JANSKÁ, Veronika, Francisco De Borja JIMÉNEZ ALFARO GONZÁLEZ, Milan CHYTRÝ, Jan DIVÍŠEK, Oleg ANENKHONOV, Andrey KOROLYUK, Nikolai LASHCHINSKYI and Martin CULEK. Palaeodistribution modelling of European vegetation types at the Last Glacial Maximum using modern analogues from Siberia: Prospects and limitations. Online. Quaternary Science Reviews. Oxford: PERGAMON-ELSEVIER SCIENCE LTD, 2017, vol. 159, March, p. 103-115. ISSN 0277-3791. Available from: https://dx.doi.org/10.1016/j.quascirev.2017.01.011. [citováno 2024-04-23]
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Basic information
Original name Palaeodistribution modelling of European vegetation types at the Last Glacial Maximum using modern analogues from Siberia: Prospects and limitations
Authors JANSKÁ, Veronika (203 Czech Republic, belonging to the institution), Francisco De Borja JIMÉNEZ ALFARO GONZÁLEZ (724 Spain, guarantor, belonging to the institution), Milan CHYTRÝ (203 Czech Republic, belonging to the institution), Jan DIVÍŠEK (203 Czech Republic, belonging to the institution), Oleg ANENKHONOV (643 Russian Federation), Andrey KOROLYUK (643 Russian Federation), Nikolai LASHCHINSKYI (643 Russian Federation) and Martin CULEK (203 Czech Republic, belonging to the institution)
Edition Quaternary Science Reviews, Oxford, PERGAMON-ELSEVIER SCIENCE LTD, 2017, 0277-3791.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10611 Plant sciences, botany
Country of publisher United Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 4.334
RIV identification code RIV/00216224:14310/17:00094647
Organization unit Faculty of Science
Doi http://dx.doi.org/10.1016/j.quascirev.2017.01.011
UT WoS 000395609300008
Keywords in English Europe; Last Glacial Maximum; Modern analogues; Palaeoecological reconstructions; Siberia; Species distribution modelling
Tags NZ, rivok
Tags International impact, Reviewed
Changed by Changed by: Ing. Nicole Zrilić, učo 240776. Changed: 10/4/2018 13:13.
Abstract
We modelled the European distribution of vegetation types at the Last Glacial Maximum (LGM) using present-day data from Siberia, a region hypothesized to be a modern analogue of European glacial climate. Distribution models were calibrated with current climate using 6274 vegetation-plot records surveyed in Siberia. Out of 22 initially used vegetation types, good or moderately good models in terms of statistical validation and expert-based evaluation were computed for 18 types, which were then projected to European climate at the LGM. The resulting distributions were generally consistent with reconstructions based on pollen records and dynamic vegetation models. Spatial predictions were most reliable for steppe, forest-steppe, taiga, tundra, fens and bogs in eastern and central Europe, which had LGM climate more similar to present-day Siberia. The models for western and southern Europe, regions with a lower degree of climatic analogy, were only reliable for mires and steppe vegetation, respectively. Modelling LGM vegetation types for the wetter and warmer regions of Europe would therefore require gathering calibration data from outside Siberia. Our approach adds value to the reconstruction of vegetation at the LGM, which is limited by scarcity of pollen and macrofossil data, suggesting where specific habitats could have occurred. Despite the uncertainties of climatic extrapolations and the difficulty of validating the projections for vegetation types, the integration of palaeodistribution modelling with other approaches has a great potential for improving our understanding of biodiversity patterns during the LGM.
Links
CZ.1.07/2.3.00/30.0037, interní kód MU
(CEP code: EE2.3.30.0037)
Name: Zaměstnáním nejlepších mladých vědců k rozvoji mezinárodní spolupráce (Acronym: Postdoc II.)
Investor: Ministry of Education, Youth and Sports of the CR, 2.3 Human resources in research and development
GAP504/11/0454, research and development projectName: Změny biodiverzity na přechodu pleistocénu a holocénu: současné analogie v reliktních ekosystémech Sibiře
Investor: Czech Science Foundation
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