Global climate change is expected to result in anywhere from two to four degrees of warming, with consequences for terrestrial ecosystems. The rate of climate change is disproportionally greater at high latitudes, resulting in landscape-scale effects on the composition, structure, and function of arctic and boreal ecology. Remote sensing offers scientists the ability to track large-scale changes through the detection of biophysical processes occurring in terrestrial ecosystems. In this research, I measured the response of boreal peatland ecosystems to a suite of different climate-related drivers including increased temperature, elevated carbon dioxide levels, and hydrologic change. Working within large-scale ecosystem manipulation experiments, I used passive remote sensing to measure the response of two different types of boreal peatlands, a rich fen and an ombrotrophic bog, to simulated climate change. Chapter 1 describes my research on the use of hyperspectral remote sensing to examine changes in the composition and biodiversity of peatlands in response to long-term experimental manipulation. Chapter 2 details my findings on using simple remote sensing techniques to detect changes in peatland ecosystem productivity in response to warming, elevated carbon dioxide, and hydrologic change. Through this work, I demonstrate that remote sensing can be used to characterize the response of a range of different ecosystem properties to global change.
University of Minnesota M.S. thesis. August 2017. Major: Natural Resources Science and Management. Advisors: Rebecca Montgomery, Michael Falkowski. 1 computer file (PDF); ix, 97 pages.
Response of boreal peatland ecosystems to global change: A remote sensing approach.
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