Microbial biomass and enzyme activities determine dynamics of soil organic carbon stocks and fractions along an age-sequence of Mongolian pine plantations

doi:10.21203/rs.3.rs-1635102/v1

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Research Article

Microbial biomass and enzyme activities determine dynamics of soil organic carbon stocks and fractions along an age-sequence of Mongolian pine plantations

https://doi.org/10.21203/rs.3.rs-1635102/v1

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Purpose

Afforestation is increasingly recognized as an effective measure to mitigate elevated atmospheric carbon (C) dioxide and combat climate change. While afforestation can increase C sequestration by biomass production with tree growth, little is known about whether and how tree growth affects soil organic carbon (SOC) stocks and stability. Here, we aimed to explore mechanisms underlying changes in SOC stocks and fractions with stand development from the perspective of tree-microbe-mineral interactions.

Methods

We measured annual litter inputs, soil exchangeable base cations, microbial biomass, hydrolytic and oxidative enzymes, and SOC stocks and fractions along an age-sequence of Mongolian pine (Pinus sylvestris var. mongolica) plantations with six age classes ranging from 15- to 61-year-old and adjacent grasslands in the Keerqin Sandy Lands, Northeast China.

Results

We found that afforestation of grasslands did not significantly affect 0–100 cm SOC stocks. Ecosystem C stocks linearly increased with stand development, and this C accretion was mainly attributed to tree biomass C sequestration. Topsoil (0–10 cm soil layer) mineral-associated C (MAOC) stocks and phenol oxidase activities increased, and particulate organic C (POC) stocks and β-glucosidase activities decreased with increasing stand age, but these changes disappeared in the 61-year-old stand. Structural equation model revealed that topsoil MAOC stocks were directly related to microbial biomass and β-glucosidase and phenol oxidase activities, but not directly to exchangeable calcium concentrations. Moreover, topsoil POC stocks were directly related to β-glucosidase activities, but not directly to annual litter inputs.

Conclusions

Altogether, our findings suggest that soil microbes play a central role in mediating the dynamics of SOC stocks and stability along stand development.

Afforestation of sandy grassland

Mineral-associated organic carbon

Mineral sorption

Particulate organic carbon

Phenol oxidase

Soil acid-base chemistry

Climate change induced by anthropogenic activities has been considered as a great threat to ecosystem health, such that world-wide strategies to mitigate climate change are imperative (Lal 2004; Bonan 2008; Creutzig et al. 2018). Afforestation has been increasingly recognized as an effective measure to mitigate elevated atmospheric carbon (C) dioxide and combat climate change (Tong et al. 2018; Hong et al. 2020). Under the action of this consensus, plantations are widely established at an annual increase rate of 1.4% and now account up to 7.2% of the global forest area (FAO 2020). Consequently, quantifying C sequestration capacity of these new forests and understanding mechanisms affecting this capacity are critical to evaluate the role of afforestation in climate change mitigation (Friggens et al. 2020; Wang and Huang 2020). Afforestation can indeed enable C sequestration by the production of tree biomass (Chen et al. 2021), yet whether and to what extent soils following afforestation contribute to C sequestration remain largely unclear.

Impacts of afforestation on soil organic C (SOC) stocks have received considerable attention, yet no consistent pattern is obtained. Previous studies have reported that afforestation has positive (Martens et al. 2004; Zhang et al. 2020), neutral (Ortiz et al. 2016; Wang et al. 2016) or even negative (Wiesmeier et al. 2009; Friggens et al. 2020) effects on SOC stocks. A key reason for these inconsistent and conflicting results may be because these studied plantations are at distinct development stages (Guo and Gifford 2002; Neumann-Cosel et al. 2011). In the early stage of stand development, SOC stocks usually decline owing to low litter inputs and to high nutrient demands of rapid tree growth that accelerate organic matter decomposition (Hiltbrunner et al. 2013; Chen et al. 2017). With stand development, SOC stocks gradually increase due to C inputs from aboveground litterfall, root exudates and root turnover outweighing C decomposition (Davis and Condron 2002; Hiltbrunner et al. 2013). In theory, when C inputs equilibrate with C outputs, a new steady state of SOC stocks can be reached at the later stage of afforestation (Bárcena et al. 2014). Therefore, studying SOC dynamics with plantation age is crucial to understand factors controlling SOC transformation and sequestration potential. However, most previous studies usually focus on short-term afforestation effects and thus the theoretically steady state of SOC stocks may not be determined, which constrains accurately evaluating the contribution of afforestation to SOC sequestration.

Apart from SOC stocks, SOC stability, reflecting the resistance of SOC to disturbance, is also considered as another important indicator to assess afforestation effects on climate change mitigation (Dungait et al. 2012). Theoretical and experimental studies suggest that the relative abundance of fast-turnover particulate organic C (POC) and slow-turnover mineral-associated organic C (MAOC) can be considered as a mechanistic indicator of SOC stability (Haddix et al. 2020; Lavallee et al. 2020). The POC mainly consists of partially decomposed plant residues and persists in soils via inherent biochemical recalcitrance, such that it is more susceptible to disturbance (Witzgall et al. 2021). In contrast, MAOC is predominantly made of microbial products and plant-derived dissolved organic matter (DOM) during the catabolism of POC, and persists in soils through chemical bonding to minerals (Sokol et al. 2019; Angst et al. 2021). Consequently, studying pool sizes and dynamics of these two C fractions is critical to understand mechanisms underlying afforestation effects on SOC accrual, persistence and response to environmental changes.

The POC and MAOC content can be influenced by stand development due to age-related variation in tree-microbe-mineral interactions (Almeida et al. 2021). With tree growth, litter production increases, and litter quality usually decreases characterized by high C:N ratios and lignin concentrations (Prescott and Vesterdal 2021). Meanwhile, stand development may lead to soil acidification because the more recalcitrant litter produced in the older stands can produce greater organic acids during decomposition and the increase of base cation accumulation in biomass with tree growth can reduce soil acid-buffering capacity (Jobbágy and Jackson 2003). Considering that soil acid-base status is a key determinant of microbial growth and survival, stand development may affect microbial biomass, community composition and extracellular enzyme activities by soil acidification (Clemmensen et al. 2015; Yang et al. 2020). Thus, POC content may change with stand development because of age-related variation in litter quantity that determines C inputs and in microbial extracellular enzyme activities that affect C outputs (Xu et al. 2021). As the precursors of MAOC are mainly microbial necromass (the in vivo microbial turnover pathway) and DOM produced by enzymatic decomposition of plant litter (the ex vivo modification pathway; Liang et al. 2017), changes in soil microbial biomass and extracellular enzyme activities with tree growth could influence MAOC content (Shao et al. 2017). Additionally, the decrease in base cations (e.g. Ca²⁺) and the increase in the solubility of Al³⁺ and Fe³⁺ associated with soil acidification can affect MAOC formation and stabilization (Clarholm and Skyllberg 2013). Specifically, the loss of Ca²⁺ can lead to the release of C adsorbed to minerals via disrupting polyvalent cation bridging (Rowley et al. 2018; Barreto et al. 2021). Conversely, increased Al³⁺ and Fe³⁺ solubility can improve MAOC content by forming complexes with C (Kleber et al. 2021). Therefore, litter quantity and quality, microbial biomass and activities, and soil geochemical properties co-determine responses of soil C fractions to stand development.

The primary objective of this study was to investigate how SOC stocks and stability changed with stand development, and to explore mechanisms underlying these changes from the perspective of tree-microbe-mineral interactions. To achieve this objective, we selected a chronosequence of Mongolian pine (Pinus sylvestris var. mongolica) stands planted on sandy grasslands with tree ages ranging from 15- to 61-year-old, and adjacent grasslands in Northeast China. All stands and grasslands are on fairly flat ground and the maximum distance between each other is less than 10 km, such that our experimental design could largely eliminate the confounding effects of climate and soil parent materials. We measured litter quantity and quality, soil exchangeable base cations, microbial biomass, hydrolytic and oxidative enzymes, and SOC, POC and MAOC stocks. Based on these measurements, the following hypotheses were tested: (1) SOC stocks would decrease at the early stage of afforestation, but gradually increase and eventually surpass the level of grassland SOC stocks with stand development; (2) POC stocks would increase with stand development because of the increase in litter quantity and the decrease in litter quality with tree growth; (3) stand development would increase MAOC stocks, since the increase in microbial biomass and enzyme activities with tree growth can transform more plant- to microbial-derived C.

Study site and experimental design

Our study was conducted at the Research Institute of Sand Control and Utilization, located in the southeast of Keerqin Sandy Lands, Liaoning Province, Northeast China (42°42′ N, 122°29′ E, 225 m a.s.l.). This study site has a temperate continental monsoon climate, with mean annual temperature of 7.7 ℃, mean annual precipitation of 474 mm and mean annual evaporation of 1580 mm. According to the US Soil Taxonomy, soil in our study site is classified as the Typic Ustipsamment developed from eolian parent materials (Chen et al. 2010). Soil is coarse textured consisting of 95.6% sand, 4.1% silt and 0.3% clay, and is nutrient poor with SOC of 3.46 g·kg^− 1 and total nitrogen (N) of 0.20 g·kg^− 1 in the 0–10 cm soil layer. The native vegetation is sandy grasslands dominated by Cleistogenes squarrosa, Eragrostis pilosa and Elymus dahuricus. For the purpose of fixing sand dunes and reducing wind erosion, Mongolian pine has been introduced for afforestation in our study site since 1950s.

A space-for-time substitution was used to investigate the long-term effect of stand development on SOC stocks and stability. We selected a chronosequence of Mongolian pine stands with six age classes (15-, 19-, 33-, 40-, 51-, and 61-year-old) and adjacent sandy grasslands in August 2020. All plantation stands were established on sandy grasslands by planting two-year-old seedlings in 40 cm × 40 cm × 40 cm pits with a spacing of 2 m × 5 m. These stands received no management practices, except that they were thinned twice between 15- and 33-year-old. For each age class, five stands were selected and a 20 m × 20 m plot was established in each stand. The distance between stands of the same age is at least 0.2 km to enable stands to be treated as independent replicates, and all stands are on fairly flat ground (a slope of less than 2°) and within 10 km to avoid confounding effects of climate and soil parent materials. Five 5 m × 5 m grassland plots were established at about 50 m distance from the plantation stand edge.

Soil and litter sampling

In August 2020, tree height and diameter at breast height (DBH, 1.3 m) were measured for all individuals in plantation plots. In each plantation and grassland plot, five soil cores were collected using a 2.5-cm diameter stainless steel corer from depths of 0–10, 10–20, 20–40, 40–60, 60–80, and 80–100 cm. Soil cores from the same plot were pooled together, sieved through a 2-mm mesh to remove rocks and roots, and then placed into a cooler, transported to the laboratory and processed immediately. Soil samples for measuring enzyme activities were immediately processed, for measuring organic C, N and acid-base chemistry were air-dried, and for measuring phospholipid fatty acid (PLFA) were stored at -80 ℃. In each plot, three soil samples of each soil layer were collected using 5-cm diameter volumetric rings to determine bulk density. For each plantation plot, annual litter input was determined by collecting litter samples from three randomly selected 50 cm × 50 cm subplots at the end of litterfall period in late-November 2020. Litter samples from these three subplots were pooled together, and freshly senesced litter was picked out and weighed after drying at 65 ℃ to constant mass. Litter samples were ground to pass a 0.25-mm mesh to measure C and N concentrations.

Soil chemical and biological analyses

For soil and litter samples, organic C concentration was determined using the K₂Cr₂O₇-H₂SO₄ oxidation method (Lefroy et al. 1993), and total N concentration was determined by a continuous-flow autoanalyzer (AutoAnalyzer III, Bran + Luebbe GmbH, Germany) after digested by the Kjeldhl method (Kirk 1950). Soil pH of 0–10 and 10–20 cm soil layers was measured in slurry of 25 ml distilled water and 10 g air-dried soils using a bench-top electrode pH meter. For determining exchangeable base cations, 10 g air-dried soil was extracted with 50 ml of 1 M ammonium acetate solution, shaken for 30 minutes, centrifuged and then filtered. Filtrate was analyzed to measure exchangeable Ca²⁺, Mg²⁺, K⁺ and Na⁺ concentrations by an inductively coupled plasma-optical emission spectrometry (5100 ICP-OES, Agilent Technologies, Santa Clara, USA). Exchangeable bases were calculated as the sum of exchangeable Ca²⁺, Mg²⁺, K⁺ and Na⁺ concentrations.

Soil organic C was separated into particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) by a size fractionation procedure (Cambardella and Elliott 1992). Briefly, 10 g air-dried soil was dispersed with 100 ml of 5 g·L^− 1 sodium hexametaphosphate, shaken at 90 rpm and 18 ℃ for 18 hours on a homothermal shaker. After that, soil slurry was sieved through a 53-µm sieve and repeatedly washed using deionized water. The POC fraction that retained on the sieve was transferred into aluminum dishes, weighed after drying at 60 ℃ to constant mass, ground, and then analyzed for C concentration. The MAOC stock was calculated as differences between SOC and POC stocks.

Potential activities of four C-degrading enzymes in 0–10 and 10–20 cm soil layers were determined by the colorimetric method (Eivazi and Tabatabai 1988; Deng and Tabatabai 1994; Dick 2011). For β-glucosidase (BG) activity, 5 g fresh soil was incubated at 37 ℃ for 1 hour with 20 ml MUB buffer (pH = 6.0) and 5 ml of 25 mM p-nitrophenol glucopyranoside, after which 5 ml of 0.5 M CaCl₂ and 20 ml of Tris buffer (pH = 12.0) were added to terminate the reaction. The product, p-nitrophenol, was measured at 400 nm with a spectrophotometer (UV-1750, Shimadzu, Kyoto, Japan). For cellobiohydrolase (CBH) activity, 10 g fresh soil was incubated at 37 ℃ for 72 hours with 1.5 ml methylbenzene, 5 ml of 1% sodium carboxymethyl cellulose and 5 ml acetate buffer (pH = 5.5). Soil suspension was thoroughly shaken and filtered, after which the product, glucose, was measured at 540 nm with the spectrophotometer. For phenol oxidases (POX) and peroxidase (PER) activities, 0.5 g fresh soil was incubated at 25 ℃ for 30 minutes with 3 ml acetate buffer (pH = 5.0) and 2 ml L-3,4-dihydroxyphenylalanine (L-DOPA) in the presence and absence of 0.2 ml of 0.3% H₂O₂, after which soil suspension was centrifuged at 5 ℃ for 5 minutes and then filtered. The product, dopachrome, was measured at 475 nm with the spectrophotometer. The POX activity is indicated by the L-DOPA metabolism in the absence of H₂O₂, and PER activity is calculated as the difference in L-DOPA metabolisms between the presence and absence of H₂O₂.

Soil microbial biomass and community structure in the 0–10 cm soil layer were determined by measuring phospholipid fatty acids (PLFA) (Bossio and Scow 1998; Lin et al. 2020). Briefly, freeze-dried soil was extracted by the mixture of methanol, chloroform and citrate buffer. Extracted lipids were divided into phospholipids, neutral lipids and glycolipids on silicic acid columns. After that, phospholipids were methylated and measured by a gas chromatograph equipped with a flame ionization detector (Agilent 6890 N, Santa Clara, CA, USA). The PLFAs were quantified by adding methyl nonadecanoate fatty acids as the internal standard. The PLFAs of i14:0, i15:0, a15:0, i16:0, 16:1ω7c, i17:0, a17:0, cy17:0, 18:1ω7c and cy19:0 were used as biomarkers of soil bacteria, and 18:2ω6,9c as the fungal biomarker (Angst et al. 2019). Fungal:bacterial (F:B) ratio was calculated as the ratio of fungal PLFAs to bacterial PLFAs.

Calculations and statistical analyses

Biomass of tree components (i.e. stem, branch, foliage and root) was calculated using the following allometric equations:

$$\text{M = }\text{a}\text{ × }{\text{DBH}}^{\text{b}}\text{ × }{\text{Y}}^{\text{c}}$$

where M is biomass of tree components, DBH is the diameter at breast height and Y is the tree age. Parameters of a, b and c shown in Table S1 were obtained from Zhang et al. (2019), which measured biomass accumulation of Mongolian pine plantations with tree ages ranging from 12- to 58-year-old in our study site. Biomass C (BC; kg) of tree components was calculated as follows:

$$\text{BC = M × (}\text{m}\text{ × Y + }\text{n}\text{) × 0.01}$$

where m and n parameters shown in Table S1 are obtained from Jia et al. (2012). Total tree biomass C (TBC; kg) was the sum of the tree components biomass C. Tree biomass C stock (TBC_stock; Mg ha^− 1) was calculated as follows:

$${\text{TBC}}_{\text{stock}}\text{ = 0.025 × }\sum _{\text{i}\text{ = 1}}^{\text{n}}{\text{TBC}}_{\text{i}}$$

where n is the number of Mongolian pines in a given plot. Total soil organic C stock (SOC_stock; Mg ha^− 1) was calculated as follows:

$${\text{SOC}}_{\text{stock}}\text{ = }\sum _{\text{i}\text{ = 1}}^{\text{6}}\text{(}{\text{SOC}}_{\text{i}}\text{ × }{\text{BD}}_{\text{i}}\text{ × }{\text{T}}_{\text{i}}\text{)}$$

where SOC_i, BD_i and T_i are the C concentration, bulk density and thickness of the ith soil layer, respectively.

All data were tested for normality by the Shapiro-Wilk test and for variance homogeneity by the Levene’s test. If data did not meet the normality and variance homogeneity, they were log₁₀-transformed prior to analyses. One-way analysis of variance was conducted to analyze how stand characteristics, SOC stocks and fractions, soil acid-base chemistry, microbial biomass and enzyme activities changed along the chronosequence of Mongolian pine plantations. Post-hoc mean comparisons were evaluated by the least significant difference. These analyses were performed using the SPSS 20.0 (SPSS Inc., Chicago, IL, USA), and the significant level was set at α = 0.05.

Structural equation model was conducted using the lavaan package in R (Rosseel 2012) to analyze the direct and indirect effects of stand ages, litter quality and quantity, soil acid-base chemistry, soil microbial properties, and C fractions on SOC stocks in the 0–10 cm soil layer. The hypothesized relationships are that SOC stocks are determined by C fractions, which are mediated by stand development through affecting litter quality and quantity, soil acid-base chemistry and soil microbial properties (Fig. S1). In this model, litter quality and quantity are indicated by litter C:N ratio and annual litter C input, respectively. Soil microbial properties are indicated by total PLFAs, F:B ratio, and potential activities of BG, CBH, PER and POX (Fig. S1). Final structural equation model was obtained by stepwise removing paths with the highest probability value until all remaining paths were significant (i.e. P < 0.05). Fitness of structural equation model was evaluated by the Chi-square (χ²) test, standardized root mean square residual (SRMR) and comparative fit index (CFI).

Stand characteristics

Tree height and DBH showed a similar increasing pattern with increasing stand age (Table 1). Specifically, Mongolian pines exhibited rapid growth before 33-year-old and slow growth after that age. Annual litter C input increased from 2.47 Mg ha^− 1 yr^− 1 at age 15 to 2.80 Mg ha^− 1 yr^− 1 at age 40, and then decreased to 1.55 Mg ha^− 1 yr^− 1 at age 61 (Table 1). Litter C:N ratio initially decreased and subsequently increased with increasing stand age (Table 1). Tree biomass C stocks ranged from 20.22 to 43.22 Mg ha^− 1 and significantly increased with increasing stand age (Fig. 1a).

Table 1

Stand characteristics of Mongolian pine plantations.
Stand age (yrs)	Stand density (trees ha^− 1)	Mean height (m)	DBH (cm)	Annual litter C input (Mg ha^− 1 yr^− 1)	Litter C:N ratio
15	1105 (62)^a	4.21 (0.28)^d	8.76 (0.34)^d	2.47 (0.53)^ab	145.00 (8.29)^a
19	550 (146)^b	6.44 (0.73)^c	14.26 (1.93)^c	1.81 (0.47)^bc	108.75 (14.06)^bc
33	355 (80)^c	10.53 (0.62)^b	21.37 (1.52)^b	2.41 (0.40)^abc	105.75 (11.62)^bc
40	405 (54)^c	10.60 (2.24)^b	20.82 (3.32)^b	2.80 (1.07)^a	101.50 (13.43)^c
51	415 (101)^c	11.27 (1.31)^b	21.12 (1.40)^b	1.68 (0.45)^cd	104.50 (2.65)^bc
61	360 (72)^c	12.87 (1.11)^a	24.86 (1.21)^a	1.55 (0.29)^d	118.20 (13.26)^b
^*Different lowercase letters indicate significant differences among stand ages. Values are means with SD in parentheses (n = 5). DBH, diameter at breast height.

SOC stocks and fractions

Across the six soil layers, stand age significantly affected SOC stocks in the 0–10 cm (Fig. 2a) and 80–100 cm (Fig. S2d), but not in the10–20 cm, 20–40 cm, 40–60 cm and 60–80 cm soil layers (Fig. S2a–S2c). In the 0–10 cm soil layer, SOC stocks slightly decreased after afforestation from 5.52 Mg ha^− 1 of grasslands to 4.44 Mg ha^− 1 of 15-year-old pine stands, but rapidly recovered with stand development and reached to 8.30 Mg ha^− 1 in 51-year-old pine stands (Fig. 2a). Afforestation significantly increased SOC stocks in the 80–100 cm soil layer from 3.74 Mg ha^− 1 of grasslands to 7.24 Mg ha^− 1 of 33-year-old pine stands (Fig. S2d). Total SOC stocks (i.e. 0–100 cm SOC stocks) did not significantly change along stand development (Fig. S2e). In contrast, ecosystem C stocks (i.e. the sum of total SOC and tree biomass C stocks) significantly increased with increasing stand age (Fig. 1b).

Stand age significantly influenced POC stocks in all six soil layers and the whole soil profile (i.e. 0–100 cm). In the 0–10 cm soil layer, POC stocks significantly decreased after afforestation from 0.71 Mg ha^− 1 of grasslands to 0.25 Mg ha^− 1 of 51-year-old pine stands, but increased to 1.42 Mg ha^− 1 in 61-year-old pine stands (Fig. 2b). For other five soil layers and the whole soil profile, afforestation initially increased POC stocks and subsequently decreased POC stocks, with the lowest value in 40-year-old pine stands (Fig. S3). Stand development significantly affected MAOC stocks in the 0–10 cm soil layer (Fig. 2c) but not in other five soil layers and the whole soil profile (Fig. S4). In the 0–10 cm soil layer, MAOC stocks initially increased with increasing stand age and reached the highest value in 51-year-old stands, but subsequently decreased to the same level as grasslands in 61-year-old pine stands (Fig. 2c). Stand age had significant effects on POC:MAOC ratios in the whole soil profile and all soil layers except the 80–100 cm soil layer (Fig. 2d, Fig. S5).

Soil acid-base chemistry and microbial properties

Stand age significantly influenced soil pH in 0–10 and 10–20 cm soil layers and exchangeable bases in the 10–20 cm soil layer, but not other four acid-base chemical variables (Fig. 3). Specifically, stand development significantly reduced soil pH in the 0–10 cm soil layer with the lowest value in 40-year-old pine stands (Fig. 3a). In the 10–20 cm soil layer, soil pH (Fig. 3a) and exchangeable bases (Fig. 3b) initially decreased but rapidly recovered with increasing stand age.

In the 0–10 cm soil layer, stand development significantly influenced BG (Fig. 4a), CBH (Fig. 4b) and POX (Fig. 4c) activities. The 19- and 40-year-old pine stands had significantly greater BG activities than 33- and 61-year-old pine stands (Fig. 4a). The CBH activity was significantly higher in 19- and 40-year-old pine stands than 15- and 33-year-old pine stands (Fig. 4b). The 51-year-old pine stands had significantly greater POX activities than other age classes (Fig. 4c). In the 10–20 cm soil layer, BG (Fig. 4a) and PER (Fig. 4d) activities were significantly affected by stand development. Stand development significantly reduced BG activities (Fig. 4a). The PER activity initially increased but subsequently decreased with increasing stand age (Fig. 4d).

In the 0–10 cm soil layer, total PLFAs (Fig. 5a) and bacterial PLFAs (Fig. 5c) did not significantly change along stand development. Fungal PLFAs (Fig. 5b) and F:B ratios (Fig. 5d) showed the similar trend with increasing stand age. Stand development initially decreased fungal PLFAs and F:B ratios to the lowest values in 40-year-old pine stands, but subsequently increased them.

Factors affecting SOC stocks and fractions

The final structural equation model was well supported by our data (χ² = 68.49, P = 0.14, CFI = 0.92, SRMR = 0.15) and separately explained 22%, 65% and 90% of variation in POC, MAOC and SOC stocks (Fig. 6). The SOC stock was positively related to POC (β = 0.23, P < 0.01) and MAOC stocks (β = 0.99, P < 0.01). The POC stock was negatively related to BG activities (β = -0.46, P < 0.01). The MAOC stock was positively correlated with total PLFAs (β = 0.30, P = 0.02), and BG (β = 0.29, P = 0.02) and POX (β = 0.61, P < 0.01) activities (Fig. 6). Total PLFAs were positively related to exchangeable Ca²⁺ concentration (β = 0.44, P = 0.02), and POX activity was negatively related to litter C:N ratio (β = -0.52, P < 0.01) and positively to exchangeable Ca²⁺ concentration (β = 0.43, P < 0.01). The BG activity was positively correlated with annual litter C input (β = 0.44, P = 0.01) and exchangeable Ca²⁺ concentration (β = 0.36, P = 0.03), and negatively with soil pH (β = -0.36, P = 0.04). Moreover, stand age negatively affected litter C:N ratio (β = -0.43, P = 0.02), annual litter C input (β = -0.60, P < 0.01) and soil pH (β = -0.38, P = 0.04; Fig. 6).

Changes in SOC stocks and fractions along stand development

After 61 years of afforestation, Mongolian pine plantations had the similar level of total SOC stocks (i.e. 0–100 cm SOC stocks) to sandy grasslands (Fig. S2e). This result was consistent with regional and global meta-analyses showing that afforestation of grasslands had no significant effect on SOC stocks (Guo and Gifford 2002; Bárcena et al. 2014). Former land use is suggested as a critical determinant of afforestation effects on SOC stocks (Bárcena et al. 2014). Compared with cultivated, degraded or eroded ecosystems that usually become SOC sinks after afforestation (Martens et al. 2004; Zhang et al. 2020), afforestation of healthy and native ecosystems such as grasslands had no positive effects on SOC stocks or even resulted in SOC losses (Hu et al. 2008; Chen et al. 2010; Hiltbrunner et al. 2013). Moreover, inconsistent with our initial hypothesis, we did not find the decrease of SOC stocks in the 15-year-old stand relative to sandy grasslands (Fig. S2e). This result may indicate the rapid recovery of SOC stocks after afforestation in our study site, considering that SOC losses usually occur at the early stage of plantation establishment owing to the disturbance during planting (Don et al. 2009; Huang et al. 2011).

Our results showed that ecosystem C stocks linearly increased with stand development, and this C accretion was mainly attributed to tree biomass C sequestration (Fig. 1). In contrast, total SOC stocks did not significantly change along stand development (Fig. S2e). This result is consistent with other sandy land afforestation studies exhibiting that tree biomass rather than soil is the major contributor to ecosystem C accretion (Richter et al. 1999; Hu et al. 2008). The non-significant response of total SOC stocks to stand development in sandy lands may be because sandy soils ensure macroporosity and a highly oxidized environment that lead to high C mineralization rates (Richter et al. 1999). Compared with fine textured soils, coarse-textured soils have less potential to physically protect SOC from microbial attack (Chen et al. 2010; Haddix et al. 2020). Moreover, the nutrient-poor condition of sandy soils could limit soil organic matter accumulation. This is because high nutrient demands with rapid tree growth could accelerate organic matter decomposition to meet nutrient requirements, especially for tree species associating with ectomycorrhizal fungi that have high nutrient mining capacities (Wiesmeier et al. 2009; Terrer et al. 2021).

Unlike total SOC stocks, topsoil (i.e. 0–10 cm soil layer) SOC stocks significantly increased with increasing stand age (Fig. 2a), indicating the more responsiveness of topsoil than deeper layers to stand development (Poeplau and Don 2013; Shi et al. 2013). Separating SOC into multiple fractions with different formation and persistence is suggested as an efficient way to understand mechanisms underlying SOC dynamics with stand development (Lavallee et al. 2020; Lugato et al. 2021). Our results showed that the topsoil C accretion was primarily attributed to the positive effect of stand development on MAOC stocks, which accounted for 89% of SOC stocks in the topsoil (Fig. 2c–2d). Conversely, POC stocks generally declined with increasing stand age but with an abrupt increase in the 61-year-old stand (Fig. 2b). The high proportion of MAOC stocks in old stands indicates the increase in SOC stability with stand development, since MAOC is less susceptible to disturbance than POC (Lavallee et al. 2020). However, the abrupt decrease in topsoil MAOC stocks, annual litter input (Table 1) and enzyme activities (Fig. 4) in the 61-year-old stand may suggest the decline in soil C sequestration potential in over-mature Mongolian pine plantations.

Changes in soil acid-base chemistry along stand development

Our results showed that with increasing stand age, soil pH and exchangeable bases decreased until 40-year-old, but subsequently recovered (Fig. 3a–3b). The increase in soil acidification with stand development may be due to the accumulation of base cations in tree biomass that reduce soil acid-buffering capacity (Jobbágy and Jackson 2003). Additionally, coniferous plantations can acidify soils through the production of organic acids during litter decomposition and the exudation of organic acids by roots (Alfredsson et al. 1998). The subsequent recovery of soil acid-base status in the 51- and 61-year-old stands may be because the increase in depth of vertical root distribution with tree growth can pump more base cations from the deep to surface soils (Dijkstra and Smits 2002; Jobbágy and Jackson 2004). Another explanation for this recovery may be the degradation of Mongolian pine plantations over 40-year-old, which can be evidenced by the abrupt decline in annual litter inputs (Table 1). Moreover, another study conducted in our study site also revealed the increasing loss of stem hydraulic conductivity when Mongolian pines are older than 40 years (Liu et al. 2018). This degradation can reduce the production of organic acids by roots and base-cation accumulation by tree growth, which may contribute to the recovery of soil acid-base status.

Soil acid-base chemistry is suggested as an important factor that regulates soil geochemical and microbial properties, which could further influence SOC formation and persistence (Clarholm and Skyllberg 2013). In neutral soils such as our study site, exchangeable Ca²⁺ plays important roles in forming MAOC through polyvalent cation bridging, which can protect C from microbial attack (Rowley et al. 2018; Kleber et al. 2021). However, our result showed that exchangeable Ca²⁺ concentration was not directly related to topsoil MAOC stocks (Fig. 6). This result may indicate that Ca²⁺ is not a limiting factor for MAOC formation when it acts as binding mediums for dissolved organic matter and mineral surfaces. In contrast, our result revealed that Ca²⁺ had significant indirect effects on topsoil POC and MAOC stocks by affecting microbial biomass and enzyme activities (Fig. 6). An explanation for this result may be that Ca is an essential constituent of microbial cell walls and plays important regulatory and metabolic functions in microbial cells (Dominguez 2004; Berg et al. 2017).

Microbial activity determines SOC dynamics along stand development

High plant C inputs alone are suggested to be insufficient to achieve large SOC stocks, and instead the efficiency of SOC formation and the degree of SOC stabilization are considered as the key determinant of SOC stocks (Dungait et al. 2012; Haddix et al. 2020). Microbial processing of plant-derived C and biosynthesis is suggested to be important in SOC formation and stabilization (Liang et al. 2017; Sokol et al. 2019). Consistent with this viewpoint, our result showed that topsoil MAOC stocks were positively related to total PLFAs and BG and POX activities, and that total POC stocks were negatively related to BG activities (Fig. 6). The positive relationship between total PLFAs and MAOC stocks may be because some proportion of C in MAOC is microbial-derived including microbial necromass and metabolites, which can be absorbed to mineral surfaces forming organo-mineral complexes (Kallenbach et al. 2016; Fan et al. 2021). Indeed, Liang et al. (2019) estimated that microbial necromass can account for about 30% of SOC stocks in temperate forest soils by synthesizing global amino sugar data. Consequently, high microbial biomass may accompany with great microbial necromass and metabolites, which can improve MAOC stocks.

Apart from microbial-derived C, another important C source in MAOC is plant compounds that are partially oxidized and mobilized by microbial extracellular enzymes (Castellano et al. 2015; Liang et al. 2017; Sokol et al. 2019). Plant-derived compounds such as phenolic acids, lignin monomers and simple sugars can be directly absorbed by mineral surfaces forming MAOC (Sokol et al. 2019). This ex vivo modification pathway is suggested to play important roles in MAOC formation in nutrient-poor soils or some bulk soils with low microbial density (Liang et al. 2017; Sokol et al. 2019). This viewpoint was supported by our finding of the positive relationship between MAOC stocks with BG and POX activities (Fig. 6). Moreover, the tighter relationship of MAOC stock with POX activity than that with BG activity (Fig. 6) may be because compounds from lignin degradation driven by POX have stronger sorptive affinity with mineral surfaces than those from polysaccharide hydrolysis driven by BG (Sokol et al. 2019). The negative effect of BG activities on POC stocks (Fig. 6) may be because high BG activities can increase the decomposition of POC which is primarily made of plant residues (Haddix et al. 2020). The opposite effect of enzyme activities on POC and MAOC stocks suggests their double-edged sword effect on SOC stocks.

Along an age-sequence of Mongolian pine plantations, we examined mechanisms underlying changes in SOC stocks and fractions with stand development from the perspective of tree-microbe-mineral interactions. We showed that ecosystem C stocks linearly increased with stand development, and this C accretion was mainly attributed to tree biomass C sequestration. Topsoil MAOC stocks and POX activities increased, and POC stocks and BG activities decreased with increasing stand age, but these changes disappeared in the 61-year-old stand. Structural equation model revealed that topsoil MAOC stocks were positively related to total PLFAs and BG and POX activities, and topsoil POC stocks were negatively related to BG activities. Collectively, our findings suggest that soil microbial biomass and enzyme activities play a central role in mediating dynamics of SOC stocks and stability along stand development.

Acknowledgements

We are grateful to the Research Institute of Sand Control and Utilization for providing the experimental site and relevant supports. This work was supported by the National Natural Science Foundation of China (Nos. 31700538, 31870603 and 31830015) and the Youth Innovation Promotion Association CAS (No. 2019200).

Author contributions

YZ, GL and DZ conceived this study; YZ, ZL and XL collected and analyzed that data. All authors contributed critically to the drafts and gave final approval for publication.

Data availability

The datasets generated during and/or analysed during the current study are available from corresponding authors on reasonable request.

Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Microbial biomass and enzyme activities determine dynamics of soil organic carbon stocks and fractions along an age-sequence of Mongolian pine plantations

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