RAPID: Collaborative Research: Testing Near-term Ecological Forecasting Throughout Emerging Extreme Drought

Colorado State University, Fort Collins CO

Investigators

Abstract

Tree die-off in response to drought, warmer temperatures, and pests and pathogens is occurring globally. These die-off events have altered forest and woodland ecosystems. This includes changes in water and energy fluxes and losses in ecosystem services in many areas. The ability to predict how forests will respond to drought is key for applying rapid land management actions to mitigate undesired outcomes. One goal of this research is to improve mortality predictions for pi?on pine (Pinus edulis) in response to drought. This will be achieved through a watering experiment and a regional survey during an emerging snow drought in the US Southwest. Multiple predictions of pi?on mortality in response to drought have already been developed. Another goal of this research is to use near-term ecological forecasting to test these different predictions. Throughout the drought, forecasts of the likelihood of tree mortality based on these different predictions will be done at intervals of 1 week to 1 year. This project will engage the public, land managers, and scientists through a website that is updated weekly with tree mortality forecasts. This project will develop and implement a teaching module to enhance undergraduate curricula and provide education training for a postdoctoral researcher. An emerging frontier of ecosystem science in the face of environmental change is to predict not just ecological responses to trends but to predict extreme ecological events to extreme climate events. Among the most important and extensive of such events is tree die-off in response to drought, warming and associated pests and pathogens. Although much research has focused simply on what exceeds thresholds for tree mortality, yielding numerous potential predictive relationships, none of these relationships have been tested with near-term ecological forecasting. Further, field experiments that have attempted to impose drought largely have been ineffective at improving predictions or testing near-term forecasts due to the challenges of effectively mimicking a severe drought or simultaneous mortality of treated and controls plots. There is thus a critical need for an experiment that takes advantage of a developing extreme drought to test multiple alternate hypotheses in a near-term ecological forecasting context. This project will rapidly implement experimental and monitoring measurements concurrent with the severe snow drought emerging across the southwestern US to test multiple predictions of tree mortality for pi?on pine (Pinus edulis), the most intensively studied tree species for drought-induced mortality. Near-term ecological forecasting will be updated at intervals of 1 week to 1 year throughout the drought, based on the frequency of available input data. Through improved mortality predictions and advancements in near-term ecological forecasting that can encompass extreme ecological events, this research will be a critical step towards developing forecasts that provide the information needed for rapid land management actions and account for longer-term implications such as carbon management. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.