Abstract:
Meadows occupy a small portion of the largely forested central Cascade region, but support a large proportion of the regional flora. Despite the ecological importance and aesthetic value of these non-forested ecosystems, there have been few studies of their composition, distribution, and environmental correlates. I present a plant community classification and gradient analysis of the montane and subalpine meadow vegetation of the Three Sisters Wilderness Area, Oregon, a UNESCO Biosphere Reserve representing the northern half of the Sierra-Cascade Province. Species composition and environmental data were collected in 152 plots representing a broad array of elevations, landforms, and hydrologic conditions; many of these sites had experienced sheep grazing during the early to middle portion of the 20th century. Classification (TWINSPAN) and direct (CCA) and indirect (DCA) gradient analyses were used to define 21 plant communities and to describe and interpret relationships with measured environmental variables. Among the full array of plots, ordination axes were strongly correlated with elevation, slope, and various landform attributes. Ordinations of subsets of the data revealed strong associations with topographic position (lower slopes to ridgetops in the montane zone), and microtopographic variables that influence the duration of snowpack and seasonal availability of soil moisture (in the subalpine zone). Although gradient analyses suggest strong environmental controls on community composition, effects of intensive grazing on floristic composition are still evident at some locations.

Keywords: Pacific Northwest vegetation, meadow communities, ordination, classification, gradient analysis

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This abstract is being presented at: 3:30 PM in session:
Poster Session #17: Vegetative Analysis.