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  • Perspective
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Near-term ecological forecasting for climate change action

Nature Climate Change volume 14, pages 1236–1244 (2024)Cite this article

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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.

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Fig. 1: Near-term iterative ecological forecasting.
Fig. 2: Ecological predictability.

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Acknowledgements

This work was supported by the NSF Research Coordination Network under grant number 1926388 and an Alfred P. Sloan Foundation grant. We thank K. Davis at Notre Dame for her work on figure development. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Author information

Authors and Affiliations

  1. Department of Earth & Environment, Boston University, Boston, MA, USA

    Michael Dietze

  2. Department of Wildlife Ecology & Conservation, University of Florida, Gainesville, FL, USA

    Ethan P. White & S. K. Morgan Ernest

  3. Mathematics, Physical and Natural Sciences Division, University of New Mexico Gallup, Gallup, NM, USA

    Antoinette Abeyta

  4. Department of Environmental Science, Policy and Management, University of California, Berkeley, Berkeley, CA, USA

    Carl Boettiger

  5. Indian Natural Resource Science & Engineering Program, Cal Poly Humboldt, Arcata, CA, USA

    Nievita Bueno Watts

  6. Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA

    Cayelan C. Carey & R. Quinn Thomas

  7. Global Science, WWF, San Francisco, CA, USA

    Rebecca Chaplin-Kramer

  8. Institute on the Environment, University of Minnesota, St. Paul, MN, USA

    Rebecca Chaplin-Kramer & Melissa A. Kenney

  9. Nicholas School of the Environment, Duke University, Durham, NC, USA

    Ryan E. Emanuel

  10. School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USA

    Renato J. Figueiredo

  11. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA

    Michael D. Gerst

  12. Department of Statistics, Virginia Tech, Blacksburg, VA, USA

    Leah R. Johnson

  13. Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA

    Jason S. McLachlan, Jody A. Peters & Alyssa M. Willson

  14. Department of Electrical & Computer Engineering, Boston University, Boston, MA, USA

    Ioannis Ch. Paschalidis

  15. Center for Tree Science, The Morton Arboretum, Lisle, IL, USA

    Christine R. Rollinson

  16. DAPPER Stats, Portland, OR, USA

    Juniper Simonis

  17. The Pew Charitable Trusts, Washington DC, USA

    Kira Sullivan-Wiley

  18. Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, USA

    R. Quinn Thomas

  19. School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia

    Glenda M. Wardle

  20. Water Mission Area, US Geological Survey, Madison, WI, USA

    Jacob Zwart

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Contributions

M.C.D. organized and led the writing of the Perspective. All authors contributed to writing the original draft, reviewing and editing.

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Correspondence to Michael Dietze.

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Nature Climate Change thanks Vicky Boult, Matteo Convertino, David Garcia-Callejas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Dietze, M., White, E.P., Abeyta, A. et al. Near-term ecological forecasting for climate change action. Nat. Clim. Chang. 14, 1236–1244 (2024). https://doi.org/10.1038/s41558-024-02182-0

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