Contribution of microbial necromass to soil organic carbon and its influencing factors under diverse ecosystems in Southwest China

Contribution of microbial necromass to soil organic carbon and its influencing factors under diverse ecosystems in Southwest China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Contribution of microbial necromass to soil organic carbon and its influencing factors under diverse ecosystems in Southwest China Tao Yang, Canfeng Li, Yalong Kang, Xingrong Wang, Xiawei Peng, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7512345/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and aims Against the backdrop of accelerating climate change and land degradation, enhancing soil carbon (C) stocks through optimized land use has garnered global attention. Conservation tillage and planted forests represent two key ecological restoration strategies that can promote long-term soil organic C (SOC) sequestration. Methods We quantified microbial necromass C (MNC) and a suite of soil properties to assess the contribution of MNC to SOC and its primary controls in conservation tillage systems(combining no-tillage and cover cropping) and planted forests, covering elevations from 1280 to 3269 m above sea level in Southwest China. Results Unexpectedly, SOC and MNC exhibited no clear elevational trends, yet both were significantly affected by land-use type and soil depth. Furthermore, we found SOC was significantly higher under conservation tillage than in planted forests. This difference may be partially explained by the enhanced MNC accumulation. While bacterial necromass was more abundant, its contribution to SOC became proportionally smaller as SOC increased, suggesting limited effectiveness in long-term stabilization. Accordingly, the stronger correlation between fungal necromass and SOC, despite its lower abundance, may be attributed to its higher inherent stability, which enhances its contribution to long-term C sequestration. The key edaphic determinants governing SOC variability were associated with nutrient profiles, with nitrogenemerging as the predominant regulatory factor for both SOC and MNC accumulation across conservation tillage and planted forest ecosystems. Conclusion These findings offering critical insights into the microbial necromass pathways driving SOC sequestration in conservation tillage and planted forests ecosystems. Microbial necromass carbon Soil organic carbon Conservation tillage Planted forest Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Soil organic carbon (SOC) represents a major reservoir within terrestrial C stocks and has been increasingly emphasized as an essential nature-based approach for alleviating human-induced climate change and mitigating land degradation (Crowther et al., 2019 ; Tong et al., 2018 ). Over the past two decades, afforestation on former croplands in southwest China has led to a marked increase in SOC stocks (Li et al., 2023 ; Xu et al., 2023 ), This SOC accumulation is primarily attributed to enhanced root exudation, continuous litter input, and the alleviation of tillage-induced soil disturbance (He et al., 2023 ; Ni et al., 2015 ). In parallel, conservation tillage practices —such as no-till combined with straw mulching—have been widely recognized as an effective SOC sequestration strategy in agroecosystems. These practices yield comparable C accrual rates (0.3–0.9 Mg C ha⁻¹ yr⁻¹) by minimizing soil structural disturbance, maintaining optimal surface residue cover, and improving nutrient-use efficiency through precision management (Liu et al., 2023 ). Across these contrasting ecosystems, microbial necromass C (MNC) represents a principal source of stabilized SOC, accounting for approximately 33–58% of soil C, with its dynamics directly linked to balance between microbial catabolic degradation and anabolic biomass synthesis (Liang et al., 2019 ). Given the tight coupling of microbial metabolism and nutrient cycles (Yang et al., 2024 ), MNC could exhibits divergent accumulation patterns between conservation tillage and planted forest ecosystems driven by contrasting nutrient availability and stoichiometry, consequently on SOC formation and stability (Liu et al., 2025 ). However, the underlying mechanisms regulating MNC dynamics across ecosystems and their link to longer SOC accrual remain poorly understood. Empirically, microorganisms transform plant-derived C and native SOC into cellular components or byproducts through anabolism, and their necromass act as persistent components to mediate soil long-term C sequestration (soil Microbial C Pump theory, sMCP) (Liang et al., 2017 ). This stabilization is attributed to the inherent recalcitrance of microbial necromass—such as chitin, peptidoglycans, and glycoproteins—which are resistant to enzymatic decomposition, as well as to their physicochemical protection within the soil matrix (Buckeridge et al., 2022 ). Accordingly, the formation, accumulation, and transformation of necromass C in soils are strongly influenced by microbial intrinsic traits (e.g., community composition and nutrient limitations) and environmental drivers (e.g., nutrient availability, tillage practices, and land-use changes) (Buckeridge et al., 2020 ). Generally, soil microorganisms persist in a state of chronic of energy (C) and nutrient limitation (Hill et al., 2012 ; Moorhead et al., 2016 ). Under such conditions, microbial physiological activities are substantially reduced, as energy is preferentially allocated to maintenance metabolism (e.g., sustaining essential cellular functions for survival) at the expense of biomass synthesis (Shao et al., 2021 ; Yang et al., 2024 ). This shift constrains necromass C production and thus impairs sMCP efficiency. Concurrently, soil microorganisms could secrete specific extracellular enzymes to prioritize the recycling of necromass as a nutrient source due to its high nutrient content (Bhople et al., 2021 ). The hydrolysis of necromass components significantly contributes to the formation of bioavailable N and P pools, representing a more efficient strategy than acquiring nutrients from bulk SOM (Pausch et al., 2024 ; Wang et al., 2020 ). This enzymatic recycling further accelerates MNC degradation, reducing its contribution to SOC accumulation (Wang et al., 2022 ). These findings collectively emphasize the fundamental role of microbial metabolic pathways and substrate availability in regulating MNC formation. A more comprehensive understanding of MNC patterns across diverse ecosystems, along with their contribution to SOC persistence, is critical for refining predictive models of soil carbon sequestration under large-scale ecological restoration frameworks. Afforestation of former croplands serves as a critical approach for boosting SOC sequestration, primarily through continuous inputs of plant-derived organic materials (Li et al., 2023 ; Stutter et al., 2015 ). These inputs not only supply a steady stream of organic C but also, through hydrolysis, significantly enhance the formation of bioavailable dissolved organic N and P pools, thereby synergistically promoting SOC formation and accumulation via improving microbial necromass formation (Stutter et al., 2015 ). Although afforestation introduces additional nutrients, these inputs do not consistently enhance SOC stocks (Hong et al., 2020 ), as their effects depend on initial soil C levels and potential stimulation of microbial activity that may trigger priming-induced losses of native SOC (Dijkstra et al., 2013 ). A previous study reported that elevated P levels in monoculture plantations have no significant impact on SOC stocks (Li et al., 2024 ). This is attributed to a trade-off induced by afforestation between microbial carbon and nutrient limitations: while afforestation alleviates microbial P limitation, it concurrently exacerbates co-limitation by C and N (Xia et al., 2024 ). This imbalance prompts microbes to accelerate the decomposition of mocrobial necromass, thereby offsetting potential SOC gains from increased nutrient availability and resulting in minimal net change in SOC stocks (Cui et al., 2020 ). In parallel, a range of conservation tillage practices in croplands, such as no-tillage, cover crops, stover mulching and integrated nutrient management, have been widely recognized for their capacity to enhance SOC sequestration (Oliveira et al., 2024 ). Specifically, straw return, which is functionally analogous to litter input in plantation ecosystems, introduces substantial amounts of plant-derived organic matter into the soil (typically ensuring at least 30% surface coverage by crop residues), thereby effectively promoting SOC accumulation (Zhang et al., 2024 ). Theoretically, these conservation practices create favorable microenvironments by regulating soil temperature and moisture conditions (Li et al., 2023 ), thereby enhancing microbial biomass synthesis and facilitating the continuous microbial-driven iterative process of soil C fixation, are important to enhance SOC sequestration from MNC in agroecosystems (Huber et al., 2024 ; Liu et al., 2024 ). A recent meta-analysis further demonstrates that conservation tillage significantly enhances the activities of extracellular enzymes associated with C, N, P, and sulfur (S) cycling, with increased enzyme activity being positively correlated with SOC changes (Zhu et al., 2024 ). Due to variations in environmental constraints and nutrient dynamics, afforestation and conservation tillage may result in divergent patterns of MNC accumulation and its contribution to SOC stabilization (Hong et al., 2020 ; Liu et al., 2023 ). However, the distinctions in microbial pathways of SOC accrual and their dominant controlling factors between these two land-use strategies have not been thoroughly explored, which limits our ability to fully understand and manage soil C sequestration and ecosystem sustainability. To address the identified knowledge gaps, we conducted soil sampling at depths of 0–20 cm and 20–40 cm along an elevational gradient (1,280–3,269 m) in conservation tillage systems (integrating no-tillage and cover cropping) and Pinus yunnanensis–dominated planted forests in the Yanggong River Basin, northwestern Yunnan Province, China. In this study, we quantified amino sugars as biomarkers of bacterial, fungal, and total microbial necromass to assess MNC content and its contribution to SOC. We also measured soil nutrient levels, microbial extracellular enzyme activities, and their stoichiometric ratios to evaluate microbial nutrient limitations. The objectives were 1) to quantify the bacterial, fungal, and total MNC and their contributions to SOC in conservation tillage and planted forests ecosystem across elevational gradient, and 2) to identify key soil nutrients and enzymes influencing microbial pathways of SOC accrual in different ecosystems. The findings will elucidate microbial mechanisms underlying soil C sequestration in contrasting land-use systems and provide a scientific basis for optimizing ecological restoration and soil C management in subtropical regions under climate change and land degradation. 2. Materials and methods 2.1. Site description and experimental design This study was conducted in the Yanggong River Basin (approximately 26°30′–27°10′N, 99°40′–100°20′E), situated in the northwest of Yunnan Province, China. The region experiences a typical subtropical monsoon climate, with a mean annual temperature of 15°C and mean annual precipitation ranging from 1,000 to 1,200 mm. The Yanggong River Basin is characterized by its complex topography, with elevations varying from approximately 1,215 meters in the river valleys to over 5,467 meters in the high-altitude mountainous areas. Precipitation is abundant but unevenly distributed throughout the year, with the majority of rainfall concentrated during the summer monsoon season. Due to the widespread distribution of karst landforms within study area, soil erosion and rocky desertification are prominent issues. To address these challenges, the government has implemented soil and water conservation projects and comprehensive rocky desertification control measures, including afforestation, the conversion of tillage to forests, and the promotion of conservation agriculture techniques. To evaluate the impact of these ecological restoration efforts on SOC, systematic soil sampling was conducted in both planted forests and conservation tillage across different elevation gradients within the Yanggong River Basin. Soil samples were collected from the depth of 0–20 cm (herein defined as topsoil) and 20–40 cm (herein defined as subsoil) in each plot, respectively, between May 9 and 22, 2023. After removing surface litter, 10 core samples were collected using a stainless-steel corer (5 cm diameter) along an S-shape pattern from each soil layer within each plot. The core samples were pooled and homogenized into a single sample. A total of 50 soil samples were collected from 13 planted forest sites and 12 conservation tillage sites, with samples taken from two soil layers at each site. Each soil sample was divided into two subsamples, which were then sieved through a 2-mm mesh to remove stones and coarse roots. The first part was stored at 4°C for the measurement of soil enzyme activities. The second part was air-dried for the analyses of soil abiotic properties and amino sugars. 2.2. Soil abiotic and biotic variables Soil organic carbon (SOC) was quantified using the dichromate oxidation method as described by Walkley and Black (1934). Total nitrogen (TN) and total phosphorus (TP) were analyzed via the Kjeldahl digestion procedure and the vanadium molybdate yellow colorimetric method, respectively. The C:N:P stoichiometric ratios were subsequently calculated based on the measured concentrations of SOC, TN, and TP. Soil enzyme activities, including hydrolases (β-glucosidase (BG), acid phosphatase (AP), N-acetyl-β-glucosaminidase (NAG), and leucine aminopeptidase (LAP)) and oxidases (polyphenol oxidase (PPO) and peroxidase (PER)), were determined using colorimetric methods. For hydrolases, soil samples were incubated with specific substrates (e.g., p-nitrophenyl derivatives for BG, AP, and NAG; L-leucine-p-nitroanilide for LAP) in appropriate buffers at 37°C for 1 h. The reactions were terminated by adding alkaline or acidic solutions, and the released p-nitrophenol (pNP) or p-nitroaniline (pNA) was measured spectrophotometrically at 400–410 nm. For oxidases, PPO activity was determined by incubating soil with L-3,4-dihydroxyphenylalanine (L-DOPA) and measuring the absorbance of quinone-like products at 460 nm, while PER activity was assessed using pyrogallol and hydrogen peroxide, with absorbance measured at 470 nm. All enzyme activities were expressed as µmol of product released per gram of dry soil per hour (µmol·g⁻¹·h⁻¹) (DeForest and Moorhead, 2020 ). Stoichiometric analysis of soil enzyme activities was used to identify potential C, N and P limitations in the soil. The enzymatic stoichiometric vector characteristics (including vector length and vector angle) were calculated according to Moorhead et al. ( 2016 ). These values were used as a rough reflection of microbial nutrient limitation: A greater vector length is indicative of microbial C limitation, while a vector angle below 45° suggests N limitation; angles exceeding this threshold denote P limitation (DeForest and Moorhead, 2020 ). Microbial resource limitation was classified into four categories—N limitation, P limitation, co-limitation by C and N, and co-limitation by C and P—based on a reference framework in which the x-axis (NAG + LAP/AP) and y-axis (BG/NAG + LAP) enzyme activity ratios are standardized to a baseline value of 1.0. The vector length and angle were computed according to Equations (1) and (2): $$\:Vector\:Length=\sqrt{{\left(\frac{\text{ln}\left(\text{B}\text{G}\right)\:}{\text{l}\text{n}\left(\text{N}\text{A}\text{G}+\text{L}\text{A}\text{P}\right)}\right)}^{2}+{\left(\frac{\text{ln}\left(\text{B}\text{G}\right)\:}{\text{l}\text{n}\left(\text{A}\text{P}\right)}\right)}^{2}}\:\:\:\left(1\right)$$ $$\:Vector\:Angle=\text{D}\text{E}\text{G}\text{R}\text{E}\text{E}\text{S}\left\{\text{A}\text{T}\text{A}\text{N}2\left[\frac{\text{ln}\left(\text{B}\text{G}\right)}{\text{l}\text{n}\left(\text{A}\text{P}\right)},\frac{\text{ln}\left(\text{B}\text{G}\right)}{\text{l}\text{n}\left(\text{N}\text{A}\text{G}+\text{L}\text{A}\text{P}\right)}\right]\right\}\:\:\:\left(2\right)$$ 2.3. Microbial necromass carbon Amino sugars, including glucosamine, mannosamine, and muramic acid, were quantified following Zhang and Amelung ( 1996 ). Soil samples (0.3 mg N) and standards were hydrolyzed in 6 M HCl at 105°C for 8 h. After cooling, myo-inositol was added as an internal standard. The hydrolysate was filtered, evaporated, reconstituted in deionized water, adjusted to pH 6.6–6.8, centrifuged, and freeze-dried. Amino sugars were extracted with methanol, and N-methyl-D-glucamine was added as a second internal standard. Derivatization involved reaction with hydroxylamine hydrochloride and 4-(dimethylamino) pyridine at 75–80°C, followed by acetylation with acetic anhydride. Aldononitrile derivatives were extracted with dichloromethane, washed, dried under N₂, and redissolved in ethyl acetate–hexane (1:1). Separation was performed using gas chromatography (GC-2014C, Shimadzu) with a DB-5 column. Fungal and bacterial necromass were estimated using equations ( 3 ) and ( 4 ) (Liang et al., 2019 ): $$\:\text{F}\text{u}\text{n}\text{g}\text{a}\text{l}\:\text{n}\text{e}\text{c}\text{r}\text{o}\text{m}\text{a}\text{s}\text{s}\:\text{C}=\left(\frac{\text{g}\text{l}\text{u}\text{c}\text{o}\text{s}\text{a}\text{m}\text{i}\text{n}\text{e}\:}{179.17}-\frac{2\times\:\:\text{m}\text{u}\text{r}\text{a}\text{m}\text{i}\text{c}\:\text{a}\text{c}\text{i}\text{d}}{251.23}\right)\times\:179.17\times\:9\:\:\:$$ 3 $$\:\text{B}\text{a}\text{c}\text{t}\text{e}\text{r}\text{i}\text{a}\text{l}\:\text{n}\text{e}\text{c}\text{r}\text{o}\text{m}\text{a}\text{s}\text{s}\:\text{C}=\text{m}\text{u}\text{r}\text{a}\text{m}\text{i}\text{c}\:\text{a}\text{c}\text{i}\text{d}\times\:45\:\:\:$$ 4 Here, glucosamine and muramic acid have molecular weights of 179.17 and 251.23, respectively, with conversion factors of 9 and 45 used to estimate fungal and bacterial necromass C (Appuhn and Joergensen, 2006 ; Joergensen, 2018 ). Total microbial necromass C (MNC) was derived by summing fungal-derived C (FNC) and bacterial-derived C (BNC). The MNC:SOC ratio was used to indicate the contribution of microbial necromass to SOC stabilization (Liang et al., 2019 ). 2.4. Statistical analyses Data normality and homoscedasticity were evaluated using the Shapiro–Wilk and Levene’s tests, respectively. When necessary, natural log-transformation was applied to meet parametric assumptions. Subsequently, linear mixed-effects models were fitted using the lme4 package in R to assess the effects of ecosystem type, soil depth, and their interaction on soil properties, enzyme activities, and microbial necromass carbon (MNC). Post-hoc comparisons were conducted with Tukey’s HSD test to determine significant differences among means across treatments. Linear regression analyses were performed using base R functions to examine associations between SOC, MNC components, soil nutrients, and enzyme activities along elevation gradients, with regression lines and significance visualized via ggplot2. Redundancy analysis (RDA) was conducted using the vegan package to identify relationships among soil nutrients, extracellular enzyme activities, and MNC fractions. Hierarchical partitioning (hier.part package) was employed to quantify the independent contributions of these variables to SOC variation. Pearson correlation analysis further assessed pairwise relationships among SOC, MNC, enzyme activities, and nutrients. Finally, structural equation modeling (SEM) was implemented using the piecewiseSEM package to disentangle the direct and indirect pathways through which ecosystem type, soil depth, enzyme activities, MNC, and nutrients influence SOC dynamics. All statistical analyses were performed in R (version 4.0.3), with significance thresholds set at p < 0.05.. 3. Results 3.1. Microbial necromass C and its contribution to SOC Overall, the contents of bacterial, fungal, and total microbial necromass C and their contributions to SOC in conservation tillage were significantly higher than that in planted forest (p < 0.05, Fig. 1 ). Specially, fungal and total microbial necromass C contents were significantly higher in the topsoil of conservation tillage compared to the subsoil, while bacterial necromass C contents were significantly higher in the topsoil of planted forests (p < 0.05, Fig. 1 a-c). Further, we found the contribution of bacteria necromass C to SOC in the conservation tillage was also significantly higher in subsoil compared to topsoil (p < 0.05, Fig. 1 e). Regardless of ecosystem type, the contents of bacterial, fungal, and total microbial necromass C, as well as the contribution of fungal necromass C to SOC, showed no significant relationship with elevation (p > 0.05, Figs. S1), while the ratios of bacterial and total microbial necromass C to SOC decreased significantly with increasing elevation. 3.2. Soil abiotic and biotic variables With the exception of C/P and N/P ratios, soil nutrient properties (SOC, TN, TP and C/N ratio) were found to be significantly influenced by ecosystem type (p < 0.05, Fig. 2 a-d). Regardless of ecosystem type, the contents of SOC and TN were greater in the topsoil than in the subsoil (p 0.05, Fig. 2 c and f). Furthermore, higher C/N and C/P ratios in the topsoil were exclusively observed in the conservation tillage system (p < 0.05, Fig. 2 c-d). Regarding to extracellular enzyme activity and vector characteristics (Fig. 3 a-i), ecosystem type only had significant effects on the activity of PPO (p < 0.05, Fig. 3 e ). The activities of four hydrolases were generally higher in the topsoil than in the subsoil in both ecosystems (p 0.05, Fig. 3 e-h). Vector analysis and extracellular enzyme stoichiometry revealed that soil microorganisms in both conservation tillage and planted forest ecosystems were primarily limited by P, rather than N (Fig. 3 h–k). In addition, microbial C limitation showed no significant difference between conservation tillage and planted forests (Fig. 3 i). Overall, most soil abiotic and biotic variables showed no significant correlation with elevation (Figs. S2 and S3). However, in planted forests, SOC, TN, and LAP activity exhibited significant positive correlations with elevation. 3.3. Correlations of microbial necromass C with soil biotic and abiotic factors According to redundancy analysis (RDA), abiotic and biotic variables (excluding SOC) collectively explained 74.88% (RDA1: 68.96%; RDA2: 5.92%) of the total variation in microbial necromass C (Fig. 4 a). Specifically, TN content and AP activity emerged as the most influential factors (p 0.05). Regression analysis demonstrated significant positive correlations between bacterial, fungal, and total microbial necromass C with TN, TP, AP, and PER (p < 0.05; Figs. S5-S7). Specifically, the soil N/P ratio showed a significant positive correlation only with bacterial and total microbial necromass C (p < 0.05; Fig. S5). Additionally, the contribution of bacterial and total microbial necromass C to SOC were significantly negatively correlated with the C/N and C/P ratios, as well as with the activities of BG, AP, and NAG. Conversely, these ratios were positively correlated with the vector angle (p < 0.05, Fig. S6). Furthermore, TN was significantly positively correlated with the ratio of fungal necromass carbon to SOC, while showing a significant negative correlation with the contribution of bacteria necromass C to SOC (p < 0.05). 3.4. Regulation of microbial traits and soil nutrients on SOC The results of hierarchical partitioning analysis revealed that soil nutrient parameters accounted for a substantially larger proportion of the cumulative variance (40.61%) in SOC content compared to microbial necromass C (32.77%) and extracellular enzyme activity (10.61%) (Fig. 5 a). Overall, SOC content exhibited positive correlations with fungal and bacterial microbial necromass C, the activity of AP, as well as TN, C/P, and C/N ratios. In contrast, SOC content showed a negative correlation with the ratio of bacterial microbial necromass C to SOC in both conservation tillage and planted forest (p < 0.05, Fig. 5 b). Notably, SOC was significantly positively correlated with the activities of PPO, BG, NAG, and the ratio of bacterial microbial necromass C to SOC exclusively in conservation tillage, while it demonstrated a significant positive correlation with TP only in planted forest (p < 0.05, Fig. S8). Additionally, structural equation modeling (SEM) was employed to analyze the relationships among microbial necromass C, soil nutrients, enzyme activities, soil depth, and ecosystem types with SOC (Fig. 6 ). The results demonstrated that the model exhibited a high level of fit, effectively explaining the interactions among the relevant variables. Consistent with hierarchical partitioning analysis, the SEM analysis revealed that SOC was predominantly and directly influenced by soil nutrients, followed by microbial necromass C. Furthermore, soil nutrients indirectly affected SOC through their direct effects on microbial necromass C. Ecosystem type had a significant direct impact on SOC, indicating that different ecosystems play a crucial regulatory role in SOC levels. Although soil depth did not exhibit a significant direct effect on SOC, it was indirectly associated with SOC via soil nutrients. In contrast, enzyme activities had a relatively weak influence on SOC, with only AP demonstrating a positive effect. 4. Discussion 4.1 Higher MNC in conservation tillage than planted forest ecosystems Microbial necromass C is primarily derived from bacterial and fungal sources (Liang et al., 2017 ). In this study, bacterial, fungal, and total microbial necromass carbon were significantly greater in conservation tillage systems than in planted forest ecosystems (Fig. 1 ). Meta-analytic evidence indicates that microbial necromass carbon (MNC) constitutes approximately 55.6% of SOC in agricultural soils, substantially higher than the 32.6% observed in forest soils (Liang et al., 2019 ). This study further supports the view that MNC is the primary driver of SOC accumulation in agriculture ecosystems, especially for conservation tillage. There are potentially reasons for this. Firstly, compared to planted forest ecosystems, the plant residues introduced through straw return practices in agricultural ecosystems (such as crop straw and roots) typically have a lower C/N ratio (Surigaoge et al., 2025 ), making them more easily decomposed and utilized by microorganisms, thereby providing a substantial amount of precursor material for the accumulation of microbial necromass (Cui et al., 2020 ). This explanation was supported by the lower C/N ratio and higher N content in conservation tillage ecosystems compared to planted forest ecosystems (Fig. 2 ). Under nitrogen-limited conditions, the rapid turnover of microbial necromass—characterized by lower C/N ratios than plant litter and bulk SOM—is closely coupled with soil nitrogen cycling. This renders necromass recycling, wherein living microbes consume necromass to access nitrogen, an efficient strategy for meeting microbial N demands (Buckeridge et al., 2022 ; Wang et al., 2022 ). The study sites are situated within a subtropical climatic zone, with numerous studies conducted in similar subtropical ecosystems, where P is often reported as the primary limiting nutrient for soil microbial communities (Cui et al., 2022 ; Du et al., 2020 ). This result aligns with evidence from extracellular enzyme stoichiometry and vector analysis, both of which indicate phosphorus rather than nitrogen as the primary limiting nutrient (Fig. 3 ). In contrast to N-limited systems, the higher N availability in our study sites likely reduces the reliance on necromass recycling as a strategy for N acquisition. This is particularly evident in conservation tillage ecosystems, where elevated soil N content may prevent extensive necromass recycling, thereby promoting the long-term stabilization and accumulation of microbial necromass C. Indeed, our results demonstrate that soil TN is the most significant factor influencing MNC, showing a highly significant positive correlation with MNC accumulation (Figs. 4 and 5 ). Third, the greatly accumulation of MNC in conservation tillage ecosystems is closely linked to tillage practices, as conventional tillage causes significant SOC loss (Ye et al., 2020). In contrast, no-till or reduced tillage have been shown to increase MNC content by up to 20% (Zhou et al., 2020), demonstrating that tillage practices critically regulate SOC dynamics through microbial necromass pathways (Huber et al., 2024 ). In summary, through the combined effects of optimized nutrient conditions, reduced soil disturbance, conservation tillage systems create a more favorable soil environment for the accumulation and stabilization of microbial necromass, thereby achieving higher SOC sequestration efficiency compared to afforested ecosystems. 4.2 Key factors regulating microbial necromass C In the current study, soil TN, TP, and C-N-P stoichiometry significantly influenced soil microbial necromass, with these effects being more pronounced than those of soil microbial extracellular enzyme activity (Fig. 4 ). As above mention, this finding can be attributed to the direct role of soil nutrients, particularly N, in driving microbial growth, reproduction, and subsequent necromass accumulation (Yang et al., 2024 ). Furthermore, the influence of soil nutrients on microbial necromass extends beyond merely providing essential substrates for microbial metabolism; it also plays a critical role in shaping microbial community structure and metabolic strategies (Wang et al., 2024 ). This, in turn, governs the trade-offs among key microbial functions, including biosynthesis, stress tolerance, and extracellular enzyme production (Klappenbach et al., 2000 ), as exemplified by elevated N availability in soils with higher C resources, which enhances microbial abundance and prioritizes growth-related functions over energy-intensive processes, thereby promoting greater necromass accumulation (Shao et al., 2021 ; Yang et al., 2024 ). In contrast, extracellular enzyme activity primarily mediates the short-term decomposition of organic matter by breaking down complex substrates into simpler forms, yet its impact on long-term necromass stabilization is indirect and secondary (Chen et al., 2018 ). In terms of extracellular enzymes and stoichiometry, the accumulation of microbial necromass C is primarily associated with microbial P-acquiring enzymes (AP), while the influence of N-acquiring enzymes (NAG and LAP) is not significant (Fig. 4 ). This phenomenon can be attributed to the predominant P limitation for microbial activity (Fig. 3 ), where the activity of AP alleviates P constraints, thereby promoting necromass accumulation (Yuan et al., 2021 ; Zhai et al., 2022 ). This explanation was supported by the positive effects of TP on microbial necromass C (Fig. S5). However, the contribution of bacterial necromass C, rather than fungal necromass, to SOC shows a negative correlation with AP activity (Fig. S6). These findings may stem from a trade-off metabolic strategy, bacterial transferred more energy from microbial CUE to P acquisition via P-acquiring enzymes production (Zhai et al., 2022 ). As a result, the accumulation of bacterial necromass gain from P acquisition does not offset the consume of native SOC during the P acquisition process. This implies that bacterial-driven P cycling may hinder SOC long-term accumulation under P-limitation condition (Wu et al., 2025 ). Previous research has identified oxidative enzymes as playing a crucial role in microbial necromass accumulation, with their activity promoting the decomposition of lignin, phenolic acids, and other plant-derived compounds, thereby enhancing the conversion of plant-derived SOC into MNC(Shi et al., 2025 ). However, in our study, we found that microbial necromass accumulation is significantly positively correlated with PPO activity but shows no correlation with PER activity (Fig. S7). This discrepancy can be attributed to the distinct functional roles of these enzymes, with PPO primarily degrading recalcitrant, C-rich compounds in soil, such as lignin and phenolic acids, which facilitates the formation of stable organic matter and promotes necromass accumulation (Zhao et al., 2024 ). This inference is further supported by the significant positive correlation between PPO activity and soil C/P ratios, whereas PER shows no significant relationship with C/P (Fig. S5). 4.3 Microbial necromass driving SOC accumulation Compelling evidence has established that microbial necromass C, as a primary stable form of soil C pools, plays a central role in the long-term accumulation of SOC (Hu et al., 2023 ). Our results demonstrate that the contribution of bacterial, fungal, and total microbial necromass C are significantly higher in conservation tillage ecosystems compared to planted forest ecosystems (Fig. 1 ). Evidently, the substantial SOC accumulation observed in conservation tillage ecosystems could be largely attributed to microbial necromass C (Figs. 5 and 6 ). In detail, we observe that the contribution of bacterial necromass C to SOC (3.37%-82.12%) were higher than fungal necromass C (0.70%-33.18%), regardless of ecosystems (Fig. 1 ). In terms of conservation tillage croplands, pervious study has reported that fungal necromass contributes more to SOC than bacteria in northeastern China (Liu et al., 2024 ), which is inconsistent with the findings of our study. The observed regional differences may be explained by contrasting N dynamics in these agricultural systems. In particular, the lower soil C/N ratios characteristic of southwestern China's croplands appear to mitigate the N limitation typically constraining bacterial growth, resulting in proportionally greater bacterial necromass accumulation relative to the N-rich but higher C/N ratio soils of northeastern China (Li et al., 2022 ). Indeed, we only observed a significant positively relationship between decreased N-limitation and the contribution of bacterial necromass C to SOC (Fig. S6). Although we observed a positive effect of the content of bacterial necromass C on SOC accumulation, the contribution of bacterial necromass C to SOC negativity related to SOC (Fig. 5 ). This suggests that there was an unproportionally increase in bacterial necromass C accrual rate compared to SOC both in conservation tillage and planted forests ecosystems. In other words, organic carbon components from other pathways—such as lignin derivatives and fungal necromass—likely exhibit higher transformation and stabilization efficiency in soils, accumulating more effectively than bacterial necromass C and serving as dominant drivers of long-term SOC accumulation (Yin et al., 2025 ). Actually, we did observe that fungal necromass C plays a more significant role in explaining the variation in SOC than bacterial necromass C, as the increase in fungal necromass C significantly promotes SOC accumulation (Fig. 5 ). As above mentioned, an explanation for this pattern is that fungal necromass C is more stable than bacterial necromass C (Xue et al., 2024 ), which can partially be supported by unchanged contribution from fungi necromass in response both biotic and abiotic factors, as well as elevation, while bacterial necromass C not. On the other hand, studies have reported that bacterial necromass C plays an important role in fungal necromass C accumulation, as fungal communities can metabolize bacterial necromass, thereby promoting their own necromass buildup and forming a stronger association with SOC (Camenzind et al., 2023 ; Liu et al., 2024 ). 5. Conclusions This study elucidates the convergent microbial necromass pathways governing SOC sequestration in subtropical China, demonstrating that MNC—fundamentally regulated by soil TN—serves as the predominant driver of SOC accumulation in both conservation tillage and afforested ecosystems. Conservation tillage systems exhibited superior MNC accrual compared to planted forest ecosystems, attributable to optimized nutrient stoichiometry and reduced necromass turnover, with fungal necromass displaying greater stabilization efficiency and predictive power for SOC persistence than its bacterial counterpart despite lower quantitative contributions. These findings challenge conventional afforestation-based C sequestration paradigms, revealing that conservation tillage practices—through enhanced nutrient retention and minimized soil disturbance—more effectively promote microbial-derived SOC stabilization in subtropical regions. The identification of microbial necromass as the central nexus in soil C cycling, with tillage management outweighing afforestation in controlling sequestration outcomes, provides a mechanistic foundation for optimizing land-use strategies to enhance carbon storage in vulnerable ecosystems under climate change. Declarations ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China (Grants No. 32471963, 42371066, 31971729), the 5·5 Engineering Research & Innovation Team Project of Beijing Forestry University (BLRC2023B09), the Yunnan Provincial Key Research and Development Program (202403AC100042), and the Geological Survey Project (DD20220879). Declaration of Interest Statement The authors declare no conflicts of interest, financial or otherwise, that could have influenced the outcomes of this study. References Appuhn A, Joergensen RG (2006) Microbial colonisation of roots as a function of plant species. Soil Biol Biochem 38:1040–1051. https://doi.org/10.1016/j.soilbio.2005.09.002 Bhople P, Keiblinger K, Djukic I, Liu D, Zehetner F, Zechmeister-Boltenstern S, Joergensen G, Murugan R, R (2021) Microbial necromass formation, enzyme activities and community structure in two alpine elevation gradients with different bedrock types. Geoderma 386:114922. https://doi.org/10.1016/j.geoderma.2020.114922 Buckeridge KM, Creamer C, Whitaker J (2022) Deconstructing the microbial necromass continuum to inform soil carbon sequestration. Funct Ecol 36:1396–1410. https://doi.org/10.1111/1365-2435.14014 Buckeridge KM, Mason KE, McNamara NP, Ostle N, Puissant J, Goodall T, Griffiths RI, Stott AW, Whitaker J (2020) Environmental and microbial controls on microbial necromass recycling, an important precursor for soil carbon stabilization. Commun Earth Environ 1:36. https://doi.org/10.1038/s43247-020-00031-4 Camenzind T, Mason-Jones K, Mansour I, Rillig MC, Lehmann J (2023) Formation of necromass-derived soil organic carbon determined by microbial death pathways. Nat Geosci 16:115–122. https://doi.org/10.1038/s41561-022-01100-3 Chen J, Luo Y, Van Groenigen KJ, Hungate BA, Cao J, Zhou X, Wang R (2018) A keystone microbial enzyme for nitrogen control of soil carbon storage. Sci Adv 4:eaaq1689. https://doi.org/10.1126/sciadv.aaq1689 Crowther TW, Van Den Hoogen J, Wan J, Mayes MA, Keiser AD, Mo L, Averill C, Maynard DS (2019) The global soil community and its influence on biogeochemistry. Science 365:eaav0550. https://doi.org/10.1126/science.aav0550 Cui J, Zhu Z, Xu X, Liu S, Jones DL, Kuzyakov Y, Shibistova O, Wu J, Ge T (2020) Carbon and nitrogen recycling from microbial necromass to cope with C:N stoichiometric imbalance by priming. Soil Biol Biochem 142:107720. https://doi.org/10.1016/j.soilbio.2020.107720 Cui Y, Bing H, Moorhead DL, Delgado-Baquerizo M, Ye L, Yu J, Zhang S, Wang X, Peng S, Guo X, Zhu B, Chen J, Tan W, Wang Y, Zhang X, Fang L (2022) Ecoenzymatic stoichiometry reveals widespread soil phosphorus limitation to microbial metabolism across Chinese forests. Commun Earth Environ 3:184. https://doi.org/10.1038/s43247-022-00523-5 DeForest JL, Moorhead DL (2020) Effects of elevated pH and phosphorus fertilizer on soil C, N and P enzyme stoichiometry in an acidic mixed mesophytic deciduous forest. Soil Biol Biochem 150:107996. https://doi.org/10.1016/j.soilbio.2020.107996 Dijkstra FA, Carrillo Y, Pendall E, Morgan JA (2013) Rhizosphere priming: a nutrient perspective. Front Microbiol 4. https://doi.org/10.3389/fmicb.2013.00216 Du E, Terrer C, Pellegrini AFA, Ahlström A, Van Lissa CJ, Zhao X, Xia N, Wu X, Jackson RB (2020) Global patterns of terrestrial nitrogen and phosphorus limitation. Nat Geosci 13:221–226. https://doi.org/10.1038/s41561-019-0530-4 Feyissa A, Raza ST, Cheng X (2023) Soil carbon stabilization and potential stabilizing mechanisms along elevational gradients in alpine forest and grassland ecosystems of Southwest China. CATENA 229, 107210. https://doi.org/10.1016/j.catena.2023.107210 He T, Sun J, Hu B, Zhu T, Zhang W (2023) The importance of fine root protection in topsoil carbon and nitrogen sequestration following land-use changes on sloping karst ecosystems. CATENA 220:106660. https://doi.org/10.1016/j.catena.2022.106660 Hill BH, Elonen CM, Seifert LR, May AA, Tarquinio E (2012) Microbial enzyme stoichiometry and nutrient limitation in US streams and rivers. Ecol Ind 18:540–551. https://doi.org/10.1016/j.ecolind.2012.01.007 Hong S, Yin G, Piao S, Dybzinski R, Cong N, Li X, Wang K, Peñuelas J, Zeng H, Chen A (2020) Divergent responses of soil organic carbon to afforestation. Nat Sustain 3:694–700. https://doi.org/10.1038/s41893-020-0557-y Hu J, Du M, Chen J, Tie L, Zhou S, Buckeridge KM, Cornelissen JHC, Huang C, Kuzyakov Y (2023) Microbial necromass under global change and implications for soil organic matter. Glob Change Biol 29:3503–3515. https://doi.org/10.1111/gcb.16676 Huber S, Rosinger C, Bodner G, Bernardini LG, Bieber M, Mentler A, Sae-Tun O, Scharf B, Keiblinger KM (2024) Highway to health: Microbial pathways of soil organic carbon accrual in conservation farming systems. Geoderma 452:117115. https://doi.org/10.1016/j.geoderma.2024.117115 Joergensen RG (2018) Amino sugars as specific indices for fungal and bacterial residues in soil. Biol Fertil Soils 54:559–568. https://doi.org/10.1007/s00374-018-1288-3 Klappenbach JA, Dunbar JM, Schmidt TM (2000) rRNA Operon Copy Number Reflects Ecological Strategies of Bacteria. Appl Environ Microbiol 66:1328–1333. https://doi.org/10.1128/AEM.66.4.1328-1333.2000 Li Q, Jia W, Wu J, Wang L, Huang F, Cheng X (2023) Changes in soil organic carbon stability in association with microbial carbon use efficiency following 40 years of afforestation. CATENA 228:107179. https://doi.org/10.1016/j.catena.2023.107179 Li X, Huang J, Qu C, Chen W, Chen C, Cai P, Huang Q (2022) Diverse regulations on the accumulation of fungal and bacterial necromass in cropland soils. Geoderma 410:115675. https://doi.org/10.1016/j.geoderma.2021.115675 Li Y, Wu M, Zhao T, Mou Z, Li T, Zhang J, Wu W, Wang F, Zhang W, Wang J, Li Y, Hui D, Lambers H, Peñuelas J, Sardans J, Liu Z (2024) Responses of soil organic carbon compounds to phosphorus addition between tropical monoculture and multispecies forests. Sci Total Environ 947:174672. https://doi.org/10.1016/j.scitotenv.2024.174672 Liang C, Amelung W, Lehmann J, Kästner M (2019) Quantitative assessment of microbial necromass contribution to soil organic matter. Glob Change Biol 25:3578–3590. https://doi.org/10.1111/gcb.14781 Liang C, Schimel JP, Jastrow JD (2017) The importance of anabolism in microbial control over soil carbon storage. Nat Microbiol 2:17105. https://doi.org/10.1038/nmicrobiol.2017.105 Liu D, Zhou Z, Iqbal S, Dou TT, Bonito G, Liu W, An S, Chater CCC, Perez-Moreno J, Che R, Jones DL, Yu F (2024) Fungal necromass contribution to carbon sequestration in global croplands: A meta-analysis of driving factors and conservation practices. Sci Total Environ 949:174954. https://doi.org/10.1016/j.scitotenv.2024.174954 Liu M, Zheng S, Pendall E, Smith P, Liu J, Li J, Fang C, Li B, Nie M (2025) Unprotected carbon dominates decadal soil carbon increase. Nat Commun 16, 2008. https://doi.org/10.1038/s41467-025-57354-z Liu X, Song X, Li S, Liang G, Wu X (2023) Understanding how conservation tillage promotes soil carbon accumulation: Insights into extracellular enzyme activities and carbon flows between aggregate fractions. Sci Total Environ 897:165408. https://doi.org/10.1016/j.scitotenv.2023.165408 Moorhead DL, Sinsabaugh RL, Hill BH, Weintraub MN (2016) Vector analysis of ecoenzyme activities reveal constraints on coupled C, N and P dynamics. Soil Biol Biochem 93:1–7. https://doi.org/10.1016/j.soilbio.2015.10.019 Ni J, Luo DH, Xia J, Zhang ZH, Hu G (2015) Vegetation in karst terrain of southwestern China allocates more biomass to roots. Solid Earth 6:799–810. https://doi.org/10.5194/se-6-799-2015 Oliveira EM, Wittwer R, Hartmann M, Keller T, Buchmann N, Van Der Heijden MGA (2024) Effects of conventional, organic and conservation agriculture on soil physical properties, root growth and microbial habitats in a long-term field experiment. Geoderma 447:116927. https://doi.org/10.1016/j.geoderma.2024.116927 Pausch J, Holz M, Zhu B, Cheng W (2024) Rhizosphere priming promotes plant nitrogen acquisition by microbial necromass recycling. Plant Cell Environ 47:1987–1996. https://doi.org/10.1111/pce.14858 Shao P, Lynch L, Xie H, Bao X, Liang C (2021) Tradeoffs among microbial life history strategies influence the fate of microbial residues in subtropical forest soils. Soil Biol Biochem 153:108112. https://doi.org/10.1016/j.soilbio.2020.108112 Shi K, Sun Y, Zeng D-H, Sheng Z, Zhang Y, Lin G (2025) Oxidative enzymes underlie tree species effects on soil organic carbon stocks: A common garden test with eight tree species. Soil Biol Biochem 202:109715. https://doi.org/10.1016/j.soilbio.2025.109715 Stutter MI, Shand CA, George TS, Blackwell MSA, Dixon L, Bol R, MacKay RL, Richardson AE, Condron LM, Haygarth PM (2015) Land use and soil factors affecting accumulation of phosphorus species in temperate soils. Geoderma 257–258:29–39. https://doi.org/10.1016/j.geoderma.2015.03.020 Surigaoge S, Yang H, Fornara D, Su Y, Du Y-H, Ren S-X, Zhang W-P, Li L (2025) Litter functional dissimilarity accelerates carbon and nitrogen release from the decomposition of straw but not root in maize/legume intercropping. Plant Soil 506:487–502. https://doi.org/10.1007/s11104-024-06616-8 Tong X, Brandt M, Yue Y, Horion S, Wang K, Keersmaecker WD, Tian F, Schurgers G, Xiao X, Luo Y, Chen C, Myneni R, Shi Z, Chen H, Fensholt R (2018) Increased vegetation growth and carbon stock in China karst via ecological engineering. Nat Sustain 1:44–50. https://doi.org/10.1038/s41893-017-0004-x Wang B, Huang Y, Li N, Yao H, Yang E, Soromotin AV, Kuzyakov Y, Cheptsov V, Yang Y, An S (2022) Initial soil formation by biocrusts: Nitrogen demand and clay protection control microbial necromass accrual and recycling. Soil Biol Biochem 167:108607. https://doi.org/10.1016/j.soilbio.2022.108607 Wang D, Gao W, Wang J, Yin H (2024) Minimal impact of nitrogen addition on bacterial and fungal communities during fungal necromass decomposition in a subalpine coniferous plantation. Soil Biol Biochem 196:109499. https://doi.org/10.1016/j.soilbio.2024.109499 Wang T, Tian Z, Tunlid A, Persson P (2020) Nitrogen acquisition from mineral-associated proteins by an ectomycorrhizal fungus. New Phytol 228:697–711. https://doi.org/10.1111/nph.16596 Wu M, Chen L, Chen S, Chen Y, Ma J, Zhang Y, Pang D, Li X (2025) Soil microbial carbon and nitrogen limitation constraints soil organic carbon stability in arid and semi-arid grasslands. J Environ Manage 373:123675. https://doi.org/10.1016/j.jenvman.2024.123675 Xia Y, Peñuelas J, Sardans J, Zhong X, Xu L, Yang Z, Yang Y, Yang L, Yue K, Fan Y (2024) Phosphorus addition accelerates soil organic carbon mineralization by desorbing organic carbon and increasing microbial activity in subtropical forest soils. Appl Soil Ecol 193:105166. https://doi.org/10.1016/j.apsoil.2023.105166 Xu L, Zhang J, Hu P, Zhang W, Xiao L, Ye Y, Xiao D, Zhao J, Xiao J, Wang K (2023) Bedrock outcrops weakly promote rather than inhibit soil carbon sequestration after vegetation restoration. Sci Total Environ 858:159470. https://doi.org/10.1016/j.scitotenv.2022.159470 Xue Z, Qu T, Li X, Chen Q, Zhou Z, Wang B, Lv X (2024) Different contributing processes in bacterial vs. fungal necromass affect soil carbon fractions during plant residue transformation. Plant Soil 494:301–319. https://doi.org/10.1007/s11104-023-06277-z Yang L, Canarini A, Zhang W, Lang M, Chen Y, Cui Z, Kuzyakov Y, Richter A, Chen X, Zhang F, Tian J (2024) Microbial life-history strategies mediate microbial carbon pump efficacy in response to N management depending on stoichiometry of microbial demand. Glob Change Biol 30:e17311. https://doi.org/10.1111/gcb.17311 Yin Q, Liu Y, Li J, Wu J, Wang, Yifan, Zhang H, Liu H, Jiang L, Yang J, Wang, Yidi, Jiang Y, Han X, Wang J (2025) Soil organic carbon formation in grassland ecosystems: Higher efficiency of roots than shoots and rhizodeposition. Soil Tillage Res 250:106523. https://doi.org/10.1016/j.still.2025.106523 Yuan Y, Li Y, Mou Z, Kuang L, Wu W, Zhang J, Wang F, Hui D, Peñuelas J, Sardans J, Lambers H, Wang J, Kuang Y, Li Z, Liu Z (2021) Phosphorus addition decreases microbial residual contribution to soil organic carbon pool in a tropical coastal forest. Glob Change Biol 27:454–466. https://doi.org/10.1111/gcb.15407 Zhai Z, Luo M, Yang Y, Liu Y, Chen X, Zhang C, Huang J, Chen J (2022) Trade-off between microbial carbon use efficiency and microbial phosphorus limitation under salinization in a tidal wetland. CATENA 209:105809. https://doi.org/10.1016/j.catena.2021.105809 Zhang J, Zhang F, Yang L (2024) Continuous straw returning enhances the carbon sequestration potential of soil aggregates by altering the quality and stability of organic carbon. J Environ Manage 358:120903. https://doi.org/10.1016/j.jenvman.2024.120903 Zhang M, Che R, Cheng Z, Zhao H, Wu C, Hu J, Zhang S, Liu D, Cui X, Wu Y (2023) Decades of reforestation significantly change microbial necromass, glomalin, and their contributions to soil organic carbon. Agric Ecosyst Environ 346:108362. https://doi.org/10.1016/j.agee.2023.108362 Zhang X, Amelung W (1996) Gas chromatographic determination of muramic acid, glucosamine, mannosamine, and galactosamine in soils. Soil Biol Biochem 28:1201–1206. https://doi.org/10.1016/0038-0717(96)00117-4 Zhao Y, Liu C, Kang E, Li X, Deng Y, Feng X (2024) Plant–microbe interactions underpin contrasting enzymatic responses to wetland drainage. Nat Clim Change 14:1078–1086. https://doi.org/10.1038/s41558-024-02101-3 Zhu Y, Zhang H, Wang Q, Zhu W, Kang Y (2024) Soil extracellular enzyme activity linkage with soil organic carbon under conservation tillage: A global meta-analysis. Eur J Agron 155:127135. https://doi.org/10.1016/j.eja.2024.127135 Supplementary Files SupplementaryInformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7512345","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510492268,"identity":"d258ea2a-d16a-48fc-881a-0e8a5d5a445c","order_by":0,"name":"Tao Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBACNvnHBx///GMjxy///OCDhIoawlr4GNKSjRkb0owlG3KSDR6cOUZYixxDjpkwY8PhxA0NCWaSD1uYiXAYw7E05sIdQC0MB9IqEhvYGPjbuxPwa2FsPvZ45pl04+2MjcduJO6QYZA4c3YDfi3MbOkGPGzWsjubGdJuJJ5hYzCQyCWghY3HTIKHjZlxwzEGs4LENmYitPDwmEnztjkrbjjDYMZAnBYJtmTDGWeAgTyDJ1ki4cwxHoJ+kZ/BfPDBhwpgVEqwH/z4o6JGjr+9F78WDMBDmvJRMApGwSgYBVgBAI1cSmyet0EHAAAAAElFTkSuQmCC","orcid":"","institution":"Beijing Forestry University","correspondingAuthor":true,"prefix":"","firstName":"Tao","middleName":"","lastName":"Yang","suffix":""},{"id":510492269,"identity":"e78fb859-0d3c-47b0-97e1-d1497966118c","order_by":1,"name":"Canfeng Li","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Canfeng","middleName":"","lastName":"Li","suffix":""},{"id":510492270,"identity":"3c0011e5-9d70-48f1-b10e-a1e9c689ead7","order_by":2,"name":"Yalong Kang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yalong","middleName":"","lastName":"Kang","suffix":""},{"id":510492271,"identity":"816964a3-001b-4fb0-8838-82f1bd487f55","order_by":3,"name":"Xingrong Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xingrong","middleName":"","lastName":"Wang","suffix":""},{"id":510492272,"identity":"279f6c4d-6014-4893-a82c-e171ba33489a","order_by":4,"name":"Xiawei Peng","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiawei","middleName":"","lastName":"Peng","suffix":""},{"id":510492273,"identity":"4685c78e-42d1-4503-93c1-5c8f4685065d","order_by":5,"name":"Liankai Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Liankai","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-09-02 02:05:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7512345/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7512345/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91067370,"identity":"5fa23841-4e00-4399-88f3-bf1c4aaf9b25","added_by":"auto","created_at":"2025-09-11 10:10:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":942111,"visible":true,"origin":"","legend":"\u003cp\u003eContents of (a) fungal necromass C, (b) bacterial necromass C, and (c) total microbial necromass C, along with their respective contributions to SOC (d–f), in topsoil (circles) and subsoil (squares) across conservation tillage (CT) and planted forest (PF) ecosystems. Lowercase letters indicate significant differences (p \u0026lt; 0.05) between soil layers within the same ecosystem. Asterisks indicate significant differences between ecosystems (*p \u0026lt; 0.05, **p \u0026lt; 0.01, *p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/d1bf661df31c953726a22f41.png"},{"id":91067371,"identity":"afc48360-db53-476c-9059-65ae8018d981","added_by":"auto","created_at":"2025-09-11 10:10:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":795922,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Soil organic carbon (SOC), (b) total nitrogen (TN), (c) total phosphorus (TP), and their stoichiometric ratios in topsoil (circles) and subsoil (squares) under conservation tillage (CT) and planted forest (PF) ecosystems. Different lowercase letters indicate significant differences (p \u0026lt; 0.05) between soil layers within the same ecosystem. Asterisks denote significant differences between ecosystems (*p \u0026lt; 0.05, **p \u0026lt; 0.01, *p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/6d8e816894cb351624c31936.png"},{"id":91068298,"identity":"9a7edb15-367f-4fa9-afef-60c396a439e3","added_by":"auto","created_at":"2025-09-11 10:18:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1258187,"visible":true,"origin":"","legend":"\u003cp\u003eActivities of soil extracellular enzyme and stoichiometry in topsoil and subsoil across conservation tillage (CT) and planted forest (PF) ecosystems. Different lowercase letters indicate significant differences (p \u0026lt; 0.05) between topsoil and subsoil within the same ecosystem. Asterisks denote significant differences between different ecosystems (p \u0026lt; 0.05; p \u0026lt; 0.01; *p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/ef70337bb9db8bc3a96b42ae.png"},{"id":91068297,"identity":"ac2f913c-2506-4a13-97c5-d1e54d69b6b3","added_by":"auto","created_at":"2025-09-11 10:18:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":644760,"visible":true,"origin":"","legend":"\u003cp\u003eRedundancy analysis (RDA) illustrating the relationships among soil nutrients, microbial extracellular enzyme activities, and microbial necromass carbon and its contribution to SOC (a). Black arrows represent response variables, while purple arrows denote explanatory variables. Panel (b) presents the proportion of variance explained by individual predictors (Explains, %), with significance levels indicated as *p \u0026lt; 0.05, **p \u0026lt; 0.01, *p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/98400a66df84821b722dbdb3.png"},{"id":91069383,"identity":"efc069b5-31e2-4178-8576-b514a2e448ec","added_by":"auto","created_at":"2025-09-11 10:26:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1114968,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Results of hierarchical partitioning analysis illustrating the independent contributions of various factors to soil organic carbon (SOC) variation. Blue bars represent microbial necromass carbon components (BNC: bacterial necromass C; BNC/SOC: BNC contribution to SOC; FNC: fungal necromass C; FNC/SOC: FNC contribution to SOC), green bars denote enzyme activities (BG: β-1,4-glucosidase; NAG: β-1,4-N-acetyl-glucosaminidase; LAP: leucine aminopeptidase; AP: acid phosphatase; PPO: polyphenol oxidase; PER: peroxidase), and orange bars indicate soil nutrient variables (TN: total nitrogen; TP: total phosphorus; C/P, C/N, N/P: elemental stoichiometric ratios). The R² value reflects the proportion of variance in SOC explained by the model. (b) Correlation analysis between SOC and microbial necromass components, soil nutrients, and enzyme activities. Regression lines are presented along with significance levels (*p \u0026lt; 0.05, **p \u0026lt; 0.01, *p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/2ca34590cc4a4d62f8ce5823.png"},{"id":91067374,"identity":"e2530706-473d-403a-90cc-f7f56c131e0d","added_by":"auto","created_at":"2025-09-11 10:10:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":573616,"visible":true,"origin":"","legend":"\u003cp\u003eStructural equation modeling (SEM) depicting the relationships among ecosystem type, soil depth, enzyme activities, microbial necromass C, soil nutrients, and SOC (a), along with the corresponding standardized effects (b). In panel (a), black solid arrows represent significant positive effects, red solid arrows indicate significant negative effects, and dashed arrows denote non-significant paths. Standardized path coefficients are shown alongside arrows, and R² values reflect the proportion of variance explained for each dependent variable. Panel (b) summarizes the direct and indirect effects of individual factors on SOC. Statistical significance was determined at p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/5b7b3c5d9e6c75aaf1f26662.png"},{"id":93154026,"identity":"a704f64a-dba1-4093-b690-e2d0fa8bc52a","added_by":"auto","created_at":"2025-10-09 15:09:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5894240,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/f5c02b64-b8f5-4eaf-a161-7faea61361a7.pdf"},{"id":91067379,"identity":"69c19c77-025a-4034-a5e2-da239d4d545f","added_by":"auto","created_at":"2025-09-11 10:10:52","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1171125,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7512345/v1/9bd4dd6662613151146ab3fb.docx"}],"financialInterests":"","formattedTitle":"Contribution of microbial necromass to soil organic carbon and its influencing factors under diverse ecosystems in Southwest China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSoil organic carbon (SOC) represents a major reservoir within terrestrial C stocks and has been increasingly emphasized as an essential nature-based approach for alleviating human-induced climate change and mitigating land degradation (Crowther et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tong et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Over the past two decades, afforestation on former croplands in southwest China has led to a marked increase in SOC stocks (Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), This SOC accumulation is primarily attributed to enhanced root exudation, continuous litter input, and the alleviation of tillage-induced soil disturbance (He et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ni et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In parallel, conservation tillage practices \u0026mdash;such as no-till combined with straw mulching\u0026mdash;have been widely recognized as an effective SOC sequestration strategy in agroecosystems. These practices yield comparable C accrual rates (0.3\u0026ndash;0.9 Mg C ha⁻\u0026sup1; yr⁻\u0026sup1;) by minimizing soil structural disturbance, maintaining optimal surface residue cover, and improving nutrient-use efficiency through precision management (Liu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Across these contrasting ecosystems, microbial necromass C (MNC) represents a principal source of stabilized SOC, accounting for approximately 33\u0026ndash;58% of soil C, with its dynamics directly linked to balance between microbial catabolic degradation and anabolic biomass synthesis (Liang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Given the tight coupling of microbial metabolism and nutrient cycles (Yang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), MNC could exhibits divergent accumulation patterns between conservation tillage and planted forest ecosystems driven by contrasting nutrient availability and stoichiometry, consequently on SOC formation and stability (Liu et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, the underlying mechanisms regulating MNC dynamics across ecosystems and their link to longer SOC accrual remain poorly understood.\u003c/p\u003e\u003cp\u003eEmpirically, microorganisms transform plant-derived C and native SOC into cellular components or byproducts through anabolism, and their necromass act as persistent components to mediate soil long-term C sequestration (soil Microbial C Pump theory, sMCP) (Liang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This stabilization is attributed to the inherent recalcitrance of microbial necromass\u0026mdash;such as chitin, peptidoglycans, and glycoproteins\u0026mdash;which are resistant to enzymatic decomposition, as well as to their physicochemical protection within the soil matrix (Buckeridge et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Accordingly, the formation, accumulation, and transformation of necromass C in soils are strongly influenced by microbial intrinsic traits (e.g., community composition and nutrient limitations) and environmental drivers (e.g., nutrient availability, tillage practices, and land-use changes) (Buckeridge et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Generally, soil microorganisms persist in a state of chronic of energy (C) and nutrient limitation (Hill et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Moorhead et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Under such conditions, microbial physiological activities are substantially reduced, as energy is preferentially allocated to maintenance metabolism (e.g., sustaining essential cellular functions for survival) at the expense of biomass synthesis (Shao et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This shift constrains necromass C production and thus impairs sMCP efficiency. Concurrently, soil microorganisms could secrete specific extracellular enzymes to prioritize the recycling of necromass as a nutrient source due to its high nutrient content (Bhople et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The hydrolysis of necromass components significantly contributes to the formation of bioavailable N and P pools, representing a more efficient strategy than acquiring nutrients from bulk SOM (Pausch et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This enzymatic recycling further accelerates MNC degradation, reducing its contribution to SOC accumulation (Wang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These findings collectively emphasize the fundamental role of microbial metabolic pathways and substrate availability in regulating MNC formation. A more comprehensive understanding of MNC patterns across diverse ecosystems, along with their contribution to SOC persistence, is critical for refining predictive models of soil carbon sequestration under large-scale ecological restoration frameworks.\u003c/p\u003e\u003cp\u003eAfforestation of former croplands serves as a critical approach for boosting SOC sequestration, primarily through continuous inputs of plant-derived organic materials (Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stutter et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These inputs not only supply a steady stream of organic C but also, through hydrolysis, significantly enhance the formation of bioavailable dissolved organic N and P pools, thereby synergistically promoting SOC formation and accumulation via improving microbial necromass formation (Stutter et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Although afforestation introduces additional nutrients, these inputs do not consistently enhance SOC stocks (Hong et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), as their effects depend on initial soil C levels and potential stimulation of microbial activity that may trigger priming-induced losses of native SOC (Dijkstra et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). A previous study reported that elevated P levels in monoculture plantations have no significant impact on SOC stocks (Li et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This is attributed to a trade-off induced by afforestation between microbial carbon and nutrient limitations: while afforestation alleviates microbial P limitation, it concurrently exacerbates co-limitation by C and N (Xia et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This imbalance prompts microbes to accelerate the decomposition of mocrobial necromass, thereby offsetting potential SOC gains from increased nutrient availability and resulting in minimal net change in SOC stocks (Cui et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn parallel, a range of conservation tillage practices in croplands, such as no-tillage, cover crops, stover mulching and integrated nutrient management, have been widely recognized for their capacity to enhance SOC sequestration (Oliveira et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Specifically, straw return, which is functionally analogous to litter input in plantation ecosystems, introduces substantial amounts of plant-derived organic matter into the soil (typically ensuring at least 30% surface coverage by crop residues), thereby effectively promoting SOC accumulation (Zhang et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Theoretically, these conservation practices create favorable microenvironments by regulating soil temperature and moisture conditions (Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), thereby enhancing microbial biomass synthesis and facilitating the continuous microbial-driven iterative process of soil C fixation, are important to enhance SOC sequestration from MNC in agroecosystems (Huber et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A recent meta-analysis further demonstrates that conservation tillage significantly enhances the activities of extracellular enzymes associated with C, N, P, and sulfur (S) cycling, with increased enzyme activity being positively correlated with SOC changes (Zhu et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Due to variations in environmental constraints and nutrient dynamics, afforestation and conservation tillage may result in divergent patterns of MNC accumulation and its contribution to SOC stabilization (Hong et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the distinctions in microbial pathways of SOC accrual and their dominant controlling factors between these two land-use strategies have not been thoroughly explored, which limits our ability to fully understand and manage soil C sequestration and ecosystem sustainability.\u003c/p\u003e\u003cp\u003eTo address the identified knowledge gaps, we conducted soil sampling at depths of 0\u0026ndash;20 cm and 20\u0026ndash;40 cm along an elevational gradient (1,280\u0026ndash;3,269 m) in conservation tillage systems (integrating no-tillage and cover cropping) and Pinus yunnanensis\u0026ndash;dominated planted forests in the Yanggong River Basin, northwestern Yunnan Province, China. In this study, we quantified amino sugars as biomarkers of bacterial, fungal, and total microbial necromass to assess MNC content and its contribution to SOC. We also measured soil nutrient levels, microbial extracellular enzyme activities, and their stoichiometric ratios to evaluate microbial nutrient limitations. The objectives were 1) to quantify the bacterial, fungal, and total MNC and their contributions to SOC in conservation tillage and planted forests ecosystem across elevational gradient, and 2) to identify key soil nutrients and enzymes influencing microbial pathways of SOC accrual in different ecosystems. The findings will elucidate microbial mechanisms underlying soil C sequestration in contrasting land-use systems and provide a scientific basis for optimizing ecological restoration and soil C management in subtropical regions under climate change and land degradation.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Site description and experimental design\u003c/h2\u003e\u003cp\u003eThis study was conducted in the Yanggong River Basin (approximately 26\u0026deg;30\u0026prime;\u0026ndash;27\u0026deg;10\u0026prime;N, 99\u0026deg;40\u0026prime;\u0026ndash;100\u0026deg;20\u0026prime;E), situated in the northwest of Yunnan Province, China. The region experiences a typical subtropical monsoon climate, with a mean annual temperature of 15\u0026deg;C and mean annual precipitation ranging from 1,000 to 1,200 mm. The Yanggong River Basin is characterized by its complex topography, with elevations varying from approximately 1,215 meters in the river valleys to over 5,467 meters in the high-altitude mountainous areas. Precipitation is abundant but unevenly distributed throughout the year, with the majority of rainfall concentrated during the summer monsoon season.\u003c/p\u003e\u003cp\u003eDue to the widespread distribution of karst landforms within study area, soil erosion and rocky desertification are prominent issues. To address these challenges, the government has implemented soil and water conservation projects and comprehensive rocky desertification control measures, including afforestation, the conversion of tillage to forests, and the promotion of conservation agriculture techniques. To evaluate the impact of these ecological restoration efforts on SOC, systematic soil sampling was conducted in both planted forests and conservation tillage across different elevation gradients within the Yanggong River Basin. Soil samples were collected from the depth of 0\u0026ndash;20 cm (herein defined as topsoil) and 20\u0026ndash;40 cm (herein defined as subsoil) in each plot, respectively, between May 9 and 22, 2023. After removing surface litter, 10 core samples were collected using a stainless-steel corer (5 cm diameter) along an S-shape pattern from each soil layer within each plot. The core samples were pooled and homogenized into a single sample. A total of 50 soil samples were collected from 13 planted forest sites and 12 conservation tillage sites, with samples taken from two soil layers at each site. Each soil sample was divided into two subsamples, which were then sieved through a 2-mm mesh to remove stones and coarse roots. The first part was stored at 4\u0026deg;C for the measurement of soil enzyme activities. The second part was air-dried for the analyses of soil abiotic properties and amino sugars.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Soil abiotic and biotic variables\u003c/h2\u003e\u003cp\u003eSoil organic carbon (SOC) was quantified using the dichromate oxidation method as described by Walkley and Black (1934). Total nitrogen (TN) and total phosphorus (TP) were analyzed via the Kjeldahl digestion procedure and the vanadium molybdate yellow colorimetric method, respectively. The C:N:P stoichiometric ratios were subsequently calculated based on the measured concentrations of SOC, TN, and TP.\u003c/p\u003e\u003cp\u003eSoil enzyme activities, including hydrolases (β-glucosidase (BG), acid phosphatase (AP), N-acetyl-β-glucosaminidase (NAG), and leucine aminopeptidase (LAP)) and oxidases (polyphenol oxidase (PPO) and peroxidase (PER)), were determined using colorimetric methods. For hydrolases, soil samples were incubated with specific substrates (e.g., p-nitrophenyl derivatives for BG, AP, and NAG; L-leucine-p-nitroanilide for LAP) in appropriate buffers at 37\u0026deg;C for 1 h. The reactions were terminated by adding alkaline or acidic solutions, and the released p-nitrophenol (pNP) or p-nitroaniline (pNA) was measured spectrophotometrically at 400\u0026ndash;410 nm. For oxidases, PPO activity was determined by incubating soil with L-3,4-dihydroxyphenylalanine (L-DOPA) and measuring the absorbance of quinone-like products at 460 nm, while PER activity was assessed using pyrogallol and hydrogen peroxide, with absorbance measured at 470 nm. All enzyme activities were expressed as \u0026micro;mol of product released per gram of dry soil per hour (\u0026micro;mol\u0026middot;g⁻\u0026sup1;\u0026middot;h⁻\u0026sup1;) (DeForest and Moorhead, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStoichiometric analysis of soil enzyme activities was used to identify potential C, N and P limitations in the soil. The enzymatic stoichiometric vector characteristics (including vector length and vector angle) were calculated according to Moorhead et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These values were used as a rough reflection of microbial nutrient limitation: A greater vector length is indicative of microbial C limitation, while a vector angle below 45\u0026deg; suggests N limitation; angles exceeding this threshold denote P limitation (DeForest and Moorhead, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Microbial resource limitation was classified into four categories\u0026mdash;N limitation, P limitation, co-limitation by C and N, and co-limitation by C and P\u0026mdash;based on a reference framework in which the x-axis (NAG\u0026thinsp;+\u0026thinsp;LAP/AP) and y-axis (BG/NAG\u0026thinsp;+\u0026thinsp;LAP) enzyme activity ratios are standardized to a baseline value of 1.0. The vector length and angle were computed according to Equations (1) and (2):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Vector\\:Length=\\sqrt{{\\left(\\frac{\\text{ln}\\left(\\text{B}\\text{G}\\right)\\:}{\\text{l}\\text{n}\\left(\\text{N}\\text{A}\\text{G}+\\text{L}\\text{A}\\text{P}\\right)}\\right)}^{2}+{\\left(\\frac{\\text{ln}\\left(\\text{B}\\text{G}\\right)\\:}{\\text{l}\\text{n}\\left(\\text{A}\\text{P}\\right)}\\right)}^{2}}\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Vector\\:Angle=\\text{D}\\text{E}\\text{G}\\text{R}\\text{E}\\text{E}\\text{S}\\left\\{\\text{A}\\text{T}\\text{A}\\text{N}2\\left[\\frac{\\text{ln}\\left(\\text{B}\\text{G}\\right)}{\\text{l}\\text{n}\\left(\\text{A}\\text{P}\\right)},\\frac{\\text{ln}\\left(\\text{B}\\text{G}\\right)}{\\text{l}\\text{n}\\left(\\text{N}\\text{A}\\text{G}+\\text{L}\\text{A}\\text{P}\\right)}\\right]\\right\\}\\:\\:\\:\\left(2\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Microbial necromass carbon\u003c/h2\u003e\u003cp\u003eAmino sugars, including glucosamine, mannosamine, and muramic acid, were quantified following Zhang and Amelung (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Soil samples (0.3 mg N) and standards were hydrolyzed in 6 M HCl at 105\u0026deg;C for 8 h. After cooling, myo-inositol was added as an internal standard. The hydrolysate was filtered, evaporated, reconstituted in deionized water, adjusted to pH 6.6\u0026ndash;6.8, centrifuged, and freeze-dried. Amino sugars were extracted with methanol, and N-methyl-D-glucamine was added as a second internal standard. Derivatization involved reaction with hydroxylamine hydrochloride and 4-(dimethylamino) pyridine at 75\u0026ndash;80\u0026deg;C, followed by acetylation with acetic anhydride. Aldononitrile derivatives were extracted with dichloromethane, washed, dried under N₂, and redissolved in ethyl acetate\u0026ndash;hexane (1:1). Separation was performed using gas chromatography (GC-2014C, Shimadzu) with a DB-5 column. Fungal and bacterial necromass were estimated using equations (\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and (\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e4\u003c/span\u003e) (Liang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\text{F}\\text{u}\\text{n}\\text{g}\\text{a}\\text{l}\\:\\text{n}\\text{e}\\text{c}\\text{r}\\text{o}\\text{m}\\text{a}\\text{s}\\text{s}\\:\\text{C}=\\left(\\frac{\\text{g}\\text{l}\\text{u}\\text{c}\\text{o}\\text{s}\\text{a}\\text{m}\\text{i}\\text{n}\\text{e}\\:}{179.17}-\\frac{2\\times\\:\\:\\text{m}\\text{u}\\text{r}\\text{a}\\text{m}\\text{i}\\text{c}\\:\\text{a}\\text{c}\\text{i}\\text{d}}{251.23}\\right)\\times\\:179.17\\times\\:9\\:\\:\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\text{B}\\text{a}\\text{c}\\text{t}\\text{e}\\text{r}\\text{i}\\text{a}\\text{l}\\:\\text{n}\\text{e}\\text{c}\\text{r}\\text{o}\\text{m}\\text{a}\\text{s}\\text{s}\\:\\text{C}=\\text{m}\\text{u}\\text{r}\\text{a}\\text{m}\\text{i}\\text{c}\\:\\text{a}\\text{c}\\text{i}\\text{d}\\times\\:45\\:\\:\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHere, glucosamine and muramic acid have molecular weights of 179.17 and 251.23, respectively, with conversion factors of 9 and 45 used to estimate fungal and bacterial necromass C (Appuhn and Joergensen, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Joergensen, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Total microbial necromass C (MNC) was derived by summing fungal-derived C (FNC) and bacterial-derived C (BNC). The MNC:SOC ratio was used to indicate the contribution of microbial necromass to SOC stabilization (Liang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Statistical analyses\u003c/h2\u003e\u003cp\u003eData normality and homoscedasticity were evaluated using the Shapiro\u0026ndash;Wilk and Levene\u0026rsquo;s tests, respectively. When necessary, natural log-transformation was applied to meet parametric assumptions. Subsequently, linear mixed-effects models were fitted using the lme4 package in R to assess the effects of ecosystem type, soil depth, and their interaction on soil properties, enzyme activities, and microbial necromass carbon (MNC). Post-hoc comparisons were conducted with Tukey\u0026rsquo;s HSD test to determine significant differences among means across treatments. Linear regression analyses were performed using base R functions to examine associations between SOC, MNC components, soil nutrients, and enzyme activities along elevation gradients, with regression lines and significance visualized via ggplot2. Redundancy analysis (RDA) was conducted using the vegan package to identify relationships among soil nutrients, extracellular enzyme activities, and MNC fractions. Hierarchical partitioning (hier.part package) was employed to quantify the independent contributions of these variables to SOC variation. Pearson correlation analysis further assessed pairwise relationships among SOC, MNC, enzyme activities, and nutrients. Finally, structural equation modeling (SEM) was implemented using the piecewiseSEM package to disentangle the direct and indirect pathways through which ecosystem type, soil depth, enzyme activities, MNC, and nutrients influence SOC dynamics. All statistical analyses were performed in R (version 4.0.3), with significance thresholds set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05..\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Microbial necromass C and its contribution to SOC\u003c/h2\u003e\u003cp\u003eOverall, the contents of bacterial, fungal, and total microbial necromass C and their contributions to SOC in conservation tillage were significantly higher than that in planted forest (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Specially, fungal and total microbial necromass C contents were significantly higher in the topsoil of conservation tillage compared to the subsoil, while bacterial necromass C contents were significantly higher in the topsoil of planted forests (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-c). Further, we found the contribution of bacteria necromass C to SOC in the conservation tillage was also significantly higher in subsoil compared to topsoil (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). Regardless of ecosystem type, the contents of bacterial, fungal, and total microbial necromass C, as well as the contribution of fungal necromass C to SOC, showed no significant relationship with elevation (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Figs. S1), while the ratios of bacterial and total microbial necromass C to SOC decreased significantly with increasing elevation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Soil abiotic and biotic variables\u003c/h2\u003e\u003cp\u003eWith the exception of C/P and N/P ratios, soil nutrient properties (SOC, TN, TP and C/N ratio) were found to be significantly influenced by ecosystem type (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-d). Regardless of ecosystem type, the contents of SOC and TN were greater in the topsoil than in the subsoil (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b), while TP and N/P ratio showed no significant differences between soil depths (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and f). Furthermore, higher C/N and C/P ratios in the topsoil were exclusively observed in the conservation tillage system (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec-d).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding to extracellular enzyme activity and vector characteristics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-i), ecosystem type only had significant effects on the activity of PPO (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee ). The activities of four hydrolases were generally higher in the topsoil than in the subsoil in both ecosystems (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-d), while oxidases showed no significant differences between soil depths (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee-h). Vector analysis and extracellular enzyme stoichiometry revealed that soil microorganisms in both conservation tillage and planted forest ecosystems were primarily limited by P, rather than N (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh\u0026ndash;k). In addition, microbial C limitation showed no significant difference between conservation tillage and planted forests (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ei). Overall, most soil abiotic and biotic variables showed no significant correlation with elevation (Figs. S2 and S3). However, in planted forests, SOC, TN, and LAP activity exhibited significant positive correlations with elevation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Correlations of microbial necromass C with soil biotic and abiotic factors\u003c/h2\u003e\u003cp\u003eAccording to redundancy analysis (RDA), abiotic and biotic variables (excluding SOC) collectively explained 74.88% (RDA1: 68.96%; RDA2: 5.92%) of the total variation in microbial necromass C (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Specifically, TN content and AP activity emerged as the most influential factors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). In contrast, the activities of LAP, NAG, and PER, as well as microbial nutrient limitations, had negligible effects on microbial necromass C (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegression analysis demonstrated significant positive correlations between bacterial, fungal, and total microbial necromass C with TN, TP, AP, and PER (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Figs. S5-S7). Specifically, the soil N/P ratio showed a significant positive correlation only with bacterial and total microbial necromass C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig. S5). Additionally, the contribution of bacterial and total microbial necromass C to SOC were significantly negatively correlated with the C/N and C/P ratios, as well as with the activities of BG, AP, and NAG. Conversely, these ratios were positively correlated with the vector angle (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig. S6). Furthermore, TN was significantly positively correlated with the ratio of fungal necromass carbon to SOC, while showing a significant negative correlation with the contribution of bacteria necromass C to SOC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Regulation of microbial traits and soil nutrients on SOC\u003c/h2\u003e\u003cp\u003eThe results of hierarchical partitioning analysis revealed that soil nutrient parameters accounted for a substantially larger proportion of the cumulative variance (40.61%) in SOC content compared to microbial necromass C (32.77%) and extracellular enzyme activity (10.61%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Overall, SOC content exhibited positive correlations with fungal and bacterial microbial necromass C, the activity of AP, as well as TN, C/P, and C/N ratios. In contrast, SOC content showed a negative correlation with the ratio of bacterial microbial necromass C to SOC in both conservation tillage and planted forest (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Notably, SOC was significantly positively correlated with the activities of PPO, BG, NAG, and the ratio of bacterial microbial necromass C to SOC exclusively in conservation tillage, while it demonstrated a significant positive correlation with TP only in planted forest (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig. S8).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAdditionally, structural equation modeling (SEM) was employed to analyze the relationships among microbial necromass C, soil nutrients, enzyme activities, soil depth, and ecosystem types with SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The results demonstrated that the model exhibited a high level of fit, effectively explaining the interactions among the relevant variables. Consistent with hierarchical partitioning analysis, the SEM analysis revealed that SOC was predominantly and directly influenced by soil nutrients, followed by microbial necromass C. Furthermore, soil nutrients indirectly affected SOC through their direct effects on microbial necromass C. Ecosystem type had a significant direct impact on SOC, indicating that different ecosystems play a crucial regulatory role in SOC levels. Although soil depth did not exhibit a significant direct effect on SOC, it was indirectly associated with SOC via soil nutrients. In contrast, enzyme activities had a relatively weak influence on SOC, with only AP demonstrating a positive effect.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Higher MNC in conservation tillage than planted forest ecosystems\u003c/h2\u003e\u003cp\u003eMicrobial necromass C is primarily derived from bacterial and fungal sources (Liang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this study, bacterial, fungal, and total microbial necromass carbon were significantly greater in conservation tillage systems than in planted forest ecosystems (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Meta-analytic evidence indicates that microbial necromass carbon (MNC) constitutes approximately 55.6% of SOC in agricultural soils, substantially higher than the 32.6% observed in forest soils (Liang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This study further supports the view that MNC is the primary driver of SOC accumulation in agriculture ecosystems, especially for conservation tillage. There are potentially reasons for this. Firstly, compared to planted forest ecosystems, the plant residues introduced through straw return practices in agricultural ecosystems (such as crop straw and roots) typically have a lower C/N ratio (Surigaoge et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), making them more easily decomposed and utilized by microorganisms, thereby providing a substantial amount of precursor material for the accumulation of microbial necromass (Cui et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This explanation was supported by the lower C/N ratio and higher N content in conservation tillage ecosystems compared to planted forest ecosystems (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUnder nitrogen-limited conditions, the rapid turnover of microbial necromass\u0026mdash;characterized by lower C/N ratios than plant litter and bulk SOM\u0026mdash;is closely coupled with soil nitrogen cycling. This renders necromass recycling, wherein living microbes consume necromass to access nitrogen, an efficient strategy for meeting microbial N demands (Buckeridge et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The study sites are situated within a subtropical climatic zone, with numerous studies conducted in similar subtropical ecosystems, where P is often reported as the primary limiting nutrient for soil microbial communities (Cui et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Du et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This result aligns with evidence from extracellular enzyme stoichiometry and vector analysis, both of which indicate phosphorus rather than nitrogen as the primary limiting nutrient (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast to N-limited systems, the higher N availability in our study sites likely reduces the reliance on necromass recycling as a strategy for N acquisition. This is particularly evident in conservation tillage ecosystems, where elevated soil N content may prevent extensive necromass recycling, thereby promoting the long-term stabilization and accumulation of microbial necromass C. Indeed, our results demonstrate that soil TN is the most significant factor influencing MNC, showing a highly significant positive correlation with MNC accumulation (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Third, the greatly accumulation of MNC in conservation tillage ecosystems is closely linked to tillage practices, as conventional tillage causes significant SOC loss (Ye et al., 2020). In contrast, no-till or reduced tillage have been shown to increase MNC content by up to 20% (Zhou et al., 2020), demonstrating that tillage practices critically regulate SOC dynamics through microbial necromass pathways (Huber et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In summary, through the combined effects of optimized nutrient conditions, reduced soil disturbance, conservation tillage systems create a more favorable soil environment for the accumulation and stabilization of microbial necromass, thereby achieving higher SOC sequestration efficiency compared to afforested ecosystems.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Key factors regulating microbial necromass C\u003c/h2\u003e\u003cp\u003eIn the current study, soil TN, TP, and C-N-P stoichiometry significantly influenced soil microbial necromass, with these effects being more pronounced than those of soil microbial extracellular enzyme activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). As above mention, this finding can be attributed to the direct role of soil nutrients, particularly N, in driving microbial growth, reproduction, and subsequent necromass accumulation (Yang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, the influence of soil nutrients on microbial necromass extends beyond merely providing essential substrates for microbial metabolism; it also plays a critical role in shaping microbial community structure and metabolic strategies (Wang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This, in turn, governs the trade-offs among key microbial functions, including biosynthesis, stress tolerance, and extracellular enzyme production (Klappenbach et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), as exemplified by elevated N availability in soils with higher C resources, which enhances microbial abundance and prioritizes growth-related functions over energy-intensive processes, thereby promoting greater necromass accumulation (Shao et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In contrast, extracellular enzyme activity primarily mediates the short-term decomposition of organic matter by breaking down complex substrates into simpler forms, yet its impact on long-term necromass stabilization is indirect and secondary (Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn terms of extracellular enzymes and stoichiometry, the accumulation of microbial necromass C is primarily associated with microbial P-acquiring enzymes (AP), while the influence of N-acquiring enzymes (NAG and LAP) is not significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This phenomenon can be attributed to the predominant P limitation for microbial activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), where the activity of AP alleviates P constraints, thereby promoting necromass accumulation (Yuan et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhai et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This explanation was supported by the positive effects of TP on microbial necromass C (Fig. S5). However, the contribution of bacterial necromass C, rather than fungal necromass, to SOC shows a negative correlation with AP activity (Fig. S6). These findings may stem from a trade-off metabolic strategy, bacterial transferred more energy from microbial CUE to P acquisition via P-acquiring enzymes production (Zhai et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As a result, the accumulation of bacterial necromass gain from P acquisition does not offset the consume of native SOC during the P acquisition process. This implies that bacterial-driven P cycling may hinder SOC long-term accumulation under P-limitation condition (Wu et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Previous research has identified oxidative enzymes as playing a crucial role in microbial necromass accumulation, with their activity promoting the decomposition of lignin, phenolic acids, and other plant-derived compounds, thereby enhancing the conversion of plant-derived SOC into MNC(Shi et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, in our study, we found that microbial necromass accumulation is significantly positively correlated with PPO activity but shows no correlation with PER activity (Fig. S7). This discrepancy can be attributed to the distinct functional roles of these enzymes, with PPO primarily degrading recalcitrant, C-rich compounds in soil, such as lignin and phenolic acids, which facilitates the formation of stable organic matter and promotes necromass accumulation (Zhao et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This inference is further supported by the significant positive correlation between PPO activity and soil C/P ratios, whereas PER shows no significant relationship with C/P (Fig. S5).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Microbial necromass driving SOC accumulation\u003c/h2\u003e\u003cp\u003eCompelling evidence has established that microbial necromass C, as a primary stable form of soil C pools, plays a central role in the long-term accumulation of SOC (Hu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our results demonstrate that the contribution of bacterial, fungal, and total microbial necromass C are significantly higher in conservation tillage ecosystems compared to planted forest ecosystems (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Evidently, the substantial SOC accumulation observed in conservation tillage ecosystems could be largely attributed to microbial necromass C (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In detail, we observe that the contribution of bacterial necromass C to SOC (3.37%-82.12%) were higher than fungal necromass C (0.70%-33.18%), regardless of ecosystems (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In terms of conservation tillage croplands, pervious study has reported that fungal necromass contributes more to SOC than bacteria in northeastern China (Liu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which is inconsistent with the findings of our study. The observed regional differences may be explained by contrasting N dynamics in these agricultural systems. In particular, the lower soil C/N ratios characteristic of southwestern China's croplands appear to mitigate the N limitation typically constraining bacterial growth, resulting in proportionally greater bacterial necromass accumulation relative to the N-rich but higher C/N ratio soils of northeastern China (Li et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Indeed, we only observed a significant positively relationship between decreased N-limitation and the contribution of bacterial necromass C to SOC (Fig. S6).\u003c/p\u003e\u003cp\u003eAlthough we observed a positive effect of the content of bacterial necromass C on SOC accumulation, the contribution of bacterial necromass C to SOC negativity related to SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This suggests that there was an unproportionally increase in bacterial necromass C accrual rate compared to SOC both in conservation tillage and planted forests ecosystems. In other words, organic carbon components from other pathways\u0026mdash;such as lignin derivatives and fungal necromass\u0026mdash;likely exhibit higher transformation and stabilization efficiency in soils, accumulating more effectively than bacterial necromass C and serving as dominant drivers of long-term SOC accumulation (Yin et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Actually, we did observe that fungal necromass C plays a more significant role in explaining the variation in SOC than bacterial necromass C, as the increase in fungal necromass C significantly promotes SOC accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). As above mentioned, an explanation for this pattern is that fungal necromass C is more stable than bacterial necromass C (Xue et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which can partially be supported by unchanged contribution from fungi necromass in response both biotic and abiotic factors, as well as elevation, while bacterial necromass C not. On the other hand, studies have reported that bacterial necromass C plays an important role in fungal necromass C accumulation, as fungal communities can metabolize bacterial necromass, thereby promoting their own necromass buildup and forming a stronger association with SOC (Camenzind et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study elucidates the convergent microbial necromass pathways governing SOC sequestration in subtropical China, demonstrating that MNC\u0026mdash;fundamentally regulated by soil TN\u0026mdash;serves as the predominant driver of SOC accumulation in both conservation tillage and afforested ecosystems. Conservation tillage systems exhibited superior MNC accrual compared to planted forest ecosystems, attributable to optimized nutrient stoichiometry and reduced necromass turnover, with fungal necromass displaying greater stabilization efficiency and predictive power for SOC persistence than its bacterial counterpart despite lower quantitative contributions. These findings challenge conventional afforestation-based C sequestration paradigms, revealing that conservation tillage practices\u0026mdash;through enhanced nutrient retention and minimized soil disturbance\u0026mdash;more effectively promote microbial-derived SOC stabilization in subtropical regions. The identification of microbial necromass as the central nexus in soil C cycling, with tillage management outweighing afforestation in controlling sequestration outcomes, provides a mechanistic foundation for optimizing land-use strategies to enhance carbon storage in vulnerable ecosystems under climate change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grants No. 32471963, 42371066, 31971729), the 5·5 Engineering Research \u0026amp; Innovation Team Project of Beijing Forestry University (BLRC2023B09), the Yunnan Provincial Key Research and Development Program (202403AC100042), and the Geological Survey Project (DD20220879).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest, financial or otherwise, that could have influenced the outcomes of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAppuhn A, Joergensen RG (2006) Microbial colonisation of roots as a function of plant species. Soil Biol Biochem 38:1040\u0026ndash;1051. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2005.09.002\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2005.09.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBhople P, Keiblinger K, Djukic I, Liu D, Zehetner F, Zechmeister-Boltenstern S, Joergensen G, Murugan R, R (2021) Microbial necromass formation, enzyme activities and community structure in two alpine elevation gradients with different bedrock types. Geoderma 386:114922. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.geoderma.2020.114922\u003c/span\u003e\u003cspan address=\"10.1016/j.geoderma.2020.114922\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBuckeridge KM, Creamer C, Whitaker J (2022) Deconstructing the microbial necromass continuum to inform soil carbon sequestration. Funct Ecol 36:1396\u0026ndash;1410. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1365-2435.14014\u003c/span\u003e\u003cspan address=\"10.1111/1365-2435.14014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBuckeridge KM, Mason KE, McNamara NP, Ostle N, Puissant J, Goodall T, Griffiths RI, Stott AW, Whitaker J (2020) Environmental and microbial controls on microbial necromass recycling, an important precursor for soil carbon stabilization. Commun Earth Environ 1:36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s43247-020-00031-4\u003c/span\u003e\u003cspan address=\"10.1038/s43247-020-00031-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCamenzind T, Mason-Jones K, Mansour I, Rillig MC, Lehmann J (2023) Formation of necromass-derived soil organic carbon determined by microbial death pathways. Nat Geosci 16:115\u0026ndash;122. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41561-022-01100-3\u003c/span\u003e\u003cspan address=\"10.1038/s41561-022-01100-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen J, Luo Y, Van Groenigen KJ, Hungate BA, Cao J, Zhou X, Wang R (2018) A keystone microbial enzyme for nitrogen control of soil carbon storage. Sci Adv 4:eaaq1689. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/sciadv.aaq1689\u003c/span\u003e\u003cspan address=\"10.1126/sciadv.aaq1689\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCrowther TW, Van Den Hoogen J, Wan J, Mayes MA, Keiser AD, Mo L, Averill C, Maynard DS (2019) The global soil community and its influence on biogeochemistry. Science 365:eaav0550. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/science.aav0550\u003c/span\u003e\u003cspan address=\"10.1126/science.aav0550\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCui J, Zhu Z, Xu X, Liu S, Jones DL, Kuzyakov Y, Shibistova O, Wu J, Ge T (2020) Carbon and nitrogen recycling from microbial necromass to cope with C:N stoichiometric imbalance by priming. Soil Biol Biochem 142:107720. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2020.107720\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2020.107720\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCui Y, Bing H, Moorhead DL, Delgado-Baquerizo M, Ye L, Yu J, Zhang S, Wang X, Peng S, Guo X, Zhu B, Chen J, Tan W, Wang Y, Zhang X, Fang L (2022) Ecoenzymatic stoichiometry reveals widespread soil phosphorus limitation to microbial metabolism across Chinese forests. Commun Earth Environ 3:184. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s43247-022-00523-5\u003c/span\u003e\u003cspan address=\"10.1038/s43247-022-00523-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeForest JL, Moorhead DL (2020) Effects of elevated pH and phosphorus fertilizer on soil C, N and P enzyme stoichiometry in an acidic mixed mesophytic deciduous forest. Soil Biol Biochem 150:107996. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2020.107996\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2020.107996\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDijkstra FA, Carrillo Y, Pendall E, Morgan JA (2013) Rhizosphere priming: a nutrient perspective. Front Microbiol 4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmicb.2013.00216\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2013.00216\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDu E, Terrer C, Pellegrini AFA, Ahlstr\u0026ouml;m A, Van Lissa CJ, Zhao X, Xia N, Wu X, Jackson RB (2020) Global patterns of terrestrial nitrogen and phosphorus limitation. Nat Geosci 13:221\u0026ndash;226. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41561-019-0530-4\u003c/span\u003e\u003cspan address=\"10.1038/s41561-019-0530-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeyissa A, Raza ST, Cheng X (2023) Soil carbon stabilization and potential stabilizing mechanisms along elevational gradients in alpine forest and grassland ecosystems of Southwest China. CATENA 229, 107210. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.catena.2023.107210\u003c/span\u003e\u003cspan address=\"10.1016/j.catena.2023.107210\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHe T, Sun J, Hu B, Zhu T, Zhang W (2023) The importance of fine root protection in topsoil carbon and nitrogen sequestration following land-use changes on sloping karst ecosystems. CATENA 220:106660. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.catena.2022.106660\u003c/span\u003e\u003cspan address=\"10.1016/j.catena.2022.106660\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHill BH, Elonen CM, Seifert LR, May AA, Tarquinio E (2012) Microbial enzyme stoichiometry and nutrient limitation in US streams and rivers. Ecol Ind 18:540\u0026ndash;551. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecolind.2012.01.007\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolind.2012.01.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHong S, Yin G, Piao S, Dybzinski R, Cong N, Li X, Wang K, Pe\u0026ntilde;uelas J, Zeng H, Chen A (2020) Divergent responses of soil organic carbon to afforestation. Nat Sustain 3:694\u0026ndash;700. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41893-020-0557-y\u003c/span\u003e\u003cspan address=\"10.1038/s41893-020-0557-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu J, Du M, Chen J, Tie L, Zhou S, Buckeridge KM, Cornelissen JHC, Huang C, Kuzyakov Y (2023) Microbial necromass under global change and implications for soil organic matter. Glob Change Biol 29:3503\u0026ndash;3515. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.16676\u003c/span\u003e\u003cspan address=\"10.1111/gcb.16676\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuber S, Rosinger C, Bodner G, Bernardini LG, Bieber M, Mentler A, Sae-Tun O, Scharf B, Keiblinger KM (2024) Highway to health: Microbial pathways of soil organic carbon accrual in conservation farming systems. Geoderma 452:117115. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.geoderma.2024.117115\u003c/span\u003e\u003cspan address=\"10.1016/j.geoderma.2024.117115\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJoergensen RG (2018) Amino sugars as specific indices for fungal and bacterial residues in soil. Biol Fertil Soils 54:559\u0026ndash;568. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00374-018-1288-3\u003c/span\u003e\u003cspan address=\"10.1007/s00374-018-1288-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKlappenbach JA, Dunbar JM, Schmidt TM (2000) rRNA Operon Copy Number Reflects Ecological Strategies of Bacteria. Appl Environ Microbiol 66:1328\u0026ndash;1333. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/AEM.66.4.1328-1333.2000\u003c/span\u003e\u003cspan address=\"10.1128/AEM.66.4.1328-1333.2000\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi Q, Jia W, Wu J, Wang L, Huang F, Cheng X (2023) Changes in soil organic carbon stability in association with microbial carbon use efficiency following 40 years of afforestation. CATENA 228:107179. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.catena.2023.107179\u003c/span\u003e\u003cspan address=\"10.1016/j.catena.2023.107179\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi X, Huang J, Qu C, Chen W, Chen C, Cai P, Huang Q (2022) Diverse regulations on the accumulation of fungal and bacterial necromass in cropland soils. Geoderma 410:115675. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.geoderma.2021.115675\u003c/span\u003e\u003cspan address=\"10.1016/j.geoderma.2021.115675\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi Y, Wu M, Zhao T, Mou Z, Li T, Zhang J, Wu W, Wang F, Zhang W, Wang J, Li Y, Hui D, Lambers H, Pe\u0026ntilde;uelas J, Sardans J, Liu Z (2024) Responses of soil organic carbon compounds to phosphorus addition between tropical monoculture and multispecies forests. Sci Total Environ 947:174672. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2024.174672\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2024.174672\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiang C, Amelung W, Lehmann J, K\u0026auml;stner M (2019) Quantitative assessment of microbial necromass contribution to soil organic matter. Glob Change Biol 25:3578\u0026ndash;3590. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.14781\u003c/span\u003e\u003cspan address=\"10.1111/gcb.14781\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiang C, Schimel JP, Jastrow JD (2017) The importance of anabolism in microbial control over soil carbon storage. Nat Microbiol 2:17105. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nmicrobiol.2017.105\u003c/span\u003e\u003cspan address=\"10.1038/nmicrobiol.2017.105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu D, Zhou Z, Iqbal S, Dou TT, Bonito G, Liu W, An S, Chater CCC, Perez-Moreno J, Che R, Jones DL, Yu F (2024) Fungal necromass contribution to carbon sequestration in global croplands: A meta-analysis of driving factors and conservation practices. Sci Total Environ 949:174954. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2024.174954\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2024.174954\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu M, Zheng S, Pendall E, Smith P, Liu J, Li J, Fang C, Li B, Nie M (2025) Unprotected carbon dominates decadal soil carbon increase. Nat Commun 16, 2008. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41467-025-57354-z\u003c/span\u003e\u003cspan address=\"10.1038/s41467-025-57354-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu X, Song X, Li S, Liang G, Wu X (2023) Understanding how conservation tillage promotes soil carbon accumulation: Insights into extracellular enzyme activities and carbon flows between aggregate fractions. Sci Total Environ 897:165408. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2023.165408\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2023.165408\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoorhead DL, Sinsabaugh RL, Hill BH, Weintraub MN (2016) Vector analysis of ecoenzyme activities reveal constraints on coupled C, N and P dynamics. Soil Biol Biochem 93:1\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2015.10.019\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2015.10.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNi J, Luo DH, Xia J, Zhang ZH, Hu G (2015) Vegetation in karst terrain of southwestern China allocates more biomass to roots. Solid Earth 6:799\u0026ndash;810. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5194/se-6-799-2015\u003c/span\u003e\u003cspan address=\"10.5194/se-6-799-2015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOliveira EM, Wittwer R, Hartmann M, Keller T, Buchmann N, Van Der Heijden MGA (2024) Effects of conventional, organic and conservation agriculture on soil physical properties, root growth and microbial habitats in a long-term field experiment. Geoderma 447:116927. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.geoderma.2024.116927\u003c/span\u003e\u003cspan address=\"10.1016/j.geoderma.2024.116927\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePausch J, Holz M, Zhu B, Cheng W (2024) Rhizosphere priming promotes plant nitrogen acquisition by microbial necromass recycling. Plant Cell Environ 47:1987\u0026ndash;1996. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/pce.14858\u003c/span\u003e\u003cspan address=\"10.1111/pce.14858\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShao P, Lynch L, Xie H, Bao X, Liang C (2021) Tradeoffs among microbial life history strategies influence the fate of microbial residues in subtropical forest soils. Soil Biol Biochem 153:108112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2020.108112\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2020.108112\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShi K, Sun Y, Zeng D-H, Sheng Z, Zhang Y, Lin G (2025) Oxidative enzymes underlie tree species effects on soil organic carbon stocks: A common garden test with eight tree species. Soil Biol Biochem 202:109715. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2025.109715\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2025.109715\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStutter MI, Shand CA, George TS, Blackwell MSA, Dixon L, Bol R, MacKay RL, Richardson AE, Condron LM, Haygarth PM (2015) Land use and soil factors affecting accumulation of phosphorus species in temperate soils. Geoderma 257\u0026ndash;258:29\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.geoderma.2015.03.020\u003c/span\u003e\u003cspan address=\"10.1016/j.geoderma.2015.03.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSurigaoge S, Yang H, Fornara D, Su Y, Du Y-H, Ren S-X, Zhang W-P, Li L (2025) Litter functional dissimilarity accelerates carbon and nitrogen release from the decomposition of straw but not root in maize/legume intercropping. Plant Soil 506:487\u0026ndash;502. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11104-024-06616-8\u003c/span\u003e\u003cspan address=\"10.1007/s11104-024-06616-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTong X, Brandt M, Yue Y, Horion S, Wang K, Keersmaecker WD, Tian F, Schurgers G, Xiao X, Luo Y, Chen C, Myneni R, Shi Z, Chen H, Fensholt R (2018) Increased vegetation growth and carbon stock in China karst via ecological engineering. Nat Sustain 1:44\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41893-017-0004-x\u003c/span\u003e\u003cspan address=\"10.1038/s41893-017-0004-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang B, Huang Y, Li N, Yao H, Yang E, Soromotin AV, Kuzyakov Y, Cheptsov V, Yang Y, An S (2022) Initial soil formation by biocrusts: Nitrogen demand and clay protection control microbial necromass accrual and recycling. Soil Biol Biochem 167:108607. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2022.108607\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2022.108607\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang D, Gao W, Wang J, Yin H (2024) Minimal impact of nitrogen addition on bacterial and fungal communities during fungal necromass decomposition in a subalpine coniferous plantation. Soil Biol Biochem 196:109499. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2024.109499\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2024.109499\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang T, Tian Z, Tunlid A, Persson P (2020) Nitrogen acquisition from mineral-associated proteins by an ectomycorrhizal fungus. New Phytol 228:697\u0026ndash;711. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/nph.16596\u003c/span\u003e\u003cspan address=\"10.1111/nph.16596\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu M, Chen L, Chen S, Chen Y, Ma J, Zhang Y, Pang D, Li X (2025) Soil microbial carbon and nitrogen limitation constraints soil organic carbon stability in arid and semi-arid grasslands. J Environ Manage 373:123675. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jenvman.2024.123675\u003c/span\u003e\u003cspan address=\"10.1016/j.jenvman.2024.123675\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXia Y, Pe\u0026ntilde;uelas J, Sardans J, Zhong X, Xu L, Yang Z, Yang Y, Yang L, Yue K, Fan Y (2024) Phosphorus addition accelerates soil organic carbon mineralization by desorbing organic carbon and increasing microbial activity in subtropical forest soils. Appl Soil Ecol 193:105166. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apsoil.2023.105166\u003c/span\u003e\u003cspan address=\"10.1016/j.apsoil.2023.105166\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu L, Zhang J, Hu P, Zhang W, Xiao L, Ye Y, Xiao D, Zhao J, Xiao J, Wang K (2023) Bedrock outcrops weakly promote rather than inhibit soil carbon sequestration after vegetation restoration. Sci Total Environ 858:159470. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2022.159470\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2022.159470\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXue Z, Qu T, Li X, Chen Q, Zhou Z, Wang B, Lv X (2024) Different contributing processes in bacterial vs. fungal necromass affect soil carbon fractions during plant residue transformation. Plant Soil 494:301\u0026ndash;319. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11104-023-06277-z\u003c/span\u003e\u003cspan address=\"10.1007/s11104-023-06277-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang L, Canarini A, Zhang W, Lang M, Chen Y, Cui Z, Kuzyakov Y, Richter A, Chen X, Zhang F, Tian J (2024) Microbial life-history strategies mediate microbial carbon pump efficacy in response to N management depending on stoichiometry of microbial demand. Glob Change Biol 30:e17311. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.17311\u003c/span\u003e\u003cspan address=\"10.1111/gcb.17311\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYin Q, Liu Y, Li J, Wu J, Wang, Yifan, Zhang H, Liu H, Jiang L, Yang J, Wang, Yidi, Jiang Y, Han X, Wang J (2025) Soil organic carbon formation in grassland ecosystems: Higher efficiency of roots than shoots and rhizodeposition. Soil Tillage Res 250:106523. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.still.2025.106523\u003c/span\u003e\u003cspan address=\"10.1016/j.still.2025.106523\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYuan Y, Li Y, Mou Z, Kuang L, Wu W, Zhang J, Wang F, Hui D, Pe\u0026ntilde;uelas J, Sardans J, Lambers H, Wang J, Kuang Y, Li Z, Liu Z (2021) Phosphorus addition decreases microbial residual contribution to soil organic carbon pool in a tropical coastal forest. Glob Change Biol 27:454\u0026ndash;466. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/gcb.15407\u003c/span\u003e\u003cspan address=\"10.1111/gcb.15407\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhai Z, Luo M, Yang Y, Liu Y, Chen X, Zhang C, Huang J, Chen J (2022) Trade-off between microbial carbon use efficiency and microbial phosphorus limitation under salinization in a tidal wetland. CATENA 209:105809. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.catena.2021.105809\u003c/span\u003e\u003cspan address=\"10.1016/j.catena.2021.105809\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang J, Zhang F, Yang L (2024) Continuous straw returning enhances the carbon sequestration potential of soil aggregates by altering the quality and stability of organic carbon. J Environ Manage 358:120903. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jenvman.2024.120903\u003c/span\u003e\u003cspan address=\"10.1016/j.jenvman.2024.120903\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang M, Che R, Cheng Z, Zhao H, Wu C, Hu J, Zhang S, Liu D, Cui X, Wu Y (2023) Decades of reforestation significantly change microbial necromass, glomalin, and their contributions to soil organic carbon. Agric Ecosyst Environ 346:108362. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.agee.2023.108362\u003c/span\u003e\u003cspan address=\"10.1016/j.agee.2023.108362\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, Amelung W (1996) Gas chromatographic determination of muramic acid, glucosamine, mannosamine, and galactosamine in soils. Soil Biol Biochem 28:1201\u0026ndash;1206. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0038-0717(96)00117-4\u003c/span\u003e\u003cspan address=\"10.1016/0038-0717(96)00117-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao Y, Liu C, Kang E, Li X, Deng Y, Feng X (2024) Plant\u0026ndash;microbe interactions underpin contrasting enzymatic responses to wetland drainage. Nat Clim Change 14:1078\u0026ndash;1086. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41558-024-02101-3\u003c/span\u003e\u003cspan address=\"10.1038/s41558-024-02101-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu Y, Zhang H, Wang Q, Zhu W, Kang Y (2024) Soil extracellular enzyme activity linkage with soil organic carbon under conservation tillage: A global meta-analysis. Eur J Agron 155:127135. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.eja.2024.127135\u003c/span\u003e\u003cspan address=\"10.1016/j.eja.2024.127135\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Microbial necromass carbon, Soil organic carbon, Conservation tillage, Planted forest","lastPublishedDoi":"10.21203/rs.3.rs-7512345/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7512345/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eBackground and aims\u003c/em\u003e Against the backdrop of accelerating climate change and land degradation, enhancing soil carbon (C) stocks through optimized land use has garnered global attention. Conservation tillage and planted forests represent two key ecological restoration strategies that can promote long-term soil organic C (SOC) sequestration.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMethods\u003c/em\u003e We quantified microbial necromass C (MNC) and a suite of soil properties to assess the contribution of MNC to SOC and its primary controls in conservation tillage systems(combining no-tillage and cover cropping) and planted forests, covering elevations from 1280 to 3269 m above sea level in Southwest China.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResults\u003c/em\u003e Unexpectedly, SOC and MNC exhibited no clear elevational trends, yet both were significantly affected by land-use type and soil depth. Furthermore, we found SOC was significantly higher under conservation tillage than in planted forests. This difference may be partially explained by the enhanced MNC accumulation. While bacterial necromass was more abundant, its contribution to SOC became proportionally smaller as SOC increased, suggesting limited effectiveness in long-term stabilization. Accordingly, the stronger correlation between fungal necromass and SOC, despite its lower abundance, may be attributed to its higher inherent stability, which enhances its contribution to long-term C sequestration. The key edaphic determinants governing SOC variability were associated with nutrient profiles, with nitrogenemerging as the predominant regulatory factor for both SOC and MNC accumulation across conservation tillage and planted forest ecosystems.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConclusion\u003c/em\u003e These findings offering critical insights into the microbial necromass pathways driving SOC sequestration in conservation tillage and planted forests ecosystems.\u003c/p\u003e","manuscriptTitle":"Contribution of microbial necromass to soil organic carbon and its influencing factors under diverse ecosystems in Southwest China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 10:10:47","doi":"10.21203/rs.3.rs-7512345/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3beabd16-5af4-4fed-bcf9-7a124b649c1b","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-09T15:01:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 10:10:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7512345","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7512345","identity":"rs-7512345","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}