Using Plant Ecophysiology, Long-Term Community Dynamics, and Experimental Restoration Techniques to Inform Riparian Restoration and Conservation

Abstract

Over three chapters of my dissertation, I aimed to address drivers of riparian ecosystem change at different scales, ranging from leaf-level plant ecophysiology to long-term plant community dynamics. In my first chapter, I assessed willow water limitation in Rocky Mountain National Park in the context of degraded sites with high ungulate browsing that have also functionally lost beaver-mediated hydrology. I found that, in these degraded contexts, willows were not water-limited compared to more intact reference sites but rather showed responses in association with seasonal drydown. In my second chapter, I assessed decadal turnover trends in riparian wetlands, wet meadows, and fens in Rocky Mountain National Park. I found that riparian ecosystems experienced the greatest compositional change while wet meadows and fen functional group components were relatively stable through time. Further, water balance metrics were the most important determinants of plant community composition and there were only a couple of instances indicating where native functional groups might exclude corresponding nonnative functional groups through limiting similarity. In my third chapter, I tested the effectiveness of using a functional trait-based approach to see if functional diversity conferred stability in productivity and reduced invasion by increased niche occupation and complementarity in a riparian restoration project in the Front Range of Colorado. I found some support for a functional diversity oriented approach contributing to the stability of productivity, whereas invasion trends were largely driven by a soil moisture gradient and not biotic contexts. Together, this collection of work provides quantitative assessments for riparian restoration and conservation trajectories that can be used in adaptive management contexts for decisions about whether to design management strategies to manage drivers of change, enhance adaptive capacity, or enable novel ecosystem configurations.