A Threshold of Substrate Addition Rate Predicts the Direction of Soil Organic Matter Priming in Different Ecosystems

Monday, 15 December 2014
Xiao-Jun Allen Liu1,2, Jinran Sun2, Rebecca L Mau2, Brianna K. Finley1,2, Zacchaeus G Compson2, Paul Dijkstra1,2, Egbert Schwartz1,2 and Bruce A Hungate1,2, (1)Northern Arizona University, Department of Biological Sciences, Flagstaff, AZ, United States, (2)Northern Arizona University, Center for Ecosystem Science and Society, Flagstaff, AZ, United States
Addition of easily available C substrates to soil can increase or decrease decomposition rates of native soil organic matter, releasing more or less CO­2 − a phenomenon known as the priming effect. However, the relationship between the amount of substrate addition and direction of priming remains unclear. In order to disentangle this relationship, an experiment was designed to analyze the effect of amounts of substrate additions on soil priming. We added substrates at concentrations corresponding to 3% to 410% of microbial biomass C pool in soils from five distinctive ecosystems along an elevation gradient. We found that 1) Each ecosystem had a different trigger value of substrate addition controlling the direction of priming. 2) Across ecosystems, however, a threshold value of substrate addition at 50% of microbial biomass C (150 μg C g-1 week-1) governed the direction of priming (negative or positive). 3) Priming was negative at low substrate addition rates, and increased linearly with the rate of substrate addition and became positive when the rate was greater than 50% of the microbial biomass carbon pool, and increasing thereafter. 4) The absolute amount of added substrate-C was a better predictor for priming compared to the amount added as a percentage of the microbial biomass carbon pool (r2 = 0.72 vs. r2 = 0.52). Our results demonstrate that the relationship between substrate addition and priming of soil organic matter was positive and linear. This relationship supports for exploring mechanisms of microbial communities shifts between r and K strategies, and stresses the significance of incorporating priming and amounts of substrate inputs as parameters to build more accurate ecosystem C models.