Artemisia pollen dataset for exploring the potential ecological indicators in deep time

doi:10.5194/essd-14-3961-2022

	Artemisia pollen dataset for exploring the potential ecological indicators in deep time
	Lu, Li-Li ; Jiao, Bo-Han ; Qin, Feng 1; Xie, Gan ; Lu, Kai-Qing ; Li, Jin-Feng ; Sun, Bin ; Li, Min ; Ferguson, David K.; Gao, Tian-Gang ; Yao, Yi-Feng ; Wang, Yu-Fei
	2022
发表期刊	EARTH SYSTEM SCIENCE DATA
ISSN	1866-3508
卷号	14 期号:9 页码:3961-3995
摘要	Artemisia, along with Chenopodiaceae, is the dominant component growing in the desert and dry grassland of the Northern Hemisphere. Artemisia pollen with its high productivity, wide distribution, and easy identification is usually regarded as an eco-indicator for assessing aridity and distinguishing grassland from desert vegetation in terms of the pollen relative abundance ratio of Chenopodiaceae/Artemisia (C/A). Nevertheless, divergent opinions on the degree of aridity evaluated by Artemisia pollen have been circulating in the palynological community for a long time. To solve the confusion, we first selected 36 species from nine clades and three outgroups of Artemisia based on the phylogenetic framework, which attempts to cover the maximum range of pollen morphological variation. Then, sampling, experiments, photography, and measurements were taken using standard methods. Here, we present pollen datasets containing 4018 original pollen photographs, 9360 pollen morphological trait measurements, information on 30 858 source plant occurrences, and corresponding environmental factors. Hierarchical cluster analysis on pollen morphological traits was carried out to subdivide Artemisia pollen into three types. When plotting the three pollen types of Artemisia onto the global terrestrial biomes, different pollen types of Artemisia were found to have different habitat ranges. These findings change the traditional concept of Artemisia being restricted to arid and semi-arid environments. The data framework that we designed is open and expandable for new pollen data of Artemisia worldwide. In the future, linking pollen morphology with habitat via these pollen datasets will create additional knowledge that will increase the resolution of the ecological environment in the geological past. The Artemisia pollen datasets are freely available at Zenodo (https://doi.org/10.5281/zenodo.6900308; Lu et al., 2022).
学科领域	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences
DOI	10.5194/essd-14-3961-2022
收录类别	SCI
语种	英语
WOS关键词	TIBETAN PLATEAU ; PALYNOLOGICAL FEATURES ; GENERA ASTERACEAE ; SYSTEMATIC MARKER ; CLIMATE ; VEGETATION ; EVOLUTION ; CHINA ; L. ; ASSEMBLAGES
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000849639000001
出版者	COPERNICUS GESELLSCHAFT MBH
文献子类	Article; Data Paper
出版地	GOTTINGEN
EISSN	1866-3516
资助机构	Strategic Priority Research Program of the Chinese Academy of Sciences [XDB26000000] ; National Natural Science Foundation of China [31970233, 32070240, 31870179, 31570204, 42077416, 32000174, 42077423] ; Chinese Academy of Sciences President's International Fellowship Initiative [2018VBA0016] ; Sino-Africa Joint Research Center [SAJC201614] ; Key Project at Central Government Level: the ability establishment of sustainable use for valuable Chinese medicine resources [2060302] ; National Plant Specimen Resource Bank [E0117G1001] ; International Partnership Program of Chinese Academy of Sciences [151853KYSB20190027]
作者邮箱	gaotg@ibcas.ac.cn ; yaoyf@ibcas.ac.cn ; wangyf@ibcas.ac.cn
作品OA属性	Green Submitted, gold
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/28608
专题	系统与进化植物学国家重点实验室
作者单位	1.Chinese Acad Sci, State Key Lab Systemat & Evolutionary Bot, Inst Bot, 20 Nanxincun Xiangshan, Beijing 100093, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 3.Ferguson, David K.] Univ Vienna, Dept Paleontol, Althan str 14, A-1090 Vienna, Austria 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Lu, Li-Li,Jiao, Bo-Han,Qin, Feng,et al. Artemisia pollen dataset for exploring the potential ecological indicators in deep time[J]. EARTH SYSTEM SCIENCE DATA,2022,14(9):3961-3995.
APA	Lu, Li-Li.,Jiao, Bo-Han.,Qin, Feng.,Xie, Gan.,Lu, Kai-Qing.,...&Wang, Yu-Fei.(2022).Artemisia pollen dataset for exploring the potential ecological indicators in deep time.EARTH SYSTEM SCIENCE DATA,14(9),3961-3995.
MLA	Lu, Li-Li,et al."Artemisia pollen dataset for exploring the potential ecological indicators in deep time".EARTH SYSTEM SCIENCE DATA 14.9(2022):3961-3995.

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