Modeling ecological disturbances in the Southeastern United States

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

Identifying foundation species in North American forests using long‐term data on ant assemblage structure

Foundation species are locally abundant and uniquely control associated biodiversity, whereas dominant species are locally abundant but are thought to be replaceable in ecological systems. It is important to distinguish foundation from dominant species to direct conservation efforts. Long‐term studies that remove abundant species while measuring community dynamics have the potential to (1) aid in the identification of foundation vs. dominant species and, (2) once a foundation species is identified, determine how long its effects persist within a community after its loss. Long‐term data on ant assemblages within two canopy‐manipulation experiments—the Harvard Forest Hemlock Removal Experiment (HF‐HeRE) and the Black Rock Future of Oak Forests Experiment (BRF‐FOFE)—provide insights into how ant assemblages change and reassemble following the loss of Tsuga canadensis or Quercus spp. Previous research documented foundation species effects on ants in the HF‐HeRE for up to four years after T. canadensis loss. Six additional years of data at HF‐HeRE presented for the first time here show that removal of T. canadensis resulted in taxonomic and some measures of functional shifts in ant assemblages that persisted for ten years, further supporting the hypothesis that T. canadensis is a foundation species at Harvard Forest. In contrast, ant assemblages at BRF‐FOFE varied little regardless of whether oaks or other tree species were removed from the canopy, suggesting that Quercusspecies do not act as foundation species at Black Rock Forest. Deer and moose exclosures within each experiment also allowed for comparisons between effects on ants of foundation or dominant tree species relative to effects of large herbivores. At HF‐HeRE, effects of T. canadensis were stronger than effects of large herbivores on taxonomic and functional diversity of ant assemblages. At BRF‐FOFE, in contrast, effects of Quercus species were weaker than effects of large herbivores on ant taxonomic diversity and some measures of ant functional diversity. These findings illustrate the importance of distinguishing between the roles of irreplaceable foundation species and replaceable dominant ones in forested ecosystems along with other drivers of biodiversity (e.g., herbivory)

Scaling Contagious Disturbance: A Spatially-Implicit Dynamic Model

Spatial processes often drive ecosystem processes, biogeochemical cycles, and land-atmosphere feedbacks at the landscape-scale. Climate-sensitive disturbances, such as fire, land-use change, pests, and pathogens, often spread contagiously across the landscape. While the climate-change implications of these factors are often discussed, none of these processes are incorporated into earth system models as contagious disturbances because they occur at a spatial scale well below model resolution. Here we present a novel second-order spatially-implicit scheme for representing the size distribution of spatially contagious disturbances. We demonstrate a means for dynamically evolving spatial adjacency through time in response to disturbance. Our scheme shows that contagious disturbance types can be characterized as a function of their size and edge-to-interior ratio. This emergent disturbance characterization allows for description of disturbance across scales. This scheme lays the ground for a more realistic global-scale exploration of how spatially-complex disturbances interact with climate-change drivers, and forwards theoretical understanding of spatial and temporal evolution of disturbance

Summary and Recommendations from Working Group 1: model uncertainty representations in convection-permitting / shorter lead-time / limited-area ensembles

WG3 discussed both the pros and cons of existing schemes as Working group 1 considered the treatment of model uncertainty (MU) in high-resolution ensembles, at grid spacings of order 1-5 km. These systems are often run for regional weather forecasting, perhaps over a single country, and for lead times of up to 5 days. Looking ahead, ECMWF’s strategy seeks to deliver global medium-range ensemble forecasts with 3-4 km grid spacings by 2030. It is questionable for what grid spacing we should dispense with a deep convection parameterization, but it will be either switched off or damped in these systems, such that deep convection can be assumed to be dominated by explicit motions. One of the problems with limited-area ensemble systems at this scale is that spread depends not only on the modelling system itself but also on the variability inherited from the large-scale boundary conditions. There is often thought to be a lack of spread in our high-resolution EPS (ensemble prediction systems), but this could reflect a lack of diversity on larger scales. The relative importance of lateral-boundary diversity and the model uncertainty mechanisms is regime dependent. The lateral boundaries will generally be more important in midlatitude winter but less so for summertime convection in relatively weak synoptic flow