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  • Systematic review and meta-analysis of near-term ecological forecasting literature, including forecast performance data. Search conducted May 2020
  • Lewis, Abigail S. L.; Virginia Tech
    Woelmer, Whitney M.; Virginia Tech
    Wander, Heather L.; Virginia Tech
    Howard, Dexter W.; Virginia Tech
    Smith, John; Virginia Tech
    McClure, Ryan P.; Virginia Tech
    Lofton, Mary E.; Virginia Tech
    Hammond, Nicholas W.; Virginia Tech
    Corrigan, Rachel; Virginia Tech
    Thomas, R. Quinn; Virginia Tech
    Carey, Cayelan C.; Virginia Tech
  • 2021-03-15
  • Lewis, A.S., W.M. Woelmer, H.L. Wander, D.W. Howard, J. Smith, R.P. McClure, M.E. Lofton, N.W. Hammond, R. Corrigan, R.Q. Thomas, and C.C. Carey. 2021. Systematic review and meta-analysis of near-term ecological forecasting literature, including forecast performance data. Search conducted May 2020 ver 1. Environmental Data Initiative. https://doi.org/DOI_PLACE_HOLDER (Accessed 2024-12-27).
  • This data publication includes results and code from a systematic review and meta-analysis of near-term ecological forecasting literature. The study had two primary goals: (1) analyze the state of near-term ecological forecasting literature, and (2) compare forecast skill across ecosystems and variables. We began by conducting a Web of Science search for “forecast*” in the title, abstract, and keywords of all papers published in ecological journals, then screened all papers from this search to identify near-term ecological forecasts. To more broadly survey the literature, we then searched all papers that cite or are cited by the near-term ecological forecasts we identified. We performed an in-depth review of all near-term ecological forecasting papers identified through this search process, and recorded forecast skill data for all papers that reported R or R2. Our results indicate that the rate of publication of near-term ecological forecasts is increasing over time and the field is becoming increasingly open and automated. Across published forecasts, we find that forecast skill decreases in predictable patterns and these patterns differ between forecast variables. This data publication includes three products from this analysis: (1) a database of all papers identified in the two searches, including our assessment of whether they included an ecological focal variable, included a forecast, and whether the forecast was near-term (≤10 years), (2) a matrix of all data collected on the near-term ecological forecasts we identified, and (3) a database of R2 values for papers that reported R or R2.

  • edi.187.1  (Uploaded 2021-03-15)  
  • This information is released under the Creative Commons license - Attribution - CC BY (https://creativecommons.org/licenses/by/4.0/). The consumer of these data (\"Data User\" herein) is required to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or co-authorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available \"as is.\" The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. Thank you.
  • DOI PLACE HOLDER
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