Research article - Peer-reviewed, 2022
European pollen-based REVEALS land-cover reconstructions for the Holocene: methodology, mapping and potentials
Githumbi, Esther; Fyfe, Ralph; Gaillard, Marie-Jose; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne-Birgitte; Poska, Anneli; Sugita, Shinya; Woodbridge, Jessie; Azuara, Julien; Feurdean, Angelica; Grindean, Roxana; Lebreton, Vincent; Marquer, Laurent; Nebout-Combourieu, Nathalie; Stancikaite, Migle; Tantau, Ioan; Tonkov, Spassimir; Shumilovskikh, LyudmilaAbstract
Quantitative reconstructions of past land cover are necessary to determine the processes involved in climate-human-land-cover interactions. We present the first temporally continuous and most spatially extensive pollen-based land-cover reconstruction for Europe over the Holocene (last 11 700 cal yr BP). We describe how vegetation cover has been quantified from pollen records at a 1 degrees x 1 degrees spatial scale using the "Regional Estimates of VEgetation Abundance from Large Sites" (REVEALS) model. REVEALS calculates estimates of past regional vegetation cover in proportions or percentages. REVEALS has been applied to 1128 pollen records across Europe and part of the eastern Mediterranean-Black Sea-Caspian corridor (30-75 degrees N, 25 degrees W-50 degrees E) to reconstruct the percentage cover of 31 plant taxa assigned to 12 plant functional types (PFTs) and 3 land-cover types (LCTs). A new synthesis of relative pollen productivities (RPPs) for European plant taxa was performed for this reconstruction. It includes multiple RPP values (>= 2 values) for 39 taxa and single values for 15 taxa (total of 54 taxa). To illustrate this, we present distribution maps for five taxa (Calluna vulgaris, Cerealia type (t)., Picea abies, deciduous Quercus t. and evergreen Quercus t.) and three land-cover types (open land, OL; evergreen trees, ETs; and summer-green trees, STs) for eight selected time windows. The reliability of the REVEALS reconstructions and issues related to the interpretation of the results in terms of landscape openness and human-induced vegetation change are discussed. This is followed by a review of the current use of this reconstruction and its future potential utility and development. REVEALS data quality are primarily determined by pollen count data (pollen count and sample, pollen identification, and chronology) and site type and number (lake or bog, large or small, one site vs. multiple sites) used for REVEALS analysis (for each grid cell). A large number of sites with high-quality pollen count data will produce more reliable land-cover estimates with lower standard errors compared to a low number of sites with lower-quality pollen count data. The REVEALS data presented here can be downloaded from https://doi.org/10.1594/PANGAEA.937075 (Fyfe et al., 2022).Published in
Earth System Science Data2022, volume: 14, number: 4, pages: 1581-1619
Publisher: COPERNICUS GESELLSCHAFT MBH
Authors' information
Githumbi, Esther
League of European Research Universities - LERU
Githumbi, Esther
Linnaeus University
Fyfe, Ralph
University of Plymouth
Gaillard, Marie-Jose
Linnaeus University
Swedish University of Agricultural Sciences, Division of Educational Affairs
Linnaeus University
Mazier, Florence
Universite de Toulouse - Jean Jaures
Nielsen, Anne-Birgitte
Lund University
Poska, Anneli
League of European Research Universities - LERU
Poska, Anneli
Tallinn University of Technology
Sugita, Shinya
Tallinn University of Technology
Woodbridge, Jessie
University of Plymouth
Azuara, Julien
CNRS - Institute of Ecology and Environment (INEE)
Feurdean, Angelica
Babes Bolyai University from Cluj
Feurdean, Angelica
Senckenberg Biodiversitat and Klima- Forschungszentrum (BiK-F)
Grindean, Roxana
Romanian Academy of Sciences
Grindean, Roxana
Babes Bolyai University from Cluj
Lebreton, Vincent
CNRS - Institute of Ecology and Environment (INEE)
Marquer, Laurent
University of Innsbruck
Nebout-Combourieu, Nathalie
CNRS - Institute of Ecology and Environment (INEE)
UKÄ Subject classification
Physical Geography
Publication Identifiers
DOI: https://doi.org/10.5194/essd-14-1581-2022
URI (permanent link to this page)
https://res.slu.se/id/publ/117137