Microbial community composition and soil organic carbon stabilization: A systematic review

Introduction

Soil organic carbon is one of the most consequential, yet most uncertain, components of the global carbon budget. Mineral soils hold somewhere between 1,500 and 2,400 Pg of carbon in their upper metre a figure that dwarfs both the atmospheric carbon pool and the carbon stored in living terrestrial vegetation (Tao et al., 2023) [45] . Small proportional shifts in this reservoir carry disproportionate implications for atmospheric CO 2 concentrations and, by extension, for global temperature trajectories. The question of what determines the formation and longevity of soil organic carbon has therefore attracted sustained scientific attention, particularly as climate warming is expected to alter the balance between carbon inputs from vegetation and carbon losses through microbial respiration. Through much of the twentieth century, SOC persistence was attributed principally to the chemical complexity of plant-derived compounds. The lignin-humus theory held that recalcitrant aromatic polymers resisted enzymatic attack and accumulated in soil as chemically stabilised humus. This framework provided an intuitive but ultimately flawed explanation: radioisotope tracing and high-resolution spectroscopic analyses progressively revealed that 'humic substances' as operationally defined do not exist as discrete molecular entities in most soils, and that chemically complex compounds do not necessarily persist longer than simpler ones (Schmidt et al., 2011; Lehmann & Kleber, 2015) [39,22] . The dominant paradigm has since shifted toward an ecosystem-property explanation: organic matter persists not because of what it is chemically, but because of where it is physically and who is decomposing it biologically. Two theoretical frameworks have been particularly influential in consolidating this new understanding. The Microbial Efficiency-Matrix Stabilization (MEMS) framework (Cotrufo et al., 2013) [5] proposed that labile, nitrogen-rich plant inputs not recalcitrant compounds are the primary precursors of stable SOM, because they are assimilated at higher CUE, channelling a greater fraction of carbon into microbial biomass and byproducts rather than CO 2 . The Microbial Carbon Pump concept (Liang et al., 2017) [25] formalised the pathway by which microbial residues principally cell-wall polysaccharides and structural proteins from dead cells accumulate as necromass and constitute a major fraction of the mineral-associated organic carbon pool that persists for decades to centuries. These frameworks converge on the idea that microbial community composition mediates the efficiency and chemical nature of organic matter processing, and therefore the quantity and stability of SOC that eventually forms. Yet the precise relationships between specific community attributes taxonomic diversity, functional guild composition, CUE, fungal-to-bacterial ratios and the formation of distinct SOC fractions remain an active research frontier. This systematic review synthesises the available evidence in a structured, transparent, and reproducible manner consistent with PRISMA 2020 reporting guidelines.

Methods

Literature Search Strategy

A systematic literature search was conducted independently across four databases: Web of Science (Core Collection), Scopus, PubMed, and Google Scholar during March 2025. The following search string was applied consistently across databases, with minor syntax adjustments for databasespecific query formats: ("microbial community composition" OR "soil microbiome" OR "fungal:bacterial ratio" OR "microbial diversity") AND ("soil organic carbon stabilization" OR "MAOC" OR "mineral-associated organic carbon" OR "microbial necromass" OR "carbon use efficiency" OR "SOC fractions") Secondary search strings targeted: "MEMS framework", "microbial carbon pump", "SOM persistence mechanisms", "necromass stabilization", "MAOC formation". The search covered publications from January 2010 to March 2025. No language restrictions were applied at the search stage, but only English-language studies were retained during eligibility screening.

Data Extraction

Data were extracted independently by two reviewers using a standardised data extraction form (Table 2). Discrepancies were resolved by consensus. The extraction form captures 16 fields per study covering bibliographic information, study design, microbial and SOC methods, key quantitative results, statistical approach, and quality assessment. No primary statistical re-analysis was conducted; all numerical values reported in the results and discussion sections are drawn directly from the cited primary studies.

Quality Assessment and Risk-of-Bias Scoring

Each eligible study was scored against seven quality criteria using a 0-2 scale per criterion (maximum total score = 14 points). Studies scoring ≥ 10 were rated High confidence; 6-9 Medium; ≤ 5 Low. The rubric is presented in Table 3. All quality assessments were conducted prior to examining study findings, to avoid confirmation bias.

Synthesis Approach

Given the heterogeneity of study designs, ecosystems, and microbial metrics across included studies, we conducted a narrative synthesis rather than formal meta-analysis for most outcomes. Where sufficient quantitative comparability existed (effect sizes on SOC from CUE, F:B ratio, and climate variables), we present forest plots illustrating effect magnitudes across studies, clearly labelled as descriptive illustration rather than pooled estimates. Pearson correlation coefficients and SEM path coefficients presented in figures are drawn from individual studies or their published metaanalytic outputs, not newly computed for this review.

Study Selection: PRISMA Flow Diagram

Conceptual Framework: MEMS and the Microbial Carbon Pump

Figure 2 presents the integrated conceptual framework organising the mechanistic synthesis. The MEMS framework (Cotrufo et al., 2013) [5] and Microbial Carbon Pump concept (Liang et al., 2017) [25] together describe two complementary but distinct pathways from plant litter inputs to stable SOC: a high-CUE pathway dominated by labile substrate decomposition that generates fungal and bacterial biomass accumulating as MAOC, and a low-CUE pathway where recalcitrant inputs or thermally stressed communities lose proportionally more carbon as CO 2 . [5,25,20] .

Discussion 5.1 Carbon Use Efficiency: A Global Driver of SOC Storage

The most striking finding to emerge from the recent literature is just how strongly microbial carbon use efficiency predicts the size of soil organic carbon stocks at the global scale. Tao et al. (2023) [45] combined deeplearning models, data assimilation, and a traditional metaanalysis of 1,076 paired field observations and consistently found that CUE accounted for at least four times more variance in SOC than any single physical or climatic factor including carbon input rate, decomposition rate, and vertical leaching. That result, published in Nature, has since been corroborated from a different angle by the multi-scale synthesis of He et al. (2024) [17] , which traced the CUE-SOC relationship to a specific mechanistic pathway: communities with higher CUE produce proportionally more biomass per unit carbon assimilated, and a fraction of that biomass ultimately dies as necromass, which then bonds directly to reactive mineral surfaces as MAOC. CUE is not fixed at the community level, however. It varies substantially with temperature, substrate nitrogen content, and the taxonomic identity of dominant decomposers. Ren et al. (2024) [38] tracked the thermal sensitivity parameter γ of microbial CUE across 60 forest sites spanning tropical to boreal biomes and found that it ranged from approximately -0.008 °C-1 in boreal forests to -0.024 °C-1 in tropical forests meaning that a 1 °C warming reduces CUE by 0.8 to 2.4 percentage points depending on biome. The long-term warming study by Frey et al. (2013) [11] found that 18 years of continuous + 5 °C warming paradoxically increased CUE, tentatively attributable to community-level thermal adaptation a finding that remains contested, as more recent experiments (reviewed in Dang et al., 2024) [6] report CUE declines under similar temperature perturbations. This unresolved disagreement over long-term CUE thermal acclimation is one of the most consequential uncertainties in soil carbon-climate feedback modelling. At the taxon level, Pold et al. (2020) [37] showed that bacterial taxa with the highest baseline CUE are simultaneously the most thermally sensitive meaning they contribute disproportionately to carbon conservation at ambient temperature but are selectively disadvantaged by warming. If this pattern holds at larger scales, climate warming could progressively erode community-average CUE even in ecosystems where aggregate thermal adaptation is observed, because the most efficient taxa decline faster than less-efficient competitors can compensate.

Microbial Diversity and the Chemical Complexity of Soil Organic Matter

Understanding how community diversity translates into SOC outcomes requires distinguishing two related but separable pathways. The first operates through CUE: diverse communities tend to achieve higher aggregate CUE because taxonomic complementarity allows different species to exploit distinct substrates and microhabitats, reducing wasteful competition and improving overall assimilation efficiency. The second pathway involves the chemical diversity of microbially-derived compounds deposited on mineral surfaces. A diverse community produces a broader portfolio of cell-wall polymers, extracellular polysaccharides, and secondary metabolites, each capable of forming organo-mineral bonds through different mechanisms such as ligand exchange, hydrophobic interactions, cation bridging that together create a more structurally complex and thermally stable SOM matrix. Domeignoz-Horta et al. (2021) [10] tested this experimentally by inoculating sterile soils with microbial consortia along a gradient from single isolates to diverse field-derived communities. They used Rock-Eval pyrolysis-a thermal analysis technique that generates an R-index reflecting the temperature at which SOM combusts, used as a proxy for chemical complexity and persistence and found that the Rindex increased significantly and non-linearly with bacterial richness. The practical implication is that there appears to be a diversity threshold below which SOM thermal stability degrades noticeably, but above which further increases in diversity produce diminishing marginal gains. A controlled incubation study (Liang et al., 2025) [26] corroborated this at the fraction level: low-diversity communities (single or twospecies inocula) produced 3.9-6.3% less bulk SOC and 8-17% less particulate organic carbon over 75 days compared to more diverse treatments. The MAOC fraction was less sensitive to diversity per se, consistent with the idea that mineral protection mechanisms operate somewhat independently of community complexity. Angst et al. (2024) [2] extended these findings to field conditions. Their analysis of soils across a diversity gradient showed that stabilised microbial necromass was more strongly correlated with microbial diversity (r = 0.61) than with the bioavailability of plant inputs (r = 0.38), directly challenging the widespread assumption that plant litter quality is the primary control on stable SOC formation. The implication for management is significant: even without changing the quantity or chemical quality of organic inputs, practices that erode microbial diversity such as repeated fumigation, intensive tillage, or persistent antibiotic contamination may reduce stable SOM formation capacity.

Fungal Necromass as the Dominant Precursor of Stable MAOC

The asymmetric contributions of fungi and bacteria to the MAOC pool have become one of the most reproducibly supported findings in the recent microbial ecology-SOC literature. The physicochemical basis for this asymmetry lies in cell wall chemistry. Fungal cell walls are dominated by chitin (a nitrogen-containing polysaccharide with high affinity for metal oxide surfaces), melanin (a phenolic polymer that is highly resistant to enzymatic degradation), and β-glucans. Bacterial cell walls are dominated by peptidoglycan (a highly biodegradable murein lattice) and lipopolysaccharide. When these cells die and lyse, fungal residues form more stable organo-mineral complexes through stronger and more diverse bonding mechanisms, while bacterial residues are degraded more rapidly and form weaker associations with mineral surfaces (Liang et al., 2019; Wang & Kuzyakov, 2024) [24,46] . A central contribution of Maillard et al. (2023) [29] was to demonstrate that even within fungal necromass, melanisation is the critical determinant of persistence. Using dual 13 C/ 15 N stable-isotope probing, they tracked the fate of melanised versus non-melanised fungal necromass in forest microcosms over 30 days. Melanised material turned over three to four times more slowly and was recovered preferentially in the MAOC fraction, while non-melanised fungal necromass was rapidly assimilated by both fungal and bacterial decomposer communities and did not preferentially accumulate in the mineral-associated pool. This finding implies that the capacity of a fungal community to build stable MAOC depends not just on fungal biomass turnover rate, but on the melanin content of the dominant species a trait that varies substantially across saprotrophic and mycorrhizal guilds and responds to environmental stress such as drought and UV exposure. At landscape scale, the New Zealand land-use gradient study (Fu et al., 2025) [12] provided perhaps the most direct empirical test of this asymmetry. Using amino sugar biomarkers across 85 soil profiles, they quantified fungal glucosamine and bacterial muramic acid contributions to the MAOC pool along a gradient from native forest to degraded arable cropland. Fungal necromass explained 71-98% of the variance in MAOC gains following land-use restoration, while bacterial muramic acid was negatively correlated with MAOC stocks meaning that high bacterial necromass input was associated with MAOC loss rather than gain. An altitudinal gradient study in the Qilian Mountains (Gao et al., 2025) [13] confirmed this pattern in a different ecosystem context: fungal necromass-C was the dominant driver of MAOC accumulation across a 2,800 m elevation gradient, with F:B ratios increasing with elevation and tracking MAOC stocks closely. (2025) [12] , Chen et al. (2025) [4] , Gao et al. (2025) [13] , and Angst et al. (2024) [2] . (2025), and Angst et al. (2024) [2] .

The Fungal-to-Bacterial Ratio as a Practical SOC Bioindicator

The fungal-to-bacterial (F:B) biomass ratio, typically estimated from PLFA profiles or ergosterol-to-muramic acid ratios, integrates the community-level balance between these two contrasting necromass contributions and has emerged as a practical bioindicator of SOC storage potential. Djemiel et al. (2023) [9] documented this at national scale: across 2,000 French soil profiles spanning forest, grassland, and cropland systems, F:B ratios were 2.4 to 3.8 times higher in semi-natural systems than in conventionally tilled croplands, and this ratio co-varied with SOC stocks at the landscape scale even after statistically removing the effects of climate and parent material. What makes the F:B ratio actionable is its sensitivity to management on timescales of years to decades. No-till farming, cover cropping, and organic amendment additions consistently elevate the F:B ratio by reducing physical disruption of hyphal networks and increasing the abundance of saprotrophic fungi. The Argentine Pampas study (Gortari et al., 2026) [14] found significantly higher ligninolytic and arbuscular mycorrhizal fungal diversity after 10 years of notill compared to conventional tillage, with corresponding increases in stable C fractions demonstrating that management-induced shifts in F:B ratio translate into measurable SOC outcomes on decade timescales. The F:B ratio thus represents a mechanistically meaningful, practically measurable, and management-sensitive indicator that bridges the gap between microbial ecology and SOC management.

Warming, Community Composition Shifts, and MAOC Vulnerability

Climate warming threatens SOC stability through two interacting pathways: direct thermodynamic acceleration of enzymatic decomposition rates, and indirect restructuring of microbial communities toward lower-CUE, bacterially dominated states that produce less stable necromass. The warming incubation study (Liao et al., 2025) [27] quantified both effects simultaneously: a + 2. (2024) [38] provides the mechanistic link: as temperature increases, microbial growth efficiency declines, reducing the amount of carbon channelled into biomass per unit substrate assimilated. At the same time, warming selectively disadvantages the high-CUE fungal taxa that are the primary contributors to stable MAOC (Pold et al., 2020) [37] . The net result is a double-negative for MAOC stability: less necromass produced per unit carbon processed, and the remaining necromass is chemically more labile. Whether long-term thermal adaptation of microbial communities can buffer these effects as suggested by Frey et al. (2013) [11] or whether they are irreversible at the community level remains one of the most important unresolved questions in soil carbon-climate research.

Microbial CUE (g C biomass g⁻¹ C assimilated) [48] , Domeignoz-Horta et al. (2021) [10] , and Ren et al. (2024) [38] .

Aggregate Architecture and Pore-Scale Carbon Protection

Physical protection of organic matter within soil aggregates constitutes a stabilisation mechanism that operates in parallel with, and often synergistically with, organo-mineral association. The ISME Journal review (2025) synthesised evidence that fungal hyphal networks physically enmesh mineral particles and partially decomposed organic fragments, nucleating macroaggregates within which SOC is spatially disconnected from extracellular enzymes. Kravchenko et al. (2019) [20] formalised this as a spatial footprint effect: the fraction of the pore network occupied by active microbial decomposers is itself a significant predictor of SOC stabilisation efficiency, with soils exhibiting more spatially heterogeneous microbial activity showing higher MAOC:POC ratios across multiple soil textures.

Arbuscular mycorrhizal fungi contribute a distinct aggregation pathway through the secretion of glomalinrelated soil proteins (GRSP), which coat aggregate exteriors and reduce their wettability and physical disruption by rainfall. The soil aggregate review (Hamza et al., 2025) [16] collated evidence that GRSP concentrations can be 2-24 times higher than humus carbon concentrations in some AMF-rich soils, and that each 1 g GRSP kg -1 increase is associated with a 2.3-4.1 g SOC kg [46,18] .

Vegetation Succession, Land Use, and Community-SOC Feedbacks

Land-use gradients and vegetation succession chronosequences provide natural experiments in which microbial community composition and SOC dynamics covary over timescales not accessible to laboratory manipulations. Yang et al. (2025, Plants) [48] tracked bacterial community dynamics and SOC fractions across four vegetation succession stages on China's Loess Plateau from recently abandoned farmland through grassland and shrubland to mature forest and found progressive increases in all SOC fractions with succession. Structural equation modelling indicated that the primary pathway linking bacterial community change to SOC accumulation operated through soil total nitrogen and pH, rather than through direct effects of community composition on decomposition rates. This finding illustrates that management practices that improve soil pH and nitrogen status may simultaneously promote SOC-building microbial communities. In subtropical plantation forests, Ding et al. (2026) [8] found that naturally regenerating forests supported higher fungal diversity and greater MAOC than plantation monocultures receiving equivalent aboveground litter inputs consistent with the MEMS prediction that diverse substrates supporting diverse decomposer communities generate more chemically complex, thermally stable SOM. Organic fertilization field experiments (Ma et al., 2025) [28] showed a rate-dependent relationship: moderate organic amendment rates stimulated labile carbon pools through CUE enhancement, while higher rates tipped the balance toward MAOC accumulation by promoting fungal dominance and microbial network complexity. Field-scale evidence from India further illustrates the sensitivity of SOC fractions to land-use management. Across the Vitalapura sub-watershed in Karnataka, different land use systems exhibited measurable differences in soil organic carbon stocks and biomass carbon, with forest land use consistently supporting higher carbon accumulation than agricultural systems (Sushma et al., 2026a; 2026b) [43,44] . Comparable findings from the Bettadapura micro-watershed demonstrated that geospatial characterisation of soils reveals significant variation in nutrient and carbon status linked to land use history (Manoj Kumar et al., 2025a; 2025b; Anand et al., 2024) [30,31,1] . Assessments of soil fertility indicators across different land use covers in Tarikere taluk likewise confirmed that land-use intensification reduces soil organic matter and associated biological activity (Shafaisal et al., 2025) [40] . Agroforestry systems in the Southern Transition Zone of Karnataka were found to store substantially greater biomass and carbon compared to monocrop systems, underscoring the role of tree-based land use in building SOC (Mitali et al., 2025) [32] . At the watershed scale, land degradation driven by soil erosion under current land use patterns further threatens SOC stocks, as documented through remote sensing and GIS analyses in Karnataka (Subramanyan et al., 2023) [42] . Carbon stock assessments across different land use systems in Kodagu District showed that natural forests and agroforestry consistently outperformed annual croplands in organic carbon sequestration (Jujin et al., 2023) [19] . The application of organic manures in intensively managed systems has been shown to enhance both soil carbon stocks and soil enzyme activities, providing a practical intervention for rebuilding microbially active SOC under high-input agricultural management (Nichita et al., 2023) [32] .

Correlation and SEM Evidence: Sources, Limitations, and Interpretation

Figures 6 and7 present a correlation matrix and SEM path diagram synthesising relationships across the reviewed literature. It is important to be explicit about what these figures represent: they are structured summaries of effect sizes and correlations drawn from individual published studies, not the products of a new statistical analysis conducted for this review. The correlation values in Figure 6 are weighted Pearson r estimates reported in primary studies (with CUE-MAOC r = 0.72 from Tao et al., 2023 [45] ; fungal necromass-MAOC r = 0.78 from Fu et al., 2025 [12] and Chen et al., 2025 [4] ; MAOC-SOC r = 0.89 from Lavallee et al., 2020) [21] . Path coefficients in Figure 7 are drawn from the SEM results of Yang et al. (2025) [48] , Domeignoz-Horta et al. (2021) [10] , and Ren et al. (2024) [38] . Readers requiring fully reproducible statistical outputs should consult the primary sources. [48] , Domeignoz-Horta et al. (2021) [10] , and Ren et al. (2024) [38] ; conceptual summary, not a newly fitted model (CFI = 0.96, RMSEA = 0.048). [24] . A recent study (Pei et al., 2025) [35] found that CUE in subsoil is primarily regulated by physicochemical protection rather than microbial diversity the opposite of topsoil implying that management strategies effective at the surface may not translate to deeper horizons.

Knowledge Gaps and

Mycorrhizal Guild Resolution

Most biogeochemical models either ignore mycorrhizal fungi or represent them as a single functional group. The evidence base now clearly distinguishes arbuscular mycorrhizal (AMF), ectomycorrhizal (ECM), and ericoid mycorrhizal fungi in terms of their CUE, necromass chemistry, and SOC stabilisation outcomes (Anthony et al., 2020; Guan et al., 2025) [3,15] . AMF primarily contribute to aggregate-bound carbon via GRSP; ECM fungi dominate MAOC in boreal and temperate forests through high-chitin necromass; ericoid mycorrhizal associations in acidic heathland soils represent a distinct and largely unstudied pathway. Incorporating mycorrhizal guild differentiation into land surface models is a scientifically justified and practically tractable priority.

Multi-Omics Integration and Functional Gene Approaches

The metagenomics study (Xie et al., 2022) [47] demonstrated that C and N metabolic gene assemblages predict SOC fraction outcomes better than taxonomic composition alone. Broader integration of metagenomics, metatranscriptomics, and metaproteomics with paired SOC fractionation in the same experimental systems especially in long-term field experiments with replicated treatments is needed to move from correlational to mechanistic understanding. The current dominance of amplicon sequencing (16S rRNA, ITS) for community characterisation, while cost-effective, sacrifices functional resolution that is arguably more relevant to SOC outcomes than taxonomic identity.

Implications for Soil Carbon Management

The mechanistic framework synthesised here points toward several actionable management recommendations for enhancing SOC sequestration through microbial community management:

• Promote fungal-dominated communities through no-till or reduced tillage, diverse crop rotations, and cover cropping. The F:B ratio can be elevated by 2-4× within a decade (Djemiel et al., 2023; Gortari et al., 2026) [9,14] , shifting communities toward MAOC-building necromass trajectories. • Optimise organic input chemistry toward moderatelability, N-rich substrates (compost, legume-based green manure) to maximise high-CUE microbial processing, consistent with MEMS framework predictions (Cotrufo et al., 2013) [5] . Highly recalcitrant inputs (wheat straw without N supplementation) may support slower decomposition but at lower CUE, generating less MAOC per unit of carbon input. • Maintain or restore soil microbial diversity through long-rotation cropping, reduced pesticide loads, and organic amendments. Diversity exerts an independent positive effect on SOM thermostability (Domeignoz-Horta et al., 2021) [10] and resilience to thermal perturbation (Angst et al., 2024; Liang et al., 2025) [2,26] , beyond its effect on CUE alone. • Manage soil mineralogy to increase MAOC saturation capacity where feasible. In highly weathered tropical soils, targeted additions of amorphous Fe/Al-rich materials can increase reactive mineral surface area (Lavallee et al., 2020) [21] . Liming to raise soil pH into the range optimal for fungal community establishment (pH 5.5-7.0) also indirectly promotes MAOC formation. [49,45] .

Conclusion

This systematic review assembled and critically evaluated 40 peer-reviewed studies spanning 2011-2026 to characterise how microbial community composition governs soil organic carbon stabilisation. Several conclusions are supported with high consistency across methodological approaches and geographic contexts. First, microbial CUE is the dominant quantitative predictor of global SOC storage a conclusion anchored by the global meta-analysis of Tao et al. (2023) [45] and corroborated by multi-scale synthesis evidence (He et al., 2024) [17] . Second, fungal necromass is the primary molecular precursor of stable MAOC, with melanised fungal cell-wall materials forming the most persistent organo-mineral associations (Maillard et al., 2023; Gao et al., 2025; Fu et al., 2025) [29,13,12] . Third, microbial diversity independently enhances SOM chemical stability through functional complementarity in compound production (Domeignoz-Horta et al., 2021; Angst et al., 2024) [10,2] . [38,37,27] . Fifth, soil aggregates and mycorrhizal fungi provide stabilisation pathways that complement organo-mineral association but remain poorly parameterised in global models (de Goede et al., 2025; Kravchenko et al., 2019) [7,20] . Limitations of this review include geographic bias toward temperate ecosystems, reliance on observational and shortterm incubation studies for many mechanistic claims, and the use of illustrative rather than formally pooled statistical outputs in the figures. Future reviews should prioritise a formal meta-analysis of fungal necromass contributions to MAOC across biomes, with pre-registered protocols and blinded quality assessment. Addressing the knowledge gaps identified in Section 6 particularly in tropical soils, subsoils, and mycorrhizal guild resolution would substantially improve the mechanistic completeness and global applicability of the synthesis presented here.

References

1. Anand S, Gurumurthy KT, Thippeshappa GN, Sridhara CJ, Ravikumar D, Shoba S. Exploring soil nutrient dynamics: Assessment and mapping in Sunnadhahalli micro-watershed: A geospatial approach. Int J Res Agron. 2024;8(12):1442-1456.
2. Angst G, Angst S, Frouz J, et al. Stabilized microbial necromass in soil is more strongly coupled with microbial diversity than with the bioavailability of plant inputs. Soil Biol Biochem. 2024;190:109323.
3. Anthony MA, Crowther TW, Maynard DS, van den Hoogen J, Averill C. Distinct assembly processes and microbial communities constrain soil organic carbon formation. One Earth. 2020;2(4):349-360.
4. Chen S, Zhang Y, Ma J, Bai M, Long J, Liu M, et al. Contribution of soil microbial necromass carbon to soil organic carbon fractions and its influencing factors in different grassland types. Soil. 2025;11(2):883-898.
5. Cotrufo MF, Wallenstein MD, Boot CM, Denef K, Paul E. The microbial efficiency-matrix stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob Change Biol. 2013;19(4):988-995.
6. Dang R, Liu J, Lichtfouse E, Zhou L, Zhou M, Xiao L. Soil microbial carbon use efficiency and the constraints. Ann Microbiol. 2024;74(1):37.
7. de Goede SP, Hannula SE, Jansen B, Morriën E. Fungal-mediated soil aggregation as a mechanism for carbon stabilization. ISME J. 2025;19(1):wraf074.
8. Ding Z, Yang Z, Yang Y, et al. Differences in soil carbon fractions and microbial communities between assisted natural regeneration and plantation forests in subtropical China. PLoS One. 2026;21(1):e0339350.
9. Djemiel C, Dequiedt S, Bailly A, Tripied J, Lelièvre M, Horrigue W, et al. Biogeographical patterns of the soil fungal:bacterial ratio across France. mSphere. 2023;8(5):e00365-23.
10. Domeignoz-Horta LA, Shinfuku M, Junier P, Poirier S, Verrecchia E, Urich T, et al. Direct evidence for the role of microbial community composition in the formation of soil organic matter composition and persistence. ISME Commun. 2021;1:64.
11. Frey SD, Lee J, Melillo JM, Six J. The temperature response of soil microbial efficiency and its feedback to climate. Nat Clim Change. 2013;3(4):395-398.
12. Fu Z, Zhang Y, Qiu W, Mohy-Ud-Din W, Yan Z, Kuzyakov Y. Fungal and bacterial necromass: Opposite drivers of mineral-associated organic carbon gains and losses. Soil Tillage Res. 2025;253:106634.
13. Gao H, Wu S, Wang X, et al. Fungal necromass drives mineral-associated organic carbon accrual across an altitudinal gradient in the Qilian Mountains. Microbiol Spectr. 2025;13(11):e01605-25.
14. Gortari M, Maguire VG, Ezquiaga JP, Cicchino M, Bailleres M, Escaray RU, et al. Associations between soil microbiomes and carbon stabilization under longterm no-till farming systems in the Argentine Pampas. Sci Rep. 2026.
15. Guan X, Jiang J, Classen AT, Ullah S, Wang G. Disentangling the contribution of mycorrhizal fungi to soil organic carbon storage. Soil Biol Biochem. 2025;209:109900.
16. Hamza A, Karčauskienė D, Mockevičienė I, Repšienė R, Tahir MA, Manzoor MZ, et al. Soil aggregate dynamics and stability: Natural and anthropogenic drivers. Agriculture. 2025;15(23):2500.
17. He X, Abs E, Allison SD, Tao F, Huang Y, Manzoni S, et al. Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle. Nat Commun. 2024;15(1):8010.
18. Iqbal S, Begum F, et al. The invisible architects: Microbial communities and their transformative role in soil health and global climate change. Environ Microbiome. 2025;20:34.
19. Jujin SA, Ravikumar D, Barker RD. Distribution of carbon stocks under different land use systems of Somawarpet Taluk, Kodagu District, India. Int J Environ Clim Change. 2023;13(9):2405-2412.
20. Kravchenko AN, Guber AK, Razavi BS, et al. Microbial spatial footprint as a driver of soil carbon stabilization. Nat Commun. 2019;10:3121.
21. Lavallee JM, Soong JL, Cotrufo MF. Conceptualizing soil organic matter into particulate and mineralassociated forms to address global change in the 21st century. Glob Change Biol. 2020;26(1):261-273.
22. Lehmann J, Kleber M. The contentious nature of soil organic matter. Nature. 2015;528(7580):60-68.
23. Liang C, Zhu X. The soil microbial carbon pump as a new concept for terrestrial carbon sequestration. Soil Ecol Lett. 2020;3:1-11.
24. Liang C, Amelung W, Lehmann J, Kästner M. Quantitative assessment of microbial necromass contribution to soil organic matter. Glob Change Biol. 2019;25(11):3578-3590.
25. Liang C, Schimel JP, Jastrow JD. The importance of anabolism in microbial control over soil carbon storage. Nat Microbiol. 2017;2(8):1-6.
26. Liang Y, Leifheit EF, Lehmann A, Rillig MC. Soil organic carbon stabilization is influenced by microbial diversity and temperature. Sci Rep. 2025;15(1):13990.
27. Liao C, Zhai D, Cheng X. Warming inhibits new soil organic carbon formation with higher bacterial necromass contribution. J Plant Ecol. 2025;18(1):rtaf005.
28. Ma M, Yang H, et al. Year-to-year variation in organic fertilization effects on soil carbon stabilization and microbial networks. Front Microbiol. 2025.
29. Maillard F, Michaud TJ, See CR, DeLancey LC, Blazewicz SJ, Kimbrel JA, et al. Melanization slows the rapid movement of fungal necromass carbon and nitrogen into both bacterial and fungal decomposer communities and soils. mSystems. 2023;8(4):e0039023.
30. Manoj Kumar HS, Ravikumar D, Anand S. Assessment and mapping of soil nutrient status in the Bettadapura micro-watershed: A geospatial analysis. Int J Res Agron. 2025;8(12S):232-247.
31. Manoj Kumar HS, Ravikumar D, Gurumurthy KT, Ananthakrishna KS, Shoba S. Characterization and classification of soils in the Bettadapura microwatershed of lower Tungabhadra catchment using a geospatial approach. Int J Res Agron. 2025;8(12S):273288.
32. Mitali M, Devagiri GM, Baliram GN, Ravikumar D, Ankush M. Biomass and carbon stock assessment in agroforestry practices: A study in Southern Transition Zone of Karnataka, India. Indian Forester. 2025;151(6):540-545.
33. Nichita CV, Raghavendra S, Champa BV, Varma S, Nagaraja MS. Role of organic manures on soil carbon stocks and soil enzyme activities in intensively managed ginger production systems. Int J Recycl Org Waste Agric. 2023;12.
34. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow C, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
35. Pei J, Li J, Luo Y, Rillig MC, Smith P, Gao W, et al. Patterns and drivers of soil microbial carbon use efficiency across soil depths in forest ecosystems. Nat Commun. 2025;16(1):5218.
36. Pérez-Pazos E, Beidler KV, Narayanan A, et al. Fungi rather than bacteria drive early mass loss from fungal necromass regardless of particle size. Environ Microbiol. 2024;26:e13280.
37. Pold G, Domeignoz-Horta LA, DeAngelis KM. Carbon use efficiency and its temperature sensitivity covary in soil bacteria. mBio. 2020;11(1):e02293-19.
38. Ren C, Zhou Z, Delgado-Baquerizo M, Bastida F, Zhao F, Yang Y, et al. Thermal sensitivity of soil microbial carbon use efficiency across forest biomes. Nat Commun. 2024;15(1):6269.
39. Schmidt MWI, Torn MS, Abiven S, Dittmar T, Guggenberger G, Janssens IA, et al. Persistence of soil organic matter as an ecosystem property. Nature. 2011;478(7367):49-56.
40. Shafaisal SM, Ravikumar D, Raveesha S, Anjali MC, Mahantesh PS, Subramanyan A, et al. Comparative assessment of the distribution of soil fertility indicators under different land use covers in Tarikere taluk of Karnataka. Int J Res Agron. 2025;SP-8(10):279-290.
41. Sokol NW, Kuebbing SE, Karlsen-Ayala E, Bradford MA. Evidence for the primacy of living root inputs, not root or shoot litter, in forming soil organic carbon. New Phytol. 2019;221(1):233-246.
42. Subramanyan A, Dharmaraj R, Gurumurthy KT, Sampangi S, Srinivasaiah YKH. Assessment of land degradation due to soil erosion based on current land use/landcover pattern using RS and GIS techniques. Arab J Geosci. 2023;16(7):431.
43. Sushma N, Ganapathi, Ravikumar D, Anand Subramanian, Manoj Kumar HS. Influence of land use systems on soil organic carbon fractions in the Vitalapura sub-watershed of Chikkamagaluru District, Karnataka, India. Plant Arch. 2026;26(1):1519-1524.
44. Sushma N, Ravikumar D, Sarvajna BS, Sridhara R, Rajashekhar DB. Evaluation of soil and biomass carbon stock across different land use systems in the Vitalapura sub-watershed, Kadur taluk, Chikkamagaluru district, Karnataka, India. Plant Sci Today. 2026;13(Special Issue 1):1-8.
45. Tao F, Huang Y, Hungate BA, Manzoni S, Frey SD, Schmidt MWI, et al. Microbial carbon use efficiency promotes global soil carbon storage. Nature. 2023;618(7967):981-985.
46. Wang B, Kuzyakov Y. Soil structure and aggregates as mediators of microbial necromass stabilization. Glob Change Biol. 2024;30:e17203.
47. Xie Z, Yu Z, Li Y, Wang G, Liu X, Tang C, et al. Soil microbial metabolism on carbon and nitrogen transformation links the crop-residue contribution to soil organic carbon. npj Biofilms Microbiomes. 2022;8(1):14.
48. Yang B, Zhai J, He M, et al. Linking soil properties and bacterial communities with organic matter carbon during vegetation succession on the Loess Plateau. Plants. 2025;14(6):937.
49. Zhu X, Jackson RD, DeLucia EH, Tiedje JM, Liang C. The soil microbial carbon pump: From conceptual insights to empirical assessments. Glob Change Biol. 2020;26(11):6032-6039.