Spatial 3D mapping of forest soil carbon stocks in Hesse, Germany

Abstract

AbstractBackgroundForest soils are an important reservoir of organic carbon (OC) and a potential source or sink for atmospheric CO2. Prediction of OC stock changes under ongoing climatic and management changes requires a spatial explicit base. Knowledge of the vertical distribution of OC stocks is very important, since varying soil layers may be affected differently by environmental change.AimThree‐dimensional regionalization of OC stocks of the forest floor (FFC) and 5 cm depth increments of the mineral soil (SOC) of Hesse, Germany.MethodsDatasets of the second National Forest Soil Inventory (NFSI II) were used for parametrization of hierarchical generalized additive models (hGAM). Validation was performed by a 10 times repeated 10‐fold cross‐validation, and spatial model uncertainty was assessed.ResultsDepth‐dependent validation indicated that model performance was best between 15 and 60 cm (amount of variance explained ≈ 0.5). All covariates showed plausible partial effects. FFC stocks were predicted to be highest under coniferous forest with a high influence of N deposition. Climate and potential cation exchange capacity affected SOC stocks markedly, whereas soil class and parent material were most important for the depth distribution. Overall, average predicted OC stocks were between 78.0 and 92.5 t ha−1, amounting to 67.6 to 80.1 Mt for all forest soils of Hesse. Between 16% and 24% were stored in the forest floor. Sixty‐eight percent to 69% of predicted SOC stocks were stored in the upper 30 cm. Model uncertainty was highest at locations with high elevation or ground water influence.ConclusionsThis work provides the first spatial explicit database for OC stocks of forest soils in Hesse at an intermediate scale. Stocks can be assessed flexibly for varying depth from the forest floor down to 100 cm. Uncertainty analysis informs about locations, where the model results have to be handled with care.