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Other literature type . 2024
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Nature Climate Change
Article . 2024 . Peer-reviewed
License: Springer Nature TDM
Data sources: Crossref
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Near-term ecological forecasting for climate change action

Authors: Michael Dietze; Ethan P. White; Antoinette Abeyta; Carl Boettiger; Nievita Bueno Watts; Cayelan C. Carey; Rebecca Chaplin-Kramer; +16 Authors

Near-term ecological forecasting for climate change action

Abstract

A substantial increase in predictive capacity is needed to anticipate and mitigate the widespread change in ecosystems and their services in the face of climate and biodiversity crises. In this era of accelerating change, we cannot rely on historical patterns or focus primarily on long-term projections that extend decades into the future. In this Perspective, we discuss the potential of near-term (daily to decadal) iterative ecological forecasting to improve decision-making on actionable time frames. We summarize the current status of ecological forecasting and focus on how to scale up, build on lessons from weather forecasting, and take advantage of recent technological advances. We also highlight the need to focus on equity, workforce development, and broad cross-disciplinary and non-academic partnerships. This work was supported by the NSF Research Coordination Network under grant number 1926388 and an Alfred P. Sloan Foundation grant. Published version

Country
United States
Related Organizations
Keywords

Climate change, Ecological forecasting

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average