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Keyword: multivariate analysis

Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

Publications Posted on: August 01, 2018
Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building.

Using canonical correlation analysis to identify environmental attitude groups: Considerations for national forest planning in the southwestern U.S

Publications Posted on: November 13, 2017
As public land management agencies pursue region-specific resource management plans, with meaningful consideration of public attitudes and values, there is a need to characterize the complex mix of environmental attitudes in a diverse population. The contribution of this investigation is to make use of a unique household, mail/ internet survey data set collected in 2007 in the Southwestern United States (Region 3 of the U.S. Forest Service).

The smell of environmental change: Using floral scent to explain shifts in pollinator attraction

Publications Posted on: July 19, 2017
As diverse environmental changes continue to influence the structure and function of plant-pollinator interactions across spatial and temporal scales, we will need to enlist numerous approaches to understand these changes.

Introduction to uses and interpretation of principal component analyses in forest biology.

Publications Posted on: May 12, 2016
The application of principal component analysis for interpretation of multivariate data sets is reviewed with emphasis on (1) reduction of the number of variables, (2) ordination of variables, and (3) applications in conjunction with multiple regression.

Effects of fire exclusion on forest structure and composition in unlogged ponderosa pine/Douglas-fir forests

Publications Posted on: July 19, 2007
Research to date on effects of fire exclusion in ponderosa pine (Pinus ponderosa) forests has been limited by narrow geographical focus, by confounding effects due to prior logging at research sites, and by uncertainty from using reconstructions of past conditions to infer changes.