Preprints
https://doi.org/10.5194/essd-2023-486
https://doi.org/10.5194/essd-2023-486
02 Apr 2024
 | 02 Apr 2024
Status: a revised version of this preprint is currently under review for the journal ESSD.

LegacyVegetation 1.0: Global reconstruction of vegetation composition and forest cover from pollen archives of the last 50 ka

Laura Schild, Peter Ewald, Chenzhi Li, Raphaël Hébert, Thomas Laepple, and Ulrike Herzschuh

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).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Laura Schild, Peter Ewald, Chenzhi Li, Raphaël Hébert, Thomas Laepple, and Ulrike Herzschuh

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on essd-2023-486', Marie-Jose Gaillard, 19 Apr 2024
    • AC1: 'Reply on CC1', Laura Schild, 10 May 2024
  • CC2: 'Comment on essd-2023-486: consider rejection', Michela Mariani, 22 Apr 2024
    • AC2: 'Reply on CC2', Laura Schild, 10 May 2024
  • RC1: 'Comment on essd-2023-486', Anonymous Referee #1, 02 May 2024
  • CC3: 'Comment on essd-2023-486', John Williams, 03 May 2024
    • AC3: 'Reply on CC3', Laura Schild, 15 May 2024
  • RC2: 'Comment on essd-2023-486', Thomas Giesecke, 07 May 2024
    • AC4: 'Reply on RC2', Laura Schild, 28 May 2024
  • AC5: 'Letter to the Editor', Laura Schild, 28 May 2024
  • EC1: 'Comment on essd-2023-486', Kirsten Elger, 02 Jun 2024
Laura Schild, Peter Ewald, Chenzhi Li, Raphaël Hébert, Thomas Laepple, and Ulrike Herzschuh

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

Laura Schild, Peter Ewald, Chenzhi Li, Raphaël Hébert, Thomas Laepple, and Ulrike Herzschuh

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Short summary
This study reconstructed past vegetation and forest cover from a global data set of pollen counts from sediment and peat cores. A model was applied to correct for differences in pollen production between different plants and modern remote-sensing forest cover was used to adjust the necessary correction factors and improve the reconstruction even further. Accurate data on past vegetation is invaluable for the investigation of vegetation-climate dynamics and the validation of vegetation models.
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