Spatial mapping of soil respiration using auxiliary variables. A small scale study

Soil respiration is a significant contributor to the global emissions of CO2 and is governed by many soil factors. Reliable estimates of CO2 emission on different scales (e.g., field, regional level) are hard to obtain due to the expressed spatial and temporal variability of the CO2 flux. This study aims to investigate the spatial variability of CO2 flux and soil properties in soybean cropland on Fluvisols (Croatia). The field measurements and soil samples were taken in a regular sampling grid (2 × 2 m) with 44 points in total and the spatial variability was assessed using the kriging and cokriging techniques. The soil CO2 flux showed relatively high spatial heterogeneity, ranging from 0.03 mg/m2s to 0.40 mg/m2s. The soil organic matter content (SOM), soil water content (SWC), and soil temperature (ST) had the lower variability ranging from 2.09% to 2.52%, from 27.7% to 46.8%, and from 13.7 °C to 18.2 °C, respectively. The spatial dependence was high for CO2 flux and ST, moderate for SOM, and low for SWC. The incorporation of the auxiliary variables increased the precision of the estimations for CO2 flux, SOM, and SWC. Kriging was the most accurate method for the spatial prediction of ST. The SWC was associated as the most important factor of the CO2 fluxes, indicated by their significant negative correlation, and the highest increase of the prediction precision during spatial modeling. However, more robust co-variates should be incorporated in future models to further increase the precision.