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Soil organic matter (SOM) content and composition may be affected by geographic region, land use (grassland vs. forest) and management intensity (intensive vs. extensive). To asses these effects SOM of 300 German soils was characterized using soil color analyses (L*,a*,b*-values) and Fourier transform infrared (FTIR) spectroscopy. Soil lightness (L*-value) was strongly negatively correlated with the soil organic carbon content and this relationship was stronger when the previously sieved soils were ground. Using the band at wavenumber 1634 cm − 1 (as determined by FTIR) as a proxy for aromaticity of SOM the L*-value was negatively correlated with aromaticity. Geographic region as well as land use affected L*-, a*- and b*-values. FTIR results suggested that particularly amides and polysaccharides were affected by geographic region, while mainly polysaccharides were affected by land use. We conclude that soil color analysis can provide additional information on environmental circumstances/site effects which may affect SOM composition. A few only weak correlations of soil color/SOM composition parameters with management intensity indicate that either changes in SOM parameters were too small or that the applied management indices were not sensitive enough to management effects.

Soil organic carbon (OC) stocks are highly variable in space. This study aimed at analysing regional soil OC stock variability with direct measurements of OC stocks at 89 sampling points distributed across a forested area (160 km − 2 ) of the Hainich region in Thuringia/Germany. We sampled complete soil profiles by horizons and depth increments. The major goal of this study was the analysis of regional OC stocks. Soils of our study area were classified as Cambisols, Luvisols and Stagnosols. The averaged total OC stocks of the solum ranged from 7.4 kg m − 2 in Luvisols to 10.3 kg m − 2 in Cambisols, but the analysis of variance revealed no significant differences among the soil groups. In contrast, significant differences in A and B horizon OC stocks of soil groups could be detected. This was not the case, when depth increments instead of soil horizons were studied. Our results implied that sampling by depth increments is favourable for the detection of regional OC stocks and that sampling by soil horizons should be used for the study of pedogenic processes which control OC stocks in soil. Differences in OC stocks among soil groups are more pronounced if horizons are considered, which shows that mixing of soil horizons by fixed depth increments destroy important pedogenetical information. A stepwise multiple regression exposed horizon thickness as the most important factor affecting OC stocks in soil horizons. This has major implications for detection of changes in carbon stock, since the variability of regional OC stocks is less controlled by OC concentration and bulk density rather than by soil horizon thickness. To detect differences smaller than 10% of regional OC stocks one would need more than 300 A horizon samples. If 0–10 cm increments were sampled, less than 100 samples would be sufficient to detect the same difference.

Soil organic carbon (OC) stocks are highly variable at the forest stand level. In order to analyse spatial variability at the stand scale, a study was conducted on a Luvisol developed from loess in Thuringia, Germany. At a 10,000 m 2 beech ( Fagus sylvatica L.) forest site, soil samples were taken at 54 points from the litter layer and the complete solum whose thickness varied between 0.24 m and 0.96 m. With a sampling scheme that incorporated a minimum horizontal sampling distance of 0.2 m, OC stocks in the litter layer and the solum were characterised by ordinary statistics and geostatistics. With respect to the vertical distribution of OC stocks, results showed that the OC stocks were 0.4 kg OC m − 2 in the litter layer, 3.0 kg OC m − 2 in the solum 0–0.12 m depth, and 4.5 kg OC m − 2 in the solum > 0.12 m depth. This highlighted the importance of subsoils in terrestrial carbon balances. No spatial pattern was observed in the litter layer, whereas semivariograms of OC stocks in the solum 0–0.12 m depth and the solum > 0.12 m depth exhibited a range of less than 5.4 m. The nugget variance accounted for around 20% of the sill in the solum 0–0.12 m depth and for over 40% of the sill in the solum > 0.12 m depth. These results emphasised the high small scale variability at the stand scale. Ordinary and spatial correlation indicated that the OC stocks are strongly affected by the thickness of the solum, whereas a relation between the distance to the nearest tree and the magnitude of OC stocks was not found. Considering the variability of the study area, the minimum detectable difference (MDD) of OC stocks for n = 9 was 0.3 kg OC m − 2 in the litter layer, 2.0 kg OC m − 2 in the solum 0–0.12 m depth, and 3.6 kg OC m − 2 in the solum > 0.12 m depth. At this site more than 300 samples would be required to detect a relative OC stock change of 10% in the solum.