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Relative pollen productivity estimates for major plant taxa of cultural landscapes in central eastern China
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.ORCID iD: 0000-0002-2025-410X
University of Tallin, Estonia.
Toulouse University-Le Mirail, France.
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2017 (English)In: Vegetation History and Archaeobotany, ISSN 0939-6314, E-ISSN 1617-6278, Vol. 26, no 6, p. 587-605Article in journal (Refereed) Published
Abstract [en]

In this study we estimate relative pollen productivity (RPP) for plant taxa characteristic of human-induced vegetation in ancient cultural landscapes of the low mountain ranges of Shandong province in eastern temperate China. RPP estimates are required to achieve pollen-based reconstructions of Holocene plant cover using modelling approaches based on Prentice's and Sugita's theoretical background and models (REVEALS and LOVE). Pollen counts in moss samples and vegetation data from 36 sites were used in the Extended R-Value (ERV) model to estimate the relevant source area of pollen (RSAP) of moss polsters and RPP of major plant taxa. The best results were obtained with the ERV sub-model 3 and Prentice's taxon-specific method (using a Gaussian Plume dispersal model) to distance weight vegetation data. RSAP was estimated to 145 m using the maximum likelihood method. RPP was obtained for 18 taxa of which two taxa had unreliable RPP (Amaranthaceae/Chenopodiaceae and Vitex negundo). RPPs for Castanea, Cupressaceae, Robinia/Sophora, Aster/Anthemis-type, Cannabis/Humulus, Caryophyllaceae, Brassicaceae and Galium-type are the first ones for China. Trees, except Robinia/Sophora (RPP = 0.78 +/- 0.03) have larger RPPs than herbs other than Artemisia (RPP = 24.7 +/- 0.36). The RPPs for Quercus, Pinus and Artemisia are comparable with other RPPs obtained in China, the RPPs for Pinus, Quercus, Ulmus, Cyperaceae and Galium-type with the mean RPPs obtained in Europe, and RPP for Cupressaceae with that for Juniperus in Europe. The values for Aster/Anthemis-type, Caryophyllaceae, Asteraceae SF Cichorioideae and Juglans differ from the few RPPs available in China and/or Europe.

Place, publisher, year, edition, pages
Springer, 2017. Vol. 26, no 6, p. 587-605
National Category
Earth and Related Environmental Sciences
Research subject
Environmental Science, Paleoecology
Identifiers
URN: urn:nbn:se:lnu:diva-59571DOI: 10.1007/s00334-017-0636-9ISI: 000413944100003OAI: oai:DiVA.org:lnu-59571DiVA, id: diva2:1061592
Available from: 2017-01-03 Created: 2017-01-03 Last updated: 2017-11-22Bibliographically approved
In thesis
1. Pollen productivity estimates and pollen-based reconstructions of Holocene vegetation cover in Norhtern adn 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 Norhtern adn 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 ; 271/2016
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)978-91-88357-52-6 (ISBN)
Public defence
2016-12-12, Fullriggaren, Kocken, Kalmar, 09:30
Opponent
Supervisors
Available from: 2017-01-03 Created: 2017-01-03 Last updated: 2017-01-12Bibliographically approved

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Li, FurongGaillard, Marie-José

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