Authors Li, Jianyong; Xu, Qinghai; Gaillard-Lemdahl, Marie-Jose; Seppa, Heikki; Li, Yuecong; Hun, Lingyun; Li, Manyue
Journal VEGETATION HISTORY AND ARCHAEOBOTANY , NOV 2013,6:22
Abstract Studies of the modern relationship between pollen, vegetation and land-use are essential to infer past human impact on vegetation from pollen records. Nevertheless, such investigations are relatively few in China. We present here a study of pollen assemblages from sediment samples collected from irrigation pools in the Tuoliang and Qipanshan catchments in northern China. Pollen and spores from natural vegetation such as Artemisia, Chenopodiaceae, Pinus and Selaginella sinensis dominate the pollen assemblages, while pollen types which could be from crops such as cereals, Brassicaceae, Fabaceae, Solanaceae, Apiaceae and Cucurbitaceae are common but not abundant. Pollen percentages of Artemisia and Chenopodiaceae become less with decreasing altitude, while Pinus and S. sinensis percentages increase, indicating that saccate Pinus pollen and S. sinensis spores are transported further than non-saccate Artemisia and Chenopodiaceae pollen, and differential sorting of pollen is occurring during transport in river water. Proportions of pollen from farmland and crops increase with decreasing altitude, showing that pollen percentages of crops might be a good indicator of the extent of farmland. A linear correlation analysis between pollen percentages and vegetation proportions shows that pollen percentages of crops are positively correlated with proportions of farmland, while correlation between pollen percentages of trees, shrubs and herbs and proportions of woodland, scrubland and grassland respectively is poor. This study indicates that the relationship between pollen percentages and vegetation proportions can be explained by the differences of pollen productivity, dispersal and deposition, and might be the basis for a modelling approach to infer past vegetation cover in northern China.
Species covered 中华卷柏 Selaginella sinensis 蒿属 Artemisia
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