EUPollMap: the European atlas of contemporary pollen distribution maps derived from an integrated Kriging interpolation approach
-
Published:2024-01-31
Issue:1
Volume:16
Page:731-742
-
ISSN:1866-3516
-
Container-title:Earth System Science Data
-
language:en
-
Short-container-title:Earth Syst. Sci. Data
Author:
Oriani FabioORCID, Mariethoz Gregoire, Chevalier ManuelORCID
Abstract
Abstract. Modern and fossil pollen data are widely used in paleoenvironmental research to characterize past environmental changes in a given location. However, their discrete and discontinuous nature can limit the inferences that can be made from them. Deriving continuous spatial maps of the pollen presence from point-based datasets would enable more robust regional characterization of such past changes. To address this problem, we propose a comprehensive collection of European pollen presence maps including 194 pollen taxa derived from the interpolation of pollen data from the Eurasian Modern Pollen Database (EMPD v2) restricted to the Euro-Mediterranean Basin. To do so, we developed an automatic Kriging-based interpolation workflow to select an optimal geostatistical model describing the spatial variability for each taxon. The output of the interpolation model consists of a series of multivariate predictive maps of Europe at 25 km scale, showing the occurrence probability of pollen taxa, the predicted presence based on diverse probability thresholds, and the interpolation uncertainty for each taxon. Combined visual inspections of the maps and systematic cross-validation tests demonstrated that the ensemble of predictions is reliable even in data-scarce regions, with a relatively low uncertainty, and robust to complex and non-stationary pollen distributions. The maps, freely distributed as GeoTIFF files (https://doi.org/10.5281/zenodo.10015695, Oriani et al., 2023), are proposed as a ready-to-use tool for spatial paleoenvironmental characterization. Since the interpolation model only uses the coordinates of the observation to spatialize the data, the model can also be employed with fossil pollen records (or other presence/absence indicators), thus enabling the spatial characterization of past changes, and possibly their subsequent use for quantitative paleoclimate reconstructions.
Funder
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung Bundesministerium für Bildung und Forschung
Publisher
Copernicus GmbH
Reference43 articles.
1. Allard, D., Comunian, A., and Renard, P.: Probability aggregation methods in geoscience, Math. Geosci., 44, 545–581, https://doi.org/10.1007/s11004-012-9396-3, 2012. a 2. Bartlein, P., Harrison, S., Brewer, S., Connor, S., Davis, B., Gajewski, K., Guiot, J., Harrison-Prentice, T., Henderson, A., Peyron, O., Prentice, I., Scholze, M., Seppä, H., Shuman, B., Sugita, S., Thompson, R., Viau, A., Williams, J., and Wu, H.: Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis, Climate Dynam., 37, 775–802, https://doi.org/10.1007/s00382-010-0904-1, 2011. a 3. Birks, H. J. B., Heiri, O., Seppä, H., and Bjune, A. E.: Strengths and Weaknesses of Quantitative Climate Reconstructions Based on Late-Quaternary Biological Proxies, Open Ecol. J., 3, 68–110, https://doi.org/10.2174/1874213001003020068, 2010. a 4. Bröcker, J. and Smith, L. A.: Increasing the reliability of reliability diagrams, Weather Forecast., 22, 651–661, https://doi.org/10.1175/WAF993.1, 2007. a 5. Chevalier, M., Davis, B. A. S., Sommer, P. S., Zanon, M., Carter, V. A., Phelps, L. N., Mauri, A., and Finsinger, W.: Eurasian Modern Pollen Database (former European Modern Pollen Database), PANGAEA [data set], https://doi.org/10.1594/PANGAEA.909130, 2019. a
|
|