As average temperatures rise and precipitation patterns change, we can expect changes in climate extremes (such as more hot droughts), and climate-driven disturbances (such as wildfire and drought mortality). Likely disturbance regime changes include increased fire severity or fire-return intervals. These changes will force ecosystems to adjust natural community composition, structure, and function in ways not previously observed; this is a no-analog future. Future management strategies, in turn, will have to adapt to changing ecosystems, especially where climate-induced changes are rapid and severe. We do not currently have the tools to understand, quantify, and predict dynamic ecosystem changes in a no-analog future. This project directly addresses this key research and capability gap. The project has two overarching goals:

(A) Build a mechanistic model to understand how natural communities will respond in a no-analog future. This includes quantifying ecosystem vulnerability in terms of composition, structure, and function, with a focus on feedbacks between fire and hydrologic regimes.

(B) Translate this new understanding into an actionable science-based decision tool for DoD site managers that will optimize potential tradeoffs between environmental conservation and mission performance.

Researchers will develop a new mechanistic modeling framework—Disturbance Response Model (DRM)—to simulate ecosystem response to changes in disturbance regimes and climate. The research team will build the DRM for the longleaf pine ecosystem on Eglin Air Force Base (AFB), with a focus on two of the endangered species it supports: the red-cockaded woodpecker and the reticulated flatwoods salamander. However, it is expected that it will be applicable to all major DoD lands. DRM will enhance and integrate existing Los Alamos National Laboratory (LANL) wildfire (FIRETEC and QUIC-Fire) and ecohydrology modeling (Amanzi-ATS) tools. The research team will test a novel looped disturbance and ecohydrological approach that will explicitly resolve dominant feedbacks between climate forcings, fire disturbance, and ecological and hydrologic response. Key DRM processes and mechanisms will be identified, simulated, and validated using observed data from Eglin AFB. Finally, the DRM will be driven with a range of future climate projections to explore climate sensitivities and uncertainty. This framework will help better understand how natural communities will respond to climate change. It will also allow DoD site managers to test the outcome of management choices, such as forest thinning and prescribed burns, with the aim of balancing ecosystem and mission resiliency.

Current understanding of ecosystem vulnerability to climate change is lacking. First, statistical/empirical models are calibrated using past observations which, are hypothesized, to break down in a no-analog future. Second, existing modeling approaches cannot capture feedbacks between climate, ecosystems, and disturbances. This project will advance the state of science and modeling by filling these gaps. It will directly benefit the wider science community, while enabling DoD sites to better manage natural resources in a no-analog future. Explicit mechanistic simulation is able to project unprecedented climate-ecohydrological conditions while avoiding bias introduced by overly-calibrated statistical relationships. This can significantly increase confidence of predicted system behavior. The resulting new science understanding and the DRM itself will help DoD site managers to develop adaptive management strategies for resilient ecosystems while sustaining critical missions at DoD sites.