Disturbance Distance: Using a process based ecosystem model to estimate and map potential thresholds in disturbance rates that would give rise to fundamentally altered ecosystems

Abstract:

Disturbance plays a critical role in shaping the structure and function of forested ecosystems as well as the ecosystem services they provide, including but not limited to: carbon storage, biodiversity habitat, water quality and flow, and land atmosphere exchanges of energy and water. As recent studies highlight novel disturbance regimes resulting from pollution, invasive pests and climate change, there is a need to include these alterations in predictions of future forest function and structure. The Ecosystem Demography (ED) model is a mechanistic model of forest ecosystem dynamics in which individual-based forest dynamics can be efficiently implemented over regional to global scales due to advanced scaling methods. We utilize ED to characterize the sensitivity of potential vegetation structure and function to changes in rates of density independent mortality. Disturbance rate within ED can either be altered directly or through the development of sub-models. Disturbance sub-models in ED currently include fire, land use and hurricanes. We use a tiered approach to understand the sensitivity of North American ecosystems to changes in background density independent mortality. Our first analyses were conducted at half-degree spatial resolution with a constant rate of disturbance in space and time, which was altered between runs. Annual climate was held constant at the site level and the land use and fire sub-models were turned off. Results showed an ~ 30% increase in non-forest area across the US when disturbance rates were changed from 0.6% a year to 1.2% a year and a more than 3.5 fold increase in non-forest area when disturbance rates doubled again from 1.2% to 2.4%. Continued runs altered natural background disturbance rates with the existing fire and hurricane sub models turned on as well as historic and future land use. By quantify differences between model outputs that characterize ecosystem structure and function related to the carbon cycle across the US, we are identifying areas and characteristics that display higher sensitivities to change in disturbance rates.