Preprints
https://doi.org/10.5194/egusphere-2022-49
https://doi.org/10.5194/egusphere-2022-49
 
17 Mar 2022
17 Mar 2022

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

Jing Fang1,2, Herman Shugart3, Feng Liu1,2, Xiaodong Yan4, Yunkun Song4, and Fucheng Lv4 Jing Fang et al.
  • 1CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China
  • 2Center of Plant Ecology, Core Botanical Gardens, Chinese Academy of Sciences, Wuhan 430074, China
  • 3Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USA
  • 4State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China

Abstract. Process-based ecological models are essential tools to quantify and predict forest growth and carbon cycle under the background of climate change. The accurate description of phenology and tree growth processes enables an improved understanding and predictive modeling of forest dynamics. An individual tree-based carbon model, FORCCHN2 (FORest ecosystem Carbon budget model for CHiNa Version 2.0), used the non-structural carbohydrates (NSC) pools to couple tree growth and phenology. This model performed well in reducing uncertainty in predicting forest carbon fluxes. Here, we describe the framework in detail and provide the source code of FORCCHN2. We also present a Dynamic Link Library (DLL) package containing the latest version of the FORCCHN2 model. This package has the advantage of using Fortran as an interface to make the model runs fast on a daily step, the package also allows the users to call it with their preferred computer tools (e.g., Matlab, R, Python, etc.). FORCCHN2 model can be used directly to predict the yearly phenology as well as the daily carbon fluxes (including photosynthesis, above- and belowground autotrophic respiration, and soil heterotrophic respiration) and biomass on plot, regional, and global scales. As case studies, we provide an example of the FORCCHN2 running, model validations in 78 forest sites, and an example model application for the carbon dynamics of Northern Hemisphere forests. We demonstrate the FORCCHN2 model can produce a reasonable agreement with flux observations. Given the potential importance of the application of this ecological model in many studies, there is substantial scope for using the FORCCHN2 model in fields as diverse as forest ecology, climate change, and carbon estimations.

Journal article(s) based on this preprint

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
Geosci. Model Dev., 15, 6863–6872, https://doi.org/10.5194/gmd-15-6863-2022,https://doi.org/10.5194/gmd-15-6863-2022, 2022
Short summary

Jing Fang et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-49', Anonymous Referee #1, 06 May 2022
    • AC1: 'Reply on RC1', Jing Fang, 29 Jun 2022
  • RC2: 'Comment on egusphere-2022-49', Anonymous Referee #2, 01 Jun 2022
    • AC2: 'Reply on RC2', Jing Fang, 29 Jun 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-49', Anonymous Referee #1, 06 May 2022
    • AC1: 'Reply on RC1', Jing Fang, 29 Jun 2022
  • RC2: 'Comment on egusphere-2022-49', Anonymous Referee #2, 01 Jun 2022
    • AC2: 'Reply on RC2', Jing Fang, 29 Jun 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Jing Fang on behalf of the Authors (06 Jul 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (08 Jul 2022) by Tomomichi Kato
RR by Anonymous Referee #2 (01 Aug 2022)
ED: Publish as is (22 Aug 2022) by Tomomichi Kato

Journal article(s) based on this preprint

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
Geosci. Model Dev., 15, 6863–6872, https://doi.org/10.5194/gmd-15-6863-2022,https://doi.org/10.5194/gmd-15-6863-2022, 2022
Short summary

Jing Fang et al.

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Short summary
Our study provided the detailed description and a package of an individual tree-based carbon model, FORCCHN2. This model used the non-structural carbohydrates (NSC) pools to couple tree growth and phenology. The model could reproduce the daily carbon fluxes across the Northern Hemisphere forests. Given the potential importance of the application of this model, there is substantial scope for using the FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimations.