Applying multivariate methods to soil–solution interactions in carbonate media

Soil solution composition depends on the solid phase properties of soils. Therefore it is necessary to determine how soil and solution interact in order to understand the processes that influence ecosystems, such as plant nutrition or the movement of contaminants in soils. As the product of many int...

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Published inGeoderma Vol. 137; no. 3; pp. 352 - 359
Main Authors González, C., Quintana, J.R., Moreno, L., Vázquez, A., Lafuente, A.L., Romero, A.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 15.01.2007
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Abstract Soil solution composition depends on the solid phase properties of soils. Therefore it is necessary to determine how soil and solution interact in order to understand the processes that influence ecosystems, such as plant nutrition or the movement of contaminants in soils. As the product of many interrelated factors, these interactions are very complex. We studied the properties of leachates of 10 calcaric Fluvisols subject to displacement with de-ionized water, in columns at atmospheric pressure, and investigated their relationship with properties of the soil. To determine these interactions we used two complementary statistical techniques: bivariate correlations and a multivariate direct gradient canonical ordination method (Redundancy Analysis). The two statistical techniques used to relate the characteristics of the solution and the properties of the soil gave similar results. The two techniques allowed the conclusion that clay (%), organic carbon (g kg − 1 ) and total nitrogen (g kg − 1 ) were the properties of the soils that determine the composition of the soil solution. Also, the multivariate methods employed have been useful to synthesize information when a large number of variables are used.
AbstractList Soil solution composition depends on the solid phase properties of soils. Therefore it is necessary to determine how soil and solution interact in order to understand the processes that influence ecosystems, such as plant nutrition or the movement of contaminants in soils. As the product of many interrelated factors, these interactions are very complex. We studied the properties of leachates of 10 calcaric Fluvisols subject to displacement with de-ionized water, in columns at atmospheric pressure, and investigated their relationship with properties of the soil. To determine these interactions we used two complementary statistical techniques: bivariate correlations and a multivariate direct gradient canonical ordination method (Redundancy Analysis). The two statistical techniques used to relate the characteristics of the solution and the properties of the soil gave similar results. The two techniques allowed the conclusion that clay (%), organic carbon (g kg − 1 ) and total nitrogen (g kg − 1 ) were the properties of the soils that determine the composition of the soil solution. Also, the multivariate methods employed have been useful to synthesize information when a large number of variables are used.
Soil solution composition depends on the solid phase properties of soils. Therefore it is necessary to determine how soil and solution interact in order to understand the processes that influence ecosystems, such as plant nutrition or the movement of contaminants in soils. As the product of many interrelated factors, these interactions are very complex. We studied the properties of leachates of 10 calcaric Fluvisols subject to displacement with de-ionized water, in columns at atmospheric pressure, and investigated their relationship with properties of the soil. To determine these interactions we used two complementary statistical techniques: bivariate correlations and a multivariate direct gradient canonical ordination method (Redundancy Analysis). The two statistical techniques used to relate the characteristics of the solution and the properties of the soil gave similar results. The two techniques allowed the conclusion that clay (%), organic carbon (g kg-1) and total nitrogen (g kg-1) were the properties of the soils that determine the composition of the soil solution. Also, the multivariate methods employed have been useful to synthesize information when a large number of variables are used.
Author Quintana, J.R.
Moreno, L.
Lafuente, A.L.
Vázquez, A.
Romero, A.
González, C.
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Issue 3
Keywords Calcaric Fluvisols
Experimental columns
Multivariate statistical analysis
Soil solution
atmosphere
Information
Total nitrogen
displacements
Motion study
soils
Fluvisols
Gradient
processes
Organic clay
Redundancy
Interaction
Property of soil
pressure
carbonates
water
correlation
Characteristics
solid phase
techniques
ecosystems
leachate
statistical analysis
Contaminant
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Snippet Soil solution composition depends on the solid phase properties of soils. Therefore it is necessary to determine how soil and solution interact in order to...
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SubjectTerms Agronomy. Soil science and plant productions
Biological and medical sciences
Calcaric Fluvisols
Earth sciences
Earth, ocean, space
Exact sciences and technology
Experimental columns
Fundamental and applied biological sciences. Psychology
Multivariate statistical analysis
Soil solution
Soils
Surficial geology
Title Applying multivariate methods to soil–solution interactions in carbonate media
URI https://dx.doi.org/10.1016/j.geoderma.2006.08.016
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