Surface pollen and modern vegetation in Southern Xinjiang,China

The study of modern pollen,and vegetation can improve the accuracy of paleoenvironmental reconstruction based on fossil pollen data.A total of 188 pollen surface samples were collected from Southern Xinjiang(34°00’–43°00’N,74°00’–94°00’E)in China,with an elevation range of 888–4530 m.Surface pollen and vegetation were studied in the northern region of the Kunlun Mountains and the southern region of the Tianshan Mountains.The results showed that the surface pollen assemblages on the southern slope of the Tianshan Mountains(3530–1124 m)were divided into three pollen zones,namely,montane steppe,montane desert steppe,and montane desert.These zones were dominated by Artemisia,Chenopodiaceae,and Ephedra pollen.The surface pollen assemblages in the eastern Pamir Plateau(4530–1287 m)could be divided into alpine meadow,montane desert steppe,and montane desert zones,which were predominantly characterized by Artemisia,Chenopodiaceae,and Asteraceae pollen.However,the Southern Tarim Basin(3548–888 m)comprised montane desert steppe and montane desert zones,which was dominated by Artemisia and Chenopodiaceae pollen.The geographic distribution of the surface pollen sites obtained using ArcGIS,the R-value,and Pearson correlation analyses indicated that the over-represented Picea and Pinus pollen were of external origin and were transported by wind,water(rivers),and ice(glacier movement).Over-representation of Ephedra and Nitraria pollen was mainly distributed in the montane desert and desert steppe zones,respectively.Pollen from Chenopodiaceae and Artemisia were over-represented and broadly distributed across Southern Xinjiang.Juglans pollen was concentrated in areas with walnut trees,strongly indicating the presence of local parent plants.According to the Hybrid Singleparticle Lagrangian Integrated Trajectory model,more Pinus pollen was transported to the Pamir region by external airflows during spring and summer,resulting in its higher surface pollen content.Research elucidating the relationship between modern pollen and vegetation in southern Xinjiang could provide data describing the surface palynological database of Xinjiang for use in large-scale paleoenvironmental reconstructions.

新疆天山大气桦木花粉与气象因子的相关分析

大气花粉的运移和沉降与各地的气象因子间存在着密切的联系.通过在新疆中天山地区处于不同植被带的3个研究点(新疆天池气象站、阜康荒漠生态系统定位站及北沙窝草炭试验站)安装花粉收集器,进行了长达5年(2001年7月~2006年7月)的大气中桦木属花粉的监测,目的是为了探讨桦木属花粉的数量变化和时空分布动态特征,以及与各个气象因子之间的响应关系.研究结果表明:(1)桦木属花粉组合与植物的花期相对应,具有季节性变化.在2003年, 3个研究点的桦木属花粉浓度都最低,可能与2003年年平均温度降低有关,低温致使花粉减产.(2)由桦木属花粉含量与主要气象因子的相关分析得出,天池研究点和阜康研究点的年平均温度高低直接影响着桦木属花粉浓度大小,年平均降水和日照时数则在不同地区表现出相反的影响,风速和风向对桦木属花粉的散布有一定影响.(3)新疆天池地区大气中桦木属花粉的产量能反映其植物分布情况;而中天山地区一些表土和全新世地层中的桦木属花粉含量偏高,应能直接表明其古植被中的植物区系成分的组成,且与全新世气候变化及人类活动的影响密切相关.该项研究有助于新疆地区古气候重建、大气环境监测和生态文明建设.

Airborne pollen patterns and their relationship with meteorological factors in the Betula microphylla-dominated wetland of Ebinur Lake,Xinjiang,China

Airborne pollen is indicative of vegetation and climatic conditions.This study investigates airborne pollen trapping in the Betula microphylla-dominated wetland of Ebinur Lake in Northwestern China from September 2012 to August 2015 using Pearson correlation analysis and the Hybrid Single-particle Lagrangian Integrated Trajectory model.Higher temperatures and moderate precipitation during the flowering period facilitated an increase in birch pollen with more exotic spruce pollen carried from the Tianshan Mountains by airflows,leading to the highest arbor pollen concentrations from September 2012 to August 2013.Peak pollen concentrations from September 2013 to August 2014 were possibly due to an increase in herbaceous pollen resulting from higher temperatures,lower precipitation and more exotic pollen from the desert of southwest Ebinur Lake and Central Asia in summer and autumn.Between September 2014 and August 2015,unfavorable climate conditions in summer and autumn decreased the pollen dispersal of xerophytes such as Artemisia and Chenopodiaceae,with little pollen transported from the Kazakh hilly area in late summer,resulting in the lowest pollen concentrations.Climatic parameters and air mass movements both greatly affected the atmospheric pollen concentration.The results provide information concerning the dispersion and distribution of birch pollen,paleoenvironmental reconstruction and wetland conservation.

Vegetation and environment changes inferred from pollen records since 3000 cal. yr BP in Kanas wetland, Xinjiang

Aims climate change can significantly affect the vegetation worldwide.thus,paleovegetation and paleoclimate reconstruction should consider the quantitative relationship between modern vegetation and climate.the specific objectives of this study were(i)to assess the influence of environmental variables on pollen assemblages in the Kanas region,(ii)to reconstruct the evolution of vegetation over the past 3000 years using pollen records and(iii)to quantify historical climate change(including mean annual temperature and total annual precipitation)using a weighted averaging partial least squares regression method(WAPLS)applied to fossil pollen data from the Kanas wetland in Xinjiang,china.Methods A total of 65 surface and 50 fossil samples were collected from the Kanas wetland and analysed for 14c,pollen and grain size.By com-bining these data with those obtained from 214 samples of surface pollen assemblages in north Xinjiang,the late Holocene climate was reconstructed using a WAPLS model.Important Findingsthe vegetation in Kanas was dominated by forest for the past 3000 years,undergoing an arbour-vegetation transition from predominantly pine to spruce over that period.the WAPLS model showed that the paleoclimate progressed from cold-wet to warm-dry and subsequently back to cold-wet.Prior to 1350 calibrated years before the present(cal.yr BP),the climate of Kanas was cold and wet,and conditions became increasingly warm and dry until 870 cal.yr BP.the temperature reconstruction model indicated that a‘Little Ice Age’occurred~380 cal.yr BP.these data will help us improve the understanding of abrupt climate change and provide important information regarding the prediction of climate.