Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Enhanced stability of grassland soil temperature by plant diversity


Extreme weather events are occurring more frequently, and research has shown that plant diversity can help mitigate the impacts of climate change by increasing plant productivity and ecosystem stability. Although soil temperature and its stability are key determinants of essential ecosystem processes, no study has yet investigated whether plant diversity buffers soil temperature fluctuations over long-term community development. Here we have conducted a comprehensive analysis of a continuous 18-year dataset from a grassland biodiversity experiment with high spatial and temporal resolutions. Our findings reveal that plant diversity acts as a natural buffer, preventing soil heating in hot weather and cooling in cold weather. This diversity effect persists year-round, intensifying with the aging of experimental communities and being even stronger under extreme climate conditions, such as hot days or dry years. Using structural equation modelling, we found that plant diversity stabilizes soil temperature by increasing soil organic carbon concentrations and, to a lesser extent, plant leaf area index. Our results suggest that, in lowland grasslands, the diversity-induced stabilization of soil temperature may help to mitigate the negative effects of extreme climatic events such as soil carbon decomposition, thus slowing global warming.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Daily temporal pattern of soil temperature offset on a 30-min scale for each season.
Fig. 2: Sown plant diversity effects on daily soil temperature offset.
Fig. 3: Plant diversity effects on soil temperature stability over 18 years.
Fig. 4: Hypothetical mechanisms underlying significant plant diversity effects on soil temperature stability.

Similar content being viewed by others

Data availability

The data supporting the results of this study are publicly available in the Jena Experiment Information System (

Code availability

The code supporting the results of this study is deposited in the Jena Experiment Information System (


  1. Rahmstorf, S. & Coumou, D. Increase of extreme events in a warming world. Proc. Natl Acad. Sci. USA 108, 17905–17909 (2011).

    Article  Google Scholar 

  2. Zhang, Y., Chen, W., Smith, S. L., Riseborough, D. W. & Cihlar, J. Soil temperature in Canada during the twentieth century: complex responses to atmospheric climate change. J. Geophys. Res. Atmospheres 110, D03112 (2005).

    Google Scholar 

  3. Pregitzer, K. S. & King, J. S. in Nutrient Acquisition by Plants: An Ecological Perspective (ed. BassiriRad, H.) 277–310 (Springer, 2005).

  4. Luo, H., Xu, H., Chu, C., He, F. & Fang, S. High temperature can change root system architecture and intensify root interactions of plant seedlings. Front. Plant Sci. 11, 160 (2020).

    Article  Google Scholar 

  5. 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  Google Scholar 

  6. Achury, R. et al. Plant diversity and functional identity alter ant occurrence and activity in experimental grasslands. Ecosphere 13, e4252 (2022).

    Article  Google Scholar 

  7. Pivonia, S., Cohen, R., Kigel, J. & Katan, J. Effect of soil temperature on disease development in melon plants infected by Monosporascus cannonballus. Plant Pathol. 51, 472–479 (2002).

    Article  Google Scholar 

  8. Onwuka, B. M. Effects of soil temperature on some soil properties and plant growth. Adv. Plants Agric. Res. 8, 34–37 (2018).

    Google Scholar 

  9. Nievola, C. C., Carvalho, C. P., Carvalho, V. & Rodrigues, E. Rapid responses of plants to temperature changes. Temp. Multidiscip. Biomed. J. 4, 371–405 (2017).

    Google Scholar 

  10. De Frenne, P. et al. Global buffering of temperatures under forest canopies. Nat. Ecol. Evol. 3, 744–749 (2019).

    Article  Google Scholar 

  11. De Frenne, P. et al. Forest microclimates and climate change: importance, drivers and future research agenda. Glob. Change Biol. 27, 2279–2297 (2021).

    Article  Google Scholar 

  12. Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020).

    Article  Google Scholar 

  13. Gillerot, L. et al. Forest structure and composition alleviate human thermal stress. Glob. Change Biol. 28, 7340–7352 (2022).

    Article  Google Scholar 

  14. Isbell, F. et al. Biodiversity increases the resistance of ecosystem productivity to climate extremes. Nature 526, 574–577 (2015).

    Article  Google Scholar 

  15. Wagg, C. et al. Biodiversity–stability relationships strengthen over time in a long-term grassland experiment. Nat. Commun. 13, 7752 (2022).

    Article  Google Scholar 

  16. Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).

    Article  Google Scholar 

  17. Borer, E. T., Seabloom, E. W. & Tilman, D. Plant diversity controls arthropod biomass and temporal stability. Ecol. Lett. 15, 1457–1464 (2012).

    Article  Google Scholar 

  18. Proulx, R. et al. Diversity promotes temporal stability across levels of ecosystem organization in experimental grasslands. PLoS ONE 5, e13382 (2010).

    Article  Google Scholar 

  19. Eisenhauer, N. et al. Impact of above- and below-ground invertebrates on temporal and spatial stability of grassland of different diversity. J. Ecol. 99, 572–582 (2011).

    Article  Google Scholar 

  20. Bond-Lamberty, B. & Thomson, A. Temperature-associated increases in the global soil respiration record. Nature 464, 579–582 (2010).

    Article  Google Scholar 

  21. Spehn, E. M., Joshi, J., Schmid, B., Diemer, M. & Christian, K. Above-ground resource use increases with plant species richness in experimental grassland ecosystems. Funct. Ecol. 14, 326–337 (2000).

    Article  Google Scholar 

  22. Zhang, S., Landuyt, D., Verheyen, K. & De Frenne, P. Tree species mixing can amplify microclimate offsets in young forest plantations. J. Appl. Ecol. 59, 1428–1439 (2022).

    Article  Google Scholar 

  23. Guimarães-Steinicke, C. et al. Biodiversity facets affect community surface temperature via 3D canopy structure in grassland communities. J. Ecol. 109, 1969–1985 (2021).

    Article  Google Scholar 

  24. Spehn, E. M., Joshi, J., Schmid, B., Alphei, J. & Körner, C. Plant diversity effects on soil heterotrophic activity in experimental grassland ecosystems. Plant Soil 224, 217–230 (2000).

    Article  Google Scholar 

  25. Weisser, W. W. et al. Biodiversity effects on ecosystem functioning in a 15-year grassland experiment: patterns, mechanisms and open questions. Basic Appl. Ecol. 23, 1–73 (2017).

    Article  Google Scholar 

  26. Weigel, R. et al. Ecosystem processes show uniform sensitivity to winter soil temperature change across a gradient from central to cold marginal stands of a major temperate forest tree. Ecosystems 24, 1545–1560 (2021).

    Article  Google Scholar 

  27. Schimel, J. P., Bilbrough, C. & Welker, J. M. Increased snow depth affects microbial activity and nitrogen mineralization in two Arctic tundra communities. Soil Biol. Biochem. 36, 217–227 (2004).

    Article  Google Scholar 

  28. Lembrechts, J. J. et al. Global maps of soil temperature. Glob. Change Biol. 28, 3110–3144 (2022).

    Article  Google Scholar 

  29. Crowther, T. W. et al. Quantifying global soil carbon losses in response to warming. Nature 540, 104–108 (2016).

    Article  Google Scholar 

  30. Melillo, J. M. et al. Long-term pattern and magnitude of soil carbon feedback to the climate system in a warming world. Science 358, 101–105 (2017).

    Article  Google Scholar 

  31. Reich, P. B. et al. Impacts of biodiversity loss escalate through time as redundancy fades. Science 336, 589–592 (2012).

    Article  Google Scholar 

  32. Ravenek, J. M. et al. Long-term study of root biomass in a biodiversity experiment reveals shifts in diversity effects over time. Oikos 123, 1528–1536 (2014).

    Article  Google Scholar 

  33. Huang, Y. et al. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362, 80–83 (2018).

    Article  Google Scholar 

  34. Vicente-Serrano, S. M., Beguería, S. & López-Moreno, J. I. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J. Clim. 23, 1696–1718 (2010).

    Article  Google Scholar 

  35. García-Palacios, P., Gross, N., Gaitán, J. & Maestre, F. T. Climate mediates the biodiversity-ecosystem stability relationship globally. Proc. Natl Acad. Sci. USA 115, 8400–8405 (2018).

    Article  Google Scholar 

  36. Zhu, D. et al. Controls of soil organic matter on soil thermal dynamics in the northern high latitudes. Nat. Commun. 10, 3172 (2019).

    Article  Google Scholar 

  37. Horton, R. in Methods of Soil Analysis (eds Dane, J. H. & Topp, G. C.) 1227–1232 (Wiley, 2002).

  38. Lange, M., Eisenhauer, N., Chen, H. & Gleixner, G. Increased soil carbon storage through plant diversity strengthens with time and extends into the subsoil. Glob. Change Biol. 29, 2627–2639 (2023).

    Article  Google Scholar 

  39. Roscher, C. et al. The role of biodiversity for element cycling and trophic interactions: an experimental approach in a grassland community. Basic Appl. Ecol. 5, 107–121 (2004).

    Article  Google Scholar 

  40. Roscher, C. et al. What happens to the sown species if a biodiversity experiment is not weeded? Basic Appl. Ecol. 14, 187–198 (2013).

    Article  Google Scholar 

  41. Pfisterer, A. B., Joshi, J., Schmid, B. & Fischer, M. Rapid decay of diversity-productivity relationships after invasion of experimental plant communities. Basic Appl. Ecol. 5, 5–14 (2004).

    Article  Google Scholar 

  42. Huang, Y., Kolle, O., Ebeling, A. & Eisenhauer, N. Climate data (daily resolution) from the climate station in The Jena Experiment from 2003 to 2022. Jena Experiment Information System (2023).

  43. Cardinale, B. J. et al. The functional role of producer diversity in ecosystems. Am. J. Bot. 98, 572–592 (2011).

    Article  Google Scholar 

  44. Huang, Y., Kolle, O., Kübler, K., Ebeling, A. & Eisenhauer, N. Standardized Precipitation-Evapotranspiration Index (SPEI) in the Jena Experiment from 2003 to 2021. Jena Experiment Information System (2023).

  45. Beguería, S., Vicente-Serrano, S. M., Reig, F. & Latorre, B. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int. J. Climatol. 34, 3001–3023 (2014).

    Article  Google Scholar 

  46. Allen, R., Pereira, L. & Smith, M. Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements-FAO Irrigation and Drainage Paper 56, Vol. 56 (Food and Agriculture Organization of the United Nations, 1998).

  47. Huang, Y. et al. Community leaf area index (LAI) in the Main Experiment from 2003 to 2020. Jena Experiment Information System (2023).

  48. Fischer, C. et al. Plant species richness and functional groups have different effects on soil water content in a decade-long grassland experiment. J. Ecol. 107, 127–141 (2019).

    Article  Google Scholar 

  49. Eisenhauer, N. et al. Plant diversity effects on soil microorganisms support the singular hypothesis. Ecology 91, 485–496 (2010).

    Article  Google Scholar 

  50. Scheu, S. Automated measurement of the respiratory response of soil microcompartments: active microbial biomass in earthworm faeces. Soil Biol. Biochem. 24, 1113–1118 (1992).

    Article  Google Scholar 

  51. Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nat. Commun. 6, 6707 (2015).

    Article  Google Scholar 

  52. Zuur, A. F., Saveliev, A. A. & Ieno, E. N. in Beginner’s Guide to Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA, Volume 1 Using GLM and GLMM 267–299 (Highland Statistics Ltd, 2017).

  53. Ochsner, T. E., Horton, R. & Ren, T. A new perspective on soil thermal properties. Soil Sci. Soc. Am. J. 65, 1641–1647 (2001).

    Article  Google Scholar 

  54. Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution and systematics. Methods Ecol. Evol. 7, 573–579 (2016).

  55. Huang, Y. et al. Data and R code used in: enhanced stability of grassland soil temperature by plant diversity. Jena Experiment Information System (2023).

Download references


We express our gratitude to the fieldworkers of the Jena Experiment. We thank the technical staff S. Eismann, G. Kratzsch, U. Köber, K. Kunze and H. Scheffler for their work in maintaining the field site and the many student helpers for weeding the experimental plots and assisting with the measurements. We also thank J. Hines for providing valuable data-analysis suggestions. Special thanks go to G. Rada (iDiv) for her exceptional artistic contribution to the illustration of Fig. 4. We would also like to thank the source of the image ‘Soil with roots’ from V. Romanov/, which was skilfully incorporated into the illustration. The Jena Experiment is funded by the German Research Foundation (DFG, FOR 5000). We gratefully acknowledge the support of iDiv, which is funded by the German Research Foundation (DFG – FZT 118, 202548816). M.S. is supported by the German Research Foundation (DFG, SH 1682/1-1). N.E. is also funded by the German Research Foundation (DFG, EI 862/29-1).

Author information

Authors and Affiliations



E.-D.S., O.K. and K.K. installed and maintained the soil temperature measurement system. N.E. sourced the funding. Y.H. conceived the project. Y.H., G.S. and H.D. cleaned and analysed the data. D.E. made substantial contributions to time-series analysis using a Bayesian approach, while N.E., B.S., H.S., A.E., J.D. and M.S. provided valuable insights and ideas for methodology development and data analysis. Y.H. and G.S. wrote the first draft of the paper. A.E. is the scientific coordinator of the Jena Experiment. G.G., A.H., M.L., C.R., B.S., A.W. and W.W.W. originally created the dataset of the covariate variables. All authors contributed to the development of the ideas, discussed the analysis and results, and edited the paper text.

Corresponding author

Correspondence to Yuanyuan Huang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Geoscience thanks Pieter De Frenne and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang, in collaboration with the Nature Geoscience team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Temperature time series at different heights and soil depths.

Data are from plots in block 2.

Extended Data Fig. 2 Air temperature at 2 m (a), precipitation (b), soil temperature at 8 cm (c), and drought index (SPEI) (d) change with time at the field site of the Jena Experiment.

In panels a and c, the lines represent predictions derived from simple linear regression models, with the shaded bands denoting the corresponding 95% confidence intervals (n = 18).

Extended Data Fig. 3 Experiment design (a) and photos of cable boxes and the temperature sensor in the plot (b, c).

a, Plots are arranged in four blocks following the randomized block design. Each plot has an area of 20 × 20 m. Different colours represent different levels of the sown plant diversity. Notably, two monoculture plots marked with a cross in panel a were excluded from our study in 2009 due to insufficient coverage of the target species. b, A photo showing the cable box in each plot for the soil temperature sensors. c, Soil temperature sensors at three different layers (5, 15, 60 cm) in block 2. In other three blocks, only the first two layers (5 and 15 cm) were measured. Photo credit: Karl Kübler.

Extended Data Fig. 4 Extreme climate days in plant communities with different plant diversity levels in each year.

Colour gradient represents the sown plant species richness from 0 to 60. The circles represent the corresponding data points. The mean number of heat days (maximum soil temperature at 5 cm is higher than 25 °C) and standard error (n = 14, 16 or 4) are shown in panel a. The mean number of freezing days (minimum soil temperature at 5 cm is lower than 0 °C) and standard error (n = 14, 16, or 4) are shown in panel b. Note that in 2013, summer data (June, July and August) is missing due to the flood.

Extended Data Fig. 5 Linear relationship between air temperature and the effects of plant diversity on daily soil temperature offset at 5 cm during days without snow cover (a) and the effects of snow cover depth on the plant diversity effects (b).

Here, plant diversity is depicted by sown plant species richness. a, Different colours represent different seasons. The lines were predicted from linear models (n = 6095). b, The black linear line and grey band representing the 95% confidence intervals are predicted from a linear mixed-effects model with the year, the months within year, and the autocorrelation of the plant diversity effects between days within year as random terms (n = 190). The symbols F and P in panel b represent the F-ratios and the corresponding P value, respectively, derived from the ANOVA table of linear mixed-effects models. The degrees of freedom for both the numerator and denominator are given in the subscript of the F value.

Extended Data Fig. 6 Nonlinear evolution of plant diversity effects over time.

Multiple nonlinear models were examined, with the logarithmic curve demonstrating the best fit. The linear year was logarithmically transformed, followed by a straightforward linear regression analysis to assess the influence of the transformed year on the effects of plant diversity on soil temperature annual stability. The depicted nonlinear curve and 95% confidence intervals band represents the model’s prediction after backtransformation of the independent variable year (n = 18).

Extended Data Table 1 Summary of annual climate data and number of days with missing soil temperature data
Extended Data Table 2 Summary statistics from mixed-effects models for the effects of air temperature, season, and year on the buffering effects of plant diversity on the soil temperature offset between vegetated and bare plots

Supplementary information

Supplementary Information

Supplementary Appendices 1 and 2, Figs. 1–13 and Tables 1–3.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, Y., Stein, G., Kolle, O. et al. Enhanced stability of grassland soil temperature by plant diversity. Nat. Geosci. 17, 44–50 (2024).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing