Targeting Extreme Events: Complementing Near-Term Ecological Forecasting With Rapid Experiments and Regional Surveys
Author
Redmond, Miranda D.Law, Darin J.
Field, Jason P.
Meneses, Nashelly
Carroll, Charles J. W.
Wion, Andreas P.
Breshears, David D.
Cobb, Neil S.
Dietze, Michael C.
Gallery, Rachel E.
Affiliation
Univ Arizona, Sch Nat Resources & EnvironmUniv Arizona, Dept Ecol & Evolutionary Biol
Issue Date
2019-11-27Keywords
ecological forecastingadaptive monitoring
anticipatory science
disturbance
climate change
climate extremes
extreme climatic event
drought
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FRONTIERS MEDIA SACitation
Redmond, M. D., Law, D. J., Field, J. P., Meneses, N., Carroll, C. J., Wion, A. P., ... & Gallery, R. E. (2019). Targeting Extreme Events: Complementing Near-Term Ecological Forecasting With Rapid Experiments and Regional Surveys. Frontiers in Environmental Science, 7, 183.Rights
Copyright © 2019 Redmond, Law, Field, Meneses, Carroll, Wion, Breshears, Cobb, Dietze and Gallery. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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.Note
Open access journalISSN
2296-665XEISSN
2296-665XVersion
Final published versionSponsors
Division of Environmental Biologyae974a485f413a2113503eed53cd6c53
10.3389/fenvs.2019.00183
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Except where otherwise noted, this item's license is described as Copyright © 2019 Redmond, Law, Field, Meneses, Carroll, Wion, Breshears, Cobb, Dietze and Gallery. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.