Articles | Volume 10, issue 9
Development and technical paper
25 Sep 2017
Development and technical paper |  | 25 Sep 2017

Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming

Iulia Ilie, Peter Dittrich, Nuno Carvalhais, Martin Jung, Andreas Heinemeyer, Mirco Migliavacca, James I. L. Morison, Sebastian Sippel, Jens-Arne Subke, Matthew Wilkinson, and Miguel D. Mahecha


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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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
AR by Iulia Ilie on behalf of the Authors (29 Aug 2017)  Manuscript 
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.