Articles | Volume 21, issue 2
Research article
30 Jan 2024
Research article |  | 30 Jan 2024

Evaluation of five models for constructing forest NPP–age relationships in China based on 3121 field survey samples

Peng Li, Rong Shang, Jing M. Chen, Mingzhu Xu, Xudong Lin, Guirui Yu, Nianpeng He, and Li Xu


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2023-137', Liming He, 07 Sep 2023
    • AC1: 'Reply on RC1', Rong Shang, 17 Nov 2023
  • RC2: 'Comment on bg-2023-137', Anonymous Referee #2, 31 Oct 2023
    • AC2: 'Reply on RC2', Rong Shang, 17 Nov 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (30 Nov 2023) by David Medvigy
AR by Rong Shang on behalf of the Authors (12 Dec 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (13 Dec 2023) by David Medvigy
RR by Anonymous Referee #1 (18 Dec 2023)
ED: Publish as is (18 Dec 2023) by David Medvigy
AR by Rong Shang on behalf of the Authors (19 Dec 2023)
Short summary
The amount of carbon that forests gain from the atmosphere, called net primary productivity (NPP), changes a lot with age. These forest NPP–age relationships could be modeled from field survey data, but we are not sure which model works best. Here we tested five different models using 3121 field survey samples in China, and the semi-empirical mathematical (SEM) function was determined as the optimal. The relationships built by SEM can improve China's forest carbon modeling and prediction.
Final-revised paper