DAPPER (Data Assimilation for Predicting Productivity of Ecosystems and Regions)

A framework for assimilating diverse observations of ecosystems into an ecosystem model using Markov chain Monte Carlo and hierarchical Bayesian methods.  First application uses the 3-PG model and applies the framework to loblolly pine ecosystems of the Southeastern U.S.  Developed by research group.

Code repository


Thomas, R. Q., E. Brooks, A. Jersild, E. Ward, R. Wynne, T.J. Albaugh, H. D. Aldridge, H. E. Burkhart, J-C Domec, T. R. Fox, C. A. Gonzalez-Benecke, A. Noormets, D. A. Sampson, and R. O. Teskey.  2017. Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments. Biogeosciences 14: 3525 – 3547 [link]

Thomas. R. Q., A. Jersild, E. Brooks, V. A. Thomas, and R. H. Wynne.  2018. A mid-century ecological forecast with partitioned uncertainty predicts increases in loblolly pine forest productivity. Ecological Applications 28: 1503-1519 [link]

ACONITE (Analyzing of CarbON Nitrogen Interactions in Terrestrial Ecosystems)

ACONITE is a simple model of ecosystem C-N cycling and interactions that builds on theory related to plant economics in order to predict key ecosystem properties (leaf area index, leaf C:N, N fixation, and plant C use efficiency). Developed by research group and Mat Williams at the University of Edinburgh.

Please contact us for more information about the model and model code.  A github site for the model is pending.


Thomas, R. Q. and Williams, M.: A model using marginal efficiency of investment to analyze carbon and nitrogen interactions in terrestrial ecosystems (ACONITE Version 1), Geosci. Model Dev., 7, 2015-2037, doi:10.5194/gmd-7-2015-2014, 2014.

Community Earth System Model (CESM) including the Community Land Model (CLM)

We contribute to the evaluation, development, and application of the Community Land Model to study how nutrient limitation of forest ecosystems and forest management influence the climate system.



Wieder, W. R., D. M. Lawrence, R. A. Fisher, G. B. Bonan, S. J. Cheng, C. L. Goodale, C. D. Koven, D. L. Lombardozzi, K. W. Oleson, and R. Q. Thomas. Beyond static benchmarking: Evaluating model assumptions with experimental manipulations. Accepted at Global Biogeochemical Cycles.

Cheng, S. J, P. Hess, W.  R. Wieder, R. Q. Thomas, K. J. Nadelhoffer, and C. L. Goodale. 2019. Decadal fates and impacts of nitrogen additions on temperate forest carbon storage: a data–model comparison. Biogeosciences 16: 2771-2793

Ahlswede, B. J. and R. Q. Thomas. 2017.  Community Earth System Model Simulations Reveal the Relative Importance of Afforestation and Forest Management to Surface Temperature in Eastern North America.  Forests 8: 499

Thomas, R.Q., E.N.J. Brookshire, and S. Gerber. 2015. Nitrogen limitation on land: How can it occur in Earth system models? Global Change Biology 21: 1777–1793

Thomas, R. Q., S. Zaehle, P.H. Templer, and C.L. Goodale. 2013. Global patterns of nitrogen limitation: Confronting two global biogeochemical models with observations.  Global Change Biology 19: 2986–2998.

Thomas, R. Q., G. B. Bonan, and C. L. Goodale. 2013.  Insights into mechanisms governing forest carbon response to nitrogen deposition: a model-data comparison using observed responses to nitrogen addition. Biogeosciences 10: 3869–3887.

Forecasting Lake and Reservoir Ecosystems (FLARE)

We have developed a framework for forecasting the physics, chemistry, and biology of aquatic ecosystems.  FLARE uses data assimilation to update and forecast using the General Lake Model.  Developed as part of the Smart Reservoir project, an NSF-funded project.

FLARE on GitHub

GLM is an open source, community developed model