Communication présentée au 24th DAAAM International Symposium on Intelligent Manufacturing and Automation, 23-26 October 2013, Zadar, Croatia.Soil organic carbon (SOC) is of big importance in the global carbon cycle. Distribution patterns of SOC in various regions of Tunisia constitute a baseline for studies on soil carbon changes. This paper presents Tunisian SOC stock calculated using soil profile descriptions defined by FAO/UNESCO classification, and the digital soil map 1:500 000. A soil database has been compiled, containing data from 5024 horizons and 1483 profiles. SOC stocks have been calculated for each profile by a classical method for a given depth, it consists of summing SOC stocks by layer determined as a product of bulk density (Db), organic carbon (OC) content, and layer thickness. Db values were calculated from pedotransfer functions when we have missing values. SOC stocks by profiles were calculated and linked by soil type to polygons of a digital soil map of Tunisia. In total, Tunisian SOC stocks are 1.006 Pg C in the 0 to 100 cm soil depth, and 0.405 Pg C in the upper layer 0-30 cm. The surface horizon (0 – 30 cm) stored 40% of the soil organic carbon stock. OC stocks were higher in Luvisols 71.6 and 159.2 t/ha in 0 – 30 and 0-100 cm soil depth, respectively. In Podzoluvisols there are 6.19 and 138.8 t/ha, but amounts are lower in Lithosols at 18.4 and 40.4 t/ha

The stock assessment of organic carbon and total nitrogen in the soil in addition to their relationships with site characteristics is of major importance whether at local, regional or global scale. The improvement of pedotransfer functions for these stocks evaluation in soils is a key for sustainability of agro-systems, especially in erodible systems of Mediterranean semi-arid areas. This work aimed to study relationships between total nitrogen stocks and other physico-chemical properties of clayey and sandy soils of Tunisian database and to do this, we used pedotransfer functions and structural equations modeling. For modeling total nitrogen stocks, two Tunisian soil databases composed from 450 horizons of clayey soils and 602 horizons of sandy soils were used. The optimal models of nitrogen stocks were given by two significant pedotransfer functions: (i) that of clayey soils with a standard error of prediction of 18.51 and associated p-value of 0.000 and (ii) that of sandy soils with a standard error of prediction of 5.76 and associated p-value of 0.016. Then, we perform a path analysis using structural equations modeling and Bayesian analysis to investigate simultaneously the interactions between the different components of the soil properties and their relationships with total nitrogen stocks. Results show that, in both soil types, the stock of total nitrogen is always controlled in the same way; it is significantly linked to chemical properties and bulk density more than by physical properties. The root mean square errors of the approximations were 0.080 and 0.043 for the clayey and sandy models, respectively.

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