The models also provide valuable pedological insights into the factors controlling SOC levels under natural conditions.
![daymap ccc daymap ccc](http://www.ccc.sa.edu.au/uploads/7/4/5/0/74507007/sports-day-2018-009.jpg)
![daymap ccc daymap ccc](http://www.ccc.sa.edu.au/uploads/7/4/5/0/74507007/sample-yearbook-3-14.jpg)
The extent of SOC decline in both absolute and relative terms was found to be highly dependent on the climate, parent material and land use regime, reaching a maximum decline of 44.3 t/ha or 50.0% relative loss in cooler (moist) conditions over mafic parent materials under regular cropping use. Total pre-clearing SOC stocks amount to 4.21 Gt in the top 30 cm, which compared with a current stock estimate of 3.68 Gt, suggesting a total SOC loss of -0.53 Gt over the entire state. Independent validation of the SOC mass predictions over the top 30 cm revealed a concordance correlation coefficient of 0.76, which was 13% higher than the currently used map. The digital soil maps of preclearing SOC (% and mass) over New South Wales provide a more sophisticated alternative to currently available, equivalent maps. It used 1690 soil profiles from undisturbed or only lightly disturbed native vegetation sites across all of eastern Australia, together with a range of covariates representing key soil-forming factors.
![daymap ccc daymap ccc](http://www.ccc.sa.edu.au/uploads/7/4/5/0/74507007/sample-yearbook-3-29_orig.jpg)
The modelling approach adopted included multiple linear regression and Cubist piecewise linear decision trees. These provide a useful first estimate of natural, unaltered soil conditions before agricultural development, which are potentially important for many carbon-accounting schemes such as those prescribed by the Intergovernmental Panel on Climate Change, carbon-turnover models such as RothC, and soil-condition monitoring programs. Abstract : Digital soil models and maps have been developed for pre-European (pre-clearing) levels of soil organic carbon (SOC) over New South Wales, Australia.