Spatial and temporal patterns of global soil heterotrophic respiration in terrestrial ecosystems

Tang, Xiaolu; Fan, Shaohui; Du, Manyi; Zhang, Wenjie; Gao, Sicong; Liu, Shibin; Chen, Guo; Yu, Zhen; Yang, Wunian

doi:https://doi.org/10.5194/essd-12-1037-2020

Articles | Volume 12, issue 2

https://doi.org/10.5194/essd-12-1037-2020

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

https://doi.org/10.5194/essd-12-1037-2020

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

Articles | Volume 12, issue 2

Data description paper

|

07 May 2020

Data description paper |

| 07 May 2020

Spatial and temporal patterns of global soil heterotrophic respiration in terrestrial ecosystems

Xiaolu Tang, Shaohui Fan, Manyi Du, Wenjie Zhang, Sicong Gao, Shibin Liu, Guo Chen, Zhen Yu, and Wunian Yang

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Final revised paper (published on 07 May 2020)
Supplement to the final revised paper
Preprint (discussion started on 03 Sep 2019)
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Interactive discussion

Status: closed

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

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RC1: 'Good analysis of a novel and important dataset', Ben Bond-Lamberty, 05 Oct 2019
- AC1: 'Response to reviwer 1#', Xiaolu Tang, 16 Dec 2019
RC2: 'Dataset itself is problematic', Ben Bond-Lamberty, 06 Oct 2019
- AC2: 'Response to reviewer 1#-dataset', Xiaolu Tang, 16 Dec 2019
RC3: 'Comments', Anonymous Referee #2, 06 Dec 2019
- AC3: 'Response to reviewer 2#', Xiaolu Tang, 16 Dec 2019

Peer-review completion

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

AR by Xiaolu Tang on behalf of the Authors (16 Dec 2019) Author's response

ED: Referee Nomination & Report Request started (27 Jan 2020) by Yuyu Zhou

RR by Anonymous Referee #3 (15 Mar 2020)

Suggestions for revision or reasons for rejection

Tang et al presented to the carbon science community an interesting dataset of RH, which may be helpful for benchmarking terrestrial biogeochemical models. They also conducted a number of statistical comparisons with other datasets, including the Hashimoto RH, and the TRENDY model outputs, and found some very interesting and logically sound patterns. Overall, I agree with the previous reviewers that this study merits publication. And the authors have worked hard to address the concerns raised in the first 3 reviewers. That being said, however, I still think the paper has some linguistic problems (more than grammar and syntax), which need to be carefully attended before the paper can be accepted. I will give my details below.

P1, L21-22: “high variations and uncertainties of RH existing in global carbon cycling models require an urgent development of data-derived RH dataset”. Although I understand the value of a data-derived RH dataset, I don’t think the logic here is well established. For instance, I can equally say a more mechanistically based modeling approach is more urgently needed. What a data-derived RH dataset will do is to provide a different angle to quantify the RH besides the biogeochemical modeling approach.

P2, L51-2: “Although it is widely recognized that warming enhances CO2 release from soils, the magnitude of release is uncertain due to variations in the temperature sensitivity of soil organic matter decomposition”. This statement is generally right, but insufficient. Because when talking about climate responses (aka warming here), the uncertainty involves both temperature and moisture, with all other granularities under the hood. I believer, this sentence need be revised to better connect with the next sentence.

P3, L66-67: “potential new numerical/algorithmic methods to better quantification and understanding of large-scale soil carbon flux”. There are misuses of adverb, and verb here. Please correct.

P3, L79: “empirically” should be “empirical”.

P3, L89 and throughout the paper: “global vegetation models” is not the right jargon, “terrestrial biogeochemical models” or “land biogeochemical models” are more often used.

P6, L169: In what way “the other two proxies were controlled”?

P7, L218: “reflecting less stress from environmental limitations”. This statement is unclear. The first half of the sentence made a contrast, manifesting a gradient-like transition, but this statement does not describe this clearly.

P8, L286: “than RH from satellite-driven estimates”, seems missing a word like “more” or “higher”.

P12, L360: “negatively feeding back to future climate change”. I was not able to figure out the logic behind this inference.

P12, L374-375: The sentence should be better broken into two, because it is mumbling currently.

P12, L376-377: “This developed RH dataset provides several advantages to the estimation of global RH”. The advantage should be established within a comparison, however, what are compared here is unclear. After all, you don’t want to people to guess, and guessing is prone to misunderstanding.

Section 4.5: Overall the authors did discuss the limitations of this study. But I think if they formulate this alternatively by stating what use can be made with this dataset will be more helpful. Of course, it is up to the authors’ decision.

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ED: Publish subject to minor revisions (review by editor) (19 Mar 2020) by Yuyu Zhou

AR by Xiaolu Tang on behalf of the Authors (26 Mar 2020) Author's response Manuscript

ED: Publish as is (07 Apr 2020) by Yuyu Zhou

AR by Xiaolu Tang on behalf of the Authors (07 Apr 2020)

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Short summary

Global soil heterotrophic respiration (RH) was modelled using Random Forest by linking published observations and globally gridded environmental variables. Globally, RH increased from 55.8 to 58.3 Pg C a⁻¹ with an increasing trend of 0.036 ± 0.007 Pg C a⁻² and an annual mean RH of 57.2 ± 0.6 Pg C a⁻¹ over 1980–2016. The developed RH dataset has great potential to serve as a benchmark to constrain global vegetation models.