This ZHU_2022__DATA_README.txt file was generated on 2022-06-21 by Xiaomin Zhu GENERAL INFORMATION 1. Title of Dataset: Data from: More soil organic carbon is sequestered through the mycelium-pathway than through the root-pathway under nitrogen enrichment in an alpine forest 2. Author Information: First author 1 Name: Dr Xiaomin Zhu Institution: Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China Email: zhuxm@cib.ac.cn Joint first author 2 Name: Dr Ziliang Zhang Institution: University of Illinois at Urbana-Champaign, Urbana, IL, USA Co-author 3 Name: Dr Qitong Wang Institution: Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China Co-author 4 Name: Prof Josep Pe?uelas Institution: Global Ecology Unit CREAF-CEAB-UAB, Cerdanyola del Valles, 08193 Catalonia, Spain Co-author 5 Name: Dr Jordi Sardans Institution: Global Ecology Unit CREAF-CEAB-UAB, Cerdanyola del Valles, 08193 Catalonia, Spain Co-author 6 Name: Prof Hans Lambers Institution: St John of God Subiaco Hospital, Perth Western Australia Co-author 7 Name: Ms Na Li Institution: Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China Co-author 8 Name: Prof Qing Liu Institution: Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China Co-author 9 Name: Prof Zhanfeng Liu Institution: South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China Corresponding author Name: Prof Huajun Yin Institution: Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China Email: yinhj@cib.ac.cn 3. Date of data collection: 2019-2020 4. Geographic location of data collection: MAO County, Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province, China 5. Funding sources that supported the collection of the data: The National Natural Science Foundation of China (32171757, 31901131, 42177289). The Chinese Academy of Sciences (CAS) Interdisciplinary Innovation Team (No. xbzg-zysys-202112). The Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (2019QZKK0301). The European Research Council Synergy project SyG-2013-610028 IMBALANCE-P and the Spanish Government grants PID2019-110521GB-I00 and PID2020-115770RB-I00. 6. Recommended citation for this dataset: Zhu et al. (2022), Data from: More soil organic carbon is sequestered through the mycelium-pathway than through the root-pathway under nitrogen enrichment in an alpine forest, Dryad, Dataset. https://doi.org/10.5061/dryad.jwstqjqc0 DATA & FILE OVERVIEW 1. Description of dataset These data were generated to investigate how N addition affect SOC accural and chemical composition through the root-pathway and mycelium-pathway in an alpine coniferous forest. Samples of plant and soil were collected from each treatment plots (non-N addition and N-addition) in 2019 and 2020. Therefore, each parameter has 6 replicates (n = 3 replicates for each treatment * 2 sampling date =6)，except for the plant-derived C in different soil size fractions (only measured the samples collected in 2019). 2. File List: File 1 Name: F1_ZHU_2022_SOC.xlsx File 1 Description: The concentration of SOC (mg g-1) in different ingrowth cores under the control and N addition treatments. Values are mean ± SE, N = 3. File 2 Name: F2_ZHU_2022_PLRC.xlsx File 2 Description: The concentrations of plant residual C (mg g-1 dry soil) in soils of different ingrowth cores. Long-chain fatty acid (Waxes): n-alkanes (> C24), n-alkanoic acid (> C22), n-alkanols (> C22); ΣCutin = C14–C18 hydroxy-alkanoic acids, C16-di-hyroxyalkanoic acid, ω-hydroxy-alkanoic acid (C16–C18) and ω-hydroxy-epoxy alkanoic acid (C16–C18); ΣSuberin = α,ω-dicarboxylic acids (C16–C24; saturated and substituted) and ω-hydroxy-alkanoic acids (C20–C30; saturated and substituted); Vanillys: vanillin, acetovanillone and vanillic acid; Syringls: syringaldehyde, acetosyringone, and syringic acid; Cinnamyls: p-coμmaric acid and ferulic acid (Otto et al., 2005; Tamura and Tharayil, 2014). Values are mean ± SE, N = 3. File 3 Name: F3_ZHU_2022_MRC.xlsx File 3 Description: The effect of N addition on microbial residual C (mg g-1) in different ingrowth cores. Values are mean ± SE, N = 3. File 4 Name: F4_ZHU_2022_SOC_Aggregates.xlsx File 4 Description: The effect of N addition on the SOC concentration (mg g-1) in different soil size fractions (Macroaggregates: 2000μm~250μm, Microaggregates: 250μm~53μm, < 53μm) in different ingrowth cores. Values are mean ± SE, N = 3. File 5 Name: F5_ZHU_2022_SOC Comp_Aggregates.xlsx File 5 Description: The chemical composition (mg g-1) of SOC in different soil size fractions in different ingrowth cores under the control and N addition treatments. Plant-derived C in different soil size fractions in ingrowth cores were determined using the samples collected in 2019, while the microbial necromass C in different soil size fractions in ingrowth cores were determined using the samples collected in 2019 and 2020. Values are mean ± SE, N = 3. File 6 Name: F6_ZHU_2022_RB_MB.xlsx File 6 Description: The effect of N addition on root/myceliμm biomass (g m-2). Values are mean ± SE, N = 3. File 7 Name: F7_ZHU_2022_PLFAs.xlsx File 7 Description: The effect of N addition on microbial PLFAs (G+, gram positive bacteria. G-, gram negative bacteria. AC, actinomycetes. Fun, fungi, nmol g-1). Values are mean ± SE, N = 3. File 8 Name: F8_ZHU_2022_Enzy.xlsx File 8 Description: The effect of N addition on extracellular enzymatic activities (BG, β-1,4-glucosidase. NAG, β-1,4-N-acetyl-glucosaminnidase. POX, phenol oxidase. PER, peroxidase, μmol g-1 hr-1). Values are mean ± SE, N = 3. File 9 Name: F9_ZHU_2022_Fe+Al.xlsx File 9 Description: The molar concentrations of Fed + Ald and Feo +Alo (μmol g-1) in each type of ingrowth cores. Values are mean ± SE, N = 3. METHODOLOGICAL INFORMATION 1. Study site The study site is located in the Maoxian Ecological Station of the Chinese Academic of Science, Sichuan Province, China (31°41′N, 103°53′E), where the mean annual temperature, precipitation and evaporation are 8.9℃, 920mm, and 796 mm, respectively (Yin et al., 2013). Considering the estimated value of local background N deposition rate is approximately 25 kg N ha-1 yr-1 (ranging from 10-38 kg N ha-1 yr-1) (Zhu et al., 2014), by referring to previous N-addition experiments in similar scale across the world (Jefts et al., 2004; Boot et al., 2016, Chen et al., 2017), we set the N addition level to 25 kg N ha-1 yr-1 to explore the mycorrhiza-mediated SOC dynamics and the underlying mechanisms in alpine coniferous forests under the context of increasing N deposition. In April 2017, a healthy 50-years old spruce plantation (2000 m a.s.l.) was chosen to conduct the N-addition experiment. Briefly, three replicated blocks of two N treatments (i.e., the non-N addition treatment and the N addition treatment with 25 kg N ha-1 year-1) were randomly located in a spruce monocultural plantation. In April, 2017, six 10 m × 10 m plots separated by 10-m wide buffer strips were established. Starting from May 2017, NH4NO3 was applied in equal amounts every month from May to October. Specifically, 118.8 g NH4NO3 (41.6 g N) was dissolved in 30 L water and applied to the soil surface of the N-addition plots using a backpack sprayer in each fertilization campaign. The same amount of water (30 L) without any fertilizer was added to the non-N addition plots at the same time. 2. Isolation of roots and mycelia using ingrowth cores To isolate roots and mycelia, we adopted an ingrowth-core technique modified from Zhang et al. (2018) and Keller et al. (2021). Ingrowth cores (6 cm inner diameter and 15 cm depth) were wrapped with a mesh with different pore sizes: mesh size of 2000 ?m allowed the ingrowth of fine roots and mycelia (both roots and mycelia accessible); 48-?m mesh permitted the growth of mycelia but not of fine roots (only mycelia accessible), and 1-?m mesh excluded the growth of both roots andmycelia (only the soil) (Fig. 2). The C source in the 2-mm mesh cores was mainly derived from roots, mycelia and litter leachates, that of the 48-?m mesh cores was derived from mycelia and litter leachates, while the 1-?m mesh cores received C only from litter leachates. The soil was collected from the mineral layer (0-15cm) at each plot. After removing the visible roots, the soil from the same plot was homogenized and sieved through a 5-mm mesh. The sieved soil was filled into ingrowth cores corresponding to the soil bulk density at 0-15 cm depth (0.796 g cm-3, approximately 337 g per core). Six sets of ingrowth cores with different mesh-size (1-?m, 48-?m and 2 mm) were installed in each treatment plot. In total, 108 ingrowth cores (2 N levels × 3 replicates × 6 sets × 3 mesh-sizes) were installed in this coniferous forest. Ingrowth cores were randomly placed in the topmost mineral horizon (0-15cm depth) in each plot in July 2017. The bottom of the ingrowth cores was covered with the corresponding size of the mesh to prevent inputs of roots and mycelia, respectively, and the top was covered by multiple layers of the corresponding size of the mesh to block the entry of coniferous litter but to allow gas and water exchange. When the cores were retrieved, we did not detect any external litter in the cores. To block the influx of new C derived from the saprophytic mycelia outside the cores, we spread a 2 mm-thick layer of silica sand around the cores. Silica sand as a growth substrate effectively reduces the disturbance of saprophytic hyphae (Hagenbo et al., 2017). Ingrowth cores were harvested in August 2019 and August 2020, respectively. Two sets of ingrowth cores were collected in each plot at each sampling date. Cores were transported to the laboratory within the icebox. After the removal of roots, soils inside the cores were sieved through a 2-mm mesh and divided into two subsamples: one subsample stored in -4 °C was used for the analyses of enzyme activities and microbial community composition; the second subsample was air-dried to perform soil aggregate fractionation, SOC determination, and soil biomarkers analysis. 3. Measurement of root biomass and mycelium biomass Roots inside the 2000-?m mesh cores were manually picked out, washed thoroughly, oven-dried at 60°C for 48 hours and then weighed to determine the total root biomass. The ectomycorrhizal mycelium biomass was estimated using mesh bags (2 cm inner diameter, 15 cm depth; mesh size: 48 ?m) filled with different particle sizes of HCl-washed silica sand (60 g, 0.36-2 mm) (Wallander et al., 2001). The mesh bags were randomly buried into the 0-15 cm soil depth in each plot in July 2017, and recovered at the same time as the ingrowth cores. The concentration of ergosterols was measured to characterize the biomass of ectomycorrhizal mycelia in the mesh bags (Parrent & Vilgalys, 2007). Ergosterols extraction and analysis To quantify the ectomycorrhizal fungal mycelium (ERM) biomass in silica sand samples, the fungal-specific biomarker ergosterol was extracted as described by Nylund & Wallander (1992). Four technical replicates were used for each extraction. A sample of 5 g sand was extracted with 5 ml 10% KOH in methanol. The samples were sonicated for 15 min, extracted overnight and then refluxed at 70 °C for 90 min. After cooling, 1 ml H2O and 2 ml cyclohexane were added. The samples were mixed in a vortex apparatus for 20 s, centrifuged for 5 min at 3000 rpm, and the cyclohexane phase was then transferred to another test-tube. The methanol was extracted with a further 1.5 ml cyclohexane. The cyclohexane was evaporated under N2 and the samples were dissolved in 1 ml of methanol. After ergosterol extraction, samples were filtered through a 0.45-ml Teflon syringe filter (Millex LCR-4; Millipore, Billerica, MA, USA). Samples were analyzed chromatographically using high-performance liquid chromatography (HPLC) with a C18 reverse-phase column (Nova-Pak; 3.9 9 150 mm; Waters, Milford, CT, USA) preceded by a C18 reverse-phase guard column (Nova-Pak; 3.9 9 20 mm; Waters). Methanol was used as the mobile phase with a flow rate of 1 ml min-1, and a UV detector operating at 282 nm measured the absorbance of the eluate. 4. Soil aggregate fractionation and SOC concentration To understand the physico-chemical protection of SOC in the RP and MP under N addition, soils were physically fractionated into three size fractions to examine the allocation of C and biomarkers among macroaggregates (Macro: 250~2000 ?m), microaggregates (Micro: 53~250 ?m) and slit-clay (< 53 ?m) by using the wet-sieving technique (Six et al., 1998). The proportions of SOC and the concentrations of biomarkers in the three fractions were measured to characterize the role of physical protection by aggregates. The SOC and total N (TN) concentrations in bulk soil and size fractions were analyzed using an elemental analyzer (Vario MACRO, Elementar Analysensysteme GmbH, Hanau, Germany). To assess the protection of SOC by minerals, two forms of Fe and Al oxides, oxalate-extractable Fe/Al oxides (Feo + Alo) and dithionite-extractable Fe/Al (Fed + Ald) were measured by using the extraction method proposed by Gentsch et al (2018). The Fed + Ald indicates the amount of pedogenic Fe and Al within oxides, silicates and organic complexes, whereas Feo + Alo represents poorly crystalline oxyhydroxides (Gentsch et al., 2018). The concentrations of Fe and Al oxides in extracts were determined by inductively coupled plasma-optical emission spectrometry (ICP-OES, Optima 8300, Perkin Elmer, USA). 5. SOC chemical composition A range of major biomarkers, which are widely accepted to trace plant-derived and microbial-derived C, respectively, were selected to reveal the changes of the chemical composition of SOC in two pathways under N addition (Barré et al., 2018; Liang et al., 2019). Air-dried soil (1 g) was sequentially extracted (solvent extraction, base hydrolysis, and CuO oxidation) to isolate solvent-extractable free lipids (long-chain fatty acids), cutin- and suberin-derived compounds and lignin-derived phenols (vanillyls, syringyls and cinnamyls), respectively, according to standard protocols (Otto & Simpson, 2007; Tamura & Tharayil, 2014). Since the direct contribution of microbial living biomass to soil amino sugars is negligible, amino sugars are good indicators of microbial necromass (Liang et al., 2017, Joergensen, 2018). Four types of amino sugars, including glucosamine, galactosamine, manosamine, and muramic acid, were tested in this study. By assessing them in soils, we can investigate microbial necromass dynamics at the community-level (i.e., fungi and bacteria) and evaluate the contributions of necromass to SOC storage under different environmental conditions (Joergensen, 2018; Liang et al., 2019). 　　Lipids and lignin monomers Sequential chemical extractions (solvent extraction, base hydrolysis, and CuO oxidation) were conducted to isolate solvent-extractable free lipids, hydrolysable bound lipids, and lignin-derived phenols (Otto and Simpson, 2007; Tamura and Tharayil, 2014; Tamura et al., 2017). A framework illustrating the chemical extractions and SOM chemical compositional information obtained from the analyses is shown in Fig. S1. Briefly, air-dried samples (1 g soil or 100 mg plant material) were sequentially extracted with 5 ml of methanol, dichloromethane: methanol (1:1; v/v), and dichloromethane in glass tubes. The three sequential extracts were combined, and 15 ml of deionized water was added to induce phase separation. The bottom layer of dichloromethane was collected and stored at -20 °C until analysis (Tamura and Tharayil, 2014). The air-dried residue from above solvent extraction was incubated at 95 °C for 3 h with 5 ml of 1 M methanolic sodium hydroxide (NaOH) to extract hydrolysable lipids (Tamura et al., 2017). After cooling to room temperature,the supernatant was transferred to a new glass tube. The residue was extracted with 5 ml of dichloromethane: methanol (1:1; v/v). The two sequential extracts were combined with 62.5 μl of heneicosanoic methyl ester (C21:0) (100 μg/ml in methanol) added as an internal standard. The extracts were acidified to pH < 2 using 12 M HCl. Hydrolysable or bound lipids were recovered by liquid–liquid extraction with 15 ml of deionized water. The bottom layer of dichloromethane was also collected and stored at -20 °C until analysis. Following base hydrolysis extraction, the residue was further subjected to CuO oxidation to isolate lignin-derived phenols: the air-dried residue was mixed with 1 g CuO, 50 mg ammonium iron (II) sulfate hexahydrate [Fe(NH4)2(SO4)2 . 6H2O], and 15 ml of NaOH solution (2 M; sparged with high purity N2) in teflon-lined acid digestion vessels. All vessels were flushed with high purity N2 in the headspace for 5 min and then incubated at 155 °C for 160 min. After cooling, 5 ml of dichloromethane was using to wash the extracts into a new glass tube, and spiked with 100 μl of internal standard (transcinnamic acid and ethylvanillin; 200 μg/ml in methanol), acidified to pH < 2 using 12 M HCl. After centrifugation, 10 ml of pre-cooled ethyl acetate was added to the clear supernatant to induce phase separation. The upper layer of ethyl acetate was collected and stored at -20 °C until analysis. Lignin-derived phenols included vanillyls (V; vanillin, acetovanillone, and vanillic acid), syringyls (S; syringaldehyde, acetosyringone, and syringic acid), and cinnamyls (C; coumaric acid and ferulic acid). Besides the lignin monomer contents, we also calculated the acid/aldehyde ratios of vanillyls [(Ad/Al)v] and syringyls [(Ad/Al)s] to assess lignin degradation, which typically increases with increasing lignin degradation (Otto and Simpson, 2007; Feng et al., 2010). 　　Extracts from the above extractions were converted to trimethylsilyl (TMS) derivatives by 90 μl of N,O-bis-(trimethylsilyl) trifluoroacetamide (BSTFA) with 10 μl pyridine for 3h at 60 °C before GC/MS analysis. The silylated samples were analyzed using an Shimadzu 2030 gas chromatography (GC) coupled to a 2020NX mass detector (Shimadzu). Separation was achieved on a RTS-5-MS fused silica capillary column (30 m × 0.25 mm i.d., 0.25 μm film thickness). GC-MS operating conditions were as follows: temperature held at 65 °C for 2 min, increased from 65 °C to 300 °C at a rate of 6 °C min-1 with final isothermal hold at 300 °C for 20 min. Helium was used as the carrier gas. The sample was injected with a 2:1 split ratio and the injector temperature was set at 280 °C. The samples (1μl) were injected with an AOC 20I plus auto injector. The mass spectrometer was operated in the electron impact mode (EI) at 70 eV ionization energy and scanned from 50 to 650 daltons. Data were acquired and processes with the GCMAnal software. Individual compounds were positively identified based on comparison of mass spectra with literature, NIST library data, authentic external standards, and interpretation of mass spectrometric fragmentation patterns (Otto and Simpson, 2007; Feng et al., 2010; Tamura and Tharayil, 2014). Compounds were quantified based on external calibration curves using authentic standards (8 phenolic compounds for lignin monomers, C10-C40 alkanes for n-alkanes, C22-C30 alkanols for n-alkanols, C22-C30 alkanoic for n-alkanoic acid, for α,ω-hydroxy-alkanoic acids, and C16–C24 for n-alkane-α,ω-dioic acid) in the total ion chromatogram (TIC). Long-chain fatty acids from the solvent extraction were calculated as the sum of > C24 alkanes and > C22 n-alkanoic acids and alkanols. Cutin was calculated as the sum of C14-C18 hydroxyalkanoic acids, C16-di-hyroxyalkanoic acid, ω-hydroxy-lkanoic acid (C16-C18) and ω-hydroxy-epoxy lkanoic acid (C16-C18). Suberin was calculated as the sum of α,ω-dicarboxilic acids (C16–C24; saturated and substituted) and ω-hydroxyalkanoic acids (C20–C30; saturated and substituted). Vanillys were calculated as the sum of vanillin, acetovanillone and vanillic acid. Syringls were calculated as the sum of syringaldehyde, acetosyringone, and syringic acid. Cinnamyls were calculated as the sum of p-coumaric acid and ferulic acid. The concentration of individual compounds was normalized to the SOC content to reflect its relative abundance in SOC. 　　Amino sugars Soil amino sugars were extracted according to Indorf et al. (2011) with minor modifications (Mou et al., 2020). Briefly, 0.5 g of freeze- dried soil was hydrolyzed with 10 ml of 6 M HCl at 105°C for 6 hr. After hydrolysis, samples were uniformly mixed and cooled to room temperature, and then filtered. An aliquot of 0.5 ml of filtrate was evaporated to dryness by nitrogen gas at 40–45°C to remove HCl. The dried residues were dissolved in 0.5 ml of deionized water, dried by nitrogen gas again, and re-dissolvedin 2 ml of deionized water and stored at -20°C before analysis. The concentrations of four amino sugars (GluN, MurN, GalN and ManN) were determined using a high-performance liquid chromatograph (Dionex Ultimate 3000, Thermo Fisher Scientific) equipped with an octadecylsilylated silica gel column (Acclaim120 C18; 150 mm, 4.6 mm, 3 μm; Thermo Fisher Scientific) after the procedure of pre-column derivatization with ortho-phthaldialdehyde. The individual amino sugars (GluN, GalN and MurN) were identified and quantified according to the chromatograms of standard solutions containing mixed amino sugars. The concentrations of individual and total amino sugars were expressed as μg/g dry soil. Microbial residual carbon (MRC) was calculated as: Fungal MRC (μg/g) = (GluN/179.17–2 × MurN/251.23) × 179.17 × 9, Bacterial MRC (μg/g) = MurN × 45, where F-GluN is fungal-derived GluN. Since GluN presents in both fungal and bacterial cell walls, Fungal GluN was calculated by subtracting bacterial-derived GluN from total GluN, assuming that MurN and GluN occurred at a 1 to 2 molar ratio in bacterial cell walls (Engelking et al., 2007). 179.2 and 251.2 are the molecular weights of GluN and MurN, respectively (Shao et al., 2017). 9 and 45 are conversion factors (Appuhn & Joergensen, 2006). 6. Microbial community composition Soil microbial community composition was characterized using the phospholipid fatty acids (PLFAs) methods (Bossio & Scow, 1998). Briefly, 8 g of freeze-dried soil samples was extracted in a chloroform–methanol–phosphate buffer (1:2:0.8 v/v/v), and the extracted lipids were fractionated into neutral lipids, glycolipids and polar lipids on a 0.5 g silica gel solid-phase extraction column (Supelco Inc.) by successive elution with chloroform, acetone and methanol. The methanol fraction (containing phospholipids) was subjected to mild alkaline methanolysis to transform the fatty acids into free methyl esters. With 19:0 (methyl non-adecanoate, C20H40O2) as the internal standard, samples were analyzed on a gas chromatograph (7890B, Agilent Technologies). The identification of the extracted fatty acid was based on a MIDI peak identification system (Microbial ID Inc., Newark, DE, USA). The PLFAs i15:0, α15:0, i16:0, i17:0, α17:0 were used to indicate the relative biomass of Gram-positive (G+) bacteria. The PLFAs 16:1ω9c, 16:1ω7c, 18:1ω7c, cy17:0, cy19:0 were used to indicate the relative biomass of Gram-negative (G-) bacteria. The PLFA 18:2ω6c was used as an indicator of saprotrophic fungal biomass. The PLFAs 10Me16:0, 10Me17:0 and 10Me18:0 were used to indicate actinomycete (AC) biomass. Microbial community composition was assessed by the ratio of saprotrophic fungal biomass to bacterial biomass (F/B ratio). 7. Extracellular enzyme activity The activities of three extracellular enzymes involved in the decomposition of lignin and fungal residues were measured as described by Saiya-Cork et al. (2002). The β-N-acetyl-glucosaminidase（NAG）participates in chitin and peptidoglycan degradation,hydrolyzing chitobiose to glucosamine (Sinsabaugh et al., 2009). NAG activity was measured fluorometrically using 4-methylumbelliferyl N-acetyl-β-D-glucosaminide as the substrate. Briefly, the assay was conducted by homogenizing 2.00 g of soil in 125 mL of 50 mM sodium acetate buffer (pH = 5.0) in a homogenizer for 1 min to form slurry. The microplates were assigned to six parts, including the sample assay, sample control, quench control, reference standard, negative control, and blank wells. First, 200 μL of buffer was pipetted into the blank, reference standard and negative control wells. Second, 50 μL of buffer was pipetted into the blank and sample control wells. Third, 200 μL of the soil slurry was pipetted into the sample assay, sample control, quench control wells, and then 50 μL of 10 μM 4-methylumbelliferyl (MUB) was pipetted into the reference standard and quench standard wells. Finally, 50 μL of 200 μM corresponding substrate was pipetted into the negative control and sample assay wells. There were eight replicate wells for each enzyme per soil sample. After incubation for 4 h at 25 °C, 10 μL of 1 M NaOH was added to each well to terminate the reaction. The microplates were scanned on Varioskan Flash multiplate reader (Thermo Scientific, USA) with 365 nm excitation and 450 nm emission wavelengths. 　　Phenol oxidases (POX) and peroxidases (PER) play an important role in degrading polyphenols, and their activities were measured colorimetrically using L-dihydroxyphenylalanine (DOPA) as the substrate. Phenol oxidase and peroxidase activities were measured spectrophotometrically using L-3, 4-dihydroxyphenylalanine (L-DOPA, Sigma, St. Louis, USA) as the substrate. A total of 200 μL soil suspension (see above) and 50 μL of 25 mM DOPA were added to each sample well. The wells of peroxidase assays additionally received 10 μL of a 0.3% H2O2 solution. The microplates were incubated in the dark at 25°C for up to 8 h and the absorbance was read at 460 nm. The background absorbance of DOPA was measured, and an extinction coefficient was calculated using a standard curve of DOPA degraded with mushroom tyrosinase. 8. Data calculation and statistical analysis To isolate the effects of root and mycelium on the SOC dynamics and associated microbial characteristics (i.e., SOC, biomarkers concentrations, fungal and bacterial biomass, and enzymes activities), net changes of the observations mediated by the root-pathway and mycelium-pathway were quantified by the difference of corresponding variables between the 2-mm mesh cores and 48-μm mesh cores, or between the 48-?m cores and 1-μm mesh cores, respectively (Fig. 2). The recent concept proposed by Zhuet al (2020) highlighted the contribution of microbial necromass to the SOC pool (i.e., MCP efficacy). Based on this concept, the changes of MCP efficacy (i.e., the contribution of increased microbial residual C to the increased SOC) under N addition were calculated as follow: Changes of MCP efficacy (% SOC) under N addition = 　　　　　　　　 (〖(MRC〗_(N )-MRC_CK))/((SOC_N-SOC_CK)) ×100% .............................................. (Eq. 1) , where MRCN, SOCN, MRCCK, and SOCCK represent the concentration of microbial residual C and SOC in the N-addition plots and the non-N addition plots, respectively. Additionally, the contribution of increased plant-derived C to the increased SOC induced by N addition was calculated using Eq. 1 but replacing microbial residual C with plant-derived C. Compared with plant-derived C, a relatively greater contribution of microbial residual C to SOC accumulation indicates that more C is likely stored in long-lasting forms (e.g., mineral-associated microbial-derived organic matter) rather than liberated readily from the soil (Zhu et al., 2020).