the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Apr 2024
LegacyVegetation 1.0: Global reconstruction of vegetation composition and forest cover from pollen archives of the last 50 ka
Abstract. With rapid anthropogenic climate change future vegetation trajectories are uncertain. Climate-vegetation models can be useful for predictions but need extensive data on past vegetation for validation and improving systemic understanding. Even though pollen data provide a great source of this information, the data is compositionally biased due to differences in taxon-specific relative pollen productivity (RPP) and dispersal.
Here we reconstructed quantitative regional vegetation cover from a global sedimentary pollen data set for the last 50 ka using the REVEALS model to correct for taxon- and basin-specific biases. In a first reconstruction, we used previously published, continental RPP values. For a second reconstruction, we statistically optimized RPP values for common taxa with the goal of improving the fit of reconstructed forest cover from modern pollen samples with remote sensing forest cover.
The data sets include taxonomic compositions as well as reconstructed forest cover for each original pollen sample. Relative pollen sources areas were also calculated and are included in the data set of the original REVEALS run. Additional metadata includes modeled ages, age model sources, basin locations, types and sizes.
The improvements in forest cover reconstructions with the REVEALS reconstruction using original/optimized parameters range from 1/0 % (Australia and Oceania/Australia and Oceania) to 58/65 % (Europe/North America) relative to the mean absolute error (MAE) in the pollen-based reconstruction. Optimizations were considerably more successful in reducing MAE when more records and RPP estimates were available. The optimizations were purely statistical and only partly ecologically informed and should, therefore, be used with caution depending on the study matter.
This improved quantitative reconstruction of vegetation cover is invaluable for the investigation of past vegetation dynamics and modern model validation. By collecting more RPP estimates for taxa in the Southern Hemisphere and adding more records to existing pollen data syntheses, reconstructions may be improved even further. Both reconstructions are freely available on PANGAEA (see Data availability section).
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Status: final response (author comments only)
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CC1: 'Comment on essd-2023-486', Marie-Jose Gaillard, 19 Apr 2024
Please see the entire comment in the attached pdf file
- AC1: 'Reply on CC1', Laura Schild, 10 May 2024
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CC2: 'Comment on essd-2023-486: consider rejection', Michela Mariani, 22 Apr 2024
The manuscript claims to adapt the REVEALS model for global climate-vegetation reconstructions. However, several critical issues compromise the validity of its findings, please see below for further details.
While quantitative palynologists globally aspire to achieve global-scale reconstructions of vegetation, the reality is that this goal is probably decades away. The manuscript presents a methodologically flawed approach that fails to meet the scientific standards required for reliable global vegetation reconstruction using the REVEALS model. The assumption that RPPEs (relative pollen productivities) are constant continentally, hemispherically and temporally undermines the meticulous and dedicated empirical work conducted by the scientific community across recent decades in creating RPPEs. Particularly, this applies to regions across the Southern Hemisphere and tropical/sub-tropical, where RPPEs are being developed for the first time.
We recommend rejection (or extensive revisions) to be undertaken to address the issues outlined below, ensuring that the model is applied appropriately and effectively within its intended ecological, temporal and geographical constraints. If a revised version is produced, this should only be geographically constrained (probably just the Northern Hemisphere might be feasible in fact).
Major issues:
Inadequate regional calibrations: The generalization of RPPEs across broad geographical scales (hemispheres) ignores crucial ecological and bioclimatic regional variations. This approach most likely leads to significant inaccuracies in the vegetation reconstructions, in spite of what the presumed ‘validation’ approach suggests (see below).
Questionable data assumptions and methodological gaps: The use of northern hemisphere RPPE values for taxa not natively present in the southern hemisphere, such as Alnus in Australia, introduces substantial and confusing biases. Presumably, the authors have not consulted the relevant scholars who worked within this field and the geographical areas mentioned. Similarly, defaulting RPP to 1 for taxa without specific data oversimplifies pollen-vegetation relationships. The paper does not adequately address the absence of data for the Southern Hemisphere, leading to a misleading portrayal of global vegetation.
It is suggested >50% of RPPEs are missing for Australia and Oceanic pollen records. So, in this work a decision was made to run these records using the Northern Hemispheric RPPEs, despite very different bioclimatic and ecological contexts. This extrapolation of Northern Hemisphere RPPEs to southern locations missing PPEs without considering ecological or bioclimatic differences is particularly problematic. RPPEs empirically produced using ground truthing work (field surveys and surface pollen collection) were ignored, especially across the Southern Hemisphere (see some references below).
Duffin, K. I., & Bunting, M. J. (2008). Relative pollen productivity and fall speed estimates for southern African savanna taxa. Vegetation History and Archaeobotany, 17, 507-525.
Mariani, M., Connor, S. E., Theuerkauf, M., Kuneš, P., & Fletcher, M. S. (2016). Testing quantitative pollen dispersal models in animal-pollinated vegetation mosaics: An example from temperate Tasmania, Australia. Quaternary Science Reviews, 154, 214-225.
Mariani, M., Connor, S. E., Fletcher, M. S., Theuerkauf, M., Kuneš, P., Jacobsen, G., ... & Zawadzki, A. (2017). How old is the Tasmanian cultural landscape? A test of landscape openness using quantitative land‐cover reconstructions. Journal of Biogeography, 44(10), 2410-2420.
Mariani, M., Connor, S. E., Theuerkauf, M., Herbert, A., Kuneš, P., Bowman, D., ... & Briles, C. (2022). Disruption of cultural burning promotes shrub encroachment and unprecedented wildfires. Frontiers in Ecology and the Environment, 20(5), 292-300.
Oversimplified and incorrect spatial and temporal settings: The inclusion of incorrect basin types in the model without appropriate adjustments is very concerning. Why are marine records included for a model explicitly designed to work for large lakes of closed basins with wind dispersal as the only mechanism for pollen deposition?
The manuscripts states that ‘all sites that were not classified as lakes were run with peatland settings’ = can we consider the ocean a peatland? REVEALS cannot work with marine records and it definitely does not make sense to apply the ‘peatland’ settings for marine records with some random arbitrary basin radius (100m?). Further, using a deep temporal scope (50ka) without any consideration for massive climatic shifts (likely larger than the effect of regional RPPEs values vs regional bioclimate variations) are concerning oversights, making any pre-Holocene glacial REVEALS reconstructions unrealistic with current interglacial PPEs.
Dubious optimization and validation: Optimizing PPEs to match remote sensing data risks validating the model based on its own assumptions rather than providing an unbiased estimation of past vegetation, which REVEALS is designed to do. This circular reasoning undermines the scientific integrity of the model's outputs. While an interesting concept this needs to be validated separately on a much smaller spatially and higher resolution scale before such a widespread application. This cannot really be called a ‘validation’.
The reconstructed forest cover for the past 500 years was compared to modern remote sensed cover. Why not a smaller and more recent age bin was considered? In the past 500 years many areas of the world have been colonised by Europeans and have experienced major shifts in vegetation structure, as management transferred from Indigenous to colonial regimes (e.g. the Americas and Australia). This means that forest cover over the whole 500 years bin is not comparable to modern remote sensing data. This highlights a Eurocentric view of the global vegetation patterns.
An example of validation of RPPEs using modern vegetation data (with surveys) has been done in the following papers:
Mariani, M., Connor, S. E., Fletcher, M. S., Theuerkauf, M., Kuneš, P., Jacobsen, G., ... & Zawadzki, A. (2017). How old is the Tasmanian cultural landscape? A test of landscape openness using quantitative land‐cover reconstructions. Journal of Biogeography, 44(10), 2410-2420.
Mariani, M., Connor, S. E., Theuerkauf, M., Herbert, A., Kuneš, P., Bowman, D., ... & Briles, C. (2022). Disruption of cultural burning promotes shrub encroachment and unprecedented wildfires. Frontiers in Ecology and the Environment, 20(5), 292-300.
Citation: https://doi.org/10.5194/essd-2023-486-CC2 - AC2: 'Reply on CC2', Laura Schild, 10 May 2024
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RC1: 'Comment on essd-2023-486', Anonymous Referee #1, 02 May 2024
Dear authors and editors,
I have read the paper by Laura Schild et al. and the comments by Marie-Jose Gaillard and Michela Mariani.
Although global quantitative vegetation reconstructions are extremely important, it is quite difficult to create a general model for both hemispheres over such a long period of time, and even in the absence of factual data. I cannot disagree with the comments made by M.-J. Gaillard and M. Mariani and suggest that the authors undertake a major revision taking these points into account. I see no point in repeating the same remarks in my review. These scientists are greater experts in the use of the REVEALS model than I am. I suggest that the authors remove the controversial points in the application of the model and try to resubmit the paper.Citation: https://doi.org/10.5194/essd-2023-486-RC1 -
CC3: 'Comment on essd-2023-486', John Williams, 03 May 2024
We’ve read with interest the manuscript by Schild et al. and are supportive of its goal to develop and publicly share an open set of global vegetation reconstructions for the late Quaternary. Such reconstructions will be of interest to many in the Earth system modeling, paleoclimate, carbon cycle, and paleoecology communities.
With this affirmation noted, we write this public comment to raise the concern that the current version of the manuscript does not adhere to best practices in open data citation and provenancing.
The analyses presented by Schild et al. are based upon data from the Legacy Pollen Dataset V1.0 (hereafter LPD1.0) (Herzschuh et al., 2022), which in turn are mostly drawn from living data curated and made openly available by communities of paleoecologists working together to support the Neotoma Paleoecology Database (hereafter Neotoma) (Williams et al., 2018). Specifically, of the original data compiled for LPD1.0, 3147 records were from Neotoma (90.6% of all records) and 324 (9.4%, mostly in China and Siberia) are from other sources. Herzschuh et al. (2022) then added value to their compiled research dataset by 1) removing some records based on quality-control criteria and 2) building a harmonized set of taxonomic names. These actions follow recommended practices for large-scale paleoecological data syntheses (Flantua et al., 2023).
The Schild et al. ms. appropriately cites LPD1.0 but fails to cite Neotoma and/or include an acknowledgement of Neotoma, its Constituent Databases, and data contributors. Given >90% of LPD1.0 data is sourced directly from Neotoma, this omission is a violation of Neotoma’s Data Use Policy (https://www.neotomadb.org/data/data-use-and-embargo-policy) and Creative Commons license (CC-BY 4.0, https://creativecommons.org/licenses/by/4.0/deed.en). The CC-BY license allows re-use and modification of Neotoma data, but requires that any downstream datasets that use Neotoma continue to provide attribution to Neotoma. Flagship open-science journals like ESSD and synthesis papers like Schild et al. can further advance open science by setting a good example to other users by following best practices in data citation.
The lack of attribution to Neotoma’s Constituent Databases severs the link between the data and the Data Stewards who compiled these data. These Stewards have regional expertise in the systematics and ecology of the taxa and the factors governing the dynamics, diversity, and distribution of species and ecosystems. Including regional experts in global-scale syntheses is also a best practice, given the high diversity and heterogeneity of paleofloristic datasets (Flantua et al., 2023).
The lack of a direct link to Neotoma datasets in this manuscript creates a break in provenance between the pollen datasets used by Schild et al. and the living datasets curated by Neotoma data stewards and Neotoma’s Constituent Databases. Updates to Neotoma datasets are uncommon, but they happen as, e.g. age-depth models (chronologies) are updated or metadata errors are discovered and fixed by the community of Data Stewards associated with the various Constituent Databases. Hence, the static datasets used by Schild et al. are now branched from the primary datasets curated by Neotoma and there is a risk that the static datasets in LPD1.0 will become stale relative to the living datasets in Neotoma.
Fortunately, the solutions are simple. First, the manuscript can add a citation and/or acknowledgment of Neotoma and the Constituent Databases that curated and provided these data: the African Pollen Database, ALPADABA, European Pollen Database, Indo-Pacific Pollen Database, Latin American Pollen Database, and North American Pollen Database. Citation endpoints and model text for acknowledgment are provided in the Neotoma Data Use Policy (https://www.neotomadb.org/data/data-use-and-embargo-policy) .
Second, the broken chain of dataset provenance and associated risk of data staleness can be removed by including a supplementary data table that has a column with a DOI link to each Neotoma dataset. This solution also helps recognize data contributors by making their data more visible and cited. (The LPD1.0 metadata table archived at Pangaea [https://doi.pangaea.de/10.1594/PANGAEA.929773] has DOIs to some original journal articles and dataset IDs for Neotoma datasets, but not Neotoma DOIs.) The R-FossilPol package (Flantua et al., 2023) functionality includes a service that will generate a data table with DOIs for each Neotoma dataset (for example, see: https://github.com/HOPE-UIB-BIO/FOSSILPOL-example-Scandinavia/blob/main/Outputs/Meta_and_references/data_assembly_meta_2023-01-20.csv).
To support this effort, we have developed and shared a GitHub Gist showing how to generate a table of DOIs and data citations using the `doi()` function from the neotoma2 R package (https://gist.github.com/SimonGoring/4a0b09b83373791a92c28b7191d07000). We have also opened an issue in the `neotoma2` GitHub repository () to improve the documentation for the `doi()` function, and to improve the package vignette to better integrate data citation best-practices.
John (Jack) W. Williams, Chair, Executive Working Group, Neotoma Leadership Council
Jessica Blois, University of California-Merced; Associate Chair, Executive Working Group, Neotoma Leadership Council
Thomas Giesecke, Utrecht University, Executive Working Group, Neotoma Leadership Council
Simon Goring, IT Team Lead, Neotoma Paleoecology Database
Sarah Ivory, Pennsylvania State University; Executive Working Group, Neotoma Leadership Council
References Cited
Flantua, S. G. A., Mottl, O., Felde, V. A., Bhatta, K. P., Birks, H. H., Grytnes, J.-A., Seddon, A. W. R., and Birks, H. J. B.: A guide to the processing and standardization of global palaeoecological data for large-scale syntheses using fossil pollen, Glob. Ecol. Biogeogr., n/a, https://doi.org/10.1111/geb.13693, 2023.
Herzschuh, U., Li, C., Böhmer, T., Postl, A. K., Heim, B., Andreev, A. A., Cao, X., Wieczorek, M., and Ni, J.: LegacyPollen 1.0: a taxonomically harmonized global late Quaternary pollen dataset of 2831 records with standardized chronologies, Earth Syst Sci Data, 14, 3213–3227, https://doi.org/10.5194/essd-14-3213-2022, 2022.
Williams, J. W., Grimm, E. G., Blois, J., Charles, D. F., Davis, E., Goring, S. J., Graham, R., Smith, A. J., Anderson, M., Arroyo-Cabrales, J., Ashworth, A. C., Betancourt, J. L., Bills, B. W., Booth, R. K., Buckland, P., Curry, B., Giesecke, T., Hausmann, S., Jackson, S. T., Latorre, C., Nichols, J., Purdum, T., Roth, R. E., Stryker, M., and Takahara, H.: The Neotoma Paleoecology Database: A multi-proxy, international community-curated data resource, Quat. Res., 89, 156–177, https://doi.org/10.1017/qua.2017.105, 2018.
Citation: https://doi.org/10.5194/essd-2023-486-CC3 - AC3: 'Reply on CC3', Laura Schild, 15 May 2024
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RC2: 'Comment on essd-2023-486', Thomas Giesecke, 07 May 2024
I have read the manuscript by Schild et al. with curiosity and agree that an attempt to reconstruct Holocene forest cover globally is a worthwhile endeavor. However, I do not understand why the authors choose using the rather complex REVEALS model and did not attempt this task using the modern analogue technique. In using REVEALS the authors make many assumptions leading to highly uncertain results, particularly for the southern hemisphere.
Before looking more closely at the manuscript I like to extent on the comment by Williams et al. of developing the underlying Legacy Pollen Dataset. Branching of a large dataset from Neotoma into the Legacy Pollen Dataset with vetting and adding metadata, results in the additional work not being linked back to Neotoma. In the spirit of open science it would be better practice to contribute to Neotoma by uploading additional datasets and correcting or adding metadata. Look up tables for taxonomic harmonization or new chronologies could then be linked to the data in Neotoma. Republishing Neotoma derived data makes scientists using that data ignore the original data source. This also means that Neotoma loses recognition for the work of the data stewards and support for acquiring funding to maintain and develop the database.
Regarding the here presented manuscript by Shild et al. I see several problems and directions of how to address them. I generally agree with the comments by Marie-Jose Gaillard and Michela Mariani regarding technical shortcomings, definition of the source area of pollen (NOT “relevant source area”) and the recommendation to restrict a REVEALS application to the northern hemisphere. If attempting to include the southern hemisphere the authors should reduce the unrealistic assumptions as some more information could be gained. Fall speeds could be estimated using the size of pollen grains and initial guesses of RPPEs could have been made by inviting experts working on the different continents and including recent publications on RPPEs.
My concerns are particularly related to the aim of the authors to publish the data resulting from the analysis. REVEALS results not only provide information on past woodland cover, but also on bias reduced abundance of the major plant genera or families. Given the way the authors used RPPEs and fall speeds for the southern hemisphere such estimates are unlikely to improve the bias in pollen percentage data. However, they may invite researchers not understanding the limitations to misuse such data. This is particularly the case where the authors adjusted RPPEs to obtain an overall better fit with modern tree cover globally. Here the authors admit that the adjusted RPPEs are ecologically meaningless, and I therefore urge the authors not to publish the resulting vegetation reconstructions as they will also be meaningless. If the authors are convinced that the resulting tree cover is meaningful, they could restrict the data publication to that.
If a data publication is pursued, the authors should explain in which way they envision the data to be used. Is the attempt to estimate the source area of 80% of pollen to then relate the information on tree cover to that area, and if so how shall that be implemented? Also, how will overlapping areas be treated? Even on the northern hemisphere the gained information is not continues and I therefore wonder how the results will be used in climate modelling. Moreover, I did not find anything in the manuscript of how the obtained data informs on the position of northern or southern forest or tree limits, that are difficult to estimate from percentage pollen data.
Retaining all the current aspects of the manuscript I would recommend to revise the manuscript and publish it in a disciplinary journal to discuss aspects of this analysis which yield new insights. If continuing with the modern comparison I would suggest to use available surface sample data or core tops marked as modern. Using top samples as old as 500 years in the comparison with modern woodland cover introduces a huge bias.
In summary, I don’t recommend the publication of the data from the current analysis and suggest restricting the analysis to the northern hemisphere with a publication of the findings in a topical journal.Detailed comments:
17: The uncertainties introduced here will not make the results invaluable for the investigation of past vegetation dynamics.
28: The study is on vegetation cover not climate.
34: Fyfe et al. 2009 is not in the reference list.
36-38: This is not allowing for a broader but a more restricted application of pollen data as some aspects may not be possible to investigate with a reduced taxonomic depth. Please reword.
49: “relevant” pollen source area is well defined, but this is not meant here.
50: Nielsen and Odgaard 2010 are a good example of applying the full Landscape Reconstruction Algorithm with a focus on LOVE not so much REVEALS.
51: “ability” rather than “accuracy”
105: No information is given where the RPPEs are coming from for the southern hemisphere if they are not set to 1 and not used from the northern Hemisphere. Please provide references.
106: Fall speeds can be easily estimated based on the size of pollen grains.
111: Not “relevant source area”
118: How was that latitudinal limit used or derived for the past?
120: In most situations the forest cover has changed dramatically over the last 500 years. Why did you not use surface sample datasets for this exercise or sites with the top sample marked as modern?
168: Chenopodiaceae are an old classification and now included in Amaranthaceae. Why do they have such different RPPEs in Europe?
189: Particularly in the southern hemisphere one would expect that the adjustments lead to improvements. It would be interesting to explore the reasons why that is not the case e.g. the low pollen productivity of many tropical trees. I cannot see that low data availability is a reason here.
195: Starting with initial values different from 1 may also be a way to explore this further.
201: It would be interesting to look at these trends for different continents. If a first approximation of forest cover could be made by adjusting arboreal pollen percentages on a continental scale that could be used by modelers as a first order estimate. Again such comparisons should better be done using the modern analogue approach.
289-296: I strongly disagree with these statements. Particularly regarding the northern and southern tree limits the manuscript is not demonstrating how their detection has improved.
Data: I looked at the resulting data for a few sites in northern Patagonia where I am familiar with the vegetation. First of all I could not find where the RPPE for Nothofagus comes from. For a site in the steppe (Lago Mosquito) with Austrocedrus on its western shore, REVEALS estimated Holocene values around 60 % forest cover, which is too high. The adjusted run did indeed lower the forest cover to between 40 and 20 %. However, this reconstruction returned the lowest forest cover for the time that Austrocedrus woodlands were present on its western shore and tree cover was highest. This may be due to the fact that Cupressaceae was not part of the taxa used for optimization. Thus, while the amount of forest cover is more realistic in the adjusted run the reconstructed Holocene trend is the reverse of what was interpreted by the authors of the site based data. Moreover, the only tree growing abundantly near the site for the last 3000 years is not part of the reconstructed vegetation in the adjusted run. This is of cause just a single example, but it does illustrate my earlier points.Citation: https://doi.org/10.5194/essd-2023-486-RC2 - AC4: 'Reply on RC2', Laura Schild, 28 May 2024
- AC5: 'Letter to the Editor', Laura Schild, 28 May 2024
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EC1: 'Comment on essd-2023-486', Kirsten Elger, 02 Jun 2024
Dear Laura Schild, Ulrike Herzschuh and co-authors,
after reading all comments (public and review reports) and your very comprehensive answers to them, I have decided to proceed with the manuscript and ask you to prepare a revised version. This version will be reviewed again by the same referees and I will also invite the researchers who have made public comments to first version as refeees for the revised version. Seeing the overall large concerns and valid criticism that were raised for the first version of the manuscript, I would like to make sure to have the community on board before I take a final decision about its publication.
Many thanks for your understanding!
Citation: https://doi.org/10.5194/essd-2023-486-EC1
Data sets
Global REVEALS reconstruction of past vegetation cover for taxonomically harmonized pollen data sets Ulrike Herzschuh et al. https://doi.org/10.1594/PANGAEA.961588
Optimized REVEALS reconstruction of past vegetation cover for taxonomically harmonized pollen data sets Laura Schild et al. https://doi.pangaea.de/10.1594/PANGAEA.961699
Model code and software
[Analysis code] LegacyVegetation 1.0: Global reconstruction of vegetation compositions and forest cover from pollen archives of the last 50 ka Laura Schild and Peter Ewald https://doi.org/10.5281/zenodo.10191859
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