Analyzing spatiotemporal variability of heterotrophic soil respiration at the field scale using orthogonal functions

This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.

Feature

Request download

Citation

Citation Options

Identification

*Title:*	Main Title: Analyzing spatiotemporal variability of heterotrophic soil respiration at the field scale using orthogonal functions
*Description:*	Abstract: Soil CO2 efflux was measured with a closed chamber system along a 180 mtransect on a bare soil field characterized by a gentle slope and a gradient in soil properties at 28 days within a year. Principal component analysis (PCA) was used to extract the most important patterns (empirical orthogonal functions, EOFs) of the underlying spatiotemporal variability in CO2 efflux. These patterns were analyzed with respect to their geostatistical properties, their relation to soil parameters obtained from laboratory analysis, and the relation of their loading time series to temporal variability of soil temperature andmoisture. A particular focuswas set on the analysis of the overfitting behaviour of two statistical models describing the spatiotemporal efflux variability: i) a multiple regression model using the k first EOFs of soil properties to predict the n first EOFs of efflux, which were then used to obtain a prediction of efflux on all days and points; and ii) a modified multiple regression model based on re-sorting of the EOFs based on their expected predictive power. It was demonstrated that PCA helped to separate meaningful spatial correlation patterns and unexplained variability in datasets of soil CO2 efflux measurements. The two PCA analyses suggested that only about half of the total variance of efflux could be related to field-scale spatial variability of soil properties, while the other halfwas “noise” attributed to temporal fluctuationsontheminute time scale andshort-range spatial heterogeneity on the decimetre scale. The most important spatial pattern in CO2 efflux was clearly related to soil moisture and the driving soil physical properties. Temperature, on the other hand, was the most important factor controlling the temporal variability of the spatial average of soil respiration.
*Identifier:*	10.1016/j.geoderma.2012.02.016 (DOI)

Responsible Party

*Creators:*	Alexander Graf (Author), Michael Herbst (Author), Lutz Weihermüller (Author), Johan A. Huisman (Author), Nils Prolingheuer (Author), Ludger Bornemann (Author), Harry Vereecken (Author)
*Publisher:*	Elsevier
*Publication Year:*	2013

Topic

*TR32 Topic:*	Soil
*Related Subproject:*	B1
*Subjects:*	Keywords: Soil CO2 efflux, Semivariogram, Closed Chamber, Soil Respiration

File Details

*Filename:*	2012_Graf_Geoderma.pdf
*Data Type:*	Text - Article
*Size:*	11 Pages
*File Size:*	691 KB
*Dates:*	Accepted: 12.02.2012 Available: 06.04.2012
*Mime Type:*	application/pdf
*Data Format:*	PDF
*Language:*	English
*Status:*	Completed

Constraints

*Download Permission:*	Only Project Members
*General Access and Use Conditions:*	For internal use only
*Access Limitations:*	For internal use only
*Licence:*	[TR32DB] Data policy agreement

Geographic

Specific Information - Publication

*Publication Status:*	Published
*Review Status:*	Peer reviewed
*Publication Type:*	Article
*Article Type:*	Journal
*Source:*	Geoderma
*Source Website:*	www.elsevier.com/locate/geoderma
*Volume:*	181-182
*Number of Pages:*	11 (91 - 101)

Metadata Details

*Metadata Creator:*	Alexander Graf
*Metadata Created:*	05.12.2013
*Metadata Last Updated:*	05.12.2013
*Subproject:*	B1
*Funding Phase:*	2
*Metadata Language:*	English
*Metadata Version:*	V50

Metadata Export

Metadata Schema:

Dataset Statistics

*Page Visits:*	832
*Metadata Downloads:*	0
*Dataset Downloads:*	3

Dataset Activity

Feature

Download

top ∧