Lin Chao, Yanyan Liu, Grégoire T. Freschet, Weidong Zhang, Xin Yu,Wenhui Zheng, Xin Guan, Qingpeng Yang, Longchi Chen, Feike A. Dijkstra, Silong Wang

Gas samples. Photo credit: Lin Chao
Gas samples. Photo credit: Lin Chao

Soils contain the largest carbon (C) stock of terrestrial ecosystems. Therefore, even a small change in soil organic carbon (SOC) would have major effects on atmospheric CO2 concentration at a global scale. The size of SOC stocks is largely determined by the balance between C inputs from plant litter and C outputs from SOC decomposition. To date, we know that new plant leaf litter inputs to soil can stimulate the decomposition rate of older SOC, a phenomenon known as the “priming effect” (PE). However, it remains largely unknown whether different types of plant litter, for instance litters with different chemical composition, would have variable effects on the strength of this PE.
To investigate this question, we collected freshly senesced leaf litter from 15 tree species differing in chemical composition and set them to decompose in an agricultural soil that strongly differed from the litter material in terms of its C isotopic signature (proportion of 13C). During the decomposition process, we differentiated the CO2 effluxes originating from the litter from those originating from the soil by regularly measuring the C isotopic signature of the emitted CO2 over time.
We demonstrated thereby that, depending on their chemical composition, leaf litters added to the soil could either stimulate or inhibit the decomposition of older SOC, that is, the PE. In the early stage of litter decomposition, the presence of high amounts of C leachates and hemicellulose and low amount of tannins in the added litter stimulated the PE. In the later stage of litter decomposition, the PE was mostly stimulated by litter with high potassium, calcium and magnesium concentrations and inhibited by high lignin and lignin:N ratios. These results open new perspectives for improving our abilities to model soil C dynamics and predict the global C cycle.

Read the paper here.

 

 

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