Articles | Volume 10, issue 9
https://doi.org/10.5194/gmd-10-3519-2017
https://doi.org/10.5194/gmd-10-3519-2017
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

Viewed

Total article views: 3,649 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,436 1,056 157 3,649 348 152 167
  • HTML: 2,436
  • PDF: 1,056
  • XML: 157
  • Total: 3,649
  • Supplement: 348
  • BibTeX: 152
  • EndNote: 167
Views and downloads (calculated since 07 Nov 2016)
Cumulative views and downloads (calculated since 07 Nov 2016)

Viewed (geographical distribution)

Total article views: 3,649 (including HTML, PDF, and XML) Thereof 3,433 with geography defined and 216 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Discussed (final revised paper)

Latest update: 12 Jul 2024
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.