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Recent field studies show that the carbon fertilization effect at ecosystem level can be strongly limited by nutrient availability. Lacking process understanding about the geographic distribution of nutrient availability leads to major uncertainties in future projections of the terrestrial carbon sink. Especially in mature forests, a significant amount of carbon is transferred to the soil, influencing microbial activity and accelerating nutrient cycling.
Root exudation is a key process that links vegetation and soil processes and thereby influences microbial-mediated nutrient mineralization and soil carbon turnover. Root exudation rates have been shown to increase under eCO2, likely increase soil carbon turnover and thus reduce soil carbon accumulation and have been hypothesized to contribute to alleviate plant nutrient limitation. However, most terrestrial biosphere models do not adequately account for these effects.
Using a terrestrial biosphere model (QUINCY-JSM) that comprises a representation of the coupled carbon-nitrogen-phosphorus cycles in terrestrial ecosystems, including explicit microbial dynamics and mineral stabilization of soil organic matter, we simulate the effect of elevated CO2 on plant exudation and its consequences for ecosystem carbon and nutrient dynamics in mature forests. We explicitly account for changes in root exudation due to carbon surplus and nutrient demand, as well as changes in microbial activity due to additional inputs of easily degradable carbon. We evaluate our model with observations obtained in the data from the EucFACE experiment in a temperate, mature, phosphorus-limited forest ecosystem and find that the model reproduces both carbon and nutrient cycle in ambient conditions, as well as the response to elevated CO2 within the measurements uncertainty. The model suggests that a 20% increase in root exudation explains the observed change in nutrient availability and increased soil respiration under elevated CO2.
These results suggest that representing root exudation is important to improve the accuracy of simulated forest carbon fluxes under increasing atmospheric CO2.
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