A survey of proximal methods for monitoring leaf phenology in temperate deciduous forests

Soudani, Kamel; Delpierre, Nicolas; Berveiller, Daniel; Hmimina, Gabriel; Pontailler, Jean-Yves; Seureau, Lou; Vincent, Gaëlle; Dufrêne, Éric

doi:https://doi.org/10.5194/bg-18-3391-2021

Articles | Volume 18, issue 11

https://doi.org/10.5194/bg-18-3391-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-18-3391-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 11

Research article

|

07 Jun 2021

Research article |

| 07 Jun 2021

A survey of proximal methods for monitoring leaf phenology in temperate deciduous forests

Kamel Soudani, Nicolas Delpierre, Daniel Berveiller, Gabriel Hmimina, Jean-Yves Pontailler, Lou Seureau, Gaëlle Vincent, and Éric Dufrêne

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Final revised paper (published on 07 Jun 2021)
Supplement to the final revised paper
Preprint (discussion started on 02 Dec 2020)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Comment', Anonymous Referee #1, 09 Jan 2021
- AC1: 'Reply on RC1', Kamel Soudani, 07 Apr 2021
RC2: 'good study with room for improvement', Anonymous Referee #2, 17 Mar 2021
- AC2: 'Reply on RC2', Kamel Soudani, 07 Apr 2021

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (review by editor) (08 Apr 2021) by Trevor Keenan

AR by Kamel Soudani on behalf of the Authors (12 Apr 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (12 Apr 2021) by Trevor Keenan

AR by Kamel Soudani on behalf of the Authors (14 Apr 2021) Author's response Manuscript

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Short summary

We present an exhaustive comparative survey of eight proximal methods to estimate forest phenology. We focused on methodological aspects and thoroughly assessed deviations between predicted and observed phenological dates and pointed out their main causes. We show that proximal methods provide robust phenological metrics. They can be used to retrieve long-term phenological series at flux measurement sites and help interpret the interannual variability and trends of mass and energy exchanges.