The power of forecasts to advance ecological theory

Abigail S. L. Lewis*, Christine R. Rollinson, Andrew J. Allyn, Jaime Ashander, Stephanie Brodie, Cole B. Brookson, Elyssa Collins, Michael C. Dietze, Amanda S. Gallinat, Noel Juvigny-Khenafou, Gerbrand Koren, Daniel J. McGlinn, Hassan Moustahfid, Jody A. Peters, Nicholas R. Record, Caleb J. Robbins, Jonathan Tonkin, Glenda M. Wardle

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Ecological forecasting provides a powerful set of methods for predicting short- and long-term change in living systems. Forecasts are now widely produced, enabling proactive management for many applied ecological problems. However, despite numerous calls for an increased emphasis on prediction in ecology, the potential for forecasting to accelerate ecological theory development remains underrealized. Here, we provide a conceptual framework describing how ecological forecasts can energize and advance ecological theory. We emphasize the many opportunities for future progress in this area through increased forecast development, comparison and synthesis. Our framework describes how a forecasting approach can shed new light on existing ecological theories while also allowing researchers to address novel questions. Through rigorous and repeated testing of hypotheses, forecasting can help to refine theories and understand their generality across systems. Meanwhile, synthesizing across forecasts allows for the development of novel theory about the relative predictability of ecological variables across forecast horizons and scales. We envision a future where forecasting is integrated as part of the toolset used in fundamental ecology. By outlining the relevance of forecasting methods to ecological theory, we aim to decrease barriers to entry and broaden the community of researchers using forecasting for fundamental ecological insight.

Original languageEnglish
Pages (from-to)746-756
Number of pages11
JournalMethods in Ecology and Evolution
Volume14
Issue number3
Early online dateAug 2022
DOIs
Publication statusPublished - Mar 2023

Keywords

  • ecological forecast
  • ecological theory
  • forecast cycle
  • forecast synthesis
  • hypothesis testing
  • modelling
  • predictability
  • transferability

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