Using geostatistics for modelling and mapping soil organic matter in forest soils: an application in southern Italy

Sustainable use of forest and soil resources is one of the ways to manage climate change and mitigate global warming. The release and conversion into carbon dioxide or methane of even small proportion of soil organic matter (SOM) can determine relevant quantitative variations in their atmospheric concentrations. Management policies of the forest ecosystems require a deeper understanding of the spatial distribution of SOM and it is crucial quantifying and understanding the spatial variation of SOM in forests. Geostatistics provides the tools to quantify the spatial variability of SOM taking into account data spatial autocorrelation and to produce continuous maps from sparse data. The main objective of the study was to quantify and map the spatial distribution of SOM in forest soils in southern Italy. The study area is a forest beech (332,000 m2) located in the Biogenetic Natural Reserve Marchesale (southern Italy) (Fig. 1a). It has a mean elevation of about 1180 m a.s.l. and soils are coarse-textured, relatively young (Entisol and Inceptisol). They are strongly dependent on the nature of the parent rock (Paleozoic granitoid rocks) and their depths range from shallow to moderately deep whereas soil profiles are characterized by A-Bw-Cr and/or A-Cr horizons. Generally, the upper A horizon has a high accumulation of organic matter (umbric epipedon) and a very dark brown colour. Surface soil samples were collected at 231 locations within the study area using a metallic core cylinder with a diameter of 7.5 cm and a height of 20 cm. Organic carbon content was measured using a TOC-L analyzer (Shimadzu Corporation, Kyoto, Japan) and converted to SOM using a factor of 2. A variogram was modelled to capture the main spatial features of SOM and used with ordinary kriging to estimate SOM values at the nodes of a 1 m x 1 m interpolation grid. SOM values varied from 2.9% to 28.2%, with a mean value of 11.4%, whereas the distribution did not depart significantly from normality. A bounded isotropic nested variograms model was fitted to experimental variogram including a nugget effect and two spherical model a short (52 m) and long (418 m) ranges. The spatial distribution of SOM is showed in Fig. 1b. The study provided a detailed knowledge about the spatial pattern of SOM in the forest topsoils in a representative site within the Biogenetic Natural Reserve Marchesale (southern Italy).