the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Jul 2025
A lacustrine surface-sediment pollen dataset covering the Tibetan Plateau and its potential in past vegetation and climate reconstructions
Abstract. A dataset of pollen extracted from the surface-sediments of lakes with an even spatial distribution is essential for pollen-based reconstructions of past vegetation and climate. We collected 90 lake surface-sediment samples from the Tibetan Plateau (TP) covering major vegetation types. A comprehensive modern pollen dataset is established by integrating our newly obtained modern pollen dataset with previous modern lacustrine pollen datasets, covering the full range of climatic gradients across the TP with mean annual precipitation (Pann) from 97 to 788 mm, mean annual temperature (Tann) -9.09 to 6.93 °C, mean temperature of the coldest month (Mtco) -23.48 to -2.65 °C, and mean temperature of the warmest month (Mtwa) 1.77 to 19.26 °C. Numerical analyses revealed that Pann is the primary climatic determinant for pollen distribution, while net primary production (NPP) is a valuable variable reflecting vegetation conditions. To detect the quantitative relationship between pollen and Pann/NPP, both weighted-averaging partial least squares (WA-PLS) and random forest algorithm (RF) were employed. The performance of both models suggests that this modern pollen dataset has good predictive power in estimating past NPP and Pann, but RF has a slight advantage with this dataset. This comprehensive modern pollen dataset is considered reliable when reconstructing vegetation and climate from pollen spectra from the central TP, but caution is needed if it is applied to pollen spectra from the marginal regions of the TP and those covering the Last Glacial period, due to poor analogue quality in those cases. The dataset, including site locations, pollen percentages, NPP, and climate data for 90 lakes, is available at the National Tibetan Plateau Data Center (TPDC; Tian, 2025; https://doi.org/10.11888/Paleoenv.tpdc.302470).
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RC1: 'Comment on essd-2025-242', Anonymous Referee #1, 07 Aug 2025
General comments
Palynologists believe that vegetation and climate reconstructed from modern pollen of lake surface sediments is more reliable than from that of surface soils, but the number of modern pollen dataset from lake surface sediments is much less than that from surface soils. More modern pollen dataset from lake surface sediments is urgently needed. This study presents a lacustrine pollen dataset from many lake surface sediments covering the most part of the Tibetan Plateau. The modern pollen and climate relationships have been further analyzed. The dataset is well described and the statistical analyses are sound. There are however a couple of key problems should be addressed before publication.
Specific comments
Abstract
As the modern pollen data from 90 lakes are new, their detailed information should be provided, including the lake area and mean depth etc. The reviewer thinks that this information really matters the committing of vegetation and climate reconstructions. Meanwhile, the author provided 90 lake surface samples, whiles the analysis was based on 476 samples. This should be clarified in the abstract, and provide briefly the improvement in the main text.
Line 14, covering major vegetation types. Please list the major vegetation types from the whole dataset, including the later added previous modern lacustrine pollen dataset. This is because later the authors only presented the climate range but no vegetation information. The final utilization of the dataset is to reconstruct both the climate and vegetation, but the vegetation-pollen relationship has not been investigated in this study.
Line 15-17, the total number of pollen sites (476) should be provided here.
Study area
There are totally 476 modern lake pollen samples, covering most of the TP, but there are still some geographical gaps in northern, western (the driest region) and southeastern TP (the moistest region). Do the authors have any suggestions to get more samples from these regions?
Another question: how many pollen samples from one lake? Only one or several? If only one sample, what is the difference from big lake and small lake? In the method section, the authors sad that there is only one sample for the 90 newly collected pollen samples. Is the one sample representative for some of the big lakes?
Fig 1, where is the NPP data come from? Reference related to the NPP data should be cited. Can the vegetation division of the TP be added in the figure or in a new figure?
Methods
Line 114, To ensure the even distribution of the sampled lakes, we collected … However, Figure 1 shows that the sampled lakes are not evenly distributed as some points are crowned with each other.
Line 141-142, The pollen data are standardized following the procedures outlined in Cao et al. (2013), including harmonization of taxonomy – generally to the family or genus level. Such harmonization of pollen taxonomy might loss some information, can the original pollen taxa be published in the dataset? For the statistical analyses, however, such harmonization is fine.
Line 144-145, a maximum ≥3% were retained for statistical analyses (n=35). What does this mean? On the other hand, the authors mentioned all pollen taxa after. Please clarify is these 35 taxa was used in RDA, WAPLS and RF.
Line 150-153, line 163-164, line 189-190: the same question as mentioned above. The analysis was based on all samples, all pollen taxa, or selected 35 taxa? Please verify.
Line 170, along climate gradients. The NPP was also used as one parameter, but it is not a climatic variable.
Line 209-210, based on the percentages of all pollen taxa. All taxa or 35 selected taxa??
Data analysis
The pollen-climate relationships and the reconstruction of climate based on modern pollen data have been extensively studied using very complex methods in this manuscript, but no any study about the pollen-vegetation relationships and the reconstruction of vegetation based on pollen data. The reviewer suggests that reducing the content of climate study but add some study on the vegetation reconstruction.
Data description
Line 250, should "selected herbaceous taxa" be more precise?
Only the newly collected pollen sites have been analyzed in their pollen features. Why not analyze the whole dataset with 476 pollen samples?
How can use pollen to indicate NPP? In my thought, NPP is the indicator of vegetation rather than species or a group of species?
Technical corrections
Line 56, delete .
Line 139, where is the Fig A1? Should be Fig S1?
Line 134, Tibetan Plateau – TP
Line 253, than that in forest sites
Line 313, Pann, lower case
Citation: https://doi.org/10.5194/essd-2025-242-RC1 -
RC2: 'Comment on essd-2025-242', Anonymous Referee #2, 09 Aug 2025
This work collected 90 lake surface-sediment samples and integrated 375 previous data from the Tibetan Plateau (TP) covering major vegetation types. At the same time, this word detected the quantitative relationship between pollen and environmental factors, such as NPP and precipitation, which is valuable for Tibetan Plateau studies.
I still have some minor revision comments:
- I think the authors should give more information about the 90 sites. For example, whether authors did vegetation investigation during sampling? Except the vegetation type, whether authors could give more information about the vegetation around the sampling sites. I think these information is important for establishing the relationships between vegetation and pollen.
- I think the table 2 is not very important, which could be put in the supporting information or revised to a figure, because the min and max value is not very important for readers, who cares more about the range and value distribution frequency.
- The figure 8 is a little hard to understand. I suggest to put these data in map, which could be more visualized.
Citation: https://doi.org/10.5194/essd-2025-242-RC2
Data sets
Pollen assemblages of lake surface sediment across the Tibetan Plateau, National Tibetan Plateau / Third Pole Environment Data Center F. Tian et al. https://doi.org/10.11888/Paleoenv.tpdc.302470
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