EFI RCN NEON Ecological Forecast Challenge

Full Description of the Challenge, Resources, and FAQ Here

The NEON Ecological Forecasting Challenge is an ongoing project and is accepting submissions across all themes!

Pre-print to a manuscript that provides an overview of the Challenge and which has been accepted for publication in Frontiers in Ecology and the Environment. Thomas, R.Q., C. Boettiger, C.C. Carey, M.C. Dietze, L.R. Johnson, M.A. Kenney, J.S. Mclachlan, J.A. Peters, E.R. Sokol, J.F. Weltzin, A. Willson, W.M. Woelmer, and Challenge Contributors.  2022.  The NEON Ecological Forecasting Challenge.  ESS Open Archive. https://www.doi.org/10.22541/essoar.167079499.99891914/v1


The NSF funded EFI Research Coordination Network (EFI-RCN) is hosting a NEON Ecological Forecast Challenge with the goal to create a community of practice that builds capacity for ecological forecasting by leveraging NEON data products. The Challenge revolves around the five theme areas listed below that span aquatic and terrestrial systems, and population, community, and ecosystem processes across a broad range of ecoregions that uses data collected by NEON.

As a community, we are excited to learn more about the predictability of ecological processes by forecasting NEON data prior to its release.  What modeling frameworks, mechanistic processes, and statistical approaches best capture community, population, and ecosystem dynamics? These questions are answerable by a community generating a diverse array of forecasts.  The Challenge is open to any individual or team that wants to submit forecasts and includes categories for different career stages. Individuals or team contacts can register to submit forecasts HERE.

The design of the Challenge is the result of contributions of over 200 participants in the May 2020 virtual EFI-RCN meeting, including partner organizations, and the hard work from the Design Teams that have developed the protocols for each of the themes.

Computational resources are supported by NSF funded CyVerse, Jetstream, and XSEDE.

Challenge Themes

Aquatic Ecosystems
Terrestrial Carbon and Water Fluxes
Tick Populations
Plant Phenology
Beetle Communities
Forecasts submitted for each theme and their evaluation scores can be viewed on this dashboard.

Instructions for Submitting Forecasts and Forecast Evaluation Details Here

Overview of Cyberinfrastructure used in the Challenge

Version 1 of the NEON Ecological Forecasting Challenge Protocols

Thomas, R.Q., C. Boettiger, C. Carey, M. Dietze, A. Fox, M.A. Kenney, C.M. Laney, J.S. McLachlan, J. Peters, J.F. Weltzin, W.M. Woelmer, J.R. Foster, J.P. Guinnip, A. Spiers, S. Ryan, K.I. Wheeler, A.R. Young, L.R. Johnson, S. Burnet, R. McClure, C. Brown, J. Zwart, G. Burba, J. Cleverly, A. Desai, W. Hammond, D. Lombardozzi, M. Bitters, M. Chen, S. LaDeau, C. Lippi, B. Melbourne, W. Moss, K. Gerst, C. Jones, A. Richardson, B. Seyednasrolla, T. Dallas, N. Franz, K. Norman, T. Surasinghe, E. Sokol, K. Yule. (2021). Ecological Forecasting Initiative: NEON Ecological Forecasting Challenge documentation V1.0 (v1.0). Zenodo. https://doi.org/10.5281/zenodo.4780155
*This version was used for round 1 of the Forecasting Challenge. The current instructions linked above are for subsequent rounds of the Challenge.

Video Resources

These videos provide a) an overview of why we need forecasts and why we are using NEON data, b) describes Forecasting Challenges in general, and c) provides an overview of the draft Ecological Forecast Standards that the EFI Cyberinfrastructure, Methods & Tools, and Theory Working Groups have developed. The Standards are still in beta testing, but you can find details on this GitHub repo which summarizes the proposed standards.

Here are videos from the December 9, 2020 AGU EFI Town Hall providing an overview of

  1. The Challenge
  2. The Challenge cyberinfrastructure
  3. The NEON data streams
Overview of the EFI-RCN, Why Forecasting is Important, and Why Use NEON Products
General Description of Forecasting Challenges
Draft of the Forecasting Standards
Playlist of Videos Describing the NEON Data Products