The Training workshops at the EFI2025 Conference enhanced participants’ skills in model development, data analysis, and stakeholder engagement.  Below are links to resources from the eight workshops.

Find a summary of the conference here: https://ecoforecast.org/advancing-ecological-forecasting-skill-building-and-community-connections-at-the-2025-ecological-forecasting-initiative-conference/.

Workshops

1. Create and automate real-time water quality forecasts 

Leads: Mary Lofton, Freya Olsson, Austin Delany, Adrienne Breef-Pilz, Rohit Shukla, Quinn Thomas, Cayelan Carey
Virginia Tech

Participants in this workshop created, submitted, and automated real-time forecasts for up to 40 freshwater physical, chemical, and biological variables in the Virginia Ecoforecast Reservoir Analysis (VERA) forecasting challenge.

● VERA forecast challenge website: https://www.ltreb-reservoirs.org/vera4cast/
● VERA forecast tutorial in R: https://github.com/LTREB-reservoirs/vera4cast-example
● VERA forecast tutorial in Python: https://github.com/LTREB-reservoirs/PY-VERA_EXAMPLE

2. Spatial forecast of post fire recovery using MODIS LAI 

Leads: Steven Hammond¹, David Durden², Chris Jones³, John Smith^1
1Montana State University, ²NEON, ³NC State University Center for Geospatial Analytics

Participants learned about creating a spatial forecast and how that differs from other non-spatial NEON forecast challenges. Forecasting wildfire recovery using MODIS LAI was used in this example. 

● Find the tutorial material at: https://github.com/eco4cast/modis-lai-forecast/tree/main/tutorials
● See the rendered html at: https://htmlpreview.github.io/?https://github.com/eco4cast/modis-lai-forecast/blob/main/tutorials/efi_2025_workshop.html

3. Hands-on introduction to the Beetle Communities NEON Ecological Forecasting Challenge 

Leads: Eric Sokol, Vicky Louangaphay
NEON

This workshop provided code-along instructions to submit forecasts for ground beetle abundance and richness across NEON’s terrestrial sites to provide a hands-on demonstration of how to participate in the NEON Forecasting Challenge. 

● https://www.neonscience.org/resources/learning-hub/tutorials/neon-beetle-forecasting

4. Introduction to Gaussian Process Modeling of time dependent ecological data in R 

Leads: Leah Johnson, Robert Gramacy, Parul Patil
Virginia Tech

This workshop introduced Gaussian Process (GP) modeling for forecasting time dependent ecological data and demonstrate applications to tick abundance in the NEON Forecasting Challenge. 

● Find workshop details, slides, and a tutorial at: https://lrjohnson0.github.io/QEDLab/training/EFI2025.html

5. Water Quality Modeling: Building aquatic ecosystem models with the modular AED framework 

Lead: Matthew Hipsey
The University of Western Australia

This workshop provided hands-on training in the simulation of aquatic ecosystem processes using the open-source Aquatic Ecosystem Dynamics (AED) platform. 

● Find workshop materials at: https://github.com/AquaticEcoDynamics/efi-workshop

6. Accessing and Using NEON Data 

Leads: Eric Sokol, David Durden, Vicky Louangaphay
NEON

This workshop included an overview of NEON data and how to use the Data Portal and the neonUtilities R package to access and work with selected datasets.
● Slides and notes from the workshop

7. Hands-on Introduction to Cloud-native, Event-driven Computing in R with FaaSr 

Lead: Renato Figueiredo, Ashish Ramrakhiani
Oregon State University

Participants in this workshop gained hands-on experience installing and running an example ecological forecasting workflow using FaaSr, an R package with cloud-native functions and workflows that execute on-demand. 

● Find workshop materials at: https://github.com/Ashish-Ramrakhiani/FaaSr_workshop

8. Evaluation, scoring, and synthesis of ecological forecasts using the NEON Forecasting Challenge Catalogue 

Leads: Freya Olsson¹, Caleb Robbins², Quinn Thomas^1
1Virginia Tech, ²Baylor University

This workshop introduced concepts and tools for forecast evaluation, scoring, and synthesis. Participants used the vast, open, catalogue of forecasts submitted to the EFI-NEON Forecasting Challenge to apply the tools for forecast evaluation and comparison.

● Find workshop materials at: https://github.com/OlssonF/Forecast-evaluation-EFI25