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

Soil CO2 efflux was measured with a closed chamber system along a 180 m transect 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 and moisture. A particular focus was 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 half was "noise" attributed to temporal fluctuations on the minute time scale and short-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. (C) 2012 Elsevier B.V. All rights reserved

On the spatial variation of soil rhizospheric and heterotrophic respiration in a winter wheat stand

Field-scale soil respiration reveals a tremendous variability in space. In order to quantify the spatial variability originating from the heterotrophic and the rhizospheric contribution to total soil respiration, the root exclusion method was applied. At 61 locations within a 50 m × 50 m plot in a winter wheat stand, 7 cm-collars and 50 cm-collars were inserted prior to the root growth to simultaneously measure total respiration and heterotrophic respiration. The rhizospheric component was determined as the difference between the flux measurements of total and heterotrophic respiration. During the vegetation period 2009, in total 18 repeated measurements, including soil temperature and moisture, were carried out.The highest spatial variability in terms of standard deviation up to 2.9 mol CO2 m−2 s−1 was detected for the rhizospheric respiration during the period of massive plant growth. Compared to the heterotrophic contribution the coefficient of variation in space was constantly higher for the rhizospheric contribution. Variogram analyses revealed an almost completely random spatial distribution of heterotrophic respira- tion, whereas the rhizospheric respiration showed a clear spatial autocorrelation. The spatial pattern of total respiration mainly resembles the pattern of the rhizospheric component and is characterized by an average spatial correlation length of 18 m.The results indicate that the sampling design for chamber-based measurements of soil respiration in agro-ecosystems should account for the high spatial variability during plant growth and collars should be separated by a distance larger than the spatial correlation range to ensure uncorrelated samples and thus unbiased representative flux estimates

Characterization and Understanding of Bare Soil Respiration Spatial Variability at Plot Scale

Soil respiration is known to be highly variable with time. Less is known, however, about the spatial variability of heterotrophic soil respiration at the plot scale. We simultaneously measured soil heterotrophic respiration, soil temperature, and soil water content at 48 locations with a nested sampling design and at 76 locations with a regular grid plus refinement within a 13- by 14-m bare soil plot for 15 measurement dates. Soil respiration was measured with a closed chamber covering a surface area of 0.032 m(2). A geostatistical data analyses indicated a mean range of 2.7 m for heterotrophic soil respiration. We detected rather high coefficients of variation of CO2 respiration between 0.13 and 0.80, with an average of 0.33. The number of observations required to estimate average respiration fluxes at a 5% error level ranged between 5 and 123. The analysis of the temporal persistence revealed that a subset of 17 sampling locations is sufficient to estimate average respiration fluxes at a tolerable root mean square error of 0.15 g C m(-2) d(-1). Statistical analysis revealed that the spatiotemporal variability of heterotrophic soil respiration could be explained by the state variables soil temperature and water content. The spatial variability of respiration was mainly driven by variability in soil water content; the variability in the soil water content was almost an order of magnitude higher than the variability in soil temperature