Ecosystem Model Uncertainty Training

This week-long uncertainty training will introduce participants to practical approaches for quantifying, propagating, and communicating uncertainty in ecosystem modeling workflows. The course will cover both frequentist and Bayesian approaches, starting with core concepts and hands-on methods before moving into model calibration, evaluation, and uncertainty propagation. By the end of the training, participants will understand how uncertainty methods can be applied systematically across modeling pipelines to support more transparent, reproducible, and decision-ready analysis.

A long, blackened, charred piece of wood or tree trunk on a wooden board, with a metal ruler and some papers nearby on a white table outdoors.

Agenda Overview

Monday
Introduction to what uncertainty is, why it matters for the carbon market, and getting into real, nested data. Learn about classical uncertainty from Dr. Stephen Ogle: variation, measurement error, bias, and the tradeoff between a simple model and an accurate one.

Tuesday
Frequentist tools. Building linear mixed effect and confidence intervals and pushing them through a decision. 

Wednesday
Bayesian thinking and a global sensitivity analysis on the model. 

Thursday
Calibration. Reducing uncertainty with SIR and MCMC. Comparing the methods, tying back to reporting, and open discussion. 

October 12-15, 2026 | In-Person ONLY
Fort Collins, CO

COST: $1600

Commercial Consortium Members: Free

Students: 50% off

Meet the Experts

Ames fowler headshot

Dr. Ames Fowler

Ecosystem Modeler, Ecosystem Modeling and Data Consortium

Ames is an ecosystem modeler with experience in processing-based modeling from the field to national scale with a diversity of hydrology, crop yield, and bio-geochemical soil system models. Ames is dedicated to enhancing access, development, technical support, and user training for CSU's state-of-the-art soil system models through the consortium. Leveraging these advanced tools, we can drive soil-based climate solutions grounded in leading-edge science. Ames’ affinity for the outdoors and agroecosystems fuels his passion for this work.

Dr. Stephen Ogle Colorado State University headshot

Dr. Stephen Ogle

Senior Research Scientist + Full Professor
Research Scientist

Ligia Souza

Dr. Ligia Souza

Data Science Lead
Ecosystem Modeling + Data Consortium

Corinne Walsh

Dr. Corinne Walsh

Consortium Operations Lead
Ecosystem Modeling + Data Consortium

Dr. Yao Zhang

Research Scientist
NREL

Frequently Asked Questions

Questions? Get in touch