Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 3519-3545, 2017
https://doi.org/10.5194/gmd-10-3519-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper
25 Sep 2017
Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming
Iulia Ilie et al.
Download
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'Comment to the authors', Anonymous Referee #1, 22 Dec 2016 Printer-friendly Version 
AC1: 'Reply to reviewer 1', Iulia Ilie, 01 Mar 2017 Printer-friendly Version 
 
RC2: 'Review of “Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming”', Anonymous Referee #2, 24 Dec 2016 Printer-friendly Version 
AC2: 'Reply to reviewer 2', Iulia Ilie, 01 Mar 2017 Printer-friendly Version 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Iulia Ilie on behalf of the Authors (10 Apr 2017)  Author's response  Manuscript
ED: Referee Nomination & Report Request started (24 Apr 2017) by Sandra Arndt
RR by Anonymous Referee #1 (12 Jun 2017)  
ED: Reconsider after major revisions (13 Jun 2017) by Sandra Arndt  
AR by Iulia Ilie on behalf of the Authors (31 Jul 2017)  Author's response  Manuscript
ED: Publish as is (21 Aug 2017) by Sandra Arndt
CC BY 4.0
Publications Copernicus
Download
Short summary
Accurate representation of land-atmosphere carbon fluxes is essential for future climate projections, although some of the responses of CO2 fluxes to climate often remain uncertain. The increase in available data allows for new approaches in their modelling. We automatically developed models for ecosystem and soil carbon respiration using a machine learning approach. When compared with established respiration models, we found that they are better in prediction as well as offering new insights.
Accurate representation of land-atmosphere carbon fluxes is essential for future climate...
Share