Soil microbial communities provide numerous ecosystem functions, such as nutrient cycling, decomposition, and carbon storage. However, global change, including land-use and climate changes, affects soil microbial communities and activity. As extreme weather events (e.g., heatwaves) tend to increase in magnitude and frequency, we investigated the effects of heat stress on the activity (e.g., respiration) of soil microbial communities that had experienced four different long-term land-use intensity treatments (ranging from extensive grassland, intensive grassland to organic and conventional croplands) and two climate conditions (ambient vs. predicted future climate).

Here, using soils from a long-term field experiment and laboratory heat stress, we investigate the combined history effects of climate change and land-use intensity on soil microbial respiration and its respiration response to heat stress (Fig. 1). Soil samples were collected from the Global Change Experimental Facility (GCEF, Fig. 1A), where soils had been subjected to a future climate treatment and varying levels of land-use intensity for ten years. To simulate heat stress, soils were incubated at either 20 °C, 25 °C, 30 °C, or 35 °C under laboratory conditions, and we assessed the soil microbial respiration response (Fig. 1C).

To investigate how soil microbial communities respond to short-term climatic extremes under realistic background conditions, we applied a controlled heat stress treatment on top of an existing long-term global change experiment. The experiment has been running for over a decade and includes a future climate manipulation (+0.5°C warming, altered precipitation patterns with a summer drought) combined with different land-use regimes. Importantly, these treatments are superimposed on ambient environmental conditions, meaning that natural climate variability and extreme events such as heatwaves have occurred throughout the duration of the experiment (Bei et al., 2023). As a result, the microbial communities have been shaped by both the experimental treatments and naturally occurring events, creating a realistic baseline of chronic global change exposure. The additional heat stress treatment was applied to simulate an acute short-term stressor, enabling us to assess microbial responses to extreme temperature events in the context of pre-existing long-term stress. This approach reflects future climate scenarios, where ecosystems will be increasingly exposed to compound stressors (IPCC, 2021; Pascual et al., 2022).

Study site

The Global Change Experimental Facility (GCEF) is located in Bad Lauchstädt, Central Germany (51°23’30"N, 11°52’49"E, 116 m a.s.l.) and is part of the Helmholtz Centre for Environmental Research - UFZ (Schädler et al., 2019). The GCEF was established in 2013 on a former arable field to study the influence of climate change on terrestrial ecosystems within different land-use intensities (Fig. 1A). The region is characterized by a sub-continental climate with an average precipitation of 442 mm and a mean temperature of 10.9°C (2014-2024). The soil type is Haplic Chernozem, which contains 70% silt and 20% clay. Therefore, it holds high levels of organic carbon and has a high water-holding capacity (Altermann et al., 2005; Korell et al., 2024).

Experimental setup and land-use treatments

The GCEF consists of ten main plots (80 m × 24 m), each divided into five plots (16 m × 24 m), resulting in a total of 50 plots. In each main plot, five land-use treatments were randomly assigned to experimental plots: extensively used grassland, intensively used grassland, organic cropland, conventional cropland, and an extensively used pasture treatment which was excluded from this study to balance the cropland vs. grassland treatments. The treatments vary in management intensity, including differences in fertilization, pesticide use, plant species richness, and management practices. Extensive grasslands, representing the lowest management intensity, consist of 56 plant species, receive no fertilization, and are mown twice per year. Intensive grasslands, by contrast, are composed of five grass cultivars, are fertilized with nitrogen (N) and phosphorus (P), and are mown up to four times per year. Organic cropland is managed without any pesticides and includes a six-year crop rotation, with legumes sown every three years, along with potassium-magnesium-sulfur (K-Mg-S) fertilization. Conventional cropland, the most intensive management type, follows a three-year crop rotation of winter rape, winter wheat, and winter barley, and relies on the use of N-P-K fertilizers and pesticides (Schädler et al., 2019).

Future climate treatment

Half of the plots are exposed to a future climate scenario, whereas the other half is exposed to ambient climate conditions. The future climate scenario was designed based on regional climate models for 2070–2100: It features a general temperature increase of 0.55°C, a 10% increase in precipitation during spring and fall, and a 20% decrease in precipitation during summer (Schädler et al., 2019). The climate manipulation was achieved by steel roof structures above each main plot, entailing tarpaulins which are closed from sunset to sunrise to achieve passive nighttime warming (Suppl. Figure S1). Additionally, the tarpaulins also reduce rainfall in summer, while an irrigation system is used to increase precipitation. Control plots had similar roof constructions to account for potential side effects (Kreyling et al., 2017).

Soil sampling

Soil samples were collected on October 10, 2024, using a steel core sampler with a diameter of 1.5 cm and a depth of 15 cm. To account for potential heterogeneity, five subsamples were taken per plot, pooled, and sieved through a 2 mm mesh. The resulting soil samples were then used to measure soil microbial respiration at four different soil temperatures, with two separate measurements conducted (i.e., technical replicates) to ensure reliable results. For the first measurement, the samples were stored at 4°C. For the second measurement, the samples were frozen at -20°C to preserve them for later analysis. Prior to soil microbial respiration and community analysis, unfrozen samples were acclimated at 20°C for three days, while frozen samples were acclimated for seven days at 20°C to ensure complete defrosting.

Soil microbial analyses and heat treatment

Soil microbial respiration was measured using an O₂-micro-compensation system (Scheu, 1992). For each soil sample, four subsamples (approx. 7g) were collected. Each subsample was subjected to one out of the four temperature conditions—20°C, 25°C, 30°C, or 35°C—for a duration of 20 h, while measuring soil microbial respiration as the oxygen consumption per hour per dry weight of soil in µl O₂ per gram dry weight per hour for a 24-hour interval (Suppl. Table S1). To assess total soil microbial biomass (μg C_mic g⁻¹ soil dry weight), we measured the maximum respiratory response by adding glucose (4 mg g⁻¹ dry weight soil, dissolved in 1.25 ml distilled water) to soil samples measured at 20°C (following Scheu, 1992). This approach provides a robust proxy for the size of the active microbial biomass. We did not correct samples for soil moisture content across treatments, as soils were supposed to reflect natural field conditions under different long-term treatments. We acknowledge that differences in initial moisture content may influence microbial respiration, but these were considered an integral part of the treatment effect and not experimentally standardized.

We used phospholipid fatty acid (PLFA) analysis to assess microbial community structure, as it provides quantitative measurements of living microbial biomass and major functional groups (e.g., Gram-positive/Gram-negative bacteria, fungi). This method captures functionally relevant shifts that are closely linked to microbial respiration, offering a more direct connection to ecosystem processes such as respiration than DNA-based approaches, which may include relic DNA and inactive community members (Carini et al., 2016). We followed the methodology described by Frostegård et al. (1991), using 5 g of fresh soil per sample. Fatty acid methyl esters were analysed on a gas chromatograph (as described in Cesarz et al., 2023). We used FA 19:0 as an internal standard to quantify bacterial and fungal PLFAs and neutral lipid fatty acids (NLFAs) in ng fatty acid methyl ester (FAME) g⁻¹ soil and to assign them to microbial groups. Bacteria were grouped in Gram-positive bacteria (PLFAs a15:0, i15:0, i16:0, and i17:0), Gram-negative (cy17:0, cy19:0) and widespread bacteria (16:1ω7), while fungi were grouped in arbuscular mycorrhizal fungi (NLFA 16:1ω5), and saprotrophic and ectomycorrhizal fungi (PLFA 18:2ω6,9, Ruess & Chamberlain, 2010). Finally, the fungal-to-bacterial ratio was calculated by dividing the sum of all fungi-specific PLFAs and NLFAs by the sum of all bacteria-specific PLFAs.

Statistical analyses

All data handling and statistical analyses were performed using the R software (version 4.4.2.). R scripts used for this project can be found in Supplementary Material S1-S4. All of the following linear mixed-effect models were tested using the lmer function from the ‘lme4’ package (Bates et al., 2015), and statistical hypotheses (i.e., residuals normality, homoscedasticity) of the following linear models were tested using the model_check function from the ‘performance’ package (Lüdecke et al., 2020).

Land use and climate effects on soil respiration

We used linear mixed models and normal distribution assumptions to test the effects of land use (four levels) and climate (two levels) treatments on soil microbial respiration at 20°C. In addition, the experimental sampling plot nested within the main plot (Schädler et al., 2019) and the respiration measurement time (unfrozen v.s. frozen samples) were set as random factors. Soil microbial respiration was log-transformed to fulfill statistical assumptions. Our experimental data were completely orthogonal and free of missing values. The significance of the explanatory variables was tested using an ANOVA type I. In addition, a post hoc test was performed to test the differences between land-use levels using the glht function from the ‘multcomp’ package (Hothorn et al., 2002).

Land use and climate effects on soil respiration response to heat treatment

Similarly, we used linear mixed models and normal distribution assumptions to test the effects of heat treatment (as a linear temperature variable), land use, climate, and their interactions on soil microbial respiration. The same random terms (sampling plot nested within the main plot and the respiration measurement time) were applied and the soil microbial respiration was log-transformed to fulfill statistical assumptions. The significance of the explanatory variables was tested using an ANOVA type I.

Land use and climate effects on soil microbial biomass and community composition

We used linear mixed models and normal distribution assumptions to test the effects of land use, climate, and their interaction on soil microbial community composition; namely microbial biomass (based on substrate-induced respiration), fungal biomass, bacterial biomass, and fungal-to-bacterial ratio. Fungal biomass, bacterial biomass, and fungal-to-bacterial ratio were log-transformed to fulfill statistical assumptions. The sampling main plot was set as a random factor. The significance of the explanatory variables was tested using an ANOVA type I. In addition, a post hoc test was performed to test the differences between land-use levels using the glht function from the ‘multcomp’ package.