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Modern pollen–€“climate relationships in north Xinjiang, northwestern China: Implications for pollen-based reconstruction of Holocene climate
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
University of Chinese Academy of Sciences, China.
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.ORCID iD: 0000-0002-2025-410X
VU University Amsterdam, The Netherlands.
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2017 (English)In: The Holocene, ISSN 0959-6836, E-ISSN 1477-0911, Vol. 27, no 7, p. 951-966Article in journal (Refereed) Published
Abstract [en]

Fossil pollen records are widely used to reconstruct past climate. Such reconstructions require that the relationships between pollen assemblages, vegetation, and climate are well understood. These can be studied in present circumstances given we assume that modern vegetation and climate are analogous to past ones. In this study, we analyze pollen–vegetation–climate relationships in the Jungar desert and Altay Mountains, northwestern China, a region for which careful reconstruction of past climate is needed to answer unsolved questions on past climate in an area located at the boundary between two different climate regimes (westerlies and monsoon). We use a dataset of 66 surface pollen samples from forest, meadow, steppe, and desert vegetation and six related climate variables, Tann, TJan, TJul, Pann, PJan, and PJul. Principal components analysis, redundancy analysis, Monte Carlo permutation tests, and variation partitioning are applied to quantify these relationships. We also assess pollen ratios as indices of aridity. We find that (1) Pann is the major climatic factor influencing pollen assemblages, followed by PJul, (2) the two variables are not correlated, and (3) the shared effect of (1) PJan and PJul, (2) PJan and Pann, (3) PJul and Tann, and (4) Tann, TJan, and TJul explains a larger portion of the variation in pollen data than the individual effect of each variable. Therefore, robust pollen–climate transfer functions can be developed for Pann and PJul, and several climate variables treated in combination. Artemisia/Chenopodiaceae is a strong index of aridity and Artemisia/Gramineae might be a useful index of Pann and PJul.

Place, publisher, year, edition, pages
Sage Publications, 2017. Vol. 27, no 7, p. 951-966
National Category
Earth and Related Environmental Sciences
Research subject
Environmental Science, Paleoecology
Identifiers
URN: urn:nbn:se:lnu:diva-59570DOI: 10.1177/0959683616678464ISI: 000406530800004Scopus ID: 2-s2.0-85025819709OAI: oai:DiVA.org:lnu-59570DiVA, id: diva2:1061586
Available from: 2017-01-03 Created: 2017-01-03 Last updated: 2019-08-29Bibliographically approved
In thesis
1. Pollen productivity estimates and pollen-based reconstructions of Holocene vegetation cover in Northern and temperate China for climate modelling
Open this publication in new window or tab >>Pollen productivity estimates and pollen-based reconstructions of Holocene vegetation cover in Northern and temperate China for climate modelling
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Model projections of future climate change require that coupled climate-vegetation models are developed and validated, i.e. these models should be able to reproduce past climate and vegetation change. Records of pollen deposited in lake bottoms and peat bogs can provide the information needed to validate these models. The aim of this thesis was i) to explore the modern relationships between pollen and vegetation in northern and temperate China and estimate pollen productivity of major plant taxa, and ii) to use the results of i) to produce the first reconstruction of plant cover in China over the last 10 000 years for the purpose of climate modelling. A study of the modern pollen-vegetation-climate relationships was performed in northwestern China (Paper I). Pollen productivity for 18 major plants of cultural landscapes in central-eastern China was estimated (Paper II). Based on a synthesis and evaluation of all existing estimates of pollen productivity in the study region, a standard dataset of pollen productivity for 31 plant taxa is proposed (Paper III). This dataset was used to achieve pollen-based REVEALS reconstructions of plant cover over the last 10 000 years in 35 regions of northern and temperate China (Paper IV). The major findings can be summarized as follows. Paper I: Annual precipitation (Pann) is the major climatic factor influencing pollen assemblages, followed by July precipitation (PJul). The shared effect of combinations of two climatic factors explains a larger portion of the variation in pollen data than individual variables. Paper II: Of the 16 reliable pollen productivities estimated, the estimates for 8 taxa are new, Castanea, Cupressaceae, Robinia/Sophora, Anthemis type/Aster type, Cannabis/Humulus, Caryophyllaceae, Cruciferae, and Galium type. Trees have in general larger pollen productivity than herbs. Paper III: Of the total 31 taxa for which estimates of pollen productivity are available in China, 13 taxa have more than 1 value. All or most of these values are similar for Artemisia, Cyperaceae, Larix, Quercus and Pinus. Eight taxa have very variable estimates. Paper IV: The REVEALS plant percentage-cover strongly differs from the pollen percentages, and they provide new important insights on past changes in plant composition and vegetation dynamics.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2016. p. 67
Series
Linnaeus University Dissertations ; 271
Keywords
climate, pollen-vegetation relationships, relative pollen productivity, REVEALS model, anthropogenic land-cover change, Holocene, China
National Category
Earth and Related Environmental Sciences
Research subject
Environmental Science, Paleoecology
Identifiers
urn:nbn:se:lnu:diva-59574 (URN)9789188357519 (ISBN)
Public defence
2016-12-12, Fullriggaren, Kocken, Kalmar, 09:30
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Felaktigt ISBN i publikationen 9789188357526

Available from: 2017-01-03 Created: 2017-01-03 Last updated: 2022-03-24Bibliographically approved

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Li, FurongGaillard, Marie-José

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