Examining bias in pollen-based quantitative climate reconstructions induced by human impact on vegetation  in China

Ding, Wei; Xu, Qinghai; Tarasov, Pavel E.

doi:https://doi.org/10.5194/cp-13-1285-2017

Articles | Volume 13, issue 9

https://doi.org/10.5194/cp-13-1285-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/cp-13-1285-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 13, issue 9

Research article

|

28 Sep 2017

Research article |

| 28 Sep 2017

Examining bias in pollen-based quantitative climate reconstructions induced by human impact on vegetation in China

Wei Ding, Qinghai Xu, and Pavel E. Tarasov

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Final revised paper (published on 28 Sep 2017)
Preprint (discussion started on 03 May 2017)

Interactive discussion

Status: closed

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

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RC1: 'A good example to illustrate the difference between pure-natural and human-impact effect on vegetation', Anonymous Referee #1, 18 May 2017
- AC1: 'Response to Reviewer #1', Wei Ding, 25 Aug 2017
RC2: 'this paper is well written, very clear and concise, and sufficiently interdisciplinary in content to be published in Climate of the Past', Anonymous Referee #2, 29 Jun 2017
- AC2: 'Response to Reviewer #2', Wei Ding, 25 Aug 2017

Peer-review completion

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

ED: Publish subject to technical corrections (29 Aug 2017) by Dominik Fleitmann

AR by Wei Ding on behalf of the Authors (30 Aug 2017) Author's response Manuscript

Short summary

Pollen-based past climate reconstruction for regions with long-term human occupation is always controversial. We examined the bias induced by the human impact on vegetation in a climate reconstruction for temperate eastern China by comparing the deviations in the reconstructed results for a fossil record based on two pollen–climate calibration sets. Climatic signals in pollen assemblages are indeed obscured by human impact; however, the extent of the bias could be assessed.