We determined four types of variables, including substrate quality, SOM association with minerals, SOM protection by aggregates, and microbial communities, to explore potential mechanisms responsible for the Q10 difference between the two soil depths. Specifically, to determine substrate quality, SOM composition was investigated by solid-state 13C CPMAS NMR. Having been treated with 10% hydrofluoric acid (HF) repeatedly (53), soil samples were rinsed with deionized water and then freeze-dried. Approximately 100 mg of HF-treated samples was measured on an AVANCE III 400 WB spectrometer (Bruker BioSpin, Rheinstetten, Baden-Württemberg, Germany) at 100.62 MHz. The spectrometer was equipped with a 4-mm CPMAS probe, and the parameters were set with a spinning rate of 8 kHz, a contact time of 2 ms, and a recycle delay of 6 s. We then used MestReNova 9.0 (Mestrelab Research S.L., Santiago de Compostela, Galicia, Spain) to integrate the spectra into the following chemical shift regions and acquire the relative intensity of each region: alkyl C [0 to 50 parts per million (ppm)], O-alkyl C (50 to 110 ppm), aromatic C (110 to 165 ppm), and carboxylic C (165 to 220 ppm) (54).

To quantify SOM protection by minerals, Fe-bound SOC, which directly reflects the proportion of SOC associated with reactive Fe, was determined on the basis of the citrate-bicarbonate-dithionite (CBD) method (55). Briefly, in the reduction treatment, a solution containing trisodium citrate and sodium bicarbonate was added to 0.25 g of soil and heated to 80°C by water bath. A reducing agent, sodium dithionite, was then added, and the mixture was held at 80°C for 15 min. Instead of CBD extraction, soil samples in the control treatment were extracted with sodium chloride (NaCl) at an equivalent ionic strength. After rinsing the soil residues three times with 1 M NaCl, SOC content of the residues in each treatment was measured. Fe-bound SOC was then calculated as followsFebound SOC(%)=SOCNaClSOCCBDSOC×100(8)where SOCNaCl and SOCCBD refer to the SOC content (g kg−1) of the control treatment and reduction treatment, respectively.

To determine SOM protection by aggregates, we isolated three SOM fractions to measure C distributions in each fraction. Specifically, using the wet-sieving technique (56), 30 g of air-dried soil (<2 mm) was submerged in water for 5 min and then wet-sieved over 250 and 53 μm of sieves, consecutively. The fraction collected on the 250-μm sieve was macroaggregates (250 to 2000 μm), and that collected on the 53-μm sieve was microaggregates (53 to 250 μm). The fraction in the remaining suspension was silt + clay (<53 μm). Each fraction was then dried at 60°C. After isolating sand in macroaggregates and microaggregates with sodium hexametaphosphate, SOC concentrations of the three fractions were measured. Of the three fractions, the proportions of SOC distributed in macroaggregates and microaggregates were used to quantify SOM protection by aggregates (27).

We adopted the PLFA approach to assess soil microbial abundance and community composition. PLFAs were extracted according to the protocol described by Bossio and Scow (57). With 19:0 (methyl nonadecanoate, C20H40O2) as the internal standard, samples were then analyzed with a gas chromatograph (Agilent 6850, Agilent Technologies, Santa Clara, CA, USA). The identification of the extracted fatty acid was based on a MIDI peak identification system (Microbial ID Inc., Newark, DE, USA). PLFAs specific to fungi (18:2ω6, 9c) and bacteria (i14:0, i15:0, a15:0, i16:0, a17:0, i17:0, 16:1ω7c, cy-17:0, 18:1ω7, cy19:0) were quantified (17). The composition of the microbial community was represented by the relative abundance of fungal PLFAs and F/B ratio.

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