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The biogeochemical complexity of environmental models is increasingcontinuously and model reliability must be reanalysed when new implementationsare brought about. This work aim to identify influential biogeochemicalparameters that control the Soil Organic Matter (SOM) dynamics and greenhousegas emissions in different ecosystems and climates predicted by aphysically-based mechanistic model. This explicitly accounts for four pools oforganic polymers, seven pools of organic monomers, five microbial functionalgroups, and inorganic N and C species. We first benchmarked our model againstvertical SOM profiles measured in a temperate forest in North-Eastern Bavaria,Germany (Staudt and Foken, 2007). Next, we conducted a sensitivity analysis tobiogeochemical parameters using modified Morris indices for target SOM poolsand gas emissions from a tropical, a temperate, and a semi-arid grassland inAustralia. We found that greenhouse gas emissions, the SOM stock, and thefungi-to-bacteria ratio in the top soil were more sensitive to the mortality ofaerobic bacteria than other biogeochemical parameters. The larger CO2 emissionrates in forests than in grasslands were explained by a greater dissolved SOMcontent. Finally, we found that the soil N availability was largely controlledby vegetation inputs in forests and by atmospheric fixation in grasslands

stochastic environmental research and risk assessment

Similarities and differences in the sensitivity of Soil Organic Matter  (SOM) dynamics to biogeochemical parameters for different vegetation inputs  and climates