Society requires better insights into how disturbances will alter the global carbon cycle. Ecosystem models help us understand the carbon cycle and make predictions about how the terrestrial land sink will change under future climate regimes. Disturbances drive ecosystem cycling, but modeling disturbances has unique challenges, particularly in incorporating heterogeneity and parameter uncertainty. In this dissertation, I explore two questions. 1) How can we capture disturbance ecology in models?, which I explore in my first and second chapters, and 2) How can we use those models to make projections for the Southeastern US?, which I explore in my third and fourth chapters.
Both my first and second chapters point to the practical trade-offs in model structure and realism. In my first chapter, I found that representing spatially implicit contagious disturbances in terms of shape and frequency accurately captured structural changes over time and separated the disturbance regimes of different regions. Representing spatially implicit disturbances in terms of shape and frequency sacrificed the specificity of a space-based approach but may be more computationally efficient. In my second chapter, I developed a framework for calibrating models based on an iterative cycle between uncertainty analysis and literature synthesis, targeted field campaigns, and statistical constraint. I found that targeted field work and statistical constraint reduced parameter uncertainty until structural uncertainty began to dominate.
Models that capture disturbance dynamics can help us anticipate effects of global change factors like climate change and invasive species. In my third chapter, I found that elevated temperatures reduce cogongrass biomass, and that cogongrass facilitates pine dominance over oaks in a mixed pine-oak stand. This suggests that cogongrass mediates inter-species competition at an ecosystem scale. Prescribed burns are a management technique used to suppress cogongrass and has an add-on benefit of reducing tick populations. However, climate change may threaten how frequently prescribed fires can be safely deployed. In my fourth chapter, I found that tick populations are most sensitive to leaf litter and humidity, which allows for management strategies as an alternative to prescribed burns
