## 4 Discussion  
In our study, the DOC and DTN concentrations fell well within the reported ranges of 2-400 mg kg\({}^{-1}\) dry soil [17; 35] and 1-292 mg kg\({}^{-1}\) dry soil [35; 36; 37], respectively, of various forest soils. Moderate variability in dissolved carbon and nitrogen was observed in this study; however, the variability in DOC and DTN may be more complex and heterogeneous with an increase in the sampling area, because the factors regulating DOC and DTN variations change at different sampling scales [38]. The value of the fractal power parameter for DOC (0.12) was slightly larger than that for DTN (0.087) indicating that the sampling scale may have a higher impact on the variability in DOC concentration. A high spatial resolution over a large area is the ideal case for soil sampling [39] that, in practice, is hardly achievable. As the DOC and DTN data followed a normal distribution (\(p>0.05\)), we could obtain a number for the samples required to estimate the mean soil DOC and DTN concentrations under different confidence levels and varying precision using Equation (1). The required number of samples was generally larger for higher confidence levels and greater precision. For instance, the sample number was generally larger for the 99% confidence level than for the 95% level, and further increased when the precision increased from 15% to 5% (Table A1). For the estimation of DOC and DTN, considerably more samples would have to be taken in a larger study area because of increased heterogeneity. Consequently, the sample number for labile C and N estimation with a precision of 5% for the current study was around 40, which is much smaller than the sample number that was actually used (111 locations). Details on the sample numbers required for estimating DOC and DTN at a given accuracy level with different sampling areas in this study can be found in Table A1. Therefore, careful consideration of the appropriate sample number to be used in the field needs to be undertaken both for practical reasons as well as for accuracy. A nugget sill ratio smaller than 25% indicates strong spatial dependence for a variable of interest [40]. The nugget ratios for both DOC and DTN were smaller than 0.25, indicating a strong spatial dependence. The variability range determines the spatial autocorrelation. When a variable is within the range values, it is spatially autocorrelated, and when it is outside of the range values, it is not. This information provides guidelines for designing appropriate sampling schemes [41]. For DOC samples with a distance smaller than 34.2 they were spatially correlated, whilst those with a distance larger than 34.2 were not spatially correlated. For DTN samples with a distance smaller than 35.1 these were spatially correlated, and for those with a distance larger than 35.1 they were not spatially correlated. As the sampling grid interval for this study (20 m) was smaller than the minimum range of 34.2, this validates our spatial analysis by meeting the requirements of sampling intervals. The mean error (ME) and root mean square error (RMSE) were relatively small, and the root mean square standardized errors (RMSSEs) were close to 1 (Figure 4), all of which indicated that the predictions of DOC and DTN by ordinary kriging and cokriging for the study area were reliable [33; 34]. Most of the parameters had smaller values using cokriging than those using ordinary kriging, which suggests that the accuracy of the cokriging technique is higher than that of the ordinary kriging technique. This may be due to the fact that DOC and DTN have similar variability structures, and this may help to enhance the prediction accuracy when one variable is set as an auxiliary variable. An investigation on the spatial variability of soil carbon stocks in the Urucu river basin, Central Amazon (Brazil) also reported a better performance using cokriging interpolation for mapping SOC stocks when the compound topographic index (CTL, which is inversely correlated with SOC stock) was incorporated as an auxiliary variable [42].