详细信息
中国及邻区利用孢粉进行古气候定量重建的回顾与数据集成 被引量:19
REVIEW AND DATA INTEGRATION OF POLLEN-BASED QUANTITATIVE PALEOCLIMATE RECONSTRUCTION STUDIES IN CHINA AND ADJACENT AREAS
文献类型:期刊文献
中文题名:中国及邻区利用孢粉进行古气候定量重建的回顾与数据集成
英文题名:REVIEW AND DATA INTEGRATION OF POLLEN-BASED QUANTITATIVE PALEOCLIMATE RECONSTRUCTION STUDIES IN CHINA AND ADJACENT AREAS
作者:郑卓[1];张潇[1];满美玲[1];魏金辉[1,2];黄康有[1]
机构:[1]中山大学地球科学与地质工程学院,广州510275;[2]广东省近海海洋变化与灾害预警技术重点实验室,广东海洋大学,湛江524088
年份:2016
卷号:36
期号:3
起止页码:503
中文期刊名:第四纪研究
外文期刊名:Quaternary Sciences
收录:CSTPCD、、北大核心2014、CSCD2015_2016、北大核心、CSCD
基金:国家自然科学基金项目(批准号:41230101和41472143)资助
语种:中文
中文关键词:孢粉;古气候重建;年均温度;年降水量;数据集成
外文关键词:integrationpollen, paleoclimate reconstruction, mean annual temperature, annual precipitation, data integration
中文摘要:摘要利用孢粉与气候的关系进行定量古气候重建是陆地古环境研究的重要手段,作为植被生态系统对气候变化响应的量化指标,孢粉数据及其定量古气候研究结果对理解冰期一间冰期的气候波动幅度及季风演变均具有十分重要的意义。本文回顾了我国学者利用孢粉数据进行定量古气候重建的历史发展过程,并对中国及局边地区利用孢粉进行定量古气候重建的数据进行收集整理。资料显示,我国几十年来引入的孢粉一气候重建方法最常用的是转换函数和最佳类比法。目前对于第四纪时间段已进行气候重建的孢粉资料不少于50个,重建结果覆盖的年代多集中在全新世以内,大部分研究采用的替代气候参数为年平均温度、年降雨量以及最冷月温度和最热月温度。对我国及邻区的一些年均温度距平的集成分析显示,全新世10.0—7.2cal.kaB.P.为振荡或起伏较大的增温期,早一中全新世总体年平均温度比现代约高出1.0~1.5℃,在4.1~2.1cal.kaB.P.为平缓降温时期,从2.1cal.kaB.P.至今为显著降温期;而年降雨量的数据标准化集成结果显示,冰消期至7.0cal.kaB.P.左右各地的重建结果差异较大,并与石笋氧同位素结果有较大的不同,但降雨量的数据集成在6.0cal.kaB.P.以来共同趋势大致相互吻合,如从4.2cal.kaB.P.开始降雨量降低,与石笋氧同位素可以对比。随着孢粉研究的年代精度提高和方法的进一步成熟,以及现代参照系孢粉代表性样点的不断扩大和国内外资源的共享,孢粉一气候定量重建已成为第四纪古环境恢复不可替代的研究内容。从目前的发展趋势看,孢粉学一定会更好地为区域和全球的第四纪定量气候研究做出新的贡献。
外文摘要:Pollen-based quantitative climate reconstruction is one of the most important methods using terrestrial paleoenvironment proxies. As an effective quantitative parameter for revealing the ecosystem response to climate changes, pollen data and related profound studies on quantitative paleoclimate reconstruction are significant for better understanding the glacial-interglacial environment changes and paleomonsoon histories. In this paper, we review the early development of the methods of pollen-based quantitative climate reconstruction after a brief historical summary. All published documents of pollen-based climate reconstruction in China and adjacent areas are collected and organized. It is shown that the most popular methods used for climate reconstruction are transfer function (TF) and modern analogue technique (MAT) in the recent decades. So far, the number of quantitative climate reconstruction archives based on pollen data for Quaternary period is at least 50 sites, most of which covers only the Holocene period. The most common climate parameters used in the reconstructions are mean annual temperature, annual precipitation, July and January temperatures. According to the data integration of temperature anomaly in China and adjacent areas, it is suggested that the Early Holocene at 10.0- 7.2cal.ka B.P. is a transitional stage into the megathermal period, but characterized by strong oscillations and large differences among regions. The average values for mean annual temperature during the Early-Mid Holocene are generally 1.0 ~ 1.5~C higher than that of present-day. Temperature gradually decreased from 4.1cal.ka B.P. and more significantly decline since 2.1cal.ka B.P. The data integration for annual precipitation is based on the values of standardization which reveals not only inconsistent changes among different sites, but also disagreement in comparison with stalagmite oxygen isotopes for the period between the Last Deglacial to 7.0cal.ka B.P. However, the trend of precipitation reconstruction is likely coherent with the stalagmite result since 6.0cal.ka B.P., in particular for the monso6nal rainfall decrease since 4.2cal.ka B.P. With the improvement of dating precision and techniques of quantitative reconstruction, as well as the enlargement of modern pollen reference samples and resource sharing of Chinese and international pollen database, pollen analysis has become now an irreplaceable method for Quaternary paleoeclima~ studies. According to the new advance of statistic techniques, there is no doubt that palynology will make better contribution to the Quaternary quantitative climate studies both in regional and global scales.
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