Soil organic carbon in peninsular Spain: Influence of environmental factors and spatial distribution

Soil organic carbon (SOC) stocks and their geographical distribution in peninsular Spain were estimated from a georeferenced database consisting of 12,724 surface samples (0–30 cm) and 3607 subsurface samples (30–50 cm), covering different climate, land use, elevation, parent material, soil type and soil pH. SOC density showed a high heterogeneity, with the lowest values in arid regions, where the average in topsoil ranged between 20 and 60 t C ha−1, under woody crops and forest respectively. Carbon stocks gradually increases as precipitation increases, and its variability is also dependent of other factors, fundamentally the presence/absence of active lime or active Al. In semi-arid zones, calcaric soils (pH ≈ 8.3) have higher contents of SOC than neutral to weakly acidic soils from siliceous materials. However, in humid regions, calcareous materials have undergo total or partial decarbonatation in the upper layer (pH < 4.0–7.5) and SOC stocks are markedly lower than in other materials. In forest soils it seems that a steady state (around 100–120 t C ha−1) (0–30 cm) has been reached in a wide range of precipitation, between 900 and 1700 mm; most of this carbon (about 80%) is labile-C. Soils from granitic rocks are acidic (pH 4.5–5.5) (Al buffering) and the mean SOC stock in the indicated precipitation range is between 170 and 200 t ha−1 (it is estimated that approximately 60% is stabilized as metal-C or mineral-C complexes). The highest values (190–240 t ha−1) are recorded in acidic soils derived from mafic rocks, which in these regions usually develop andic properties (around 73% is involved in stable metal-C or mineral C complexes). Finally, the SOC stored in neutral soils from serpentinized ultramafic rocks (without excess Ca or Al) is similar to that of the decarbonated soils derived from calcareous materials. In all regions, forest soils are a much more important SOC sink than live forest biomass (2–4 times higher in the upper 30 cm and 3–6 times greater in the upper 50 cm). Random Forest regression was used as modeling tool and digital mapping. Mean annual precipitation was estimated to be the most important predictor variable, followed by land use, lithology/soil type and soil pH. Model performance was calibrated by the internal RF validation and through cross-validation, and the results were similar. In topsoil, the mean error, root mean square error and R2 were −0.007% C, 1.48% C and 0.61, respectively. In the subsurface layer these indices were −0.020, 1.07 and 0.37, respectively. SOC stock for peninsular Spain was estimated at 3.33 Pg in the upper (0–30 cm) layer, and 0.85 Pg in the subsurface (30–50 cm) layer. Total SOC stock for 0–50 cm was 4.19 Pg, with a 95% confidence interval ranging between 3.33 and 5.03 PgThis work was supported by the Ministry of Science and Innovation, Spain (CGL2009, 13857: 2010-2014); and the Consellería de Educación-Xunta de Galicia, Spain (2014-GRC GI-124, 2014-2017)S