University of Oulu

Chevalier, M., Davis, B. A. S., Heiri, O., Seppä, H., Chase, B. M., Gajewski, K., Lacourse, T., Telford, R. J., Finsinger, W., Guiot, J., Kühl, N., Maezumi, S. Y., Tipton, J. R., Carter, V. A., Brussel, T., Phelps, L. N., Dawson, A., Zanon, M., Vallé, F., … Kupriyanov, D. (2020). Pollen-based climate reconstruction techniques for late Quaternary studies. Earth-Science Reviews, 210, 103384.

Pollen-based climate reconstruction techniques for late Quaternary studies

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Author: Chevalier, Manuel1; Davis, Basil A.S.1; Heiri, Oliver2;
Organizations: 1Institute of Earth Surface Dynamics, Geopolis, University of Lausanne, Switzerland
2Geoecology, Department of Environmental Sciences, University of Basel, Switzerland
3Department of Geosciences and Geography, P.O. Box 64, 00014, University of Helsinki, Finland
4Institut des Sciences de l'Evolution-Montpellier (ISEM), University of Montpellier, Centre National de la Recherche Scientifique (CNRS), EPHE, IRD, Montpellier, France
5Department of Geography, Environment and Geomatics, University of Ottawa, Canada
6Department of Biology and Centre for Forest Biology, University of Victoria, Canada
7Department of Biological Sciences, University of Bergen and Bjerknes Centre for Climate Research, Postbox 7803, N-5020 Bergen, Norway
8ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
9Aix Marseille Univ, CNRS, IRD, INRA, Coll France, CEREGE, Aix-en-Provence, France
10Institute of Forest Sciences, Chair of Silviculture, Tennenbacherstr. 4, University of Freiburg, 79106 Freiburg, Germany
11Department of Ecosystem and Landscape Dynamics, University of Amsterdam, the Netherlands
12Department of Archaeology, University of Exeter, United Kingdom
13Department of Mathematical Sciences, University of Arkansas, USA
14Department of Botany, Charles University, Prague, Czechia
15Department of Geography, University of Oregon, Eugene, Oregon 97403, USA
16School of Geosciences, University of Edinburgh, UK
17Royal Botanic Gardens Edinburgh, UK
18Mount Royal University, Calgary, Alberta, Canada
19Institute of Pre- and Protohistoric Archaeology, Christian-Albrechts-Universität zu Kiel, Germany
20Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
21Woods Institute for the Environment, Stanford University, USA
22European Commission, Joint Research Centre, Directorate D – Sustainable Resources - Bio-Economy Unit, Italy
23Geotop & Department of Earth and atmospheric sciences, Université du Québec à Montréal, Canada
24School of Geographical Sciences, University of Bristol, UK
25Laboratoire des Sciences du Climat et de l'Environment, CNRS-CEA-UVSQ, Université Paris-Saclay, France
26Research Unit of Mathematical Sciences, University of Oulu, Finland
27Department of Geoscience, University of Wisconsin-, Madison, USA
28Department of Geography, University of Wisconsin-, Madison, USA
29Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
30Department of Physical Geography and Landscape Science, Faculty of Geography, Lomonosov Moscow State University, Russia
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 11.4 MB)
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Language: English
Published: Elsevier, 2020
Publish Date: 2020-11-19


Fossil pollen records are well-established indicators of past vegetation changes. The prevalence of pollen across environmental settings including lakes, wetlands, and marine sediments, has made palynology one of the most ubiquitous and valuable tools for studying past environmental and climatic change globally for decades. A complementary research focus has been the development of statistical techniques to derive quantitative estimates of climatic conditions from pollen assemblages. This paper reviews the most commonly used statistical techniques and their rationale and seeks to provide a resource to facilitate their inclusion in more palaeoclimatic research. To this end, we first address the fundamental aspects of fossil pollen data that should be considered when undertaking pollen-based climate reconstructions. We then introduce the range of techniques currently available, the history of their development, and the situations in which they can be best employed. We review the literature on how to define robust calibration datasets, produce high-quality reconstructions, and evaluate climate reconstructions, and suggest methods and products that could be developed to facilitate accessibility and global usability. To continue to foster the development and inclusion of pollen climate reconstruction methods, we promote the development of reporting standards. When established, such standards should 1) enable broader application of climate reconstruction techniques, especially in regions where such methods are currently underused, and 2) enable the evaluation and reproduction of individual reconstructions, structuring them for the evolving open-science era, and optimising the use of fossil pollen data as a vital means for the study of past environmental and climatic variability. We also strongly encourage developers and users of palaeoclimate reconstruction methodologies to make associated programming code publicly available, which will further help disseminate these techniques to interested communities.

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Series: Earth-science reviews
ISSN: 0012-8252
ISSN-E: 1872-6828
ISSN-L: 0012-8252
Volume: 210
Article number: 103384
DOI: 10.1016/j.earscirev.2020.103384
Type of Publication: A1 Journal article – refereed
Field of Science: 1171 Geosciences
Funding: The PCMIP (Pollen-Climate Methods Intercomparison Project) workshop was funded by an International Exploratory Workshop Grant from the Swiss National Science Foundation (SNF/FNS) (#IZ32Z0_173407). Participation of early career scientists at the workshop was assisted by travel grants from the International Union for Quaternary Research (INQUA) (Project no. 1705P) and the Past Global Changes organisation (PAGES). MC and PSS were supported by the SNF/FNS funded ‘HORNET’ Project (#200021_169598), KG and TL by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grants, KI by CLAVICHORD Project (H2020-MSCA-IF-EF, 705895), LNP by the FNS grant P2LAP2_187745, and MZ by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) Project number 2901391021 – SFB 1266. SYM was supported by the European Commission (Marie Curie) Fellowship 792197. The development of CREST was supported by the European Research Council (ERC) under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC Starting Grant ‘HYRAX’, grant agreement no. 258657.
Copyright information: © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (