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应用生态学报 ›› 2016, Vol. 27 ›› Issue (6): 1759-1766.doi: 10.13287/j.1001-9332.201606.033

• 目次 • 上一篇    下一篇

典型喀斯特小流域不同植被类型间土壤养分的差异性及其空间预测方法

王苗苗1,2,3, 陈洪松1,2*, 付同刚1,2,3, 张 伟1,2, 王克林1,2   

  1. 1中国科学院亚热带农业生态研究所亚热带农业生态过程重点实验室, 长沙 410125;
    2中国科学院环江喀斯特农业生态系统观测研究站, 广西环江 547100;
    3中国科学院大学, 北京 100049
  • 收稿日期:2015-12-15 发布日期:2016-06-18
  • 通讯作者: hbchs@isa.ac.cn
  • 作者简介:王苗苗, 女, 1988年生,博士研究生,主要从事区域生态与景观生态研究. E-mail: 307205590@qq.com
  • 基金资助:
    本文由国家重点基础研究发展计划项目(2015CB452703)和中国科学院STS计划项目(KFJ-EW-STS-092)资助

Differences of soil nutrients among different vegetation types and their spatial prediction in a small typical karst catchment.

WANG Miao-miao1,2,3, CHEN Hong-song1,2*, FU Tong-gang1,2,3, ZHANG Wei1,2, WANG Ke-lin1,2   

  1. 1Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China;
    2Huanjiang Observation and Research Station of Karst Ecosystem, Chinese Academy of Sciences, Huanjiang 547100, Guangxi, China;
    3University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2015-12-15 Published:2016-06-18

摘要: 植被类型制约着土壤结构和元素的异质化过程,致使土壤养分空间分布存在差异性.本文研究了典型喀斯特小流域不同植被类型间土壤养分(全氮TN、全磷TP、全钾TK、有机质SOM)含量分布的差异性,分析比较了普通克里金、回归模型、基于植被类型的回归模型对土壤养分预测的精度.结果表明: TN、TK、SOM与植被类型显著相关(P<0.05),TP与植被类型无显著相关(P=0.390),且TN和SOM在灌木林与耕地之间的差异性显著,TK在乔木林与灌草丛、灌木林与耕地、灌草丛与耕地间的含量差异皆显著;非连续的典型喀斯特小流域地形因子空间异质性较高,基于各样点间真实地形因子的多元线性回归预测模型精度优于基于已知点和预测点位置信息的普通克里金预测方法,且基于植被类型的回归预测模型提高了TN的预测精度.

Abstract: Vegetation types restrict soil structure and heterogeneous processes of elements, which result in difference in spatial distribution of soil nutrients. In this study, the differences in contents of soil nutrients, TN, TP, TK, and soil organic matter (SOM) among different vegetation types were analyzed, and the accuracy of ordinary kriging, regression model and regression model based on vegetation type in predicting soil nutrients was compared. The results showed that, TN, TK and SOM were significantly (P<0.05) correlated to vegetation type, and TP had no significant correlation with vegetation type (P=0.390). TN and SOM had significant difference between shrubbery and arable land. TK had significant difference between arbor and scrub-grassland, shrubbery and arable land, and scrub-grassland and arable land, respectively. In a non-continuous typical small karst catchment, because of high spatial heterogeneity of terrain, the accuracy of multivariate linear regression model based on the real terrain factors of various points was considerably higher than that of ordinary kriging prediction method considering the locations of the known points and prediction points. Moreover, the regression model based on vegetation type improved the prediction accuracy of the TN.