EGU26-7603, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-7603
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Wednesday, 06 May, 14:00–15:45 (CEST), Display time Wednesday, 06 May, 14:00–18:00
 
Hall X1, X1.22
TECO-CNP Sv1.0: a coupled carbon-nitrogen-phosphorus model  with data assimilation for subtropical forests
Fangxiu Wan1, Chenyu Bian1, Ensheng Weng2, Yiqi Luo3, Kun Huang1, and Jianyang Xia1
Fangxiu Wan et al.
  • 1Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai
  • 2Center for Climate Systems Research, Columbia University, New York, NY 10964, USA
  • 3School of Integrative Plant Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853, USA

Subtropical forests play a crucial role in the global carbon cycle, yet their carbon sink capacity is significantly constrained by phosphorus availability. Models that omit phosphorus dynamics risk overestimating carbon sinks, potentially undermining the scientific basis for carbon neutrality strategies. In this study, we developed TECO-CNP Sv1.0, a coupled carbon-nitrogen-phosphorus model based on the Terrestrial ECOsystem (TECO) model, which explicitly captures key biogeochemical interactions and nutrient-regulated carbon cycling. The model simulates how plant growth and carbon partitioning respond to both external soil nutrient availability and internal physiological constraints, enabling plant acclimation to varying nutrient conditions. Using observations from a phosphorus-limited subtropical forest in East China, we first evaluated the model’s performance in estimating state variables with empirically calibrated parameters. Compared to the C-only and coupled C-N configurations, the CNP model more accurately reproduced the observed pools of plant and soil C, N, and P. To systematically optimize model parameters and reduce uncertainties in predictions, we further incorporated a built-in data assimilation framework for parameter optimization. The CNP model with optimized parameters significantly improved carbon flux estimates, reducing root mean square errors and enhancing concordance correlation coefficients for gross primary productivity, ecosystem respiration, and net ecosystem exchange. By explicitly incorporating phosphorus dynamics and data assimilation, this study provides a more accurate and robust framework for predicting carbon sequestration in phosphorus-limited subtropical forests.

How to cite: Wan, F., Bian, C., Weng, E., Luo, Y., Huang, K., and Xia, J.: TECO-CNP Sv1.0: a coupled carbon-nitrogen-phosphorus model  with data assimilation for subtropical forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7603, https://doi.org/10.5194/egusphere-egu26-7603, 2026.