Targeting Extreme Events: Complementing Near-Term Ecological Forecasting With Rapid Experiments and Regional Surveys

Miranda D Redmond,David D Breshears,Charles J W Carroll,Neil S Cobb,Andreas P Wion,Rachel E Gallery,Jason P Field,Darin J Law,Michael C Dietze,Nashelly Meneses

doi:10.3389/fenvs.2019.00183

Abstract

Ecologists are improving predictive capability using near-term ecological forecasts, in which predictions are made iteratively and publically to increase transparency, rate of learning, and maximize utility. Ongoing ecological forecasting efforts focus mostly on long-term datasets of continuous variables, such as CO2 fluxes, or more abrupt variables, such as phenological events or algal blooms. Generally lacking from these forecasting efforts is the integration of short-term, opportunistic data concurrent with developing climate extremes such as drought. We posit that incorporating targeted experiments and regional surveys, implemented rapidly during developing extreme events, into current forecasting efforts will ultimately enhance our ability to forecast ecological responses to climate extremes, which are projected to increase in both frequency and intensity. We highlight a project “chasing tree die-off”, in which we coupled an experiment with regional-scale observational field surveys during a developing severe drought to test and improve forecasts of tree die-off. General insights to consider in incorporating this approach include: (1) tracking developing climate extremes in near-real time to efficiently ramp up measurements rapidly and, if feasible, initiate an experiment quickly—including funding and site selection challenges; (2) accepting uncertainty in projected extreme climatic events and adjusting sampling design over-time as needed, especially given the spatially heterogeneous nature of many ecological disturbances; and (3) producing timely and iterative output. In summary, targeted experiments and regional surveys implemented rapidly during developing extreme climatic events offer promise to efficiently (both financially and logistically) improve our ability to forecast ecological responses to climate extremes.

Highlights

The frequency and severity of climate extremes such as drought, floods, and heat waves are projected to increase with global climate change (de Coninck et al, 2018; Hayhoe et al, 2018)
Given the importance of extreme climatic events, we propose that rapidly implemented studies at local and regional scales can be a useful complement to other approaches based on ongoing long-term data collection (Figure 1A)
Climate change is occurring at such a rapid pace that the Anthropocene falls outside of the typical range of natural variability (Smith et al, 2009), creating a need for iterative near-term ecological forecasting (Dietze et al, 2018)

Summary

Introduction

The frequency and severity of climate extremes such as drought, floods, and heat waves are projected to increase with global climate change (de Coninck et al, 2018; Hayhoe et al, 2018). We propose that adding rapidly implemented experimental and regional studies during developing extreme climate events can complement existing near-term ecological forecasting efforts to improve our capacity to forecast ecological responses to climate extremes.

Results

Conclusion