Articles | Volume 14, issue 14
Biogeosciences, 14, 3525–3547, 2017
https://doi.org/10.5194/bg-14-3525-2017
Biogeosciences, 14, 3525–3547, 2017
https://doi.org/10.5194/bg-14-3525-2017

Research article 26 Jul 2017

Research article | 26 Jul 2017

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

R. Quinn Thomas et al.

Data sets

The Duke FACE study H. R. McCarthy, R. Oren,K. H. Johnsen, A. Gallet-Budynek, S. G. Pritchard, C. W. Cook, S. L. LaDeau, R. B. Jackson, and A. C. Finzi https://doi.org/10.1111/j.1469-8137.2009.03078.x

The PINEMAP studies Terrestrial Carbon (TerraC) Information System http://terrac.ifas.ufl.edu

The US-DK3 eddy-flux tower data Ameriflux database http://ameriflux.lbl.gov

SSURGO soils database USDA https://sdmdataaccess.sc.egov.usda.gov

The Waycross data C. Bryars, C. Maier, D. Zhao, M. Kane, B. Borders, R. Will,and R. Teskey https://doi.org/10.1016/j.foreco.2012.09.031

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Short summary
To improve predictions of future forest productivity, we introduce an analytical approach that uses data from numerous research experiments that have occurred across the southeastern US to calibrate a mathematical forest model and estimate uncertainty in predictions. As a result, predictions using the model are consistent with a rich history of forest research in a region that supplies a large fraction of wood products to the world.
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