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

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 CO 2 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 overtime 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.

The power of forecasts to advance ecological theory

“…Iterative forecasts-those that are made repeatedly, updating the forecast model through confrontation with new data-may be particularly useful for hypothesis testing and theory development. When developing iterative forecasts, researchers are able to conduct targeted sampling to resolve uncertain model processes or states, developing a more complete and accurate understanding of the ecological process (Redmond et al, 2019). Changing the data collection strategy in response to forecasts is a unique opportunity that forecasting offers in comparison with retrospective analysis, and is transformative as a means of distinguishing between competing hypotheses (Coelho et al, 2019).…”

Preparing Aquatic Research for an Extreme Future: Call for Improved Definitions and Responsive, Multidisciplinary Approaches

“…Extreme events are often sporadic in time and variable across space, which creates a challenge for researchers seeking not only to demarcate the event itself but to measure the ecological responses to such intense disturbances (Redmond et al 2019 ). With limited monitoring resources, trade-offs in spatial and temporal resolution often lead to high temporal frequency observations at low spatial resolution or high spatial resolution monitoring at low temporal frequency (Krause et al 2015 ).…”

“…However, these long-term monitoring programs are often not designed to capture extreme events; for example, weekly or monthly sampling could miss short-term algal blooms, or concentrated summer sampling could miss rare spring heatwaves. The utility of extreme event research can be enhanced by employing targeted short-term studies and regional surveys implemented rapidly during developing extreme events (Redmond et al 2019 ). Another temporal challenge, especially for opportunistic studies, is the lack of data measured consistently before, during, and after extreme events.…”

“…Similarly, temporal scales are often constrained by ongoing long-term monitoring programs, short-term studies, or safety or logistic concerns during an extreme event. To address these challenges, we recommend developing contingency plans and protocols that can be executed rapidly during developing extreme events (Redmond et al 2019 ). For example, to account for spatial heterogeneity, ecologists can pair remotely sensed technologies that integrate across larger areas with targeted in situ sampling or leverage distributed sampling efforts through collaboration.…”

Forest Management Under Megadrought: Urgent Needs at Finer Scale and Higher Intensity

“…A first step in anticipatory management for hotter drought is to accurately identify in advance the forested ecosystems most at risk to drought (Millar and Stephenson, 2015). Identification of vulnerable forest stands can be aided by Earth System Models (Swann et al, 2018); forest health monitoring networks (Hartmann et al, 2018); nearterm ecological forecasting of extreme events (Dietze et al, 2018;Redmond et al, 2019); remote sensing (Mu et al, 2013), traits related to drought-induced mortality (Anderegg et al, 2016;Sperry et al, 2016;O'Brien et al, 2017); and ground surveys (Breshears et al, 2005;Redmond et al, 2019).…”