Study On Relevant Source Area Of Pollen And Relative Pollen Productivity Estimates Of The Southern Typical Steppe In China

The discussion on past climate change and environmental evolution process has long been not only a research hot spot, but also one of the effective ways which can help human beings to predict the trend of environmental change in the future. The response to climate change from vegetation in an area is exceedingly significant. It is easy to judge the historical process of climate change if we acknowledge the vegetation evolution of a certain area in the past through some substitute index. Among them, the pollen analysis is the most frequently-used way. By virtue of its small volume, high yield, wide spread extent, tough crust which is hard to be corroded and the durability of saving for a long time, pollen has become a kind of important substitute index in simulating of the vegetation change. Pollen analysis can reveal the spatial and temporal variations between vegetation and climate, thus it is irreplaceable in terms of understanding and quantificationally rebuilding the past landscape. However, there is not a simple linear relationship between pollen and vegetation, that is, we cannot simply think that the vegetation coverage in an area can be directly reflected by its corresponding percentage of all kinds of taxa in a pollen assemblages. At present, the ERV (Extend R Value) model is commonly applied in quantitative study of the relationship between pollen and vegetation. The RSAP (Relevant Source Area of Pollen) and PPEs (Relative Pollen Productivity Estimates) estimated by the ERV model are the basis of reconstruction of paleovegetation according to pollen data.In this paper, we estimated the RSAP and calculated the pollen fall speed and PPEs of main taxa by different ERV models based on two years’sampling and detailed vegetation investigation (by different sampling strategies) in Bashang steppe located in the junction of Inner Mongolia and Hebei, North China.The study found that the pollen of herbs mainly come from:Artemisia, Chenopodiaceae, Poaceae, Asteraceae, Fabaceae and Cyperaceae, accounting for more than 85% in the pollen assemblages in Bashang steppe. Accordingly, these taxa also have a large advantage in vegetation composition, especially Poaceae, Fabaceae and Asteraceae. Therefore, the vegetation composition in study area can be basically reflected by pollen of herbs. However, there are still some obvious differences between certain pollen percentage and vegetation composition changes, such as Chenopodiaceae and Cyperaceae.In 2013, we used the 3 ERV sub-models with 1/d,1/d2 and Prentice weighted method to get likelihood function curves respectively, and after detailed comparison, the initial RSAP could be estimated as 2000m. In 2014, after changing the strategy of sampling and adjusting wind speed according to meteorological data, we found that the trend of likelihood function curves were in contrast to the curves attained in 2013, in spite of that, we supposed the RSAP was close to 3000m.The PPEs of main taxa in Bashang steppe estimated by ERV models in 2013 and 2014 are displayed as follows(using Poaceae as the reference taxon):Artemisia (21.81 ± 0.49 and 0.49±0.60), Chenopodiaceae (24.90±2.96 and 2.96±1.32) are the highest, the rest are Asteraceae(7.98±0.61 and 0.61±0.31), Cyperaceae (6.45±0.31 and 0.31±0.07), Allium (1.99 ± 0.39 and 0.39 ± 0.22) and Fabaceae (0.15 ± 0.12 and 0.15 ± 0.09).The correction of relationship between pollen and vegetation based on PPEs shows that the majority of relationships between pollen and vegetation have been promoted to a certain extent (except Poaceae) and are relatively close in the two years. The dominant species such as Artemisia, Chenopodiaceae and Asteraceae are promoted obviously; the R value of Allium and Fabaceae has increased, but not by much. While there is almost no change for Cyperaceae, even if its correlation in 2013 is better in 2014.Through this study we can conclude that in addition to the influence of geographical environment and species differences, strategy of sampling and inter annual variability of local climate are also important influence factors of RSAP and PPEs. Considering the lack of species which can be compared and the lack of successive studies in similar area, thus further studies are needed about the influence degree of various factors.