Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale

Li, Wei; Ciais, Philippe; Stehfest, Elke; van Vuuren, Detlef; Popp, Alexander; Arneth, Almut; Di Fulvio, Fulvio; Doelman, Jonathan; Humpenöder, Florian; Harper, Anna B.; Park, Taejin; Makowski, David; Havlik, Petr; Obersteiner, Michael; Wang, Jingmeng; Krause, Andreas; Liu, Wenfeng

doi:https://doi.org/10.5194/essd-12-789-2020

Articles | Volume 12, issue 2

https://doi.org/10.5194/essd-12-789-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-12-789-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 2

Data description paper

|

02 Apr 2020

Data description paper |

| 02 Apr 2020

Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale

Wei Li, Philippe Ciais, Elke Stehfest, Detlef van Vuuren, Alexander Popp, Almut Arneth, Fulvio Di Fulvio, Jonathan Doelman, Florian Humpenöder, Anna B. Harper, Taejin Park, David Makowski, Petr Havlik, Michael Obersteiner, Jingmeng Wang, Andreas Krause, and Wenfeng Liu

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Final revised paper (published on 02 Apr 2020)
Supplement to the final revised paper
Preprint (discussion started on 05 Aug 2019)
Supplement to the preprint

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Comments on "Monthly Gridded Data Product of Northern Wetland Methane Emissions Based on Upscaling Eddy Covariance Observations"', Anonymous Referee #1, 27 Oct 2019
- AC1: 'reply to Reviewer 1', Wei Li, 31 Dec 2019
RC2: 'comments', Anonymous Referee #2, 28 Oct 2019
- AC2: 'reply to Reviewer 2', Wei Li, 31 Dec 2019

Peer-review completion

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

AR by Wei Li on behalf of the Authors (19 Jan 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (22 Jan 2020) by Scott Stevens

RR by Anonymous Referee #2 (10 Feb 2020)

ED: Publish subject to technical corrections (25 Feb 2020) by Scott Stevens

AR by Wei Li on behalf of the Authors (26 Feb 2020) Manuscript

Short summary

We generated spatially explicit bioenergy crop yields based on field measurements with climate, soil condition and remote-sensing variables as explanatory variables and the machine-learning method. We further compared our yield maps with the maps from three integrated assessment models (IAMs; IMAGE, MAgPIE and GLOBIOM) and found that the median yields in our maps are > 50 % higher than those in the IAM maps.