Abstract
Pollen productivity is a critical parameter in the interpretation of pollen-vegetation relationships, and in the quantitative reconstructions of past vegetation from fossil pollen records. One-year monitoring records were collected for 143 pollen traps in various parts of northern China, together with modern vegetation data. Absolute Pollen Productivity Estimates (APPE) were calculated for 11 taxa using the ratio of pollen influx to plant coverage at each applicable sampling site, in which the plants of the target taxon were present. Relative Pollen Productivity Estimates (RPPE) were calculated for the 11 taxa (taking Poaceae as the reference taxon) at those sites in which each taxon occurred together with Poaceae. Artemisia and Chenopodiaceae were found to have the highest RPPEs and the largest RPPEs ranges, while Pinus and Quercus also had higher RPPEs than Poaceae; Abies, Betula, Larix, Picea and Cyperaceae had relatively low RPPEs. Variations in RPPE between different areas may be explained by variations in climatic conditions, plant coverage and land use practices which might influence plant growing situation. Marked effect that variations in pollen productivity can have on vegetation reconstructions was demonstrated by applying these distinct RPPEs to reconstructions of Holocene vegetation in the Lake Daihai area (northern China), such as a large range of RPPE produces a large range of plant coverage. Variations in RPPEs within a single taxon, related to vegetation coverage and climatic conditions, therefore need to be considered in future vegetation reconstructions.
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Acknowledgements
This research was supported by the National Natural Science Foundation of China (Grant Nos. 41877459 and 41630753) and the CAS Pioneer Hundred Talents Program (Xianyong Cao) the German Research Foundation (DFG) (No. 41861134030). Cathy Jenks provided help with language editing.
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Zhang, K., Qin, W., Tian, F. et al. Influence of plant coverage and environmental variables on pollen productivities: evidence from northern China. Front. Earth Sci. 14, 789–802 (2020). https://doi.org/10.1007/s11707-020-0834-0
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DOI: https://doi.org/10.1007/s11707-020-0834-0