Thermal responses of soil microbial growth and respiration, global dataset

Kodie I. S. Chontos, Daniela Guasconi, Rebecca M. Varney, Maja Siegenthaler, Honorine Dumontel, Lettice Hicks, Luiz Domeignoz-Horta, Albert Brangarí, Johannes Rousk, Stefano Manzoni

The dataset provides measurements from published laboratory studies that quantify soil microbial growth and respiration responses to short-term experimental warming. It consists of harmonized observations across multiple studies, including both original reported values and values expressed in standardized units (µg C g⁻¹ soil h⁻¹) for direct comparison, as well as meta-data from the sites including soil properties, mean annual temperature (MAP), mean annual precipitation (MAP), and the conditions of the incubation experiments (e.g. incubation duration, temperatures, and pre-incubation).

The studies span between 2004 and 2025 across a wide range of soil and climatic conditions, and from different ecosystems, presented as spatially scattered sampling sites. Measurements were generated through short-term laboratory incubations using established methods for microbial growth (e.g., isotopic tracing and substrate incorporation) and respiration (e.g., gas chromatography).

TerrestrialSoilSoil microbesMicrobial growthTemperature responseSoil carbonCarbon quality

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Citation

References

Alster CJ, Schipper LA, Bååth E (2025) Thermal Adaptation of Bacterial and Fungal Growth in a Geothermally Influenced Soil Transect. Global Change Biology 31. https://doi.org/10.1111/gcb.70605

BÁRCENAS‐MORENO G, GÓMEZ‐BRANDÓN M, ROUSK J, BÅÅTH E (2009) Adaptation of soil microbial communities to temperature: comparison of fungi and bacteria in a laboratory experiment. Global Change Biology 15:2950–2957. https://doi.org/10.1111/j.1365-2486.2009.01882.x

Cruz-Paredes C, Tájmel D, Rousk J (2021) Can moisture affect temperature dependences of microbial growth and respiration? Soil Biology and Biochemistry 156:108223. https://doi.org/10.1016/j.soilbio.2021.108223

Cruz-Paredes C, Tájmel D, Rousk J (2023) Variation in Temperature Dependences across Europe Reveals the Climate Sensitivity of Soil Microbial Decomposers. Applied and Environmental Microbiology 89. https://doi.org/10.1128/aem.02090-22

Domeignoz‐Horta LA, Pold G, Erb H, Sebag D, Verrecchia E, Northen T, Louie K, Eloe‐Fadrosh E, Pennacchio C, Knorr MA, Frey SD, Melillo JM, DeAngelis KM (2022) Substrate availability and not thermal acclimation controls microbial temperature sensitivity response to long‐term warming. Global Change Biology 29:1574–1590. https://doi.org/10.1111/gcb.16544

Donhauser J, Qi W, Bergk‐Pinto B, Frey B (2021) High temperatures enhance the microbial genetic potential to recycle C and N from necromass in high‐mountain soils. Global Change Biology 27:1365–1386. https://doi.org/10.1111/gcb.15492

Kritzberg E, Bååth E (2022) Seasonal variation in temperature sensitivity of bacterial growth in a temperate soil and lake. FEMS Microbiology Ecology 98. https://doi.org/10.1093/femsec/fiac111

Li J, Pei J, Dijkstra FA, Nie M, Pendall E (2021) Microbial carbon use efficiency, biomass residence time and temperature sensitivity across ecosystems and soil depths. Soil Biology and Biochemistry 154:108117. https://doi.org/10.1016/j.soilbio.2020.108117

Pietikäinen J, Pettersson M, Bååth E (2005) Comparison of temperature effects on soil respiration and bacterial and fungal growth rates. FEMS Microbiology Ecology 52:49–58. https://doi.org/10.1016/j.femsec.2004.10.002

Ren C, Zhou Z, Delgado-Baquerizo M, Bastida F, Zhao F, Yang Y, Zhang S, Wang J, Zhang C, Han X, Wang J, Yang G, Wei G (2024) Thermal sensitivity of soil microbial carbon use efficiency across forest biomes. Nature Communications 15. https://doi.org/10.1038/s41467-024-50593-6

Rinnan R, Rousk J, Yergeau E, Kowalchuk GA, Bååth E (2009) Temperature adaptation of soil bacterial communities along an Antarctic climate gradient: predicting responses to climate warming. Global Change Biology 15:2615–2625. https://doi.org/10.1111/j.1365-2486.2009.01959.x

Rousk J, Frey SD, Bååth E (2012) Temperature adaptation of bacterial communities in experimentally warmed forest soils. Global Change Biology 18:3252–3258. https://doi.org/10.1111/j.1365-2486.2012.02764.x

chnecker J, Spiegel F, Li Y, Richter A, Sandén T, Spiegel H, Zechmeister-Boltenstern S, Fuchslueger L (2023) Microbial responses to soil cooling might explain increases in microbial biomass in winter. Biogeochemistry 164:521–535. https://doi.org/10.1007/s10533-023-01050-x

Simon E, Canarini A, Martin V, Séneca J, Böckle T, Reinthaler D, Pötsch EM, Piepho H-P, Bahn M, Wanek W, Richter A (2020) Microbial growth and carbon use efficiency show seasonal responses in a multifactorial climate change experiment. Communications Biology 3. https://doi.org/10.1038/s42003-020-01317-1

Tájmel D, Cruz‐Paredes C, Rousk J (2023) Heat wave‐induced microbial thermal trait adaptation and its reversal in the Subarctic. Global Change Biology 30. https://doi.org/10.1111/gcb.17032

Van Gestel, N. C., Reischke, S., & Bååth, E. (2013). Temperature sensitivity of bacterial growth in a hot desert soil with large temperature fluctuations. Soil Biology and Biochemistry, 65, 180–185. https://doi.org/10.1016/j.soilbio.2013.05.016

Weedon JT, Bååth E, Rijkers R, Reischke S, Sigurdsson BD, Oddsdottir E, van Hal J, Aerts R, Janssens IA, van Bodegom PM (2023) Community adaptation to temperature explains abrupt soil bacterial community shift along a geothermal gradient on Iceland. Soil Biology and Biochemistry 177:108914. https://doi.org/10.1016/j.soilbio.2022.108914

Yang J, Wang Z, Chang Q, Liu Z, Jiang Q, Fan X, Meng D, Bai E (2025) Temperature effects on microbial carbon use efficiency and priming effects in soils under vegetation restoration. CATENA 249:108632. https://doi.org/10.1016/j.catena.2024.108632

Zheng Q, Hu Y, Zhang S, Noll L, Böckle T, Richter A, Wanek W (2019) Growth explains microbial carbon use efficiency across soils differing in land use and geology. Soil Biology and Biochemistry 128:45–55. https://doi.org/10.1016/j.soilbio.2018.10.006

Data description

The dataset Meta_Microbial.xlsx contains soil Microbial Growth and Respiration rates, and the meta-data pertaining to each site. The dataset provided is compiled as a .xlsx spreadsheet file with two sheets:

README.md

contains information on the content and structure of the main dataset.

Source_data.csv

contains information on each paper including DOI's, year of publication, Source_ID,'Data_type' and data aquisition.

Microbial_all.csv

containing all microbial growth and respiration measurements and accompanying metadata.

Variables:

• Study_type
  • A – Studies which measure bacterial growth using leucine incorporation and fungal growth using acetate incorporation, and respiration using gas chromatography
  • B – Studies which measure total microbial growth using 18O water tracing method, and respiration using gas chromatography
  • C – Studies which measure only bacterial growth using leucine incorporation, no respiration measured.
• Data_source Citation of the source (e.g. Ren et al. 2018)
• Year Year of publication
• Source_ID Numerical ID allocated to a given source (1,2,3…)
• Lat Decimal coordinates of sampling sites
• Long Decimal coordinates of sampling sites
• Elevation_m Elevation of study site in meters
• Land_cover 13 categories of land cover including:
  • Agricultural land
  • Coniferous forest
  • Broadleaf forest
  • Rainforest
  • Other forest
  • Dryland
  • Wetland
  • Grassland
  • Shrubland/Heathland
  • Mosses/Lichens/Rocky vegetation
  • Urban
  • Alpine
  • Geothermal zone
• Sampling_year Year of soil sampling
• Sampling_month Month of soil sampling
• Site_ID Based on geographical coordinates, MAP and MAT - if field warming is used to manipulate climatic conditions then a different site code is assigned.
• Plot_ID Assigned according to plot replicates indicated in the study, treated separately in incubation experiment.
• Soil_ID Based on soil properties, samples with differing properties (pH, SOM, etc.) are assigned different codes.
• Sample_ID Based on treatment soil samples were subjected to during the incubation (e.g. different soil moisture)
• Rep_ID These are replicates established post sampling, in the lab, and incubated several times at the same temperature.
• MAST_C Mean annual soil temperature (°C).
• MAT_C Mean annual atmospheric Temperature (°C).
• MAP_mm Mean Annual Precipitation (mm).
• pH Soil acidity (1-7 scale).
• TC Total soil organic carbon.
• TC_units units for total carbon indicated in the original data sources.
• TN Total Nitrogen.
• TN_units units for total nitrogen indicated in the original paper.
• C_N Carbon to Nitrogen ratio.
• SOM Soil Organic Matter.
• SOM_units Units for Soil Organic Matter indicated in the original paper.
• SOC Soil Organic Carbon.
• SOC_units Units for Soil Organic Carbon indicated in the original paper.
• Clay percentage of clay.
• Sand percentage of sand.
• Silt percentage of silt.
• Texture texture of the soil according to the USDA soil triangle.
• BD Bulk Density (g/cm3)
• MBC – Microbial Biomass Carbon
• WHC_perc Water holding capacity (%) of the soil samples were adjusted to prior to incubations.
• Treatment the studies had varying treatments such as land use, or field warming; the treatment is listed here.
• Field_W_method Five methods of field warming including:
  • IR – Infrared Heating
  • OTC – Open Top Chambers
  • HC – Heating cables
  • TP – Transplant (moving samples from higher to lower elevation).
  • NA – For control, and other studies which do not conduct field warming.
  • Field_W – Control, Warmed, or Cooled.
  • FW_T – Number of degrees (°C) of temperature increase or decrease compared to the control plots in climate manipulation experiments.
  • Zero is assigned for control plots, and NA for everything else.
• FW_durationDuration of field warming (Change to be in months for all)
• Incubation_T_BG Incubation temperatures (°C) used to measure bacterial growth.
• Duration_BG Duration (hours) the incubations took place for bacterial growth.
• Incubation_T_FG Incubation temperatures (°C) used to measure fungal growth.
• Duration_FG - Duration (hours) the incubations took place for fungal growth. measurements.
• Incubation_T – Incubation temperatures used for measuring respiration and total microbial growth.
• Duration_Growth – Duration (hours) the incubations took place for microbial growth.
• Duration_Resp_h – Duration (hours) the incubations took place for microbial growth.
• CUE Carbon Use Efficiency; Estimated from converted values for growth and respiration. CUE = Growth/(Growth + Respiration)
• SOM_ug_g Soil organic matter (SOM) converted to μg SOM g-1 soil h-1
• SOC_ug_g Soil organic carbon (SOC) converted to μg SOC g-1 soil h-1
• BG_ug_g Bacterial growth converted to μg C g-1 soil h-1
• FG_ug_g Fungal growth converted to μg C g-1 soil h-1
• Growth_ug_g Total microbial growth converted to μg C g-1 soil h-1; this contains measurements of total growth using 18O water tracing method and bacterial growth + fungal growth as an estimate of total growth for studies using leucine and acetate incorporation.
• Resp_ug_g Respiration converted to μg C g-1 soil h-1
• Uptake Uptake calculated as Growth + Respiration; this was only possible using paired measurements of growth and respiration.
• CQ Soil organic carbon quality estimates using the Arrhenius model to calculate Uptake at 15°C / SOC

Project

This project was funded by European Union Horizon 2020 Research and Innovation Programme, project “Holistic management practices, modeling, and monitoring for European forest soils – HoliSoils” (grant agreement 101000289). The European Research Council under the European Union Horizon 2020 Research and Innovation Programme, project “Microbial responses to land use and climatic changes in the light of evolution – SMILE” (grant agreement 10100160) and the Schmidt Sciences LLC, project “Carbon Loss In Plants, Soils and Oceans – CALIPSO”.

Publisher

Bolin Centre Database

License

Open Data Commons Attribution License (ODC-By) v1.0

First name

Kodie

Last name or organisation

Chontos

Email address

k.chontos@outlook.com

Address

Department of Physical Geography; Stockholm University

Postal code

SE-106 91

City

Stockholm

Country

Sweden

Dataset language

English

DOI

Time