the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Sep 2023
A modern pollen dataset from lake surface sediments on the central-western Tibetan Plateau
Qingfeng Ma
Jianting Ju
Junbo Wang
Yong Wang
Lei Huang
Torsten Haberzettl
Abstract. Modern pollen datasets are essential for pollen-based quantitative paleoclimate (e.g. precipitation) reconstructions, which can aid to better understand recent climate change and its underlying forcing mechanisms. A modern pollen dataset based on surface sediments from 90 lakes in the shrub, meadow, steppe and desert regions of the central and western Tibetan Plateau (TP) was established to fill geographical gaps left by previous datasets. Ordination analyses of pollen data and climatic parameters revealed that annual precipitation is the dominant factor for modern pollen distribution on the central and western TP. A regional transfer function for annual precipitation was developed with the weighted averaging partial least squares (WAPLS), which suggests a good inference power of the modern pollen dataset for annual precipitation. A case study in which the transfer function was effectively applied to a fossil pollen record from Lake Tangra Yumco on the central TP for paleoprecipitation reconstruction demonstrated the significance of the modern pollen dataset in less data region for paleoclimate change studies. Data from this study are openly available via the Zenodo portal (Ma et al., 2023; https://doi.org/10.5281/zenodo.8008474).
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Qingfeng Ma et al.
Status: closed
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RC1: 'Comment on essd-2023-215', Anonymous Referee #1, 03 Oct 2023
The strength of the paper and the dataset is that the modern pollen surface samples are from lake sediments. This is an edge compared to most other modern pollen datasets from China and other regions. The procedure for using this dataset for constructing a pollen-climate calibration model is described in the paper, and it follows a standard routine with WA-PLS-based quantitative climate reconstructions. The data and the results are generally clearly presented, although the paper is very short with hardly any relevant discussion.
As a data description, the paper can be fine as such, but it would interesting to develop the study in the future. The authors stress the importance of having both the modern pollen samples and fossil pollen samples from the same sedimentary environment, lakes in this case, and I agree with this. Consequently, it would be interesting to test whether the current calibration model works better as compared to the calibration models based on samples collected from varying sedimentary environments, such as topsoils, moss polsters etc.
Another interesting angle for the study would be to apply some novel transfer function approach in the study. In Fig. 4 we can see that the calibration model has a quite serious bias towards too low values at the upper end of the precipitation gradient. The authors briefly comment on this underestimation of high values. Such an edge effect is a typical problem with WA-PLS-based transfer functions. An amendment has been suggested with the use of tolerance-weighted WA-PLS (Liu et al., 2020) and it would be really interesting to see whether the use of tolerance-weighted WA-PLS would improve the edge effect problem in the calibration model and influence the precipitation reconstruction shown in Fig. 6.
Some minor remarks
-page 2 line 36 “reconstruction of climate data” remove “data”
-page 2 line 51 remove “desperately”
-page 3 as this is a dataset paper, it would be better to include key data from all 90 sites, such as location, altitude, climate etc.
-page 4 Fig. 1 add an index map
-page 5 lines 103-104. This in unclear. What does “reanalysis datasets” mean? And how were the altitudinal differences handled? Was the windward or leeward side location of the lakes in relation to the mountains considered?
-page 6 add citations to the selection of RDA as the linear method and add citations to the use of VIF to check for collinearity.
-page 7 line 137 “a novel method” delete “novel”. What was novel in 2011 is not novel any more.
-page 9 It would have been better not to remove this one outlier site from the dataset. While outliers are sometimes deleted this way, it is a questionable thing to do. Firstly, it is an easy trick to improve performance statistics by removing the “dodgy” samples. Secondly, the performance statistics of the current dataset (e.g. R2 values) cannot be compared directly with other datasets in which no samples have been removed.
References
Liu, M. et al. 2020. An improved statistical approach for reconstructing past climates from biotic assemblages. Proc.R.Soc.A476:20200346.https://doi.org/10.1098/rspa.2020.0346
Citation: https://doi.org/10.5194/essd-2023-215-RC1 -
RC2: 'Reply on RC1', Anonymous Referee #2, 04 Oct 2023
In this manuscript, the authors present a modern pollen dataset based on surface sediments from 90 lakes covering the central and western Tibetan Plateau, and applied it to reconstruct the paleoprecipitation of a fossil pollen record from Lake Tangra Yumco on the central TP. This study provides a significant dataset for modern pollen research in the TP. The results of the investigation are important and this is a very interesting paper, I believe upon update will be a good article. Therefore, I suggest that some minor issues to be improved.
1) In the Study area, only the climate and vegetation are included, adding the geological and geomorphological information would provide a more comprehensive understanding, because these may also affect pollen assemblages.
2) Quercus E and Quercus D should be marked with their full names when they first appear in the text.
3) The sum of Variance explained of Pann, TJan and TJuly in RDA results is only 35.3%. Is there any influence of other factors considered?
4) Line 212, What the “Hill‟s N2” means?
5)”This dataset can be openly accessible via Zenodo portal: https://doi.org/10.5281/zenodo.8008474”, the URL cannot be opened, please check whether the URL is correct.
Citation: https://doi.org/10.5194/essd-2023-215-RC2 -
AC2: 'Reply on RC2', Liping Zhu, 30 Oct 2023
Dear reviewer,
We sincerely thank you for your feedback on our manuscript (No. essd-2023-215). Those comments and suggestions are very valuable and helpful for revising and improving our manuscript. Please see the point-by-point responses to your comments in the attachment. The reviewer’s comments are laid out in italicized font and have been numbered. Each comment is followed by our response to this comment in normal font. We hope that our revisions meet the expected standards.
Yours Sincerely,
Prof. Dr. Liping Zhu
Corresponding author and on behalf of all the authors
-
AC2: 'Reply on RC2', Liping Zhu, 30 Oct 2023
-
AC1: 'Reply on RC1', Liping Zhu, 30 Oct 2023
Dear reviewer,
We sincerely thank you for your feedback on our manuscript (No. essd-2023-215). Those comments and suggestions are very valuable and helpful for revising and improving our manuscript. Please see the point-by-point responses to your comments in the attachment. The reviewer’s comments are laid out in italicized font and have been numbered. Each comment is followed by our response to this comment in normal font. We hope that our revisions meet the expected standards.
Yours Sincerely,
Prof. Dr. Liping Zhu
Corresponding author and on behalf of all the authors
-
RC2: 'Reply on RC1', Anonymous Referee #2, 04 Oct 2023
Status: closed
-
RC1: 'Comment on essd-2023-215', Anonymous Referee #1, 03 Oct 2023
The strength of the paper and the dataset is that the modern pollen surface samples are from lake sediments. This is an edge compared to most other modern pollen datasets from China and other regions. The procedure for using this dataset for constructing a pollen-climate calibration model is described in the paper, and it follows a standard routine with WA-PLS-based quantitative climate reconstructions. The data and the results are generally clearly presented, although the paper is very short with hardly any relevant discussion.
As a data description, the paper can be fine as such, but it would interesting to develop the study in the future. The authors stress the importance of having both the modern pollen samples and fossil pollen samples from the same sedimentary environment, lakes in this case, and I agree with this. Consequently, it would be interesting to test whether the current calibration model works better as compared to the calibration models based on samples collected from varying sedimentary environments, such as topsoils, moss polsters etc.
Another interesting angle for the study would be to apply some novel transfer function approach in the study. In Fig. 4 we can see that the calibration model has a quite serious bias towards too low values at the upper end of the precipitation gradient. The authors briefly comment on this underestimation of high values. Such an edge effect is a typical problem with WA-PLS-based transfer functions. An amendment has been suggested with the use of tolerance-weighted WA-PLS (Liu et al., 2020) and it would be really interesting to see whether the use of tolerance-weighted WA-PLS would improve the edge effect problem in the calibration model and influence the precipitation reconstruction shown in Fig. 6.
Some minor remarks
-page 2 line 36 “reconstruction of climate data” remove “data”
-page 2 line 51 remove “desperately”
-page 3 as this is a dataset paper, it would be better to include key data from all 90 sites, such as location, altitude, climate etc.
-page 4 Fig. 1 add an index map
-page 5 lines 103-104. This in unclear. What does “reanalysis datasets” mean? And how were the altitudinal differences handled? Was the windward or leeward side location of the lakes in relation to the mountains considered?
-page 6 add citations to the selection of RDA as the linear method and add citations to the use of VIF to check for collinearity.
-page 7 line 137 “a novel method” delete “novel”. What was novel in 2011 is not novel any more.
-page 9 It would have been better not to remove this one outlier site from the dataset. While outliers are sometimes deleted this way, it is a questionable thing to do. Firstly, it is an easy trick to improve performance statistics by removing the “dodgy” samples. Secondly, the performance statistics of the current dataset (e.g. R2 values) cannot be compared directly with other datasets in which no samples have been removed.
References
Liu, M. et al. 2020. An improved statistical approach for reconstructing past climates from biotic assemblages. Proc.R.Soc.A476:20200346.https://doi.org/10.1098/rspa.2020.0346
Citation: https://doi.org/10.5194/essd-2023-215-RC1 -
RC2: 'Reply on RC1', Anonymous Referee #2, 04 Oct 2023
In this manuscript, the authors present a modern pollen dataset based on surface sediments from 90 lakes covering the central and western Tibetan Plateau, and applied it to reconstruct the paleoprecipitation of a fossil pollen record from Lake Tangra Yumco on the central TP. This study provides a significant dataset for modern pollen research in the TP. The results of the investigation are important and this is a very interesting paper, I believe upon update will be a good article. Therefore, I suggest that some minor issues to be improved.
1) In the Study area, only the climate and vegetation are included, adding the geological and geomorphological information would provide a more comprehensive understanding, because these may also affect pollen assemblages.
2) Quercus E and Quercus D should be marked with their full names when they first appear in the text.
3) The sum of Variance explained of Pann, TJan and TJuly in RDA results is only 35.3%. Is there any influence of other factors considered?
4) Line 212, What the “Hill‟s N2” means?
5)”This dataset can be openly accessible via Zenodo portal: https://doi.org/10.5281/zenodo.8008474”, the URL cannot be opened, please check whether the URL is correct.
Citation: https://doi.org/10.5194/essd-2023-215-RC2 -
AC2: 'Reply on RC2', Liping Zhu, 30 Oct 2023
Dear reviewer,
We sincerely thank you for your feedback on our manuscript (No. essd-2023-215). Those comments and suggestions are very valuable and helpful for revising and improving our manuscript. Please see the point-by-point responses to your comments in the attachment. The reviewer’s comments are laid out in italicized font and have been numbered. Each comment is followed by our response to this comment in normal font. We hope that our revisions meet the expected standards.
Yours Sincerely,
Prof. Dr. Liping Zhu
Corresponding author and on behalf of all the authors
-
AC2: 'Reply on RC2', Liping Zhu, 30 Oct 2023
-
AC1: 'Reply on RC1', Liping Zhu, 30 Oct 2023
Dear reviewer,
We sincerely thank you for your feedback on our manuscript (No. essd-2023-215). Those comments and suggestions are very valuable and helpful for revising and improving our manuscript. Please see the point-by-point responses to your comments in the attachment. The reviewer’s comments are laid out in italicized font and have been numbered. Each comment is followed by our response to this comment in normal font. We hope that our revisions meet the expected standards.
Yours Sincerely,
Prof. Dr. Liping Zhu
Corresponding author and on behalf of all the authors
-
RC2: 'Reply on RC1', Anonymous Referee #2, 04 Oct 2023
Qingfeng Ma et al.
Data sets
A modern pollen dataset from lake surface sediments on the central-western Tibetan Plateau Qingfeng Ma, Liping Zhu, Jianting Ju, Junbo Wang, Yong Wang, Lei Huang, and Torsten Haberzettl https://doi.org/10.5281/zenodo.8008474
Qingfeng Ma et al.
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