Abstract
To cope with the challenges in forest management that are contemporarily caused by climate change, data on current chemical and physical soil properties are more and more necessary. For this purpose, we present a further amalgam of depth functions and SCORPAN modelling to provide data at arbitrary depth layers. In this concept, regionalisation is split up into the modelling of plot totals and the estimation of vertical distributions. The intended benefits by splitting up are: consistency between estimates on plot level and depth layer level, avoidance of artificial depth gradients, straightforward interpretation of covariates in the sense of pedogenetic processes, and circumnavigation of the propagation of uncertainties associated with separation between horizons during field sampling. The methodology was tailored to the circumstances within the north-eastern lowlands and the utilisation of current inventory data of the National Forest Soil Inventory (NFSI) in Brandenburg (Germany). Using the regionalisation of soil organic carbon (SOC) as an example, the application is demonstrated and discussed in detail. The depth to groundwater table and terrain parameters related to the catchment area were the main factors in SOC storage. The use of kriging did not improve the model performance. The relative depth gradients of SOC were especially distinguished by tree species composition and stand age. We suppose that interesting fields of application may be found in scenario-based modelling of SOC and when SOC serves as a basis for hydrological modelling.
Highlights
Nowadays, regional data on forest soil properties are increasingly demanded for various questions concerning forest management practices, like tree species selection, liming, harvest intensity, or the detection of risk areas
Erosion within the catchments causes a corresponding deposition at the sites, while at high erosive potential (SPI ), the Soil organic carbon (SOC) is lowered by topsoil losses or loss of surface inputs
We suppose that our amalgam of soil depth functions and digital soil mapping can be a handy methodology whenever coherent depth gradients are of special importance for the subsequent analyses
Summary
Regional data on forest soil properties are increasingly demanded for various questions concerning forest management practices, like tree species selection, liming, harvest intensity, or the detection of risk areas. Soil organic carbon (SOC) profoundly influences a soil’s cation exchange capacity [1,2,3], which is a key feature for nutrient supply to trees. In the case of the mainly sandy textured soils of the northeastern lowlands, soil organic carbon strongly influences the spatial patterns of hydraulic properties [10]. In addition to these well-understood principles, which are widely used in modelling water and element budgets, SOC affects the wettability of soils [11,12]
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