Document Type
Dissertation - Open Access
Award Date
2013
Degree Name
Doctor of Philosophy (PhD)
Department / School
Geospatial Science and Engineering
First Advisor
Thomas Loveland
Abstract
Sagebrush (Artemisia spp.) ecosystems constitute the largest single North American shrub ecosystem and provide vital ecological, hydrological, biological, agricultural, and recreational ecosystem services. Disturbances continue to alter this ecosystem, with climate change possibly representing the greatest future disturbance risk. Improved ways to characterize and monitor gradual change in this ecosystem are vital to its future management. A new remote sensing sagebrush characterization approach was developed in Wyoming which integrates three scales of remote sensing to derive four primary continuous field components (bare ground, herbaceousness, litter, and shrub), and four secondary components (sagebrush, big sagebrush, Wyoming sagebrush, and shrub height) using a regression tree. An independent accuracy assessment of results revealed the primary component root mean square error values ranged from 4.90% to 10.16% for 2.4-m QuickBird, 6.01% to 15.54% for 30-m Landsat, and 6.97% to 16.14% for 56-m AWiFS. The change over time of five of these continuous field components (bare ground, herbaceous, litter, sagebrush, and shrub) was measured on the ground and by satellite across six seasons and four years to validate component change capability. Correlation of ground measurements to remote sensing predictions indicated that annual component predictions tracked ground measurements more closely than seasonal ones, and QuickBird predictions tracked ground measurements more closely than Landsat predictions. Correlation of component predictions to DAYMET precipitation revealed QuickBird components had better response to precipitation patterns than Landsat components. Further in-depth analysis of precipitation and component change patterns was completed from 1984 to 2011 for the same five components. A statistically significant correlation model between vegetation components and precipitation was established, and used to forecast vegetation components response in 2050 using IPCC precipitation scenarios. Bare ground increased under future scenarios, with the remaining components all decreasing. When 2050 future component results were applied to sage-grouse habitat models, a loss of about 12% of nesting habitat and 4% of summer habitat were predicted to occur. Results demonstrate the successful ability of sagebrush components to characterize the sagebrush ecosystem, monitor precipitation driven gradual change, support linear models to forecast future component response, and quantify future habitat impacts on sage-grouse.
Library of Congress Subject Headings
Sagebrush -- Ecology -- Remote sensing
Sage grouse -- Habitat -- Forecasting
Climatic changes -- Forecasting
Description
Includes bibliographical references
Format
application/pdf
Number of Pages
198
Publisher
South Dakota State University
Rights
Copyright © 2013 Collin G. Homer
Recommended Citation
Homer, Collin G., "Sagebrush Ecosystem Characterization, Monitoring, and Forecasting with Remote Sensing: Quantifying Future Climate and Wildlife Habitat Change" (2013). Electronic Theses and Dissertations. 1079.
https://openprairie.sdstate.edu/etd/1079
Included in
Climate Commons, Ecology and Evolutionary Biology Commons, Geographic Information Sciences Commons, Physical and Environmental Geography Commons, Remote Sensing Commons