LegacyVegetation: Northern Hemisphere reconstruction of past plant cover and total tree cover from pollen archives of the last 14&thinsp;kyr

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

doi:https://doi.org/10.5194/essd-17-2007-2025

Articles | Volume 17, issue 5

https://doi.org/10.5194/essd-17-2007-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-17-2007-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 5

Data description paper

|

12 May 2025

Data description paper |

| 12 May 2025

LegacyVegetation: Northern Hemisphere reconstruction of past plant cover and total tree cover from pollen archives of the last 14 kyr

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

Supplement

https://doi.org/10.5194/essd-17-2007-2025-supplement

Data sets

LegacyVegetation: Northern Hemisphere reconstruction of past plant cover and total tree cover from pollen archives of the last 14 ka Ulrike Herzschuh et al. https://doi.org/10.1594/PANGAEA.974798

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

Rasterization script for LegacyVegetation Laura Schild https://doi.org/10.5281/zenodo.13902976

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Short summary

This study reconstructed vegetation and tree cover in the Northern Hemisphere from a harmonized dataset of pollen counts from sediment and peat cores for the past 14 000 years. A model was applied to correct for differences in pollen production between different plants, and modern remote-sensing forest cover was used to validate the reconstructed tree cover. Accurate data on past vegetation are invaluable for the investigation of vegetation–climate dynamics and the validation of vegetation models.