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A Review of Relativ...
A Review of Relative Pollen Productivity Estimates From Temperate China for Pollen-Based Quantitative Reconstruction of Past Plant Cover
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- Li, Furong (author)
- Linnéuniversitetet,Institutionen för biologi och miljö (BOM)
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- Gaillard, Marie-José, 1953- (author)
- Linnéuniversitetet,Institutionen för biologi och miljö (BOM)
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- Xu, Qinghai (author)
- Hebei Normal Univ, China
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- Bunting, Mairi J. (author)
- Univ Hull, UK
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- Li, Yuecong (author)
- Hebei Normal Univ, China
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- Li, Jie (author)
- Hebei Normal Univ, China
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- Mu, Huishuang (author)
- Hebei Normal Univ, China
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- Lu, Jingyao (author)
- Hebei Normal Univ, China
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- Zhang, Panpan (author)
- Hebei Normal Univ, China
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- Zhang, Shengrui (author)
- Hebei Normal Univ, China
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- Cui, Qiao-Yu (author)
- Chinese Acad Sci, China
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- Zhang, Yahong (author)
- Hebei Normal Univ, China
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- Shen, Wei (author)
- Hebei Normal Univ, China
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(creator_code:org_t)
- 2018-09-05
- 2018
- English.
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In: Frontiers in Plant Science. - : Frontiers Media S.A.. - 1664-462X. ; 9
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Abstract
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- Model-based quantitative reconstruction of past plant cover in Europe has shown great potential for: (i) testing hypotheses related to Holocene vegetation dynamics, biodiversity, and their relationships with climate and land use; (ii) studying long term interactions between climate and land use. Similar model-based quantitative reconstruction of plant cover in China has been restricted due to the lack of standardized datasets of existing estimates of relative pollen productivity (RPP). This study presents the first synthesis of all RPP values available to date for 39 major plant taxa from temperate China and proposes standardized RPP datasets that can be used for model-based quantitative reconstructions of past plant cover using fossil pollen records for the region. We review 11 RPP studies in temperate China based on modern pollen and related vegetation data around the pollen samples. The study areas include meadow, steppe and desert vegetation, various woodland types, and cultural landscapes. We evaluate the strategies of each study in terms of selection of study areas and distribution of study sites; pollen- and vegetation-data collection in field; vegetation-data collection from satellite images and vegetation maps; and data analysis. We compare all available RPP estimates, select values based on precise rules and calculate mean RPP estimates. We propose two standardized RPP datasets for 31 (Alt1) and 29 (Alt2) plant taxa. The ranking of mean RPPs (Alt-2) relative to Poaceae (= 1) for eight major taxa is: Artemisia (21) > Pinus (18.4) > Betula (12.5) > Castanea (11.5) > Elaeagnaceae (8.8) > Juglans (7.5) > Compositae (4.5) > Amaranthaceae/Chenopodiaceae (4). We conclude that although RPPs are comparable between Europe and China for some genera and families, they can differ very significantly, e.g., Artemisia, Compositae, and Amaranthaceae/Chenopodiaceae. For some taxa, we present the first RPP estimates e.g. Castanea, Elaeagnaceae, and Juglans. The proposed standardized RPP datasets are essential for model-based reconstructions of past plant cover using fossil pollen records from temperate China.
Subject headings
- NATURVETENSKAP -- Biologi -- Ekologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Ecology (hsv//eng)
- NATURVETENSKAP -- Geovetenskap och miljövetenskap (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences (hsv//eng)
Keyword
- Extended R-Value (ERV) model
- relevant source area of pollen (RSAP)
- fall speed of pollen (FSP)
- vegetation-data collection
- modern pollen sampling
- Paleoecology
- Paleoekologi
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- By the author/editor
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Li, Furong
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Gaillard, Marie- ...
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Xu, Qinghai
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Bunting, Mairi J ...
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Li, Yuecong
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Li, Jie
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show more...
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Mu, Huishuang
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Lu, Jingyao
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Zhang, Panpan
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Zhang, Shengrui
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Cui, Qiao-Yu
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Zhang, Yahong
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Shen, Wei
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show less...
- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Biological Scien ...
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and Ecology
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Earth and Relate ...
- Articles in the publication
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Frontiers in Pla ...
- By the university
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Linnaeus University