Spatially Nonstationary Relationships between Copper Accumulation in Rice Grain and Some Related Soil Properties in Paddy Fields at a Regional Scale

Previous studies on the relationships between trace metal accumulation in plants and related soil properties have commonly assumed spatial stationarity by using traditional (global) regression techniques such as ordinary least squares regression (OLS). In this study, geographically weighted regressi...

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Bibliographic Details
Published inSoil Science Society of America journal Vol. 78; no. 5; pp. 1765 - 1774
Main Authors Qu, Mingkai, Li, Weidong, Zhang, Chuanrong, Huang, Biao, Zhao, Yongcun
Format Journal Article
LanguageEnglish
Published Madison The Soil Science Society of America, Inc 01.09.2014
American Society of Agronomy
Subjects
Accumulation
Biogeochemistry
Copper
Hazardous materials
Metals
Organic matter
Rice
Soil contamination
Soil organic matter
Soil properties
Trace metals
Variance analysis
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Summary:Previous studies on the relationships between trace metal accumulation in plants and related soil properties have commonly assumed spatial stationarity by using traditional (global) regression techniques such as ordinary least squares regression (OLS). In this study, geographically weighted regression (GWR) was used to explore the relationships between the Cu concentration in rice (Oryza sativa L.) grain and a set of perceived soil properties, including total Cu in the soil, pH, and soil organic matter in Jiaxing, China. It was found that GWR performed much better than OLS in characterizing the relationships, in terms of the coefficient of determination (R2), corrected Akaike information criterion, ANOVA test, sum of squared residuals, and spatial autocorrelations of residuals. The GWR analysis showed that the relationships between grain Cu and the three related soil properties were not constant across space and there was great spatial non‐stationarity. Results also indicated that GWR could reveal the spatial variations of the relationships ignored by OLS and thus could be used to explain the local causes of Cu accumulation in rice grain. This study demonstrated the advantages of local spatial modeling techniques in modeling the accumulation of hazardous materials in soil–plant systems at regional scales.
Bibliography:All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.
ISSN:0361-5995
1435-0661
DOI:10.2136/sssaj2014.02.0067