Dissertation

Bridging structure and function in semi-arid ecosystems by integrating remote sensing and ground based measurements

Krofcheck, Dan J

2014

Overview

The Southwestern US is projected to continue to experience a significant warming trend, with increased variability in the timing and magnitude of rainfall events. The effects of theses changes in climate are already manifesting in the form of expansive, prolonged 'megadroughts', which have resulted in the widespread mortality of woody vegetation across the region.Therefore the need to monitor and model forest mortality and carbon dynamics at the landscape and regional scale is an essential component of regional and global climate mitigation strategies, and critical if we are to understand how the imminent state transitions taking place in forests globally will affect climate forcing and feedbacks. Remote sensing offers the only solution to multitemporal regional observation, yet many challenges exist with employing modern remote sensing solutions in highly stressed vegetation characteristic of semi-arid biomes, making one of the most expansive biomes on the globe also one of the most difficult to accurately monitor and model. The goal of this research was to investigate how changes in the structure of semi-arid woodlands following forest mortality impacts ecosystem function, and address this question in the context of remote sensing data sets, thereby contributing to the remote sensing community's ability to interact with these challenging ecosystems. We first focused on pinus edulis and juniperous monosperma (pinon-juniper) woodlands, as they comprise a model semi-arid biome. We tested the ability of high resolution remote sensing data to mechanistically describe the patterns in overstory mortality and understory green-up, and were able to observe the heterogeneous response of the understory as a function of cover type. We also investigated the relationship between changes in soil water content and the greenness of the canopy, noting that in these stress ecosystems there is often a decoupling of the canopy as measured remotely (e.g., via vegetation indices, VI), and photoysnthesis, potentially presenting a significant source of error in existing light use efficiency models of carbon uptake. Our analysis also suggested that leveraging remeote sensing data which measures in the red-edge portion of reflected light can provide increased sensitivity to the low leaf area, ephemeral pulses of greenup that we identified post canopy mortality. Given these findings, we developed a hierarchy of simple linear models to test the ability of a moisture sensitive VI, and a red-edge leveraging VI, to predict carbon uptake. We determined that the red-edge VI and the moisture sensitive VI both constrained uncertainty associated with carbon uptake, but that the variability in satellite view angle from scene to scene can impose a significant amount of noise in sparse canopy ecosystems. Finally, given the extent and prevalence of j. monosperma across the region, and its complex growth morphology, we tested the ability of aerial lidar to quantify the biomass of juniperous ecosystems. In this simplified case study, we developed a methodology to relate the volume of canopy objects to the equivalent stem area at the root crown. By working in a single species ecosystem, we circumvented many challenges associated with driving allometries remotely, but also present a workflow that we intend adapted to more complex systems, namely pinon-juniper woodlands. Together, this work describes and addresses existing challenges with respect to remote sensing of semi-arid vegetation, and provides a body of research that can mitigate the difficulties associated with monitoring mortality / recovery dynamics, predicting canopy funciton, and determining ecosystem state parameters in these complex, sensitive biomes.

• Publisher: ProQuest Dissertations & Theses
• Subject: Ecology / Remote sensing
• ISBN: 9781321552492, 1321552491