The SOMDY model presents some innovative features in comparison to other existing published models of decomposition processes of either litter or soil organic matter. In particular, this model is new in its capability to represent the interactions between the chemical nature of organic matter and its physical structure as mineral/ organic complexes in the soil. The concepts implemented in SOMDY allow capturing several complex phenomena that may play a major role in controlling
Addition of fresh labile organic
cu cr labile component resistant component
Fig. 11.6 Exercise of theoretical simulation to show the occurrence of priming and protection effects, and related CO2 release, after addition to soil of organic matter with different chemical composition soil organic matter dynamics. For instance, it is possible to assess the consequence of organic amendments on carbon sequestration and mineralization processes, as induced by different chemical compositions of organic additions.
Figure 11.6 shows a qualitative example of such emerging complex interactions. Addition of fresh labile organic materials induces a flush of decomposition process with a sudden rise of CO2 emissions, due to an increased microbial mineralization of the added substrate. Interestingly, also the emissions from resistant components of SOM show a smooth increase due to the well-known "priming" effect (Kuzyako 2002) caused by a greater microbial activity (Fig. 11.6, left-hand side). Furthermore, the addition of a well-humified and/or stabilized EOM such as mature compost induces a relatively slight mineralization increase of the added EOM, but also increases the protection on labile compounds, whose emissions are consequently reduced (Fig. 11.6, right-hand side).
There results demonstrate that our model may well be applied to predict different scenarios of agricultural management, having the capability and suitability to assess their short- and medium-term impacts on SOM and carbon sequestration balance.
Future work will be addressed to improve the model parameterization to fit different environmental conditions and application to long-term predictions aimed to provide an improved environmental sustainability of agricultural managements.
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