Soil moisture induced changes on fine-scale spatial pattern of soil respiration in a semi-arid sandy grassland

High variability of soil respiration measured at fine spatial scale increases the uncertainty when trying to determine the representative average soil respiration (R-s) flux. A possible way to decrease the uncertainty, while also optimising measurement effort, could be the calculation of required number of R, measurements (N-opt) together with the optimisation of their spatial arrangement. The goals of this study were to find explanatory variables of the structural parameters of fine-scale 12, spatial pattern and of N-opt for sampling optimisation. We conducted field R-s, soil temperature (T-s) and soil water content (SWC) measurements in a Hungarian sandy pasture over several years along circular transects of 75 evenly spaced (20 cm distance) sampling positions. Structural parameters of patterns of R-s and the covariates were determined from variograms. Ranges of spatial autocorrelation varied between 0 and 3.6 m for R-s, 0 and 3 m for SWC and 0 and 2.9 m for T-s. Patch size of R-s depended negatively on transect average SWC. To understand and quantify the spatial dependence of variables, cross-variograms were calculated. R, proved to be positively spatially correlated to SWC at low water supply, while T-s-R-s, and SWC-T-s spatial correlations were mostly negative, both due the direct effect of evaporative cooling on T-s. We found that spatial patchiness became less robust and the correlations generally decreased as soil moisture content was high. We found that explanatory variable of N-opt was also SWC, with negative correlation between them. We conclude that sampling could be optimized on the basis of the easily measurable actual SWC, which determines both the optimal number of R-s measurements and the minimum distances between individual samples in semi-arid ecosystems. (C) 2013 Elsevier B.V. All rights reserved.