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Frontiers in Ecology and Evolution ·

Volume 14 - 2026 | https://doi.org/10.3389/fevo.2026.1969592

Lithology influences soil microbial functional potential in subtropical forests

  • Qiumei Ling1,2,3
  • Hanqing Wu1,2*corresponding author
  • Songjiang Hu1,2,3
  • Shenglong Li4
  • Wei Wan5
  • Peilei Hu1,2
  • Jun Xiao1,2
  • Tiangang Tang1,2
  • Hu Du1,2
  • Jie Zhao1,2
  • Wei Zhang1,2*corresponding author
  • Hongsong Chen1,2
  • Kelin Wang1,2*corresponding author
  1. 1Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
  2. 2Huanjiang Agriculture Ecosystem Observation and Research Station of Guangxi, Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang, China
  3. 3University of Chinese Academy of Sciences, Beijing, China
  4. 4College of Urban and Environmental Sciences, Central China Normal University, Wuhan, China
  5. 5School of Resources and Environment, Nanchang University, Nanchang, China
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Abstract

Lithology shapes the Earth’s critical zone, yet its influence on microbial genomic potential in subtropical forests remains unclear. Here, we quantified soil carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) cycling functional genes across three contrasting lithologies in southwest China using HT-qPCR. We found limestone soils consistently harbored significantly higher gene abundances than dolostone and clasolite soils. Random forest models explained a substantial proportion of the variation in functional gene pools ( R 2 = 0.87–0.92). Based on these identified key drivers, we propose a Nitrogen availability–Microbial resource limitation–Reactive minerals (NMR) framework, where total dissolved nitrogen fuels activity, eco-enzymatic stoichiometry reflects metabolic adaptation, and iron/aluminum oxides regulate substrate accessibility via physical protection. Overall, specific carbonate rock types should be differentiated when modeling biogeochemical cycles.

Keywords

Highlights

  • Lithology dictates microbial functional gene abundances in subtropical forests.
  • Limestone soils harbor higher C, N, P, and S cycling potential than dolostone and clasolite soils.
  • Total dissolved N, enzymatic stoichiometry, and pedogenic Fe/Al oxides are the key predictors of microbial functional potential.
  • A “Nitrogen availability–Microbial resource limitation–Reactive minerals” (NMR) framework is proposed.

Subtropical karst landscapes in southwest China represent one of the most extensive karst systems globally (Li et al., 2021; Wang et al., 2019). These karst forest ecosystems feature high heterogeneity, calcium (Ca) and magnesium (Mg) alkalinity, and vulnerability to environmental change (D'Ettorre et al., 2024; Hu et al., 2025). Within these landscapes, lithology (parent material) dictates soil function, defines critical zone structure, and influences the biogeochemical cycling of carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) (Hu et al., 2022, 2024a; Pan et al., 2024; Wang et al., 2018).

The habitat heterogeneity in karst regions is primarily driven by divergent weathering processes across bedrock types (Aehnelt and Totsche, 2025; Liu et al., 2021). Carbonate rocks (dolostone and limestone) undergo intense chemical weathering and karstification, forming a complex microhabitat landscape of rocky outcrops, fissures, and shallow soil layers (Li et al., 2021; Xiao et al., 2023a). These microhabitats differ sharply in water dynamics, nutrient status, and pH, creating specialized microbial niches (Xiao et al., 2023a, b). In contrast, non-karst lithologies such as clasolite yield deeper, acidic soils dominated by silicate mineral matrices (Hu et al., 2024b).

Soil microorganisms mediate the transformation of essential nutrient elements (Dong et al., 2020; Ruan et al., 2026). Their functional gene abundances reflect microbial metabolic potential, serving as a vital link between genetic diversity and potential ecosystem function (Zhu et al., 2024). Although lithological impacts on microbial taxonomy are well-documented (Bhople et al., 2021; Weemstra et al., 2020; Xiao et al., 2024), how lithology affects microbial functional potential for multi-element cycling remains unresolved. In this study, microbial functional potential refers to the potential capacity of soil microbial communities to perform specific biogeochemical functions, as inferred from the abundance of functional genes associated with C, N, P, and S cycling (Zheng et al., 2018; Zhu et al., 2024). Clarifying the lithological influence is essential for predicting ecosystem resilience and C sink capacities under climate change.

Here, we employed high-throughput quantitative PCR (HT-qPCR) technology to profile C, N, P, and S cycling genes across limestone, dolostone, and clasolite soils in subtropical forests. Our objectives were to: (1) quantify the lithological variations in functional gene abundances; (2) identify key environmental predictors; and (3) explore the potential mechanisms regulating microbial functional potential across complex geological terrains.

We found that soil microbial functional gene pools exhibited distinct and lithology-dependent patterns (Figure 1). Limestone soils consistently harbored significantly higher abundances of C, N, P, and S cycling genes than dolostone and clasolite soils (Figure 1). Specifically, limestone soils were enriched in genes encoding the degradation of both labile (e.g., starch, hemicellulose) and recalcitrant (e.g., chitin, lignin) organic matter (Figure 1A), N ammonification (ureC), mineralization (gdhA), and denitrification (nosZ) (Figure 1B), organic P mineralization (phnK, phoD) and inorganic P solubilization (gcd, ppx) (Figure 1C), as well as S oxidation/reduction genes (apsA, dsrA, yedZ, soxY) (Figure 1D). This elevated functional potential in limestone soils could be linked to five synergistic factors: (1) High CaO content may contribute to slightly alkaline, Ca-rich conditions favorable for microbial growth and aggregate stabilization (Banwart et al., 2019; Hu et al., 2025); (2) High organic C, total N, and available P supply steady nutrients to support greater microbial biomass (Ling et al., 2025); (3) Highly complex and stable microbial co-occurrence networks may be associated with stronger inter-specific interactions and resource processing (Xiao et al., 2026); (4) High pH and Ca2+ boost phosphatase activity, mitigating potential P limitation (Song et al., 2017); (5) Higher bacterial and fungal diversity provides functional redundancy against environmental fluctuations (Sveen et al., 2025).

Comparison of soil microbial functional potential indicated by C-, N-, P-, and S-cycling gene abundances across three typical lithology types in subtropical forests, Southwest China. **(a)** C-cycling gene abundance; **(b)** N-cycling gene abundance; **(c)** P-cycling gene abundance; **(d)** S-cycling gene abundance. Asterisks indicate significant differences among lithology types ( ***, p < 0.001; **, p < 0.01; *, p < 0.05).
Figure 1. Comparison of soil microbial functional potential indicated by C-, N-, P-, and S-cycling gene abundances across three typical lithology types in subtropical forests, Southwest China. (a) C-cycling gene abundance; (b) N-cycling gene abundance; (c) P-cycling gene abundance; (d) S-cycling gene abundance. Asterisks indicate significant differences among lithology types ( *, p < 0.001; , p < 0.01; *, p < 0.05).

Combining random forest (RF) modeling with Mantel’s test identified the primary environmental predictors of functional gene pools (Figures 2, 3). RF models explained a substantial proportion of the variance for C (R2 = 0.92), N (R2 = 0.90), P (R2 = 0.92), and S (R2 = 0.87) cycling gene pools (Figure 2, p < 0.01). Total dissolved N (TDN), eco-enzymatic stoichiometry [BG/(LAP+NAG)], and free iron/aluminum oxides [(Fe+Al)d] consistently emerged as the top predictors (Figure 2, p < 0.05), as supported by the Mantel’s tests (Figure 3). These results indicate that soil microbial functional potential is not only associated with immediate nutrient availability and microbial metabolic limitation, but also with reactive minerals (Cui et al., 2025; Kang et al., 2024).

The model-averaged relative importance of Drivers on soil microbial functional potential indicated by C-, N-, P-, and S-cycling gene abundances across three typical lithology types in subtropical forests, Southwest China. **(a)** C-cycling genes; **(b)** N-cycling genes; **(c)** P-cycling genes; **(d)** S-cycling genes. The importance was calculated by “*randomForest*”. (Ca+Mg)<sub>e</sub>, the sum of exchangeable Ca<sup>2+</sup> and Mg<sup>2+</sup>; (Fe+Al)<sub>d</sub>, the sum of pedogenic Fe and Al; (Fe+Al)<sub>o</sub>, the sum of poorly crystalline oxyhydroxides Fe and Al; pH, soil pH; SOC, soil organic carbon; STN, soil total nitrogen; NH<sub>4</sub><sup>+</sup>, ammonium; TDN, soil total dissolved nitrogen; BG/(LAP+NAG), the ratio of BG to LAP and NAG; (LAP+NAG)/AP, the ratio of LAP and NAG to AP; Viruses<sub>α</sub>, *α* diversity of soil viruses; Bacteria<sub>α</sub>, *α* diversity of soil bacteria; Fungi<sub>α</sub>, *α* diversity of soil fungi; Clay+Silt, clay and silt content; MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; MBC/MBN, the ratio of MBC and MBN; CIA, the chemical index of alteration. ***p* < 0.01; **p* < 0.05; ns, *p* > 0.05.
Figure 2. The model-averaged relative importance of Drivers on soil microbial functional potential indicated by C-, N-, P-, and S-cycling gene abundances across three typical lithology types in subtropical forests, Southwest China. (a) C-cycling genes; (b) N-cycling genes; (c) P-cycling genes; (d) S-cycling genes. The importance was calculated by “randomForest”. (Ca+Mg)e, the sum of exchangeable Ca2+ and Mg2+; (Fe+Al)d, the sum of pedogenic Fe and Al; (Fe+Al)o, the sum of poorly crystalline oxyhydroxides Fe and Al; pH, soil pH; SOC, soil organic carbon; STN, soil total nitrogen; NH4+, ammonium; TDN, soil total dissolved nitrogen; BG/(LAP+NAG), the ratio of BG to LAP and NAG; (LAP+NAG)/AP, the ratio of LAP and NAG to AP; Virusesα, α diversity of soil viruses; Bacteriaα, α diversity of soil bacteria; Fungiα, α diversity of soil fungi; Clay+Silt, clay and silt content; MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; MBC/MBN, the ratio of MBC and MBN; CIA, the chemical index of alteration. **p < 0.01; *p < 0.05; ns, p > 0.05.
Mantel’s test illustrating the integrated relationships between soil environmental attributes, microbial properties, and C-, N-, P-, and S-cycling gene abundances. **(a)** Pairwise correlations among soil physicochemical properties, enzymatic stoichiometry, microbial diversity, and their linkages with overarching functional gene groups (C-, N-, P-, and S-cycling genes). **(b–e)** Detailed Mantel’s test networks decoupling the specific sub-functional pathways, including: **(b)** C-degradation, C-fixation, and methane metabolism; **(c)** N-fixation, ammonification, mineralization, nitrification, and denitrification; **(d)** organic P mineralization and inorganic P solubilization; and **(e)** S reduction and S oxidation. ***, p < 0.001; **, p < 0.01; *, p < 0.05.
Figure 3. Mantel’s test illustrating the integrated relationships between soil environmental attributes, microbial properties, and C-, N-, P-, and S-cycling gene abundances. (a) Pairwise correlations among soil physicochemical properties, enzymatic stoichiometry, microbial diversity, and their linkages with overarching functional gene groups (C-, N-, P-, and S-cycling genes). (b–e) Detailed Mantel’s test networks decoupling the specific sub-functional pathways, including: (b) C-degradation, C-fixation, and methane metabolism; (c) N-fixation, ammonification, mineralization, nitrification, and denitrification; (d) organic P mineralization and inorganic P solubilization; and (e) S reduction and S oxidation. *, p < 0.001; , p < 0.01; *, p < 0.05.

Based on these key predictors, we propose a robust tripartite framework: “Nitrogen availability–Microbial resource limitation–Reactive minerals” (NMR) (Figure 4). This framework provides a conceptual interpretation for the variations in microbial functional gene abundance across subtropical lithologies. First, TDN provides essential N for microbial protein and nucleic acid synthesis, potentially supporting microbial metabolic processes and functional gene abundance (L Espérance et al., 2024; Rabbi et al., 2025). High N availability enables microbes to allocate energy toward synthesizing extracellular enzymes, thereby expanding the functional gene pool across multi-element cycles (Fujita et al., 2018; Liao et al., 2024; Wang and Kuzyakov, 2023). Second, the eco-enzymatic stoichiometry ratio BG/(LAP+NAG) reflects microbial C vs. N acquisition strategies (Cui et al., 2023; Moorhead et al., 2023). A high ratio indicates elevated C investment under alleviated N limitation, which promotes overall metabolic activity and gene expression (Mori et al., 2023; Zheng et al., 2022). Conversely, low ratios signify severe N limitation, which suppresses microbial metabolism and functional gene abundance (Mori, 2020). Third, reactive minerals ((Fe+Al)d) may affect functional gene abundance via physical protection and mineral adsorption (Dong et al., 2023; Shabtai et al., 2023; Wu et al., 2023). While moderate Fe and Al oxide levels stabilize extracellular enzymes and extracellular DNA against enzymatic breakdown, excessive mineral binding could restrict substrate accessibility, lower microbial carbon use efficiency (CUE) and functional gene abundances (Hu et al., 2026; Jia et al., 2024; Li et al., 2025).

Conceptual diagram of the “Nitrogen Availability–Microbial Resource Limitation–Reactive Minerals” regulatory triangle framework illustrates the coordinated mechanism and interactive pathways driving the abundances and spatial variations of soil carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) nutrient-cycling functional genes in subtropical forest ecosystems across distinct lithologies.
Figure 4. Conceptual diagram of the “Nitrogen Availability–Microbial Resource Limitation–Reactive Minerals” regulatory triangle framework illustrates the coordinated mechanism and interactive pathways driving the abundances and spatial variations of soil carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) nutrient-cycling functional genes in subtropical forest ecosystems across distinct lithologies.

In conclusion, lithology is a key regulator of soil microbial functional potential in subtropical forests. Limestone soils harbor significantly higher functional potential for nutrient cycling than dolostone and clasolite soils, driven by bedrock-mediated N availability, microbial resource limitation, and reactive mineral dynamics. These findings highlight lithological impacts on soil microbiome in subtropical forest ecosystems, and suggest that lithology should be integrated into the Earth system models to predict biogeochemical cycling and ecosystem functions, especially in the sensitive karst regions.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fevo.2026.1969592/full#supplementary-material

Supplementary material Supplementary material at the source

Footnotes

Edited by: Shuai Shang, Binzhou University, China

Reviewed by: Yongxin Lin, Fujian Normal University, China

Cao Pengxi, Xizang University, China

Tao Yang, Beijing Forestry University, China

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

The author(s) declared financial support was received for this work and/or its publication. This study was supported by the Natural Science Foundation of Guangxi Zhuang Autonomous Region (2026GXNSFFA00640003; 2025GXNSFAA069812); the Science and Technology Innovation Program of Hunan Province (2025RC1066); the Natural Science Foundation of China (42407045).

Data availability

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

Author contributions

QL: Data curation, Formal analysis, Investigation, Writing – original draft. HW: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Writing – original draft, Writing – review & editing, Supervision, Validation. SH: Validation, Writing – review & editing. SL: Writing – review & editing, Validation. WW: Visualization, Writing – review & editing, Validation. PH: Writing – review & editing, Validation. JX: Writing – review & editing, Validation. TT: Writing – review & editing, Validation. HD: Investigation, Writing – review & editing, Resources. JZ: Writing – review & editing, Validation. WZ: Conceptualization, Funding acquisition, Writing – review & editing, Methodology, Supervision, Validation. HC: Writing – review & editing, Validation. KW: Funding acquisition, Writing – review & editing, Conceptualization, Validation.

Acknowledgements

We thank the Institutional Center for Shared Technologies and Facilities of the Institute of Subtropical Agriculture, Chinese Academy of Sciences, for supporting the analyses of bedrock and soil properties.

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Citation

Ling, Q., et al. (2026). Lithology influences soil microbial functional potential in subtropical forests. Frontiers in Ecology and Evolution, Volume 14. https://doi.org/
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Copyright © 2026 Ling, Wu, Hu, Li, Wan, Hu, Xiao, Tang, Du, Zhao, Zhang, Chen and Wang.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Hanqing Wu; Wei Zhang; Kelin Wang

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