@article{e11f1e89fe1e433fa0de0aa82fa97155,
title = "The power of forecasts to advance ecological theory",
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.",
keywords = "ecological forecast, ecological theory, forecast cycle, forecast synthesis, hypothesis testing, modelling, predictability, transferability",
author = "Lewis, {Abigail S. L.} and Rollinson, {Christine R.} and Allyn, {Andrew J.} and Jaime Ashander and Stephanie Brodie and Brookson, {Cole B.} and Elyssa Collins and Dietze, {Michael C.} and Gallinat, {Amanda S.} and Noel Juvigny-Khenafou and Gerbrand Koren and McGlinn, {Daniel J.} and Hassan Moustahfid and Peters, {Jody A.} and Record, {Nicholas R.} and Robbins, {Caleb J.} and Jonathan Tonkin and Wardle, {Glenda M.}",
note = "Funding Information: This manuscript originated out of 2 years of discussions within the Ecological Forecasting Initiative's Theory Working Group—we thank all participants, past and present, who contributed to the development of these ideas. We also thank Elliott Hazen, Gavin Simpson and two anonymous reviewers for comments that improved this manuscript. Financial support for this project comes from a U.S. National Science Foundation graduate research fellowship to ASLL (DGE‐1651272), NSF MSB‐1638577 (MCD), the Ecological Forecasting Initiative Research Coordination Network (NSF RCN‐1926388), the Alfred P. Sloan Foundation (JAP) and NOAA grant NA19NOS4780187 (NRR). ASLL recieves additional support from NSF DEB‐1753639 and the Institute for Critical Technology and Applied Science at Virginia Tech. JDT is supported by a Rutherford Discovery Fellowship administered by the Royal Society Te Apārangi (RDF‐18‐UOC‐007); Bioprotection Aotearoa and Te Pūnaha Matatini, both Centres of Research Excellence funded by the Tertiary Education Commission, New Zealand; and by the MBIE funded Antarctic Science Platform (ANTA1801). SB and AJA are supported by a grant from the National Aeronautics and Space Administration (NASA: 80NSSC19K0187). ASG is supported by NSF grants DEB‐2017831, DEB‐2017848, and DEB‐2017815. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the US government. Funding Information: This manuscript originated out of 2 years of discussions within the Ecological Forecasting Initiative's Theory Working Group—we thank all participants, past and present, who contributed to the development of these ideas. We also thank Elliott Hazen, Gavin Simpson and two anonymous reviewers for comments that improved this manuscript. Financial support for this project comes from a U.S. National Science Foundation graduate research fellowship to ASLL (DGE-1651272), NSF MSB-1638577 (MCD), the Ecological Forecasting Initiative Research Coordination Network (NSF RCN-1926388), the Alfred P. Sloan Foundation (JAP) and NOAA grant NA19NOS4780187 (NRR). ASLL recieves additional support from NSF DEB-1753639 and the Institute for Critical Technology and Applied Science at Virginia Tech. JDT is supported by a Rutherford Discovery Fellowship administered by the Royal Society Te Apārangi (RDF-18-UOC-007); Bioprotection Aotearoa and Te Pūnaha Matatini, both Centres of Research Excellence funded by the Tertiary Education Commission, New Zealand; and by the MBIE funded Antarctic Science Platform (ANTA1801). SB and AJA are supported by a grant from the National Aeronautics and Space Administration (NASA: 80NSSC19K0187). ASG is supported by NSF grants DEB-2017831, DEB-2017848, and DEB-2017815. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the US government. Publisher Copyright: {\textcopyright} 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.",
year = "2023",
month = mar,
doi = "10.1111/2041-210X.13955",
language = "English",
volume = "14",
pages = "746--756",
journal = "Methods in Ecology and Evolution",
issn = "2041-210X",
publisher = "John Wiley & Sons, Ltd (10.1111)",
number = "3",
}