Articles | Volume 15, issue 17
Model description paper
09 Sep 2022
Model description paper |  | 09 Sep 2022

FORCCHN V2.0: an individual-based model for predicting multiscale forest carbon dynamics

Jing Fang, Herman H. Shugart, Feng Liu, Xiaodong Yan, Yunkun Song, and Fucheng Lv

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Cited articles

Balzarolo, M., Boussetta, S., Balsamo, G., Beljaars, A., Maignan, F., Calvet, J.-C., Lafont, S., Barbu, A., Poulter, B., Chevallier, F., Szczypta, C., and Papale, D.: Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network, Biogeosciences, 11, 2661–2678,, 2014. 
Fang, J.: Daily and annual carbon flux predicted by FORCCHN2 model, Figshare [data set],, 2022. 
Fang, J., Lutz, J. A., Shugart, H. H., and Yan, X.: A physiological model for predicting dynamics of tree stem-wood non-structural carbohydrates, J. Ecol., 108, 702–718,, 2020a. 
Short summary
Our study provided a detailed description and a package of an individual tree-based carbon model, FORCCHN2. This model used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. The model could reproduce daily carbon fluxes across Northern Hemisphere forests. Given the potential importance of the application of this model, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimation.