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Soil carbon sequestration enhanced by long-term nitrogen and phosphorus fertilization

Nature Geoscience (2025)Cite this article

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Abstract

Soil organic carbon is crucial for climate mitigation and agroecosystem sustainability, yet its depletion is concerning and its response to long-term fertilization remains unclear. Here we leverage the Broadbalk Classical Experiment at Rothamsted (UK), the world’s longest-running continuous winter wheat fertilization trial, along with 14C labelling, metagenomics and metabolomics to determine how 180 years of nitrogen (N) and phosphorus (P) fertilization impact soil organic carbon dynamics. Compared with no fertilization, long-term P, N and combined NP fertilization increased the soil organic carbon content by 10%, 22% and 28%, respectively. P application alone disproportionately increased microbial respiration (37%) and biomass (20%), limiting stable carbon formation and slightly increasing labile carbon. N application alone increased microbial carbon use and necromass accumulation efficiency, increasing mineral-associated carbon build-up. Combined NP fertilization enhanced plant-derived carbon inputs and the transformation of labile carbon into stable carbon, increasing soil organic carbon quantity and stability. A meta-analysis of the effects of fertilization duration on soil organic carbon revealed that N and P fertilization globally increased cropland soil organic carbon by 21% and 13%, and these promoting effects decreased before increasing after 16 and 34 years, respectively. Overall, long-term mineral fertilization can effectively enhance soil carbon sequestration.

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Fig. 1: Effect of long-term nitrogen and phosphorus fertilization on wheat yield, straw biomass and SOC.
Fig. 2: Effects of long-term nitrogen and phosphorus fertilization on SOC pools and microbial carbon metabolism in 2022.
Fig. 3: Effects of long-term fertilization on the decomposition and microbial immobilization of 14C-labelled substrates.
Fig. 4: Microbial carbon cycling genes abundance and enzyme activities across treatments.
Fig. 5: Global meta-analysis of fertilization effects on SOC.
Fig. 6: Conceptual diagram illustrating different magnitudes and mechanisms of SOC increase resulting from 180-year nitrogen and phosphorus fertilization.

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Data availability

All data generated and analysed during this study are available via Figshare at https://doi.org/10.6084/m9.figshare.28792301 (ref. 64). Sequencing data have been archived and are publicly accessible via the National Center for Biotechnology Information (NCBI) database under project number PRJNA1071733. Source data are provided with this paper.

Code availability

All code used in this study has been archived and is available via Code Ocean https://codeocean.com/capsule/2397954/tree/v1 (ref. 65).

References

  1. Lehmann, J. & Kleber, M. The contentious nature of soil organic matter. Nature 528, 60–68 (2015).

    Article  CAS  Google Scholar 

  2. Tang, X. L. et al. Carbon pools in China’s terrestrial ecosystems: new estimates based on an intensive field survey. Proc. Natl Acad. Sci. USA 115, 4021–4026 (2018).

    Article  CAS  Google Scholar 

  3. Feng, J. G., Song, Y. J. & Zhu, B. Ecosystem-dependent responses of soil carbon storage to phosphorus enrichment. N. Phytol. 238, 2363–2374 (2023).

    Article  CAS  Google Scholar 

  4. Sanderman, J., Hengl, T. & Fiske, G. J. Soil carbon debt of 12,000 years of human land use. Proc. Natl Acad. Sci. USA 114, 9575–9580 (2017).

    Article  CAS  Google Scholar 

  5. Fan, L. J. et al. Long-term nitrogen and phosphorus addition have stronger negative effects on microbial residual carbon in subsoils than topsoils in subtropical forests. Glob. Change Biol. 30, e17210 (2024).

    Article  CAS  Google Scholar 

  6. Wu, W. et al. Meta-analysis of the impacts of phosphorus addition on soil microbes. Agric. Ecosyst. Environ. 340, 108180 (2022).

    Article  CAS  Google Scholar 

  7. Spohn, M., Braun, S. & Sierra, C. A. Continuous decrease in soil organic matter despite increased plant productivity in an 80-years-old phosphorus-addition experiment. Commun. Earth Environ. 4, 251 (2023).

    Article  Google Scholar 

  8. Hu, Y. et al. Depth-dependent responses of soil organic carbon under nitrogen deposition. Glob. Change Biol. 30, e17247 (2024).

    Article  CAS  Google Scholar 

  9. Liu, H. Y., Huang, N., Zhao, C. M. & Li, J. H. Responses of carbon cycling and soil organic carbon content to nitrogen addition in grasslands globally. Soil Biol. Biochem. 186, 109164 (2023).

    Article  CAS  Google Scholar 

  10. Luo, X., Zhang, L., Lin, Y., Wen, D. & Hou, E. Nitrogen availability mediates soil organic carbon cycling in response to phosphorus supply: a global meta-analysis. Soil Biol. Biochem. 185, 109158 (2023).

    Article  CAS  Google Scholar 

  11. Zou, Z. C. et al. Decadal application of mineral fertilizers alters the molecular composition and origins of organic matter in particulate and mineral-associated fractions. Soil Biol. Biochem. 182, 109042 (2023).

    Article  CAS  Google Scholar 

  12. Angst, G. et al. Unlocking complex soil systems as carbon sinks: multi-pool management as the key. Nat. Commun. 14, 2967 (2023).

    Article  CAS  Google Scholar 

  13. Zhou, Z. et al. Global turnover of soil mineral-associated and particulate organic carbon. Nat. Commun. 15, 5329 (2024).

    Article  CAS  Google Scholar 

  14. Wu, J. et al. Particulate organic carbon is more sensitive to nitrogen addition than mineral-associated organic carbon: a meta-analysis. Soil. Res. 232, 105770 (2023).

    Google Scholar 

  15. Chen, J., Xiao, W., Zheng, C. & Zhu, B. Nitrogen addition has contrasting effects on particulate and mineral-associated soil organic carbon in a subtropical forest. Soil Biol. Biochem. 142, 107708 (2020).

    Article  CAS  Google Scholar 

  16. Yuan, X. et al. Sensitivity of soil carbon dynamics to nitrogen and phosphorus enrichment in an alpine meadow. Soil Biol. Biochem. 150, 107984 (2020).

    Article  CAS  Google Scholar 

  17. Meng, X. T. et al. Nitrogen fertilizer builds soil organic carbon under straw return mainly via microbial necromass formation. Soil Biol. Biochem. 188, 109223 (2024).

    Article  CAS  Google Scholar 

  18. Tao, F. et al. Microbial carbon use efficiency promotes global soil carbon storage. Nature 618, 981–985 (2023).

    Article  CAS  Google Scholar 

  19. Liang, C., Schimel, J. P. & Jastrow, J. D. The importance of anabolism in microbial control over soil carbon storage. Nat. Microbiol. 2, 17105 (2017).

    Article  CAS  Google Scholar 

  20. Ma, T. et al. Effects of short- and long-term nutrient addition on microbial carbon use efficiency and carbon accumulation efficiency in the Tibetan alpine grassland. Soil. Res. 229, 105657 (2023).

    Google Scholar 

  21. Feng, X. H. et al. Nitrogen input enhances microbial carbon use efficiency by altering plant-microbe-mineral interactions. Glob. Change Biol. 28, 4845–4860 (2022).

    Article  Google Scholar 

  22. Feng, J. G., Zhang, Q. F., Yuan, X. & Zhu, B. Effects of nitrogen and phosphorus addition on soil organic carbon: review and prospects. Chin. J. Plant Ecol. 46, 855–870 (2022).

    Article  CAS  Google Scholar 

  23. Guo, X. et al. Gene-informed decomposition model predicts lower soil carbon loss due to persistent microbial adaptation to warming. Nat. Commun. 11, 4897 (2020).

    Article  CAS  Google Scholar 

  24. Clausing, S. et al. Impact of nitrogen and phosphorus addition on resident soil and root mycobiomes in beech forests. Biol. Fertil. Soils 57, 1031–1052 (2021).

    Article  CAS  Google Scholar 

  25. Brown, R. W. et al. Nutrient (C, N and P) enrichment induces significant changes in the soil metabolite profile and microbial carbon partitioning. Soil Biol. Biochem. 172, 108779 (2022).

    Article  CAS  Google Scholar 

  26. Treseder, K. K. Nitrogen additions and microbial biomass: a meta-analysis of ecosystem studies. Ecol. Lett. 11, 1111–1120 (2008).

    Article  Google Scholar 

  27. Oburger, E. & Jones, D. L. Substrate mineralization studies in the laboratory show different microbial C partitioning dynamics than in the field. Soil Biol. Biochem. 41, 1951–1956 (2009).

    Article  CAS  Google Scholar 

  28. Liang, Z. et al. Microbial mediation of soil carbon loss at the potential climax of alpine grassland under warming. Soil Biol. Biochem. 192, 109395 (2024).

    Article  CAS  Google Scholar 

  29. Jiao, S. et al. Soil microbiomes with distinct assemblies through vertical soil profiles drive the cycling of multiple nutrients in reforested ecosystems. Microbiome 6, 146 (2018).

    Article  Google Scholar 

  30. Spohn, M. et al. Soil microbial carbon use efficiency and biomass turnover in a long-term fertilization experiment in a temperate grassland. Soil Biol. Biochem. 97, 168–175 (2016).

    Article  CAS  Google Scholar 

  31. Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., 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. 19, 988–995 (2013).

    Article  Google Scholar 

  32. Richy, E. et al. Phosphorus limitation promotes soil carbon storage in a boreal forest exposed to long-term nitrogen fertilization. Glob. Change Biol. 30, e17516 (2024).

    Article  CAS  Google Scholar 

  33. Spohn, M., Diáková, K., Aburto, F., Doetterl, S. & Borovec, J. Sorption and desorption of organic matter in soils as affected by phosphate. Geoderma 405, 115377 (2022).

    Article  CAS  Google Scholar 

  34. Yuan, Y. et al. Phosphorus addition decreases microbial residual contribution to soil organic carbon pool in a tropical coastal forest. Glob. Change Biol. 27, 454–466 (2021).

    Article  CAS  Google Scholar 

  35. Tang, S. et al. Soil nitrogen and phosphorus regulate decomposition of organic nitrogen compounds in the Rothamsted experiment. Soil Biol. Biochem. 196, 109502 (2024).

    Article  CAS  Google Scholar 

  36. Bölscher, T. et al. Beyond growth: the significance of non-growth anabolism for microbial carbon-use efficiency in the light of soil carbon stabilisation. Soil Biol. Biochem. 193, 109400 (2024).

    Article  Google Scholar 

  37. Ni, H. W., Liu, C. Y., Sun, B. & Liang, Y. T. Response of global farmland soil organic carbon to nitrogen application over time depends on soil type. Geoderma 406, 115542 (2022).

    Article  CAS  Google Scholar 

  38. Lekberg, Y. et al. Nitrogen and phosphorus fertilization consistently favor pathogenic over mutualistic fungi in grassland soils. Nat. Commun. 12, 3484 (2021).

    Article  CAS  Google Scholar 

  39. Qi, P. et al. Changes in soil particulate and mineral-associated organic carbon concentrations under nitrogen addition in China—a meta-analysis. Plant Soil 489, 439–452 (2023).

    Article  CAS  Google Scholar 

  40. Abdalla, K. et al. Long-term continuous farmyard manure application increases soil carbon when combined with mineral fertilizers due to lower priming effects. Geoderma 428, 116216 (2022).

    Article  CAS  Google Scholar 

  41. Shi, T.-S. et al. A global meta-analysis on the effects of organic and inorganic fertilization on grasslands and croplands. Nat. Commun. 15, 3411 (2024).

    Article  CAS  Google Scholar 

  42. Gaudaré, U. et al. Soil organic carbon stocks potentially at risk of decline with organic farming expansion. Nat. Clim. Change. 13, 719–725 (2023).

    Article  Google Scholar 

  43. Margaret, G. & Paul, P. Broadbalk wheat annual grain and straw yields 1968–2022. Electronic Rothamsted Archive (Rothamsted Research, 2023); https://doi.org/10.23637/rbk1-yld6822-01

  44. Rothamsted, R. Broadbalk experiment fertilizer and manure treatments, 1852–2021. Electron. Rothamsted Arch. Rothamsted Res. https://doi.org/10.23637/rbk1-FertTreats (2018).

    Article  Google Scholar 

  45. Vance, E. D., Brookes, P. C. & Jenkinson, D. S. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem. 19, 703–707 (1987).

    Article  CAS  Google Scholar 

  46. Murphy, J. & Riley, J. P. A modified single solution method for the determination of phosphate in natural waters. Anal. Chim. Acta 27, 31–36 (1962).

    Article  CAS  Google Scholar 

  47. Soong, J. L. et al. Five years of whole-soil warming led to loss of subsoil carbon stocks and increased CO2 efflux. Sci. Adv. 7, eabd1343 (2021).

    Article  CAS  Google Scholar 

  48. Bian, Q. et al. Divergent accumulation of microbe- and plant-derived carbon in different soil organic matter fractions in paddy soils under long-term organic amendments. Agric. Ecosyst. Environ. 366, 108934 (2024).

    Article  CAS  Google Scholar 

  49. Mou, Z. J. et al. Climatic and edaphic controls over the elevational pattern of microbial necromass in subtropical forests. CATENA 207, 105707 (2021).

    Article  CAS  Google Scholar 

  50. Zhang, X. et al. Aridity and NPP constrain contribution of microbial necromass to soil organic carbon in the Qinghai-Tibet alpine grasslands. Soil Biol. Biochem. 156, 108213 (2021).

    Article  CAS  Google Scholar 

  51. Xie, Y. et al. Crop rotation stage has a greater effect than fertilisation on soil microbiome assembly and enzymatic stoichiometry. Sci. Total Environ. 815, 152956 (2022).

    Article  CAS  Google Scholar 

  52. Sinsabaugh, R. L. & Follstad Shah, J. J. Ecoenzymatic stoichiometry and ecological theory. Annu. Rev. Ecol. Evol. Syst. 43, 313–343 (2012).

    Article  Google Scholar 

  53. Chong, J. et al. MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic Acids Res. 46, 486–494 (2018).

    Article  Google Scholar 

  54. Ma, Q. X. et al. Farmyard manure applications stimulate soil carbon and nitrogen cycling by boosting microbial biomass rather than changing its community composition. Soil Biol. Biochem. 144, 11 (2020).

    Article  Google Scholar 

  55. Glanville, H. C., Hill, P. W., Schnepf, A., Oburger, E. & Jones, D. L. Combined use of empirical data and mathematical modelling to better estimate the microbial turnover of isotopically labelled carbon substrates in soil. Soil Biol. Biochem. 94, 154–168 (2016).

    Article  CAS  Google Scholar 

  56. Galiwango, E., Abdel Rahman, N. S., Al-Marzouqi, A. H., Abu-Omar, M. M. & Khaleel, A. A. Isolation and characterization of cellulose and α-cellulose from date palm biomass waste. Heliyon 5, e02937 (2019).

    Article  Google Scholar 

  57. Jones, D. L. et al. Moisture activation and carbon use efficiency of soil microbial communities along an aridity gradient in the Atacama Desert. Soil Biol. Biochem. 117, 68–71 (2018).

    Article  CAS  Google Scholar 

  58. Jones, D. L. et al. Role of substrate supply on microbial carbon use efficiency and its role in interpreting soil microbial community-level physiological profiles (CLPP). Soil Biol. Biochem. 123, 1–6 (2018).

    Article  CAS  Google Scholar 

  59. Greenfield, L. M. et al. Is soluble protein mineralisation and protease activity in soil regulated by supply or demand? Soil Biol. Biochem. 150, 108007 (2020).

    Article  CAS  Google Scholar 

  60. Zhu, L. H., Liao, R. R., Wu, N., Zhu, G. S. & Yang, C. S. Heat stress mediates changes in fecal microbiome and functional pathways of laying hens. Appl. Microbiol. Biotechnol. 103, 461–472 (2019).

    Article  CAS  Google Scholar 

  61. Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M. & Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, 457–462 (2016).

    Article  Google Scholar 

  62. Tang, S. et al. Microbial community succession in soil is mainly driven by carbon and nitrogen contents rather than phosphorus and sulphur contents. Soil Biol. Biochem. 180, 109019 (2023).

    Article  CAS  Google Scholar 

  63. Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).

    Article  Google Scholar 

  64. Tang, S. et al. Soil carbon sequestration enhanced by long-term nitrogen and phosphorus fertilisation. Figshare https://doi.org/10.6084/m9.figshare.28792301 (2025).

  65. Tang, S. et al. Soil carbon sequestration enhanced by long-term nitrogen and phosphorus fertilisation. Code Ocean https://codeocean.com/capsule/2397954/tree/v1 (2025).

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Acknowledgements

This work was supported by the National Key R&D Program of China (2023YFD2302200, 2023YFD1900601), National Natural Science Foundation of China (32402680, 32172674, U24A20575), Zhejiang Provincial Natural Science Foundation (LZ23C150002), Smart Fertilization Project (05) and the Rothamsted Long-Term Experiments National Bioscience Research Infrastructure (RLTE-NBRI), supported by the UK Research and Innovation Biotechnology and Biological Sciences Research Council (UKRI-BBSRC) under award number BBS/E/RH/23NB0007 (2023–2028) and the Lawes Agricultural Trust. We also thank the curators of the Electronic Rothamsted Archive (e-RA) for providing access to data from the Rothamsted Long-Term Experiments.

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Authors and Affiliations

  1. Ministry of Education Key Lab of Environmental Remediation and Ecosystem Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China

    Sheng Tang, Wankun Pan, Zhongkui Luo, Lianghuan Wu, Yongchao Liang & Qingxu Ma

  2. State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, Hangzhou, China

    Sheng Tang, Wankun Pan, Zhongkui Luo, Lianghuan Wu, Yongchao Liang & Qingxu Ma

  3. Anhui Province Key Lab of Farmland Ecological Conservation and Nutrient Utilization, College of Resources and Environment, Anhui Agricultural University, Hefei, China

    Sheng Tang

  4. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China

    Yuanhe Yang

  5. Division of Terrestrial Ecosystem Research, Department of Microbiology and Ecosystem Science, Center of Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

    Wolfgang Wanek

  6. Department of Soil Science of Temperate Ecosystems, University of Göttingen, Göttingen, Germany

    Yakov Kuzyakov

  7. Bioeconomy Research Institute, Vytautas Magnus University, Agriculture Academy, Akademija, Lithuania

    Yakov Kuzyakov

  8. School of Environmental and Natural Sciences, Bangor University, Gwynedd, UK

    Karina A. Marsden, David R. Chadwick & Davey L. Jones

  9. Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA

    Guopeng Liang

  10. Institute for Global Change Biology and School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA

    Guopeng Liang

  11. Protecting Crops and the Environment, Rothamsted Research, Harpenden, UK

    Andrew S. Gregory

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Contributions

S.T., L.W. and Q.M. contributed to conceptualization, methodology, formal analysis and writing—original draft. Y.Y., Z.L. and G.L. contributed to writing—review and editing. W.W., K.A.M., Y.K. and D.L.J. contributed to writing—original draft. A.S.G., D.R.C., W.P. and D.L.J. contributed to investigation. K.A.M. and D.R.C. also contributed to methodology and conceptualization. Y.L. contributed to conceptualization and writing—review and editing. D.L.J. supervised the study and acquired funding.

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Correspondence to Qingxu Ma.

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Nature Geoscience thanks Kate Lajtha and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Camilla Brunello, Xujia Jiang and Carolina Ortiz Guerrero, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Global trends in nitrogen (N) and phosphorus (P2O5) fertilizer consumption since 1961.

a-c, Annual consumption rates of N (a), P2O5 (b), and combined N + P2O5 (c) fertilizers in China, India, the United Kingdom, and the United States. Data source: FAOSTAT (Food and Agriculture Organization of the United Nations, https://www.fao.org/faostat/en/#data/RFN).

Source data

Extended Data Fig. 2 Effects of long-term N and P fertilization on soil organic matter, amino sugars, and microbial necromass contents.

a, Soil organic matter. b, Muramic acid (MurN). c, Galactosamine (GalN). d, Glucosamine (GluN). e, Bacterial necromass C. f, Fungal necromass C. g, The ratio of bacterial to fungal necromass C. Box plots represent first and third quartiles (box), medians (central horizontal line), largest value smaller than 1.5 times the interquartile range (upper vertical line) and smallest value larger than 1.5 times the interquartile range (lower vertical line). Different letters above boxes indicate statistically significant differences among treatments (n = 4), determined using one-way ANOVA followed by Tukey’s post hoc test (two-sided; p < 0.05). Nil, no fertilization; P, P-only fertilization; N, N-only fertilization; NP, combined fertilization with N and P.

Source data

Extended Data Fig. 3 Variation in δ13C abundance and relationships between microbial necromass C and microbial C use efficiency and biomass C.

a, Linear relationship between microbial necromass C and microbial C use efficiency. b, Linear relationship between microbial necromass C and microbial biomass C. c, Box plots showing δ¹³C values of soil organic matter under four fertilization treatments: Nil (unfertilized control), N (nitrogen), P (phosphorus), and NP (combined N and P). Box plots represent first and third quartiles (box), medians (central horizontal line), largest value smaller than 1.5 times the interquartile range (upper vertical line) and smallest value larger than 1.5 times the interquartile range (lower vertical line). Different letters above boxes indicate statistically significant differences among treatments (n = 4), determined using one-way ANOVA followed by Tukey’s post hoc test (two-sided; p < 0.05). d, Linear relationship between soil δ13C and SOC content across all treatments. Solid line indicates the fitted linear regression; the shaded area represents the 95% confidence interval.

Source data

Extended Data Fig. 4 Metabolic responses to long-term N and P fertilization.

a, Heatmap of soil metabolite z-scores across fertilization regimes. Color gradient (red to blue) indicates metabolite concentrations standardized to the mean (scale bar: −2 to +2 standard deviations). b, Principal component analysis (PCA) of metabolite profiles, showing treatment-specific clustering (95% confidence ellipses). Treatment effects were tested by permutational multivariate analysis of variance (PERMANOVA) with multiple comparisons (p < 0.001, Benjamini–Hochberg corrected). Axes indicate percentage variance explained by each component. c, Comparative analysis of the abundances of differentially expressed metabolites under each fertilization treatment, with numbers in blue and red representing the number of significantly (two-sided t-test, FDR corrected, p < 0.05) decreased and increased metabolites between treatments, respectively. Nil, no fertilizer application; P, P-only fertilization; N, N-only fertilization; NP, combined fertilization with N and P.

Source data

Extended Data Fig. 5 Effects of long-term N and P fertilization on microbial community diversity, composition, and structure.

a, Archaeal α-diversity (Shannon index), community structure (non-metric multidimensional scaling, NMDS based on Bray–Curtis dissimilarities), and taxonomic composition under four fertilization treatments: Nil (no fertilizer), P (phosphorus fertilization), N (nitrogen fertilization), and NP (combined N and P fertilization). b, Bacterial community. c, Fungal community. Box plots represent first and third quartiles (box), medians (central horizontal line), largest value smaller than 1.5 times the interquartile range (upper vertical line) and smallest value larger than 1.5 times the interquartile range (lower vertical line). Different letters above boxes indicate statistically significant differences among treatments (n = 4), determined using one-way ANOVA followed by Tukey’s post hoc test (two-sided; p < 0.05). Different lowercase letters indicate significant differences (p < 0.05) between fertilization treatments. Asterisks in NMDS plots indicate significant differences in microbial community structure between treatments based on PERMANOVA, with p-values adjusted using the Benjamini–Hochberg method (FDR corrected, p < 0.05). Shaded areas in NMDS plots represent 95% confidence intervals for each treatment group.

Source data

Extended Data Fig. 6 Partial least squares path modelling (PLS-PM) of fertilization effects on SOC.

a, Pathways of fertilization effects on SOC. Arrow colors indicate effect direction (blue: positive, red: negative). Path coefficients are shown adjacent to arrows (standardized values). Significance was assessed via bootstrapping (1000 iterations). *p < 0.05, **p < 0.01, ***p < 0.001. b, Standardized total effects of factors on SOC.

Source data

Extended Data Fig. 7 Drivers of soil carbon pool variation: N and P contributions.

a, Random Forest analysis quantifying the relative importance of soil N and P fractions in explaining C pool variability. b, Pearson correlations combined with Random forest analysis between soil N, soil P and soil C contents. Colors indicate correlation direction (red: positive; blue: negative). Circle size represents variable importance in Random Forest analysis (larger circles = higher importance). *p < 0.05, **p < 0.01, ***p < 0.001. BN: bacterial necromass; FN: fungal necromass; TN: total necromass; POC: particulate organic C; MAOC: mineral-associated organic C; SOC: soil organic C; SOM: soil organic matter; DOC: dissolved organic C. c, Variation partitioning via redundancy analysis quantifying unique and shared explanatory power of N and P.

Source data

Extended Data Fig. 8 PRISMA-flowchart: observational meta-analysis.

a, Nitrogen fertilization. b, Phosphorus fertilization.

Supplementary information

Supplementary Information

Supplementary Figs. 1–8, materials and methods, Table 1 and 2 and references

Source data

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Tang, S., Pan, W., Yang, Y. et al. Soil carbon sequestration enhanced by long-term nitrogen and phosphorus fertilization. Nat. Geosci. (2025). https://doi.org/10.1038/s41561-025-01789-y

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