  The biogeochemical complexity of environmental models is increasing
continuously and model reliability must be reanalysed when new implementations
are brought about. This work aim to identify influential biogeochemical
parameters that control the Soil Organic Matter (SOM) dynamics and greenhouse
gas emissions in different ecosystems and climates predicted by a
physically-based mechanistic model. This explicitly accounts for four pools of
organic polymers, seven pools of organic monomers, five microbial functional
groups, and inorganic N and C species. We first benchmarked our model against
vertical SOM profiles measured in a temperate forest in North-Eastern Bavaria,
Germany (Staudt and Foken, 2007). Next, we conducted a sensitivity analysis to
biogeochemical parameters using modified Morris indices for target SOM pools
and gas emissions from a tropical, a temperate, and a semi-arid grassland in
Australia. We found that greenhouse gas emissions, the SOM stock, and the
fungi-to-bacteria ratio in the top soil were more sensitive to the mortality of
aerobic bacteria than other biogeochemical parameters. The larger CO2 emission
rates in forests than in grasslands were explained by a greater dissolved SOM
content. Finally, we found that the soil N availability was largely controlled
by vegetation inputs in forests and by atmospheric fixation in grasslands
