Articles | Volume 13, issue 11
https://doi.org/10.5194/bg-13-3305-2016
https://doi.org/10.5194/bg-13-3305-2016
Research article
 | 
06 Jun 2016
Research article |  | 06 Jun 2016

Modelling interannual variation in the spring and autumn land surface phenology of the European forest

Victor F. Rodriguez-Galiano, Manuel Sanchez-Castillo, Jadunandan Dash, Peter M. Atkinson, and Jose Ojeda-Zujar

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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
ED: Reconsider after major revisions (14 Jan 2016) by Andreas Ibrom
AR by Victor Rodriguez-Galiano on behalf of the Authors (02 Mar 2016)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (07 Mar 2016) by Andreas Ibrom
RR by Anonymous Referee #1 (05 Apr 2016)
ED: Reconsider after major revisions (13 Apr 2016) by Andreas Ibrom
AR by Victor Rodriguez-Galiano on behalf of the Authors (22 Apr 2016)
ED: Publish subject to minor revisions (Editor review) (11 May 2016) by Andreas Ibrom
AR by Victor Rodriguez-Galiano on behalf of the Authors (11 May 2016)  Author's response   Manuscript 
ED: Publish as is (14 May 2016) by Andreas Ibrom
AR by Victor Rodriguez-Galiano on behalf of the Authors (16 May 2016)
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Short summary
This research reveals new insights into the weather drivers of land surface phenology (LSP) across the entire European forest, while at the same time it establishes a new conceptual framework for modelling LSP. Specifically, a sophisticated machine learning regression method (RF) was introduced for LSP modelling across very large areas and across multiple years simultaneously. The RF models explained 81 and 62 % of the variance in the spring and autumn LSP interannual variation.
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