Detecting changes in surface moisture and water table position with spectral changes in surface vegetation in northern peatlands

Due to warmer and drier conditions, wildland fire has been increasing in extent into peatland ecosystems during recent decades. As such, there is an increasing need for broadly applicable tools to detect surface peat moisture, in order to ascertain the susceptibility of peat burning, and the vulnerability of deep peat consumption in the event of a wildfire. In this thesis, a field portable spectroradiometer was used to measure surface reflectance of two Sphagnum moss dominated peatlands. Relationships were developed correlating spectral indices to surface moisture as well as water table position. Spectral convolutions were also applied to the high resolution spectra to represent spectral sensitivity of earth observing sensors. Band ratios previously used to monitor surface moisture with these sensors were assessed. Strong relationships to surface moisture and water table position are evident for both the narrowband indices as well as broadened indices. This study also found a dependence of certain spectral relationships on changes in vegetation cover by leveraging an experimental vegetation manipulation. Results indicate broadened indices employing the 1450-1650 nm region may be less stable under changing vegetation cover than those located in the 1200 nm region.

BEYOND ROOTS ALONE: NOVEL METHODOLOGIES FOR ANALYZING COMPLEX SOIL AND MINIRHIZOTRON IMAGERY USING IMAGE PROCESSING AND GIS TOOLS

Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.