摘要
基于南岭亚高山泥炭湿地在维持华南亚热地区生态系统和区域水平衡中起关键作用,且这一区域的生物因子-古水位定量重建的工作还未有系统展开的现状,以南岭西部的湖南省大坪泥炭地为研究对象,初步开展了该地区现代有壳变形虫的种类组成鉴定工作;通过多元统计分析方法,确定地下水位埋深(Water-Table Depth,WTD)是影响本地区有壳变形虫群落结构变化的主要环境因子,并据此利用生物-环境因子转换函数模型,初步构建了大坪现代泥炭湿地有壳变形虫-地下水位埋深的转换函数关系.研究结果表明:转换函数预测的地下水位埋深与实测地下水位埋深呈一定的相关性,但受制于本次采用面积小、鉴定样本量较少和水位环境梯度较窄的条件下,转换函数预测性能的精度还较低.此次工作可为将来系统开展华南亚热带地区高山泥炭湿地的古水文定量重建工作奠定宝贵的基础数据.
Subalpine peatlands in Nanling Mountains play an important role in maintaining ecosystem and regional water balance in subtropical regions of South China.However,there is still no systematic investigation into the quantitative palaeoenviroment reconstructions in this area.A preliminary study of the distribution of the modern testate amoebae assemblage in Daping peatland in the western Naning Mountains is conducted.A multivariate statistical analysis demonstrated that the water-table depth(WTD)was the main environmental factor for the testate amoeba community composition.Accordingly,testate amoebae-based transfer functions were developed using a variety of commonly used models.The results showed that all transfer function models performed similarly and produced similar reconstructions.However,the root mean square error of prediction(RMSEP)and coefficient of determination tested relatively poor performance of the transfer functions,which was likely due to the relatively small sampling area,insufficient sampling sites and short sampling gradient of water-table depth.A valuable data base can be provided for the further systematic research of the quantitative hydrological reconstructions in subalpine peatlands from subtropical regions of South China.
作者
魏志强
钟巍
欧阳军
叶素素
商圣潭
杨坤有
唐小雯
薛积彬
Robert K BOOTH
WEI Zhiqiang;ZHONG Wei;OUYANG Jun;YE Susu;SHANG Shengtan;YANG Kunyou;TANG Xiaowen;XUE Jibin;Robert K BOOTH(School of Geography,South China Normal University,Guangzhou510631,China;Department of Earth and Environmental Science,Lehigh University,Bethlehem18015,USA)
出处
《华南师范大学学报(自然科学版)》
CAS
北大核心
2019年第3期70-78,共9页
Journal of South China Normal University(Natural Science Edition)
基金
国家自然科学基金项目(41571187,41071137)
广东省自然科学基金项目(2014A030313435,S2011010003413)